Bioinformatics tools used for whole-genome sequencing analysis of Neisseria gonorrhoeae: a literature review

Whole Genome Sequencing and Comparative Genomics Analysis of Goat-Derived Klebsiella oxytoca

Background: This research aims to enhance the genomic database of Klebsiella oxytoca by identifying virulence genes through the whole genome sequencing and comparative analysis of a goat-derived K. oxytoca (KOHN1) strain, while clarifying the relationship between its genetic evolution and virulence, ultimately providing a theoretical foundation for clinical prevention and diagnosis. Methods: Third-generation Oxford Nanopore Technologies (ONT) sequencing and second-generation Illumina sequencing were used to sequence the strain and analyze the database annotations. Screening for 10 virulence genes was conducted using PCR. Comparative genomic analyses of the strain KOHN1 with four human-derived K. oxytoca model strains were performed using collinearity analysis, taxonomy classification through ANI analysis, and gene function family analysis. Results: The genome size of the KOHN1 strain was 5,817,806 bp, and the GC content was 55.14%. It contained 5227 predicted coding genes, including 25 rRNA genes, 85 tRNA genes, and 53 sRNA genes. A total of 14 type VI secretion system effector proteins and 146 virulence factor-related genes were annotated. Additionally, eight virulence genes-fimA, fimH, entB, mrkD, clpV, rmpA, vgrG, and hcp-were detected through PCR identification. The strain has 448 drug resistance genes, mainly against β-lactams and fosfomycins. Comparative genomic analysis indicated that its closest relation is the human isolate ASM338647. Conclusions: In this study, the whole genome sequence of a goat-derived K. oxytoca (KOHN1) strain was obtained, revealing its evolutionary relationship with domestic and foreign isolates and providing a reference for future studies on the mechanisms of antimicrobial resistance and the pathogenicity of K. oxytoca.

Whole Genome Sequencing: Applications in Clinical Bacteriology

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. Since 2004, high-throughput next-generation sequencing technologies have been developed, which are highly efficient, require less time, and are cost-effective for 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. 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 applications of WGS in clinical bacteriology.

Emergence and Genomic Characterization of Neisseria gonorrhoeae Isolates with High Levels of Ceftriaxone and Azithromycin Resistance in Guangdong, China, from 2016 to 2019

Currently, antibiotic resistance (especially ceftriaxone and azithromycin dual resistance) in Neisseria gonorrhoeae is the main obstacle affecting the efficacy of treatment. As analysis of drug sensitivity, molecular features, and dissemination of dual-resistant strains is important for gonococcal prevention and control, MIC, genotyping, and genome analysis were conducted to reveal the molecular characteristics and phylogeny of N. gonorrhoeae isolates. During 2016 to 2019, 5 out of 4,113 strains were defined as dual-resistant clones, with ceftriaxone MICs of 0.25 to ≥1 mg/L and azithromycin MICs of 2 to ≥2,048 mg/L. In particular, two strains with a ceftriaxone MIC above 0.5 mg/L were characterized as penA-60.001 FC428-related clones, and two isolates with a high-level azithromycin MIC above 1,024 mg/L featuring a 23S rRNA mutation were identified. Furthermore, phylogenetic analysis confirmed that the dual-resistant strains were closer to the evolutionary origin of F89 in France, global FC428-related clones, and high-level dual-resistant clones in Australia and the United Kingdom. Dual-resistant strains, including FC428-related clones and high-level azithromycin-resistant clones, have circulated in Guangdong, China. The ability of laboratories to perform real-time drug susceptibility and genetic analyses should be strengthened to monitor the spread of threatening strains. IMPORTANCE Here, we report five sporadic dual-resistant isolates, including FC428-related ceftriaxone-resistant clones with MICs of ≥0.5 mg/L and high-level azithromycin resistance with MICs of ≥1,024 mg/L. This study highlights that dual-resistant clones with the same evolutionary origin as FC428, A2735, and F89 have circulated in Guangdong, China, which suggests that the capacity for antibiotic resistance testing and genome analysis should be strengthened in daily epidemiological surveillance.

Assessment of Antibiotic Resistance and Efflux Pump Gene Expression in Neisseria Gonorrhoeae Isolates from South Africa by Quantitative Real-Time PCR and Regression Analysis

Introduction

Treatment of gonorrhoea infection is limited by the increasing prevalence of multidrug-resistant strains. Cost-effective molecular diagnostic tests can guide effective antimicrobial stewardship. The aim of this study was to correlate mRNA expression levels in Neisseria gonorrhoeae antibiotic target genes and efflux pump genes to antibiotic resistance in our population.

Methods

This study investigated the expression profile of antibiotic resistance-associated genes (penA, ponA, pilQ, mtrR, mtrA, mtrF, gyrA, parC, parE, rpsJ, 16S rRNA, and 23S rRNA) and efflux pump genes (macAB, norM, and mtrCDE), by quantitative real-time PCR, in clinical isolates from KwaZulu-Natal, South Africa. Whole-genome sequencing was used to determine the presence or absence of mutations.

Results

N. gonorrhoeae isolates, from female and male patients presenting for care at clinics in KwaZulu-Natal, South Africa, were analysed. As determined by binomial regression and ROC analysis, the most significant (p ≤ 0.05) markers for resistance prediction in this population, and their cutoff values, were determined to be mtrC (p = 0.024; cutoff <0.089), gyrA (p = 0.027; cutoff <0.0518), parE (p = 0.036; cutoff <0.0033), rpsJ (p = 0.047; cutoff <0.0012), and 23S rRNA (p = 0.042; cutoff >7.754).

Conclusion

Antimicrobial stewardship includes exploring options to conserve currently available drugs for gonorrhoea treatment. There is the potential to predict an isolate as either susceptible or nonsusceptible based on the mRNA expression level of specific candidate markers, to inform patient management. This real-time qPCR approach, with few targets, can be further investigated for use as a potentially cost-effective diagnostic tool to detect resistance.