Sulphate-reducing microorganisms (SRMs) are a physiologically and phylogenetically diverse group of anaerobic bacterial and archaeal species that are important both ecologically and industrially. The application of systems biology tools has provided insights into the stress responses in SRMs at the cell, population, community and ecosystem levels.
Analyses using comparative and functional genomics support hydrogen cycling as a mode of energy metabolism that is characteristic of SRMs, and highlight the central role of this process in stress responses in Desulfovibrio vulgaris Hildenborough, the best known model SRM.
D. vulgaris activates distinct pathways in response to specific stresses. This is consistent with comparative genomic analyses that reveal this species has an unusually large number of diverse response regulators for signal transduction.
Despite the divergence in stress responses in D. vulgaris, the oxidative stress response seems to have a prevalent role in coping with many different stresses, as components of the defence pathways against reactive oxygen species are highly expressed even under non-oxidative stress conditions. This anticipatory expression may confer an adaptive advantage, as stress caused by reactive oxygen species is the most critical stress to anaerobes such as SRMs.
The ability of D. vulgaris to grow syntrophically with methanogens allows its distribution and evolution in environments that are depleted of sulphate, a condition that is an insurmountable stress for other SRMs. Integrated 'omics' analyses further indicate that D. vulgaris has genes (such as those involved in hydrogen cycling) that are dedicated to survival by syntrophy, and that the bacteria can evolve enhanced stability and productivity as a part of a community.
High-throughput sequencing and metagenomic technologies (such as GeoChip and PhyloChip) have been used to demonstrate that SRMs are widely distributed and well adapted to diverse environments. Metagenomic studies show that the distribution and activity of SRMs are constrained by the environmental boundaries defined by the cell's physiological limit to launch an effective stress response. Thus, a system-level understanding of stress responses provides critical knowledge for designing strategies for the application or elimination of SRMs in distinctive environments.
Next-generation genomics and other new technologies hold great promise for us to gain a more comprehensive understanding of SRMs (for example, by linking genotypes to phenotypes through experimental evolution, by high-resolution population genomics studies of SRMs, and by modelling SRM activity in a variety of environments). Analysis of SRM populations in communities with different levels of complexity is essential for predicting the ecological and evolutionary responses of microbial communities to environmental change. Novel mathematical frameworks and computational tools will greatly help us address these challenges.
Sulphate-reducing microorganisms (SRMs) are a phylogenetically diverse group of anaerobes encompassing distinct physiologies with a broad ecological distribution. As SRMs have important roles in the biogeochemical cycling of carbon, nitrogen, sulphur and various metals, an understanding of how these organisms respond to environmental stresses is of fundamental and practical importance. In this Review, we highlight recent applications of systems biology tools in studying the stress responses of SRMs, particularly Desulfovibrio spp., at the cell, population, community and ecosystem levels. The syntrophic lifestyle of SRMs is also discussed, with a focus on system-level analyses of adaptive mechanisms. Such information is important for understanding the microbiology of the global sulphur cycle and for developing biotechnological applications of SRMs for environmental remediation, energy production, biocorrosion control, wastewater treatment and mineral recovery.
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We thank M. W. Fields, A. Deutschbauer, K. S. Bender, R. Chakraborty and L. Rajeev for providing comments on this Review. The efforts in preparing this Review were supported by the Genomics: GTL Foundational Science programme of the US Department of Energy, Office of Science, Office of Biological and Environmental Research, through contract DE-AC02-05CH11231 (as part of ENIGMA (Ecosystems and Networks Integrated with Genes and Molecular Assemblies), a Scientific Focus Area) to the Lawrence Berkeley National Laboratory, and in part through award 0854332 from the Environmental Engineering Program of the US National Science Foundation.
The authors declare no competing financial interests.
A deviation from optimal growth conditions that leads to a reduced growth rate or cellular damage as a result of environmental or internal changes.
Genetically encoded traits that enhance the fitness of their bearers.
- Functional genomics
Large-scale genomic studies that use functional measurements such as changes in the levels of mRNAs, proteins and metabolites, combined with statistical analyses, mathematical modelling and computational analysis of the results, to gain knowledge of cell physiology.
Pertaining to a type of mutualism in which two or more species cooperate to complete a single energy-yielding reaction from which neither species alone can gain energy.
Pertaining to the study of microbial community genomes directly from environmental samples using high-throughput sequencing and associated genomics technologies.
- Signal transduction
A mechanism that converts a mechanical or chemical stimulus into a specific cellular response.
The phenotypic response of a population to a change in environmental conditions.
The systematic study of a transcriptome (a collection of all of the RNA molecules (mRNA, ribosomal RNA, tRNA and other non-coding RNAs) that are produced in a cell population) using microarrays or sequencing.
The large-scale study of proteins, particularly their structures and functions. Mass spectrometry is a popular method for conducting proteomic measurements in a high-throughput manner.
The systematic study of a metabolome, which is the collection of all the metabolites in a biological cell, tissue, organ or organism.
- One-component signal transduction systems
Signal-sensing and response systems in which the signal transducer is the direct fusion of an input domain to an output domain in a single protein molecule.
- Cyclic di-GMP
A second messenger that is used in signal transduction in a wide variety of bacteria.
- Transcription factor σ54
A protein in bacteria that enables binding of RNA polymerase to gene promoters specifically in response to nitrogen limitation.
A set of genes or operons that are regulated by the same regulatory protein.
- Flux balance analysis
Mathematical modelling of the flux of metabolites through metabolic networks, which can be as complex as the total metabolic capacity encoded by a genome.
- Functional gene arrays
Microarrays that contain probes targeting sequences which are unique to genes within families of interest. For example, these may be genes encoding enzymes that are involved in antibiotic resistance, energy metabolism, stress responses, the degradation of organic contaminants or the biogeochemical cycles of carbon, nitrogen, phosphorus, sulphur and various metals, or they may be genes from phages or human pathogens.
The interface region with a sharp vertical chemical gradient in a body of water. In this case, it refers to an O2 gradient, which is caused by the production of O2 by the cyanobacteria in a mat.
- Single-cell genomics
The characterization of the genome of an isolated single cell (or a group of these cells) by large-scale sequencing and other high-throughput technologies. Single cells are typically isolated by optical tweezers (which use highly focused laser beams to physically manipulate microscopic objects), flow sorting or serial dilution, and these cells are then subjected to genome amplification, sequencing and/or functional measurements.
- Experimental evolution
An approach to studying evolution that involves the propagation of populations for many generations in controlled and reproducible environmental conditions, and the observation of the phenotypic and genetic changes in those populations.
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Zhou, J., He, Q., Hemme, C. et al. How sulphate-reducing microorganisms cope with stress: lessons from systems biology. Nat Rev Microbiol 9, 452–466 (2011) doi:10.1038/nrmicro2575
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