KeyWest - MABSC Identification and Resistance Prediction Pipeline

This Nextflow pipeline identifies Mycobacterium abscessus complex (MABSC), predicts drug resistance, performs species identification, and assembles genomes from Illumina paired-end reads. It uses Docker/Singularity containers and generates comprehensive summary results with Erm(41) resistance gene detection.

Requirements

• Nextflow 23.04.0+
• Singularity
• Conda

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Input

Paired-end FASTQ files placed under fastqs/:

sample1_1.fastq.gz
sample1_2.fastq.gz
sample2_1.fastq.gz
sample2_2.fastq.gz

For lab samples format as prefix-date-xxx-xx_S1_L001_R1_001.fastq.gz:

# Use resources/rename.sh to convert lab sample names
bash resources/rename.sh

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Setup

Check Parameters

Verify params.yaml has all required paths:

input_dir: "/path/to/fastqs"
output: "/path/to/output"
reference: "/path/to/reference.fasta"
erm41: "/path/to/erm41.fasta"
card_database: "/path/to/card_db"
kraken2_db: "/path/to/kraken2_db"
NTM_profiler_db: "/path/to/NTM-profiler"

Check FASTQ Files

Ensure files follow naming convention:

sample1_1.fastq.gz & sample1_2.fastq.gz
sample2_1.fastq.gz & sample2_2.fastq.gz

Build Conda Environment

conda env create -f resources/keywest.yml
conda activate keywest

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Run the Pipeline

Local Execution

nextflow run main.nf -params-file params.yaml

HiPerGator Usage

sbatch keywest.sh

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Output Structure

output/
+-- {sample}/
¦   +-- fastp/              # Quality control reports
¦   +-- ntm_profiler/       # Species identification
¦   +-- kraken2/            # Taxonomic classification
¦   +-- bwa/                # Read alignment
¦   +-- samtools/           # BAM processing
¦   +-- unicycler/          # Genome assembly
¦   +-- hmmer/              # Erm(41) resistance gene analysis
¦   +-- stats/              # Coverage statistics
¦   +-- summary/            # Comprehensive CSV report
¦       +-- {sample}_sample_summary.csv
+-- multiqc_report.html     # Aggregate quality report

Pipeline Workflow

1. fastp - Quality control and trimming
2. NTM-Profiler - Mycobacterial species identification
3. Kraken2 - Taxonomic classification
4. BWA - Read mapping to reference
5. Samtools - BAM file processing
6. Unicycler - Genome assembly
7. HMMER - Erm(41) resistance gene detection + CARD BLAST
8. Stats - Coverage and mapping statistics
9. Summary - Comprehensive CSV report generation
10. MultiQC - Aggregate quality reporting

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Database Requirements

Required Databases

• Reference genome: Mycobacterial reference (FASTA)
• Erm(41) sequences: Query genes for resistance detection
• CARD database: Comprehensive Antibiotic Resistance Database
• Kraken2 database: Taxonomic classification
• NTM-Profiler database: Mycobacterial species identification. (The NTM-Profiler database for BPHL use by HiperGator has been modified by author.)

Database Setup

(For Non-HiPerGator Users)

# CARD Database
wget https://card.mcmaster.ca/latest/data
tar -xf data
makeblastdb -in card_protein_homolog_model.fasta -dbtype prot -out card_db

# Kraken2 Database  
wget https://genome-idx.s3.amazonaws.com/kraken/minikraken2_v2_8GB_201904.tgz
tar -xzf minikraken2_v2_8GB_201904.tgz

# NTM-Profiler
git clone https://github.com/jodyphelan/NTM-Profiler.git

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Troubleshooting

(For Non-HiPerGator Users)

Please install the following modules manually:

HMMER: https://github.com/EddyRivasLab/hmmer/tree/master

wget http://eddylab.org/software/hmmer/hmmer.tar.gz
tar zxf hmmer.tar.gz
cd hmmer-3.4
./configure --prefix /your/install/path
make && make install

NCBI BLAST+: https://blast.ncbi.nlm.nih.gov/doc/blast-help/downloadblastdata.html

wget https://ftp.ncbi.nlm.nih.gov/blast/executables/blast+/LATEST/ncbi-blast-*-x64-linux.tar.gz
tar -xzf ncbi-blast-*-x64-linux.tar.gz

BWA-MEM2: https://github.com/bwa-mem2/bwa-mem2

git clone https://github.com/bwa-mem2/bwa-mem2
cd bwa-mem2
make