Variations in the persistence of 5'-end genomic and subgenomic SARS-CoV-2 RNAs in wastewater from aircraft, airports and wastewater treatment plants

Abstract

Wastewater sequencing has become a powerful supplement to clinical testing in monitoring SARS-CoV-2 infections in the post-COVID-19 pandemic era. While its applications in measuring the viral burden and main circulating lineages in the community have proved their efficacy, the variations in sequencing quality and coverage across the different regions of the SARS-CoV-2 genome are not well understood. Furthermore, it is unclear how different sample origins, viral extraction and concentration methods and environmental factors impact the reads sequenced from wastewater. Using high-coverage, amplicon-based, paired-end read sequencing of viral RNA extracted from wastewater collected directly from aircraft, pooled from different aircraft and airport buildings or from regular wastewater plants, we assessed the genome coverage across the sample groups with a focus on the 5'-end region covering the leader sequence and investigated whether it was possible to detect subgenomic RNA from viral material recovered from wastewater. We identified distinct patterns in the persistence of the different genomic regions across the different types of wastewaters and the existence of chimeric reads mapping to non-amplified regions. Our findings suggest that preservation of the 5'-end of the genome and the ability to detect subgenomic RNA reads, though highly susceptible to environment and sample processing conditions, may be indicative of the quality and amount of the viral RNA present in wastewater.

Keywords: SARS-CoV-2; Subgenomic RNA; Transcription/replication; Wastewater.

Fig. 1

Genome coverage profile of the analyzed wastewater samples. The coverage profiles of reads sequenced from 74 wastewater samples collected in 2023 as shown. The samples consisted of wastewater collected directly from six long-distance flights arriving at Copenhagen airport (I, orange), 10 pooled samples from aircraft and airport buildings (II, green), and samples collected from 29 wastewater treatment plants in Denmark in week 24 (III, dark blue) and week 47 (IV, purple). The first vertical dotted line marks position 300, the second vertical dotted line the start position of subgenomic E (position 26,237) and the third vertical dotted line the start position of subgenomic Orf9 (position 28,255). The y-axis was limited to 30,000 reads per position. Samples covered by more than 10 reads in the 5′-end first 300-nucleotide region are marked with a triangle above the 300-nucletide region. Samples in which subgenomic RNAs were detected are marked in yellow. (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article.)

Fig. 2

View of the subgenomic reads in ORF9 and E for the wastewater sample taken from an aircraft (AC3). A snapshot taken with IGV-2.16.2 depicting all subgenomic reads mapping to ORF9. Soft-clipped bases on the leftmost positions map to the region of the leader (position 52–67) containing the GTAGATCTGTTC sequence (green). (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article.)

Fig. 3

Sequence read coverage variation across wastewater sample groups. Panel A: Principal Component Analysis biplot on mean sequence coverage per region and the total number of raw and mapped reads, coverage at 10X coverage, presence/absence of the first 300 nucleotides of the 5′-UTR, and N2 Ct value. Panel B: Barplot showing the proportion of samples with each genomic region with at least 10X mean coverage. The samples are colored based on whether they originated directly from an aircraft (red), from pooled wastewater from aircraft and airport hangars and terminals (green) or from a wastewater treatment plant collected in week 24 (blue) and week 47 (purple). Statistical differences between sample groups in panel B were assessed using a Kruskal-Wallis test. (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article.)

Fig. 4

Schematic representation of the plausible template switching mechanism occurring to some 5′end reads. Hexamers and random primers attach to the positive strand viral RNA, and the negative strand cDNA is generated by the reverse transcriptase included in the reaction. In some cases, non-random template switch occurs on the 5′-end with another positive-strand RNA while generating cDNA for positive-strand RNA template. The resulting cDNA is then amplified by the reverse ARTIC primer and a hexamer that reverse complements the positive strand sequence generated by template switching. In the tagmentation step, fragments containing i) the forward hexamer primer on the 5′-end, ii) the ARTIC reverse primer sequence on the 3′-end or iii) none of the primer sequences are amplified by post-PCR.