Shankar Srinivas

Molecular profiling of single cells has advanced our knowledge of the molecular basis of development. However, current approaches mostly rely on dissociating cells from tissues, thereby losing the crucial spatial context of regulatory processes. Here, we apply an image-based single-cell transcriptomics method, sequential fluorescence in situ hybridization (seqFISH), to detect mRNAs for 387 target genes in tissue sections of mouse embryos at the 8-12 somite stage. By integrating spatial context and multiplexed transcriptional measurements with two single-cell transcriptome atlases, we characterize cell types across the embryo and demonstrate that spatially resolved expression of genes not profiled by seqFISH can be imputed. We use this high-resolution spatial map to characterize fundamental steps in the patterning of the midbrain-hindbrain boundary (MHB) and the developing gut tube. We uncover axes of cell differentiation that are not apparent from single-cell RNA-sequencing (scRNA-seq) data, such as early dorsal-ventral separation of esophageal and tracheal progenitor populations in the gut tube. Our method provides an approach for studying cell fate decisions in complex tissues and development.

We demonstrate wavefront sensorless aberration correction in a two-photon excited fluorescence microscope. Using analysis of the image-formation process, we have developed an optimized correction scheme permitting image-quality improvement with minimal additional exposure of the sample. We show that, as a result, our correction process induces little photobleaching and significantly improves the quality of images of biological samples. In particular, increased visibility of small structures is demonstrated. Finally, we illustrate the use of this technique on various fresh and fixed biological tissues.