1
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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. [PMID: 38997112 DOI: 10.1021/acs.biochem.4c00012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [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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2
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Deal C, De Wannemaeker L, De Mey M. Towards a rational approach to promoter engineering: understanding the complexity of transcription initiation in prokaryotes. FEMS Microbiol Rev 2024; 48:fuae004. [PMID: 38383636 PMCID: PMC10911233 DOI: 10.1093/femsre/fuae004] [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: 08/31/2023] [Revised: 01/29/2024] [Accepted: 02/20/2024] [Indexed: 02/23/2024] Open
Abstract
Promoter sequences are important genetic control elements. Through their interaction with RNA polymerase they determine transcription strength and specificity, thereby regulating the first step in gene expression. Consequently, they can be targeted as elements to control predictability and tuneability of a genetic circuit, which is essential in applications such as the development of robust microbial cell factories. This review considers the promoter elements implicated in the three stages of transcription initiation, detailing the complex interplay of sequence-specific interactions that are involved, and highlighting that DNA sequence features beyond the core promoter elements work in a combinatorial manner to determine transcriptional strength. In particular, we emphasize that, aside from promoter recognition, transcription initiation is also defined by the kinetics of open complex formation and promoter escape, which are also known to be highly sequence specific. Significantly, we focus on how insights into these interactions can be manipulated to lay the foundation for a more rational approach to promoter engineering.
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Affiliation(s)
- Cara Deal
- Centre for Synthetic Biology, Ghent University. Coupure Links 653, BE-9000 Ghent, Belgium
| | - Lien De Wannemaeker
- Centre for Synthetic Biology, Ghent University. Coupure Links 653, BE-9000 Ghent, Belgium
| | - Marjan De Mey
- Centre for Synthetic Biology, Ghent University. Coupure Links 653, BE-9000 Ghent, Belgium
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3
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Zeng M, Sarker B, Howitz N, Shah I, Andrews LB. Synthetic Homoserine Lactone Sensors for Gram-Positive Bacillus subtilis Using LuxR-Type Regulators. ACS Synth Biol 2024; 13:282-299. [PMID: 38079538 PMCID: PMC10805106 DOI: 10.1021/acssynbio.3c00504] [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: 08/18/2023] [Revised: 10/11/2023] [Accepted: 10/18/2023] [Indexed: 01/23/2024]
Abstract
A universal biochemical signal for bacterial cell-cell communication could facilitate programming dynamic responses in diverse bacterial consortia. However, the classical quorum sensing paradigm is that Gram-negative and Gram-positive bacteria generally communicate via homoserine lactones (HSLs) or oligopeptide molecular signals, respectively, to elicit population responses. Here, we create synthetic HSL sensors for Gram-positive Bacillus subtilis 168 using allosteric LuxR-type regulators (RpaR, LuxR, RhlR, and CinR) and synthetic promoters. Promoters were combinatorially designed from different sequence elements (-35, -16, -10, and transcriptional start regions). We quantified the effects of these combinatorial promoters on sensor activity and determined how regulator expression affects its activation, achieving up to 293-fold activation. Using the statistical design of experiments, we identified significant effects of promoter regions and pairwise interactions on sensor activity, which helped to understand the sequence-function relationships for synthetic promoter design. We present the first known set of functional HSL sensors (≥20-fold dynamic range) in B. subtilis for four different HSL chemical signals: p-coumaroyl-HSL, 3-oxohexanoyl-HSL, n-butyryl-HSL, and n-(3-hydroxytetradecanoyl)-HSL. This set of synthetic HSL sensors for a Gram-positive bacterium can pave the way for designable interspecies communication within microbial consortia.
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Affiliation(s)
- Min Zeng
- Department
of Chemical Engineering, University of Massachusetts
Amherst, Amherst, Massachusetts 01003, United States
| | - Biprodev Sarker
- Department
of Chemical Engineering, University of Massachusetts
Amherst, Amherst, Massachusetts 01003, United States
| | - Nathaniel Howitz
- Department
of Chemical Engineering, University of Massachusetts
Amherst, Amherst, Massachusetts 01003, United States
| | - Ishita Shah
- Department
of Chemical Engineering, University of Massachusetts
Amherst, Amherst, Massachusetts 01003, United States
| | - Lauren B. Andrews
- Department
of Chemical Engineering, University of Massachusetts
Amherst, Amherst, Massachusetts 01003, United States
- Molecular
and Cellular Biology Graduate Program, University
of Massachusetts Amherst, Amherst, Massachusetts 01003, United States
- Biotechnology
Training Program, University of Massachusetts
Amherst, Amherst, Massachusetts 01003, United States
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4
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Turecka K, Firczuk M, Werel W. Alteration of the -35 and -10 sequences and deletion the upstream sequence of the -35 region of the promoter A1 of the phage T7 in dsDNA confirm the contribution of non-specific interactions with E. coli RNA polymerase to the transcription initiation process. Front Mol Biosci 2024; 10:1335409. [PMID: 38259683 PMCID: PMC10800924 DOI: 10.3389/fmolb.2023.1335409] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2023] [Accepted: 12/18/2023] [Indexed: 01/24/2024] Open
Abstract
Transcription initiation is a multi-step process, in which the RNA polymerase holoenzyme binds to the specific promoter sequences to form a closed complex, which, through intermediate stages, isomerizes into an open complex capable of initiating the productive phase of transcription. The aim of this work was to determine the contribution of the -10 and -35 regions of the promoter, as well as the role of non-specific interactions, in the binding of RNA polymerase and the formation of an active initiation complex capable of transcription. Therefore, fragments of promoter DNA, derived from the strong promoter A1 of the phage T7, containing completely and partially altered elements -35 and -10, and devoid of an upstream region, were constructed using genetic engineering methods. Functional analyses of modified promoter fragments were carried out, checking their ability to form binary complexes with Escherichia coli RNA polymerase (RNAP) and the efficiency of converting binary complexes into triple complexes characteristic of the productive phase of transcription. The obtained results suggest that, in relation to the A1 promoter of the T7 phage, the most important role of the -35 region is carrying the open complex through the next phases of transcription initiation. The weakening of specific impacts within the region -35 is a reason for the defect associated with the transformation of the open complex, formed by a DNA fragment containing the completely altered -35 region, into elongation and the impairment of RNA synthesis. This leads to breaking contacts with the RNA polymerase holoenzyme, and destabilization and disintegration of the complex in the initial phase of productive transcription. This confirms the hypothesis of the so-called stressed intermediate state associated with the stage of transition from the open complex to the elongation complex. The experiments carried out in this work confirm also that the process of promoter localization and recognition, as well as the formation of binary complexes, is sequential in nature, and that the region located upstream of the -35 hexamer, and the hexamer itself, plays here an additive role.
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Affiliation(s)
- Katarzyna Turecka
- Department of Pharmaceutical Microbiology, Faculty of Pharmacy, Medical University of Gdańsk, Gdańsk, Poland
| | | | - Władysław Werel
- Department of Pharmaceutical Microbiology, Faculty of Pharmacy, Medical University of Gdańsk, Gdańsk, Poland
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5
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Huttanus HM, Triola EKH, Velasquez-Guzman JC, Shin SM, Granja-Travez RS, Singh A, Dale T, Jha RK. Targeted mutagenesis and high-throughput screening of diversified gene and promoter libraries for isolating gain-of-function mutations. Front Bioeng Biotechnol 2023; 11:1202388. [PMID: 37545889 PMCID: PMC10400447 DOI: 10.3389/fbioe.2023.1202388] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2023] [Accepted: 06/25/2023] [Indexed: 08/08/2023] Open
Abstract
Targeted mutagenesis of a promoter or gene is essential for attaining new functions in microbial and protein engineering efforts. In the burgeoning field of synthetic biology, heterologous genes are expressed in new host organisms. Similarly, natural or designed proteins are mutagenized at targeted positions and screened for gain-of-function mutations. Here, we describe methods to attain complete randomization or controlled mutations in promoters or genes. Combinatorial libraries of one hundred thousands to tens of millions of variants can be created using commercially synthesized oligonucleotides, simply by performing two rounds of polymerase chain reactions. With a suitably engineered reporter in a whole cell, these libraries can be screened rapidly by performing fluorescence-activated cell sorting (FACS). Within a few rounds of positive and negative sorting based on the response from the reporter, the library can rapidly converge to a few optimal or extremely rare variants with desired phenotypes. Library construction, transformation and sequence verification takes 6-9 days and requires only basic molecular biology lab experience. Screening the library by FACS takes 3-5 days and requires training for the specific cytometer used. Further steps after sorting, including colony picking, sequencing, verification, and characterization of individual clones may take longer, depending on number of clones and required experiments.
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Affiliation(s)
- Herbert M. Huttanus
- Bioscience Division, Los Alamos National Laboratory, Los Alamos, NM, United States
- Agile BioFoundry, Emeryville, CA, United States
| | - Ellin-Kristina H. Triola
- Bioscience Division, Los Alamos National Laboratory, Los Alamos, NM, United States
- Agile BioFoundry, Emeryville, CA, United States
| | - Jeanette C. Velasquez-Guzman
- Bioscience Division, Los Alamos National Laboratory, Los Alamos, NM, United States
- Agile BioFoundry, Emeryville, CA, United States
| | - Sang-Min Shin
- Bioscience Division, Los Alamos National Laboratory, Los Alamos, NM, United States
- BOTTLE Consortium, Golden, CO, United States
| | - Rommel S. Granja-Travez
- Bioscience Division, Los Alamos National Laboratory, Los Alamos, NM, United States
- BOTTLE Consortium, Golden, CO, United States
| | - Anmoldeep Singh
- Bioscience Division, Los Alamos National Laboratory, Los Alamos, NM, United States
| | - Taraka Dale
- Bioscience Division, Los Alamos National Laboratory, Los Alamos, NM, United States
- Agile BioFoundry, Emeryville, CA, United States
- BOTTLE Consortium, Golden, CO, United States
| | - Ramesh K. Jha
- Bioscience Division, Los Alamos National Laboratory, Los Alamos, NM, United States
- Agile BioFoundry, Emeryville, CA, United States
- BOTTLE Consortium, Golden, CO, United States
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6
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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] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [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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7
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Modulating binding affinity, specificity and configurations by multivalent interactions. Biophys J 2022; 121:1868-1880. [PMID: 35450827 DOI: 10.1016/j.bpj.2022.04.017] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2021] [Revised: 10/20/2021] [Accepted: 04/14/2022] [Indexed: 11/22/2022] Open
Abstract
Biological functions of proteins rely on their specific interactions with binding partners. Many proteins contain multiple domains, which can bind to their targets that often have more than one binding site, resulting in multivalent interactions. While it has been shown that multivalent interactions play an crucial role in modulating binding affinity and specificity, other potential effects of multivalent interactions are less explored. Here, we developed a broadly applicable transfer matrix formalism and used it to investigate the binding of two-domain ligands to targets with multiple binding sites. We show that 1) ligands with two specific binding domains can drastically boost both the binding affinity and specificity and down-shift the working concentration range, compared to single-domain ligands, 2) the presence of a positive domain-domain cooperativity or containing a non-specific binding domain can down-shift the working concentration range of ligands by increasing the binding affinity without compromising the binding specificity, 3) the configuration of the bound ligands has a strong concentration dependence, providing important insights into the physical origin of phase-separation processes taking place in living cells. In line with previous studies, our results suggest that multivalent interactions are utilized by cells for highly efficient regulation of target binding involved in a diverse range of cellular processes such as signal transduction, gene transcription, antibody-antigen recognition.
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8
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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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9
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Lagator M, Sarikas S, Steinrueck M, Toledo-Aparicio D, Bollback JP, Guet CC, Tkačik G. Predicting bacterial promoter function and evolution from random sequences. eLife 2022; 11:64543. [PMID: 35080492 PMCID: PMC8791639 DOI: 10.7554/elife.64543] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2020] [Accepted: 01/09/2022] [Indexed: 12/12/2022] Open
Abstract
Predicting function from sequence is a central problem of biology. Currently, this is possible only locally in a narrow mutational neighborhood around a wildtype sequence rather than globally from any sequence. Using random mutant libraries, we developed a biophysical model that accounts for multiple features of σ70 binding bacterial promoters to predict constitutive gene expression levels from any sequence. We experimentally and theoretically estimated that 10–20% of random sequences lead to expression and ~80% of non-expressing sequences are one mutation away from a functional promoter. The potential for generating expression from random sequences is so pervasive that selection acts against σ70-RNA polymerase binding sites even within inter-genic, promoter-containing regions. This pervasiveness of σ70-binding sites implies that emergence of promoters is not the limiting step in gene regulatory evolution. Ultimately, the inclusion of novel features of promoter function into a mechanistic model enabled not only more accurate predictions of gene expression levels, but also identified that promoters evolve more rapidly than previously thought.
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Affiliation(s)
- Mato Lagator
- School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, United Kingdom.,Institute of Science and Technology Austria, Klosterneuburg, Austria
| | - Srdjan Sarikas
- Institute of Science and Technology Austria, Klosterneuburg, Austria.,Center for Physiology and Pharmacology, Medical University of Vienna, Klosterneuburg, Austria
| | | | | | - Jonathan P Bollback
- Institute of Integrative Biology, Functional and Comparative Genomics, University of Liverpool, Liverpool, United Kingdom
| | - Calin C Guet
- Institute of Science and Technology Austria, Klosterneuburg, Austria
| | - Gašper Tkačik
- Institute of Science and Technology Austria, Klosterneuburg, Austria
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10
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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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11
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Tietze L, Lale R. Importance of the 5' regulatory region to bacterial synthetic biology applications. Microb Biotechnol 2021; 14:2291-2315. [PMID: 34171170 PMCID: PMC8601185 DOI: 10.1111/1751-7915.13868] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2021] [Revised: 06/03/2021] [Accepted: 06/04/2021] [Indexed: 01/02/2023] Open
Abstract
The field of synthetic biology is evolving at a fast pace. It is advancing beyond single-gene alterations in single hosts to the logical design of complex circuits and the development of integrated synthetic genomes. Recent breakthroughs in deep learning, which is increasingly used in de novo assembly of DNA components with predictable effects, are also aiding the discipline. Despite advances in computing, the field is still reliant on the availability of pre-characterized DNA parts, whether natural or synthetic, to regulate gene expression in bacteria and make valuable compounds. In this review, we discuss the different bacterial synthetic biology methodologies employed in the creation of 5' regulatory regions - promoters, untranslated regions and 5'-end of coding sequences. We summarize methodologies and discuss their significance for each of the functional DNA components, and highlight the key advances made in bacterial engineering by concentrating on their flaws and strengths. We end the review by outlining the issues that the discipline may face in the near future.
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Affiliation(s)
- Lisa Tietze
- PhotoSynLabDepartment of BiotechnologyFaculty of Natural SciencesNorwegian University of Science and TechnologyTrondheimN‐7491Norway
| | - Rahmi Lale
- PhotoSynLabDepartment of BiotechnologyFaculty of Natural SciencesNorwegian University of Science and TechnologyTrondheimN‐7491Norway
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12
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Chowdhury D, Wang C, Lu A, Zhu H. Cis-Regulatory Logic Produces Gene-Expression Noise Describing Phenotypic Heterogeneity in Bacteria. Front Genet 2021; 12:698910. [PMID: 34650591 PMCID: PMC8506120 DOI: 10.3389/fgene.2021.698910] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2021] [Accepted: 08/31/2021] [Indexed: 12/04/2022] Open
Abstract
Gene transcriptional process is random. It occurs in bursts and follows single-molecular kinetics. Intermittent bursts are measured based on their frequency and size. They influence temporal fluctuations in the abundance of total mRNA and proteins by generating distinct transcriptional variations referred to as “noise”. Noisy expression induces uncertainty because the association between transcriptional variation and the extent of gene expression fluctuation is ambiguous. The promoter architecture and remote interference of different cis-regulatory elements are the crucial determinants of noise, which is reflected in phenotypic heterogeneity. An alternative perspective considers that cellular parameters dictating genome-wide transcriptional kinetics follow a universal pattern. Research on noise and systematic perturbations of promoter sequences reinforces that both gene-specific and genome-wide regulation occur across species ranging from bacteria and yeast to animal cells. Thus, deciphering gene-expression noise is essential across different genomics applications. Amidst the mounting conflict, it is imperative to reconsider the scope, progression, and rational construction of diversified viewpoints underlying the origin of the noise. Here, we have established an indication connecting noise, gene expression variations, and bacterial phenotypic variability. This review will enhance the understanding of gene-expression noise in various scientific contexts and applications.
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Affiliation(s)
- Debajyoti Chowdhury
- HKBU Institute for Research and Continuing Education, Shenzhen, China.,Computational Medicine Lab, Hong Kong Baptist University, Hong Kong, China.,Institute of Integrated Bioinformedicine and Translational Sciences, School of Chinese Medicine, Hong Kong Baptist University, Hong Kong, China
| | - Chao Wang
- HKBU Institute for Research and Continuing Education, Shenzhen, China.,Institute of Integrated Bioinformedicine and Translational Sciences, School of Chinese Medicine, Hong Kong Baptist University, Hong Kong, China
| | - Aiping Lu
- Computational Medicine Lab, Hong Kong Baptist University, Hong Kong, China.,Institute of Integrated Bioinformedicine and Translational Sciences, School of Chinese Medicine, Hong Kong Baptist University, Hong Kong, China
| | - Hailong Zhu
- HKBU Institute for Research and Continuing Education, Shenzhen, China.,Computational Medicine Lab, Hong Kong Baptist University, Hong Kong, China.,Institute of Integrated Bioinformedicine and Translational Sciences, School of Chinese Medicine, Hong Kong Baptist University, Hong Kong, China
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13
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Zrimec J, Buric F, Kokina M, Garcia V, Zelezniak A. Learning the Regulatory Code of Gene Expression. Front Mol Biosci 2021; 8:673363. [PMID: 34179082 PMCID: PMC8223075 DOI: 10.3389/fmolb.2021.673363] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2021] [Accepted: 05/24/2021] [Indexed: 11/13/2022] Open
Abstract
Data-driven machine learning is the method of choice for predicting molecular phenotypes from nucleotide sequence, modeling gene expression events including protein-DNA binding, chromatin states as well as mRNA and protein levels. Deep neural networks automatically learn informative sequence representations and interpreting them enables us to improve our understanding of the regulatory code governing gene expression. Here, we review the latest developments that apply shallow or deep learning to quantify molecular phenotypes and decode the cis-regulatory grammar from prokaryotic and eukaryotic sequencing data. Our approach is to build from the ground up, first focusing on the initiating protein-DNA interactions, then specific coding and non-coding regions, and finally on advances that combine multiple parts of the gene and mRNA regulatory structures, achieving unprecedented performance. We thus provide a quantitative view of gene expression regulation from nucleotide sequence, concluding with an information-centric overview of the central dogma of molecular biology.
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Affiliation(s)
- Jan Zrimec
- Department of Biology and Biological Engineering, Chalmers University of Technology, Gothenburg, Sweden
| | - Filip Buric
- Department of Biology and Biological Engineering, Chalmers University of Technology, Gothenburg, Sweden
| | - Mariia Kokina
- Department of Biology and Biological Engineering, Chalmers University of Technology, Gothenburg, Sweden
- Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, Kongens Lyngby, Denmark
| | - Victor Garcia
- School of Life Sciences and Facility Management, Zurich University of Applied Sciences, Wädenswil, Switzerland
| | - Aleksej Zelezniak
- Department of Biology and Biological Engineering, Chalmers University of Technology, Gothenburg, Sweden
- Science for Life Laboratory, Stockholm, Sweden
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14
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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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15
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Erlendsson S, Teilum K. Binding Revisited-Avidity in Cellular Function and Signaling. Front Mol Biosci 2021; 7:615565. [PMID: 33521057 PMCID: PMC7841115 DOI: 10.3389/fmolb.2020.615565] [Citation(s) in RCA: 44] [Impact Index Per Article: 14.7] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2020] [Accepted: 12/09/2020] [Indexed: 12/16/2022] Open
Abstract
When characterizing biomolecular interactions, avidity, is an umbrella term used to describe the accumulated strength of multiple specific and unspecific interactions between two or more interaction partners. In contrast to the affinity, which is often sufficient to describe monovalent interactions in solution and where the binding strength can be accurately determined by considering only the relationship between the microscopic association and dissociation rates, the avidity is a phenomenological macroscopic parameter linked to several microscopic events. Avidity also covers potential effects of reduced dimensionality and/or hindered diffusion observed at or near surfaces e.g., at the cell membrane. Avidity is often used to describe the discrepancy or the "extra on top" when cellular interactions display binding that are several orders of magnitude stronger than those estimated in vitro. Here we review the principles and theoretical frameworks governing avidity in biological systems and the methods for predicting and simulating avidity. While the avidity and effects thereof are well-understood for extracellular biomolecular interactions, we present here examples of, and discuss how, avidity and the underlying kinetics influences intracellular signaling processes.
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Affiliation(s)
- Simon Erlendsson
- Structural Studies Division, Medical Research Council Laboratory of Molecular Biology, Cambridge, United Kingdom.,Structural Molecular Biology Group, Novo Nordisk Foundation Centre for Protein Research, Faculty of Health and Medical Sciences University of Copenhagen, Copenhagen, Denmark
| | - Kaare Teilum
- Structural Biology and NMR Laboratory and the Linderstrøm-Lang Centre for Protein Science, Department of Biology, University of Copenhagen, Copenhagen, Denmark
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16
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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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17
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Zielinski DC, Patel A, Palsson BO. The Expanding Computational Toolbox for Engineering Microbial Phenotypes at the Genome Scale. Microorganisms 2020; 8:E2050. [PMID: 33371386 PMCID: PMC7767376 DOI: 10.3390/microorganisms8122050] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2020] [Revised: 12/07/2020] [Accepted: 12/16/2020] [Indexed: 02/06/2023] Open
Abstract
Microbial strains are being engineered for an increasingly diverse array of applications, from chemical production to human health. While traditional engineering disciplines are driven by predictive design tools, these tools have been difficult to build for biological design due to the complexity of biological systems and many unknowns of their quantitative behavior. However, due to many recent advances, the gap between design in biology and other engineering fields is closing. In this work, we discuss promising areas of development of computational tools for engineering microbial strains. We define five frontiers of active research: (1) Constraint-based modeling and metabolic network reconstruction, (2) Kinetics and thermodynamic modeling, (3) Protein structure analysis, (4) Genome sequence analysis, and (5) Regulatory network analysis. Experimental and machine learning drivers have enabled these methods to improve by leaps and bounds in both scope and accuracy. Modern strain design projects will require these tools to be comprehensively applied to the entire cell and efficiently integrated within a single workflow. We expect that these frontiers, enabled by the ongoing revolution of big data science, will drive forward more advanced and powerful strain engineering strategies.
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Affiliation(s)
- Daniel Craig Zielinski
- Department of Bioengineering, University of California, San Diego, San Diego, CA 92093, USA; (D.C.Z.); (A.P.)
| | - Arjun Patel
- Department of Bioengineering, University of California, San Diego, San Diego, CA 92093, USA; (D.C.Z.); (A.P.)
| | - Bernhard O. Palsson
- Department of Bioengineering, University of California, San Diego, San Diego, CA 92093, USA; (D.C.Z.); (A.P.)
- Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, 2800 Lyngby, Denmark
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18
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Imashimizu M, Tokunaga Y, Afek A, Takahashi H, Shimamoto N, Lukatsky DB. Control of Transcription Initiation by Biased Thermal Fluctuations on Repetitive Genomic Sequences. Biomolecules 2020; 10:biom10091299. [PMID: 32916947 PMCID: PMC7564750 DOI: 10.3390/biom10091299] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2020] [Revised: 08/23/2020] [Accepted: 09/04/2020] [Indexed: 12/12/2022] Open
Abstract
In the process of transcription initiation by RNA polymerase, promoter DNA sequences affect multiple reaction pathways determining the productivity of transcription. However, the question of how the molecular mechanism of transcription initiation depends on the sequence properties of promoter DNA remains poorly understood. Here, combining the statistical mechanical approach with high-throughput sequencing results, we characterize abortive transcription and pausing during transcription initiation by Escherichia coli RNA polymerase at a genome-wide level. Our results suggest that initially transcribed sequences, when enriched with thymine bases, contain the signal for inducing abortive transcription, whereas certain repetitive sequence elements embedded in promoter regions constitute the signal for inducing pausing. Both signals decrease the productivity of transcription initiation. Based on solution NMR and in vitro transcription measurements, we suggest that repetitive sequence elements within the promoter DNA modulate the nonlocal base pair stability of its double-stranded form. This stability profoundly influences the reaction coordinates of the productive initiation via pausing.
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Affiliation(s)
- Masahiko Imashimizu
- Cellular and Molecular Biotechnology Research Institute, National Institute of Advanced Industrial Science and Technology, Tokyo 135-0064, Japan;
- Correspondence: (M.I.); (D.B.L.); Tel.: +81-3-3599-8232 (M.I.); +972-8642-8370 (D.B.L.)
| | - Yuji Tokunaga
- Cellular and Molecular Biotechnology Research Institute, National Institute of Advanced Industrial Science and Technology, Tokyo 135-0064, Japan;
| | - Ariel Afek
- Center for Genomic and Computational Biology, Department of Biostatistics and Bioinformatics, Duke University, Durham, NC 27708, USA;
| | - Hiroki Takahashi
- Medical Mycology Research Center, Chiba University, Chiba 260-8673, Japan;
- Molecular Chirality Research Center, Chiba University, Chiba 263-8522, Japan
- Plant Molecular Science Center, Chiba University, Chiba 260-8675, Japan
| | - Nobuo Shimamoto
- National Institute of Genetics, Mishima, Shizuoka 411-8540, Japan;
| | - David B. Lukatsky
- Department of Chemistry, Ben-Gurion University of the Negev, Beer-Sheva 8410501, Israel
- Correspondence: (M.I.); (D.B.L.); Tel.: +81-3-3599-8232 (M.I.); +972-8642-8370 (D.B.L.)
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19
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Genome and sequence determinants governing the expression of horizontally acquired DNA in bacteria. ISME JOURNAL 2020; 14:2347-2357. [PMID: 32514119 PMCID: PMC7608860 DOI: 10.1038/s41396-020-0696-1] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/29/2019] [Revised: 05/22/2020] [Accepted: 05/28/2020] [Indexed: 01/23/2023]
Abstract
While horizontal gene transfer is prevalent across the biosphere, the regulatory features that enable expression and functionalization of foreign DNA remain poorly understood. Here, we combine high-throughput promoter activity measurements and large-scale genomic analysis of regulatory regions to investigate the cross-compatibility of regulatory elements (REs) in bacteria. Functional characterization of thousands of natural REs in three distinct bacterial species revealed distinct expression patterns according to RE and recipient phylogeny. Host capacity to activate foreign promoters was proportional to their genomic GC content, while many low GC regulatory elements were both broadly active and had more transcription start sites across hosts. The difference in expression capabilities could be explained by the influence of the host GC content on the stringency of the AT-rich canonical σ70 motif necessary for transcription initiation. We further confirm the generalizability of this model and find widespread GC content adaptation of the σ70 motif in a set of 1,545 genomes from all major bacterial phyla. Our analysis identifies a key mechanism by which the strength of the AT-rich σ70 motif relative to a host's genomic GC content governs the capacity for expression of acquired DNA. These findings shed light on regulatory adaptation in the context of evolving genomic composition.
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20
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Azpeitia E, Wagner A. Short Residence Times of DNA-Bound Transcription Factors Can Reduce Gene Expression Noise and Increase the Transmission of Information in a Gene Regulation System. Front Mol Biosci 2020; 7:67. [PMID: 32411721 PMCID: PMC7198700 DOI: 10.3389/fmolb.2020.00067] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2019] [Accepted: 03/25/2020] [Indexed: 12/14/2022] Open
Abstract
Gene expression noise is not just ubiquitous but also variable, and we still do not understand some of the most elementary factors that affect it. Among them is the residence time of a transcription factor (TF) on DNA, the mean time that a DNA-bound TF remains bound. Here, we use a stochastic model of transcriptional regulation to study how residence time affects the gene expression noise that arises when a TF induces gene expression. We find that the effect of residence time on gene expression noise depends on the TF’s concentration and its affinity to DNA, which determine the level of induction of the gene. At high levels of induction, residence time has no effect on gene expression noise. However, as the level of induction decreases, short residence times reduce gene expression noise. The reason is that fast on-off TF binding dynamics prevent long periods where proteins are predominantly synthesized or degraded, which can cause excessive fluctuations in gene expression. As a consequence, short residence times can help a gene regulation system acquire information about the cellular environment it operates in. Our predictions are consistent with the observation that experimentally measured residence times are usually modest and lie between seconds to minutes.
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Affiliation(s)
- Eugenio Azpeitia
- Department of Evolutionary Biology and Environmental Studies, University of Zürich, Zurich, Switzerland.,Swiss Institute of Bioinformatics, Lausanne, Switzerland.,Centro de Ciencias Matemáticas, UNAM, Morelia, Mexico
| | - Andreas Wagner
- Department of Evolutionary Biology and Environmental Studies, University of Zürich, Zurich, Switzerland.,Swiss Institute of Bioinformatics, Lausanne, Switzerland.,Santa Fe Institute, Santa Fe, NM, United States
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21
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Han L, Chen Q, Lin Q, Cheng J, Zhou L, Liu Z, Guo J, Zhang L, Cui W, Zhou Z. Realization of Robust and Precise Regulation of Gene Expression by Multiple Sigma Recognizable Artificial Promoters. Front Bioeng Biotechnol 2020; 8:92. [PMID: 32140461 PMCID: PMC7042180 DOI: 10.3389/fbioe.2020.00092] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2019] [Accepted: 01/31/2020] [Indexed: 01/28/2023] Open
Abstract
Precise regulation of gene expression is fundamental for tailor-made gene circuit design in synthetic biology. Current strategies for this type of development are mainly based on directed evolution beginning with a native promoter template. The performances of engineered promoters are usually limited by the growth phase because only one promoter is recognized by one type of sigma factor (σ). Here, we constructed multiple-σ recognizable artificial hybrid promoters (AHPs) composed of tandems of dual and triple natural minimal promoters (NMPs). These NMPs, which use σA, σH and σW, had stable functions in different growth phases. The functions of these NMPs resulted from an effect called transcription compensation, in which AHPs sequentially use one type of σ in the corresponding growth phase. The strength of the AHPs was influenced by the combinatorial order of each NMP and the length of the spacers between the NMPs. More importantly, the output of the precise regulation was achieved by equipping AHPs with synthetic ribosome binding sites and by redesigning them for induced systems. This strategy might offer promising applications to rationally design robust synthetic promoters in diverse chassis to spur the construction of more complex gene circuits, which will further the development of synthetic biology.
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Affiliation(s)
- Laichuang Han
- Key Laboratory of Industrial Biotechnology, School of Biotechnology, Jiangnan University, Wuxi, China
| | - Qiaoqing Chen
- Key Laboratory of Industrial Biotechnology, School of Biotechnology, Jiangnan University, Wuxi, China
| | - Qiao Lin
- Key Laboratory of Industrial Biotechnology, School of Biotechnology, Jiangnan University, Wuxi, China
| | - Jintao Cheng
- Key Laboratory of Industrial Biotechnology, School of Biotechnology, Jiangnan University, Wuxi, China
| | - Li Zhou
- Key Laboratory of Industrial Biotechnology, School of Biotechnology, Jiangnan University, Wuxi, China
| | - Zhongmei Liu
- Key Laboratory of Industrial Biotechnology, School of Biotechnology, Jiangnan University, Wuxi, China
| | - Junling Guo
- Key Laboratory of Industrial Biotechnology, School of Biotechnology, Jiangnan University, Wuxi, China
| | - Linpei Zhang
- Key Laboratory of Industrial Biotechnology, School of Biotechnology, Jiangnan University, Wuxi, China
| | - Wenjing Cui
- Key Laboratory of Industrial Biotechnology, School of Biotechnology, Jiangnan University, Wuxi, China
| | - Zhemin Zhou
- Key Laboratory of Industrial Biotechnology, School of Biotechnology, Jiangnan University, Wuxi, China
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