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Ethel Nankya Successfully Defends

Congratulations to Ethel Nankya on the successful defense of their thesis. "Computational Approaches for Metatranscriptomic Profiling in Translational Medicine and Pulmonary Diseases" Great job Ethel!


To learn more about Ethel's thesis, read their abstract below:



Use of total RNA-seq in host and microbiome analysis allows for multi-omic interrogation of microbial profiles, assessment of their function and their interaction with host immune and metabolic pathways. This type of analysis calls for novel computational techniques. However, existing tools for analyzing microbial multi-omic data are lacking, as they typically address a single data type. For example, there are many available tools for the characterization of microbial communities, but these are unable to investigate microbial-host interactions. To address this need, a novel computational pipeline that integrates existing methods for microbial and host expression profiling was developed. This pipeline provides insight into possible personalized medical interventions in translational medicine. This dissertation utilized – transcriptomics and metatranscriptomics to interrogate: 1) host-microbial interactions in people with indeterminate pulmonary nodules, 2) the role of Human Endogenous Retroviruses in pulmonary diseases like lung cancer and in the early onset of ageing observed in virologically suppressed HIV positive individuals, and finally 3) to characterize humoral responses to SARSCoV- 2 peptides in Covid -19 patients.


Cigarette smoking has been known to cause or exacerbate many lung pathologies, including the association with the majority of lung cancers. Smoking also plays a major role in offsetting the human microbiota, a regulator of human health. For the first project (above), nasal and bronchial brushings were collected from current and former smokers with indeterminate pulmonary nodules (IPNs) from the Detection of Early Lung Cancer Among Military Personnel (DECAMP) study. Datasets were processed, sources of batch effects were addressed, and statistical approaches were utilized to identify differentially abundant microbes in current and former smokers and malignant and benign samples. Lastly, the most abundant microbes in both datasets were linked to human pathways and tested for their strength of association. This approach aided in providing insight into the possible functional profile of these microbes and their role in lung cancer.


The advent of Highly Active Antiretroviral Therapy (HAART) has led to an increased life expectancy among HIV infected individuals. While this has been celebrated within the medical world, it has become more evident that people living with HIV (PLWHIV) are susceptible to ageing related conditions which are normally observed in the elderly. Some of the ageing conditions are caused by chronic inflammation and immune activation. The second study aimed to identify HERVS differentially expressed in HIV positive individuals. In addition, this work sought to investigate whether these HERVS were associated with human pathways involved in ageing associated inflammation and plasma inflammatory markers. Using total RNA-seq from whole blood from PLWHIV and HIV negative individuals, Telescope software was used to generate HERVs counts. Differential analyses were then performed to identify differentially expressed HERVs in PLHIV. The association with pathways involved in inflammageing and inflammatory markers was then investigated. From these analyses, this work identified HERVS that could act as therapeutic targets to reduce the chronic inflammation in the HIV setting. In addition, these HERVs can serve as diagnostic markers for chronic inflammation in PLWHIV.


The emergence of SARS-CoV-2 virus a betacoronavirus greatly impacted economies and health systems globally. The disease spectrum caused by SARS-CoV-2 ranges from asymptomatic cases to mild disease forms which could progress to severe forms. For project three, this work sought to characterize IgG and IgM humoral responses to SARS-CoV-2 at the epitope level using high-density peptide microarrays covering the entire proteome. Using data generated by our collaborators, discriminating epitopes for disease severity were identified. Epitopes conserved between SARS-CoV-2 virus and other Human coronaviruses were also discovered, allowing the investigation of associations with less severe disease outcomes. These epitopes could serve as discriminative markers for COVID-19 disease severity.


In conclusion, we have applied novel computational tools to interrogate functional profiles in microbes and Human Endogenous retroviruses. 

Major Professor: W. Evan Johnson


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