Is there a command(s) to analyze miseq illumina 16S community profile data for the presence of antibiotic resistance or antibiotic producing genes?
We have already completed the 16S Microbial Analysis with mothur (extended) tutorial, but we would like to identify the presence of antibiotic resistance or antibiotic producing genes. If there is a way to run a few more command lines to determine this, we would greatly appreciate the help.
16S data contain sequences from rRNA cluster, not antibiotic resistance genes. It seems you need different type of data, whole metagenome sequencing data.
One of the option is a metagenome assembly followed by scan for antibiotic resistance genes. Galaxy Training Network has tutorials for both steps.
from a quick look, the paper you shared describes prediction of ARG from 16S data. Maybe I missed it, but I don’t see any validation of the prediction. The paper relies on Tax4fun. The software was wrapped for Galaxy (=available in the main Galaxy tool shed), but it is not maintained since 2017. The wrapper has no tests, plus there were some other issues with the wrapper, so, it was not installed to Galaxy Australia. I could not find it on Galaxy Europe, either. If you can find it on a public Galaxy server, you can try the protocol described in the paper. v.2 of Tax4fun was resealed in 2022. Maybe this version will be adapted for Galaxy at some point.
As for the tutorials: please check this section Galaxy Training! .
Thank you so much for your help. I am helping a undergraduate student with a project and we are learning as we go. I greatly appreciate your patience. So, I should be able to use my data to assemble metagenome and then do further analysis using the tutorials to look for args?
I think I am still confused about whether I can use this data for this process or not. The student would like to look for args so I’m trying to find some way to help them do that with the data that we have.
First, someone with experience in metagenomics might provide a better answer. Second, I have a semantic issue: 16S data does not contain ARGs, hence can be used only for prediction of ARGs, while detection of ‘ARG presence’ requires whole metagenomic data. I might be wrong here, and people consider prediction or extrapolation as a presence. Maybe this approach provides a good approximation, but it seems there is no validation or confirmation of this in the paper.