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Optimizing Recombinant Protein Production for Domain Antibodies: Proof-of-Concept

Description

Recent studies in traumatic brain injury (TBI) have found a temporal window where therapeutics on the nanometer scale can cross the blood-brain barrier and enter the parenchyma. Developing protein-based therapeutics is attractive for a number of reasons, yet, the production

Recent studies in traumatic brain injury (TBI) have found a temporal window where therapeutics on the nanometer scale can cross the blood-brain barrier and enter the parenchyma. Developing protein-based therapeutics is attractive for a number of reasons, yet, the production pipeline for high yield and consistent bioactive recombinant proteins remains a major obstacle. Previous studies for recombinant protein production has utilized gram-negative hosts such as Escherichia coli (E. coli) due to its well-established genetics and fast growth for recombinant protein production. However, using gram-negative hosts require lysis that calls for additional optimization and also introduces endotoxins and proteases that contribute to protein degradation. This project directly addressed this issue and evaluated the potential to use a gram-positive host such as Brevibacillus choshinensis (Brevi) which does not require lysis as the proteins are expressed directly into the supernatant. This host was utilized to produce variants of Stock 11 (S11) protein as a proof-of-concept towards this methodology. Variants of S11 were synthesized using different restriction enzymes which will alter the location of protein tags that may affect production or purification. Factors such as incubation time, incubation temperature, and media were optimized for each variant of S11 using a robust design of experiments. All variants of S11 were grown using optimized parameters prior to purification via affinity chromatography. Results showed the efficiency of using Brevi as a potential host for domain antibody production in the Stabenfeldt lab. Future aims will focus on troubleshooting the purification process to optimize the protein production pipeline.

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2019-05

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Discovering factors that drive the migration of immune cells to malignant pleural mesothelioma tumors

Description

Malignant Pleural Mesothelioma (MPM) is an aggressive deadly tumor that has few therapeutic options. Immunotherapies have shown great potential in alleviating MPM patient symptoms. Using patient data from the Cancer Genome Atlas (TCGA) we sought to identify mutations, regulators, and

Malignant Pleural Mesothelioma (MPM) is an aggressive deadly tumor that has few therapeutic options. Immunotherapies have shown great potential in alleviating MPM patient symptoms. Using patient data from the Cancer Genome Atlas (TCGA) we sought to identify mutations, regulators, and immune factors driving immune cell migration. We explored computational methods to define regulatory causal flows in order to make biological predictions. These predictions were verified by cross-referencing peer-reviewed articles. A disease-relevant inference model was developed to examine the chemokine IL-18’s effect on natural killer cell (NK cell) migration.

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Date Created
2020-05

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Characterizing Primary Mesothelioma Cell Lines by Exome Sequencing

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Malignant Pleural Mesothelioma is a type of lung cancer usually discovered at an advanced stage at which point there is no cure. Six primary MPM cell lines were used to conduct in vitro research to make conclusions about specific gene

Malignant Pleural Mesothelioma is a type of lung cancer usually discovered at an advanced stage at which point there is no cure. Six primary MPM cell lines were used to conduct in vitro research to make conclusions about specific gene mutations associated with Mesothelioma. DNA exome sequencing, a time efficient and inexpensive technique, was used for identifying specific DNA mutations. Computational analysis of exome sequencing data was used to make conclusions about copy number variation among common MPM genes. Results show a CDKN2A gene heterozygous deletion in Meso24 cell line. This data is validated by a previous CRISPR-Cas9 outgrowth screen for Meso24 where the knocked-out gene caused increased Meso24 growth.

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Date Created
2020-05

SRC dependent EGFRvIII-STAT5 activation drives resistance of glioblastoma cells

Description

Glioblastoma (GBM) is the most lethal primary brain tumor in adults with a less than 5% chance of survival beyond 5 years. With few effective therapies beyond the standard of care, there are often treatment resistant recurrences seen in most

Glioblastoma (GBM) is the most lethal primary brain tumor in adults with a less than 5% chance of survival beyond 5 years. With few effective therapies beyond the standard of care, there are often treatment resistant recurrences seen in most patients. STAT5 is a protein that has shown to be upregulated in highly invasive and treatment resistant GBM. Elucidating the role of STAT5 in GBM could reveal a node of therapeutic vulnerability in primary and recurrent GBM.

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Date Created
2022-05

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Applying Regulatory Networks to the Immune Landscape of Mesothelioma

Description

An immune regulatory network was constructed for the purpose of identifying target regulators in malignant pleural mesothelioma for therapies. An identified causal flow linked a mutation of D-dopachrome tautomerase to a heightened expression of regulator ASH1L and consequent down regulation

An immune regulatory network was constructed for the purpose of identifying target regulators in malignant pleural mesothelioma for therapies. An identified causal flow linked a mutation of D-dopachrome tautomerase to a heightened expression of regulator ASH1L and consequent down regulation of chemokine CCL5 and invasion of CD8+ T cells. Experimental validation of this initial use case indicates mRNA expression of CCL5 within the tumor cells and subsequent protein expression and secretion. Further analyses will explore the migration of CD8+ T cells in response to the chemotactic CCL5.

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Date Created
2022-05

panCanSYGNAL

Description

panCanSYGNAL is a web-application designed to allow cancer researchers to search the relationships between somatic mutations, regulators, and biclusters corresponding to many cancers using a Google-like searchable database.

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2022-05