SearchGUI: An open-source graphical user interface for simultaneous OMSSA and X!Tandem searches

Discovering Novel Proteoforms Using Proteogenomic Workflows Within the Galaxy Bioinformatics Platform

Proteogenomics is a growing "multi-omics" research area that combines mass spectrometry-based proteomics and high-throughput nucleotide sequencing technologies. Proteogenomics has helped in genomic annotation for organisms whose complete genome sequences became available by using high-throughput DNA sequencing technologies. Apart from genome annotation, this multi-omics approach has also helped researchers confirm expression of variant proteins belonging to unique proteoforms that could have resulted from single-nucleotide polymorphism (SNP), insertion and deletions (Indels), splice isoforms, or other genome or transcriptome variations.A proteogenomic study depends on a multistep informatics workflow, requiring different software at each step. These integrated steps include creating an appropriate protein sequence database, matching spectral data against these sequences, and finally identifying peptide sequences corresponding to novel proteoforms followed by variant classification and functional analysis. The disparate software required for a proteogenomic study is difficult for most researchers to access and use, especially those lacking computational expertise. Furthermore, using them disjointedly can be error-prone as it requires setting up individual parameters for each software. Consequently, reproducibility suffers. Managing output files from each software is an additional challenge. One solution for these challenges in proteogenomics is the open-source Web-based computational platform Galaxy. Its capability to create and manage workflows comprised of disparate software while recording and saving all important parameters promotes both usability and reproducibility. Here, we describe a workflow that can perform proteogenomic analysis on a Galaxy-based platform. This Galaxy workflow facilitates matching of spectral data with a customized protein sequence database, identifying novel protein variants, assessing quality of results, and classifying variants along with visualization against the genome.

Proteomics Can Rise to the Challenge of Pseudogenes' Coding Nature

Throughout the past decade, technological advances in genomics and transcriptomics have revealed pervasive translation throughout mammalian genomes. These putative proteins are usually excluded from proteomics analyses, as they are absent from common protein repositories. A sizable portion of these noncanonical proteins is translated from pseudogenes. Pseudogenes are commonly termed defective copies of coding genes unable to produce proteins. Here, we suggest that proteomics can help in their annotation. First, we define important terms and review specific examples underlining the caveats in pseudogene annotation and their coding potential. Then, we will discuss the challenges inherent to pseudogenes that have thus far rendered complex their confidence in omics data. Finally, we identify recent developments in experimental procedures, instrumentation, and computational methods in proteomics that put the field in a unique position to solve the pseudogene annotation conundrum.

Dysregulation of FLVCR1a-dependent mitochondrial calcium handling in neural progenitors causes congenital hydrocephalus

Congenital hydrocephalus (CH), occurring in approximately 1/1,000 live births, represents an important clinical challenge due to the limited knowledge of underlying molecular mechanisms. The discovery of novel CH genes is thus essential to shed light on the intricate processes responsible for ventricular dilatation in CH. Here, we identify FLVCR1 (feline leukemia virus subgroup C receptor 1) as a gene responsible for a severe form of CH in humans and mice. Mechanistically, our data reveal that the full-length isoform encoded by the FLVCR1 gene, FLVCR1a, interacts with the IP3R3-VDAC complex located on mitochondria-associated membranes (MAMs) that controls mitochondrial calcium handling. Loss of Flvcr1a in mouse neural progenitor cells (NPCs) affects mitochondrial calcium levels and energy metabolism, leading to defective cortical neurogenesis and brain ventricle enlargement. These data point to defective NPCs calcium handling and metabolic activity as one of the pathogenetic mechanisms driving CH.

Soil Metaproteomics for Microbial Community Profiling: Methodologies and Challenges

Soil represents a complex and dynamic ecosystem, hosting a myriad of microorganisms that coexist and play vital roles in nutrient cycling and organic matter transformation. Among these microorganisms, bacteria and fungi are key members of the microbial community, profoundly influencing the fate of nitrogen, sulfur, and carbon in terrestrial environments. Understanding the intricacies of soil ecosystems and the biological processes orchestrated by microbial communities necessitates a deep dive into their composition and metabolic activities. The advent of next-generation sequencing and 'omics' techniques, such as metagenomics and metaproteomics, has revolutionized our understanding of microbial ecology and the functional dynamics of soil microbial communities. Metagenomics enables the identification of microbial community composition in soil, while metaproteomics sheds light on the current biological functions performed by these communities. However, metaproteomics presents several challenges, both technical and computational. Factors such as the presence of humic acids and variations in extraction methods can influence protein yield, while the absence of high-resolution mass spectrometry and comprehensive protein databases limits the depth of protein identification. Notwithstanding these limitations, metaproteomics remains a potent tool for unraveling the intricate biological processes and functions of soil microbial communities. In this review, we delve into the methodologies and challenges of metaproteomics in soil research, covering aspects such as protein extraction, identification, and bioinformatics analysis. Furthermore, we explore the applications of metaproteomics in soil bioremediation, highlighting its potential in addressing environmental challenges.

A novel clinical metaproteomics workflow enables bioinformatic analysis of host-microbe dynamics in disease

Clinical metaproteomics has the potential to offer insights into the host-microbiome interactions underlying diseases. However, the field faces challenges in characterizing microbial proteins found in clinical samples, usually present at low abundance relative to the host proteins. As a solution, we have developed an integrated workflow coupling mass spectrometry-based analysis with customized bioinformatic identification, quantification, and prioritization of microbial proteins, enabling targeted assay development to investigate host-microbe dynamics in disease. The bioinformatics tools are implemented in the Galaxy ecosystem, offering the development and dissemination of complex bioinformatic workflows. The modular workflow integrates MetaNovo (to generate a reduced protein database), SearchGUI/PeptideShaker and MaxQuant [to generate peptide-spectral matches (PSMs) and quantification], PepQuery2 (to verify the quality of PSMs), Unipept (for taxonomic and functional annotation), and MSstatsTMT (for statistical analysis). We have utilized this workflow in diverse clinical samples, from the characterization of nasopharyngeal swab samples to bronchoalveolar lavage fluid. Here, we demonstrate its effectiveness via analysis of residual fluid from cervical swabs. The complete workflow, including training data and documentation, is available via the Galaxy Training Network, empowering non-expert researchers to utilize these powerful tools in their clinical studies.

IMPORTANCE

Clinical metaproteomics has immense potential to offer functional insights into the microbiome and its contributions to human disease. However, there are numerous challenges in the metaproteomic analysis of clinical samples, including handling of very large protein sequence databases for sensitive and accurate peptide and protein identification from mass spectrometry data, as well as taxonomic and functional annotation of quantified peptides and proteins to enable interpretation of results. To address these challenges, we have developed a novel clinical metaproteomics workflow that provides customized bioinformatic identification, verification, quantification, and taxonomic and functional annotation. This bioinformatic workflow is implemented in the Galaxy ecosystem and has been used to characterize diverse clinical sample types, such as nasopharyngeal swabs and bronchoalveolar lavage fluid. Here, we demonstrate its effectiveness and availability for use by the research community via analysis of residual fluid from cervical swabs.

A Comprehensive Understanding of Post-Translational Modification of Sox2 via Acetylation and O-GlcNAcylation in Colorectal Cancer

Aberrant expression of the pluripotency-associated transcription factor Sox2 is associated with poor prognosis in colorectal cancer (CRC). We investigated the regulatory roles of major post-translational modifications in Sox2 using two CRC cell lines, SW480 and SW620, derived from the same patient but with low and high Sox2 expression, respectively. Acetylation of K75 in the Sox2 nuclear export signal was relatively increased in SW480 cells and promotes Sox2 nucleocytoplasmic shuttling and proteasomal degradation of Sox2. LC-MS-based proteomics analysis identified HDAC4 and p300 as binding partners involved in the acetylation-mediated control of Sox2 expression in the nucleus. Sox2 K75 acetylation is mediated by the acetyltransferase activity of CBP/p300 and ACSS3. In SW620 cells, HDAC4 deacetylates K75 and is regulated by miR29a. O-GlcNAcylation on S246, in addition to K75 acetylation, also regulates Sox2 stability. These findings provide insights into the regulation of Sox2 through multiple post-translational modifications and pathways in CRC.

Identification of protein components of the transformation system in the cell line of immortalized human keratinocytes HaCaT exposed to surfactants

Using the method of shotgun mass spectrometry, we have evaluated changes in the proteomic profile of HaCat cells in response to the treatment with sodium dodecyl sulfate (anionic surfactant) and Triton-X100 (non-ionic surfactant) in two concentrations (12.5 µg/ml and 25.0 µg/ml). The study revealed induction of orphan CYP2S1 (biotransformation phase I) in response to Triton-X100. We have identified proteins of II (glutathione-S-transferases, GSTs) and III (solute carrier proteins, SLCs) biotransformation phases, as well as antioxidant proteins (peroxiredoxins, PRDXs; catalase, CAT; thioredoxin, TXN). Thus, proteins of all three xenobiotic detoxification phases were detected. The presented results suggest a new prospect of using HaCaT keratinocytes as a model of human epidermis for studying the metabolism of drugs/toxicants in human skin in vitro.

Interaction of Whitefly Effector G4 with Tomato Proteins Impacts Whitefly Performance

The phloem-feeding insect Bemisia tabaci is an important pest, responsible for the transmission of several crop-threatening virus species. While feeding, the insect secretes a cocktail of effectors to modulate plant defense responses. Here, we present a set of proteins identified in an artificial diet on which B. tabaci was salivating. We subsequently studied whether these candidate effectors can play a role in plant immune suppression. Effector G4 was the most robust suppressor of an induced- reactive oxygen species (ROS) response in Nicotiana benthamiana. In addition, G4 was able to suppress ROS production in Solanum lycopersicum (tomato) and Capsicum annuum (pepper). G4 localized predominantly in the endoplasmic reticulum in N. benthamiana leaves and colocalized with two identified target proteins in tomato: REF-like stress related protein 1 (RSP1) and meloidogyne-induced giant cell protein DB141 (MIPDB141). Silencing of MIPDB141 in tomato reduced whitefly fecundity up to 40%, demonstrating that the protein is involved in susceptibility to B. tabaci. Together, our data demonstrate that effector G4 impairs tomato immunity to whiteflies by interfering with ROS production and via an interaction with tomato susceptibility protein MIPDB141. [Formula: see text] Copyright © 2024 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license.

VEuPathDB: the eukaryotic pathogen, vector and host bioinformatics resource center in 2023

The Eukaryotic Pathogen, Vector and Host Informatics Resource (VEuPathDB, https://veupathdb.org) is a Bioinformatics Resource Center funded by the National Institutes of Health with additional funding from the Wellcome Trust. VEuPathDB supports >600 organisms that comprise invertebrate vectors, eukaryotic pathogens (protists and fungi) and relevant free-living or non-pathogenic species or hosts. Since 2004, VEuPathDB has analyzed omics data from the public domain using contemporary bioinformatic workflows, including orthology predictions via OrthoMCL, and integrated the analysis results with analysis tools, visualizations, and advanced search capabilities. The unique data mining platform coupled with >3000 pre-analyzed data sets facilitates the exploration of pertinent omics data in support of hypothesis driven research. Comparisons are easily made across data sets, data types and organisms. A Galaxy workspace offers the opportunity for the analysis of private large-scale datasets and for porting to VEuPathDB for comparisons with integrated data. The MapVEu tool provides a platform for exploration of spatially resolved data such as vector surveillance and insecticide resistance monitoring. To address the growing body of omics data and advances in laboratory techniques, VEuPathDB has added several new data types, searches and features, improved the Galaxy workspace environment, redesigned the MapVEu interface and updated the infrastructure to accommodate these changes.

Bioinformatic Workflows for Metaproteomics

The strong influence of microbiomes on areas such as ecology and human health has become widely recognized in the past years. Accordingly, various techniques for the investigation of the composition and function of microbial community samples have been developed. Metaproteomics, the comprehensive analysis of the proteins from microbial communities, allows for the investigation of not only the taxonomy but also the functional and quantitative composition of microbiome samples. Due to the complexity of the investigated communities, methods developed for single organism proteomics cannot be readily applied to metaproteomic samples. For this purpose, methods specifically tailored to metaproteomics are required. In this work, a detailed overview of current bioinformatic solutions and protocols in metaproteomics is given. After an introduction to the proteomic database search, the metaproteomic post-processing steps are explained in detail. Ten specific bioinformatic software solutions are focused on, covering various steps including database-driven identification and quantification as well as taxonomic and functional assignment.

The Application of Ejaculate-Based Shotgun Proteomics for Male Infertility Screening

Problems with the male reproductive system are of both medical and social significance. As a rule, spermatozoa and seminal plasma proteomes are investigated separately to assess sperm quality. The current study aimed to compare ejaculate proteomes with spermatozoa and seminal plasma protein profiles regarding the identification of proteins related to fertility scores. A total of 1779, 715, and 2163 proteins were identified in the ejaculate, seminal plasma, and spermatozoa, respectively. Among these datasets, 472 proteins were shared. GO enrichment analysis of the common proteins enabled us to distinguish biological processes such as single fertilization (GO:0007338), spermatid development (GO:0007286), and cell motility (GO:0048870). Among the abundant terms for GO cellular components, zona pellucida receptor complex, sperm fibrous sheath, and outer dense fiber were revealed. Overall, we identified 139 testis-specific proteins. For these proteins, PPI networks that are common in ejaculate, spermatozoa, and seminal plasma were related to the following GO biological processes: cilium movement (GO:0003341), microtubule-based movement (GO:0007018), and sperm motility (GO:0097722). For ejaculate and spermatozoa, they shared 15 common testis-specific proteins with spermatogenesis (GO:0007283) and male gamete generation (GO:0048232). Therefore, we speculated that ejaculate-based proteomics could yield new insights into the peculiar reproductive physiology and spermatozoa function of men and potentially serve as an explanation for male infertility screening.

A novel clinical metaproteomics workflow enables bioinformatic analysis of host-microbe dynamics in disease

Clinical metaproteomics has the potential to offer insights into the host-microbiome interactions underlying diseases. However, the field faces challenges in characterizing microbial proteins found in clinical samples, which are usually present at low abundance relative to the host proteins. As a solution, we have developed an integrated workflow coupling mass spectrometry-based analysis with customized bioinformatic identification, quantification and prioritization of microbial and host proteins, enabling targeted assay development to investigate host-microbe dynamics in disease. The bioinformatics tools are implemented in the Galaxy ecosystem, offering the development and dissemination of complex bioinformatic workflows. The modular workflow integrates MetaNovo (to generate a reduced protein database), SearchGUI/PeptideShaker and MaxQuant (to generate peptide-spectral matches (PSMs) and quantification), PepQuery2 (to verify the quality of PSMs), and Unipept and MSstatsTMT (for taxonomy and functional annotation). We have utilized this workflow in diverse clinical samples, from the characterization of nasopharyngeal swab samples to bronchoalveolar lavage fluid. Here, we demonstrate its effectiveness via analysis of residual fluid from cervical swabs. The complete workflow, including training data and documentation, is available via the Galaxy Training Network, empowering non-expert researchers to utilize these powerful tools in their clinical studies.

Start codon-associated ribosomal frameshifting mediates nutrient stress adaptation

A translating ribosome is typically thought to follow the reading frame defined by the selected start codon. Using super-resolution ribosome profiling, here we report pervasive out-of-frame translation immediately from the start codon. Start codon-associated ribosomal frameshifting (SCARF) stems from the slippage of ribosomes during the transition from initiation to elongation. Using a massively paralleled reporter assay, we uncovered sequence elements acting as SCARF enhancers or repressors, implying that start codon recognition is coupled with reading frame fidelity. This finding explains thousands of mass spectrometry spectra that are unannotated in the human proteome. Mechanistically, we find that the eukaryotic initiation factor 5B (eIF5B) maintains the reading frame fidelity by stabilizing initiating ribosomes. Intriguingly, amino acid starvation induces SCARF by proteasomal degradation of eIF5B. The stress-induced SCARF protects cells from starvation by enabling amino acid recycling and selective mRNA translation. Our findings illustrate a beneficial effect of translational 'noise' in nutrient stress adaptation.

Similar proteome expression profiles of the aggregated lymphoid nodules area and Peyer's patches in Bactrian camel

BACKGROUND

The presence of Aggregated Lymphoid Nodules Area (ALNA) is a notable anatomical characteristic observed in the abomasum of Bactrian camels. This area is comprised of two separate regions, namely the Reticular Mucosal Folds Region (RMFR) and the Longitudinal Mucosal Folds Region (LMFR). The histological properties of ALNA exhibit significant similarities to those of Peyer's patches (PPs) found in the gastrointestinal system. The functional characteristics of ALNA were examined in relation to mucosal immunity in the gastrointestinal system.

RESULTS

We used iTRAQ-based proteomic analysis on twelve Bactrian camels to measure the amount of proteins expressed in ALNA. In the experiment, we sampled the RMFR and LMFR separately from the ALNA and compared their proteomic quantification results with samples from the PPs. A total of 1253 proteins were identified, among which 39 differentially expressed proteins (DEPs) were found between RMFR and PPs, 33 DEPs were found between LMFR and PPs, and 22 DEPs were found between LMFR and RMFR. The proteins FLNA, MYH11, and HSPB1 were chosen for validation using the enzyme-linked immunosorbent assay (ELISA), and the observed expression profiles were found to be in agreement with the results obtained from the iTRAQ study. The InnateDB database was utilized to get data pertaining to immune-associated proteins in ALNA. It was observed that a significant proportion, specifically 76.6%, of these proteins were found to be associated with the same orthogroups as human immune-related genes. These proteins are acknowledged to be associated with a diverse range of functions, encompassing the uptake, processing and presentation of antigens, activation of lymphocytes, the signaling pathways of T-cell and B-cell receptors, and the control of actin polymerization.

CONCLUSIONS

The experimental results suggest that there are parallels in the immune-related proteins found in ALNA and PPs. Although there are variations in the structures of LMFR and RMFR, the proteins produced in both structures exhibit a high degree of similarity and perform comparable functions in the context of mucosal immune responses.

IQMMA: Efficient MS1 Intensity Extraction Pipeline Using Multiple Feature Detection Algorithms for DDA Proteomics

One of the key steps in data dependent acquisition (DDA) proteomics is detection of peptide isotopic clusters, also called "features", in MS1 spectra and matching them to MS/MS-based peptide identifications. A number of peptide feature detection tools became available in recent years, each relying on its own matching algorithm. Here, we provide an integrated solution, the intensity-based Quantitative Mix and Match Approach (IQMMA), which integrates a number of untargeted peptide feature detection algorithms and returns the most probable intensity values for the MS/MS-based identifications. IQMMA was tested using available proteomic data acquired for both well-characterized (ground truth) and real-world biological samples, including a mix of Yeast and E. coli digests spiked at different concentrations into the Human K562 digest used as a background, and a set of glioblastoma cell lines. Three open-source feature detection algorithms were integrated: Dinosaur, biosaur2, and OpenMS FeatureFinder. None of them was found optimal when applied individually to all the data sets employed in this work; however, their combined use in IQMMA improved efficiency of subsequent protein quantitation. The software implementing IQMMA is freely available at https://github.com/PostoenkoVI/IQMMA under Apache 2.0 license.

ERFVII action and modulation through oxygen-sensing in Arabidopsis thaliana

Oxygen is a key signalling component of plant biology, and whilst an oxygen-sensing mechanism was previously described in Arabidopsis thaliana, key features of the associated PLANT CYSTEINE OXIDASE (PCO) N-degron pathway and Group VII ETHYLENE RESPONSE FACTOR (ERFVII) transcription factor substrates remain untested or unknown. We demonstrate that ERFVIIs show non-autonomous activation of root hypoxia tolerance and are essential for root development and survival under oxygen limiting conditions in soil. We determine the combined effects of ERFVIIs in controlling gene expression and define genetic and environmental components required for proteasome-dependent oxygen-regulated stability of ERFVIIs through the PCO N-degron pathway. Using a plant extract, unexpected amino-terminal cysteine sulphonic acid oxidation level of ERFVIIs was observed, suggesting a requirement for additional enzymatic activity within the pathway. Our results provide a holistic understanding of the properties, functions and readouts of this oxygen-sensing mechanism defined through its role in modulating ERFVII stability.

Interruption of p53-MDM2 Interaction by Nutlin-3a in Human Lymphoma Cell Models Initiates a Cell-Dependent Global Effect on Transcriptome and Proteome Level

In most lymphomas, p53 signaling pathway is inactivated by various mechanisms independent to p53 gene mutations or deletions. In many cases, p53 function is largely regulated by alterations in the protein abundance levels by the action of E3 ubiquitin-protein ligase MDM2, targeting p53 to proteasome-mediated degradation. In the present study, an integrating transcriptomics and proteomics analysis was employed to investigate the effect of p53 activation by a small-molecule MDM2-antagonist, nutlin-3a, on three lymphoma cell models following p53 activation. Our analysis revealed a system-wide nutlin-3a-associated effect in all examined lymphoma types, identifying in total of 4037 differentially affected proteins involved in a plethora of pathways, with significant heterogeneity among lymphomas. Our findings include known p53-targets and novel p53 activation effects, involving transcription, translation, or degradation of protein components of pathways, such as a decrease in key members of PI3K/mTOR pathway, heat-shock response, and glycolysis, and an increase in key members of oxidative phoshosphorylation, autophagy and mitochondrial translation. Combined inhibition of HSP90 or PI3K/mTOR pathway with nutlin-3a-mediated p53-activation enhanced the apoptotic effects suggesting a promising strategy against human lymphomas. Integrated omic profiling after p53 activation offered novel insights on the regulatory role specific proteins and pathways may have in lymphomagenesis.

Small extracellular vesicles but not microvesicles from Opisthorchis viverrini promote cell proliferation in human cholangiocytes

Chronic infection with O. viverrini has been linked to the development of cholangiocarcinoma (CCA), which is a major public health burden in the Lower Mekong River Basin countries, including Thailand, Lao PDR, Vietnam and Cambodia. Despite its importance, the exact mechanisms by which O. viverrini promotes CCA are largely unknown. In this study, we characterized different extracellular vesicle populations released by O. viverrini (OvEVs) using proteomic and transcriptomic analyses and investigated their potential role in host-parasite interactions. While 120k OvEVs promoted cell proliferation in H69 cells at different concentrations, 15k OvEVs did not produce any effect compared to controls. The proteomic analysis of both populations showed differences in their composition that could contribute to this differential effect. Furthermore, the miRNAs present in 120k EVs were analysed and their potential interactions with human host genes was explored by computational target prediction. Different pathways involved in inflammation, immune response and apoptosis were identified as potentially targeted by the miRNAs present in this population of EVs. This is the first study showing specific roles for different EV populations in the pathogenesis of a parasitic helminth, and more importantly, an important advance towards deciphering the mechanisms used in establishment of opisthorchiasis and liver fluke infection-associated malignancy.

Comparison of SPEED, S-Trap, and In-Solution-Based Sample Preparation Methods for Mass Spectrometry in Kidney Tissue and Plasma

Mass spectrometry is a powerful technique for investigating renal pathologies and identifying biomarkers, and efficient protein extraction from kidney tissue is essential for bottom-up proteomic analyses. Detergent-based strategies aid cell lysis and protein solubilization but are poorly compatible with downstream protein digestion and liquid chromatography-coupled mass spectrometry, requiring additional purification and buffer-exchange steps. This study compares two well-established detergent-based methods for protein extraction (in-solution sodium deoxycholate (SDC); suspension trapping (S-Trap)) with the recently developed sample preparation by easy extraction and digestion (SPEED) method, which uses strong acid for denaturation. We compared the quantitative performance of each method using label-free mass spectrometry in both sheep kidney cortical tissue and plasma. In kidney tissue, SPEED quantified the most unique proteins (SPEED 1250; S-Trap 1202; SDC 1197). In plasma, S-Trap produced the most unique protein quantifications (S-Trap 150; SDC 148; SPEED 137). Protein quantifications were reproducible across biological replicates in both tissue (R2 = 0.85–0.90) and plasma (SPEED R2 = 0.84; SDC R2 = 0.76, S-Trap R2 = 0.65). Our data suggest SPEED as the optimal method for proteomic preparation in kidney tissue and S-Trap or SPEED as the optimal method for plasma, depending on whether a higher number of protein quantifications or greater reproducibility is desired.

Start codon-associated ribosomal frameshifting mediates nutrient stress adaptation

A translating ribosome is typically thought to follow the reading frame defined by the selected start codon. Using super-resolution ribosome profiling, here we report pervasive out-of-frame translation immediately from the start codon. The start codon-associated ribosome frameshifting (SCARF) stems from the slippage of ribosomes during the transition from initiation to elongation. Using a massively paralleled reporter assay, we uncovered sequence elements acting as SCARF enhancers or repressors, implying that start codon recognition is coupled with reading frame fidelity. This finding explains thousands of mass spectrometry spectra unannotated from human proteome. Mechanistically, we find that the eukaryotic initiation factor 5B (eIF5B) maintains the reading frame fidelity by stabilizing initiating ribosomes. Intriguingly, amino acid starvation induces SCARF by proteasomal degradation of eIF5B. The stress-induced SCARF protects cells from starvation by enabling amino acid recycling and selective mRNA translation. Our findings illustrate a beneficial effect of translational "noise" in nutrient stress adaptation.

MetaLab-MAG: A Metaproteomic Data Analysis Platform for Genome-Level Characterization of Microbiomes from the Metagenome-Assembled Genomes Database

The studies of microbial communities have drawn increased attention in various research fields such as agriculture, environment, and human health. Recently, metaproteomics has become a powerful tool to interpret the roles of the community members by investigating the expressed proteins of the microbes. However, analyzing the metaproteomic data sets at genome resolution is still challenging because of the lack of efficient bioinformatics tools. Here we develop MetaLab-MAG, a specially designed tool for the characterization of microbiomes from metagenome-assembled genomes databases. MetaLab-MAG was evaluated by analyzing various human gut microbiota data sets and performed comparably or better than searching the gene catalog protein database directly. MetaLab-MAG can quantify the genome-level microbiota compositions and supports both label-free and isobaric labeling-based quantification strategies. MetaLab-MAG removes the obstacles of metaproteomic data analysis and provides the researchers with in-depth and comprehensive information from the microbiomes.

Finding haplotypic signatures in proteins

BACKGROUND

The nonrandom distribution of alleles of common genomic variants produces haplotypes, which are fundamental in medical and population genetic studies. Consequently, protein-coding genes with different co-occurring sets of alleles can encode different amino acid sequences: protein haplotypes. These protein haplotypes are present in biological samples and detectable by mass spectrometry, but they are not accounted for in proteomic searches. Consequently, the impact of haplotypic variation on the results of proteomic searches and the discoverability of peptides specific to haplotypes remain unknown.

FINDINGS

Here, we study how common genetic haplotypes influence the proteomic search space and investigate the possibility to match peptides containing multiple amino acid substitutions to a publicly available data set of mass spectra. We found that for 12.42% of the discoverable amino acid substitutions encoded by common haplotypes, 2 or more substitutions may co-occur in the same peptide after tryptic digestion of the protein haplotypes. We identified 352 spectra that matched to such multivariant peptides, and out of the 4,582 amino acid substitutions identified, 6.37% were covered by multivariant peptides. However, the evaluation of the reliability of these matches remains challenging, suggesting that refined error rate estimation procedures are needed for such complex proteomic searches.

CONCLUSIONS

As these procedures become available and the ability to analyze protein haplotypes increases, we anticipate that proteomics will provide new information on the consequences of common variation, across tissues and time.

Analysis of Golgi Protein Acetylation Using In Vitro Assays and Parallel Reaction Monitoring Mass Spectrometry

Acetylation is one of the most abundant post-translational protein modifications that regulates all cellular compartments ranging from chromatin to cytoskeleton and Golgi. The dynamic acetylation of the Golgi stacking protein GRASP55 was shown to regulate Golgi reassembly after mitosis. Here we provide a detailed protocol for the analysis of Golgi acetylation including in vitro assays to detect protein acetylation and mass spectrometry analysis to identify specific acetylation sites and their relative abundance.

Comparative proteoinformatics revealed the essentials of SDS impact on HaCaT keratinocytes

There is no direct evidence supporting that SDS is a carcinogen, so to investigate this fact, we used HaCaT keratinocytes as a model of human epidermal cells. To reveal the candidate proteins and/or pathways characterizing the SDS impact on HaCaT, we proposed comparative proteoinformatics pipeline. For protein extraction, the performance of two sample preparation protocols was assessed: 0.2% SDS-based solubilization combined with the 1DE-gel concentration (Protocol 1) and osmotic shock (Protocol 2). As a result, in SDS-exposed HaCaT cells, Protocol 1 revealed 54 differentially expressed proteins (DEPs) involved in the disease of cellular proliferation (DOID:14566), whereas Protocol 2 found 45 DEPs of the same disease ID. The 'skin cancer' term was a single significant COSMIC term for Protocol 1 DEPs, including those involved in double-strand break repair pathway (BIR, GO:0000727). Considerable upregulation of BIR-associated proteins MCM3, MCM6, and MCM7 was detected. The eightfold increase in MCM6 level was verified by reverse transcription qPCR. Thus, Protocol 1 demonstrated high effectiveness in terms of the total number and sensitivity of MS identifications in HaCaT cell line proteomic analysis. The utility of Protocol 1 was confirmed by the revealed upregulation of cancer-associated MCM6 in HaCaT keratinocytes induced by non-toxic concentration of SDS. Data are available via ProteomeXchange with identifier PXD035202.

FYCO1 Increase and Effect of Arimoclomol-Treatment in Human VCP-Pathology

Dominant VCP–mutations cause a variety of neurological manifestations including inclusion body myopathy with early–onset Paget disease and frontotemporal dementia 1 (IBMPFD). VCP encodes a ubiquitously expressed multifunctional protein that is a member of the AAA+ protein family, implicated in multiple cellular functions ranging from organelle biogenesis to ubiquitin–dependent protein degradation. The latter function accords with the presence of protein aggregates in muscle biopsy specimens derived from VCP–patients. Studying the proteomic signature of VCP–mutant fibroblasts, we identified a (pathophysiological) increase of FYCO1, a protein involved in autophagosome transport. We confirmed this finding applying immunostaining also in muscle biopsies derived from VCP–patients. Treatment of fibroblasts with arimoclomol, an orphan drug thought to restore physiologic cellular protein repair pathways, ameliorated cellular cytotoxicity in VCP–patient derived cells. This finding was accompanied by increased abundance of proteins involved in immune response with a direct impact on protein clearaqnce as well as by elevation of pro–survival proteins as unravelled by untargeted proteomic profiling. Hence, the combined results of our study reveal a dysregulation of FYCO1 in the context of VCP–etiopathology, highlight arimoclomol as a potential drug and introduce proteins targeted by the pre–clinical testing of this drug in fibroblasts.

Quantitative proteomics of small numbers of closely-related cells: Selection of the optimal method for a clinical setting

Mass spectrometry (MS)-based proteomics profiling has undoubtedly increased the knowledge about cellular processes and functions. However, its applicability for paucicellular sample analyses is currently limited. Although new approaches have been developed for single-cell studies, most of them have not (yet) been standardized and/or require highly specific (often home-built) devices, thereby limiting their broad implementation, particularly in non-specialized settings. To select an optimal MS-oriented proteomics approach applicable in translational research and clinical settings, we assessed 10 different sample preparation procedures in paucicellular samples of closely-related cell types. Particularly, five cell lysis protocols using different chemistries and mechanical forces were combined with two sample clean-up techniques (C18 filter- and SP3-based), followed by tandem mass tag (TMT)-based protein quantification. The evaluation was structured in three phases: first, cell lines from hematopoietic (THP-1) and non-hematopoietic (HT-29) origins were used to test the approaches showing the combination of a urea-based lysis buffer with the SP3 bead-based clean-up system as the best performer. Parameters such as reproducibility, accessibility, spatial distribution, ease of use, processing time and cost were considered. In the second phase, the performance of the method was tested on maturation-related cell populations: three different monocyte subsets from peripheral blood and, for the first time, macrophages/microglia (MAC) from glioblastoma samples, together with T cells from both tissues. The analysis of 50,000 cells down to only 2,500 cells revealed different protein expression profiles associated with the distinct cell populations. Accordingly, a closer relationship was observed between non-classical monocytes and MAC, with the latter showing the co-expression of M1 and M2 macrophage markers, although pro-tumoral and anti-inflammatory proteins were more represented. In the third phase, the results were validated by high-end spectral flow cytometry on paired monocyte/MAC samples to further determine the sensitivity of the MS approach selected. Finally, the feasibility of the method was proven in 194 additional samples corresponding to 38 different cell types, including cells from different tissue origins, cellular lineages, maturation stages and stimuli. In summary, we selected a reproducible, easy-to-implement sample preparation method for MS-based proteomic characterization of paucicellular samples, also applicable in the setting of functionally closely-related cell populations.

Construction of 2DE Patterns of Plasma Proteins: Aspect of Potential Tumor Markers

The use of tumor markers aids in the early detection of cancer recurrence and prognosis. There is a hope that they might also be useful in screening tests for the early detection of cancer. Here, the question of finding ideal tumor markers, which should be sensitive, specific, and reliable, is an acute issue. Human plasma is one of the most popular samples as it is commonly collected in the clinic and provides noninvasive, rapid analysis for any type of disease including cancer. Many efforts have been applied in searching for “ideal” tumor markers, digging very deep into plasma proteomes. The situation in this area can be improved in two ways—by attempting to find an ideal single tumor marker or by generating panels of different markers. In both cases, proteomics certainly plays a major role. There is a line of evidence that the most abundant, so-called “classical plasma proteins”, may be used to generate a tumor biomarker profile. To be comprehensive these profiles should have information not only about protein levels but also proteoform distribution for each protein. Initially, the profile of these proteins in norm should be generated. In our work, we collected bibliographic information about the connection of cancers with levels of “classical plasma proteins”. Additionally, we presented the proteoform profiles (2DE patterns) of these proteins in norm generated by two-dimensional electrophoresis with mass spectrometry and immunodetection. As a next step, similar profiles representing protein perturbations in plasma produced in the case of different cancers will be generated. Additionally, based on this information, different test systems can be developed.

An Open-Source Pipeline for Processing Direct Infusion Mass Spectrometry Data of the Human Plasma Metabolome

Direct infusion mass spectrometry (DIMS) is growing in popularity as an effective method for the screening of biological samples in clinical metabolomics. Being quick to execute, DIMS generally requires special skills when interpreting the results of measurements. By inspecting the similarities between two-dimensional electrospray ionization with quadrupole time-of-flight (ESI-QTOF) and matrix-assisted laser desorption/ionization (MALDI) mass spectra, the pipeline for processing QTOF mass spectra using open-source packages (MALDIquant, MSnbase and MetaboAnalystR) was tested. Previously, all algorithmic workflows have relied on the application of software either provided by a vendor or privately developed by enthusiasts. Here, we computationally examined two ways of interpreting the DIMS results of human blood metabolomic profiling. The studied spectra were acquired using ESI-QTOF maXis Impact II (Bruker Daltonics, Billerica, MA, USA), then pre-processed using COMPASS/DataAnalysis commercial software and mapped onto the metabolites using in-lab-developed MatLab scripts. Alternatively, in this work we used the open-source packages MALDIquant, for spectrum pre-processing, and MetaboAnalystR, for data interpretation, instead of the low-availability commercial and home-made tools. Using a set of 100 plasma samples (20 from volunteers with normal body mass index and 80 from patients at different stages of obesity), we observed a high degree of concordance in annotated metabolic pathways between the proprietary DataAnalysis/MatLab pipeline and our freely available solution.

Comprehensive and systematic characterization of multi-functionalized cisplatin nano-conjugate: from the chemistry and proteomic biocompatibility to the animal model

Background

Nowadays, nanoparticles (NPs) have evolved as multifunctional systems combining different custom anchorages which opens a wide range of applications in biomedical research. Thus, their pharmacological involvements require more comprehensive analysis and novel nanodrugs should be characterized by both chemically and biological point of view. Within the wide variety of biocompatible nanosystems, iron oxide nanoparticles (IONPs) present mostly of the required features which make them suitable for multifunctional NPs with many biopharmaceutical applications.

Results

Cisplatin-IONPs and different functionalization stages have been broadly evaluated. The potential application of these nanodrugs in onco-therapies has been assessed by studying in vitro biocompatibility (interactions with environment) by proteomics characterization the determination of protein corona in different proximal fluids (human plasma, rabbit plasma and fetal bovine serum),. Moreover, protein labeling and LC–MS/MS analysis provided more than 4000 proteins de novo synthetized as consequence of the nanodrugs presence defending cell signaling in different tumor cell types (data available via ProteomeXchanges with identified PXD026615). Further in vivo studies have provided a more integrative view of the biopharmaceutical perspectives of IONPs.

Conclusions

Pharmacological proteomic profile different behavior between species and different affinity of protein coating layers (soft and hard corona). Also, intracellular signaling exposed differences between tumor cell lines studied. First approaches in animal model reveal the potential of theses NPs as drug delivery vehicles and confirm cisplatin compounds as strengthened antitumoral agents.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12951-022-01546-y.

Endoplasmic reticulum-stress and unfolded protein response-activation in immune-mediated necrotizing myopathy

Patients suffering from immune-mediated necrotizing myopathies (IMNM) harbor, the pathognomonic myositis-specific auto-antibodies anti-SRP54 or -HMGCR, while about one third of them do not. Activation of chaperone-assisted autophagy was described as being part of the molecular etiology of IMNM. Endoplasmic reticulum (ER)/sarcoplasmic reticulum (SR)-stress accompanied by activation of the unfolded protein response (UPR) often precedes activation of the protein clearance machinery and represents a cellular defense mechanism toward restoration of proteostasis. Here, we show that ER/SR-stress may be part of the molecular etiology of IMNM. To address this assumption, ER/SR-stress related key players covering the three known branches (PERK-mediated, IRE1-mediated, and ATF6-mediated) were investigated on both, the transcript and the protein levels utilizing 39 muscle biopsy specimens derived from IMNM-patients. Our results demonstrate an activation of all three UPR-branches in IMNM, which most likely precedes the activation of the protein clearance machinery. In detail, we identified increased phosphorylation of PERK and eIF2a along with increased expression and protein abundance of ATF4, all well-documented characteristics for the activation of the UPR. Further, we identified increased general XBP1-level, and elevated XBP1 protein levels. Additionally, our transcript studies revealed an increased ATF6-expression, which was confirmed by immunostaining studies indicating a myonuclear translocation of the cleaved ATF6-form toward the forced transcription of UPR-related chaperones. In accordance with that, our data demonstrate an increase of downstream factors including ER/SR co-chaperones and chaperones (e.g., SIL1) indicating an UPR-activation on a broader level with no significant differences between seropositive and seronegative patients. Taken together, one might assume that UPR-activation within muscle fibers might not only serve to restore protein homeostasis, but also enhance sarcolemmal presentation of proteins crucial for attracting immune cells. Since modulation of ER-stress and UPR via application of chemical chaperones became a promising therapeutic treatment approach, our findings might represent the starting point for new interventional concepts.

Protocol for Increasing the Sensitivity of MS-Based Protein Detection in Human Chorionic Villi

An important step in the proteomic analysis of missing proteins is the use of a wide range of tissues, optimal extraction, and the processing of protein material in order to ensure the highest sensitivity in downstream protein detection. This work describes a purification protocol for identifying low-abundance proteins in human chorionic villi using the proposed “1DE-gel concentration” method. This involves the removal of SDS in a short electrophoresis run in a stacking gel without protein separation. Following the in-gel digestion of the obtained holistic single protein band, we used the peptide mixture for further LC–MS/MS analysis. Statistically significant results were derived from six datasets, containing three treatments, each from two tissue sources (elective or missed abortions). The 1DE-gel concentration increased the coverage of the chorionic villus proteome. Our approach allowed the identification of 15 low-abundance proteins, of which some had not been previously detected via the mass spectrometry of trophoblasts. In the post hoc data analysis, we found a dubious or uncertain protein (PSG7) encoded on human chromosome 19 according to neXtProt. A proteomic sample preparation workflow with the 1DE-gel concentration can be used as a prospective tool for uncovering the low-abundance part of the human proteome.

Quantitative Proteogenomic Characterization of Inflamed Murine Colon Tissue Using an Integrated Discovery, Verification, and Validation Proteogenomic Workflow

Chronic inflammation of the colon causes genomic and/or transcriptomic events, which can lead to expression of non-canonical protein sequences contributing to oncogenesis. To better understand these mechanisms, Rag2-/-Il10-/- mice were infected with Helicobacter hepaticus to induce chronic inflammation of the cecum and the colon. Transcriptomic data from harvested proximal colon samples were used to generate a customized FASTA database containing non-canonical protein sequences. Using a proteogenomic approach, mass spectrometry data for proximal colon proteins were searched against this custom FASTA database using the Galaxy for Proteomics (Galaxy-P) platform. In addition to the increased abundance in inflammatory response proteins, we also discovered several non-canonical peptide sequences derived from unique proteoforms. We confirmed the veracity of these novel sequences using an automated bioinformatics verification workflow with targeted MS-based assays for peptide validation. Our bioinformatics discovery workflow identified 235 putative non-canonical peptide sequences, of which 58 were verified with high confidence and 39 were validated in targeted proteomics assays. This study provides insights into challenges faced when identifying non-canonical peptides using a proteogenomics approach and demonstrates an integrated workflow addressing these challenges. Our bioinformatic discovery and verification workflow is publicly available and accessible via the Galaxy platform and should be valuable in non-canonical peptide identification using proteogenomics.

Auxiliary ATP binding sites support DNA unwinding by RecBCD

The RecBCD helicase initiates double-stranded break repair in bacteria by processively unwinding DNA with a rate approaching ∼1,600 bp·s⁻¹, but the mechanism enabling such a fast rate is unknown. Employing a wide range of methodologies — including equilibrium and time-resolved binding experiments, ensemble and single-molecule unwinding assays, and crosslinking followed by mass spectrometry — we reveal the existence of auxiliary binding sites in the RecC subunit, where ATP binds with lower affinity and distinct chemical interactions as compared to the known catalytic sites. The essentiality and functionality of these sites are demonstrated by their impact on the survival of E.coli after exposure to damage-inducing radiation. We propose a model by which RecBCD achieves its optimized unwinding rate, even when ATP is scarce, by using the auxiliary binding sites to increase the flux of ATP to its catalytic sites.

RecBCD is a remarkably fast DNA helicase. Using a battery of biophysical methods, Zananiri et. al reveal additional, non-catalytic ATP binding sites that increase the ATP flux to the catalytic sites that allows fast unwinding when ATP is scarce.

The cation channel TRPM8 influences the differentiation and function of human monocytes

Monocytes are mononuclear phagocytes that can differentiate to a variety of cell fates under the influence of their microenvironment and hardwired commitment. We found that inhibition of TRPM8 in human blood CD14⁺ monocytes during a critical 3‐h window at the beginning of their differentiation into macrophages led to enhanced survival and LPS‐driven TNFα production after 24 h. TRPM8 antagonism also promoted LPS‐driven TNFα production in CD14⁺ monocytes derived from the intestinal mucosa. Macrophages that had been derived for 6 days under blockade of TRPM8 had impaired phagocytic capacity and were transcriptionally distinct. Most of the affected genes were altered in a way that opposed normal monocyte to macrophage differentiation indicating that TRPM8 activity promotes aspects of this differentiation programme. Thus, we reveal a novel role for TRPM8 in regulating human CD14⁺ monocyte fate and function.

An overview of technologies for MS-based proteomics-centric multi-omics

INTRODUCTION

Mass spectrometry-based proteomics reveals dynamic molecular signatures underlying phenotypes reflecting normal and perturbed conditions in living systems. Although valuable on its own, the proteome has only one level of moleclar information, with the genome, epigenome, transcriptome, and metabolome, all providing complementary information. Multi-omic analysis integrating information from one or more of these other domains with proteomic information provides a more complete picture of molecular contributors to dynamic biological systems.

AREAS COVERED

Here, we discuss the improvements to mass spectrometry-based technologies, focused on peptide-based, bottom-up approaches that have enabled deep, quantitative characterization of complex proteomes. These advances are facilitating the integration of proteomics data with other 'omic information, providing a more complete picture of living systems. We also describe the current state of bioinformatics software and approaches for integrating proteomics and other 'omics data, critical for enabling new discoveries driven by multi-omics.

EXPERT COMMENTARY

Multi-omics, centered on the integration of proteomics information with other 'omic information, has tremendous promise for biological and biomedical studies. Continued advances in approaches for generating deep, reliable proteomic data and bioinformatics tools aimed at integrating data across 'omic domains will ensure the discoveries offered by these multi-omic studies continue to increase.

Comparative proteomic analysis of Leishmania parasites isolated from visceral and cutaneous leishmaniasis patients

Leishmaniasis is an infectious disease in which different clinical manifestations are classified into three primary forms: visceral, cutaneous and mucocutaneous. These disease forms are associated with parasite species of the protozoan genus Leishmania. For instance, Leishmania infantum and Leishmania tropica are typically linked with visceral (VL) and cutaneous (CL) leishmaniasis, respectively; however, these two species can also cause other form to a lesser extent. What is more alarming is this characteristic, which threatens current medical diagnosis and treatment, is started to be acquired by other species. Our purpose was to address this issue; therefore, gel-based and gel-free proteomic analyses were carried out on the species L. infantum to determine the proteins differentiating between the parasites caused VL and CL. In addition, L. tropica parasites representing the typical cases for CL were included. According to our results, electrophoresis gels of parasites caused to VL were distinguishable regarding the repetitive down-regulation on some specific locations. In addition, a distinct spot of an antioxidant enzyme, superoxide dismutase, was shown up only on the gels of CL samples regardless of the species. In the gel-free approach, 37 proteins that were verified with a second database search using a different search engine, were recognized from the comparison between VL and CL samples. Among them, 31 proteins for the CL group and six proteins for the VL group were determined differentially abundant. Two proteins from the gel-based analysis, pyruvate kinase and succinyl-coA:3-ketoacid-coenzyme A transferase analysis were encountered in the protein list of the CL group.

Silencing of Opisthorchis viverrini Tetraspanin Gene Expression Results in Reduced Secretion of Extracellular Vesicles

Inter-phylum transfer of molecular information is exquisitely exemplified in the uptake of parasite extracellular vesicles (EVs) by their target mammalian host tissues. The oriental liver fluke, Opisthorchis viverrini is the major cause of bile duct cancer in people in Southeast Asia. A major mechanism by which O. viverrini promotes cancer is through the secretion of excretory/secretory products which contain extracellular vesicles (OvEVs). OvEVs contain microRNAs that are predicted to impact various mammalian cell proliferation pathways, and are internalized by cholangiocytes that line the bile ducts. Upon uptake, OvEVs drive relentless proliferation of cholangiocytes and promote a tumorigenic environment, but the underlying mechanisms of this process are unknown. Moreover, purification and characterization methods for helminth EVs in general are ill defined. We therefore compared different purification methods for OvEVs and characterized the sub-vesicular compartment proteomes. Two CD63-like tetraspanins (Ov-TSP-2 and TSP-3) are abundant on the surface of OvEVs, and could serve as biomarkers for these parasite vesicles. Anti-TSP-2 and -TSP-3 IgG, as well as different endocytosis pathway inhibitors significantly reduced OvEV uptake and subsequent proliferation of cholangiocytes in vitro. Silencing of Ov-tsp-2 and tsp-3 gene expression in adult flukes using RNA interference resulted in substantial reductions in OvEV secretion, and those vesicles that were secreted were deficient in their respective TSP proteins. Our findings shed light on the importance of tetraspanins in fluke EV biogenesis and/or stability, and provide a conceivable mechanism for the efficacy of anti-tetraspanin subunit vaccines against a range of parasitic helminth infections.

Deciphering Biomarkers for Leptomeningeal Metastasis in Malignant Hemopathies (Lymphoma/Leukemia) Patients by Comprehensive Multipronged Proteomics Characterization of Cerebrospinal Fluid

Simple Summary

The early diagnosis of leptomeningeal disease is a challenge because it is asymptomatic in the early stages. Consequently, it is important to identify a panel of biomarkers to help in its diagnosis and/or prognosis. For this purpose, we explored a multipronged proteomics approach in cerebrospinal fluid (CSF) to determine a potential panel of biomarkers. Thus, a systematic and exhaustive characterization of more than 300 CSF samples was performed by an integrated approach by Liquid Chromatography-Tandem Mass Spectrometry (LC-MS/MS) and functional proteomics analysis to establish protein profiles, which were useful for developing a panel of biomarkers validated by in silico approaches.

Abstract

In the present work, leptomeningeal disease, a very destructive form of systemic cancer, was characterized from several proteomics points of view. This pathology involves the invasion of the leptomeninges by malignant tumor cells. The tumor spreads to the central nervous system through the cerebrospinal fluid (CSF) and has a very grim prognosis; the average life expectancy of patients who suffer it does not exceed 3 months. The early diagnosis of leptomeningeal disease is a challenge because, in most of the cases, it is an asymptomatic pathology. When the symptoms are clear, the disease is already in the very advanced stages and life expectancy is low. Consequently, there is a pressing need to determine useful CSF proteins to help in the diagnosis and/or prognosis of this disease. For this purpose, a systematic and exhaustive proteomics characterization of CSF by multipronged proteomics approaches was performed to determine different protein profiles as potential biomarkers. Proteins such as PTPRC, SERPINC1, sCD44, sCD14, ANPEP, SPP1, FCGR1A, C9, sCD19, and sCD34, among others, and their functional analysis, reveals that most of them are linked to the pathology and are not detected on normal CSF. Finally, a panel of biomarkers was verified by a prediction model for leptomeningeal disease, showing new insights into the research for potential biomarkers that are easy to translate into the clinic for the diagnosis of this devastating disease.

Proteomic Sample Preparation and Data Analysis in Line with the Archaeal Proteome Project

Despite the ecological, evolutionary and economical significance of archaea, key aspects of their cell biology, metabolic pathways, and adaptations to a wide spectrum of environmental conditions, remain to be elucidated. Proteomics allows for the system-wide analysis of proteins, their changes in abundance between different conditions, as well as their post-translational modifications, providing detailed insights into the function of proteins and archaeal cell biology. In this chapter, we describe a sample preparation and mass spectrometric analysis workflow that has been designed for Haloferax volcanii but can be applied to a broad range of archaeal species. Furthermore, proteomics experiments provide a wealth of data that is invaluable to various disciplines. Therefore, we previously initiated the Archaeal Proteome Project (ArcPP), a community project that combines the analysis of multiple datasets with expert knowledge in various fields of archaeal research. The corresponding bioinformatic analysis, allowing for the integration of new proteomics data into the ArcPP, as well as the interactive exploration of ArcPP results is also presented here. In combination, these protocols facilitate an optimized, detailed and collaborative approach to archaeal proteomics.

Effect of polyethylene glycol 20 000 on protein extraction efficiency of formalin-fixed paraffin-embedded tissues in South Africa

BACKGROUND

Optimal protocols for efficient and reproducible protein extraction from formalin-fixed paraffin-embedded (FFPE) tissues are not yet standardised and new techniques are continually developed and improved. The effect of polyethylene glycol (PEG) 20 000 on protein extraction efficiency has not been evaluated using human FFPE colorectal cancer tissues and there is no consensus on the protein extraction solution required for efficient, reproducible extraction.

OBJECTIVE

The impact of PEG 20 000 on protein extraction efficiency, reproducibility and protein selection bias was evaluated using FFPE colonic tissue via liquid chromatography tandem mass spectrometry analysis.

METHODS

This study was conducted from August 2017 to July 2019 using human FFPE colorectal carcinoma tissues from the Anatomical Pathology department at Tygerberg Hospital in South Africa. Samples were analysed via label-free liquid chromatography tandem mass spectrometry to determine the impact of using PEG 20 000 in the protein extraction solution. Data were assessed regarding peptide and protein identifications, method efficiency, reproducibility, protein characteristics and organisation relating to gene ontology categories.

RESULTS

Polyethylene glycol 20 000 exclusion increased peptides and proteins identifications and the method was more reproducible compared to the samples processed with PEG 20 000. However, no differences were observed with regard to protein selection bias. We found that higher protein concentrations (> 10 µg) compromised the function of PEG.

CONCLUSION

This study indicates that protocols generating high protein yields from human FFPE tissues would benefit from the exclusion of PEG 20 000 in the protein extraction solution.

Critical Assessment of MetaProteome Investigation (CAMPI): a multi-laboratory comparison of established workflows

Metaproteomics has matured into a powerful tool to assess functional interactions in microbial communities. While many metaproteomic workflows are available, the impact of method choice on results remains unclear. Here, we carry out a community-driven, multi-laboratory comparison in metaproteomics: the critical assessment of metaproteome investigation study (CAMPI). Based on well-established workflows, we evaluate the effect of sample preparation, mass spectrometry, and bioinformatic analysis using two samples: a simplified, laboratory-assembled human intestinal model and a human fecal sample. We observe that variability at the peptide level is predominantly due to sample processing workflows, with a smaller contribution of bioinformatic pipelines. These peptide-level differences largely disappear at the protein group level. While differences are observed for predicted community composition, similar functional profiles are obtained across workflows. CAMPI demonstrates the robustness of present-day metaproteomics research, serves as a template for multi-laboratory studies in metaproteomics, and provides publicly available data sets for benchmarking future developments.

Accurate Prediction of Protein Sequences for Proteogenomics Data Integration

This book chapter discusses proteogenomics data integration and provides an overview into the different omics layer involved in defining the proteome of a living organism. Various aspects of genome variability affecting either the sequence or abundance level of proteins are discussed in this book chapter, such as the effect of single-nucleotide variants or larger genomic structural variants on the proteome. Next, various sequencing technologies are introduced and discussed from a proteogenomics data integration perspective such as those providing short- and long-read sequencing and listing their respective advantages and shortcomings for accurate protein variant prediction using genomic/transcriptomics sequencing data. Finally, the various bioinformatics tools used to process and analyze DNA/RNA sequencing data are discussed with the ultimate goal of obtaining accurately predicted sample-specific protein sequences that can be used as a drop-in replacement in existing approaches for peptide and protein identification using popular database search engines such as MSFragger, SearchGUI/PeptideShaker.

Critical Assessment of MetaProteome Investigation (CAMPI): a multi-laboratory comparison of established workflows

Metaproteomics has matured into a powerful tool to assess functional interactions in microbial communities. While many metaproteomic workflows are available, the impact of method choice on results remains unclear. Here, we carry out a community-driven, multi-laboratory comparison in metaproteomics: the critical assessment of metaproteome investigation study (CAMPI). Based on well-established workflows, we evaluate the effect of sample preparation, mass spectrometry, and bioinformatic analysis using two samples: a simplified, laboratory-assembled human intestinal model and a human fecal sample. We observe that variability at the peptide level is predominantly due to sample processing workflows, with a smaller contribution of bioinformatic pipelines. These peptide-level differences largely disappear at the protein group level. While differences are observed for predicted community composition, similar functional profiles are obtained across workflows. CAMPI demonstrates the robustness of present-day metaproteomics research, serves as a template for multi-laboratory studies in metaproteomics, and provides publicly available data sets for benchmarking future developments.

Deepening into Intracellular Signaling Landscape through Integrative Spatial Proteomics and Transcriptomics in a Lymphoma Model

Human Proteome Project (HPP) presents a systematic characterization of the protein landscape under different conditions using several complementary-omic techniques (LC-MS/MS proteomics, affinity proteomics, transcriptomics, etc.). In the present study, using a B-cell lymphoma cell line as a model, comprehensive integration of RNA-Seq transcriptomics, MS/MS, and antibody-based affinity proteomics (combined with size-exclusion chromatography) (SEC-MAP) were performed to uncover correlations that could provide insights into protein dynamics at the intracellular level. Here, 5672 unique proteins were systematically identified by MS/MS analysis and subcellular protein extraction strategies (neXtProt release 2020-21, MS/MS data are available via ProteomeXchange with identifier PXD003939). Moreover, RNA deep sequencing analysis of this lymphoma B-cell line identified 19,518 expressed genes and 5707 protein coding genes (mapped to neXtProt). Among these data sets, 162 relevant proteins (targeted by 206 antibodies) were systematically analyzed by the SEC-MAP approach, providing information about PTMs, isoforms, protein complexes, and subcellular localization. Finally, a bioinformatic pipeline has been designed and developed for orthogonal integration of these high-content proteomics and transcriptomics datasets, which might be useful for comprehensive and global characterization of intracellular protein profiles.

Severe types of fetopathy are associated with changes in the serological proteome of diabetic mothers

ABSTRACT

Pregestational or gestational diabetes are the main risk factors for diabetic fetopathy. There are no generalized signs of fetopathy before the late gestational age due to insufficient sensitivity of currently employed instrumental methods. In this cross-sectional observational study, we investigated several types of severe diabetic fetopathy (cardiomyopathy, central nervous system defects, and hepatomegaly) established in type 2 diabetic mothers during 30 to 35 gestational weeks and confirmed upon delivery. We examined peripheral blood plasma and determined a small proportion of proteins strongly associated with a specific type of fetopathy or anatomical malfunction. Most of the examined markers participate in critical processes at different stages of embryogenesis and regulate various phases of morphogenesis. Alterations in CDCL5 had a significant impact on mRNA splicing and DNA repair. Patients with central nervous system defects were characterized by the greatest depletion (ca. 7% of the basal level) of DFP3, a neurotrophic factor needed for the proper specialization of oligodendrocytes. Dysregulation of noncanonical wingless-related integration site signaling pathway (Wnt) signaling guided by pigment epithelium-derived factor (PEDF) and disheveled-associated activator of morphogenesis 2 (DAAM2) was also profound. In addition, deficiency in retinoic acid and thyroxine transport was exhibited by the dramatic increase of transthyretin (TTHY). The molecular interplay between the identified serological markers leads to pathologies in fetal development on the background of a diabetic condition. These warning serological markers can be quantitatively examined, and their profile may reflect different severe types of diabetic fetopathy, producing a beneficial effect on the current standard care for pregnant women and infants.

Intracellular Lipid Accumulation and Mitochondrial Dysfunction Accompanies Endoplasmic Reticulum Stress Caused by Loss of the Co-chaperone DNAJC3

Recessive mutations in DNAJC3, an endoplasmic reticulum (ER)-resident BiP co-chaperone, have been identified in patients with multisystemic neurodegeneration and diabetes mellitus. To further unravel these pathomechanisms, we employed a non-biased proteomic approach and identified dysregulation of several key cellular pathways, suggesting a pathophysiological interplay of perturbed lipid metabolism, mitochondrial bioenergetics, ER-Golgi function, and amyloid-beta processing. Further functional investigations in fibroblasts of patients with DNAJC3 mutations detected cellular accumulation of lipids and an increased sensitivity to cholesterol stress, which led to activation of the unfolded protein response (UPR), alterations of the ER-Golgi machinery, and a defect of amyloid precursor protein. In line with the results of previous studies, we describe here alterations in mitochondrial morphology and function, as a major contributor to the DNAJC3 pathophysiology. Hence, we propose that the loss of DNAJC3 affects lipid/cholesterol homeostasis, leading to UPR activation, β-amyloid accumulation, and impairment of mitochondrial oxidative phosphorylation.

20S and 26S proteasome-binding proteins of the rabbit brain: A proteomic dataset

Fractions of 26S and 20S proteasomes isolated from the rabbit brain by the method of salt fractionation (salt-induced precipitation) contain intrinsic proteasome proteins responsible for assembly of the core particle and regulatory particle of proteasome and also proteasome-binding proteins. These proteasome-binding proteins include components of the ubiquitin-proteasome system, some ubiquitinated proteins, as well as cytoskeleton components, protective proteins, regulators of gene expression, cell division, and differentiation, and multifunctional proteins (mainly, glycolytic enzymes: glyceraldehyde-3-phosphate dehydrogenase (GAPDH), aldolase, pyruvate kinase, etc.). The multifunctional proteins also known as "moonlighting proteins" are involved in various (regulatory) processes in the cell and obviously represent important components of the proteasome interactome rather than contaminants of the 26S and 20S proteasome fractions.

Human blood serum proteome changes after 6 hours of sleep deprivation at night

Background

The aim of this study was to discover significantly changed proteins in human blood serum after loss of 6 h sleep at night. Furthermore, to reveal affected biological process- and molecular function categories that might be clinically relevant, by exploring systems biological databases.

Methods

Eight females were recruited by volunteer request. Peripheral venous whole blood was sampled at 04:00 am, after 6 h of sleep and after 6 h of sleep deprivation. We used within-subjects design (all subjects were their own control). Blood serum from each subject was depleted before protein digestion by trypsin and iTRAQ labeling. Labled peptides were analyzed by mass spectrometry (LTQ OritrapVelos Elite) connected to a LC system (Dionex Ultimate NCR-3000RS).

Results

We identified 725 proteins in human blood serum. 34 proteins were significantly differentially expressed after 6 h of sleep deprivation at night. Out of 34 proteins, 14 proteins were up-regulated, and 20 proteins were down-regulated. We emphasized the functionality of the 16 proteins commonly differentiated in all 8 subjects and the relation to pathological conditions. In addition, we discussed Histone H4 (H4) and protein S100-A6/Calcyclin (S10A6) that were upregulated more than 1.5-fold. Finally, we discussed affected biological process- and molecular function categories.

Conclusions

Overall, our study suggest that acute sleep deprivation, at least in females, affects several known biological processes- and molecular function categories and associates to proteins that also are changed under pathological conditions like impaired coagulation, oxidative stress, immune suppression, neurodegenerative related disorder, and cancer. Data are available via ProteomeXchange with identifier PXD021004.

How to Illuminate the Dark Proteome Using the Multi-omic OpenProt Resource

Ten of thousands of open reading frames (ORFs) are hidden within genomes. These alternative ORFs, or small ORFs, have eluded annotations because they are either small or within unsuspected locations. They are found in untranslated regions or overlap a known coding sequence in messenger RNA and anywhere in a "non-coding" RNA. Serendipitous discoveries have highlighted these ORFs' importance in biological functions and pathways. With their discovery came the need for deeper ORF annotation and large-scale mining of public repositories to gather supporting experimental evidence. OpenProt, accessible at https://openprot.org/, is the first proteogenomic resource enforcing a polycistronic model of annotation across an exhaustive transcriptome for 10 species. Moreover, OpenProt reports experimental evidence cumulated across a re-analysis of 114 mass spectrometry and 87 ribosome profiling datasets. The multi-omics OpenProt resource also includes the identification of predicted functional domains and evaluation of conservation for all predicted ORFs. The OpenProt web server provides two query interfaces and one genome browser. The query interfaces allow for exploration of the coding potential of genes or transcripts of interest as well as custom downloads of all information contained in OpenProt. © 2020 The Authors. Basic Protocol 1: Using the Search interface Basic Protocol 2: Using the Downloads interface.

DDASSQ: an open-source, multiple peptide sequencing strategy for label free quantification based on an OpenMS pipeline in the KNIME analytics platform

In this study we investigated the performance of a computational pipeline for protein identification and label free quantification (LFQ) of LC–MS/MS data sets from experimental animal tissue samples, as well as the impact of its specific peptide search combinatorial approach. The full pipeline workflow was composed of peptide search engine adapters based on different identification algorithms, in the frame of the open‐source OpenMS software running within the KNIME analytics platform. Two different in silico tryptic digestion, database‐search assisted approaches (X!Tandem and MS‐GF+), de novo peptide sequencing based on Novor and consensus library search (SpectraST), were tested for the processing of LC‐MS/MS raw data files obtained from proteomic LC‐MS experiments done on proteolytic extracts from mouse ex vivo liver samples. The results from proteomic LFQ were compared to those based on the application of the two software tools MaxQuant and Proteome Discoverer for protein inference and label‐free data analysis in shotgun proteomics. Data are available via ProteomeXchange with identifier PXD025097.