High-throughput single-cell sequencing and analysis

In 2015 a major technological breakthrough for the first time allowed to perform high-throughput single-cell transcriptome analysis and ushered in a new age of complex organism biology research. This thesis describes efforts to optimize the inDrops method for single-cell transcriptome analysis, as well as its application for studying complex biological systems. Optimizations of the separate steps of the inDrops workflow allowed for up to 10-times more efficient capture of unique transcripts from the individual cells. The second part of this thesis describes how Epithelial-Mesenchymal Transition was characterized at single-cell resolution for the first time using HMLE cell model. One drawback of single-cell transcriptional profiling, however, is the sparse nature of the data. Because of this, weak gene-gene correlations can be obscured during analysis. We have shown how this limitation can be addressed using imputation algorithms based on data diffusion. The final part of this thesis focuses on breast cancer. In collaboration with MSKCC (USA) clinicians, an atlas of immune cells was constructed for the first time, combining over 62000 individual immune cells isolated from eight patients. This atlas revealed a vast diversity in immune cells of both the adaptive and innate immune systems. Results presented in this thesis indicate that the complex signaling and local niches in tumor microenvironment play a significant role in shaping the host immune response