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Title: Minimal Interspecies Interaction Adjustment (MIIA): Inference of Neighbor-Dependent Interactions in Microbial Communities

Abstract

An intriguing aspect in microbial communities is that pairwise interactions can be influenced by neighboring species. This creates context dependencies for microbial interactions that are based on the functional composition of the community. Context dependent interactions are ecologically important and clearly present in nature, yet firmly established theoretical methods are lacking from many modern computational investigations. Here, we propose a novel network inference method that enables predictions for interspecies interactions affected by shifts in community composition and species populations. Our approach first identifies interspecies interactions in binary communities, which is subsequently used as a basis to infer modulation in more complex multi-species communities based on the assumption that microbes minimize adjustments of pairwise interactions in response to neighbor species. We termed this rule-based inference minimal interspecies interaction adjustment (MIIA). Our critical assessment of MIIA has produced reliable predictions of shifting interspecies interactions that are dependent on the functional role of neighbor organisms. We also show how MIIA has been applied to a microbial community composed of competing soil bacteria to elucidate a new finding that – in many cases – adding fewer competitors could impose more significant impact on binary interactions. The ability to predict membership-dependent community behavior is expectedmore » to help deepen our understanding of how microbiomes are organized in nature and how they may be designed and/or controlled in the future.« less

Authors:
; ; ; ; ; ; ;
Publication Date:
Research Org.:
Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
Sponsoring Org.:
USDOE
OSTI Identifier:
1525546
Alternate Identifier(s):
OSTI ID: 1544786
Report Number(s):
PNNL-SA-131990
Journal ID: ISSN 1664-302X; 1264
Grant/Contract Number:  
AC05-76RL01830
Resource Type:
Published Article
Journal Name:
Frontiers in Microbiology
Additional Journal Information:
Journal Name: Frontiers in Microbiology Journal Volume: 10; Journal ID: ISSN 1664-302X
Publisher:
Frontiers Media SA
Country of Publication:
Switzerland
Language:
English
Subject:
59 BASIC BIOLOGICAL SCIENCES; context dependence; network inference; rule-based approach; microbiome modeling; microbialecology

Citation Formats

Song, Hyun-Seob, Lee, Joon-Yong, Haruta, Shin, Nelson, William C., Lee, Dong-Yup, Lindemann, Stephen R., Fredrickson, Jim K., and Bernstein, Hans C. Minimal Interspecies Interaction Adjustment (MIIA): Inference of Neighbor-Dependent Interactions in Microbial Communities. Switzerland: N. p., 2019. Web. doi:10.3389/fmicb.2019.01264.
Song, Hyun-Seob, Lee, Joon-Yong, Haruta, Shin, Nelson, William C., Lee, Dong-Yup, Lindemann, Stephen R., Fredrickson, Jim K., & Bernstein, Hans C. Minimal Interspecies Interaction Adjustment (MIIA): Inference of Neighbor-Dependent Interactions in Microbial Communities. Switzerland. doi:10.3389/fmicb.2019.01264.
Song, Hyun-Seob, Lee, Joon-Yong, Haruta, Shin, Nelson, William C., Lee, Dong-Yup, Lindemann, Stephen R., Fredrickson, Jim K., and Bernstein, Hans C. Tue . "Minimal Interspecies Interaction Adjustment (MIIA): Inference of Neighbor-Dependent Interactions in Microbial Communities". Switzerland. doi:10.3389/fmicb.2019.01264.
@article{osti_1525546,
title = {Minimal Interspecies Interaction Adjustment (MIIA): Inference of Neighbor-Dependent Interactions in Microbial Communities},
author = {Song, Hyun-Seob and Lee, Joon-Yong and Haruta, Shin and Nelson, William C. and Lee, Dong-Yup and Lindemann, Stephen R. and Fredrickson, Jim K. and Bernstein, Hans C.},
abstractNote = {An intriguing aspect in microbial communities is that pairwise interactions can be influenced by neighboring species. This creates context dependencies for microbial interactions that are based on the functional composition of the community. Context dependent interactions are ecologically important and clearly present in nature, yet firmly established theoretical methods are lacking from many modern computational investigations. Here, we propose a novel network inference method that enables predictions for interspecies interactions affected by shifts in community composition and species populations. Our approach first identifies interspecies interactions in binary communities, which is subsequently used as a basis to infer modulation in more complex multi-species communities based on the assumption that microbes minimize adjustments of pairwise interactions in response to neighbor species. We termed this rule-based inference minimal interspecies interaction adjustment (MIIA). Our critical assessment of MIIA has produced reliable predictions of shifting interspecies interactions that are dependent on the functional role of neighbor organisms. We also show how MIIA has been applied to a microbial community composed of competing soil bacteria to elucidate a new finding that – in many cases – adding fewer competitors could impose more significant impact on binary interactions. The ability to predict membership-dependent community behavior is expected to help deepen our understanding of how microbiomes are organized in nature and how they may be designed and/or controlled in the future.},
doi = {10.3389/fmicb.2019.01264},
journal = {Frontiers in Microbiology},
number = ,
volume = 10,
place = {Switzerland},
year = {2019},
month = {6}
}

Journal Article:
Free Publicly Available Full Text
Publisher's Version of Record
DOI: 10.3389/fmicb.2019.01264

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Works referenced in this record:

Network Relationships of Bacteria in a Stable Mixed Culture
journal, January 2008


Indirect Effects and Habitat Use in an Intertidal Community: Interaction Chains and Interaction Modifications
journal, January 1993

  • Wootton, J. Timothy
  • The American Naturalist, Vol. 141, Issue 1
  • DOI: 10.1086/285461

Microbial interactions: from networks to models
journal, July 2012

  • Faust, Karoline; Raes, Jeroen
  • Nature Reviews Microbiology, Vol. 10, Issue 8
  • DOI: 10.1038/nrmicro2832

Higher-order interactions stabilize dynamics in competitive network models
journal, July 2017

  • Grilli, Jacopo; Barabás, György; Michalska-Smith, Matthew J.
  • Nature, Vol. 548, Issue 7666
  • DOI: 10.1038/nature23273

Regulatory on/off minimization of metabolic flux changes after genetic perturbations
journal, May 2005

  • Shlomi, T.; Berkman, O.; Ruppin, E.
  • Proceedings of the National Academy of Sciences, Vol. 102, Issue 21
  • DOI: 10.1073/pnas.0406346102

Precision microbiome reconstitution restores bile acid mediated resistance to Clostridium difficile
journal, October 2014

  • Buffie, Charlie G.; Bucci, Vanni; Stein, Richard R.
  • Nature, Vol. 517, Issue 7533
  • DOI: 10.1038/nature13828

Indirect Interspecies Regulation: Transcriptional and Physiological Responses of a Cyanobacterium to Heterotrophic Partnership
journal, March 2017


Stability criteria for complex ecosystems
journal, February 2012


Design Principles of Microbial Communities: From Understanding to Engineering
journal, October 2018


Microbial Consortia Engineering for Cellular Factories: in Vitro to in Silico Systems
journal, October 2012

  • Bernstein, Hans C.; Carlson, Ross P.
  • Computational and Structural Biotechnology Journal, Vol. 3, Issue 4
  • DOI: 10.5936/csbj.201210017

Systems-level metabolism of the altered Schaedler flora, a complete gut microbiota
journal, November 2016

  • Biggs, Matthew B.; Medlock, Gregory L.; Moutinho, Thomas J.
  • The ISME Journal, Vol. 11, Issue 2
  • DOI: 10.1038/ismej.2016.130

Will a Large Complex System be Stable?
journal, August 1972


Microbial Community Metabolic Modeling: A Community Data-Driven Network Reconstruction: COMMUNITY DATA-DRIVEN METABOLIC NETWORK MODELING
journal, June 2016

  • Henry, Christopher S.; Bernstein, Hans C.; Weisenhorn, Pamela
  • Journal of Cellular Physiology, Vol. 231, Issue 11
  • DOI: 10.1002/jcp.25428

Synthetic microbial communities
journal, April 2014


Metagenomics meets time series analysis: unraveling microbial community dynamics
journal, June 2015


Fermentation of Fructooligosaccharides and Inulin by Bifidobacteria: a Comparative Study of Pure and Fecal Cultures
journal, October 2005


Analysis of optimality in natural and perturbed metabolic networks
journal, November 2002

  • Segre, D.; Vitkup, D.; Church, G. M.
  • Proceedings of the National Academy of Sciences, Vol. 99, Issue 23
  • DOI: 10.1073/pnas.232349399

Synthetic Escherichia coli consortia engineered for syntrophy demonstrate enhanced biomass productivity
journal, January 2012


Beyond pairwise mechanisms of species coexistence in complex communities
journal, June 2017

  • Levine, Jonathan M.; Bascompte, Jordi; Adler, Peter B.
  • Nature, Vol. 546, Issue 7656
  • DOI: 10.1038/nature22898

Synergistic growth in bacteria depends on substrate complexity
journal, January 2016


Prospects of microbial cell factories developed through systems metabolic engineering
journal, July 2016


Predicting microbial interactions through computational approaches
journal, June 2016


Biochemical Systems Theory: A Review
journal, January 2013


Dynamics in microbial communities: unraveling mechanisms to identify principles
journal, December 2014

  • Konopka, Allan; Lindemann, Stephen; Fredrickson, Jim
  • The ISME Journal, Vol. 9, Issue 7
  • DOI: 10.1038/ismej.2014.251

A roadmap for biocatalysis - functional and spatial orchestration of enzyme cascades
journal, July 2016

  • Schmidt-Dannert, Claudia; Lopez-Gallego, Fernando
  • Microbial Biotechnology, Vol. 9, Issue 5
  • DOI: 10.1111/1751-7915.12386

Engineering microbial consortia for controllable outputs
journal, March 2016

  • Lindemann, Stephen R.; Bernstein, Hans C.; Song, Hyun-Seob
  • The ISME Journal, Vol. 10, Issue 9
  • DOI: 10.1038/ismej.2016.26

Mathematical Modeling of Microbial Community Dynamics: A Methodological Review
journal, October 2014

  • Song, Hyun-Seob; Cannon, William; Beliaev, Alexander
  • Processes, Vol. 2, Issue 4
  • DOI: 10.3390/pr2040711

Biofuels 2020: Biorefineries based on lignocellulosic materials
journal, July 2016

  • Valdivia, Miguel; Galan, Jose Luis; Laffarga, Joaquina
  • Microbial Biotechnology, Vol. 9, Issue 5
  • DOI: 10.1111/1751-7915.12387

Food-web analysis through field measurement of per capita interaction strength
journal, January 1992


Phenotypic responses to interspecies competition and commensalism in a naturally-derived microbial co-culture
journal, January 2018


High-order species interactions shape ecosystem diversity
journal, August 2016

  • Bairey, Eyal; Kelsic, Eric D.; Kishony, Roy
  • Nature Communications, Vol. 7, Issue 1
  • DOI: 10.1038/ncomms12285

Lotka-Volterra pairwise modeling fails to capture diverse pairwise microbial interactions
journal, March 2017


Microbial regulation of global biogeochemical cycles
journal, March 2014


The human microbiome: at the interface of health and disease
journal, March 2012

  • Cho, Ilseung; Blaser, Martin J.
  • Nature Reviews Genetics, Vol. 13, Issue 4
  • DOI: 10.1038/nrg3182

How context dependent are species interactions?
journal, April 2014

  • Chamberlain, Scott A.; Bronstein, Judith L.; Rudgers, Jennifer A.
  • Ecology Letters, Vol. 17, Issue 7
  • DOI: 10.1111/ele.12279

Emergent cooperation in microbial metabolism
journal, January 2010

  • Wintermute, Edwin H.; Silver, Pamela A.
  • Molecular Systems Biology, Vol. 6, Issue 1
  • DOI: 10.1038/msb.2010.66

Community structure follows simple assembly rules in microbial microcosms
journal, March 2017

  • Friedman, Jonathan; Higgins, Logan M.; Gore, Jeff
  • Nature Ecology & Evolution, Vol. 1, Issue 5
  • DOI: 10.1038/s41559-017-0109

Metabolic dependencies drive species co-occurrence in diverse microbial communities
journal, May 2015

  • Zelezniak, Aleksej; Andrejev, Sergej; Ponomarova, Olga
  • Proceedings of the National Academy of Sciences, Vol. 112, Issue 20
  • DOI: 10.1073/pnas.1421834112