Umek Nejc, Meznarič Marija, Šink Žiga, Blagotinšek Cokan Kaja, Prosenc Zmrzljak Uršula, Horvat Simon
Institute of Anatomy, Faculty of Medicine, University of Ljubljana, Vrazov Trg 2, 1000, Ljubljana, Slovenia.
Molecular Biology Laboratory, BIA Separations CRO, Labena Ltd., Ljubljana, Slovenia.
Cell Tissue Res. 2025 Mar;399(3):291-302. doi: 10.1007/s00441-024-03945-z. Epub 2025 Jan 9.
Traditional transcriptomic studies often overlook the complex heterogeneity of skeletal muscle, as they typically isolate RNA from mixed muscle fibre and cell populations, resulting in an averaged transcriptomic profile that obscures fibre type-specific differences. This study assessed the potential of the recently developed Xenium platform for high-resolution spatial transcriptomic analysis of human skeletal muscle histological sections. Human vastus lateralis muscle samples from two individuals were analysed using the Xenium platform and Human Multi-Tissue and Cancer Panel targeting 377 genes complemented by staining of successive sections for Myosin Heavy Chain isoforms to differentiate between type 1 and type 2 muscle fibres. Manual segmentation of muscle fibres allowed accurate comparisons of transcript densities across fibre types and subcellular regions, overcoming limitations in the platform's automated segmentation. The analysis revealed higher transcript density in type 1 fibres, particularly in nuclear and perinuclear areas, and identified 191 out of 377 genes with differential expression between muscle fibres and perimysium. Genes such as PROX1, S100A1, LGR5, ACTA2, and LPL exhibited higher expression in type 1 fibres, whereas PEBP4, CAVIN1, GATM, and PVALB in type 2 fibres. We demonstrated that the Xenium platform is capable of high-resolution spatial in situ transcriptomic analysis of skeletal muscle histological sections. This study demonstrates that, with manual segmentation, the Xenium platform effectively performs fibre type-specific transcriptomic analysis, providing new insights into skeletal muscle biology.
传统的转录组学研究常常忽略骨骼肌复杂的异质性,因为它们通常从混合的肌纤维和细胞群体中分离RNA,从而得到一个平均的转录组图谱,掩盖了纤维类型特异性差异。本研究评估了最近开发的Xenium平台用于人类骨骼肌组织学切片高分辨率空间转录组分析的潜力。使用Xenium平台和针对377个基因的人类多组织和癌症分析板对两名个体的股外侧肌样本进行分析,并对连续切片进行肌球蛋白重链异构体染色,以区分1型和2型肌纤维。通过手动分割肌纤维,可以准确比较不同纤维类型和亚细胞区域的转录本密度,克服了该平台自动分割的局限性。分析显示1型纤维中的转录本密度更高,尤其是在细胞核和核周区域,并在377个基因中鉴定出了191个在肌纤维和肌束膜之间存在差异表达的基因。PROX1、S100A1、LGR5、ACTA2和LPL等基因在1型纤维中表达较高,而PEBP4、CAVIN1、GATM和PVALB在2型纤维中表达较高。我们证明了Xenium平台能够对骨骼肌组织学切片进行高分辨率空间原位转录组分析。这项研究表明,通过手动分割,Xenium平台能够有效地进行纤维类型特异性转录组分析,为骨骼肌生物学提供了新的见解。