Proteogenomic Analysis of Mycobacterium smegmatis Using High Resolution Mass Spectrometry.

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The integration of experimental data collected at the proteome level using high resolution mass spectrometry allows for improvements in genome annotation by providing evidence for novel gene models, while validating or modifying others. Here, we report the results of a proteogenomic analysis of a reference strain of Mycobacterium smegmatis (mc(2)155), a fast growing model organism for the pathogenic Mycobacterium tuberculosis-the causative agent for Tuberculosis. By integrating high throughput LC/MS/MS proteomic data with genomic six frame translation and ab initio gene prediction databases, a total of 2887 ORFs were identified, including 2810 ORFs annotated to a Reference protein, and 63 ORFs not previously annotated to a Reference protein. Further, the translational start site (TSS) was validated for 558 Reference proteome gene models, while upstream translational evidence was identified for 81. In addition, N-terminus derived peptide identifications allowed for downstream TSS modification of a further 24 gene models. We validated the existence of six previously described interrupted coding sequences at the peptide level, and provide evidence for four novel frameshift positions. Analysis of peptide posterior error probability (PEP) scores indicates high-confidence novel peptide identifications and shows that the genome of M. smegmatis mc(2)155 is not yet fully annotated. Data are available via ProteomeXchange with identifier PXD003500.", "claims": [{"id": "claim-method", "statement": "As non-normal PEP score distributions were found, the non-parametric Kruskal–Wallis analysis of variance test was chosen to investigate for differences between the groups—using the kruskal.test function from the R stats package, followed by post-hoc analysis with a two-sided Dunn test (Dunn, 1964) with Bonferroni correction using the dunnTest function from the R FSA package (Ogle, 2016).", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:27092112", "locator": "sections[9] \"Proteogenomic analysis\" paragraph 9", "quote": "As non-normal PEP score distributions were found, the non-parametric Kruskal–Wallis analysis of variance test was chosen to investigate for differences between the groups—using the kruskal.test function from the R stats package, followed by post-hoc analysis with a two-sided Dunn test (Dunn, 1964) with Bonferroni correction using the dunnTest function from the R FSA package (Ogle, 2016)."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium (Vizcaíno et al., 2014) via the PRIDE partner repository (Vizcaíno et al., 2013) with the dataset identifier PXD003500 and the data is freely available4.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:27092112", "locator": "sections[8] \"Database search using maxquant\" paragraph 2", "quote": "The mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium (Vizcaíno et al., 2014) via the PRIDE partner repository (Vizcaíno et al., 2013) with the dataset identifier PXD003500 and the data is freely available4."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": null, "steps": [{"id": "read_published_estimate", "order": 1, "name": "Read the published estimate from the source", "kind": "other", "state": "complete", "blocked_on": null, "description": "The claim, method and evidence span published with the source article.", "duration_hours": null, "parameters": {}, "inputs": ["source:pmid:27092112"], "outputs": ["the published estimate and its evidence"], "instruments": [], "reagents": []}, {"id": "obtain_source_data", "order": 2, "name": "Obtain the source data from the named repository", "kind": "data-preparation", "state": "complete", "blocked_on": null, "description": "The GEO series accession resolves and its sample accessions are listed. 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