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Article: Gene-centric metagenomics analysis of feline intestinal microbiome using 454 junior pyrosequencing

TitleGene-centric metagenomics analysis of feline intestinal microbiome using 454 junior pyrosequencing
Authors
KeywordsFeline intestinal microbiome
Metagenomics
Pyrosequencing
Zoonotic pathogens
Issue Date2012
PublisherElsevier BV. The Journal's web site is located at http://www.elsevier.com/locate/jmicmeth
Citation
Journal Of Microbiological Methods, 2012, v. 88 n. 3, p. 369-376 How to Cite?
AbstractThe feline gastrointestinal microbiota have direct influence on feline health and also human health as a reservoir for potential zoonotic pathogens and antibiotic resistant bacterial strains. In order to describe the feline gastrointestinal microbial diversity, fecal samples from cats have been characterized using both culture-dependent and culture-independent methods. However, data correlating total microbial composition and their functions are lacking. Present descriptive study evaluated both phylogenetic and metabolic diversity of the feline intestinal microbiota using GS Junior titanium shotgun pyrosequencing. A total of 152,494 pyrosequencing reads (5405 assembled contigs) were generated and classified into both phylogenetic and metabolic profiles of the feline intestinal microbiota. The Bacteroides/Chlorobi group was the most predominant bacterial phylum comprising ~. 68% of total classified diversity, followed by Firmicutes (~. 13%) and Proteobacteria (~. 6%) respectively. Archaea, fungi and viruses made up the minor communities in the overall microbial diversity. Interestingly, this study also identified a range of potential enteric zoonotic pathogens (0.02-1.25%) and genes involved in antimicrobial resistance (0.02-0.7%) in feline fecal materials. Based on clustering among nine gastrointestinal metagenomes from five different monogastric hosts (dog, human, mice, cat and chicken), the cat metagenome clustered closely together with chicken in both phylogenetic and metabolic level (> 80%). Future studies are required to provide deeper understandings on both intrinsic and extrinsic effects such as impact of age, genetics and dietary interventions on the composition of the feline gastrointestinal microbiome. © 2012 Elsevier B.V.
Persistent Identifierhttp://hdl.handle.net/10722/146039
ISSN
2014 Impact Factor: 2.026
2013 SCImago Journal Rankings: 0.955
ISI Accession Number ID
References

 

DC FieldValueLanguage
dc.contributor.authorTun, HMen_HK
dc.contributor.authorBrar, MSen_HK
dc.contributor.authorKhin, Nen_HK
dc.contributor.authorJun, Len_HK
dc.contributor.authorHui, RKHen_HK
dc.contributor.authorDowd, SEen_HK
dc.contributor.authorLeung, FCCen_HK
dc.date.accessioned2012-03-27T09:07:33Z-
dc.date.available2012-03-27T09:07:33Z-
dc.date.issued2012en_HK
dc.identifier.citationJournal Of Microbiological Methods, 2012, v. 88 n. 3, p. 369-376en_HK
dc.identifier.issn0167-7012en_HK
dc.identifier.urihttp://hdl.handle.net/10722/146039-
dc.description.abstractThe feline gastrointestinal microbiota have direct influence on feline health and also human health as a reservoir for potential zoonotic pathogens and antibiotic resistant bacterial strains. In order to describe the feline gastrointestinal microbial diversity, fecal samples from cats have been characterized using both culture-dependent and culture-independent methods. However, data correlating total microbial composition and their functions are lacking. Present descriptive study evaluated both phylogenetic and metabolic diversity of the feline intestinal microbiota using GS Junior titanium shotgun pyrosequencing. A total of 152,494 pyrosequencing reads (5405 assembled contigs) were generated and classified into both phylogenetic and metabolic profiles of the feline intestinal microbiota. The Bacteroides/Chlorobi group was the most predominant bacterial phylum comprising ~. 68% of total classified diversity, followed by Firmicutes (~. 13%) and Proteobacteria (~. 6%) respectively. Archaea, fungi and viruses made up the minor communities in the overall microbial diversity. Interestingly, this study also identified a range of potential enteric zoonotic pathogens (0.02-1.25%) and genes involved in antimicrobial resistance (0.02-0.7%) in feline fecal materials. Based on clustering among nine gastrointestinal metagenomes from five different monogastric hosts (dog, human, mice, cat and chicken), the cat metagenome clustered closely together with chicken in both phylogenetic and metabolic level (> 80%). Future studies are required to provide deeper understandings on both intrinsic and extrinsic effects such as impact of age, genetics and dietary interventions on the composition of the feline gastrointestinal microbiome. © 2012 Elsevier B.V.en_HK
dc.languageengen_US
dc.publisherElsevier BV. The Journal's web site is located at http://www.elsevier.com/locate/jmicmethen_HK
dc.relation.ispartofJournal of Microbiological Methodsen_HK
dc.subjectFeline intestinal microbiomeen_HK
dc.subjectMetagenomicsen_HK
dc.subjectPyrosequencingen_HK
dc.subjectZoonotic pathogensen_HK
dc.titleGene-centric metagenomics analysis of feline intestinal microbiome using 454 junior pyrosequencingen_HK
dc.typeArticleen_HK
dc.identifier.emailHui, RKH: rkhhui@hkucc.hku.hken_HK
dc.identifier.emailLeung, FCC: fcleung@hkucc.hku.hken_HK
dc.identifier.authorityHui, RKH=rp00711en_HK
dc.identifier.authorityLeung, FCC=rp00731en_HK
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1016/j.mimet.2012.01.001en_HK
dc.identifier.pmid22265636en_HK
dc.identifier.scopuseid_2-s2.0-84857238169en_HK
dc.identifier.hkuros199088en_US
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-84857238169&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume88en_HK
dc.identifier.issue3en_HK
dc.identifier.spage369en_HK
dc.identifier.epage376en_HK
dc.identifier.isiWOS:000302666000005-
dc.publisher.placeNetherlandsen_HK
dc.identifier.scopusauthoridTun, HM=38062179300en_HK
dc.identifier.scopusauthoridBrar, MS=44161059200en_HK
dc.identifier.scopusauthoridKhin, N=54911566400en_HK
dc.identifier.scopusauthoridJun, L=54913789200en_HK
dc.identifier.scopusauthoridHui, RKH=7103304764en_HK
dc.identifier.scopusauthoridDowd, SE=25627491800en_HK
dc.identifier.scopusauthoridLeung, FCC=7103078633en_HK
dc.identifier.citeulike10252759-

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