1
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De Baets J, De Paepe B, De Mey M. Delaying production with prokaryotic inducible expression systems. Microb Cell Fact 2024; 23:249. [PMID: 39272067 PMCID: PMC11401332 DOI: 10.1186/s12934-024-02523-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2024] [Accepted: 09/04/2024] [Indexed: 09/15/2024] Open
Abstract
BACKGROUND Engineering bacteria with the purpose of optimizing the production of interesting molecules often leads to a decrease in growth due to metabolic burden or toxicity. By delaying the production in time, these negative effects on the growth can be avoided in a process called a two-stage fermentation. MAIN TEXT During this two-stage fermentation process, the production stage is only activated once sufficient cell mass is obtained. Besides the possibility of using external triggers, such as chemical molecules or changing fermentation parameters to induce the production stage, there is a renewed interest towards autoinducible systems. These systems, such as quorum sensing, do not require the extra interference with the fermentation broth to start the induction. In this review, we discuss the different possibilities of both external and autoinduction methods to obtain a two-stage fermentation. Additionally, an overview is given of the tuning methods that can be applied to optimize the induction process. Finally, future challenges and prospects of (auto)inducible expression systems are discussed. CONCLUSION There are numerous methods to obtain a two-stage fermentation process each with their own advantages and disadvantages. Even though chemically inducible expression systems are well-established, an increasing interest is going towards autoinducible expression systems, such as quorum sensing. Although these newer techniques cannot rely on the decades of characterization and applications as is the case for chemically inducible promoters, their advantages might lead to a shift in future inducible expression systems.
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Affiliation(s)
- Jasmine De Baets
- Centre for Synthetic Biology, Ghent University, Coupure Links 653, 9000, Ghent, Belgium
| | - Brecht De Paepe
- Centre for Synthetic Biology, Ghent University, Coupure Links 653, 9000, Ghent, Belgium
| | - Marjan De Mey
- Centre for Synthetic Biology, Ghent University, Coupure Links 653, 9000, Ghent, Belgium.
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2
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Stevanovic M, Teuber Carvalho JP, Bittihn P, Schultz D. Dynamical model of antibiotic responses linking expression of resistance genes to metabolism explains emergence of heterogeneity during drug exposures. Phys Biol 2024; 21:036002. [PMID: 38412523 PMCID: PMC10988634 DOI: 10.1088/1478-3975/ad2d64] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2023] [Revised: 01/25/2024] [Accepted: 02/27/2024] [Indexed: 02/29/2024]
Abstract
Antibiotic responses in bacteria are highly dynamic and heterogeneous, with sudden exposure of bacterial colonies to high drug doses resulting in the coexistence of recovered and arrested cells. The dynamics of the response is determined by regulatory circuits controlling the expression of resistance genes, which are in turn modulated by the drug's action on cell growth and metabolism. Despite advances in understanding gene regulation at the molecular level, we still lack a framework to describe how feedback mechanisms resulting from the interdependence between expression of resistance and cell metabolism can amplify naturally occurring noise and create heterogeneity at the population level. To understand how this interplay affects cell survival upon exposure, we constructed a mathematical model of the dynamics of antibiotic responses that links metabolism and regulation of gene expression, based on the tetracycline resistancetetoperon inE. coli. We use this model to interpret measurements of growth and expression of resistance in microfluidic experiments, both in single cells and in biofilms. We also implemented a stochastic model of the drug response, to show that exposure to high drug levels results in large variations of recovery times and heterogeneity at the population level. We show that stochasticity is important to determine how nutrient quality affects cell survival during exposure to high drug concentrations. A quantitative description of how microbes respond to antibiotics in dynamical environments is crucial to understand population-level behaviors such as biofilms and pathogenesis.
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Affiliation(s)
- Mirjana Stevanovic
- Department of Microbiology and Immunology, Geisel School of Medicine at Dartmouth, Hanover, NH, United States of America
| | - João Pedro Teuber Carvalho
- Department of Microbiology and Immunology, Geisel School of Medicine at Dartmouth, Hanover, NH, United States of America
| | - Philip Bittihn
- Max Planck Institute for Dynamics and Self-Organization, Göttingen, Germany
- Institute for the Dynamics of Complex Systems, University of Göttingen, Göttingen, Germany
| | - Daniel Schultz
- Department of Microbiology and Immunology, Geisel School of Medicine at Dartmouth, Hanover, NH, United States of America
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3
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Naseri G, Raasch H, Charpentier E, Erhardt M. A versatile regulatory toolkit of arabinose-inducible artificial transcription factors for Enterobacteriaceae. Commun Biol 2023; 6:1005. [PMID: 37789111 PMCID: PMC10547716 DOI: 10.1038/s42003-023-05363-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2023] [Accepted: 09/15/2023] [Indexed: 10/05/2023] Open
Abstract
The Gram-negative bacteria Salmonella enterica and Escherichia coli are important model organisms, powerful prokaryotic expression platforms for biotechnological applications, and pathogenic strains constitute major public health threats. To facilitate new approaches for research and biotechnological applications, we here develop a set of arabinose-inducible artificial transcription factors (ATFs) using CRISPR/dCas9 and Arabidopsis-derived DNA-binding proteins to control gene expression in E. coli and Salmonella over a wide inducer concentration range. The transcriptional output of the different ATFs, in particular when expressed in Salmonella rewired for arabinose catabolism, varies over a wide spectrum (up to 35-fold gene activation). As a proof-of-concept, we use the developed ATFs to engineer a Salmonella two-input biosensor strain, SALSOR 0.2 (SALmonella biosenSOR 0.2), which detects and quantifies alkaloid drugs through a measurable fluorescent output. Moreover, we use plant-derived ATFs to regulate β-carotene biosynthesis in E. coli, resulting in ~2.1-fold higher β-carotene production compared to expression of the biosynthesis pathway using a strong constitutive promoter.
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Affiliation(s)
- Gita Naseri
- Max Planck Unit for the Science of Pathogens, Charitéplatz 1, 10117, Berlin, Germany.
- Institut für Biologie, Humboldt-Universität zu Berlin, Philippstrasse 13, 10115, Berlin, Germany.
| | - Hannah Raasch
- Institut für Biologie, Humboldt-Universität zu Berlin, Philippstrasse 13, 10115, Berlin, Germany
| | - Emmanuelle Charpentier
- Max Planck Unit for the Science of Pathogens, Charitéplatz 1, 10117, Berlin, Germany
- Institut für Biologie, Humboldt-Universität zu Berlin, Philippstrasse 13, 10115, Berlin, Germany
| | - Marc Erhardt
- Max Planck Unit for the Science of Pathogens, Charitéplatz 1, 10117, Berlin, Germany.
- Institut für Biologie, Humboldt-Universität zu Berlin, Philippstrasse 13, 10115, Berlin, Germany.
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4
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Stevanovic M, Carvalho JPT, Bittihn P, Schultz D. Dynamical model of antibiotic responses linking expression of resistance to metabolism explains emergence of heterogeneity during drug exposures. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.09.22.558994. [PMID: 37790326 PMCID: PMC10542528 DOI: 10.1101/2023.09.22.558994] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/05/2023]
Abstract
Antibiotic responses in bacteria are highly dynamic and heterogeneous, with sudden exposure of bacterial colonies to high drug doses resulting in the coexistence of recovered and arrested cells. The dynamics of the response is determined by regulatory circuits controlling the expression of resistance genes, which are in turn modulated by the drug's action on cell growth and metabolism. Despite advances in understanding gene regulation at the molecular level, we still lack a framework to describe how feedback mechanisms resulting from the interdependence between expression of resistance and cell metabolism can amplify naturally occurring noise and create heterogeneity at the population level. To understand how this interplay affects cell survival upon exposure, we constructed a mathematical model of the dynamics of antibiotic responses that links metabolism and regulation of gene expression, based on the tetracycline resistance tet operon in E. coli. We use this model to interpret measurements of growth and expression of resistance in microfluidic experiments, both in single cells and in biofilms. We also implemented a stochastic model of the drug response, to show that exposure to high drug levels results in large variations of recovery times and heterogeneity at the population level. We show that stochasticity is important to determine how nutrient quality affects cell survival during exposure to high drug concentrations. A quantitative description of how microbes respond to antibiotics in dynamical environments is crucial to understand population-level behaviors such as biofilms and pathogenesis.
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Affiliation(s)
- Mirjana Stevanovic
- Department of Microbiology and Immunology, Geisel School of Medicine at Dartmouth, Hanover, NH, United States
| | - João Pedro Teuber Carvalho
- Department of Microbiology and Immunology, Geisel School of Medicine at Dartmouth, Hanover, NH, United States
| | - Philip Bittihn
- Max Planck Institute for Dynamics and Self-Organization, Göttingen, Germany
- Institute for the Dynamics of Complex Systems, University of Göttingen, Göttingen, Germany
| | - Daniel Schultz
- Department of Microbiology and Immunology, Geisel School of Medicine at Dartmouth, Hanover, NH, United States
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5
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Zhou GJ, Zhang F. Applications and Tuning Strategies for Transcription Factor-Based Metabolite Biosensors. BIOSENSORS 2023; 13:428. [PMID: 37185503 PMCID: PMC10136082 DOI: 10.3390/bios13040428] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/27/2023] [Revised: 03/24/2023] [Accepted: 03/27/2023] [Indexed: 05/17/2023]
Abstract
Transcription factor (TF)-based biosensors are widely used for the detection of metabolites and the regulation of cellular pathways in response to metabolites. Several challenges hinder the direct application of TF-based sensors to new hosts or metabolic pathways, which often requires extensive tuning to achieve the optimal performance. These tuning strategies can involve transcriptional or translational control depending on the parameter of interest. In this review, we highlight recent strategies for engineering TF-based biosensors to obtain the desired performance and discuss additional design considerations that may influence a biosensor's performance. We also examine applications of these sensors and suggest important areas for further work to continue the advancement of small-molecule biosensors.
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Affiliation(s)
- Gloria J. Zhou
- Department of Energy, Environmental and Chemical Engineering, Washington University in St. Louis, St. Louis, MO 63130, USA;
| | - Fuzhong Zhang
- Department of Energy, Environmental and Chemical Engineering, Washington University in St. Louis, St. Louis, MO 63130, USA;
- Division of Biology & Biomedical Sciences, Washington University in St. Louis, St. Louis, MO 63130, USA
- Institute of Materials Science & Engineering, Washington University in St. Louis, St. Louis, MO 63130, USA
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6
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Nuñez S, Barra M, Garrido D. Developing a Fluorescent Inducible System for Free Fucose Quantification in Escherichia coli. BIOSENSORS 2023; 13:bios13030388. [PMID: 36979599 PMCID: PMC10046853 DOI: 10.3390/bios13030388] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/12/2023] [Revised: 03/10/2023] [Accepted: 03/13/2023] [Indexed: 05/28/2023]
Abstract
L-Fucose is a monosaccharide abundant in mammalian glycoconjugates. In humans, fucose can be found in human milk oligosaccharides (HMOs), mucins, and glycoproteins in the intestinal epithelium. The bacterial consumption of fucose and fucosylated HMOs is critical in the gut microbiome assembly of infants, dominated by Bifidobacterium. Fucose metabolism is important for the production of short-chain fatty acids and is involved in cross-feeding microbial interactions. Methods for assessing fucose concentrations in complex media are lacking. Here we designed and developed a molecular quantification method of free fucose using fluorescent Escherichia coli. For this, low- and high-copy plasmids were evaluated with and without the transcription factor fucR and its respective fucose-inducible promoter controlling the reporter gene sfGFP. E. coli BL21 transformed with a high copy plasmid containing pFuc and fucR displayed a high resolution across increasing fucose concentrations and high fluorescence/OD values after 18 h. The molecular circuit was specific against other monosaccharides and showed a linear response in the 0-45 mM range. Adjusting data to the Hill equation suggested non-cooperative, simple regulation of FucR to its promoter. Finally, the biosensor was tested on different concentrations of free fucose and the supernatant of Bifidobacterium bifidum JCM 1254 supplemented with 2-fucosyl lactose, indicating the applicability of the method in detecting free fucose. In conclusion, a bacterial biosensor of fucose was validated with good sensitivity and precision. A biological method for quantifying fucose could be useful for nutraceutical and microbiological applications, as well as molecular diagnostics.
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7
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Chakraborty S, Singh P, Seshasayee ASN. Understanding the Genome-Wide Transcription Response To Various cAMP Levels in Bacteria Using Phenomenological Models. mSystems 2022; 7:e0090022. [PMID: 36409084 PMCID: PMC9765429 DOI: 10.1128/msystems.00900-22] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2022] [Accepted: 10/17/2022] [Indexed: 11/23/2022] Open
Abstract
Attempts to understand gene regulation by global transcription factors have largely been limited to expression studies under binary conditions of presence and absence of the transcription factor. Studies addressing genome-wide transcriptional responses to changing transcription factor concentration at high resolution are lacking. Here, we create a data set containing the entire Escherichia coli transcriptome in Luria-Bertani (LB) broth as it responds to 10 different cAMP concentrations spanning the biological range. We use the Hill's model to accurately summarize individual gene responses into three intuitively understandable parameters, Emax, n, and k, reflecting the sensitivity, nonlinearity, and midpoint of the dynamic range. Our data show that most cAMP-regulated genes have an n of >2, with their k values centered around the wild-type concentration of cAMP. Additionally, cAMP receptor protein (CRP) affinity to a promoter is correlated with Emax but not k, hinting that a high-affinity CRP promoter need not ensure transcriptional activation at lower cAMP concentrations and instead affects the magnitude of the response. Finally, genes belonging to different functional classes are tuned to have different k, n, and Emax values. We demonstrate that phenomenological models are a better alternative for studying gene expression trends than classical clustering methods, with the phenomenological constants providing greater insights into how genes are tuned in a regulatory network. IMPORTANCE Different genes may follow different trends in response to various transcription factor concentrations. In this study, we ask two questions: (i) what are the trends that different genes follow in response to changing transcription factor concentrations and (ii) what methods can be used to extract information from the gene trends so obtained. We demonstrate a method to analyze transcription factor concentration-dependent genome-wide expression data using phenomenological models. Conventional clustering methods and principal-component analysis (PCA) can be used to summarize trends in data but have limited interpretability. The use of phenomenological models greatly enhances the interpretability and thus utility of conventional clustering. Transformation of dose-response data into phenomenological constants opens up avenues to ask and answer many different kinds of question. We show that the phenomenological constants obtained from the model fits can be used to generate insights about network topology and allows integration of other experimental data such as chromatin immunoprecipitation sequencing (ChIP-seq) to understand the system in greater detail.
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Affiliation(s)
- Shweta Chakraborty
- National Centre for Biological Sciences, Tata Institute of Fundamental Research, Bangalore, Karnataka, India
| | | | - Aswin Sai Narain Seshasayee
- National Centre for Biological Sciences, Tata Institute of Fundamental Research, Bangalore, Karnataka, India
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8
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Schultz D, Stevanovic M, Tsimring LS. Optimal transcriptional regulation of dynamic bacterial responses to sudden drug exposures. Biophys J 2022; 121:4137-4152. [PMID: 36168291 PMCID: PMC9675034 DOI: 10.1016/j.bpj.2022.09.028] [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: 04/11/2022] [Revised: 08/22/2022] [Accepted: 09/23/2022] [Indexed: 11/17/2022] Open
Abstract
Cellular responses to the presence of toxic compounds in their environment require prompt expression of the correct levels of the appropriate enzymes, which are typically regulated by transcription factors that control gene expression for the duration of the response. The characteristics of each response dictate the choice of regulatory parameters such as the affinity of the transcription factor to its binding sites and the strength of the promoters it regulates. Although much is known about the dynamics of cellular responses, we still lack a framework to understand how different regulatory strategies evolved in natural systems relate to the selective pressures acting in each particular case. Here, we analyze a dynamical model of a typical antibiotic response in bacteria, where a transcriptionally repressed enzyme is induced by a sudden exposure to the drug that it processes. We identify strategies of gene regulation that optimize this response for different types of selective pressures, which we define as a set of costs associated with the drug, enzyme, and repressor concentrations during the response. We find that regulation happens in a limited region of the regulatory parameter space. While responses to more costly (toxic) drugs favor the usage of strongly self-regulated repressors, responses where expression of enzyme is more costly favor the usage of constitutively expressed repressors. Only a very narrow range of selective pressures favor weakly self-regulated repressors. We use this framework to determine which costs and benefits are most critical for the evolution of a variety of natural cellular responses that satisfy the approximations in our model and to analyze how regulation is optimized in new environments with different demands.
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Affiliation(s)
- Daniel Schultz
- Department of Microbiology and Immunology, Geisel School of Medicine at Dartmouth, Hanover, New Hampshire.
| | - Mirjana Stevanovic
- Department of Microbiology and Immunology, Geisel School of Medicine at Dartmouth, Hanover, New Hampshire
| | - Lev S Tsimring
- Synthetic Biology Institute, University of California, San Diego, La Jolla, California
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9
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Chagas MDS, Medeiros F, dos Santos MT, de Menezes MA, Carvalho-Assef APD, da Silva FAB. An updated gene regulatory network reconstruction of multidrug-resistant Pseudomonas aeruginosa CCBH4851. Mem Inst Oswaldo Cruz 2022; 117:e220111. [PMID: 36259790 PMCID: PMC9565603 DOI: 10.1590/0074-02760220111] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2022] [Accepted: 09/09/2022] [Indexed: 11/22/2022] Open
Abstract
BACKGROUND Healthcare-associated infections due to multidrug-resistant (MDR) bacteria such as Pseudomonas aeruginosa are significant public health issues worldwide. A system biology approach can help understand bacterial behaviour and provide novel ways to identify potential therapeutic targets and develop new drugs. Gene regulatory networks (GRN) are examples of in silico representation of interaction between regulatory genes and their targets. OBJECTIVES In this work, we update the MDR P. aeruginosa CCBH4851 GRN reconstruction and analyse and discuss its structural properties. METHODS We based this study on the gene orthology inference methodology using the reciprocal best hit method. The P. aeruginosa CCBH4851 genome and GRN, published in 2019, and the P. aeruginosa PAO1 GRN, published in 2020, were used for this update reconstruction process. FINDINGS Our result is a GRN with a greater number of regulatory genes, target genes, and interactions compared to the previous networks, and its structural properties are consistent with the complexity of biological networks and the biological features of P. aeruginosa. MAIN CONCLUSIONS Here, we present the largest and most complete version of P. aeruginosa GRN published to this date, to the best of our knowledge.
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Affiliation(s)
- Márcia da Silva Chagas
- Fundação Oswaldo Cruz-Fiocruz, Programa de Computação Científica, Rio de Janeiro, RJ, Brasil,+ Corresponding authors: /
| | - Fernando Medeiros
- Fundação Oswaldo Cruz-Fiocruz, Instituto Nacional de Infectologia, Laboratório de Pesquisa Clínica em Doenças Febris Agudas, Rio de Janeiro, RJ, Brasil
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10
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Leifer I, Sánchez-Pérez M, Ishida C, Makse HA. Predicting synchronized gene coexpression patterns from fibration symmetries in gene regulatory networks in bacteria. BMC Bioinformatics 2021; 22:363. [PMID: 34238210 PMCID: PMC8265036 DOI: 10.1186/s12859-021-04213-5] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2020] [Accepted: 05/19/2021] [Indexed: 11/15/2022] Open
Abstract
BACKGROUND Gene regulatory networks coordinate the expression of genes across physiological states and ensure a synchronized expression of genes in cellular subsystems, critical for the coherent functioning of cells. Here we address the question whether it is possible to predict gene synchronization from network structure alone. We have recently shown that synchronized gene expression can be predicted from symmetries in the gene regulatory networks described by the concept of symmetry fibrations. We showed that symmetry fibrations partition the genes into groups called fibers based on the symmetries of their 'input trees', the set of paths in the network through which signals can reach a gene. In idealized dynamic gene expression models, all genes in a fiber are perfectly synchronized, while less idealized models-with gene input functions differencing between genes-predict symmetry breaking and desynchronization. RESULTS To study the functional role of gene fibers and to test whether some of the fiber-induced coexpression remains in reality, we analyze gene fibrations for the gene regulatory networks of E. coli and B. subtilis and confront them with expression data. We find approximate gene coexpression patterns consistent with symmetry fibrations with idealized gene expression dynamics. This shows that network structure alone provides useful information about gene synchronization, and suggest that gene input functions within fibers may be further streamlined by evolutionary pressures to realize a coexpression of genes. CONCLUSIONS Thus, gene fibrations provide a sound conceptual tool to describe tunable coexpression induced by network topology and shaped by mechanistic details of gene expression.
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Affiliation(s)
- Ian Leifer
- Levich Institute,Physics Department, City College of New York, New York, NY, 10031, USA
| | - Mishael Sánchez-Pérez
- Levich Institute,Physics Department, City College of New York, New York, NY, 10031, USA
- Programa de Genómica Computacional, Centro de Ciencias Genómicas, Universidad Nacional Autónoma de México, Cuernavaca, Mexico
| | - Cecilia Ishida
- Faculty of Medicine and Biomedical Sciences, Autonomous University of Chihuahua, 31125, Chihuahua, Chihuahua, Mexico
| | - Hernán A Makse
- Levich Institute,Physics Department, City College of New York, New York, NY, 10031, USA.
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11
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Ding N, Zhou S, Deng Y. Transcription-Factor-based Biosensor Engineering for Applications in Synthetic Biology. ACS Synth Biol 2021; 10:911-922. [PMID: 33899477 DOI: 10.1021/acssynbio.0c00252] [Citation(s) in RCA: 59] [Impact Index Per Article: 19.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]
Abstract
Transcription-factor-based biosensors (TFBs) are often used for metabolite detection, adaptive evolution, and metabolic flux control. However, designing TFBs with superior performance for applications in synthetic biology remains challenging. Specifically, natural TFBs often do not meet real-time detection requirements owing to their slow response times and inappropriate dynamic ranges, detection ranges, sensitivity, and selectivity. Furthermore, designing and optimizing complex dynamic regulation networks is time-consuming and labor-intensive. This Review highlights TFB-based applications and recent engineering strategies ranging from traditional trial-and-error approaches to novel computer-model-based rational design approaches. The limitations of the applications and these engineering strategies are additionally reviewed.
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Affiliation(s)
- Nana Ding
- National Engineering Laboratory for Cereal Fermentation Technology (NELCF), Jiangnan University, 1800 Lihu Road, Wuxi, Jiangsu 214122, China
- Jiangsu Provincial Research Center for Bioactive Product Processing Technology, Jiangnan University, 1800 Lihu Road, Wuxi, Jiangsu 214122, China
| | - Shenghu Zhou
- National Engineering Laboratory for Cereal Fermentation Technology (NELCF), Jiangnan University, 1800 Lihu Road, Wuxi, Jiangsu 214122, China
- Jiangsu Provincial Research Center for Bioactive Product Processing Technology, Jiangnan University, 1800 Lihu Road, Wuxi, Jiangsu 214122, China
| | - Yu Deng
- National Engineering Laboratory for Cereal Fermentation Technology (NELCF), Jiangnan University, 1800 Lihu Road, Wuxi, Jiangsu 214122, China
- Jiangsu Provincial Research Center for Bioactive Product Processing Technology, Jiangnan University, 1800 Lihu Road, Wuxi, Jiangsu 214122, China
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12
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Kochanowski K, Okano H, Patsalo V, Williamson J, Sauer U, Hwa T. Global coordination of metabolic pathways in Escherichia coli by active and passive regulation. Mol Syst Biol 2021; 17:e10064. [PMID: 33852189 PMCID: PMC8045939 DOI: 10.15252/msb.202010064] [Citation(s) in RCA: 24] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2020] [Revised: 03/04/2021] [Accepted: 03/09/2021] [Indexed: 12/15/2022] Open
Abstract
Microorganisms adjust metabolic activity to cope with diverse environments. While many studies have provided insights into how individual pathways are regulated, the mechanisms that give rise to coordinated metabolic responses are poorly understood. Here, we identify the regulatory mechanisms that coordinate catabolism and anabolism in Escherichia coli. Integrating protein, metabolite, and flux changes in genetically implemented catabolic or anabolic limitations, we show that combined global and local mechanisms coordinate the response to metabolic limitations. To allocate proteomic resources between catabolism and anabolism, E. coli uses a simple global gene regulatory program. Surprisingly, this program is largely implemented by a single transcription factor, Crp, which directly activates the expression of catabolic enzymes and indirectly reduces the expression of anabolic enzymes by passively sequestering cellular resources needed for their synthesis. However, metabolic fluxes are not controlled by this regulatory program alone; instead, fluxes are adjusted mostly through passive changes in the local metabolite concentrations. These mechanisms constitute a simple but effective global regulatory program that coarsely partitions resources between different parts of metabolism while ensuring robust coordination of individual metabolic reactions.
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Affiliation(s)
- Karl Kochanowski
- Institute of Molecular Systems BiologyETH ZurichZurichSwitzerland
- Life Science Zurich PhD Program on Systems BiologyZurichSwitzerland
| | - Hiroyuki Okano
- Department of PhysicsUniversity of California at San DiegoLa JollaCAUSA
| | - Vadim Patsalo
- Department of Integrative Structural and Computational Biology, and The Skaggs Institute for Chemical BiologyThe Scripps Research InstituteLa JollaCAUSA
| | - James Williamson
- Department of Integrative Structural and Computational Biology, and The Skaggs Institute for Chemical BiologyThe Scripps Research InstituteLa JollaCAUSA
| | - Uwe Sauer
- Institute of Molecular Systems BiologyETH ZurichZurichSwitzerland
| | - Terence Hwa
- Department of PhysicsUniversity of California at San DiegoLa JollaCAUSA
- Institute for Theoretical ScienceETH ZurichZurichSwitzerland
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13
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Hong J, Hua B, Springer M, Tang C. Computational study on ratio-sensing in yeast galactose utilization pathway. PLoS Comput Biol 2020; 16:e1007960. [PMID: 33275601 PMCID: PMC7744065 DOI: 10.1371/journal.pcbi.1007960] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2020] [Revised: 12/16/2020] [Accepted: 10/16/2020] [Indexed: 01/02/2023] Open
Abstract
Metabolic networks undergo gene expression regulation in response to external nutrient signals. In microbes, the synthesis of enzymes that are used to transport and catabolize less preferred carbon sources is repressed in the presence of a preferred carbon source. For most microbes, glucose is a preferred carbon source, and it has long been believed that as long as glucose is present in the environment, the expression of genes related to the metabolism of alternative carbon sources is shut down, due to catabolite repression. However, recent studies have shown that the induction of the galactose (GAL) metabolic network does not solely depend on the exhaustion of glucose. Instead, the GAL genes respond to the external concentration ratio of galactose to glucose, a phenomenon of unknown mechanism that we termed ratio-sensing. Using mathematical modeling, we found that ratio-sensing is a general phenomenon that can arise from competition between two carbon sources for shared transporters, between transcription factors for binding to communal regulatory sequences of the target genes, or a combination of the aforementioned two levels of competition. We analyzed how the parameters describing the competitive interaction influenced ratio-sensing behaviors in each scenario and found that the concatenation of both layers of signal integration could expand the dynamical range of ratio-sensing. Finally, we investigated the influence of circuit topology on ratio-sensing and found that incorporating negative auto-regulation and/or coherent feedforward loop motifs to the basic signal integration unit could tune the sensitivity of the response to the external nutrient signals. Our study not only deepened our understanding of how ratio-sensing is achieved in yeast GAL metabolic regulation, but also elucidated design principles for ratio-sensing signal processing that can be used in other biological settings, such as being introduced into circuit designs for synthetic biology applications. Microbes make sophisticated choices about the uptake and metabolism of nutrients depending on the variety of nutrient choices available to them in their environment. In the well-studied yeast galactose utilization network, a recent study has shown that galactose metabolic genes respond to the external concentration ratio of galactose to glucose. Using computational models, we showed that this type of phenomenon could arise from a competition between galactose and glucose for transporters, a competition between transcription factors for promoters, or a combination of these two mechanisms. We further revealed the controlling parameters that determined the system sensitivity towards competing input signals and that determined the concentration ratio required to induce the metabolic network in each scenario. Combining competition inhibition at both the transporter level and the transcriptional level can enlarge the ratio-sensing regime, resulting a robust signal integration module. We suspect that modules of this kind may be common in many areas of biology.
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Affiliation(s)
- Jiayin Hong
- Center for Quantitative Biology and Peking-Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China
| | - Bo Hua
- Department of Systems Biology, Harvard Medical School, Boston, Massachusetts, United States of America
| | - Michael Springer
- Department of Systems Biology, Harvard Medical School, Boston, Massachusetts, United States of America
| | - Chao Tang
- Center for Quantitative Biology and Peking-Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China.,School of Physics, Peking University, Beijing, China
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14
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Kamino K, Keegstra JM, Long J, Emonet T, Shimizu TS. Adaptive tuning of cell sensory diversity without changes in gene expression. SCIENCE ADVANCES 2020; 6:6/46/eabc1087. [PMID: 33188019 PMCID: PMC7673753 DOI: 10.1126/sciadv.abc1087] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/08/2020] [Accepted: 09/30/2020] [Indexed: 05/24/2023]
Abstract
In the face of uncertainty, cell populations tend to diversify to enhance survival and growth. Previous studies established that cells can optimize such bet hedging upon environmental change by modulating gene expression to adapt both the average and diversity of phenotypes. Here, we demonstrate that cells can tune phenotypic diversity also using posttranslational modifications. In the chemotaxis network of Escherichia coli, we find, for both major chemoreceptors Tar and Tsr, that cell-to-cell variation in response sensitivity is dynamically modulated depending on the presence or absence of their cognate chemoeffector ligands in the environment. Combining experiments with mathematical modeling, we show that this diversity tuning requires only the environment-dependent covalent modification of chemoreceptors and a standing cell-to-cell variation in their allosteric coupling. Thus, when environmental cues are unavailable, phenotypic diversity enhances the population's readiness for many signals. However, once a signal is perceived, the population focuses on tracking that signal.
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Affiliation(s)
- K Kamino
- AMOLF Institute, Amsterdam, Netherlands
- Departments of Molecular, Cellular and Developmental Biology and Physics, Yale University, New Haven, CT, USA
- Quantitative Biology Institute, Yale University, New Haven, CT, USA
| | | | - J Long
- Departments of Molecular, Cellular and Developmental Biology and Physics, Yale University, New Haven, CT, USA
| | - T Emonet
- Departments of Molecular, Cellular and Developmental Biology and Physics, Yale University, New Haven, CT, USA.
- Quantitative Biology Institute, Yale University, New Haven, CT, USA
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15
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Dey S, Baba SA, Bhatt A, Dhyani R, Navani NK. Transcription factor based whole-cell biosensor for specific and sensitive detection of sodium dodecyl sulfate. Biosens Bioelectron 2020; 170:112659. [PMID: 33035895 DOI: 10.1016/j.bios.2020.112659] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2020] [Revised: 09/18/2020] [Accepted: 09/25/2020] [Indexed: 01/06/2023]
Abstract
Extensive use of Sodium Dodecyl Sulfate (SDS) in households, agricultural operations, and industries is leading to its subsequent disposal in waterways. There is an apprehension of the adverse effect of such detergents on various living organisms. Thus, an efficient, specific, and simple detection method to monitor SDS reliably in the environment is needed. We used sdsB1 activator protein and SDS-responsive promoter of sdsA1 gene along with Green Fluorescent Protein (GFP) to construct a novel SDS biosensor in Pseudomonas aeruginosa chassis. The GFP intensity of the biosensor showed a linear relationship (R2 = 0.99) from 0.4 to 62.5 ppm of SDS with a detection limit of 0.1 ppm. This biosensor is highly specific for SDS and has minimal interference from other detergents, metals, and inorganic ions. The biosensor showed a satisfactory and reproducible recovery rate for the detection of SDS in real samples. Overall, this is a low cost, easy-to-use, selective, and reliable biosensor for monitoring SDS in the environment.
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Affiliation(s)
- Sourik Dey
- Chemical Biology Laboratory, Department of Biotechnology, Indian Institute of Technology, Roorkee, 247667, India
| | - Shahnawaz Ahmad Baba
- Chemical Biology Laboratory, Department of Biotechnology, Indian Institute of Technology, Roorkee, 247667, India
| | - Ankita Bhatt
- Chemical Biology Laboratory, Department of Biotechnology, Indian Institute of Technology, Roorkee, 247667, India
| | - Rajat Dhyani
- Chemical Biology Laboratory, Department of Biotechnology, Indian Institute of Technology, Roorkee, 247667, India
| | - Naveen Kumar Navani
- Chemical Biology Laboratory, Department of Biotechnology, Indian Institute of Technology, Roorkee, 247667, India.
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16
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Abstract
Feedback mechanisms are critical to control physiological responses. In gene regulation, one important example, termed negative autoregulation (NAR), occurs when a transcription factor (TF) inhibits its own production. NAR is common across the tree of life, enabling rapid homeostatic control of gene expression. NAR behavior can be described in accordance with its core biochemical parameters, but how constrained these parameters are by evolution is unclear. Here, we describe a model genetic network controlled by an NAR circuit within the bacterium Escherichia coli and elucidate these constraints by experimentally changing a key parameter and measuring its effect on circuit response and fitness. This analysis yielded a parameter-fitness landscape representing the genetic network, providing a window into what gene-environment conditions favor evolution of this regulatory strategy. Feedback mechanisms are fundamental to the control of physiological responses. One important example in gene regulation, termed negative autoregulation (NAR), occurs when a transcription factor (TF) inhibits its own production through transcriptional repression. This enables more-rapid homeostatic control of gene expression. NAR circuits presumably evolve to limit the fitness costs of gratuitous gene expression. The key biochemical reactions of NAR can be parameterized using a mathematical model of promoter activity; however, this model of NAR has been studied mostly in the context of synthetic NAR circuits that are disconnected from the target genes of the TFs. Thus, it remains unclear how constrained NAR parameters are in a native circuit context, where the TF target genes can have fitness effects on the cell. To quantify these constraints, we created a panel of Escherichia coli strains with different lexA-NAR circuit parameters and analyzed the effect on SOS response function and bacterial fitness. Using a mathematical model for NAR, these experimental data were used to calculate NAR parameter values and derive a parameter-fitness landscape. Without feedback, survival of DNA damage was decreased due to high LexA concentrations and slower SOS “turn-on” kinetics. However, we show that, even in the absence of DNA damage, the lexA promoter is strong enough that, without feedback, high levels of lexA expression result in a fitness cost to the cell. Conversely, hyperfeedback can mimic lexA deletion, which is also costly. This work elucidates the lexA-NAR parameter values capable of balancing the cell’s requirement for rapid SOS response activation with limiting its toxicity. IMPORTANCE Feedback mechanisms are critical to control physiological responses. In gene regulation, one important example, termed negative autoregulation (NAR), occurs when a transcription factor (TF) inhibits its own production. NAR is common across the tree of life, enabling rapid homeostatic control of gene expression. NAR behavior can be described in accordance with its core biochemical parameters, but how constrained these parameters are by evolution is unclear. Here, we describe a model genetic network controlled by an NAR circuit within the bacterium Escherichia coli and elucidate these constraints by experimentally changing a key parameter and measuring its effect on circuit response and fitness. This analysis yielded a parameter-fitness landscape representing the genetic network, providing a window into what gene-environment conditions favor evolution of this regulatory strategy.
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17
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Leifer I, Morone F, Reis SDS, Andrade JS, Sigman M, Makse HA. Circuits with broken fibration symmetries perform core logic computations in biological networks. PLoS Comput Biol 2020; 16:e1007776. [PMID: 32555578 PMCID: PMC7299331 DOI: 10.1371/journal.pcbi.1007776] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2019] [Accepted: 03/06/2020] [Indexed: 01/09/2023] Open
Abstract
We show that logic computational circuits in gene regulatory networks arise from a fibration symmetry breaking in the network structure. From this idea we implement a constructive procedure that reveals a hierarchy of genetic circuits, ubiquitous across species, that are surprising analogues to the emblematic circuits of solid-state electronics: starting from the transistor and progressing to ring oscillators, current-mirror circuits to toggle switches and flip-flops. These canonical variants serve fundamental operations of synchronization and clocks (in their symmetric states) and memory storage (in their broken symmetry states). These conclusions introduce a theoretically principled strategy to search for computational building blocks in biological networks, and present a systematic route to design synthetic biological circuits. We show that the core functional logic of genetic circuits arises from a fundamental symmetry breaking of the interactions of the biological network. The idea can be put into a hierarchy of symmetric genetic circuits that reveals their logical functions. We do so through a constructive procedure that naturally reveals a series of building blocks, widely present across species. This hierarchy maps to a progression of fundamental units of electronics, starting with the transistor, progressing to ring oscillators and current-mirror circuits and then to synchronized clocks, switches and finally to memory devices such as latches and flip-flops.
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Affiliation(s)
- Ian Leifer
- Levich Institute and Physics Department, City College of New York, New York, New York, United States of America
| | - Flaviano Morone
- Levich Institute and Physics Department, City College of New York, New York, New York, United States of America
| | - Saulo D. S. Reis
- Departamento de Física, Universidade Federal do Ceará, Fortaleza, Ceará, Brazil
| | - José S. Andrade
- Departamento de Física, Universidade Federal do Ceará, Fortaleza, Ceará, Brazil
| | - Mariano Sigman
- Laboratorio de Neurociencia, Universidad Torcuato Di Tella, Buenos Aires, Argentina
- CONICET (Consejo Nacional de Investigaciones Científicas y Tecnicas), Argentina
- Facultad de Lenguas y Educacion, Universidad Nebrija, Madrid, Spain
| | - Hernán A. Makse
- Levich Institute and Physics Department, City College of New York, New York, New York, United States of America
- * E-mail:
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18
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Osuna BA, Karambelkar S, Mahendra C, Sarbach A, Johnson MC, Kilcher S, Bondy-Denomy J. Critical Anti-CRISPR Locus Repression by a Bi-functional Cas9 Inhibitor. Cell Host Microbe 2020; 28:23-30.e5. [PMID: 32325051 DOI: 10.1016/j.chom.2020.04.002] [Citation(s) in RCA: 39] [Impact Index Per Article: 9.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/24/2019] [Revised: 03/05/2020] [Accepted: 03/31/2020] [Indexed: 02/06/2023]
Abstract
Bacteriophages must rapidly deploy anti-CRISPR proteins (Acrs) to inactivate the RNA-guided nucleases that enforce CRISPR-Cas adaptive immunity in their bacterial hosts. Listeria monocytogenes temperate phages encode up to three anti-Cas9 proteins, with acrIIA1 always present. AcrIIA1 binds and inhibits Cas9 with its C-terminal domain; however, the function of its highly conserved N-terminal domain (NTD) is unknown. Here, we report that the AcrIIA1NTD is a critical transcriptional repressor of the strong anti-CRISPR promoter. A rapid burst of anti-CRISPR transcription occurs during phage infection and the subsequent negative feedback by AcrIIA1NTD is required for optimal phage replication, even in the absence of CRISPR-Cas immunity. In the presence of CRISPR-Cas immunity, full-length AcrIIA1 uses its two-domain architecture to act as a "Cas9 sensor," tuning acr expression according to Cas9 levels. Finally, we identify AcrIIA1NTD homologs in other Firmicutes and demonstrate that they have been co-opted by hosts as "anti-anti-CRISPRs," repressing phage anti-CRISPR deployment.
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Affiliation(s)
- Beatriz A Osuna
- Department of Microbiology and Immunology, University of California, San Francisco, San Francisco, CA 94158, USA
| | - Shweta Karambelkar
- Department of Microbiology and Immunology, University of California, San Francisco, San Francisco, CA 94158, USA
| | - Caroline Mahendra
- Department of Microbiology and Immunology, University of California, San Francisco, San Francisco, CA 94158, USA
| | - Anne Sarbach
- Institute of Food, Nutrition, and Health, ETH Zurich, Zurich CH 8092, Switzerland
| | - Matthew C Johnson
- Department of Microbiology and Immunology, University of California, San Francisco, San Francisco, CA 94158, USA
| | - Samuel Kilcher
- Institute of Food, Nutrition, and Health, ETH Zurich, Zurich CH 8092, Switzerland.
| | - Joseph Bondy-Denomy
- Department of Microbiology and Immunology, University of California, San Francisco, San Francisco, CA 94158, USA; Quantitative Biosciences Institute, University of California, San Francisco, San Francisco, CA 94158, USA; Innovative Genomics Institute, Berkeley, CA, USA.
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19
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Abstract
Microbes adapt their metabolism to take advantage of nutrients in their environment. Such adaptations control specific metabolic pathways to match energetic demands with nutrient availability. Upon depletion of nutrients, rapid pathway recovery is key to release cellular resources required for survival under the new nutritional conditions. Yet, little is known about the regulatory strategies that microbes employ to accelerate pathway recovery in response to nutrient depletion. Using the fatty acid catabolic pathway in Escherichia coli, here, we show that fast recovery can be achieved by rapid release of a transcriptional regulator from a metabolite-sequestered complex. With a combination of mathematical modeling and experiments, we show that recovery dynamics depend critically on the rate of metabolite consumption and the exposure time to nutrients. We constructed strains with rewired transcriptional regulatory architectures that highlight the metabolic benefits of negative autoregulation over constitutive and positive autoregulation. Our results have wide-ranging implications for our understanding of metabolic adaptations, as well as for guiding the design of gene circuitry for synthetic biology and metabolic engineering.IMPORTANCE Rapid metabolic recovery during nutrient shift is critical to microbial survival, cell fitness, and competition among microbiota, yet little is known about the regulatory mechanisms of rapid metabolic recovery. This work demonstrates a previously unknown mechanism where rapid release of a transcriptional regulator from a metabolite-sequestered complex enables fast recovery to nutrient depletion. The work identified key regulatory architectures and parameters that control the speed of recovery, with wide-ranging implications for the understanding of metabolic adaptations as well as synthetic biology and metabolic engineering.
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20
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Hasan ABMSU, Kurata H, Pechmann S. Improvement of the memory function of a mutual repression network in a stochastic environment by negative autoregulation. BMC Bioinformatics 2019; 20:734. [PMID: 31881978 PMCID: PMC6935196 DOI: 10.1186/s12859-019-3315-2] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2019] [Accepted: 12/12/2019] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Cellular memory is a ubiquitous function of biological systems. By generating a sustained response to a transient inductive stimulus, often due to bistability, memory is central to the robust control of many important biological processes. However, our understanding of the origins of cellular memory remains incomplete. Stochastic fluctuations that are inherent to most biological systems have been shown to hamper memory function. Yet, how stochasticity changes the behavior of genetic circuits is generally not clear from a deterministic analysis of the network alone. Here, we apply deterministic rate equations, stochastic simulations, and theoretical analyses of Fokker-Planck equations to investigate how intrinsic noise affects the memory function in a mutual repression network. RESULTS We find that the addition of negative autoregulation improves the persistence of memory in a small gene regulatory network by reducing stochastic fluctuations. Our theoretical analyses reveal that this improved memory function stems from an increased stability of the steady states of the system. Moreover, we show how the tuning of critical network parameters can further enhance memory. CONCLUSIONS Our work illuminates the power of stochastic and theoretical approaches to understanding biological circuits, and the importance of considering stochasticity when designing synthetic circuits with memory function.
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Affiliation(s)
- A B M Shamim Ul Hasan
- Department of Biochemistry, Université de Montréal, 2900 Edouard Montpetit Blvd, Montreal, QC, H3T 1J4, Canada.,The Biomedical Informatics R&D Center, Kyushu Institute of Technology, 680-4 Kawazu, Iizuka, Fukuoka, 820-8502, Japan
| | - Hiroyuki Kurata
- The Biomedical Informatics R&D Center, Kyushu Institute of Technology, 680-4 Kawazu, Iizuka, Fukuoka, 820-8502, Japan.
| | - Sebastian Pechmann
- Department of Biochemistry, Université de Montréal, 2900 Edouard Montpetit Blvd, Montreal, QC, H3T 1J4, Canada.
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21
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Gene networks that compensate for crosstalk with crosstalk. Nat Commun 2019; 10:4028. [PMID: 31492904 PMCID: PMC6731275 DOI: 10.1038/s41467-019-12021-y] [Citation(s) in RCA: 21] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2017] [Accepted: 08/12/2019] [Indexed: 12/18/2022] Open
Abstract
Crosstalk is a major challenge to engineering sophisticated synthetic gene networks. A common approach is to insulate signal-transduction pathways by minimizing molecular-level crosstalk between endogenous and synthetic genetic components, but this strategy can be difficult to apply in the context of complex, natural gene networks and unknown interactions. Here, we show that synthetic gene networks can be engineered to compensate for crosstalk by integrating pathway signals, rather than by pathway insulation. We demonstrate this principle using reactive oxygen species (ROS)-responsive gene circuits in Escherichia coli that exhibit concentration-dependent crosstalk with non-cognate ROS. We quantitatively map the degree of crosstalk and design gene circuits that introduce compensatory crosstalk at the gene network level. The resulting gene network exhibits reduced crosstalk in the sensing of the two different ROS. Our results suggest that simple network motifs that compensate for pathway crosstalk can be used by biological networks to accurately interpret environmental signals. Crosstalk between genetic circuits is a major challenge for engineering sophisticated networks. Here the authors design networks that compensate for crosstalk by integrating, not insulating, pathways.
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22
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Guinn MT, Balázsi G. Noise-reducing optogenetic negative-feedback gene circuits in human cells. Nucleic Acids Res 2019; 47:7703-7714. [PMID: 31269201 PMCID: PMC6698750 DOI: 10.1093/nar/gkz556] [Citation(s) in RCA: 20] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2019] [Revised: 06/10/2019] [Accepted: 06/12/2019] [Indexed: 12/16/2022] Open
Abstract
Gene autorepression is widely present in nature and is also employed in synthetic biology, partly to reduce gene expression noise in cells. Optogenetic systems have recently been developed for controlling gene expression levels in mammalian cells, but most have utilized activator-based proteins, neglecting negative feedback except for in silico control. Here, we engineer optogenetic gene circuits into mammalian cells to achieve noise-reduction for precise gene expression control by genetic, in vitro negative feedback. We build a toolset of these noise-reducing Light-Inducible Tuner (LITer) gene circuits using the TetR repressor fused with a Tet-inhibiting peptide (TIP) or a degradation tag through the light-sensitive LOV2 protein domain. These LITers provide a range of nearly 4-fold gene expression control and up to 5-fold noise reduction from existing optogenetic systems. Moreover, we use the LITer gene circuit architecture to control gene expression of the cancer oncogene KRAS(G12V) and study its downstream effects through phospho-ERK levels and cellular proliferation. Overall, these novel LITer optogenetic platforms should enable precise spatiotemporal perturbations for studying multicellular phenotypes in developmental biology, oncology and other biomedical fields of research.
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Affiliation(s)
- Michael Tyler Guinn
- Biomedical Engineering Department, Stony Brook University, Stony Brook, NY 11794, USA
- The Louis and Beatrice Laufer Center for Physical and Quantitative Biology, Stony Brook University, Stony Brook, NY 11794, USA
- Stony Brook Medical Scientist Training Program, Renaissance School of Medicine at Stony Brook University, Stony Brook, NY 11794, USA
| | - Gábor Balázsi
- Biomedical Engineering Department, Stony Brook University, Stony Brook, NY 11794, USA
- The Louis and Beatrice Laufer Center for Physical and Quantitative Biology, Stony Brook University, Stony Brook, NY 11794, USA
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23
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Design, cloning and characterization of transcription factor-based inducible gene expression systems. Methods Enzymol 2019; 621:153-169. [PMID: 31128776 DOI: 10.1016/bs.mie.2019.02.018] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
Cellular functions are often controlled by small molecular weight molecules such as metabolites. Microorganisms, mainly prokaryotes, have evolved sensing and regulatory mechanisms based on transcriptional regulators (TRs) that are able to activate gene expression in response to changes in intra- and extracellular metabolite (ligand) concentrations. To understanding control mechanisms and cell factory development in synthetic biology applications, high throughput analytical procedures are required. In this chapter, we outline a methodological pipeline to design and build reporter constructs enabling the characterization of metabolite-responsive inducible gene expression systems. As an example, we present the design, cloning and characterization of the itaconate-inducible system which is composed of the LysR-type transcriptional regulator ItcR and the promoter Pccl from Yersinia pseudotuberculosis. Fluorescence-based plate reader and flow cytometry assays are described and the steps for performing data analysis are provided.
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24
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McLaughlin PT, Bhardwaj V, Feeley BE, Higgs PI. MrpC, a CRP/Fnr homolog, functions as a negative autoregulator during the
Myxococcus xanthus
multicellular developmental program. Mol Microbiol 2018; 109:245-261. [DOI: 10.1111/mmi.13982] [Citation(s) in RCA: 20] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2018] [Revised: 05/05/2018] [Accepted: 05/05/2018] [Indexed: 02/06/2023]
Affiliation(s)
| | - Vidhi Bhardwaj
- Department of EcophysiologyMax Planck Institute for Terrestrial MicrobiologyMarburg Hesse Germany
| | - Brooke E. Feeley
- Department of Biological SciencesWayne State UniversityDetroit MI USA
| | - Penelope I. Higgs
- Department of Biological SciencesWayne State UniversityDetroit MI USA
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25
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Engineering a Functional Small RNA Negative Autoregulation Network with Model-Guided Design. ACS Synth Biol 2018; 7:1507-1518. [PMID: 29733627 DOI: 10.1021/acssynbio.7b00440] [Citation(s) in RCA: 28] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
RNA regulators are powerful components of the synthetic biology toolbox. Here, we expand the repertoire of synthetic gene networks built from these regulators by constructing a transcriptional negative autoregulation (NAR) network out of small RNAs (sRNAs). NAR network motifs are core motifs of natural genetic networks, and are known for reducing network response time and steady state signal. Here we use cell-free transcription-translation (TX-TL) reactions and a computational model to design and prototype sRNA NAR constructs. Using parameter sensitivity analysis, we design a simple set of experiments that allow us to accurately predict NAR function in TX-TL. We transfer successful network designs into Escherichia coli and show that our sRNA transcriptional network reduces both network response time and steady-state gene expression. This work broadens our ability to construct increasingly sophisticated RNA genetic networks with predictable function.
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26
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Saltepe B, Kehribar EŞ, Su Yirmibeşoğlu SS, Şafak Şeker UÖ. Cellular Biosensors with Engineered Genetic Circuits. ACS Sens 2018; 3:13-26. [PMID: 29168381 DOI: 10.1021/acssensors.7b00728] [Citation(s) in RCA: 45] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
An increasing interest in building novel biological devices with designed cellular functionalities has triggered the search of innovative tools for biocomputation. Utilizing the tools of synthetic biology, numerous genetic circuits have been implemented such as engineered logic operation in analog and digital circuits. Whole cell biosensors are widely used biological devices that employ several biocomputation tools to program cells for desired functions. Up to the present date, a wide range of whole-cell biosensors have been designed and implemented for disease theranostics, biomedical applications, and environmental monitoring. In this review, we investigated the recent developments in biocomputation tools such as analog, digital, and mix circuits, logic gates, switches, and state machines. Additionally, we stated the novel applications of biological devices with computing functionalities for diagnosis and therapy of various diseases such as infections, cancer, or metabolic diseases, as well as the detection of environmental pollutants such as heavy metals or organic toxic compounds. Current whole-cell biosensors are innovative alternatives to classical biosensors; however, there is still a need to advance decision making capabilities by developing novel biocomputing devices.
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Affiliation(s)
- Behide Saltepe
- UNAM-Institute
of Materials Science and Nanotechnology, Bilkent University, 06800 Ankara, Turkey
| | - Ebru Şahin Kehribar
- UNAM-Institute
of Materials Science and Nanotechnology, Bilkent University, 06800 Ankara, Turkey
| | | | - Urartu Özgür Şafak Şeker
- UNAM-Institute
of Materials Science and Nanotechnology, Bilkent University, 06800 Ankara, Turkey
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27
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Lewis DD, Chavez M, Chiu KL, Tan C. Reconfigurable Analog Signal Processing by Living Cells. ACS Synth Biol 2018; 7:107-120. [PMID: 29113433 DOI: 10.1021/acssynbio.7b00255] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
Living cells are known for their capacity for versatile signal processing, particularly the ability to respond differently to the same stimuli using biochemical networks that integrate environmental signals and reconfigure their dynamic responses. However, the complexity of natural biological networks confounds the discovery of fundamental mechanisms behind versatile signaling. Here, we study one specific aspect of reconfigurable signal processing in which a minimal biological network integrates two signals, using one to reconfigure the network's transfer function with respect to the other, producing an emergent switch between induction and repression. In contrast to known mechanisms, the new mechanism reconfigures transfer functions through genetic networks without extensive protein-protein interactions. These results provide a novel explanation for the versatility of genetic programs, and suggest a new mechanism of signal integration that may govern flexibility and plasticity of gene expression.
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Affiliation(s)
- Daniel D. Lewis
- Department
of Biomedical Engineering, University of California Davis, 1 Shields Avenue, Davis, California 95616, United States
- Integrative
Genetics and Genomics, University of California Davis, 1 Shields Avenue, Davis, California 95616, United States
| | - Michael Chavez
- Department
of Biomedical Engineering, University of California Davis, 1 Shields Avenue, Davis, California 95616, United States
| | - Kwan Lun Chiu
- Department
of Biomedical Engineering, University of California Davis, 1 Shields Avenue, Davis, California 95616, United States
| | - Cheemeng Tan
- Department
of Biomedical Engineering, University of California Davis, 1 Shields Avenue, Davis, California 95616, United States
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28
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Schultz D, Palmer AC, Kishony R. Regulatory Dynamics Determine Cell Fate following Abrupt Antibiotic Exposure. Cell Syst 2017; 5:509-517.e3. [PMID: 29102611 DOI: 10.1016/j.cels.2017.10.002] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2016] [Revised: 06/26/2017] [Accepted: 09/29/2017] [Indexed: 02/06/2023]
Abstract
Bacterial resistance mechanisms must cope with transient fast-changing conditions. These systems are often repressed in the absence of the drug, and it is unclear how their regulation can provide a quick response when challenged. Here, we focus on the tet operon, which provides resistance to tetracycline through efflux pump TetA. We show that, somewhat counterintuitively, prompt expression of the TetA repressor TetR is key for cellular survival upon abrupt drug exposure. Tracking individual cells upon exposure, we find that differences in the rate of TetR elevation result in three distinct cell fates: recovery (high rate), death due to excess TetA (intermediate rate), and death from the drug (low rate). A surge of TetR expression optimizes the response by allowing sensitive detection of both the initial rise and the later decline of intracellular drug, avoiding an undesirable overshoot in TetA expression. These results show how regulatory circuits of resistance genes have evolved for optimized dynamics.
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Affiliation(s)
- Daniel Schultz
- Department of Biology, Technion - Israel Institute of Technology, Haifa 3200003, Israel; Department of Systems Biology, Harvard Medical School, Boston, MA 02115, USA
| | - Adam C Palmer
- Department of Systems Biology, Harvard Medical School, Boston, MA 02115, USA
| | - Roy Kishony
- Department of Biology, Technion - Israel Institute of Technology, Haifa 3200003, Israel; Department of Systems Biology, Harvard Medical School, Boston, MA 02115, USA; Department of Computer Science, Technion - Israel Institute of Technology, Haifa 3200003, Israel.
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29
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Rodrigo G, Bajić D, Elola I, Poyatos JF. Deconstructing a multiple antibiotic resistance regulation through the quantification of its input function. NPJ Syst Biol Appl 2017; 3:30. [PMID: 29018569 PMCID: PMC5630622 DOI: 10.1038/s41540-017-0031-2] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2017] [Revised: 09/01/2017] [Accepted: 09/12/2017] [Indexed: 12/21/2022] Open
Abstract
Many essential bacterial responses present complex transcriptional regulation of gene expression. To what extent can the study of these responses substantiate the logic of their regulation? Here, we show how the input function of the genes constituting the response, i.e., the information of how their transcription rates change as function of the signals acting on the regulators, can serve as a quantitative tool to deconstruct the corresponding regulatory logic. To demonstrate this approach, we consider the multiple antibiotic resistance (mar) response in Escherichia coli. By characterizing the input function of its representative genes in wild-type and mutant bacteria, we recognize a dual autoregulation motif as main determinant of the response, which is further adjusted by the interplay with other regulators. We show that basic attributes, like its reaction to a wide range of stress or its moderate expression change, are associated with a strong negative autoregulation, while others, like the buffering of metabolic signals or the lack of memory to previous stress, are related to a weak positive autoregulation. With a mathematical model of the input functions, we identify some constraints fixing the molecular attributes of the regulators, and also notice the relevance of the bicystronic architecture harboring the dual autoregulation that is unique in E. coli. The input function emerges then as a tool to disentangle the rationale behind most of the attributes defining the mar phenotype. Overall, the present study supports the value of characterizing input functions to deconstruct the complexity of regulatory architectures in prokaryotic and eukaryotic systems. Many cellular responses result from the integration of numerous regulatory signals. To deconstruct the regulation of one of these responses, which enables resistance to multiple antibiotics in Escherichia coli, a team led by Juan F. Poyatos at the National Center for Biotechnology in Madrid studied the response input function by combining theoretical models and experiments. This function quantifies the rate of transcription of the genes constituting the response with respect to the signals acting on its cognate regulators. By examining how the shape of the function changes in different situations, e.g., when a given regulator is mutated, the team identified the implications for the specificity and dynamics of the response of a dual autoregulation at the core of the control architecture. The use of input functions as quantitative tools allows us to reverse engineer the complex regulations that dictate essential physiological functions in both prokaryotic and eukaryotic cells.
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Affiliation(s)
- Guillermo Rodrigo
- Instituto de Biología Molecular y Celular de Plantas, CSIC-UPV, 46022 Valencia, Spain
| | - Djordje Bajić
- Logic of Genomic Systems Laboratory, CNB-CSIC, 28049 Madrid, Spain.,Present Address: Department of Ecology and Evolutionary Biology, Yale University, New Haven, USA
| | - Ignacio Elola
- Logic of Genomic Systems Laboratory, CNB-CSIC, 28049 Madrid, Spain
| | - Juan F Poyatos
- Logic of Genomic Systems Laboratory, CNB-CSIC, 28049 Madrid, Spain
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30
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Folliard T, Steel H, Prescott TP, Wadhams G, Rothschild LJ, Papachristodoulou A. A Synthetic Recombinase-Based Feedback Loop Results in Robust Expression. ACS Synth Biol 2017; 6:1663-1671. [PMID: 28602075 DOI: 10.1021/acssynbio.7b00131] [Citation(s) in RCA: 25] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
Accurate control of a biological process is essential for many critical functions in biology, from the cell cycle to proteome regulation. To achieve this, negative feedback is frequently employed to provide a highly robust and reliable output. Feedback is found throughout biology and technology, but due to challenges posed by its implementation, it is yet to be widely adopted in synthetic biology. In this paper we design a synthetic feedback network using a class of recombinase proteins called integrases, which can be re-engineered to flip the orientation of DNA segments in a digital manner. This system is highly orthogonal, and demonstrates a strong capability for regulating and reducing the expression variability of genes being transcribed under its control. An excisionase protein provides the negative feedback signal to close the loop in this system, by flipping DNA segments in the reverse direction. Our integrase/excisionase negative feedback system thus provides a modular architecture that can be tuned to suit applications throughout synthetic biology and biomanufacturing that require a highly robust and orthogonally controlled output.
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Affiliation(s)
- Thomas Folliard
- Department
of Biochemistry, University of Oxford, South Parks Road, Oxford, OX1 3QU, U.K
| | - Harrison Steel
- Department
of Engineering Science, University of Oxford, Parks Road, Oxford, OX1 3PJ, U.K
| | - Thomas P. Prescott
- Department
of Engineering Science, University of Oxford, Parks Road, Oxford, OX1 3PJ, U.K
| | - George Wadhams
- Department
of Biochemistry, University of Oxford, South Parks Road, Oxford, OX1 3QU, U.K
| | - Lynn J. Rothschild
- National
Aeronautics
and Space Administration Ames Research Center, Moffett Field, California 94035, United States
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31
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Rohlhill J, Sandoval NR, Papoutsakis ET. Sort-Seq Approach to Engineering a Formaldehyde-Inducible Promoter for Dynamically Regulated Escherichia coli Growth on Methanol. ACS Synth Biol 2017; 6:1584-1595. [PMID: 28463494 PMCID: PMC5569641 DOI: 10.1021/acssynbio.7b00114] [Citation(s) in RCA: 63] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
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Tight and tunable control of gene
expression is a highly desirable
goal in synthetic biology for constructing predictable gene circuits
and achieving preferred phenotypes. Elucidating the sequence–function
relationship of promoters is crucial for manipulating gene expression
at the transcriptional level, particularly for inducible systems dependent
on transcriptional regulators. Sort-seq methods employing fluorescence-activated
cell sorting (FACS) and high-throughput sequencing allow for the quantitative
analysis of sequence–function relationships in a robust and
rapid way. Here we utilized a massively parallel sort-seq approach
to analyze the formaldehyde-inducible Escherichia coli promoter (Pfrm) with single-nucleotide
resolution. A library of mutated formaldehyde-inducible promoters
was cloned upstream of gfp on a plasmid. The library
was partitioned into bins via FACS on the basis of green fluorescent
protein (GFP) expression level, and mutated promoters falling into
each expression bin were identified with high-throughput sequencing.
The resulting analysis identified two 19 base pair repressor binding
sites, one upstream of the −35 RNA polymerase (RNAP) binding
site and one overlapping with the −10 site, and assessed the
relative importance of each position and base therein. Key mutations
were identified for tuning expression levels and were used to engineer
formaldehyde-inducible promoters with predictable activities. Engineered
variants demonstrated up to 14-fold lower basal expression, 13-fold
higher induced expression, and a 3.6-fold stronger response as indicated
by relative dynamic range. Finally, an engineered formaldehyde-inducible
promoter was employed to drive the expression of heterologous methanol
assimilation genes and achieved increased biomass levels on methanol,
a non-native substrate of E. coli.
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Affiliation(s)
- Julia Rohlhill
- Department of Chemical & Biomolecular Engineering and the Delaware Biotechnology Institute, University of Delaware, Newark, Delaware 19711, United States
| | - Nicholas R. Sandoval
- Department of Chemical & Biomolecular Engineering, Tulane University, New Orleans, Louisiana 70118, United States
| | - Eleftherios T. Papoutsakis
- Department of Chemical & Biomolecular Engineering and the Delaware Biotechnology Institute, University of Delaware, Newark, Delaware 19711, United States
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32
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Shopera T, He L, Oyetunde T, Tang YJ, Moon TS. Decoupling Resource-Coupled Gene Expression in Living Cells. ACS Synth Biol 2017; 6:1596-1604. [PMID: 28459541 DOI: 10.1021/acssynbio.7b00119] [Citation(s) in RCA: 40] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
Synthetic biology aspires to develop frameworks that enable the construction of complex and reliable gene networks with predictable functionalities. A key limitation is that increasing network complexity increases the demand for cellular resources, potentially causing resource-associated interference among noninteracting circuits. Although recent studies have shown the effects of resource competition on circuit behaviors, mechanisms that decouple such interference remain unclear. Here, we constructed three systems in Escherichia coli, each consisting of two independent circuit modules where the complexity of one module (Circuit 2) was systematically increased while the other (Circuit 1) remained identical. By varying the expression level of Circuit 1 and measuring its effect on the expression level of Circuit 2, we demonstrated computationally and experimentally that indirect coupling between these seemingly unconnected genetic circuits can occur in three different regulatory topologies. More importantly, we experimentally verified the computational prediction that negative feedback can significantly reduce resource-coupled interference in regulatory circuits. Our results reveal a design principle that enables cells to reliably multitask while tightly controlling cellular resources.
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Affiliation(s)
- Tatenda Shopera
- Department of Energy, Environmental
and Chemical Engineering, Washington University in St. Louis, St. Louis, Missouri 63130, United States
| | - Lian He
- Department of Energy, Environmental
and Chemical Engineering, Washington University in St. Louis, St. Louis, Missouri 63130, United States
| | - Tolutola Oyetunde
- Department of Energy, Environmental
and Chemical Engineering, Washington University in St. Louis, St. Louis, Missouri 63130, United States
| | - Yinjie J. Tang
- Department of Energy, Environmental
and Chemical Engineering, Washington University in St. Louis, St. Louis, Missouri 63130, United States
| | - Tae Seok Moon
- Department of Energy, Environmental
and Chemical Engineering, Washington University in St. Louis, St. Louis, Missouri 63130, United States
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33
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Holowko MB, Wang H, Jayaraman P, Poh CL. Biosensing Vibrio cholerae with Genetically Engineered Escherichia coli. ACS Synth Biol 2016; 5:1275-1283. [PMID: 27529184 DOI: 10.1021/acssynbio.6b00079] [Citation(s) in RCA: 36] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
Cholera is a potentially mortal, infectious disease caused by Vibrio cholerae bacterium. Current treatment methods of cholera still have limitations. Beneficial microbes that could sense and kill the V. cholerae could offer potential alternative to preventing and treating cholera. However, such V. cholerae targeting microbe is still not available. This microbe requires a sensing system to be able to detect the presence of V. cholera bacterium. To this end, we designed and created a synthetic genetic sensing system using nonpathogenic Escherichia coli as the host. To achieve the system, we have moved proteins used by V. cholerae for quorum sensing into E. coli. These sensor proteins have been further layered with a genetic inverter based on CRISPRi technology. Our design process was aided by computer models simulating in vivo behavior of the system. Our sensor shows high sensitivity to presence of V. cholerae supernatant with tight control of expression of output GFP protein.
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Affiliation(s)
- Maciej B. Holowko
- School of Chemical and Biomedical
Engineering, Nanyang Technological University, Singapore 639798
| | - Huijuan Wang
- School of Chemical and Biomedical
Engineering, Nanyang Technological University, Singapore 639798
| | - Premkumar Jayaraman
- School of Chemical and Biomedical
Engineering, Nanyang Technological University, Singapore 639798
| | - Chueh Loo Poh
- School of Chemical and Biomedical
Engineering, Nanyang Technological University, Singapore 639798
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34
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Marciano DC, Lua RC, Herman C, Lichtarge O. Cooperativity of Negative Autoregulation Confers Increased Mutational Robustness. PHYSICAL REVIEW LETTERS 2016; 116:258104. [PMID: 27391757 PMCID: PMC5152588 DOI: 10.1103/physrevlett.116.258104] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/24/2015] [Indexed: 05/05/2023]
Abstract
Negative autoregulation is universally found across organisms. In the bacterium Escherichia coli, transcription factors often repress their own expression to form a negative feedback network motif that enables robustness to changes in biochemical parameters. Here we present a simple phenomenological model of a negative feedback transcription factor repressing both itself and another target gene. The strength of the negative feedback is characterized by three parameters: the cooperativity in self-repression, the maximal expression rate of the transcription factor, and the apparent dissociation constant of the transcription factor binding to its own promoter. Analysis of the model shows that the target gene levels are robust to mutations in the transcription factor, and that the robustness improves as the degree of cooperativity in self-repression increases. The prediction is tested in the LexA transcriptional network of E. coli by altering cooperativity in self-repression and promoter strength. Indeed, we find robustness is correlated with the former. Considering the proposed importance of gene regulation in speciation, parameters governing a transcription factor's robustness to mutation may have significant influence on a cell or organism's capacity to evolve.
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Affiliation(s)
- David C. Marciano
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, Texas 77030, USA
| | - Rhonald C. Lua
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, Texas 77030, USA
| | - Christophe Herman
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, Texas 77030, USA
| | - Olivier Lichtarge
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, Texas 77030, USA
- Verna and Marrs McLean Department of Biochemistry and Molecular Biology, Baylor College of Medicine, Houston, Texas 77030, USA
- Computational and Integrative Biomedical Research Center, Baylor College of Medicine, Houston, Texas 77030, USA
- Corresponding author.
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35
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Evaluating network inference methods in terms of their ability to preserve the topology and complexity of genetic networks. Semin Cell Dev Biol 2016; 51:44-52. [PMID: 26851626 DOI: 10.1016/j.semcdb.2016.01.012] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2016] [Accepted: 01/07/2016] [Indexed: 12/26/2022]
Abstract
Network inference is a rapidly advancing field, with new methods being proposed on a regular basis. Understanding the advantages and limitations of different network inference methods is key to their effective application in different circumstances. The common structural properties shared by diverse networks naturally pose a challenge when it comes to devising accurate inference methods, but surprisingly, there is a paucity of comparison and evaluation methods. Historically, every new methodology has only been tested against gold standard (true values) purpose-designed synthetic and real-world (validated) biological networks. In this paper we aim to assess the impact of taking into consideration aspects of topological and information content in the evaluation of the final accuracy of an inference procedure. Specifically, we will compare the best inference methods, in both graph-theoretic and information-theoretic terms, for preserving topological properties and the original information content of synthetic and biological networks. New methods for performance comparison are introduced by borrowing ideas from gene set enrichment analysis and by applying concepts from algorithmic complexity. Experimental results show that no individual algorithm outperforms all others in all cases, and that the challenging and non-trivial nature of network inference is evident in the struggle of some of the algorithms to turn in a performance that is superior to random guesswork. Therefore special care should be taken to suit the method to the purpose at hand. Finally, we show that evaluations from data generated using different underlying topologies have different signatures that can be used to better choose a network reconstruction method.
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36
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Ma KC, Perli SD, Lu TK. Foundations and Emerging Paradigms for Computing in Living Cells. J Mol Biol 2016; 428:893-915. [DOI: 10.1016/j.jmb.2016.02.018] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2016] [Revised: 02/13/2016] [Accepted: 02/15/2016] [Indexed: 01/11/2023]
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37
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Galán-Vásquez E, Sánchez-Osorio I, Martínez-Antonio A. Transcription Factors Exhibit Differential Conservation in Bacteria with Reduced Genomes. PLoS One 2016; 11:e0146901. [PMID: 26766575 PMCID: PMC4713081 DOI: 10.1371/journal.pone.0146901] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2015] [Accepted: 12/23/2015] [Indexed: 11/18/2022] Open
Abstract
The description of transcriptional regulatory networks has been pivotal in the understanding of operating principles under which organisms respond and adapt to varying conditions. While the study of the topology and dynamics of these networks has been the subject of considerable work, the investigation of the evolution of their topology, as a result of the adaptation of organisms to different environmental conditions, has received little attention. In this work, we study the evolution of transcriptional regulatory networks in bacteria from a genome reduction perspective, which manifests itself as the loss of genes at different degrees. We used the transcriptional regulatory network of Escherichia coli as a reference to compare 113 smaller, phylogenetically-related γ-proteobacteria, including 19 genomes of symbionts. We found that the type of regulatory action exerted by transcription factors, as genomes get progressively smaller, correlates well with their degree of conservation, with dual regulators being more conserved than repressors and activators in conditions of extreme reduction. In addition, we found that the preponderant conservation of dual regulators might be due to their role as both global regulators and nucleoid-associated proteins. We summarize our results in a conceptual model of how each TF type is gradually lost as genomes become smaller and give a rationale for the order in which this phenomenon occurs.
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Affiliation(s)
- Edgardo Galán-Vásquez
- Center for Research and Advanced Studies of the National Polytechnic Institute, Campus Irapuato, Genetic Engineering Department, Cinvestav, Km. 9.6 Libramiento Norte Carr. Irapuato-León 36821, Irapuato Gto, México
| | - Ismael Sánchez-Osorio
- Center for Research and Advanced Studies of the National Polytechnic Institute, Campus Irapuato, Genetic Engineering Department, Cinvestav, Km. 9.6 Libramiento Norte Carr. Irapuato-León 36821, Irapuato Gto, México
| | - Agustino Martínez-Antonio
- Center for Research and Advanced Studies of the National Polytechnic Institute, Campus Irapuato, Genetic Engineering Department, Cinvestav, Km. 9.6 Libramiento Norte Carr. Irapuato-León 36821, Irapuato Gto, México
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38
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Schikora-Tamarit MÀ, Toscano-Ochoa C, Domingo Espinós J, Espinar L, Carey LB. A synthetic gene circuit for measuring autoregulatory feedback control. Integr Biol (Camb) 2016; 8:546-55. [PMID: 26728081 DOI: 10.1039/c5ib00230c] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Abstract
Autoregulatory feedback loops occur in the regulation of molecules ranging from ATP to MAP kinases to zinc. Negative feedback loops can increase a system's robustness, while positive feedback loops can mediate transitions between cell states. Recent genome-wide experimental and computational studies predict hundreds of novel feedback loops. However, not all physical interactions are regulatory, and many experimental methods cannot detect self-interactions. Our understanding of regulatory feedback loops is therefore hampered by the lack of high-throughput methods to experimentally quantify the presence, strength and temporal dynamics of autoregulatory feedback loops. Here we present a mathematical and experimental framework for high-throughput quantification of feedback regulation and apply it to RNA binding proteins (RBPs) in yeast. Our method is able to determine the existence of both direct and indirect positive and negative feedback loops, and to quantify the strength of these loops. We experimentally validate our model using two RBPs which lack native feedback loops and by the introduction of synthetic feedback loops. We find that RBP Puf3 does not natively participate in any direct or indirect feedback regulation, but that replacing the native 3'UTR with that of COX17 generates an auto-regulatory negative feedback loop which reduces gene expression noise. Likewise, RBP Pub1 does not natively participate in any feedback loops, but a synthetic positive feedback loop involving Pub1 results in increased expression noise. Our results demonstrate a synthetic experimental system for quantifying the existence and strength of feedback loops using a combination of high-throughput experiments and mathematical modeling. This system will be of great use in measuring auto-regulatory feedback by RNA binding proteins, a regulatory motif that is difficult to quantify using existing high-throughput methods.
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Affiliation(s)
- Miquel Àngel Schikora-Tamarit
- Experimental and Health Sciences, Universitat Pompeu Fabra, 88 Dr. Aiguader, UPF, PRBB, 3rd floor reception, Barcelona, Barcelona, Spain.
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39
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Rogers JK, Guzman CD, Taylor ND, Raman S, Anderson K, Church GM. Synthetic biosensors for precise gene control and real-time monitoring of metabolites. Nucleic Acids Res 2015; 43:7648-60. [PMID: 26152303 PMCID: PMC4551912 DOI: 10.1093/nar/gkv616] [Citation(s) in RCA: 162] [Impact Index Per Article: 18.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2014] [Revised: 04/20/2015] [Accepted: 06/01/2015] [Indexed: 12/19/2022] Open
Abstract
Characterization and standardization of inducible transcriptional regulators has transformed how scientists approach biology by allowing precise and tunable control of gene expression. Despite their utility, only a handful of well-characterized regulators exist, limiting the complexity of engineered biological systems. We apply a characterization pipeline to four genetically encoded sensors that respond to acrylate, glucarate, erythromycin and naringenin. We evaluate how the concentration of the inducing chemical relates to protein expression, how the extent of induction affects protein expression kinetics, and how the activation behavior of single cells relates to ensemble measurements. We show that activation of each sensor is orthogonal to the other sensors, and to other common inducible systems. We demonstrate independent control of three fluorescent proteins in a single cell, chemically defining eight unique transcriptional states. To demonstrate biosensor utility in metabolic engineering, we apply the glucarate biosensor to monitor product formation in a heterologous glucarate biosynthesis pathway and identify superior enzyme variants. Doubling the number of well-characterized inducible systems makes more complex synthetic biological circuits accessible. Characterizing sensors that transduce the intracellular concentration of valuable metabolites into fluorescent readouts enables high-throughput screening of biological catalysts and alleviates the primary bottleneck of the metabolic engineering design-build-test cycle.
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Affiliation(s)
- Jameson K Rogers
- Wyss Institute for Biologically Inspired Engineering, Harvard University, 3 Blackfan Circle, Boston, MA 02115, USA School of Engineering and Applied Sciences, Harvard University, 29 Oxford Street, Cambridge, MA 02143, USA
| | - Christopher D Guzman
- Wyss Institute for Biologically Inspired Engineering, Harvard University, 3 Blackfan Circle, Boston, MA 02115, USA
| | - Noah D Taylor
- Wyss Institute for Biologically Inspired Engineering, Harvard University, 3 Blackfan Circle, Boston, MA 02115, USA Department of Genetics, Harvard Medical School, 77 Avenue Louis Pasteur, Boston, MA 02115, USA
| | - Srivatsan Raman
- Wyss Institute for Biologically Inspired Engineering, Harvard University, 3 Blackfan Circle, Boston, MA 02115, USA Department of Genetics, Harvard Medical School, 77 Avenue Louis Pasteur, Boston, MA 02115, USA
| | - Kelley Anderson
- Wyss Institute for Biologically Inspired Engineering, Harvard University, 3 Blackfan Circle, Boston, MA 02115, USA
| | - George M Church
- Wyss Institute for Biologically Inspired Engineering, Harvard University, 3 Blackfan Circle, Boston, MA 02115, USA Department of Genetics, Harvard Medical School, 77 Avenue Louis Pasteur, Boston, MA 02115, USA
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40
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Suvorova IA, Korostelev YD, Gelfand MS. GntR Family of Bacterial Transcription Factors and Their DNA Binding Motifs: Structure, Positioning and Co-Evolution. PLoS One 2015; 10:e0132618. [PMID: 26151451 PMCID: PMC4494728 DOI: 10.1371/journal.pone.0132618] [Citation(s) in RCA: 67] [Impact Index Per Article: 7.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2015] [Accepted: 06/16/2015] [Indexed: 12/03/2022] Open
Abstract
The GntR family of transcription factors (TFs) is a large group of proteins present in diverse bacteria and regulating various biological processes. Here we use the comparative genomics approach to reconstruct regulons and identify binding motifs of regulators from three subfamilies of the GntR family, FadR, HutC, and YtrA. Using these data, we attempt to predict DNA-protein contacts by analyzing correlations between binding motifs in DNA and amino acid sequences of TFs. We identify pairs of positions with high correlation between amino acids and nucleotides for FadR, HutC, and YtrA subfamilies and show that the most predicted DNA-protein interactions are quite similar in all subfamilies and conform well to the experimentally identified contacts formed by FadR from E. coli and AraR from B. subtilis. The most frequent predicted contacts in the analyzed subfamilies are Arg-G, Asn-A, Asp-C. We also analyze the divergon structure and preferred site positions relative to regulated genes in the FadR and HutC subfamilies. A single site in a divergon usually regulates both operons and is approximately in the middle of the intergenic area. Double sites are either involved in the co-operative regulation of both operons and then are in the center of the intergenic area, or each site in the pair independently regulates its own operon and tends to be near it. We also identify additional candidate TF-binding boxes near palindromic binding sites of TFs from the FadR, HutC, and YtrA subfamilies, which may play role in the binding of additional TF-subunits.
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Affiliation(s)
- Inna A. Suvorova
- Research and Training Center on Bioinformatics, Institute for Information Transmission Problems RAS (The Kharkevich Institute), Moscow, Russia
- * E-mail:
| | - Yuri D. Korostelev
- Research and Training Center on Bioinformatics, Institute for Information Transmission Problems RAS (The Kharkevich Institute), Moscow, Russia
| | - Mikhail S. Gelfand
- Research and Training Center on Bioinformatics, Institute for Information Transmission Problems RAS (The Kharkevich Institute), Moscow, Russia
- Faculty of Bioengineering and Bioinformatics, Moscow State University, Moscow, Russia
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41
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Small regulatory RNA-induced growth rate heterogeneity of Bacillus subtilis. PLoS Genet 2015; 11:e1005046. [PMID: 25790031 PMCID: PMC4366234 DOI: 10.1371/journal.pgen.1005046] [Citation(s) in RCA: 41] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2014] [Accepted: 02/01/2015] [Indexed: 11/26/2022] Open
Abstract
Isogenic bacterial populations can consist of cells displaying heterogeneous physiological traits. Small regulatory RNAs (sRNAs) could affect this heterogeneity since they act by fine-tuning mRNA or protein levels to coordinate the appropriate cellular behavior. Here we show that the sRNA RnaC/S1022 from the Gram-positive bacterium Bacillus subtilis can suppress exponential growth by modulation of the transcriptional regulator AbrB. Specifically, the post-transcriptional abrB-RnaC/S1022 interaction allows B. subtilis to increase the cell-to-cell variation in AbrB protein levels, despite strong negative autoregulation of the abrB promoter. This behavior is consistent with existing mathematical models of sRNA action, thus suggesting that induction of protein expression noise could be a new general aspect of sRNA regulation. Importantly, we show that the sRNA-induced diversity in AbrB levels generates heterogeneity in growth rates during the exponential growth phase. Based on these findings, we hypothesize that the resulting subpopulations of fast- and slow-growing B. subtilis cells reflect a bet-hedging strategy for enhanced survival of unfavorable conditions. Bacterial cells that share the same genetic information can display very different phenotypes, even if they grow under identical conditions. Despite the relevance of this population heterogeneity for processes like drug resistance and development, the molecular players that induce heterogenic phenotypes are often not known. Here we report that in the Gram-positive model bacterium Bacillus subtilis a small regulatory RNA (sRNA) can induce heterogeneity in growth rates by increasing cell-to-cell variation in the levels of the transcriptional regulator AbrB, which is important for rapid growth. Remarkably, the observed variation in AbrB levels is induced post-transcriptionally because of AbrB’s negative autoregulation, and is not observed at the abrB promoter level. We show that our observations are consistent with mathematical models of sRNA action, thus suggesting that induction of protein expression noise could be a new general aspect of sRNA regulation. Since a low growth rate can be beneficial for cellular survival, we propose that the observed subpopulations of fast- and slow-growing B. subtilis cells reflect a bet-hedging strategy for enhanced survival of unfavorable conditions.
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42
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Afroz T, Biliouris K, Boykin KE, Kaznessis Y, Beisel CL. Trade-offs in engineering sugar utilization pathways for titratable control. ACS Synth Biol 2015; 4:141-9. [PMID: 24735079 PMCID: PMC4384834 DOI: 10.1021/sb400162z] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
![]()
Titratable
systems are common tools in metabolic engineering to
tune the levels of enzymes and cellular components as part of pathway
optimization. For nonmodel microorganisms with limited genetic tools,
inducible sugar utilization pathways offer built-in titratable systems.
However, these pathways can exhibit undesirable single-cell behaviors
that hamper the uniform and tunable control of gene expression. Here,
we applied mathematical modeling and single-cell measurements of l-arabinose utilization in Escherichia coli to systematically explore how sugar utilization pathways can be
altered to achieve desirable inducible properties. We found that different
pathway alterations, such as the removal of catabolism, constitutive
expression of high-affinity or low-affinity transporters, or further
deletion of the other transporters, came with trade-offs specific
to each alteration. For instance, sugar catabolism improved the uniformity
and linearity of the response at the cost of requiring higher sugar
concentrations to induce the pathway. Within these alterations, we
also found that a uniform and linear response could be achieved with
a single alteration: constitutively expressing the high-affinity transporter.
Equivalent modifications to the d-xylose utilization pathway
yielded similar responses, demonstrating the applicability of our
observations. Overall, our findings indicate that there is no ideal
set of typical alterations when co-opting natural utilization pathways
for titratable control and suggest design rules for manipulating these
pathways to advance basic genetic studies and the metabolic engineering
of microorganisms for optimized chemical production.
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Affiliation(s)
- Taliman Afroz
- Department
of Chemical and Biomolecular Engineering North Carolina State University Raleigh, North Carolina 27695, United States
| | - Konstantinos Biliouris
- Department
of Chemical Engineering and Materials Science University of Minnesota Minneapolis, Minnesota 55455, United States
| | - Kelsey E. Boykin
- Department
of Chemical and Biomolecular Engineering North Carolina State University Raleigh, North Carolina 27695, United States
| | - Yiannis Kaznessis
- Department
of Chemical Engineering and Materials Science University of Minnesota Minneapolis, Minnesota 55455, United States
| | - Chase L. Beisel
- Department
of Chemical and Biomolecular Engineering North Carolina State University Raleigh, North Carolina 27695, United States
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Shimizu K. Metabolic Regulation and Coordination of the Metabolism in Bacteria in Response to a Variety of Growth Conditions. ADVANCES IN BIOCHEMICAL ENGINEERING/BIOTECHNOLOGY 2015; 155:1-54. [PMID: 25712586 DOI: 10.1007/10_2015_320] [Citation(s) in RCA: 25] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Abstract
Living organisms have sophisticated but well-organized regulation system. It is important to understand the metabolic regulation mechanisms in relation to growth environment for the efficient design of cell factories for biofuels and biochemicals production. Here, an overview is given for carbon catabolite regulation, nitrogen regulation, ion, sulfur, and phosphate regulations, stringent response under nutrient starvation as well as oxidative stress regulation, redox state regulation, acid-shock, heat- and cold-shock regulations, solvent stress regulation, osmoregulation, and biofilm formation, and quorum sensing focusing on Escherichia coli metabolism and others. The coordinated regulation mechanisms are of particular interest in getting insight into the principle which governs the cell metabolism. The metabolism is controlled by both enzyme-level regulation and transcriptional regulation via transcription factors such as cAMP-Crp, Cra, Csr, Fis, P(II)(GlnB), NtrBC, CysB, PhoR/B, SoxR/S, Fur, MarR, ArcA/B, Fnr, NarX/L, RpoS, and (p)ppGpp for stringent response, where the timescales for enzyme-level and gene-level regulations are different. Moreover, multiple regulations are coordinated by the intracellular metabolites, where fructose 1,6-bisphosphate (FBP), phosphoenolpyruvate (PEP), and acetyl-CoA (AcCoA) play important roles for enzyme-level regulation as well as transcriptional control, while α-ketoacids such as α-ketoglutaric acid (αKG), pyruvate (PYR), and oxaloacetate (OAA) play important roles for the coordinated regulation between carbon source uptake rate and other nutrient uptake rate such as nitrogen or sulfur uptake rate by modulation of cAMP via Cya.
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Affiliation(s)
- Kazuyuki Shimizu
- Kyushu Institute of Technology, Iizuka, Fukuoka, 820-8502, Japan. .,Institute of Advanced Biosciences, Keio University, Tsuruoka, Yamagata, 997-0017, Japan.
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Evangelopoulos D, Gupta A, Lack NA, Maitra A, ten Bokum AM, Kendall S, Sim E, Bhakta S. Characterisation of a putative AraC transcriptional regulator from Mycobacterium smegmatis. Tuberculosis (Edinb) 2014; 94:664-71. [PMID: 25443504 PMCID: PMC4266540 DOI: 10.1016/j.tube.2014.08.007] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2014] [Revised: 08/09/2014] [Accepted: 08/13/2014] [Indexed: 11/16/2022]
Abstract
MSMEG_0307 is annotated as a transcriptional regulator belonging to the AraC protein family and is located adjacent to the arylamine N-acetyltransferase (nat) gene in Mycobacterium smegmatis, in a gene cluster, conserved in most environmental mycobacterial species. In order to elucidate the function of the AraC protein from the nat operon in M. smegmatis, two conserved palindromic DNA motifs were identified using bioinformatics and tested for protein binding using electrophoretic mobility shift assays with a recombinant form of the AraC protein. We identified the formation of a DNA:AraC protein complex with one of the motifs as well as the presence of this motif in 20 loci across the whole genome of M. smegmatis, supporting the existence of an AraC controlled regulon. To characterise the effects of AraC in the regulation of the nat operon genes, as well as to gain further insight into its function, we generated a ΔaraC mutant strain where the araC gene was replaced by a hygromycin resistance marker. The level of expression of the nat and MSMEG_0308 genes was down-regulated in the ΔaraC strain when compared to the wild type strain indicating an activator effect of the AraC protein on the expression of the nat operon genes.
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Affiliation(s)
- Dimitrios Evangelopoulos
- Mycobacteria Research Laboratory, Institute of Structural and Molecular Biology, Department of Biological Sciences, Birkbeck, University of London, Malet Street, London WC1E 7HX, UK
- Department of Pharmacology, University of Oxford, Mansfield Road, Oxford OX1 3QT, UK
| | - Antima Gupta
- Mycobacteria Research Laboratory, Institute of Structural and Molecular Biology, Department of Biological Sciences, Birkbeck, University of London, Malet Street, London WC1E 7HX, UK
| | - Nathan A. Lack
- Department of Pharmacology, University of Oxford, Mansfield Road, Oxford OX1 3QT, UK
| | - Arundhati Maitra
- Mycobacteria Research Laboratory, Institute of Structural and Molecular Biology, Department of Biological Sciences, Birkbeck, University of London, Malet Street, London WC1E 7HX, UK
| | - Annemieke M.C. ten Bokum
- Department of Pathology and Infectious Diseases, The Royal Veterinary College, Royal College Street, London NW1 0TU, UK
| | - Sharon Kendall
- Department of Pathology and Infectious Diseases, The Royal Veterinary College, Royal College Street, London NW1 0TU, UK
| | - Edith Sim
- Department of Pharmacology, University of Oxford, Mansfield Road, Oxford OX1 3QT, UK
| | - Sanjib Bhakta
- Mycobacteria Research Laboratory, Institute of Structural and Molecular Biology, Department of Biological Sciences, Birkbeck, University of London, Malet Street, London WC1E 7HX, UK
- Corresponding author. Tel.: +44 (0)20 7631 6355 (office), +44 (0)20 7079 0799 (lab); fax: +44 (0)20 7631 6246.
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Ventura AC, Bush A, Vasen G, Goldín MA, Burkinshaw B, Bhattacharjee N, Folch A, Brent R, Chernomoretz A, Colman-Lerner A. Utilization of extracellular information before ligand-receptor binding reaches equilibrium expands and shifts the input dynamic range. Proc Natl Acad Sci U S A 2014; 111:E3860-9. [PMID: 25172920 PMCID: PMC4169960 DOI: 10.1073/pnas.1322761111] [Citation(s) in RCA: 26] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/01/2023] Open
Abstract
Cell signaling systems sense and respond to ligands that bind cell surface receptors. These systems often respond to changes in the concentration of extracellular ligand more rapidly than the ligand equilibrates with its receptor. We demonstrate, by modeling and experiment, a general "systems level" mechanism cells use to take advantage of the information present in the early signal, before receptor binding reaches a new steady state. This mechanism, pre-equilibrium sensing and signaling (PRESS), operates in signaling systems in which the kinetics of ligand-receptor binding are slower than the downstream signaling steps, and it typically involves transient activation of a downstream step. In the systems where it operates, PRESS expands and shifts the input dynamic range, allowing cells to make different responses to ligand concentrations so high as to be otherwise indistinguishable. Specifically, we show that PRESS applies to the yeast directional polarization in response to pheromone gradients. Consideration of preexisting kinetic data for ligand-receptor interactions suggests that PRESS operates in many cell signaling systems throughout biology. The same mechanism may also operate at other levels in signaling systems in which a slow activation step couples to a faster downstream step.
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Affiliation(s)
- Alejandra C Ventura
- Institute of Physiology, Molecular Biology, and Neuroscience (IFIBYNE), University of Buenos Aires (UBA)-National Scientific and Technical Research Council (CONICET), Department of Physiology, Molecular, and Cell Biology, School of Exact and Natural Sciences (FCEN)
| | - Alan Bush
- Institute of Physiology, Molecular Biology, and Neuroscience (IFIBYNE), University of Buenos Aires (UBA)-National Scientific and Technical Research Council (CONICET), Department of Physiology, Molecular, and Cell Biology, School of Exact and Natural Sciences (FCEN)
| | - Gustavo Vasen
- Institute of Physiology, Molecular Biology, and Neuroscience (IFIBYNE), University of Buenos Aires (UBA)-National Scientific and Technical Research Council (CONICET), Department of Physiology, Molecular, and Cell Biology, School of Exact and Natural Sciences (FCEN)
| | - Matías A Goldín
- Institute of Physiology, Molecular Biology, and Neuroscience (IFIBYNE), University of Buenos Aires (UBA)-National Scientific and Technical Research Council (CONICET), Department of Physiology, Molecular, and Cell Biology, School of Exact and Natural Sciences (FCEN)
| | - Brianne Burkinshaw
- Institute of Physiology, Molecular Biology, and Neuroscience (IFIBYNE), University of Buenos Aires (UBA)-National Scientific and Technical Research Council (CONICET), Department of Physiology, Molecular, and Cell Biology, School of Exact and Natural Sciences (FCEN)
| | | | - Albert Folch
- Department of Bioengineering, University of Washington, Seattle, WA 98195; and
| | - Roger Brent
- Fundación Instituto Leloir, C1405BWE Buenos Aires, Argentina
| | - Ariel Chernomoretz
- Physics Institute of Buenos Aires (IFIBA), CONICET, and Department of Physics, FCEN, UBA, C1428EGA Buenos Aires, Argentina; Fundación Instituto Leloir, C1405BWE Buenos Aires, Argentina
| | - Alejandro Colman-Lerner
- Institute of Physiology, Molecular Biology, and Neuroscience (IFIBYNE), University of Buenos Aires (UBA)-National Scientific and Technical Research Council (CONICET), Department of Physiology, Molecular, and Cell Biology, School of Exact and Natural Sciences (FCEN),
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46
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The transport and mediation mechanisms of the common sugars in Escherichia coli. Biotechnol Adv 2014; 32:905-19. [DOI: 10.1016/j.biotechadv.2014.04.009] [Citation(s) in RCA: 62] [Impact Index Per Article: 6.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2013] [Revised: 03/23/2014] [Accepted: 04/18/2014] [Indexed: 11/17/2022]
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47
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Housden BE, Perrimon N. Spatial and temporal organization of signaling pathways. Trends Biochem Sci 2014; 39:457-64. [PMID: 25155749 DOI: 10.1016/j.tibs.2014.07.008] [Citation(s) in RCA: 41] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2014] [Revised: 07/23/2014] [Accepted: 07/24/2014] [Indexed: 12/14/2022]
Abstract
The development and maintenance of the many different cell types in metazoan organisms requires robust and diverse intercellular communication mechanisms. Relatively few such signaling pathways have been identified, leading to the question of how such a broad diversity of output is generated from relatively simple signals. Recent studies have revealed complex mechanisms integrating temporal and spatial information to generate diversity in signaling pathway output. We review some general principles of signaling pathways, focusing on transcriptional outputs in Drosophila. We consider the role of spatial and temporal aspects of different transduction pathways and then discuss how recently developed tools and approaches are helping to dissect the complex mechanisms linking pathway stimulation to output.
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Affiliation(s)
| | - Norbert Perrimon
- Department of Genetics, Harvard Medical School, Boston, MA 02115, USA; Howard Hughes Medical Institute, Harvard Medical School, Boston, MA 02115, USA.
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48
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Zhang Y, Smolen P, Baxter DA, Byrne JH. Computational analyses of synergism in small molecular network motifs. PLoS Comput Biol 2014; 10:e1003524. [PMID: 24651495 PMCID: PMC3961176 DOI: 10.1371/journal.pcbi.1003524] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2013] [Accepted: 02/06/2014] [Indexed: 12/21/2022] Open
Abstract
Cellular functions and responses to stimuli are controlled by complex regulatory networks that comprise a large diversity of molecular components and their interactions. However, achieving an intuitive understanding of the dynamical properties and responses to stimuli of these networks is hampered by their large scale and complexity. To address this issue, analyses of regulatory networks often focus on reduced models that depict distinct, reoccurring connectivity patterns referred to as motifs. Previous modeling studies have begun to characterize the dynamics of small motifs, and to describe ways in which variations in parameters affect their responses to stimuli. The present study investigates how variations in pairs of parameters affect responses in a series of ten common network motifs, identifying concurrent variations that act synergistically (or antagonistically) to alter the responses of the motifs to stimuli. Synergism (or antagonism) was quantified using degrees of nonlinear blending and additive synergism. Simulations identified concurrent variations that maximized synergism, and examined the ways in which it was affected by stimulus protocols and the architecture of a motif. Only a subset of architectures exhibited synergism following paired changes in parameters. The approach was then applied to a model describing interlocked feedback loops governing the synthesis of the CREB1 and CREB2 transcription factors. The effects of motifs on synergism for this biologically realistic model were consistent with those for the abstract models of single motifs. These results have implications for the rational design of combination drug therapies with the potential for synergistic interactions. Cellular responses to stimuli are controlled by complex regulatory networks that comprise many molecular components. Understanding such networks is critical for understanding normal cellular functions and pathological conditions. Because the complexity of these networks often precludes intuitive insights, a useful approach is to study mathematical models of small network motifs having reduced complexity yet consisting of key regulatory components of the more complex networks. Computational studies have analyzed the behavior of small motifs, and have begun to describe the ways in which variations in parameters affect their functional properties. Here, we investigated how variations in pairs of parameters act synergistically (or antagonistically) to alter responses of ten common network motifs. Simulations identified parameter variations that maximized synergism, and examined the ways in which synergism was affected by stimulus protocols and motif architecture. The results have implications for the rational design of combination drug therapies where a goal is to identify drugs that when administered together have a greater effect than would be predicted by simple addition of single-drug effects (i.e., super-additive effects), thereby allowing for lower drug doses, minimizing undesirable effects.
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Affiliation(s)
- Yili Zhang
- Department of Neurobiology and Anatomy, The University of Texas Medical School at Houston, Houston, Texas, United States of America
| | - Paul Smolen
- Department of Neurobiology and Anatomy, The University of Texas Medical School at Houston, Houston, Texas, United States of America
| | - Douglas A. Baxter
- Department of Neurobiology and Anatomy, The University of Texas Medical School at Houston, Houston, Texas, United States of America
| | - John H. Byrne
- Department of Neurobiology and Anatomy, The University of Texas Medical School at Houston, Houston, Texas, United States of America
- * E-mail:
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49
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Roquet N, Lu TK. Digital and analog gene circuits for biotechnology. Biotechnol J 2014; 9:597-608. [PMID: 24677719 DOI: 10.1002/biot.201300258] [Citation(s) in RCA: 32] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2013] [Revised: 12/05/2013] [Accepted: 01/08/2014] [Indexed: 11/08/2022]
Abstract
Biotechnology offers the promise of valuable chemical production via microbial processing of renewable and inexpensive substrates. Thus far, static metabolic engineering strategies have enabled this field to advance industrial applications. However, the industrial scaling of statically engineered microbes inevitably creates inefficiencies due to variable conditions present in large-scale microbial cultures. Synthetic gene circuits that dynamically sense and regulate different molecules can resolve this issue by enabling cells to continuously adapt to variable conditions. These circuits also have the potential to enable next-generation production programs capable of autonomous transitioning between steps in a bioprocess. Here, we review the design and application of two main classes of dynamic gene circuits, digital and analog, for biotechnology. Within the context of these classes, we also discuss the potential benefits of digital-analog interconversion, memory, and multi-signal integration. Though synthetic gene circuits have largely been applied for cellular computation to date, we envision that utilizing them in biotechnology will enhance the efficiency and scope of biochemical production with living cells.
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Affiliation(s)
- Nathaniel Roquet
- Synthetic Biology Group, Research Lab of Electronics, Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA, USA; Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA; Harvard Biophysics Program, Boston, MA, USA
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50
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Information transfer by leaky, heterogeneous, protein kinase signaling systems. Proc Natl Acad Sci U S A 2014; 111:E326-33. [PMID: 24395805 DOI: 10.1073/pnas.1314446111] [Citation(s) in RCA: 86] [Impact Index Per Article: 8.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Abstract
Cells must sense extracellular signals and transfer the information contained about their environment reliably to make appropriate decisions. To perform these tasks, cells use signal transduction networks that are subject to various sources of noise. Here, we study the effects on information transfer of two particular types of noise: basal (leaky) network activity and cell-to-cell variability in the componentry of the network. Basal activity is the propensity for activation of the network output in the absence of the signal of interest. We show, using theoretical models of protein kinase signaling, that the combined effect of the two types of noise makes information transfer by such networks highly vulnerable to the loss of negative feedback. In an experimental study of ERK signaling by single cells with heterogeneous ERK expression levels, we verify our theoretical prediction: In the presence of basal network activity, negative feedback substantially increases information transfer to the nucleus by both preventing a near-flat average response curve and reducing sensitivity to variation in substrate expression levels. The interplay between basal network activity, heterogeneity in network componentry, and feedback is thus critical for the effectiveness of protein kinase signaling. Basal activity is widespread in signaling systems under physiological conditions, has phenotypic consequences, and is often raised in disease. Our results reveal an important role for negative feedback mechanisms in protecting the information transfer function of saturable, heterogeneous cell signaling systems from basal activity.
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