Quantitative and analytical tools to analyze the spatiotemporal population dynamics of microbial consortia

被引:10
作者
Liu, Yugeng [1 ]
Xu, Peng [1 ,2 ]
机构
[1] Guangdong Technion Israel Inst Technol, Dept Chem Engn, Shantou 515063, Guangdong, Peoples R China
[2] Guangdong Technion Israel Inst Technol, Guangdong Prov Key Lab Mat & Technol Energy Conve, Shantou 515063, Guangdong, Peoples R China
基金
中国国家自然科学基金;
关键词
COMMUNITIES; MODELS;
D O I
10.1016/j.copbio.2022.102754
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
Microorganisms occupy almost every niche on earth. They play critical roles in maintaining ecological balance, atmospheric C/ N cycle, and human health. Microbes live in consortia with metabolite exchange or signal communication. Quantitative and analytical tools are becoming increasingly important to study microbial consortia dynamics. We argue that a combined reductionist and holistic approach will be important to understanding the assembly rules and spatiotemporal population dynamics of the microbial community (MICOM). Reductionism allows us to reconstruct complex MICOM from isolated or simple synthetic consortia. Holism allows us to understand microbes as a community with cooperation and competition. Here we review the recent development of quantitative and analytical tools to uncover the underlying principles in microbial communities that govern their spatiotemporal change and interaction dynamics. Mathematical models and analytical tools will continue to provide essential knowledge and expand our capability to manipulate and control microbial consortia.
引用
收藏
页数:11
相关论文
共 48 条
  • [1] HPIDB 2.0: a curated database for host-pathogen interactions
    Ammari, Mais G.
    Gresham, Cathy R.
    McCarthy, Fiona M.
    Nanduri, Bindu
    [J]. DATABASE-THE JOURNAL OF BIOLOGICAL DATABASES AND CURATION, 2016,
  • [2] An insight to flux-balance analysis for biochemical networks
    Anand, Shreya
    Mukherjee, Koel
    Padmanabhan, Padmini
    [J]. BIOTECHNOLOGY AND GENETIC ENGINEERING REVIEWS, VOL 36, NO 1, 2020, 36 (01): : 32 - 55
  • [3] An efficient and scalable top-down method for predicting structures of microbial communities
    Ansari, Aamir Faisal
    Reddy, Yugandhar B. S.
    Raut, Janhavi
    Dixit, Narendra M.
    [J]. NATURE COMPUTATIONAL SCIENCE, 2021, 1 (09): : 619 - +
  • [4] NCBI GEO: archive for functional genomics data sets-update
    Barrett, Tanya
    Wilhite, Stephen E.
    Ledoux, Pierre
    Evangelista, Carlos
    Kim, Irene F.
    Tomashevsky, Maxim
    Marshall, Kimberly A.
    Phillippy, Katherine H.
    Sherman, Patti M.
    Holko, Michelle
    Yefanov, Andrey
    Lee, Hyeseung
    Zhang, Naigong
    Robertson, Cynthia L.
    Serova, Nadezhda
    Davis, Sean
    Soboleva, Alexandra
    [J]. NUCLEIC ACIDS RESEARCH, 2013, 41 (D1) : D991 - D995
  • [5] Persistence and plasticity in bacterial gene regulation
    Baumgart, Leo A.
    Lee, Ji Eun
    Salamov, Asaf
    Dilworth, David J.
    Na, Hyunsoo
    Mingay, Matthew
    Blow, Matthew J.
    Zhang, Yu
    Yoshinaga, Yuko
    Daum, Chris G.
    O'Malley, Ronan C.
    [J]. NATURE METHODS, 2021, 18 (12) : 1499 - +
  • [6] Spatial-omics: Novel approaches to probe cell heterogeneity and extracellular matrix biology
    Bingham, Grace C.
    Lee, Fred
    Naba, Alexandra
    Barker, Thomas H.
    [J]. MATRIX BIOLOGY, 2020, 91-92 : 152 - 166
  • [7] Design of synthetic human gut microbiome assembly and butyrate production
    Clark, Ryan L.
    Connors, Bryce M.
    Stevenson, David M.
    Hromada, Susan E.
    Hamilton, Joshua J.
    Amador-Noguez, Daniel
    Venturelli, Ophelia S.
    [J]. NATURE COMMUNICATIONS, 2021, 12 (01)
  • [8] A resource ratio theory of cooperation
    de Mazancourt, Claire
    Schwartz, Mark W.
    [J]. ECOLOGY LETTERS, 2010, 13 (03) : 349 - 359
  • [9] DIENER C, 2020, MSYSTEMS, V5, DOI DOI 10.1128/MSYSTEMS.00606-19
  • [10] Inferring Correlation Networks from Genomic Survey Data
    Friedman, Jonathan
    Alm, Eric J.
    [J]. PLOS COMPUTATIONAL BIOLOGY, 2012, 8 (09)