Biology subjects

Chemparathy, A.

Publications and source records attributed to Chemparathy, A..

3 recordsLinked to original sources

bioRxiv2020

Development of CRISPR as a prophylactic strategy to combat novel coronavirus and influenza

The outbreak of the coronavirus disease 2019 (COVID-19), caused by the Severe Acute Respiratory Syndrome coronavirus 2 (SARS-CoV-2), has infected more than 100,000 people worldwide with over 3,000 deaths since December 2019. There is no cure for COVID-19 and the vaccine development is estimated to require 12-18 months. Here we demonstrate a CRISPR-Cas13-based strategy, PAC-MAN (Prophylactic Antiviral CRISPR in huMAN cells), for viral inhibition that can effectively degrade SARS-CoV-2 sequences and live influenza A virus (IAV) genome in human lung epithelial cells. We designed and screened a group of CRISPR RNAs (crRNAs) targeting conserved viral regions and identified functional crRNAs for cleaving SARS-CoV-2. The approach is effective in reducing respiratory cell viral replication for H1N1 IAV. Our bioinformatic analysis showed a group of only six crRNAs can target more than 90% of all coronaviruses. The PAC-MAN approach is potentially a rapidly implementable pan-coronavirus strategy to deal with emerging pandemic strains.

bioengineering↗

bioRxiv2020

An overview of the quality assurance and quality control of magnetic resonance imaging data for the Ontario Neurodegenerative Disease Research Initiative (ONDRI): pipeline development and neuroinformatics

Large scale research studies combining magnetic resonance imaging data generated at multiple sites on multiple vendor platforms are becoming more commonplace. The Ontario Neurodegenerative Disease Research Initiative (ONDRI - http://ondri.ca/), a project funded by the Ontario Brain Institute (OBI), is a recently established province-wide natural history study, which has recruited more than 500 participants from neurodegenerative disease groups including amyotrophic lateral sclerosis, fronto-temporal dementia, Parkinsons disease, Alzheimers disease, mild cognitive impairment, and cerebrovascular disease (previously referred to as the vascular cognitive impairment cohort). Because of its multi-site nature, all captured data must be standardized and meet minimum quality standards to reduce variability. The goal of the ONDRI imaging platform is to maximize data quality by implementing vendor-specific harmonized MR imaging protocols (consistent with the Canadi-an Dementia Imaging Protocol - http://www.cdip-pcid.ca/), monitoring protocol adherence, qualitatively assessing image quality, measuring signal-to-noise and contrast-to-noise, monitoring system stability, and applying corrections based on the analysis of images from two different phantoms regularly acquired at each site. To maximize image quality, this work describes the use of various automatic pipelines and manual assessment steps, integrated within an established informatics and databasing platform, the Stroke Patient Recovery Research Database (SPReD) built on the Extensible Neuroimaging Archive Toolkit (XNAT), and contained within the Brain-CODE (Centre for Ontario Data Exploration) framework. The purpose of the current paper is to describe the steps undertaken by ONDRI to achieve this high standard of data integrity. Data have been successfully collected for the past 4 years with the pipelines and assessments identifying deviations, allowing for timely interventions and assessment of image quality.

neuroscience↗

bioRxiv2019

Uncovering patterns of atomic interactions in static and dynamic structures of proteins

The number of structures and molecular dynamics simulations of proteins is exploding owing to dramatic advances in cryo-electron microscopy, crystallography, and computing. One of the most powerful ways to analyze structural information involves comparisons of interatomic interactions across different structures or simulations of the same protein or related proteins from the same family (e.g. different GPCRs). Such comparative analyses are of interest to a wide range of researchers but currently prove challenging for all but a few. To facilitate comparative structural analyses, we have developed tools for (i) rapidly computing and comparing interatomic interactions and (ii) interactively visualizing interactions to enable structure-based interpretations. Using these tools, we have developed the Contact Comparison Atlas, a web-based resource for the comparative analysis of interactions in structures and simulations of proteins. Using the Contact Comparison Atlas and our tools, we have identified patterns of interactions with functional implications in structures of G-protein-coupled receptors, G proteins and kinases and in the dynamics of muscarinic receptors. The Contact Comparison Atlas can be used to enable structure modeling, drug discovery, protein engineering, and the prediction of disease-associated mutations. Contact Comparison Atlas website: https://getcontacts.github.io/atlas/

biophysics↗