Biology subjects

Michael, A. R. M.

Publications and source records attributed to Michael, A. R. M..

3 recordsLinked to original sources

bioRxiv2024

Click-linking: a cell-compatible protein crosslinking method based on click chemistry

Crosslinking mass spectrometry (XL-MS) has the potential to map the human interactome at high resolution and with high fidelity, replacing indirect, error prone sampling methods such as affinity pulldown MS. However, the sampling depth of XL-MS remains stubbornly low. We present a novel crosslinking strategy that splits the crosslinking reaction into two sequential and orthogonal coupling events. The method involves pre-stabilizing the spatial proteome with a fixation protocol inspired by immunofluorescence imaging, followed by a stepwise process that begins with extensively labeling surface-accessible lysines in the cell with N-hydroxysuccinimide (NHS)-modified click reagents. We show that a subsequent copper-catalyzed azide-alkyne cycloaddition (CuAAC) reaction of the installed precursors generates crosslinks at levels approaching 30% of the total signal, as demonstrated by a subtractive approach. The method generates no detectable side reactions or obvious distortions of the spatial proteome. Protein-protein interactions (PPIs) are detected at levels approximately 20 times higher than a conventional DSS-based method, outperforming even enrichable crosslinkers.

biochemistry↗

bioRxiv2024

Cell fixation improves performance of in situ crosslinking mass spectrometry while preserving cellular ultrastructure

Crosslinking mass spectrometry (XL-MS) has the potential to map the interactome of the cell with high resolution and depth of coverage. However, current in vivo XL-MS methods are hampered by crosslinkers that demonstrate low cell permeability and require long reaction times. Consequently, interactome sampling is not high and long incubation times can distort the cell, bringing into question the validity any protein interactions identified by the method. We address these issues with a fast formaldehyde-based fixation method applied prior to the introduction of secondary crosslinkers. Using human A549 cells and a range of reagents, we show that 4% formaldehyde fixation with membrane permeabilization preserves cellular ultrastructure and simultaneously improves reaction conditions for in situ XL-MS. Protein labeling yields can be increased even for nominally membrane-permeable reagents, and surprisingly, formaldehyde does not compete with conventional amine-reactive crosslinking reagents. Prefixation with permeabilization uncouples cellular dynamics from crosslinker dynamics, enhancing control over crosslinking yield and permitting the use of any chemical crosslinker.

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↗