Solute carrier (SLC) expression reveals skeletogenic cell diversity.

Within the developing embryo is a microcosm of cell type diversity. Single cell RNA-sequencing (scRNA-seq) is used to reveal cell types, typically by grouping cells according to their gene regulatory states. However, both across and within these regulatory states are additional layers of cellular diversity represented by the differential expression of genes that govern cell function. Here, we analyzed scRNA-seq data representing the late gastrula stage of Strongylocentrotus purpuratus (purple sea urchin) to understand the patterning of transporters belonging to the ABC and SLC families. These transporters handle diverse substrates from amino acids to signaling molecules, nutrients and xenobiotics. Using transporter-based clustering, we identified unique transporter patterns that are both shared across cell lineages, as well as those that were unique to known cell types. We further explored three patterns of transporter expression in mesodermal cells including secondary mesenchyme cells (pigment cells and blastocoelar cells) and skeletogenic cells (primary mesenchyme cells). The results revealed the enrichment of SMTs potentially involved in nutrient absorption (SLC5A9, SLC7A11, SLC35F3, and SLC52A3) and skeletogenesis (SLC9A3, SLC13A2/3/5, and SLC39A13) in pigment cells and blastocoelar cells respectively. The results indicated that the strategy of clustering by cellular activity can be useful for discovering cellular populations that would otherwise remain obscured.

Semi-automated, high-content imaging of drug transporter knockout sea urchin (Lytechinus pictus) embryos.

A defining feature of sea urchins is their extreme fecundity. Urchins produce millions of transparent, synchronously developing embryos, ideal for spatial and temporal analysis of development. This biological feature has been effectively utilized for ensemble measurement of biochemical changes. However, it has been underutilized in imaging studies, where single embryo measurements are used. Here we present an example of how stable genetics and high content imaging, along with machine learning-based image analysis, can be used to exploit the fecundity and synchrony of sea urchins in imaging-based drug screens. Building upon our recently created sea urchin ABCB1 knockout line, we developed a high-throughput assay to probe the role of this drug transporter in embryos. We used high content imaging to compare accumulation and toxicity of canonical substrates and inhibitors of the transporter, including fluorescent molecules and antimitotic cancer drugs, in homozygous knockout and wildtype embryos. To measure responses from the resulting image data, we used a nested convolutional neural network, which rapidly classified embryos according to fluorescence or cell division. This approach identified sea urchin embryos with 99.8% accuracy and determined two-cell and aberrant embryos with 96.3% and 89.1% accuracy, respectively. The results revealed that ABCB1 knockout embryos accumulated the transporter substrate calcein 3.09 times faster than wildtypes. Similarly, knockouts were 4.71 and 3.07 times more sensitive to the mitotic poisons vinblastine and taxol. This study paves the way for large scale pharmacological screens in the sea urchin embryo.