4.6 Article

Unraveling the hidden universe of small proteins in bacterial genomes

期刊

MOLECULAR SYSTEMS BIOLOGY
卷 15, 期 2, 页码 -

出版社

WILEY
DOI: 10.15252/msb.20188290

关键词

mass spectroscopy; mycoplasmas; protein prediction; random forest classifier; small proteins

资金

  1. Spanish Ministry of Economy, Industry and Competitiveness (MEIC)
  2. Spanish Ministry of Economy and Competitiveness, Centro de Excelencia Severo Ochoa
  3. European Research Council (ERC) under the European Union [670216]
  4. CERCA Programme/Generalitat de Catalunya
  5. European Regional Development Fund (ERDF) project from Instituto Carlos III (ISCIII, Accion Estrategica en Salud 2016) [CP16/00094]
  6. Secretaria d'Universitats i Recerca del Departament d'Economia i Coneixement de la Generalitat de Catalunya [2014SGR678]
  7. Instituto de Salud Carlos III from the Spanish Government [PT13/0001]
  8. European Research Council (ERC) [670216] Funding Source: European Research Council (ERC)

向作者/读者索取更多资源

Identification of small open reading frames (smORFs) encoding small proteins (<= 100 amino acids; SEPs) is a challenge in the fields of genome annotation and protein discovery. Here, by combining a novel bioinformatics tool (RanSEPs) with -omics approaches, we were able to describe 109 bacterial small ORFomes. Predictions were first validated by performing an exhaustive search of SEPs present in Mycoplasma pneumoniae proteome via mass spectrometry, which illustrated the limitations of shotgun approaches. Then, RanSEPs predictions were validated and compared with other tools using proteomic datasets from different bacterial species and SEPs from the literature. We found that up to 16 +/- 9% of proteins in an organism could be classified as SEPs. Integration of RanSEPs predictions with transcriptomics data showed that some annotated non-coding RNAs could in fact encode for SEPs. A functional study of SEPs highlighted an enrichment in the membrane, translation, metabolism, and nucleotide-binding categories. Additionally, 9.7% of the SEPs included a N-terminus predicted signal peptide. We envision RanSEPs as a tool to unmask the hidden universe of small bacterial proteins.

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