Discipline: Biological Sciences
Subcategory: Cell and Molecular Biology
Qiu Chang Wu - Colorado College
Co-Author(s): Alain Bonny, M.S., University of California San Francisco, San Francisco, CA; Joao Fonseca, Ph.D, University of California San Francisco, San Francisco, CA; Hana El-Samad, Ph.D, University of California San Francisco, San Francisco, CA
Cellular heterogeneity is often overlooked in the study of molecular biology. In isoclonal cell populations in uniform environments, gene expression of the same gene varies across the population. Such variation phenomenon is described by noise biologist as gene expression noise. In recent years, gene expression noise has been shown to have a functional role in cell fate decisions (Moris et al. 2016) and HIV latency reactivation (Dar et al. 2014). While efforts have been made to measure noise, less is known about how to control noise. Here, we present our efforts in developing a noise control system in the form of a genetic circuit which we call a noise rheostat. The basic architecture of the circuit involves two small molecule inducible transcription systems linked in series, driving expression of the green fluorescent protein gene. The in-series architecture has been shown by the El-Samad laboratory to be effective in controlling noise in S. cerevisiae (Arandra-Diaz et al. 2017). Using a human embryonic kidney cell line (HEK293), we performed transient transfections and characterized the system through drug dosage experiments using flow cytometry. Data was analyzed using MATLAB and revealed a promising first working prototype of a mammalian noise rheostat by demonstrating that gene expression variance may be dialable while maintaining the gene expression mean. Further experiments are required to ensure that such system may control endogenous gene expression noise. We suggest that the mammalian noise rheostat will be a useful tool in the study of noise biology.
Aranda-Diaz, A., Mace, K., Zuleta, I., Harrigan, P., El-Samad, H. Robust synthetic circuits for two-dimensional control of gene expression in yeast. ACS Synth. Biol. 6(3), 545-554 (2017).
Dar, R., Hosmane, N., Arkin, M., Siliciano, R., Weinberger, L. Screening for noise in gene expression identifies drug synergies. Science 344(6190), 1392-1396 (2014).
Moris, N., Pina, C.,Martinez Arias, A. Transition states and cell fate decisions in epigenetic landscapes. Nature Reviews Genetics 17, 693-703 (2016).ABSTRACT_Wu_Qiu.docx
Funder Acknowledgement(s): I would like to thank the National Science Foundation for their support of my first REU experience at University of California San Francisco. I would also like to thank Colorado College Career Center and Jean Paul Bonny, for supporting my second summer at University of California San Francisco.
Faculty Advisor: Hana El-Samad, Hana.El-Samad@ucsf.edu
Role: This was my own project. Coauthors on the paper are my mentors.