Literature DB >> 31452088

Bolt: a New Age Peptide Search Engine for Comprehensive MS/MS Sequencing Through Vast Protein Databases in Minutes.

Amol Prakash1, Shadab Ahmad2, Swetaketu Majumder2, Conor Jenkins3, Ben Orsburn4.   

Abstract

Recent increases in mass spectrometry speed, sensitivity, and resolution now permit comprehensive proteomics coverage. However, the results are often hindered by sub-optimal data processing pipelines. In almost all MS/MS peptide search engines, users must limit their search space to a canonical database due to time constraints and q value considerations, but this typically does not reflect the individual genetic variations of the organism being studied. In addition, engines will nearly always assume the presence of only fully tryptic peptides and limit PTMs to a handful. Even on high-performance servers, these search engines are computationally expensive, and most users decide to dial back their search parameters. We present Bolt, a new cloud-based search engine that can search more than 900,000 protein sequences (canonical, isoform, mutations, and contaminants) with 41 post-translation modifications and N-terminal and C-terminal partial tryptic search in minutes on a standard configuration laptop. Along with increases in speed, Bolt provides an additional benefit of improvement in high-confidence identifications. Sixty-one percent of peptides uniquely identified by Bolt may be validated by strong fragmentation patterns, compared with 13% of peptides uniquely identified by SEQUEST and 6% of peptides uniquely identified by Mascot. Furthermore, 30% of unique Bolt identifications were verified by all three software on the longer gradient analysis, compared with only 20% and 27% for SEQUEST and Mascot identifications respectively. Bolt represents, to the best of our knowledge, the first fully scalable, cloud-based quantitative proteomic solution that can be operated within a user-friendly GUI interface. Data are available via ProteomeXchange with identifier PXD012700.

Entities:  

Keywords:  Bolt; Cloud; MS/MS; Mass spectrometry; Mutations; Peptide; Proteomics; Search engine; Sequencing; Variants

Mesh:

Substances:

Year:  2019        PMID: 31452088     DOI: 10.1007/s13361-019-02306-3

Source DB:  PubMed          Journal:  J Am Soc Mass Spectrom        ISSN: 1044-0305            Impact factor:   3.109


  27 in total

1.  Probability-based protein identification by searching sequence databases using mass spectrometry data.

Authors:  D N Perkins; D J Pappin; D M Creasy; J S Cottrell
Journal:  Electrophoresis       Date:  1999-12       Impact factor: 3.535

2.  The Paragon Algorithm, a next generation search engine that uses sequence temperature values and feature probabilities to identify peptides from tandem mass spectra.

Authors:  Ignat V Shilov; Sean L Seymour; Alpesh A Patel; Alex Loboda; Wilfred H Tang; Sean P Keating; Christie L Hunter; Lydia M Nuwaysir; Daniel A Schaeffer
Journal:  Mol Cell Proteomics       Date:  2007-05-27       Impact factor: 5.911

3.  Ultrafast Peptide Label-Free Quantification with FlashLFQ.

Authors:  Robert J Millikin; Stefan K Solntsev; Michael R Shortreed; Lloyd M Smith
Journal:  J Proteome Res       Date:  2017-11-08       Impact factor: 4.466

4.  Operational Experience of an Open-Access, Subscription-Based Mass Spectrometry and Proteomics Facility.

Authors:  Nicholas A Williamson
Journal:  J Am Soc Mass Spectrom       Date:  2018-01-03       Impact factor: 3.109

5.  Method to correlate tandem mass spectra of modified peptides to amino acid sequences in the protein database.

Authors:  J R Yates; J K Eng; A L McCormack; D Schieltz
Journal:  Anal Chem       Date:  1995-04-15       Impact factor: 6.986

Review 6.  Proteogenomics: concepts, applications and computational strategies.

Authors:  Alexey I Nesvizhskii
Journal:  Nat Methods       Date:  2014-11       Impact factor: 28.547

7.  Byonic: advanced peptide and protein identification software.

Authors:  Marshall Bern; Yong J Kil; Christopher Becker
Journal:  Curr Protoc Bioinformatics       Date:  2012-12

8.  MSFragger: ultrafast and comprehensive peptide identification in mass spectrometry-based proteomics.

Authors:  Andy T Kong; Felipe V Leprevost; Dmitry M Avtonomov; Dattatreya Mellacheruvu; Alexey I Nesvizhskii
Journal:  Nat Methods       Date:  2017-04-10       Impact factor: 28.547

9.  An Optimized Shotgun Strategy for the Rapid Generation of Comprehensive Human Proteomes.

Authors:  Dorte B Bekker-Jensen; Christian D Kelstrup; Tanveer S Batth; Sara C Larsen; Christa Haldrup; Jesper B Bramsen; Karina D Sørensen; Søren Høyer; Torben F Ørntoft; Claus L Andersen; Michael L Nielsen; Jesper V Olsen
Journal:  Cell Syst       Date:  2017-06-07       Impact factor: 10.304

10.  Fast and Accurate Protein False Discovery Rates on Large-Scale Proteomics Data Sets with Percolator 3.0.

Authors:  Matthew The; Michael J MacCoss; William S Noble; Lukas Käll
Journal:  J Am Soc Mass Spectrom       Date:  2016-08-29       Impact factor: 3.109

View more
  4 in total

1.  Cloudy with a Chance of Peptides: Accessibility, Scalability, and Reproducibility with Cloud-Hosted Environments.

Authors:  Benjamin A Neely
Journal:  J Proteome Res       Date:  2021-01-29       Impact factor: 4.466

2.  High Performance Computing Framework for Tera-Scale Database Search of Mass Spectrometry Data.

Authors:  Muhammad Haseeb; Fahad Saeed
Journal:  Nat Comput Sci       Date:  2021-08-20

Review 3.  Evaluation of the Sensitivity of Proteomics Methods Using the Absolute Copy Number of Proteins in a Single Cell as a Metric.

Authors:  Benjamin C Orsburn
Journal:  Proteomes       Date:  2021-07-20

Review 4.  Proteome Discoverer-A Community Enhanced Data Processing Suite for Protein Informatics.

Authors:  Benjamin C Orsburn
Journal:  Proteomes       Date:  2021-03-23
  4 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.