1
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Lei G, Huang J, Zhou H, Chen Y, Song J, Xie X, Vasseur L, You M, You S. Polygenic adaptation of a cosmopolitan pest to a novel thermal environment. INSECT MOLECULAR BIOLOGY 2024; 33:387-404. [PMID: 38488345 DOI: 10.1111/imb.12908] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/27/2023] [Accepted: 03/01/2024] [Indexed: 07/10/2024]
Abstract
The fluctuation in temperature poses a significant challenge for poikilothermic organisms, notably insects, particularly in the context of changing climatic conditions. In insects, temperature adaptation has been driven by polygenes. In addition to genes that directly affect traits (core genes), other genes (peripheral genes) may also play a role in insect temperature adaptation. This study focuses on two peripheral genes, the GRIP and coiled-coil domain containing 2 (GCC2) and karyopherin subunit beta 1 (KPNB1). These genes are differentially expressed at different temperatures in the cosmopolitan pest, Plutella xylostella. GCC2 and KPNB1 in P. xylostella were cloned, and their relative expression patterns were identified. Reduced capacity for thermal adaptation (development, reproduction and response to temperature extremes) in the GCC2-deficient and KPNB1-deficient P. xylostella strains, which were constructed by CRISPR/Cas9 technique. Deletion of the PxGCC2 or PxKPNB1 genes in P. xylostella also had a differential effect on gene expression for many traits including stress resistance, resistance to pesticides, involved in immunity, trehalose metabolism, fatty acid metabolism and so forth. The ability of the moth to adapt to temperature via different pathways is likely to be key to its ability to remain an important pest species under predicted climate change conditions.
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Affiliation(s)
- Gaoke Lei
- State Key Laboratory for Ecological Pest Control of Fujian and Taiwan Crops, Institute of Applied Ecology, Fujian Agriculture and Forestry University, Fuzhou, China
- Joint International Research Laboratory of Ecological Pest Control, Ministry of Education, Fuzhou, China
- Ministerial and Provincial Joint Innovation Centre for Safety Production of Cross-Strait Crops, Fujian Agriculture and Forestry University, Fuzhou, China
| | - Jieling Huang
- State Key Laboratory for Ecological Pest Control of Fujian and Taiwan Crops, Institute of Applied Ecology, Fujian Agriculture and Forestry University, Fuzhou, China
- Joint International Research Laboratory of Ecological Pest Control, Ministry of Education, Fuzhou, China
- Ministerial and Provincial Joint Innovation Centre for Safety Production of Cross-Strait Crops, Fujian Agriculture and Forestry University, Fuzhou, China
| | - Huiling Zhou
- State Key Laboratory for Ecological Pest Control of Fujian and Taiwan Crops, Institute of Applied Ecology, Fujian Agriculture and Forestry University, Fuzhou, China
- Joint International Research Laboratory of Ecological Pest Control, Ministry of Education, Fuzhou, China
- Ministerial and Provincial Joint Innovation Centre for Safety Production of Cross-Strait Crops, Fujian Agriculture and Forestry University, Fuzhou, China
| | - Yanting Chen
- State Key Laboratory for Ecological Pest Control of Fujian and Taiwan Crops, Institute of Applied Ecology, Fujian Agriculture and Forestry University, Fuzhou, China
- Joint International Research Laboratory of Ecological Pest Control, Ministry of Education, Fuzhou, China
- Ministerial and Provincial Joint Innovation Centre for Safety Production of Cross-Strait Crops, Fujian Agriculture and Forestry University, Fuzhou, China
- Institute of Plant Protection Fujian Academy of Agricultural Sciences, Fuzhou, China
| | | | | | - Liette Vasseur
- State Key Laboratory for Ecological Pest Control of Fujian and Taiwan Crops, Institute of Applied Ecology, Fujian Agriculture and Forestry University, Fuzhou, China
- Joint International Research Laboratory of Ecological Pest Control, Ministry of Education, Fuzhou, China
- Department of Biological Sciences, Brock University, St. Catharines, Ontario, Canada
| | - Minsheng You
- State Key Laboratory for Ecological Pest Control of Fujian and Taiwan Crops, Institute of Applied Ecology, Fujian Agriculture and Forestry University, Fuzhou, China
- Joint International Research Laboratory of Ecological Pest Control, Ministry of Education, Fuzhou, China
- Ministerial and Provincial Joint Innovation Centre for Safety Production of Cross-Strait Crops, Fujian Agriculture and Forestry University, Fuzhou, China
| | - Shijun You
- State Key Laboratory for Ecological Pest Control of Fujian and Taiwan Crops, Institute of Applied Ecology, Fujian Agriculture and Forestry University, Fuzhou, China
- Joint International Research Laboratory of Ecological Pest Control, Ministry of Education, Fuzhou, China
- Ministerial and Provincial Joint Innovation Centre for Safety Production of Cross-Strait Crops, Fujian Agriculture and Forestry University, Fuzhou, China
- BGI Research, Sanya, China
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2
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Helenek C, Krzysztoń R, Petreczky J, Wan Y, Cabral M, Coraci D, Balázsi G. Synthetic gene circuit evolution: Insights and opportunities at the mid-scale. Cell Chem Biol 2024:S2451-9456(24)00219-8. [PMID: 38925113 DOI: 10.1016/j.chembiol.2024.05.018] [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: 02/12/2024] [Revised: 05/07/2024] [Accepted: 05/30/2024] [Indexed: 06/28/2024]
Abstract
Directed evolution focuses on optimizing single genetic components for predefined engineering goals by artificial mutagenesis and selection. In contrast, experimental evolution studies the adaptation of entire genomes in serially propagated cell populations, to provide an experimental basis for evolutionary theory. There is a relatively unexplored gap at the middle ground between these two techniques, to evolve in vivo entire synthetic gene circuits with nontrivial dynamic function instead of single parts or whole genomes. We discuss the requirements for such mid-scale evolution, with hypothetical examples for evolving synthetic gene circuits by appropriate selection and targeted shuffling of a seed set of genetic components in vivo. Implementing similar methods should aid the rapid generation, functionalization, and optimization of synthetic gene circuits in various organisms and environments, accelerating both the development of biomedical and technological applications and the understanding of principles guiding regulatory network evolution.
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Affiliation(s)
- Christopher Helenek
- The Louis and Beatrice Laufer Center for Physical and Quantitative Biology, Stony Brook University, Stony Brook, NY 11794, USA; Department of Biomedical Engineering, Stony Brook University, Stony Brook, NY 11794, USA
| | - Rafał Krzysztoń
- The Louis and Beatrice Laufer Center for Physical and Quantitative Biology, Stony Brook University, Stony Brook, NY 11794, USA
| | - Julia Petreczky
- The Louis and Beatrice Laufer Center for Physical and Quantitative Biology, Stony Brook University, Stony Brook, NY 11794, USA; Department of Chemistry, Stony Brook University, Stony Brook, NY 11794, USA
| | - Yiming Wan
- The Louis and Beatrice Laufer Center for Physical and Quantitative Biology, Stony Brook University, Stony Brook, NY 11794, USA
| | - Mariana Cabral
- The Louis and Beatrice Laufer Center for Physical and Quantitative Biology, Stony Brook University, Stony Brook, NY 11794, USA; Department of Biomedical Engineering, Stony Brook University, Stony Brook, NY 11794, USA
| | - Damiano Coraci
- The Louis and Beatrice Laufer Center for Physical and Quantitative Biology, Stony Brook University, Stony Brook, NY 11794, USA
| | - Gábor Balázsi
- The Louis and Beatrice Laufer Center for Physical and Quantitative Biology, Stony Brook University, Stony Brook, NY 11794, USA; Department of Biomedical Engineering, Stony Brook University, Stony Brook, NY 11794, USA; Stony Brook Cancer Center, Stony Brook University, Stony Brook, NY 11794, USA.
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3
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Wan Y, Mu Q, Krzysztoń R, Cohen J, Coraci D, Helenek C, Tompkins C, Lin A, Farquhar K, Cross E, Wang J, Balázsi G. Adaptive DNA amplification of synthetic gene circuit opens a way to overcome cancer chemoresistance. Proc Natl Acad Sci U S A 2023; 120:e2303114120. [PMID: 38019857 DOI: 10.1073/pnas.2303114120] [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: 02/22/2023] [Accepted: 09/27/2023] [Indexed: 12/01/2023] Open
Abstract
Drug resistance continues to impede the success of cancer treatments, creating a need for experimental model systems that are broad, yet simple, to allow the identification of mechanisms and novel countermeasures applicable to many cancer types. To address these needs, we investigated a set of engineered mammalian cell lines with synthetic gene circuits integrated into their genome that evolved resistance to Puromycin. We identified DNA amplification as the mechanism underlying drug resistance in 4 out of 6 replicate populations. Triplex-forming oligonucleotide (TFO) treatment combined with Puromycin could efficiently suppress the growth of cell populations with DNA amplification. Similar observations in human cancer cell lines suggest that TFOs could be broadly applicable to mitigate drug resistance, one of the major difficulties in treating cancer.
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Affiliation(s)
- Yiming Wan
- Department of Biomedical Engineering, Stony Brook University, Stony Brook, NY 11794
- The Louis and Beatrice Laufer Center for Physical and Quantitative Biology, Stony Brook University, Stony Brook, NY 11794
| | - Quanhua Mu
- Department of Chemical and Biological Engineering, Division of Life Science, State Key Laboratory of Molecular Neuroscience, The Hong Kong University of Science and Technology, Hong Kong Special Administrative Region 999077, China
| | - Rafał Krzysztoń
- Department of Biomedical Engineering, Stony Brook University, Stony Brook, NY 11794
- The Louis and Beatrice Laufer Center for Physical and Quantitative Biology, Stony Brook University, Stony Brook, NY 11794
| | - Joseph Cohen
- Department of Biomedical Engineering, Stony Brook University, Stony Brook, NY 11794
- The Louis and Beatrice Laufer Center for Physical and Quantitative Biology, Stony Brook University, Stony Brook, NY 11794
| | - Damiano Coraci
- Department of Biomedical Engineering, Stony Brook University, Stony Brook, NY 11794
- The Louis and Beatrice Laufer Center for Physical and Quantitative Biology, Stony Brook University, Stony Brook, NY 11794
| | - Christopher Helenek
- Department of Biomedical Engineering, Stony Brook University, Stony Brook, NY 11794
- The Louis and Beatrice Laufer Center for Physical and Quantitative Biology, Stony Brook University, Stony Brook, NY 11794
| | | | - Annie Lin
- Department of Biomedical Engineering, Stony Brook University, Stony Brook, NY 11794
- The Louis and Beatrice Laufer Center for Physical and Quantitative Biology, Stony Brook University, Stony Brook, NY 11794
| | - Kevin Farquhar
- Department of Biomedical Engineering, Stony Brook University, Stony Brook, NY 11794
- The Louis and Beatrice Laufer Center for Physical and Quantitative Biology, Stony Brook University, Stony Brook, NY 11794
| | | | - Jiguang Wang
- Department of Chemical and Biological Engineering, Division of Life Science, State Key Laboratory of Molecular Neuroscience, The Hong Kong University of Science and Technology, Hong Kong Special Administrative Region 999077, China
| | - Gábor Balázsi
- Department of Biomedical Engineering, Stony Brook University, Stony Brook, NY 11794
- The Louis and Beatrice Laufer Center for Physical and Quantitative Biology, Stony Brook University, Stony Brook, NY 11794
- Stony Brook Cancer Center, Stony Brook University, Stony Brook, NY 11794
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4
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Wan Y, Cohen J, Szenk M, Farquhar KS, Coraci D, Krzysztoń R, Azukas J, Van Nest N, Smashnov A, Chern YJ, De Martino D, Nguyen LC, Bien H, Bravo-Cordero JJ, Chan CH, Rosner MR, Balázsi G. Nonmonotone invasion landscape by noise-aware control of metastasis activator levels. Nat Chem Biol 2023; 19:887-899. [PMID: 37231268 PMCID: PMC10299915 DOI: 10.1038/s41589-023-01344-z] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2022] [Accepted: 04/18/2023] [Indexed: 05/27/2023]
Abstract
A major pharmacological assumption is that lowering disease-promoting protein levels is generally beneficial. For example, inhibiting metastasis activator BACH1 is proposed to decrease cancer metastases. Testing such assumptions requires approaches to measure disease phenotypes while precisely adjusting disease-promoting protein levels. Here we developed a two-step strategy to integrate protein-level tuning, noise-aware synthetic gene circuits into a well-defined human genomic safe harbor locus. Unexpectedly, engineered MDA-MB-231 metastatic human breast cancer cells become more, then less and then more invasive as we tune BACH1 levels up, irrespective of the native BACH1. BACH1 expression shifts in invading cells, and expression of BACH1's transcriptional targets confirm BACH1's nonmonotone phenotypic and regulatory effects. Thus, chemical inhibition of BACH1 could have unwanted effects on invasion. Additionally, BACH1's expression variability aids invasion at high BACH1 expression. Overall, precisely engineered, noise-aware protein-level control is necessary and important to unravel disease effects of genes to improve clinical drug efficacy.
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Affiliation(s)
- Yiming Wan
- Department of Biomedical Engineering, Stony Brook University, Stony Brook, NY, USA
- Louis and Beatrice Laufer Center for Physical and Quantitative Biology, Stony Brook University, Stony Brook, NY, USA
| | - Joseph Cohen
- Department of Biomedical Engineering, Stony Brook University, Stony Brook, NY, USA
- Louis and Beatrice Laufer Center for Physical and Quantitative Biology, Stony Brook University, Stony Brook, NY, USA
| | - Mariola Szenk
- Department of Biomedical Engineering, Stony Brook University, Stony Brook, NY, USA
- Louis and Beatrice Laufer Center for Physical and Quantitative Biology, Stony Brook University, Stony Brook, NY, USA
| | - Kevin S Farquhar
- Department of Biomedical Engineering, Stony Brook University, Stony Brook, NY, USA
- Louis and Beatrice Laufer Center for Physical and Quantitative Biology, Stony Brook University, Stony Brook, NY, USA
- Genetics and Epigenetics Graduate Program, The University of Texas MD Anderson Cancer Center, UT Health Graduate School of Biomedical Sciences, Houston, TX, USA
| | - Damiano Coraci
- Louis and Beatrice Laufer Center for Physical and Quantitative Biology, Stony Brook University, Stony Brook, NY, USA
| | - Rafał Krzysztoń
- Department of Biomedical Engineering, Stony Brook University, Stony Brook, NY, USA
- Louis and Beatrice Laufer Center for Physical and Quantitative Biology, Stony Brook University, Stony Brook, NY, USA
| | - Joshua Azukas
- Department of Biomedical Engineering, Stony Brook University, Stony Brook, NY, USA
| | - Nicholas Van Nest
- Department of Biomedical Engineering, Stony Brook University, Stony Brook, NY, USA
- Louis and Beatrice Laufer Center for Physical and Quantitative Biology, Stony Brook University, Stony Brook, NY, USA
| | - Alex Smashnov
- Department of Biomedical Engineering, Stony Brook University, Stony Brook, NY, USA
- Louis and Beatrice Laufer Center for Physical and Quantitative Biology, Stony Brook University, Stony Brook, NY, USA
| | - Yi-Jye Chern
- Department of Pharmacological Sciences, Stony Brook University, Stony Brook, NY, USA
- Department of Molecular and Cellular Biology, Roswell Park Cancer Institute, Buffalo, NY, USA
| | - Daniela De Martino
- Department of Medicine, Division of Hematology and Oncology, Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Long Chi Nguyen
- Ben May Department for Cancer Research, University of Chicago, Chicago, IL, USA
| | - Harold Bien
- Louis and Beatrice Laufer Center for Physical and Quantitative Biology, Stony Brook University, Stony Brook, NY, USA
| | - Jose Javier Bravo-Cordero
- Department of Medicine, Division of Hematology and Oncology, Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Chia-Hsin Chan
- Department of Pharmacological Sciences, Stony Brook University, Stony Brook, NY, USA
- Department of Molecular and Cellular Biology, Roswell Park Cancer Institute, Buffalo, NY, USA
| | - Marsha Rich Rosner
- Ben May Department for Cancer Research, University of Chicago, Chicago, IL, USA
| | - Gábor Balázsi
- Department of Biomedical Engineering, Stony Brook University, Stony Brook, NY, USA.
- Louis and Beatrice Laufer Center for Physical and Quantitative Biology, Stony Brook University, Stony Brook, NY, USA.
- Stony Brook Cancer Center, Stony Brook University, Stony Brook, NY, USA.
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5
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Barajas C, Del Vecchio D. Synthetic biology by controller design. Curr Opin Biotechnol 2022; 78:102837. [PMID: 36343564 DOI: 10.1016/j.copbio.2022.102837] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2021] [Revised: 02/26/2022] [Accepted: 10/07/2022] [Indexed: 11/06/2022]
Abstract
Natural biological systems display complex regulation and synthetic biomolecular systems have been used to understand their natural counterparts and to parse sophisticated regulations into core design principles. At the same time, the engineering of biomolecular systems has unarguable potential to transform current and to enable new, yet-to-be-imagined, biotechnology applications. In this review, we discuss the progression of control systems design in synthetic biology, from the purpose of understanding the function of naturally occurring regulatory motifs to that of creating genetic circuits whose function is sufficiently robust for biotechnology applications.
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Affiliation(s)
- Carlos Barajas
- Department of Mechanical Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA.
| | - Domitilla Del Vecchio
- Department of Mechanical Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA
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6
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Prochazka L, Michaels YS, Lau C, Jones RD, Siu M, Yin T, Wu D, Jang E, Vázquez‐Cantú M, Gilbert PM, Kaul H, Benenson Y, Zandstra PW. Synthetic gene circuits for cell state detection and protein tuning in human pluripotent stem cells. Mol Syst Biol 2022; 18:e10886. [PMID: 36366891 PMCID: PMC9650275 DOI: 10.15252/msb.202110886] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2021] [Revised: 10/13/2022] [Accepted: 10/17/2022] [Indexed: 11/13/2022] Open
Abstract
During development, cell state transitions are coordinated through changes in the identity of molecular regulators in a cell type‐ and dose‐specific manner. The ability to rationally engineer such transitions in human pluripotent stem cells (hPSC) will enable numerous applications in regenerative medicine. Herein, we report the generation of synthetic gene circuits that can detect a desired cell state using AND‐like logic integration of endogenous miRNAs (classifiers) and, upon detection, produce fine‐tuned levels of output proteins using an miRNA‐mediated output fine‐tuning technology (miSFITs). Specifically, we created an “hPSC ON” circuit using a model‐guided miRNA selection and circuit optimization approach. The circuit demonstrates robust PSC‐specific detection and graded output protein production. Next, we used an empirical approach to create an “hPSC‐Off” circuit. This circuit was applied to regulate the secretion of endogenous BMP4 in a state‐specific and fine‐tuned manner to control the composition of differentiating hPSCs. Our work provides a platform for customized cell state‐specific control of desired physiological factors in hPSC, laying the foundation for programming cell compositions in hPSC‐derived tissues and beyond.
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Affiliation(s)
- Laura Prochazka
- Institute of Biomedical Engineering (BME) University of Toronto Toronto ON Canada
- Donnelly Centre for Cellular & Biomolecular Research University of Toronto Toronto ON Canada
| | - Yale S Michaels
- Michael Smith Laboratories University of British Columbia Vancouver BC Canada
- School of Biomedical Engineering University of British Columbia Vancouver BC Canada
| | - Charles Lau
- Institute of Biomedical Engineering (BME) University of Toronto Toronto ON Canada
- Donnelly Centre for Cellular & Biomolecular Research University of Toronto Toronto ON Canada
- Michael Smith Laboratories University of British Columbia Vancouver BC Canada
- School of Biomedical Engineering University of British Columbia Vancouver BC Canada
| | - Ross D Jones
- Michael Smith Laboratories University of British Columbia Vancouver BC Canada
- School of Biomedical Engineering University of British Columbia Vancouver BC Canada
| | - Mona Siu
- Michael Smith Laboratories University of British Columbia Vancouver BC Canada
- School of Biomedical Engineering University of British Columbia Vancouver BC Canada
| | - Ting Yin
- Institute of Biomedical Engineering (BME) University of Toronto Toronto ON Canada
- Donnelly Centre for Cellular & Biomolecular Research University of Toronto Toronto ON Canada
| | - Diana Wu
- Institute of Biomedical Engineering (BME) University of Toronto Toronto ON Canada
- Donnelly Centre for Cellular & Biomolecular Research University of Toronto Toronto ON Canada
| | - Esther Jang
- Institute of Biomedical Engineering (BME) University of Toronto Toronto ON Canada
- Donnelly Centre for Cellular & Biomolecular Research University of Toronto Toronto ON Canada
| | - Mercedes Vázquez‐Cantú
- Institute of Biomedical Engineering (BME) University of Toronto Toronto ON Canada
- Donnelly Centre for Cellular & Biomolecular Research University of Toronto Toronto ON Canada
- Swiss Federal Institute of Technology (ETH) Zürich, Department of Biosystems Science and Engineering (D‐BSSE) Basel Switzerland
| | - Penney M Gilbert
- Institute of Biomedical Engineering (BME) University of Toronto Toronto ON Canada
- Donnelly Centre for Cellular & Biomolecular Research University of Toronto Toronto ON Canada
- Department of Cell and Systems Biology University of Toronto Toronto ON Canada
| | - Himanshu Kaul
- School of Engineering University of Leicester Leicester UK
- Department of Respiratory Sciences University of Leicester Leicester UK
| | - Yaakov Benenson
- Swiss Federal Institute of Technology (ETH) Zürich, Department of Biosystems Science and Engineering (D‐BSSE) Basel Switzerland
| | - Peter W Zandstra
- Michael Smith Laboratories University of British Columbia Vancouver BC Canada
- School of Biomedical Engineering University of British Columbia Vancouver BC Canada
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7
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Jiang A, Song Y, You J, Zhang X, Xu M, Rao Z. High-yield ectoine production in engineered Corynebacterium glutamicum by fine metabolic regulation via plug-in repressor library. BIORESOURCE TECHNOLOGY 2022; 362:127802. [PMID: 36007762 DOI: 10.1016/j.biortech.2022.127802] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/11/2022] [Revised: 08/15/2022] [Accepted: 08/16/2022] [Indexed: 06/15/2023]
Abstract
Ectoine is a high-value protective and stabilizing agent with different applications in biopharmaceuticals, biotechnology, and fine chemicals. Here, efficient production of ectoine in Corynebacterium glutamicum was achieved by combination of metabolic engineering and plug-in repressor library strategy. First, the ectBAC cluster from Pseudomonas stutzeri was introduced into strain K02, and the titer of the obtained strain was 2.12 g/L. Metabolic engineering was then performed for further optimization, including removal of competing pathways (pck and ldh knockout), deletion of glycolysis repressor (sugR knockout), and enhancement of precursor supply (overexpression of Ecasd and CglysCS301Y). Next, two repressor libraries were designed for targeted flux control to improve ectoine production. Finally, strain CB5L6 produced 45.52 g/L ectoine and had the highest yield in C. glutamicum. For the first time, plug-in repressor library was employed to engineer C. glutamicum for metabolites production, which will provide a guideline for the construction of microbial cell factories.
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Affiliation(s)
- An Jiang
- Key Laboratory of Industrial Biotechnology of the Ministry of Education, School of Biotechnology, Jiangnan University, Wuxi, Jiangsu 214122, China
| | - Yunhai Song
- Key Laboratory of Industrial Biotechnology of the Ministry of Education, School of Biotechnology, Jiangnan University, Wuxi, Jiangsu 214122, China
| | - Jia You
- Key Laboratory of Industrial Biotechnology of the Ministry of Education, School of Biotechnology, Jiangnan University, Wuxi, Jiangsu 214122, China
| | - Xian Zhang
- Key Laboratory of Industrial Biotechnology of the Ministry of Education, School of Biotechnology, Jiangnan University, Wuxi, Jiangsu 214122, China
| | - Meijuan Xu
- Key Laboratory of Industrial Biotechnology of the Ministry of Education, School of Biotechnology, Jiangnan University, Wuxi, Jiangsu 214122, China.
| | - Zhiming Rao
- Key Laboratory of Industrial Biotechnology of the Ministry of Education, School of Biotechnology, Jiangnan University, Wuxi, Jiangsu 214122, China
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8
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Nussinov R, Tsai CJ, Jang H. Allostery, and how to define and measure signal transduction. Biophys Chem 2022; 283:106766. [PMID: 35121384 PMCID: PMC8898294 DOI: 10.1016/j.bpc.2022.106766] [Citation(s) in RCA: 23] [Impact Index Per Article: 11.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2021] [Revised: 01/21/2022] [Accepted: 01/24/2022] [Indexed: 12/15/2022]
Abstract
Here we ask: What is productive signaling? How to define it, how to measure it, and most of all, what are the parameters that determine it? Further, what determines the strength of signaling from an upstream to a downstream node in a specific cell? These questions have either not been considered or not entirely resolved. The requirements for the signal to propagate downstream to activate (repress) transcription have not been considered either. Yet, the questions are pivotal to clarify, especially in diseases such as cancer where determination of signal propagation can point to cell proliferation and to emerging drug resistance, and to neurodevelopmental disorders, such as RASopathy, autism, attention-deficit/hyperactivity disorder (ADHD), and cerebral palsy. Here we propose a framework for signal transduction from an upstream to a downstream node addressing these questions. Defining cellular processes, experimentally measuring them, and devising powerful computational AI-powered algorithms that exploit the measurements, are essential for quantitative science.
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Affiliation(s)
- Ruth Nussinov
- Computational Structural Biology Section, Frederick National Laboratory for Cancer Research in the Laboratory of Cancer Immunometabolism, National Cancer Institute, Frederick, MD 21702, USA; Department of Human Molecular Genetics and Biochemistry, Sackler School of Medicine, Tel Aviv University, Tel Aviv 69978, Israel.
| | - Chung-Jung Tsai
- Computational Structural Biology Section, Frederick National Laboratory for Cancer Research in the Laboratory of Cancer Immunometabolism, National Cancer Institute, Frederick, MD 21702, USA
| | - Hyunbum Jang
- Computational Structural Biology Section, Frederick National Laboratory for Cancer Research in the Laboratory of Cancer Immunometabolism, National Cancer Institute, Frederick, MD 21702, USA
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9
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Fierro F, Vaca I, Castillo NI, García-Rico RO, Chávez R. Penicillium chrysogenum, a Vintage Model with a Cutting-Edge Profile in Biotechnology. Microorganisms 2022; 10:microorganisms10030573. [PMID: 35336148 PMCID: PMC8954384 DOI: 10.3390/microorganisms10030573] [Citation(s) in RCA: 17] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2021] [Revised: 02/15/2022] [Accepted: 02/17/2022] [Indexed: 12/20/2022] Open
Abstract
The discovery of penicillin entailed a decisive breakthrough in medicine. No other medical advance has ever had the same impact in the clinical practise. The fungus Penicillium chrysogenum (reclassified as P. rubens) has been used for industrial production of penicillin ever since the forties of the past century; industrial biotechnology developed hand in hand with it, and currently P. chrysogenum is a thoroughly studied model for secondary metabolite production and regulation. In addition to its role as penicillin producer, recent synthetic biology advances have put P. chrysogenum on the path to become a cell factory for the production of metabolites with biotechnological interest. In this review, we tell the history of P. chrysogenum, from the discovery of penicillin and the first isolation of strains with high production capacity to the most recent research advances with the fungus. We will describe how classical strain improvement programs achieved the goal of increasing production and how the development of different molecular tools allowed further improvements. The discovery of the penicillin gene cluster, the origin of the penicillin genes, the regulation of penicillin production, and a compilation of other P. chrysogenum secondary metabolites will also be covered and updated in this work.
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Affiliation(s)
- Francisco Fierro
- Departamento de Biotecnología, Universidad Autónoma Metropolitana-Unidad Iztapalapa, Ciudad de México 09340, Mexico
- Correspondence:
| | - Inmaculada Vaca
- Departamento de Química, Facultad de Ciencias, Universidad de Chile, Santiago 7800003, Chile;
| | - Nancy I. Castillo
- Grupo de Investigación en Ciencias Biológicas y Químicas, Facultad de Ciencias, Universidad Antonio Nariño, Bogotá 110231, Colombia;
| | - Ramón Ovidio García-Rico
- Grupo de Investigación GIMBIO, Departamento De Microbiología, Facultad de Ciencias Básicas, Universidad de Pamplona, Pamplona 543050, Colombia;
| | - Renato Chávez
- Departamento de Biología, Facultad de Química y Biología, Universidad de Santiago de Chile, Santiago 9170020, Chile;
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10
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Zhu D, Johnson HJ, Chen J, Schaffer DV. Optogenetic Application to Investigating Cell Behavior and Neurological Disease. Front Cell Neurosci 2022; 16:811493. [PMID: 35273478 PMCID: PMC8902366 DOI: 10.3389/fncel.2022.811493] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2021] [Accepted: 01/04/2022] [Indexed: 11/13/2022] Open
Abstract
Cells reside in a dynamic microenvironment that presents them with regulatory signals that vary in time, space, and amplitude. The cell, in turn, interprets these signals and accordingly initiates downstream processes including cell proliferation, differentiation, migration, and self-organization. Conventional approaches to perturb and investigate signaling pathways (e.g., agonist/antagonist addition, overexpression, silencing, knockouts) are often binary perturbations that do not offer precise control over signaling levels, and/or provide limited spatial or temporal control. In contrast, optogenetics leverages light-sensitive proteins to control cellular signaling dynamics and target gene expression and, by virtue of precise hardware control over illumination, offers the capacity to interrogate how spatiotemporally varying signals modulate gene regulatory networks and cellular behaviors. Recent studies have employed various optogenetic systems in stem cell, embryonic, and somatic cell patterning studies, which have addressed fundamental questions of how cell-cell communication, subcellular protein localization, and signal integration affect cell fate. Other efforts have explored how alteration of signaling dynamics may contribute to neurological diseases and have in the process created physiologically relevant models that could inform new therapeutic strategies. In this review, we focus on emerging applications within the expanding field of optogenetics to study gene regulation, cell signaling, neurodevelopment, and neurological disorders, and we comment on current limitations and future directions for the growth of the field.
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Affiliation(s)
- Danqing Zhu
- California Institute for Quantitative Biosciences, University of California, Berkeley, Berkeley, CA, United States
| | - Hunter J. Johnson
- Department of Bioengineering, University of California, Berkeley, Berkeley, CA, United States
- Graduate Program in Bioengineering, University of California, San Francisco, San Francisco, CA, United States
- Graduate Program in Bioengineering, University of California, Berkeley, Berkeley, CA, United States
| | - Jun Chen
- California Institute for Quantitative Biosciences, University of California, Berkeley, Berkeley, CA, United States
| | - David V. Schaffer
- California Institute for Quantitative Biosciences, University of California, Berkeley, Berkeley, CA, United States
- Department of Bioengineering, University of California, Berkeley, Berkeley, CA, United States
- Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, CA, United States
- Department of Chemical and Biomolecular Engineering, University of California, Berkeley, Berkeley, CA, United States
- Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, CA, United States
- *Correspondence: David V. Schaffer
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11
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Komera I, Gao C, Guo L, Hu G, Chen X, Liu L. Bifunctional optogenetic switch for improving shikimic acid production in E. coli. BIOTECHNOLOGY FOR BIOFUELS AND BIOPRODUCTS 2022; 15:13. [PMID: 35418155 PMCID: PMC8822657 DOI: 10.1186/s13068-022-02111-3] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/22/2021] [Accepted: 01/28/2022] [Indexed: 12/19/2022]
Abstract
BACKGROUND Biomass formation and product synthesis decoupling have been proven to be promising to increase the titer of desired value add products. Optogenetics provides a potential strategy to develop light-induced circuits that conditionally control metabolic flux redistribution for enhanced microbial production. However, the limited number of light-sensitive proteins available to date hinders the progress of light-controlled tools. RESULTS To address these issues, two optogenetic systems (TPRS and TPAS) were constructed by reprogramming the widely used repressor TetR and protease TEVp to expand the current optogenetic toolkit. By merging the two systems, a bifunctional optogenetic switch was constructed to enable orthogonally regulated gene transcription and protein accumulation. Application of this bifunctional switch to decouple biomass formation and shikimic acid biosynthesis allowed 35 g/L of shikimic acid production in a minimal medium from glucose, representing the highest titer reported to date by E. coli without the addition of any chemical inducers and expensive aromatic amino acids. This titer was further boosted to 76 g/L when using rich medium fermentation. CONCLUSION The cost effective and light-controlled switch reported here provides important insights into environmentally friendly tools for metabolic pathway regulation and should be applicable to the production of other value-add chemicals.
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Affiliation(s)
- Irene Komera
- State Key Laboratory of Food Science and Technology, Jiangnan University, Wuxi, 214122, China.,International Joint Laboratory On Food Safety, Jiangnan University, Wuxi, 214122, China
| | - Cong Gao
- State Key Laboratory of Food Science and Technology, Jiangnan University, Wuxi, 214122, China.,International Joint Laboratory On Food Safety, Jiangnan University, Wuxi, 214122, China
| | - Liang Guo
- State Key Laboratory of Food Science and Technology, Jiangnan University, Wuxi, 214122, China.,International Joint Laboratory On Food Safety, Jiangnan University, Wuxi, 214122, China
| | - Guipeng Hu
- School of Pharmaceutical Science, Jiangnan University, Wuxi, 214122, China
| | - Xiulai Chen
- State Key Laboratory of Food Science and Technology, Jiangnan University, Wuxi, 214122, China.,International Joint Laboratory On Food Safety, Jiangnan University, Wuxi, 214122, China
| | - Liming Liu
- State Key Laboratory of Food Science and Technology, Jiangnan University, Wuxi, 214122, China. .,International Joint Laboratory On Food Safety, Jiangnan University, Wuxi, 214122, China.
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12
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Krzysztoń R, Wan Y, Petreczky J, Balázsi G. Gene-circuit therapy on the horizon: synthetic biology tools for engineered therapeutics. Acta Biochim Pol 2021; 68:377-383. [PMID: 34460209 PMCID: PMC8590856 DOI: 10.18388/abp.2020_5744] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2021] [Accepted: 07/19/2021] [Indexed: 01/17/2023]
Abstract
Therapeutic genome modification requires precise control over the introduced therapeutic functions. Current approaches of gene and cell therapy fail to deliver such command and rely on semi-quantitative methods with limited influence on timing, contextuality and levels of transgene expression, and hence on therapeutic function. Synthetic biology offers new opportunities for quantitative functionality in designing therapeutic systems and their components. Here, we discuss synthetic biology tools in their therapeutic context, with examples of proof-of-principle and clinical applications of engineered synthetic biomolecules and higher-order functional systems, i.e. gene circuits. We also present the prospects of future development towards advanced gene-circuit therapy.
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Affiliation(s)
- Rafał Krzysztoń
- Biomedical Engineering Department, Stony Brook University, Stony Brook, NY 11974, USA
- The Louis & Beatrice Laufer Center for Physical and Quantitative Biology, Stony Brook University, Stony Brook, NY 11794, USA
| | - Yiming Wan
- Biomedical Engineering Department, Stony Brook University, Stony Brook, NY 11974, USA
- The Louis & Beatrice Laufer Center for Physical and Quantitative Biology, Stony Brook University, Stony Brook, NY 11794, USA
| | - Julia Petreczky
- Biomedical Engineering Department, Stony Brook University, Stony Brook, NY 11974, USA
- The Louis & Beatrice Laufer Center for Physical and Quantitative Biology, Stony Brook University, Stony Brook, NY 11794, USA
| | - Gábor Balázsi
- Biomedical Engineering Department, Stony Brook University, Stony Brook, NY 11974, USA
- The Louis & Beatrice Laufer Center for Physical and Quantitative Biology, Stony Brook University, Stony Brook, NY 11794, USA
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13
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Lee JY, Cha S, Lee JH, Lim HG, Noh MH, Kang CW, Jung GY. Plug-in repressor library for precise regulation of metabolic flux in Escherichia coli. Metab Eng 2021; 67:365-372. [PMID: 34333137 DOI: 10.1016/j.ymben.2021.07.013] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/04/2021] [Revised: 07/10/2021] [Accepted: 07/28/2021] [Indexed: 10/20/2022]
Abstract
In metabolic engineering, enhanced production of value-added chemicals requires precise flux control between growth-essential competing and production pathways. Although advances in synthetic biology have facilitated the exploitation of a number of genetic elements for precise flux control, their use requires expensive inducers, or more importantly, needs complex and time-consuming processes to design and optimize appropriate regulator components, case-by-case. To overcome this issue, we devised the plug-in repressor libraries for target-specific flux control, in which expression levels of the repressors were diversified using degenerate 5' untranslated region (5' UTR) sequences employing the UTR Library Designer. After we validated a wide expression range of the repressor libraries, they were applied to improve the production of lycopene from glucose and 3-hydroxypropionic acid (3-HP) from acetate in Escherichia coli via precise flux rebalancing to enlarge precursor pools. Consequently, we successfully achieved optimal carbon fluxes around the precursor nodes for efficient production. The most optimized strains were observed to produce 2.59 g/L of 3-HP and 11.66 mg/L of lycopene, which were improved 16.5-fold and 2.82-fold, respectively, compared to those produced by the parental strains. These results indicate that carbon flux rebalancing using the plug-in library is a powerful strategy for efficient production of value-added chemicals in E. coli.
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Affiliation(s)
- Ji Yeon Lee
- School of Interdisciplinary Bioscience and Bioengineering, Pohang University of Science and Technology, 77 Cheongam-Ro, Nam-Gu, Pohang, Gyeongbuk, 37673, South Korea
| | - Sanghak Cha
- Department of Chemical Engineering, Pohang University of Science and Technology, 77 Cheongam-Ro, Nam-Gu, Pohang, Gyeongbuk, 37673, South Korea
| | - Ji Hoon Lee
- School of Interdisciplinary Bioscience and Bioengineering, Pohang University of Science and Technology, 77 Cheongam-Ro, Nam-Gu, Pohang, Gyeongbuk, 37673, South Korea
| | - Hyun Gyu Lim
- Department of Chemical Engineering, Pohang University of Science and Technology, 77 Cheongam-Ro, Nam-Gu, Pohang, Gyeongbuk, 37673, South Korea
| | - Myung Hyun Noh
- Department of Chemical Engineering, Pohang University of Science and Technology, 77 Cheongam-Ro, Nam-Gu, Pohang, Gyeongbuk, 37673, South Korea
| | - Chae Won Kang
- Department of Chemical Engineering, Pohang University of Science and Technology, 77 Cheongam-Ro, Nam-Gu, Pohang, Gyeongbuk, 37673, South Korea
| | - Gyoo Yeol Jung
- School of Interdisciplinary Bioscience and Bioengineering, Pohang University of Science and Technology, 77 Cheongam-Ro, Nam-Gu, Pohang, Gyeongbuk, 37673, South Korea; Department of Chemical Engineering, Pohang University of Science and Technology, 77 Cheongam-Ro, Nam-Gu, Pohang, Gyeongbuk, 37673, South Korea.
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14
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Shakiba N, Jones RD, Weiss R, Del Vecchio D. Context-aware synthetic biology by controller design: Engineering the mammalian cell. Cell Syst 2021; 12:561-592. [PMID: 34139166 PMCID: PMC8261833 DOI: 10.1016/j.cels.2021.05.011] [Citation(s) in RCA: 27] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2020] [Revised: 04/19/2021] [Accepted: 05/14/2021] [Indexed: 12/25/2022]
Abstract
The rise of systems biology has ushered a new paradigm: the view of the cell as a system that processes environmental inputs to drive phenotypic outputs. Synthetic biology provides a complementary approach, allowing us to program cell behavior through the addition of synthetic genetic devices into the cellular processor. These devices, and the complex genetic circuits they compose, are engineered using a design-prototype-test cycle, allowing for predictable device performance to be achieved in a context-dependent manner. Within mammalian cells, context effects impact device performance at multiple scales, including the genetic, cellular, and extracellular levels. In order for synthetic genetic devices to achieve predictable behaviors, approaches to overcome context dependence are necessary. Here, we describe control systems approaches for achieving context-aware devices that are robust to context effects. We then consider cell fate programing as a case study to explore the potential impact of context-aware devices for regenerative medicine applications.
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Affiliation(s)
- Nika Shakiba
- Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; Synthetic Biology Center, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.
| | - Ross D Jones
- Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; Synthetic Biology Center, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.
| | - Ron Weiss
- Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; Synthetic Biology Center, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.
| | - Domitilla Del Vecchio
- Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; Synthetic Biology Center, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; Department of Mechanical Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.
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15
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Ding N, Zhou S, Deng Y. Transcription-Factor-based Biosensor Engineering for Applications in Synthetic Biology. ACS Synth Biol 2021; 10:911-922. [PMID: 33899477 DOI: 10.1021/acssynbio.0c00252] [Citation(s) in RCA: 59] [Impact Index Per Article: 19.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]
Abstract
Transcription-factor-based biosensors (TFBs) are often used for metabolite detection, adaptive evolution, and metabolic flux control. However, designing TFBs with superior performance for applications in synthetic biology remains challenging. Specifically, natural TFBs often do not meet real-time detection requirements owing to their slow response times and inappropriate dynamic ranges, detection ranges, sensitivity, and selectivity. Furthermore, designing and optimizing complex dynamic regulation networks is time-consuming and labor-intensive. This Review highlights TFB-based applications and recent engineering strategies ranging from traditional trial-and-error approaches to novel computer-model-based rational design approaches. The limitations of the applications and these engineering strategies are additionally reviewed.
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Affiliation(s)
- Nana Ding
- National Engineering Laboratory for Cereal Fermentation Technology (NELCF), Jiangnan University, 1800 Lihu Road, Wuxi, Jiangsu 214122, China
- Jiangsu Provincial Research Center for Bioactive Product Processing Technology, Jiangnan University, 1800 Lihu Road, Wuxi, Jiangsu 214122, China
| | - Shenghu Zhou
- National Engineering Laboratory for Cereal Fermentation Technology (NELCF), Jiangnan University, 1800 Lihu Road, Wuxi, Jiangsu 214122, China
- Jiangsu Provincial Research Center for Bioactive Product Processing Technology, Jiangnan University, 1800 Lihu Road, Wuxi, Jiangsu 214122, China
| | - Yu Deng
- National Engineering Laboratory for Cereal Fermentation Technology (NELCF), Jiangnan University, 1800 Lihu Road, Wuxi, Jiangsu 214122, China
- Jiangsu Provincial Research Center for Bioactive Product Processing Technology, Jiangnan University, 1800 Lihu Road, Wuxi, Jiangsu 214122, China
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16
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Zhang Y, Ding W, Wang Z, Zhao H, Shi S. Development of Host-Orthogonal Genetic Systems for Synthetic Biology. Adv Biol (Weinh) 2021; 5:e2000252. [PMID: 33729696 DOI: 10.1002/adbi.202000252] [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: 09/03/2020] [Revised: 11/18/2020] [Indexed: 12/17/2022]
Abstract
The construction of a host-orthogonal genetic system can not only minimize the impact of host-specific nuances on fine-tuning of gene expression, but also expand cellular functions such as in vivo continuous evolution of genes based on an error-prone DNA polymerase. It represents an emerging powerful approach for making biology easier to engineer. In this review, the recent advances are described on the design of genetic systems that can be stably inherited in the host cells and are responsible for important biological processes including DNA replication, RNA transcription, protein translation, and gene regulation. Their applications in synthetic biology are summarized and the future challenges and opportunities are discussed in developing such systems.
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Affiliation(s)
- Yang Zhang
- Beijing Advanced Innovation Center for Soft Matter Science and Engineering, Beijing University of Chemical Technology, Beijing, 100029, P. R. China
| | - Wentao Ding
- Beijing Advanced Innovation Center for Soft Matter Science and Engineering, Beijing University of Chemical Technology, Beijing, 100029, P. R. China.,Key Laboratory of Food Nutrition and Safety (Tianjin University of Science and Technology) Ministry of Education, College of Food Engineering and Biotechnology, Tianjin University of Science and Technology, No. 29, 13th Avenue, TEDA, Tianjin, 300457, P. R. China
| | - Zhihui Wang
- Beijing Advanced Innovation Center for Soft Matter Science and Engineering, Beijing University of Chemical Technology, Beijing, 100029, P. R. China
| | - Huimin Zhao
- Department of Chemical and Biomolecular Engineering, University of Illinois at Urbana-Champaign, Urbana, IL, 61801, USA
| | - Shuobo Shi
- Beijing Advanced Innovation Center for Soft Matter Science and Engineering, Beijing University of Chemical Technology, Beijing, 100029, P. R. China
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17
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Haellman V, Saxena P, Jiang Y, Fussenegger M. Rational design and optimization of synthetic gene switches for controlling cell-fate decisions in pluripotent stem cells. Metab Eng 2021; 65:99-110. [PMID: 33744461 DOI: 10.1016/j.ymben.2021.03.009] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2020] [Revised: 02/25/2021] [Accepted: 03/09/2021] [Indexed: 11/26/2022]
Abstract
Advances in synthetic biology have enabled robust control of cell behavior by using tunable genetic circuits to regulate gene expression in a ligand-dependent manner. Such circuits can be used to direct the differentiation of pluripotent stem cells (PSCs) towards desired cell types, but rational design of synthetic gene circuits in PSCs is challenging due to the variable intracellular environment. Here, we provide a framework for implementing synthetic gene switches in PSCs based on combinations of tunable transcriptional, structural, and posttranslational elements that can be engineered as required, using the vanillic acid-controlled transcriptional activator (VanA) as a model system. We further show that the VanA system can be multiplexed with the well-established reverse tetracycline-controlled transcriptional activator (rtTA) system to enable independent control of the expression of different transcription factors in human induced PSCs in order to enhance lineage specification towards early pancreatic progenitors. This work represents a first step towards standardizing the design and construction of synthetic gene switches for building robust gene-regulatory networks to guide stem cell differentiation towards a desired cell fate.
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Affiliation(s)
- Viktor Haellman
- Department of Biosystems Science and Engineering, ETH Zurich, Mattenstrasse 26, CH, 4058, Basel, Switzerland
| | - Pratik Saxena
- Department of Biosystems Science and Engineering, ETH Zurich, Mattenstrasse 26, CH, 4058, Basel, Switzerland
| | - Yanrui Jiang
- Department of Biosystems Science and Engineering, ETH Zurich, Mattenstrasse 26, CH, 4058, Basel, Switzerland
| | - Martin Fussenegger
- Department of Biosystems Science and Engineering, ETH Zurich, Mattenstrasse 26, CH, 4058, Basel, Switzerland; Faculty of Science, University of Basel, Mattenstrasse 26, CH, 4058, Basel, Switzerland.
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18
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Miller CA, Ho JM, Parks SE, Bennett MR. Macrolide Biosensor Optimization through Cellular Substrate Sequestration. ACS Synth Biol 2021; 10:258-264. [PMID: 33555859 PMCID: PMC7901672 DOI: 10.1021/acssynbio.0c00572] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
Abstract
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Developing and optimizing small-molecule biosensors is a central goal of synthetic
biology. Here we incorporate additional cellular components to improve biosensor
sensitivity by preventing target molecules from diffusing out of cells. We demonstrate
that trapping erythromycin within Escherichia coli through
phosphorylation increases the sensitivity of its biosensor (MphR) by approximately
10-fold. When combined with prior engineering efforts, our optimized biosensor can
detect erythromycin concentrations as low as 13 nM. We show that this strategy works
with a range of macrolide substrates, enabling the potential usage of our optimized
system for drug development and metabolic engineering. This strategy can be extended in
future studies to improve the sensitivity of other biosensors. Our findings further
suggest that many naturally evolved genes involved in resistance to multiple classes of
antibiotics may increase intracellular drug concentrations to modulate their own
expression, acting as a form of regulatory feedback.
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Affiliation(s)
- Corwin A. Miller
- Department of Biosciences, Rice University, 6100 Main Street, Houston, Texas 77005, United States
| | - Joanne M. Ho
- Department of Biosciences, Rice University, 6100 Main Street, Houston, Texas 77005, United States
| | - Sydney E. Parks
- Department of Biosciences, Rice University, 6100 Main Street, Houston, Texas 77005, United States
| | - Matthew R. Bennett
- Department of Biosciences, Rice University, 6100 Main Street, Houston, Texas 77005, United States
- Department of Bioengineering, Rice University, 6100 Main Street, Houston, Texas 77005, United States
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19
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Duan Y, Zhai W, Liu W, Zhang X, Shi JS, Zhang X, Xu Z. Fine-Tuning Multi-Gene Clusters via Well-Characterized Gene Expression Regulatory Elements: Case Study of the Arginine Synthesis Pathway in C. glutamicum. ACS Synth Biol 2021; 10:38-48. [PMID: 33382575 DOI: 10.1021/acssynbio.0c00405] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
Promoters and ribosome binding sites (RBSs) are routinely applied in gene expression regulation, but their orthogonality and combinatorial effects have not yet been systematically studied in Corynebacterium glutamicum. Here, 17 core promoters and 29 RBSs in C. glutamicum were characterized, which exhibited 470-fold and 430-fold in transcriptional and translational activity, respectively. By comparing the expression of two reporter genes regulated by multiple RBSs, the RBS efficacy showed significant dependence on the gene context, besides the RBSs' strength, reflecting the poor orthogonality of RBSs. Bicistron-modified RBS (referred as bc-RBS) was adapted to C. glutamicum, which improved RBS reliability. By coupling a series of promoters with RBSs/bc-RBSs, a much broader regulation range that spanned 4 orders of magnitude was observed compared with that of a sole element, and the contribution to gene expression of RBS was more than that of promoter. Finally, promoters and RBSs were applied as built-in elements to fine-tune the gene cluster in the arginine synthesis pathway in C. glutamicum. Compared with the original strain, more arginine (1.61-fold) or citrulline (2.35-fold) was accumulated in a 7 L bioreactor by strains with the gene expression regulation system rationally engineered. We demonstrated that, via combination of well-characterized gene elements, and overall consideration for both transcription and translation, the biosynthesis pathway can be effectively balanced, and the yield of a target metabolite can be further improved.
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Affiliation(s)
- Yanting Duan
- National Engineering Laboratory for Cereal Fermentation Technology, Key Laboratory of Industrial Biotechnology, Jiangnan University, 1800 Lihu Avenue, Wuxi 214122, China
- Biotechnology of Ministry of Education, School of Biotechnology, Jiangnan University, 1800 Lihu Avenue, Wuxi 214122, China
| | - Weiji Zhai
- National Engineering Laboratory for Cereal Fermentation Technology, Key Laboratory of Industrial Biotechnology, Jiangnan University, 1800 Lihu Avenue, Wuxi 214122, China
- Biotechnology of Ministry of Education, School of Biotechnology, Jiangnan University, 1800 Lihu Avenue, Wuxi 214122, China
| | - Weijia Liu
- Biotechnology of Ministry of Education, School of Biotechnology, Jiangnan University, 1800 Lihu Avenue, Wuxi 214122, China
| | - Xiaomei Zhang
- School of Pharmaceutical Science, Jiangnan University, 1800 Lihu Avenue, Wuxi 214122, China
- Jiangsu Engineering Research Center for Bioactive Products Processing Technology, Jiangnan University, 1800 Lihu Avenue, Wuxi 214122, China
| | - Jin-Song Shi
- School of Pharmaceutical Science, Jiangnan University, 1800 Lihu Avenue, Wuxi 214122, China
- Jiangsu Engineering Research Center for Bioactive Products Processing Technology, Jiangnan University, 1800 Lihu Avenue, Wuxi 214122, China
| | - Xiaojuan Zhang
- National Engineering Laboratory for Cereal Fermentation Technology, Key Laboratory of Industrial Biotechnology, Jiangnan University, 1800 Lihu Avenue, Wuxi 214122, China
- Biotechnology of Ministry of Education, School of Biotechnology, Jiangnan University, 1800 Lihu Avenue, Wuxi 214122, China
| | - Zhenghong Xu
- National Engineering Laboratory for Cereal Fermentation Technology, Key Laboratory of Industrial Biotechnology, Jiangnan University, 1800 Lihu Avenue, Wuxi 214122, China
- Biotechnology of Ministry of Education, School of Biotechnology, Jiangnan University, 1800 Lihu Avenue, Wuxi 214122, China
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20
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Jones RD, Qian Y, Siciliano V, DiAndreth B, Huh J, Weiss R, Del Vecchio D. An endoribonuclease-based feedforward controller for decoupling resource-limited genetic modules in mammalian cells. Nat Commun 2020; 11:5690. [PMID: 33173034 PMCID: PMC7656454 DOI: 10.1038/s41467-020-19126-9] [Citation(s) in RCA: 48] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2020] [Accepted: 09/18/2020] [Indexed: 12/17/2022] Open
Abstract
Synthetic biology has the potential to bring forth advanced genetic devices for applications in healthcare and biotechnology. However, accurately predicting the behavior of engineered genetic devices remains difficult due to lack of modularity, wherein a device's output does not depend only on its intended inputs but also on its context. One contributor to lack of modularity is loading of transcriptional and translational resources, which can induce coupling among otherwise independently-regulated genes. Here, we quantify the effects of resource loading in engineered mammalian genetic systems and develop an endoribonuclease-based feedforward controller that can adapt the expression level of a gene of interest to significant resource loading in mammalian cells. Near-perfect adaptation to resource loads is facilitated by high production and catalytic rates of the endoribonuclease. Our design is portable across cell lines and enables predictable tuning of controller function. Ultimately, our controller is a general-purpose device for predictable, robust, and context-independent control of gene expression.
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Affiliation(s)
- Ross D Jones
- Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA
- Synthetic Biology Center, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA
| | - Yili Qian
- Synthetic Biology Center, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA
- Department of Mechanical Engineering, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA
| | - Velia Siciliano
- Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA
- Synthetic Biology Center, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA
- Instituto Italiano di Tecnologia, Napoli, 80125, Italy
| | - Breanna DiAndreth
- Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA
- Synthetic Biology Center, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA
| | - Jin Huh
- Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA
- Synthetic Biology Center, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA
| | - Ron Weiss
- Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA.
- Synthetic Biology Center, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA.
- Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA.
| | - Domitilla Del Vecchio
- Synthetic Biology Center, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA.
- Department of Mechanical Engineering, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA.
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