Romine Margaret F.

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Romine
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Margaret F.
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  • Preprint
    Comparative systems biology across an evolutionary gradient within the Shewanella genus
    ( 2009-07) Konstantinidis, Konstantinos T. ; Serres, Margrethe H. ; Romine, Margaret F. ; Rodrigues, Jorge L. M. ; Auchtung, Jennifer ; McCue, Lee-Ann ; Lipton, Mary S. ; Obraztsova, Anna Y. ; Giometti, Carol S. ; Nealson, Kenneth H. ; Fredrickson, James K. ; Tiedje, James M.
    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 ten 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 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 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 towards beginning a systems-level understanding of bacterial species and genera.
  • Article
    Conserved synteny at the protein family level reveals genes underlying Shewanella species’ cold tolerance and predicts their novel phenotypes
    (Springer, 2009-10-03) Karpinets, Tatiana V. ; Obraztsova, Anna Y. ; Wang, Yanbing ; Schmoyer, Denise D. ; Kora, Guruprasad H. ; Park, Byung H. ; Serres, Margrethe H. ; Romine, Margaret F. ; Land, Miriam L. ; Kothe, Terence B. ; Fredrickson, James K. ; Nealson, Kenneth H. ; Uberbacher, Edward C.
    Bacteria of the genus Shewanella can thrive in different environments and demonstrate significant variability in their metabolic and ecophysiological capabilities including cold and salt tolerance. Genomic characteristics underlying this variability across species are largely unknown. In this study, we address the problem by a comparison of the physiological, metabolic, and genomic characteristics of 19 sequenced Shewanella species. We have employed two novel approaches based on association of a phenotypic trait with the number of the trait-specific protein families (Pfam domains) and on the conservation of synteny (order in the genome) of the trait-related genes. Our first approach is top-down and involves experimental evaluation and quantification of the species’ cold tolerance followed by identification of the correlated Pfam domains and genes with a conserved synteny. The second, a bottom-up approach, predicts novel phenotypes of the species by calculating profiles of each Pfam domain among their genomes and following pair-wise correlation of the profiles and their network clustering. Using the first approach, we find a link between cold and salt tolerance of the species and the presence in the genome of a Na+/H+ antiporter gene cluster. Other cold-tolerance-related genes include peptidases, chemotaxis sensory transducer proteins, a cysteine exporter, and helicases. Using the bottom-up approach, we found several novel phenotypes in the newly sequenced Shewanella species, including degradation of aromatic compounds by an aerobic hybrid pathway in Shewanella woodyi, degradation of ethanolamine by Shewanella benthica, and propanediol degradation by Shewanella putrefaciens CN32 and Shewanella sp. W3-18-1.
  • Article
    Comparisons of Shewanella strains based on genome annotations, modeling, and experiments
    (BioMed Central, 2014-03-12) Ong, Wai Kit ; Vu, Trang T. ; Lovendahl, Klaus N. ; Llull, Jenna M. ; Serres, Margrethe H. ; Romine, Margaret F. ; Reed, Jennifer L.
    Shewanella 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. In 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. We 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.