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Diet can influence the composition of the human microbiome, and yet relatively few dietary ingredients have been systematically investigated with respect to their impact on the functional potential of the microbiome. Dietary resistant starch (RS) has been shown to have health benefits, but we lack a mechanistic understanding of the metabolic processes that occur in the gut during digestion of RS. Here, we collected samples during a dietary crossover study with diets containing large or small amounts of RS. We determined the impact of RS on the gut microbiome and metabolic pathways in the gut, using a combination of "omics" approaches, including 16S rRNA gene sequencing, metaproteomics, and metabolomics. This multiomics approach captured changes in the abundance of specific bacterial species, proteins, and metabolites after a diet high in resistant starch (HRS), providing key insights into the influence of dietary interventions on the gut microbiome. The combined data showed that a high-RS diet caused an increase in the ratio of Firmicutes to Bacteroidetes, including increases in relative abundances of some specific members of the Firmicutes and concurrent increases in enzymatic pathways and metabolites involved in lipid metabolism in the gut.IMPORTANCE This work was undertaken to obtain a mechanistic understanding of the complex interplay between diet and the microorganisms residing in the intestine. Although it is known that gut microbes play a key role in digestion of the food that we consume, the specific contributions of different microorganisms are not well understood. In addition, the metabolic pathways and resultant products of metabolism during digestion are highly complex. To address these knowledge gaps, we used a combination of molecular approaches to determine the identities of the microorganisms in the gut during digestion of dietary starch as well as the metabolic pathways that they carry out. Together, these data provide a more complete picture of the function of the gut microbiome in digestion, including links between an RS diet and lipid metabolism and novel linkages between specific gut microbes and their metabolites and proteins produced in the gut.

Viruses influence the ecology and evolutionary trajectory of microbial communities. Yet our understanding of their roles in ecosystems is limited by the paucity of model systems available for hypothesis generation and testing. Further, virology is limited by the lack of a broadly accepted conceptual framework to classify viral diversity into evolutionary and ecologically cohesive units. Here, we introduce genomes, structural proteomes, and quantitative host range data for eight Pseudoalteromonas phages isolated from Helgoland (North Sea, Germany) and use these data to advance a genome-based viral operational taxonomic unit (OTU) definition. These viruses represent five new genera and inform 498 unaffiliated or unannotated protein clusters (PCs) from global virus metagenomes. In a comparison of previously sequenced Pseudoalteromonas phage isolates (n = 7) and predicted prophages (n = 31), the eight phages are unique. They share a genus with only one other isolate, Pseudoalteromonas podophage RIO-1 (East Sea, South Korea) and two Pseudoalteromonas prophages. Mass-spectrometry of purified viral particles identified 12-20 structural proteins per phage. When combined with 3-D structural predictions, these data led to the functional characterization of five previously unidentified major capsid proteins. Protein functional predictions revealed mechanisms for hijacking host metabolism and resources. Further, they uncovered a hybrid sipho-myovirus that encodes genes for Mu-like infection rarely described in ocean systems. Finally, we used these data to evaluate a recently introduced definition for virus populations that requires members of the same population to have >95% average nucleotide identity across at least 80% of their genes. Using physiological traits and genomics, we proposed a conceptual model for a viral OTU definition that captures evolutionarily cohesive and ecologically distinct units. In this trait-based framework, sensitive hosts are considered viral niches, while host ranges and infection efficiencies are tracked as viral traits. Quantitative host range assays revealed conserved traits within virus OTUs that break down between OTUs, suggesting the defined units capture niche and fitness differentiation. Together these analyses provide a foundation for model system-based hypothesis testing that will improve our understanding of marine copiotrophs, as well as phage-host interactions on the ocean particles and aggregates where Pseudoalteromonas thrive.

Viruses are ecologically important, yet environmental virology is limited by dominance of unannotated genomic sequences representing taxonomic and functional "viral dark matter." Although recent analytical advances are rapidly improving taxonomic annotations, identifying functional dark matter remains problematic. Here, we apply paired metaproteomics and dsDNA-targeted metagenomics to identify 1,875 virion-associated proteins from the ocean. Over one-half of these proteins were newly functionally annotated and represent abundant and widespread viral metagenome-derived protein clusters (PCs). One primarily unannotated PC dominated the dataset, but structural modeling and genomic context identified this PC as a previously unidentified capsid protein from multiple uncultivated tailed virus families. Furthermore, four of the five most abundant PCs in the metaproteome represent capsid proteins containing the HK97-like protein fold previously found in many viruses that infect all three domains of life. The dominance of these proteins within our dataset, as well as their global distribution throughout the world's oceans and seas, supports prior hypotheses that this HK97-like protein fold is the most abundant biological structure on Earth. Together, these culture-independent analyses improve virion-associated protein annotations, facilitate the investigation of proteins within natural viral communities, and offer a high-throughput means of illuminating functional viral dark matter.

The CRISPR/Cas system, comprised of clustered regularly interspaced short palindromic repeats along with their associated (Cas) proteins, protects bacteria and archaea from viral predation and invading nucleic acids. While the mechanism of action for this acquired immunity is currently under investigation, the response of Cas protein expression to phage infection has yet to be elucidated. In this study, we employed shotgun proteomics to measure the global proteome expression in a model system for studying the CRISPR/Cas response in S. thermophilus DGCC7710 infected with phage 2972. Host and viral proteins were simultaneously measured following inoculation at two different multiplicities of infection and across various time points using two-dimensional liquid chromatography tandem mass spectrometry. Thirty-seven out of forty predicted viral proteins were detected, including all proteins of the structural virome and viral effector proteins. In total, 1,013 of 2,079 predicted S. thermophilus proteins were detected, facilitating the monitoring of host protein synthesis changes in response to virus infection. Importantly, Cas proteins from all four CRISPR loci in the S. thermophilus DGCC7710 genome were detected, including loci previously thought to be inactive. Many Cas proteins were found to be constitutively expressed, but several demonstrated increased abundance following infection, including the signature Cas9 proteins from the CRISPR1 and CRISPR3 loci, which are key players in the interference phase of the CRISPR/Cas response. Altogether, these results provide novel insights into the proteomic response of S. thermophilus, specifically CRISPR-associated proteins, upon phage 2972 infection.

An important challenge in microbial ecology is developing methods that simultaneously examine the physiology of organisms at the molecular level and their ecosystem level interactions in complex natural systems. We integrated extensive proteomic, geochemical, and biological information from 28 microbial communities collected from an acid mine drainage environment and representing a range of biofilm development stages and geochemical conditions to evaluate how the physiologies of the dominant and less abundant organisms change along environmental gradients. The initial colonist dominates across all environments, but its proteome changes between two stable states as communities diversify, implying that interspecies interactions affect this organism's metabolism. Its overall physiology is robust to abiotic environmental factors, but strong correlations exist between these factors and certain subsets of proteins, possibly accounting for its wide environmental distribution. Lower abundance populations are patchier in their distribution, and proteomic data indicate that their environmental niches may be constrained by specific sets of abiotic environmental factors. This research establishes an effective strategy to investigate ecological relationships between microbial physiology and the environment for whole communities in situ.

Abstract Background High-resolution tandem mass spectra can now be readily acquired with hybrid instruments, such as LTQ-Orbitrap and LTQ-FT, in high-throughput shotgun proteomics workflows. The improved spectral quality enables more accurate de novo sequencing for identification of post-translational modifications and amino acid polymorphisms. Results In this study, a new de novo sequencing algorithm, called Vonode, has been developed specifically for analysis of such high-resolution tandem mass spectra. To fully exploit the high mass accuracy of these spectra, a unique scoring system is proposed to evaluate sequence tags based primarily on mass accuracy information of fragment ions. Consensus sequence tags were inferred for 11,422 spectra with an average peptide length of 5.5 residues from a total of 40,297 input spectra acquired in a 24-hour proteomics measurement of Rhodopseudomonas palustris. The accuracy of inferred consensus sequence tags was 84%. According to our comparison, the performance of Vonode was shown to be superior to the PepNovo v2.0 algorithm, in terms of the number of de novo sequenced spectra and the sequencing accuracy. Conclusions Here, we improved de novo sequencing performance by developing a new algorithm specifically for high-resolution tandem mass spectral data. The Vonode algorithm is freely available for download at http://compbio.ornl.gov/Vonode.

Rhodopseudomonas palustris is unique among characterized nonsulfur purple bacteria because of its capacity for anaerobic photoheterotrophic growth using aromatic acids. Like growth with other reduced electron donors, this growth typically requires the presence of bicarbonate/C[O.sub.2] or some other added electron acceptor in the growth medium. Proteomic studies indicated that there was specific accumulation of form I ribulose 1, 5-bisphosphate carboxylase/oxygenase (RubisCO) subunit proteins (CbbL and CbbS), as well as the CbbX protein, in cells grown on benzoate without added bicarbonate; such cells used the small amounts of dissolved C[O.sub.2] in the medium to support growth. These proteins were not observed in extracts from cells grown in the presence of high levels (10 mM) of added bicarbonate. To confirm the results of the proteomics studies, it was shown that the total RubisCO activity levels were significantly higher (five- to sevenfold higher) in wild-type (CGA010) cells grown on benzoate with a low level (0.5 mM) of added bicarbonate. Immunoblots indicated that the increase in RubisCO activity levels was due to a specific increase in the amount of form I RubisCO (CbbLS) and not in the amount of form II RubisCO (CbbM), which was constitutively expressed. Deletion of the main transcriptional regulator gene, cbbR, resulted in impaired growth on benzoate-containing low-bicarbonate media, and it was established that form I RubisCO synthesis was absolutely and specifically dependent on CbbR. To understand the regulatory role of the CbbRRS two-component system, strains with nonpolar deletions of the cbbRRS genes were grown on benzoate. Distinct from the results obtained with photoautotrophic growth conditions, the results of studies with various CbbRRS mutant strains indicated that this two-component system did not affect the observed enhanced synthesis of form I RubisCO under benzoate growth conditions. These studies indicate that diverse growth conditions differentially affect the ability of the CbbRRS two-component system to influence cbb transcription.

Many methods of microbial proteome characterizations require large quantifies of cellular biomass (> 1-2 g) for sample preparation and protein identification. Our experimental approach differs from traditional techniques by providing the ability to identify the proteomic state of a microbe from a few milligrams of starting cellular material. The small-scale, guanidine lysis method minimizes sample loss by achieving cellular lysis and protein digestion in a single-tube experiment. For this experimental approach, the freshwater microbe Shewanella oneidensis MR-1 and the purple non-sulfur bacterium Rhodopseudomonas palustris CGA0010 were used as model organisms for technology development and evaluation. A 2-D LC-MS/MS comparison between a standard sonication lysis method and the small-scale guanidine lysis techniques demonstrates that the guanidine lysis method is more efficient with smaller sample amounts of cell pellet (i.e., down to 1 mg). The described methodology enables deeper proteome measurements from a few milliliters of confluent bacterial cultures. We also report a new protocol for efficient lysis from small amounts of natural biofilm samples for deep proteome measurements, which should greatly enhance the emerging field of environmental microbial community proteomics. This straightforward sample boiling protocol is complementary to the small-scale guanidine lysis technique, is amenable for small sample quantifies, and requires no special reagents that might complicate the MS measurements.

A profile likelihood algorithm is proposed for quantitative shotgun proteomics to infer the abundance ratios of proteins from the abundance ratios of isotopically labeled peptides derived from proteolysis. Previously, we have shown that the estimation variability and bias of peptide abundance ratios can be predicted from their profile signal-to-noise ratios. Given multiple quantified peptides for a protein, the profile likelihood algorithm probabilistically weighs the peptide abundance ratios by their inferred estimation variability, accounts for their expected estimation bias, and suppresses contribution from outliers. This algorithm yields maximum likelihood point estimation and profile likelihood confidence interval estimation of protein abundance ratios. This point estimator is more accurate than an estimator based on the average of peptide abundance ratios. The confidence interval estimation provides an 'error bar' for each protein abundance ratio that reflects its estimation precision and statistical uncertainty. The accuracy of the point estimation and the precision and confidence level of the interval estimation were benchmarked with standard mixtures of isotopically labeled proteomes. The profile likelihood algorithm was integrated into a quantitative proteomics program, called ProRata, freely available at www.MSProRata.org.

Algorithmic search engines bridge the gap between large tandem mass spectrometry data sets and the identification of proteins associated with biological samples. Improvements in these tools can greatly enhance biological discovery. We present a new scoring scheme for comparing tandem mass spectra with a protein sequence database. The MASPIC (Multinomial Algorithm for Spectral Profile-based Intensity Comparison) scorer converts an experimental tandem mass spectrum into a m/z profile of probability and then scores peak lists from potential candidate peptides using a multinomial distribution model. The MASPIC scoring scheme incorporates intensity, spectral peak density variations, and m/z error distribution associated with peak matches into a multinomial distribution. The scoring scheme was validated on two standard protein mixtures and an additional set of spectra collected on a complex ribosomal protein mixture from Rhodopseudomonas palustris. The results indicate a 5-15% improvement over Sequest for high-confidence identifications. The performance gap grows as sequence database size increases. Additional tests on spectra from proteinase-K digest data showed similar performance improvements demonstrating the advantages in using MASPIC for studying proteins digested with less specific proteases. All these investigations show MASPIC to be a versatile and reliable system for peptide tandem mass spectral identification.

There is currently a great need for rapid detection and positive identification of biological threat agents, as well as microbial species in general, directly from complex environmental samples. This need is most urgent in the area of homeland security, but also extends into medical, environmental, and agricultural sciences. Mass-spectrometry-based analysis is one of the leading technologies in the field with a diversity of different methodologies for biothreat detection. Over the past few years, 'shotgun' proteomics has become one method of choice for the rapid analysis of complex protein mixtures by mass spectrometry. Recently, it was demonstrated that this methodology is capable of distinguishing a target species against a large database of background species from a single-component sample or dual-component mixtures with relatively the same concentration (Dworzanski, J. P.; Snyder, A. P.; Chen, R.; Zhang, H.; Wishart, D.; Li, L. Anal. Chem. 2004, 76, 2355-2366). Here, we examine the potential of shotgun proteomics to analyze a target species in a background of four contaminant species. We tested the capability of a common commercial mass-spectrometry-based shotgun proteomics platform for the detection of the target species (Escherichia coli) at four different concentrations and four different time points of analysis. We also tested the effect of database size on positive identification of the four microbes used in this study by testing a small (13-species) database and a large (261-species) database. The results clearly indicated that this technology could easily identify the target species at 20% in the background mixture at a 60, 120, 180, or 240 min analysis time with the small database. The results also indicated that the target species could easily be identified at 20% or 6% but could not be identified at 0.6% or 0.06% in either a 240 min analysis or a 30 h analysis with the small database. The effects of the large database were severe on the target species where detection above the background at any concentration used in this study was impossible, though the three other microbes used in this study were clearly identified above the background when analyzed with the large database. This study points to the potential application of this technology for biological threat agent detection but highlights many areas of needed research before the technology will be useful in real world samples.

Site-directed mutagenesis of R67 dihydrofolate reductase reveals that the enzyme possesses a 'hot spot' binding surface, which binds both folate and NADPH ligands, during catalysis. Data indicate that the enzyme exhibits an endo conformer for cooperative binding of ligands, which suggests primitivity of the enzyme.

Abstract Background Butanol is a second generation biofuel produced by Clostridium acetobutylicum through acetone-butanol-ethanol (ABE) fermentation process. Shotgun proteomics provides a direct approach to study the whole proteome of an organism in depth. This paper focuses on shotgun proteomic profiling of C. acetobutylicum from ABE fermentation using glucose and xylose to understand the functional mechanisms of C. acetobutylicum proteins involved in butanol production. Results We identified 894 different proteins in C. acetobutylicum from ABE fermentation process by two dimensional - liquid chromatography - tandem mass spectrometry (2D-LC-MS/MS) method. This includes 717 proteins from glucose and 826 proteins from the xylose substrate. A total of 649 proteins were found to be common and 22 significantly differentially expressed proteins were identified between glucose and xylose substrates. Conclusion Our results demonstrate that flagellar proteins are highly up-regulated with glucose compared to xylose substrate during ABE fermentation. Chemotactic activity was also found to be lost with the xylose substrate due to the absence of CheW and CheV proteins. This is the first report on the shotgun proteomic analysis of C. acetobutylicum ATCC 824 in ABE fermentation between glucose and xylose substrate from a single time data point and the number of proteins identified here is more than any other study performed on this organism up to this report.

Abstract Background Pseudomonas putida is a model organism for bioremediation because of its remarkable metabolic versatility, extensive biodegradative functions, and ubiquity in contaminated soil environments. To further the understanding of molecular pathways responding to the heavy metal chromium(VI) [Cr(VI)], the proteome of aerobically grown, Cr(VI)-stressed P. putida strain F1 was characterized within the context of two disparate nutritional environments: rich (LB) media and minimal (M9L) media containing lactate as the sole carbon source. Results Growth studies demonstrated that F1 sensitivity to Cr(VI) was impacted substantially by nutrient conditions, with a carbon-source-dependent hierarchy (lactate > glucose >> acetate) observed in minimal media. Two-dimensional HPLC-MS/MS was employed to identify differential proteome profiles generated in response to 1 mM chromate under LB and M9L growth conditions. The immediate response to Cr(VI) in LB-grown cells was up-regulation of proteins involved in inorganic ion transport, secondary metabolite biosynthesis and catabolism, and amino acid metabolism. By contrast, the chromate-responsive proteome derived under defined minimal growth conditions was characterized predominantly by up-regulated proteins related to cell envelope biogenesis, inorganic ion transport, and motility. TonB-dependent siderophore receptors involved in ferric iron acquisition and amino acid adenylation domains characterized up-regulated systems under LB-Cr(VI) conditions, while DNA repair proteins and systems scavenging sulfur from alternative sources (e.g., aliphatic sulfonates) tended to predominate the up-regulated proteome profile obtained under M9L-Cr(VI) conditions. Conclusions Comparative analysis indicated that the core molecular response to chromate, irrespective of the nutritional conditions tested, comprised seven up-regulated proteins belonging to six different functional categories including transcription, inorganic ion transport/metabolism, and amino acid transport/metabolism. These proteins might potentially serve as indicators of chromate stress in natural microbial communities.

Abstract Background High-resolution tandem mass spectra can now be readily acquired with hybrid instruments, such as LTQ-Orbitrap and LTQ-FT, in high-throughput shotgun proteomics workflows. The improved spectral quality enables more accurate de novo sequencing for identification of post-translational modifications and amino acid polymorphisms. Results In this study, a new de novo sequencing algorithm, called Vonode, has been developed specifically for analysis of such high-resolution tandem mass spectra. To fully exploit the high mass accuracy of these spectra, a unique scoring system is proposed to evaluate sequence tags based primarily on mass accuracy information of fragment ions. Consensus sequence tags were inferred for 11,422 spectra with an average peptide length of 5.5 residues from a total of 40,297 input spectra acquired in a 24-hour proteomics measurement of Rhodopseudomonas palustris. The accuracy of inferred consensus sequence tags was 84%. According to our comparison, the performance of Vonode was shown to be superior to the PepNovo v2.0 algorithm, in terms of the number of de novo sequenced spectra and the sequencing accuracy. Conclusions Here, we improved de novo sequencing performance by developing a new algorithm specifically for high-resolution tandem mass spectral data. The Vonode algorithm is freely available for download at http://compbio.ornl.gov/Vonode.

A proteomics-based approach to simultaneously document the strain membership and microbial physiology of the dominant Geobacter community members during in situ acetate amendment of the U-contaminated Rifle, CO, and aquifer is reported. The evolving Geobacter strain composition might be linked to changes in protein abundance over the course of biostimulation and might reflect changes in metabolic functioning.

The analysis of near-complete population (composite) genomic sequences for coexisting acidophilic iron-oxidizing Leptospirillum group II and III bacteria (phylum Nitrospirae) and an extrachromosomal plasmid from a Richmnd Mine, Iron Mountain, Ca, acid mine drainage biofilm is presented. Both the bacterial groups are found to have genes for community-essential functions, including carbon fixation and biosynthesis of vitamins, fatty acids, and biopolymers and multiple pathways for osmotic protection.

The characterization of a novel, soluble cytochrome with an unusual visible signature at 579 nm (Cyt(579)) is described. The results suggested that Cyt(579) plays an important role as an electron transfer protein to shuttle electrons derived from Fe(II) oxidation to support critical metabolical functions in the acidophilic microbial community.

Proteome analysis requires robust separations and rapid protein identification. Currently, two-dimensional polyacrylamide gel electrophoresis (2-D PAGE) followed by mass spectrometry (MS) analysis is the gold standard. Recently there has been [...]

Current proteomics and genomics research has spurred the pharmaceutical and biotechnology industries to keep up with technical demands. There is currently a need for robust liquid-phase separations of complex protein [...]