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Description:

csstar 2.1.0

c-SSTAR
CLI-Sequence Search Tool for Antimicrobial Resistance

System Requirements

Linux or Mac OS X platform
BLAST+ (blastn and makeblastdb)
Python 2.7 or 3 with BioPython

Usage
c-SSTAR -g <genome_file> -d <database_file>

Input

FastA formatted genome
FastA database of antimicrobial resistance (AR) gene sequences from SSTAR. Two databases are available (ARG-ANNOT or ResFinder), which are formatted according to Kat Holt's clustering approach for SRST2. A combination of these two databases also exists "ResGANNOT"

Output
I) Summary output (to stdout)
A tab-delimited summary is printed to standard out with the following fields:

AR gene family (from database)
AR gene variant (from database)
sequence defline/header where the AR gene is located (from genome)
% nucleotide identity (from blastn output)
bp length of alignment (from blastn output)
bp length of AR gene (from blastn output)

Columns 1 and 2 will have suffixes appended to denote special interest:

* indicates the best scoring allele is full-length but has >=1 mismatch (SNP). This often means you have a novel allele.
? indicates uncertainty in the result due to incomplete length alignment
TR indicates truncation due to an internal stop codon being present
$ indicates gene detected at edge of contig

II) Raw alignment output (OUTDIR/BASENAME.blastn.tsv)
The tab-delimited outfmt 6 of blast is saved with three columns added to the right. Column 13 is the query (AR gene database) length, column 14 is the subject (contig) length, and column 15 is the subject (contig's AR gene) sequence.
III) Log output (OUTDIR/c-SSTAR_BASENAME.log)
A text file is generated to log the date and time of execution, user ID, shell environment, python version, blastn binary location, and blastn version.
Example Install
pip install biopython
git clone https://github.com/chrisgulvik/c-SSTAR.git $HOME
echo 'export PATH="$PATH:$HOME/c-SSTAR"' >> $HOME/.bash_profile

Example Usage
Run c-SSTAR on several genomes with the combo database
for F in *.fna; do
B=$(basename $F .fna)
c-SSTAR -g $F -d ~/c-SSTAR/db/ResGANNOT_srst2.fasta.gz -o $B > "$B"_ResGANNOT.tab
done

Example Summary Output
c-SSTAR -g ~/c-SSTAR/tests/data/SRR3112344.fa.gz \
-d ~/c-SSTAR/db/ResGANNOT_srst2.fasta.gz

AR_Family
AR_Variant
Query_Defline
Identity
Aln_Len
DB_Gene_Len

aac(3)*
aac(3)-IId*
tig093
99.884%
861
861

aac(3)?
aac(3)-Ib-aac(6')-Ib'?
tig123
99.097%
554
1005

aac(6')
aac(6')-Ib-cr
tig123
100.0%
600
600

aac(6')?
aac(6')-30-aac(6')-Ib'?
tig123
99.309%
579
987

aadA2?
aadA2?
tig104
99.875%
802
819

ampH*
ampH*
tig003
98.88%
1161
1161

aph(3'')*
aph(3'')-Ib*
tig096
99.876%
804
804

aph(6)*
aph(6)-Id*
tig096
99.881%
837
837

blaCTX
blaCTX-M-15
tig089
100.0%
876
876

blaOXA
blaOXA-1
tig123
100.0%
831
831

blaSHV
blaSHV-11
tig016
100.0%
861
861

blaSHV*
blaSHV-100*
tig016
95.111%
900
900

blaTEM
blaTEM-1B
tig108
100.0%
861
861

catA2*
catA2*
tig127
96.106%
642
642

catB3?$
catB3?$
tig123
100.0%
440
633

catB4?$
catB4?$
tig123
100.0%
440
549

dfrA12
dfrA12
tig104
100.0%
498
498

dfrA14*
dfrA14*
tig134
99.586%
483
483

fosA6?$
fosA6?$
tig026
98.81%
420
433

mph(A)?TR
mph(A)?TR
tig110
99.675%
922
921

oqxA
oqxA
tig024
100.0%
1176
1176

oqxB
oqxB
tig024
100.0%
3153
3153

qnrB1*TR
qnrB1*TR
tig080
99.853%
681
681

sul1*
sul1*
tig104
99.885%
867
867

sul2
sul2
tig096
100.0%
816
816

tet(D)
tet(D)
tig108
100.0%
1185
1185

Literature References
c-SSTAR: Cunningham SA, Limbago B, Traczewski M, Anderson K, Hackel M, Hindler J, Sahm D, Alyanak E, Lawsin A, Gulvik CA, de Man TJB, Mandrekar JN, Schuetz AN, Jenkins S, Humphries R, Palavecino E, Vasoo S, Patel R. 2017. Multicenter Performance Assessment of Carba NP Test. J Clin Microbiol 55(6):1954-1960. doi: 10.1128/JCM.00244-17
SSTAR: de Man TJB, Limbago BM. 2016. SSTAR, a stand-alone easy-to-use antimicrobial resistance gene predictor. mSphere 1(1): e00050-15. doi: 10.1128/mSphere.00050-15
ARG-ANNOT database: Gupta SK, Padmanabhan BR, Diene SM, Lopez-Rojas R, Kempf M, Landraud L, Rolain J-M. 2014. ARG-ANNOT (Antibiotic Resistance Gene-ANNOTation), a new bioinformatic tool to discover antibiotic resistance genes in bacterial genomes. Antimicrobial Agents and Chemotherapy 58:212–220. doi: 10.1128/AAC.01310-13
ResFinder database: Zankari E, Hasman H, Cosentino S, Vestergaard M, Rasmussen S, Lund O, Aarestrup F, Larsen MV. 2012. Identification of acquired antimicrobial resistance genes. Journal of Antimicrobial Chemotherapy 67:2640–2644. doi: 10.1093/jac/dks261