Proteomic reference map for sarcopenia research: mass spectrometric identification of key muscle proteins located in the sarcomere, cytoskeleton and the extracellular matrix


Published: 24 May 2024
Abstract Views: 255
PDF: 112
Publisher's note
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

Authors

  • Paul Dowling Department of Biology, Maynooth University, National University of Ireland, Maynooth, Co. Kildare, Ireland; Kathleen Lonsdale Institute for Human Health Research, Maynooth University, Maynooth, Co. Kildare, Ireland.
  • Stephen Gargan Department of Biology, Maynooth University, National University of Ireland, Maynooth, Co. Kildare, Ireland; Kathleen Lonsdale Institute for Human Health Research, Maynooth University, Maynooth, Co. Kildare, Ireland.
  • Margit Zweyer Department of Neonatology and Paediatric Intensive Care, Children’s Hospital, University of Bonn, Bonn, Germany; German Center for Neurodegenerative Diseases, Bonn, Germany.
  • Michael Henry National Institute for Cellular Biotechnology, Dublin City University, Dublin, Ireland. https://orcid.org/0000-0001-5312-4961
  • Paula Meleady National Institute for Cellular Biotechnology, Dublin City University, Dublin, Ireland.
  • Dieter Swandulla Institute of Physiology, Medical Faculty, University of Bonn, Bonn, Germany. https://orcid.org/0000-0003-0923-7090
  • Kay Ohlendieck Department of Biology, Maynooth University, National University of Ireland, Maynooth, Co. Kildare, Ireland; Kathleen Lonsdale Institute for Human Health Research, Maynooth University, Maynooth, Co. Kildare, Ireland. https://orcid.org/0000-0002-6266-4510

Sarcopenia of old age is characterized by the progressive loss of skeletal muscle mass and concomitant decrease in contractile strength. Age-related skeletal muscle dysfunctions play a key pathophysiological role in the frailty syndrome and can result in a drastically diminished quality of life in the elderly. Here we have used mass spectrometric analysis of the mouse hindlimb musculature to establish the muscle protein constellation at advanced age of a widely used sarcopenic animal model. Proteomic results were further analyzed by systems bioinformatics of voluntary muscles. In this report, the proteomic survey of aged muscles has focused on the expression patterns of proteins involved in the contraction-relaxation cycle, membrane cytoskeletal maintenance and the formation of the extracellular matrix. This includes proteomic markers of the fast versus slow phenotypes of myosin-containing thick filaments and actin-containing thin filaments, as well as proteins that are associated with the non-sarcomeric cytoskeleton and various matrisomal layers. The bioanalytical usefulness of the newly established reference map was demonstrated by the comparative screening of normal versus dystrophic muscles of old age, and findings were verified by immunoblot analysis.


Hatton IA, Galbraith ED, Merleau NSC, et al. The human cell count and size distribution. Proc Natl Acad Sci U S A 2023;120:e2303077120. DOI: https://doi.org/10.1073/pnas.2303077120

Frontera WR, Ochala J. Skeletal muscle: a brief review of structure and function. Calcif Tissue Int 2015;96:183-95. DOI: https://doi.org/10.1007/s00223-014-9915-y

Mukund K, Subramaniam S. Skeletal muscle: A review of molecular structure and function, in health and disease. Wiley Interdiscip Rev Syst Biol Med 2020;12:e1462. DOI: https://doi.org/10.1002/wsbm.1462

Brooks SV, Guzman SD, Ruiz LP. Skeletal muscle structure, physiology, and function. Handb Clin Neurol 2023;195:3-16 DOI: https://doi.org/10.1016/B978-0-323-98818-6.00013-3

Pette D, Vrbov G. The Contribution of Neuromuscular Stimulation in Elucidating Muscle Plasticity Revisited. Eur J Transl Myol 2017;27:6368. DOI: https://doi.org/10.4081/ejtm.2017.6368

Ravara B, Giuriati W, Maccarone MC, et al. Optimized progression of Full-Body In-Bed Gym workout: an educational case report. Eur J Transl Myol 2023;33:11525. DOI: https://doi.org/10.4081/ejtm.2023.11525

Seaborne RAE, Ochala J. The dawn of the functional genomics era in muscle physiology. J Physiol 2023;601:1343-52. DOI: https://doi.org/10.1113/JP284206

Robinson NB, Krieger K, Khan FM, et al. The current state of animal models in research: A review. Int J Surg 2019;72:9-13. DOI: https://doi.org/10.1016/j.ijsu.2019.10.015

Navabpour S, Kwapis JL, Jarome TJ. A neuroscientist's guide to transgenic mice and other genetic tools. Neurosci Biobehav Rev 2020;108:732-748. DOI: https://doi.org/10.1016/j.neubiorev.2019.12.013

Serano M, Paolini C, Michelucci A, et al. High-fat diet impairs muscle function and increases the risk of environmental heatstroke in mice. Int J Mol Sci 2022;23:5286. DOI: https://doi.org/10.3390/ijms23095286

Girolami B, Serano M, Michelucci A, et al. Store-operated Ca2+ entry in skeletal muscle contributes to the increase in body temperature during exertional stress. Int J Mol Sci 2022;23:3772. DOI: https://doi.org/10.3390/ijms23073772

Moreno-Jiménez L, Benito-Martín MS, Sanclemente-Alamán I, et al. Murine experimental models of amyotrophic lateral sclerosis: an update. Neurologia (Engl Ed) 2024;39:282-91. DOI: https://doi.org/10.1016/j.nrleng.2021.07.004

Ruberte J, Schofield PN, Sundberg JP, et al. Bridging mouse and human anatomies; a knowledge-based approach to comparative anatomy for disease model phenotyping. Mamm Genome 2023;34:389-407. DOI: https://doi.org/10.1007/s00335-023-10005-4

Vanhooren V, Libert C. The mouse as a model organism in aging research: usefulness, pitfalls and possibilities. Ageing Res Rev 2013;12:8-21. DOI: https://doi.org/10.1016/j.arr.2012.03.010

Ackert-Bicknell CL, Anderson LC, Sheehan S, et al. Aging research using mouse models. Curr Protoc Mouse Biol 2015;5:95-133. DOI: https://doi.org/10.1002/9780470942390.mo140195

Cai N, Wu Y, Huang Y. Induction of accelerated aging in a mouse model. Cells 2022;11:1418. DOI: https://doi.org/10.3390/cells11091418

Christian CJ, Benian GM. Animal models of sarcopenia. Aging Cell 2020;19:e13223. DOI: https://doi.org/10.1111/acel.13223

Xie WQ, He M, Yu DJ, et al. Mouse models of sarcopenia: classification and evaluation. J Cachexia Sarcopenia Muscle 2021;12:538-54. DOI: https://doi.org/10.1002/jcsm.12709

Van Long N, Chien PN, Tung TX, et al. Complementary combination of biomarkers for diagnosis of sarcopenia in C57BL/6J mice. Life Sci 2023;312:121213. DOI: https://doi.org/10.1016/j.lfs.2022.121213

Cruz-Jentoft AJ, Sayer AA. Sarcopenia. Lancet 2019;393:2636-46. Erratum in: Lancet 2019;393:2590. DOI: https://doi.org/10.1016/S0140-6736(19)31138-9

Larsson L, Degens H, Li M, et al. Sarcopenia: aging-related loss of muscle mass and function. Physiol Rev 2019;99:427-511. DOI: https://doi.org/10.1152/physrev.00061.2017

Nishikawa H, Fukunishi S, Asai A, et al. Pathophysiology and mechanisms of primary sarcopenia (Review). Int J Mol Med 2021;48:156. DOI: https://doi.org/10.3892/ijmm.2021.4989

Kim JW, Kim R, Choi H, et al. Understanding of sarcopenia: from definition to therapeutic strategies. Arch Pharm Res 2021;44:876-89. DOI: https://doi.org/10.1007/s12272-021-01349-z

Zheng Y, Feng J, Yu Y, et al. Advances in sarcopenia: mechanisms, therapeutic targets, and intervention strategies. Arch Pharm Res 2024 Apr 9. doi: 10.1007/s12272-024-01493-2. Epub ahead of print. DOI: https://doi.org/10.1007/s12272-024-01493-2

Liu JC, Dong SS, Shen H, Yang DY, Chen BB, Ma XY, Peng YR, Xiao HM, Deng HW. Multi-omics research in sarcopenia: Current progress and future prospects. Ageing Res Rev 2022;76:101576. DOI: https://doi.org/10.1016/j.arr.2022.101576

Rivero-Segura NA, Bello-Chavolla OY, Barrera-Vázquez OS, et al. Promising biomarkers of human aging: In search of a multi-omics panel to understand the aging process from a multidimensional perspective. Ageing Res Rev 2020;64:101164. DOI: https://doi.org/10.1016/j.arr.2020.101164

Pan Y, Ji T, Li Y, Ma L. Omics biomarkers for frailty in older adults. Clin Chim Acta 2020;510:363-72. DOI: https://doi.org/10.1016/j.cca.2020.07.057

Danese E, Montagnana M, Lippi G. Proteomics and frailty: a clinical overview. Expert Rev Proteomics 2018;15:657-64. DOI: https://doi.org/10.1080/14789450.2018.1505511

Fernández-Lázaro D, Garrosa E, Seco-Calvo J, Garrosa M. Potential satellite cell-linked biomarkers in aging skeletal muscle tissue: proteomics and proteogenomics to monitor sarcopenia. Proteomes 2022;10:29. DOI: https://doi.org/10.3390/proteomes10030029

Dowling P, Gargan S, Swandulla D, Ohlendieck K. Fiber-type shifting in sarcopenia of old age: proteomic profiling of the contractile apparatus of skeletal muscles. Int J Mol Sci 2023;24:2415. DOI: https://doi.org/10.3390/ijms24032415

Moaddel R, Ubaida-Mohien C, Tanaka T, et al. Proteomics in aging research: A roadmap to clinical, translational research. Aging Cell 2021;20:e13325. DOI: https://doi.org/10.1111/acel.13325

Dowling P, Swandulla D, Ohlendieck K. Mass spectrometry-based proteomic technology and its application to study skeletal muscle cell biology. Cells 2023;12:2560. DOI: https://doi.org/10.3390/cells12212560

Murphy S, Dowling P, Ohlendieck K. Comparative Skeletal Muscle Proteomics Using Two-Dimensional Gel Electrophoresis. Proteomes 2016;4:27. DOI: https://doi.org/10.3390/proteomes4030027

Burniston JG, Connolly J, Kainulainen H, et al. Label-free profiling of skeletal muscle using high-definition mass spectrometry. Proteomics 2014;14:2339-44. DOI: https://doi.org/10.1002/pmic.201400118

Ohlendieck K. Skeletal muscle proteomics: current approaches, technical challenges and emerging techniques. Skelet Muscle 2011;1:6. DOI: https://doi.org/10.1186/2044-5040-1-6

Deshmukh AS, Murgia M, Nagaraj N, et al. Deep proteomics of mouse skeletal muscle enables quantitation of protein isoforms, metabolic pathways, and transcription factors. Mol Cell Proteomics 2015;14:841-53. DOI: https://doi.org/10.1074/mcp.M114.044222

Højlund K, Yi Z, Hwang H, et al. Characterization of the human skeletal muscle proteome by one-dimensional gel electrophoresis and HPLC-ESI-MS/MS. Mol Cell Proteomics 2008;7:257-67. DOI: https://doi.org/10.1074/mcp.M700304-MCP200

Parker KC, Walsh RJ, Salajegheh M, et al. Characterization of human skeletal muscle biopsy samples using shotgun proteomics. J Proteome Res 2009;8:3265-77. DOI: https://doi.org/10.1021/pr800873q

Murphy S, Zweyer M, Raucamp M, et al. Proteomic profiling of the mouse diaphragm and refined mass spectrometric analysis of the dystrophic phenotype. J Muscle Res Cell Motil 2019;40:9-28. DOI: https://doi.org/10.1007/s10974-019-09507-z

Adhikari S, Nice EC, Deutsch EW, et al. A high-stringency blueprint of the human proteome. Nat Commun 2020;11:5301. DOI: https://doi.org/10.1038/s41467-020-19045-9

Capitanio D, Moriggi M, Gelfi C. Mapping the human skeletal muscle proteome: progress and potential. Expert Rev Proteomics 2017;14:825-39. DOI: https://doi.org/10.1080/14789450.2017.1364996

Gonzalez-Freire M, Semba RD, Ubaida-Mohien C, et al. The Human Skeletal Muscle Proteome Project: a reappraisal of the current literature. J Cachexia Sarcopenia Muscle 2017;8:5-18. DOI: https://doi.org/10.1002/jcsm.12121

Hadrévi J, Hellström F, Kieselbach T, et al. Protein differences between human trapezius and vastus lateralis muscles determined with a proteomic approach. BMC Musculoskelet Disord 2011;12:181. DOI: https://doi.org/10.1186/1471-2474-12-181

Eggers B, Schork K, Turewicz M, et al. Advanced fiber type-specific protein profiles derived from adult murine skeletal muscle. Proteomes 2021;9:28. DOI: https://doi.org/10.3390/proteomes9020028

Murgia M, Nagaraj N, Deshmukh AS, et al. Single muscle fiber proteomics reveals unexpected mitochondrial specialization. EMBO Rep 2015;16:387-95. DOI: https://doi.org/10.15252/embr.201439757

Fomchenko KM, Walsh EM, Yang X, et al. Spatial proteomic approach to characterize skeletal muscle myofibers. J Proteome Res 2021;20:888-94. DOI: https://doi.org/10.1021/acs.jproteome.0c00673

Donoghue P, Doran P, Wynne K, et al. Proteomic profiling of chronic low-frequency stimulated fast muscle. Proteomics 2007;7:3417-30. DOI: https://doi.org/10.1002/pmic.200700262

Dowling P, Murphy S, Ohlendieck K. Proteomic profiling of muscle fibre type shifting in neuromuscular diseases. Expert Rev Proteomics 2016;13:783-99. DOI: https://doi.org/10.1080/14789450.2016.1209416

Hunt LC, Graca FA, Pagala V, et al. Integrated genomic and proteomic analyses identify stimulus-dependent molecular changes associated with distinct modes of skeletal muscle atrophy. Cell Rep 2021;37:109971. DOI: https://doi.org/10.1016/j.celrep.2021.109971

Deshmukh AS, Steenberg DE, Hostrup M, et al. Deep muscle-proteomic analysis of freeze-dried human muscle biopsies reveals fiber type-specific adaptations to exercise training. Nat Commun 2021;12:304. Erratum in: Nat Commun 2021;12:1600. DOI: https://doi.org/10.1038/s41467-020-20556-8

Li FH, Sun L, Wu DS, et al. Proteomics-based identification of different training adaptations of aged skeletal muscle following long-term high-intensity interval and moderate-intensity continuous training in aged rats. Aging (Albany NY) 2019;11:4159-82. Erratum in: Aging (Albany NY) 2019;11:10781-2. DOI: https://doi.org/10.18632/aging.102596

de Sousa Neto IV, Carvalho MM, Marqueti RC, et al. Proteomic changes in skeletal muscle of aged rats in response to resistance training. Cell Biochem Funct 2020;38:500-9. DOI: https://doi.org/10.1002/cbf.3497

Hesketh SJ, Stansfield BN, Stead CA, Burniston JG. The application of proteomics in muscle exercise physiology. Expert Rev Proteomics 2020;17:813-25. DOI: https://doi.org/10.1080/14789450.2020.1879647

Gelfi C, Vasso M, Cerretelli P. Diversity of human skeletal muscle in health and disease: contribution of proteomics. J Proteomics 2011;74:774-95. DOI: https://doi.org/10.1016/j.jprot.2011.02.028

Choi YC, Hong JM, Park KD, et al. Proteomic analysis of the skeletal muscles from dysferlinopathy patients. J Clin Neurosci 2020;71:186-90. DOI: https://doi.org/10.1016/j.jocn.2019.08.068

Gargan S, Dowling P, Zweyer M, et al. Proteomic identification of markers of membrane repair, regeneration and fibrosis in the aged and dystrophic diaphragm. Life (Basel) 2022;12:1679. DOI: https://doi.org/10.3390/life12111679

Giebelstein J, Poschmann G, Højlund K, et al. The proteomic signature of insulin-resistant human skeletal muscle reveals increased glycolytic and decreased mitochondrial enzymes. Diabetologia 2012;55:1114-27. DOI: https://doi.org/10.1007/s00125-012-2456-x

Kruse R, Højlund K. Proteomic study of skeletal muscle in obesity and type 2 diabetes: progress and potential. Expert Rev Proteomics 2018;15:817-828. DOI: https://doi.org/10.1080/14789450.2018.1528147

Shum AMY, Poljak A, Bentley NL, et al. Proteomic profiling of skeletal and cardiac muscle in cancer cachexia: alterations in sarcomeric and mitochondrial protein expression. Oncotarget 2018;9:22001-22. DOI: https://doi.org/10.18632/oncotarget.25146

Gelfi C, Vigano A, Ripamonti M, et al. The human muscle proteome in aging. J Proteome Res 2006;5:1344-53. DOI: https://doi.org/10.1021/pr050414x

Staunton L, Zweyer M, Swandulla D, Ohlendieck K. Mass spectrometry-based proteomic analysis of middle-aged vs. aged vastus lateralis reveals increased levels of carbonic anhydrase isoform 3 in senescent human skeletal muscle. Int J Mol Med 2012;30:723-33. DOI: https://doi.org/10.3892/ijmm.2012.1056

Ohlendieck K. Two-cydye-based 2D-DIGE analysis of aged human muscle biopsy specimens. Methods Mol Biol 2023;2596:265-89. DOI: https://doi.org/10.1007/978-1-0716-2831-7_19

Gueugneau M, Coudy-Gandilhon C, Gourbeyre O, et al. Proteomics of muscle chronological ageing in post-menopausal women. BMC Genomics 2014;15:1165. DOI: https://doi.org/10.1186/1471-2164-15-1165

Baraibar MA, Gueugneau M, Duguez S, et al. Expression and modification proteomics during skeletal muscle ageing. Biogerontology 2013;14:339-52. DOI: https://doi.org/10.1007/s10522-013-9426-7

Théron L, Gueugneau M, Coudy C, et al. Label-free quantitative protein profiling of vastus lateralis muscle during human aging. Mol Cell Proteomics 2014;13:283-94. DOI: https://doi.org/10.1074/mcp.M113.032698

Liao CY, Kennedy BK. Mouse models and aging: longevity and progeria. Curr Top Dev Biol 2014;109:249-85. DOI: https://doi.org/10.1016/B978-0-12-397920-9.00003-2

Ersoy U, Kanakis I, Alameddine M, et al. Lifelong dietary protein restriction accelerates skeletal muscle loss and reduces muscle fibre size by impairing proteostasis and mitochondrial homeostasis. Redox Biol 2024;69:102980. DOI: https://doi.org/10.1016/j.redox.2023.102980

Murphy S, Zweyer M, Henry M, et al. Proteomic analysis of the sarcolemma-enriched fraction from dystrophic mdx-4cv skeletal muscle. J Proteomics 2019;191:212-27. DOI: https://doi.org/10.1016/j.jprot.2018.01.015

Gargan S, Dowling P, Zweyer M, et al. Mass spectrometric profiling of extraocular muscle and proteomic adaptations in the mdx-4cv model of duchenne muscular dystrophy. Life (Basel) 2021;11:595. DOI: https://doi.org/10.3390/life11070595

Dowling P, Gargan S, Zweyer M, et al. Proteome-wide Changes in the mdx-4cv Spleen due to Pathophysiological Cross Talk with Dystrophin-Deficient Skeletal Muscle. iScience 2020;23:101500. DOI: https://doi.org/10.1016/j.isci.2020.101500

Dowling P, Gargan S, Zweyer M, et al. Proteomic profiling of the interface between the stomach wall and the pancreas in dystrophinopathy. Eur J Transl Myol 2021;31:9627. DOI: https://doi.org/10.4081/ejtm.2020.9627

Gargan S, Ohlendieck K. Sample Preparation and Protein Determination for 2D-DIGE Proteomics. Methods Mol Biol 2023;2596:325-37. DOI: https://doi.org/10.1007/978-1-0716-2831-7_22

Wiśniewski JR, Zougman A, Nagaraj N, Mann M. Universal sample preparation method for proteome analysis. Nat Methods 2009;6:359-62. DOI: https://doi.org/10.1038/nmeth.1322

Wiśniewski JR. Filter aided sample preparation - a tutorial. Anal Chim Acta 2019;1090:23-30. DOI: https://doi.org/10.1016/j.aca.2019.08.032

Dowling P, Gargan S, Zweyer M, et al. Protocol for the bottom-up proteomic analysis of mouse spleen. STAR Protoc 2020;1:100196. DOI: https://doi.org/10.1016/j.xpro.2020.100196

Mi H, Ebert D, Muruganujan A, et al. PANTHER version 16: a revised family classification, tree-based classification tool, enhancer regions and extensive API. Nucleic Acids Res 2021;49:D394-D403. DOI: https://doi.org/10.1093/nar/gkaa1106

Szklarczyk D, Gable AL, Nastou KC, et al. The STRING database in 2021: customizable protein-protein networks, and functional characterization of user-uploaded gene/measurement sets. Nucleic Acids Res 2021;49:D605-12. DOI: https://doi.org/10.1093/nar/gkaa1074

Gargan S, Dowling P, Ohlendieck K. Sample preparation for proteomics and MS from clinical tissue. In Proteomics Mass Spectrometry Methods: Sample Preparation, Protein Digestion, and Research Protocols, 1st ed.; Meleady, P., Ed.; Academic Press: London, United Kingdom, 2024; Chapter 4, pp. 55-77. DOI: https://doi.org/10.1016/B978-0-323-90395-0.00011-5

Doran P, O'Connell K, Gannon J, Kavanagh M, Ohlendieck K. Opposite pathobiochemical fate of pyruvate kinase and adenylate kinase in aged rat skeletal muscle as revealed by proteomic DIGE analysis. Proteomics 2008;8:364-77. DOI: https://doi.org/10.1002/pmic.200700475

Capitanio D, Vasso M, Fania C, et al. Comparative proteomic profile of rat sciatic nerve and gastrocnemius muscle tissues in ageing by 2-D DIGE. Proteomics 2009;9:2004-20. DOI: https://doi.org/10.1002/pmic.200701162

Lombardi A, Silvestri E, Cioffi F, et al. Defining the transcriptomic and proteomic profiles of rat ageing skeletal muscle by the use of a cDNA array, 2D- and Blue native-PAGE approach. J Proteomics 2009;72:708-21. DOI: https://doi.org/10.1016/j.jprot.2009.02.007

Gannon J, Doran P, Kirwan A, Ohlendieck K. Drastic increase of myosin light chain MLC-2 in senescent skeletal muscle indicates fast-to-slow fibre transition in sarcopenia of old age. Eur J Cell Biol 2009;88:685-700. DOI: https://doi.org/10.1016/j.ejcb.2009.06.004

Lourenço Dos Santos S, Baraibar MA, Lundberg S, et al. Oxidative proteome alterations during skeletal muscle ageing. Redox Biol 2015;5:267-74. DOI: https://doi.org/10.1016/j.redox.2015.05.006

Gregorich ZR, Peng Y, Cai W, et al. Top-down targeted proteomics reveals decrease in myosin regulatory light-chain phosphorylation that contributes to sarcopenic muscle dysfunction. J Proteome Res 2016;15:2706-16. DOI: https://doi.org/10.1021/acs.jproteome.6b00244

Capitanio D, Vasso M, De Palma S, et al. Specific protein changes contribute to the differential muscle mass loss during ageing. Proteomics 2016;16:645-56. DOI: https://doi.org/10.1002/pmic.201500395

Doran P, Gannon J, O'Connell K, Ohlendieck K. Aging skeletal muscle shows a drastic increase in the small heat shock proteins alphaB-crystallin/HspB5 and cvHsp/HspB7. Eur J Cell Biol 2007;86:629-40. DOI: https://doi.org/10.1016/j.ejcb.2007.07.003

Dowling P, Trollet C, Negroni E, et al. How can proteomics help to elucidate the pathophysiological crosstalk in muscular dystrophy and associated multi-system dysfunction? Proteomes 2024;12:4. DOI: https://doi.org/10.3390/proteomes12010004

Aslam B, Basit M, Nisar MA, et al. Proteomics: technologies and their applications. J Chromatogr Sci 2017;55:182-96. DOI: https://doi.org/10.1093/chromsci/bmw167

Duong VA, Lee H. Bottom-up proteomics: advancements in sample preparation. Int J Mol Sci 2023;24:5350. DOI: https://doi.org/10.3390/ijms24065350

Miller RM, Smith LM. Overview and considerations in bottom-up proteomics. Analyst 2023;148:475-86. DOI: https://doi.org/10.1039/D2AN01246D

Ercan H, Resch U, Hsu F, et al. A practical and analytical comparative study of gel-based top-down and gel-free bottom-up proteomics including unbiased proteoform detection. Cells 2023;12:747. DOI: https://doi.org/10.3390/cells12050747

Zhang Y, Fonslow BR, Shan B, et al. Protein analysis by shotgun/bottom-up proteomics. Chem Rev 2013;113:2343-94. DOI: https://doi.org/10.1021/cr3003533

Manes NP, Nita-Lazar A. Application of targeted mass spectrometry in bottom-up proteomics for systems biology research. J Proteomics 2018;189:75-90. DOI: https://doi.org/10.1016/j.jprot.2018.02.008

Murphy S, Ohlendieck K. Protein Digestion for 2D-DIGE Analysis. Methods Mol Biol 2023;2596:339-49. DOI: https://doi.org/10.1007/978-1-0716-2831-7_23

Glatter T, Ludwig C, Ahrné E, et al. Large-scale quantitative assessment of different in-solution protein digestion protocols reveals superior cleavage efficiency of tandem Lys-C/trypsin proteolysis over trypsin digestion. J Proteome Res 2012;11:5145-56. DOI: https://doi.org/10.1021/pr300273g

Giansanti P, Tsiatsiani L, Low TY, Heck AJ. Six alternative proteases for mass spectrometry-based proteomics beyond trypsin. Nat Protoc 2016;11:993-1006. DOI: https://doi.org/10.1038/nprot.2016.057

Dau T, Bartolomucci G, Rappsilber J. Proteomics using protease alternatives to trypsin benefits from sequential digestion with trypsin. Anal Chem 2020;92:9523-7. DOI: https://doi.org/10.1021/acs.analchem.0c00478

Duong VA, Park JM, Lee H. Review of three-dimensional liquid chromatography platforms for bottom-up proteomics. Int J Mol Sci 2020;21:1524. DOI: https://doi.org/10.3390/ijms21041524

Shah AD, Goode RJA, Huang C, et al. LFQ-analyst: an easy-to-use interactive web platform to analyze and visualize label-free proteomics data preprocessed with MaxQuant. J Proteome Res 2020;19:204-211. DOI: https://doi.org/10.1021/acs.jproteome.9b00496

Distler U, Sielaff M, Tenzer S. Label-free proteomics of quantity-limited samples using ion mobility-assisted data-independent acquisition mass spectrometry. Methods Mol Biol 2021;2228:327-339. DOI: https://doi.org/10.1007/978-1-0716-1024-4_23

Matzinger M, Mayer RL, Mechtler K. Label-free single cell proteomics utilizing ultrafast LC and MS instrumentation: A valuable complementary technique to multiplexing. Proteomics 2023;23:e2200162. DOI: https://doi.org/10.1002/pmic.202200162

Raddatz K, Albrecht D, Hochgrfe F, et al. A proteome map of murine heart and skeletal muscle. Proteomics 2008;8:1885-97. DOI: https://doi.org/10.1002/pmic.200700902

Drexler HC, Ruhs A, Konzer A, et al. On marathons and Sprints: an integrated quantitative proteomics and transcriptomics analysis of differences between slow and fast muscle fibers. Mol Cell Proteomics 2012;11:M111.010801. DOI: https://doi.org/10.1074/mcp.M111.010801

Dowling P, Zweyer M, Swandulla D, Ohlendieck K. Characterization of Contractile Proteins from Skeletal Muscle Using Gel-Based Top-Down Proteomics. Proteomes 2019;7:25. Erratum in: Proteomes 2019;7. DOI: https://doi.org/10.3390/proteomes7030028

Reed PW, Densmore A, Bloch RJ. Optimization of large gel 2D electrophoresis for proteomic studies of skeletal muscle. Electrophoresis 2012;33:1263-70. DOI: https://doi.org/10.1002/elps.201100642

Drissi R, Dubois ML, Boisvert FM. Proteomics methods for subcellular proteome analysis. FEBS J 2013;280:5626-34. DOI: https://doi.org/10.1111/febs.12502

Lee YH, Tan HT, Chung MC. Subcellular fractionation methods and strategies for proteomics. Proteomics 2010;10:3935-56. DOI: https://doi.org/10.1002/pmic.201000289

Ploscher M, Granvogl B, Reisinger V, Masanek A, Eichacker LA. Organelle proteomics. Methods Mol Biol 2009;519:65-82. DOI: https://doi.org/10.1007/978-1-59745-281-6_5

Dowling P, Gargan S, Swandulla D, Ohlendieck K. Identification of subproteomic markers for skeletal muscle profiling. Methods Mol Biol 2023;2596:291-302. DOI: https://doi.org/10.1007/978-1-0716-2831-7_20

Holland A, Ohlendieck K. Proteomic profiling of the contractile apparatus from skeletal muscle. Expert Rev Proteomics 2013;10:239-57. DOI: https://doi.org/10.1586/epr.13.20

Lin BL, Song T, Sadayappan S. Myofilaments: Movers and Rulers of the Sarcomere. Compr Physiol 2017;7:675-92. DOI: https://doi.org/10.1002/cphy.c160026

Sweeney HL, Hammers DW. Muscle Contraction. Cold Spring Harb Perspect Biol 2018;10:a023200. DOI: https://doi.org/10.1101/cshperspect.a023200

Schiaffino S, Reggiani C, Murgia M. Fiber type diversity in skeletal muscle explored by mass spectrometry-based single fiber proteomics. Histol Histopathol 2020;35:239-46.

Brunello E, Fusi L. Regulating striated muscle contraction: through thick and thin. Annu Rev Physiol 2024;86:255-75. DOI: https://doi.org/10.1146/annurev-physiol-042222-022728

Henderson CA, Gomez CG, Novak SM, et al. Overview of the muscle cytoskeleton. Compr Physiol 2017;7:891-944. DOI: https://doi.org/10.1002/cphy.c160033

Boppart MD, Mahmassani ZS. Integrin signaling: linking mechanical stimulation to skeletal muscle hypertrophy. Am J Physiol Cell Physiol 2019;317:C629-41. DOI: https://doi.org/10.1152/ajpcell.00009.2019

Dowling P, Gargan S, Murphy S, et al. The dystrophin node as integrator of cytoskeletal organization, lateral force transmission, fiber stability and cellular signaling in skeletal muscle. Proteomes 2021;9:9. DOI: https://doi.org/10.3390/proteomes9010009

Wilson DGS, Tinker A, Iskratsch T. The role of the dystrophin glycoprotein complex in muscle cell mechanotransduction. Commun Biol 2022;5:1022. DOI: https://doi.org/10.1038/s42003-022-03980-y

Wohlgemuth RP, Brashear SE, Smith LR. Alignment, cross linking, and beyond: a collagen architect's guide to the skeletal muscle extracellular matrix. Am J Physiol Cell Physiol 2023;325:C1017-30. DOI: https://doi.org/10.1152/ajpcell.00287.2023

Mahdy MAA. Skeletal muscle fibrosis: an overview. Cell Tissue Res 2019;375:575-88. DOI: https://doi.org/10.1007/s00441-018-2955-2

Dowling P, Gargan S, Zweyer M, et al. Extracellular matrix proteomics: the mdx-4cv mouse diaphragm as a surrogate for studying myofibrosis in dystrophinopathy. Biomolecules 2023;13:1108. DOI: https://doi.org/10.3390/biom13071108

Supporting Agencies

Science Foundation Ireland, Kathleen Lonsdale Institute for Human Health Research

Dowling, P., Gargan, S., Zweyer, M., Henry, M., Meleady, P., Swandulla, D., & Ohlendieck, K. (2024). Proteomic reference map for sarcopenia research: mass spectrometric identification of key muscle proteins located in the sarcomere, cytoskeleton and the extracellular matrix. European Journal of Translational Myology. https://doi.org/10.4081/ejtm.2024.12564

Downloads

Download data is not yet available.

Citations


Similar Articles

You may also start an advanced similarity search for this article.