Format

Send to

Choose Destination
J Proteomics. 2016 Oct 21;149:64-68. doi: 10.1016/j.jprot.2016.04.042. Epub 2016 Apr 29.

Data Independent Acquisition analysis in ProHits 4.0.

Author information

1
Centre for Systems Biology, Lunenfeld-Tanenbaum Research Institute, Sinai Health System, Toronto, Ontario, Canada.
2
Department of Pathology, University of Michigan, Ann Arbor, USA; Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, USA.
3
Center for Computational Mass Spectrometry, University of California, San Diego, La Jolla, California, USA; Department of Computer Science and Engineering, University of California, San Diego, La Jolla, California, USA.
4
Institute for Research in Immunology and Cancer, Université de Montréal, Montréal, Québec, Canada.
5
Princess Margaret Cancer Institute, Department of Medical Biophysics, University of Toronto, Ontario, Canada.
6
Center for Computational Mass Spectrometry, University of California, San Diego, La Jolla, California, USA; Department of Computer Science and Engineering, University of California, San Diego, La Jolla, California, USA; Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California, San Diego, La Jolla, California, USA.
7
Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Singapore; Institute of Molecular and Cell Biology, Agency for Science, Technology, and Research, Singapore, Singapore.
8
Centre for Systems Biology, Lunenfeld-Tanenbaum Research Institute, Sinai Health System, Toronto, Ontario, Canada; Department of Molecular Genetics, University of Toronto, Toronto, Ontario, Canada. Electronic address: gingras@lunenfeld.ca.

Abstract

Affinity purification coupled with mass spectrometry (AP-MS) is a powerful technique for the identification and quantification of physical interactions. AP-MS requires careful experimental design, appropriate control selection and quantitative workflows to successfully identify bona fide interactors amongst a large background of contaminants. We previously introduced ProHits, a Laboratory Information Management System for interaction proteomics, which tracks all samples in a mass spectrometry facility, initiates database searches and provides visualization tools for spectral counting-based AP-MS approaches. More recently, we implemented Significance Analysis of INTeractome (SAINT) within ProHits to provide scoring of interactions based on spectral counts. Here, we provide an update to ProHits to support Data Independent Acquisition (DIA) with identification software (DIA-Umpire and MSPLIT-DIA), quantification tools (through DIA-Umpire, or externally via targeted extraction), and assessment of quantitative enrichment (through mapDIA) and scoring of interactions (through SAINT-intensity). With additional improvements, notably support of the iProphet pipeline, facilitated deposition into ProteomeXchange repositories and enhanced export and viewing functions, ProHits 4.0 offers a comprehensive suite of tools to facilitate affinity proteomics studies.

SIGNIFICANCE:

It remains challenging to score, annotate and analyze proteomics data in a transparent manner. ProHits was previously introduced as a LIMS to enable storing, tracking and analysis of standard AP-MS data. In this revised version, we expand ProHits to include integration with a number of identification and quantification tools based on Data-Independent Acquisition (DIA). ProHits 4.0 also facilitates data deposition into public repositories, and the transfer of data to new visualization tools.

KEYWORDS:

Affinity purification coupled to mass spectrometry; Data Independent Acquisition; Laboratory Information Management System; Mass spectrometry; Protein-protein interactions; Proteomics

PMID:
27132685
PMCID:
PMC5079801
DOI:
10.1016/j.jprot.2016.04.042
[Indexed for MEDLINE]
Free PMC Article

Supplemental Content

Full text links

Icon for Elsevier Science Icon for PubMed Central
Loading ...
Support Center