AMR and Virulence Factors

Overview

After preparing the eight assembly files, we can screen the genomes for antimicrobial resistance genes and virulence factors.

In this lesson, we will use ABRicate to screen assembly FASTA files against two databases:

ncbi for antimicrobial resistance genes
vfdb for virulence factor genes

Learning objectives

By the end of this lesson, you should be able to:

activate the amr environment
create an output directory for ABRicate results
run ABRicate on multiple assembly files
identify antimicrobial resistance genes
identify virulence factor genes
summarise ABRicate results across samples

Input files

In the previous lesson, we copied eight filtered assembly files into the assemblies directory.

Check that the files are present:

ls assemblies

You should see files such as:

S1_contigs_filtered.fasta
S2_contigs_filtered.fasta
S3_contigs_filtered.fasta
S4_contigs_filtered.fasta
S5_contigs_filtered.fasta
S6_contigs_filtered.fasta
S7_contigs_filtered.fasta
S8_contigs_filtered.fasta

Count the number of assembly files:

ls assemblies/*_contigs_filtered.fasta | wc -l

The expected number is:

Important

For this lesson, we will screen all filtered assembly files:

assemblies/*_contigs_filtered.fasta

Activate the AMR environment

Activate the amr environment:

conda activate amr

Check that ABRicate is available:

abricate --version

You will see:

abricate 1.4.0

Check available ABRicate databases:

abricate --list

Example ABRicate database list

After running:

abricate --list

you may see output like this:

DATABASE        SEQUENCES  DBTYPE  DATE
ecoli_vf        2701       nucl    2026-Apr-3
ncbi            8232       nucl    2026-Apr-3
vfdb            4592       nucl    2026-Apr-3
argannot        2224       nucl    2026-Apr-3
upec_expec_vf   77         nucl    2026-Apr-3
resfinder       3206       nucl    2026-Apr-3
card            6052       nucl    2026-Apr-3
plasmidfinder   488        nucl    2026-Apr-3
bacmet2         746        prot    2026-Apr-3
ecoh            597        nucl    2026-Apr-3
victors         4545       nucl    2026-Apr-3
megares         6635       nucl    2026-Apr-3

Interpreting the database list

Column	Meaning
`DATABASE`	Name of the ABRicate database
`SEQUENCES`	Number of sequences in the database
`DBTYPE`	Database type, usually nucleotide (`nucl`) or protein (`prot`)
`DATE`	Date when the database was last updated

For this lesson, we will mainly use:

Analysis	Database
AMR gene screening	`ncbi`
Virulence factor screening	`vfdb`
Plasmid screening	`plasmidfinder`

Create output directory

Create a directory named abricate:

mkdir -p abricate

Check that the directory was created:

ls

you will see:

abricate  
annotation  
assemblies  
classify

Run ABRicate for AMR genes

Run ABRicate using the ncbi database:

abricate \
  --db ncbi \
  --threads 4 \
  assemblies/*_contigs_filtered.fasta \
  > abricate/amr.tsv

Understanding the AMR command

Option	Meaning
`abricate`	Runs ABRicate
`--db ncbi`	Uses the NCBI AMR database
`--threads 4`	Uses 4 CPU threads
`assemblies/*_contigs_filtered.fasta`	Screens all filtered assembly files
`>`	Redirects output to a file
`abricate/amr.tsv`	AMR output table

Check AMR output

Check that the output file was created:

ls abricate

Output:

amr.tsv

View the first few lines:

head abricate/amr.tsv

Exercise

Open abricate/amr.tsv.

Which AMR genes are detected in sample S1?

Summarise AMR results

Create a summary table for AMR genes:

abricate --summary abricate/amr.tsv > abricate/amr_summary.tsv

ls abricate

Output:

amr.tsv  amr_summary.tsv

View the summary:

cat abricate/amr_summary.tsv

you may see output like this:

#FILE                                   NUM_FOUND  almE    almF    almG    catB9   dfrA1   dfrA31  qnrVC5  varG
assemblies/S1_contigs_filtered.fasta    5          100.00  100.00  100.00  100.00  .       .       .       100.00
assemblies/S2_contigs_filtered.fasta    5          100.00  100.00  100.00  .       .       100.00  100.00  .
assemblies/S3_contigs_filtered.fasta    6          100.00  100.00  100.00  100.00  100.00  .       .       100.00
assemblies/S4_contigs_filtered.fasta    5          100.00  100.00  100.00  100.00  .       .       .       100.00
assemblies/S5_contigs_filtered.fasta    3          100.00  100.00  100.00  .       .       .       .       .
assemblies/S6_contigs_filtered.fasta    4          100.00  100.00  100.00  .       .       .       .       100.00
assemblies/S7_contigs_filtered.fasta    4          100.00  100.00  100.00  .       .       .       .       100.00
assemblies/S8_contigs_filtered.fasta    5          100.00  100.00  100.00  100.00  .       .       .       100.00

Interpreting the AMR summary

Each row represents one genome assembly.

Each column after NUM_FOUND represents an AMR-associated gene detected by ABRicate.

Column	Meaning
`#FILE`	Input assembly file
`NUM_FOUND`	Number of AMR genes detected in that assembly
Gene columns	Percentage identity or coverage reported for each detected gene
`.`	Gene was not detected in that assembly

In this example, all samples contain:

almE
almF
almG

These genes were detected at 100.00 in all eight assemblies.

Summary of AMR gene presence

Sample	Number of genes detected	Genes detected
`S1`	5	`almE`, `almF`, `almG`, `catB9`, `varG`
`S2`	5	`almE`, `almF`, `almG`, `dfrA31`, `qnrVC5`
`S3`	6	`almE`, `almF`, `almG`, `catB9`, `dfrA1`, `varG`
`S4`	5	`almE`, `almF`, `almG`, `catB9`, `varG`
`S5`	3	`almE`, `almF`, `almG`
`S6`	4	`almE`, `almF`, `almG`, `varG`
`S7`	4	`almE`, `almF`, `almG`, `varG`
`S8`	5	`almE`, `almF`, `almG`, `catB9`, `varG`

Questions

Question 1

Which sample has the highest number of AMR genes detected?

We can also visualize the amr_summary.tsv in a heatmap using a custop python/R script.

Note

We will share the script with you later this training session so you can understand how to visualize an AMR dataset

Figure 1: AMR gene heatmap for all 8 samples

Question 2

Which AMR genes are found in all eight samples?

Question 3

Which sample contains qnrVC5?

Question 4

Which samples contain catB9?

Run ABRicate for virulence factors

Run ABRicate using the vfdb database:

abricate \
  --db vfdb \
  --threads 4 \
  assemblies/*_contigs_filtered.fasta \
  > abricate/vf.tsv

Understanding the virulence factor command

Option	Meaning
`--db vfdb`	Uses the virulence factor database
`assemblies/*_contigs_filtered.fasta`	Screens all filtered assembly files
`abricate/vf.tsv`	Virulence factor output table

Check virulence factor output

View the first few lines:

ls abricate

You should now have:

amr.tsv
amr_summary.tsv
vf.tsv

View the first few lines:

head abricate/vf.tsv

you may see output like this:

#FILE   SEQUENCE    START   END STRAND  GENE    COVERAGE    COVERAGE_MAP    GAPS    %COVERAGE   %IDENTITY   DATABASE    ACCESSION   PRODUCT RESISTANCE
assemblies/S1_contigs_filtered.fasta    NODE_15_length_78481_cov_84.780315  182 556 -   ctxB    1-375/375   =============== 0/0 100.00  99.47   vfdb    WP_000593522    (ctxB) cholera enterotoxin B subunit [CT (VF0128) - Exotoxin (VFC0235)] [Vibrio cholerae O1 biovar El Tor str. N16961]  
assemblies/S1_contigs_filtered.fasta    NODE_15_length_78481_cov_84.780315  553 1329    -   ctxA    1-777/777   =============== 0/0 100.00  100.00  vfdb    WP_001881225    (ctxA) cholera enterotoxin A subunit [CT (VF0128) - Exotoxin (VFC0235)] [Vibrio cholerae O1 biovar El Tor str. N16961]  
assemblies/S1_contigs_filtered.fasta    NODE_15_length_78481_cov_84.780315  1428    2627    -   zot 1-1200/1200 =============== 0/0 100.00  100.00  vfdb    WP_000021616    (zot) zona occludens toxin [Zot (VF0129) - Exotoxin (VFC0235)] [Vibrio cholerae O1 biovar El Tor str. N16961]   
assemblies/S1_contigs_filtered.fasta    NODE_15_length_78481_cov_84.780315  2624    2917    -   ace 1-294/294   =============== 0/0 100.00  100.00  vfdb    WP_000979342    (ace) accessory cholera enterotoxin [Ace (VF0130) - Exotoxin (VFC0235)] [Vibrio cholerae O1 biovar El Tor str. N16961]  
assemblies/S1_contigs_filtered.fasta    NODE_15_length_78481_cov_84.780315  56878   58047   +   cqsA    1-1170/1170 =============== 0/0 100.00  99.92   vfdb    WP_001039912    (cqsA) CAI-1 autoinducer synthase [CAI-1 (VF0405) - Biofilm (VFC0271)] [Vibrio cholerae O1 biovar El Tor str. N16961]   
assemblies/S1_contigs_filtered.fasta    NODE_17_length_73937_cov_105.952587 16160   18172   +   mshH    1-2013/2013 ========/====== 2/2 99.95   99.85   vfdb    WP_164923315    (mshH) MSHA biogenesis protein MshH [MSHA pili (VF0515) - Adherence (VFC0001)] [Vibrio cholerae O1 biovar El Tor str. N16961]   
assemblies/S1_contigs_filtered.fasta    NODE_17_length_73937_cov_105.952587 18185   19624   +   mshI    1-1440/1440 =============== 0/0 100.00  100.00  vfdb    WP_000743253    (mshI) MSHA biogenesis protein MshI [MSHA pili (VF0515) - Adherence (VFC0001)] [Vibrio cholerae O1 biovar El Tor str. N16961]   
assemblies/S1_contigs_filtered.fasta    NODE_17_length_73937_cov_105.952587 19621   20271   +   mshJ    1-651/651   =============== 0/0 100.00  100.00  vfdb    WP_000835144    (mshJ) MSHA biogenesis protein MshJ [MSHA pili (VF0515) - Adherence (VFC0001)] [Vibrio cholerae O1 biovar El Tor str. N16961]   
assemblies/S1_contigs_filtered.fasta    NODE_17_length_73937_cov_105.952587 20264   20581   +   mshK    1-318/318   =============== 0/0 100.00  100.00  vfdb    WP_000252812    (mshK) MSHA biogenesis protein MshK [MSHA pili (VF0515) - Adherence (VFC0001)] [Vibrio cholerae O1 biovar El Tor str. N16961]

Interpreting the virulence factor result

Each row represents one virulence factor hit detected in the assembly.

Column	Meaning
`#FILE`	Input assembly file
`SEQUENCE`	Contig where the virulence gene was detected
`START`	Start position of the hit on the contig
`END`	End position of the hit on the contig
`STRAND`	DNA strand of the hit, either `+` or `-`
`GENE`	Virulence-associated gene detected
`%COVERAGE`	Percentage of the reference gene covered by the hit
`%IDENTITY`	Percentage identity between query and reference
`DATABASE`	Database used for screening
`PRODUCT`	Description of the detected virulence factor

Key virulence genes detected in this example

Gene	Product or role
`ctxB`	Cholera enterotoxin B subunit
`ctxA`	Cholera enterotoxin A subunit
`zot`	Zona occludens toxin
`ace`	Accessory cholera enterotoxin
`cqsA`	CAI-1 autoinducer synthase
`mshH`	MSHA biogenesis protein MshH
`mshI`	MSHA biogenesis protein MshI
`mshJ`	MSHA biogenesis protein MshJ
`mshK`	MSHA biogenesis protein MshK

Interpretation

In this example, sample S1 contains several important virulence-associated genes.

The genes:

ctxA
ctxB
zot
ace

are located on the same contig:

NODE_15_length_78481_cov_84.780315

These genes are associated with cholera toxin and related toxin elements.

The genes:

mshH
mshI
mshJ
mshK

are located on another contig:

NODE_17_length_73937_cov_105.952587

These genes are associated with MSHA pili, which are involved in adherence.

Question 1

Which cholera toxin genes are detected in this example?

Question 2

Which genes are found on NODE_15_length_78481_cov_84.780315?

Question 3

Which virulence genes are associated with MSHA pili in this example?

Question 4

Which database was used for this virulence factor screening?

Summarise virulence factor results

Create a summary table for virulence factor genes:

abricate --summary abricate/vf.tsv > abricate/vf_summary.tsv

View the summary:

head abricate/vf_summary.tsv

Note

We will not understand by simply viewing the file using head command in terminal since the file is very large. So will download –> filter –> organize –> visualize.

Figure 2: VF gene heatmap for all 8 samples

Now we will deactivate the environment

conda deactivate

Download ABRicate results from the server

If you are working on a remote server, download the annotation folder to your local computer.

From your local desktop terminal, run:

scp -r genomevm@172.28.28.12:~/tanzim/abricate .

scp -r genomevm@172.28.28.12:~/tanzim/`abricate` .

If you are working on a remote server, download the ABRicate results to your local computer.

From your local desktop terminal, run:

scp -r genomevm@172.28.28.12:~/tanzim/abricate/*summary.tsv .

scp -r genomevm@172.28.28.12:~/tanzim/abricate/`*summary.tsv` .

Final directory structure

At the end of this lesson, your directory should look like this:

.
├── assemblies
│   ├── S1_contigs_filtered.fasta
│   ├── S2_contigs_filtered.fasta
│   ├── S3_contigs_filtered.fasta
│   ├── S4_contigs_filtered.fasta
│   ├── S5_contigs_filtered.fasta
│   ├── S6_contigs_filtered.fasta
│   ├── S7_contigs_filtered.fasta
│   └── S8_contigs_filtered.fasta
└── abricate
    ├── amr.tsv
    ├── amr_summary.tsv
    ├── vf.tsv
    └── vf_summary.tsv

Practical exercise

Complete the following tasks:

Activate the amr environment.
Run ABRicate using the ncbi database.
Save the output as abricate/amr.tsv.
Run ABRicate using the vfdb database.
Save the output as abricate/vf.tsv.
Create summary files for both results.
Compare AMR and virulence factor profiles across the eight samples.

Exercise: AMR and virulence summary

Create a small table in your notes:

Sample	AMR genes detected	Virulence factors detected	Comment
S1
S2
S3
S4
S5
S6
S7
S8

Use:

abricate/amr_summary.tsv
abricate/vf_summary.tsv

to fill in the table.

Optional: plasmid screening

If a plasmid database is available in your ABRicate installation, you can also screen for plasmid-associated sequences.

First, check available databases:

abricate --list

If plasmidfinder is available, run:

abricate \
  --db plasmidfinder \
  --threads 4 \
  assemblies/*_contigs_filtered.fasta \
  > abricate/plasmid.tsv

Create a summary:

abricate --summary abricate/plasmid.tsv > abricate/plasmid_summary.tsv

Note

Only run plasmid screening if the required database is installed and available in abricate --list.

Key points

Important

ABRicate screens genome assemblies against gene databases.
The ncbi database can be used for AMR gene screening.
The vfdb database can be used for virulence factor screening.
Summary files make it easier to compare results across multiple samples.
The output files are stored in the abricate directory.

Next step

In the next lesson, we will use annotation files to perform pangenome analysis.