ArticleBMC genomics2014
Proteogenomic mapping of Mycoplasma hyopneumoniae virulent strain 232.
Article in BMC genomics, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
12 citing papers in PubMed, 21 citations in OpenAlex.
- Comparative evaluation and validation of rapid quantification methods for Mycoplasma hyopneumoniae: development of a PMA-based viability qPCR assay.Scientific reports · 2026Article
- Porcine antibody profiles of 33 Mycoplasma hyopneumoniae fusion proteins from M. hyopneumoniae natural infection but not vaccination.Veterinary medicine and science · 2023Article
- Perspectives for improvement of Mycoplasma hyopneumoniae vaccines in pigs.Veterinary research · 2021Review
- Article
- Mycoplasma hyopneumoniae surface-associated proteases cleave bradykinin, substance P, neurokinin A and neuropeptide Y.Scientific reports · 2019Article
- Development of an indirect ELISA for detecting humoral immunodominant proteins of Mycoplasma hyopneumoniae which can discriminate between inactivated bacterin-induced hyperimmune sera and convalescent sera.BMC veterinary research · 2019Article
- Chickspress: a resource for chicken gene expression.Database : the journal of biological databases and curation · 2019Article
- Mycoplasma hyopneumoniae resides intracellularly within porcine epithelial cells.Scientific reports · 2018Article
- Extracellular Actin Is a Receptor forFrontiers in cellular and infection microbiology · 2018Article
- N-terminomics identifies widespread endoproteolysis and novel methionine excision in a genome-reduced bacterial pathogen.Scientific reports · 2017Article
- Article
- Post-translational processing targets functionally diverse proteins in Mycoplasma hyopneumoniae.Open biology · 2016Article
Corrections and comments
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Authors and funding
7 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundMycoplasma hyopneumoniae causes respiratory disease in swine and contributes to the porcine respiratory disease complex, a major disease problem in the swine industry. The M. hyopneumoniae strain 232 genome is one of the smallest and best annotated microbial genomes, containing only 728 annotated genes and 691 known proteins. Standard protein databases for mass spectrometry only allow for the identification of known and predicted proteins, which if incorrect can limit our understanding of the biological processes at work. Proteogenomic mapping is a methodology which allows the entire 6-frame genome translation of an organism to be used as a mass spectrometry database to help identify unknown proteins as well as correct and confirm existing annotations. This methodology will be employed to perform an in-depth analysis of the M. hyopneumoniae proteome.
resultsProteomic analysis indicates 483 of 691 (70%) known M. hyopneumoniae strain 232 proteins are expressed under the culture conditions given in this study. Furthermore, 171 of 328 (52%) hypothetical proteins have been confirmed. Proteogenomic mapping resulted in the identification of previously unannotated genes gatC and rpmF and 5-prime extensions to genes mhp063, mhp073, and mhp451, all conserved and annotated in other M. hyopneumoniae strains and Mycoplasma species. Gene prediction with Prodigal, a prokaryotic gene predicting program, completely supports the new genomic coordinates calculated using proteogenomic mapping.
conclusionsProteogenomic mapping showed that the protein coding genes of the M. hyopneumoniae strain 232 identified in this study are well annotated. Only 1.8% of mapped peptides did not correspond to genes defined by the current genome annotation. This study also illustrates how proteogenomic mapping can be an important tool to help confirm, correct and append known gene models when using a genome sequence as search space for peptide mass spectra. Using a gene prediction program which scans for a wide variety of promoters can help ensure genes are accurately predicted or not missed completely. Furthermore, protein extraction using differential detergent fractionation effectively increases the number of membrane and cytoplasmic proteins identifiable my mass spectrometry.
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