ena-PROJECT-UMBI-12-09-2012-08:13:15:170-5
Whole genome sequencing of four nosocomial methicillin-resistant Staphylococcus aureus (strains MRSA 261, MRSA 332, MRSA 377 and MRSA 775) representative of dominant MRSA pulsotypes circulating in a Malaysian university teaching hospital
To better understand the biology and molecular characteristics of nosocomial MRSA strains endemic to our hospital, we identified the hospital’s dominant MRSA genotype via molecular typing and sequenced the whole genomes of 4 MRSAs which were representative of this genotype using an Ion PGM sequencer.   After sequencing, reads were filtered and trimmed prior de novo assembly using GS De Novo Assembler version 2.70.  The protein coding gene models were predicted using ab initio based gene predictors Glimmer version 3.02 and Genemark.hmm version 2.10b while gene annotations were carried out using BLASTp searched against NCBI NR, SwissProt, NR, GO and KEGG databases.   For the de novo assembly, 638,248~ 923,828 clean reads spanning 115,836,594~ 180,374,605 bases were assembled and aligned. 97~125 contigs were generated, which totalled 2,956,301, 3,019,328, 2,851,702, 3,000,990 bps for MRSA 261, MRSA 332, MRSA 377 and MRSA 775, respectively, with  >95% coverage for all assembly against reference genomes. GC count was similar for all 4 strains (32.6% for MRSA 261, MRSA 332 and MRSA 775, 32.7% for MRSA 377). About 2000 proteins were annotated for all strains using the SwissProt, while Genbank NR annotation predicted larger amount of proteins (> 2800) for each strain.  Gene ontology functional classification showed similar distribution for all 4 strains, owing to their close relatedness as visualized with PFGE typing.
To better understand the biology and molecular characteristics of nosocomial MRSA strains endemic to our hospital, we identified the hospital’s dominant MRSA genotype via molecular typing and sequenced the whole genomes of 4 MRSAs which were representative of this genotype using an Ion PGM sequencer.   After sequencing, reads were filtered and trimmed prior de novo assembly using GS De Novo Assembler version 2.70.  The protein coding gene models were predicted using ab initio based gene predictors Glimmer version 3.02 and Genemark.hmm version 2.10b while gene annotations were carried out using BLASTp searched against NCBI NR, SwissProt, NR, GO and KEGG databases.   For the de novo assembly, 638,248~ 923,828 clean reads spanning 115,836,594~ 180,374,605 bases were assembled and aligned. 97~125 contigs were generated, which totalled 2,956,301, 3,019,328, 2,851,702, 3,000,990 bps for MRSA 261, MRSA 332, MRSA 377 and MRSA 775, respectively, with  >95% coverage for all assembly against reference genomes. GC count was similar for all 4 strains (32.6% for MRSA 261, MRSA 332 and MRSA 775, 32.7% for MRSA 377). About 2000 proteins were annotated for all strains using the SwissProt, while Genbank NR annotation predicted larger amount of proteins (> 2800) for each strain.  Gene ontology functional classification showed similar distribution for all 4 strains, owing to their close relatedness as visualized with PFGE typing.