Joyaditya Saha’s scientific contributions

Recent advances in single cell sequencing and multi-omics techniques have significantly improved our understanding of biological phenomena and our capacity to model them. Despite combined capture of data modalities showing similar progress, notably single cell transcriptomics and proteomics, simultaneous multi-omics level probing still remains challenging. As an alternative to combined capture of biological data, in this review, we explore current and upcoming methods for post-hoc network inference and integration with an emphasis on single cell transcriptomics and proteomics. By examining various approaches, from probabilistic models to graph-based algorithms, we outline the challenges and potential strategies for effectively combining biological data types while simultaneously highlighting the importance of model validation. With this review, we aim to inform readers of the breadth of tools currently available for the purpose-specific generation of heterogeneous multi-layer networks.

Clonal proliferation dynamics within a tumor channels the course of tumor growth, drug response and activity. A high-throughput image screening technique is required to analyze and quantify the spatiotemporal variations in cell proliferation and influence of chemotherapy on clonal colonies. We present two protocols for generating spatial, Lentiviral Gene Ontology (LeGO) fluorescent tag based, mono- and co-culture systems with provisions for spatio-temporal tracking of clonal growth at the nucleus- and cytoplasm-level. The cultured cells are subjected to either drug treatment or co-cultured with fibroblasts and analyzed with a novel image processing framework. This framework enables alignment of cell positions based on motion capture techniques, tracking through time and investigation of drug actions or co-culturing on individual cell colonies. Finally, utilizing this framework, we develop agent-based models to simulate and predict the effects of the microenvironment and clonal density on cell proliferation. The model and experimental findings suggest growth stimulating effects of local clonal density irrespective of overall cell confluency.KeywordsLeGOcell trackingdiffusion dynamicsagent-based model