<p>Bacteriophages are viruses that
infect and kill bacteria. They are the most abundant organism on the planet and
the largest source of untapped genetic information. Every year, more
bacteriophages are isolated from the environment, purified, and sequenced. Once
sequenced, their genomes are annotated to determine the location and putative
function of each gene expressed by the phage. Phages have been used in the past
for genetic engineering and new research is being done into how they can be
used for the treatment of disease, water safety, agriculture, and food safety. </p>
<p>Despite the influx of sequenced
bacteriophages, a majority of the genes annotated are hypothetical proteins,
also known as No Known Function (NKF) proteins. They are expressed by the
phages, but research has not identified a possible function. Wet lab research
into the functions of the hundreds of NKF phages genes would be costly and
could take years. Bioinformatics methods could be used to determine putative
functions and functional categories for these hypothetical proteins. A new
bioinformatics method using algorithms such as Domain Assignments, Hidden
Markov Models, Structure Prediction, Sub-Cellular Localization, and iterative
algorithms is proposed here. This new method was tested on the bacteriophage
genome PotatoSplit and dropped the number of NKF genes from 57 to 40. A total of 17 new
functions were found. The functional class was identified for an additional six
proteins, though no specific functions were named. Structure Prediction and
Simulations were tested with a focus on two NKF proteins within lytic phages
and both returned possible functional categories with high confidence.</p>
<p>Additionally, this research focuses on the possibility
of phage therapy and FDA regulation. A database of phage proteins was built and
tested using R Statistical Analysis to determine proteins significant to phage
infecting <i>M. tuberculosis</i> and to the lytic cycle of phages. The statistical
methods were also tested on both pharmaceutical products recalled by the FDA
between 2012 and 2018 to determine ingredients/manufacturing steps that could
affect product quality and on the FDA Adverse Event Reporting System (FAERS)
data to determine if AERs could be used to judge the quality of a product. Many
significant excipients/manufacturing steps were identified and used to score products
on their quality. The AERs were evaluated on two case studies with mixed
results. </p>
| Identifer | oai:union.ndltd.org:purdue.edu/oai:figshare.com:article/14502315 |
| Date | 05 May 2021 |
| Creators | Emily A Kerstiens (10716540) |
| Source Sets | Purdue University |
| Detected Language | English |
| Type | Text, Thesis |
| Rights | CC BY 4.0 |
| Relation | https://figshare.com/articles/thesis/NEW_BIOINFORMATIC_METHODS_OF_BACTERIOPHAGE_PROTEIN_STUDY/14502315 |
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