作者
Lindsey Lammlin,Huong X Tran,Aanya Mohan,Michael D Newton,Scarlet Howser,Stephen J Redding,Christina A Capobianco,Kurt D. Hankenson,Alexander J Knights,Tristan Maerz
摘要
Successful generation of high-quality spatial transcriptomics data from murine musculoskeletal tissues has been impeded by the challenge of preserving RNA integrity through the harsh tissue processing steps required for histological sectioning. In particular, the need to thoroughly fix and decalcify mineralized tissues has proven problematic. We detail a comprehensive sample processing pipeline for three common murine musculoskeletal tissue samples, enabling high-quality transcript detection via imaging-based spatial transcriptomics using the Xenium Prime 5K platform from 10x Genomics. Our protocol outlines methodological details for transcardiac perfusion, fixation, decalcification, paraffin processing, and a sample co-embedding strategy facilitating anatomically consistent and simultaneous sectioning of multiple samples onto the spatial transcriptomics slide. Rigorous quality control demonstrates high-quality tissue-specific outcomes across intact knee joints, tibiae, and lumbar spines from adult mice. Our pipeline enabled 70-91% high-quality transcripts across synovium, meniscus, patellar tendon, articular cartilage, subchondral bone, cortical bone, bone marrow, muscle, fracture callus, and dorsal root ganglion tissues. The average number of detected transcripts varied markedly between tissue types - soft tissues such as synovium, patellar tendon, muscle, bone marrow, and callus exhibited ~200 - 400 transcript per cell; mineralized tissues such as subchondral bone, meniscus, and cortical bone exhibited ~ 13 - 150 transcripts per cell; highly active neuronal tissues such as dorsal root ganglion neurons yielded 750 - 1100 transcripts per cell. Canonical cell markers within each tissue confirmed successful identification and representation of key cell types. Through rigorous sample quality assessment at multiple stages of processing, this protocol yields high-quality RNA transcript detection while preserving critical anatomical context and will serve as a valuable tool enabling spatial transcriptomic profiling of intact musculoskeletal tissue samples.