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Deep Protein and Gene Maps Reveal How Pig Muscle Fibers Flip From Slow to Fast

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In a study that could reshape how scientists think about muscle development, meat quality, and even human disease modeling, researchers in China have charted the molecular choreography of skeletal muscle formation in pigs from the womb to young adulthood. By combining two powerful techniques—next-generation proteomics and transcriptomics—the team traced how fast-twitch and slow-twitch muscle fibers emerge, diverge, and mature across six carefully chosen developmental stages. Their findings, published in Advanced Biotechnology, pinpoint a surprisingly narrow window after birth when muscle fibers commit to their metabolic fates, and they identify a little-studied kinase called NEK3 as a molecular brake on fast-twitch muscle differentiation.

The research focused on the Bama miniature pig, a small breed from Guangxi in southern China prized both for its excellent meat quality and its growing role as a biomedical model for human research. The team collected samples from two anatomically distinct muscles at six time points: embryonic days 57, 73, and 90, and postnatal days 1, 28, and 120. The longissimus dorsi, a back muscle dominated by glycolytic type IIB fibers, represents the fast-twitch archetype, while the semitendinosus, rich in oxidative type I fibers, embodies the slow-twitch phenotype. This dual-region, dual-time design allowed the researchers to separate the effects of anatomy from the effects of developmental time—a distinction that many earlier studies, which sampled only single muscles or single stages, could not make.

Technically, the proteomic work was ambitious. The team employed non-targeted data-independent acquisition mass spectrometry, or nDIA, applied for the first time to porcine embryonic skeletal muscle fibers. Using an Orbitrap Astral mass spectrometer with 300 DIA windows and high-resolution scanning, they identified an average of 6,118 proteins per sample, with a range spanning roughly 3,500 to 7,400. The transcriptomic side relied on Illumina NovaSeq 6000 sequencing, capturing an average of 13,354 genes per sample. Together, these datasets covered the vast majority of the expressed muscle proteome and transcriptome, giving the researchers an unusually complete view of how gene activity and protein abundance change in parallel—and, crucially, where they diverge.

The most striking pattern to emerge was temporal rather than spatial. Across developmental stages, the researchers identified 3,509 differentially abundant proteins, dwarfing the 272 proteins that differed between the two muscle regions at any given stage. Principal component analysis showed that fetal samples from E57 through E90 clustered tightly together, with correlation coefficients between adjacent fetal stages reaching 0.86. But after birth, the samples separated sharply along the developmental timeline, and the correlation between E90 and P1 dropped to just 0.59—the lowest of any adjacent pair. Birth, in other words, marks a molecular discontinuity, a wholesale reprogramming of the muscle proteome that no other transition in the study approached in magnitude.

Within that postnatal reprogramming, one window stood out. Between postnatal days 1 and 28, the semitendinosus gained more newly expressed proteins than the longissimus dorsi, and the two regions showed significant differences in both protein abundance and the biological processes those proteins supported. A heatmap of mitochondrial respiratory complex proteins revealed that regional differences in oxidative machinery first appeared at P28 and reached their peak at P120. Because oxidative fibers carry far more mitochondrial content than glycolytic fibers, this divergence in mitochondrial protein abundance is a direct molecular signature of the slow-versus-fast fiber split. The finding aligns with older histological work from 1972 showing that pig oxidative and glycolytic fibers become distinguishable between 21 and 28 days after birth—but the new study supplies the protein-level detail that histology alone could never provide.

The integrated analysis also exposed a deep layer of post-transcriptional regulation. Classifying genes by how their RNA and protein levels changed together, the researchers found that more than 90 percent fell into categories showing minimal or discordant changes between the two levels. Most tellingly, the proportion of Type 2 genes—those with substantial protein-level changes but minimal RNA-level changes—jumped from under 10 percent during fetal stages to 12.8 percent at P1, 23 percent at P28, and 27.7 percent at P120. At P28, these Type 2 genes were enriched in ribosome biogenesis, lysosome function, and basal transcription factors, and gene set enrichment analysis linked them to fatty acid metabolism, a pathway known to run at higher activity in slow fibers. At P120, Type 5 genes, whose RNA and protein levels move in opposite directions, were enriched in the mTOR signaling pathway and lipoic acid metabolism. The message is clear: RNA sequencing alone would miss much of what actually drives muscle fiber specialization.

From the protein domain analysis came the study’s headline discovery. The serine/threonine kinase domain S_TKc was enriched in specific abundance trends in both muscles, but the proteins carrying it showed region-specific temporal patterns. One of these, NEK3—Never In Mitosis Gene A-Related Kinase 3—appeared as a differentially abundant protein between the two muscles at P1 with a striking log2 fold change exceeding 10, yet its RNA levels remained identical between regions throughout development. That discrepancy pointed to post-transcriptional control, and it is precisely the kind of regulatory mechanism that only a combined proteomic-transcriptomic approach can catch. The team used AlphaFold3 to model NEK3’s structure, then moved to the laboratory to test its function.

The functional experiments delivered a consistent verdict. When the researchers overexpressed NEK3 in mouse C2C12 myoblasts, MYHC expression dropped significantly, confirmed by both immunofluorescence and quantitative PCR. Western blotting showed that NEK3 overexpression suppressed MYH4, a fast-twitch fiber marker, while boosting MYH7 and PGC-1α, both hallmarks of slow oxidative fibers. The team then repeated the experiments in porcine embryonic muscle progenitor cells isolated from Bama pigs at 35 days post-coitum—a more physiologically relevant system—and observed the same pattern: fewer myotubes formed, and fast-twitch markers declined. NEK3, in short, acts as a conserved negative regulator of fast-twitch muscle fiber differentiation, and its transient, protein-only appearance at P1 suggests it helps orchestrate the fiber-type decisions made in the critical days after birth.

A second regulator, NCOA2, added another layer of nuance. This nuclear receptor coactivator, known to promote myogenic differentiation through the MEF2C pathway, showed distinct temporal patterns in the two muscles. In the fast-twitch longissimus dorsi, NCOA2 abundance began declining at E73 and vanished by P28; in the slow-twitch semitendinosus, the decline started later, at E90, and did not reach zero until P120. Because most fetal pig muscle fibers start life with slow-twitch characteristics, the researchers interpret NCOA2 as a molecular brake on the slow-to-fast transition: its early disappearance in the longissimus dorsi licenses that muscle to become fast, while its persistence in the semitendinosus preserves slow fiber identity deep into maturity.

Finally, the team widened the lens across species. Comparing 1,869 single-copy orthologous genes among pig, human, and mouse skeletal muscle at weaning-equivalent stages—postnatal day 28 in pigs, day 20 in mice, and 7 months in humans—they found that pig-specific high-expression clusters were enriched in skeletal muscle organ development, circulatory system development, and heart development, while pig-specific low-expression clusters involved autophagy and insulin receptor signaling. Intriguingly, genes tied to lung development were also elevated in pigs at this stage, hinting at a coordinated developmental program in which maturing respiratory muscles provide the mechanical forces that drive lung maturation. For pig farmers, the P28 window coincides with weaning, the most economically sensitive moment in production, suggesting that management strategies protecting muscle development during this period could pay dividends in both meat quality and animal health. For biomedical researchers, the study offers a molecular roadmap of muscle maturation in one of the most important animal models of human physiology—and a reminder that the proteins, not just the genes, tell the fuller story.

Subject of Research: Dynamic changes in muscle fiber types across developmental stages of porcine skeletal muscle, analyzed by integrated proteomics and transcriptomics

Article Title: Integrated proteomics and transcriptomics analysis of dynamic changes in muscle fiber types in different regions of porcine skeletal muscle

Article References: Integrated proteomics and transcriptomics analysis of dynamic changes in muscle fiber types in different regions of porcine skeletal muscle. (n.d.). https://doi.org/10.1007/s44307-025-00080-w

Image Credits: AI Generated

DOI: 10.1007/s44307-025-00080-w

Keywords: skeletal muscle, muscle fiber types, proteomics, transcriptomics, Bama miniature pig, NEK3, NCOA2, mitochondria, myogenesis, meat quality, data-independent acquisition, postnatal development

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Tags: Bama miniature pigbioinformatics in muscle researchdata-independent acquisitionfast-twitch vs slow-twitch muscle fibersMeat Qualitymeat quality and muscle fiber compositionmitochondriamolecular regulation of muscle fiber typesmuscle development from embryo to adulthoodmuscle development stages in miniature pigsmuscle fiber commitment window after birthmuscle fiber developmentmuscle fiber typesmyogenesisNCOA2NEK3NEK3 kinase role in muscle differentiationpig as a model for human muscle diseasespostnatal developmentProteomicsproteomics and transcriptomics in pig muscle formationskeletal muscleskeletal muscle fiber differentiationTranscriptomics

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