High performance Legionella pneumophila source attribution using genomics-based machine learning classification.

Fundamental to effective Legionnaires' disease outbreak control is the ability to rapidly identify the environmental source(s) of the causative agent, Legionella pneumophila. Genomics has revolutionized pathogen surveillance, but L. pneumophila has a complex ecology and population structure that can limit source inference based on standard core genome phylogenetics. Here, we present a powerful machine learning approach that assigns the geographical source of Legionnaires' disease outbreaks more accurately than current core genome comparisons. Models were developed upon 534 L. pneumophila genome sequences, including 149 genomes linked to 20 previously reported Legionnaires' disease outbreaks through detailed case investigations. Our classification models were developed in a cross-validation framework using only environmental L. pneumophila genomes. Assignments of clinical isolate geographic origins demonstrated high predictive sensitivity and specificity of the models, with no false positives or false negatives for 13 out of 20 outbreak groups, despite the presence of within-outbreak polyclonal population structure. Analysis of the same 534-genome panel with a conventional phylogenomic tree and a core genome multi-locus sequence type allelic distance-based classification approach revealed that our machine learning method had the highest overall classification performance-agreement with epidemiological information. Our multivariate statistical learning approach maximizes the use of genomic variation data and is thus well-suited for supporting Legionnaires' disease outbreak investigations.IMPORTANCEIdentifying the sources of Legionnaires' disease outbreaks is crucial for effective control. Current genomic methods, while useful, often fall short due to the complex ecology and population structure of Legionella pneumophila, the causative agent. Our study introduces a high-performing machine learning approach for more accurate geographical source attribution of Legionnaires' disease outbreaks. Developed using cross-validation on environmental L. pneumophila genomes, our models demonstrate excellent predictive sensitivity and specificity. Importantly, this new approach outperforms traditional methods like phylogenomic trees and core genome multi-locus sequence typing, proving more efficient at leveraging genomic variation data to infer outbreak sources. Our machine learning algorithms, harnessing both core and accessory genomic variation, offer significant promise in public health settings. By enabling rapid and precise source identification in Legionnaires' disease outbreaks, such approaches have the potential to expedite intervention efforts and curtail disease transmission.

Bacterial endosymbionts protect beneficial soil fungus from nematode attack.

Fungi of the genus Mortierella occur ubiquitously in soils where they play pivotal roles in carbon cycling, xenobiont degradation, and promoting plant growth. These important fungi are, however, threatened by micropredators such as fungivorous nematodes, and yet little is known about their protective tactics. We report that Mortierella verticillata NRRL 6337 harbors a bacterial endosymbiont that efficiently shields its host from nematode attacks with anthelmintic metabolites. Microscopic investigation and 16S ribosomal DNA analysis revealed that a previously overlooked bacterial symbiont belonging to the genus Mycoavidus dwells in M. verticillata hyphae. Metabolic profiling of the wild-type fungus and a symbiont-free strain obtained by antibiotic treatment as well as genome analyses revealed that highly cytotoxic macrolactones (CJ-12,950 and CJ-13,357, syn necroxime C and D), initially thought to be metabolites of the soil-inhabiting fungus, are actually biosynthesized by the endosymbiont. According to comparative genomics, the symbiont belongs to a new species (Candidatus Mycoavidus necroximicus) with 12% of its 2.2 Mb genome dedicated to natural product biosynthesis, including the modular polyketide-nonribosomal peptide synthetase for necroxime assembly. Using Caenorhabditis elegans and the fungivorous nematode Aphelenchus avenae as test strains, we show that necroximes exert highly potent anthelmintic activities. Effective host protection was demonstrated in cocultures of nematodes with symbiotic and chemically complemented aposymbiotic fungal strains. Image analysis and mathematical quantification of nematode movement enabled evaluation of the potency. Our work describes a relevant role for endofungal bacteria in protecting fungi against mycophagous nematodes.

Unstable chromosome rearrangements in Staphylococcus aureus cause phenotype switching associated with persistent infections.

Staphylococcus aureus small-colony variants (SCVs) are associated with unusually chronic and persistent infections despite active antibiotic treatment. The molecular basis for this clinically important phenomenon is poorly understood, hampered by the instability of the SCV phenotype. Here we investigated the genetic basis for an unstable S. aureus SCV that arose spontaneously while studying rifampicin resistance. This SCV showed no nucleotide differences across its genome compared with a normal-colony variant (NCV) revertant, yet the SCV presented the hallmarks of S. aureus linked to persistent infection: down-regulation of virulence genes and reduced hemolysis and neutrophil chemotaxis, while exhibiting increased survival in blood and ability to invade host cells. Further genome analysis revealed chromosome structural variation uniquely associated with the SCV. These variations included an asymmetric inversion across half of the S. aureus chromosome via recombination between type I restriction modification system (T1RMS) genes, and the activation of a conserved prophage harboring the immune evasion cluster (IEC). Phenotypic reversion to the wild-type-like NCV state correlated with reversal of the chromosomal inversion (CI) and with prophage stabilization. Further analysis of 29 complete S. aureus genomes showed strong signatures of recombination between hsdMS genes, suggesting that analogous CI has repeatedly occurred during S. aureus evolution. Using qPCR and long-read amplicon deep sequencing, we detected subpopulations with T1RMS rearrangements causing CIs and prophage activation across major S. aureus lineages. Here, we have discovered a previously unrecognized and widespread mechanism of reversible genomic instability in S. aureus associated with SCV generation and persistent infections.

Comparative Genomics Shows That Mycobacterium ulcerans Migration and Expansion Preceded the Rise of Buruli Ulcer in Southeastern Australia.

Since 2000, cases of the neglected tropical disease Buruli ulcer, caused by infection with Mycobacterium ulcerans, have increased 100-fold around Melbourne (population 4.4 million), the capital of Victoria, in temperate southeastern Australia. The reasons for this increase are unclear. Here, we used whole-genome sequence comparisons of 178 M. ulcerans isolates obtained primarily from human clinical specimens, spanning 70 years, to model the population dynamics of this pathogen from this region. Using phylogeographic and advanced Bayesian phylogenetic approaches, we found that there has been a migration of the pathogen from the east end of the state, beginning in the 1980s, 300 km west to the major human population center around Melbourne. This move was then followed by a significant increase in M. ulcerans population size. These analyses inform our thinking around Buruli ulcer transmission and control, indicating that M. ulcerans is introduced to a new environment and then expands, rather than it being from the awakening of a quiescent pathogen reservoir.IMPORTANCE Buruli ulcer is a destructive skin and soft tissue infection caused by Mycobacterium ulcerans and is characterized by progressive skin ulceration, which can lead to permanent disfigurement and long-term disability. Despite the majority of disease burden occurring in regions of West and central Africa, Buruli ulcer is also becoming increasingly common in southeastern Australia. Major impediments to controlling disease spread are incomplete understandings of the environmental reservoirs and modes of transmission of M. ulcerans The significance of our research is that we used genomics to assess the population structure of this pathogen at the Australian continental scale. We have then reconstructed a historical bacterial spread and modeled demographic dynamics to reveal bacterial population expansion across southeastern Australia. These findings provide explanations for the observed epidemiological trends with Buruli ulcer and suggest possible management to control disease spread.

Insertion sequence element single nucleotide polymorphism typing provides insights into the population structure and evolution of Mycobacterium ulcerans across Africa.

Buruli ulcer is an indolent, slowly progressing necrotizing disease of the skin caused by infection with Mycobacterium ulcerans. In the present study, we applied a redesigned technique to a vast panel of M. ulcerans disease isolates and clinical samples originating from multiple African disease foci in order to (i) gain fundamental insights into the population structure and evolutionary history of the pathogen and (ii) disentangle the phylogeographic relationships within the genetically conserved cluster of African M. ulcerans. Our analyses identified 23 different African insertion sequence element single nucleotide polymorphism (ISE-SNP) types that dominate in different areas where Buruli ulcer is endemic. These ISE-SNP types appear to be the initial stages of clonal diversification from a common, possibly ancestral ISE-SNP type. ISE-SNP types were found unevenly distributed over the greater West African hydrological drainage basins. Our findings suggest that geographical barriers bordering the basins to some extent prevented bacterial gene flow between basins and that this resulted in independent focal transmission clusters associated with the hydrological drainage areas. Different phylogenetic methods yielded two well-supported sister clades within the African ISE-SNP types. The ISE-SNP types from the "pan-African clade" were found to be widespread throughout Africa, while the ISE-SNP types of the "Gabonese/Cameroonian clade" were much rarer and found in a more restricted area, which suggested that the latter clade evolved more recently. Additionally, the Gabonese/Cameroonian clade was found to form a strongly supported monophyletic group with Papua New Guinean ISE-SNP type 8, which is unrelated to other Southeast Asian ISE-SNP types.

Unraveling the intricacies of host-pathogen interaction through single-cell genomics.

Single-cell genomics provide researchers with tools to assess host-pathogen interactions at a resolution previously inaccessible. Transcriptome analysis, epigenome analysis, and immune profiling techniques allow for a better comprehension of the heterogeneity underlying both the host response and infectious agents. Here, we highlight technological advancements and data analysis workflows that increase our understanding of host-pathogen interactions at the single-cell level. We review various studies that have used these tools to better understand host-pathogen dynamics in a variety of infectious disease contexts, including viral, bacterial, and parasitic diseases. We conclude by discussing how single-cell genomics can advance our understanding of host-pathogen interactions.

Genomic oropharyngeal Neisseria surveillance detects MALDI-TOF MS species misidentifications and reveals a novel Neisseria cinerea clade.

Introduction. Commensal Neisseria spp. are highly prevalent in the oropharynx as part of the healthy microbiome. N. meningitidis can colonise the oropharynx too from where it can cause invasive meningococcal disease. To identify N. meningitidis, clinical microbiology laboratories often rely on Matrix Assisted Laser Desorption/Ionisation Time of Flight Mass Spectrometry (MALDI-TOF MS).Hypothesis/Gap statement. N. meningitidis may be misidentified by MALDI-TOF MS.Aim. To conduct genomic surveillance of oropharyngeal Neisseria spp. in order to: (i) verify MALDI-TOF MS species identification, and (ii) characterize commensal Neisseria spp. genomes.Methodology. We analysed whole genome sequence (WGS) data from 119 Neisseria spp. isolates from a surveillance programme for oropharyngeal Neisseria spp. in Belgium. Different species identification methods were compared: (i) MALDI-TOF MS, (ii) Ribosomal Multilocus Sequence Typing (rMLST) and (iii) rplF gene species identification. WGS data were used to further characterize Neisseria species found with supplementary analyses of Neisseria cinerea genomes.Results. Based on genomic species identification, isolates from the oropharyngeal Neisseria surveilence study were composed of the following species: N. meningitidis (n=23), N. subflava (n=61), N. mucosa (n=15), N. oralis (n=8), N. cinerea (n=5), N. elongata (n=3), N. lactamica (n=2), N. bacilliformis (n=1) and N. polysaccharea (n=1). Of these 119 isolates, four isolates identified as N. meningitidis (n=3) and N. subflava (n=1) by MALDI-TOF MS, were determined to be N. polysaccharea (n=1), N. cinerea (n=2) and N. mucosa (n=1) by rMLST. Phylogenetic analyses revealed that N. cinerea isolates from the general population (n=3, cluster one) were distinct from those obtained from men who have sex with men (MSM, n=2, cluster two). The latter contained genomes misidentified as N. meningitidis using MALDI-TOF MS. These two N. cinerea clusters persisted after the inclusion of published N. cinerea WGS (n=42). Both N. cinerea clusters were further defined through pangenome and Average Nucleotide Identity (ANI) analyses.Conclusion. This study provides insights into the importance of genomic genus-wide Neisseria surveillance studies to improve the characterization and identification of the Neisseria genus.

Phylogenomic investigation of an outbreak of fluoroquinolone-resistant Salmonella enterica subsp. enterica serovar Paratyphi A in Phnom Penh, Cambodia.

In early 2020, the Medical Biology Laboratory of the Pasteur Institute of Cambodia isolated an unusually high number of fluoroquinolone-resistant Salmonella enterica subspecies enterica serovar Paratyphi A strains during its routine bacteriological surveillance activities in Phnom Penh, Cambodia. A public-health investigation was supported by genome sequencing of these Paratyphi A strains to gain insights into the genetic diversity and population structure of a potential outbreak of fluoroquinolone-resistant paratyphoid fever. Comparative genomic and phylodynamic analyses revealed the 2020 strains were descended from a previously described 2013-2015 outbreak of Paratyphi A infections. Our analysis showed sub-lineage 2.3.1 had remained largely susceptible to fluoroquinolone drugs until 2015, but acquired chromosomal resistance to these drugs during six separate events between late 2012 and 2015. The emergence of fluoroquinolone resistance was rapidly followed by the replacement of the original susceptible Paratyphi A population, which led to a dramatic increase of fluoroquinolone-resistant blood-culture-confirmed cases in subsequent years (2016-2020). The rapid acquisition of resistance-conferring mutations in the Paratyphi A population over a 3 year period is suggestive of a strong selective pressure on that population, likely linked with fluoroquinolone use. In turn, emergence of fluoroquinolone resistance has led to increased use of extended-spectrum cephalosporins like ceftriaxone that are becoming the drug of choice for empirical treatment of paratyphoid fever in Cambodia.

Statistical modeling based on structured surveys of Australian native possum excreta harboring Mycobacterium ulcerans predicts Buruli ulcer occurrence in humans.

Background: Buruli ulcer (BU) is a neglected tropical disease caused by infection of subcutaneous tissue with Mycobacterium ulcerans. BU is commonly reported across rural regions of Central and West Africa but has been increasing dramatically in temperate southeast Australia around the major metropolitan city of Melbourne, with most disease transmission occurring in the summer months. Previous research has shown that Australian native possums are reservoirs of M. ulcerans and that they shed the bacteria in their fecal material (excreta). Field surveys show that locales where possums harbor M. ulcerans overlap with human cases of BU, raising the possibility of using possum excreta surveys to predict the risk of disease occurrence in humans. Methods: We thus established a highly structured 12 month possum excreta surveillance program across an area of 350 km2 in the Mornington Peninsula area 70 km south of Melbourne, Australia. The primary objective of our study was to assess using statistical modeling if M. ulcerans surveillance of possum excreta provided useful information for predicting future human BU case locations. Results: Over two sampling campaigns in summer and winter, we collected 2,282 possum excreta specimens of which 11% were PCR positive for M. ulcerans-specific DNA. Using the spatial scanning statistical tool SaTScan, we observed non-random, co-correlated clustering of both M. ulcerans positive possum excreta and human BU cases. We next trained a statistical model with the Mornington Peninsula excreta survey data to predict the future likelihood of human BU cases occurring in the region. By observing where human BU cases subsequently occurred, we show that the excreta model performance was superior to a null model trained using the previous year's human BU case incidence data (AUC 0.66 vs 0.55). We then used data unseen by the excreta-informed model from a new survey of 661 possum excreta specimens in Geelong, a geographically separate BU endemic area to the southwest of Melbourne, to prospectively predict the location of human BU cases in that region. As for the Mornington Peninsula, the excreta-based BU prediction model outperformed the null model (AUC 0.75 vs 0.50) and pinpointed specific locations in Geelong where interventions could be deployed to interrupt disease spread. Conclusions: This study highlights the One Health nature of BU by confirming a quantitative relationship between possum excreta shedding of M. ulcerans and humans developing BU. The excreta survey-informed modeling we have described will be a powerful tool for the efficient targeting of public health responses to stop BU. Funding: This research was supported by the National Health and Medical Research Council of Australia and the Victorian Government Department of Health (GNT1152807 and GNT1196396).

Effects of decontamination, DNA extraction, and amplification procedures on the molecular diagnosis of Mycobacterium ulcerans disease (Buruli ulcer).

We compared two DNA extraction methods (a semiautomated method using a Maxwell kit and a modified Boom method) and three amplification procedures (a single-step PCR, a nested PCR, and a real-time quantitative PCR) on 74 surgical tissue specimens from patients with clinically suspected Buruli ulcer. All of these procedures were compared before and after decontamination. We observed that, among the procedures tested, real-time PCR after the modified Boom extraction method or a single-run PCR assay after the Maxwell 16 extraction method, performed on nondecontaminated suspensions, are the best for the molecular diagnosis of Mycobacterium ulcerans disease.