NYIT faculty members to develop novel direct RNA sequencing methods under multi-year NIH grant

NYIT (New York Institute of Technology) faculty members Shenglong Zhang, Ph.D., and Wenjia Li, Ph.D., have won a cutting edge research award (R21) from the National Institutes of Health’s National Human Genome Research Institute to develop novel direct RNA sequencing methods. The grant totals $568,000 over three years and promises new tools to explore potential environmental and biological factors in serious diseases like cancer and diabetes. The new sequencing tools that Zhang and Li are developing can be used for analyzing RNA modifications in human, animal, and bacterial cells, thus allowing studies of how environmental and biological factors affect the human genome.

Combining their expertise, Zhang, assistant professor of Life Science, and Li, assistant professor of Computer Science, have tackled a problem with repercussions for all 21st-century humans: how to reliably detect and quantify modifications in RNA molecules. Recent evidence suggests such changes are occurring at an accelerating pace, likely due to environmental factors. Changes in RNA can change disease risks, both within individuals and across generations. “Damage to our DNA and RNA caused by a toxic environment is incremental and not observable,” said Li. “Nevertheless,” he added, “it may be inheritable. Recent studies in epigenetics provide a lot of evidence that environmental change may be leaving its mark on our genome.” To have a thorough understanding of these changes, scientists need to be able to identify and measure RNA modifications, which cannot yet be done reliably or accurately.

As cellular signals of environmental changes, RNA modifications are closely linked to major conditions like breast cancer, type 2 diabetes, and obesity. More than 100 RNA modifications have been identified, but there may be many others yet to be identified; scientists have thus far lacked tools to discern and analyze how these chemical changes function within the cell. And what we don’t know can hurt not only us, but also potentially our progeny. It is hoped that Zhang and Li’s research will inform policymakers, scientists, and practitioners so that they can better manage environmental impacts as they appear in different stages of gene expression.

Li and Zhang bring an innovative, interdisciplinary approach to their task. Scientists have long been able to use mass spectrometry (MS) to uncover modifications in proteins, but MS results alone cannot clearly reveal the identity and position of RNA modifications. Li and Zhang will combine MS with liquid chromatography (LC) and an algorithm they developed to successfully sequence the RNA. “The RNA data resulting from MS are complex, but our algorithm can exploit predictable regularities in LC separation to simplify the data,” said Li. “One of the advantages of our method is that it can identify, locate, and quantify a broad spectrum of RNA modifications that other methods are not capable of,” added Zhang.

Life Science Department Chair Niharika Nath, Ph.D., is enthusiastic about the potential for this research. “Li and Zhang’s RNA sequencing method could become a robust, easy-to-use, and broadly applicable tool,” she said. “Not only would it be effective, but it would also work well with other tools already in use, such as the Next Generation Sequencing (NGS) technology that helps to identify a specific modification like methylation.”

Dean Nada Marie Anid, Ph.D., of NYIT’s School of Engineering and Computing Sciences, said that this NIH grant, in addition to advancing basic science, will benefit NYIT undergraduate and graduate students over the next three years. “The development of new sequencing tools provides an ideal opportunity for student research and skills training across multiple disciplines, and prepares them for the U.S. science and technology-based economy,” she said.

The research team will seek to communicate their results to the scientific community through conference presentations, patents, and peer-reviewed publications.

Source – NYIT

Leave a Reply

Your email address will not be published. Required fields are marked *


Time limit is exhausted. Please reload CAPTCHA.