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bioRxiv · 10.1101/2021.06.17.448865

Metagenome-based comparisons of decay rates and host-specificity of fecal microbial communities for improved microbial source tracking

Abstract

Fecal material in the environment is a primary source of pathogens that cause waterborne diseases and affect over a billion people worldwide. Microbial source tracking (MST) assays based on single genes (e.g., 16S rRNA) do not always provide the resolution needed to attribute fecal contamination sources. In this work, we used dialysis bag mesocosms simulating a freshwater habitat that were spiked separately with cow, pig, or human feces to monitor the decay of host-specific fecal signals over time with metagenomics, traditional qPCR, and culture-based methods. Sequencing of the host fecal communities used as inocula recovered 79 non-redundant metagenome-assembled genomes (MAGs) whose abundance patterns showed that the majority of the fecal community signal was not detectable in the mesocosm metagenomes after four days. Several MAGs showed high host specificity, and thus are promising candidates for biomarkers for their respective host type. Traditional qPCR methods varied in their correlation with MAG decay kinetics. Notably, the human-specific Bacteroides assay, HF183/BFDRev, consistently under-estimated fecal pollution due to not being present in all hosts and/or primer mismatches. This work provides new insights on the persistence and decay kinetics of host-specific gut microbes in the environment and identifies several MAGs as putative biomarkers for improved MST. SYNOPSISWe track cow, pig, and human fecal pollution in lake water over time with metagenomics and benchmark these novel protocols against standard culture-based and qPCR tests for water quality monitoring.

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BibTeXRIS

Suttner, B., Lindner, B. G., Kim, M., Conrad, R. E., Rodriguez, L. M., Orellana, L. H., Johnston, E. R., Hatt, J. K., Zhu, K. J., Brown, J., Konstantinidis, K. T.. 2021-06-17. Metagenome-based comparisons of decay rates and host-specificity of fecal microbial communities for improved microbial source tracking. https://doi.org/10.1101/2021.06.17.448865

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