Convergence of single cell assays, bioinformatics and simulation to study tissue injury and regeneration

Rajanikanth Vadigepalli, PhD
Vice Chair of Research and Professor of Pathology, Anatomy and Cell Biology
Thomas Jefferson University
Thu, December 10, 2020 at 2:30 PM

Recent technological advances have enabled the study of transcriptional and proteomic profiles of single cells within a tissue at an unprecedented scale, revealing a high degree of variability in molecular levels and cellular functions among single cells within a population. Analysis of the molecular variability at the single-cell scale has revealed that cells within any population can be organized into multiple functional subtypes, likely arising in response to different cellular inputs, spatial location in the tissue, developmental stage, and other intrinsic and extrinsic factors. The emerging view is that the balance among heterogeneous cellular subtypes, i.e., the relative proportions of cells in each functional state, enables effective tissue-scale responses to perturbations in a manner that may not be possible in tissues lacking heterogeneous cellular subtypes. Despite significant research efforts, how the extensive variability in the molecular states of single cells translates to a tightly constrained tissue response to perturbations remains an open question. It is becoming evident that the molecular/functional states of cells are not randomly distributed, but are likely tuned along a gradient between the patterns observed in canonical archetypes. A key unaddressed challenge is that of understanding the tissue scale physiological impact of dynamically organized single cell heterogeneity of functional states. Tackling this challenge requires a convergence of single cell assays (‘omics’ or not), bioinformatics, and dynamic modeling/simulation.

Rajanikanth Vadigepalli, Ph.D.

Rajanikanth Vadigepalli is the Vice Chair of Research and a Professor of Pathology, Anatomy and Cell Biology at the Daniel Baugh Institute for Functional Genomics/Computational Biology in Thomas Jefferson University. Dr. Vadigepalli’s collaborative research program is driven by a convergence of systems engineering, computational modeling, bioinformatics, and single cell scale transcriptomics, to identify and target key control points for intervention in disease. Ongoing collaborative projects focus on central and peripheral neural circuits controlling the heart, brainstem neuroinflammation and neuroimmune processes leading to hypertension, tissue repair and regeneration, and alcoholic liver disease. Recent research from the group has led to: new microRNA-based molecular targets to prevent essential hypertension; novel insights into the process of liver regeneration paving the way for new clinical decision-making tools; new analytical tools for mining high-dimensional data; and, novel methods for computational modeling of biological networks and processes. Dr. Vadigepalli is a member of the Committee on Credible Practice of Modeling & Simulation in Healthcare, and is developing guidelines and best practices for building and documenting computational models in healthcare.

Dr. Vadigepalli received his Bachelors in Chemical Engineering from the Indian Institute of Technology-Madras in 1996; his PhD in Chemical Engineering from the University of Delaware in 2001, with Specialization in Systems and Control Engineering; and his postdoctoral training in Bioinformatics at Thomas Jefferson University.