Genomic determinants of speciation and spread of the Mycobacterium tuberculosis complex

Models on how bacterial lineages differentiate increase our understanding of early bacterial speciation events and the genetic loci involved. Here, we analyze the population genomics events leading to the emergence of the tuberculosis pathogen. The emergence is characterized by a combination of recombination events involving core pathogenesis functions and purifying selection on early diverging loci. We identify the phoR gene, the sensor kinase of a two-component system involved in virulence, as a key functional player subject to pervasive positive selection after the divergence of the Mycobacterium tuberculosis complex from its ancestor. Previous evidence showed that phoR mutations played a central role in the adaptation of the pathogen to different host species. Now, we show that phoR mutations have been under selection during the early spread of human tuberculosis, during later expansions, and in ongoing transmission events. Our results show that linking pathogen evolution across evolutionary and epidemiological time scales points to past and present virulence determinants.Peer reviewe

Genomics for public health and international surveillance of antimicrobial resistance.

Historically, epidemiological investigation and surveillance for bacterial antimicrobial resistance (AMR) has relied on low-resolution isolate-based phenotypic analyses undertaken at local and national reference laboratories. Genomic sequencing has the potential to provide a far more high-resolution picture of AMR evolution and transmission, and is already beginning to revolutionise how public health surveillance networks monitor and tackle bacterial AMR. However, the routine integration of genomics in surveillance pipelines still has considerable barriers to overcome. In 2022, a workshop series and online consultation brought together international experts in AMR and pathogen genomics to assess the status of genomic applications for AMR surveillance in a range of settings. Here we focus on discussions around the use of genomics for public health and international AMR surveillance, noting the potential advantages of, and barriers to, implementation, and proposing recommendations from the working group to help to drive the adoption of genomics in public health AMR surveillance. These recommendations include the need to build capacity for genome sequencing and analysis, harmonising and standardising surveillance systems, developing equitable data sharing and governance frameworks, and strengthening interactions and relationships among stakeholders at multiple levels

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 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 NgoAXII 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

Evaluation of parameters affecting performance and reliability of machine learning-based antibiotic susceptibility testing from whole genome sequencing data.

Prediction of antibiotic resistance phenotypes from whole genome sequencing data by machine learning methods has been proposed as a promising platform for the development of sequence-based diagnostics. However, there has been no systematic evaluation of factors that may influence performance of such models, how they might apply to and vary across clinical populations, and what the implications might be in the clinical setting. Here, we performed a meta-analysis of seven large Neisseria gonorrhoeae datasets, as well as Klebsiella pneumoniae and Acinetobacter baumannii datasets, with whole genome sequence data and antibiotic susceptibility phenotypes using set covering machine classification, random forest classification, and random forest regression models to predict resistance phenotypes from genotype. We demonstrate how model performance varies by drug, dataset, resistance metric, and species, reflecting the complexities of generating clinically relevant conclusions from machine learning-derived models. Our findings underscore the importance of incorporating relevant biological and epidemiological knowledge into model design and assessment and suggest that doing so can inform tailored modeling for individual drugs, pathogens, and clinical populations. We further suggest that continued comprehensive sampling and incorporation of up-to-date whole genome sequence data, resistance phenotypes, and treatment outcome data into model training will be crucial to the clinical utility and sustainability of machine learning-based molecular diagnostics

Antimicrobial resistance prediction and phylogenetic analysis of Neisseria gonorrhoeae isolates using the Oxford Nanopore MinION sequencer

Antimicrobial resistance (AMR) in Neisseria gonorrhoeae is common, compromising gonorrhoea treatment internationally. Rapid characterisation of AMR strains could ensure appropriate and personalised treatment, and support identification and investigation of gonorrhoea outbreaks in nearly real-time. Whole-genome sequencing is ideal for investigation of emergence and dissemination of AMR determinants, predicting 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 generates bacterial genomes within one day. However, 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 including de novo assembly and optimised BLAST algorithms, we show that 2D ONT-derived sequences can be used for accurate prediction of decreased susceptibility or resistance to recommended antimicrobials in gonococcal isolates. We also show that the 2D ONT-derived sequences are useful for rapid phylogenomic-based molecular epidemiological investigations, and, in hybrid assemblies with Illumina sequences, for producing contiguous assemblies and finished reference genomes.</p

Antimicrobial resistance prediction and phylogenetic analysis of Neisseria gonorrhoeae isolates using the Oxford Nanopore MinION sequencer

Antimicrobial resistance (AMR) inandnbsp;Neisseria gonorrhoeaeandnbsp;is common, compromising gonorrhoea treatment internationally. Rapid characterisation of AMR strains could ensure appropriate and personalised treatment, and support identification and investigation of gonorrhoea outbreaks in nearly real-time. Whole-genome sequencing is ideal for investigation of emergence and dissemination of AMR determinants, predicting 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 generates bacterial genomes within one day. However, 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 anandnbsp;in house-developed CLC Genomics Workbench includingandnbsp;de novoandnbsp;assembly and optimised BLAST algorithms, we show that 2Dandnbsp;ONT-derived sequences can be used for accurate prediction of decreased susceptibility or resistance to recommended antimicrobials in gonococcal isolates. We also show that the 2Dandnbsp;ONT-derived sequences are useful for rapid phylogenomic-based molecular epidemiological investigations, and, in hybrid assemblies with Illumina sequences, for producing contiguous assemblies and finished reference genomes.</p

Increased power from conditional bacterial genome-wide association identifies macrolide resistance mutations in Neisseria gonorrhoeae

The mechanisms underlying resistance of Neisseria gonorrhoeae to the antibiotic azithromycin are incompletely understood. Here, Ma et al. conduct a conditional genome-wide association study to identify new resistance mutations and experimentally confirm that a mutation in ribosomal protein L4 confers increased resistance

Genomic epidemiology of a national outbreak of post-surgical Mycobacterium abscessus wound infections in Brazil

An epidemic of post-surgical wound infections, caused by a non-tuberculous mycobacterium, has been on-going in Brazil. It has been unclear whether one or multiple lineages are responsible and whether their wide geographical distribution across Brazil is due to spread from a single point source or is the result of human-mediated transmission. 188 isolates, collected from nine Brazilian states, were whole genome sequenced and analysed using phylogenetic and comparative genomic approaches. The isolates from Brazil formed a single clade, which was estimated to have emerged in 2003. We observed temporal and geographic structure within the lineage that enabled us to infer the movement of sub-lineages across Brazil. The genome size of the Brazilian lineage was reduced relative to most strains in the three subspecies of Mycobacterium abscessus and contained a novel plasmid, pMAB02, in addition to the previously described pMAB01 plasmid. One lineage, which emerged just prior to the initial outbreak, is responsible for the epidemic of post-surgical wound infections in Brazil. Phylogenetic analysis indicates that multiple transmission events led to its spread. The presence of a novel plasmid and the reduced genome size suggest that the lineage has undergone adaptation to the surgical niche