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Massachusetts Institute of Technology

Insights into microbial community structure from pairwise interaction networks

Abstract

dc:description.abstract

Microbial communities are typically incredibly diverse, with many species contributing to the overall function of the community. The structure of these communities is the result of many complex biotic and abiotic factors. In this thesis, my colleagues and I employ a bottom-up approach to investigate the role of interspecies interactions in determining the structure of multispecies communities. First, we investigate the network of pairwise competitive interactions in a model community consisting of 20 strains of naturally co-occurring soil bacteria. The resulting interaction network is strongly hierarchical and lacks significant non-transitive motifs, a result that is robust across multiple environments. Multispecies competitions resulted in extinction of all but the most highly competitive strains, indicating that higher order interactions do not play a major role in structuring this community.

Degree

thesis:*
Department dc:contributor.department
Massachusetts Institute of Technology. Department of Biology
Grantor dc:publisher
Massachusetts Institute of Technology
Year dc:date.issued
2017

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Higgins, Logan Massie.
Advisor dc:contributor.advisor
  • Jeff Gore.

Subjects

dc:subject × 1

Rights

dc:rights
Statement dc:rights
  • MIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission.
Language dc:language.iso
eng

Identifiers

dc:identifier.*
Handle dc:identifier.uri
http://hdl.handle.net/1721.1/113465
OAI identifier oai:identifier
oai:dspace.mit.edu:1721.1/113465

Chain of custody

source
Harvested from
MIT
Base URL
dspace.mit.edu/oai/request
Last updated
2026-07-22
Source record
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related terms
citation

Higgins, Logan Massie.. Insights into microbial community structure from pairwise interaction networks. Massachusetts Institute of Technology, 2017. http://hdl.handle.net/1721.1/113465