Published September 24, 2021 | Version Submitted
Discussion Paper Open

Ratiometric RNA labeling allows dynamic multiplexed analysis of gene circuits in single cells

  • 1. ROR icon Peking University
  • 2. ROR icon California Institute of Technology

Abstract

Biological processes are highly dynamic and are regulated by genes that connect with one and another, forming regulatory circuits and networks. Understanding how gene regulatory circuits operate dynamically requires monitoring the expression of multiple genes in the same cell. However, it is limited by the relatively few distinguishable fluorescent proteins. Here, we developed a multiplexed real-time transcriptional imaging method based on two RNA stem-loop binding proteins, and employed it to analyze the temporal dynamics of synthetic gene circuits. By incorporating different ratios of MS2 and PP7 stem-loops, we were able to monitor the real-time nascent transcriptional activities of up to five genes in the same cell using only two fluorescent proteins. Applying this multiplexing capability to synthetic linear or branched gene regulatory cascades revealed that propagation of transcriptional dynamics is enhanced by non-stationary dynamics and is dictated by the slowest regulatory branch in the presence of combinatorial regulation. Mathematical modeling provided further insight into temporal multi-gene interactions and helped to understand potential challenges in regulatory inference using snapshot single-cell data. Ratiometric multiplexing should scale exponentially with additional labelling channels, providing a way to track the dynamics of larger circuits.

Additional Information

The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY 4.0 International license. This version posted September 23, 2021. Y.L. acknowledges the supports from National Natural Science Foundation of China (Grant # 31771425) and National Key R&D Program of China (Grant # 2020YFA0906900, 2018YFA0900703). M.B.E. acknowledges the supports from National Science Foundation (Grant # 1547056; Grant # EF-2021552 under subaward UWSC10142). MBE is a Howard Hughes Medical Institute Investigator. We thank the flow cytometry core at the National Center for Protein Sciences at Peking University and the Quantitative Imaging facility at the Center for Quantitative Biology at Peking University for equipment supports. Data and code availability: The data and code used in this paper can be downloaded from the following link: https://github.com/IndigoMad/Multiplexed-transcriptional-reporter. Author Contributions: Y.L. and M.B.E. conceived the concept of the reporter; S.X., K.L. and L.M. performed the research; J.Z. and S.Y. contributed new reagents/analytic tools; S.X. K.L. and Y.L. wrote the Competing Interest Statement: A patent application based on the developed technology was submitted in China. manuscript with inputs from M.B.E.

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Additional details

Identifiers

Eprint ID
111086
Resolver ID
CaltechAUTHORS:20210929-151425994

Funding

National Natural Science Foundation of China
31771425
National Key Research and Development Program of China
2020YFA0906900
National Key Research and Development Program of China
2018YFA0900703
NSF
MCB-1547056
NSF
EF-2021552
Paul G. Allen Frontiers Group
UWSC10142
Howard Hughes Medical Institute (HHMI)

Dates

Created
2021-09-29
Created from EPrint's datestamp field
Updated
2021-11-16
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Caltech Custom Metadata

Caltech groups
Division of Biology and Biological Engineering (BBE)