One gene can give rise to many functionally distinct proteoforms, each of which has a characteristic molecular mass. Top-down mass spectrometry enables the analysis of intact proteins and proteoforms. Here members of the Consortium for Top-Down Proteomics provide a decision tree that guides researchers to robust protocols for mass analysis of intact proteins (antibodies, membrane proteins and others) from mixtures of varying complexity. We also present cross-platform analytical benchmarks using a protein standard sample, to allow users to gauge their proficiency.
In recent years, there has been increasing interest in top-down mass spectrometry (TDMS) approaches for protein analysis, driven both by technological advancements and efforts such as those by the multinational Consortium for Top-Down Proteomics (CTDP). Today, diverse sample preparation and ionization methods are employed to facilitate TDMS analysis of denatured and native proteins and their complexes. The goals of these studies vary, ranging from protein and proteoform identification, to determination of the binding site of a (non)covalently-bound ligand, and in some cases even with the aim to study the higher order structure of proteins and complexes. Currently, however, no widely accepted terminology exists to precisely and unambiguously distinguish between the different types of TDMS experiments that can be performed. Instead, ad hoc developed terminology is often used, which potentially complicates communication of top-down and allied methods and their results. In this communication, we consider the different types of top-down (or top-down-related) MS experiments that have been performed and reported, and define distinct categories based on the protocol used and type(s) of information that can be obtained. We also consider the different possible conventions for distinguishing between middle- and top-down MS, based on both sample preparation and precursor ion mass. We believe that the proposed framework presented here will prove helpful for researchers to communicate about TDMS and will be an important step toward harmonizing and standardizing this growing field.
Graphical Abstract
Pairing light and heavy chains in monoclonal antibodies (mAbs) using top-down (TD) or middle-down (MD) mass spectrometry (MS) may complement the sequence information on single chains provided by highthroughput genomic sequencing and bottom-up proteomics, favoring the rational selection of drug candidates. The 50 kDa F(ab) subunits of mAbs are the smallest structural units that contain the required information on chain pairing. These subunits can be enzymatically produced from whole mAbs and interrogated in their intact form by TD/MD MS approaches. However, the high structural complexity of F(ab) subunits requires increased sensitivity of the modern TD/MD MS for a comprehensive structural analysis. To address this and similar challenges, we developed and applied a multiplexed TD/MD MS workflow based on spectral averaging of tandem mass spectra (MS/MS) across multiple liquid chromatography (LC)−MS/MS runs acquired in reduced or full profile mode using an Orbitrap Fourier transform mass spectrometer (FTMS). We first benchmark the workflow using myoglobin as a reference protein, and then validate it for the analysis of the 50 kDa F(ab) subunit of a therapeutic mAb, trastuzumab. Obtained results confirm the envisioned benefits in terms of increased signal-to-noise ratio of product ions from utilizing multiple LC−MS/MS runs for TD/MD protein analysis using mass spectral averaging. The workflow performance is compared with the earlier introduced multiplexed TD/MD MS workflow based on transient averaging in Orbitrap FTMS. For the latter, we also report on enabling absorption mode FT processing and demonstrate its comparable performance to the enhanced FT (eFT) spectral representation.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.