Lab Matters Fall 2024 | Page 135

APHL 2024 POSTER ABSTRACTS

Quality Matters : Harmonizing Non-standardized Wastewater Surveillance Laboratory Results through OCWA ’ s Innovative Interlab Program

A . Chik , C . Adam , J . Ho , Ontario Clean Water Agency

The collection of municipal wastewater samples for estimation of severe acute respiratory syndrome coronavirus-2 ( SARS-CoV-2 ) genetic fragment concentrations has demonstrated remarkable utility for monitoring community public health trends throughout the COVID-19 pandemic . However , the comparability of wastewater surveillance results between laboratories remains largely unreconciled owing to the various unstandardized methodologies deployed . This could potentially undermine efforts of state- and nation-wide wastewater surveillance programs that aggregate datasets across multiple laboratories to provide trends and insights at broader regional scales .

As wastewater surveillance programs continue to expand and mature for other targets of public health relevance , rigorous frameworks to support the evaluation of laboratory data quality and method comparability must also be in place . In 2020 , Ontario Clean Water Agency ( OCWA ) established a wastewater surveillance inter-laboratory methods comparison program . Through an ongoing quarterly assessment of split-sample testing over the past three years , streamlined quality assurance and quality control ( QA / QC ) across a network of laboratories has been shown to yield reliable data that are not only fit for tracking trends , but also comparable between laboratories ( Chik et al ., in review ).

Here we present and highlight key considerations in the design , implementation and evolution of OCWA ’ s interlaboratory methods program . Over 40 academic , public health / environmental and commercial sector laboratories in Canada and the United States have participated in this program to date . We will also provide an update on the imminent transition of this program into a first-of-itskind accredited Proficiency Testing program ( ISO 17043:2010 ) to continue serving laboratories undertaking wastewater surveillance activities .

Presenter : Alex Chik , achik @ ocwa . com

SARS-CoV-2 Detection in Wastewater : A Long-term Application

S . Zekovich , M . Robinson , J . Knibbs , M . Asbell , R . Jamal , Indiana Department of Health

In response to the COVID-19 pandemic , the Centers for Disease Control and Prevention ( CDC ) launched the National Wastewater Surveillance System ( NWSS ) in September 2020 . The CDC developed NWSS to coordinate and build the nation ’ s capacity to monitor the presence of SARS-CoV-2 , the virus that causes COVID-19 , in wastewater samples collected across the country . Wastewater-based epidemiology ( WBE ) is used by epidemiologists and local health departments to assess and monitor the spread of disease to predict an outbreak . Individuals infected with SARS- CoV-2 can shed the virus in their feces , even if they don ’ t have symptoms , allowing symptomatic and asymptomatic infections in the community to be detected via wastewater surveillance , increasing health equity in communities across Indiana . Preventative measures such as encouraging the use of masks , social distancing in impacted communities and informing hospitals of a possible elevated number of cases to allow proper allocation of staff , resources and bed space . Clinical and wastewater data can be used collectively to provide a comprehensive view of disease spread in communities , regardless of access to clinical testing .

IDOHL has received raw wastewater samples collected from over eight wastewater treatment plants across the state of Indiana . Samples are concentrated using Ceres Nanotrap ® Microbiome Particles and RNA is extracted using the Promega Maxwell ® HT Environmental TNA Kit on the KingFisher . Digital polymerase chain reaction ( dPCR ) on the QIAGEN QIAcuity dPCR System is performed using the GT Molecular SARS-CoV-2 Wastewater Surveillance kit . Results are reported from STARLIMS directly to CDC NWSS . Normalized data are posted publicly on the CDC COVID Data Tracker and IDOH Wastewater Dashboards . Sequencing results will also be reported to the CDC and data may be used to monitor the current SARS-CoV-2 strains circulating within a community . Preliminary sequencing has been performed using the QIAGEN QIAseq DIRECT SARS-CoV-2 Kits on the Illumina NextSeq 1000 sequencing system .

Results from over 800 samples have been analyzed and compared to clinical case data within a region to provide more information on the spread of disease in a community . Wastewater surveillance programs nationally , including IDOHL , intend to develop sequencing capacity and expand testing to include other infectious disease pathogens such as Influenza A , Influenza B and Respiratory Syncytial Virus .

Presenter : Sarah Zekovich , szekovich @ health . in . gov

SPLiNTER : A NextFlow Pipeline for Genome Assembly and Determination of Relative Variant Abundances in SARS- CoV-2 Wastewater Samples

S . Bennett , H . Moon , L . Fink , L . Turner , Virginia Division of Consolidated Laboratory Services

Background : Utilizing the viral shedding of SARS-CoV-2 through fecal matter that occurs in infected individuals , testing of wastewater samples allows for efficient sampling independent of healthcare seeking behaviors and symptom presence . Targeted next-generation sequencing ( NGS ) of SARS-CoV-2 in samples taken from county level wastewater facilities has proven to be an effective surveillance tool for identifying emerging variants . In conjunction with onboarding whole genome sequencing methods for wastewater surveillance , the Division of Consolidated Laboratory Services ( DCLS ) developed and validated an automated analysis pipeline , SPLiNTER , a DSL2 NextFlow pipeline , by combining parts of our clinical SARS-CoV-2 genome assembly NextFlow pipeline with additional tools to calculate relative variant abundance .

Methods : SPLiNTER uses Trimmomatic and BBDUK for quality trimming and adapter removal of the Illuminia paired-end reads ( FASTQs ). The quality trimmed reads are then aligned using Minimap2 . SAMtools and iVAR are used to generate alignment files . These alignment files are used to recover relative lineage abundance and variant calls via Freyja . All tools used within this pipeline are accessed through Docker containers . Sequencing quality metrics as well as the recovered relative lineage abundances are outputted into human readable CSV and TSV files . The pipeline is packaged so that it is easily deployable in a LINUX environment