Microorganisms are capable of carrying out molecular functionality relevant to a range of human interests, including health, industrial production, and bioremediation. Current microbial taxonomy is phylogeny-guided, i.e., the organisms are grouped based on their evolutionary relationships. Due to horizontal gene transfer, evolutionary relatedness cannot guarantee genome-encoded molecular functional similarity. In this work, we establish a computational framework for comparison of microorganisms based on their molecular functionality. In the fusion (functional-repertoire similarity-based organism network) representation, organisms can be consistently assigned to groups based on a quantitative measure of their functional similarities. The results highlight the specific environmental factor(s) that explain the functional differences between groups of microorganism. We deposit the functional data in fusionDB, mapping bacteria and their functions to available metadata: habitat/niche, preferred temperature, and oxygen use. The web interface further allows mapping new microbial genomes to the functional spectrum of reference bacteria. In the end, we describe mi-faser (microbiome functional annotation of sequencing reads), the meta-genomic/-transcriptomic analysis pipeline combining an algorithm that is optimised to map reads to molecular functions encoded by the read-correspondent genes, and a manually curated reference database of protein functions. With mi-faser, we identify previously unseen oil degradation-specific functions in BP oil-spill data, and reveal the role of gut microbiome in Crohn’s disease pathogenicity, showing that the patient microbiomes are enriched in both the functions that promote inflammation and those that help bacteria survive it.
Subject (authority = RUETD)
Topic
Microbiology and Molecular Genetics
RelatedItem (type = host)
TitleInfo
Title
Rutgers University Electronic Theses and Dissertations
Identifier (type = RULIB)
ETD
Identifier
ETD_7926
PhysicalDescription
Form (authority = gmd)
electronic resource
InternetMediaType
application/pdf
InternetMediaType
text/xml
Extent
1 online resource (xi, 123 p. : ill.)
Note (type = degree)
Ph.D.
Note (type = bibliography)
Includes bibliographical references
Subject (authority = ETD-LCSH)
Topic
Bioinformatics
Subject (authority = ETD-LCSH)
Topic
Microbial genomes
Note (type = statement of responsibility)
by Chengsheng Zhu
RelatedItem (type = host)
TitleInfo
Title
Graduate School - New Brunswick Electronic Theses and Dissertations
Identifier (type = local)
rucore19991600001
Location
PhysicalLocation (authority = marcorg); (displayLabel = Rutgers, The State University of New Jersey)
Rutgers University. Graduate School - New Brunswick
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Type
License
Name
Author Agreement License
Detail
I hereby grant to the Rutgers University Libraries and to my school the non-exclusive right to archive, reproduce and distribute my thesis or dissertation, in whole or in part, and/or my abstract, in whole or in part, in and from an electronic format, subject to the release date subsequently stipulated in this submittal form and approved by my school. I represent and stipulate that the thesis or dissertation and its abstract are my original work, that they do not infringe or violate any rights of others, and that I make these grants as the sole owner of the rights to my thesis or dissertation and its abstract. I represent that I have obtained written permissions, when necessary, from the owner(s) of each third party copyrighted matter to be included in my thesis or dissertation and will supply copies of such upon request by my school. I acknowledge that RU ETD and my school will not distribute my thesis or dissertation or its abstract if, in their reasonable judgment, they believe all such rights have not been secured. I acknowledge that I retain ownership rights to the copyright of my work. I also retain the right to use all or part of this thesis or dissertation in future works, such as articles or books.