RESULTS: We developed a stand-alone software that implements the FineMAV statistic. To graphically visualise the FineMAV scores, it outputs the statistics as bigWig files, which is a common file format supported by many genome browsers. It is available as a command-line and graphical user interface. The software was tested by replicating the FineMAV scores obtained using 1000 Genomes Project African, European, East and South Asian populations and subsequently applied to whole-genome sequencing datasets from Singapore and China to highlight population specific variants that can be subsequently modelled. The software tool is publicly available at https://github.com/fadilla-wahyudi/finemav .
CONCLUSIONS: The software tool described here determines genome-wide FineMAV scores, using low or high-coverage whole-genome sequencing datasets, that can be used to prioritize a list of population specific, highly differentiated candidate variants for in vitro or in vivo functional screens. The tool displays these scores on the human genome browsers for easy visualisation, annotation and comparison between different genomic regions in worldwide human populations.
METHODS AND RESULTS: Fifteen clinical isolates (isolated from tracheal secretion, urine and bronchoalveolar lavage) were subjected to whole genome sequencing. Raw sequences were assembled using SPAdes and species were identified using KmerFinder 3.2. The assembled genomes were annotated using the Prokka v1.14.6. Resfinder 4.6.0 was used to determine antibiotic resistance genes. The sequences were aligned against seven housekeeping genes aka sequence tags (STs) available within the MLST database (v 2.0.9). MobileGeneticElement finder (v1.0.3) were used for profiling mobile genetic elements associated with the antibiotic resistance genes. The genomes of nosocomial A. baumannii were assembled with an average N50 of 23,480 and GC content of 38%. There were approximately 3700 CDs, 53 tRNA and 3 rRNA. About 80% of the isolates were ST2 type. The genomes possessed antibiotic resistance genes (n = 24) belonging to 17 drug classes. The predicted phenotype was multidrug resistant. Among the mobile genetic elements, 12 insertion sequences and 2 composite transposons were also found. The mode of antibiotic resistance was mostly through antibiotic inactivation in all the isolates.
CONCLUSIONS: The results imply the occurrence of multidrug resistant genes in clinical isolates of A. baumannii strains in the healthcare settings of Kuwait. A more comprehensive survey should be undertaken for antimicrobial resistance monitoring on a regular basis for surveillance, contact tracing, and potential mitigation in clinical settings.