文献检索文档翻译深度研究
Suppr Zotero 插件Zotero 插件
邀请有礼套餐&价格历史记录

新学期,新优惠

限时优惠:9月1日-9月22日

30天高级会员仅需29元

1天体验卡首发特惠仅需5.99元

了解详情
不再提醒
插件&应用
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
高级版
套餐订阅购买积分包
AI 工具
文献检索文档翻译深度研究
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2025

预测微生物群落中涌现特性的生态建模方法。

Ecological modelling approaches for predicting emergent properties in microbial communities.

机构信息

Medical Research Council Toxicology Unit, University of Cambridge, Cambridge, UK.

Department of Biotechnology and Food Science, Norwegian University of Science and Technology, Trondheim, Norway.

出版信息

Nat Ecol Evol. 2022 Jul;6(7):855-865. doi: 10.1038/s41559-022-01746-7. Epub 2022 May 16.


DOI:10.1038/s41559-022-01746-7
PMID:35577982
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7613029/
Abstract

Recent studies have brought forward the critical role of emergent properties in shaping microbial communities and the ecosystems of which they are a part. Emergent properties-patterns or functions that cannot be deduced linearly from the properties of the constituent parts-underlie important ecological characteristics such as resilience, niche expansion and spatial self-organization. While it is clear that emergent properties are a consequence of interactions within the community, their non-linear nature makes mathematical modelling imperative for establishing the quantitative link between community structure and function. As the need for conservation and rational modulation of microbial ecosystems is increasingly apparent, so is the consideration of the benefits and limitations of the approaches to model emergent properties. Here we review ecosystem modelling approaches from the viewpoint of emergent properties. We consider the scope, advantages and limitations of Lotka-Volterra, consumer-resource, trait-based, individual-based and genome-scale metabolic models. Future efforts in this research area would benefit from capitalizing on the complementarity between these approaches towards enabling rational modulation of complex microbial ecosystems.

摘要

最近的研究提出了突发属性在塑造微生物群落及其所属生态系统方面的关键作用。突发属性——不能从组成部分的属性线性推断出的模式或功能——是重要生态特征的基础,如弹性、生态位扩展和空间自组织。虽然很明显,突发属性是群落内部相互作用的结果,但它们的非线性性质使得数学建模对于建立群落结构和功能之间的定量联系至关重要。随着保护和合理调节微生物生态系统的需求日益明显,考虑到模型突发属性的方法的优缺点也变得越来越重要。在这里,我们从突发属性的角度来回顾生态系统建模方法。我们考虑了洛特卡-沃尔泰拉、消费者-资源、基于特征、基于个体和基于基因组规模代谢模型的范围、优势和局限性。该研究领域的未来工作将受益于利用这些方法之间的互补性,以实现对复杂微生物生态系统的合理调节。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2899/7613029/9ff5606d85d8/EMS143980-f003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2899/7613029/1fe73c40ae30/EMS143980-f001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2899/7613029/c5f4c901234e/EMS143980-f002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2899/7613029/9ff5606d85d8/EMS143980-f003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2899/7613029/1fe73c40ae30/EMS143980-f001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2899/7613029/c5f4c901234e/EMS143980-f002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2899/7613029/9ff5606d85d8/EMS143980-f003.jpg

相似文献

[1]
Ecological modelling approaches for predicting emergent properties in microbial communities.

Nat Ecol Evol. 2022-7

[2]

2004

[3]
Predicting emergent animal biodiversity patterns across multiple scales.

Glob Chang Biol. 2024-7

[4]
Exploring spatial segregation induced by competition avoidance as driving mechanism for emergent coexistence in microbial communities.

Phys Rev E. 2024-7

[5]
Modelling microbial communities using biochemical resource allocation analysis.

J R Soc Interface. 2019-11-6

[6]
Metabolic and demographic feedbacks shape the emergent spatial structure and function of microbial communities.

PLoS Comput Biol. 2013-12-26

[7]
Short-range interactions govern the dynamics and functions of microbial communities.

Nat Ecol Evol. 2020-2-10

[8]
When does a Lotka-Volterra model represent microbial interactions? Insights from nasal bacterial communities.

mSystems. 2023-6-29

[9]
Formation of a constructed microbial community in a nutrient-rich environment indicates bacterial interspecific competition.

mSystems. 2024-4-16

[10]
Identifying and explaining resilience in ecological networks.

Ecol Lett. 2024-8

引用本文的文献

[1]
Detecting (the Absence of) Species Interactions in Microbial Ecological Systems.

Stud Appl Math. 2025-2

[2]
In silico encounters: harnessing metabolic modelling to understand plant-microbe interactions.

FEMS Microbiol Rev. 2025-1-14

[3]
Integrative systems biology approaches for analyzing microbiome dysbiosis and species interactions.

Brief Bioinform. 2025-7-2

[4]
Dissecting the physics of bacterial biofilms with agent-based simulations.

Curr Opin Solid State Mater Sci. 2025-7

[5]
A survey of computational approaches for characterizing microbial interactions in microbial mats.

Genome Biol. 2025-6-16

[6]
Diffusion-based mechanism explains spatial organization in cross-feeding biofilms.

NPJ Biofilms Microbiomes. 2025-6-11

[7]
Harnessing emergent properties of microbial consortia for Agriculture: Assembly of the Xilonen SynCom.

Biofilm. 2025-5-3

[8]
Impact of Virus-Mediated Modifications in Bacterial Communities on the Accumulation of Soil Organic Carbon.

Adv Sci (Weinh). 2025-8

[9]
Can the Discovery of High-Impact Diagnostics Be Improved by Matching the Sampling Rate of Clinical Diagnostics to the Frequency Domain of Diagnostic Information?

Cancers (Basel). 2025-4-22

[10]
Leveraging strain competition to address antimicrobial resistance with microbiota therapies.

Gut Microbes. 2025-12

本文引用的文献

[1]
Microbial community dynamics revisited.

Nat Comput Sci. 2021-10

[2]
Bacterial growth in multicellular aggregates leads to the emergence of complex life cycles.

Curr Biol. 2022-7-25

[3]
Positive interactions are common among culturable bacteria.

Sci Adv. 2021-11-5

[4]
Rules of Engagement: A Guide to Developing Agent-Based Models.

Methods Mol Biol. 2022

[5]
Diverse communities behave like typical random ecosystems.

Phys Rev E. 2021-9

[6]
Heavy-tailed abundance distributions from stochastic Lotka-Volterra models.

Phys Rev E. 2021-9

[7]
metaGEM: reconstruction of genome scale metabolic models directly from metagenomes.

Nucleic Acids Res. 2021-12-2

[8]
Environmental fluctuations reshape an unexpected diversity-disturbance relationship in a microbial community.

Elife. 2021-9-3

[9]
Adaptive laboratory evolution of microbial co-cultures for improved metabolite secretion.

Mol Syst Biol. 2021-8

[10]
Structural identifiability of the generalized Lotka-Volterra model for microbiome studies.

R Soc Open Sci. 2021-7-21

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

推荐工具

医学文档翻译智能文献检索