# Presentation: 934107

## University of Washington

- GTL VIMSS
- Applied and Environmental Microbiology Core

- Environmental Stress Responses in Metal-reducers
- D.A. Stahl

## Collaborators

- 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

## 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

## 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.  

## No Universal Definition for StressHighly dependent upon the individual cellWorking 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

## 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)

## Response to Stress Shadings between adaptive response and response to cellular damage

## StarvationHeat ShockCold ShockEnvelope StressOxidative StressOxygen DeprivationOsmotic ChallengesAcid StressSodium StressSOS Response to DNA Damage

- The Laundry List of Better Studied Stressors & Microbial Response Systems

## The Adaptive Landscape

*Ecology: Individuals, Populations, and Communities.*  Begon, Harper, Townsend.  Sinauer Associates.  1986

## The multiple dimensionality of stress

*Ecology: Individuals, Populations, and Communities.*  Begon, Harper, Townsend.  Sinauer Associates.  1986

## The Concept of Niche

- The “Hutchinsonian” Niche (1957)

- G.E. Hutchinson (1957) Concluding remarks.  *Cold Spring Harbor Symposium on Quantitatvie Biology* **22**: 415-427

*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.)

## Suggestion

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

## Impacts of metal contamination on microbial communities in a sediment system (Lake DePue, Illinois)

- Case Study

## Lake DePue, Illinois, USAlatitude 41o19’ north,   longitude 89o18’ west

- Lake DePue, Illinois, USAlatitude 41o19’ north,   longitude 89o18’ west

## Total Zinc in Lake DePue, Illinois, USA

- 0

- 500

- 1000

- scale in meters

- Background concentrations

- 113 mg/kg

- 483/mg/kg

- 436 mg/kg

- Mississippi River

- Illinois River

- Backwater lakes

- Map source:	United States Geological Survey, 7.5 minute map series, DePue, Illinois Quadrangle, 1966, photorevised 1979.

- _Site 1_
- 24960 mg/kg

- _Site 2_
- 11602 mg/kg

- _Site 3_
- 6530 mg/kg

- _Site 4_
- 4475 mg/kg

- _Site 5_
- 3350 mg/kg

**Notes:**
Insert slide from ISEB with site selection criteria

## 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

## Accounting for Confounding Variables: Site Characterization

## Initial Characterization pH, DOC, TOC, C:N, soil classification, moisture content

## 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.

## 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.

**Notes:**

General trend
Higher biomass than soils or contaminated soils.
Lower, but in the same range, as Hg cont. sediments.

	P-LP (nmol P/g)
Soil1)	39
Pb contaminated soil1)	1 to 5
Marine sediment2)	
Hg contaminated freshwater sediment (Macalady et al., 2000)	400-1000
	 1)  Konopka (1999)

## DAPI and PLP-biomass correlated

## Dissolved Zn versus PLP-biomass

- Data variability represents the average of the deviation from the mean for 2 discreet depth intervals collected from 3 core samples (6 samples total).

- 0

- 50

- 100

- 150

- 200

- 250

- 300

- 0.0

- 2.0

- 4.0

- 6.0

- 8.0

**PLP (nmole P/dry g)**

**Notes:**
An apparent trend with pore water Zn

Questions:
Is correlation significant
Can trend be attributed to any other parameters?
Recall – env parameters can not explain the trend.

## 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

## Impact of Metals Contamination on Microbial Activity

## Sulfate Reduction in Lake DePue compared to other sediments

**Notes:**
Sulfate variations
 srr variations – changes with depth as expected.
 highest srr at highest metal contaminated site – result of sulfate or metal concentration?

## 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

## Impact of Metals Contamination on Microbial Diversity

## 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.

## Examples of Bacterial TRFLP profiles

- Site 1 (highest metal)

- Site 2

- Site 5 (lowest metal)

**12%**

**2.5%**

**4.4%**

**8.6%**

**94**

**379**

**12%**

**12%**

## Relative abundances of majority of TRFs were independent of metals

## A Few ExceptionsCorrelation 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

## Cloned Sequences correlated with Arc TRF 191

- Sequences cluster with anaerobic and soil crenarchaeota
- 190-194 is common cut length for crenarchaeota
- No known isolates of mesophilic crenarcheaota – metabolism not known

- anaerobes

- thermophiles

- soils

- marine

- thermophiles

**arcVF1, 890 (193)**

**arcVD3, 545 (191)**

**arcVF5, 231 (192)**

**arcVD1, 611 (unknown)**

**arcVA1, 958 (194)**

**arcVC5, 739 (192)**

**arcVC2, 673 (192)**

**arcYC2, 796 (192)**

**arcVE4, 581 (190)**

**arcVA5, 714 (191)**

## 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!

## University of Washington

- GTL VIMSS
- Applied and Environmental Microbiology Core

## 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 *Desulfovibrio* *vulgaris*, *Geobacter* *metallireducens*, and *Shewanella* *oneidensis*.

- 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

## 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

- 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

- Changing Appreciation of
- Sulfate-reducing Bacterial Diversity

## Slide 37

## Slide 38

## Biofilm Reactor Systems

## Methanococcus

*Methanococcus*

*Desulfovibrio*

- Syntrophic Co-culture of bioreactor *Desulfovibrio isolate*
- with methanogen on lactate without sulfate

## Syntrophic co-culture of Desulfovibrio & Methanococcus

- Syntrophic co-culture of *Desulfovibrio* & *Methanococcus*
*sulfate depleted medium*

**CO****2**

***Methanococcus***

**Lactate**

***Interspecies Hydrogen-transfer***

**H****2**** ****	****H****2**** ****	****  ****CH****4**

**Acetate + CO****2**

***Desulfovibrio***

## Effect of hydrogen partial pressure on free energy

- at 1 atm H2:

- *G**0****’****** ***=  _-8.8  kJ/mol_

- at 10-4 atm H2:

- *G**0****’******	***=  -8.8 + 2 *RT* ln [10-4]
- 	=  _- 54 kJ/mol_

*Desulfovibrio* fermentation of lactate

- CH3CHOHCO2- (lactate) + H2O              CH3COO- (acetate) + CO2 + 2 H2

## NaCl Growth Curves on B3 media @ 30 ̊C

**Hours**

**Hours**

**Abs @ 600nm**

**Abs @ 600nm**

## MgSO4 Growth Curves on B3 media @ 30 ̊C

- MgSO4 Growth Curves on B3 media @ 30 ̊C

**Hours**

**Hours**

**Abs @ 600nm**

**Abs @ 600nm**

## Syntrophic co-culture:  Growth and Metabolites

## Adaptation to Syntrophic GrowthTypical growth curves for several consecutive passages of D. vulgaris and M. maripaludis co-cultures

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

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

## 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.

## Microarrays and Transcriptomics

*Duggan,   D. J. et al.*
*Nature Genet.,   1999*

**Primer design               PCR amplification Purification           Transfer to 384-well plates**

**Hybridization**

**Label**

**Cy3**

**Cy5**

**Conditon 2 RNA**

**Condition 1**
**RNA**

**RNA isolation**

**Data analysis   (HP QuantArray)**

**Robotic Printing**

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**Scan slides             (HP ScanArray 5000)**

**Cy3       (543 nm) **

**Cy5       (633 nm)**** **

## 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)

## Flux Balance Model for Analysis Desulfovibrio vulgaris Metabolism

- Flux Balance Model for Analysis *Desulfovibrio vulgaris *Metabolism

## Flux Balance Model for Analysis Methanococcus maripaludis metabolism

- Flux Balance Model for Analysis *Methanococcus maripaludis *metabolism

## Lake DePue Desulfovibrio Isolates

- Enrichments on lactate fresh water sediment
- media to isolate *Desulfovibrio*-like microbes.
- Isolated using anaerobic roll tube method with FeSO4

- Samples -  Lake DePue Zinc contaminated sediment
- Sampling, Oct. 2002

- DP1 isolate

## Slide 54

## PFGE of Lake DePue Isolates

- 2,10)	*D. vulgaris Hildenborough (*DvH) (undigested genomic DNA)
- 3, 11)	L. DePue isolates DP4 and DP8 undigested genomic DNA
- 4)	DvH DNA digested with I-CeuI; 5,6- DP4 and DP8 DNA digested with I-CeuI
- 7)	DvH gDNA digested with NotI
- 8,9)	DP4 and DP8 DNA digested with NotI; Arrows indicate extrachromosomal (plasmid) DNA; red diamods indicate I – CeuI fragments of DvH

## Comparative Genomic DNA hybridization

- 				Hildenborough
**Similarity – 16S rRNA****	****   **100%		  >99%		 95%	**	**
**Similarity**
**(hybridization trends)****	****   **100%		 ~ 90%	        ~ 60%*** ****	**
**Potential deletion regions     **No			Regions 1-7	       Regions 5 & 6

## GeneID	DP4/HI		Functional annotations from TIGR

**	**
**Region 1 (44 genes)****	**
- ORF00763	**0.20****	**	adenine specific DNA methyltransferase, putative
- ORF00765	**0.38****	**	tail fiber assembly protein, putative
- ORF00766	**0.29****	**	tail fiber protein, putative
- ORF00771	**0.23****	**	hypothetical protein
- ORF00774	**0.15****	**	baseplate assembly protein, putative
- ORF00777	**0.13****	**	baseplate assembly protein, putative
- ORF00778	**0.12****	**	hypothetical protein
- ORF00779	**0.18****	**	hypothetical protein
- ORF00781	**0.15****	**	tail tape measure protein, FRAMESHIFT
- ORF00784	**0.13****	**	hypothetical protein
- ORF00786	**0.35****	**	ATPase domain protein
- ORF00788	**0.14****	**	hypothetical protein
- ORF00790	**0.16****	**	hypothetical protein
- ORF00794	**0.21****	**	hypothetical protein
- ORF00795	**0.23****	**	virion morphogenesis protein
- ORF00796	**0.15****	**	conserved hypothetical protein
- ORF00797	**0.12****	**	hypothetical protein
- ORF00798	**0.16****	**	hypothetical protein
- ORF00800	**0.17****	**	conserved hypothetical protein
- ORF00801	**1.14****	**	virion morphogenesis protein
- ORF00802	**0.09****	**	conserved hypothetical protein
- ORF00803	**0.26****	**	hypothetical protein
- ORF00805	**0.33****	**	portal protein, putative
- ORF00807	**0.10****	**	conserved domain protein
- ORF00810	**0.12****	**	hypothetical protein
- ORF00811	**0.46****	**	hypothetical protein
- ORF00812	**0.24****	**	lipoprotein, putative
- ORF00815	**0.11****	**	lysozyme, putative
- ORF00816	**0.10****	**	conserved hypothetical protein
- ORF00817	**0.09****	**	DNA-binding domain protein
- ORF00818	**0.08****	**	hypothetical protein
- ORF00819	**0.13****	**	conserved hypothetical protein
- ORF00820	**0.25****	**	hypothetical protein
- ORF00822	**0.14****	**	DNA-binding protein HU, beta subunit (hupB)
- ORF00823	**0.10****	**	conserved domain protein
- ORF00824	**0.12****	**	host-nuclease inhibitor protein Gam, putative
- ORF00826	**0.12****	**	hypothetical protein
- ORF00827	**0.11****	**	hypothetical protein
- ORF00829	**0.09****	**	bacteriophage DNA transposition B protein, putati
- ORF00830	**0.11****	**	bacteriophage transposase A protein, putative
- ORF00832	**0.08****	**	hypothetical protein
- ORF00833	**0.14****	**	transcriptional regulator, putative
- ORF00836	**0.11****	**	hypothetical protein
- ORF00837	**0.28****	**	transcriptional regulator, Cro/CI family

## D. vulgaris Hildenborough chromosome map and gene clusters deleted in the Dp4 isolate genome

## Understanding of long-term stress (e.g., heavy metal impacted soil, sediments, or subsurface systems), as needed for improved system control...

- Population Selection (species composition, as determined by stress-response boundaries)
- Long and short-term adaptation of populations (elimination of phage elements?)
- Stress Response Machinery