Asymptomatic and Mild SARS-CoV-2 Infections in a Hungarian Outpatient Cohort in the First Year of the COVID-19 Pandemic.

We aimed to estimate the proportion of the population infected with SARS-CoV-2 in the first year of the pandemic. The study population consisted of outpatient adults with mild or no COVID-19 symptoms and was divided into subpopulations with different levels of exposure. Among the subpopulation without known previous COVID-19 contacts, 4143 patients were investigated. Of the subpopulation with known COVID-19 contacts, 594 patients were investigated. IgG- and IgA-seroprevalence and RT-PCR positivity were determined in context with COVID-19 symptoms. Our results suggested no significant age-related differences between participants for IgG positivity but indicated that COVID-19 symptoms occurred most frequently in people aged between 20 and 29 years. Depending on the study population, 23.4-74.0% PCR-positive people (who were symptomless SARS-CoV-2 carriers at the time of the investigation) were identified. It was also observed that 72.7% of the patients remained seronegative for 30 days or more after their first PCR-positive results. This study hoped to contribute to the scientific understanding of the significance of asymptomatic and mild infections in the long persistence of the pandemic.

High temporal resolution Nanopore sequencing dataset of SARS-CoV-2 and host cell RNAs.

BACKGROUND: Recent studies have disclosed the genome, transcriptome, and epigenetic compositions of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and the effect of viral infection on gene expression of the host cells. It has been demonstrated that, besides the major canonical transcripts, the viral genome also codes for noncanonical RNA molecules. While the structural characterizations have revealed a detailed transcriptomic architecture of the virus, the kinetic studies provided poor and often misleading results on the dynamics of both the viral and host transcripts due to the low temporal resolution of the infection event and the low virus/cell ratio (multiplicity of infection [MOI] = 0.1) applied for the infection. It has never been tested whether the alteration in the host gene expressions is caused by aging of the cells or by the viral infection. FINDINGS: In this study, we used Oxford Nanopore's direct cDNA and direct RNA sequencing methods for the generation of a high-coverage, high temporal resolution transcriptomic dataset of SARS-CoV-2 and of the primate host cells, using a high infection titer (MOI = 5). Sixteen sampling time points ranging from 1 to 96 hours with a varying time resolution and 3 biological replicates were used in the experiment. In addition, for each infected sample, corresponding noninfected samples were employed. The raw reads were mapped to the viral and to the host reference genomes, resulting in 49,661,499 mapped reads (54,62 Gbs). The genome of the viral isolate was also sequenced and phylogenetically classified. CONCLUSIONS: This dataset can serve as a valuable resource for profiling the SARS-CoV-2 transcriptome dynamics, the virus-host interactions, and the RNA base modifications. Comparison of expression profiles of the host gene in the virally infected and in noninfected cells at different time points allows making a distinction between the effect of the aging of cells in culture and the viral infection. These data can provide useful information for potential novel gene annotations and can also be used for studying the currently available bioinformatics pipelines.

Transcriptome dataset of six human pathogen RNA viruses generated by nanopore sequencing.

Long-read sequencing (LRS) approaches shed new light on the complexity of viral (Kakuk et al., 2021 [1]; Boldogkoi et al., 2019 [2]; Depledge et a., 2019 [3]), bacterial (Yan et al., 2018 [4]) and eukaryotic (Tilgner et al., 2014 [5]) transcriptomes. Emerging RNA viruses are zoonotic (Woolhouse et al., 2016 [6]) and create public health problems, e.g. influenza pandemic caused by H1N1 virus in (Fraser et al., 2009 [7]), as well as the current SARS-CoV-2 pandemic (Kim et al., 2020 [8]). In this study, we carried out nanopore sequencing for generating transcriptomic data valuable for structural and kinetic profiling of six important human pathogen RNA viruses, the H1N1 subtype of Influenza A virus (IVA), the Zika virus (ZIKV), the West Nile virus (WNV), the Crimean-Congo hemorrhagic fever virus (CCHFV), the Coxsackievirus [group B serotype 5 (CVB5)] and the Vesicular stomatitis Indiana virus (VSIV), and the response of host cells upon viral infection. The raw sequencing data were filtered during basecalling and only high quality reads (Qscore ≥ 7) were mapped to the appropriate viral and host genomes. Length distribution of sequencing reads were assessed and statistics of data were plotted by the ReadStat.4 python script. The datasets can be used to profile the transcriptomic landscape of RNA viruses, provide information for novel gene annotations, can serve as resource for studying the virus-host interactions, and for the analysis of RNA base modifications. These datasets can be used to compare the different sequencing techniques, library preparation approaches, bioinformatics pipelines, and to analyze the RNA profiles of viruses with small RNA genomes.