Dr. Vadigepalli is an Associate Professor of Pathology, Cell Biology and Anatomy at Thomas Jefferson University. He also holds an Adjunct Professor position in Chemical Engineering at the University of Delaware. He received his Bachelors in Chemical Engineering from the Indian Institute of Technology in Madras, India, 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.
Work in Dr. Vadigepalli’s lab is directed at understanding the operational principles of mammalian tissue plasticity and adaptation in response to functional demands and in chronic disease. They are interested in understanding the plasticity of cell phenotypes that are shaped by underlying regulatory networks. The driving postulate is that variability of gene expression across cell types in functioning tissues is dysregulated as an adaptive mechanism in the contexts of chronic disease and abnormally altered cell fates during development. His lab employs computational modeling, nonlinear systems analysis, and bioinformatics approaches to complement high-throughput experimentation at the tissue and single cell scales. Their recent focus has been on analyzing and modeling gene and miRNA regulatory networks from molecularly and spatially defined single cells acquired through laser capture microdissection. At Jefferson, he developed a bioinformatics tool named PAINT for promoter and network analysis that has been in continuous use by researchers world-wide for over 10 years. His recent modeling results revealed that robustness of gene regulation arises from a balance of transcription factor subtypes that dynamically compensate for activity and can explain confounding results from pathway inhibitor experiments.
Dr. Vadigepalli has authored or co-authored over 35 peer-reviewed journal and conference publications in Biology/Medicine, Computational Biology and Systems Engineering. He has served on multiple review panels for the NIH, NSF and Army Research Office, and his work has been continuously funded by multiple grants from NIH. He currently serves as a Co-lead for the Computational Neuroscience Working Group of the Muti-scale Modeling Consortium led by the National Institute of Biomedical Imaging and Bioengineering and the Interagency Modeling and Analysis Group.
Through cross-disciplinary collaborative projects, the Vadigepalli lab studies:
- Central autonomic control circuits adversely adapted in hypertension and neuroinflammation – Recent efforts uncovered a surprisingly “highly organized variability” of gene regulation in single neurons with implications for the development of hypertension. They are developing multi-scale models that integrate cellular interactions with gene and miRNA regulatory networks.
- Plasticity of liver repair and regeneration in alcoholic liver disease – The Vadigepalli lab has recently identified a novel balance of miRNAs, genes and transcription factors that defines the cell phenotypes that can promote or inhibit liver regeneration. They are employing miRNA antagonists and mimics to manipulate the cell phenotypes in vivo to normalize the alcohol-disrupted liver regeneration. Further, they are developing dynamic models that integrate omic data sets on gene and miRNA expression, transcription factor binding (via ChIP-seq), and cytokine profiles.
- Stem cell fate and neural development in fetal alcohol spectrum disorders – Recent results on pathway-scale gene expression, miRNAs, and single cell protein measures revealed that prenatal alcohol exposure shifts the embryonic stem cell fate away from neural lineage at developmental stages much earlier than are currently appreciated. They are currently employing miRNA mimics and antagonists to counteract alcohol effects on cell fate.
Additionally, Dr. Vadigepalli’s lab now collaborates with the Molecular Diagnostics group at Thomas Jefferson University Hospital to analyze genomic aberrations in various cancers. In this project, they are integrating in-house developed and externally sourced bioinformatics resources to provide detailed analysis of patient-specific next-generation sequencing and microarray data-sets.