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Antibodies that bind to both H1 and H3 influenza strains exist in the pre-vaccination serum repertoire of healthy adults; most vaccine-elicited clonotypes bind either H1 or H3 strains. Molecular understanding of serological immunity to influenza has been confounded by the complexity of the polyclonal antibody response in humans. Here we used high-resolution proteomics analysis of immunoglobulin (referred to as Ig-seq) coupled with high-throughput sequencing of transcripts encoding B cell receptors (BCR-seq) to quantitatively determine the antibody repertoire at the individual clonotype level in the sera of young adults before and after vaccination with trivalent seasonal influenza vaccine. The serum repertoire comprised between 40 and 147 clonotypes that were specific to each of the three monovalent components of the trivalent influenza vaccine, with boosted pre-existing clonotypes accounting for ∼60% of the response. An unexpectedly high fraction of serum antibodies recognized both the H1 and H3 monovalent vaccines. Recombinant versions of these H1 + H3 cross-reactive antibodies showed broad binding to hemagglutinins (HAs) from previously circulating virus strains; several of these antibodies, which were prevalent in the serum of multiple donors, recognized the same conserved epitope in the HA head domain. Although the HA-head-specific H1 + H3 antibodies did not show neutralization activity in vitro , they protected mice against infection with the H1N1 and H3N2 virus strains when administered before or after challenge. Collectively, our data reveal unanticipated insights regarding the serological response to influenza vaccination and raise questions about the added benefits of using a quadrivalent vaccine instead of a trivalent vaccine.

Most vaccines confer protection via the elicitation of serum antibodies, yet more than 100 y after the discovery of antibodies, the molecular composition of the human serum antibody repertoire to an antigen remains unknown. Using high-resolution liquid chromatography tandem MS proteomic analyses of serum antibodies coupled with next-generation sequencing of the V gene repertoire in peripheral B cells, we have delineated the human serum IgG and B-cell receptor repertoires following tetanus toxoid (TT) booster vaccination. We show that the TT ⁺ serum IgG repertoire comprises ∼100 antibody clonotypes, with three clonotypes accounting for >40% of the response. All 13 recombinant IgGs examined bound to vaccine antigen with K d ∼ 10 ⁻⁸–10 ⁻¹⁰ M. Five of 13 IgGs recognized the same linear epitope on TT, occluding the binding site used by the toxin for cell entry, suggesting a possible explanation for the mechanism of protection conferred by the vaccine. Importantly, only a small fraction (<5%) of peripheral blood plasmablast clonotypes (CD3 ⁻CD14 ⁻CD19 ⁺CD27 ⁺⁺CD38 ⁺⁺CD20 ⁻TT ⁺) at the peak of the response (day 7), and an even smaller fraction of memory B cells, were found to encode antibodies that could be detected in the serological memory response 9 mo postvaccination. This suggests that only a small fraction of responding peripheral B cells give rise to the bone marrow long-lived plasma cells responsible for the production of biologically relevant amounts of vaccine-specific antibodies (near or above the K d). Collectively, our results reveal the nature and dynamics of the serological response to vaccination with direct implications for vaccine design and evaluation.

Transcription, mRNA decay, translation and protein degradation are essential processes during eukaryotic gene expression, but their relative global contributions to steady‐state protein concentrations in multi‐cellular eukaryotes are largely unknown. Using measurements of absolute protein and mRNA abundances in cellular lysate from the human Daoy medulloblastoma cell line, we quantitatively evaluate the impact of mRNA concentration and sequence features implicated in translation and protein degradation on protein expression. Sequence features related to translation and protein degradation have an impact similar to that of mRNA abundance, and their combined contribution explains two‐thirds of protein abundance variation. mRNA sequence lengths, amino‐acid properties, upstream open reading frames and secondary structures in the 5′ untranslated region (UTR) were the strongest individual correlates of protein concentrations. In a combined model, characteristics of the coding region and the 3′UTR explained a larger proportion of protein abundance variation than characteristics of the 5′UTR. The absolute protein and mRNA concentration measurements for >1000 human genes described here represent one of the largest datasets currently available, and reveal both general trends and specific examples of post‐transcriptional regulation. Synopsis mRNA decay, translation regulation and protein degradation are essential parts of eukaryotic gene expression regulation (Hieronymus and Silver, 2004 ; Mata et al , 2005 ), which enable the dynamics of cellular systems and their responses to external and internal stimuli without having to rely exclusively on transcription regulation. The importance of these processes is emphasized by the generally low correlation between mRNA and protein concentrations. For many prokaryotic and eukaryotic organisms, <50% of variation in protein abundance variation is explained by variation in mRNA concentrations (de Sousa Abreu et al , 2009 ). Given the plethora of regulatory mechanisms involved, most studies have focused so far on individual regulators and specific targets. Particularly in human, we currently lack system‐wide, quantitative analyses that evaluate the relative contribution of regulatory elements encoded in the mRNA and protein sequence. Existing studies have been carried out only in bacteria and yeast (Nie et al , 2006 ; Brockmann et al , 2007 ; Tuller et al , 2007 ; Wu et al , 2008 ). Here, we present the first comprehensive analysis on the impact of translation and protein degradation on protein abundance variation in a human cell line. For this purpose, we experimentally measured absolute protein and mRNA concentrations in the Daoy medulloblastoma cell line, using shotgun proteomics and microarrays, respectively (Figure 1 ). These data comprise one of the largest such sets available today for human. We focused on sequence features that likely impact protein translation and protein degradation, including length, nucleotide composition, structure of the untranslated regions (UTRs), coding sequence, composition of the translation initiation site, presence of upstream open reading frames putative target sites of miRNAs, codon usage, amino‐acid composition and protein degradation signals. Three types of tests have been conducted: (a) we examined partial Spearman's rank correlation of numerical features (e.g. length) with protein concentration, accounting for variation in mRNA concentrations; (b) for numerical and categorical features (e.g. function), we compared two extreme populations with Welch's t ‐test and (c) using a Multivariate Adaptive Regression Splines model, we analyzed the combined contributions of mRNA expression and sequence features to protein abundance variation (Figure 1 ). To account for the non‐linearity of many relationships, we use non‐parametric approaches throughout the analysis. We observed a significant positive correlation between mRNA and protein concentrations, larger than many previous measurements (de Sousa Abreu et al , 2009 ). We also show that the contribution of translation and protein degradation is at least as important as the contribution of mRNA transcription and stability to the abundance variation of the final protein products. Although variation in mRNA expression explains ∼25–30% of the variation in protein abundance, another 30–40% can be accounted for by characteristics of the sequences, which we identified in a comparative assessment of global correlates. Among these characteristics, sequence length, amino‐acid frequencies and also nucleotide frequencies in the coding region are of strong influence (Figure 3A ). Characteristics of the 3′UTR and of the 5′UTR, that is length, nucleotide composition and secondary structures, describe another part of the variation, leaving 33% expression variation unexplained. The unexplained fraction may be accounted for by mechanisms not considered in this analysis (e.g. regulation by RNA‐binding proteins or gene‐specific structural motifs), as well as expression and measurement noise. Our combined model including mRNA concentration and sequence features can explain 67% of the variation of protein abundance in this system—and thus has the highest predictive power for human protein abundance achieved so far (Figure 3B ). We provide a large‐scale dataset on absolute protein and matching mRNA concentrations from the human medulloblastoma cell line Daoy. The correlation between mRNA and protein concentrations is significant and positive ( R s =0.46, R 2 =0.29, P ‐value<2e16), although non‐linear. Out of ∼200 tested sequence features, sequence length, frequency and properties of amino acids, as well as translation initiation‐related features are the strongest individual correlates of protein abundance when accounting for variation in mRNA concentration. When integrating mRNA expression data and all sequence features into a non‐parametric regression model (Multivariate Adaptive Regression Splines), we were able to explain up to 67% of the variation in protein concentrations. Half of the contributions were attributed to mRNA concentrations, the other half to sequence features relating to regulation of translation and protein degradation. The sequence features are primarily linked to the coding and 3′ untranslated region. To our knowledge, this is the most comprehensive predictive model of human protein concentrations achieved so far.

The yeast Saccharomyces cerevisiae is powerful for studying human G protein-coupled receptors as they can be coupled to its mating pathway. However, some receptors, including the mu opioid receptor, are non-functional, which may be due to the presence of the fungal sterol ergosterol instead of cholesterol. Here we engineer yeast to produce cholesterol and introduce diverse mu, delta, and kappa opioid receptors to create sensitive opioid biosensors that recapitulate agonist binding profiles and antagonist inhibition. Additionally, human mu opioid receptor variants, including those with clinical relevance, largely display expected phenotypes. By testing mu opioid receptor-based biosensors with systematically adjusted cholesterol biosynthetic intermediates, we relate sterol profiles to biosensor sensitivity. Finally, we apply sterol-modified backgrounds to other human receptors revealing sterol influence in SSTR5, 5-HTR4, FPR1, and NPY1R signaling. This work provides a platform for generating human G protein-coupled receptor-based biosensors, facilitating receptor deorphanization and high-throughput screening of receptors and effectors. The yeast Saccharomyces cerevisiae is powerful for studying human G protein-coupled receptors as they can be coupled to its mating pathway. Here the authors engineer baker’s yeast to produce human sterols and show that vertebrate G protein coupled receptors are more sensitive in this membrane environment.

We have developed and validated a methodology for determining the antibody composition of the polyclonal serum response after immunization. Pepsin-digested serum IgGs were subjected to standard antigen-affinity chromatography, and resulting elution, wash, and flow-through fractions were analyzed by bottom-up, liquid chromatography–high-resolution tandem mass spectrometry. Identification of individual monoclonal antibodies required the generation of a database of IgG variable gene (V-gene) sequences constructed by NextGen sequencing of mature B cells. Antibody V-gene sequences are characterized by short complementarity determining regions (CDRs) of high diversity adjacent to framework regions shared across thousands of IgGs, greatly complicating the identification of antigen-specific IgGs from proteomically observed peptides. By mapping peptides marking unique V H CDRH3 sequences, we identified a set of V-genes heavily enriched in the affinity chromatography elution, constituting the serum polyclonal response. After booster immunization in a rabbit, we find that the antigen-specific serum immune response is oligoclonal, comprising antibodies encoding 34 different CDRH3s that group into 30 distinct antibody V H clonotypes. Of these 34 CDRH3s, 12 account for ∼60% of the antigen-specific CDRH3 peptide mass spectral counts. For comparison, antibodies with 18 different CDRH3s (12 clonotypes) were represented in the antigen-specific IgG fraction from an unimmunized rabbit that fortuitously displayed a moderate titer for BSA. Proteomically identified antibodies were synthesized and shown to display subnanomolar affinities. The ability to deconvolute the polyclonal serum response is likely to be of key importance for analyzing antibody responses after vaccination and for more completely understanding adaptive immune responses in health and disease.

Background Post-translational modification (PTM) of proteins is central to many cellular processes across all domains of life, but despite decades of study and a wealth of genomic and proteomic data the biological function of many PTMs remains unknown. This is especially true for prokaryotic PTM systems, many of which have only recently been recognized and studied in depth. It is increasingly apparent that a deep sampling of abundance across a wide range of environmental stresses, growth conditions, and PTM types, rather than simply cataloging targets for a handful of modifications, is critical to understanding the complex pathways that govern PTM deposition and downstream effects. Results We utilized a deeply-sampled dataset of MS/MS proteomic analysis covering 9 timepoints spanning the Escherichia coli growth cycle and an unbiased PTM search strategy to construct a temporal map of abundance for all PTMs within a 400 Da window of mass shifts. Using this map, we are able to identify novel targets and temporal patterns for N-terminal N α acetylation, C-terminal glutamylation, and asparagine deamidation. Furthermore, we identify a possible relationship between N-terminal N α acetylation and regulation of protein degradation in stationary phase, pointing to a previously unrecognized biological function for this poorly-understood PTM. Conclusions Unbiased detection of PTM in MS/MS proteomics data facilitates the discovery of novel modification types and previously unobserved dynamic changes in modification across growth timepoints.

Modern systems biology requires extensive, carefully curated measurements of cellular components in response to different environmental conditions. While high-throughput methods have made transcriptomics and proteomics datasets widely accessible and relatively economical to generate, systematic measurements of both mRNA and protein abundances under a wide range of different conditions are still relatively rare. Here we present a detailed, genome-wide transcriptomics and proteomics dataset of E. coli grown under 34 different conditions. Additionally, we provide measurements of doubling times and in-vivo metabolic fluxes through the central carbon metabolism. We manipulate concentrations of sodium and magnesium in the growth media, and we consider four different carbon sources glucose, gluconate, lactate, and glycerol. Moreover, samples are taken both in exponential and stationary phase, and we include two extensive time-courses, with multiple samples taken between 3 hours and 2 weeks. We find that exponential-phase samples systematically differ from stationary-phase samples, in particular at the level of mRNA. Regulatory responses to different carbon sources or salt stresses are more moderate, but we find numerous differentially expressed genes for growth on gluconate and under salt and magnesium stress. Our data set provides a rich resource for future computational modeling of E. coli gene regulation, transcription, and translation.

How do bacteria regulate their cellular physiology in response to starvation? Here, we present a detailed characterization of Escherichia coli growth and starvation over a time-course lasting two weeks. We have measured multiple cellular components, including RNA and proteins at deep genomic coverage, as well as lipid modifications and flux through central metabolism. Our study focuses on the physiological response of E. coli in stationary phase as a result of being starved for glucose, not on the genetic adaptation of E. coli to utilize alternative nutrients. In our analysis, we have taken advantage of the temporal correlations within and among RNA and protein abundances to identify systematic trends in gene regulation. Specifically, we have developed a general computational strategy for classifying expression-profile time courses into distinct categories in an unbiased manner. We have also developed, from dynamic models of gene expression, a framework to characterize protein degradation patterns based on the observed temporal relationships between mRNA and protein abundances. By comparing and contrasting our transcriptomic and proteomic data, we have identified several broad physiological trends in the E. coli starvation response. Strikingly, mRNAs are widely down-regulated in response to glucose starvation, presumably as a strategy for reducing new protein synthesis. By contrast, protein abundances display more varied responses. The abundances of many proteins involved in energy-intensive processes mirror the corresponding mRNA profiles while proteins involved in nutrient metabolism remain abundant even though their corresponding mRNAs are down-regulated.

Thermophilic organisms flourish in varied high-temperature environmental niches that are deadly to other organisms. Recently, genomic evidence has implicated a critical role for disulfide bonds in the structural stabilization of intracellular proteins from certain of these organisms, contrary to the conventional view that structural disulfide bonds are exclusively extracellular. Here both computational and structural data are presented to explore the occurrence of disulfide bonds as a protein-stabilization method across many thermophilic prokaryotes. Based on computational studies, disulfide-bond richness is found to be widespread, with thermophiles containing the highest levels. Interestingly, only a distinct subset of thermophiles exhibit this property. A computational search for proteins matching this target phylogenetic profile singles out a specific protein, known as protein disulfide oxidoreductase, as a potential key player in thermophilic intracellular disulfide-bond formation. Finally, biochemical support in the form of a new crystal structure of a thermophilic protein with three disulfide bonds is presented together with a survey of known structures from the literature. Together, the results provide insight into biochemical specialization and the diversity of methods employed by organisms to stabilize their proteins in exotic environments. The findings also motivate continued efforts to sequence genomes from divergent organisms.

Maintaining control over inflammatory processes represents a paradox for viral pathogens. Although many viruses induce host inflammatory responses to facilitate infection, control is necessary to avoid overactivation. One way is through the manipulation of proinflammatory chemokine levels, both host and viral. Murine cytomegalovirus (MCMV), a model betaherpesvirus, encodes a viral C-C chemokine, MCK2, which promotes host inflammatory responses and incorporates into virions to facilitate viral dissemination. Here, we show that the activity of M48, the conserved MCMV deubiquitinating enzyme (DUB), regulates MCK2 levels during infection. Inactivation of M48 DUB activity results in viral attenuation and exacerbates virally induced, MCK2-dependent inflammatory responses. M48 DUB activity also influences MCK2 incorporation into virions. Importantly, attenuation of DUB-mutant virus acute replication in vitro and in vivo is largely ameliorated by targeted deletion of MCK2. Thus, uncontrolled MCK2 levels appear to mediate DUB-mutant virus attenuation in specific tissues or cell types. This demonstrates that MCMV M48 DUB activity plays a previously unappreciated role in controlling MCK2 levels, thereby managing MCK2-dependent processes. These findings reveal a novel intrinsic control mechanism of virally induced inflammation and support the identification of betaherpesvirus DUBs as possible new targets for antiviral therapies. IMPORTANCE Human cytomegalovirus infections represent a tremendous burden not only to those afflicted but also to health care systems worldwide. As cytomegalovirus infections are a leading cause of nongenetic sensory loss and neurodevelopmental delay, it is imperative that valuable model systems exist in order that we might understand what viral factors contribute to replication and pathogenesis. Currently, the only approved drug treatments against CMV infection are nucleoside analogues, to which some strains have become resistant. Understanding unique viral enzymatic contributions to infections will allow the development of novel pharmacological therapies. Here, we show that M48, the conserved MCMV deubiquitinase, is critical for MCMV replication in mice and demonstrate that attenuation is due to deregulated production of a viral proinflammatory chemokine. The deubiquitinases of both human and murine CMV represent structurally unique DUBs and are therefore attractive targets for pharmacological intervention. Continued research into the substrates of these DUBs will lend additional insight into their potential as targets. Human cytomegalovirus infections represent a tremendous burden not only to those afflicted but also to health care systems worldwide. As cytomegalovirus infections are a leading cause of nongenetic sensory loss and neurodevelopmental delay, it is imperative that valuable model systems exist in order that we might understand what viral factors contribute to replication and pathogenesis. Currently, the only approved drug treatments against CMV infection are nucleoside analogues, to which some strains have become resistant. Understanding unique viral enzymatic contributions to infections will allow the development of novel pharmacological therapies. Here, we show that M48, the conserved MCMV deubiquitinase, is critical for MCMV replication in mice and demonstrate that attenuation is due to deregulated production of a viral proinflammatory chemokine. The deubiquitinases of both human and murine CMV represent structurally unique DUBs and are therefore attractive targets for pharmacological intervention. Continued research into the substrates of these DUBs will lend additional insight into their potential as targets.