Spatial Variations in the Nasal Microbiota of Staff Working in a Healthcare-Associated Research Core Facility

Mustafa, Abu Salim; Habibi, Nazima

doi:10.1159/000535983

Cited by 4 publications

(1 citation statement)

References 34 publications

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“…More recently, several next-generation sequencing (NGS) technologies for whole genome sequencing (WGS) have been developed [ 18 ]. These NGS technologies can be exploited to provide information about the complete genome of an organism [ 19 , 20 ] and can detect many pathogens in clinical specimens simultaneously [ 21 , 22 ]. Data obtained from WGS can be analyzed by using a battery of bioinformatics tools [ 23 , 24 ], which provide information about the quality of sequenced genomes and identify species, strains, and genotypes of the infecting organisms, as well as predications about drug susceptibility/resistance and epidemiological investigations [ 25 – 30 ].…”

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confidence: 99%

Whole Genome Sequencing: Applications in Clinical Bacteriology

Mustafa

2024

Med Princ Pract

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The success in determining the whole genome sequence of a bacterial pathogen was first achieved in 1995 by determining the complete nucleotide sequence of Haemophilus influenzae Rd using the chain-termination method established by Sanger et al. in 1977 and automated by Hood et al. in 1987. However, this technology was laborious, costly, and time-consuming to obtain whole genome sequences. Since 2004, high-throughput next-generation sequencing technologies have been developed, which are highly efficient, require less time, and are cost-effective to perform whole genome sequencing (WGS) of all organisms, including bacterial pathogens. In recent years, the data obtained using WGS technologies coupled with bioinformatics analyses of the sequenced genomes have been projected to revolutionize clinical bacteriology practices. The WGS technologies have been used in the identification of bacterial species, strains, and genotypes from cultured organisms and directly from clinical specimens. WGS has also helped in determining resistance to antibiotics by the detection of antimicrobial resistance genes and point mutations. Furthermore, WGS data have helped in the epidemiological tracking and surveillance of pathogenic bacteria in healthcare settings as well as in communities. This review focuses on the above-mentioned applications of WGS in clinical bacteriology.

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