Biology subjects

Unemo, M.

Publications and source records attributed to Unemo, M..

8 recordsLinked to original sources

bioRxiv2023

pyngoST: fast, simultaneous and accurate multiple sequence typing of Neisseria gonorrhoeae genome collections

Extensive gonococcal surveillance has been performed using molecular typing at global, regional, national and local levels. The three main genotyping schemes for this pathogen, Multi-Locus Sequence Typing (MLST), Neisseria gonorrhoeae Multi-Antigen Sequence Typing (NG-MAST) and N. gonorrhoeae Sequence Typing for Antimicrobial Resistance (NG-STAR), allow inter-laboratory and inter-study comparability and reproducibility and provide an approximation to the gonococcal population structure. With high-throughput whole-genome sequencing (WGS), we obtain a substantially higher and more accurate discrimination between strains, i.e., compared to previous molecular typing schemes where isolates with the same sequence type often have a different genomic background. However, WGS remains unavailable or not affordable in many laboratories, accordingly, bioinformatic tools that allow the integration of data among laboratories with and without access to WGS is imperative for a joint effort to increase our understanding of global pathogen threats. Here, we present pyngoST, a command-line Python tool for a fast, simultaneous and accurate sequence typing of the WHO priority pathogen N. gonorrhoeae, from WGS assemblies. pyngoST integrates MLST, NG-MAST and NG-STAR, and can also designate NG-STAR clonal complexes and NG-MAST genogroups, facilitating multiple sequence typing from large WGS assembly collections. Exact matches for existing alleles and STs are reported, but also closest matches of new alleles and STs. The implementation of a fast multi-pattern searching algorithm allows pyngoST to be rapid and report results on 500 WGS assemblies in under 1 minute. The mapping of typing results on a core genome tree of 2,375 gonococcal genomes revealed that NG-STAR is the scheme that best represents the population structure of this pathogen, emphasizing the role of antimicrobial use and antimicrobial resistance (AMR) as a driver of gonococcal evolution. IMPACT STATEMENTMolecular typing has been key for N. gonorrhoeae epidemiological and AMR surveillance, and WGS has revolutionized this typing. The most frequently used molecular typing schemes include MLST, NG-MAST and NG-STAR, and modifications of those. These schemes can be extracted from WGS assemblies for comparability and reproducibility of results with laboratories that do not have access to WGS technologies. pyngoST is a unique command-line Python tool that integrates all these common typing schemes under the same framework and performs rapid simultaneous user-defined multiple typing of large number of gonococcal genomes through a fast multi-pattern searching algorithm. Typing results on 2,375 gonococcal genomes revealed that NG-STAR best represents the genomic population structure of N. gonorrhoeae, highlighting the importance of antimicrobial use and AMR on the evolution of this pathogen. DATA SUMMARYO_LIpyngoST is written in Python 3 and is available from Github under the GPL-3.0 License (https://github.com/leosanbu/pyngoST). C_LIO_LIThe script can be installed via the Python pip package. C_LIO_LIGenome assemblies used in this study are from the Euro-GASP 2018 WGS survey and are available from Pathogenwatch: https://pathogen.watch/collection/eurogasp2018 (1,2). Pairwise single nucleotide polymorphism (SNP) distances among isolates from this dataset are also available from the same link. C_LIO_LIResults from running pyngoST on the Euro-GASP 2018 WGS dataset can be explored from Microreact: https://microreact.org/project/wYpBzCs9A6Uf7HEMA6zmmY-eurogasp2018-pyngost. C_LI

bioinformatics↗

bioRxiv2020

A community-driven resource for genomic surveillance of Neisseria gonorrhoeae at Pathogenwatch

BackgroundAntimicrobial resistant (AMR) Neisseria gonorrhoeae is an urgent threat to public health, as strains resistant to at least one of the two last line antibiotics used in empiric therapy of gonorrhoea, ceftriaxone and azithromycin, have spread internationally. Whole genome sequencing (WGS) data can be used to identify new AMR clones, transmission networks and inform the development of point-of-care tests for antimicrobial susceptibility, novel antimicrobials and vaccines. Community driven tools that provide an easy access to and analysis of genomic and epidemiological data is the way forward for public health surveillance. MethodsHere we present a public health focussed scheme for genomic epidemiology of N. gonorrhoeae at Pathogenwatch (https://pathogen.watch/ngonorrhoeae). An international advisory group of experts in epidemiology, public health, genetics and genomics of N. gonorrhoeae was convened to inform on the utility of current and future analytics in the platform. We implement backwards compatibility with MLST, NG-MAST and NG-STAR typing schemes as well as an exhaustive library of genetic AMR determinants linked to a genotypic prediction of resistance to eight antibiotics. A collection of over 12,000 N. gonorrhoeae genome sequences from public archives has been quality-checked, assembled and made public together with available metadata for contextualization. ResultsAMR prediction from genome data revealed specificity values over 99% for azithromycin, ciprofloxacin and ceftriaxone and sensitivity values around 99% for benzylpenicillin and tetracycline. A case study using the Pathogenwatch collection of N. gonorrhoeae public genomes showed the global expansion of an azithromycin resistant lineage carrying a mosaic mtr over at least the last 10 years, emphasizing the power of Pathogenwatch to explore and evaluate genomic epidemiology questions of public health concern. ConclusionsThe N. gonorrhoeae scheme in Pathogenwatch provides customized bioinformatic pipelines guided by expert opinion that can be adapted to public health agencies and departments with little expertise in bioinformatics and lower resourced settings with internet connection but limited computational infrastructure. The advisory group will assess and identify ongoing public health needs in the field of gonorrhoea, particularly regarding gonococcal AMR, in order to further enhance utility with modified or new analytic methods.

genomics↗

bioRxiv2020

Increased antibiotic susceptibility in Neisseria gonorrhoeae through adaptation to the cervical environment

Neisseria gonorrhoeae is an urgent public health threat due to rapidly increasing incidence and antibiotic resistance. In contrast with the trend of increasing resistance, clinical isolates that have reverted to susceptibility regularly appear, prompting questions about which pressures compete with antibiotics to shape gonococcal evolution. Here, we used genome-wide association on the largest collection of N. gonorrhoeae isolates to date (n=4852) to identify loss-of-function (LOF) mutations in the efflux pump mtrCDE operon as a mechanism of increased antibiotic susceptibility and demonstrate that these mutations are overrepresented in cervical isolates relative to urethral isolates (odds ratio (OR) = 3.74, 95% CI [1.98-6.70]). In support of a model in which pump expression incurs a fitness cost in this niche, cervical isolates were also enriched relative to urethral isolates in LOF mutations in the mtrCDE activator mtrA (OR = 8.60, 95% CI [4.96-14.57]) and in farA, a subunit of the FarAB efflux pump (OR = 6.25, 95% CI [3.90-9.83]). In total, approximately 2 in 5 cervical isolates (42.6%) contained a LOF mutation in either the efflux pump components mtrC or farA or the activator mtrA. Our findings extend beyond N. gonorrhoeae to other Neisseria: mtrC LOF mutations are rare (<1%) in the primarily nasopharyngeal-colonizing N. meningitidis in a collection of 14,798 genomes but enriched in a heterosexual urethritis-associated lineage (8.6%, p = 9.90x10-5), indicating that efflux pump downregulation contributes broadly to the adaptation of pathogenic Neisseria to the female urogenital tract. Overall, our findings highlight the impact of integrating microbial population genomics with host metadata and demonstrate how host environmental pressures can lead to increased antibiotic susceptibility.

microbiology↗

bioRxiv2019

Genetic variation regulates the activation and specificity of Restriction-Modification systems in Neisseria gonorrhoeae

Restriction-Modification systems (RMS) are one of the main mechanisms of defence against foreign DNA invasion and can have an important role in the regulation of gene expression. The obligate human pathogen Neisseria gonorrhoeae carries one of the highest loads of RMS in its genome; between 13 to 15 of the three main types. Previous work has described their organization in the reference genome FA1090 and has experimentally inferred the associated methylated motifs. Here, we studied the structure of RMS and target methylated motifs in 25 gonococcal strains sequenced with Single Molecule Real-Time (SMRT) technology, which provides data on DNA modification. The results showed a variable picture of active RMS in different strains, with phase variation switching the activity of Type III RMS, and both the activity and specificity of a Type I RMS. Interestingly, the Dam methylase was found in place of the NgoAXI endonuclease in two of the strains, despite being previously thought to be absent in the gonococcus. We also identified the real methylation target of NgoAX as 5-GCAGA-3, different from that previously described. Results from this work give further insights into the diversity and dynamics of RMS and methylation patterns in N. gonorrhoeae.

microbiology↗

bioRxiv2019

The rise and fall of the new variant of Chlamydia trachomatis in Sweden: mathematical modelling study

ObjectivesA new variant of Chlamydia trachomatis (nvCT) was discovered in Sweden in 2006. The nvCT has a plasmid deletion, which escaped detection by two nucleic acid amplification tests (Abbott/Roche, AR), which were used in 14 of 21 Swedish counties. The objectives of this study were to assess when and where nvCT emerged in Sweden, the proportion of nvCT in each county, and the role of a potential fitness difference between nvCT and co-circulating wild-type strains (wtCT). MethodsWe used a compartmental mathematical model describing the spatial and temporal spread of nvCT and wtCT. We parameterised the model using sexual behaviour data and Swedish spatial and demographic data. We used Bayesian inference to fit the model to surveillance data about reported diagnoses of chlamydia infection in each county and data from four counties that assessed the proportion of nvCT in multiple years. ResultsModel results indicated that nvCT emerged in central Sweden (Dalarna, Gavleborg, Vasternorrland), reaching a proportion of 1% of prevalent CT infections in late 2002 or early 2003. The diagnostic selective advantage enabled rapid spread of nvCT in the presence of high treatment rates. After detection, the proportion of nvCT decreased from 30-70% in AR counties and 5-20% in counties that Becton Dickinson tests, to around 5% in 2015 in all counties. The decrease in nvCT was consistent with an estimated fitness cost of around 5% in transmissibility or 17% reduction in infectious duration. ConclusionsWe reconstructed the course of a natural experiment in which a mutant strain of C. trachomatis spread across Sweden. Our modelling study provides support, for the first time, of a reduced transmissibility or infectious duration of nvCT. This mathematical model improved our understanding of the first nvCT epidemic in Sweden and can be adapted to investigate the impact of future diagnostic escape mutants. Key messagesO_LIThe dynamics of a new variant of Chlamydia trachomatis (nvCT) that escaped testing and treatment in Sweden can be reconstructed using a mathematical transmission model. C_LIO_LIOur study for the first time provides support of a reduced transmissibility or infectious duration of the nvCT in Sweden. C_LIO_LIThis mathematical model improved our understanding of the nvCT epidemic in Sweden and can be adapted to investigate the impact of future diagnostic escape mutants. C_LI

epidemiology↗

bioRxiv2018

Quantitative proteomics of the 2016 WHO Neisseria gonorrhoeae reference strains surveys vaccine candidates and antimicrobial resistance determinants

The sexually transmitted disease gonorrhea (causative agent: Neisseria gonorrhoeae) remains an urgent public health threat globally due to the repercussions on reproductive health, high incidence, widespread antimicrobial resistance (AMR), and absence of a vaccine. To mine gonorrhea antigens and enhance our understanding of gonococcal AMR at the proteome level, we performed the first large-scale proteomic profiling of a diverse panel (n=15) of gonococcal strains, including the 2016 World Health Organization (WHO) reference strains. These strains show all existing AMR profiles, previously described in regard to phenotypic and reference genome characteristics, and are intended for quality assurance in laboratory investigations. Herein, these isolates were subjected to subcellular fractionation and labeling with tandem mass tags coupled to mass spectrometry and multi-combinatorial bioinformatics. Our analyses detected 901 and 723 common proteins in cell envelope and cytoplasmic subproteomes, respectively. We identified nine novel gonorrhea vaccine candidates. Expression and conservation of new and previously selected antigens were investigated. In addition, established gonococcal AMR determinants were evaluated for the first time using quantitative proteomics. Six new proteins, WHO_F_00238, WHO_F_00635, WHO_F_00745, WHO_F_01139, WHO_F_01144, and WHO_F_01226, were differentially expressed in all strains, suggesting that they represent global proteomic AMR markers, indicate a predisposition toward developing or compensating gonococcal AMR, and/or act as new antimicrobial targets. Finally, phenotypic clustering based on the isolates defined antibiograms and common differentially expressed proteins yielded seven matching clusters between established and proteome-derived AMR signatures. Together, our investigations provide a reference proteomics databank for gonococcal vaccine and AMR research endeavors, which enables microbiological, clinical, or epidemiological projects and enhances the utility of the WHO reference strains.

microbiology↗

bioRxiv2018

Oxford Nanopore MinION genome sequencer: performance characteristics, optimised analysis workflow, phylogenetic analysis and prediction of antimicrobial resistance in Neisseria gonorrhoeae

Antimicrobial resistant (AMR) Neisseria gonorrhoeae strains are common and compromise gonorrhoea treatment internationally. Rapid identification and characterisation of AMR gonococcal strains could ensure appropriate and even personalised treatment, and support identification and investigation of gonorrhoea outbreaks in nearly real-time. Whole-genome sequencing is ideal for investigation of the emergence and dissemination of AMR determinants that predict AMR in the gonococcal population and spread of AMR strains in the human population. The novel, rapid and revolutionary long-read sequencer MinION is a small hand-held device that can generate bacterial genomes within one day. However, the accuracy of MinION reads has been suboptimal for many objectives and the MinION has not been evaluated for gonococci. In this first MinION study for gonococci, we show that MinION-derived sequences analysed with existing open-access, web-based sequence analysis tools are not sufficiently accurate to identify key gonococcal AMR determinants. Nevertheless, using an in house-developed CLC Genomics Workbench, we show that ONT-derived sequences can be used for accurate prediction of decreased susceptibility or resistance to recommended therapeutic antimicrobials. We also show that the ONT-derived sequences can be useful for rapid phylogenomic-based molecular epidemiological investigations, and, in hybrid assemblies with Illumina sequences, for producing contiguous assemblies and finished reference genomes.

genomics↗

bioRxiv2018

Antimicrobial exposure in sexual networks drives divergent evolution in modern gonococci

The sexually transmitted pathogen Neisseria gonorrhoeae is regarded as being on the way to becoming an untreatable superbug. Despite its clinical importance, little is known about its emergence and evolution, and how this corresponds with the introduction of antimicrobials. We present a genome-based phylogeographic analysis of 419 gonococcal isolates from across the globe. Results indicate that modern gonococci originated in Europe or Africa as late as the 16thcentury and subsequently disseminated globally. We provide evidence that the modern gonococcal population has been shaped by antimicrobial treatment of sexually transmitted and other infections, leading to the emergence of two major lineages with different evolutionary strategies. The well-described multi-resistant lineage is associated with high rates of homologous recombination and infection in high-risk sexual networks where antimicrobial treatment is frequent. A second, multi-susceptible lineage associated with heterosexual networks, where asymptomatic infection is more common, was also identified, with potential implications for infection control.

genomics↗