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Fecal microbiota of the synanthropic golden jackal (Canis aureus)

Overview of attention for article published in Animal Microbiome, August 2023
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Title
Fecal microbiota of the synanthropic golden jackal (Canis aureus)
Published in
Animal Microbiome, August 2023
DOI 10.1186/s42523-023-00259-3
Pubmed ID
Authors

Roi Lapid, Yair Motro, Hillary Craddock, Boris Khalfin, Roni King, Gila Kahila Bar-Gal, Jacob Moran-Gilad

Abstract

The golden jackal (Canis aureus), is a medium canid carnivore widespread throughout the Mediterranean region and expanding into Europe. This species thrives near human settlements and is implicated in zoonoses such as rabies. This study explores for the first time, the golden jackal fecal microbiota. We analyzed 111 fecal samples of wild golden jackals using 16S rRNA amplicon sequencing the connection of the microbiome to animal characteristics, burden of pathogens and geographic and climate characteristics. We further compared the fecal microbiota of the golden jackal to the black-backed jackal and domestic dog. We found that the golden jackal fecal microbiota is dominated by the phyla Bacteroidota, Fusobacteriota and Firmicutes. The golden jackal fecal microbiota was associated with different variables, including geographic region, age-class, exposure to rabies oral vaccine, fecal parasites and toxoplasmosis. A remarkable variation in the relative abundance of different taxa was also found associated with different variables, such as age-class. Linear discriminant analysis effect size (LEfSe) analysis found abundance of specific taxons in each region, Megasphaera genus in group 1, Megamonas genus in group 2 and Bacteroides coprocola species in group 3. We also found a different composition between the fecal microbiota of the golden jackal, blacked-backed jackal and the domestic dog. Furthermore, LEfSe analysis found abundance of Fusobacterium and Bacteroides genera in the golden jackal, Clostridia class in blacked-backed jackal and Megamonas genus in domestic dog. The golden jackal fecal microbiota is influenced by multiple factors including host traits and pathogen burden. The characterization of the microbiota of this thriving species may aid in mapping its spread and proximity to human settlements. Moreover, understanding the jackal microbiota could inform the study of potential animal and human health risks and inform control measures.

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The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 14 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 14 100%

Demographic breakdown

Readers by professional status Count As %
Unspecified 2 14%
Researcher 2 14%
Student > Bachelor 1 7%
Student > Ph. D. Student 1 7%
Unknown 8 57%
Readers by discipline Count As %
Agricultural and Biological Sciences 2 14%
Unspecified 2 14%
Veterinary Science and Veterinary Medicine 1 7%
Environmental Science 1 7%
Engineering 1 7%
Other 0 0%
Unknown 7 50%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 05 August 2023.
All research outputs
#16,191,224
of 25,589,756 outputs
Outputs from Animal Microbiome
#233
of 299 outputs
Outputs of similar age
#175,999
of 359,833 outputs
Outputs of similar age from Animal Microbiome
#9
of 12 outputs
Altmetric has tracked 25,589,756 research outputs across all sources so far. This one is in the 34th percentile – i.e., 34% of other outputs scored the same or lower than it.
So far Altmetric has tracked 299 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 13.2. This one is in the 17th percentile – i.e., 17% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 359,833 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 47th percentile – i.e., 47% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 12 others from the same source and published within six weeks on either side of this one. This one is in the 16th percentile – i.e., 16% of its contemporaries scored the same or lower than it.