# Systems Level Characterization of a New Epigenetic Mechanism of Gene Expression and Cellular Adaptation

> **NIH NIH F32** · COLUMBIA UNIVERSITY HEALTH SCIENCES · 2020 · $23,102

## Abstract

Project Summary:
The reprogramming of gene expression in response to changes in the external environment is critical for
cellular adaptation and survival. These hard-coded responses evolve over geological time-scales and are fine-
tuned to the requirements of the native habitat. However, organisms may encounter novel or extreme
environments for which their gene regulatory network is inadequate for appropriate reprogramming of gene
expression. Our laboratory has recently discovered a powerful new epigenetic mechanism in Saccharomyces
cerevisiae that allows cells to adapt to novel extreme environments without the benefit of hardwired regulatory
networks. We call this mechanism “stochastic tuning,” by which inherent transcriptional noise and fitness-
driven feedback enable cells to optimize appropriate gene expression states without the need to sense the
external environment directly. The aim of this study is to characterize the stochastic tuning dynamics in
individual cells and to discover the underlying effectors and regulators involved. Given the inherently
stochastic nature of the phenomenon, characterizing the single-cell trajectory of tuning at the molecular level is
an essential step. The characterization of gene expression can be achieved at a global scale using high-
throughput methods or at high resolution using microscopy to study mRNA temporal dynamics. Single-cell
transcriptomics in mammalian cells is a rapidly advancing field. However, these methods are not effective in
yeast due the presence of a thick cell wall. I have therefore started to develop a promising alternative
technology for efficient and low-cost transcriptome profiling in yeast cells. I will also use live cell imaging of
MS2/ PP7 tagged mRNAs to study transcriptional dynamics at high temporal and spatial resolution. In
addition, I aim to systematically discover all the factors involved in stochastic tuning. I will use Clustered
Regularly Interspaced Short Palindromic Repeats (CRISPR) technology to activate or repress all essential and
non-essential genes in order to systematically discover loci that affect stochastic tuning. Our preliminary
studies in yeast demonstrate that stochastic tuning operates locally at the level of each individual gene and
that chromatin modification and remodeling machinery modulates the efficacy of this process. I will study the
dynamics of local histone modifications using Chromatin Immunoprecipitation coupled with quantitative PCR
along the different stages of stochastic tuning. In addition, I will study the local chromatin state using DNase-I-
Hypersensitivity assays. These studies will enable us to monitor the local chromatin state during the process
of stochastic tuning and match it to transcriptional output and cellular fitness. The proposed studies will reveal
the molecular details of a powerful new adaptation mechanism at the single-cell level and within the local
chromatin context. Our work will also reveal the key effectors and regul...

## Key facts

- **NIH application ID:** 10191180
- **Project number:** 3F32GM125170-02S1
- **Recipient organization:** COLUMBIA UNIVERSITY HEALTH SCIENCES
- **Principal Investigator:** Amir Momen-Roknabadi
- **Activity code:** F32 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $23,102
- **Award type:** 3
- **Project period:** 2018-07-01 → 2020-10-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10191180

## Citation

> US National Institutes of Health, RePORTER application 10191180, Systems Level Characterization of a New Epigenetic Mechanism of Gene Expression and Cellular Adaptation (3F32GM125170-02S1). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10191180. Licensed CC0.

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