Reagent Contamination Distorts Pathogen Detection in mNGS
Content
August 29, 2025
FOR IMMEDIATE RELEASE
Mengchu Wu
Co-Founder, CEO, Chairwoman of the Board, Micronbrane Medical
mengchu@micronbrane.com
micronbrane.com
Reagent Contamination Distorts Pathogen Detection in mNGS
New study demonstrates brand- and lot-specific microbial DNA signatures; Micronbrane Medical establishes mNGS-grade as a measurable quality standard.
ZHUBEI CITY, Taiwan — August 28, 2025 — A newly published study in Microbiology Spectrum confirms that contaminating DNA in extraction reagents is a critical source of error in metagenomic next-generation sequencing (mNGS). The research demonstrates that microbial DNA contaminants, sometimes referred to as the kitome, are both brand- and lot-specific, capable of producing false positives and, in some cases, masking clinically important pathogens.
The study compared four widely used extraction kits and found substantial variation in background microbial DNA. Some lots contained organisms associated with infection, raising the risk of misinterpretation in both research and clinical contexts. Lot-to-lot variation within the same brand was also observed, underscoring the challenge of reproducibility in mNGS.
“Our results confirm that contaminating DNA in extraction reagents is not incidental. In a clinical context, false positives and unreliable negatives are unacceptable, and reproducibility across sites is essential,” said Dr. Zi-Lun Lai, Postdoctoral Research Fellow at China Medical University Hospital and first author of the study. “This study highlights the importance of transparent characterization of reagent backgrounds and the use of proper controls as necessary safeguards if mNGS is to be trusted in infectious disease diagnostics.”
Micronbrane Medical has established mNGS-grade as a quality framework to directly address this problem. All extraction reagents are manufactured under stringent protocols, tested for background microflora, and released only with a Certificate of Analysis (COA) documenting lot-specific contaminant profiles.
“Contamination is a pervasive issue across the entire mNGS workflow. In research, workarounds are possible, but in clinical applications accuracy cannot be compromised,” said Dr. Mengchu Wu, Co-Founder, CEO, and Chairwoman of Micronbrane Medical. “We developed mNGS-grade as a measurable quality framework based on lot-level testing and certification. By qualifying every lot and documenting background microflora, Micronbrane Medical provides the transparency needed for researchers and clinicians to separate background signals from true pathogens and to trust the accuracy of their results.”
The Micronbrane Medical Microbial DNA Enrichment Kit supports multiple genomic applications including mNGS, 16S rRNA sequencing, qPCR, and end-point PCR. By depleting host nucleated cells in the samples, it increases microbial composition by 10–1000 fold, reduces extraction time to 1.5 hours, and delivers high-yield DNA from both Gram-positive and Gram-negative bacteria.
The full article, Deciphering the impact of contaminating microbiota in DNA extraction reagents on metagenomic next-generation sequencing workflows (Lai Z-L, Su Y-D, Lin H-H, Wang S-Y, Lin Y-C, Liang S-J, Chen W-C, Hsueh P-R), was published online in Microbiology Spectrum on August 20, 2025.
Brand-to-Brand and Lot-to-Lot Variation: The Scope of the Problem
The contamination challenge extends well beyond a single problematic reagent batch. When researchers at CMUH systematically compared extraction kits from multiple manufacturers, heat map and principal component analysis (PCA) clustering revealed that each brand carried a distinct contaminating microflora profile. The contaminant signatures were non-overlapping between brands, confirming that the organisms were inherent to the manufacturing process rather than introduced from a shared laboratory environment.
Perhaps more concerning for laboratories that rely on consistent results, lot-to-lot variation within the same brand was substantial. Two lots of the same extraction kit produced measurably different contaminant profiles. This has a direct operational consequence: a no-template control processed with a different reagent lot than the test sample may fail to capture the relevant background organisms, leading to incorrect pathogen calls. The practical recommendation is that negative controls must always come from the same reagent lot as the test samples and should be processed simultaneously.
Practical Mitigation Strategies for Laboratories
For laboratories implementing or refining mNGS workflows, several evidence-based strategies can reduce the impact of reagent contamination on results:
- Use mNGS-grade reagents with lot-specific COAs. Reagents manufactured under stringent quality control and released with documented background microflora profiles allow laboratories to anticipate and subtract known contaminants. Micronbrane Medical’s mNGS-grade framework provides this transparency.
- Control surface and workflow contamination. Dedicated decontamination protocols, including nucleotide-removal tools such as XNA Decontaminating Spray, help reduce environmental nucleic-acid carryover before it enters the extraction workflow.
- Run lot-matched no-template controls (NTCs). Every extraction batch should include at least one NTC using the same reagent lot. This captures the specific contaminant fingerprint for that lot and enables accurate background subtraction during bioinformatics analysis.
- Implement spike-in process controls (SICP). Research at CMUH demonstrated that SICPs containing known organisms (such as Allobacillus halotolerans and Imtechella halotolerans) serve as both positive and negative controls without introducing additional contaminants. The spike-in organisms verify extraction and sequencing performance, while all other detected organisms represent reagent background.
- Apply multi-stage bioinformatics filtering. Raw sequencing output from clinical samples can produce hundreds of organism hits. Systematic filtering — applying minimum read thresholds, microbial sequence percentage cutoffs, system control subtraction, and computational filtering — can reduce hundreds of raw hits to just the true pathogens present in the sample.
Cross-site reproducibility testing showed that contaminant profiles were largely consistent between the manufacturer’s QC laboratory and the clinical site, meaning lot-specific COA data is broadly applicable regardless of where reagents are used.
For a detailed walkthrough of the CMUH study data and bioinformatics filtering approach, see How DNA Extraction Reagent Contamination Distorts mNGS.
Related reading: Study Identifies Key Contamination Sources in mNGS | mNGS Data Analysis
About Micronbrane Medical
Micronbrane Medical is a life science start up that develops metagenomic Next-Generation Sequencing (mNGS) enabling technologies. The company’s proprietary technologies reduce contamination, complexity and the costs associated with mNGS workflows, including specialized collection devices, novel host depletion, mNGS-grade reagents, advanced metagenomic sequencing assays, automation instruments plus rapid bioinformatic analysis software. Headquartered in Taiwan and Singapore, the company has partnerships and collaborations with leading academic institutions, health systems, and clinical laboratories worldwide, underscoring its commitment to making mNGS more accessible and affordable. For more information visit Micronbrane Medical.
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