Investigation of Interactions between Rev and Microtubules: Purification of Wild-type and Mutant Rev Protein and Optimization of Microtubule Depolymerization Assays

As a logical pharmaceutical target for antiviral drugs, HIV-1 Rev is a regulatory protein essential for viral infection (Hope, 1999). The development of antiviral drugs that target Rev has been hindered by the lack of high-resolution structural information due to the protein\u27s tendency to aggregate in solution. While searching for solution conditions rendering Rev amenable to crystallographic analyses, Watts et al., (2000) discovered a novel in vitro interaction between Rev and microtubules (MTs) whereby addition of equimolar Rev and tubulin forms bilayered rings called Rev-tubulin toroidal complexes (RTTs). RTTs are similar to those seen when MTs are mixed with certain anti-MT drugs and KinI kinesins (Watts et al., 2000). Coupled with the sequence homology that exists between KinI kinesins and Rev, I hypothesize that Rev and KinI\u27s are depolymerizing MTs by a shared mechanism. This mechanism may include the binding of the Rev/KinI to the end of the MT inducing a curved confirmation in the MT thereby destabilizing it to promote depolymerization. I propose to test this hypothesis through measuring Rev-MT interactions by adapting biochemical and microscopy-based assays used to measure MT depolymerization by KinI proteins. These assays require microgram amounts of highly purified wild-type and mutant Rev proteins as well as purified tubulin from which MTs can be polymerized in vitro. To this end, I have purified wild type Rev with no visible contaminants on coomasie stained gels. Rev mutants R42A and E57A can also be purified with limited visible contaminants. However, the appropriate controls can be generated from non-expressing cells to address this issue. Rev mutants A37D and R39A can also be partially purified. Using purified Rev proteins, I then applied sedimentation assays to measure Rev-stimulated MT depolymerization. There was a statistically significant time dependence for wild type Rev to depolymerize MTs although there was no evidence for concentration dependence. Visual assays demonstrate no significant difference in the length of MTs treated with Rev although Rev decreased the number of MTs on the coverslip over time. This could contribute to the finding that MT depolymerization by Rev is time dependent. These results demonstrate that it is possible to measure Rev-MT interactions in vitro although it is clear that these assays are deficient in certain ways, including the ability of MTs to depolymerize on their own and RTTs potentially pelleting during the depolymerization assay. However, it is likely that cycling tubulin and/or using taxol to further stabilize the MTs can remedy the deficiency of MT depolymerization on their own. EM could also be used to determine if RTTs are pelleting during the depolymerization assay. After using mutant Rev proteins in the depolymerization and visual assays, it is the long-term goal that mechanistic information about Rev will lend valuable evidence to the study of KinI kinesins. Generating structural Rev information may also be helpful in the drug design of anti-mitotic peptides

QuickCut CNC Waterjet Cutter

This design project was dedicated to improving the existing design and making functional the QuickCut CNC Waterjet Cutter. The scope of work consisted of making the machine mobile and more structurally stable as well as programming the CNC controls. The project was started in the 2018/19 school year by a former mechanical engineering student. The subsystems consist of the frame, power, motor, water pump and associated plumbing, nozzle, abrasive feed system, x/y gantry, Arduino control system and the cutting bed. Unfortunately, due to the COVID-19 pandemic, the full scope was not able to be completed in its entirety

Comparison of Computational Models for Assessing Conservation of Gene Expression across Species

Assessing conservation/divergence of gene expression across species is important for the understanding of gene regulation evolution. Although advances in microarray technology have provided massive high-dimensional gene expression data, the analysis of such data is still challenging. To date, assessing cross-species conservation of gene expression using microarray data has been mainly based on comparison of expression patterns across corresponding tissues, or comparison of co-expression of a gene with a reference set of genes. Because direct and reliable high-throughput experimental data on conservation of gene expression are often unavailable, the assessment of these two computational models is very challenging and has not been reported yet. In this study, we compared one corresponding tissue based method and three co-expression based methods for assessing conservation of gene expression, in terms of their pair-wise agreements, using a frequently used human-mouse tissue expression dataset. We find that 1) the co-expression based methods are only moderately correlated with the corresponding tissue based methods, 2) the reliability of co-expression based methods is affected by the size of the reference ortholog set, and 3) the corresponding tissue based methods may lose some information for assessing conservation of gene expression. We suggest that the use of either of these two computational models to study the evolution of a gene's expression may be subject to great uncertainty, and the investigation of changes in both gene expression patterns over corresponding tissues and co-expression of the gene with other genes is necessary

A jackknife-like method for classification and uncertainty assessment of multi-category tumor samples using gene expression information

<p>Abstract</p> <p>Background</p> <p>The use of gene expression profiling for the classification of human cancer tumors has been widely investigated. Previous studies were successful in distinguishing several tumor types in binary problems. As there are over a hundred types of cancers, and potentially even more subtypes, it is essential to develop multi-category methodologies for molecular classification for any meaningful practical application.</p> <p>Results</p> <p>A jackknife-based supervised learning method called paired-samples test algorithm (PST), coupled with a binary classification model based on linear regression, was proposed and applied to two well known and challenging datasets consisting of 14 (GCM dataset) and 9 (NC160 dataset) tumor types. The results showed that the proposed method improved the prediction accuracy of the test samples for the GCM dataset, especially when t-statistic was used in the primary feature selection. For the NCI60 dataset, the application of PST improved prediction accuracy when the numbers of used genes were relatively small (100 or 200). These improvements made the binary classification method more robust to the gene selection mechanism and the size of genes to be used. The overall prediction accuracies were competitive in comparison to the most accurate results obtained by several previous studies on the same datasets and with other methods. Furthermore, the relative confidence R(T) provided a unique insight into the sources of the uncertainty shown in the statistical classification and the potential variants within the same tumor type.</p> <p>Conclusion</p> <p>We proposed a novel bagging method for the classification and uncertainty assessment of multi-category tumor samples using gene expression information. The strengths were demonstrated in the application to two bench datasets.</p

Comparison of Two Output-Coding Strategies for Multi-Class Tumor Classification Using Gene Expression Data and Latent Variable Model as Binary Classifier

Multi-class cancer classification based on microarray data is described. A generalized output-coding scheme based on One Versus One (OVO) combined with Latent Variable Model (LVM) is used. Results from the proposed One Versus One (OVO) outputcoding strategy is compared with the results obtained from the generalized One Versus All (OVA) method and their efficiencies of using them for multi-class tumor classification have been studied. This comparative study was done using two microarray gene expression data: Global Cancer Map (GCM) dataset and brain cancer (BC) dataset. Primary feature selection was based on fold change and penalized t-statistics. Evaluation was conducted with varying feature numbers. The OVO coding strategy worked quite well with the BC data, while both OVO and OVA results seemed to be similar for the GCM data. The selection of output coding methods for combining binary classifiers for multi-class tumor classification depends on the number of tumor types considered, the discrepancies between the tumor samples used for training as well as the heterogeneity of expression within the cancer subtypes used as training data

Benchmarking database systems for Genomic Selection implementation

Motivation: With high-throughput genotyping systems now available, it has become feasible to fully integrate genotyping information into breeding programs. To make use of this information effectively requires DNA extraction facilities and marker production facilities that can efficiently deploy the desired set of markers across samples with a rapid turnaround time that allows for selection before crosses needed to be made. In reality, breeders often have a short window of time to make decisions by the time they are able to collect all their phenotyping data and receive corresponding genotyping data. This presents a challenge to organize information and utilize it in downstream analyses to support decisions made by breeders. In order to implement genomic selection routinely as part of breeding programs, one would need an efficient genotyping data storage system. We selected and benchmarked six popular open-source data storage systems, including relational database management and columnar storage systems. Results: We found that data extract times are greatly influenced by the orientation in which genotype data is stored in a system. HDF5 consistently performed best, in part because it can more efficiently work with both orientations of the allele matrix

Integrated measurements of acoustical and optical thin layers I: Vertical scales of association

This study combined measurements from multiple platforms with acoustic instruments on moorings and on a ship and optics on a profiler and an autonomous underwater vehicle (AUV) to examine the relationships between fluorescent, bioluminescent, and acoustically scattering layers in Monterey Bay during nighttime hours in July and August of 2006 and May of 2008. We identified thin bioluminescent layers that were strongly correlated with acoustic scattering at the same depth but were part of vertically broad acoustic features, suggesting layers of unique composition inside larger biomass features. These compositional thin layers nested inside larger biomass features may be a common ecosystem component and are likely to have significant ecological impacts but are extremely difficult to identify as most approaches capable of the vertical scales of measurement necessary for the identification of sub-meter scale patterns assess bulk properties rather than specific layer composition. Measurements of multiple types of thin layers showed that the depth offset between thin phytoplankton and zooplankton layers was highly variable with some layers found at the same depth but others found up to 16 m apart. The vertical offset between phytoplankton and zooplankton thin layers was strongly predicted by the fraction of the water column fluorescence contained within a thin phytoplankton layer. Thin zooplankton layers were only vertically associated with thin phytoplankton layers when the phytoplankton in a layer accounted for more than about 18–20% of the water column chlorophyll. Trophic interactions were likely occurring between phytoplankton and zooplankton thin layers but phytoplankton thin layers were exploited by zooplankton only when they represented a large fraction of the available phytoplankton, suggesting zooplankton have some knowledge of the available food over the entire water column. The horizontal extent of phytoplankton layers, discussed in the second paper in this series, is likely an important factor contributing to this selective exploitation by zooplankton. The pattern of vertical offset between phytoplankton and zooplankton layers was consistent between studies in different years and using different combinations of platforms, indicating the importance of the relationship between zooplankton layers and the fraction of phytoplankton within a layer at night within Monterey Bay. These results highlight the value of integrating measurements of various types of organisms to understand thin layers processes and the importance of assessing ecological interactions in plankton thin layers within the context of the properties of the entire water column, like the animals themselves do

Pills and prayers: a comparative qualitative study of community conceptualisations of pre-eclampsia and pluralistic care in Ethiopia, Haiti and Zimbabwe.

BACKGROUND: Pre-eclampsia is a leading cause of preventable maternal and perinatal deaths globally. While health inequities remain stark, removing financial or structural barriers to care does not necessarily improve uptake of life-saving treatment. Building on existing literature elaborating the sociocultural contexts that shape behaviours around pregnancy and childbirth can identify nuanced influences relating to pre-eclampsia care. METHODS: We conducted a cross-cultural comparative study exploring lived experiences and understanding of pre-eclampsia in Ethiopia, Haiti and Zimbabwe. Our primary objective was to examine what local understandings of pre-eclampsia might be shared between these three under-resourced settings despite their considerable sociocultural differences. Between August 2018 and January 2020, we conducted 89 in-depth interviews with individuals and 17 focus group discussions (n = 106). We purposively sampled perinatal women, survivors of pre-eclampsia, families of deceased women, partners, older male and female decision-makers, traditional birth attendants, religious and traditional healers, community health workers and facility-based health professionals. Template analysis was conducted to facilitate cross-country comparison drawing on Social Learning Theory and the Health Belief Model. RESULTS: Survivors of pre-eclampsia spoke of their uncertainty regarding symptoms and diagnosis. A lack of shared language challenged coherence in interpretations of illness related to pre-eclampsia. Across settings, raised blood pressure in pregnancy was often attributed to psychosocial distress and dietary factors, and eclampsia linked to spiritual manifestations. Pluralistic care was driven by attribution of causes, social norms and expectations relating to alternative care and trust in biomedicine across all three settings. Divergence across the contexts centred around nuances in religious or traditional practices relating to maternal health and pregnancy. CONCLUSIONS: Engaging faith and traditional caregivers and the wider community offers opportunities to move towards coherent conceptualisations of pre-eclampsia, and hence greater access to potentially life-saving care