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Title: The genotype-phenotype landscape of an allosteric protein

Abstract

Allostery is a fundamental biophysical mechanism that underlies cellular sensing, signaling, and metabolism. Yet a quantitative understanding of allosteric genotype-phenotype relationships remains elusive. Here, we report the large-scale measurement of the genotype-phenotype landscape for an allosteric protein: the lac repressor from Escherichia coli, LacI. Using a method that combines long-read and short-read DNA sequencing, we quantitatively measure the dose-response curves for nearly 105 variants of the LacI genetic sensor. The resulting data provide a quantitative map of the effect of amino acid substitutions on LacI allostery and reveal systematic sequence-structure-function relationships. We find that in many cases, allosteric phenotypes can be quantitatively predicted with additive or neural-network models, but unpredictable changes also occur. For example, we were surprised to discover a new band-stop phenotype that challenges conventional models of allostery and that emerges from combinations of nearly silent amino acid substitutions.

Authors:
ORCiD logo [1]; ORCiD logo [1];  [1]; ORCiD logo [1]; ORCiD logo [2]; ORCiD logo [1];  [1];  [1]; ORCiD logo [1]
  1. National Inst. of Standards and Technology (NIST), Gaithersburg, MD (United States)
  2. SLAC National Accelerator Lab., Menlo Park, CA (United States); Joint Initiative for Metrology in Biology, Stanford, CA (United States)
Publication Date:
Research Org.:
SLAC National Accelerator Lab., Menlo Park, CA (United States)
Sponsoring Org.:
USDOE Office of Science (SC), Basic Energy Sciences (BES)
OSTI Identifier:
1781600
Grant/Contract Number:  
AC02-76SF00515
Resource Type:
Accepted Manuscript
Journal Name:
Molecular Systems Biology
Additional Journal Information:
Journal Volume: 17; Journal Issue: 3; Journal ID: ISSN 1744-4292
Publisher:
Wiley
Country of Publication:
United States
Language:
English
Subject:
59 BASIC BIOLOGICAL SCIENCES; allostery; genetic sensor; genotype-phenotype relationships; highthroughput measurements; transcription factor

Citation Formats

Tack, Drew S., Tonner, Peter D., Pressman, Abe, Olson, Nathan D., Levy, Sasha F., Romantseva, Eugenia F., Alperovich, Nina, Vasilyeva, Olga, and Ross, David. The genotype-phenotype landscape of an allosteric protein. United States: N. p., 2021. Web. doi:10.15252/msb.202010179.
Tack, Drew S., Tonner, Peter D., Pressman, Abe, Olson, Nathan D., Levy, Sasha F., Romantseva, Eugenia F., Alperovich, Nina, Vasilyeva, Olga, & Ross, David. The genotype-phenotype landscape of an allosteric protein. United States. https://doi.org/10.15252/msb.202010179
Tack, Drew S., Tonner, Peter D., Pressman, Abe, Olson, Nathan D., Levy, Sasha F., Romantseva, Eugenia F., Alperovich, Nina, Vasilyeva, Olga, and Ross, David. Mon . "The genotype-phenotype landscape of an allosteric protein". United States. https://doi.org/10.15252/msb.202010179. https://www.osti.gov/servlets/purl/1781600.
@article{osti_1781600,
title = {The genotype-phenotype landscape of an allosteric protein},
author = {Tack, Drew S. and Tonner, Peter D. and Pressman, Abe and Olson, Nathan D. and Levy, Sasha F. and Romantseva, Eugenia F. and Alperovich, Nina and Vasilyeva, Olga and Ross, David},
abstractNote = {Allostery is a fundamental biophysical mechanism that underlies cellular sensing, signaling, and metabolism. Yet a quantitative understanding of allosteric genotype-phenotype relationships remains elusive. Here, we report the large-scale measurement of the genotype-phenotype landscape for an allosteric protein: the lac repressor from Escherichia coli, LacI. Using a method that combines long-read and short-read DNA sequencing, we quantitatively measure the dose-response curves for nearly 105 variants of the LacI genetic sensor. The resulting data provide a quantitative map of the effect of amino acid substitutions on LacI allostery and reveal systematic sequence-structure-function relationships. We find that in many cases, allosteric phenotypes can be quantitatively predicted with additive or neural-network models, but unpredictable changes also occur. For example, we were surprised to discover a new band-stop phenotype that challenges conventional models of allostery and that emerges from combinations of nearly silent amino acid substitutions.},
doi = {10.15252/msb.202010179},
journal = {Molecular Systems Biology},
number = 3,
volume = 17,
place = {United States},
year = {Mon Mar 01 00:00:00 EST 2021},
month = {Mon Mar 01 00:00:00 EST 2021}
}

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