Combining Short- and Long-Read Sequencing Technologies to Identify SARS-CoV-2 Variants in Wastewater.

Area of Science:

• Environmental microbiology
• Genomics
• Public health virology

Background:

• Wastewater surveillance of SARS-CoV-2 RNA provided community-level insights into infection dynamics and variant evolution during the COVID-19 pandemic.
• The increasing diversity of SARS-CoV-2 sublineages complicated variant identification in mixed wastewater samples, especially for novel or low-abundance variants.

Purpose of the Study:

• To compare the efficacy of Illumina (short-read) and Oxford Nanopore Technologies (long-read) sequencing for detecting SARS-CoV-2 variants of differing abundance in wastewater.
• To evaluate two analytical approaches for variant identification: signature mutation presence and co-occurring mutations within amplicons.

Main Methods:

• Analysis of 248 wastewater samples from Quebec and Ontario using both Illumina and Oxford Nanopore sequencing platforms.
• Variant identification based on signature mutations and mutation co-occurrence within amplicons.

Main Results:

• Illumina sequencing showed higher sensitivity for detecting low-abundance or previously unknown lineages.
• Nanopore sequencing demonstrated a greater capacity for detecting high-abundance variants like B.1.1.7 (Alpha) and identifying co-occurring mutations within the same amplicon.

Conclusions:

• Both sequencing technologies offer complementary strengths for SARS-CoV-2 variant detection in wastewater.
• An integrated workflow combining short-read and long-read sequencing enhances the comprehensive identification of diverse SARS-CoV-2 lineages in complex environmental samples.