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Boston University

Using high throughput data to understand microbes and their interaction with the environment

Abstract

dc:description.abstract

The human microbiome ecosystem plays numerous, yet poorly understood beneficial roles in human health. It can shape the immune response and provide essential vitamins and enzymes to the host. The different environments present in the human host are a major determinant of community composition. Conversely, the presence of certain bacteria in specific parts of the human body is sometimes associated with an increased chance of pathologies. Advances in DNA sequencing have increased our understanding of the relationship of microbes with the environment. However, sequencing data alone is unlikely to provide such understanding without the help of appropriate computational models and analyses. For the first part of this thesis, I applied to the infant gut microbiome an approach previously used to understand the order of colonization of microbial biofilms. Available metagenomic sequencing data from infant fecal samples collected for 2.5 years was queried to test whether or not the gut colonization process is a multi-step process, in which the organisms that are prevalent at a given time are closely related, in their metabolic capabilities, to the organisms present at the previous time step. I further used network expansion algorithms previously developed for the study of large-scale biogeochemical evolution, to explore the dynamics and diet-dependency of the gut microbiome. These analyses suggest that metabolic relatedness among organisms is an important factor in the colonization process. The second part of my thesis explores the role of H. pylori in gastric cancer. I analyzed public microarray data for gastric AGS cancer cell lines infected with different strains of H. pylori differing in pathogenicity. Relative to uninfected AGS cell lines, low-pathogenic H. pylori strain displayed no major metabolic dysregulation, consistent with the fact that H. pylori does not cause inflammation/gastric cancer in a majority of the human population. However, gastric AGS cell lines infected with highly pathogenic strains showed more significant differences, including the upregulation of purine metabolism, possibly consistent with an inflammatory response. The results in this dissertation thus offer insights into how the interplay between metabolic activity of human-associated microbes and their surrounding environment plays an important role in the colonization process as well as in pathogenesis.

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Kar, Amrita

Subjects

dc:subject × 1

Rights

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Statement dc:rights
  • Attribution 4.0 International
Language dc:language.iso
en_US

Identifiers

dc:identifier.*
Handle dc:identifier.uri
https://hdl.handle.net/2144/20739
OAI identifier oai:identifier
oai:open.bu.edu:2144/20739

Chain of custody

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Boston University
Base URL
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Last updated
2026-07-24
Source record
OAI-PMH GetRecord
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citation

Kar, Amrita. Using high throughput data to understand microbes and their interaction with the environment. 2017. https://hdl.handle.net/2144/20739