Alcohol-based Hand Sanitizers amid COVID-19: Chemical Formulation, Analysis, Safety.

Alcohol-based hand sanitizers (ABHSs) containing ethanol (EtOH) or isopropyl alcohol (IPA) to inactivate microorganisms help prevent the spread of respiratory diseases. These products have become very popular during the COVID-19 pandemic. Apart from vaccines or other preventative antiseptic measures, the majority of consumers have relied on different types of ABHSs to disinfect their hands. As a result, there has been a global rush in the demand for these ABHSs and other antiseptic hygiene products. This has resulted in the formation of many new commercial sanitizer producers. There are around fifty companies of varying sizes that have been marketing their ABHSs in Bangladesh, most of which have only been manufacturing their products for the first time since the COVID-19 pandemic. To monitor the quality and components of these products, the Bangladesh Council of Scientific and Industrial Research (BCSIR) analyzed approximately 200 different hand sanitizer samples using GC-FID method. All samples were alcohol-based except for 3 which were alcohol-free aqueous hand sanitizers. Of the supplied formulated ABHSs, 80 samples were found to contain only IPA and 54 contained only EtOH. However, 28 samples were found to be contaminated with methanol (MeOH), 7 samples contained only MeOH and 18 samples contained both EtOH and IPA. This is the first study to explore the analysis of alcohol content in formulated ABHSs and their marketing status in Bangladesh, but the findings could be of use in other jurisdictions as similar issues have been raised in many parts of the world.

VirusTaxo: Taxonomic classification of viruses from the genome sequence using k-mer enrichment.

Classification of viruses into their taxonomic ranks (e.g., order, family, and genus) provides a framework to organize an abundant population of viruses. Next-generation metagenomic sequencing technologies lead to a rapid increase in generating sequencing data of viruses which require bioinformatics tools to analyze the taxonomy. Many metagenomic taxonomy classifiers have been developed to study microbiomes, but it is particularly challenging to assign the taxonomy of diverse virus sequences and there is a growing need for dedicated methods to be developed that are optimized to classify virus sequences into their taxa. For taxonomic classification of viruses from metagenomic sequences, we developed VirusTaxo using diverse (e.g., 402 DNA and 280 RNA) genera of viruses. VirusTaxo has an average accuracy of 93% at genus level prediction in DNA and RNA viruses. VirusTaxo outperformed existing taxonomic classifiers of viruses where it assigned taxonomy of a larger fraction of metagenomic contigs compared to other methods. Benchmarking of VirusTaxo on a collection of SARS-CoV-2 sequencing libraries and metavirome datasets suggests that VirusTaxo can characterize virus taxonomy from highly diverse contigs and provide a reliable decision on the taxonomy of viruses.

Genome Sequences of Two Novel Coronavirus (SARS-CoV-2) Isolates from Dhaka, Bangladesh.

This study reports the genome sequences of two severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) strains detected in the nasopharyngeal swab specimens of two coronavirus disease 2019 (COVID-19) patients from Dhaka, Bangladesh.

Choice of assemblers has a critical impact on de novo assembly of SARS-CoV-2 genome and characterizing variants.

BACKGROUND: Coronavirus Disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has become a global pandemic following its initial emergence in China. SARS-CoV-2 has a positive-sense single-stranded RNA virus genome of around 30Kb. Using next-generation sequencing technologies, a large number of SARS-CoV-2 genomes are being sequenced at an unprecedented rate and being deposited in public repositories. For the de novo assembly of the SARS-CoV-2 genomes, a myriad of assemblers is being used, although their impact on the assembly quality has not been characterized for this virus. In this study, we aim to understand the variabilities on assembly qualities due to the choice of the assemblers. RESULTS: We performed 6648 de novo assemblies of 416 SARS-CoV-2 samples using eight different assemblers with different k-mer lengths. We used Illumina paired-end sequencing reads and compared the assembly quality of those assemblers. We showed that the choice of assembler plays a significant role in reconstructing the SARS-CoV-2 genome. Two metagenomic assemblers, e.g. MEGAHIT and metaSPAdes, performed better compared with others in most of the assembly quality metrics including, recovery of a larger fraction of the genome, constructing larger contigs and higher N50, NA50 values, etc. We showed that at least 09% (259/2873) of the variants present in the assemblies between MEGAHIT and metaSPAdes are unique to one of the assembly methods. CONCLUSION: Our analyses indicate the critical role of assembly methods for assembling SARS-CoV-2 genome using short reads and their impact on variant characterization. This study could help guide future studies to determine the best-suited assembler for the de novo assembly of virus genomes.