ARTICLE
TITLE

The gut microbiome and mucosal defenses in cats with coronaviruses: a pilot study

SUMMARY

Feline Infectious Peritonitis (FIP) develops from a mutation of enteric feline coronaviruses (FCoVs) and an imbalance of the host immune response. The wide polymorphism of FCoVs is associated with the viral replication rate (Licitra et al. 2013).  Changes in the composition of the gut microbiota may induce quali-quantitative modifications in FCoVs and/or different immune profiles (Weese et al., 2015). Few information is available on feline gut microbiome and the association between microbiota and the predisposition to pathological conditions (Ramadan et al., 2014).The aim of this study is to provide preliminary data about the composition of gut microbiota in healthy cats compared with FCoV infected cats (with and without  FIP), in order to evaluate whether changes of gut microbiota may induce changes in FCoV, in its genetic polymorphism and in the mucosal immunity.Screening analyses have been performed on 22 cats:- Routine hematology and biochemistry on EDTA and serum (included electrophoresis and alpha-1-acid glycoprotein measurement for cats suspected with FIP)- Nested RT-PCR-3’UTR on frozen faeces- Effusion evaluation- FIV/FeLV serologyDue to strict inclusion criteria (cats younger than 2.5 years old, indoor and not assuming antibiotics in the previous two months) and based on the results obtained from the complete set of analysis, only 15 cats, specifically 5 cats for each of the following 3 groups: FIP- affected, healthy negative and positive for FCoV, have been recruited to perform the following analyses: - microbiota analysis through NGS of 16S rRNA gene (V4 region) amplicons followed by bioinformatic analysis -  evaluation of secretory IgA (ELISA kit)- phylogenetic analysis of FCoVs S gene sequencesInnovative results will be provided on the feline gut microbiota composition. These will be correlated with the presence and genetic polymorphisms of FCoV and mucosal defenses to establish significant correlations between the analysed factors.

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