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In Australia, native possums are a major wildlife reservoir for Mycobacterium ulcerans , the causative agent of the neglected tropical skin disease Buruli ulcer (BU). Large-scale possum excreta surveys that use PCR to detect M. ulcerans in 100-1,000 s of excreta specimens are an important tool that can inform geospatial modeling and predict locations of future human BU risk. However, the significant expense of commercial kits used to extract DNA from specimens is a major barrier to routine implementation. Here, we developed a low-cost method for DNA extraction from possum excreta, possum tissue, and pure mycobacterial cultures, using a guanidinium isothiocyanate lysis solution and paramagnetic beads. In a 96-well plate format for high-throughput processing, the paramagnetic bead DNA extraction method was threefold less sensitive but only 1/6 the cost of a commonly used commercial kit. Applied to tissue swabs, the method was fourfold more sensitive and 1/5 the cost of a commercial kit. When used for preparing DNA from pure mycobacterial cultures, the method yielded purified genomic DNA with quality metrics comparable to more lengthy techniques. Our paramagnetic bead method is an economical means to undertake large-scale M. ulcerans environmental surveillance that will directly inform efforts to halt the spread of BU in Victoria, Australia, with potential for applicability in other endemic countries., Importance: Buruli ulcer (BU) is a neglected tropical skin disease, with an incidence that has dramatically increased in temperate southeastern Australia over the last decade. In southeastern Australia, BU is a zoonosis with native possums the major wildlife reservoir of the causative pathogen, Mycobacterium ulcerans . Infected possums shed M. ulcerans in their excreta, and excreta surveys using PCR to screen for the presence of pathogen DNA are a powerful means to predict future areas of Buruli ulcer risk for humans. However, excreta surveys across large geographic areas require testing of many thousands of samples. The cost of commercial DNA extraction reagents used for preparing samples for PCR testing can thus become prohibitive to effective surveillance. Here, we describe a simple, low-cost method for extracting DNA from possum excreta using paramagnetic beads. The method is versatile and adaptable to a variety of other sample types including swabs collected from possum tissues and pure cultures of mycobacteria.

Alphavirus infections are transmitted by mosquitoes, but the mode of transmission for Mycobacterium ulcerans, which causes Buruli ulcer, is contested. Using notification data for Victoria, Australia, during 2017-2022, adjusted for incubation period, we show close alignment between alphavirus and Buruli ulcer seasons, supporting the hypothesis of mosquito transmission of M. ulcerans.

Haemophilus influenzae is a human respiratory pathogen and inhabits the human respiratory tract as its only niche. Despite this, the molecular mechanisms that allow H. influenzae to establish persistent infections of human epithelia are not well understood. Here, we have investigated how H. influenzae adapts to the host environment and triggers the host immune response using a human primary cell-based infection model that closely resembles human nasal epithelia (NHNE). Physiological assays combined with dualRNAseq revealed that NHNE from five healthy donors all responded to H. influenzae infection with an initial, 'unproductive' inflammatory response that included a strong hypoxia signature but did not produce pro-inflammatory cytokines. Subsequently, an apparent tolerance to large extracellular and intraepithelial burdens of H. influenzae developed, with NHNE transcriptional profiles resembling the pre-infection state. This occurred in parallel with the development of intraepithelial bacterial populations, and appears to involve interruption of NFκB signalling. This is the first time that large-scale, persistence-promoting immunomodulatory effects of H. influenzae during infection have been observed, and we were able to demonstrate that only infections with live, but not heat-killed H. influenzae led to immunomodulation and reduced expression of NFκB-controlled cytokines such as IL-1β, IL-36γ and TNFα. Interestingly, NHNE were able to re-activate pro-inflammatory responses towards the end of the 14-day infection, resulting in release of IL-8 and TNFα. In addition to providing first molecular insights into mechanisms enabling persistence of H. influenzae in the host, our data further indicate the presence of infection stage-specific gene expression modules, highlighting fundamental similarities between immune responses in NHNE and canonical immune cells, which merit further investigation., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Kappler et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Critical scientific questions remain regarding infection with Mycobacterium ulcerans, the organism responsible for the neglected tropical disease, Buruli ulcer (BU). A controlled human infection model has the potential to accelerate our knowledge of the immunological correlates of disease, to test prophylactic interventions and novel therapeutics. Here we present microbiological evidence supporting M. ulcerans JKD8049 as a suitable human challenge strain. This non-genetically modified Australian isolate is susceptible to clinically relevant antibiotics, can be cultured in animal-free and surfactant-free media, can be enumerated for precise dosing, and has stable viability following cryopreservation. Infectious challenge of humans with JKD8049 is anticipated to imitate natural infection, as M. ulcerans JKD8049 is genetically stable following in vitro passage and produces the key virulence factor, mycolactone. Also reported are considerations for the manufacture, storage, and administration of M. ulcerans JKD8049 for controlled human infection., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Muhi et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

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., Competing Interests: The authors declare no conflict of interest.

Buruli ulcer, a chronic subcutaneous infection caused by Mycobacterium ulcerans, is increasing in prevalence in southeastern Australia. Possums are a local wildlife reservoir for M. ulcerans and, although mosquitoes have been implicated in transmission, it remains unclear how humans acquire infection. We conducted extensive field survey analyses of M. ulcerans prevalence among mosquitoes in the Mornington Peninsula region of southeastern Australia. PCR screening of trapped mosquitoes revealed a significant association between M. ulcerans and Aedes notoscriptus. Spatial scanning statistics revealed overlap between clusters of M. ulcerans-positive Ae. notoscriptus, M. ulcerans-positive possum excreta and Buruli ulcer cases, and metabarcoding analyses showed individual mosquitoes had fed on humans and possums. Bacterial genomic analysis confirmed shared single-nucleotide-polymorphism profiles for M. ulcerans detected in mosquitoes, possum excreta and humans. These findings indicate Ae. notoscriptus probably transmit M. ulcerans in southeastern Australia and highlight mosquito control as a Buruli ulcer prevention measure., (© 2024. The Author(s).)

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 km 2 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)., Competing Interests: KV, AB, JP, AV, JW, KB, MD, VB, JF, ET, PJ, SW, NG, TS No competing interests declared, (© 2023, Vandelannoote, Buultjens et al.)

The ability to detect SARS-CoV-2 is critical to implementing evidence-based strategies to address the COVID-19 global pandemic. Expanding SARS-CoV-2 diagnostic ability beyond well-equipped laboratories widens the opportunity for surveillance and control efforts. However, such advances are predicated on the availability of rapid, scalable, accessible, yet high-performance diagnostic platforms. Methods to detect viral RNA using reverse transcription loop-mediated isothermal amplification (RT-LAMP) show promise as rapid and field-deployable tests; however, the per-unit costs of the required diagnostic hardware can be a barrier for scaled deployment. Here, we describe a diagnostic hardware configuration for LAMP technology, named the FABL-8 , that can be built for approximately US$380 per machine and provide results in under 30 min. Benchmarking showed that FABL-8 has a similar performance to a high-end commercial instrument for detecting fluorescence-based LAMP reactions. Performance testing of the instrument with RNA extracted from a SARS-CoV-2 virus dilution series revealed an analytical detection sensitivity of 50 virus copies per microliter-a detection threshold suitable to detect patient viral load in the first few days following symptom onset. In addition to the detection of SARS-CoV-2, we show that the system can be used to detect the presence of two bacterial pathogens, demonstrating the versatility of the platform for the detection of other pathogens. This cost-effective and scalable hardware alternative allows democratization of the instrumentation required for high-performance molecular diagnostics, such that it could be available to laboratories anywhere-supporting infectious diseases surveillance and research activities in resource-limited settings.

The COVID-19 pandemic has exposed the dependence of diagnostic laboratories on a handful of large corporations with market monopolies on the worldwide supply of reagents, consumables, and hardware for molecular diagnostics. Global shortages of key consumables for RT-qPCR detection of SARS-CoV-2 RNA have impaired the ability to run essential, routine diagnostic services. Here, we describe a workflow for rapid detection of SARS-CoV-2 RNA in upper respiratory samples including nasal swabs and saliva, utilizing low-cost equipment and readily accessible reagents. Using repurposed Creality3D Ender-3 three-dimensional (3D) printers, we built a semiautomated paramagnetic bead RNA extraction platform. The hardware for the system was built for $300 USD, and the material cost per reaction was $1 USD. Named the Ender VX500 , instrument performance when paired with RT-qPCR for SARS-CoV-2 detection in nasal and saliva specimens was two virus copies per microliter. There was a high-performance agreement (assessed using 458 COVID-19 nasal swab specimens) with the Aptima SARS-CoV-2 assay run on the Hologic Panther, a commercial automated RNA extraction and detection platform. Inter- and intrainstrument precision was excellent (coefficients of variation (CoV) of 1.10 and 0.66-1.32%, respectively) across four instruments. The platform is scalable with throughput ranging from 23 specimens on a single instrument run by one user in 50 min to 364 specimens on four instruments run by four users in 190 min. Step-by-step instructions and protocols for building and running the Ender VX500 have been made available without restriction.