Construction of Protein Sequence Databases for Metaproteomics: A Review of the Current Tools and Databases DOI
Muzaffer Arıkan,

Başak Atabay

Journal of Proteome Research, Journal Year: 2024, Volume and Issue: unknown

Published: Oct. 25, 2024

In metaproteomics studies, constructing a reference protein sequence database that is both comprehensive and not overly large critical for the peptide identification step. Therefore, availability of well-curated databases tools custom construction essential to enhance performance analyses. this review, we first provide an overview by presenting concise historical background, outlining typical experimental bioinformatics workflow, emphasizing crucial step metaproteomics. We then delve into current available building such databases, highlighting their individual approaches, utility, advantages limitations. Next, examine existing detailing scope relevance in research. Then, practical recommendations metaproteomics, along with challenges area. conclude discussion anticipated advancements, emerging trends, future directions

Language: Английский

Metagenome-informed metaproteomics of the human gut microbiome, host, and dietary exposome uncovers signatures of health and inflammatory bowel disease DOI
Rafael Valdés‐Mas, Avner Leshem,

Danping Zheng

et al.

Cell, Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 1, 2025

Language: Английский

Citations

4
Embracing the unknown: Proteomic insights into the human microbiome DOI

Shuqin Zeng,

Alexandre Almeida, Dezhi Mu

et al.

Cell Metabolism, Journal Year: 2025, Volume and Issue: 37(4), P. 799 - 801

Published: April 1, 2025

Language: Английский

Citations

0
Evaluation of imputation and imputation-free strategies for differential abundance analysis in metaproteomics data DOI Creative Commons

Xinyi Mou,

Huaidong Du, Gang Qiao

et al.

Briefings in Bioinformatics, Journal Year: 2025, Volume and Issue: 26(2)

Published: March 1, 2025

Abstract For metaproteomics data derived from the collective protein composition of dynamic multi-organism systems, proportion missing values and dimensions exceeds that observed in single-organism experiments. Consequently, evaluations differential analysis strategies other mass spectrometry (MS) (such as proteomics metabolomics) may not be directly applicable to data. In this study, we systematically evaluated five imputation methods [sample minimum, quantile regression, k-nearest neighbors (KNN), Bayesian principal component (bPCA), random forest (RF)] six imputation-free (moderated t-test, two-part Wilcoxon test, semiparametric abundance analysis, with Bayes shrinkage estimation variance method, Mixture) for simulated metaproteomic datasets based on both data-dependent acquisition MS experiments emerging data-independent The simulation comprised 588 scenarios by considering impacts sample size, fold change between case control, value ratio at nonrandom. Compared methods, KNN, bPCA, RF performed poorly a high missingness large size resulted false-positive risk. We made empirical recommendations balance sensitivity control false positives. moderated t-test was optimal low ratio. test recommended small or comprehensive our study can provide guidance metaproteomics.

Language: Английский

Citations

0
NovoLign: metaproteomics by sequence alignment DOI Creative Commons
Hugo B.C. Kleikamp,

Ramon van der Zwaan,

Ramon van Valderen

et al.

ISME Communications, Journal Year: 2024, Volume and Issue: 4(1)

Published: Jan. 1, 2024

Abstract Tremendous advances in mass spectrometric and bioinformatic approaches have expanded proteomics into the field of microbial ecology. The commonly used spectral annotation method for metaproteomics data relies on database searching, which requires sample-specific databases obtained from whole metagenome sequencing experiments. However, creating these is complex, time-consuming, prone to errors, potentially biasing experimental outcomes conclusions. This asks alternative that can provide rapid orthogonal insights data. Here, we present NovoLign, a de novo pipeline performs sequence alignment sequences complete enables taxonomic profiling complex communities evaluates coverage searches. Furthermore, NovoLign supports creation reference searching ensure comprehensive coverage. We assessed false positive annotations using wide range silico data, including pure strains, laboratory enrichment cultures, synthetic communities, environmental communities. In summary, employs large-scale enable profiling, evaluation outcomes, databases. publicly available via: https://github.com/hbckleikamp/NovoLign.

Language: Английский

Citations

2
Activity-based metaproteomics driven discovery and enzymological characterization of potential α-galactosidases in the mouse gut microbiome DOI Creative Commons
Jianbing Jiang,

Diana Czuchry,

Yan-Xia Ru

et al.

Communications Chemistry, Journal Year: 2024, Volume and Issue: 7(1)

Published: Aug. 16, 2024

The gut microbiota offers an extensive resource of enzymes, but many remain uncharacterized. To distinguish the activities similar annotated proteins and mine potentially applicable ones in microbiome, we applied effective Activity-Based Metaproteomics (ABMP) strategy using a specific activity-based probe (ABP) to screen entire microbiome for directly discovering active enzymes their potential applications, not exploring host-microbiome interactions. By cyclophellitol aziridine α-galactosidases (AGAL), successfully identified characterized several possessing AGAL activities. Cryo-electron microscopy analysis newly enzyme (AGLA5) revealed covalent binding conformations between AGAL5 site ABP, which could provide insights into enzyme's catalytic mechanism. four AGALs have diverse activities, including raffinose family oligosaccharides (RFOs) hydrolysis enzymatic blood group transformation. Collectively, present ABMP platform that facilitates discovery, biochemical activity annotations industrial or biopharmaceutical applications. however, Here, authors apply metaproteomics identify characterize

Language: Английский

Citations

1
Orthrus: an AI-powered, cloud-ready, and open-source hybrid approach for metaproteomics DOI Creative Commons
Yun Chiang, Matthew J. Collins

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2024, Volume and Issue: unknown

Published: Nov. 15, 2024

Abstract While metaproteomics provides invaluable insight into microbial communities and functions, significant bioinformatics challenges persist due to data complexity the limitations of database searching. We introduce Orthrus , a hybrid approach combining transformer-based de novo sequencing ( Casanovo ) searching with rescoring Sage + Mokapot ). Benchmarking against PEAKS ® 11 MaxQuant MetaNovo demonstrates high peptide outputs, taxonomic diversity, proteome coverage. is Python-based accessible all via Google Colaboratory.

Language: Английский

Citations

1
Validation of urine p-cresol glucuronide as renal cell carcinoma non-invasive biomarker DOI
Júlia Oto, Raquel Herranz, P Verger

et al.

Journal of Proteomics, Journal Year: 2024, Volume and Issue: 311, P. 105357 - 105357

Published: Nov. 17, 2024

Language: Английский

Citations

1
Insights on Wet and Dry Workflows for Human Gut Metaproteomics DOI Creative Commons
Valeria Marzano, Stefano Levi Mortera, Lorenza Putignani

et al.

PROTEOMICS, Journal Year: 2024, Volume and Issue: unknown

Published: Dec. 30, 2024

The human gut microbiota (GM) is a community of microorganisms that resides in the gastrointestinal (GI) tract. Recognized as critical element health, functions GM extend beyond GI well-being to influence overall systemic health and susceptibility disease. Among other omic sciences, metaproteomics highlights additional facets make it highly valuable discipline study GM. Indeed, allows protein inventory complex microbial communities. Proteins with associated taxonomic membership function are identified quantified from their constituent peptides by liquid chromatography coupled mass spectrometry analyses querying specific databases (DBs). aim this review was compile comprehensive information on metaproteomic studies GM, focus bacterial component, assist newcomers understanding methods types research conducted field. outlines key steps metaproteomic-based study, such extraction, DB selection, bioinformatic workflow. importance standardization emphasized. In addition, list previously published provided hints for researchers interested investigating role disease states.

Language: Английский

Citations

1
Spectral entropy as a measure of the metaproteome complexity DOI
Haonan Duan, Zhibin Ning, Ailing Zhang

et al.

PROTEOMICS, Journal Year: 2024, Volume and Issue: 24(16)

Published: May 25, 2024

The diversity and complexity of the microbiome's genomic landscape are not always mirrored in its proteomic profile. Despite anticipated diversity, observed complexities microbiome samples often lower than expected. Two main factors contribute to this discrepancy: limitations mass spectrometry's detection sensitivity bioinformatics challenges metaproteomics identification. This study introduces a novel approach evaluating sample directly at full spectrum (MS1) level rather relying on peptide identifications. When analyzing under identical spectrometry conditions, displayed significantly higher complexity, as evidenced by spectral entropy candidate entropy, compared single-species samples. research provides solid evidence for proteomics indicating optimization potential workflow.

Language: Английский

Citations

0
Fecal metaproteomics enables functional characterization of remission in patients with inflammatory bowel disease DOI
M. Wolf,

Julian Lange,

Dirk Benndorf

et al.

medRxiv (Cold Spring Harbor Laboratory), Journal Year: 2024, Volume and Issue: unknown

Published: July 3, 2024

Abstract Background The gut microbiome is an important contributor to the development and course of inflammatory bowel disease (IBD). While changes in composition were observed response IBD therapy using biologics, studies elucidating human microbial proteins pathways dependence on success are sparse. Methods Fecal samples a cohort patients collected before after 14 weeks treatment with three different biologics. Clinical activity scores used determine clinical remission. metaproteomes remitting (n=12) non-remitting compared within both groups assessed over sampling time identify functional potential biomarkers. Results abundance associated intestinal barrier, neutrophilic granulocytes, immunoglobulins significantly decreased patients. In contrast, increase those was There significant metabolism from remission therapy. This included, for example, increased butyrate fermentation. Finally, new biomarkers prediction monitoring could be identified, e.g. lysosome-associated membrane glycoprotein 1, cytotoxicity marker, or anthranilate synthase component 2, part tryptophan metabolism. Conclusions Distinct related inflammation showed whether achieved not. suggests that metaproteomics useful tool therapies.

Language: Английский

Citations

0