Biology subjects

Mason, C. E.

Publications and source records attributed to Mason, C. E..

4 recordsLinked to original sources

bioRxiv2018

Ozone Treatment for Elimination of Bacteria in Medical Environments

Pathogenic bacteria and viruses in medical environments can lead to treatment complications and hospital-acquired infections (HAIs), and current cleaning protocols do not address hard-to-access areas or that may be beyond line-of-sight treatment such as with ultraviolet radiation. At the time of writing, the ongoing pandemic of the novel coronavirus known as novel coronavirus (2019-nCoV) has claimed over 4 million cases worldwide and is expected to have multiple peaks, with possible resurgences throughout 2020. It is therefore imperative that disinfection methods in the meantime be employed to keep up with the supply of personal protective equipment (PPE) and sterilize a wide array of surfaces as quarantine lockdowns begin to be lifted. Here, we tested the efficacy of Sani Sport ozone devices as a means to treat hospital equipment and surfaces for killing bacteria, degrading synthetic severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA, and RNA from non-replicative capsid enclosed SARS-CoV-2. We observed a rapid killing of medically-relevant and environmental bacteria (Escherichia coli, Enterococcus faecalis, Bacillus subtlis, and Deinococcus radiodurans) across four surfaces (blankets, catheter, remotes, and syringes) within 30 minutes, and up to a 99% reduction in viable bacteria at the end of 2-hour treatment cycles. Significant RNA degradation of synthetic SARS-CoV-2 RNA was seen an hour into the ozone treatment as compared to non-treated controls and a non-replicative form of the virus was shown to have significant RNA degradation at 30 minutes compared to a no treatment control and RNA degradation could be reliably detected at 10,000 and 1,000 copies of virus per sample. These results show the strong promise of ozone treatment for reducing risk of infection and HAIs.

microbiology↗

bioRxiv2018

Best Practices for Benchmarking Germline Small Variant Calls in Human Genomes

Assessing accuracy of NGS variant calling is immensely facilitated by a robust benchmarking strategy and tools to carry it out in a standard way. Benchmarking variant calls requires careful attention to definitions of performance metrics, sophisticated comparison approaches, and stratification by variant type and genome context. The Global Alliance for Genomics and Health (GA4GH) Benchmarking Team has developed standardized performance metrics and tools for benchmarking germline small variant calls. This team includes representatives from sequencing technology developers, government agencies, academic bioinformatics researchers, clinical laboratories, and commercial technology and bioinformatics developers for whom benchmarking variant calls is essential to their work. Benchmarking variant calls is a challenging problem for many reasons:\n\nO_LIEvaluating variant calls requires complex matching algorithms and standardized counting because the same variant may be represented differently in truth and query callsets.\nC_LIO_LIDefining and interpreting resulting metrics such as precision (aka positive predictive value = TP/(TP+FP)) and recall (aka sensitivity = TP/(TP+FN)) requires standardization to draw robust conclusions about comparative performance for different variant calling methods.\nC_LIO_LIPerformance of NGS methods can vary depending on variant types and genome context; and as a result understanding performance requires meaningful stratification.\nC_LIO_LIHigh-confidence variant calls and regions that can be used as \"truth\" to accurately identify false positives and negatives are difficult to define, and reliable calls for the most challenging regions and variants remain out of reach.\nC_LI\n\nWe have made significant progress on standardizing comparison methods, metric definitions and reporting, as well as developing and using truth sets. Our methods are publicly available on GitHub (https://github.com/ga4gh/benchmarking-tools) and in a web-based app on precisionFDA, which allow users to compare their variant calls against truth sets and to obtain a standardized report on their variant calling performance. Our methods have been piloted in the precisionFDA variant calling challenges to identify the best-in-class variant calling methods within high-confidence regions. Finally, we recommend a set of best practices for using our tools and critically evaluating the results.

genomics↗

bioRxiv2017

Nanopore detection of bacterial DNA base modifications

The common bacterial base modification N6-methyladenine (m6A) is involved in many pathways related to an organisms ability to survive and interact with its environment. Recent research has shown that nanopore sequencing can detect m5C with per-read accuracy of upwards of 80% but m6A with significantly lower accuracy. Here we use a binary classifier to improve m6A classification by marking adenines as methylated or unmethylated based on differences between measured and expected current values as each adenine travels through the nanopore. We also illustrate the importance of read quality for base modification detection and compare to PacBio methylation calls. With recent demonstrations of nanopore sequencing in Antarctica and onboard the International Space Station, the ability to reliably characterize m6A presents an opportunity to further examine the role of methylation in bacterial adaptation to extreme or very remote environments.

genomics↗

bioRxiv2017

Rahu Is A Mutant Allele Of Dnmt3c, Encoding A DNA Methyltransferase Required For Meiosis And Transposon Repression In The Mouse Male Germline

Transcriptional silencing by heritable cytosine-5 methylation is an ancient strategy to repress transposable elements. It was previously thought that mammals possess four DNA methyltransferase paralogs--Dnmt1, Dnmt3a, Dnmt3b and Dnmt3l--that establish and maintain cytosine-5 methylation. Here we identify a fifth paralog, Dnmt3c, that is essential for retrotransposon methylation and repression in the mouse male germline. From a phenotype-based forward genetics screen, we isolated a mutant mouse called rahu, which displays severe defects in double-strand-break repair and homologous chromosome synapsis during male meiosis, resulting in sterility. rahu is an allele of a transcription unit (Gm14490, renamed Dnmt3c) that was previously mis-annotated as a Dnmt3-family pseudogene. Dnmt3c encodes a cytosine methyltransferase homolog, and Dnmt3crahu mutants harbor a non-synonymous mutation of a conserved residue within one of its cytosine methyltransferase motifs, similar to a mutation in human DNMT3B observed in patients with immunodeficiency, centromeric instability and facial anomalies syndrome. The rahu mutation lies at a potential dimerization interface and near the potential DNA binding interface, suggesting that it compromises protein-protein and/or protein-DNA interactions required for normal DNMT3C function in vivo. Dnmt3crahu mutant males fail to establish normal methylation within LINE and LTR retrotransposon sequences in the germline and accumulate higher levels of transposon-derived transcripts and proteins, particularly from distinct L1 and ERVK retrotransposon families. Phylogenetic analysis indicates that Dnmt3c arose during rodent evolution by tandem duplication of Dnmt3b, after the divergence of the Dipodoidea and Muroidea superfamilies. These findings provide insight into the evolutionary dynamics and functional specialization of the transposon suppression machinery critical for mammalian sexual reproduction and epigenetic regulation.

genetics↗