Wastewater surveillance allows early detection of SARS-CoV-2 omicron in North Rhine-Westphalia, Germany

Abstract

Wastewater-based epidemiology (WBE) has demonstrated its importance to support SARS-CoV-2 epidemiology complementing individual testing strategies. Due to their immune-evasive potential and the resulting significance for public health, close monitoring of SARS-CoV-2 variants of concern (VoC) is required to evaluate the regulation of early local countermeasures. In this study, we demonstrate a rapid workflow for wastewater-based early detection and monitoring of the newly emerging SARS-CoV-2 VoCs Omicron in the end of 2021 at the municipal wastewater treatment plant (WWTP) Emschermuendung (KLEM) in the Federal State of North-Rhine-Westphalia (NRW, Germany). Initially, available primers detecting Omicron-related mutations were rapidly validated in a central laboratory. Subsequently, RT-qPCR analysis of purified SARS-CoV-2 RNA was performed in a decentral PCR laboratory in close proximity to KLEM. This decentralized approach enabled the early detection of K417N present in Omicron in samples collected on 8th December 2021 and the detection of further mutations (N501Y, Δ69/70) in subsequent biweekly sampling campaigns. The presence of Omicron in wastewater was confirmed by next generation sequencing (NGS) in a central laboratory with samples obtained on 14th December 2021. Moreover, the relative increase of the mutant fraction of Omicron was quantitatively monitored over time by dPCR in a central PCR laboratory starting on 12th December 2021 confirming Omicron as the dominant variant by the end of 2021. In conclusions, WBE plays a crucial role in surveillance of SARS-CoV-2 variants and is suitable as an early warning system to identify variant emergence. In particular, the successive workflow using RT-qPCR, RT-dPCR and NGS demonstrates the strength of WBE as a versatile tool to monitor variant spreading.

Keywords: COVID-19 surveillance; Detection workflow; Omicron, B.1.1.529; SARS-CoV-2 monitoring; Variant of concern; Wastewater-based epidemiology (WBE).

Graphical abstract

Fig. 1

Monitoring of SARS-CoV-2 viral RNA fragments in WWTP KLEM. A) Wastewater samples were analysed (RT-qPCR) for total viral load using primer pairs detecting two targets in the SARS-CoV-2 N gene (N1/N2). B and C) The presence of Omicron characteristic mutations K417N, N501Y and del69/70 in SARS-CoV-2 Spike was detected using RT-qPCR. Panel B illustrates the decline of non-Omicron amino acids K417, 69/70, and N501. Panel B shows the increase in Omicron specific substitutions K417N, del 69/70, and N501Y. The graphs on the left indicate the ct values over time. The corresponding reciprocal values are illustrated in the plot on the right.

Fig. 2

Identification of the SARS-CoV-2 Omicron variant by NGS. Upper panel: Occurrence (i.e., the numbers of reads corresponding to each mutation) of characteristic S, E, M, and N protein mutations and ORF1ab mutations of the Omicron variant. Lower panels: Heatmap showing the allele frequency and the mutations corresponding to the Sars-CoV-2 genome position.

Fig. 3

Tracking of SARS-CoV-2 Omicron specific mutant fraction of K417N using digital PCR. A) 7-day incidence (left) and the Omicron mutant fraction (right) for Germany and North-Rhine-Westphalia (NRW) are indicated. Epidemiological data are based on individual testing and were obtained from official data repository of the German Federal Robert Koch Institute (RKI). B) Total SARS-CoV-2 levels (left) and the Omicron-detecting substitution K417N (right) determined in wastewater samples from WWTP KLEM. C) 7-day incidence in NRW correlates to detected SARS-CoV-2 levels in wastewater (left). The relative mutant fraction of Omicron determined by individual testing is highly comparable to the relative fraction of K417N found in wastewater (right).