Life Sciences – Page 3 – UROP Spring Symposium 2021

Life Sciences

Mass spectrometry based assessment of the Tryptophan catabolism in Chronic Kidney Disease accelerated heart disease

Despite the improvements in renal replacement therapies, cardiovascular disease (CVD) remains one of the leading causes of mortality for chronic kidney disease (CKD) patients with a 10-fold increase in mortality rate compared to individuals without CKD. The reason behind this increased risk is not fully explained through classical risk factors; however, non-traditional risk factors like inflammation play an important role in the pathogenesis of CKD atherosclerosis. More specifically, tryptophan metabolism has been linked to inflammation in CKD patients through the kynurenine pathway (KP). In our previous study, tryptophan metabolite levels were associated with incident CVD in CKD patients. With this knowledge, this current study intends to prove that tryptophan catabolism is disproportionately upregulated in atherosclerotic lesions of CKD patients. Plasma and aortic tissue of CKD patients varying in CKD stage will be matched with CVD patients with normal renal function with the objective of finding the disproportionate tryptophan catabolism in atherosclerotic lesions. Aortic tissue will be homogenized and both plasma and tissue lysates will be extracted for tryptophan metabolites using organic solvents. We will use Liquid Chromatography Mass Spectrometry to measure a panel of tryptophan catabolites from these extracts. We expect to find significant differences in KP metabolites in atherosclerotic lesions compared to controls, and correlate lesion KP metabolites to circulating KP metabolites and further prove the strength of using KP metabolites as prospective measures for detecting CVD in CKD patients.

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The Effects of Radiation on Porcine Submandibular Glands

Roughly 600,000+ cases of head and neck cancer are diagnosed annually with the majority of these patients being treated with therapeutic irradiation (IR). Unfortunately, IR often causes irreversible salivary gland (SG) damage, hyposalivation, and permanent xerostomia (dry mouth syndrome). A lack of saliva negatively impacts the oral cavity by increasing tooth decay and infections, as well as impairing swallowing, speech, and sense of taste. To address the underlying mechanisms causing SG dysfunction, and to ultimately bring new therapies to treat this condition to the clinic, preclinical test models are needed. Unlike small rodents, minipigs serve as an ideal model as they are more closely related to humans based on the anatomy and location of the SGs in the head and neck area. Most pig models focus solely on the parotid gland and do not include the SMG. As both glands can be affected by radiation and may require repair, we applied two different radiation doses and evaluated the submandibular glands (SMGs) for morphological damage using immunohistochemistry and immunofluorescence staining. Our overall goals are to determine which radiation dose most closely mimics the damage observed in human studies and to establish a preclinical minipig model for xerostomia that affects the SMG.

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Dysfunction of insulin producing pancreatic beta cells – The Central Problem in Diabetes

This lab and experience over the past school year has involved two separate components. The first component was in a wet lab doing actual work. The work I was doing was genotyping different mice and their offspring to test for genetic mutations. This was done through a tail snip being taken from the mice and digested to release the DNA. The DNA is then placed in a polymerase chain reaction (PCR) to replicate the DNA strand. The results of this PCR were then ran through a Gel electrophoresis system in order to measure the base pair lengths of genes being investigated. This in person lab research coincides with the auxiliary research I was doing. I was told to investigate how Beta cells measure the glucose level of blood and release the correct corresponding amount of insulin. This knowledge can then be used to see if certain genetic mutations in different mice result in differing insulin production or even a stop of insulin production.

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Developing a Liquid Biopsy Diagnostic Technique for Head and Neck Squamous Cell Carcinoma

Head and Neck Squamous Cell Carcinoma (HNSCC) is the sixth most common cancer in the United States and has one of the highest recurrence rates. The cancer is frequently caught late, especially in recurring cases, as most diagnostic techniques are highly invasive. Research was conducted to develop a liquid biopsy technique which would use circulating tumor (ct)DNA, also known as cell-free DNA, to track cancer markers in the blood. This technique could be used as both a prognostic and diagnostic technique for patients with HNSCC or those who have a chance of recurrence. We have had success using cell-free DNA extraction procedures to separate the ctDNA from patient blood samples. Now we are looking towards developing a diagnostic technique using this data. This technique would be incredibly useful for monitoring HNSCC patients’ responses to treatment because it would be fast and non-invasive. Particularly, the research is currently focused on HPV positive patients because the HPV ctNDA marker can be easily identified in patient blood. The liquid biopsy technique could also be extended and used for the detection of other types of cancers. This could significantly improve cancer diagnosis times and would help provide frequent and non-invasive tracking of the responses of cancer patients to treatments.

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Comprehensive Cataloguing of Clinically Identified MUTYH Variants in Cancer Patients

Grace Clark Pronouns: she.her Research Mentor(s): Shelby Hemker, Postdoctoral Fellow Research Mentor School/College/Department: Human Genetics, Michigan Medicine Presentation Date: Thursday, April 22, 2021 Session: Session 5 (3pm-3:50pm) Breakout Room: Room 7 Presenter: 8 Event Link Abstract For privacy concerns this abstract cannot be published at this time. Authors: Grace Clark, Shelby Hemker, Jacob Kitzman Research

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Residue Depth Computation Project

Proteins, a class of macromolecules essential to biological processes, are characterized by their structure which directly correlates to functionality. Residues are considered the building blocks of proteins and studying their positions has been crucial in understanding the role a protein plays in a biological system. This research project investigates different measures of residue depth through calculations of RSA, DPX, Residue Depth, HalfSpace Depth, and L1 depth. The L1 depth function surpasses other residue structure predictors in that it can obtain positions of residues buried under the protein surface, or nested in pockets. In addition, the function uses O(N) time complexity, making it much more efficient than the HalfSpace predictor. Values of depth have strong correlations with properties such as physiochemical propensities, flexibility and polarity. Data was obtained from CULLPDB, Phospho3D, and PLB datasets. After reading in necessary information into an IDE, residue depth of each protein in the datasets and the correlation coefficients between the means of depth values of amino acids and hydrophobicity index of amino acids were calculated through an algorithm written in C++. These results showed that the means of depth values were strongly relative with hydrophobicity of amino acids. In addition, the secondary structures of the residues are also associated with L1 depth values, as residues in sheets are deeper under the surface in comparison to residues in coils and helices.

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The importance of the interface in predict protein-protein interactions

Protein-protein interactions (PPIs) are physical contacts between two or more protein molecules. The field of structural homology-based PPI prediction, has generally accepted that the interface region of the complex structure matters more than the global structure of proteins in predicting PPIs, although our preliminary data suggests otherwise. A study was undertaken to investigate the influence of the protein interface in predicting PPIs, using a tweaked version of TMalign. This edited version of the algorithm allows a weighting factor to be applied to specific residues, the interface residues, in these experiments. This study consists of experiments using different weighting values, each of which will be done on three sets of query data. The three data sets are: 1. pairs of proteins that are known to have positive interactions, 2. pairs of proteins that are said to not interact with one another, and 3. a randomized data set. The latter two will allow us to confirm the results of non-interactions. Once each query protein is aligned to the structural homologs in the database, the score can be calculated and then all scores will be sorted to determine the cutoff for classifying predicted positive interactions. The results allow us to determine how impactful the interface is in predicting whether two given proteins will interact or not. Additionally, it will either confirm or deny the long standing assumption that only the interface matters.

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Neutrophil depletion’s effect on lung cancer

Lung cancer remains the leading cause of cancer-related deaths worldwide, with non-small cell lung cancer (NSCLC) making up 85% of lung cancers. NSCLC is comprised of adenocarcinomas and lung squamous cell carcinoma and develops primarily in individuals over the age of 55 who regularly smoke. Current research on the tumor microenvironment revealed that neutrophils, a type of white blood cell responsible for fighting infections, actually aids tumor progression by allowing the creation of chemotaxis that promote tumor metastasis. Additionally, current immunotherapies are only 30% effective. This study looks specifically at how neutrophils affect the tumor microenvironment (TME). We hypothesized that if neutrophils depleted in mice with adenocarcinoma they would decrease in tumor burden, as the chemotaxis transport mechanism for cancer cells would be gone. We have established a murine model of lung cancer, wherein expression of oncogenic Kras and p53 can be controlled genetically, allowing activation of oncogenic Kras to initiate tumor growth, tumor eradication upon Kras depletion and re-activation as a means to model relapse, and p53 speeds up tumor progression. Control mice were used alongside our cancer inducible mice, to test the effects of neutrophil depletion. Half of the mice were given the antibody IgG that has no effect on neutrophil depletion while GR-1, a neutrophil depleted antibody was given to the other half. After 4-week treatment, we took lung tissue; paraffin embedded it and stained it with HE. Tumors were counted and the subsequent analysis revealed 1) Mice with both Kras and p53 on have more tumors than those with just Kras on 2) Neutrophil depletion resulted in lower tumor counts for mice. In summary, neutrophils play likely a tumor-promoting role in lung cancer. Depletion of neutrophils by antibodies resulted in a decrease in tumor burden suggesting new treatment option for lung cancer patients by modulating TME.

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Quantifying Gene Regulation in HNSCC

My project focuses on developing precision medicine for head and neck squamous cell carcinoma (HNSCC). Many HNSCC tumors are caused by human papilloma virus (HPV) infection. E7, an HPV protein, has proven to occasionally change the expression of certain genes in HPV positive tumors. My project aims to analyze RNA expression patterns to determine what triggers HPV-mediated gene regulation. We collect RNA from patient-derived cell lines and generate a complimentary DNA (cDNA) sample. We then use the process of qPCR to replicate the cDNA and measure the CT value. This value quantifies RNA expression where a low CT value implies higher amounts of RNA in the original sample meaning increased transcription of our gene of interest. Finally, we will use a script written in R Code to create a summary table of qPCR data along with a graph of CT values. We have already generated, and verified using qPCR, cell lines that express HPV genes. We expect that the expression of the HPV E7 gene will decrease the expression of the HLAA, HLAB, and HLAC genes, all of which are needed for an antiviral and anti-tumor immune response. By measuring the effect HPV genes have on the transcription of immune response genes, we will be able to understand the mechanism by which HPV evades the immune system. As of now, treatments for HNSCC are similar to those for the majority of cancer types. This research will help develop treatment tailored to HNSCC which can hopefully improve recovery for afflicted patients.

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Dysfunction of insulin producing pancreatic beta cells – The Central Problem in Diabetes

Syed Mustafa Pronouns: He/Him Research Mentor(s): Mehboob Hussain, Professor Research Mentor School/College/Department: Internal Medicine, Metabolism, Endocrinology, Diabetes, Michigan Medicine Presentation Date: Thursday, April 22, 2021 Session: Session 5 (3pm-3:50pm) Breakout Room: Room 12 Presenter: 2 Event Link Abstract Authors: Syed Mustafa Research Method: Laboratory Research with Animals

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