1
|
Yue XJ, Wang JR, Zhao JN, Pan Z, Li YZ. Determination of the chromosomal position effects for plug-and-play application in the Myxococcus xanthus chassis cells. Synth Syst Biotechnol 2024; 9:540-548. [PMID: 38680947 PMCID: PMC11046052 DOI: 10.1016/j.synbio.2024.04.007] [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: 11/27/2023] [Revised: 03/30/2024] [Accepted: 04/08/2024] [Indexed: 05/01/2024] Open
Abstract
The chromosomal position effect can significantly affect the transgene expression, which may provide an efficient strategy for the inauguration of alien genes in new hosts, but has been less explored rationally. The bacterium Myxococcus xanthus harbors a large circular high-GC genome, and the position effect in this chassis may result in a thousand-fold expression variation of alien natural products. In this study, we conducted transposon insertion at TA sites on the M. xanthus genome, and used enrichment and dilution indexes to respectively appraise high and low expression potentials of alien genes at insertion sites. The enrichment sites are characteristically distributed along the genome, and the dilution sites are overlapped well with the horizontal transfer genes. We experimentally demonstrated the enrichment sites as high expression integration sites (HEISs), and the dilution sites unsuitable for gene integration expression. This work highlights that HEISs are the plug-and-play sites for efficient expression of integrated genes.
Collapse
Affiliation(s)
- Xin-jing Yue
- State Key Laboratory of Microbial Technology, Institute of Microbial Technology, Shandong University, Qingdao, PR China
| | - Jia-rui Wang
- State Key Laboratory of Microbial Technology, Institute of Microbial Technology, Shandong University, Qingdao, PR China
| | - Jun-ning Zhao
- State Key Laboratory of Microbial Technology, Institute of Microbial Technology, Shandong University, Qingdao, PR China
| | - Zhuo Pan
- State Key Laboratory of Microbial Technology, Institute of Microbial Technology, Shandong University, Qingdao, PR China
| | - Yue-zhong Li
- State Key Laboratory of Microbial Technology, Institute of Microbial Technology, Shandong University, Qingdao, PR China
| |
Collapse
|
2
|
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.
Collapse
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
| |
Collapse
|
3
|
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.
Collapse
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
| |
Collapse
|
4
|
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.
Collapse
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
| |
Collapse
|
5
|
Saunders SH, Ahmed AM. ORBIT for E. coli: kilobase-scale oligonucleotide recombineering at high throughput and high efficiency. Nucleic Acids Res 2024; 52:e43. [PMID: 38587185 PMCID: PMC11077079 DOI: 10.1093/nar/gkae227] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2023] [Revised: 02/28/2024] [Accepted: 03/19/2024] [Indexed: 04/09/2024] Open
Abstract
Microbiology and synthetic biology depend on reverse genetic approaches to manipulate bacterial genomes; however, existing methods require molecular biology to generate genomic homology, suffer from low efficiency, and are not easily scaled to high throughput. To overcome these limitations, we developed a system for creating kilobase-scale genomic modifications that uses DNA oligonucleotides to direct the integration of a non-replicating plasmid. This method, Oligonucleotide Recombineering followed by Bxb-1 Integrase Targeting (ORBIT) was pioneered in Mycobacteria, and here we adapt and expand it for Escherichia coli. Our redesigned plasmid toolkit for oligonucleotide recombineering achieved significantly higher efficiency than λ Red double-stranded DNA recombineering and enabled precise, stable knockouts (≤134 kb) and integrations (≤11 kb) of various sizes. Additionally, we constructed multi-mutants in a single transformation, using orthogonal attachment sites. At high throughput, we used pools of targeting oligonucleotides to knock out nearly all known transcription factor and small RNA genes, yielding accurate, genome-wide, single mutant libraries. By counting genomic barcodes, we also show ORBIT libraries can scale to thousands of unique members (>30k). This work demonstrates that ORBIT for E. coli is a flexible reverse genetic system that facilitates rapid construction of complex strains and readily scales to create sophisticated mutant libraries.
Collapse
Affiliation(s)
- Scott H Saunders
- Green Center for Systems Biology - Lyda Hill Department of Bioinformatics, University of Texas Southwestern Medical Center, Dallas, TX 75320, USA
| | - Ayesha M Ahmed
- Green Center for Systems Biology - Lyda Hill Department of Bioinformatics, University of Texas Southwestern Medical Center, Dallas, TX 75320, USA
| |
Collapse
|
6
|
Park S, Kim M, Lee JW. Optimizing Nucleic Acid Delivery Systems through Barcode Technology. ACS Synth Biol 2024; 13:1006-1018. [PMID: 38526308 DOI: 10.1021/acssynbio.3c00602] [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] [Indexed: 03/26/2024]
Abstract
Conventional biological experiments often focus on in vitro assays because of the inherent limitations when handling multiple variables in vivo, including labor-intensive and time-consuming procedures. Often only a subset of samples demonstrating significant efficacy in the in vitro assays can be evaluated in vivo. Nonetheless, because of the low correlation between the in vitro and in vivo tests, evaluation of the variables under examination in vivo and not solely in vitro is critical. An emerging approach to achieve high-throughput in vivo tests involves using a barcode system consisting of various nucleotide combinations. Unique barcodes for each variant enable the simultaneous testing of multiple entities, eliminating the need for separate individual tests. Subsequently, to identify crucial parameters, samples were collected and analyzed using barcode sequencing. This review explores the development of barcode design and its applications, including the evaluation of nucleic acid delivery systems and the optimization of gene expression in vivo.
Collapse
Affiliation(s)
- Soan Park
- Department of Chemical Engineering, Pohang University of Science and Technology, 77 CheongamRo, Gyeongbuk, 37673 NamGu, Pohang, Republic of Korea
| | - Mibang Kim
- Department of Chemical Engineering, Pohang University of Science and Technology, 77 CheongamRo, Gyeongbuk, 37673 NamGu, Pohang, Republic of Korea
| | - Jeong Wook Lee
- Department of Chemical Engineering, Pohang University of Science and Technology, 77 CheongamRo, Gyeongbuk, 37673 NamGu, Pohang, Republic of Korea
- School of Interdisciplinary Bioscience and Bioengineering, Pohang University of Science and Technology, 77 CheongamRo, Gyeongbuk, 37673 NamGu, Pohang, Republic of Korea
| |
Collapse
|
7
|
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.
Collapse
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
| |
Collapse
|
8
|
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.
Collapse
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
| |
Collapse
|
9
|
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.
Collapse
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
| |
Collapse
|
10
|
Okay S. Fine-Tuning Gene Expression in Bacteria by Synthetic Promoters. Methods Mol Biol 2024; 2844:179-195. [PMID: 39068340 DOI: 10.1007/978-1-0716-4063-0_12] [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] [Indexed: 07/30/2024]
Abstract
Promoters are key genetic elements in the initiation and regulation of gene expression. A limited number of natural promoters has been described for the control of gene expression in synthetic biology applications. Therefore, synthetic promoters have been developed to fine-tune the transcription for the desired amount of gene product. Mostly, synthetic promoters are characterized using promoter libraries that are constructed via mutagenesis of promoter sequences. The strength of promoters in the library is determined according to the expression of a reporter gene such as gfp encoding green fluorescent protein. Gene expression can be controlled using inducers. The majority of the studies on gram-negative bacteria are conducted using the expression system of the model organism Escherichia coli while that of the model organism Bacillus subtilis is mostly used in the studies on gram-positive bacteria. Additionally, synthetic promoters for the cyanobacteria, which are phototrophic microorganisms, are evaluated, especially using the model cyanobacterium Synechocystis sp. PCC 6803. Moreover, a variety of algorithms based on machine learning methods were developed to characterize the features of promoter elements. Some of these in silico models were verified using in vitro or in vivo experiments. Identification of novel synthetic promoters with improved features compared to natural ones contributes much to the synthetic biology approaches in terms of fine-tuning gene expression.
Collapse
Affiliation(s)
- Sezer Okay
- Department of Vaccine Technology, Vaccine Institute, Hacettepe University, Ankara, Türkiye
| |
Collapse
|
11
|
Zhang P, Wang H, Xu H, Wei L, Liu L, Hu Z, Wang X. Deep flanking sequence engineering for efficient promoter design using DeepSEED. Nat Commun 2023; 14:6309. [PMID: 37813854 PMCID: PMC10562447 DOI: 10.1038/s41467-023-41899-y] [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: 04/22/2023] [Accepted: 09/20/2023] [Indexed: 10/11/2023] Open
Abstract
Designing promoters with desirable properties is essential in synthetic biology. Human experts are skilled at identifying strong explicit patterns in small samples, while deep learning models excel at detecting implicit weak patterns in large datasets. Biologists have described the sequence patterns of promoters via transcription factor binding sites (TFBSs). However, the flanking sequences of cis-regulatory elements, have long been overlooked and often arbitrarily decided in promoter design. To address this limitation, we introduce DeepSEED, an AI-aided framework that efficiently designs synthetic promoters by combining expert knowledge with deep learning techniques. DeepSEED has demonstrated success in improving the properties of Escherichia coli constitutive, IPTG-inducible, and mammalian cell doxycycline (Dox)-inducible promoters. Furthermore, our results show that DeepSEED captures the implicit features in flanking sequences, such as k-mer frequencies and DNA shape features, which are crucial for determining promoter properties.
Collapse
Affiliation(s)
- Pengcheng Zhang
- Ministry of Education Key Laboratory of Bioinformatics; Center for Synthetic and Systems Biology; Bioinformatics Division, Beijing National Research Center for Information Science and Technology; Department of Automation, Tsinghua University, Beijing, China
| | - Haochen Wang
- Ministry of Education Key Laboratory of Bioinformatics; Center for Synthetic and Systems Biology; Bioinformatics Division, Beijing National Research Center for Information Science and Technology; Department of Automation, Tsinghua University, Beijing, China
| | - Hanwen Xu
- Ministry of Education Key Laboratory of Bioinformatics; Center for Synthetic and Systems Biology; Bioinformatics Division, Beijing National Research Center for Information Science and Technology; Department of Automation, Tsinghua University, Beijing, China
| | - Lei Wei
- Ministry of Education Key Laboratory of Bioinformatics; Center for Synthetic and Systems Biology; Bioinformatics Division, Beijing National Research Center for Information Science and Technology; Department of Automation, Tsinghua University, Beijing, China
| | - Liyang Liu
- Ministry of Education Key Laboratory of Bioinformatics; Center for Synthetic and Systems Biology; Bioinformatics Division, Beijing National Research Center for Information Science and Technology; Department of Automation, Tsinghua University, Beijing, China
| | - Zhirui Hu
- Center for Statistical Science, Tsinghua University, Beijing, China
| | - Xiaowo Wang
- Ministry of Education Key Laboratory of Bioinformatics; Center for Synthetic and Systems Biology; Bioinformatics Division, Beijing National Research Center for Information Science and Technology; Department of Automation, Tsinghua University, Beijing, China.
| |
Collapse
|
12
|
Scholz SA, Lindeboom CD, Freddolino PL. Genetic context effects can override canonical cis regulatory elements in Escherichia coli. Nucleic Acids Res 2022; 50:10360-10375. [PMID: 36134716 PMCID: PMC9561378 DOI: 10.1093/nar/gkac787] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2022] [Revised: 08/10/2022] [Accepted: 09/02/2022] [Indexed: 11/12/2022] Open
Abstract
Recent experiments have shown that in addition to control by cis regulatory elements, the local chromosomal context of a gene also has a profound impact on its transcription. Although this chromosome-position dependent expression variation has been empirically mapped at high-resolution, the underlying causes of the variation have not been elucidated. Here, we demonstrate that 1 kb of flanking, non-coding synthetic sequences with a low frequency of guanosine and cytosine (GC) can dramatically reduce reporter expression compared to neutral and high GC-content flanks in Escherichia coli. Natural and artificial genetic context can have a similarly strong effect on reporter expression, regardless of cell growth phase or medium. Despite the strong reduction in the maximal expression level from the fully-induced reporter, low GC synthetic flanks do not affect the time required to reach the maximal expression level after induction. Overall, we demonstrate key determinants of transcriptional propensity that appear to act as tunable modulators of transcription, independent of regulatory sequences such as the promoter. These findings provide insight into the regulation of naturally occurring genes and an independent control for optimizing expression of synthetic biology constructs.
Collapse
Affiliation(s)
- Scott A Scholz
- Department of Biological Chemistry, University of Michigan Medical School, Ann Arbor, MI, USA
| | - Chase D Lindeboom
- Department of Biological Chemistry, University of Michigan Medical School, Ann Arbor, MI, USA
| | - Peter L Freddolino
- Department of Biological Chemistry, University of Michigan Medical School, Ann Arbor, MI, USA
- Department of Computational Medicine and Bioinformatics, University of Michigan Medical School, Ann Arbor, MI, USA
| |
Collapse
|
13
|
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.
Collapse
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.
| |
Collapse
|
14
|
Kondratyeva L, Alekseenko I, Chernov I, Sverdlov E. Data Incompleteness May form a Hard-to-Overcome Barrier to Decoding Life's Mechanism. BIOLOGY 2022; 11:1208. [PMID: 36009835 PMCID: PMC9404739 DOI: 10.3390/biology11081208] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/19/2022] [Revised: 08/03/2022] [Accepted: 08/10/2022] [Indexed: 11/23/2022]
Abstract
In this brief review, we attempt to demonstrate that the incompleteness of data, as well as the intrinsic heterogeneity of biological systems, may form very strong and possibly insurmountable barriers for researchers trying to decipher the mechanisms of the functioning of live systems. We illustrate this challenge using the two most studied organisms: E. coli, with 34.6% genes lacking experimental evidence of function, and C. elegans, with identified proteins for approximately 50% of its genes. Another striking example is an artificial unicellular entity named JCVI-syn3.0, with a minimal set of genes. A total of 31.5% of the genes of JCVI-syn3.0 cannot be ascribed a specific biological function. The human interactome mapping project identified only 5-10% of all protein interactions in humans. In addition, most of the available data are static snapshots, and it is barely possible to generate realistic models of the dynamic processes within cells. Moreover, the existing interactomes reflect the de facto interaction but not its functional result, which is an unpredictable emerging property. Perhaps the completeness of molecular data on any living organism is beyond our reach and represents an unsolvable problem in biology.
Collapse
Affiliation(s)
- Liya Kondratyeva
- Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry of the Russian Academy of Sciences, Moscow 117997, Russia
| | - Irina Alekseenko
- Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry of the Russian Academy of Sciences, Moscow 117997, Russia
- Institute of Molecular Genetics of National Research Centre “Kurchatov Institute”, Moscow 123182, Russia
| | - Igor Chernov
- Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry of the Russian Academy of Sciences, Moscow 117997, Russia
| | - Eugene Sverdlov
- Institute of Molecular Genetics of National Research Centre “Kurchatov Institute”, Moscow 123182, Russia
- Kurchatov Center for Genome Research, National Research Center “Kurchatov Institute”, Moscow 123182, Russia
| |
Collapse
|
15
|
Lawrence JM, Yin Y, Bombelli P, Scarampi A, Storch M, Wey LT, Climent-Catala A, Baldwin GS, O’Hare D, Howe CJ, Zhang JZ, Ouldridge TE, Ledesma-Amaro R. Synthetic biology and bioelectrochemical tools for electrogenetic system engineering. SCIENCE ADVANCES 2022; 8:eabm5091. [PMID: 35507663 PMCID: PMC9067924 DOI: 10.1126/sciadv.abm5091] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/15/2023]
Abstract
Synthetic biology research and its industrial applications rely on deterministic spatiotemporal control of gene expression. Recently, electrochemical control of gene expression has been demonstrated in electrogenetic systems (redox-responsive promoters used alongside redox inducers and electrodes), allowing for the direct integration of electronics with biological processes. However, the use of electrogenetic systems is limited by poor activity, tunability, and standardization. In this work, we developed a strong, unidirectional, redox-responsive promoter before deriving a mutant promoter library with a spectrum of strengths. We constructed genetic circuits with these parts and demonstrated their activation by multiple classes of redox molecules. Last, we demonstrated electrochemical activation of gene expression under aerobic conditions using a novel, modular bioelectrochemical device. These genetic and electrochemical tools facilitate the design and improve the performance of electrogenetic systems. Furthermore, the genetic design strategies used can be applied to other redox-responsive promoters to further expand the available tools for electrogenetics.
Collapse
Affiliation(s)
- Joshua M. Lawrence
- Department of Biochemistry, University of Cambridge, Cambridge, UK
- Yusuf Hamied Department of Chemistry, University of Cambridge, Cambridge, UK
| | - Yutong Yin
- Department of Bioengineering, Imperial College London, London, UK
| | - Paolo Bombelli
- Department of Biochemistry, University of Cambridge, Cambridge, UK
- Department of Bioengineering, Imperial College London, London, UK
- Department of Environmental Science and Policy, Università degli Studi di Milano, Milano, Italy
| | - Alberto Scarampi
- Department of Biochemistry, University of Cambridge, Cambridge, UK
| | - Marko Storch
- London DNA Foundry, Imperial College Translation and Innovation Hub, London, UK
| | - Laura T. Wey
- Department of Biochemistry, University of Cambridge, Cambridge, UK
| | | | | | - Geoff S. Baldwin
- Department of Life Sciences, Imperial College London, London, UK
| | - Danny O’Hare
- Department of Bioengineering, Imperial College London, London, UK
| | | | - Jenny Z. Zhang
- Yusuf Hamied Department of Chemistry, University of Cambridge, Cambridge, UK
| | | | - Rodrigo Ledesma-Amaro
- Department of Bioengineering, Imperial College London, London, UK
- Corresponding author.
| |
Collapse
|
16
|
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.
Collapse
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.
| |
Collapse
|
17
|
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: 16] [Impact Index Per Article: 8.0] [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.
Collapse
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
| |
Collapse
|
18
|
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.
Collapse
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
| |
Collapse
|
19
|
Ma X, Ma L, Huo YX. Reconstructing the transcription regulatory network to optimize resource allocation for robust biosynthesis. Trends Biotechnol 2021; 40:735-751. [PMID: 34895933 DOI: 10.1016/j.tibtech.2021.11.002] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2021] [Revised: 11/07/2021] [Accepted: 11/08/2021] [Indexed: 11/16/2022]
Abstract
An ideal microbial cell factory (MCF) should deliver maximal resources to production, which conflicts with the microbe's native growth-oriented resource allocation strategy and can therefore lead to early termination of the high-yield period. Reallocating resources from growth to production has become a critical factor in constructing robust MCFs. Instead of strengthening specific biosynthetic pathways, emerging endeavors are focused on rearranging the gene regulatory network to fundamentally reprogram the resource allocation pattern. Combining this idea with transcriptional regulation within the hierarchical regulatory network, this review discusses recent engineering strategies targeting the transcription machinery, module networks, regulatory edges, and bottom network layer. This global view will help to construct a production-oriented phenotype that fully harnesses the potential of MCFs.
Collapse
Affiliation(s)
- Xiaoyan Ma
- Key Laboratory of Molecular Medicine and Biotherapy, School of Life Science, Beijing Institute of Technology, 5 South Zhongguancun Street, Haidian District, Beijing 100081, People's Republic of China
| | - Lianjie Ma
- Key Laboratory of Molecular Medicine and Biotherapy, School of Life Science, Beijing Institute of Technology, 5 South Zhongguancun Street, Haidian District, Beijing 100081, People's Republic of China
| | - Yi-Xin Huo
- Key Laboratory of Molecular Medicine and Biotherapy, School of Life Science, Beijing Institute of Technology, 5 South Zhongguancun Street, Haidian District, Beijing 100081, People's Republic of China; Tobacco Research Institute, Chinese Academy of Agricultural Sciences, Qingdao 266101, People's Republic of China.
| |
Collapse
|
20
|
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.
Collapse
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
| |
Collapse
|
21
|
The spatial position effect: synthetic biology enters the era of 3D genomics. Trends Biotechnol 2021; 40:539-548. [PMID: 34607694 DOI: 10.1016/j.tibtech.2021.09.001] [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: 07/23/2021] [Revised: 08/31/2021] [Accepted: 09/01/2021] [Indexed: 11/23/2022]
Abstract
Microbial cell factories are critical to achieving green biomanufacturing. A position effect occurs when a synthetic gene circuit is expressed from different positions in the chassis strain genome. Here, we propose the concept of the 'spatial position effect,' which uses technologies in 3D genomics to reveal the spatial structure characteristics of the 3D genome of the chassis. On this basis, we propose to rationally design the integration sites of synthetic gene circuits, use reporter genes for preliminary screening, and integrate synthetic gene circuits into promising sites for further experiments. This approach can produce stable and efficient chassis strains for green biomanufacturing. The proposed spatial position effect brings synthetic biology into the era of 3D genomics.
Collapse
|
22
|
Sinyakov AN, Ryabinin VA, Kostina EV. Application of Array-Based Oligonucleotides for Synthesis of Genetic Designs. Mol Biol 2021. [DOI: 10.1134/s0026893321030109] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
|
23
|
Improved Dynamic Range of a Rhamnose-Inducible Promoter for Gene Expression in Burkholderia spp. Appl Environ Microbiol 2021; 87:e0064721. [PMID: 34190606 DOI: 10.1128/aem.00647-21] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/06/2023] Open
Abstract
A diverse genetic toolkit is critical for understanding bacterial physiology and genotype-phenotype relationships. Inducible promoter systems are an integral part of this toolkit. In Burkholderia and related species, the l-rhamnose-inducible promoter is among the first choices due to its tight control and the lack of viable alternatives. To improve upon its maximum activity and dynamic range, we explored the effect of promoter system modifications in Burkholderia cenocepacia with a LacZ-based reporter. By combining the bacteriophage T7 gene 10 stem-loop and engineered rhaI transcription factor-binding sites, we obtained a rhamnose-inducible system with a 6.5-fold and 3.0-fold increases in maximum activity and dynamic range, respectively, compared to the native promoter. We then added the modified promoter system to pSCrhaB2 and pSC201, common genetic tools used for plasmid-based and chromosome-based gene expression, respectively, in Burkholderia, creating pSCrhaB2plus and pSC201plus. We demonstrated the utility of pSCrhaB2plus for gene expression in B. thailandensis, B. multivorans, and B. vietnamiensis and used pSC201plus to control highly expressed essential genes from the chromosome of B. cenocepacia. The utility of the modified system was demonstrated as we recovered viable mutants to control ftsZ, rpoBC, and rpsF, whereas the unmodified promoter was unable to control rpsF. The modified expression system allowed control of an essential gene depletion phenotype at lower levels of l-rhamnose, the inducer. pSCRhaB2plus and pSC201plus are expected to be valuable additions to the genetic toolkit for Burkholderia and related species. IMPORTANCE Species of Burkholderia are dually recognized as being of attractive biotechnological potential but also opportunistic pathogens for immunocompromised individuals. Understanding the genotype-phenotype relationship is critical for synthetic biology approaches in Burkholderia to disentangle pathogenic from beneficial traits. A diverse genetic toolkit, including inducible promoters, is the foundation for these investigations. Thus, we sought to improve on the commonly used rhamnose-inducible promoter system. Our modifications resulted in both higher levels of heterologous protein expression and broader control over highly expressed essential genes in B. cenocepacia. The significance of our work is in expanding the genetic toolkit to enable more comprehensive studies into Burkholderia and related bacteria.
Collapse
|
24
|
Park J, Wang HH. Systematic dissection of σ 70 sequence diversity and function in bacteria. Cell Rep 2021; 36:109590. [PMID: 34433066 PMCID: PMC8716302 DOI: 10.1016/j.celrep.2021.109590] [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: 05/18/2020] [Revised: 04/19/2021] [Accepted: 08/02/2021] [Indexed: 10/29/2022] Open
Abstract
Primary σ70 factors are key conserved bacterial regulatory proteins that interact with regulatory DNA to control gene expression. It is, however, poorly understood whether σ70 sequence diversity in different bacteria reflects functional differences. Here, we employ comparative and functional genomics to explore the sequence and function relationship of primary σ70. Using multiplex automated genome engineering and deep sequencing (MAGE-seq), we generate a saturation mutagenesis library and high-resolution fitness map of E. coli σ70 in domains 2-4. Mapping natural σ70 sequence diversity to the E. coli σ70 fitness landscape reveals significant predicted fitness deficits across σ70 orthologs. Interestingly, these predicted deficits are larger than observed fitness changes for 15 σ70 orthologs introduced into E. coli. Finally, we use a multiplexed transcriptional reporter assay and RNA sequencing (RNA-seq) to explore functional differences of several σ70 orthologs. This work provides an in-depth analysis of σ70 sequence and function to improve efforts to understand the evolution and engineering potential of this global regulator.
Collapse
Affiliation(s)
- Jimin Park
- Department of Systems Biology, Columbia University Irving Medical Center, New York, NY, USA; Integrated Program in Cellular, Molecular and Biomedical Studies, Columbia University Irving Medical Center, New York, NY, USA.
| | - Harris H Wang
- Department of Systems Biology, Columbia University Irving Medical Center, New York, NY, USA; Department of Pathology and Cell Biology, Columbia University Irving Medical Center, New York, NY, USA.
| |
Collapse
|
25
|
Park J, Yim SS, Wang HH. High-Throughput Transcriptional Characterization of Regulatory Sequences from Bacterial Biosynthetic Gene Clusters. ACS Synth Biol 2021; 10:1859-1873. [PMID: 34288650 DOI: 10.1021/acssynbio.0c00639] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/06/2023]
Abstract
Recent efforts to sequence, survey, and functionally characterize the diverse biosynthetic capabilities of bacteria have identified numerous Biosynthetic Gene Clusters (BGCs). Genes found within BGCs are typically transcriptionally silent, suggesting their expression is tightly regulated. To better elucidate the underlying mechanisms and principles that govern BGC regulation on a DNA sequence level, we employed high-throughput DNA synthesis and multiplexed reporter assays to build and to characterize a library of BGC-derived regulatory sequences. Regulatory sequence transcription levels were measured in the Actinobacteria Streptomyces albidoflavus J1074, a popular model strain from a genus rich in BGC diversity. Transcriptional activities varied over 1000-fold in range and were used to identify key features associated with expression, including GC content, transcription start sites, and sequence motifs. Furthermore, we demonstrated that transcription levels could be modulated through coexpression of global regulatory proteins. Lastly, we developed and optimized a S. albidoflavus cell-free expression system for rapid characterization of regulatory sequences. This work helps to elucidate the regulatory landscape of BGCs and provides a diverse library of characterized regulatory sequences for rational engineering and activation of cryptic BGCs.
Collapse
Affiliation(s)
- Jimin Park
- Department of Systems Biology, Columbia University Irving Medical Center, New York, New York 10032, United States
- Integrated Program in Cellular, Molecular and Biomedical Studies, Columbia University Irving Medical Center, New York, New York 10032, United States
| | - Sung Sun Yim
- Department of Systems Biology, Columbia University Irving Medical Center, New York, New York 10032, United States
- Department of Pathology and Cell Biology, Columbia University Irving Medical Center, New York, New York 10032, United States
| | - Harris H. Wang
- Department of Systems Biology, Columbia University Irving Medical Center, New York, New York 10032, United States
- Department of Pathology and Cell Biology, Columbia University Irving Medical Center, New York, New York 10032, United States
| |
Collapse
|
26
|
Cazier AP, Blazeck J. Advances in promoter engineering: novel applications and predefined transcriptional control. Biotechnol J 2021; 16:e2100239. [PMID: 34351706 DOI: 10.1002/biot.202100239] [Citation(s) in RCA: 36] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2021] [Revised: 07/30/2021] [Accepted: 08/03/2021] [Indexed: 11/08/2022]
Abstract
Synthetic biology continues to progress by relying on more robust tools for transcriptional control, of which promoters are the most fundamental component. Numerous studies have sought to characterize promoter function, determine principles to guide their engineering, and create promoters with stronger expression or tailored inducible control. In this review, we will summarize promoter architecture and highlight recent advances in the field, focusing on the novel applications of inducible promoter design and engineering towards metabolic engineering and cellular therapeutic development. Additionally, we will highlight how the expansion of new, machine learning techniques for modeling and engineering promoter sequences are enabling more accurate prediction of promoter characteristics. This article is protected by copyright. All rights reserved.
Collapse
Affiliation(s)
- Andrew P Cazier
- School of Chemical and Biomolecular Engineering, Georgia Institute of Technology, 311 Ferst St. NW, Atlanta, Georgia, 30332, USA
| | - John Blazeck
- School of Chemical and Biomolecular Engineering, Georgia Institute of Technology, 311 Ferst St. NW, Atlanta, Georgia, 30332, USA
| |
Collapse
|
27
|
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.
Collapse
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; ,
| |
Collapse
|
28
|
Vlková M, Morampalli BR, Silander OK. Efficiency of the synthetic self-splicing RiboJ ribozyme is robust to cis- and trans-changes in genetic background. Microbiologyopen 2021; 10:e1232. [PMID: 34459545 PMCID: PMC8383906 DOI: 10.1002/mbo3.1232] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2021] [Revised: 08/04/2021] [Accepted: 08/04/2021] [Indexed: 01/08/2023] Open
Abstract
The expanding knowledge of the variety of synthetic genetic elements has enabled the construction of new and more efficient genetic circuits and yielded novel insights into molecular mechanisms. However, context dependence, in which interactions between cis- or trans-genetic elements affect the behavior of these elements, can reduce their general applicability or predictability. Genetic insulators, which mitigate unintended context-dependent cis-interactions, have been used to address this issue. One of the most commonly used genetic insulators is a self-splicing ribozyme called RiboJ, which can be used to decouple upstream 5' UTR in mRNA from downstream sequences (e.g., open reading frames). Despite its general use as an insulator, there has been no systematic study quantifying the efficiency of RiboJ splicing or whether this autocatalytic activity is robust to trans- and cis-genetic context. Here, we determine the robustness of RiboJ splicing in the genetic context of six widely divergent E. coli strains. We also check for possible cis-effects by assessing two SNP versions close to the catalytic site of RiboJ. We show that mRNA molecules containing RiboJ are rapidly spliced even during rapid exponential growth and high levels of gene expression, with a mean efficiency of 98%. We also show that neither the cis- nor trans-genetic context has a significant impact on RiboJ activity, suggesting this element is robust to both cis- and trans-genetic changes.
Collapse
Affiliation(s)
- Markéta Vlková
- School of Natural and Computational SciencesMassey UniversityAucklandNew Zealand
| | | | - Olin K. Silander
- School of Natural and Computational SciencesMassey UniversityAucklandNew Zealand
| |
Collapse
|
29
|
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.
Collapse
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
| |
Collapse
|
30
|
Martin-Pascual M, Batianis C, Bruinsma L, Asin-Garcia E, Garcia-Morales L, Weusthuis RA, van Kranenburg R, Martins Dos Santos VAP. A navigation guide of synthetic biology tools for Pseudomonas putida. Biotechnol Adv 2021; 49:107732. [PMID: 33785373 DOI: 10.1016/j.biotechadv.2021.107732] [Citation(s) in RCA: 41] [Impact Index Per Article: 13.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2020] [Revised: 03/12/2021] [Accepted: 03/18/2021] [Indexed: 12/12/2022]
Abstract
Pseudomonas putida is a microbial chassis of huge potential for industrial and environmental biotechnology, owing to its remarkable metabolic versatility and ability to sustain difficult redox reactions and operational stresses, among other attractive characteristics. A wealth of genetic and in silico tools have been developed to enable the unravelling of its physiology and improvement of its performance. However, the rise of this microbe as a promising platform for biotechnological applications has resulted in diversification of tools and methods rather than standardization and convergence. As a consequence, multiple tools for the same purpose have been generated, whilst most of them have not been embraced by the scientific community, which has led to compartmentalization and inefficient use of resources. Inspired by this and by the substantial increase in popularity of P. putida, we aim herein to bring together and assess all currently available (wet and dry) synthetic biology tools specific for this microbe, focusing on the last 5 years. We provide information on the principles, functionality, advantages and limitations, with special focus on their use in metabolic engineering. Additionally, we compare the tool portfolio for P. putida with those for other bacterial chassis and discuss potential future directions for tool development. Therefore, this review is intended as a reference guide for experts and new 'users' of this promising chassis.
Collapse
Affiliation(s)
- Maria Martin-Pascual
- Laboratory of Systems and Synthetic Biology, Wageningen University & Research, Wageningen 6708 WE, The Netherlands
| | - Christos Batianis
- Laboratory of Systems and Synthetic Biology, Wageningen University & Research, Wageningen 6708 WE, The Netherlands
| | - Lyon Bruinsma
- Laboratory of Systems and Synthetic Biology, Wageningen University & Research, Wageningen 6708 WE, The Netherlands
| | - Enrique Asin-Garcia
- Laboratory of Systems and Synthetic Biology, Wageningen University & Research, Wageningen 6708 WE, The Netherlands
| | - Luis Garcia-Morales
- Laboratory of Systems and Synthetic Biology, Wageningen University & Research, Wageningen 6708 WE, The Netherlands
| | - Ruud A Weusthuis
- Bioprocess Engineering, Wageningen University and Research, Droevendaalsesteeg 1, 6708 PB Wageningen, The Netherlands
| | - Richard van Kranenburg
- Corbion, Gorinchem 4206 AC, The Netherlands; Laboratory of Microbiology, Wageningen University & Research, Wageningen 6708 WE, the Netherlands
| | - Vitor A P Martins Dos Santos
- Laboratory of Systems and Synthetic Biology, Wageningen University & Research, Wageningen 6708 WE, The Netherlands; LifeGlimmer GmbH, Berlin 12163, Germany.
| |
Collapse
|
31
|
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.
Collapse
|
32
|
Overcoming the design, build, test bottleneck for synthesis of nonrepetitive protein-RNA cassettes. Nat Commun 2021; 12:1576. [PMID: 33707432 PMCID: PMC7952577 DOI: 10.1038/s41467-021-21578-6] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2020] [Accepted: 01/20/2021] [Indexed: 01/03/2023] Open
Abstract
We apply an oligo-library and machine learning-approach to characterize the sequence and structural determinants of binding of the phage coat proteins (CPs) of bacteriophages MS2 (MCP), PP7 (PCP), and Qβ (QCP) to RNA. Using the oligo library, we generate thousands of candidate binding sites for each CP, and screen for binding using a high-throughput dose-response Sort-seq assay (iSort-seq). We then apply a neural network to expand this space of binding sites, which allowed us to identify the critical structural and sequence features for binding of each CP. To verify our model and experimental findings, we design several non-repetitive binding site cassettes and validate their functionality in mammalian cells. We find that the binding of each CP to RNA is characterized by a unique space of sequence and structural determinants, thus providing a more complete description of CP-RNA interaction as compared with previous low-throughput findings. Finally, based on the binding spaces we demonstrate a computational tool for the successful design and rapid synthesis of functional non-repetitive binding-site cassettes. Phage-coat proteins can be used to build synthetic biology parts. Here the authors use an oligo library and machine learning to predict and verify sequences based on binding scores.
Collapse
|
33
|
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.
Collapse
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
| |
Collapse
|
34
|
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.
Collapse
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.
| |
Collapse
|
35
|
Shimamoto N, Imashimizu M. RNA Polymerase and Transcription Mechanisms: The Forefront of Physicochemical Studies of Chemical Reactions. Biomolecules 2020; 11:E32. [PMID: 33383858 PMCID: PMC7823607 DOI: 10.3390/biom11010032] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2020] [Revised: 12/24/2020] [Accepted: 12/25/2020] [Indexed: 12/13/2022] Open
Abstract
The study of transcription and its regulation is an interdisciplinary field that is closely connected with genetics, structural biology, and reaction theory. Among these, although less attention has been paid to reaction theory, it is becoming increasingly useful for research on transcription. Rate equations are commonly used to describe reactions involved in transcription, but they tend to be used unaware of the timescales of relevant physical processes. In this review, we discuss the limitation of rate equation for describing three-dimensional diffusion and one-dimensional diffusion along DNA. We then introduce the chemical ratchet mechanism recently proposed for explaining the antenna effect, an enhancement of the binding affinity to a specific site on longer DNA, which deviates from a thermodynamic rule. We show that chemical ratchet cannot be described with a single set of rate equations but alternative sets of rate equations that temporally switch no faster than the binding reaction.
Collapse
Affiliation(s)
- Nobuo Shimamoto
- National Institute of Genetics Mishima, Shizuoka-ken 411-8540, Japan
| | - Masahiko Imashimizu
- Cellular and Molecular Biotechnology Research Institute, National Institute of Advanced Industrial Science and Technology, Tokyo 135-0064, Japan;
| |
Collapse
|
36
|
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.
Collapse
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.
| |
Collapse
|
37
|
Nieuwkoop T, Finger-Bou M, van der Oost J, Claassens NJ. The Ongoing Quest to Crack the Genetic Code for Protein Production. Mol Cell 2020; 80:193-209. [PMID: 33010203 DOI: 10.1016/j.molcel.2020.09.014] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2020] [Revised: 08/10/2020] [Accepted: 09/10/2020] [Indexed: 01/05/2023]
Abstract
Understanding the genetic design principles that determine protein production remains a major challenge. Although the key principles of gene expression were discovered 50 years ago, additional factors are still being uncovered. Both protein-coding and non-coding sequences harbor elements that collectively influence the efficiency of protein production by modulating transcription, mRNA decay, and translation. The influences of many contributing elements are intertwined, which complicates a full understanding of the individual factors. In natural genes, a functional balance between these factors has been obtained in the course of evolution, whereas for genetic-engineering projects, our incomplete understanding still limits optimal design of synthetic genes. However, notable advances have recently been made, supported by high-throughput analysis of synthetic gene libraries as well as by state-of-the-art biomolecular techniques. We discuss here how these advances further strengthen understanding of the gene expression process and how they can be harnessed to optimize protein production.
Collapse
Affiliation(s)
- Thijs Nieuwkoop
- Laboratory of Microbiology, Wageningen University, Stippeneng 4, 6708 WE Wageningen, the Netherlands
| | - Max Finger-Bou
- Laboratory of Microbiology, Wageningen University, Stippeneng 4, 6708 WE Wageningen, the Netherlands
| | - John van der Oost
- Laboratory of Microbiology, Wageningen University, Stippeneng 4, 6708 WE Wageningen, the Netherlands
| | - Nico J Claassens
- Laboratory of Microbiology, Wageningen University, Stippeneng 4, 6708 WE Wageningen, the Netherlands.
| |
Collapse
|
38
|
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.
Collapse
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
| |
Collapse
|
39
|
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.
Collapse
|
40
|
Comprehensive study on Escherichia coli genomic expression: Does position really matter? Metab Eng 2020; 62:10-19. [PMID: 32795614 DOI: 10.1016/j.ymben.2020.07.007] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2019] [Revised: 07/20/2020] [Accepted: 07/20/2020] [Indexed: 12/14/2022]
Abstract
As a biorefinery platform host, Escherichia coli has been used extensively to produce metabolites of commercial interest. Integration of foreign DNA onto the bacterial genome allows for stable expression overcoming the need for plasmid expression and its associated instability. Despite the development of numerous tools and genome editing technologies, the question of where to incorporate a synthetic pathway remains unanswered. To address this issue, we studied the genomic expression in E. coli and linked it not only to 26 rationally selected genomic locations, but also to the gene direction in relation to the DNA replication fork, to the carbon and nitrogen source, to DNA folding and supercoiling, and to metabolic burden. To enable these experiments, we have designed a fluorescent expression cassette to eliminate specific local effects on gene expression. Overall it can be concluded that although the expression range obtained by changing the genomic location of a pathway is small compared to the range typically seen in promoter-RBS libraries, the effect of culture medium, environmental stress and metabolic burden can be substantial. The characterization of multiple effects on genomic expression, and the associated libraries of well-characterized strains, will only stimulate and improve the creation of stable production hosts fit for industrial settings.
Collapse
|
41
|
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.
Collapse
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.
| |
Collapse
|
42
|
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.
Collapse
|
43
|
Crook N, Ferreiro A, Condiotte Z, Dantas G. Transcript Barcoding Illuminates the Expression Level of Synthetic Constructs in E. coli Nissle Residing in the Mammalian Gut. ACS Synth Biol 2020; 9:1010-1021. [PMID: 32324995 PMCID: PMC7293544 DOI: 10.1021/acssynbio.0c00040] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Abstract
The development of robust engineered probiotic therapies demands accurate knowledge of genetic construct expression in the gut. However, the monetary and ethical costs of testing engineered strains in vertebrate hosts are incompatible with current high-throughput design-build-test cycles. To enable parallel measurement of multiple construct designs, we placed unique DNA barcodes in engineered transcripts and measured barcode abundances via sequencing. In standard curve experiments, the barcode sequences exhibited consistent relationships between input and measured abundances, which allowed us to use transcript barcoding to measure expression levels of 30 GFP-expressing strains of E. coli Nissle in parallel. Applying this technology in culture and in the mouse gut, we found that GFP expression in the gut could often be predicted from expression levels in culture, but several strains exhibited gut-specific expression. This work establishes the experimental design parameters and advantages of transcript barcoding to measure the performance of many engineered probiotic designs in mammalian hosts.
Collapse
Affiliation(s)
- Nathan Crook
- Department of Chemical and Biomolecular Engineering, North Carolina State University, Raleigh, North Carolina, USA
| | - Aura Ferreiro
- The Edison Family Center for Genome Sciences & Systems Biology, Washington University School of Medicine, St. Louis, Missouri 63110, USA
- Department of Biomedical Engineering, Washington University in St. Louis, St. Louis, Missouri 63130, USA
| | - Zevin Condiotte
- Department of Biomedical Engineering, Washington University in St. Louis, St. Louis, Missouri 63130, USA
| | - Gautam Dantas
- The Edison Family Center for Genome Sciences & Systems Biology, Washington University School of Medicine, St. Louis, Missouri 63110, USA
- Department of Biomedical Engineering, Washington University in St. Louis, St. Louis, Missouri 63130, USA
- Department of Pathology and Immunology, Washington University School of Medicine, St. Louis, Missouri 63110, USA
- Department of Molecular Microbiology, Washington University School of Medicine, St. Louis, Missouri 63110, USA
| |
Collapse
|
44
|
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.
Collapse
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
| |
Collapse
|
45
|
Jin L, Nawab S, Xia M, Ma X, Huo Y. Context-dependency of synthetic minimal promoters in driving gene expression: a case study. Microb Biotechnol 2019; 12:1476-1486. [PMID: 31578818 PMCID: PMC6801132 DOI: 10.1111/1751-7915.13489] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2019] [Accepted: 09/09/2019] [Indexed: 12/13/2022] Open
Abstract
Synthetic promoters are considered ideal candidates in driving robust gene expression. Most of the available synthetic promoters are minimal promoters, for which the upstream sequence of the 5' end of the core region is usually excluded. Although the upstream sequence has been shown to mediate transcription of natural promoters, its impact on synthetic promoters has not been widely studied. Here, a library of chromosomal DNA fragments is randomly fused with the 5' end of the J23119 synthetic promoter, and the transcriptional performance of the promoter is evaluated through β-galactosidase assay, fluorescence intensity and chemical biosynthesis. Results show that changes in the upstream sequence can induce significant variation in the promoter strength of up to 5.8-fold. The effect is independent of the length of the insertions and the number of potential transcription factor binding sites. Several DNA fragments that are able to enhance the transcription of both the natural and the synthetic promoters are identified. This study indicates that the synthetic minimal promoters are susceptible to the surrounding sequence context. Therefore, the upstream sequence should be treated as an indispensable component in the design and application of synthetic promoters, or as an independent genetic part for the fine-tuning of gene expression.
Collapse
Affiliation(s)
- Liyuan Jin
- Key Laboratory of Molecular Medicine and BiotherapySchool of Life ScienceBeijing Institute of Technology5 South Zhongguancun Street, Haidian DistrictBeijing100081China
| | - Said Nawab
- Key Laboratory of Molecular Medicine and BiotherapySchool of Life ScienceBeijing Institute of Technology5 South Zhongguancun Street, Haidian DistrictBeijing100081China
| | - Mengli Xia
- Key Laboratory of Molecular Medicine and BiotherapySchool of Life ScienceBeijing Institute of Technology5 South Zhongguancun Street, Haidian DistrictBeijing100081China
| | - Xiaoyan Ma
- Key Laboratory of Molecular Medicine and BiotherapySchool of Life ScienceBeijing Institute of Technology5 South Zhongguancun Street, Haidian DistrictBeijing100081China
| | - Yi‐Xin Huo
- Key Laboratory of Molecular Medicine and BiotherapySchool of Life ScienceBeijing Institute of Technology5 South Zhongguancun Street, Haidian DistrictBeijing100081China
- UCLA Institute for Technology Advancement (Suzhou)10 Yueliangwan Road, Suzhou Industrial ParkSuzhou215123China
| |
Collapse
|
46
|
Yim SS, Johns NI, Park J, Gomes ALC, McBee RM, Richardson M, Ronda C, Chen SP, Garenne D, Noireaux V, Wang HH. Multiplex transcriptional characterizations across diverse bacterial species using cell-free systems. Mol Syst Biol 2019; 15:e8875. [PMID: 31464371 PMCID: PMC6692573 DOI: 10.15252/msb.20198875] [Citation(s) in RCA: 36] [Impact Index Per Article: 7.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2019] [Revised: 07/01/2019] [Accepted: 07/03/2019] [Indexed: 12/14/2022] Open
Abstract
Cell-free expression systems enable rapid prototyping of genetic programs in vitro. However, current throughput of cell-free measurements is limited by the use of channel-limited fluorescent readouts. Here, we describe DNA Regulatory element Analysis by cell-Free Transcription and Sequencing (DRAFTS), a rapid and robust in vitro approach for multiplexed measurement of transcriptional activities from thousands of regulatory sequences in a single reaction. We employ this method in active cell lysates developed from ten diverse bacterial species. Interspecies analysis of transcriptional profiles from > 1,000 diverse regulatory sequences reveals functional differences in promoter activity that can be quantitatively modeled, providing a rich resource for tuning gene expression in diverse bacterial species. Finally, we examine the transcriptional capacities of dual-species hybrid lysates that can simultaneously harness gene expression properties of multiple organisms. We expect that this cell-free multiplex transcriptional measurement approach will improve genetic part prototyping in new bacterial chassis for synthetic biology.
Collapse
Affiliation(s)
- Sung Sun Yim
- Department of Systems BiologyColumbia UniversityNew YorkNYUSA
| | - Nathan I Johns
- Department of Systems BiologyColumbia UniversityNew YorkNYUSA
- Integrated Program in Cellular, Molecular, and Biomedical StudiesColumbia UniversityNew YorkNYUSA
- Present address:
Department of BioengineeringStanford UniversityStanfordCAUSA
| | - Jimin Park
- Department of Systems BiologyColumbia UniversityNew YorkNYUSA
- Integrated Program in Cellular, Molecular, and Biomedical StudiesColumbia UniversityNew YorkNYUSA
| | - Antonio LC Gomes
- Department of ImmunologyMemorial Sloan Kettering Cancer CenterNew YorkNYUSA
| | - Ross M McBee
- Department of Systems BiologyColumbia UniversityNew YorkNYUSA
- Department of Biological SciencesColumbia UniversityNew YorkNYUSA
| | - Miles Richardson
- Department of Systems BiologyColumbia UniversityNew YorkNYUSA
- Integrated Program in Cellular, Molecular, and Biomedical StudiesColumbia UniversityNew YorkNYUSA
| | - Carlotta Ronda
- Department of Systems BiologyColumbia UniversityNew YorkNYUSA
| | - Sway P Chen
- Department of Systems BiologyColumbia UniversityNew YorkNYUSA
- Integrated Program in Cellular, Molecular, and Biomedical StudiesColumbia UniversityNew YorkNYUSA
| | - David Garenne
- School of Physics and AstronomyUniversity of MinnesotaMinneapolisMNUSA
| | - Vincent Noireaux
- School of Physics and AstronomyUniversity of MinnesotaMinneapolisMNUSA
| | - Harris H Wang
- Department of Systems BiologyColumbia UniversityNew YorkNYUSA
- Department of Pathology and Cell BiologyColumbia UniversityNew YorkNYUSA
| |
Collapse
|
47
|
How the avidity of polymerase binding to the -35/-10 promoter sites affects gene expression. Proc Natl Acad Sci U S A 2019; 116:13340-13345. [PMID: 31196959 PMCID: PMC6613100 DOI: 10.1073/pnas.1905615116] [Citation(s) in RCA: 20] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Abstract
Although the key promoter elements necessary to drive transcription in Escherichia coli have long been understood, we still cannot predict the behavior of arbitrary novel promoters, hampering our ability to characterize the myriad sequenced regulatory architectures as well as to design new synthetic circuits. This work builds upon a beautiful recent experiment by Urtecho et al. [G. Urtecho, et al, Biochemistry, 68, 1539-1551 (2019)] who measured the gene expression of over 10,000 promoters spanning all possible combinations of a small set of regulatory elements. Using these data, we demonstrate that a central claim in energy matrix models of gene expression-that each promoter element contributes independently and additively to gene expression-contradicts experimental measurements. We propose that a key missing ingredient from such models is the avidity between the -35 and -10 RNA polymerase binding sites and develop what we call a multivalent model that incorporates this effect and can successfully characterize the full suite of gene expression data. We explore several applications of this framework, namely, how multivalent binding at the -35 and -10 sites can buffer RNA polymerase (RNAP) kinetics against mutations and how promoters that bind overly tightly to RNA polymerase can inhibit gene expression. The success of our approach suggests that avidity represents a key physical principle governing the interaction of RNA polymerase to its promoter.
Collapse
|
48
|
Barnes SL, Belliveau NM, Ireland WT, Kinney JB, Phillips R. Mapping DNA sequence to transcription factor binding energy in vivo. PLoS Comput Biol 2019; 15:e1006226. [PMID: 30716072 PMCID: PMC6375646 DOI: 10.1371/journal.pcbi.1006226] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2018] [Revised: 02/14/2019] [Accepted: 11/06/2018] [Indexed: 11/18/2022] Open
Abstract
Despite the central importance of transcriptional regulation in biology, it has proven difficult to determine the regulatory mechanisms of individual genes, let alone entire gene networks. It is particularly difficult to decipher the biophysical mechanisms of transcriptional regulation in living cells and determine the energetic properties of binding sites for transcription factors and RNA polymerase. In this work, we present a strategy for dissecting transcriptional regulatory sequences using in vivo methods (massively parallel reporter assays) to formulate quantitative models that map a transcription factor binding site’s DNA sequence to transcription factor-DNA binding energy. We use these models to predict the binding energies of transcription factor binding sites to within 1 kBT of their measured values. We further explore how such a sequence-energy mapping relates to the mechanisms of trancriptional regulation in various promoter contexts. Specifically, we show that our models can be used to design specific induction responses, analyze the effects of amino acid mutations on DNA sequence preference, and determine how regulatory context affects a transcription factor’s sequence specificity. It has been said that we live in the “genomic era,” a time where we can readily sequence full genomes at will. However, it remains difficult to interpret much of the information within a genome. This is especially true of non-coding sequences such as promoters, which contain a number of features such as transcription factor binding sites that determine how genes are regulated. There is no straightforward regulatory “code” that tells us how transcription factor binding sites are organized within a promoter. In this work we examine how DNA sequence determines one of the most important features of a promoter, the strength with which a transcription factor binds to its DNA binding site. We discuss an approach to modeling DNA sequence-specific transcription factor binding energies in vivo using a massively parellel reporter assay. We develop models that allow us to predict the binding energy between a transcription factor and a mutated version of its binding site. We then show that this modeling technique can be used to address a number of scientific and design questions, such as engineering the behavior of genetic circuit elements or examining how transcription factors and their binding sites co-evolve.
Collapse
Affiliation(s)
- Stephanie L. Barnes
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, California, United States of America
| | - Nathan M. Belliveau
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, California, United States of America
| | - William T. Ireland
- Department of Physics, California Institute of Technology, Pasadena, California, United States of America
| | - Justin B. Kinney
- Simons Center for Quantitative Biology, Cold Spring Harbor Laboratory, Cold Spring Harbor, New York, United States of America
| | - Rob Phillips
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, California, United States of America
- Department of Physics, California Institute of Technology, Pasadena, California, United States of America
- * E-mail:
| |
Collapse
|
49
|
Systematic approach for dissecting the molecular mechanisms of transcriptional regulation in bacteria. Proc Natl Acad Sci U S A 2018; 115:E4796-E4805. [PMID: 29728462 PMCID: PMC6003448 DOI: 10.1073/pnas.1722055115] [Citation(s) in RCA: 54] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022] Open
Abstract
Organisms must constantly make regulatory decisions in response to a change in cellular state or environment. However, while the catalog of genomes expands rapidly, we remain ignorant about how the genes in these genomes are regulated. Here, we show how a massively parallel reporter assay, Sort-Seq, and information-theoretic modeling can be used to identify regulatory sequences. We then use chromatography and mass spectrometry to identify the regulatory proteins that bind these sequences. The approach results in quantitative base pair-resolution models of promoter mechanism and was shown in both well-characterized and unannotated promoters in Escherichia coli. Given the generality of the approach, it opens up the possibility of quantitatively dissecting the mechanisms of promoter function in a wide range of bacteria. Gene regulation is one of the most ubiquitous processes in biology. However, while the catalog of bacterial genomes continues to expand rapidly, we remain ignorant about how almost all of the genes in these genomes are regulated. At present, characterizing the molecular mechanisms by which individual regulatory sequences operate requires focused efforts using low-throughput methods. Here, we take a first step toward multipromoter dissection and show how a combination of massively parallel reporter assays, mass spectrometry, and information-theoretic modeling can be used to dissect multiple bacterial promoters in a systematic way. We show this approach on both well-studied and previously uncharacterized promoters in the enteric bacterium Escherichia coli. In all cases, we recover nucleotide-resolution models of promoter mechanism. For some promoters, including previously unannotated ones, the approach allowed us to further extract quantitative biophysical models describing input–output relationships. Given the generality of the approach presented here, it opens up the possibility of quantitatively dissecting the mechanisms of promoter function in E. coli and a wide range of other bacteria.
Collapse
|