ASU Electronic Theses and Dissertations
This collection includes most of the ASU Theses and Dissertations from 2011 to present. ASU Theses and Dissertations are available in downloadable PDF format; however, a small percentage of items are under embargo. Information about the dissertations/theses includes degree information, committee members, an abstract, supporting data or media.
In addition to the electronic theses found in the ASU Digital Repository, ASU Theses and Dissertations can be found in the ASU Library Catalog.
Dissertations and Theses granted by Arizona State University are archived and made available through a joint effort of the ASU Graduate College and the ASU Libraries. For more information or questions about this collection contact or visit the Digital Repository ETD Library Guide or contact the ASU Graduate College at gradformat@asu.edu.
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Three approaches were used for the characterization of these suppressors. The first approach focused on side chain specificity. The results showed that certain suppressor sites prefer a particular side chain property, such as size, to overcome the F610A defect. The second approach focused on the effects of efflux pump inhibitors. The results showed that though the suppressor residues were able to overcome the intrinsic defect of F610A, they were unable to overcome the extrinsic defect caused by the efflux pump inhibitors. This showed that the mechanism by which F610A imposes its effect on AcrB function is different than that of the efflux pump inhibitors. The final approach was to determine whether suppressors mapping in the periplasmic and trans-membrane domains act by the same or different mechanisms. The results showed both overlapping and distinct mechanisms of suppression.
To conclude, these approaches have provided a deeper understanding of the mechanisms by which novel suppressor residues of AcrB overcome the functional defect of the drug binding domain alteration, F610A.
Characterization and Manipulation of Microbiomes From Arid Landfills for Improved Methane Production
This can make mutation detection difficult; and while increasing sequencing depth
can often help, sequence-specific errors and other non-random biases cannot be de-
tected by increased depth. The problem of accurate genotyping is exacerbated when
there is not a reference genome or other auxiliary information available.
I explore several methods for sensitively detecting mutations in non-model or-
ganisms using an example Eucalyptus melliodora individual. I use the structure of
the tree to find bounds on its somatic mutation rate and evaluate several algorithms
for variant calling. I find that conventional methods are suitable if the genome of a
close relative can be adapted to the study organism. However, with structured data,
a likelihood framework that is aware of this structure is more accurate. I use the
techniques developed here to evaluate a reference-free variant calling algorithm.
I also use this data to evaluate a k-mer based base quality score recalibrator
(KBBQ), a tool I developed to recalibrate base quality scores attached to sequencing
data. Base quality scores can help detect errors in sequencing reads, but are often
inaccurate. The most popular method for correcting this issue requires a known
set of variant sites, which is unavailable in most cases. I simulate data and show
that errors in this set of variant sites can cause calibration errors. I then show that
KBBQ accurately recalibrates base quality scores while requiring no reference or other
information and performs as well as other methods.
Finally, I use the Eucalyptus data to investigate the impact of quality score calibra-
tion on the quality of output variant calls and show that improved base quality score
calibration increases the sensitivity and reduces the false positive rate of a variant
calling algorithm.