Suppr超能文献

可视化葡萄酒酵母研究的下一个前沿领域。

Visualizing the next frontiers in wine yeast research.

机构信息

ARC Centre of Excellence in Synthetic Biology, Macquarie University, Sydney, NSW 2109, Australia.

出版信息

FEMS Yeast Res. 2022 Mar 11;22(1). doi: 10.1093/femsyr/foac010.

Abstract

A range of game-changing biodigital and biodesign technologies are coming of age all around us, transforming our world in complex ways that are hard to predict. Not a day goes by without news of how data-centric engineering, algorithm-driven modelling, and biocyber technologies-including the convergence of artificial intelligence, machine learning, automated robotics, quantum computing, and genome editing-will change our world. If we are to be better at expecting the unexpected in the world of wine, we need to gain deeper insights into the potential and limitations of these technological developments and advances along with their promise and perils. This article anticipates how these fast-expanding bioinformational and biodesign toolkits might lead to the creation of synthetic organisms and model systems, and ultimately new understandings of biological complexities could be achieved. A total of four future frontiers in wine yeast research are discussed in this article: the construction of fully synthetic yeast genomes, including minimal genomes; supernumerary pan-genome neochromosomes; synthetic metagenomes; and synthetic yeast communities. These four concepts are at varying stages of development with plenty of technological pitfalls to overcome before such model chromosomes, genomes, strains, and yeast communities could illuminate some of the ill-understood aspects of yeast resilience, fermentation performance, flavour biosynthesis, and ecological interactions in vineyard and winery settings. From a winemaker's perspective, some of these ideas might be considered as far-fetched and, as such, tempting to ignore. However, synthetic biologists know that by exploring these futuristic concepts in the laboratory could well forge new research frontiers to deepen our understanding of the complexities of consistently producing fine wines with different fermentation processes from distinctive viticultural terroirs. As the saying goes in the disruptive technology industry, it take years to create an overnight success. The purpose of this article is neither to glorify any of these concepts as a panacea to all ills nor to crucify them as a danger to winemaking traditions. Rather, this article suggests that these proposed research endeavours deserve due consideration because they are likely to cast new light on the genetic blind spots of wine yeasts, and how they interact as communities in vineyards and wineries. Future-focussed research is, of course, designed to be subject to revision as new data and technologies become available. Successful dislodging of old paradigms with transformative innovations will require open-mindedness and pragmatism, not dogmatism-and this can make for a catch-22 situation in an archetypal traditional industry, such as the wine industry, with its rich territorial and socio-cultural connotations.

摘要

一系列具有变革性的生物数字和生物设计技术正在我们身边涌现,以复杂且难以预测的方式改变着我们的世界。每天都有新闻报道称,以数据为中心的工程、算法驱动的建模以及生物 cyber 技术——包括人工智能、机器学习、自动化机器人、量子计算和基因组编辑的融合——将如何改变我们的世界。如果我们想要在葡萄酒世界中更好地预测意料之外的情况,我们就需要更深入地了解这些技术发展及其潜力和局限性,以及它们的承诺和风险。本文预计这些快速扩展的生物信息和生物设计工具包如何导致合成生物体和模型系统的创建,并最终实现对生物复杂性的新理解。本文讨论了葡萄酒酵母研究的四个未来前沿领域:完全合成酵母基因组的构建,包括最小基因组;额外的泛基因组新染色体;合成宏基因组;以及合成酵母群落。这四个概念处于不同的发展阶段,在这些模型染色体、基因组、菌株和酵母群落能够阐明酵母弹性、发酵性能、风味生物合成以及葡萄园和酿酒厂环境中的生态相互作用的一些未被充分理解的方面之前,还有很多技术难题需要克服。从酿酒师的角度来看,这些想法中的一些可能被认为是牵强附会的,因此很容易被忽视。然而,合成生物学家知道,通过在实验室中探索这些未来主义的概念,很可能会开拓新的研究前沿,加深我们对利用不同发酵工艺从独特风土条件下生产优质葡萄酒的复杂性的理解。正如颠覆性技术行业的一句俗语所说,创造一个一夜成名的产品需要数年时间。本文的目的不是将这些概念中的任何一个都视为万灵药,也不是将它们视为酿酒传统的危险而加以谴责。相反,本文认为,这些拟议的研究工作值得考虑,因为它们可能会揭示葡萄酒酵母的遗传盲点,以及它们在葡萄园和酿酒厂中作为群落相互作用的方式。当然,未来的研究是为了随着新数据和技术的出现而进行修订。用变革性创新成功取代旧范式需要开放的心态和务实精神,而不是教条主义——这在葡萄酒等具有丰富地域和社会文化内涵的典型传统行业中可能会形成一个两难的局面。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cfc5/8916113/e015b647c8fb/foac010fig1.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验