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Oliver Deusch

Researcher at Waltham Centre for Pet Nutrition

Publications -  30
Citations -  1750

Oliver Deusch is an academic researcher from Waltham Centre for Pet Nutrition. The author has contributed to research in topics: Microbiome & Genome. The author has an hindex of 19, co-authored 28 publications receiving 1514 citations. Previous affiliations of Oliver Deusch include Massey University & University of Düsseldorf.

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A Pyrosequencing Investigation of Differences in the Feline Subgingival Microbiota in Health, Gingivitis and Mild Periodontitis.

TL;DR: The species identified were very similar to those observed in canine plaque in the corresponding health and disease states, suggesting that interventions targeted at human pathogenic species will not be effective for use in cats but there is more potential for commonalities in interventions for cats and dogs.
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The canine oral microbiome: variation in bacterial populations across different niches

TL;DR: The ability to distinguish the niches by their microbiota signature offers the potential for microbial biomarkers to be identified in each unique niche for diagnostic use.
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Evolutionary Dynamics of Introns in Plastid-Derived Genes in Plants: Saturation Nearly Reached but Slow Intron Gain Continues

TL;DR: After the transfer to the nuclear genome, the plastid-derived genes have undergone a massive intron invasion that, by the time of the divergence of dicots and monocots, yielded intron densities only slightly lower than those in ancestral genes.
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Comparative Genomics of the Genus Porphyromonas Identifies Adaptations for Heme Synthesis within the Prevalent Canine Oral Species Porphyromonas cangingivalis.

TL;DR: Porphyromonas cangingivalis is the most prevalent canine oral bacterial species in both plaque from healthy gingiva and plaque from dogs with early periodontitis as discussed by the authors.
Posted ContentDOI

Combining whole genome shotgun sequencing and rDNA amplicon analyses to improve detection of microbe-microbe interaction networks in plant leaves

TL;DR: The metagenome data is used, which captures the ratio of bacterial to plant DNA in leaves of wild plants, to scale the 16S rDNA amplicon data such that they reflect absolute bacterial abundance, and it is shown that this cost-effective hybrid strategy overcomes compositionality problems in ampliconData and leads to fundamentally different conclusions about microbiome community assembly.