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Using multi-response models to investigate pathogen coinfections across scales: insights from emerging diseases of amphibians.

ABSTRACT: Associations among parasites affect many aspects of host-parasite dynamics, but a lack of analytical tools has limited investigations of parasite correlations in observational data that are often nested across spatial and biological scales.Here we illustrate how hierarchical, multiresponse modeling can characterize parasite associations by allowing for hierarchical structuring, offering estimates of uncertainty, and incorporating correlational model structures. After introducing the general approach, we apply this framework to investigate coinfections among four amphibian parasites (the trematodes Ribeiroia ondatrae and Echinostoma spp., the chytrid fungus Batrachochytrium dendrobatidis, and ranaviruses) and among >2000 individual hosts, 90 study sites, and five amphibian host species.Ninety-two percent of sites and 80% of hosts supported two or more pathogen species. Our results revealed strong correlations between parasite pairs that varied by scale (from among hosts to among sites) and classification (microparasite versus macroparasite), but were broadly consistent across taxonomically diverse host species. At the host-scale, infection by the trematode R. ondatrae correlated positively with the microparasites, B. dendrobatidis and ranavirus, which were themselves positively associated. However, infection by a second trematode (Echinostoma spp.) correlated negatively with B. dendrobatidis and ranavirus, both at the host- and site-level scales, highlighting the importance of differential relationships between micro- and macroparasites.Given the extensive number of coinfecting symbiont combinations inherent to natural systems, particularly across multiple host species, multiresponse modeling of cross-sectional field data offers a valuable tool to identify a tractable number of hypothesized interactions for experimental testing while accounting for uncertainty and potential sources of co-exposure. For amphibians specifically, the high frequency of co-occurrence and coinfection among these pathogens - each of which is known to impair host fitness or survival - highlights the urgency of understanding parasite associations for conservation and disease management.

SUBMITTER: Stutz WE

PROVIDER: S-EPMC5978769 | biostudies-literature | 2018 Apr

REPOSITORIES: biostudies-literature

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Using multi-response models to investigate pathogen coinfections across scales: insights from emerging diseases of amphibians.

Stutz William E WE Blaustein Andrew R AR Briggs Cheryl J CJ Hoverman Jason T JT Rohr Jason R JR Johnson Pieter T J PTJ

Methods in ecology and evolution 20171113 4

Associations among parasites affect many aspects of host-parasite dynamics, but a lack of analytical tools has limited investigations of parasite correlations in observational data that are often nested across spatial and biological scales.Here we illustrate how hierarchical, multiresponse modeling can characterize parasite associations by allowing for hierarchical structuring, offering estimates of uncertainty, and incorporating correlational model structures. After introducing the general appr ...[more]

PMID: 29861885

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Project description:Candida auris is a recently described pathogenic fungus that is causing invasive outbreaks on all continents. The fungus is of high concern given the numbers of multidrug-resistant strains that have been isolated in distinct sites across the globe. The fact that its diagnosis is still problematic suggests that the spreading of the pathogen remains underestimated. Notably, the molecular mechanisms of virulence and antifungal resistance employed by this new species are largely unknown. In the present work, we compared two clinical isolates of C. auris with distinct drug susceptibility profiles and a Candida albicans reference strain using a multi-omics approach. Our results show that, despite the distinct drug resistance profile, both C. auris isolates appear to be very similar, albeit with a few notable differences. However, compared to C. albicans both C. auris isolates have major differences regarding their carbon utilization and downstream lipid and protein content, suggesting a multifactorial mechanism of drug resistance. The molecular profile displayed by C. auris helps to explain the antifungal resistance and virulence phenotypes of this new emerging pathogen.IMPORTANCECandida auris was first described in Japan in 2009 and has now been the cause of significant outbreaks across the globe. The high number of isolates that are resistant to one or more antifungals, as well as the high mortality rates from patients with bloodstream infections, has attracted the attention of the medical mycology, infectious disease, and public health communities to this pathogenic fungus. In the current work, we performed a broad multi-omics approach on two clinical isolates isolated in New York, the most affected area in the United States and found that the omic profile of C. auris differs significantly from C. albicans In addition to our insights into C. auris carbon utilization and lipid and protein content, we believe that the availability of these data will enhance our ability to combat this rapidly emerging pathogenic yeast.

Dataset Information

Using multi-response models to investigate pathogen coinfections across scales: insights from emerging diseases of amphibians.

Publications

Using multi-response models to investigate pathogen coinfections across scales: insights from emerging diseases of amphibians.

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