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Bifidobacteria are common and frequently dominant members of the gut microbiota of many animals, including mammals and insects. Carbohydrates are considered key carbon sources for the gut microbiota, imposing strong selective pressure on the complex microbial consortium of the gut. Despite its importance, the genetic traits that facilitate carbohydrate utilization by gut microbiota members are still poorly characterized. Here, genome analyses of 47 representative Bifidobacterium (sub)species revealed the genes predicted to be required for the degradation and internalization of a wide range of carbohydrates, outnumbering those found in many other gut microbiota members. The glycan-degrading abilities of bifidobacteria are believed to reflect available carbon sources in the mammalian gut. Furthermore, transcriptome profiling of bifidobacterial genomes supported the involvement of various chromosomal loci in glycan metabolism. The widespread occurrence of bifidobacterial saccharolytic features is in line with metagenomic and metatranscriptomic datasets obtained from human adult/infant faecal samples, thereby supporting the notion that bifidobacteria expand the human glycobiome. This study also underscores the hypothesis of saccharidic resource sharing among bifidobacteria through species-specific metabolic specialization and cross feeding, thereby forging trophic relationships between members of the gut microbiota.
Predicted glycobiome of the Bifidobacterium genus and some additional members of the Bifidobacteriaceae family.: GH families and carbohydrate-utilization pathways profiles, based on CAZy database and Pathway-tools software, respectively, were used to construct a hierarchical clustering of all tested species of the Bifidobacteriumgenus and additional members of the Bifidobacteriaceae family. This clustering highlights the presence of three distinct clusters named GHP/A, GHP/B and GHP/C that display a different repertoire of GHs as well as a different repertoire of plant carbohydrate degradation pathways. GH arsenal prediction for every analyzed Bifidobacteriaceae species is represented by a bar plot. The presence of pathways for degradation of simple or complex carbohydrates is represented by the red color in the heat map and the GH index (the number of GHs predicted in each genome normalized by genome size expressed as Mbp) is illustrated as an orange bar plot. Pathways denominations are indicated as follows: 1 Bifidobacteriumshunt, 2 galactose degradation I (Leloir pathway), 3 melibiose degradation, 4 ribose degradation, 5 lactose degradation III, 6 glycogen degradation I, 7 glycogen degradation II, 8 sucrose degradation IV, 9 L-arabinose degradation I, 10 xylose degradation I, 11 D-mannose degradation, 12 (1,4)-ß-xylan degradation, 13 starch degradation V, 14 chitin degradation (chitinase), 15 trehalose degradation IV, 16 Pectin (homogalacturonan) degradation, 17 2'-deoxy-a-D-ribose 1-phosphate degradation, 18 trehalose degradation I (low osmolarity), 19 L-rhamnose degradation II.
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SCIENTIFIC RepoRts | 5:15782 | DOI: 10.1038/srep15782
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Bidobacteria exhibit social
behavior through carbohydrate
resource sharing in the gut
Christian Milani
1
, Gabriele Andrea Lugli
1
, Sabrina Duranti
1
, Francesca Turroni
2
,
Leonardo Mancabelli
1
, Chiara Ferrario
1
, Marta Mangifesta
1
, Arancha Hevia
3
,
Alice Viappiani
1
, Matthias Scholz
4
, Stefania Arioli
1
, Borja Sanchez
3,†
, Jonathan Lane
5
,
Doyle V. Ward
6
, Rita Hickey
5
, Diego Mora
7
, Nicola Segata
4
, Abelardo Margolles
3
,
Douwe van Sinderen
2
& Marco Ventura
1
Bidobacteria are common and frequently dominant members of the gut microbiota of many
animals, including mammals and insects. Carbohydrates are considered key carbon sources for the
gut microbiota, imposing strong selective pressure on the complex microbial consortium of the gut.
Despite its importance, the genetic traits that facilitate carbohydrate utilization by gut microbiota
members are still poorly characterized. Here, genome analyses of 47 representative Bidobacterium
(sub)species revealed the genes predicted to be required for the degradation and internalization of
a wide range of carbohydrates, outnumbering those found in many other gut microbiota members.
The glycan-degrading abilities of bidobacteria are believed to reect available carbon sources in
the mammalian gut. Furthermore, transcriptome proling of bidobacterial genomes supported
the involvement of various chromosomal loci in glycan metabolism. The widespread occurrence of
bidobacterial saccharolytic features is in line with metagenomic and metatranscriptomic datasets
obtained from human adult/infant faecal samples, thereby supporting the notion that bidobacteria
expand the human glycobiome. This study also underscores the hypothesis of saccharidic resource
sharing among bidobacteria through species-specic metabolic specialization and cross feeding,
thereby forging trophic relationships between members of the gut microbiota.
Bidobacteria are Gram positive bacteria with high GC-content genomes that typically reside in the
gastro intestinal (GIT) tract of various animal species, including warm blooded mammals and social
insects
1,2
. Noteworthy, bidobacteria reach a very high relative abundance as part of the infant gut micro-
biota
3-5
, and this early life prevalence supports their purported role as modulators of various metabolic
and immune activities of their host
1
. Non-digestible carbohydrates derived from the diet, together with
host-produced glycans found in the mammalian gut represent critical energy sources believed to be
responsible for the survival and proliferation of many microbial components of the gut microbiota,
including bidobacteria
6
. It is therefore important to know what molecular strategies are employed
by members of the gut microbiota to harvest and metabolize complex glycans in order to understand
how they underpin their ecological tness in, and adaptation to, the GIT environment. Furthermore,
1
Laboratory of Probiogenomics, Department of Life Sciences, University of Parma, Italy.
2
APC Microbiome Institute
and School of Microbiology, Bioscience Institute, National University of Ireland, Cork, Ireland.
3
Departamento de
Microbiologia y Bioquimica de Productos Lacteos, IPLA – CSIC, Villaviciosa, Asturias, Spain.
4
Centre for Integrative
Biology, University of Trento, Trento, Italy.
5
Teagasc Food Research Centre, Moorepark, Cork, Ireland.
6
Broad
Institute, 415 Main St., Cambridge, USA.
7
Department of Food Environmental and Nutritional Sciences, University
of Milan, Italy.
Present address: Department of Analytical Chemistry and Food Science, Faculty of Food Science
and Technology, University of Vigo, Spain. Correspondence and requests for materials should be addressed to M.V.
(email: marco.ventura@unipr.it)
Received: 27 May 2015
Accepted: 02 October 2015
Published: 28 October 2015
OPEN
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SCIENTIFIC RepoRts | 5:15782 | DOI: 10.1038/srep15782
carbohydrate metabolism in the mammalian gut may occur in a concerted manner by various members
of the microbiota, including bidobacteria
7
. us, carbohydrates are presumed to be partly responsible
for microbiota dynamics in this changeable environment. Genomics has been crucial in revealing the
complex interactions and molecular dialogue between a host and its resident (bido)bacteria, and in
unraveling bidobacterial gut colonization strategies
8
. Recently, all 47 currently recognized bidobacte-
rial sub/species have been genomically decoded
9,10
, thus providing the necessary genetic background for
this group of bacteria. Here, we describe an analysis of the genomes and transcriptomes of representa-
tives of all 47 (sub)species that are currently assigned to the Bidobacterium genus, predicting bidobac-
terial genome-based strategies for carbohydrate metabolism that impact on the overall glycobiome of the
gut microbiota and host, while also being pivotal for the establishment of trophic relationships between
members of gut microbiota.
Results and Discussion
Genomes of the Bidobacterium genus and carbohydrate metabolism. Genome sequences
from the type strain of each of the 47 Bidobacterium (sub)species (Table S1) were used to assess the
contribution of carbohydrate metabolism to the corresponding pan-genome, core genome and vari-
ome, determined as described previously
9
. In total, 18,181 and 551 BifCOGs (Bidobacterium-specic
Clusters of Orthologous Genes) represent the pan-genome (pan BifCOGs) and the core of bidobacte-
rial genomic coding sequences (core BifCOGs) of the Bidobacterium genus, respectively. Functional
annotation of the core BifCOGs, based on a recently updated EggNog database
11
, indicates, as expected,
that a large part of the conserved core genes encode housekeeping functions and functions involved in
the adaptation to/interaction with a particular environment, including carbohydrate metabolism (Fig.
S1). Interestingly, about 5.5% of the core BifCOGs is associated with carbohydrate metabolism (Fig. S1),
whereas the carbohydrate metabolism functional family is the most represented COG family of the pan
BifCOGs (13.7%) (Fig. S1). is nding suggests a strong selective pressure towards the acquisition and
retention of accessory genes for carbohydrate utilization by bidobacteria in order to be competitive in
a particular ecological niche. e commitment of bidobacteria towards the utilization of a wide array
of simple and complex carbohydrates is further underlined by EggNog proling of adult humans faecal
metagenomes sequenced as part of the Human Microbiome Project (HMP). Results showed that the
average abundance of the carbohydrate metabolism functional family in HMP metagenomic datasets is
8.0%, thus being 58% lower than the abundance detected in the bidobacterial pan-genome, i.e. 13.7%
(Fig. S1). Notably, the carbohydrate metabolism functional family is the most abundantly represented
COG family within the Bidobacterium pan-genome (Fig. S1). e pan-genome analysis also allowed the
identication of the Truly Unique Genes (TUG), consisting of genes present in just one of the examined
bidobacterial genomes (Fig. S1). Interestingly, no functional annotation can be made for the majority
of TUGs (54.1%) (Fig. S1). However, 13.2% of the identied TUG can be attributed to a COG fam-
ily representing proteins involved in carbohydrate metabolism, including glycosyl hydrolases (GH) and
carriers for carbohydrate uptake. is data supports the notion that carbohydrate metabolism supports
adaptation and specialisation processes, and consequently speciation within the Bidobacterium genus.
Carbohydrate-active enzymes encoded by the genus Bidobacterium. Considering the impor-
tance of carbohydrate metabolism and energy conversion systems in gut inhabitants such as bidobacte-
ria, we decided to investigate the presence of genes predicted to encode GHs, polysaccharide lyases (PLs),
carbohydrate esterases (CE), glycosyl transferases (GT) and carbohydrate binding modules (CBM), and
other carbohydrate metabolic pathway components using the predicted core- and pan-genome of the
Bidobacterium genus. Genomic data showed that B. scardovii and B. biavatii have a signicantly larger
set of genes involved in carbohydrate metabolism, also termed glycobiome
12
, as compared to other
bidobacterial species (Fig.1). Normalization of GH counts against genome size (Mbp), generating a GH
index, provided an insight into the relative extent of adaptive events related to carbohydrate metabolism
found in individual bidobacterial species. Notably, four species (B. scardovii, B. biavatii, Bidobacterium
saeculare and Bidobacterium dentium) possess a GH index that is approximately 50% higher than the
bidobacterial average (Fig. 1). Classication according to the Carbohydrate Active Enzymes (CAZy)
system
13
revealed that the pan-genome of the analysed Bidobacterium representatives includes 3,385
genes encoding predicted carbohydrate-active enzymes, including members of 57 GH, 13 GT and seven
CE families (Fig.1, Fig. S2 and Fig. S3), while no putative Polysaccharide Lyases (PL)-encoding genes
were detected. Genes encoding members of CAZy family GH13 are most commonly found in bidobac-
terial genomes, especially for those bidobacteria isolated from the mammalian gut (24.2% of the total
predicted bidobacterial GH repertoire, Fig.1). Enzymes belonging to this family are widespread in bac-
teria and are characterized by their degradative abilities towards a wide range of carbohydrates, including
plant-derived polysaccharides, such as starch and related substrates (amylose and amylopectin and/or
(cyclo)maltodextrins), and trehalose. Furthermore, stachyose, ranose and melibiose may also represent
a target for members of the GH13 family
14
and their complete breakdown is achieved with the involve-
ment of GH36 enzymes, which were shown to be abundant in the analysed bidobacterial genomes
(Figure S2). Such carbon sources indeed represent very common glycans found in the adult mammalian
(omnivore and herbivore) diet
6
. We also observed distinct dierences between predicted glycobiomes
of Bidobacterium species with regards to their (predicted) ability to degrade plant polysaccharides as
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SCIENTIFIC RepoRts | 5:15782 | DOI: 10.1038/srep15782
opposed to host-derived glycans, such as N- or O-linked glycoproteins, human milk oligosaccharides
(HMOs) and glycosaminoglycans
1
. e bidobacterial glycobiome was shown to contain members of
GH families that are known to be involved in host-glycan degradation, such as GH33, encompassing
exo-sialidases, GH29 and GH95, which represent fucosidases, GH20, which include hexosaminidase
and lacto-N-biosidase activities, GH112, representing lacto-N-biosidases, GH38 and GH125, involv-
ing α -mannosidases as well as GH101 and GH129, which include α -N-acetylgalactosaminidases.
Interestingly, members of the B. scardovii, B. longum subsp. infantis and Bidobacterium bidum species
possess the most extensive set of such host-glycan-degrading GH families (Fig. 1). Such glycobiome
specialization probably reects species-specic adaptation to a particular ecological niche and illustrates
strict co-evolution with their mammalian host. Clustering of bidobacterial species based on their pre-
dicted GH and carbohydrate-degradation pathway repertoire (Fig.1) allows the identication of a cluster,
designated as GHP/A, representing species with a considerable array of predicted GH43 family enzymes
involved in degradation of complex plant polysaccharides, such as (arabino)xylan, which plays an impor-
tant structural role as a main constituent of the plant cell wall
15
, and as such represents a substantial
component of plant cell wall-derived dietary ber
16
. is nding suggests that bidobacteria rich in
GH43 member-specifyings genes are adapted to hosts with a vegetarian or omnivore diet. A subgroup
of the cluster GHP/A, named GHP/A1, appears to possess a wider array of GHs (Fig.1). is subgroup
encodes a large number of GH3 family enzymes that are predicted to be involved in the degradation
of an extensive range of plant-derived polysaccharides (e.g., cellodextrin, (arabino)xylan and (arabino)
galactan), as well as involved in bacterial cell wall biosynthesis and turnover. Notably, bidobacterial
species isolated from honey/bumblebees specify a peculiar GHP/C cluster, whose members possess a
Figure 1. Predicted glycobiome of the Bidobacterium genus and some additional members of the
Bidobacteriaceae family. GH families and carbohydrate-utilization pathways proles, based on CAZy
database and Pathway-tools soware, respectively, were used to construct a hierarchical clustering of all
tested species of the Bidobacterium genus and additional members of the Bidobacteriaceae family. is
clustering highlights the presence of three distinct clusters named GHP/A, GHP/B and GHP/C that display a
dierent repertoire of GHs as well as a dierent repertoire of plant carbohydrate degradation pathways. GH
arsenal prediction for every analyzed Bidobacteriaceae species is represented by a bar plot. e presence of
pathways for degradation of simple or complex carbohydrates is represented by the red color in the heat map
and the GH index (the number of GHs predicted in each genome normalized by genome size expressed as
Mbp) is illustrated as an orange bar plot. Pathways denominations are indicated as follows: 1 Bidobacterium
shunt, 2 galactose degradation I (Leloir pathway), 3 melibiose degradation, 4 ribose degradation, 5 lactose
degradation III, 6 glycogen degradation I, 7 glycogen degradation II, 8 sucrose degradation IV, 9 L-arabinose
degradation I, 10 xylose degradation I, 11 D-mannose degradation, 12 (1,4)-ß-xylan degradation, 13 starch
degradation V, 14 chitin degradation (chitinase), 15 trehalose degradation IV, 16 Pectin (homogalacturonan)
degradation, 17 2'-deoxy-α-D-ribose 1-phosphate degradation, 18 trehalose degradation I (low osmolarity),
19 L-rhamnose degradation II.
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SCIENTIFIC RepoRts | 5:15782 | DOI: 10.1038/srep15782
discrete set of GH43 and GH3 enzymes, but in addition these particular bidobacterial genomes are
predicted to encode a very limited repertoire of GH13 representatives, in contrast to all other bidobac-
teria. is is in accordance with the absence or paucity of carbohydrates with α -glucosidic linkages in the
honey/bumblebee diet
17
. e remaining bidobacterial species, not tting in clusters GHP/A or GHP/C,
are included in cluster GHP/B, which is characterized by an under-representation of GH43 and GH3.
In order to further evaluate the importance of the bidobacterial contribution to degradation of
complex carbohydrates found in the human gut, we compared the bidobacterial GH repertoire with all
the so far sequenced members of the human gut microbiome
18,19
. For this purpose, we used GH data of
2,674 genomes available in the CAZy database
13
with the addition of data obtained from the bidobac-
terial genomes analysed in this study. Interestingly, the Bidobacterium genus was shown to specify one
of the largest arsenal of GH13, GH43, GH3 and GH51 family members (2.0 fold-, 2.6 fold-, 5.8 fold-,
7.0 fold-, respectively, more with respect to the average GH arsenal of the gut microbiome), along with
Bacteroides spp. (Bacteroidales family) and Clostridiales family. Furthermore, abundance of these GH
families has been shown by a small number of other members of the gut microbiota such as Paenibacillus
spp. (Bacillales family) and Streptomyces spp. (Actinomycetales family) (Fig.2). ese ndings corroborate
the very substantial contribution to glycan-breakdown potential by bidobacteria in the mammalian gut.
Secreted glycosyl hydrolases of bidobacteria. In order to allow GH enzymes produced by dif-
ferent organisms to act in concert and to access glycans with a degree of polymerization exceeding that
of the corresponding uptake system, certain GH enzymes are expected to be located on the cell surface
or secreted into the environment. Notably, even though the majority of the identied GH enzymes from
the bidobacterial pan-genome is predicted to be intracellular, 10.9% of the deduced bidobacterial
GH pool is predicted to be extracellular, of which 32.9% are members of the GH13 family and anno-
tated as pullulanases and α -amylases, 24% are members of the GH43 family and predicted to act as
β -xylosidases and α -L-arabinofuranosidases, while 12% are members of the GH51 family and classied
as α -L-arabinofuranosidases. ese data suggest that bidobacteria secrete a relevant pool of GH for the
degradation of plant polysaccharides, which would accordingly represent an important resource for the
host in the context of obtaining access to dietary bres. e secreted bidobacterial pan-genome also
encompasses GHs involved in host-glycan degradation (see above), being classied as families GH29,
GH33, GH95 and GH101, and constituting 0.4%, 3.5%, 0.8% and 2.7% of this secreted pan-genome,
respectively. Predicted extracellular GHs were identied in 43 species of the genus Bidobacterium, with
a particularly high prevalence in B. biavatii (endowed with 17 secreted GHs, including 4 GH43 and 4
Figure 2. Comparative analysis of bidobacterial GHs against other gut bacteria. e central heat map
shows GH prediction data of 2721 sequenced bacterial strains belonging to bacterial orders residing in the
human gut, identied by dierent color codes as explained in the underlying table. e four heat map rows,
situated above the main heat map, represent an enlarged view of the GH51, GH3, GH43 and GH13 content.
Data regarding Bidobacteriales are highlighted in blue. Data regarding Clostridiales and Bacteroidales are
highlighted in green.
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SCIENTIFIC RepoRts | 5:15782 | DOI: 10.1038/srep15782
GH13 members), B. scardovii (endowed with 11 secreted GHs, including 3 GH43 and 3 GH51, annotated
as α -L-arabinofuranosidases) and B. bidum (endowed with 11 secreted GHs, including two GH84 and
two GH33 members, predicted to act as N-acetyl β -glucosaminidases and sialidases, respectively). e
remaining bidobacterial genomes are predicted to encode seven or less secreted GHs. e two secreted
N-acetyl β -glucosaminidases and the two secreted sialidases found in B. bidum are crucial for the uti-
lization of HMOs and intestinal glycoconjugates such as mucin, thus further supporting the notion that
this microorganism is highly adaptated to colonize and persist in the mammalian gut
20,21
. Nevertheless,
B. bidum is unable to use sialic acid as its sole carbon source and the activity of sialidases appears to be
important only to allow access to other carbohydrates associated to sialylated host-encoded glycans
20,21
.
Furthermore, the released sialic acid can be utilized by other bidobacteria, such as B. breve, resulting in
cross-feeding between bidobacterial species that share the same ecological niche
20,21
.
Saccharolytic pathways of bidobacteria. Predictions of complete pathways for the degradation of
simple (di/trisaccharides) and complex sugars through Pathway Tools soware
22
showed that B. biavatii
species the largest number of such pathways (14 complete pathways) (Fig.1), while the predicted rep-
ertoire for carbohydrate degradation of B. bombi, Bidobacterium crudilactis, B. longum subsp. infantis,
B. minimum and Bidobacterium ruminantium is limited to just nine pathways (Fig.1). Notably, when
assessing presence/absence data of pathways involved in the breakdown of simple and complex car-
bohydrates shown in the GHP clustering prole (Fig. 1), bidobacterial species isolated from honey/
bumblebees, constituting cluster GHP/C (Fig.1), lack genes encoding glycogen degradation I and gly-
cogen degradation II pathways. Based on recent discoveries, glycogen metabolic pathways are present
in bacterial species able to face diverse environments and showing a exible lifestyle
23
. More recently, it
was reported that the ability of Lactobacillus acidophilus to synthesize and store energy in the form of
glycogen, either prior to or during its transit through the host, potentially confers a competitive advan-
tage in the GI tract
24
. is is supported by the fact that glycogen storage is ubiquitous among enteric
bacteria, possibly due to the necessity to support rapid growth in the intestinal environment where
there is intense trophic competition
25
. On the other hand, it was hypothesized
26
that the loss of glycogen
pathways is a strong indication of genome degradation associated with parasitic or symbiotic behaviour
of bacteria. ough the original study of Henrissat et al. was based on the analysis and comparison
of just 55 fully sequenced bacterial genomes, their ndings have more recently been substantiated by
others involving 1202 bacterial proteomes
23
. Among Bidobacteriaceae, it is noteworthy that B. actinoco-
loniiforme, B. asteroides, B. bohemicum, B. bombi, B. coryneforme and B. indicum, species isolated from
insects and constituting the GHP/C cluster, show a smaller genome size compared to all other bido-
bacterial species isolated from mammals. We therefore speculate that Bidobacterium members linked to
insects have enjoyed a longer adaptation history to their hosts, in evolutionary terms, because mammals
appeared on earth in the late Paleocene (between 65 and 23 mya), whereas insects in the Devonian period
(between 459 and 359 mya) or even before according to a recent phylogenomics study
27
. is hypothesis
is conrmed by comparison of the phylogenetic supertree of all known bidobacterial species and that
obtained for their corresponding hosts, revealing a co-evolution host-microbe prole (Fig. S4).
e genomes of B. asteroides, B. actinocoloniiforme, B. indicum, B. coryneforme, B. bombi and B.
bohemicum possess a complete trehalose degradation IV pathway, which is absent in the majority of the
other bidobacteria and in all other examined members of the family Bidobacteriaceae. e acquisition
of this pathway, which is apparently specic for bidobacterial species isolated from the insect gut, may
be related to the fact that trehalose is used as carbohydrate storage and blood-sugar by many insects
including bees
28
. Remarkably, a large majority of bidobacterial genomes included in cluster GHP/B do
not encompass pathways for L-arabinose and/or xylose metabolism (Fig.1). ese genomes encode rela-
tively few GH43 enzymes compared to the GHP/A and GHP/C clusters, thus conrming a strict genetic
adaptation to ecological niches where these plant carbohydrates are not available. e ecological origin
of most of the GHP/B members that do not possess L-arabinose and/or xylose degradation pathways is
either raw/fermented milk or faecal material/gastrointestinal tract of suckling animals (Table S1), where
a milk-based diet represents the main nutrient retrieval opportunity. In this context, B. breve, B. bidum
and B. longum subsp. infantis have been isolated from infants, B. thermacidophilum subsp. porcinum
and B. choerinum from piglet, B. crudilactis from raw bovine milk and B. mongoliense from fermented
mares milk (Table S1), thus suggesting that these species have evolved to focus solely or predominantly
on the degradation of carbon sources present in milk and have lost or did not acquire the ability to use
(certain) plant polysaccharides. Fermented milk is a strict anthropogenic environment and these bacteria
are unlikely to have evolved in fermented milk per se. In fact, the natural ecological environment of these
species is still expected to be the gut from various (suckling) animals. In this environment such bidobac-
terial taxa have enjoyed the presence of a rich reservoir of milk-based carbohydrates (oligosaccharides/
lactose), which thus caused their genomes to acquire a genetic arsenal that allowed them to access these
carbon sources. In contrast, B. ruminantium and B. boum taxa have been isolated from the bovine rumen
(Table S1), an environment rich in plant polysaccharides, although they lack GH43-encoding genes and
consequently cluster in GHP/B. Other rumen-derived bidobacteria do encode GH43 enzymes, perhaps
indicating that certain bidobacteria rely on cross-feeding, which is in line with bidobacteria being a
minor component of the rumen microbiota, although their functional role is largely unknown. B. breve
deserves a special mention as this species seems to have adopted a non-specialist strategy of acquiring
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SCIENTIFIC RepoRts | 5:15782 | DOI: 10.1038/srep15782
constituent elements of both plant- and host-derived carbohydrates (consistent with its isolation from
both infants and adults), yet is lacking the ability to directly access (many) HMOs, or mucin, nor possess-
ing the ability to metabolize xylose/arabinose-containing carbohydrates, though it can metabolize a wide
range of α /β -glucose- and α /β -galactose-containing sugars
14,20
. us, it may, perhaps co-operatively, rely
on other (bido)bacterial species like B. bidum or B. longum subsp. infantis in order to sustain growth
on the above mentioned complex sugars
29
.
Carbohydrate utilization patterns of Bidobacterium. Fermentation proles of the 47 sequenced
Bidobacterium strains revealed that all strains are able to ferment a common set of sugars, which include
glucose, sucrose and ranose (Fig. S5, panel a). In contrast, fermentation capabilities for other sugars,
such as lactose, galactose, maltose, melibiose, fructose, lactulose, maltodextrins, turanose, β -gentibiose
and xylose, were shown to be variable for the majority of the strains tested (Fig. S5, panel a). Notably,
we identied bidobacterial taxa such as B. cuniculi displaying an ability to grow on a wide range of
simple and complex carbohydrates (Fig. S5, panel a), thus suggesting metabolic expansion of its car-
bohydrate acquisition abilities perhaps to enhance competitiveness in one or more ecological niches.
In contrast, other bidobacterial species, such as Bidobacterium animalis subsp. animalis, only utilize
a relatively small number of the carbohydrates assayed here (Fig. S5, panel a), an observation which,
together with the very limited number of predicted GHs/carbohydrate pathways encoded by this taxon
(Fig. 1), underlines a rather high level of genetic adaptation to an ecological niche. Growth studies
highlighted the existence of dierent carbon sources that are dierentially utilized by bidobacteria,
in a manner consistent with our predictions. In this context growth experiments involving most mem-
bers of the B. asteroides phylogenetic group showed that they do not exhibit any appreciable growth
on glycogen, an observation which is consistent with in silico pathway predictions. Cultivation trials
performed on plant-derived carbohydrates such as arabinose or xylose revealed that these sugars are
utilized by a majority of the bidobacteria tested except for those taxa that form the GHP/B cluster
(Fig.1), which are not predicted to encode enzymes of the L-arabinose degradation I and xylose deg-
radation I pathways. e ubiquitous monosaccharide mannose that is found in both plant and ani-
mal glycans, is easily shunted into the glycolytic pathway via isomerization of mannose-6-phosphate to
fructose-6-phosphate
30
. Growth on mannose is, however, not a wide-spread property among the tested
bidobacterial taxa, a nding that is consistent with genomic data (Fig. 1), which revealed a variable
distribution of genes supporting bidobacterial mannose utilization such as genes encoding predicted
mannosidases and mannose-6-phosphate isomerases. Interestingly, when mannosidase-encoding genes
were detected, they were in the large majority of cases shown to be located within a putative N-glycan
(host-derived) degradation cluster. Lactose constitutes a typical glycan that specically occurs in the
mammalian diet, though normally limited to the early stages of life
31
. In silico analyses involving the
genomes of 47 bidobacterial taxa revealed a ubiquitous distribution in their chromosomes of genes
encoding β -galactosidases. is nding suggests a rather wide-spread utilization of lactose as well as
other galactose-containing glycans such as galactan, galacto-oligosaccharides, Human milk oligosaccha-
rides (HMO) and mucin, which require particular β -galactosidases for their degradation, among mem-
bers of the Bidobacterium genus
20,32
. Growth experiments involving lactose showed that, except for B.
ruminantium and B. thermacidophilum subsp. thermacidophilum, all other tested bidobacteria are able
to ferment this disaccharide. In contrast, in silico analyses suggested that L-rhamnose is rarely used by
bidobacteria due to the apparent lack of genes encoding L-rhamno-gamma-lactonase, L-rhamnoate
dehydratase and 2-keto-3-deoxy-L-rhamnoate aldolase. Notably, fermentation proles involving this car-
bon source conrmed that only B. biavatii is able to ferment L-rhamnose. Furthermore, we evaluated
the abilities of members of the genus Bidobacterium to utilize typical host glycans like mucin and
HMO. Interestingly, in addition to the currently known bidobacterial archetypes that can utilize these
host-glycans (B. bidum and B. longum subsp. infantis)
20,33
, we identied that B. biavatii, B. crudilac-
tis, B. kashiwanohense, Bidobacterium stellenboschense and Bidobacterium mongoliense are all capable
of HMO metabolism. Inspection of their genome sequences revealed the presence of genes predicted
to encode sialidases, fucosidases, N-acetyl-β -hexosaminidases, endo-α -N-acetylgalactosaminidase and
β -galactosidases, which have previously been shown to be crucial for the breakdown of these complex
carbohydrates
20,33
. is further illustrates the broad catabolic abilities of bidobacteria in general and in
particular their specialization to utilize complex carbohydrates that are commonly found in the (infant)
mammalian GIT.
In order to substantiate the notion that bidobacterial genomes contain specic genes responsible
for the utilization of key carbohydrates that are present in their ecological niches and correspond to
their saccharolytic phenotype, we investigated the transcriptome for a representative bidobacterial spe-
cies for each of the seven bidobacterial phylogenetic clusters described previously
10
grown on (where
possible) glucose, glycogen, lactose, xylose, rhamnose, mannose, trehalose or HMO as the sole carbon
source (Fig. S5, panel b). RNAseq experiments allowed the identication of the transcriptomes for each
bidobacterial strain tested in cases where growth was obtained, revealing that the carbohydrate metab-
olism COG family [COG category (G)], is one of the most represented in the transcriptomes (Fig. S5,
panel c). Manual inspection of the identied transcriptomes highlighted the existence of a large arsenal
of genes encoding GHs and other enzymes that constitute parts of carbohydrate metabolic pathways,
including suspected carbohydrate carrier systems that are expressed when bidobacteria are cultivated
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on a carbohydrate (Fig. S6). In this context, we identied β -galactosidases of the GH2 and GH42 families
that were shown to be expressed when bidobacteria are grown on lactose, as well as MFS and ABC
systems predicted to act as carriers for lactose and/or glucose and/or galactose (Fig. S6). Cultivation of
bidobacteria on mannose, rhamnose, trehalose or xylose resulted, in cases where growth was observed,
in the transcription of genes encoding specic catabolic pathways such as D-mannose degradation,
L-rhamnose degradation II, trehalose degradation I and xylose degradation I (Fig. S6), observations that
are consistent with our in silico assignments. e transcriptomes of bidobacteria grown on glycogen
clearly showed that transcription of genes encompassing the glycogen degradation I pathway, predicted
to be indispensable for glycogen to glucose breakdown, is switched on under these circumstances (Fig.
S6). e only exceptions are represented by the transcriptomes of Bidobacterium pseudocatenulatum
and B. stellenboschense in which the genes predicted to specify amylomaltase and glucokinase enzymes
are not expressed, suggesting the existence of an alternative pathway for conversion of the intermedi-
ate carbohydrate maltose into β -D-glucose-6-phosphate. Transcriptomic data recovered from growth
of B. biavatii on the complex substrate HMO revealed up-regulation of a sizable number of dierent
GH-encoding genes, such as those predicted to belong to GH1 (predicted β -D-fucosidases), GH2 (puta-
tive β -galactosidases), GH3 (putative β -N-acetylhexosaminidases), GH29 (α -L-fucosidases), GH30 (pos-
sible β -fucosidases), GH36 (likely α -N-acetylgalactosaminidases), GH42 (putative β -galactosidases),
GH85 (endo-β -N-acetylglucosaminidases) and GH112 (predicted galacto-N-biose/lacto-N-biose phos-
phorylases) (Fig. S6). Other up-regulated GH-coding genes included those specifying members of GH13,
GH32 and GH43 families, even though their predicted enzymatic activities do not appear to be directed
against HMO.
Mutualistic/commensal breakdown activities of bidobacteria on carbohydrates. In gut
ecosystems, bacteria can exploit mutualistic as well as commensal and competitive activities during
metabolism of various carbon sources available in such an environment. us, we were interested to
evaluate possible trophic relationships towards carbohydrates between bidobacterial taxa found in
various ecological niches. Specic bi-association of bidobacterial taxa were selected based on their
common ecological origin (e.g., human-, porcine-, or rabbit-gut). eir growth performances on car-
bon sources that are commonly available in their particular ecological niche were assayed during
co-cultivation (bi-association) and compared to those achieved when the strains were grown separately
(mono-association). Such trials suggested that when cultivated together these bidobacterial taxa were
taking an evident benet as supported by the enhanced cell densities in the bi-associations compared to
the mono-associations (Fig.3). ese growth-benets were in a few cases evident for both strains such
as in the case of the B. magnum and B. cuniculi combination when these strains were cultivated on xylan
or on starch (Fig.3). Such ndings were further supported by the evaluation of transcriptomic changes,
employing an RNAseq approach, observed for these bidobacterial strains when cultivated together
as compared to the situation where these strains were assayed separately. Notably, in bi-associations
where a benet was noticed in terms of cell numbers for both strains, such as for B. magnum and B.
cuniculi cultivated on starch, complementarity in terms of the transcription of the genetic repertoire
for the metabolism of this complex sugar was observed for these strains. In fact, under such conditions
the alpha-glucoside phosphorylase-specifying genes, i.e. BMAGN_0016 and BCUN_1467, as well as
amylase-encoding genes, i.e. BMAGN_0612 and BCUN_0313, of both B. magnum and B. cuniculi were
shown to be transcribed (Fig.3). Interestingly, while these latter enzymes are predicted to be intracellular,
two genes encoding putative extracellular pullulanases (BCUN_0354 and BCUN_0356), were shown to
be transcribed. Even though the detected transcription level for these genes was low, it may be that such
enzymes allowed a partial de-branching of starch so as to allow internalization of the released degrada-
tion products into the bacterial cell for complete degradation. e resulting starch-degradation products
such as maltose and alpha-glucosides are presumed to be internalized by means of ABC transporters
(BMAGN_0006-BMAGN_0009 and BCUN_2019-BCUN_2022) and/or PTS systems (BMAGN_0338
and BCUN_1552), of which the corresponding genes were shown to exhibit increased transcription
(2.37 fold and 10.42 fold with p < 0.001, respectively) relative to mono-association conditions (Fig.3).
us, on this substrate both strains appear to co-operate in order to achieve starch degradation thanks
to the collective action of their extracellular amylases, perhaps resulting in the production of a larger
amount of starch-derivatives compared to that achieved when the strains are cultivated separately on this
substrate. In contrast, when these strains were co-cultivated on xylan, we only noticed an up-regulation
of the gene encoding a beta-xylosidase (BCUN_1638) in B. cuniculi. Similarly, B. cuniculi exhibited a
modest transcriptional upregulation of the genes specifying the putative uptake and degradation machin-
ery for xylose (BCUN_0705-BCUN_0707 and BCUN_1645), whereas B. magnum showed no modula-
tion in the beta-xylosidase-encoding gene, yet down-regulation of genes involved in xylose transport.
e latter ndings suggest that B. magnum modulates gene expression in order to support growth of B.
cuniculi and allows this latter strain to participate in xylan degradation and harvesting of the deriving
xylose. Since none of these enzymes are predicted to be extracellular, an alternative explanation for this
behavior is partial degradation of xylan to xylo-oligosaccharides during media preparation. ese deg-
radation products can be the target for specic uptake transporters, allowing their complete breakdown
inside the bacterial cells. Another scenario was noticed for the co-cultivation of B. stellenboschense and
B. biavatii grown in the presence of glycogen, where only the latter strain seems to take advantage of
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the presence of the other strain (Fig. 3). In fact, under these circumstances B. biavatii substantially
enhanced transcription of various genes encoding enzymes predicted to be involved in the hydrolysis
of glycogen such as predicted glycosyl hydrolases of the GH13 and GH77 families, as well as a glycogen
phosphorylase (Fig. 3). In contrast, B. stellenboschense did not reveal any transcriptional modulation
of genes with predicted functions in glycogen utilization when the strains were co-cultivated (Fig. 3).
Similarly, data concerning co-cultivation of B. longum subsp. suis and B. thermacidophilum subsp. por-
cinum on starch is also consistent with a cross-feeding scenario. In fact, under these growth conditions,
qPCR assays revealed that cell numbers of B. longum subsp. suis are enhanced ( 2 fold) with respect to
those noticed when this strain was cultivated on its own on this substrate. Furthermore, transcriptome
analyses revealed a signicant induction ( 8 fold, p < 0.001) of genes encoding a complete ABC system
involved in the up-take of maltose, which is a starch-derived glycan, of B. longum subsp. suis when grown
with B. thermacidophilum subsp. porcinum in the presence of starch as the sole carbon source (Fig.3).
In contrast, even though the B. thermacidophilum subsp. porcinum genome is predicted to encode a
Figure 3. Evaluation of possible bidobacterial cross-feeding by a transcriptomics approach. (Panel a)
reports the abundance, observed through quantitative qRT-PCR, of eight bidobacterial species cultivated in
MRS supplemented with four dierent carbohydrates. ese species were either grown on their own (mono-
association) or in the presence of another bidobacterial strain (bi-associations) sharing the same ecological
niche. e ve case studies analysed are named progressively with letters from A to D, corresponding to: B.
cuniculi and B. magnum grown on starch (A), B. cuniculi and B. magnum grown on xylan (B), B. biavatii
and B. stellenboschense grown on glycogen (C) and B. thermacidophilum subsp. porcinum and B. longum
subsp. suis grown on starch (D). (Panel b) shows the transcriptional fold change of genes encoding enzymes
in the breakdown of glycans observed in the ve case studies, named progressively with letters from A to
D. Functional annotation of enzymes are indicated in orange while the functional annotation of transporter
encoding genes and the predicted glycan specicity is highlighted in green.
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secreted GH13 family enzyme (BPORC_0608), the transcription of genes predicted to be involved in
starch metabolism of B. thermacidophilum subsp. porcinum did not appear to be aected by the presence
of B. longum subsp. suis (Fig.3).
Overall, our ndings suggest that bidobacteria access carbohydrates that are commonly present in
their ecologic niches employing trophic interactions that may vary from commensalism to mutualistic.
Furthermore, these concerted breakdown activities may similarly exert positive eects on other members
of the gut microbiota and thus promote an expansion of the gut glycobiome.
Bidobacteria and mammalian gut adaptation. Bidobacteria have predominantly been iden-
tied in the GIT of mammals
1
. However, their functional contribution to the microbiota residing in
this body compartment has not been thoroughly investigated. We therefore looked for the presence of
GH-encoding bidobacterial DNA sequences among 44 out of 136 available gut metagenome data sets
Figure 4. Data mining for bidobacterial GH genes and bidobacterial pathways for carbohydrate
degradation in adult and infant fecal metagenome data sets and an infant fecal metatranscriptome
data set. Bar plots above the heatmaps show the relative abundance of bidobacteria in the analysed
samples. Heatmaps in the upper part depict the coverage obtained by alignment of adult and infant fecal
metagenomic data sets, or infant metatranscriptome data sets to predicted bidobacterial GH-encoding
genes. In order to compare results for datasets with dierent sizes, all coverage values were normalized
as obtained from a 10 million read dataset. Heatmaps in the lower part of the image represent the
coverage obtained by alignment of the same datasets to genes constituting the bidobacterial pathways
for carbohydrate degradation. Relevant GH genes and pathways involved in the metabolism of glycans are
highlighted in red. Pathways designations are identical to those indicated in Fig.1.
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from healthy adults, enrolled in the Human Microbiome Project
19
that had shown consistent presence
of bidobacteria based on MetaPhlAn proling
34
, as well as in nine metagenomes and related meta-
transcriptomes of healthy infant gut microbiota, sequenced by the Broad Institute (NCBI bioproject ID
63661). e coverage of each gene included in the bidobacterial pangenome was computed based on
the metagenomic reads with >98% full-length identity. As displayed in Fig. 4, the average abundance
of Bidobacterium genes ranged from 0.2% to 35.9%, with a distinctly higher prevalence of bidobac-
teria in the faecal metagenomes from infants. is is consistent with the catabolic potential for HMOs.
Interestingly, among the most frequently represented bidobacterial genes in the metagenomic data sets
from adult, the presence of an extensive repertoire of GH-encoding genes, such as those specifying
GH3, GH13, GH43, GH51 and GH77 (involved in the breakdown of complex plant carbohydrates), is
noteworthy (Fig.4). Such ndings reinforce the notion that despite the relative paucity of bidobacte-
ria detected in the adult human gut, their functional contribution to the human gut microbiome may
be important in terms of expanding the overall glycobiome of the large intestine, thereby aecting the
overall gut physiology. Furthermore, in the metagenome datasets from infants the relatively high bido-
bacterial abundance is also reected by the prevalence of bidobacterial GH-encoding genes, such as
those specifying members of the GH2, GH20, GH29, GH33, GH36, GH42, GH84, GH95, GH101 and
GH112 families, involved in the degradation of milk-related carbohydrates such as lactose and HMOs,
as well as in mucin degradation (Fig. 4). Notably, GH-specifying genes encoding β -hexosaminidases,
lacto-N-biosidases, galacto-N-biose/lacto-N-biose phosphorylases, α -L-fucosidases, sialidases, neurami-
nidases, N-acetyl β -glucosaminidases, hyaluronidases and endo-α -N-acetylgalactosaminidases are not
widespread in adult metagenomes (Fig.4). Availability of metatranscriptomes corresponding to the ana-
lysed infants’ metagenomes revealed pronounced transcription of the bidobacterial GH gene predicted
to be involved in milk, HMO and mucin degradation (Fig.4), clearly supporting the key functional roles
exploited by these GHs in the infant gut microbiota.
To further elucidate the functional contribution of bidobacteria to the human microbiota we screened
the metagenomic and metatranscriptomic datasets for the presence of genes encompassing carbohydrate
degradation pathways that had been predicted to be present in the bidobacterial pan-genome (Figs1
and 4). Both the adult and infant metagenomes showed a high abundance of genes for the Bidobacterium
phosphoketolase-dependent, or so-called bif shunt, pathway, as expected, as well as genes involved in
galactose degradation I, melibiose degradation, lactose degradation III, glycogen degradation I, glycogen
degradation II and sucrose degradation IV pathways (Fig.4), accompanied by presence of genes involved
in starch degradation V, arabinose degradation I, xylan degradation and xylose degradation I pathways.
e presence of such pathways illustrates their presumed importance for adaptation of bidobacteria to
the human gut environment. Interestingly, the infants metatranscriptomic datasets correspond to the
presence of the bif shunt (as expected) and pathways for galactose, lactose, glycogen and sucrose deg-
radation, while no or low transcriptional activity was detected that corresponded to catalytic pathways
for the plant polysaccharides arabinose, xylan and xylose (Fig.4), reecting the paucity of these carbo-
hydrates in an infants diet.
Conclusions
Bidobacteria may be considered as key representatives of the mammalian gut microbiota, especially
during the rst phase of their hosts life. However, very little is known about their genetic strategies
to colonize and persist within the gut, and to get access to the nutrients available in this environment.
e current study highlights the very extensive saccharolytic features displayed by members of the
Bidobacterium genus, revealing how these bacteria metabolize specic carbohydrates available in their
particular ecological niche. Comparison of the glycobiome identied in the genus Bidobacterium with
those identied in other members of the human gut microbiota revealed their unique and important
contribution in terms of GHs involved in the breakdown of complex plant carbohydrates such as arab-
inoxylan, galactan and starch. e impact of bidobacteria in the breakdown of dietary carbohydrates
is also crucial for the establishment and reinforcement of trophic relationships between members of the
gut microbiota. In fact, both mutualistic as well as commensal interactions in the mammalian gut can
be carbohydrate-driven
6,7
. Here, we have shown how a simple bidobacterial community may co-operate
between themselves as well as with other members of the gut microbiota in the utilization of specic
glycans, commonly available in the mammalian gut, by means of cross-feeding activities so as to provide
growth benets to one or both members of such a community as well as with the other members of
the gut microbiota. Such ndings support the concept of the existence of a social intelligence of bido-
bacterial communities in the harvesting and metabolism of glycans available in their ecological niches,
which regulate the dynamics of the gut microbiota relationships. However, it is reasonable to expect
that in much more complex microbial communities such as those identied in the mammalian gut,
cross-feeding activities as exemplied by bidobacteria also involve other members of the gut microbi-
ota, perhaps generating an even larger benecial eect. A survey of human gut metagenomic datasets,
representing both adult and infant samples, revealed that, notwithstanding their relatively low abundance
in adults, the functional contribution of bidobacteria to the enzymatic arsenal directed at degradation of
complex carbohydrates is relevant. In this context, the expansion of the GH repertoire dedicated to the
metabolism of infant dietary sugars, such as HMOs, as well as mucin is noteworthy. Another clear sign
of advanced bidobacterial adaptation to its mammalian host is represented by the identication in a
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small number of bidobacterial taxa which include B. bidum, B. longum subsp. infantis
20,33
, as well as B.
biavatii, B. crudilactis, B. kashiwanohense, B. stellenboschense and B. mongoliense, of metabolic repertoires
involved in the breakdown of host-derived glycans such as HMOs and mucin.
Materials and Methods
Bacterial strains, growth conditions. All Bidobacterium strains were cultivated in an anaer-
obic atmosphere (2.99% H
2
, 17.01% CO
2
and 80% N
2
) in a chamber (Concept 400, Ruskin) on De
Man-Rogosa-Sharp (MRS) broth (Scharlau Chemie, Barcelona, Spain) supplemented with 0.05% (w/v)
L-cysteine hydrochloride and incubated at 37 °C. Cell growth on semi synthetic MRS medium sup-
plemented with 1% (wt/vol) of a particular sugar was monitored by optical density at 600 nm using a
plate reader (Biotek, Vermont, USA). e plate reader was run in discontinuous mode, with absorbance
readings performed in 60 min intervals, and preceded by 30 sec shaking at medium speed. Cultures were
grown in biologically independent triplicates and the resulting growth data were expressed as the mean
of these replicates. Carbohydrates were purchased from Sigma (Milan, Italy) or Carbosynth (Berkshire,
UK). All the carbohydrates were dissolved in water and then sterilized by ltration using 0.2 micron l-
ter size and then added to autoclaved MRS with the exception of xylan (Poly(β -D-xylopyranose[1 4])
(Sigma, Aldrich) which was autoclaved with MRS.
In the case of HMO experiments, human milk samples were kindly provided by the Western rust
Human Milk Bank (Irvinestown, Co. Fermanagh, Ireland). e isolation of oligosaccharides from pooled
samples (n 3) was performed as described previously
35
. Briey, samples were defatted by centrifugation
at 4 °C (3850 × g, 20 min, Sorvall RC6 plus
®
). Caseins were precipitated at pH 4.6. Aer neutralization,
large peptides were removed by ultraltration (5 kDa molecular-weight cut-o, Millipore
®
Helicon S10
Spiral Cartridge). e permeates were freeze-dried and stored at 80 °C until further processing. To
remove lactose and residual peptides, the extracts were re-solubilized in MilliQ
®
water and applied to a
Sephadex G-25 column (Pharmacia, Uppsala, Sweden; 92 × 2.6 cm). Elution was performed with deion-
ized water (5 mL/min). Fractions were monitored for peptides according to Bradford
36
and the lactose
content was determined by HPAEC
35
. Fractions low in peptide- and lactose content were pooled and
used for further characterization.
Bidobacterial and hosts phylogenetic reconstruction. e phylogeny of the 47 was recon-
structed as described previously
9,10
. Phylogeny of the eukaryotic hosts was reconstructed through the
SUPERFAMILY web tool
37
.
Bidobacterial transcriptomics identication through RNAseq assays. B. biavatii, B. boum,
B. stellenboschense, B. coryneforme, B. cuniculi, B. gallinarum and B. pseudocatenulatum were selected
as representatives for each of the seven phylogenetic groups. ese strains were grown in MRS sup-
plemented with glucose, glycogen, lactose, xylose, rhamnose, mannose, trehalose or HMO as a carbon
source. In order to evaluate cross-feeding activities between two bidobacterial strains, bacteria were
co-cultivated on MRS supplemented with a particular glycan [RS2-resistant starch (Sigma, Aldrich),
xylan (Poly(β -D-xylopyranose[1 4]) (Sigma, Aldrich) or glycogen (Sigma, Aldrich)], and growth was
monitored by the evaluation of optical density at 600 nm followed by qRT-PCR using strain-specic
primers (see below).
When growth was observed during logarithmic phase, cell pellets were resuspended in 1 ml of
QUIAZOL (Quiagen, UK) and placed in a tube containing 0.8 g of glass beads (diameter, 106 μ m; Sigma).
e cells were lysed by shaking the mix on a BioSpec homogenizer at 4 °C for 2 min (maximum set-
ting). e mixture was then centrifuged at 12,000 rpm for 15 min, and the upper phase containing the
RNA-containing sample was recovered. e RNA sample was further puried by phenol extraction and
ethanol precipitation according to an established method
38
. Quality and integrity of the RNA was checked
by Agilent 2200 Tape Station Nucleic Acid System (Agilent Technologies, Palo Alto, Calif.). One hundred
ng of total RNA was used as the starting input for RNA-Seq library preparation. Briey, 100 ng of total
RNA was treated with Ribo-Zero rRNA removal kit for Gram-positive bacteria (Epicentre, Madison,
WI, U.S.A.) to remove rRNA according to the supplier’s instructions. e yield of rRNA depletion was
checked by Agilent 2200 Tape Station Nucleic Acid System (Agilent Technologies, Palo Alto, Calif.).
en, rRNA-depleted RNA samples were fragmented using RNaseIII (Life Technologies, USA) followed
by size evaluation using Experion (BioRad, UK). Whole transcriptome library was constructed using the
Ion Total-RNA Seq Kit v2 (Life Technologies, USA). Barcoded libraries were quantied by qRT-PCR
and each library template was amplied on Ion Sphere Particles using Ion One Touch 200 Template
Kit v2 (Life Technologies, USA). Samples were loaded into 316 Chips and sequenced on the PGM (Life
Technologies, USA). Sequencing reads were depleted of adapters, quality ltered (with overall quality,
quality window and length lters) with FastqMcf (https://code.google.com/p/ea-utils/) and aligned to the
respective bidobacterial reference genome through BWA
39
with high stringency cut-os (99% nucleotide
identity) in order to accurately map reads of co-cultivation datasets on the correct genome. Counts of
reads overlapping ORFs were performed using HTSeq (http://www-huber.embl.de/users/anders/HTSeq/
doc/overview.html) and analysis of the count data was performed using the R package DESeq2
40
. When
the RNAseq analyses of mono-associations, DESeq2 output consists of fold induction values determined
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SCIENTIFIC RepoRts | 5:15782 | DOI: 10.1038/srep15782
as the normalized number of transcripts identied for a given gene for bacterial cells cultivated on MRS
containing a specic carbohydrate, relative to the number of identied transcripts for that same gene
when the strain was grown on MRS containing glucose (reference condition). In case of RNAseq anal-
ysis of bi-associations, DESeq2 output consists of fold-induction values determined as the normalized
number of transcripts identied for a given gene for bacterial cells cultivated in mono-association relative
to the normalized number of identied transcripts for that same gene when the strain was cultivated in
bi-association, using MRS supplemented with the same carbohydrate for both conditions. DESeq2 data
normalization and dierential gene expression analysis are based on the negative binomial distribution,
which takes into consideration the overall transcript abundance identied for each analysed sample
40
.
Evaluation of the cell density by qPCR. e co-cultivation with other bacteria was monitored by
quantitative PCR (qPCR). e copy-number of a gene for a given strain used in the co-cultivation exper-
iments was evaluated and compared to the growth rate of each individually cultivated microorganism.
qPCR was performed using the CFX96 system (BioRad, CA, USA). Primers used in this study are listed
in Table S2. Each PCR reaction mix contained the following: 7.5 μ l 2× SYBR SuperMix Green (BioRad,
CA, USA), 5 μ l of DNA dilution, each of the forward and reverse primers at 0.5 μ M and nuclease-free
water was added to obtain a nal volume of 15 μ l. PCR products were detected with SYBR Green uo-
rescent dye and amplied according to the following protocol: one cycle of 95 °C for 3 minutes, followed
by 39 cycles of 95 °C for 5 s and 60 °C for 20 s. Melting curve: 65 °C to 95 °C with increments of 0.5 °C/s.
In each run, negative controls (no DNA) for each primer set were included. Standard curve was built
using the CFX96 soware (BioRad).
Bidobacterial gene survey of human gut metagenomic and metatranscriptomic datasets.
We surveyed the presence of bidobacterial genes into the microbial diversity of the healthy gut of
44 adults and nine infants. To this end we implemented a mapping-based pipeline to detect the pres-
ence and quantify the coverage of these gene categories annotated from the newly sequenced strains
into the Illumina deep shotgun-sequenced metagenomic data sets derived from stool samples of the
Human Microbiome Project (HMP)
19
and into Illumina deep shotgun-sequenced metagenomic and
metatranscriptomic data sets obtained from stool samples of nine healthy infants. e mapping was
performed using BowTie2
41
using multiple-hit mapping and “very-sensitive” policy. e mapping was
post-processed with a custom script to retain those matches with at least 98% full-length identity with
respect to at least one reference gene by threshold-ing the BowTie2 score at 12 for the 100 nt-long
adults and infant datasets (6 is the penalty for a high-quality mismatch). Genes covered by matching
reads for less than 90% of their full length were discarded and the nal gene-wise average coverage was
computed using SAMtools
42
and BEDtools
43
. In the nal matrices, GHs genes and genes constituting
carbohydrate-degrading pathways were collapsed into GH families and MetaCyc pathways. e estima-
tion of the relative abundance of bidobacteria (at the genus level) was performed with MetaPhlAn
34
.
Data Deposition. e RNAseq data were deposited in SRA database under the following study acces-
sion numbers: PRJNA239567 and PRJNA277297.
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Acknowledgements
We thank GenProbio srl for nancial support of the Laboratory of Probiogenomics. is work was
nancially supported by a FEMS Jensen Award to FT, and by a Ph.D. fellowship (Spinner 2013, Regione
Emilia Romagna) to S.D. DvS and FT are members of e APC Microbiome Institute, while DvS is also
a member of the Alimentary Glycoscience Research Cluster, both funded by Science Foundation Ireland
(SFI), through the Irish Government’s National Development Plan (Grant numbers SFI/12/RC/2273
and 08/SRC/B1393, respectively). is work was also partially supported by Fondazione Caritro, by
the EU FP7 (PCIG13- GA-2013-618833), and by MIUR “Futuro in Ricerca” E68C13000500001 to NS.
Furthermore, this project has been funded in part with funds from the National Institute of Allergy and
Infectious Diseases, National Institutes of Health, Department of Health and Human Services, under
Contract No. HHSN272200900018C.
Author Contributions
C.M. designed all of the experiments, performed bionformatics analyses as well as pathways predictions
and wrote the manuscript. G.A.L. and L.M. performed genomics and comparative genomics bioinformatic
analyses. N.S., D.V.W. and M.S. were involved in screening of metagenomics datasets. S.D., F.T., C.F.,
www.nature.com/scientificreports/
14
SCIENTIFIC RepoRts | 5:15782 | DOI: 10.1038/srep15782
M.M. and A.V. performed all the experiments involving RnaSeq sequencing while A.H., S.A., B.S., J.L.,
R.H. and D.M. were involved in growth of bidobacterial strains on dierent substrates. M.V., A.M. and
D.V.S. conceived the study, revised and approved the manuscript. All authors reviewed the manuscript.
Additional Information
Supplementary information accompanies this paper at http://www.nature.com/srep
Competing nancial interests: e authors declare no competing nancial interests.
How to cite this article: Milani, C. et al. Bidobacteria exhibit social behavior through carbohydrate
resource sharing in the gut. Sci. Rep. 5, 15782; doi: 10.1038/srep15782 (2015).
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images or other third party material in this article are included in the article’s Creative Com-
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Creative Commons license, users will need to obtain permission from the license holder to reproduce
the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/
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