Predicting pathogenic features (AMR, Virulence factors, Plasmids) (via UNIX/conda)

• In this worksheet you will learn how predict a range of pathogenic features such as antimicrobial resistance and virulence factors (abritAMR), and plasmid presence (PlasmidFinder)
• This is two separate analyses but use similar inputs

Suggested prerequisites

• It is recommended that you have followed the Concepts in Computer Programming and UNIX tutorial (basics) tutorials before starting.
• A knowledge of the two primary tools is useful. You can access their manuals here: abritAMR, PlasmidFinder
• Installing abritAMR and PlasmidFinder through conda is easiest so its suggested you have followed the Setting up and using conda tutorial.

Dataset

• This demonstration uses the output of Assembling a genome from short reads (e.g. Illumina) using SPAdes worksheet but this will work on any assembly, such as that created in the Assembling a genome from long reads (e.g. ONT) using Flye worksheet. Thus, it is suggested you run at least one of these assembly methods first.
  • You can download the example scaffolds output file of the SPAdes worksheet here: DRR187559_scaffolds.fasta

AMR and virulence factor prediction (ABRitamr steps)

1. Create a directory for your analyses and step into it

   mkdir pathogenesis_demo
   cd pathogenesis_demo
   

2. Copy your assembled genome into this folder or download the sample data
   • You can save this directly to your terminal current working directory by using the wget command (wget can be installed via conda).

wget https://conmeehan.github.io/PathogenDataCourse/Datasets/DRR187559_scaffolds.fasta

1. Install ABRitamr using conda
   • It is recommended to always install packages in their own environments so here will we create an enironment and install ABRitamr in one step.

     mamba create -n abritamr -c bioconda abritamr -y
     mamba activate abritamr
     

2. Run ABRitamr on the scaffolds file
   • The run command tells ABRitamr we wish to run the analysis (as opposed to the other pipeline which is to create a specific report)
   • -c is the genome assembly file
   • -px is the name of the folder to put all the output files in

     abritamr run -c DRR187559_scaffolds.fasta -px DRR187559_ABRitamr
     

3. Inside the resulting output folder you will find multiple files. Their contents are explained here

4. Deactivate your mamba environment when finished

   mamba deactivate
   

Plasmid detection (PlasmidFinder steps)

1. If you did not follow the abritAMR steps above, perform steps 1 and 2 now.
   • If you did, navigate into the pathogenesis_demo folder
2. Install PlasmidFinder using conda
   • It is recommended to always install packages in their own environments so here will we create an enironment and install PlasmidFinder in one step.

     mamba create -n plasmidfinder -c bioconda plasmidfinder -y
     mamba activate plasmidfinder
     

3. The database for PlasmidFinder must be downloaded. This is done with a built in programe that should be available in your PlasmidFinder conda environment
   • We will redirect some of the produced information to a log file (>plasmidfinder-db.log) for future use

     download-db.sh >plasmidfinder-db.log
     

4. Look in the plasmidfinder-db.log file for the location of the downloaded database

   cat plasmidfinder-db.log
   

• This will be listed after ‘Downloading PlasmidFinder 2.1 database to ‘ and before ‘…’
• e.g. on my computer it is /Users/cmeehan/opt/miniconda3/envs/plasmidfinder/share/plasmidfinder-2.1.6/database

1. Make an output directory for PlasmidFinder

   mkdir DRR187559_plasmidfinder
   

2. Run PlasmidFinder on the assembled genome

• -x tells PlasmidFinder to give us all (extended) output files
• -i is the input genome assembly file
• -o is the output directory created i step 5
• -p is the database file we downloaded in step 3, using the absolute path as noted down in step 4

plasmidfinder.py -x -i DRR187559_scaffolds.fasta -o DRR187559_plasmidfinder -p /Users/cmeehan/opt/miniconda3/envs/plasmidfinder/share/plasmidfinder-2.1.6/database

1. Get the information on contigs/scaffolds that may contain plasmids

• The results_tab.tsv file lists each plasmid the had a hit to a contig along with the length of the hit

• Be wary when interpreting these results and look carefully at the length of the plasmids (can view on NCBI website using the accessions listed at the end of each line)

  • Often short hits (<1kb) can occur erroneously to plasmids on contigs with similar genes; this does not mean there is a plasmid there (or that a plasmid is not there if you get such short hits)
  • Bad assemblies (i.e. large or messy assembly graphs in Bandage) can produce such results

cat DRR187559_plasmidfinder/results_tab.tsv

1. Deactivate your mamba environment when finished

   mamba deactivate