Biology subjects

Simopoulos, C. M. A.

Publications and source records attributed to Simopoulos, C. M. A..

2 recordsLinked to original sources

bioRxiv2021

MetaProClust-MS1: A tool for clustering metaproteomes using rapid MS1 profiling

Metaproteomics is used to explore the composition, dynamics and function of microbial communities. How-ever, acquiring data by tandem mass spectrometry is time consuming and resource intensive. To mediate this challenge, we present MetaProClust-MS1, a computational framework for microbiome screening developed to reduce the time required for data acquisition by mass spectrometry. In this proof-of-concept study, we tested MetaProClust-MS1 on data acquired using short 15 minute MS1-only mass spectrometry gradients and compared the results to those produced using data acquired by a traditional tandem mass spectrometry approach. MetaProClust-MS1 identified robust microbiome shifts caused by xenobiotics in both datasets. Cluster topologies were also significantly correlated. We demonstrate that MetaProClust-MS1 is able to rapidly screen microbiomes using only short MS1 profiles. This approach can be used to prioritize samples for deep metaproteomic analysis and will be especially useful in large-scale metaproteomic screens or in clinical settings where rapid results are required.

bioinformatics↗

bioRxiv2019

pepFunk, a tool for peptide-centric functional analysis in metaproteomic human gut microbiome studies

Enzymatic digestion of proteins before mass spectrometry analysis is a key process in metaproteomic workflows. Canonical metaproteomic data processing pipelines typically involve matching spectra produced by the mass spectrometer to a theoretical spectra database, followed by matching the identified peptides back to parent proteins. However, the nature of enzymatic digestion produces peptides that can be found in multiple proteins due to conservation or chance, presenting difficulties with protein and functional assignment. To combat this challenge, we developed a peptide-centric metaproteomic workflow focused on the analysis of human gut microbiome samples. Our workflow includes a curated peptide database annotated with KEGG terms and a pathway enrichment analysis adapted for peptide level data. Analysis using our peptide-centric workflow is fast and identifies more enriched KEGG pathways than protein-centric analysis. Our workflow is open source and available as a web application or source code to be run locally.

bioinformatics↗