Microbial eukaryotic predation pressure and biomass at deep-sea hydrothermal vents.

Deep-sea hydrothermal vent geochemistry shapes the foundation of the microbial food web by fueling chemolithoautotrophic microbial activity. Microbial eukaryotes (or protists) play a critical role in hydrothermal vent food webs as consumers and hosts of symbiotic bacteria, and as a nutritional source to higher trophic levels. We measured microbial eukaryotic cell abundance and predation pressure in low-temperature diffuse hydrothermal fluids at the Von Damm and Piccard vent fields along the Mid-Cayman Rise in the Western Caribbean Sea. We present findings from experiments performed under in situ pressure that show cell abundances and grazing rates higher than those done at 1 atmosphere (shipboard ambient pressure); this trend was attributed to the impact of depressurization on cell integrity. A relationship between the protistan grazing rate, prey cell abundance, and temperature of end-member hydrothermal vent fluid was observed at both vent fields, regardless of experimental approach. Our results show substantial protistan biomass at hydrothermally fueled microbial food webs, and when coupled with improved grazing estimates, suggest an important contribution of grazers to the local carbon export and supply of nutrient resources to the deep ocean.

Draft Genome Sequence of Desulfurobacterium sp. Strain AV08, a Thermophilic Chemolithoautotroph Isolated from a Deep-Sea Hydrothermal Vent.

A thermophilic chemolithoautotrophic bacterium was isolated from vent fluids at Axial Seamount, an active deep-sea volcano in the northeast Pacific Ocean. We present the draft genome sequence of Desulfurobacterium sp. strain AV08.

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.

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

BACKGROUND: 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. RESULTS: 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. CONCLUSIONS: 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.

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.

Changes in translational efficiency is a dominant regulatory mechanism in the environmental response of bacteria.

To understand how cell physiological state affects mRNA translation, we used Shewanella oneidensis MR-1 grown under steady state conditions at either 20% or 8.5% O2. Using a combination of quantitative proteomics and RNA-Seq, we generated high-confidence data on >1000 mRNA and protein pairs. By using a steady state model, we found that differences in protein-mRNA ratios were primarily due to differences in the translational efficiency of specific genes. When oxygen levels were lowered, 28% of the proteins showed at least a 2-fold change in expression. Transcription levels were sp. significantly altered for 26% of the protein changes; translational efficiency was significantly altered for 46% and a combination of both was responsible for the remaining 28%. Changes in translational efficiency were significantly correlated with the codon usage pattern of the genes and measurable tRNA pools changed in response to altered O2 levels. Our results suggest that changes in the translational efficiency of proteins, in part due to altered tRNA pools, is a major determinant of regulated alterations in protein expression levels in bacteria.

Detection of transcriptional triggers in the dynamics of microbial growth: application to the respiratorily versatile bacterium Shewanella oneidensis.

The capacity of microorganisms to respond to variable external conditions requires a coordination of environment-sensing mechanisms and decision-making regulatory circuits. Here, we seek to understand the interplay between these two processes by combining high-throughput measurement of time-dependent mRNA profiles with a novel computational approach that searches for key genetic triggers of transcriptional changes. Our approach helped us understand the regulatory strategies of a respiratorily versatile bacterium with promising bioenergy and bioremediation applications, Shewanella oneidensis, in minimal and rich media. By comparing expression profiles across these two conditions, we unveiled components of the transcriptional program that depend mainly on the growth phase. Conversely, by integrating our time-dependent data with a previously available large compendium of static perturbation responses, we identified transcriptional changes that cannot be explained solely by internal network dynamics, but are rather triggered by specific genes acting as key mediators of an environment-dependent response. These transcriptional triggers include known and novel regulators that respond to carbon, nitrogen and oxygen limitation. Our analysis suggests a sequence of physiological responses, including a coupling between nitrogen depletion and glycogen storage, partially recapitulated through dynamic flux balance analysis, and experimentally confirmed by metabolite measurements. Our approach is broadly applicable to other systems.

Large-scale comparative phenotypic and genomic analyses reveal ecological preferences of shewanella species and identify metabolic pathways conserved at the genus level.

The use of comparative genomics for the study of different microbiological species has increased substantially as sequence technologies become more affordable. However, efforts to fully link a genotype to its phenotype remain limited to the development of one mutant at a time. In this study, we provided a high-throughput alternative to this limiting step by coupling comparative genomics to the use of phenotype arrays for five sequenced Shewanella strains. Positive phenotypes were obtained for 441 nutrients (C, N, P, and S sources), with N-based compounds being the most utilized for all strains. Many genes and pathways predicted by genome analyses were confirmed with the comparative phenotype assay, and three degradation pathways believed to be missing in Shewanella were confirmed as missing. A number of previously unknown gene products were predicted to be parts of pathways or to have a function, expanding the number of gene targets for future genetic analyses. Ecologically, the comparative high-throughput phenotype analysis provided insights into niche specialization among the five different strains. For example, Shewanella amazonensis strain SB2B, isolated from the Amazon River delta, was capable of utilizing 60 C compounds, whereas Shewanella sp. strain W3-18-1, isolated from deep marine sediment, utilized only 25 of them. In spite of the large number of nutrient sources yielding positive results, our study indicated that except for the N sources, they were not sufficiently informative to predict growth phenotypes from increasing evolutionary distances. Our results indicate the importance of phenotypic evaluation for confirming genome predictions. This strategy will accelerate the functional discovery of genes and provide an ecological framework for microbial genome sequencing projects.

Shewanella knowledgebase: integration of the experimental data and computational predictions suggests a biological role for transcription of intergenic regions.

Shewanellae are facultative gamma-proteobacteria whose remarkable respiratory versatility has resulted in interest in their utility for bioremediation of heavy metals and radionuclides and for energy generation in microbial fuel cells. Extensive experimental efforts over the last several years and the availability of 21 sequenced Shewanella genomes made it possible to collect and integrate a wealth of information on the genus into one public resource providing new avenues for making biological discoveries and for developing a system level understanding of the cellular processes. The Shewanella knowledgebase was established in 2005 to provide a framework for integrated genome-based studies on Shewanella ecophysiology. The present version of the knowledgebase provides access to a diverse set of experimental and genomic data along with tools for curation of genome annotations and visualization and integration of genomic data with experimental data. As a demonstration of the utility of this resource, we examined a single microarray data set from Shewanella oneidensis MR-1 for new insights into regulatory processes. The integrated analysis of the data predicted a new type of bacterial transcriptional regulation involving co-transcription of the intergenic region with the downstream gene and suggested a biological role for co-transcription that likely prevents the binding of a regulator of the upstream gene to the regulator binding site located in the intergenic region. Database URL: http://shewanella-knowledgebase.org:8080/Shewanella/ or http://spruce.ornl.gov:8080/Shewanella/

Conserved synteny at the protein family level reveals genes underlying Shewanella species' cold tolerance and predicts their novel phenotypes.

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.

Evolution by leaps: gene duplication in bacteria.

BACKGROUND: Sequence 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. RESULTS: Equivalent 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. CONCLUSIONS: Protein 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.

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.

Protein families reflect the metabolic diversity of organisms and provide support for functional prediction.

Comparative genomics has shown that protein families vary significantly within and across organisms in both number and functional composition. In the present work, we tested how the diversity at the family level reflects biological differences among organisms and contributes to their unique characteristics. For this purpose, we collected sequence-similar proteins of three selected families from model bacteria: Escherichia coli, Bacillus subtilis, and Pseudomonas aeruginosa. Protein relationships were identified using a phylogenomic approach to connect the functional diversity of enzymes to the metabolic capabilities of these organisms. All protein families studied have distinct functional compositions across the selected bacteria as supported by our Bayesian analysis. Some conserved functional features among family members included a shared reaction mechanism, cofactor usage, and/or ligand specificity. Many observations of the presence/absence of protein functions matched current knowledge of the physiology and biochemistry of the bacteria. In some cases, new functional predictions were made to family members previously uncharacterized. We believe that genome comparisons at the protein family level would also be useful in predicting metabolic diversity for organisms that are relatively unknown or currently uncultured in the laboratory.

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.

Identification of diverse carbon utilization pathways in Shewanella oneidensis MR-1 via expression profiling.

To identify pathways of carbon utilization in the metal-reducing marine bacterium Shewanella oneidensis MR-1, we assayed the expression of cells grown with various carbon sources using a high-density oligonucleotide Affymetrix microarray. Our expression profiles reveal genes and regulatory mechanisms which govern the sensing, import, and utilization of the nucleoside inosine, the chitin monomer N-acetylglucosamine, and a casein-derived mixture of amino acids. Our analysis suggests a prominent role for the pentose-phosphate and Entner-Doudoroff pathways in energy metabolism, and regulatory coupling between carbon catabolism and electron acceptor pathways. In sum, these results indicate that S. oneidensis possesses a broader capacity for carbon utilization than previously reported, a view with implications for optimizing its role in microbial fuel cell and bioremediative applications.

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.

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.

Gene fusions and gene duplications: relevance to genomic annotation and functional analysis.

BACKGROUND: Escherichia coli a model organism provides information for annotation of other genomes. Our analysis of its genome has shown that proteins encoded by fused genes need special attention. Such composite (multimodular) proteins consist of two or more components (modules) encoding distinct functions. Multimodular proteins have been found to complicate both annotation and generation of sequence similar groups. Previous work overstated the number of multimodular proteins in E. coli. This work corrects the identification of modules by including sequence information from proteins in 50 sequenced microbial genomes. RESULTS: Multimodular E. coli K-12 proteins were identified from sequence similarities between their component modules and non-fused proteins in 50 genomes and from the literature. We found 109 multimodular proteins in E. coli containing either two or three modules. Most modules had standalone sequence relatives in other genomes. The separated modules together with all the single (un-fused) proteins constitute the sum of all unimodular proteins of E. coli. Pairwise sequence relationships among all E. coli unimodular proteins generated 490 sequence similar, paralogous groups. Groups ranged in size from 92 to 2 members and had varying degrees of relatedness among their members. Some E. coli enzyme groups were compared to homologs in other bacterial genomes. CONCLUSION: The deleterious effects of multimodular proteins on annotation and on the formation of groups of paralogs are emphasized. To improve annotation results, all multimodular proteins in an organism should be detected and when known each function should be connected with its location in the sequence of the protein. When transferring functions by sequence similarity, alignment locations must be noted, particularly when alignments cover only part of the sequences, in order to enable transfer of the correct function. Separating multimodular proteins into module units makes it possible to generate protein groups related by both sequence and function, avoiding mixing of unrelated sequences. Organisms differ in sizes of groups of sequence-related proteins. A sample comparison of orthologs to selected E. coli paralogous groups correlates with known physiological and taxonomic relationships between the organisms.

Global profiling of Shewanella oneidensis MR-1: expression of hypothetical genes and improved functional annotations.

The gamma-proteobacterium Shewanella oneidensis strain MR-1 is a metabolically versatile organism that can reduce a wide range of organic compounds, metal ions, and radionuclides. Similar to most other sequenced organisms, approximately 40% of the predicted ORFs in the S. oneidensis genome were annotated as uncharacterized "hypothetical" genes. We implemented an integrative approach by using experimental and computational analyses to provide more detailed insight into gene function. Global expression profiles were determined for cells after UV irradiation and under aerobic and suboxic growth conditions. Transcriptomic and proteomic analyses confidently identified 538 hypothetical genes as expressed in S. oneidensis cells both as mRNAs and proteins (33% of all predicted hypothetical proteins). Publicly available analysis tools and databases and the expression data were applied to improve the annotation of these genes. The annotation results were scored by using a seven-category schema that ranked both confidence and precision of the functional assignment. We were able to identify homologs for nearly all of these hypothetical proteins (97%), but could confidently assign exact biochemical functions for only 16 proteins (category 1; 3%). Altogether, computational and experimental evidence provided functional assignments or insights for 240 more genes (categories 2-5; 45%). These functional annotations advance our understanding of genes involved in vital cellular processes, including energy conversion, ion transport, secondary metabolism, and signal transduction. We propose that this integrative approach offers a valuable means to undertake the enormous challenge of characterizing the rapidly growing number of hypothetical proteins with each newly sequenced genome.

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.