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Dowd, S.

Publications and source records attributed to Dowd, S..

2 recordsLinked to original sources

Evaluation of the bacterial and fungal microbiome on the skin of Anaxyrus boreas, Rhinella marina, and Xenopus laevis and implications related to Batrachochytrium dendrobatidis susceptibility

The skin and its microbiome are the first lines of defense against environmental stressors and pathogens. The symbiotic relationships between the host and the microbiome and within the microbiome are critical to host health. In frogs, this research area is lacking especially in the context of their skin infection with Batrachochytrium dendrobatidis. B. dendrobatidis is a major fungal skin pathogen to amphibians that has caused the extinction of hundreds of amphibian species populations. While some frog species are known susceptible to B. dendrobatidis infections, and others are resistant, we hypothesized that the skin microbiome of frogs plays a role in the prevention of B. dendrobatidis infections that is yet unknown. Therefore, in this work we have examined the bacterial and fungal skin microbiome of one species that is sensitive to B. dendrobatidis infections, Anaxyrus boreas (formerly: Bufo boreas), and the resistant species, Xenopus laevis and Rhinella marina (formerly: Bufo marinus). This was accomplished using tag-encoded FLX amplicon pyrosequencing (bTEFAP) of the 16S rRNA and ITS DNA regions. Our results showed that the bacterial and fungal skin microbiome of A. boreas and R. marina were more similar than to that of X. laevis. We found distinct patterns between the skin microbiome of B. dendrobatidis sensitive and resistant frog species. For the bacterial microbiome, the most abundant bacterial genus observed in all frog samples was Microbacterium. The resistant species had higher abundance in the genera Pseudomonas, Sphingobium, Pedobacter, Variovorax, Morganella, Sphingomonas, Giesbergeria, and Agromyces. In contrast, they had lower abundance of Elizabethkingia (formerly: Flavobacterium), Enterobacter, Ochrobactrum, Arthobacter, Stenotrophomonas, Shinella, Klebsiella, Aeromonas, Comomonas, Chitinophaga, and Rhodococcus. Regarding the fungal microbiome, the resistant species showed higher abundance in the genera Aspergillus, Cladosporium, Elaphomyces, Monascus, Tritirachium, Ceratostomella, and Claviceps, while Asterotremella, Trichosporon, and Malasezzia genera were less represented in resistant species. We have also observed that in the resistant species, the skin microbiome had higher diversity in the fungal microbiota, but not in the bacterial microbiota. We speculate that those observed differences have implications in B. dendrobatidis susceptibility that are yet to be determined, possibly through competition for nutrients or the production of specific anti-fungal molecules. GRAPHICAL ABSTRACT O_FIG_DISPLAY_L [Figure 1] M_FIG_DISPLAY C_FIG_DISPLAY

microbiology↗

Temporal Effects on Radiation Responses in Nonhuman Primates: Identification of Biofluid Small Molecule Signatures by Gas Chromatography - Mass Spectrometry Metabolomics

Whole body exposure to ionizing radiation (IR) (> 0.7 Gy) damages tissues leading to a range of physical symptoms contributing to acute radiation syndrome (ARS). Radiation biodosimetry aims to determine characteristic early biomarkers indicative of radiation exposure (generally at doses > 2 Gy) and is a necessity for effective triage in the event of an unanticipated radiological incident and emergency preparedness. Radiation metabolomics can address this aim by assessing metabolic perturbations following various emergency scenarios (e.g., elapsed time to medical care, absorbed dose, combined injury). Gas chromatography - mass spectrometry (GC-MS) is a standardized platform ideal for chromatographic separation, identification, and quantification of metabolites to discriminate molecular signatures that can be utilized in assessing radiation injury. We performed GC time-of-flight (TOF) MS for global profiling of nonhuman primate (NHP) urine and serum samples up to 60 d after a single 4 Gy {gamma}-ray total body exposure. Multivariate statistical analysis showed a higher separation of groups from urine signatures vs. serum signatures. We identified biofluid markers involved in amino acid, lipid, purine, and serotonin metabolism, some of which may indicate host microbiome dysbiosis. Sex differences were observed amino acid fold changes in serum samples. Additionally, we explored mitochondrial dysfunction by analysis of tricarboxylic acid (TCA) intermediates with a GC tandem quadrupole (TQ) MS platform in samples collected in a time course during the first week (1, 3, 5, and 7 d) after exposure. By adding this temporal component to our previous work exploring dose effects at a single time point of 7 d, we observed the highest fold changes occurring at 3 d, returning closer to basal levels by 7 d. These results emphasize the utility of both MS-based metabolomics for biodosimetry and complementary analytical platforms for increased metabolome coverage.

biochemistry↗