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Comparative genomic analysis revealed genetic divergence between Bifidobacterium catenulatum subspecies present in infant versus adult guts

Abstract

Background

The two subspecies of Bifidobacterium catenulatum, B. catenulatum subsp. kashiwanohense and B. catenulatum subsp. catenulatum, are usually from the infant and adult gut, respectively. However, the genomic analysis of their functional difference and genetic divergence has been rare. Here, 16 B. catenulatum strains, including 2 newly sequenced strains, were analysed through comparative genomics.

Results

A phylogenetic tree based on 785 core genes indicated that the two subspecies of B. catenulatum were significantly separated. The comparison of genomic characteristics revealed that the two subspecies had significantly different genomic sizes (p < 0.05) but similar GC contents. The functional comparison revealed the most significant difference in genes of carbohydrate utilisation. Carbohydrate-active enzymes (CAZyme) present two clustering patterns in B. catenulatum. The B. catenulatum subsp. kashiwanohense specially including the glycoside hydrolases 95 (GH95) and carbohydrate-binding modules 51 (CBM51) families involved in the metabolism of human milk oligosaccharides (HMO) common in infants, also, the corresponding fucosylated HMO gene clusters were detected. Meanwhile, B. catenulatum subsp. catenulatum rich in GH3 may metabolise more plant-derived glycan in the adult intestine.

Conclusions

These findings provide genomic evidence of carbohydrate utilisation bias, which may be a key cause of the genetic divergence of two B. catenulatum subspecies.

Peer Review reports

Introduction

Bifidobacterium is a genus of gram-positive, anaerobic microorganisms that are commonly found in the intestine of humans and animals [1, 2]. Some strains of Bifidobacterium have attracted significant attention due to their probiotic function in regulating microbiota and immune metabolism [3, 4]. Bifidobacterium catenulatum (B. catenulatum) is an important member of the genus; some of its strains demonstrate favourable probiotic characteristics, such as the preclinical treatment of acute liver injury [5], in vitro inhibition of pathogenic bacteria as well as the ability to stay alive in yoghurt for a long period [6]. These potential probiotic properties suggest that B. catenulatum may be a candidate for probiotics in food or medicine.

Bifidobacterium has long been considered an important intestinal symbiotic bacterium co-evolving with its hosts. In the previous studies, the dominant species of Bifidobacterium in the gut of infants and adults are usually different [1, 7, 8]. For example, B. bifidum, B. longum subsp. infantis and B. breve are commonly found in the gut of infants, while B. adolescentis and B. catenulatum usually appear in the intestinal tract of adults [9,10,11,12]. According to the latest taxonomy [13], B. catenulatum contains two subspecies, B. catenulatum subsp. kashiwanohense and B. catenulatum subsp. catenulatum. These two subspecies have different preferences in infant and adult intestine [14, 15]. B. catenulatum subsp. catenulatum is usually the dominant Bifidobacterium species in the adult gut [12, 15, 16]. Although B. catenulatum subsp. catenulatum is also present in infants, it is not the dominant Bifidobacterium species in the infant gut microbiota [15], and it is shown to be shared between in single mother-infant pairs [1]. B. catenulatum subsp. kashiwanohense is a greatly rare species, which lives mainly in the gut of infants [14]. Current research suggests that B. catenulatum’s adaptation to different hosts is partially due to the functional preference of different subspecies, such as carbohydrate metabolism [14]. However, there is limited genomic evidence corresponding to the different functional preferences of the two subspecies. Therefore, it is necessary to fill the gap in the genomic knowledge of the genetic divergence and functional differentiation of the two subspecies; the additional information will be useful for supplementing the existing knowledge on the bacterium and providing scientific support for their purported health benefits.

In-species comparative genomics analysis allows for a deeper understanding of the individual characteristics between genomes [17]. However, because the Bifidobacterium genus is strictly anaerobic, thus it is difficult to culture and easily contaminated by other species [18]. The number of published B. catenulatum genomes is currently limited. Recently, newly developed sequencing technologies have begun to uncover the B. catenulatum genomes [19]. While there have been genomic analyses of this species, most of the genomic information of B. catenulatum remains unexplored.

In the current study, a total of 19 genomes of B. catenulatum species were analysed, including 12 B. catenulatum subsp. catenulatum and 5 B. catenulatum subsp. kashiwanohense from the Refseq database, and 2 newly sequenced (IMAUFB085 and IMAUFB087) strains. The study dissected the genetic background and functional genomic information in B. catenulatum using comparative genomic approaches. This work not only provides general insights into the genomic differences between two subspecies of B. catenulatum but also reveals the key factors leading to their divergence.

Results

Average nucleotide identity (ANI) and Total nucleotide identity (TNI) analyses of B. catenulatum strains

The sequence similarity and taxonomic status among the strains used in this study were confirmed by calculating the pairwise ANI (Fig. 1A) and TNI (Fig. 1B) values of all 20 genome assemblies. Strains with an ANI value of over 95% are generally considered the same species [20]. The ANI and TNI analyses produced similar clustering results, displaying distinct subspecies branches. IMAUFB085 and IMAUFB087 were grouped with most of the B. catenulatum subsp. catenulatum strains; their ANI values compared to that of B. catenulatum subsp. catenulatum JCM1194T were 98.41% and 98.42%, and TNI values were 87.45% and 84.48%, respectively. These results confirmed the classification of IMAUFB085 and IMAUFB087 as B. catenulatum subsp. catenulatum.

Fig. 1
figure 1

Heatmap of ANI (A) and TNI (B) based on the sequences of 20 genomes. The location and isolated resource of primary B. catenulatum isolates were annotated

ANI analysis revealed that 3 B. catenulatum subsp. catenulatum strains, JGBg468, BCJG468 and MC1, significantly differed from the other B. catenulatum subsp. catenulatum strains; their ANI values compared to JCM1194T were 93.83%, 93.88% and 93.86%, respectively, less than the threshold value of 95%. Therefore, these strains were subsequently excluded. In addition, cluster analysis distinguished two subspecies. The ANI value was greater than 95% between the 2 subspecies groups, and greater than 98% within the subspecies, indicating that these strains belonged to the same species.

Comparison of general genomic features between two subspecies

The general information of the strains shows that all B. catenulatum subsp. kashiwanohense strains are derived from infants, while only two strains of B. catenulatum subsp. catenulatum are known to be infantile isolates (Table S1). The genomic features of 19 B. catenulatum genomes are summarised (Table 1) and the genomic characteristics within the B. catenulatum species exhibited different degrees of difference. The genome size and GC content of B. catenulatum isolates were 2.16 ± 0.13 Mb and 56.21 ± 0.11%, respectively. A comparison of the basic genomic characteristics of the two subspecies (Fig. S1) indicated that the genome size of B. catenulatum subsp. kashiwanohense (2.36 ± 0.05 Mb) was significantly larger than that of B. catenulatum subsp. catenulatum (2.09 ± 0.07 Mb) (p = 0.0021), while there were no significant differences in GC content (p > 0.05). The substantial genomic differences reflected the speciation boundaries of the two subspecies, while the similarity in GC content represented a close relationship between them [21, 22]. In addition, B. catenulatum subsp. kashiwanohense contained more coding genes (CDSs) than B. catenulatum subsp. catenulatum (p = 0.0046) and there were no statistical differences in the number of tRNAs (p > 0.05).

Table 1 General genomic features of B. catenulatum genomes

The overall genomic differences between the two subspecies were further explored using the BLAST Ring Image Generator (BRIG) to graphically compare B. catenulatum strains with B. catenulatum subsp. kashiwanohense strain JCM15439T as the reference (Fig. S2). Overall, most of the sequences in JCM15439T were also in all other strains, and the genomes were more than 90% identical. However, two large genomic gaps (GGs) existed separately in the two newly sequenced strains, IMAUFB085 and IMAUFB087, which had less than 70% of the matched degree compared to JCM15439T. In general, the GG sequences represent hypothetical CDSs, genomic islands or prophages [23]. These data indicate that these two strains have many unknown genomic information to be explored.

Phylogenetic divergence of two subspecies of B. catenulatum

Classification of species and establishment of intra-specific relationships are frequently based on phylogenetic analysis. A phylogenetic tree based on 785 core genes was constructed that confirmed the subspecies divergence of B. catenulatum (Fig. 2A). 16 B. catenulatum strains were clearly divided into two subspecies, indicating the genetic differences between the two subspecies at the genomic level. Interestingly, the annotation of the source of the isolates suggested a significant cluster. Infant isolates, including all B. catenulatum subsp. kashiwanohense strains and 2 B. catenulatum subsp. catenulatum strains, exhibited intra-specific genetic similarity, while the rest were adult isolates in another cluster, indicating close phylogenetic relationships. These data suggest that the divergence of the B. catenulatum strains likely dependent on their hosts. B. catenulatum may adapt its functions to infant and adult intestines respectively, thus gradually differentiating into different subspecies.

Fig. 2
figure 2

Phylogenetic tree of two subspecies of B. catenulatum. Phylogenetic NJtree of B. catenulatum species and taken B. pseudocatenulatum JCM1200T as the outgroup. Bootstrap was set as 1000. All the B. catenulatum strains were annotated to isolate location and source. The scale bars represent 0.01 substitutions per site (A). UpSet diagram showing shared and unique core genes distribution among B. catenulatum strains. The horizontal bars represent the total number of genes identified of individual strains. The vertical bars or intersections represent the number of genes that were regulated by one or more strains. The orange dots represent unique genes and the yellow dots represent core genes. The green items represent information about B. catenulatum subsp. catenulatum, and the blue items represent information about B. catenulatum subsp. kashiwanohense. Groups with fewer than 10 genes were filtered (B)

Constructing the pan-core genome of B. catenulatum

The gene pool of a population contains all the genetic material and functions of a species. Roary was used to calculate the pan-core genome of the 16 B. catenulatum strains; a total of 4608 pan genes were searched. The genetic distribution of B. catenulatum showed that the two subspecies of B. catenulatum shared 998 core genes (21.66%) (Fig. 2B). There were unique core gene sets in the 2 subspecies, with 87 unique core genes in B. catenulatum subsp. kashiwanohense and 63 in B. catenulatum subsp. catenulatum (Table S2). The unique core gene sets of two subspecies are involved in the metabolism of diversity functions, such as carbohydrate (group_1783, group_2168, et al.), amino acid (metI, group_2203, et al.), protein (group_1013, group_1298, et al.), and so on. These unique core genes may play a role in the differentiation of their species [2, 22, 24], although some are hypothetical proteins. Additionally, there were different numbers of strain-specific genes in the B. catenulatum subspecies; their numbers ranged from 20 to 578, suggesting the potential genetic diversity among B. catenulatum species.

Subsequently, the pan-core gene curves for the genomes of the B. catenulatum species were established (Fig. S3A). With the addition of the new genomes, the number of pan genes increased, indicating the existence of an open pan-genome within the species of B. catenulatum. In contrast, the number of core genes was not expected to be significantly reduced by the addition of the new genomes since the exponential trendline reached the number of 1000. Notably, B. catenulatum subsp. catenulatum has a fairly open pan-core genome (Fig. S3B), while B. catenulatum subsp. kashiwanohense’s genome tends to be closed (Fig. S3C). These results indicate that B. catenulatum subsp. catenulatum may have flexible environmental adaptability, while B. catenulatum subsp. kashiwanohense exists in a more specific and conserved habitat [25]. However, due to the limitation of B. catenulatum genome number, this deduction needs more sequencing results to confirm.

Comparison of the main functions between two subspecies

The above results have uncovered the genetic differences between the two subspecies at the general genomics level, which are usually associated with functional differentiation [24]. Therefore, it is necessary to conduct further functional genomic comparisons between the two subspecies of B. catenulatum. Their functional genomic differences were obtained by annotating all the strains through the RAST website. The functional annotations of 16 B. catenulatum genomes were examined in 23 functional categories (Fig. S4). These results suggest that the function of amino acid derivatives (21.06%) is the most highly represented category within B. catenulatum followed by protein metabolism (21.00%) and carbohydrate metabolism (15.73%) (Fig. S4). It indicates that the three functions are the main ability to utilise substrates by B. catenulatum. The comparison of the main functional differences between the two subspecies showed the subspecies differ significantly in their metabolism of carbohydrates (p = 0.01), amino acids (p = 0.011) and proteins (p = 0.012) (Fig. 3A, 3B, 3C).

Fig. 3
figure 3

Comparison of the main functions between B. catenulatum subsp. catenulatum and B. catenulatum subsp. Kashiwanohense. Significant difference of genes in major functions. Amino acid derivatives (A); Protein metabolism (B); Carbohydrate metabolism (C). Heat maps of detailed subcategories of main functions (D). The numbers in the heat map indicate the number of copies of functional genes. *p < 0.05, **p < 0.01, ***p < 0.001

In view of the remarkably significant differences in the metabolic functions of carbohydrates, amino acids and proteins in the two subspecies, the detailed categories of the main functions were compared in the two subspecies (Fig. 3D). It showed that the two subspecies are divided into two clusters, and the difference in functional genes was most significant in carbohydrates, it mainly lie in aminosugars, monosaccharides and an unclassed subcategory related to carbohydrates. In addition, the most significant differences in protein occurred in genes related to protein biosynthesis, and for amino acids it occurred in functional genes of lysine, threonine, methionine, and cysteine. This suggests that the functional difference in these significant subcategories is the key to the difference in the functional genomes of the two subspecies of B. catenulatum. Because of the most significant difference between the two subspecies was in carbohydrate function, the B. catenulatum genes involved in carbohydrate utilisation were analysed.

Different carbohydrate utilisation patterns in two subspecies of B. catenulatum

The carbohydrate utilisation abilities of B. catenulatum subspecies at the genomic level were compared by analysing the functional genes of carbohydrate-active enzymes (CAZymes) of 16 B. catenulatum strains. As shown in Fig. 4A, 16 B. catenulatum strains were distributed in all six carbohydrate-active enzyme families, indicating that they had rich carbohydrate functions. Notably, the clustering results of CAZymes were roughly consistent with those of the phylogenetic trees in that the two subspecies were distinct. This finding not only suggests that the two subspecies have different metabolic patterns in terms of carbohydrate utilisation, but also indicates that CAZymes-related genes are closely associated with the divergence of B. catenulatum subspecies.

Among the identified GH families in B. catenulatum species, the most dominant ones were GH3, GH13 and GH43; meanwhile, GT2 and GT4 were the main carbohydrate enzyme families within B. catenulatum species. Comparing the main carbohydrate hydrolase families in the subspecies revealed the number of GH3 family members was significantly higher in B. catenulatum subsp. catenulatum than those in B. catenulatum subsp. kashiwanohense (p = 0.0038, Fig. 4B). GH3 is mainly involved in the metabolism of plant-derived glycan common in the adult diet, such as β-glucosidase and xylosidase [26]. However, there was no statistically significant difference in the function of GH13, GH43, GT2 and GT4 between the two subspecies (p > 0.05) (Fig. 4C, 4D, 4E, 4F). Therefore, GH3 may be a key factor in the divergence of carbohydrate functional genes between the two subspecies of B. catenulatum.⁠

Fig. 4
figure 4

Prediction of CAZymes in 16 B. catenulatum strains. The Heatmap of CAZymes in B. catenulatum. The isolated source of strains was annotated (A). The significance analysis of the key CAZymes families between two subspecies of B. catenulatum including GH3 (B), GH13 (C), GH43 (D), GT2 (E), and GT4 (F). Specific CAZymes in B. catenulatum subsp. kashiwanohense (G)

Analysis of the specific CAZymes of B. catenulatum subsp. kashiwanohense revealed five families that only existed in the subspecies, including GH18, CBM5, GH95, CBM51 and CBM66 (Fig. 4G). The CBM family is primarily responsible for banding carbohydrates. In addition, the GH18 family often combines with CBM5 to participate in the function of chitinase, and CBM66 mainly assists in the degradation of fructose [27]. In particular, the GH95 family is specifically involved in the production of α-L-fucosidase, the most abundant substance in HMO and closely related to the function of infant-specific species [28]. Additionally, the CBM51 family helps GH95 enzymes pick up fucose to metabolise HMO [29]. These CAZyme families CBM51 and GH95 may be conducive to the colonisation of B. catenulatum subsp. kashiwanohense in the intestines of infants, especially the utilization of HMO, in contrast to the abundance of plant-derived glycan of B. catenulatum subsp. catenulatum, further suggesting the bias of the two subspecies in carbohydrate utilisation. In addition, GH29 enzymes often interact with GH95 enzymes to utilise HMO [30], and the study found that GH29 is only in B. catenulatum subsp. kashiwanohense except for PV20-2.

Identification of HMO gene clusters in B. catenulatum genomes

Considering the specific utilisation of fucosylated HMO (FHMO) by GH29 and GH95 enzymes, the FHMO gene cluster in B. catenulatum were subsequently examined. Two Bifidobacterium strains (B. longum subsp. longum SC596 and B. pseudocatenulatum JCM1200T) with typically structural FHMO gene clusters were selected as the reference [31] for the search for the homologous FHMO gene cluster in all of the B. catenulatum genomes. The homologous alignment showed an integrated FHMO gene cluster in all B. catenulatum subsp. kashiwanohense genomes but not in B. catenulatum subsp. catenulatum (Fig. 5), further confirming the unique ability to utilise HMO by B. catenulatum subsp. kashiwanohense. In the study, two different structures of FHMO gene clusters, named type I and type, ⁠were found in B. catenulatum subsp. kashiwanohense (Table S3). Type I shared 89.6% homology with B. longum subsp. longum SC596. The size of type I was about 13.0 kb, including 11 open reading frames (ORF), manifested as GH95, GH29, fucU, dihydrodipicolinate synthase family protein (DHP), amidohydrolase family protein, SDR family oxidoreductase, fuconate dehydratase, three ABC transporters and lacI. Meanwhile, type II shared 97.8% homology with B. pseudocatenulatum JCM1200T; it was only found in PV20-2 and lacked GH29 and fucU genes, consistent with the results of CAZymes.

Fig.5
figure 5

HMO gene clusters in B. catenulatum subsp. kashiwanohense and two reference clusters in Bifidobacterium. Arrows represent genes, and numbers on top of each gene indicate the locus tag number in the respective genome. Numbers inside the arrows indicate percent identity between corresponding genes and homologs relative to reference. The numbers outside on the left indicate percent identity of full clusters relative to reference. SBP: Solute Binding Protein; cABC: carbohydrate ABC transporter; sABC: sugar ABC transporter; SDR: SDR family oxidoreductase; DHP: dihydrodipicolinate synthase family protein; fucU: L-fucose mutarotase; fucd: fuconate dehydratase

Notably, the GC content of the FHMO gene clusters in B. catenulatum subsp. kashiwanohense was significantly lower than the entire subspecies (Fig. S5), suggesting that its FHMO gene clusters might be obtained through horizontal gene transfer (HGT) [32,33,34]. The identification of the FHMO gene clusters in B. catenulatum subsp. kashiwanohense further confirmed its advantage of HMO utilisation, thus providing genomic evidence for its adaptability in the infant intestine.

Discussion

As a typical intestinal symbiotic bacteria, Bifidobacterium has experienced a long and extensive evolutionary process in human hosts [1]. For example, B. catenulatum has evolved into two subspecies, B. catenulatum subsp. kashiwanohense and B. catenulatum subsp. catenulatum. Previous studies have revealed that B. catenulatum subsp. kashiwanohense and B. catenulatum subsp. catenulatum have a close phylogenetic relationship [2]. Here, phylogenetic reconstruction has revealed genetic differences between the two subspecies. The genome size and the number of the CDSs of B. catenulatum subsp. catenulatum were significantly lower than that of B. catenulatum subsp. kashiwanohense. Also, both subspecies have a unique core gene set, such results represent a marker of genetic divergence [22]. In addition, there was obvious host differentiation in B. catenulatum, that B. catenulatum subsp. catenulatum is more present in adult intestines [1, 2], while B. catenulatum subsp. kashiwanohense commonly be confirmed as an infant-associated species [14]. Although B. catenulatum subsp. kashiwanohense is only rarely reported, previous studies have shown that kashiwanohense can be present in breast milk samples [15] and utilize milk-derived substrates, suggesting that the infant gut may be its main niche [14]. In this study, the possible association between subspecies divergence and the host was further explored through functional genomic comparisons to explain the divergence of B. catenulatum at the genomic level.

Bifidobacterium is a genus of saccharolytic microorganisms whose ability to utilise indigestible carbohydrates is essential for their establishment in the gastrointestinal tract [35]. In this study, functional genomics revealed significant differences in the carbohydrates consumed by the subspecies of B. catenulatum. Notably, the CAZymes cluster results are consistent with the phylogenetic tree analysis, suggesting that the functional differences in carbohydrates may be related to the genetic divergence of B. catenulatum. This study found that the GH3 content of B. catenulatum subsp. catenulatum was significantly higher than that of B. catenulatum subsp. kashiwanohense. Previous studies have shown that GH3 is a key family in the evolution of Bifidobacterium and is involved in the degradation of plant polysaccharides [36]. The results here indicate that GH3 is also a key factor for the divergence of B. catenulatum in carbohydrate function. Studies have shown that the gut environment in adults is more complex than in infants because adults typically consume more difficult-to-digest carbon sources, such as plant-based dietary fibre [9, 10]. Kim et al. found that B. catenulatum strains can degrade fructooligosaccharides (FOS) in nutritionally restricted environments [37]. Previous studies have shown that a low-fiber diet in adults can cause a significant increase in the abundance of B. catenulatum [38]. Here, the results demonstrate that B. catenulatum subsp. catenulatum has more GH3 that utilises plant-derived glycans; therefore, the subspecies is conducive to the decomposition of difficult-to-use plant-derived glycans in the adult gut.

On the other hand, infants, especially those who are breastfed, have many HMOs in their intestines. HMO is a prebiotic unique to breast milk and is especially enriched in human breast milk [39]. The ability of infant-specific Bifidobacterium to metabolise HMO has been recognised as a specific marker of its adaptive colonisation and beneficial for strengthening the immune system in infants [40]. For B. catenulatum subsp. kashiwanohense, which is characterised by infant adaptation [14], its two specific CAZymes, namely GH95 and CBM51, which are notable. GH95 mainly utilises fucosyllactose, a major component of HMO [41]. On the other hand, CBM51 is beneficial to GH95 and helps it pick up FHMO [29]. Thus, this study suggests that GH95 and CBM51 act synergistically in the utilisation of FHMO by B. catenulatum subsp. kashiwanohense. In particular, GH29 is often identified with GH95 as the family of metabolic HMO [30]. In B. catenulatum subsp. kashiwanohense, all strains except PV20-2 contain GH29. Therefore, the study suggests that these three families (GH29, GH95 and CBM51) play an important role in the colonisation of B. catenulatum subsp. kashiwanohense in the infant intestine.

Based on the findings related to the HMO-related families, this study further confirms the existence of relatively conserved HMO gene clusters in B. catenulatum subsp. kashiwanohense while not in B. catenulatum subsp. catenulatum. These HMO gene clusters are highly homologous to those in other typical infantile adapted Bifidobacterium that are connected to the GH95 and GH29 families. Only the PV20-2 strain lacks GH29 and fucU, while the genome of PV20-2 shares high homology with the HMO gene cluster of B. pseudocatenulatum JCM1200T, which can grow in purified FHMO [42], the lack of these two genes appears to have little effect on the overall ability to use FHMO. Given that the reference genomes in HMO gene clusters are all from infants, their clusters have been demonstrated to be conducive to their utilisation of HMO [35, 42]. This study suggests that B. catenulatum subsp. kashiwanohense may have a similar utilisation mechanism of FHMO for adaptive survival in the infant intestine [30, 35, 41]. Previous studies [14, 43] had confirmed through gene expression experiments that the fucosyllactose transporters in B. catenulatum subsp. kashiwanohense JCM15439T and HMO genes in B. catenulatum subsp. kashiwanohense APCKJ1 endowed them with ability of HMO consumption, thus contributing to their adaptation in the HMO-rich environments. Given the high similarity of the HMO gene clusters in B. catenulatum subsp. kashiwanohense, this ability to consume HMO may be an intrinsic characteristic of this subspecies. In addition, a group_2168 gene codes L-fuconate dehydratase specifically exists in the unique set of B. catenulatum subsp. kashiwanohense (Table S2), which would be one of the markers of genetic divergence [22] and is consistent with the conclusion that it adapts to metabolizing FHMO. Notably, B. catenulatum subsp. catenulatum 1899B and IMAUFB085 belong to infant isolates, but no HMO genes were found in them, further confirming that possession of HMO genes is a genetic trait of B. catenulatum subsp. kashiwanohense.

The complex carbohydrate environment in the human gut can drive HGT events in Bifidobacterium, and commonly occurs between closely related species [44, 45]. Garrido et al. [11] propose that the HMO gene clusters have transferred from B. longum subsp. infantis to B. longum subsp. longum during evolution. Notably, the HMO gene cluster in B. catenulatum subsp. kashiwanohense in this study showed a significant decrease in GC content. Previous reports confirmed that HGT fragments differ from native genes in GC content [33, 34]. Thus we infer that the HMO clusters of B. catenulatum subsp. kashiwanohense were obtained by HGT, which were important in the genomic evolution of species [11]. At present, these types of HMO gene clusters have been found in typical infant-derived strains, such as B. breve, B. longum and B. pseudocatenulatum species, and they have high homology with each other [30, 35, 42]. This study proposes that B. catenulatum subsp. kashiwanohense acquired HMO gene clusters through HGT from other proximal species (such as B. longum), the acquisition of HGT contributed to the specific function of genome divergence and HMO utilisation.

Although the two subspecies of B. catenulatum are closely phylogenetically related and share a common ancestor [2], previous studies have confirmed that they showed different tendencies adapted in infants and adult intestines [9, 10, 14]. Taken together, given that the carbohydrate genetic pattern of the two subspecies was consistent with the phylogenetic relationship, we speculated that the B. catenulatum species evolved to retain the competitive carbohydrate function genes to adapt to the intestinal environment of infants and adults respectively, driving the emergence of two subspecies. Our results are similar to the divergence of B. longum, for the infantis subspecies of it has specific genes related to the metabolism of HMO and is more suitable for breast-feeding infant intestines, while the longum subspecies is present in both infant and adult hosts but has more genes for the utilization of plant-derived glycan and is more suitable for adult diets [35]. The example of this divergence of species in different hosts seems to suggest a potential pattern of genetic divergence of Bifidobacterium, in which infant and adult wealthy species have more HMO genes and plant-derived glycan genes respectively in the human gut in order to adapt to their respective hosts.

Conclusions

In summary, this study proposes that the B. catenulatum species evolved to retain the competitive carbohydrate function genes to adapt to the respective intestinal environment in infants and adults, driving the emergence of two subspecies. This study has provided genomic evidence for the potential host adaptation phenomenon of B. catenulatum in infant and adult intestines. However, the number of B. catenulatum strains is limited; more strains will need to be sequenced in the future to dissect further the mechanism underlying their genetic divergence.

Methods

Bacterial strains, DNA extraction and publicly available assemblies

The two B. catenulatum strains (IMAUFB085 and IMAUFB087) that sequenced in this study were provided by the Lactic Acid Bacteria Collection Center (LABCC). Moreover, IMAUFB085 was isolated from infant faeces and IMAUFB087 from adult faeces in Tibet, China [46].

The two strains were cultured under anaerobic conditions in the Man Rogosa and Sharpe (MRS) broth with L-cysteine hydrochloride at 37 °C for 24 h. DNA extraction was performed using the TIANamp Bacteria DNA Kit. Genomic DNA was quantified using a TBS-380 fluorometer. High-quality DNA samples were obtained to construct fragment libraries.

In addition, other 17 B. catenulatum genomes were obtained from the National Coalition Building Institute (NCBI, https://www.ncbi.nlm.nih.gov/) on 4 February 2021, including that of type strains, namely B. catenulatum subsp. catenulatum (JCM1194T) and B. catenulatum subsp. kashiwanohense (JCM15439T) (Table S1). Additionally, the B. pseudocatenulatum strain (JCM1200T) in the B. adolescentis group, most closely related to B. catenulatum according to the phylogenetic relationship of Bifidobacterium genus in a previous study [2], were downloaded to infer phylogenetic relationships across species within it.

Genome sequencing and assembly

Genome sequencing was performed using the Illumina HiSeq platform to generate 150-bp paired-end reads for each sample. Then, the sequences were filtered through the Illumina HiSeq system. The high-quality sequences were assembled using SOAPdenovo2 [47] on a 64-bit Linux system. High-quality data corresponding to a sequencing depth of about 387-fold, was generated for each strain. In addition, local inner gaps were filled, and single-base errors were corrected using GapCloser (http://sourceforge.net/projects/soapdenovo2/files/GapCloser/).

Genome annotation

In this study, all the general genomic information of B. catenulatum genomes was generated using self-made Perl scripts with statFASTA.pl. The functional gene information of B. catenulatum was obtained by performing the gene prediction and preliminary annotation of all B. catenulatum genomes through the Rapid Annotation using Subsystems Technology (RAST) server (https://rast.nmpdr.org/rast.cgi). In addition, tRNA genes were identified using tRNAscan-SE (http://trna.ucsc.edu/tRNAscan-SE/).

ANI and TNI

The genetic relatedness between the two B. catenulatum subspecies was evaluated, and the taxonomic status of the strains in this study was confirmed by analysing the ANI and TNI values of all the strains. B. pseudocatenulatum JCM1200T, the type strain most phylogenetically related to B. catenulatum [2], was included in the comparison. All pairwise ANI values were calculated according to the method proposed by Goris et al. [48]. TNI values were calculated according to the method proposed by Chen et al. [49]. Finally, the clustering heat map was drawn using TBtools [50].

Construction of pan-core genome and strain-specific genes

The annotated genomes of B. catenulatum were obtained using Prokka v1.12 [51] and processed using Roary v3.8.0 [52] to identify the pan genes, core genes and specific genes using the default parameters. The intersection groups, representing the unique sets of genes identified only between the intersected genomes, were visualised using the UpSet diagram in TBtools [50].

Phylogenetic analysis

The core gene alignment from Roary was used in TreeBeST [53] with 1,000 bootstrap iterations to build a phylogenetic NJtree through Neighbor-Joining (NJ) [54]. The phylogenetic trees were then visualised and annotated using iTOL (https://itol.embl.de/).

BRIG (BLAST Ring Image Generator)

BRIG v0.95 [55] was adapted to compare the genomes of B. catenulatum strains based on a JAVA language environment. All settings use default parameters. The image of the circular genomes was also generated through BRIG.

CAZymes online annotation

The identification of CAZymes across the B. catenulatum genomes was carried out using the dbCAN2 meta server (http://bcb.unl.edu/dbCAN2/), using three annotation tools, including HMMER, DIAMOND and Hotpep searches [56]. The database includes glycosyltransferases (GTs), glycoside hydrolases (GHs), carbohydrate esterases (CEs), polysaccharide lyases (PLs), auxiliary activity (AA) and carbohydrate-binding modules (CBMs). According to the annotation results, the detailed information on the active carbohydrate enzyme family was checked on the CAZyme website (http: //www.aczy.org/).

Detection of the HMO gene clusters

Taking B. longum subsp. longum SC596 and B. pseudocatenulatum JCM1200T as the reference, which possess typical HMO gene clusters. In addition, the genome of SC596 was obtained from the IMG database [57]. The corresponding protein-encoding sequences were extracted from the genomes and compared using BLASTp with default parameters from the NCBI website. The cut-off values of 50% of similarity across 50% of protein length and a 0.0001 e-value as a significance for the identification of homologous proteins. The recognised HMO gene clusters were visualised using the genoplotR package.

Statistical analysis

The data were presented as means ± SEM. The Wilcoxon signed-rank test was used to verify the significance of the difference between the groups, and visualisation was performed using the ggpubr packages in R (4.0.3). Lastly, significance was set at a p-value of less than 0.05.

Data availability

The assembly and Sequence Read Archive (SRA) data of the two newly isolated sequences in this work were submitted as a Whole Genome project (BioProject No. PRJNA751426) at GenBank under the accessions JAIEWL000000000 (IMAUFB087) and JAIEWM000000000 (IMAUFB085) (available at https://www.ncbi.nlm.nih.gov/bioproject/PRJNA751426). The phylogenetic trees and alignment files in this study were submitted to the TreeBASE web (Accession No. 28852) (available at http://purl.org/phylo/treebase/phylows/study/TB2:S28852).

Availability of data and materials

The assembly and Sequence Read Archive (SRA) data of the two newly isolated sequences in this work were submitted as a Whole Genome project (BioProject No. PRJNA751426) at GenBank under the accessions JAIEWL000000000 (IMAUFB087) and JAIEWM000000000 (IMAUFB085) (available at https://www.ncbi.nlm.nih.gov/bioproject/PRJNA751426). The phylogenetic trees and alignment files in this study were submitted to the TreeBASE web (Accession No. 28852) (available at http://purl.org/phylo/treebase/phylows/study/TB2:S28852).

Abbreviations

LABCC:

Lactic Acid Bacteria Collection Center

MRS:

Man Rogosa and Sharpe

ANI:

Average Nucleotide Identity

TNI:

Total Nucleotide Identity

CDSs:

Coding Sequences

GGs:

Genome Gaps

NJ:

Neighbor-Joining

RAST:

Rapid Annotation using Subsystems Technology

BRIG:

BLAST Ring Image Generator

HMOs:

Human Milk Oligosaccharides

FHMO:

Fucosylated HMO

B. catenulatum :

Bifidobacterium catenulatum

CAZymes:

Carbohydrate-active enzymes

GTs:

Glycosyltransferases

GHs:

Glycoside hydrolases

CEs:

Carbohydrate esterases

PLs:

Polysaccharide Lyases

AA:

Auxiliary Activity

CBMs:

Carbohydrate-Binding Modules

HGT:

Horizontal Gene Transfer

FOS:

Fructooligosaccharides

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Acknowledgements

Not applicable.

Funding

This work was supported by the earmarked fund for CARS36, and Science and Technology Major Projects of Inner Mongolia Autonomous Region (2021ZD0014).

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Authors and Affiliations

Authors

Contributions

HZ designed the study. JL and WL performed comparative genomics analyses and wrote the manuscript. CY and JY participated in the culture and sequencing of two new strains in this study. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Heping Zhang.

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Supplementary Information

Additional file 1: TableS1.

General information of B. catenulatum genomes.

Additional file 2: Table S2.

Unique core genes oftwo subspecies of B. catenulatum.

Additional file 3: Table S3.

Information on HMOgene clusters of B. catenulatum subsp. kashiwanohenseand its references.

Additional file 4: Fig. S1.

Comparison ofgenomic features between two subspecies of B. catenulatum, includinggenome size (A), GC Content (B), CDSs (C) and tRNA (D).

Additional file 5: Fig. S2.

A display of thegenome circle map of 16 B. catenulatum genomes. The figure was generatedbased on comparison of 16 B. catenulatum genomes according to percentageidentity (100%, 90%, or 70%). The numbers on the rings from inside to outside,1: JCM15439T, 2: DSM21854(2)T, 3: DSM21854T,4: APCKJ1, 5: PV20-2, 6: HGUT-01490, 7: LMG11043T, 8: A1, 9: A3, 10:A2, 11: 1899B, 12: DSM16992T, 13: DSM16992(2)T, 14:JCM1164T, 15: IMAUFB085, 16: IMAUFB087.

Additional file 6: Fig. S3.

Tendency curves forpan-core genomes of B. catenulatum. B. catenulatum (A), B.catenulatum subsp. catenulatum (B), B. catenulatumsubsp. kashiwanohense (C).

Additional file 7: Fig. S4.

Comparison of 23functional categories between B. catenulatum genomes. The numbers in theheat map indicate the number of copies of functional genes.

Additional file 8: Fig. S5.

Comparisonof GC content between full-length genomes and FHMO clusters in B. catenulatumsubsp. kashiwanohense.

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Liu, J., Li, W., Yao, C. et al. Comparative genomic analysis revealed genetic divergence between Bifidobacterium catenulatum subspecies present in infant versus adult guts. BMC Microbiol 22, 158 (2022). https://doi.org/10.1186/s12866-022-02573-3

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Keywords

  • Bifidobacterium catenulatum
  • Genomics
  • Carbohydrate utilization
  • Plant-derived glycan
  • Human milk oligosaccharides