A spatial single-cell type multiplex map of human spermatogenesis

Understanding how transcriptional programs are translated into functional protein landscapes within intact tissues remains a major challenge in biology. While single-cell RNA sequencing (scRNA-seq) has enabled high-resolution identification of cellular states, corresponding protein expression within its spatial context remains poorly resolved at scale. Here, we present a scalable framework that integrates scRNA-seq with multiplex immunohistochemistry (mIHC) and automated image analysis to achieve spatially resolved, single-cell-level protein mapping across human spermatogenesis.

Using this approach, we quantified the expression of nearly 500 proteins across 12 discrete germ cell states within intact human testis tissue, generating a high-resolution spatiotemporal proteomic atlas. Comparative analysis of mRNA and protein expression revealed widespread temporal discordance, indicating that transcriptional state is not always predictive of protein abundance. Notably, we identify delayed translation of key regulators such as PIWIL4, whose protein expression peaks at later differentiation stages than its mRNA expression.

Together, our results establish a generalizable strategy for proteome-wide spatial mapping of single-cell states and demonstrate the importance of integrating protein-level measurements to resolve cellular identity and function in complex tissues.