Improvements in proteomic metrics of low abundance proteins through proteome equalization using ProteoMiner prior to MudPIT

dc.creatorFonslow, Bryan R.
dc.creatorCarvalho, Paulo C.
dc.creatorAcademia, Katrina
dc.creatorFreeby, Steve
dc.creatorXu, Tao
dc.creatorNakorchevsky, Aleksey
dc.creatorPaulus, Aran
dc.creatorYates, John R.
dc.date2018-03-27T16:33:55Z
dc.date2018-03-27T16:33:55Z
dc.date2011
dc.date.accessioned2023-09-26T23:33:54Z
dc.date.available2023-09-26T23:33:54Z
dc.identifierFONSLOW, Bryan R. et al. Improvements in proteomic metrics of low abundance proteins through proteome equalization using ProteoMiner prior to MudPIT. J Proteome Res., v.10, n.8, p.3690-3700, Aug. 2011.
dc.identifier1535-3893
dc.identifierhttps://www.arca.fiocruz.br/handle/icict/25527
dc.identifier10.1021/pr200304u
dc.identifier1535-3907
dc.identifier.urihttps://repositorioslatinoamericanos.uchile.cl/handle/2250/8891931
dc.descriptionIdeally, shotgun proteomics would facilitate the identification of an entire proteome with 100% protein sequence coverage. In reality, the large dynamic range and complexity of cellular proteomes results in oversampling of abundant proteins, while peptides from low abundance proteins are undersampled or remain undetected. We tested the proteome equalization technology, ProteoMiner, in conjunction with Multidimensional Protein Identification Technology (MudPIT) to determine how the equalization of protein dynamic range could improve shotgun proteomics methods for the analysis of cellular proteomes. Our results suggest low abundance protein identifications were improved by two mechanisms: (1) depletion of high abundance proteins freed ion trap sampling space usually occupied by high abundance peptides and (2) enrichment of low abundance proteins increased the probability of sampling their corresponding more abundant peptides. Both mechanisms also contributed to dramatic increases in the quantity of peptides identified and the quality of MS/MS spectra acquired due to increases in precursor intensity of peptides from low abundance proteins. From our large data set of identified proteins, we categorized the dominant physicochemical factors that facilitate proteome equalization with a hexapeptide library. These results illustrate that equalization of the dynamic range of the cellular proteome is a promising methodology to improve low abundance protein identification confidence, reproducibility, and sequence coverage in shotgun proteomics experiments, opening a new avenue of research for improving proteome coverage.
dc.description2030-01-01
dc.formatapplication/pdf
dc.languageeng
dc.publisherAmerican Chemical Society
dc.rightsrestricted access
dc.subjectidentificação de peptídeos
dc.subjectproteômica de espingarda
dc.subjectcobertura proteômica
dc.subjectfaixa dinâmica de abundância de proteína
dc.subjectshotgun proteomics
dc.subjectpeptide identification
dc.subjectproteome coverage
dc.subjectprotein abundance dynamic range
dc.titleImprovements in proteomic metrics of low abundance proteins through proteome equalization using ProteoMiner prior to MudPIT
dc.typeArticle


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