Quantitative Cross-Linking/Mass Spectrometry Reveals Subtle Protein Conformational Changes

Molecular Systems Biology

et al. 2019

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148

142

We present a concise workflow to enhance the mass spectrometric detection of crosslinked peptides by introducing sequential digestion and the crosslink identification software xiSEARCH. Sequential digestion enhances peptide detection by selective shortening of long tryptic peptides. We demonstrate our simple 12‐fraction protocol for crosslinked multi‐protein complexes and cell lysates, quantitative analysis, and high‐density crosslinking, without requiring specific crosslinker features. This overall approach reveals dynamic protein–protein interaction sites, which are accessible, have fundamental functional relevance and are therefore ideally suited for the development of small molecule inhibitors.

“…C3b monomer and dimer were labelled as described elsewhere (Chen et al, 2016c) and in-gel digested with trypsin. Samples were divided into four parts and desalted using C18-StageTips.…”

Section: Methods and Protocolsmentioning

confidence: 99%

Section: Sequential Digestion Increases the Number Of Identified Crosmentioning

confidence: 99%

An integrated workflow for crosslinking mass spectrometry

Mendes

Molecular Systems Biology

et al. 2019

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148

142

“…The identified crosslinked peptides were quantified based on their precursor MS signals. Quantitation was carried out with a semi-automated workflow using Pinpoint software (Thermo Fisher Scientific) (7).…”

Section: Methodsmentioning

confidence: 99%

Quantitative cross-linking/mass spectrometry using isotope-labeled cross-linkers and MaxQuant

Cox

et al. 2016

Preprint

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The function of proteins is often linked to conformational rearrangements. Quantitative cross-linking/mass spectrometry (QCLMS) 1 using isotope-labeled cross-linkers (1-4) is emerging as a new strategy to study such conformation changes of proteins (5). Applications include the trans-membrane protein complex F-type ATPases (6), the multidomain protein C3 converting into C3b (7), modeling the structure of iC3 (8) and the maturation of the proteasome lid complex (9). These show that the QCLMS approach has great potential for detecting protein conformational changes in macro protein assemblies and possibly also complex protein mixtures such as large protein networks. However, great challenges result from the size and complexity of data sets generated when studying such large and complex protein systems.Manually interrogating QCLMS data (6, 10) by experts can be superior to the performance of automated algorithms, however it is also time consuming, subject to human handling errors and invites the omission of important controls. Consequently, a benchmark study (7) relied on a semiautomated quantitation setup for cross-linking data by exploring the functionality of a quantitative proteomics software Pinpoint (Thermo Fisher Scientific, San Jose, CA). However, still, manually inspecting and correcting quantitation results from Pinpoint was tedious, required expertise and will become increasingly impractical as data size increases. Recently, Kukacka et al. presented a workflow using mMass at the example of calmodulin (17 kDa) in presence and absence of Ca 2ϩ (11). However, the scalability of this approach remains to be shown. As a prove-of-principle, we established a computational workflow to quantify the signals of crosslinked peptides in an automated manner (5). We developed an elementary computational tool, XiQ (5), which allowed us to accurately quantify our model data set. Yet, XiQ has three major drawbacks: (1) it is not optimized for chromatographic feature detection; (2) XiQ is a command line based application and lacks an easy user interface; (3) XiQ does not visualize its output and hence does not facilitate manual inspection and validation.To overcome these disadvantages, we exploited the wellestablished chromatographic feature detection function and 1 The abbreviations used are: BS 3 , Bis[sulfosuccinimidyl] suberate; CLMS, Cross-linking/mass spectrometry; MS1, the initial mass-tocharge-ratio (m/z) spectrum collected for all components in a sample;. QCLMS, Quantitative cross-linking/mass spectrometry.

“…Using our tried and tested workflow ( Fig. 2A) (32,33), a total of 94 cross-linked pairs of amino acid residues ("cross-links") were quantified for these two proteins (Fig. 3A).…”

Section: C3(h 2 O) Versus C3 Comparison Confirms Structural Rearrangementioning

confidence: 99%

Structure of complement C3(H₂O) revealed by quantitative cross-linking/mass spectrometry and modeling

Pellarin²,

et al. 2016

Preprint

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The slow but spontaneous and ubiquitous formation of C3(H 2 O), the hydrolytic and conformationally rearranged product of C3, initiates antibody-independent activation of the complement system that is a key first line of antimicrobial defense. The structure of C3(H 2 O) has not been determined. Here we subjected C3(H 2 O) to quantitative cross-linking/mass spectrometry (QCLMS). This revealed details of the structural differences and similarities between C3(H 2 O) and C3, as well as between C3(H 2 O) and its pivotal proteolytic cleavage product, C3b, which shares functionally similarity with C3(H 2 O). Considered in combination with the crystal structures of C3 and C3b, the QCMLS data suggest that C3(H 2 O) generation is accompanied by the migration of the thioester-containing domain of C3 from one end of the molecule to the other. This creates a stable C3b-like platform able to bind the zymogen, factor B, or the regulator, factor H. Integration of available crystallographic and QCLMS data allowed the determination of a 3D model of the C3(H 2 O) domain architecture. The unique arrangement of domains thus observed in C3(H 2 O), which retains the anaphylatoxin domain (that is excised when C3 is enzymatically activated to C3b), can be used to rationalize observed differences between C3(H 2 O) and C3b in terms of complement activation and regulation. Molecular & Cellular Proteomics