Comparative bacterial proteomics: analysis of the core genome concept

A local-scale One Health genomic surveillance of Clostridioides difficile demonstrates highly related strains from humans, canines, and the environment

Although infections caused by Clostridioides difficile have historically been attributed to hospital acquisition, growing evidence supports the role of community acquisition in C. difficile infection (CDI). Symptoms of CDI can range from mild, self-resolving diarrhoea to toxic megacolon, pseudomembranous colitis, and death. In this study, we sampled C. difficile from clinical, environmental, and canine reservoirs in Flagstaff, Arizona, USA, to understand the distribution and transmission of the pathogen in a One Health framework; Flagstaff is a medium-sized, geographically isolated city with a single hospital system, making it an ideal site to characterize genomic overlap between sequenced C. difficile isolates across reservoirs. An analysis of 562 genomes from Flagstaff isolates identified 65 sequence types (STs), with eight STs being found across all three reservoirs and another nine found across two reservoirs. A screen of toxin genes in the pathogenicity locus identified nine STs where all isolates lost the toxin genes needed for CDI manifestation (tcdB, tcdA), demonstrating the widespread distribution of non-toxigenic C. difficile (NTCD) isolates in all three reservoirs; 15 NTCD genomes were sequenced from symptomatic, clinical samples, including two from mixed infections that contained both tcdB+ and tcdB- isolates. A comparative single nucleotide polymorphism (SNP) analysis of clinically derived isolates identified 78 genomes falling within clusters separated by ≤2 SNPs, indicating that ~19 % of clinical isolates are associated with potential healthcare-associated transmission clusters; only symptomatic cases were sampled in this study, and we did not sample asymptomatic transmission. Using this same SNP threshold, we identified genomic overlap between canine and soil isolates, as well as putative transmission between environmental and human reservoirs. The core genome of isolates sequenced in this study plus a representative set of public C. difficile genomes (n=136), was 2690 coding region sequences, which constitutes ~70 % of an individual C. difficile genome; this number is significantly higher than has been published in some other studies, suggesting that genome data quality is important in understanding the minimal number of genes needed by C. difficile. This study demonstrates the close genomic overlap among isolates sampled across reservoirs, which was facilitated by maximizing the genomic search space used for comprehensive identification of potential transmission events. Understanding the distribution of toxigenic and non-toxigenic C. difficile across reservoirs has implications for surveillance sampling strategies, characterizing routes of infections, and implementing mitigation measures to limit human infection.

“Omics” Technologies - What Have They Told Us About Uropathogenic Escherichia coli Fitness and Virulence During Urinary Tract Infection?

Uropathogenic Escherichia coli (UPEC) is the main etiological agent of urinary tract infection (UTI), a widespread infectious disease of great impact on human health. This is further emphasized by the rapidly increase in antimicrobial resistance in UPEC, which compromises UTI treatment. UPEC biology is highly complex since uropathogens must adopt extracellular and intracellular lifestyles and adapt to different niches in the host. In this context, the implementation of forefront ‘omics’ technologies has provided substantial insight into the understanding of UPEC pathogenesis, which has opened the doors for new therapeutics and prophylactics discovery programs. Thus, ‘omics’ technologies applied to studies of UPEC during UTI, or in models of UTI, have revealed extensive lists of factors that are important for the ability of UPEC to cause disease. The multitude of large ‘omics’ datasets that have been generated calls for scrutinized analysis of specific factors that may be of interest for further development of novel treatment strategies. In this review, we describe main UPEC determinants involved in UTI as estimated by ‘omics’ studies, and we compare prediction of factors across the different ‘omics’ technologies, with a focus on those that have been confirmed to be relevant under UTI-related conditions. We also discuss current challenges and future perspectives regarding analysis of data to provide an overview and better understanding of UPEC mechanisms involved in pathogenesis which should assist in the selection of target sites for future prophylaxis and treatment.

Genome Mining of the Genus Streptacidiphilus for Biosynthetic and Biodegradation Potential

The genus Streptacidiphilus represents a group of acidophilic actinobacteria within the family Streptomycetaceae, and currently encompasses 15 validly named species, which include five recent additions within the last two years. Considering the potential of the related genera within the family, namely Streptomyces and Kitasatospora, these relatively new members of the family can also be a promising source for novel secondary metabolites. At present, 15 genome data for 11 species from this genus are available, which can provide valuable information on their biology including the potential for metabolite production as well as enzymatic activities in comparison to the neighboring taxa. In this study, the genome sequences of 11 Streptacidiphilus species were subjected to the comparative analysis together with selected Streptomyces and Kitasatospora genomes. This study represents the first comprehensive comparative genomic analysis of the genus Streptacidiphilus. The results indicate that the genomes of Streptacidiphilus contained various secondary metabolite (SM) producing biosynthetic gene clusters (BGCs), some of them exclusively identified in Streptacidiphilus only. Several of these clusters may potentially code for SMs that may have a broad range of bioactivities, such as antibacterial, antifungal, antimalarial and antitumor activities. The biodegradation capabilities of Streptacidiphilus were also explored by investigating the hydrolytic enzymes for complex carbohydrates. Although all genomes were enriched with carbohydrate-active enzymes (CAZymes), their numbers in the genomes of some strains such as Streptacidiphilus carbonis NBRC 100919^T were higher as compared to well-known carbohydrate degrading organisms. These distinctive features of each Streptacidiphilus species make them interesting candidates for future studies with respect to their potential for SM production and enzymatic activities.

Genetic Variants of the DSF Quorum Sensing System in Stenotrophomonas maltophilia Influence Virulence and Resistance Phenotypes Among Genotypically Diverse Clinical Isolates

The pathogenicity of Stenotrophomonas maltophilia is regulated in part by its quorum sensing (QS) system. The main QS signaling molecule in S. maltophilia is known as diffusible signal factor (DSF), and the rpf gene cluster is responsible for its synthesis and perception. Two cluster variants have been previously described, rpf-1 and rpf-2, which differ basically in the conditions under which DSF is produced. Here, correlations between the rpf variant and antibiotic susceptibility, LPS electrophoretic profiles and virulence-related phenotypes were evaluated for a collection of 78 geographically and genetically diverse clinical strains of S. maltophilia. In general there were associations between previously established genogroups and the genetic variant of the rpf cluster. However, only few genotype-phenotype correlations could be observed. Resistance to the β-lactam antibiotics ceftazidime and ticarcillin was associated with strains carrying the rpf-1 variant, whereas strains of variant rpf-2, particularly those of genogroup C, showed higher resistance levels to colistin. Strains of variant rpf-2 were also significantly more virulent to Galleria mellonella larvae than those of rpf-1, most likely due to an increased ability of rpf-2 strains to form biofilms. A comparative genomic analysis revealed the presence of proteins unique to individual genogroups. In particular, the strains of genogroup C share an operon that encodes for a new virulence determinant in S. maltophilia related to the synthesis of an alternative Flp/Tad pilus. Overall, this study establishes a link between the DSF-based QS system and the virulence and resistance phenotypes in this species, and identifies potential high-risk clones circulating in European hospitals.

Metaproteomics analysis of microbial diversity of human saliva and tongue dorsum in young healthy individuals

Background: The human oral microbiome influences initiation or progression of diseases like caries or periodontitis. Metaproteomics approaches enable the simultaneous investigation of microbial and host proteins and their interactions to improve understanding of oral diseases.

Objective: In this study, we provide a detailed metaproteomics perspective of the composition of salivary and tongue microbial communities of young healthy subjects.

Design: Stimulated saliva and tongue samples were collected from 24 healthy volunteers, subjected to shotgun nLC-MS/MS and analyzed by the Trans-Proteomic Pipeline and the Prophane tool.

Results: 3,969 bacterial and 1,857 human proteins could be identified from saliva and tongue, respectively. In total, 1,971 bacterial metaproteins and 1,154 human proteins were shared in both sample types. Twice the amount of bacterial metaproteins were uniquely identified for the tongue dorsum compared to saliva. Overall, 107 bacterial genera of seven phyla formed the microbiome. Comparative analysis identified significant functional differences between the microbial biofilm on the tongue and the microbiome of saliva.

Conclusion: Even if the microbial communities of saliva and tongue dorsum showed a strong similarity based on identified protein functions and deduced bacterial composition, certain specific characteristics were observed. Both microbiomes exhibit a great diversity with seven genera being most abundant.

The synergistic effect of concatenation in phylogenomics: the case in Pantoea

With the increased availability of genome sequences for bacteria, it has become routine practice to construct genome-based phylogenies. These phylogenies have formed the basis for various taxonomic decisions, especially for resolving problematic relationships between taxa. Despite the popularity of concatenating shared genes to obtain well-supported phylogenies, various issues regarding this combined-evidence approach have been raised. These include the introduction of phylogenetic error into datasets, as well as incongruence due to organism-level evolutionary processes, particularly horizontal gene transfer and incomplete lineage sorting. Because of the huge effect that this could have on phylogenies, we evaluated the impact of phylogenetic conflict caused by organism-level evolutionary processes on the established species phylogeny for Pantoea, a member of the Enterobacterales. We explored the presence and distribution of phylogenetic conflict at the gene partition and nucleotide levels, by identifying putative inter-lineage recombination events that might have contributed to such conflict. Furthermore, we determined whether smaller, randomly constructed datasets had sufficient signal to reconstruct the current species tree hypothesis or if they would be overshadowed by phylogenetic incongruence. We found that no individual gene tree was fully congruent with the species phylogeny of Pantoea, although many of the expected nodes were supported by various individual genes across the genome. Evidence of recombination was found across all lineages within Pantoea, and provides support for organism-level evolutionary processes as a potential source of phylogenetic conflict. The phylogenetic signal from at least 70 random genes recovered robust, well-supported phylogenies for the backbone and most species relationships of Pantoea, and was unaffected by phylogenetic conflict within the dataset. Furthermore, despite providing limited resolution among taxa at the level of single gene trees, concatenated analyses of genes that were identified as having no signal resulted in a phylogeny that resembled the species phylogeny of Pantoea. This distribution of signal and noise across the genome presents the ideal situation for phylogenetic inference, as the topology from a ≥70-gene concatenated species phylogeny is not driven by single genes, and our data suggests that this finding may also hold true for smaller datasets. We thus argue that, by using a concatenation-based approach in phylogenomics, one can obtain robust phylogenies due to the synergistic effect of the combined signal obtained from multiple genes.

Major Traditional Probiotics: Comparative Genomic Analyses and Roles in Gut Microbiome of Eight Cohorts

Modulating gut microbiota to promote host health is well recognized. Therefore, people consume dietary products containing traditional probiotics in wishing to improve their health, and they need more research-based advices on how to select products with suitable probiotic species. Probiotic designers are sometimes confused about how to design precision products for different consumers by taking advantages of different probiotic species’ strengths. Additionally, large-scale analyses on traditional probiotic complementarity potentials and their roles in gut microbiome related to common diseases are not well understood. Here, we comprehensively analyzed 444 genomes of major traditional probiotic (sub) species (MTPS, n = 15) by combining one newly sequenced genome with all of the public NCBI-available MTPS-related genomes. The public human fecal metagenomic data (n = 1,815) of eight cohorts were used to evaluate the roles of MTPS, compared to other main gut bacteria, in disease association by examining the species enrichment direction in disease group or the control group. Our work provided a comprehensive genetic landscape and complementarity relations for MTPS and shed light on personalized probiotic supplements for consumers with different health status and the necessity that researchers and manufactures could explore novel probiotics as well as traditional ones.

A degeneration-reducing criterion for optimal digital mapping of genetic codes

Bioinformatics may seem to be a scientific field processing primarily large string datasets, as nucleotides and amino acids are represented with dedicated characters. On the other hand, many computational tasks that bioinformatics challenges are mathematical problems understandable as operations with digits. In fact, many computational tasks are solved this way in the background. One of the most widely used digital representations is mapping of nucleotides and amino acids with integers 0–3 and 0–20, respectively. The limitation of this mapping occurs when the digital signal of nucleotides has to be translated into a digital signal of amino acids as the genetic code is degenerated. This causes non-monotonies in a mapping function. Although map for reducing this undesirable effect has already been proposed, it is defined theoretically and for standard genetic codes only. In this study, we derived a novel optimal criterion for reducing the influence of degeneration by utilizing a large dataset of real sequences with various genetic codes. As a result, we proposed a new robust global optimal map suitable for any genetic code as well as specialized optimal maps for particular genetic codes.

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Optimization of 1D numerical representation for DNA to protein translation.

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Reducing genetic code degeneracy in numerical representation of DNA sequences.

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More robust numerical conversion used for genomic-proteomic analysis.

1,520 reference genomes from cultivated human gut bacteria enable functional microbiome analyses

Reference genomes are essential for metagenomic analyses and functional characterization of the human gut microbiota. We present the Culturable Genome Reference (CGR), a collection of 1,520 nonredundant, high-quality draft genomes generated from >6,000 bacteria cultivated from fecal samples of healthy humans. Of the 1,520 genomes, which were chosen to cover all major bacterial phyla and genera in the human gut, 264 are not represented in existing reference genome catalogs. We show that this increase in the number of reference bacterial genomes improves the rate of mapping metagenomic sequencing reads from 50% to >70%, enabling higher-resolution descriptions of the human gut microbiome. We use the CGR genomes to annotate functions of 338 bacterial species, showing the utility of this resource for functional studies. We also carry out a pan-genome analysis of 38 important human gut species, which reveals the diversity and specificity of functional enrichment between their core and dispensable genomes.

A resource of >1,500 bacterial reference genomes sheds light on the human gut microbiome.

Individual Variability of Protein Expression in Human Tissues

Human tissues are known to exhibit interindividual variability, but a deeper understanding of the different factors affecting protein expression is necessary to further apply this knowledge. Our goal was to explore the proteomic variability between individuals as well as between healthy and diseased samples, and to test the efficacy of machine learning classifiers. In order to investigate whether disparate proteomics data sets may be combined, we performed a retrospective analysis of proteomics data from 9 different human tissues. These data sets represent several different sample prep methods, mass spectrometry instruments, and tissue health. Using these data, we examined interindividual and intertissue variability in peptide expression, and analyzed the methods required to build accurate tissue classifiers. We also evaluated the limits of tissue classification by downsampling the peptide data to simulate situations where less data is available, such as clinical biopsies, laser capture microdissection or potentially single-cell proteomics. Our findings reveal the strong potential for utilizing proteomics data to build robust tissue classifiers, which has many prospective clinical applications for evaluating the applicability of model clinical systems.

BPSL1626: Reverse and Structural Vaccinology Reveal a Novel Candidate for Vaccine Design against Burkholderia pseudomallei

Due to significant advances in computational biology, protein prediction, together with antigen and epitope design, have rapidly moved from conventional methods, based on experimental approaches, to in silico-based bioinformatics methods. In this context, we report a reverse vaccinology study that identified a panel of 104 candidate antigens from the Gram-negative bacterial pathogen Burkholderia pseudomallei, which is responsible for the disease melioidosis. B. pseudomallei can cause fatal sepsis in endemic populations in the tropical regions of the world and treatment with antibiotics is mostly ineffective. With the aim of identifying potential vaccine candidates, we report the experimental validation of predicted antigen and type I fimbrial subunit, BPSL1626, which we show is able to recognize and bind human antibodies from the sera of Burkholderia infected patients and to stimulate T-lymphocytes in vitro. The prerequisite for a melioidosis vaccine, in fact, is that both antibody- and cell-mediated immune responses must be triggered. In order to reveal potential antigenic regions of the protein that may aid immunogen re-design, we also report the crystal structure of BPSL1626 at 1.9 Å resolution on which structure-based epitope predictions were based. Overall, our data suggest that BPSL1626 and three epitope regions here-identified can represent viable candidates as potential antigenic molecules.

Comparative Analysis of Secretome Profiles of Manganese(II)-Oxidizing Ascomycete Fungi

Fungal secretomes contain a wide range of hydrolytic and oxidative enzymes, including cellulases, hemicellulases, pectinases, and lignin-degrading accessory enzymes, that synergistically drive litter decomposition in the environment. While secretome studies of model organisms such as Phanerochaete chrysosporium and Aspergillus species have greatly expanded our knowledge of these enzymes, few have extended secretome characterization to environmental isolates or conducted side-by-side comparisons of diverse species. Thus, the mechanisms of carbon degradation by many ubiquitous soil fungi remain poorly understood. Here we use a combination of LC-MS/MS, genomic, and bioinformatic analyses to characterize and compare the protein composition of the secretomes of four recently isolated, cosmopolitan, Mn(II)-oxidizing Ascomycetes (Alternaria alternata SRC1lrK2f, Stagonospora sp. SRC1lsM3a, Pyrenochaeta sp. DS3sAY3a, and Paraconiothyrium sporulosum AP3s5-JAC2a). We demonstrate that the organisms produce a rich yet functionally similar suite of extracellular enzymes, with species-specific differences in secretome composition arising from unique amino acid sequences rather than overall protein function. Furthermore, we identify not only a wide range of carbohydrate-active enzymes that can directly oxidize recalcitrant carbon, but also an impressive suite of redox-active accessory enzymes that suggests a role for Fenton-based hydroxyl radical formation in indirect, non-specific lignocellulose attack. Our findings highlight the diverse oxidative capacity of these environmental isolates and enhance our understanding of the role of filamentous Ascomycetes in carbon turnover in the environment.

Pan-proteomics, a concept for unifying quantitative proteome measurements when comparing closely-related bacterial strains

The comparison of proteomes between genetically heterogeneous bacterial strains may offer valuable insights into physiological diversity and function, particularly where such variation aids in the survival and virulence of clinically-relevant strains. However, reports of such comparisons frequently fail to account for underlying genetic variance. As a consequence, the current knowledge regarding bacterial physiological diversity at the protein level may be incomplete or inaccurate. To address this, greater consideration must be given to the impact of genetic heterogeneity on proteome comparisons. This may be possible through the use of pan-proteomics, an analytical concept that permits the ability to qualitatively and quantitatively compare the proteomes of genetically heterogeneous organisms. Limited examples of this emerging technology highlight currently unmet analytical challenges. In this article we define pan-proteomics, where its value lies in microbiology, and discuss the technical considerations critical to its successful execution and potential future application.

Comparative Genomic Analysis of Mannheimia haemolytica from Bovine Sources

Bovine respiratory disease is a common health problem in beef production. The primary bacterial agent involved, Mannheimia haemolytica, is a target for antimicrobial therapy and at risk for associated antimicrobial resistance development. The role of M. haemolytica in pathogenesis is linked to serotype with serotypes 1 (S1) and 6 (S6) isolated from pneumonic lesions and serotype 2 (S2) found in the upper respiratory tract of healthy animals. Here, we sequenced the genomes of 11 strains of M. haemolytica, representing all three serotypes and performed comparative genomics analysis to identify genetic features that may contribute to pathogenesis. Possible virulence associated genes were identified within 14 distinct prophage, including a periplasmic chaperone, a lipoprotein, peptidoglycan glycosyltransferase and a stress response protein. Prophage content ranged from 2–8 per genome, but was higher in S1 and S6 strains. A type I-C CRISPR-Cas system was identified in each strain with spacer diversity and organization conserved among serotypes. The majority of spacers occur in S1 and S6 strains and originate from phage suggesting that serotypes 1 and 6 may be more resistant to phage predation. However, two spacers complementary to the host chromosome targeting a UDP-N-acetylglucosamine 2-epimerase and a glycosyl transferases group 1 gene are present in S1 and S6 strains only indicating these serotypes may employ CRISPR-Cas to regulate gene expression to avoid host immune responses or enhance adhesion during infection. Integrative conjugative elements are present in nine of the eleven genomes. Three of these harbor extensive multi-drug resistance cassettes encoding resistance against the majority of drugs used to combat infection in beef cattle, including macrolides and tetracyclines used in human medicine. The findings here identify key features that are likely contributing to serotype related pathogenesis and specific targets for vaccine design intended to reduce the dependency on antibiotics to treat respiratory infection in cattle.

Comparative Proteomic Analysis of Desulfotomaculum reducens MI-1: Insights into the Metabolic Versatility of a Gram-Positive Sulfate- and Metal-Reducing Bacterium

The proteomes of the metabolically versatile and poorly characterized Gram-positive bacterium Desulfotomaculum reducens MI-1 were compared across four cultivation conditions including sulfate reduction, soluble Fe(III) reduction, insoluble Fe(III) reduction, and pyruvate fermentation. Collectively across conditions, we observed at high confidence ~38% of genome-encoded proteins. Here, we focus on proteins that display significant differential abundance on conditions tested. To the best of our knowledge, this is the first full-proteome study focused on a Gram-positive organism cultivated either on sulfate or metal-reducing conditions. Several proteins with uncharacterized function encoded within heterodisulfide reductase (hdr)-containing loci were upregulated on either sulfate (Dred_0633-4, Dred_0689-90, and Dred_1325-30) or Fe(III)-citrate-reducing conditions (Dred_0432-3 and Dred_1778-84). Two of these hdr-containing loci display homology to recently described flavin-based electron bifurcation (FBEB) pathways (Dred_1325-30 and Dred_1778-84). Additionally, we propose that a cluster of proteins, which is homologous to a described FBEB lactate dehydrogenase (LDH) complex, is performing lactate oxidation in D. reducens (Dred_0367-9). Analysis of the putative sulfate reduction machinery in D. reducens revealed that most of these proteins are constitutively expressed across cultivation conditions tested. In addition, peptides from the single multiheme c-type cytochrome (MHC) in the genome were exclusively observed on the insoluble Fe(III) condition, suggesting that this MHC may play a role in reduction of insoluble metals.

The Pacific Northwest National Laboratory library of bacterial and archaeal proteomic biodiversity

This Data Descriptor announces the submission to public repositories of the PNNL Biodiversity Library, a large collection of global proteomics data for 112 bacterial and archaeal organisms. The data comprises 35,162 tandem mass spectrometry (MS/MS) datasets from ~10 years of research. All data has been searched, annotated and organized in a consistent manner to promote reuse by the community. Protein identifications were cross-referenced with KEGG functional annotations which allows for pathway oriented investigation. We present the data as a freely available community resource. A variety of data re-use options are described for computational modelling, proteomics assay design and bioengineering. Instrument data and analysis files are available at ProteomeXchange via the MassIVE partner repository under the identifiers PXD001860 and MSV000079053.

Systems biology perspectives on minimal and simpler cells

The concept of the minimal cell has fascinated scientists for a long time, from both fundamental and applied points of view. This broad concept encompasses extreme reductions of genomes, the last universal common ancestor (LUCA), the creation of semiartificial cells, and the design of protocells and chassis cells. Here we review these different areas of research and identify common and complementary aspects of each one. We focus on systems biology, a discipline that is greatly facilitating the classical top-down and bottom-up approaches toward minimal cells. In addition, we also review the so-called middle-out approach and its contributions to the field with mathematical and computational models. Owing to the advances in genomics technologies, much of the work in this area has been centered on minimal genomes, or rather minimal gene sets, required to sustain life. Nevertheless, a fundamental expansion has been taking place in the last few years wherein the minimal gene set is viewed as a backbone of a more complex system. Complementing genomics, progress is being made in understanding the system-wide properties at the levels of the transcriptome, proteome, and metabolome. Network modeling approaches are enabling the integration of these different omics data sets toward an understanding of the complex molecular pathways connecting genotype to phenotype. We review key concepts central to the mapping and modeling of this complexity, which is at the heart of research on minimal cells. Finally, we discuss the distinction between minimizing the number of cellular components and minimizing cellular complexity, toward an improved understanding and utilization of minimal and simpler cells.

Construction of a dairy microbial genome catalog opens new perspectives for the metagenomic analysis of dairy fermented products

Background

Microbial communities of traditional cheeses are complex and insufficiently characterized. The origin, safety and functional role in cheese making of these microbial communities are still not well understood. Metagenomic analysis of these communities by high throughput shotgun sequencing is a promising approach to characterize their genomic and functional profiles. Such analyses, however, critically depend on the availability of appropriate reference genome databases against which the sequencing reads can be aligned.

Results

We built a reference genome catalog suitable for short read metagenomic analysis using a low-cost sequencing strategy. We selected 142 bacteria isolated from dairy products belonging to 137 different species and 67 genera, and succeeded to reconstruct the draft genome of 117 of them at a standard or high quality level, including isolates from the genera Kluyvera, Luteococcus and Marinilactibacillus, still missing from public database. To demonstrate the potential of this catalog, we analysed the microbial composition of the surface of two smear cheeses and one blue-veined cheese, and showed that a significant part of the microbiota of these traditional cheeses was composed of microorganisms newly sequenced in our study.

Conclusions

Our study provides data, which combined with publicly available genome references, represents the most expansive catalog to date of cheese-associated bacteria. Using this extended dairy catalog, we revealed the presence in traditional cheese of dominant microorganisms not deliberately inoculated, mainly Gram-negative genera such as Pseudoalteromonas haloplanktis or Psychrobacter immobilis, that may contribute to the characteristics of cheese produced through traditional methods.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-15-1101) contains supplementary material, which is available to authorized users.

Genomic encyclopedia of type strains of the genus Bifidobacterium

Bifidobacteria represent one of the dominant microbial groups that are present in the gut of various animals, being particularly prevalent during the suckling stage of life of humans and other mammals. However, the overall genome structure of this group of microorganisms remains largely unexplored. Here, we sequenced the genomes of 42 representative (sub)species across the Bifidobacterium genus and used this information to explore the overall genetic picture of this bacterial group. Furthermore, the genomic data described here were used to reconstruct the evolutionary development of the Bifidobacterium genus. This reconstruction suggests that its evolution was substantially influenced by genetic adaptations to obtain access to glycans, thereby representing a common and potent evolutionary force in shaping bifidobacterial genomes.

SPOCS: software for predicting and visualizing orthology/paralogy relationships among genomes

SUMMARY

At the rate that prokaryotic genomes can now be generated, comparative genomics studies require a flexible method for quickly and accurately predicting orthologs among the rapidly changing set of genomes available. SPOCS implements a graph-based ortholog prediction method to generate a simple tab-delimited table of orthologs and in addition, html files that provide a visualization of the predicted ortholog/paralog relationships to which gene/protein expression metadata may be overlaid.

AVAILABILITY AND IMPLEMENTATION

A SPOCS web application is freely available at http://cbb.pnnl.gov/portal/tools/spocs.html. Source code for Linux systems is also freely available under an open source license at http://cbb.pnnl.gov/portal/software/spocs.html; the Boost C++ libraries and BLAST are required.

Fluctuations in species-level protein expression occur during element and nutrient cycling in the subsurface

While microbial activities in environmental systems play a key role in the utilization and cycling of essential elements and compounds, microbial activity and growth frequently fluctuates in response to environmental stimuli and perturbations. To investigate these fluctuations within a saturated aquifer system, we monitored a carbon-stimulated in situ Geobacter population while iron reduction was occurring, using 16S rRNA abundances and high-resolution tandem mass spectrometry proteome measurements. Following carbon amendment, 16S rRNA analysis of temporally separated samples revealed the rapid enrichment of Geobacter-like environmental strains with strong similarity to G. bemidjiensis. Tandem mass spectrometry proteomics measurements suggest high carbon flux through Geobacter respiratory pathways, and the synthesis of anapleurotic four carbon compounds from acetyl-CoA via pyruvate ferredoxin oxidoreductase activity. Across a 40-day period where Fe(III) reduction was occurring, fluctuations in protein expression reflected changes in anabolic versus catabolic reactions, with increased levels of biosynthesis occurring soon after acetate arrival in the aquifer. In addition, localized shifts in nutrient limitation were inferred based on expression of nitrogenase enzymes and phosphate uptake proteins. These temporal data offer the first example of differing microbial protein expression associated with changing geochemical conditions in a subsurface environment.

Expression divergence between Escherichia coli and Salmonella enterica serovar Typhimurium reflects their lifestyles

Escherichia coli K12 is a commensal bacteria and one of the best-studied model organisms. Salmonella enterica serovar Typhimurium, on the other hand, is a facultative intracellular pathogen. These two prokaryotic species can be considered related phylogenetically, and they share a large amount of their genetic material, which is commonly termed the "core genome." Despite their shared core genome, both species display very different lifestyles, and it is unclear to what extent the core genome, apart from the species-specific genes, plays a role in this lifestyle divergence. In this study, we focus on the differences in expression domains for the orthologous genes in E. coli and S. Typhimurium. The iterative comparison of coexpression methodology was used on large expression compendia of both species to uncover the conservation and divergence of gene expression. We found that gene expression conservation occurs mostly independently from amino acid similarity. According to our estimates, at least more than one quarter of the orthologous genes has a different expression domain in E. coli than in S. Typhimurium. Genes involved with key cellular processes are most likely to have conserved their expression domains, whereas genes showing diverged expression are associated with metabolic processes that, although present in both species, are regulated differently. The expression domains of the shared "core" genome of E. coli and S. Typhimurium, consisting of highly conserved orthologs, have been tuned to help accommodate the differences in lifestyle and the pathogenic potential of Salmonella.

By their genes ye shall know them: genomic signatures of predatory bacteria

Predatory bacteria are taxonomically disparate, exhibit diverse predatory strategies and are widely distributed in varied environments. To date, their predatory phenotypes cannot be discerned in genome sequence data thereby limiting our understanding of bacterial predation, and of its impact in nature. Here, we define the 'predatome,' that is, sets of protein families that reflect the phenotypes of predatory bacteria. The proteomes of all sequenced 11 predatory bacteria, including two de novo sequenced genomes, and 19 non-predatory bacteria from across the phylogenetic and ecological landscapes were compared. Protein families discriminating between the two groups were identified and quantified, demonstrating that differences in the proteomes of predatory and non-predatory bacteria are large and significant. This analysis allows predictions to be made, as we show by confirming from genome data an over-looked bacterial predator. The predatome exhibits deficiencies in riboflavin and amino acids biosynthesis, suggesting that predators obtain them from their prey. In contrast, these genomes are highly enriched in adhesins, proteases and particular metabolic proteins, used for binding to, processing and consuming prey, respectively. Strikingly, predators and non-predators differ in isoprenoid biosynthesis: predators use the mevalonate pathway, whereas non-predators, like almost all bacteria, use the DOXP pathway. By defining predatory signatures in bacterial genomes, the predatory potential they encode can be uncovered, filling an essential gap for measuring bacterial predation in nature. Moreover, we suggest that full-genome proteomic comparisons are applicable to other ecological interactions between microbes, and provide a convenient and rational tool for the functional classification of bacteria.

Visualizing evolution in real-time method for strain engineering

The adaptive landscape for an industrially relevant phenotype is determined by the effects of the genetic determinants on the fitness of the microbial system. Identifying the underlying adaptive landscape for a particular phenotype of interest will greatly enhance our abilities to engineer more robust microbial strains. Visualizing evolution in real-time (VERT) is a recently developed method based on in vitro adaptive evolution that facilitates the identification of fitter mutants throughout the course of evolution. Combined with high-throughput genomic tools, VERT can greatly enhance the mapping of adaptive landscapes of industrially relevant phenotypes in microbial systems, thereby expanding our knowledge on the parameters that can be used for strain engineering.

Comparative omics-driven genome annotation refinement: application across Yersiniae

Genome sequencing continues to be a rapidly evolving technology, yet most downstream aspects of genome annotation pipelines remain relatively stable or are even being abandoned. The annotation process is now performed almost exclusively in an automated fashion to balance the large number of sequences generated. One possible way of reducing errors inherent to automated computational annotations is to apply data from omics measurements (i.e. transcriptional and proteomic) to the un-annotated genome with a proteogenomic-based approach. Here, the concept of annotation refinement has been extended to include a comparative assessment of genomes across closely related species. Transcriptomic and proteomic data derived from highly similar pathogenic Yersiniae (Y. pestis CO92, Y. pestis Pestoides F, and Y. pseudotuberculosis PB1/+) was used to demonstrate a comprehensive comparative omic-based annotation methodology. Peptide and oligo measurements experimentally validated the expression of nearly 40% of each strain's predicted proteome and revealed the identification of 28 novel and 68 incorrect (i.e., observed frameshifts, extended start sites, and translated pseudogenes) protein-coding sequences within the three current genome annotations. Gene loss is presumed to play a major role in Y. pestis acquiring its niche as a virulent pathogen, thus the discovery of many translated pseudogenes, including the insertion-ablated argD, underscores a need for functional analyses to investigate hypotheses related to divergence. Refinements included the discovery of a seemingly essential ribosomal protein, several virulence-associated factors, a transcriptional regulator, and many hypothetical proteins that were missed during annotation.

GlyGly-CTERM and rhombosortase: a C-terminal protein processing signal in a many-to-one pairing with a rhomboid family intramembrane serine protease

The rhomboid family of serine proteases occurs in all domains of life. Its members contain at least six hydrophobic membrane-spanning helices, with an active site serine located deep within the hydrophobic interior of the plasma membrane. The model member GlpG from Escherichia coli is heavily studied through engineered mutant forms, varied model substrates, and multiple X-ray crystal studies, yet its relationship to endogenous substrates is not well understood. Here we describe an apparent membrane anchoring C-terminal homology domain that appears in numerous genera including Shewanella, Vibrio, Acinetobacter, and Ralstonia, but excluding Escherichia and Haemophilus. Individual genomes encode up to thirteen members, usually homologous to each other only in this C-terminal region. The domain's tripartite architecture consists of motif, transmembrane helix, and cluster of basic residues at the protein C-terminus, as also seen with the LPXTG recognition sequence for sortase A and the PEP-CTERM recognition sequence for exosortase. Partial Phylogenetic Profiling identifies a distinctive rhomboid-like protease subfamily almost perfectly co-distributed with this recognition sequence. This protease subfamily and its putative target domain are hereby renamed rhombosortase and GlyGly-CTERM, respectively. The protease and target are encoded by consecutive genes in most genomes with just a single target, but far apart otherwise. The signature motif of the Rhombo-CTERM domain, often SGGS, only partially resembles known cleavage sites of rhomboid protease family model substrates. Some protein families that have several members with C-terminal GlyGly-CTERM domains also have additional members with LPXTG or PEP-CTERM domains instead, suggesting there may be common themes to the post-translational processing of these proteins by three different membrane protein superfamilies.

Archaeosortases and exosortases are widely distributed systems linking membrane transit with posttranslational modification

Multiple new prokaryotic C-terminal protein-sorting signals were found that reprise the tripartite architecture shared by LPXTG and PEP-CTERM: motif, TM helix, basic cluster. Defining hidden Markov models were constructed for all. PGF-CTERM occurs in 29 archaeal species, some of which have more than 50 proteins that share the domain. PGF-CTERM proteins include the major cell surface protein in Halobacterium, a glycoprotein with a partially characterized diphytanylglyceryl phosphate linkage near its C terminus. Comparative genomics identifies a distant exosortase homolog, designated archaeosortase A (ArtA), as the likely protein-processing enzyme for PGF-CTERM. Proteomics suggests that the PGF-CTERM region is removed. Additional systems include VPXXXP-CTERM/archeaosortase B in two of the same archaea and PEF-CTERM/archaeosortase C in four others. Bacterial exosortases often fall into subfamilies that partner with very different cohorts of extracellular polymeric substance biosynthesis proteins; several species have multiple systems. Variant systems include the VPDSG-CTERM/exosortase C system unique to certain members of the phylum Verrucomicrobia, VPLPA-CTERM/exosortase D in several alpha- and deltaproteobacterial species, and a dedicated (single-target) VPEID-CTERM/exosortase E system in alphaproteobacteria. Exosortase-related families XrtF in the class Flavobacteria and XrtG in Gram-positive bacteria mark distinctive conserved gene neighborhoods. A picture emerges of an ancient and now well-differentiated superfamily of deeply membrane-embedded protein-processing enzymes. Their target proteins are destined to transit cellular membranes during their biosynthesis, during which most undergo additional posttranslational modifications such as glycosylation.

Efficient de novo assembly of single-cell bacterial genomes from short-read data sets

Whole genome amplification by the multiple displacement amplification (MDA) method allows sequencing of DNA from single cells of bacteria that cannot be cultured. Assembling a genome is challenging, however, because MDA generates highly nonuniform coverage of the genome. Here we describe an algorithm tailored for short-read data from single cells that improves assembly through the use of a progressively increasing coverage cutoff. Assembly of reads from single Escherichia coli and Staphylococcus aureus cells captures >91% of genes within contigs, approaching the 95% captured from an assembly based on many E. coli cells. We apply this method to assemble a genome from a single cell of an uncultivated SAR324 clade of Deltaproteobacteria, a cosmopolitan bacterial lineage in the global ocean. Metabolic reconstruction suggests that SAR324 is aerobic, motile and chemotaxic. Our approach enables acquisition of genome assemblies for individual uncultivated bacteria using only short reads, providing cell-specific genetic information absent from metagenomic studies.

An integrated proteomics/transcriptomics approach points to oxygen as the main electron sink for methanol metabolism in Methylotenera mobilis

Methylotenera species, unlike their close relatives in the genera Methylophilus, Methylobacillus, and Methylovorus, neither exhibit the activity of methanol dehydrogenase nor possess mxaFI genes encoding this enzyme, yet they are able to grow on methanol. In this work, we integrated a genome-wide proteomics approach, shotgun proteomics, and a genome-wide transcriptomics approach, shotgun transcriptome sequencing (RNA-seq), of Methylotenera mobilis JLW8 to identify genes and enzymes potentially involved in methanol oxidation, with special attention to alternative nitrogen sources, to address the question of whether nitrate could play a role as an electron acceptor in place of oxygen. Both proteomics and transcriptomics identified a limited number of genes and enzymes specifically responding to methanol. This set includes genes involved in oxidative stress response systems, a number of oxidoreductases, including XoxF-type alcohol dehydrogenases, a type II secretion system, and proteins without a predicted function. Nitrate stimulated expression of some genes in assimilatory nitrate reduction and denitrification pathways, while ammonium downregulated some of the nitrogen metabolism genes. However, none of these genes appeared to respond to methanol, which suggests that oxygen may be the main electron sink during growth on methanol. This study identifies initial targets for future focused physiological studies, including mutant analysis, which will provide further details into this novel process.

Core proteome of the minimal cell: comparative proteomics of three mollicute species

Mollicutes (mycoplasmas) have been recognized as highly evolved prokaryotes with an extremely small genome size and very limited coding capacity. Thus, they may serve as a model of a 'minimal cell': a cell with the lowest possible number of genes yet capable of autonomous self-replication. We present the results of a comparative analysis of proteomes of three mycoplasma species: A. laidlawii, M. gallisepticum, and M. mobile. The core proteome components found in the three mycoplasma species are involved in fundamental cellular processes which are necessary for the free living of cells. They include replication, transcription, translation, and minimal metabolism. The members of the proteome core seem to be tightly interconnected with a number of interactions forming core interactome whether or not additional species-specific proteins are located on the periphery. We also obtained a genome core of the respective organisms and compared it with the proteome core. It was found that the genome core encodes 73 more proteins than the proteome core. Apart of proteins which may not be identified due to technical limitations, there are 24 proteins that seem to not be expressed under the optimal conditions.

Discovering mercury protein modifications in whole proteomes using natural isotope distributions observed in liquid chromatography-tandem mass spectrometry

The identification of peptides that result from post-translational modifications is critical for understanding normal pathways of cellular regulation as well as identifying damage from, or exposures to xenobiotics, i.e. the exposome. However, because of their low abundance in proteomes, effective detection of modified peptides by mass spectrometry (MS) typically requires enrichment to eliminate false identifications. We present a new method for confidently identifying peptides with mercury (Hg)-containing adducts that is based on the influence of mercury's seven stable isotopes on peptide isotope distributions detected by high-resolution MS. Using a pure protein and E. coli cultures exposed to phenyl mercuric acetate, we show the pattern of peak heights in isotope distributions from primary MS single scans efficiently identified Hg adducts in data from chromatographic separation coupled with tandem mass spectrometry with sensitivity and specificity greater than 90%. Isotope distributions are independent of peptide identifications based on peptide fragmentation (e.g. by SEQUEST), so both methods can be combined to eliminate false positives. Summing peptide isotope distributions across multiple scans improved specificity to 99.4% and sensitivity above 95%, affording identification of an unexpected Hg modification. We also illustrate the theoretical applicability of the method for detection of several less common elements including the essential element, selenium, as selenocysteine in peptides.

Community transcriptomics reveals universal patterns of protein sequence conservation in natural microbial communities

Background

Combined metagenomic and metatranscriptomic datasets make it possible to study the molecular evolution of diverse microbial species recovered from their native habitats. The link between gene expression level and sequence conservation was examined using shotgun pyrosequencing of microbial community DNA and RNA from diverse marine environments, and from forest soil.

Results

Across all samples, expressed genes with transcripts in the RNA sample were significantly more conserved than non-expressed gene sets relative to best matches in reference databases. This discrepancy, observed for many diverse individual genomes and across entire communities, coincided with a shift in amino acid usage between these gene fractions. Expressed genes trended toward GC-enriched amino acids, consistent with a hypothesis of higher levels of functional constraint in this gene pool. Highly expressed genes were significantly more likely to fall within an orthologous gene set shared between closely related taxa (core genes). However, non-core genes, when expressed above the level of detection, were, on average, significantly more highly expressed than core genes based on transcript abundance normalized to gene abundance. Finally, expressed genes showed broad similarities in function across samples, being relatively enriched in genes of energy metabolism and underrepresented by genes of cell growth.

Conclusions

These patterns support the hypothesis, predicated on studies of model organisms, that gene expression level is a primary correlate of evolutionary rate across diverse microbial taxa from natural environments. Despite their complexity, meta-omic datasets can reveal broad evolutionary patterns across taxonomically, functionally, and environmentally diverse communities.

Genomic fluidity: an integrative view of gene diversity within microbial populations

Background

The dual concepts of pan and core genomes have been widely adopted as means to assess the distribution of gene families within microbial species and genera. The core genome is the set of genes shared by a group of organisms; the pan genome is the set of all genes seen in any of these organisms. A variety of methods have provided drastically different estimates of the sizes of pan and core genomes from sequenced representatives of the same groups of bacteria.

Results

We use a combination of mathematical, statistical and computational methods to show that current predictions of pan and core genome sizes may have no correspondence to true values. Pan and core genome size estimates are problematic because they depend on the estimation of the occurrence of rare genes and genomes, respectively, which are difficult to estimate precisely because they are rare. Instead, we introduce and evaluate a robust metric - genomic fluidity - to categorize the gene-level similarity among groups of sequenced isolates. Genomic fluidity is a measure of the dissimilarity of genomes evaluated at the gene level.

Conclusions

The genomic fluidity of a population can be estimated accurately given a small number of sequenced genomes. Further, the genomic fluidity of groups of organisms can be compared robustly despite variation in algorithms used to identify genes and their homologs. As such, we recommend that genomic fluidity be used in place of pan and core genome size estimates when assessing gene diversity within genomes of a species or a group of closely related organisms.

Implications of Human Microbiome Research for the Developing World

The human microbiome refers to all of the species that inhabit the human body, residing both on and in it. Over the past several years, there has been a significantly increased interest directed to the understanding of the microorganisms that reside on and in the human body. These studies of the human microbiome promise to reveal all these species and increase our understanding of the normal inhabitants, those that trigger disease and those that vary in response to disease conditions. It is anticipated that these directed research efforts, coupled with new technological advances, will ultimately allow one to gain a greater understanding of the relationships of these species with their human hosts. The various chapters in this book present a range of aspects of human microbiome research, explain the scientific and technological rationale, and highlight the significant potential that the results from these studies hold. In this chapter, we begin to address the potential and long-term implications of the knowledge gained from human microbiome research (which currently is centered in the developed world) for the developing world, which has often lagged behind in the benefits of these new technologies and their implications to new research areas.

An empirical strategy for characterizing bacterial proteomes across species in the absence of genomic sequences

Global protein identification through current proteomics methods typically depends on the availability of sequenced genomes. In spite of increasingly high throughput sequencing technologies, this information is not available for every microorganism and rarely available for entire microbial communities. Nevertheless, the protein-level homology that exists between related bacteria makes it possible to extract biological information from the proteome of an organism or microbial community by using the genomic sequences of a near neighbor organism. Here, we demonstrate a trans-organism search strategy for determining the extent to which near-neighbor genome sequences can be applied to identify proteins in unsequenced environmental isolates. In proof of concept testing, we found that within a CLUSTAL W distance of 0.089, near-neighbor genomes successfully identified a high percentage of proteins within an organism. Application of this strategy to characterize environmental bacterial isolates lacking sequenced genomes, but having 16S rDNA sequence similarity to Shewanella resulted in the identification of 300-500 proteins in each strain. The majority of identified pathways mapped to core processes, as well as to processes unique to the Shewanellae, in particular to the presence of c-type cytochromes. Examples of core functional categories include energy metabolism, protein and nucleotide synthesis and cofactor biosynthesis, allowing classification of bacteria by observation of conserved processes. Additionally, within these core functionalities, we observed proteins involved in the alternative lactate utilization pathway, recently described in Shewanella.

A metaproteomic analysis of the human salivary microbiota by three-dimensional peptide fractionation and tandem mass spectrometry

Metagenomics uses gene expression patterns to understand the taxonomy and metabolic activities of microbial communities. Metaproteomics applies the same approach to community proteomes. Previously, we used a novel three-dimensional peptide separation method to identify over 2000 salivary proteins. This study used those data to carry out the first metaproteomic analysis of the human salivary microbiota. The metagenomic software MEGAN generated a phylogenetic tree, which was checked against the Human Oral Microbiome Database (HOMD). Pathway analyses were performed with the Clusters of Orthologous Groups and MetaCyc databases. Thirty-seven per cent of the peptides were identifiable only at the level of cellular organisms or bacteria. The rest were distributed among five bacterial phyla (61%), archea (0.5%), and viruses (0.8%); 29% were assignable at the genus level, and most belonged to Streptococcus (17%). Eleven per cent of all peptides could be assigned to species. Most taxa were represented in HOMD and they included well-known species such as periodontal pathogens. However, there also were 'exotic' species including aphid endosymbionts; plant, water, and soil bacteria; extremophiles; and archea. The pathway analysis indicated that peptides were linked to translation (37%), followed by glycolysis (19%), amino acid metabolism (8%), and energy production (8%). The taxonomic structure of the salivary metaproteome is very diverse but is dominated by streptococci. 'Exotic' species may actually represent close relatives that have not yet been sequenced. Salivary microbes appear to be actively engaged in protein synthesis, and the pathway analysis is consistent with the metabolism of salivary glycoproteins.

Proteomic detection of non-annotated protein-coding genes in Pseudomonas fluorescens Pf0-1

Genome sequences are annotated by computational prediction of coding sequences, followed by similarity searches such as BLAST, which provide a layer of possible functional information. While the existence of processes such as alternative splicing complicates matters for eukaryote genomes, the view of bacterial genomes as a linear series of closely spaced genes leads to the assumption that computational annotations that predict such arrangements completely describe the coding capacity of bacterial genomes. We undertook a proteomic study to identify proteins expressed by Pseudomonas fluorescens Pf0-1 from genes that were not predicted during the genome annotation. Mapping peptides to the Pf0-1 genome sequence identified sixteen non-annotated protein-coding regions, of which nine were antisense to predicted genes, six were intergenic, and one read in the same direction as an annotated gene but in a different frame. The expression of all but one of the newly discovered genes was verified by RT-PCR. Few clues as to the function of the new genes were gleaned from informatic analyses, but potential orthologs in other Pseudomonas genomes were identified for eight of the new genes. The 16 newly identified genes improve the quality of the Pf0-1 genome annotation, and the detection of antisense protein-coding genes indicates the under-appreciated complexity of bacterial genome organization.

Proteogenomic monitoring of Geobacter physiology during stimulated uranium bioremediation

Implementation of uranium bioremediation requires methods for monitoring the membership and activities of the subsurface microbial communities that are responsible for reduction of soluble U(VI) to insoluble U(IV). Here, we report a proteomics-based approach for simultaneously documenting the strain membership and microbial physiology of the dominant Geobacter community members during in situ acetate amendment of the U-contaminated Rifle, CO, aquifer. Three planktonic Geobacter-dominated samples were obtained from two wells down-gradient of acetate addition. Over 2,500 proteins from each of these samples were identified by matching liquid chromatography-tandem mass spectrometry spectra to peptides predicted from seven isolate Geobacter genomes. Genome-specific peptides indicate early proliferation of multiple M21 and Geobacter bemidjiensis-like strains and later possible emergence of M21 and G. bemidjiensis-like strains more closely related to Geobacter lovleyi. Throughout biostimulation, the proteome is dominated by enzymes that convert acetate to acetyl-coenzyme A and pyruvate for central metabolism, while abundant peptides matching tricarboxylic acid cycle proteins and ATP synthase subunits were also detected, indicating the importance of energy generation during the period of rapid growth following the start of biostimulation. Evolving Geobacter strain composition may be linked to changes in protein abundance over the course of biostimulation and may reflect changes in metabolic functioning. Thus, metagenomics-independent community proteogenomics can be used to diagnose the status of the subsurface consortia upon which remediation biotechnology relies.

Genome analysis and genome-wide proteomics of Thermococcus gammatolerans, the most radioresistant organism known amongst the Archaea

The genome sequence of Thermococcus gammatolerans, a radioresistant archaeon, is described; a proteomic analysis reveals that radioresistance may be due to unknown DNA repair enzymes.

Background

Thermococcus gammatolerans was isolated from samples collected from hydrothermal chimneys. It is one of the most radioresistant organisms known amongst the Archaea. We report the determination and annotation of its complete genome sequence, its comparison with other Thermococcales genomes, and a proteomic analysis.

Results

T. gammatolerans has a circular chromosome of 2.045 Mbp without any extra-chromosomal elements, coding for 2,157 proteins. A thorough comparative genomics analysis revealed important but unsuspected genome plasticity differences between sequenced Thermococcus and Pyrococcus species that could not be attributed to the presence of specific mobile elements. Two virus-related regions, tgv1 and tgv2, are the only mobile elements identified in this genome. A proteogenome analysis was performed by a shotgun liquid chromatography-tandem mass spectrometry approach, allowing the identification of 10,931 unique peptides corresponding to 951 proteins. This information concurrently validates the accuracy of the genome annotation. Semi-quantification of proteins by spectral count was done on exponential- and stationary-phase cells. Insights into general catabolism, hydrogenase complexes, detoxification systems, and the DNA repair toolbox of this archaeon are revealed through this genome and proteome analysis.

Conclusions

This work is the first archaeal proteome investigation done at the stage of primary genome annotation. This archaeon is shown to use a large variety of metabolic pathways even under a rich medium growth condition. This proteogenomic study also indicates that the high radiotolerance of T. gammatolerans is probably due to proteins that remain to be characterized rather than a larger arsenal of known DNA repair enzymes.

Proteomic investigation of the time course responses of RAW 264.7 macrophages to infection with Salmonella enterica

To investigate the extent to which macrophages respond to Salmonella infection, we infected RAW 264.7 macrophages with Salmonella enterica serotype Typhimurium and analyzed macrophage proteins at various time points following infection by using a global proteomic approach. A total of 1,006 macrophage and 115 Salmonella proteins were identified with high confidence. Most of the Salmonella proteins were observed in the late stage of the infection time course, which is consistent with the fact that the bacterial cells proliferate inside RAW 264.7 macrophages. The peptide abundances of most of the identified macrophage proteins remained relatively constant over the time course of infection. Compared to those of the control, the peptide abundances of 244 macrophage proteins (i.e., 24% of the total identified macrophage proteins) changed significantly after infection. The functions of these Salmonella-affected macrophage proteins were diverse, including production of antibacterial nitric oxide (i.e., inducible nitric oxide synthase), production of prostaglandin H(2) (i.e., cyclooxygenase 2), and regulation of intracellular traffic (e.g., sorting nexin 5 [SNX5], SNX6, and SNX9). Diverse functions of the Salmonella-affected macrophage proteins demonstrate a global macrophage response to Salmonella infection. Western blot analysis not only confirmed the proteomic results for a selected set of proteins but also revealed that (i) the protein abundance of mitochondrial superoxide dismutase increased following macrophage infection, indicating an infection-induced oxidative stress in mitochondria, and (ii) in contrast to infection of macrophages by wild-type Salmonella, infection by the sopB deletion mutant had no negative impact on the abundance of SNX6, suggesting a role for SopB in regulating the abundance of SNX6.

Global proteomic pattern of Tropheryma whipplei: a Whipple's disease bacterium

The proteome of Tropheryma whipplei, the intracellular bacterium responsible for Whipple's disease (WD), was analyzed using two complementary approaches: 2-DE coupled with MALDI-TOF and SDS-PAGE with nanoLC-MS/MS. This strategy led to the identification of 206 proteins of 808 predicted ORFs, resolving some questions raised by the genomic sequence of this bacterium. We successfully identified antibiotic targets and proteins with predicted N-terminal signal sequences. Additionally, we identified a family of surface proteins (known as T. whipplei surface proteins (WiSPs)), which are encoded by a unique group of species-specific genes and serve as both coding regions and DNA repeats that promote genomic recombination. Comparison of the protein expression profiles of the intracellular facultative host-associated WD bacterium with other host-associated, intracellular obligate, and environmental bacteria revealed that T. whipplei shares a proteomic expression profile with other host-associated facultative intracellular bacteria. In summary, this study describes the global protein expression pattern of T. whipplei and reveals some specific features of the T. whipplei proteome.

Insights into the physiology of Methylotenera mobilis as revealed by metagenome-based shotgun proteomic analysis

While the shotgun proteomics approach is gaining momentum in understanding microbial physiology, it remains limited by the paucity of high-quality genomic data, especially when it comes to poorly characterized newly identified phyla. At the same time, large-scale metagenomic sequencing projects produce datasets representing genomes of a variety of environmental microbes, although with lower sequence coverage and sequence quality. In this work we tested the utility of a metagenomic dataset enriched in sequences of environmental strains of Methylotenera mobilis, to assess the protein profile of a laboratory-cultivated strain, M. mobilis JLW8, as a proof of principle. We demonstrate that a large portion of the proteome predicted from the metagenomic sequence (approx. 20 %) could be identified with high confidence (three or more peptide sequences), thus gaining insights into the physiology of this bacterium, which represents a new genus within the family Methylophilaceae.