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Klasson KT. A discussion and evaluation of statistical procedures used by JIMB authors when comparing means. J Ind Microbiol Biotechnol 2024; 51:kuae001. [PMID: 38200715 PMCID: PMC10845891 DOI: 10.1093/jimb/kuae001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2023] [Accepted: 01/08/2024] [Indexed: 01/12/2024]
Abstract
Out of the 166 articles published in Journal of Industrial Microbiology and Biotechnology (JIMB) in 2019-2020 (not including special issues or review articles), 51 of them used a statistical test to compare two or more means. The most popular test was the (Standard) t-test, which often was used to compare several pairs of means. Other statistical procedures used included Fisher's least significant difference (LSD), Tukey's honest significant difference (HSD), and Welch's t-test; and to a lesser extent Bonferroni, Duncan's Multiple Range, Student-Newman-Keuls, and Kruskal-Wallis tests. This manuscript examines the performance of some of these tests with simulated experimental data, typical of those reported by JIMB authors. The results show that many of the most common procedures used by JIMB authors result in statistical conclusions that are prone to have large false positive (Type I) errors. These error-prone procedures included the multiple t-test, multiple Welch's t-test, and Fisher's LSD. These multiple comparisons procedures were compared with alternatives (Fisher-Hayter, Tukey's HSD, Bonferroni, and Dunnett's t-test) that were able to better control Type I errors. NON-TECHNICAL SUMMARY The aim of this work was to review and recommend statistical procedures for Journal of Industrial Microbiology and Biotechnology authors who often compare the effect of several treatments on microorganisms and their functions.
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Affiliation(s)
- K Thomas Klasson
- U.S. Department of Agriculture, Agricultural Research Service, New Orleans, LA 70124, USA
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2
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Patwari P, Pruckner F, Fabris M. Biosensors in microalgae: A roadmap for new opportunities in synthetic biology and biotechnology. Biotechnol Adv 2023; 68:108221. [PMID: 37495181 DOI: 10.1016/j.biotechadv.2023.108221] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2023] [Revised: 06/22/2023] [Accepted: 07/22/2023] [Indexed: 07/28/2023]
Abstract
Biosensors are powerful tools to investigate, phenotype, improve and prototype microbial strains, both in fundamental research and in industrial contexts. Genetic and biotechnological developments now allow the implementation of synthetic biology approaches to novel different classes of microbial hosts, for example photosynthetic microalgae, which offer unique opportunities. To date, biosensors have not yet been implemented in phototrophic eukaryotic microorganisms, leaving great potential for novel biological and technological advancements untapped. Here, starting from selected biosensor technologies that have successfully been implemented in heterotrophic organisms, we project and define a roadmap on how these could be applied to microalgae research. We highlight novel opportunities for the development of new biosensors, identify critical challenges, and finally provide a perspective on the impact of their eventual implementation to tackle research questions and bioengineering strategies. From studying metabolism at the single-cell level to genome-wide screen approaches, and assisted laboratory evolution experiments, biosensors will greatly impact the pace of progress in understanding and engineering microalgal metabolism. We envision how this could further advance the possibilities for unraveling their ecological role, evolutionary history and accelerate their domestication, to further drive them as resource-efficient production hosts.
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Affiliation(s)
- Payal Patwari
- SDU Biotechnology, Faculty of Engineering, University of Southern Denmark, Odense M DK-5230, Denmark
| | - Florian Pruckner
- SDU Biotechnology, Faculty of Engineering, University of Southern Denmark, Odense M DK-5230, Denmark
| | - Michele Fabris
- SDU Biotechnology, Faculty of Engineering, University of Southern Denmark, Odense M DK-5230, Denmark.
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3
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Ding Q, Ye C. Microbial engineering for shikimate biosynthesis. Enzyme Microb Technol 2023; 170:110306. [PMID: 37598506 DOI: 10.1016/j.enzmictec.2023.110306] [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: 06/27/2023] [Revised: 08/03/2023] [Accepted: 08/14/2023] [Indexed: 08/22/2023]
Abstract
Shikimate, a precursor to the antiviral drug oseltamivir (Tamiflu®), can influence aromatic metabolites and finds extensive use in antimicrobial, antitumor, and cardiovascular applications. Consequently, various strategies have been developed for chemical synthesis and plant extraction to enhance shikimate biosynthesis, potentially impacting environmental conditions, economic sustainability, and separation and purification processes. Microbial engineering has been developed as an environmentally friendly approach for shikimate biosynthesis. In this review, we provide a comprehensive summary of microbial strategies for shikimate biosynthesis. These strategies primarily include chassis construction, biochemical optimization, pathway remodelling, and global regulation. Furthermore, we discuss future perspectives on shikimate biosynthesis and emphasize the importance of utilizing advanced metabolic engineering tools to regulate microbial networks for constructing robust microbial cell factories.
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Affiliation(s)
- Qiang Ding
- School of Life Sciences, Anhui University, Hefei 230601, China; Key Laboratory of Human Microenvironment and Precision Medicine of Anhui Higher Education Institutes, Anhui University, Hefei 230601, Anhui, China; Anhui Key Laboratory of Modern Biomanufacturing, Hefei 230601, Anhui, China
| | - Chao Ye
- School of Food Science and Pharmaceutical Engineering, Nanjing Normal University, Nanjing 210023, China.
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Jiang J, Yang G, Ma F. Fluorescence coupling strategies in fluorescence-activated droplet sorting (FADS) for ultrahigh-throughput screening of enzymes, metabolites, and antibodies. Biotechnol Adv 2023; 66:108173. [PMID: 37169102 DOI: 10.1016/j.biotechadv.2023.108173] [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: 01/11/2023] [Revised: 04/17/2023] [Accepted: 05/06/2023] [Indexed: 05/13/2023]
Abstract
Fluorescence-activated droplet sorting (FADS) has emerged as a powerful tool for ultrahigh-throughput screening of enzymes, metabolites, and antibodies. Fluorescence coupling strategies (FCSs) are key to the development of new FADS methods through their coupling of analyte properties such as concentration, activities, and affinity with fluorescence signals. Over the last decade, a series of FCSs have been developed, greatly expanding applications of FADS. Here, we review recent advances in FCS for different analyte types, providing a critical comparison of the available FCSs and further classification into four categories according to their principles. We also summarize successful FADS applications employing FCSs in enzymes, metabolites, and antibodies. Further, we outline possible future developments in this area.
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Affiliation(s)
- Jingjie Jiang
- Medical Enzyme Engineering Center, CAS Key Lab of Bio-Medical Diagnostics, Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou, Jiangsu 215163, China
| | - Guangyu Yang
- State Key Laboratory of Microbial Metabolism, Joint International Research Laboratory of Metabolic and Developmental Sciences, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai 200240, China.
| | - Fuqiang Ma
- Medical Enzyme Engineering Center, CAS Key Lab of Bio-Medical Diagnostics, Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou, Jiangsu 215163, China.
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Sun G, Qu L, Azi F, Liu Y, Li J, Lv X, Du G, Chen J, Chen CH, Liu L. Recent progress in high-throughput droplet screening and sorting for bioanalysis. Biosens Bioelectron 2023; 225:115107. [PMID: 36731396 DOI: 10.1016/j.bios.2023.115107] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2022] [Revised: 01/09/2023] [Accepted: 01/25/2023] [Indexed: 01/31/2023]
Abstract
Owing to its ability to isolate single cells and perform high-throughput sorting, droplet sorting has been widely applied in several research fields. Compared with flow cytometry, droplet allows the encapsulation of single cells for cell secretion or lysate analysis. With the rapid development of this technology in the past decade, various droplet sorting devices with high throughput and accuracy have been developed. A droplet sorter with the highest sorting throughput of 30,000 droplets per second was developed in 2015. Since then, increased attention has been paid to expanding the possibilities of droplet sorting technology and strengthening its advantages over flow cytometry. This review aimed to summarize the recent progress in droplet sorting technology from the perspectives of device design, detection signal, actuating force, and applications. Technical details for improving droplet sorting through various approaches are introduced and discussed. Finally, we discuss the current limitations of droplet sorting for single-cell studies along with the existing gap between the laboratory and industry and provide our insights for future development of droplet sorters.
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Affiliation(s)
- Guoyun Sun
- Science Center for Future Foods, Jiangnan University, Wuxi, 214122, China; Key Laboratory of Carbohydrate Chemistry and Biotechnology, Ministry of Education, Jiangnan University, Wuxi, 214122, China
| | - Lisha Qu
- Key Laboratory of Carbohydrate Chemistry and Biotechnology, Ministry of Education, Jiangnan University, Wuxi, 214122, China
| | - Fidelis Azi
- Department of Chemical Engineering, Guangdong Technion-Israel Institute of Technology GTIIT, Shantou, Guangdong, 515063, China
| | - Yanfeng Liu
- Science Center for Future Foods, Jiangnan University, Wuxi, 214122, China; Key Laboratory of Carbohydrate Chemistry and Biotechnology, Ministry of Education, Jiangnan University, Wuxi, 214122, China
| | - Jianghua Li
- Key Laboratory of Carbohydrate Chemistry and Biotechnology, Ministry of Education, Jiangnan University, Wuxi, 214122, China
| | - Xueqin Lv
- Science Center for Future Foods, Jiangnan University, Wuxi, 214122, China; Key Laboratory of Carbohydrate Chemistry and Biotechnology, Ministry of Education, Jiangnan University, Wuxi, 214122, China
| | - Guocheng Du
- Science Center for Future Foods, Jiangnan University, Wuxi, 214122, China; Key Laboratory of Carbohydrate Chemistry and Biotechnology, Ministry of Education, Jiangnan University, Wuxi, 214122, China
| | - Jian Chen
- Science Center for Future Foods, Jiangnan University, Wuxi, 214122, China; Key Laboratory of Carbohydrate Chemistry and Biotechnology, Ministry of Education, Jiangnan University, Wuxi, 214122, China
| | - Chia-Hung Chen
- Department of Biomedical Engineering, College of Engineering, City University of Hong Kong, Hong Kong, China.
| | - Long Liu
- Science Center for Future Foods, Jiangnan University, Wuxi, 214122, China; Key Laboratory of Carbohydrate Chemistry and Biotechnology, Ministry of Education, Jiangnan University, Wuxi, 214122, China.
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Yu W, Xu X, Jin K, Liu Y, Li J, Du G, Lv X, Liu L. Genetically encoded biosensors for microbial synthetic biology: From conceptual frameworks to practical applications. Biotechnol Adv 2023; 62:108077. [PMID: 36502964 DOI: 10.1016/j.biotechadv.2022.108077] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2022] [Revised: 12/06/2022] [Accepted: 12/06/2022] [Indexed: 12/13/2022]
Abstract
Genetically encoded biosensors are the vital components of synthetic biology and metabolic engineering, as they are regarded as powerful devices for the dynamic control of genotype metabolism and evolution/screening of desirable phenotypes. This review summarized the recent advances in the construction and applications of different genetically encoded biosensors, including fluorescent protein-based biosensors, nucleic acid-based biosensors, allosteric transcription factor-based biosensors and two-component system-based biosensors. First, the construction frameworks of these biosensors were outlined. Then, the recent progress of biosensor applications in creating versatile microbial cell factories for the bioproduction of high-value chemicals was summarized. Finally, the challenges and prospects for constructing robust and sophisticated biosensors were discussed. This review provided theoretical guidance for constructing genetically encoded biosensors to create desirable microbial cell factories for sustainable bioproduction.
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Affiliation(s)
- Wenwen Yu
- Key Laboratory of Carbohydrate Chemistry and Biotechnology, Ministry of Education, Jiangnan University, Wuxi 214122, China; Science Center for Future Foods, Jiangnan University, Wuxi 214122, China
| | - Xianhao Xu
- Key Laboratory of Carbohydrate Chemistry and Biotechnology, Ministry of Education, Jiangnan University, Wuxi 214122, China; Science Center for Future Foods, Jiangnan University, Wuxi 214122, China
| | - Ke Jin
- Key Laboratory of Carbohydrate Chemistry and Biotechnology, Ministry of Education, Jiangnan University, Wuxi 214122, China; Science Center for Future Foods, Jiangnan University, Wuxi 214122, China
| | - Yanfeng Liu
- Key Laboratory of Carbohydrate Chemistry and Biotechnology, Ministry of Education, Jiangnan University, Wuxi 214122, China; Science Center for Future Foods, Jiangnan University, Wuxi 214122, China
| | - Jianghua Li
- Key Laboratory of Carbohydrate Chemistry and Biotechnology, Ministry of Education, Jiangnan University, Wuxi 214122, China; Science Center for Future Foods, Jiangnan University, Wuxi 214122, China
| | - Guocheng Du
- Science Center for Future Foods, Jiangnan University, Wuxi 214122, China
| | - Xueqin Lv
- Key Laboratory of Carbohydrate Chemistry and Biotechnology, Ministry of Education, Jiangnan University, Wuxi 214122, China; Science Center for Future Foods, Jiangnan University, Wuxi 214122, China
| | - Long Liu
- Key Laboratory of Carbohydrate Chemistry and Biotechnology, Ministry of Education, Jiangnan University, Wuxi 214122, China; Science Center for Future Foods, Jiangnan University, Wuxi 214122, China.
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Kaczmarek JA, Prather KLJ. Effective use of biosensors for high-throughput library screening for metabolite production. J Ind Microbiol Biotechnol 2021; 48:6339276. [PMID: 34347108 PMCID: PMC8788864 DOI: 10.1093/jimb/kuab049] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2021] [Accepted: 07/19/2021] [Indexed: 11/14/2022]
Abstract
The development of fast and affordable microbial production from recombinant pathways is a challenging endeavor, with targeted improvements difficult to predict due to the complex nature of living systems. To address the limitations in biosynthetic pathways, much work has been done to generate large libraries of various genetic parts (promoters, RBSs, enzymes, etc.) to discover library members that bring about significantly improved levels of metabolite production. To evaluate these large libraries, high throughput approaches are necessary, such as those that rely on biosensors. There are various modes of operation to apply biosensors to library screens that are available at different scales of throughput. The effectiveness of each biosensor-based method is dependent on the pathway or strain to which it is applied, and all approaches have strengths and weaknesses to be carefully considered for any high throughput library screen. In this review, we discuss the various approaches used in biosensor screening for improved metabolite production, focusing on transcription factor-based biosensors.
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Affiliation(s)
- Jennifer A Kaczmarek
- Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge 02142, USA
| | - Kristala L J Prather
- Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge 02142, USA
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Bowman EK, Wagner JM, Yuan SF, Deaner M, Palmer CM, D'Oelsnitz S, Cordova L, Li X, Craig FF, Alper HS. Sorting for secreted molecule production using a biosensor-in-microdroplet approach. Proc Natl Acad Sci U S A 2021; 118:e2106818118. [PMID: 34475218 PMCID: PMC8433520 DOI: 10.1073/pnas.2106818118] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2021] [Accepted: 07/28/2021] [Indexed: 11/18/2022] Open
Abstract
Sorting large libraries of cells for improved small molecule secretion is throughput limited. Here, we combine producer/secretor cell libraries with whole-cell biosensors using a microfluidic-based screening workflow. This approach enables a mix-and-match capability using off-the-shelf biosensors through either coencapsulation or pico-injection. We demonstrate the cell type and library agnostic nature of this workflow by utilizing single-guide RNA, transposon, and ethyl-methyl sulfonate mutagenesis libraries across three distinct microbes (Escherichia coli, Saccharomyces cerevisiae, and Yarrowia lipolytica), biosensors from two organisms (E. coli and S. cerevisiae), and three products (triacetic acid lactone, naringenin, and L-DOPA) to identify targets improving production/secretion.
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Affiliation(s)
- Emily K Bowman
- Interdisciplinary Life Sciences Graduate Program, The University of Texas at Austin, Austin, TX 78712
| | - James M Wagner
- McKetta Department of Chemical Engineering, The University of Texas at Austin, Austin, TX 78712
| | - Shuo-Fu Yuan
- Interdisciplinary Life Sciences Graduate Program, The University of Texas at Austin, Austin, TX 78712
| | - Matthew Deaner
- McKetta Department of Chemical Engineering, The University of Texas at Austin, Austin, TX 78712
| | - Claire M Palmer
- Interdisciplinary Life Sciences Graduate Program, The University of Texas at Austin, Austin, TX 78712
| | - Simon D'Oelsnitz
- Interdisciplinary Life Sciences Graduate Program, The University of Texas at Austin, Austin, TX 78712
| | - Lauren Cordova
- McKetta Department of Chemical Engineering, The University of Texas at Austin, Austin, TX 78712
| | - Xin Li
- Sphere Fluidics Limited, Cambridge CB21 6GP, United Kingdom
| | - Frank F Craig
- Sphere Fluidics Limited, Cambridge CB21 6GP, United Kingdom
| | - Hal S Alper
- Interdisciplinary Life Sciences Graduate Program, The University of Texas at Austin, Austin, TX 78712;
- McKetta Department of Chemical Engineering, The University of Texas at Austin, Austin, TX 78712
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