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- All Subjects: Biochemistry
- All Subjects: Infectious Diseases
Description
The influenza virus, also known as "the flu", is an infectious disease that has constantly affected the health of humanity. There is currently no known cure for Influenza. The Center for Innovations in Medicine at the Biodesign Institute located on campus at Arizona State University has been developing synbodies as a possible Influenza therapeutic. Specifically, at CIM, we have attempted to design these initial synbodies to target the entire Influenza virus and preliminary data leads us to believe that these synbodies target Nucleoprotein (NP). Given that the synbody targets NP, the penetration of cells via synbody should also occur. Then by Western Blot analysis we evaluated for the diminution of NP level in treated cells versus untreated cells. The focus of my honors thesis is to explore how synthetic antibodies can potentially inhibit replication of the Influenza (H1N1) A/Puerto Rico/8/34 strain so that a therapeutic can be developed. A high affinity synbody for Influenza can be utilized to test for inhibition of Influenza as shown by preliminary data. The 5-5-3819 synthetic antibody's internalization in live cells was visualized with Madin-Darby Kidney Cells under a Confocal Microscope. Then by Western Blot analysis we evaluated for the diminution of NP level in treated cells versus untreated cells. Expression of NP over 8 hours time was analyzed via Western Blot Analysis, which showed NP accumulation was retarded in synbody treated cells. The data obtained from my honors thesis and preliminary data provided suggest that the synthetic antibody penetrates live cells and targets NP. The results of my thesis presents valuable information that can be utilized by other researchers so that future experiments can be performed, eventually leading to the creation of a more effective therapeutic for influenza.
ContributorsHayden, Joel James (Author) / Diehnelt, Chris (Thesis director) / Johnston, Stephen (Committee member) / Legutki, Bart (Committee member) / Barrett, The Honors College (Contributor) / Department of Psychology (Contributor) / Department of Chemistry and Biochemistry (Contributor)
Created2014-05
Description
The devastating 2014 Ebola virus outbreak in Western Africa demonstrated the lack of therapeutic approaches available for the virus. Although monoclonal antibodies (mAb) and other molecules have been developed that bind the virus, no therapeutic has shown the efficacy needed for FDA approval. Here, a library of 50 peptide based ligands that bind the glycoprotein of the Zaire Ebola virus (GP) were developed. Using whole virus screening of vesicular stomatitis virus pseudotyped with GP, low affinity peptides were identified for ligand construction. In depth analysis showed that two of the peptide based molecules bound the Zaire GP with <100 nM KD. One of these two ligands was blocked by a known neutralizing mAb, 2G4, and showed cross-reactivity to the Sudan GP. This work presents ligands with promise for therapeutic applications across multiple variants of the Ebola virus.
ContributorsRabinowitz, Joshua Avraam (Author) / Diehnelt, Chris (Thesis director) / Johnston, Stephen (Committee member) / School of Molecular Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2016-12
Description
Predicting the binding sites of proteins has historically relied on the determination of protein structural data. However, the ability to utilize binding data obtained from a simple assay and computationally make the same predictions using only sequence information would be more efficient, both in time and resources. The purpose of this study was to evaluate the effectiveness of an algorithm developed to predict regions of high-binding on proteins as it applies to determining the regions of interaction between binding partners. This approach was applied to tumor necrosis factor alpha (TNFα), its receptor TNFR2, programmed cell death protein-1 (PD-1), and one of its ligand PD-L1. The algorithms applied accurately predicted the binding region between TNFα and TNFR2 in which the interacting residues are sequential on TNFα, however failed to predict discontinuous regions of binding as accurately. The interface of PD-1 and PD-L1 contained continuous residues interacting with each other, however this region was predicted to bind weaker than the regions on the external portions of the molecules. Limitations of this approach include use of a linear search window (resulting in inability to predict discontinuous binding residues), and the use of proteins with unnaturally exposed regions, in the case of PD-1 and PD-L1 (resulting in observed interactions which would not occur normally). However, this method was overall very effective in utilizing the available information to make accurate predictions. The use of the microarray to obtain binding information and a computer algorithm to analyze is a versatile tool capable of being adapted to refine accuracy.
ContributorsBrooks, Meilia Catherine (Author) / Woodbury, Neal (Thesis director) / Diehnelt, Chris (Committee member) / Ghirlanda, Giovanna (Committee member) / Department of Psychology (Contributor) / School of Molecular Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
Description
Advancements in both the medical field and public health have substantially minimized the detrimental impact of infectious diseases. Health education and disease prevention remains a vital tool to maintain and propagate this success. In order to determine the relationship between knowledge of disease and reported preventative behavior 180 participants amongst the ASU student population were surveyed about their knowledge and prevention behavior for 10 infectious diseases. Of the 180 participants only 138 were completed surveys and used for analysis. No correlation was found between knowledge or perceived risk and preventative measures within the total sample of 138 respondents, however there was a correlation found within Lyme disease and Giardia exposure to information and prevention. Additionally, a cultural consensus analysis was used to compare the data of 17 US-born and 17 foreign-born participants to analyze patterns of variation and agreement on disease education based on national origins. Cultural consensus analysis showed a strong model of agreement among all participants as well as within the US-born and foreign-born student groups. There was a model of agreement within the questions pertaining to transmission and symptoms. There was not however a model of agreement within treatment questions. The findings suggest that accurate knowledge on infectious diseases may be less impactful on preventative behavior than social expectations.
ContributorsVernon, Samantha (Author) / Maupin, Jonathan (Thesis director) / Jehn, Megan (Committee member) / Barrett, The Honors College (Contributor) / School of Human Evolution and Social Change (Contributor)
Created2018-05
Description
Extensive efforts have been made to develop efficient and low-cost methods for diagnostics to identify molecular biomarkers that are linked to a wide array of conditions, including cancer. A highly developed method includes utilizing the gene-editing enzyme CRISPR-Cas12a (Cpf1), which demonstrates double-stranded DNase activity with RuvC catalytic domain with high sensitivity and specificity. This DNase activity is RNA-guided and requires a T-rich PAM site on the target sequence for functional cleavage. There have been recent efforts to utilize this DNase activity of Cas12a by combining it with isothermal amplification and analysis by lateral strip tests. This project examined CRISPR-based early detection of microRNA biomarkers. MicroRNA are short RNA molecules that have large roles in post-transcriptional gene regulation. However, due the short length of microRNA and its single-stranded nature, it is challenging to use Cas12a for microRNA detection using existing methods. Thus, this project investigated the potential of two microRNA detection strategies for recognition by CRISPR-Cas12a. These methods were microRNA-splinted ligation with polymerase chain reaction (PCR) and MicroRNA-specific reverse transcriptase PCR (RT-PCR). Gel imaging demonstrated effective amplification of ligated DNA through microRNA-splinted ligation with PCR/RPA. In addition, lateral strips tests showed effective cleavage of the target sequences by Cas12a. However, RT-PCR method demonstrated low amplification by PCR and inefficient poly(A) elongation. This project paves the way for the detection of an extensive range of microRNA biomarkers that are linked to an array of diseases. Future directions include analysis and modifications of RT-PCR method to improve experimental results, extending these detection methods to a larger range of microRNA sequences, and eventually utilizing them for detection in human samples.
ContributorsStaren, Michael Steven (Author) / Green, Alexander (Thesis director) / Stephanopoulos, Nicholas (Committee member) / Diehnelt, Chris (Committee member) / School of Life Sciences (Contributor) / College of Health Solutions (Contributor) / Barrett, The Honors College (Contributor)
Created2019-05
Description
Currently, treatment for multiple myeloma (MM), a hematological cancer, is limited to post-symptomatic chemotherapy combined with other pharmaceuticals and steroids. Even so, the immuno-depressing cancer can continue to proliferate, leading to a median survival period of two to five years. B cells in the bone marrow are responsible for generating antigen-specific antibodies, but in MM the B cells express mutated, non-specific monoclonal antibodies. Therefore, it is hypothesized that antibody-based assay and therapy may be feasible for detecting and treating the disease. In this project, 330k peptide microarrays were used to ascertain the binding affinity of sera antibodies for MM patients with random sequence peptides; these results were then contrasted with normal donor assays to determine the "immunosignatures" for MM. From this data, high-binding peptides with target-specificity (high fluorescent intensity for one patient, low in all other patients and normal donors) were selected for two MM patients. These peptides were narrowed down to two lists of five (10 total peptides) to analyze in a synthetic antibody study. The rationale behind this originates from the idea that antibodies present specific binding sites on either of their branches, thus relating high binding peptides from the arrays to potential binding targets of the monoclonal antibodies. Furthermore, these peptides may be synthesized on a synthetic antibody scaffold with the potential to induce targeted delivery of radioactive or chemotherapeutic molecular tags to only myelomic B cells. If successful, this would provide a novel alternative to current treatments that is less invasive, has fewer side effects, more specifically targets the cause of MM, and reliably diagnoses the cancer in the presymptomatic stage.
ContributorsBerry, Jameson (Co-author) / Buelt, Allison (Co-author) / Johnston, Stephen (Thesis director) / Diehnelt, Chris (Committee member) / School of Molecular Sciences (Contributor) / School of International Letters and Cultures (Contributor) / Division of Teacher Preparation (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
Description
The field of biomedical research relies on the knowledge of binding interactions between various proteins of interest to create novel molecular targets for therapeutic purposes. While many of these interactions remain a mystery, knowledge of these properties and interactions could have significant medical applications in terms of understanding cell signaling and immunological defenses. Furthermore, there is evidence that machine learning and peptide microarrays can be used to make reliable predictions of where proteins could interact with each other without the definitive knowledge of the interactions. In this case, a neural network was used to predict the unknown binding interactions of TNFR2 onto LT-ɑ and TRAF2, and PD-L1 onto CD80, based off of the binding data from a sampling of protein-peptide interactions on a microarray. The accuracy and reliability of these predictions would rely on future research to confirm the interactions of these proteins, but the knowledge from these methods and predictions could have a future impact with regards to rational and structure-based drug design.
ContributorsPoweleit, Andrew Michael (Author) / Woodbury, Neal (Thesis director) / Diehnelt, Chris (Committee member) / Chiu, Po-Lin (Committee member) / School of Molecular Sciences (Contributor, Contributor) / Barrett, The Honors College (Contributor)
Created2021-05