Biology subjects

Sarpe, V.

Publications and source records attributed to Sarpe, V..

3 recordsLinked to original sources

bioRxiv2025

Recommendations for Automating Hydrogen/Deuterium Exchange Mass Spectrometry Measurements using Data-Independent Acquisition Methods

Hydrogen/deuterium exchange mass spectrometry (HX-MS) is a method used to study solution-phase protein structure and dynamics. Despite its many applications, HX-MS is limited in throughput because manual data analysis is still the norm. We previously developed HX-MS2 technology to add a second dimension of deuteration data and promote automated data processing. Data-independent acquisition (DIA) techniques enable this approach, but we require optimized methods for best performance. Using an Orbitrap Eclipse for illustration, we show that ion optics and collision energy settings typical of a proteomics DIA experiment generate maximal peptide retrieval from the DIA library. As few as three MS2 sequence ions are sufficient to generate a deuteration measurement with a precision that exceeds what is possible in traditional HX-MS. DIA window sizes are based on the chromatographic resolution of the method. An inter-scan window offset method is the recommended default configuration for most HX-DIA applications, but an intra-scan overlap method can be tuned for highest performance and is recommended when maximum peptide retrieval is desired. A fully automated HX-MS2 solution consists of Trajan HDX automation technology, an Orbitrap Eclipse mass spectrometer and AutoHX software. We demonstrate its robustness on an extensive time-course analysis of phosphorylase B and an epitope analysis of single domain antibodies (VHHs, nanobodies) specific to the receptor binding domain of SARS-CoV2 spike protein.

biochemistry↗

bioRxiv2023

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

We developed 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-validation 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-validation 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.

biochemistry↗

bioRxiv2023

High sensitivity proteome-scale search for crosslinked peptides using CRIMP 2.0

Crosslinking mass spectrometry (XL-MS) is a valuable technique for the generation of point-to-point distance measurements in protein space. Applications involving in situ chemical crosslinking have created the possibility of mapping whole protein interactomes with high spatial resolution. However, an XL-MS experiment carried out directly on cells requires highly efficient software that can detect crosslinked peptides with sensitivity and controlled error rates. Many algorithmic approaches invoke a filtering strategy designed to reduce the size of the database prior to mounting a search for crosslinks, but concern has been expressed over the possibility of reduced sensitivity with such strategies. Here we present a full upgrade to CRIMP, the crosslinking app in the Mass Spec Studio, which implements a new strategy for the detection of both component peptides in the MS2 spectrum. Using several published datasets, we demonstrate that this pre-searching method is sensitive and fast, permitting whole proteome searches on a conventional desktop computer for both cleavable and noncleavable crosslinkers. We introduce a new strategy for scoring crosslinks, adapted from computer vision algorithms, that properly resolves conflicting XL hits from other crosslinking reaction products, and we present a method for enhancing the detection of protein-protein interactions that relies upon compositional data.

systems biology↗