Document Type

Dissertation

Degree

Doctor of Philosophy (PhD)

Department

Biology

First Advisor's Name

DeEtta Mills

First Advisor's Committee Title

Committee Chair

Second Advisor's Name

Eric Von Wettberg

Second Advisor's Committee Title

Committee Member

Third Advisor's Name

Jeffrey Wells

Third Advisor's Committee Title

Committee Member

Fourth Advisor's Name

Jennifer Gebelein

Fourth Advisor's Committee Title

Committee Member

Fifth Advisor's Name

John Kominoski

Fifth Advisor's Committee Title

Committee Member

Keywords

soil provenance, microbial profiling, forensics, spatial scale, temporal variability, machine learning, functional diversity

Date of Defense

10-28-2016

Abstract

The current ecological hypothesis states that the soil type (e.g., chemical and physical properties) determines which microbes occupy a particular soil and provides the foundation for soil provenance studies. As human profiles are used to determine a match between evidence from a crime scene and a suspect, a soil microbial profile can be used to determine a match between soil found on the suspect’s shoes or clothing to the soil at a crime scene. However, for a robust tool to be applied in forensic application, an understanding of the uncertainty associated with any comparisons and the parameters that can significantly influence variability in profiles needs to be determined. This study attempted to address some of the most obvious uncertainties of soil provenance applications such as spatial variability, temporal variability, and marker selection (i.e., taxa discrimination). Pattern analysis was used to validate the ecological theories driving the soil microbial biogeography. Elucidating soil microbial communities’ spatial and temporal variability is critical to improve our understanding of the factors regulating their structure and function. Microbial profiling and bioinformatics analyses of the soil community provided a rapid method for soil provenance that can be informative, easier to perform, and more cost effective than approaches using traditional physico-chemical data. This study also showed that stable profiles may allow comparison between evidence and a possible crime scene despite the time lapse (4 years) between sample collections, however, this is dependent on the analysis method, site, vegetation, and level of disturbance. Marker selection was also an important consideration for profiling. Even though Fungi look promising for single taxon soil discrimination, the additional markers can help discriminate between a wide variety of soil types. As in human identification, the more DNA markers queried the greater the discrimination power. Lastly, this study illustrated a novel method to query the iron relating genes and ability to design a novel marker that can easily be used to profile the functional diversity of a soil community to enhance soil classification. Overall this research demonstrated the potential and effectiveness of using microbial DNA from soil, not just for comparison, but also for intelligence gathering to pinpoint the geographic origin of the soil.

Identifier

FIDC001216

Available for download on Tuesday, December 04, 2018

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