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Ladeira et al. Microbiome Res Rep 2023;2:9 https://dx.doi.org/10.20517/mrr.2023.01 Page 11 of 15

Figure 5. Graphical summary.

Following our exploratory analysis of the ecology of the Bifidobacterium community, we evaluated the
functions of Bifidobacterium associated with partitions in a pangenomic analysis (i.e., functional variability
within species). We studied Bifidobacterium-assigned MAGs retrieved from an extensive dataset for the
[16]
human gut microbiome , which could be assigned to metadata and gut microbiome features. EggNOG
analysis confirmed known functional differences between the most prevalent Bifidobacterium species, such
as the specificity of alpha-L-arabinofuranosidase to B. longum, involved in the metabolism of arabinans,
arabinoxylans, and arabinogalactans [27,59] , glycoside hydrolases of host carbohydrate metabolism (mucin,
[60]
human milk oligosaccharide) for B. bifidum , and glycoside hydrolase GH 43 for B. pseudocatenulatum .
[61]
Asparagine synthetase was found to be highly specific to B. adolescentis .
[62]
The association between species function and Bifidobacterium partitions revealed a difference in the
functional features of B. bifidum MAGs across Bifidobacterium partitions in association with health status.
Specifically, B. bifidum MAGs harboring a set of genes potentially related to phages were more prevalent in
partitions associated with a lower gut microbiome diversity and were genetically more closely related. This
potentially highlights the existence of a B. bifidum subspecies with a selective advantage for the colonization
of gut microbiomes with a particular composition. Interest in the possible contribution of phages to gut
microbiome ecology has increased significantly over the last decade, and one recent study showed the
[63]
phages of Bifidobacterium to be rather specific. Overall, our pangenomic analysis revealed several functional
features of B. bifidum differing between Bifidobacterium partitions as a function of health status [Figure 5].

This study has several limitations. First, it is based on the pooling of studies, an approach that is increasingly
used to increase the sample size for ecological analysis. However, there are inherent differences in technical
parameters between studies. Second, only a small amount of metadata is included. Diet is a major factor
underlying gut microbiome variation between subjects. Carbohydrates are the dietary component most
frequently reported to be positively associated with Bifidobacterium . In previous metagenomics-based
[10]
studies with species-level analysis, B. adolescentis was identified as the bifidobacterial species most
significantly associated with dietary habits , whereas both common and different associations between
[11]
different Bifidobacterium species and food scores were identified . The associations between dietary habits,
[12]
partitions, variation of the LCT gene (lactase persistence), and other parameters should, therefore, be