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Lessons from the microbiome in health and in death

dc.contributor.authorNieciecki, Victoria, author
dc.contributor.authorMetcalf, Jessica, advisor
dc.contributor.authorWrighton, Kelly, committee member
dc.contributor.authorAbdo, Zaid, committee member
dc.contributor.authorLana, Susan, committee member
dc.date.accessioned2025-06-02T15:21:20Z
dc.date.available2025-06-02T15:21:20Z
dc.date.issued2025
dc.descriptionZip file contains appendixes A and B spreadsheets.
dc.description.abstractThe work presented in this dissertation explores two very different microbial ecosystems found within the broad field of microbiome science–tumors and cadavers. In health, recently described low-biomass tumor-associated microbial communities are implicated in disease, and therefore microbial intervention may represent a therapeutic target. In death, the microbial decomposers of human remains show potential as a novel forensic tool that could help solve homicide cases and provide relief to the families of victims. In Chapter 1, I give a brief review of each of my research areas and summarize current knowledge gaps that exist within these fields to help provide additional context for my work in Chapters 2–4. In Chapter 2, I use 16S rRNA gene amplicon sequencing to characterize the microbiome of mucin-secreting Pseudomyxoma peritonei human tumors, focusing on microbial contamination and data reproducibility. Moving away from human health and the tumor microbiome, Chapter 3 investigates the spatial and temporal responses of microbial communities found in soil near decomposing cadavers. Finally, in Chapter 4, I explore the effects of enclosed shelter on the cadaver microbiome during human decomposition and develop microbiome-based models to estimate the postmortem interval, or time since death. In summary, my dissertation presents new and valuable insights into microbial community structure and assembly in health and in death and provides new tools for assessing environmental contamination that afflict low-biomass samples and for estimating time since death using microbial-based machine learning models.
dc.format.mediumborn digital
dc.format.mediumdoctoral dissertations
dc.format.mediumZIP
dc.format.mediumXLSX
dc.identifierNieciecki_colostate_0053A_18884.pdf
dc.identifier.urihttps://hdl.handle.net/10217/241059
dc.languageEnglish
dc.language.isoeng
dc.publisherColorado State University. Libraries
dc.relation.ispartof2020-
dc.rightsCopyright and other restrictions may apply. User is responsible for compliance with all applicable laws. For information about copyright law, please see https://libguides.colostate.edu/copyright.
dc.subjectcancer
dc.subjectmachine learning
dc.subjecttumor microbiome
dc.subjectforensics
dc.subjectcadaver microbiome
dc.subjectreproducibility
dc.titleLessons from the microbiome in health and in death
dc.typeText
dcterms.rights.dplaThis Item is protected by copyright and/or related rights (https://rightsstatements.org/vocab/InC/1.0/). You are free to use this Item in any way that is permitted by the copyright and related rights legislation that applies to your use. For other uses you need to obtain permission from the rights-holder(s).
thesis.degree.disciplineCell and Molecular Biology
thesis.degree.grantorColorado State University
thesis.degree.levelDoctoral
thesis.degree.nameDoctor of Philosophy (Ph.D.)

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