MS Annika 2.0 Identifies Cross-Linked Peptides in MS2-MS3-Based Workflows at High Sensitivity and Specificity.

Cross-linking mass spectrometry has become a powerful tool for the identification of protein-protein interactions and for gaining insight into the structures of proteins. We previously published MS Annika, a cross-linking search engine which can accurately identify cross-linked peptides in MS2 spectra from a variety of different MS-cleavable cross-linkers. In this publication, we present MS Annika 2.0, an updated version implementing a new search algorithm that, in addition to MS2 level, only supports the processing of data from MS2-MS3-based approaches for the identification of peptides from MS3 spectra, and introduces a novel scoring function for peptides identified across multiple MS stages. Detected cross-links are validated by estimating the false discovery rate (FDR) using a target-decoy approach. We evaluated the MS3-search-capabilities of MS Annika 2.0 on five different datasets covering a variety of experimental approaches and compared it to XlinkX and MaXLinker, two other cross-linking search engines. We show that MS Annika detects up to 4 times more true unique cross-links while simultaneously yielding less false positive hits and therefore a more accurate FDR estimation than the other two search engines. All mass spectrometry proteomics data along with result files have been deposited to the ProteomeXchange consortium via the PRIDE partner repository with the dataset identifier PXD041955.

Mimicked synthetic ribosomal protein complex for benchmarking crosslinking mass spectrometry workflows.

Cross-linking mass spectrometry has matured to a frequently used tool for the investigation of protein structures as well as interactome studies up to a system-wide level. The growing community generated a broad spectrum of applications, linker types, acquisition strategies and specialized data analysis tools, which makes it challenging to decide for an appropriate analysis workflow. Here, we report a large and flexible synthetic peptide library as reliable instrument to benchmark crosslink workflows. Additionally, we provide a tool, IMP-X-FDR, that calculates the real, experimentally validated, FDR, compares results across search engine platforms and analyses crosslink properties in an automated manner. We apply the library with 6 commonly used linker reagents and analyse the data with 6 established search engines. We thereby show that the correct algorithm and search setting choice is highly important to improve identification rate and reliability. We reach identification rates of up to ~70 % of the theoretical maximum (i.e. 700 unique lysine-lysine cross-links) while maintaining a real false-discovery-rate of <3 % at cross-link level with high reproducibility, representatively showing that our test system delivers valuable and statistically solid results.

Chromoplast differentiation in bell pepper (Capsicum annuum) fruits.

We report here a detailed analysis of the proteome adjustments that accompany chromoplast differentiation from chloroplasts during bell pepper (Capsicum annuum) fruit ripening. While the two photosystems are disassembled and their constituents degraded, the cytochrome b6 f complex, the ATPase complex, and Calvin cycle enzymes are maintained at high levels up to fully mature chromoplasts. This is also true for ferredoxin (Fd) and Fd-dependent NADP reductase, suggesting that ferredoxin retains a central role in the chromoplasts' redox metabolism. There is a significant increase in the amount of enzymes of the typical metabolism of heterotrophic plastids, such as the oxidative pentose phosphate pathway (OPPP) and amino acid and fatty acid biosynthesis. Enzymes of chlorophyll catabolism and carotenoid biosynthesis increase in abundance, supporting the pigment reorganization that goes together with chromoplast differentiation. The majority of plastid encoded proteins decline but constituents of the plastid ribosome and AccD increase in abundance. Furthermore, the amount of plastid terminal oxidase (PTOX) remains unchanged despite a significant increase in phytoene desaturase (PDS) levels, suggesting that the electrons from phytoene desaturation are consumed by another oxidase. This may be a particularity of non-climacteric fruits such as bell pepper that lack a respiratory burst at the onset of fruit ripening.

A protocol for studying structural dynamics of proteins by quantitative crosslinking mass spectrometry and data-independent acquisition.

Quantitative crosslinking mass spectrometry (QCLMS) reveals structural details of protein conformations in solution. QCLMS can benefit from data-independent acquisition (DIA), which maximises accuracy, reproducibility and throughput of the approach. This DIA-QCLMS protocol comprises of three main sections: sample preparation, spectral library generation and quantitation. The DIA-QCLMS workflow supports isotope-labelling as well as label-free quantitation strategies, uses xiSEARCH for crosslink identification, and xiDIA-Library to create a spectral library for a peptide-centric quantitative approach. We integrated Spectronaut, a leading quantitation software, to analyse DIA data. Spectronaut supports DIA-QCLMS data to quantify crosslinks. It can be used to reveal the structural dynamics of proteins and protein complexes, even against a complex background. In combination with photoactivatable crosslinkers (photo-DIA-QCLMS), the workflow can increase data density and better capture protein dynamics due to short reaction times. Additionally, this can reveal conformational changes caused by environmental influences that would otherwise affect crosslinking itself, such as changing pH conditions. SIGNIFICANCE: This protocol is an detailed step-by-step description on how to implement our previously published DIA-QCLMS workflow (Müller et al. Mol Cell Proteomics. 2019 Apr;18(4):786-795). It includes sample preparation for QCLMS, Optimization of DIA strategies, implementation of the Spectronaut software and required python scripts and guideline on how to analyse quantitative crosslinking data. The DIA-QCLMS workflow widen the scope for a range of new crosslinking applications and this step-by-step protocol enhances the accessibility to a broad scientific user base.

Quantitative Photo-crosslinking Mass Spectrometry Revealing Protein Structure Response to Environmental Changes.

Protein structures respond to changes in their chemical and physical environment. However, studying such conformational changes is notoriously difficult, as many structural biology techniques are also affected by these parameters. Here, the use of photo-crosslinking, coupled with quantitative crosslinking mass spectrometry (QCLMS), offers an opportunity, since the reactivity of photo-crosslinkers is unaffected by changes in environmental parameters. In this study, we introduce a workflow combining photo-crosslinking using sulfosuccinimidyl 4,4'-azipentanoate (sulfo-SDA) with our recently developed data-independent acquisition (DIA)-QCLMS. This novel photo-DIA-QCLMS approach is then used to quantify pH-dependent conformational changes in human serum albumin (HSA) and cytochrome C by monitoring crosslink abundances as a function of pH. Both proteins show pH-dependent conformational changes resulting in acidic and alkaline transitions. 93% and 95% of unique residue pairs (URP) were quantifiable across triplicates for HSA and cytochrome C, respectively. Abundance changes of URPs and hence conformational changes of both proteins were visualized using hierarchical clustering. For HSA we distinguished the N-F and the N-B form from the native conformation. In addition, we observed for cytochrome C acidic and basic conformations. In conclusion, our photo-DIA-QCLMS approach distinguished pH-dependent conformers of both proteins.

Data-independent Acquisition Improves Quantitative Cross-linking Mass Spectrometry.

Quantitative cross-linking mass spectrometry (QCLMS) reveals structural detail on altered protein states in solution. On its way to becoming a routine technology, QCLMS could benefit from data-independent acquisition (DIA), which generally enables greater reproducibility than data-dependent acquisition (DDA) and increased throughput over targeted methods. Therefore, here we introduce DIA to QCLMS by extending a widely used DIA software, Spectronaut, to also accommodate cross-link data. A mixture of seven proteins cross-linked with bis[sulfosuccinimidyl] suberate (BS3) was used to evaluate this workflow. Out of the 414 identified unique residue pairs, 292 (70%) were quantifiable across triplicates with a coefficient of variation (CV) of 10%, with manual correction of peak selection and boundaries for PSMs in the lower quartile of individual CV values. This compares favorably to DDA where we quantified cross-links across triplicates with a CV of 66%, for a single protein. We found DIA-QCLMS to be capable of detecting changing abundances of cross-linked peptides in complex mixtures, despite the ratio compression encountered when increasing sample complexity through the addition of E. coli cell lysate as matrix. In conclusion, the DIA software Spectronaut can now be used in cross-linking and DIA is indeed able to improve QCLMS.

On the Reproducibility of Label-Free Quantitative Cross-Linking/Mass Spectrometry.

Quantitative cross-linking/mass spectrometry (QCLMS) is an emerging approach to study conformational changes of proteins and multi-subunit complexes. Distinguishing protein conformations requires reproducibly identifying and quantifying cross-linked peptides. Here we analyzed the variation between multiple cross-linking reactions using bis[sulfosuccinimidyl] suberate (BS3)-cross-linked human serum albumin (HSA) and evaluated how reproducible cross-linked peptides can be identified and quantified by LC-MS analysis. To make QCLMS accessible to a broader research community, we developed a workflow that integrates the established software tools MaxQuant for spectra preprocessing, Xi for cross-linked peptide identification, and finally Skyline for quantification (MS1 filtering). Out of the 221 unique residue pairs identified in our sample, 124 were subsequently quantified across 10 analyses with coefficient of variation (CV) values of 14% (injection replica) and 32% (reaction replica). Thus our results demonstrate that the reproducibility of QCLMS is in line with the reproducibility of general quantitative proteomics and we establish a robust workflow for MS1-based quantitation of cross-linked peptides. Graphical Abstract ᅟ.