scholarly journals Evaluation of bottom-up and top-down mass spectrum identifications with different customized protein sequences databases

Author(s):  
Ziwei Li ◽  
Bo He ◽  
Weixing Feng

Abstract Motivation Generally, bottom-up and top-down are two complementary approaches for proteoforms identification. The inference of proteoforms relies on searching mass spectra against an accurate proteoform sequence database. A customized protein sequence database derived by RNA-Seq data can be used to better identify the proteoform existed in a studied species. However, the quality of sequences in customized databases which constructed by different strategies affect the performances of mass spectrometry (MS) identification. Additionally, performances of identifications between bottom-up and top-down using customized databases are also needed to be evaluated Results Three customized databases were constructed with different strategies separately. Two of them were based on translating assembled transcripts with or without genomic annotation, and the third one is a variant-extending protein database. By testing with bottom-up and top-down MS data separately, a variant-extending protein database could identify not only the most number of spectra but also the alleles expressed at the same time in diploid cells. An assembled database could identify the spectrum missed in reference database and amino acid (AA) alterations existed in studied species. Availability and implementation Experimental results demonstrated that the proteoform sequences in an annotated database are more suitable for identifying AA alterations and peptide sequences missed in reference database. An unannotated database instead of a reference proteome database gets an enough high sensitivity of identifying mass spectra. The variant-extending reference database is the most sensitive to identify mass spectra and single AA variants Supplementary information Supplementary data are available at Bioinformatics online.

2019 ◽  
Vol 35 (18) ◽  
pp. 3489-3490 ◽  
Author(s):  
Diogo B Lima ◽  
André R F Silva ◽  
Mathieu Dupré ◽  
Marlon D M Santos ◽  
Milan A Clasen ◽  
...  

Abstract Motivation We present the first tool for unbiased quality control of top-down proteomics datasets. Our tool can select high-quality top-down proteomics spectra, serve as a gateway for building top-down spectral libraries and, ultimately, improve identification rates. Results We demonstrate that a twofold rate increase for two E. coli top-down proteomics datasets may be achievable. Availability and implementation http://patternlabforproteomics.org/tdgc, freely available for academic use. Supplementary information Supplementary data are available at Bioinformatics online.


PROTEOMICS ◽  
2017 ◽  
Vol 17 (23-24) ◽  
pp. 1600321 ◽  
Author(s):  
Kira Vyatkina ◽  
Lennard J. M. Dekker ◽  
Si Wu ◽  
Martijn M. VanDuijn ◽  
Xiaowen Liu ◽  
...  

Author(s):  
Xiaolong Cao ◽  
Jinchuan Xing

Abstract Summary As the next-generation sequencing technology becomes broadly applied, genomics and transcriptomics are becoming more commonly used in both research and clinical settings. However, proteomics is still an obstacle to be conquered. For most peptide search programs in proteomics, a standard reference protein database is used. Because of the thousands of coding DNA variants in each individual, a standard reference database does not provide perfect match for many proteins/peptides of an individual. A personalized reference database can improve the detection power and accuracy for individual proteomics data. To connect genomics and proteomics, we designed a Python package PrecisionProDB that is specialized for generating a personized protein database for proteomics applications. PrecisionProDB supports multiple popular file formats and reference databases, and can generate a personized database in minutes. To demonstrate the application of PrecisionProDB, we generated human population-specific reference protein databases with PrecisionProDB, which improves the number of identified peptides by 0.34% on average. In addition, by incorporating cell line-specific variants into the protein database, we demonstrated a 0.71% improvement for peptide identification in the Jurkat cell line. With PrecisionProDB and these datasets, researchers and clinicians can improve their peptide search performance by adopting the more representative protein database or adding population and individual-specific proteins to the search database with minimum increase of efforts. Availabilityand implementation PrecisionProDB and pre-calculated protein databases are freely available at https://github.com/ATPs/PrecisionProDB and https://github.com/ATPs/PrecisionProDB_references. Supplementary information Supplementary data are available at Bioinformatics online.


2010 ◽  
Vol 38 (5) ◽  
pp. 1307-1313 ◽  
Author(s):  
Paul G. Hitchen ◽  
Katie Twigger ◽  
Esmeralda Valiente ◽  
Rebecca H. Langdon ◽  
Brendan W. Wren ◽  
...  

With glycosylation now firmly established across both Archaeal and bacterial proteins, a wide array of glycan diversity has become evident from structural analysis and genomic data. These discoveries have been built in part on the development and application of mass spectrometric technologies to the bacterial glycoproteome. This review highlights recent findings using high sensitivity MS of the large variation of glycans that have been reported on flagellin and pilin proteins of bacteria, using both ‘top down’ and ‘bottom up’ approaches to the characterization of these glycoproteins. We summarize current knowledge of the sugar modifications that have been observed on flagellins and pilins, in terms of both the diverse repertoire of monosaccharides observed, and the assemblage of moieties that decorate many of these sugars.


2014 ◽  
Vol 13 (7) ◽  
pp. 3241-3248 ◽  
Author(s):  
Xiaowen Liu ◽  
Lennard J. M. Dekker ◽  
Si Wu ◽  
Martijn M. Vanduijn ◽  
Theo M. Luider ◽  
...  

PsycCRITIQUES ◽  
2005 ◽  
Vol 50 (19) ◽  
Author(s):  
Michael Cole
Keyword(s):  
Top Down ◽  

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