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MicFunPred: A conserved approach to predict functional profiles from 16S rRNA gene sequence data

Existing imputed metagenome prediction tools uses variable regions of 16S rRNA gene sequence (OTUs/ASVs) to predict the gene content (gene copy numbers) at OTU/ASV level. This means, all existing tools try to assign species or strain level taxonomy to each ASVs/OTUs. Given the fact that, sometimes not only variable region but itself full length of 16S rRNA gene sequence is unable to identify organisms at species level.

Hence, most of the microbiome research or studies restrict the whole analysis upto genus level taxonomy. In such cases, predictions of imputed metagenomes based on variable regions of 16S rRNA gene would give many false positive (wrongly predicted as present) genes.

We have developed "MicFunPred", which shows low False Positive Rate (FPR) and similar True Positive Rate (TPR) as copared to these tools. MicFunPred uses a set of core genes predicted at the genus level to derive imputed metagenomes with minimal false positive predictions. MicFunPred predicts a set of core genes using ~32,000 reference IMG permanent/finished draft genomes. On simulated datasets, MicFunPred showed the lowest False Positive Rate (FPR) with mean Spearman’s correlation of 0.89 (SD=0.03) while on 7 different real datasets the mean correlation was 0.75 (SD=0.08). MicFunPred was found to be faster with low computational requirements and performed better or comparable when compared with other tools.

MicFunPred can predict metagenomes in terms of Kegg Orthology (KO), Cluster Of Genes (COG), CAZymes, TIGRFAM, Enzyme Commission (EC), and Protein Family (Pfam).

Citation/Reference

Mongad, D. S., Chavan, N. S., Narwade, N. P., Dixit, K., Shouche, Y. S., & Dhotre, D. P. (2021). MicFunPred: A conserved approach to predict functional profiles from 16S rRNA gene sequence data. Genomics, 113(6), 3635-3643.