{"title":"From bench to biofactory: high-throughput technologies and automated workflows to accelerate biomanufacturing","authors":"Christopher J Petzold , Aindrila Mukhopadhyay","doi":"10.1016/j.copbio.2025.103320","DOIUrl":null,"url":null,"abstract":"<div><div>Microbial production of target molecules has advanced significantly in recent years driven by innovations in enzyme engineering, DNA synthesis, and genomic editing. However, to access the massive potential of microbial production, a vast parametric space remains to be investigated to optimize these biobased processes for a robust bioeconomy. Here, we review the current state of the art, some key challenges and possible solutions. We see a critical role of automation, high-throughput technologies, self-driving and cloud labs, and data management to enable Artificial Intelligence/Machine Learning and mechanistic models to overcome the design space challenges and accelerate the development of novel bio-based solutions. Accurate models will expedite the development and scale-up of engineered microbes for a range of final products from many starting materials.</div></div>","PeriodicalId":10833,"journal":{"name":"Current opinion in biotechnology","volume":"94 ","pages":"Article 103320"},"PeriodicalIF":7.1000,"publicationDate":"2025-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Current opinion in biotechnology","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0958166925000643","RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"BIOCHEMICAL RESEARCH METHODS","Score":null,"Total":0}
引用次数: 0
Abstract
Microbial production of target molecules has advanced significantly in recent years driven by innovations in enzyme engineering, DNA synthesis, and genomic editing. However, to access the massive potential of microbial production, a vast parametric space remains to be investigated to optimize these biobased processes for a robust bioeconomy. Here, we review the current state of the art, some key challenges and possible solutions. We see a critical role of automation, high-throughput technologies, self-driving and cloud labs, and data management to enable Artificial Intelligence/Machine Learning and mechanistic models to overcome the design space challenges and accelerate the development of novel bio-based solutions. Accurate models will expedite the development and scale-up of engineered microbes for a range of final products from many starting materials.
期刊介绍:
Current Opinion in Biotechnology (COBIOT) is renowned for publishing authoritative, comprehensive, and systematic reviews. By offering clear and readable syntheses of current advances in biotechnology, COBIOT assists specialists in staying updated on the latest developments in the field. Expert authors annotate the most noteworthy papers from the vast array of information available today, providing readers with valuable insights and saving them time.
As part of the Current Opinion and Research (CO+RE) suite of journals, COBIOT is accompanied by the open-access primary research journal, Current Research in Biotechnology (CRBIOT). Leveraging the editorial excellence, high impact, and global reach of the Current Opinion legacy, CO+RE journals ensure they are widely read resources integral to scientists' workflows.
COBIOT is organized into themed sections, each reviewed once a year. These themes cover various areas of biotechnology, including analytical biotechnology, plant biotechnology, food biotechnology, energy biotechnology, environmental biotechnology, systems biology, nanobiotechnology, tissue, cell, and pathway engineering, chemical biotechnology, and pharmaceutical biotechnology.