Benefits of iterative searches of large databases to interpret large human gut metaproteomic datasets
Ontology highlight
ABSTRACT:
INSTRUMENT(S): Q Exactive Plus
ORGANISM(S): Microbiota (ncbitaxon:13613)
SUBMITTER: 
Ariane BASSIGNANI
PROVIDER: MSV000085993 | MassIVE | Fri Aug 21 08:54:00 BST 2020
SECONDARY ACCESSION(S): PXD021050
REPOSITORIES: MassIVE
Similar Datasets
Project description:DNA, RNA and protein were extracted from the culture and subjected to massive parallel sequencing and nano-LC-MS-MS respectively
2010-03-25 | GSE18535 | GEO
Project description:The gut microbiome plays an important role in normal immune function and has been implicated in several autoimmune disorders. Here we use high-throughput 16S rRNA sequencing to investigate the gut microbiome in subjects with multiple sclerosis (MS, n=61) and healthy controls (n=43). Alterations in the gut microbiome in MS include increases in the genera Methanobrevibacter and Akkermansia and decreases in Butyricimonas, and correlate with variations in the expression of genes involved in dendritic cell maturation, interferon signaling and NF-kB signaling pathways in circulating T cells and monocytes. Patients on disease-modifying treatment show increased abundances of the genera Prevotella and Sutterella, and decreased Sarcina, compared to untreated patients. MS patients of a second cohort show elevated breath methane compared to controls, consistent with our observation of increased gut Methanobrevibacter in MS in the first cohort. Further study is required to assess whether the observed alterations in the gut microbiome play a role in, or are a consequence of, MS pathogenesis.
2016-05-11 | GSE81279 | GEO
Project description:BackgroundMicrobiome research is providing important new insights into the metabolic interactions of complex microbial ecosystems involved in fields as diverse as the pathogenesis of human diseases, agriculture and climate change. Poor correlations typically observed between RNA and protein expression datasets make it hard to accurately infer microbial protein synthesis from metagenomic data. Additionally, mass spectrometry-based metaproteomic analyses typically rely on focused search sequence databases based on prior knowledge for protein identification that may not represent all the proteins present in a set of samples. Metagenomic 16S rRNA sequencing only targets the bacterial component, while whole genome sequencing is at best an indirect measure of expressed proteomes. Here we describe a novel approach, MetaNovo, that combines existing open-source software tools to perform scalable de novo sequence tag matching with a novel algorithm for probabilistic optimization of the entire UniProt knowledgebase to create tailored sequence databases for target-decoy searches directly at the proteome level, enabling metaproteomic analyses without prior expectation of sample composition or metagenomic data generation and compatible with standard downstream analysis pipelines.ResultsWe compared MetaNovo to published results from the MetaPro-IQ pipeline on 8 human mucosal-luminal interface samples, with comparable numbers of peptide and protein identifications, many shared peptide sequences and a similar bacterial taxonomic distribution compared to that found using a matched metagenome sequence database-but simultaneously identified many more non-bacterial peptides than the previous approaches. MetaNovo was also benchmarked on samples of known microbial composition against matched metagenomic and whole genomic sequence database workflows, yielding many more MS/MS identifications for the expected taxa, with improved taxonomic representation, while also highlighting previously described genome sequencing quality concerns for one of the organisms, and identifying an experimental sample contaminant without prior expectation.ConclusionsBy estimating taxonomic and peptide level information directly on microbiome samples from tandem mass spectrometry data, MetaNovo enables the simultaneous identification of peptides from all domains of life in metaproteome samples, bypassing the need for curated sequence databases to search. We show that the MetaNovo approach to mass spectrometry metaproteomics is more accurate than current gold standard approaches of tailored or matched genomic sequence database searches, can identify sample contaminants without prior expectation and yields insights into previously unidentified metaproteomic signals, building on the potential for complex mass spectrometry metaproteomic data to speak for itself.
| S-EPMC10310047 | biostudies-literature
Project description:DNA, RNA and protein were extracted from the culture and subjected to massive parallel sequencing and nano-LC-MS-MS respectively Combination of these methods enabled the reconstruction of the complete genome sequence of M oxyfera from the metagenome and identification of the functionally relevant enzymes and genes
2010-03-25 | E-GEOD-18535 | biostudies-arrayexpress
Project description:Tooth is a remarkable source of information for paleoanthropologists. Investigation of ancient dental proteomes is able to provide biomolecular data helping at understanding past life. In particular, the enamel protein amelogenin (AMEL) offers the possibilty to determine the sex of the specimen. In this study, we have analysed eleven 5000 year-old human teeth from a French Neolithic site to set up dedicated paleoproteomics strategies for phenotypic and taxonomic characterization of ancient samples. We have developed an optimized 3-step iterative search strategy using a custom human protein database of shotgun proteomics nanoLC-MS/MS data. This allowed the identification of a total number of 1496 proteins in two replicate experiments. Most of the proteins were identified thanks to the no-enzyme database search mode included in the dedicated bioinformatics data analysis pipeline based on iterative database search strategy. In particular, in addition to specific tooth proteins, this optimized shotgun proteomics approach led to the identification of two other proteins of interest, cementum protein 1 (CEMP1) and collagen alpha-1(X) (COL10A1). Noteworthy, the presence of single amino acid variations K55E and D128N could also be identified in CEMP1 and COL10A1, respectively. These polymorphisms are rarely found in the European population today. We have also designed a targeted nanoLC-PRM strategy using the sex specific peptides TALVLTPLK and IALVLTPLK of the AMELX and AMELY proteins. This sensitive approach allowed to successfully identify the sex of the individuals in 91% of the samples.
2021-08-06 | PXD012481 | Pride
Project description:MicroRNA (miRNA) biogenesis is a tightly controlled multi-step process operated in the nucleus by the activity of the Large Drosha Complex (LDC). Through high resolution mass spectrometry (MS) analysis we discovered that the LDC is extensively methylated, with 82 distinct methylated sites associated to 16 out of 23 subunits of the LDC. The majority of these modifications occurs on arginine (R)- residues (61), leading to 86 methylation events, while 29 lysine (K)-methylation events occurs on 21 sites of the complex. Interestingly, the depletion and pharmacological inhibition of PRMT1 lead to a widespread alteration of the methylation state of the complex and induce global decrease of miRNA expression, as a consequence of the specific impairment of the pri-to-pre-miRNA processing step. In particular, we show that the reduced methylation of the ILF3 subunit of the complex is linked to its diminished binding to the target pri-miRNAs. Overall, our study uncovers a previously uncharacterized role of R-methylation in the regulation of the LDC activity in mammalian cells, thus effecting global miRNA levels.
2019-10-23 | PXD011617 | Pride
Project description:Tooth is a remarkable source of information for paleoanthropologists. Investigation of ancient dental proteomes is able to provide biomolecular data helping at understanding past life. In particular, the enamel protein amelogenin (AMEL) offers the possibility to determine the sex of the specimen. Here, we have analysed eleven 5000 year-old human teeth from a French Neolithic site using a dedicated paleoproteomics strategy for phenotypic characterization of ancient samples. We have set up a shotgun proteomics analysis based on an optimized 3-step iterative search strategy. This allowed the identification of a total number of 1496 proteins including the main proteins characteristic of dental tissues. Most of the proteins were identified by the no enzyme database search mode included in the iterative bioinformatics data analysis pipeline. This demonstrates that a number of peptides issued from randomly degraded proteins may be missed when using the conventional semi-tryptic database search mode. Based on the identification of the sex-specific peptides TALVLTPLK, IALVLTPLK and WYQSIRPPYP of amelogenin, a targeted MS approach using a parallel reaction monitoring (PRM) mode was performed to maximize the sensitivity and the reproducibility of detecting these unique peptides for sex estimation. This led to confirm the sex of individualsin all the samples.
2019-11-13 | PXD014442 | Pride
Project description:Metaproteomic portrait of the healthy human gut microbiota. Re-analysis of existing datasets, selected based on the following inclusion criteria: human cohort including at least 5 healthy (clearly not labeled as diseased) adult (>18 years old) individuals; data derived from LC-MS/MS DDA label-free analysis of fecal samples (with neither subcellular fractionation of microbial cells nor offline fractionation of peptides); availability of raw MS data on public repositories.
2024-05-16 | PXD046818 | Pride
Project description:We present a human gut metaproteomic dataset deposited in the ProteomeXchange Consortium via the PRIDE partner repository with the dataset identifier PXD001573. Ten aliquots of a single stool sample collected from a healthy human volunteer were either pretreated by differential centrifugation (DC; N=5) or not centrifuged (NC; N=5). Protein extracts were then processed by filter-aided sample preparation, single-run liquid chromatography and high-resolution mass spectrometry, and peptide identification was carried out using Sequest-HT as search engine within the Proteome Discoverer informatic platform. The dataset described here is also related to the research article entitled "Enrichment or depletion? The impact of stool pretreatment on metaproteomic characterization of the human gut microbiota" published in Proteomics (Tanca et al., 2015), [1].
| S-EPMC4536287 | biostudies-literature
Project description:In the presented study, in order to unravel gut microbial community multiplicity and the influence of maternal milk nutrients (i.e., IgA) on gut mucosal microbiota onset and shaping, a mouse GM (MGM) was used as newborn study model to discuss genetic background and feeding modulation on gut microbiota in term of symbiosis, dysbiosis and rebiosis maintenance during early gut microbiota onset and programming after birth. Particularly, a bottom-up shotgun metaproteomic approach, combined with a computational pipeline, has been compred with a culturomics analysis of mouse gut microbiota, obtained by MALDI-TOF mass spectrometry (MS).
2016-10-13 | PXD004033 | Pride