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Mohamed Helmy¹, Hosam Elhalis², Md Mamunur Rashid³

¹Vaccine and Infectious Disease Organization (VIDO), University of Saskatchewan, SK, Canada; Department of Computer Science, Lakehead University, ON, Canada; Department of Computer Science, College of Science and Engineering, Idaho State University, ID, USA; Bioinformatics Institute (BII), Agency for Science, Technology and Research (A⁎STAR), Singapore 138671, Singapore.

Current opinion in biotechnology

|March 28, 2024

概括

可持续的粮食生产需要了解微生物生长. 数字双胞胎技术集成了微生物模型的多经济学数据,优化了替代食品来源并识别了生产瓶.

科学领域:

微生物学微生物学
系统生物学系统生物学
生物工程是生物工程.

背景情况:

全球人口增长和粮食安全挑战需要可持续的粮食生产方法.
微生物提供了一个有希望的替代食物来源,但优化它们的生产需要更深入的生物学理解.
目前的单一omics方法不足以充分理解和优化微生物生长和产品输出.

研究的目的:

讨论数字双胞胎 (DT) 方法在微生物食品生产中分析多组数据的潜力.
突出DT模型如何提供对微生物系统的整体理解.
倡导开发DT模型,以加强基于微生物的食品生产.

主要方法:

整合系统生物学和人工智能来分析多态数据集.
开发数字双胞胎 (DT) 模型作为微生物复制模型用于in silico测试.
利用DT模型,了解微生物生长和代谢物生物合成.

主要成果:

DT模型提供了对微生物生长和代谢途径的整体观点.
这些模型可以识别基于微生物的生产系统中的关键瓶.
通过DTs进行in silico测试,可以在实体生产之前进行优化.

结论:

数字双胞胎技术对于推进基于微生物的替代食品生产至关重要.
通过DTs集成多态数据可以彻底改变效率和产量.
进一步开发DT模型对于未来可持续的粮食供应至关重要.

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