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Pham C, Stogios PJ, Savchenko A, Mahadevan R. Computation-guided transcription factor biosensor specificity engineering for adipic acid detection. Comput Struct Biotechnol J 2024; 23:2211-2219. [PMID: 38817964 PMCID: PMC11137364 DOI: 10.1016/j.csbj.2024.05.002] [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: 12/13/2023] [Revised: 05/01/2024] [Accepted: 05/02/2024] [Indexed: 06/01/2024] Open
Abstract
Transcription factor (TF)-based biosensors that connect small-molecule sensing with readouts such as fluorescence have proven to be useful synthetic biology tools for applications in biotechnology. However, the development of specific TF-based biosensors is hindered by the limited repertoire of TFs specific for molecules of interest since current construction methods rely on a limited set of characterized TFs. In this study, we present an approach for engineering the specificity of TFs through a computation-based workflow using molecular docking that enables targeted alteration of TF ligand specificity. Using this method, we engineer the LysR family BenM TF to alter its specificity from its cognate ligand cis,cis-muconic acid to adipic acid through a single amino acid substitution identified by our computational workflow. When implemented in a cell-free system, the engineered biosensor shows higher ligand sensitivity, expanding the potential applications of this circuit. We further investigate ligand binding through molecular dynamics to analyze the substitution, elucidating the impact of modulating a single amino acid position on the mechanism of BenM ligand binding. This study represents the first application of biomolecular modeling methods for altering BenM specificity and for gaining insights into how mutations influence the structural dynamics of BenM. Such methods can potentially be applied to other TFs to alter specificity and analyze the dynamics responsible for these changes, highlighting the applicability of computational tools for informing experiments. In addition, our developed adipic acid biosensor can be applied for the identification and engineering of enzymes to produce adipic acid.
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Affiliation(s)
- Chester Pham
- Department of Chemical Engineering and Applied Chemistry, University of Toronto, Ontario, Canada
| | - Peter J. Stogios
- Department of Chemical Engineering and Applied Chemistry, University of Toronto, Ontario, Canada
| | - Alexei Savchenko
- Department of Chemical Engineering and Applied Chemistry, University of Toronto, Ontario, Canada
- Department of Microbiology, Immunology and Infectious Diseases, University of Calgary, Calgary, Alberta, Canada
| | - Radhakrishnan Mahadevan
- Department of Chemical Engineering and Applied Chemistry, University of Toronto, Ontario, Canada
- The Institute of Biomedical Engineering, University of Toronto, Ontario, Canada
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2
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Ding N, Yuan Z, Ma Z, Wu Y, Yin L. AI-Assisted Rational Design and Activity Prediction of Biological Elements for Optimizing Transcription-Factor-Based Biosensors. Molecules 2024; 29:3512. [PMID: 39124917 PMCID: PMC11313831 DOI: 10.3390/molecules29153512] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2024] [Revised: 07/22/2024] [Accepted: 07/24/2024] [Indexed: 08/12/2024] Open
Abstract
The rational design, activity prediction, and adaptive application of biological elements (bio-elements) are crucial research fields in synthetic biology. Currently, a major challenge in the field is efficiently designing desired bio-elements and accurately predicting their activity using vast datasets. The advancement of artificial intelligence (AI) technology has enabled machine learning and deep learning algorithms to excel in uncovering patterns in bio-element data and predicting their performance. This review explores the application of AI algorithms in the rational design of bio-elements, activity prediction, and the regulation of transcription-factor-based biosensor response performance using AI-designed elements. We discuss the advantages, adaptability, and biological challenges addressed by the AI algorithms in various applications, highlighting their powerful potential in analyzing biological data. Furthermore, we propose innovative solutions to the challenges faced by AI algorithms in the field and suggest future research directions. By consolidating current research and demonstrating the practical applications and future potential of AI in synthetic biology, this review provides valuable insights for advancing both academic research and practical applications in biotechnology.
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Affiliation(s)
- Nana Ding
- State Key Laboratory of Subtropical Silviculture, Zhejiang A&F University, Hangzhou 311300, China;
- Zhejiang Provincial Key Laboratory of Resources Protection and Innovation of Traditional Chinese Medicine, Zhejiang A&F University, Hangzhou 311300, China
| | - Zenan Yuan
- State Key Laboratory of Subtropical Silviculture, Zhejiang A&F University, Hangzhou 311300, China;
- Zhejiang Provincial Key Laboratory of Resources Protection and Innovation of Traditional Chinese Medicine, Zhejiang A&F University, Hangzhou 311300, China
| | - Zheng Ma
- Zhejiang Provincial Key Laboratory of Biometrology and Inspection & Quarantine, College of Life Sciences, China Jiliang University, Hangzhou 310018, China;
| | - Yefei Wu
- Zhejiang Qianjiang Biochemical Co., Ltd., Haining 314400, China;
| | - Lianghong Yin
- State Key Laboratory of Subtropical Silviculture, Zhejiang A&F University, Hangzhou 311300, China;
- Zhejiang Provincial Key Laboratory of Resources Protection and Innovation of Traditional Chinese Medicine, Zhejiang A&F University, Hangzhou 311300, China
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3
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Martín Lázaro H, Marín Bautista R, Carbonell P. DetSpace: a web server for engineering detectable pathways for bio-based chemical production. Nucleic Acids Res 2024; 52:W476-W480. [PMID: 38634809 PMCID: PMC11223873 DOI: 10.1093/nar/gkae287] [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: 01/29/2024] [Revised: 03/18/2024] [Accepted: 04/16/2024] [Indexed: 04/19/2024] Open
Abstract
Tackling climate change challenges requires replacing current chemical industrial processes through the rational and sustainable use of biodiversity resources. To that end, production routes to key bio-based chemicals for the bioeconomy have been identified. However, their production still remains inefficient in terms of titers, rates, and yields; because of the hurdles found when scaling up. In order to make production more efficient, strategies like automated screening and dynamic pathway regulation through biosensors have been applied as part of strain optimization. However, to date, no systematic way exists to design a genetic circuit that is responsive to concentrations of a given target compound. Here, the DetSpace web server provides a set of integrated tools that allows a user to select and design a biological circuit that performs the sensing of a molecule of interest by its enzymatic conversion to a detectable molecule through a transcription factor. In that way, the DetSpace web server allows synthetic biologists to easily design biosensing routes for the dynamic regulation of metabolic pathways in applications ranging from genetic circuits design, screening, production, and bioremediation of bio-based chemicals, to diagnostics and drug delivery.
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Affiliation(s)
- Hèctor Martín Lázaro
- Institute of Industrial Control Systems and Computing (AI2), Universitat Politècnica de València (UPV), Camí de Vera s/n, 46022 València, Spain
| | - Ricardo Marín Bautista
- Institute of Industrial Control Systems and Computing (AI2), Universitat Politècnica de València (UPV), Camí de Vera s/n, 46022 València, Spain
| | - Pablo Carbonell
- Institute of Industrial Control Systems and Computing (AI2), Universitat Politècnica de València (UPV), Camí de Vera s/n, 46022 València, Spain
- Institute for Integrative Systems Biology I2SysBio, Universitat de València-CSIC, Escardino Street 9, Paterna, 46980 València, Spain
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4
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Bahrami Moghadam E, Nguyen N, Wang Y, Cirino PC. Directed Evolution of Protein-Based Sensors for Anaerobic Biological Activation of Methane. BIOSENSORS 2024; 14:325. [PMID: 39056601 PMCID: PMC11275114 DOI: 10.3390/bios14070325] [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: 05/24/2024] [Revised: 06/24/2024] [Accepted: 06/27/2024] [Indexed: 07/28/2024]
Abstract
Microbial alkane degradation pathways provide biological routes for converting these hydrocarbons into higher-value products. We recently reported the functional expression of a methyl-alkylsuccinate synthase (Mas) system in Escherichia coli, allowing for the heterologous anaerobic activation of short-chain alkanes. However, the enzymatic activation of methane via natural or engineered alkylsuccinate synthases has yet to be reported. To address this, we employed high-throughput screening to engineer the itaconate (IA)-responsive regulatory protein ItcR (WT-ItcR) from Yersinia pseudotuberculosis to instead respond to methylsuccinate (MS, the product of methane addition to fumarate), resulting in genetically encoded biosensors for MS. Here, we describe ItcR variants that, when regulating fluorescent protein expression in E. coli, show increased sensitivity, improved overall response, and enhanced specificity toward exogenously added MS relative to the wild-type repressor. Structural modeling and analysis of the ItcR ligand binding pocket provide insights into the altered molecular recognition. In addition to serving as biosensors for screening alkylsuccinate synthases capable of methane activation, MS-responsive ItcR variants also establish a framework for the directed evolution of other molecular reporters, targeting longer-chain alkylsuccinate products or other succinate derivatives.
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Affiliation(s)
| | | | | | - Patrick C. Cirino
- Department of Chemical and Biomolecular Engineering, University of Houston, Houston, TX 77204-4004, USA; (E.B.M.)
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5
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Moratti CF, Yang SNN, Scott C, Coleman NV. Development of a whole-cell biosensor for ethylene oxide and ethylene. Microb Biotechnol 2024; 17:e14511. [PMID: 38925606 PMCID: PMC11197473 DOI: 10.1111/1751-7915.14511] [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: 03/01/2024] [Accepted: 06/07/2024] [Indexed: 06/28/2024] Open
Abstract
Ethylene and ethylene oxide are widely used in the chemical industry, and ethylene is also important for its role in fruit ripening. Better sensing systems would assist risk management of these chemicals. Here, we characterise the ethylene regulatory system in Mycobacterium strain NBB4 and use these genetic parts to create a biosensor. The regulatory genes etnR1 and etnR2 and cognate promoter Petn were combined with a fluorescent reporter gene (fuGFP) in a Mycobacterium shuttle vector to create plasmid pUS301-EtnR12P. Cultures of M. smegmatis mc2-155(pUS301-EtnR12P) gave a fluorescent signal in response to ethylene oxide with a detection limit of 0.2 μM (9 ppb). By combining the epoxide biosensor cells with another culture expressing the ethylene monooxygenase, the system was converted into an ethylene biosensor. The co-culture was capable of detecting ethylene emission from banana fruit. These are the first examples of whole-cell biosensors for epoxides or aliphatic alkenes. This work also resolves long-standing questions concerning the regulation of ethylene catabolism in bacteria.
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Affiliation(s)
- Claudia F. Moratti
- School of Life and Environmental SciencesUniversity of SydneyCamperdownNew South WalesAustralia
| | - Sui Nin Nicholas Yang
- School of Life and Environmental SciencesUniversity of SydneyCamperdownNew South WalesAustralia
| | - Colin Scott
- CSIRO Advanced Engineering Biology Future Science Platform, Black Mountain Research & Innovation ParkCanberraAustralian Capital TerritoryAustralia
| | - Nicholas V. Coleman
- School of Natural Sciences and ARC Centre of Excellence in Synthetic BiologyMacquarie UniversityNorth RydeNew South WalesAustralia
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6
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Sankar K, Kuzmanović U, Schaus SE, Galagan JE, Grinstaff MW. Strategy, Design, and Fabrication of Electrochemical Biosensors: A Tutorial. ACS Sens 2024; 9:2254-2274. [PMID: 38636962 DOI: 10.1021/acssensors.4c00043] [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: 04/20/2024]
Abstract
Advanced healthcare requires novel technologies capable of real-time sensing to monitor acute and long-term health. The challenge relies on converting a real-time quantitative biological and chemical signal into a desired measurable output. Given the success in detecting glucose and the commercialization of glucometers, electrochemical biosensors continue to be a mainstay of academic and industrial research activities. Despite the wealth of literature on electrochemical biosensors, reports are often specific to a particular application (e.g., pathogens, cancer markers, glucose, etc.), and most fail to convey the underlying strategy and design, and if it is transferable to detection of a different analyte. Here we present a tutorial review for those entering this research area that summarizes the basic electrochemical techniques utilized as well as discusses the designs and optimization strategies employed to improve sensitivity and maximize signal output.
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7
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Abebe BK, Wang H, Li A, Zan L. A review of the role of transcription factors in regulating adipogenesis and lipogenesis in beef cattle. J Anim Breed Genet 2024; 141:235-256. [PMID: 38146089 DOI: 10.1111/jbg.12841] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2023] [Revised: 11/25/2023] [Accepted: 11/30/2023] [Indexed: 12/27/2023]
Abstract
In the past few decades, genomic selection and other refined strategies have been used to increase the growth rate and lean meat production of beef cattle. Nevertheless, the fast growth rates of cattle breeds are often accompanied by a reduction in intramuscular fat (IMF) deposition, impairing meat quality. Transcription factors play vital roles in regulating adipogenesis and lipogenesis in beef cattle. Meanwhile, understanding the role of transcription factors in regulating adipogenesis and lipogenesis in beef cattle has gained significant attention to increase IMF deposition and meat quality. Therefore, the aim of this paper was to provide a comprehensive summary and valuable insight into the complex role of transcription factors in adipogenesis and lipogenesis in beef cattle. This review summarizes the contemporary studies in transcription factors in adipogenesis and lipogenesis, genome-wide analysis of transcription factors, epigenetic regulation of transcription factors, nutritional regulation of transcription factors, metabolic signalling pathways, functional genomics methods, transcriptomic profiling of adipose tissues, transcription factors and meat quality and comparative genomics with other livestock species. In conclusion, transcription factors play a crucial role in promoting adipocyte development and fatty acid biosynthesis in beef cattle. They control adipose tissue formation and metabolism, thereby improving meat quality and maintaining metabolic balance. Understanding the processes by which these transcription factors regulate adipose tissue deposition and lipid metabolism will simplify the development of marbling or IMF composition in beef cattle.
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Affiliation(s)
- Belete Kuraz Abebe
- College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi, People's Republic of China
- Department of Animal Science, Werabe University, Werabe, Ethiopia
| | - Hongbao Wang
- College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi, People's Republic of China
| | - Anning Li
- College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi, People's Republic of China
| | - Linsen Zan
- College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi, People's Republic of China
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8
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Nishikawa KK, Chen J, Acheson JF, Harbaugh SV, Huss P, Frenkel M, Novy N, Sieren HR, Lodewyk EC, Lee DH, Chávez JL, Fox BG, Raman S. Highly multiplexed design of an allosteric transcription factor to sense novel ligands. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.03.07.583947. [PMID: 38496486 PMCID: PMC10942455 DOI: 10.1101/2024.03.07.583947] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/19/2024]
Abstract
Allosteric transcription factors (aTF), widely used as biosensors, have proven challenging to design for detecting novel molecules because mutation of ligand-binding residues often disrupts allostery. We developed Sensor-seq, a high-throughput platform to design and identify aTF biosensors that bind to non-native ligands. We screened a library of 17,737 variants of the aTF TtgR, a regulator of a multidrug exporter, against six non-native ligands of diverse chemical structures - four derivatives of the cancer therapeutic tamoxifen, the antimalarial drug quinine, and the opiate analog naltrexone - as well as two native flavonoid ligands, naringenin and phloretin. Sensor-seq identified novel biosensors for each of these ligands with high dynamic range and diverse specificity profiles. The structure of a naltrexone-bound design showed shape-complementary methionine-aromatic interactions driving ligand specificity. To demonstrate practical utility, we developed cell-free detection systems for naltrexone and quinine. Sensor-seq enables rapid, scalable design of new biosensors, overcoming constraints of natural biosensors.
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Affiliation(s)
- Kyle K Nishikawa
- Department of Biochemistry, University of Wisconsin-Madison, Madison, Wisconsin, USA
| | - Jackie Chen
- Department of Biochemistry, University of Wisconsin-Madison, Madison, Wisconsin, USA
| | - Justin F Acheson
- Department of Biochemistry, University of Wisconsin-Madison, Madison, Wisconsin, USA
| | - Svetlana V Harbaugh
- 711th Human Performance Wing, Air Force Research Laboratory Wright Patterson Air Force Base, OH, USA
| | - Phil Huss
- Department of Biochemistry, University of Wisconsin-Madison, Madison, Wisconsin, USA
| | - Max Frenkel
- Department of Biochemistry, University of Wisconsin-Madison, Madison, Wisconsin, USA
| | - Nathan Novy
- Department of Biochemistry, University of Wisconsin-Madison, Madison, Wisconsin, USA
| | - Hailey R Sieren
- Department of Biochemistry, University of Wisconsin-Madison, Madison, Wisconsin, USA
| | - Ella C Lodewyk
- Department of Biochemistry, University of Wisconsin-Madison, Madison, Wisconsin, USA
| | - Daniel H Lee
- Department of Biochemistry, University of Wisconsin-Madison, Madison, Wisconsin, USA
| | - Jorge L Chávez
- 711th Human Performance Wing, Air Force Research Laboratory Wright Patterson Air Force Base, OH, USA
| | - Brian G Fox
- Department of Biochemistry, University of Wisconsin-Madison, Madison, Wisconsin, USA
- Great Lakes Bioenergy Research Center, University of Wisconsin-Madison, Madison, WI, USA
| | - Srivatsan Raman
- Department of Biochemistry, University of Wisconsin-Madison, Madison, Wisconsin, USA
- Department of Bacteriology, University of Wisconsin-Madison, Madison, WI, USA
- Department of Chemical and Biological Engineering, University of Wisconsin-Madison, Madison, WI, USA
- Great Lakes Bioenergy Research Center, University of Wisconsin-Madison, Madison, WI, USA
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9
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Chaisupa P, Wright RC. State-of-the-art in engineering small molecule biosensors and their applications in metabolic engineering. SLAS Technol 2024; 29:100113. [PMID: 37918525 PMCID: PMC11314541 DOI: 10.1016/j.slast.2023.10.005] [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: 07/07/2023] [Revised: 10/18/2023] [Accepted: 10/25/2023] [Indexed: 11/04/2023]
Abstract
Genetically encoded biosensors are crucial for enhancing our understanding of how molecules regulate biological systems. Small molecule biosensors, in particular, help us understand the interaction between chemicals and biological processes. They also accelerate metabolic engineering by increasing screening throughput and eliminating the need for sample preparation through traditional chemical analysis. Additionally, they offer significantly higher spatial and temporal resolution in cellular analyte measurements. In this review, we discuss recent progress in in vivo biosensors and control systems-biosensor-based controllers-for metabolic engineering. We also specifically explore protein-based biosensors that utilize less commonly exploited signaling mechanisms, such as protein stability and induced degradation, compared to more prevalent transcription factor and allosteric regulation mechanism. We propose that these lesser-used mechanisms will be significant for engineering eukaryotic systems and slower-growing prokaryotic systems where protein turnover may facilitate more rapid and reliable measurement and regulation of the current cellular state. Lastly, we emphasize the utilization of cutting-edge and state-of-the-art techniques in the development of protein-based biosensors, achieved through rational design, directed evolution, and collaborative approaches.
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Affiliation(s)
- Patarasuda Chaisupa
- Department of Biological Systems Engineering, Virginia Tech, Blacksburg, VA 24061, United States
| | - R Clay Wright
- Department of Biological Systems Engineering, Virginia Tech, Blacksburg, VA 24061, United States; Translational Plant Sciences Center (TPSC), Virginia Tech, Blacksburg, VA 24061, United States.
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10
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Lerner A, Benzvi C, Vojdani A. The Potential Harmful Effects of Genetically Engineered Microorganisms (GEMs) on the Intestinal Microbiome and Public Health. Microorganisms 2024; 12:238. [PMID: 38399642 PMCID: PMC10892181 DOI: 10.3390/microorganisms12020238] [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: 01/01/2024] [Revised: 01/20/2024] [Accepted: 01/22/2024] [Indexed: 02/25/2024] Open
Abstract
Gut luminal dysbiosis and pathobiosis result in compositional and biodiversified alterations in the microbial and host co-metabolites. The primary mechanism of bacterial evolution is horizontal gene transfer (HGT), and the acquisition of new traits can be achieved through the exchange of mobile genetic elements (MGEs). Introducing genetically engineered microbes (GEMs) might break the harmonized balance in the intestinal compartment. The present objectives are: 1. To reveal the role played by the GEMs' horizontal gene transfers in changing the landscape of the enteric microbiome eubiosis 2. To expand on the potential detrimental effects of those changes on the human genome and health. A search of articles published in PubMed/MEDLINE, EMBASE, and Scielo from 2000 to August 2023 using appropriate MeSH entry terms was performed. The GEMs' horizontal gene exchanges might induce multiple human diseases. The new GEMs can change the long-term natural evolution of the enteric pro- or eukaryotic cell inhabitants. The worldwide regulatory authority's safety control of GEMs is not enough to protect public health. Viability, biocontainment, and many other aspects are only partially controlled and harmful consequences for public health should be avoided. It is important to remember that prevention is the most cost-effective strategy and primum non nocere should be the focus.
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Affiliation(s)
- Aaron Lerner
- Chaim Sheba Medical Center, The Zabludowicz Center for Autoimmune Diseases, Ramat Gan 52621, Israel;
- Ariel Campus, Ariel University, Ariel 40700, Israel
| | - Carina Benzvi
- Chaim Sheba Medical Center, The Zabludowicz Center for Autoimmune Diseases, Ramat Gan 52621, Israel;
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11
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Incardona JP, Linbo TL, Cameron JR, French BL, Bolton JL, Gregg JL, Donald CE, Hershberger PK, Scholz NL. Biological Responses of Pacific Herring Embryos to Crude Oil Are Quantifiable at Exposure Levels Below Conventional Limits of Quantitation for PAHs in Water and Tissues. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2023; 57:19214-19222. [PMID: 37963111 DOI: 10.1021/acs.est.3c04122] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2023]
Abstract
Pacific herring (Clupea pallasii), a cornerstone of marine food webs, generally spawn on marine macroalgae in shallow nearshore areas that are disproportionately at risk from oil spills. Herring embryos are also highly susceptible to toxicity from chemicals leaching from oil stranded in intertidal and subtidal zones. The water-soluble components of crude oil trigger an adverse outcome pathway that involves disruption of the physiological functions of cardiomyocytes in the embryonic herring heart. In previous studies, impaired ionoregulation (calcium and potassium cycling) in response to specific polycyclic aromatic hydrocarbons (PAHs) corresponds to lethal embryolarval heart failure or subtle chamber malformations at the high and low ends of the PAH exposure range, respectively. Sublethal cardiotoxicity, which involves an abnormal outgrowth (ballooning) of the cardiac ventricular chamber soon after hatching, subsequently compromises juvenile heart structure and function, leading to pathological hypertrophy of the ventricle and reduced individual fitness, measured as cardiorespiratory performance. Previous studies have not established a threshold for these sublethal and delayed-in-time effects, even with total (∑)PAH exposures as low as 29 ng/g of wet weight (tissue dose). Here, we extend these earlier findings showing that (1) cyp1a gene expression provides an oil exposure metric that is more sensitive than typical quantitation of PAHs via GC-MS and (2) heart morphometrics in herring embryos provide a similarly sensitive measure of toxic response. Early life stage injury to herring (impaired heart development) thus occurs below the quantitation limits for PAHs in both water and embryonic tissues as a conventional basis for assessing oil-induced losses to coastal marine ecosystems.
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Affiliation(s)
- John P Incardona
- National Oceanic and Atmospheric Administration, Northwest Fisheries Science Center, Seattle, Washington 98112, United States
| | - Tiffany L Linbo
- National Oceanic and Atmospheric Administration, Northwest Fisheries Science Center, Seattle, Washington 98112, United States
| | - James R Cameron
- National Oceanic and Atmospheric Administration, Saltwater, Inc., under Contract to Northwest Fisheries Science Center, Seattle, Washington 98112, United States
| | - Barbara L French
- National Oceanic and Atmospheric Administration, Northwest Fisheries Science Center, Seattle, Washington 98112, United States
| | - Jennie L Bolton
- National Oceanic and Atmospheric Administration, Northwest Fisheries Science Center, Seattle, Washington 98112, United States
| | - Jacob L Gregg
- Marrowstone Marine Field Station, US Geological Survey, Western Fisheries Research Center, Nordland, Washington 98358-9633, United States
| | - Carey E Donald
- Institute of Marine Research, Bergen, Nordnes 5817, Norway
| | - Paul K Hershberger
- Marrowstone Marine Field Station, US Geological Survey, Western Fisheries Research Center, Nordland, Washington 98358-9633, United States
| | - Nathaniel L Scholz
- National Oceanic and Atmospheric Administration, Northwest Fisheries Science Center, Seattle, Washington 98112, United States
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12
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Zhou GJ, Zhang F. Applications and Tuning Strategies for Transcription Factor-Based Metabolite Biosensors. BIOSENSORS 2023; 13:428. [PMID: 37185503 PMCID: PMC10136082 DOI: 10.3390/bios13040428] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/27/2023] [Revised: 03/24/2023] [Accepted: 03/27/2023] [Indexed: 05/17/2023]
Abstract
Transcription factor (TF)-based biosensors are widely used for the detection of metabolites and the regulation of cellular pathways in response to metabolites. Several challenges hinder the direct application of TF-based sensors to new hosts or metabolic pathways, which often requires extensive tuning to achieve the optimal performance. These tuning strategies can involve transcriptional or translational control depending on the parameter of interest. In this review, we highlight recent strategies for engineering TF-based biosensors to obtain the desired performance and discuss additional design considerations that may influence a biosensor's performance. We also examine applications of these sensors and suggest important areas for further work to continue the advancement of small-molecule biosensors.
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Affiliation(s)
- Gloria J. Zhou
- Department of Energy, Environmental and Chemical Engineering, Washington University in St. Louis, St. Louis, MO 63130, USA;
| | - Fuzhong Zhang
- Department of Energy, Environmental and Chemical Engineering, Washington University in St. Louis, St. Louis, MO 63130, USA;
- Division of Biology & Biomedical Sciences, Washington University in St. Louis, St. Louis, MO 63130, USA
- Institute of Materials Science & Engineering, Washington University in St. Louis, St. Louis, MO 63130, USA
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