Direct characterization of overproduced proteins by native mass spectrometry
- 15 January 2020
- journal article
- research article
- Published by Springer Nature in Nature Protocols
- Vol. 15 (2) , 236-265
Abstract
Proteins derived by recombinant technologies must be characterized to ensure quality, consistency and optimal production. These properties are usually assayed following purification procedures that are time consuming and labor intensive. Here, we describe a native mass spectrometry (MS) approach, direct-MS, for rapid characterization of intact overexpressed proteins immediately from crude samples. In this protocol, we discuss the multiple applications of the method and outline the necessary steps required for sample preparation, data collection and interpretation of results. We begin with the sample preparation workflows, which are relevant for recombinant proteins produced within bacteria, those analyzed straight from crude cell lysate, and secreted proteins generated in eukaryotic expression systems that are assessed directly from the growth culture medium. We continue with the mass acquisition steps that enable immediate definition of properties such as expressibility, solubility, assembly state, folding, overall structure, stability, post-translational modifications and associations with biomolecules. We demonstrate the applicability of the method by presenting the characterization of a computationally designed toxin–antitoxin heterodimer, activity and protein-interaction determination of a regulatory protein and detailed glycosylation analysis of a designed intact antibody. Overall, we describe a simple and rapid protocol that is relevant to both prokaryotic and eukaryotic expression systems and can be carried out on multiple mass spectrometers, such as Orbitrap and quadrupole time-of-flight (QTOF)-based mass spectroscopy platforms, that enable intact protein detection. The procedure takes from 30 min to several hours, from sample collection to data acquisition, depending on the depth of MS analysis.Keywords
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