Deciphering pathogenicity and antibiotic resistance islands in methicillin-resistant Staphylococcus aureus genomes

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This article explores the use of an information-entropy-based gene clustering method for genomic island detection in MRSA.

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14 p.

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Jani, Mehul; Sengupta, Soham; Hu, Kelsey & Azad, Rajeev K. November 16, 2017.

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This article is part of the collection entitled: UNT Scholarly Works and was provided by the UNT College of Science to the UNT Digital Library, a digital repository hosted by the UNT Libraries. It has been viewed 246 times, with 8 in the last month. More information about this article can be viewed below.

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This article explores the use of an information-entropy-based gene clustering method for genomic island detection in MRSA.

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14 p.

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Abstract: Staphylococcus aureus is a versatile pathogen that is capable of causing infections in both humans and animals. It can cause furuncles, septicaemia, pneumonia and endocarditis. Adaptation of S. aureus to the modern hospital environment has been facilitated, in part, by the horizontal acquisition of drug resistance genes, such as mecA gene that imparts resistance to methicillin. Horizontal acquisitions of islands of genes harbouring virulence and antibiotic resistance genes have made S. aureus resistant to commonly used antibiotics. To decipher genomic islands (GIs) in 22 hospital- and 9 community-associated methicillin-resistant S. aureus strains and classify a subset of GIs carrying virulence and resistance genes as pathogenicity and resistance islands respectively, we applied a host of methods for localizing genomic islands in prokaryotic genomes. Surprisingly, none of the frequently used GI prediction methods could perform well in delineating the resistance islands in the S. aureus genomes. Rather, a gene clustering procedure exploiting biases in codon usage for identifying horizontally transferred genes outperformed the current methods for GI detection, in particular in identifying the known islands in S. aureus including the SCCmec island that harbours the mecA resistance gene. The gene clustering approach also identified novel, as yet unreported islands, with many of these found to harbour virulence and/or resistance genes. These as yet unexplored islands may provide valuable information on the evolution of drug resistance in S. aureus.

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  • Open Biology, 2017. London, UK: The Royal Society

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  • Publication Title: Open Biology
  • Volume: 7
  • Page Start: 1
  • Page End: 14
  • Peer Reviewed: Yes

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UNT Scholarly Works

Materials from the UNT community's research, creative, and scholarly activities and UNT's Open Access Repository. Access to some items in this collection may be restricted.

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  • November 16, 2017

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  • April 15, 2017

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  • November 16, 2017

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  • July 30, 2018, 12:01 p.m.

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  • Feb. 8, 2021, 4:40 p.m.

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Jani, Mehul; Sengupta, Soham; Hu, Kelsey & Azad, Rajeev K. Deciphering pathogenicity and antibiotic resistance islands in methicillin-resistant Staphylococcus aureus genomes, article, November 16, 2017; London, United Kingdom. (https://digital.library.unt.edu/ark:/67531/metadc1213690/: accessed November 14, 2025), University of North Texas Libraries, UNT Digital Library, https://digital.library.unt.edu; crediting UNT College of Science.

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