Effective protein extraction combined with data independent acquisition analysis reveals a comprehensive and quantifiable insight into the proteomes of articular cartilage and subchondral bone.
Abstract: The objectives of this study was to establish a sensitive and reproducible method to map the cartilage and subchondral bone proteomes in quantitative terms, and mine the proteomes for proteins of particular interest in the pathogenesis of osteoarthritis (OA). The horse was used as a model animal. Protein was extracted from articular cartilage and subchondral bone samples from three horses in triplicate by pressure cycling technology or ultrasonication. Digested proteins were analysed by data independent acquisition based mass spectrometry. Data was processed using a pre-established spectral library as reference database (FDR 1%). We identified to our knowledge the hitherto most comprehensive quantitative cartilage (1758 proteins) and subchondral bone (1482 proteins) proteomes in all species presented to date. Both extraction methods were sensitive and reproducible and the high consistency of the identified proteomes (>97% overlap) indicated that both methods preserved the diversity among the extracted proteins. Proteome mining revealed a substantial number of quantifiable cartilage and bone matrix proteins and proteins involved in osteogenesis and bone remodeling, including ACAN, BGN, PRELP, FMOD, COMP, ACP5, BMP3, BMP6, BGLAP, TGFB1, IGF1, ALP, MMP3, and collagens. A number of proteins, including COMP and TNN, were identified in different protein isoforms with potential unique biological roles. We have successfully developed two sensitive and reproducible non-species specific workflows enabling a comprehensive quantitative insight into the proteomes of cartilage and subchondral bone. This facilitates the prospect of investigating the molecular events at the osteochondral unit in the pathogenesis of OA in future projects.
Copyright © 2021 The Authors. Published by Elsevier Ltd.. All rights reserved.
Publication Date: 2021-09-20 PubMed ID: 34547431DOI: 10.1016/j.joca.2021.09.006Google Scholar: Lookup
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- Journal Article
Summary
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This research article is about the development of a method to map the articular cartilage and subchondral bone proteins quantitatively using a high throughput method, presented through the study of horses. This can lead to a better understanding of osteoarthritis development.
Research Objective
- The primary objective is to create a sensitive, reproducible method capable of mapping the proteins in articular cartilage and subchondral bone, which could aid in understanding the pathogenesis of Osteoarthritis (OA).
- The secondary goal is to identify proteins of particular interest that could be implicated in the development of OA.
Research Methodology
- The study used horses as model animals.
- Protein extraction was carried out from samples of articular cartilage and subchondral bone using ultrasonication or pressure cycling technology.
- A proteomics analytical technique called data independent acquisition based mass spectrometry was used to study the proteins extracted.
- A pre-existing spectral library served as the reference database, with a false discovery rate of 1%.
Results
- The researchers were able to identify a comprehensive quantitative cartilage (1758 proteins) and subchondral bone (1482 proteins) proteomes, which is the largest set for these species to date.
- The protein extraction methods were found to be reproducible and sensitive, indicating a high consistency (>97% overlap) among the identified proteins.
- Proteome mining highlighted a significant count of quantifiable proteins associated with cartilage, bone matrix, osteogenesis, and bone remodeling. Proteins included ACAN, BGN, PRELP, FMOD, COMP, ACP5, BMP3, BMP6, BGLAP, TGFB1, IGF1, ALP, MMP3, and collagens.
- Some proteins were identified in distinct protein isoforms with potentially unique biological roles, such as COMP and TNN.
Implications
- The successful development of two reproducible and sensitive workflows enables a comprehensive quantitative insight into the proteomes of cartilage and subchondral bone in any species.
- This advancement opens the potential for future studies to better understand the molecular events within the osteochondral unit contributory to the pathogenesis of OA.
Cite This Article
APA
Bundgaard L, Åhrman E, Malmström J, Auf dem Keller U, Walters M, Jacobsen S.
(2021).
Effective protein extraction combined with data independent acquisition analysis reveals a comprehensive and quantifiable insight into the proteomes of articular cartilage and subchondral bone.
Osteoarthritis Cartilage, 30(1), 137-146.
https://doi.org/10.1016/j.joca.2021.09.006 Publication
Researcher Affiliations
- Section of Medicine and Surgery, Department of Veterinary Clinical Sciences, University of Copenhagen, 2630 Taastrup, Denmark. Section for Protein Science and Biotherapeutics, DTU Bioengineering, Technical University of Denmark, 2800 Kgs. Lyngby, Denmark. Electronic address: lb@sund.ku.dk.
- Division of Infection Medicine Proteomics, Department of Clinical Sciences, Lund University, Lund 221 84, Sweden. Electronic address: emma.ahrman@gmail.com.
- Division of Infection Medicine Proteomics, Department of Clinical Sciences, Lund University, Lund 221 84, Sweden. Electronic address: johan.malmstrom@med.lu.se.
- Section for Protein Science and Biotherapeutics, DTU Bioengineering, Technical University of Denmark, 2800 Kgs. Lyngby, Denmark. Electronic address: uadk@dtu.dk.
- Section of Medicine and Surgery, Department of Veterinary Clinical Sciences, University of Copenhagen, 2630 Taastrup, Denmark. Electronic address: emw@sund.ku.dk.
- Section of Medicine and Surgery, Department of Veterinary Clinical Sciences, University of Copenhagen, 2630 Taastrup, Denmark. Electronic address: stj@sund.ku.dk.
MeSH Terms
- Animals
- Cartilage, Articular / chemistry
- Chemistry Techniques, Analytical
- Horses
- Proteome / analysis
Conflict of Interest Statement
Conflict of interest The authors declare to have no conflict of interests.
Citations
This article has been cited 3 times.- Dementieva N, Nikitkina E, Shcherbakov Y, Nikolaeva O, Mitrofanova O, Ryabova A, Atroshchenko M, Makhmutova O, Zaitsev A. The Genetic Diversity of Stallions of Different Breeds in Russia.. Genes (Basel) 2023 Jul 24;14(7).
- Schurman CA, Burton JB, Rose J, Ellerby LM, Alliston T, Schilling B. Molecular and Cellular Crosstalk between Bone and Brain: Accessing Bidirectional Neural and Musculoskeletal Signaling during Aging and Disease.. J Bone Metab 2023 Feb;30(1):1-29.
- Gueto-Tettay C, Tang D, Happonen L, Heusel M, Khakzad H, Malmström J, Malmström L. Multienzyme deep learning models improve peptide de novo sequencing by mass spectrometry proteomics.. PLoS Comput Biol 2023 Jan;19(1):e1010457.
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