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Buultjens, A.

Publications and source records attributed to Buultjens, A..

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A low-cost and versatile paramagnetic bead DNA extraction method for Mycobacterium ulcerans environmental surveillance.

In Australia, native possums are an animal reservoir for Mycobacterium ulcerans, the causative agent of Buruli ulcer, a neglected tropical skin disease that can progress to extensive ulceration with deformity and disability. Surveillance of possum excreta for shedding of M. ulcerans can be used to inform geospatial modelling to predict locations at which humans are at increased risk of disease acquisition. This discovery provides opportunities to disrupt transmission pathways. However, the significant expense of commercial kits used for DNA extraction from environmental samples in large scale surveillance studies can hinder implementation of public health measures. To address this barrier, we developed a low-cost method for extraction of nucleic acids from possum excreta, possum tissue swabs, and mycobacterial cultures, using a guanidinium thiocyanate lysis solution and paramagnetic beads for DNA clean-up. In 96-well plate format for high-throughput processing, the SPRI-bead DNA extraction method for possum excreta was 3-fold less sensitive but only 1/6 the cost of a widely used commercial kit. While a SPRI-bead microtube-based extraction method for tissue swabs sampled from possums was 4-fold more sensitive and 1/5 the cost of the corresponding commercial kit. Furthermore, when used for preparing DNA from pure mycobacterial cultures, the SPRI-bead method produced genomic DNA with quality metrics comparable to more laborious techniques. The methods described here provide an economical means to continue large-scale M. ulcerans environmental surveillance that should facilitate efforts to halt the spread of Buruli ulcer in Victoria, Australia, with potential for applicability in other endemic countries. IMPORTANCEBuruli ulcer is a neglected tropical skin disease, with an incidence that has dramatically increased in temperate southeastern Australia over the last decade. In this region of the world Buruli ulcer is a zoonosis, Australian native possums are a major wildlife reservoir of the causative agent, Mycobacterium ulcerans, and mosquitoes the vector to humans. 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 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.

microbiology↗

A Supervised Statistical Learning Approach For Accurate Legionella pneumophila Source Attribution During Outbreaks

Public health agencies are increasingly relying on genomics during Legionnaires disease investigations. However, the causative bacterium (Legionella pneumophila) has an unusual population structure with extreme temporal and spatial genome sequence conservation. Furthermore, Legionnaires disease outbreaks can be caused by multiple L. pneumophila genotypes in a single source. These factors can confound cluster identification using standard phylogenomic methods. Here, we show that a statistical learning approach based on\n\nL. pneumophila core genome single nucleotide polymorphism (SNP) comparisons eliminates ambiguity for defining outbreak clusters and accurately predicts exposure sources for clinical cases. We illustrate the performance of our method by genome comparisons of 234 L. pneumophila isolates obtained from patients and cooling towers in Melbourne, Australia between 1994 and 2014. This collection included one of the largest reported Legionnaires disease outbreaks, involving 125 cases at an aquarium. Using only sequence data from L. pneumophila cooling tower isolates and including all core genome variation, we built a multivariate model using discriminant analysis of principal components (DAPC) to find cooling tower-specific genomic signatures, and then used it to predict the origin of clinical isolates. Model assignments were 93% congruent with epidemiological data, including the aquarium Legionnaires outbreak and three other unrelated outbreak investigations. We applied the same approach to a recently described investigation of Legionnaires disease within a UK hospital and observed model predictive ability of 86%. We have developed a promising means to breach L. pneumophila genetic diversity extremes and provide objective source attribution data for outbreak investigations.

microbiology↗