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.

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.comparative genomics ͉ evolution ͉ proteomics ͉ speciation ͉ phenotype

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.

An enriched classification system for cellular functions of gene products of Escherichia coli K-12 was developed based on the initial classification by Riley. In the new classification scheme, MultiFun, cellular functions are divided into 10 major categories: Metabolism, Information Transfer, Regulation, Transport, Cell Processes, Cell Structure, Location, Extra-chromosomal Origin, DNA Site, and Cryptic Gene. These major categories are further sub-divided into a hierarchical scheme. Two thousand nine hundred twenty-two gene products of E. coli K-12 were assigned to one or more functions depending on the role they play in the cell. Functional assignments were made to 66% of E. coli gene products, ranging from 1 to 16 assignments per gene product. The expansion of cellular function categories and the assignment to more than one category (multifunction) provides a more complete description of the gene products and their roles and hence better reflects the functional complexity of organisms. We believe this classification system will be useful in the field of genome analysis, both for annotation purposes and for comparative studies. The functional classification scheme and the cellular function assignments made to E. coli gene products can be accessed from the web at the databases GenProtEC (http://genprotec.mbl.edu) and EcoCyc (http://www.ecocyc.org).

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.