Neisseria gonorrhoeae clustering to reveal major European whole-genome-sequencing-based genogroups in association with antimicrobial resistance

Local emergence and global evolution of Neisseria gonorrhoeae with high-level resistance to azithromycin

Antimicrobial resistance in Neisseria gonorrhoeae (Ng) has severely reduced treatment options, including azithromycin (AZM), which had previously been recommended as dual therapy with ceftriaxone. This study characterizes the emergence of high-level resistance to AZM (HLR-AZM) Ng in Baltimore, Maryland, USA, and describes the global evolution of HLR-AZM Ng. Whole genome sequencing (WGS) of 30 Ng isolates with and without HLR-AZM from Baltimore was used to identify clonality and resistance determinants. Publicly available WGS data from global HLR-AZM Ng (n = 286) and the Baltimore HLR-AZM Ng (n = 3) were used to assess the distribution, clonality, and diversity of HLR-AZM Ng. The HLR-AZM Ng isolates from Baltimore identified as multi-locus sequencing typing sequence type (ST) 9363 and likely emerged from circulating strains. ST9363 was the most widely disseminated ST globally represented in eight countries and was associated with sustained transmission events. The number of global HLR-AZM Ng, countries reporting these isolates, and strain diversity increased in the last decade. The majority (89.9%) of global HLR-AZM Ng harbored the A2059G mutation in all four alleles of the 23S rRNA gene, but isolates with two or three A2059G alleles, and alternative HLR-AZM mechanisms were also identified. In conclusion, HLR-AZM in Ng has increased in the last few years, with ST9363 emerging as an important gonococcal lineage globally. The 23S rRNA A2059G mutation is the most common resistance mechanism, but alternative mechanisms are emerging. Continued surveillance of HLR-AZM Ng, especially ST9363, and extensively drug-resistant Ng is warranted.

The evolutionary features and roles of single nucleotide variants and charged amino acid mutations in influenza outbreaks during NPI period

The epidemic and outbreaks of influenza B Victoria lineage (Bv) during 2019-2022 led to an analysis of genetic, epitopes, charged amino acids and Bv outbreaks. Based on the National Influenza Surveillance Network (NISN), the Bv 72 strains isolated during 2019-2022 were selected by spatio-temporal sampling, then were sequenced. Using the Compare Means, Correlate and Cluster, the outbreak data were analyzed, including the single nucleotide variant (SNV), amino acid (AA), epitope, evolutionary rate (ER), Shannon entropy value (SV), charged amino acid and outbreak. With the emergence of COVID-19, the non-pharmaceutical interventions (NPIs) made Less distant transmission and only Bv outbreak. The 2021-2022 strains in the HA genes were located in the same subset, but were distinct from the 2019-2020 strains (P < 0.001). The codon G → A transition in nucleotide was in the highest ratio but the transversion of C → A and T → A made the most significant contribution to the outbreaks, while the increase in amino acid mutations characterized by polar, acidic and basic signatures played a key role in the Bv epidemic in 2021-2022. Both ER and SV were positively correlated in HA genes (R = 0.690) and NA genes (R = 0.711), respectively, however, the number of mutations in the HA genes was 1.59 times higher than that of the NA gene (2.15/1.36) from the beginning of 2020 to 2022. The positively selective sites 174, 199, 214 and 563 in HA genes and the sites 73 and 384 in NA genes were evolutionarily selected in the 2021-2022 influenza outbreaks. Overall, the prevalent factors related to 2021-2022 influenza outbreaks included epidemic timing, Tv, Ts, Tv/Ts, P137 (B → P), P148 (B → P), P199 (P → A), P212 (P → A), P214 (H → P) and P563 (B → P). The preference of amino acid mutations for charge/pH could influence the epidemic/outbreak trends of infectious diseases. Here was a good model of the evolution of infectious disease pathogens. This study, on account of further exploration of virology, genetics, bioinformatics and outbreak information, might facilitate further understanding of their deep interaction mechanisms in the spread of infectious diseases.

Antimicrobial susceptibility profile of Neisseria gonorrhoeae from patients attending a medical laboratory, Institut Pasteur de Madagascar between 2014 and 2020: phenotypical and genomic characterisation in a subset of Neisseria gonorrhoeae isolates

OBJECTIVES

Antimicrobial-resistant Neisseria gonorrhoeae (NG) is a concern. Little is known about antimicrobial susceptibility profiles and associated genetic resistance mechanisms of NG in Madagascar. We report susceptibility data of NG isolates obtained by the medical laboratory (CBC) of the Institut Pasteur de Madagascar, Antananarivo, Madagascar, during 2014-2020. We present antimicrobial resistance mechanisms data and phenotype profiles of a subset of isolates.

METHODS

We retrieved retrospective data (N=395) from patients with NG isolated during 2014-2020 by the CBC. We retested 46 viable isolates including 6 found ceftriaxone and 2 azithromycin resistant, as well as 33 isolated from 2020. We determined minimal inhibitory concentrations for ceftriaxone, ciprofloxacin, azithromycin, penicillin, tetracycline and spectinomycin using Etest. We obtained whole-genome sequences and identified the gene determinants associated with antimicrobial resistance and the sequence types (STs).

RESULTS

Over the study period, ceftriaxone-resistant isolates exceeded the threshold of 5% in 2017 (7.4% (4 of 54)) and 2020 (7.1% (3 of 42)). All retested isolates were found susceptible to ceftriaxone, azithromycin and spectinomycin, and resistant to ciprofloxacin. The majority were resistant to penicillin (83% (38 of 46)) and tetracycline (87% (40 of 46)). We detected chromosomal mutations associated with antibiotic resistance in gyrA, parC, penA, ponA, porB and mtrR genes. None of the retested isolates carried the mosaic penA gene. The high rate of resistance to penicillin and tetracycline is explained by the presence of bla TEM (94.7% (36 of 38)) and tetM (97.5% (39 of 40)). We found a high number of circulating multilocus STs. Almost half of them were new types, and one new type was among the four most predominant.

CONCLUSIONS

Our report provides a detailed dataset obtained through phenotypical and genotypical methods which will serve as a baseline for future surveillance of NG. We could not confirm the occurrence of ceftriaxone-resistant isolates. Our results highlight the importance of implementing quality-assured gonococcal antimicrobial resistance surveillance in Madagascar.

ReporTree: a surveillance-oriented tool to strengthen the linkage between pathogen genetic clusters and epidemiological data

BACKGROUND

Genomics-informed pathogen surveillance strengthens public health decision-making, playing an important role in infectious diseases' prevention and control. A pivotal outcome of genomics surveillance is the identification of pathogen genetic clusters and their characterization in terms of geotemporal spread or linkage to clinical and demographic data. This task often consists of the visual exploration of (large) phylogenetic trees and associated metadata, being time-consuming and difficult to reproduce.

RESULTS

We developed ReporTree, a flexible bioinformatics pipeline that allows diving into the complexity of pathogen diversity to rapidly identify genetic clusters at any (or all) distance threshold(s) or cluster stability regions and to generate surveillance-oriented reports based on the available metadata, such as timespan, geography, or vaccination/clinical status. ReporTree is able to maintain cluster nomenclature in subsequent analyses and to generate a nomenclature code combining cluster information at different hierarchical levels, thus facilitating the active surveillance of clusters of interest. By handling several input formats and clustering methods, ReporTree is applicable to multiple pathogens, constituting a flexible resource that can be smoothly deployed in routine surveillance bioinformatics workflows with negligible computational and time costs. This is demonstrated through a comprehensive benchmarking of (i) the cg/wgMLST workflow with large datasets of four foodborne bacterial pathogens and (ii) the alignment-based SNP workflow with a large dataset of Mycobacterium tuberculosis. To further validate this tool, we reproduced a previous large-scale study on Neisseria gonorrhoeae, demonstrating how ReporTree is able to rapidly identify the main species genogroups and characterize them with key surveillance metadata, such as antibiotic resistance data. By providing examples for SARS-CoV-2 and the foodborne bacterial pathogen Listeria monocytogenes, we show how this tool is currently a useful asset in genomics-informed routine surveillance and outbreak detection of a wide variety of species.

CONCLUSIONS

In summary, ReporTree is a pan-pathogen tool for automated and reproducible identification and characterization of genetic clusters that contributes to a sustainable and efficient public health genomics-informed pathogen surveillance. ReporTree is implemented in python 3.8 and is freely available at https://github.com/insapathogenomics/ReporTree .

Loop-Mediated Isothermal Amplification Assay for Identifying Neisseria gonorrhoeae Nonmosaic penA-Targeting Strains Potentially Eradicable by Cefixime

Treatment regimens for gonorrhea have limited efficacy worldwide due to the rapid spread of antimicrobial resistance. Cefixime (CFM) is currently not recommended as a first-line treatment for gonorrhea due to the increasing number of resistant strains worldwide. Nonetheless, Neisseria gonorrhoeae strains can be eradicated by CFM at a 400 mg/day dose, provided that the strains are CFM responsive (MIC ≤ 0.064 mg/L). To develop a nonculture test for predicting the CFM responsiveness of N. gonorrhoeae strains, we developed an assay to detect N. gonorrhoeae nonmosaic penA using loop-mediated isothermal amplification (LAMP). To avoid false-positive reactions with commensal Neisseria spp. penA, we amplified specific regions of the N. gonorrhoeae penA (NG-penA-LAMP1) and also the nonmosaic N. gonorrhoeae penA (NG-penA-LAMP3). This assay was validated using isolated N. gonorrhoeae (n = 204) and Neisseria spp. (n = 95) strains. Clinical specimens (n = 95) with confirmed positivity in both culture and real-time PCR were evaluated to validate the system. The combination of the previously described NG-penA-LAMP1 and our new NG-penA-LAMP3 assays had high sensitivity (100%) and specificity (100%) for identifying N. gonorrhoeae carrying the nonmosaic type. To determine whether CFM could be applicable for gonorrhea treatment without culture testing, we developed a LAMP assay that targets penA allele-specific nonmosaic types for use as one of the tools for point-of-care testing of antimicrobial resistance. IMPORTANCE Neisseria gonorrhoeae is among the hot topics of "resistance guided therapy," one of the top 5 urgent antimicrobial threats according to the Centers for Disease Control and Prevention (CDC). There is a need either to develop new agents or to make effective use of existing agents, with the current limited number of therapeutic agents available. Knowing the drug susceptibility information of the target microorganism prior to treating patients is very useful in selecting an effective antibiotic, especially in gonococcal infections where drug resistance is prominent, and is also important in preventing treatment failure. In this study, we developed a new method for obtaining drug susceptibility profiles of Neisseria gonorrhoeae using the loop-mediated isothermal amplification (LAMP) method. The LAMP assay does not require expensive devices. Therefore, this method is expected to be a tool for point-of-care testing of antimicrobial resistance for individualized treatment in the future.

Decentralized Investigation of Bacterial Outbreaks Based on Hashed cgMLST

Whole-genome sequencing (WGS)-based outbreak investigation has proven to be a valuable method for the surveillance of bacterial pathogens. Its utility has been successfully demonstrated using both gene-by-gene (cgMLST or wgMLST) and single-nucleotide polymorphism (SNP)-based approaches. Among the obstacles of implementing a WGS-based routine surveillance is the need for an exchange of large volumes of sequencing data, as well as a widespread reluctance to share sequence and metadata in public repositories, together with a lacking standardization of suitable bioinformatic tools and workflows. To address these issues, we present chewieSnake, an intuitive and simple-to-use cgMLST workflow. ChewieSnake builds on the allele calling software chewBBACA and extends it by the concept of allele hashing. The resulting hashed allele profiles can be readily compared between laboratories without the need of a central allele nomenclature. The workflow fully automates the computation of the allele distance matrix, cluster membership, and phylogeny and summarizes all important findings in an interactive HTML report. Furthermore, chewieSnake can join allele profiles generated at different laboratories and identify shared clusters, including a stable and intercommunicable cluster nomenclature, thus facilitating a joint outbreak investigation. We demonstrate the feasibility of the proposed approach with a thorough method comparison using publically available sequencing data for Salmonella enterica. However, chewieSnake is readily applicable to all bacterial taxa, provided that a suitable cgMLST scheme is available. The workflow is freely available as an open-source tool and can be easily installed via conda or docker.