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Title: Deep scanning lysine metabolism in Escherichia coli

Abstract

Our limited ability to predict genotype–phenotype relationships has called for strategies that allow testing of thousands of hypotheses in parallel. Deep scanning mutagenesis has been successfully implemented to map genotype–phenotype relationships at a single-protein scale, allowing scientists to elucidate properties that are difficult to predict. However, most phenotypes are dictated by several proteins that are interconnected through complex and robust regulatory and metabolic networks. These sophisticated networks hinder our understanding of the phenotype of interest and limit our capabilities to rewire cellular functions. Here, we leveraged CRISPR-EnAbled Trackable genome Engineering to attempt a parallel and high-resolution interrogation of complex networks, deep scanning multiple proteins associated with lysine metabolism in Escherichia coli. We created over 16,000 mutations to perturb this pathway and mapped their contribution toward resistance to an amino acid analog. By doing so, we identified different routes that can alter pathway function and flux, uncovering mechanisms that would be difficult to rationally design. This method sets a framework for forward investigation of complex multigenic phenotypes.

Authors:
 [1];  [2];  [1];  [1];  [1];  [2];  [2]; ORCiD logo [3]
  1. Univ. of Colorado, Boulder, CO (United States)
  2. Inscripta, Inc., Boulder, CO (United States)
  3. Inscripta, Inc., Boulder, CO (United States); Univ. of Colorado, Boulder, CO (United States)
Publication Date:
Research Org.:
Univ. of Colorado, Boulder, CO (United States)
Sponsoring Org.:
USDOE Office of Science (SC), Biological and Environmental Research (BER) (SC-23)
OSTI Identifier:
1547418
Grant/Contract Number:  
SC0018368; SC0008812
Resource Type:
Accepted Manuscript
Journal Name:
Molecular Systems Biology
Additional Journal Information:
Journal Volume: 14; Journal Issue: 11; Journal ID: ISSN 1744-4292
Publisher:
Wiley
Country of Publication:
United States
Language:
English
Subject:
CRISPR-Cas9; genotype–phenotype; lysine; mapping; mutagenesis

Citation Formats

Bassalo, Marcelo C., Garst, Andrew D., Choudhury, Alaksh, Grau, William C., Oh, Eun J., Spindler, Eileen, Lipscomb, Tanya, and Gill, Ryan T. Deep scanning lysine metabolism in Escherichia coli. United States: N. p., 2018. Web. doi:10.15252/msb.20188371.
Bassalo, Marcelo C., Garst, Andrew D., Choudhury, Alaksh, Grau, William C., Oh, Eun J., Spindler, Eileen, Lipscomb, Tanya, & Gill, Ryan T. Deep scanning lysine metabolism in Escherichia coli. United States. doi:10.15252/msb.20188371.
Bassalo, Marcelo C., Garst, Andrew D., Choudhury, Alaksh, Grau, William C., Oh, Eun J., Spindler, Eileen, Lipscomb, Tanya, and Gill, Ryan T. Mon . "Deep scanning lysine metabolism in Escherichia coli". United States. doi:10.15252/msb.20188371. https://www.osti.gov/servlets/purl/1547418.
@article{osti_1547418,
title = {Deep scanning lysine metabolism in Escherichia coli},
author = {Bassalo, Marcelo C. and Garst, Andrew D. and Choudhury, Alaksh and Grau, William C. and Oh, Eun J. and Spindler, Eileen and Lipscomb, Tanya and Gill, Ryan T.},
abstractNote = {Our limited ability to predict genotype–phenotype relationships has called for strategies that allow testing of thousands of hypotheses in parallel. Deep scanning mutagenesis has been successfully implemented to map genotype–phenotype relationships at a single-protein scale, allowing scientists to elucidate properties that are difficult to predict. However, most phenotypes are dictated by several proteins that are interconnected through complex and robust regulatory and metabolic networks. These sophisticated networks hinder our understanding of the phenotype of interest and limit our capabilities to rewire cellular functions. Here, we leveraged CRISPR-EnAbled Trackable genome Engineering to attempt a parallel and high-resolution interrogation of complex networks, deep scanning multiple proteins associated with lysine metabolism in Escherichia coli. We created over 16,000 mutations to perturb this pathway and mapped their contribution toward resistance to an amino acid analog. By doing so, we identified different routes that can alter pathway function and flux, uncovering mechanisms that would be difficult to rationally design. This method sets a framework for forward investigation of complex multigenic phenotypes.},
doi = {10.15252/msb.20188371},
journal = {Molecular Systems Biology},
number = 11,
volume = 14,
place = {United States},
year = {2018},
month = {11}
}

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