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.
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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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- All Subjects: Biology
- Creators: Taylor, Jesse
- Creators: Krajmalnik-Brown, Rosa
This work begins by defining a working window of light intensity (LI). Wild-type and laurate-excreting Synechocystis required an LI of at least 5 µE/m2-s to sustain themselves, but are photo-inhibited by LI of 346 to 598 µE/m2-s.
Fixing electrons into valuable organic products, e.g., biomass and excreted laurate, is critical to success. Wild-type Synechocystis channeled 75% to 84% of its fixed electrons to biomass; laurate-excreting Synechocystis fixed 64 to 69% as biomass and 6.6% to 10% as laurate. This means that 16 to 30% of the electrons were diverted to non-valuable soluble products, and the trend was accentuated with higher LI.
How the Ci concentration depended on the pH and the nitrogen source was quantified by the proton condition and experimentally validated. Nitrate increased, ammonium decreased, but ammonium nitrate stabilized alkalinity and Ci. This finding provides a mechanistically sound tool to manage Ci and pH independently.
Independent evaluation pH and Ci on the growth kinetics of Synechocystis showed that pH 8.5 supported the fastest maximum specific growth rate (µmax): 2.4/day and 1.7/day, respectively, for the wild type and modified strains with LI of 202 µE/m2-s. Half-maximum-rate concentrations (KCi) were less than 0.1 mM, meaning that Synechocystis should attain its µmax with a modest Ci concentration (≥1.0 mM).
Biomass grown with day-night cycles had a night endogenous decay rate of 0.05-1.0/day, with decay being faster with higher LI and the beginning of dark periods. Supplying light at a fraction of daylight reduced dark decay rate and improved overall biomass productivity.
This dissertation systematically evaluates and synthesizes fundamental growth factors of cyanobacteria: light, inorganic carbon (Ci), and pH. LI remains the most critical growth condition to promote biomass productivity and desired forms of biomass, while Ci and pH now can be managed to support optimal productivity.
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.