BioSIFTR infers gut microbiome functions from shallow sequencing

BioSIFTR estimates microbial functions from shallow shotgun sequencing by mapping sequencing reads to precalculated functions in biome-specific genome catalogues. Benchmarked on synthetic communities and gut microbiomes from red junglefowl, mice and humans, the software outperformed similar functional-inference approaches. The study reports validation in gut microbiomes and identifies broader validation as a priority for future work.

Shallow shotgun sequencing can accurately profile microbiomes, but its limited sequencing depth restricts functional analysis. BioSIFTR addresses this constraint by extrapolating from the reads obtained in shallow datasets to functional information represented in pangenome catalogues. The software draws on 15 MGnify biome-specific catalogues spanning host-associated and environmental microbiomes.

Its workflow maps observed reads against the catalogue selected for the relevant biome and infers functions from the mapped sequence information. Because the inferred output is tied to the functions represented in the selected catalogue, the analysis is an inference based on available reference genomes rather than a direct measurement of every function present in the sampled microbiome. The study evaluated BioSIFTR using synthetic microbial communities and three gut microbiome datasets: red junglefowl, mouse and human.

Each gut dataset was tested with matched deep shotgun sequencing and 16S rRNA metabarcoding data. According to the study abstract, BioSIFTR outperformed similar approaches in these benchmarks. The supplied evidence does not identify the competing methods, numerical performance measures or the detailed results for each benchmark dataset.

The current results support BioSIFTR as a practical method for inferring microbiome functions from shallow shotgun sequencing, with reported validation focused on gut microbiomes. The authors state that further validation will require matched benchmark datasets and describe this work as a priority for future research.

Subject of Research: Functional inference from shallow shotgun sequencing using biome-specific genome catalogues

Article Title: BioSIFTR: functional inference from shallow shotgun sequencing using biome-specific genome catalogues benchmarked in gut microbiomes

Article References: Escobar-Zepeda, A., Ruuskanen, M. O., Beracochea, M., Lu, J., Mongad, D., Richardson, L., Finn, R. D., & Lahti, L. (2026). BioSIFTR: functional inference from shallow shotgun sequencing using biome-specific genome catalogues benchmarked in gut microbiomes. Genome Biology. https://doi.org/10.1186/s13059-026-04303-8

Image Credits: AI Generated

DOI: 10.1186/s13059-026-04303-8

Keywords: BioSIFTR, microbiome, shallow shotgun sequencing, functional inference, pangenome catalogues, gut microbiomes, metagenomics, bioinformatics, MGnify, synthetic communities, functional, inference