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.

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.

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.

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.

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.

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.