Development of an Interspecies Nested Dose-Response Model for Mycobacterium avium subspecies paratuberculosis

A microbial risk assessor's guide to Valley Fever (Coccidioides spp.): Case study and review of risk factors

Valley Fever is a respiratory disease caused by inhalation of arthroconidia, a type of spore produced by fungi within the genus Coccidioides spp. which are found in dry, hot ecosystems of the Western Hemisphere. A quantitative microbial risk assessment (QMRA) for the disease has not yet been performed due to a lack of dose-response models and a scarcity of quantitative occurrence data from environmental samples. A literature review was performed to gather data on experimental animal dosing studies, environmental occurrence, human disease outbreaks, and meteorological associations. As a result, a risk framework is presented with information for parameterizing QMRA models for Coccidioides spp., with eight new dose-response models proposed. A probabilistic QMRA was conducted for a Southwestern US agricultural case study, evaluating eight scenarios related to farming occupational exposures. Median daily workday risks for developing severe Valley Fever ranged from 2.53 × 10-7 (planting by hand while wearing an N95 facemask) to 1.33 × 10-3 (machine harvesting while not wearing a facemask). The literature review and QMRA synthesis confirmed that exposure to aerosolized arthroconidia has the potential to result in high attack rates but highlighted that the mechanistic relationships between environmental conditions and disease remain poorly understood. Recommendations for Valley Fever risk assessment research needs in order to reduce disease risks are discussed, including interventions for farmers.

A High-Throughput Approach for Identification of Nontuberculous Mycobacteria in Drinking Water Reveals Relationship between Water Age and Mycobacterium avium

Nontuberculous mycobacteria (NTM) frequently detected in drinking water (DW) include species associated with human infections, as well as species rarely linked to disease. Methods for improved the recovery of NTM DNA and high-throughput identification of NTM are needed for risk assessment of NTM infection through DW exposure. In this study, different methods of recovering bacterial DNA from DW were compared, revealing that a phenol-chloroform DNA extraction method yielded two to four times as much total DNA and eight times as much NTM DNA as two commercial DNA extraction kits. This method, combined with high-throughput, single-molecule real-time sequencing of NTM rpoB genes, allowed the identification of NTM to the species, subspecies, and (in some cases) strain levels. This approach was applied to DW samples collected from 15 households serviced by a chloraminated distribution system, with homes located in areas representing short (<24 h) and long (>24 h) distribution system residence times. Multivariate statistical analysis revealed that greater water age (i.e., combined distribution system residence time and home plumbing stagnation time) was associated with a greater relative abundance of Mycobacterium avium subsp. avium, one of the most prevalent NTM causing infections in humans. DW from homes closer to the treatment plant (with a shorter water age) contained more diverse NTM species, including Mycobacterium abscessus and Mycobacterium chelonae. Overall, our approach allows NTM identification to the species and subspecies levels and can be used in future studies to assess the risk of waterborne infection by providing insight into the similarity between environmental and infection-associated NTM.

An extraction method for improved recovery of DNA from nontuberculous mycobacteria (NTM), combined with single-molecule real-time sequencing (PacBio) of NTM rpoB genes, was used for high-throughput characterization of NTM species and in some cases strains in drinking water (DW). The extraction procedure recovered, on average, eight times as much NTM DNA and three times as much total DNA from DW as two widely used commercial DNA extraction kits. The combined DNA extraction and sequencing approach allowed high-throughput screening of DW samples to identify NTM, revealing that the relative abundance of Mycobacterium avium subsp. avium increased with water age. Furthermore, the two-step barcoding approach developed as part of the PacBio sequencing method makes this procedure highly adaptable, allowing it to be used for other target genes and species.

Distribution comparison and risk assessment of free-floating and particle-attached bacterial pathogens in urban recreational water: Implications for water quality management

The risk of pathogen exposure in recreational water is a concern worldwide. Moreover, suspended particles, as ideal shelters for pathogens, in these waters also need attention. However, the risk caused by the pathogen-particle attachment is largely unknown. Accordingly, water samples in three recreational lakes in Beijing were collected and separated into free-floating (FL, 0.22-5μm) and particle-attached (PA, >5μm) fractions. Next-generation sequencing (NGS) was employed to determine the diversity of genera containing pathogens, and quantitative PCR (qPCR) was used to assess the presence of genes from Escherichia coli (uidA), Salmonella enterica (invA), Aeromonas spp. (aerA), Mycobacterium avium (16S) and Pseudomonas aeruginosa (oaa). The NGS results showed stable pathogen genera composition distinctions between the PA and FL fractions. Some genera, such as Aeromonas and Mycobacterium, exhibited higher abundances in the PA fractions. qPCR revealed that most of the gene concentrations were higher within particles than were FL fractions. Some gene levels showed correlations with the particle concentrations and lake nutrient levels. Further quantitative microbial risk assessment (QMRA) of selected strains (S. enterica and M. avium) indicated a higher health risk during secondary contact activities in lakes with more nutrients and particles. We concluded that suspended particles (mainly composed of algae) in urban recreational water might influence the pathogen distribution and could serve as reservoirs for pathogen contamination, with important management implications.

Human health risks for Legionella and Mycobacterium avium complex (MAC) from potable and non-potable uses of roof-harvested rainwater

A quantitative microbial risk assessment (QMRA) of opportunistic pathogens Legionella pneumophila (LP) and Mycobacterium avium complex (MAC) was undertaken for various uses of roof-harvested rainwater (RHRW) reported in Queensland, Australia to identify appropriate usages and guide risk management practices. Risks from inhalation of aerosols due to showering, swimming in pools topped up with RHRW, use of a garden hose, car washing, and toilet flushing with RHRW were considered for LP while both ingestion (drinking, produce consumption, and accidental ingestion from various activities) and inhalation risks were considered for MAC. The drinking water route of exposure presented the greatest risks due to cervical lymphadenitis and disseminated infection health endpoints for children and immune-compromised populations, respectively. It is therefore not recommended that these populations consume untreated rainwater. LP risks were up to 6 orders of magnitude higher than MAC risks for the inhalation route of exposure for all scenarios. Both inhalation and ingestion QMRA simulations support that while drinking, showering, and garden hosing with RHRW may present the highest risks, car washing and clothes washing could constitute appropriate uses of RHRW for all populations, and toilet flushing and consumption of lettuce irrigation with RHRW would be appropriate for non- immune-compromised populations.

Dose response models and a quantitative microbial risk assessment framework for the Mycobacterium avium complex that account for recent developments in molecular biology, taxonomy, and epidemiology

Mycobacterium avium complex (MAC) is a group of environmentally-transmitted pathogens of great public health importance. This group is known to be harbored, amplified, and selected for more human-virulent characteristics by amoeba species in aquatic biofilms. However, a quantitative microbial risk assessment (QMRA) has not been performed due to the lack of dose response models resulting from significant heterogeneity within even a single species or subspecies of MAC, as well as the range of human susceptibilities to mycobacterial disease. The primary human-relevant species and subspecies responsible for the majority of the human disease burden and present in drinking water, biofilms, and soil are M. avium subsp. hominissuis, M. intracellulare, and M. chimaera. A critical review of the published literature identified important health endpoints, exposure routes, and susceptible populations for MAC risk assessment. In addition, data sets for quantitative dose-response functions were extracted from published in vivo animal dosing experiments. As a result, seven new exponential dose response models for human-relevant species of MAC with endpoints of lung lesions, death, disseminated infection, liver infection, and lymph node lesions are proposed. Although current physical and biochemical tests used in clinical settings do not differentiate between M. avium and M. intracellulare, differentiating between environmental species and subspecies of the MAC can aid in the assessment of health risks and control of MAC sources. A framework is proposed for incorporating the proposed dose response models into susceptible population- and exposure route-specific QMRA models.

Development of a microbial dose response visualization and modelling application for QMRA modelers and educators

Microbial dose response modelling is vital to a well-characterized microbial risk estimate. Dose response modelling is an inherently multidisciplinary field, which collates knowledge and data from disparate scientific fields. This multidisciplinary nature presents a key challenge to the expansion of microbial dose response modelling into new groups of researchers and modelers. This research employs a dose response optimization R code used in 18 peer-reviewed research studies to develop a multi-functional dose response software. The underlying R code performs an optimization of the two primary dose response models using the MLE method and outputs statistical analyses of the fits and bootstrapped uncertainty information for the models. VizDR (Visual Dose Response) was developed to provide microbial dose response modelling capabilities to a larger audience. VizDR is programmed in JavaScript with underlying Python scripts for intercommunication with Rserve. VizDR allows for dose response model visualization and optimization of a user's own experimental data.