Using a model of Salmonella infection in isolators limiting animal-animal recontaminations and animal reinfection and thus homogenisation of individual Salmonella carriage , we confirm the existence of variability linked to genetics and microbiota composition. We evidenced gut microbiota differences associated to both the genetic line (N vs 61) and individual Salmonella carriage status (high vs. low ISC carriers). On average, line N had less Salmonella abundance than line 61, suggesting a genetic control of the carriage. In line 61, the larger observed variability allowed us to identify contrasted groups of low and high carriers. Finally, through our caecal microbiota taxonomic analysis, we identified taxa and metabolism pathways that may be associated with Salmonella carriage.
In both experiments conducted, line N was more resistant and microbiota taxonomic composition was clearly different between both lines. Nevertheless, ISC was higher for line N in the second experiment and the DA OTUs between lines were not strictly the same between experiments. These differences in microbiota composition might be due to the impact of the immediate environment on individual microbiota composition. Although conditions were controlled to be similar between both experiments, even slight changes might lead to differences in the primo-colonisation of the intestinal tract [34, 35]. The hatching environment might have differed between both batches and/or the two batches of eggs might have carried different microbes. Those potential differences might have affected the bacterial gut primo-colonisation of the newborn chicks. As a result, a difference in microbiota composition before infection could affect the microbiota composition after infection. In the following section, since ISC and microbiota composition differed slightly between experiments, we will focus only on results validated in both experiments.
Impact of the chicken genetic line on the Individual Salmonella Enteritidis carriage
Previous studies showed the impact of host genetics on Salmonella carriage, using different infection models. Significant differences in Salmonella Enteritidis carriage in commercial or local chicken breed have already been identified [36–38]. Our results with lines N and 61 confirm previous results obtained without using isolators with the same lines, with on-floor grouped rearing [2, 39], confirming that line N is a lower Salmonella Enteritidis carrier than line 61. Previous studies validated candidate genes associated with resistance to Salmonella Enteritidis carriage, such as SLC11A1 and TLR4 [40–42] and identified QTLs on several chromosomes i [2–4]. Nevertheless, due to the highly polygenic control of carrier-state in these lines, with many loci with weak effects involved , identification of causal genes at the QTLs has not been yet possible. The infection of birds in isolators, which would allow for much larger individual variability , might be a way to improve future QTL detection studies and identification of causal genes. Interestingly, we observed a larger variability in ISC in line 61, confirmed in two independent experiments. This larger variability of ISC generates new hypotheses: could this ISC variability be caused by intra-line genetic variations, or by a variability of the microbiota composition?
Impact of the genetic line on the microbiota composition
In both experiments conducted, we showed a clear difference of the caecal microbiota composition between lines N and 61 at 12 days post-infection, which suggests the existence of a host genetic control of this composition. For each experiment, birds from lines N and 61 were hatched in the same environment at the same time, and raised together until the experimental infection, so that the initial microbial environment was similar for all birds tested before infection. Differences in caecal microbiota composition between lines can therefore not be attributed to differential exposures to environmental microbes before infection. Furthermore, for experiment 1, we observed no significant difference of microbiota composition between the two isolators used for the same line (P>0.1, Additional file 5, Table 4). Thus, we cannot associate differences in microbiota composition between lines with isolators in experiment 1. In experiment 2, we observed a significant difference of microbiota composition between the two isolators used for the same line (P<0.01, Additional file 5, Table 4). It can be argued that isolators might be populated by different microbial populations, which could in turn influence the caecal microbiota composition after infection. Howerver, isolators were sterilized between each experimentation. In addition, we inverted the isolators containing each line in the second experiment, and still observed a similar difference between lines in terms of caecal microbiota composition. Moreover, since the utilisation of isolators decreases the oro-faecal recontamination of commensal microbiota as well as pathogenic bacteria, the caecal microbiota composition of each chicken can mature isolated from the impact of the other birds.
Since we analysed caecal microbiota composition after infection, we cannot exclude that the infection by Salmonella affected this microbiota composition. Does the higher susceptibility of line 61, with a higher number of Salmonella in the caeca, causes a shift in microbiota composition? Comparing seven different time points after infection with SE, Liu et al. showed 18 genera significantly DA between treated and control group . Nevertheless, it was shown in other studies that infection with SE does not have a huge impact on gut microbiota composition. Videnska et al. showed that the infection significantly impacts only the Lactobacillaceae, while Zeng et al. identified only a lower abundance of Ruminococcaceae at 4 dpi in an infected group [21, 45]. Although we lack samples collected from a control group before infection to verify this hypothesis, we hypothesize that SE infection presumably had a weak impact on microbiota composition.
A study on Campylobacter resistance between lines N and 61 was conducted by Chintoan-Uta and colleagues . Their objectives were to transfer microbiota from the resistant line to the susceptible line and to study the Campylobacter carriage. First, they showed no significant difference of microbiota composition between donor birds from the N and 61 lines at 21 days, despite a clustering on an NMDS representation. The authors hypothesized that the low number of samples, only five per line, could likely explain this non-significant result. Secondly, they showed that at 21 days in the recipient line after transplantation, the genetic line had a significant impact on microbiota composition, while the transplanted microbiota did not. This supports our hypothesis that genetics have a strong impact on the composition of the microbiota, at least 3 weeks after hatching in lines N and 61. Nevertheless, Chintoan-Uta et al. did not show that transplantation of microbiota composition from the resistant line to the susceptible induces a decrease of Campylobacter infection, and they concluded that the microbiota does not have an impact on the mechanism of Campylobacter resistance, even if heritable genetic differences exist. Nevertheless, their conclusion could be the result of a lack of power since few samples were tested.
In chicken as well as in other livestock species and in human, the genetic control of the intestinal microbiota composition is well documented. In human studies, the high sensitivity of the gut microbiota to a myriad of parameters, especially differences in diet, makes statistical analyses complex due to many confounding factors. In spite of these difficulties, some bacteria known to be associated with immunity seem to be heritable and candidate genes have been identified . For example, the family Christensenellaceae, which are the most heritable bacteria in the study of Goodrich et al. in human, show a heritability of 0.39, while other studies reported an heritability of 0.62 for this family [48, 49]. Candidate genes in human that might be associated with Christensenellaceae abundance, such as ILR23 or FUT2,were also identified [50, 51]. In chicken, studies identified differences in microbiota composition between genetic lines, for instance in two chicken lines that differ in their susceptibility to bacterial infections  or in two divergent genetic lines for body weight . Another study compared four commercial lines and an indigenous Indian breed, which revealed a significant impact of the genetic background on microbiota composition and led to the identification of 42 specific biomarkers . At least two studies identified moderate heritabilities of bacteria families and several QTLs involved in the control of these bacterial abundances [22, 55].
Finally, we conclude that this clear difference of microbiota composition between lines after Salmonella infection is probably caused by host genetic variations between lines N and 61. We also showed a difference in ISC between lines. Therefore, in contrast to Chintoan-Uta's conclusion for Campylobacter, we formulate the hypothesis that genetic variations between lines N and 61 might indirectly influence Salmonella carriage through an influence on the microbiota composition. This does not exclude other potential pathways, in particular those involving host immunity. For example, the candidate genes SIVA1, implicated in a cell death mechanism in extracellular trap production, or SLC11A1, associated with heterophil extracellular trap production and phagocytosis of SE, may be implicated in leukocyte function and in the inhibition of intracellular bacterial growth by depleting metal ions .
Relation of caecal microbiota diversity and composition with individual Salmonella Enteritidis carriage
The colonisation and the adhesion of commensal bacteria covering the mucosal epithelium constitute a protective biofilm by their competitive exclusion (CE) function. Studies affirm that CE is currently the best approach to decrease Salmonella colonization in chicken in commercial production .
In our study, all animals were experimentally infected and the identification of signature bacteria was performed by comparing chickens with differences of individual Salmonella carriage between lines or intra-lines. Our hypothesis is that the abundance of commensal, potentially competitive bacteria is higher in the microbiota of resistant chickens, thus preventing the colonisation of Salmonella in the intestinal tract. The genetic background could in part control this abundance of competitive bacteria. We first compared the microbiota of line 61 (susceptible) to line N (resistant), and we subsequently compared the high and low carriers in line 61. Thus, differences of caecal microbiota diversity or composition between lines and between high and low carriers could be indicative of potential signature bacteria taxa of high and low ISC.
The weak correlation of microbiota diversity with ISC
The average value of microbiota beta diversity within a group measures the similarity of microbiota composition of each chicken of this group compared to all the chickens of the group. The higher the value of beta diversity, the more individual microbiota in the group differ from each other. We compared here two groups: line N vs. line 61.
We showed that the microbiota beta diversity is not significantly different between lines (Whittaker index = 0.2 for the two lines). Thus, the difference of ISC between lines and the larger ISC variability in line 61 cannot be related to a difference in beta diversity of the caecal microbiota. Similarly, the average alpha diversity was not significantly different between lines and cannot be related to the observed differences of ISC. Thus, at 12 dpi, it seems that differences in genetic backgrounds do not have an impact on the microbiota diversity. Furthermore, the comparison of high and low carriers in line 61 showed that alpha diversity cannot be associated with differences in ISC. Comparing chickens infected and non-infected with SE, Liu and colleagues (2018) showed a slight decrease of richness at 14 dpi in the infected group, but no significant difference for the Shannon index . At 10 dpi, another study similarly showed no significant difference between infected and non-infected groups . These observations corroborate ours and lead us to conclude that the infection with SE or the level of SE carriage do not affect the OTU diversity in the caecal microbiota.
However, we identified a significant difference in beta diversity between high and low carriers within line 61: individual microbiota of high carriers are more similar compared to the individual microbiota of low carriers, which harbour more differences. Does the higher level of Salmonella drive the microbiota to a more similar composition in high-carriers? Or are these animals more susceptible to Salmonella because some shared characteristics of their microbiota lead to a less efficient competitive exclusion? These questions remain open; as we also cannot exclude that genetic variations within line 61 could explain these differences in caecal microbiota beta diversity.
Correlation between individual microbiota composition and Individual Salmonella Enteritidis carriage and functional analysis
DA OTUs and pathways identified between lines could potentially be associated with differences in ISC. Likewise, DA OTUs and pathways identified between high and low carriers in line 61 could be associated with ISC.
Short-Chain Fatty Acids (SCFAs) metabolic pathway
We showed that the SCFAs metabolic pathway would be more abundant both in the resistant line N and in low carriers in the susceptible line 61. Thus, the production of SCFAs could be associated with low Salmonella carriage. This result is coherent with many studies showing a relationship between Salmonella colonisation and SCFA. Many studies showed that the production of SCFAs, such as butyrate, by the intestinal microbiota has beneficial effects for the host. Studies have conferred to SCFAs several functions: the regulation of immune cell function , the activation of macrophages  or the maintenance of the oxygen balance preventing dysbiosis . In mice, Zhou and collaborators showed in 2017 that butyric acid could increase the host capacity to resist to pathogen infection by restoring the gastrointestinal barrier , and in 2019, they showed that butyric acid can decrease the inflammation in chicken . Besides, we know that an increase of inflammation makes electron acceptors available to Salmonella for oxygen respiration, which in turn increases the ability of Salmonella for competition and colonisation . More specifically, it was shown that the rise of SCFAs on in vitro culture of avian intestinal cells decreases the pathogenicity of Salmonella, blocking its entry into the organism . Thus, line N and low carriers in line 61 could carry a beneficial microbiota for Salmonella resistance.
Catechol degradation pathway
The catechol degradation pathway was also more abundant in both the resistant line N and in the low Salmonella carriers of the susceptible line 61. Several studies report the association of catechol with Salmonella virulence. Salmonella have the ability to produce auto-inducers 3 (AI-3), which have a similar chemical structure as the catecholamine from the catechol family [64, 65]. In chicken and in pigs, studies have already showed that a treatment with catecholamine, e.g. Norepinephrine, increases Salmonella colonization in the host and Salmonella spread in the environment [66, 67]. Two mechanisms have been described to explain this phenomenon: the iron availability and the quorum sensing signal. A study in mice on Salmonella Typhimurium showed that molecules from the catechol family increase the iron availability for Salmonella by chelating iron III in their aromatic function and increasing iron accumulation in macrophages, which in turn facilitate Salmonella colonisation . Besides, catechol plays a role of quorum sensing signal for the production of biofilm, thus increasing the virulence of Salmonella during host infection [64, 69]. Outside the host, this biofilm increases the Salmonella capacity to resist on eggs or meat, rising salmonellosis risks in human . Thus, the microbiota capacity of catechol degradation in line N and low carriers in line 61 could be beneficial for Salmonella resistance.
We showed that the Christensenellaceae family is more abundant in low Salmonella carriers (Figure 4). This bacteria family was already associated with beneficial impact on health in human and in mice . For example, it has been associated with longevity , with beneficial impacts on obesity [48, 72] and with metabolic health . The ability of Christensenellaceae to produce butyric acid confers to these bacteria a real health interest (refer to the section “Short-Chain Fatty Acids metabolic pathway”). Interestingly, in parallel, it was shown that Christensenellaceae is one of the most heritable bacterial families of the human intestinal microbiota . This leads us to formulate the hypothesis that host genetic variations between lines N and 61 might cause variations in Christensenellaceae abundance, which in turn could affect Salmonella resistance. However, to our knowledge, the heritability of Christensenellaceae has not been assessed in chicken. Finally, Azcarate-Peril et al. showed that the use of Galacto-Oligosaccharides (GOS) as a prebiotic in chicken increases the clearance of Salmonella Typhimurium after infection and interestingly also increases the Christensenellaceae abundance . Indeed, Christensenellaceae have the capacity to metabolize GOS unlike the host or Salmonella, which could be in disfavour of Salmonella [73, 74].
Family Enterobacteriaceae, Butyrate producers and anaerobisation
The family Enterobacteriaceae was more abundant in the resistant line (Figure 4). These bacteria are in competition with Salmonella for the respiration of oxygen  and for the use of nutrients as iron . These bacteria are also able to product bacteriocine to inhibit the proliferation of Salmonella . The family Ruminococcaceae and the genera Flavonifractor, Pseudoflavonifractor, Anaerostipes and Intestinimonas, which are butyrate producers [77, 78], were also more abundant in the resistant line. We have already described the beneficial effects of butyrate (see the section “Short-Chain Fatty Acids metabolic pathway “). We can add that, according to Litvak and colleagues in 2019, the combined effects of butyrate production, maintaining a low oxygen concentration, and oxygen respiration by competitive bacteria such as Enterobacteriaceae, lead to an anaerobisation of the lumen and thus, a decrease of the capacity of Salmonella colonisation . Our results are compatible with this hypothesis.
Family Ruminococcaceae and inflammation
We showed that the Ruminococcaceae family is less abundant in the susceptible line 61 (Figure 4). It has been shown that a decrease of Ruminococcaceae can be associated with an increase of inflammation  and thus an increase of Salmonella competition .
Other interesting bacteria associated with low carriage were identified in experiment 2 but not confirmed in experiment 1. This is the case of Lactobacillus, which were more abundant in the resistant line. Some species of these bacteria, used as a probiotic, were shown to significantly decrease the Salmonella Enteritidis carriage [79, 80] and are also associated with the acceleration of Salmonella Typhimurium clearance in chicken . Nevertheless, bacteria beneficial for health have also been found with a higher abundance in the susceptible line. For example, the Blautia genus, which is more abundant in line 61 in experiment 2 (not confirmed in experiment 1), is a butyrate producer  and has beneficial anti-inflammatory effects . Thus, looking at individual taxa might not be sufficient. More likely, we suggest that the total balance of beneficial bacteria has an impact on the Salmonella resistance, which supports the idea of studying the aggregated contributions of several taxa to the same metabolic pathway.