1
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Wagner A. Genotype sampling for deep-learning assisted experimental mapping of a combinatorially complete fitness landscape. Bioinformatics 2024; 40:btae317. [PMID: 38745436 PMCID: PMC11132821 DOI: 10.1093/bioinformatics/btae317] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2024] [Revised: 03/21/2024] [Accepted: 05/14/2024] [Indexed: 05/16/2024] Open
Abstract
MOTIVATION Experimental characterization of fitness landscapes, which map genotypes onto fitness, is important for both evolutionary biology and protein engineering. It faces a fundamental obstacle in the astronomical number of genotypes whose fitness needs to be measured for any one protein. Deep learning may help to predict the fitness of many genotypes from a smaller neural network training sample of genotypes with experimentally measured fitness. Here I use a recently published experimentally mapped fitness landscape of more than 260 000 protein genotypes to ask how such sampling is best performed. RESULTS I show that multilayer perceptrons, recurrent neural networks, convolutional networks, and transformers, can explain more than 90% of fitness variance in the data. In addition, 90% of this performance is reached with a training sample comprising merely ≈103 sequences. Generalization to unseen test data is best when training data is sampled randomly and uniformly, or sampled to minimize the number of synonymous sequences. In contrast, sampling to maximize sequence diversity or codon usage bias reduces performance substantially. These observations hold for more than one network architecture. Simple sampling strategies may perform best when training deep learning neural networks to map fitness landscapes from experimental data. AVAILABILITY AND IMPLEMENTATION The fitness landscape data analyzed here is publicly available as described previously (Papkou et al. 2023). All code used to analyze this landscape is publicly available at https://github.com/andreas-wagner-uzh/fitness_landscape_sampling.
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Affiliation(s)
- Andreas Wagner
- Department of Evolutionary Biology and Environmental Studies, University of Zurich, 8057 Zurich, Switzerland
- Swiss Institute of Bioinformatics, Quartier Sorge-Batiment Genopode,1015 Lausanne, Switzerland
- The Santa Fe Institute, Santa Fe, 87501 NM, United States
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2
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Papkou A, Garcia-Pastor L, Escudero JA, Wagner A. A rugged yet easily navigable fitness landscape. Science 2023; 382:eadh3860. [PMID: 37995212 DOI: 10.1126/science.adh3860] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2023] [Accepted: 09/29/2023] [Indexed: 11/25/2023]
Abstract
Fitness landscape theory predicts that rugged landscapes with multiple peaks impair Darwinian evolution, but experimental evidence is limited. In this study, we used genome editing to map the fitness of >260,000 genotypes of the key metabolic enzyme dihydrofolate reductase in the presence of the antibiotic trimethoprim, which targets this enzyme. The resulting landscape is highly rugged and harbors 514 fitness peaks. However, its highest peaks are accessible to evolving populations via abundant fitness-increasing paths. Different peaks share large basins of attraction that render the outcome of adaptive evolution highly contingent on chance events. Our work shows that ruggedness need not be an obstacle to Darwinian evolution but can reduce its predictability. If true in general, the complexity of optimization problems on realistic landscapes may require reappraisal.
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Affiliation(s)
- Andrei Papkou
- Department of Evolutionary Biology and Environmental Studies, University of Zurich, Zurich, Switzerland
| | - Lucia Garcia-Pastor
- Departamento de Sanidad Animal and VISAVET Health Surveillance Centre, Universidad Complutense de Madrid, Madrid, Spain
| | - José Antonio Escudero
- Departamento de Sanidad Animal and VISAVET Health Surveillance Centre, Universidad Complutense de Madrid, Madrid, Spain
| | - Andreas Wagner
- Department of Evolutionary Biology and Environmental Studies, University of Zurich, Zurich, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
- The Santa Fe Institute, Santa Fe, NM, USA
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3
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Chowdhury S, Zielinski DC, Dalldorf C, Rodrigues JV, Palsson BO, Shakhnovich EI. Empowering drug off-target discovery with metabolic and structural analysis. Nat Commun 2023; 14:3390. [PMID: 37296102 PMCID: PMC10256842 DOI: 10.1038/s41467-023-38859-x] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2022] [Accepted: 05/15/2023] [Indexed: 06/12/2023] Open
Abstract
Elucidating intracellular drug targets is a difficult problem. While machine learning analysis of omics data has been a promising approach, going from large-scale trends to specific targets remains a challenge. Here, we develop a hierarchic workflow to focus on specific targets based on analysis of metabolomics data and growth rescue experiments. We deploy this framework to understand the intracellular molecular interactions of the multi-valent dihydrofolate reductase-targeting antibiotic compound CD15-3. We analyse global metabolomics data utilizing machine learning, metabolic modelling, and protein structural similarity to prioritize candidate drug targets. Overexpression and in vitro activity assays confirm one of the predicted candidates, HPPK (folK), as a CD15-3 off-target. This study demonstrates how established machine learning methods can be combined with mechanistic analyses to improve the resolution of drug target finding workflows for discovering off-targets of a metabolic inhibitor.
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Affiliation(s)
- Sourav Chowdhury
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA, USA
| | - Daniel C Zielinski
- Department of Bioengineering, University of California, San Diego, La Jolla, CA, USA
| | - Christopher Dalldorf
- Department of Bioengineering, University of California, San Diego, La Jolla, CA, USA
| | - Joao V Rodrigues
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA, USA
| | - Bernhard O Palsson
- Department of Bioengineering, University of California, San Diego, La Jolla, CA, USA
- Department of Pediatrics, University of California, San Diego, La Jolla, CA, USA
- Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, Kemitorvet, Building 220, 2800, Kongens Lyngby, Denmark
| | - Eugene I Shakhnovich
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA, USA.
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4
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Angermayr SA, Pang TY, Chevereau G, Mitosch K, Lercher MJ, Bollenbach T. Growth-mediated negative feedback shapes quantitative antibiotic response. Mol Syst Biol 2022; 18:e10490. [PMID: 36124745 PMCID: PMC9486506 DOI: 10.15252/msb.202110490] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2021] [Revised: 08/19/2022] [Accepted: 08/26/2022] [Indexed: 11/15/2022] Open
Abstract
Dose-response relationships are a general concept for quantitatively describing biological systems across multiple scales, from the molecular to the whole-cell level. A clinically relevant example is the bacterial growth response to antibiotics, which is routinely characterized by dose-response curves. The shape of the dose-response curve varies drastically between antibiotics and plays a key role in treatment, drug interactions, and resistance evolution. However, the mechanisms shaping the dose-response curve remain largely unclear. Here, we show in Escherichia coli that the distinctively shallow dose-response curve of the antibiotic trimethoprim is caused by a negative growth-mediated feedback loop: Trimethoprim slows growth, which in turn weakens the effect of this antibiotic. At the molecular level, this feedback is caused by the upregulation of the drug target dihydrofolate reductase (FolA/DHFR). We show that this upregulation is not a specific response to trimethoprim but follows a universal trend line that depends primarily on the growth rate, irrespective of its cause. Rewiring the feedback loop alters the dose-response curve in a predictable manner, which we corroborate using a mathematical model of cellular resource allocation and growth. Our results indicate that growth-mediated feedback loops may shape drug responses more generally and could be exploited to design evolutionary traps that enable selection against drug resistance.
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Affiliation(s)
- S Andreas Angermayr
- Institute for Biological PhysicsUniversity of CologneCologneGermany
- Institute of Science and Technology AustriaKlosterneuburgAustria
- Present address:
CeMM Research Center for Molecular Medicine of the Austrian Academy of SciencesViennaAustria
| | - Tin Yau Pang
- Institute for Computer ScienceHeinrich Heine University DüsseldorfDüsseldorfGermany
- Department of BiologyHeinrich Heine University DüsseldorfDüsseldorfGermany
| | | | - Karin Mitosch
- Institute of Science and Technology AustriaKlosterneuburgAustria
- Genome Biology UnitEuropean Molecular Biology Laboratory (EMBL)HeidelbergGermany
| | - Martin J Lercher
- Institute for Computer ScienceHeinrich Heine University DüsseldorfDüsseldorfGermany
- Department of BiologyHeinrich Heine University DüsseldorfDüsseldorfGermany
| | - Tobias Bollenbach
- Institute for Biological PhysicsUniversity of CologneCologneGermany
- Center for Data and Simulation ScienceUniversity of CologneCologneGermany
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5
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Gao L, Wu X, Li C, Xia X. Exploitation of Strong Constitutive and Stress-driven Promoters from Acetobacter pasteurianus for Improving Acetic acid Tolerance. J Biotechnol 2022; 350:24-30. [PMID: 35390361 DOI: 10.1016/j.jbiotec.2022.03.013] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2021] [Revised: 03/28/2022] [Accepted: 03/30/2022] [Indexed: 10/18/2022]
Abstract
Acetobacter pasteurianus is an excellent cell factory for production of highly-strength acetic acid, and attracts an increasing attention in metabolic engineering. However, the available well-characterized constitutive and inducible promoters are rather limited to adjust metabolic fluxes in A. pasteurianus. In this study, we screened a panel of constitutive and acid stress-driven promoters based on time-series of RNA-seq data and characterized in A. pasteurianus and Escherichia coli. Nine constitutive promoters ranged in strength from 1.7-fold to 100-fold that of the well-known strong promoter Padh under non-acetic acid environment. Subsequently, an acetic acid-stable red fluorescent visual reporting system was established and applied to evaluate acid stress-driven promoter in A. pasteurianus during highly-acidic fermentation environment. PgroES was identified as acid stress-driven strong promoters, with expression outputs varied from 100% to 200% when acetic acid treatment. To assess their application potential, ultra-strong constitutive promoter Ptuf and acid stress-driven strong promoter PgroES were selected to overexpress acetyl-CoA synthase and greatly improved acetic acid tolerance. Notably, the acid stress-driven promoter displayed more favorable for regulating strain robustness against acid stress by overexpressing tolerance gene. In summary, this is the first well-characterized constitutive and acid stress-driven promoter library from A. pasteurianus, which could be used as a promising toolbox for metabolic engineering in acetic acid bacteria and other gram-negative bacteria.
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Affiliation(s)
- Ling Gao
- The Key Laboratory of Industrial Biotechnology, Ministry of Education, School of Biotechnology, Jiangnan University, Wuxi, PR China; State Key Laboratory of Biobased Material and Green Papermaking, Qilu University of Technology, Shandong Academy of Sciences, Jinan, PR China
| | - Xiaodan Wu
- The Key Laboratory of Industrial Biotechnology, Ministry of Education, School of Biotechnology, Jiangnan University, Wuxi, PR China
| | - Chenyu Li
- State Key Laboratory of Biobased Material and Green Papermaking, Qilu University of Technology, Shandong Academy of Sciences, Jinan, PR China
| | - Xiaole Xia
- The Key Laboratory of Industrial Biotechnology, Ministry of Education, School of Biotechnology, Jiangnan University, Wuxi, PR China.
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6
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Razban RM, Dasmeh P, Serohijos AWR, Shakhnovich EI. Avoidance of protein unfolding constrains protein stability in long-term evolution. Biophys J 2021; 120:2413-2424. [PMID: 33932438 PMCID: PMC8390877 DOI: 10.1016/j.bpj.2021.03.042] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2020] [Revised: 02/24/2021] [Accepted: 03/17/2021] [Indexed: 11/28/2022] Open
Abstract
Every amino acid residue can influence a protein's overall stability, making stability highly susceptible to change throughout evolution. We consider the distribution of protein stabilities evolutionarily permittable under two previously reported protein fitness functions: flux dynamics and misfolding avoidance. We develop an evolutionary dynamics theory and find that it agrees better with an extensive protein stability data set for dihydrofolate reductase orthologs under the misfolding avoidance fitness function rather than the flux dynamics fitness function. Further investigation with ribonuclease H data demonstrates that not any misfolded state is avoided; rather, it is only the unfolded state. At the end, we discuss how our work pertains to the universal protein abundance-evolutionary rate correlation seen across organisms' proteomes. We derive a closed-form expression relating protein abundance to evolutionary rate that captures Escherichia coli, Saccharomyces cerevisiae, and Homo sapiens experimental trends without fitted parameters.
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Affiliation(s)
- Rostam M Razban
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, Massachusetts
| | - Pouria Dasmeh
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, Massachusetts; Departement de Biochimie, Université de Montréal, Montreal, Quebec, Canada
| | | | - Eugene I Shakhnovich
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, Massachusetts.
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7
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Bhattacharyya S, Bershtein S, Adkar BV, Woodard J, Shakhnovich EI. Metabolic response to point mutations reveals principles of modulation of in vivo enzyme activity and phenotype. Mol Syst Biol 2021; 17:e10200. [PMID: 34180142 PMCID: PMC8236904 DOI: 10.15252/msb.202110200] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/01/2021] [Revised: 05/08/2021] [Accepted: 05/11/2021] [Indexed: 12/14/2022] Open
Abstract
The relationship between sequence variation and phenotype is poorly understood. Here, we use metabolomic analysis to elucidate the molecular mechanism underlying the filamentous phenotype of E. coli strains that carry destabilizing mutations in dihydrofolate reductase (DHFR). We find that partial loss of DHFR activity causes reversible filamentation despite SOS response indicative of DNA damage, in contrast to thymineless death (TLD) achieved by complete inhibition of DHFR activity by high concentrations of antibiotic trimethoprim. This phenotype is triggered by a disproportionate drop in intracellular dTTP, which could not be explained by drop in dTMP based on the Michaelis-Menten-like in vitro activity curve of thymidylate kinase (Tmk), a downstream enzyme that phosphorylates dTMP to dTDP. Instead, we show that a highly cooperative (Hill coefficient 2.5) in vivo activity of Tmk is the cause of suboptimal dTTP levels. dTMP supplementation rescues filamentation and restores in vivo Tmk kinetics to Michaelis-Menten. Overall, this study highlights the important role of cellular environment in sculpting enzymatic kinetics with system-level implications for bacterial phenotype.
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Affiliation(s)
| | - Shimon Bershtein
- Department of Life SciencesBen‐Gurion University of the NegevBeer‐ShevaIsrael
| | - Bharat V Adkar
- Department of Chemistry and Chemical BiologyHarvard UniversityCambridgeMAUSA
| | - Jaie Woodard
- Department of Chemistry and Chemical BiologyHarvard UniversityCambridgeMAUSA
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8
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Anand A, Olson CA, Sastry AV, Patel A, Szubin R, Yang L, Feist AM, Palsson BO. Restoration of fitness lost due to dysregulation of the pyruvate dehydrogenase complex is triggered by ribosomal binding site modifications. Cell Rep 2021; 35:108961. [PMID: 33826886 PMCID: PMC8489512 DOI: 10.1016/j.celrep.2021.108961] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2020] [Revised: 02/22/2021] [Accepted: 03/16/2021] [Indexed: 11/23/2022] Open
Abstract
Pyruvate dehydrogenase complex (PDC) functions as the main determinant of the respiro-fermentative balance because it converts pyruvate to acetyl-coenzyme A (CoA), which then enters the TCA (tricarboxylic acid cycle). PDC is repressed by the pyruvate dehydrogenase complex regulator (PdhR) in Escherichia coli. The deletion of the pdhR gene compromises fitness in aerobic environments. We evolve the E. coli pdhR deletion strain to examine its achievable growth rate and the underlying adaptive strategies. We find that (1) optimal proteome allocation to PDC is critical in achieving optimal growth rate; (2) expression of PDC in evolved strains is reduced through mutations in the Shine-Dalgarno sequence; (3) rewiring of the TCA flux and increased reactive oxygen species (ROS) defense occur in the evolved strains; and (4) the evolved strains adapt to an efficient biomass yield. Together, these results show how adaptation can find alternative regulatory mechanisms for a key cellular process if the primary regulatory mode fails.
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Affiliation(s)
- Amitesh Anand
- Department of Bioengineering, University of California, San Diego, La Jolla, CA 92093, USA
| | - Connor A Olson
- Department of Bioengineering, University of California, San Diego, La Jolla, CA 92093, USA
| | - Anand V Sastry
- Department of Bioengineering, University of California, San Diego, La Jolla, CA 92093, USA
| | - Arjun Patel
- Department of Bioengineering, University of California, San Diego, La Jolla, CA 92093, USA
| | - Richard Szubin
- Department of Bioengineering, University of California, San Diego, La Jolla, CA 92093, USA
| | - Laurence Yang
- Department of Bioengineering, University of California, San Diego, La Jolla, CA 92093, USA; Department of Chemical Engineering, Queen's University, Kingston, ON, Canada
| | - Adam M Feist
- Department of Bioengineering, University of California, San Diego, La Jolla, CA 92093, USA; Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, Kemitorvet, Building 220, 2800 Kongens, Lyngby, Denmark
| | - Bernhard O Palsson
- Department of Bioengineering, University of California, San Diego, La Jolla, CA 92093, USA; Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, Kemitorvet, Building 220, 2800 Kongens, Lyngby, Denmark.
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9
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Kovács K, Farkas Z, Bajić D, Kalapis D, Daraba A, Almási K, Kintses B, Bódi Z, Notebaart RA, Poyatos JF, Kemmeren P, Holstege FCP, Pál C, Papp B. Suboptimal Global Transcriptional Response Increases the Harmful Effects of Loss-of-Function Mutations. Mol Biol Evol 2021; 38:1137-1150. [PMID: 33306797 PMCID: PMC7947755 DOI: 10.1093/molbev/msaa280] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/04/2023] Open
Abstract
The fitness impact of loss-of-function mutations is generally assumed to reflect the loss of specific molecular functions associated with the perturbed gene. Here, we propose that rewiring of the transcriptome upon deleterious gene inactivation is frequently nonspecific and mimics stereotypic responses to external environmental change. Consequently, transcriptional response to gene deletion could be suboptimal and incur an extra fitness cost. Analysis of the transcriptomes of ∼1,500 single-gene deletion Saccharomyces cerevisiae strains supported this scenario. First, most transcriptomic changes are not specific to the deleted gene but are rather triggered by perturbations in functionally diverse genes. Second, gene deletions that alter the expression of dosage-sensitive genes are especially harmful. Third, by elevating the expression level of downregulated genes, we could experimentally mitigate the fitness defect of gene deletions. Our work shows that rewiring of genomic expression upon gene inactivation shapes the harmful effects of mutations.
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Affiliation(s)
- Károly Kovács
- HCEMM-BRC Metabolic Systems Biology Lab, Szeged, Hungary
- Biological Research Centre, Synthetic and Systems Biology Unit, Institute of Biochemistry, Szeged, Hungary
| | - Zoltán Farkas
- Biological Research Centre, Synthetic and Systems Biology Unit, Institute of Biochemistry, Szeged, Hungary
| | - Djordje Bajić
- Biological Research Centre, Synthetic and Systems Biology Unit, Institute of Biochemistry, Szeged, Hungary
- Logic of Genomic Systems Laboratory, Department of Systems Biology, CNB-CSIC, Madrid, Spain
- Department of Ecology and Evolutionary Biology, Yale University, New Haven, CT
- Microbial Sciences Institute, Yale University West Campus, West Haven, CT
| | - Dorottya Kalapis
- HCEMM-BRC Metabolic Systems Biology Lab, Szeged, Hungary
- Biological Research Centre, Synthetic and Systems Biology Unit, Institute of Biochemistry, Szeged, Hungary
| | - Andreea Daraba
- Biological Research Centre, Synthetic and Systems Biology Unit, Institute of Biochemistry, Szeged, Hungary
| | - Karola Almási
- Biological Research Centre, Synthetic and Systems Biology Unit, Institute of Biochemistry, Szeged, Hungary
| | - Bálint Kintses
- Biological Research Centre, Synthetic and Systems Biology Unit, Institute of Biochemistry, Szeged, Hungary
- HCEMM-BRC Translational Microbiology Lab, Szeged, Hungary
- Department of Biochemistry and Molecular Biology, University of Szeged, Szeged, Hungary
| | - Zoltán Bódi
- Biological Research Centre, Synthetic and Systems Biology Unit, Institute of Biochemistry, Szeged, Hungary
| | - Richard A Notebaart
- Food Microbiology, Wageningen University & Research, Wageningen, The Netherlands
| | - Juan F Poyatos
- Logic of Genomic Systems Laboratory, Department of Systems Biology, CNB-CSIC, Madrid, Spain
| | - Patrick Kemmeren
- Princess Máxima Center for Pediatric Oncology, Utrecht, The Netherlands
| | | | - Csaba Pál
- Biological Research Centre, Synthetic and Systems Biology Unit, Institute of Biochemistry, Szeged, Hungary
| | - Balázs Papp
- HCEMM-BRC Metabolic Systems Biology Lab, Szeged, Hungary
- Biological Research Centre, Synthetic and Systems Biology Unit, Institute of Biochemistry, Szeged, Hungary
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10
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Gao L, Wu X, Xia X, Jin Z. Fine-tuning ethanol oxidation pathway enzymes and cofactor PQQ coordinates the conflict between fitness and acetic acid production by Acetobacter pasteurianus. Microb Biotechnol 2020; 14:643-655. [PMID: 33174682 PMCID: PMC7936290 DOI: 10.1111/1751-7915.13703] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2020] [Revised: 09/23/2020] [Accepted: 10/22/2020] [Indexed: 12/28/2022] Open
Abstract
The very high concentrations required for industrial production of free acetic acid create toxicity and low pH values, which usually conflict with the host cell growth, leading to a poor productivity. Achieving a balance between cell fitness and product synthesis is the key challenge to improving acetic acid production efficiency in metabolic engineering. Here, we show that the synergistic regulation of alcohol/aldehyde dehydrogenase expression and cofactor PQQ level could not only efficiently relieve conflict between increased acetic acid production and compromised cell fitness, but also greatly enhance acetic acid tolerance of Acetobacter pasteurianus to a high initial concentration (3% v/v) of acetic acid. Combinatorial expression of adhA and pqqABCDE greatly shortens the duration of starting‐up process from 116 to 99 h, leading to a yield of 69 g l‐1 acetic acid in semi‐continuous fermentation. As a final result, average acetic acid productivity has been raised to 0.99 g l‐1 h‐1, which was 32% higher than the parental A. pasteurianus. This study is of great significance for decreasing cost of semi‐continuous fermentation for producing high‐strength acetic acid industrially. We envisioned that this strategy will be useful for production of many other desired organic acids, especially those involving cofactor reactions.
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Affiliation(s)
- Ling Gao
- State Key Laboratory of Food Science and Technology, School of Food Science and Technology, Jiangnan University, Wuxi, China.,State Key Laboratory of Biobased Material and Green Papermaking, Qilu University of Technology, Shandong Academy of Sciences, Jinan, China
| | - Xiaodan Wu
- The Key Laboratory of Industrial Biotechnology, Ministry of Education, School of Biotechnology, Jiangnan University, Wuxi, China
| | - Xiaole Xia
- State Key Laboratory of Food Science and Technology, School of Food Science and Technology, Jiangnan University, Wuxi, China.,The Key Laboratory of Industrial Biotechnology, Ministry of Education, School of Biotechnology, Jiangnan University, Wuxi, China
| | - Zhengyu Jin
- State Key Laboratory of Food Science and Technology, School of Food Science and Technology, Jiangnan University, Wuxi, China
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11
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Thompson S, Zhang Y, Ingle C, Reynolds KA, Kortemme T. Altered expression of a quality control protease in E. coli reshapes the in vivo mutational landscape of a model enzyme. eLife 2020; 9:53476. [PMID: 32701056 PMCID: PMC7377907 DOI: 10.7554/elife.53476] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2019] [Accepted: 07/09/2020] [Indexed: 12/03/2022] Open
Abstract
Protein mutational landscapes are shaped by the cellular environment, but key factors and their quantitative effects are often unknown. Here we show that Lon, a quality control protease naturally absent in common E. coli expression strains, drastically reshapes the mutational landscape of the metabolic enzyme dihydrofolate reductase (DHFR). Selection under conditions that resolve highly active mutants reveals that 23.3% of all single point mutations in DHFR are advantageous in the absence of Lon, but advantageous mutations are largely suppressed when Lon is reintroduced. Protein stability measurements demonstrate extensive activity-stability tradeoffs for the advantageous mutants and provide a mechanistic explanation for Lon’s widespread impact. Our findings suggest possibilities for tuning mutational landscapes by modulating the cellular environment, with implications for protein design and combatting antibiotic resistance.
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Affiliation(s)
- Samuel Thompson
- Graduate Group in Biophysics, University of California San Francisco, San Francisco, United States
| | - Yang Zhang
- Department of Bioengineering and Therapeutic Sciences, University of California San Francisco, San Francisco, United States
| | - Christine Ingle
- The Green Center for Systems Biology, University of Texas Southwestern Medical Center, Dallas, United States
| | - Kimberly A Reynolds
- The Green Center for Systems Biology, University of Texas Southwestern Medical Center, Dallas, United States.,Department of Biophysics, University of Texas Southwestern Medical Center, Dallas, United States
| | - Tanja Kortemme
- Graduate Group in Biophysics, University of California San Francisco, San Francisco, United States.,Department of Bioengineering and Therapeutic Sciences, University of California San Francisco, San Francisco, United States.,Chan Zuckerberg Biohub, San Francisco, United States
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12
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Abstract
The distribution of fitness effects of mutation plays a central role in constraining protein evolution. The underlying mechanisms by which mutations lead to fitness effects are typically attributed to changes in protein specific activity or abundance. Here, we reveal the importance of a mutation's collateral fitness effects, which we define as effects that do not derive from changes in the protein's ability to perform its physiological function. We comprehensively measured the collateral fitness effects of missense mutations in the Escherichia coli TEM-1 β-lactamase antibiotic resistance gene using growth competition experiments in the absence of antibiotic. At least 42% of missense mutations in TEM-1 were deleterious, indicating that for some proteins collateral fitness effects occur as frequently as effects on protein activity and abundance. Deleterious mutations caused improper posttranslational processing, incorrect disulfide-bond formation, protein aggregation, changes in gene expression, and pleiotropic effects on cell phenotype. Deleterious collateral fitness effects occurred more frequently in TEM-1 than deleterious effects on antibiotic resistance in environments with low concentrations of the antibiotic. The surprising prevalence of deleterious collateral fitness effects suggests they may play a role in constraining protein evolution, particularly for highly expressed proteins, for proteins under intermittent selection for their physiological function, and for proteins whose contribution to fitness is buffered against deleterious effects on protein activity and protein abundance.
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13
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Chromosomal barcoding of E. coli populations reveals lineage diversity dynamics at high resolution. Nat Ecol Evol 2020; 4:437-452. [PMID: 32094541 DOI: 10.1038/s41559-020-1103-z] [Citation(s) in RCA: 28] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2019] [Accepted: 01/08/2020] [Indexed: 01/28/2023]
Abstract
Evolutionary dynamics in large asexual populations is strongly influenced by multiple competing beneficial lineages, most of which segregate at very low frequencies. However, technical barriers to tracking a large number of these rare lineages in bacterial populations have so far prevented a detailed elucidation of evolutionary dynamics. Here, we overcome this hurdle by developing a chromosomal-barcoding technique that allows simultaneous tracking of approximately 450,000 distinct lineages in Escherichia coli, which we use to test the effect of sub-inhibitory concentrations of common antibiotics on the evolutionary dynamics of low-frequency lineages. We find that populations lose lineage diversity at distinct rates that correspond to their antibiotic regimen. We also determine that some lineages have similar fates across independent experiments. By analysing the trajectory dynamics, we attribute the reproducible fates of these lineages to the presence of pre-existing beneficial mutations, and we demonstrate how the relative contribution of pre-existing and de novo mutations varies across drug regimens. Finally, we reproduce the observed lineage dynamics by simulations. Altogether, our results provide a valuable methodology for studying bacterial evolution as well as insights into evolution under sub-inhibitory antibiotic levels.
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14
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Eguchi Y, Bilolikar G, Geiler-Samerotte K. Why and how to study genetic changes with context-dependent effects. Curr Opin Genet Dev 2019; 58-59:95-102. [PMID: 31593884 DOI: 10.1016/j.gde.2019.08.003] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2019] [Revised: 08/21/2019] [Accepted: 08/29/2019] [Indexed: 01/18/2023]
Abstract
The phenotypic impacts of a genetic change can depend on genetic background (e.g. epistasis), as well as other contexts including environment, developmental stage, cell type, disease state, and higher-order combinations thereof. Recent advances in high-throughput phenotyping are uncovering examples of context dependence faster than genotype-phenotype maps and other core concepts are changing to reflect the dynamic nature of biological systems. Here, we review several approaches to study context dependence and their findings. In our opinion, these findings encourage more studies that examine the spectrum of effects a genetic change may have, as opposed to studies that exclusively measure the impact of a genetic change in a particular context. Studies that elucidate the mechanisms that cause the effects of genetic change to vary with context are of special interest. Previous studies of the mechanisms underlying context dependence have improved predictions of phenotype from genotype and have provided insight about how biological systems function and evolve.
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Affiliation(s)
- Yuichi Eguchi
- Center for Mechanisms of Evolution, School of Life Sciences, Arizona State University, Tempe, AZ 85287, United States
| | - Gaurav Bilolikar
- Center for Mechanisms of Evolution, School of Life Sciences, Arizona State University, Tempe, AZ 85287, United States
| | - Kerry Geiler-Samerotte
- Center for Mechanisms of Evolution, School of Life Sciences, Arizona State University, Tempe, AZ 85287, United States.
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15
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Rodrigues JV, Shakhnovich EI. Adaptation to mutational inactivation of an essential gene converges to an accessible suboptimal fitness peak. eLife 2019; 8:50509. [PMID: 31573512 PMCID: PMC6828540 DOI: 10.7554/elife.50509] [Citation(s) in RCA: 22] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2019] [Accepted: 09/30/2019] [Indexed: 12/14/2022] Open
Abstract
The mechanisms of adaptation to inactivation of essential genes remain unknown. Here we inactivate E. coli dihydrofolate reductase (DHFR) by introducing D27G,N,F chromosomal mutations in a key catalytic residue with subsequent adaptation by an automated serial transfer protocol. The partial reversal G27- > C occurred in three evolutionary trajectories. Conversely, in one trajectory for D27G and in all trajectories for D27F,N strains adapted to grow at very low metabolic supplement (folAmix) concentrations but did not escape entirely from supplement auxotrophy. Major global shifts in metabolome and proteome occurred upon DHFR inactivation, which were partially reversed in adapted strains. Loss-of-function mutations in two genes, thyA and deoB, ensured adaptation to low folAmix by rerouting the 2-Deoxy-D-ribose-phosphate metabolism from glycolysis towards synthesis of dTMP. Multiple evolutionary pathways of adaptation converged to a suboptimal solution due to the high accessibility to loss-of-function mutations that block the path to the highest, yet least accessible, fitness peak. Predicting how viruses and bacteria evolve remains a challenge. The ability to anticipate when and how bacteria might develop drug resistance would make treating life-threatening diseases easier and could potentially help prevent drug resistance altogether. Studying bacterial evolution under different conditions and cataloguing all possible DNA mutations that allow these bacteria to survive are crucial steps in predicting the appearance of drug resistance. Studies have revealed that bacteria can adapt to sources of stress, such as antibiotics, in different ways – each involving mutations in distinct genes. However, not all the mutations provide the same benefits to the organism, and the factors that influence how bacteria will adapt are unclear. Now, Rodrigues and Shakhnovich have used a new approach to push the adaptation ability of the bacterium Escherichia coli to the limit. First, they genetically engineered different E. coli strains by introducing distinct mutations to an enzyme the bacterium needs to make DNA. These mutations make the resulting strains dependent on external molecules to synthesize new DNA. Next, the cells were grown in conditions where the supply of these DNA precursors was progressively decreased, forcing them to adapt. The obvious way for bacteria to adapt to these conditions would be to ‘revert’ the mutations that Rodrigues and Shakhnovich introduced in the first place. By using this approach, Rodrigues and Shakhnovich were able to test how often the obvious evolutionary solution happens compared with presumably less-preferred alternative routes. In rare cases, a specific mutation did restore the activity of the enzyme that enabled DNA synthesis. However, in most cases the bacteria found a different evolutionary solution whereby they all adapt to the decrease in external DNA precursors in the same way, but not by reverting the original mutation. Instead, further mutations disrupt the activity of two metabolic genes, allowing the cells to use the external DNA precursors more efficiently, and keep building DNA. These cells are therefore able to survive even when the levels of the external DNA components are very low, but they will die in the complete absence of these precursor molecules. This evolutionary solution leads to a non-optimal effect: mutations that restore the activity of the original enzyme, which are the best solution when the two metabolic genes are intact, are no longer as effective. This finding represents a clear example of interactions between genes determining evolutionary outcomes. Rodrigues and Shakhnovich showed that, since it is more likely for a random mutation to disrupt a gene than to revert a previous mutation, adaptations that are less-than-optimal but still work might predominate simply because they happen faster. Understanding why certain evolutionary adaptations prevail is an important step in predicting evolution and may lead to breakthroughs in many areas. For example, if scientists can identify mutations likely to make bacteria resistant to drugs, it may be possible to act proactively against the bacterial strains that carry those mutations. Eventually, if the factors that lead to specific adaptations are known, it may be possible to exploit this knowledge to create weaknesses in the bacteria’s own defences.
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Affiliation(s)
- João V Rodrigues
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, United States
| | - Eugene I Shakhnovich
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, United States
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16
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Gallie J, Bertels F, Remigi P, Ferguson GC, Nestmann S, Rainey PB. Repeated Phenotypic Evolution by Different Genetic Routes in Pseudomonas fluorescens SBW25. Mol Biol Evol 2019; 36:1071-1085. [PMID: 30835268 PMCID: PMC6519391 DOI: 10.1093/molbev/msz040] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022] Open
Abstract
Repeated evolution of functionally similar phenotypes is observed throughout the tree of life. The extent to which the underlying genetics are conserved remains an area of considerable interest. Previously, we reported the evolution of colony switching in two independent lineages of Pseudomonas fluorescens SBW25. The phenotypic and genotypic bases of colony switching in the first lineage (Line 1) have been described elsewhere. Here, we deconstruct the evolution of colony switching in the second lineage (Line 6). We show that, as for Line 1, Line 6 colony switching results from an increase in the expression of a colanic acid-like polymer (CAP). At the genetic level, nine mutations occur in Line 6. Only one of these—a nonsynonymous point mutation in the housekeeping sigma factor rpoD—is required for colony switching. In contrast, the genetic basis of colony switching in Line 1 is a mutation in the metabolic gene carB. A molecular model has recently been proposed whereby the carB mutation increases capsulation by redressing the intracellular balance of positive (ribosomes) and negative (RsmAE/CsrA) regulators of a positive feedback loop in capsule expression. We show that Line 6 colony switching is consistent with this model; the rpoD mutation generates an increase in ribosomal gene expression, and ultimately an increase in CAP expression.
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Affiliation(s)
- Jenna Gallie
- Department of Evolutionary Theory, Max Planck Institute for Evolutionary Biology, Plön, Germany.,New Zealand Institute for Advanced Study, Massey University at Albany, Auckland, New Zealand
| | - Frederic Bertels
- New Zealand Institute for Advanced Study, Massey University at Albany, Auckland, New Zealand.,Department of Microbial Population Biology, Max Planck Institute for Evolutionary Biology, Plön, Germany
| | - Philippe Remigi
- New Zealand Institute for Advanced Study, Massey University at Albany, Auckland, New Zealand.,Laboratoire des Interactions Plantes-Microorganismes (LIPM), Université de Toulouse, INRA, CNRS, Castanet-Tolosan, France
| | - Gayle C Ferguson
- School of Natural and Computational Sciences, Massey University at Albany, Auckland, New Zealand
| | - Sylke Nestmann
- New Zealand Institute for Advanced Study, Massey University at Albany, Auckland, New Zealand
| | - Paul B Rainey
- New Zealand Institute for Advanced Study, Massey University at Albany, Auckland, New Zealand.,Department of Microbial Population Biology, Max Planck Institute for Evolutionary Biology, Plön, Germany.,Ecole Supérieure de Physique et de Chimie Industrielles de la Ville de Paris (ESPCI ParisTech), CNRS UMR 8231, PSL Research University, Paris, France
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17
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Rodrigues JV, Ogbunugafor CB, Hartl DL, Shakhnovich EI. Chimeric dihydrofolate reductases display properties of modularity and biophysical diversity. Protein Sci 2019; 28:1359-1367. [PMID: 31095809 DOI: 10.1002/pro.3646] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2019] [Accepted: 05/13/2019] [Indexed: 01/12/2023]
Abstract
While reverse genetics and functional genomics have long affirmed the role of individual mutations in determining protein function, there have been fewer studies addressing how large-scale changes in protein sequences, such as in entire modular segments, influence protein function and evolution. Given how recombination can reassort protein sequences, these types of changes may play an underappreciated role in how novel protein functions evolve in nature. Such studies could aid our understanding of whether certain organismal phenotypes related to protein function-such as growth in the presence or absence of an antibiotic-are robust with respect to the identity of certain modular segments. In this study, we combine molecular genetics with biochemical and biophysical methods to gain a better understanding of protein modularity in dihydrofolate reductase (DHFR), an enzyme target of antibiotics also widely used as a model for protein evolution. We replace an integral α-helical segment of Escherichia coli DHFR with segments from a number of different organisms (many nonmicrobial) and examine how these chimeric enzymes affect organismal phenotypes (e.g., resistance to an antibiotic) as well as biophysical properties of the enzyme (e.g., thermostability). We find that organismal phenotypes and enzyme properties are highly sensitive to the identity of DHFR modules, and that this chimeric approach can create enzymes with diverse biophysical characteristics.
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Affiliation(s)
- João V Rodrigues
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, Massachusetts
| | - C Brandon Ogbunugafor
- Department of Ecology and Evolutionary Biology, Brown University, Providence, Rhode Island
| | - Daniel L Hartl
- Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, Massachusetts
| | - Eugene I Shakhnovich
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, Massachusetts
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18
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Dasmeh P, Serohijos AWR. Estimating the contribution of folding stability to nonspecific epistasis in protein evolution. Proteins 2018; 86:1242-1250. [DOI: 10.1002/prot.25588] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2018] [Revised: 06/28/2018] [Accepted: 07/18/2018] [Indexed: 12/28/2022]
Affiliation(s)
- Pouria Dasmeh
- Department of BiochemistryUniversity of Montreal Montreal Quebec Canada
- Cedergren Center for Bioinformatics and GenomicsUniversity of Montreal Montreal, Quebec Canada
- Department of Biochemistry and Institute for Data Valorization (IVADO)University of Montreal Montreal, Quebec Canada
| | - Adrian W. R. Serohijos
- Department of BiochemistryUniversity of Montreal Montreal Quebec Canada
- Cedergren Center for Bioinformatics and GenomicsUniversity of Montreal Montreal, Quebec Canada
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19
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Trade-offs with stability modulate innate and mutationally acquired drug resistance in bacterial dihydrofolate reductase enzymes. Biochem J 2018; 475:2107-2125. [PMID: 29871875 DOI: 10.1042/bcj20180249] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2018] [Revised: 06/04/2018] [Accepted: 06/05/2018] [Indexed: 01/30/2023]
Abstract
Structural stability is a major constraint on the evolution of protein sequences. However, under strong directional selection, mutations that confer novel phenotypes but compromise structural stability of proteins may be permissible. During the evolution of antibiotic resistance, mutations that confer drug resistance often have pleiotropic effects on the structure and function of antibiotic-target proteins, usually essential metabolic enzymes. In the present study, we show that trimethoprim (TMP)-resistant alleles of dihydrofolate reductase from Escherichia coli (EcDHFR) harboring the Trp30Gly, Trp30Arg or Trp30Cys mutations are significantly less stable than the wild-type, making them prone to aggregation and proteolysis. This destabilization is associated with a lower expression level, resulting in a fitness cost and negative epistasis with other TMP-resistant mutations in EcDHFR. Using structure-based mutational analysis, we show that perturbation of critical stabilizing hydrophobic interactions in wild-type EcDHFR enzyme explains the phenotypes of Trp30 mutants. Surprisingly, though crucial for the stability of EcDHFR, significant sequence variation is found at this site among bacterial dihydrofolate reductases (DHFRs). Mutational and computational analyses in EcDHFR and in DHFR enzymes from Staphylococcus aureus and Mycobacterium tuberculosis demonstrate that natural variation at this site and its interacting hydrophobic residues modulates TMP resistance in other bacterial DHFRs as well, and may explain the different susceptibilities of bacterial pathogens to TMP. Our study demonstrates that trade-offs between structural stability and function can influence innate drug resistance as well as the potential for mutationally acquired drug resistance of an enzyme.
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20
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Canale AS, Venev SV, Whitfield TW, Caffrey DR, Marasco WA, Schiffer CA, Kowalik TF, Jensen JD, Finberg RW, Zeldovich KB, Wang JP, Bolon DNA. Synonymous Mutations at the Beginning of the Influenza A Virus Hemagglutinin Gene Impact Experimental Fitness. J Mol Biol 2018; 430:1098-1115. [PMID: 29466705 DOI: 10.1016/j.jmb.2018.02.009] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2017] [Revised: 01/19/2018] [Accepted: 02/05/2018] [Indexed: 01/15/2023]
Abstract
The fitness effects of synonymous mutations can provide insights into biological and evolutionary mechanisms. We analyzed the experimental fitness effects of all single-nucleotide mutations, including synonymous substitutions, at the beginning of the influenza A virus hemagglutinin (HA) gene. Many synonymous substitutions were deleterious both in bulk competition and for individually isolated clones. Investigating protein and RNA levels of a subset of individually expressed HA variants revealed that multiple biochemical properties contribute to the observed experimental fitness effects. Our results indicate that a structural element in the HA segment viral RNA may influence fitness. Examination of naturally evolved sequences in human hosts indicates a preference for the unfolded state of this structural element compared to that found in swine hosts. Our overall results reveal that synonymous mutations may have greater fitness consequences than indicated by simple models of sequence conservation, and we discuss the implications of this finding for commonly used evolutionary tests and analyses.
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Affiliation(s)
- Aneth S Canale
- Department of Biochemistry and Molecular Pharmacology, University of Massachusetts Medical School, Worcester, MA 01655, USA
| | - Sergey V Venev
- Program in Bioinformatics and Integrative Biology, University of Massachusetts Medical School, Worcester, MA 01655, USA
| | - Troy W Whitfield
- Program in Bioinformatics and Integrative Biology, University of Massachusetts Medical School, Worcester, MA 01655, USA; Department of Medicine, University of Massachusetts Medical School, Worcester, MA 01655, USA
| | - Daniel R Caffrey
- Department of Medicine, University of Massachusetts Medical School, Worcester, MA 01655, USA
| | - Wayne A Marasco
- Department of Cancer Immunology & Virology, Dana-Farber Cancer Institute, Harvard Medical School, 450 Brookline Avenue, Boston, MA 02215, USA
| | - Celia A Schiffer
- Department of Biochemistry and Molecular Pharmacology, University of Massachusetts Medical School, Worcester, MA 01655, USA
| | - Timothy F Kowalik
- Department of Microbiology and Physiological Systems, University of Massachusetts Medical School, Worcester, MA 01655, USA
| | - Jeffrey D Jensen
- School of Life Sciences, Center for Evolution & Medicine, Arizona State University, Tempe, AZ. 85281, USA
| | - Robert W Finberg
- Department of Medicine, University of Massachusetts Medical School, Worcester, MA 01655, USA
| | - Konstantin B Zeldovich
- Program in Bioinformatics and Integrative Biology, University of Massachusetts Medical School, Worcester, MA 01655, USA
| | - Jennifer P Wang
- Department of Medicine, University of Massachusetts Medical School, Worcester, MA 01655, USA.
| | - Daniel N A Bolon
- Department of Biochemistry and Molecular Pharmacology, University of Massachusetts Medical School, Worcester, MA 01655, USA.
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21
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Evolutionary mechanisms studied through protein fitness landscapes. Curr Opin Struct Biol 2018; 48:141-148. [DOI: 10.1016/j.sbi.2018.01.001] [Citation(s) in RCA: 28] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2017] [Revised: 12/26/2017] [Accepted: 01/01/2018] [Indexed: 12/15/2022]
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22
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Chen K, Gao Y, Mih N, O'Brien EJ, Yang L, Palsson BO. Thermosensitivity of growth is determined by chaperone-mediated proteome reallocation. Proc Natl Acad Sci U S A 2017; 114:11548-11553. [PMID: 29073085 PMCID: PMC5664499 DOI: 10.1073/pnas.1705524114] [Citation(s) in RCA: 59] [Impact Index Per Article: 8.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022] Open
Abstract
Maintenance of a properly folded proteome is critical for bacterial survival at notably different growth temperatures. Understanding the molecular basis of thermoadaptation has progressed in two main directions, the sequence and structural basis of protein thermostability and the mechanistic principles of protein quality control assisted by chaperones. Yet we do not fully understand how structural integrity of the entire proteome is maintained under stress and how it affects cellular fitness. To address this challenge, we reconstruct a genome-scale protein-folding network for Escherichia coli and formulate a computational model, FoldME, that provides statistical descriptions of multiscale cellular response consistent with many datasets. FoldME simulations show (i) that the chaperones act as a system when they respond to unfolding stress rather than achieving efficient folding of any single component of the proteome, (ii) how the proteome is globally balanced between chaperones for folding and the complex machinery synthesizing the proteins in response to perturbation, (iii) how this balancing determines growth rate dependence on temperature and is achieved through nonspecific regulation, and (iv) how thermal instability of the individual protein affects the overall functional state of the proteome. Overall, these results expand our view of cellular regulation, from targeted specific control mechanisms to global regulation through a web of nonspecific competing interactions that modulate the optimal reallocation of cellular resources. The methodology developed in this study enables genome-scale integration of environment-dependent protein properties and a proteome-wide study of cellular stress responses.
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Affiliation(s)
- Ke Chen
- Department of Bioengineering, University of California, San Diego, La Jolla, CA 92093
| | - Ye Gao
- Division of Biological Sciences, University of California, San Diego, La Jolla, CA 92093
| | - Nathan Mih
- Department of Bioengineering, University of California, San Diego, La Jolla, CA 92093
- Bioinformatics and Systems Biology, University of California, San Diego, La Jolla, CA 92093
| | - Edward J O'Brien
- Department of Bioengineering, University of California, San Diego, La Jolla, CA 92093
| | - Laurence Yang
- Department of Bioengineering, University of California, San Diego, La Jolla, CA 92093
| | - Bernhard O Palsson
- Department of Bioengineering, University of California, San Diego, La Jolla, CA 92093;
- Department of Pediatrics, University of California, San Diego, La Jolla, CA 92093
- Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, 2800 Kongens Lyngby, Denmark
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23
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Ligand-promoted protein folding by biased kinetic partitioning. Nat Chem Biol 2017; 13:369-371. [PMID: 28218913 PMCID: PMC5362304 DOI: 10.1038/nchembio.2303] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2016] [Accepted: 12/12/2016] [Indexed: 01/03/2023]
Abstract
Protein folding in cells occurs in the presence of high concentrations of endogenous binding partners, and exogenous binding partners have been exploited as pharmacological chaperones. A combined mathematical modeling and experimental approach shows that a ligand improves the folding of a destabilized protein by biasing the kinetic partitioning between folding and alternative fates (aggregation or degradation). Computationally predicted inhibition of test protein aggregation and degradation as a function of ligand concentration are validated by experiments in two disparate cellular systems.
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24
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Bershtein S, Serohijos AW, Shakhnovich EI. Bridging the physical scales in evolutionary biology: from protein sequence space to fitness of organisms and populations. Curr Opin Struct Biol 2016; 42:31-40. [PMID: 27810574 DOI: 10.1016/j.sbi.2016.10.013] [Citation(s) in RCA: 46] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2016] [Accepted: 10/14/2016] [Indexed: 01/11/2023]
Abstract
Bridging the gap between the molecular properties of proteins and organismal/population fitness is essential for understanding evolutionary processes. This task requires the integration of the several physical scales of biological organization, each defined by a distinct set of mechanisms and constraints, into a single unifying model. The molecular scale is dominated by the constraints imposed by the physico-chemical properties of proteins and their substrates, which give rise to trade-offs and epistatic (non-additive) effects of mutations. At the systems scale, biological networks modulate protein expression and can either buffer or enhance the fitness effects of mutations. The population scale is influenced by the mutational input, selection regimes, and stochastic changes affecting the size and structure of populations, which eventually determine the evolutionary fate of mutations. Here, we summarize the recent advances in theory, computer simulations, and experiments that advance our understanding of the links between various physical scales in biology.
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Affiliation(s)
- Shimon Bershtein
- Department of Life Sciences, Ben-Gurion University of the Negev, Beer-Sheva 84501, Israel
| | - Adrian Wr Serohijos
- Département de Biochimie, Centre Robert-Cedergren en Bioinformatique & Génomique, Université de Montréal, Montréal, QC H3T 1J4, Canada
| | - Eugene I Shakhnovich
- Department of Chemistry and Chemical Biology, Harvard University, 12 Oxford Street, Cambridge, MA 02138, United States.
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25
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Boucher JI, Bolon DNA, Tawfik DS. Quantifying and understanding the fitness effects of protein mutations: Laboratory versus nature. Protein Sci 2016; 25:1219-26. [PMID: 27010590 DOI: 10.1002/pro.2928] [Citation(s) in RCA: 57] [Impact Index Per Article: 7.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2016] [Revised: 03/21/2016] [Accepted: 03/21/2016] [Indexed: 11/11/2022]
Abstract
The last decade has seen a growing number of experiments aimed at systematically mapping the effects of mutations in different proteins, and of attempting to correlate their biophysical and biochemical effects with organismal fitness. While insightful, systematic laboratory measurements of fitness effects present challenges and difficulties. Here, we discuss the limitations associated with such measurements, and in particular the challenge of correlating the effects of mutations at the single protein level ("protein fitness") with their effects on organismal fitness. A variety of experimental setups are used, with some measuring the direct effects on protein function and others monitoring the growth rate of a model organism carrying the protein mutants. The manners by which fitness effects are calculated and presented also vary, and the conclusions, including the derived distributions of fitness effects of mutations, vary accordingly. The comparison of the effects of mutations in the laboratory to the natural protein diversity, namely to amino acid changes that have fixed in the course of millions of years of evolution, is also debatable. The results of laboratory experiments may, therefore, be less relevant to understanding long-term inter-species variations yet insightful with regard to short-term polymorphism, for example, in the study of the effects of human SNPs.
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Affiliation(s)
- Jeffrey I Boucher
- Department of Biochemistry and Molecular Pharmacology, University of Massachusetts Medical School, Worcester, Massachusetts, 01605
| | - Daniel N A Bolon
- Department of Biochemistry and Molecular Pharmacology, University of Massachusetts Medical School, Worcester, Massachusetts, 01605
| | - Dan S Tawfik
- Department of Biological Chemistry, Weizmann Institute of Science, Rehovot, 76100, Israel
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26
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Abstract
Fitness landscapes of drug resistance constitute powerful tools to elucidate mutational pathways of antibiotic escape. Here, we developed a predictive biophysics-based fitness landscape of trimethoprim (TMP) resistance for Escherichia coli dihydrofolate reductase (DHFR). We investigated the activity, binding, folding stability, and intracellular abundance for a complete set of combinatorial DHFR mutants made out of three key resistance mutations and extended this analysis to DHFR originated from Chlamydia muridarum and Listeria grayi We found that the acquisition of TMP resistance via decreased drug affinity is limited by a trade-off in catalytic efficiency. Protein stability is concurrently affected by the resistant mutants, which precludes a precise description of fitness from a single molecular trait. Application of the kinetic flux theory provided an accurate model to predict resistance phenotypes (IC50) quantitatively from a unique combination of the in vitro protein molecular properties. Further, we found that a controlled modulation of the GroEL/ES chaperonins and Lon protease levels affects the intracellular steady-state concentration of DHFR in a mutation-specific manner, whereas IC50 is changed proportionally, as indeed predicted by the model. This unveils a molecular rationale for the pleiotropic role of the protein quality control machinery on the evolution of antibiotic resistance, which, as we illustrate here, may drastically confound the evolutionary outcome. These results provide a comprehensive quantitative genotype-phenotype map for the essential enzyme that serves as an important target of antibiotic and anticancer therapies.
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27
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Protein Homeostasis Imposes a Barrier on Functional Integration of Horizontally Transferred Genes in Bacteria. PLoS Genet 2015; 11:e1005612. [PMID: 26484862 PMCID: PMC4618355 DOI: 10.1371/journal.pgen.1005612] [Citation(s) in RCA: 54] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2015] [Accepted: 09/25/2015] [Indexed: 01/02/2023] Open
Abstract
Horizontal gene transfer (HGT) plays a central role in bacterial evolution, yet the molecular and cellular constraints on functional integration of the foreign genes are poorly understood. Here we performed inter-species replacement of the chromosomal folA gene, encoding an essential metabolic enzyme dihydrofolate reductase (DHFR), with orthologs from 35 other mesophilic bacteria. The orthologous inter-species replacements caused a marked drop (in the range 10–90%) in bacterial growth rate despite the fact that most orthologous DHFRs are as stable as E.coli DHFR at 37°C and are more catalytically active than E. coli DHFR. Although phylogenetic distance between E. coli and orthologous DHFRs as well as their individual molecular properties correlate poorly with growth rates, the product of the intracellular DHFR abundance and catalytic activity (kcat/KM), correlates strongly with growth rates, indicating that the drop in DHFR abundance constitutes the major fitness barrier to HGT. Serial propagation of the orthologous strains for ~600 generations dramatically improved growth rates by largely alleviating the fitness barriers. Whole genome sequencing and global proteome quantification revealed that the evolved strains with the largest fitness improvements have accumulated mutations that inactivated the ATP-dependent Lon protease, causing an increase in the intracellular DHFR abundance. In one case DHFR abundance increased further due to mutations accumulated in folA promoter, but only after the lon inactivating mutations were fixed in the population. Thus, by apparently distinguishing between self and non-self proteins, protein homeostasis imposes an immediate and global barrier to the functional integration of foreign genes by decreasing the intracellular abundance of their products. Once this barrier is alleviated, more fine-tuned evolution occurs to adjust the function/expression of the transferred proteins to the constraints imposed by the intracellular environment of the host organism. Horizontal gene transfer (HGT) is central to bacterial evolution. The outcome of an HGT event (fixation in a population, elimination, or separation as a subdominant clone) depends not only on the availability of a new gene but crucially on the fitness cost or benefit of the genomic incorporation of the foreign gene and its expression in recipient bacteria. Here we studied the fitness landscape for inter-species chromosomal replacement of an essential protein, dihydrofolate reductase (DHFR) encoded by the folA gene, by its orthologs from other mesophilic bacteria. We purified and biochemically characterized 33 out of 35 orthologous DHFRs and found that most of them are stable and more catalytically active than E. coli DHFR. However, the inter-species replacement of DHFR caused significant fitness loss for most transgenic strains due to low abundance of orthologous DHFRs in E. coli cytoplasm. Laboratory evolution resulted in an increase in orthologous DHFR abundance leading to a dramatic fitness improvement. Genomic and proteomic analyses of “naive” and evolved strains suggest a new function of protein homeostasis to discriminate between “self” and “non-self” proteins, thus creating fitness barriers to HGT.
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