ABSTRACT: evaluate the impact of fecal sample preparation protein digestion data acquisition mode and bioinformatic workflow on metaproteomic observations
Project description:Evaluates the impact of fecal sample preparation, protein digestion, data acquisition mode and bioinformatic workflow on metaproteomic observations
Project description:Analysis of large-scale data-independent acquisition mass spectrometry (DIA-MS) metaproteomics data remains a computational challenge. Here, we present a computational pipeline called metaExpertPro for metaproteomics data analysis. This pipeline encompasses spectral library generation using data-dependent acquisition MS (DDA-MS), protein identification and quantification using DIA-MS, functional and taxonomic annotation, as well as quantitative matrix generation for both microbiota and hosts. By integrating FragPipe and DIA-NN, metaExpertPro offers compatibility with both Orbitrap and timsTOF MS instruments. To evaluate the depth and accuracy of identification and quantification, we conducted extensive assessments using human fecal samples and benchmark tests. Performance tests conducted on human fecal samples indicated that metaExpertPro quantified an average of 45,000 peptides in a 60-minute diaPASEF injection. Notably, metaExpertPro outperformed three existing software tools by characterizing a higher number of peptides and proteins. Importantly, metaExpertPro maintained a low factual false discovery rate (FDR) of approximately 5% for protein groups across four benchmark tests. Applying a filter of five peptides per genus, metaExpertPro achieved relatively high accuracy (F-score = 0.67–0.90) in genus diversity and showed a high correlation (rSpearman = 0.73–0.82) between the measured and true genus relative abundance in benchmark tests. Additionally, the quantitative results at the protein, taxonomy, and function levels exhibited high reproducibility and consistency across the commonly adopted public human gut microbial protein databases IGC and UHGP. In a metaproteomic analysis of dyslipidemia (DLP) patients, metaExpertPro revealed characteristic alterations in microbial functions and potential interactions between the microbiota and the host.
Project description:Mucosal-luminal interface (MLI) samples were collected from a cohort of children with new-onset IBD and microbial cells were harvested and processed for metaproteomic analysis. Deep metaproteomics data analysis was then performed for better understanding the MLI microbiota functions in the development of pediatric IBD.
Project description:Metaproteomics of a human fecal standard, MetaP, with ASTRAL tandem mass spectometer operated in data-dependent analysis for deep-proteotyping and evaluate metaproteomics strategies.
Project description:Metaproteomics of a human fecal standard, MetaP, with an Exploris480 tandem mass spectometer operated in data-dependent analysis for proteotyping and evaluation of metaproteomics strategies.
Project description:A metaproteomics analysis was conducted on the infant fecal microbiome to characterize global protein expression in 8 samples obtained from infants with a range of early-life experiences. Samples included breast-, formula- or mixed-fed, mode of delivery, and antibiotic treatment and one set of monozygotic twins. Although label-free mass spectrometry-based proteomics is routinely used for the identification and quantification of thousands of proteins in complex samples, the metaproteomic analysis of the gut microbiome presents particular technical challenges. Among them: the extreme complexity and dynamic range of member taxa/species, the need for matched, well-annotated metagenomics databases, and the high inter-protein sequence redundancy/similarity between related members. In this study, a metaproteomic approach was developed for assessment of the biological phenotype and functioning, as a complement to 16S rRNA sequencing analysis to identify constituent taxa. A sample preparation method was developed for recovery and lysis of bacterial cells, followed by trypsin digestion, and pre-fractionation using Strong Cation Exchange chromatography. Samples were then subjected to high performance LC-MS/MS. Data was searched against the Human Microbiome Project database, and a homology-based meta-clustering strategy was used to combine peptides from multiple species into representative proteins. Bacterial taxonomies were also identified, based on species-specific protein sequences, and protein metaclusters were assigned to pathways and functional groups. The results obtained demonstrate the applicability of this approach for performing qualitative comparisons of human fecal microbiome composition, physiology and metabolism, and also provided a more detailed assessment of microbial composition in comparison to 16S rRNA.
Project description:Objective Crohn’s Disease (CD) and Ulcerative Colitis (UC) are chronic inflammatory diseases of the gastrointestinal tract. Reliable diagnosis of these diseases requires a comprehensive examination of the patient, which include invasive endoscopy. This study assesses whether non-invasive LC-MS/MS based analysis of microbial and human proteins from feces may support the diagnosis of the diseases. Design In order to mimic a representative clinical background for this study, we investigated 17 healthy controls, 11 CD patients, 14 UC patients, also 13 Irritable Bowel Disease (IBS) patients, 8 Colon Adenoma (CA) patients, and 8 Gastric Carcinoma (GCA) patients. The proteins were extracted from the fecal samples with liquid phenol in a ball mill. Subsequently, the proteins were digested tryptically to peptides and analyzed by liquid chromatography coupled to an Orbitrap MS/MS. For protein identification and interpretation of taxonomic and functional results, the MetaProteomeAnalyzer software and the UniProtKB/SwissProt database and several metagenomes from human fecal samples were used. Results Cluster analysis and ANOSIM show a separation of healthy controls from patients with CD and UC as well as from patients with GCA. Among others, UC and CD correlated with an increase of neutrophil extracellular traps and immunoglobulins G (IgG) as well as a decrease of IgA. A specific marker metaprotein for CD was an increase of the human enzyme sucrose-isomaltase. IBS and CA patient’s fecal metaproteome showed only minor alterations. Conclusion Metaproteome analysis distinguished between patients with UC, CD and healthy controls and is therefore useful as a non-invasive tool for routine diagnostics in hospitals.
Project description:The aim of this study was to test the hypothesis that replenishing the microbiota with a fecal microbiota transplant (FMT) can rescue a host from an advanced stage of sepsis. We developed a clinically-relevant mouse model of lethal polymicrobial gut-derived sepsis in mice using a 4-member pathogen community (Candida albicans, Klebsiella oxytoca, Serratia marcescens, Enterococcus faecalis) isolated from a critically ill patient. In order to mimic pre-operative surgical patient condition mice were exposed to food restriction and antibiotics. Approximately 18 hours prior to surgery food was removed from the cages and the mice were allowed only tap water. Each mouse received an intramuscular Cefoxitin injection 30 minutes prior to the incision at a concentration of 25 mg/kg into the left thigh. Mice were then subjected to a midline laparotomy, 30% hepatectomy of the left lateral lobe of the liver and a direct cecal inoculation of 200 µL of the four pathogen community. On postoperative day one, the mice were administered rectal enema. Mice were given either 1 ml of fecal microbiota transplant (FMT) or an autoclaved control (AC). This was again repeated on postoperative day two. Mice were then followed for mortality. Chow was restored to the cages on postoperative day two, approximately 45 hours after the operation. The injection of fecal microbiota transplant by enema significantly protected mice survival, reversed the composition of gut microflora and down-regulated the host inflammatory response. The cecum, left lobe of the liver, and spleen were isolated from mice for microarray processing with three or more replicates for six expermental conditions: non-treated control, SAHC POD1, SAHC.AC POD2, SAHC.FMT POD2, SAHC.AC POD7, SAHC.FMT POD7
Project description:High-calorie diets lead hepatic steatosis and to the development of non-alcoholic fatty liver disease (NAFLD), which can evolve over many years into the inflammatory form non-alcoholic steatohepatits (NASH) posing a risk for the development of hepatocellular carcinoma (HCC). Due to the diet and the liver alteration, the axis between liver and gut is disturbed, resulting in gut microbiome alterations. Consequently, detecting these gut microbiome alterations repre-sents a promising strategy for early NASH and HCC detection. We analyzed medical parame-ters and the fecal metaproteome of 19 healthy controls, 32 NASH, and 29 HCC patients target-ing the discovery of diagnostic biomarkers. Here, NASH and HCC resulted in increased in-flammation status and shifts within the composition of the gut microbiome. Increased abun-dance of kielin/chordin, E3 ubiquitin ligase, and nucleophosmin 1 represented valuable fecal biomarkers indicating disease-related changes in the liver. Whereas a single biomarker failed to separate NASH and HCC, machine learning-based classification algorithms provided 0.86% accuracy in distinguishing between controls, NASH, and HCC. Conclusion: Fecal metaproteomics enables early detection of NASH and HCC by providing single biomarkers and ma-chine learning-based metaprotein panels.