This study investigated how diets with different inclusion levels of whole grain rye influenced fecal microbiota composition, SCFA profile, and ATTD in dogs. The main differences were observed with the highest inclusion level of rye (50% of DM), which caused a change in microbial composition, mainly due to an increase in the relative abundance of Prevotella.
Multivariate analysis showed a difference in microbial composition after the R diet compared with the other diets. This difference was primarily driven by an increase in Prevotella and a decrease in Catenibacterium, Bacteroides, Romboutsia, and Megamonas (Fig. 3). Univariate analysis showed that the relative abundance of several taxa changed significantly between the baseline and after the diet periods in general. For Prevotella, Romboutsia, and an unclassified member of Peptostreptococcaceae, the model revealed that the changes were significant only for the R diet. The detection of higher relative abundance of Prevotella is in line with findings in a previous study on humans examining the effect of rye-kernel bread versus white wheat bread on gut microbiota . That study found that Prevotella increased after rye bread compared with white wheat bread consumption, but that Bacteroides showed a tendency to decrease with rye bread consumption compared with wheat bread. In a study on pigs, increased abundance of Prevotella following consumption of an arabinoxylan-rich diet, although derived from wheat, has been reported . A recently published study on Beagle dogs fed a vegetarian diet supplemented with feather meal and either corn meal, rye, or fermented rye did not find any significant influence on microbiota composition, but addition of rye, fermented or not, increased the proportion of the phylum Bacteroidetes, in particular in some dogs . Prevotella is a dominant member of the Bacteroidetes phylum, and thus our results point in the same direction as those in that study. Our finding of increased relative abundance of Prevotella after the R diet is interesting, since a previous study in humans and mice found that high abundance of Prevotella had a favorable impact on glucose metabolism when the test subjects consumed a fiber-rich diet compared with a refined carbohydrate product . It would be interesting to investigate, using a larger sample, whether this connection also exists in dogs.
Since the abundance of the different taxa was measured as relative proportions, it is plausible that the difference seen in PCoA and ANOSIM was driven by the large increase in Prevotella after the R diet and that the reductions in the other taxa were mainly a consequence of that. However, there was large variation in relative abundance of taxa, both between and within the dogs, which in combination with a small sample size probably masked other changes in microbial composition linked to the experimental diets.
Firmicutes/Bacteroidetes ratio and Prevotella/Bacteroides ratio have previously been shown to be affected by carbohydrate to protein ratio in the diet of humans [44, 45] and dogs . In humans, the amount of complex carbohydrates is suggested to be the main influence . Our study, although based on a limited number of animals, showed similar indications, with a lower Firmicutes/Bacteroidetes ratio after the R diet period and a tendency for higher Prevotella/Bacteroides ratio depending on diet and time. The change in Prevotella abundance was likely the main contributor to the changes in both ratios. The shift in ratio after the R diet period aligns well with the findings from the previous mentioned study , which also observed that inclusion of rye, but not corn, shifted the Firmicutes/Bacteroidetes ratio in favor of Bacteroidetes.
For the other taxa identified in this study, a few published papers have reported associations to dietary fiber. A decrease in Catenibacterium abundance was indicated as important for the difference in ANOSIM after the R diet, whereas a previous study in pigs observed an increase in Catenibacterium abundance after inclusion of oat bran in the diet . Megamonas abundance has been found to increase in dogs fed a diet based on raw meat supplemented with inulin, compared with a control . Faecalibacterium, which has previously been associated with fiber-rich diets [12, 49] and colonic health in dogs , decreased in relative abundance after all diets in our study.
The three experimental diets were designed to be as similar as possible in terms of fat content, but all experimental diets had a higher fat content than the dogs’ standard diet. This change from the normal diet might have contributed to some of the changes detected in microbiota composition, as a previous study on dogs found that consumption of a high-fat, low-starch diet led to a decrease in Prevotella compared with a high-starch, low-fat diet . However, the high fat content in the diets in our study did not seem to have a negative effect on Prevotella.
Statistical analysis of fecal SCFA indicated a tendency for an increased proportion of acetic acid depending on diet, which was due to a difference between baseline R diet and post R diet, but no other differences were found. Acetate has been reported to suppress appetite in mice , indicating one possible way in which rye can promote satiety. Prevotella-dominant microbiota has been shown to correlate with increased relative production of propionate rather than acetate, although with some differences depending on substrate [16, 51]. However, high proportional acetate production has been seen in combination with Prevotella-dominated microbiota in finisher pigs fed pea fiber . The total amount of SCFA produced is also reported to depend on the dominant genera. Prevotella-dominated fecal inoculum has been found to increase the amount of SCFA in vitro compared with Bacteroides fermenting the same type of fiber, indicating higher fiber-utilizing capacity in Prevotella . We expected total fecal SCFA to increase with increased inclusion of whole grain rye, due to the larger quantity of fermentable fiber. However, the absolute levels of SCFA could not be determined, because some of the dogs apparently ingested small amounts of gravel from their outdoor pen, which contaminated the fecal samples.
In the R diet period, ATTD was lower for all nutrients, including GE, compared with the other diet periods. This is in line with findings in a study on pigs comparing whole grain cereals from rye and wheat , where lower digestibility (both ileal and total tract) was seen for rye and attributed, in part, to higher viscosity. A study on dogs in which rye was added at 20%, as-is, to a basic diet found no differences in ATTD of crude protein or crude fat . Dog foods containing other cereals have been observed to vary in digestibility of nutrients depending on carbohydrate source , with digestibility decreasing with increasing fiber inclusion . The difference in ATTD between diets in our study may also have been due to the rye meal being more coarsely ground than the wheat meal. Our fecal collection period of three days, with only one sample per day, might also have added some uncertainty to the results. The European Pet Food Industry Federation  recommends total fecal collection over a period of four days, which was not practically possible in our case. The difference in ATTD could have been expected to affect fecal DM, but no such difference was detected. However, we observed more sand and gravel in the feces following the R diet, and it is possible that the fecal DM content in R period samples would have been lower without this contamination.
Most dogs accepted all diets but the subjects were laboratory Beagle dogs, which are accustomed to eat what they are offered, and dogs of other breeds or privately owned dogs might be more selective. However, all dogs lost weight during all periods, which can be attributed to a number of factors. Apart from differences in ATTD, we calculated the daily energy requirement of the dogs based on the National Research Council recommendation for the average laboratory kennel dog, without considering individual variation. In addition, the outdoor temperature differed between periods and might have affected energy expenditure to a considerable extent. That was the reason for the increment in the daily ration in the RW diet period, the coldest period. Since some adjustments were made to the daily portion size and the weather conditions were different, no statistical analysis was performed on the weight loss.
Fecal samples are often used in studies examining gut microbiota composition and function, due to the non-invasiveness and ease with which they can be collected. We were interested in the effects of different cereal carbohydrate sources on microbial composition and production of SCFA and ATTD, and we assumed that fecal samples would give a fair approximation of these effects. One limitation is that samples taken from different parts of the intestine often differ in microbial composition . However, the differences between colon and rectum have been shown to be non-significant , which indicates that fecal samples give a good reflection of the colonic microbiota. The composition and amount of SCFA have also been shown to shift in samples collected along the large intestine of pigs , presumably due to colonic uptake of SCFA and depletion of fermentable substrate. To our knowledge, no study has compared SCFA content in cecum/proximal colon fecal samples from dogs. However, given the considerably smaller cecum and shorter colon of dogs compared with pigs, these considerations might not be completely applicable to dogs. Therefore, fecal samples may give a reasonable approximation of SCFA produced along the colon.
Our study was limited by the small sample size. Large inter-individual variation was likely one reason why some of the differences between diets did not prove statistically significant. Further, although we did not observe any coprophagia, it might have occurred. This could have affected the microbiota, SCFA, and ATTD. To mitigate these effects, we did not apply a cross-over design in the experiments, even though some of the effects seen could then have been due to seasonal fluctuations in the microbiota. However, we did not see any differences in the baseline samples that could explain the differences after the diet periods, indicating that the changes were indeed due to diet.