CAVEMol: an immersive 3D molecule viewer

As the number of solved molecular structures deposited with the Protein Data Bank (PDB) increases, so too does the desire for more advanced ways of using this data. Traditional applications for viewing and manipulating molecular structures create a computer-generated model on a standard desktop computer screen. The display may employ some method of stereography to create the illusion of depth, but generally the user just sees a flat image. The user is able to interact with the molecule by magnifying it to see a particular area of interest, or by rotating it to see all sides of the molecule. The user may also be able to see animated changes in the molecule over time, or they may even be able to make modifications to the structure in real time. Regardless of the amount of control the user has over the molecule, however, one thing remains the same: the user experiences the molecule as though it were an object floating behind the monitor screen which they can indirectly control using a mouse or other pointing device. An immersive environment, on the other hand, provides a new paradigm for molecular visualization, allowing the user a much more realistic interaction with the molecule. The user becomes part of the viewing experience, traversing a molecule as though walking or flying within it. The molecule can completely surround them on all sides, giving them a true sense of the size and shape of the molecule in three dimensions. The user may also interact with the object directly, moving and rotating it with their hands rather than a mouse. This approach should prove particularly valuable for operations such as interactive docking, which allows a user to manipulate the interface between two molecules to identify favorable interaction sites. This thesis presents the design and implementation of CAVEMol, a molecular visualization application for immersive environments. I will also give an overview of molecular visualization and immersive environments, and then discuss future work that can be done in this area as well as applications where molecular visualization in an immersive environment can offer unique advantages

Reproducibly sampling SARS-CoV-2 genomes across time, geography, and viral diversity

The COVID-19 pandemic has led to a rapid accumulation of SARS-CoV-2 genomes, enabling genomic epidemiology on local and global scales. Collections of genomes from resources such as GISAID must be subsampled to enable computationally feasible phylogenetic and other analyses. We present genome-sampler, a software package that supports sampling collections of viral genomes across multiple axes including time of genome isolation, location of genome isolation, and viral diversity. The software is modular in design so that these or future sampling approaches can be applied independently and combined (or replaced with a random sampling approach) to facilitate custom workflows and benchmarking. genome-sampler is written as a QIIME 2 plugin, ensuring that its application is fully reproducible through QIIME 2’s unique retrospective data provenance tracking system. genome-sampler can be installed in a conda environment on macOS or Linux systems. A complete default pipeline is available through a Snakemake workflow, so subsampling can be achieved using a single command. genome-sampler is open source, free for all to use, and available at https://caporasolab.us/genome-sampler. We hope that this will facilitate SARS-CoV-2 research and support evaluation of viral genome sampling approaches for genomic epidemiology.ISSN:2046-140

Defining the Pandemic at the State Level: Sequence-Based Epidemiology of the SARS-CoV-2 virus by the Arizona COVID-19 Genomics Union (ACGU)

In December of 2019, a novel coronavirus, SARS-CoV-2, emerged in the city of Wuhan, China causing severe morbidity and mortality. Since then, the virus has swept across the globe causing millions of confirmed infections and hundreds of thousands of deaths. To better understand the nature of the pandemic and the introduction and spread of the virus in Arizona, we sequenced viral genomes from clinical samples tested at the TGen North Clinical Laboratory, provided to us by the Arizona Department of Health Services, and at Arizona State University and the University of Arizona, collected as part of community surveillance projects. Phylogenetic analysis of 79 genomes we generated from across Arizona revealed a minimum of 9 distinct introductions throughout February and March. We show that >80% of our sequences descend from clades that were initially circulating widely in Europe but have since dominated the outbreak in the United States. In addition, we show that the first reported case of community transmission in Arizona descended from the Washington state outbreak that was discovered in late February. Notably, none of the observed transmission clusters are epidemiologically linked to the original travel-related cases in the state, suggesting successful early isolation and quarantine. Finally, we use molecular clock analyses to demonstrate a lack of identifiable, widespread cryptic transmission in Arizona prior to the middle of February 2020

An Early Pandemic Analysis of SARS-CoV-2 Population Structure and Dynamics in Arizona

In December of 2019, a novel coronavirus, SARS-CoV-2, emerged in the city of Wuhan, China, causing severe morbidity and mortality. Since then, the virus has swept across the globe, causing millions of confirmed infections and hundreds of thousands of deaths. To better understand the nature of the pandemic and the introduction and spread of the virus in Arizona, we sequenced viral genomes from clinical samples tested at the TGen North Clinical Laboratory, the Arizona Department of Health Services, and those collected as part of community surveillance projects at Arizona State University and the University of Arizona. Phylogenetic analysis of 84 genomes from across Arizona revealed a minimum of 11 distinct introductions inferred to have occurred during February and March. We show that >80% of our sequences descend from strains that were initially circulating widely in Europe but have since dominated the outbreak in the United States. In addition, we show that the first reported case of community transmission in Arizona descended from the Washington state outbreak that was discovered in late February. Notably, none of the observed transmission clusters are epidemiologically linked to the original travel-related case in the state, suggesting successful early isolation and quarantine. Finally, we use molecular clock analyses to demonstrate a lack of identifiable, widespread cryptic transmission in Arizona prior to the middle of February 2020.IMPORTANCE As the COVID-19 pandemic swept across the United States, there was great differential impact on local and regional communities. One of the earliest and hardest hit regions was in New York, while at the same time Arizona (for example) had low incidence. That situation has changed dramatically, with Arizona now having the highest rate of disease increase in the country. Understanding the roots of the pandemic during the initial months is essential as the pandemic continues and reaches new heights. Genomic analysis and phylogenetic modeling of SARS-COV-2 in Arizona can help to reconstruct population composition and predict the earliest undetected introductions. This foundational work represents the basis for future analysis and understanding as the pandemic continues.Open access journalThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]