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Biology subjects

Fasse, A. J.

Publications and source records attributed to Fasse, A. J..

2 recordsLinked to original sources

Sphingolipid metabolism is spatially regulated in the developing embryo by SOXE genes

During epithelial-to-mesenchymal transition (EMT), significant rearrangements occur in plasma membrane protein and lipid content that are important for membrane function and acquisition of cell motility. To gain insight into how neural crest cells regulate their lipid content at the transcriptional level during EMT, here we identify critical enhancer sequences that regulate the expression of SMPD3, a gene responsible for sphingomyelin hydrolysis to produce ceramide, which is necessary for neural crest EMT. We uncovered three enhancer regions within the first intron of the SMPD3 locus that drive reporter expression in distinct spatial and temporal domains, together collectively recapitulating the expression domains of endogenous SMPD3 within the ectodermal lineages. We further dissected one enhancer that is specifically active in the migrating neural crest. By mutating putative transcriptional input sites or knocking down upstream regulators, we find that the SoxE-family transcription factors Sox9 and Sox10 regulate the expression of SMPD3 in migrating neural crest cells. Together these results shed light on how core components of developmental gene regulatory networks interact with metabolic effector genes to control changes in membrane lipid content. HighlightsO_LISMPD3 is expressed in the neural tube, neural crest, and notochord during early development C_LIO_LISMPD3 expression is regulated by at least three intronic enhancers C_LIO_LISox10 and its binding sites are required for expression by a migratory neural crest-specific SMPD3 enhancer C_LIO_LISox10 is a positive regulator of endogenous SMPD3 expression during neural crest migration C_LI

developmental biology↗

Clonal differences underlie variable responses to sequential and prolonged treatment

Cancer cells exhibit dramatic differences in gene expression at the single-cell level which can predict whether they become resistant to treatment. Treatment perpetuates this heterogeneity, resulting in a diversity of cell states among resistant clones. However, it remains unclear whether these differences lead to distinct responses when another treatment is applied or the same treatment is continued. In this study, we combined single-cell RNA-sequencing with barcoding to track resistant clones through prolonged and sequential treatments. We found that cells within the same clone have similar gene expression states after multiple rounds of treatment. Moreover, we demonstrated that individual clones have distinct and differing fates, including growth, survival, or death, when subjected to a second treatment or when the first treatment is continued. By identifying gene expression states that predict clone survival, this work provides a foundation for selecting optimal therapies that target the most aggressive resistant clones within a tumor.

systems biology↗