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 a...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Tack, Drew S [verfasserIn] Tonner, Peter D [verfasserIn] Pressman, Abe [verfasserIn] Olson, Nathan D [verfasserIn] Levy, Sasha F [verfasserIn] Romantseva, Eugenia F [verfasserIn] Alperovich, Nina [verfasserIn] Vasilyeva, Olga [verfasserIn] Ross, David [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2021 |
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| Schlagwörter: |
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| Anmerkung: |
© The Author(s) 2021 |
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| Übergeordnetes Werk: |
Enthalten in: Molecular Systems Biology - Nature Publishing Group UK, 2023, 17(2021), 3 vom: 30. März |
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| Übergeordnetes Werk: |
volume:17 ; year:2021 ; number:3 ; day:30 ; month:03 |
| Links: |
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| DOI / URN: |
10.15252/msb.202010179 |
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| Katalog-ID: |
SPR058094725 |
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| 520 | |a 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 $ 10^{5} $ 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. | ||
| 520 | |a SYNOPSIS A large‐scale approach is used to measure the dose‐response curves of > 60,000 variants of the lac repressor. The results reveal systematic sequence‐structure‐function relationships underlying allostery, as well as a surprising diversity of allosteric phenotypes. Long‐read and short‐read DNA sequencing is used to measure the genotype and dose‐response phenotype of 62,000 variants of the lac repressor.The effects of single amino acid substitutions reveal systematic sequence‐structure‐function relationships underlying LacI allostery that may apply to allosteric proteins more generally.Novel phenotypes emerge with few substitutions, including variants with inverted dose‐response curves and variants with biphasic dose‐response curves. | ||
| 520 | |a Graphical Abstract A large‐scale approach is used to measure the dose‐response curves of > 60,000 variants of the lac repressor. The results reveal systematic sequence‐structure‐function relationships underlying allostery, as well as a surprising diversity of allosteric phenotypes. | ||
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| 700 | 1 | |a Ross, David |e verfasserin |0 (orcid)0000-0002-7790-218X |4 aut | |
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10.15252/msb.202010179 doi (DE-627)SPR058094725 (SPR)msb.202010179-e DE-627 ger DE-627 rakwb eng Tack, Drew S verfasserin (orcid)0000-0002-9380-4643 aut The genotype‐phenotype landscape of an allosteric protein 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2021 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 $ 10^{5} $ 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. SYNOPSIS A large‐scale approach is used to measure the dose‐response curves of > 60,000 variants of the lac repressor. The results reveal systematic sequence‐structure‐function relationships underlying allostery, as well as a surprising diversity of allosteric phenotypes. Long‐read and short‐read DNA sequencing is used to measure the genotype and dose‐response phenotype of 62,000 variants of the lac repressor.The effects of single amino acid substitutions reveal systematic sequence‐structure‐function relationships underlying LacI allostery that may apply to allosteric proteins more generally.Novel phenotypes emerge with few substitutions, including variants with inverted dose‐response curves and variants with biphasic dose‐response curves. Graphical Abstract A large‐scale approach is used to measure the dose‐response curves of > 60,000 variants of the lac repressor. The results reveal systematic sequence‐structure‐function relationships underlying allostery, as well as a surprising diversity of allosteric phenotypes. allostery (dpeaa)DE-He213 genetic sensor (dpeaa)DE-He213 genotype‐phenotype relationships (dpeaa)DE-He213 high‐throughput measurements (dpeaa)DE-He213 transcription factor (dpeaa)DE-He213 Tonner, Peter D verfasserin (orcid)0000-0003-2840-0930 aut Pressman, Abe verfasserin aut Olson, Nathan D verfasserin (orcid)0000-0003-2585-3037 aut Levy, Sasha F verfasserin (orcid)0000-0002-0923-1636 aut Romantseva, Eugenia F verfasserin (orcid)0000-0003-0929-7966 aut Alperovich, Nina verfasserin aut Vasilyeva, Olga verfasserin aut Ross, David verfasserin (orcid)0000-0002-7790-218X aut Enthalten in Molecular Systems Biology Nature Publishing Group UK, 2023 17(2021), 3 vom: 30. März (DE-627)490536905 (DE-600)2193510-5 1744-4292 nnns volume:17 year:2021 number:3 day:30 month:03 https://dx.doi.org/10.15252/msb.202010179 X:SPRINGER Resolving-System kostenfrei Volltext SYSFLAG_0 GBV_SPRINGER GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_72 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_636 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4029 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4116 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4155 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4311 GBV_ILN_4313 GBV_ILN_4314 GBV_ILN_4315 GBV_ILN_4318 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4393 GBV_ILN_4598 GBV_ILN_4700 AR 17 2021 3 30 03 |
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10.15252/msb.202010179 doi (DE-627)SPR058094725 (SPR)msb.202010179-e DE-627 ger DE-627 rakwb eng Tack, Drew S verfasserin (orcid)0000-0002-9380-4643 aut The genotype‐phenotype landscape of an allosteric protein 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2021 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 $ 10^{5} $ 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. SYNOPSIS A large‐scale approach is used to measure the dose‐response curves of > 60,000 variants of the lac repressor. The results reveal systematic sequence‐structure‐function relationships underlying allostery, as well as a surprising diversity of allosteric phenotypes. Long‐read and short‐read DNA sequencing is used to measure the genotype and dose‐response phenotype of 62,000 variants of the lac repressor.The effects of single amino acid substitutions reveal systematic sequence‐structure‐function relationships underlying LacI allostery that may apply to allosteric proteins more generally.Novel phenotypes emerge with few substitutions, including variants with inverted dose‐response curves and variants with biphasic dose‐response curves. Graphical Abstract A large‐scale approach is used to measure the dose‐response curves of > 60,000 variants of the lac repressor. The results reveal systematic sequence‐structure‐function relationships underlying allostery, as well as a surprising diversity of allosteric phenotypes. allostery (dpeaa)DE-He213 genetic sensor (dpeaa)DE-He213 genotype‐phenotype relationships (dpeaa)DE-He213 high‐throughput measurements (dpeaa)DE-He213 transcription factor (dpeaa)DE-He213 Tonner, Peter D verfasserin (orcid)0000-0003-2840-0930 aut Pressman, Abe verfasserin aut Olson, Nathan D verfasserin (orcid)0000-0003-2585-3037 aut Levy, Sasha F verfasserin (orcid)0000-0002-0923-1636 aut Romantseva, Eugenia F verfasserin (orcid)0000-0003-0929-7966 aut Alperovich, Nina verfasserin aut Vasilyeva, Olga verfasserin aut Ross, David verfasserin (orcid)0000-0002-7790-218X aut Enthalten in Molecular Systems Biology Nature Publishing Group UK, 2023 17(2021), 3 vom: 30. März (DE-627)490536905 (DE-600)2193510-5 1744-4292 nnns volume:17 year:2021 number:3 day:30 month:03 https://dx.doi.org/10.15252/msb.202010179 X:SPRINGER Resolving-System kostenfrei Volltext SYSFLAG_0 GBV_SPRINGER GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_72 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_636 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4029 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4116 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4155 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4311 GBV_ILN_4313 GBV_ILN_4314 GBV_ILN_4315 GBV_ILN_4318 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4393 GBV_ILN_4598 GBV_ILN_4700 AR 17 2021 3 30 03 |
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10.15252/msb.202010179 doi (DE-627)SPR058094725 (SPR)msb.202010179-e DE-627 ger DE-627 rakwb eng Tack, Drew S verfasserin (orcid)0000-0002-9380-4643 aut The genotype‐phenotype landscape of an allosteric protein 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2021 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 $ 10^{5} $ 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. SYNOPSIS A large‐scale approach is used to measure the dose‐response curves of > 60,000 variants of the lac repressor. The results reveal systematic sequence‐structure‐function relationships underlying allostery, as well as a surprising diversity of allosteric phenotypes. Long‐read and short‐read DNA sequencing is used to measure the genotype and dose‐response phenotype of 62,000 variants of the lac repressor.The effects of single amino acid substitutions reveal systematic sequence‐structure‐function relationships underlying LacI allostery that may apply to allosteric proteins more generally.Novel phenotypes emerge with few substitutions, including variants with inverted dose‐response curves and variants with biphasic dose‐response curves. Graphical Abstract A large‐scale approach is used to measure the dose‐response curves of > 60,000 variants of the lac repressor. The results reveal systematic sequence‐structure‐function relationships underlying allostery, as well as a surprising diversity of allosteric phenotypes. allostery (dpeaa)DE-He213 genetic sensor (dpeaa)DE-He213 genotype‐phenotype relationships (dpeaa)DE-He213 high‐throughput measurements (dpeaa)DE-He213 transcription factor (dpeaa)DE-He213 Tonner, Peter D verfasserin (orcid)0000-0003-2840-0930 aut Pressman, Abe verfasserin aut Olson, Nathan D verfasserin (orcid)0000-0003-2585-3037 aut Levy, Sasha F verfasserin (orcid)0000-0002-0923-1636 aut Romantseva, Eugenia F verfasserin (orcid)0000-0003-0929-7966 aut Alperovich, Nina verfasserin aut Vasilyeva, Olga verfasserin aut Ross, David verfasserin (orcid)0000-0002-7790-218X aut Enthalten in Molecular Systems Biology Nature Publishing Group UK, 2023 17(2021), 3 vom: 30. März (DE-627)490536905 (DE-600)2193510-5 1744-4292 nnns volume:17 year:2021 number:3 day:30 month:03 https://dx.doi.org/10.15252/msb.202010179 X:SPRINGER Resolving-System kostenfrei Volltext SYSFLAG_0 GBV_SPRINGER GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_72 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_636 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4029 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4116 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4155 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4311 GBV_ILN_4313 GBV_ILN_4314 GBV_ILN_4315 GBV_ILN_4318 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4393 GBV_ILN_4598 GBV_ILN_4700 AR 17 2021 3 30 03 |
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10.15252/msb.202010179 doi (DE-627)SPR058094725 (SPR)msb.202010179-e DE-627 ger DE-627 rakwb eng Tack, Drew S verfasserin (orcid)0000-0002-9380-4643 aut The genotype‐phenotype landscape of an allosteric protein 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2021 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 $ 10^{5} $ 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. SYNOPSIS A large‐scale approach is used to measure the dose‐response curves of > 60,000 variants of the lac repressor. The results reveal systematic sequence‐structure‐function relationships underlying allostery, as well as a surprising diversity of allosteric phenotypes. Long‐read and short‐read DNA sequencing is used to measure the genotype and dose‐response phenotype of 62,000 variants of the lac repressor.The effects of single amino acid substitutions reveal systematic sequence‐structure‐function relationships underlying LacI allostery that may apply to allosteric proteins more generally.Novel phenotypes emerge with few substitutions, including variants with inverted dose‐response curves and variants with biphasic dose‐response curves. Graphical Abstract A large‐scale approach is used to measure the dose‐response curves of > 60,000 variants of the lac repressor. The results reveal systematic sequence‐structure‐function relationships underlying allostery, as well as a surprising diversity of allosteric phenotypes. allostery (dpeaa)DE-He213 genetic sensor (dpeaa)DE-He213 genotype‐phenotype relationships (dpeaa)DE-He213 high‐throughput measurements (dpeaa)DE-He213 transcription factor (dpeaa)DE-He213 Tonner, Peter D verfasserin (orcid)0000-0003-2840-0930 aut Pressman, Abe verfasserin aut Olson, Nathan D verfasserin (orcid)0000-0003-2585-3037 aut Levy, Sasha F verfasserin (orcid)0000-0002-0923-1636 aut Romantseva, Eugenia F verfasserin (orcid)0000-0003-0929-7966 aut Alperovich, Nina verfasserin aut Vasilyeva, Olga verfasserin aut Ross, David verfasserin (orcid)0000-0002-7790-218X aut Enthalten in Molecular Systems Biology Nature Publishing Group UK, 2023 17(2021), 3 vom: 30. März (DE-627)490536905 (DE-600)2193510-5 1744-4292 nnns volume:17 year:2021 number:3 day:30 month:03 https://dx.doi.org/10.15252/msb.202010179 X:SPRINGER Resolving-System kostenfrei Volltext SYSFLAG_0 GBV_SPRINGER GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_72 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_636 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4029 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4116 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4155 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4311 GBV_ILN_4313 GBV_ILN_4314 GBV_ILN_4315 GBV_ILN_4318 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4393 GBV_ILN_4598 GBV_ILN_4700 AR 17 2021 3 30 03 |
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10.15252/msb.202010179 doi (DE-627)SPR058094725 (SPR)msb.202010179-e DE-627 ger DE-627 rakwb eng Tack, Drew S verfasserin (orcid)0000-0002-9380-4643 aut The genotype‐phenotype landscape of an allosteric protein 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2021 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 $ 10^{5} $ 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. SYNOPSIS A large‐scale approach is used to measure the dose‐response curves of > 60,000 variants of the lac repressor. The results reveal systematic sequence‐structure‐function relationships underlying allostery, as well as a surprising diversity of allosteric phenotypes. Long‐read and short‐read DNA sequencing is used to measure the genotype and dose‐response phenotype of 62,000 variants of the lac repressor.The effects of single amino acid substitutions reveal systematic sequence‐structure‐function relationships underlying LacI allostery that may apply to allosteric proteins more generally.Novel phenotypes emerge with few substitutions, including variants with inverted dose‐response curves and variants with biphasic dose‐response curves. Graphical Abstract A large‐scale approach is used to measure the dose‐response curves of > 60,000 variants of the lac repressor. The results reveal systematic sequence‐structure‐function relationships underlying allostery, as well as a surprising diversity of allosteric phenotypes. allostery (dpeaa)DE-He213 genetic sensor (dpeaa)DE-He213 genotype‐phenotype relationships (dpeaa)DE-He213 high‐throughput measurements (dpeaa)DE-He213 transcription factor (dpeaa)DE-He213 Tonner, Peter D verfasserin (orcid)0000-0003-2840-0930 aut Pressman, Abe verfasserin aut Olson, Nathan D verfasserin (orcid)0000-0003-2585-3037 aut Levy, Sasha F verfasserin (orcid)0000-0002-0923-1636 aut Romantseva, Eugenia F verfasserin (orcid)0000-0003-0929-7966 aut Alperovich, Nina verfasserin aut Vasilyeva, Olga verfasserin aut Ross, David verfasserin (orcid)0000-0002-7790-218X aut Enthalten in Molecular Systems Biology Nature Publishing Group UK, 2023 17(2021), 3 vom: 30. März (DE-627)490536905 (DE-600)2193510-5 1744-4292 nnns volume:17 year:2021 number:3 day:30 month:03 https://dx.doi.org/10.15252/msb.202010179 X:SPRINGER Resolving-System kostenfrei Volltext SYSFLAG_0 GBV_SPRINGER GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_72 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_636 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4029 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4116 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4155 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4311 GBV_ILN_4313 GBV_ILN_4314 GBV_ILN_4315 GBV_ILN_4318 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4393 GBV_ILN_4598 GBV_ILN_4700 AR 17 2021 3 30 03 |
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Enthalten in Molecular Systems Biology 17(2021), 3 vom: 30. März volume:17 year:2021 number:3 day:30 month:03 |
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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 $ 10^{5} $ 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.</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">SYNOPSIS A large‐scale approach is used to measure the dose‐response curves of > 60,000 variants of the lac repressor. The results reveal systematic sequence‐structure‐function relationships underlying allostery, as well as a surprising diversity of allosteric phenotypes. Long‐read and short‐read DNA sequencing is used to measure the genotype and dose‐response phenotype of 62,000 variants of the lac repressor.The effects of single amino acid substitutions reveal systematic sequence‐structure‐function relationships underlying LacI allostery that may apply to allosteric proteins more generally.Novel phenotypes emerge with few substitutions, including variants with inverted dose‐response curves and variants with biphasic dose‐response curves.</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Graphical Abstract A large‐scale approach is used to measure the dose‐response curves of > 60,000 variants of the lac repressor. 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The genotype‐phenotype landscape of an allosteric protein allostery (dpeaa)DE-He213 genetic sensor (dpeaa)DE-He213 genotype‐phenotype relationships (dpeaa)DE-He213 high‐throughput measurements (dpeaa)DE-He213 transcription factor (dpeaa)DE-He213 |
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The genotype‐phenotype landscape of an allosteric protein |
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the genotype‐phenotype landscape of an allosteric protein |
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The genotype‐phenotype landscape of an allosteric protein |
| abstract |
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 $ 10^{5} $ 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. SYNOPSIS A large‐scale approach is used to measure the dose‐response curves of > 60,000 variants of the lac repressor. The results reveal systematic sequence‐structure‐function relationships underlying allostery, as well as a surprising diversity of allosteric phenotypes. Long‐read and short‐read DNA sequencing is used to measure the genotype and dose‐response phenotype of 62,000 variants of the lac repressor.The effects of single amino acid substitutions reveal systematic sequence‐structure‐function relationships underlying LacI allostery that may apply to allosteric proteins more generally.Novel phenotypes emerge with few substitutions, including variants with inverted dose‐response curves and variants with biphasic dose‐response curves. Graphical Abstract A large‐scale approach is used to measure the dose‐response curves of > 60,000 variants of the lac repressor. The results reveal systematic sequence‐structure‐function relationships underlying allostery, as well as a surprising diversity of allosteric phenotypes. © The Author(s) 2021 |
| abstractGer |
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 $ 10^{5} $ 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. SYNOPSIS A large‐scale approach is used to measure the dose‐response curves of > 60,000 variants of the lac repressor. The results reveal systematic sequence‐structure‐function relationships underlying allostery, as well as a surprising diversity of allosteric phenotypes. Long‐read and short‐read DNA sequencing is used to measure the genotype and dose‐response phenotype of 62,000 variants of the lac repressor.The effects of single amino acid substitutions reveal systematic sequence‐structure‐function relationships underlying LacI allostery that may apply to allosteric proteins more generally.Novel phenotypes emerge with few substitutions, including variants with inverted dose‐response curves and variants with biphasic dose‐response curves. Graphical Abstract A large‐scale approach is used to measure the dose‐response curves of > 60,000 variants of the lac repressor. The results reveal systematic sequence‐structure‐function relationships underlying allostery, as well as a surprising diversity of allosteric phenotypes. © The Author(s) 2021 |
| abstract_unstemmed |
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 $ 10^{5} $ 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. SYNOPSIS A large‐scale approach is used to measure the dose‐response curves of > 60,000 variants of the lac repressor. The results reveal systematic sequence‐structure‐function relationships underlying allostery, as well as a surprising diversity of allosteric phenotypes. Long‐read and short‐read DNA sequencing is used to measure the genotype and dose‐response phenotype of 62,000 variants of the lac repressor.The effects of single amino acid substitutions reveal systematic sequence‐structure‐function relationships underlying LacI allostery that may apply to allosteric proteins more generally.Novel phenotypes emerge with few substitutions, including variants with inverted dose‐response curves and variants with biphasic dose‐response curves. Graphical Abstract A large‐scale approach is used to measure the dose‐response curves of > 60,000 variants of the lac repressor. The results reveal systematic sequence‐structure‐function relationships underlying allostery, as well as a surprising diversity of allosteric phenotypes. © The Author(s) 2021 |
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| title_short |
The genotype‐phenotype landscape of an allosteric protein |
| url |
https://dx.doi.org/10.15252/msb.202010179 |
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| author2 |
Tonner, Peter D Pressman, Abe Olson, Nathan D Levy, Sasha F Romantseva, Eugenia F Alperovich, Nina Vasilyeva, Olga Ross, David |
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Tonner, Peter D Pressman, Abe Olson, Nathan D Levy, Sasha F Romantseva, Eugenia F Alperovich, Nina Vasilyeva, Olga Ross, David |
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| doi_str |
10.15252/msb.202010179 |
| up_date |
2024-10-25T04:56:12.810Z |
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| score |
7.4007034 |