University of Washington GTL VIMSS Applied and Environmental Microbiology Core

1. Environmental Stress Responses in Metal-reducers D.A. Stahl University of Washington GTL VIMSS Applied and Environmental Microbiology Core

2. Collaborators • Genomatica, San Diego, CA • Steve Van Dien • Northwestern University • Jean-Francois Gaillard • Amy Dahl • University of Washington • Sergey Stolyar • Beto Zuniga • Martin Koenneke • Heidi Gough • LBNL • Terry Hazen • Sharon Borglin • ORNL • Jizhong Zhou • Zhili He • Qiang He

3. Outline I. The Adaptive Landscape - Ecological Considerations II. Case Study - Heavy Metal Impacted System III. VIMSS Development of reactor systems that mimic environmental conditions. Develop testable conceptual models of stress regulatory pathways based on results of the Computational Core that could predict natural attenuation and suggest biostimulatory strategies for immobilization of metals and radionuclides at DOE contaminated sites

4. The environment is the context in which genomes evolved, function, and continue to evolve. It is the only context in which they can be fully understood.

5. No Universal Definition for StressHighly dependent upon the individual cellWorking definitions • Any deviation from optimal growth conditions that results in reduced growth rate • An environmental situation that results in damage of cellular components in the absence of a cellular response • Any situation that stimulates expression of known stress-response genes

6. Since microorganisms generally live in a world of constantly changing circumstance, stress response is the physiologically more relevant condition (vs growth in rich broth).Although pure culture studies of stress response lay claim to direct environmental relevance, there has been little direct inspection of stress response within a natural context (e.g., biofilms, interacting or competing microbial species, fluctuating environmental conditions)

7. Response to Stress Shadings between adaptive response and response to cellular damage

8. StarvationHeat ShockCold ShockEnvelope StressOxidative StressOxygen DeprivationOsmotic ChallengesAcid StressSodium StressSOS Response to DNA Damage The Laundry List of Better Studied Stressors & Microbial Response Systems

9. The Adaptive Landscape Ecology: Individuals, Populations, and Communities. Begon, Harper, Townsend. Sinauer Associates. 1986

10. The multiple dimensionality of stress Ecology: Individuals, Populations, and Communities. Begon, Harper, Townsend. Sinauer Associates. 1986

11. The Concept of Niche The “Hutchinsonian” Niche (1957) • An N-dimensional hypervolume of environmental conditions within which the organism can maintain a population • Two categories of conditions: • Physical/Chemical (temp, salinity,flow, pressure, etc.) • Resources (nutrients, energy sources, space, etc.) G.E. Hutchinson (1957) Concluding remarks. Cold Spring Harbor Symposium on Quantitatvie Biology22: 415-427

12. Suggestion The concept of a microbial species will likely be informed be informed by mapping of various stress-response boundaries

13. Impacts of metal contamination on microbial communities in a sediment system (Lake DePue, Illinois) Case Study

14. 0 500 1000 scale in meters Lake DePue, Illinois, USAlatitude 41o19’ north, longitude 89o18’ west

15. Total Zinc in Lake DePue, Illinois, USA Background concentrations Backwater lakes Illinois River Mississippi River Site 1 24960 mg/kg 436 mg/kg 483/mg/kg 113 mg/kg Site 4 4475 mg/kg Site 2 11602 mg/kg Site 5 3350 mg/kg Site 3 6530 mg/kg 0 500 1000 scale in meters Map source: United States Geological Survey, 7.5 minute map series, DePue, Illinois Quadrangle, 1966, photorevised 1979.

16. Model predictions for community responses to metal stress • Diaz-Ravina and Bååth (1996) – mechanistic model for community change due to metal stress with no impact to biomass. 1. Sensitive organisms die 2. Resistant organisms compete for resources 3. New community structure results

17. Accounting for Confounding Variables: Site Characterization

18. Initial CharacterizationpH, DOC, TOC, C:N, soil classification, moisture content

19. Response of microbial system to metals contamination • Samples from 5 sites, 3 replicate cores, upper 2 cm. • Biomass by Phospholipid phosphate (PLP) and DAPI cell counts. • Metals (Cu, As, Cr, Zn, Pb, Fe, and Mn) in sequential extractions and filtered pore waters by FAA or ICPMS. • Monitor potentially confounding variables (pH, DOC, C:N, soil classification, moisture content, etc.) • Multiple regression to evaluate correlations.

20. Site Sediment Biomass Each value is the average of the samples from two depth intervals and three cores collected at the site (n=6). Error represents the mean deviation.

21. DAPI and PLP-biomass correlated

22. Dissolved Zn versus PLP-biomass 300 250 200 PLP (nmole P/dry g) 150 100 50 0 0.0 2.0 4.0 6.0 8.0 Data variability represents the average of the deviation from the mean for 2 discreet depth intervals collected from 3 core samples (6 samples total).

23. Findings regarding microbial biomass • Microbial biomass was negatively correlated to pore water Zn and As concentrations. • Other observations: • Biomass positively correlated with pore water Mn concentrations • TOC potentially accumulated in most-contaminated sediments

24. Impact of Metals Contamination on Microbial Activity

25. Site description SO42- (mM) SRR (nmol/cc/d) freshwater Lake DePue (eutrophic) 3.5 37800 Lake Mendota (eutrophic) 0.2 600 Lake Wintergreen (eutrophic) 0.03 171 Mining lake 5.2 171 marine Organic-rich coastal 25 750 Black Sea shelf 17 100 other – Great Salt Lake Moderate-saline 14 6000 Hyper-saline 208 32 Sulfate Reduction in Lake DePue compared to other sediments

26. Sulfate reducing bacteria (SRB) and metals • Influence fate and transport of metals • Generate sulfide that complexes and precipitates metals => less toxic • Reduce metals => less toxic • Suggested for in situ bioremediation • Sensitivity to stress (e.g. metal toxicity) varies • Both sensitive and resistant species reported • Variation may occur within the same genus

27. Impact of Metals Contamination on Microbial Diversity

28. Overview of Terminal Restriction Length Fragment Polymorphism (TRFLP) “Whole” Community DNA Fingerprinting • Blue – terminal fragments derived from restriction digestion of PCR amplification of 16S rRNA genes • Red – DNA size fragment standard • Data is analyzed as a chromatogram, and fragment size and peak area are tabulated.

29. Examples of Bacterial TRFLP profiles 12% Site 1 (highest metal) 2.5% Site 2 12% 4.4% Site 5 (lowest metal) 8.6% 12% 94 379

30. Relative abundances of majority of TRFs were independent of metals

31. A Few ExceptionsCorrelation of Arc TRF 191 and total Zn • Major peak in Archaeal TRFLP profiles • Correlated to total Zn • High correlation coefficient • Similar association in enrichment study

32. marine Cloned Sequences correlated with Arc TRF 191 arcVD3, 545 (191) soils arcVF1, 890 (193) • Sequences cluster with anaerobic and soil crenarchaeota • 190-194 is common cut length for crenarchaeota • No known isolates of mesophilic crenarcheaota – metabolism not known thermophiles arcVF5, 231 (192) arcVA5, 714 (191) arcVD1, 611 (unknown) anaerobes arcVA1, 958 (194) arcVC5, 739 (192) arcVC2, 673 (192) arcYC2, 796 (192) arcVE4, 581 (190) thermophiles

33. Conceptual Models for community responses to metal stress • Diaz-Ravina and Bååth (1996) – mechanistic model for community change due to metal stress. 1. Sensitive organisms die 2. Resistant organisms compete for resources 3. New community structure results 1. Start with a pre-selected community 2. Increasing stress alters growth of community 3. Resulting community similar to starting community, with decreased biomass - Stressed!

34. University of Washington GTL VIMSS Applied and Environmental Microbiology Core

35. Selected Objectives of GTL VIMSS Survey and map DOE sites contaminated by metals and radionuclides using chemical and molecular/microbiological parameters to determine major microbial populations and potential stressors for Desulfovibriovulgaris, Geobactermetallireducens, and Shewanellaoneidensis. Create defensible environmental simulators that can replicate key features of field site chemical and biological structure to mimic stress conditions for single populations and later for microbial communities (chemostats to soil columns) Develop testable conceptual models of stress regulatory pathways based on results of the Computational Core that could predict natural attenuation and suggest biostimulatory strategies for immobilization of metals and radionuclides at DOE contaminated sites

36. Changing Appreciation of Sulfate-reducing Bacterial Diversity • Respiration • SO4=, SO3= (SSO3=, So, NO3-, NO2-) • Chlorinated Organics • Reduction • Fe+3, Mn+4, and toxic metals (e.g., uranium, selenium, technetium, arsenate, chromium), • O2 • e- DONORS • Toluene • Saturated aliphatics • Benzene, Naphthalene, ... • Disproportionation of Inorganic Sulfur Compounds

39. Biofilm Reactor Systems

40. Syntrophic Co-culture of bioreactor Desulfovibrio isolate with methanogen on lactate without sulfate Methanococcus Desulfovibrio

41. Syntrophic co-culture of Desulfovibrio & Methanococcus sulfate depleted medium CO2 Lactate Interspecies Hydrogen-transfer H2H2CH4 Acetate + CO2 Desulfovibrio Methanococcus

42. Effect of hydrogen partial pressure on free energy Desulfovibrio fermentation of lactate CH3CHOHCO2- (lactate) + H2O CH3COO- (acetate) + CO2 + 2 H2 at 10-4 atm H2: at 1 atm H2: DG0’= -8.8 + 2 RT ln [10-4] = - 54 kJ/mol DG0’= -8.8 kJ/mol

43. NaCl Growth Curves on B3 media @ 30˚C Abs @ 600nm Hours Abs @ 600nm Hours

44. MgSO4 Growth Curves on B3 media @ 30˚C Abs @ 600nm Hours Abs @ 600nm Hours

45. Syntrophic co-culture: Growth and Metabolites

46. Adaptation to Syntrophic GrowthTypical growth curves for several consecutive passages of D. vulgaris and M. maripaludis co-cultures

47. RNA isolation Growth curves of the six parallel batch co-cultures of D. vulgaris and M. maripaludis C4 (8th passage)

48. Initial Microarray Analyses Batch syntrophic and Chemostat cultures harvested for microarray analysis at ORNL (Jizhong Zhou) Microarray: 70mers for all ORFs of D. vulgaris and M. maripaludis genomes - 3574 and 1766 oligonucleotides, respectively.

49. Microarrays and Transcriptomics RNA isolation Cy5 (633 nm) Cy3 (543 nm) Conditon 2 RNA Condition 1 RNA Scan slides (HP ScanArray 5000) Primer design PCR amplification Purification Transfer to 384-well plates Label Cy5 Cy3 • • • • • • • • • • • • • • Robotic Printing Data analysis (HP QuantArray) Hybridization Duggan, D. J. et al. Nature Genet., 1999

50. Co-culture/24 hr Sulfate-limited Chemostat Dsv. vulgaris H (Jul. 14, 2004) Gene ID Co-culture/24 hr chemostat Functional annotation ORF03736 4.735 7.242 minor capsid protein C (phage) ORF01941 4.623 3.970 hypothetical protein ORF04118 3.087 3.516 hypothetical protein ORF04140 2.547 3.302 Na+/H+ antiporter NhaC (nhaC) ORF03712 1.445 2.474 tail/DNA circulation protein, putative (phage) ORF02762 1.418 2.205 hypothetical protein ORF00660 1.293 2.396 glucokinase, putative ORF02808 1.157 2.033 methyl-accepting chemotaxis protein, putative ORF01324 0.000 0.090 Heptosyltransferase family ORF02917 0.000 0.090 outer membrane protein, putative ORF02422 0.000 0.086 hypothetical protein ORF05495 0.000 0.085 selenocysteine-specific translation elongation factor (selB) ORF03314 0.000 0.080 chemotaxis MotB protein, putative ORF04420 0.000 0.079 cytochrome d ubiquinol oxidase, subunit I, POINT MUTATION (cydA) ORF05549 0.000 0.078 hmc operon protein 4 ORF05761 0.000 0.077 hypothetical protein ORF03449 0.000 0.076 hypothetical protein ORF00252 0.000 0.073 histidinol dehydrogenase (hisD) ORF01604 0.000 0.063 iron-sulfur cluster-binding protein ORF01996 0.000 0.062 hypothetical protein ORF00134 0.000 0.058 queuine tRNA-ribosyltransferase (tgt) ORF01744 0.000 0.051 hypothetical protein ORF04935 0.000 0.048 thiosulfate reductase, putative ORF00151 0.000 0.029 cell cycle histidine kinase CckA, putative ORF01870 0.000 0.023 periplasmic [Fe] hydrogenase, small subunit (hydB) ORF04043 0.000 0.000 oxygen-independent coproporphyrinogen III oxidase, putative ORF02953 0.000 0.000 hypothetical protein ORF03023 0.000 0.000 ABC transporter, permease protein ORF02238 0.000 0.000 conserved hypothetical protein ORF01057 0.000 0.000 conserved hypothetical protein TIGR00159 ORF01861 0.000 0.000 thiH protein (thiH) ORF02661 0.000 0.000 single-strand binding protein (ssb)