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Bacterial metatranscriptomes in wastewater can differentiate virally infected human populations

Salido, R. A.; Martino, C.; Karthikeyan, S.; Huang, S.; Rahman, G.; Gonzalez, A.; Zaramela, L. S.; Beck, K. L.; Bhute, S.; Cantrell, K.; Carrieri, A. P.; Farmer, S.; Haiminen, N.; Humphrey, G.; Kim, H.-C.; Parida, L.; Richter, R. A.; Vazquez-Baeza, Y.; Zengler, K.; Swafford, A.; Bartko, A.; Knight, R.

2022-02-24 microbiology
10.1101/2022.02.23.481658 bioRxiv
Show abstract

Monitoring wastewater samples at building-level resolution screens large populations for SARS-CoV-2, prioritizing testing and isolation efforts. Here we perform untargeted metatranscriptomics on virally-enriched wastewater samples from 10 locations on the UC San Diego campus, demonstrating that resulting bacterial taxonomic and functional profiles discriminate SARS-CoV-2 status even without direct detection of viral transcripts. Our proof-of-principle reveals emergent threats through changes in the human microbiome, suggesting new approaches for untargeted wastewater-based epidemiology.

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"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.