Lab Matters Fall 2024 | Page 131

APHL 2024 POSTER ABSTRACTS submitted for WGS as part of CDPHE ’ s clinical surveillance program . We developed an innovative tool to track all mutations seen over time in wastewater samples , concentrating on novel and recurrent ( at least six months between detections ) mutations . We used this tool to perform a retrospective analysis of data generated from March 2021 – December 2023 , capturing surge periods of high wastewater viral concentration along with periods of low viral concentration . First , we compared wastewater and clinical lineage proportions before , during and between the Omicron , XBB and JN . 1 surges to determine lineage trends and prevalence during varying levels of disease burden . Second , we compared when lineage-defining mutations appeared relative to when the lineages themselves were initially identified in wastewater data . As part of the early warning system , we calculated features for each mutation , including gene location , mutation type and weekly growth rates . Finally , we are comparing data between wastewater facilities that serve different population sizes to determine if there is a minimum population level needed to obtain an accurate representation of SARS-CoV-2 activity .

In this retrospective analysis of the Omicron and XBB surges and real-time analysis of the rise of JN . 1 , we detected lineages in wastewater before clinical samples . We also detected lineagedefining mutations before corresponding lineage identification in wastewater . Our results demonstrate the usefulness and importance of wastewater WGS in supplementing clinical surveillance systems to facilitate a timely and effective public health response .

Presenter : Arianna Smith , arianna . smith @ state . co . us

Development of Digital PCR Assays for Quantifying Carbapenem-resistant Genes From Wastewater for Public Health Surveillance

E . Doolittle 1 , G . Knuth 1 , L . Simonson 1 , K . Janssen 1 , A . Bruckert 1 , M . Collins 1 , M . Schussman 2 , S . McLellan 2 , J . Hemming 1 , M . Shafer 1 , Wisconsin State Laboratory of Hygiene 1 , School of Freshwater Sciences , University of Wisconsin-Milwaukee 2

Antibiotic resistance ( AR ) is a serious and growing threat globally ; it is estimated that 1.27 million people die annually from AR infections . Although AR is autochthonous to our ecosystems , human activities ( e . g ., pharmaceutical and veterinary industries ) can promote the spread and persistence of AR genes in the environment . Wastewater is one of the engineered habitats considered a hotspot / receptor of AR genes and multidrugresistant organisms . The COVID-19 pandemic spurred the further development and broad implementation of wastewater surveillance for infectious diseases , opening the door to a new and widespread monitoring approach for AR worldwide . Wastewater is a valuable and equitable tool to monitor community disease trends and community and building level surveillance applications of AR and multidrugresistant organisms are just beginning to be developed and validated . Among the AR of concern , carbapenem resistance ( CR ) in bacteria is a major concern as carbapenem antibiotics are often the last line of effective treatment for serious infections that do not respond to other antibiotics . Clinical testing and surveillance of CR often relies on culturing patient samples , which is not optimal for widespread surveillance . The use of quantitative PCR has become a useful tool alongside culture-based approaches to monitor for AR , however many of the assays developed have been designed for clinical samples and may lack the sensitivity and specificity needed for processing environmental samples .

The Wisconsin State Laboratory of Hygiene ( WSLH ) and its partner in the Wisconsin wastewater-based epidemiology program , the University of Wisconsin-Milwaukee , have optimized and validated digital PCR ( dPCR ) methods to quantify key CR genes in wastewater . At WSLH , six CR genes were selected for assay development based on clinical relevance in the state of Wisconsin . The selected genes include bla-KPC , bla-NDM , bla-IMP , bla-VIM , bla-OXA24 and bla-OXA48 . Primers and probes were optimized and validated for dPCR quantification in both singleplex and multiplex approaches using synthetic DNA positive control sequences , bacterial strains harboring the target CR gene and influent wastewater samples from sewershed communities in Wisconsin . Testing indicated that multiplex designs generate similar results to singleplex in terms of sensitivity ( LOD ) and quantification . In addition to dPCR assay development , we compared two wastewater microbe concentration methods , membrane ( HA ) filtration and nanoparticle ( Nanotrap ® , Ceres Nanosciences ) concentration for CR recovery with mixed results . Lastly , a three-year retrospective study of archived filtered wastewater was conducted to assess the temporal trends of these six CR gene targets from selected sewersheds , indicating that the prevalence of selected gene targets varies over time and amongst collection sites .

The expansion and optimization of dPCR testing for AR and specifically CR genes from wastewater samples can provide insight into their prevalence within a community , as well as identify potential sources within sewersheds , including hospitals and other industries . These efforts can support clinical testing and health care responses for infection control while broadening the understanding of AR in public health on a community level .

Presenter : Evelyn Doolittle , Evelyn . Doolittle @ slh . wisc . edu

Digital PCR Assay Development and Comparison for the Quantification of C . auris From Wastewater

G . Knuth , K . Janssen , M . Collins , J . Hemming , M . Shafer , Wisconsin State Laboratory of Hygiene

Candida auris is an opportunistic fungal pathogen capable of causing serious infections that may result in death , particularly an increasing concern in congregate care facilities . The CDC has listed C . auris as an urgent threat due to its increasing incidence and persistence as well as growing resistance to antifungals . The hardiness of C . auris also causes complications in its prevention and control as it is able to survive on hard surfaces , making it highly transmissible . C . auris has been found in multiple clinical samples including the skin , wounds , blood , sputum , urine and stool . Monitoring of C . auris in healthcare settings often utilizes screening methods that include screening patients before admittance , point of prevalence surveys and screening of current patients . These screening methods , however , may underestimate the prevalence of C . auris and take time and additional resources of the health care staff . Detection of C . auris has relied on culture-based approaches or PCR assays designed for clinical use . Additional supportive approaches to healthcare surveillance , such as wastewater surveillance , may be helpful in tracking and estimating the overall amount of C . auris within a healthcare setting or community .