bioRxiv ScienceSearch

bioRxiv · 10.1101/311936

Basidiobolus haptosporus-like fungus as a causal agent of gastrointestinal basidiobolomycosis and its link to the common house gecko (Hemidactylus frenatus) as a potential risk factor

Abstract

Basidiobolus spp. are a significant causal agent of infections in man and animals including gastrointestinal basidiobolomycosis (GIB). Little information is available on how these infections are acquired or transmitted, apart from the postulation that environmental sources are implicated. This study aimed to identify Basidiobolus spp. from GIB patients and from the house gecko as a possible source of infection in Aseer, Saudi Arabia. Basidiobolus spp. were isolated from patient specimens (colonic mass biopsy) and from house gecko (gut contents) from Muhayil Aseer areas, in southern Saudi Arabia, using Sabouraud dextrose agar (SDA) which was incubated aerobically for up to three weeks at 30{degrees}C. Isolated fungi were initially identified using classical mycological tools and confirmed by sequence analysis of the large subunit ribosomal RNA gene. Cultured specimens from humans and geckos revealed phenotypically similar zygomycete-like fungi which conform to those of Basidiobolus species. The strains formed a monophyletic clade in the 28S ribosomal RNA gene phylogenetic tree. They shared 99.97% similarity with B. haptosporus and 99.97% with B. haptosporus var. minor but have a relatively remote similarity to B. ranarum (99.925%). One isolates from a gecko (L3) fall within the sub-clade encompassing B. haptosporus strain NRRL28635. The study strongly suggests a new and a serious causal agent of GIB related to Basidiobolus haptosporus. The isolation of identical Basidiobolus haptosporus-like strains from humans and lizards from one area is an important step towards identifying risk factors for GIB. Research is underway to screen more environmental niches and fully describe the Basidiobolus strains.

Source connections

Explore related subjects

Keep this discovery

BibTeXRIS

Al Bshabshe, A., Joseph, M. R. P., AL-HAKAMI, A. M., Al Azraqi, T., Al Humayed, S., Hamid, M. E.. 2018-05-02. Basidiobolus haptosporus-like fungus as a causal agent of gastrointestinal basidiobolomycosis and its link to the common house gecko (Hemidactylus frenatus) as a potential risk factor. https://doi.org/10.1101/311936

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

Translating surveillance data into incidence estimates

Monitoring a population for a disease requires the hosts to be sampled and tested for the pathogen. This results in sampling series from which to estimate the disease incidence, i.e. the proportion of hosts infected. Existing estimation methods assume that disease incidence is not changing between monitoring rounds, resulting in underestimation of the disease incidence. In this paper we develop an incidence estimation model accounting for epidemic growth with monitoring rounds sampling varying incidence. We also show how to accommodate the asymptomatic period characteristic to most diseases. For practical use, we produce an approximation of the model, which is subsequently shown accurate for relevant epidemic and sampling parameters. Both the approximation and the full model are applied to stochastic spatial simulations of epidemics. The results prove their consistency for a very wide range of situations.

epidemiology

The Swiss Primary Ciliary Dyskinesia registry: objectives, methods and first results

Primary Ciliary Dyskinesia (PCD) is a rare hereditary, multi-organ disease caused by defects in ciliary structure and function. It results in a wide range of clinical manifestations, most commonly in the upper and lower airways. Central data collection in national and international registries is essential to studying the epidemiology of rare diseases and filling in gaps in knowledge of diseases such as PCD. For this reason, the Swiss Primary Ciliary Dyskinesia Registry (CH-PCD) was founded in 2013 as a collaborative project between epidemiologists and adult and paediatric pulmonologists.\n\nThe registry records patients of any age, suffering from PCD, who are treated and resident in Switzerland. It collects information from patients identified through physicians, diagnostic facilities, and patient organisations. The registry dataset contains data on diagnostic evaluations, lung function, microbiology and imaging, symptoms, treatments, and hospitalizations.\n\nBy May 2018, CH-PCD has contacted 566 physicians of different specialties and identified 134 patients with PCD. At present this number represents an overall 1 in 63,000 prevalence of people diagnosed with PCD in Switzerland. Prevalence differs by age and region; it is highest in children and adults younger than 30 years, and in Espace Mittelland. The median age of patients in the registry is 25 years (range 5-73), and 49 patients have a definite PCD diagnosis based on recent international guidelines. Data from CH-PCD are contributed to international collaborative studies and the registry facilitates patient identification for nested studies.\n\nCH-PCD has proven to be a valuable research tool that already has highlighted weaknesses in PCD clinical practice in Switzerland. Development of centralised diagnostic and management centres and adherence to international guidelines are needed to improve diagnosis and management--particularly for adult PCD patients.

epidemiology

Perfect Counterfactuals for Epidemic Simulations

Simulation studies are often used to predict the expected impact of control measures in infectious disease outbreaks. Typically, two independent sets of simulations are conducted, one with the intervetnion, and one without, and epidemic sizes (or some related metric) are compared to estimate the effect of the intervention. Since it is possible that controlled epidemics are larger than uncontrolled ones if there is substantial stochastic variation between epidemics, uncertainty intervals from this approach can include a negative effect even for an effective intervention. To more precisely estimate the number of cases an intervention will prevent within a single epidemic, here we develop a single world approach to matching simulations of controlled epidemics to their exact uncontrolled counterfac-tual. Our method borrows concepts from percolation approaches prune out possible epidemic histories and create potential epidemic graph that can be realized to create perfectly matched controlled and uncontrolled epidemics. We present an implementation of this method for a common class of compartmental models, and its application in a simple SIR model. Results illustrate how, at the cost of some computation time, this method substantially narrows confidence intervals and avoids non-sensical inferences.

epidemiology