Biodegradation of a Sulfur-Containing Pah, Dibenzothiophene, by a Mixed Bacterial Community

Home , Dibenzothiophene

BIODEGRADATION OF A SULFUR-CONTAINING PAH, DIBENZOTHIOPHENE, BY A MIXED BACTERIAL COMMUNITY

by Ellen M. Cooper Nicholas School of the Environment Duke University

Date:______

Approved:

______Dr. Heather Stapleton, Supervisor

______Dr. Andrew J. Schuler

______Dr. Richard T. Di Giulio

______Dr. Rytas Vilgalys

______Dr. Michael Aitken

Dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in the Nicholas School of the Environment in the Graduate School of Duke University

2009 ABSTRACT BIODEGRADATION OF A SULFUR-CONTAINING PAH, DIBENZOTHIOPHENE, BY A MIXED BACTERIAL COMMUNITY

by Ellen M. Cooper Nicholas School of the Environment Duke University

Date:______

Approved:

______Dr. Heather Stapleton, Supervisor

______Dr. Andrew J. Schuler

______Dr. Richard T. Di Giulio

______Dr. Rytas Vilgalys

______Dr. Michael Aitken

An abstract of a dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in the Nicholas School of the Environment in the Graduate School of Duke University

2009 Copyright by Ellen M. Cooper 2009 Abstract

Dibenzothiophene (DBT) is a constituent of creosote and petroleum waste contamination, it is a model compound for more complex thiophenes, and its degradation by mixed microbial communities has received little attention. The chemical characteristics, environmental fate and ecotoxicology of DBT degradation products are not well understood. This research investigated DBT degradation in an enrichment culture derived from creosote-contaminated estuarian sediment using a suite of assays to monitor bacterial populations, bacterial growth, degradation products, DBT loss, and toxicity. Ultraviolet (UV) irradiation was evaluated as a sequential treatment following biodegradation. Additionally, to advance SYBR-Green qPCR methodology for characterizing mixed microbial communities, an alternative approach for evaluating qPCR data using a sigmoidal model to fit the amplification curve was compared to the conventional approach in artificial mixed communities. The overall objective of this research was to gain a comprehensive understanding of the degradation of a model heterocyclic PAH, DBT, by a mixed microbial community, particularly within the context of remediation goals.

DBT biodegradation was evaluated in laboratory scale cultures with and without pH control. The microbial community was monitored with 10 primer sets using SYBR- Green quantitative polymerase chain reaction (qPCR). Twenty-seven degradation products were identified by gas chromatography and mass spectrometry (GC/MS). The diversity of these products indicated that multiple pathways functioned in the community. DBT degradation appeared inhibited under acidic conditions. Toxicity to bioluminescent bacteria Vibrio fischerimore than doubled in the first few days of degradation, was never reduced below initial levels, and was attributed in part to one or more degradation products. UV treatment following biodegradation was explored using a monochromatic

iv (254 nm) low-pressure UV lamp. While DBT was not extensively photooxidized, several biodegradation products were susceptible to UV treatment. At higher doses, UV treatment following DBT biodegradation exacerbated cardiac defects in Fundulus heteroclitus embryos, but slightly reduced toxicity to V. fischeri.

This research provides a uniquely comprehensive view of the DBT degradation process, identifying bacterial populations previously unassociated with PAH biodegradation, as well as potentially hazardous products that may form during biodegradation. Additionally, this research contributes to development of unconventional remediation strategies combining microbial degradation with subsequent UV treatment.

v Table of Contents

Abstract...... iv

List of Tables...... x

List of Figures...... xiii

Acknowledgements...... xxi

Chapter 1. .Introduction...... 1

1.1. Research premise...... 1

1.2. Background ...... 3 1.2.1. PAH contamination and environmental behavior...... 3 1.2.2. Bioremediation of PAHs...... 6 1.2.3. Degradation pathways and products...... 8 1.2.4. Monitoring bacterial populations by qPCR...... 13 1.2.5. Photooxidation in contaminant reduction...... 18 1.3. Research Plan...... 22 1.3.1. Hypotheses ...... 22 1.3.2. Research Objectives...... 23 1.4. Scientific significance...... 25

Chapter 2.. Microbial population dynamics during DBT degradation...... 27

2.1. Introduction...... 27

2.2. Methods...... 30 2.2.1. Culture establishment, 16S rRNA gene clone library construction, isolation of pure cultures, and phylogenetic analysis ...... 30 2.2.2. qPCR primer design and assay ...... 31 2.2.3. Degradation study ...... 34 2.2.4. Toxicity assay with bioluminescent bacteria...... 36 2.2.5. Statistical analyses...... 37 2.3. Results...... 37

vi 2.3.1. Phylogenetic analysis ...... 37 2.3.2. DBT degradation, pH and microbial growth ...... 41 2.3.3. Population dynamics...... 46 2.4. Discussion...... 50

2.5. Conclusion...... 55

Chapter 3.. Products of DBT degradation by a mixed microbial community...... 56

3.1. Introduction...... 56

3.2. Materials and methods ...... 62 3.2.1. Source of enrichment culture ...... 62 3.2.2. DBT degradation studies...... 62 3.2.3. Sample preparation and analysis by GC/MS...... 63 3.2.4. Toxicity assay and dose-response experiments...... 69 3.2.5. Statistical Analyses...... 70 3.3. Results...... 71 3.3.1. Identification of DBT degradation products...... 71 3.3.2. Toxicity of DBT and selected degradation products to V. fischeri...... 89 3.3.3. Trends in toxicity during DBT degradation...... 91 3.3.4. Trends in DBT and degradation products...... 92 3.4. Discussion...... 97

3.5. Conclusion...... 104

Chapter 4.. Conventional and alternative approaches in the analysis bacterial populations by SYBR-Green qPCR...... 105

4.1. Introduction...... 105

4.2. Materials and methods...... 110 4.2.1. Bacterial cell culture and genomic DNA stock preparation...... 110 4.2.2. Cloning, PCR and Sequencing...... 111 4.2.3. Preparation of DNA mixes, clone single isolate DNA, and genomic single isolate samples...... 112 4.2.4. Primer design and qPCR assays...... 113 4.2.5. Modeling and data analysis ...... 115

vii 4.2.6. Calculation of 16S rRNA gene cell copy number...... 120 4.3. Results...... 120 4.3.1. Calculated efficiencies...... 121 4.3.2. Cell copy numbers of 16S rRNA gene...... 125 4.3.3. Quantitation with isolate-specific primers...... 126 4.3.4. Quantitation with universal primer...... 128 4.3.5. Asymmetry parameter f ...... 132 4.4. Discussion...... 135

4.5. Conclusion...... 138

Chapter 5.. UV treatment of DBT and its biodegradation products...... 139

5.1. Introduction...... 139

5.2. Materials and methods...... 142 5.2.1. Preparation of test solutions...... 142 5.2.2. UV exposures ...... 142 5.2.3. Toxicity to Fundulus heteroclitus embryos and Vibrio fischeri ...... 145 5.3. Results...... 146 5.3.1. Photolysis of DBT ...... 146 5.3.2. Photolysis of degradation products in Post-biodegradation solution ..... 152 5.3.2.1. Overview monitored products...... 152 5.3.2.2. UV effects on DBT degradation products in Post-biodegradation solution...... 155 5.3.3. Toxicity to Vibrio fischeri and Fundulus embryos...... 157 5.4. Discussion...... 159

5.5. Conclusion...... 165

Chapter 6.. Conclusions...... 167

Appendices...... 172

Appendix A: Chapter 2 Data...... 172

Appendix B: Chapter 3 Data...... 182

viii Appendix C: Chapter 4 Data...... 199

Appendix D: Chapter 5 Data...... 212

References...... 222

Biography...... 239

ix List of tables

Table 1.1. Physical and chemical properties of DBT and selected PAHs...... 5

Table 2.1. Characteristics of qPCR primers used to analyze population dynamics during DBT degradation...... 32

Table 3.1. Structures and GC/MS identification parameters of compounds identified extracts of the media of a microbial enrichment culture degrading DBT. Asterisks (*) indicate the five most abundant degradation products based on relative responses of quantifying ions to that of the internal standard, 2-naphthol...... 65

Table 4.1. Composition of DNA mixtures analyzed by qPCR...... 113

Table 4.2. Primers used in qPCR. All primers were developed as part of this study except as noted...... 114

Table 4.3. Summary of data analysis approaches...... 116

Table 4.4. Cell copy numbers of 16S rRNA genes based on amplification of isolate genomic DNA with isolate-specific primers, estimated by the Ct approach or sigmoidal fitting with second derivative maxima as a diagnostic point...... 126

Table 5.1. Summary of kinetic fits for DBT and selected degradation products in DBT media and Culture media...... 150

Table A.1. Typical composition of Instant OceanTM artificial seawater (22.2 g-1 L )...... 172

Table A.2. Rarefaction data for the DBT-degrading mixed microbial community presented in Figure 2.2...... 173

Table A.3. Selected data for DBT degradation experiment without pH control (Fig- ures 2.3 and 2.4)...... 174

Table A.4. Selected data for DBT degradation experiment with pH control (Fig- ures 2.3 and 2.4)...... 175

Table A.5. 16S rRNA gene copies of taxonomic groups monitored by qPCR during DBT degradation without pH control (Figure 2.5)...... 176

x Table A.6. 16S rRNA gene copies of taxonomic groups monitored by qPCR during DBT degradation with pH control (Figure 2.5)...... 177

Table A.7. Relative 16S rRNA gene copy numbers of taxonomic groups monitored during DBT degradation without pH control (Figure 2.6)...... 179

Table A.8. Relative 16S rRNA gene copy numbers of taxonomic groups monitored during DBT degradation with pH control (Figure 2.6)...... 180

Table B.1. Inhibition of luminescence in Vibrio fischeri exposed to DBT and selected DBT degradation products (Figure 3.19)...... 182

Table B.2. Concentrations of DBT and other compounds analyzed by GC/MS in extracts from culture media during DBT degradation without pH control (Figures 3.20 and 3.21)...... 185

Table B.3. Concentrations of DBT and other compounds analyzed by GC/MS in extracts from culture media during DBT degradation with pH control (Figures 3.20 and 3.21)...... 190

Table B.4. Inhibition of luminescence in Vibrio fischeri exposed to culture media collected during DBT degradation without pH control (Figure 3.20a)...... 197

Table B.5. Inhibition of luminescence in Vibrio fischeri exposed to culture media collected during DBT degradation with pH control (Figure 3.20a)...... 198

Table C.1. qPCR amplification data forPseudomonas assays included in Figure 4.1...... 199

Table C.2. Amplification efficiencies calculated by conventional and alternative approaches for qPCR analyses of artificial mixed communities using group-specific primers (Figure 4.3)...... 204

Table C.3. Amplification efficiencies calculated by conventional and alternative approaches for qPCR analyses of artificial mixed communities using the universal primer (Figure 4.3)...... 205

Table C.4. Log copy number errors calculated by conventional and alternative approaches for qPCR analyses of artificial mixed communities using group-specific primers (Figure 4.4)...... 206

xi Table C.5. Log copy number errors calculated by conventional and alternative approaches for qPCR analyses of artificial mixed communities using the universal primer (Figure 4.5)...... 207

Table C.6. Fits and first and second derivatives of fits with actual and hypothetical f parameters for qPCR reaction fluorescence from genomic isolate DNA from 106 Pseudomonas cells amplified with PSU primer (Figure 4.6)..209

Table C.7. f parameters calculated by sigmoidal fitting approaches for qPCR analyses of artificial mixed communities using group-specific and universal primers (Figure 4.7)...... 211

Table D.1. Results from GC/MS analyses of DBT and other compounds in DBT and Post-biodegradation test solutions exposed to UV light. (Figures 5.2, 5.3, 5.4, and 5.5)...... 212

Table D.2. Cardiac deformity scores for Fundulus embryos exposed to Control, DBT and Post-biodegradation solutions treated with UV light (Figure 5.6)..220

Table D.3. Inhibition of luminescence in Vibrio fischeri exposed to Control, DBT and Post-biodegradation solutions treated with UV light (Figure 5.6)...... 221

xii List of Figures

Figure 1.1. Bacterial pathways of DBT degradation. Enzymes are indicated in italics. Genes and/or proteins of enzymes in blue type have been isolated and characterized in select isolates...... 9

Figure 1.2. Stages of an ideal qPCR reaction: 1-exponential stage; 2-linear stage; -3-plateau stage...... 15

Figure 2.1. Unrooted maximum parsimony phylogenetic tree based on an 1040 base pair alignment of 16SS rRNA gene sequences of isolates and clones from DBT-degrading enrichment culture with reference sequences indicated by GenBank accession numbers. Branch values are bootstrap values from 500 iterations. The scale bar represents a 10% difference in nucleotide sequence. Numbers of clones () and isolates () obtained are given in parentheses adjacent to symbol. Letters represent group-specific primer sets: (a) Firmicutes, (b) Flavobacteriaceae, (c) Planctomycetaceae, (d) Rhizobiales-like bactera, (e) Rhodospirillaceae-like bacteria, (f) Other Alphaproteobacteria, (g) Azospirillum-like bacteria, (h) Kor- diimonas, (i) Chromatiales and (j) Pseudomonas...... 39

Figure 2.2. Rarefaction curve constructed from the 16S rRNA gene sequences of clones and isolates from the DBT-degrading mixed microbial culture. Solid line represents number of different operational taxonomic units (OTUs) observed per number of sequences sampled. Dashed lines represent 95% upper and lower confidence bounds...... 40

Figure 2.3. Total DBT (a), final pH (b ), and aqueous DBT (c) in inoculated and uninoculated (control) flasks during DBT degradation with and without pH control...... 43

Figure 2.4. Total protein (a) and total 16S rRNA gene copies (b) in inoculated and control (non-inoculated) flasks during DBT degradation with and without pH control. Total 16S rRNA gene copies are averages of values calculated from 10 standard curves used in qPCR. Each standard curve included a template from one of the 10 taxonomic groups studied...... 45

Figure 2.5. Absolute abundance of group-specific 16S rRNA gene copies determined by qPCR during DBT degradation with and without pH control. Firmicutes was below qPCR detection regardless of pH

xiii control, while Azospirillum-like and Planctomycetaceae were below detection only in the experiment with pH control...... 47

Figure 2.6. Group-specific 16S rRNA gene copies determined by qPCR during DBT degradation (a) without pH control and (b) with pH control, expressed as a percent of total 16S rRNA gene copies quatnified using universal primers given in Table 2.1. Total 16S rRNA gene copies are presented as averages of values calculated from standard curves for each group-specific template...... 48

Figure 3.1. Figure 3.1. Known pathways of bacterial aerobic degradation of DBT. Red products were observed in this research. Starred (*) were detected as methyl esters after derivatization with diazomethane. Functional groups likely deprotonated at culture pH indicated with hydrogens in parentheses (“(H)”). Pathways are based on Bressler and Fedorak, 2001a,b; Gray et al., 1996; Kodama et al., 1973; Seo et al., 2006; and van Afferden et al., 1993. Numbers in bold italics refer to entries in Table 3.1...... 58

Figure 3.2. Reactions forming dimers from bacterial DBT aerobic degradation products. Red products were observed in this research. Starred (*) were detected as methyl esters after derivatization with diazomethane. Functional groups likely deprotonated at culture pH indicated with hydrogens in parentheses (“(H)”). Reactions are adapted from Bressler and Fedorak, 2001b, and Baker et al., 1952. Note: presence of 2-mercaptophenylglyoxylate is indicated by detection of benzothiophene-2,3-dione (9), which forms upon acidification. Numbers in bold italics refer to entries in Table 3.1...... 60

Figure 3.3. GC/MS total ion chromatograms of DCM extract, (a) without derivatization, and (b) with derivatization with diazomethane, of media from a DBT-degrading microbial enrichment culture four days after inoculation and maintained at pH 7.5. Separations were achieved using a DB-XLB column (30 m, 250 µm nominal diameter, 0.25 µm film thickness; J&W Scientific). Numbers in bold italics refer to entries in Table 3.1...... 72

Figure 3.4. Structures and electron impact mass spectra of (a) benzoic acid (1), as its methyl ester after derivatization with diazomethane, and (b) benzothiophene (2) detected in media of a microbial enrichment culture degrading DBT. Numbers in bold italics refer to entries in Table 3.1...... 73

xiv Figure 3.5. Structures and electron impact mass spectra of (a) benzisothiazole (3) and (b) 2-methylsulfinyl phenol (4) detected in media of a microbial enrichment culture degrading DBT. Numbers in bold italics refer to entries in Table 3.1...... 74

Figure 3.6. Structures and electron impact mass spectra of (a) 2-hydroxybenzothiophene (5) and (b) 3-hydroxybenzothiophene (6) detected in media of a microbial enrichment culture degrading DBT. Numbers in bold italics refer to entries in Table 3.1...... 75

Figure 3.7. Structures and electron impact mass spectra of (a) thiosalicylic acid (7), as its methyl ester after derivatization with diazomethane, detected in media of a microbial enrichment culture degrading DBT, and (b) 2-naphtholol (8), used as an internal standard in GC/ MS analyses. Numbers in bold italics refer to entries in Table 3.1...... 76

Figure 3.8. Structures and electron impact mass spectra of (a) benzothiophene- 2,3-dione (9) and (b) 1,2-benzodithiol-3-one (10) detected in media of a microbial enrichment culture degrading DBT. Numbers in bold italics refer to entries in Table 3.1...... 77

Figure 3.9. Structures and electron impact mass spectra of (a) benzothiophene- 2,3-diol (11) and (b) 3-hydroxy-1-benzothiophene-2-carbaldehyde (12) detected in media of a microbial enrichment culture degrading DBT. Numbers in bold italics refer to entries in Table 3.1...... 78

Figure 3.10. Structures and electron impact mass spectra of (a) benzothiophene-3-carboxylic acid (13) and (b) 3-hydroxybenzothiophe-2 -one (14) detected in media of a microbial enrichment culture degrading DBT. Numbers in bold italics refer to entries in Table 3.1...... 79

Figure 3.11. Structures and electron impact mass spectra of (a) DBT (15) and (b) benzothiophene-2,3-dicarbaldehyde (16) detected in media of a microbial enrichment culture degrading DBT. Numbers in bold italics refer to entries in Table 3.1...... 80

Figure 3.12. Structures and electron impact mass spectra of (a) benzothiophene-2,3-dicarboxylic acid, detected as its dimethyl ester after derivatization with diazomethane17 ( ) and (b) benzothieno[2,3-c] furan-1,3-dione (18) detected in media of a microbial enrichment culture degrading DBT. Numbers in bold italics refer to entries in Table 3.1...... 81

xv Figure 3.13. Structures and electron impact mass spectra of benzothienopyranones (19, 20) detected at (a) 21.78 min and (b) 22.12 min by GC/ MS in media of a microbial enrichment culture degrading DBT. Specific structure assignments for spectra cannot be determined. Numbers in bold italics refer to entries in Table 3.1...... 82

Figure 3.14. Structures and electron impact mass spectra of (a) DBT sulfone (21) and (b) dibenzothiophene sulfoxide (22) detected in media of a microbial enrichment culture degrading DBT. Numbers in bold italics refer to entries in Table 3.1...... 83

Figure 3.15. Structures and electron impact mass spectra of dithiosalicylides (23, 24) detected at (a) 24.10 min and (b) 25.06 min in media of a microbial enrichment culture degrading DBT. Specific structure assignments cannot be determined for these spectra. Numbers in bold italics refer to entries in Table 3.1...... 84

Figure 3.16. Structures and electron impact mass spectra of (a) thioindigo (25) and (b) dithiosalicylic acid (26), as its dimethyl ester after derivatization with diazomethane, detected in media of a microbial enrichment culture degrading DBT. Numbers in bold italics refer to entries in Table 3.1...... 85

Figure 3.17. Structures and electron impact mass spectra of (a) 2-{[2- (carboxycarbonyl)phenyl]disulfanyl}benzoic acid dimethyl ester (28) and (b) 2-{[2-2,2’-(disulfanediyldibenzene-2,1-diyl) bis(oxoacetic acid) dimethyl ester 29( ) detected after derivatization with diazomethane in media of a microbial enrichment culture degrading DBT. Numbers in bold italics refer to entries in Table 3.1...... 86

Figure 3.18. Structure and electron impact mass spectra of an unknown compound (27) with a molecular ion at 284 m/z detected in media of a microbial enrichment culture degrading DBT. A possible molecular formula and structure are postulated from the spectrum. Num- bers in bold italics refer to entries in Table 3.1...... 87

Figure 3.19. Dose-response effect of DBT 15( ) and selected DBT degradation products in artificial seawater media on toxicity measured as inhibition of luminescence in Vibrio fischeri. Error bars are standard deviations of three replicates. Numbers in bold italics in parentheses refer to compound structures in Table 3.1. Concentration ranges in parentheses are the ranges observed in the degradation

xvi studies. Note that percent inhibition of luminescence from exposure to DBT sulfone (21) was at or near zero at all concentrations tested...... 91

Figure 3.20. Trends by day after inoculation in (a) toxicity, (b) aqueous DBT (15), (c) DBT sulfone (21), (d) 2-hydroxybenzothiophene (5), (e) 3-hydroxybenzothiophene (6), (f) benzothiophene-2,3-dione (9) and (g) 2,3-dihydroxybenzothiophene (11) in media of a DBT-degrading culture under conditions with and without pH control. Toxicity is measured as inhibition of luminescence in Vibrio fischeri. Relative responses were determined using 2-naphthol (8) as an internal standard. Numbers in bold italics refer to entries in Table 3.1...... 93

Figure 3.21. Trends by day after inoculation in (a) DBT sulfoxide (22), (b) 3-hydroxy-1-benzothiophene-2-carbaldehyde (12), (c) 3-hydroxybenzothiophen-2-one (14), (d) benzothiophene-3-carboxylic acid (13), (e) thiosalicylic acid (7), (f) dithiosalicylic acid (26) and (g) thioindigo (25) in media of a DBT-degrading culture under conditions with and without pH control. Relative responses were determined using 2-naphthol (8) as an internal standard. Numbers in bold italics refer to entries in Table 3.1...... 94

Figure 4.1. Representative qPCR amplification curve indicating threshold fluorescence used to determine cycle threshold (Ct) in conventional data analysis, diagnostic points (Ct and second derivative maximum) used for gene copy number quantification, first derivative maximum predicted by five-parameter sigmoidal fitting, and the ranges of cycles included in Full, Swin and Fwin sigmoidal fits. The range of cycles included in Swin is variable and determined by statistical criteria (see Methods for details)...... 118

Figure 4.2. Example QPCR amplification curves for clone and genomic Pseudomonas (single isolate) and mixed DNA amplified with isolate-specific primer PSU. For the Pseudomonas clone DNA curves, which served as standards, numbers associated with curves indicate copy number per qPCR reaction. Mixed DNA in this example contained 105, 107 and 107 16S rRNA gene copies/ reaction (clone DNA) or DNA from 105, 107 and 107 cells/reaction (genomic DNA) from Pseudomonas, Martelella, and Vitellibacter isolates, respectively. Genomic Pseudomonas DNA contained DNA from 105 Pseudomonas cells/reaction. Relative fluorescence is the background-corrected SYBR-Green fluorescence normalized to the passive dye ROX...... 121

xvii Figure 4.3. Average calculated qPCR efficiencies compared across approach (Ct, Full, Swin and Fwin) and DNA source for isolate-specific primers (a: PSU, b: RZB, c: VIT) and the universal primer (d) applied to each of these bacterial groups. For the Ct approach, one efficiency was calculated from each isolate’s set of standards (clone isolate DNA), resulting in three standard-dependent efficiencies for each DNA source. Sets of standards were included with qPCR assays for clone mixed DNA, genomic isolate DNA, and genomic mixed DNA. Each bar represents results from all samples of a given DNA source averaged together...... 123

Figure 4.4. Log copy number error for clone (a) and genomic (b and c) DNA sources amplified with isolate-specific primers and analyzed with Ct, Full, Swin and Fwin using diagonistic points (cycle threshold for Ct, second derivative maxima for all others) or initial fluorescence (Full, Swin and Fwin only). Log copy number error was calculated by Equation 4.6...... 127

Figure 4.5. Log copy number error for clone (a) and genomic (b) mixed DNA amplified with universal primer and analyzed with the Ct, Full, Swin and Fwin approaches. Total gene copies are calculated as the sum of gene copies of isolates in the mixture determined with isolate-specific primers (Sum of isolates), based on Pseudomo- nas, Martelella or Vitellibacter standard curves, as an average of values obtained by the standard curves, and by initial fluorescence (Full, Swin and Fwin fits only). Log copy number error was calculated by Equation 4.7...... 131

Figure 4.6. Effect of the sigmoidal model asymmetry parameterf on curve shapes of the fit (solid lines), first derivatives (dashed lines) and second derivatives (dashed-dotted lines) of qPCR reaction fluorescence from genomic isolate DNA from 106 Pseudomonas cells amplified with PSU primer. Curves for experimental data ( ) and actual fit (f=2.0) are shown in black...... 133

Figure 4.7. f parameters from Full, Swin and Fwin log-logistic five-parameter sigmoidal fits for (a) clone isolate DNA (standards), (b) clone mixed DNA, (c) genomic isolate DNA and (d) genomic mixed DNA amplified with isolate-specific (PSU, RZB, VIT) and universal (UNI) primers. Symbols above bars indicate that f is significantly greater (*) or less () than 1 (p<0.05). When f=1, the qPCR amplification curve is symmetrical and the fit is equivalent to a four-parameter sigmoidal model...... 134

xviii Figure 5.1. UV spectra of molar absorption of dibenzothiophene (1.5 μM) in artificial seawater medium (DBT solution) and the low-pressure mercury vapor UV lamp used for treating test solutions...... 143

Figure 5.2. Effect of UV fluence on (a) DBT (15), DBT sulfone (21), (c) DBT sulfoxide (22), (d) benzothiophene-2,3-dione (9), (e) 2-hydroxybenzothiophene (5), (f) 3-hydroxybenzothiophene (6), (g) 2,3-dihydroxybenzothiophene (11) and (h) 3-hydroxy-1-benzothiophen-2-one (14) in DBT solution and Post-biodegradation solution. Relative responses were determined using 2-naphthol (8) as an internal standard. Starred (*) products were only observed in the Post-biodegradation solution. Arrows point to y-axis associated with the data series. Numbers in bold italics refer to entries in Table 3.1...... 147

Figure 5.3. Effect of UV fluence on (a) benzothiophene carboxylic acid (13), (b) benzothiophene-2,3-dicarboxylic acid (17), (c) benzoic acid (1), (d) thiosalicylic acid (7), (e) 3-hydroxy-1-benzothiophene-2- carbaldehyde (12), (f) dithiosalicylic acid (26), (g) thioindigo (25) and (h) an unknown with M+ 284 m/z (27) in Post-biodegradation solution. Relative responses were determined using 2-naphthol (8) as an internal standard. None of these products were observed in artificial seawater containing DBT only (DBT solution). Numbers in bold italics refer to entries in Table 3.1...... 148

Figure 5.4. Apparent first-order kinetic fits of DBT loss in DBT solution and Post- biodegradation solution, and losses of benzothiophene-2,3-dicarboxylic acid (17) and an unknown DBT degradation product (27) in Post-biodegradation solution. Relative response is based on the response of the quantitative ion to that of 2-naphthol (8) used as an internal standard in GC/MS analyses. Numbers in bold italics refer to entries in Table 3.1...... 151

Figure 5.5. Apparent phototransformation rates of selected degradation products formed in DBT solution and Post-biodegradation solution formed during exposure to 0, 500, 1250 and 2000 mJ cm-2 UV at 254 nm. Panel a: zero-order kinetic fits of DBT sulfoxide (22) in DBT solution, and beonzoic acid (1) and 3-hydroxybenzothiophene (6) in Post-biodegradation solution. Panel b: first-order kinetic fits of benzothiophene carboxylic acid (13) and thioindigo (25) in Post-biodegradation solution. Relative responses are based on 2-napthol (8) used as an internal standard. Numbers in bold italics refer to entries in Table 3.1...... 154

xix Figure 5.6. Toxicity assessed as (a) average cardiac deformity score in Fundulus embryos and (b) inhibition of luminescence in V. fischeri for Con- trol solution, DBT (1.5 µM) solution and Post-biodegradation solution following treatment of the test solutions with LP UV (254 nm) at fluences of 0, 500, 1250 and 2000 mJ cm-2. Fundulus embryos were dosed with test solutions 24 h post-fertilization and scored 6 d after dosing. Scoring scale: 0 = normal; 1 = mild deformities; 2 = severe deformities. Error bars are standard deviations. Within a given panel for a given test solution, bars labeled with the same letter are not significantly different pat <0.05 in ANOVA comparisons... 158

xx Acknowledgements

This work could not have been completed without the support of numerous peo- ple, as well as Duke University’s Superfund Basic Research Program, which sponsored my graduate study. For their unselfish and much-appreciated aid in my analytical and technical endeavors, I thank Dr. Zuzana Bohrerova, Lisa Bukovnik, Dr. Larry Claxton, Dr. George Dubay, Dr. Claudia Gunsch, Jason Jackson, Dr. Tim James, Shannon Kelly, Dr. Song Qian, Dr. Hilla Shemer, Dr. Andrej-Nikolai Spiess and Wes Willis. Special thanks to Dwina Martin, whose friendship and technical expertise were invaluable, and to my husband Peter Harrell, who supported my efforts with patience and a sense of humor. Much thanks also go to Dr. Cole Matson for conducting the Fundulus embryo toxicity assays. I am grateful to Drs. Rich Di Giulio, Rytas Vilgalys and Mike Aitken, who formed a uniquely talented, balanced and supportive committee, and whom I respect tremendously. I -ex tend deepest gratitude to my advisors Drs. Andrew Schuler and Heather Stapleton, who helped shape and focus this research, and graciously gave me the freedom and indepen- dence to pursue my ideas, even the ones that didn’t work. Finally, thanks to my parents for their constant love and support through all stages of my life.

xxi Chapter 1. Introduction

1.1. Re s e a r c h p r e m i s e

Remediation of polycyclic aromatic hydrocarbon (PAH) contamination is a necessary task for reducing hazards at many sites worldwide, a significant portion of which are located near populated areas. In the United States, the Environmental Protection Agen- cy’s (EPA) National Priority List recognized, as of January 2008, 555 sites where sediment (161 sites), soil (433 sites), groundwater (378 sites) and/or surface waters (57 sites) are contaminated through human activity with a spectrum of PAHs derived primarily from petroleum sources (USEPA, 2008). At many sites, PAHs occur as incompletely defined complex mixtures, sometimes with other classes of contaminants such as heavy metals, complicating the selection of a successful remediation strategy as well as the development of new techniques. PAHs are persistent in the environment due to their inherently low solubility, strong association with organic matter, and resistance to biotic and abiotic degradation (ATSDR, 1995; Aitken and Long, 2004).

PAH contamination presents a hazard for human health and ecological welfare because these compounds may elicit a variety of toxic effects (ATSDR, 1995; Penning et al., 1999), among which carcinogenicity is often of primary concern driving remediation efforts. Of known PAHs, 16 are considered priority pollutants by the EPA (Keith and Telliard, 1979), and 7 of these are classified as carcinogens (USEPA, 1993). Reduction of the levels of, and/or exposure to, these PAHs, particularly the 7 carcinogens, is a primary goal dictating remediation efforts.

A common remediation strategy for PAH contaminated sediments and soils is the excavation, incineration and off-site disposal of the contaminated media, followed

1 by site restoration. This approach is expensive (e.g., $250-2000 -3m ; Mulligan, 2002) and highly disruptive to the site, but it guarantees hazard reduction. Bioremediation, an umbrella term encompassing techniques such as bioaugmentation, biostimulation and natural attenuation, is often considered as a lower-cost (e.g., $30-300-3 m ; Mulligan, 2002) and less invasive alternative. Not uncommonly, however, bioremediation of PAH is unsuccessful in reaching remediation goals, particularly when site contaminants include larger PAHs (e.g., benzo[a]pyrene) and/or metals, as is the case at many creosote-contaminated sites. Unsuccessful bioremediation may leave not only the original contaminants in place but also introduce a suite of unknown degradation products that may contaminants themselves, possibly augmenting the original site hazard (e.g., White and Claxton, 2004).

My broad objective for this research was to investigate how a mixed microbial culture degrades the sulfur-containing model PAH dibenzothiophene (DBT) in order to understand what factors may enhance or inhibit contaminant degradation, or introduce new potential hazards, in natural or engineered systems. Because biodegradation in natural and engineered systems often involves a mixed microbial community (Bouchez et al., 1995; Trzesicka-Mlynarz and Ward, 1995), a key part of this research involved understanding how the microbial community changes during degradation. The recent development of molecular biological techniques such as quantitative polymerase chain reaction (qPCR) offers the possibility to monitor distinct taxa in a quantitative manner previously difficult to achieve. So far, however, this technique has only been applied to study biodegradation in a few studies (e.g., Singleton et al., 2006; Singleton et al., 2007). The current research used qPCR to follow bacterial populations of a mixed community during the degradation of DBT. Because qPCR has not been widely used for this application, questions remain regarding how best to process qPCR data. Some of these ques-

2 tions were addressed in the current research by comparing the most commonly used data processing approach to a recently developed alternative approach.

Another key was understanding what products were formed during DBT biodegradation by the mixed culture, and how those products may have contributed to the overall hazard present. In this research, gas chromatography with mass spectrometry (GC/MS) was used to identify and monitor products during DBT biodegradation, and trends of degradation products were compared to trends in toxicity assayed using the bioluminescent bacteria Vibrio fischeri.

Exploring means to overcome obstacles of incomplete mineralization and unexpected problems related to degradation products is yet another key, which relates directly to the development of new bioremediation strategies. One promising yet largely unexplored strategy is the use of photolysis in conjunction with bioremediation. This research evaluated the use of UV after biodegradation to reduce remaining degradation products and ameliorate residual toxicity, which was evaluated with two toxicity assays, one using bioluminescent V. fischeri and the other using Fundulus heteroclitus (killifish) embryos.

1.2. Ba c k g r o u n d

1.2.1. PAH contamination and environmental behavior

PAHs are compounds consisting of two or more fused aromatic rings that may include heteroatoms oxygen, nitrogen and sulfur. Although these compounds are formed in small quantities naturally through combustion of organic materials, PAHs found at high levels are usually derived from petroleum sources and are introduced

3 into the environment through human activities including spills, improper disposal, and combustion (Edwards, 1983; Wilson and Jones, 1993) PAHs are typified by low aqueous solubility (typical range:2.2 x 103 to 242 µM ), high octanol-water coefficients (typical log

-8 Kow range: 3.4-6.8) and low vapor pressures (typical range: 1.2 x 10 to 10.4 Pa) (Mackay, 1992; ATSDR, 1995). These characteristics are demonstrated by DBT and selected PAHs in Table 1.1.

n - c o 8 4 8 7 ti 8 7 8 3 a --- 2 2 p 3 2

r m / / / / m i

o x s 9 5 8 9 a 5 6 6 3 b ----n a 2 2 2 3 m

UV ) C ) ° C b - 5 ° 2 5 --- ( 2 9 re r

2 a 2 0 u ( 1 . P

0 p o 0 1 . 7 0 1 0 0 ---- V a 0

6 pre ss 0 . 0 0 . 0 . a w o 3 3 9 5 1949 3 1 9 5

K . . . .

3 6 3 4 er, l og n . a - Wer

1 y ; 5 . 0 M -- 4 1 1 0 . . µ PAHs 7 0 7 1 . 2 --- 2002 0 lubilit

o l ., S a

. - t - e

-1 t l 7 3 2 6

h 1 3 2 2 o selected ez . . . . g 8 4 4 6 m

2 5 8 6 i gu lecular lecular 1 2 1 1 o Wei --g 1998.

, odr M et al., 1997 other l . R y

; a t k e

and d

2000 g T

Mac

B d l ., a n

Maa D t

de of o

; a L

S ; 1999 , n 2001

Structure Structure e l ., o et al., 1990; a l s i r a

properties a t C e

d e Valer t

n a

ba n emical a e S 0 3

8 h 7 1995; - ; - - ss - , 5 0 c 2 a 3 g 6 L 2 3 7 -

- - - ; 2 1 0 6 1953

CA S 3 9 e r 5 8 Kolli

and t ., 1

l a a

w t

e e

s ical re 2002; n y n

u e e a Physical and chemical properties of DBT and selected PAHs. and selected of DBT properties and chemical Physical p n h

al., e p

n l m Ph r e i o e y i n et g d

p e h l t ] i e e ei re a a o 1.1. L n R [ u h z

oun d t e s o n p r h m z m e o p n b u a i ro e l Fro Mea F Table N Co m B D F b a c Table 1.1. Table

5 Additionally, PAHs have a strong affinity to sorb to soils and sediments particularly when organic matter content is high, and many, particularly the larger PAHs, are resistant to biological and abiotic breakdown (ATSDR, 1995). Half-lives for PAHs in soils and sediments vary considerably depending on molecular size and site conditions, ranging from a few days up to or exceeding 5000 d (ATSDR, 1995; Oleszczuk and Baran, 2003). Persistence of PAHs, the result of compound properties, site conditions and microbial activity, is generally more pronounced with increasing number of rings (Wilson and Jones, 1993; Wilcke, 2000). The characteristics of PAHs largely dictate their environmental fate: they tend to concentrate in solid environmental media and persist near the origin of contamination with limited potential of migrating off-site through the vapor phase or with leachate and groundwater.

From the perspective of remediation, the primary human health risk associated with PAHs is carcinogenicity. Although DBT itself is not carcinogenic, it and other PAHs may elicit other toxic effects. Some research indicates various PAHs may elicit repro- ductive, developmental, hematopoietic (i.e., related to production of blood cells), and immunological effects (ATSDR, 1995; Penning et al., 1999) For example, Incardona et al. (2004) observed cardiac defects along with altered morphology during development of zebrafish (Danio rerio) embryos exposed to DBT. Additionally, at the subcellular level, DBT has been shown to interfere with mitochondrial electron transport chains (HSDB, 2006).

1.2.2. Bioremediation of PAHs

A variety of remediation approaches exist for PAH-contaminated systems, including in-situ treatments such as natural attenuation, biostimulation, bioaugmentation, bio-

6 filters and physical entombment, and ex-situ treatments such as biopiling, slurry-phase bioreactors, incineration and off-site disposal (USEPA, 2001; Mulligan, 2002). Strategies involving excavation and off-site disposal, while common, result in undesirably heavy site impact. Biologically-based strategies are often preferred because of their low cost relative to intensively engineered techniques (Mulligan, 2002), and because they often can be implemented with little negative site impact reducing post-cleanup site restoration. Where feasible, bioremediation for PAHs under aerobic conditions is often favored because aerobic degradation is typically more rapid and complete than anaerobic degradation (Bauer and Capone, 1985; Genthner et al., 1997). A variety of PAH-degrading microbes from diverse environments have been discovered (e.g., references within Cerniglia, 1993; Samanta et al., 2002; Aitken and Long, 2004), and considerable research has explored the degradation potential of isolated strains. Despite the demonstration of isolated strains to degrade single PAHs or simple mixtures, considerable evidence indicates that degradation of PAHs in contaminated systems may be more successful when a mixed community is involved (Wilson and Jones, 1993; Samanta et al., 2002; Aitken and Long, 2004). In natural systems or unremediated contaminated sites, PAH degradation by a community of microbes is most likely the case. Often, little is known about the taxa of many mixed cultures involved in degradation and even less is known about how the structure of the microbial community changes during degradation.

Despite its inherent challenges, bioremediation has been successfully applied in some contaminated sites. For example, indigenous degraders in a bioslurry reactor removed 93.4% of total PAHs from a creosote-contaminated soil over 12 weeks (Lewis, 1993). Many bioremediation attempts, however, are unsuccessful, i.e., they don’t completely remove contaminants in a timely manner while also reducing the toxicity associated with the contamination, or they impart additional negative impact to the site or surrounding area. Factors limiting bioremediation are diverse including low contaminant

7 bioavailability, toxicity of the PAHs, other site contaminants (e.g. heavy metals) or toxicity of degradation products to microbial degraders or unfavorable site conditions such as poor nutrient availability, insufficient oxygen, unsuitable pH or temperature (Wilson and Jones, 1993; Aitken and Long, 2004). In some cases, these factors, particularly those that may be categorized under site conditions, can be mitigated to enhance bioremediation. For example, surfactants may augment bioavailability, fertilizer application may improve nutrient status, aeration or H2O2 can be used to enhance oxygen levels in anoxic zones, or pH can be raised through liming or lowered by amendment with sulfur or sul- fates (e.g., ammonium sulfate; Wilson and Jones, 1993, and references therein). These ameliorations, however, do not guarantee successful bioremediation at all sites.

The degrading abilities of the microbes themselves may have considerable limitations. Low molecular weight PAHs (e.g., 2-3 rings) are more readily degraded by a wider variety of organisms than are larger PAHs (see review by Doyle et al., 2008). Consequen- tially, microbes may effectively reduce concentrations of the low molecular weight PAHs but are unable to achieve the desired levels for the larger PAHs, such as benzo[a]pyrene, that often are of greater concern. In some cases, microbes degrade PAHs into metabolites that may transiently or permanently increase toxicity (Belkin et al., 1994; Phillips et al., 2000; Ahtiainen et al., 2002; White and Claxton, 2004; Donnelly et al., 2005), which counteracts the goals of remediation. Often, the potentially toxic metabolites are unidentified compounds about which little is known.

1.2.3. Degradation pathways and products

Microbial aerobic degradation of PAHs occurs naturally as well as during bioremediation, and many PAHs are degraded along similar pathways that can be demon-

8 strated using DBT (Figure 1.1). DBT degradation has primarily been studied in detail for a few bacterial strains including Pseudomonas, Sphingomonas, Rhodococcus, Mycobac- terium, Terrabacter, Burkholderia, Paenibacillus, Gordonia, among others (Kodama et al., 1973; Bressler and Fedorak, 2000; Gray et al., 2003; van Herwijnen et al., 2003; Seo et al., 2006), some of which do not fully mineralize the compound (Gibson, 1999; Gray et al., 2003).

4 4a 6 dibenzothiophene 3 S S 7 dioxygenase cis-1,2-dihyroxydihydro- 2 8 NADH dibenzothiophene dibenzothiophene 1 O2 9 + O NAD monooxygenase 2 OH H2O FMNH HO O 2 dibenzothiophene dihydrodiol S dehydrogenase FMN + + NAD 2H

NADH S dibenzothiophene-5-oxide H + O2 FMNH2 dibenzothiophene NAD+ flavin reductase monooxygenase OH FMN HO NADH O O H O + + 1,2-dihyroxydibenzothiophene 2 H NAD dihydroxy-dibenzothiophene S O NADH 2 dioxygenase FMNH2 O2 O NADH dibenzothiophene-5,55- H+ O O(H) dibenzothiophene-5,5-dioxide dioxide monogenase S cis-4-[2-(3-hydroxy)- O O H FMN thionapthenyl]-2-oxo-3- OH OH S + NAD , H2O butenoic acid (enzyme unknown) OH (H)O O S cis-4-(2-(3-hydroxy)-thionaphthenyl) cis-4,4a-dibenzothiophene -2-oxo-3-butenoate isomerase -5,5-dioxide dihydrodiol (unstable) (H)O S O O (H)O HO OH S HO 2'-hydroxybiphenyl- 2-sulfinic acid OH O H O H2O 2 trans-4-(2-(3-hydroxy)-thionaphthenyl)

2',3'-dihydroxybiphenyl- 2’-hydroxybiphenyl -2-oxo-3-butenoate hydratase 2-sulfinic acid 2-sulfinate desulfinase 2- S CHO SO3 H3C O (enzyme unknown) HO + O O(H) O O H O OH S 3-hydroxy-2-formylbenzothiophene pyruvate O (mildly unstable)

O(H) 2-hydroxybiphenyl 6(2'-sulfinophenyl)-6-oxo-6- (2-hydroxy-phenyl)-hexa-2,4- dienoic acid

further degradation Figure 1.1. Bacterial pathways of DBT degradation. Enzymes are indicated in italics. GenesFigure and/or1.1. Bacterial proteins pathways of of enzymes DBT degradation. in blue Enzymes type haveare indicated been in isolated italics. Genes and and/or characterized proteins in of enzymes in blue type have been isolated and characterized in select isolates. Pathway is summarized from selectKodama isolates. et al., 1973, Bressler and Fedorak, 2000, Gray et al., 2003; van Herwijnen et al., 2003, Seo et al., 2006, Gibson, 1999, and Gray et al., 2003. 9 For DBT and many other PAHs including fluorene, dibenzofuran and carbazole, one type of initial attack, so-called “lateral dioxygenation,” involves addition of both oxygens of molecular oxygen (O2) by a Rieske-type Fe-S dioxygenase to two adjacent ring carbons, a process requiring NAD(P)H resulting in dihydrodiol products (Figure 1.1) (Bertini et al., 1996; Moser and Stahl, 2001; Habe and Omori, 2003; Aitken and Long, 2004; Yamazoe et al., 2004; Seo et al., 2006). A dehydrogenase extracts two hydrogens from the dihydrodiol, restoring aromaticity of the dihydroxylated ring. A second dioxygenation step incorporates two more oxygens to catalyze ring cleavage, which may occur between the already hydroxylated ring carbons (“intradiol” or “ortho” cleavage) or adjacent to either carbon (“extradiol” or “meta” cleavage), yielding a variety of products with carboxylic, hydroxyl, and/or aldehyde moieties (Figure 1.1) (Bressler and Fedorak, 2000; Habe and Omori, 2003). At this point, fragments of the cleaved ring can be removed and energy finally gained. The variety of products that can form along the lateral dioxygenation pathway arises because the initial dioxygenation can happen at different positions on the ring resulting in multiple possible dihydroxylated isomers and because these isomers may undergo more than one type of ring cleavage. For DBT, additional compounds can be formed abiotically from biodegradation products, including several disulfides (Bressler and Fedorak, 2000; Seo et al., 2006). Not all theoretically possible products are observed for a given PAH; some products are never observed while others seem favored (Bressler and Fedorak, 2000; Habe and Omori, 2003).

Some PAHs may also be degraded along the “angular dioxygenation” pathway (Bressler et al., 1998 ; Nojiri and Omori, 2002). For DBT and fluorene, degradation via this pathway requires first oxygenation of DBT’s sulfur or the carbon of fluorene’s meth- ylene bridge (Bressler et al., 1998 ; Nojiri and Omori, 2002). For DBT, the sulfur is oxy- genated twice in succession by a monooxygenase to yield dibenzothiophene-5,5-dioxide (Bressler and Fedorak, 2000). Addition of oxygen at the bridging atom, not necessary

10 for dibenzofuran or carbazole, serves to draw electron density from the bridging atom weakening the bond between this atom and the aromatic ring and making it more susceptible to further attack. For ring cleavage, both atoms of O2 are added by a non-heme Rieske-type Fe dioxygenase to the aryl ring adjacent to the bridging atom (e.g., carbons 4 and 4a of DBT, Figure 1.1), forming a transient cis-dihydrodiol (Bugg, 2003). This product is unstable and spontaneously undergoes cleavage between the bridging atom and the ring (e.g., ring carbon 4a of DBT), forming substituted biphenyls, one ring of which is dihydroxylated (e.g., Figure 1.1). Further dioxygenation at the dihydroxylated ring cleaves the ring yielding an aromatic ring structure with an alkenoic acid substituent (Figure 1.1), the target of further attacks that finally yield energy. Interestingly, for the analogs -car bazole and dibenzofuran, this pathway has been more widely explored in isolated strains than the lateral dioxygenation pathway. Whether or not this implies that the angular dioxygenation pathway is the more common pathway among bacteria in general is not clear.

Many of the genes and/or enzymes associated with the first few steps of the lateral and angular dioxygenation pathways have been characterized for a variety of bacterial strains (Nojiri et al., 2001; Habe and Omori, 2003). Not only do known enzymes for a given step show mechanistic similarity, they or their genes often share considerable identity across strains. Consequently, it is not surprising that some of these organisms can perform the same transformations on related compounds (Nojiri et al., 2001; van Herwijnen et al., 2003). In contrast, comparatively little is known about the genes and enzymes that participate in the pathways beyond ring cleavage.

Another degradation pathway, biodesulfurization, exists for DBT and other condensed thiophenes, and branches off the angular dioxygenation pathway after the carbon-sulfur bond is cleaved forming a substituted biphenyl. Analogous pathways

11 have not been reported for fluorene, dibenzofuran or carbazole. In biodesulfurization, the second carbon-sulfur bond is cleaved by 2’hydroxybiphenyl-2-sulfinate desulfinase releasing sulfite and leaving hydroxybiphenyl as a final product (Figure 1.1) (Gray et al., 2003; Lee, 2006). This step is often inhibited by sulfate (Gray et al., 2003). Biodesulfu- rization, demonstrated in Xanthomonas sp. (Constanti et al., 1994), Nocardia globerula (Wang and Krawiec, 1994), Corynebacterium (Rhodococcus) sp. SY1 (Omori et al., 1992), Janibacter sp. YY-1 (Yamazoe et al., 2004), Paenibacillus sp. A11-2 (Ishii et al., 2000), and Rhodococcus erythropolis IGTS8 (Kilbane and Jackowski, 1992), is of interest for use in reducing sulfur content of petroleum during refining, however, it is not clear how important this pathway is for biodegradation of contaminants by mixed cultures.

As demonstrated above, aerobic degradation introduces oxygen functionalities (e.g., -OH, -C(O)H, -C(O)OH) to the PAH structure increasing compound solubility, po- larity and reactivity. This also translates to decreasing compound lipophilicity, and so degradation products may have less affinity for living tissues resulting in reduced bioac- cumulation potential. Although degradation products may have greater solubilities than parent PAHs, which may suggest greater potential to disperse in ground and surface water and migrate off-site, their environmental fate remains unclear. For example, the presence of ortho-positioned functional groups with active hydrogens, common in PAH degradation products, may sorb strongly to minerals common to soils and sediments (Evanko and Dzombak, 1999; Guan et al., 2006). Additionally, while these pathways seem clearly defined, it is not known whether they remain distinct in mixed cultures proceeding in the same manner observed for isolates, or whether pathways “intertwine” in a more complex manner.

12 1.2.4. Monitoring bacterial populations by qPCR

Much previous work on PAH degradation has focused on isolated bacterial strains. As noted above, mixed cultures are of interest because they may more effectively remove a variety of contaminants, including PAHs, than pure cultures (Belkin et al., 1994; Trzesicka-Mlynarz and Ward, 1995). Study of mixed cultures presents some technical challenges: until recently, there has been a lack of techniques available to readily and quantitatively monitor the populations comprising the mixture. Investigations of population changes within microbial communities have relied on culture-independent molecular techniques that are often based on detection of 16S rRNA gene sequences. Methods used to study population dynamics degradation of individual PAHs or PAH-containing pollutants (e.g., creosote) include denaturing gradient gel electrophoresis (DGGE: Duarte et al., 2001; Vinas et al., 2005a), restriction fragment length polymorphism characterization (RFLP: Eriksson et al., 2003; Liu et al., 1997), fluorescent in-situ hybridization (FISH: Castle et al., 2006), and, more recently, quantitative real-time PCR (qPCR: Smits et al., 2004; Singleton et al., 2006;Singleton et al., 2007). Although DGGE, RFLP and FISH are valuable qualitative techniques, quantitative information can be difficult to achieve with them. While qPCR has been applied to quantitatively measure specific strains within natural environments (Hristova et al., 2001), phylogenetic groups in soil

(Fierer et al., 2005) and PAH catabolic genes (Da Silva et al., 2006), few reports yet exist demonstrating the use of qPCR to monitor population dynamics of multiple taxonomic groups during the course of contaminant degradation. Smits et al. (2004) demonstrated the use of qPCR to monitor multiple bacterial strains involved in chloroethene degradation, while Singleton et al. (2006, 2007) combined stable isotope probing with qPCR to follow the dynamics of pyrene degraders in a bioreactor containing a slurry of PAH- contaminated soil. Using their qPCR approach, Singleton et al. (2006) demonstrated that the pyrene degraders, consisting of 3 taxonomically distinct uncultured alpha- and

13 beta–proteobacteria not previously implicated in pyrene degradation, represented at most about 14% of the total 16S rRNA gene copies of the bioreactor’s mixed community, and that the 3 groups exhibited different growth trends over a period of 10 days.

Because the use of qPCR to monitor multiple bacterial taxa in complex systems is a fairly recent application, some questions remain as to how best to acquire and process the data, a concern that will be addressed in the research described below. This application of qPCR is complicated by uncertainties as to how best to process qPCR data when comparing assays for different targets, such as the short regions of the 16S rRNA gene that are used to identify taxonomic groups. The most common approach to obtain starting gene copy numbers in a sample from raw qPCR data is based on the threshold cycle (“Ct”), or the cycle at which fluorescence of the reporter (i.e., SYBR Green) for an individual sample (i.e., qPCR reaction) exceeds a threshold and is distinguishable from background fluorescence (Kubista et al., 2006a). This “Ct” approach is usually part of the software operating the qPCR instrument. The Ct usually occurs early in the exponential phase of the qPCR reaction (Figure 1.2), which, under ideal conditions can be described by:

N = N × 1+ E cn cn 0 ( ) (1.1)

where: Ncn is gene copy number at cycle n

N0 is gene copy number at cycle 0 E is amplification efficiency, ideally 1 cn is the cycle number

14 1.0 a 1 2 3 0.8 0.6 Cycle threshold, "Ct" ﬂuorescence threshold Relative Fluorescence Relative 0.4

0 10 20 30 40 Cycle number

FigureFigure 1.2. 1.2. Stages Stages of of an an ideal ideal qPCR qPCR reaction: reaction: 1-expo - nential1- exponential stage; 2-linear stage; stage; 2-linear -3-plateau stage; 3-plateaustage. stage.

a Relativea Relative fluorescence, ﬂuorescence, e.g., e.g., byby SYBR-Green,SYBR Green, is is a a measure of amount of DNA in the reaction. measure of amount of DNA in the reaction.

Cts are collected for samples and standards containing known copy numbers of the target sequence. Copy numbers in samples are calculated from Ct values based on a linear fit of the Ct values and expected copy numbers of the standard curve. This approach assumes that standards and all samples analyzed with the same primer set amplify with the same efficiencyE ( in the equation above), an assumption that may not always be valid. However, as demonstrated in the equation above, amplification efficiency can have a strong influence on the outcome of PCR reactions (Liu and Saint, 2002a; b). Liu and Saint (2002b) used a mathematical model to simulate the entire PCR reaction (i.e., the early or exponential phase, middle or linear phase, and final or plateau phase), and demonstrate how PCR reaction parameters including initial gene copy number, Ct and amplification efficiency influence each other. The simulations indicated that, when amplification efficiencies differed across samples, higher fluorescence at the plateau

15 phase was not synonymous with higher initial gene copies for a given target, which also demonstrates a potential problem with using endpoint PCR techniques such as clone libraries or DGGE for quantifying bacterial populations. Relatedly, lower Ct values did not necessarily indicate higher initial gene copies in the simulations when amplification- ef ficiencies differed for a given target. Therefore, by assuming identical efficiencies, the Ct approach may significantly over- or underestimate copy numbers, but this has not been well-studied. Amplification efficiencies may vary for a given target because they may be sensitive to the nature and quantity of background non-target DNA and presence of PCR inhibitors, among other things (e.g., Chui et al., 2004; Wolffs et al., 2004a), which may vary across samples derived from a changing complex bacterial community and which may not be the same for samples and standards.

A primary goal for using qPCR in studying bacterial populations within a mixed culture is to understand what fraction of the total community a given population represents. This requires obtaining gene copy numbers of both the population of interest and the total community. If this is done simply by adding up the copy numbers of all populations to obtain the copy number of the total community, there is no assurance that the targeted populations capture the entire community. Instead, the copy numbers of the total community can be obtained using a “universal” primer set, i.e., a primer set that will amplify a region of the 16S rRNA gene from all members of the community. However, this region, while generally conserved, may vary in length and sequence across populations and so not all populations may amplify with identical efficiencies. Since the Ct approach is based on the assumption that amplification efficiencies are identical, this draws into question what template (i.e., the 16S rRNA gene of which population) should be used as a standard curve.

16 Smits et al. (2004), in developing a qPCR-based method to monitor three chlo- roethane degraders in mixed cultures and environmental samples, noted that standard curves for the 16S rRNA genes of the different degraders amplified with a universal primer at efficiencies ranging widely from 50-100%. Amplification efficiencies of the genus-specific primers were not expressly stated. In trying to measure copy numbers of known concentrations of E. coli chromosomal DNA with the universal primer, the different standard curves yielded E. coli 16S rRNA gene copy numbers that varied up to two orders of magnitude, with the variation increasing with decreasing sample copy number. This was not surprising given the variation in amplification efficiencies and the fact that the copy numbers being measured extended three orders of magnitude below the linear region of two of the standard curves. To address the question of which standard curve to use to obtain total copy numbers in order to find the fraction of group-specific copy numbers, the authors recommend dividing the group-specific copy numbers by the total copy numbers calculated according to that group’s standard curve. Hence, for each group, the denominator (i.e., total copy numbers in the sample) is a different number. Additionally, this approach remains dependent on the assumption upon which the Ct approach rests, that all targets analyzed with a given standard curve amplify identically.

When the approach proposed by Smits et al. (2004) is used to determine the relative abundance of a target group’s copy numbers, i.e., the fraction of the total copy numbers belonging to the target group within a mixed culture, it is not possible to tell how accurate that fraction is since all other groups are not being accounted for. Howev- er, when trying to account for essentially all known groups in the DBT-degrading culture using qPCR, which is part of Objective 1 below, the sum of fraction of copy numbers for each group as determined by the Smits et al. (2004) approach rarely approximated 1. While this may have been a result of the presence of additional groups that were missed in the qPCR assays, it also could have been due to the lack of a firm and consistent value

17 for total copy numbers upon which each fraction was based. Given the potential use for qPCR in assaying complex microbial communities, research is needed to test this approach in a controlled and systematic way using other targets and primers to help resolve issues of how best to determine relative abundances.

The Ct approach is not the only way to analyze qPCR data. Another approach, sigmoidal curve fitting (SCF) (Liu and Saint, 2002a; b; Rutledge, 2004; Spiess et al., 2007), models the entire qPCR reaction and calculates amplification efficiencies and starting fluorescence attributable to the target sequence, which can be converted into copy numbers, for individual reactions. This approach, which is explained in detail in Chapter 4, can be used to evaluate how consistent amplification efficiencies are for a given target. Because SCF does not rely on assumptions of identical amplification- effi ciencies across reactions for a given target, it may yield more accurate values for target copy numbers than the Ct approach. The application of this approach to studying bacterial groups in mixed cultures has not been explored. A comparison of both Ct and SCF approaches may not only test the assumption of identical amplification efficiencies inherent to the Ct approach, but also help determine the best way to process qPCR data in studies on mixed communities.

1.2.5. Photooxidation in contaminant reduction

With the aim of improving remediation strategies for persistent contaminants such as PAHs, many researchers have investigated a variety of approaches to overcome contaminant recalcitrance. For example, surfactants have been used to enhance contaminant desorption from solid matrices to facilitate further treatment, such as through biodegradation, with varying degrees of success (Boonchan et al., 1998; Sobisch et al.,

18 2000; Bach et al., 2005). The ecological impact of this approach is not always apparent since surfactants may be toxic themselves, may increase bioavailability to sensitive organisms, or facilitate off-site transport by increasing aqueous concentrations. Physi- cal and chemical oxidation treatment is another approach that may be used to enhance degradation of contaminants, and may be achieved using Fenton’s reagent (Fe(II)/H2O2), solar or UV light (i.e., photooxidation), ultrasound, ozonation, or a combination of these and related treatments (e.g., Nadarajah et al., 2002; Jonsson et al., 2006; Shemer and Linden, 2007a; b). Of these techniques, photooxidation is of particular interest because it is one of the more commonly used techniques in water treatment, and it also occurs naturally in surface water.

Photooxidation has also been combined with biodegradation, usually as a pretreatment, under the hypothesis that oxidation will enhance bioavailability and facilitate microbial attack (Lehto et al., 2003;Benoit Guieysse et al., 2004; Guieysse and Viklund, 2005; Holt et al., 2005), however, demonstration of this hypothesis has yielded mixed results. Research by Guieysse and Viklund (2005) showed complete removal of several PAHs including benzo[a]pyrene by dissolving the compounds in organic solvent for UV irradiation followed by transfer into silicone oil for biodegradation in a two-phase reactor. Lehto et al. (2003) evaluated UV irradiation of individual and mixed PAHs (anthracene, pyrene, benz[a]anthracene, and dibenz[a,h]anthracene) as well as creosote in deionized water at saturation followed by degradation by an enrichment culture derived from creosote-contaminated sediment. UV pretreatment enhanced biodegradation of individual PAHs, except for dibenz[a,h]anthracene, had no effect on biodegradation of the PAH mixture, and reduced biodegradation of PAHs in creosote compared to biodegradation without UV. Reasons why UV treatment inhibited biodegradation of creosote, although not clear from the study by Lehto et al. (2003), may include the formation of toxic photoproducts such as quinones (Holt et al., 2005), as well as photo-induced

19 toxicity of UV-activated PAHs, which can be many times more toxic and/or more acutely toxic than non-irradiated PAHs (Arfsten et al., 1996; Yu, 2002). Photooxidation of PAHs typically results in products containing oxygen functionality, including carboxylic acids, hydroxylated compounds, and quinones (David and Boule, 1993; McConkey et al., 1997; Mallakin et al., 1999). The identities, environmental fates and toxicities of many of these products are not well understood, yet these products may have important impacts on humans and wildlife.

Most of the research evaluating combined UV-biodegradation treatment of PAHs has focused on non-heterocyclic compounds. The use of UV treatment following biodegradation for DBT has only been explored by Chamberlin (2005) using the same mixed culture as the current proposed research. Chamberlin (2005) evaluated UV treatment of supernatant from the culture and assayed (1) changes in overall UV spectra of supernatant following exposure to a medium pressure monochromatic Hg vapor UV lamp at fluences up to 1000 mJ cm-2, (2) changes in aqueous DBT and unknown degradation products measured by HPLC in culture supernatant at 0 and 8 days post-inoculation before and after UV exposure at fluences up to 800 mJ -2cm , (3) the effects of UV treatment during biodegradation to enhance DBT removal compared to biodegradation alone. Overall, these studies showed that some potential degradation products were susceptible to UV treatment, however the identities of the products were not discovered. These studies monitored only aqueous phase components but did not report total DBT although DBT was added above solubility.

Photooxidation of DBT by UV alone, not combined with biodegradation, has been explored in several studies. Shemer and Linden (2007a, b) observed that UV alone (2000 mJ cm-2 fluence, low pressure lamp) transformed only 15% of initial of DBT (4.5 µM in 2 mM phosphate buffer, pH 7) and did not reduce toxicity to bioluminescent bacteria (Vi-

20 brio fischeri). The combination of UV with H2O2, however, resulted in 98% DBT removal and reduced toxicity by approximately 75%. DBT photoproducts observed in the literature include benzothiophene-2,3-dicarboxylic acid, 2-sulfobenzoic acid, DBT carboxylic acids, DBT sultine, DBT sulfone, among others (Bobinger et al., 1999; Traulsen et al., 1999). Many of these products are also biodegradation products (Bressler and Fedorak, 2000; Nojiri et al., 2001; Gray et al., 2003; Seo et al., 2006). Although some products such as DBT sulfone have been shown to be less toxic than DBT itself (Seymour et al., 1997), little is known about the potential hazards of other products.

Biodegradation of DBT by mixed cultures requires further investigation to both improve the effectiveness of bioremediation strategies as well as to understand -bet ter what may be happening naturally at sites containing elevated levels of these compounds. Research needs include deepening current understanding of community structure of complex contaminant-degrading cultures, increasing knowledge of degradation products, and determining how to mitigate residual or transient toxicity. Addressing these needs simultaneously can maximize benefits gained through research. The research proposed below addresses all of these goals by exploring how a microbial community obtained from a creosote-contaminated site degrades DBT, how toxicity and the bacterial populations of that community change during degradation, what degradation products are formed, and whether or not post-biodegradation UV photolysis can reduce degradation products and/or toxicity.

21 1.3. Re s e a r c h Pl a n

1.3.1. Hypotheses

The chemical characteristics, environmental fate and ecotoxicology of degradation products of DBT are not well understood, and the microbial populations involved in degradation are incompletely studied apart from some isolated strains. Yet, all of these aspects may influence the goals, strategies and effectiveness of bioremediation. Few studies incorporate toxicity assays along with identification and monitoring of both degradation products and microbial populations during contaminant degradation. To the best of my knowledge, this combined approach has not been previously explored for DBT. The use of UV oxidation following biodegradation to remove residual degradation products has received little attention, particularly for heterocyclic PAHs including DBT. Yet, PAH-contaminated sites commonly contain heterocyclic compounds and UV treatment post-biodegradation may be a valuable means to improve the success of bioremediation.

This research investigated the degradation of DBT in an enrichment culture -de rived from creosote-contaminated estuarian sediment using a suite of assays to monitor bacterial populations, degradation products, DBT loss, and toxicity. In addition, the use of UV was evaluated as a secondary treatment following biodegradation. As mentioned above, the overall objective of this research was to gain a comprehensive understanding of the degradation of a model heterocyclic PAH, DBT, by a mixed microbial community, particularly within the context of remediation goals. The primary hypotheses underlying this research include:

22 Hypothesis 1: A mixed culture derived from a creosote-contaminated site should contain organisms capable of tolerating and degrading DBT.

Hypothesis 2: Monitoring bacterial population dynamics in mixed cultures should reveal new strains potentially important to degradation of DBT but which have not been successfully demonstrated to have the ability to mineralize DBT in pure cultures.

Hypothesis 3: The degradation of DBT by a mixed culture will follow multiple degradation pathways forming an array of products.

Hypothesis 4: Some degradation products may interfere with the remediation goals of contaminant reduction and toxicity amelioration by being toxic themselves and/ or by inhibiting the degradation process.

Hypothesis 5: Because the SCF approach for processing qPCR data makes no assumptions for amplification efficiencies, it may yield more accurate copy number values than the conventional Ct approach, and so may aid in determining percentages of group- specific copy numbers within a mixed microbial community.

Hypothesis 6: At least some biodegradation products may be susceptible to UV treatment, which may reduce residual toxicity by further degrading products remaining after biodegradation.

1.3.2. Research Objectives

The following research objectives will address the proposed hypotheses:

23 Objective 1: Evaluate DBT biodegradation by a mixed bacterial culture.

A bacterial culture obtained by enrichment from a creosote-contaminated site was used in this research. This objective was addressed by evaluating DBT loss, formation of degradation products, culture growth, changes in bacterial populations assessed using qPCR and toxicity assayed with the bioluminescent bacterial species Vibrio fischeri under conditions with and without pH control. This objective focused on Hypotheses 1, 2, 3 and 4, and is the focus of Chapters 2 and 3.

Objective 2: Compare conventional and alternative approaches for evaluating quantitative PCR data from mixed cultures.

As mentioned above, the Ct approach for processing qPCR data is strongly founded on the assumption that all samples being analyzed with a given standard curve amplify with the same efficiency as the standard curve. An alternative approach uses sigmoidal curve fitting (SCF) to model each reaction to determine the amount of initial fluorescence of the reporter dye, in this case the double-stranded DNA stain SYBR Green, which is proportional to DNA concentration and can be used to calculate starting target copy numbers for that reaction. This objective was approached by comparing the conventional Ct approach to the SCF approach for determining total and group-specific 16S rRNA gene copies measured by qPCR in artificial mixed cultures comprised of cloned and genomic DNA from isolates, and to evaluate amplification differences between standards (i.e., clone plasmid containing target 16S rRNA genes) and genomic DNA. This work, presented in Chapter 4, targeted Hypothesis 5, and supported qPCR methodology used in Objective 1.

24 Objective 3: Examine the use of post-biodegradation UV treatment.

This objective, which targeted Hypothesis 6, expanded on the research conducted by Chamberlin (2005), which demonstrated the potential of post-biodegradation UV treatment to reduce residual biodegradation products in the culture supernatant. To address this objective, this research evaluated the effect of UV fluence (i.e., doses) from a low-pressure monochromatic UV source (254 nm) on DBT biodegradation products and toxicity using two different bioassays. This objective was the subject of Chapter 5.

1.4. Scientific significance

Because this research focused on a mixed culture, it expands current understanding of biodegradation of DBT not possible through the study of bacterial isolates. It is well-known that very few bacteria can be cultured in isolation, which has limited identification of contaminant degraders. Additionally, contaminant degradation can require more than one organism, further limiting the ability of culturing approaches to identify degraders. The use of the culture-independent qPCR approach to study a mixed culture in this research aids in identifying bacterial populations previously unassociated with PAH biodegradation.

Complex microbial systems are not restricted to contaminated sites. They include essentially all environmental media (e.g., soils, sediments, water), as well as biological environments such as the gastrointestinal tract and engineered systems such as water treatment facilities. The growing need to understand these complex systems requires the adaptation of culture-independent methods, such as qPCR, to monitor a suite

25 of bacterial populations. This research advances current methodology by comparing ways to process qPCR data for this application. Given the widespread nature of complex microbial systems, this research can benefit environmental, engineering, agricultural, ecological, and medical sciences.

In many soils and sediments contaminated with PAHs, biodegradation can occur naturally as well as during conscientious bioremediation efforts, and degradation products will form. Current understanding of the identities, fates and potential toxicity of these products is limited, particularly for complex systems, yet some of these products may be of concern to environmental integrity and human health. This research adds to current knowledge through the identification of biodegradation products and monitoring toxicity associated with their formation and/or disappearance during the course of PAH biodegradation. Association of biodegradation products with measurements of toxicity aids in refining bioremediation strategies to limit on-site levels and/or off-site transport of potentially toxic degradation products. No previous studies have combined advanced techniques such as qPCR for monitoring bacterial community composition with assessments of toxicity and degradation products during the course of biodegradation of any PAH.

This research further assists in improvement of bioremediation strategies by in- vestigating an unconventional approach combining microbial degradation with photolysis using UV. The addition of UV treatment has the potential to reduce levels of residual microbial degradation products that may be toxic. With the exception of the work of Chamberlin (2005), this approach is relatively untried for DBT. This research addresses questions regarding the value of this treatment approach to reduce contaminants and the overall effect on toxicity.

26 Chapter 2. Microbial population dynamics during DBT degradation

2.1. In t r o d u c t i o n

Polycyclic aromatic hydrocarbons (PAHs) are persistent and ubiquitous environmental contaminants associated with petroleum products and combustion (Aitken and Long, 2004), and they may elicit a variety of toxic effects (ATSDR, 1995; Penning et al., 1999). PAH recalcitrance and toxicity drives remediation efforts to restore contaminated ecosystems and protect human health. Biodegradation of PAH contaminants and resulting changes in toxicity in natural and engineered systems are complex phenomena because these contaminants are often present in mixtures, they have many metabolites whose chemical characteristics, environmental fates and ecotoxicological effects are unknown, and because multiple bacterial strains are likely involved in the degradation processes.

As discussed in Chapter 1, much previous work on PAH degradation has focused on pure cultures. However, mixed cultures are of interest because environmental samples occur as population mixtures, and they may more effectively remove a variety of contaminants, including PAHs, than pure cultures (Belkin et al., 1994; Trzesicka-Mlynarz and Ward, 1995). This suggests that different micro organisms may play specialized, synergistic roles in biodegradation such as initiation of degradation by one organism and degradation of intermediates by others. In addition, intermediate formation can result in increased toxicity (Belkin et al., 1994; Phillips et al., 2000; Ahtiainen et al., 2002), which may endanger the success of bioremediation efforts, but little work has been performed to assess toxicity during PAH degradation. Bioremediation may also be hampered by changes in environmental conditions linked to the degradation process, such as changes

27 in pH. A better understanding of what microorganisms comprise a mixed community degrading a toxic compound, how microbial populations change during the course of degradation, the metabolites produced or consumed, the cultural conditions that pro- mote degradation, and net effects on toxicity will increase our fundamental understanding of complex system behaviors, and may aid in the development and improvement of bioremediation strategies.

Investigations of population dynamics within microbial communities have often used culture-independent molecular techniques that are often based on detection of 16S rRNA gene sequences. Methods used to study population dynamics degradation of PAHs or PAH-containing pollutants (e.g., creosote) include denaturing gradient gel electrophoresis (DGGE: Duarte et al., 2001; Vinas et al., 2005) restriction fragment length polymorphism characterization (RFLP: Eriksson et al., 2003; Liu et al., 1997), fluorescent in-situ hybridization (Castle et al., 2006), and, more recently, quantitative real-time PCR (qPCR: Smits et al., 2004; Singleton et al., 2006). The former three are powerful qualitative techniques, but quantitative information can be difficult to achieve with them. While qPCR has been applied to quantitatively measure specific strains within natural environments (Hristova et al., 2001), phylogenetic groups in soil (Fierer et al., 2005) and PAH catabolic genes (Da Silva et al., 2006), few reports yet exist demonstrating the use of qPCR to monitor population dynamics of multiple taxonomic groups during the course of contaminant degradation. Smits et al. (2004) demonstrated the use of qPCR to monitor multiple bacterial strains involved in chloroethene degradation, while Singleton et al. (2006) combined stable isotope probing with qPCR to follow the dynamics of pyrene degraders in a bioreactor.

The sulfur-containing PAH dibenzothiophene (DBT) is a common, low solubility, recalcitrant constituent of creosote and petroleum wastes and is a model compound

28 for more complex sulfur-containing heterocyclic aromatic hydrocarbons. DBT may be degraded by bacteria through attack at sulfur (the “angular dioxygenation” pathway) or the aromatic ring (the “lateral dioxygenation” pathway; Bressler and Fedorak, 2000). But metabolism of DBT has primarily been studied in detail only for specific bacterial strains (Kodama et al., 1973; Gray et al., 2003; van Herwijnen et al., 2003), some of which do not fully mineralize the compound (Gray et al., 2003). The chemical characteristics, environmental fate and ecotoxicology of DBT metabolites are not well understood, and the microbial populations involved in DBT degradation have not been studied in mixed communities. Yet, all of these aspects may influence the goals, strategies and effectiveness of DBT bioremediation.

From the perspectives of improving the effectiveness of bioremediation efforts and gaining a better understanding of biodegradation processes by mixed cultures, there is a need for research that monitors microbial population dynamics using quantitative techniques, formation of degradation intermediates and effects on toxicity. In this study, these aspects were evaluated in a DBT-degrading enrichment culture during DBT degradation using 16S rRNA gene-based qPCR assays targeting taxonomic groups, a bioluminescent bacterial toxicity assay, and chromatographic techniques to monitor the loss of DBT. Additionally, experiments were performed under conditions with and without pH control to include the effect of a critical environmental variable. This unique combination of measurements should provide a broader perspective on DBT degradation than currently available, encompassing not only microbial ecology but also considerations important to bioremediation, such as DBT loss, cultural requirements and effects on toxicity. This study addressed Hypothesis 1 provided in Chapter 1, that a mixed culture derived from a creosote-contaminated site would contain bacteria tolerant of and capable of degrading DBT. The study also focused on the second hypothesis, that monitoring bacterial population dynamics in mixed cultures would reveal new strains potentially

29 important to DBT degradation but which have not been linked to DBT degradation in pure culture studies. Finally, this study addressed Hypothesis 3, that changes in pH during degradation would affect the extent of DBT degradation, and subsequently toxicity.

2.2. Me t h o d s

2.2.1. Culture establishment, 16S rRNA gene clone library construction, isolation of pure cultures, and phylogenetic analysis

An enrichment culture growing on DBT as a sole carbon source was established from sediment from a PAH-contaminated brackish tidal inlet along the southern branch of the Elizabeth River, Portsmouth, Virginia (36° 48’ 28.6’’ N 76° 17’ 39’’W), adjacent to the Atlantic Woods Industries, Inc., National Priorities List Site. The culture was shaken in the dark in artificial seawater media (22.22 g-1 L Instant OceanTM) supplemented with

-1 -1 -1 . 1 g L NH4NO3, 0.2 g L K2HPO4 and 0.05 g L FeCl3 6H2O (adapted from Chang et al., 2000, and Kasai et al., 2002) and adjusted to pH 7.5 prior to inoculation. The enrichment culture was subcultured approximately five times over three months by transfer of 200 µL of culture to fresh medium, at which point 5 mL of the culture was centrifuged and DNA was extracted from the pelleted cells by bead-beating (UltraClean Soil DNA Extrac- tion Kit, MoBio Laboratories, Solana Beach, CA). 16S rRNA gene sequences were amplified using universal primers fD1 (AGAGTTTGATCCTGGCTCAG, Escherichia coli positions 8 to 27) and rP2 (ACGGCTACCTTGTTACGACTT, positions 1513 to 1494) (Weisburg et al., 1991). Integrated DNA Technologies, Coralville, IA) in 50 µL reactions containing approximately 5 ng of template DNA, primers (0.5 µM each), deoxynucleoside triphosphates

(0.8 µM each), MgCl2 (2.0 mM)¬, Taq polymerase (2.5 U; Qiagen, Valencia, CA), and 1x PCR buffer (Qiagen). The PCR protocol consisted of initial incubation at 95° C for 6 min, a second stage of 30 cycles of 60 s at 95° C, 30 s at 52° C, and 60 s at 72° C, and a third

30 stage of 10 min at 72° C. A 16S rRNA gene clone library was prepared using TOPO-TA cloning kit with One Shot Top10 chemically competent cells and pCR 2.1 vector (Invitro- gen Corporation, Carlsbad, CA). 16S rRNA gene sequences from 52 clones were amplified using the above primer set and PCR protocol. Isolates were obtained by selective subculturing on solid media (liquid artificial seawater media, 12 g-1 L agar, 5 g L-1 glucose, 5 g L-1 yeast extract, 5 g L-1 peptone). Isolation using DBT as a sole carbon source was also attempted on solid media containing no glucose, yeast extract or peptone, but no organisms were successfully cultured. DNA was extracted from the isolates and amplified as described above. PCR reaction products from clones and isolates were purified using a QiaQuick PCR cleanup kit (Qiagen) and sequenced on an automated sequencer (Model 3700, Applied Biosystems, Foster City, CA) using the BigDye Terminator kit (v. 3.0). Sequences were proofread using FinchTV (v. 1.3; Geospiza, www.geospiza.com) and screened for chimeras using Chimera Check program (v. 2.7, Ribosomal Database Program (RDP: Cole et al., 2005). Of the clone sequences, 3 were excluded as possible chimeras. Taxonomic groups were assigned to all sequences using the RDP Classifier program (Cole et al., 2005). Sequences were aligned using ClustalX 1.81 (EMBL, Heidel- berg, Germany), and the alignment was trimmed using BioEdit. Parsimonious phylogenetic analysis was conducted using PHYLIP v. 3.6 programs DNAPARS and SEQBOOT (Felsenstein, 2005), and phylogenetic trees were viewed using TreeView v.1.6.6 (Page, 1996, 2000). Rarefaction, calculated using EstimateS (Colwell, 2005), was used to assess how completely the culture’s taxonomic groups were sampled using clone and isolate sequences.

2.2.2. qPCR primer design and assay

Ten group-specific primer sets and one universal primer set targeting 16S rRNA gene sequences were designed using Primrose 2.15 (Ashelford et al., 2002) based on the phylogenetic alignment from the enrichment culture (Table 2.1).

r b e 6 7 6 8 8 8 8 8 6 7 8 o n 0 0 0 0 0 0 0 0 0 0 0 ti - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 u m 2 2 2 3 3 3 3 3 1 3 3 e c a n g e 0 0 0 0 0 0 0 0 0 0 0 1 1 1 1 1 1 1 1 1 1 1 R e t D o p y N C h e ) s r a t m 2 7 5 9 5 0 1 6 8 2 8 7 3 7 0 9 7 5 4 1 9 p a i 9 1 1 1 3 1 1 2 3 1 1 e o x i o n L e g t c i b a s p r p l ( A m A

s o n . e a l ti u r 3 3 3 3 3 2 6 3 2 3 3 3 6 3 3 4 3 3 3 3 3 4 d a n e a t a / 5 / 5 / 5 / 5 / 5 / 5 / 5 / 5 / 5 / 5 / 5 / 5 / 5 / 5 / 5 / 5 / 5 / 5 / 5 / 5 / 5 / 5 r A 9 7 9 9 9 8 1 9 8 9 8 9 1 0 8 9 9 8 8 8 8 9 ° C / g r 5 5 5 5 5 5 6 5 5 5 5 5 6 6 5 5 5 5 5 5 5 5 t p e e l e m T d e M T B s n g D e i r 2 1 9 8 2 1 2 0 1 4 1 0 4 1 4 1 0 9 9 2 0 4 2 2 1 1 2 2 2 2 2 2 2 2 2 2 2 2 2 1 1 2 2 2 a s B P a i d u r s c i m o n d y a ti C G G a G C T C A G A G C T G C C T A T C G T T G G . T T T C G C A G T C A T T p o u l C A T G A e R T A C G C A G T C G A T A C G T G C T T y z G C T G Y T T A G C T l A T C G T C A G . , 1 9 ) A G T l G T G T A C T n a A G T C G T T . C A G T a T t G C T G T C G A T o a e s T A G C T A T G A T C e A C G T A G T C A T A G C T e C T A C T G A C T T G T e r C G A T o g i i e d t C A G T n c G C A T G T e C A G T G C A T T T G A C T Y A G C R T A G T C A G T M u s G C A T G A C T h n o l s C A G T C G T G C A T T G C A T T r C A G T e S e q u C G T G C A T G A T C G T A C G T G C A T T C G T C T C T C G A T C G T G T C G A T C T C A G T C T C G A T G T G A C T C T C R A T T e c m 3 5 ( i A ‡ † F F F F F F F F F F F R R R R R R R R R R R p r L g c R r e d D N e m t i q P C a i a r g r o f s e t e c c n t h e d p r ti a s I s b i i r o i a e r o m t e t i a r s -like o c e t e s r e r f p u b l c a a d l e Characteristics of qPCR primers used to analyze population dynamics during DBT degradation. dynamics during population to analyze used of qPCR primers Characteristics a p r t e a e a e o u p e r c a c b n r c s -like i l a a o m h o o m r t a b i r i l e G i a ti a e t e o p m r c c i a i s o d f o y s r t e b t e o l e d m a p o c a d m t e u ﬁ o r a s a E V p r i z o o r 2 . 1 C h a e p r t o b h h R s m e e a i c u c o Other A l p R R C h Kordiimonas P o d i h n v i v m b l a x o n m l a 1 6 s

M Table 2.1. Table T a T G a F i r m P A l p U n F l a † ‡

32 Group-specific primers were selected to have more than two mismatches between target and non-target sequences, to have similar melting temperatures for each primer in a set, to have minimal likelihood for secondary structure or dimer formation, and to amplify less than 500 bp. Two primers were modified from previously published primers to more precisely match the selected sequences. These included the Firmicutes reverse primer based on the Lcg353 probe (Potter et al., 1999) and the universal reverse primer rP2 (Weisburg et al., 1991). All other primers were unique to this study, and were 18- 24 base pairs long with melting temperatures of 57-61° C. SYBR Green-based qPCR was performed on an ABI Prism 7000 (Applied Biosystems) or a Stratagene MP3000 (Strata- gene, La Jolla, CA) using iTaq SYBR Green Supermix with ROX (BioRad, Hercules, CA) according to manufacturer’s instructions with primer-specific annealing temperatures. Target amplicons were 98-346 base pairs long. Primer specificity was checked in qPCR assays including meltcurve analyses comparing representative clones and/or isolates from target and non-target groups in the culture as well as sequencing of qPCR samples as described above to confirm amplification of the target sequence. For standards, 16S rRNA gene copies for each group were cloned as described above, plasmids were recovered using the QiaPrep Plasmid Miniprep kit (Qiagen) and DNA was quantified using a NanoDrop ND-1000 spectrophotometer (NanoDrop Technologies, Wilmington, DE). Standard curves were prepared from purified plasmids as 10-fold serial dilutions over the dynamic range of each assay (Table 2.1). Standard curves and no-template controls were included for all qPCR assays, and all standards, samples and no-template controls were analyzed in triplicate. Because the universal primers amplified target DNA from all taxonomic groups, for each of which there was a set of standards, determination of total 16S rRNA gene copies by the universal primers was achieved by first calculating gene copy numbers from Ct values according to each standard curve, yielding 10 values for total 16S rRNA gene copies, one for each set of standards. These 10 values were averaged to give total 16S rRNA gene copies. This approach to calculating total 16S rRNA

33 gene copies using the universal primers was found to provide acceptable quantitation in simulated mixed communities containing known amounts of DNA (see Chapter 4).

2.2.3. Degradation study

For the DBT degradation studies, 0.152 mmoles DBT (Aldrich) in 200 µL acetone was added to sterile 50 mL Erlenmeyer flasks and allowed to dry. Mass of DBT added to the flasks was confirmed by HPLC analysis as described below. Twenty-five mL sterile artificial seawater media (described above) was added for an initial DBT concentration of 6.08 mM, which was above the solubility limit for DBT in pure water (1.1 µM; Lassen and Carlsen, 1999). After media addition, flasks were inoculated with 100 µL of a stock enrichment culture (0.3 optical density at 600 nm) that either had been maintained without pH control (for the experiment with no pH control) or had been adapted to pH- controlled conditions established by adjusting culture pH to 7.5 every 2 days (for the -ex periment with pH control) . Control flasks were prepared in a similar manner but without inoculum. Flasks were mixed on an orbital shaker in the dark. Sampling occurred every 2 days for the first 20 days in experiments with and without pH control, and every 4 days between 20 and 32 days in the experiment with pH control. For the experiment with pH control, pH adjustments were made on the same schedule as sampling. Sam- pling was not continued beyond 20 days in the experiment without pH control because no significant changes were observed in total DBT concentration.

Each sampling included sacrificing 6 control and 6 inoculated flasks (12 flasks per sampling), as described below, requiring a total of 168 flasks for the experiment with pH control and 132 flasks for the experiment without pH control. At each sampling, 3 control and 3 inoculated flasks were acidified to pH 2 with 6 M HCl, DBT was extracted

34 with 25 mL of ethyl acetate for 2 h on an end-over-end shaker, and total DBT was measured by reversed-phase HPLC. Samples were acidified to protonate acidic groups on potential degradation products and facilitate their partitioning into the organic phase (ethyl acetate) and their detection by HPLC. HPLC results for DBT degradation products (not included) were ultimately replaced by results of GC/MS analyses (described below) because it provided greater opportunity for product identification. HPLC was performed on an Agilent 1100 series instrument with a Zorbax Eclipse XDB-C18 column (250 x 4.2 mm) (Agilent, Newark, DE) at a flow rate of 1 mL min-1 and 234 nm detection. The mo- bile phase was a gradient of methanol and 0.1 M ammonium acetate buffer at pH 4.5. The gradient consisted of 30% methanol:70% buffer for 2 minutes followed by a gradient to 100% methanol by 22 min. GC/MS was not used to obtain total DBT concentrations because this technique was not available when the analyses were done. Contents from the additional 3 control and 3 inoculated flasks were processed and analyzed for toxicity and aqueous DBT and DBT degradation products as described in Chapter 3.

Pelleted cells from each inoculated sample flask wereresuspended in 400 µL of sterile artificial seawater media. A 25 µL aliquot was used to determine total protein -us ing the Pierce bicinchoninic acid assay kit (Pierce, Rockford, IL) using a FLUOstar Optima (BMG LabTech, Durham, NC) plate reader according to the manufacturer’s instructions. DNA from selected days was extracted from the remainder of the cells for qPCR using the PowerSoil DNA extraction kit (MoBio). For all remaining flasks in the experiment with pH control, pH was adjusted to pH 7.5±0.1 with NaOH to approximate pore water pH of 7.55 from the source site.

The DBT degrading ability of isolates, alone and in combination, was evaluated using experimental and sampling procedures as described above with some modifica- tion. For these studies, final concentration of total DBT was 2 mM. Stock cultures of

35 isolates were grown in supplemented artificial seawater media similar to the solid media used to obtain isolates (described above) without agar. Eight isolates, indicated in Figure 2.1, were evaluated. Prior to inoculation, cultures were centrifuged at 5000 x g, washed twice with sterile artificial seawater, and resuspended in this solution to an optical density of 0.3 at 600 nm. A composite isolate stock was prepared using equal volumes of all nine isolates. Flasks were inoculated with 100 µL of the appropriate single or combined isolate stock. Triplicate flasks were prepared for both individual isolate and the isolate combination. Every two days pH was adjusted as described above, and samples were taken at days 0 and 20. Samples were analyzed for DBT and total protein as described above.

2.2.4. Toxicity assay with bioluminescent bacteria.

Toxicity was assessed as inhibition of luminescence in the bioluminescent bacterium Vibrio fischeri (also known as Photobacterium phosphoreum), strain NRRL B-11177 (ATCC, Manassas, VA), using a method adapted from McConkey et al. (1997). Bacteria were grown in Photobacterium broth (Fluka BioChemika, Buchs, Switzerland) at 15° C on an orbital shaker in the dark for 3 days. Cells were centrifuged for 5 min at 5000 x g, the supernatant was removed and the cells were resuspended in chilled 2% w/v NaCl to an optical density of 0.82-0.86 at 600 nm. This bacterial suspension was added to a polystyrene 48-well plate (0.5 mL per well), the plate was incubated in the dark for 10 min at 15° C, and luminescence was measured using a FLUOStar Optima plate reader. Filtered aqueous supernatant (0.5 mL) collected from the degradation study flasks described above was adjusted to pH 7.5±0.1 with NaOH, added to the wells, incubated for 30 min, and luminescence was measured again. In addition to experimental (uninoculated) controls, all toxicity assays included a control dosed with artificial seawater media free

36 of DBT. The toxicity of each sample and control was expressed as percent inhibition of luminescence calculated as (Mcconkey et al., 1997):

% inhibi on of luminescence 100 (2.1)

2.2.5. Statistical analyses.

Analyses of variance (ANOVAs) were used to compare variables between pH treatments and time points. ANOVAs were performed on a PC using the statistical -soft ware R (R Development Core Team, 2008).

2.3. Re s u l t s

2.3.1. Phylogenetic analysis

A clone library was prepared from the enrichment culture 16S rRNA genes, and 52 clones were selected for sequencing, of which 3 were discarded as chimeric sequences. The remaining 49 clones represented 7 taxonomically distinct species (Figure 2.1). Isolation by successive agar plating yielded 8 distinct strains, some of which were repeatedly isolated. These strains included Bacillus sp. (99% sequence match to Gen- Bank accession number AB02115), Vitellibacter sp. (99% match to GenBank AB071382), two Rhizobiales sp. (99% matches to GenBank AY649762 and 100% match to GenBank AM403232), Rhodospirillaceae sp. (98% match to GenBank AY186195), Pseudomo- 37 nas stutzeri (99% match to GenBank AJ244724), P. balearica (99% match to GenBank U26417), and Marinobacter sp. (97% match to GenBank AB167042). With the exception of one clone and one isolate with 99% match to the Vitellibacter vladivostokensis 16S rRNA gene sequence, there was no redundancy between sequences obtained through cloning and isolation techniques. This likely reflects well-known biases and limitations in the use of culturing techniques to isolate bacterial strains (Ward et al., 1990; Wagner et al., 1993).

38 Firmicutes a. Bacillus ﬂexus AB021185 (3) Gelidibacter sp. 99 AY682382 (2) 99 b. Flavobacteriaceae Vitellibacter vladivostokensis 99 AB071382 93 (1) (6)

(1) c. 96 Planctomycetales sp. AY162119 Planctomycetaceae 98 (6) 58 (2) d. 99 Martellela mediterranea AY649762 (1) (1)

e. 99 Rhodospirillales sp. AY18695 (1) (9) 90 38 (1) f. 94 99 (1) Alphaproteobacteria 60 (2)

g. 97 (1) 37 Azospirillum sp. AF413109 h. 99 Kordiimonas gwangyangensis AY682384 (2)

i. 80 Thialkalivibrio denitriﬁcans AY360060 (14)

99 (5) (1) Gammaproteobacteria

j. 99 Pseudomonas stutzeri AJ312159

Pseudomonas balearica U26417 (8) (1) 0.1

FigureFigure 2.1. 2.1. Unrooted maximum parsimony phylogeneticphylogenetic treetree basedbased onon anan 10401040 basebase pairpair alignment alignment of of 16SS 16SS rRNA rRNA gene gene sequences sequences of of isolates isolates and and clones clones fromfrom DBT-degrading enrichmentDBT-degrading culture enrichment with reference culture sequences with reference indicated sequences by GenBank indicated accession by GenBank numbers. Branchaccession values numbers. are bootstrap Branch values values from are bootstrap 500 iterations. values Thefrom scale 500 iterations.bar represents The ascale 10% differencebar represents in nucleotide a 10% diﬀerence sequence. in nucleotide Numbers ofsequence. clones ( ) andNumbers isolates of clones() obtained () and are givenisolates in parentheses () obtained adjacent are given to in symbol. parentheses Letters adjacent represent to symbol. group-specific Letters representprimer sets: (a)group-speciﬁc Firmicutes, (b) primer Flavobacteriaceae sets: (a) Firmicutes, (c) Planctomycetaceae, (b) Flavobacteriaceae, (d) ,Rhizobiales (c) -like bactera, (e)Planctomycetaceae Rhodospirillaceae,-like (d) Rhizobialesbacteria, (f)-like Other bactera, Alphaproteobacteria (e) Rhodospirillaceae, (g) Azospirillum-like bacteria,-like (f) bacteria,Other Alphaproteobacteria (h) Kordiimonas, (i), Chromatiales(g) Azospirillum and-like (j) bacteria,Pseudomonas (h) Kordiimonas. , (i) Chromatiales and (j) Pseudomonas.

39 After an initial linear stage, the rarefaction curve, which depicted the number of new operational taxonomic units per sequence sampled, showed decreasing slope approaching a plateau (Figure 2.2). This finding suggested that the microbi- cal culture was well-characterized by the sequencing and phylogenetic analyses.

18 16 14 12 10 8 6 4 Number of di erent OTUs Number of di erent 2 0 0 10 20 30 40 50 60 70 Number of sequences sampled

FigureFigure 2.2. 2.2. RarefactionRarefaction curvecurve constructedconstructed fromfrom thethe 16S16S rRNArRNA genegene sequencessequences ofof clones clones and and isolates isolates from from the the DBT-degrading DBT-degrading mixed mixed microbial microbial culture. culture. Solid Solid line representsline represents number number of different of diﬀerent operational operational taxonomic taxonomic units units(OTUs) (OTUs) observed per numberobserved of sequencesper number sampled. of sequences Dashed sampled. lines represent Dashed 95%lines upperrepresent and 95%lower con- fidenceupper andbounds. lower conﬁdence bounds.

Based on taxonomic characterization of sequences from the clone library and isolated strains, the DBT-degrading enrichment culture was comprised of members from

40 five major taxonomic bacterial groups, including the Firmicutes, Flavobacteriaceae, Planctomycetaceae, Alphaproteobacteria and Gammaproteobacteria (Figure 2.1). The culture included some sequences similar to organisms known to degrade DBT and/ or other PAHs, including Pseudomonas stutzeri (Monticello et al., 1985; Hirano et al., 2004; Lalucat et al., 2006), Kordiimonas gwanyangensis (Kwon et al., 2005), and also an uncultured Rhodospirillaceae-like species (GenBank AY18695) from deep sea sediment associated with PAH-degradation. Two isolates were identified Bacillusas , some species of which have been found to degrade PAHs (Kazunga and Aitken, 2000). For the qPCR assays, the Firmicutes, Flavobacteriaceae and Planctomycetaceae were represented with one primer set each (Figure 2. 1, Table 2.1). Alphaproteobacteria were represented with five primer sets targeting Rhizobiales-like sequences, Rhodospirillaceae-like sequences, Azospirillum-like sequences, Kordiimonas, and other unclassified Alphaproteobacteria. Gammaproteobacteria were represented by two primer sets, one for Pseudomonas and one for Chromatiales.

2.3.2. DBT degradation, pH and microbial growth

Regardless of whether pH control was included, limited DBT degradation occurred during the first 2 days (Figure 2.3a). After this time, total DBT decreased more or less steadily throughout the experiment under pH control, while under no pH control DBT decreased from 2 to 6 days after which time no further degradation was observed. Under controlled pH, total DBT concentration was 0.57±0.04 mM by day 32 (including solid and aqueous DBT), representing a 91% reduction of the initial DBT added. Only 36% of initial DBT was transformed by day 20 when pH was not controlled. Total DBT was not significantly different between the pH treatments through 16 days, after which time total DBT was significantly lower (p<0.05) under

41 controlled pH. Total DBT in uninoculated controls did not significantly change over the course of the experiments and were not significantly different between pH treatments. None of the isolates alone or in combination were able to grow on DBT as a sole carbon source and they were not able to reduce total DBT concentrations below that of uninoculated controls in pure culture experiments (data not shown). This finding suggests that DBT degradation in the mixed culture was at least partly reliant on taxa that were not cultured by the cultivation method employed in this study.

42 without pH control, uninoculated without pH control, inoculated with pH control, uninoculated a. with pH control, inoculated 8 7 6 5 4 3 2 Total DBT (mM) 1 0 0 4 8 121620 242832 Day

b. 8.0

6.5

Final pH 5.0

3.5 0 4 8 1216 2024 2832 Day c. 2.5 2.0 1.5 1.0 0.5 Aqueous Aqueous DBT (mM) 0 0 4 8 121620 242832 Day

FigureFigure 2.3. Total2.3. DBTTotal (a), DBT ﬁnal (a), pH final (b ), pHand (b aqueous ), and aqueous DBT (c) DBTin inoculated (c) in inoculated and uninoculated and uninocu - (control)lated ﬂasks (control) during flasks DBT duringdegradation DBT degradation with and without with and pH withoutcontrol. pH control.

43 In the experiment without pH control, the culture pH dropped sharply during the first 10 days from pH 7.56±0.02 to 4.22±0.02 (Figure 2.2b), and remained relatively constant thereafter. In the controlled pH experiment, pH was readjusted every 2 days to 7.50±0.10, and the average measured pH before adjustment reading was 6.72±0.35. Under controlled pH, no aqueous DBT was observed in inoculated flasks beyond day 0 (Figure 2.3c), indicating that the rate of initial DBT transformation was greater than DBT dissolution throughout the experiment, and that DBT dissolution may have limited the bacterial growth rate. Without pH control, aqueous DBT increased sharply after 6 days, reaching 2.04±0.09 µM by the end of the experiment. The timing of this (~6 days) approximated that of the cessation of DBT degradation (Figure 2.3b) and pH drop (Figure 2.3a), suggesting that the pH drop contributed to the halt in degradation. Aqueous DBT in uninoculated flasks averaged 1.64±0.15 µM across both experiments, and this was similar to the solubility of 1.1 µM reported for DBT in pure water at room temperature (Lassen and Carlsen, 1999).

Total protein, a measurement of bacterial growth, increased most rapidly during the first 10 days of the experiment without pH control, reached a plateau between 306-

340 mg L-1 until 18 days, and then increased to 470±28 mg -1L at 20 days (Figure 2.4a).

) 600

-1 with pH control 500 without pH control 400 300 200

Total Protein (mg L 100 0 0 4 8 12 16 20 24 28 32 Day b. 6 x 109 5 x 109 )

-1 4 x 109 3 x 109

(copies L 2 x 109 1 x 109 Total 16S rRNA gene 0 0 4 8 12 16 20 24 28 32 Day

FigureFigure 2.4. 2.4. Total protein (a)(a) andand totaltotal 16S16S rRNArRNA genegene copiescopies (b)(b) inin inoculatedinoculated and controland control (non-inoculated) (non-inoculated) flasks ﬂasksduring during DBT degradationDBT degradation with andwith andwithout without pH control. TotalpH control.16S rRNA Total gene 16S copies rRNA are gene averages copies of are values averages calculated of values from calculated 10 standard from curves used10 standardin qPCR. curves Each standard used in qPCR.curve included Each standard a template curve from included one of a thetemplate 10 taxonomic groupsfrom onestudied. of the 10 taxonomic groups studied.

A similar trend was observed in total 16S rRNA gene copies measured with qPCR using the universal primer set and expressed as an average of copy numbers calculated from the standard curves of all group-specific templates although the increase in gene copies between days 16 and 20 was not statistically significant (Figure 2.4b). Total 16S

45 rRNA gene copy numbers was expressed in this manner based on findings in Chapter 4 that demonstrated this approach to adequately quantify total 16S rRNA gene copies in artificial communities of known composition. With pH control, both total protein and total 16S rRNA gene copies increased steadily throughout the entire experiment, reaching 446±53 mg protein L-1 and 3.5x109±1.3x109 copies L-1 by day 32 (Figure 2.4b). De- spite the greater loss of total DBT observed in the pH controlled experiment, both total protein and 16S rRNA gene copies were lower than values observed when pH was not controlled. Slight differences between trends in total protein and 16S rRNA gene copies may reflect differences in the ratios of these components in the different bacterial populations in the culture, or they could be the result of changes in metabolic activities. No growth was observed in experiments involving isolate growth on DBT (data not shown).

2.3.3. Population dynamics.

Bacterial population compositions were dynamic during DBT degradation and differed with pH treatment (Figures 2.5 and 2.6). Overall, greater diversity was observed when pH was not controlled. However, cultures under both pH conditions were clearly dominated by Rhizobiales-like bacteria, Flavobacteriaceae and Chromatiales, together comprising 70-93% (with pH control) and 68-95% (without pH control) of the average total 16S rRNA gene copies L-1 measured with the universal primer presented above. Regardless of pH control, Firmicutes 16S rRNA gene copy numbers were below detection, indicating that this group was present only in trace numbers despite isolation of Firmicutes species by agar plating. Under controlled pH, Azospirillum-like and Plancto- mycetaceae were also below detection in the pH controlled cultures. All other bacterial groups were minor components of the cultures. The sums of copy numbers of all bacterial groups determined with group-specific primers 72-95% and 87-104% of average total

46 16S rRNA gene copy numbers determined with the universal primer for experiments with and without pH control, respectively, which indicates that the group-specific qPCR primers effectively captured most of the microbial community.

with pH control without pH control

2.5 x 109 Chromatiales 2.5 x 109 Chromatiales )

Flavobacteriaceae ) Flavobacteriaceae -1 9 9 2.0 x 10 Rhizobiales-like -1 2.0 x 10 Rhizobiales-like 1.5 x 109 1.5 x 109 1.0 x 109 1.0 x 109 (copies L 9 (copies L 16S rRNA gene 0.5 x 10 9 16S rRNA gene 0.5 x 10 0 0 0 4 8 12 16 20 24 28 32 0 4 8 12 16 20 24 28 32 Day Day

2.5 x 108 Pseudomonas 2.5 x 108 ) 8 Rhodospirillaceae-like ) 8 -1 2.0 x 10 2.0 x 10 -1 1.5 x 108 1.5 x 108 1.0 x 108 8 Pseudomonas 1.0 x 10 Rhodospirillaceae- (copies (copies L 0.5 x 108 (copies L 0.5 x 108 like 16S rRNA gene

16S rRNA gene Azospirillum-like 0 0 0 4 8 12 16 20 24 28 32 0 4 8 12 16 20 24 28 32 Day Day

6.0 x 106 Other Alphaproteobacteria 1.5 x 108 Other Alphaproteobacteria Kordiimonas Kordiimonas ) ) Planctomycetaceae -1 6 4.0 x 10 -1 1.0 x 108

2.0 x 106 0.5 x 108 (copies L (copies L 16S rRNA gene 0 16S rRNA gene 0 0 4 8 12 16 20 24 28 32 0 4 8 12 16 20 24 28 32 Day Day

Figure 2.5. Absolute abundance of group-speciﬁc 16S rRNA gene copies Figure 2.5. Absolute abundance of group-specific 16S rRNA gene copies determined determined by qPCR during DBT degradation with and without pH control. by qPCR during DBT degradation with and without pH control. Firmicutes was below qPCR detectionFirmicutes regardless was below of pH qPCR control, detection while regardlessAzospirillum-like of pH control,and Planctomycetaceae while were belowAzospirillum detection-like only and in thePlanctomycetaceae experiment with were pH control. below detection only in the experiment with pH control.

47 a. 1.0

0.8 Other Alphaproteobacteria Planctomycetaceae Kordiimonas 0.6 Azospirillum-like Pseudomonas 0.4 Rhodospirillaceae-like Rhizobiales-like Chromatiales

Relative copy numbers 0.2 Flavobacteriaceae

0.0 0 4 6 10 16 20 Day b.

1.0

0.8

0.6

0.4

0.2 Relative copy numbers

0.0 0 4 6 10 16 20 24 32 Day

Figure 2.6. Group-specific 16S rRNA gene copies determined by qPCR during FigureDBT 2.6. degradation Group-specific (a) without 16S rRNApH control gene andcopies (b) determinedwith pH control, by qPCR expressed during asDBT a deg- radationpercent (a) of without total 16S pH rRNA control gene and copies (b) withquantified pH control, using expressed universal asprimers a percent given of total 16S inrRNA Table gene 2.1. copies Total 16Squatnified rRNA gene using copies universal are presented primers givenas averages in Table of 2.1. values Total 16S rRNAcalculated gene copies from are standard presented curves as averages for each group-specificof values calculated template. from standard curves for each group-specific template.

48 When pH was not controlled, most bacterial groups, with the notable exceptions of the Rhizobiales-like bacteria, Pseudomonas and Planctomycetaceae, showed detectable growth from the start of the study and reached maximum copy numbers at the end of the experiment (Figure 2.5). In contrast, Rhizobiales-like bacteria were the most abundant group through day 10 reaching 1.0 x 109 16S rRNA gene copies L-1, and steadily declined over the remainder of the experiment (Figure 2.6). Similarly, Planctomyc- etaceae and Pseudomonas reached maximum abundances at 16 days and then clearly declined. The sharp transition from growth to decline for these groups suggests that cultural conditions became unfavorable for these groups, possibly due to the decline in pH, presence of toxic DBT metabolites in the culture or competition from other groups. After an initial lag phase of about 6 days, theChromatiales exhibited rapid growth up to16 days when it was the most dominant group in the culture (Figure 2.6). The Flavobacte- riaceae showed similar trends to the Chromatiales through day 10, after which time this group appeared to reach a somewhat stationary growth phase.

Under pH controlled conditions, culture composition was also strongly dominated by the Flavobacteriaceae and Chromatiales than in pH-uncontrolled conditions (Figures 2.5 and 2.6), and the Rhizobiales-like bacteria were third most abundant overall. With the exception of the Rhizobiales-like bacteria, 16S rRNA gene copy numbers of all other groups were consistently one or more orders of magnitude below those of Flavobacteriaceae or Chromatiales. Abundances of bacterial populations at day 0 under pH controlled conditions differed from those at day 0 in the experiment without pH control, indicting that the culture changed during adaptation to pH-controlled conditions. A consistent trend with and without pH control was the initial dominance of Flavobacteriaceae, followed by dominance of Chromatiales by day 16. The Chromatiales group was one of the least affected by pH conditions based on similar growth trends with and without pH control. Growth of Rhizobiales-like bacteria was much lower when

49 pH was controlled, increasing slowly until day 20, exhibiting a rapid increase to 3.2 x 108

16S rRNA gene copies L-1 at day 24, and rapidly declining thereafter. Abundances of 16s rRNA gene copies of the remaining detectable but non-dominant bacterial groups were generally reduced under pH controlled treatment compared to no pH control. The Kor- diimonas group was unique in that it demonstrated two apparent growth cycles peaking at 4 and 24 days, an effect not observed without pH control. The combined results from both pH treatments suggest that the Flavobacteriaceae and the Chromatiales are among the most important components of the DBT degrading culture. Rhizobiales-like bacteria were generally the third most abundant, and their presence was increased when pH was not controlled.

2.4. Di s c u s s i o n

Degradation of DBT by the enrichment culture in this study was affected by pH treatment. When pH was maintained near 7.5, the culture was able to degrade nearly all initial DBT (91%) within 32 days, however DBT degradation was significantly impaired after only 6 days when pH was not controlled. The tendency for pH to decrease under both controlled and uncontrolled pH conditions was consistent with observations that several steps in the pathway of DBT degradation are acidifying (Kodama et al., 1973), which is also true for degradation pathways of other PAHs. The trends observed for pH in these experiments are relevant for buffered systems such as seawater, and for closed- systems such as bioreactors, and do not necessarily represent what might happen in an open system, such as the tidal estuary from which the enrichment culture was derived. Cessation of DBT degradation coinciding with the pH drop to approximately 4.3 implies that pH may have impaired bacterial growth in this culture and/or degradation-related metabolic functions. However, growth beyond the time when loss of the parent com-

50 pound DBT ceased (i.e., >6 days; Figures 2.2a and 2.3) suggests that microbes may have continued to consume some degradation products.

The lower bacterial growth when pH was controlled, compared to growth without pH control, seems contradictory to the effect pH control had on increasing DBT transformation. Because DBT was the only carbon source supplied, this result suggests that either the protein and 16s rRNA gene yields were higher when pH was not controlled, or degradation products were consumed to a greater extent, or formed to a lesser extent, when pH was not controlled. Evaluation of the trends of potential metabolites monitored by GC/MS during degradation, explored in Chapter 3, indicated generally greater concentrations of metabolites when pH was controlled, supporting the second hypothesis above.

Phylogenetic analysis of 16S rRNA gene sequences from clones and isolated strains revealed a diverse community, including members from five major taxonomic groups: Firmicutes, Flavobacteriaceae, Planctomycetaceae, Alphaproteobacteria and Gammaproteobacteria. This diversity is consistent with that observed in other enrichment cultures growing on PAHs (Duarte et al., 2001), although the distribution of observed taxa was not identical to that of other PAH-degrading enrichment cultures. The community examined in this study was considerably less complex than communities observed at PAH-contaminated sites (e.g., Gray and Herwig, 1996; Piza et al., 2004; Single- ton et al., 2006), which is not surprising given that the culturing conditions were highly restrictive and limited to organisms that could tolerate and degrade DBT and its degradation products. Although the culture included sequences similar to known PAH degraders (e.g., P. stutzeri: Monticello et al., 1985: Hirano et al., 2004), none of these were dominant in our culture. No isolates obtained from this culture were able to degrade DBT either alone or in combination with other isolates (data not shown), suggesting that these

51 isolates (including P. stutzeri along with relatives of other known degraders) either could not perform initial DBT transformation steps, that DBT degrading functionality was lost during the isolation process or that a microbial consortium was required for DBT degradation. The bacterial composition of the cultures within each pH treatment was largely consistent in the replicate cultures, but varied significantly between pH treatments, with greater species diversity associated with no pH control. Absolute abundances of several groups, including Azospirillum-like, Kordiimonas, Other Alphaproteobacteria, Plancto- mycetaceae, Pseudomonas, Rhizobiales-like bacteria and Rhodospirillaceae-like bacteria were greatly decreased when pH was maintained at 7.5. Based on relative abundances (i.e., group-specific 16S rRNA gene copy numbers normalized to total 16S rRNA gene copy numbers), the qPCR primers used in this study were able to capture most of the bacterial community, which demonstrates that qPCR can be used successfully to monitor population dynamics, particularly in restricted communities such the DBT-degrading culture.

It is difficult to determine the specific roles of all taxonomic groups in the enrichment culture without information on functional genes. Because DBT was supplied as a sole carbon source, it is likely that the groups exhibiting the most growth (e.g., the Fla- vobacteriaceae, Chromatiales and the Rhizobiales-like bacteria) played important roles in the direct degradation of DBT and/or its metabolites. On the other hand, the Firmicutes, which were identified in phylogenetic analyses but not detectable by qPCR during DBT degradation, were likely present because of their spore-forming ability that allows them to persist through unfavorable conditions. Growth trends and shifts in culture composition provided clues to the relative roles bacterial groups may have had in DBT degradation. For example, it is plausible that groups exhibiting their most rapid growth early in the experiment were involved in DBT transformation steps earlier in the degradation pathway while those groups with their most rapid growth later in the experiments were

52 consuming intermediates formed later in the degradation pathway. Of the three most abundant bacterial groups, the Flavobacteriaceae and the Rhizobiales-like bacteria were most likely to have participated in early DBT transformation steps in the experiments with and without pH control, respectively, by this rationale. Regardless of pH control, the Chromatiales, which exhibited their most rapid growth after 6-10 days, seem more likely to have been involved in later steps in the DBT degradation pathway. It should be noted, however, that non-dominant groups are not necessarily less important to DBT degradation simply because of their low abundance.

Previous research supports the DBT- and/or PAH-degrading potential of some of the bacterial groups observed in this study. The Flavobacteriaceae are chemoheterotro- phs common to many marine habitats, and are known for their ability to degrade a variety of biopolymers and high molecular weight organic material (Kirchman, 2002). Flavobacteriaceae have not previously been specifically linked to DBT degradation, but members of the Flavobacteriaceae have been implicated in the degradation of other contaminants and related aromatic compounds including petroleum oil (Sanchez et al., 2005), various PAHs (Barnsley, 1988; Vinas et al., 2005) as well as smaller aromatics such as phenol (Whiteley and Bailey, 2000). Little research has followed bacterial dynamics of Flavobacteriaceae during degradation. In a study by Vinas et al. (2005), the Cytophaga- Flexibacter-Bacteroides group, of which the Flavobacteriaceae are a part, comprised a significant portion of DGGE bands for a PAH-community in creosote-contaminated soil.

The presence of Alphaproteobacteria in the culture was not surprising since this phylum is ecologically diverse, metabolically versatile and contains many aerobic species. Previous research identified Azospirillum sp. (Alphaproteobacteria) in a PAH-degrading bacterial community (Vinas et al., 2005), and a strain of Azospirillum brasilense has been shown to degrade crude oil (Muratova et al., 2005). Rhizobiales have been found

53 at PAH-contaminated sites (Vinas et al., 2005), and a Rhizobium meliloti strain has been shown to degrade DBT (Frassinetti et al., 1998).

The discovery of Planctomycetes in the enrichment culture was not surprising given that this phylum is common in seawater and marine sediments (Shu and Jiao, 2008). While Planctomycetes have been observed in oil-contaminated marine sediments (Abed et al., 2007) and in a consortium degrading 2-bromophenol (Knight et al., 1999), none have been directly linked to PAH degradation.

The Gammaproteobacteria are common in marine habitats (Cho and Giovanonni, 2004), accounting for their presence in the enrichment culture examined in this study, and several taxa have been associated with PAH degradation. Numerous Pseudomonas strains have shown abilities to completely or incompletely mineralize some PAHs, including DBT (Kodama et al., 1973; Kropp et al., 1997). The finding that Chromatiales may play a central role in DBT degradation is new, although they were found to be abundant in petroleum refining waste (Cooper, 1963). Because the Chromatiales are often metabolically flexible and able to grow heterotrophically and/or autotrophically (Imhoff, 2003), they may have unrealized potential for contaminant degradation. Indeed, the flexibility of the Chromatiales was demonstrated in this study in their adaptability to large differences in culture pH. To the best of our knowledge, this is the first reported association of a member of the Chromatiales with DBT degradation. The finding that culture isolates related to known DBT-degraders (e.g., Pseudomonas, Rhizobiales) could not degrade DBT alone or in combination with other isolates suggests that the isolated strains either could not perform initial DBT degradation steps or had lost degrading functions during the isolation process.

54 2.5. Co n c l u s i o n

This is the first study to examine the degradation of DBT as a sole carbon source by an enrichment culture combining chemical analysis along with assessment of microbial population dynamics using qPCR to characterize DBT degradation. Composition of bacterial groups identified using qPCR varied considerably with and without pH control, however, the culture was dominated by Flavobacteriaceae and Chromatiales under both pH conditions. These groups may therefore play important roles in DBT degradation, which has not been previously reported. DBT degradation by this culture was impaired when pH was not controlled, but resulted in a 91% reduction of total DBT when pH was maintained at pH 7.5. Based on these findings alone, a remediation goal of contaminant reduction would require steps to forestall drops in culture pH.

55 Chapter 3. Products of DBT degradation by a Mixed Microbial Community

3.1. In t r o d u c t i o n

Condensed thiophenes, including dibenzothiophene (DBT), are heterocyclic polycyclic aromatic hydrocarbons (PAHs) and represent an often environmentally recalcitrant component of petroleum and petroleum-based materials such as creosote. Microbial degradation of DBT and other PAHs plays a primary role in the environmental fate of these compounds. In terms of remediation of environmental contamination from DBT and other PAHs, key objectives for microbial degradation are mineralization of the contaminants and subsequent reduction of associated risk. However, biodegradation of these compounds can produce transient or persistent degradation products, many of which are poorly characterized, that may impede the degradation process, pose a hazard themselves, and ultimately affect the success of remediation. Evidence that biodegradation products can increase toxicity and/or hazard has been demonstrated in several studies (Belkin et al., 1994; Brooks et al., 1998; Ahtiainen et al., 2002; Lundstedt et al., 2003). Fundamental information necessary to addressing potential problems caused by degradation products includes their identification, an understanding of how they are formed, and some characterization of their chemical and toxicological properties.

Previous research has explored bacterial degradation pathways of DBT, a model condensed thiophene, and has identified several DBT degradation products (Kodama et al., 1970; Kodama et al., 1973; Laborde and Gibson, 1977; Kropp et al., 1997; Bressler and Fedorak, 2001a; b). Although this work has provided valuable information, most of it has focused on bacterial isolates, and little of it has included a toxicological assessment of the products. Many bacterial species cannot be isolated in pure culture, and

56 so their degradative capabilities remain unknown. Additionally, biodegradation in the environment usually involves a microbial community, whose biodegradation pathway dynamics may be more complex than those of a bacterial isolate. These issues can only be addressed by studying DBT degradation by microbial communities, which have thus far received little attention.

Known bacterial pathways of aerobic DBT degradation (Figure 3. 1) include lateral dioxygenation (Kodama et al., 1973; Bressler and Fedorak, 2000; Seo et al., 2006), angular dioxygenation (van Afferden et al., 1993), and biodesulfurization (Gray et al., 1996; Bressler and Fedorak, 2000). Lateral dioxygenation, a pathway common among PAHs, involves ortho dioxygenation of an aromatic ring, followed by ring cleavage and breakdown of the ring fragments. Degradation products include hydroxylated compounds, carboxylic acids, ketones and quinones, and aldehydes (Kodama et al., 1973; Bressler et al., 1998; Bressler and Fedorak, 2000; Seo et al., 2006). Angular dioxygenation begins with two oxygenations of the sulfur atom, followed by aromatic ring dioxygenation at the carbons adjacent to the sulfur atom, resulting in cleavage of the C-S bond (Bressler and Fedorak, 2000) (Figure 3.1).

57 O O 6 ) 5 ) O S H H O 3-hydroxybenzothiophene ( O 2-hydroxybenzothiophene ( (H) O (H) O (H) O O benzothieno[2,3-c] O furan-1,3-dione ( 18 ) furan-1,3-dione S S O O S S * (H) O O 17 ) O 11 ) (H) O O O O O (H) O S O O H (H) H H S O S O O O (H) * S benzothiophene-2,3- dicarboxylic acid ( dicarboxylic (H) 7 ) S O H carboxyethenylbenzothiophene acids carboxylic O formylbenzothiophene formylbenzothiophene acids carboxylic ) H ( O O 2,3-dihydroxybenzothiophene ( 2,3-dihydroxybenzothiophene H S H O O O thiosalicylic acid ( O H O ) O hydroxybenzothiophenyl acids -oxobutenoic )

O O O H Lateral dioxygenation Lateral H

( H ( tautomerization

O O O H S H H O O S S

O S O O H glyoxylate S S H S 2-mercaptophenyl dioxydibenzothiophenes 9 ) 14 ) with O H with acidification O H O acidification O 2-one ( O H hydroxybenzothiophene hydroxybenzothiophene ( 12 ) carbaldehydes O O O O ) O S S S H S S ( 19, 20 3-hydroxybenzothiophen- benzothiophene-2,3-dione ( benzothienopyranones dihydrodioxydibenzothiophenes * biphenyl O O 1 ) H H O 7 8 S 6 2-sulfinic acid 2-hydroxybiphenyl O ) ) 2'-hydroxybiphenyl- 9 Biodesulfurization H H benzoic acid ( benzoic ( ( O ) O S H ( O 4a O H 1 O 4 H O 2 3 O DBT sulfone ( 21 ) sulfone DBT 2',3'-dihydroxybiphenyl- 2-sulfinic acid DBT sulfoxide ( 22 ) sulfoxide DBT Figure 3.1. Known pathways of bacterial aerobic degradation of DBT. Red products were observed in this research. research. in this observed were Red products of DBT. degradation aerobic of bacterial pathways 3.1. Known Figure O H ) S S O O ) O O H 15 ( S O O ) S H ( DBT ( DBT O 2,4-dienoic acid Angular dioxygenation 6(2'-sulfinophenyl)-6-oxo- Figure 3.1. Known pathways of bacterial aerobic degradation of DBT. Red products were observed in this research. Starred (*) were detected as observed detected Redwere were (*) in research.products this Starred of bacterial of degradation DBT. aerobic Figure 3.1. pathways Known hydrogens parentheses in at with culture pH deprotonated indicated likely with diazomethane. Functional groups derivatization after esters methyl et al., based 1996;are 2001a,b; onet al., Bressler Kodama and 1973; Gray Fedorak, Seo et al.,("(H)"). 2006;1993. and Afferden Pathways van 3.1. entries to in Table inNumbers bold italics refer 6-(2-hydroxyphenyl)-hexa- Figure 3.1. Figure at deprotonated likely groups Functional with diazomethane. derivatization after esters as methyl detected (*) were Starred al., et 2001a,b; Gray and Fedorak, based on Bressler are (“(H)”). Pathways in parentheses with hydrogens pH indicated culture Table 3.1. in to entries refer in bold italics et al., 1993. Numbers Afferden al., 2006; and van al., 1973; Seo et et 1996; Kodama

58 Cleavage and metabolism of the aromatic ring then follows. Common metabolites of this pathway include DBT sulfoxide and sulfone, along with sulfinic acids (van Afferden et al., 1993). Angular dioxygenation can occur with other PAHs depending on their structure, including DBT analogs fluorene and dibenzofuran (Bressler and Fedorak, 2000). Biodesulfurization is unique to thiophene PAHs. This pathway branches from that of angular dioxygenation after the initial C-S bond cleavage, at which point the second C-S bond is cleaved and sulfite released leaving 2-hydroxybiphenyl, which may or may not be subsequently degraded (Gray et al., 1996). The role of this pathway in natural systems, particularly those where S is not limiting, is unclear, however, in engineered systems it is commonly explored as part of petroleum refining processes. In addition to biotic reactions, some DBT degradation products (thiosalicylic acid (7), 3-hydroxy-1-benzothiophene-2-carbaldehyde (12) (Fanning et al., 1972; Bressler and Fedorak, 2001) undergo abiotic reactions, particularly dimerizations (Structure numbers 23, 24, 25, 26, 28, 29; Figure 3.2). For most of the DBT degradation products that have been identified, the chemical and toxicological characteristics are largely unexplored, partly because many are not commercially available, easily synthesized, or stable over time (e.g., weeks to months) in solid form or in solution at ambient conditions, as is the case for 3-hydroxybenzothiophene-2-carbaldehyde (Bressler and Fedorak, 2001a). Additionally, many of these products have not been monitored during the course of degradation, especially in mixed microbial communities.

59 S S O S O O + O H O H S O 3-hydroxy-1-benzothiophene- (12) thioindigo (25) 2-carbaldehyde (12)

O H O S S H S H S + O O O H O dithiosalicylic acid (26) * O O O (H) O (H) O thiosalicylic acid (7) * (7) S

S S S dithiosalicylides (23, 24) O

SH O S H O(H) O O + O S S O (H)O H O O O (H) 2-mercaptophenylglyoxylate (7) * 2-{[2-(carboxycarbonyl)phenyl]disulfanyl}benzoic acid (28)

SH O SH O O O O(H) O(H) O(H) + S S (H)O O O O O

*2,2'-(disulfanediyldibenzene-2,1-diyl)bis(oxoacetic acid) (29)

Figure 3.2. Reactions forming dimers from bacterial DBT aerobic degradation products. Red products were observedFigure in this 3.2. research. Reactions Starred (*)forming were detected dimers asfrom methyl bacterial esters afterDBT aerobicderivatization degradation with diazomethane. prod- Functional groups likely deprotonated at culture pH indicated with hydrogens in parentheses ("(H)"). ucts. Red products were observed in this research. Starred (*) were detected as methyl Reactions are adapted from Bressler and Fedorak, 2001b, and Baker et al., 1952. Note: presence of 2-mercaptophenylglyoxylateesters after derivatization is indicated bywith detection diazomethane. of benzothiophene-2,3-dione Functional groups (9 ),likely which formsdeprotonated upon at acidiﬁcation.culture NumberspH indicated in bold withitalics hydrogens refer to entries in parentheses in Table 3.1. (“(H)”). Reactions are adapted from Bressler and Fedorak, 2001b, and Baker et al., 1952. Note: presence of 2-mercaptophenylglyoxylate is indicated by detection of benzothiophene-2,3-dione (9), which forms upon acidification. Numbers in bold italics refer to entries in Table 3.1.

60 The aim of this study was to address how DBT is degraded by a mixed microbial community, identify product formation and evaluate overall toxicity. The study included two sequential experiments, the first of which explored DBT degradation by the culture without controlling pH. Under this treatment, culture pH dropped during degradation and appeared to impair the degradation process (as will be discussed below), prompt- ing a second study with controlled pH. This research is a companion to a study on the microbial population dynamics within the community (Chapter 2), and builds on the hypotheses that (1) degradation of DBT by a mixed microbial culture follows a more complex pathway and produces a wider array of degradation products than has been observed with single bacterial isolates in pure culture, and (2) some degradation products may be more toxic than DBT itself, which could impair further DBT degradation and, in contaminated systems, interfere with remediation goals. Specific objectives of this study included:

1. Identify DBT degradation products produced by the microbial culture.

2. Monitor and compare trends of primary DBT degradation products during degradation by a mixed microbial culture under conditions with and without pH control.

3. Evaluate toxicity during the course of DBT degradation with and without pH control using a bioluminescent bacterial assay, and compare toxicity changes during degradation to trends in degradation products to identify potentially toxic products.

The findings of this research provides insight into the complexity of degradation processes within a mixed microbial community, along with a dynamic view of the toxicity associated with mixtures of degradation products, which more closely approximates degradation in an environmental system than do investigations using bacterial isolates in pure culture. With specific regard to toxicity, evaluation of the toxicity of a complex

61 mixture of products formed during the degradation of DBT may more closely represent toxicity during degradation in the environment or in a controlled bioremediation process than would independent evaluation of the toxicity of specific degradation products alone.

3.2. Ma t e r i a l s a n d m e t h o d s

3.2.1. Source of enrichment culture

A microbial enrichment culture growing on dibenzothiophene (DBT) as a sole carbon source was established from sediment from a PAH-contaminated brackish tidal inlet along the southern branch of the Elizabeth River, Portsmouth, Virginia, adjacent to the Atlantic Woods Industries, Inc., National Priorities List Site, as described in Chapter 2. The culture was maintained as described in Chapter 2: briefly, culture flasks were shaken at room temperature in the dark in artificial seawater media (22.22 g-1 L Instant

-1 -1 -1 OceanTM) at pH 7.5 supplemented with 1 g L NH4NO3, 0.2 g L K2HPO4 and 0.05 g L

FeCl3•6H2O (adapted from Chang et al., 2000 and Kasai et al., 2002).

3.2.2. DBT degradation studies

For degradation studies, 0.152 mmoles DBT (Sigma-Aldrich, St. Louis, MO) in

200 µL acetone was added to sterile 50 mL Erlenmeyer flasks and allowed to dry. Mass of DBT added to the flasks was confirmed by HPLC analysis as described in Chapter 2. Twenty-five mL sterile artificial seawater media (described above) was added for an initial total DBT concentration of 6.08 mM, which was above the solubility limit for DBT in water (1.1 µM: (Lassen and Carlsen, 1999). After media addition, flasks were inocu-

62 lated with 100 µL of a stock enrichment culture (0.3 optical density at 600 nm). Control flasks were prepared in a similar manner but without inoculum. Flasks were mixed on an orbital shaker in the dark. Sampling occurred every 2 days for the first 20 days in experiments with and without pH control, and every 4 days between 20 and 32 days in the experiment with pH control. For the experiment with pH control, pH adjustments on all remaining flasks were made on the same schedule as sampling using NaOH to main- tain pH near 7.55, the pH of pore water of the source site. Sampling was not continued beyond 20 days in the experiment without pH control (final pH approximately 4.2) because no significant changes were observed in total DBT concentration. Each sampling included sacrificing 6 control and 6 inoculated flasks (12 flasks per sampling, 6 flasks for DBT analysis and 6 flasks for toxicity assay), as described below, requiring a total of 168 flasks for the experiment with pH control and 132 flasks for the experiment without pH control. At each sampling timepoint, 3 control and 3 inoculated flasks were extracted for total DBT, which is further discussed in Chapter 2. Contents from the additional 3 control and 3 inoculated flasks were centrifuged for 20 min at 5000 x g, and the supernatant was filtered through a 0.2 µm polycarbonate membrane and analyzed for toxicity (described below). 15 mL of the supernatant was acidified to pH 2 with 6 M HCl to maximize transfer of acidic products into the organic phase, and extracted for DBT and its degradation products three times with dichloromethane (DCM) on and end-over-end shaker in the dark.

3.2.3. Sample preparation and analysis by GC/MS

For each sample, the DCM fractions of the 3 extracts were combined and con- centrated to 200 µL using rapid evaporation (Turbo Vap, Zymark Inc.) followed by gentle evaporation under N2. Half (100 µL) of the extract was reserved for derivatization with

63 diazomethane and subsequent analysis of degradation products, which is the focus of Chapter 3. To the remaining 100 µL of the extract, 10 µL of 200 µM 2-naphthol (Sigma- Aldrich) in dichloromethane (DCM) was added as an internal standard, and extracts were analyzed for aqueous DBT, along with DBT degradation products (Chapter 3), by GC/MS (Agilent 6890 in electron impact (EI) mode using splitless injection (300°C). Separation of analytes was achieved on a DB-XLB column (30 m, 250 µm nominal diameter, 0.25 µm film thickness; J&W Scientific) using an oven temperature program (with a thermal gradient (100°C for 2 min, increase to 210°C over 15.7 min, hold at 210°C for 1 min, increase to 315°C over 4.2 min, hold at 315°C for 11 min) under constant pressure at 1 ml min-1 flow. Structures, identification support and references, and identifying ions used in GC/ MS analyses of DBT and DBT degradation products are presented in Table 3.1. Referenc- es to structure numbers in chapter text, tables and figures are presented in bold italics; e.g., “DBT (15).”

64 k -

l a

r a

T o

T h h tr d IS c ss ss IS tc tc e e N

a a

N F l

; ; ; ; a 2006 h Ma Ma Sp

m m d h

, d d d r tr . r r r r T T tc tc a c ss a a a a al a IS IS e

t nd m 72% 97% N N m

nd nd nd

e Ma

Sp h h a : :

a a a uppo t d d t t t T o s s tc tc y y

s s s ss e

a r r a IS c 92% D S c c c 91%

a a

ti N : m m

r r 1994; 1994; : ti ti ti

n / d d

b b , ,

n n n i i y e r r T e e e e L L r

e e h h h c l l h h h IS ary a t 91% 96% u u t t t 1997; r r n a a

tc tc

u N : : , u u u

b e b 1991; a a . a ra ra d d tr tr i i

a a a

c c y y L L e e ć e

al m m o i r r

l l

e e

o o o f t tt tt t a a

t t t i i a a e

r r e n Sp Sp

N N n n R n 2002; tr tr Gal

b b

o i i - n c c , 91% 95% i d d . L L ć

ss ss s o s o s o s i e e

i : : i e n l n l al d d t b

a a a a s r

y y Sp Sp ar ari ari ari t l

Ma Ma r r tr tr

n n e p p p p G

a c c T T ss ss ke r r d e e m n IS IS b b i n i i i Eato N K com com N com com Eato Sp L Sp Ma a L F Ma )

n n i o m ti (

682 308 177 354 707 272 n b 666 183 816 e e t 6 . 9 . 7 . 12 . 12 . 14 . 11 . 14 . 13 . e R Ti m a s n o 7 I

11 3 10 8 10 8

, , , g 10 8 121 10 8 11 5 121 n

i , , , 105 y

141 136 136 f

i , , , t 135, 150 134 150, 144 n 136 e 156 168 164 d I H O H O e H O N O r O O O O u H H t S S S O O c u S S S r t S H H S O ) d r a e e e n n n nd l o e e a i o t d s -

ph ph l o o a i i 2,3 n h h phen e c - r

t t e l e e d l e o o m y t z z o a n n z n n c i aci N

a ( e e lﬁ

i c l b b phen phen d h o s u y y t o o l aci i i x x h

o y t h h s c o o licyli i t h t i r r t o o o o poun ph d d s a e Structures and GC/MS identification parameters of compounds identified extracts of the media of a microbial enrich extracts of the media a compounds identified of parameters and GC/MS identification Structures y y a m io m h h n o h C t 2 - benz benz 3 - 2 - benz benz 2 - e

ur k t * * * a 7 4 3 2 1 8 6 9 5 ruc Pe t S Table 3.1. Table responses of relative products based on degradation abundant most the five (*) indicate Asterisks DBT. degrading culture ment 2-naphthol. standard, of the internal to that ions quantifying

l a

T tr h h c IS tc tc e a a N

; Sp m m h

d r r tc ss a a 91% 97% m nd Ma

: : a uppo d d T t s y y

IS r r D c 96% a a I N

r r : ti 2001a

/ d b b ,

n i i y k e e L L r

h a c l l h a r t r n a a tc 1997; o u

b e a 1998 , tr tr i d r

a . ,

c c L e . e

m l

e e al o f F

al a e t

d Sp Sp t e n R tr 2006

n e c ,

95% n a .

ss ss s o i e

: e er d al

t sed y g Sp ari t

Ma Ma r o ' s

n p e l i a

p T T ss r b o nk IS IS b r i i N com N F B o p Seo L Bressler Ma

) n n i o ti m 3 9 6 5 64 37 ( 32 7 503 65 6 159 n

e e t 21 . 15 . 15 . 17 . 19 . 15 . 17 . 19 . e R Ti m a

s , n o I 12 1 18 5 10 8

134, 120

, , g 13 9 16 1 140 n

i , , , y 104 177, 136 219, 136 150, 162 f

i , , , , , t 178 184 168 n e 250 178 166 166 190 d I H O O O O O e OH r S O H O u O O OH H S t O O c O O u S S S S r S t S S S

, d e d aci

y d c h li e e 2 - aci y n

- d e x l c e o n o a li e b 2 - b y - r x n a ph o phen c o i icar b i e o i d d h n - - phe t h o car t o o i o z 3 - 3 - 2,3 2,3 h - - - - n t l e e e e o c o i b r benz y h e e t t x enz

i d 1 - s o b - phen phen phen y d r e y y

o o o h o l i i i d x x e y y h h h ound Name o o d t t t h h r r l p i t o o o d d a d benz e m y y - b - T r o h h m B i a C 2,3 benz 3 - c benz benz 3 - D d 1,2 e /

* * ur

k t 12 13 16 17 15 10 a 11 14 ruc Pe t S Table 3.1. Continued. Table

er er l l

p l l p ss ss 94% a a

o : tr tr d c c Kr Bre Bre y

e e r ; ; ; a t d d d 1998; r r Sp Sp r r r

, b a a a i ss ss L al

l nd nd nd t a a a a uppo e Ma Ma

t t t s

s s s

T T c D c c c I e IS IS

neti ti ti ti / N N

n n n Sp

; ; e e e e h h c h h h ss t t t n tc tc Frass i u u u e

a a 1981 r

a a a Ma , 1972

1990

e .

m m 2001 b 2001 b ,

, o o o f T

. 1994 . , , t t t al

, IS k k al . al t n R n n

2006;

a a

N t e t r r

al ,

64% 91%

e s o s o s o e o o

e t : :

d d al g k d d e n

y y ari ari ari n t e e h r r i p e c p p p F F e a

1994; p tc k s o

r r d d , o nn o a . b b n n e a i i com com m S com L al Jac F a R e i n a L Kr

) n n i o 182 177 463 153 ti m 4 3 ( 102 042 n 479 06 2

24 . 22 . 22 . e 25 . e

t 21 . 26 . 23 . 25 . 23 . e R 16: 17: 22: Ti m 21: a s n o I 16 8 146 12 0 13 2 17 2 108

, , , g 167 n

i , y 187, 174, 240, 136 184 160 f

i , , , , , , t 334 n e 272 202 200 296 216 204 d I O O ) E S O M (

O S O S e O O r O u O O t S c O u S r S S O O t S O S S S O O O S O S S O

O ) E M ( e n o i d - e d 1,3 e i - x n n o s f ra lfo l u ne s u su o c

c]f n e e d - a n n 3 s e e aci yr e

2 , p c d ph ph o o[

o o i i o en en h h i i licyli licyli t t g i ound Name h h o o t t s a s a p z z o o nd n n i io io m e e h h o o i b b i it it i C h d d benz d d benz t e / ur 20 24 k t

a 22 26 21 18 25 19, 23, ruc Pe t S Table 3.1. Continued. Table

67 t r 2001b

uppo s

M D I 2001b

/ , ,

k k e a a c r r n o o e d d r e e e f F F

e d d R n n a a

Bressler Bressler

) n n i o ti m 9 4 2 8 ( 138 n

e e t 27 . 29 . 26 . e R Ti m a s n o I 18 4 16 7 13 6

, , g n

i ) y 228, 195 195 c f

i , , , ﬁ t ti n n e 284 362 390 e d i I c S

W & J

; ) e O e ss M ) ( e O k n O M c O ( i O th

O m l ﬁ

O O O e m r S . µ S u

: e t e c n S r 25 S u a u r t 0 . h t

c t , S u O r e e O t m ) str e e o e l z M ( m a S i O a sib i d

u d O O

) h l O t a i pla n Me w i (

. n m d o o e ti n n

a li z r m e µ

c vati i r und r e 250 e t s

i , s d

e n

r m l

- o e y ] i 0 l

h y g t (3 aft

n n e i c s n e - ) r y m f e e i m t t ti d u 2,1 )ph s a

l - n t i e d ol y

a e l d c n c

y o S aci o i qu a B

4 b h L ; t o c r t i O x e X i 8 a - o o c z m B (d H s ( y - 5 n bold i s D 1

e a n C

o n )b b i

} : d b 2,2' e o l )

l e n y + t a ound Name y e n w n c c l p h ( M o e t y - ( fa t

l m n e n 2 s k [ o e { n s u m de n C

i i o s i 2 - d d U ph

r separated

s la e und e u / 2005. o ur

c , k t p e T a 28 29 27 alyt m IS n ruc Pe t N A Mol C o

S c a d b

Table 3.1. Continued. Table 68 Molecular ions were confirmed by either negative or positive chemical ionization GC/MS using the conditions listed above for EI. Identification and concentration of DBT and several degradation products were determined using authentic standards: DBT sulfone (22) (Aldrich), benzothiophene-2,3-dione (9) (Ryan Scientific, Mt. Pleas- ant, SC), thiosalicylic acid (7) (Aldrich, detected as a methyl ester after derivatization), dithiosalicylic acid ( 26) (Alfa Aesar, Ward Hill, MA, detected as a dimethyl ester after derivatization), and thioindigo (25) (TCI America, Portland, OR). With the exceptions of two potential degradation products14 ( and 27), all DBT degradation products were identified by comparison to an authentic standard, using spectral libraries (NIST Mass Spec- tral Library, 2005), and/or by comparison to reference spectra from previously published research. Where authentic standards were not available and spectral libraries were used for identification, degradation product spectra showed 91% or greater match to library spectra with the exception of 2-methylsulfinyl phenol (72% match; 4). Concentration of 2,3-dihydroxybenzothiophene (11) was determined semi-quantitatively based on benzothiophene-2,3-dione (9). Amounts of all other products were reported as relative response of peak area for the appropriate quantification ion (see Table 3.1) compared to that of the internal standard 2-naphthol (8).

3.2.4. Toxicity assay and dose-response experiments.

Toxicity was assessed as inhibition of luminescence in the bioluminescent bacterium Vibrio fischeri (also known as Photobacterium phosphoreum), strain NRRL B-11177 (ATCC, Manassas, VA), using a method adapted from McConkey et al. (1997). This assay was selected because of its ease of use and similarity to other toxicity tests that are increasingly used to screen soil and water (e.g., MicrotoxTM: Ocampo-Duque et al., 2008; Bulich et al., 1992), and that use the same or similar bacterial species. Bacteria were

69 grown in Photobacterium broth (Fluka BioChemika, Buchs, Switzerland) at 15°C on an orbital shaker in the dark for three days. Cells were centrifuged for 5 min at 5000 x g, the supernatant was removed and the cells were resuspended in chilled 2% w/v NaCl to an optical density of 0.82-0.86 at 600 nm. This bacterial suspension was added to a polystyrene 48-well plate (0.5 mL per well),the plate was incubated in the dark for 10 min at 15°C, and luminescence was measured using a FLUOStar Optima plate reader (BMG LabTech, Durham, NC). Filtered aqueous supernatant (0.5 mL) collected from the degradation study flasks described above was adjusted to pH 7.5±0.1 with NaOH, added to the wells, incubated for 30 min, and luminescence was measured again. In addition to experimental (non-inoculated) controls, all toxicity assays included a control dosed with artificial seawater media free of DBT. The toxicity of each sample and control was expressed as percent inhibition of luminescence, as previously described (McConkey et al. 1997; Equation 2.1).

The effect of concentration on toxicity toV. fischeri using the assay described above was explored for DBT and selected commercially-available DBT degradation products in the artificial seawater media at pH 7.5 over the following concentration ranges:

DBT (15) 0-1.5 µM; benzoic acid (1) 0-10,000 µM; thiosalicylic acid (7) 0-10,000 µM; benzothiophene-2,3-dione (9) 0-1000 µM; DBT sulfone (21) 0-20 µM; thioindigo (25) 0-10 µM; and dithiosalicylic acid (26) 0-1000 µM. Concentration ranges were selected to include ranges observed in the degradation experiments, and, for DBT (15), DBT sulfone (21), thioindigo (25) were limited by apparent compound solubility limits.

3.2.5. Statistical Analyses

Statistical analyses, including analyses of variance (ANOVAs) and regression, were conducted using JMP 7.0 software (SAS, Inc., 2007).

70 3.3. Re s u l t s

3.3.1. Identification of DBT degradation products

Twenty-seven potential DBT degradation products were observed by GC/MS in the media of the microbial community consuming DBT as a sole carbon source (Table 3.1, Figures 3.3-3.18). In the text, tables and figures below, numbers in bold italics refer to compound structures and chromatographic peaks in Table 3.1 and Figures 3.3-3.18. These products were observed regardless of whether or not pH was maintained at 7.55. Of the observed products, 16 have been previously reported as products from bacterial degradation of DBT via angular dioxygenation in pure cultures (1, 21, 22; Figure 3.1) and lateral dioxygenation (5, 6, 7, 9, 11, 12, 17, 19, 20, 25, 26, 28, 29; Figure 3.1) (Kodama et al., 1970; Kodama et al., 1973; Bohonos et al., 1977; Laborde and Gibson, 1977; Monti- cello et al., 1985; Mormile and Atlas, 1988; Olson et al., 1993; van Afferden et al., 1993; Resnick and Gibson, 1996; Finkel’stein et al., 1997; Kropp et al., 1997; Oldfield et al., 1997; Frassinetti et al., 1998; Lu et al., 1999; Meyer et al., 1999; Bressler and Fedorak, 2001a; b; Seo et al., 2006). Of these, 4 are formed through abiotic dimerization (Figure 3.2). Thioindigo (25) is the dimerization product of 3-hydroxy-1-benzothiophene-2- carbaldehyde (12) (Bressler and Fedorak, 2001a; b). Dithiosalicylic acid (26) is a known dimerization product of thiosalicylic acid (Bressler and Fedorak, 2001a; b). Thiosalicylic acid (7) and 2-mercaptophenylglyoxylate form 2-{[2-(carboxycarbonyl)phenyl]disulfanyl}benzoic acid (28), and 2-mercaptophenylglyoxylate dimerizes with itself to form 2,2’-(dithiodi-2,1-phenylene)bis(oxoacetic acid) (29) (Figure 3. 2) (Bressler and Fedorak, 2001a; b). No products of biodesulfurization (e.g., 2-hydroxybiphenyl) were found.

71 a. 19 )

100 9 ) 6 ) 14 )

80 5 ) benzothiophene-2,3-dione ( benzothiophene-2,3-dione 284 ( 27 )

+ benzothienopyraonone 22.19 min ( benzothienopyraonone

y 60 t i 15 ) 11 ) 3-hydroxybenzothiophene ( 3-hydroxybenzothiophene 18 ) s 20 ) n 21 ) e 8 ) unknown M unknown 22 ) t 3-hydroxybenzothiophen-2-one ( 3-hydroxybenzothiophen-2-one 24 ) 13 ) n 23 ) 2-hydroxybenzothiophene ( 2-hydroxybenzothiophene I

v e 40 a ti 4 ) l 10 ) e R 2 ) dibenzothiophene (DBT) ( (DBT) dibenzothiophene 3 ) 2,3-dihydroxybenzothiophene ( 2,3-dihydroxybenzothiophene dibenzothiophene sulfone ( sulfone dibenzothiophene 20 ( 12 ) 3-hydroxybenzothiophene-2-carbaldehyde dithiosalicylide 25.06 min ( dibenzothiophene sulfoxide ( sulfoxide dibenzothiophene dithiosalicylide 24.12 min ( thioindigo ( 25 ) thioindigo benzothieno[2,3-c]furan-1,3-dione ( benzothieno[2,3-c]furan-1,3-dione 2-naphthol (internal standard) ( standard) (internal 2-naphthol benzothienopyraonone 22.46 min ( benzothienopyraonone benzothiophene-2,3-dicarbaldehyde ( 16 ) benzothiophene-2,3-dicarbaldehyde 1,2-benzodithiol-3-one ( 1,2-benzodithiol-3-one benzothiophene ( benzothiophene 2-methylsulﬁnyl phenol ( 2-methylsulﬁnyl benzisothiazole ( benzisothiazole benzothiophene-3-carboxylic acid ( benzothiophene-3-carboxylic

0 6 11 16 21 26 31 Min b. 100 17 ) 80 y 26 ) t i s n

e 60 t n I 8 ) v e 29 ) 7 ) a ti l e 28 )

R 40 benzoic acid, methyl ester ( 1 ) ester acid, methyl benzoic dithiosalicylic acid, dimethyl ester ( ester dithiosalicylic acid, dimethyl 2-{[2-(carboxycarbonyl)phenyl]disulfanyl}benzoic acid, 2-{[2-(carboxycarbonyl)phenyl]disulfanyl}benzoic ( ester dimethyl benzothiophene-2,3-dicarboxylic acid, dimethyl ester ( ester acid, dimethyl benzothiophene-2,3-dicarboxylic

20 dimethyl2-{[2-2,2’-(disulfanediyldibenzene-2,1- acid) ( diyl)bis(oxoacetic 2-naphthol (internal standard) ( standard) (internal 2-naphthol thiosalicylic acid, methyl ester ( ester thiosalicylic acid, methyl

0 6 11 16 21 26 31 Min Figure 3.3 GC/MS total ion chromatograms of DCM extract, (a) without derivatization, and (b) with derivati- Figurezation 3.3. with diazomethane,GC/MS total of ionmedia chromatograms from a DBT-degrading of microbialDCM extract, enrichment (a) culture without four derivatization,days after andinoculation (b) with and derivatization maintained at pH 7.5.with Separations diazomethane, were achieved of media using afrom DB-XLB a columnDBT-degrading (30 m, 250 µmmicrobial enrichmentnominal diameter, culture 0.25 fourµm ﬁlm days thickness; after J&W inoculation Scientiﬁc). Numbersand maintained in bold italics at refer pH to 7.5. compound Separations structures in Table 3.1. were achieved using a DB-XLB column (30 m, 250 µm nominal diameter, 0.25 µm film thickness; J&W Scientific). Numbers in bold italics refer to entries in Table 3.1.

72 a.

100 benzoic acid, methyl ester (1) [M-CH3O] 105 90 [M-C2H3O2] (100) O 80 77 (69) 70 O y t i

s 60 n e t [M+]

n 50 I 136 e

v 40 (33) ti a l

e 30 R 20 10 0 60 80 100 120 140

m/z

b. 100 benzothiophene (2) [M+] 90 134 (100) 80 S 70 y t i

s 60 n e t

n 50 I

v 40 ti a l [M-CHS] e 30 R 89 [M-C H ] 20 (10) 2 2 108 10 (4) 0 60 80 100 120 140

m/z

Figure 3.4. Structures and electron impact mass spectra of (a) benzoic acid (1), as its Figuremethyl 3.4. esterStructures after and derivatization electron impact with mass diazomethane, spectra of (a) benzoicand (b) acidbenzothiophene (1), as its methyl (2) detect ester- aftered derivatizationin media of a microbial with diazomethane, enrichment andculture (b) benzothiophene degrading DBT. (2) detected Numbers in inmedia bold of italics a microbial enrichmentrefer to entriesculture degradingin Table 3.1. DBT. Numbers in bold italics refer to entries in Table 3.1.

73 a. 100 [M+] benzisothiazole (3) 90 135 (100) 80 S 70 N y t i

s 60 n e

t [M-CHN]

n 50 I

e 91 108 v 40 (33) ti (31) a l

e 30 R 20 10 0 60 80 100 120 140

m/z

b. 100 + 2-methylsulﬁnyl phenol (4) [M-CH3] [M ] 156 90 [M-C2H3O] 141 (100) (81) 80 113 O (73) S 70

y OH t i

s 60 n e t

n 50 I

v 40 ti a l

e 30 R 20 10 0 60 80 100 120 140 160 m/z

FigureFigure 3.5. 3.5. StructuresStructures andand electronelectron impact impact mass mass spectra spectra of of (a) (a) benzisothiazole benzisothiazole (3) (and3) and (b) (b)2-methylsulﬁnyl 2-methylsulfinyl phenol phenol (4) (4detected) detected in media in media of a of microbial a microbial enrichment enrichment culture culture degrading de- gradingDBT. Numbers DBT. Numbers in bold initalics bold refer italics to referentries to inentries Table 3.1.in Table 3.1.

74 a. 100 [M-CHO] [M+] 2-hydroxybenzothiophene (5) 121 150 90 (100) (85) 80 S OH 70 y t i

s 60 n e t

n 50 I [M-C OS] e 2 v 40

ti 78 a

l (29)

e 30 R 20 10 0 60 80 100 120 140 160

m/z

b. + 100 3-hydroxybenzothiophene (6) [M-CHO] [M ] 150 90 121 (100) (99) S 80 70 y t i OH s 60 n e t

n 50 I

v 40 [M-C OS]

ti 2 a

l 78

e 30

R (22) 20 10 0 60 80 100 120 140 160 m/z Figure 3.6. Structures and electron impact mass spectra of (a) 2-hydroxybenzothiophene (5) and Figure 3.6. Structures and electron impact mass spectra of (a) 2-hydroxybenzothio- (b) 3-hydroxybenzothiophene (6) detected in media of a microbial enrichment culture degrading phene (5) and (b) 3-hydroxybenzothiophene (6) detected in media of a microbial enrich- DBT. Numbers in bold italics refer to entries in Table 3.1. ment culture degrading DBT. Numbers in bold italics refer to entries in Table 3.1.

75 a. 100 thiosalicylic acid, methyl ester (7) [M-CH3OH] 90 136 (100) 80 70

y S H O t i

s 60 n e

t O [M-C2H3O2H]

n 50 I 108 e (36) v 40 [M+] ti a

l 168

e 30

R (20) 20 10 0 60 80 100 120 140 160 180

m/z

[M+] b. [M-CHO] 144 115 (100) 100 2-naphthol (8) (94) 90 80 OH 70 y t i

s 60 n e t

n 50 I

v 40 ti a l [M-C3H3O] e 30

R 89 20 (12) 10 0 60 80 100 120 140 160 m/z Figure 3.7. Structures and electron impact mass spectra of (a) thiosalicylic acid (7), as its Figure 3.7. Structures and electron impact mass spectra of (a) thiosalicylic acid (7), as methyl ester after derivatization with diazomethane, detected in media of a microbial enrich- its methyl ester after derivatization with diazomethane, detected in media of a microbial ment culture degrading DBT, and (b) 2-naphtholol (8), used as an internal standard in GC/MS analyses.enrichment Numbers culture in degrading bold italics DBT, refer and to entries (b) 2-naphtholol in Table 3.1. (8), used as an internal standard in GC/MS analyses. Numbers in bold italics refer to entries in Table 3.1.

76 a. 100 benzothiophene-2,3-dione (9) [M-CO] 136 90 (100) S 80 O 70

y [M-C2O2] t i

s 60 O 108 n

e (48) t

n 50 I

v 40 ti a l

e 30 R + 20 [M ] 164 10 (5) 0 60 80 100 120 140 160

m/z

b. 100 1,2-benzodithiol-3-one (10) [M+] 90 168 (100) 80 O 70 y t i S s 60 n

e S t

n 50 I [M-CO] e [M-S2] v 40 96 140 ti 104 a

l (28) (26) (27) e 30 R 20 10 0 60 80 100 120 140 160 180

m/z

FigureFigure 3.8. 3.8. Structures andand electron electron impact impact mass mass spectra spectra of of(a) (a) benzothiophene-2,3-dione benzothiophene-2,3-dione(9 )( 9and) and (b) (b)1,2-benzodithiol-3-one 1,2-benzodithiol-3-one (10) (detected10) detected in media in media of a microbial of a microbial enrichment enrichment culture culturedegrading degrading DBT. Numbers DBT. Numbers in bold initalics bold refer italics to referentries to in entries Table 3.1.in Table 3.1.

77 a.

100 dihydroxybenzothiophene (11) [M-CH2O] 90 136 S (100) 80 OH 70 y t i

s 60 OH n

e [M-C2H2O2] t

n 50 I

108

e (38) [M+] v 40 ti 166 a l

e 30 (23) R 20 10 0 60 80 100 120 140 160

m/z b. 100 3-hydroxy-1-benzothiophene-2-carbaldehyde (12) [M+] 90 178 80 O (100) S 70 y t i

s 60 n e t OH n 50 I [M-C2HO2] e

v 40 121 ti a

l (29)

e 30 R [M-CO] 20 150 10 (5) 0 60 80 100 120 140 160 180 200

m/z

FigureFigure 3.9. 3.9. StructuresStructures andand electron electron impact impact mass mass spectra spectra of (a)of (a)benzothiophene-2,3-diol benzothiophene-2,3-diol (11) and (b) 3-hydroxy-1-benzothiophene-2-carbaldehyde (12) detected in media of a microbial (11) and (b) 3-hydroxy-1-benzothiophene-2-carbaldehyde (12) detected in media of a enrichment culture degrading DBT. Numbers in bold italics refer to entries in Table 3.1. microbial enrichment culture degrading DBT. Numbers in bold italics refer to entries in Table 3.1.

78 a. 100 benzothiophene-3-carboxylic acid (13) [M+] [M-OH] 178 90 S 161 (100) 80 (77) 70 OH y t i s 60 O n

e [M-C2HO2S] t

n 50 I 89 e

v 40 (37) ti [M-CHO2] a l

e 30 133 R (20) 20 10 0 60 80 100 120 140 160 180 200

m/z

b. 100 3-hydroxybenzothiophen-2-one (14) [M-OCH2O] 90 120 S (100) 80 O 70 y t i

s 60 n e

t OH

n 50 I +

e [M ]

v 40 ti [M-CH2O] 166 a [M-C2H2O2] l (23) e 30 108 136 R (18) 20 (17) [M-O] 10 150 (1) 0 60 80 100 120 140 160 180

m/z

FigureFigure 3.10. 3.10. StructuresStructures and and electron electron impact impact mass mass spectra spectra of (a) of benzothiophene-3-carboxylic(a) benzothiophene-3- carboxylicacid (13) andacid (b) (13 3-hydroxybenzothiophe-2-one) and (b) 3-hydroxybenzothiophe-2-one (14) detected (14 in) media detected of a inmicrobial media ofenrich a - microbialment culture enrichment degrading culture DBT. Numbersdegrading in DBT. bold italicsNumbers refer in to bold entries italics in Table refer 3.1. to entries in Table 3.1.

79 a. 100 DBT (15) [M+] 90 184 (100) 80 S 70 y t i

s 60 n e t

n 50 I

v 40 ti [M-CHS] a l

e 30 139 R [M-S] (17) 20 152 (9) 10 0 60 80 100 120 140 160 180 200

m/z

b. 100 benzothiophene-2,3-dicarbaldehyde (16) [M-CHO] 90 O 161 (100) 80 S 70 y t i

s 60 O n [M+] e t

n 50 190 I [M-C3HO2S]

e (39) v 40 89 ti

a (31) [M-C HO ]

l 2 2

e 30

R 133 20 (16) 10 0 60 80 100 120 140 160 180 200

m/z Figure 3.11. Structures and electron impact mass spectra of (a) DBT (15) and (b) Figure 3.11. Structures and electron impact mass spectra of (a) DBT (15) and (b) benzo- benzothiophene-2,3-dicarbaldehyde (16) detected in media of a microbial enrichment culture thiophene-2,3-dicarbaldehyde (16) detected in media of a microbial enrichment culture degrading DBT. Numbers in bold italics refer to entries in Table 3.1. degrading DBT. Numbers in bold italics refer to entries in Table 3.1.

80 a. 100 benzothiophene-2,3-dicarboxylic acid, [M-CH O] 90 dimethyl ester (17) 3 219 80 (100) O [M+] 70

y S 250 t

i O s 60 (56) n e t O

n 50 I

v 40 O [M-C2H5O2] ti

a 189 l

e 30 (22) R 20 10 0 60 80 100 120 140 160 180 200 220 240 260

m/z

100 benzothieno[2,3-c]furan-1,3-dione (18) [M-CO2] 90 O 160 S (100) 80 [M-C O ] O 2 3 70 132 y

t (60) i

s 60 [M+] n O e

t 204

n 50 I

(43) e

v 40 ti a l

e 30 R 20 10 0 60 80 100 120 140 160 180 200 220

m/z

FigureFigure 3.12. 3.12. Structures Structures and and electronelectron impactimpact mass mass spectra spectra of of (a) (a) benzothiophene-2,3 benzothiophene-2,3-- dicarboxylicdicarboxylic acid, acid, detected detected as as its its dimethyl dimethyl ester ester afterafter derivatization with with diazomethane diazomethane (17)( 17and) and (b) (b) benzothieno[2,3-c]furan-1,3-dione benzothieno[2,3-c]furan-1,3-dione ( (1818)) detecteddetected in mediamedia of of a a microbial microbial enrichmentenrichment culture culture degrading degrading DBT. DBT. Numbers Numbers in in boldbold italics referrefer to to entries entries in in Table Table 3.1. 3.1.

81 a. 100 21.78 min [M+] [M-CO] 202 90 (100) 174 80 [M-C2O2] (74) 70 146 y

t (59) i

s 60 n e

t (46)

n 50 I

v 40 ti a l

e 30 R 20 10 0 60 80 100 120 140 160 180 200 220 m/z O O benzothioenopyranones O (19, 20) O S S b. + 100 22.12 min [M ] 202 90 (100) 80 70 y t i

s 60 n e t

n 50 I

v 40 ti a l

e 30 [M-CO] R [M-C2O2] 20 146 174 (8) (8) 10 0 60 80 100 120 140 160 180 200 220 m/z

FigureFigure 3.13. 3.13. Structures Structures and and electron electron impact mass mass spectra spectra of ofbenzothienopyranones benzothienopyranones (19, 20(19,) detected20) detected at (a)at (a) 21.78 21.78 min min and and (b) (b) 22.12 22.12 minmin by GC/MSGC/MS in in media media of ofa microbiala microbial enrichmentenrichment culture culture degrading degrading DBT. DBT. Specific Speciﬁc structurestructure assignments assignments for for spectra spectra cannot cannot be determined.be determined. Numbers Numbers in bold in bolditalics italics refer refer to entries to entries in Tablein Table 3.1. 3.1.

82 a. 100 DBT sulfone (21) [M+] 90 216 O O (100) 80 S 70 y t i

s 60

n [M-CHO] e t 187 n 50 I [M-SO] (41) e

v 40 168 ti 136

a (30) l

e 30 (25) R 20 10 0 60 80 100 120 140 160 180 200 220

m/z

100 DBT sulfoxide (22) [M-O] 90 184 (100) 80 O 70 S y t i

s 60 n e t

n 50 I [M+] e

v 40 [M-CHO]

ti 200 a

l 171 (28)

e 30

R (23) 20 10 0 60 80 100 120 140 160 180 200 220

m/z Figure 3.14. Structures and electron impact mass spectra of (a) DBT sulfone (21) and (b) Figuredibenzothiophene 3.14. Structures sulfoxide and electron (22) detected impact in mass media spectra of a microbial of (a) DBT enrichment sulfone (culture21) and (b) dibenzothiophenedegrading DBT. Numbers sulfoxide in bold (22) italicsdetected refer in to media entries of in a Table microbial 3.1. enrichment culture degrading DBT. Numbers in bold italics refer to entries in Table 3.1.

83 a. 100 24.10 min [M-C7H4OS] 90 136 (100) 80 70 y t i [M-C8H4O2S] s 60 n

e 108 t

n 50

I (41)

v 40 ti a l

e 30

R + 227 [M ] 20 272 (9) 10 (5) 0 60 100 140 180 220 260 300

m/z O O S O dithiosalicylides (23, 24) S S S b. O

100 25.06 min [M-C7H4OS] 90 136 (100) 80 70 y t i s 60 [M-C8H4O2S] n e

t 108

n 50 I (37) e

v 40 ti a l + e 30 [M ] R 227 272 20 (9) (10) 10 0 60 100 140 180 220 260 300

m/z FigureFigure 15. 3.15.Structures Structures and electron and impact electron mass impact spectra massof dithiosalicylides spectra of dithiosalicylides (23, 24) detected at(23, (a) 24) 24.10detected min and at (b) (a) 25.06 24.10 in media min and of a (b)microbial 25.06 enrichment min in media culture of adegrading microbial DBT. enrichment Speciﬁc structure culture assignments cannot be determined for these spectra. degrading DBT. Specific structure assignments cannot be determined for these spectra. Numbers in bold italics refer to entries in Table 3.1.

84 a. 100 thioindigo (25) [M+] 90 296 80 (100) O S 70 y t i

s 60 n e

t S O

n 50 I

v 40 ti a l

e 30 120 240 R 20 (18) (18) 10 0 60 100 140 180 220 260 300

m/z

b. dithiosalicylic acid, dimethyl ester (26) 100 [M-C8H7O2S] 90 167 (100) 80 O 70 y

t O S S

i O

s 60 n

e O t

n 50 I

e [M-C9H10O2S] v 40 + ti 152 [M ] a l 334 e 30 (24) R [M-C10H10O4S] (20) 20 108 (9) 10 0 60 100 140 180 220 260 300 340 380

m/z Figure 3.16. Structures and electron impact mass spectra of (a) thioindigo (25) and (b) Figuredithiosalicylic 3.16. Structures acid (26), as and its dimethylelectron esterimpact after mass derivatization spectra of (a) withthioindigo diazomethane, (25) and detected (b)in dithiosalicylic media of a microbial acid (26 enrichment), as its dimethyl culture esterdegrading after DBT. derivatization Numbers in bold with italics diazomethane, refer to detectedentries in in Table media 3.1. of a microbial enrichment culture degrading DBT. Numbers in bold italics refer to entries in Table 3.1.

85 a. 2-{[2-(carboxycarbonyl)phenyl]disulfanyl}benzoic acid (28) 100 [M-C8H7O2S] 90 [M-C9H7O3S] 195 (100) 80 167 (69) 70 O O y t

i [M-C10H10O4S] s 60 S S O n 136 e t (38)

n 50 O O I

v 40 ti a l

e 30 + R [M ] 20 362 (9) 10 0 60 100 140 180 220 260 300 340 380

m/z

b. 2,2’-(disulfanediyldibenzene-2,1-diyl)bis(oxoacetic acid), 100 dimethyl ester (29) 90 [M-C9H7O3S] O 195 80 O (100) O 70

y [M-C11H10O5S] t

i S s 60 136 S n

e (49) t [M-C12H10O6S] n 50

I O

e 108 O v 40 (36) ti a

l O

e 30 R 20 [M+] 10 390 (3) 0 60 100 140 180 220 260 300 340 380

m/z

FigureFigure 3.17. 3.17. Structures Structures and andelectron electron impact impact mass spectramass spectra of (a) 2-{[2 of (a)- 2-{[2- (carboxycarbonyl)phenyl]disulfanyl}benzoic(carboxycarbonyl)phenyl]disulfanyl}benzoic acid aciddimethyl dimethyl ester (ester28) and (28 (b)) and (b) 2-{[2-2,2’- 2-{[2-2,2’-(disulfanediyldibenzene-2,1-diyl)bis(oxoacetic(disulfanediyldibenzene-2,1-diyl)bis(oxoacetic acid) acid)dimethyl dimethyl ester ester (29) 29( detected) detected after after derivatizationderivatization with with diazomethane diazomethane in mediain media of a ofmicrobial a microbial enrichment enrichment culture culturedegrading degrading DBT. NumbersDBT. Numbers in bold italicsin bold refer italics to entries refer to in entriesTable 3.1. in Table 3.1.

86 Unknown M+ 284 (27) 100 + C15H8O4S [M ] 284 90 O plausible S (100) 80 structure: O [M-C2O2] 70 O 228 y t

i O (71) s 60 n DBT fragmentation pattern e t

n 50 I

e [M-C3O4] v 40 ti 184 a l (28)

e 30 R 108 120 (10) 20 (12) 139 152 (6) (8) 10 (8) 0 60 80 100 120 140 160 180 200 220 240 260 280 300

m/z

FigureFigure 3.18. 3.18. Structures Structure and andelectron electron impact impact mass massspectra spectra of an ofunknown an unknown compound compound (27) with a molecular(27) with ion a atmolecular 284 m/z iondetected at 284 in m/z media detected of a microbial in media enrichment of a microbial culture enrichment degrading culDBT.- A possibleture degrading molecular DBT. formula A possible and structure molecular are postulated formula and from structure the spectrum. are postulated Numbers from in bold the italicsspectrum. refer to entriesNumbers in Tablein bold 3.1. italics refer to entries in Table 3.1.

For some of the remaining compounds, clues to their formation can be derived from previously published literature. For example, 2-methylsulfinyl phenol (4; identified by 72% match to NIST spectral library), although not previously reported as a DBT degradation product, is the sulfur analog of 2-hydroxyacetophenone, a product formed during the degradation via angular dioxygenation of dibenzofuran, an analog of DBT (Harms et al., 1995; Gai et al., 2007). Benzothiophene-3-carboxylic acid (13) has been found as a degradation product of benzothiophene (2) (Eaton and Nitterauer, 1994), also observed in this study. 2-hydroxybenzothiophene (5) likely formed from 2,3-dihydroxybenzothiophene (11), as has been reported for its isomer 3-hydroxybenzothiophene (6). Benzo- thieno-1,3-furandione (18) may have formed biotically or abiotically as an anhydride of

87 benzothiophene-2,3-dicarboxylic acid (17) (Reinecke et al., 1981). The dithiosalicylide isomers (23, 24), observed at trace levels, are possible dimerization products of thiosalicylic acid (7) (Fanning et al., 1972). Benzothiophene-2,3-dicarbaldehyde (16) has been reported as a DBT photoproduct (Bobinger et al., 1999). The presence of this compound in the current study may indicate a previously unreported bacterial degradation product, or it may have formed inadvertently during sample processing even though care was taken to minimize exposure of the samples to light to prevent its formation by DBT photooxidation. With the exception of 2-methylsulfinylphenol (4), the above products likely formed via the lateral dioxygenation pathway (Figure 3.2).

The formation of benzothiophene (2), benzisothiazole (3) and 1,2-benzodithiol-3- one (10) are not readily explained. In organic syntheses, 1,2-benzodithiol-3-one (10) can be formed from thiosalicylic acid (7) in several steps under controlled conditions (e.g.,

H2SO4, thioacetic acid) (McKibben and McClelland, 1923; Iyer et al., 1990), but it is not clear how an analogous reaction could occur under the conditions of the current study. A pathway leading to benzisothiazole (3) is not apparent, but this compound may have formed through reactions of other DBT products with inorganic nitrogen supplied as a nutrient in the media.

Spectra of two potential products, 14 and 27, could not be matched to known compounds. Product 14 gave a molecular ion of 166 m/z in both electron impact and negative chemical ionization mass spectrometry. Fragments observed in EI mode include (1) 150 m/z (1% relative abundance), indicating a loss of –O; (2) 136 m/z (18%) from loss of –CH2O, (3) 120 m/z (100%) from loss of –OCH2O; and (4) 108 m/z (17%) indicating a loss of –C2H2O2 (Figure 3.10). The molecular mass and spectrum are consistent with a molecular formula of C8H6O2S, and the structure of 3-hydroxybenzothiophen-2-one, the proposed identity for peak14 . Computational chemistry predictions

88 indicate that, in DCM or in water at any pH, this compound is the dominant tautomer of 2,3-dihydroxybenzothiophene (10) (Finkel’stein et al., 1997); (Carreira), a known lateral dioxygenation DBT product observed in the culture. Product 27 yielded a molecular ion of 284 m/z (100%), with EI fragments of 255 m/z (8%), 228 m/z (71%), 227 m/z (71%), 184 m/z (28%), 152 m/z (8%) and 139 m/z (6%) (Figure 3.18). The first three fragments indicate losses of –CHO, -C2O2 and –C2HO2. The latter three fragments (184 m/z, 152 m/z, 139 m/z) are indicative of the fragmentation pattern of DBT (15) (Figure 3.11), suggesting that this product contains a DBT skeleton. A molecular formula consistent with the molecular mass and fragmentation pattern is C18H8O4S. Based on these results, one possible structure for product 27 is benzothieno[2,3-h][1,5]benzodioxepine-2,3(4H)-dione (Table 3.1, Figure 3.18). Because the sulfur is not oxidized, this product would most likely have formed via the lateral dioxygenation pathway (Figure 3.2), however, exactly how this product may have resulted is not clear. Because of the number of DBT products observed, several of which were observed at very low levels, further results focus on a subset of these products.

3.3.2. Toxicity of DBT and selected degradation products to V. fischeri

Dose-response effects of DBT and selected degradation products benzoic acid (1), thiosalicylic acid (7), benzothiophene-2,3-dione (9), DBT sulfone (21), thioindigo (25) and dithiosalicylic acid (26) on toxicity to V. fischeri are presented in Figure 3.19. Tox- icity was measured as inhibition of luminescence in the bacteria. This assay, which is similar to commercial assays used to screen water, soil, and sediments (e.g., MicrotoxTM:

Ocampo-Duque et al., 2008; Bulich et al., 1992), provides a general indication of toxicity as an overall affect on the organism’s metabolism, and does not provide information on

89 specific toxic mechanisms. DBT elicited clear toxic effects at 1.0 – 1.5 µM, indicating that DBT contributed to toxicity observed in the DBT degradation experiments during times when aqueous DBT fell within this range ( see Figure 3.20b below). These time periods included the first few days of the DBT degradation experiments, and, for the experiment without control, at 14-20 d. Concentrations above 1.5 µM exceeded DBT solubility limit in the artificial seawater and were not evaluated, although higher concentrations were observed in inoculated flasks (Figure3.20b) possibly due to the presence of lipids from bacteria that may have enhanced apparent DBT solubility. DBT sulfone (21) produced no toxicity in V. fischeri at any concentration tested. All other compounds tested showed no toxic effect over concentration ranges observed in the degradation studies, suggesting that they did not contribute to toxicity observed during DBT degradation. Because all compounds were tested individually, these results do not reflect any mixture effects on toxicity that may have played a role in toxicity observed during DBT degradation (presented below).

90 60 DBT (15; 0-1.5 μM) benzoic acid (1; 0-0.2 μM)

) 50 thiosalicylic acid (7; 0-4 μM) % ( benzothiophen---2,3-dionee (9; 0-0.79 μM) e c

n DBT sulfone (21; 0-0.65 μM) e

c 40

s dithiosalicylic acid (26; 0-0.2 μM) e n

i thioindigo (25; 0-0.53 μM)

m 30 u l

f o

n o 20 ti i b i h n I 10

0 .001 .01 0.1 1 10 100 1000 10,0000 µM

Figure 3.19.Figure Dose-response 3.19 Dose-response effect of effect DBT (15 of) DBTand (selected15) and selectedDBT degradation DBT degradation products in artificialproducts seawater in artificial media on seawatertoxicity measuredmedia on astoxicity inhibition measured of luminescence as inhibition in Vibrio of fischeri. Errorluminescence bars are standard in Vibrio deviations fischeri. Error of three bars replicates.are standard Numbers deviations in bold of italicsthree in parenthesesreplicates. refer to compound Numbers in structures bold italics in inTable parentheses 3.1. Concentration refer to compound ranges in structures parentheses are inthe Table ranges 3.1. observed Concentration in the degradation ranges in parentheses studies. Noteare thethat ranges percent observed inhibition in of luminescencethe degradation from exposure studies. to DBT Note sulfone that (21percent) was inhibitionat or near zero of luminescence at all concentra from- tions tested.exposure to DBT sulfone (21) was at or near zero at all concentrations tested.

3.3.3. Trends in toxicity during DBT degradation

Changes in toxicity over time by the microbial community with and without maintenance of pH at 7.55 are shown in Figure 3.20a. Regardless of pH treatment, toxicity rose dramatically during the first few days after inoculation (Figure 3.20a) from

91 approximately 21% inhibition of luminescence at day 0 (representing the toxicity attributable to DBT at solubility) to 51% and 62% inhibition of luminescence at day 4 with and without pH control, respectively. Under pH control, toxicity values steadily decreased after 4 d to 22% inhibition of luminescence by the end of the experiment. Without pH control, toxicity also decreased after 4 d until 8 d when values rose again to 42% at 12-14 d, after which time values fell to 25%. Final toxicity values were not statistically different from initial values for both pH treatments. Because aqueous DBT concentrations decreased during the first few days under both pH treatments, the increase in toxicity observed at this time was likely due to one or more degradation products. Aqueous DBT was not detectable beyond 10 d when pH was controlled, hence the residual toxicity was likely attributable to degradation products. When pH was not controlled, the presence of aqueous DBT after about 8 d, along with degradation products, likely contributed to toxicity at this time. At no time in either experiment was toxicity reduced below initial values. In uninoculated flasks, average inhibition of luminescence ranged from

16.9±0.7% to 22.9±2.7% during the study and was not significantly different between pH treatments (data not shown).

3.3.4. Trends in DBT and degradation products

Trends in aqueous DBT and its degradation products over time by the microbial community with and without maintaining pH at 7.55 are shown in Figures 3.20 and 3.21. Initial aqueous DBT concentrations, determined by GC/MS, were 1.55 µM and 1.34 µM in treatments with and without pH control, respectively. These values were not statistically different.

92 a. no pH control )

60 % pH controlled ( f

o e

c n n

o 40 e ti i c s b i e h

n 20 i n I m u

L 0 0 4 8 12 16 20 24 28 32 Day b. c. 3.0 1.0 2.4 0.8

1.8 (15) 0.6 O O (21) S S

μM 1.2 μM 0.4 0.6 0.2 0.0 0.0 0 4 8 12 16 20 24 28 32 0 4 8 12 16 20 24 28 32 Day Day d. e. 9 9 S (6) 6 S OH 6 (5) OH 3 3

Relative Response Relative 0 Response Relative 0 0 4 8 12 16 20 24 28 32 0 4 8 12 16 20 24 28 32 Day Day

f. g. 1.0 2.5 S OH S O 2.0 (9) (11) OH O 1.5 0.5 μM μM 1.0 0.5 0.0 0.0 0 4 8 12 16 20 24 28 32 0 4 8 12 16 20 24 28 32 Day Day Figure 3.20. Trends by day after inoculation in (a) toxicity, (b) aqueous DBT (15), (c) DBT sulfone (21), (d) Figure2-hydroxybenzothiophene 3.20. Trends by (day5), (e) after 3-hydroxybenzothiophene inoculation in (a) (6 ), toxicity,(f) benzothiophene-2,3-dione (b) aqueous DBT ( (159) and), (c) (g) DBT2,3-dihydroxybenzothiophene sulfone (21), (d) 2-hydroxybenzothiophene (11) in media of a DBT-degrading (5), (e) culture 3-hydroxybenzothiophene under conditions with and without (6), pH (f) benzothiophene-2,3-dionecontrol. Toxicity is measured as inhibition (9) and of(g) luminescence 2,3-dihydroxybenzothiophene in Vibrio ﬁscheri. Relative responses (11) in mediawere deter - mined using 2-naphthol (8) as an internal standard. Numbers in bold italics refer to entries in Table 3.1. of a DBT-degrading culture under conditions with and without pH control. Toxicity is measured as inhibition of luminescence in Vibrio fischeri. Relative responses were determined using 2-naphthol (8) as an internal standard. Numbers in bold italics refer to entries in Table 3.1.

93 a. b. 1.2 1.2 O O (22) S 0.8 S 0.8 (12) OH 0.4 0.4 Relative Response Relative Relative Response Relative 0.0 0.0 0 4 8 12 16 20 24 28 32 0 4 8 12 16 20 24 28 32 Day Day c. d. 10 3 S S (13) 8 O 2 6 (14) OH OH O 4 1 2 Relative Response Relative Relative Response Relative 0 0 0 4 8 12 16 20 24 28 32 0 4 8 12 16 20 24 28 32 Day Day

e. f. O 6 0.3 SH OH O HO O S 4 0.2 S (7) OH μM μM O 2 0.1 (26) O

0 0.0 0 4 8 12 16 20 24 28 32 0 4 8 12 16 20 24 28 32 Day Day

g. 0.8 O 0.6 S

0.4 S μM O (25) 0.2

0.0 0 4 8 12 16 20 24 28 32 Day Figure 3.21. Trends by day after inoculation in (a) DBT sulfoxide (22), (b) 3-hydroxy-1-benzothiophene-2- Figurecarbaldehyde 3.21. (12Trends), (c) 3-hydroxybenzothiophen-2-one by day after inoculation (14 ),in (d) (a) benzothiophene-3-carboxylic DBT sulfoxide (22), (b) 3-hydroxy-acid (13), (e) thiosali- 1-benzothiophene-2-carbaldehydecylic acid (7), (f) dithiosalicylic acid (26) and ( (g)12 thioindigo), (c) 3-hydroxybenzothiophen-2-one (25) in media of a DBT-degrading culture (14 ),under (d) conditions benzothiophene-3-carboxylicwith and without pH control. Relative acid responses (13), (e) were thiosalicylic determined acidusing (2-naphthol7), (f) dithiosalicylic (8) as an internal acid standard. (26Numbers) and (g)in bold thioindigo italics refer (25 to )entries in media in Table of 3.1. a DBT-degrading culture under conditions with and without pH control. Relative responses were determined using 2-naphthol (8) as an internal standard. Numbers in bold italics refer to entries in Table 3.1.

94 In both pH treatments, aqueous DBT was rapidly depleted to trace levels. With pH control, aqueous DBT levels fell below detection from 10 d through the end of the experiment. However, when pH was not controlled, aqueous DBT concentrations increased after 6 d to 2.37 µM at 14 d and remained high until the end of the experiment. These results indicate that DBT degradation was impaired, apparently because of the pH decrease to 4.22 by 10 d (see Chapter 2, Figure 2.3). This drop in pH was likely due to acidifying bacterial processes, including several DBT degradation steps such as ring cleavage and dehydrogenation of DBT dihydrodiols (Kodama et a., 1973) (see Chapter 1, Figure 1.1).

Trends in DBT sulfone (21) and DBT sulfoxide (22), products of the angular dioxygenation pathway, were similar for a given pH treatment, however they differed between pH treatments (Figures 3.20c and 3.21a). When pH was controlled, DBT sulfoxide (22) and DBT sulfone (21) levels increased to a maximum at 2 and 4 d, respectively, after which time these products decreased to below detection by 10 d. Without pH control, these compounds were present at low levels but increased rapidly from 6 through 14 d, following a trend similar to that of aqueous DBT and indicating impairment of the angular dioxygenation pathway.

Monitored products from the lateral dioxygenation pathway included 2- and 3-hydroxybenzothiophenes (5 and 6), benzothiophene-2,3-dione (9), 2,3-dihydroxybenzothiophene (11), 3-hydroxy-1-benzothiophene-2-carbaldehyde (12), benzothiophene- 3-carboxylic acid (12), 3-hydroxybenzothiophene-2-one (14) and thiosalicylic acid (7) (Figures 3.20 and 3.21). Of these, benzothiophene-2,3-dione (9), 2,3-dihydroxybenzothiophene (11), 3-hyroxybenzothiophen-2-one (14) and 3-hydroxy-1-benzothiophene-2-carbaldehyde (12) were present above trace levels by the end of the experiments. Benzothi- ophene-2,3-dione (9) followed a similar trend in both pH treatments: the concentration

95 of this product increased to 0.79 µM by 6 d, and, with the exception of a slight spike at 14 d when pH was not controlled, concentration decreased thereafter to approximately 0.27 µM. When pH was controlled, 2,3-dihydroxybenzothiophene (11) and 3-hydroxybenzothiophen-2-one (14) followed trends similar to that of benzothiophene-2,3-dione (9), reaching maximum levels (1.76 µM for 2,3-dihydroxybenzothiophene (11)) by 4-6 d and reducing to a residual level (e.g., 0.48 µM for 2,3-dihydroxybenzothiophene (11) by 32 d (Figures 3.20 and 3.21). 3-hydroxy-1-benzothiophene-2-carbaldehyde (12), however, did not reach maximum concentration until 32 d. When pH was not controlled, these three compounds (11, 12, 14) generally increased until 10-14 d, decreasing thereafter. Under pH control, the monohydroxybenzothiophenes (5, 6), thiosalicylic acid (7) and benzothiophene-3-carboxylic acid (13) concentrations peaked around 4 d, decreasing to trace levels or below by 10-14 d. Without pH control, little thiosalicylic acid (7) was observed only in the early days of the experiment, while monohydroxybenzothiophenes (5, 6) and benzothiophene-3-carboxylic acid (13) levels tended to peak between 6 and 14 d (depending on the compound) but never reaching maximum levels observed under pH control.

Some of the lateral dioxygenation products (6, 11, 14; Figures 3.20 and 3.21) reached maximum levels at a later time in the experiment when pH was not controlled than when pH was controlled, suggesting that the lateral dioxygenation pathway may have proceeded more slowly without pH control than with pH control. With regard to toxicity, several products in this pathway, including benzothiophene-2,3-dione (9), mono- and dihydroxybenzothiophenes (5, 6, 11), 3-hydroxybenzothiophen-2-one (14), thiosalicylic acid (7) and benzothiophene-3-carboxylic acid (13), may have contributed to the increased toxicity observed early in the degradation experiments, although thiosalicylic acid (7) and benzothiophene-2,3-dione (9) were not toxic to V. fischeri when present as the sole degradation product at concentrations observed in the degradation

96 experiments (Figure 3.19). However, of the lateral dioxygenation products, only benzothiophene-2,3-dione (9), 2,3-dihydroxybenzopthiophene (11) and 3-hydroxybenzothiophen-2-one (14) were present above trace levels at the end of the experiments, making them candidates for compounds contributing to residual toxicity.

Two dimerization products, thioindigo (25) and dithiosalicylic acid (26) were monitored during DBT biodegradation (Figure 3.21g and f, respectively). Dithiosalicylic acid (26) was not observed when pH was not controlled. This was not surprising since the product (26) is a dimer of thiosalicylic acid (7), which was only briefly present at low levels under this condition. When pH was controlled, dithiosalicylic acid (26) followed a trend similar to that of thiosalicylic acid (7) (Figures 3.21f and e, respectively), reaching a maximum concentration of 0.2 µM at 4 d, and becoming non-detectable by 24 d. Under pH controlled conditions, thioindigo (25) reached maximum concentration (0.53 µM) at 6 d, becoming non-detectable by 32 d (Figure 3.21g). Without pH control, concentration of thioindigo (25) did not reach maximum level (0.21 µM) until 10 d. Although the trends in the concentrations of these dimerization products suggest both thioindigo (25) and dithiosalicylic acid (26) may have contributed to toxicity observed in the early days of the experiments, results from dose-response experiments did not indicate that either compound (when present individually) was toxic to V. fischeri at concentrations relevant to those observed in the degradation studies. This does not rule out their possible contribution through mixture effects, however, as discussed below.

3.4. Di s c u s s i o n

Known DBT bacterial degradation pathways (Figure 3.1) include (1) the angular dioxygenation pathway, which begins by two consecutive oxygenations at the sulfur

97 atom followed by cleavage of the S-C bond and subsequent cleavage of one of the aromatic rings (van Afferden et al., 1993); (2) lateral dioxygenation, in which an aromatic ring is deoxygenated followed by ring cleavage (Kodama et al., 1973; Laborde and Gib- son, 1977; Bressler and Fedorak, 2000; Bressler and Fedorak, 2001b); and (3) biodesulfurization, which, after oxygenations at sulfur, cleaves both C-S bonds removing sulfite from the structure (Gray et al., 1996). Angular dioxygenation is also a major degradation pathway for similar PAHs, including dibenzofuran, carbazole and fluorene (Fortnagel et al., 1990; Grifoll et al., 1994; Resnick and Gibson, 1996; Bressler and Fedorak, 2000). Lateral dioxygenation has been observed for many PAHs (Bressler and Fedorak, 2000). Among PAHs, biodesulfurization is specific for condensed thiophenes. Degradation products observed in the current study, including DBT sulfoxide (22) and DBT sulfone (21), indicated that the angular dioxygenation pathway was active in the DBT degrading microbial community. Likewise, identification of mono- and dihydroxybenzothiophenes (5, 6, 11), benzothiophene-2,3-dione (9), 3-hydroxy-1-benzothiophene-2-carbaldehyde (12) and other products signified that the lateral dioxygenation pathway was also operating. No clear evidence of biodesulfurization, such as presence of hydroxybiphenyl or biphenyl, was observed in this study. However, these products may not have been observed if they were degraded at least as rapidly as they were formed, and so it is not possible to dismiss the activity of the biodesulfurization pathway.

The taxa comprising the DBT-degrading community include Vitellibacter, Plancto- mycetaceae, Chromatiales, Pseudomonas, Bacillus, Kordiimonas, Rhizobiales-like species Rhodospirillaceae-like species, and other Alphproteobacteria species (see Chapter 2, Figure 2.1). Previous research has identified Isolates from some of these taxa that can degrade DBT to different extents, which may provide insight as to the roles the taxa in this community may play. Pseudomonas isolates have been shown to degrade DBT along the lateral dioxygenation pathway (Yamada et al., 1968; Kodama et al., 1970; Kodama et

98 al., 1973; Monticello et al., 1985; Mormile and Atlas, 1988; Resnick and Gibson, 1996; Bianchi et al., 1997; Bressler and Fedorak, 2001b) forming DBT dihydrodiols, 3-hydroxy- 1-benzothiophene-2-carbaldehyde (12), benzothiophene-2,3dione (9), thiosalicylic acid (7), Some Pseudomonas strains can oxidize DBT at the sulfur atom, yielding DBT sulfoxide (22) and sulfone (21) (Resnick and Gibson, 1996; Kropp et al., 1997), as well as perform biodesulfurization (van Afferden et al., 1993). In the Rhizobiales, a Rhizo- bium meliloti strain and Xanthobacter polyaromaticivorans 127W have been shown to degrade DBT via lateral dioxygenation as well as oxidize sulfur (Frassinetti et al., 1998; Hirano et al., 2004). Several other Alphaproteobacteria strains have been shown to degrade DBT. Other Alphaproteobacteria known to degrade DBT, such as Sphingomonas strains (Laborde and Gibson, 1977; Cerniglia et al., 1979; Bunz and Cook, 1993; Gibson, 1999; Lu et al., 1999; Nadalig et al., 2002; Gray et al., 2003; van Herwijnen et al., 2003), do not appear closely related to species in the microbial community based on 16S rRNA gene phylogeny (see Chapter 2, Figure 2.1). Among Bacilli, the only DBT degradation pathway observed has been biodesulfurization in B. subtilis WU-S2B (Kirimura et al., 2004). These findings support roles in lateral and angular dioxygenation of DBT by Pseudomonas, Rhizobiales-like, and Bacillus strains in the microbial community, however it is not possible to specifically assign degradation steps to bacterial taxa from the results of these experiments. This would require, for example, demonstration of DBT degradation or the discovery of DBT degradation genes in isolates from the community, neither of which were achieved (see Chapter 2). DBT degradation has not been demonstrated in Vitellibacter, Planctomycetaceae, Chromatiales, Rhodospirillales, or Kordiimonas, so their roles in the mixed community are unclear.

The effects of pH produced complex shifts in DBT degradation pathways. With- out pH control, DBT degradation was inhibited as pH dropped to 4.2 (see Chapter 2, Fig- ure 2.3). More specifically, declining pH appeared to inhibit angular dioxygenation after

99 oxidation of sulfur and prior to ring cleavage, based on the increasing concentrations of both DBT sulfone (21) and sulfoxide (22) in the media when pH was not controlled (Fig- ures 3.20 and 3.21). This is consistent with the concept that DBT dihydrodiol dehydrogenation and ring cleavage steps in PAH degradation are often acidifying (e.g., Kodama et al., 1973), and it is possible that these steps would be inhibited at low pH. The effect of pH on the lateral dioxygenation pathway is less clear. Low pH altered degradation along the lateral dioxygenation pathway compared to degradation under pH 7.55 conditions, shifting relative proportions of degradation products and delaying maximum concentrations of several lateral dioxygenation products including 2,3-dihydroxybenzothiophene (11), 3-hydroxybenzothiophene (6), and 3-hydroxybenzothiophen-2-one (14) (Figures 3.20 and 3.21). The lateral dioxygenation pathway may have been slowed by decreasing pH since total DBT remained relatively constant after about 8 d (see Chapter 2, Figure 2.3), however this pathway was not entirely inhibited since several degradation products continued to form and/or dissipate beyond this time.

Ionization of several DBT degradation products can change over the pH range observed in the degradation experiments, including those with carboxylic acid groups: benzoic acid (1, pKa 4.15; Vandenbelt et al., 1954); thiosalicylic acid (7; pKa 3.45, Diebler et al., 1984); benzothiophene carboxylic acid (13, pKa 3.34-4.03, Schuetz and Nilles,

1971); benzothiophene-2,3-dicarboxylic acid (17, predicted pKa1 2.5 and pKa2 3.88; SPARC

Online Calculator( Carreira)); dithiosalicylic acid (26, predicted pKa1 3.8 and pKa2 4.43;

SPARC Online Calculator(Carreira)), and the dimers 27 (predicted pKa1 3.41 and pKa2

4.23; SPARC Online Calculator (Carreira)) and 29 (predicted pKa1 3.2 and pKa2 3.81; SPARC Online Calculator (Carreira)). At pH 7.55, carboxylic acid groups would be deprotonated for all of these compounds. At the most acidic pH observed in the experiment without pH control (pH 4.2), carboxylic acid compounds with pKa ≤ 3.2 (17, 29) would be at least

90% protonated. For the other acidic compounds with higher pKas (1, 7, 13, 26, 27, 29),

100 the ionized species would comprise a larger proportion (>10%, depending on pKa) of the total species (protonated and ionized) for a given compound. Since speciation af- fects both chemical and biochemical behavior, it may have contributed to differences in trends of acidic compounds in the two degradation experiments. For example, carboxy- lates are more soluble in water than their protonated counterparts, and are more likely to form complexes with metals and to undergo intramolecular hydrogen bonding there- by changing molecular structure and electronic distribution. Compound speciation may also affect enzyme-substrate complex formation and enzymatic reactions, which could subsequently affect degradation processes. However, the effects of compound speciation on enzyme-substrate complexes have not been explored in bacterial DBT degradation enzymes.

No published study has tracked as many DBT degradation products during degradation as the current study. These previous studies have focused on either pure cultures or incompletely defined microbial communities, and the products most often monitored include DBT sulfone (21), DBT sulfoxide (22), 3-hydroxy-1-benzothiophene-2-carbaldehyde (12), and benzothiophene-2,3-dione (9). The kinetics of DBT disappearance and product formation has been shown to vary considerably, even among different strains of the same genus (e.g., Pseudomonas, (Kropp et al., 1997). Among three Pseudomonas strains in pure culture, Kropp et al. (1997) found that DBT sulfone (21) and DBT sulfoxide (22) accumulated, while 3-hydroxy-1-carbaldehyde (12) accumulated with or without then dissipating depending on the strain. The net trends observed by Kropp et al. (1997) for these products in strain BT1 were generally similar to those observed in the mixed microbial community when pH was not controlled. However, Kropp et al. (1997) observed only trace amounts of benzothiophene-2,3-dione (9) for all strains, while the dione was a prominent product in the current study under both pH treatments. Kropp et al. (1997) did not monitor or adjust pH during degradation experiments, so it is difficult

101 to assess whether or not pH affect the trends observed in the degradation products in that study. In addition to pH conditions, other factors could be responsible for the differences in biodegradation between the current study and the study by Kropp et al. (1997) and similar studies, including differing metabolic capabilities of microbial species, differing growth conditions or optimal growth requirements of the cultures, and the possibility of synergistic or antagonistic effects between taxa in the mixed culture that is not a factor in pure cultures. Kinetics of biodegradation may also differ under environmental conditions, such as in a soil remediation scenario. In this case, additional factors such as the presence of additional contaminants (e.g., other PAHs, toxic metals) or a solid surface (i.e., soil) that could affect microbial growth as well as sorption of contaminants or degradation products. For example, in soil spiked with heterocyclic PAHs including DBT, DBT sulfoxide (22) was not observed until after 25 d, peaked near 80 d, and dissipated thereafter (Meyer et al., 1999).

DBT itself was clearly toxic to V. fischeri at 1.0-1.5 µM, which is consistent with previous studies that have shown DBT (present as a sole toxicant) to be toxic to V. fischeri (Seymour et al., 1997), Daphnia magna (Seymour et al., 1997), Oryzias latipes (Rho- des et al., 2005), and Danio rerio (Incardona et al., 2004). The research presented here suggested that some DBT products were also likely to have been toxic to V. fischeri based on the observations that toxicity dramatically increased in the first few days after inoculation, regardless of pH control, and that a significant level of toxicity remained at the end of the experiment under pH control even though no aqueous DBT was present (Fig- ure 3.20). Based on dose-response effects on toxicity to V. fischeri for the degradation products that were commercially available (Figure 3.19), DBT sulfone (21), benzoic acid (1), thiosalicylic acid (7), benzothiophene-2,3-dione (9), thioindigo (25) and dithiosalicylic acid (26) were not highly toxic by themselves, although mixture effects (e.g., antagonistic or synergistic effects) on toxicity between one or more compounds were possible.

102 The finding that DBT sulfone (21) and benzothiophene-2,3-dione (9) were not toxic to V. fischeri at concentrations observed in the degradation experiments was consistent with previous research (Seymour et al., 1997). Seymour et al. (1997) observed relatively low toxicity to V. fischeri for benzothiophene-2,3-dione (9) (IC50 670 µM) compared to DBT (IC50 0.87 µM). DBT sulfoxide (22) (IC50 10 µM), while not as toxic as DBT, was more toxic than the dione (9), and so could have contributed to toxicity in the current study. Thiosalicylic acid (7) has not shown high oral acute toxicity to mice (LD50 1250 mg kg-1 day-1; Shafer and Bowles, 1985), and toxicity of this compound (7) and its dimer, dithiosalicylic acid (26), to human and murine kidney cells is relatively low (LC50 > 1000 µM; Park et al., 2007) with respect to levels observed in this study. Dithiosalicylides (e.g., 23, 24) and other disulfides have also been shown to elicit oxidative damage to rat erythrocytes in vitro (Munday, 1985). Thioindigo (25) has shown low oral acute toxic-

-1 ity to rats (LC50 4170 mg kg ; Vasilenko et al., 1985). None of the degradation products discussed so far in this paragraph have been shown to be mutagenic. No toxicological information is available for the other DBT degradation products observed in this study, however, since several of these compounds (e.g., hydroxybenzothiophenes (5, 6), 3-hydroxy-1-benzothiophene-2-carbaldehyde (12)) were primary degradation products often showing trends similar to that of toxicity in V. fischeri, their potential toxicity cannot be discounted. Because of the complex chemical nature of the post-biodegradation solution during DBT degradation, it is likely that the observed toxicity was a result of multiple compounds. The elevated toxicity during degradation and the residual toxicity following degradation suggest that, in a remediation scenario, additional steps would be required to reduce risk from contaminants. Such post-biodegradation treatments could include chemical and/or photolytic oxidation to further degrade residual toxic compounds.

103 3.5. Co n c l u s i o n

This study demonstrated that DBT degradation by a mixed bacterial culture with and without maintaining pH at 7.55 involves multiple degradation pathways forming a more complex suite of degradation products than has been reported for single-strain cultures. Of the 27 potential degradation products observed, nine have not been previously reported in bacterial DBT degradation. DBT itself was toxic to bioluminescent bacteria, but toxicity more than doubled during DBT degradation and was never reduced below initial levels regardless of pH treatment, indicating that some degradation products were toxic. Several degradation products exhibited trends similar to that of toxicity, complicating identification of specific toxic products. However, toxicity could not be attributed to any commercially available degradation product. These findings imply that bioremediation of a contaminated site could, at least transiently, increase hazard at the site, warranting steps to monitor and control transport of degradation products in addition to parent contaminants. Given that the toxicity assay used in this study does not provide information on toxic mechanisms and that these degradation products could potentially occur in environmental systems, additional investigation into toxic effects on other organisms would be needed to better understand hazard associated with DBT degradation. These findings also support investigation of remediation strategies combining biodegradation with additional steps, such as post-biodegradation UV treatments that is the focus of Chapter 5, to reduce residual degradation products and ameliorate toxicity.

104 Chapter 4. conventional and alternative approaches in the analysis bacterial populations by SYBR-Green qPCR

4.1. In t r o d u c t i o n

SYBR-Green based quantitative polymerase chain reaction (qPCR) has been demonstrated to be a powerful and sensitive technique for quantifying target genes, with a wide range of applications. Within the context of microbial ecology it shows promise not only for quantification of functional genes (e.g., those involved with pollutant- deg radation), but also to distinguish and monitor target taxonomic groups within microbial communities, such as by quantifying specific bacterial 16S rRNA genes. Investigations of populations within microbial communities have used culture-independent molecular techniques based on detection of 16S rRNA gene sequences including denaturing gradient gel electrophoresis (DGGE: Duarte et al., 2001; Vinas et al., 2005), terminal restriction fragment length polymorphism characterization (T-RFLP: Liu et al., 1997), and fluorescent in-situ hybridization (FISH: Castle et al., 2006). Although DGGE and T-RFLP techniques are valuable qualitative techniques, they are less useful for quantification. FISH, although quantitative, relies on probes that may be difficult and expensive to- de sign, may require flow cytometry or analysis of large numbers of images, and is not easily adapted to monitor more than a few targets at a time. The more recently developed SYBR-Green qPCR technique offers distinct advantages over other molecular techniques: it is a fairly rapid assay not reliant on gel preparation, expensive probes or hybridization, and it has the potential to be more reliably quantitative than the other techniques.

Application of qPCR to study complexity and dynamics of multiple populations in microbial communities, particularly within environmental matrices, is fairly recent. Smits

105 et al. (2004) applied qPCR to monitor three closely-related bacterial strains involved in chloroethene degradation in anaerobic digesters and enrichment cultures. Fierer et al. (2005) used qPCR to quantify rRNA gene copy numbers of total Bacteria and Eucarya as well as selected major taxonomic groups within these domains in soil samples. Singleton et al. (2006, 2007) combined stable isotope probing with qPCR to follow the dynamics of pyrene degraders in a bioreactor containing a slurry of PAH-contaminated soil.

QPCR is still evolving as a quantitative technique, particularly in its application to the study of microbial ecology, and fundamental questions remain as to the optimal approach for processing qPCR fluorescence data for quantification. The conventional approach, typically used by software running qPCR platforms, relies on a diagnostic point on the amplification curve at which the fluorescence crosses a threshold value for a given assay (Kubista et al., 2006; Rebrikov and Trofimov, 2006). The reaction cycle number where this occurs is often termed the “cycle threshold” (Ct). Since SYBR-Green fluorescence represents the amount of double-stranded DNA in a sample, all samples theoretically contain the same amount of PCR product DNA at their Ct values. Ct values from standards of known gene copy number are plotted against log(copy number) to obtain a standard curve from which samples for that assay can be quantified. Reaction efficiency, which refers to how many copies are produced in each cycle, can be calculated from the standard curve using Equation 4.1 (Pfaffl, 2001), wheres = the slope of the

standard curve (log (copy numbers) cycle-1).

(−1 ) Efficiency = 10 s (4.1)

106 One efficiency is calculated for the assay and it is assumed to be constant for all standards and samples. The Ct approach therefore assumes that all standards and samples follow the same reaction kinetics for a given assay (Kubista et al., 2006).

The assumptions of the Ct approach have been challenged in several studies showing that samples and standards can vary in reaction efficiencies and kinetics for a given assay (Labrenz et al., 2004; Guescini et al., 2008; Rutledge and Stewart, 2008), calling into question its reliability for quantitation. A variety of alternative approaches for analyzing qPCR data based on modeling of individual amplification curves have been developed (Rebrikov and Trofimov, 2006; Spiess et al., 2008). These approaches can be separated into two categories: those that use a diagnostic point and those based on prediction of initial target fluorescence. A diagnostic point is a value that can be determined from fitting a model to each amplification curve and used, like the Ct value, for quantification according to a standard curve. Example diagnostic points include the amplification curve first and second derivative maxima (Luu-The et al., 2005; Rebrikov and Trofimov, 2006; Spiess et al., 2008). The second derivative maximum is often selected because it occurs in the exponential phase of the reaction when change in fluorescence signal is detectable and reaction efficiency is not decreasing rapidly (Tichopad et al., 2003; Luu-The et al., 2005). Use of these diagnostic points may provide more accurate quantitation than Ct values because they are determined sample-by-sample and are not based on a single threshold value for all samples in the assay. Prediction of initial target fluorescence, which is the portion of fluorescence at the start of amplification that can be attributed to the target, offers the advantage of being free from both Cts and the use of target-specific standard curves. Initial target fluorescence predicted from model fitting can be used to calculate target DNA concentration using a conversion factor that relates SYBR-Green fluorescence to a known DNA amount (Rutledge, 2004; Rutledge and Stewart, 2008), as SYBR-Green fluorescence is theoretically proportional to double-

107 stranded DNA concentration. This factor can be determined using samples with known DNA quantities. Subsequently, gene copy number can be calculated using the size and sequence of the target gene.

Several models have been explored to derive either diagnostic points or initial fluorescence (Tichopad et al., 2003; Rutledge, 2004; Rebrikov and Trofimov, 2006; Spiess et al., 2008). These include fitting the amplification curve to a sigmoidal function with four parameters, as in Equation 4.2 (Rutledge, 2004; Rutledge and Stewart, 2008) or five parameters, as in Equation 4.3 (Spiess et al., 2008).

d = + Fx c (b(x−e) (1+  ) (4.2)

d − c Fx = c + (b(log(x)−log(e)) f (1+  ) (4.3)

Here, Fx is fluorescence,x is cycle number, b and e describe slope, c and d are asymptotic minimum fluorescence and asymptotic maximum fluorescence, respectively, and f accounts for curve asymmetry. The 4-parameter curve in Equation 4.2 assumes that the amplification curve is symmetrical (i.e., f = 1). Allowing for asymmetry in the amplification curvef ( ≠ 1) in the 5-parameter model (Equation 4.3) resulted in improved

108 fitting, as well as more accurate DNA quantitation compared to the 4-parameter model (Spiess et al., 2008).

Sigmoidal models of qPCR data have primarily been applied to monitoring functional genes by reverse-transcriptase qPCR. They have not yet been evaluated for quantifying 16S rRNA gene targets in genomic DNA, as in the study of microbial populations in mixed microbial communities. Differences in DNA sources (e.g., cDNA, genomic DNA, cloned DNA) may also affect the performance of these alternative approaches to analyzing qPCR data, but this has not been previously evaluated.

Questions also remain as to how to best quantify total 16S rRNA gene copy numbers in mixed microbial communities. A common approach to obtaining total 16S copy numbers is by amplification using universal primers that target the 16S rRNA gene in all bacteria in the community. However, universal primers do not always amplify with the same kinetics for all bacteria (e.g., Smits et al., 2004), which is contrary to the assumptions of the conventional Ct approach. The Ct approach relies on a standard curve, which is typically a dilution series of the cloned DNA target. The selection of which target to use as a standard is therefore problematic, since the presence of other targets ampli- fying at different rates in the mixed sample will lead to errors in quantitation. Solutions to this problem have not been thoroughly explored. For example, quantitation by predicted initial fluorescence, as described above, could theoretically eliminate this problem since factors converting SYBR-Green fluorescence to DNA amount are not dependent on amplification kinetics, but this approach has not yet been evaluated for this purpose.

The objectives of this study were to (1) evaluate conventional (i.e., Ct) and alternative qPCR data analysis approaches using the 5-parameter log-logistic sigmoidal model (Equation 4.3), for the quantitation of mixed microbial communities, using- syn thetic mixtures of known composition, (2) to compare these alternative approaches to

109 quantitation as applied to two DNA sources (i.e., DNA from clones containing bacterial 16S rRNA gene inserts or genomic DNA extracted from the isolates), and to targets present singly and in mixtures, (3) to explore how calculated reaction kinetics, particularly efficiencies, vary with approach, primer, target DNA quantity, and presence of non-target DNA, and (4) to evaluate quantitation of total 16S rRNA gene copy numbers in a mixed community by the Ct and alternative approaches with and without the use of a universal primer.

4.2. Ma t e r i a l s a n d m e t h o d s

4.2.1. Bacterial cell culture and genomic DNA stock preparation.

Three bacterial strains were isolated from an enrichment culture growing on dibenzothiophene as sole carbon source in artificial seawater media (22.22 g-1 L Instant

TM -1 -1 -1 Ocean ) at pH 7.5 supplemented with 1 g L NH4NO3, 0.2 g L K2HPO4 and 0.05 g L

. FeCl3 6H2O (adapted from Chang et al., 2000 and Kasai et al., 2002) as part of a study on polycyclic aromatic hydrocarbon biodegradation. Isolates were obtained by selective subculturing on solid media (liquid artificial seawater media, 12 g-1 L agar, 5 g L-1 glucose,

5 g L-1 yeast extract, 5 g L-1 peptone). Isolate cultures were harvested near the late exponential growth phase (3-5 days) and cells were pelleted by centrifugation and washed and resuspended in sterile artificial seawater for preparation of genomic DNA stocks. Resuspended cells were counted under a microscope using a Petroff-Hausser counting chamber (Hausser Scientific, Horsham PA) and 1 mL stocks of 109 cells mL-1 were prepared for each isolate. Genomic DNA was extracted from cell stocks using Qiagen 100/G Genomic-tips. Final DNA stocks were resuspended in 1 mL 10 mM TRIS buffer (pH 7.5) to have a final concentration of genomic DNA from 109 cells mL-1.

110 4.2.2. Cloning, PCR and Sequencing.

For taxonomic identification of isolates and preparation of 16S rRNA gene clones, DNA was extracted from pelleted isolate cells (5 mL) by bead-beating (UltraClean Soil DNA Extraction Kit, MoBio Laboratories, Solana Beach, CA). 16S rRNA gene sequences were amplified using universal primers fD1 (AGAGTTTGATCCTGGCTCAG, Escherichia coli positions 8 to 27) and rP2 (ACGGCTACCTTGTTACGACTT, positions 1513 to 1494; Weis- burg et al., 1991) (MWG Biotech, Huntsville, AL). PCR products were used to prepare 16S rRNA gene clones for each isolate using the StrataClone PCR cloning kit (Stratagene, La Jolla, CA), and both the PCR products from the isolates along with the 16S rRNA gene inserts from the clones were sequenced on an automated sequencer (Model 3730, Applied Biosystems, Foster City, CA) using the BigDye Terminator kit (v. 3.1). Proofread sequences were screened for chimeras using Chimera Check program (v. 2.7, Ribosomal Database Program (RDP: Cole et al., 2005)). Taxonomic groups were assigned to sequences using the RDP-X Classifier program (Cole et al., 2007). Isolates were classified as Pseudomonas (Gammaproteobacteria), Vitellibacter (Flavobacteria), and Martelella (Alphaproteobacteria, class Rhizobiales). For preparation of clone DNA stocks, clones of each isolate were grown overnight, cells were pelleted by centrifuging, and plasmids were recovered using the QiaPrep Plasmid Midi-prep kit (Qiagen). Stock DNA concentration was determined using PicoGreen according to the manufacturer’s instructions (Invit- rogen, Carlsbad, CA).

111 4.2.3. Preparation of DNA mixes, clone single isolate DNA, and genomic single isolate samples.

Twenty-one mixtures with varying amounts of each of the three isolate DNA sources were prepared for both the clone and genomic DNA stocks (giving a total of 42 mixtures). Each isolate was present at final concentrations of 103, 105 or 107 16S rRNA gene copies per qPCR reaction (for clone DNA) or DNA from 103, 105 or 107 cells per qPCR reaction (for genomic DNA). Composition of the 21 mixtures is provided in Table 4.1. Clone and genomic single isolate DNA samples were prepared in 10 mM TRIS buffer for each isolate from the corresponding DNA stocks as 10-fold serial dilutions from 108 to

103 16S rRNA gene copies per qPCR reaction (for clone DNA) or DNA from 108 to 103 cells per qPCR reaction (for genomic DNA) (Table 4.1).

112 TableTable 4.1. 4.1. Composition Composition ofof DNADNA mmixturesixtures analyzedanalyzed byby qPCR.qPCR.

Mixture Pseudomonas Martelella Vitellibacter Sum ------log(quantity) per reaction a ------1 7 7 7 7.4771 2 7 7 5 7.3032 3 7 7 3 7.3011 4 7 5 7 7.3032 5 7 5 5 7.0086 6 7 5 3 7.0044 7 7 3 7 7.3011 8 7 3 5 7.0044 9 7 3 3 7.0001 10 5 7 7 7.3032 11 5 7 5 7.0086 12 5 7 3 7.0044 13 5 5 7 7.0086 14 5 5 5 5.4771 15 5 3 7 7.0044 16 3 7 7 7.3011 17 3 7 5 7.0044 18 3 7 3 7.0001 19 3 5 7 7.0044 20 3 3 7 7.0001 21 3 3 3 3.4771 a For clone DNA, quantities are number of 16S rRNA gene copies per reaction; for genomic DNA, quantities are number of cells from which DNA was extracted per reaction.

4.2.4. Primer design and qPCR assays.

Three isolate-specific primer sets and one universal primer set targeting 16S rRNA gene sequences were designed using Primrose 2.15 (Ashelford et al., 2002) based on the isolate 16S rRNA gene sequences (Table 4.2).

113 8 8 8 8 Ͳ 10 Ͳ 10 Ͳ 10 Ͳ 10 3 3 3 3 Number 10 10 10 10 Copy Detection Range Length pairs) as noted. (base Amplicon 21 2022 118 2424 192 21 19 346 Base Pairs study except developed as part of this primers were al., 1991). All Sequence ACGGCTACCTTGTTACGACTT † F CCCTTGTCCTTAGTTACCAGCACG F TGATACTGGAAGTCTTGAGTCCGAGF CGATTGCGAAGGCAGGTCAC 25 175 R CCGGACTACGATCGGTTTTATGGG R CTGCGCCACCAAATAGCATGC R GCCGGACAGCTAGTATCCATCG R qPCR. (Weisburg et used in primer isolates F GTCGTCAGCTCGTGYYGTG Primers used in qPCR. All primers were developed as part of this study except as noted. except as part of this study developed were used in qPCR. All primers Primers Pseudomonas Martelella Vitellibacter all Primers 4.2. universal rP2 Primer Isolate PSU Table RZB VIT Universal †

4.2. Table

114 Isolate-specific primers were selected to have more than two mismatches between target and non-target sequences, to have similar melting temperatures for each primer in a set, to have minimal likelihood for secondary structure or dimer formation, and to amplify less than 500 bp. The universal reverse primer was modified from previously published primer rP2 (Weisburg et al. 1991) to more precisely match the sequences in the current study. All other primers used in qPCR were developed for this research, and were 19-24 base pairs long with melting temperatures of 57-60° C. Target amplicons were 118-346 base pairs long (Table 4.2). SYBR Green-based qPCR was performed on a Stratagene MP3000 (Stratagene, La Jolla, CA) using iTaq SYBR Green Supermix with ROX (BioRad, Hercules, CA) according to manufacturer’s instructions with primer-specific annealing temperatures (Table 4.2). Primer specificity was checked in qPCR assays including meltcurve analyses comparing target and non-target clone and isolate (genomic) DNA. For all qPCR assays, standard curves (clone DNA dilution series) and no-template controls were included, and all standards, samples and no-template controls were analyzed in triplicate.

4.2.5. Modeling and data analysis

Preliminary investigations indicated that normalization and background correction improved the consistency of qPCR assays. Background correction was performed using the adaptive baseline algorithm in the Stratagene MxPro software and sample- specific selection of beginning and ending cycles for baseline determination to avoid background subtraction errors.

This study compared data analysis by the conventional Ct approach included in the MxPro software to analysis using the 5-parameter sigmoidal model (Equation 4.3). A summary of all data fitting approaches evaluated in detail is provided in Table 4.3.

115

derivative Determination assay from for each maximum maximum for each determined for each determined for each determined at the second derivative at the second derivative at the second Efficiency standard curve regression efficiency efficiency efficiency efficiency reaction reaction reaction one

s s s initial ye ye ye n/ a from ﬂuorescence

point derivative d n maximum maximum maximum o Copy Number Quantitation c diagnostic e y s second derivative second derivative (Ct ) cycle threshold b

of early fitting derivative to determined within a fixed cycles variance in the influence above first s e l c y c approach included in instrument 11 cycles to minimize n qPCR o i of qPCR cycles a subset t p i Summary of data analysis approaches. analysis Summary of data r residual the lowest c s e D models all models conventional software maximum to maximum) give derivative second below window (6 cycles of qPCR models a subset stages on fitting and late plateau t i F 5 - Parameter sigmoidal model Full Swin Conventional Ct Fwin

4.3. Table

116 For analysis by the Ct approach, a threshold fluorescence was calculated by the MxPro software and cycle thresholds (Ct values) for all standards and samples were determined where amplification curve fluorescence equaled the threshold fluorescence. The reaction efficiency for the Ct approach was calculated from the linear regression line of the log(gene copy number) and Ct data for the template standards (Equation 4.1).

The 5-parameter sigmoidal model (Equation 4.3), was fit to fluorescence data using the qpcR package (Ritz and Spiess, 2008; Spiess et al., 2008) in R language (R Development Team, 2008), which calculated model parameters as well as first and second derivative maxima, efficiencies and initial fluorescence. The model was applied in three ways depicted in Figure 4.1: (1) to data from all cycles of the amplification curve (“Full”), (2) to a subset of qPCR cycles determined to give the lowest residual variance in fitting (sliding window, or “Swin”), and (3) to a subset of qPCR cycles within a fixed window (6 cycles below second derivative maximum to 11 cycles above first derivative maximum) to minimize the influence of early and late plateau stages on fitting (fixed window, or “Fwin”). For Swin, the set of cycles used was the subset of the data providing the lowest residual variance, as determined using the qpcR package’s “pcropt1” function. The window size for Swin varied from 15 to 40 cycles. The criteria for window selection for Fwin, an approach designed as part of this research, were determined through preliminary investigations to determine the most consistent quantitative results across sample replicates for windows that included both first and second derivative maxima, resulting in Fwin window sizes ranging from 19 to 22 cycles.

117 1.0 Cycles included in sigmoidal fitting 0.9 Full Swin 0.8 Fwin 0.7 0.6 0.5 first derivative 0.4 maximum 0.3 Relative Fluorescence 0.2 ct second derivative 0.1 maximum threshold fluorescence 0 0 5 10 15 20 25 30 35 40 Cycle Figure 4.1. Representative qPCR amplification curve indicating threshold fluorescence used Figureto determine 4.1. Representative cycle threshold qPCR (Ct) inamplification conventional curve data indicatinganalysis, diagnostic threshold pointsfluorescence (Ct and usedsecond to determine derivative cycle maximum) threshold used (Ct) for in geneconventional copy number data quantification,analysis, diagnostic first pointsderivative (Ctmaximum and second predicted derivative by five-parameter maximum) used sigmoidal for gene fitting, copy number and the quantification, ranges of cycles firstincluded in derivative maximum predicted by five-parameter sigmoidal fitting, and the ranges of Full, Swin and Fwin sigmoidal fits. The range of cycles included in Swin is variable and deter- cycles included in Full, Swin and Fwin sigmoidal fits. The range of cycles included in Swin mined by statistical criteria (see Methods for details). is variable and determined by statistical criteria (see Methods for details).

The amplification efficiency of any given cycle was calculated using:

F E = x F(x−1) (4.4)

where E is efficiency, F is fluorescence and x is cycle number. For comparative purposes, the efficiency in the 5-parameter sigmoidal fitting approaches was calculated wherex = second derivative maximum.

118 For each of the data fitting approaches described above (Full, Swin and Fwin) gene copy numbers were quantified in two ways: using the second derivative maximum (calculated from model fitting) as a diagnostic point, and using the predicted initial fluorescence values calculated using the 5-parameter model (Eqn. 4.3) and fitted parameters. Quantitation using the second derivative maximum was achieved using a calibration curve constructed from second derivative maxima. Quantitation using initial fluorescence relies on the linear relationship between fluorescence and amount of double-stranded DNA (Rutledge, 2004). Predicted initial fluorescence from standards containing a known amount of DNA was used to calculate a fluorescence conversion factor (CF) according to Rutledge (Rutledge, 2004):

F CF = 0 M 0 (4.5)

where F0 is the predicted initial fluorescence andM 0 is the mass of target DNA initially present in the reaction. CFs were determined separately for Full, Swin and Fwin fits for isolate-specific and universal qPCR assays of clone single isolate DNA. DNA quantities were calculated using Equation 4.5 above and the appropriateCF . 16S rRNA gene copy number was subsequently calculated based on the size of the corresponding template. Analyses of variance (ANOVAs) and regression used in statistical analyses were conducted using JMP 7.0 software (SAS Inc., 2007).

119 4.2.6. Calculation of 16S rRNA gene cell copy number.

The 16S rRNA gene copy numbers per cell were determined using qPCR assays of genomic isolate DNA amplified with isolate-specific primers. Estimates were calculated for each data analysis approach as:

16S rRNA gene copies measured copy number= number of cells in reaction (4.6)

4.3. Re s u l t s

QPCR reaction kinetics differed depending on DNA source (clone and genomic, mixtures and isolates) for all primers evaluated. Amplification of clone single and mixed DNA samples and most genomic isolate DNA samples yielded amplification curves conforming to the expected sigmoidal shape (Figure 4.2). This was not always the case for genomic mixed DNA, which often showed drift in the fluorescence -sig

nal in ground and especially plateau stages of the reaction (Figure 4.2). Similar drift was observed by Rutledge and Stewart (Rutledge and Stewart, 2008). The cause of this deviation from expected qPCR reaction kinetics may be related to the quantity and/or complexity of the mixed genomic DNA compared to the other DNA sources.

120 1.0 Clone Pseudomonas isolate DNA (standards) 0.9 Clone DNA mixture 0.8 Genomic Pseudomonas isolate DNA Genomic DNA mixture 0.7 0.6 0.5 0.4 0.3 108 107 106 105 104 103

Relative Fluorescence 0.2 0.1 0 0 5 10 15 20 25 30 35 40 Cycle Figure 4.2. Example QPCR amplification curves for clone and genomic Pseudomonas (single Figureisolate) 4.2. and Example mixed DNA QPCR amplified amplification with isolate-specific curves for clone primer and PSU. genomic For Pseudomo the Pseudomonas- nasclone (single DNA isolate) curves, and which mixed served DNA as amplified standards, with numbers isolate-specific associated primer with curves PSU. indicateFor the copy Pseudomonasnumber per qPCRclone reaction.DNA curves, Mixed which DNA served in this as examplestandards, contained numbers 10 associated5, 107 and 10with7 16S rRNA curvesgene indicatecopies/reaction copy number (clone per DNA) qPCR or reaction. DNA from 10Mixed5, 10 7DNA and in 10 this7 cells/reaction example contained (genomic 10DNA)5, 107 fromand 10Pseudomonas,7 16S rRNA gene Martelella copies/reaction, and Vitellibacter (clone DNA)isolates, or DNArespectively. from 105, 10 Genomic7 and 5 10Pseudomonas7 cells/reaction DNA (genomic contained DNA) DNA from from Pseudomonas, 10 Pseudomonas Martelella cells/reaction., and Vitellibacter Relative iso- fluores- cence is the background-corrected SYBR-Green fluorescence normalized to the passive dye lates, respectively. Genomic Pseudomonas DNA contained DNA from 105 Pseudomonas ROX. cells/reaction. Relative fluorescence is the background-corrected SYBR-Green fluorescence normalized to the passive dye ROX.

4.3.1. Calculated efficiencies

QPCR reaction efficiency is known to depend largely on concentrations of reaction components and the characteristics of the polymerase (Arezi et al., 2003; Wolffs et al., 2004). Efficiency changes during the course of the reaction, with initially high values that rapidly decline thereafter (Liu and Saint, 2002b). As noted, efficiencies were calcu-

121 lated based on the slope of the associated standard curve for the Ct approach (Equation 4.1) and at the second derivative maximum for all sigmoidal fitting approaches (Equa- tion 4.4). Consistent efficiencies are desirable in part because this enables application of standard curves to different mixture combinations. When all samples (including all mixture combinations) were considered together, average efficiencies, shown in Figure 4.3, were significantly affected by primer (PSU, RZB, VIT and UNI; p<0.001), fitting approach (Fwin, Swin, Full and Ct; p<0.001), DNA source (clone isolate, clone mixed, genomic isolate, and genomic mixed; p<0.05). An efficiency of 2.0 represents 100% efficiency in the PCR reaction, indicating a doubling of amplified DNA each cycle. For isolate-specific assays, efficiencies calculated from the Ct approach ranged from 1.87-2.02 and showed the following trend: RZB < PSU ≈ UNI < VIT. Reasons why efficiencies for some primers were lower than efficiencies for others are not apparent, but may be reflective of- dif ferences in effects of reagents and thermocycling conditions on the different assays. For many samples, efficiencies calculated using sigmoidal fitting approaches were at or above 2, particularly for efficiencies of genomic mixed DNA calculated by the Full approach. While trends in these efficiencies varied with fitting approach, RZB efficiencies were consistently lowest.

Variability of calculated efficiencies was markedly affected by fitting approach for some primer-DNA source combinations. Although some variability in efficiency may be expected across samples amplified with the same primer, high variability can indicate either problems with the qPCR reaction itself (e.g., presence of PCR inhibitors, poor technique in preparing qPCR preparations, interference from non-target DNA, or dete- riorated or contaminated samples or reagents) or with the ability of the fitting approach to fit all amplification curves well. The Full approach applied to genomic DNA mixtures yielded the widest range of efficiencies as indicated by the associated large error bars (standard deviations) in Figure 4.3.

122 - Fwin Fwin Swin Swin RZB Full Full UNI

b. standards

Vitellibacter on based

4.5 4.0 3.5 3.0 2.5 2.0 1.5 1.0

Eﬃciency

standards

Martelella Martelella

based on on based Ct

standards

Pseudomonas on based d.

4.5 4.0 3.5 3.0 2.5 2.0 1.5 1.0 Eﬃciency clone isolate DNA (standards) clone mixed DNA genomic isolate DNA genomic mixed DNA Fwin Fwin Swin Swin PSU VIT Full Full Average calculated qPCR efficiencies compared across approach (Ct, Full, Swin and Fwin) and DNA source for isolate- Swin and Fwin) DNA source (Ct, Full, approach across compared qPCR efficiencies calculated Average Ct Ct c. a.

4.5 4.0 3.5 3.0 2.5 2.0 1.5 1.0 4.5 4.0 3.5 3.0 2.5 2.0 1.5 1.0

Efficiency Efficiency Figure 4.3. Average calculated qPCR efficiencies compared across approach (Ct, Full, Swin and Fwin) DNA source for isolate-specific primers (a: PSU, b: RZB, c: VIT) and the unive rsal primer (d) applied to each of these bacterial groups. For Ct approach, one efficiency was calculated from each isolate’s set o f standards (clone isolate DNA), resulting in three standard-dependent efficiencies for each DNA source. Sets of st andards were included with qPCR assays clone mixed DNA, genomic isolate DNA, and mixed DNA. Each bar represent s results from all samples of a given DNA source averaged together. ficiencies for each DNA source. Sets of standards were included with qPCR assays for clone mixed DNA, genomic isolate DNA, and genomic isolate DNA, for clone mixed included with qPCR assays were standards of Sets for each DNA source. ficiencies together. averaged DNA source all samples of a given from results bar represents DNA. Each mixed genomic Figure 4.3. Figure For the Ct approach, groups. to each of these bacterial primer (d) applied c: VIT) and the universal b: RZB, (a: PSU, specific primers ef standard-dependent three resulting in DNA), (clone isolate standards set of from each isolate’s calculated was one efficiency

123 Across individual samples for all targets, efficiencies calculated by the Full approach (which are averaged by target in Figure 4.3) ranged from 1.52 to 7.93. Similar results were observed for some genomic isolate DNA amplified with PSU, RZB and UNI primers.

Because amplification curves for genomic mixed DNA often showed drift in plateau stages causing curve shapes to differ from the expected sigmoidal shape (Figure 4.2), the wide range in efficiencies for the Full approach likely indicated poor fitting by this approach and was not a reliable indication of actual amplification efficiency. Clone mixed DNA fit with the Full approach showed a smaller range in efficiencies across all individual samples (1.78-2.64; data is averaged by target in Figure 4.3) with much less variability than in genomic DNA sources, suggesting that the ability of the Full approach to fit amplification curves is dependent on DNA source. Fwin and Swin approaches, which use truncated data sets that do not include the early and late plateau stages of the reaction, predicted efficiencies with less variability for a given target indicating better fitting than with the Full approach.

The Fwin and Swin approaches yielded more consistent efficiencies across the four DNA sources for each primer than did the Full approach (Figure 4.3), which is desirable in selecting an approach that relies on cloned DNA to quantify genomic DNA. For example, the Fwin and Swin approaches showed no significant differences (p<0.05) among efficiencies from different DNA sources for the PSU and UNI primers although this was not the case with RZB and VIT primers. The Full fit clone isolate DNA efficiencies were significantly different from the genomic mixed DNA efficiencies for all primers, and from genomic isolate DNA for PSU and RZB primers (p<0.05). However, clone isolate DNA efficiencies were not significantly different from clone mixed DNA for all primers and fitting approaches. These results demonstrate that DNA sources generally affect calculated efficiencies, indicating that qPCR reaction kinetics differ with DNA sources.

124 This violates the assumption of the Ct approach that all samples amplify with the same efficiency as standards (typically clone isolate DNA) for a given primer.

4.3.2. Cell copy numbers of 16S rRNA gene

The accuracy of the different fitting approaches for quantifying target DNA was evaluated by calculating the absolute value of the percent error in calculated log copy number (log copy number error) according to Equation 4.7:

calculatedlog copies expectedlog copies Logcopynumbererror= (4.7) expectedlog copies ൫ ሺ ሻ൯െ൫ ሺ ሻ൯ ቆ ቇ ൈ ͳͲͲ ൫ ሺ ሻ൯

While the clone standard copy numbers were known, an estimate of gene copy numbers per cell (Table 4.4) for each isolate was required to calculate log copy number error in the genomic DNA samples (Equation 4.7). Cell copy number estimates were determined for each isolate-fitting approach combination. For sigmoidal approaches, 16S rRNA gene copy numbers were determined using a diagnostic point (second derivative maximum) instead of predicted initial fluorescence because predicted initial fluorescence was found to be highly error-prone, as described below. Calculated cell copy numbers of the 16S rRNA gene were from 6.54 to 12.80, which was within ranges reported for bacteria (e.g., 1-15 copies cell-1 (Rainey et al., 1996; Klappenbach et al., 2000).

125 Table 4.4. Cell copy numbers of 16S rRNA genes based on Table 4.4. amplificationCell copy numbers of isolate of 16Sgenomic rRNA DNAgenes with based isolate-specific on amplification of isolate genomic DNAprimers, with isolate-specificestimated by the primers, Ct approach estimated or sigmoidal by the fitting Ct approach or sigmoidal fitting withwith secondsecond derivativederivative maxima maxima asas aa diagnostic point point. .

Fit Organism EstimatedCellCopies Ct Pseudomonas 9.68 ± 0.35 Martelella 7.67 ± 1.05 Vitellibacter 7.30 ± 1.05

Full Pseudomonas 12.80 ± 0.94 Martelella 10.17 ± 1.01 Vitellibacter 7.81 ± 1.02

SiSwin PdPseudomonas 9.26 ± 0.72 Martelella 11.60 ± 0.90 Vitellibacter 7.76 ± 0.77

Fwin Pseudomonas 10.98 ± 0.46 Martelella 11.95 ± 0.91 Vitellibacter 6.54 ± 0.91

4.3.3. Quantitation with isolate-specific primers The log copy number errors calculated for the isolate-specific primers, evaluated for clone and genomic mixtures (listed in Table 4.1) and for genomic isolate DNA, are presented in Figure 4.4. This log-based approach was used because of the exponential nature of the qPCR method. Errors in terms of non-log numbers can be calculated from the log copy number errors and the expected copy numbers. To give an indication of the magnitude of the non-log errors, note that a log copy number error of ± 10% with expected 10^3 copies/L reflects an error of -50 to +100%, while when 10^7 copies/L is expected, the error is -80 to +401%. For the sigmoidal fitting approaches, quantitation based on initial fluorescence predictions consistently yielded greater errors than quantitation based on the second derivative maxima for all isolate-specific primers and DNA sources.

126 a. 100 Clone mixed DNA Initial 90 Diagnostic point ﬂuorescence 80 70 Ct Full 60 Full Swin 50 Swin Fwin 40 30 Fwin 20 log copy number error log copy 10 0 PSU RZB VIT b. 100 160.7 Genomic isolate 90 DNA 80 70 60 50 40 30 20 log copy number error log copy 10 0 PSU RZB VIT c. 100 104.6 Genomic mixed 90 DNA 80 70 60 50 40 30 20

log copy number error log copy 10 0 PSU RZB VIT

FigureFigure 4.4. 4.4. Log copy numbernumber errorerror for for clone clone (a) (a) and and genomic genomic (b (b and and c) c) DNA DNA sources sources amplified amplifiedwith isolate-specific with isolate-specific primers and primers analyzed and with analyzed Ct, Full, with Swin Ct, and Full, Fwin Swin using and diagonistic Fwin using points diagonistic(cycle threshold points for (cycle Ct, second threshold derivative for Ct, secondmaxima derivativefor all others) maxima or initial for all fluorescence others) or (Full, initialSwin andfluorescence Fwin only). (Full, Log copySwin numberand Fwin error only). was Log calculated copy number by Equation error was4.6. calculated by Equation 4.6.

127 This finding was most apparent for RZB targets in genomic DNA sources, where log copy number errors from quantitation by initial fluorescence were 71.7% and 96.2% for mixed and isolate samples, respectively, compared to 6.33% and 3.25%, respectively, from quantitation by diagnostic point. Because quantitation based on initial fluorescence predictions yielded relatively high errors, further comparisons for isolate-specific assays focused on the Ct and diagnostic point approaches.

Log copy number errors ranged from 1.43% to 16.8% for the diagnostic point approaches (Ct and sigmoidal fitting; Figure 4.4). With the exception of the Fwin approach applied to samples amplified with the PSU primer, combinations of primer and fitting approaches showed statistically significantp ( < 0.05) log copy number errors across DNA sources, with the smallest errors observed for the clone mixed DNA. Greater errors observed with genomic DNA may be due to interference of non-target DNA in the qPCR reaction. When Ct and diagnostic point approaches were compared for both clone and genomic DNA amplified with isolate-specific primers, log copy number errors from the Ct approach were greater than any of the sigmoidal fitting-diagnostic point approaches, however this trend was only significant p( <0.05) for genomic mixed DNA.

4.3.4. Quantitation with universal primer

Quantifying total 16S rRNA gene copy numbers in mixed samples is used as a measurement of the entire bacterial population, and is needed where individual populations are expressed as a fraction of a total population. However, qPCR quantitation of mixed populations using the UNI primer presents unique challenges for approaches that rely on a standard curve (e.g., the Ct and sigmoidal fit-diagnostic point approaches). With three different templates in the mixtures, there were three different UNI standard

128 curves that could be applied to qPCR data, yielding three different calculated total 16S rRNA gene copy numbers for each fitting approach. Using any one isolate’s standard curve to quantify total 16S rRNA gene copy numbers for the other isolates assumes that all the isolates amplify with the same kinetics, which is not necessarily the case (e.g., Smits et al., 2004), as observed in the above comparisons of efficiencies (Figure 4.3).

Several ways to determine total 16S rRNA gene copy numbers for the clone and genomic mixtures were evaluated: (1) by each isolate’s UNI standard curve, (2) as an average of the three values calculated from the three UNI standard curves, (3) as the sum of the copy numbers quantified with isolate-specific primers (i.e., not reliant on a UNI primer), and (4) by predicted initial fluorescence (sigmoidal fits only) (Figure 4.5). A weighted average approach was also evaluated, in which the contribution of the total 16S rRNA gene copy numbers from any one isolate’s standard curve was proportioned by the fraction that isolate theoretically comprised in the mixture (data not shown). However, this approach was not a significant improvement over the unweighted average approach for the mixtures considered in this study, and in any event required a-priori knowledge of the mixture contents.

Log copy number errors were generally lower for clone mixed DNA than for genomic mixed DNA for a given fit-total copy number calculation combination, with the consistent exception of quantitation by the VIT standard curve for all four fitting approaches (Figure 4.5). The most striking differences between clone and genomic mixed DNA were found for quantitation by initial fluorescence. For the genomic mixed DNA, the log copy number errors were 7.91%, 16.7% and 30.8% for Fwin, Swin and Full fits, respectively, compared to 5.74%, 6.44% and 8.36% for the same fits of the clone mixed DNA. These results corroborate the finding above for the isolate-specific primers (Figure

129 4.4) that initial fluorescence predictions yielded higher errors than the diagnostic point approaches, particularly for genomic DNA.

For clone mixed DNA, total gene copy quantitation by the sum of the copy numbers quantified with isolate-specific primers provided the lowest error (1.66%-1.85%) (Figure 4.5). This was also generally true for the Full, Swin, and Fwin approaches for the genomic mixed DNA, although use of the Rhizobiales standard curve yielded similar error for the Swin and Fwin approaches. The single case where the sum of the isolates yielded significantly higher log copy number error (7.18%) than any other approach to quantify total 16S rRNA gene copy numbers occurred with the Ct approach applied to the genomic mixed DNA, for which quantitation by VIT standard curve resulted in the lowest log copy number error (3.59%). These results suggest that, in mixtures for which taxonomic groups are quantifiable by isolate-specific primers, total 16S rRNA gene copy number is most accurately obtained by summing copy numbers of each group determined by group-specific primers; however, such well-defined populations may be uncommon in environmental samples.

Other options for total 16S rRNA gene copy number quantitation include using a single standard curve based on one of the taxonomic groups (i.e., dilution series of clone DNA containing the 16S insert of the taxonomic group) or an average of the copy numbers determined using the standard curves of all known taxonomic groups in the mixture. Of these options, quantitation using an average of values obtained by the standard curves may present less bias. In this study, log copy number error ranged from 4.09%- 6.23% in clone mixed isolate DNA and 4.93%-6.57% in genomic mixed DNA, depending on the fitting approach used (Figure 4.5).

130 a. 35 Clone mixed DNA 30 25 20 15 10

number error log copy 5 0 Ct Full Swin Fwin

b. 35 Genomic mixed DNA 37.3 30 25 20 15 10

log copy number error log copy 5 0 Ct Full Swin Fwin Sum of isolates Average of values from standard curves By Pseudomonas standard curve By Martelella standard curve By Vitellibacter standard curve Initial ﬂuorescence

Figure 4.5. Log copy number error for clone (a) and genomic (b) mixed DNA ampli- Figure 4.5. Log copy number error for clone (a) and genomic (b) mixed DNA amplified fied with universal primer and analyzed with the Ct, Full, Swin and Fwin approaches. with universal primer and analyzed with the Ct, Full, Swin and Fwin approaches. Total Total gene copies are calculated as the sum of gene copies of isolates in the mixture genedetermined copies are with calculated isolate-specific as the sum primers of gene (Sum copies of isolates), of isolates based in the on Pseudomonasmixture deter-, minedMartelella with isolate-specific or Vitellibacter standardprimers (Sum curves, of isolates), as an average based of on values Pseudomonas obtained, Martelella by the orstandard Vitellibacter curves, standard and by curves, initial asfluorescence an average (Full, of values Swin obtainedand Fwin byfits the only). standard Log copy curves,number and error by initial was calculated fluorescence by Equation (Full, Swin 4.7. and Fwin fits only). Log copy number error was calculated by Equation 4.7.

131 For genomic mixed DNA, log copy number error for quantitation by average of standard curve values was not significantly different across Fwin, Swin, Ct and Full approaches. For clone mixed DNA, log copy number errors for quantitation using the average of standard curve values were significantly lower p( <0.05) for Fwin and Ct than Swin, while values for Full were not significantly different from other fitting approaches. Based on these results, use of the average of standard curve values to determine total 16S rRNA gene copy numbers is recommended as a reasonable approach when summing copy numbers from all taxonomic groups in the community is not feasible.

4.3.5. Asymmetry parameter f

The 5-parameter sigmoidal model used in this study incorporates a parameter (f) to account for asymmetry in the qPCR curve (see Figure 4.6). When all other model parameters are held constant, f = 1 signifies a symmetrical curve,f < 1 signifies a curve with a less steep slope prior to the first derivative maximum than after, and f >1 signifies a curve with a steeper slope prior to the first derivative maximum than after (Figure 4.6). Given the recent introduction of this model for qPCR analysis (Spiess et al., 2008), little research has reported on amplification curve asymmetry. In this study, the f parameter significantly differed from 1 (p<0.05) in 43 of the 48 (89.6%) DNA source-primer-fitting approach combinations (Figure 4.7), indicating that qPCR reaction curves are typically asymmetric. Where f ≠ 1, 90% of samples yielded f > 1. Genomic mixed DNA analyzed with the Full approach showed the greatest variability in predicted f, a trend similar to that observed for efficiency (Figure 4.3), and that likely resulted from poor fitting of curves that do not exhibit a clear plateau stage (Figure 4.2). The greatest variability in predicted f was found for genomic mixed DNA analyzed with the Full approach, which fit all qPCR cycles.

132 0.8

0.7

0.6

0.5 First Second f Fit derivative derivative 0.4 0.5

uorescence 1.0 F l 2.0

v e 0.3 5.0 Experimental data R elati 0.2

0.1

0.0 0 10 20 30 40 Cycle Figure 4.6. Effect of the sigmoidal model asymmetry parameter f Figure 4.6. onEffect curve shapesof the sigmoidal of the fit (solidmodel lines), asymmetry first derivatives parameter f(dashed on curve shapes of the fit (solidlines) lines), and firstsecond derivatives derivatives (dashed (dashed-dotted lines) and secondlines) of derivatives qPCR reac- (dashed-dotted 6 lines) of qPCRtion reaction fluorescence fluorescence from genomic from isolategenomic DNAisolate from DNA106 Pseudomonasfrom 10 Pseudomonas cells amplifiedcells amplifiedwith PSU withprimer. PSU Curves primer. for Curves experimental for experimental data ( ) and data actual () fit (f=2.0) are shown andin black. actual fit (f=2.0) are shown in black.

133 - f =1, f =1, the qPCR * * * * * UNI UNI * ) than 1 (p<0.05). When ○ ○ p <0.05). When * VI T VI T * * * * ) or lesser ( * RZ B RZ B * * * * U U Genomic mixed DNA * * PS PS Genomic isolate DNA * * c. d.

8 6 4 2 0 8 6 4 2 0

12 10 12 10

r aramete p f r e t e m a r pa f * * * * Full Swin Fwin * * UNI UNI * ○ ○ * * VI T VI T * * * * * RZ B RZ B * * U U * * parameters from Full, Swin and Fwin log-logistic five-parameter sigmoidal fits for (a) clone isolate DNA (standards), DNA (standards), for (a) clone isolate sigmoidal fits five-parameter and Fwin log-logistic Full, Swin from f parameters PS PS * Clone isolate DNA * Clone mixed DNA parameters from Full, Swin and Fwin log-logistic five-parameter sigmoidal fits for (a) clone isolate DNA (standards), (standards), DNA for (a) clone isolate sigmoidal fits five-parameter and Fwin log-logistic Full, Swin from f parameters b. a.

8 6 4 2 0 8 6 4 2 0

12 10 12 10

r e t e m a r pa f r aramete p f Figure 4.7. Figure VIT) and RZB, (PSU, DNA amplified with isolate-specific mixed DNA and (d) genomic isolate DNA, (c) genomic (b) clone mixed ( greater f is significantly that indicate bars above Symbols (UNI) primers. universal the qPCR amplification curve is symmetrical and the fit is equivalent to a four-parameter sigmoidal model. four-parameter to a and the fit is equivalent symmetrical curve is the qPCR amplification amplification curve is symmetrical and the fit is equivalent to a four-parameter sigmoidal model. a four-parameter to and the fit is equivalent symmetrical curve is amplification is significantly greater (*) or less (  ) than 1 ( greater f is significantly that indicate bars above Symbols (UNI) primers. versal Figure 4.7. Figure VIT) and uni RZB, (PSU, DNA amplified with isolate-specific mixed DNA and (d) genomic isolate DNA, (c) genomic (b) clone mixed

134 4.4. Di s c u s s i o n

This research evaluated a conventional approach (Ct) and alternative approaches (Full, Swin, Fwin) based on a 5-parameter sigmoidal model for analyzing SYBR-Green qPCR data from amplification of clone and genomic DNA present as single or mixed templates.

QPCR reaction behavior was influenced by multiple factors including DNA source, primer and fitting approach. Comparing reaction kinetics of DNA sources to those of clone isolate DNA is particularly instructive because clone isolate DNA is commonly used as standards for qPCR. The largest discrepancies in kinetics were observed for genomic mixed DNA compared to clone isolate DNA, particularly for the Full approach, as evidenced by differences in values and variances in efficiencies and f parameters (Figures 4.3 and 4.7). The fluorescence drift in late reaction stages observed for many genomic mixed DNA samples (Figure 4.2) provides additional evidence that genomic mixed DNA amplifies with different kinetics than clone qPCR standards used for quantitation. Dis- crepancies were generally less for genomic isolate DNA, and they were least for clone mixed DNA, the source most similar to qPCR standards. The reasons for these differences remain to be determined, but reaction kinetics may be dependent on the total amount and/or complexity of target and non-target DNA in the reactions.

Prior to the first application of the 5-parameter sigmoidal model (Equation 4.3) to qPCR by Spiess et al.( 2008), asymmetry was not considered in modeling the qPCR reaction curves. Spiess et al.(2008) demonstrated superior performance of the 5-parameter model over the symmetric 4-parameter sigmoidal model (Equation 4.2; Rutledge, 2004; Rutledge and Stewart, 2008), which is analogous to the 5-parameter model where f=1. In this research, the asymmetry parameter f allowed for improved fitting of the sigmoi-

135 dal model to qPCR amplification curves, as evidenced by the majority of samples with f≠1, particularly for genomic mixed DNA samples (Figure 4.7). Reasons for asymmetry in amplification curves remain unclear and require further research, but they may be related to sample characteristics such as the total amount and/or nature of sample DNA, to reagent depletion or to enzyme inactivation.

Preferred approaches for qPCR data analysis in the study of mixed bacterial communities should provide accurate and reliable quantitation of targets such as the 16S rRNA gene. The approaches compared in this research included the conventional Ct approach and sigmoidal fitting approaches that offer the possibility of using either predicted initial fluorescence or a diagnostic point for quantitation. No studies have been previously published that compare diagnostic point and initial fluorescence approaches in quantifying multiple targets in mixtures of DNA from different bacterial taxa. Spiess et al. (2008), using the 5-parameter model, found quantitation of cDNA targets using predicted initial fluorescence generally less accurate and precise than quantitation using the second derivative maximum as a diagnostic point. Likewise, in the current study, quantitation using the second derivative maximum was clearly superior to quantitation by predicted initial fluorescence, which yielded larger log copy number errors with greater variability for most fit-primer-DNA source combinations (Figure 4.4). However, research by Rutledge (Rutledge, 2004; Rutledge and Stewart, 2008), using a 4-parameter model, demonstrated improved quantitative accuracy using initial fluorescence over the conventional Ct approach for cDNA and lambda DNA targets. The reasons for the differences in the findings of these studies are not clear, but they may suggest differences in optimal applications of the 4-parameter and 5-paramter models, or they may be related to differences in qPCR equipment, reagents and sample characteristics.

136 All sigmoidal fitting-diagnostic point approaches were superior quantitatively to the conventional Ct approach based on their significantly lower log copy number errors, although quantitation by the Ct approach was slightly less accurate than sigmoidal-fitting approaches despite invalidation of the approach’s assumptions regarding efficiencies. This finding supports the use of the Ct approach in cases where sigmoidal fitting approaches are not practical, for example, when fitting cannot be readily automated for high-throughput. Among the sigmoidal fitting-diagnostic point approaches, no single method of data truncation was clearly superior quantitatively for all primers and DNA sources. However, Fwin and Swin approaches, which excluded ground and plateau cycles in fitting, are recommended over the Full approach because of their improved fits of the data, resulting in more reliable kinetic parameters.

Approaches for assessing total 16S rRNA gene copy numbers in a mixed bacterial community by qPCR must deal with the challenge of including targets from multiple bacterial groups, which may amplify with different kinetics. As explained above, when a primer is used that targets multiple bacterial strains (here, UNI), the question of what standard curve to use arises. Ideally, quantitation by initial fluorescence would bypass this problem, however this approach yielded higher errors than other approaches for genomic mixed isolate DNA, particularly for Swin and Full fits (Figures 4.4 and 4.5).

The sum of copy numbers obtained by each of the isolate-specific primers yielded the lowest error of all approaches for both clone and genomic mixed DNA (Figure 4.5). However, the utility of this approach is limited to mixtures in which all templates are known and can be quantified by qPCR. For complex microbial communities, such as those found in environmental matrices, this may not be possible, and the use of a universal primer is the only practical means to quantify total 16S rRNA gene copies. The results from this study suggest that using the average of the total 16S rRNA gene copies

137 obtained by all the standard curves may be a reasonable alternative for genomic mixed DNA, since this approach yielded only slightly higher errors than summing quantities from isolate-specific primers.

4.5. Co n c l u s i o n

This study demonstrated that sigmoidal fitting of qPCR data using calculated second derivative maxima as diagnostic points performs better than the conventional Ct approach for quantitation of bacterial 16S rRNA gene copy numbers based on analyses of well-defined clone and genomic DNA mixtures. Although quantitation by initial fluorescence predicted from sigmoidal fitting offers freedom from standard curves, this approach yielded the largest quantitative errors in this study. Sigmoidal fitting of the entire amplification curve (Full), especially for genomic DNA, resulted in greater variability in efficiency and the asymmetry parameter f than fitting a truncated curve from which early and late plateau stages have been trimmed by either statistical selection of beginning and end cycles (Swin) or using a set range of cycles (Fwin). While all sigmoidal fitting approaches using a diagnostic point (second derivative maximum) generally yielded lower errors compared to the Ct approach, approaches using truncated data sets (Fwin, Swin) are recommended because of their lower variability in calculated efficiencies and kinetic parameters such as f. Overall, these results provide guidance for the analysis of qPCR data obtained in the investigation of environmental samples, and supports its utility in this growing application.

138 Chapter 5. UV treatment of DBT and its biodegradation products

5.1. In t r o d u c t i o n

Biodegradation of polycyclic aromatic hydrocarbons (PAHs), whether under natural or engineered conditions, plays an important role in contaminant fate in contaminated environments and often involves mixed microbial communities. Sulfur-containing polycyclic aromatic hydrocarbon, such as the model compound dibenzothiophene (DBT), can be recalcitrant to biodegradation, and are not always completely mineralized, resulting in formation of numerous degradation products whose characteristics and fates are poorly characterized. Although bacterial isolates often degrade DBT along a well-defined pathway and produce a limited number of DBT degradation products (e.g., Kodama et al., 1973; Bressler et al., 1998; Seo et al., 2002), degradation of DBT by mixed bacterial communities can follow multiple pathways leading to a complex mixture of degradation products, as observed in Chapter 3 (Table 3.1; Figures 3.3-3.18).

Extremely slow or incomplete biodegradation of contaminants is usually not acceptable for remediation purposes. Successful remediation requires a reduction in hazard, which is not always achieved with bioremediation. Several bench-scale and field studies have reported transient or lasting increases in toxicity, an indicator of hazard, with PAH biodegradation that were often attributed to degradation products (Belkin et al., 1994; Phillips et al., 2000; Ahtiainen et al., 2002). As discussed in Chapters 2 and 3, DBT biodegradation by a mixed bacterial community more than doubled toxicity to the bioluminescent bacteria Vibrio fischeri within the first few days of degradation, and did not reduce toxicity below that of DBT itself even when 91% of initial DBT was degraded

139 (Figures 2.2, 2.3). These results indicated that one or more DBT degradation products were toxic.

Reports of incomplete biodegradation and increases in toxicity indicate that biodegradation alone may not be sufficient to achieve remediation goals. Conventional alternatives to biodegradation, such as excavation and off-site disposal or containment, may not be desirable because of their expense (e.g., 250-2000 m-3; Mulligan, 2002) or because of uncertainty regarding long-term effectiveness (as may be the case with containment approaches). Novel alternatives to biodegradation may include combining biodegradation with a second treatment step. In aqueous or slurry systems, UV light may be an effective means to break down original contaminants and degradation products remaining after biodegradation.

Most studies exploring combined UV and biodegradation employ UV as a pretreatment (Lehto et al., 2003; Guieysse and Viklund, 2005). Fewer studies have addressed UV treatment following biodegradation as a sequential treatment process. Karetnikova et al. (2008) found that biodegradation by Penicillium tardum strain H-2 eliminated the test contaminant p-cresol while subsequent UV irradiation from a high pressure mercury lamp greatly reduced its biodegradation products. The only investigation of sequential biodegradation-UV treatment for DBT was conducted by Chamberlin (2005), who found that some DBT biodegradation products, formed by the mixed microbial culture that is the focus of this dissertation, were susceptible to UV treatment using a medium pressure UV source. However, Chamberlin did not evaluate DBT losses or identify DBT degradation products.

This study builds on the findings of Chamberlin (2005) and investigates application of UV treatment following biodegradation of DBT by a mixed microbial culture under the hypothesis that UV treatment may reduce the concentration of DBT and its

140 degradation products remaining after biodegradation, and subsequently reduce residual toxicity. Specific objectives of this study were to:

1. Compare the effectiveness of UV light in reducing DBT levels in both an aqueous solution of pure DBT, and in media from a mixed microbial culture following DBT biodegradation.

2. Determine how UV changes the toxicity of DBT experimental solutions using a bioluminescent bacterial assay (a non-specific acute toxicity screening test) and an assay that evaluates cardiac development in Fundulus heteroclitus embryos.

3. Monitor and identify products formed by UV treatment of DBT and compare to products formed via biodegradation alone.

By combining chemical analyses with toxicity assays, this research addresses two potentially limiting factors affecting the success of remediation techniques: contaminant reduction and hazard amelioration. By applying this approach in the evaluation of post- biodegradation UV treatment of DBT and its degradation products, this research aids in advancing novel remediation strategies for commonly recalcitrant contaminants such as DBT.

141 5.2. Ma t e r i a l s a n d m e t h o d s

5.2.1. Preparation of test solutions

All test solutions in this study were based on the artificial seawater media (artificial seawater, pH 7.55, supplemented with NH4NO3, K2HPO4 and FeCl3•6H2O as described in Chapter 2) used to culture the microbial community that degraded DBT and formed its degradation products. Effect of UV treatment was evaluated in three test solutions: (1) freshly made culture containing no DBT or DBT degradation products (“Control solution”), which was used as a control; (2) freshly made culture containing DBT at its apparent solubility limit of 1.5 μM in the artificial seawater media, (“DBT solution”), and (3) culture media from the DBT-degrading microbial community collected at 4, 6, 8, 10, 12 and 16 d after inoculation, combined and stored in amber glass bottles the dark at -40°C until use (up to 3 months) (“Post-biodegradation solution”). Preliminary analyses of solutions stored under these conditions indicated that products were stable beyond 3 months. All solutions were adjusted to pH 7.55 and filtered through 0.2 µm polycarbonate membranes to ensure solutions contained no particulates or microbial cells.

5.2.2. UV exposures

Low pressure (LP) UV irradiation was conducted using a quasi-collimated beam apparatus fitted with 15W Hg vapor germicidal lamps (General Electric G15T8) emit- ting monochromatic UV light at 254 nm (Sharpless and Linden, 2003). Although the LP lamp does not emit light near the UV absorption maximum for DBT (234 nm), DBT does absorb some light at 254 nm (Figure 5.1).

142 60000 1.0

50000 y DBT LP lamp 0.8 t s i n e 40000 t n ) I

-1 0.6 v e ti cm 30000 a l -1 r e

(M 0.4 p

20000 m a l

0.2 V 10000 U Molar absorption coeﬃcient

0 0.0 200 250 300 350 Wavelength (nm)

Figure 5.1. UV spectra of molar absorption of dibenzothiophene (1.5 μM) in artificial seawater medium (DBT solution) and the low-pressure mercury vapor UV lamp used for treating test solutions.

UV exposure times needed to achieve UV fluences of 0, 500, 1250 and 2000 mJ

cm-2 were determined based on incident UV irradiance at the surface of the sample, average irradiance over the entire volume of the sample, and initial UV absorbance of the sample. Here fluence is defined as the amount of photons from the UV source, expressed in terms of energy, reaching the surface of the test solution. Incident UV ir-

radiance (in mW cm-2) was measured in the center of the collimated beam at the height of the sample solution surface using a calibrated UV radiometer (IL1700, SED 240/W, In- ternational Light, Peabody, MA). UV absorbance spectrum of the sample was measured for a 0.5 mL aliquot of the sample in a quartz cell using a Cary Bio100 spectrophotom-

eter (Varian, Inc., Palo Alto, CA). Average UV irradiance (in mW cm-2) for the sample was determined from the initial UV absorbance of the sample, sample depth and incident UV irradiance. Exposure times for desired UV fluences were calculated as:

143

UV uence, mJ cmͲ2 Exposure Ɵme, s= Ͳ2 (5.1) Average UV irradiance,mW cm

For exposures at 0, 500, 1250 and 2000 mJ cm-2, 85 mL of test solution was placed in an uncovered 70 x 50 mm Pyrex glass crystallization dish. Sample depth was

2.2 cm, and surface area was 34.2 cm2. A small Teflon-coated stirbar was used to gen- tly mix the solution without disturbing the surface. The sample dish was placed in the center of the collimated beam on a stirplate and the solution surface was allowed to become still before beginning the exposure. Samples receiving 0 mJ cm-2 were prepared in the same manner and placed in the apparatus for five minutes in the dark to serve as UV dose controls. After exposure, the sample was immediately removed from the UV apparatus, 1.8 mL was transferred to a glass vial for toxicity assays using bioluminescent bacteria Vibrio fischeri, 15 mL was placed in an amber glass bottle for liquid-liquid extraction of DBT and degradation products, and the remaining solution was reserved in a separate amber glass bottle for toxicity assays using Fundulus heteroclitus embryos. Ali- quots taken for toxicity assays were immediately frozen at -40°C until analysis. Aliquots (15 mL) taken for extraction were acidified to pH < 2 with 6 M HCl and extracted with dichloromethane (DCM), and were prepared for and analyzed by GC/MS as described in Chapter 3. All test solution-UV fluence combinations were repeated in triplicate. Expo- sure of test solutions to plastics was minimized at all stages of preparation, sampling and analysis.

144 5.2.3. Toxicity to Fundulus heteroclitus embryos and Vibrio fischeri

Two assays using different species were used to evaluate the effects of UV fluence on toxicity. Inhibition of luminescence in the prokaryoteVibrio fischeri was conducted on aliquots taken after exposures as described in Chapter 2. This assay does not target a specific toxic mechanism but rather reflects a general impairment of the -me tabolism of the organism. A second test, described in Matson et al. (2008), was included using Fundulus heteroclitus (killifish) embryos to evaluate effects on cardiac development in an aquatic vertebrate. Adult killifish were collected at an uncontaminated reference site on King’s Creek in southeastern Virginia (37°17’52.4’’N, 76°25’31.4’’W). Care of the killifish used for spawning in this assay is described in Matson et al. (2008). For this assay, fish were spawned manually and fertilized in vitro. Eggs were incubated at 28.5°C and then screened at 24 h post fertilization for normal development. Normal embryos at neurula stage were selected for the assay. Each embryo was placed in 5 mL of the test solution in a 20 mL glass scintillation vials at room temperature and the vial was placed into an incubator at 28.5°C. For each test solution-UV fluence sample replicate, 10 embryos were dosed and scored. Embryos screened for cardiovascular developmental defects were scored at 7 days after fertilization, or 6 days after dosing. Observed defects were scored 0 (normal), 1 (mild deformities, including elongation between atrium and ventricle, reduction of atrial volume and rotation of heart chambers ) or 2 (severe deformities, including exacerbation of all “mild deformities” plus elongation of ventricle and possible loss of atrium). The cardiac defect scoring scale correlates to hatching success, with a score of 2 indicating no hatching, and a score of 1 indicating approximately 40- 60% reduction in hatching (Matson et al., 2008).

145 Statistical analyses, including linear regression in determining phototransformation rates and treatment comparisons, were performed using JMP 7.0 software (SAS Inc., 2007).

5.3. Re s u l t s

5.3.1. Photolysis of DBT

Trends of DBT and its biodegradation products in UV irradiated test solutions are shown in Figures 5.2 and 5.3. Effects of UV fluence on DBT were evaluated in DBT-satu- rated fresh Post-biodegradation solution (“DBT solution”) and in media collected periodi- cally during DBT biodegradation by a mixed microbial community (“Post-biodegradation solution”) (Figure 5.2a). Initial concentrations of DBT in DBT solution and Post-biodegradation solution were 1.49±0.13 µM and 0.24±0.03 µM, respectively. In both test solutions, DBT concentrations decreased with increasing UV fluence, the highest of which

(2000 mJ cm-2) reduced initial DBT concentration by 28% (1.08±0.23 µM final concentration) in DBT solution and 81% (0.045±0.016 µM final concentration) in Post-biodegradation solution (Figure 5.2a). In solutions similar to the DBT solution in which only 28% DBT was lost at the highest fluence, reduction of DBT by UV alone would require extensive dosing that may not be practical for contaminant treatment.

146 a. b. S O O 2 (15) 2 S * (21) 1 1 μM μM Post-biodegradation solution DBT solution 0 0 0 500 1000 1500 2000 0 500 1000 1500 2000 UV Fluence (mJ/cm2) UV Fluence (mJ/cm2)

c. O d. 20 0.3 25 * S (22) S O 15 20 (9) 0.2 15 10 μM O 0.1 10 5 5 Relative Response Relative

0 0.0 Response Relative 0 0 500 1000 1500 2000 0 500 1000 1500 2000 UV Fluence (mJ cm-2) UV Fluence (mJ cm-2)

e. f. S 20 0.03 20 (6) 0.03 S OH 15 15 OH (5) 0.02 0.02 10 10 0.01 0.01 5 5

Relative Response Relative 0 0.00 Response Relative Response Relative 0 0.00 Response Relative 0 500 1000 1500 2000 0 500 1000 1500 2000 UV Fluence (mJ cm-2) UV Fluence (mJ cm-2)

g. S OH h. 20 (11) 0.03 4 S * (14) O OH 0.02 10 2

μM μM OH 0.01

0 0.00 Response Relative 0 0 500 1000 1500 2000 0 500 1000 1500 2000 UV Fluence (mJ cm-2) UV Fluence (mJ cm-2)

Figure 5.1. Eﬀect of UV ﬂuence on (a) DBT, (15) DBT sulfone (21), (c) DBT sulfoxide (22), (d) Figurebenzothiophene-2,3-dione 5.2. Effect of UV (9fluence), (e) 2-hydroxybenzothiophene on (a) DBT (15), DBT (5 ),sulfone (f) 3-hydroxybenzothiophene (21), (c) DBT sulfoxide (6), (g) (22), (d) benzothiophene-2,3-dione2,3-dihydroxybenzothiophene (11 )( 9and), (e) (h) 3-hydroxy-1-benzothiophen-2-one2-hydroxybenzothiophene ((514),) in(f) DBT 3-hydroxyben media and - Culture media. Relative responses were determined using 2-naphthol (8) as an internal standard. zothiopheneStarred (*) products(6), (g) were2,3-dihydroxybenzothiophene only observed in the culture media. (11 Arrows) and point(h) 3-hydroxy-1-benzothio to y-axis associated with - phen-2-onethe data series. (14) inNumbers DBT solution in bold italics and refer Post-biodegradation to entries in Table 3.1. solution. Relative responses were determined using 2-naphthol (8) as an internal standard. Starred (*) products were only observed in the Post-biodegradation solution. Arrows point to y-axis associated with the data series. Numbers in bold italics refer to entries in Table 3.1.

147 O S a. b. OH 2 Post-biodegradation solution 1.5 (17) O S O 1.0 HO 1 (13) 0.5 OH Relative Response Relative 0 Response Relative 0.0 0 500 1000 1500 2000 0 500 1000 1500 2000 UV Fluence (mJ cm-2) UV Fluence (mJ cm-2)

c. d.

5 OH 5 SH OH (7) 4 (1) 4 O O 3 3 μM μM 2 2 1 1 0 0 0 500 1000 1500 2000 0 500 1000 1500 2000 UV Fluence (mJ cm-2) UV Fluence (mJ cm-2)

f. e. O 0.4 O 0.6 O S HO (25) 0.4 S 0.2 S OH μM OH 0.2 (26) O O Relative Response Relative 0.0 0 0 500 1000 1500 2000 0 500 1000 1500 2000 UV Fluence (mJ cm-2) UV Fluence (mJ cm-2)

g. h. 20 O (25) 4 S Unknown M+ 284 m/z 3 (27) S 10 O 2 μM 1

0 Response Relative 0 0 500 1000 1500 2000 0 500 1000 1500 2000 UV Fluence (mJ cm-2) UV Fluence (mJ cm-2) Figure 5.2. Effect of UV fluence on (a) benzothiophene carboxylic acid (13), (b) benzothiophene-2,3- Figuredicarboxylic 5.3. Effect acid (17 ),of (c)UV benzoic fluence acid (1on), (d)(a) thiosalicylic benzothiophene acid (7), (e) carboxylic 3-hydroxy-1-benzothiophene-2 acid (13), (b) ben- + zothiophene-2,3-dicarboxyliccarbaldehyde (12), (f) dithiosalicylic acid acid (17 (26), (c)), (g) benzoic thioindigo acid (25) (and1), (h)(d) an thiosalicylic unknown with acid M 284(7), m/z(e) (27) in culture media. Relative responses were determined using 2-naphthol (8) as an internal stan- 3-hydroxy-1-benzothiophene-2-carbaldehydedard. None of these products were observed in artificial (12), seawater (f) dithiosalicylic containing DBT acid only (26 (DBT), (g) media). thio- indigoNumbers (25) and in bold (h) italics an unknown refer to entries with in MTable+ 284 3.1. m/z (27) in Post-biodegradation solution. Relative responses were determined using 2-naphthol (8) as an internal standard. None of these products were observed in artificial seawater containing DBT only (DBT solution). Numbers in bold italics refer to entries in Table 3.1.

148 DBT phototransformation was modeled as a first-order reaction, dC/dF = -k’C, where C = DBT concentration (μM), k’ is the first order rate constant (cm2 mJ-1), and F is the UV dose expressed as fluence (mJ cm-2) (Table 5.1 and Figure 5.4). Apparent rate constant of DBT loss was higher in the Post-biodegradation solution (7.4 x 10-4 cm2 mJ-1) than in the DBT solution (1.5 x 10-4 cm2 mJ-1) (Table 5.1). The higher apparent first-order rate constan for loss of DBT in the Post-biodegradation solution is likely attributable to pathways of indirect photoloysis involving UV-absorbing species such as DBT degradation products not present in the DBT solution, as described in the Discussion section below. Due to the complex nature of the Post-biodegradation solution, however, it is difficult to determine precise photolytic mechanisms.

149 1 1 1 1 Ͳ Ͳ Ͳ Ͳ mJ mJ mJ mJ 1 1 1 1 1 Ͳ Ͳ Ͳ Ͳ Ͳ 2 2 2 2 mJ mJ mJ mJ mJ mJ k' k' cm cm cm cm 2 2 2 2 2 , a a a cm RR cm RR cm µM RR cm cm cm 3 Ͳ 4 4 4 2 4 3 3 Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ 4 Ͳ constant constant 10 0 0 10 10 10 10 10 1 10 10 x 10 x x x x x x x x x media. rate rate 4 .1 . 0.8 1.2 0.7 0.35 0.1 0.1 0 0 0 4 ± 0.5 ± ± ± ± ± ± ± ± ± 4 4 4 4 3 2 4 3 3 Culture Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ 0 0 10 10 10 10 10 10 10 1 10 10 Apparent Apparent standard. x x x x x x x x x x and 9 2 . 1.5 1.2 1.1 7.4 1.1 1.5 1. 3 3 2 2.1 internal media an as DBT in 1 1 1 used ) Order Order 8 Reaction Apparent ( products ) ) 2 Ͳ naphthol Ͳ Fitted 2 cm cm 2000 1 2000 0 1250 0 2000 1 2000 0 1250 0 2000 1250 2000 1250 2000 1 Ͳ Ͳ Ͳ of Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ 0 0 0 0 0 0 0 0 0 0 Fluence (mJ (mJ Range that degradation to on ti oss loss loss l fitted fitted Trend orma selected formation formation f f ti formation compound ) loss of and 17 ( ion ) formation DBT acid 13 ( for ) fits 6 acid quantitative ( ) of 2 27 ( dicarboxylic kinetic z Ͳ / of m ) 2,3 response carboxylic Ͳ 4 ) 22 ) ) ( 28 1 ( + 25 25 ( ( M response; ) ) acid Summary Summary of kinetic fits for DBT and selected degradation products in DBT media and Culture media. DBT media and Culture products in degradation DBT and selected for Summary fits of kinetic 15 15 media ( ( sulfoxide nown 5.1. k hydroxybenzothiophene media relative Ͳ DBT DBT DBT benzothiophene Un benzoic 3 benzothiophene thioindigo thioindigo RR: Table Compound Compound DBT Culture a Table 5.1. Table

150 Fluence (mJ cm-2) 0 500 1000 1500 2000 2.0

1.0

0.0 ) e p o n s s e

R -1.0 v e ti a l e R

o r

µM -2.0 n ( l

DBT solution: DBT -3.0 Post-biodegradation solution: DBT Unknown M+ 284 m/z (27) -4.0 benzothiophene-2,3-dicarboxylic acid (17)

Figure 5.3. Apparent ﬁrst-order kinetic ﬁts of DBT loss in DBT media and Culture Figure 5.4. Apparent first-order kinetic fits of DBT loss in DBT solution and Post-biodeg- media, and losses of benzothiophene-2,3-dicarboxylic acid (17) and an unknown DBT radationdegradation solution, product and losses(27) in Cultureof benzothiophene-2,3-dicarboxylic media. Relative response is acidbased (17) andon the an un- knownresponse DBT degradationof the quantitative product ion(27 ) toin thatPost-biodegradation of 2-naphthol (8) used solution. as an internal Relative standard response is basedin GC/MS on the analyses. response Numbers of the quantitative in bold italics referion to to that entries of 2-naphthol in Table 3.1. (8) used as an internal standard in GC/MS analyses. Numbers in bold italics refer to entries in Table 3.1.

151

5.3.2. Photolysis of degradation products in Post-biodegradation solution

5.3.2.1. Overview monitored products

Of the 27 DBT degradation products identified in the Post-biodegradation solution (Chapter 3, Table 3.1), 15 were monitored in all test solutions after treatment with UV (Figures 5.2 and 5.3). Numbers in bold italics following names of products in tables, text and figures refer to entries in Table 3.1 and chromatographic peaks in Figure 3.3. The degradation products monitored included benzoic acid (1), thiosalicylic acid (7), 2-hydroxybenzothiophene (5), 3-hydroxybenzothiophene (6), benbzothiophene-2,3- dione (9), 2,3-dihydroxybenzothiophene (11), 3-hydroxybenthiophene-2-carbaldehyde (13), 3-hydroxy-1-benzothiophen-2-one (14), DBT sulfone (21), DBT sulfoxide (22), benzothiophene carboxylic acid (12), benzothiophene-2,3-dicarboxylic acid (17), thioindigo

(25), dithiosalicylic acid (26), and an unknown with M+ 284 m/z (27). Where applicable, simple kinetics were determined for either compound formation or loss (but not both) by zero or first-order models. Apparent reaction order was assigned based on which kinetic model provided the best fit of the data. Because some compounds showed complex trends, simple kinetic values could not be calculated for all products.

Of the 15 products monitored, only 4 were observed in DBT solution following UV treatment (Figure 5.2, dashed lines): 2- and 3-hydroxybenzothiophene (5, 6), 2,3- dihydroxybenzothiophene (11), and DBT sulfoxide (22). Of these, only DBT sulfoxide (22) has been previously reported as a product of DBT desulfurization by UV light (Shiraishi et al., 1998). Although DBT sulfone (21) was also reported (Shiraishi et al., 1998), this product was not observed in the current study. Maximum levels of hydroxylated benzothiophenes (5, 6) were observed at 500 mJ cm-2 UV fluence, dissipating rapidly at higher

152 fluences (Figure 5.2 e, f, g). The presence of these compounds suggests that ring cleavage of DBT was achievable at low fluences. Ring cleavage may also have occurred at higher fluences, but hydroxylated benzothiophenes were not observed at higher fluences possibly because they were degraded faster than they were formed. Phototransfor- mation rates were not calculated for these compounds because of poor fits to the kinetic models evaluated. Photooxidation of sulfur forming DBT sulfoxide (22) increased with increasing fluence (Figure 5.2c), and was modeled with a zero-order fit (Figure 5.5) yielding an apparent rate constant of 1.2 x 10-4 relative response cm2 mJ-1 (Table 5.1). Here, relative response (“RR”), indicates the response of the quantitative ion of the compound of interest to that of 2-naphthol (8), which was used as an internal standard in GC/MS analyses. This was performed because appropriate standards needed to calculate actual concentrations were not commercially available. Because actual concentrations could not be determined for DBT sulfoxide (22) or the hydroxybenzothiophenes (5, 6), the mass balance of phototransformed DBT could not be traced, and it is possible that other photoproducts were formed but not detected in GC/MS analyses.

153 13 ) d ( i c 6 ) a c i b o x y l r 2 0 o p h e n ( a h i 2 ) o t n e c 1 ) Post-biodegradation Post-biodegradation 25 ) d e ( d ( i c . Panel b: first-order b: first-order . Panel o p h e o x i g o ( a f h i c o x y b e n z ) 1 5 0 u l o i o t n d i -2 T s o i m h y d r B h i D b e n z 3 - b e n z t . Relative responses are based responses are . Relative J c (m

e c 1 0 soltuion: n e B T u l D solution: Post-biodegradation F 5 0 Post-biodegradation solution Post-biodegradation b. 0 6 ) in ) in Culture media. Panel b: ﬁrst-order kinetic kinetic b: ﬁrst-order Panel media. 6 ) in Culture Post-biodegradation solution Post-biodegradation

0 . 5 1 . 0 1 . 5 2 . 0 3 . 0 2 . 5 2 . 0 1 . 5 1 . 0 0 . 5 0 .

- - - - ) e s n o p s e R e v ti a l e R r o ( n l µM

UV at 254 nm. Panel a: zero-order kinetic fits of DBT sulfoxide DBT sulfoxide fits of kinetic a: zero-order 254 nm. Panel UV at 25 ) in

-2

mJ cm • Response) Relative or (µM

-1 2 on based are responses Relative media. 25 ) in Culture UV at 254 nm. Panel a: zero-order kinetic ﬁts of DBT sulfoxide sulfoxide ﬁts of DBT kinetic a: zero-order 254 nm. Panel UV at -2 m 0 . 3 0 . 2 5 0 . 2 0 . 1 5 0 . 1 0 . 5 0 . J c m 2 0 ) and thioindigo ( 13 ) and thioindigo ) and 3-hydroxybenzothiophene ( 1 ) and 3-hydroxybenzothiophene ) 1 5 0 -2 m J c on second axis on second m (

e c 1 0 n e u l F 5 0 ) used as an internal standard. Numbers in bold italics refer to entries in Table 3.1. in Table entries to refer in bold italics Numbers standard. 8 ) used as an internal Apparent phototransformation rates of selected degradation products formed in DBT solution and formed in products degradation of selected rates phototransformation Apparent 0 a. formed during exposure to 0, 500, 1250 and 2000 mJ cm to during exposure formed 8 6 4 2 0

2 0 1 8 1 6 1 4 1 2 1 0

) and 3-hydroxybenzothiophene ( acid ( 1 ) and 3-hydroxybenzothiophene and beonzoic media, ( 22 ) in DBT acid ( 13 ) and thioindigo ( carboxylic ﬁts of benzothiophene 3.1. in Table entries to refer in bold italics Numbers standard. as an internal ( 8 ) used 2-napthol Figure 5.4 Apparent phototransformation rates of selected degradation products formed in DBT media and Culture media media and Culture DBT formed in products degradation of selected rates phototransformation 5.4 Apparent Figure 1250 and 2000 500, 0, to during exposure formed

mJ cm • Response) Relative or (µM

-1 2 ) in DBT solution, and beonzoic acid ( solution, and beonzoic ( 22 ) in DBT Figure 5.5. Figure solution kinetic fits of benzothiophene carboxylic acid ( carboxylic fits of benzothiophene kinetic ( on 2-napthol 154

5.3.2.2. UV effects on DBT degradation products in Post- biodegradation solution

Trends of DBT degradation products in the UV-treated Post-biodegradation solution, shown in Figures 5.2 and 5.3, fell into three general categories increasing in complexity: (1) decrease with increasing UV fluence, (2) net formation at lower fluence followed by net loss at higher fluence (e.g., lines in Figures 5.2 and 5.3 go up, then down), and (3) net loss and formation alternating with increasing fluence in a more complex trend than in (2). Here, increasing amounts of a compound were interpreted as net formation, while decreasing amounts were viewed as a net loss, since the possibility that processes of formation and loss may have been concurrent could not be excluded.

Benzothiophene-2,3-dicarboxylic acid (17) and the unidentified product with M+ 284 m/z (27) decreased with increasing fluence, with the highest fluence reducing initial concentrations of benzothiophene-2,3-dicarboxylic acid (17) by only 29% and the M+ 284 m/z product by 98% (Figure 5.3b, g). Losses of these products were fit to a first-order model (Figure 5.3). Apparent first order photolysis rate constant (Table 5.1) of the unidentified product (27, k’ = 1.9 x 10-3 cm2 mJ-1) was higher than that of of the dicarboxylic acid (17, k’ = 2.1 x 10-4 cm2 mJ-1).

Benzoic acid (1), 3-hydroxybenzothiophene (6) and thioindigo (25) increased up to 1250 mJ cm-2, but sharply decreased to zero or near initial concentrations at the highest fluence (Figures 5.1f, 5.2c,e). For these compounds, net formation was modeled across all but the highest fluence. Benzoic acid (1) and 3-hydroxbenzothiophene (6) exhibited zero-order kinetics (Figure 5.5), with apparent rate constants of 1.5 x 10-3 and

1.1 x 10-2 (µM or RR) • cm2 mJ-1 for benzoic acid (1) and 3-hydroxybenzothiophene (6), respectively (Table 5.1). Notably, 2-hydroxybenzothiophene (5) followed a more complex

155 trend than its isomer, 3-hydroxybenzothiophene (6), indicating that some phototransfor- mations were isomer-selective. Neither benzoic acid (1) nor hydroxybenzothiophenes (5, 6) have been reported as photoproducts of DBT or any of its degradation products, and the mechanisms of their formation remain unknown. Thioindigo (25) formation fit a first-order model yielding an apparent rate constant of 3.2 x 10-3 cm2 mJ-1. This compound is thought to be a dimer of 3-hydroxybenzothiophene-2-carbaldehyde (12) (Bress- er and Fedorak, 2001), which was present in the Post-biodegradation solution.

The majority of the DBT degradation products exhibited net loss or formation alternating with increasing fluence in more complex trends than observed for other compounds. For example, benzothiophene-2,3-dione (9) decreased 71% from an initial concentration of 4.1±1.04 µM to 1.17±0.07 µM at the lowest UV fluence (500 mJ cm-2), indicating net photolysis (Figure 5.2d). A higher fluence of 1250 mJ cm-2 resulted in a dramatic increase in the dione to 19±4.05 µM (363% of initial concentration), signifying that formation of the compound dominated photolysis. The highest fluence (2000 mJ cm-2) again resulted in net photolysis decreasing dione concentration of 0.66±0.07 µM. Other compounds followed a similar trends, including DBT sulfone (22), DBT sulfoxide (21), 2-hydroxybenzothiophene (5), 2,3-dihydroxybenzothiophene (11), 3-hydroxy-1-benzothiophen-2-one (13) and 3-hydroxy-1-benzothiophene-2-carbaldehyde (12) (Figures 5.2 and 5.3). Thiosalicylic acid (7), as well as its dimer dithiosalicylic acid (26), showed an equally complex but opposite trend of net formation at both the lowest and highest fluences, and net loss at 1250 mJ cm-2 (Figure 5.2d). For these compounds exhibiting alternating formation and loss with UV fluence, simple kinetic rates could not be determined.

156 5.3.3. Toxicity to Vibrio fischeri and Fundulus embryos

Effects of UV on the toxicity of the test solutions to bioluminescent bacteria Vi- brio fischeri and Fundulus embryos are shown in Figure 5.6. Regardless of UV exposure, Control solution (i.e., freshly made artificial seawater media) elicited no toxic response in either assay. DBT solution at all fluences produced mild toxic responses in Fundulus embryos, but these responses were not statistically different from those observed with the Control solution. In V. fischeri, however, DBT solution caused 21-25% inhibition of luminescence after treatment with 0 to 1250 mJ cm-2 UV. A statistically significant (ANOVA p < 0.05) increase in toxicity to the bacteria resulted with treatment of the DBT solution with the highest UV fluence. DBT concentration decreased at this fluence (Figure 5.2a), indicating that DBT photoproducts may have caused the increased toxicity to V. fischeri. Of the products that were identified in the DBT solution after UV exposure, DBT sulfoxide (21) was the only one exhibiting maximal levels at the highest UV fluence, and therefore was the most likely of these to have raised toxicity.

Of the test solutions, the Post-biodegradation solution was most toxic overall to both V. fischeri and Fundulus embryos. Untreated Post-biodegradation solution produced moderately severe deformities (score of 1.54) in Fundulus embryos. Deformity scores increased with increasing UV fluence, reaching 1.97 (out of a maximum of 2) at the highest fluence. Based on this assay, UV treatment exacerbated hazard already attributable to the media, and therefore was not a successful post-biodegradation step. V. fischeri responded differently to UV-treated Post-biodegradation solution. Inhibition of luminescence was increased from 37.9% in untreated media to 42.2% at the lowest UV fluence. Toxicity to the bacteria decreased with higher fluences resulting in 32% inhibition of luminescence at 2000 mJ cm-2, a small but significant (ANOVA p<0.05) reduction in toxicity compared to the untreated Post-biodegradation solution.

157 a. Fundulus embryo toxicity assay bc c 2.0 ab Control solution a 1.5 DBT solution Post-biodegradation solution 1.0

Deformity Score 0.5 a a a a a a a a increasing deformities 0.0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 0 5 0 5 5 5 5 0 2 0 2 0 2 2 1 2 1 2 1

UV Fluence (mJ cm-2)

b. V. ﬁscheri toxicity assay )

% 50 ( c bc

o n ab

ti 40 a

b i c

n h i 30 b b I a e

n c 20 e c s 10 n e i a a a a u m

L 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 0 5 0 5 0 5 5 5 2 0 2 0 2 0 1 2 1 2 1 2

UV Fluence (mJ cm-2)

Figure 5.6. Toxicity assessed as (a) average cardiac deformity score in Fundulus em- Figure 5.5. Toxicity assessed as (a) average deformity in Fundulus embryos and (b) bryos and (b) inhibition of luminescence in V. fischeri for Control solution, DBT (1.5 µM) inhibition of luminescence in V. fischeri for Control media, DBT (1.5 µM) media and solution and Post-biodegradation solution following treatment of the test solutions with Culture media following treatment of the test solutions with LP UV (254 nm) at LP UV (254 nm) at fluences of 0, 500, 1250 and 2000 mJ cm-2. Fundulus embryos were fluences of 0, 500, 1250 and 2000 mJ cm-2. Fundulus embryos were dosed with test dosed with test solutions 24 h post-fertilization and scored 6 d after dosing. Scoring solutions 24 h post-fertilization and scored 6 d after dosing. Scoring scale: 0 = normal; 1scale: = mild 0 =deformities; normal; 1 = mild2 = severe deformities; deformities. 2 = severe Error deformities. bars are standard Error deviations. bars are standard For a givendeviations. assay-media Within combination, a given panel barsfor alabeled given test with solution, the same barsletter labeled are not with significantly the same let- differentter are not at significantlyp<0.05 in ANOVA different comparisons. at p<0.05 in ANOVA comparisons.

158 5.4. Di s c u s s i o n

Photolysis of DBT and its biodegradation products have been little studied, par-

ticularly in seawater. UV photolysis of 1.5 µM DBT in pH 7.55 artificial seawater (DBT solution) followed apparent first-order kinetics yielding a rate constant of 1.5 x 10-4 cm2 mJ-1. Similar kinetics, with a slightly lower rate constant (0.6 x 10-4 ± 0.08 x 10-4 cm2 mJ-1), were observed by Shemer and Linden (2007b) for direct photolysis by LP UV of 2 µM DBT in 20 mM phosphate buffer, pH 7. In the same study, DBT photolysis rate increased to approximately 2.6 x 10-4 ± 0.2 x 10-4 mJ cm-2 in natural estuary water with salinity similar to that of the DBT solution. The increased photolysis rate was attributed to indirect photolysis of DBT from other photooxidants in the natural estuary water, particularly dissolved organic matter. Here, “indirect photolysis” of a compound refers to reactions resulting from absorption of UV light by species other than the compound. For example, indirect photolysis of one compound may occur due to transfer of energy from a second compound after it has absorbed UV light. In the current study, DBT photolysis rate constant in DBT solution was significantly lowerp ( <0.05, two-tailed t-test) than that of DBT in the natural estuary water studied by Shemer and Linden (2007b), possibly because the DBT solution contained no dissolved organic matter. DBT photolysis in DBT solution was faster (p<0.05, two-tailed t-test) than in the phosphate buffer used by Shemer and Linden (2007b), possibly due to the presence of other photooxidants in the DBT solution such as nitrate, carbonate, hydroxyl radical, and singlet oxygen, trace metals such as

Fe2+/3+ and other inorganic species not present in the phosphate buffer.

DBT photolysis (i.e., loss due to UV exposure) in the Post-biodegradation solution (k’=7.4 x 10-4 cm2 mJ-1) proceeded more rapidly than in the DBT solution and in the natural estuary water investigated by Shemer and Linden (2007b), possibly because DBT

159 degradation products and other microbially produced compounds (e.g., lipids, proteins) served as photooxidants in addition to those listed above for the DBT solution. These -re sults suggest that indirect photolysis played an important role in DBT degradation by UV, particularly in the Post-biodegradation solution. However, even though UV was capable of degrading DBT, the majority (72%) of initial DBT remained even after the highest dose, indicating that UV alone would not be an efficient way to reduce contaminant levels. Higher doses are generally impractical for contaminant treatment due to the energy requirements. Although not a focus of the current study, it may be possible to enhance photooxidation by combining UV with oxidants such as H2O2. For example, Shemer and Linden (2007b) observed almost one order of magnitude increase in DBT photolysis rate

-1 using a combination of LP UV and 25 mg L H2O2.

DBT photodegradation by UV at 254 nm in the DBT solution yielded DBT sulfoxide (21) along with hydroxylated benzothiophenes (5, 6, 11). Little research has explored products of DBT photolysis at UV 254 in artificial seawater, however, DBT sulfoxide (21) has been reported as a photodegradation product in seawater exposed to natural sunlight (Payne, 1985; Berthou and Vignier, 1986) and in engineered biphasic systems after DBT exposure to high-pressure Hg lamps (>280 nm) (Shiraishi et al., 1999). Previous research has also reported DBT sulfone (22), benzothiophene carboxylic acid (13) and benzothiophene-2,3-dicarboxylic acid (17), 2-sulfobenzoic acid, 2-hydroxybiphenyl-2’- sulfinic acid sultine, thiophene carboxylic acids, 5-sulfoisophthalic acid, and acetylbenzo- thiophenecarboxylic acid as photoproducts of DBT (Berthou and Vignier, 1986; Bobinger et al., 1999; Shiraishi et al., 1999; Traulsen et al. 1999). These studies observed these DBT photoproducts using GC/MS analyses similar to those used in the current study, yet none of these products was observed in the DBT solution at any fluence for reasons that are not apparent in this study. Hydroxylated benzothiophenes have not been previously

160 reported as DBT photodegradation products for any light source yet they were identified in this experiment.

Without any UV treatment, the Post-biodegradation solution was chemically complex, containing some DBT along with a suite of DBT microbial degradation products (see Chapter 3, Table 3.1). Because of this complexity, it was not possible to confirm the identity of precursors to the products that showed net formation at any UV dose, which included DBT sulfone, (22), DBT sulfoxide (21), benzoic acid (1), hydroxybenzothiophenes (5, 6, 11), benzothiophene-2,3-dione (9), thiosalicylic acid (7), dithiosalicylic acid (26), thioindigo (25) and 3-hydroxybenzothiophene-2-carbaldehyde (13) (Figures 5.2 and 5.3). Of the DBT products monitored, DBT sulfoxide (21), DBT sulfone (22), benzothiophene carboxylic acid (13) and benzothiophene-2,3-dicarboxylic acid (17) have been previously reported as photoproducts of DBT (Berthou and Vignier, 1986; Bobinger et al. 1999; Shiraishi et al., 1999; Traulsen et al. 1999), suggesting that DBT may have been a precur- sor to these products observed in the Post-biodegradation solution, although they were not observed in the DBT solution. Little to no research has explored photodegradation of most of the DBT degradation products identified in the Post-biodegradation solution. Some research has demonstrated deoxygenation of DBT sulfoxide (21) to yield DBT (Kumazoe et al., 2003; Gregory et al., 2006). This reaction was not apparent from the trends in the products observed in the current study, i.e., DBT concentration did not increase when DBT sulfoxide (21) decreased (Figure 5.2). However, the reaction cannot be dismissed since the observed trends may obscure processes that are not dominant. Previously reported photoproducts (observed using GC/MS analyses similar that used in the current study), Including 2-sulfobenzoic acid, 2-hydroxybiphenyl-2’-sulfinic acid sultine, thiophene carboxylic acids, 5-sulfoisophthalic acid, and acetylbenzothiophen- ecarboxylic acid (Bobinger et al., 1999; Traulsen et al., 1999) were not observed in the Post-biodegradation solution after UV irradiation.

161 One measure of the effectiveness of UV as a remediation treatment is its ability to reduce toxicity, however, this measurement can be dependent on the toxicity assay used. Fundulus embryos appeared to be little affected by DBT alone in the DBT solution, regardless of UV treatment (Figure 5.6a). These results are consistent with those of Wassenberg et al. (2005), who observed no significant effect on embryo toxicity or deformity from exposure to 0-2.72 µM DBT. V. fischeri, however, showed considerable toxicity from DBT itself, and, in this case, toxic effects were exacerbated at higher UV fluences (Figure 5.6b). Based on this assay, UV treatment appeared counterproduc- tive towards a remediation goal of toxicity reduction. The elevated toxicity V.to fischeri observed in DBT solution at the highest UV dose may have been related to formation of

DBT sulfoxide (21), which has been previously shown to be toxic (IC50 10 µM) to V. fischeri (Seymour et al., 1997) as well as some plant species (Schlesinger and Mowry, 1951). The difference in the results between the toxicity assays may be due partly to fact that the assays address different aspects of toxicity. For example, the V. fischeri assay is not based on a specific toxic mechanism but instead reflects a general effect on the organism’s metabolism and, subsequently, the ATP-dependent luciferase reaction that produces luminescence. In contrast, the Fundulus embryo assay specifically addresses cardiac deformities, which might not reflect other toxic effects to the embryo. Differences between the assays may also have been affected by other factors, including differences physiology (e.g., membrane properties and permeability) that can impact uptake and metabolism of DBT and its degradation products.

Unlike the DBT solution, the Post-biodegradation solution was very toxic to both V. fischeri and Fundulus embryos (Figure 5.6), possibly due to one or more products of DBT degradation. UV treatment of Post-biodegradation solution, however, produced different toxicity trends in the two organisms. Whereas UV treatment produced a transient increase in toxicity at low fluence in V. fischeri, increasing detections of cardiac

162 deformity was observed with increasing UV fluence in the fish embryos (Figure 5.6a). Based on correlation between hatching success and the deformity scores used in the Fundulus embryo assay (Matson et al., 2008), roughly 65% of embryos exposed to untreated (i.e., 0 mJ cm-2 UV) Post-biodegradation solution would not be expected to hatch, while no successful hatching would be expected in Post-biodegradation solution treated at the highest UV fluence. From a remediation perspective, both biodegradation and post-biodegradation could present a greater problem than the original contaminant DBT if measures to prevent exposure to humans and wildlife were not implemented.

While it is difficult to definitively identify the toxic components in the Post-biodegradation solution because of its chemical complexity, comparison of trends in toxicity to those of DBT and DBT degradation products can provide some candidates. For example, the most extreme toxicity to the embryos in the Post-biodegradation solution occurred at the highest UV fluence, which resulted in nearly complete losses of 12 of the 15 compounds monitored Figures 5.2 and 5.3). The remaining compounds may have contributed to toxicity: benzothiophene-2,3-dicarboxylic acid (17), thiosalicylic acid (7), and dithiosalicylic acid (26). Formation of new photoproducts was not apparent, since chromatograms of UV-treated Post-biodegradation solution did not show new peaks not present in untreated Post-biodegradation solution. Toxicity of benzothiophene-2,3-dicarboxylic acid (17) is unknown. Thiosalicylic acid (7) and dithiosalicylic acid (26) were not shown to be toxic to V. fischeri at concentrations observed in the Post-biodegradation solution (Chapter 3, Figure 3.19). Previous studies have reported low in vivo and in vitro toxicity of thiosalicylic acid (7) and dithiosalicylic acid (26) (Shafer and Bowles, 1985: deer mice (Peromyscus maniculatus) and house mice (Mus musculus); Park et al., 2007: murine and human kidney cells), however these studies did not assay aquatic organisms. It is possible that toxic photoproducts may have formed in the Post-biodegradation solution but were not detected. For example, products may have been lost or transformed

163 during sample preparation, or may not have been amenable to GC/MS analysis due to thermal lability or retention on materials in the gas chromatograph or column, or inabil- ity to ionize. It is also possible that toxicity was a result of mixture effects between two or more DBT degradation products. Toxicity to V. fischeri was investigated for commercially available DBT degradation products individually (Chapter 2), but any effects produced from mixtures of these products were not explored.

The use of UV treatment in series with biodegradation treatments has been little studied. Most studies combining UV treatment and biodegradation apply UV as a pretreatment to initiate attack on compounds that are resistant to biodegradation (e.g., Lehto et al. 2003; Guieysse et al., 2004). Regardless of whether UV is used before or after biodegradation, the combination of treatments does not always satisfactorily reduce contaminants and/or toxicity. Karetnikova et al. (2008) found that UV irradiation from a high-pressure Hg lamp after degradation of p-cresol by Penicillium tardum reduced biodegradation products but not toxicity measured as mortality of the protozoan Colpoda steini. These authors did not identify degradation products or characterize the toxic components, but their results, similar to those from the current study, indicate that post-biodegradation UV treatment may still be unsuccessful from a toxicity perspective even when monitored biodegradation products are reduced.

The results of this research highlight avenues for future work. Further research is needed to evaluate whether treatment alternatives, such as combining UV with a strong photooxidant such as H2O2, may be more effective in reducing residual biodegradation products as well as toxicity compared to UV alone. Additional research may help determine if currently unidentified photoproducts contributing to toxicity are formed upon irradiation. Further exploration into the effects of mixtures of degradation products on toxicity to V. fischeri and/or Fundulus embryos may resolve questions concerning wheth-

164 er or not synergistic toxic effects play an important role in systems where DBT degradation is occurring. The current study explored only UV at 254 nm, which is not a dominant component of natural sunlight at the earth’s surface. Although DBT is not a strong absorber of visible wavelengths, some degradation products do (e.g., thioindigo, benzothiophene-2,3-dione), and so may be susceptible to phototransformation under visible light. Investigation of the effects of natural sunlight on DBT, its biodegradation products, and toxicity would help determine how DBT biodegradation and phototransformation occurring naturally in a contaminated system open to sunlight (such as an estuary) could positively or negatively influence remediation success.

5.5. Co n c l u s i o n

Post-biodegradation UV irradiation of the medium from a DBT-degrading mixed culture significantly reduced residual DBT and 11 monitored DBT degradation products at the highest UV fluence. However, amelioration of initial toxicity did not accompany loss of degradation products. To the contrary, although high UV fluence did decrease toxicity to V. fischeri, high UV fluence exacerbated toxic effects in Fundulus embryos. Since reduction of both contaminants and toxicity is often a goal of remediation, these findings stress the importance of monitoring toxicity when evaluating potential remediation strategies. The two toxicity assays in this study (Vibrio fischeri bioluminescence assay and Fundulus embryo deformity assay) yielded assay-dependent trends for both DBT in artificial seawater media and medium from the degradation culture. These findings suggest that a single toxicity assay may not provide a complete toxicological characterization, supporting the use of multiple assays in monitoring toxicity when evaluating remediation approaches. Degradation of DBT in artificial seawater media from UV exposure yielded hydroxybenzothiophenes not previously reported as photodegradation

165 products. This research contributes to fundamental knowledge of phototransformation of condensed thiophenes as well as to the development of novel remediation strategies.

166 Chapter 6. Conclusions

This research investigated degradation of the sulfur-containing polycyclic aromatic hydrocarbon dibenzothiophene (DBT) by a mixed microbial community using a multifaceted approach that included monitoring bacterial populations using SYBR-Green quantitative polymerase chain reaction (qPCR), measurements of bacterial growth and DBT loss, analysis of DBT biodegradation products, and assessment of toxicity using bioluminescent bacteria Vibrio fischeri. In addition, this research explored the efficacy of an unconventional remediation strategy using ultraviolet (UV) irradiation following biodegradation to reduce residual DBT, biodegradation products and associated toxicity. Additionally, a recently introduced approach for evaluating qPCR data using sigmoidal curve fitting was investigated as an alternative to the conventional approach for the characterization of mixed microbial communities. The broad objective for this research was to gain a comprehensive perspective of DBT degradation by mixed microbial culture to understand what factors may affect contaminant degradation and associated potential hazards, particularly within the context of remediation.

The mixed microbial culture used in this study was established by enrichment from sediment from a creosote-contaminated estuary. The culture was maintained in artificial seawater media with DBT as the sole carbon source. Phylogenetic analysis of

16S rRNA gene sequences from clones and isolates obtained from the culture indicated the DBT-degrading mixed microbial community was taxonomically diverse, including Firmicutes, Flavobacteriaceae, Planctomycetaceae, Alphaproteobacteria, and Gam- maproteobacteria. Characterization of the microbial community by qPCR showed that whether or not pH was maintained near 7.5 during DBT degradation, complex effects on trends of bacterial populations result. Generally, greater species diversity was observed during DBT degradation without pH control than with pH control. Regardless of pH treat-

167 ment, the culture was dominated by Flavobacteriaceae during the first 6-10 days, and by Chromatiales thereafter, signifying their importance to DBT degradation. Association of Flavobacteriaceae and Chromatiales with DBT degradation has not been previously reported.

DBT degradation by the enrichment culture was impaired when pH was not controlled, but resulted in a 91% loss of initial DBT when pH was maintained near 7.5. Twenty-seven degradation products were identified in the culture by GC/MS, many of which have been previously observed as DBT degradation products including DBT sulfone, DBT sulfoxide, hydroxylated and carboxylated benzothiophenes, and 3-hydroxybenzothiophene-2-carbaldehyde among others. The diversity of degradation products indicated that both lateral and angular dioxygenation pathways were active. Degrada- tion products specific to the DBT biodesulfurization pathway were not observed. Nine of the observed degradation products have not been previously reported for DBT degradation by bacteria, including benzothiophene, benzisothiazole, benzothiophene-2,3-dicarbaldehyde and dithiosalicylides among others. Toxicity assessed using V. fischeri reached maxima of 51% and 62% inhibition of luminescence within 4 days with and without pH control, respectively, and was never reduced below initial levels of 21% inhibition of luminescence associated with DBT at saturation (1.5 µM). These results suggested that some degradation products were toxic. While several products showed trends similar to that of toxicity, which products contributed to toxicity could not be specified, and it was possible that multiple degradation products contributed to toxicity through mixture effects. Within the context of remediation, these results indicate that, while DBT degradation by this culture might achieve a remediation goal of contaminant (i.e., DBT) reduction, it may not also successfully reach a second goal of toxicity and hazard reduction.

168 UV treatment was evaluated as a secondary treatment to bioremediation, with the aim of reducing residual degradation products and ameliorating toxicity. At the highest UV dose, UV treatment of the media from the DBT-degrading mixed culture was able to reduce 11 monitored DBT degradation products and resulted in low levels of residual DBT. However, UV could not also ameliorate toxicity of the solution. Higher UV doses exacerbated cardiac defects in Fundulus embryos and only slightly reduced toxicity to V. fischeri. Since reduction of toxicity is often a goal of remediation, these findings indicate that UV irradiation would not be an acceptable treatment for the Post-biodegradation solution. Photooxidation of DBT alone in artificial seawater media did not greatly reduce initial DBT levels (1.5 µM), which is consistent with published research on DBT photolysis, but did yield hydroxybenzothiophenes not previously reported as DBT photoproducts.

Because the use of qPCR is a relatively recent addition to culture-independent techniques for monitoring mixed cultures, questions persist regarding the best approach for processing qPCR data. Current conventional SYBR-Green qPCR methodology for characterizing microbial communities using 16S rRNA gene is based on the assumption that all samples and standards assayed with a given primer set amplify with identical reaction efficiencies, which is not always the case. Using simple artificial microbial communities, this research compared the conventional approach for analyzing qPCR data to an alternative approach involving fitting amplification curves to a recently introduced 5-parameter sigmoidal model to calculate sample-specific efficiencies and values used in gene copy determination. Sigmoidal fitting showed that nearly all curves were asymmetric and that amplification efficiencies varied among samples and standards for a given assay depending on a variety of factors, thus invalidating the assumption upon which the conventional cycle threshold approach is based. Overall, quantitation of 16S rRNA gene copies using the second derivative maximum calculated from sigmoidal fitting

169 of amplification curves truncated to exclude early and late plateau stages was more -ac curate than quantitation by the conventional approach. Evaluation of alternative qPCR analysis approaches also explored a variety of ways to determine total 16S rRNA gene copies of all populations in the culture. Summation of quantities calculated using taxa- specific primers yielded the most accurate results. This approach, however, is not always possible with incompletely defined microbial communities, for which total 16S rRNA gene copy quantitation relies on a universal primer. Use of universal primers can be strongly affected by PCR biases, since the universal primers can amplify DNA with different efficiencies for different taxa. In this research, acceptable quantitation of total 16S rRNA gene copies using a universal primer was obtained using the average of the values of total 16S rRNA gene copies calculated by each taxa’s set of standards.

Several questions could not be fully addressed from this research, and remain as areas for further studies. Specific roles of the bacterial taxa in DBT biodegradation, which could not be determined in these studies, could be probed by searching for degradation genes or through more extensive studies on isolates than were performed in this research. Additionally, although the culture used in this research was established from contaminated sediment, it is not known how the populations in the culture compare to those in sediment. The ability of the culture to degrade DBT degradation products when these products are presented as the sole carbon source was not studied here, but could help confirm what metabolic pathways produce specific DBT products as well as aid in understanding the degradation roles of bacterial taxa. Because DBT is structurally similar to other common PAHs such as fluorene and dibenzofuran, it is possible that the mixed culture could also degrade other PAHs, yet this was not explored. In assessing the toxicity of commercially-available DBT degradation products, this research did not investigate toxic effects from mixtures of these products, which may be help explain some of the toxicity results observed in Chapters 3 and 5. Finally, although UV alone was insuf-

170 ficient to reduce toxicity of the Post-biodegradation solution, the effectiveness of UV treatment may be enhanced through the addition of H2O2, ozone or other oxidant.

Because of the multifaceted approach of this research, findings are relevant to a variety of research fields and practical applications. Since the research focused on a mixed culture using culture-independent qPCR assays, it expands current understanding of DBT biodegradation beyond what is possible through the study of bacterial isolates and aids in identifying taxa not previously associated with DBT degradation. By exploring unconventional approaches for analyzing qPCR data, this research advances current qPCR methodology for the study of microbial communities, which are the focus of much research in environmental, engineering, agricultural, ecological, and medical sciences. Few studies have monitored so many products during the degradation of any PAH degraded by a mixed microbial community, and so this research adds to current understanding of the complexity of degradation products and pathways possible in mixed communities, particularly those that may be present at contaminated sites. Associa- tion of changes in toxicity with those of biodegradation products, many of which are not commercially available or easily synthesized, furthers understanding of what products may enhance hazard during bioremediation and require monitoring and/or steps to reduce their off-site transport. Finally, investigation of post-biodegradation UV treatment, while not successful in reducing post-biodegradation residual toxicity in this study, furthers development of alternatives to current remediation strategies, such as site excavation, that are often expensive and environmentally disruptive.

171 Appendices

Ap p e n d i x A: Ch a p t e r 2 Da t a Table A.1. Typical composition of Instant OceanTM artificial seawater (22.2 g-1 L ).

Component mM Chloride 342 Sodium 295 Sulfate 17.4 Magnesium 34.1 Potassium 6.75 Calcium 6.27 Bi/Carbonate 2.10 Bromide 0.441 Strontium 0.063 Boron 0.326 Fluoride 0.033 Lithium 0.027 Iodide 0.0012 Barium < 0.0002 Iron < 0.0005 Manganese < 0.0003 Chromium < 0.0002 Cobalt < 0.0002 Copper < 0.00015 Nickel < 0.00016 Selenium < 0.00012 Vanadium < 0.00019 Zinc < 0.00014 Molybdenum < 0.00007 Aluminum < 0.0001 Lead < 0.00001 Arsenic < 0.00003 Cadmium < 0.00001 Nitrate 0 Phosphate 0

172 Table A.2. Rarefaction data for the DBT-degrading mixed microbial community presented in Figure 2.2.

NumberofSequences Numberof NumberofSequences Numberof Sampl lded OTUsa Sampl lded OTUsa 1 1 35 35 2 2 36 36 3 3 37 37 4 4 38 38 5 5 39 39 6 6 40 40 7 7 41 41 8 8 42 42 9 9 43 43 10 10 44 44 11 11 45 45 12 12 46 46 13 13 47 47 14 14 48 48 15 15 49 49 16 16 50 50 17 17 51 51 18 18 52 52 19 19 53 53 20 20 54 54 21 21 55 55 22 22 56 56 23 23 57 57 24 24 58 58 25 25 59 59 26 26 60 60 27 27 61 61 28 28 62 62 29 29 63 63 30 30 64 64 31 31 65 65 32 32 66 66 33 33 67 67 34 34 68 68 aOTU:operationaltaxonomyunit

173 % of as Toxicity Inhibition Luminescence, Ͳ 1 RNA r gene copies L 16S l Ͳ 1 L ota T mg Protein, DBT, mM Total

DBT, µM Aqueous pH Inoculated 2 1 7.21 0.000 5.354Inoculated 61.097Inoculated 10 10 n.d. 1 2 40.744 4.24 4.22Inoculated 0.758Inoculated 0.855 14Inoculated 3.896 16Inoculated 5.030 16 3 315.173 16 1 291.879 5.6E+07 2 8.1E+07 4.29 3Inoculated 4.39Inoculated 25.182 4.23 1.662 20Inoculated 25.081 4.25 1.601 20 4.918 1.758 20 1 4.444 1.786 2 316.057 3.815 3 312.206 4.23 4.854 n.d. 326.654 7.2E+07 4.40 331.960 9.5E+07 4.27 1.974 9.0E+07 2.016 38.056 45.673 4.294 2.140 36.956 3.560 33.784 465.964 3.908 499.554 8.0E+07 443.696 8.4E+07 1.0E+08 32.680 31.758 26.373 InoculatedInoculatedInoculated 0 0 0 1 2 3 7.56 7.52 7.54 1.741 1.588 6.573 1.691 6.037 34.962 5.685 30.659 6.7E+06 37.737 5.4E+06 6.0E+06 19.475 20.357 20.747 InoculatedInoculatedInoculated 4Inoculated 4Inoculated 4 1 6 2 6 3 6.56 1Inoculated 6.61 2 6.61 0.000 6.53 8 0.000 6.50 4.939 0.000 5.956 0.000 3 116.565 5.771 0.062 99.699 1.9E+07 4.342 106.404 4.95 3.805 2.0E+07 175.038 2.5E+07 54.452 160.242 2.9E+07 0.910 2.6E+07 59.821 58.429 4.487 48.500 46.656 296.738 n.d. 26.445 InoculatedInoculated 2 2 2 3Inoculated 7.25Inoculated 7.24Inoculated 6 0.000 8 0.000 8 6.177 3 5.875 1 61.354Inoculated 2 64.360Inoculated 6.30 10 n.d.Inoculated 4.76 12 n.d.Inoculated 4.75 0.000 12 3Inoculated 1.001 12 1Inoculated 4.740 0.973 43.600 14 2 4.211 36.520 4.21 170.238 14 3 4.857 4.44 271.208 1 2.8E+07 4.52 252.112 0.978 2 n.d. 4.62 1.224Inoculated n.d. 38.466 4.37 4.452 1.240Inoculated 4.42 4.451 1.232 18Inoculated 312.206 4.071 1.538 35.885 18 304.397 6.6E+07 4.076 1.554 31.202 18 1 312.046 3.853 2 n.d. 326.004 4.740 3 n.d. 25.954 322.432 4.40 n.d. 315.092 4.32 n.d. 44.066 4.29 1.704 n.d. 42.382 1.665 36.612 3.886 1.781 43.019 4.402 357.868 44.876 4.761 311.006 n.d. 350.738 n.d. n.d. 28.900 32.708 30.503 % Sample Day Replicate Final of as 17.428 Toxicity Inhibition Luminescence, Ͳ 1 a RNA r n.d. gene copies L 16S l Ͳ 1 L ota T mg Protein, DBT, mM Total DBT, µM Aqueous pH Selected data for DBT degradation experiment without pH control (Figures 2.3 and 2.4). (Figures control without pH experiment degradation DBT for data Selected determined. not n.d.: UninoculatedUninoculated 2Uninoculated 2Uninoculated 4Uninoculated 2 4Uninoculated 3 4Uninoculated 1 7.54 6Uninoculated 2 7.54 6Uninoculated 3 7.43 6Uninoculated 1.594 1 7.44 8Uninoculated 1.826 2 7.44 8Uninoculated 5.831 1.634 3 7.40 8Uninoculated 5.774 1.469 1 10 7.37 0.000Uninoculated 6.355 1.927 2 10 7.38 0.000Uninoculated 5.621 1.647 3 10 1 7.30 0.000Uninoculated 5.730 1.480 n.d. 12 2 7.34 0.000Uninoculated 6.346 1.942 n.d. 0.0E+00 12 3 7.29 0.000Uninoculated 5.741 1.699 0.0E+00 7.30 12 1 0.000Uninoculated 6.257 1.735 19.325 0.0E+00 7.33 14 2 0.000Uninoculated 5.516 1.734 16.998 18.235 0.0E+00 7.32 1.581 14 3 0.000Uninoculated 5.804 20.254 0.0E+00 7.27 1.799 14 1 0.000Uninoculated 6.159 19.236 7.33 5.624 1.695 16 2 0.000Uninoculated n.d. 18.256 7.30 6.310 1.612 16 3 0.000Uninoculated n.d. 17.994 7.31 0.000 6.482 1.724 16 1Uninoculated n.d. 0.0E+00 7.29 0.000 6.356 1.774 18 2Uninoculated 0.0E+00 19.265 7.27 0.000 5.954 1.900 18 3Uninoculated 0.0E+00 20.325 7.23 0.000 6.561 1.782 18 1Uninoculated 18.256 21.001 7.20 0.000 5.868 1.731 20 n.d. 2 20.168 Uninoculated 7.24 0.000 6.239 1.744 20 n.d. 3 19.225 7.28 0.000 6.026 1.695 20 n.d. 1 7.31 0.000 6.364 1.774 n.d. 2 19.102 7.30 0.000 6.092 1.641 3 n.d. 18.254 7.24 0.000 5.649 1.730 n.d. 17.365 0.0E+00 7.25 0.000 5.972 1.697 19.564 0.0E+00 7.23 0.000 6.578 1.464 20.318 0.0E+00 0.000 6.588 1.695 18.196 18.268 0.0E+00 0.000 6.492 1.803 19.649 0.000 6.407 n.d. 20.167 0.000 6.105 n.d. 18.215 0.000 n.d. 0.0E+00 0.000 17.026 0.0E+00 19.025 0.0E+00 19.036 18.975 20.467 18.632 UninoculatedUninoculated 0Uninoculated 0Uninoculated 0 1 2 2 3 7.56 1 7.52 7.54 1.720 7.52 1.685 6.573 1.675 6.037 1.721 34.962 5.685 30.659 6.272 0.0E+00 37.737 0.0E+00 0.000 0.0E+00 19.475 20.357 20.747 Sample Day Replicate Final a Table A.3. Table

174 % of as Toxicity Inhibition Luminescence, Ͳ 1 RNA r gene copies L 16S l Ͳ 1 L ota T mg Protein, DBT, mM Total DBT, µM Aqueous pH Inoculated 2 1 7.28 0.000 6.005Inoculated 32.235Inoculated 10 10 n.d. 1 2 43.427 6.68 6.56Inoculated 0.000Inoculated 0.000 14Inoculated 4.482 16Inoculated 4.665 16 3 105.610 16 1 107.432 1.7E+07 2 1.4E+07 6.45 3Inoculated 7.04Inoculated 36.454 6.93 0.000 20Inoculated 34.582 6.95 0.000 20Inoculated 4.313 0.000 20 1Inoculated 3.713 0.000 24 2Inoculated 158.815 3.995 24 3 178.896 6.81 4.247 24 1 n.d. 174.336 1.7E+07 6.77 2 165.896 2.6E+07 6.70 0.000 3Inoculated 2.5E+07 6.65 0.000Inoculated 30.379 30.027 6.55 2.433 0.000 32Inoculated 26.770 6.41 2.991 0.000 32 22.613 174.290 2.445 0.000 32 1 198.828 2.6E+07 1.829 0.000 2 232.421 2.9E+07 1.614 3 217.405 2.0E+07 6.25 2.057 23.355 261.714 2.2E+07 6.10 26.285 274.396 2.6E+07 6.08 0.000 25.453 2.1E+07 0.000 28.404 0.581 0.000 25.101 0.525 24.824 447.816 0.599 392.200 1.6E+07 498.993 1.5E+07 1.5E+07 22.306 22.545 20.861 InoculatedInoculatedInoculated 4Inoculated 4Inoculated 4 1 6 2 6 3 7.26 1Inoculated 7.26 2 7.28 0.000 6.87 8 0.000 6.78 5.442 0.000 5.287 0.000 3 53.215 5.482 0.000 52.727 5.161 1.4E+07 42.467 6.31 5.099 1.5E+07 66.532 1.8E+07 51.420 50.038 0.000 2.2E+07 51.830 2.8E+07 51.391 4.372 45.258 122.560 48.595 n.d. 37.267 InoculatedInoculatedInoculated 0 0 0 1 2 3 7.56 7.57 7.55 1.496 1.651 6.124 1.431 5.982 18.041 6.030 18.416 8.3E+06 18.733 6.6E+06 6.2E+06 21.561 23.616 22.586 InoculatedInoculated 2 2 2 3Inoculated 7.26Inoculated 7.24Inoculated 6 0.000 8 0.000 8 5.974 3 6.169 1 45.231Inoculated 2 31.962Inoculated 6.79 10 n.d.Inoculated 6.36 12 n.d.Inoculated 6.20 0.000 12 3Inoculated 0.000 12 1Inoculated 4.737 0.000 47.178 14 2 4.570 45.449 6.58 14 53.904 3 4.479 7.06 105.078 1 2.5E+07 7.29 0.000 95.229 2 n.d. 7.08 0.000Inoculated 6.61 4.492 0.000 n.d. 42.517 Inoculated 6.69 4.124 0.000 18Inoculated 92.457 4.955 0.000 36.118 18 100.452 4.342 0.000 18 1 2.3E+07 35.919 138.779 4.182 2 n.d. 119.124 3.859 3 n.d. 141.875 32.221 6.70 n.d. 183.706 6.58 n.d. 35.372 6.48 0.000Inoculated n.d. 34.389 0.000Inoculated 29.710 3.073 0.000 28Inoculated 28.300 3.552 28 185.944 28.701 2.701 28 1 161.246 2 n.d. 166.978 3 n.d. 6.57 n.d. 6.42 28.236 6.33 0.000 22.602 0.000 23.780 1.740 0.000 1.702 284.823 1.497 379.224 n.d. n.d. n.d. n.d. 20.872 17.185 21.348 % Sample Day Replicate Final of as 20.133 Toxicity Inhibition Luminescence, Ͳ 1 a RNA r n.d. gene copies L 16S l Ͳ 1 L ota T mg Protein, DBT, mM Total DBT, µM Aqueous pH Selected data for DBT degradation experiment with pH control (Figures 2.3 and 2.4). (Figures control with pH experiment degradation DBT for data Selected determined. not n.d.: UninoculatedUninoculated 2Uninoculated 2Uninoculated 4Uninoculated 2 4Uninoculated 3 4Uninoculated 1 7.45 6Uninoculated 2 7.47 6Uninoculated 3 7.47 6Uninoculated 1.513 1 7.48 8Uninoculated 1.587 2 7.50 8Uninoculated 6.022 1.587 3 7.38 8Uninoculated 6.102 1.579 1 10 7.42 0.000Uninoculated 6.042 1.474 2 10 7.40 0.000Uninoculated 6.105 1.662 3 10 1 7.47 0.000Uninoculated 5.977 1.555 n.d. 12 2 7.42 0.000Uninoculated 6.040 1.660 n.d. 0.0E+00 12 3 7.44 0.000Uninoculated 6.081 1.758 0.0E+00 7.37 12 1 0.000Uninoculated 6.098 1.829 24.158 0.0E+00 7.36 14 2 0.000Uninoculated 6.007 1.644 21.855 24.264 0.0E+00 7.35 1.451 14 3 0.000Uninoculated 6.051 20.631 0.0E+00 7.42 1.613 14 1 0.000Uninoculated 6.138 21.133 7.46 6.218 1.892 16 2 0.000Uninoculated n.d. 24.507 7.45 6.067 1.493 16 3 0.000Uninoculated n.d. 20.584 7.42 0.000 6.081 1.758 16 1Uninoculated n.d. 0.0E+00 7.45 0.000 6.153 1.734 18 2Uninoculated 0.0E+00 21.687 7.46 0.000 6.087 1.378 18 3Uninoculated 0.0E+00 21.063 7.41 0.000 6.026 1.840 18 1Uninoculated 17.899 19.233 7.42 0.000 6.033 1.649 20 n.d. 2 17.946 Uninoculated 7.47 0.000 6.071 1.477 20 n.d. 3 18.092 Uninoculated 7.42 0.000 6.227 1.413 20 n.d. 1Uninoculated 7.46 0.000 6.187 1.697 24 n.d. 2Uninoculated 18.111 7.45 0.000 6.095 1.349 24 n.d. 3Uninoculated 19.988 7.42 0.000 6.095 1.771 24 n.d. 1Uninoculated 17.563 0.0E+00 7.47 0.000 6.004 1.402 28 2Uninoculated 19.193 0.0E+00 7.40 0.000 6.044 1.325 28 3Uninoculated 17.326 0.0E+00 7.39 0.000 6.164 1.620 28 1 18.546 Uninoculated 17.639 0.0E+00 7.45 0.000 6.232 1.477 32 2 17.740 Uninoculated 7.41 0.000 6.004 1.515 32 n.d. 3 17.342 7.41 0.000 6.036 1.689 32 n.d. 1 18.560 7.37 0.000 6.222 1.483 n.d. 2 0.0E+00 7.45 0.000 6.031 1.631 3 19.214 0.0E+00 7.37 0.000 6.247 1.521 17.575 0.0E+00 7.45 0.000 6.064 1.583 17.375 17.636 0.0E+00 7.41 0.000 6.004 1.889 17.468 0.0E+00 0.000 6.091 1.606 17.398 0.0E+00 0.000 6.192 1.585 17.311 0.000 6.091 n.d. 16.123 0.000 6.181 n.d. 17.400 0.000 n.d. 0.0E+00 0.000 17.704 0.0E+00 18.421 0.0E+00 17.308 19.324 19.324 18.975 UninoculatedUninoculated 0Uninoculated 0Uninoculated 0 1 2 2 3 7.58 1 7.55 7.54 1.505 7.42 1.402 6.024 1.636 6.000 1.544 0.000 6.223 0.000 6.042 0.0E+00 0.000 0.0E+00 0.000 0.0E+00 19.176 21.294 20.232 Sample Day Replicate Final a Table A.4. Table

175 Ͳ 1 08 05 L + + 575E+08 420E 996E+09 173E . . . . Copies 8 220E 07 1.575E+08 1 1 1 664E 08 1.996E+09 1 3 2 2 3 3 3 3 6 6 000 14 24 34 16 26 6.685E+07 36 5.866E+07 1 5.886E+07 2 9.714E+07 3 1.072E+08 1.383E+08 1.895E+08 1.757E+08 1.664E+08 000 14 24 34 16 26 1.840E+07 36 1.205E+07 1 1.132E+07 2 2.794E+07 3 2.101E+07 3.770E+07 3.855E+07 3.552E+07 4.050E+07 20 20 20 20 101010 116 216 316 120 220 5.651E+08 3 8.325E+08 1 8.085E+08 2 1.390E+09 1.840E+09 1.623E+09 2.062E+09 2.874E+09 101010 116 216 316 120 220 7.477E+07 3 9.607E+07 1 1.182E+08 2 1.535E+08 2.045E+08 2.131E+08 6.123E+05 3.712E+05 Day Rep eeeee 0e 0e 0e 1 4e 2 4e 3 4e 1 6e 2 6e 7.301E+06 3 6e 5.844E+06 10 1e 7.133E+06 10 2e 3.269E+07 10 3 1 3.171E+07 16e 2 5.449E+07 16 3 7.221E+07 16 1 8.220E+07 20 2 8.335E+07 7.441E+07 3 1.474E+08 1 1.065E+08 1.098E+08 1.718E+08 1.417E+08 1.719E+08 k k k k k k k k k k k k k k k k i i i i i i i i i i i i i i i i l l l l l l l lik l l l l l l l l l like lik Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ like aceae aceae aceae aceae aceae aceae aceae aceae aceae aceae aceae aceae aceae aceae aceae aceae aceae es es es es es es es es es es es es es es es es es ll ll ll ll ll ll ll ll ll ll ll ll ll ll ll ll l l l l l l l l l l l l l l l l l ill r i omonas omonas omonas omonas omonas omonas omonas omonas omonas omonas omonas omonas omonas omonas omonas omonas omonas omonas ospiri ospiri ospiri ospiri ospiri ospiri ospiri ospiri ospiri ospiri ospiri ospiri ospiri ospiri ospiri ospiri osp d d d d d d d d d d d d d d d d d d d d d d d d d d d d d d d d d d d o o o o o o o o o o o o o o o o o romatia romatia romatia romatia romatia romatia romatia romatia romatia romatia romatia romatia romatia romatia romatia romatia romatia h h h h h h h h h h h h h h h h h h h h h h h h h h h h h h h h h seu R R R R R R R R R R R R R R R R Pseu Pseu Pseu Pseu Pseu Pseu Pseu Pseu Pseu Pseu Pseu Pseu Pseu Pseu Pseu Pseu Pseu Taxonomic Group Rh d i ill Rhodospirillaceae Rh Ch i l Chromatiales P C C C C C C C C C C C C C C C C C Ͳ 1 08 08 L + + 902E+08 432E 040E+07 703E . . . . 6 149E 07 1.902E+08 1 1 2 391E 06 8.040E+07 8 1 2 2 3 3 3 3 000 14 24 34 16 26 1.129E+07 36 7.549E+06 1 1.074E+07 2 2.527E+07 3 2.900E+07 3.553E+07 5.293E+07 6.149E+07 4.705E+07 6 6 000 14 24 34 16 26 1.543E+06 36 1.100E+06 1 1.071E+06 2 7.016E+05 3 6.346E+05 8.384E+05 3.274E+06 2.482E+06 2.391E+06 101010 116 216 316 120 2 2.946E+07 3 2.786E+07 1 6.125E+07 1.451E+08 2.471E+08 2.037E+08 1.502E+08 20 20 20 20 101010 116 216 316 120 220 2.186E+06 3 5.152E+06 1 7.542E+06 2 7.416E+07 8.061E+07 3.726E+07 1.043E+08 6.875E+07 e e e e e e e e e e e e e e e e e eeee 0e 0e 0e 1 4e 2 4e 3 4e 1 6e 2 6e 1.178E+08 3 6e 9.897E+07 10 1e 1.214E+08 10 2e 4.000E+08 10 3 1e 3.563E+08 16 2e 5.195E+08 16 3e 5.894E+08 16 1 6.341E+08 20 2 6.365E+08 20 8.461E+08 3 1.148E+09 1 1.029E+09 2 5.524E+08 5.234E+08 4.707E+08 2.227E+08 4.803E+08 k k k k k k k k k k k k k k k k i i i i i i i i i i i i i i i i k k k k k k k k k k k k k k k k k l l l l l l l lik l l l l l l l l l like lik i i i i i i i i i i i i i i i i i Ͳ like Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ l l l l l l l l l l l l l l l l l lik Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ es es es es es es es es es es es es es es es es es es um um um um um um um um um um um um um um um um um l l l l l l l l l l l l l l l l l l ll ll ll ll ll ll ll ll ll ll ll ll ll ll ll ll ill a ia ia ia ia ia ia ia ia ia ia ia ia ia ia ia ia ia r i b b b b b b b b b b b b b b b b b bi iimonas iimonas iimonas iimonas iimonas iimonas iimonas iimonas iimonas iimonas iimonas iimonas iimonas iimonas iimonas iimonas iimonas d d d d d d d d d d d d d d d d d zo izo izo izo izo izo izo izo izo izo izo izo izo izo izo izo izo izo zospiri zospiri zospiri zospiri zospiri zospiri zospiri zospiri zospiri zospiri zospiri zospiri zospiri zospiri zospiri zospiri zosp h h h h h h h h h h h h h h h h h Taxonomic GroupA DayA A RepA A A A A Copies A iA ill A A A A A A Azospirillum A K dii Kordiimonas Rhi Kor Kor Kor Kor Kor Kor Kor Kor Kor Kor Kor Kor Kor Kor Kor Kor Kor R R R R R R R R R R R R R R R R R Ͳ 1 08 07 L + + 906E+08 071E 914E+07 122E . . . . 1 322E 08 6.906E+08 6 6 2 751E 07 1.914E+07 1 4 2 2 3 3 3 3 0004 14 24 36 1.521E+07 16 1.354E+07 26 1.254E+07 3 2.257E+08 1 2.204E+08 2 6.967E+07 3 1.661E+08 1.322E+08 1.721E+08 6 6 0004 14 24 36 7.710E+06 16 7.603E+06 26 5.063E+06 3 1.457E+07 1 1.199E+07 2 1.578E+07 3 2.117E+07 1.858E+07 2.751E+07 0004 14 24 36 1.412E+06 16 1.140E+06 26 1.014E+06 3 1.227E+07 1 8.094E+06 2 1.392E+07 3 1.363E+07 1.711E+07 1.700E+07 10101016 116 216 320 7.918E+08 1 5.194E+08 2 5.363E+08 3 3.044E+08 1 5.484E+08 4.457E+08 7.858E+08 20 20 20 20 10101016 116 216 320 1.955E+07 120 2.335E+07 2 2.881E+07 3 5.220E+07 1 8.265E+07 2 5.974E+07 2.627E+07 3.069E+07 10101016 116 216 320 2.474E+07 120 2.899E+07 2 3.098E+07 3 1.958E+07 1 3.238E+07 2 2.313E+07 8.603E+07 4.616E+07 Day Rep Copies a i er t acteria acteria acteria acteria acteria acteria acteria acteria acteria acteria acteria acteria acteria acteria acteria acteria acteria ac b b b b b b b b b b b b b b b b b b 16S rRNA gene copies of taxonomic groups monitored by qPCR during DBT degradation without pH control (Figure 2.5). (Figure control without pH degradation qPCR during DBT by monitored groups of taxonomic copies 16S rRNA gene eo t aceae i aproteo aproteo aproteo aproteo aproteo aproteo aproteo aproteo aproteo aproteo aproteo aproteo aproteo aproteo aproteo aproteo aproteo apro er h h h h h h h h h h h h h h h h h h t p p p p p p p p p p p p p p p p p p p acteriaceae acteriaceae acteriaceae acteriaceae acteriaceae acteriaceae acteriaceae acteriaceae acteriaceae acteriaceae acteriaceae acteriaceae acteriaceae acteriaceae acteriaceae acteriaceae ac Al Al Al Al Al Al Al Al Al Al Al Al Al Al Al Al Al Al b b b b b b b b b b b b b b b b b er er er er er er er er er er er er er er er er er er h h h h h h h h h h h h h h h h h anctomycetaceae anctomycetaceae anctomycetaceae anctomycetaceae anctomycetaceae anctomycetaceae anctomycetaceae anctomycetaceae anctomycetaceae anctomycetaceae anctomycetaceae anctomycetaceae anctomycetaceae anctomycetaceae anctomycetaceae anctomycetaceae anctomycetaceae avo avo avo avo avo avo avo avo avo avo avo avo avo avo avo avo avo l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l F F F F F F F F F F F F F F Taxonomic Group F FlF b t i Flavobacteriaceae Fl P Pl P Planctomycetaceae Ot Ot Oth P P P P P P P P P P P P P P P Ot Ot Ot Ot Ot Ot Ot Ot Ot Ot Ot Ot Ot Ot Ot Table A.5. Table

176 Table A.6. 16S rRNA gene copies of taxonomic groups monitored by qPCR during DBT degradation with pH control (Figure 2.5).

TaxonomicGroup Day Rep CopiesLͲ1 TaxonomicGroup Day Rep CopiesLͲ1 FlFlavobacteriaceae b t i 01 4.378E+074 378E+07 Azospirillum i ill Ͳliklike 0 1 bd Flavobacteriaceae 0 2 3.238E+07 Azospirillum Ͳlike 0 2 bd Flavobacteriaceae 0 3 4.312E+07 Azospirillum Ͳlike 0 3 bd Flavobacteriaceae 4 1 2.484E+08 Azospirillum Ͳlike 4 1 bd Flavobacteriaceae 4 2 2.242E+08 Azospirillum Ͳlike 4 2 bd Flavobacteriaceae 4 3 1.862E+08 Azospirillum Ͳlike 4 3 bd Flavobacteriaceae 6 1 4.322E+08 Azospirillum Ͳlike 6 1 bd Flavobacteriaceae 6 2 4.390E+08 Azospirillum Ͳlike 6 2 bd Flavobacteriaceae 6 3 4.334E+08 Azospirillum Ͳlike 6 3 bd Flavobacteriaceae 10 1 5.430E+08 Azospirillum Ͳlike 10 1 bd Flavobacteriaceae 10 2 4.065E+08 Azospirillum Ͳlike 10 2 bd FlavobacteriaceaeFlavobacteriaceae 10 3 5. 930E+08930E+08 AzospirillumAzospirillum Ͳlikelike 10 3 bd Flavobacteriaceae 16 1 2.802E+08 Azospirillum Ͳlike 16 1 bd Flavobacteriaceae 16 2 5.290E+08 Azospirillum Ͳlike 16 2 bd Flavobacteriaceae 16 3 5.083E+08 Azospirillum Ͳlike 16 3 bd Flavobacteriaceae 20 1 nda Azospirillum Ͳlike 20 1 bd Flavobacteriaceae 20 2 3.643E+08 Azospirillum Ͳlike 20 2 bd Flavobacteriaceae 20 3 4.638E+08 Azospirillum Ͳlike 20 3 bd Flavobacteriaceae 24 1 9.446E+07 Azospirillum Ͳlike 24 1 bd Flavobacteriaceae 24 2 8.642E+07 Azospirillum Ͳlike 24 2 bd Flavobacteriaceae 24 3 1.034E+08 Azospirillum Ͳlike 24 3 bd Flavobacteriaceae 32 1 3.713E+08 Azospirillum Ͳlike 32 1 bd FlavobacteriaceaeFlavobacteriaceae 32 2 2. 320E+08 AzospirillumAzospirillum Ͳlikelike 32 2 bd Flavobacteriaceae 32 3 2.179E+08 Azospirillum Ͳlike 32 3 bd Planctomycetaceae 0 1 bdb Kordiimonas 0 1 9.594E+04 Planctomycetaceae 0 2 bd Kordiimonas 0 2 1.354E+05 Planctomycetaceae 0 3 bd Kordiimonas 0 3 8.311E+04 Planctomycetaceae 4 1 bd Kordiimonas 4 1 1.880E+06 Planctomycetaceae 4 2 bd Kordiimonas 4 2 2.365E+06 Planctomycetaceae 4 3 bd Kordiimonas 4 3 1.806E+06 Planctomycetaceae 6 1 bd Kordiimonas 6 1 4.482E+05 Planctomycetaceae 6 2 bd Kordiimonas 6 2 4.760E+05 Planctomycetaceae 6 3 bd Kordiimonas 6 3 5.643E+05 Planctomycetaceae 10 1 bd Kordiimonas 10 1 2. 510E+05 Planctomycetaceae 10 2 bd Kordiimonas 10 2 1.719E+03 Planctomycetaceae 10 3 bd Kordiimonas 10 3 1.991E+05 Planctomycetaceae 16 1 bd Kordiimonas 16 1 1.725E+05 Planctomycetaceae 16 2 bd Kordiimonas 16 2 2.542E+05 Planctomycetaceae 16 3 bd Kordiimonas 16 3 7.027E+05 Planctomycetaceae 20 1 bd Kordiimonas 20 1 1.575E+06 Planctomycetaceae 20 2 bd Kordiimonas 20 2 1.948E+06 Planctomycetaceae 20 3 bd Kordiimonas 20 3 1.818E+06 Planctomycetaceae 24 1 bd Kordiimonas 24 1 5.464E+06 Planctomycetaceae 24 2 bd Kordiimonas 24 2 3.985E+06 Planctomycetaceae 24 3 bd Kordiimonas 24 3 2. 958E+06 Planctomycetaceae 32 1 bd Kordiimonas 32 1 2.784E+06 Planctomycetaceae 32 2 bd Kordiimonas 32 2 1.610E+06 Planctomycetaceae 32 3 bd Kordiimonas 32 3 1.796E+06 OtherAlphaproteobacteria 0 1 6.890E+03 Rhizobiales Ͳlike 0 1 6.897E+04 OtherAlphaproteobacteria 0 2 9.956E+03 Rhizobiales Ͳlike 0 2 1.041E+05 OtherAlphaproteobacteria 0 3 8.102E+03 Rhizobiales Ͳlike 0 3 9.831E+04 OtherAlphaproteobacteria 4 1 3.572E+05 Rhizobiales Ͳlike 4 1 7.389E+05 OtherAlphaproteobacteria 4 2 8.118E+05 Rhizobiales Ͳlike 4 2 1.654E+06 OtherAlphaproteobacteria 4 3 5.642E+05 Rhizobiales Ͳlike 4 3 3.538E+06 OtherAlphaproteobacteria 6 1 2.611E+05 Rhizobiales Ͳlike 6 1 1.274E+07 OtherAlphaproteobacteria 6 2 2.998E2.998E+05+05 Rhizobiales Ͳlike 6 2 9.092E9.092E+06+06 OtherAlphaproteobacteria 6 3 3.182E+05 Rhizobiales Ͳlike 6 3 2.375E+07 OtherAlphaproteobacteria 10 1 8.758E+05 Rhizobiales Ͳlike 10 1 3.760E+07 OtherAlphaproteobacteria 10 2 5.597E+05 Rhizobiales Ͳlike 10 2 3.959E+07 OtherAlphaproteobacteria 10 3 6.278E+05 Rhizobiales Ͳlike 10 3 2.777E+07 OtherAlphaproteobacteria 16 1 2.930E+05 Rhizobiales Ͳlike 16 1 5.210E+07 OtherAlphaproteobacteria 16 2 5.792E+05 Rhizobiales Ͳlike 16 2 1.297E+08 OtherAlphaproteobacteria 16 3 6.761E+05 Rhizobiales Ͳlike 16 3 1.897E+08 OtherAlphaproteobacteria 20 1 4.007E+05 Rhizobiales Ͳlike 20 1 8.596E+07 OtherAlphaproteobacteria 20 2 3.845E+05 Rhizobiales Ͳlike 20 2 5.567E+07 OtherAlphaproteobacteria 20 3 2.482E+05 Rhizobiales Ͳlike 20 3 7.711E+07 OtherAAlphaproteobacterialphaproteobacteria 24 1 8.253E+058.253E+05 Rhizobiales Ͳlike 241 3 3.053E+08.053E+08 OtherAlphaproteobacteria 24 2 6.342E+05 Rhizobiales Ͳlike 24 2 3.639E+08 OtherAlphaproteobacteria 24 3 6.545E+05 Rhizobiales Ͳlike 24 3 2.916E+08 OtherAlphaproteobacteria 32 1 9.055E+05 Rhizobiales Ͳlike 32 1 1.582E+08 OtherAlphaproteobacteria 32 2 6.026E+05 Rhizobiales Ͳlike 32 2 1.110E+08 OtherAlphaproteobacteria 32 3 9.784E+05 Rhizobiales Ͳlike 32 3 9.242E+07 and:notdetermined bbd:belowdetection

177 Table A6. Continued.

TaxonomicGroup Day Rep CopiesLͲ1 Rhodospirillaceae Ͳlike 0 1 6.028E+05 Rhodospirillaceae Ͳlike 0 2 6.196E+05 Rhodospirillaceae Ͳlike 0 3 3.807E+05 Rhodospirillaceae Ͳlike 4 1 3.905E+06 Rhodospirillaceae Ͳlike 4 2 4.517E+06 Rhodospirillaceae Ͳlike 4 3 3.939E+06 Rhodospirillaceae Ͳlike 6 1 3.593E+06 Rhodospirillaceae Ͳlike 6 2 3.441E+06 Rhodospirillaceae Ͳlike 6 3 3.139E+06 Rhodospirillaceae Ͳlike 10 1 7.888E+06 Rhodospirillaceae Ͳlike 10 2 8.946E+06 Rhodospirillaceae Ͳlike 10 3 9.513E+06 Rhodospirillaceae Ͳlike 16 1 5.488E+06 Rhodospirillaceae Ͳlike 16 2 1.134E+07 Rhodospirillaceae Ͳlike 16 3 1.046E+07 Rhodospirillaceae Ͳlike 20 1 1.288E+07 Rhodospirillaceae Ͳlike 20 2 1.321E+07 Rhodospirillaceae Ͳlike 20 3 1.214E+07 Rhodospirillaceae Ͳlike 16 1 2.829E+07 Rhodospirillaceae Ͳlike 16 2 2.514E+07 Rhodospirillaceae Ͳlike 16 3 4.059E+07 Rhodospirillaceae Ͳlike 20 1 2.823E+07 Rhodospirillaceae Ͳlike 20 2 3.354E+07 Rhodospirillaceae Ͳlike 20 3 4.005E+07 Chromatiales 0 1 2.565E+07 Chromatiales 0 2 2.050E+07 Chromatiales 0 3 1.435E+07 Chromatiales 4 1 4.469E+07 Chromatiales 4 2 9.845E+07 Chromatiales 4 3 5.097E+07 Chromatiales 6 1 1.341E+08 Chromatiales 6 2 9.380E+07 Chromatiales 6 3 1.075E+08 Chromatiales 10 1 1.861E+08 Chromatiales 10 2 1.451E+08 Chromatiales 10 3 1.180E+08 Chromatiales 16 1 8.500E+08 Chromatiales 16 2 1.158E+09 Chromatiales 16 3 1.238E+09 Chromatiales 20 1 1.696E+09 Chromatiales 20 2 1.399E+09 Chromatiales 20 3 1.208E+09 Chromatiales 16 1 9.755E+08 Chromatiales 16 2 2.287E+09 Chromatiales 16 3 1.730E+09 Chromatiales 20 1 2.194E+09 Chromatiales 20 2 1.633E+09 Chromatiales 20 3 2.241E+09 Pseudomonas 0 1 9.878E+05 Pseudomonas 0 2 7.816E+05 Pseudomonas 0 3 9.158E+05 Pseudomonas 4 1 1.772E+06 Pseudomonas 4 2 1.149E+06 Pseudomonas 4 3 1.884E+06 Pseudomonas 6 1 1.423E+06 Pseudomonas 6 2 1.546E+06 Pseudomonas 6 3 1.008E+06 Pseudomonas 10 1 1.723E+06 Pseudomonas 10 2 2.834E+06 Pseudomonas 10 3 2.321E+06 Pseudomonas 16 1 2.993E+06 Pseudomonas 16 2 5.209E+06 Pseudomonas 16 3 5.476E+06 Pseudomonas 20 1 8.243E+06 Pseudomonas 20 2 8.124E+06 Pseudomonas 20 3 1.135E+07 Pseudomonas 16 1 1.872E+07 Pseudomonas 16 2 1.735E+07 Pseudomonas 16 3 1.720E+07 Pseudomonas 20 1 3.597E+07 Pseudomonas 20 2 3.117E+07 Pseudomonas 20 3 2.901E+07

178 Copy 03 40 00 . . . 0 0 0 Numbers Relative 3 3 3 000 14 24 34 16 26 0.27 36 0.30 1 0.27 2 0.13 3 0.14 0.14 0.16 0.17 0.15 000 14 24 34 16 26 0.07 36 0.06 1 0.05 2 0.04 3 0.03 0.04 0.03 0.03 0.04 20 20 20 101010 116 216 316 120 220 0.24 3 0.23 1 0.28 2 0.45 0.44 0.41 0.54 0.70 101010 116 216 316 120 220 0.03 3 0.03 1 0.04 2 0.05 0.05 0.05 0.00 0.00 Day Rep eeeee 0e 0e 0e 1 4e 2 4e 3 4e 1 6e 2 6 0.03 e 3 6 0.03 e 10 1 0.03 e 10 2 0.05 e 10 3 1 0.04 e 16e 2 0.06 16 3 0.06 16 1 0.08 20 2 0.07 20 0.03 3 0.04 1 0.04 2 0.04 0.04 0.04 0.04 0.04 k k k k k k k k k k k k k k k k k i i i i i i i i i i i i i i i i i l l l l l l l l l l l l l l l l l lik Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ aceae aceae aceae aceae aceae aceae aceae aceae aceae aceae aceae aceae aceae aceae aceae aceae aceae aceae es es es es es es es es es es es es es es es es es es ll ll ll ll ll ll ll ll ll ll ll ll ll ll ll ll ll l l l l l l l l l l l l l l l l l l ill a r i ti omonas omonas omonas omonas omonas omonas omonas omonas omonas omonas omonas omonas omonas omonas omonas omonas omonas omonas ospiri ospiri ospiri ospiri ospiri ospiri ospiri ospiri ospiri ospiri ospiri ospiri ospiri ospiri ospiri ospiri ospiri osp d d d d d d d d d d d d d d d d d d d d d d d d d d d d d d d d d d d d o o o o o o o o o o o o o o o o o o romatia romatia romatia romatia romatia romatia romatia romatia romatia romatia romatia romatia romatia romatia romatia romatia romatia roma h h h h h h h h h h h h h h h h h h h h h h h h h h h h h h h h h h seu R R R R R R R R R R R R R R R R R C C C C C C C C C C C C C C C C C Rh Ch P Pseu Pseu Pseu Pseu Pseu Pseu Pseu Pseu Pseu Pseu Pseu Pseu Pseu Pseu Pseu Pseu Pseu Copy 03 02 03 . . . 0 0 0 Numbers Taxonomic Group Relative 3 3 3 000 14 24 34 16 26 0.05 36 0.04 1 0.05 2 0.03 3 0.04 0.04 0.04 0.06 0.04 000 14 24 34 16 26 0.01 36 0.01 1 0.00 2 0.00 3 0.00 0.00 0.00 0.00 0.00 101010 116 216 316 120 220 0.01 3 0.01 1 0.02 2 0.05 0.06 0.05 0.04 0.05 101010 116 216 316 120 220 0.00 3 0.00 1 0.00 2 0.02 0.02 0.01 0.03 0.02 20 20 20 e e e e e e e e e e e e e e e e e e eeee 0e 0e 0e 1 4e 2 4e 3 4e 1 6e 2 6 0.48 e 3 6 0.51 e 10 1 0.56 e 10 2 0.55 e 10 3 1 0.45 e 16 2 0.53 e 16 3 0.50 e 16 1 0.60 20 2 0.56 20 0.35 3 0.32 1 0.36 2 0.18 0.12 0.12 0.06 0.12 k k k k k k k k k k k k k k k k k i i i i i i i i i i i i i i i i i k k k k k k k k k k k k k k k k k l l l l l l l l l l l l l l l l l lik i i i i i i i i i i i i i i i i i Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ l l l l l l l l l l l l l l l l l lik Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ es es es es es es es es es es es es es es es es es es um um um um um um um um um um um um um um um um um um l l l l l l l l l l l l l l l l l l ll ll ll ll ll ll ll ll ll ll ll ll ll ll ll ll ll ill a ia ia ia ia ia ia ia ia ia ia ia ia ia ia ia ia ia r i monas b b b b b b b b b b b b b b b b b bi iimonas iimonas iimonas iimonas iimonas iimonas iimonas iimonas iimonas iimonas iimonas iimonas iimonas iimonas iimonas iimonas iimonas d d d d d d d d d d d d d d d d d dii zo izo izo izo izo izo izo izo izo izo izo izo izo izo izo izo izo izo zospiri zospiri zospiri zospiri zospiri zospiri zospiri zospiri zospiri zospiri zospiri zospiri zospiri zospiri zospiri zospiri zospiri zosp h h h h h h h h h h h h h h h h h or Kor Kor Kor Kor Kor Kor Kor Kor Kor Kor Kor Kor Kor Kor Kor Kor Kor R R R R R R R R R R R R R R R R R A A A A A A A A A A A A A A A A A A K Rhi Copy 12 00 01 . . . 0 0 0 Numbers Taxonomic Group Day Rep Relative 3 3 3 0004 14 24 36 16 26 0.06 3 0.07 1 0.06 2 0.31 3 0.28 0.07 0.14 0.12 0.15 0004 14 24 36 16 26 0.03 3 0.04 1 0.02 2 0.02 3 0.02 0.02 0.02 0.02 0.02 0004 14 24 36 16 26 0.01 3 0.01 1 0.00 2 0.02 3 0.01 0.01 0.01 0.02 0.01 10101016 116 216 320 120 2 0.33 3 0.15 1 0.19 2 0.10 0.13 0.11 0.20 0.17 20 20 20 10101016 116 216 320 120 2 0.01 3 0.01 1 0.01 2 0.02 0.02 0.02 0.01 0.01 10101016 116 216 320 120 2 0.01 3 0.01 1 0.01 2 0.01 0.01 0.01 0.02 0.01 Day Rep a i er t acteria acteria acteria acteria acteria acteria acteria acteria acteria acteria acteria acteria acteria acteria acteria acteria acteria ac Relative 16S rRNA gene copy numbers of taxonomic groups monitored during DBT degradation without pH control control without pH degradation during DBT monitored groups taxonomic of numbers copy gene 16S rRNA Relative b b b b b b b b b b b b b b b b b b eo t aceae t aceae i aproteo aproteo aproteo aproteo aproteo aproteo aproteo aproteo aproteo aproteo aproteo aproteo aproteo aproteo aproteo aproteo aproteo apro er h h h h h h h h h h h h h h h h h h t p p p p p p p p p p p p p p p p p p acteriaceae acteriaceae acteriaceae acteriaceae acteriaceae acteriaceae acteriaceae acteriaceae acteriaceae acteriaceae acteriaceae acteriaceae acteriaceae acteriaceae acteriaceae acteriaceae acteriaceae ac Al Al Al Al Al Al Al Al Al Al Al Al Al Al Al Al Al Al omyce t b b b b b b b b b b b b b b b b b b er er er er er er er er er er er er er er er er er er h h h h h h h h h h h h h h h h h anctomycetaceae anctomycetaceae anctomycetaceae anctomycetaceae anctomycetaceae anctomycetaceae anctomycetaceae anctomycetaceae anctomycetaceae anctomycetaceae anctomycetaceae anctomycetaceae anctomycetaceae anctomycetaceae anctomycetaceae anctomycetaceae anctomycetaceae anc avo avo avo avo avo avo avo avo avo avo avo avo avo avo avo avo avo avo l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l P P P P P P P P P P P P P P P P Taxonomic Group Fl P Pl Ot Oth Ot Ot Ot Ot Ot Ot Ot Ot Ot Ot Ot Ot Ot Ot Ot Ot F F F F F F F F F F F F F F F F F Table A.7. Table 2.6). (Figure

179 Table A.8. Relative 16S rRNA gene copy numbers of taxonomic groups monitored during DBT degradation with pH control (Figure 2.6).

RelativeCopy TaxonomicGroup Day Rep Numbers TaxonomicGroup Day Rep Flavobacteriaceae 0 1 0.58 Azospirillum Ͳlike 01 Flavobacteriaceae 0 2 0.53 Azospirillum Ͳlike 02 Flavobacteriaceae 0 3 0.74 Azospirillum Ͳlike 03 Flavobacteriaceae 4 1 0.66 Azospirillum Ͳlike 41 Flavobacteriaceae 4 2 0.56 Azospirillum Ͳlike 42 Flavobacteriaceae 4 3 0.49 Azospirillum Ͳlike 43 Flavobacteriaceae 6 1 0.60 Azospirillum Ͳlike 61 Flavobacteriaceae 6 2 0.61 Azospirillum Ͳlike 62 Flavobacteriaceae 6 3 0.65 Azospirillum Ͳlike 63 Flavobacteriaceae 10 1 0.61 Azospirillum Ͳlike 10 1 Flavobacteriaceae 10 2 0.55 Azospirillum Ͳlike 10 2 Flavobacteriaceae 10 3 0.57 Azospirillum Ͳlike 10 3 Flavobacteriaceae 16 1 0.18 Azospirillum Ͳlike 16 1 Flavobacteriaceae 16 2 0.23 Azospirillum Ͳlike 16 2 Flavobacteriaceae 16 3 0.24 Azospirillum Ͳlike 16 3 Flavobacteriaceae 20 1 nda Azospirillum Ͳlike 20 1 Flavobacteriaceae 20 2 0.13 Azospirillum Ͳlike 20 2 Flavobacteriaceae 20 3 0.20 Azospirillum Ͳlike 20 3 Flavobacteriaceae 24 1 0.04 Azospirillum Ͳlike 24 1 Flavobacteriaceae 24 2 0.03 Azospirillum Ͳlike 24 2 Flavobacteriaceae 24 3 0.04 Azospirillum Ͳlike 24 3 Flavobacteriaceae 32 1 0.10 Azospirillum Ͳlike 32 1 Flavobacteriaceae 32 2 0.08 Azospirillum Ͳlike 32 2 Flavobacteriaceae 32 3 0.06 Azospirillum Ͳlike 32 3 Planctomycetaceae 0 1 bdb Kordiimonas 01 Planctomycetaceae 0 2 bd Kordiimonas 02 Planctomycetaceae 0 3 bd Kordiimonas 03 Planctomycetaceae 4 1 bd Kordiimonas 41 Planctomycetaceae 4 2 bd Kordiimonas 42 Planctomycetaceae 4 3 bd Kordiimonas 43 Planctomycetaceae 6 1 bd Kordiimonas 61 Planctomycetaceae 6 2 bd Kordiimonas 62 Planctomycetaceae 6 3 bd Kordiimonas 63 Planctomycetaceae 10 1 bd Kordiimonas 10 1 Planctomycetaceae 10 2 bd Kordiimonas 10 2 Planctomycetaceae 10 3 bd Kordiimonas 10 3 Planctomycetaceae 16 1 bd Kordiimonas 16 1 Planctomycetaceae 16 2 bd Kordiimonas 16 2 Planctomycetaceae 16 3 bd Kordiimonas 16 3 Planctomycetaceae 20 1 bd Kordiimonas 20 1 Planctomycetaceae 20 2 bd Kordiimonas 20 2 Planctomycetaceae 20 3 bd Kordiimonas 20 3 Planctomycetaceae 24 1 bd Kordiimonas 24 1 Planctomycetaceae 24 2 bd Kordiimonas 24 2 Planctomycetaceae 24 3 bd Kordiimonas 24 3 Planctomycetaceae 32 1 bd Kordiimonas 32 1 Planctomycetaceae 32 2 bd Kordiimonas 32 2 Planctomycetaceae 32 3 bd Kordiimonas 32 3 OtherAlphaproteobacteria 0 1 0.00 Rhizobiales Ͳlike 0 1 OtherAlphaproteobacteria 0 2 0.00 Rhizobiales Ͳlike 0 2 OtherAlphaproteobacteria 0 3 0.00 Rhizobiales Ͳlike 0 3 OtherAlphaproteobacteria 4 1 0.00 Rhizobiales Ͳlike 4 1 OtherAlphaproteobacteria 4 2 0.00 Rhizobiales Ͳlike 4 2 OtherAlphaproteobacteria 4 3 0.00 Rhizobiales Ͳlike 4 3 OtherAlphaproteobacteria 6 1 0.00 Rhizobiales Ͳlike 6 1 OtherAlphaproteobacteria 6 2 0.00 Rhizobiales Ͳlike 6 2 OtherAlphaproteobacteria 6 3 0.00 Rhizobiales Ͳlike 6 3 OtherAlphaproteobacteria 10 1 0.00 Rhizobiales Ͳlike 10 1 OtherAlphaproteobacteria 10 2 0.00 Rhizobiales Ͳlike 10 2 OtherAlphaproteobacteria 10 3 0.00 Rhizobiales Ͳlike 10 3 OtherAlphaproteobacteria 16 1 0.00 Rhizobiales Ͳlike 16 1 OtherAlphaproteobacteria 16 2 0.00 Rhizobiales Ͳlike 16 2 OtherAlphaproteobacteria 16 3 0.00 Rhizobiales Ͳlike 16 3 OtherAlphaproteobacteria 20 1 0.00 Rhizobiales Ͳlike 20 1 OtherAlphaproteobacteria 20 2 0.00 Rhizobiales Ͳlike 20 2 OtherAlphaproteobacteria 20 3 0.00 Rhizobiales Ͳlike 20 3 OtherAlphaproteobacteria 24 1 0.00 Rhizobiales Ͳlike 24 1 OtherAlphaproteobacteria 24 2 0.00 Rhizobiales Ͳlike 24 2 OtherAlphaproteobacteria 24 3 0.00 Rhizobiales Ͳlike 24 3 OtherAlphaproteobacteria 32 1 0.00 Rhizobiales Ͳlike 32 1 OtherAlphaproteobacteria 32 2 0.00 Rhizobiales Ͳlike 32 2 OtherAlphaproteobacteria 32 3 0.00 Rhizobiales Ͳlike 32 3 and:notdetermined bbd:belowdetection

180 Table A8. Continued.

RelativeCopy TaxonomicGroup Day Rep Numbers Rhodospirillaceae Ͳlike 0 1 0.01 Rhodospirillaceae Ͳlike 0 2 0.01 Rhodospirillaceae Ͳlike 0 3 0.01 Rhodospirillaceae Ͳlike 4 1 0.01 Rhodospirillaceae Ͳlike 4 2 0.01 Rhodospirillaceae Ͳlike 4 3 0.01 Rhodospirillaceae Ͳlike 6 1 0.01 Rhodospirillaceae Ͳlike 6 2 0.00 Rhodospirillaceae Ͳlike 6 3 0.00 Rhodospirillaceae Ͳlike 10 1 0.01 Rhodospirillaceae Ͳlike 10 2 0.01 Rhodospirillaceae Ͳlike 10 3 0.01 Rhodospirillaceae Ͳlike 16 1 0.00 Rhodospirillaceae Ͳlike 16 2 0.00 Rhodospirillaceae Ͳlike 16 3 0.00 Rhodospirillaceae Ͳlike 20 1 0.01 Rhodospirillaceae Ͳlike 20 2 0.00 Rhodospirillaceae Ͳlike 20 3 0.01 Rhodospirillaceae Ͳlike 16 1 0.01 Rhodospirillaceae Ͳlike 16 2 0.01 Rhodospirillaceae Ͳlike 16 3 0.01 Rhodospirillaceae Ͳlike 20 1 0.01 Rhodospirillaceae Ͳlike 20 2 0.01 Rhodospirillaceae Ͳlike 20 3 0.01 Chromatiales 0 1 0.34 Chromatiales 0 2 0.34 Chromatiales 0 3 0.25 Chromatiales 4 1 0.12 Chromatiales 4 2 0.24 Chromatiales 4 3 0.14 Chromatiales 6 1 0.19 Chromatiales 6 2 0.13 Chromatiales 6 3 0.16 Chromatiales 10 1 0.21 Chromatiales 10 2 0.19 Chromatiales 10 3 0.11 Chromatiales 16 1 0.55 Chromatiales 16 2 0.50 Chromatiales 16 3 0.59 Chromatiales 20 1 0.76 Chromatiales 20 2 0.49 Chromatiales 20 3 0.53 Chromatiales 16 1 0.41 Chromatiales 16 2 0.67 Chromatiales 16 3 0.61 Chromatiales 20 1 0.59 Chromatiales 20 2 0.55 Chromatiales 20 3 0.60 Pseudomonas 0 1 0.01 Pseudomonas 0 2 0.01 Pseudomonas 0 3 0.02 Pseudomonas 4 1 0.00 Pseudomonas 4 2 0.00 Pseudomonas 4 3 0.00 Pseudomonas 6 1 0.00 Pseudomonas 6 2 0.00 Pseudomonas 6 3 0.00 Pseudomonas 10 1 0.00 Pseudomonas 10 2 0.00 Pseudomonas 10 3 0.00 Pseudomonas 16 1 0.00 Pseudomonas 16 2 0.00 Pseudomonas 16 3 0.00 Pseudomonas 20 1 0.00 Pseudomonas 20 2 0.00 Pseudomonas 20 3 0.00 Pseudomonas 16 1 0.01 Pseudomonas 16 2 0.01 Pseudomonas 16 3 0.01 Pseudomonas 20 1 0.01 Pseudomonas 20 2 0.01 Pseudomonas 20 3 0.01

181 Ap p e n d i x B: Ch a p t e r 3 Da t a Table B.1. Inhibition of luminescence in Vibrio fischeri exposed to DBT and selected DBT degradation products (Figure 3.19).

InitialLuminescence FinalLuminescence Luminescence Compound Concentration,µM Replicate Units Units Inhŝbition,% Control 0 1 171846 123357 0.00 Control 0 2 143291 123977 0.00 Control 0 3 176078 128879 0.00 benzoicacid 0 1 179827 13756 89.34 benzoicacid 0 2 181563 14639 88.77 benzoicacid 0 3 190021 153043 0.00 benzoicacid 0.1 1 192193 150279 0.00 benzoic acid 010.1 2 170293 150600 0. 00 benzoicacid 0.1 3 178344 132778 0.00 benzoicacid 1 1 189920 161781 0.00 benzoicacid 1 2 166312 150211 0.00 benzoicacid 1 3 188436 138880 0.00 benzoicacid 10 1 194287 157958 0.00 benzoicacid 10 2 181332 170016 0.00 benzoicacid 10 3 191002 143150 0.00 benzoicacid 100 1 195946 159599 0.00 benzoicacid 100 2 179605 146220 5.90 benzoicacid 100 3 195496 152498 0.00 bibenzoicacidid 1000 1 195767 142320 00.00 00 benzoicacid 1000 2 188391 166521 0.00 benzoicacid 1000 3 193821 149942 0.00 benzoicacid 10000 1 189181 75495 44.41 benzoicacid 10000 2 176681 74682 51.15 benzoicacid 10000 3 184060 84585 37.10 benzothiopheneͲ2,3Ͳdione 0 1 187915 146587 0.00 benzothiopheneͲ2,3Ͳdione 0 2 177461 129832 0.00 benzothiopheneͲ2,3Ͳdione 0 3 185901 150023 0.00 benzothiopheneͲ2,3Ͳdione 0.01 1 196116 150903 0.00 benzothiophenep,Ͳ2,3Ͳdione 0.01 2 177408 157603 0.00 benzothiopheneͲ2,3Ͳdione 0.01 3 195974 165711 0.00 benzothiopheneͲ2,3Ͳdione 0.1 1 185350 131823 0.92 benzothiopheneͲ2,3Ͳdione 0.1 2 165762 123076 0.00 benzothiopheneͲ2,3Ͳdione 0.1 3 186577 139312 0.00 benzothiopheneͲ2,3Ͳdione 0.5 1 185061 135585 0.00 benzothiopheneͲ2,3Ͳdione 0.5 2 161690 139370 0.38 benzothiopheneͲ2,3Ͳdione 0.5 3 180050 143200 0.00 benzothiopheneͲ2,3Ͳdione 1 1 187825 143646 0.00 benzothiopheneͲ2,3Ͳdione 1 2 163150 149546 0.00 benzothiopheneͲ2,3Ͳdione 1 3 189954 148544 0.00 benzothiopheneͲ22,3,3Ͳdione 2.52.5 1 190643 150971 0.000.00 benzothiopheneͲ2,3Ͳdione 2.5 2 170961 156582 0.00 benzothiopheneͲ2,3Ͳdione 2.5 3 194032 158882 0.00 benzothiopheneͲ2,3Ͳdione 10 1 193180 153050 0.00 benzothiopheneͲ2,3Ͳdione 10 2 167654 154266 0.00 benzothiopheneͲ2,3Ͳdione 10 3 194836 165198 0.00 benzothiopheneͲ2,3Ͳdione 1000 1 195272 134741 3.88 benzothiopheneͲ2,3Ͳdione 1000 2 177044 147113 3.96 benzothiopheneͲ2,3Ͳdione 1000 3 194871 138129 2.98 DBT 0 1 197674 168922 0.00 DBT 0 2 176508 149001 0.00 DBT 0 3 190125 156987 0. 00 DBT 0.001 1 177629 129274 0.00 DBT 0.001 2 147047 119541 0.00 DBT 0.001 3 182739 140355 0.00 DBT 0.015 1 178858 133099 0.00 DBT 0.01 2 146806 121305 4.50 DBT 0.01 3 185197 147146 0.00 DBT 0.12 1 178992 150887 0.00 DBT 0.1 2 152433 136596 0.00 DBT 0.1 3 181753 156714 0.00 DBT 0.469 1 182940 150015 0.00

182 Table B1. Continued.

InitialLuminescence FinalLuminescence Luminescence Compound Concentration,µM Replicate Units Units Inhŝbition,% DBTsulfone 0 1 193421 159433 0.00 DBTsulfone 0 2 183236 146705 0.00 DBTsulfone 0 3 178302 145436 0.00 DBTsulfone 0.01 1 185063 139202 0.00 DBTsulfone 0.01 2 159472 140641 0.00 DBTsulfone 0.01 3 182939 144217 0.00 DBTsulfone 0.1 1 189354 145799 0.00 DBTsulfone 010.1 2 167511 144359 0. 39 DBTsulfone 0.1 3 189485 150105 0.00 DBTsulfone 0.5 1 191472 150938 0.00 DBTsulfone 0.5 2 169063 156482 0.00 DBTsulfone 0.5 3 199093 174125 0.00 DBTsulfone 1 1 195849 158310 0.00 DBTsulfone 1 2 169319 153238 0.00 DBTsulfone 1 3 194593 164754 0.00 DBTsulfone 10 1 195406 152576 0.00 DBTsulfone 10 2 171706 158256 0.00 DBTsulfone 10 3 194230 166824 0.00 DBTsulfone lf 1000 1 196456 142580 00.00 00 DBTsulfone 1000 2 171253 149966 0.00 DBTsulfone 1000 3 195685 146470 0.00 Dithiosalicylicacid 0 1 195584 150643 0.00 Dithiosalicylicacid 0 2 187688 150012 0.00 Dithiosalicylicacid 0 3 192321 149023 0.00 Dithiosalicylicacid 0.001 1 195012 155053 0.00 Dithiosalicylicacid 0.001 2 175212 152408 0.00 Dithiosalicylicacid 0.001 3 194683 161095 0.00 Dithiosalicylicacid 0.01 1 196149 157319 0.00 Dithiosalicylicy acid 0.01 2 179642 157380 0.00 Dithiosalicylicacid 0.01 3 193622 163784 0.00 Dithiosalicylicacid 0.1 1 197465 157203 0.00 Dithiosalicylicacid 0.1 2 184994 166396 0.00 Dithiosalicylicacid 0.1 3 196937 165406 0.00 Dithiosalicylicacid 0.5 1 189942 137088 0.00 Dithiosalicylicacid 0.5 2 169452 146779 0.00 Dithiosalicylicacid 0.5 3 188840 147212 0.00 Dithiosalicylicacid 1 1 185363 142359 0.00 Dithiosalicylicacid 1 2 158745 145676 0.00 Dithiosalicylicacid 1 3 179197 135530 0.00 Dithiosalicylic acid 10 1 189298 144982 0.000.00 Dithiosalicylicacid 10 2 164788 145596 0.00 Dithiosalicylicacid 10 3 189020 142447 0.00 Dithiosalicylicacid 1000 1 193605 120788 13.09 Dithiosalicylicacid 1000 2 173006 119743 20.00 Dithiosalicylicacid 1000 3 195212 113787 20.22 thioindigo 0 1 182208 144365 0.00 thioindigo 0 2 198960 143876 1.02 thioindigo 0 3 174490 132043 0.00 thioindigo 0.01 1 190154 143441 0.00 thioindigo 0.01 2 177273 152488 0.58 thioindigothioindigo 0. 01 3 189990 143077 0. 00 thioindigo 0.1 1 196684 158167 0.00 thioindigo 0.1 2 179921 158395 0.00 thioindigo 0.1 3 194503 158521 0.00 thioindigo 0.5 1 196477 159247 0.00 thioindigo 0.5 2 177444 159122 0.00 thioindigo 0.5 3 196422 171763 0.00 thioindigo 1 1 197906 156417 0.00 thioindigo 1 2 191078 168595 0.00 thioindigo 1 3 199631 180978 0.00 thioindigo 1.5 1 189484 142938 0.00

183 Table B1. Continued.

InitialLuminescence FinalLuminescence Luminescence Compound Concentration,µM Replicate Units Units Inhŝbition,% thiosalicylicacid 0 1 195633 146582 0.00 thiosalicylicacid 0 2 173209 136573 0.00 thiosalicylicacid 0 3 185638 135648 0.00 thiosalicylicacid 0.1 1 196594 161104 0.00 thiosalicylicacid 0.1 2 176355 158499 0.00 thiosalicylicacid 0.1 3 194577 169928 0.00 thiosalicylicacid 0.5 1 196940 156432 0.00 thiosalicylicacid 050.5 2 184786 164484 0. 00 thiosalicylicacid 0.5 3 199113 176263 0.00 thiosalicylicacid 1 1 190565 135948 0.62 thiosalicylicacid 1 2 168521 148509 0.00 thiosalicylicacid 1 3 189331 147262 0.00 thiosalicylicacid 5 1 188293 135942 0.00 thiosalicylicacid 5 2 160443 138765 0.04 thiosalicylicacid 5 3 186125 142417 0.00 thiosalicylicacid 10 1 188834 132362 2.35 thiosalicylicacid 10 2 164701 136757 4.03 thiosalicylicacid 10 3 189006 133877 3.05 thithiosalicylic li liacid id 1000 1 193479 118998 1414.32 32 thiosalicylicacid 1000 2 169309 127359 13.06 thiosalicylicacid 1000 3 192817 121213 13.96 thiosalicylicacid 10000 1 193551 94801 31.77 thiosalicylicacid 10000 2 167713 89821 38.10 thiosalicylicacid 10000 3 197903 95209 34.15

184 Table B.2. Concentrations of DBT and other compounds analyzed by GC/MS in extracts from culture media during DBT degradation without pH control (Figures 3.20 and 3.21).

ConcentrationinFlask AAnalytical l ti l (µM)( M)orRelativeR l ti Compound Day Replicate Area Concentration(µM) Response(RR) Unit 2Ͳnaphthol(internalstandard) 0 1 579525 20 naa µM 2Ͳnaphthol 0 2 3826396 20 na µM 2Ͳnaphthol 2 1 869229 20 na µM 2Ͳnaphthol 2 2 979322 20 na µM 2Ͳnaphthol 2 3 1123412 20 na µM 2Ͳnaphthol 4 1 1086621 20 na µM 2Ͳnaphthol 4 2 1453022 20 na µM 2Ͳnaphthol 4 3 1215334 20 na µM 2Ͳnaphthol 6 1 875131 20 na µM 2Ͳnaphthol 6 2 1032311 20 na µM 2Ͳnaphthol 6 3 1196493 20 na µM 2Ͳnaphthol 10 1 745345 20 na µM 2Ͳnaphthol 10 2 540320 20 na µM 2Ͳnaphthol 10 3 227425 20 na µM 2Ͳnaphthol 14 1 988040 20 na µM 2Ͳnaphthol 14 2 1035186 20 na µM 2Ͳnaphthol 14 3 1739586 20 na µM 2Ͳnaphthol 20 1 1214494 20 na µM 2Ͳnaphthol 20 2 962879 20 na µM 2Ͳnaphthol 20 3 929181 20 na µM Thiosalicylicacid 0 1 0 0 0 µM Thiosalicylicacid 0 2 0 0 0 µM Thiosalicylicacid 2 1 56624 12.400 0.165 µM Thiosalicylicacid 2 2 45160 17.254 0.230 µM Thiosalicylicacid 2 3 42678 14.025 0.187 µM Thiosalicylicacid 4 1 103588 20.930 0.279 µM Thiosalicylicacid 4 2 74678 24.075 0.321 µM Thiosalicylicacid 4 3 98154 16.051 0.214 µM Thiosalicylicacid 6 1 68462 13.742 0.183 µM Thiosalicylicacid 6 2 54873 15.675 0.209 µM Thiosalicylicacid 6 3 45578 11.325 0.151 µM Thiosalicylicacid 10 1 16558 8.850 0.118 µM Thiosalicylicacid 10 2 10995 12.225 0.163 µM Thiosalicylicacid 10 3 16817 6.525 0.087 µM Thiosalicylicacid 14 1 49245 8.753 0.117 µM Thiosalicylicacid 14 2 57648 9.781 0.130 µM Thiosalicylicacid 14 3 44534 7.351 0.098 µM Thiosalicylicacid 20 1 0 0 0 µM Thiosalicylicacid 20 2 0 0 0 µM Thiosalicylicacid 20 3 0 0 0 µM 2Ͳhydroxybenzothiophene 0 1 0 na 0 RR 2Ͳhydroxybenzothiophene 0 2 0 na 0 RR 2Ͳhydroxybenzothiophene 2 1 134638 na 0.155 RR 2Ͳhydroxybenzothiophene 2 2 124873 na 0.144 RR 2Ͳhydroxybenzothiophene 2 3 102014 na 0.117 RR 2Ͳhydroxybenzothiophene 4 1 1456986 na 1.341 RR 2Ͳhydroxybenzothiophene 4 2 1524665 na 1.403 RR 2Ͳhydroxybenzothiophene 4 3 845372 na 0.778 RR 2Ͳhydroxybenzothiophene 6 1 2557835 na 2. 923 RR 2Ͳhydroxybenzothiophene 6 2 1845789 na 2.109 RR 2Ͳhydroxybenzothiophene 6 3 1975428 na 2.257 RR 2Ͳhydroxybenzothiophene 10 1 1293004 na 1.735 RR 2Ͳhydroxybenzothiophene 10 2 669690 na 1.239 RR 2Ͳhydroxybenzothiophene 10 3 254575 na 1.119 RR 2Ͳhydroxybenzothiophene 14 1 639250 na 0.647 RR 2Ͳhydroxybenzothiophene 14 2 530618 na 0.513 RR 2Ͳhydroxybenzothiophene 14 3 404530 na 0.391 RR 2Ͳhydroxybenzothiophene 20 1 253748 na 0.209 RR 2Ͳhydroxybenzothiophene 20 2 116922 na 0.121 RR 2Ͳhhydroxybenzothiopheneydroxybenzothiophene 20 3 147679 na 0. 159 RR 3Ͳhydroxybenzothiophene 0 1 0 na 0 RR 3Ͳhydroxybenzothiophene 0 2 0 na 0 RR 3Ͳhydroxybenzothiophene 2 1 634163 na 0.730 RR

185 Table B.2. Continued.

ConcentrationinFlask AAnalytical l ti l (µM)( M)orRelativeR l ti Compound Day Replicate Area Concentration(µM) Response(RR) Unit 3Ͳhydroxybenzothiophene 2 2 316471 na 0.364 RR 3Ͳhydroxybenzothiophene 2 3 452678 na 0.521 RR 3Ͳhydroxybenzothiophene 4 1 1233164 na 1.135 RR 3Ͳhydroxybenzothiophene 4 2 1167925 na 1.075 RR 3Ͳhydroxybenzothiophene 4 3 805675 na 0.741 RR 3Ͳhydroxybenzothiophene 6 1 1756894 na 2.008 RR 3Ͳhydroxybenzothiophene 6 2 1249252 na 1.428 RR 3Ͳhydroxybenzothiophene 6 3 1087965 na 1.243 RR 3Ͳhhydroxybenzothiopheneydroxybenzothiophene 101 1334068 na 1.790 RR 3Ͳhydroxybenzothiophene 10 2 857856 na 1.588 RR 3Ͳhydroxybenzothiophene 10 3 622084 na 1.151 RR 3Ͳhydroxybenzothiophene 14 1 2956181 na 2.992 RR 3Ͳhydroxybenzothiophene 14 2 2139168 na 2.066 RR 3Ͳhydroxybenzothiophene 14 3 2315431 na 2.237 RR 3Ͳhydroxybenzothiophene 20 1 813076 na 0.669 RR 3Ͳhydroxybenzothiophene 20 2 553125 na 0.574 RR 3Ͳhydroxybenzothiophene 20 3 532534 na 0.573 RR benzothiopheneͲ2,3Ͳdione 0 1 0 0 0 µM benzothiopheneͲ2,3Ͳdione 0 2 0 0 0 µM benzothiopheneͲ22,3,3Ͳdione 2 1 6323903 25.85325.853 0.3450.345 µM benzothiopheneͲ2,3Ͳdione 2 2 6045820 22.931 0.306 µM benzothiopheneͲ2,3Ͳdione 2 3 4501879 31.811 0.424 µM benzothiopheneͲ2,3Ͳdione 4 1 8585191 43.743 0.583 µM benzothiopheneͲ2,3Ͳdione 4 2 9457822 37.717 0.503 µM benzothiopheneͲ2,3Ͳdione 4 3 7545681 30.419 0.406 µM benzothiopheneͲ2,3Ͳdione 6 1 10699440 59.865 0.798 µM benzothiopheneͲ2,3Ͳdione 6 2 9487562 54.124 0.722 µM benzothiopheneͲ2,3Ͳdione 6 3 11245672 63.827 0.851 µM benzothiopheneͲ2,3Ͳdione 10 1 8092502 41.441 0.553 µM benzothiopheneͲ2,3Ͳdione 10 2 4956041 29.580 0.394 µM benzothiopheneͲ232,3Ͳdione 10 3 1665448 26. 160 0. 349 µM benzothiopheneͲ2,3Ͳdione 14 1 11152712 53.033 0.707 µM benzothiopheneͲ2,3Ͳdione 14 2 9158265 45.938 0.613 µM benzothiopheneͲ2,3Ͳdione 14 3 8932011 37.791 0.504 µM benzothiopheneͲ2,3Ͳdione 20 1 3576434 22.515 0.300 µM benzothiopheneͲ2,3Ͳdione 20 2 1817325 18.278 0.244 µM benzothiopheneͲ2,3Ͳdione 20 3 2141586 19.995 0.267 µM 2,3Ͳdihydroxybenzothiophene 0 1 0 na 0 RR 2,3Ͳdihydroxybenzothiophene 0 2 15990 na 0.004 RR 2,3Ͳdihydroxybenzothiophene 2 1 271808 na 0.313 RR 2,3Ͳdihydroxybenzothiophene 2 2 304587 na 0.350 RR 232,3Ͳdihydroxybenzothiophenedihydroxybenzothiophene 2 3 159489 na 0. 183 RR 2,3Ͳdihydroxybenzothiophene 4 1 834837 na 0.768 RR 2,3Ͳdihydroxybenzothiophene 4 2 810234 na 0.746 RR 2,3Ͳdihydroxybenzothiophene 4 3 608461 na 0.560 RR 2,3Ͳdihydroxybenzothiophene 6 1 666370 na 0.761 RR 2,3Ͳdihydroxybenzothiophene 6 2 620145 na 0.709 RR 2,3Ͳdihydroxybenzothiophene 6 3 884052 na 1.010 RR 2,3Ͳdihydroxybenzothiophene 10 1 847826 na 1.137 RR 2,3Ͳdihydroxybenzothiophene 10 2 560877 na 1.038 RR 2,3Ͳdihydroxybenzothiophene 10 3 329240 na 1.448 RR 2,3Ͳdihydroxybenzothiophene 14 1 937785 na 0.949 RR 232,3Ͳdihdihydroxybenzothiophene d b thi h 14 2 1034481 na 0.9990 999 RR 2,3Ͳdihydroxybenzothiophene 14 3 989344 na 0.956 RR 2,3Ͳdihydroxybenzothiophene 20 1 703444 na 0.579 RR 2,3Ͳdihydroxybenzothiophene 20 2 507196 na 0.527 RR 2,3Ͳdihydroxybenzothiophene 20 3 459030 na 0.494 RR

186 Table B.2. Continued.

ConcentrationinFlask AnalyticalA l ti l (µM)( M)orRelativeR l ti Compound Day Replicate Area Concentration(µM) Response(RR) Unit benzothiopheneͲ2,3Ͳdione 0 1 0 0 0 µM benzothiopheneͲ2,3Ͳdione 0 2 0 0 0 µM benzothiopheneͲ2,3Ͳdione 0 3 0 0 0 µM benzothiopheneͲ2,3Ͳdione 2 1 3929221 657.330 3.743 µM benzothiopheneͲ2,3Ͳdione 2 2 4875839 4100.500 4.645 µM benzothiopheneͲ2,3Ͳdione 2 3 4336447 596.650 3.397 µM benzothiopheneͲ2,3Ͳdione 4 1 11886377 1116.490 10.371 µM benzothiopheneͲ2,3Ͳdione 4 2 14154636 2241.060 12.761 µM benzothiobenzothiophenepheneͲ2,3Ͳdione 4 3 21587052 2513.900 14.315 µµMM benzothiopheneͲ2,3Ͳdione 6 1 18287460 1502.000 8.553 µM benzothiopheneͲ2,3Ͳdione 6 2 15159822 5675.690 13.185 µM benzothiopheneͲ2,3Ͳdione 6 3 15574956 2257.150 12.853 µM benzothiopheneͲ2,3Ͳdione 10 1 7643760 134.490 6.308 µM benzothiopheneͲ2,3Ͳdione 10 2 1889159 289.060 1.646 µM benzothiopheneͲ2,3Ͳdione 10 3 7030270 930.570 5.299 µM benzothiopheneͲ2,3Ͳdione 14 1 2003202 322.110 1.834 µM benzothiopheneͲ2,3Ͳdione 14 2 2822751 427.590 2.435 µM benzothiopheneͲ2,3Ͳdione 14 3 1758705 301.980 1.720 µM benzothiopheneͲ2,3Ͳdione 20 1 6673923 10521.500 6.525 µM benzothiopheneͲ22,3,3Ͳdione 20 2 3510343 1077.0401077.040 6.1336.133 µM benzothiopheneͲ2,3Ͳdione 20 3 4494142 253.310 4.339 µM benzothiopheneͲ2,3Ͳdione 24 1 4504315 94.280 4.348 µM benzothiopheneͲ2,3Ͳdione 24 2 3089178 525.780 2.994 µM benzothiopheneͲ2,3Ͳdione 24 3 1428942 217.250 1.237 µM benzothiopheneͲ2,3Ͳdione 32 1 1182425 72.110 1.024 µM benzothiopheneͲ2,3Ͳdione 32 2 969684 762.490 4.342 µM benzothiopheneͲ2,3Ͳdione 32 3 1974359 365.240 2.080 µM 2,3Ͳdihydroxybenzothiophene 0 1 0 na 0 RR 2,3Ͳdihydroxybenzothiophene 0 2 0 na 0 RR 2,3Ͳdihydroxybenzothiophene 0 3 0 na 0 RR 232,3Ͳdihydroxybenzothiophene 2 1 554183 na 0. 246 RR 2,3Ͳdihydroxybenzothiophene 2 2 866659 na 0.235 RR 2,3Ͳdihydroxybenzothiophene 2 3 905484 na 0.528 RR 2,3Ͳdihydroxybenzothiophene 4 1 1059161 na 0.826 RR 2,3Ͳdihydroxybenzothiophene 4 2 1597931 na 0.709 RR 2,3Ͳdihydroxybenzothiophene 4 3 1953627 na 0.924 RR 2,3Ͳdihydroxybenzothiophene 6 1 1875397 na 1.441 RR 2,3Ͳdihydroxybenzothiophene 6 2 2250865 na 1.295 RR 2,3Ͳdihydroxybenzothiophene 6 3 1895932 na 1.244 RR 2,3Ͳdihydroxybenzothiophene 10 1 1114726 na 1.958 RR 2,3Ͳdihydroxybenzothiophene 10 2 898879 na 1.565 RR 232,3Ͳdihydroxybenzothiophenedihydroxybenzothiophene 10 3 1323115 na 1. 117 RR 2,3Ͳdihydroxybenzothiophene 14 1 1116945 na 0.783 RR 2,3Ͳdihydroxybenzothiophene 14 2 915638 na 0.997 RR 2,3Ͳdihydroxybenzothiophene 14 3 719359 na 1.023 RR 2,3Ͳdihydroxybenzothiophene 20 1 793688 na 0.790 RR 2,3Ͳdihydroxybenzothiophene 20 2 811850 na 0.703 RR 2,3Ͳdihydroxybenzothiophene 20 3 706944 na 0.776 RR 2,3Ͳdihydroxybenzothiophene 24 1 423013 na 0.794 RR 2,3Ͳdihydroxybenzothiophene 24 2 642194 na 0.682 RR 2,3Ͳdihydroxybenzothiophene 24 3 590004 na 0.504 RR 2,3Ͳdihydroxybenzothiophene 32 1 306212 na 0.622 RR 232,3Ͳdihdihydroxybenzothiophene d b thi h 32 2 237652 na 0.5110 511 RR 2,3Ͳdihydroxybenzothiophene 32 3 603978 na 0.329 RR

187 Table B.2. Continued.

ConcentrationinFlask AnalyticalA l ti l (µM)( M)orRelativeR l ti Compound Day Replicate Area Concentration(µM) Response(RR) Unit 2ͲhydroxybenzothiopheneͲ3Ͳcarbaldehyde 0 1 0 na 0 RR 2ͲhydroxybenzothiopheneͲ3Ͳcarbaldehyde 0 2 0 na 0 RR 2ͲhydroxybenzothiopheneͲ3Ͳcarbaldehyde 0 3 0 na 0 RR 2ͲhydroxybenzothiopheneͲ3Ͳcarbaldehyde 2 1 133042 na 0.127 RR 2ͲhydroxybenzothiopheneͲ3Ͳcarbaldehyde 2 2 81831 na 0.161 RR 2ͲhydroxybenzothiopheneͲ3Ͳcarbaldehyde 2 3 119107 na 0.093 RR 2ͲhydroxybenzothiopheneͲ3Ͳcarbaldehyde 4 1 69934 na 0.061 RR 2ͲhydroxybenzothiopheneͲ3Ͳcarbaldehyde 4 2 184123 na 0.166 RR 2ͲhhydroxybenzothiopheneydroxybenzothiopheneͲ3Ͳcarbaldehydecarbaldehyde 4 3 207321 na 0.137 RR 2ͲhydroxybenzothiopheneͲ3Ͳcarbaldehyde 6 1 269985 na 0.126 RR 2ͲhydroxybenzothiopheneͲ3Ͳcarbaldehyde 6 2 286060 na 0.249 RR 2ͲhydroxybenzothiopheneͲ3Ͳcarbaldehyde 6 3 109927 na 0.091 RR 2ͲhydroxybenzothiopheneͲ3Ͳcarbaldehyde 10 1 114388 na 0.094 RR 2ͲhydroxybenzothiopheneͲ3Ͳcarbaldehyde 10 2 15889 na 0.014 RR 2ͲhydroxybenzothiopheneͲ3Ͳcarbaldehyde 10 3 139137 na 0.105 RR 2ͲhydroxybenzothiopheneͲ3Ͳcarbaldehyde 14 1 53422 na 0.049 RR 2ͲhydroxybenzothiopheneͲ3Ͳcarbaldehyde 14 2 86941 na 0.075 RR 2ͲhydroxybenzothiopheneͲ3Ͳcarbaldehyde 14 3 18303 na 0.018 RR 2ͲhydroxybenzothiopheneͲ3Ͳcarbaldehyde 20 1 100690 na 0.098 RR 2ͲhydroxybenzothiopheneͲ3Ͳcarbaldehyde 20 2 74160 na 0.1300.130 RR 2ͲhydroxybenzothiopheneͲ3Ͳcarbaldehyde 20 3 29436 na 0.028 RR 2ͲhydroxybenzothiopheneͲ3Ͳcarbaldehyde 24 1 106544 na 0.103 RR 2ͲhydroxybenzothiopheneͲ3Ͳcarbaldehyde 24 2 116295 na 0.113 RR 2ͲhydroxybenzothiopheneͲ3Ͳcarbaldehyde 24 3 82682 na 0.072 RR 2ͲhydroxybenzothiopheneͲ3Ͳcarbaldehyde 32 1 754578 na 0.653 RR 2ͲhydroxybenzothiopheneͲ3Ͳcarbaldehyde 32 2 159957 na 0.716 RR 2ͲhydroxybenzothiopheneͲ3Ͳcarbaldehyde 32 3 623081 na 0.656 RR Benzothiophenecarboxylicacid 0 1 0 na 0 RR Benzothiophenecarboxylicacid 0 2 0 na 0 RR Benzothiophenecarboxylicacid 0 3 0 na 0.000 RR Benzothiophenecarboxylicacid 2 1 15913 na 0. 015 RR Benzothiophenecarboxylicacid 2 2 31201 na 0.061 RR Benzothiophenecarboxylicacid 2 3 27305 na 0.021 RR Benzothiophenecarboxylicacid 4 1 177578 na 0.155 RR Benzothiophenecarboxylicacid 4 2 288669 na 0.260 RR Benzothiophenecarboxylicacid 4 3 274516 na 0.182 RR Benzothiophenecarboxylicacid 6 1 5021719 na 2.349 RR Benzothiophenecarboxylicacid 6 2 2357777 na 2.051 RR Benzothiophenecarboxylicacid 6 3 2001070 na 1.651 RR Benzothiophenecarboxylicacid 10 1 0 na 0.000 RR Benzothiophenecarboxylicacid 10 2 0 na 0.000 RR BenzothiopheneBenzothiophenecarcarboxylicboxylicacacidid 10 3 29766 na 0. 022 RR Benzothiophenecarboxylicacid 14 1 0 na 0.000 RR Benzothiophenecarboxylicacid 14 2 0 na 0.000 RR Benzothiophenecarboxylicacid 14 3 0 na 0.000 RR Benzothiophenecarboxylicacid 20 1 0 na 0.000 RR Benzothiophenecarboxylicacid 20 2 0 na 0.000 RR Benzothiophenecarboxylicacid 20 3 0 na 0.000 RR Benzothiophenecarboxylicacid 24 1 0 na 0.000 RR Benzothiophenecarboxylicacid 24 2 0 na 0.000 RR Benzothiophenecarboxylicacid 24 3 0 na 0.000 RR Benzothiophenecarboxylicacid 32 1 0 na 0.000 RR BBenzothiophene thi h carboxylicb li acidid 32 2 0 na 0.0000 000 RR Benzothiophenecarboxylicacid 32 3 0 na 0.000 RR

188 Table B.2. Continued.

ConcentrationinFlask AAnalytical l ti l (µM)( M)orRelativeR l ti Compound Day Replicate Area Concentration(µM) Response(RR) Unit Thioindigo 0 1 00 0µM Thioindigo 0 2 00 0µM Thioindigo 2 1 00 0µM Thioindigo 2 2 00 0µM Thioindigo 2 3 00 0µM Thioindigo 4 1 183683 12.799 0.171 µM Thioindigo 4 2 125803 8.638 0.115 µM Thioindigo 4 3 124537 8.547 0.114 µM ThioindigoThioindigo 6 1 129798 11. 180 0. 149 µMµM Thioindigo 6 2 165492 14.367 0.192 µM Thioindigo 6 3 177894 15.474 0.206 µM Thioindigo 10 1 131162 13.341 0.178 µM Thioindigo 10 2 89414 12.521 0.167 µM Thioindigo 10 3 65401 22.060 0.294 µM Thioindigo 14 1 124591 9.444 0.126 µM Thioindigo 14 2 108577 7.787 0.104 µM Thioindigo 14 3 98465 7.127 0.095 µM Thioindigo 20 1 52081 2.943 0.039 µM ThioindigoThioindigo 20 2 74528 55.640.640 00.075.075 µµMM Thioindigo 20 3 43186 3.224 0.043 µM Dithiosalicylicacid 0 1 ndb µM Dithiosalicylicacid 0 2 nd µM Dithiosalicylicacid 2 1 nd µM Dithiosalicylicacid 2 2 nd µM Dithiosalicylicacid 2 3 nd µM Dithiosalicylicacid 4 1 nd µM Dithiosalicylicacid 4 2 nd µM Dithiosalicylicacid 4 3 nd µM Dithiosalicylicacid 6 1 nd µM DithiDithiosa lilicy lilicaciidd 6622 nd µMM Dithiosalicylicacid 6 3 nd µM Dithiosalicylicacid 10 1 nd µM Dithiosalicylicacid 10 2 nd µM Dithiosalicylicacid 10 3 nd µM Dithiosalicylicacid 14 1 nd µM Dithiosalicylicacid 14 2 nd µM Dithiosalicylicacid 14 3 nd µM Dithiosalicylicacid 20 1 nd µM Dithiosalicylicacid 20 2 nd µM Dithiosalicylicacid 20 3 nd µM ana:notapplicable. bnd:notdetected.

189 Table B.3. Concentrations of DBT and other compounds analyzed by GC/MS in extracts from culture media during DBT degradation with pH control (Figures 3.20 and 3.21).

ConcentrationinFlask AnalyticalA l ti l (µM)( M)orRelativeR l ti Compound Day Replicate Area Concentration(µM) Response(RR) Unit 2Ͳnaphthol(internalstandard) 0 1 717495 20 naa µM 2Ͳnaphthol 0 2 565230 20 na µM 2Ͳnaphthol 0 3 1049754 20 na µM 2Ͳnaphthol 2 1 508620 20 na µM 2Ͳnaphthol 2 2 1276373 20 na µM 2Ͳnaphthol 2 3 1146098 20 na µM 2Ͳnaphthol 4 1 1109203 20 na µM 2Ͳnaphthol 4 2 1508032 20 na µM 2Ͳnaphthol 4 3 2138205 20 na µM 2Ͳnaphthol 6 1 1149796 20 na µM 2Ͳnaphthol 6 2 1211804 20 na µM 2Ͳnaphthol 6 3 998104 20 na µM 2Ͳnaphthol 10 1 1147758 20 na µM 2Ͳnaphthol 10 2 1326744 20 na µM 2Ͳnaphthol 10 3 1092146 20 na µM 2Ͳnaphthol 14 1 1159341 20 na µM 2Ͳnaphthol 14 2 1022777 20 na µM 2Ͳnaphthol 14 3 111396 20 na µM 2Ͳnaphthol 20 1 572379 20 na µM 2Ͳnaphthol 20 2 1035871 20 na µM 2Ͳnaphthol 20 3 839030 20 na µM 2Ͳnaphthol 24 1 1031830 20 na µM 2Ͳnaphthol 24 2 1155125 20 na µM 2Ͳnaphthol 24 3 931399 20 na µM 2Ͳnaphthol 32 1 223337 20 na µM 2Ͳnaphthol 32 2 949335 20 na µM 2Ͳnaphthol 32 3 929181 20 na µM Thiosalicylicacid 0 1 0 0 0 µM Thiosalicylicacid 0 2 0 0 0 µM Thiosalicylicy acid 0 3 0 0 0 µMµ Thiosalicylicacid 2 1 0 0.000 0.000 µM Thiosalicylicacid 2 2 0 0.000 0.000 µM Thiosalicylicacid 2 3 0 0.000 0.000 µM Thiosalicylicacid 4 1 1976500 300.290 4.004 µM Thiosalicylicacid 4 2 1469527 232.670 3.102 µM Thiosalicylicacid 4 3 3097566 360.720 4.810 µM Thiosalicylicacid 6 1 3534700 290.310 3.871 µM Thiosalicylicacid 6 2 913598 195.410 2.605 µM Thiosalicylicacid 6 3 1216476 176.290 2.351 µM Thiosalicylicacid 10 1 0 0.000 0.000 µM Thiosalicylicacid 10 2 0 0.000 0.000 µM Thiosalicylicacid 10 3 0 0.000 0.000 µM Thiosalicylicacid 14 1 0 0.000 0.000 µM Thiosalicylicacid 14 2 0 0.000 0.000 µM Thiosalicylicacid 14 3 0 0.000 0.000 µM Thiosalicylicacid 20 1 0 0.000 0.000 µM Thiosalicylicacid 20 2 0 0.000 0.000 µM Thiosalicylicacid 20 3 0 0.000 0.000 µM ThiThiosalicylic li li acidid 24 1 0 00.000 000 0. 000 µMM Thiosalicylicacid 24 2 0 0.000 0.000 µM Thiosalicylicacid 24 3 0 0.000 0.000 µM Thiosalicylicacid 32 1 0 0.000 0.000 µM Thiosalicylicacid 32 2 0 0.000 0.000 µM Thiosalicylicacid 32 3 0 0.000 0.000 µM

190 Table B.3. Continued.

ConcentrationinFlask AnalyticalA l ti l (µM)( M)orRelativeR l ti Compound Day Replicate Area Concentration(µM) Response(RR) Unit 2Ͳhydroxybenzothiophene 0 1 0 na 0.000 RR 2Ͳhydroxybenzothiophene 0 2 0 na 0.000 RR 2Ͳhydroxybenzothiophene 0 3 0 na 0.000 RR 2Ͳhydroxybenzothiophene 2 1 247438 na 0.236 RR 2Ͳhydroxybenzothiophene 2 2 162196 na 0.319 RR 2Ͳhydroxybenzothiophene 2 3 352219 na 0.276 RR 2Ͳhydroxybenzothiophene 4 1 3200759 na 2.793 RR 2Ͳhydroxybenzothiophene 4 2 4855798 na 4.378 RR 2Ͳhy droxy benzot thihiop hene 4 3 5722115 na 33.794 794 RR 2Ͳhydroxybenzothiophene 6 1 10877694 na 5.087 RR 2Ͳhydroxybenzothiophene 6 2 6133869 na 5.335 RR 2Ͳhydroxybenzothiophene 6 3 6406311 na 5.287 RR 2Ͳhydroxybenzothiophene 10 1 225227 na 0.226 RR 2Ͳhydroxybenzothiophene 10 2 183843 na 0.160 RR 2Ͳhydroxybenzothiophene 10 3 2357196 na 1.777 RR 2Ͳhydroxybenzothiophene 14 1 304089 na 0.278 RR 2Ͳhydroxybenzothiophene 14 2 283807 na 0.245 RR 2Ͳhydroxybenzothiophene 14 3 232639 na 0.227 RR 2Ͳhydroxybenzothiophene 20 1 442504 na 0.433 RR 2Ͳhdhydroxybenzothiophene b h h 20 2 324679 na 0.567 RR 2Ͳhydroxybenzothiophene 20 3 456441 na 0.441 RR 2Ͳhydroxybenzothiophene 24 1 52870 na 0.063 RR 2Ͳhydroxybenzothiophene 24 2 156056 na 0.151 RR 2Ͳhydroxybenzothiophene 24 3 88855 na 0.077 RR 2Ͳhydroxybenzothiophene 32 1 53330 na 0.057 RR 2Ͳhydroxybenzothiophene 32 2 151752 na 0.679 RR 2Ͳhydroxybenzothiophene 32 3 160818 na 0.169 RR 3Ͳhydroxybenzothiophene 0 1 0 na 0 RR 3Ͳhydroxybenzothiophene 0 2 0 na 0 RR 3Ͳhydroxybenzothiophene 0 3 0 na 0 RR 3Ͳhydroxybenzothiophene 2 1 6139097 na 5.848 RR 3Ͳhydroxybenzothiophene 2 2 3526314 na 6.933 RR 3Ͳhydroxybenzothiophene 2 3 10285734 na 8.059 RR 3Ͳhydroxybenzothiophene 4 1 10566717 na 8.279 RR 3Ͳhydroxybenzothiophene 4 2 9126206 na 8.228 RR 3Ͳhydroxybenzothiophene 4 3 9309324 na 6.173 RR 3Ͳhydroxybenzothiophene 6 1 6209850 na 2.904 RR 3Ͳhydroxybenzothiophene 6 2 8143165 na 3.808 RR 3Ͳhydroxybenzothiophene 6 3 4047928 na 3.340 RR 3Ͳhydroxybenzothiophene 10 1 285622 na 0.286 RR 3Ͳhydroxybenzothiopheneyy p 10 2 351963 na 0.307 RR 3Ͳhydroxybenzothiophene 10 3 1094830 na 0.825 RR 3Ͳhydroxybenzothiophene 14 1 444326 na 0.407 RR 3Ͳhydroxybenzothiophene 14 2 426998 na 0.368 RR 3Ͳhydroxybenzothiophene 14 3 395031 na 0.386 RR 3Ͳhydroxybenzothiophene 20 1 451087 na 0.441 RR 3Ͳhydroxybenzothiophene 20 2 284827 na 0.498 RR 3Ͳhydroxybenzothiophene 20 3 291098 na 0.281 RR 3Ͳhydroxybenzothiophene 24 1 182939 na 0.218 RR 3Ͳhydroxybenzothiophene 24 2 352022 na 0.341 RR 3Ͳhydroxybenzothiophene 24 3 321990 na 0.279 RR 3Ͳhydroxybenzothiophenehydroxybenzothiophene 321 224262 na 00.241.241 RR 3Ͳhydroxybenzothiophene 32 2 269946 na 1.209 RR 3Ͳhydroxybenzothiophene 32 3 299551 na 0.316 RR

191 Table B.3. Continued.

192 Table B.3. Continued.

193 Table B.3. Continued.

ConcentrationinFlask AnalyticalA l ti l (µM)( M)orRelativeR l ti Compound Day Replicate Area Concentration(µM) Response(RR) Unit 3ͲhydroxybenzothiophenͲ2Ͳone 0 1 0 na 0.000 RR 3ͲhydroxybenzothiophenͲ2Ͳone 0 2 0 na 0.000 RR 3ͲhydroxybenzothiophenͲ2Ͳone 0 3 0 na 0.000 RR 3ͲhydroxybenzothiophenͲ2Ͳone 2 1 4441228 na 4.231 RR 3ͲhydroxybenzothiophenͲ2Ͳone 2 2 3469376 na 6.821 RR 3ͲhydroxybenzothiophenͲ2Ͳone 2 3 7664409 na 6.005 RR 3ͲhydroxybenzothiophenͲ2Ͳone 4 1 5934323 na 5.178 RR 3ͲhydroxybenzothiophenͲ2Ͳone 4 2 4016787 na 3.621 RR 3ͲhydroxybenzothiophenhydroxybenzothiophenͲ2Ͳone 4 3 3610072 na 3.255 RR 3ͲhydroxybenzothiophenͲ2Ͳone 6 1 5837433 na 2.730 RR 3ͲhydroxybenzothiophenͲ2Ͳone 6 2 3428360 na 2.982 RR 3ͲhydroxybenzothiophenͲ2Ͳone 6 3 2059909 na 1.792 RR 3ͲhydroxybenzothiophenͲ2Ͳone 10 1 345186 na 0.346 RR 3ͲhydroxybenzothiophenͲ2Ͳone 10 2 792989 na 0.691 RR 3ͲhydroxybenzothiophenͲ2Ͳone 10 3 729874 na 0.636 RR 3ͲhydroxybenzothiophenͲ2Ͳone 14 1 1759907 na 1.611 RR 3ͲhydroxybenzothiophenͲ2Ͳone 14 2 1808061 na 1.560 RR 3ͲhydroxybenzothiophenͲ2Ͳone 14 3 1685787 na 1.648 RR 3ͲhydroxybenzothiophenͲ2Ͳone 20 1 1299433 na 1.270 RR 3ͲhydroxybenzothiophenͲ2Ͳone 20 2 649374 na 1.1351.135 RR 3ͲhydroxybenzothiophenͲ2Ͳone 20 3 771016 na 0.744 RR 3ͲhydroxybenzothiophenͲ2Ͳone 24 1 555072 na 0.662 RR 3ͲhydroxybenzothiophenͲ2Ͳone 24 2 1129369 na 1.095 RR 3ͲhydroxybenzothiophenͲ2Ͳone 24 3 1189562 na 1.030 RR 3ͲhydroxybenzothiophenͲ2Ͳone 32 1 767820 na 0.824 RR 3ͲhydroxybenzothiophenͲ2Ͳone 32 2 762523 na 0.819 RR 3ͲhydroxybenzothiophenͲ2Ͳone 32 3 931781 na 0.982 RR DBT 0 1 6639432 115.990 1.547 µM DBT 0 2 7582316 116.810 1.557 µM DBT 0 3 6503223 20.280 0.270 µM DBT 2 1 4069325 16. 410 0. 219 µM DBT 2 2 3189003 18.310 0.244 µM DBT 2 3 3053268 19.750 0.263 µM DBT 4 1 4007692 17.970 0.240 µM DBT 4 2 3761864 18.280 0.244 µM DBT 4 3 4605230 15.320 0.204 µM DBT 6 1 3427723 10.253 0.137 µM DBT 6 2 3445487 10.253 0.137 µM DBT 6 3 trb 0.000 0.000 µM DBT 10 1 tr 0.000 0.000 µM DBT 10 2 tr 0.000 0.000 µM DBT 10 3 ndnd 0. 000 0. 000 µMµM DBT 14 1 tr 0.000 0.000 µM DBT 14 2 tr 0.000 0.000 µM DBT 14 3 tr 0.000 0.000 µM DBT 20 1 tr 0.000 0.000 µM DBT 20 2 tr 0.000 0.000 µM DBT 20 3 tr 0.000 0.000 µM DBT 24 1 tr 0.000 0.000 µM DBT 24 2 tr 0.000 0.000 µM DBT 24 3 tr 0.000 0.000 µM DBT 32 1 tr 0.000 0.000 µM DBT 32 2 ttr 00.000 000 00.000 000 µMM DBT 32 3 tr 0.000 0.000 µM

194 Table B.3. Continued.

ConcentrationinFlask AnalyticalA l ti l (µM)( M)orRelativeR l ti Compound Day Replicate Area Concentration(µM) Response(RR) Unit DBTsulfone 0 1 439513 0 0 µM DBTsulfone 0 2 109699 0 0 µM DBTsulfone 0 3 155110 29.970 0.400 µM DBTsulfone 2 1 132582 32.415 0.432 µM DBTsulfone 2 2 105158 36.000 0.480 µM DBTsulfone 2 3 207155 37.019 0.494 µM DBTsulfone 4 1 290177 54.297 0.724 µM DBTsulfone 4 2 367440 50.461 0.673 µM DBTsulfone 4 3 377764 36.148 0.482 µµMM DBTsulfone 6 1 262590 47.197 0.629 µM DBTsulfone 6 2 199341 33.547 0.447 µM DBTsulfone 6 3 16875 2.010 0.027 µM DBTsulfone 10 1 0 0.000 0.000 µM DBTsulfone 10 2 0 0.000 0.000 µM DBTsulfone 10 3 0 0.000 0.000 µM DBTsulfone 14 1 0 0.000 0.000 µM DBTsulfone 14 2 0 0.000 0.000 µM DBTsulfone 14 3 0 0.000 0.000 µM DBTsulfone 20 1 0 0.000 0.000 µM DBTsulfone 20 2 0 0.0000.000 0.0000.000 µM DBTsulfone 20 3 0 0.000 0.000 µM DBTsulfone 24 1 0 0.000 0.000 µM DBTsulfone 24 2 0 0.000 0.000 µM DBTsulfone 24 3 0 0.000 0.000 µM DBTsulfone 32 1 0 0.000 0.000 µM DBTsulfone 32 2 0 0.000 0.000 µM DBTsulfone 32 3 0 0.000 0.000 µM DBTsulfoxide 0 1 0 na 0.000 RR DBTsulfoxide 0 2 0 na 0.000 RR DBTsulfoxide 0 3 0 na 0.000 RR DBTsulfoxide 2 1 508217 na 0. 484 RR DBTsulfoxide 2 2 556788 na 0.530 RR DBTsulfoxide 2 3 553522 na 0.434 RR DBTsulfoxide 4 1 396889 na 0.346 RR DBTsulfoxide 4 2 404363 na 0.365 RR DBTsulfoxide 4 3 302665 na 0.201 RR DBTsulfoxide 6 1 304952 na 0.143 RR DBTsulfoxide 6 2 235548 na 0.205 RR DBTsulfoxide 6 3 210811 na 0.183 RR DBTsulfoxide 10 1 0 na 0.000 RR DBTsulfoxide 10 2 18629 na 0.016 RR DBTsusulfoxidelfoxide 10 3 0 na 0. 000 RR DBTsulfoxide 14 1 0 na 0.000 RR DBTsulfoxide 14 2 0 na 0.000 RR DBTsulfoxide 14 3 0 na 0.000 RR DBTsulfoxide 20 1 19302 na 0.019 RR DBTsulfoxide 20 2 16734 na 0.029 RR DBTsulfoxide 20 3 0 na 0.000 RR DBTsulfoxide 24 1 0 na 0.000 RR DBTsulfoxide 24 2 15964 na 0.015 RR DBTsulfoxide 24 3 0 na 0.000 RR DBTsulfoxide 32 1 0 na 0.000 RR DBTsulfoxidelf id 32 2 0 na 0.0000 000 RR DBTsulfoxide 32 3 0 na 0.000 RR

195 Table B.3. Continued.

ConcentrationinFlask AnalyticalA l ti l (µM)( M)orRelativeR l ti Compound Day Replicate Area Concentration(µM) Response(RR) Unit Thioindigo 0 1 00 0µM Thioindigo 0 2 00 0µM Thioindigo 0 3 00 0µM Thioindigo 2 1 210140 15.23204943 0.200 µM Thioindigo 2 2 166077 25.10271203 0.327 µM Thioindigo 2 3 373801 22.47280335 0.293 µM Thioindigo 4 1 221641 14.701 0.193 µM Thioindigo 4 2 205407 14.060 0.185 µM ThioindigoThioindigo 4 3 601875 30. 774 0. 399 µMµM Thioindigo 6 1 991055 35.804 0.463 µM Thioindigo 6 2 524392 35.224 0.456 µM Thioindigo 6 3 821605 52.562 0.678 µM Thioindigo 10 1 198909 15.162 0.199 µM Thioindigo 10 2 118654 8.880 0.119 µM Thioindigo 10 3 92003 5.011 0.069 µM Thioindigo 14 1 86744 5.798 0.079 µM Thioindigo 14 2 21932 1.071 0.019 µM Thioindigo 14 3 24231 1.444 0.024 µM ThioindiThioindigogo 20 1 35503 22.305.305 00.035.035 µµMM Thioindigo 20 2 81332 7.166 0.097 µM Thioindigo 20 3 26616 1.600 0.026 µM Thioindigo 24 1 21924 1.634 0.026 µM Thioindigo 24 2 0 0.000 0.000 µM Thioindigo 24 3 15975 0.673 0.014 µM Thioindigo 32 1 0 0.000 0.000 µM Thioindigo 32 2 0 0.000 0.000 µM Thioindigo 32 3 29583 2.027 0.031 µM Dithiosalicylicacid 0 1 0 0 0 µM Dithiosalicylicacid 0 2 0 0 0 µM Dithiosalicylicacid 0 3 0 0 0 µM Dithiosalicylicacid 2 1 980866 1.000 0.013 µM Dithiosalicylicacid 2 2 1458850 0.963 0.013 µM Dithiosalicylicacid 2 3 1219518 1.550 0.021 µM Dithiosalicylicacid 4 1 1261556 16.020 0.214 µM Dithiosalicylicacid 4 2 2222849 10.480 0.140 µM Dithiosalicylicacid 4 3 1867012 17.800 0.237 µM Dithiosalicylicacid 6 1 1940431 6.360 0.085 µM Dithiosalicylicacid 6 2 4747179 6.370 0.085 µM DithiosalicylicDithiosalicylicacidacid 6 3 1455520 7. 850 0. 105 µMµM Dithiosalicylicacid 10 1 42614 0.000 0.000 µM Dithiosalicylicacid 10 2 155612 0.000 0.000 µM Dithiosalicylicacid 10 3 918744 2.950 0.039 µM Dithiosalicylicacid 14 1 124795 0.520 0.007 µM Dithiosalicylicacid 14 2 302832 0.380 0.005 µM Dithiosalicylicacid 14 3 203115 0.110 0.001 µM Dithiosalicylicacid 20 1 701892 0.220 0.003 µM Dithiosalicylicacid 20 2 294969 0.330 0.004 µM Dithiosalicylicacid 20 3 445240 1.0001.000 0.0130.013 µM Dithiosalicylicacid 24 1 246036 0.000 0.000 µM Dithiosalicylicacid 24 2 358637 0.420 0.006 µM Dithiosalicylicacid 24 3 258039 0.140 0.002 µM Dithiosalicylicacid 32 1 157887 0.000 0.000 µM Dithiosalicylicacid 32 2 692427 0.110 0.001 µM Dithiosalicylicacid 32 3 927526 0.542 0.007 µM ana:notapplicable. btr:trace.

196 Table B.4. Inhibition of luminescence in Vibrio fischeri exposed to culture media collected during DBT degradation without pH control (Figure 3.20a).

Initial FinalLuminescence Luminescence Day Replicate LuminescenceUnits Units Inhobition,% Control 1 199165 200007 0.00 Control 2 197563 200008 0.00 Control 3 187742 199373 0.00 0 1 191855 154363 19.88 0 2 194207 151685 22.22 0 3 198023 152844 23.14 2 1 193939 116335 40.29 2 2 195224 114802 41.33 2 3 195652 132479 32.50 4 1 194262 82714 57.57 4 2 190094 68576 64.04 4 3 185309 68056 63.38 6 1 199699 111229 44.54 6 2 199922 125882 37.30 6 3 199842 111579 44.40 8 1 199885 138149 31.18 8 2 199403 165535 17.35 8 3 198504 179362 10.03 10 1 174672 138359 25.41 10 2 174212 138062 25.28 10 3 185314 128698 34.60 12 1 182358 114076 41.02 12 2 189720 114495 43.16 12 3 189638 118975 40.87 14 1 193720 114105 44.52 14 2 191988 122772 39.77 14 3 194597 121045 41.43 16 1 192520 130241 36.27 16 2 195519 143051 31.10 16 3 193484 151354 26.26 18 1 192842 141901 30.70 18 2 192307 159999 21.58 18 3 191620 151960 25.31 20 1 136790 151065 30.27 20 2 126847 157771 21.34 20 3 129910 149717 27.26

197 Table B.5. Inhibition of luminescence in Vibrio fischeri exposed to culture media collected during DBT degradation with pH control (Figure 3.20a).

Initial FinalLuminescence Luminescence Day Replicate LuminescenceUnits Units Inhobition,% Control 1 180140 199574 0.00 Control 2 193577 199931 0.00 Control 3 194000 200007 0.00 0 1 218491 180980 21.56 0 2 217493 175433 23.62 0 3 218714 178798 22.59 2 1 188145 112400 43.43 2 2 209367 116786 47.18 2 3 212361 122332 45.45 4 1 211426 111549 50.04 4 2 218775 111286 51.83 4 3 224151 115060 51.39 6 1 221926 128291 45.26 6 2 205462 111532 48.60 6 3 208396 126501 42.52 8 1 233565 157561 36.12 8 2 235881 159620 35.92 8 3 235983 156329 37.27 10 1 236014 158377 36.45 10 2 236014 163042 34.58 10 3 236014 168928 32.22 12 1 230159 157077 35.37 12 2 219536 152108 34.39 12 3 219475 162910 29.71 14 1 231582 175345 28.30 14 2 234730 176733 28.70 14 3 236007 174390 30.03 16 1 236011 173515 30.38 16 2 236007 182507 26.77 16 3 231375 189082 22.61 18 1 191619 145215 28.24 18 2 222197 181607 22.60 18 3 232643 187251 23.78 20 1 234746 189997 23.36 20 2 235952 183674 26.28 20 3 236013 185793 25.45 24 1 235937 178383 28.40 24 2 218617 172914 25.10 24 3 235371 186852 24.82 28 1 229240 191552 20.87 28 2 198834 173887 17.18 28 3 235993 196008 21.35 32 1 236006 193632 22.31 32 2 236014 193042 22.55 32 3 236008 197236 20.86

198 Ap p e n d i x C: Ch a p t e r 4 Da t a . 00178 27123 72062 . . . Ͳ 0.0006 0 00178 0.27123 0 0 71567 0 72062 Ͳ 0.00122 Ͳ Ͳ 0.00228 Ͳ 0.00128 Relative Fluorescence 1 0.00386 2 3 6 7 0.00329 5 4 8 0.0091 9 0.02191 13 30 38 PSU PSU PSU PSU PSU PSU PSU PSU 14 0.39916 PSU 30 0.71567 PSU 39 0.7262 PSU PSU PSU PSU 15 0.50159 PSU 16 0.58107 PSU 31 0.72235 PSU 40 0.72784 PSU PSU 17 0.6327 PSU 32 0.72759 PSU 18 0.66084 PSU 33 0.73215 PSU PSU 19 0.68236 PSU 10 0.04666 PSU 20 0.70517 PSU 34 0.72536 PSU 11 0.08772 PSU 35 0.72338 PSU 12 0.15742 PSU 36 0.73505 PSU 21 0.71151 PSU 22 0.70336 PSU 23 0.70378 PSU 37 0.72815 PSU 24 0.70658 PSU 25 0.71903 PSU 26 0.72763 PSU 27 0.72457 PSU 28 0.72556 PSU 29 0.71932 rRNA 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 copies) Primer Cycle (16S gene log DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA e t a l so isolate i isolate i l isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate omonas d seu Pseudomonas Pseudomonas Pseudomonas P Pseudomonas P d Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Source one Clone Cl Clone Cl Clone Clone 0.73 Clone 1831 . 00033 73454 0.1831 0 . 0.7191 Clone 0.0015 Clone . 0.0095 Clone 0.7295 Clone 0.7326 Clone 0.00091 Clone 0 00033 0.00028 Clone 0.30655 Clone 0.72694 Clone 0.73067 Clone 0 72694 0 73454 0.00005 Clone 0.42845 Clone 0.72775 0.51374 Clone 0.57971 Clone 0.72462 Clone 0.63173 Clone 0.72682 Clone 0.66762 Clone 0.02109 Clone 0.68541 Clone 0.04747 Clone 0.69845 Clone 0.09791 Clone 0.72565 Clone 0.73134 Clone 0.71614 Clone 0.72445 Clone 0.73094 Clone 0.72574 Clone 0.71676 Clone 0.72099 Clone 0.72739 Clone Ͳ 0.00056 Clone Ͳ Ͳ 0.00029Ͳ 0.00156 Clone Clone assays included in Figure 4.1 included in Figure assays Relative Fluorescence DNA 1 2 3 6 7 5 4 8 9 13 30 38 Pseudomonas PSU PSU PSU PSU 8 PSU 8 PSU 8 8 8 8 8 PSU 88 PSU PSU 8 PSU 14 8 PSU 30 8 PSU 39 8 PSU 8 PSU 15 8 PSU 31 8 PSU 40 8 PSU 8 PSU 16 8 PSU 17 8 PSU 32 8 PSU 8 PSU 18 8 PSU 33 8 PSU 19 8 PSU 34 8 PSU 10 8 PSU 20 8 PSU 11 8 PSU 21 8 PSU 35 8 PSU 12 8 PSU 36 8 PSU 37 8 PSU 22 8 PSU 23 8 PSU 24 8 PSU 25 8 PSU 26 8 PSU 27 8 PSU 28 8 PSU 29 (16S copies) Primer Cycle log rRNA gene DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA e t a l so isolate i isolate i l isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate qPCR amplification data for data qPCR amplification omonas d seu Pseudomonas Pseudomonas Pseudomonas P Pseudomonas P d Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas one Clone Clone Clone Clone DNA Source Clone Cl Clone Clone Clone Cl Clone Clone Clone Clone Clone Clone Clone Clone Clone Clone Clone Clone Clone Clone Clone Clone Clone Clone Clone Clone Clone Clone Clone Clone Clone Clone Clone Clone Clone Clone Clone Clone Table C.1. Table

199 19808 . Ͳ 0.0022 0 00091 0 19808 0.68456 Ͳ 0.00091 Ͳ 0.00369 Ͳ 0.00262 Ͳ 0.00382 Ͳ 0.00275 Ͳ 0.00153 Ͳ 0.00414 Ͳ 0.00501 Ͳ 0.00349 Relative Fluorescence 1 0.00889 2 0.00553 3 0.00087 5 4 6 7 8 9 13 21 29 PSU PSU PSU PSU PSU PSU PSU 13 PSU 22 0.32167 PSU 30 0.69424 PSU PSU PSU 14 0.00137 PSU 23 0.43587 PSU 31 0.6991 PSU PSU 15 0.0044 PSU 24 0.51767 PSU 32 0.70187 PSU PSU 16 0.0091 PSU 25 0.57865 PSU 33 0.7012 PSU PSU 17 0.01818 PSU 26 0.61996 PSU 34 0.71399 PSU 10 PSU PSU 18 0.03335 PSU 27 0.6461 PSU 35 0.72593 PSU 19 0.06099 PSU 28 0.66474 PSU 36 0.72115 PSU 11 PSU 20 0.11081 PSU 29 0.68456 PSU 37 0.7197 PSU 12 PSU 38 0.73079 PSU 39 0.72691 PSU 40 0.71678 rRNA 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 copies) Primer Cycle (16S gene log DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA i l t isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate Pseudomonas Pseudomonas P d Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Source Cl Clone Clone Clone 0.172 Clone 62113 . 0.0123 Clone 0.00601 Clone 0.00211 Clone 0.02704 Clone 0.66132 Clone 0.73211 Clone 0 02704 0 62113 0.72474 0.05249 Clone 0.68618 Clone 0.73012 Clone 0.09634 Clone 0.70013 Clone 0.72752 Clone 0.70062 Clone 0.72606 Clone 0.28909 Clone 0.70038 Clone 0.72051 Clone 0.00159 Clone 0.00022 Clone 0.41367 Clone 0.70662 Clone 0.72336 Clone 0.51015 Clone 0.71684 Clone 0.72801 Clone 0.57375 Clone 0.72474 Clone 0.72689 Clone 0.00493 Clone 0.72685 Clone 0.72799 Clone 0.72441 Ͳ 0.00131 Clone Ͳ 0.00305 Clone Ͳ 0.00274 Clone Ͳ 0.00339 Clone Ͳ 0.00312 Clone Ͳ 0.00125 Clone Relative Fluorescence DNA 1 2 3 5 4 6 7 8 9 13 21 29 PSU PSU PSU 6 PSU 6 PSU 6 6 6 6 PSU 6 PSU 6 PSU 13 6 PSU 22 6 PSU 30 6 PSU 6 PSU 14 6 PSU 23 6 PSU 31 6 PSU 6 PSU 15 6 PSU 24 6 PSU 32 6 PSU 6 PSU 16 6 PSU 25 6 PSU 33 6 PSU 6 PSU 17 6 PSU 26 6 PSU 34 6 PSU 10 6 PSU 6 PSU 18 6 PSU 27 6 PSU 35 6 PSU 19 6 PSU 28 6 PSU 36 6 PSU 20 6 PSU 29 6 PSU 37 6 PSU 11 6 PSU 12 6 PSU 38 6 PSU 39 6 PSU 40 (16S copies) Primer Cycle log rRNA gene DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA i l t isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate Pseudomonas Pseudomonas P d Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Clone Clone Clone DNA Source Clone Cl Clone Clone Clone Clone Clone Clone Clone Clone Clone Clone Clone Clone Clone Clone Clone Clone Clone Clone Clone Clone Clone Clone Clone Clone Clone Clone Clone Clone Clone Clone Clone Clone Clone Clone Clone Clone Clone Table C.1. Continued. Table

200 00295 . 0 00334 0 00295 0.32687 0.00266 Ͳ 0.00217 Ͳ 0.00334 Ͳ 0.00019 Ͳ 0.00191 Ͳ 0.00346 Ͳ 0.00096 Ͳ 0.00424 Ͳ 0.00086 Ͳ 0.00374 Ͳ 0.00083 Ͳ 0.00331 Ͳ 0.00187 Ͳ Ͳ 0.00226 Ͳ 0.00208 Ͳ 0.00297 Ͳ 0.00076 Relative Fluorescence 1 0.01153 2 0.00655 3 0.0026 5 4 6 7 8 9 13 21 29 PSU PSU PSU PSU PSU PSU PSU 22 0.00484 PSU 30 0.43738 PSU PSU 13 PSU PSU 23 0.00915 PSU 31 0.51822 PSU PSU 14 PSU 24 0.02076 PSU 32 0.57702 PSU 15 PSU PSU 25 0.03578 PSU 33 0.62055 PSU 16 PSU PSU 26 0.06218 PSU 34 0.65105 PSU 17 PSU PSU 27 0.11358 PSU 35 0.67635 PSU 18 PSU 10 PSU 28 0.20504 PSU 36 0.68781 PSU 19 PSU 11 PSU 29 0.32687 PSU 12 PSU 37 0.68706 PSU 20 PSU 38 0.69403 PSU 39 0.69455 PSU 40 0.68919 rRNA 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 copies) Primer Cycle (16S gene log DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA i l t isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate Pseudomonas Pseudomonas P d Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Source Cl Clone Clone Clone 03645 . 0.7254 Clone 0.0178 Clone Ͳ 0.0041 Clone 0.01256 Clone 0.00701 Clone 0 00361 0.00076 Clone 0.06977 Clone 0.65693 Clone 0 03645 0.62571 0.12339 Clone 0.68518 Clone 0.21464 Clone 0.70569 Clone 0.00032 Clone 0.33475 Clone 0.70841 Clone 0.44343 Clone 0.71439 Clone 0.00137 Clone 0.52396 Clone 0.72627 Clone 0.00348 Clone 0.58165 Clone 0.72617 Clone 0.62571 Clone 0.00908 Clone 0.73507 Clone 0.73523 Clone 0.73119 Ͳ 0.00443 Clone Ͳ 0.00361 Clone Ͳ 0.00258 Clone Ͳ 0.00583 Clone Ͳ 0.00097 Clone Ͳ 0.00014 Clone Ͳ 0.00163 Clone Ͳ 0.00246 Clone Ͳ 0.00264 Clone Ͳ 0.00254 Clone Ͳ 0.00365 Clone Relative Fluorescence DNA 1 2 3 5 4 6 7 8 9 13 21 29 PSU PSU PSU 4 PSU 4 PSU 4 4 4 4 PSU 4 PSU 4 PSU 13 4 PSU 22 4 PSU 30 4 PSU 4 PSU 23 4 PSU 31 4 PSU 4 PSU 14 4 PSU 24 4 PSU 32 4 PSU 15 4 PSU 4 PSU 25 4 PSU 33 4 PSU 16 4 PSU 4 PSU 26 4 PSU 34 4 PSU 17 4 PSU 4 PSU 27 4 PSU 35 4 PSU 18 4 PSU 10 4 PSU 28 4 PSU 36 4 PSU 29 4 PSU 37 4 PSU 19 4 PSU 11 4 PSU 20 4 PSU 12 4 PSU 38 4 PSU 39 4 PSU 40 (16S copies) Primer Cycle log rRNA gene DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA i l t isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate Pseudomonas Pseudomonas P d Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Clone Clone Clone DNA Source Clone Cl Clone Clone Clone Clone Clone Clone Clone Clone Clone Clone Clone Clone Clone Clone Clone Clone Clone Clone Clone Clone Clone Clone Clone Clone Clone Clone Clone Clone Clone Clone Clone Clone Clone Clone Clone Clone Clone Table C.1. Continued. Table

201 49003 . 0 02025 0 49003 0.82983 Ͳ 0.00284 Ͳ 0.00531 Ͳ 0.00736 Ͳ 0.00568 Ͳ 0.00363 Ͳ 0.00631 Ͳ 0.00738 Relative Fluorescence 3 4 2 0.00455 1 0.01583 8 9 7 5 6 13 21 29 PSU 40 1.00802 PSU 39 0.98575 PSU 38 0.96475 PSU 37 0.9514 PSU 20 0.39682 PSU 29 0.82983 PSU 19 0.29109 PSU 36 0.93868 PSU 28 0.80751 PSU 18 0.1904 PSU 35 0.92019 PSU 27 0.78249 PSU 17 0.11901 PSU 26 0.75578 PSU 34 0.90501 PSU PSU PSU 16 0.07739 PSU 25 0.72733 PSU 33 0.89527 PSU PSU 15 0.05226 PSU 24 0.68911 PSU 32 0.87971 PSU PSU 14 0.03365 PSU 23 0.63151 PSU 31 0.86406 PSUPSUPSU 10 11 12 0.00069 0.00587 0.01157 PSU PSU PSU PSU 13 0.02025 PSU 22 0.56517 PSU 30 0.8493 PSU PSU PSU PSU PSU rRNA 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 copies) Primer Cycle (16S gene log DNA DNA DNA DNA i d mixed mixed mixed mixed DNA mixed DNA mixed DNA mixed DNA mixed DNA mixed DNA mixed DNA mixed DNA mixed DNA mixed DNA mixed DNA mixed DNA mixed DNA mixed DNA mixed DNA mixed DNA mixed DNA mixed DNA mixed DNA mixed DNA mixed DNA mixed DNA mixed DNA mixed DNA mixed DNA mixed DNA mixed DNA mixed DNA mixed DNA mixed DNA Source G i Genomic Genomic 35689 0.7414 Genomic 0.7393 Genomic 0.2266 Genomic 0.7083 Genomic . Ͳ 0.0028 Genomic mixed DNA Ͳ 0.0044 Genomic mixed DNA 0.73793 Genomic 0.72959 Genomic 0.72481 Genomic 0.12766 Genomic 0.72774 Genomic 0.71669 Genomic 0.06973 Genomic 0.73403 Genomic 0.03708 Genomic 0.68739 Genomic 0.72857 Genomic 0.00094 Genomic 0.01933 Genomic 0.65848 Genomic 0.72038 Genomic 0.00362 Genomic 0.00959 Genomic 0.62177 Genomic 0.72693 Genomic 0.00867 Genomic 0.00352 Genomic 0.56267 Genomic 0.73154 Genomic 0.00022 Genomic 0.47461 Genomic 0.73051 Genomic 0 00022 0 35689 0.72481 Ͳ 0.00063 Genomic mixed DNA Ͳ 0.00303Ͳ 0.00183 Genomic mixed DNA Genomic mixed DNA Ͳ 0.00408Ͳ 0.00308 Genomic mixed DNA Genomic mixed DNA Ͳ 0.00252 Genomic mixed DNA Ͳ 0.00418 Genomic mixed DNA Relative Fluorescence DNA 4 3 2 1 8 9 5 6 7 13 21 29 PSU PSU PSU 6 PSU 40 6 PSU 39 6 PSU 38 6 PSU 20 6 PSU 37 6 PSU 29 6 PSU 19 6 PSU 36 6 PSU 28 6 PSU 18 6 PSU 27 6 PSU 35 6 PSU 6 PSU 17 6 PSU 26 6 PSU 34 6 PSU 6 PSU 16 6 PSU 25 6 PSU 33 6 PSU 6 PSU 15 6 PSU 24 6 PSU 32 6 PSU 66 PSU PSU 11 12 666 PSU PSU PSU6 10 PSU 14 6 PSU 23 6 PSU 31 6 PSU 6 PSU 13 6 PSU 22 6 PSU 30 66 PSU PSU 6 6 6 (16S copies) Primer Cycle log rRNA gene DNA DNA DNA DNA i d mixed mixed mixed mixed DNA mixed DNA mixed DNA mixed DNA mixed DNA mixed DNA mixed DNA mixed DNA mixed DNA mixed DNA mixed DNA mixed DNA mixed DNA mixed DNA mixed DNA mixed DNA mixed DNA mixed DNA mixed DNA mixed DNA mixed DNA mixed DNA mixed DNA mixed DNA mixed DNA mixed DNA mixed DNA mixed DNA mixed DNA mixed DNA mixed DNA mixed DNA mixed DNA mixed DNA mixed DNA mixed DNA mixed DNA mixed DNA mixed DNA Clone Clone Clone Clone Clone Clone Clone Clone Clone Clone Clone Clone Clone Clone Clone Clone Clone Clone Clone Clone Clone Clone Clone Clone Clone Clone Clone Clone Clone Clone Clone Clone Clone DNA Source Clone Cl Clone Clone Clone Clone Clone Clone Clone Table C.1. Continued. Table

202 60295 0.0489 . Ͳ 0.0018 0.00733 0.00454 0.00185 0.01531 0.64674 0.74653 0.02707 0.67806 0.75323 0.00073 0.70425 0.76056 0.00661 0.09595 0.72774 0.75266 0.18202 0.73734 0.74487 0.31165 0.73961 0.74867 0.44544 0.74332 0.75604 0.54239 0.74657 0.75809 0.75565 0.76049 0.76728 0 01531 0 60295 0.74657 Ͳ 0.00152 Ͳ 0.00077 Ͳ 0.00184 Ͳ 0.00298 Ͳ 0.00264 Ͳ 0.00218 Relative Fluorescence 1 2 3 4 5 6 7 8 9 13 21 29 PSU PSU PSU 6 PSU 6 PSU 6 PSU 13 6 PSU 22 6 PSU 30 666 PSU 6 PSU 6 PSU 66 PSU 6 PSU PSU PSU PSU6 10 PSU 14 6 PSU 23 6 PSU 31 6 PSU6 11 PSU 15 6 PSU 24 6 PSU 32 6 PSU6 12 PSU 16 6 PSU 25 6 PSU 33 6 PSU 17 6 PSU 26 6 PSU 34 6 PSU 18 6 PSU 27 6 PSU 35 6 PSU 19 6 PSU 28 6 PSU 36 6 PSU 20 6 PSU 29 6 PSU 37 6 PSU 38 6 PSU 39 6 6 6 6 PSU 40 (16S copies) Primer Cycle log rRNA gene DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA DNA i l t isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate isolate Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas Pseudomonas P d Pseudomonas Pseudomonas DNA Source Genomic Genomic GGenomic i Genomic Genomic Genomic Genomic Genomic Genomic Genomic Genomic Genomic Genomic Genomic Genomic Genomic Genomic Genomic Genomic Genomic Genomic Genomic Genomic Genomic Genomic Genomic Genomic Genomic Genomic Genomic Genomic Genomic Genomic Genomic Genomic Genomic Genomic Genomic Genomic Genomic Genomic Table C.1. Continued. Table

203 Table C.2. Amplification efficiencies calculated by conventional and alternative- ap proaches for qPCR analyses of artificial mixed communities using group-specific primers (Figure 4.3).

Clone isolateisolate CoefficientCoefficient Fitting Average DNA of Primer Approach DNA Source N Efficiency Deviation Variance Variance PSU Ct Clone isolate DNA 36 1.927839 naa na na PSU Full Clone isolate DNA 36 2.102104 0.119667 5.6927351 0.01432 PSU Swin Clone isolate DNA 36 2.091682 0.120486 5.7602468 0.014517 PSU Fwin Clone isolate DNA 36 2.093552 0.122357 5.8444468 0.014971 PSU Ct Clone mixed DNA 62 2.012643 na na na PSU Full Clone mixed DNA 62 2.114175 0.156236 7.3899062 0.02441 PSU Swin Clone mixed DNA 62 2.065916 0.128854 6.2371491 0.016603 PSU FwinFi CloneCl mixed i d DN DNAA 62 2.1167652 116765 0.1595980 159598 7.53969967 5396996 0.0254710 025471 PSU Ct Genomic isolate DNA 18 1.926363 na na na PSU Full Genomic isolate DNA 18 2.568553 1.405545 54.721266 1.975556 PSU Swin Genomic isolate DNA 18 2.173035 0.27651 12.724613 0.076458 PSU Fwin Genomic isolate DNA 18 2.125373 0.145811 6.8605051 0.021261 PSU Ct Genomic mixed DNA 63 1.843036 na na na PSU Full Genomic mixed DNA 63 3.077459 1.373618 44.63482 1.886827 PSU Swin Genomic mixed DNA 63 2.106704 0.36281 17.22171 0.131631 PSU Fwin Genomic mixed DNA 63 2.096792 0.331705 15.819658 0.110028 RZB Ct Clone isolate DNA 34 1.873509 0.046176 2.4646829 0.002132 RZB FullFull CloneClone isolateisolate DNA 34 1.931477 0.23523 12. 178776 0.055333 RZB Swin Clone isolate DNA 34 1.855042 0.108278 5.8369339 0.011724 RZB Fwin Clone isolate DNA 34 1.910326 0.115744 6.0588614 0.013397 RZB Ct Clone mixed DNA 61 1.916399 na na na RZB Full Clone mixed DNA 61 2.07393 0.185899 8.9635874 0.034558 RZB Swin Clone mixed DNA 61 1.91495 0.114957 6.0031255 0.013215 RZB Fwin Clone mixed DNA 61 1.981391 0.099464 5.019905 0.009893 RZB Ct Genomic isolate DNA 18 1.890711 na na na RZB Full Genomic isolate DNA 18 2.28791 0.446595 19.519777 0.199447 RZB Swin Genomic isolate DNA 18 1.965562 0.164237 8.355707 0.026974 RZB Fwin Genomic isolate DNA 18 1.940669 0.076559 3.9449915 0.005861 RZB Ct Genomic mixed DNA 62 1.825257 na na na RZB Full Genomic mixed DNA 62 2.117546 0.396099 18.705544 0.156894 RZB Swin Genomic mixed DNA 62 1.780674 0.118193 6.6375342 0.01397 RZB Fwin Genomic mixed DNA 62 1.774491 0.078007 4.3960379 0.006085 VIT Ct Clone isolate DNA 39 2.02135 0.081254 0.8164954 0.000272 VIT Full Clone isolate DNA 39 2.159938 0.085694 3.9674177 0.007343 VIT Swin Clone isolate DNA 39 2.064602 0.064881 3.1425621 0.00421 VIT Fwin Clone isolate DNA 39 2.129044 0.062441 2.9328076 0.003899 VIT Ct Clone mixed DNA 62 2.038947 na na na VITFull Clone mixed DNDNAA 62 2.189731 0.107722 4.9194233 0.011604 VIT Swin Clone mixed DNA 62 2.043411 0.082063 4.0159859 0.006734 VIT Fwin Clone mixed DNA 62 2.135425 0.077068 3.6090128 0.005939 VIT Ct Genomic isolate DNA 18 1.963737 na na na VIT Full Genomic isolate DNA 18 2.049392 0.083002 4.0500991 0.006889 VIT Swin Genomic isolate DNA 18 1.979352 0.102288 5.1677655 0.010463 VIT Fwin Genomic isolate DNA 18 2.043338 0.097448 4.769079 0.009496 VIT Ct Genomic mixed DNA 63 2.006268 na na na VIT Full Genomic mixed DNA 63 2.440076 0.544391 22.310402 0.296361 VIT Swin Genomic mixed DNA 63 1.964326 0.199503 10.156326 0.039802 VIT Fwin Genomic mixed DNA 63 2.063433 0.188842 9.1518405 0.035661 a na: not applicable; Ct approach yields only one efficiency for all samples in a given assa

204 Table C.3. Amplification efficiencies calculated by conventional and alternative- ap proaches for qPCR analyses of artificial mixed communities using the universal primer (Figure 4.3).

Clone isolate Coefficient Fitting Average DNA of Primer Approach DNA Source N Efficiency Deviation Variance Variance UNI on clone Pseudonomas isolate DNA Ct Clone isolate DNA 34 1.962456 0.127249 6.4841779 0.016192 UNI on clone Pseudonomas isolate DNA Ct Clone mixed DNA 41 2.08782 naa na na UNI on clone Pseudonomas isolate DNA Ct Genomic isolate DNA 54 2.045276 na na na UNI on clone Pseudonomas isolate DNA Ct Genomic mixed DNA 62 1.837092 na na na UNI on clone l MMartelella t l ll iisolate l t DNADNA Ct CloneCl isolate i l t DN DNAA 35 1.9097891 909789 0.0771270 077127 4.03848484 0384848 0.0059490 005949 UNI on clone Martelella isolate DNA Ct Clone mixed DNA 41 1.988009 na na na UNI on clone Martelella isolate DNA Ct Genomic isolate DNA 54 1.94844 na na na UNI on clone Martelella isolate DNA Ct Genomic mixed DNA 62 1.835914 na na na UNI on clone Vitellibacter isolate DNA Ct Clone isolate DNA 36 1.951665 0.027844 1.4266916 0.000775 UNI on clone Vitellibacter isolate DNA Ct Clone mixed DNA 41 1.92421 na na na UNI on clone Vitellibacter isolate DNA Ct Genomic isolate DNA 54 1.994161 na na na UNI on clone Vitellibacter isolate DNA Ct Genomic mixed DNA 62 1.979119 na na na UNI on clone Pseudonomas isolate DNA Full Clone isolate DNA 34 2.056896 0.144578 7.0289571 0.020903 UNI on clone Pseudonomas isolate DNA Full Clone mixed DNA 41 2.175026 0.181716 8.3546692 0.033021 UNI on cloneclone PseudonomasPseudonomas isolateisolate DNA FullFull GenomicGenomic isolateisolate DNA 54 2.142354 0.51417 24. 00023 0.264371 UNI on clone Pseudonomas isolate DNA Full Genomic mixed DNA 62 3.039073 0.880595 28.975762 0.775447 UNI on clone Martelella isolate DNA Full Clone isolate DNA 35 1.999702 0.147529 7.3775672 0.021765 UNI on clone Martelella isolate DNA Full Clone mixed DNA 41 2.175026 0.181716 8.3546692 0.033021 UNI on clone Martelella isolate DNA Full Genomic isolate DNA 54 2.142354 0.51417 24.00023 0.264371 UNI on clone Martelella isolate DNA Full Genomic mixed DNA 62 3.039073 0.880595 28.975762 0.775447 UNI on clone Vitellibacter isolate DNA Full Clone isolate DNA 36 2.035204 0.217558 10.689744 0.047332 UNI on clone Vitellibacter isolate DNA Full Clone mixed DNA 41 2.175026 0.181716 8.3546692 0.033021 UNI on clone Vitellibacter isolate DNA Full Genomic isolate DNA 54 2.142354 0.51417 24.00023 0.264371 UNI on clone Vitellibacter isolate DNA Full Genomic mixed DNA 62 3.039073 0.880595 28.975762 0.775447 UNI on clone Pseudonomas isolate DNA Swin Clone isolate DNA 34 1.990567 0.132103 6.6364556 0.017451 UNI on clone Pseudonomas isolate DNA Swin Clone mixed DNA 41 1.996796 0.133696 6.6955093 0.017875 UNI on clone Pseudonomas isolate DNA Swin Genomic isolate DNA 54 1.965353 0.288804 14.69476 0.083408 UNI on clone Pseudonomas isolate DNA Swin Genomic mixed DNA 62 2.023638 0.179447 8.8675663 0.032201 UNI on clone Martelella isolate DNA Swin Clone isolate DNA 35 1.913897 0.135136 7.0607659 0.018262 UNI on clone Martelella isolate DNA Swin Clone mixed DNA 41 1.996796 0.133696 6.6955093 0.017875 UNI on clone Martelella isolate DNA Swin Genomic isolate DNA 54 1.965353 0.288804 14.69476 0.083408 UNI on clone Martelella isolate DNA Swin Genomic mixed DNA 62 2.023638 0.179447 8.8675663 0.032201 UNI on clone Vitellibacter isolate DNA Swin Clone isolate DNA 36 1.95097 0.199605 10.23107 0.039842 UNI on clone Vitellibacter isolate DNA Swin Clone mixed DNA 41 1.996796 0.133696 6.6955093 0.017875 UNI on clone Vitellibacter isolate DNDNAA Swin Genomic isolate DNDNAA 54 1.9653531.965353 0.2888040.288804 14.6947614.69476 0.0834080.083408 UNI on clone Vitellibacter isolate DNA Swin Genomic mixed DNA 62 2.023638 0.179447 8.8675663 0.032201 UNI on clone Pseudonomas isolate DNA Fwin Clone isolate DNA 34 2.040432 0.117878 5.7771294 0.013895 UNI on clone Pseudonomas isolate DNA Fwin Clone mixed DNA 41 2.013842 0.123714 6.143188 0.015305 UNI on clone Pseudonomas isolate DNA Fwin Genomic isolate DNA 54 1.995154 0.237744 11.916078 0.056522 UNI on clone Pseudonomas isolate DNA Fwin Genomic mixed DNA 62 1.99583 0.139229 6.9760166 0.019385 UNI on clone Martelella isolate DNA Fwin Clone isolate DNA 35 1.957572 0.123427 6.3051198 0.015234 UNI on clone Martelella isolate DNA Fwin Clone mixed DNA 41 2.013842 0.123714 6.143188 0.015305 UNI on clone Martelella isolate DNA Fwin Genomic isolate DNA 54 1.995154 0.237744 11.916078 0.056522 UNI on clone Martelella isolate DNA Fwin Genomic mixed DNA 62 1.99583 0.139229 6.9760166 0.019385 UNI on clone Vitellibacter isolate DNA Fwin Clone isolate DNA 36 1.955684 0.161005 8.232665 0.025923 UNI on clone Vitellibacter isolate DNA Fwin Clone mixed DNA 41 2.013842 0.123714 6.143188 0.015305 UNI on clone Vitellibacter isolate DNA Fwin Genomic isolate DNA 54 1.995154 0.237744 11.916078 0.056522 UNI on clone Vitellibacter isolate DNA Fwin Genomic mixed DNA 62 1.99583 0.139229 6.9760166 0.019385 a na: not applicable; Ct approach yields only one efficiency for all samples in a given assa

205 Table C.4. Log copy number errors calculated by conventional and alternative -ap proaches for qPCR analyses of artificial mixed communities using group-specific primers (Figure 4.4).

Averagelog cocopypy number Standard Coefficient Primer FittingApproach DNASource N error Deviation ofVariance PSU Ct ClonemixedDNA 62 4.64 1.41 30.48 RZB Ct ClonemixedDNA 61 3.22 2.38 73.91 VIT Ct ClonemixedDNA 62 6.13 9.63 157.04 PSU Full,Diagnosticpoint ClonemixedDNA 62 2.65 2.60 98.38 RZB Full,Diagnosticpoint ClonemixedDNA 61 2.41 1.80 74.79 VIT Full,Diagnosticpoint ClonemixedDNA 62 5.96 9.87 165.67 PSU Swin,Diagnosticpoint ClonemixedDNA 62 2.82 2.72 96.46 RZB Swin,Diagnosticpoint ClonemixedDNA 61 2.45 1.66 67.89 VIT Swin,Diagnosticpoint ClonemixedDNA 62 5.87 8.95 152.55 PSU Fwin,Diagnosticpoint ClonemixedDNA 62 2.68 2.83 105.71 RZB Fwin,Diagnosticpoint ClonemixedDNA 61 2.46 1.75 71.28 VIT Fwin,Diagnosticpoint ClonemixedDNA 62 5.85 9.57 163.69 PSU Full,initialfluorescence ClonemixedDNA 62 6.45 4.93 76.34 RZB Full,initialfluorescence ClonemixedDNA 61 16.67 23.77 142.56 VIT Full,initialfluorescence ClonemixedDNA 62 8.03 6.49 80.90 PSU Swin,initialfluorescence ClonemixedDNA 62 7.76 7.64 98.47 RZB Swin,initialfluorescence ClonemixedDNA 61 10.9610.96 11.3511.35 103.58103.58 VIT Swin,initialfluorescence ClonemixedDNA 62 14.46 15.31 105.92 PSU Fwin,initialfluorescence ClonemixedDNA 62 4.93 4.38 88.86 RZB Fwin,initialfluorescence ClonemixedDNA 61 8.42 8.90 105.71 VIT Fwin,initialfluorescence ClonemixedDNA 62 8.03 7.71 95.98 PSU Ct GenomicisolateDNA 18 1.53 1.50 98.35 RZB Ct GenomicisolateDNA 18 15.81 10.65 67.40 VIT Ct GenomicisolateDNA 18 13.34 6.30 47.20 PSU Full,Diagnosticpoint GenomicisolateDNA 18 10.62 3.12 29.42 RZB Full,Diagnosticpoint GenomicisolateDNA 18 3.32 2.49 75.01 VIT FullFull,DiagnosticDiagnosticpointpoint GenomicGenomicisolateisolateDNA 18 11. 08 5. 60 50. 54 PSU Swin,Diagnosticpoint GenomicisolateDNA 18 4.12 2.47 59.87 RZB Swin,Diagnosticpoint GenomicisolateDNA 18 6.33 3.26 51.60 VIT Swin,Diagnosticpoint GenomicisolateDNA 18 11.35 5.23 46.09 PSU Fwin,Diagnosticpoint GenomicisolateDNA 18 4.02 1.81 44.93 RZB Fwin,Diagnosticpoint GenomicisolateDNA 18 7.61 3.15 41.42 VIT Fwin,Diagnosticpoint GenomicisolateDNA 18 16.95 7.89 46.54 PSU Full,initialfluorescence GenomicisolateDNA 18 10.65 11.05 103.77 RZB Full,initialfluorescence GenomicisolateDNA 18 96.05 64.48 67.13 VIT Full,initialfluorescence GenomicisolateDNA 18 10.04 6.28 62.56 PSU Swin,initiallfluorescencefl Genomicisolatel DNA 18 7.49 6.50 86.77 RZB Swin,initialfluorescence GenomicisolateDNA 18 9.59 7.23 75.37 VIT Swin,initialfluorescence GenomicisolateDNA 18 6.60 4.23 64.07 PSU Fwin,initialfluorescence GenomicisolateDNA 18 5.90 4.72 79.93 RZB Fwin,initialfluorescence GenomicisolateDNA 18 8.78 7.46 84.90 VIT Fwin,initialfluorescence GenomicisolateDNA 18 11.61 6.33 54.48 PSU Ct GenomicmixedDNA 63 5.27 2.59 49.15 RZB Ct GenomicmixedDNA 62 10.92 3.83 35.07 VIT Ct GenomicmixedDNA 63 8.39 2.92 34.85 PSU Full, Diagnosticpoint GenomicmixedDNA63 4.04 1.85 45.74 RZB Full,Diagnosticpoint GenomicmixedDNA 62 6.68 5.68 85.10 VIT Full,Diagnosticpoint GenomicmixedDNA 63 6.56 5.61 85.66 PSU Swin,Diagnosticpoint GenomicmixedDNA 63 2.32 1.65 71.17 RZB Swin,Diagnosticpoint GenomicmixedDNA 62 7.58 5.53 72.98 VIT Swin,Diagnosticpoint GenomicmixedDNA 63 7.29 4.17 57.22 PSU Fwin,Diagnosticpoint GenomicmixedDNA 63 2.10 1.58 75.12 RZB Fwin,Diagnosticpoint GenomicmixedDNA 62 7.88 5.50 69.75 VIT Fwin,Diagnosticpoint GenomicmixedDNA 63 7.15 4.58 64.12 PSU Full,initialfluorescence GenomicmixedDNA 63 26.19 16.80 64.12 RZB Full,initialfluorescence GenomicmixedDNA 62 71. 84 32. 93 45. 84 VIT Full,initialfluorescence GenomicmixedDNA 63 23.87 15.54 65.12 PSU Swin,initialfluorescence GenomicmixedDNA 63 14.62 14.26 97.54 RZB Swin,initialfluorescence GenomicmixedDNA 62 8.74 6.52 74.59 VIT Swin,initialfluorescence GenomicmixedDNA 63 17.57 21.05 119.77 PSU Fwin,initialfluorescence GenomicmixedDNA 63 13.74 13.94 101.44 RZB Fwin,initialfluorescence GenomicmixedDNA 62 8.48 7.35 86.67 VIT Fwin,initialfluorescence GenomicmixedDNA 63 14.85 17.28 116.37

206 Table C.5. Log copy number errors calculated by conventional and alternative -ap proaches for qPCR analyses of artificial mixed communities using the universal primer (Figure 4.5).

Averagelog Totall16SrRNAgenecopycalculationll Fitting copynumberb Standarddd Coefficientff approach DNASource Approach N error Deviation ofVariance Sumofisolates ClonemixedisolateDNA Ct 48 2.61 1.37 52.53 Sumofisolates ClonemixedisolateDNA Full 48 1.85 1.18 63.89 Sumofisolates ClonemixedisolateDNA Swin 48 1.72 1.21 70.12 Sumofisolates ClonemixedisolateDNA Fwin 48 1.66 1.20 72.25 Averageofvaluesfromstandardcurves ClonemixedisolateDNA Ct 41 4.09 1.92 46.79 Averageofvaluesfromstandardcurves ClonemixedisolateDNA Full 41 5.79 3.43 59.24 Averageofvaluesfromstandardcurves ClonemixedisolateDNA Swin 41 6.23 3.12 49.97 AverageAverageooffvavaluesluesffromromstanstandarddardcurves CloneClonemmixedixedisolateisolateDNA FwinFwin 41 5. 79 3. 24 55. 85 byPseudomonas standardcurve ClonemixedisolateDNA Ct 41 4.24 4.27 100.85 byPseudomonas standardcurve ClonemixedisolateDNA Full 41 4.88 3.75 76.76 byPseudomonas standardcurve ClonemixedisolateDNA Swin 41 4.49 3.40 75.75 byPseudomonas standardcurve ClonemixedisolateDNA Fwin 41 4.63 4.02 86.98 byMartelella standardcurve ClonemixedisolateDNA Ct 41 4.91 2.55 51.95 byMartelella standardcurve ClonemixedisolateDNA Full 41 6.42 3.42 53.36 byMartelella standardcurve ClonemixedisolateDNA Swin 41 7.49 3.55 47.48 byMartelella standardcurve ClonemixedisolateDNA Fwin 41 6.80 3.45 50.73 bbyyVitelllibacter standardcurve Clone mixedisolateDNA Ct 41 7.07 4.24 60.02 byVitelllibacter standardcurve ClonemixedisolateDNA Full 41 10.39 4.74 45.67 byVitelllibacter standardcurve ClonemixedisolateDNA Swin 41 10.18 4.84 47.52 byVitelllibacter standardcurve ClonemixedisolateDNA Fwin 41 10.17 4.72 46.45 initialfluorescence ClonemixedisolateDNA Ct 41 naa na na initialfluorescence ClonemixedisolateDNA Full 40 8.36 5.31 63.44 initialfluorescence ClonemixedisolateDNA Swin 41 6.44 4.30 66.71 initialfluorescence ClonemixedisolateDNA Fwin 41 5.74 4.04 70.36 Sumofisolates GenomicsingleisolateDNA Ct 54 9.45 8.93 94.54 Sumofisolates GenomicsingleisolateDNA Full 54 7.69 5.33 69.40 Sumofisolates GenomicsingleisolateDNA Swin 54 7.18 4.95 68.94 Sumofisolates GenomicsingleisolateDNA Fwin 54 8.81 7.64 86.70 Averageofvaluesfromstandardcurves GenomicsingleisolateDNA Ct 54 7.74 4.69 60.67 Averageofvaluesfromstandardcurves GenomicsingleisolateDNA Full 54 7.94 6.54 82.40 Averageofvaluesfromstandardcurves GenomicsingleisolateDNA Swin 54 8.58 5.74 66.95 Averageofvaluesfromstandardcurves GenomicsingleisolateDNA Fwin 54 7.77 5.31 68.26 byPseudomonas standardcurve GenomicsingleisolateDNA Ct 54 8.98 4.77 53.16 byPseudomonas standardcurve GenomicsingleisolateDNA Full 54 7.93 5.79 73.02 byPseudomonas standardcurve GenomicsingleisolateDNA Swin 54 9.85 8.55 86.82 byPseudomonas standardcurve GenomicsingleisolateDNA Fwin 54 8. 23 6. 70 81. 46 byMartelella standardcurve GenomicsingleisolateDNA Ct 54 8.59 7.76 90.29 byMartelella standardcurve GenomicsingleisolateDNA Full 54 7.82 6.21 79.33 byMartelella standardcurve GenomicsingleisolateDNA Swin 54 8.57 5.98 69.72 byMartelella standardcurve GenomicsingleisolateDNA Fwin 54 9.36 7.48 79.93 byVitelllibacter standardcurve GenomicsingleisolateDNA Ct 54 8.62 4.74 54.99 byVitelllibacter standardcurve GenomicsingleisolateDNA Full 54 10.01 7.78 77.75 byVitelllibacter standardcurve GenomicsingleisolateDNA Swin 54 8.42 4.80 56.99 byVitelllibacter standardcurve GenomicsingleisolateDNA Fwin 54 8.39 5.13 61.21 initialfluorescence GenomicsingleisolateDNACt 54 na na na initialfluorescence GenomicsingleisolateDNA Full 54 17.17 10.53 61.32 initialfluorescence GenomicsingleisolateDNA Swin 54 16.23 9.96 61.39 initialfluorescence GenomicsingleisolateDNA Fwin 54 11.54 9.27 80.34 ana:notapplicable;Ctapproachcannotbeusedtocalculateinitialfluorescence.

207 Table C.5. Continued.

Averagelog Totall16SrRNAgenecopycalculationll Fitting copynumberb Standarddd Coefficientff approach DNASource Approach N error Deviation ofVariance Sumofisolates GenomicmixedisolateDNA Ct 60 7.12 3.09 43.36 Sumofisolates GenomicmixedisolateDNA Full 60 3.55 3.01 84.88 Sumofisolates GenomicmixedisolateDNA Swin 60 4.21 3.19 75.77 Sumofisolates GenomicmixedisolateDNA Fwin 60 4.23 2.71 64.20 Averageofvaluesfromstandardcurves GenomicmixedisolateDNA Ct 62 5.87 3.55 60.51 Averageofvaluesfromstandardcurves GenomicmixedisolateDNA Full 62 4.93 4.41 89.44 Averageofvaluesfromstandardcurves GenomicmixedisolateDNA Swin 62 6.05 4.26 70.39 AverageAverageooffvavaluesluesffromromstanstandarddardcurves GenomicGenomicmixedmixedisolateisolateDNA FwinFwin 62 6. 57 4. 14 63. 05 byPseudomonas standardcurve GenomicmixedisolateDNA Ct 62 7.06 3.33 47.07 byPseudomonas standardcurve GenomicmixedisolateDNA Full 62 5.90 4.61 78.20 byPseudomonas standardcurve GenomicmixedisolateDNA Swin 62 6.99 4.20 60.07 byPseudomonas standardcurve GenomicmixedisolateDNA Fwin 62 8.66 3.72 42.98 byMartelella standardcurve GenomicmixedisolateDNA Ct 62 7.76 3.34 43.01 byMartelella standardcurve GenomicmixedisolateDNA Full 62 6.54 5.01 76.62 byMartelella standardcurve GenomicmixedisolateDNA Swin 62 8.79 4.09 46.46 byMartelella standardcurve GenomicmixedisolateDNA Fwin 62 9.18 3.97 43.22 bybyVitelllibacter standardcurve Genomic mixedisolateDNA Ct 62 3.59 3.39 94.52 byVitelllibacter standardcurve GenomicmixedisolateDNA Full 62 5.57 2.87 51.45 byVitelllibacter standardcurve GenomicmixedisolateDNA Swin 62 3.92 3.51 89.63 byVitelllibacter standardcurve GenomicmixedisolateDNA Fwin 62 4.05 3.46 85.48 initialfluorescence GenomicmixedisolateDNA Ct 62 naa na na initialfluorescence GenomicmixedisolateDNA Full 61 30.77 6.49 21.11 initialfluorescence GenomicmixedisolateDNA Swin 61 16.66 5.56 33.36 initialfluorescence GenomicmixedisolateDNA Fwin 60 7.91 4.82 60.95 ana:notapplicable;Ctapproachcannotbeusedtocalculateinitialfluorescence.

208 14 14 11 09 08 46 06 60 37 05 31 26 22 19 16 Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ 5.0 07999E 041320017 000241305 . . . 7 07999E 0 0 041320017 00 000241305 08 08 07 1.19803E 06 1.20598E 05 7.63229E 27 8.33132E 36 1.59998E 22 3.38354E 19 4.33821E 16 2.37129E 13 1.76153E 12 3.29955E 10 2.25159E Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ model 3.0 : 3682E . f 026396435 000144855 1 3682E . . 0 0 026396435 00 000144855 parameters for qPCR reaction fluorescence fluorescence qPCR reaction for parameters f 05 05 05 0.000257995 0.000429627 05 0.000109731 0.000182814 09 1.7384E 05 0.000192594 0.000320782 12 3.39315E 08 2.16226E 06 8.90627E 06 5.66939E 05 1.10765E Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ parameter 5 Ͳ Hypothetical of 1.0 00936823 . 83094E 001468909 . fit . 0 0 00936823 44 83094E 0 001468909 the of 05 0505 0.000158312 0.00047423405 0.000116243 0.000789224 8.60712E 0.00034834 0.00057992 05 3.65913E 05 05 2.01518E 05 6.42398E 06 3.99777E Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ 0.5 41577E 017496715 004758126 . . . derivative 22 41577E 0 017496715 0 0 004758126 First 05 06 05 06 05 1.82974E 18 4.35116E 05 0.026505666 0.003757844 2.84669E 24 2.74077E 15 0.000219275 7.67666E 12 0.000690777 1.0158E 10 0.001682226 7.53034E 09 0.003480981 3.86938E 0807 0.00643668 0.010957612 0.000154368 0.000511484 9.57509E 4.553E Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ : f 5249E . 2.0 09124E 017920718 . 99 5249E . 6 09124E 7.21491E 0 0 017920718 Actual cells amplified with PSU primer (Figure 4.6). amplified with PSU primer (Figure cells 002182 646174 754532 . . . 0 002182 0 0 646174 00 754532 : f 002182 687851 754910 . . . e=16.98968. 0 002182 0 0 687851 00 754910 model Pseudomonas

003509 732224 755287 Hypothetical 6 . . . 0 003509 0 0 732224 00 755287 d=0.7554763; parameter 5 Ͳ of Fit 033802 743759 755382 . . . 0 033802 0 0 743759 00 755382 c=0.00218155; : f 002184 710308 755104 . . . 2.0 0.5 1.0 3.0 5.0 0 002184 0 0 710308 00 755104 9.977496; Actual Ͳ b= 00264 70425 76049 . . . 0.0489 0.041573 0.358671 0.170887 0.010643 0.002606 0.040101101 0.09200961 0.087085352 0.013103704 0.001095394 0.0018 0.002182 0.003868 0.002185 0.002182 0.002182 1.04539E Fits and first and second derivatives of fits with actual and hypothetical of fits with actual and derivatives and second Fits and first Ͳ 0.18202 0.1953280.44544 0.5356480.54239 0.432935 0.3799700.60295 0.531091 0.6559490.64674 0.097202 0.603855 0.690876 0.026081 0.5695710.67806 0.654289 0.713754 0.631815 0.324077 0.688045 0.728425 0.184802 0.111441261 0.6743420.72774 0.442061 0.737777 0.309493 0.7023450.73734 0.537349 0.078037223 0.724954 0.428276 0.110092482 0.7204940.73961 0.607060 0.11052833 0.734631 0.747618 0.524743 0.0854234230.74332 0.655328 0.042363026 0.741077 0.750136 0.08339924 0.739842 0.596074 0.060720656 0.028200519 0.073531818 0.745415 0.034960535 0.751799 0.744833 0.041137587 0.709540 0.125149731 0.018206635 0.051564224 0.752913 0.118334677 0.680482 0.748140 0.0272488890.75323 0.723996 0.011615465 0.034396461 0.10807253 0.703744 0.7503580.76056 0.733682 0.082158278 0.007409439 0.022396691 0.125837374 0.751808 0.109022562 0.719504 0.0118069290.75266 0.740224 0.014470702 0.05804624 0.752802 0.754545 0.730228 0.0078317430.74487 0.039473702 0.003087314 0.083577972 0.753507 0.754797 0.059820992 0.005244061 0.7536140.74867 0.002027639 0.006110215 0.754014 0.754977 0.003549092 0.7541190.75604 0.749904 0.017577644 0.001348837 0.004026529 0.754381 0.755105 0.028092625 0.746212 0.7544770.75809 0.751411 0.011740663 0.002684505 0.00090889 0.754649 0.755198 0.748713 0.754734 0.752483 0.007897421 0.01901875 0.001811593 0.754847 0.755266 0.012907254 0.001176191 0.750494 0.754921 0.753253 0.005361171 0.755317 0.751774 0.000831732 0.755057 0.753810 0.000299292 0.008814267 0.752702 0.755157 0.754218 0.000211432 0.000597844 0.00059415 0.753380 0.000428562 0.754519 0.001784675 0.000422484 0.000150931 0.002959771 0.753881 0.000311987 0.001262887 0.000108813 0.000301662 0.002097233 0.000229121 0.000217518 0.000902588 7.9185E 0.000169674 0.000651269 0.001500326 5.81376E 0.00108331 4.30447E 0 00264 0 0 70425 00 76049 0.00454 0.002182 0.002199 0.002182 0.002182 0.002182 3.86365E 0.00218 0.002204 0.055581 0.005967 0.002182 0.002182 4.31606E 0.00073 0.002323 0.087749 0.011901 0.002183 0.002182 0.000249985 0.038305875 0.008702359 4.34635E 0.00661 0.002939 0.133095 0.024933 0.002202 0.002182 0.001204662 0.052780838 0.018345356 5.02027E 0.01531 0.005589 0.193841 0.050945 0.002386 0.002182 0.004822969 0.068788295 0.035003444 0.000440045 3.07334E 0.00733 0.002182 0.002182 0.002182 0.002182 0.002182 9.21915E 0.00185 0.002182 0.002313 0.002182 0.002182 0.002182 7.5134E 0.02707 0.014976 0.270237 0.097568 0.003711 0.002206 0.015705426 0.083423677 0.059371712 0.002855892 7.63188E 0.00152 0.002182 0.002735 0.002182 0.002182 0.002182 1.61921E 0.09595 0.099686 0.450764 0.269310 0.035773 0.006406 0.077389184 0.090268052 0.107508142 0.040557555 0.00850021 0.00077 0.002182 0.006368 0.002205 0.002182 0.002182 3.1485E 0.001840.00298 0.002182 0.002182 0.011215 0.019763 0.002290 0.002592 0.002182 0.002182 0.002182 0.002182 5.60166E 6.77499E Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ parameters: Data Relative Fluorescence model Actual 2 9 1 3 4 5 6 7 8 36 37 1819 20 21 0.31111222 23 0.314813 0.604925 0.48446226 27 0.199865 0.08321128 29 0.1229542963031 0.060100514 0.096177994 0.74112733 0.118267958 0.080795277 0.74112334 0.74836635 0.750396 0.753667 0.754185 0.751862 0.752896 0.744687 0.737579 0.747762 0.742663 0.002428925 0.001681001 0.000620188 0.000428348 0.001237398 0.000855227 0.00367666 0.002548135 0.006069113 0.004217847 10 17 24 24 25 32 39 39 40 0.767280 0.755187 0.755403 0.755330 0.755036 0.754743 38 0.755112 0.754994 0.755354 0.755232 0.754742 0.754253 0.000126649 3.21251E 11 12 13 14 16 15 Cycle Other a Table C.6. Table 10 DNA from isolate genomic from

209 44 36 30 25 21 18 15 59 05 13 05 13 05 11 09 07 05 05 Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ 5.0 83751E 78282E 015718176 . . . 0.01093928 0.00151455 5.01177E 3 83751E 66 78282E 9.25037E Ͳ Ͳ 0 0 015718176 0.007235774 0.023516173 0.000712379 0.025662639 0.007411235 0.021320798 0.004969055 0.003327609 0.002237263 0.001033964 0.000495476 0.000347887 0.000246539 0.000176298 0.000127171 Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ 26 2.03649E 21 5.51376E 18 5.3021E 15 2.31852E 13 1.43522E 1109 2.30398E 1.37502E 35 7.82192E 08 05 08 05 05 07 5.82085E 05 5.27507E 05 05 Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ model e=16.98968. 3.0 : 38769E 07359E 010718692 . . 3.0093E f . Ͳ 4 38769E 44 07359E 7.64263E 5.55712E 0 0 010718692 0.0074309480.023915615 0.023645255 0.026130112 0.007135942 0.000430391 0.021536657 0.004702418 0.015659249 0.003097203 0.002049941 0.001367468 0.000920793 0.000626297 0.000298799 0.000209521 0.000148341 0.000106004 Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ parameter 09 2.51481E 07 2.08532E 06 6.44201E 05 3.28057E 05 5.34094E 11 9.81723E 05 05 05 05 05 05 05 05 5 Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ d=0.7554763; of Hypothetical fit 1.0 35916E 001459497 004044553 . . . 0.02342501 0.00258177 the 11 35916E 1.00385E 7.01037E 4.95867E 3.54101E 2.55167E 1.85467E Ͳ Ͳ 0 001459497 0 0 004044553 0.0066981770.020294948 0.043745585 0.022214502 0.03879451 0.047400843 0.019856534 0.014459996 0.000144457 0.009742594 0.001656384 0.006323575 0.001072128 0.000701468 0.000464313 0.000310993 0.000210753 0.000100106 Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ of 05 9.04564E 05 3.589E 06 06 06 05 05 05 05 05 05 06 c=0.00218155; Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ derivative 0.5 79745E 007703175 002084759 . 7.2353E . . 0.00131728 Ͳ 66 79745E 5.02017E 5.01167E 3.50848E 2.48108E 1.77145E 1.27635E 9.27624E Ͳ 0 007703175 0 0 002084759 0.016144719 0.018674797 0.016240629 0.012014305 0.008119767 0.005238521 0.000839602 0.003312496 0.000541121 0.000353032 0.007438515 0.01277464 0.037464766 0.014693987 0.000233227 0.000156008 0.000105626 Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ 9.977496; Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Second b= 14 0.000291544 2.29724E 12 0.000688832 2.27984E 10 0.00134197 1.35206E 09 0.002313858 5.78916E 07 0.003665778 0.000197914 3.9568E 06 0.005452228 0.000573286 1.64538E 05 05 05 05 17 8.67784E 22 1.09322E 05 05 0.010373104 0.003335922 8.17909E 05 05 05 05 Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ : f 6792E . 1.979E 26052E Ͳ parameters: 007513369 . 22 6792E 6.9761E . Ͳ Ͳ 1 26052E 9.76574E 5.02826E 3.65545E Actual 0 0 007513369 0.002108614 0.021202183 0.004893748 0.000283934 0.026094335 0.022505824 0.016615687 0.003180448 0.000196937 0.011373896 0.002076009 0.001365892 0.000907516 0.000609414 0.000413723 0.000138001 Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ Ͳ model 3 4.67757E 4 7.56046E 5 3.90488E 6 9.80022E 7 1.49425E 8 1.58033E 2 3.60805E 9 1 1.72185E 10 7.99675E 1718 19 0.024941774 24 24 25 32 39 39 40 20 21 11 0.000415754 0.013217762 0.006898614 1.12284E 22 26 33 12 0.001785035 0.015555979 0.012803239 0.000115998 2.99437E 23 27 13 0.0062169 0.015979643 0.020694385 0.000891902 1.06414E 28 141516 0.016739631 0.03217606 0.012475671 0.039473646 0.027356319 0.00390709 0.004871107 0.026174629 0.000225179 0.017466699 0.002590997 29 30 31 34 35 36 37 38 Cycle 2.0 Other a Table C.6. Continued. Table

210 Table C.7. f parameters calculated by sigmoidal fitting approaches for qPCR analyses of artificial mixed communities using group-specific and universal primers (Figure 4.7).

Clone isolate Fitting DNA Coefficient Approach DNASource Primer N Averagef Deviation ofVariance Full CloneisolateDNA PSU 36 1.2924344 0.3012803 23.31 Full CloneisolateDNA RZB 32 1.3222748 0.4053161 30.65 Full CloneisolateDNA VIT 39 1.0579548 0.1563788 14.78 Full CloneisolateDNA UNI 105 1.4787967 0.4810259 32.53 Swin CloneisolateDNA PSU 34 1.1855707 0.1584349 13.36 Swin CloneisolateDNA RZB 34 1.013058 0.1817653 17.94 Swin CloneisolateDNA VIT 39 0.8725644 0.09801 11.23 Swin CloneisolateDNA UNI 105 1.2521738 0.3277894 26.18 Fwin CloneisolateDNA PSU 36 1.3797869 0.316983 22.97 Fwin CloneisolateDNA RZB 34 1.4019838 0.4584523 32.70 Fwin CloneisolateDNA VIT 39 1.0297886 0.1452688 14.11 Fwin CloneisolateDNA UNI 105 1.5363925 0.383646 24.97 Fu ll ClonemiidxedDNA PSU 62 1.2619612 0.2361959 18.72 Full ClonemixedDNA RZB 61 1.6358868 0.650732 39.78 Full ClonemixedDNA VIT 62 1.1267605 0.157806 14.01 Full ClonemixedDNA UNI 41 1.6795983 0.4648609 27.68 Swin ClonemixedDNA PSU 62 1.14966 0.1520348 13.22 Swin ClonemixedDNA RZB 61 1.1280435 0.2295218 20.35 Swin ClonemixedDNA VIT 62 0.8464141 0.1206983 14.26 Swin ClonemixedDNA UNI 41 1.2016669 0.2317879 19.29 Fwin ClonemixedDNA PSU 62 1.3627543 0.235712 17.30 Fwin ClonemixedDNA RZB 61 1.622306 0.3940288 24.29 Fwin ClonemixedDNA VIT 62 1.1065459 0.2172455 19.63 Fwin ClonemixedDNA UNI 41 1.2730091 0.2193908 17.23 Full GenomicisolateDNA PSU 15 1.3640426 0.3708086 27.18 Full GenomicisolateDNA RZB 15 2.050538 1.3516052 65.91 Full GenomicisolateDNA VIT 18 1.0143442 0.1281541 12.63 Full GenomicisolateDNA UNI 50 1.4998319 0.6891456 45.95 Swin GenomicisolateDNA PSU 18 1.5953901 0.8922983 55.93 Swin GenomicisolateDNA RZB 18 1.47282 0.8197566 55.66 Swin GenomicisolateDNA VIT 18 0.8554411 0.0948493 11.09 Swin GenomicisolateDNA UNI 54 1.302856 0.6160345 47.28 Fwin GenomicisolateDNA PSU 18 1.4673112 0.328316 22.38 Fwin GenomicisolateDNA RZB 18 1.4335642 0.2646858 18.46 Fwin GenomicisolateDNA VIT 18 1.0690706 0.1632528 15.27 Fwin GenomicisolateDNA UNI 54 1.5184373 0.4144501 27.29 Full GenomicmixedDNA PSU 63 6.9174144 5.0483977 78.76 Full GenomicmixedDNA RZB 62 4.6325393 4.1472072 89.52 Full GenomicmixedDNA VIT 63 3.372916 3.3294087 98.71 Full GenomicmixedDNA UNI 62 6.4726921 3.3346718 51.52 Swin GenomicmixedDNA PSU 63 2.089147 1.5506909 74.23 Swin GenomicmixedDNA RZB 62 1.4011033 0.6649155 47.46 Swin GenomicmixedDNA VIT 63 1.0824636 0.5025144 46.42 Swin GenomicmixedDNA UNI 62 1.6731377 0.883076 52.78 Fwin GenomicmixedDNA PSU 63 2.1057738 0.9156227 43.48 Fwin GenomicmixedDNA RZB 62 1.5083279 0.3192882 21.17 Fwin GenomicmixedDNA VIT 63 1.5847165 0.5399556 34.07 Fwin GenomicmixedDNA UNI 62 1.5415179 0.3972264 25.77

211 Ap p e n d i x D: Ch a p t e r 5 Da t a ) ) M µM ( (µ n ln(µM) l ln(µM) na na na na na na na na na na na na na na na na na na na na na na na na na 62 0972 .47 . 0 4762 0 Ͳ 0.1468 ln(µM) fitting Unit kinetic Value used in M 0.0972 ln µM 0.3716 ln(µM) µM µ µM RR RR RR RR 00 1 6 1021 0015 0027 flask . . . 1.4500 0.0028 RR 1.1619 µM1.2547 µM 0.1500 ln(µM) 0.2269 ln(µM) 11. 6100 1 0.0000 RR 0.0000 RR 0.0000 RR 0 0015 0 0.0027 RR 1.5189 µM1.4043 µM 0.4180 ln(µM) 1.0779 µM0.8635 µM 0.3395 ln(µM) 1.3144 µM 0.0750 ln(µM) 0.2734 ln(µM) 0.0027 RR 0.0025 0.0000 RR 1.3600 µM 0.3075 ln(µM) 1.2856 µM 0.2512 ln(µM) 0.0028 RR 0.0016 RR 0.0254 0.0000 RR 1.1021 0.0000 RR 0.0201 RR 0.0216 RR 0.0026 RR 0.0018 RR 0.0017 RR 0.0016 RR 0.0012 RR 0.0010 RR 0.0010 RR 0.0018 RR in or relative zero Ͳ or first Ͳ order models. response (RR) Unit fit (µM) Concentration not _ _ a na na na na na na na na na na na na na na na na na na na na na na na na 66 75 . . na 102 94.1 82 120 75 that did analytical in sample (µM) Concentration 0 0 0 0 0 0 1224 2743 for compounds 300293 044591 488104 375.428 . . 38347705621106 108.75 87.14 5729906 2920172 4991536 113.92 4664671 80.84 31780703568712 64.76 98.58 3280651 105.32 4026519 4014546 96.42 2920172 82.66 404.0125 15746.64 4104.767 1030.0191 Response 1990.66686 1604.33278 1413.73649 2048.488104 1683 044591 2048 2184.062933 1398.909322 1076.447971 824.5592481 824.5592481 1982.174117 reported not kinetic fits ene h hene p op hi concentration; enzot b benzothio y roxy d drox y y p y y hydroxybenzothiophene hydroxybenzothiophene h analytical Ͳ 2 Ͳ hydroxybenzothiophene 2 Ͳ hydroxybenzothiophene DBT DBT DBT 2 Ͳ hydroxybenzothiophene 2 Ͳ hydroxybenzothiophene DBT DBT 2 3 DBT DBT 3 Ͳ hydroxybenzothiophene DBT DBT DBT 2 Ͳ hydroxybenzothiophene 3 Ͳ hydroxybenzothiophene DBT DBT 2 Ͳ hydroxybenzothiophene 2 Ͳ hydroxybenzothiophene 3 Ͳ hydroxybenzothiophene 3 Ͳ hydroxybenzothiophene 3 Ͳ hydroxybenzothiophene DBT 3 Ͳ hydroxybenzothiophene 2 Ͳ hydroxybenzothiophene 3 Ͳ hydroxybenzothiophene 3 Ͳ hydroxybenzothiophene 3 Ͳ h 3 Ͳ hydroxybenzothiophene 2 Ͳ hydroxybenzothiophene 2 Ͳ hydroxybenzothiophene 3 Ͳ hydroxybenzothiophene 2 Ͳ hydroxybenzothiophene 3 Ͳ hydroxybenzothiophene d d ze ze i i vat vat i i er er d d response have no n n Underivatized Underivatized Underivatized Underivatized Underivatized U Underivatized Underivatized U Underivatized Underivatized Underivatized Underivatized Underivatized Underivatized Underivatized Underivatized Underivatized Underivatized Underivatized Underivatized Underivatized Underivatized Underivatized Underivatized Underivatized Underivatized Underivatized Underivatized Underivatized Underivatized Underivatized Underivatized Underivatized Underivatized Underivatized Underivatized Underivatized Underivatized Underivatized 2 3 3 1 as relative Replicate Un/derivatized Compound Ͳ 2 0 0 3 00 2 3 0 1 0 1 0 1 0 2 0 3 500 2 500 2 500 3 500 1 500 1 500 3 500500500 1 2 3 1250 2000 1250 2000 1 1250 2 1250 1 12502000 2 2000 2 3 1250 1 1250 3 1250 3 1250 2 1250 1 2000 1 1250 3 2000 1 2000 2 2000 2 2000 3 mJ cm UV Fluence, samples reported Results from GC/MS analyses of DBT and other compounds in DBT and Post-biodegradation test solutions exposed solutions test and Post-biodegradation in DBT and other compounds of DBT GC/MS analyses from Results applicable; na: not Test Solution DBT DBT DBT DBT DBT DBT DBT DBT a DBT DBT DBT DBT DBT DBT DBT DBT DBT DBT DBT DBT DBT DBT DBT DBT DBT DBT DBT DBT DBT DBT DBT DBT DBT DBT DBT DBT DBT DBT D.1. Table 5.2, 5.3, 5.4, and 5.5). (Figures UV light. to

212 (µ ) RR na na na na na na na na na na na na na na 2675 . 0.0431 RR 0.0111 RR 0 2675 0.0000 RR 0.1609 RR 0.0000 RR 0.0000 RR 0.1065 RR 0.0168 RR 0.1232 RR 0.1810 RR 0.1776 RR Ͳ 1.5654 ln(µM) Ͳ 2.1396 ln(µM) Ͳ 1.3436 ln(µM) Ͳ 2.4968 ln(µM) Ͳ 1.4403 ln(µM) Ͳ 3.1199 ln(µM) Ͳ 3.5191 ln(µM) Ͳ 2.2657 ln(µM) Ͳ 2.7958 ln(µM) Ͳ 2.4693 ln(µM) Ͳ 2.1398 ln(µM) Ͳ 2.2954 ln(µM) fitting Unit kinetic Value used in M µM µ µM RR µ µM µM 0000 0000 2675 flask . . . 0.0000 0.0431 RR 0.0111 RR 0.0000 µM 0.0000 µM 0.0000 µM 0 0000 0 0 2675 0.0201 0.2090 µM 0.1177 µM 0.0000 RR 0.0179 µM 0.0000 µM 0.0000 µM 0.0000 0.1609 RR 0.2609 µM 0.0823 µM 0.0000 RR 0.0021 µM 0.0232 µM 0.2369 µM 0.0442 µM 0.0296 µM 0.0611 µM 0.0000 RR 0.1065 RR 0.1038 µM 0.0168 RR 0.0846 µM 0.1232 RR 0.1177 µM 0.1007 µM 0.1810 RR 0.1776 RR in or relative response (RR) Unit (µM) Concentration _ _ 0 0 0 0 0 0 0 0 0 na na na na na na na na na na na na 1.34 0.16 1.74 4.5800 analytical in sample (µM) Concentration 0 0 0 0 6966 8062 2559 2167 2167 1871 1107 1140 3657 3886 2045 1.50825 1070 2821 9161 4501 . 2294.4 869631 3.312 710769818394 2.222 143498 2129833 15.68 1314562 8.828 1825852 19.568 1144260 6.176 2147139 17.764 1695335 7.782 1416754 6.348 1205639 8.826 1019884 7.554 Response 76911.9521 156974.264 301731 9161 120549.3822 83750.55864 ene h hene p op hi enzot b benzothio y roxy d drox y y sulfoxide sulfoxide dihydroxybenzothiophene dih dihydroxybenzothiophene Ͳ Ͳ dihydroxybenzothiophene Ͳ dihydroxybenzothiophene Ͳ dihydroxybenzothiophene Ͳ dihydroxybenzothiophene Ͳ dihydroxybenzothiophene Ͳ dihydroxybenzothiophene Ͳ dihydroxybenzothiophene Ͳ dihydroxybenzothiophene Ͳ dihydroxybenzothiophene Ͳ dihydroxybenzothiophene 3 3 Ͳ dih , , DBT sulfoxide DBT sulfoxide 2 3 2 DBT DBT sulfoxide 2,3 DBT DBT 2,3 2,3 DBT sulfoxide 2,3 2,3 DBT DBT DBT sulfoxide 2,3 2,3 2,3 2,3 2 2,3 DBT sulfoxide DBT DBT DBT sulfoxide DBT sulfoxide DBT DBT DBT DBT sulfoxide DBT DBT DBT sulfoxide DBT DBT sulfoxide d ze i vat i er d d d n Underivatized Underivatized Underivatized U Underivatized Underivatized Underivatized Underivatized Underivatized Underivatized Underivatized Underivatized Underivatized Underivatized Underivatized Underivatized Underivatized Underivatized Underivatized Underivatized Underivatized Underivatized Underivatized Underivatized Underivatized Underivatized Underivatized Underivatized Underivatized Underivatized Underivatized Underivatized Underivatized Underivatized Underivatized Underivatized Underivatized Underivatized 2 3 3 Replicate Un/derivatized Compound Ͳ 2 0 0 1 0 3 0 2 0 1 0 3 500 3 500 2 500 3 500 1 500 2 500 1 1250 2000 1250 1 2000 1 2000 2 2000 3 1250 1 1250 2 1250 3 1250 2 1250 3 2000 1 2000 2 mJ cm UV Fluence, g DBT DBT Test Solution DBT DBT DBT DBT DBT Post Ͳ biodegradation 0 1 Post Ͳ biodegradation 1250 2 DBT DBT DBT DBT Post Ͳ biodegradation 0 2 Post Ͳ biodegradation 1250 3 DBT DBT DBT DBT DBT DBT DBT Post Ͳ biodegradation 0 3 Post Ͳ biodegradation 2000 1 DBT DBT DBT Post Ͳ biodegradation 500 1 Post Ͳ biodegradationPost Ͳ biodegradation 2000 2000 2 3 DBT DBT Post Ͳ biodegradation 500 2 Post Ͳ biodegradation 500 3 DBT Post Ͳ biodegradation 1250 1 DBT Table D.2. Continued. D.2. Table

213 µM na na na na na na na na na na na na na na na na na na na na na na na na na na 0941 . 0 0941 fitting Unit kinetic Value used in M µM µ µM µM µM µM RR µM 0.3953 µM 5 µM 063 9323 0941 flask . . . 0 0635 0 0 0941 0.9323 0.0065 0.0741 µM 0.0395 µM 0.0045 µM 0.0000 µM 0.0000 0.6080 µM 0.6080 µM 0.0043 µM 0.7011 µM 0.7037 µM 0.4872 µM 0.4872 µM 3.2539 RR 6.4837 RR 1.4834 RR 1.9562 8.8881 RR 0.3923 RR 1.9349 µM 1.9349 µM 0.0000 µM 1.8145 RR 0.2318 RR 2.6448 µM 2.6448 µM 0.1685 µM 0.1685 µM 0.7321 RR 0.1941 RR 1.9171 µM 1.9171 µM 0.4573 µM0.3953 0.4573 µM 0.0851 µM 0.0851 µM 0.8165 RR 0.1435 µM 0.1435 µM 1.7811 µM 1.7811 µM 9.4397 RR in or relative response (RR) Unit (µM) Concentration _ _ 0 0 0 na na na na na na na na na na na na 76 06 92 . . . 5.56 4 76 7 06 2.96 0.34 45.6 34.3 6.38 69 analytical in sample (µM) Concentration 23224 33427 21501 33427 69.92 36366 32716 35717 28861 0.484275 37220 52934 233903200540248 0.3256 52.58 52.78 44825 36.54 30522 83198 99800 13233 145.12 37079 15875 198.36 21408 12.64 21767 143.78 11020 64972 27552 29.649 10288 10.76 21367 133.58 358129 848531 106687 12150.8 Response 42638.85523 148918.2076 445714.3014 241914.0492 284463.0556 249121.9397 acid acid one acid acid acid acid acid acid acid acid acid acid acid lf sulfone sulfone y y p DBT sulfone DBT su DBT benzoic DBT sulfone DBT sulfone DBT sulfone DBT sulfone DBT sulfone benzoic 2 Ͳ hydroxybenzothiophene 2 Ͳ hydroxybenzothiophene DBT sulfone DBT sulfone DBT sulfone benzoic 2 Ͳ hydroxybenzothiophene 2 Ͳ hydroxybenzothiophene DBT sulfone 2 Ͳ hydroxybenzothiophene 2 Ͳ hydroxybenzothiophene 2 Ͳ hydroxybenzothiophene 2 Ͳ hydroxybenzothiophene benzoic DBT sulfone 2 Ͳ hydroxybenzothiophene benzoic benzoic 2 Ͳ hydroxybenzothiophene benzoic benzoic 2 Ͳ hydroxybenzothiophene benzoic benzoic benzoic benzoic 2 Ͳ hydroxybenzothiophene d ze i vat i er d d d n Underivatized U Underivatized Underivatized Underivatized Underivatized Underivatized Underivatized Underivatized Underivatized Underivatized Underivatized Underivatized Underivatized Underivatized Underivatized Underivatized Underivatized Underivatized Underivatized Underivatized Underivatized Underivatized Underivatized Underivatized Underivatized Underivatized Underivatized Underivatized Underivatized Underivatized Underivatized Underivatized Underivatized Underivatized Underivatized Underivatized Underivatized 2 3 3 Replicate Un/derivatized Compound Ͳ 2 0 1250 2000 mJ cm UV Fluence, on i at d radation 1250 3 g g egra d o bi biodegradation biodegradation biodegradation Ͳ Post Ͳ biodegradation 0 3 Test Solution Post Ͳ Post Post Ͳ biodegradation 2000 1 Post Ͳ biodegradation 500 2 Post Post Ͳ biodegradation 0 1 Post Ͳ biodegradation 1250 2 Post Ͳ biodegradation 0 1 Post Ͳ biodegradation 500 1 Post Ͳ biodegradation 500 2 Post Ͳ biodegradation 500 3 Post Ͳ biodegradation 2000 2 Post Ͳ biodegradationPost Ͳ biodegradation 500Post Ͳ biodegradation 1250Post Ͳ biode 1250 3 1 2 Post Ͳ biodegradation 1250 1 Post Ͳ biodegradation 2000 3 Post Ͳ biodegradation 0 2 Post Ͳ biodegradation 1250 3 Post Ͳ biodegradationPost Ͳ biodegradation 0 500 3 1 Post Ͳ biodegradation 2000 1 Post Ͳ biodegradation 2000 2 Post Ͳ biodegradation 1250 2 Post Ͳ biodegradation 0 1 Post Ͳ biodegradation 500 2 Post Ͳ biodegradation 2000 3 Post Ͳ biodegradation 1250 3 Post Ͳ biodegradation 0 2 Post Ͳ biodegradation 500 3 Post Ͳ biodegradation 2000 1 Post Ͳ biodegradation 0 3 Post Ͳ biodegradation 2000 2 Post Ͳ biodegradation 500 1 Post Ͳ biodegradation 1250 1 Table D.2. Continued. D.2. Table

214 RR RR 3 na na na na na na na na na na na na na na na na na na na na na na na na 5 38 0490 . 1. 1 3853 0.1350 RR 0.6647 RR 1.4943 RR 6.1695 RR 0.7835 RR 8.5327 RR 9.0586 RR 13 fitting Unit kinetic Value used in RR RR µM µ RR RR 3 5 38 5830 0490 flask . . 1 3853 0 5830 1.3549 µM 1.8893 µM 1.9203 µM 1.2548 µM 0.9064 µM 0.9803 µM 0.6643 µM 0.7555 µM 0.9936 µM 1. 0.1350 0.6647 RR 4.0578 µM1.1026 µM 4.0578 RR 2.1288 RR 1.4943 RR 6.1695 0.7835 RR 5.1329 µM 1.1558 µM 8.5327 RR 3.0515 µM 0.6727 µM 9.0586 RR 1.2489 µM 0.7218 µM in 13 13.0490 RR 13.0490 RR 18.9883 µM 15.5965 µM 14.8883 µM 15.5090 µM 18.1073 µM 23.4606 µM 17.9415 RR 17.9415 RR 13.8156 RR 13.8156 RR or relative response (RR) Unit (µM) Concentration _ _ na na na na na na na na na na na na na 722 . 43 722 74.5200 analytical in sample (µM) Concentration 739 . 334431 365420 433545 101.62 461709426954383296 1424.12 1169.74 49.82 347131456501428092344142 141.7 335623 144.02 94.10625 435775 67.98 73.52 1116.62 363310388612 56.66 412081 3917056 8109436 304.34 4369453 82.698 3555822 384.97 4067330 86.682 7360216 228.86 4332407 1,163.18 570357848244764125048 1,358.05 1,759.54 50.46 5569825 93.67 3291421 54.136 58128.705 Response 1245757 1245757.739 27896.04287 340466.4306 24264.71537 282891.0006 2819475.644 3155829.039 364607.5823 ene h hene dione Ͳ Ͳ dione Ͳ dione Ͳ dione Ͳ dione Ͳ dione Ͳ dione Ͳ dione Ͳ dione Ͳ dione Ͳ dione Ͳ dione p 3 op , 2 3 hi Ͳ Ͳ 2,3 Ͳ 2,3 Ͳ 2,3 Ͳ 2,3 Ͳ 2,3 Ͳ 2,3 Ͳ 2,3 Ͳ 2,3 Ͳ 2,3 Ͳ 2,3 Ͳ 2,3 enzot b benzothio y y y p roxy d drox y y Ͳ dihydroxybenzothiophene Ͳ dihydroxybenzothiophene Ͳ dihydroxybenzothiophene Ͳ dihydroxybenzothiophene Ͳ dihydroxybenzothiophene Ͳ dihydroxybenzothiophene Ͳ dihydroxybenzothiophene Ͳ dihydroxybenzothiophene Ͳ dihydroxybenzothiophene Ͳ dihydroxybenzothiophene Ͳ dihydroxybenzothiophene Ͳ dihydroxybenzothiophene hydroxybenzothiophene hydroxybenzothiophene h Ͳ , 3 Ͳ h 3 3 benzothiophene 3 Ͳ hydroxybenzothiophene 3 Ͳ hydroxybenzothiophene 3 Ͳ hydroxybenzothiophene benzothiophene 3 Ͳ hydroxybenzothiophene benzothiophene 2,3 2,3 2,3 2,3 2,3 2,3 2,3 2,3 2,3 2,3 2,3 2,3 3 Ͳ hydroxybenzothiophene 3 Ͳ hydroxybenzothiophene 3 Ͳ hydroxybenzothiophene benzothiophene benzothiophene 3 Ͳ hydroxybenzothiophene benzothiophene benzothiophene benzothiophene benzothiophene benzothiophene 3 Ͳ hydroxybenzothiophene 3 Ͳ hydroxybenzothiophene benzothiophene benzothiophene d ze i vat i er d d d n Underivatized U Underivatized Underivatized Underivatized Underivatized Underivatized Underivatized Underivatized Underivatized Underivatized Underivatized Underivatized Underivatized Underivatized Underivatized Underivatized Underivatized Underivatized Underivatized Underivatized Underivatized Underivatized Underivatized Underivatized Underivatized Underivatized Underivatized Underivatized Underivatized Underivatized Underivatized Underivatized Underivatized Underivatized Underivatized Underivatized Underivatized 2 3 3 Replicate Un/derivatized Compound Ͳ 2 0 1250 2000 mJ cm UV Fluence, on i at d radation 1250 3 g g egra d o bi biodegradation biodegradation biodegradation Ͳ Post Ͳ biodegradation 0 3 Post Ͳ biodegradationPost Ͳ biodegradation 1250 2000 3 1 Test Solution Post Ͳ Post Post Ͳ biodegradation 2000 1 Post Ͳ biodegradation 500 2 Post Post Ͳ biodegradation 0 1 Post Ͳ biodegradation 1250 2 Post Ͳ biodegradationPost Ͳ biodegradationPost Ͳ biodegradation 0Post Ͳ biodegradation 0 500Post Ͳ biodegradation 500Post Ͳ biodegradation 500 2 1250 3 1 2 Post Ͳ biodegradation 3 1 Post Ͳ biodegradation 2000 2000 2 3 Post Ͳ biodegradation 0 1 Post Ͳ biodegradationPost Ͳ biodegradation 2000Post Ͳ biodegradation 0 0 3 1 2 Post Ͳ biodegradation 500 3 Post Ͳ biodegradationPost Ͳ biodegradation 500 500 1 2 Post Ͳ biodegradation 2000 2 Post Ͳ biodegradation 0 3 Post Ͳ biodegradation 1250 1 Post Ͳ biodegradationPost Ͳ biodegradation 1250Post Ͳ biodegradation 1250 2000 2 3 1 Post Ͳ biodegradation 500Post Ͳ biode 3 Post Ͳ biodegradation 500 1 Post Ͳ biodegradation 2000 2 Post Ͳ biodegradationPost Ͳ biodegradation 1250 1250 1 2 Table D.2. Continued. D.2. Table

215 na na na na na na na na na na na na na na na na na na na na na na na na na na na na na na na na na na na na na na fitting Unit kinetic Value used in RR RR RR RR RR 03 7 0 2151 1499 flask . . . 0 0703 0 0 1499 1.0125 0.2137 RR 9.6620 RR 0.5147 0.2784 RR 2.0208 RR 0.2151 RR 0.0616 RR 0.1101 RR 0.0433 RR 0.3664 RR 2.5929 RR 2.8732 RR 0.0228 RR 0.4209 RR 3.2429 RR 0.9959 RR 0.0226 RR 0.0158 RR 2.3351 RR 2.1189 RR 0.5838 RR 0.9231 RR 0.0568 RR 2.8342 RR 2.0005 RR 0.1221 RR 0.3311 RR 1.5262 RR 0.0297 RR 0.2845 RR 0.3427 RR in 15.0535 RR 13.3781 RR or relative response (RR) Unit (µM) Concentration _ _ na na na na na na na na na na na na na na na na na na na na na na na na na na na na na na na na na na na na na analytical in sample (µM) Concentration 12 . 9824 8664 7507 68430 87308 51933 74484 27766 1341.3 1038.5 . . 7872.2 345748 487865 654655 455809 13267.8 45667.2 15180.1 20535 20535.12 684226.4 Response 157751.703 10340.7373 16969 87308 82392 51933 70604.97708 922412.3876 97002.39959 807.6793266 25094.81542 15941.08341 231385.7329 222923.0665 18079.92639 305038.3512 18782.24229 52579.46292 531716.4314 353061.8654 e d de y y h e ld a b carbaldehyde carbaldehyde Ͳ car one Ͳ 3 3 3 Ͳ 3 carbaldehyde Ͳ Ͳ 3 carbaldehyde Ͳ 3 carbaldehyde Ͳ 3 carbaldehyde Ͳ 3 carbaldehyde Ͳ 3 carbaldehyde Ͳ 3 carbaldehyde Ͳ 3 carbaldehyde Ͳ 3 carbaldehyde Ͳ 3 carbaldehyde 2 Ͳ Ͳ 2 one Ͳ 2 one Ͳ 2 one Ͳ 2 one Ͳ 2 one Ͳ 2 one Ͳ 2 one Ͳ 2 one Ͳ 2 one Ͳ 2 one Ͳ 2 one ene h hene Ͳ 3 carbaldeh p op hi enzot b benzothio y roxy d drox y y hydroxybenzothiophene hydroxybenzothiophene h hydroxybenzothiophen Ͳ Ͳ 2 Ͳ h DBT sulfoxide 2 2 3 2 Ͳ hydroxybenzothiophene 2 Ͳ hydroxybenzothiophene 2 Ͳ hydroxybenzothiophene 3 Ͳ hydroxybenzothiophen DBT sulfoxide DBT sulfoxide 3 Ͳ hydroxybenzothiophen DBT sulfoxide DBT sulfoxide DBT sulfoxide DBT sulfoxide 3 Ͳ hydroxybenzothiophen DBT sulfoxide 2 Ͳ hydroxybenzothiophene 2 Ͳ hydroxybenzothiophene 3 Ͳ hydroxybenzothiophen DBT sulfoxide 2 Ͳ hydroxybenzothiophene 3 Ͳ hydroxybenzothiophen DBT sulfoxide 2 Ͳ hydroxybenzothiophene 3 Ͳ hydroxybenzothiophen 3 Ͳ hydroxybenzothiophen 3 Ͳ hydroxybenzothiophen 3 Ͳ hydroxybenzothiophen 3 Ͳ hydroxybenzothiophen DBT sulfoxide 2 Ͳ hydroxybenzothiophene 3 Ͳ hydroxybenzothiophen DBT sulfoxide 2 Ͳ hydroxybenzothiophene 2 Ͳ hydroxybenzothiophene d ze i vat i er d d d n Underivatized U Underivatized Underivatized Underivatized Underivatized Underivatized Underivatized Underivatized Underivatized Underivatized Underivatized Underivatized Underivatized Underivatized Underivatized Underivatized Underivatized Underivatized Underivatized Underivatized Underivatized Underivatized Underivatized Underivatized Underivatized Underivatized Underivatized Underivatized Underivatized Underivatized Underivatized Underivatized Underivatized Underivatized Underivatized Underivatized Underivatized 2 3 3 Replicate Un/derivatized Compound Ͳ 2 0 1250 2000 mJ cm UV Fluence, on i at d radation 1250 3 g g egra d o bi biodegradation biodegradation biodegradation Ͳ Post Ͳ biodegradation 0 3 Post Ͳ biodegradation 1250 3 Test Solution Post Ͳ Post Post Ͳ biodegradation 2000 1 Post Ͳ biodegradation 500 2 Post Post Ͳ biodegradation 0 1 Post Ͳ biodegradation 1250 2 Post Ͳ biodegradation 0 2 Post Ͳ biodegradation 0 1 Post Ͳ biodegradation 500 3 Post Ͳ biodegradationPost Ͳ biodegradation 2000 2000 1 2 Post Ͳ biodegradation 1250 1 Post Ͳ biodegradation 0 3 Post Ͳ biodegradation 500 1 Post Ͳ biodegradation 2000 2 Post Ͳ biodegradation 2000 3 Post Ͳ biodegradation 1250 2 Post Ͳ biodegradation 500 1 Post Ͳ biodegradation 2000 3 Post Ͳ biodegradation 1250 3 Post Ͳ biodegradation 500 2 Post Ͳ biodegradation 500 2 Post Ͳ biodegradation 0 1 Post Ͳ biodegradation 2000 1 Post Ͳ biodegradation 0 2 Post Ͳ biodegradation 2000 2 Post Ͳ biodegradation 500 3 Post Ͳ biodegradation 500 3 Post Ͳ biodegradation 0 3 Post Ͳ biodegradation 500 1 Post Ͳ biodegradation 1250 1 Post Ͳ biodegradation 1250 1 Post Ͳ biodegradation 1250 2 Post Ͳ biode Table D.2. Continued. D.2. Table

216 ) ) M µM ( (µ n ln(µM) l ln(µM) na na na na na na na na na na na na 3208 3770 . 1 3208 2 1.3726 RR 1.5465 RR 1.5150 RR 1.4561 RR 1.1796 RR 1.5559 RR 1.3078 RR 1.8317 RR 1.7364 RR 1.6008 RR 1.3143 RR 1.8378 RR Ͳ 1. Ͳ 1.5082 ln(µM) Ͳ 1.1161 ln(µM) Ͳ 0.6045 ln(µM) Ͳ 0.1837 ln(µM) Ͳ 0.6017 ln(µM) Ͳ 0.1297 ln(µM) Ͳ 0.6426 ln(µM) fitting Unit kinetic Value used in M 2.3770 ln µM µ µM µM 2669 3923 7721 flask . . . 0 2669 5 3923 0.2213 µM 1.0492 µM 0.0480 ln(µM) 4.1355 µM 0.3276 µM 1.3726 RR 1.5465 RR 0.5463 µM 0.8322 µM 3.7627 µM 1.5150 RR 0.5479 µM 0.8783 µM 2.2043 µM 1.4561 RR 0.5259 µM 1.4291 µM 1.6235 µM 1.5435 µM 4.8693 µM 1.1796 RR 1.5559 RR 1.0517 µM 1.2808 µM 4.0245 µM 1.3078 RR 1.8317 RR 2.2635 µM 1.7364 RR 1.6008 RR 1.3143 RR 1.8378 RR in 10.7721 10 14.4210 µM14.4290 µM 2.6687 ln(µM) 2.6692 ln(µM) or relative response (RR) Unit (µM) Concentration _ _ na na na na na na na na na na na na 91 42 . . 019 . 20 019 807 404 42 analytical in sample (µM) Concentration 9807 27949 16.5975 20503 24.57 84766 41.092 65930 39.443 49155 115.76 27122 96.06 110595 807.91 110595 252259 213234 78.69 290206 310.16 120165 40.98 169421 62.415 284553 282.2 463073 228477 65.876 143703 165.32 113665 107.18 366952 121.76 424585 123411 1,081.58 158557 1,082.18 181106 78.88 317551 301.84 933250 883297 215653 169.76 605914 1089577 1095343 1107000 4223983 1178783 365.2 1146251 1022356 1089612 Response acid acid acid acid acid acid acid acid acid acid acid acid y carboxylic carboxylic carboxylic carboxylic carboxylic carboxylic carboxylic carboxylic carboxylic carboxylic carboxylic carboxylic acid acid acid acid acid acid acid acid acid acid acid acid acid p o go g di n i o hi Thioindigo T Thioindigo thiosalicylic Thioindi Thioindigo Thioindigo thiosalicylic benzothiophene benzothiophene Thioindigo Thioindigo Thioindigo thiosalicylic benzothiophene benzothiophene Thioindigo Thioindigo thiosalicylic benzothiophene Thioindigo thiosalicylic thiosalicylic benzothiophene Thioindigo Thioindigo thiosalicylic thiosalicylic thiosalicylic thiosalicylic benzothiophene benzothiophene thiosalicylic thiosalicylic benzothiophene benzothiophene benzothiophene benzothiophene d ze d i vat i er d n Underivatized U Underivatized Derivatized Underivatized Underivatized Underivatized Derivatized Derivatized Derivatized Underivatized Underivatized Underivatized Derivatized Derivatized Derivatized Underivatized Underivatized Derivatized Derivatized Underivatized Derivatized Derivatized Derivatized Underivatized Underivatized Derivatized Derivatized Derivatized Derivatized Derivatized Derivatized Derivatized Derivatized Derivatized Derivatized Derivatized Derivatized 2 3 3 Replicate Un/derivatized Compound Ͳ 2 0 1250 2000 mJ cm UV Fluence, on i at d radation 1250 3 g g egra d o bi biodegradation biodegradation biodegradation Ͳ Test Solution Post Ͳ Post Ͳ biodegradation 0Post 3 Post Ͳ biodegradation 2000 1 Post Ͳ biodegradation 500 2 Post Post Ͳ biodegradation 0 1 Post Ͳ biodegradation 1250 2 Post Ͳ biodegradation 0 1 Post Ͳ biodegradation 500 1 Post Ͳ biodegradation 2000 2 Post Ͳ biodegradation 500 3 Post Ͳ biodegradation 0 2 Post Ͳ biodegradation 1250 3 Post Ͳ biodegradation 500 2 Post Ͳ biodegradation 2000 3 Post Ͳ biodegradation 1250 1 Post Ͳ biodegradation 2000 1 Post Ͳ biodegradation 500 3 Post Ͳ biodegradation 0 1 Post Ͳ biodegradation 1250 2 Post Ͳ biodegradation 0 3 Post Ͳ biodegradation 1250 1 Post Ͳ biodegradationPost Ͳ biode 1250 2 Post Ͳ biodegradation 0 2 Post Ͳ biodegradation 1250 3 Post Ͳ biodegradation 2000 1 Post Ͳ biodegradation 2000 2 Post Ͳ biodegradation 500 1 Post Ͳ biodegradation 2000 2 Post Ͳ biodegradation 0 3 Post Ͳ biodegradation 500 1 Post Ͳ biodegradation 500 2 Post Ͳ biodegradation 2000 3 Post Ͳ biodegradation 500 3 Post Ͳ biodegradation 1250 1 Table D.2. Continued. D.2. Table

217 ) ) RR RR ( ( () n ln(RR) l ln(RR) 1 na na na na na na na na na na na na 3 4 1018 0 . . 0 0 0431 1.2028 ln(RR) 0.7321 ln(RR) 0.2088 ln(RR) 0.7757 ln(RR) 0.2025 ln(RR) Ͳ 0.1018 ln Ͳ 1.5812 ln(RR) Ͳ 0.3609 ln(RR) Ͳ 1.5482 ln(RR) Ͳ 2.8214 ln(RR) Ͳ 0.1523 ln(RR) Ͳ 0.2250 ln(RR) Ͳ 0.1876 ln(RR) Ͳ 0.5352 ln(RR) Ͳ 3.2202 ln(RR) Ͳ 0.5243 ln(RR) Ͳ 3.2695 ln(RR) Ͳ 0.4819 ln(RR) Ͳ 0.1141 ln(RR) Ͳ 1.1552 ln(RR) Ͳ 0.0794 ln(RR) Ͳ 0.6683 ln(RR) Ͳ 0.1833 ln(RR) fitting Unit kinetic Value used in RR RR RR RR RR RR 441 RR 0 9032 0677 flask . . 1 0441 0 0 0677 0.9032 RR 3.3295 RR 0.2057 RR 1. 2.0795 RR 0.2126 RR 1.2323 RR 0.6971 RR 0.4915 RR 2.1722 RR 0.0595 RR 0.8587 RR 0.7985 RR 0.8289 RR 0.5855 RR 0.0399 RR 0.5277 RR 0.5920 RR 0.0380 RR 0.6176 RR 1.2245 RR 0.8921 RR 0.0200 RR 0.3150 RR 0.0400 0.9237 RR 0.0152 RR 0.0000 RR 0.5126 RR 0.0064 RR 0.0114 0.0397 RR 0.8325 RR 0.0532 0.3133 RR in or relative response (RR) Unit (µM) Concentration _ _ na na na na na na na na na na na na na na na na na na na na na na na na na na na na na na na na na na na na na analytical in sample (µM) Concentration 43630 27693 97832 19181 20299 39233 20426 27442 17200 19560 20906 21516 74721 19305 30488 93284 96231 793768 276066 276066 317961 240436 681620 591497 621875 206805 808301 569756 765781 100883 177189 370691 846789 589653 106032 196600 3249826 Response id acid acid acid acid acid acid acid acid acid acid acid acid acid c ac li lic y oxy b car dicarboxylic di dicarboxylic / Ͳ Ͳ dicarboxylic Ͳ dicarboxylic Ͳ dicarboxylic Ͳ dicarboxylic Ͳ dicarboxylic Ͳ dicarboxylic Ͳ dicarboxylic Ͳ dicarboxylic Ͳ dicarboxylic Ͳ dicarboxylic 3 3 Ͳ dicarbox , , m/z m/z m/z m/z m/z m/z m/z m/z m/z m/z m/z m/z 2 2 3 2 Ͳ Ͳ 2,3 Ͳ 2,3 Ͳ 2,3 Ͳ 2,3 Ͳ 2,3 Ͳ 2,3 Ͳ 2,3 Ͳ 2,3 Ͳ 2,3 Ͳ 2,3 acid acid acid acid acid acid acid acid acid acid acid acid acid ene h hene Ͳ 2 p M+ 284 M+ 284 M+ 284 M+ 284 M+ 284 M+ 284 M+ 284 M+ 284 M+ 284 M+ 284 M+ 284 M+ 284 op hi enzot benzothiophene b benzothiophene Dithiosalicylic benzothio benzothiophene benzothiophene Dithiosalicylic Unknown Unknown Unknown Unknown benzothiophene Unknown benzothiophene benzothiophene Unknown Dithiosalicylic Unknown Unknown Unknown benzothiophene benzothiophene Unknown Dithiosalicylic Unknown Unknown benzothiophene Dithiosalicylic Dithiosalicylic Dithiosalicylic benzothiophene Dithiosalicylic Dithiosalicylic benzothiophene Dithiosalicylic Dithiosalicylic Dithiosalicylic d d ze i vat i er Derivatized D Derivatized Derivatized Derivatized Derivatized Derivatized Derivatized Underivatized Underivatized Underivatized Underivatized Derivatized Underivatized Derivatized Derivatized Underivatized Derivatized Underivatized Underivatized Underivatized Derivatized Derivatized Underivatized Derivatized Underivatized Underivatized Derivatized Derivatized Derivatized Derivatized Derivatized Derivatized Derivatized Derivatized Derivatized Derivatized Derivatized 2 3 3 Replicate Un/derivatized Compound Ͳ 2 0 1250 2000 mJ cm UV Fluence, on i at d radation 1250 3 g g egra d o bi biodegradation biodegradation biodegradation Ͳ Test Solution Post Ͳ Post Ͳ biodegradation 0Post 3 Post Ͳ biodegradation 2000 1 Post Ͳ biodegradation 500 2 Post Post Ͳ biodegradation 0 1 Post Ͳ biodegradation 1250 2 Post Ͳ biodegradation 0 2 Post Ͳ biodegradation 1250 3 Post Ͳ biodegradation 0 1 Post Ͳ biodegradation 0 3 Post Ͳ biodegradation 500 1 Post Ͳ biodegradation 2000 2 Post Ͳ biodegradation 2000 1 Post Ͳ biodegradation 500 3 Post Ͳ biodegradation 500 1 Post Ͳ biodegradation 2000 2 Post Ͳ biodegradation 500 2 Post Ͳ biodegradation 500 2 Post Ͳ biodegradation 2000 3 Post Ͳ biodegradation 2000 3 Post Ͳ biodegradation 1250 1 Post Ͳ biodegradation 500 3 Post Ͳ biodegradation 1250 1 Post Ͳ biodegradation 500 3 Post Ͳ biodegradation 0 1 Post Ͳ biodegradation 1250 2 Post Ͳ biodegradation 1250 3 Post Ͳ biodegradation 1250 1 Post Ͳ biodegradation 0 2 Post Ͳ biodegradation 2000 1 Post Ͳ biodegradation 1250 2 Post Ͳ biodegradation 0 3 Post Ͳ biodegradation 500 1 Post Ͳ biodegradation 2000 2 Post Ͳ biode Table D.2. Continued. D.2. Table

218 na na na na na na na na na na na na na na na na na na na na na na na na na na na na na na na na na na na na na na fitting Unit kinetic Value used in M µM µM µ µM µM µ µM µM µM µM µM µM µM µM µM µM µM µM µM µM µM µM µM µM µM µM µM µM µM µM µM µM µM µM µM µM µM µM flask in or relative response (RR) Unit (µM) Concentration _ _ 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 analytical in sample (µM) Concentration 1789 4548 26391 13104 22968 95468 30971 45853 624254 549781 638641 730225 136262 729182 161605 749240 786734 867323 330433 793784 708271 808144 348381 760247 305661 194799 713581 241417 660121 227847 829030 430583 723223 1128086 2714847 1062065 Response ) ) d) ar d d) d standard) standard) standard) standard) standard) standard) standard stan standard) standard) standard) standard) standard) standard) standard) standard) standard) standard) standard) standard) standard) standard) standard) standard) standard) standard) standard) standard) standard) standard) standard) standard) standard) standard) standard) standard) standard) standard) standard) l nterna internal ( l (i ( (internal (internal ( (internal (internal (internal (internal (internal (internal (internal (internal (internal (internal (internal (internal (internal (internal (internal (internal (internal (internal (internal (internal (internal (internal (internal (internal (internal (internal (internal (internal (internal (internal (internal (internal (internal (internal (internal l o h t h hthol h h l p p naphthol naphthol naphthol Ͳ nap Ͳ 2 Ͳ naphthol 2 2 2 d ze i vat i er d d d n Underivatized 2 Ͳ naphthol Underivatized 2 Ͳ naphthol Underivatized U Underivatized Underivatized Underivatized 2 Ͳ naphthol Underivatized 2 Ͳ naphthol Underivatized 2 Ͳ naphthol Underivatized 2 Ͳ naphthol Underivatized 2 Ͳ naphthol Underivatized 2 Ͳ na Underivatized 2 Ͳ naphthol Underivatized 2 Ͳ naphthol Derivatized 2 Ͳ naphthol Derivatized 2 Ͳ naphthol Underivatized 2 Ͳ naphthol Underivatized 2 Ͳ naphthol Derivatized 2 Ͳ naphthol Derivatized 2 Ͳ naphthol Underivatized 2 Ͳ naphthol Underivatized 2 Ͳ naphthol Derivatized 2 Ͳ naphthol Derivatized 2 Ͳ naphthol Underivatized 2 Ͳ naphthol Underivatized 2 Ͳ naphthol Derivatized 2 Ͳ naphthol Derivatized 2 Ͳ naphthol Underivatized 2 Ͳ naphthol Underivatized 2 Ͳ naphthol Derivatized 2 Ͳ naphthol Derivatized Underivatized 2 Ͳ naphthol Underivatized 2 Ͳ naphthol Derivatized 2 Ͳ naphthol Underivatized 2 Ͳ naphthol Underivatized 2 Ͳ naphthol Derivatized 2 Ͳ naphthol 2 3 3 Replicate Un/derivatized Compound Ͳ 2 0 3 0 1 0 500 4 500 5 500 6 1250 2000 1250 1 1250 2 1250 3 2000 1 2000 2 2000 3 mJ cm UV Fluence, g biodegradation Ͳ DBT DBT DBT DBT DBT DBT DBT Test Solution DBT DBT DBT Post Ͳ biodegradation 500 2 Post Post Ͳ biodegradation 0 1 Post Ͳ biodegradation 1250 2 DBT Post Ͳ biodegradation 500 3 Post Ͳ biodegradation 0 2 Post Ͳ biodegradation 1250 3 DBT Post Ͳ biodegradation 1250 1 Post Ͳ biodegradation 0 3 Post Ͳ biodegradation 2000 1 Post Ͳ biodegradation 0 1 Post Ͳ biodegradation 1250 2 Post Ͳ biodegradation 500 1 Post Ͳ biodegradation 2000 2 Post Ͳ biodegradation 0 2 Post Ͳ biodegradation 1250 3 Post Ͳ biodegradation 500 2 Post Ͳ biodegradation 2000 3 Post Ͳ biodegradation 0 3 Post Ͳ biodegradation 2000 1 Post Ͳ biodegradation 500 3 Post Ͳ biodegradation 500 1 Post Ͳ biodegradation 2000 2 Post Ͳ biodegradation 1250 1 DBT Table D.2. Continued. D.2. Table

219 Table D.2. Cardiac deformity scores for Fundulus embryos exposed to Control, DBT and Post-biodegradation solutions treated with UV light (Figure 5.6).

UVfluence, CardiacDeformityScoresat7dpostͲfertilizationfor Average TestSolution mJcmͲ2 Replicate 10embryos Score Mortality Control 0 1 000000a 000 0 0 0% 500 1 000000000 0 0 0% 1250 1 000000000 0 0 0% 2000 1 000000000 0 0 0% DBT 0 1 000000000 0 0 0% 500 1 000000000 0 0 0% 1250 1 0000000db 00 0 10% 2000 1 000000000 0 0 0% PostͲbiodegradation 0 1 222221211 2 1.7 0% 500 1 222222222 1 1.9 0% 1250 1 22d22d222 2 2 20% 2000 1 222222222 2 2 0% Control 0 2 000000000 0 0.0 0% 500 2 0000000d0 0 0.0 10% 1250 2 000000000 0 0.0 0% 2000 2 000000000 0 0.0 0% DBT 0 2 ac 00000000 0 0.0 0% 500 2 001000000 0 0.1 0% 1250 2 000000000 0 0.0 0% 2000 2 00000000d 0 0.0 10% PostͲbiodegradation 0 2 d 11212211 1 1.3 10% 500 2 1 d 2 d d 2 1 2 1 2 1.6 30% 1250 2 d 2122d222 2 1.9 20% 2000 2 2 d d d 2 2 d 2 2 d 2.0 50% Control 0 3 d 00000000 0 0.0 10% 500 3 000000000 0 0.0 0% 1250 3 000000000 0 0.0 0% 2000 3 000000000 0 0.0 0% DBT 0 3 000210000 0 0.3 0% 500 3 000000200 0 0.2 0% 1250 3 100011000 0 0.3 0% 2000 3 001010000 1 0.3 0% PostͲbiodegradation 0 3 122122112 2 1.6 0% 500 3 121112211 2 1.4 0% 1250 3 222212222 1 1.8 0% 2000 3 222122222 2 1.9 0% abrainhemorrage bdead cembryohad2hearts,removedfromanalysis

220 Table D.3. Inhibition of luminescence in Vibrio fischeri exposed to Control, DBT and Post-biodegradation solutions treated with UV light (Figure 5.6).

UV Initial Final Fluence, Luminescence Luminescence Luminescence TestSolution mJcmͲ2 Replicate Units Units Inhibition,% Testcontrol 0 1 30501 93717 0.00 Testcontrol 0 2 30449 101275 0.00 Testcontrol 0 3 30378 103766 0.00 Control 0 1 33501 108717 0.60 Control 0 2 31449 101275 1.37 Control 0 3 33378 108766 0.19 Control 500 1 34119 114541 0.00 Control 500 2 34334 118515 0.00 Control 500 3 32525 115540 0.00 Control 1250 1 31375 108204 0.00 Control 1250 2 32098 110256 0.00 Control 1250 3 30765 106994 0.00 Control 2000 1 33147 111241 0.00 Control 2000 2 33747 110082 0. 09 Control 2000 3 33043 116443 0.00 DBT 0 1 32354 81776 22.58 DBT 0 2 31003 75790 25.12 DBT 0 3 32952 81804 23.96 DBT 500 1 34114 84006 24.58 DBT 500 2 33430 81843 25.01 DBT 500 3 33490 82246 24.78 DBT 1250 1 34422 86986 22.60 DBT 1250 2 34243 87006 22.18 DBT 1250 3 32600 86670 18.57 DBT 2000 1 30259 69953 29.19 DBT 2000 2 31919 74786 28.24 DBT 2000 3 32292 73720 30.08 PostͲbiodegradation 0 1 30505 74150 38.26 PostͲbiodegradation 0 2 32270 75313 40.7240.72 PostͲbiodegradation 0 3 32117 75659 40.17 PostͲbiodegradation 500 1 33035 75234 42.15 PostͲbiodegradation 500 2 32048 69945 44.57 PostͲbiodegradation 500 3 29902 70932 39.75 PostͲbiodegradation 1250 1 29911 72664 38.29 PostͲbiodegradation 1250 2 31199 79496 35.28 PostͲbiodegradation 1250 3 30298 78069 34.55 PtPostͲbibiodegradation d d ti 2000 1 31613 83969 32.5332 53 PostͲbiodegradation 2000 2 32533 82516 35.58 PostͲbiodegradation 2000 3 30962 87989 27.82

221 References

Abed, R.M., B. Zein, A. Al-Thukair and D. De Beer. 2007. Phylogenetic diversity and activity of aerobic heterotrophic bacteria from a hypersaline oil-polluted microbial mat. Syst Appl Microbiol 30: 319-330.

Ahtiainen, J., R. Valo, M. Jarvinen and A. Joutti. 2002. Microbial toxicity tests and chemical analysis as monitoring parameters at composting of creosote-contaminated soil. Ecotox Environ Safe 53: 323-329.

Aitken, M.D. and T.C. Long. 2004. Biotransformation, biodegradation and bioremediation of polycyclic aromatic hydrocarbons. In Soil biology, volume 2: Biodegradation and bioremediation, 83-124. Heidelberg, Germany: Springer-Verlag.

Arezi, B., W. Xing, J. Sorge and H. Hogrefe. 2003. Amplification efficiency of thermostable DNA polymerases. Anal Biochem 321: 226-235.

Arfsten, D.P., D.J. Schaeffer and D.C. Mulveny. 1996. The effects of near ultraviolet ra- diation on the toxic effects of polycyclic aromatic hydrocarbons in animals and plants: A review. Ecotox Environ Safe 33: 1-24.

Ashelford, K.E., A.J. Weightman and J.C. Fry. 2002. Primrose: A computer program for generating and estimating the phylogenetic range of 16S rRNA oligonucleotide probes and primers in conjunction with the RDP-II database. Nucleic Acids Res 30: 3481-3489.

ATSDR. 1995. Toxicological profile for polycyclic aromatic hydrocarbons. Atlanta, GA: U.S. Department of Health and Human Services, Public Health Service.

Bach, Q.D., S.J. Kim, S.C. Choi and Y.S. Oh. 2005. Enhancing the intrinsic bioremediation of PAH-contaminated anoxic estuarine sediments with biostimulating agents. J Microbiol 43: 319-324.

Barnsley, E.A. 1988. Metabolism of 2,6-dimethylnaphthalene by Flavobacteria. Appl Environ Microbiol 54: 428-433.

Bauer, J.E. and D.G. Capone. 1985. Degradation and mineralization of the polycyclic aromatic-hydrocarbons anthracene and naphthalene in intertidal marine-sediments. Appl Environ Microbiol 50: 81-90.

222 Belkin, S., M. Stieber, A. Tiehm, F.H. Frimmel, A. Abeliovich, P. Werner and S. Ulitzur. 1994. Toxicity and genotoxicity enhancement during polycyclic aromatic hydrocarbons’ biodegradation. Environ Toxicol Water Qual 9: 303-309.

Bertini, I., M.A. Cremonini, S. Ferretti, I. Lozzi, C. Luchinat and M.S. Viezzoli. 1996. Arene hydroxylases: Metalloenzymes catalysing dioxygenation of aromatic compounds. Coordin Chem Rev 151: 145-160.

Bianchi, D., A. Bosetti, D. Cidaria, A. Bernardi, I. Gagliardi and P. D’amico. 1997. Oxida- tion of polycyclic aromatic heterocycles byPseudomonas fluorescens TTC1. Appl Microbiol Biotechnol. 47: 596-599.

Bobinger, S., F. Traulsen and J.T. Andersson. 1999. Dibenzothiophene in crude oils: Prod- ucts from the photochemical degradation. Polycyclic Aromatic Compounds 14-15: 253-263.

Bohonos, N., T.W. Chou and R.J. Spanggord. 1977. Some observations on biodegradation of pollutants in aquatic systems. Jpn J Antibiot 30 Suppl: 275-285.

Boonchan, S., M.L. Britz and G.A. Stanley. 1998. Surfactant-enhanced biodegradation of high molecular weight polycyclic aromatic hydrocarbons byStenotrophomonas maltophilia. Biotechnol Bioengineering 59: 482-494.

Bouchez, M., D. Blanchet and J.-P. Vandecasteele. 1995. Degradation of polycyclic aromatic hydrocarbons by pure strains and by defined strain associations: Inhibition phenomena and cometabolism. Appl Microbiol Biotechnol 43: 156-164.

Bressler, D.C. and P.M. Fedorak. 2000. Bacterial metabolism of fluorene, dibenzofuran, dibenzothiophene, and carbazole. Can J Microbiol 46: 397-409.

Bressler, D.C. and P.M. Fedorak. 2001a. Identification of disulfides from the biodegradation of dibenzothiophene. Appl Environ Microb 67: 5084-5093.

Bressler, D.C. and P.M. Fedorak. 2001b. Purification, stability, and mineralization of 3-hydroxy-2-formylbenzothiophene, a metabolite of dibenzothiophene. Appl Environ Microb 67: 821-826.

Bressler, D.C., J.A. Norman and P.M. Fedorak. 1998. Ring cleavage of sulfur heterocycles: How does it happen? Biodegradation 8: 297-311.

223 Brooks, L.R., T.J. Hughes, L.D. Claxton, B. Austern, R. Brenner and F. Kremer. 1998. Bioas- say-directed fractionation and chemical identification of mutagens in bioremedi- ated soils. Environ Hlth Persp 106: 1435-1440.

Bugg, T.D.H. 2003. Dioxygenase enzymes: Catalytic mechanisms and chemical models. Tetrahedron 59: 7075-7101.

Bulich, A.A., Greene, M.W., Underwood, S.R., 1992. Measurement of soil and sediment toxicity to bioluminescence bacteria when in direct contact for a fixed time period. In: Water Environmental Federation 65th Annual Conference and Exposi- tion, New Orleans, LO, pp. 53–63.

Bunz, P.V. and A.M. Cook. 1993. Dibenzofuran 4,4a-dioxygenase from Sphingomonas sp. Strain RW1: Angular dioxygenation by a three-component enzyme system. J Bacteriol 175: 6467-6475.

Carreira, L.A. Sparc On-line Calculator. http://ibmlc2.chem.uga.edu/sparc/index.cfm.

Castle, D.M., M.T. Montgomery and D.L. Kirchman. 2006. Effects of naphthalene on microbial community composition in the Delaware estuary. FEMS Microbiol Ecol 56: 55-63.

Cerniglia, C.E. 1993. Biodegradation of polycyclic aromatic hydrocarbons. Biodegradation 3: 351-368.

Cerniglia, C.E., J.C. Morgan and D.T. Gibson. 1979. Bacterial and fungal oxidation of dibenzofuran. Biochem J 180: 175-185.

Chamberlin, J.F. 2005. Combined microbial and photochemical degradation of dibenzothiophene, ix, 99 leaves: Duke University, 2005.

Chang, Y., J. Stephen, A. Richter, A. Venosa, J. Brüggemann, S. Macnaughton, G. Kow- alchuk, J. Haines, E. Kline and D. White. 2000. Phylogenetic analysis of aerobic freshwater and marine enrichment cultures efficient in hydrocarbon degradation: Effect of profiling method. J Microbiol Methods 40: 19-31.

Cho, J.C. and S.J. Giovannoni. 2004. Cultivation and growth characteristics of a diverse group of oligotrophic marine Gammaproteobacteria. Appl Environ Microbiol 70: 432-440.

224 Chui, L.W., R. King, P. Lu, K. Manninen and J. Sim. 2004. Evaluation of four DNA extraction methods for the detection of Mycobacterium avium subsp paratuberculosis by polymerase chain reaction. Diagn Micr Infec Dis 48: 39-45.

Cole, J., B. Chai, R. Farris, Q. Wang, A. Kulam-Syed-Mohideen, D. Mcgarrell, A. Bandela, E. Cardenas, G. Garrity and J. Tiedje. 2007. The Ribosomal Database Project (RDP- II): Introducing MyRDP Space and quality controlled public data. Nucleic Acids Res 35: D169-172.

Cole, J., B. Chai, R. Farris, Q. Wang, S. Kulam, D. Mcgarrell, G. Garrity and J. Tiedje. 2005. The Ribosomal Database Project (RDP-II): Sequences and tools for high-throughput rRNA analysis. Nucleic Acids Res 33: D294-296.

Colwell, R. K. 2005. EstimateS: Statistical estimation of species richness and shared- spe cies from samples. Version 7.5. User’s Guide and application published at: http:// purl.oclc.org/estimates.

Constanti, M., A. Bordons and J. Giralt. 1994. Degradation of dibenzothiophene by Pseudomonas putida. Lett Appl Microbiol 18: 107-111.

Cooper, R.C. 1963. Photosynthetic bacteria in waste treatment. Devel Indust Microbiol 4: 95-103.

Mackay, W.Y. Shiu and K.C. Ma. 1992. Illustrated handbook of physical-chemical properties and environmental fate for organic chemicals: Boca Ratón, Florida, CRC Press Inc.

Da Silva, M.L., R. Kamath and P.J. Alvarez. 2006. Effect of simulated rhizodeposition on the relative abundance of polynuclear aromatic hydrocarbon catabolic genes in a contaminated soil. Environ Toxicol Chem 25: 386-391.

David, B. and P. Boule. 1993. Phototransformation of hydrophobic pollutants in aqueous medium I- PAHs adsorbed on silica. Chemosphere 26: 1617-1631.

Donnelly, K.C., H.J. Huebner, L.D. Claxton, J.A. Calvin, G.A. Vos, L. Cizmas and L.Y. He. 2005. Biodegradation of simple chemical mixtures in soil. Environ Toxicol Chemy 24: 2839-2845.

Doyle, E., L. Muckian, A.M. Hickey and N. Clipson. 2008. Microbial PAH degradation. Adv Appl Microbiol 65:27-66.

225 Duarte, G.F., A.S. Rosado, L. Seldin, W. De Araujo and J.D. Van Elsas. 2001. Analysis of bacterial community structure in sulfurous-oil-containing soils and detection of species carrying dibenzothiophene desulfurization (dsz) genes. Appl Environ Microbiol 67: 1052-1062.

Eaton, R.W. and J.D. Nitterauer. 1994. Biotransformation of benzothiophene by isopropy- lbenzene-degrading bacteria. J Bacteriol. 176: 3997-4002.

Edwards, N.T. 1983. Polycyclic aromatic-hydrocarbons (PAHs) in the terrestrial environment - a review. J Environ Qual 12: 427-441.

Eriksson, M., E. Sodersten, Z. Yu, G. Dalhammar and W.W. Mohn. 2003. Degradation of polycyclic aromatic hydrocarbons at low temperature under aerobic and nitrate- reducing conditions in enrichment cultures from northern soils. Appl Environ Microb 69: 275-284.

Evanko, C.R. and D.A. Dzombak. 1999. Surface complexation modeling of organic acid sorption to goethite. J Coll Int Sci 214: 189-206.

Fanning, A.T., G.R. Bickford and T.D. Roberts. 1972. Preparation and diazotization of thioanthranilic acid chemistry of 4-oxo-3,4-dihydro-3,1,2-benzothiadiazine. J Am Chem Soc 94: 8505-&.

Fedorak, P.M. and D. Grbić-Galić. 1991. Aerobic microbial cometabolism of benzothiophene and 3-methylbenzothiophene. Appl Environ Microb 57: 932-940.

Felsenstein, J. 2005. Phylip (phylogeny inference package) version 3.6. Department of Genome Sciences, University of Washington, Seattle: Distributed by the author.

Fierer, N., J.A. Jackson, R. Vilgalys and R.B. Jackson. 2005. Assessment of soil microbial community structure by use of taxon-specific quantitative PCR assays. Appl Envi- ron Microbiol 71: 4117-4120.

Finkel’stein, Z.I., B.P. Baskunov, L.N. Vavilova and L.A. Golovleva. 1997. Microbial transformation of dibenzothiophene and 4,6-dimethyldibenzothiophene. Microbiol- ogy (Moscow)(Translation of Mikrobiologiya) 66: 402-407.

Fortnagel, P., H. Harms, R.M. Wittich, S. Krohn, H. Meyer, V. Sinnwell, H. Wilkes and W. Francke. 1990. Metabolism of dibenzofuran by Pseudomonas sp. Strain HH69 and the mixed culture HH27. Appl Environ Microb 56: 1148-1156.

226 Frassinetti, S., L. Setti, A. Corti, P. Farrinelli, P. Montevecchi and G. Vallini. 1998. Biodeg- radation of dibenzothiophene by a nodulating isolate of Rhizobium meliloti. Can J Microbiol 44: 289-297.

Gai, Z.H., B. Yu, L. Li, Y. Wang, C.Q. Ma, J.H. Feng, Z.X. Deng and P. Xu. 2007. Cometabolic degradation of dibenzofuran and dibenzothiophene by a newly isolated carbazole-degrading Sphingomonas sp strain. Appl Environ Microb 73: 2832-2838.

Genthner, B.R.S., G.T. Townsend, S.E. Lantz and J.G. Mueller. 1997. Persistence of polycyclic aromatic hydrocarbon components of creosote under anaerobic enrichment conditions. Arch Environ Contam Toxicol 32: 99-105.

Gibson, D.T. 1999. Beijerinckia sp strain B1: A strain by any other name. J Ind Microbiol Biotechnol 23: 284-293.

Gray, K.A., G.T. Mrachko and C.H. Squires. 2003. Biodesulfurization of fossil fuels. Curr Opin Microbiol 6: 229-235.

Gray, K.A., O.S. Pogrebinsky, G.T. Mrachko, L. Xi, D.J. Monticello and C.H. Squires. 1996. Molecular mechanisms of biocatalytic desulfurization of fossil fuels. Nat Biotech- nol 14: 1705-1709.

Gray, J.P. and R.P. Herwig. 1996. Phylogenetic analysis of the bacterial communities in marine sediments. Appl Environ Microb 62: 4049-4059.

Grifoll, M., S.A. Selifonov and P.J. Chapman. 1994. Evidence for a novel pathway in the degradation of fluorene byPseudomonas sp. Strain f274. Appl Environ Microb 60: 2438-2449.

Guan, X.H., C. Shang and G.H. Chen. 2006. ATR-FTIR investigation of the role of phenolic groups in the interaction of some nom model compounds with aluminum hydrox- ide. Chemosphere 65: 2074-2081.

Guescini, M., D. Sisti, M. Rocchi, L. Stocchi and V. Stocchi. 2008. A new real-time PCR method to overcome significant quantitative inaccuracy due to slight amplification inhibition. BMC Bioinformatics 9: 326.

Guieysse, B. and G. Viklund. 2005. Sequential UV-biological degradation of polycyclic aromatic hydrocarbons in two-phases partitioning bioreactors. Chemosphere 59: 369-376.

227 Guieysse, B., G. Viklund, A.C. Toes and B. Mattiasson. 2004. Combined UV-biological degradation of PAHs. Chemosphere 55: 1493-1499.

Habe, H. and T. Omori. 2003. Genetics of polycyclic aromatic hydrocarbon metabolism in diverse aerobic bacteria. Biosci Biotechnol Biochem 67: 225-243.

Harms, H., H. Wilkes, R.-M. Wittich and P. Fortnagel. 1995. Metabolism of hydroxydiben- zofurans, methoxydibenzofurans, acetoxydibenzofurans, and nitrodibenzofurans by Sphingomonas sp. Strain HH69. Appl Environ Microb 61: 2499-2505.

Hirano, S.I., F. Kitauchi, M. Haruki, T. Imanaka, M. Morikawa and S. Kanaya. 2004. Isola- tion and characterization of Xanthobacter polyaromaticivorans sp nov 127w that degrades polycyclic and heterocyclic aromatic compounds under extremely low oxygen conditions. Biosci Biotechnol Biochem 68: 557-564.

Holt, J., S. Hothem, H. Howerton, R. Larson and R. Sanford. 2005. 9,10-phenanthrenequinone photoautocatalyzes its formation from phenanthrene, and inhibits biodegradation of naphthalene. J Environ Qual 34: 462-468.

Hristova, K.R., C.M. Lutenegger and K.M. Scow. 2001. Detection and quantification of methyl tert-butyl ether-degrading strain pm1 by real-time Taqman PCR. Appl Environ Microb 67: 5154-5160.

Hazardous Substances Database (HSDB), Bethesda, MD, National library of medicine; last revision date 8/30/2006; cited 1/23/2008. Dibenzothiophene; hazardous substances databank number: 7409. Available from: Http://toxnet.Nlm.Nih.Gov/ cgi-bin/sis/htmlgen?Hsdb.

Imhoff, J. 2003. The Chromatiaceae. In The Prokaryotes: An evolving electronic re- source for the microbiological community, 3rd edition, release 3.13, May 12, 2003, Springer-Verlag, New York, http://link.Springer-ny.Com/link/service/ books/10125/.

SAS Inc., S.I. 2007. Jmp, version 7. Cary, NC: SAS Institute Inc.

Incardona, J.P., T.K. Collier and N.L. Scholz. 2004. Defects in cardiac function precede morphological abnormalities in fish embryos exposed to polycyclic aromatic- hy drocarbons. Toxicol Appl Pharmacol 196: 191-205.

228 Ishii, Y., J. Konishi, H. Okada, K. Hirasawa, T. Onaka and M. Suzuki. 2000. Operon structure and functional analysis of the genes encoding thermophilic desulfurizing enzymes of Paenibacillus sp a11-2. Biochem Bioph Res Co 270: 81-88.

Iyer, R.P., L.R. Phillips, W. Egan, J.B. Regan and S.L. Beaucage. 1990. The automated synthesis of sulfur-containing oligodeoxyribonucleotides using 3h-1,2-benzodithiol-3 -one 1,1-dioxide as a sulfur-transfer reagent. J Org Chem 55: 4693-4699.

Jackson, P.M. and C.J. Moody. 1990. Diels-alder reactions of 2,3-dimethylenepyrrole analogs - a new synthesis of indoles. J Chem Soc-Perkin Trans. 1: 2156-2158.

Jonsson, S., Y. Persson, S. Frankki, S. Lundstedt, B. Van Bavel, P. Haglund and M. Tysklind. 2006. Comparison of Fenton’s reagent and ozone oxidation of polycyclic aromatic hydrocarbons in aged contaminated soils. J Soil Sediment 6: 208-214.

Kasai, Y., H. Kishira and S. Harayama. 2002. Bacteria belonging to the genus Cycloclasti- cus play a primary role in the degradation of aromatic hydrocarbons released in a marine environment. Appl Environ Microbiol 68: 5625-5633.

Kazunga, C. and M.D. Aitken. 2000. Products from the incomplete metabolism of pyrene by polycyclic aromatic hydrocarbon-degrading bacteria. Appl Environ Microb 66: 1917-1922.

Keith, L.H. and W.A. Telliard. 1979. Priority pollutants I-a perspective view. Environ Sci Technol 13: 416-423.

Kilbane, J.J., Ii and K. Jackowski. 1992. Biodesulfurization of water-soluble coal-derived material by Rhodococcus rhodochrous IGTS8. Biotechnol Bioengineer 40: 1107- 1114.

Kim, I.-K. and O.-J. Jung. 2002. Sonochemical reaction mechanism of a polycyclic aromatic sulfur hydrocarbon in aqueous phase. Bull Kor Chem Soc 23: 990-994.

Kirchman, D.L. 2002. The ecology of Cytophaga-Flavobacteria in aquatic environments. FEMS Microbiol Ecol 39: 91-100.

Kirimura, K., K. Harada, H. Iwasawa, T. Tanaka, Y. Iwasaki, T. Furuya, Y. Ishii and K. Kino. 2004. Identification and functional analysis of the genes encoding dibenzothiophene-desulfurizing enzymes from thermophilic bacteria. Appl Microbiol Bio- technol 65: 703-713.

229 Klappenbach, J., J. Dunbar and T. Schmidt. 2000. rRNA operon copy number reflects ecological strategies of bacteria. Appl Environ Microbiol 66: 1328-1333.

Knight, V.K., L.J. Kerkhof and M.M. Haggblom. 1999. Community analyses of sulfidogenic 2-bromophenol-dehalogenating and phenol-degrading microbial consortia. FEMS Microbiol. Ecol. 29: 137-147.

Kodama, K., S. Nakatani, K. Umehara, K. Shimizu, Y. Minoda and K. Yamada. 1970. Mi- crobial conversion of petro-sulfur compounds. III. Isolation and identification of products from dibenzothiophene. Agric Biol Chem 34: 1320-1324.

Kodama, K., K. Umehara, K. Shimizu, S. Nakatani, Y. Minoda and K. Yamada. 1973. Mi- crobial conversion of petrosulfur compounds. IV. Identification of microbial products from dibenzothiophene and its proposed oxidation pathway. Agric Biol Chem 37: 45-50.

Kropp, K.G., J.A. Goncalves, J.T. Andersson and P.M. Fedorak. 1994. Bacterial transformations of benzothiophene and methylbenzothiophenes. Environ Sci Technol 28: 1348-1356.

Kropp, K.G., J.T. Andersson and P.M. Fedorak. 1997. Bacterial transformations of 1,2,3,4- tetrahydrodibenzothiophene and dibenzothiophene. Appl Environ Microb 63: 3032-3042.

Kubista, M., J. Andrade, M. Bengtsson, A. Forootan, J. Jonák, K. Lind, R. Sindelka, R. Sjöback, B. Sjögreen, L. Strömbom, A. Ståhlberg and N. Zoric. 2006a. The real- time polymerase chain reaction. Mol Aspects Med 27: 95-125.

Kwon, K.K., H.S. Lee, S.H. Yang and S.J. Kim. 2005. Kordiimonas gwangyangensis gen. nov., sp nov., a marine bacterium isolated from marine sediments that forms a distinct phyletic lineageKordiimonadales ( ord. nov.) in the ‘Alphaproteobacteria’. Int J System Evol Microbiol 55: 2033-2037.

Laborde, A.L. and D.T. Gibson. 1977. Metabolism of dibenzothiophene by a Beijerinckia species. Appl Environ Microb 34: 783-790.

Labrenz, M., I. Brettar, R. Christen, S. Flavier, J. Bötel and M. Höfle. 2004. Development and application of a real-time PCR approach for quantification of uncultured- bac teria in the central Baltic Sea. Appl Environ Microbiol 70: 4971-4979.

230 Lalucat, J., A. Bennasar, R. Bosch, E. Garcia-Valdes and N.J. Palleroni. 2006. Biology of Pseudomonas stutzeri. Microbiol Mol Biol Rev 70: 510-547.

Lassen, P. and L. Carlsen. 1999. The effect of humic acids on the water solubility and water - organic carbon partitioning of fluorene and its NSO-heteroanalogs: carbazole, dibenzofuran, and dibenzothiophene. Chemosphere 38: 2959-2968.

Lee, K. 2006. P-hydroxylation reactions catalyzed by naphthalene dioxygenase. FEMS Microbiol Lett 255: 316-320.

Lehto, K.M., J.A. Puhakka and H. Lemmetyinen. 2003. Biodegradation of selected UV- irradiated and non-irradiated polycyclic aromatic hydrocarbons (PAHs). Biodegra- dation 14: 249-263.

Lewis, R.F. 1993. Site demonstration of slurry-phase biodegradation of PAH contaminated soil. Air and Waste 43: 503-508.

Liu, W. and D. Saint. 2002a. A new quantitative method of real time reverse transcription polymerase chain reaction assay based on simulation of polymerase chain reaction kinetics. Anal Biochem 302: 52-59.

Liu, W. and D. Saint. 2002b. Validation of a quantitative method for real time PCR kinetics. Biochem Biophys Res Commun 294: 347-353.

Liu, W.T., T.L. Marsh, H. Cheng and L.J. Forney. 1997. Characterization of microbial diversity by determining terminal restriction fragment length polymorphisms of genes encoding 16S rRNA. Appl Environ Microb 63: 4516-4522.

Lu, J., T. Nakajima-Kambe, T. Shigeno, A. Ohbo, N. Nomura and T. Nakahara. 1999. Bio- degradation of dibenzothiophene and 4,6-dimethyldibenzothiophene bySphin - gomonas paucimobilis strain TZS-7. J Biosci Bioengineer 88: 293-299.

Lundstedt, S., P. Haglund and L. Oeberg. 2003. Degradation and formation of polycyclic aromatic compounds during bioslurry treatment of an aged gasworks soil. Envi- ron Toxicol Chem 22: 1413-1420.

Luu-the, V., N. Paquet, E. Calvo and J. Cumps. 2005. Improved real-time RT-PCR method for high-throughput measurements using second derivative calculation and double correction. Biotechniques 38: 287-293.

231 Mallakin, A., B.J. Mcconkey, G.B. Miao, B. Mckibben, V. Snieckus, D.G. Dixon and B.M. Greenberg. 1999. Impacts of structural photomodification on the toxicity of environmental contaminants: anthracene photooxidation products. Ecotox Environ Safe 43: 204-212.

Matson, C.W., B.W. Clark, M.J. Jenny, C.R. Fleming, M.E. Hahn and R.T. Di Giulio. 2008. Development of the morpholino gene knockdown technique in Fundulus heteroclitus: A tool for studying molecular mechanisms in an established environmental model. Aquat Toxicol. 87: 289-295.

Mcconkey, B.J., C.L. Duxbury, D.G. Dixon and B.M. Greenberg. 1997. Toxicity of a PAH photooxidation product to the bacteriaPhotobacterium phosphoreum and the duckweed Lemna gibba: Effects of phenanthrene and its primary photoproduct, phenanthrenequinone. Environmental Toxicology and Chemistry 16: 892-899.

Mckibben, M. and W. Mcclelland. 1923. Production and reactions of 2-dithiobenzoyl. J Chem Soc 123: 170-173.

Meyer, S., S. Cartellieri and H. Steinhart. 1999. Simultaneous determination of PAHs, hetero-PAHs (N, S, O), and their degradation products in creosote-contaminated soils. Method development, validation, and application to hazardous waste sites. Anal Chem 71: 4023-4029.

Monticello, D.J., D. Bakker and W.R. Finnerty. 1985. Plasmid-mediated degradation of dibenzothiophene by Pseudomonas species. Appl Environ Microb 49: 756-760.

Mormile, M.R. and R.M. Atlas. 1988. Mineralization of the dibenzothiophene biodegradation products 3-hydroxy-2-formyl benzothiophene and dibenzothiophene sulfone. Appl Environ Microb 54: 3183-3184.

Moser, R. and U. Stahl. 2001. Insights into the genetic diversity of initial dioxygenases from PAH-degrading bacteria. Appl Microbiol Biotechnol 55: 609-618.

Mulligan, C.N. 2002. Environmental biotreatment. Technologies for air, water, soil and wastes. Government Institutes, Rockville, Maryland.

Munday, R. 1985. Toxicity of aromatic disulfides. II. Intra-erythrocytic hydrogen -per oxide formation and oxidative damage by aromatic disulfides. J Appl Toxicol 5: 409-413.

232 Muratova, A.Y., O.V. Turkovskaya, L.P. Antonyuk, O.E. Makarov, L.I. Pozdnyakova and V.V. Ignatov. 2005. Oil-oxidizing potential of associative rhizobacteria of the genus Azospirillum. Microbiol 74: 210-215.

Nadalig, T., N. Raymond, N.M. Gilewicz, H. Budzinski and J.C. Bertrand. 2002. Degrada- tion of phenanthrene, methylphenanthrenes and dibenzothiophene by aSphin - gomonas strain 2MPII. Appl Microbiol Biotechnol 59: 79-85.

Nadarajah, N., J. Van Hamme, J. Pannu, A. Singh and O. Ward. 2002. Enhanced transformation of polycyclic aromatic hydrocarbons using a combined Fenton’s reagent, microbial treatment and surfactants. Appl Microbiol Biotechnol 59: 540-544.

Nojiri, H., H. Habe and T. Omori. 2001. Bacterial degradation of aromatic compounds via angular dioxygenation. J Gen Appl Microbiol 47: 279-305.

Nojiri, H. and T. Omori. 2002. Molecular bases of aerobic bacterial degradation of diox- ins: Involvement of angular dioxygenation. Biosci Biotechnol Biochemy 66: 2001- 2016.

Ocampo-Duque, W., J. Sierra, N. Ferre-Huguet, M. Schuhmacher and J.L. Domingo. 2008. Estimating the environmental impact of micro-pollutants in the Low Ebro River (Spain): An approach based on screening toxicity with Vibrio fischeri. Chemo- sphere 72: 715-721.

Oldfield, C., O. Pogrebinsky, J. Simmonds, E.S. Olson and C.F. Kulpa. 1997. Elucidation of the metabolic pathway for dibenzothiophene desulfurization by Rhodococcus sp. strain IGTS8 (ATCC 53968). Microbiol 143: 2961-2973.

Oleszczuk, P. and S. Baran. 2003. Degradation of individual polycyclic aromatic hydrocarbons (PAHs) in soil polluted with aircraft fuel. Pol J Environ Stud 12: 431-437.

Olson, E.S., D.C. Stanley and J.R. Gallagher. 1993. Characterization of intermediates in the microbial desulfurization of dibenzothiophene. Energy & Fuels 7: 159-164.

Omori, T., L. Monna, Y. Saiki and T. Kodama. 1992. Desulfurization of dibenzothiophene by Corynebacterium sp. strain SY1. Appl Environ Microb 58: 911-915.

Page, R.D. 1996. Treeview: An application to display phylogenetic trees on personal com- puters. Comput Appl Biosci 12: 357-358.

233 Page, R.D.M. ed. 2000. Treeview—tree drawing software for Apple Macintosh and Win- dows. Http://taxonomy.Zoology.Gla.Ac.Uk/rod/treeview.Html.

Park, E.K., S.K. Mak, D. Kultz and B.D. Hammock. 2007. Evaluation of cytotoxicity attributed to thimerosal on murine and human kidney cells. J Toxicol Environ Health A 70: 2092-2095.

Penning, T.M., M.E. Burczynski, C.-F. Hung, K.D. Mccoull, N.T. Palackal and L.S. Tsuruda. 1999. Dihydrodiol dehydrogenases and polycyclic aromatic hydrocarbon activa- tion: Generation of reactive and redox active o-quinones. Chem Res Toxicol 12: 1-18.

Pfaffl, M. 2001. A new mathematical model for relative quantification in real-time RT- PCR. Nucleic Acids Res 29: e45.

Phillips, T.M., D. Liu, A.G. Seech, H. Lee and J.T. Trevors. 2000. Monitoring bioremediation in creosote-contaminated soils using chemical analysis and toxicity tests. J Ind Microbiol Biotechnol 24: 132-139.

Piza, F.F., P.I. Prado and G.P. Manfio. 2004. Investigation of bacterial diversity in Brazilian tropical estuarine sediments reveals high actinobacterial diversity. Antonie Van Leeuwenhoek 86: 317-328.

Potter, C.L., J.A. Glaser, L.W. Chang, J.R. Meier, M.A. Dosani and R.F. Herrmann. 1999. Degradation of polynuclear aromatic hydrocarbons under bench-scale compost conditions. Environ Sci Technol 33: 1717-1725.

R Language Team. 2005. Vienna, Austria: R Foundation for Statistical Computing.

Rainey, F., N. Ward-Rainey, P. Janssen, H. Hippe and E. Stackebrandt. 1996. Clostridium paradoxum DSM 7308t contains multiple 16S rRNA genes with heterogeneous intervening sequences. Microbiol 142: 2087-2095.

Rebrikov, D. and D. Trofimov. 2006. Real-time PCR: Approaches to data analysis (a review). Prikl Biokhim Mikrobiol 42: 520-528.

Reinecke, M.G., J.G. Newsom and L.J. Chen. 1981. Thermolysis of thiophenedicarboxylic acid anhydrides as a route to 5-membered hetarynes. J Am Chem Soc 103: 2760- 2769.

234 Resnick, S.M. and D.T. Gibson. 1996. Regio- and stereospecific oxidation of fluorene, dibenzofuran, and dibenzothiophene by naphthalene dioxygenase from Pseudomonas sp. strain NCIB 9816-4. Appl Environ Microb 62: 4073-4080.

Rhodes, S., A. Farwell, L.M. Hewitt, M. Mackinnon and D.G. Dixon. 2005. The effects of dimethylated and alkylated polycyclic aromatic hydrocarbons on the embryonic development of the Japanese medaka. Ecotoxicol Environ Saf 60: 247-258.

Ritz, C. and A. Spiess. 2008. qPCR: An r package for sigmoidal model selection in quantitative real-time polymerase chain reaction analysis. Bioinformatics 24: 1549- 1551.

Rutledge, R. 200a. Sigmoidal curve-fitting redefines quantitative real-time PCR with the prospective of developing automated high-throughput applications. Nucleic Acids Res 32: e178.

Rutledge, R. and D. Stewart. 2008. A kinetic-based sigmoidal model for the polymerase chain reaction and its application to high-capacity absolute quantitative real-time PCR. BMC Biotechnology 8.

Samanta, S.K., O.V. Singh and R.K. Jain. 2002. Polycyclic aromatic hydrocarbons: Environ- mental pollution and bioremediation. Trends Biotechnol 20: 243-248.

Sanchez, O., E. Diestra, I. Esteve and J. Mas. 2005. Molecular characterization of an oil- degrading cyanobacterial consortium. Microb Ecol 50: 580-588.

Schafer, E.W., Jr. and W.A. Bowles, Jr. 1985. Acute oral toxicity and repellency of 933 chemicals to house and deer mice. Arch Environ Contam Toxicol 14: 111-129.

Seo, J.-S., Y.-S. Keum, I.K. Cho and Q.X. Li. 2006. Degradation of dibenzothiophene and carbazole by Arthrobacter sp. P1-1. Int Biodeterior Biodegrad 58: 36-43.

Seymour, D.T., A.G. Verbeek, S.E. Hrudey and P.M. Fedorak. 1997. Acute toxicity and aqueous solubility of some condensed thiophenes and their microbial metabolites. Environ Toxicol Chem 16: 658-665.

Shemer, H. and K.G. Linden. 2007a. Aqueous photodegradation and toxicity of the polycyclic aromatic hydrocarbons fluorene, dibenzofuran, and dibenzothiophene. Wat Res 41: 853-861.

235 Shemer, H. and K.G. Linden. 2007b. Photolysis, oxidation and subsequent toxicity of a mixture of polycyclic aromatic hydrocarbons in natural waters. Journal of Photo- chem Photobiol A-Chem 187: 186-195.

Shu, Q. and N. Jiao. 2008. Different Planctomycetes diversity patterns in latitudinal surface seawater of the open sea and in sediment. J Microbiol 46: 154-159.

Singleton, D.R., M. Hunt, S.N. Powell, R. Frontera-Suau and M.D. Aitken. 2007. Stable-isotope probing with multiple growth substrates to determine substrate specificity of uncultivated bacteria. J Microbiol Meth 69: 180-187.

Singleton, D.R., R. Sangaiah, A. Gold, L.M. Ball and M.D. Aitken. 2006. Identification and quantification of uncultivatedProteobacteria associated with pyrene degradation in a bioreactor treating PAH-contaminated soil. Environ Microbiol 8: 1736-1745.

Smits, T.H.M., C. Devenoges, K. Szynalski, J. Maillard and C. Holliger. 2004. Development of a real-time PCR method for quantification of the three generaDehalobacter, Dehalococcoides, and Desulfitobacterium in microbial communities. J Microbiol Meth 57: 369-378.

Sobisch, T., H. Hess, H. Niebelschutz and U. Schmidt. 2000. Effect of additives on biodegradation of PAH in soils. Coll Surf A-Physicochem Engineer Asp 162: 1-14.

Spiess, A., C. Feig and C. Ritz. 2008. Highly accurate sigmoidal fitting of real-time PCR data by introducing a parameter for asymmetry. BMC Bioinformatics 9.

R Development Team. 2008a. R: A language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing. http://www.R-project. org.

Tichopad, A., M. Dilger, G. Schwarz and M. Pfaffl. 2003. Standardized determination of real-time PCR efficiency from a single reaction set-up. Nucl Acids Res 31: 6688- 6688.

Traulsen, F., J.T. Andersson and M.G. Ehrhardt. 1999. Acidic and non-acidic products from the photo-oxidation of the crude oil component dibenzothiophene dissolved in seawater. Analytica Chimica Acta 392: 19-28.

Trzesicka-Mlynarz, D. and O.P. Ward. 1995. Degradation of polycyclic aromatic hydrocarbons (PAHs) by a mixed culture and its component pure cultures, obtained from PAH-contaminated soil. Can J Microbiol 41: 470-476.

236 U.S. Environmental Protection Agency. 1993. Provisional guidance for quantitative risk assessment of polycyclic aromatic hydrocarbons. Epa/600/r-93/089. : U.S. Envi- ronmental Protection Agency, Washington, DC.

U.S. Environmental Protection Agency. 2001. Use of bioremediation at superfund sites. U.S. Epa 542-r-01-019.: Environmental Protection Agency, Washington, DC.

US Environmental Protection Agency. 2008. National priorities list. Http://www.Epa. Gov/superfund/sites/npl/index.Htm. van Afferden, M., D. Tappe, M. Beyer, H.G. Trueper and J. Klein. 1993. Biochemical mechanisms for the desulfurization of coal-relevant organic sulfur compounds. Fuel 72: 1635-1643.

Van Herwijnen, R., P. Wattiau, L. Bastiaens, L. Daal, L. Jonker, D. Springael, H.A.J. -Gov ers and J.R. Parsons. 2003. Elucidation of the metabolic pathway of fluorene and cometabolic pathways of phenanthrene, fluoranthene, anthracene and dibenzothiophene by Sphingomonas sp. LB126. Res Microbiol 154: 199-206.

Vasilenko, N.M., V.M. Garmash and V.A. Volodchenko. 1985. Toxicity of a series of thioin- digoid dyes. Gigiena i Sanitariya 8:91-92.

Vinas, M., J. Sabate, M.J. Espuny and A.M. Solanas. 2005a. Bacterial community dynamics and polycyclic aromatic hydrocarbon degradation during bioremediation of heavily creosote-contaminated soil. Appl Environ Microbiol 71: 7008-7018.

Vinas, M., J. Sabate, C. Guasp, J. Lalucat and A.M. Solanas. 2005b. Culture-dependent and -independent approaches establish the complexity of a PAH-degrading microbial consortium. Can J Microbiol 51: 897-909.

Wagner, M., R. Amann, H. Lemmer and K.H. Schleifer. 1993. Probing activated-sludge with oligonucleotides specific for proteobacteria - inadequacy of culture-dependent methods for describing microbial community structure. Appl Environ Microb 59: 1520-1525.

Wang, P. and S. Krawiec. 1994. Desulfurization of dibenzothiophene to 2-hydroxybiphenyl by some newly isolated bacterial strains. Arch Microbiol 161: 266-271.

Ward, D.M., R. Weller and M.M. Bateson. 1990. 16S rRNA sequences reveal numerous uncultured microorganisms in a natural community. Nature 345: 63-65.

237 Wassenberg, D.M., A.L. Nerlinger, L.P. Battle and R.T. Di Giulio. 2005. Effects of the polycyclic aromatic hydrocarbon heterocycles, carbazole and dibenzothiophene, on in vivo and in vitro CYP1A activity and polycyclic aromatic hydrocarbon-derived embryonic deformities. Environ Toxicol Chem 24: 2526-2532.

Weisburg, W., S. Barns, D. Pelletier and D. Lane. 1991a. 16S ribosomal DNA amplification for phylogenetic study. J Bacteriol 173: 697-703.

White, P.A. and L.D. Claxton. 2004. Mutagens in contaminated soil: A review. Mut Res- Rev Mut Res 567: 227-345.

Whiteley, A.S. and M.J. Bailey. 2000. Bacterial community structure and physiological state within an industrial phenol bioremediation system. Appl Environ Microbiol 66: 2400-2407.

Wilcke, W. 2000. Polycyclic aromatic hydrocarbons (PAHs) in soil - a review. J Plant Nutr Soil Sci 163: 229-248.

Wolffs, P., H. Grage, O. Hagberg and P. Rådström. 2004a. Impact of DNA polymerases and their buffer systems on quantitative real-time PAH. J Clin Microbiol 42: 408-411.

Yamada, K., Y. Minoda, K. Kodama, S. Nakatani and T. Akasaki. 1968. Microbial conversion of petrosulfur compounds. I. Isolation and identification of dibenzothiophene- utilizing bacteria. Agric Biol Chem 32: 840-845.

Yamazoe, A., O. Yagi and H. Oyaizu. 2004. Degradation of polycyclic aromatic hydrocarbons by a newly isolated dibenzofuran-utilizing Janibacter sp. strain YY-1. Appl Microbiol Biotechnol 65: 211-218.

Yu, H.T. 2002. Environmental carcinogenic polycyclic aromatic hydrocarbons: Photochem- istry and phototoxicity. J Environ Sci Heal C 20: 149-183.

238 Biography

I was born on March 27, 1971, in Chester County, Pennsylvania. I grew up in Oxford, Pennsylvania, graduating as valedictorian from Oxford Area High School in 1989. I pursued under- graduate study in ornamental horticulture and music composition at the University of Delaware, and graduated with a Bachelor of Science degree in 1994. While working toward my undergradu- ate degree, I assisted in soil science and environmental management research in the laboratory of Dr. J. Thomas Sims, who then offered me a graduate position in his lab. During my graduate studies at the University of Delaware, I explored the phytoremediation of lead-contaminated soils with and without the use of organic chelates to enhance lead solubility. This work was achieved with support from the DuPont Company. I graduated with a Master of Science degree from the University of Delaware in 1996, and published my work in the Journal of Environmental Quality.

After graduation, I continued as a research associate in Dr. Sims’s lab, working on lead remediation strategies and techniques for determining nitrogen status in wheat, among other projects. I also worked as a technical writer for Dr. Scott Cunningham at the DuPont Company, as- sisting in the preparation of book chapters and other manuscripts largely focused on remediation techniques. In 1998, I returned to graduate study at Penn State University and received an NSF fellowship in the university’s Root Biology Program. My work at Penn State focused on shikonins, dyes produced by the plant Lithospermum erythrorhizon (Boraginaceae). Opportunities at Penn State allowed me to study organic chemical structure analysis, which became crucial to the current research. As sometimes happens, however, life took an unexpected turn requiring me to forego further study at that time.

In 1999, I came to Duke University to work as a researcher and lab manager in Dharni Vasudevan’s environmental chemistry lab, where I studied interfacial interactions between polar/ ionogenic compounds and soil and mineral surfaces. In 2004, I transferred to Andrew Schuler’s biological engineering lab where I worked on PAH biodegradation. This position opened an opportunity to pursue doctoral research at Duke University, where I received a First-Year Engineering Fellowship from the Pratt School of Engineering. During my doctoral studies, I was co-advised by Drs. Schuler and Heather Stapleton, whose diverse experience and talents were invaluable to my cross-disciplinary project. Beyond the professional scientific arena, I am an avid distance runner, amateur musician and photographer, and enjoy life with my husband and furry family.

239