Dataset Information

MetaNovo : an open-source pipeline for probabilistic peptide discovery in complex metaproteomic datasets

ABSTRACT: Results We 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 database - but simultaneously identified proteins present in the samples that are derived from known gut organisms that were missed by the previous analyses. Finally, MetaNovo was benchmarked on samples of known microbial composition against matched metagenomic and whole genomic database workflows, yielding many more MS/MS for the expected taxa, with improved taxonomic representation, while also highlighting previously described genome sequencing quality concerns for one of the organisms, and providing evidence for a known sample contaminant without prior expectation. Conclusions By 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 search databases. We show that the MetaNovo approach to mass spectrometry metaproteomics can be more accurate than current gold standard approaches of tailored or matched genomic database searches, identify sample contaminants without prior expectation and that increases in assigned spectra from this approach can yield novel insights into previously unidentified metaproteomic signals - building on the potential for complex mass spectrometry metaproteomic data to speak for itself. The pipeline source code is available on GitHub and documentation is provided to run the software as a singularity-compatible docker image available from the Docker Hub.

INSTRUMENT(S): Q Exactive

ORGANISM(S): Human Gut Metagenome

SUBMITTER: Matthys Potgieter

LAB HEAD: Nicola Mulder

PROVIDER: PXD030708 | Pride | 2023-05-16

REPOSITORIES: Pride

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Project description:We developed a laboratory-scale model to improve our understanding and capacity to assess the biological risks of genetically engineered bacteria and their genetic elements in the natural environment. Our hypothetical scenario concerns an industrial bioreactor failure resulting in the introduction of genetically engineered bacteria to a downstream municipal wastewater treatment plant (MWWTP). As the first step towards developing a model for this scenario, we sampled microbial communities from the aeration basin of a MWWTP at three seasonal time points. Having established a baseline for community composition, we investigated how the community changed when propagated in the laboratory, including cell culture media conditions that could provide selective pressure in future studies. Specifically, using PhyloChip 16S rRNA gene-targeting microarrays, we compared the compositions of sampled communities to those of inoculates propagated in the laboratory in simulated wastewater conditionally amended with various carbon sources (glucose, chloroacetate, D-threonine) or the ionic liquid 1-ethyl-3-methylimidazolium chloride ([C2mim]Cl). Proteobacteria, Bacteroidetes, and Actinobacteria were predominant in aeration basin and laboratory-cultured populations. Laboratory-cultured populations were enriched in Gammaproteobacteria. Enterobacteriaceae and Aeromonadaceae were enriched by glucose, Pseudomonadaceae by chloroacetate and D-threonine, and Burkholderiaceae by high (50 mM) concentrations of chloroacetate. Microbial populations cultured with chloroacetate and D-threonine were more similar to sampled populations than thoes cultured with glucose or [C2mim]Cl. Although observed relative richness in operational taxonomic units was lower for laboratory cultures than for sampled populations, both flask and reactor systems cultured phylogenetically diverse communities. These results importantly provide a foundation for laboratory models of industrial bioreactor failure scenarios. 46 samples, flask and reactor experiments were conducted in triplicate with two exceptions: [C2mim]Cl_flask and No-Carbon_flask treatments had only one sample (no replicates).

Dataset Information

MetaNovo : an open-source pipeline for probabilistic peptide discovery in complex metaproteomic datasets

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