以网络为工具,定义微生物群的突发特性及其稳定性。

IF 13.8 1区 生物学 Q1 MICROBIOLOGY Microbiome Pub Date : 2024-09-28 DOI:10.1186/s40168-024-01868-z
Kacie T Kajihara, Nicole A Hynson
{"title":"以网络为工具,定义微生物群的突发特性及其稳定性。","authors":"Kacie T Kajihara, Nicole A Hynson","doi":"10.1186/s40168-024-01868-z","DOIUrl":null,"url":null,"abstract":"<p><p>The potential promise of the microbiome to ameliorate a wide range of societal and ecological challenges, from disease prevention and treatment to the restoration of entire ecosystems, hinges not only on microbiome engineering but also on the stability of beneficial microbiomes. Yet the properties of microbiome stability remain elusive and challenging to discern due to the complexity of interactions and often intractable diversity within these communities of bacteria, archaea, fungi, and other microeukaryotes. Networks are powerful tools for the study of complex microbiomes, with the potential to elucidate structural patterns of stable communities and generate testable hypotheses for experimental validation. However, the implementation of these analyses introduces a cascade of dichotomies and decision trees due to the lack of consensus on best practices. Here, we provide a road map for network-based microbiome studies with an emphasis on discerning properties of stability. We identify important considerations for data preparation, network construction, and interpretation of network properties. We also highlight remaining limitations and outstanding needs for this field. This review also serves to clarify the varying schools of thought on the application of network theory for microbiome studies and to identify practices that enhance the reproducibility and validity of future work. Video Abstract.</p>","PeriodicalId":18447,"journal":{"name":"Microbiome","volume":"12 1","pages":"184"},"PeriodicalIF":13.8000,"publicationDate":"2024-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11439251/pdf/","citationCount":"0","resultStr":"{\"title\":\"Networks as tools for defining emergent properties of microbiomes and their stability.\",\"authors\":\"Kacie T Kajihara, Nicole A Hynson\",\"doi\":\"10.1186/s40168-024-01868-z\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>The potential promise of the microbiome to ameliorate a wide range of societal and ecological challenges, from disease prevention and treatment to the restoration of entire ecosystems, hinges not only on microbiome engineering but also on the stability of beneficial microbiomes. Yet the properties of microbiome stability remain elusive and challenging to discern due to the complexity of interactions and often intractable diversity within these communities of bacteria, archaea, fungi, and other microeukaryotes. Networks are powerful tools for the study of complex microbiomes, with the potential to elucidate structural patterns of stable communities and generate testable hypotheses for experimental validation. However, the implementation of these analyses introduces a cascade of dichotomies and decision trees due to the lack of consensus on best practices. Here, we provide a road map for network-based microbiome studies with an emphasis on discerning properties of stability. We identify important considerations for data preparation, network construction, and interpretation of network properties. We also highlight remaining limitations and outstanding needs for this field. This review also serves to clarify the varying schools of thought on the application of network theory for microbiome studies and to identify practices that enhance the reproducibility and validity of future work. Video Abstract.</p>\",\"PeriodicalId\":18447,\"journal\":{\"name\":\"Microbiome\",\"volume\":\"12 1\",\"pages\":\"184\"},\"PeriodicalIF\":13.8000,\"publicationDate\":\"2024-09-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11439251/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Microbiome\",\"FirstCategoryId\":\"99\",\"ListUrlMain\":\"https://doi.org/10.1186/s40168-024-01868-z\",\"RegionNum\":1,\"RegionCategory\":\"生物学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"MICROBIOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Microbiome","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.1186/s40168-024-01868-z","RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MICROBIOLOGY","Score":null,"Total":0}
引用次数: 0

摘要

微生物组在改善从疾病预防和治疗到恢复整个生态系统等一系列社会和生态挑战方面的潜在前景,不仅取决于微生物组工程,还取决于有益微生物组的稳定性。然而,由于这些由细菌、古细菌、真菌和其他微核生物组成的群落中存在着复杂的相互作用和往往难以解决的多样性,微生物组稳定性的特性仍然难以捉摸,而且难以辨别。网络是研究复杂微生物群的强大工具,有可能阐明稳定群落的结构模式,并产生可检验的假设供实验验证。然而,由于对最佳实践缺乏共识,这些分析的实施引入了一连串的二分法和决策树。在这里,我们为基于网络的微生物组研究提供了一个路线图,重点是辨别稳定性的特性。我们确定了数据准备、网络构建和网络属性解释的重要注意事项。我们还强调了这一领域仍然存在的局限性和有待满足的需求。本综述还有助于澄清将网络理论应用于微生物组研究的不同流派,并确定可提高未来工作可重复性和有效性的做法。视频摘要。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Networks as tools for defining emergent properties of microbiomes and their stability.

The potential promise of the microbiome to ameliorate a wide range of societal and ecological challenges, from disease prevention and treatment to the restoration of entire ecosystems, hinges not only on microbiome engineering but also on the stability of beneficial microbiomes. Yet the properties of microbiome stability remain elusive and challenging to discern due to the complexity of interactions and often intractable diversity within these communities of bacteria, archaea, fungi, and other microeukaryotes. Networks are powerful tools for the study of complex microbiomes, with the potential to elucidate structural patterns of stable communities and generate testable hypotheses for experimental validation. However, the implementation of these analyses introduces a cascade of dichotomies and decision trees due to the lack of consensus on best practices. Here, we provide a road map for network-based microbiome studies with an emphasis on discerning properties of stability. We identify important considerations for data preparation, network construction, and interpretation of network properties. We also highlight remaining limitations and outstanding needs for this field. This review also serves to clarify the varying schools of thought on the application of network theory for microbiome studies and to identify practices that enhance the reproducibility and validity of future work. Video Abstract.

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
Microbiome
Microbiome MICROBIOLOGY-
CiteScore
21.90
自引率
2.60%
发文量
198
审稿时长
4 weeks
期刊介绍: Microbiome is a journal that focuses on studies of microbiomes in humans, animals, plants, and the environment. It covers both natural and manipulated microbiomes, such as those in agriculture. The journal is interested in research that uses meta-omics approaches or novel bioinformatics tools and emphasizes the community/host interaction and structure-function relationship within the microbiome. Studies that go beyond descriptive omics surveys and include experimental or theoretical approaches will be considered for publication. The journal also encourages research that establishes cause and effect relationships and supports proposed microbiome functions. However, studies of individual microbial isolates/species without exploring their impact on the host or the complex microbiome structures and functions will not be considered for publication. Microbiome is indexed in BIOSIS, Current Contents, DOAJ, Embase, MEDLINE, PubMed, PubMed Central, and Science Citations Index Expanded.
期刊最新文献
Ileal microbial microbiome and its secondary bile acids modulate susceptibility to nonalcoholic steatohepatitis in dairy goats. The links between dietary diversity and RNA virus diversity harbored by the great evening bat (Ia io). From grasslands to genes: exploring the major microbial drivers of antibiotic-resistance in microhabitats under persistent overgrazing. Correction: Parabacteroides distasonis regulates the infectivity and pathogenicity of SVCV at different water temperatures. The intestinal microbiome and Cetobacterium somerae inhibit viral infection through TLR2-type I IFN signaling axis in zebrafish.
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1