Dataset Information

Spatial Proteomic Approach to Characterize Skeletal Muscle Myofibers.

ABSTRACT: Skeletal muscle myofibers have differential protein expression resulting in functionally distinct slow- and fast-twitch types. While certain protein classes are well-characterized, the depth of all proteins involved in this process is unknown. We utilized the Human Protein Atlas (HPA) and the HPASubC tool to classify mosaic expression patterns of staining across 49,600 unique tissue microarray (TMA) images using a visual proteomic approach. We identified 2164 proteins with potential mosaic expression, of which 1605 were categorized as "likely" or "real." This list included both well-known fiber-type-specific and novel proteins. A comparison of the 1605 mosaic proteins with a mass spectrometry (MS)-derived proteomic dataset of single human muscle fibers led to the assignment of 111 proteins to fiber types. We additionally used a multiplexed immunohistochemistry approach, a multiplexed RNA-ISH approach, and STRING v11 to further assign or suggest fiber types of newly characterized mosaic proteins. This visual proteomic analysis of mature skeletal muscle myofibers greatly expands the known repertoire of twitch-type-specific proteins.

SUBMITTER: Fomchenko KM

PROVIDER: S-EPMC8826490 | biostudies-literature | 2021 Jan

REPOSITORIES: biostudies-literature

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Spatial Proteomic Approach to Characterize Skeletal Muscle Myofibers.

Fomchenko Katherine M KM Walsh Elise M EM Yang Xiaoping X Verma Rohan X RX Lin Brian L BL Nieuwenhuis Tim O TO Patil Arun H AH Fox-Talbot Karen K McCall Matthew N MN Kass David A DA Rosenberg Avi Z AZ Halushka Marc K MK

Journal of proteome research 20201130 1

Skeletal muscle myofibers have differential protein expression resulting in functionally distinct slow- and fast-twitch types. While certain protein classes are well-characterized, the depth of all proteins involved in this process is unknown. We utilized the Human Protein Atlas (HPA) and the HPASubC tool to classify mosaic expression patterns of staining across 49,600 unique tissue microarray (TMA) images using a visual proteomic approach. We identified 2164 proteins with potential mosaic expre ...[more]

PMID: 33251806

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Project description:Chikungunya virus (CHIKV) is an arthritogenic alphavirus that acutely causes fever as well as severe joint and muscle pain. Chronic musculoskeletal pain persists in a substantial fraction of patients for months to years after the initial infection, yet we still have a poor understanding of what promotes chronic disease. While replicating virus has not been detected in joint-associated tissues of patients with persistent arthritis nor in various animal models at convalescent time points, viral RNA is detected months after acute infection. To identify the cells that might contribute to pathogenesis during this chronic phase, we developed a recombinant CHIKV that expresses Cre recombinase (CHIKV-3'-Cre). CHIKV-3'-Cre replicated in myoblasts and fibroblasts, and it induced arthritis during the acute phase in mice. Importantly, it also induced chronic disease, including persistent viral RNA and chronic myositis and synovitis similar to wild-type virus. CHIKV-3'-Cre infection of tdTomato reporter mice resulted in a population of tdTomato+ cells that persisted for at least 112 days. Immunofluorescence and flow cytometric profiling revealed that these tdTomato+ cells predominantly were myofibers and dermal and muscle fibroblasts. Treatment with an antibody against Mxra8, a recently defined host receptor for CHIKV, reduced the number of tdTomato+ cells in the chronic phase and diminished the levels of chronic viral RNA, implicating these tdTomato+ cells as the reservoir of chronic viral RNA. Finally, isolation and flow cytometry-based sorting of the tdTomato+ fibroblasts from the skin and ankle and analysis for viral RNA revealed that the tdTomato+ cells harbor most of the persistent CHIKV RNA at chronic time points. Therefore, this CHIKV-3'-Cre and tdTomato reporter mouse system identifies the cells that survive CHIKV infection in vivo and are enriched for persistent CHIKV RNA. This model represents a useful tool for studying CHIKV pathogenesis in the acute and chronic stages of disease.

Dataset Information

Spatial Proteomic Approach to Characterize Skeletal Muscle Myofibers.

Publications

Spatial Proteomic Approach to Characterize Skeletal Muscle Myofibers.

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