Margrethe H. Serres

Towards Environmental Systems Biology of Shewanella

Bacteria of the genus Shewanella are known for their versatile electron-accepting capacities, which allow them to couple the decomposition of organic matter to the reduction of the various terminal electron acceptors that they encounter in their stratified environments. Owing to their diverse metabolic capabilities, shewanellae are important for carbon cycling and have considerable potential for the remediation of contaminated environments and use in microbial fuel cells. Systems-level analysis of the model species Shewanella oneidensis MR-1 and other members of this genus has provided new insights into the signal-transduction proteins, regulators, and metabolic and respiratory subsystems that govern the remarkable versatility of the shewanellae.

Escherichia coli K-12: a cooperatively developed annotation snapshot—2005

The goal of this group project has been to coordinate and bring up-to-date information on all genes of Escherichia coli K-12. Annotation of the genome of an organism entails identification of genes, the boundaries of genes in terms of precise start and end sites, and description of the gene products. Known and predicted functions were assigned to each gene product on the basis of experimental evidence or sequence analysis. Since both kinds of evidence are constantly expanding, no annotation is complete at any moment in time. This is a snapshot analysis based on the most recent genome sequences of two E.coli K-12 bacteria. An accurate and up-to-date description of E.coli K-12 genes is of particular importance to the scientific community because experimentally determined properties of its gene products provide fundamental information for annotation of innumerable genes of other organisms. Availability of the complete genome sequence of two K-12 strains allows comparison of their genotypes and mutant status of alleles.

A functional update of the Escherichia coli K-12 genome.

BackgroundSince the genome of Escherichia coli K-12 was initially annotated in 1997, additional functional information based on biological characterization and functions of sequence-similar proteins has become available. On the basis of this new information, an updated version of the annotated chromosome has been generated.ResultsThe E. coli K-12 chromosome is currently represented by 4,401 genes encoding 116 RNAs and 4,285 proteins. The boundaries of the genes identified in the GenBank Accession U00096 were used. Some protein-coding sequences are compound and encode multimodular proteins. The coding sequences (CDSs) are represented by modules (protein elements of at least 100 amino acids with biological activity and independent evolutionary history). There are 4,616 identified modules in the 4,285 proteins. Of these, 48.9% have been characterized, 29.5% have an imputed function, 2.1% have a phenotype and 19.5% have no function assignment. Only 7% of the modules appear unique to E. coli, and this number is expected to be reduced as more genome data becomes available. The imputed functions were assigned on the basis of manual evaluation of functions predicted by BLAST and DARWIN analyses and by the MAGPIE genome annotation system.ConclusionsMuch knowledge has been gained about functions encoded by the E. coli K-12 genome since the 1997 annotation was published. The data presented here should be useful for analysis of E. coli gene products as well as gene products encoded by other genomes.

GenProtEC: an updated and improved analysis of functions of Escherichia coli K-12 proteins

Using more than one approach to characterizing functions of unknown proteins, we now present in GenProtEC (http://genprotec.mbl.edu/) some level of function information for 87% of Escherichia coli K-12 proteins. A new approach that has yielded new information entails assigning content of structural domains and their functions to E.coli proteins. In addition, some earlier methods have been further refined to provide more meaningful data. The process of identifying and separating multimodular or fused proteins into component modules has been improved. As a result, groups of sequence-similar (paralogous) proteins have been refined. Experimental information from recent literature on previously unknown genes has been incorporated. We now use a rich system of characterizing cell roles which accents the fact that many proteins play more than one cellular role and therefore carry more than one designation from our detailed catalog of roles, MultiFun.

Comparative systems biology across an evolutionary gradient within the Shewanella genus

To what extent genotypic differences translate to phenotypic variation remains a poorly understood issue of paramount importance for several cornerstone concepts of microbiology including the species definition. Here, we take advantage of the completed genomic sequences, expressed proteomic profiles, and physiological studies of 10 closely related Shewanella strains and species to provide quantitative insights into this issue. Our analyses revealed that, despite extensive horizontal gene transfer within these genomes, the genotypic and phenotypic similarities among the organisms were generally predictable from their evolutionary relatedness. The power of the predictions depended on the degree of ecological specialization of the organisms evaluated. Using the gradient of evolutionary relatedness formed by these genomes, we were able to partly isolate the effect of ecology from that of evolutionary divergence and to rank the different cellular functions in terms of their rates of evolution. Our ranking also revealed that whole-cell protein expression differences among these organisms, when the organisms were grown under identical conditions, were relatively larger than differences at the genome level, suggesting that similarity in gene regulation and expression should constitute another important parameter for (new) species description. Collectively, our results provide important new information toward beginning a systems-level understanding of bacterial species and genera.

Genomic Analysis of Carbon Source Metabolism of Shewanella oneidensis MR-1: Predictions versus Experiments

Genomic sequences have been used to find the genetic foundation for carbon source metabolism in Shewanella oneidensis MR-1. Annotated S. oneidensis MR-1 gene products were examined for their sequence similarity to enzymes participating in pathways for utilization of carbon and energy as described in the BioCyc database (http://www.biocyc.org/) or in the primary literature. A picture emerges that relegates five- and six-carbon sugars to minor roles as carbon sources, whereas multiple pathways for utilization of up to three-carbon carbohydrates seem to be present. Capacity to utilize amino acids for carbon and energy is also present. A few contradictions emerged in which enzymes appear to be present by annotations but are not active in the cell according to physiological experiments. Annotations are based on close sequence similarity and will not reveal inactivity due to deleterious mutations or due to lack of coordination of regulation and transport. Genes for a few enzymes known by experiment to be active are not found in the genome. This may be due to extensive divergence after duplication or convergence of function in separate lines in evolution rendering activities undetectable by sequence similarity. To minimize false predictions from protein sequences, we have been conservative in predicting pathways. We did not predict any pathway when, although a partial pathway was seen it was composed largely of enzymes already accounted for in any other complete pathway. This is an example of how a biochemically oriented sequence analysis can generate questions and direct further experimental investigation.

Inference of interactions in cyanobacterial- heterotrophic co-cultures via transcriptome sequencing

We used deep sequencing technology to identify transcriptional adaptation of the euryhaline unicellular cyanobacterium Synechococcus sp. PCC 7002 and the marine facultative aerobe Shewanella putrefaciens W3-18-1 to growth in a co-culture and infer the effect of carbon flux distributions on photoautotroph–heterotroph interactions. The overall transcriptome response of both organisms to co-cultivation was shaped by their respective physiologies and growth constraints. Carbon limitation resulted in the expansion of metabolic capacities, which was manifested through the transcriptional upregulation of transport and catabolic pathways. Although growth coupling occurred via lactate oxidation or secretion of photosynthetically fixed carbon, there was evidence of specific metabolic interactions between the two organisms. These hypothesized interactions were inferred from the excretion of specific amino acids (for example, alanine and methionine) by the cyanobacterium, which correlated with the downregulation of the corresponding biosynthetic machinery in Shewanella W3-18-1. In addition, the broad and consistent decrease of mRNA levels for many Fe-regulated Synechococcus 7002 genes during co-cultivation may indicate increased Fe availability as well as more facile and energy-efficient mechanisms for Fe acquisition by the cyanobacterium. Furthermore, evidence pointed at potentially novel interactions between oxygenic photoautotrophs and heterotrophs related to the oxidative stress response as transcriptional patterns suggested that Synechococcus 7002 rather than Shewanella W3-18-1 provided scavenging functions for reactive oxygen species under co-culture conditions. This study provides an initial insight into the complexity of photoautotrophic–heterotrophic interactions and brings new perspectives of their role in the robustness and stability of the association.

Evolution by leaps : gene duplication in bacteria

BackgroundSequence related families of genes and proteins are common in bacterial genomes. In Escherichia coli they constitute over half of the genome. The presence of families and superfamilies of proteins suggest a history of gene duplication and divergence during evolution. Genome encoded protein families, their size and functional composition, reflect metabolic potentials of the organisms they are found in. Comparing protein families of different organisms give insight into functional differences and similarities.ResultsEquivalent enzyme families with metabolic functions were selected from the genomes of four experimentally characterized bacteria belonging to separate genera. Both similarities and differences were detected in the protein family memberships, with more similarities being detected among the more closely related organisms. Protein family memberships reflected known metabolic characteristics of the organisms. Differences in divergence of functionally characterized enzyme family members accounted for characteristics of taxa known to differ in those biochemical properties and capabilities. While some members of the gene families will have been acquired by lateral exchange and other former family members will have been lost over time, duplication and divergence of genes and functions appear to have been a significant contributor to the functional diversity of today’s microbes.ConclusionsProtein families seem likely to have arisen during evolution by gene duplication and divergence where the gene copies that have been retained are the variants that have led to distinct bacterial physiologies and taxa. Thus divergence of the duplicate enzymes has been a major process in the generation of different kinds of bacteria.ReviewersThis article was reviewed by Drs. Iyer Aravind, Ardcady Mushegian, and Pierre Pontarotti.

Live cell chemical profiling of temporal redox dynamics in a photoautotrophic cyanobacterium

Protein reduction-oxidation (redox) modification is an important mechanism that allows microorganisms to sense environmental changes and initiate cellular responses. We have developed a quantitative chemical probe approach for live cell labeling and imaging of proteins that are sensitive to redox modifications. We utilize this in vivo strategy to identify 176 proteins undergoing ∼5-10-fold dynamic redox change in response to nutrient limitation and subsequent replenishment in the photoautotrophic cyanobacterium Synechococcus sp. PCC 7002. We detect redox changes in as little as 30 s after nutrient perturbation and oscillations in reduction and oxidation for 60 min following the perturbation. Many of the proteins undergoing dynamic redox transformations participate in the major components for the production (photosystems and electron transport chains) or consumption (Calvin-Benson cycle and protein synthesis) of reductant and/or energy in photosynthetic organisms. Thus, our in vivo approach reveals new redox-susceptible proteins and validates those previously identified in vitro.

Comparisons of Shewanella strains based on genome annotations, modeling, and experiments

BackgroundShewanella is a genus of facultatively anaerobic, Gram-negative bacteria that have highly adaptable metabolism which allows them to thrive in diverse environments. This quality makes them an attractive bacterial target for research in bioremediation and microbial fuel cell applications. Constraint-based modeling is a useful tool for helping researchers gain insights into the metabolic capabilities of these bacteria. However, Shewanella oneidensis MR-1 is the only strain with a genome-scale metabolic model constructed out of 21 sequenced Shewanella strains.ResultsIn this work, we updated the model for Shewanella oneidensis MR-1 and constructed metabolic models for three other strains, namely Shewanella sp. MR-4, Shewanella sp. W3-18-1, and Shewanella denitrificans OS217 which span the genus based on the number of genes lost in comparison to MR-1. We also constructed a Shewanella core model that contains the genes shared by all 21 sequenced strains and a few non-conserved genes associated with essential reactions. Model comparisons between the five constructed models were done at two levels – for wildtype strains under different growth conditions and for knockout mutants under the same growth condition. In the first level, growth/no-growth phenotypes were predicted by the models on various carbon sources and electron acceptors. Cluster analysis of these results revealed that the MR-1 model is most similar to the W3-18-1 model, followed by the MR-4 and OS217 models when considering predicted growth phenotypes. However, a cluster analysis done based on metabolic gene content revealed that the MR-4 and W3-18-1 models are the most similar, with the MR-1 and OS217 models being more distinct from these latter two strains. As a second level of comparison, we identified differences in reaction and gene content which give rise to different functional predictions of single and double gene knockout mutants using Comparison of Networks by Gene Alignment (CONGA). Here, we showed how CONGA can be used to find biomass, metabolic, and genetic differences between models.ConclusionsWe developed four strain-specific models and a general core model that can be used to do various in silico studies of Shewanella metabolism. The developed models provide a platform for a systematic investigation of Shewanella metabolism to aid researchers using Shewanella in various biotechnology applications.