Metaproteomic and 16S rRNA Gene Sequencing Analysis of the Infant Fecal Microbiome.

A metaproteomic analysis was conducted on the fecal microbiome of eight infants to characterize global protein and pathway expression. Although mass spectrometry-based proteomics is now a routine tool, analysis of the microbiome presents specific technical challenges, including the complexity and dynamic range of member taxa, the need for well-annotated metagenomic databases, and high inter-protein sequence redundancy and similarity. In this study, an approach was developed for assessment of biological phenotype and metabolic status, as a functional complement to DNA sequence analysis. Fecal samples were prepared and analysed by tandem mass spectrometry and a homology-based meta-clustering strategy was used to combine peptides from multiple species into representative proteins. In total, 15,250 unique peptides were sequenced and assigned to 2154 metaclusters, which were then assigned to pathways and functional groups. Differences were noted in several pathways, consistent with the dominant genera observed in different subjects. Although this study was not powered to draw conclusions from the comparisons, the results obtained demonstrate the applicability of this approach and provide the methods needed for performing semi-quantitative comparisons of human fecal microbiome composition, physiology and metabolism, as well as a more detailed assessment of microbial composition in comparison to 16S rRNA gene sequencing.

Identification of peptides with tolerogenic potential in a hydrolysed whey-based infant formula.

BACKGROUND: Failure to induce oral tolerance may result in food allergy. Hydrolysed cow's milk-based infant formulas are recommended in subjects with a high risk of developing allergic disease. Presentation of T cell epitopes is a prerequisite to generate regulatory T cells that could contribute to oral tolerance. OBJECTIVE: To investigate whether a specific hydrolysed whey-based infant formula contains peptides that function as T cell epitopes to support the development of oral tolerance to whey. METHODS: First, a novel liquid chromatography-mass spectrometry (LC-MS) method was developed to characterize ß-lactoglobulin-derived peptides present in a specific infant formula with a focus on region AA#13-48 of ß-lactoglobulin, which has previously been described to contain T cell epitopes with tolerogenic potential. Second, the formula was subjected to the ProImmune ProPresent® antigen presentation assay and MHC class II binding algorithm to identify relevant HLA-DRB1-restricted peptides. Third, identified peptides were tested on human cow's milk protein-specific T cell lines to determine T cell recognition. RESULTS: Thirteen peptides of minimal 9AAs long that overlap with AA#13-48 of ß-lactoglobulin were identified. Six of them were found across all batches analysed. It was further confirmed that these peptides were processed and presented by human dendritic cells. The identified HLA-DRB1-restricted peptides were correlated to AA#11-30 and AA#23-39 of ß-lactoglobulin. Importantly, the proliferation assay showed that the synthetic peptides were recognized by cow's milk protein-specific T cell lines and induced T cell proliferation. CONCLUSION AND CLINICAL RELEVANCE: This study demonstrates that the tested hydrolysed infant formula contains functional HLA-DRB1-restricted T cell epitopes, which can potentially support the development of oral tolerance to whey.

Alternative reading frame selection mediated by a tRNA-like domain of an internal ribosome entry site.

The dicistrovirus intergenic region internal ribosome entry site (IRES) utilizes a unique mechanism, involving P-site tRNA mimicry, to directly assemble 80S ribosomes and initiate translation at a specific non-AUG codon in the ribosomal A site. A subgroup of dicistrovirus genomes contains an additional stem-loop 5'-adjacent to the IRES and a short open reading frame (ORFx) that overlaps the viral structural polyprotein ORF (ORF2) in the +1 reading frame. Using mass spectrometry and extensive mutagenesis, we show that, besides directing ORF2 translation, the Israeli acute paralysis dicistrovirus IRES also directs ORFx translation. The latter is mediated by a UG base pair adjacent to the P-site tRNA-mimicking domain. An ORFx peptide was detected in virus-infected honey bees by multiple reaction monitoring mass spectrometry. Finally, the 5' stem-loop increases IRES activity and may couple translation of the two major ORFs of the virus. This study reveals a novel viral strategy in which a tRNA-like IRES directs precise, initiator Met-tRNA-independent translation of two overlapping ORFs.

Connexin multi-site phosphorylation: mass spectrometry-based proteomics fills the gap.

Connexins require an integrated network for protein synthesis, assembly, gating, internalization, degradation and feedback control that are necessary to regulate the biosynthesis, and turnover of gap junction channels. At the most fundamental level, the introduction of sequence-altering, modifications introduces changes in protein conformation, activity, charge, stability and localization. Understanding the sites, patterns and magnitude of protein post-translational modification, including phosphorylation, is absolutely critical. Historically, the examination of connexin phosphorylation has been placed within the context that one or small number of sites of modification strictly corresponds to one molecular function. However, the release of high-profile proteomic datasets appears to challenge this dogma by demonstrating connexins undergo multiple levels of multi-site phosphorylation. With the growing prominence of mass spectrometry in biology and medicine, we are now getting a glimpse of the richness of connexin phosphate signals. Having implications to health and disease, this review provides an overview of technologies in the context of targeted and discovery proteomics, and further discusses how these techniques are being applied to "fill the gaps" in understanding of connexin post-translational control. This article is part of a Special Issue entitled: The Communicating junctions, roles and dysfunctions.

Quantitative proteomics by metabolic labeling of model organisms.

In the biological sciences, model organisms have been used for many decades and have enabled the gathering of a large proportion of our present day knowledge of basic biological processes and their derailments in disease. Although in many of these studies using model organisms, the focus has primarily been on genetics and genomics approaches, it is important that methods become available to extend this to the relevant protein level. Mass spectrometry-based proteomics is increasingly becoming the standard to comprehensively analyze proteomes. An important transition has been made recently by moving from charting static proteomes to monitoring their dynamics by simultaneously quantifying multiple proteins obtained from differently treated samples. Especially the labeling with stable isotopes has proved an effective means to accurately determine differential expression levels of proteins. Among these, metabolic incorporation of stable isotopes in vivo in whole organisms is one of the favored strategies. In this perspective, we will focus on methodologies to stable isotope label a variety of model organisms in vivo, ranging from relatively simple organisms such as bacteria and yeast to Caenorhabditis elegans, Drosophila, and Arabidopsis up to mammals such as rats and mice. We also summarize how this has opened up ways to investigate biological processes at the protein level in health and disease, revealing conservation and variation across the evolutionary tree of life.

In vivo stable isotope labeling of fruit flies reveals post-transcriptional regulation in the maternal-to-zygotic transition.

An important hallmark in embryonic development is characterized by the maternal-to-zygotic transition (MZT) where zygotic transcription is activated by a maternally controlled environment. Post-transcriptional and translational regulation is critical for this transition and has been investigated in considerable detail at the gene level. We used a proteomics approach using metabolic labeling of Drosophila to quantitatively assess changes in protein expression levels before and after the MZT. By combining stable isotope labeling of fruit flies in vivo with high accuracy quantitative mass spectrometry we could quantify 2,232 proteins of which about half changed in abundance during this process. We show that approximately 500 proteins increased in abundance, providing direct evidence of the identity of proteins as a product of embryonic translation. The group of down-regulated proteins is dominated by maternal factors involved in translational control of maternal and zygotic transcripts. Surprisingly a direct comparison of transcript and protein levels showed that the mRNA levels of down-regulated proteins remained relatively constant, indicating a translational control mechanism specifically targeting these proteins. In addition, we found evidence for post-translational processing of cysteine proteinase-1 (Cathepsin L), which became activated during the MZT as evidenced by the loss of its N-terminal propeptide. Poly(A)-binding protein was shown to be processed at its C-terminal tail, thereby losing one of its protein-interacting domains. Altogether this quantitative proteomics study provides a dynamic profile of known and novel proteins of maternal as well as embryonic origin. This provides insight into the production, stability, and modification of individual proteins, whereas discrepancies between transcriptional profiles and protein dynamics indicate novel control mechanisms in genome activation during early fly development.

Straightforward and de novo peptide sequencing by MALDI-MS/MS using a Lys-N metalloendopeptidase.

In this work, we explore the potential of the metalloendopeptidase Lys-N for MALDI-MS/MS proteomics applications. Initially we digested a HEK293 cellular lysate with Lys-N and, for comparison, in parallel with the protease Lys-C. The resulting peptides were separated by strong cation exchange to enrich and isolate peptides containing a single N-terminal lysine. MALDI-MS/MS analysis of these peptides yielded CID spectra with clear and often complete sequence ladders of b-ions. To test the applicability for de novo sequencing we next separated an ostrich muscle tissue protein lysate by one-dimensional SDS-PAGE. A protein band at 42 kDa was in-gel digested with Lys-N. Relatively straightforward sequencing resulted in the de novo identification of the two ostrich proteins creatine kinase and actin. We therefore conclude that this method that combines Lys-N, strong cation exchange enrichment, and MALDI-MS/MS analysis provides a valuable alternative proteomics strategy.

MSQuant, an open source platform for mass spectrometry-based quantitative proteomics.

Mass spectrometry-based proteomics critically depends on algorithms for data interpretation. A current bottleneck in the rapid advance of proteomics technology is the closed nature and slow development cycle of vendor-supplied software solutions. We have created an open source software environment, called MSQuant, which allows visualization and validation of peptide identification results directly on the raw mass spectrometric data. MSQuant iteratively recalibrates MS data thereby significantly increasing mass accuracy leading to fewer false positive peptide identifications. Algorithms to increase data quality include an MS(3) score for peptide identification and a post-translational modification (PTM) score that determines the probability that a modification such as phosphorylation is placed at a specific residue in an identified peptide. MSQuant supports relative protein quantitation based on precursor ion intensities, including element labels (e.g., (15)N), residue labels (e.g., SILAC and ICAT), termini labels (e.g., (18)O), functional group labels (e.g., mTRAQ), and label-free ion intensity approaches. MSQuant is available, including an installer and supporting scripts, at http://msquant.sourceforge.net .

Monitoring of changes in the membrane proteome during stationary phase adaptation of Bacillus subtilis using in vivo labeling techniques.

Bacillus subtilis has been developed as a model system for physiological proteomics. However, thus far these studies have mainly been limited to cytoplasmic, extracellular, and cell-wall attached proteins. Although being certainly important for cell physiology, the membrane protein fraction has not been studied in comparable depth due to inaccessibility by traditional 2-DE-based workflows and limitations in reliable quantification. In this study, we now compare the potential of stable isotope labeling with amino acids (SILAC) and (14)N/(15)N-labeling for the analysis of bacterial membrane fractions in physiology-driven proteomic studies. Using adaptation of B. subtilis to amino acid (lysine) and glucose starvation as proof of principle scenarios, we show that both approaches provide similarly valuable data for the quantification of bacterial membrane proteins. Even if labeling with stable amino acids allows a more straightforward analysis of data, the (14)N/(15)N-labeling has some advantages in general such as labeling of all amino acids and thereby increasing the number of peptides for quantification. Both, SILAC as well as (14)N/(15)N-labeling are compatible with 2-DE, 2-D LC-MS/MS, and GeLC-MS/MS and thus will allow comprehensive simultaneous interrogation of cytoplasmic and enriched membrane proteomes.

Optimizing identification and quantitation of 15N-labeled proteins in comparative proteomics.

Comparative proteomics has emerged as a powerful approach to determine differences in protein abundance between biological samples. The introduction of stable-isotopes as internal standards especially paved the road for quantitative proteomics for comprehensive approaches to accurately determine protein dynamics. Metabolic labeling with (15)N isotopes is applied to an increasing number of organisms, including Drosophila, C. elegans, and rats. However, (15)N-enrichment is often suboptimal (<98%), which may hamper identification and quantitation of proteins. Here, we systematically investigated two independent (15)N-labeled data sets to explore the influence of heavy nitrogen enrichment on the number of identifications as well as on the error in protein quantitation. We show that specifically larger (15)N-labeled peptides are under-represented when compared to their (14)N counterparts and propose a correction method, which significantly increases the number of identifications. In addition, we developed a method that corrects for inaccurate peptide ratios introduced by incomplete (15)N enrichment. This results in improved accuracy and precision of protein quantitation. Altogether, this study provides insight into the process of protein identification and quantitation, and the methods described here can be used to improve both qualitative and quantitative data obtained by labeling with heavy nitrogen with enrichment less than 100%.

A Highly Effective Component Vaccine against Nontyphoidal Salmonella enterica Infections.

UNLABELLED: Nontyphoidal Salmonella enterica (NTS) infections are a major burden to global public health, as they lead to diseases ranging from gastroenteritis to systemic infections and there is currently no vaccine available. Here, we describe a highly effective component vaccine against S. enterica serovar Typhimurium in both gastroenteritis and systemic murine infection models. We devised an approach to generate supernatants of S. enterica serovar Typhimurium, an organism that is highly abundant in virulence factors. Immunization of mice with this supernatant resulted in dramatic protection against a challenge with serovar Typhimurium, showing increased survival in the systemic model and decreased intestinal pathology in the gastrointestinal model. Protection correlated with specific IgA and IgG levels in the serum and specific secretory IgA levels in the feces of immunized mice. Initial characterization of the protective antigens in the bacterial culture supernatants revealed a subset of antigens that exhibited remarkable stability, a highly desirable characteristic of an effective vaccine to be used under suboptimal environmental conditions in developing countries. We were able to purify a subset of the peptides present in the supernatants and show their potential for immunization of mice against serovar Typhimurium resulting in a decreased level of colonization. This component vaccine shows promise with regard to protecting against NTS, and further work should significantly help to establish vaccines against these prevalent infections. IMPORTANCE: Salmonella enterica infections other than typhoid and paratyphoid fever are a major global health burden, as they cause high morbidity and mortality worldwide. Strategies that prevent Salmonella-related diseases are greatly needed, and there is a significant push for the development of vaccines against nontyphoidal Salmonella enterica serovars. In this work, we describe an S. Typhimurium supernatant-derived vaccine that is effective in reducing bacterial colonization in mouse models of gastroenteritis as well as invasive disease. This is a component vaccine that shows high stability to heat, a feature that is important for use under suboptimal conditions, such as those found in sub-Saharan Africa.

A horizontally acquired transcription factor coordinates Salmonella adaptations to host microenvironments.

UNLABELLED: The transcription factors HilA and SsrB activate expression of two type III secretion systems (T3SSs) and cognate effectors that reprogram host cell functions to benefit infecting Salmonella in the host. These transcription factors, the secretion systems, and the effectors are all encoded by horizontally acquired genes. Using quantitative proteomics, we quantified the abundance of 2,149 proteins from hilA or ssrB Salmonella in vitro. Our results suggest that the HilA regulon does not extend significantly beyond proteins known to be involved in direct interactions with intestinal epithelium. On the other hand, SsrB influences the expression of a diverse range of proteins, many of which are ancestral to the acquisition of ssrB. In addition to the known regulon of T3SS-related proteins, we show that, through SodCI and bacterioferritin, SsrB controls resistance to reactive oxygen species and that SsrB down-regulates flagella and motility. This indicates that SsrB-controlled proteins not only redirect host cell membrane traffic to establish a supportive niche within host cells but also have adapted to the chemistry and physical constraints of that niche. IMPORTANCE: Expression of T3SSs typically requires a transcription factor that is linked in a genomic island. Studies of the targets of HilA and SsrB have focused on almost exclusively on T3SS substrates that are either linked or encoded in distinct genomic islands. By broadening our focus, we found that the regulon of SsrB extended considerably beyond T3SS-2 and its substrates, while that of HilA did not. That at least two SsrB-regulated processes streamline existence in the intracellular niche afforded by T3SS-2 seems to be a predictable outcome of evolution and natural selection. However, and importantly, these are the first such functions to be implicated as being SsrB dependent. The concept of T3SS-associated transcription factors coordinating manipulations of host cells together with distinct bacterial processes for increased efficiency has unrealized implications for numerous host-pathogen systems.

MSQuant: a platform for stable isotope-based quantitative proteomics.

Quantitative approaches in proteomics are emerging as a powerful tool to probe the dynamics of protein expression across biological conditions. Thereby, quantification helps to recognize proteins with potential biological relevance, which greatly aids in the design of follow-up experiments. Although multiple methods have been established that are based on stable-isotope labeling and label-free approaches, one of the remaining bottlenecks is the analysis and quantification of proteins in large datasets. MSQuant is a platform for protein quantification, capable of handling multiple labeling strategies and supporting several vendor data formats. Here, we report on the use and versatility of MSQuant.

Metabolic labeling of model organisms using heavy nitrogen (15N).

Quantitative proteomics aims to identify and quantify proteins in cells or organisms that have been obtained from different biological origin (e.g., "healthy vs. diseased"), that have received different treatments, or that have different genetic backgrounds. Protein expression levels can be quantified by labeling proteins with stable isotopes, followed by mass spectrometric analysis. Stable isotopes can be introduced in vitro by reacting proteins or peptides with isotope-coded reagents (e.g., iTRAQ, reductive methylation). A preferred way, however, is the metabolic incorporation of heavy isotopes into cells or organisms by providing the label, in the form of amino acids (such as in SILAC) or salts, in the growth media. The advantage of in vivo labeling is that it does not suffer from side reactions or incomplete labeling that might occur in chemical derivatization. In addition, metabolic labeling occurs at the earliest possible moment in the sample preparation process, thereby minimizing the error in quantitation. Labeling with the heavy stable isotope of nitrogen (i.e., (15)N) provides an efficient way for accurate protein quantitation. Where the application of SILAC is mostly restricted to cell culture, (15)N labeling can be used for micro-organisms as well as a number of higher (multicellular) organisms. The most prominent examples of the latter are Caenorhabditis elegans and Drosophila (fruit fly), two important model organisms for a range of regulatory processes underlying developmental biology. Here we describe in detail the labeling with (15)N atoms, with a particular focus on fruit flies and C. elegans. We also describe methods for the identification and quantitation of (15)N-labeled proteins by mass spectrometry and bioinformatic analysis.

Highly robust, automated, and sensitive online TiO2-based phosphoproteomics applied to study endogenous phosphorylation in Drosophila melanogaster.

Reversible protein phosphorylation ranks among the most important post-translational modifications, and elucidation of phosphorylation sites is essential to understand the regulation of key cellular processes such as signal transduction. Enrichment of phosphorylated peptides is a prerequisite for successful analysis due to their low stoichiometry, heterogeneity, and low abundance. Enrichment is often performed manually, which is inherently labor-intensive and a major hindrance in large-scale analyses. Automation of the enrichment method would vastly improve reproducibility and thereby facilitate 'high-throughput' phosphoproteomics research. Here, we describe a robust and automated online TiO 2-based two-dimensional chromatographic approach to selectively enrich phosphorylated peptides from digests of complete cellular lysates. We demonstrate method enhancement for both adsorption and desorption of phosphorylated peptides resulting in lower limits of detection. Phosphorylated peptides from a mere 500 attomole tryptic digest of a protein mixture were easily detected. With the combination of strong cation exchange chromatography with the online TiO 2 enrichment, 2152 phosphopeptides were enriched from 250 microg of protein originating for the cell lysate of Drosophila melanogaster S2 cells. This is a 4-fold improvement when compared to an enrichment strategy based solely on strong cation exchange/LC-MS. Phosphopeptide enrichment methods are intrinsically biased against relatively basic phosphopeptides. Analysis of the p I distributions of the enriched/detected phosphopeptides showed that the p I profile resembles that of a total Drosophila protein digest, revealing that the current described online procedure does not discriminate against either more acidic or basic phosphopeptides. However, careful comparison of our new and existing phosphopeptide enrichment techniques also reveal that, like many enrichment techniques, we are still far from comprehensive phosphoproteomics analyses, and we describe several factors that still require to be addressed. Still, as the online approach allows the complementary measurements of phosphopeptides and their nonphosphorylated counterparts in subsequent analyses, this method is well-suited for automated quantitative phosphoproteomics.

Expression clustering reveals detailed co-expression patterns of functionally related proteins during B cell differentiation: a proteomic study using a combination of one-dimensional gel electrophoresis, LC-MS/MS, and stable isotope labeling by amino acids in cell culture (SILAC).

B cells play an essential role in the immune response. Upon activation they may differentiate into plasma cells that secrete specific antibodies against potentially pathogenic non-self antigens. To identify the cellular proteins that are important for efficient production of these antibodies we set out to study the B cell differentiation process at the proteome level. We performed an in-depth proteomic study to quantify dynamic relative protein expression patterns of several hundreds of proteins at five consecutive time points after lipopolysaccharide-induced activation of B lymphocytes. The proteome analysis was performed using a combination of stable isotope labeling using [13C6]leucine added to the murine B cell cultures, one-dimensional gel electrophoresis, and LC-MS/MS. In this study we identified 1,001 B cell proteins. We were able to quantify the expression levels of a quarter of all identified proteins (i.e. 234) at each of the five different time points. Nearly all proteins revealed changes in expression patterns. The quantitative dataset was further analyzed using an unbiased clustering method. Based on their expression profiles, we grouped the entire set of 234 quantified proteins into a limited number of 12 distinct clusters. Functionally related proteins showed a strong correlation in their temporal expression profiles. The quality of the quantitative data allowed us to even identify subclusters within functionally related classes of proteins such as in the endoplasmic reticulum proteins that are involved in antibody production.

Derivatization of small oligosaccharides prior to analysis by matrix-assisted laser desorption/ionization using glycidyltrimethylammonium chloride and Girard's reagent T.

In matrix-assisted laser desorption/ionization (MALDI) analyses of small oligosaccharides a very large increase in sensitivity (by a factor of 1000) may be obtained by introducing a quaternary ammonium center ('quaternization'). Such a quaternary ammonium center may be introduced into the saccharide by reaction with commercially available glycidyltrimethylammonium chloride (GTMA), or by using Girard's reagent T (Naven and Harvey, Rapid Commun. Mass Spectrom. 1996; 10: 829). GTMA reacts with alcohol functionalities, whereas Girard's reagent T is specific for aldehyde and keto groups. Thus reducing saccharides can be derivatized by both GTMA and Girard's reagent T. For example, glucose or cellobiose having a stock concentration of 3 x 10(-5) M (5 microg/mL) produces no sugar-derived signals in conventional MALDI, but their quaternized derivatives, also at 3 x 10(-5) M, yield intense signals, with the matrix-derived signals only being weak. Similar results were obtained for glucosamine. Non-reducing saccharides as well as sugar alcohols can be derivatized using GTMA; thus, although sucrose, raffinose and sorbitol do not react with Girard's reagent T, they all produce intense signals after derivatization with GTMA. An example of the application of these derivatization reactions is provided by the analysis of oligosaccharides in beer.