Build Status License: GPL v2 Don't judge me
Mass screening of contigs for antimicrobial resistance or virulence genes. It comes bundled with multiple databases: NCBI, CARD, ARG-ANNOT, Resfinder, MEGARES, EcOH, PlasmidFinder, Ecoli_VF and VFDB.
- It only supports contigs, not FASTQ reads
- It only detects acquired resistance genes, NOT point mutations
- It uses a DNA sequence database, not protein
- It needs BLAST+ >= 2.7 and
any2fastato be installed - It's written in Perl π«
If you are happy with the above, then please continue! Otherwise consider using Ariba, Resfinder, RGI, SRST2, AMRFinderPlus, etc.
% abricate 6159.fasta
Using database resfinder: 2130 sequences - Mar 17, 2017
Processing: 6159.fna
Found 3 genes in 6159.fna
#FILE SEQUENCE START END STRAND GENE COVERAGE COVERAGE_MAP GAPS %COVERAGE %IDENTITY DATABASE ACCESSION PRODUCT RESISTANCE
6159.fna NC_017338.1 39177 41186 + mecA_15 1-2010/2010 =γ=γ=γ=γ=γ=γ=γ=γ=γ=γ=γ=γ=γ=γ=γ 0/0 100.00 100.000 ncbi AB505628 n/a FUSIDIC_ACID
6159.fna NC_017338.1 727191 728356 - norA_1 1-1166/1167 =γ=γ=γ=γ=γ=γ=γ=γ=γ=γ=γ=γ=γ=γ=γ 0/0 99.91 92.367 ncbi M97169 n/a FOSFOMYCIN
6159.fna NC_017339.1 10150 10995 + blaZ_32 1-846/846 =γ=γ=γ=γ=γ=γ=γ=γ=γ=γ=γ=γ=γ=γ=γ 0/0 100.00 100.000 ncbi AP004832 betalactamase BETA-LACTAM;PENICILLIN
If you are using the MacOS Homebrew or LinuxBrew packaging system:
brew install brewsci/bio/abricate
abricate --check
abricate --list
If you use Conda follow the instructions to add the Bioconda channel:
conda install -c conda-forge -c bioconda -c defaults abricate
abricate --check
abricate --list
If you install from source, Abricate has the following package dependencies:
any2fastafor sequence file format conversion- BLAST+ >2.7.0 for
blastn,makeblastdb,blastdbcmd - Perl modules:
LWP::Simple,Bio::Perl,JSON,Path::Tiny git,unzip,gzipfor updating databases
Most of these are easy to install on an Ubuntu-based system:
sudo apt-get install bioperl ncbi-blast+ gzip unzip git \
libjson-perl libtext-csv-perl libpath-tiny-perl liblwp-protocol-https-perl libwww-perl
git clone https://github.com/tseemann/abricate.git
./abricate/bin/abricate --check
./abricate/bin/abricate --setupdb
./abricate/bin/abricate ./abricate/test/assembly.fa
Abricate takes any sequence file that any2fasta can convert to FASTA files (eg. Genbank,
EMBL), and they can be optionally gzip or bzip2 compressed.
abricate assembly.fa
abricate assembly.fa.gz
abricate assembly.gbk
abricate assembly.gbk.bz2
It can take multiple files at once too:
abricate assembly.*
abricate /mnt/ncbi/bacteria/*.gbk.gz
Or you can provide it a "file of file names" (a "FOFN"):
% cat test/fofn.txt
assembly.fa
assembly.fa.gz
assembly.gbk
assembly.gbk.bz2
% abricate --fofn test/fofn.txt
It does not accept raw FASTQ reads; please use Ariba or SRTS2 for that.
Abricate produces a tap-separated output file with the following columns:
| Column | Example | Description |
|---|---|---|
| FILE | Ecoli.fna |
The filename this hit came from |
| SEQUENCE | contig000324 |
The sequence in the filename |
| START | 23423 |
Start coordinate in the sequence |
| END | 24117 |
End coordinate |
| STRAND | + |
Strand + or - |
| GENE | tet(M) |
AMR gene name |
| COVERAGE | 1-1920/1920 |
What proportion of the gene is in our sequence |
| COVERAGE_MAP | =============== |
A visual represenation of the hit. ==aligned, .=unaligned, /=has_gaps |
| GAPS | 1/4 |
Openings / gaps in subject and query - possible psuedogene? |
| %COVERAGE | 100.00% |
Proportion of gene covered |
| %IDENTITY | 99.95% |
Proportion of exact nucleotide matches |
| DATABASE | ncbi |
The database this sequence comes from |
| ACCESSION | NC_009632:49744-50476 |
The genomic source of the sequence |
| PRODUCT | aminoglycoside O-phosphotransferase APH(3')-IIIa |
Gene product (if available) |
| RESISTANCE | TETRACYCLINE;FUSIDIC_ACID |
putative antibiotic resistance phenotype, ;-separated |
- Does not find mutational resistance, only acquired genes.
- Gap reporting incomplete
- Sometimes two heavily overlapping genes will be reported for the same locus
- Possible coverage calculation issues
ABRicate comes with some pre-downloaded databases:
You can check what you have installed with the --list command.
This lists the available databases in TSV (or CSV with --csv) and three
columns:
% abricate --list
DATABASE SEQUENCES DBTYPE DATE
argannot 1749 nucl 2019-Jul-28
card 2241 nucl 2019-Jul-28
ecoh 597 nucl 2019-Jul-28
ecoli_vf 2701 nucl 2019-Jul-28
megares 6635 nucl 2020-Feb-20
ncbi 4324 nucl 2019-Jul-28
plasmidfinder 263 nucl 2019-Jul-28
resfinder 2434 nucl 2019-Jul-28
vfdb 2597 nucl 2019-Jul-28
The default database is ncbi.
You can choose a different database using the --db option:
% abricate --db vfdb --quiet 6159.fa
6159.fna NC_017338.1 2724620 2726149 aur 1-1530/1530 =γ=γ=γ=γ=γ=γ=γ=γ=γ=γ=γ=γ=γ=γ=γ 0/0 100.00 99.346 vfdb NP_647375 zinc metalloproteinase aureolysin
6159.fna NC_017338.1 2766595 2767155 icaR 1-561/561 =γ=γ=γ=γ=γ=γ=γ=γ=γ=γ=γ=γ=γ=γ=γ 0/0 100.00 98.930 vfdb NP_647402 N-acetylglucosaminyltransferase
6159.fna NC_017338.1 2767319 2768557 icaA 1-1239/1239 =γ=γ=γ=γ=γ=γ=γ=γ=γ=γ=γ=γ=γ=γ=γ 0/0 100.00 99.677 vfdb NP_647403 n/a
6159.fna NC_017338.1 2768521 2768826 icaD 1-306/306 =γ=γ=γ=γ=γ=γ=γ=γ=γ=γ=γ=γ=γ=γ=γ 0/0 100.00 99.020 vfdb NP_647404 n/a
6159.fna NC_017338.1 2768823 2769695 icaB 1-873/873 =γ=γ=γ=γ=γ=γ=γ=γ=γ=γ=γ=γ=γ=γ=γ 0/0 100.00 99.542 vfdb NP_647405 n/a
6159.fna NC_017338.1 2769682 2770734 icaC 1-1053/1053 =γ=γ=γ=γ=γ=γ=γ=γ=γ=γ=γ=γ=γ=γ=γ 0/0 100.00 98.955 vfdb NP_647406 n/a
6159.fna NC_017338.1 2771040 2773085 lip 1-2046/2046 =γ=γ=γ=γ=γ=γ=γ=γ=γ=γ=γ=γ=γ=γ=γ 0/0 100.00 98.778 vfdb NP_647407 triacylglycerol lipase precursor
ABRicate can combine results into a simple matrix of gene presence/absence.
An absent gene is denoted . and a present gene is represented by its '%COVERAGE`.
This can be individual abricate reports, or a combined one.
# Run abricate on each .fa file
% abricate 1.fna > 1.tab
% abricate 2.fna > 2.tab
# Combine
% abricate --summary 1.tab 2.tab
#FILE NUM_FOUND aac(6')-aph(2'')_1 aadD_1 blaZ_32 blaZ_36 erm(A)_1 mecA_15 norA_1 spc_1 tet(M)_7
1.tab 8 100.00 100.00 . 100.00 100.00 100.00 99.91 100.00 100.00
2.tab 3 . . 100.00 . . 100.00 99.91 . .
Or if you ran everything in a single report, it will work too.
% abricate *.fna > results.tab
% abricate --summary results.tab > summary.tab
# force download of latest version
% abricate-get_db --db ncbi --force
# re-use existing download and just regenerate the database
% abricate-get_db --db ncbi
Let's say you want to make your own database called tinyamr.
All you need is a FASTA file of nucleotide sequences, say tinyamr.fa.
Ideally the sequence IDs would have the format >DB~~~ID~~~ACC~~~RESISTANCES DESC
where DB is tinyamr, ID is the gene name, ACC is an accession
number of the sequence source, RESISTANCES is the phenotype(s) to report,
and DESC can be any textual description.
% cd /path/to/abricate/db # this is the --datadir default option
% mkdir tinyamr
% cp /path/to/tinyamr.fa sequences
% head -n 1 sequences
>tinyamr~~~GENE_ID~~~GENE_ACC~~RESISTANCES some description here
% abricate --setupdb
% # or just do this: makeblastdb -in sequences -title tinyamr -dbtype nucl -hash_index
% abricate --list
DATABASE SEQUENCES DBTYPE DATE
tinyamr 173 nucl 2019-Aug-28
% abricate --db tinyamr screen_this.fasta
The name "ABRicate" was chosen as the first 3 letters are a common acronym for "Anti-Biotic Resistance". It also has the form of an English verb, which suggests the tool actual taking "action" against the problem of antibiotic resistance. It is also relatively unique in Google, and is unlikely to receive an infamous JABBA Award.
If you publish the results of Abricate please cite both the software and
the appropriate database you used with --db
- Seemann T, Abricate, Github
https://github.com/tseemann/abricate - NCBI AMRFinderPlus - doi: 10.1128/AAC.00483-19
- CARD - doi:10.1093/nar/gkw1004
- Resfinder - doi:10.1093/jac/dks261
- ARG-ANNOT - doi:10.1128/AAC.01310-13
- VFDB - doi:10.1093/nar/gkv1239
- PlasmidFinder - doi:10.1128/AAC.02412-14
- EcOH - doi:10.1099/mgen.0.000064
- MEGARES 2.00 - doi:10.1093/nar/gkz1010
Please report problems to the Issues Page.
Torsten Seemann | @torstenseemann | blog