The clinical utility of Nanopore 16S rRNA gene sequencing for direct bacterial identification in normally sterile body fluids.

The prolonged incubation period of traditional culture methods leads to a delay in diagnosing invasive infections. Nanopore 16S rRNA gene sequencing (Nanopore 16S) offers a potential rapid diagnostic approach for directly identifying bacteria in infected body fluids. To evaluate the clinical utility of Nanopore 16S, we conducted a study involving the collection and sequencing of 128 monomicrobial samples, 65 polymicrobial samples, and 20 culture-negative body fluids. To minimize classification bias, taxonomic classification was performed using 3 analysis pipelines: Epi2me, Emu, and NanoCLUST. The result was compared to the culture references. The limit of detection of Nanopore 16S was also determined using simulated bacteremic blood samples. Among the three classifiers, Emu demonstrated the highest concordance with the culture results. It correctly identified the taxon of 125 (97.7%) of the 128 monomicrobial samples, compared to 109 (85.2%) for Epi2me and 102 (79.7%) for NanoCLUST. For the 230 cultured species in the 65 polymicrobial samples, Emu correctly identified 188 (81.7%) cultured species, compared to 174 (75.7%) for Epi2me and 125 (54.3%) for NanoCLUST. Through ROC analysis on the monomicrobial samples, we determined a threshold of relative abundance at 0.058 for distinguishing potential pathogens from background in Nanopore 16S. Applying this threshold resulted in the identification of 107 (83.6%), 117 (91.4%), and 114 (91.2%) correctly detected samples for Epi2me, Emu, and NanoCLUST, respectively, in the monomicrobial samples. Nanopore 16S coupled with Epi2me could provide preliminary results within 6 h. However, the ROC analysis of polymicrobial samples exhibited a random-like performance, making it difficult to establish a threshold. The overall limit of detection for Nanopore 16S was found to be about 90 CFU/ml.

Aerosol transmission of SARS-CoV-2 due to the chimney effect in two high-rise housing drainage stacks.

Stack aerosols are generated within vertical building drainage stacks during the discharge of wastewater containing feces and exhaled mucus from toilets and washbasins. Fifteen stack aerosol-related outbreaks of coronavirus disease 2019 (COVID-19) in high-rise buildings have been observed in Hong Kong and Guangzhou. Currently, we investigated two such outbreaks of COVID-19 in Hong Kong, identified the probable role of chimney effect-induced airflow in a building drainage system in the spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). We injected tracer gas (SF6) into the drainage stacks via the water closet of the index case and monitored tracer gas concentrations in the bathrooms and along the facades of infected and non-infected flats and in roof vents. The air temperature, humidity, and pressure in vertical stacks were also monitored. The measured tracer gas distribution agreed with the observed distribution of the infected cases. Phylogenetic analysis of the SARS-CoV-2 genome sequences demonstrated clonal spread from a point source in cases along the same vertical column. The stack air pressure and temperature distributions suggested that stack aerosols can spread to indoors through pipe leaks which provide direct evidence for the long-range aerosol transmission of SARS-CoV-2 through drainage pipes via the chimney effect.

A low-cost TaqMan minor groove binder probe-based one-step RT-qPCR assay for rapid identification of N501Y variants of SARS-CoV-2.

The increasing prevalence of N501Y variants of SARS-CoV-2 has kindled global concern due to their enhanced transmissibility. Genome sequencing is the gold standard method to identify the emerging variants of concern. But it is time-consuming and expensive, limiting the widespread deployment of genome surveillance in some countries. Health authorities surge the development of alternative assay to expand screening capacity with reduced time and cost. In this study, we developed an in-house TaqMan minor groove binder (MGB) probe-based one-step RT-qPCR assay to detect the presence of N501Y mutation in SARS-CoV-2. A total of 168 SARS-CoV-2 positive respiratory specimens were collected to determine diagnostic accuracy of the RT-qPCR assay. As a reference standard, PANGO lineages and the mutation patterns of all samples were characterised by whole-genome sequencing. The analytical sensitivity and the ability of the assay to detect low frequency of N501Y variants were also evaluated. A total of 31 PANGO lineages were identified from 168 SARS-CoV-2 positive cases, in which 34 samples belonged to N501Y variants, including B.1.1.7 (n = 20), B.1.351 (n = 12) and P.3 (n = 2). The N501Y RT-qPCR correctly identified all 34 samples as N501Y-positive and the other 134 samples as wildtype. The limit-of-detection of the assay consistently achieved 1.5 copies/µL on four different qPCR platforms. N501Y mutation was successfully detected at an allele frequency as low as 10 % in a sample with mixed SARS-CoV-2 lineage. The N501Y RT-qPCR is simple and inexpensive (US$1.6 per sample). It enables robust high-throughput screening for surveillance of SARS-CoV-2 variants of concern harbouring N501Y mutation.

The Clinical Utility of Two High-Throughput 16S rRNA Gene Sequencing Workflows for Taxonomic Assignment of Unidentifiable Bacterial Pathogens in Matrix-Assisted Laser Desorption Ionization-Time of Flight Mass Spectrometry.

Bacterial pathogens that cannot be identified using matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) are occasionally encountered in clinical laboratories. The 16S rRNA gene is often used for sequence-based analysis to identify these bacterial species. Nevertheless, traditional Sanger sequencing is laborious, time-consuming, and low throughput. Here, we compared two commercially available 16S rRNA gene sequencing tests that are based on Illumina and Nanopore sequencing technologies, respectively, in their ability to identify the species of 172 clinical isolates that failed to be identified by MALDI-TOF MS. Sequencing data were analyzed by the respective built-in programs (MiSeq Reporter software of Illumina and Epi2me of Nanopore) and BLAST+ (v2.11.0). Their agreement with Sanger sequencing on species-level identification was determined. Discrepancies were resolved by whole-genome sequencing. The diagnostic accuracy of each workflow was determined using the composite sequencing result as the reference standard. Despite the high base-calling accuracy of Illumina sequencing, we demonstrated that the Nanopore workflow had a higher taxonomic resolution at the species level. Using built-in analysis algorithms, the concordance of Sanger 16S with the Illumina and Nanopore workflows was 33.14% and 87.79%, respectively. The agreement was 65.70% and 83.14%, respectively, when BLAST+ was used for analysis. Compared with the reference standard, the diagnostic accuracy of Nanopore 16S was 96.36%, which was identical to that of Sanger 16S and better than that of Illumina 16S (69.07%). The turnaround time of the Illumina workflow and the Nanopore workflow was 78 h and 8.25 h, respectively. The per-sample cost of the Illumina and Nanopore workflows was US$28.5 and US$17.7, respectively.

Viral MicroRNAs Encoded by Nucleocapsid Gene of SARS-CoV-2 Are Detected during Infection, and Targeting Metabolic Pathways in Host Cells.

MicroRNAs (miRNAs) are critical regulators of gene expression that may be used to identify the pathological pathways influenced by disease and cellular interactions. Viral miRNAs (v-miRNAs) encoded by both DNA and RNA viruses induce immune dysregulation, virus production, and disease pathogenesis. Given the absence of effective treatment and the prevalence of highly infective SARS-CoV-2 strains, improved understanding of viral-associated miRNAs could provide novel mechanistic insights into the pathogenesis of COVID-19. In this study, SARS-CoV-2 v-miRNAs were identified by deep sequencing in infected Calu-3 and Vero E6 cell lines. Among the ~0.1% small RNA sequences mapped to the SARS-CoV-2 genome, the top ten SARS-CoV-2 v-miRNAs (including three encoded by the N gene; v-miRNA-N) were selected. After initial screening of conserved v-miRNA-N-28612, which was identified in both SARS-CoV and SARS-CoV-2, its expression was shown to be positively associated with viral load in COVID-19 patients. Further in silico analysis and synthetic-mimic transfection of validated SARS-CoV-2 v-miRNAs revealed novel functional targets and associations with mechanisms of cellular metabolism and biosynthesis. Our findings support the development of v-miRNA-based biomarkers and therapeutic strategies based on improved understanding of the pathophysiology of COVID-19.