Microbial source tracking (MST) enables identification of fecal contamination sources in water, providing crucial support for water quality management and public health protection. PCR-based detection of host-associated markers remains a central approach in MST. However, the success of this method relies on designing assays that can accurately and efficiently amplify marker sequences. Here, we introduce MicrobiomePrime, the first fully automated bioinformatics pipeline that leverages k-mer based analysis to design highly sensitive and specific primer pairs for MST directly from any type of amplicon sequencing data. By automating this process, MicrobiomePrime streamlines assay development, enabling researchers and water quality laboratories to create novel MST assays without requiring extensive bioinformatics expertise. The pipeline was tested on 16S rRNA gene amplicon sequencing data from 715 animal fecal samples and 52 stored animal waste samples (manure and slurry), representing over 50 mammalian and avian species, along with 186 publicly available human fecal microbiome samples. Using this dataset, we designed a suite of novel MST assays targeting diverse fecal sources—including cattle, pig, dog, and nutria—as well as cattle and pig fecal waste, which are microbially distinct from fresh feces. In vitro validation of 51 assays resulted in high performance of multiple assays with 18 of them achieving exceptional, 100 % specificity, demonstrating the utility of MicrobiomePrime for developing robust MST assays. MicrobiomePrime is available on GitHub:
https://github.com/tanjazlender/MicrobiomePrime.
