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The squid Euprymna scolopesand the luminescent bacterium Vibrio fischeriform a highly specific beneficial light organ symbiosis. Not only does the host have to select V. fischerifrom the environment, but it must also prevent subsequent colonization by non-symbiotic microorganisms. Host macrophage-like hemocytes are believed to play a role in mediating the symbiosis with V. fischeri. Previous studies have shown that the colonization state of the light organ influences the host's hemocyte response to the symbiont. To further understand the molecular mechanisms behind this process, we used two quantitative mass-spectrometry-based proteomic techniques, isobaric tags for relative and absolute quantification (iTRAQ) and label-free spectral counting, to compare and quantify the adult hemocyte proteomes from colonized (sym) and uncolonized (antibiotic-treated/cured) squid. Overall, iTRAQ allowed for the quantification of 1,024 proteins with two or more peptides. Thirty-seven unique proteins were determined to be significantly different between sym and cured hemocytes (pvalue < 0.05), with 20 more abundant proteins and 17 less abundant in sym hemocytes. The label-free approach resulted in 1,241 proteins that were identified in all replicates. Of 185 unique proteins present at significantly different amounts in sym hemocytes (as determined by spectral counting), 92 were more abundant and 93 were less abundant. Comparisons between iTRAQ and spectral counting revealed that 30 of the 37 proteins quantified via iTRAQ exhibited trends similar to those identified by the label-free method. Both proteomic techniques mutually identified 16 proteins that were significantly different between the two groups of hemocytes (pvalue < 0.05). The presence of V. fischeriin the host light organ influenced the abundance of proteins associated with the cytoskeleton, adhesion, lysosomes, proteolysis, and the innate immune response. These data provide evidence that colonization by V. fischerialters the hemocyte proteome and reveals proteins that may be important for maintaining host–symbiont specificity.

Advances in the field of T cell immunology have contributed to the understanding that cross-reactivity is an intrinsic characteristic of the T cell receptor (TCR), and that each TCR can potentially interact with many different T cell epitopes. To better define the potential for TCR cross-reactivity between epitopes derived from the human genome, the human microbiome, and human pathogens, we developed a new immunoinformatics tool, JanusMatrix, that represents an extension of the validated T cell epitope mapping tool, EpiMatrix. Initial explorations, summarized in this synopsis, have uncovered what appear to be important differences in the TCR cross-reactivity of selected regulatory and effector T cell epitopes with other epitopes in the human genome, human microbiome, and selected human pathogens. In addition to exploring the T cell epitope relationships between human self, commensal and pathogen, JanusMatrix may also be useful to explore some aspects of heterologous immunity and to examine T cell epitope relatedness between pathogens to which humans are exposed (Dengue serotypes, or HCV and Influenza, for example). In Hand-Foot-Mouth disease (HFMD) for example, extensive enterovirus and human microbiome cross-reactivity (and limited cross-reactivity with the human genome) seemingly predicts immunodominance. In contrast, more extensive cross-reactivity with proteins contained in the human genome as compared to the human microbiome was observed for selected Treg epitopes. While it may be impossible to predict all immune response influences, the availability of sequence data from the human genome, the human microbiome, and an array of human pathogens and vaccines has made computationally–driven exploration of the effects of T cell epitope cross-reactivity now possible. This is the first description of JanusMatrix, an algorithm that assesses TCR cross-reactivity that may contribute to a means of predicting the phenotype of T cells responding to selected T cell epitopes. Whether used for explorations of T cell phenotype or for evaluating cross-conservation between related viral strains at the TCR face of viral epitopes, further JanusMatrix studies may contribute to developing safer, more effective vaccines.

Temporal genomic profiling and whole-cell proteomic analyses were performed to characterize the dynamic molecular response of the metal-reducing bacterium Shewanella oneidensisMR-1 to an acute chromate shock. The complex dynamics of cellular processes demand the integration of methodologies that describe biological systems at the levels of regulation, gene and protein expression, and metabolite production. Genomic microarray analysis of the transcriptome dynamics of midexponential phase cells subjected to 1 mmpotassium chromate (K2CrO4) at exposure time intervals of 5, 30, 60, and 90 min revealed 910 genes that were differentially expressed at one or more time points. Strongly induced genes included those encoding components of a TonB1 iron transport system (tonB1-exbB1-exbD1), hemin ATP-binding cassette transporters (hmuTUV), TonB-dependent receptors as well as sulfate transporters (cysP, cysW-2, and cysA-2), and enzymes involved in assimilative sulfur metabolism (cysC, cysN, cysD, cysH, cysI, and cysJ). Transcript levels for genes with annotated functions in DNA repair (lexA, recX, recA, recN, dinP, and umuD), cellular detoxification (so1756, so3585, and so3586), and two-component signal transduction systems (so2426) were also significantly up-regulated (p< 0.05) in Cr(VI)-exposed cells relative to untreated cells. By contrast, genes with functions linked to energy metabolism, particularly electron transport (e.g. so0902-03-04, mtrA, omcA, and omcB), showed dramatic temporal alterations in expression with the majority exhibiting repression. Differential proteomics based on multidimensional HPLC-MS/MS was used to complement the transcriptome data, resulting in comparable induction and repression patterns for a subset of corresponding proteins. In total, expression of 2,370 proteins were confidently verified with 624 (26%) of these annotated as hypothetical or conserved hypothetical proteins. The initial response of S. oneidensisto chromate shock appears to require a combination of different regulatory networks that involve genes with annotated functions in oxidative stress protection, detoxification, protein stress protection, iron and sulfur acquisition, and SOS-controlled DNA repair mechanisms.

At the present time we know little about how microbial communities function in their natural habitats. For example, how do microorganisms interact with each other and their physical and chemical surroundings and respond to environmental perturbations? We might begin to answer these questions if we could monitor the ways in which metabolic roles are partitioned amongst members as microbial communities assemble, determine how resources such as carbon, nitrogen, and energy are allocated into metabolic pathways, and understand the mechanisms by which organisms and communities respond to changes in their surroundings. Because many organisms cannot be cultivated, and given that the metabolisms of those growing in monoculture are likely to differ from those of organisms growing as part of consortia, it is vital to develop methods to study microbial communities in situ. Chemoautotrophic biofilms growing in mine tunnels hundreds of meters underground drive pyrite (FeS2) dissolution and acid and metal release, creating habitats that select for a small number of organism types. The geochemical and microbial simplicity of these systems, the significant biomass, and clearly defined biological-inorganic feedbacks make these ecosystem microcosms ideal for development of methods for the study of uncultivated microbial consortia. Our approach begins with the acquisition of genomic data from biofilms that are sampled over time and in different growth conditions. We have demonstrated that it is possible to assemble shotgun sequence data to reveal the gene complement of the dominant community members and to use these data to confidently identify a significant fraction of proteins from the dominant organisms by mass spectrometry (MS)–based proteomics. However, there are technical obstacles currently restricting this type of "proteogenomic" analysis. Composite genomic sequences assembled from environmental data from natural microbial communities do not capture the full range of genetic potential of the associated populations. Thus, it is necessary to develop bioinformatics approaches to generate relatively comprehensive gene inventories for each organism type. These inventories are critical for expression and functional analyses. In proteomic studies, for example, peptides that differ from those predicted from gene sequences can be measured, but they generally cannot be identified by database matching, even if the difference is only a single amino acid residue. Furthermore, many of the identified proteins have no known function. We propose that these challenges can be addressed by development of proteogenomic, biochemical, and geochemical methods that will be initially deployed in a simple, natural model ecosystem. The resulting approach should be broadly applicable and will enhance the utility and significance of genomic data from isolates and consortia for study of organisms in many habitats. Solutions draining pyrite-rich deposits are referred to as acid mine drainage (AMD). AMD is a very prevalent, international environmental problem associated with energy and metal resources. The biological-mineralogical interactions that define these systems can be harnessed for energy-efficient metal recovery and removal of sulfur from coal. The detailed understanding of microbial ecology and ecosystem dynamics resulting from the proposed work will provide a scientific foundation for dealing with the environmental challenges and technological opportunities, and yield new methods for analysis of more complex natural communities.

The emergence of advanced liquid chromatography mass spectrometry technologies for characterizing very complex mixtures of proteins has greatly propelled the field of proteomics, the goal of which is the simultaneous examination of all the proteins expressed by an organism. This research area represents a paradigm shift in molecular biology by attempting to provide a top-down qualitative and quantitative view of all the proteins (including their modifications and interactions) that are essential for an organism’s life cycle, rather than targeting a particular protein family. This level of global protein information about an organism such as a bacterium can be combined with genomic and metabolomic data to enable a systems biology approach for understanding how these organisms live and function.

The chain length dependence of helix formation of transmembrane peptides in lipids was investigated using fragments corresponding to the second transmembrane domain of the α-factor receptor from Saccharomyces cerevisiae. Seven peptides with chain lengths of 10 (M2-10; FKYLLSNYSS), 14 (M2-14), 18 (M2-18), 22 (M2-22), 26 (M2-26), 30 (M2-30) and 35 (M2-35; RSRKTPIFIINQVSLFLIILHSALYFKYLLSNYSS) residues, respectively, were synthesized. CD spectra revealed that M2-10 was disordered, and all of the other peptides assumed partially α-helical secondary structures in 99% trifluoroethanol (TFE)/H2O. In 50% TFE/H2O, M2-30 assumed a β-like structure. The other six peptides exhibited the same CD patterns as those found in 99% TFE/H2O. In 1,2-dimyristoyl-sn-glycero-3-phosphocholine/1,2-dimyristoyl-sn-glycero-3-phospho-rac-(1-glycerol) (4:1 ratio) vesicles, M2-22, M2-26, and M2-35 formed α-helical structures, whereas the other peptides formed β-like structures. Fourier transform infrared spectroscopy in 1,2-dimyristoyl-sn-glycero-3-phosphocholine/1,2-dimyristoyl-sn-glycero-3-phospho-rac-(1-glycerol) (4:1) multilayers showed that M2-10, M2-14, M2-18, and M2-30 assumed β-structures in this environment. Another homologous 30-residue peptide (M2-30B), missing residues SNYSS from the N terminus and extending to RSRKT on the C terminus, was helical in lipid bilayers, suggesting that residues at the termini of transmembrane domains influence their biophysical properties. Attenuated total reflection Fourier transform infrared spectroscopy revealed that M2-22, M2-26, M2-30B, and M2-35 were α-helical and oriented at angles of 12°, 13°, 36°, and 34°, respectively, with respect to the multilayer normal. This study showed that chain length must be taken into consideration when using peptides representing single transmembrane domains as surrogates for regions of an intact receptor. Furthermore, this work indicates that the tilt angle and conformation of transmembrane portions of G protein-coupled receptors may be estimated by detailed spectroscopic measurements of single transmembrane peptides.

ABSTRACTDiet 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 Firmicutesto Bacteroidetes, including increases in relative abundances of some specific members of the Firmicutesand concurrent increases in enzymatic pathways and metabolites involved in lipid metabolism in the gut.IMPORTANCEThis 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.

ABSTRACTTransposases, enzymes that catalyze the movement of mobile genetic elements, are the most abundant genes in nature. While many bacteria encode an abundance of transposases in their genomes, the current paradigm is that the expression of transposase genes is tightly regulated and generally low due to its severe mutagenic effects. In the current study, we detected the highest number of transposase proteins ever reported in bacteria, in symbionts of the gutless marine worm Olavius algarvensiswith metaproteomics. At least 26 different transposases from 12 different families were detected, and genomic and proteomic analyses suggest that many of these are active. This high expression of transposases indicates that the mechanisms for their tight regulation have been disabled or no longer exist.IMPORTANCEThe expansion of transposable elements (TE) within the genomes of host-restricted symbionts and pathogens plays an important role in their emergence and evolution and might be a key mechanism for adaptation to the host environment. However, little is known so far about the underlying causes and evolutionary mechanisms of this TE expansion. The current model of genome evolution in host-restricted bacteria explains TE expansion within the confines of the paradigm that transposase expression is always low. However, recent work failed to verify this model. Based on our data, we hypothesize that increased transposase expression, which has not previously been described, may play a role in TE expansion, and could be one explanation for the sometimes very rapid emergence and evolution of new obligate symbionts and pathogens from facultative ones.

ABSTRACTTandem high-throughput proteomics and metabolomics were employed to functionally characterize natural microbial biofilm communities. Distinct molecular signatures exist for each analyzed sample. Deconvolution of the high-resolution molecular data demonstrates that identified proteins and detected metabolites exhibit organism-specific correlation patterns. These patterns are reflective of the functional differentiation of two bacterial species that share the same genus and that co-occur in the sampled microbial communities. Our analyses indicate that the two species have similar niche breadths and are not in strong competition with one another.IMPORTANCENatural microbial assemblages represent dynamic consortia that exhibit extensive complexity at all levels. In the present study, we demonstrate that correlations between protein and metabolite abundances allow the deconvolution of complex molecular data sets into shared and organism-specific contingents. We demonstrate that evolutionary divergence is associated with the restructuring of cellular metabolic networks, which in turn allows bacterial species to occupy distinct ecological niches. The apparent lack of interspecific competition may explain the extensive population-level genetic heterogeneity observed extensively within microbial communities. The reported findings have broad implications for the in-depth investigation of the ecology and evolution of distinct microbial community members and for leveraging the solution of cryptic metabolic processes in the future.