Optimization of parameters for coverage of low molecular weight proteins

Deep proteomics reveals incorporation of unedited proteins into mitochondrial protein complexes in Arabidopsis

The mitochondrial proteome consists of numerous types of proteins which either are encoded and synthesized in the mitochondria, or encoded in the cell nucleus, synthesized in the cytoplasm and imported into the mitochondria. Their synthesis in the mitochondria, but not in the nucleus, relies on the editing of the primary transcripts of their genes at defined sites. Here, we present an in-depth investigation of the mitochondrial proteome of Arabidopsis (Arabidopsis thaliana) and a public online platform for the exploration of the data. For the analysis of our shotgun proteomic data, an Arabidopsis sequence database was created comprising all available protein sequences from the TAIR10 and Araport11 databases, supplemented with sequences of proteins translated from edited and nonedited transcripts of mitochondria. Amino acid sequences derived from partially edited transcripts were also added to analyze proteins encoded by the mitochondrial genome. Proteins were digested in parallel with six different endoproteases to obtain maximum proteome coverage. The resulting peptide fractions were finally analyzed using liquid chromatography coupled to ion mobility spectrometry and tandem mass spectrometry. We generated a "deep mitochondrial proteome" of 4,692 proteins. 1,339 proteins assigned to mitochondria by the SUBA5 database (https://suba.live) accounted for >80% of the total protein mass of our fractions. The coverage of proteins by identified peptides was particularly high compared to single-protease digests, allowing the exploration of differential splicing and RNA editing events at the protein level. We show that proteins translated from nonedited transcripts can be incorporated into native mitoribosomes and the ATP synthase complex. We present a portal for the use of our data, based on "proteomaps" with directly linked protein data. The portal is available at www.proteomeexplorer.de.

No country for old methods: New tools for studying microproteins

Microproteins encoded by small open reading frames (sORFs) have emerged as a fascinating frontier in genomics. Traditionally overlooked due to their small size, recent technological advancements such as ribosome profiling, mass spectrometry-based strategies and advanced computational approaches have led to the annotation of more than 7000 sORFs in the human genome. Despite the vast progress, only a tiny portion of these microproteins have been characterized and an important challenge in the field lies in identifying functionally relevant microproteins and understanding their role in different cellular contexts. In this review, we explore the recent advancements in sORF research, focusing on the new methodologies and computational approaches that have facilitated their identification and functional characterization. Leveraging these new tools hold great promise for dissecting the diverse cellular roles of microproteins and will ultimately pave the way for understanding their role in the pathogenesis of diseases and identifying new therapeutic targets.

Mass spectrometry in the discovery of peptides involved in intercellular communication: From targeted to untargeted peptidomics approaches

Endogenous peptide hormones represent an essential class of biomolecules, which regulate cell-cell communications in diverse physiological processes of organisms. Mass spectrometry (MS) has been developed to be a powerful technology for identifying and quantifying peptides in a highly efficient manner. However, it is difficult to directly identify these peptide hormones due to their diverse characteristics, dynamic regulations, low abundance, and existence in a complicated biological matrix. Here, we summarize and discuss the roles of targeted and untargeted MS in discovering peptide hormones using bioassay-guided purification, bioinformatics screening, or the peptidomics-based approach. Although the peptidomics approach is expected to discover novel peptide hormones unbiasedly, only a limited number of successful cases have been reported. The critical challenges and corresponding measures for peptidomics from the steps of sample preparation, peptide extraction, and separation to the MS data acquisition and analysis are also discussed. We also identify emerging technologies and methods that can be integrated into the discovery platform toward the comprehensive study of endogenous peptide hormones.

Newfound Coding Potential of Transcripts Unveils Missing Members of Human Protein Communities

Recent proteogenomic approaches have led to the discovery that regions of the transcriptome previously annotated as non-coding regions [i.e., untranslated regions (UTRs), open reading frames overlapping annotated coding sequences in a different reading frame, and non-coding RNAs] frequently encode proteins, termed alternative proteins (altProts). This suggests that previously identified protein-protein interaction (PPI) networks are partially incomplete because altProts are not present in conventional protein databases. Here, we used the proteogenomic resource OpenProt and a combined spectrum- and peptide-centric analysis for the re-analysis of a high-throughput human network proteomics dataset, thereby revealing the presence of 261 altProts in the network. We found 19 genes encoding both an annotated (reference) and an alternative protein interacting with each other. Of the 117 altProts encoded by pseudogenes, 38 are direct interactors of reference proteins encoded by their respective parental genes. Finally, we experimentally validate several interactions involving altProts. These data improve the blueprints of the human PPI network and suggest functional roles for hundreds of altProts.

Low Molecular Weight Sericin Enhances the In Vitro of Immunological Modulation and Cell Migration

Sericin, a waste product of the silk textile industry, has favorable physicochemical and biological properties. In this study, we extracted a low molecular weight (MW) sericin (LMW-sericin; below 10 kDa) by a performing high-temperature and high-pressure method and confirmed the MW using matrix-assisted laser desorption ionization-time of flight and liquid chromatography–mass spectrometry. Furthermore, we determined its biological effects on macrophages and human adipose stem cells (hASCs) as cell models to investigate the biocompatibility, immunomodulation behavior, and potential signaling pathway-related wound healing via analyses of gene expression of focal adhesion and human cytokines and chemokines using quantitative real-time polymerase chain reaction and cytokine assay. LMW-sericin showed good biocompatibility both in macrophages and hASCs. Macrophages cultured with 0.1 mg/ml LMW-sericin displayed an improved inflammatory response shown by the upregulation of CXCL9, IL12A, BMP7, and IL10, which developed Th1 and Th2 balance. LMW-sericin also improved the differentiation of macrophages toward the M2 phenotype by significantly enhancing the expression of Arg-1, which is conducive to the repair of the inflammatory environment. Moreover, the gene expression of hASCs showed that LMW-sericin promoted the secretion of beneficial adhesion molecules that potentially activate the gene transcription of differentiation and migration in hASCs, as well as significantly enhanced the levels of PKCβ1, RhoA, and RasGFR1 as fruitful molecules in wound healing. These findings provide insights into LMW-sericin application as a potential biomaterial for wound management.

Common Features in lncRNA Annotation and Classification: A Survey

Long non-coding RNAs (lncRNAs) are widely recognized as important regulators of gene expression. Their molecular functions range from miRNA sponging to chromatin-associated mechanisms, leading to effects in disease progression and establishing them as diagnostic and therapeutic targets. Still, only a few representatives of this diverse class of RNAs are well studied, while the vast majority is poorly described beyond the existence of their transcripts. In this review we survey common in silico approaches for lncRNA annotation. We focus on the well-established sets of features used for classification and discuss their specific advantages and weaknesses. While the available tools perform very well for the task of distinguishing coding sequence from other RNAs, we find that current methods are not well suited to distinguish lncRNAs or parts thereof from other non-protein-coding input sequences. We conclude that the distinction of lncRNAs from intronic sequences and untranslated regions of coding mRNAs remains a pressing research gap.

Peptidomics and proteogenomics: background, challenges and future needs

INTRODUCTION

With available genomic data and related information, it is becoming possible to better highlight mutations or genomic alterations associated with a particular disease or disorder. The advent of high-throughput sequencing technologies has greatly advanced diagnostics, prognostics, and drug development.

AREAS COVERED

Peptidomics and proteogenomics are the two post-genomic technologies that enable the simultaneous study of peptides and proteins/transcripts/genes. Both technologies add a remarkably large amount of data to the pool of information on various peptides associated with gene mutations or genome remodeling. Literature search was performed in the PubMed database and is up to date.

EXPERT OPINION

This article lists various techniques used for peptidomic and proteogenomic analyses. It also explains various bioinformatics workflows developed to understand differentially expressed peptides/proteins and their role in disease pathogenesis. Their role in deciphering disease pathways, cancer research, and biomarker discovery using biofluids is highlighted. Finally, the challenges and future requirements to overcome the current limitations for their effective clinical use are also discussed.

Escherichia coli Small Proteome

Escherichia coli was one of the first species to have its genome sequenced and remains one of the best-characterized model organisms. Thus, it is perhaps surprising that recent studies have shown that a substantial number of genes have been overlooked. Genes encoding more than 140 small proteins, defined as those containing 50 or fewer amino acids, have been identified in E. coli in the past 10 years, and there is substantial evidence indicating that many more remain to be discovered. This review covers the methods that have been successful in identifying small proteins and the short open reading frames that encode them. The small proteins that have been functionally characterized to date in this model organism are also discussed. It is hoped that the review, along with the associated databases of known as well as predicted but undetected small proteins, will aid in and provide a roadmap for the continued identification and characterization of these proteins in E. coli as well as other bacteria.

Bottom-up and top-down proteomic approaches for the identification, characterization, and quantification of the low molecular weight proteome with focus on short open reading frame-encoded peptides

The recent discovery of alternative open reading frames creates a need for suitable analytical approaches to verify their translation and to characterize the corresponding gene products at the molecular level. As the analysis of small proteins within a background proteome by means of classical bottom-up proteomics is challenging, method development for the analysis of small open reading frame encoded peptides (SEPs) have become a focal point for research. Here, we highlight bottom-up and top-down proteomics approaches established for the analysis of SEPs in both pro- and eukaryotes. Major steps of analysis, including sample preparation and (small) proteome isolation, separation and mass spectrometry, data interpretation and quality control, quantification, the analysis of post-translational modifications, and exploration of functional aspects of the SEPs by means of proteomics technologies are described. These methods do not exclusively cover the analytics of SEPs but simultaneously include the low molecular weight proteome, and moreover, can also be used for the proteome-wide analysis of proteolytic processing events.

A workflow to identify novel proteins based on the direct mapping of peptide-spectrum-matches to genomic locations

Background

Small Proteins have received increasing attention in recent years. They have in particular been implicated as signals contributing to the coordination of bacterial communities. In genome annotations they are often missing or hidden among large numbers of hypothetical proteins because genome annotation pipelines often exclude short open reading frames or over-predict hypothetical proteins based on simple models. The validation of novel proteins, and in particular of small proteins (sProteins), therefore requires additional evidence. Proteogenomics is considered the gold standard for this purpose. It extends beyond established annotations and includes all possible open reading frames (ORFs) as potential sources of peptides, thus allowing the discovery of novel, unannotated proteins. Typically this results in large numbers of putative novel small proteins fraught with large fractions of false-positive predictions.

Results

We observe that number and quality of the peptide-spectrum matches (PSMs) that map to a candidate ORF can be highly informative for the purpose of distinguishing proteins from spurious ORF annotations. We report here on a workflow that aggregates PSM quality information and local context into simple descriptors and reliably separates likely proteins from the large pool of false-positive, i.e., most likely untranslated ORFs. We investigated the artificial gut microbiome model SIHUMIx, comprising eight different species, for which we validate 5114 proteins that have previously been annotated only as hypothetical ORFs. In addition, we identified 37 non-annotated protein candidates for which we found evidence at the proteomic and transcriptomic level. Half (19) of these candidates have close functional homologs in other species. Another 12 candidates have homologs designated as hypothetical proteins in other species. The remaining six candidates are short (< 100 AA) and are most likely bona fide novel proteins.

Conclusions

The aggregation of PSM quality information for predicted ORFs provides a robust and efficient method to identify novel proteins in proteomics data. The workflow is in particular capable of identifying small proteins and frameshift variants. Since PSMs are explicitly mapped to genomic locations, it furthermore facilitates the integration of transcriptomics data and other sources of genome-level information.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12859-021-04159-8.

Multi-protease Approach for the Improved Identification and Molecular Characterization of Small Proteins and Short Open Reading Frame-Encoded Peptides

The identification of proteins below approximately 70-100 amino acids in bottom-up proteomics is still a challenging task due to the limited number of peptides generated by proteolytic digestion. This includes the short open reading frame-encoded peptides (SEPs), which are a subset of the small proteins that were not previously annotated or that are alternatively encoded. Here, we systematically investigated the use of multiple proteases (trypsin, chymotrypsin, LysC, LysargiNase, and GluC) in GeLC-MS/MS analysis to improve the sequence coverage and the number of identified peptides for small proteins, with a focus on SEPs, in the archaeon Methanosarcina mazei. Combining the data of all proteases, we identified 63 small proteins and additional 28 SEPs with at least two unique peptides, while only 55 small proteins and 22 SEP could be identified using trypsin only. For 27 small proteins and 12 SEPs, a complete sequence coverage was achieved. Moreover, for five SEPs, incorrectly predicted translation start points or potential in vivo proteolytic processing were identified, confirming the data of a previous top-down proteomics study of this organism. The results show clearly that a multi-protease approach allows to improve the identification and molecular characterization of small proteins and SEPs. LC-MS data: ProteomeXchange PXD023921.

Discovery of novel community-relevant small proteins in a simplified human intestinal microbiome

BACKGROUND

The intestinal microbiota plays a crucial role in protecting the host from pathogenic microbes, modulating immunity and regulating metabolic processes. We studied the simplified human intestinal microbiota (SIHUMIx) consisting of eight bacterial species with a particular focus on the discovery of novel small proteins with less than 100 amino acids (= sProteins), some of which may contribute to shape the simplified human intestinal microbiota. Although sProteins carry out a wide range of important functions, they are still often missed in genome annotations, and little is known about their structure and function in individual microbes and especially in microbial communities.

RESULTS

We created a multi-species integrated proteogenomics search database (iPtgxDB) to enable a comprehensive identification of novel sProteins. Six of the eight SIHUMIx species, for which no complete genomes were available, were sequenced and de novo assembled. Several proteomics approaches including two earlier optimized sProtein enrichment strategies were applied to specifically increase the chances for novel sProtein discovery. The search of tandem mass spectrometry (MS/MS) data against the multi-species iPtgxDB enabled the identification of 31 novel sProteins, of which the expression of 30 was supported by metatranscriptomics data. Using synthetic peptides, we were able to validate the expression of 25 novel sProteins. The comparison of sProtein expression in each single strain versus a multi-species community cultivation showed that six of these sProteins were only identified in the SIHUMIx community indicating a potentially important role of sProteins in the organization of microbial communities. Two of these novel sProteins have a potential antimicrobial function. Metabolic modelling revealed that a third sProtein is located in a genomic region encoding several enzymes relevant for the community metabolism within SIHUMIx.

CONCLUSIONS

We outline an integrated experimental and bioinformatics workflow for the discovery of novel sProteins in a simplified intestinal model system that can be generically applied to other microbial communities. The further analysis of novel sProteins uniquely expressed in the SIHUMIx multi-species community is expected to enable new insights into the role of sProteins on the functionality of bacterial communities such as those of the human intestinal tract. Video abstract.

Ribosome-bound Get4/5 facilitates the capture of tail-anchored proteins by Sgt2 in yeast

The guided entry of tail-anchored proteins (GET) pathway assists in the posttranslational delivery of tail-anchored proteins, containing a single C-terminal transmembrane domain, to the ER. Here we uncover how the yeast GET pathway component Get4/5 facilitates capture of tail-anchored proteins by Sgt2, which interacts with tail-anchors and hands them over to the targeting component Get3. Get4/5 binds directly and with high affinity to ribosomes, positions Sgt2 close to the ribosomal tunnel exit, and facilitates the capture of tail-anchored proteins by Sgt2. The contact sites of Get4/5 on the ribosome overlap with those of SRP, the factor mediating cotranslational ER-targeting. Exposure of internal transmembrane domains at the tunnel exit induces high-affinity ribosome binding of SRP, which in turn prevents ribosome binding of Get4/5. In this way, the position of a transmembrane domain within nascent ER-targeted proteins mediates partitioning into either the GET or SRP pathway directly at the ribosomal tunnel exit.

The guided entry of tail-anchored proteins (GET) pathway assists in the delivery of such proteins to the ER. Here, the authors reveal that the pathway components Get4/5 probe a region near the ribosomal exit tunnel. Upon emergence of a client protein, Get4/5 recruits Sgt2 and initiates the targeting phase of the pathway.

Questioning coverage values determined by 2D western blots: A critical study on the characterization of anti-HCP ELISA reagents

Host cell proteins (HCPs) constitute a major class of process-related impurities, whose substantial clearance must be demonstrated by suitable analytical methods to warrant product quality and reduce potential safety risks for patients. In this regard, enzyme linked immunosorbent assays (ELISAs), which primarily rely on the quality of the HCP reference standard (immunogen) and HCP-specific polyclonal antibodies, are considered the gold standard for HCP monitoring. For the qualification of the employed antibodies, two-dimensional (2D) western blots (2D-WBs) are the preferred technique to determine the coverage, though a number of practical constraints are well recognized. By using several orthogonal approaches, such as affinity-based mass spectrometry and indirect ELISA, the present study revealed potential detection gaps (i.e., noncovered HCPs) of conventional 2D-WBs, which can be primarily attributed to two different root causes: (i) low amounts of proteins or antibodies being unable to overcome the detection limit and (ii) western blot artifacts due to the loss of conformational epitopes through protein denaturation hindering HCP-antibody recognition. In contrast, the lack of specific antibodies against certain (particularly, low molecular weight) HCPs, as proposed in previous studies, seems to play only a minor role. Together, these findings imply that CHO-HCP ELISA antibodies are better than qualification studies by 2D-WBs indicate.

Mitochondrial Transfer by Human Mesenchymal Stromal Cells Ameliorates Hepatocyte Lipid Load in a Mouse Model of NASH

Mesenchymal stromal cell (MSC) transplantation ameliorated hepatic lipid load; tissue inflammation; and fibrosis in rodent animal models of non-alcoholic steatohepatitis (NASH) by as yet largely unknown mechanism(s). In a mouse model of NASH; we transplanted bone marrow-derived MSCs into the livers; which were analyzed one week thereafter. Combined metabolomic and proteomic data were applied to weighted gene correlation network analysis (WGCNA) and subsequent identification of key drivers. Livers were analyzed histologically and biochemically. The mechanisms of MSC action on hepatocyte lipid accumulation were studied in co-cultures of hepatocytes and MSCs by quantitative image analysis and immunocytochemistry. WGCNA and key driver analysis revealed that NASH caused the impairment of central carbon; amino acid; and lipid metabolism associated with mitochondrial and peroxisomal dysfunction; which was reversed by MSC treatment. MSC improved hepatic lipid metabolism and tissue homeostasis. In co-cultures of hepatocytes and MSCs; the decrease of lipid load was associated with the transfer of mitochondria from the MSCs to the hepatocytes via tunneling nanotubes (TNTs). Hence; MSCs may ameliorate lipid load and tissue perturbance by the donation of mitochondria to the hepatocytes. Thereby; they may provide oxidative capacity for lipid breakdown and thus promote recovery from NASH-induced metabolic impairment and tissue injury.

Stress response of Escherichia coli to essential oil components - insights on low-molecular-weight proteins from MALDI-TOF

The antibacterial effects of essential oils and their components (EOCs) are usually attributed to effects on membranes and metabolism. Studies of the effects of EOCs on protein expression have primarily analysed proteins larger than 10 kDa using gel electrophoresis. In the present study, we used MALDI-TOF-MS to investigate the effects of EOCs on low-molecular-weight proteins. From 297 m/z features, we identified 94 proteins with important differences in expression among untreated samples, samples treated with EOCs, and samples treated with antibiotics, peroxide, or chlorine. The targets of these treatments obviously differ, even among EOCs. In addition to ribosomal proteins, stress-, membrane- and biofilm-related proteins were affected. These findings may provide a basis for identifying new targets of essential oils and synergies with other antibiotics.

Proteomic Substrate Identification for Membrane Proteases in the Brain

Cell-cell communication in the brain is controlled by multiple mechanisms, including proteolysis. Membrane-bound proteases generate signaling molecules from membrane-bound precursor proteins and control the length and function of cell surface membrane proteins. These proteases belong to different families, including members of the “a disintegrin and metalloprotease” (ADAM), the beta-site amyloid precursor protein cleaving enzymes (BACE), membrane-type matrix metalloproteases (MT-MMP) and rhomboids. Some of these proteases, in particular ADAM10 and BACE1 have been shown to be essential not only for the correct development of the mammalian brain, but also for myelination and maintaining neuronal connections in the adult nervous system. Additionally, these proteases are considered as drug targets for brain diseases, including Alzheimer’s disease (AD), schizophrenia and cancer. Despite their biomedical relevance, the molecular functions of these proteases in the brain have not been explored in much detail, as little was known about their substrates. This has changed with the recent development of novel proteomic methods which allow to identify substrates of membrane-bound proteases from cultured cells, primary neurons and other primary brain cells and even in vivo from minute amounts of mouse cerebrospinal fluid (CSF). This review summarizes the recent advances and highlights the strengths of the individual proteomic methods. Finally, using the example of the Alzheimer-related proteases BACE1, ADAM10 and γ-secretase, as well as ADAM17 and signal peptide peptidase like 3 (SPPL3), we illustrate how substrate identification with novel methods is instrumental in elucidating broad physiological functions of these proteases in the brain and other organs.

Comparison and optimization of methods for the simultaneous extraction of DNA, RNA, proteins, and metabolites

The challenge of performing a time-resolved comprehensive analysis of molecular systems has led to the quest to optimize extraction methods. When the size of a biological sample is limited, there is demand for the simultaneous extraction of molecules representing the four areas of "omics": genomics, transcriptomics, proteomics, and metabolomics. Here we optimized a protocol for the simultaneous extraction of DNA, RNA, proteins, and metabolites and compared it with two existing protocols. Our optimization comprised the addition of a methanol/chloroform metabolite purification before the separation of DNA/RNA and proteins. Extracted DNA, RNA, proteins, and metabolites were quantitatively and/or qualitatively analyzed. Of the three methods, only the newly developed protocol yielded all biomolecule classes of adequate quantity and quality.

PIPINO: A Software Package to Facilitate the Identification of Protein-Protein Interactions from Affinity Purification Mass Spectrometry Data

The functionality of most proteins is regulated by protein-protein interactions. Hence, the comprehensive characterization of the interactome is the next milestone on the path to understand the biochemistry of the cell. A powerful method to detect protein-protein interactions is a combination of coimmunoprecipitation or affinity purification with quantitative mass spectrometry. Nevertheless, both methods tend to precipitate a high number of background proteins due to nonspecific interactions. To address this challenge the software Protein-Protein-Interaction-Optimizer (PIPINO) was developed to perform an automated data analysis, to facilitate the selection of bona fide binding partners, and to compare the dynamic of interaction networks. In this study we investigated the STAT1 interaction network and its activation dependent dynamics. Stable isotope labeling by amino acids in cell culture (SILAC) was applied to analyze the STAT1 interactome after streptavidin pull-down of biotagged STAT1 from human embryonic kidney 293T cells with and without activation. Starting from more than 2,000 captured proteins 30 potential STAT1 interaction partners were extracted. Interestingly, more than 50% of these were already reported or predicted to bind STAT1. Furthermore, 16 proteins were found to affect the binding behavior depending on STAT1 phosphorylation such as STAT3 or the importin subunits alpha 1 and alpha 6.

Osteoblast-released Matrix Vesicles, Regulation of Activity and Composition by Sulfated and Non-sulfated Glycosaminoglycans

Our aging population has to deal with the increasing threat of age-related diseases that impair bone healing. One promising therapeutic approach involves the coating of implants with modified glycosaminoglycans (GAGs) that mimic the native bone environment and actively facilitate skeletogenesis. In previous studies, we reported that coatings containing GAGs, such as hyaluronic acid (HA) and its synthetically sulfated derivative (sHA1) as well as the naturally low-sulfated GAG chondroitin sulfate (CS1), reduce the activity of bone-resorbing osteoclasts, but they also induce functions of the bone-forming cells, the osteoblasts. However, it remained open whether GAGs influence the osteoblasts alone or whether they also directly affect the formation, composition, activity, and distribution of osteoblast-released matrix vesicles (MV), which are supposed to be the active machinery for bone formation. Here, we studied the molecular effects of sHA1, HA, and CS1 on MV activity and on the distribution of marker proteins. Furthermore, we used comparative proteomic methods to study the relative protein compositions of isolated MVs and MV-releasing osteoblasts. The MV proteome is much more strongly regulated by GAGs than the cellular proteome. GAGs, especially sHA1, were found to severely impact vesicle-extracellular matrix interaction and matrix vesicle activity, leading to stronger extracellular matrix formation and mineralization. This study shows that the regulation of MV activity is one important mode of action of GAGs and provides information on underlying molecular mechanisms.

Comparative Life Cycle Transcriptomics Revises Leishmania mexicana Genome Annotation and Links a Chromosome Duplication with Parasitism of Vertebrates

Leishmania spp. are protozoan parasites that have two principal life cycle stages: the motile promastigote forms that live in the alimentary tract of the sandfly and the amastigote forms, which are adapted to survive and replicate in the harsh conditions of the phagolysosome of mammalian macrophages. Here, we used Illumina sequencing of poly-A selected RNA to characterise and compare the transcriptomes of L. mexicana promastigotes, axenic amastigotes and intracellular amastigotes. These data allowed the production of the first transcriptome evidence-based annotation of gene models for this species, including genome-wide mapping of trans-splice sites and poly-A addition sites. The revised genome annotation encompassed 9,169 protein-coding genes including 936 novel genes as well as modifications to previously existing gene models. Comparative analysis of gene expression across promastigote and amastigote forms revealed that 3,832 genes are differentially expressed between promastigotes and intracellular amastigotes. A large proportion of genes that were downregulated during differentiation to amastigotes were associated with the function of the motile flagellum. In contrast, those genes that were upregulated included cell surface proteins, transporters, peptidases and many uncharacterized genes, including 293 of the 936 novel genes. Genome-wide distribution analysis of the differentially expressed genes revealed that the tetraploid chromosome 30 is highly enriched for genes that were upregulated in amastigotes, providing the first evidence of a link between this whole chromosome duplication event and adaptation to the vertebrate host in this group. Peptide evidence for 42 proteins encoded by novel transcripts supports the idea of an as yet uncharacterised set of small proteins in Leishmania spp. with possible implications for host-pathogen interactions.

A novel bacterial Water Hypersensitivity-like protein shows in vivo protection against cold and freeze damage

Metagenomic library screening, by functional or sequence analysis, has become an established method for the identification of novel genes and gene products, including genetic elements implicated in microbial stress response and adaptation. We have identified, using a sequence-based approach, a fosmid clone from an Antarctic desert soil metagenome library containing a novel gene which codes for a protein homologous to a Water Hypersensitivity domain (WHy). The WHy domain is typically found as a component of specific LEA (Late Embryogenesis Abundant) proteins, particularly the LEA-14 (LEA-8) variants, which occur widely in plants, nematodes, bacteria and archaea and which are typically induced by exposure to stress conditions. The novel WHy-like protein (165 amino acid, 18.6 kDa) exhibits a largely invariant NPN motif at the N-terminus and has high sequence identity to genes identified in Pseudomonas genomes. Expression of this protein in Escherichia coli significantly protected the recombinant host against cold and freeze stress.

Pathway and time-resolved benzo[a]pyrene toxicity on Hepa1c1c7 cells at toxic and subtoxic exposure

Benzo[a]pyrene (B[a]P) is an environmental contaminant mainly studied for its toxic/carcinogenic effects. For a comprehensive and pathway orientated mechanistic understanding of the effects directly triggered by a toxic (5 μM) or a subtoxic (50 nM) concentration of B[a]P or indirectly by its metabolites, we conducted time series experiments for up to 24 h to study the effects in murine hepatocytes. These cells rapidly take up and actively metabolize B[a]P, which was followed by quantitative analysis of the concentration of intracellular B[a]P and seven representative degradation products. Exposure with 5 μM B[a]P led to a maximal intracellular concentration of 1604 pmol/5 × 10(4) cells, leveling at 55 pmol/5 × 10(4) cells by the end of the time course. Changes in the global proteome (>1000 protein profiles) and metabolome (163 metabolites) were assessed in combination with B[a]P degradation. Abundance profiles of 236 (both concentrations), 190 (only 5 μM), and 150 (only 50 nM) proteins were found to be regulated in response to B[a]P in a time-dependent manner. At the endogenous metabolite level amino acids, acylcarnitines and glycerophospholipids were particularly affected by B[a]P. The comprehensive chemical, proteome and metabolomic data enabled the identification of effects on the pathway level in a time-resolved manner. So in addition to known alterations, also protein synthesis, lipid metabolism, and membrane dysfunction were identified as B[a]P specific effects.

Species determination of Culicoides biting midges via peptide profiling using matrix-assisted laser desorption ionization mass spectrometry

Background

Culicoides biting midges are vectors of bluetongue and Schmallenberg viruses that inflict large-scale disease epidemics in ruminant livestock in Europe. Methods based on morphological characteristics and sequencing of genetic markers are most commonly employed to differentiate Culicoides to species level. Proteomic methods, however, are also increasingly being used as an alternative method of identification. These techniques have the potential to be rapid and may also offer advantages over DNA-based techniques. The aim of this proof-of-principle study was to develop a simple MALDI-MS based method to differentiate Culicoides from different species by peptide patterns with the additional option of identifying discriminating peptides.

Methods

Proteins extracted from 7 Culicoides species were digested and resulting peptides purified. Peptide mass fingerprint (PMF) spectra were recorded using matrix-assisted laser desorption/ionization time of flight mass spectrometry (MALDI-TOF-MS) and peak patterns analysed in R using the MALDIquant R package. Additionally, offline liquid chromatography (LC) MALDI-TOF tandem mass spectrometry (MS/MS) was applied to determine the identity of peptide peaks in one exemplary MALDI spectrum obtained using an unfractionated extract.

Results

We showed that the majority of Culicoides species yielded reproducible mass spectra with peak patterns that were suitable for classification. The dendrogram obtained by MS showed tentative similarities to a dendrogram generated from cytochrome oxidase I (COX1) sequences. Using offline LC-MALDI-TOF-MS/MS we determined the identity of 28 peptide peaks observed in one MALDI spectrum in a mass range from 1.1 to 3.1 kDa. All identified peptides were identical to other dipteran species and derived from one of five highly abundant proteins due to an absence of available Culicoides data.

Conclusion

Shotgun mass mapping by MALDI-TOF-MS has been shown to be compatible with morphological and genetic identification of specimens. Furthermore, the method performs at least as well as an alternative approach based on MS spectra of intact proteins, thus establishing the procedure as a method in its own right, with the additional option of concurrently using the same samples in other MS-based applications for protein identifications. The future availability of genomic information for different Culicoides species may enable a more stringent peptide detection based on Culicoides-specific sequence information.

Electronic supplementary material

The online version of this article (doi:10.1186/1756-3305-7-392) contains supplementary material, which is available to authorized users.

Proteomics and metabolomics for in situ monitoring of wound healing

Wound healing of soft tissue and bone defects is a complex process in which cellular differentiation and adaption are regulated by internal and external factors, among them are many different proteins. In contrast to insights into the significance of various single proteins based on model systems, the knowledge about the processes at the actual site of wound healing is still limited. This is caused by a general lack of methods that allow sampling of extracellular factors, metabolites, and proteins in situ. Sampling of wound fluids in combination with proteomics and metabolomics is one of the promising approaches to gain comprehensive and time resolved data on effector molecules. Here, we describe an approach to sample metabolites by microdialysis and to extract proteins simultaneously by adsorption. With this approach it is possible (i) to collect, enrich, and purify proteins for a comprehensive proteome analysis; (ii) to detect more than 600 proteins in different defects including more than 100 secreted proteins, of which many proteins have previously been demonstrated to have diagnostic or predictive power for the wound healing state; and (iii) to combine continuous sampling of cytokines and metabolites and discontinuous sampling of larger proteins to gain complementary information of the same defect.

Subtoxic and toxic concentrations of benzene and toluene induce Nrf2-mediated antioxidative stress response and affect the central carbon metabolism in lung epithelial cells A549

Since people in industrialized countries spend most of their time indoors, the effects of indoor contaminants such as volatile organic compounds become more and more relevant. Benzene and toluene are among the most abundant compounds in the highly heterogeneous group of indoor volatile organic compounds. In order to understand their effects on lung epithelial cells (A549) representing lung's first line of defense, we chose a global proteome and a targeted metabolome approach in order to detect adverse outcome pathways caused by exposure to benzene and toluene. Using a DIGE approach, 93 of 469 detected protein spots were found to be differentially expressed after exposure to benzene, and 79 of these spots were identified by MS. Pathway analysis revealed an enrichment of proteins involved in Nrf2-mediated and oxidative stress response glycolysis/gluconeogenesis. The occurrence of oxidative stress at nonacute toxic concentrations of benzene and toluene was confirmed by the upregulation of the stress related proteins NQO1 and SOD1. The changes in metabolism were validated by ion chromatography MS/MS analysis revealing significant changes of glucose-6-phosphate, fructose-6-phosphate, 3-phosphoglycerate, and NADPH. The molecular alterations identified as a result of benzene and toluene exposure demonstrate the detrimental effect of nonacute toxic concentrations on lung epithelial cells. The data provided here will allow for a targeted validation in in vivo models.

Analysis of the STAT3 interactome using in-situ biotinylation and SILAC

Signal transducer and activator of transcription 3 (STAT3) is activated by a variety of cytokines and growth factors. To generate a comprehensive data set of proteins interacting specifically with STAT3, we applied stable isotope labeling with amino acids in cell culture (SILAC). For high-affinity pull-down using streptavidin, we fused STAT3 with a short peptide tag allowing biotinylation in situ (bio-tag), which did not affect STAT3 functions. By this approach, 3642 coprecipitated proteins were detected in human embryonic kidney-293 cells. Filtering using statistical and functional criteria finally extracted 136 proteins as putative interaction partners of STAT3. Both, a physical interaction network analysis and the enrichment of known and predicted interaction partners suggested that our filtering criteria successfully enriched true STAT3 interactors. Our approach identified numerous novel interactors, including ones previously predicted to associate with STAT3. By reciprocal coprecipitation, we were able to verify the physical association between STAT3 and selected interactors, including the novel interaction with TOX4, a member of the TOX high mobility group box family. Applying the same method, we next investigated the activation-dependency of the STAT3 interactome. Again, we identified both known and novel interactions. Thus, our approach allows to study protein-protein interaction effectively and comprehensively.

BIOLOGICAL SIGNIFICANCE

The location, activity, function, degradation, and synthesis of proteins are significantly regulated by interactions of proteins with other proteins, biopolymers and small molecules. Thus, the comprehensive characterization of interactions of proteins in a given proteome is the next milestone on the path to understanding the biochemistry of the cell. In order to generate a comprehensive interactome dataset of proteins specifically interacting with a selected bait protein, we fused our bait protein STAT3 with a short peptide tag allowing biotinylation in situ (bio-tag). This bio-tag allows an affinity pull-down using streptavidin but affected neither the activation of STAT3 by tyrosine phosphorylation nor its transactivating potential. We combined SILAC for accurate relative protein quantification, subcellular fractionation to increase the coverage of interacting proteins, high-affinity pull-down and a stringent filtering method to successfully analyze the interactome of STAT3. With our approach we confirmed several already known and identified numerous novel STAT3 interactors. The approach applied provides a rapid and effective method, which is broadly applicable for studying protein-protein interactions and their dependency on post-translational modifications.

Identification of new protein coding sequences and signal peptidase cleavage sites of Helicobacter pylori strain 26695 by proteogenomics

Correct annotation of protein coding genes is the basis of conventional data analysis in proteomic studies. Nevertheless, most protein sequence databases almost exclusively rely on gene finding software and inevitably also miss protein annotations or possess errors. Proteogenomics tries to overcome these issues by matching MS data directly against a genome sequence database. Here we report an in-depth proteogenomics study of Helicobacter pylori strain 26695. MS data was searched against a combined database of the NCBI annotations and a six-frame translation of the genome. Database searches with Mascot and X! Tandem revealed 1115 proteins identified by at least two peptides with a peptide false discovery rate below 1%. This represents 71% of the predicted proteome. So far this is the most extensive proteome study of Helicobacter pylori. Our proteogenomic approach unambiguously identified four previously missed annotations and furthermore allowed us to correct sequences of six annotated proteins. Since secreted proteins are often involved in pathogenic processes we further investigated signal peptidase cleavage sites. By applying a database search that accommodates the identification of semi-specific cleaved peptides, 63 previously unknown signal peptides were detected. The motif LXA showed to be the predominant recognition sequence for signal peptidases.

BIOLOGICAL SIGNIFICANCE

The results of MS-based proteomic studies highly rely on correct annotation of protein coding genes which is the basis of conventional data analysis. However, the annotation of protein coding sequences in genomic data is usually based on gene finding software. These tools are limited in their prediction accuracy such as the problematic determination of exact gene boundaries. Thus, protein databases own partly erroneous or incomplete sequences. Additionally, some protein sequences might also be missing in the databases. Proteogenomics, a combination of proteomic and genomic data analyses, is well suited to detect previously not annotated proteins and to correct erroneous sequences. For this purpose, the existing database of the investigated species is typically supplemented with a six-frame translation of the genome. Here, we studied the proteome of the major human pathogen Helicobacter pylori that is responsible for many gastric diseases such as duodenal ulcers and gastric cancer. Our in-depth proteomic study highly reliably identified 1115 proteins (FDR<0.01%) by at least two peptides (FDR<1%) which represent 71% of the predicted proteome deposited at NCBI. The proteogenomic data analysis of our data set resulted in the unambiguous identification of four previously missed annotations, the correction of six annotated proteins as well as the detection of 63 previously unknown signal peptides. We have annotated proteins of particular biological interest like the ferrous iron transport protein A, the coiled-coil-rich protein HP0058 and the lipopolysaccharide biosynthesis protein HP0619. For instance, the protein HP0619 could be a drug target for the inhibition of the LPS synthesis pathway. Furthermore it has been proven that the motif "LXA" is the predominant recognition sequence for the signal peptidase I of H. pylori. Signal peptidases are essential enzymes for the viability of bacterial cells and are involved in pathogenesis. Therefore signal peptidases could be novel targets for antibiotics. The inclusion of the corrected and new annotated proteins as well as the information of signal peptide cleavage sites will help in the study of biological pathways involved in pathogenesis or drug response of H. pylori.

Quantitative proteomics reveals altered expression of extracellular matrix related proteins of human primary dermal fibroblasts in response to sulfated hyaluronan and collagen applied as artificial extracellular matrix

Fibroblasts are the main matrix producing cells of the dermis and are also strongly regulated by their matrix environment which can be used to improve and guide skin wound healing processes. Here, we systematically investigated the molecular effects on primary dermal fibroblasts in response to high-sulfated hyaluronan [HA] (hsHA) by quantitative proteomics. The comparison of non- and high-sulfated HA revealed regulation of 84 of more than 1,200 quantified proteins. Based on gene enrichment we found that sulfation of HA alters extracellular matrix remodeling. The collagen degrading enzymes cathepsin K, matrix metalloproteinases-2 and -14 were found to be down-regulated on hsHA. Additionally protein expression of thrombospondin-1, decorin, collagen types I and XII were reduced, whereas the expression of trophoblast glycoprotein and collagen type VI were slightly increased. This study demonstrates that global proteomics provides a valuable tool for revealing proteins involved in molecular effects of growth substrates for further material optimization.

Quantitative trait loci mapping of the mouse plasma proteome (pQTL)

A current challenge in the era of genome-wide studies is to determine the responsible genes and mechanisms underlying newly identified loci. Screening of the plasma proteome by high-throughput mass spectrometry (MALDI-TOF MS) is considered a promising approach for identification of metabolic and disease processes. Therefore, plasma proteome screening might be particularly useful for identifying responsible genes when combined with analysis of variation in the genome. Here, we describe a proteomic quantitative trait locus (pQTL) study of plasma proteome screens in an F(2) intercross of 455 mice mapped with 177 genetic markers across the genome. A total of 69 of 176 peptides revealed significant LOD scores (≥5.35) demonstrating strong genetic regulation of distinct components of the plasma proteome. Analyses were confirmed by mechanistic studies and MALDI-TOF/TOF, liquid chromatography-tandem mass spectrometry (LC-MS/MS) analyses of the two strongest pQTLs: A pQTL for mass-to-charge ratio (m/z) 3494 (LOD 24.9, D11Mit151) was identified as the N-terminal 35 amino acids of hemoglobin subunit A (Hba) and caused by genetic variation in Hba. Another pQTL for m/z 8713 (LOD 36.4; D1Mit111) was caused by variation in apolipoprotein A2 (Apoa2) and cosegregated with HDL cholesterol. Taken together, we show that genome-wide plasma proteome profiling in combination with genome-wide genetic screening aids in the identification of causal genetic variants affecting abundance of plasma proteins.

Quantitative proteomics reveals novel functions of osteoclast-associated receptor in STAT signaling and cell adhesion in human endothelial cells

Previous studies indicate a novel role for the osteoclast-associated receptor (OSCAR) in oxidative stress-mediated atherogenesis. However, the functional role of OSCAR in endothelial cells is unknown. Here we characterized OSCAR signaling in human endothelial cells using a proteomic approach. OSCAR was either overexpressed or silenced, and the functional effects were assessed by an in-depth proteomic study using stable isotope labeling with amino acids in cell culture (SILAC). Reduction of complexity using subcellular protein fractions from the membrane, the cytosol, and the nucleus of human endothelial cells enabled the detection of 4975 unique proteins. Of these proteins, OSCAR overexpression regulated 145 and OSCAR silencing regulated 110. These proteins were mainly involved in cellular proliferation, inflammatory response and cell-to-cell signaling. Interestingly, OSCAR modulation reciprocally regulated signal transducer and activator of transcription 1 (STAT1) and 3 (STAT3). Thus, STAT1 and several interferon-induced proteins showed a clear inverse correlation to OSCAR expression, which was further verified by Western blot analysis. In contrast, it was found that OSCAR overexpression activated STAT3. Furthermore, OSCAR overexpression increased proteins involved in cell adhesion, which correlated with an increased adhesion of monocytes to the endothelium after OSCAR overexpression. In conclusion, using a comprehensive proteomic approach, endothelial cell-derived OSCAR was found to be involved in the STAT signaling pathway and to affect monocyte adhesion. This indicates a novel role of OSCAR in the vascular-immune cross-talk.

Concentration-response concept in ecotoxicoproteomics: effects of different phenanthrene concentrations to the zebrafish (Danio rerio) embryo proteome

Concentration-response experiments, based on the testing of less replicates in favour of more exposure concentrations, represent the typical design of choice applied in toxicological and ecotoxicological effect assessment studies using traditional endpoints such as lethality. However, to our knowledge this concept has not found implementation in the increasingly applied OMICS techniques studying thousands of molecular endpoints at the same time. The present study is among the first applying the concentration-response concept for an ecotoxicoproteomics study. The effects of six different concentrations in the low effect range (<LC₂₀) of the PAH phenanthrene to the proteome of the ecotoxicological vertebrate model zebrafish (Danio rerio) embryo were investigated (two replicates per concentration) after 5 days exposure. Proteomics analyses were performed on organism extracts using 2-DE DIGE. Protein abundance profiles of around 713 protein spots were studied. About one-third of the protein signals could be detected to show robust reactions correlating with stressor concentration. Within this group, 65 protein signals showed significant changes compared to controls already at 1% lethal concentration (LC₀₁). Interestingly, 28 proteins significantly reacted at very low concentrations (<LC₀₁) and showed an exposure concentration dependent regulation status. Characteristic protein spots were identified by mass spectrometry. With the results of the present study the utility and several benefits using a concentration-response approach in proteomics studies could be shown. These included (i) knowledge about and the ability to model concentration dependent dynamics of molecular endpoints, (ii) to gain information about sensitivity of the molecular response in comparison to traditional endpoints and (iii) to help selecting the most promising protein spots for further investigations such as protein identification and biomarker studies. Using this experimental design based on testing of several exposure concentrations and less replicates might provide a step forward in getting increased output from toxicoproteomics studies.

Combined proteomic and metabolomic profiling of serum reveals association of the complement system with obesity and identifies novel markers of body fat mass changes

Obesity is associated with multiple adverse health effects and a high risk of developing metabolic and cardiovascular diseases. Therefore, there is a great need to identify circulating parameters that link changes in body fat mass with obesity. This study combines proteomic and metabolomic approaches to identify circulating molecules that discriminate healthy lean from healthy obese individuals in an exploratory study design. To correct for variations in physical activity, study participants performed a one hour exercise bout to exhaustion. Subsequently, circulating factors differing between lean and obese individuals, independent of physical activity, were identified. The DIGE approach yielded 126 differentially abundant spots representing 39 unique proteins. Differential abundance of proteins was confirmed by ELISA for antithrombin-III, clusterin, complement C3 and complement C3b, pigment epithelium-derived factor (PEDF), retinol binding protein 4 (RBP4), serum amyloid P (SAP), and vitamin-D binding protein (VDBP). Targeted serum metabolomics of 163 metabolites identified 12 metabolites significantly related to obesity. Among those, glycine (GLY), glutamine (GLN), and glycero-phosphatidylcholine 42:0 (PCaa 42:0) serum concentrations were higher, whereas PCaa 32:0, PCaa 32:1, and PCaa 40:5 were decreased in obese compared to lean individuals. The integrated bioinformatic evaluation of proteome and metabolome data yielded an improved group separation score of 2.65 in contrast to 2.02 and 2.16 for the single-type use of proteomic or metabolomics data, respectively. The identified circulating parameters were further investigated in an extended set of 30 volunteers and in the context of two intervention studies. Those included 14 obese patients who had undergone sleeve gastrectomy and 12 patients on a hypocaloric diet. For determining the long-term adaptation process the samples were taken six months after the treatment. In multivariate regression analyses, SAP, CLU, RBP4, PEDF, GLN, and C18:2 showed the strongest correlation to changes in body fat mass. The combined serum proteomic and metabolomic profiling reveals a link between the complement system and obesity and identifies both novel (C3b, CLU, VDBP, and all metabolites) and confirms previously discovered markers (PEDF, RBP4, C3, ATIII, and SAP) of body fat mass changes.

RNAcode: robust discrimination of coding and noncoding regions in comparative sequence data

With the availability of genome-wide transcription data and massive comparative sequencing, the discrimination of coding from noncoding RNAs and the assessment of coding potential in evolutionarily conserved regions arose as a core analysis task. Here we present RNAcode, a program to detect coding regions in multiple sequence alignments that is optimized for emerging applications not covered by current protein gene-finding software. Our algorithm combines information from nucleotide substitution and gap patterns in a unified framework and also deals with real-life issues such as alignment and sequencing errors. It uses an explicit statistical model with no machine learning component and can therefore be applied "out of the box," without any training, to data from all domains of life. We describe the RNAcode method and apply it in combination with mass spectrometry experiments to predict and confirm seven novel short peptides in Escherichia coli and to analyze the coding potential of RNAs previously annotated as "noncoding." RNAcode is open source software and available for all major platforms at http://wash.github.com/rnacode.