Network-centric analysis of co-fractionated protein complex profiles using SECAT

Benjamin J Bokor; Darvesh Gorhe; Marko Jovanovic; George Rosenberger

doi:10.1016/j.xpro.2023.102293

Network-centric analysis of co-fractionated protein complex profiles using SECAT

STAR Protoc. 2023 May 12;4(2):102293. doi: 10.1016/j.xpro.2023.102293. Online ahead of print.

Authors

Benjamin J Bokor¹, Darvesh Gorhe², Marko Jovanovic², George Rosenberger³

Affiliations

¹ Department of Biological Sciences, Columbia University, New York City, NY 10027, USA. Electronic address: bjb2181@columbia.edu.
² Department of Biological Sciences, Columbia University, New York City, NY 10027, USA.
³ Department of Systems Biology, Columbia University, New York City, NY 10032, USA. Electronic address: gr2578@cumc.columbia.edu.

Abstract

The Size-Exclusion Chromatography Analysis Toolkit (SECAT) elucidates protein complex dynamics using co-fractionated bottom-up mass spectrometry (CF-MS) data. Here, we present a protocol for the network-centric analysis and interpretation of CF-MS profiles using SECAT. We describe the technical steps for preprocessing, scoring, semi-supervised machine learning, and quantification, including common pitfalls and their solutions. We further provide guidance for data export, visualization, and the interpretation of SECAT results to discover dysregulated proteins and interactions, supporting new hypotheses and biological insights. For complete details on the use and execution of this protocol, please refer to Rosenberger et al. (2020).¹.

Keywords: Bioinformatics; Mass Spectrometry; Proteomics.

Abstract

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