Automating data analysis for hydrogen/deuterium exchange mass spectrometry using data-independent acquisition methodology

Filandr, Frantisek; Sarpe, Vladimir; Raval, Shaunak; Crowder, D. Alex; Khan, Morgan F.; Douglas, Pauline; Coales, Stephen; Viner, Rosa; Syed, Aleem; Tainer, John A.; Lees-Miller, Susan P.; Schriemer, David C.

doi:10.1038/s41467-024-46610-3

Title: Automating data analysis for hydrogen/deuterium exchange mass spectrometry using data-independent acquisition methodology

Journal Article · 11 March 2024 · Nature Communications

DOI: https://doi.org/10.1038/s41467-024-46610-3 · OSTI ID:2470753

Filandr, Frantisek ^[1]; Sarpe, Vladimir ^[1]; Raval, Shaunak ^[1]; Crowder, D. Alex ^[1]; Khan, Morgan F. ^[1]; Douglas, Pauline ^[1]; Coales, Stephen ^[2];

^[3];

^[4]; Tainer, John A. ^[5];

^[1];

^[1]

Univ. of Calgary, AB (Canada)
Trajan Scientific & Medical, Raleigh, NC (United States)
Thermo Fisher Scientific, San Jose, CA (United States)
Harvard Medical School, Boston, MA (United States)
Univ. of Texas, Houston, TX (United States). MD Anderson Cancer Center; Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)

We present a hydrogen/deuterium exchange workflow coupled to tandem mass spectrometry (HX-MS²) that supports the acquisition of peptide fragment ions alongside their peptide precursors. The approach enables true auto-curation of HX data by mining a rich set of deuterated fragments, generated by collisional-induced dissociation (CID), to simultaneously confirm the peptide ID and authenticate MS¹-based deuteration calculations. The high redundancy provided by the fragments supports a confidence assessment of deuterium calculations using a combinatorial strategy. The approach requires data-independent acquisition (DIA) methods that are available on most MS platforms, making the switch to HX-MS² straightforward. Importantly, we find that HX-DIA enables a proteomics-grade approach and wide-spread applications. Considerable time is saved through auto-curation and complex samples can now be characterized and at higher throughput. We illustrate these advantages in a drug binding analysis of the ultra-large protein kinase DNA-PKcs, isolated directly from mammalian cells.

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Research Organization:: Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)

Sponsoring Organization:: USDOE; Canada Discovery Grants; National Institutes of Health (NIH)

Grant/Contract Number:: AC02-05CH11231

OSTI ID:: 2470753

Journal Information:: Nature Communications, Journal Name: Nature Communications Journal Issue: 1 Vol. 15; ISSN 2041-1723

Publisher:: Nature Publishing GroupCopyright Statement

Country of Publication:: United States

Language:: English

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