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| Item Type: | Article |
|---|---|
| Title: | Mitigation and detection of putative microbial contaminant reads from long-read metagenomic datasets |
| Creators Name: | Ayala-Montaño, Stefany, Afolayan, Ayorinde O., Kociurzynski, Raisa, Löber, Ulrike and Reuter, Sandra |
| Abstract: | Metagenomic sequencing of clinical samples has significantly enhanced our understanding of microbial communities. However, microbial contamination and host-derived DNA remain a major obstacle to accurate data interpretation. Here, we present a methodology called 'Stop-Check-Go' for detecting and mitigating contaminants in metagenomic datasets obtained from neonatal patient samples (nasal and rectal swabs). This method incorporates laboratory and bioinformatics work combining a prevalence method, coverage estimation and microbiological reports. We compared the 'Stop-Check-Go' decontamination system with other published decontamination tools and commonly found poor performance in decontaminating microbiologically negative patients (false positives). We emphasize that host DNA decreased by an average of 76% per sample using a lysis method and was further reduced during post-sequencing analysis. Microbial species were classified as putative contaminants and assigned to 'Stop' in nearly 60% of the dataset. The 'Stop-Check-Go' system was developed to address the specific need of decontaminating low-biomass samples, where existing tools primarily designed for short-read metagenomic data showed limited performance. |
| Keywords: | Contamination, Enterobacterales, Genomic Surveillance, Long-Read Sequencing, Metagenomes, Nanopore |
| Source: | Microbial Genomics |
| ISSN: | 2057-5858 |
| Publisher: | Microbiology Society |
| Volume: | 12 |
| Number: | 1 |
| Page Range: | 001609 |
| Date: | 22 January 2026 |
| Official Publication: | https://doi.org/10.1099/mgen.0.001609 |
| PubMed: | View item in PubMed |
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