Veterinary Microbiology · 2020 · 86 citations · 26 references
Life SciencesMicrobiologyVeterinary MicrobiologyBacteriologyMicrobial EcologyMicrobiome ResearchAnimal Microbial EcologyMicrobial Community ProfilingMicrobiological AnalysisMicrobiome Data AnalysisMicrobiome DiversitySkin MicrobiomeClinical Next-generation SequencingMicrobial Diversity LossSkin Microbial EcologySkin Microbiome CompositionSkin Microbiome DiversitySkin Microbiome In DiseaseSkin Microbiome SamplingSkin Site-specific Microbiomes
This study analyzed the complex bacterial and fungal microbiota of healthy and clinically affected canine ear and skin samples. A total of 589 canine samples were included: 257 ear swab samples (128 healthy vs. 129 clinically affected) and 332 skin swab samples (172 healthy vs. 160 clinically affected) were analyzed using next-generation sequencing (NGS) to determine both relative and absolute abundances of bacteria and fungi present in the samples. This study highlighted the canine microbiota of clinically affected cases was characterized by an overall loss of microbial diversity, high microbial biomass, with overgrowth of certain members of the microbiota. The observed phenotype of these samples was best described by the combination of both relative and absolute microbial abundances. Compared to healthy samples, 78.3% of the clinically affected ear samples had microbial overgrowth; 69.8% bacterial overgrowth, 16.3% fungal overgrowth, and 7.0% had both bacterial and fungal overgrowth. The most important microbial taxa enriched in clinically affected ears were Malassezia pachydermatis, Staphylococcus pseudintermedius, Staphylococcus schleiferi, and a few anaerobic bacteria such as Finegoldia magna, Peptostreptococcus canis, and Porphyromonas cangingivalis. The anaerobic microbes identified here were previously not commonly recognized as pathogens in canine ear infections. Similar observations were found for skin samples, but yeasts and anaerobes were less abundant when compared to clinically affected cases. Results highlighted herein, signify the potential of NGS-based methods for the accurate quantification and identification of bacterial and fungal populations in diagnosing canine skin and ear infections, and highlight the limitations of traditional culture-based testing.
26
DADA2: High-resolution sample inference from Illumina amplicon data
Benjamin J. Callahan, Paul J. McMurdie, Michael Rosen et al. · Nature Methods · 2016 · 36.3K citations
Structure, function and diversity of the healthy human microbiome
Curtis Huttenhower, J. Fah Sathirapongsasuti, Nicola Segata et al. · Nature · 2012 · 11.9K citations · Full text
Life Sciences, Biology, Microbiology +17
Stefanie Handl, Scot E. Dowd, José F. García-Mazcorro et al. · FEMS Microbiology Ecology · 2011 · 440 citations · Full text