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Flush With Data (or) Optimizing and Validating the Efficacy of Free and Computationally Simple 16S Metabarcoding Approaches for Use in Wastewater Surveillance.

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Title: Flush With Data (or) Optimizing and Validating the Efficacy of Free and Computationally Simple 16S Metabarcoding Approaches for Use in Wastewater Surveillance.
Authors: Berta, Joe1 (AUTHOR) cberta@tulane.edu, Rowe, Lori A.2 (AUTHOR), Multala, Evan3 (AUTHOR), Garry, Robert F.4 (AUTHOR)
Source: Environmental Microbiology. May2026, Vol. 28 Issue 5, p1-15. 15p.
Subjects: Bacteria classification, Bioinformatics, Microbial diversity, Mathematical optimization, Genetic barcoding, Sewage microbiology
Abstract: We propose free and low‐computationally complex methods of 16S rRNA metabarcoding analysis, then optimized and validate their accuracy for wastewater bacterial surveillance. Three taxonomic analysis pipelines were augmented: NCBI BLAST subsampling, Kraken 2/Bracken and QIIME 2/DADA 2. Our optimization strategies for the high complexity of wastewater samples raised QIIME 2/DADA 2's sensitivity to species‐level taxa by 240.5%, while they increased the species‐level selectivity of Kraken 2/Bracken and NCBI BLAST subsampling by 18.7% and 79.1%, respectively. Optimization vastly lowered the read mapping error for BLAST subsampling and Kraken 2/Bracken, by 42.0% and 11.4%, respectively. Microbial community diversity estimates were also improved through our optimization strategies. Richness measurements for BLAST subsampling became 95.6% more accurate, while Kraken 2/Bracken and QIIME 2/DADA 2 improved by 2.2% and 37.8%. Shannon entropy estimates by BLAST subsampling increased in accuracy by 17.4%, while for Kraken 2/Bracken and QIIME 2/DADA 2 they increased by 19.7% and 41.4%. For beta diversity, Bray–Curtis dissimilarity estimates by QIIME 2/DADA 2 increased in accuracy by 8.5% and by Kraken 2/Bracken by 174.3%. [ABSTRACT FROM AUTHOR]
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Database: Engineering Source
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Abstract:We propose free and low‐computationally complex methods of 16S rRNA metabarcoding analysis, then optimized and validate their accuracy for wastewater bacterial surveillance. Three taxonomic analysis pipelines were augmented: NCBI BLAST subsampling, Kraken 2/Bracken and QIIME 2/DADA 2. Our optimization strategies for the high complexity of wastewater samples raised QIIME 2/DADA 2's sensitivity to species‐level taxa by 240.5%, while they increased the species‐level selectivity of Kraken 2/Bracken and NCBI BLAST subsampling by 18.7% and 79.1%, respectively. Optimization vastly lowered the read mapping error for BLAST subsampling and Kraken 2/Bracken, by 42.0% and 11.4%, respectively. Microbial community diversity estimates were also improved through our optimization strategies. Richness measurements for BLAST subsampling became 95.6% more accurate, while Kraken 2/Bracken and QIIME 2/DADA 2 improved by 2.2% and 37.8%. Shannon entropy estimates by BLAST subsampling increased in accuracy by 17.4%, while for Kraken 2/Bracken and QIIME 2/DADA 2 they increased by 19.7% and 41.4%. For beta diversity, Bray–Curtis dissimilarity estimates by QIIME 2/DADA 2 increased in accuracy by 8.5% and by Kraken 2/Bracken by 174.3%. [ABSTRACT FROM AUTHOR]
ISSN:14622912
DOI:10.1111/1462-2920.70276