Distribution of Metabolic Characteristics Among Aerobic Soil Bacteria and Implications for Biotransformation of Organic and Metallic Wastes

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DISTRIBUTION OF METABOLIC CHARACTERISTICS AMONG AEROBIC SOIL BACTERIA AND IMPLICATIONS FOR BIOTRANSFORMATION OF ORGANIC AND METALLIC WASTES

FANGMEI ZHANG

Submitted in partial fulfillment of the requirements

For the degree of Doctor of Philosophy

Dissertation Advisor: Dr. Karen L. Skubal

Department of Civil Engineering

CASE WESTERN RESERVE UNIVERSITY

January, 2007

CASE WESTERN RESERVE UNIVERSITY

SCHOOL OF GRADUATE STUDIES

We hereby approve the dissertation of

______

candidate for the Ph.D. degree *.

(signed)______(chair of the committee)

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(date) ______

*We also certify that written approval has been obtained for any proprietary material contained therein.

TABLE OF CONTENTS

LIST OF TABLES……………………………………………………………...... v LIST OF FIGURES………………………………………………………………. vi ACKNOWLEDGEMENTS……………………………………………………… ix NOMENCLATURE……………………………………………………………… xi ABSTRACT……………………………………………………………...... xiv

CHAPTER 1. Introduction…………………………………………………… 1 1.1. Research hypothesis and significance of the work…………… 3 1.2. Experimental approach……………………………………….. 5 1.3. Chromium pollution: sources and chemistry……………………………………………………..... 6 1.4. Chromium uptake, transformation, and resistance by soil microorganisms……………………………………………...... 9 1.5. Microbial partitioning in soil and its implications for pollutant biotransformation……………………………………. 12 Cell partitioning and physiological properties……………….. 13 Abundance and activity of planktonic versus attached bacteria 13 Mechanisms of attachment………………………………….... 14 Solid surfaces and microbial attachment……………………... 16 Cell surface properties and microbial attachment…………..... 16 Cell structures and microbial attachment…………………….. 17 Biochemical stimulation of attachment………………………. 18 1.6. Oligotrophy, copiotrophy and bacterial attachment………… 18 CHAPTER 2. Isolation and Physiological Characterization of Microbial Communities and Isolates from Unsaturated Soil……………. 22 2. 1. Introduction…………………………………………………….. 22 2. 2. Materials and Methods………………………………………… 24 Soil sampling and characterization…………………………… 24 Adhesion-based extraction of soil microorganisms………….. 24 Isolation of dominant microbial populations………………… 25 Characterization of variably-attached microbial communities and isolates………………………………………………...... 27 MATH assays………………………………………………… 27 HIC and EIC………………………………………………….. 28 Colloid titrations……………………………………………… 29

i 2. 3. Results…………………………………………………...... 30 Soil characterization………………………………………….. 30 MATH assay for microbial elution fractions F1 and F3……... 31 Gram staining and catalase activity of colony isolates from variably-attached microbial fractions………………………… 33 Cell hydrophobicity and charge of colony isolates from variably-attached microbial fractions…….…….…….…….… 33 2. 4. Conclusions…….…….…….…….…….…….…….…….……. 37 CHAPTER 3. Growth of Soil Microbial Communities and Isolates on Organic Substrates…….…….…….…….…….…….…….…… 40 3. 1. Introduction…….…….…….…….…….…….…….…….……. 40 Substrate selection…….…….…….…….…….…….…….….. 41 Models of cell growth…….…….…….…….…….…….……. 42 3. 2. Materials and Methods…….…….…….…….…….…….……. 44 Microcosm preparation…….…….…….…….…….…….…… 44 Spectroscopic analysis…….…….…….…….…….…….……. 45 3. 3. Results…….…….…….…….…….…….…….…….…….…….. 45 Growth of microbial consortia on yeast extract as a limiting substrate…….…….…….…….…….…….…….…….……… 45 Growth of microbial isolates on yeast extract as a limiting substrate…….…….…….…….…….…….…….…….……… 47 Growth of microbial isolates on salicylic acid as a limiting substrate…….…….…….…….…….…….…….…….……… 49 Growth of isolate F12 on salicylic acid…….…….…….……. 53 Extent of salicylic acid transformation…….…….…….…….. 56 3. 4. Conclusions…….…….…….…….…….…….…….…….……… 57 CHAPTER 4. Effect of Chromium on the Growth of Microbial Communities and Isolates Derived from Soil…….…….…….. 60 4. 1. Introduction…….…….…….…….…….…….…….…….……. 60 4. 2. Materials and Methods…….…….…….…….…….…….……. 60 Experiments assessing the impact of chromium(VI) on microbial consortia…….…….…….…….…….…….…….… 60 Experiments assessing chromium(VI) impact on microbial isolates grown on yeast extract…….…….…….…….…….…. 62 Experiments assessing chromium(VI) impact on isolates grown in simulated comingled waste with salicylic acid……. 62 4. 3. Results…….…….…….…….…….…….…….…….…….…….. 62 Impact of Cr(VI) on biomass production by consortia F1 and F3 in yeast extract medium…….…….…….…….…….……. 62

ii Impact of Cr(VI) on the growth rate of consortia F1 and F3 in yeast extract medium…….…….…….…….…….…….……. 66 Impact of Cr(VI) on the death kinetics of consortia F1 and F3 in yeast extract medium…….…….…….…….…….…….….. 67 Degrees of inhibition by Cr(VI) to individual microbial isolates in yeast extract medium…….…….…….…….……… 69 Relationships between substrate affinity and Cr(VI) tolerance by microbial isolates in yeast extract medium…….…….……. 70 Impact of Cr(VI) on the lag phase of microbial isolates in yeast extract medium…….…….…….…….…….…….…….. 72 Chromium tolerance and cell surface properties of microbial isolates…….…….…….…….…….…….…….…….…….….. 75 Inhibition of isolates in simulated comingled waste…….…… 76 4. 4. Conclusions…….…….…….…….…….…….…….…….……… 77 CHAPTER 5. Spectroscopic Studies of Chromium Biotransformation and Uptake by Microbial Communities and Isolates…….…….…. 79 5. 1. Introduction…….…….…….…….…….…….…….…….……. 79 The use of XAFS for characterization of metals in environmental samples….…….…….…….…….…….…….… 80 5. 2. Materials and Methods…….…….…….…….…….…….……. 82 Biomass preparation…….…….…….…….…….…….……… 82 Metal uptake experiments…….…….…….…….…….…….… 82 X-ray analyses…….…….…….…….…….…….…….……… 85 Determination of biosorption kinetics…….…….…….……… 86 5. 3. Results…….…….…….…….…….…….…….…….…….…….. 87 Spectral signatures for chromium standards…….…….……… 87 XAFS determination of chromium reduction by microorganisms…….…….…….…….…….…….………….. 89 Normalization of chromium sorption to biomass…….……… 92 Chromium uptake after two hours of exposure- results of the XAFS study…….…….…….…….…….…….…….…….….. 96 Chromium sorption versus growth phase in the XAFS study... 97 Chromium sorption and cell surface properties in the XAFS study…….…….…….…….…….…….…….…….…….……. 97 Models of chromium biosorption kinetics…….…….…….…. 103 Chromium biosorption kinetics by microbial isolates in batch systems…….…….…….…….…….…….…….…….…….… 104 Equilibrium chromium sorption and cell surface properties…. 106 5. 4. Conclusions…….……….…….…….…….…….…….…….…… 111 CHAPTER 6. Summary and Recommendations…….…….…….…….……… 113

iii 6. 1. Summary….…….…….…….…….…….…….…….…….…….. 113 6. 2. Recommendations for future work….…….…….…….…….… 118 REFERENCES…….…….…….…….…….…….…….…….…….…….…….…. 119

LIST OF TABLES

Table 2.1. Media and resins used in HIC and EIC…….…….…….…….….. 29 Table 2.2. Biochemical and morphological characterization of five variably-attached microbial isolates eluted from soil…….……… 33 Table 2.3. Relative hydrophobicity and surface charge of five microbial isolates extracted using serial soil elution…….…….…….……... 34 Table 3.1. Monod growth parameters for microbial consortia and isolates grown on yeast extract at 19°C…….…….…….…….…….……. 49 Table 3.2. Kinetic parameters for isolate F12 on two substrates…….……… 55 Table 4.1. First-order death constants for stationary-phase cultures of consortia F1 and F3 exposed to hexavalent chromium…….……. 69 Table 4.2. Growth rates and lag phases of five microbial isolates in yeast extract medium with hexavalent chromium…….…….…….…… 73 Table 5.1. Microbial samples analyzed for chromium uptake and transformation using atomic absorption spectroscopy (AA) and X-ray absorption fine structure (XAFS) spectroscopy…….……. 85 Table 5.2. Chromium standards used to generate Cr(III) and Cr(VI) reference spectra for XAFS analyses…….…….…….…….……. 86 Table 5.3. Metal uptake in cultures incubated with 2 mM (approximately 100 mg/L) hexavalent or trivalent chromium for two hours……. 94 Table 5.4. Chromium biosorption at equilibrium and after 2 and 24 hours of incubation for four microbial isolates…….…….…….…….……. 109

LIST OF FIGURES

Figure 2.1. Relative hydrophobicity, based on the MATH assay, of variably- attached microbial fractions eluted from soil and grown to late exponential phase in yeast extract medium……………………… 32 Figure 2.2. Relative cell surface hydrophobicity of “loosely-attached” colony isolates F11, F12, and F13, and of “tightly-attached” colony isolates F31 and F32 …….…….…….…….…….……… 35 Figure 2.3. Relative cell surface charge of “loosely-attached” colony isolates F11, F12, and F13, and of “tightly-attached” colony isolates F31 and F32 …….…….…….…….…….…….…….…. 36 Figure 2.4. Total negative surface charge of cells from “loosely-attached” colony isolates F11, F12, and F13 and from “tightly-attached” colony isolates F31 and F32, as measured by colloid titration…. 36 Figure 3.1. Two pathways of aerobic salicylate biodegradation..….…….…. 42 Figure 3.2. Growth of two microbial consortia on yeast extract as a limiting carbon source…….…….…….…….…….…….…….…….……. 46 Figure 3.3. Growth of five microbial isolates on yeast extract as a limiting carbon source…….…….…….…….…….…….…….…….……. 48 Figure 3.4. Growth dependence of isolate F11 on salicylic acid concentration…….…….…….…….…….…….…….…….……. 51 Figure 3.5. Growth dependence of isolate F12 on salicylic acid concentration…….…….…….…….…….…….…….…….……. 51 Figure 3.6. Growth dependence of isolate F13 on salicylic acid concentration…….…….…….…….…….…….…….…….……. 52 Figure 3.7. Growth dependence of isolate F32 on salicylic acid concentration…….…….…….…….…….…….…….…….……. 52 Figure 3.8. Maximum culture density of the five isolates when grown in 40 mg/L salicylic acid…….…….…………….…….…….…….… 53 Figure 3.9. Monod growth curve of isolate F12 with salicylic acid as the sole carbon source…….…….…….…….…….…….…….……. 54 Figure 3.10. Lineweaver-Burk plot of the growth of isolate F12 on salicylic acid…….…….…….…….…….…….…….…….…….…….….. 55 Figure 3.11. Growth data for isolate F12 fit to the modified Monod kinetic model…….…….…….…….…….…….…….…….…….…….… 55 Figure 3.12. Transformation of salicylic acid by isolate F12…….…….…….. 56

vi Figure 4.1. Final biomass concentration versus hexavalent chromium concentration for consortia F1 and F3 grown on 100 mg/L yeast extract and exposed to chromium during the entire two-week incubation period…….…….…….…….…….…….……….……. 64 Figure 4.2. Decrease in biomass production by consortia F1 and F3 with respect to hexavalent chromium concentration…….…….……… 65 Figure 4.3. First-order toxicity model for the impact of 30, 60 and 90 mg/L Cr(VI) on the net biomass production of microbial consortia F1 and F3…….…….…….…….…….…….…….…….…….……… 65 Figure 4.4. Growth rate of consortia F1 and F3 in the presence of low concentrations of hexavalent chromium…….…….…….…….… 66 Figure 4.5. Normalized growth rate µ versus hexavalent chromium concentration (0 - 15 mg/L) for microbial consortia F1 and F3 in sucrose medium…….…….…….…….…….…….…….…….… 67 Figure 4.6. Decrease in viable cell counts X for stationary-phase cultures of consortia F1 and F3 that had been grown in 200 mg/L yeast extract medium and were subsequently exposed to 0, 5 or 25 mg/L Cr6+.…….…….…….…….…….…….…….…….…….… 68 Figure 4.7. Growth rates of five microbial isolates in 100 mg/L yeast extract medium with hexavalent chromium at 0, 5, 20, 50, 100, and 200 mg/L…….…….…….…….…….…….…….…….…….…….… 72 Figure 4.8. Growth rates of five microbial isolates in 500 mg/L yeast extract medium with hexavalent chromium at 0, 5, 20, 50, 100, and 200 mg/L…….…….…….…….…….…….…….…….…….…….… 73 Figure 4.9. Relationships between the Monod affinity constant and chromium tolerance (expressed as µ/µo) for microbial isolates F11, F12, F13, F31, and F32…….…….…….…….…….…….… 74

Figure 4.10. Chromium tolerance (µ/µo) versus the lag phase observed before the onset of growth of microbial isolates F11, F12, F13, F31, and F32…….…….…….…….…….…….…….…….…….……. 75

Figure 4.11. Chromium tolerance (µ/µo) versus negative cell surface charge of microbial isolates as determined by colloid titration…….…… 76

Figure 4.12. Chromium tolerance (µ/µo) versus negative cell surface charge of microbial isolates as determined by electrostatic interaction chromatography. …….…….…….…….…….…….…….…….… 76 Figure 5.1. Graphical representation of the experimental analysis of chromium adsorption and transformation by microbial consortia and isolates.. …….…….…….…….…….…….…….…….……. 84 Figure 5.2. Chromium fluorescence XAFS spectra (fluorescence intensity in arbitrary units versus incident x-ray photon energy) for a number of trivalent and hexavalent chromium standards. …….…….….. 89

vii Figure 5.3. Cr fluorescence XAFS spectra (fluorescence intensity in arbitrary units versus incident x-ray photon energy) for chromium sorbed to cells from consortia F1 and F3 and isolates F12, F13, F31, and F32…….…….…….…….…….…….……… 91 Figure 5.4. Chromium fluorescence XAFS spectra (fluorescence intensity in arbitrary units versus incident x-ray photon energy) for trivalent chromium standard, hexavalent chromium standard, and microbial samples containing cell-sorbed chromium………….... 92 Figure 5.5. Relationships between protein mass and dry cell mass for the microbial consortia and isolates tested…….…….…….…….….. 93 Figure 5.6. A comparison of chromium sorbed to cell biomass versus that remaining in solution following two hours of incubation with 100 mg/L chromium…….…….…….…….……………………. 98 Figure 5.7. A comparison of sorbed and aqueous chromium following two hours of incubation with 100 mg/L hexavalent or trivalent Cr and consortia F1 and F3 and isolates F12, F13, F31, and F32 in exponential and stationary phase………………………………... 99 Figure 5.8. Chromium partitioning between cells and supernatant for microbial consortia and isolates…….…….…….…….…….…… 100 Figure 5.9. Chromium biosorption with respect to growth phase for four bacterial isolates and two consortia following two hours of exposure to 100 mg/L trivalent or hexavalent chromium at pH 7. Cr(III) and Cr(VI) were initially present as Cr(NO3)3 and K2Cr2O7, respectively. …….…….…….…….…….…….……… 101 Figure 5.10. Chromium biosorption by microbial isolates F12, F13, F31, and F32 with respect to cell surface charge and relative hydrophobicity…….…….…….…….…….…….…….…….…. 102 Figure 5.11. Chromium sorption by microbial isolate F11 represented by a pseudo-second order model…….…….…….…….…….………. 106 Figure 5.12. Chromium sorption by microbial isolate F12 represented by a pseudo-second order model…….…….…….…….…….…….… 107 Figure 5.13. Chromium sorption by microbial isolate F13 represented by a pseudo-second order model…….…….…….…….…….…….… 107 Figure 5.14. Chromium sorption by microbial isolate F31 represented by a pseudo-second order model…….…….…….…….…….…….… 108 Figure 5.15. Chromium sorption by microbial isolate F32 represented by a pseudo-second order model…….…….…….…….…….………. 108 Figure 5.16. pseudo-second order chromium sorption model parameters for the five variably-attached microbial isolates F11, F12, F13, F31, and F32…….…….…….…….…….…….……………………… 109 Figure 5.17. The pseudo-second order equilibrium chromium sorption constant qe plotted against microbial isolates’ negative surface charge…….…….…….…………………………………………. 110

viii

ACKNOWLEDGEMENTS

I would like to acknowledge many people for helping me during my doctoral work. Without their support and encouragement, my dissertation would not be completed.

Firstly, I would like to give special thanks to my dissertation committee, Dr.

Karen Skubal, Dr. Aaron Jennings, Dr. Robert Mullen, and Dr. Andrew Swanson for their input, valuable guidance, and suggestions.

I would especially like to thank my advisor, Dr. Karen Skubal, for her continuous support and encouragement in multiple ways in the pursuit of this degree. I am grateful for her guidance, understanding, patience, and mostly her friendship during my graduate studies at CWRU. She has always been there to listen to me, comfort me, help me, and advise me as much as she could not only as an advisor but also like a friend and a sister. I have learnt much from her for both my professional and personal growth.

Dr. Aaron Jennings’s constructive suggestions have always motivated me when I have talked to him. I greatly value his suggestions, his patience, and encouragement. I have also always enjoyed his anecdotal lectures, his sense of humor, and his broad range of conversational topics.

I owe a special note of gratitude to Dr. Robert Mullen, the chairman of

Department of Civil Engineering at CWRU. I really appreciated his efforts in finding financial support for my last semester.

I would like to acknowledge Dr. Laura Skubal for conducting XAFS analysis in

Argonne National Lab. This is a very important and supportive experiment in my dissertation.

ix The support of the Civil Engineering Department personnel and other friends has been tremendous. My deepest thanks go to Dr. Jun Ma, who graduated from Civil

Engineering earlier, and his wife. As my best friends, they have given me much comfort,

help, and encouragement these years. I also thank Mrs. Saho Ikemoto-Linton for her

precious and continuous friendship and lots of encouragement and support, who also

graduated from the Civil Engineering Department earlier. I have had a very nice

officemate, Ms. Judith Wang. I thank her for helping me to improve my English, listening

to my complaints, and giving me lots of helpful suggestions and advice in different

aspects. I also feel fortunate to have more dear friends: Mr. Rogier Bronk, Ms. Chunmei

He, Dr. Yunyi Zou, and Ms. Jia Zhong. Their encouragement, help, and caring made my

doctoral years enjoyable.

Last, but not least, I thank my family. None of this would be possible without

their love and support even though they have been far away from me. I am indebted to

the profound love and support of my sister, brothers, and my parents. I am thankful and

grateful for their encouragement and love that they have shown me over the years.

NOMENCLATURE

µ specific growth rate constant, time-1 chromium tolerance, the ratio of a culture’s growth rate constant in the µ/µo presence of chromium (µ) to its growth rate constant in chromium- free medium (µo). -1 µmax maximum growth rate constant, time

µo first-order specific growth rate constant in the absence of chromium

A600 optical absorbance at a wavelength of 600 nm AA atomic absorption spectroscopy AHLs acylated homoserine lactones ANL Argonne National Laboratory APS Advanced Photon Source, a synchrotron facility at Argonne National Laboratory ATP adenosine triphosphate BCA bicinchoninic acid assay for protein analysis BOD biochemical oxygen demand CFU colony forming unit CFU/g colony forming units per gram consortium a multiple-species bacterial culture Cr(VI) hexavalent chromium EIC electrostatic interaction chromatography EPA Environmental Protection Agency EPS extracellular polymeric substances eV electron volts EXAFS extended X-ray absorption fine spectroscopy F1 microbial consortium extracted from soil using the “least stringent” procedure, which involved elution with mineral medium F11, F12, F13 single-colony microbial isolates obtained from consortium F1 F3 microbial consortium extracted from soil using the “most stringent” procedure, which involved elution with mineral medium, elution with

xi surfactant solution, and sonication F31, F32 single-colony microbial isolates obtained from consortium F3 g acceleration due to gravity HIC hydrophobic interaction chromatography HSLs homoserine lactones hr hour first-order constant describing chromium-dependent decrease in kµ growth rate -1 -1 k1,ads Lagergren first-order rate constant for metal sorption (g▪mg min )

-1 -1 k2,ads second-order rate constant for metal sorption (g▪mg min ) first-order characteristic toxicity constant describing the effect of kc chromium on biomass production kd death rate constant

Ks Monod affinity constant or half-saturation constant, mass/volume M molarity (moles/L) MATH microbial adhesion to hydrocarbons assay meq milliequivalents of charge mM millimolar n.d. not detected NADH nicotinamide adenine dinucleotide NADPH nicotinamide adenine dinucleotide phosphate nm nanometer NOM natural organic matter OD optical density PAH polycyclic aromatic hydrocarbon q metal uptake by cells (mg/g dry cells) qe equilibrium metal uptake by cells R percent retention of cells in a column 2 2 r or R correlation coefficient S substrate concentration

xii minimum or threshold concentration required for substrate Smin metabolism td doubling time, the period required for one cell to divide into two tlag lag period preceding the onset of exponential growth (time) UV ultraviolet v/v volume-to-volume ratio w cell mass w/v weight-to-volume ratio wt% percent by weight X biomass or cell concentration XAFS X-ray absorption fine structure spectroscopy XANES X-ray absorption near edge structure spectroscopy

Xc biomass concentration produced in the presence of chromium

Xo biomass concentration produced in the absence of chromium XRF X-ray fluorescence YE yeast extract

xiii

Distribution of Metabolic Characteristics Among Aerobic Soil Bacteria and Implications for Biotransformation of Organic and Metallic Wastes

Abstract

FANGMEI ZHANG

Comingled organic and metallic pollutants challenge soil remediation efforts because of their distinct chemical and biological transformation behavior.

Bioremediation of such wastes depends upon pollutant types, remediation endpoints, and microbial metabolism and habitat. This research examined relationships between habitat, cell physiology, and aerobic biotransformation of chromium and organics. It was hypothesized that the degree of soil attachment by culturable heterotrophic bacterial communities in the vadose zone correlates to chromium biosorption, reduction, and tolerance; cell surface properties; growth rate; and substrate affinity. Compared to weakly soil-associated communities, strongly-associated communities were expected to have slower growth and greater substrate affinity, hydrophobicity, and chromium tolerance. Community-level relationships were not expected to hold true at the population level, however. Instead, bacterial isolates were anticipated to exhibit cell surface properties and biotransformation behavior not necessarily linked to their original soil association or community. The research sought to identify the biotransformation potential of often-overlooked soil microorganisms and to assess their use in achieving low residual contaminant concentrations in comingled chromium wastes.

xiv Serial elution was used to extract two variably-attached bacterial communities

from noncontaminated vadose zone soil. Five microbial isolates were cultured from

these consortia. Consortia and isolates were characterized with respect to: 1. cell surface

hydrophobicity and charge, using solvent-, resin-, and titration-based tests; 2. the rate and

extent of growth on yeast extract and salicylic acid, a model organic pollutant; 3.

chromium toxicity under variable substrate conditions; 4. chromium reduction, measured

via x-ray spectroscopy; and 5. the kinetics and extent of chromium biosorption.

As hypothesized, the easily-detached bacterial community (F1) was less

hydrophobic than its counterpart (F3), but its isolates varied unpredictably in

hydrophobicity. Furthermore, F1 exhibited faster Monod-type growth but lower affinity

-1 -1 for yeast extract (µmax=0.35 hr , Ks=36.6 mg/L) than F3 (µmax=0.30 hr , Ks=12.2 mg/L),

whereas its isolates showed growth variability. Salicylic acid generally produced non-

Monod growth and increased apparent chromium toxicity. All isolates and consortia

were able to sorb and reduce chromium, regardless of cell surface properties or original

attachment. Chromium resistance was negatively correlated to substrate (yeast extract)

affinity among isolates, positively correlated to the substrate affinity of consortia (as hypothesized), and independent of cell surface properties.

CHAPTER 1. Introduction

The presence of hazardous, comingled metal and organic pollutants represents the most significant environmental stewardship problem at many government, industrial, and brownfield sites. A 1997 survey of Superfund sites with signed Records of Decision revealed that 49% were contaminated with a combination of hydrocarbons and metals

(USEPA, 1997). Despite the frequency of comingled wastes at disposal sites, few remediation technologies can address both types of pollutants (Mulligan et al., 2001).

The usefulness of in situ or ex situ processes designed to remove or transform one category of pollutant can be substantially limited by the presence of the other type of pollutant. For example, the presence of toxic heavy metals can reduce the efficiency of biodegradation processes geared for organic waste destruction (Malakul et al., 1998).

Similarly, organic constituents may interfere with physicochemical or biological processes that are used to remove metals. Even pump-and-treat methods that attempt to remove metals and organics simultaneously can be limited by low metal solubility or by the fact that co-contaminated waste streams are difficult and expensive to treat.

Bioremediation is a management and remediation approach that uses microbial processes for contaminant transformation in soil and groundwater, with or without amendments. Natural and enhanced in situ bioremediation is a viable, cost-effective option for treating a wide variety of organic pollutants. It offers the ability to remediate vast volumes of contaminated soil and water (Fliermans et al., 1988) and to overcome mass transfer limitations that make physicochemical treatment of certain chemicals

1 inefficient and costly (Munakata-Marr et al., 1996; Adriaens and Vogel, 1995).

However, the presence of metal co-contaminants at polluted sites may negatively impact bioremediation by altering the community structure of microbial ecosystems or by inhibiting microbial activity (Hughes and Poole, 1989; Kuo and Genthner, 1996; Said and

Lewis, 1991), reducing the likelihood that remediation endpoints will be achieved.

Adverse impacts on organic pollutant-degrading microbial communities can in turn affect the speciation, uptake, and mobility of metals. While metals themselves are not biodegradable, they are biotransformable, and metal stabilization and immobilization via biotic or abiotic processes are potentially inexpensive and effective means for reducing metal toxicity and enhancing metal containment in the subsurface. However, much remains to be learned regarding the complex biological, physical, and chemical interactions that govern in situ organic pollutant transformations and metal cycling in co- contaminated systems.

Biological, chemical, and physical interactions are all components of microbial habitat, a general term that includes substrate type and concentration; substrate age and availability; nutrient and electron acceptor conditions; soil composition; and the physical location of microorganisms within the soil matrix. Habitat characteristics and the metabolic capabilities of microorganisms both control biotransformation kinetics and achievable bioremediation endpoints for target pollutants in a particular subsurface zone.

Because natural environmental systems are far too complex to simulate completely under laboratory conditions, bioremediation experiments limit the number of variables that are tested, thereby introducing biases into the results. For example, studies may focus on the fate of only one contaminant, utilize a pure culture, or measure lumped biokinetic

2 parameters that do not reflect the activities of dynamic microbial communities under

fluctuating environmental conditions. The objective of this research was to examine

normally-overlooked aspects of organic and heavy metal transformation by soil bacteria,

particularly with respect to the substrates that are examined and the manner in which

microorganisms are extracted and chosen for study.

1.1 Research hypothesis and significance of the work

Research was performed to elucidate previously-unexplored relationships

between microbial habitat, cell physiology, and the biotransformation of metals and

organics in the context of soil and sediment remediation. The heavy metal used in this

work was chromium. The governing research hypothesis was that the degree of

association of indigenous culturable, heterotrophic bacterial communities within vadose

zone soil correlates with their propensity for chromium biosorption and reduction,

chromium tolerance, cell surface properties, growth rate, and organic substrate affinity.

Communities more strongly associated with soil particles were expected to be more oligotrophic than those that were weakly-attached; that is, they should have a higher

affinity for primary organic substrates and slower growth kinetics. Their larger substrate

affinity was expected to result from more efficient, tightly-controlled substrate uptake

systems that would simultaneously provide microorganisms with greater resistance to

chromium toxicity. Strongly soil-associated bacterial communities were also expected to

possess cell surface properties reflective of their attachment to soil, for example elevated

hydrophobicity for enhanced interactions with hydrophobic soil organic matter.

Although these relationships were expected to hold at the community level, they were not

3 expected to apply uniformly at the population level. Instead, individual bacterial isolates cultured from larger communities were anticipated to exhibit unique cell surface properties and biotransformation behavior that would not necessarily reflect their original

degree of soil association.

Validation of the research hypothesis would have two main implications. First, it would demonstrate potential experimental biases resulting from the use of “standard” microbiological elution methods that wash only easily-eluted organisms from soil.

Procedures for isolating soil bacteria for use in laboratory studies typically involve a relatively short, gentle soil washing step that recovers only a small fraction of easily- detached soil organisms (Dunbar et al., 1997). Microorganisms that remain trapped, and thus unstudied, in washed soil may possess useful traits, such as high substrate affinities

and metal tolerance, that could be exploited for improved in situ or ex situ remediation

performance. Thus, the possible consequences of employing widely-accepted but flawed

extraction measures are the underestimation of the rate and extent of comingled waste

biotransformation and the incorrect extrapolation of laboratory data to the field.

Second, a valid hypothesis would suggest that long-term immobilization of heavy

metals such as chromium could be facilitated by manipulating nutrient loads to

subsurface environments in order to shift microbial ecology for specific purposes.

Improved remediation could be achieved through a two-phased approach, for example.

During the first phase, copiotrophic microbial populations (those most often studied or

cultivated in the laboratory, characterized by fast growth and a preference for high

substrate and nutrient concentrations) could be stimulated in contaminated soil, perhaps

through the addition of supplemental nutrients or electron donors. With their relatively

4 low substrate affinities, copiotrophs could transform or mineralize organics to moderate

residual levels. During the second phase, metal-reducing oligotrophic species could be stimulated, for example by decreasing or halting the provision of nutrients. Oligotrophs would reduce metals to less toxic, less mobile species, and their greater substrate affinity would allow them to achieve lower residual organic pollutant concentrations than possible by copiotrophs alone, thereby achieving a “polishing step.”

Although previous studies have characterized subsurface bacteria based on their attachment to soil or other solid matrices (Campbell et al., 1999; DeFlaun et al., 1999;

Holm et al., 1992; Johnson et al., 1996; Lehman et al., 2001a,b; Lehman and O’Connell,

2002; Van Schie and Fletcher, 1999), or according to their ability to degrade organics in the presence of heavy metals (Drzyzga et al., 2002; Kuo and Genther, 1996; Sandrin et al., 2000), this study examined relationships between bacterial association with soil, cell surface properties, metal transformation and resistance, and affinity for organic substrates in subsurface environments.

1.2 Experimental approach

The research utilized a combination of microbiological methods, chemical assays, and advanced nondisruptive spectroscopic analyses, including x-ray absorption near edge spectroscopy (XANES) and extended x-ray absorption fine structure spectroscopy

(EXAFS), to examine the biotransformation of chromium, organics, and chromium- organic mixtures. The bacteria used were aerobic, heterotrophic communities and isolates distinguished by their variable retention in vadose zone soil. Specific goals included the following:

5 refinement of a soil elution procedure for stepwise extraction of bacterial communities

selection and preservation of eluted microbial consortia and isolates for detailed study

establishment of the uniqueness of consortia and isolates through identification of distinguishing cell surface characteristics and other biochemical properties

measurement of cultures’ growth kinetics and substrate affinity for organic electron donors

determination of the tolerance of consortia and isolates to toxic hexavalent chromium in the presence of a labile substrate or a model organic pollutant

establishment of whether metal tolerance was correlated to cell properties such as primary substrate affinity

measurement of the rate and extent of chromium biosorption by the cultures

assessment of whether microbial consortia and isolates were able to reduce hexavalent chromium to the trivalent form, and if so, whether this ability was related to substrate utilization characteristics.

1.3 Chromium pollution: sources and chemistry

This research focused on chromium. The release of metals such as chromium into

the environment is of great environmental concern because of their toxicity and

persistence. Although chromium is found naturally in soils and minerals, most chromium in the environment originates from industrial processes such as electroplating, steel and glass manufacturing, mining, dye and pigment synthesis, and leather tanning (Kimbrough et al., 1999; Mukherjee, 1998). The metal is also commonly found in industrial wastes

6 such as sludges, fly ash, and slag. Chromium has been found at concentrations as high as

2740 mg/L in groundwater (Office of Technology Assessment, 1984).

Chromium exists in multiple oxidation states, most of which are unstable in the

environment. Two major forms persist in environmental systems: trivalent chromium

(Cr[III]) and hexavalent chromium (Cr[VI]) (Kroshwitz, 1993). Most chromium present

in industrial wastes exists in the hexavalent form (Mukherjee, 1998). Hexavalent

chromium is carcinogenic, mutagenic, and teratogenic to humans and other animals and

is approximately one hundred times more toxic than the trivalent form (Langand, 1983;

Petrilli and DeFlora, 1977). Persistent hexavalent chromium may prove toxic to

subsurface microbial communities and negatively impact the biodegradation potential of

organic substrates. Because of its toxicological properties, legislative regulations for

chromium are based on valence state, rather than total concentration.

Hexavalent chromium compounds are generally more water soluble than trivalent

chromium compounds, particularly in the biologically-relevant pH range of 5-7. For

purposes of in situ metal immobilization, it is desirable to convert chromium (VI)

contaminants to less soluble, less toxic chromium (III) compounds. Aqueous solubilities

of both trivalent and hexavalent chromium compounds vary over many orders of

magnitude (Kimbrough et al., 1999). Chromium (III) precipitates as a hydroxide at a pH

above 5.5 (Alloway, 1990), existing in natural aquatic environments primarily in the form

2+ + of relatively insoluble metal hydroxides, including [Cr(OH) ], [Cr(OH)2 ], [Cr(OH)3],

- 5+ [Cr(OH)4 ], and [Cr3(OH)4 ] (Faust and Aly, 1981). The solubilities of these compounds

are particularly low at elevated pH. Unlike trivalent chromium, which may be found as

chromic ion (Cr3+), hexavalent chromium does not exist as a free cation (Cr6+) in waters.

7 Instead, it is present as oxides that behave as divalent anions rather than hexavalent

-2 -2 cations. These oxides include chromate (CrO4 ) and dichromate (Cr2O7 ) ions, both soluble in water over a wide pH range. Electron transfer between oxygen and various chromium compounds is key to the interconversion of trivalent and hexavalent chromium. The most important natural oxygen source for subsurface redox transformations of chromium is water, but molecular oxygen from the atmosphere and from supplied sources such as ozone, hydrogen peroxide, and metal oxides must also be taken into account (i.e., during the use of aquifer oxygenation technologies). Even so, dissolved oxygen alone has not been found to induce measurable chromium (III) oxidation, even after more than four months (Saleh et al., 1989).

Chromium in soils and pore water exists in states similar to those found in aquatic systems: as trivalent chromium, trivalent chromium compounds, and hexavalent chromium oxides. The chemical and sorptive properties of chromium in soil environments are complex and poorly understood. Physisorbed chromium can be leached from soils, indicating that sorption of the metal is a reversible process. Trivalent chromium compounds readily form stable complexes with negatively charged inorganic or organic particles in soils and sediments, including mineral solids with exposed surface hydroxy groups and silicates. From a site management standpoint, chromium sorption to soil and sediment components is favorable since it leads to stabilization and immobilization of the metal. Cr(III) that is not sorbed to the solid phase generally eventually precipitates as Cr(OH)3 (Barber and Stuckey, 2000).

Unlike Cr(III), hexavalent chromium is highly unstable and mobile in soils because it adsorbs poorly to soil components under natural conditions. However, the

8 interconversion between precipitated chromium, adsorbed chromium, and dissolved chromium in soil water is complicated. It appears to be dependent on a variety of parameters including the species of chromium present; soil pH; biological activity in soil; oxygen concentration; oxidizing and/or reducing agents such as hydrogen sulfide, sulfur, iron sulfides, ammonium, nitrite, and ferrous iron (Bodek et al., 1988); and the presence of organic matter. Organic matter has a greater influence on Cr(VI) reduction than most other chemical constituents, for it is able to promote accelerated reduction of Cr(VI) at almost any pH (Mukherjee, 1998). As long as anoxic sediments are themselves physically stable and are not depleted in reducing power, they can effectively promote chromium reduction, reduce chromium toxicity, and enhance chromium stability. When reducing power becomes exhausted by high Cr(VI) concentrations, soil amendments may become necessary for continued long-term metal immobilization. Aerobic environments often provide more of a challenge in controlling the speciation of chromium. In well- aerated soils, the chemistry of chromium resembles that of iron, and in fact chromium speciation and mobility is strongly influenced by that of iron (Mukherjee, 1998).

1.4 Chromium uptake, transformation, and resistance by soil microorganisms

A number of studies have demonstrated the detoxification of chromium via microbial reduction of Cr(VI) to Cr(III) and subsequent precipitation of Cr(III) (Bopp and

Ehrlich, 1988; Gvozdyak et al., 1985; Horitsu et al., 1987; Suzuki et al., 1992; Wang and

Shen, 1995), which is less able to cross the cell membrane (Nieboer and Jusys, 1988).

Microbial transformations of Cr(VI) to Cr(III) typically occur most quickly at neutral pH and at temperature, soil moisture, and nutrient conditions coinciding with the optimal

9 growth of chromium-reducing microorganisms. High cell densities are almost always necessary to obtain significant rates of Cr(VI) reduction (Wang and Shen, 1995). Known electron donors for Cr(VI) reduction under both aerobic and anaerobic conditions are generally limited to natural aliphatic compounds, amino acids, fatty acids, simple sugars and hydrogen, although one study demonstrated chromium reduction in a co-culture utilizing phenol (Shen and Wang, 1995). Under aerobic conditions, endogenous cell reserves and NADH (nicotinamide ademine dinucleotide, a carrier of electrons and protons), also may serve as the electron donor for Cr(VI) reduction (Wang and Shen,

1995). Both aerobic and anaerobic microorganisms from a wide range of subsurface environments and genera are able to reduce chromium.

Reduction at cell surfaces may occur through a three-step process in which

2- negatively charged dichromate (Cr2O7 ) is bound to positively charged groups on cell surfaces; reduced by adjacent functional groups; and released as Cr(III) by electronic repulsion (Parka et al., 2005). Some bacteria are known to possess enzymes with large reduction potentials that are capable of transforming hexavalent chromium. For example,

Pseudomonas ambigua G-1 has a NADPH-dependent reductase (Suzuki et al., 1992),

Escherichia coli has a flavin reductase (Puzon et al., 2002), and Shewanella oneidensis

MR-1 has a nitrite reductase (Viamajala et al., 2002).

Microbial chromium resistance, a phenomenon not exclusive to the ability to reduce chromium, is often observed in microorganisms indigenous to chromium- impacted environments (Cervantes, 1991; Nieto et al., 1989; Ohtake et al., 1987; Wang et al., 1989). Resistance to the metal may be achieved through the adsorption of chromium(VI) to bacterial surfaces or by chromium accumulation inside cells.

10 Chromium resistance appears to be more prevalent among prokaryotes than eukaryotes

(Shakoori et al., 2000) and tends to diminish as chromium accumulates in the cell.

Microbial metal reduction and resistance have been shown to take place over

concentrations ranging from trace levels up to 0.27 M total chromium or more (Badar et

al., 2000; Fude et al., 1994; Shakoori et al., 2000).

Extracellular polymeric substances (EPS) are thought to play a major role in metal

resistance and in the binding and accumulation of metals at cell surfaces. EPS is often

acidic (Czajka et al., 1997; Sutherland, 1982), and metals readily adsorb to the multiple

high-affinity binding sites on polysaccharides and other EPS functional groups (Rudd et

al., 1984; Kellems and Lion, 1989). Metals may also deposit on cell surfaces as oxides

(Ghiorse, 1984; Lion et al., 1988; Nelson et al., 1994; Chen et al., 1994). EPS serves as a

physical and chemical barrier that is thought to protect cells from compound toxicity

(Brown and Gilbert, 1993; Chen, et al., 1993; Costerton et al., 1987; Evans et al., 1990;

Gilbert et al., 1997; Gristina et al., 1987; Hoyle et al., 1990; Stewart, 1996; Xu et al.,

2000). Much of what is known about toxicity to bacteria comes from studies of antibiotic resistance, which have shown that extracellular polymeric substances retard the diffusion of antibiotics (Ishida et al., 1998) and other solutes (Stewart, 1998), thus protecting biofilm organisms. Bacteria living deep in a biofilm may exist in a slow-growing state

(Brown et al., 1988), which further prevents the uptake of antibiotics and increases

apparent resistance. Comparable explanations have been offered for tolerance to heavy

metals and toxic organics (Junter et al., 2002; Bessems and Terpstra, 2003).

Bacterial biomass is a very efficient metal biosorbent because of cells’ high

surface area-to-volume ratio and the presence of functional groups that have high

11 affinities for heavy metals (Beveridge, 1989a; Beveridge and Murray, 1980; Daughney

and Fein, 1998; Daughney et al., 1998; Fein et al., 1997; Fowle and Fein, 1999). Two

types of bacterial uptake systems for heavy metals have been postulated. One is

constitutively expressed and results in fast, nonspecific metal uptake that is dependent on

chemiosmotic gradients across the cytoplasmic membrane. The second system is

inducible as needed and results in slower, metal-specific uptake that often requires ATP consumption in addition to a chemiosmotic gradient (Nies and Silver, 1995; Nies, 1999).

1.5 Microbial partitioning in soil and its implications for pollutant biotransformation

The physical location or partitioning of microorganisms between soil surfaces, pore water, and groundwater is significant to in situ bioremediation applications. For instance, control over cell attachment and detachment is necessary for bioaugmentation strategies that rely on the uniform delivery, without clogging near the injection point, of biodegradative organisms introduced into a contaminated zone. Following introduction, bacteria should be adherent to an extent such that they are not displaced from the bioactive zone by groundwater flow or during delivery of supporting nutrients or substrates. Cell adhesion also affects the types and quantities of substrates encountered by and available to cells, thus affecting remediation endpoints that can be expected for soluble and sorbed contaminants. Bacteria adapted to living on contaminated surfaces and those that exist in the surrounding groundwater or pore water are expected to form communities with different capacities to degrade organics and to tolerate or transform heavy metals. For example, adhesive bacteria may be expected to have greater exposure

12 to strongly-sorbing organics, soil-sequestered heavy metals, and natural organic matter

compared to planktonic organisms in a given contaminated microenvironment. Cell

attachment, particularly in biofilms, is also known to confer selective advantages to cells,

including physical protection from predators, pH fluctuations, temperature gradients, and

antimicrobial agents; the sharing of metabolites and extracellular enzymes; and horizontal

gene transfer.

Cell partitioning and physiological properties. Microbial partitioning of bacteria

between solid and aqueous phases has in fact been shown to be related to the physical

distribution of physiological properties such as growth rates, exopolymer synthesis, and

enzyme activity (Lehman and O’Connell, 2002; Van Loosdrecht et al., 1990), although it

is often uncertain whether the differences are due to functional expression or community

structure (Delong et al., 1993; Karner and Herndl, 1992; Murrell et al., 1999; Okabe et

al., 1994). Individual bacterial species possess distinct capacities for degrading sorbed

and dissolved organic contaminants such as naphthalene (Guerin and Boyd, 1992) and

exhibit divergent metabolic traits depending upon the relative hydrophobicity of the microenvironment they occupy (Bastiaens et al., 2000). Lehman et al. (2001b) found that attached heterotrophic bacteria isolated from aquifer core material were morphologically more diverse than free-living bacteria isolated from groundwater at the same depths.

Bacteria attached to particulates have been found to exhibit greater extracellular enzyme

activity than free-living bacteria in aqueous habitats (Karner and Herndl, 1992;

Middleboe et al., 1995).

Abundance and activity of planktonic versus attached bacteria. The relative

amount of biomass present as attached and free-living bacteria appears to be site-

13 dependent. A number of studies of aquifer material have identified the majority of total

biomass as being attached to the solid phase (Holm et al., 1992; Kolbel-Boelke et al.,

1988; Lehman et al., 2001a; Harvey et al., 1984; Alfreider et al., 1997; Escobar et al.,

1996; Ghiorse and Wilson, 1988; Hazen et al., 1991; Pedersen and Ekendahl, 1990;

Dispirito et al., 1983; Kirchman and Mitchell, 1982; Caron et al., 1982). One bench-scale column study demonstrated that about 99% of total biomass and 96% of phenol-oxidizing microorganisms were attached to the geologic medium (Lehman et al., 2001a). Other researchers have found greater quantities of free-living bacterial biomass (Lehman et al.,

2001b; Bidle and Fletcher, 1995; Griffith et al., 1994; Turley and Mackie, 1994;

Kirchman and Mitchell, 1982; Middleboe et al., 1995; Simon et al, 1990; Unanue et al.,

1992; Kogure, 1989, Smith et al., 1995; Bekins et al., 1999; Thomas et al., 1987). Based on this information, it is difficult to state presumptively whether sessile or planktonic organisms will prevail in a given environment.

Mechanisms of attachment. Microbial attachment is a complicated process involving physicochemical and biological reactions between solid surfaces, bacteria, and the ambient environment. The first step in attachment is a weak physicochemical interaction between bacterium and surface that may be reversed by gentle shearing forces

(Marshall et al., 1971; Marshall, 1992). Stronger, potentially irreversible adhesion may subsequently develop (Dankert et al., 1986; Marshall, 1985; Marshall et al., 1971), for example through specific or nonspecific bridging (Marshall, 1992) of extracellular polymeric substances including polysaccharides, proteins, glycoproteins, or lipopolysaccharides (Allison et al., 1987; Costerton et al., 1985; Fletcher and Floodgate,

1973; Marshall, 1992; Marshall, 1985, Underwood et al., 1995; Heissenberger et al.,

14 1996; Bennett et al., 1999; Ransom et al., 1999; Makin and Beveridge, 1996). In fact, a

lack of bacterial EPS has been linked to less adherence (Christensen et al., 1982, Davey

and O’Toole, 2000).

Both long-range and short-range forces are involved in attachment (An and

Friedman, 1997; Dankert et al., 1986; Krekeler et al., 1989; Marshall, 1992; Marshall,

1985). Attractive forces between cells and surfaces include van der Waals forces,

gravitational forces, and electrostatic and hydrophobic interations (Dankert et al., 1986;

Krekeler et al., 1989). Chemical fluctuations can cause changes in cell surface properties, attractive forces, and attachment tendences; for example, lactic acid was shown to alter the hydrophobicity of Listeria monocytogenes, affecting the

microorganism’s adherence (Briandet et al., 1999).

Attachment is both environment- and species-specific. One study that used

Tween 20 to treat attached cells found that hydrophobic interactions were not involved in

maintaining the structure of marine biofilms, but were important in certain freshwater

organisms (Fletcher, 1989). Another study determined that attached Cyanobacteria had

hydrophobic surfaces, whereas planktonic cells were hydrophilic (Fattom and Shilo,

1984). Such phenomena may be explained by the activation of specific genes following

attachment; these genes may trigger production of extracellular materials (e.g., EPS) that

stabilize attachment and alter cell surface properties (McCarter and Silverman, 1990). A

number of studies have demonstrated the genetic control of biofilm development (e.g.,

Costerton et al., 1999; Davies et al., 1993; Watnick et al., 2001; Fan and Macnab, 1996;

Stephens et al., 1997; Davies and Geesey, 1995; Prigent-Combaret et al., 1999).

15 Solid surfaces and microbial attachment. The chemical composition of surfaces is among the most important factors influencing microbial attachment (Harvey et al.,

1989). Biomaterials have been found to permit easier cell attachment (Sugarman and

Musher, 1981) than abiotic surfaces (e.g., steel, glass, plastic, and soil), which are mostly non-nutritive and may require bacteria to produce exudates to facilitate adhesion.

Specific components of abiotic surfaces have varying effects on cell attachment. Iron and aluminum hydroxides in sediments have been found to enhance bacterial retention in aquifers (Knapp et al., 1998; Ghiorse, 1984; Lion et al., 1988; Dong et al., 2002), possibly by altering surface charge or nutrient conditions (Nelson et al., 1994). However, organic matter adsorbed to the surfaces of metal oxide coatings can preclude adhesion

(Dong et al., 2002). Hydrophobic surfaces, such as those bearing silicon, can also decrease cell attachment (van Schie and Fletcher, 1999). Granular activated carbon is relatively favorable for attachment, comparable to sand and anthracite (Camper et al.,

1987; Malony et al., 1984).

The physical nature of surfaces is also important to attachment. Surface roughness, topography, and grain size are all significant. Deep narrow pits provide a safe environment for bacteria to avoid predators (Murray and Jumers, 2002; DeFlaun and

Mayer, 1983). Boyd et al., (2002) used atomic force microscopy to detect the attachment

of individual bacteria on surfaces of different topographies and discovered that bacteria

became more strongly attached to abraded surfaces than to smooth layers. Knoell et al.

(1999) found that irregular or elliptical pores discouraged bacterial retention.

Cell surface properties and microbial attachment. Many studies have focused on

hydrophobic and electrostatic interactions between cells and surfaces and their role in

16 attachment (Fattom et al., 1984; Fletcher and Marshall, 1982; Kjelleberg and

Hermansson, 1984; Gannon et al., 1991b; McCalou et al., 1995; Absolom et al., 1983;

Busscher et al., 1984; Hermansson et al., 1982; Hermesse et al., 1988; Morisaki, 1986;

Marshall et al., 1971; van Loosdrecht et al., 1987a; Briandet et al., 1999; Dickson and

Koohmaraie, 1989; Gordon and Millero, 1984; Fletcher, 1996; Taylor et al., 1997; van

Loosdrecht et al., 1990; Daniels, 1980; Rijnaarts et al., 1999; Bendinger et al., 1993;

Dickson, 1989; Marshall, 1985; Rutter and Vincent, 1984; van Oss, 1993). Makin and

Beveridge (1996) showed that hydrophobic cells such as those of Pseudomonas aeruginosa easily attached to hydrophobic surfaces, whereas hydrophilic cells’ attachment was controlled more by surface charge (Makin and Beveridge, 1996).

Hydrophobic bacteria were shown not to attach effectively to hydrophilic materials

(Yousefi, et al., 1998; Knoell et al., 1999; Gómez-Suarez et al., 2001; Cunliffe et al.,

1999). Nevertheless, bacteria are normally negatively charged because of the presence of carboxyl and phosphate groups, among others, and these contribute a measure of hydrophilicity. In fact, electronegatively charged bacteria can bind to either positively- or negatively-charged surfaces, the latter as a result of counterions involved in cation bridging mechanisms (Urrutia and Beveridge, 1993; Ueshima et al., 2002).

Cell surface properties can change with growth phase. Although growth phase affects bacterial attachment (Weiss et al., 1995), it appears to be species-dependent, with some strains showing greater adhesion during exponential phase and others during stationary phase (van Schie and Fletcher, 1999; Grasso et al., 1996; Stewart et al., 1997).

Cell structures and microbial attachment. Cell structures that facilitate attachment include capsules, pili, and fimbriae (rigid, straight protein filaments, 0.2-20

17 nm in length and numbering 10-1000 per cell) (Jones and Isaacson, 1983; Michiels et al.,

1991). Fimbriated bacteria tend to be more hydrophobic than nonfimbriated cells and are often gram negative. Flagella and the microbial motility they impart may also facilitate

attachment by increasing the likelihood and force of cell-surface contact (Fletcher, 1996;

Morisaki et al., 1999), but motility is not a prerequisite (Dan, 2003).

Biochemical stimulation of attachment. Certain bacteria are known to have the

ability to sense surfaces and respond phenotypically or behaviorally. For example,

biofilms grown on submerged stones were found to produce the quorum-sensing signal

molecules acylated homoserine lactones (acyl-HSLs or AHLs) which can stimulate

attachment (McLean et al., 1997). Studies have also shown a tendency for antagonistic

behavior by particle-associated bacteria, particularly at high cell densities (Long and

Azam, 2001; Grossart et al., 2003). Interactions between species could be especially

prevalent and important in controlling microbial community composition at surfaces.

1.6 Oligotrophy, copiotrophy and bacterial attachment

Microbial communities in soil evolve under a variety of environmental pressures,

including fluctuations in nutrient and carbonaceous substrate availability. Populations

comprising soil communities have been classified into two main groups based upon their

niche, or function, their general response to environmental stresses, and their kinetic

behavior (MacArthur and Wilson, 1967; Panikov, 1995). Oligotrophic microorganisms

are characterized by broad substrate specificity, high substrate affinity, low cell

maintenance requirements, slow growth, and resistance to starvation conditions. Hu et al.

(1999) demonstrated that soil oligotrophs were in fact inhibited by highly-available

18 mineralizable carbon. Copiotrophic microorganisms, on the other hand, display narrower

substrate specificity, lower substrate affinity, fast or explosive growth, and less tolerance

to starvation. Given the low-energy maintenance needs and high-affinity substrate

transport systems of oligotrophs, these organisms may be expected to thrive in mass transfer-limited, substrate-poor environments, achieving threshold concentrations, or residual levels, of contaminants that are orders of magnitude lower than those achieved by copiotrophic organisms (Bosma et al., 1997). In carbon-poor environments contaminated by weathered organic compounds that are released slowly over long periods of time, oligotrophs could outcompete copiotrophs (Button, 1991) and contribute more significantly to pollutant biodegradation. It should be noted that oligotrophy and copiotrophy are not strictly defined but can be considered extremes on a wide spectrum of microbial carbon requirements (Semenov, 1991). Furthermore, oligotrophs and copiotrophs can coexist, for instance in the presence of multiple limiting substrates or nutrients, or under conditions of dormancy (Hu et al., 1999).

Oligotrophic or copiotrophic behavior is not necessarily an inherent trait of a microbial species. Cells are known to adjust their metabolism during periods of stress in order to compete for nutrients, adopting a feast-or-famine type of strategy (Egli, 1995;

Kovárová-Kovar and Egli, 1998). Nutrient limitations or starvation conditions can cause cells to change in size, rates of endogenous respiration, protein synthesis, or cell surface

hydrophobicity, for instance. The effect of starvation on cell attachment appears to be

species- and environment-specific. Starved marine bacteria were found to become more

adhesive in oligotrophic habitats (Marshall, 1989), and certain microorganisms have been

found to synthesize unique membrane and periplasmic proteins during starvation, which

19 could contribute to observed increases in their attachment (Nyström et al., 1989). In other species, starvation results in decreased attachment (van Schie and Fletcher, 1999).

Other environmental stresses that are known to impact bacterial metabolism and attachment include fluctuations in pH (Nyvad and Kilian, 1990; Ørstavik, 1977; Gordon et al., 1981; Harber et al., 1983; Scholl and Harvey, 1992; Kinoshita et al., 1993; Jewett et al., 1994); salinity (Zita and Hermansson, 1994; Gordon and Millero, 1984); ionic strength (Fontes et al., 1991; Gannon et al., 1991a; Gannon et al., 1991b; Jewett et al.,

1994; van Loosdrecht et al., 1990; Ørstavik, 1977; Abbot et al., 1983; Sampson and

Blake, 1999); specific ions such as Fe3+ (van Schie and Fletcher, 1999; O’Toole and

Kolter, 1998a), nitrate, and sulfate (van Loosdrecht et al., 1990); fluid dynamics (van

Loosdrecht et al., 1990; Gómez-Suarez et al., 2000; Gómez-Suarez al. 1999a; Gómez-

Suarez et al., 1999b, Gómez-Suarez et al., 2001; Harvey et al., 2002; McClaine and Ford,

2002; Sjollema et al., 1989; Boyd et al., 2002; Klausen, 2003); carbon dioxide concentration (Denyer, 1990); osmolarity (Fletcher, 1996); and organic pollutants and surfactants (Bekins et al., 1999; Harvey et al., 1984; Harvey and George, 1987; Hazen et al., 1991; Niels et al., 1995; van Schie and Fletcher, 1999).

The community structure, kinetic characteristics, and adaptability of microorganisms also appear to be related to their degree of attachment to soil. Rihana-

Abdallah (2000) found ecological variation (measured using phospholipid fatty acid profiles) between loosely-attached and tightly-attached microbial fractions eluted from soil. Differences between fractions diminished with increasing soil organic carbon content. Divergence in kinetic parameters was also observed between microbial fractions, most notably in low-carbon soils. Tightly-attached microorganisms adapted

20 more readily to changes in substrate type and concomitantly exhibited decreased

membrane fluidity, a phenomenon that has been linked to resistance to environmental

stresses, for example changes in temperature (Annous et al., 1999). This type of membrane response by tightly-attached, oligotroph-like populations could lead to increased metal resistance and enhanced organic pollutant biodegradation compared to the behavior of loosely-attached, copiotroph-like organisms. Attached bacteria have also been found to show higher uptake rates for certain substrates (Palumbo et al., 1984;

Unanue et al., 1992); greater biodegradative capability for organics (Jeffrey and Paul,

1986; van Loosdrecht et al., 1987a), and faster decomposition of labile matter associated with particles (Cho et al., 1988). Furthermore, bench-scale column studies revealed that attached bacteria had a preference for more complex organics than unattached bacteria

(Lehman et al., 2001a).

CHAPTER 2. Isolation and Physiological Characterization of Microbial

Communities and Isolates from Unsaturated Soil

2.1 Introduction

This research study commenced with the selection of a field site from which soil

samples and indigenous soil bacteria could be obtained. An undisturbed pasture at a

research farm managed by Case Western Reserve University was chosen because it was accessible and was not impacted by tilling, agriculture, pesticide application, or historic

contamination. Thus, it could reasonably represent conditions in a subsurface

environment before the onset of a contamination event. Soil cores were collected from

the shallow vadose zone. The vadose zone is defined as the unsaturated soil region above

the groundwater table, extending from the bottom of the capillary fringe to the soil

surface. It includes surface soil, which is the uppermost soil layer normally disturbed

during tilling. Surface soil in noncultivated environments typically ranges in depth from

7 to 20 centimeters (Sylvia et al., 1999). The vadose zone was expected to be aerobic and

to support microbial populations accustomed to living in close physical association with

soil material and utilizing natural organic matter as a primary substrate. Many of the

functional groups present in natural organic compounds are analogous to chemical

structures found in xenobiotic chemicals.

Soil samples were used to test and refine a serial elution procedure that employed

increasingly stringent physical and chemical methods to remove microorganisms.

Microbiology studies that seek to detach cells with improved efficiency can employ

22 chemical procedures in which samples are suspended in buffer with sodium chloride, sodium pyrophosphate, or surfactants (Ogram and Feng, 1997; Rihana-Abdallah, 2000); mechanical processes that use shaking, vortexing, centrifugation and ultrasonication; or enzymatic treatments that use lipases, α-glucosidase, or β-galactosidase to degrade the extracellular polymeric substances binding cells to soil. “Standard” microbiology practices such as shaking or vortexing are considered insufficient for removing tightly- attached bacteria (McLean et al., 2001).

In this study, cells that were collected during the first, gentlest elution step and during the final, harshest step comprised two consortia or “microbial fractions” that were the focus of much of the research. These consortia were generically categorized as

“loosely-attached” and “tightly-attached,” respectively, although the specific chemistry of their interactions with the soil matrix was outside the scope of this work. Individual bacterial isolates were also cultured from the two fractions with the goal of comparing their physiological traits to those of the parent consortia.

Microbial consortia and isolates were characterized using Gram stains, catalase tests, and other common microbiology assays, along with partitioning tests to determine cell surface properties. The microbial adhesion to hexadecane (MATH) test was used to measure cell surface hydrophobicity by comparing the partitioning of a cell suspension in organic solvent and water phases (Rosenberg et al., 1980). Hydrophobic interaction chromatography was used to differentiate the elution of cell suspensions through small columns packed with hydrophobic and control resins. Electrostatic interaction chromatography was employed to compare the elution of cells through anion-exchange and control resins. These tests were performed to establish the uniqueness of the cultures

23 and to examine whether surface properties correlated to biotransformation behavior

examined in subsequent chapters.

2.2 Materials and Methods

Soil sampling and characterization. Soil samples were collected in April, 2003

and January, 2004 at Case Western Reserve University’s Squire Valleevue Farm, a 400-

acre research and teaching facility located in Hunting Valley, Ohio. Soil cores were removed from the vadose zone of untilled grassland at depths of approximately 12 to 18 inches using a hand auger. Cores were sealed in plastic and stored at 4°C prior to subdivision and use in laboratory studies. Soil pH was measured in a suspension of 10 g

air-dried soil and 25 mL distilled, deionized water after shaking at 175 rpm for 15

minutes at 19°C (Rowell, 1994). Soil moisture content was determined gravimetrically

following sample drying for 24 hours at 105°C. Total organic carbon content was

measured as weight loss following combustion of oven-dried samples at 550°C for 30

minutes.

Adhesion-based extraction of soil microorganisms. Soil core material was

processed by hand to remove plant roots, leaves, and other detritus before being subjected

to a serial elution procedure based on that of Rihana-Abdallah (2000), which fractionates

microbial communities according to the strength of their adhesion to soil particles.

During each extraction test a suspension of 100 g soil and 350 mL of autoclaved mineral

medium was shaken for four hours at 225 rpm and room temperature. Mineral medium

consisted of nitrogen-augmented BOD dilution water (American Public Health

Association et al., 1998) with a pH of 7.0 and the following composition: 8.5 mg/L

24 KH2PO4; 21.75 mg/L K2HPO4; 33.4 mg/L Na2HPO4•7H2O; 22.5 mg/L MgSO4•7H2O;

27.5 mg/L CaCl2; 0.25 mg/L FeCl3•6H2O; and 1.0 g/L NH4Cl.

The soil suspension was centrifuged at 4,500×g for 10 minutes and the

supernatant was subsequently filtered with Whatman 50 filter paper (>2.7 μm particle

retention) to collect eluent containing relatively easily-detached microorganisms. The

filtrate from this stage was termed “loosely-attached fraction F1,” representative of

easily-eluted microbial communities that would be obtained by traditional

microbiological extraction methods. A second elution was performed by resuspending

the drained soil with 300 mL of fresh, sterile high-nitrogen BOD water containing 0.2%

(v/v) Tween 80 surfactant, agitating the mixture for 2 hours at 100 rpm, and centrifuging as before. The collected filtrate, termed the “F2” fraction, represented microbial communities of intermediate attachment strength. It was not used in experiments. A third elution of the same soil sample was performed to extract microbial communities of greater attachment strength. This final step entailed resuspending the twice-eluted soil in

300 mL of fresh medium, agitating as before, and then mildly sonicating the slurry for 15 minutes prior to centrifugation. The filtrate, termed fraction “F3,” contained cells that were not detached during the previous two elutions and was assumed to include the most strongly adherent cells recovered by the method.

Isolation of dominant microbial populations. “Whole” microbial communities were harvested from filtrate fractions F1 and F3 by centrifuging at 10,000×g for 15 minutes, washing cell pellets twice with sterile 10 mM phosphate buffer (pH 7.4; composed of 1.08 g/L Na2HPO4•7H2O; 0.135 g/L NaH2PO4•H2O), and resuspending

pellets in fresh phosphate buffer. Aliquots of the concentrated community cultures were

25 used immediately or amended with 20% (v/v) glycerol and stored cryogenically at -80°C

to provide an inoculum source of consistent composition for subsequent experiments.

Predominant culturable microbial populations were isolated from fractions F1 and

F3 using serial dilution and plating techniques. First, concentrated aliquots of F1 and F3

were transferred to high-nitrogen BOD water containing 100 ppm yeast extract (Difco)

and 200 ppm cycloheximide (Aldrich), a fungal inhibitor. Cultures were shake-incubated

at 100 rpm and room temperature for 24 hours. Next, aliquots were removed from the

shake flasks and spread onto agar plates prepared with granulated agar and one-tenth

strength nutrient broth (Difco; final concentration 0.3 g/L beef extract and 0.5 g/L

peptone). Colony counting was used to enumerate culturable aerobic, heterotrophic bacterial cells extracted from the field soil samples in elution fractions F1 and F3. In

addition, colonies of distinct morphology and appearance were selected from the plates and further isolated by culturing in liquid medium and streak-plating three times in sequence. The resulting five distinct isolates were used as representatives of predominant culturable populations present in fractions F1 and F3. The “loosely-attached” isolates from fraction F1 were designated F11, F12, and F13, while the “tightly-attached” isolates from fraction F3 were designated F31 and F32. These five isolates were cultured, harvested, and cryogenically stored for future use as described previously. It should be noted that the isolation methods used to obtain microbial isolates may have introduced a

culture bias. Even at one-tenth strength, nutrient broth may be considered a rich substrate medium, and its use may have inhibited the growth of highly sensitive oligotrophic

microorganisms.

26 Characterization of variably-attached microbial communities and isolates.

Assays were performed to characterize the structural and biochemical properties of

variably-attached bacterial communities and populations isolated by the soil elution

protocol. Standard biochemical assays included Gram staining, the bicinchoninic acid

(BCA) method of protein analysis (Sigma-Aldrich, Inc., 2004), and catalase tests. Cell

surface properties, including charge and hydrophobicity, were characterized using four

techniques: the microbial adhesion to hydrocarbons (MATH) assay, hydrophobic

interaction chromatography (HIC), electrostatic interaction chromatography (EIC), and

colloid titrations.

The Gram stain reaction forms an insoluble, intracellular complex of crystal violet

and iodine inside cells. This complex is alcohol-extractable in gram-negative bacteria but

not in gram-positive organisms, which have thicker cell walls and peptidoglycan layers.

The BCA determination of protein is a colorimetric method that first complexes protein to Cu+2 under alkaline conditions, then uses bicinchoninic acid to reduce the copper to a

purple-blue Cu+ complex. The absorbance is measured at 562 nm and is compared to that

of known protein standards (Sigma-Aldrich, Inc., 2004). The catalase test determines the

presence of catalase, an enzyme typically produced by aerobic and facultatively aerobic bacteria to destroy hydrogen peroxide, a toxic byproduct of respiration. Catalase positive

cells are indicated by the formation of bubbles within thirty seconds of placing a drop of

hydrogen peroxide atop a bacterial colony (Colome et al., 1986).

MATH assays. MATH assays are used to measure the relative surface

hydrophobicity of cells. Hexadecane was used as the hydrocarbon phase according to the

method of Sanin et al., (2003). Cell cultures to be tested were grown in high-nitrogen

27 BOD medium with yeast extract as the sole substrate. In most cases a single

concentration of 100 mg/L yeast extract was used, although certain tests used 0-1000

mg/L yeast extract to examine concentration effects. Cells were grown until late

exponential phase was reached, harvested by centrifugation at 10,000×g for 15 minutes,

and resuspended in pH 7.4 phosphate buffer. Three-milliliter aliquots of cell suspensions

were added to small round-bottom test tubes, and the initial optical absorbance (also

denoted herein as optical density, OD) values (ODinitial) were measured spectrophotometrically at 600 nm. Hexadecane (0.3 mL) was then added to each suspension and the tubes were vortex-mixed for two minutes, then allowed to settle for fifteen minutes, after which the final optical density of the mixture (ODfinal) was

measured. Hydrophobicity was defined by Equation 2.1:

⎛⎞OD− OD % hydrophobicity= 100⎜⎟initial final (Eqn. 2.1) ⎝⎠ODinitial

HIC and EIC. Hydrophobic interaction chromatography and electrostatic interaction chromatography were performed according to the method described by van

Schie and Fletcher (1999). Cells to be tested were harvested from late exponential phase liquid cultures by centrifugation, washed twice with sterile 10 mM phosphate buffer at pH 7.4 (buffer was augmented with 4 M sodium chloride in HIC tests), and resuspended in fresh medium to give an optical density (600 nm) of 0.7 – 1.0. HIC and EIC columns were prepared using Pasteur pipettes plugged with sterile glass wool. The columns were rinsed with 5 mL of 95% ethanol and then augmented with 1 mL of control resin or exchange resin, which was held in the column by the glass wool. HIC tests used

® ® hydrophobic Octyl Sepharose CL-4B resin with Sepharose CL-4B resin as the control.

® ® EIC assays used DEAE Sepharose CL-6B as a control and DEAE Sepharose CL-6B as

28 an anion exchanger (Table 2.1; all resins were obtained from Sigma Chemical, St. Louis,

MO). Once placed in the columns, resins were washed with 5 mL of buffered media.

Finally, 0.3 mL aliquots of prepared cell suspensions were dispensed into the tops of the

Pasteur pipette column, allowed to equilibrate statically with the resin for 15 minutes,

drained, and then eluted from the column with 2 mL of fresh buffer. Carbon- and

nitrogen-free media were used in cell preparation and equilibration steps to avoid errors

originating from electrostatic effects (Sanin et al., 2003). The effluent from columns,

comprised of cells and buffer, was collected from each test and measured for optical

absorbance at 650 nm. Hydrophobicity and surface charge for the HIC and EIC tests,

respectively, were expressed as the difference between the percentage of cell retention in

the exchange column and the one in the control column (Equation 2.2).

100()OD− OD Retention of cells, R(%)= initial final (Eqn. 2.2) ODinitial

Table 2.1. Media and resins used in HIC and EIC. Control resin Test Equilibrium buffer Exchange resin (Sigma Chemical) 4 M NaCl in 10 mM HIC: Hydrophobic resin: phosphate buffer, Sepharose CL-4B hydrophobicity Octyl Sepharose CL-4B pH 7.4 EIC: 0.2 M phosphate Anion exchange resin: Sepharose CL-6B surface charge buffer, pH 7.4 DEAE Sepharose CL-6B

Colloid titrations. A colloid titration method (van Damme et al., 1994) was used

to determine the total negative charge of the cell surfaces, rather than the relative value

measured by EIC. Dextran sulfate sodium salt (average molecular weight 500,000,

Fisher Scientific) and low molecular weight Cat-Floc (poly[diallyldimethylammonium

chloride], Aldrich) were used as the standard polyanion and polycation, respectively.

The charge of the polyanion was determined by measuring the sodium concentration in a

29 standard dextran sulfate solution using atomic absorption spectroscopy; the charge of Na+ equals the negative charge of sulfate moieties in the compound. The charge of dextran sulfate used in colloid titrations was determined to be 4.43 ± 0.65 meq/g. Titration of

Cat-Floc with a standard solution of dextran sulfate and 0.1% (v/v) toluidine blue indicator dye yielded a charge equivalent for the Cat-Floc of 4.00 meq/g.

Colloid titrations were performed by mixing 20 µL of 0.1% (v/v) toluidine blue with 5 mL of cell suspension in an acid-washed test tube, then adding 0.2% (w/v) Cat-

Floc solution until the original purple color transitioned to blue. Excess Cat-Floc equal to twice the original quantity was then added to ensure saturation of all negative sites on the cell surface. Back-titration was subsequently performed using 0.1% (w/v) dextran sulfate to reach a purple endpoint. The total surface charge of the 5 mL aliquot of cells was determined from the difference of the charge of added Cat-Floc and that of the dextran sulfate. Cell surface charge was normalized to protein concentration as determined from the bincinchoninic protein assay described above.

2.3 Results

Soil characterization. Soil samples used in this study had a pH of 3.58, a moisture content of 23.5 wt%, and a natural organic matter concentration of 5.11 ± 0.097 wt% (based on duplicate measurements). The number of aerobic heterotrophic colony- forming units per gram of dry soil (CFU/g) varied from test to test, as is reasonable for heterogeneous soil samples microbially enumerated using the plate count method. The

farm soil typically contained on the order of 4×105 CFU/g for the first-eluted fraction F1

(“loosely-attached” cells) and 4×107 CFU/g for the last-eluted fraction F3 (“tightly-

30 attached” cells). The colonies arising from fraction F1 showed a greater diversity of

colony morphologies and colors compared to elution fraction F3. Physical descriptions

of the five colony isolates used in this study are shown in Table 2.2; the five colony types

possessed distinct morphologies.

MATH assay for microbial elution fractions F1 and F3. It was expected that the elutability of microbial fractions F1 and F3 from soil would correspond to differences in cell hydrophobicity. This was confirmed by the results of microbial adhesion to hydrocarbon (MATH) assays, as shown in Figure 2.1. Cells isolated in the first-eluted fraction, F1, were less hydrophobic than cells from the last-eluted fraction, F3, across the entire range of yeast extract concentrations tested (0-1000 mg/L). Furthermore, the

hydrophobicity of fraction F3 varied little with substrate concentration, whereas that of

F1 did.

The maximum relative hydrophobicity of fraction F3, 75%, was measured at the

highest and lowest substrate concentrations tested (0 mg/L and 1000 mg/L yeast extract).

The minimum measured hydrophobicity (68%) for this microbial fraction occurred

following growth in 200 mg/L yeast extract. Statistical analysis showed that the

hydrophobicity of F3 did not vary significantly with substrate concentration based on a

low correlation coefficient r2 of 0.44 for linear regression analysis of relative

hydrophobicity versus substrate concentration (slope m=0.004). The hydrophobic surface

properties of F3 cells may have helped them to adhere to hydrophobic organic matter or

surface moieties present in the pasture soil from which they were extracted. Because

fraction F3 was a consortium of multiple species, it is also noteworthy that increasing the

substrate concentration did not shift the overall hydrophobicity. Either the species

31 predominance did not shift as a result of changing substrate concentration, or the major species present in fraction F3 exhibited a narrow range of hydrophobicities.

The hydrophobicity of fraction F1 showed a slightly higher correlation to

substrate concentration (r2 = 0.62, slope m = 0.019) than did consortium F3. Cells eluted

directly from soil (0 mg/L yeast extract) had a 50% relative hydrophobicity, while those grown in 500 mg/L yeast extract showed the maximum hydrophobicity, 63%.

Hydrophobicity at 50 mg/L yeast extract was not considered in this analysis because of

the unusually large discrepancy between replicate tests, which may have indicated an

experimental error.

120 33.4±87.7 F1, Loosely-attached F3, Tightly-attached 100 68.9±20.4 72.8±2.1 74.8±0.7 80 75.0±0.0 67.5±2.3 61.7±8.2 61.3±1.8 62.5±1.2

60 50.0±0.0

40 Hydrophobicity (%) Hydrophobicity

0 0 50 200 500 1000

Yeast extract concentration (mg/L)

Figure 2.1. Relative hydrophobicity, based on the MATH assay, of variably-attached microbial fractions eluted from soil and grown to late exponential phase in yeast extract medium. A yeast extract concentration of zero indicates that cells were eluted from soil and tested directly, without substrate addition. Data at 50 mg/L substrate show large errors and were not used in analyses.

Gram staining and catalase activity of colony isolates from variably-attached

microbial fractions. Gram staining of consortium F1 revealed the presence of both gram

32 positive and gram negative cells, while consortium F3 showed only gram negative

bacteria. The five unique colony isolates extracted from these two parent consortia were exclusively gram negative (Table 2.2). The three “loosely-attached” isolates F11, F12, and F13 were catalase-positive, while F31 and F32 were both catalase-negative.

Table 2.2. Biochemical and morphological characterization of five variably-attached microbial isolates eluted from soil. Isolates from the initial elution Isolates from the final consortium, F1 elution consortium, F3 F11 F12 F13 F31 F32 Gram stain negative negative negative negative negative Catalase test positive positive positive negative negative color: white yellow white white white Colony form: punctiform punctiform circular circular irregular morphology* elevation: convex pulvinate flat convex flat Form Elevation *Graphical depiction of morphologies :

Cell hydrophobicity and charge of colony isolates from variably-attached microbial fractions. The five microbial isolates previously characterized through Gram stains and catalase tests were assessed further using hydrophobic interaction chromatography, electrostatic interaction chromatography, and colloid titrations to compare cell surface hydrophobicity and charge. The results of these three assays are presented in Table 2.3 and in Figures 2.2 to 2.4.

Although the previously-described MATH assays demonstrated that the bacterial consortium obtained from soil elution fraction F1 was less hydrophobic than that obtained from fraction F3, HIC tests showed this behavior was not necessarily true for each isolates obtained from the two fractions. HIC results for five individual microbial isolates cultured from F1 and F3 demonstrated that the isolates possessed unique

33 hydrophobicities that were not necessarily similar to those of the “intact” eluted microbial consortia from which they were derived (Table 2.3 and Figure 2.2). For example, among the five tested isolates, F11 and F12 had the largest HIC hydrophobicities, 56% and 73% respectively. However, these isolates originated from elution fraction F1, which according to MATH assays was less hydrophobic than fraction F3. This disparity may be explained by the effect of population density on the contribution of a single species to the overall hydrophobicity of a mixed culture; for instance, it is possible that isolate F13, which had the lowest measured HIC hydrophobicity (25%), predominated in the F1 consortium. Its low hydrophobicity and presumed populousness could explain why F1 was the less hydrophobic elution fraction. Similarly, isolate F32 (37% HIC hydrophobicity) may have prevailed in fraction F3, reducing the contribution of isolate

F31 (26% HIC hydrophobicity) and making fraction F3 more hydrophobic. Verification of these explanations would require species-level analysis of the F1 and F3 consortia.

Table 2.3. Relative hydrophobicity and surface charge of five microbial isolates extracted using serial soil elution. HIC-based Colloid titration- EIC-based negative relative based negative cell Colony isolate relative surface hydrophobicity surface charge charge (%) (in millionths of (%) mEq/mg protein) F11 56.08 ± 13.58 11.39 ± 4.75 0.116±0.090 “Loosely-attached” isolates from initial F12 72.97 ± 56.93 59.06 ± 45.60 0.583±0.187 elution fraction F1 F13 24.54 ± 16.66 20.25 ± 4.26 0.059±0.051 “Tightly-attached” F31 26.24 ± 5.48 53.82 ± 14.26 0.126±0.130 isolates from final elution fraction F3 F32 36.69 ± 11.27 51.35 ± 4.89 0.079±0.058 mEq = milliequivalent of charge

34 140 F12

120

100

80 F11

60 F32 F13

Hydrophobicity (%) Hydrophobicity 40 F31

Figure 2.2. Relative cell surface hydrophobicity of “loosely-attached” colony isolates F11, F12, and F13, and of “tightly-attached” colony isolates F31 and F32, as measured by hydrophobic interaction chromatography (HIC).

Colloid titrations and electrostatic interaction chromatography produced estimates of the relative negative surface charge of colony isolates. The results from these two methods were generally consistent with each other. From Table 2.3 it is seen that F12 was the most negatively charged of the five isolates (59% relative negative surface charge by EIC; 0.583 × 10-6 mEq/mg protein by colloid titration), followed by isolate F31

(54% relative negative charge by EIC, 0.126 × 10-6 mEq/mg protein by titration). In

comparison, isolate F13 had a low negative surface charge (20.3% by EIC, 0.06 × 10-6 mEq/g protein by titration). The isolates in order of decreasing negative surface charge

(Figures 2.3 and 2.4) were as follows:

EIC-based: F12 > F31 > F32 > F13 > F11 colloid titration-based: F12 > F31 > F11 > F32 > F13

35 120 F12 100

80 F31

60 F32

40 F13

Relative negative charge (%) 20 F11

Figure 2.3. Relative cell surface charge of “loosely-attached” colony isolates F11, F12, and F13, and of “tightly-attached” colony isolates F31 and F32, as measured by electrostatic interaction chromatography (EIC).

0.8

F12 0.6

0.4

0.2 F31 F11 milliequivalents per mg protein) milliequivalents Negative charge (inNegative millionths charge of F32 F13

0.0

Figure 2.4. Total negative surface charge of cells from “loosely-attached” colony isolates F11, F12, and F13 and from “tightly-attached” colony isolates F31 and F32, as measured by colloid titration.

Previously it was stated that the low hydrophobicity of isolate F13 could have contributed to the correspondingly low hydrophobicity of fraction F1. It is also possible

36 that cell surface charge played a role in this; isolate F12 (also derived from fraction F1) was relatively hydrophobic according to the HIC assay, but its large negative surface charge may have imparted some degree of hydrophilicity to fraction F1. Fraction F3 was

determined to be relatively hydrophobic according to the MATH assay, and this may be

explained in part by the hydrophobicity and small negative surface charge of one of its

constituents, isolate F32. Species-level microbial community profiling would be

necessary to verify whether F32 was dominant in elution fraction F3.

Cell surface charges could have played a role in the observed detachment

behavior of isolates F12 and F32. Isolate F12, which was extracted from soil in the first,

gentlest elution step, had the highest negative surface charge (Figure 2.3), making F12

cells likely to be repelled by negatively-charged clay and mineral surfaces in soil. In

comparison, isolate F32 was not recovered during the first soil extraction step but instead

was isolated from the third, most stringent step. It is reasonable to expect that it was

more tightly associated with the soil matrix. It possessed the second-lowest titratable

negative charge (0.079×10-6 mEq/g protein, Figure 2.4), which could result in

electrostatic attraction to soil minerals.

2.4 Conclusions

Vadose zone soil samples collected from an undisturbed grassy field site were

subjected to a serial elution procedure that successfully yielded culturable indigenous,

aerobic, heterotrophic bacterial communities and isolates for studies related to cell

surface properties and retention in soil. It was hypothesized that the “easily eluted”

community, comprised of cells extracted by buffered mineral medium in an initial elution

step, would differ in properties such as charge and hydrophobicity from the community

37 subsequently extracted from the same soil following the harsher techniques of sonication

and surfactant addition. Indeed, the first-eluted microbial consortium, designated F1, was significantly less hydrophobic than the last-eluted consortium, F3, based on a solvent partitioning assay. This behavior held true across a range of growth substrate concentrations from 0 to 1000 mg/L. The hydrophobicity of fraction F3 varied only slightly (about 6%) across this range of substrate levels, whereas that of fraction F1 varied more substantially (38%). This could potentially be explained by a greater substrate sensitivity among F1 microbial species, leading to more evident shifts in microbial community structure (and net hydrophobicity) compared to F3.

Strong cell partitioning into an organic solvent, such as that used in one of the hydrophobicity assays, would likely correspond to the tendency of cells to adhere to high molecular weight, hydrophobic natural organic matter (NOM) in soil. It is therefore reasonable to conclude that the bacteria comprising fraction F3 could have a greater ability to tightly partition into, or to sorb onto, the organic carbon present in their soil habitat. As a result, stronger extraction methods would be required for their detachment.

The hydrophobicity of bacterial isolates obtained from the F1 and F3 fractions did not uniformly correspond to that of their parent consortia. For example, two isolates from the less-hydrophobic F1 fraction showed very high relative hydrophobicity. This apparent inconsistency could potentially be accounted for through a consideration of the population density of each species within the F1 consortium. For example, if F1 were comprised largely of its third constituent isolate, F13, which was the least hydrophobic among those tested, then its low hydrophobicity makes sense.

38 Cell surface charge also varied among isolates from the same consortium, but in the case of at least two isolates, hydrophobicity and charge were strongly related to the elutability of the isolates from soil. The importance of these isolates to the overall behavior of their parent consortia would of course depend upon their respective population densities.

The five microbial isolates described in this chapter were used in subsequent work focused on growth kinetics and heavy metal tolerance and transformation. Strong evidence indicates that these five isolates are indeed unique cultures. This is based in part on differences in hydrophobicity, charge characteristics, colony morphology, Gram stain, and catalase reaction among the isolates.

CHAPTER 3. Growth of Soil Microbial Communities and Isolates on Organic

Substrates

3.1 Introduction

The growth of heterotrophic microorganisms is controlled in part by the

availability of carbon and energy substrates in the environment (Egli, 1995; Harms and

Bosma, 1997). In natural systems, substrate concentrations are often very low, and

bioavailability restricts bacterial growth (Egli, 1995). Even when substrates are plentiful

and accessible, however, compound transformation can be limited by the physiological

and kinetic properties of bacteria. Substrate affinity, enzyme expression, and toxicity can

all play a role in controlling the rate and extent of biodegradation processes. It is

important that laboratory studies not exclusively employ “standard” microbiological

practices and culture conditions that can mask the significance of these parameters.

Instead, research should recognize potential experimental biases and attempt to eliminate

them when possible.

This chapter describes the assessment of growth kinetics of the variably-attached

heterotrophic microbial communities and isolates described in Chapter 2. Batch

microcosms and organic substrates were used. It was hypothesized that the metabolic strategies exhibited by the cultures, for example a tendency towards relative copiotrophy

or oligotrophy, would be related to their cell surface properties and qualitative degree of

attachment in soil as defined by the elution procedure, with more oligotrophic behavior

attributable to more strongly-adhered cells. It is known that attached and unattached

40 microbial communities exhibit different metabolic activities, although the differences are

not always consistent between studies and it is uncertain whether the differences are

attributable to function or to community structure (Delong et al., 1993; Karner and

Herndl, 1992; Murrell et al., 1999; Acinas et al., 1999; Bidle and Fletcher, 1995; Delong

et al., 1993; Crump et al., 1999).

Substrate selection. Yeast extract and salicylic acid were used as representative

organic substrates. Yeast extract is the water-soluble portion of autolyzed yeast cells,

comprised primarily of carbohydrates, protein, and salts, with little if any lipid content. It

represents a labile, soluble, bioavailable substrate. Salicylic acid (2-hydroxybenzoic acid,

HOC6H4CO2H) contains a substituted aromatic ring and is known to biodegrade

aerobically through multiple pathways, such as the two shown in Figure 3.1 for its

conjugate base, salicylate (University of Minnesota Biocatalysis/Biodegradation

Database, 2006). Salicylic acid is an intermediate in the aerobic transformation of

polycyclic aromatic hydrocarbon (PAH) pollutants such as naphthalene, and it can also

induce PAH dioxygenases and thus stimulate the degradation of high molecular weight

PAHs such as phenanthrene, fluoranthene, pyrene, benz[a]anthracene, chrysene, and

benzo[a]pyrene (Chen and Aitken, 1999). It is generally considered to be labile (Liu et

al., 1995) and its metabolites readily enter the citric acid cycle and are further

biodegraded. It was selected for its characteristic aromatic functional group, its relevance to pollutant biodegradation pathways, its intermediate solubility of 2.228 g/L (Yaws,

1999), and its ability to be analyzed rapidly using spectroscopy.

Figure 3.1. Two pathways of aerobic salicylate biodegradation. Both catechol and gentisate can ultimately be mineralized through the citric acid cycle.

Models of cell growth. The growth cycle of a microbial population inoculated

into fresh liquid medium in a batch system typically includes a lag phase, an exponential

growth phase, a stationary phase in which the growth rate equals the death rate, and a

death phase during which viable cell numbers decrease. The growth rate of cells

reproducing in medium with a particular initial substrate concentration is expressed as the

change in biomass concentration X with respect to time, t (Equation 3.1),

dX = μ X (Eqn. 3.1) dt where µ is the specific growth rate constant. Biomass can be measured in terms of

colony-forming units per volume, optical absorbance, protein concentration, or other

biochemical parameters.

Equation 3.1 may be integrated and written as:

X =−μμ ln ttlag (Eqn. 3.2) X o where tlag is the time between inoculation and the beginning of exponential growth, and

Xo is the initial biomass concentration. A plot of ln(X/Xo) versus time has a slope equal to the specific growth rate constant for a particular set of conditions. The value of μ

42 depends on the microbial population under consideration, substrate type, substrate concentration, temperature, and other environmental parameters.

A batch microbial culture in which environmental conditions, including the initial concentrations of non-limiting nutrients, are held constant while the concentration of a single growth-limiting substrate is varied will typically exhibit a hyperbolic variation in growth rate constant with respect to concentration. This relationship is described by the

Monod model, which relates the specific growth rate at substrate concentration S to the maximum growth rate, µmax, that may be realized:

S μμ= (Eqn. 3.3) max + KSs The parameter Ks, the “half-saturation constant” or “affinity constant,” is the concentration of the limiting nutrient for which the specific growth rate constant is half of

µmax, its maximum value. The half-saturation constant roughly divides the concentration- growth relationship into a lower-concentration region in which growth is linearly dependent on S and a higher-concentration range in which µ is independent of S. It also reflects the general ability of a culture to uptake and utilize substrate, with a lower affinity constant indicating a more adept uptake mechanism.

Equation 3.3 may be linearized to facilitate the determination of µmax and Ks from experimental data. Taking the reciprocal of both sides of the equation yields Equation

-1 -1 3.4, for which a plot of µ versus S has a slope equal to Ks/µmax and a y-intercept equal to 1/µmax.

111K =+s (Eqn. 3.4) μμ μ maxS max The Monod model is a simple representation of common microbial growth behavior in batch systems. Not all microorganisms follow Monod growth patterns,

43 however, and a variety of other models have been developed to describe growth in batch systems (Panikov, 1995). Even when the Monod model describes growth adequately, its parameters are not necessarily static; they may vary with culture conditions (Kovárová-

Kovar and Egli, 1998). For example, one study found that the affinity for carbon substrate decreased and the maximum specific growth rate increased when bacteria isolated from seawater were transferred into substrate-rich media (Jannash, 1968).

Another study revealed that cells that were adapted to steady-state culture conditions exhibited decreased specific growth rates and glucose affinity when transferred to batch cultures with high glucose concentrations (Kovárová-Kovar and Egli, 1998).

At polluted sites characterized by temporal fluctuations in substrate type or concentration, both the impact of carbon sources and the effect of microbial habitat and

“lifestyle” (e.g., copiotrophy or oligotrophy) on the rate and extent of pollutant biotransformation could govern the outcome of bioremediation efforts.

3.2 Materials and Methods

Microcosm preparation. Microbial consortia and isolates were obtained from soil using the elution procedure described in Chapter 2. Based on elutability, consortium F1 was classified as loosely attached to soil, whereas consortium F3 was obtained using harsher physical and chemical extractions and was classified as tightly attached to soil.

Deep-frozen samples of these cultures were used to inoculate duplicate flasks containing

100 mL of high-nitrogen BOD dilution medium amended with substrate. Cycloheximide

(200 mg/L) was added to suppress the growth of fungi, which can have antagonistic interactions with bacteria (Mille-Linblom and Tranvik, 2003). Foam-stoppered flasks were incubated at 19°C and pH 7.0 with 100 rpm constant shaking, and growth was

44 monitored over time by recording the optical absorbance at 600 nm in 3 mL aliquots of sampled culture fluid.

Yeast extract and salicylic acid were used as growth-limiting substrates in separate experiments. Yeast extract was added from a sterile stock solution and was provided at initial concentrations of 50, 100, 200, 500, and 1000 mg/L. A salicylic acid stock solution was prepared from reagent-grade chemical (Aldrich), adjusted to pH 7.0 with 1.0 N sodium hydroxide, filter-sterilized, and used to provide initial concentrations of 40, 80, 160, 480, and 960 mg/L salicylic acid to microcosms. Dry weight analyses of growing cultures were performed to permit calculation of maximum yield coefficients from substrate utilization data.

Spectroscopic analysis. Salicylic acid concentration was determined by measuring absorbance at 225 nm using a UV-visible spectrophotometer (Milton Roy

Spectronic 1001 Plus) (Chao, 2001). A standard curve was prepared using salicylic acid stock solutions varying from 1.6 to 960 mg/L. Microcosm samples were passed through

0.22 μm syringe filters to remove cells prior to analysis.

3.3 Results

Growth of microbial consortia on yeast extract as a limiting substrate. Consortia

F1 and F3 both exhibited Monod kinetics (Figure 3.2) in yeast extract medium but possessed distinct growth parameters. F1, isolated from the least-stringent soil elution step, had higher values of both Ks and µmax compared to F3, a community extracted from the same soil using harsher ultrasonic and chemical techniques. F1 had a Ks value of 36.6 mg/L, three times higher than that of F3 (12.2 mg/L), and a maximum growth rate of

45 0.35 hour-1 compared to 0.3 hour-1 for F3. These growth rates corresponded to minimum doubling times of 1.98 and 2.31 hours, respectively.

The relatively “tightly-attached” community F3 may be described as more oligotrophic than F1, based on kinetic comparisons. Its lower Ks value indicates a tendency of the dominant F3 populations to favor lower-carbon environments, and it suggests a more efficient substrate uptake system in these organisms. Although F1 is also capable of using yeast extract across the entire concentration range tested, its affinity for this substrate is smaller and its growth is slower than that of F3 at substrate concentrations below about 200 mg/L. These results support the hypothesis that easily- eluted microorganisms tend to exhibit r-strategism or copiotrophy, while organisms that are more difficult to remove from soil tend to display K-strategism or oligotrophy.

0.4

µ 0.3

Loosely-attached F1 0.2 Tightly-attached F3 (1/hr)

F1: K s = 36.6 mg/L

0.1 µ max = 0.35 1/hr Specific growth rate, rate, growth Specific F3: K s = 12.2 mg/L

µ max = 0.30 1/hr 0 0 200 400 600 800 1000 Yeast extract concentration (mg/L)

Figure 3.2. Growth of two microbial consortia on yeast extract as a limiting carbon source. A least square fit of the experimental data was used to determine the Monod parameters Ks and μmax from these data. Error bars represent one standard deviation.

46 Growth of microbial isolates on yeast extract as a limiting substrate. The growth kinetics of the five previously-described colony isolates were assessed under conditions similar to those used to test the growth of microbial fractions F1 and F3. The isolates all exhibited Monod-type growth curves that, for low to moderate substrate concentrations of

0-500 mg/L, generally clustered together based on their parent consortium (Figure 3.3).

However, not all individual isolates possessed Monod parameters that conformed to those of parent consortia F1 and F3.

Isolates F31 and F32 displayed the largest observed growth rates over the entire substrate concentration range (with the exception of isolate F12 at 1000 mg/L yeast extract, which slightly exceeded the growth rate of F31); their respective µmax values of

0.27 hr-1 and 0.31 hr-1 were comparable to that of the parent consortium F3 (0.30 hr-1,

Table 3.1). However, only isolate F31 had a half-saturation constant Ks that approximated the value for its parent culture (13.4 mg/L and 12.2 mg/L, respectively).

Its counterpart, F32, had a substantially higher substrate affinity constant (Ks =

37.3 mg/L) and thus a lower overall affinity for yeast extract. Cell surface properties may have played a role in this. F32 had the second-lowest titratable negative surface charge of all isolates (Chapter 2) and was more hydrophobic than F31 based on hydrophobic interaction chromatography. These characteristics may have lowered its uptake efficiency for highly soluble organic compounds.

It was suggested in Chapter 2 that the overall hydrophobicity of consortium F3 could potentially be explained by a prevalence of isolate F32 over F31. The disparity in

Ks values between F3 and F32 does not necessarily contradict this suggestion.

Consortium F3 likely contained many more species than were characterized, and

47 microbial competition and other species interactions could easily have masked the kinetic behavior of a single organism in spite of its numerical majority. Consortium growth includes kinetic contributions from multiple interacting species, not all of which are necessarily populous or even culturable.

This could also explain why the F1 isolates grew more slowly than the F3 isolates even though the parent consortia displayed the opposite behavior. Isolate F11 possessed

-1 the lowest µmax value, 0.16 hr (minimum doubling time td,min = 4.33 hours), followed by

-1 isolate F13, 0.2 hr (td,min = 3.46 hours). Interestingly, two F1 isolates did display aspects of the copiotrophic traits exhibited by their parent consortium: F12 and F13 had significantly higher Ks values (107.2 and 59.8 mg/L, respectively) than the two F3 isolates (Table 3.1). Like the F1 consortium as a whole, these “loosely-attached” isolates had a lower affinity for yeast extract, as was hypothesized.

0.3 F32 (1/hr) μ F31 F12

0.2 F13

F11

Specific growth rate, rate, growth Specific 0.1

0.0 0 200 400 600 800 1000 Yeast extract concentration (mg/L)

Figure 3.3. Growth of five microbial isolates on yeast extract as a limiting carbon source. These data were used to determine the Monod parameters Ks and μmax. Error bars represent one standard deviation.

Table 3.1. Monod growth parameters for microbial consortia and isolates grown on yeast extract at 19°C. -1 minimum doubling Culture Ks, mg/L µmax, hours time td, hours Consortium F1 36.6 0.35 1.98 (first elution stage) isolate F11 33.9 0.16 4.33 isolate F12 107.2 0.27 2.57 isolate F13 59.8 0.20 3.46 Consortium F3 12.2 0.30 2.31 (final elution stage) isolate F31 13.4 0.27 2.57 isolate F32 37.3 0.31 2.24

Growth of microbial isolates on salicylic acid as a limiting substrate. Growth of the five microbial isolates on salicylic acid as the sole carbon source was studied in batch cultures. Plots of culture density (as optical absorbance at 600 nm, A600) versus incubation time are shown for isolates obtained from “loosely-attached” microbial consortium F1 (isolates F11, F12, F13; Figures 3.4, 3.5, and 3.6, respectively) and from

“tightly-attached” consortium F3 (isolate F32, Figure 3.7). Isolate F31, which was successfully grown on yeast extract in previous experiments, did not grow on salicylic acid at any of the concentrations tested. Although salicylic acid is a relatively labile pollutant analog, it is reasonable to expect that not all soil bacteria possess the requisite uptake systems or enzymes needed to instigate its transformation.

Among the three “loosely-attached” microbial isolates, F11 and F13 showed similar growth patterns (Figures 3.4 and 3.6). Both attained a maximum A600 of roughly

0.1, a low value that indicates generally poor growth, and both exhibited an inverse relationship between salicylic acid concentration (40-960 mg/L) and culture turbidity, likely indicating substrate toxicity. F13 appeared to be more sensitive to salicylic acid

49 toxicity; its growth shut down altogether at substrate concentrations between 160 and 480 mg/L.

Isolate F12 behaved much differently and was the only one of the five isolates to display Monod-like behavior. It revealed no adverse effects from salicylic acid; instead, its growth rate and biomass concentration increased with substrate levels (Figure 3.5).

The culture attained a maximum A600 value of 1.11, indicating strong growth at high substrate concentrations. Interestingly, this isolate had a lag period of nearly 40 hours before the onset of visible growth. It is likely that the enzyme(s) needed for substrate transformation were nonconstitutive in this organism.

Isolate F32, derived from the “tightly-attached” consortium, also had a lengthy lag phase, but in other respects it more closely resembled F11 and F13 in that its growth was impeded by increasing salicylic acid concentrations. In fact, the two isolates derived from “tightly-attached” consortium F3 were the most highly sensitive to salicylic acid toxicity. Isolate F31 did not grow at all (data not shown), while F32 grew only at the lowest salicylic acid concentration tested, 40 mg/L (Figure 3.7). F32 proved to be unique in its ability to utilize such a dilute level of salicylic acid; among the five microbial isolates, it achieved the highest culture density under these conditions (A600 = 0.18 after

183 hours for 40 mg/L substrate; Figure 3.8). In this respect, F32 possessed oligotrophic tendencies compared to F12, which did not grow at all at 40 mg/L salicylic acid but thrived in concentrations as high as 960 mg/L. From a remediation perspective, F32 would be valuable for its ability to achieve low residual “contaminant” concentrations.

However, the simple elution procedures commonly used in biodegradation research

50 would likely not isolate this microorganism, leading to flawed biotransformation measurements.

0.14 40 mg/L 0.12 80 mg/L 160 mg/L 0.10 40 mg/L 480 mg/L 960 mg/L 0.08

rbance at 600 nm 480 mg/L 0.06

0.04 960 mg/L 0.02 F11 culture absoF11 culture

0.00 0 102030405060708090 Time (hours)

Figure 3.4. Growth dependence of isolate F11 on salicylic acid concentration. Error bars represent one standard deviation.

1.4

1.2 40 mg/L 80 mg/L 1.0 160 mg/L 960 mg/L 480 mg/L 960 mg/L 0.8

480 mg/L 0.6

0.4 160 mg/L

F12 culture absorbance at 600 nm 0.2 40 and 80 mg/L

0.0 0 20 40 60 80 100 120 140 160 Time (hours) Figure 3.5. Growth dependence of isolate F12 on salicylic acid concentration. Error bars represent one standard deviation.

51 0.11

40 mg/L 80 mg/L 0.09 160 mg/L 480 mg/L 960 mg/L 0.07 40 mg/L

0.05 80 mg/L 160 mg/L

F13 cultureF13 absorbance at 600 nm 0.03 480 mg/L

960 mg/L 0.01 0 102030405060 Time (hours)

Figure 3.6. Growth dependence of isolate F13 on salicylic acid concentration. Error bars represent one standard deviation.

0.20

0.16

0.12

40 mg/L 80 mg/L 0.08

0.04 F32 culture absorbance at 600 nm

0.00 0 50 100 150 200 Time (hours)

Figure 3.7. Growth dependence of isolate F32 on salicylic acid concentration. Error bars represent one standard deviation.

52 0.2 0.179

0.16 0.125 0.12 0.093

0.08

0.039 0.04 0.013 Maximum absorbancenm at 600 0 F11 F12 F13 F31 F32

Figure 3.8. Maximum culture density (as optical absorbance) of the five isolates when grown in 40 mg/L salicylic acid. F12 did not grow significantly at this low concentration, but it exceeded the growth of the other isolates at higher substrate levels. Error bars indicate one standard deviation of duplicate experiments.

Growth of isolate F12 on salicylic acid. As previously noted, isolate F12 did not grow measurably in the presence of 80 mg/L or less of salicylic acid. According to the

Monod model μμ= S , growth on a labile substrate should occur as long as it is max + Ks S present at nontoxic levels. Microorganisms such as F12, however, may require a minimum or “threshold” substrate concentration, Smin, to induce the appropriate catabolic enzymes for organic compound biodegradation (Tros et al., 1996; Kovárová-Kovar and

Egli, 1998; Kovárová-Kovar and Egli, 1996) or for cell maintenance in the absence of growth (Kovárová-Kovar and Egli, 1998). For cultures that exhibit nongrowth behavior in the presence of biodegradable substrate, a modified Monod model (Boethling and

Alexander, 1979; Rittmann and McCarty, 1980; Schmidt et al., 1985; Sterkenburg et al.,

1984; Tros et al., 1996) is applicable:

()SS− μμ= min (Eqn. 3.5) max +− KSSS ()min

53 Both the Monod and the modified Monod models were used to obtain kinetic parameters for isolate F12 for the purpose of comparison. Figure 3.9 and Figure 3.10 show the ordinary Monod model with growth data for salicylic acid concentrations greater than 80 mg/L. The half-saturation constant Ks was 148 mg/L salicylic acid, µmax was 0.08 hour-1, and the minimum doubling time was 8.7 hours. Experimental data plotted with the modified Monod model are shown in Figure 3.11. This model yielded the same µmax but a slightly lower Ks value (103 mg/L salicylic acid) and a minimum substrate concentration Smin of 50 mg/L salicylic acid.

Isolate F12 grew more rapidly on yeast extract than on salicylic acid, as reflected by the µmax values for each substrate (Table 3.2). Interestingly, it had a greater affinity

(smaller Ks) for salicylic acid. Compared to the other isolates, F12 possessed relatively copiotrophic growth and uptake characteristics.

0.1

0.08 (1/hr) μ 0.06

0.04

0.02 F12 growth rate rate growth F12 0 0 200 400 600 800 1000 1200 Salicylic acid concentration (mg/L)

Figure 3.9. Monod growth curve of isolate F12 with salicylic acid as the sole carbon source. Error bars represent one standard deviation.

54 25

15 y = 1852.5x + 12.409

(hours) 2

μ R = 0.9728 1/

10 Isolate F12 Ks = 148.29 (mg/L) μmax = 0.081 (1/hr) 5 0 0.001 0.002 0.003 0.004 0.005 0.006 1/S (L/mg)

Figure 3.10. Lineweaver-Burk plot of the growth of isolate F12 on salicylic acid, used to retrieve the Monod half-saturation constant Ks and maximum growth rate µmax.

2000

Experimental data 1600 Predicted data

K s = 103.09 mg/L

1200 μ max = 0.08 (1/hr)

S min = 50 mg/L

800 Salicylic acid 400 concentration (mg/L)

0 0 0.02 0.04 0.06 0.08 0.1 Growth rate μ (1/hr)

Figure 3.11. Growth data for isolate F12 fit to the modified Monod kinetic model. Salicylic acid is the sole carbon source. Error bars represent one standard deviation.

Table 3.2. Kinetic parameters for isolate F12 on two substrates. Yeast extract Salicylic acid (Monod model) (Modified Monod model) -1 µmax, hour 0.27 0.08 td, minimum, hours 2.6 8.7 Ks, mg/L 107.2 103 lag time, hours 0 40

Extent of salicylic acid transformation. Although isolates F11, F12, F13, and F32 showed evidence of weak growth on salicylic acid, UV spectroscopic analyis revealed that only F12 substantially transformed this compound. Figure 3.12 shows initial and final substrate concentrations during a 160-hour incubation of F12. At the lowest concentration tested (about 47 mg/L), neither visible growth nor substrate loss was observed. However, approximately 91% of salicylic acid was transformed by the isolate when an initial concentration of 87 mg/L was provided, and 85% transformation occurred for an initial concentration of 225 mg/L. In these two cases, the residual salicylic acid levels were approximately 8 and 34 mg/L, respectively.

Growth yield coefficients for isolate F12 were calculated based on the measured dry weight of produced cells and the observed loss of salicylic acid. Maximum yield coefficients were 2.73±0.02 and 2.25±1.20 g dry cells▪g-1 salicylic acid for initial substrate concentrations of 87 mg/L and 225 mg/L, respectively.

250 224.7±14.1 F12-initial-0hrs F12-final-160hrs 200

150

100 86.9±0.4

47.2±0.3 49.3±0.6 50 34.3±1.1 Salicylic acid concentration (mg/L) concentration Salicylic acid 7.5±0.2 0

Figure 3.12. Transformation of salicylic acid by isolate F12. Error bars indicate one standard deviation.

56 3.4 Conclusions

The growth behavior of two bacterial consortia and five isolates was studied under different substrate conditions. Consortium F1 was qualitatively characterized as being weakly associated with soil particles and possessing less hydrophobic cell surface properties (Chapter 2) than consortium F3, described as more tightly soil-associated.

Batch microcosm experiments using 0-1000 mg/L of yeast extract, a labile, soluble substrate, revealed distinct Monod-type growth behavior for each consortium. F1 had a slightly larger maximum growth rate and a threefold larger half-saturation constant Ks than consortium F3. Although both cultures grew strongly without a lag phase on yeast extract, “loosely-attached” F1 had relatively copiotrophic traits– faster growth and lower substrate affinity– compared to “tightly-attached” F3. These results supported the experimental hypothesis relating physical habitat to growth kinetics.

The disparity in growth behavior was not uniformly reflected by microbial isolates obtained from the two consortia. Over nearly the entire range of yeast extract concentrations tested, the two F3-derived isolates, F31 and F32, grew faster on yeast extract than F1-derived isolates F11, F12, and F13. The measured µmax values for F31 and F32 were consistent with that obtained for their parent consortium (0.3 hr-1). In contrast, all three F1 isolates grew more slowly than their parent consortium. For example, the minimum doubling time of isolate F11 was 4.3 hours, more than twice that of consortium F1. Nevertheless, the F1 isolates possessed large affinity constants (34 –

107 mg/L) and thus mirrored aspects of the copiotrophic behavior found in their parent consortium.

57 Differences between the growth of consortia and their isolates may be explainable in terms of microbial community structure. Experiments assessed only a very limited number of isolates that were selected because they grew as colonies from one elution fraction but not the other. It is reasonable to expect that consortia F1 and F3 bore many other species that were not tested and perhaps not even culturable. These unidentified species need not have been present in large numbers to influence the kinetics of their parent consortia.

The second carbon source used in batch growth experiments, salicylic acid, was tested with the five microbial isolates from consortia F1 and F3. Isolate F31 was unable to use salicylic acid as an electron donor for growth. Isolates F11, F13, and F32 grew only sparingly on this compound and showed signs of substrate toxicity above 40 mg/L, the lowest concentration tested. Isolate F12 displayed the opposite behavior. Its growth rate and culture turbidity increased with salicylic acid concentration from an Smin of 50 mg/L up to 960 mg/L, the highest level tested. Despite its strong, copiotroph-like growth,

F12 experienced a 40 hour lag phase when inoculated from a frozen culture that had been raised on yeast extract. This lag indicated the possible involvement of nonconstitutive oxygenase enzymes in biotransformation.

Although the growth studies presented in this chapter are limited in the number of isolates and substrates tested, they demonstrate the great variability in microbial metabolic strategies present among soil bacteria. Variations in growth patterns, substrate utilization kinetics, and substrate toxicity are important considerations for designing and predicting the results of remediation strategies. Consider a hypothetical remediation effort attempting to use salicylic acid to induce PAH biodegradation (perhaps through

58 aerobic cometabolism) by an organism such as F12 in contaminated soil. A bioavailable salicylic acid concentration of at least Smin would accommodate the organism’s basal metabolism, but higher substrate levels would be necessary to support active biotransformation. As the target PAHs biodegraded and approached the minimum threshold concentration for the organism, remediation would slow and an alternate strategy would be required. In this example, the addition of salicylic acid to the system could be decreased to favor the emergence of organisms such as isolate F32 with high affinities for this inducing compound. During such a “polishing stage,” F32 would degrade the primary substrate and PAHs to even lower levels. If F32 were strongly soil- associated, as the elution procedure qualitatively indicated, it might have improved access to soil-sorbed PAHs (Barr and Aust, 1994; Cerniglia, 1992; Sutherland, 1992) and potentially achieve residual contaminant concentrations within regulatory requirements for the site.

The results described in this chapter were used in experiments assessing isolate behavior in the presence of heavy metals. As will be shown in Chapters 4 and 5, the five isolates possessed different tolerances to metals and were all capable of reducing chromium when grown on organic substrates. In an environment contaminated with comingled chromium and organic pollutants, metal biotransformation would likely depend strongly on microorganisms’ ability to utilize organic pollutants (or natural organic matter) at in situ concentrations. The organic compounds themselves would influence microbial community structure and activity. Clearly, a deeper understanding of physicochemical habitat and its effect on microbial community structure is essential for the prediction and improvement of engineered remediation strategies.

CHAPTER 4. Effect of Chromium on the Growth of Microbial Communities and

Isolates Derived from Soil

4.1 Introduction

This chapter describes a series of five experiments that were performed to assess the inhibitory effects of hexavalent chromium on soil cultures that had been previously characterized with respect to cell surface properties (Chapter 2) and growth on organic substrates (Chapter 3). The first three experiments focused on microbial consortia F1 and

F3, isolated from the first and last steps of the soil elution protocol, respectively. These experiments examined the impact of chromium on total biomass production and the growth rate of cells exposed to the metal throughout incubation, and on the death kinetics of stationary phase cells first exposed to the metal. The fourth experiment examined the impact of hexavalent chromium on individual microbial isolates obtained from consortia

F1 and F3. Although chromium was added in the hexavalent form in all tests and is referred to as Cr(VI) or Cr6+, subsequent experiments (Chapter 5) showed that all consortia and isolates reduced hexavalent chromium to the trivalent form. The last experiment in this chapter examined the chromium impact on isolates grown in simulated comingled wastes with salicylic acid.

4.2 Materials and Methods

Experiments assessing the impact of chromium(VI) on microbial consortia. Three experiments were performed to study the effects of chromium on consortia F1 and F3.

The first experiment exposed cells to chromium during the entire growth period to assess

60 its impact on biomass production. Aliquots of F1 and F3 were inoculated into duplicate foam-stoppered flasks containing 100 mL of high-nitrogen BOD water, 100 mg/L yeast extract, 50 mg/L cycloheximide, and 0, 30, 60, or 90 mg/L of hexavalent chromium added from a filter-sterilized stock solution of 14.71 g/L potassium dichromate, K2Cr2O7.

Flasks were shake-incubated at 100 rpm and 19°C for two weeks, at which time biomass was measured using the bicinchoninic acid (BCA) protein assay (Sigma Chemical Co.,

2005).

The second experiment complemented the first by assessing the impact of hexavalent chromium on the growth rate, rather than the biomass yield, of F1 and F3.

The two consortia were shake-incubated at 19°C and 100 rpm in high-nitrogen BOD medium with 100 mg/L sucrose (Difco) as the sole carbon source and 0, 5, 10, or 15 mg/L of hexavalent chromium. Growth was spectroscopically measured as the increase in optical absorbance of the cultures at 600 nm. Growth kinetics were determined using the Monod model as in Chapter 3.

The third experiment examined the effect of hexavalent chromium on the death kinetics of fully-grown, stationary phase cultures. Stationary phase was used to represent the metabolic state that might be expected of stable soil and sediment populations in the subsurface. At the start of the experiment, duplicate flasks containing chromium-free high-nitrogen BOD medium with 200 mg/L yeast extract and 200 mg/L cycloheximide were inoculated with microbial cultures. After approximately 40 hours, stationary phase was reached and heterotrophic plate counts were performed. Hexavalent chromium was then added to flasks at concentrations of 0, 5, and 25 mg/L. Total heterotrophic counts were again made after 121 and 192 hours of incubation to assess cell death.

61 Experiments assessing chromium(VI) impact on microbial isolates grown on yeast extract. The five previously-characterized microbial isolates obtained from consortia F1 and F3— designated F11, F12, F13, F31, and F32— were tested with hexavalent chromium in duplicate aerobic batch cultures. Cells were shake-incubated at 100 rpm and 19°C in 100 mL of neutral high-nitrogen BOD water with 100 or 500 mg/L of yeast extract as the primary substrate and sole carbon source. Potassium dichromate was added to provide hexavalent chromium concentrations of 0, 5, 20, 50, 100, or 200 mg/L. At various points during incubation, 3 mL aliquots were withdrawn from flasks and the optical absorbance was measured spectroscopically at 600 nm to monitor growth.

Experiments assessing chromium(VI) impact on isolates grown in simulated comingled waste with salicylic acid. Isolates F11, F12, F13, F31, and F32 were cultured in duplicate batch systems to assess the effect of chromium on cells’ ability to use salicylic acid as a sole carbon source. Media containing a heavy metal and an aromatic organic substrate was used to simulate a simple comingled aqueous waste. Cultures were shake-incubated at 100 rpm and 19°C in 100 mL of pH 7 high-nitrogen BOD water with

5 mg/L hexavalent chromium. Salicylic acid was provided at the concentrations that best supported individual isolate growth in chromium-free medium, as reported in Chapter 3

(Figures 3.4 to 3.7). These concentrations were 80 mg/L for F11, 160 mg/L for F12, and

40 mg/L for F13, F31 and F32. Growth was monitored spectroscopically at 600 nm.

4.3 Results

Impact of Cr(VI) on biomass production by consortia F1 and F3 in yeast extract medium. Exposure to hexavalent chromium at concentrations of 30, 60, or 90 mg/L during the entire growth period reduced the net biomass production of consortia F1 and

62 F3 in yeast extract medium (Figure 4.1). The percentage decrease in biomass was calculated using Equation 4.1,

X average biomass decrease (%) = (1−×C ) 100 (Eqn. 4.1) X 0 where XC is the final protein concentration produced in the presence of chromium concentration C, and X0 is the protein concentration produced in the absence of chromium. In the absence of chromium, culture F1 grew to a stationary-phase protein concentration of approximately 54 mg/L. Net protein production by this consortium dropped by 17% and 44% in the presence of 30 and 60 mg/L Cr6+, respectively (Figure

4.2). Biomass production decreased another 5% as chromium concentration increased from 60 mg/L to 90 mg/L (Figure 4.1). Similar behavior was observed for consortium

F3. This culture produced more protein than F1 in chromium-free yeast extract medium, yielding a stationary-phase concentration of 137 mg protein•L-1. Protein production dropped by about 26% and 38% in the presence of 30 and 60 mg/L Cr6+, respectively.

Unlike F1, no additional impact on biomass production was observed at a chromium concentration of 90 mg/L. Clearly, both cultures were negatively impacted by hexavalent chromium concentrations higher than 30 mg/L, although they were still able to grow in solutions containing as much as 90 mg/L Cr6+. Consortium F3 appeared to be more resistant than F1 to the toxic effects of chromium concentrations above 60 mg/L.

A first-order characteristic toxicity constant kc was used to compare biomass production by consortia F1 and F3 under the influence of chromium. Equation 4.2 describes a model relationship between chromium concentration C (mg Cr6+•L-1) and biomass, X (mg protein•L-1).

dX =−kX (Eqn. 4.2) dC C

63 Integrating this equation results in an inverse exponential relationship (Equation 4.3) that permits kc to be determined from a plot of the natural log of normalized biomass concentration versus chromium concentration (Figure 4.3).

X =− ln( ) kCC (Eqn. 4.3) X 0 The data for consortium F1 fit this model well, yielding a correlation coefficient of 0.96

2 and a characteristic toxicity constant kc of 0.0082 L/mg. Consortium F3 fit less well (r =

0.74), with a lower kc value (0.0062 L/mg) indicating greater chromium tolerance.

Characteristic toxicity 137.1 constant k (L/mg): 130 F3 c F1: 0.008 F3: 0.006 101.2 87.9 90 85.4

54.0 50 44.6

Protein concentration (mg/L) concentration Protein F1 30.1 27.1

10 0 306090 Cr(VI) concentration (mg/L)

Figure 4.1. Final biomass concentration (as protein) versus hexavalent chromium concentration for consortia F1 and F3 grown on 100 mg/L yeast extract and exposed to chromium during the entire two-week incubation period. Biomass was measured after stationary phase was reached. Error bars represent one standard deviation.

64 49.8 50 44.3

37.7 35.9 30 26.2

20 F3 17.4

10 0.0 F1 % Decrease in protein% Decrease concentration 0 0 306090 Cr(VI) concentration (mg/L)

Figure 4.2. Decrease in biomass production by consortia F1 and F3 with respect to hexavalent chromium concentration (another representation of Figure 4.1).

Cr(VI) concentration (mg/L) 0306090

-0.2 F3: y = -0.0062x r 2 = 0.7376 ) o F1: y = -0.0082x LN(X/X r 2 = 0.9562 -0.5 F1 F3 Linear (F1) Linear (F3)

-0.8

Figure 4.3. First-order toxicity model for the impact of 30, 60 and 90 mg/L Cr(VI) on the net biomass production (from Figure 4.1) of microbial consortia F1 and F3. The characteristic toxicity constant kC (L/mg) was obtained from the slope of each linear fit..

65 Impact of Cr(VI) on the growth rate of consortia F1 and F3 in yeast extract medium. Cultures F1 and F3 were inoculated into sucrose media containing 0, 5, 10, or

15 mg/L of hexavalent chromium to establish the effect of the metal on the specific growth rate, µ. Although these two cultures survived chromium concentrations of up to

90 mg/L (Figure 4.1), negative impacts on their growth were discernable at much lower levels (Figure 4.4). Both F1 and F3 showed slight declines in growth rate for chromium concentrations between 5 and 15 mg/L. However, F1 showed a more negative impact overall because its growth rate in a metal-free sucrose solution was twice that of F3. The first-order chromium-dependent decrease in growth rate can be represented as kµ and determined using an expression analogous to Eqn. 4.3. The values of kµ , obtained from a plot of the logarithm of normalized growth rate versus chromium concentration (Figure

4.5), were 0.104 L/mg for F1 and 0.066 L/mg for F3, showing that, as in the case of biomass production, F1 was more sensitive to growth inhibition by chromium than was

F3.

0.04

0.034 F1 0.03 F3 (1/hr) μ 0.02 0.015 0.015 0.012 0.014 0.01 0.008 Growth rate rate Growth 0.008 0.005 0.00 0 5 10 15 Cr(VI) concentration (mg/L)

Figure 4.4. Growth rate of consortia F1 and F3 in the presence of low concentrations of hexavalent chromium (up to 15 mg/L). The primary substrate was 100 mg/L sucrose, and growth was measured spectroscopically using optical absorbance at 600 nm.

66 Cr(VI) concentration (mg/L) 0 5 10 15

-0.1

-0.5 F3: y = -0.066x R 2 = 0.8989 ) o μ / μ -0.9 LN (

-1.3 F1 F1: y = -0.1035x F3 R 2 = 0.9088

-1.7

Figure 4.5. Normalized growth rate µ versus hexavalent chromium concentration (0 - 15 mg/L) for microbial consortia F1 and F3 in sucrose medium. The data in this figure are replotted from Figure 4.4. The term µ represents the growth rate constant at a given chromium concentration, and µo represents the growth rate constant in chromium-free medium. The decrease in first-order decrease in growth rate with respect to Cr(VI), termed kμ, was obtained from the slope of linear fits: 0.104 L/mg for culture F1 and 0.066 L/mg for F3.

Impact of Cr(VI) on the death kinetics of consortia F1 and F3 in yeast extract medium. Cultures of F1 and F3 were grown to stationary phase in 200 mg/L yeast extract medium, enumerated with respect to total heterotrophs, and then exposed to 5 or 25 mg/L of hexavalent chromium for 121 and 192 hours (0.72 and 1.14 weeks). A first-order death model was applied to the data using Equation 4.4,

dX =−kX (Eqn. 4.4) dt d where X is biomass concentration, measured in this experiment as colony forming units per mL (CFU/mL), and kd is the death rate constant. Integration of Eqn. 4.4 results in a linear equation (Eqn. 4.5) that enables the death rate constant to be obtained from the slope of a plot of normalized biomass versus time, as in Figure 4.6 and Table 4.1.

67 X =− ln( ) ktd (Eqn. 4.5) X 0 As Table 4.1 illustrates, the death rates of cultures F1 and F3 were low in the absence of chromium but approximately doubled in the presence of 5 mg/L Cr6+.

Increasing the chromium concentration from 5 mg/L to 25 mg/L did not increase the death rate for either culture. It appears that small concentrations of chromium do have a negative impact on the death of stationary-phase cultures, but this effect is not proportional to the chromium concentration.

Time (hours) 0 40 80 120 160 200 0

) -5 o LN(X/X

-10 F1-0 mg/L F3-0 mg/L

F1-5 mg/L F3-5 mg/L

F1-25 mg/L F3-25 mg/L -15

Figure 4.6 Decrease in viable cell counts X for stationary-phase cultures of consortia F1 and F3 that had been grown in 200 mg/L yeast extract medium and were subsequently exposed to 0, 5 or 25 mg/L Cr6+ (as shown in the legend). The first- order death constants kd were obtained from the slopes of linear data fits, as identified in Table 4.1.

68 Table 4.1. First-order death constants for stationary-phase cultures of consortia F1 and F3 exposed to hexavalent chromium. Death kinetics were determined from heterotrophic colony counts. F1 F3 6+ -1 2 -1 2 Cr , mg/L kd, hr r of fit* kd, hr r of fit* 0 0.036 0.85 0.029 0.73 5 0.077 0.96 0.063 0.96 25 0.078 0.97 0.063 0.99 *r: correlation coefficient

Degrees of inhibition by Cr(VI) to individual microbial isolates in yeast extract medium. Three microbial isolates (F11, F12, and F13) extracted from “weakly-attached” consortium F1 and two isolates (F31 and F32) from “tightly-attached” consortium F3 were tested for their growth in the presence of hexavalent chromium at concentrations of

5, 20, 50, 100, and 200 mg/L. The effect of primary substrate concentration on chromium toxicity was also evaluated in these experiments by using two concentrations of yeast extract, 100 mg/L and 500 mg/L.

None of the isolates grew in the presence of 200 or 100 mg/L chromium; the metal was consistently toxic and inhibitory at these levels, regardless of primary substrate concentration (Figures 4.7 and 4.8). Microbial growth was also prevented by 50 mg/L chromium, with the exception of cultures of F11 and F13, which developed slight turbidity only in the presence of 500 mg/L yeast extract. Despite the evident survival of

F11 and F13 cells in 50 mg/L Cr6+, their growth was extremely poor and not sustained.

Only at chromium concentrations less than or equal to 20 mg/L did exponential growth become possible. Growth rate was inversely related to chromium concentration and was dependent upon the primary substrate concentration. Four of the five isolates,

F11, F13, F31, and F32, were completely inhibited in media containing 20 mg/L chromium with 100 mg/L yeast extract; only isolate F12 was able to grow in this medium

69 at a rate of 0.04 hr-1 (Figure 4.7 and Table 4.2). At a yeast extract concentration of 500 mg/L, however, all five isolates grew in the presence of 20 mg/L Cr6+ with rates ranging from 0.11 hr-1 (F32) to 0.04 hr-1 (F31) (Figure 4.8). Thus, substrate-rich media appeared to mitigate the effects of chromium toxicity.

The lowest chromium concentration tested, 5 mg/L, had relatively little negative impact on most of the isolates, with growth rates approaching those for cells in chromium-free medium at either yeast extract concentration. In fact, isolate F32 showed no inhibition at all by 5 mg/L Cr6+ in 100 mg/L yeast extract; it grew faster in the presence of this low concentration of metal than in yeast extract alone. Only isolate F31 showed evidence of substantial toxic effects at this chromium concentration, with a decrease in growth rate of 82% in 100 mg/L yeast extract and 40% in 500 mg/L yeast extract. Again, medium rich in yeast extract appeared to mitigate chromium toxicity.

Relationships between substrate affinity and Cr(VI) tolerance by microbial isolates in yeast extract medium. Affinity for the primary substrate, yeast extract, was generally negatively correlated with chromium tolerance for the microbial isolates.

Substrate affinity is expressed by the Monod half-saturation constant (affinity constant)

Ks and was reported in Chapter 3 (Table 3.1) for the five microbial isolates under study.

Large values of Ks indicate a low affinity for a particular substrate. Chromium tolerance may be expressed as µ/µo, the ratio of a culture’s growth rate constant in the presence of chromium (µ) to its growth rate constant in chromium-free medium (µo). Increasing values of µ/µo correspond to increasing resistance to chromium toxicity.

This trend is shown in Figure 4.9, which depicts plots of chromium tolerance with respect to substrate affinity for three growth conditions: 1) 500 mg/L yeast extract with

70 20 mg/L Cr6+; 2), 500 mg/L yeast extract with 5 mg/L Cr6+; and 3) 100 mg/L yeast extract with 5 mg/L Cr6+. The first two conditions showed a strongly linear (r2 > 0.94) inverse relationship between substrate affinity and chromium tolerance (Figure 4.9, top and middle). Increasing values of Ks (i.e., decreasing substrate affinity) corresponded to increases in µ/µo (greater chromium tolerance). Isolate F12 was the only exception to this trend; it possessed the lowest affinity for yeast extract (Ks = 107 mg/L) but showed only moderate chromium tolerance, particularly at 20 mg/L Cr6+. The third growth condition produced results that were similar to those discussed above, although the correlation between metal tolerance and substrate affinity was low (r2 = 0.75) (Figure 4.9, bottom). Isolate F32 showed unusual tolerance of chromium in this case, growing at a faster rate than in the absence of chromium, and it was excluded from the linear fit.

Thus, greater substrate affinity generally corresponded to greater chromium sensitivity among the five microbial isolates. This was not true for consortia F1 and F3, however. F1 had a Ks value for yeast extract of 36.6 mg/L and therefore a lower substrate

affinity than F3, whose KS was 12.2 mg/L (Table 3.1). It might be expected to tolerate the metal better than F3. This was not the case, however; F1 was more sensitive to chromium toxicity with respect to biomass production and growth rate. As in the case of other microbial characteristics (cell surface properties or kinetic parameters, for instance), community structure may explain the disparity between the properties of bacterial isolates and their parent consortia. The consortia likely contained species other than the five isolates tested, and the contributions of these unknown species could have significantly impacted consortia properties.

71 Impact of Cr(VI) on the lag phase of microbial isolates in yeast extract medium.

Another consideration of these growth experiments was the effect of chromium on the onset of cell reproduction. Metal toxicity is known to extend the lag phase preceding exponential growth in bacterial cultures (Bopp and Ehrlich, 1988), and this was shown to be true for the five microbial isolates of this study. Figure 4.10 demonstrates that low chromium tolerance (as µ/µo) was generally accompanied by lag periods of up to 30 hours, whereas growth commenced immediately in cultures that experienced no obvious chromium toxicity.

0.5 100 mg/L yeast extract medium 0.4 0 mg/L

(1/hr) 5 mg/L μ 0.3 20 mg/L

0.2 Growth rate

0.1

0.0 F11 F12 F13 F31 F32

Figure 4.7. Growth rates of five microbial isolates in 100 mg/L yeast extract medium with hexavalent chromium at 0, 5, 20, 50, 100, and 200 mg/L. Growth did not occur above 50 mg/L Cr6+ and was evident in only one culture (F12) at 20 mg/L Cr6+.

72 500 mg/L yeast extract medium 0.3 0 mg/L 5 mg/L

20 mg/L (1/hr) μ

0.2

0.1 Growth rate Growth

0.0 F11 F12 F13 F31 F32

Figure 4.8. Growth rates of five microbial isolates in 500 mg/L yeast extract medium with hexavalent chromium at 0, 5, 20, 50, 100, and 200 mg/L. Growth did not occur above 50 mg/L Cr6+.

Table 4.2. Growth rates and lag phases of five microbial isolates in yeast extract medium with hexavalent chromium. F11 F12 F13 F31 F32 YE- YE- YE- YE- YE- YE- YE- YE- YE- YE- Cr(VI), 100 500 100 500 100 500 100 500 100 500 mg/L mg/L mg/L mg/L mg/L mg/L mg/L mg/L mg/L mg/L mg/L Growth 0 0.12 0.15 0.14 0.23 0.13 0.17 0.22 0.25 0.22 0.28 rate μ, 5 0.06 0.12 0.11 0.20 0.10 0.16 0.04 0.15 0.41 0.22 hr-1 20 0.00 0.06 0.04 0.05 0.00 0.09 0.00 0.04 0.00 0.11 Lag 5 30 0 0 0 0 0 30 20 0 0 phase, hr 20 n.d. 20 20 20 n.d. 0 n.d. 25 n.d. 0 YE = yeast extract; n.d. = no detectable growth

Figure 4.9. Relationships between the Monod affinity constant and chromium tolerance (expressed as µ/µo) for microbial isolates F11, F12, F13, F31, and F32. The parameter µo is the growth rate constant in yeast extract medium (100 or 500 mg/L, as indicated) without chromium, and µ is the value for the same medium with Cr(VI) (5 or 20 mg/L, as shown). Anomalous data points are labeled with circular or triangular symbols and are not included in the linear data fits.

Figure 4.10. Chromium tolerance (µ/µo as in Figure 4.9) versus the lag phase observed before the onset of growth of microbial isolates F11, F12, F13, F31, and F32. A single linear fit was applied to all data from the three different culture conditions identified in the graph legend.

Chromium tolerance and cell surface properties of microbial isolates. Chromium tolerance, µ/µo, was examined with respect to the negative cell surface charge of microbial isolates. An increase in the negativity of cell surfaces might be expected to enhance the electrostatic repulsion of hexavalent chromium, which in these experiments

2- was added as dichromate anion (Cr2O7 ). This in turn could improve microbial tolerance of the metal. Figures 4.11 and 4.12 showed little evidence that cell surface charge and chromium tolerance were correlated. As discussed in the next chapter of this dissertation, cell surface charge also did not correlate to chromium sorption to cells.

75 2.0 100 mg/L yeast extract & 5 mg/L Cr

1.5 500 mg/L yeast extract & 5 mg/L Cr 500 mg/L yeast extract & 20 mg/L Cr o μ

/ 1.0 μ

0.5

0.0 0 0.1 0.2 0.3 0.4 0.5 0.6

Negative titratable charge, millionths of mEq/mg protein

Figure 4.11. Chromium tolerance (µ/µo) versus negative cell surface charge of microbial isolates as determined by colloid titration.

2.0 100 mg/L yeast extract & 5 mg/L Cr 500 mg/L yeast extract & 5 mg/L Cr 1.5 500 mg/L yeast extract & 20 mg/L Cr o μ

/ 1.0 μ

0.5

0.0 20 30 40 50 60 70 80

Negative EIC-based charge, %

Figure 4.12. Chromium tolerance (µ/µo) versus negative cell surface charge of microbial isolates as determined by electrostatic interaction chromatography.

Inhibition of isolates in simulated comingled waste. The five microbial isolates were inoculated into synthetic comingled waste containing both chromium and salicylic acid at concentrations that were known to permit growth when present alone. Chromium

76 was used at 5 mg/L, and salicylic acid was provided at levels previously shown to be optimum for each isolate. It was expected that the combination of the metal and the organic would also support growth to some extent, although differences in isolates’ growth patterns were anticipated. Interestingly, none of the five isolates grew in the simulated comingled waste. Chromium may have interfered with the activity of oxygenase enzymes involved in salicylic acid biotransformation, or nonadditive toxic effects of the two substances may have compounded the liquid medium’s overall toxicity to completely inhibitory levels.

4.4 Conclusions

Two previously-characterized microbial consortia and five isolates derived from soil were studied to elucidate the impact of chromium on their growth behavior under variable substrate conditions. Net biomass production, growth rate, and death kinetics were examined in aerobic batch cultures inoculated with consortia F1 and F3, derived from the first and final steps of a soil elution process, with consortium F1 isolates F11,

F12, and F13 and F3 isolates F31 and F32.

Consortia F1 and F3 both experienced significantly decreased biomass production and growth rates when cultured in media with 100 mg/L of yeast extract or sucrose and with chromium at concentrations from 10-90 mg/L. In the presence of 90 mg/L Cr6+, for example, biomass production by F1 decreased nearly 50% while that of F3 decreased

36%. First-order models showed that consortium F1 was more sensitive to chromium inhibition over the entire range of metal concentrations assessed.

Microbial isolates F11, F12, F13, F31, and F32 were also negatively affected by chromium. At chromium concentrations higher than 20 mg/L, exponential growth did

77 not occur. Between 5 and 20 mg/L Cr6+, growth rate decreased with increasing chromium concentration, although metal toxicity was mitigated by the richness of the labile carbon substrate in culture media. Isolates’ affinity for the primary substrate, yeast extract, was also related to chromium tolerance; cells with less affinity for substrate

(higher Ks) were more resistant to metal toxicity.

Although all of the microbial isolates tolerated 5 mg/L of chromium with little adverse effect and could use salicylic acid as a growth substrate, microbiological media containing comingled chromium and metabolizable concentrations of salicylic acid completely inhibited the growth of all cultures. This result illustrated the difficulty of predicting growth and biodegradation in complex waste mixtures bearing organic and metallic components.

CHAPTER 5. Spectroscopic Studies of Chromium Biotransformation and Uptake

by Microbial Communities and Isolates

5.1 Introduction

An understanding of the distribution of biotransformation activity in the subsurface is crucial for effective implementation of remediation methods. In the case of heavy metals in soil, remediation strategies often attempt to stimulate reductive processes that convert metals from mobile, toxic forms to insoluble reduced species that are more likely to precipitate and become immobilized. Reduction can be induced abiotically through the introduction of reducing agents or biologically through the addition of nutrients, electron acceptors, and/or primary substrates that stimulate and support metal- reducing bacteria. Stable long-term metal sequestration is the goal in either case.

Unanticipated changes in subsurface microbiology or in soil and groundwater chemistry can lead to uncontrolled resolubilization and migration of metals.

This chapter focuses on chromium uptake and biotransformation by aerobic soil bacteria. These two processes were studied with respect to bacterial growth and cell surface properties. X-ray absorption fine structure (XAFS) spectroscopy was used to identify chromium binding and redox transformation without the need to disrupt cells.

XAFS includes both extended X-ray absorption fine spectroscopy and X-ray absorption near edge structure spectroscopy and provides information about element valence states, coordinating atoms, and other local structure information. The objectives of X-ray analyses were to determine whether cells change the valence state of sorbed chromium;

79 to assess whether the extent of chromium binding to cells corresponds to electrostatic and hydrophobic characteristics of cell surfaces; to identify functional groups to which chromium binds; and to determine whether cell growth phase affects the extent of chromium sorption.

The use of XAFS for characterization of metals in environmental samples.

Historically, metal speciation and interactions between metals and soils have been determined using wet chemistry analytical techniques. These methods are time consuming and radically change the chemistry of a sample. Advances in synchrotron radiation during the last ten years have provided alternative, non-destructive techniques by which to characterize metals in soils and sediments. Surface chemical processes such as metal sorption and precipitation reactions can be examined in near real-time. The most promising synchrotron technique used in recent years to characterize metal behavior in environmental samples is x-ray absorption fine structure. XAFS is a collective term for methods that identify x-ray absorption near and above the core-level binding energy of a selected atom (Newville, 2002). The local atomic structure of a material can be determined by measuring the absorption of x-rays as a function of their energy. XAFS is composed of two regimes: x-ray absorption near edge spectroscopy (XANES) and extended x-ray absorption fine structure spectroscopy (EXAFS). XANES is sensitive to formal oxidation state and coordination chemistry (e.g., octahedral, tetrahedral coordination) of the absorbing atom while EXAFS is sensitive to distances, coordination number, and species of the neighbors of the absorbing atom (Newville, 2002). EXAFS and XANES can be used to identify the redox state of a metal and the molecule encompassing it. X-ray absorption measurements are relatively straightforward,

80 providing the experimenters have available an intense and tunable x-ray source. The

Advanced Photon Source (APS) at Argonne National Laboratory is one such source and was used in this research.

XANES and EXAFS were first used in 1980 to characterize metals in environmental samples (Jaklevic et al., 1980). A benchmark 1993 study used XANES to quantify hexavalent chromium in cementitous samples with ±5% accuracy at detection limits approaching 10 ppm Cr6+ (Bajt, 1993). More recent studies have used EXAFS and

XANES to examine the reduction of aqueous Cr6+ to Cr3+ in magnetite-bearing soils from chromium contaminated sites (Peterson, 1997). As with all EXAFS and XANES work, the chromium characterizations were performed at ambient conditions, without extraction, dissolution, or concentration techniques that can result in analytical artifacts

(Gaillard, 2001). XAFS has been used to analyze soils for other metals, including copper, zinc, and nickel (Frenkel, 2001; Isaure, 2002; Roberts et al., 2002; Scheinost,

2002; Manceau, 2003). The Frenkel study showed definite structural differences between extractable and bound metals in soils. Manceau et al. (2003) demonstrated that nickel selectively associates only with iron and manganese oxides in soil, and Roberts et al.

(2002) showed that zinc speciation rather than total zinc concentration controls zinc desorption from soils. As these X-ray techniques are used and developed, they may become fundamental in determining appropriate remediation methods and required chemical and biological controls for a particular soil or sediment environment.

81 5.2 Materials and Methods

Bacterial isolates and mixed cultures that exhibited distinct cell surface properties

(Chapter 2) and growth characteristics (Chapter 3) were chosen for studies assessing their ability to uptake and transform chromium. The mixed cultures F1 and F3, isolated from the weakest and most stringent soil elution steps, respectively, and two colony isolates from each of these mixed cultures (“weakly-attached” isolates F12 and F13, and “tightly- attached” isolates F31 and F32) were used. The experimental procedures described below are graphically illustrated in Figure 5.1.

Biomass preparation. Deep-frozen glycerol stock cultures of each isolate and consortium were defrosted and used to inoculate growth flasks that were prepared in duplicate. Cultures were shake-incubated at 100 rpm and 19°C in high-nitrogen BOD medium with 500 mg/L yeast extract (Difco) at pH 7.0 until exponential phase (20 hours) or stationary phase (40 hours) was reached. Cells were then pelleted by centrifugation at

10,000×g for 15 minutes, washed of any remaining substrate by triple resuspension in sterile 0.9% NaCl solution at pH 7.0 (Panak et al., 2002), and then pelleted once more via centrifugation. The supernatant was removed and the wet pellet weight was determined.

Wet pellets were then resuspended in 10 mL of sterile 0.9% NaCl solution, after which 1 mL aliquots were removed for protein analysis.

Metal uptake experiments. The remaining 9 mL sample suspensions were exposed to trivalent or hexavalent chromium via the addition of filter-sterilized, concentrated metal solutions to provide a final concentration of 2 mM (approximately

100 mg/L) chromium metal. Hexavalent chromium was added as potassium dichromate

(K2Cr2O7), while trivalent chromium was added as chromium (III) nitrate nonahydrate

82 (Cr[NO3]3•9H2O). Both metal stock solutions were prepared in 0.9% NaCl at pH 7.0 using reagent-grade chemicals. Cell suspensions were shake-incubated with chromium at

100 rpm for two hours at 19°C, then centrifuged to recover cell pellets and supernatant.

The supernatant from each tube was expressed through a 0.22 μm syringe filter to remove any remaining cells, then analyzed for chromium concentration using atomic absorption spectroscopy (AA) with a certified chromium reference standard (Fisher

Scientific). Cell pellets were prepared for x-ray analysis by rinsing with sterile saline, resuspending in 5 mL aliquots of 20% (v/v) glycerol solution, transferring the aliquots into x-ray fluorescence (XRF) cups (Chemplex Industries, Inc.) covered with Kapton® film (DuPont), and then deep-freezing at -80°C. The frozen samples were stored overnight before express shipment on dry ice to Argonne National Laboratory (ANL,

Argonne, Illinois) for x-ray spectroscopic analysis at the Advanced Photon Source (APS).

Following x-ray analysis, the samples were removed from XRF cups, acid-digested according to EPA Method 3010A, and analyzed for total chromium using atomic absorption spectroscopy. This analysis was performed at Argonne by Dr. Laura Skubal

(ANL Office of Naval Research Project Office). Table 5.1 identifies the samples tested using AA and XAFS.

83 A. Colony isolates or consortia • Exponential-phase harvest • Stationary-phase harvest

B. Wash & pellet cells C. Determine wet weight

D. Resuspend in 10 mL saline

F. 9 mL incubated 2 hrs with Cr3+ or E. 1 mL for protein Cr6+. Total sample volume = 10 mL, analysis (10% of total containing 90% of total original original biomass & biomass and protein. protein)

G. Pellet cells

Supernatant Cells

H. AA for total Cr I. Preserve in 5 mL of 20% glycerol

J. XAFS

Digest

K. AA for total Cr

Figure 5.1. Graphical representation of the experimental analysis of chromium adsorption and transformation by microbial consortia and isolates. “AA” designates flame atomic absorption spectroscopy.

84 Table 5.1. Microbial samples analyzed for chromium uptake and transformation using atomic absorption spectroscopy (AA) and X-ray absorption fine structure (XAFS) spectroscopy.* A. “Loosely-attached” colony isolates from the first, least-stringent, soil elution stage F12 F13 Cr3+ Cr6+ Cr3+ Cr6+ stat. exp. stat. exp. stat. exp. stat. exp. 1 2 3 4 5 6 7 8 B. “Tightly-attached” colony isolates from the third, most-stringent, soil elution stage F31 F32 Cr3+ Cr6+ Cr3+ Cr6+ stat. exp. stat. exp. stat. exp. stat. exp. 9 10 11 12 13 14 15 16 C. Microbial consortium extracted from D. Microbial consortium extracted from the first, least-stringent soil elution stage the third, most-stringent soil elution stage F1 F3 Cr3+ Cr6+ Cr3+ Cr6+ stat. exp. stat. exp. stat. exp. stat. exp. 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 *Notes: • Cr3+ indicates chromium added as chromium (III) nitrate; Cr6+ indicates it was added as potassium dichromate. • “Stat.” and “exp.” indicate metal was added to stationary-phase and exponential-phase cultures, respectively. • Numbers are sample identifiers. Italicized, underlined numbers indicate samples that were analyzed for chromium uptake using AA but that were not tested using XAFS. All other samples were analyzed using both methods.

X-ray analyses. The state of chromium in thawed samples was determined by Dr.

Matthew Newville (Consortium for Advanced Radiation Science, The University of

Chicago) at ANL’s Advanced Photon Source (APS), a third-generation synchrotron radiation source. APS GSECARS Beamline 13BM was used with beamtime donated by

Dr. Laura Skubal. Samples were positioned at 45 degrees to the beam. The XAFS spectra were recorded in fluorescence mode as a function of incident x-ray energy from a water-cooled Si(111) monochromator by measuring the Cr fluorescence intensity using a

16-element Ge detector placed in a horizontal plane along the polarization vector of the synchrotron radiation.

85 Reagent grade chromium standards were tested to generate Cr(III) and Cr(VI) reference spectra and to verify that no interference or redox transformations arose from interactions between chromium and components of high-nitrogen BOD medium, saline solution, or glycerol solution used to cultivate, wash, and preserve cells. Table 5.2 identifies the chromium standards that were used.

Table 5.2. Chromium standards used to generate Cr(III) and Cr(VI) reference spectra for XAFS analyses. Metal valence ID Standard Phase state S1 distilled, deionized water control aqueous -- +3 S2 chromium nitrate, Cr(NO3)3 solid Cr 6+ S3 sodium chromate, Na2CrO4 solid Cr 6+ S4 potassium chromate, K2CrO4 solid Cr S10 1.33 g/L chromium nitrate in 20 vol% glycerol aqueous Cr3+ S11 0.49 g/L potassium dichromate in 20 vol% glycerol aqueous Cr6+ 33 100 mg/L total chromium as chromium nitrate, prepared aqueous Cr3+ in high-nitrogen BOD mineral medium at pH 7.0 34 100 mg/L total chromium as chromium nitrate, prepared aqueous Cr3+ in 0.9% NaCl solution at pH 7.0 35 100 mg/L total chromium as potassium dichromate, aqueous Cr6+ prepared in high-nitrogen BOD mineral medium at pH 7.0 36 100 mg/L total chromium as potassium dichromate, aqueous Cr6+ prepared in 0.9% NaCl solution at pH 7.0 37 100 mg/L total chromium as potassium dichromate, aqueous Cr6+ prepared in distilled, deionized water 38 100 mg/L total chromium as chromium nitrate, prepared aqueous Cr3+ in distilled, deionized water

Determination of biosorption kinetics. Bacterial isolates F11, F12, F13, F31, and

F32 were grown to late exponential phase in 500 mg/L yeast extract and harvested by centrifugation (15 minutes, 10,000×g). The cell pellets were washed twice with sterile

10 mM phosphate buffer (pH 7.0) and resuspended in additional buffer. An aliquot of each resuspension was removed and transferred to crucibles for determination of cell

86 concentration on a dry weight basis so that data could be normalized to biomass. The remaining volume of each resuspended culture was immediately used in kinetic experiments.

Biosorption tests were performed using sterile 50 mL centrifuge tubes. Bacterial suspensions were amended with 100 mg/L hexavalent chromium (as potassium dichromate, K2Cr2O7) and shake-incubated at 100 rpm at room temperature (19°C).

Abiotic controls were used to account for any chromium sorption to the walls of centrifuge tubes. Following incubation periods of zero minutes, 16 minutes, 40 minutes,

2 hours, 6 hours, 24 hours, and 48 hours, duplicate samples were centrifuged at 10,000×g for 15 minutes and expressed through sterile 0.22 μm syringe filters to recover the supernatant. A few drops of concentrated nitric acid were added to supernatant samples to prevent chromium precipitation before analysis. Chromium concentration was measured using atomic absorption spectroscopy, and observed decreases in metal content were attributed to metal sorption to cells.

5.3 Results

Spectral signatures for chromium standards. A number of standard chromium solutions were analyzed using XAFS to develop signature spectra to which XAFS analyses of biological samples could be compared. This was done not only to verify the quality of reagent-grade chromium compounds used in the experiments, but to determine whether chromium in these compounds was abiotically oxidized or reduced during exposure to chemical constitutents present in the aerobic media or in preservative solutions such as saline or glycerol. In the absence of observed abiotic reactions, redox transformations in biotic samples would be attributable to bacterial activity.

87 XAFS spectra for six selected chromium standards are shown in Figure 5.2. The experimentally-determined spectra (lines labeled “data” in the graphs) were approximated by fitting them with combinations of XAFS signatures of known chromium compounds. For example, Figure 5.2D shows a curve-fitted representation of the experimental data for Sample #36, potassium dichromate in 0.9% sodium chloride solution. The data is most closely reproduced by the spectrum that would arise from a solution of 35% potassium chromate and 65% sodium chromate, as indicated by the expression “0.35 K2CrO4 + 0.65 Na2CrO4.” Because both potassium chromate and sodium chromate contain only hexavalent chromium, the potassium dichromate in

Sample #36 remained in the hexavalent form; it was not abiotically reduced during the course of the experiment. An examination of the other standards reveals that abiotic chromium transformation was insignificant or absent during sample incubation, transport, and testing. Figures 5.2 A and B show spectra for samples of chromium(III) nitrate in high-nitrogen BOD medium and saline, respectively. Mathematical fits to the experimental data show a 90% match to the signature of Cr(NO3)3, with a slight contribution from the spectrum of Cr(VI) as sodium chromate. In other words, the chromium nitrate used in sterile standards and controls largely remained in the trivalent state; it did not spontaneously oxidize. Similarly, hexavalent chromium was not abiotically reduced in mineral medium, saline, or water (Figures 5.2 C, D, E), because

Cr(VI) standards could all be represented by the spectra of hexavalent chromium salts.

Figure 5.2. Chromium fluorescence XAFS spectra (fluorescence intensity in arbitrary units versus incident x-ray photon energy) for a number of trivalent and hexavalent chromium standards. The chemical expressions atop each graph represent the best fit to the data. Note that “CrNO3” is used to denote chromium(III) nitrate, Cr(NO3)3.

XAFS determination of chromium reduction by microorganisms. Bacterial consortia and isolates were incubated with trivalent or hexavalent chromium and analyzed intact to determine whether cell-bound chromium was oxidized, reduced, or unchanged compared to its original state. Figure 5.3 shows the spectra for Samples 1-24,

26, and 28, which are described in Table 5.1, and for hexavalent and trivalent chromium standards. Five conclusions can be drawn from the XAFS results.

89 First, all consortia and bacterial isolates showed evidence of cell-associated chromium, indicating that metal sorption occurred. Second, all of the spectra are narrowly aligned and closely match that of trivalent chromium (Figure 5.4), indicating that metal added as chromium(III) nitrate remained in the trivalent state, while metal added as potassium dichromate was always reduced to the less toxic trivalent form. The fit of the data suggests that more than 95% of the chromium in all analyzed samples existed in the Cr3+ state (Newville, 2005). Third, because analysis of cell-free controls and standards showed that abiotic chromium reduction did not occur, the two bacterial consortia and four isolates tested in this study were responsible for reducing chromium under aerobic conditions.

Fourth, chromium reduction was independent of the growth stage in which cells were harvested; cells collected during exponential growth and stationary phase both reduced the metal. Whether this was a fortuitous process or one used for metal detoxification or energy production is unclear. Soil from which these organisms were extracted did not exceed the “background” total chromium concentrations of 20 mg/kg reported for the Cleveland area (Jennings et al., 2002), and it is reasonable to expect that levels of bioavailable trivalent chromium (the only form that serves as an electron acceptor) were even lower, so it is unlikely that the organisms coupled chromium reduction to substrate oxidation as a primary mode of energy synthesis in their original habitat.

The fifth conclusion, based on interpretation of XANES results for the cell samples, is that the functional groups to which hexavalent chromium became bound were likely oxygen or water ligands, with the additional possibility of chlorine-containing

90 2+ moieties similar to [CrCl(H2O)5] (Newville, 2005). Thus, chromium initially added as trivalent Cr(NO3)3 dissociated from nitrate and recombined with alternate chemical groups, while chromium added as hexavalent K2Cr2O7 became reduced and reassociated.

These processes could have taken place inside cells, at the cell surface, or through extracellular reactions.

Figure 5.3. Cr fluorescence XAFS spectra (fluorescence intensity in arbitrary units versus incident x-ray photon energy) for chromium sorbed to cells from consortia F1 and F3 and isolates F12, F13, F31, and F32. Samples are described in Table 5.1. Chromium was initially added in the trivalent or hexavalent state, but the final spectra for all samples are indistinguishable and show the exclusive presence of trivalent chromium.

Figure 5.4. Chromium fluorescence XAFS spectra (fluorescence intensity in arbitrary units versus incident x-ray photon energy) for trivalent chromium standard, hexavalent chromium standard, and microbial samples containing cell-sorbed chromium (cell data). The spectra for microbial samples closely corresponded to that of Cr3+ and indicated that more than 95% of the sorbed chromium existed in the trivalent state.

Normalization of chromium sorption to biomass. Atomic absorption spectroscopy was used to measure total chromium concentrations (Cr3+ plus Cr6+) in cell-free supernatant (Figure 5.1, Box H) and in concentrated biomass (Figure 5.1, Box K) following two hours of culture exposure to aqueous chromium. Because cell concentrations varied among the incubated samples (Table 5.3), metal uptake was normalized to biomass, which could be expressed as dry cell mass or protein mass.

(Colony plate counts would have been impractical for this study.) Figure 5.5 shows the relationship between dry cell mass and protein mass for each of the isolates and consortia

92 tested. It is common for different cultures to possess distinct protein-dry cell ratios even when grown under identical culture conditions.

35 F1 F12

30 F13 F31 25 F32

20 F3 Protein mass (mg) mass Protein 15

10 0.04 0.08 0.12 0.16 0.20

Dry cell mass (g)

Figure 5.5. Relationships between protein mass and dry cell mass for the microbial consortia and isolates tested. These two parameters were used to normalize chromium uptake data to cell concentration.

93 Table 5.3. Metal uptake in cultures incubated with 2 mM (approximately 100 mg/L) hexavalent or trivalent chromium for two hours. Wet Dry Supernatant Cr Cell-sorbed Cr Growth Sample Protein Supernatant Cr Cell-sorbed Cr Culture1 Cr biomass biomass (mg/g dry (mg/g dry phase2 # (mg) (mg/g protein) (mg/g protein) (g) (g) cells)3 cells)4 Stat. 1 1.4105 0.282 43.39 5.331 2.864 34.66 18.62 Cr3+ Exp. 2 0.4544 0.091 24.65 7.926 2.542 29.22 9.37 F12 Stat. 3 1.3824 0.276 43.39 4.633 2.534 29.52 16.14 Cr6+ Exp. 4 0.3113 0.062 21.09 9.846 2.875 29.07 8.49 Stat. 5 0.6401 0.192 25.55 4.853 2.247 36.47 16.89 Cr3+ Exp. 6 0.4318 0.130 33.83 5.715 1.389 21.88 5.32 F13 Stat. 7 0.3661 0.110 22.39 5.032 1.165 24.69 5.72 Cr6+ Exp. 8 0.4953 0.149 34.07 5.479 2.766 23.89 12.06 Stat. 9 0.4454 0.098 36.00 10.973 2.260 29.87 6.15 Cr3+ Exp. 10 0.1625 0.036 19.13 10.886 2.027 20.35 3.79 F31 Stat. 11 0.4044 0.089 35.28 11.137 2.349 28.09 5.92 Cr6+ Exp. 12 0.2038 0.045 18.26 15.578 3.447 38.25 8.46 Stat. 13 0.2319 0.042 12.71 11.703 4.108 38.43 13.49 Cr3+ Exp. 14 0.5985 0.108 24.75 10.464 6.010 45.55 26.16 F32 Stat. 15 0.6848 0.123 28.29 5.289 1.971 23.05 8.59 Cr6+ Exp. 16 0.6036 0.109 28.77 4.916 1.620 18.57 6.12 continued on next page

Table 5.3, continued. Metal uptake in cultures incubated with hexavalent or trivalent chromium for two hours. Wet Dry Supernatant Cr Supernatant Cr Cell-sorbed Cr Growth Sample Protein Cell-sorbed Cr Culture1 Cr biomass biomass (mg/g dry (mg/g (mg/g phase2 # (mg) (mg/g dry cells)4 (g) (g) cells)3 protein)3 protein)4 Stat. 17 0.8003 0.160 44.20 7.115 4.295 25.77 15.56 Cr3+ Exp. 18 0.6583 0.132 35.44 6.522 3.627 24.23 13.47 F1, set 1 Stat. 19 0.7398 0.148 40.34 6.257 3.639 22.95 13.35 Cr6+ Exp. 20 0.5938 0.119 29.89 4.365 1.852 17.34 7.36 Stat. 21 0.6178 0.124 25.41 6.271 3.869 30.49 18.81 Cr3+ Exp. 22 0.4766 0.095 20.25 6.245 4.024 29.39 18.94 F1, set 2 Stat. 23 0.6473 0.129 24.98 3.855 1.877 19.98 9.73 Cr6+ Exp. 24 0.5022 0.100 19.03 3.526 1.399 18.61 7.38 Stat. 25 0.7606 0.152 45.80 7.661 4.559 25.44 15.14 Cr3+ Exp. 26 0.3837 0.077 19.58 2.980 1.297 11.68 5.08 F3, set 1 Stat. 27 0.4280 0.086 38.41 6.677 4.199 14.88 9.36 Cr6+ Exp. 28 0.1706 0.034 14.19 3.506 2.139 8.43 5.14 Stat. 29 0.4979 0.100 23.50 5.348 3.344 22.66 14.17 Cr3+ Exp. 30 0.1884 0.038 12.65 5.449 2.216 16.23 6.60 F3, set 2 Stat. 31 0.3806 0.076 17.84 3.115 1.918 13.29 8.18 Cr6+ Exp. 32 0.0995 0.020 10.43 4.291 2.187 8.18 4.17 1. F1 and F3 are consortia from first and third soil elution steps, respectively. F12 and F13 are isolates from F1. F31 and F32 are isolates from F3. 2. Stat. = stationary phase; Exp. = exponential phase. 3. Culture supernatant was obtained by centrifugation after two hours of incubation with chromium. The units refer to mass of chromium remaining in the supernatant normalized to the biomass (as dry cells or protein) that had grown in that liquid supernatant. 4. Cells were pelleted by centrifugation following two hours of incubation with chromium, then resuspended in 5 mL of an aqueous solution of 20% glycerol. As in the previous note, chromium mass is normalized to biomass.

Chromium uptake after two hours of exposure- results of the XAFS study. All tested microbial consortia and isolates that were incubated with 2 mM (100 mg/L) of chromium sorbed the metal to some extent (Figure 5.6), but more than 50% of added chromium remained in solution, regardless of the particular culture or its growth phase

(Figures 5.7 and 5.8). Metal added initially as chromium(III) nitrate remained in the -3 valence state during the course of the experiment, since previous work showed no biotic or abiotic chromium oxidation. Chromium added in the hexavalent state, on the other hand, was almost completely reduced to the trivalent form upon sorption by the microorganisms used in this study. Hexavalent chromium that was not sorbed was not analyzed via XAFS, but it could have been reduced in the solution phase as well.

Transient cell-metal binding or extracellular reduction reactions could explain such a phenomenon. Additional XAFS work would be necessary to prove its existence and to produce a clearer picture of the total contribution of biotic processes to chromium reduction.

The greatest chromium sorption, 6.01 mg Cr▪mg-1 dry cells (“mg/g”), occurred in an exponential-phase culture of isolate F32 exposed to 100 mg/L Cr3+ at pH 7 (Table 5.3 and Figure 5.6). This gram-negative isolate also substantially sorbed trivalent chromium when harvested in the stationary phase (4.11 mg/g). When chromium was initially added as Cr6+, substantially less metal sorbed to F32 (1.62 and 1.97 mg/g for exponential-state and stationary-state cells, respectively). The least sorption observed in this study, 1.17 mg/g, was attributed to a stationary-phase culture of isolate F13 exposed to Cr6+.

Microbial consortia F1 and F3 differed little in chromium uptake; their average sorption values, including the two chromium species and both growth states, were

96 3.07±1.16 and 2.73±1.17 mg/g, respectively. Consortium F3 showed a larger range in sorption values, from a maximum of 4.56 mg/g (in a stationary phase culture with Cr3+) to a minimum of 1.30 mg/g (in an exponential phase culture with Cr3+). In general, F1 and F3 were both able to sorb approximately 30% or more of the Cr(III) or Cr(VI) initially added to microcosms (Figure 5.8).

Chromium sorption versus growth phase in the XAFS study. Microbial consortia

F1 and F3 both showed greater chromium sorption in the stationary phase than in the exponential phase, regardless of whether the metal was added in the trivalent or hexavalent form (Figure 5.9). Metal sorption did not uniformly correspond to growth phase among the microbial isolates, however. For example, isolates F12, F13, and F31 all showed more extensive Cr3+ sorption in the stationary phase than in the exponential phase, and more extensive Cr6+ sorption in the exponential phase than the stationary phase; however, isolate F32 showed the opposite behavior.

Chromium sorption and cell surface properties in the XAFS study. Chromium sorption data were examined with respect to the cell surface charge and hydrophobicity

(Chapter 2) of microbial isolates F12, F13, F31, and F32, but no clear relationships were evident between cell surface characteristics and metal sorption. The three plots shown in

Figure 5.10 identify chromium as trivalent or hexavalent to distinguish the compound that was initially added to cultures; however, all sorbed chromium was ultimately reduced at the cell surface. Cells were studied in late exponential phase. Part A of the figure presents sorption with respect to cells’ negative colloid-titration charge. Most of the data points cluster around a surface charge of 0.1×10-6 mEq/mg protein and between

1 and 3.5 mg/g of sorbed chromium. Two outlying points at a much higher surface

97 charge of approximately 0.6×10-6 mEq/mg protein have a similar sorptive capacity, 2-3 mEq/g. Based solely on charge considerations, an increase in negative cell surface charge might be expected to repel hexavalent chromium and prevent its association with

2- cells, since aqueous Cr(VI) exists as anions such as dichromate (Cr2O7 ). However, this interference does not appear to have occurred. Similarly, negative charge measured via electrostatic interaction chromatography (Part B) does not correspond to metal uptake.

The same is true for cell surface hydrophobicity (Part C). It is possible that net charge and hydrophobicity are too general to be used as predictors of chromium sorption.

Specific binding sites may be involved in metal uptake, and the nature and concentration of these sites may not be reflected by EIC, HIC, or colloid titration methods.

18 16 Cr in supernatant (mg/g dry cells) 14 Cr in cell pellets (mg/g dry cells) 12 10 8 6 4 2

Cr content (mg/g dry cells) (mg/gdry content Cr 0 SESESESESESESESESESESESE

Cr(III) Cr(VI) Cr(III) Cr(VI) Cr(III) Cr(VI) Cr(III) Cr(VI) Cr(III) Cr(VI) Cr(III) Cr(VI)

F12 F13 F31 F32 F1 F3

Figure 5.6. A comparison of chromium sorbed to cell biomass versus that remaining in solution following two hours of incubation with 100 mg/L chromium. Data are normalized to the total amount of dry biomass in each culture. In all cultures, the majority of metal remained in solution. S: stationary phase; E: exponential phase.

Figure 5.7. A comparison of sorbed and aqueous chromium following two hours of incubation with 100 mg/L hexavalent or trivalent Cr and consortia F1 and F3 and isolates F12, F13, F31, and F32 in exponential and stationary phase. The dashed line represents equal percentages of chromium in the liquid and sorbed phases; more than half of the added chromium remained in solution under all test conditions.

Figure 5.8. Chromium partitioning between cells and supernatant for microbial consortia and isolates (a more detailed view of the data in Figure 5.7). Graphs A and B show systems originally provided with 100 mg/L trivalent chromium, and graphs C and D show systems initially amended with 100 mg/L hexavalent chromium, all at pH 7. “Stat” and “exp” indicate cells harvested in stationary phase and exponential phase, respectively.

Cr in cell pellets at stationary phase 6.01 6 Cr in cell pellets at exponential phase

5 4.43

4.11 3.92 3.61 4 3.45 3.12 2.86 2.88 3 2.77 2.46 2.54 2.53 2.35 1.79 2.25 2.26 2.00 2.03 1.97 1.90 2 1.62 1.39 1.17 Biosorbed chromium (mg/g dry cells) (mg/g dry chromium Biosorbed 1

0 F12- F12- F13- F13- F31- F31- F32- F32- F1-Cr(III) F1-Cr(VI) F3-Cr(III) F3-Cr(VI) Cr(III) Cr(VI) Cr(III) Cr(VI) Cr(III) Cr(VI) Cr(III) Cr(VI)

Figure 5.9. Chromium biosorption with respect to growth phase for four bacterial isolates and two consortia following two hours of exposure to 100 mg/L trivalent or hexavalent chromium at pH 7. Cr(III) and Cr(VI) were initially present as Cr(NO3)3 and K2Cr2O7, respectively. Cr(VI) was reduced to Cr(VI) during the incubation period and was sorbed almost exclusively in this valence state.

Figure 5.10. Chromium biosorption by isolates F12, F13, F31, and F32 with respect to: (A) titratable surface charge; (B) relative negative cell surface charge as measured by EIC; and (C) relative hydrophobicity as measured by HIC. Data are from a 2-hour incubation with 100 mg/L Cr(III) or Cr(VI) at pH 7.

102

Models of chromium biosorption kinetics. Metal uptake q in cells is represented by Equation 5.1,

()CCV− q = 0 t (Eqn. 5.1) 1000w where

q = uptake of metal by cells (mg/g dry cells)

C0 = initial concentration of soluble metal (mg/L)

Ct = metal concentration at time t (mg/L)

V = volume of liquid solution (mL)

w = dry mass of cells in each sample (g).

Two different kinetic models were applied to chromium biosorption data: the pseudo- first order Lagergren model and a pseudo-second order model. The pseudo-first order model (Antunes et al., 2003) represents the rate of sorption as being proportional to the number of unoccupied binding sites, and it is expressed by Equation 5.2,

dq =−kqq() (Eqn. 5.2) dt 1,ads e where

qe, q = biomass-normalized quantities of adsorbed metals on

the cells at equilibrium and at any time t, respectively

(mg▪g-1 dry cells)

-1 -1 k1,ads = Lagergren first-order rate constant (g▪mg min ).

Integrating Eqn. 5.2 subject to (q) =0 and t=0 to t=t results in Equation 5.3. The rate constant k1,ads is obtained from the slope of a plot of log(qe) versus time, using an estimated value of qe, the equilibrium sorption capacity.

103 k log(qq−= ) log q −1,ads t (Eqn. 5.3) ee2.303 A pseudo-second order model (Ho and McKay, 1998) was also used to assess biosorption data. This model assumes that the rate of metal sorption is proportional to the square of the number of empty binding sites, as in Equation 5.4,

dq =−kqq()2 (Eqn. 5.4) dt 2,ads e -1 -1 where k2,ads is the second-order rate constant (g▪mg min ). Integration and rearrangement of this equation using the boundary conditions t=0 to t=t and q=0 to q=q results in the linearized form shown in Equation 5.5. The term qe is determined from the slope of a plot of t/q versus time and k2, ads is calculated from the intercept.

t =+11 2 t (Eqn. 5.5) qk2,ads q e q e Chromium biosorption kinetics by microbial isolates in batch systems. Chromium biosorption kinetics were measured in batch systems with 100 mg/L hexavalent chromium, exponential-phase cultures of microbial isolates, up to 48 hours of incubation, and other conditions as used in the preceding two-hour sorption study. Abiotic controls used in these kinetic tests showed negligible chromium sorption to centrifuge tubes. In biotic systems, the pseudo-second order model better represented chromium sorption for all cultures than did the Langergren first-order model, as demonstrated in Figure 5.11 for isolate F11. Chromium sorption for the remaining microbial isolates (F11, F12 and F13 obtained from the initial soil elution step; F31 and F32 from the final elution step) is shown in Figures 5.12 through 5.15. The pseudo-second order kinetic parameters for each culture are compared in Figure 5.16.

104 The five microbial isolates showed distinct behavior in terms of the rate and extent of chromium sorption, with isolates F11 and F31 displaying behavior “extremes.”

“Weakly-attached” isolate F11 showed the fastest chromium uptake, with a pseudo-

-4 -1 -1 second order rate constant k2,ads equal to 5.2×10 g▪mg min , seventeen times higher than that of “tightly-attached” isolate F31, which showed the slowest chromium sorption.

Despite its relatively fast initial uptake of metal, F11 possessed the smallest model- predicted equilibrium metal load, 21.9 mg Cr▪g-1 dry cells. Isolate F31, on the other hand, showed the greatest predicted equilibrium sorption capacity, 44.1 mg Cr▪g-1 dry cells (Figure 5.16).

In addition to varying in their rate and extent of chromium uptake, isolates F11 and F31 differed in their growth in 500 mg/L yeast extract medium, which was used in both biosorption studies and previous growth studies. F11 had the slowest growth rate of all five isolates in this chromium-free medium, 0.15 hr-1, while F31 had the second- highest growth rate, 0.25 hr-1 (Chapter 4, Table 4.2). Thus, a comparison of the

“extremes” in isolate behavior shows that slow growth was accompanied by low equilibrium-based metal uptake, but a high initial rate of sorption. Faster growth was linked to greater chromium sorption capacity, but a slower initial rate of metal sorption.

None of the microbial isolates attained equilibrium during the first several hours of incubation. Table 5.4 compares the calculated equilibrium concentration qe of cell- sorbed metal to the extent of chromium sorption observed after 2 and 24 hours of incubation. Sorption was at most about 12% complete after two hours (e.g., isolate F13).

After 24 hours, it was as much as 95% complete (e.g., isolate F12). Thus, while the

XAFS-based study provided proof of chromium reduction by cells, the subsequent

105 longer-term kinetic experiments were necessary to estimate total chromium removal from the aqueous phase. Further work would be necessary to elucidate the specific nature and extent of chromium sorption and reduction, i.e., whether chromium binding to cells is permanent or whether dichromate anions can be bound, reduced, and desorbed as Cr3+, thereby liberating sorption sites for additional Cr6+ transformation.

Equilibrium chromium sorption and cell surface properties. Equilibrium-based concentrations of sorbed chromium (qe) were examined with respect to the cell surface properties of microbial isolates (Figure 5.17). As in the case of the 2-hour chromium sorption data (Figure 5.10), the equilibrium values are not distinctly related to cell surface charge or hydrophobicity. Increases in cell surface charge, measured by colloid titration or EIC, do not reduce the ability of cells to sorb hexavalent (anionic) chromium in solution.

25 Second-order sorption model parameters for F11:

K 2 = 0.00052 g/mg▪min

20 q e = 21.9 mg/g dry cells

10 Cr sorbed (mg/g dry cells) 5 average Cr sorbed (mg/g dry cells)

Cr sorbed using pseudo-second order model 0 0 240 480 720 960 1200 1440 Time (minutes)

Figure 5.11. Chromium sorption by microbial isolate F11 represented by a pseudo- second order model.

106 45 Second-order sorption model parameters for F12:

40 K 2,ads = 0.00017 (g/mg▪min)

q e = 33.1 (mg/g dry cells) 35

15 average Cr sorbed (mg/g dry cells) Cr sorbed (mg/g dry cells) 10 Cr sorbed using pseudo-second order model 5

0 0 500 1000 1500 2000 2500 3000 Time (minutes)

Figure 5.12. Chromium sorption by microbial isolate F12 represented by a pseudo-second order model.

30 Second-order sorption model parameters for F13:

K 2,ads = 0.00013 (g/mg▪min) 25 q e = 22.5 (mg/g dry cells)

10 Cr sorbed (mg/g dry cells) average Cr sorbed (mg/g dry cells)

5 Cr sorbed using pseudo-second order model

0 0 500 1000 1500 2000 2500 3000 Time (minutes)

Figure 5.13. Chromium sorption by microbial isolate F13 represented by a pseudo- second order model.

107 60

Second-order sorption model parameters for F31: 50 K 2,ads =0.00003 (g/mg.min) q e=44.1 (mg/g dry cells)

20 Cr sorbed (mg/g dry cells) dry (mg/g sorbed Cr 10 average Cr sorbed (mg/g dry cells) Cr sorbed using pseudo-second order model 0 0 500 1000 1500 2000 2500 3000 time (minutes)

Figure 5.14. Chromium sorption by microbial isolate F31 represented by a pseudo- second order model.

35 Second-order sorption model parameters for F32:

K 2,ads = 0.00014 (g/mg·min) 30 q e = 23.4 (mg/g dry cells) average Cr sorbed (mg/g dry cells) 25 Cr sorbed using pseudo-second order model

10 Cr sorbed (mg/g dry cells) 5

0 0 500 1000 1500 2000 2500 3000 Time (minutes)

Figure 5.15. Chromium sorption by microbial isolate F32 represented by a pseudo- second order model.

108

50 0.0006 44.1 0.00052 0.0005 40 33.1 0.0004 30 23.4 21.9 22.5 0.0003 20 (g/mg·min) (mg/g dry cells) dry (mg/g 2,ads 0.00017 e 0.0002 K q 0.00013 0.00014 10 0.0001 0.00003 0 0 F11 F12 F13 F31 F32 F11 F12 F13 F31 F32

Figure 5.16. Pseudo-second order chromium sorption model parameters for the five variably-attached microbial isolates F11, F12, F13, F31, and F32. Left: qe, the amount of chromium sorbed to cells at equilibrium. Right: k2,ads, the sorption rate constant.

Table 5.4. Chromium biosorption at equilibrium and after 2 and 24 hours of incubation for four microbial isolates. Microbial % sorption completed % sorption completed qe, equilibrium isolate during the first 2 hours* during the first 24 sorption, hours* mg▪g-1 dry cells F12 8.7 94.6 33.1 F13 12.3 76.4 22.5 F31 6.4 84.1 44.1 F32 6.6 36.0 23.4 *% of qe

109

Figure 5.17. The pseudo-second order equilibrium chromium sorption constant qe plotted against microbial isolates’ negative surface charge (via colloid titration), top; relative negative charge (via electrostatic interaction chromatography), middle; and hydrophobicity (via hydrophobic interaction chromatography), bottom.

110 5.4 Conclusions

Aerobic microbial consortia and isolates were tested for their ability to reduce and sorb chromium at an initial concentration of 100 mg/L in liquid media at neutral pH.

XAFS studies showed that all of the cultures examined— consortia F1 and F3 and isolates F12, F13, F31, and F32— were able to sorb chromium and reduce it to the less toxic, less soluble trivalent form. Because the cultures used in this study were originally isolated from noncontaminated soils that were low in chromium, and because chromium sorption and reduction occurred during the first two hours of incubation, it is likely that any enzymes involved in chromium uptake and transformation were either constitutive or quickly induced by chromium stress.

Chromium uptake likely occurred through interactions with oxygen- or water- bearing ligands, based on XANES results. Biotransformation of Cr(III) to Cr(VI) may have occurred fortuitously or for detoxification purposes, but probably not for energy production. It could not be determined whether chromium reduction was exclusively a cell surface-associated phenomenon, or whether it also occurred extracellularly. Abiotic chromium reduction did not occur under experimental conditions.

Biological chromium reduction was largely independent of microbial growth stage, occurring in all cultures regardless of whether they were harvested in exponential or stationary phase. Chromium sorption, on the other hand, was somewhat dependent on growth phase. During two-hour sorption tests, consortia F1 and F3 both sorbed chromium more extensively when harvested in the stationary phase than in the exponential phase. However, the five microbial isolates did not all follow this pattern.

111 Equilibrium biosorption was approached after about 24 hours of continued exposure to 100 mg/L chromium in 500 mg/L yeast extract medium. The maximum expected value of equilibrium chromium uptake for a culture was 44 mg Cr▪g-1 dry cells, predicted for isolate F31. Isolates’ cell surface properties, including negative charge or hydrophobicity, did not appear to control or correlate with the extent of chromium sorption. The kinetics of chromium biosorption varied, particularly among the five microbial isolates, and was well-described by a pseudo-second order model.

In this chapter, as in earlier chapters, microbial isolates extracted from soil were found to exhibit physiological behavior that was frequently very different from that of their parent consortia. Studying only a single “fraction” of soil microorganisms, for example a community that is easily-eluted from soil, could easily neglect many of the biotransformation traits that are most desirable for the remediation of heavy metals or organics. In situ remediation could potentially benefit from practices, such as primary substrate addition, that stimulate or favor organisms most capable of transforming and tolerating the contaminants of interest. Ex situ or reactor-based biotreatment would likely be even further enhanced because of the ability to control microbial habitat more closely.

112

CHAPTER 6. Summary and Recommendations

6.1 Summary

The bioremediation of comingled organic and metallic wastes is complicated by inherent differences in the biological and chemical transformation behavior of these two compound types. It is partly for this reason that few bioremediation studies have focused on comingled pollutants. The goal of this work was to examine the biotransformation of a heavy metal, chromium, with respect to bacterial metabolism and habitat. Habitat in this sense includes physical, chemical, and biological components: the association of bacteria with soil, the substrate conditions bacteria experience, and the presence of single or multiple populations in an environment. This research was focused exclusively on culturable heterotrophic aerobes collected from undisturbed, noncontaminated pasture soil. As in most bioremediation studies, the results of this work are site-specific but may have wider applicability.

The governing hypothesis was that the degree of soil attachment by bacterial communities can be used as a general indicator of chromium biosorption, reduction, and tolerance; bacterial surface properties; growth kinetics; and substrate affinity. Compared to weakly soil-associated communities, strongly-associated communities were expected to have slower growth and higher affinity for primary substrates, greater cell surface hydrophobicity, and greater ability to withstand the toxic effects of hexavalent chromium.

However, these community-level correlations were not expected to extend to bacterial isolates extracted from the communities. Rather, individual isolates were predicted to

113 exhibit traits distinct from their parent consortia. Thus, biotransformation behavior was hypothesized to be easier to predict at the community level compared to the species level.

Another aspect of the work was the identification of the metabolic capabilities of potentially-overlooked soil bacteria. A soil elution procedure with increasingly stringent physicochemical extraction steps was used to remove variably-attached bacterial communities from soil. The first elution fraction represented bacteria that would be detached from soil using “standard” microbiological practices. The final elution fraction represented organisms that would ordinarily not be removed from soil and whose contributions to net biotransformation would therefore be neglected. The study of this final elution fraction and of its constituent bacterial isolates represents a novel and significant aspect of the research.

A total of two bacterial consortia and five isolates were characterized and used in biotransformation experiments. Characterization involved an examination of colony morphology, Gram stain, catalase activity, cell hydrophobicity, and cell surface charge.

Based on these assays, it was apparent that the seven cultures were unique, and that the bacterial isolates may have represented different species. One aspect of the research hypothesis regarding hydrophobicity was shown to be true: the microbial culture obtained from the least-stringent elution step (consortium “F1”) was indeed less hydrophobic than the consortium extracted during the final, harshest step (“F3”). In the presence of yeast extract at 0-1000 mg/L, F1 had a relative hydrophobicity of about 50-

63% and F3 had a hydrophobicity of 69-75%. The isolates derived from these consortia did not uniformly conform to this behavior.

114 Growth studies were performed using yeast extract and salicylic acid as representative organic substrates. As hypothesized, consortium F1 showed somewhat

-1 faster growth and significantly lower substrate affinity (µmax=0.35 hr , Ks=36.6 mg/L)

-1 than consortium F3 (µmax=0.30 hr , Ks=12.2 mg/L) when cultured in yeast extract medium. Individual isolates showed the opposite behavior; F1 isolates grew in yeast extract more slowly than the F3 isolates. Unlike yeast extract, salicylic acid proved to be a relatively recalcitrant substrate. Only one of the five isolates, F12 (derived from F1) showed Monod-type growth when it was provided this compound as a sole carbon source. The other isolates grew poorly and showed an inverse relationship between salicylic acid concentration (40-960 mg/L) and biomass production. Again, there was no clear relationship between the isolates’ origin and their use of this model pollutant; while

F12 grew well, another F1 isolate (F13) showed poor growth and was inhibited completely at salicylic acid concentrations between 160 and 480 mg/L. One isolate from

F3 (F32) did have the unique ability to grow in salicylic acid at levels as low as 40 mg/L and therefore the potential to achieve low residual concentrations of this compound.

However, commonly-used soil elution protocols would likely not detect the presence and activity of this isolate.

Not only was salicylic acid relatively recalcitrant, it compounded the apparent toxicity of chromium. Microbial isolates that grew in the presence of yeast extract and chromium were completely inhibited when yeast extract was replaced with metabolizable levels of salicylic acid. This is one example of the sometimes nonadditive toxic effects of comingled waste mixtures.

115 Chromium tolerance was determined for bacteria cultured in yeast extract medium. The results both supported and refuted the hypothesis that metal resistance increases with increasing substrate affinity (e.g., decreasing Ks). The hypothesis was valid for consortia F1 and F3, but not for the microbial isolates. In fact, the resistance of isolates to 5 mg/L or more of chromium was strongly negatively correlated to primary substrate affinity. Again, this illustrates the differences between the metabolic characteristics of bacterial consortia and constituent isolates.

Studies of chromium biosorption yielded a number of significant outcomes. All of the cultures tested were able to sorb hexavalent chromium and reduce it to the less toxic, less soluble trivalent form. Chromium uptake likely occurred through interactions with oxygen- or water-bearing ligands, based on XANES results. It could not be established whether chromium reduction was exclusively a cell surface-associated phenomenon, or whether it also occurred extracellularly. Chromium reduction was largely independent of microbial growth stage, but its sorption appeared to depend on the growth stage of consortia F1 and F3 (but not on that of the isolates). Equilibrium biosorption was approached after about 24 hours of continued exposure to 100 mg/L chromium in 500 mg/L yeast extract medium, and it was well-represented by a pseudo- second order model. Maximum equilibrium sorption was determined to be about

44 mg Cr▪g-1 dry cells, a value predicted for isolate F31 (derived from consortium F3).

Isolates’ cell surface properties, including negative charge or hydrophobicity, did not appear to correlate with chromium sorption.

The results of this study provide an improved understanding of the distribution and activity of biodegradative organisms in the subsurface. Despite the soil-specific

116 nature of this work, it is clear that experimentally-determined values for organic or metallic compound biotransformation by bacteria must be qualified with an account of how cultures were obtained and used. It is also clear that microbial communities may be selectable in the subsurface through manipulation of nutrient concentrations and types.

Such a practice could encourage the prevalence of desirable microbial traits, such as metal resistance or the ability to achieve low residual contaminant concentrations, and would have important implications for the remediation of comingled wastes.

6.2 Recommendations for future work

Contaminated subsurface environments often exhibit complex, heterogeneous characteristics that complicate the prediction of remediation outcomes. Spatially- and temporally-dynamic pollutant and nutrient profiles, contaminant weathering, and microbial community structure are examples of the many variables that control the macroscopic and microscopic habitat of soil microorganisms and influence their biotransformation behavior. This in turn impacts the progress and extent of remediation.

Given the number of parameters that control bioremediation, particularly of comingled wastes, many avenues for future research are possible. One important consideration is the microbial ecology of subsurface environments. Soil elution procedures such as that used in this work lessen but certainly do not eliminate the experimental biases that arise from “standard” bacterial isolation methods. The microbial communities isolated in this research likely represented only a small fraction of bacterial biomass in soil. They were used in part because they were culturable under laboratory conditions. However, many organisms are either not culturable or so sensitive to

117 substrate concentrations, temperature, pH, or artificially-induced shifts in community composition that their activities may be obscured during microcosm experiments. An examination of intact microbial communities and their response to pollutant or substrate influxes would be a useful approach for estimating field-relevant biotransformation behavior. Molecular tools such as phospholipid fatty acid analysis or RNA- or DNA- based profiling could take into account both population density and species diversity.

Species-level information could facilitate the isolation and culturing of particular species for individual soil-based biotransformation studies, which in turn could suggest how best to manipulate subsurface conditions to stimulate desirable populations.

The research could also be expanded to address different combinations of heavy metals and organic compounds (e.g., polycylic aromatic hydrocarbons, chlorinated solvents, petroleum mixtures) in fresh or aged systems. Pollutant sequestration and chemistry both change over time in soils and sediments, and pollutant bioavailability is of enormous significance in bioremediation.

Metal-microbe interactions could be further elucidated through more detailed

XANES analysis of the concentrations and types of cell-surface functional groups involved in metal binding by individual bacteria species. Research measuring the stability constants for metal-organic complexes and the total metal sorption capacity in a particular subsurface zone or habitat (under controlled substrate conditions, for example) would also provide information useful for the design and implementation of remediation strategies.

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