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The ISME Journal (2016) 10, 2235–2245 © 2016 International Society for Microbial Ecology All rights reserved 1751-7362/16
www.nature.com/ismej

ORIGINAL ARTICLE

Ecological robustness of the gut microbiota in response to ingestion of transient food-borne microbes

Chenhong Zhang1, Muriel Derrien2, Florence Levenez1, Rémi Brazeilles2, Sonia A Ballal3, Jason Kim3, Marie-Christine Degivry2, Gaëlle Quéré2, Peggy Garault2, Johan ET van Hylckama Vlieg2,4, Wendy S Garrett3, Joël Doré1,5 and Patrick Veiga2,3,5
1Metagenopolis, Institut National de la Recherche Agronomique, Jouy-en-Josas, France; 2Life Science, Danone Nutricia Research, Palaiseau, France and 3Harvard T. H. Chan School of Public Health, Boston, MA, USA

Resident gut microbes co-exist with transient bacteria to form the gut microbiota. Despite increasing evidence suggesting a role for transient microbes on gut microbiota function, the interplay between resident and transient members of this microbial community is poorly defined. We aimed to determine the extent to which a host’s autochthonous gut microbiota influences niche permissivity to transient bacteria using a fermented milk product (FMP) as a vehicle for five food-borne bacterial strains. Using conventional and gnotobiotic rats and gut microbiome analyses (16S rRNA genes pyrosequencing and reverse transcription qPCR), we demonstrated that the clearance kinetics of one FMP bacterium, Lactococcus lactis CNCM I-1631, were dependent on the structure of the resident gut microbiota. Susceptibility of the resident gut microbiota to modulation by FMP intervention correlated with increased persistence of L. lactis. We also observed gut microbiome configurations that were associated with altered stability upon exposure to transient bacteria. Our study supports the concept that allochthonous bacteria have transient and subject-specific effects on the gut microbiome that can be leveraged to re-engineer the gut microbiome and improve dysbiosis-related diseases. The ISME Journal (2016) 10, 2235–2245; doi:10.1038/ismej.2016.13; published online 8 March 2016

Introduction
Mammals are holobionts that host microbial communities of astounding density and complexity within their gastrointestinal (GI) tracts. Microorganisms from maternal and environmental microbiomes rapidly colonize the GI tract of the newborn, and a stable microbial ecosystem develops within the first three years of life (Koenig et al., 2011). This microbial stability is then continuously challenged by daily ingestion of environmental bacteria originating from sources such as diet (van Hylckama Vlieg et al., 2011), indoor environments (Lax et al., 2014), human co-inhabitants (Song et al., 2013) and, more recently, by symbionts used to restore a perturbed microbiota (Reeves et al., 2012; Atarashi
Correspondence: J Doré, Institut National de la Recherche Agronomique, Jouy-en-Josas, France. E-mail: joel.dore@jouy.inra.fr or P Veiga, Life Science, Danone Nutricia Research, Palaiseau 91120, France. E-mail: patrick.veiga@danone.com 4Present address: Chr. Hansen, Boege Allé 10-12, DK-2970, Hoersholm Denmark. 5Co-senior authors. Received 23 June 2015; revised 18 December 2016; accepted 8 January 2016; published online 8 March 2016

et al., 2013; Deriu et al., 2013; Laval et al., 2015; Martin et al., 2015). One of the many traits ascribed to the autochthonous (that is, resident) gut microbiota is its ability to prevent colonization by allochthonous (that is, exogenous) bacteria, especially pathogens. This function of the microbial ecosystem is known as ‘colonization resistance’ or ‘the barrier effect’ (van der Waaij et al., 1971). Colonization resistance has been well-established with respect to Escherichia coli, Clostridium difficile and Salmonella spp. (Que and Hentges 1985; Wilson et al., 1986; Vollaard et al., 1990; Stecher et al., 2005) and has been linked to certain features of the gut microbiota, for example, community complexity as well as the presence of specific taxa (de La Cochetiere et al., 2010; Manges et al., 2010; Stecher et al., 2010; Rousseau et al., 2011).
Bacteria in foodstuffs are a major source of allochthonous bacteria, ranging from 104 to 109 colony-forming units per gram of food with fermented foods having the highest viable bacterial counts (Lang et al., 2014). These food-borne bacteria can temporarily integrate into the gut microbiome and constitute what can be called the transient microbiome (McNulty et al., 2011; David et al., 2014; Veiga et al., 2014; Eloe-Fadrosh et al., 2015). Emerging evidence suggests a significant role of

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transient food-borne bacteria on the overall gut specific pathogen-free animal facility, and fed a

microbiota community structure and function standard autoclaved chow diet (ref. R03, SAFE,

(McNulty et al., 2011; Veiga et al., 2014; Derrien Augy, France) ad libitum. After adaptation and

and van Hylckama Vlieg 2015; Unno et al., 2015).

15 days of run-in, the rats were gavaged with the

In the present study, we examined if a host’s FMP (0.5 ml per day) for 15 days (Day 1–15). During

autochthonous gut microbiota influences niche the last 5 days of the gavage period, Geobacillus

permissivity (that is, colonization resistance) for stearothermophilus spores (Merck, Darmstadt,

transient bacteria administered in a fermented milk Germany) were added to the FMP as a GI transit

product (FMP) containing a consortium of five marker (107 day per rat). Spores collected from fecal

strains: Bifidobacterium animalis subsp. lactis samples were germinated at 65 °C in G-spore

CNCM I-2494, Lactococcus lactis subsp. lactis medium (Drouault et al., 2002). The 15 days after

CNCM I-1631 Lactobacillus delbrueckii subsp. the FMP gavage served as a wash-out period (Day

bulgaricus CNCM I-1632, L. delbrueckii subsp. 16–30). The feces of the rats were collected during

bulgaricus CNCM I-1519 and Streptococcus thermo- the experimental period and the collection time

philus CNCM I-1630. Following FMP administration points are shown in Figure 1a.

to conventional rats, we observed that one subgroup

of rats (hereafter called ‘resistant’) eliminated L. lactis CNCM I-1631 as fast as a GI transit marker, whereas another subgroup (hereafter called ‘permissive’) shed the strain over an additional 24–48 h. Gut microbiota analyses showed that resistant and permissive rats differed in their abundance of Lachnospiraceae and that resistant rats had a microbiota less susceptible to FMPinduced changes compared with the permissive rats. Based on these findings, we re-analyzed the 16S ribosomal RNA (rRNA) amplicon survey data from the McNulty et al.'s, study (2011), which investigated the effects of a similar FMP on human gut microbiota (n = 14), and observed similar patterns. We then used fecal transplantation in germ-free rats

RNA and DNA extraction The fecal samples were stored at − 80 °C until RNA and DNA extraction. The RNA was extracted by High Pure Isolation Kit (Roche, Branford, CT, USA) with an improved protocol described previously (Tap et al., 2015). A frozen aliquot (200 mg) of each fecal sample was suspended in 250 μl of guanidine thiocyanate, 0.1 M Tris (pH 7.5) and 40 μl of 10% N-lauroyl sarcosine, and DNA was extracted as previously described (Manichanh et al., 2006). RNA and DNA concentration and molecular weight were estimated using a nanodrop instrument (Thermo Scientific, Wilmington, DE, USA) and agarose gel electrophoresis, respectively.

to demonstrate that the resistant and permissive

phenotypes were gut microbiota-dependent.

Fecal quantitative reverse transcription PCR

The bacterial culture used for standard curves,

Materials and methods

the primers and quantitative reverse transcription PCR system and protocol were described

Study product The product was an FMP (Danone Research), which contains the following strains: L. lactis subsp. lactis (strain I-1631 from the French National Collection of Cultures of Microorganisms (CNCM),

previously (Veiga et al., 2010) (Supplementary Table S1). The quantity of each FMP strain was normalized by the number of total bacteria. We converted the number of detected molecules (RNA) into cell equivalents.

Paris, France), B. animalis subsp. lactis CNCM

I-2494, L. delbrueckii subsp. bulgaricus CNCM I-1632,
L. delbrueckii subsp. bulgaricus CNCM I-1519
and S. thermophilus CNCM I-1630. The FMP contains ~ 108 colony-forming units L. lactis ml − 1, B. lactis ml − 1, L. bulgaricus ml − 1 and 6 × 108 S. thermophilus ml − 1. The energy density of the FMP was 6.0–7.2 kcal g − 1 and the pH values were
4.35–4.5.

Pyrosequencing of the V3–V4 region of 16S rRNA genes The PCR of the V3–V4 region of 16S rRNA genes and pyrosequencing was performed by Genoscreen (France, www.genoscreen.com) with GS-FLX platform (Roche). The following universal 16S rRNA primers were used for the PCR reactions: V3F (TACGGRAGGCAGCAG, 343–357 E. coli position) and V4R (GGACTACCAGGGTATCTAAT, 787–806

E. coli position).

Conventional animal study Animal studies and experiments were approved by the National Ethics committee on Animal Experimentation and carried out according to its guidelines (Sous le numéro 45). Eight-week-old male adult Fisher 344 rats (purchased from IcoCrl Charles River Laboratories, L'Arbresle, France, n = 24; originating from 14 different litters) were maintained in a

Bioinformatics and statistical analysis The quality control of raw sequences, operational taxonomic units (OTUs) classification, alignment of the representative sequence of each OTU, chimera removal, taxonomic assignment and alpha and beta diversity analyses were performed with QIIME (macQIIME 1.7) (Caporaso et al., 2010). The

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Figure 1 Experimental design and fecal abundance of L. lactis, B. lactis, L. bulgaricus and G. stearothermophilus spores in conventional rat. (a) Experimental design. (b) Fecal abundance of Geobacillus stearothermophilus spores. Each symbol represents a sample from an individual rat (n = 24). RT-qPCR quantification of (c) L. lactis, (d) B. lactis and (e) L. bulgaricus. Each symbol represents a sample from a given individual. Data expressed as log10 (equivalent cells gm − 1 feces). Medians are reported.

sequences were split based on barcodes (10 nt) and filtered according to the following quality criteria: length between 250–1000 nt, no mismatch allowed in barcodes and primers, and exclusion of homopolymers larger than 6 nt, quality above 25 over a 50 base pairs window). Resulting sequences were used to pick OTUs. The delineation of OTUs was conducted with Uclust using 97% cutoff, the representative sequence of each OTU was aligned using PyNAST and chimeric sequences were removed using ChimeraSlayer. The representative sequence of each OTU was assigned the taxonomic classification with the Ribosomal Database Project Classifier with a minimum bootstrap threshold of 80%. Rarefaction curves were generated with Faith’s phylogenetic diversity (PD_Whole tree), Chao 1 and Observed Species method in QIIME. Raw data from 127 samples generated by McNulty et al., (2011) were obtained and processed in QIIME v 1.8 (OTU

were picked against the May 2013 Greengenes database) in order to generate taxonomy profiles and beta diversity matrixes. Lactococcus relative abundance was calculated as the average of the Lactococcus-assigned OTUs through the FMP administration period (that is, weeks 5, 6, 8, 11 as per the McNulty et al., study) or wash-out periods (that is, weeks 13, 15 as per the McNulty et al., study) in order to smooth temporal intraindividual variations. LEfSe analyses were performed on the website http://huttenhower.sph. harvard.edu/galaxy (Segata et al., 2011) to identify OTU separating permissive or resistant subjects. The differential features were identified at the OTU (97% similarity), Phylum, Class, Order, Family and genus levels using the following parameters: (1) the alpha value for the factorial Kruskal–Wallis test among classes is o0.05 and (2) the threshold on the logarithmic LDA score for discriminative

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features is 42.0. Comparison between UniFrac

We quantified the abundance of the FMP species

distance kinetics of Lactoc+ and Lactoc − subjects during the FMP intervention and observed a high

was carried out using linear mixed models with intra-individual variability (that is, within a two-log

repeated measures and a random effect. Partial-Least range) when assessed at four time points

Square Discriminant Analyses and receiving opera- (Supplementary Figure S1). These data suggest that

tor characteristic analyses were performed with the fecal abundance of the FMP strains during FMP

R packages ‘muma’ and ‘pROC’.

administration could not be a reliable marker of

Canonical analysis of principal coordinates colonization resistance. Subsequently, we focused

(CAP) and permutational multivariate analysis of on the elimination kinetics of the FMP species

variance were performed by using the method during the wash-out period.

implemented in the R ‘BiodiversityR’ and ‘vegan’

We verified that the GI transit time was compar-

package, respectively. The Bray–Curtis method was able for all animals by measuring the fecal abun-

used for calculating ecological distance in CAP and dance of G. stearothermophilus spores, a commonly

permutational multivariate analysis of variance. used experimental GI transit marker. Its levels

Permutation tests using the trace and the greatest dropped below the limit of detection after two days

root statistics were performed to assess the signifi- (Day 17) in all the rats (Figure 1b). Unlike B. lactis

cance of the discrimination. The permuted P-values and L. bulgaricus, L. lactis was still detected in the

were obtained with 999 permutations in CAP and feces of 450% of rats (n = 12) after 2 days

permutational multivariate analysis of variance.

(Figures 1c–e). We confirmed the elimination

dynamics of L. lactis in two additional independent

experiments (n = 52) (Supplementary Figure S2) and

Gnotobiotic rat study Germ-free male Fischer 344 rats (8-week-old) (Anaxem INRA, Jouy-en-Josas, France) were maintained in two plastic flexible film isolators (n = 8 per isolator), and fed a standard autoclaved chow diet (ref. R03, SAFE) ad libitum. Rats in one isolator were conventionalized with two gavages of a fecal suspension originating from one randomly selected permissive conventional rat while rats in the other isolator were conventionalized with two gavages of a

again observed no effect on the other FMP strains (data not shown). The differential pattern of L. lactis elimination kinetics suggested that the transient persistence of this strain differed between individual rats. Thus, we separated the rats into two groups, ‘resistant’ and ‘permissive’, based on their elimination kinetics of L. lactis, with resistant rats showing an elimination of L. lactis similar to the transit marker and permissive rats having a longer persistence of L. lactis compared with resistant rats.

fecal suspension originating from one randomly

selected resistant conventional rat. After 4 weeks of

conventionalization, both groups of conventionalized rats were gavaged with the FMP similar to the experiment performed in conventional rats.

Permissive and resistant phenotypes display distinct autochthonous gut microbiota in rats To determine whether permissivity to L. lactis was associated with a specific gut microbiota structure,

we analyzed the gut microbiota of the rats before the

Results

FMP intervention (Day − 2 and 0), at the end of treatment (Day 15), during the wash-out period (Days

Clearance kinetics of food-borne bacteria varies

16, 17, 18 and 20) and 2 weeks after the wash-out

across rats

(Day 30) using bar-coded pyrosequencing. After

Twenty-four conventional rats received an FMP quality-control filtering, we obtained 646 627 reads

containing five bacterial strains (L. lactis subsp. of the V3–V4 region of 16S rRNA genes from 192

lactis CNCM I-1631, B. animalis subsp. lactis samples with an average of 3368 reads per sample

CNCM I-2494, L. delbrueckii subsp. bulgaricus (±303.3 s.d.) and 12 161 OTUs were delineated with

CNCM I-1632, L. delbrueckii subsp. bulgaricus CNCM a 97% cutoff (Rarefaction curves (Supplementary

I-1519 and S. thermophilus CNCM I-1630) by daily Figure S3)). ‘Permissive’ and ‘resistant’ rats showed

oral gavage for 15 days (Figure 1a). FMP species were no significant differences in diversity based on

not detected in feces before the start of the gavage. observed OTUs, PD whole-tree and Shannon diver-

During the FMP intervention, the ingested species of sity indexes. Firmicutes (54.5% ± 9.8%, mean ± s.d.)

L. lactis, B. lactis and L. bulgaricus were detected and Bacteroidetes (41.0% ± 9.1%, mean ± s.d.) con-

and quantified (4105 cell equivalents gm − 1 feces) in stituted the two most dominant phyla of the rat fecal

100% of the stool samples. In contrast, during the bacterial communities, followed by Proteobacteria

FMP intervention, S. thermophilus CNCM I-1630′s (2.5%± 1.1%, mean ± s.d.) and Tenericutes (1.4%

DNA was recovered in only 50% of the stool samples ± 1.8%, mean ± s.d.) (Supplementary Figure S4A).

at concentrations too low to allow reliable qPCR The relative abundance of the bacteria phylogeneti-

quantification. Owing to the poor recovery of cally close to the FMP species was extremely low at

S. thermophilus DNA, the dynamics of this strain baseline (that is, Bifidobacteriaceaeo0.04%, Lacto-

could not be further investigated. We thus focused bacillaceae o0.26% and Streptococcaceae o0.04%,

on the other FMP strains.

Supplementary Figure S4B). We used LEfSe, a linear

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discriminant analysis effect size tool (Segata et al., 2011), to discriminate differential abundance of bacterial phylotypes between permissive (n = 12) and resistant rats (n = 12) prior to the FMP intervention. Forty-three OTUs were found to discriminate between the gut microbiota of resistant and permissive rats (Figure 2a and Supplementary Table S2). We next used a Partial-Least Square Discriminant Analysis coupled with a receiving operator characteristic analysis and confirmed that LEfSe successfully identified OTUs discriminating between permissive and resistant rats with an Area Under the Curve of 0.90 (Supplementary Figure S5). At the family level, permissive rats had a higher relative abundance of Ruminococcaceae, and a lower relative abundance of Lachnospiraceae, as compared with resistant rats (Figures 2b and c). Similar results were obtained in a second independent experiment

(n = 12) (Supplementary Figure S6). Conflicting results were observed for Bacteroidetes assigned OTUs between the two experiments. In one experiment (Figure 2a), Bacteroidetes OTUs did not efficiently discriminate between permissive and resistant rats, whereas they appear to be more discriminant in the other experiment (Supplementary Figure S6).
Gut microbiota robustness observed in ‘resistant’ rats To estimate the effect of the FMP intervention on the gut microbiota structure, we calculated the phylogenetic dissimilarities of gut microbial communities between time points at baseline and after the end of the FMP intervention for each rat using weighted UniFrac and Bray–Curtis methods. The results showed that the variation of the gut microbiota induced by the FMP intervention was higher in

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Figure 2 Permissive and resistant rats differ in their gut microbiota and in the amplitude of ecological changes induced by the FMP. (a) LDA scores computed for taxa differentially abundant between permissive and resistant rats at baseline (Day –2 and 0). The heat map shows the relative abundance (log10 transformation) of OTUs in each sample. Abundance of (b) Ruminococcaceae and (c) Lachnospiraceae. Each symbol represents a sample from an individual rat. Data are expressed as relative abundance (%). The median of the data is shown. **Po0.01 and *Po0.05 by Kruskal–Wallis (KW) sum-rank test. The distance between Day 0 and 15 of each rat was calculated using the (d) UniFrac and (e) Bray–Curtis distances, mean ± s.e.m. **Po0.01 and *Po0.05 by Student's t-test. Canonical analysis of principal coordinates (CAP) of the gut microbiota in (f) permissive (n = 12) and (g) resistant (n = 12) rats prior to (Day − 2 and 0), during (Day 15 and 16) and after FMP administration period (Day 17, 18, 20 and 30).
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permissive rats than in resistant ones (Figures 2d and e).

In line with this observation, a CAP (Anderson and

Willis, 2003) based on Bray–Curtis distance revealed

a greater dispersion of the gut microbiota composi-

tion in the permissive compared with resistant rats

during the FMP intervention (Figures 2f and g). We

further used a cross-validated correct classification

rates to quantify such dispersion using the first

46 and 37 principal coordinates accounting for

84.9% and 79.2% of the total variations in the

permissive and resistant groups, respectively.

Consistent with the previous analysis, the correct

classification rates of the permissive group was

higher (62.9%) compared with the resistant group

(47.4%). The CAP model of the rats in the second

independent experiments had a similar distribution

(Supplementary Figure S7). Using a permutational

multivariate analysis of variance, a method that

can assess the effects of factors directly based on

Bray–Curtis distance matrices (McArdle and

Anderson, 2001), we confirmed that the FMP

intervention induced limited changes in the gut

microbiota structure of the resistant compared to

permissive rats (Supplementary Table S3).

To further assess the resilience of the gut micro-

biota, we focused our analysis on the kinetics

of FMP-modulated phylotypes as identified by

LEfSe. In the resistant group, the FMP increased

Turicibacteraceae and Desulfovibrionaceae, whereas

it decreased Porphyromonadaceae, Prevotellaceae

and Cyanobacteria (Supplementary Figure S8A and Figure 3 Transplantation of fecal microbiota from permissive

Supplementary Table S4). These taxa recovered to and resistant donors into germ-free rats. (a) Principal component

their baseline levels after only 2 days of wash-out. At the lower phylogenetic level, the trend was similar (Supplementary Figure S9). In permissive rats, Lachnospiraceae and Unclassified Bacteroidales

analysis (PCA) of the fecal bacterial communities of permissive or resistant donors and their recipients. (b) Abundance of L. lactis in gnotobiotic rats inoculated with a permissive microbiota (Gnotopermissive; n = 8) or a resistant microbiota (Gnoto-resistant; n = 8). Fecal samples were collected after 15 days of daily FMP

were increased upon the FMP administration while unclassified Clostridiales, Ruminococcaceae and Porphyromonadaceae taxa decreased (Supplementary

administration and during the wash-out period. Data are expressed as log10 (equivalent cells gm − 1 feces) and mean ± se.m. for each
group. **Po0.01 by Student's t-test.

Figure S8B and Supplementary Table S5). In

contrast with the resistant group, the majority of (Supplementary Figure S11) and observed that

these phylotypes (four out of five) did not recover to L. lactis CNCM I-1631 persisted longer in permissive

their baseline levels at Day 17; indicating a lower recipients compared with resistant recipients

degree of resilience of the gut microbiota in (Figure 3b), indicating that permissivity for L. lactis

permissive rats.

CNCM I-1631 was microbiota-dependent.

Transfer of the permissive and resistant phenotypes by gut microbiota transplantation Fecal microbiota samples from selected donors of the permissive and resistant groups were transplanted into separate groups (n = 8 × 2) of 8-week-old male Fisher 344 germ-free rats. Four weeks after transplantation, we verified that the gut microbiota of the recipient rats resembled those of the donors (Figure 3a and Supplementary Figure S10). Next, we administered the FMP to the two groups of conventionalized rats over 15 days and assessed the transit time using G. stearothermophilus spores. We confirmed that the transit time of the conventionalized rats were similar across recipient rats

Evidence of permissive and resistant phenotypes in human To test whether humans contain gut microbiota signatures similar to permissive and resistant rats, we examined the gut microbiota data from a previous clinical trial, which used the same FMP in 14 healthy females and followed a design resembling the one of our rat study (McNulty et al., 2011). Based on 16S rDNA sequencing data, all individuals were positive for Lactococcus during the FMP consumption period, and Lactococcus prevalence decreased from 100 to 36% during the wash-out period (Figure 4a). This strong correlation between Lactococcus levels and the FMP consumption periods indicated that

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linear mixed model to test the difference between the kinetics of the groups and observed a trend (P = 0.086) toward higher inter-individual Weighted UniFrac distances in the Lactococcus carriers compared with the non-carriers (Figure 4c). Interestingly, this difference reached its maximum after the first week (P = 0.0502). No significant difference was observed with the Bray–Curtis metrics.

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Figure 4 Evidence of permissive and resistant phenotypes in human (a) Distribution of Lactococcus carriers (Lactoc+) and noncarriers (Lactoc–) during and after the FMP administration. (b) Relative abundance of Lachnospiraceae in Lactococcus carriers and non-carriers. (c) Kinetics of weighted UniFrac distances of Lactoc+ and Lactoc– subjects expressed as mean ± s.e.m. A linear mixed model showed a difference (P = 0.086) between groups across the intervention. x axis label (weeks) were numbered as per the Mc Nulty et al. study.
Lactococcus abundance was a reliable marker of L. lactis I-1631′s shedding. Lactococcus kinetics data enabled us to discriminate between two groups of subjects: the Lactococcus carriers (n = 5) and the Lactococcus non-carriers (n = 9) during the wash-out period; analogs of the permissive and resistant rats (Figure 4a). Next, we analyzed the baseline gut microbiota of the Lactococcus carriers and noncarriers. At the family level, Lactococcus carriers had a higher relative abundance of Barnesiellaceae (P = 0.01), Odoribacteraceae (P = 0.03) and Clostridiaceae (P = 0.05) and tended to have a higher relative abundance of Streptococcaceae (P = 0.08) and Lachnospiraceae (P = 0.109) (Mann–Whitney test, Figure 4b and Supplementary S12). Although it did not reach statistical significance, the abundance of Lachnospiraceae was the only common signature between humans and rats discriminating Lactococcus carriers from non-carriers (Figure 4b). We also observed that Lachnospiraceae was the only family with comparable levels in humans and rats (Supplementary Figure S13), whereas the others (Barnesiellaceae, Clostridiaceae, Streptococcaceae and to a lesser extend Odoribacteraceae) were less abundant in rats (Supplementary Figure S13).
To assess the effect of the FMP on the structure of the gut microbiota of Lactococcus carriers and noncarriers, we calculated the weighted Unifrac and Bray– Curtis distances between the two groups during baseline and the FMP consumption period. We used a

Discussion
Our study sheds light on the inter-individual variability of ecological forces at play in resistance and resilience mechanisms in response to allochthonous bacteria. We showed that individuals with a ‘resistant’ phenotype, as assessed by clearance of L. lactis following FMP intervention, have a more robust microbiota leading to limited FMP-induced changes and faster resilience kinetics compared with permissive rats. Of interest, similar trends were observed in humans despite differences between rat and human gut microbiota and limited statistical power (cf. Supplementary Material; Supplementary Figure S11–S13).
There is increasing evidence that food-borne bacteria, principally contained in fermented products, are biologically active in the colon (Oozeer et al., 2005; McNulty et al., 2011; David et al., 2014; Veiga et al., 2014; Eloe-Fadrosh et al., 2015), indicating that they might participate in gut microbial community function. In some cases, such activities might be part of the mechanisms underlying beneficial effects. The FMP used in this study has been shown to ameliorate symptoms associated with irritable bowel syndrome in humans and to decrease intestinal inflammation in mice with variable efficacy across individuals (Veiga et al., 2010; Marteau et al., 2013). Our results suggest that overall ecological robustness of the gut microbial community might be a previously unrecognized cause of inter-individual variation responses to FMP interventions in humans and rodents.
A previous study showed that baseline levels of resident Enterobacteriaceae predicted the susceptibility of mice to be colonized by Salmonella, a pathogen belonging to the Enterobacteriaceae family (Stecher et al., 2010). This observation led the authors to define the ‘like-to-like’ rule, which predicts that gut microbiota with high abundance of autochthonous Enterobacteriaceae are more likely to provide favorable conditions for allochthonous Enterobacteriaceae—including pathogens such as Salmonella. The same concept seemed to hold true for the non-pathogenic bacteria Lactobacillus reuteri (Stecher et al., 2010). In our rat data set, the relative abundance of Streptococcaceae (to which L. lactis belongs to) was extremely low (o0.034%) and rare (only detected in two rats), excluding the possibility of a strong association with our phenotypes. In our human cohort, the levels of Streptococcaceae were lower in the permissive individuals suggesting that

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the ‘like-to-like’ rule might not prevail in the case of

Adhesion is another factor ascribed to probiotic

the persistence of L. lactis. Similarly, detection of persistence in the gut (Mandlik et al., 2008). In silico

Lactobacillus rhamnosus DR20 after a 6-month- analyses of L. lactis CNCM I-1631 genome showed

consumption period was inversely associated with that proteins with host-binding domains were

the baseline abundance of fecal Lactobacillus spp. predicted to be anchored to L. lactis’ peptidoglycan

(Tannock et al., 2000).

via a Sortase A (SrtA)-dependent mechanism

Consistent with the known ecological niches of (Supplementary Information; Supplementary Table S6).

L. lactis (for example, dairy and plant environments To further assess the functionality of these L. lactis

(Bachmann et al., 2012)), we and others (Kimoto et al., cell wall proteins in vivo, we piloted an experiment

2003) have shown that L. lactis does not persist with a L. lactis ΔsrtA mutant, which was adminis-

43 days in the colon of conventional animals. tered to the conventionalized ex-gnotobiotic rats. We

However, in the absence of ecological competition observed a shorter persistence of this ΔsrtA mutant in

(that is, germ-free animals), L. lactis can colonize and permissive individuals (Supplementary Figure S14E).

thrive in the mouse intestines (Roy et al., 2008) Although these preliminary data require to be

demonstrating its capacity to utilize gut-derived carbon confirmed with a complemented ΔsrtA mutant to

sources. Proteomic analyses of L. lactis mono- unambiguously confirm the role of SrtA in the

colonized mice indicated a shift of the lactococcal persistence of L. lactis, the correlation between the

metabolism from lactose catabolism to N-acetylgluco- inactivation of the SrtA enzyme and the loss of

samine and mannose utilization (Roy et al., 2008). lactococcal persistence in permissive rats already

Known sources of mannose and N-acetylglucosamine allows us to hypothesize that lactococcal adhesion

in the intestine are extracellular glycans (that is, might be involved in the observed permissive pheno-

mucins) produced by the gut epithelium (Derrien type. In addition, genes encoding surface exposed

et al., 2010). Inactivation of the E. coli genes involved proteins, or other pathways, might be differentially

in mannose or N-acetylglucosamine utilization led to regulated in permissive and resistant rats.

an impairment of E. coli growth in mouse intestine;

Our study also sheds light on the inter-individual

showing that these two carbohydrates are relevant variability of the gut microbiota of animals housed in

carbon sources for metabolically active bacteria in the the same facility. This observation is consistent with

gut (Fabich et al., 2008). A previous study demon- previous studies, which reported intra-facility varia-

strated that intestinal growth rates and adhesion are tions of gut microbiota-related features such as

two factors influencing the kinetics of elimination of enterotype distribution, antibiotic response or mucus

exogenous bacteria (de Jong et al., 2007). In resistant permeability (da SQ-MK et al., 2005; Rooks et al.,

rats, L. lactis CNCM I-1631 was eliminated as fast as 2014; Jakobsson et al., 2015).

the transit marker suggesting a passive clearance with

In humans, 4 out of 14 individuals showed a

no growth or adhesion of the ingested strain. In 2-week persistency of B. lactis CNCM I-2494 after the

permissive rats, L. lactis CNCM I-1631 was retained end of the FMP consumption, indicating that this

longer in the colon; raising the possibility that the strain can integrate and transiently persist in some

ingested strain can either grow in vivo, adhere to humans in contrast to what we observed in rats. In

intestinal wall or both. Growth of L. lactis in the gut general, the intestinal abundance of Bifidobacterium

requires carbon sources such as N-acetylglucosamine in human is higher in average (~4.5%) (Arumugam

and/or mannose as discussed above. These two et al., 2011) compared with laboratory rats, which

carbohydrates are likely to be highly demanded by harbor in averageo0.1% Bifidobacterium as

members of the gut microbiota using such carbon observed by us and others (da SQ-MK et al.,

sources. Lachnospiraceae and Ruminococcaceae spe- 2005; Delroisse et al., 2008; Ketabi et al., 2011;

cies are among the known species able to utilize Dossou-Yovo et al., 2014). This difference may

mucin-derived carbohydrates (Tailford et al., 2015), reflect intestinal conditions and/or diets more favor-

suggesting a possible competition between Rumino- able to the growth of Bifidobacterium species

coccaceae and/or Lachnospiraceae. As the FMP con- (including B. lactis CNCM I-2494) in humans

sumption was associated with a decrease of compared with laboratory rats.

Ruminococcaceae and an increase of Lachnospiraceae

Collectively, our results suggest that the composi-

in permissive rats, one can hypothesize that tion of the autochthonous gut microbial community

L. lactis competes with Ruminococcaceae. Another might account for the amplitude and persistence of

hypothesis would be that L. lactis, and possibly the effects of supplements containing allochthonous

other bacteria of the FMP, might stimulate Lachnospir- microbes (for example, symbionts or probiotics).

aceae which in turn compete with Ruminococcaceae. Beneficial microbes-based therapies directed at

This last hypothesis is supported by prior studies ‘resistant’ individuals might require a tailor-made

showing that the same FMP increased Lachnospira- diet able to maximize the transit time of beneficial

ceae species in human (Veiga et al., 2014) and in a microbes. Recent studies have shown that diet and

mouse model of intestinal inflammation (Veiga et al., dairy matrix might account for the survival and

2010). No effects of the FMP on the Ruminococcaceae persistence of lactic acid bacteria in the gut (Zhou

family were reported in these studies (Rooks et al., et al., 2008; Tachon et al., 2014). In our case, further

2014; Veiga et al., 2010, 2014).

studies using an FMP without probiotics or probiotic

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Gut microbiota response to food-borne bacteria C Zhang et al

species without FMP are warranted. In conclusion, evaluation of gut microbiota directed therapies involving administration of allochthonous microbes should consider the endogenous gut microbiota as a stratifying factor.
Accession numbers The raw pyrosequencing and Illumina read data for all samples has been deposited in the Sequence Read Archive under the accession number SRP055846.
Conflict of Interest
The authors declare no conflict of interest.
Acknowledgements
We thank Jean-Christophe Piard for kindly sharing the pDelA plasmid, Chloë Béal for her technical help, Nathan McNulty and Tanya Yatsunenko for generously sharing clinical study data, Timothy Swartz for his critical reading of the manuscript. We thank Thierry Haddad, Sacha van Hijum and Miaomiao Zhou for their kind contribution to the LocateP analysis of our strain (Zhou et al., 2008). We wish to thank T Meylheuc (INRA- MIMA2 platform: www. jouy.inra.fr/mima2) for SEM analysis. The quantitative reverse transcription PCR used was operated under Yakult License (YIFSCAN technology).
Author contributions
CZ and FL conducted animal trial and microbiota analyses; MD and RB analyzed the data from the human clinical trial; M-C D, GQ, PG performed the L. lactis ΔsrtA-related work; SB, JK performed the adhesion assays. PV, JD, CZ, MD, JV, WG participated in the experimental design and the manuscript writing.
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