Person:
Konstantinidis, Kostas T.

Permanent Link
https://hdl.handle.net/1853/71418
Associated Organization(s)
ORCID
ArchiveSpace Name Record

Filters

2024 1
1
1
1
1
Reset filters

Settings
Author: Brown, Joe ×

Publication Search Results

Now showing 1 - 1 of 1
  • No Thumbnail Available
    Item
    Metagenomic evaluation of the performance of passive Moore swabs for sewage monitoring relative to composite sampling over time resolved deployments
    (Georgia Institute of Technology, 2024-01) Cha, Gyuhyon ; Zhu, Kevin J. ; Fisher, Jamie M. ; Flores, Camryn I. ; Brown, Joe ; Pinto, Ameet ; Hatt, Janet K. ; Konstantinos, Kostas T. ; Graham, Katherine E.
    Moore swabs have re-emerged as a versatile tool in the field of wastewater-based epidemiology during the COVID-19 pandemic and offer unique advantages for monitoring pathogens in sewer systems, especially at the neighborhood-level. However, whether Moore swabs provide comparable results to more commonly used composite samples remains to be rigorously tested including the optimal duration of Moore swab deployment. This study provides new insights into these issues by comparing the results from Moore swab samples to those of paired composite samples collected from the same sewer lines continuously over six to seventy-two hours post-deployment, during low COVID-19 prevalence periods. Our results show that Moore swabs accumulated approximately 10-fold higher PMMoV concentrations (on a basis of mL of Moore swab squeezed filtrate to mL of composite sewage) and showed comparable trends in terms of bacterial species abundance when compared to composite samples. Moore swabs also generally captured higher SARS-CoV-2 N1/N2 RNA concentrations than composite samples. Moore swabs showed comparable trends in terms of abundance dynamics of the sewage microbiome to composite samples and variable signs of saturation over time that were site and/or microbial population-specific. Based on our dual ddRT-PCR and shotgun metagenomic approach, we find that Moore swabs at our sites were optimally deployed for 6 hours at a time at two sites.