Kil Koang Kwon , Jinju Lee , Haseong Kim , Dae-Hee Lee , Seung-Goo Lee
{"title":"Advancing high-throughput screening systems for synthetic biology and biofoundry","authors":"Kil Koang Kwon , Jinju Lee , Haseong Kim , Dae-Hee Lee , Seung-Goo Lee","doi":"10.1016/j.coisb.2023.100487","DOIUrl":null,"url":null,"abstract":"<div><p>High-throughput (HT) methodologies are extensively applied in synthetic biology for the rapid enrichment and selection of desired properties from a wide range of genetic diversity. In order to effectively analyze these vast variants, HT tools must offer parallel experiments and compact reaction capabilities to enhance overall throughput. Here, we discuss about various aspects of three representative high-throughput screening (HTS) systems: microwell-, droplet-, and single-cell-based screening. These systems can be categorized based on their reaction volume, which in turn determines the associated technology, machinery, and supporting applications. Furthermore, HT techniques that rapidly connect numerous genotypes and phenotypes have evolved to enhance the precision of predictions through the integration of digital technologies like machine learning and artificial intelligence. The use of advanced HT techniques within biofoundry will enable rapid selection and analysis from extensive genetic diversity, making it a driving force for the advancement of synthetic biology.</p></div>","PeriodicalId":37400,"journal":{"name":"Current Opinion in Systems Biology","volume":"37 ","pages":"Article 100487"},"PeriodicalIF":3.4000,"publicationDate":"2023-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2452310023000446/pdfft?md5=c79f76a94a5c0e68e948902ca3894d28&pid=1-s2.0-S2452310023000446-main.pdf","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Current Opinion in Systems Biology","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2452310023000446","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"BIOCHEMISTRY & MOLECULAR BIOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
High-throughput (HT) methodologies are extensively applied in synthetic biology for the rapid enrichment and selection of desired properties from a wide range of genetic diversity. In order to effectively analyze these vast variants, HT tools must offer parallel experiments and compact reaction capabilities to enhance overall throughput. Here, we discuss about various aspects of three representative high-throughput screening (HTS) systems: microwell-, droplet-, and single-cell-based screening. These systems can be categorized based on their reaction volume, which in turn determines the associated technology, machinery, and supporting applications. Furthermore, HT techniques that rapidly connect numerous genotypes and phenotypes have evolved to enhance the precision of predictions through the integration of digital technologies like machine learning and artificial intelligence. The use of advanced HT techniques within biofoundry will enable rapid selection and analysis from extensive genetic diversity, making it a driving force for the advancement of synthetic biology.
期刊介绍:
Current Opinion in Systems Biology is a new systematic review journal that aims to provide specialists with a unique and educational platform to keep up-to-date with the expanding volume of information published in the field of Systems Biology. It publishes polished, concise and timely systematic reviews and opinion articles. In addition to describing recent trends, the authors are encouraged to give their subjective opinion on the topics discussed. As this is such a broad discipline, we have determined themed sections each of which is reviewed once a year. The following areas will be covered by Current Opinion in Systems Biology: -Genomics and Epigenomics -Gene Regulation -Metabolic Networks -Cancer and Systemic Diseases -Mathematical Modelling -Big Data Acquisition and Analysis -Systems Pharmacology and Physiology -Synthetic Biology -Stem Cells, Development, and Differentiation -Systems Biology of Mold Organisms -Systems Immunology and Host-Pathogen Interaction -Systems Ecology and Evolution