Understanding the chemistry of volcanic RNA to treat cancer & COVID-19,Jordan L. Meier, Ph.D., Senior Investigator, Epigenetics and Metabolism Section, NIH
The Department of Chemistry Presents Jordan L. Meier, Ph.D. Senior Investigator, Chemical Biology Laboratory, Epigenetics and Metabolism Section, NIH, National Cancer Instititute, Center for Cancer Research
NOTE: The status has been changed. This is now an online seminar only
N4-acetylcytidine is an ancient RNA modification catalyzed by an enzyme essential for human life. However, its distribution, dynamics, and function remain mysterious. In this seminar I will introduce my group’s work developing chemical tools to investigate RNA acetylation, why this led us to study an organism that thrives in solfatara (volcanic craters), and how fundamental studies such as these are being used to fuel new therapeutic approaches for the treatment of cancer and COVID-19.
Bio
Jordan Meier is Senior Investigator and Head of the Epigenetics and Metabolism Section within the Chemical Biology Laboratory in the Center of Cancer Research of the NCI. His work focuses on the development of chemical approaches to study epigenetic signaling and its relationship to cellular metabolism. The goal of his studies is to better understand how conditional protein and nucleic acid modifications alter gene activity, in order to facilitate the diagnosis and treatment of cancer.
Research Summary
Epigenetic mechanisms—factors other than an individual’s DNA sequence—play a critical role in the regulation of gene expression and undergo routine disruption in cancer. Dr. Meier’s work focuses on the development of chemical approaches to study epigenetic signaling and its relationship to cellular metabolism. The goal of these studies is to better elucidate the underlying logic linking gene expression and metabolism, and apply this knowledge towards new approaches to cancer therapy, diagnosis, and chemoprevention.
Papers:
A Chemical Signature for Cytidine Acetylation in RNA
Dynamic RNA acetylation revealed by quantitative cross-evolutionary mapping