Metagenomic Sequencing samples - Crossref

Identification of missed viruses by metagenomic sequencing of clinical respiratory samples from Kenya

Most molecular diagnoses of viruses rely on polymerase chain reaction assays, but primer mismatches may result in failure due to primer mismatch. In Kilifi, Kenya, we investigated the effectiveness of routine virus diagnostics by using random-primed viral next generation sequencing on respiratory samples that were not positive for common respiratory pathogens by a local standard diagnostic panel. Among 95 hospitalized pneumonia patients and 95 household-cohort patients, research of viral NGS revealed at least one respiratory-associated virus in 35 and 23 samples, respectively.

Source link: https://doi.org/10.1038/s41598-021-03987-1

Gut microbiome comparability of fresh-frozen versus stabilized-frozen samples from hospitalized patients using 16S rRNA gene and shotgun metagenomic sequencing

Chemical stabilization has been demonstrated by previous experiments in healthy/non-hospitalized volunteers, which has revealed that chemical stabilization leads to similar findings to FF samples. Both 16S rRNA gene and shotgun metagenomic sequencing were used to evaluate this in a hospital setting. We compared FF and SF approaches across 17 patients undergoing haematopoietic stem cell transplantation, using both 16S rRNA gene and shotgun metagenomic sequencing to see which is the most relevant in a hospital setting. A paired comparison of FF and SF samples was carried out, with an overall similarity in relative taxonomic abundances between the two sampling methods. Both methods were not significantly different, and we were unable to accept the null argument that a sample variation in FF and SF were similar within-sample variation.

Source link: https://doi.org/10.1038/s41598-019-49956-7

Identification of core and rare species in metagenome samples based on shotgun metagenomic sequencing, Fourier transforms and spectral comparisons

By introducing the rare species identifier device, we provide a path to increased species-level specificity, reduced false discovery, and omission rates of core and rare species in complex metagenomic samples. The python software is based on discrete Fourier transforms and spectral comparisons of biological and reference frequency signals obtained from real and ideal distributions of short DNA reads mapping to circular reference genomes. Human Streptococcus spp. has been described as a species-level differentiation of rare Escherichia coli and Shigella spp. , as well as the explicit differentiation of human Streptococcus spp. raspir reanalyzed publicly available human placenta sequencing results.

Source link: https://doi.org/10.1038/s43705-021-00010-6

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