合成生物学的新时代--微生物群落设计

IF 3.2 4区 生物学 Q1 Agricultural and Biological Sciences
Anna B. Matuszyńska, O. Ebenhöh, Matias D Zurbriggen, Daniel C Ducat, Ilka M. Axmann
{"title":"合成生物学的新时代--微生物群落设计","authors":"Anna B. Matuszyńska, O. Ebenhöh, Matias D Zurbriggen, Daniel C Ducat, Ilka M. Axmann","doi":"10.1093/synbio/ysae011","DOIUrl":null,"url":null,"abstract":"\n Synthetic biology conceptualises biological complexity as a network of biological parts, devices and systems with predetermined functionalities, and has had a revolutionary impact on fundamental and applied research. With the unprecedented ability to synthesise and transfer any DNA and RNA across organisms, the scope of synthetic biology is expanding and being recreated in previously unimaginable ways. The field has matured to a level where highly complex networks, such as artificial communities of synthetic organisms can be constructed. In parallel, computational biology became an integral part of biological studies, with computational models aiding the unravelling of the escalating complexity and emerging properties of biological phenomena. However, there is still a vast untapped potential for the complete integration of modelling into the synthetic design process, presenting exciting opportunities for scientific advancements. Here, we first highlight the most recent advances in computer-aided design of microbial communities. Next, we propose that such a design can benefit from an organism-free modular modelling approach that places its emphasis on modules of organismal function towards the design of multi-species communities. We argue for a shift in perspective from single organism-centred approaches to emphasising the functional contributions of organisms within the community. By assembling synthetic biological systems using modular computational models with mathematical descriptions of parts and circuits, we can tailor organisms to fulfil specific functional roles within the community. This approach aligns with synthetic biology strategies and presents exciting possibilities for the design of artificial communities.","PeriodicalId":22158,"journal":{"name":"Synthetic Biology","volume":null,"pages":null},"PeriodicalIF":3.2000,"publicationDate":"2024-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A new era of Synthetic Biology - microbial community design\",\"authors\":\"Anna B. Matuszyńska, O. Ebenhöh, Matias D Zurbriggen, Daniel C Ducat, Ilka M. Axmann\",\"doi\":\"10.1093/synbio/ysae011\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"\\n Synthetic biology conceptualises biological complexity as a network of biological parts, devices and systems with predetermined functionalities, and has had a revolutionary impact on fundamental and applied research. With the unprecedented ability to synthesise and transfer any DNA and RNA across organisms, the scope of synthetic biology is expanding and being recreated in previously unimaginable ways. The field has matured to a level where highly complex networks, such as artificial communities of synthetic organisms can be constructed. In parallel, computational biology became an integral part of biological studies, with computational models aiding the unravelling of the escalating complexity and emerging properties of biological phenomena. However, there is still a vast untapped potential for the complete integration of modelling into the synthetic design process, presenting exciting opportunities for scientific advancements. Here, we first highlight the most recent advances in computer-aided design of microbial communities. Next, we propose that such a design can benefit from an organism-free modular modelling approach that places its emphasis on modules of organismal function towards the design of multi-species communities. We argue for a shift in perspective from single organism-centred approaches to emphasising the functional contributions of organisms within the community. By assembling synthetic biological systems using modular computational models with mathematical descriptions of parts and circuits, we can tailor organisms to fulfil specific functional roles within the community. This approach aligns with synthetic biology strategies and presents exciting possibilities for the design of artificial communities.\",\"PeriodicalId\":22158,\"journal\":{\"name\":\"Synthetic Biology\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":3.2000,\"publicationDate\":\"2024-07-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Synthetic Biology\",\"FirstCategoryId\":\"99\",\"ListUrlMain\":\"https://doi.org/10.1093/synbio/ysae011\",\"RegionNum\":4,\"RegionCategory\":\"生物学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"Agricultural and Biological Sciences\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Synthetic Biology","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.1093/synbio/ysae011","RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"Agricultural and Biological Sciences","Score":null,"Total":0}
引用次数: 0

摘要

合成生物学将生物复杂性概念化为具有预定功能的生物部件、装置和系统网络,对基础研究和应用研究产生了革命性的影响。由于合成和跨生物体转移任何 DNA 和 RNA 的能力前所未有,合成生物学的范围不断扩大,并以以前无法想象的方式进行再创造。该领域已经发展到可以构建高度复杂网络的水平,例如合成生物的人工群落。与此同时,计算生物学也成为生物学研究不可或缺的一部分,计算模型有助于揭示生物现象不断升级的复杂性和新特性。然而,将建模完全融入合成设计过程仍有巨大的潜力尚未开发,这为科学进步带来了令人兴奋的机遇。在此,我们首先重点介绍微生物群落计算机辅助设计的最新进展。接下来,我们提出,这种设计可以受益于无生物模块建模方法,这种方法将重点放在生物功能模块上,从而设计出多物种群落。我们主张转变视角,从以单一生物为中心的方法转向强调群落内生物的功能贡献。通过使用具有部件和电路数学描述的模块化计算模型组装合成生物系统,我们可以定制生物体,使其在群落中发挥特定的功能作用。这种方法符合合成生物学战略,为设计人工群落提供了令人兴奋的可能性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A new era of Synthetic Biology - microbial community design
Synthetic biology conceptualises biological complexity as a network of biological parts, devices and systems with predetermined functionalities, and has had a revolutionary impact on fundamental and applied research. With the unprecedented ability to synthesise and transfer any DNA and RNA across organisms, the scope of synthetic biology is expanding and being recreated in previously unimaginable ways. The field has matured to a level where highly complex networks, such as artificial communities of synthetic organisms can be constructed. In parallel, computational biology became an integral part of biological studies, with computational models aiding the unravelling of the escalating complexity and emerging properties of biological phenomena. However, there is still a vast untapped potential for the complete integration of modelling into the synthetic design process, presenting exciting opportunities for scientific advancements. Here, we first highlight the most recent advances in computer-aided design of microbial communities. Next, we propose that such a design can benefit from an organism-free modular modelling approach that places its emphasis on modules of organismal function towards the design of multi-species communities. We argue for a shift in perspective from single organism-centred approaches to emphasising the functional contributions of organisms within the community. By assembling synthetic biological systems using modular computational models with mathematical descriptions of parts and circuits, we can tailor organisms to fulfil specific functional roles within the community. This approach aligns with synthetic biology strategies and presents exciting possibilities for the design of artificial communities.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Synthetic Biology
Synthetic Biology Agricultural and Biological Sciences-Agricultural and Biological Sciences (miscellaneous)
CiteScore
4.50
自引率
3.10%
发文量
28
审稿时长
25 weeks
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信