Literature DB >> 22465599

Modeling microbial communities: current, developing, and future technologies for predicting microbial community interaction.

Peter Larsen1, Yuki Hamada, Jack Gilbert.   

Abstract

Never has there been a greater opportunity for investigating microbial communities. Not only are the profound effects of microbial ecology on every aspect of Earth's geochemical cycles beginning to be understood, but also the analytical and computational tools for investigating microbial Earth are undergoing a rapid revolution. This environmental microbial interactome, the system of interactions between the microbiome and the environment, has shaped the planet's past and will undoubtedly continue to do so in the future. We review recent approaches for modeling microbial community structures and the interactions of microbial populations with their environments. Different modeling approaches consider the environmental microbial interactome from different aspects, and each provides insights to different facets of microbial ecology. We discuss the challenges and opportunities for the future of microbial modeling and describe recent advances in microbial community modeling that are extending current descriptive technologies into a predictive science.
Copyright © 2012 Elsevier B.V. All rights reserved.

Mesh:

Year:  2012        PMID: 22465599     DOI: 10.1016/j.jbiotec.2012.03.009

Source DB:  PubMed          Journal:  J Biotechnol        ISSN: 0168-1656            Impact factor:   3.307


  11 in total

Review 1.  Soil Microbial Biogeography in a Changing World: Recent Advances and Future Perspectives.

Authors:  Haiyan Chu; Gui-Feng Gao; Yuying Ma; Kunkun Fan; Manuel Delgado-Baquerizo
Journal:  mSystems       Date:  2020-04-21       Impact factor: 6.496

2.  Mathematical modeling of primary succession of murine intestinal microbiota.

Authors:  Simeone Marino; Nielson T Baxter; Gary B Huffnagle; Joseph F Petrosino; Patrick D Schloss
Journal:  Proc Natl Acad Sci U S A       Date:  2013-12-23       Impact factor: 11.205

3.  A metastable equilibrium model for the relative abundances of microbial phyla in a hot spring.

Authors:  Jeffrey M Dick; Everett L Shock
Journal:  PLoS One       Date:  2013-09-02       Impact factor: 3.240

4.  MMinte: an application for predicting metabolic interactions among the microbial species in a community.

Authors:  Helena Mendes-Soares; Michael Mundy; Luis Mendes Soares; Nicholas Chia
Journal:  BMC Bioinformatics       Date:  2016-09-02       Impact factor: 3.169

5.  Automated generation of genome-scale metabolic draft reconstructions based on KEGG.

Authors:  Emil Karlsen; Christian Schulz; Eivind Almaas
Journal:  BMC Bioinformatics       Date:  2018-12-04       Impact factor: 3.169

6.  Season, irrigation, leaf age, and Escherichia coli inoculation influence the bacterial diversity in the lettuce phyllosphere.

Authors:  Thomas R Williams; Anne-Laure Moyne; Linda J Harris; Maria L Marco
Journal:  PLoS One       Date:  2013-07-02       Impact factor: 3.240

7.  Evaluating the impact of different sequence databases on metaproteome analysis: insights from a lab-assembled microbial mixture.

Authors:  Alessandro Tanca; Antonio Palomba; Massimo Deligios; Tiziana Cubeddu; Cristina Fraumene; Grazia Biosa; Daniela Pagnozzi; Maria Filippa Addis; Sergio Uzzau
Journal:  PLoS One       Date:  2013-12-09       Impact factor: 3.240

8.  Bridging the divide: a model-data approach to Polar and Alpine microbiology.

Authors:  James A Bradley; Alexandre M Anesio; Sandra Arndt
Journal:  FEMS Microbiol Ecol       Date:  2016-01-31       Impact factor: 4.194

9.  Environmental Disturbances Decrease the Variability of Microbial Populations within Periphyton.

Authors:  Cristina M Herren; Kyle C Webert; Katherine D McMahon
Journal:  mSystems       Date:  2016-05-17       Impact factor: 6.496

Review 10.  K-Selection as Microbial Community Management Strategy: A Method for Improved Viability of Larvae in Aquaculture.

Authors:  Olav Vadstein; Kari J K Attramadal; Ingrid Bakke; Yngvar Olsen
Journal:  Front Microbiol       Date:  2018-11-14       Impact factor: 5.640

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