Moving beyond SARS-CoV-2 surveillance: How can next-generation sequencing support wastewater-based epidemiology?
About the session
Since the emergence of the COVID-19 pandemic, there has been an unprecedented interest in identifying ways to monitor and measure SARS-CoV-2 transmission. Many groups have focused on developing wastewater-based surveillance methods. By targeting wastewater, large populations of individuals can be monitored at different levels of scale in a passive, non-invasive and affordable way. By gathering information about fecal shedding of the virus in all persons, including symptomatic and asymptomatic individuals, viral trends in wastewater can be compared to trend observed from sequenced clinical specimens. The combination of clinical and wastewater-based sequencing can reveal the virus's response to treatment, drugs and vaccines in large populations.
Wastewater epidemiology for SARS-CoV-2 has two aims: (1) to monitor the abundance of the virus in wastewater samples over time, and (2) to determine the relative amounts of mutations associated with variants of concern (VOC) that are of interest to healthcare professionals.
This session focuses on efforts to perform next-generation sequencing (NGS) of SARS-CoV-2 from wastewater using both targeted and whole genome amplification approaches. Dr. Smyth will discuss how she and her colleagues leveraged their prior experiences and knowledge to overcome challenges associated with varying viral concentrations and viral genome fragmentation (degradation) characteristic of wastewater samples so that NGS and analysis could be conducted successfully. In particular, the utility of a new solution, the QIAseq DIRECT SARS-CoV-2 Kit, will be evaluated, revealing how its ultrafast workflow and novel primer design for RNA-seq library preparation make it highly suited for the detection of emerging new SARS-CoV-2 variants. Finally, other bottlenecks and barriers to viral NGS-based wastewater analysis will be discussed in relation to potential future pandemics.
Speakers
![Davida Smyth](/%5E%5Ecdi={B97DE005-4A20-4B74-A750-B6AD53DCC278}%5Ehash=/-/media/project/qiagen/qiagen-home/service-and-support/learning-hub/virtual-events/innovation-forum-2022/davida-smyth.jpg)