Document Type
Article
Publication Date
7-26-2022
Publication Title
Genomics
Issue
4
First page number:
1
Last page number:
16
Abstract
High-throughput assay systems have had a large impact on understanding the mechanisms of basic cell functions. However, high-throughput assays that directly assess molecular functions are limited. Herein, we describe the “GigaAssay”, a modular high-throughput one-pot assay system for measuring molecular functions of thousands of genetic variants at once. In this system, each cell was infected with one virus from a library encoding thousands of Tat mutant proteins, with each viral particle encoding a random unique molecular identifier (UMI). We demonstrate proof of concept by measuring transcription of a GFP reporter in an engineered reporter cell line driven by binding of the HIV Tat transcription factor to the HIV long terminal repeat. Infected cells were flow- sorted into 3 bins based on their GFP fluorescence readout. The transcriptional activity of each Tat mutant was calculated from the ratio of signals from each bin. The use of UMIs in the GigaAssay produced a high average accuracy (95%) and positive predictive value (98%) determined by comparison to literature benchmark data, known C-terminal truncations, and blinded independent mutant tests. Including the substitution tolerance with structure/function analysis shows restricted substitution types spatially concentrated in the Cys-rich region. Tat has abundant intragenic epistasis (10%) when single and double mutants are compared.
Keywords
Tat; Transcription; High-throughput assay; Saturation mutagenesis; Protein structure; Intragenic epistasis
Disciplines
Medicine and Health Sciences
File Format
File Size
6600 KB
Language
English
Rights
IN COPYRIGHT. For more information about this rights statement, please visit http://rightsstatements.org/vocab/InC/1.0/
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.
Repository Citation
Benjamin, R.,
Giacoletto, C. J.,
FitzHugh, Z. T.,
Eames, D.,
Buczek, L.,
Wu, X.,
Newsome, J.,
Han, M. V.,
Pearson, T.,
Wei, Z.,
Banerjee, A.,
Brown, L.,
Valente, L. J.,
Shen, S.,
Deng, H.,
Schiller, M. R.
(2022).
GigaAssay – An Adaptable High-Throughput Saturation Mutagenesis Assay Platform.
Genomics(4),
1-16.
Available at:
http://dx.doi.org/10.1016/j.ygeno.2022.110439