Structure and Physiological Activity of Cyanobacterial Communities in a Freshwater Lake: A Three- Year Study Using 16S rRNA Gene Sequencing Analysis
Jorge W. Santo Domingo, NRMRL, [email protected]
Collaborators: Mark Bagley, Aabir Banerji, Jody Shoemaker, Joel Allen • DISCLAIMER: The views expressed in this presentation are those of the authors and do not necessarily represent the views or policies of the U.S. Environmental Protection Agency. Today’s talk:
• Identification of cyanobacterial species, their population dynamics and levels of activity in Lake Harsha using 16S rRNA gene sequencing approaches (2015-2017). We will data generate for 2018 samples.
Other Ongoing Projects:
• Development of 18S rRNA gene database to identify eukaryotic planktonic community. Generated and analyzed molecular data for three years (2015-2017).
• Use of regression models to determine the planktonic biota that is associated to microcystin blooms. Several bacterial (20) and eukaryotic (4) taxonomic groups and environmental factors (6) variables were identified. Identification of bacterial taxa that can be used in forecasting cyano bacterial blooms
• Evaluation of commercially available kits for the detection of microcystin, anatoxin, and saxitoxin in Lake Harsha and in different Ohio drinking water sources
• Molecular survey of cyanobacterial species in Ohio drinking water sources Lake Harsha, Clermont County, OH
• Watershed Area • 342 miles2 • Lake Uses • Recreational Activities • Drinking Water Source • Flood Prevention • Habitat for multiple species HAB Monitoring Tools
HF Physico-chemical Phototroph In-vivo Cyanotoxin Molecular Methods Wet Chemistry Fluorescence • Temperature • Toxicity Using DNA and RNA as templates to • Total Nitrogen • pH • BBE Algae Online – Online Toxicity determine the presence and level of Analyzer activity of different groups • NO -NO • ORP Monitors 2 3 – Green Algae • Next Gen Sequencing • Total NH • Specific Conductance – Laboratory Assays 4 – 16S rRNA gene • Turbidity – Cyanobacteria • Analytical • Total Phosphorous Quantification – 18S rRNA gene • Dissolved Oxygen – Brown (diatoms) • Total Reactive – ELISA – Cytochrome oxidase I • Total Organic Carbon – Cryptophyta Phosphorous • MC-ADDA – Metagenomes • Dissolved Organic – Total Chlorophyll – Metatranscriptomes Carbon • YSI – LC-MSMS • Microcystin • PCR and qPCR assays • NO3-N – Total Chlorophyll congeners – Toxin specific gene • UV-Vis spectral profile – Phycocyanin assays • PAR • Cylindrosper (cyanobacteria) mopsin – 16S rRNA gene group • Weather • Anatoxin-a and genus specific assays • MMPB – 18S rRNA gene group specific assays Illumina MiSeq using 16S rRNA gene barcoded primers (Caporaso et al) and Mothur pipeline for bioinformatic analyses Taxonomy based on 16S rRNA gene sequences
Akiko Tomitani et al. PNAS 2006 BUOY 60 Actinobacteria Actinobacteria JSD Cyanobacteria Cyanobacteria JSD
50 - Two different bioinformatic approaches generated similar results
40
30
20 % of total DNA seqeunces DNA % of total
10
0
Sampling Dates Relative Abundance of Total Cyanobacteria in 2015 70 p__Cyanobacteria-DNA-EFLS p__Cyanobacteria-DNA-Buoy p__Cyanobacteria-DNA-CGB p__Cyanobacteria-DNA-EFLD p__Cyanobacteria-DNA-EMB
60 - Intense sampling - Difference between sites - Shifts in photosynthetic populations 50
40
30
% of total sequences 20
10
0
Sampling Dates Relative Abundance of Total Cyanobacteria in 2016 80 p__Cyanobacteria-BOUY-DNA p__Cyanobacteria-EFLD-DNA p__Cyanobacteria-EFLS-DNA p__Cyanobacteria-EMB-DNA p__Cyanobacteria-CGB-DNA
70
60
50
40
30 % of total sequences
20
10
0 Relative Abundance of Total Cyanobacteria in 2017 90 p__Cyanobacteria-BOUY-DNA p__Cyanobacteria-EFLD-DNA p__Cyanobacteria-EFLS-DNA p__Cyanobacteria-EMB_DNA p__Cyanobacteria-CGB_DNA
80
70
60
50
40 % of total sequences 30
20
10
0
Sampling Dates 0.2k__Bacteria 0.2.1 p__AC1 0.2.4 p__Actinobacteria 0.2.7 p__Armatimonadetes 0.2.9 p__BRC1 taxon 0.2.10p__Bacteroidetes 0.2.15p__Chlorobi k__Bacteria k__Bacteria 0.2.16p__Chloroflexi p__Cyanobacteria 0.2.18p__Cyanobacteria p__Cyanobacteria 0.2.23p__Elusimicrobia c__4C0d-2 c__Chloroplast 38 bacterial phyla 0.2.24p__FBP c__Chloroplast o__Chlorophyta 0.2.26p__Fibrobacteres f__Chlamydomonadaceae 0.2.27p__Firmicutes c__ML635J-21 o__Stramenopiles 0.2.28p__Fusobacteria 0.2.31p__GN02 c__Nostocophycideae o__Cryptophyta o__Euglenozoa 0.2.34p__Gemmatimonadetes c__Oscillatoriophycideae 0.2.35p__H-178 o__Haptophyceae 0.2.41p__Lentisphaerae c__Synechococcophycideae o__Streptophyta 0.2.45p__NC10 unclassified c__Nostocophycideae 0.2.46p__NKB19 g__Aphanizomenon 0.2.48p__Nitrospirae g__Cylindrospermopsis 0.2.50p__OD1 0.2.52p__OP11 g__Dolichospermum 0.2.53p__OP3 g__Trichormus 0.2.54p__OP8 g__Anabaena 0.2.58p__Planctomycetes c__Oscillatoriophycideae 0.2.60p__Proteobacteria g__Microcystis 0.2.64p__SR1 g__Phormidium 0.2.65p__Spirochaetes g__Planktothrix 0.2.68p__TM6 g__Snowella 0.2.69p__TM7 c__Synechococcophycideae 0.2.71p__Tenericutes g__ 0.2.72p__Thermi Pseudanabaena 0.2.75p__Verrucomicrobia g__Synechococcus 0.2.77p__WS1 0.2.79p__WS3 0.2.80p__WS4 0.2.81p__WS5 0.2.84p__ZB3 Most Abundant Cyanobacterial Classes EMB 2015
60 p__Cyanobacteria c__Chloroplast c__Nostocophycideae c__Oscillatoriophycideae c__Synechococcophycideae
50
40
30 % of total seqeunces % of total
20
10
0
Sampling Date Most Abundant Toxic Cyanobacteria Genera BUOY 2015 70
60
50
40
30
% of total sequences 20
10
0
Sampling Date
p__Cyanobacteria-BUOY-DNA g__Aphanizomenon-BUOY-DNA g__Cylindrospermopsis-BUOY-DNA g__Dolichospermum-BUOY-DNA g__Microcystis-BUOY-DNA g__Planktothrix-BUOY-DNA g__Pseudanabaena-BUOY-DNA Most Abundant Toxic Cyanobacteria Genera EFLS 2015 70
60
50
40
30
% of total sequences 20
10
0
Sampling Date
p__Cyanobacteria-DNA-EFLS g__Aphanizomenon-DNA-EFLS g__Cylindrospermopsis-DNA-EFLS g__Dolichospermum-DNA-EFLS g__Microcystis-DNA-EFLS g__Planktothrix-DNA-EFLS g__Pseudanabaena-DNA-EFLS Most Abundant Toxic Cyanobacteria Genera EFLS 2016 70 p__Cyanobacteria g__Aphanizomenon g__Cylindrospermopsis g__Dolichospermum g__Microcystis g__Planktothrix g__Pseudanabaena
60
50
40
30 % of total sequences 20
10
0
Sampling Date Most Abundant Toxic Cyanobacteria Genera EFLS 2017
70 g__Aphanizomenon g__Cylindrospermopsis g__Dolichospermum g__Microcystis g__Planktothrix g__Pseudanabaena
60
50
40
30
% of total sequences 20
10
0
Sampling Date Drawbacks of DNA-based methods: • Under some environmental conditions DNA can resist degradation • DNA can be associated with cell debris and dead cells • DNA correlation with viable/active bacteria can be shaky at times • DNA-based detection does not strictly imply presence of bacteria recently inhabiting a given matrix Omics Central Metabolomics
Metabolites
DNA RNA Protein
Genomics Proteomics Transcriptomics Metatranscriptomics Metagenomics RNA-based methods:
• RNA more unstable than DNA in the environment due to widespread presence of RNAses • Declines quickly in less active cells, thus correlates with cellular activity • Natural amplification of targeted gene, i.e., 1000s to 10000s of copies per cell • Better correlation with active (viable?) bacterial fraction EMB p__Cyanobacteria-cDNA p__Cyanobacteria-DNA 100
90
80
70
60
50
40 % of total sequences total of % 30
20
10
0
Sampling Dates EFLS 100 p__Cyanobacteria-DNA p__Cyanobacteria-cDNA
90
80
70
60
50
40 % of total sequences
30
20
10
0
Sampling Date EFLD 90 p__Cyanobacteria-DNA p__Cyanobacteria-cDNA
80
70
60
50
40
% of total sequences 30
20
10
0
Sampling Date EMB 2016 RNA vs DNA 100 g__Cylindrospermopsis-EMB_cDNA g__Dolichospermum-EMB_cDNA g__Microcystis-EMB_cDNA g__Cylindrospermopsis-EMB_DNA g__Dolichospermum-EMB_DNA g__Microcystis-EMB_DNA 90
80
70
60
50
40 % of total sequences 30
20
10
0
Sampling Date EFLS 2017 RNA vs DNA 100
90
80
70
60
50
40
30
20
10
0
g__Cylindrospermopsis-EFLS_cDNA g__Dolichospermum-EFLS_cDNA g__Microcystis-EFLS_cDNA g__Planktothrix-EFLS_cDNA g__Cylindrospermopsis-EFLS_DNA g__Dolichospermum-EFLS_DNA g__Microcystis-EFLS_DNA g__Planktothrix-EFLS_DNA BUOY DNA vs Microcystin 2015 60 3.5 g__Cylindrospermopsis g__Dolichospermum g__Microcystis g__Planktothrix MC-total
3.0 50
Microcystin 2.5 40
2.0
30 ng/L 1.5
20 1.0 % or total sequences reads sequences total or % 10 0.5
0 0.0
Sampling Dates BUOY RNA vs microcystin 2015 100 3.5 g__Aphanizomenon g__Cylindrospermopsis g__Dolichospermum g__Microcystis g__Planktothrix MC-total
90 3.0 80 Microcystin
70 2.5
60 2.0
50 mg/L 1.5 40
30 1.0
% or total sequences reads sequences total or % 20 0.5 10
0 0.0
Sampling Dates EMB-DNA vs Microcystin 2016 70 6.0
60 5.0
50 4.0
40
3.0 ug/L 30
2.0
% of total sequences 20
1.0 10
0 0.0
g__Aphanizomenon g__Cylindrospermopsis g__Dolichospermum g__Microcystis g__Planktothrix g__Pseudanabaena MC-LR MC-LY EMB-cDNA vs Microcystin 2016 100 g__Aphanizomenon-cDNA g__Cylindrospermopsis-cDNA g__Dolichospermum-cDNA g__Microcystis-cDNA 6 g__Planktothrix-cDNA g__Pseudanabaena-cDNA MC-LR MC-LY 90
5 80
70 4
60
50 3 ug/L
40
% of total sequences 2 30
20 1
10
0 0 EMB_cDNA_04_01_2016 EMB_cDNA_04_13_2016 EMB_cDNA_04_27_2016 EMB_cDNA_05_11_2016 EMB_cDNA_05_18_2016 EMB_cDNA_05_25_2016 EMB_cDNA_06_01_2016 EMB_cDNA_06_03_2016 EMB_cDNA_06_06_2016 EMB_cDNA_06_08_2016 EMB_cDNA_06_10_2016 EMB_cDNA_06_13_2016 EMB_cDNA_06_15_2016 EMB_cDNA_06_17_2016 EMB_cDNA_06_20_2016 EMB_cDNA_06_22_2016 EMB_cDNA_06_24_2016 EMB_cDNA_06_27_2016 EMB_cDNA_06_29_2016 EMB_cDNA_07_01_2016 EMB_cDNA_07_06_2016 EMB_cDNA_07_14_2016 EMB_cDNA_07_20_2016 EMB_cDNA_07_22_2016 EMB_cDNA_07_27_2016 EMB_cDNA_08_03_2016 EMB_cDNA_08_10_2016 EMB_cDNA_08_17_2016 EMB_cDNA_08_24_2016 EMB_cDNA_08_31_2016 EMB_cDNA_09_14_2016 EMB_cDNA_09_28_2016 BUOY cDNA vs Microcystin 2016 100 5.0 g__Aphanizomenon-cDNA g__Cylindrospermopsis-cDNA
90 g__Dolichospermum-cDNA g__Microcystis-cDNA 4.5 g__Planktothrix-cDNA g__Pseudanabaena-cDNA 80 MC-LR MC-LY 4.0
70 3.5
60 3.0
50 2.5 ug/L
40 2.0
% of total seqeunces 30 1.5
20 1.0
10 0.5
0 0.0 Buoy_cDNA_04_01_2016 Buoy_cDNA_04_13_2016 Buoy_cDNA_04_27_2016 Buoy_cDNA_05_11_2016 Buoy_cDNA_05_18_2016 Buoy_cDNA_05_25_2016 Buoy_cDNA_06_01_2016 Buoy_cDNA_06_03_2016 Buoy_cDNA_06_06_2016 Buoy_cDNA_06_08_2016 Buoy_cDNA_06_10_2016 Buoy_cDNA_06_13_2016 Buoy_cDNA_06_15_2016 Buoy_cDNA_06_17_2016 Buoy_cDNA_06_20_2016 Buoy_cDNA_06_22_2016 Buoy_cDNA_06_24_2016 Buoy_cDNA_06_27_2016 Buoy_cDNA_06_29_2016 Buoy_cDNA_07_01_2016 Buoy_cDNA_07_06_2016 Buoy_cDNA_07_14_2016 Buoy_cDNA_07_20_2016 Buoy_cDNA_07_22_2016 Buoy_cDNA_07_27_2016 Buoy_cDNA_08_03_2016 Buoy_cDNA_08_17_2016 Buoy_cDNA_08_24_2016 Buoy_cDNA_08_31_2016 Buoy_cDNA_09_14_2016 Buoy_cDNA_09_28_2016
Sampling Dates Microcystis Cyclindrospermopsis Lake Harsha 2015. Sphingobacteriales Bacillariophyta Saprospirales Random forest regressions Candidatus Xiphinematobacter featuring: Alphaproteobacteria ACK-M1 (Actinomycetales) • 88 eukaryotic (18S) OTUs
Flavobacterium • 142 prokaryotic (16S) OTUs Chitinophagaceae • 12 different abiotic Synechococcus environmental Actinomycetales measurements (including Cercozoa lake inflow/outflow, temperature, pH, rainfall, Saprospiraceae (Saprospirales) Pseudanabaena and N and P concentrations). Burkholderiales
Agaricomycotina
Pseudanabaenaceae 211ds20 (Alteromonadales) Bacteroidetes Random Forest Regression Model: Predict Microcystis Relative Abundance
4-day Interval Microcystis Variance Most informative Taxonomy Explained Model Feature Same interval 90.1% OTU275 Deltaproteobacteria, Myxococcales 1 prior 78.0% OTU317 Betaproteobacteria 2 prior 84.8% OTU196 Bacteroidetes 3 prior 90.1% OTU45 Acetobacteraceae, Roseomonas 4 prior 77.3% 3-day ave. rain Forest regression for Lake Harsha 2015 using 16S rRNA gene sequencing data Conclusions:
Cyanobacteria genera identified: 25
Most abundant toxic cyanobacterial species: Dolichospermum, Cylindrospermopsis, Microcystis, Planktothrix, Aphanizomenon, Pseudoanabaena
Most cyanobacteria are active (based on RNA:DNA ratios)
Potential microcystin culprits: Microcystis, Planktothrix, Pseudanabaena Any questions?