How Much Is Enough? an Analysis of the 5' Nontranslated Region of the Deformed Wing Virus in Honeybees

Honeybees are an essential component of today¿s agricultural system because of their role as pollinators. However, viruses, including a member of the Picornavirales order known commonly as Deformed Wing Virus (DWV), are compromising the health of honeybee colonies. Many picornaviruses, such as poliovirus, have been studied in depth because of their relation to human disease, but also because of their use of an Internal Ribosome Entry Site (IRES) to initiate translation. The primary goal of this thesis was to determine if the 5¿ Non-Translated Region (NTR) of Deformed Wing Virus (DWV) functions as an IRES. A secondary goal was to determine if there are specific parts of that 5¿ NTR that are important to IRES function. Six plasmids were constructed by inserting three different sections of the 5¿ NTR of DWV, in both sense and antisense directions, between two reporter genes. These plasmids, along with several control plasmids, were transfected into Sf9 cells, and post-transfection luciferase assays were conducted. Results were inconclusive. This could have been due to an inability of the plasmids to be expressed in Sf9 cells, an error in the construction of the plasmids, or a mechanical error in the assay procedure. At this time it appears most likely that the 5¿ NTR of DWV may be cell-type or species specific, and the next step would be to transfect the plasmids into a recently developed cultured honeybee cell line.

Measuring Correlation Between HIV Sequence Variation and Disease Stage of HIV-Infected Individuals

With a virus such as Human Immunodeficiency Virus (HIV) that has infected millions of people worldwide, and with many unaware that they are infected, it becomes vital to understand how the virus works and how it functions at the molecular level. Because there currently is no vaccine and no way to eradicate the virus from an infected person, any information about how the virus interacts with its host greatly increases the chances of understanding how HIV works and brings scientists one step closer to being able to combat such a destructive virus. Thousands of HIV viruses have been sequenced and are available in many online databases for public use. Attributes that are linked to each sequence include the viral load within the host and how sick the patient is currently. Being able to predict the stage of infection for someone is a valuable resource, as it could potentially aid in treatment options and proper medication use. Our approach of analyzing region-specific amino acid composition for select genes has been able to predict patient disease state up to an accuracy of 85.4%. Moreover, we output a set of classification rules based on the sequence that may prove useful for diagnosing the expected clinical outcome of the infected patient.