Hello, we would like to perform metabolite prediction using MelonnPan.
Our data is an OTU table with 16S nucleotide sequences, and I would like to use this table for metabolite prediction. I have learned from the tutorial and this forum that MelonnPan does not accept nucleotide sequences, but Uniref90, which is a protein sequence. To use MelonnPan, I downloaded the UniRef90 reference and tried to use Blast+ package to annotate the 16S nucleotide sequences based on Uniref90, but it has been challenging.
Are there any resources that I should look at for annotating the 16S nucleotide sequence to UniRef to use MelonnPan? I appreciate any advice from you.
Hi @seibikobara - there are multiple avenues to use MelonnPan and not surprisingly, some of them are easier than others.
First of all, if you have paired metabolites and microbiome data, you can always use the MelonnPan-Train workflow and apply the trained model to new microbiome samples to predict metabolites. This particular avenue does not depend on Uniref90 annotation and likewise, is reference-agnostic.
Second, for the situation above when you have paired metabolites and microbiome data, you can also perform function prediction using PICRUSt and then use the PICRUSt output as input to perform metabolite prediction using other tools such as MIMOSA or using MelonnPan similar to the first avenue mentioned above.
Third, if you don’t have paired metabolites and microbiome data, you may perform function prediction using PICRUSt but it is not possible to convert KOs to UniRef90s since that mapping is one-to-many as discussed here.
We will have a future MelonnPan version that will eventually support non-Uniref90 input, but as of yet, MelonnPan is limited to UniRef90’s for prediction using the default trained model or without re-training a model.
All the best,
Hi @himel.mallick, i have a related question.
Is it possible to predict metabolites using HUMAnN3 generated genefamily data with default trained model?
Hi @himel.mallick, thank you so much for your great input. I came to recognize that the next step is using MIMOSA to predict metabolites prediction.
I am looking forward to the new feature of MelonnPan which accepts non-UniRef annotation, but I appreciate your support, by which I found the next step.
It might be possible with the caveat that the default model was trained with version 2 but in general, as long as you have sufficient matching UniRef90s across versions, you can use the default model.
Thanks a bunch,