Comparative Evaluation of DNA Extraction Workflows for Efficient Recovery of pBI143 from Wastewater

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Publication: Ali et al., Food and Environmental Virology (2026)

Overview

This study compared Nanotrap® Microbiome magnetic particle capture, polyethylene glycol (PEG) precipitation, and direct extraction for recovery of the emerging human fecal marker pBI143 from wastewater. Twelve wastewater samples collected from six treatment plants in Maryland and Washington, D.C. were analyzed by qPCR. The study also evaluated crAssphage, tomato brown rugose fruit virus (ToBRFV), and pepper mild mottle virus (PMMoV) as alternative fecal markers for wastewater-based epidemiology (WBE). The Nanotrap workflow used Microbiome Particles A and B with automated KingFisher™ Apex processing.

Key Findings

Nanotrap significantly improved pBI143 recovery

• pBI143 was detected in 100% of wastewater samples with all three workflows.

• Average pBI143 concentrations were 9.68 log₁₀ copies/L with Nanotrap, compared with 9.02 for direct extraction and 8.55 for PEG precipitation.

• Nanotrap produced significantly higher pBI143 concentrations than both PEG and direct extraction (p<0.05). The same performance advantage was observed for crAssphage.

Higher recovery despite substantially lower sample volume

• The Nanotrap workflow processed only 4.8 mL of wastewater versus 40 mL for PEG precipitation, yet produced significantly higher target concentrations.

• The authors attribute this result to efficient magnetic capture and enrichment of microbial cells and associated nucleic acids before extraction.

• As shown in Figure 1 on page 4, both pBI143 and crAssphage concentrations were highest with the Nanotrap workflow.

Particle selection matters for target recovery

• Unlike an earlier study that used Microbiome Particle A alone, this workflow combined Nanotrap Microbiome Particles A and B.

• The authors suggest that using both particle types likely contributed to improved pBI143 recovery, highlighting the importance of optimizing particle chemistry for the intended microbial targets.

Faster, automation-compatible workflow

• Nanotrap concentration and nucleic acid extraction required approximately 45–60 minutes, compared with 3–4 hours for PEG precipitation.

• Automated processing on the KingFisher Apex provides a practical pathway toward scalable, high-throughput wastewater surveillance while reducing manual sample handling.

Nanotrap supported recovery of diverse fecal markers

• Using Nanotrap-extracted total nucleic acids, pBI143, crAssphage, ToBRFV, and PMMoV were detected in 100% of samples.

• pBI143, crAssphage, and ToBRFV occurred at similarly high concentrations, while PMMoV was significantly lower (p<0.05), as illustrated in Figure 2 on page 5.

• Based on concentration alone, the authors identify pBI143, crAssphage, and ToBRFV as promising alternatives to PMMoV for wastewater normalization.

Implications for Nanotrap Technology

This study provides independent evidence that the Nanotrap Microbiome Combined workflow can outperform PEG precipitation for recovery of wastewater-associated genetic targets while substantially reducing processing time. Importantly, the workflow co-captured both DNA and RNA targets, supporting its potential for multiplexed wastewater surveillance. The combination of efficient target enrichment, magnetic particle capture, and automated KingFisher processing positions Nanotrap technology as a scalable sample preparation approach for next-generation WBE programs.

Conclusion

The authors conclude that the Nanotrap Microbiome workflow was superior to PEG precipitation for pBI143 recovery, despite processing approximately eightfold less wastewater, while reducing processing time from several hours to under one hour. The study also demonstrates the value of combining Nanotrap particle chemistries to broaden target capture. A key limitation is that the samples contained relatively high fecal-marker concentrations; therefore, method-specific limits of detection and performance at low target abundance remain to be established. Overall, the results support Nanotrap as a rapid, scalable platform for high-throughput wastewater-based epidemiology.

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