Differences in caecal microbiota composition and Salmonella carriage between experimentally infected inbred lines of chickens

Abstract

Background Salmonella Enteritidis (SE) is one of the major causes of human foodborne intoxication resulting from consumption of contaminated poultry products. Genetic selection of animals that are more resistant to Salmonella carriage and modulation of the gut microbiota are two promising ways to decrease individual Salmonella carriage. The aims of this study were to identify the main genetic and microbial factors that control the level of Salmonella carriage in chickens (Gallus gallus) under controlled experimental conditions. Two-hundred and forty animals from the White Leghorn inbred lines N and 61 were infected by SE at 7 days of age. After infection, animals were kept in isolators to reduce recontamination of birds by Salmonella. Caecal contents were sampled at 12 days post-infection and used for DNA extraction. Microbiota DNA was used to measure individual counts of SE by digital PCR and to determine the bacterial taxonomic composition, using a 16S rRNA gene high-throughput sequencing approach. Results Our results confirmed that the N line is more resistant to Salmonella carriage than the 61 line, and that intra-line variability is higher for the 61 line. Furthermore, the 16S analysis showed strong significant differences in microbiota taxonomic composition between the two lines. Among the 617 operational taxonomic units (OTU) observed, more than 390 were differentially abundant between the two lines. Furthermore, within the 61 line, we found a difference in the microbiota taxonomic composition between the high and low Salmonella carriers, with 39 differentially abundant OTU. Using metagenome functional prediction based on 16S data, several metabolic pathways that are potentially associated to microbiota taxonomic differences (e.g. short chain fatty acids pathways) were identified between high and low carriers. Conclusions Overall, our findings demonstrate that the caecal microbiota composition differs between genetic lines of chickens. This could be one of the reasons why the investigated lines differed in Salmonella carriage levels under experimental infection conditions.

Comparative analysis of the caecal tonsil transcriptome in two hen lines experimentally infected withSalmonellaEnteritidis

“…The latter genes code for the major histocompatibility complex I or II (MHCIBF2, MHCIYF5, MHCIIBLB1, MHCIIBLB2), antimicrobial peptides such as granzyme A and K, or the avian betadefensines 10, 13 and 14. In the same way, the genes TLR 1,2,4,7,15 [31][32][33][34], NOS2, Gal 13, PSAP and IGL, which have already been associated with SE resistance in a genetic study in chicken [13], were more expressed in the resistant line N. Interestingly, we showed previously that the caecal microbiota composition of these animals was highly different between individuals from lines N and 6 1 [30]. Do some of these DEGs in caecal tonsils indirectly impact Salmonella carriage through the modulation of the caecal microbiota composition?…”

“…Results of the DEG and BP GO term enrichment analyses. Results of the 16S analysis from the study [30].…”

“…This hypothesis was not contradicted by our latest study, in which we identified significant differences in microbiota composition between line N and line 6 1 , and between low and high Salmonella carriers in line 6 1 . We were able to identify some bacteria associated with Salmonella resistance, such as the Christensenellaceae family [30]. In the current study, we performed an integrative analysis using information about caecal gene expression and caecal microbiota composition in two distinct genetic lines: the inbred chicken lines N and 6 1 , respectively resistant and susceptible to SE infection.…”

“…(i) identify differentially expressed genes between genetic lines in the caecal tonsils after SE infection, in order to identify potential pathways involved in the genetic resistance to SE; (ii) identify genes and pathways associated with SE resistance within line (low vs high carriers); (iii) link the results to those we obtained on the caecal microbiota [30] to identify potential interactions between the host and its microbiota that could explain differences in resistance to SE infection.…”

Tree Species Diversity and Forest Edge Density Jointly Shape the Gut Microbiota Composition in Juvenile Great Tits (Parus major)

“…Tyzzerella 3 showed a fold change (Log 2 ) of -30, indicating that this genus is strongly associated with a reduction in fledging success. Tyzzerella 3 has previously been linked to diabetes ( Yue et al, 2019 ; Ma et al, 2020 ), cardiovascular diseases ( Kelly et al, 2016 ) and even reduced disease resistance in poultry ( Cazals et al, 2022 ). The abundance of Brachybacterium , Brevibacterium , Serratia , and Sphingomonas , was also negatively linked to fledging success.…”