Evidence map›Paper›PMID 39641602›Full record

ArticleApplied and environmental microbiology2025

Viral concentration method biases in the detection of viral profiles in wastewater.

Naeema Cheshomi, Absar Alum, Matthew F Smith, Efrem S Lim, Otakuye Conroy-Ben, Morteza Abbaszadegan

Abstract read
In one paragraph

Article in Applied and environmental microbiology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Naeema CheshomiSchool of Sustainable Engineering and the Built Environment, Arizona State University, Tempe, Arizona, USA.ORCID 0009-0008-4780-9276
Absar AlumSchool of Sustainable Engineering and the Built Environment, Arizona State University, Tempe, Arizona, USA.ORCID 0000-0001-7737-7541
Matthew F SmithCenter for Fundamental and Applied Microbiomics, Biodesign Institute, Arizona State University, Tempe, Arizona, USA.
Efrem S LimCenter for Fundamental and Applied Microbiomics, Biodesign Institute, Arizona State University, Tempe, Arizona, USA.ORCID 0000-0002-3397-9310
Otakuye Conroy-BenSchool of Sustainable Engineering and the Built Environment, Arizona State University, Tempe, Arizona, USA.
Morteza AbbaszadeganSchool of Sustainable Engineering and the Built Environment, Arizona State University, Tempe, Arizona, USA.ORCID 0000-0002-7368-4242

Funding

UA Student Development: Data Warriors Fellowship ProgramS06GM142123 · NIGMS · INTER TRIBAL COUNCIL OF ARIZONA, INC. · PI DADGAR, MARIA, SOLOMON, TESHIA G. ARAMBULA · 2021 to 2024
$5.0M
NIGMS NIH HHS S06 GM142123
6 · The paper itself

Abstract

Viral detection methodologies used for wastewater-based epidemiology (WBE) studies have a broad range of efficacies. The complex matrix and low viral particle load in wastewater emphasize the importance of the concentration method. This study focused on comparing three commonly used virus concentration methods: polyethylene glycol precipitation (PEG), immuno-magnetic nanoparticles (IMNP), and electronegative membrane filtration (EMF). Influent and effluent wastewater samples were processed by the methods and analyzed by DNA/RNA quantification and sequencing for the detection of human viruses. SARS-COV-2, Astrovirus, and Hepatitis C virus were detected by all the methods in both sample types. PEG precipitation resulted in the detection of 20 types of viruses in influent and 16 types in effluent samples. The corresponding number of virus types detected was 21 and 11 for IMNP, and 16 and 8 for EMF. Certain viruses were unique to only one concentration method. For example, PEG detected three types of viruses in influent and six types in effluent compared to IMNP, which detected seven types in influent and one type in effluent samples. However, the EMF method appeared to be the least effective, detecting three types in influent and none in effluent samples. Rotavirus was detected in influent sample using IMNP method, whereas EMF and PEG methods failed to yield a similar outcome. Consequently, the potential false negative results pose a risk to the credibility of WBE applications. Therefore, implementation of a proper concentration technique is critical to minimize method biases and ensure accurate viral profiling in WBE studies.IMPORTANCEIn recent years, significant research efforts have been focused on the development of viral detection methodology for wastewater-based epidemiology studies, showing a range of variability in detection efficacies. A proper methodology is essential for an appropriate evaluation of disease prevalence and community health in such studies and necessitates designing a concentration method based on the target pathogenic virus. There remains a need for comparative performance evaluations of methods in the context of detection efficiencies. This study highlights the significant impact of sample matrix, viral structure, and nucleic acid composition on the efficacy of viral concentration methods. Assessing WBE techniques to ensure accurate detection and understanding of viral presence within wastewater samples is critical for revealing viral profiles in municipality wastewater samples.

Indexed as

Viral LoadVirusesWastewaterFiltrationHumansPolyethylene GlycolsSARS-CoV-2Polyethylene GlycolsWastewaterenveloped/non-enveloped virusnext-generation sequencingviral concentration methodwastewater-based epidemiologywastewater sample matrix

Identifiers

PMID39641602
PMCPMC11784009

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.