1
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Liu MQ, Guo Y, Wu C, Gao CX, Liu F, Hui CY. Visual arsenic detection in environmental waters: Innovating with a naked-eye biosensor for universal application. JOURNAL OF HAZARDOUS MATERIALS 2024; 477:135398. [PMID: 39096639 DOI: 10.1016/j.jhazmat.2024.135398] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/28/2024] [Revised: 07/27/2024] [Accepted: 07/31/2024] [Indexed: 08/05/2024]
Abstract
Arsenic contamination in environmental water sources poses a significant threat to human health, necessitating the development of sensitive and accessible detection methods. This study presents a multidimensional optimization of a bacterial biosensor for the susceptible and deoxyviolacein (DV)-based visual detection of arsenic. The research involved screening six different arsenic resistance (ars) operons and optimizing the genetic circuit to minimize background noise. Introducing an arsenic-specific transport channel enhanced the sensor's sensitivity to 1 nM with a quantitative range from 0.036 to 1.171 μM. The pigment-based biosensor offers a simple colorimetric approach for arsenic detection without complex instrumentation. The preferred biosensor demonstrated characteristics of anti-chelating agent interference, consistently quantified As(III) concentrations ranging from 0.036 to 1.171 μM covering the World Health Organization (WHO) drinking water limit. Innovatively, it effectively detects arsenic in seawater within a linear regression range of 0.071 to 1.125 μM. The biosensor's selectivity for arsenic was confirmed, with minimal cross-response to group 15 metals. Our naked-eye biosensor offers a novel approach for the rapid, on-site detection of arsenic in various water sources. Its simplicity, cost-effectiveness, and versatility make it a valuable tool for environmental monitoring and public health initiatives.
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Affiliation(s)
- Ming-Qi Liu
- School of Public Health, Guangdong Medical University, Dongguan 523808, China
| | - Yan Guo
- Shenzhen Prevention and Treatment Center for Occupational Diseases, 2019 Buxin Road, Shenzhen 518020, China
| | - Can Wu
- Department of Environmental Health, School of Public Health, Southern Medical University, Guangzhou 510515, China
| | - Chao-Xian Gao
- Shenzhen Prevention and Treatment Center for Occupational Diseases, 2019 Buxin Road, Shenzhen 518020, China
| | - Fen Liu
- Shenzhen Prevention and Treatment Center for Occupational Diseases, 2019 Buxin Road, Shenzhen 518020, China
| | - Chang-Ye Hui
- Shenzhen Prevention and Treatment Center for Occupational Diseases, 2019 Buxin Road, Shenzhen 518020, China.
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2
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Chauhan V, Baptista ISC, Arsh AM, Jagadeesan R, Dash S, Ribeiro AS. Transcription Attenuation in Synthetic Promoters in Nonoverlapping Tandem Formation. Biochemistry 2024; 63:2009-2022. [PMID: 38997112 PMCID: PMC11339919 DOI: 10.1021/acs.biochem.4c00012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2024] [Revised: 07/01/2024] [Accepted: 07/01/2024] [Indexed: 07/14/2024]
Abstract
Closely spaced promoters are ubiquitous in prokaryotic and eukaryotic genomes. How their structure and dynamics relate remains unclear, particularly for tandem formations. To study their transcriptional interference, we engineered two pairs and one trio of synthetic promoters in nonoverlapping, tandem formation, in single-copy plasmids transformed into Escherichia coli cells. From in vivo measurements, we found that these promoters in tandem formation can have attenuated transcription rates. The attenuation strength can be widely fine-tuned by the promoters' positioning, natural regulatory mechanisms, and other factors, including the antibiotic rifampicin, which is known to hamper RNAP promoter escape. From this, and supported by in silico models, we concluded that the attenuation in these constructs emerges from premature terminations generated by collisions between RNAPs elongating from upstream promoters and RNAPs occupying downstream promoters. Moreover, we found that these collisions can cause one or both RNAPs to falloff. Finally, the broad spectrum of possible, externally regulated, attenuation strengths observed in our synthetic tandem promoters suggests that they could become useful as externally controllable regulators of future synthetic circuits.
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Affiliation(s)
- Vatsala Chauhan
- Faculty
of Medicine and Health Technology, Tampere
University, 33520 Tampere, Finland
- Department
of Cell and Molecular Biology (ICM), Uppsala
University, 751 24 Uppsala, Sweden
| | - Ines S. C. Baptista
- Faculty
of Medicine and Health Technology, Tampere
University, 33520 Tampere, Finland
| | - Amir M. Arsh
- Faculty
of Medicine and Health Technology, Tampere
University, 33520 Tampere, Finland
| | - Rahul Jagadeesan
- Faculty
of Medicine and Health Technology, Tampere
University, 33520 Tampere, Finland
| | - Suchintak Dash
- Faculty
of Medicine and Health Technology, Tampere
University, 33520 Tampere, Finland
| | - Andre S. Ribeiro
- Faculty
of Medicine and Health Technology, Tampere
University, 33520 Tampere, Finland
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3
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Örn OE, Hagman A, Ismail M, Leiva Eriksson N, Hatti-Kaul R. Enhancing metabolic efficiency via novel constitutive promoters to produce protocatechuic acid in Escherichia coli. Appl Microbiol Biotechnol 2024; 108:442. [PMID: 39153079 PMCID: PMC11330383 DOI: 10.1007/s00253-024-13256-6] [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: 10/31/2023] [Revised: 05/27/2024] [Accepted: 07/15/2024] [Indexed: 08/19/2024]
Abstract
The antioxidant molecule protocatechuic acid (PCA) can also serve as a precursor for polymer building blocks. PCA can be produced in Escherichia coli overexpressing 3-dehydroshikimate dehydratase (DSD), an enzyme that catalyses the transformation of 3-dehydroshikimate to PCA. Nevertheless, optimizing the expression rate of recombinant enzymes is a key factor in metabolic engineering when producing biobased chemicals. In this study, a degenerate synthetic promoter approach was investigated to improve further the production of PCA. By limited screening of a randomized promoter library made using pSEVA221 plasmid in E. coli, three novel synthetic constitutive promoters were selected that increased the PCA yield from glucose by 10-21% compared to the inducible T7-promoter. RT-qPCR analysis showed that the DSD gene, regulated by the synthetic promoters, had high expression during the exponential phase, albeit the gene expression level dropped 250-fold during stationary phase. Besides the increased product yield, the synthetic promoters avoided the need for a costly inducer for gene expression. Screening of the entire promoter library is likely to provide more positive hits. The study also shows that E. coli transformed with the DSD gene on either pSEVA221 or pCDFDuet plasmids exhibit background PCA levels (~ 0.04 g/L) in the absence of a transcriptional regulatory element. KEY POINTS: • Degenerate synthetic promoters are remarkable tools to produce protocatechuic acid. • The constitutive synthetic promoters did not affect the growth rate of the bacterial host. • The use of constitutive synthetic promoters avoids the need for the costly inducer.
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Affiliation(s)
- Oliver Englund Örn
- Division of Biotechnology, Department of Chemistry, Center for Chemistry & Chemical Engineering, Lund University, Box 124, 221 00, Lund, Sweden
| | - Arne Hagman
- Division of Biotechnology, Department of Chemistry, Center for Chemistry & Chemical Engineering, Lund University, Box 124, 221 00, Lund, Sweden
| | - Mohamed Ismail
- Division of Biotechnology, Department of Chemistry, Center for Chemistry & Chemical Engineering, Lund University, Box 124, 221 00, Lund, Sweden
| | - Nélida Leiva Eriksson
- Division of Biotechnology, Department of Chemistry, Center for Chemistry & Chemical Engineering, Lund University, Box 124, 221 00, Lund, Sweden.
| | - Rajni Hatti-Kaul
- Division of Biotechnology, Department of Chemistry, Center for Chemistry & Chemical Engineering, Lund University, Box 124, 221 00, Lund, Sweden.
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4
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van der Sijs A, Visser T, Moerman P, Folkers G, Kegel W. Broccoli aptamer allows quantitative transcription regulation studies in vitro. PLoS One 2024; 19:e0304677. [PMID: 38870160 PMCID: PMC11175446 DOI: 10.1371/journal.pone.0304677] [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: 02/16/2024] [Accepted: 05/15/2024] [Indexed: 06/15/2024] Open
Abstract
Quantitative transcription regulation studies in vivo and in vitro often make use of reporter proteins. Here we show that using Broccoli aptamers, quantitative study of transcription in various regulatory scenarios is possible without a translational step. To explore the method we studied several regulatory scenarios that we analyzed using thermodynamic occupancy-based models, and found excellent agreement with previous studies. In the next step we show that non-coding DNA can have a dramatic effect on the level of transcription, similar to the influence of the lac repressor with a strong affinity to operator sites. Finally, we point out the limitations of the method in terms of delay times coupled to the folding of the aptamer. We conclude that the Broccoli aptamer is suitable for quantitative transcription measurements.
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Affiliation(s)
- Amanda van der Sijs
- Van ’t Hoff Laboratory for Physical and Colloidal Chemistry, Debye Institute for Nanomaterials Science, Utrecht University, Utrecht, The Netherlands
| | - Thomas Visser
- Van ’t Hoff Laboratory for Physical and Colloidal Chemistry, Debye Institute for Nanomaterials Science, Utrecht University, Utrecht, The Netherlands
| | - Pepijn Moerman
- Self-Organizing Soft Matter, Chemical Engineering and Chemistry, Eindhoven University of Technology, Eindhoven, The Netherlands
| | - Gert Folkers
- Utrecht NMR Group, Bijvoet Centre fo Biomolecular Research, Utrecht University, Utrecht, The Netherlands
| | - Willem Kegel
- Van ’t Hoff Laboratory for Physical and Colloidal Chemistry, Debye Institute for Nanomaterials Science, Utrecht University, Utrecht, The Netherlands
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5
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Pan RW, Röschinger T, Faizi K, Garcia H, Phillips R. Deciphering regulatory architectures from synthetic single-cell expression patterns. ARXIV 2024:arXiv:2401.15880v2. [PMID: 38351929 PMCID: PMC10862939] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Figures] [Subscribe] [Scholar Register] [Indexed: 02/19/2024]
Abstract
For the vast majority of genes in sequenced genomes, there is limited understanding of how they are regulated. Without such knowledge, it is not possible to perform a quantitative theory-experiment dialogue on how such genes give rise to physiological and evolutionary adaptation. One category of high-throughput experiments used to understand the sequence-phenotype relationship of the transcriptome is massively parallel reporter assays (MPRAs). However, to improve the versatility and scalability of MPRA pipelines, we need a "theory of the experiment" to help us better understand the impact of various biological and experimental parameters on the interpretation of experimental data. These parameters include binding site copy number, where a large number of specific binding sites may titrate away transcription factors, as well as the presence of overlapping binding sites, which may affect analysis of the degree of mutual dependence between mutations in the regulatory region and expression levels. To that end, in this paper we create tens of thousands of synthetic single-cell gene expression outputs using both equilibrium and out-of-equilibrium models. These models make it possible to imitate the summary statistics (information footprints and expression shift matrices) used to characterize the output of MPRAs and from this summary statistic to infer the underlying regulatory architecture. Specifically, we use a more refined implementation of the so-called thermodynamic models in which the binding energies of each sequence variant are derived from energy matrices. Our simulations reveal important effects of the parameters on MPRA data and we demonstrate our ability to optimize MPRA experimental designs with the goal of generating thermodynamic models of the transcriptome with base-pair specificity. Further, this approach makes it possible to carefully examine the mapping between mutations in binding sites and their corresponding expression profiles, a tool useful not only for better designing MPRAs, but also for exploring regulatory evolution.
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Affiliation(s)
- Rosalind Wenshan Pan
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA
| | - Tom Röschinger
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA
| | - Kian Faizi
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA
| | - Hernan Garcia
- Biophysics Graduate Group, University of California, Berkeley, CA
- Department of Physics, University of California, Berkeley, CA
- Department of Molecular and Cell Biology, University of California, Berkeley, CA
- Institute for Quantitative Biosciences-QB3, University of California, Berkeley, CA
| | - Rob Phillips
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA
- Department of Physics, California Institute of Technology, Pasadena, CA
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6
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Pan RW, Röschinger T, Faizi K, Garcia H, Phillips R. Deciphering regulatory architectures from synthetic single-cell expression patterns. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.01.28.577658. [PMID: 38352569 PMCID: PMC10862715 DOI: 10.1101/2024.01.28.577658] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 02/22/2024]
Abstract
For the vast majority of genes in sequenced genomes, there is limited understanding of how they are regulated. Without such knowledge, it is not possible to perform a quantitative theory-experiment dialogue on how such genes give rise to physiological and evolutionary adaptation. One category of high-throughput experiments used to understand the sequence-phenotype relationship of the transcriptome is massively parallel reporter assays (MPRAs). However, to improve the versatility and scalability of MPRA pipelines, we need a "theory of the experiment" to help us better understand the impact of various biological and experimental parameters on the interpretation of experimental data. These parameters include binding site copy number, where a large number of specific binding sites may titrate away transcription factors, as well as the presence of overlapping binding sites, which may affect analysis of the degree of mutual dependence between mutations in the regulatory region and expression levels. To that end, in this paper we create tens of thousands of synthetic single-cell gene expression outputs using both equilibrium and out-of-equilibrium models. These models make it possible to imitate the summary statistics (information footprints and expression shift matrices) used to characterize the output of MPRAs and from this summary statistic to infer the underlying regulatory architecture. Specifically, we use a more refined implementation of the so-called thermodynamic models in which the binding energies of each sequence variant are derived from energy matrices. Our simulations reveal important effects of the parameters on MPRA data and we demonstrate our ability to optimize MPRA experimental designs with the goal of generating thermodynamic models of the transcriptome with base-pair specificity. Further, this approach makes it possible to carefully examine the mapping between mutations in binding sites and their corresponding expression profiles, a tool useful not only for better designing MPRAs, but also for exploring regulatory evolution.
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Affiliation(s)
- Rosalind Wenshan Pan
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA
| | - Tom Röschinger
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA
| | - Kian Faizi
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA
| | - Hernan Garcia
- Biophysics Graduate Group, University of California, Berkeley, CA
- Department of Physics, University of California, Berkeley, CA
- Department of Molecular and Cell Biology, University of California, Berkeley, CA
- Institute for Quantitative Biosciences-QB3, University of California, Berkeley, CA
| | - Rob Phillips
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA
- Department of Physics, California Institute of Technology, Pasadena, CA
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7
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Lally P, Gómez-Romero L, Tierrafría VH, Aquino P, Rioualen C, Zhang X, Kim S, Baniulyte G, Plitnick J, Smith C, Babu M, Collado-Vides J, Wade JT, Galagan JE. Predictive Biophysical Neural Network Modeling of a Compendium of in vivo Transcription Factor DNA Binding Profiles for Escherichia coli. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.05.23.594371. [PMID: 38826350 PMCID: PMC11142182 DOI: 10.1101/2024.05.23.594371] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/04/2024]
Abstract
The DNA binding of most Escherichia coli Transcription Factors (TFs) has not been comprehensively mapped, and few have models that can quantitatively predict binding affinity. We report the global mapping of in vivo DNA binding for 139 E. coli TFs using ChIP-Seq. We used these data to train BoltzNet, a novel neural network that predicts TF binding energy from DNA sequence. BoltzNet mirrors a quantitative biophysical model and provides directly interpretable predictions genome-wide at nucleotide resolution. We used BoltzNet to quantitatively design novel binding sites, which we validated with biophysical experiments on purified protein. We have generated models for 125 TFs that provide insight into global features of TF binding, including clustering of sites, the role of accessory bases, the relevance of weak sites, and the background affinity of the genome. Our paper provides new paradigms for studying TF-DNA binding and for the development of biophysically motivated neural networks.
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Affiliation(s)
- Patrick Lally
- Department of Biomedical Engineering, Boston University, 44 Cummington Mall, Boston, MA 02215
| | - Laura Gómez-Romero
- Instituto Nacional de Medicina Genómica, Periférico Sur 4809, Arenal Tepepan, Ciudad de México 14610, México
- Escuela de Medicina y Ciencias de la Salud, Tecnológico de Monterrey, Ciudad de México, México
| | - Víctor H. Tierrafría
- Department of Biomedical Engineering, Boston University, 44 Cummington Mall, Boston, MA 02215
- Centro de Ciencias Genómicas, Universidad Nacional Autónoma de México, Avenida Universidad s/n, Cuernavaca 62210, Morelos, México
| | - Patricia Aquino
- Department of Biomedical Engineering, Boston University, 44 Cummington Mall, Boston, MA 02215
| | - Claire Rioualen
- Centro de Ciencias Genómicas, Universidad Nacional Autónoma de México, Avenida Universidad s/n, Cuernavaca 62210, Morelos, México
| | - Xiaoman Zhang
- Department of Biomedical Engineering, Boston University, 44 Cummington Mall, Boston, MA 02215
| | - Sunyoung Kim
- Department of Biochemistry, University of Regina, Regina, Saskatchewan, SK S4S 0A2, Canada
| | | | - Jonathan Plitnick
- Wadsworth Center, New York State Department of Health, Albany, NY, USA
| | - Carol Smith
- Wadsworth Center, New York State Department of Health, Albany, NY, USA
| | - Mohan Babu
- Department of Biochemistry, University of Regina, Regina, Saskatchewan, SK S4S 0A2, Canada
| | - Julio Collado-Vides
- Department of Biomedical Engineering, Boston University, 44 Cummington Mall, Boston, MA 02215
- Centro de Ciencias Genómicas, Universidad Nacional Autónoma de México, Avenida Universidad s/n, Cuernavaca 62210, Morelos, México
- Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology, Dr. Aiguader 88, Barcelona 08003, Universitat Pompeu Fabra (UPF), Barcelona, Spain
| | - Joseph T. Wade
- Wadsworth Center, New York State Department of Health, Albany, NY, USA
- Department of Biomedical Sciences, University at Albany, SUNY, Albany, NY, USA
| | - James E. Galagan
- Department of Biomedical Engineering, Boston University, 44 Cummington Mall, Boston, MA 02215
- Bioinformatics Program, Boston University, 24 Cummington Mall, Boston, MA 02215
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8
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Liu Y, Wu Y, Wang L, Zhu L, Dong Y, Xu W. A ratiometric dual-fluorescent paper-based synthetic biosensor for visual detection of tetracycline on-site. JOURNAL OF HAZARDOUS MATERIALS 2024; 467:133647. [PMID: 38335608 DOI: 10.1016/j.jhazmat.2024.133647] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/08/2023] [Revised: 01/16/2024] [Accepted: 01/26/2024] [Indexed: 02/12/2024]
Abstract
The excessive use of tetracycline poses a threat to human health, making it essential to monitor and regulate its usage. While whole-cell biosensors offer a simple and cost-effective method, their utility is constrained by limitations in sensitivity, portability, and robustness, hindering real-time measurements within complex environmental contexts. In this study, a ratiometric i/cTetR synthetic biosensing test strip with an engineered modified dual-fluorescence reporting was developed for detecting Tet antibiotics in water and food. First, the standardized unidirectional promoter PtetR by tailoring and screening TetR transcription factor binding sites and verified by molecular docking, shortening the detection time. Secondly, decoupling the sensing and reporting modules enhances the biosensor's performance, eliminating genetic background leakage and tripling the output signal. Thirdly, a ratiometric dual fluorescence signal i/cTetR biosensing test strip was designed. Under the light box LED/UV light source, the dual signal output method significantly reduced false negative results and enhanced the anti-interference capability of the biosensor. The i/cTetR strips can detect Tet in tap water (5-1280 μg/mL) and milk (50-3200 μg/kg) within 45 min in high volume on-site without separation and purification. This study provides a standardized and universal sensing method for the field detection of antibiotic contaminants.
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Affiliation(s)
- Yanger Liu
- Key Laboratory of Veterinary Anatomy, College of Veterinary Medicine, China Agricultural University, Beijing, 100193, People's Republic of China; Food Laboratory of Zhongyuan, Key Laboratory of Precision Nutrition and Food Quality, Department of Nutrition and Health, China Agricultural University, Beijing, 100193, People's Republic of China
| | - Yifan Wu
- Food Laboratory of Zhongyuan, Key Laboratory of Precision Nutrition and Food Quality, Department of Nutrition and Health, China Agricultural University, Beijing, 100193, People's Republic of China
| | - Lei Wang
- Key Laboratory of Veterinary Anatomy, College of Veterinary Medicine, China Agricultural University, Beijing, 100193, People's Republic of China
| | - Longjiao Zhu
- Food Laboratory of Zhongyuan, Key Laboratory of Precision Nutrition and Food Quality, Department of Nutrition and Health, China Agricultural University, Beijing, 100193, People's Republic of China
| | - Yulan Dong
- Key Laboratory of Veterinary Anatomy, College of Veterinary Medicine, China Agricultural University, Beijing, 100193, People's Republic of China.
| | - Wentao Xu
- Key Laboratory of Veterinary Anatomy, College of Veterinary Medicine, China Agricultural University, Beijing, 100193, People's Republic of China; Food Laboratory of Zhongyuan, Key Laboratory of Precision Nutrition and Food Quality, Department of Nutrition and Health, China Agricultural University, Beijing, 100193, People's Republic of China.
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9
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Yang H, He Y, Zhou S, Deng Y. Dynamic regulation and cofactor engineering of escherichia coli to enhance production of glycolate from corn stover hydrolysate. BIORESOURCE TECHNOLOGY 2024; 398:130531. [PMID: 38447620 DOI: 10.1016/j.biortech.2024.130531] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/27/2023] [Revised: 02/24/2024] [Accepted: 03/03/2024] [Indexed: 03/08/2024]
Abstract
Glycolic acid is widely employed in chemical cleaning, the production of polyglycolic acid-lactic acid, and polyglycolic acid. Currently, the bottleneck of glycolate biosynthesis lies on the imbalance of metabolic flux and the deficiency of NADPH. In this study, a dynamic regulation system was developed and optimized to enhance the metabolic flux from glucose to glycolate. Additionally, the knockout of transhydrogenase (sthA), along with the overexpression of pyridine nucleotide transhydrogenase (pntAB) and the implementation of the Entner-Doudoroff pathway, were performed to further increase the production of the NADPH, thereby increasing the titer of glycolate to 5.6 g/L. To produce glycolate from corn stover hydrolysate, carbon catabolite repression was alleviated and glucose utilization was accelerated. The final strain, E. coli Mgly10-245, is inducer-free, achieving a glycolate titer of 46.1 g/L using corn stover hydrolysate (77.1 % of theoretical yield). These findings will contribute to the advancement of industrial glycolate production.
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Affiliation(s)
- Haining Yang
- National Engineering Research Center of Cereal Fermentation and Food Biomanufacturing, Jiangnan University, 1800 Lihu Road, Wuxi, Jiangsu 214122, China
| | - Yucai He
- State Key Laboratory of Biocatalysis and Enzyme Engineering, School of Life Sciences, Hubei University, China, 430062
| | - Shenghu Zhou
- National Engineering Research Center of Cereal Fermentation and Food Biomanufacturing, 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 Research Center of Cereal Fermentation and Food Biomanufacturing, 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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10
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Alba Burbano D, Cardiff RAL, Tickman BI, Kiattisewee C, Maranas CJ, Zalatan JG, Carothers JM. Engineering activatable promoters for scalable and multi-input CRISPRa/i circuits. Proc Natl Acad Sci U S A 2023; 120:e2220358120. [PMID: 37463216 PMCID: PMC10374173 DOI: 10.1073/pnas.2220358120] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2022] [Accepted: 06/13/2023] [Indexed: 07/20/2023] Open
Abstract
Dynamic, multi-input gene regulatory networks (GRNs) are ubiquitous in nature. Multilayer CRISPR-based genetic circuits hold great promise for building GRNs akin to those found in naturally occurring biological systems. We develop an approach for creating high-performing activatable promoters that can be assembled into deep, wide, and multi-input CRISPR-activation and -interference (CRISPRa/i) GRNs. By integrating sequence-based design and in vivo screening, we engineer activatable promoters that achieve up to 1,000-fold dynamic range in an Escherichia coli-based cell-free system. These components enable CRISPRa GRNs that are six layers deep and four branches wide. We show the generalizability of the promoter engineering workflow by improving the dynamic range of the light-dependent EL222 optogenetic system from 6-fold to 34-fold. Additionally, high dynamic range promoters enable CRISPRa systems mediated by small molecules and protein-protein interactions. We apply these tools to build input-responsive CRISPRa/i GRNs, including feedback loops, logic gates, multilayer cascades, and dynamic pulse modulators. Our work provides a generalizable approach for the design of high dynamic range activatable promoters and enables classes of gene regulatory functions in cell-free systems.
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Affiliation(s)
- Diego Alba Burbano
- Department of Chemical Engineering, University of Washington, Seattle, WA98195
- Center for Synthetic Biology, University of Washington, Seattle, WA98195
| | - Ryan A. L. Cardiff
- Center for Synthetic Biology, University of Washington, Seattle, WA98195
- Molecular Engineering & Sciences Institute, University of Washington, Seattle, WA98195
| | - Benjamin I. Tickman
- Center for Synthetic Biology, University of Washington, Seattle, WA98195
- Molecular Engineering & Sciences Institute, University of Washington, Seattle, WA98195
| | - Cholpisit Kiattisewee
- Center for Synthetic Biology, University of Washington, Seattle, WA98195
- Molecular Engineering & Sciences Institute, University of Washington, Seattle, WA98195
| | - Cassandra J. Maranas
- Center for Synthetic Biology, University of Washington, Seattle, WA98195
- Molecular Engineering & Sciences Institute, University of Washington, Seattle, WA98195
| | - Jesse G. Zalatan
- Center for Synthetic Biology, University of Washington, Seattle, WA98195
- Molecular Engineering & Sciences Institute, University of Washington, Seattle, WA98195
- Department of Chemistry, University of Washington, Seattle, WA98195
| | - James M. Carothers
- Department of Chemical Engineering, University of Washington, Seattle, WA98195
- Center for Synthetic Biology, University of Washington, Seattle, WA98195
- Molecular Engineering & Sciences Institute, University of Washington, Seattle, WA98195
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11
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Chen X, Chi J, Liu Y, Du R, Guo M, Xu W. Synthetic symbiotic bacteria reduces the toxicity of mercury ingested via contaminated food. Food Chem Toxicol 2023:113937. [PMID: 37433354 DOI: 10.1016/j.fct.2023.113937] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2023] [Revised: 06/22/2023] [Accepted: 07/07/2023] [Indexed: 07/13/2023]
Abstract
Mercury contamination in food poses a significant threat to human health. In this article, we propose a novel approach to solve this problem by enhancing the function of gut microbiota against mercury using a synthetically engineered bacterial strain. An engineered Escherichia coli biosensor MerR with mercury binding function was introduced into the intestines of mice for colonization, whereafter the mice were challenged with oral mercury. Compared with the control mice and mice colonized with unengineered Escherichia coli, the mice with biosensor MerR cells in their gut showed significantly stronger mercury resistance. Furthermore, mercury distribution analysis revealed that biosensor MerR cells promoted the excretion of oral mercury with feces, thereby blocking the entry of mercury into the mice, decreasing the concentration of mercury in the circulatory system and organs, and, thus, attenuating the toxicity of mercury to the liver, kidneys and intestines. Colonization with the biosensor MerR did not result in significant health problems in the mice, nor were genetic circuit mutations or lateral transfers identified during the experiments, thus demonstrating the safety of this approach. This study elucidates the remarkable promise of synthetic biology for modulating gut microbiota function.
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Affiliation(s)
- Xiaolin Chen
- School of Food and Health, Beijing Technology and Business University, Beijing, 100048, China
| | - Jiani Chi
- Key Laboratory of Precision Nutrition and Food Quality, Department of Nutrition and Health, China Agricultural University, Beijing, 100083, China
| | - Yanger Liu
- Key Laboratory of Precision Nutrition and Food Quality, Department of Nutrition and Health, China Agricultural University, Beijing, 100083, China
| | - Ruoxi Du
- Key Laboratory of Precision Nutrition and Food Quality, Department of Nutrition and Health, China Agricultural University, Beijing, 100083, China
| | - Mingzhang Guo
- School of Food and Health, Beijing Technology and Business University, Beijing, 100048, China; Key Laboratory of Precision Nutrition and Food Quality, Department of Nutrition and Health, China Agricultural University, Beijing, 100083, China.
| | - Wentao Xu
- Key Laboratory of Precision Nutrition and Food Quality, Department of Nutrition and Health, China Agricultural University, Beijing, 100083, China.
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12
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Mengiste AA, Wilson RH, Weissman RF, Papa III LJ, Hendel SJ, Moore CL, Butty VL, Shoulders MD. Expanded MutaT7 toolkit efficiently and simultaneously accesses all possible transition mutations in bacteria. Nucleic Acids Res 2023; 51:e31. [PMID: 36715334 PMCID: PMC10085711 DOI: 10.1093/nar/gkad003] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2022] [Revised: 11/16/2022] [Accepted: 01/03/2023] [Indexed: 01/31/2023] Open
Abstract
Targeted mutagenesis mediated by nucleotide base deaminase-T7 RNA polymerase fusions has recently emerged as a novel and broadly useful strategy to power genetic diversification in the context of in vivo directed evolution campaigns. Here, we expand the utility of this approach by introducing a highly active adenosine deaminase-T7 RNA polymerase fusion protein (eMutaT7A→G), resulting in higher mutation frequencies to enable more rapid directed evolution. We also assess the benefits and potential downsides of using this more active mutator. We go on to show in Escherichia coli that adenosine deaminase-bearing mutators (MutaT7A→G or eMutaT7A→G) can be employed in tandem with a cytidine deaminase-bearing mutator (MutaT7C→T) to introduce all possible transition mutations simultaneously. We illustrate the efficacy of this in vivo mutagenesis approach by exploring mutational routes to antibacterial drug resistance. This work sets the stage for general application of optimized MutaT7 tools able to induce all types of transition mutations during in vivo directed evolution campaigns across diverse organisms.
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Affiliation(s)
- Amanuella A Mengiste
- Department of Chemistry, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Robert H Wilson
- Department of Chemistry, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Rachel F Weissman
- Department of Chemistry, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Louis J Papa III
- Department of Chemistry, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Samuel J Hendel
- Department of Chemistry, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Christopher L Moore
- Department of Chemistry, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Vincent L Butty
- BioMicroCenter, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Matthew D Shoulders
- Department of Chemistry, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
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13
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Simas RG, Pessoa Junior A, Long PF. Mechanistic aspects of IPTG (isopropylthio-β-galactoside) transport across the cytoplasmic membrane of Escherichia coli-a rate limiting step in the induction of recombinant protein expression. J Ind Microbiol Biotechnol 2023; 50:kuad034. [PMID: 37849239 PMCID: PMC10639102 DOI: 10.1093/jimb/kuad034] [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: 05/20/2023] [Accepted: 10/16/2023] [Indexed: 10/19/2023]
Abstract
Coupling transcription of a cloned gene to the lac operon with induction by isopropylthio-β-galactoside (IPTG) has been a favoured approach for recombinant protein expression using Escherichia coli as a heterologous host for more than six decades. Despite a wealth of experimental data gleaned over this period, a quantitative relationship between extracellular IPTG concentration and consequent levels of recombinant protein expression remains surprisingly elusive across a broad spectrum of experimental conditions. This is because gene expression under lac operon regulation is tightly correlated with intracellular IPTG concentration due to allosteric regulation of the lac repressor protein (lacY). An in-silico mathematical model established that uptake of IPTG across the cytoplasmic membrane of E. coli by simple diffusion was negligible. Conversely, lacY mediated active transport was a rapid process, taking only some seconds for internal and external IPTG concentrations to equalize. Optimizing kcat and KM parameters by targeted mutation of the galactoside binding site in lacY could be a future strategy to improve the performance of recombinant protein expression. For example, if kcat were reduced whilst KM was increased, active transport of IPTG across the cytoplasmic membrane would be reduced, thereby lessening the metabolic burden on the cell and expediating accumulation of recombinant protein. The computational model described herein is made freely available and is amenable to optimize recombinant protein expression in other heterologous hosts. ONE-SENTENCE SUMMARY A computational model made freely available to optimize recombinant protein expression in Escherichia coli other heterologous hosts.
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Affiliation(s)
- Rodrigo G Simas
- Faculty of Life Sciences & Medicine, King's College London, 150 Stamford Street, London SE1 9NH, UK
- Faculdade de Ciências Farmacêuticas, Universidade de São Paulo, Av. Prof. Lineu Prestes, 580, B16, 05508-000 São Paulo, SP, Brazil
| | - Adalberto Pessoa Junior
- Faculty of Life Sciences & Medicine, King's College London, 150 Stamford Street, London SE1 9NH, UK
- Faculdade de Ciências Farmacêuticas, Universidade de São Paulo, Av. Prof. Lineu Prestes, 580, B16, 05508-000 São Paulo, SP, Brazil
| | - Paul F Long
- Faculty of Life Sciences & Medicine, King's College London, 150 Stamford Street, London SE1 9NH, UK
- Faculdade de Ciências Farmacêuticas, Universidade de São Paulo, Av. Prof. Lineu Prestes, 580, B16, 05508-000 São Paulo, SP, Brazil
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14
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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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15
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LaFleur TL, Hossain A, Salis HM. Automated model-predictive design of synthetic promoters to control transcriptional profiles in bacteria. Nat Commun 2022; 13:5159. [PMID: 36056029 PMCID: PMC9440211 DOI: 10.1038/s41467-022-32829-5] [Citation(s) in RCA: 55] [Impact Index Per Article: 27.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2022] [Accepted: 08/19/2022] [Indexed: 12/22/2022] Open
Abstract
Transcription rates are regulated by the interactions between RNA polymerase, sigma factor, and promoter DNA sequences in bacteria. However, it remains unclear how non-canonical sequence motifs collectively control transcription rates. Here, we combine massively parallel assays, biophysics, and machine learning to develop a 346-parameter model that predicts site-specific transcription initiation rates for any σ70 promoter sequence, validated across 22132 bacterial promoters with diverse sequences. We apply the model to predict genetic context effects, design σ70 promoters with desired transcription rates, and identify undesired promoters inside engineered genetic systems. The model provides a biophysical basis for understanding gene regulation in natural genetic systems and precise transcriptional control for engineering synthetic genetic systems.
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Affiliation(s)
- Travis L LaFleur
- Department of Chemical Engineering, Pennsylvania State University, University Park, PA, 16801, USA
| | - Ayaan Hossain
- Bioinformatics and Genomics, Pennsylvania State University, University Park, PA, 16801, USA
| | - Howard M Salis
- Department of Chemical Engineering, Pennsylvania State University, University Park, PA, 16801, USA.
- Bioinformatics and Genomics, Pennsylvania State University, University Park, PA, 16801, USA.
- Department of Biological Engineering, Pennsylvania State University, University Park, PA, 16801, USA.
- Department of Biomedical Engineering, Pennsylvania State University, University Park, PA, 16801, USA.
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16
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Zhang Q, Azarin SM, Sarkar CA. Model-guided engineering of DNA sequences with predictable site-specific recombination rates. Nat Commun 2022; 13:4152. [PMID: 35858965 PMCID: PMC9300676 DOI: 10.1038/s41467-022-31538-3] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2021] [Accepted: 06/22/2022] [Indexed: 11/09/2022] Open
Abstract
Site-specific recombination (SSR) is an important tool in synthetic biology, but its applications are limited by the inability to predictably tune SSR reaction rates. Facile rate manipulation could be achieved by modifying the DNA substrate sequence; however, this approach lacks rational design principles. Here, we develop an integrated experimental and computational method to engineer the DNA attachment sequence attP for predictably modulating the inversion reaction mediated by the recombinase Bxb1. After developing a qPCR method to measure SSR reaction rate, we design, select, and sequence attP libraries to inform a machine-learning model that computes Bxb1 inversion rate as a function of attP sequence. We use this model to predict reaction rates of attP variants in vitro and demonstrate their utility in gene circuit design in Escherichia coli. Our high-throughput, model-guided approach for rationally tuning SSR reaction rates enhances our understanding of recombinase function and expands the synthetic biology toolbox.
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Affiliation(s)
- Qiuge Zhang
- grid.17635.360000000419368657Department of Chemical Engineering and Materials Science, University of Minnesota, Minneapolis, MN 55455 USA
| | - Samira M. Azarin
- grid.17635.360000000419368657Department of Chemical Engineering and Materials Science, University of Minnesota, Minneapolis, MN 55455 USA
| | - Casim A. Sarkar
- grid.17635.360000000419368657Department of Biomedical Engineering, University of Minnesota, Minneapolis, MN 55455 USA
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17
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Gene regulation in Escherichia coli is commonly selected for both high plasticity and low noise. Nat Ecol Evol 2022; 6:1165-1179. [PMID: 35726087 DOI: 10.1038/s41559-022-01783-2] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2021] [Accepted: 05/03/2022] [Indexed: 11/08/2022]
Abstract
Bacteria often respond to dynamically changing environments by regulating gene expression. Despite this regulation being critically important for growth and survival, little is known about how selection shapes gene regulation in natural populations. To better understand the role natural selection plays in shaping bacterial gene regulation, here we compare differences in the regulatory behaviour of naturally segregating promoter variants from Escherichia coli (which have been subject to natural selection) to randomly mutated promoter variants (which have never been exposed to natural selection). We quantify gene expression phenotypes (expression level, plasticity and noise) for hundreds of promoter variants across multiple environments and show that segregating promoter variants are enriched for mutations with minimal effects on expression level. In many promoters, we infer that there is strong selection to maintain high levels of plasticity, and direct selection to decrease or increase cell-to-cell variability in expression. Taken together, these results expand our knowledge of how gene regulation is affected by natural selection and highlight the power of comparing naturally segregating polymorphisms to de novo random mutations to quantify the action of selection.
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18
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Parisutham V, Chhabra S, Ali MZ, Brewster RC. Tunable transcription factor library for robust quantification of regulatory properties in Escherichia coli. Mol Syst Biol 2022; 18:e10843. [PMID: 35694815 PMCID: PMC9189660 DOI: 10.15252/msb.202110843] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2021] [Revised: 05/11/2022] [Accepted: 05/13/2022] [Indexed: 11/12/2022] Open
Abstract
Predicting the quantitative regulatory function of transcription factors (TFs) based on factors such as binding sequence, binding location, and promoter type is not possible. The interconnected nature of gene networks and the difficulty in tuning individual TF concentrations make the isolated study of TF function challenging. Here, we present a library of Escherichia coli strains designed to allow for precise control of the concentration of individual TFs enabling the study of the role of TF concentration on physiology and regulation. We demonstrate the usefulness of this resource by measuring the regulatory function of the zinc-responsive TF, ZntR, and the paralogous TF pair, GalR/GalS. For ZntR, we find that zinc alters ZntR regulatory function in a way that enables activation of the regulated gene to be robust with respect to ZntR concentration. For GalR and GalS, we are able to demonstrate that these paralogous TFs have fundamentally distinct regulatory roles beyond differences in binding affinity.
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Affiliation(s)
- Vinuselvi Parisutham
- Department of Systems BiologyUniversity of Massachusetts Chan Medical SchoolWorcesterMAUSA
| | - Shivani Chhabra
- Department of Pharmacological SciencesIcahn School of Medicine at Mount SinaiNew YorkNYUSA
| | - Md Zulfikar Ali
- Department of Systems BiologyUniversity of Massachusetts Chan Medical SchoolWorcesterMAUSA
| | - Robert C Brewster
- Department of Systems BiologyUniversity of Massachusetts Chan Medical SchoolWorcesterMAUSA
- Department of Microbiology and Physiological SystemsUniversity of Massachusetts Chan Medical SchoolWorcesterMAUSA
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19
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Baptista ISC, Kandavalli V, Chauhan V, Bahrudeen MNM, Almeida BLB, Palma CSD, Dash S, Ribeiro AS. Sequence-dependent model of genes with dual σ factor preference. BIOCHIMICA ET BIOPHYSICA ACTA. GENE REGULATORY MECHANISMS 2022; 1865:194812. [PMID: 35338024 DOI: 10.1016/j.bbagrm.2022.194812] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/02/2021] [Revised: 03/08/2022] [Accepted: 03/16/2022] [Indexed: 10/18/2022]
Abstract
Escherichia coli uses σ factors to quickly control large gene cohorts during stress conditions. While most of its genes respond to a single σ factor, approximately 5% of them have dual σ factor preference. The most common are those responsive to both σ70, which controls housekeeping genes, and σ38, which activates genes during stationary growth and stresses. Using RNA-seq and flow-cytometry measurements, we show that 'σ70+38 genes' are nearly as upregulated in stationary growth as 'σ38 genes'. Moreover, we find a clear quantitative relationship between their promoter sequence and their response strength to changes in σ38 levels. We then propose and validate a sequence dependent model of σ70+38 genes, with dual sensitivity to σ38 and σ70, that is applicable in the exponential and stationary growth phases, as well in the transient period in between. We further propose a general model, applicable to other stresses and σ factor combinations. Given this, promoters controlling σ70+38 genes (and variants) could become important building blocks of synthetic circuits with predictable, sequence-dependent sensitivity to transitions between the exponential and stationary growth phases.
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Affiliation(s)
- Ines S C Baptista
- Laboratory of Biosystem Dynamics, Faculty of Medicine and Health Technology, Tampere University, Tampere 33520, Finland
| | - Vinodh Kandavalli
- Laboratory of Biosystem Dynamics, Faculty of Medicine and Health Technology, Tampere University, Tampere 33520, Finland; Department of Cell and Molecular Biology, Uppsala University, Uppsala 752 37, Sweden
| | - Vatsala Chauhan
- Laboratory of Biosystem Dynamics, Faculty of Medicine and Health Technology, Tampere University, Tampere 33520, Finland
| | - Mohamed N M Bahrudeen
- Laboratory of Biosystem Dynamics, Faculty of Medicine and Health Technology, Tampere University, Tampere 33520, Finland
| | - Bilena L B Almeida
- Laboratory of Biosystem Dynamics, Faculty of Medicine and Health Technology, Tampere University, Tampere 33520, Finland
| | - Cristina S D Palma
- Laboratory of Biosystem Dynamics, Faculty of Medicine and Health Technology, Tampere University, Tampere 33520, Finland
| | - Suchintak Dash
- Laboratory of Biosystem Dynamics, Faculty of Medicine and Health Technology, Tampere University, Tampere 33520, Finland
| | - Andre S Ribeiro
- Laboratory of Biosystem Dynamics, Faculty of Medicine and Health Technology, Tampere University, Tampere 33520, Finland; Center of Technology and Systems (CTS-Uninova), NOVA University of Lisbon, 2829-516 Monte de Caparica, Portugal.
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20
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Development of highly characterized genetic bioparts for efficient gene expression in CO2-fixing Eubacterium limosum. Metab Eng 2022; 72:215-226. [DOI: 10.1016/j.ymben.2022.03.016] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2022] [Revised: 03/20/2022] [Accepted: 03/26/2022] [Indexed: 12/22/2022]
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21
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Armetta J, Schantz-Klausen M, Shepelin D, Vazquez-Uribe R, Bahl MI, Laursen MF, Licht TR, Sommer MO. Escherichia coli Promoters with Consistent Expression throughout the Murine Gut. ACS Synth Biol 2021; 10:3359-3368. [PMID: 34842418 DOI: 10.1021/acssynbio.1c00325] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/26/2022]
Abstract
Advanced microbial therapeutics have great potential as a novel modality to diagnose and treat a wide range of diseases. Yet, to realize this potential, robust parts for regulating gene expression and consequent therapeutic activity in situ are needed. In this study, we characterized the expression level of more than 8000 variants of the Escherichia coli sigma factor 70 (σ70) promoter in a range of different environmental conditions and growth states using fluorescence-activated cell sorting and deep sequencing. Sampled conditions include aerobic and anaerobic culture in the laboratory as well as growth in several locations of the murine gastrointestinal tract. We found that σ70 promoters in E. coli generally maintain consistent expression levels across the murine gut (R2: 0.55-0.85, p value < 1 × 10-5), suggesting a limited environmental influence but a higher variability between in vitro and in vivo expression levels, highlighting the challenges of translating in vitro promoter activity to in vivo applications. Based on these data, we design the Schantzetta library, composed of eight promoters spanning a wide expression range and displaying a high degree of robustness in both laboratory and in vivo conditions (R2 = 0.98, p = 0.000827). This study provides a systematic assessment of the σ70 promoter activity in E. coli as it transits the murine gut leading to the definition of robust expression cassettes that could be a valuable tool for reliable engineering and development of advanced microbial therapeutics.
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Affiliation(s)
- Jeremy Armetta
- Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, DK-2800 Lyngby, Denmark
| | - Michael Schantz-Klausen
- Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, DK-2800 Lyngby, Denmark
| | - Denis Shepelin
- Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, DK-2800 Lyngby, Denmark
| | - Ruben Vazquez-Uribe
- Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, DK-2800 Lyngby, Denmark
| | - Martin Iain Bahl
- National Food Institute, Technical University of Denmark, DK-2800 Lyngby, Denmark
| | | | - Tine Rask Licht
- National Food Institute, Technical University of Denmark, DK-2800 Lyngby, Denmark
| | - Morten O.A. Sommer
- Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, DK-2800 Lyngby, Denmark
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22
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Wang Q, Lin J. Heterogeneous recruitment abilities to RNA polymerases generate nonlinear scaling of gene expression with cell volume. Nat Commun 2021; 12:6852. [PMID: 34824198 PMCID: PMC8617254 DOI: 10.1038/s41467-021-26952-y] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2021] [Accepted: 10/27/2021] [Indexed: 11/09/2022] Open
Abstract
While most genes' expression levels are proportional to cell volumes, some genes exhibit nonlinear scaling between their expression levels and cell volume. Therefore, their mRNA and protein concentrations change as the cell volume increases, which often have crucial biological functions such as cell-cycle regulation. However, the biophysical mechanism underlying the nonlinear scaling between gene expression and cell volume is still unclear. In this work, we show that the nonlinear scaling is a direct consequence of the heterogeneous recruitment abilities of promoters to RNA polymerases based on a gene expression model at the whole-cell level. Those genes with weaker (stronger) recruitment abilities than the average ability spontaneously exhibit superlinear (sublinear) scaling with cell volume. Analysis of the promoter sequences and the nonlinear scaling of Saccharomyces cerevisiae's mRNA levels shows that motifs associated with transcription regulation are indeed enriched in genes exhibiting nonlinear scaling, in concert with our model.
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Affiliation(s)
- Qirun Wang
- Center for Quantitative Biology, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, 100871, China
| | - Jie Lin
- Center for Quantitative Biology, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, 100871, China.
- Peking-Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, 100871, China.
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23
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Ropers D, Couté Y, Faure L, Ferré S, Labourdette D, Shabani A, Trouilh L, Vasseur P, Corre G, Ferro M, Teste MA, Geiselmann J, de Jong H. Multiomics Study of Bacterial Growth Arrest in a Synthetic Biology Application. ACS Synth Biol 2021; 10:2910-2926. [PMID: 34739215 DOI: 10.1021/acssynbio.1c00115] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
We investigated the scalability of a previously developed growth switch based on external control of RNA polymerase expression. Our results indicate that, in liter-scale bioreactors operating in fed-batch mode, growth-arrested Escherichia coli cells are able to convert glucose to glycerol at an increased yield. A multiomics quantification of the physiology of the cells shows that, apart from acetate production, few metabolic side effects occur. However, a number of specific responses to growth slow-down and growth arrest are launched at the transcriptional level. These notably include the downregulation of genes involved in growth-associated processes, such as amino acid and nucleotide metabolism and translation. Interestingly, the transcriptional responses are buffered at the proteome level, probably due to the strong decrease of the total mRNA concentration after the diminution of transcriptional activity and the absence of growth dilution of proteins. Growth arrest thus reduces the opportunities for dynamically adjusting the proteome composition, which poses constraints on the design of biotechnological production processes but may also avoid the initiation of deleterious stress responses.
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Affiliation(s)
| | - Yohann Couté
- Université Grenoble Alpes, INSERM, CEA, UMR BioSanté U1292, CNRS, CEA, FR2048, 38000 Grenoble, France
| | | | - Sabrina Ferré
- Université Grenoble Alpes, INSERM, CEA, UMR BioSanté U1292, CNRS, CEA, FR2048, 38000 Grenoble, France
| | - Delphine Labourdette
- GeT-Biopuces, TBI, Université de Toulouse, CNRS, INRAE, INSA, 31077 Toulouse, France
| | - Arieta Shabani
- Université Grenoble Alpes, Inria, 38000 Grenoble, France
| | - Lidwine Trouilh
- GeT-Biopuces, TBI, Université de Toulouse, CNRS, INRAE, INSA, 31077 Toulouse, France
| | | | | | - Myriam Ferro
- Université Grenoble Alpes, INSERM, CEA, UMR BioSanté U1292, CNRS, CEA, FR2048, 38000 Grenoble, France
| | - Marie-Ange Teste
- GeT-Biopuces, TBI, Université de Toulouse, CNRS, INRAE, INSA, 31077 Toulouse, France
| | - Johannes Geiselmann
- Université Grenoble Alpes, Inria, 38000 Grenoble, France
- Université Grenoble Alpes, CNRS, LIPhy, 38000 Grenoble, France
| | - Hidde de Jong
- Université Grenoble Alpes, Inria, 38000 Grenoble, France
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24
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Guharajan S, Chhabra S, Parisutham V, Brewster RC. Quantifying the regulatory role of individual transcription factors in Escherichia coli. Cell Rep 2021; 37:109952. [PMID: 34758318 PMCID: PMC8667592 DOI: 10.1016/j.celrep.2021.109952] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2021] [Revised: 08/02/2021] [Accepted: 10/13/2021] [Indexed: 11/30/2022] Open
Abstract
Gene regulation often results from the action of multiple transcription factors (TFs) acting at a promoter, obscuring the individual regulatory effect of each TF on RNA polymerase (RNAP). Here we measure the fundamental regulatory interactions of TFs in E. coli by designing synthetic target genes that isolate individual TFs' regulatory effects. Using a thermodynamic model, each TF's regulatory interactions are decoupled from TF occupancy and interpreted as acting through (de)stabilization of RNAP and (de)acceleration of transcription initiation. We find that the contribution of each mechanism depends on TF identity and binding location; regulation immediately downstream of the promoter is insensitive to TF identity, but the same TFs regulate by distinct mechanisms upstream of the promoter. These two mechanisms are uncoupled and can act coherently, to reinforce the observed regulatory role (activation/repression), or incoherently, wherein the TF regulates two distinct steps with opposing effects.
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Affiliation(s)
- Sunil Guharajan
- Department of Systems Biology, University of Massachusetts Chan Medical School, Worcester, MA 01605, USA
| | - Shivani Chhabra
- Department of Pharmacological Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Vinuselvi Parisutham
- Department of Systems Biology, University of Massachusetts Chan Medical School, Worcester, MA 01605, USA
| | - Robert C Brewster
- Department of Systems Biology, University of Massachusetts Chan Medical School, Worcester, MA 01605, USA; Department of Microbiology and Physiological Systems, University of Massachusetts Chan Medical School, Worcester, MA 01605, USA.
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25
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Anderson DA, Voigt CA. Competitive dCas9 binding as a mechanism for transcriptional control. Mol Syst Biol 2021; 17:e10512. [PMID: 34747560 PMCID: PMC8574044 DOI: 10.15252/msb.202110512] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2021] [Revised: 10/10/2021] [Accepted: 10/11/2021] [Indexed: 12/24/2022] Open
Abstract
Catalytically dead Cas9 (dCas9) is a programmable transcription factor that can be targeted to promoters through the design of small guide RNAs (sgRNAs), where it can function as an activator or repressor. Natural promoters use overlapping binding sites as a mechanism for signal integration, where the binding of one can block, displace, or augment the activity of the other. Here, we implemented this strategy in Escherichia coli using pairs of sgRNAs designed to repress and then derepress transcription through competitive binding. When designed to target a promoter, this led to 27-fold repression and complete derepression. This system was also capable of ratiometric input comparison over two orders of magnitude. Additionally, we used this mechanism for promoter sequence-independent control by adopting it for elongation control, achieving 8-fold repression and 4-fold derepression. This work demonstrates a new genetic control mechanism that could be used to build analog circuit or implement cis-regulatory logic on CRISPRi-targeted native genes.
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Affiliation(s)
- Daniel A Anderson
- Synthetic Biology CenterDepartment of Biological EngineeringMassachusetts Institute of TechnologyCambridgeMAUSA
| | - Christopher A Voigt
- Synthetic Biology CenterDepartment of Biological EngineeringMassachusetts Institute of TechnologyCambridgeMAUSA
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26
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Myers KS, Noguera DR, Donohue TJ. Promoter Architecture Differences among Alphaproteobacteria and Other Bacterial Taxa. mSystems 2021; 6:e0052621. [PMID: 34254822 PMCID: PMC8407463 DOI: 10.1128/msystems.00526-21] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2021] [Accepted: 06/17/2021] [Indexed: 11/20/2022] Open
Abstract
Much of our knowledge of bacterial transcription initiation has been derived from studying the promoters of Escherichia coli and Bacillus subtilis. Given the expansive diversity across the bacterial phylogeny, it is unclear how much of this knowledge can be applied to other organisms. Here, we report on bioinformatic analyses of promoter sequences of the primary σ factor (σ70) by leveraging publicly available transcription start site (TSS) sequencing data sets for nine bacterial species spanning five phyla. This analysis identifies previously unreported differences in the -35 and -10 elements of σ70-dependent promoters in several groups of bacteria. We found that Actinobacteria and Betaproteobacteria σ70-dependent promoters lack the TTG triad in their -35 element, which is predicted to be conserved across the bacterial phyla. In addition, the majority of the Alphaproteobacteria σ70-dependent promoters analyzed lacked the thymine at position -7 that is highly conserved in other phyla. Bioinformatic examination of the Alphaproteobacteria σ70-dependent promoters identifies a significant overrepresentation of essential genes and ones encoding proteins with common cellular functions downstream of promoters containing an A, C, or G at position -7. We propose that transcription of many σ70-dependent promoters in Alphaproteobacteria depends on the transcription factor CarD, which is an essential protein in several members of this phylum. Our analysis expands the knowledge of promoter architecture across the bacterial phylogeny and provides new information that can be used to engineer bacteria for use in medical, environmental, agricultural, and biotechnological processes. IMPORTANCE Transcription of DNA to RNA by RNA polymerase is essential for cells to grow, develop, and respond to stress. Understanding the process and control of transcription is important for health, disease, the environment, and biotechnology. Decades of research on a few bacteria have identified promoter DNA sequences that are recognized by the σ subunit of RNA polymerase. We used bioinformatic analyses to reveal previously unreported differences in promoter DNA sequences across the bacterial phylogeny. We found that many Actinobacteria and Betaproteobacteria promoters lack a sequence in their -35 DNA recognition element that was previously assumed to be conserved and that Alphaproteobacteria lack a thymine residue at position -7, also previously assumed to be conserved. Our work reports important new information about bacterial transcription, illustrates the benefits of studying bacteria across the phylogenetic tree, and proposes new lines of future investigation.
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Affiliation(s)
- Kevin S. Myers
- Wisconsin Energy Institute and Great Lakes Bioenergy Research Center, University of Wisconsin—Madison, Madison, Wisconsin, USA
| | - Daniel R. Noguera
- Wisconsin Energy Institute and Great Lakes Bioenergy Research Center, University of Wisconsin—Madison, Madison, Wisconsin, USA
- Department of Civil & Environmental Engineering, University of Wisconsin—Madison, Madison, Wisconsin, USA
| | - Timothy J. Donohue
- Wisconsin Energy Institute and Great Lakes Bioenergy Research Center, University of Wisconsin—Madison, Madison, Wisconsin, USA
- Department of Bacteriology, University of Wisconsin—Madison, Madison, Wisconsin, USA
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27
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Abstract
Bacterial protein synthesis rates have evolved to maintain preferred stoichiometries at striking precision, from the components of protein complexes to constituents of entire pathways. Setting relative protein production rates to be well within a factor of two requires concerted tuning of transcription, RNA turnover, and translation, allowing many potential regulatory strategies to achieve the preferred output. The last decade has seen a greatly expanded capacity for precise interrogation of each step of the central dogma genome-wide. Here, we summarize how these technologies have shaped the current understanding of diverse bacterial regulatory architectures underpinning stoichiometric protein synthesis. We focus on the emerging expanded view of bacterial operons, which encode diverse primary and secondary mRNA structures for tuning protein stoichiometry. Emphasis is placed on how quantitative tuning is achieved. We discuss the challenges and open questions in the application of quantitative, genome-wide methodologies to the problem of precise protein production. Expected final online publication date for the Annual Review of Microbiology, Volume 75 is October 2021. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.
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Affiliation(s)
- James C Taggart
- Department of Biology, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA; ,
| | - Jean-Benoît Lalanne
- Department of Biology, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA; , .,Department of Physics, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA.,Current affiliation: Department of Genome Sciences, University of Washington, Seattle, Washington 98195, USA;
| | - Gene-Wei Li
- Department of Biology, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA; ,
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28
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Razo-Mejia M, Marzen S, Chure G, Taubman R, Morrison M, Phillips R. First-principles prediction of the information processing capacity of a simple genetic circuit. Phys Rev E 2021; 102:022404. [PMID: 32942428 DOI: 10.1103/physreve.102.022404] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2020] [Accepted: 07/02/2020] [Indexed: 11/07/2022]
Abstract
Given the stochastic nature of gene expression, genetically identical cells exposed to the same environmental inputs will produce different outputs. This heterogeneity has been hypothesized to have consequences for how cells are able to survive in changing environments. Recent work has explored the use of information theory as a framework to understand the accuracy with which cells can ascertain the state of their surroundings. Yet the predictive power of these approaches is limited and has not been rigorously tested using precision measurements. To that end, we generate a minimal model for a simple genetic circuit in which all parameter values for the model come from independently published data sets. We then predict the information processing capacity of the genetic circuit for a suite of biophysical parameters such as protein copy number and protein-DNA affinity. We compare these parameter-free predictions with an experimental determination of protein expression distributions and the resulting information processing capacity of E. coli cells. We find that our minimal model captures the scaling of the cell-to-cell variability in the data and the inferred information processing capacity of our simple genetic circuit up to a systematic deviation.
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Affiliation(s)
- Manuel Razo-Mejia
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, California 91125, USA
| | - Sarah Marzen
- Department of Physics, W. M. Keck Science Department, Claremont McKenna College, Claremont, California 91711, USA
| | - Griffin Chure
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, California 91125, USA
| | - Rachel Taubman
- Department of Physics, W. M. Keck Science Department, Claremont McKenna College, Claremont, California 91711, USA
| | - Muir Morrison
- Department of Physics, California Institute of Technology, Pasadena, California 91125, USA
| | - Rob Phillips
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, California 91125, USA.,Department of Physics, California Institute of Technology, Pasadena, California 91125, USA
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29
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Alam K, Hao J, Zhang Y, Li A. Synthetic biology-inspired strategies and tools for engineering of microbial natural product biosynthetic pathways. Biotechnol Adv 2021; 49:107759. [PMID: 33930523 DOI: 10.1016/j.biotechadv.2021.107759] [Citation(s) in RCA: 26] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2020] [Revised: 03/28/2021] [Accepted: 04/23/2021] [Indexed: 02/08/2023]
Abstract
Microbial-derived natural products (NPs) and their derivative products are of great importance and used widely in many fields, especially in pharmaceutical industries. However, there is an immediate need to establish innovative approaches, strategies, and techniques to discover new NPs with novel or enhanced biological properties, due to the less productivity and higher cost on traditional drug discovery pipelines from natural bioresources. Revealing of untapped microbial cryptic biosynthetic gene clusters (BGCs) using DNA sequencing technology and bioinformatics tools makes genome mining possible for NP discovery from microorganisms. Meanwhile, new approaches and strategies in the area of synthetic biology offer great potentials for generation of new NPs by engineering or creating synthetic systems with improved and desired functions. Development of approaches, strategies and tools in synthetic biology can facilitate not only exploration and enhancement in supply, and also in the structural diversification of NPs. Here, we discussed recent advances in synthetic biology-inspired strategies, including bioinformatics and genetic engineering tools and approaches for identification, cloning, editing/refactoring of candidate biosynthetic pathways, construction of heterologous expression hosts, fitness optimization between target pathways and hosts and detection of NP production.
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Affiliation(s)
- Khorshed Alam
- Helmholtz International Lab for Anti-Infectives, Shandong University-Helmholtz Institute of Biotechnology, State Key Laboratory of Microbial Technology, Shandong University, Qingdao 266237, PR China.
| | - Jinfang Hao
- Helmholtz International Lab for Anti-Infectives, Shandong University-Helmholtz Institute of Biotechnology, State Key Laboratory of Microbial Technology, Shandong University, Qingdao 266237, PR China
| | - Youming Zhang
- Helmholtz International Lab for Anti-Infectives, Shandong University-Helmholtz Institute of Biotechnology, State Key Laboratory of Microbial Technology, Shandong University, Qingdao 266237, PR China.
| | - Aiying Li
- Helmholtz International Lab for Anti-Infectives, Shandong University-Helmholtz Institute of Biotechnology, State Key Laboratory of Microbial Technology, Shandong University, Qingdao 266237, PR China.
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30
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The Context-Dependent Influence of Promoter Sequence Motifs on Transcription Initiation Kinetics and Regulation. J Bacteriol 2021; 203:JB.00512-20. [PMID: 33139481 DOI: 10.1128/jb.00512-20] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022] Open
Abstract
The fitness of an individual bacterial cell is highly dependent upon the temporal tuning of gene expression levels when subjected to different environmental cues. Kinetic regulation of transcription initiation is a key step in modulating the levels of transcribed genes to promote bacterial survival. The initiation phase encompasses the binding of RNA polymerase (RNAP) to promoter DNA and a series of coupled protein-DNA conformational changes prior to entry into processive elongation. The time required to complete the initiation phase can vary by orders of magnitude and is ultimately dictated by the DNA sequence of the promoter. In this review, we aim to provide the required background to understand how promoter sequence motifs may affect initiation kinetics during promoter recognition and binding, subsequent conformational changes which lead to DNA opening around the transcription start site, and promoter escape. By calculating the steady-state flux of RNA production as a function of these effects, we illustrate that the presence/absence of a consensus promoter motif cannot be used in isolation to make conclusions regarding promoter strength. Instead, the entire series of linked, sequence-dependent structural transitions must be considered holistically. Finally, we describe how individual transcription factors take advantage of the broad distribution of sequence-dependent basal kinetics to either increase or decrease RNA flux.
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31
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Cetnar DP, Salis HM. Systematic Quantification of Sequence and Structural Determinants Controlling mRNA stability in Bacterial Operons. ACS Synth Biol 2021; 10:318-332. [PMID: 33464822 DOI: 10.1021/acssynbio.0c00471] [Citation(s) in RCA: 40] [Impact Index Per Article: 13.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/18/2023]
Abstract
mRNA degradation is a central process that affects all gene expression levels, and yet, the determinants that control mRNA decay rates remain poorly characterized. Here, we applied a synthetic biology, learn-by-design approach to elucidate the sequence and structural determinants that control mRNA stability in bacterial operons. We designed, constructed, and characterized 82 operons in Escherichia coli, systematically varying RNase binding site characteristics, translation initiation rates, and transcriptional terminator efficiencies in the 5' untranslated region (UTR), intergenic, and 3' UTR regions, followed by measuring their mRNA levels using reverse transcription quantitative polymerase chain reaction (RT-qPCR) assays during exponential growth. We show that introducing long single-stranded RNA into 5' UTRs reduced mRNA levels by up to 9.4-fold and that lowering translation rates reduced mRNA levels by up to 11.8-fold. We also found that RNase binding sites in intergenic regions had much lower effects on mRNA levels. Surprisingly, changing the transcriptional termination efficiency or introducing long single-stranded RNA into 3' UTRs had no effect on upstream mRNA levels. From these measurements, we developed and validated biophysical models of ribosome protection and RNase activity with excellent quantitative agreement. We also formulated design rules to rationally control a mRNA's stability, facilitating the automated design of engineered genetic systems with desired functionalities.
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32
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Morrison M, Razo-Mejia M, Phillips R. Reconciling kinetic and thermodynamic models of bacterial transcription. PLoS Comput Biol 2021; 17:e1008572. [PMID: 33465069 PMCID: PMC7845990 DOI: 10.1371/journal.pcbi.1008572] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2020] [Revised: 01/29/2021] [Accepted: 11/28/2020] [Indexed: 11/18/2022] Open
Abstract
The study of transcription remains one of the centerpieces of modern biology with implications in settings from development to metabolism to evolution to disease. Precision measurements using a host of different techniques including fluorescence and sequencing readouts have raised the bar for what it means to quantitatively understand transcriptional regulation. In particular our understanding of the simplest genetic circuit is sufficiently refined both experimentally and theoretically that it has become possible to carefully discriminate between different conceptual pictures of how this regulatory system works. This regulatory motif, originally posited by Jacob and Monod in the 1960s, consists of a single transcriptional repressor binding to a promoter site and inhibiting transcription. In this paper, we show how seven distinct models of this so-called simple-repression motif, based both on thermodynamic and kinetic thinking, can be used to derive the predicted levels of gene expression and shed light on the often surprising past success of the thermodynamic models. These different models are then invoked to confront a variety of different data on mean, variance and full gene expression distributions, illustrating the extent to which such models can and cannot be distinguished, and suggesting a two-state model with a distribution of burst sizes as the most potent of the seven for describing the simple-repression motif.
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Affiliation(s)
- Muir Morrison
- Department of Physics, California Institute of Technology, Pasadena, California, USA
| | - Manuel Razo-Mejia
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, California, USA
| | - Rob Phillips
- Department of Physics, California Institute of Technology, Pasadena, California, USA
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, California, USA
- * E-mail:
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33
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Yu TC, Liu WL, Brinck MS, Davis JE, Shek J, Bower G, Einav T, Insigne KD, Phillips R, Kosuri S, Urtecho G. Multiplexed characterization of rationally designed promoter architectures deconstructs combinatorial logic for IPTG-inducible systems. Nat Commun 2021; 12:325. [PMID: 33436562 PMCID: PMC7804116 DOI: 10.1038/s41467-020-20094-3] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2020] [Accepted: 11/04/2020] [Indexed: 12/21/2022] Open
Abstract
A crucial step towards engineering biological systems is the ability to precisely tune the genetic response to environmental stimuli. In the case of Escherichia coli inducible promoters, our incomplete understanding of the relationship between sequence composition and gene expression hinders our ability to predictably control transcriptional responses. Here, we profile the expression dynamics of 8269 rationally designed, IPTG-inducible promoters that collectively explore the individual and combinatorial effects of RNA polymerase and LacI repressor binding site strengths. We then fit a statistical mechanics model to measured expression that accurately models gene expression and reveals properties of theoretically optimal inducible promoters. Furthermore, we characterize three alternative promoter architectures and show that repositioning binding sites within promoters influences the types of combinatorial effects observed between promoter elements. In total, this approach enables us to deconstruct relationships between inducible promoter elements and discover practical insights for engineering inducible promoters with desirable characteristics.
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Affiliation(s)
- Timothy C Yu
- Department of Bioengineering, University of California, Los Angeles, CA, 90095, USA
| | - Winnie L Liu
- Department of Molecular, Cell, and Developmental Biology, University of California, Los Angeles, CA, 90095, USA
| | - Marcia S Brinck
- Department of Microbiology, Immunology, and Molecular Genetics, University of California, Los Angeles, CA, 90095, USA
| | - Jessica E Davis
- Department of Chemistry and Biochemistry, University of California, Los Angeles, CA, 90095, USA
| | - Jeremy Shek
- Department of Chemistry and Biochemistry, University of California, Los Angeles, CA, 90095, USA
| | - Grace Bower
- Department of Molecular, Cell, and Developmental Biology, University of California, Los Angeles, CA, 90095, USA
| | - Tal Einav
- Department of Physics, California Institute of Technology, Pasadena, CA, 91125, USA
| | - Kimberly D Insigne
- Bioinformatics Interdepartmental Graduate Program, University of California, Los Angeles, CA, 90095, USA
| | - Rob Phillips
- Department of Physics, California Institute of Technology, Pasadena, CA, 91125, USA
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA, 91125, USA
- Department of Applied Physics, California Institute of Technology, Pasadena, CA, 91125, USA
| | - Sriram Kosuri
- Department of Chemistry and Biochemistry, University of California, Los Angeles, CA, 90095, USA.
- UCLA-DOE Institute for Genomics and Proteomics, Los Angeles, CA, 90095, USA.
- Institute for Quantitative and Computational Biosciences (QCB), University of California, Los Angeles, Los Angeles, CA, 90095, USA.
- Eli and Edythe Broad Center of Regenerative Medicine and Stem Cell Research, University of California, Los Angeles, Los Angeles, CA, 90095, USA.
- Jonsson Comprehensive Cancer Center, University of California, Los Angeles, CA, 90095, USA.
- Molecular Biology Interdepartmental Doctoral Program, University of California, Los Angeles, CA, 90095, USA.
| | - Guillaume Urtecho
- Molecular Biology Interdepartmental Doctoral Program, University of California, Los Angeles, CA, 90095, USA.
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34
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Adhikari A, Vilkhovoy M, Vadhin S, Lim HE, Varner JD. Effective Biophysical Modeling of Cell Free Transcription and Translation Processes. Front Bioeng Biotechnol 2020; 8:539081. [PMID: 33324619 PMCID: PMC7726328 DOI: 10.3389/fbioe.2020.539081] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2020] [Accepted: 11/02/2020] [Indexed: 12/18/2022] Open
Abstract
Transcription and translation are at the heart of metabolism and signal transduction. In this study, we developed an effective biophysical modeling approach to simulate transcription and translation processes. The model, composed of coupled ordinary differential equations, was tested by comparing simulations of two cell free synthetic circuits with experimental measurements generated in this study. First, we considered a simple circuit in which sigma factor 70 induced the expression of green fluorescent protein. This relatively simple case was then followed by a more complex negative feedback circuit in which two control genes were coupled to the expression of a third reporter gene, green fluorescent protein. Many of the model parameters were estimated from previous biophysical studies in the literature, while the remaining unknown model parameters for each circuit were estimated by minimizing the difference between model simulations and messenger RNA (mRNA) and protein measurements generated in this study. In particular, either parameter estimates from published studies were used directly, or characteristic values found in the literature were used to establish feasible ranges for the parameter estimation problem. In order to perform a detailed analysis of the influence of individual model parameters on the expression dynamics of each circuit, global sensitivity analysis was used. Taken together, the effective biophysical modeling approach captured the expression dynamics, including the transcription dynamics, for the two synthetic cell free circuits. While, we considered only two circuits here, this approach could potentially be extended to simulate other genetic circuits in both cell free and whole cell biomolecular applications as the equations governing the regulatory control functions are modular and easily modifiable. The model code, parameters, and analysis scripts are available for download under an MIT software license from the Varnerlab GitHub repository.
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Affiliation(s)
- Abhinav Adhikari
- Robert Frederick Smith School of Chemical and Biomolecular Engineering, College of Engineering, Cornell University, Ithaca, NY, United States
| | - Michael Vilkhovoy
- Robert Frederick Smith School of Chemical and Biomolecular Engineering, College of Engineering, Cornell University, Ithaca, NY, United States
| | - Sandra Vadhin
- Robert Frederick Smith School of Chemical and Biomolecular Engineering, College of Engineering, Cornell University, Ithaca, NY, United States
| | - Ha Eun Lim
- Robert Frederick Smith School of Chemical and Biomolecular Engineering, College of Engineering, Cornell University, Ithaca, NY, United States
| | - Jeffrey D Varner
- Robert Frederick Smith School of Chemical and Biomolecular Engineering, College of Engineering, Cornell University, Ithaca, NY, United States
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35
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Liu Y, Guo M, Du R, Chi J, He X, Xie Z, Huang K, Luo Y, Xu W. A gas reporting whole-cell microbial biosensor system for rapid on-site detection of mercury contamination in soils. Biosens Bioelectron 2020; 170:112660. [DOI: 10.1016/j.bios.2020.112660] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2020] [Revised: 09/24/2020] [Accepted: 09/26/2020] [Indexed: 11/26/2022]
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36
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Reis AC, Salis HM. An Automated Model Test System for Systematic Development and Improvement of Gene Expression Models. ACS Synth Biol 2020; 9:3145-3156. [PMID: 33054181 DOI: 10.1021/acssynbio.0c00394] [Citation(s) in RCA: 80] [Impact Index Per Article: 20.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
Abstract
Gene expression models greatly accelerate the engineering of synthetic metabolic pathways and genetic circuits by predicting sequence-function relationships and reducing trial-and-error experimentation. However, developing models with more accurate predictions remains a significant challenge. Here we present a model test system that combines advanced statistics, machine learning, and a database of 9862 characterized genetic systems to automatically quantify model accuracies, accept or reject mechanistic hypotheses, and identify areas for model improvement. We also introduce model capacity, a new information theoretic metric for correct cross-data-set comparisons. We demonstrate the model test system by comparing six models of translation initiation rate, evaluating 100 mechanistic hypotheses, and uncovering new sequence determinants that control protein expression levels. We then applied these results to develop a biophysical model of translation initiation rate with significant improvements in accuracy. Automated model test systems will dramatically accelerate the development of gene expression models, and thereby transition synthetic biology into a mature engineering discipline.
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37
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Van Brempt M, Clauwaert J, Mey F, Stock M, Maertens J, Waegeman W, De Mey M. Predictive design of sigma factor-specific promoters. Nat Commun 2020; 11:5822. [PMID: 33199691 PMCID: PMC7670410 DOI: 10.1038/s41467-020-19446-w] [Citation(s) in RCA: 26] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2020] [Accepted: 10/13/2020] [Indexed: 02/07/2023] Open
Abstract
To engineer synthetic gene circuits, molecular building blocks are developed which can modulate gene expression without interference, mutually or with the host's cell machinery. As the complexity of gene circuits increases, automated design tools and tailored building blocks to ensure perfect tuning of all components in the network are required. Despite the efforts to develop prediction tools that allow forward engineering of promoter transcription initiation frequency (TIF), such a tool is still lacking. Here, we use promoter libraries of E. coli sigma factor 70 (σ70)- and B. subtilis σB-, σF- and σW-dependent promoters to construct prediction models, capable of both predicting promoter TIF and orthogonality of the σ-specific promoters. This is achieved by training a convolutional neural network with high-throughput DNA sequencing data from fluorescence-activated cell sorted promoter libraries. This model functions as the base of the online promoter design tool (ProD), providing tailored promoters for tailored genetic systems.
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Affiliation(s)
- Maarten Van Brempt
- Centre for Synthetic Biology (CSB), Department of Biotechnology, Ghent University, 9000, Ghent, Belgium
| | - Jim Clauwaert
- KERMIT, Department of Data Analysis and Mathematical Modelling, Ghent University, 9000, Ghent, Belgium
| | - Friederike Mey
- Centre for Synthetic Biology (CSB), Department of Biotechnology, Ghent University, 9000, Ghent, Belgium
| | - Michiel Stock
- KERMIT, Department of Data Analysis and Mathematical Modelling, Ghent University, 9000, Ghent, Belgium
| | - Jo Maertens
- Centre for Synthetic Biology (CSB), Department of Biotechnology, Ghent University, 9000, Ghent, Belgium
| | - Willem Waegeman
- KERMIT, Department of Data Analysis and Mathematical Modelling, Ghent University, 9000, Ghent, Belgium
| | - Marjan De Mey
- Centre for Synthetic Biology (CSB), Department of Biotechnology, Ghent University, 9000, Ghent, Belgium.
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38
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Eck E, Liu J, Kazemzadeh-Atoufi M, Ghoreishi S, Blythe SA, Garcia HG. Quantitative dissection of transcription in development yields evidence for transcription-factor-driven chromatin accessibility. eLife 2020; 9:e56429. [PMID: 33074101 PMCID: PMC7738189 DOI: 10.7554/elife.56429] [Citation(s) in RCA: 22] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2020] [Accepted: 10/16/2020] [Indexed: 12/28/2022] Open
Abstract
Thermodynamic models of gene regulation can predict transcriptional regulation in bacteria, but in eukaryotes, chromatin accessibility and energy expenditure may call for a different framework. Here, we systematically tested the predictive power of models of DNA accessibility based on the Monod-Wyman-Changeux (MWC) model of allostery, which posits that chromatin fluctuates between accessible and inaccessible states. We dissected the regulatory dynamics of hunchback by the activator Bicoid and the pioneer-like transcription factor Zelda in living Drosophila embryos and showed that no thermodynamic or non-equilibrium MWC model can recapitulate hunchback transcription. Therefore, we explored a model where DNA accessibility is not the result of thermal fluctuations but is catalyzed by Bicoid and Zelda, possibly through histone acetylation, and found that this model can predict hunchback dynamics. Thus, our theory-experiment dialogue uncovered potential molecular mechanisms of transcriptional regulatory dynamics, a key step toward reaching a predictive understanding of developmental decision-making.
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Affiliation(s)
- Elizabeth Eck
- Biophysics Graduate Group, University of California at BerkeleyBerkeleyUnited States
| | - Jonathan Liu
- Department of Physics, University of California at BerkeleyBerkeleyUnited States
| | | | - Sydney Ghoreishi
- Department of Molecular and Cell Biology, University of California at BerkeleyBerkeleyUnited States
| | - Shelby A Blythe
- Department of Molecular Biosciences, Northwestern UniversityEvanstonUnited States
| | - Hernan G Garcia
- Biophysics Graduate Group, University of California at BerkeleyBerkeleyUnited States
- Department of Physics, University of California at BerkeleyBerkeleyUnited States
- Department of Molecular and Cell Biology, University of California at BerkeleyBerkeleyUnited States
- Institute for Quantitative Biosciences-QB3, University of California at BerkeleyBerkeleyUnited States
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39
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Ireland WT, Beeler SM, Flores-Bautista E, McCarty NS, Röschinger T, Belliveau NM, Sweredoski MJ, Moradian A, Kinney JB, Phillips R. Deciphering the regulatory genome of Escherichia coli, one hundred promoters at a time. eLife 2020; 9:e55308. [PMID: 32955440 PMCID: PMC7567609 DOI: 10.7554/elife.55308] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2020] [Accepted: 09/18/2020] [Indexed: 01/28/2023] Open
Abstract
Advances in DNA sequencing have revolutionized our ability to read genomes. However, even in the most well-studied of organisms, the bacterium Escherichia coli, for ≈65% of promoters we remain ignorant of their regulation. Until we crack this regulatory Rosetta Stone, efforts to read and write genomes will remain haphazard. We introduce a new method, Reg-Seq, that links massively parallel reporter assays with mass spectrometry to produce a base pair resolution dissection of more than a E. coli promoters in 12 growth conditions. We demonstrate that the method recapitulates known regulatory information. Then, we examine regulatory architectures for more than 80 promoters which previously had no known regulatory information. In many cases, we also identify which transcription factors mediate their regulation. This method clears a path for highly multiplexed investigations of the regulatory genome of model organisms, with the potential of moving to an array of microbes of ecological and medical relevance.
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Affiliation(s)
- William T Ireland
- Department of Physics, California Institute of TechnologyPasadenaUnited States
| | - Suzannah M Beeler
- Division of Biology and Biological Engineering, California Institute of TechnologyPasadenaUnited States
| | - Emanuel Flores-Bautista
- Division of Biology and Biological Engineering, California Institute of TechnologyPasadenaUnited States
| | - Nicholas S McCarty
- Division of Biology and Biological Engineering, California Institute of TechnologyPasadenaUnited States
| | - Tom Röschinger
- Division of Chemistry and Chemical Engineering, California Institute of TechnologyPasadenaUnited States
| | - Nathan M Belliveau
- Division of Biology and Biological Engineering, California Institute of TechnologyPasadenaUnited States
| | - Michael J Sweredoski
- Proteome Exploration Laboratory, Division of Biology and Biological Engineering, Beckman Institute, California Institute of TechnologyPasadenaUnited States
| | - Annie Moradian
- Proteome Exploration Laboratory, Division of Biology and Biological Engineering, Beckman Institute, California Institute of TechnologyPasadenaUnited States
| | - Justin B Kinney
- Simons Center for Quantitative Biology, Cold Spring Harbor LaboratoryCold Spring HarborUnited States
| | - Rob Phillips
- Department of Physics, California Institute of TechnologyPasadenaUnited States
- Division of Biology and Biological Engineering, California Institute of TechnologyPasadenaUnited States
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Abstract
The correct mapping of promoter elements is a crucial step in microbial genomics. Also, when combining new DNA elements into synthetic sequences, predicting the potential generation of new promoter sequences is critical. Over the last years, many bioinformatics tools have been created to allow users to predict promoter elements in a sequence or genome of interest. Here, we assess the predictive power of some of the main prediction tools available using well-defined promoter data sets. Using Escherichia coli as a model organism, we demonstrated that while some tools are biased toward AT-rich sequences, others are very efficient in identifying real promoters with low false-negative rates. We hope the potentials and limitations presented here will help the microbiology community to choose promoter prediction tools among many available alternatives. The promoter region is a key element required for the production of RNA in bacteria. While new high-throughput technology allows massively parallel mapping of promoter elements, we still mainly rely on bioinformatics tools to predict such elements in bacterial genomes. Additionally, despite many different prediction tools having become popular to identify bacterial promoters, no systematic comparison of such tools has been performed. Here, we performed a systematic comparison between several widely used promoter prediction tools (BPROM, bTSSfinder, BacPP, CNNProm, IBBP, Virtual Footprint, iPro70-FMWin, 70ProPred, iPromoter-2L, and MULTiPly) using well-defined sequence data sets and standardized metrics to determine how well those tools performed related to each other. For this, we used data sets of experimentally validated promoters from Escherichia coli and a control data set composed of randomly generated sequences with similar nucleotide distributions. We compared the performance of the tools using metrics such as specificity, sensitivity, accuracy, and Matthews correlation coefficient (MCC). We show that the widely used BPROM presented the worse performance among the compared tools, while four tools (CNNProm, iPro70-FMWin, 70ProPred, and iPromoter-2L) offered high predictive power. Of these tools, iPro70-FMWin exhibited the best results for most of the metrics used. We present here some potentials and limitations of available tools, and we hope that future work can build upon our effort to systematically characterize this useful class of bioinformatics tools. IMPORTANCE The correct mapping of promoter elements is a crucial step in microbial genomics. Also, when combining new DNA elements into synthetic sequences, predicting the potential generation of new promoter sequences is critical. Over the last years, many bioinformatics tools have been created to allow users to predict promoter elements in a sequence or genome of interest. Here, we assess the predictive power of some of the main prediction tools available using well-defined promoter data sets. Using Escherichia coli as a model organism, we demonstrated that while some tools are biased toward AT-rich sequences, others are very efficient in identifying real promoters with low false-negative rates. We hope the potentials and limitations presented here will help the microbiology community to choose promoter prediction tools among many available alternatives.
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Genome-Scale Transcription-Translation Mapping Reveals Features of Zymomonas mobilis Transcription Units and Promoters. mSystems 2020; 5:5/4/e00250-20. [PMID: 32694125 PMCID: PMC7566282 DOI: 10.1128/msystems.00250-20] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/29/2022] Open
Abstract
Efforts to rationally engineer synthetic pathways in Zymomonas mobilis are impeded by a lack of knowledge and tools for predictable and quantitative programming of gene regulation at the transcriptional, posttranscriptional, and posttranslational levels. With the detailed functional characterization of the Z. mobilis genome presented in this work, we provide crucial knowledge for the development of synthetic genetic parts tailored to Z. mobilis. This information is vital as researchers continue to develop Z. mobilis for synthetic biology applications. Our methods and statistical analyses also provide ways to rapidly advance the understanding of poorly characterized bacteria via empirical data that enable the experimental validation of sequence-based prediction for genome characterization and annotation. Zymomonas mobilis is an ethanologenic alphaproteobacterium with promise for the industrial conversion of renewable plant biomass into fuels and chemical bioproducts. Limited functional annotation of the Z. mobilis genome is a current barrier to both fundamental studies of Z. mobilis and its development as a synthetic biology chassis. To gain insight, we collected sample-matched multiomics data, including RNA sequencing (RNA-seq), transcription start site (TSS) sequencing (TSS-seq), termination sequencing (term-seq), ribosome profiling, and label-free shotgun proteomic mass spectrometry, across different growth conditions and used these data to improve annotation and assign functional sites in the Z. mobilis genome. Proteomics and ribosome profiling informed revisions of protein-coding genes, which included 44 start codon changes and 42 added proteins. We developed statistical methods for annotating transcript 5′ and 3′ ends, enabling the identification of 3,940 TSSs and their corresponding promoters and 2,091 transcription termination sites, which were distinguished from RNA processing sites by the lack of an adjacent RNA 5′ end. Our results revealed that Z. mobilis σA −35 and −10 promoter elements closely resemble canonical Escherichia coli −35 and −10 elements, with one notable exception: the Z. mobilis −10 element lacks the highly conserved −7 thymine observed in E. coli and other previously characterized σA promoters. The σA promoters of another alphaproteobacterium, Caulobacter crescentus, similarly lack the conservation of −7 thymine in their −10 elements. Our results anchor the development of Z. mobilis as a platform for synthetic biology and establish strategies for empirical genome annotation that can complement purely computational methods. IMPORTANCE Efforts to rationally engineer synthetic pathways in Zymomonas mobilis are impeded by a lack of knowledge and tools for predictable and quantitative programming of gene regulation at the transcriptional, posttranscriptional, and posttranslational levels. With the detailed functional characterization of the Z. mobilis genome presented in this work, we provide crucial knowledge for the development of synthetic genetic parts tailored to Z. mobilis. This information is vital as researchers continue to develop Z. mobilis for synthetic biology applications. Our methods and statistical analyses also provide ways to rapidly advance the understanding of poorly characterized bacteria via empirical data that enable the experimental validation of sequence-based prediction for genome characterization and annotation.
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Hossain A, Lopez E, Halper SM, Cetnar DP, Reis AC, Strickland D, Klavins E, Salis HM. Automated design of thousands of nonrepetitive parts for engineering stable genetic systems. Nat Biotechnol 2020; 38:1466-1475. [PMID: 32661437 DOI: 10.1038/s41587-020-0584-2] [Citation(s) in RCA: 51] [Impact Index Per Article: 12.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2019] [Accepted: 05/31/2020] [Indexed: 01/08/2023]
Abstract
Engineered genetic systems are prone to failure when their genetic parts contain repetitive sequences. Designing many nonrepetitive genetic parts with desired functionalities remains a difficult challenge with high computational complexity. To overcome this challenge, we developed the Nonrepetitive Parts Calculator to rapidly generate thousands of highly nonrepetitive genetic parts from specified design constraints, including promoters, ribosome-binding sites and terminators. As a demonstration, we designed and experimentally characterized 4,350 nonrepetitive bacterial promoters with transcription rates that varied across a 820,000-fold range, and 1,722 highly nonrepetitive yeast promoters with transcription rates that varied across a 25,000-fold range. We applied machine learning to explain how specific interactions controlled the promoters' transcription rates. We also show that using nonrepetitive genetic parts substantially reduces homologous recombination, resulting in greater genetic stability.
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Affiliation(s)
- Ayaan Hossain
- Bioinformatics and Genomics, Pennsylvania State University, University Park, PA, USA
| | - Eriberto Lopez
- Department of Electrical & Computer Engineering, University of Washington, Seattle, WA, USA
| | - Sean M Halper
- Department of Chemical Engineering, Pennsylvania State University, University Park, PA, USA
| | - Daniel P Cetnar
- Department of Chemical Engineering, Pennsylvania State University, University Park, PA, USA
| | - Alexander C Reis
- Department of Chemical Engineering, Pennsylvania State University, University Park, PA, USA
| | - Devin Strickland
- Department of Electrical & Computer Engineering, University of Washington, Seattle, WA, USA
| | - Eric Klavins
- Department of Electrical & Computer Engineering, University of Washington, Seattle, WA, USA
| | - Howard M Salis
- Bioinformatics and Genomics, Pennsylvania State University, University Park, PA, USA. .,Department of Chemical Engineering, Pennsylvania State University, University Park, PA, USA. .,Department of Biological Engineering, Pennsylvania State University, University Park, PA, USA. .,Department of Biomedical Engineering, Pennsylvania State University, University Park, PA, USA.
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Kemble H, Eisenhauer C, Couce A, Chapron A, Magnan M, Gautier G, Le Nagard H, Nghe P, Tenaillon O. Flux, toxicity, and expression costs generate complex genetic interactions in a metabolic pathway. SCIENCE ADVANCES 2020; 6:eabb2236. [PMID: 32537514 PMCID: PMC7269641 DOI: 10.1126/sciadv.abb2236] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/08/2020] [Accepted: 03/31/2020] [Indexed: 05/31/2023]
Abstract
Our ability to predict the impact of mutations on traits relevant for disease and evolution remains severely limited by the dependence of their effects on the genetic background and environment. Even when molecular interactions between genes are known, it is unclear how these translate to organism-level interactions between alleles. We therefore characterized the interplay of genetic and environmental dependencies in determining fitness by quantifying ~4000 fitness interactions between expression variants of two metabolic genes, starting from various environmentally modulated expression levels. We detect a remarkable variety of interactions dependent on initial expression levels and demonstrate that they can be quantitatively explained by a mechanistic model accounting for catabolic flux, metabolite toxicity, and expression costs. Complex fitness interactions between mutations can therefore be predicted simply from their simultaneous impact on a few connected molecular phenotypes.
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Affiliation(s)
- Harry Kemble
- IAME, INSERM, Université de Paris, Université Paris Nord, 75018 Paris, France
- Laboratory of Biochemistry (LBC), Chimie Biologie et Innovation, ESPCI Paris, PSL University, CNRS, 75005 Paris, France
| | | | - Alejandro Couce
- IAME, INSERM, Université de Paris, Université Paris Nord, 75018 Paris, France
- Department of Life Sciences, Imperial College, London SW7 2AZ, UK
| | - Audrey Chapron
- IAME, INSERM, Université de Paris, Université Paris Nord, 75018 Paris, France
| | - Mélanie Magnan
- IAME, INSERM, Université de Paris, Université Paris Nord, 75018 Paris, France
| | - Gregory Gautier
- Centre de Recherche sur l'Inflammation, INSERM, UMRS 1149, 75018 Paris, France
- Laboratoire d’Excellence INFLAMEX, Université de Paris, Sorbonne Paris Cité, 75018 Paris, France
| | - Hervé Le Nagard
- IAME, INSERM, Université de Paris, Université Paris Nord, 75018 Paris, France
| | - Philippe Nghe
- Laboratory of Biochemistry (LBC), Chimie Biologie et Innovation, ESPCI Paris, PSL University, CNRS, 75005 Paris, France
| | - Olivier Tenaillon
- IAME, INSERM, Université de Paris, Université Paris Nord, 75018 Paris, France
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Ali MZ, Choubey S, Das D, Brewster RC. Probing Mechanisms of Transcription Elongation Through Cell-to-Cell Variability of RNA Polymerase. Biophys J 2020; 118:1769-1781. [PMID: 32101716 PMCID: PMC7136280 DOI: 10.1016/j.bpj.2020.02.002] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2019] [Revised: 01/31/2020] [Accepted: 02/03/2020] [Indexed: 11/17/2022] Open
Abstract
The process of transcription initiation and elongation are primary points of control in the regulation of gene expression. Although biochemical studies have uncovered the mechanisms involved in controlling transcription at each step, how these mechanisms manifest in vivo at the level of individual genes is still unclear. Recent experimental advances have enabled single-cell measurements of RNA polymerase (RNAP) molecules engaged in the process of transcribing a gene of interest. In this article, we use Gillespie simulations to show that measurements of cell-to-cell variability of RNAP numbers and interpolymerase distances can reveal the prevailing mode of regulation of a given gene. Mechanisms of regulation at each step, from initiation to elongation dynamics, produce qualitatively distinct signatures, which can further be used to discern between them. Most intriguingly, depending on the initiation kinetics, stochastic elongation can either enhance or suppress cell-to-cell variability at the RNAP level. To demonstrate the value of this framework, we analyze RNAP number distribution data for ribosomal genes in Saccharomyces cerevisiae from three previously published studies and show that this approach provides crucial mechanistic insights into the transcriptional regulation of these genes.
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Affiliation(s)
- Md Zulfikar Ali
- Program in Systems Biology, University of Massachusetts Medical School, Worcester, Massachusetts; Department of Microbiology and Physiological Systems, University of Massachusetts Medical School, Worcester, Massachusetts
| | - Sandeep Choubey
- Max Planck institute for the Physics of Complex Systems, Dresden, Germany.
| | - Dipjyoti Das
- Department of Biological Sciences, Indian Institute of Science Education and Research Kolkata, Nadia, West Bengal, India
| | - Robert C Brewster
- Program in Systems Biology, University of Massachusetts Medical School, Worcester, Massachusetts; Department of Microbiology and Physiological Systems, University of Massachusetts Medical School, Worcester, Massachusetts.
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45
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Schuller A, Cserjan-Puschmann M, Tauer C, Jarmer J, Wagenknecht M, Reinisch D, Grabherr R, Striedner G. Escherichia coli σ 70 promoters allow expression rate control at the cellular level in genome-integrated expression systems. Microb Cell Fact 2020; 19:58. [PMID: 32138729 PMCID: PMC7059391 DOI: 10.1186/s12934-020-01311-6] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2019] [Accepted: 02/17/2020] [Indexed: 12/18/2022] Open
Abstract
Background The genome-integrated T7 expression system offers significant advantages, in terms of productivity and product quality, even when expressing the gene of interest (GOI) from a single copy. Compared to plasmid-based expression systems, this system does not incur a plasmid-mediated metabolic load, and it does not vary the dosage of the GOI during the production process. However, long-term production with T7 expression system leads to a rapidly growing non-producing population, because the T7 RNA polymerase (RNAP) is prone to mutations. The present study aimed to investigate whether two σ70 promoters, which were recognized by the Escherichia coli host RNAP, might be suitable in genome-integrated expression systems. We applied a promoter engineering strategy that allowed control of expressing the model protein, GFP, by introducing lac operators (lacO) into the constitutive T5 and A1 promoter sequences. Results We showed that, in genome-integrated E. coli expression systems that used σ70 promoters, the number of lacO sites must be well balanced. Promoters containing three and two lacO sites exhibited low basal expression, but resulted in a complete stop in recombinant protein production in partially induced cultures. In contrast, expression systems regulated by a single lacO site and the lac repressor element, lacIQ, on the same chromosome caused very low basal expression, were highly efficient in recombinant protein production, and enables fine-tuning of gene expression levels on a cellular level. Conclusions Based on our results, we hypothesized that this phenomenon was associated with the autoregulation of the lac repressor protein, LacI. We reasoned that the affinity of LacI for the lacO sites of the GOI must be lower than the affinity of LacI to the lacO sites of the endogenous lac operon; otherwise, LacI autoregulation could not take place, and the lack of LacI autoregulation would lead to a disturbance in lac repressor-mediated regulation of transcription. By exploiting the mechanism of LacI autoregulation, we created a novel E. coli expression system for use in recombinant protein production, synthetic biology, and metabolic engineering applications.
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Affiliation(s)
- Artur Schuller
- Christian Doppler Laboratory for Production of Next-level Biopharmaceuticals in E. coli, Department of Biotechnology, University of Natural Resources and Life Sciences, Muthgasse 18, 1190, Vienna, Austria
| | - Monika Cserjan-Puschmann
- Christian Doppler Laboratory for Production of Next-level Biopharmaceuticals in E. coli, Department of Biotechnology, University of Natural Resources and Life Sciences, Muthgasse 18, 1190, Vienna, Austria.
| | - Christopher Tauer
- Christian Doppler Laboratory for Production of Next-level Biopharmaceuticals in E. coli, Department of Biotechnology, University of Natural Resources and Life Sciences, Muthgasse 18, 1190, Vienna, Austria
| | - Johanna Jarmer
- Boehringer Ingelheim RCV GmbH & Co KG, Dr.-Boehringer-Gasse 5-11, 1120, Vienna, Austria
| | - Martin Wagenknecht
- Boehringer Ingelheim RCV GmbH & Co KG, Dr.-Boehringer-Gasse 5-11, 1120, Vienna, Austria
| | - Daniela Reinisch
- Boehringer Ingelheim RCV GmbH & Co KG, Dr.-Boehringer-Gasse 5-11, 1120, Vienna, Austria
| | - Reingard Grabherr
- Christian Doppler Laboratory for Production of Next-level Biopharmaceuticals in E. coli, Department of Biotechnology, University of Natural Resources and Life Sciences, Muthgasse 18, 1190, Vienna, Austria
| | - Gerald Striedner
- Christian Doppler Laboratory for Production of Next-level Biopharmaceuticals in E. coli, Department of Biotechnology, University of Natural Resources and Life Sciences, Muthgasse 18, 1190, Vienna, Austria
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Phillips R, Belliveau NM, Chure G, Garcia HG, Razo-Mejia M, Scholes C. Figure 1 Theory Meets Figure 2 Experiments in the Study of Gene Expression. Annu Rev Biophys 2020; 48:121-163. [PMID: 31084583 DOI: 10.1146/annurev-biophys-052118-115525] [Citation(s) in RCA: 35] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
It is tempting to believe that we now own the genome. The ability to read and rewrite it at will has ushered in a stunning period in the history of science. Nonetheless, there is an Achilles' heel exposed by all of the genomic data that has accrued: We still do not know how to interpret them. Many genes are subject to sophisticated programs of transcriptional regulation, mediated by DNA sequences that harbor binding sites for transcription factors, which can up- or down-regulate gene expression depending upon environmental conditions. This gives rise to an input-output function describing how the level of expression depends upon the parameters of the regulated gene-for instance, on the number and type of binding sites in its regulatory sequence. In recent years, the ability to make precision measurements of expression, coupled with the ability to make increasingly sophisticated theoretical predictions, has enabled an explicit dialogue between theory and experiment that holds the promise of covering this genomic Achilles' heel. The goal is to reach a predictive understanding of transcriptional regulation that makes it possible to calculate gene expression levels from DNA regulatory sequence. This review focuses on the canonical simple repression motif to ask how well the models that have been used to characterize it actually work. We consider a hierarchy of increasingly sophisticated experiments in which the minimal parameter set learned at one level is applied to make quantitative predictions at the next. We show that these careful quantitative dissections provide a template for a predictive understanding of the many more complex regulatory arrangements found across all domains of life.
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Affiliation(s)
- Rob Phillips
- Department of Physics, California Institute of Technology, Pasadena, California, USA; .,Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, California, USA
| | - Nathan M Belliveau
- Howard Hughes Medical Institute, Chevy Chase, Maryland 20815, USA.,Department of Biology, University of Washington, Seattle, Washington 98195, USA
| | - Griffin Chure
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, California, USA
| | - Hernan G Garcia
- Department of Molecular & Cell Biology, Department of Physics, Biophysics Graduate Group, and Institute for Quantitative Biosciences-QB3, University of California, Berkeley, California, USA
| | - Manuel Razo-Mejia
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, California, USA
| | - Clarissa Scholes
- Department of Systems Biology, Harvard Medical School, Boston, Massachusetts, USA
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47
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Landberg J, Mundhada H, Nielsen AT. An autoinducible trp-T7 expression system for production of proteins and biochemicals in Escherichia coli. Biotechnol Bioeng 2020; 117:1513-1524. [PMID: 32022248 PMCID: PMC7186829 DOI: 10.1002/bit.27297] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2019] [Revised: 01/11/2020] [Accepted: 02/03/2020] [Indexed: 12/19/2022]
Abstract
Inducible expression systems can be applied to control the expression of proteins or biochemical pathways in cell factories. However, several of the established systems require the addition of expensive inducers, making them unfeasible for large‐scale production. Here, we establish a genome integrated trp‐T7 expression system where tryptophan can be used to control the induction of a gene or a metabolic pathway. We show that the initiation of gene expression from low‐ and high‐copy vectors can be tuned by varying the initial concentration of tryptophan or yeast extract, and that expression is tightly regulated and homogenous when compared with the commonly used lac‐T7 system. Finally, we apply the trp‐T7 expression system for the production of l‐serine, where we reach titers of 26 g/L in fed‐batch fermentation.
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Affiliation(s)
- Jenny Landberg
- The Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, Kongens Lyngby, Denmark
| | - Hemanshu Mundhada
- The Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, Kongens Lyngby, Denmark.,CysBio ApS, Hørsholm, Denmark
| | - Alex Toftgaard Nielsen
- The Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, Kongens Lyngby, Denmark
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48
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Chen YL, Guo DH, Li QZ. An energy model for recognizing the prokaryotic promoters based on molecular structure. Genomics 2019; 112:2072-2079. [PMID: 31809797 DOI: 10.1016/j.ygeno.2019.12.001] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2019] [Revised: 11/06/2019] [Accepted: 12/01/2019] [Indexed: 11/19/2022]
Abstract
Promoter is an important functional elements of DNA sequences, which is in charge of gene transcription initiation. Recognizing promoter have important help for understanding the relative life phenomena. Based on the concept that promoter is mainly determined by its sequence and structure, a novel statistical physics model for predicting promoter in Escherichia coli K-12 is proposed. The total energies of DNA local structure of sequence segments in the three benchmark promoter sequence datasets, the sole prediction parameter, are calculated by using principles from statistical physics and information theory. The better results are obtained. And a web-server PhysMPrePro for predicting promoter is established at http://202.207.14.87:8032/bioinformation/PhysMPrePro/index.asp, so that other scientists can easily get their desired results by our web-server.
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Affiliation(s)
- Ying-Li Chen
- Laboratory of Theoretical Biophysics, School of Physical Science and Technology, Inner Mongolia University, Hohhot 010021, China; The State key Laboratory of Reproductive Regulation and Breeding of Grassland Livestock, Inner Mongolia University, Hohhot 010070, China.
| | - Dong-Hua Guo
- Laboratory of Theoretical Biophysics, School of Physical Science and Technology, Inner Mongolia University, Hohhot 010021, China
| | - Qian-Zhong Li
- Laboratory of Theoretical Biophysics, School of Physical Science and Technology, Inner Mongolia University, Hohhot 010021, China; The State key Laboratory of Reproductive Regulation and Breeding of Grassland Livestock, Inner Mongolia University, Hohhot 010070, China.
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49
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Xu W, Klumbys E, Ang EL, Zhao H. Emerging molecular biology tools and strategies for engineering natural product biosynthesis. Metab Eng Commun 2019; 10:e00108. [PMID: 32547925 PMCID: PMC7283510 DOI: 10.1016/j.mec.2019.e00108] [Citation(s) in RCA: 31] [Impact Index Per Article: 6.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2019] [Revised: 11/05/2019] [Accepted: 11/05/2019] [Indexed: 02/08/2023] Open
Abstract
Natural products and their related derivatives play a significant role in drug discovery and have been the inspiration for the design of numerous synthetic bioactive compounds. With recent advances in molecular biology, numerous engineering tools and strategies were established to accelerate natural product synthesis in both academic and industrial settings. However, many obstacles in natural product biosynthesis still exist. For example, the native pathways are not appropriate for research or production; the key enzymes do not have enough activity; the native hosts are not suitable for high-level production. Emerging molecular biology tools and strategies have been developed to not only improve natural product titers but also generate novel bioactive compounds. In this review, we will discuss these emerging molecular biology tools and strategies at three main levels: enzyme level, pathway level, and genome level, and highlight their applications in natural product discovery and development.
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Affiliation(s)
- Wei Xu
- Institute of Chemical and Engineering Sciences, Agency for Science, Technology, and Research, Singapore
| | - Evaldas Klumbys
- Institute of Chemical and Engineering Sciences, Agency for Science, Technology, and Research, Singapore
| | - Ee Lui Ang
- Institute of Chemical and Engineering Sciences, Agency for Science, Technology, and Research, Singapore
| | - Huimin Zhao
- Institute of Chemical and Engineering Sciences, Agency for Science, Technology, and Research, Singapore.,Department of Chemical and Biomolecular Engineering, University of Illinois at Urbana-Champaign, Urbana, IL, 61801, USA
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50
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Promoter engineering strategies for the overproduction of valuable metabolites in microbes. Appl Microbiol Biotechnol 2019; 103:8725-8736. [PMID: 31630238 DOI: 10.1007/s00253-019-10172-y] [Citation(s) in RCA: 48] [Impact Index Per Article: 9.6] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2019] [Revised: 10/04/2019] [Accepted: 10/08/2019] [Indexed: 12/16/2022]
Abstract
Promoter engineering is an enabling technology in metabolic engineering and synthetic biology. As an indispensable part of synthetic biology, the promoter is a key factor in regulating genetic circuits and in coordinating multi-gene biosynthetic pathways. In this review, we summarized the recent progresses in promoter engineering in microbes. Specifically, the endogenous promoters are firstly discussed, followed by the statement of the influence of nucleotides exchange on the strength of promoters explored by site-selective mutagenesis. We then introduced the promoter libraries with a wide range of strength, which are constructed focusing on core promoter regions and upstream activating sequences by rational designs. Finally, the application of promoter libraries in the optimization of multi-gene metabolic pathways for high-yield production of metabolites was illustrated with a couple of recent examples.
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