scholarly journals Optimized cross-linking mass spectrometry for in situ interaction proteomics

2018 ◽  
Author(s):  
Zheng Ser ◽  
Paolo Cifani ◽  
Alex Kentsis

AbstractRecent development of mass spectrometer cleavable protein cross-linkers and algorithms for their spectral identification now permits large-scale cross-linking mass spectrometry (XL-MS). Here, we optimized the use of cleavable disuccinimidyl sulfoxide (DSSO) cross-linker for labeling native protein complexes in live human cells. We applied a generalized linear mixture model to calibrate cross-link peptide-spectra matching (CSM) scores to control the sensitivity and specificity of large-scale XL-MS. Using specific CSM score thresholds to control the false discovery rate, we found that higher-energy collisional dissociation (HCD) and electron transfer dissociation (ETD) can both be effective for large-scale XL-MS protein interaction mapping. We found that the density and coverage of protein-protein interaction maps can be significantly improved through the use of multiple proteases. In addition, the use of sample-specific search databases can be used to improve the specificity of cross-linked peptide spectral matching. Application of this approach to human chromatin labeled in live cells recapitulated known and revealed new protein interactions of nucleosomes and other chromatin-associated complexes in situ. This optimized approach for mapping native protein interactions should be useful for a wide range of biological problems.

2020 ◽  
Author(s):  
Diogo Borges Lima ◽  
Ying Zhu ◽  
Fan Liu

ABSTRACTSoftware tools that allow visualization and analysis of protein interaction networks are essential for studies in systems biology. One of the most popular network visualization tools in biology is Cytoscape, which offers a large selection of plugins for interpretation of protein interaction data. Chemical cross-linking coupled to mass spectrometry (XL-MS) is an increasingly important source for such interaction data, but there are currently no Cytoscape tools to analyze XL-MS results. In light of the suitability of Cytoscape platform but also to expand its toolbox, here we introduce XlinkCyNET, an open-source Cytoscape Java plugin for exploring large-scale XL-MS-based protein interaction networks. XlinkCyNET offers rapid and easy visualization of intra and intermolecular cross-links and the locations of protein domains in a rectangular bar style, allowing subdomain-level interrogation of the interaction network. XlinkCyNET is freely available from the Cytoscape app store: http://apps.cytoscape.org/apps/xlinkcynet and at https://www.theliulab.com/software/xlinkcynet.


2017 ◽  
Vol 114 (7) ◽  
pp. 1732-1737 ◽  
Author(s):  
Devin K. Schweppe ◽  
Juan D. Chavez ◽  
Chi Fung Lee ◽  
Arianne Caudal ◽  
Shane E. Kruse ◽  
...  

Mitochondrial protein interactions and complexes facilitate mitochondrial function. These complexes range from simple dimers to the respirasome supercomplex consisting of oxidative phosphorylation complexes I, III, and IV. To improve understanding of mitochondrial function, we used chemical cross-linking mass spectrometry to identify 2,427 cross-linked peptide pairs from 327 mitochondrial proteins in whole, respiring murine mitochondria. In situ interactions were observed in proteins throughout the electron transport chain membrane complexes, ATP synthase, and the mitochondrial contact site and cristae organizing system (MICOS) complex. Cross-linked sites showed excellent agreement with empirical protein structures and delivered complementary constraints for in silico protein docking. These data established direct physical evidence of the assembly of the complex I–III respirasome and enabled prediction of in situ interfacial regions of the complexes. Finally, we established a database and tools to harness the cross-linked interactions we observed as molecular probes, allowing quantification of conformation-dependent protein interfaces and dynamic protein complex assembly.


2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Sabine Wittig ◽  
Marcelo Ganzella ◽  
Marie Barth ◽  
Susann Kostmann ◽  
Dietmar Riedel ◽  
...  

AbstractSynaptic vesicles are storage organelles for neurotransmitters. They pass through a trafficking cycle and fuse with the pre-synaptic membrane when an action potential arrives at the nerve terminal. While molecular components and biophysical parameters of synaptic vesicles have been determined, our knowledge on the protein interactions in their membranes is limited. Here, we apply cross-linking mass spectrometry to study interactions of synaptic vesicle proteins in an unbiased approach without the need for specific antibodies or detergent-solubilisation. Our large-scale analysis delivers a protein network of vesicle sub-populations and functional assemblies including an active and an inactive conformation of the vesicular ATPase complex as well as non-conventional arrangements of the luminal loops of SV2A, Synaptophysin and structurally related proteins. Based on this network, we specifically target Synaptobrevin-2, which connects with many proteins, in different approaches. Our results allow distinction of interactions caused by ‘crowding’ in the vesicle membrane from stable interaction modules.


2021 ◽  
Author(s):  
Christian H Ihling ◽  
Lolita Piersimoni ◽  
Marc Kipping ◽  
Andrea Sinz

The combination of cross-linking/mass spectrometry (XL-MS) and ion mobility is still underexplored for conducting protein conformational and protein-protein interaction studies. We present a method for analyzing cross-linking mixtures on a timsTOF Pro mass spectrometer that allows separating ions based on their gas phase mobilities. Cross-linking was performed with three urea-based MS-cleavable cross-linkers that deliver distinct fragmentation patterns for cross-linked species upon collisional activation. The discrimination of cross-linked species from non-cross-linked peptides was readily performed based on their collisional cross sections. We demonstrate the general feasibility of our combined XL-MS/ion mobility approach for three protein systems of increasing complexity: (i) Bovine serum albumin, (ii) E. coli ribosome, and (iii) HEK293T cell nuclear lysates. We identified a total of 508 unique cross-linking sites for BSA, 868 for the E. coli ribosome, and 1,623 unique cross-links for nuclear lysates, corresponding to 1,088 intra- and 535 interprotein interactions and yielding 564 distinct protein-protein interactions. Our results underline the strength of combining XL-MS with ion mobility not only for deriving 3D-structures of single proteins, but also for performing system-wide protein interaction studies.


2017 ◽  
Vol 17 (6) ◽  
pp. 1055-1066 ◽  
Author(s):  
Helena Maria Barysz ◽  
Johan Malmström

Cross-linking mass spectrometry (CLMS) provides distance constraints to study the structure of proteins, multiprotein complexes and protein-protein interactions which are critical for the understanding of protein function. CLMS is an attractive technology to bridge the gap between high-resolution structural biology techniques and proteomic-based interactome studies. However, as outlined in this review there are still several bottlenecks associated with CLMS which limit its application on a proteome-wide level. Specifically, there is an unmet need for comprehensive software that can reliably identify cross-linked peptides from large data sets. In this review we provide supporting information to reason that targeted proteomics of cross-links may provide the required sensitivity to reliably detect and quantify cross-linked peptides and that a reporter ion signature for cross-linked peptides may become a useful approach to increase confidence in the identification process of cross-linked peptides. In addition, the review summarizes the recent advances in CLMS workflows using the analysis of condensin complex in intact chromosomes as a model complex.


2019 ◽  
Author(s):  
Michael Götze ◽  
Claudio Iacobucci ◽  
Christian Ihling ◽  
Andrea Sinz

ABSTRACTWe present a cross-linking/mass spectrometry (XLMS) workflow for performing proteome-wide cross-linking analyses within one week. The workflow is based on the commercially available MS-cleavable cross-linker disuccinimidyl dibutyric urea (DSBU) and can be employed by every lab having access to a mass spectrometer with tandem MS capabilities. We provide an updated version 2.0 of the freeware software tool MeroX, available at www.StavroX.com, that allows conducting fully automated and reliable studies delivering insights into protein-protein interaction networks and protein conformations at the proteome level. We exemplify our optimized workflow for mapping protein-protein interaction networks in Drosophila melanogaster embryos on a system-wide level. From cross-linked Drosophila embryo extracts, we detected 18,037 cross-link spectrum matches corresponding to 5,129 unique cross-linked residues in biological triplicate experiments at 5% FDR (3,098 at 1% FDR). Among these, 1,237 interprotein cross-linking sites were identified that contain valuable information on protein-protein interactions. The remaining 3,892 intra-protein cross-links yield information on conformational changes of proteins in their cellular environment.


2021 ◽  
Vol 118 (32) ◽  
pp. e2023360118
Author(s):  
Andrew Wheat ◽  
Clinton Yu ◽  
Xiaorong Wang ◽  
Anthony M. Burke ◽  
Ilan E. Chemmama ◽  
...  

Defining protein–protein interactions (PPIs) in their native environment is crucial to understanding protein structure and function. Cross-linking–mass spectrometry (XL-MS) has proven effective in capturing PPIs in living cells; however, the proteome coverage remains limited. Here, we have developed a robust in vivo XL-MS platform to facilitate in-depth PPI mapping by integrating a multifunctional MS-cleavable cross-linker with sample preparation strategies and high-resolution MS. The advancement of click chemistry–based enrichment significantly enhanced the detection of cross-linked peptides for proteome-wide analyses. This platform enabled the identification of 13,904 unique lysine–lysine linkages from in vivo cross-linked HEK 293 cells, permitting construction of the largest in vivo PPI network to date, comprising 6,439 interactions among 2,484 proteins. These results allowed us to generate a highly detailed yet panoramic portrait of human interactomes associated with diverse cellular pathways. The strategy presented here signifies a technological advancement for in vivo PPI mapping at the systems level and can be generalized for charting protein interaction landscapes in any organisms.


2019 ◽  
Vol 26 (1) ◽  
pp. 35-43 ◽  
Author(s):  
Natalie K. Garcia ◽  
Galahad Deperalta ◽  
Aaron T. Wecksler

Background: Biotherapeutics, particularly monoclonal antibodies (mAbs), are a maturing class of drugs capable of treating a wide range of diseases. Therapeutic function and solutionstability are linked to the proper three-dimensional organization of the primary sequence into Higher Order Structure (HOS) as well as the timescales of protein motions (dynamics). Methods that directly monitor protein HOS and dynamics are important for mapping therapeutically relevant protein-protein interactions and assessing properly folded structures. Irreversible covalent protein footprinting Mass Spectrometry (MS) tools, such as site-specific amino acid labeling and hydroxyl radical footprinting are analytical techniques capable of monitoring the side chain solvent accessibility influenced by tertiary and quaternary structure. Here we discuss the methodology, examples of biotherapeutic applications, and the future directions of irreversible covalent protein footprinting MS in biotherapeutic research and development. Conclusion: Bottom-up mass spectrometry using irreversible labeling techniques provide valuable information for characterizing solution-phase protein structure. Examples range from epitope mapping and protein-ligand interactions, to probing challenging structures of membrane proteins. By paring these techniques with hydrogen-deuterium exchange, spectroscopic analysis, or static-phase structural data such as crystallography or electron microscopy, a comprehensive understanding of protein structure can be obtained.


2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Sungmin O. ◽  
Rene Orth

AbstractWhile soil moisture information is essential for a wide range of hydrologic and climate applications, spatially-continuous soil moisture data is only available from satellite observations or model simulations. Here we present a global, long-term dataset of soil moisture derived through machine learning trained with in-situ measurements, SoMo.ml. We train a Long Short-Term Memory (LSTM) model to extrapolate daily soil moisture dynamics in space and in time, based on in-situ data collected from more than 1,000 stations across the globe. SoMo.ml provides multi-layer soil moisture data (0–10 cm, 10–30 cm, and 30–50 cm) at 0.25° spatial and daily temporal resolution over the period 2000–2019. The performance of the resulting dataset is evaluated through cross validation and inter-comparison with existing soil moisture datasets. SoMo.ml performs especially well in terms of temporal dynamics, making it particularly useful for applications requiring time-varying soil moisture, such as anomaly detection and memory analyses. SoMo.ml complements the existing suite of modelled and satellite-based datasets given its distinct derivation, to support large-scale hydrological, meteorological, and ecological analyses.


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