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ARS Home » Northeast Area » Ithaca, New York » Robert W. Holley Center for Agriculture & Health » Emerging Pests and Pathogens Research » Research » Publications at this Location » Publication #333945

Research Project: Management and Biology of Arthropod Pests and Arthropod-borne Plant Pathogens

Location: Emerging Pests and Pathogens Research

Title: A general method for targeted quantitative cross-linking mass spectrometry

Author
item CHAVEZ, JUAN - University Of Washington
item ENG, JIMMY - University Of Washington
item Heck, Michelle
item RIVERA, KEITH - Cold Spring Harbor Laboratory
item ZHONG, XUEFEI - University Of Washington
item WU, XIA - University Of Washington
item SCHWEPPE, DEVIN - University Of Washington
item ALLEN, TERRENCE - Cold Spring Harbor Laboratory
item KHURGEL, MOSHE - Cold Spring Harbor Laboratory
item KUMAR, AKHILSH - Cold Spring Harbor Laboratory
item LAMPROPOULOS, ATHANASIOS - Cold Spring Harbor Laboratory
item LARSSON, MARTEN - Cold Spring Harbor Laboratory
item MAITY, SHUVADEEP - Cold Spring Harbor Laboratory
item MOROZOV, YAROSLAV - Cold Spring Harbor Laboratory
item PATHMASIRI, WIMAL - Cold Spring Harbor Laboratory
item PEREZ-NEUT, MATHEW - Cold Spring Harbor Laboratory
item PINEYRO-RUIZ, CORINESS - Cold Spring Harbor Laboratory
item POLINA, ELIZABETH - Cold Spring Harbor Laboratory
item POST, STEPHANIE - Cold Spring Harbor Laboratory
item RIDER, MARK - Cold Spring Harbor Laboratory
item TOKMINA-ROSZYK, DOROTA - Cold Spring Harbor Laboratory
item PARRINE SANT'ANA, DEBORA VIERA - Cold Spring Harbor Laboratory
item BRUCE, JAMES - University Of Washington

Submitted to: PLoS ONE
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 11/16/2016
Publication Date: 12/20/2016
Citation: Chavez, J.D., Eng, J.K., Cilia, M., Rivera, K., Zhong, X., Wu, X., Schweppe, D., Allen, T., Khurgel, M., Kumar, A., Lampropoulos, A., Larsson, M., Maity, S., Morozov, Y., Pathmasiri, W., Perez-Neut, M., Pineyro-Ruiz, C., Polina, E., Post, S., Rider, M., Tokmina-Roszyk, D., Parrine Sant'Ana, D., Bruce, J.E. 2016. A general method for targeted quantitative cross-linking mass spectrometry. PLoS One. 11(12):e0167547.

Interpretive Summary: Approaches that can measure how protein structures and protein interactions change under various conditions can be very useful to study dynamic biological problems such as host-vector-pathogen interactions. We describe a general method to quantify protein structure and protein interaction information using mass spectrometry. We conducted a study in a lab that specializes in mass spectrometry-based protein interaction technology as well as in a course designed to teach biologists with little training in this area how to make these complex measurements. The students were able to replicate the data produced by the expert lab, confirming the broad usefulness of the general method to quantify protein structure and protein interactions.

Technical Abstract: Chemical cross-linking mass spectrometry (XL-MS) provides protein structural information by identifying covalently linked proximal amino acid residues on protein surfaces. The information gained by this technique is complementary to other structural biology methods such as x-ray crystallography, NMR and cryo-electron microscopy[1]. The extension of traditional quantitative proteomics methods with chemical cross-linking can provide information on the structural dynamics of protein structures and protein complexes. The identification and quantitation of cross-linked peptides remains challenging for the general community, requiring specialized expertise ultimately limiting more widespread adoption of the technique. We describe a general method for targeted quantitative mass spectrometric analysis of cross-linked peptide pairs. We report the adaptation of the widely used, open source software package Skyline, for the analysis of quantitative XL-MS data as a means for data analysis and sharing of methods. We demonstrate the utility and robustness of the method with a cross-laboratory study and present data that is supported by and validates previously published data on quantified cross-linked peptide pairs. This advance provides an easy to use resource so that any lab with access to a LC-MS system capable of performing targeted quantitative analysis (e.g., Thermo QE+) can quickly and accurately measure dynamic changes in protein structure and protein interactions.