High-Sensitivity Proteome-Scale Searches for Crosslinked Peptides Using CRIMP 2.0

Abstract

Crosslinking mass spectrometry (XL-MS) is a valuable technique for generating point-to-point distance measurements in protein space. However, cell-based XL-MS experiments require efficient software that can detect crosslinked peptides with sensitivity and controlled error rates. Many algorithms implement 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 using these strategies. We present a new scoring method that uses a rapid presearch method and a concept inspired by computer vision algorithms to resolve crosslinks from other conflicting reaction products. Searches of several curated crosslink datasets demonstrate high crosslink detection rates, and even the most complex proteome-level searches (using cleavable or noncleavable crosslinkers) can be completed efficiently on a conventional desktop computer. The detection of protein–protein interactions is increased twofold through the inclusion of compositional terms in the scoring equation. The combined functionality is made available as CRIMP 2.0 in the Mass Spec Studio.

Do Not Waste Time─Ensure Success in Your Cross-Linking Mass Spectrometry Experiments before You Begin

“…All raw files were analyzed using Mass Spec Studio 32 (v2.4) CRIMP 2.0, 33 including those from Rey et al. 2021 23 for consistency.…”

Innovation in Cross-Linking Mass Spectrometry Workflows: Toward a Comprehensive, Flexible, and Customizable Data Analysis Platform

“…20 An obvious advantage of Mass spec studio is that it supports multiple custom additions in its user interface, allowing visualization of MS1 and MS2 data in the results interface and allowing users to map cross-linking results directly to protein structures with PyMol (Figure 3D). Besides, the recently updated CRIMP 2.0 integrates an improved two-pass library reduction engine and a new scoring algorithm, 43 allows for a search of both noncleavable and MS-cleavable cross-linkers. However, the overall performance of the engine and its capabilities to identify various cross-linkers remain to be tested.…”

Cell fixation improves performance ofin situcrosslinking mass spectrometry while preserving cellular ultrastructure

“…After crosslink installation, cells are lysed and digested in a standard “bottom-up” workflow common to conventional proteomics routines, generating linked peptides for detection by MS. Crosslinked peptides are minor reaction products and cannot be identified with the conventional database searching strategies used in the proteomics community. New software makes the detection of crosslinks more efficient than ever before 14–18 , but very little progress has been made in improving the crosslinking reaction itself. To faithfully sample both the spatial and temporal properties of the proteome, crosslinkers must cross the cell membrane, perfuse freely throughout the cell, and react quickly.…”