Lactose and Bovine Milk Oligosaccharides Synergistically Stimulate B

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Lactose and Bovine Milk Oligosaccharides Synergistically Stimulate B. longum subsp. longum Growth in a Simplified Model of the Infant Gut Microbiome Louise M. A. Jakobsen,*,† Ulrik K. Sundekilde,† Henrik J. Andersen,‡ Dennis S. Nielsen,§ and Hanne C. Bertram† †

Department of Food Science, Aarhus University, Kirstinebjergvej 10, Årslev 5792, Denmark Arla Food Ingredients Group P/S, Sønderhøj 10, Viby J 8260, Denmark § Department of Food Science, University of Copenhagen, Rolighedsvej 30, Frederiksberg C 1958, Denmark

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S Supporting Information *

ABSTRACT: Increasing awareness of the importance of a healthy Bifidobacterium-rich microbiome has led to a need for more knowledge on how different prebiotic carbohydrates specifically impact the infant microbiome, especially as a community instead of single bacterial targets. In this study, we combined proton nuclear magnetic resonance (1H NMR) metabolomics and molecular biology methods for quantification of bacteria to compare the prebiotic effect of bovine milk oligosaccharides (BMO) and synthetic galacto oligosaccharides (GOS) using mono- and cocultures of eight major bacteria related to a healthy infant microbiome. The results revealed that BMO treatments supported growth of Bifidobacterium longum subsp. longum and Parabacteroides distasonis, while at the same time growth of Clostridium perfringens and Escherichia coli was inhibited. In addition, there was a synergistic effect of combining lactose and BMO in regards to reducing C. perfringens, maintaining stable numbers of P. distasonis and simultaneously increasing numbers of the beneficial B. longum subsp. longum. These results indicate that the oligosaccharide composition plays a vital role in shaping the developing microbiota. KEYWORDS: prebiotic oligosaccharides, infant nutrition, symbiotic interactions, NMR metabolomics, microbial interactions, gut bacteria, commensal microbiome, pathogen inhibition


metabolic responses to prebiotic carbohydrates will facilitate the development of infant formula with targeted effects on the microbiome with benefits to the evolving infant. Oligosaccharides from human and bovine milk appear to stimulate the growth of Bifidobacterium species in the infant gut,8,9 contributing to the development of the immune system during early life.10−14 Infant formula, however, appears to produce a more diverse adult-like microbial community,4 which might impose long-term impact on health and potentially higher risk of diseases. Efforts have been made to increase the prebiotic effect of infant formula by adding ingredients that are selectively metabolized by Bifidobacterium species. Purified human milk oligosaccharides (HMOs) are very expensive as the source is limited. The simplest forms of HMO can be synthesized, but it is not yet viable to synthesize the more complex HMOs in commercial scale. Bovine milk oligosaccharides (BMOs) recovered from colostrum or whey permeate have

The composition of the infant gut microbiome is strongly influenced by breastfeeding or infant formula milk.1−3 Breastfeeding is the golden standard for delivering the right nutrients at the right time to the infant and its gut microbiome, creating a microbiome dominated by bifidobacteria and lactobacilli.4,5 However, in some cases, infant formula is the only available mode of nutrition, creating a more heterogeneous microbiome with fewer bifidobacteria and higher numbers of clostridia and staphylococci.5 Breastfeeding also led to a lower Clostridium difficile prevalence in infants.6 Increasing awareness about the importance of a healthy Bifidobacterium-rich, gut microbiome has led to a need for more knowledge on how different prebiotic carbohydrates specifically impact the infant microbiome, especially as a community instead of single bacterial targets. A prebiotic is defined as “a non-digestible compound that, through its metabolization by microorganisms in the gut, modulates composition and/or activity of the gut microbiota, thus conferring a beneficial physiological effect on the host.”7 Knowledge on the detailed compositional and © XXXX American Chemical Society

Received: April 3, 2019 Published: July 2, 2019 A

DOI: 10.1021/acs.jproteome.9b00211 J. Proteome Res. XXXX, XXX, XXX−XXX


Journal of Proteome Research

2.0%, glucose 21.6%, DP2/lactose 31.1%, DP3 25.1%, DP4 13.6%, and DP5+ 6.4%. A modified version of a previously published minimal media21 was prepared and contained per liter: peptone (2.5 g), yeast extract (1.25 g), NaCHO3 (2.5 g), bovine bile acids (0.625 g), NaCl (0.125 g), K2PO4 (0.05 g), KH2PO4 (0.05 g), MgSO4 × 7H2O (0.0125 g), CaCl2 × 2H2O (0.0125 g), Tween 80 (2.5 mL), resazurin (0.625 mg), hemin (6.2 mg), L-cysteine-HCl (0.63 g), and Vitamin K (0.01 g). A total of eight single or 1:1 or 1:1:1 combinations of carbohydrates were prepared as 5% (w/v) stocks (including one blank): blank, 0% carbohydrate; LAC, 5% lactose; GOS, 5% GOS; LAC-GOS, 2.5% lactose and 2.5% GOS; BMO, 5% BMO; LAC-BMO, 2.5% lactose and 2.5% BMO; GOS-BMO, 2.5% lactose and 2.5% BMO; and LAC-GOS-BMO, 1.6% lactose, 1.6% GOS, and 1.6% BMO. The carbohydrate stocks were aseptically added to the minimal media by sterile filtering through 0.22 μm filters (Q-Max Syringe Filter, Frisenette, Knebel, Denmark) to obtain a final concentration of carbohydrate of 1% (w/v). The medium was prereduced by placing in an anaerobic chamber at room temperature overnight.

been found to be a good source of oligosaccharides, some of which are similar to HMOs.15 BMOs have been suggested as a potential source of prebiotic carbohydrates.16 The carbohydrates in BMOs can be classified into acidic oligosaccharides that contain sialic acid or N-acetylneuraminic acid (e.g., 3-sialyl lactose, 3SL; 6-sialyl lactose, 6SL; 6-sialyl-N-acetyllactosamine, 6-SLN) and neutral oligosaccharides that contain N-acetylhexosamine.17 Sialic acids are terminal glycans in mucin, and, interestingly, acidic BMOs containing sialic acid have been shown to inhibit hemagglutination by enterotoxigenic E. coli18 and protect against pathogen adhesion to gastrointestinal tissue in in vitro assays.19 On the other hand, neutral BMOs are endorsed for their bifidogenic effect.17 An example of a prebiotic carbohydrate applied in infant formula is galacto oligosaccharides (GOS), a carbohydrate mixture produced using βgalactosidase (lactase, EC in a transglycosylation reaction of lactose and galactose resulting in a mixture of monosaccharides (glucose and galactose) and oligosaccharides of lactose with degrees of polymerization (DP) ranging from DP2 to 5+.20 As compared to other synthetic or plant-derived oligosaccharides, GOS have been shown to specifically stimulate growth of Bifidobacterium species along with decreasing clostridia numbers as studied in an in vitro model system.21 This is consistent with studies showing that fermentation of GOS by other species than Bifidobacterium is low and that GOS therefore represents a selective nutrient source.22 However, as compared to naturally occurring oligosaccharides (human or bovine), which are branched structures of different glycan moieties, GOSs are linear structures of lactose/galactose16 and are therefore less complex. It still remains to be fully uncovered to which extent prebiotic carbohydrates like GOS and BMO and downstream metabolites from bacterial fermentation affect bacterial composition and metabolic activity especially in the infant microbiome. Therefore, we applied a simple human infant microbiome model with bacterial strains grown in mono- and cocultures with GOS or BMO and sampled supernatant and cell pellets for nuclear magnetic resonance (NMR) metabolomics and molecular biology-based methods for quantification of bacteria. We chose a consortium of bacteria consisting of eight bacterial species that were previously reported as being representative of human baby microbiome.8,23 The aim was to obtain an understanding of microbe−microbe interactions by studying the detailed substrate-dependent compositional changes and metabolic activity. We hypothesized that complex carbohydrates such as GOS and BMO are specific nutrient sources for Bifidobacterium species and when supplied as a substrate in coculture will lead to an increased growth of Bifidobacterium species and limit the growth of other less beneficial bacteria.

Propagation of Bacteria

The following bacterial strains were used in the study: Staphylococcus aureus (DSM 20231T), Staphylococcus epidermidis (DSM 20044T), Escherichia coli (DSM 30083T), Parabacteroides distasonis (DSM 20701T), Clostridium perfringens (DSM 756T), Bifidobacterium longum subsp. longum (DSM 20219T), Lactobacillus rhamnosus (LMG 18243), and Bifidobacterium breve (LMG 13208). The bacteria were initially propagated in optimal media: S. aureus, S. epidermidis, and E. coli in Difco WL Nutrient broth (BD, Sparks, MD, USA), P. distasonis in GAM (Nissui Pharmaceuticals CO., LTD, Tokyo, Japan), C. perfringens in Brain Heart Infusion (Thermo Scientific Oxoid, Waltham, MA), L. rhamnosus in M.R.S (Thermo Scientific Oxoid, Waltham, MA) with 0.05% (w/v) L-cysteine and B. longum subsp. longum, and B. breve in Bifidus Selective Media (Sigma-Aldrich, St. Louis, MO). During activation the cultures were maintained at anaerobic conditions at 37 °C for 24−48 h (except for B. breve and C. perfringens 48−72 h and B. longum subsp. longum 72−96 h). The second propagation was performed in optimal media enriched with 0.1% (w/v) GOS and 0.5% (w/v) cGMP (24 h). Mono- and Cocultures

Mono- and cocultures were prepared to study individual activity and their interactions. The optical density (OD600nm) of activated overnight cultures was adjusted to 1.0 using the same broth as used for propagation. In the coculture experiments, a coculture was prepared by mixing OD600nmadjusted monocultures of the eight bacteria in equal volumes. A volume of 2 μL of this coculture was inoculated into prereduced minimal media (2 biological and 2 technical replicates) with 1% (w/v) of carbohydrate. In monoculture experiments, 2 μL of OD600nm-adjusted culture was directly inoculated into prereduced minimal media with 1% (w/v) of carbohydrate (2 replicates). In blank samples, 2 μL of autoclaved water was added to prereduced media. 24 h fermentations were performed under anaerobic conditions at 37 °C. Samples of pellet and supernatant were collected by centrifugation at 8000g for 3 min, and the supernatant was transferred to a new autoclaved tube. Samples were stored at −80 °C until further use.


Carbohydrate Sources

Three carbohydrate sources were used in this study: purified bovine milk oligosaccharide (BMO), galacto oligosaccharides (GOS), and pure lactose (minimum purity 99.0%). The carbohydrate sources were provided by Arla Food Ingredients Group P/S (Aarhus, Denmark). The BMO product was a white powder with a total oligosaccharide content of 44% (w/v) with the following composition: 3′-sialyl lactose (3SL) 37.4% (w/v), 6′-sialyl lactose (6SL) 6.2% (w/v), and 6′-sialyl (6′-sialyl-Nacetyllactosamine (6SLN)) 0.4% (w/v). The GOS product was a syrup with a dry matter content of 75% containing galactose B

DOI: 10.1021/acs.jproteome.9b00211 J. Proteome Res. XXXX, XXX, XXX−XXX


Journal of Proteome Research Table 1. Primer Sets for Bacterial 16S rRNA Gene of the Eight Bacteria Used in This Study strain for standards B. longum subsp. longum (DSM 20219) B. breve (DSM 20213) L. rhamnosus (LMG 18243) S. aureus (DSM 20231T)/S. epidermidis (DSM 20044T) Clostridium perfringens (DSM 756T) P. distasonis (DSM 20701T) E. coli (DSM 30083T)


sequences (5′-3′)



s-Clper-F CIPER-R P.disF P.disR E. coli Fw E. coli rev

Proton Nuclear Magnetic Resonance (1H NMR) Metabolomics

product size (bp)

melting temp (°C)


59.57 58.41 57.87 59.46 57.85 58.57 56.77 52.68

288 296 257

170 159 96

57.49 54.8 58.67 59.68 58.99 59.2

ref Wang et al. 199653 Ehara et al. 20168 Matsuda et al. 200954 Matsuda et al. 200755 Matsuda et al. 200954 Ehara et al. 20168 Huijsdens et al. 200256

Gmbh, Rheinstetten, Germany). In Matlab (Version R2014b, The MathWorks Inc., Natic, MA), data were referenced to DSS at 0.0 ppm and normalized to the area of DSS. Regions that contain no metabolite signals (above 10 ppm and below 0.5 ppm), the interval containing the residual water signal (4.90− 4.76 ppm), and ethanol signals (3.67−3.63 and 1.26−1.12 ppm) were excluded. Finally, the spectra were binned into 0.005 ppm intervals. Multivariate and Univariate Statistical Analyses. The preprocessed 1H NMR spectral data were imported to SIMCA (version, Umetrics AB, Umeå, Sweden) for multivariate data analysis. Pareto scaling was applied and principal component analysis (PCA) was performed to visualize differences between samples and treatments. Orthogonal partial leastsquares discriminative analysis (OPLS-DA) was performed to maximize the separation between treatment groups and to identify metabolites differentially represented in the specific groups. Depending on the amount of samples included in the OPLS-DA models, the models were cross validated (CV) to ensure valid and reliable models and to avoid overfitting.27 S-line plots28 were generated to visualize the differences between classes in OPLS-DA models. Chenomx Profiler (NMR suite 8.1 professional, Chenomx Inc., Edmonton, Alberta, Canada) was used for fitting and quantifying selected carbohydrates and metabolites identified as being important for the separation of groups in OPLS-DA models. A standard t test with a two-tailed distribution was used to calculate the level of significance of differences in pH and metabolite concentrations between treatment groups in R (version 3.5.0, The R Foundation, Vienna, Austria). A pairwise t test with Holm’s adjustment for multiple comparisons was used to test the difference between individual treatment groups.

Sample Preparation. Supernatant samples were thawed at room temperature for 30 min, moved to a polystyrene tray with ice, vortexed, and sterile filtered through a 0.22 μm sterile filter (Q-Max Syringe Filter, Frisenette, Knebel, Denmark). The sterile samples were then filtered through prewashed 10k Millipore centrifugal filters (Amicon Ultra, Millipore Corp., Billerica, MA) by centrifugation at 14 000g for 30 min at 4 °C. A volume of 500 μL of filtered sample was transferred to an NMR tube with 60 μL of phosphate buffer (pH = 7.4) containing 10 mM DSS (3-(trimethylsilyl)-1-propanesulfonic acid-d6 sodium salt, Sigma-Aldrich, St. Louis, MO) and 70 μL of D2O (deuterium oxide, 99.9%, Cambridge Isotope Laboratories, Andover, MA). pH was measured using a pH meter fitted with a silver electrode (Radiometer, Copenhagen, Denmark) before and after addition of buffer. Acquisition of 1H NMR Spectra. NMR spectra were acquired on a Bruker Avance 600 MHz NMR spectrometer (Bruker BioSpin, Gmbh, Rheinstetten, Germany) operating at a proton NMR frequency of 600.13 MHz for 1H and equipped with a 5 mm TXI probe. The 1D NOESY pulse experiment with presaturation of the spectral region containing the water peak (noesypr1d) was used with a recycle delay of 5 s. A total of 64 FIDs were acquired, and the acquisition parameters included 32K complex data points, a spectral width of 7289 Hz (12.15 ppm), and an acquisition time of 2.25 s. Measurements were done at 298 K. Reference spectra for 3SL and 6SL were acquired in-house using chemical standards (Carbosynth, Berkshire, UK). Other BMO and GOS resonances were also detected, but due to the lack of chemical standards, they could not be assigned to specific oligosaccharides. GOS resonances (δ 4.08, 4.17, 4.20, 4.22, 5.45, 5.41, 5.24, 5.23, 5.26, 5.28, 4.51, and 4.30 ppm) were partly assigned using the annotations by van Leeuwen20,24 and BMO resonances (δ 5.34 and 5.36 ppm) using annotations by Crost25 and van Leeuwen.26 An overview of the resonance assignment is given in Table S1. Preprocessing of 1H NMR Data for Multivariate Analysis. An experimental window function with a linebroadening factor of 0.3 Hz was applied to all FIDs before Fourier transformation. The resulting spectra were manually phase corrected and automatically baseline corrected by polynomials using the Topspin 3.0 software (Bruker BioSpin,

Quantitative PCR

Preparation of Standard Curves. The eight bacteria were propagated anaerobically at 37 °C in optimal media until OD of the monocultures reached at least 1.0. The pure cultures were serially diluted in autoclaved saline water (0.9% NaCl) to produce 10−1−10−7 dilutions. A volume of 100 μL of the dilutions 10−4, 10−5, 10−6, and 10−7 were plated on suitable agar plates (medium as mentioned earlier). The plates were incubated anaerobically at 37 °C until counts were stable (C. perfringens, 48 h; S. epidermidis, 48 h; L. rhamnosus, 24 h; S. aureus, 24 h; B. longum subsp. longum, 48 h; B. breve, 48 h; E. coli, C

DOI: 10.1021/acs.jproteome.9b00211 J. Proteome Res. XXXX, XXX, XXX−XXX


Journal of Proteome Research

Figure 1. Relative log(CFU/mL) changes of seven bacteria in a coculture after 24 h exposure to different carbohydrate treatments and a no carbohydrate treatment. Each stacked bar shows the mean difference in log(CFU/mL) of each of the seven bacteria relative to the quantities in the no carbohydrate treatment using two biological and two technical replicates. Positive values indicate increased log(CFU/mL), and negative indicate decreased log(CFU/mL). The bars are colored according to species in the legend on the right side of the plot. LAC, lactose; GOS, galacto oligosaccharides; BMO, bovine milk oligosaccharides; LAC, lactose; GOS, galacto oligosaccharides; BMO, bovine milk oligosaccharides.

24 h; and P. distasonis, 24 h). For each bacterial strain, log CFU/ mL was calculated using the average of visible colonies for the most populated plates with counts >20 and 0.09). Similarly, Staphylcoccus spp. did not change significantly in LAC, GOS, and LAC-GOS treatments (p > 0.09). None of the carbohydrate treatments supported growth of L. rhamnosus (Figure 2F). L. rhamnosus decreased significantly by −0.7 log in LAC (p < 0.001), −0.8 log in BMO (p < 0.001), −1.8 log in LAC-GOS (p = 0.036), and −0.5 log in LAC-GOS-BMO (p < 0.001), whereas only a tendency for a decrease in LACBMO (p = 0.05) and no change in GOS-BMO (p = 0.13) were observed. Similarly, none of the carbohydrate treatments supported additional growth of B. breve (Figure 2G). The significant decreases were in the range of −0.2 to −0.7 for LACGOS (p = 0.04), LAC-BMO (p = 0.05), GOS-BMO (p = 0.02), and LAC-GOS-BMO (p = 0.03). B. breve remained unchanged in LAC (p = 0.52), GOS (p = 0.29), and BMO (p = 0.36).

pH and Metabolite Differences across Carbohydrate Treatments after 24 h Fermentation with Coculture

Major differences in pH of the fermentation media appeared as a result of the organic acids produced by fermentation of the available carbohydrates (Figure 4A). The lowest pH was measured in LAC-BMO and LAC-GOS-BMO samples (pH = 5.4), and the highest pH was measured in the pure BMO samples (pH = 7.5), indicating restricted growth and metabolic activity. Principal component analysis (PCA) scores plot of the metabolite data covered 31.1% and 19.4% of the total variation in the first and second principal components, respectively (Figure 3A). The PC1 and PC2 showed good separation of samples with (blue) or without (red) BMO after 24 h of fermentation. In addition, all of the samples containing no carbohydrates were clustered close together, indicating no changes in the metabolite pattern in these samples upon 24 h fermentation. Furthermore, samples subjected to the same treatment were clustered close to each other, indicating a good experimental reproducibility. Acetate, butyrate, formate, lactate, and succinate were the major metabolites produced by the cocultures. The concentration of these metabolites was generally increased in carbohydrate treatments after 24 h fermentation as compared to the no carbohydrate treatment (Figure 4B−F) and exhibited greater variation within BMO treatments, especially GOS-BMO and LAC-GOS-BMO. Concentration of succinate was generally low in BMO treatments (Figure 4F), whereas lactate was higher in these treatments (Figure 4E). With lower concentrations of

Glycan Metabolism

NMR spectra were examined for metabolites involved in glycan metabolism. Quantification of lactose, galactose, glucose, 3SL, and 6SL before and after 24 h fermentation with the coculture showed that no significant differences were found, but there was a general pattern toward lower glycan level after the 24 h fermentation (Figure S2A−E). The main glycans in BMO were 3SL, 6SL, and small amounts of lactose as well as other resonances originating from BMO moieties. After 24 h of fermentation with the coculture, lactose concentrations were lower, 6SL remained unchanged, and 3SL appeared slightly higher (Figure S2A, D, and C) following fermentation with BMO as substrate. Other BMO resonances were also lower after 24 h fermentation. The doublets observed at δ 5.34 and 5.36 ppm are anomeric signals from BMOs (Figure S3), which might be resonances from an α1−3 fucosylated glycan, although in F

DOI: 10.1021/acs.jproteome.9b00211 J. Proteome Res. XXXX, XXX, XXX−XXX


Journal of Proteome Research

Figure 4. pH (A) and concentration in mM (C−F) of major metabolites in the supernatant of a seven species coculture exposed to seven carbohydrate treatment and a no carbohydrate treatment for 24 h. Bars represent mean values of two biological and two technical replicates, and error bars represent standard error of the mean (SEM). The P-value indicates the overall effect of treatment, and stars indicate significant differences from the no carbohydrate treatment using Holm’s adjusted p-value: *p < 0.05, **p < 0.01, ***p < 0.001. Red shade, treatment without BMO; blue shade, treatment with BMO. (A) pH, (B) acetate, (C) butyrate, (D) formate, (E) lactate, and (F) succinate. LAC, lactose; GOS, galacto oligosaccharides; BMO, bovine milk oligosaccharides.

histidine, isoleucine, and leucine), adenosine, and cystine decreased in intensity. Amino acids were also decreased in treatments with carbohydrates (Figure 5A,B and Figure S1A− C), indicating some degree of proteolytic fermentation or that amino acids were incorporated into the bacterial cells due to growth. The resonances of butyrate, acetate, and lactate also increased in samples with carbohydrate treatment, indicating higher metabolic activity of the bacteria when carbohydrates were supplied. The BMO and BMO-LAC treatments resulted in a set of unique metabolites, whereas LAC and GOS treatments resulted in the most similar metabolic pattern. The BMO treatment (Figure S1C) showed major metabolite activity with higher levels of 3-phenylpropionate, desaminotyrosine, 3SL, cadaverine, 5-aminopentanoate, TMA, and an unknown metabolite at 2.3 ppm along with decreases in levels of inosine, lactose, threonine, arginine, glutamate, isoleucine, leucine, and BMO_1 and BMO_2 (δ 5.34 and 5.36 ppm, Figure S3). When BMO and lactose were combined (LAC-BMO), a different metabolite pattern was found as compared to the individual carbohydrate sources separately. Specifically, the

acetate, butyrate, and lactate, the pure BMO treatment differed from the other BMO treatments (Figure 4B,C,E). To investigate the specific metabolite patterns produced by the coculture in each carbohydrate treatment, orthogonal partial least-squares discriminative analysis (OPLS-DA) models were constructed using the preprocessed NMR data of media without coculture (0 h, blank) as one group and media after 24 h fermentation (24 h, coculture) as the other group (Figure 5A and B and Figure S1A−C). Assignment of compounds can be found in Table S1. In general, across all carbohydrate treatments, 24 h fermentation resulted in decreased levels of adenosine, tryptophan, phenylalanine, tyrosine, and cystine, while at the same time increased levels of hypoxanthine, uracil, formate, succinate, lactate, and acetate were detected. In the treatment with no carbohydrate source (Figure 5A), 24 h of fermentation with the coculture indicated that metabolites related to nonsaccharolytic fermentation were produced, for example, higher intensities of formate, uracil, hypoxanthine, succinate, acetate, lactate, glucocholate, and cholate, while several amino acids (tryptophan, phenylalanine, tyrosine, G

DOI: 10.1021/acs.jproteome.9b00211 J. Proteome Res. XXXX, XXX, XXX−XXX


Journal of Proteome Research

Figure 5. The S-line plots from PLS-DA showing metabolite differences between noninoculated media (negative signals) and media inoculated with a seven bacteria coculture after 24 h fermentation (positive signals). Color of the peaks indicates the intensity of the correlation according to the bar on the right side of each figure. (A) No carbohydrate treatment (Q2 = 0.99, R2X = 0.85), (B) LAC-BMO treatment (Q2 = 0.96, R2X = 0.74). LAC, lactose; GOS, galacto oligosaccharides; BMO, bovine milk oligosaccharides.

LAC-BMO treatment (Figure 5B) showed an increase in 3phenylpropionte, deasaminotyrosine, 5-aminopentanoate, TMA, lactose, and cholate, while uracil, phenylalanine, tyrosine, 3SL, lactate, cystine, ornithine, isoleucine, leucine, valine, and glycholate decreased after 24 h fermentation. For LAC (Figure S1A), increases in levels of 5-aminopentanoate, cadaverine, 4-aminobutyrate, and an unassigned resonance at 3.4 ppm were identified. At the same time, a decreased level of lactose, glutamate, and glycocholate was observed. In the GOS treatment (Figure S1B), the metabolic activity resulted in higher levels of ornithine and cholate, while lower intensities of signals for glucose, lactose, galactose,

methionine, isoleucine, leucine, glycocholate, and GOS_d (δ 5.23 ppm). Growth, pH, Glycan, and Metabolite Differences after 24 h Fermentation in Monocultures

The results from the cocultures were further elucidated using monocultures of B. longum subsp. longum, P. distasonis, and C. perfringens using the same carbohydrate treatments of LAC, GOS, and BMO. Growth was observed by optical density at 600 nm (OD600nm), and 1H NMR metabolomics was performed to explore metabolic differences. There was a significant effect of carbohydrate treatment on OD600nm of B. longum subsp. longum and P. distasonis H

DOI: 10.1021/acs.jproteome.9b00211 J. Proteome Res. XXXX, XXX, XXX−XXX


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treatment) resulted in lower pH in monocultures of C. perfringens (p = 0.052), E. coli (p < 0.0001), L. rhamnosus (p = 0.015), and P. distasonis (p = 0.015). The GOS-BMO treatment resulted in lower pH in monocultures of B. longum subsp. longum (p = 0.048) and P. distasonis (p = 0.02). Finally, the treatment with all carbohydrates combined (LAC-GOS-BMO) resulted in significantly lower pH in monocultures of B. breve (p = 0.0038), B. longum subsp. longum (p = 0.035), and P. distasonis (p = 0.021). In terms of metabolites in monocultures, lactate and acetate were high in B. longum subsp. longum monocultures, especially in BMO with LAC or GOS, but surprisingly not in pure BMO treatments. C. perfringens was identified as the only bacterial species in this consortium that produces butyrate. The high butyrate in the LAC treatment is consistent with the finding that C. perfringens reached the highest level in this treatment. Higher butyrate concentration is also consistent with higher C. perfringens in the GOS treatment. P. distasonis produced some propionate in LAC-BMO and LAC-GOS-BMO, but other than that did not show major metabolic activity as analyzed in the current study.

monocultures (p < 0.001 and p = 0.009, respectively, Figure S5A,B), whereas this was not the case for C. perfringens (p = 0.72, Figure S5C). For B. longum subsp. longum (Figure S5A), significantly higher OD600nm as compared to the no carbohydrate treatment was observed in LAC-GOS (p = 0.022), GOSBMO (p = 0.009), and LAC-GOS-BMO (p = 0.045). The OD600nm values of GOS and LAC-BMO appeared higher than the no carbohydrate treatment, but this only tended to be significant (p = 0.12 and p = 0.11, respectively). For P. distasonis (Figure S5B) and C. perfringens (Figure S5C), there were no significant differences in pairwise comparisons between the no carbohydrate and other carbohydrate treatments. To isolate the effects related to carbohydrate metabolism, OD600nm-values were adjusted by subtracting the OD600nm-value of that monoculture in the no carbohydrate treatment from the individual carbohydrate treatment OD600nm-values (Figure S6). Comparisons within carbohydrate treatments showed that in the BMO treatment (Figure S6E), there was no overall difference in adjusted OD600nm between the monocultures of B. longum subsp. longum, P. distasonis, and C. perfringens (p = 0.38). In the GOS treatment (Figure S6C), there were significant differences in adjusted OD600nm of the monocultures (p = 0.009); however, this was not reflected in the pairwise comparisons between each of the bacteria (B. longum subsp. longum, P. distasonis, and C. perfringens). Similarly, there was a significant effect of LAC treatment (Figure S6B) on the adjusted OD600nm of monocultures (p < 0.0001), showing significant higher adjusted OD600nm in C. perfringens as compared to P. distasonis (p = 0.04) and trending to be higher than B. longum subsp. longum (p = 0.058). When GOS was combined with LAC (Figure S6D) or BMO (Figure S6G), B. longum subsp. longum showed significantly higher adjusted OD600nm than did P. distasonis and C. perfringens. The overall effect was significant for LAC-GOS and GOS-BMO (p < 0.001 and p < 0.0001, respectively). Adjusted OD600nm of B. longum subsp. longum was significantly higher than P. distasonis (p = 0.014) and C. perfringens (p = 0.033) in LAC-GOS and higher than C. perfringens (p = 0.001), but only trended to be higher than P. distasonis (p = 0.11) in GOS-BMO. In general, there were no major differences between C. perfringens and P. distasonis within the same carbohydrate treatments. Several resonances assigned to GOS moieties were decreased after 24 h fermentation in the coculture. In monocultures of C. perfringens and P. distasonis, the intensity of these resonances also decreased, while only some of them decreased in B. longum subsp. longum cultures (Figure S4). The overall effect of carbohydrate treatment on the pH in monocultures (Figure S7) was significant for B. longum subsp. longum (p = 0.041), C. perfringens (p = 0.0025), L. rhamnosus (p < 0.0001), P. distasonis (p < 0.0001), and S. aureus (p = 0.021), but not in monocultures of B. breve (p = 0.15), E. coli (p = 0.057), and S. epidermidis (p = 0.23). In general, the LAC treatment did not result in major pH differences as compared to the no carbohydrate treatment, indicating low ability of the bacteria to utilize pure lactose for organic acid production. The GOS treatments, on the other hand, resulted in significantly lower pH when available in monocultures of B. longum subsp. longum (p = 0.027), E. coli (p = 0.014), P. distasonis (p = 0.029), and S. aureus (p = 0.04). It is possible, however, that this is a result of fermentation of glucose present in the GOS product. The BMO treatment resulted in lower pH only in the monoculture of B. breve (p = 0.0075), whereas combination of BMO with lactose (LAC-BMO

DISCUSSION In the present study, we have used an in vitro coculture of a simple, but representative population of eight commensals of the infant microbiome to access the bifidogenic effects of lactose, galacto oligosaccharides (GOS), and bovine milk oligosaccharides (BMO) alone or in combination on the metabolic activity and growth of the bacteria using 1H NMR spectroscopy and qPCR analyses. Effects of Prebiotic Carbohydrate Sources on Growth and Metabolic Activity

Monoculture experiments showed that P. distasonis and C. perfringens appear to grow relatively well on the no carbohydrate treatment, but B. longum subsp. longum does not. On the other hand, B. longum subsp. longum appears to have improved ability to grow on the carbohydrate treatments, and when adjusted for the growth on the no carbohydrate treatment, B. longum subsp. longum’s ability to grow is superior to that of C. perfringens and P. distasonis. This growth is accompanied by production of organic acids especially in treatments where LAC, GOS, and BMO are combined. In the coculture, neither access to lactose, GOS, nor the combination of these two inhibited the growth of the two potential pathogens C. perfringens and E. coli. In contrast, access to BMO only promoted growth of P. distasonis and to a minor extent B. longum subsp. longum, while this was not the case for C. perfringens, E. coli, or the other infant gut commensals tested. Interestingly, access to BMO in combination with lactose, GOS, or both, inhibited growth of C. perfringens and E. coli in the coculture. B. longum subsp. longum appeared to dominate and substitute the substantial growth seen by P. distasonis when BMO was the only carbohydrate source. The concurrent change in growth of B. longum subsp. longum and P. distasonis as a result of carbohydrate accessibility indicated substrate competition and possibly cross-feeding in the presence of the multiple carbohydrate sources, as especially the combinations of BMO and lactose stimulated growth of B. longum subsp. longum as compared to access to only the individual carbohydrate sources. Not many studies on the fermentation of oligosaccharides in Parabacteroides spp. have been conducted despite that Parabacteroides spp. are commensals in the human gut. However, a recent study has shown that P. distasonis has a limited ability to I

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carbohydrate sources were not found to be selective, as B. longum subsp. longum, C. perfringens, and E. coli only showed minor differences in their ability to grow in the media with these carbohydrate sources. Consumption of specific GOS isomers is not shared across different bifidobacteria species.36,37 While B. breve (ATCC 15700) consumes a wide range of GOS structures, especially DP3, B. longum subsp. longum (DJO10A) grow less efficiently, but consumes larger oligosaccharides with DP5 and 6 and to a lesser degree DP7 and 8.37 However, the GOS product in the current study only contains a very low amount of DP5+ (6.4%). It is intriguing that in the current study of GOS, C. perfringens did grow along with B. longum subsp. longum. This is in contrast to several other studies showing an inverse relation between B. longum and clostridia38,39 as well as inhibitory effects of the organic acids produced by B. longum subsp. longum on clostridia when GOS is the major carbohydrate source.22 In the latter study, it was also found that E. coli and Clostridium jejuni did not grow noticeably on GOS.22 The BMO treatments led to higher lactate and acetate concentrations in monocultures, which again lead to lower pH in the B. longum culture medium. Such a decrease in pH might explain the inhibition of C. perfringens growth in cocultures with access to BMO, while this was not the case in the GOS supplemented media. The GOS syrup used the current study contained 24% monosaccharides, 31% lactose, and 45% oligosaccharides why the microorganisms have had additional carbohydrate sources to a possible nonfermentable GOS source for several of the tested organisms. These high concentrations of mono- and disaccharides constitute an opportunity for C. perfringens to grow well in this environment in contrast to the BMO media where no mono- and disaccharides or GOS moieties are available. Lactobacilli spp. also mainly utilizes monosaccharides and lactose in GOS and in return produces lactate and small amounts of acetate.40 In the current study, however, L. rhamnosus did not grow in cocultures with the GOS treatments, possibly due to longer lag-time of this strain as compared to C. perfringens, allowing the latter to gain the momentum and using the available carbohydrate sources. It could be speculated whether administering GOS with L. rhamnosus in pretreating the product could reduce the amount of free mono- and disaccharides reaching the gut, thereby preventing the growth of opportunistic pathogens that also easily consume these simple saccharides. Theoretically, this would also increase the concentration of organic acids, thereby lowering the pH of the syrup and probably creating a more acidic environment, which is favorable for bifidobacteria. Lactobacillus spp. is acid tolerant and has been shown to survive throughout the GI tract.41 The advantage of combining B. longum subsp. longum and L. rhamnosus was previously suggested by Martin et al. 2009,39 who tested the effect of feeding GOS with or without L. rhamnosus to gnotobiotic mice with a bacterial composition of the same organims as used in the current study, that is, B. longum subsp. longum, B. breve, S. aureus, S. epidermidis, E. coli, C. perfringens, and Bacteroides distasonis (later reclassified to Parabacteroides). Martin et al. 200939 found an increased B. longum subsp. longum colonization and metabolic activity when administering L. rhamnosus. They also found that GOS alone increased B. breve, B. longum subsp. longum, and B. distasonis, and concomitantly reduced E. coli and C. perfringens. This pattern is slightly different from the results obtained in the current study, where the major difference was an increase in C. perfringens upon GOS administration. The different outcomes could also be attributed to discrepancies when comparing in vitro and in vivo

ferment oligosaccharides as compared to the most common Bacteroides species.29 Parabacteroides spp. share almost 80% of the conserved regions with the most common gut-associated Bacteroides thetaiotamicron and Bacteroides fragilis.30 However, their proteomes mainly overlap in the COG categories “amino acid transport and metabolism” and “translation, ribosomal structure, and biogenesis”,30 indicating that the common saccharolytic fermentation mechanisms are not shared between Bacteroides species and P. distasonis. In the present study, P. distasonis appeared to grow on the oligosaccharide sources, while it was not able to ferment lactose. Even though P. distasonis grows well in the carbohydrate depleted media (Figure S5B), demonstrating effective proteolytic fermentation, the additional growth (Figure S 6) and decrease in GOS and BMO constituents when exposed to these oligosaccharides indicate that P. distasonis does perform saccharolytic fermentation of these oligosaccharides. An inverse relation between P. distasonis and B. longum subsp. longum was found in a recent crosssectional study of microbiome across different age groups in a Japanese population.31 These authors tested this observation using mono- and cocultures of P. distasonis (JCM 5825) and B. longum subsp. longum (JCM 1217) in GAM broth. In the cocultures, P. distasonis was only marginally reduced, while the growth of B. longum subsp. longum was reduced to almost 50% of the growth seen in the monoculture, indicating either superior nutrient utilization by P. distasonis or a growth inhibitory mechanism of P. distasonis on B. longum subsp. longum. The carbon sources in GAM broth are dextrose and starch, and therefore a similar experiment using other carbohydrate sources might show different results. The superiority of BMO as carbohydrate source for P. distasonis as compared to B. longum subsp. longum was recently supported in a study that analyzed the microbiome response to the two sialyllactose isomers, 3SL and 6SL, in the CoMiniGut model that simulates the gut environment of a breastfed infant.32 The study showed that 3SL and 6SL, the most abundant oligosaccharides (37.4% and 6.2%, respectively) in the BMO product used in the current study, both increased the relative abundance of P. distasonis in the infant colon model, while only 3SL supported the growth of B. longum subsp. longum. This indicates selectivity between the sialyllactose isomers in supporting growth of P. distasonis and B. longum subsp. longum, which is compatible with the present study, where mainly 6SL together with other smaller BMO resonances decreased in cocultures where P. distasonis or B. longum subsp. longum increased, indicating that these are the carbohydrates utilized by dominating bacteria. In the coculture, B. longum subsp. longum grew well on GOS, while LAC and BMO appeared to only stimulate growth when provided together, suggesting a synergistic effect of LAC and BMO. The limited growth of B. longum subsp. longum with access to lactose is in contrast to previous studies.33 In terms of BMO fermentation, B. longum subsp. infantis is the only Bifidobacterium subspecies that has been reported as capable of metabolizing the major BMO subconstituent sialalylactose (not further specified),34 supporting our finding that B. longum subsp. longum does not grow solely on BMO. Growth of bacteria on GOS was not only related to the presence of monosaccharides in this product, as multivariate models also showed that there was degradation of other, more complex carbohydrates of DP2 or 3 or larger. In general, GOS is considered to favor growth of bifidobacteria including B. longum and B. breve.35 In the present study, lactose and GOS as J

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study, such as bacteriocin production.44,45 Although it might not be the primary mechanism of pathogen suppression in the current study, Bifidobacteria sp. including species of B. longum subsp. longum has the ability to produce bacteriocins,46 and the same has been found for P. distasonis.47 In the current study, we applied simple mono- and coculture experiments to investigate the detailed consumption patterns, metabolic profiles, and growth profiles related to bacterial metabolism of prebiotic oligosaccharides from GOS and BMO. It is possible that a fermentation time of 24 h is too short to see significant differences due to delayed induction of enzyme expression, and therefore several sampling times longer than 24 h might give a better understanding of the dynamic changes in metabolite productions and glycan degradation. In addition, we applied NMR metabolomics to obtain an untargeted and wide ranging metabolite profile covering several metabolite classes.48 However, MS-based methods might have provided higher resolution and a better identification of oligosaccharides with higher DP,49,50 which are very difficult to precisely identify using 1 H NMR.37,50 In conclusion, coculture and cross-feeding experiments involving P. distasonis, C. perfringens, and B. longum subsp. longum can contribute to a better understanding of the specific interactions that occur under different prebiotic treatments and add to the discussion of what specific mechanisms are related to the inhibition of C. perfringens in the BMO treatments. Deciphering the role of prebiotic nondigestive oligosaccharides and their influence on bifidobacteria and other main commensal gut bacteria is pivotal to understand how access to specific oligosaccharides supports the development of a healthy gut in infants. Both lactose51 and the BMO-like structures that are found in human milk52 are meant to promote the innate immune system; however, this is the first time it has been reported that a potential synergistic prebiotic effect exists between the two. Specifically, the present coculture experiments showed an effect of lactose and BMO in inhibiting the growth of C. perfringens and stable numbers of P. distasonis with a simultaneous increase in the beneficial B. longum subsp. longum. Access to BMO and lactose caused a lower pH and formation of a unique set of metabolites supporting the notion that the oligosaccharide composition supports the developing microbiome and potentially the innate immune system.

studies, as there might be microbe−host interactions occurring that cannot be accounted for in the in vitro study. Also, the authors did not report the composition of their in-house preparation of GOS, which might deviate from the GOS product used in the current study. Possible Inhibitory Mechanisms: SCFA, Bacteriocins, Organic Acids, and pH

Access to BMO either alone or in combination with lactose and/ or GOS resulted in a reduction in viable C. perfringens in the coculture. This indicate that metabolites produced by the other bacteria or the bacteria that are able to ferment BMOs produce metabolites directly and/or indirectly inhibit C. perfringens growth in this environment, considering that C. perfringens was able to grow on BMO in the monoculture system. The compositional changes in bacterial log CFU/mL in the coculture were accompanied by a decrease in pH and a unique metabolite profile when BMO was part of the carbohydrate source(s), resulting in increased formation of acetate, formate, and lactate, which was especially pronounced when BMO was combined with lactose and/or GOS. An advantage in carbohydrate consumption is one way for bacteria to occupy an ecological niche; however, production of SCFA, organic acids, and antimicrobial bacteriocins are additional mechanisms for the exclusion of competing commensals including pathogens in the gut microbiome. Acetate, formate, succinate, and lactate are common organic acids produced by fermentation of GOS and other oligosaccharides.35 Formate, lactate, and succinate are produced by, among others, bifidobacteria and lactobacilli and reduce the pH in the intestines and prevent the growth of pathogenic bacteria.42 B. longum subsp. longum was the main producer of lactate in the current study, and the low lactate concentration in the BMO treatment is consistent with a lower count of B. longum subsp. longum in this treatment. Lactate and acetate from Bifidobacteria can be consumed by butyrate-producing bacteria in a pH-dependent cross-feeding mechanism,42,43 which represents a possible mechanism for C. perfringens growth in GOS treatments in the current study. It is, however, puzzling why lactate produced in the BMO treatments does not have the same effect, but it might be a result of the low pH observed, if, for example, the process is more efficient at higher pH. Butyrate was high in most carbohydrate treatments, except when the only carbohydrate source was BMO, where the formation of butyrate was remarkably low. It is somewhat surprising that butyrate is not lower when BMO was combined with LAC and GOS given the fact that C. perfringens was actually lower in these treatments. However, C. perfringens was still present in these samples (up to 5 log in total in BMO samples) and therefore contributes to butyrate concentration, possibly through an increased metabolic activity. pH was especially low in cocultures with LAC-BMO and LAC-GOS-BMO as carbohydrate sources, that gave rise to a low number of C. perfringens in these cultures, which is consistent with the effect of pH on C. perfringens growth. Interestingly, the pH in cocultures only containing BMO as carbohydrate source was significantly higher, however, still resulting in reduced numbers of C. perfringens, suggesting that another mechanism is in play in terms of C. perfringens inhibition. Considering the pronounced growth of P. distasonis without any relation to any of the metabolites measured in the present study indicates that the mechanism is related to compounds not assessed in the current


S Supporting Information *

The Supporting Information is available free of charge on the ACS Publications website at DOI: 10.1021/acs.jproteome.9b00211. Table S1, assignments of observed 1H NMR resonances in fermentation media after 24 h of fermentation; Figure S1, S-line plots showing metabolite differences between blank (negative signals) and coculture (positive signals) after 24 h fermentation in two treatments; Figure S2, differences in lactose, galactose, glucose, 6SL, and 3SL at 0 h “blank” and after 24 h fermentation “coculture”; Figure S3, BMO and GOS resonances not assigned to specific molecules and differences between 0 h (blank, blue) and 24 h (coculture, red); Figure S4, intensity of unassigned BMO and GOS resonances in monocultures; Figure S5, optical density at 600 nm (OD600nm) of monocultures with B. longum subsp. longum, P. distasonis, and C. perfringens across the different carbohydrate treatments; K

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(8) Ehara, T.; Izumi, H.; Tsuda, M.; Nakazato, Y.; Iwamoto, H.; Namba, K.; Takeda, Y. Combinational Effects of Prebiotic Oligosaccharides on Bifidobacterial Growth and Host Gene Expression in a Simplified Mixed Culture Model and Neonatal Mice. Br. J. Nutr. 2016, 116, 1−9. (9) Karav, S.; Le Parc, A.; de Moura, J. M. L. N.; Frese, S. A.; Kirmiz, N.; Block, D. E.; Barile, D.; Mills, D. A. Oligosaccharides Released from Milk Glycoproteins Are Selective Growth Substrates for InfantAssociated Bifidobacteria. Appl. Environ. Microbiol. 2016, 82, 3622− 3630. (10) Lim, E. S.; Wang, D.; Holtz, L. R. The Bacterial Microbiome and Virome Milestones of Infant Development. Trends Microbiol. 2016, 24, 801−810. (11) Bunyavanich, S.; Shen, N.; Grishin, A.; Wood, R.; Burks, W.; Dawson, P.; Jones, S. M.; Leung, D. Y.; Sampson, H.; Sicherer, S.; et al. Early-Life Gut Microbiome Composition and Milk Allergy Resolution. J. Allergy Clin. Immunol. 2016, 138, 1122−1130. (12) Charbonneau, M. R.; O’Donnell, D.; Blanton, L. V.; Totten, S. M.; Davis, J. C.; Barratt, M. J.; Cheng, J.; Guruge, J.; Talcott, M.; Bain, J. R.; et al. Sialylated Milk Oligosaccharides Promote MicrobiotaDependent Growth in Models of Infant Undernutrition. Cell 2016, 164, 859−871. (13) Brody, E. P. Biological Activities of Bovine Glycomacropeptide. Br. J. Nutr. 2000, 84, 39−46. (14) Puccio, G.; Alliet, P.; Cajozzo, C.; Janssens, E.; Corsello, G.; Sprenger, N.; Wernimont, S.; Egli, D.; Gosoniu, L.; Steenhout, P. Effects of Infant Formula with Human Milk Oligosaccharides on Growth and Morbidity: A Randomized Multicenter Trial. J. Pediatr. Gastroenterol. Nutr. 2017, 64, 624. (15) Barile, D.; Tao, N.; Lebrilla, C. B.; Coisson, J.-D.; Arlorio, M.; German, J. B. Permeate from Cheese Whey Ultrafiltration Is a Source of Milk Oligosaccharides. Int. Dairy J. 2009, 19, 524−530. (16) Zivkovic, A. M.; Barile, D. Bovine Milk as a Source of Functional Oligosaccharides for Improving Human Health. Adv. Nutr. 2011, 2, 284−289. (17) Barile, D.; Marotta, M.; Chu, C.; Mehra, R.; Grimm, R.; Lebrilla, C.; German, J. Neutral and Acidic Oligosaccharides in HolsteinFriesian Colostrum during the First 3 Days of Lactation Measured by High Performance Liquid Chromatography on a Microfluidic Chip and Time-of-Flight Mass Spectrometry. J. Dairy Sci. 2010, 93, 3940−3949. (18) Martín-Sosa, S.; Martín, M.-J.; Hueso, P. The Sialylated Fraction of Milk Oligosaccharides Is Partially Responsible for Binding to Enterotoxigenic and Uropathogenic Escherichia Coli Human Strains. J. Nutr. 2002, 132, 3067−3072. (19) Simon, P. M.; Goode, P. L.; Mobasseri, A.; Zopf, D. Inhibition of Helicobacter Pylori Binding to Gastrointestinal Epithelial Cells by Sialic Acid-Containing Oligosaccharides. Infect. Immun. 1997, 65, 750− 757. (20) Van Leeuwen, S. S.; Kuipers, B. J.; Dijkhuizen, L.; Kamerling, J. P. Comparative Structural Characterization of 7 Commercial GalactoOligosaccharide (GOS) Products. Carbohydr. Res. 2016, 425, 48−58. (21) Rycroft, C.; Jones, M.; Gibson, G.; Rastall, R. A Comparative in Vitro Evaluation of the Fermentation Properties of Prebiotic Oligosaccharides. J. Appl. Microbiol. 2001, 91, 878−887. (22) Wang, J.; Chen, C.; Yu, Z.; He, Y.; Yong, Q.; Newburg, D. S. Relative Fermentation of Oligosaccharides from Human Milk and Plants by Gut Microbes. Eur. Food Res. Technol. 2017, 243, 133−146. (23) Martin, F.-P. J.; Wang, Y.; Sprenger, N.; Yap, I. K. S.; Lundstedt, T.; Lek, P.; Rezzi, S.; Ramadan, Z.; van Bladeren, P.; Fay, L. B.; et al. Probiotic Modulation of Symbiotic Gut Microbial-Host Metabolic Interactions in a Humanized Microbiome Mouse Model. Mol. Syst. Biol. 2008, 4, 157−171. (24) Van Leeuwen, S. S.; Kuipers, B. J.; Dijkhuizen, L.; Kamerling, J. P. 1 H NMR Analysis of the Lactose Beta-Galactosidase-Derived GalactoOligosaccharide Components of Vivinal GOS up to DP5. Carbohydr. Res. 2014, 400, 59−73. (25) Crost, E. H.; Tailford, L. E.; Le Gall, G.; Fons, M.; Henrissat, B.; Juge, N. Utilisation of Mucin Glycans by the Human Gut Symbiont Ruminococcus Gnavus Is Strain-Dependent. PLoS One 2013, 8, 1−13.

Figure S6, adjusted optical density at 600 nm (OD600nm) of monocultures with B. longum subsp. longum, C. perfringens, and P. distasonis within the difference carbohydrate treatments; Figure S7, carbohydrate effect on pH within each bacterial monoculture; bars are mean values, and error bars represent standard error of the mean (SEM) (PDF)


Corresponding Author

*E-mail: [email protected] ORCID

Louise M. A. Jakobsen: 0000-0002-2631-7386 Ulrik K. Sundekilde: 0000-0003-4849-0996 Hanne C. Bertram: 0000-0002-1882-5321 Author Contributions

L.M.A.J., U.K.S., H.J.A., D.S.N., and H.C.B. designed the study. L.M.A.J. performed the experiments and analyzed the data. L.M.A.J., U.K.S., and H.C.B. drafted the manuscript. All authors contributed to the editing and revision of the manuscript as well as read and approved the final manuscript. Notes

The authors declare no competing financial interest. The raw 1H NMR data have been uploaded to

ACKNOWLEDGMENTS L.M.A.J. greatly acknowledges the excellent technical assistance provided by laboratory trainees Naja Stenberg Andersen and Mette Marie Arnt Schjelde. This work was funded by Arla Foods Amba and Aarhus University, as was part of L.M.A.J.’s Ph.D. project.


(1) Wang, M.; Li, M.; Wu, S.; Lebrilla, C. B.; Chapkin, R. S.; Ivanov, I.; Donovan, S. M. Fecal Microbiota Composition of Breast-Fed Infants Is Correlated with Human Milk Oligosaccharides Consumed. J. Pediatr. Gastroenterol. Nutr. 2015, 60, 825−833. (2) Laursen, M. F.; Andersen, L. B.; Michaelsen, K. F.; Mølgaard, C.; Trolle, E.; Bahl, M. I.; Licht, T. R. Infant Gut Microbiota Development Is Driven by Transition to Family Foods Independent of Maternal Obesity. Msphere 2016, 1, 1−16. (3) Sela, D. A.; Mills, D. A. Nursing Our Microbiota: Molecular Linkages between Bifidobacteria and Milk Oligosaccharides. Trends Microbiol. 2010, 18, 298−307. (4) Bäckhed, F.; Roswall, J.; Peng, Y.; Feng, Q.; Jia, H.; KovatchevaDatchary, P.; Li, Y.; Xia, Y.; Xie, H.; Zhong, H.; et al. Dynamics and Stabilization of the Human Gut Microbiome during the First Year of Life. Cell Host Microbe 2015, 17, 690−703. (5) Harmsen, H. J.; Wildeboer–Veloo, A. C.; Raangs, G. C.; Wagendorp, A. A.; Klijn, N.; Bindels, J. G.; Welling, G. W. Analysis of Intestinal Flora Development in Breast-Fed and Formula-Fed Infants by Using Molecular Identification and Detection Methods. J. Pediatr. Gastroenterol. Nutr. 2000, 30, 61−67. (6) Penders, J.; Vink, C.; Driessen, C.; London, N.; Thijs, C.; Stobberingh, E. E. Quantification of Bifidobacterium Spp., Escherichia Coli and Clostridium Difficile in Faecal Samples of Breast-Fed and Formula-Fed Infants by Real-Time PCR. FEMS Microbiol. Lett. 2005, 243, 141−147. (7) Bindels, L. B.; Delzenne, N. M.; Cani, P. D.; Walter, J. Towards a More Comprehensive Concept for Prebiotics. Nat. Rev. Gastroenterol. Hepatol. 2015, 12, 303−310. L

DOI: 10.1021/acs.jproteome.9b00211 J. Proteome Res. XXXX, XXX, XXX−XXX


Journal of Proteome Research (26) Van Leeuwen, S. S.; Schoemaker, R. J.; Gerwig, G. J.; van Leusenvan Kan, E. J.; Dijkhuizen, L.; Kamerling, J. P. Rapid Milk Group Classification by 1H NMR Analysis of Le and H Epitopes in Human Milk Oligosaccharide Donor Samples. Glycobiology 2014, 24, 728−739. (27) Kjeldahl, K.; Bro, R. Some Common Misunderstandings in Chemometrics. J. Chemom. 2010, 24, 558−564. (28) Cloarec, O.; Dumas, M. E.; Trygg, J.; Craig, A.; Barton, R. H.; Lindon, J. C.; Nicholson, J. K.; Holmes, E. Evaluation of the Orthogonal Projection on Latent Structure Model Limitations Caused by Chemical Shift Variability and Improved Visualization of Biomarker Changes in 1H NMR Spectroscopic Metabonomic Studies. Anal. Chem. 2005, 77, 517−526. (29) Ose, R.; Hirano, K.; Maeno, S.; Nakagawa, J.; Salminen, S.; Tochio, T.; Endo, A. The Ability of Human Intestinal Anaerobes to Metabolize Different Oligosaccharides: Novel Means for Microbiota Modulation? Anaerobe 2018, 51, 110−119. (30) Xu, J.; Mahowald, M. A.; Ley, R. E.; Lozupone, C. A.; Hamady, M.; Martens, E. C.; Henrissat, B.; Coutinho, P. M.; Minx, P.; Latreille, P.; et al. Evolution of Symbiotic Bacteria in the Distal Human Intestine. PLoS Biol. 2007, 5, 1574−1586. (31) Odamaki, T.; Kato, K.; Sugahara, H.; Hashikura, N.; Takahashi, S.; Xiao, J.; Abe, F.; Osawa, R. Age-Related Changes in Gut Microbiota Composition from Newborn to Centenarian: A Cross-Sectional Study. BMC Microbiol 2016, 16, 1−12. (32) Wiese, M.; Khakimov, B.; Nielsen, S.; Sørensen, H.; van den Berg, F.; Nielsen, D. S. CoMiniGuta Small Volume in Vitro Colon Model for the Screening of Gut Microbial Fermentation Processes. Peer J. 2018, 6, 1−22. (33) Hopkins, M.; Cummings, J.; Macfarlane, G. Inter-Species Differences in Maximum Specific Growth Rates and Cell Yields of Bifidobacteria Cultured on Oligosaccharides and Other Simple Carbohydrate Sources. J. Appl. Microbiol. 1998, 85, 381−386. (34) Idota, T.; Kawakami, H.; Nakajima, I. Growth-Promoting Effects of N-Acetylneuraminic Acid-Containing Substances on Bifidobacteria. Biosci., Biotechnol., Biochem. 1994, 58, 1720−1722. (35) Satoh, T.; Odamaki, T.; Namura, M.; Shimizu, T.; Iwatsuki, K.; Nishimoto, M.; Kitaoka, M.; Xiao, J. In Vitro Comparative Evaluation of the Impact of Lacto-N-Biose I, a Major Building Block of Human Milk Oligosaccharides, on the Fecal Microbiota of Infants. Anaerobe 2013, 19, 50−57. (36) Peacock, K. S.; Ruhaak, L. R.; Tsui, M. K.; Mills, D. A.; Lebrilla, C. B. Isomer-Specific Consumption of Galactooligosaccharides by Bifidobacterial Species. J. Agric. Food Chem. 2013, 61, 12612−12619. (37) Barboza, M.; Sela, D. A.; Pirim, C.; LoCascio, R. G.; Freeman, S. L.; German, J. B.; Mills, D. A.; Lebrilla, C. B. Glycoprofiling Bifidobacterial Consumption of Galacto-Oligosaccharides by Mass Spectrometry Reveals Strain-Specific, Preferential Consumption of Glycans. Appl. Environ. Microbiol. 2009, 75, 7319−7325. (38) Hopkins, M. J.; Macfarlane, G. T. Nondigestible Oligosaccharides Enhance Bacterial Colonization Resistance against Clostridium Difficile in Vitro. Appl. Environ. Microbiol. 2003, 69, 1920−1927. (39) Martin, F.-P. J.; Sprenger, N.; Yap, I. K.; Wang, Y.; Bibiloni, R.; Rochat, F.; Rezzi, S.; Cherbut, C.; Kochhar, S.; Lindon, J. C.; et al. Panorganismal Gut Microbiome- Host Metabolic Crosstalk. J. Proteome Res. 2009, 8, 2090−2105. (40) Endo, A.; Nakamura, S.; Konishi, K.; Nakagawa, J.; Tochio, T. Variations in Prebiotic Oligosaccharide Fermentation by Intestinal Lactic Acid Bacteria. Int. J. Food Sci. Nutr. 2016, 67, 125−132. (41) Martinic, A.; Barouei, J.; Bendiks, Z.; Mishchuk, D.; Heeney, D. D.; Martin, R.; Marco, M. L.; Slupsky, C. M. Supplementation of Lactobacillus Plantarum Improves Markers of Metabolic Dysfunction Induced by a High Fat Diet. J. Proteome Res. 2018, 17, 2790−2802. (42) Umu, Ö . C.; Rudi, K.; Diep, D. B. Modulation of the Gut Microbiota by Prebiotic Fibres and Bacteriocins. Microbial ecology in health and disease 2017, 28, 1−11. (43) Sánchez-Moya, T.; López-Nicolás, R.; Planes, D.; GonzálezBermúdez, C.; Ros-Berruezo, G.; Frontela-Saseta, C. In Vitro Modulation of Gut Microbiota by Whey Protein to Preserve Intestinal Health. Food Funct. 2017, 8, 3053−3063.

(44) Gibson, G. R.; Wang, X. Regulatory Effects of Bifidobacteria on the Growth of Other Colonic Bacteria. J. Appl. Bacteriol. 1994, 77, 412− 420. (45) Brook, I. Bacterial Interference. Crit. Rev. Microbiol. 1999, 25, 155−172. (46) Martinez, F. A. C.; Balciunas, E. M.; Converti, A.; Cotter, P. D.; de Souza Oliveira, R. P. Bacteriocin Production by Bifidobacterium Spp. A Review. Biotechnol. Adv. 2013, 31, 482−488. (47) Nakano, V.; Ignacio, A.; Fernandes, M. R.; Fukugaiti, M. H.; Avila-Campos, M. J. Intestinal Bacteroides and Parabacteroides Species Producing Antagonistic Substances. Microbiology 2006, 1, 61−64. (48) Bertram, H. C.; Jakobsen, L. M. A. Nutrimetabolomics: Integrating Metabolomics in Nutrition to Disentangle Intake of Animal-Based Foods. Metabolomics 2018, 14, 1−10. (49) De Leoz, M. L. A.; Kalanetra, K. M.; Bokulich, N. A.; Strum, J. S.; Underwood, M. A.; German, J. B.; Mills, D. A.; Lebrilla, C. B. Human Milk Glycomics and Gut Microbial Genomics in Infant Feces Show a Correlation between Human Milk Oligosaccharides and Gut Microbiota: A Proof-of-Concept Study. J. Proteome Res. 2015, 14, 491−502. (50) Issa, S. M.; Vitiazeva, V.; Hayes, C. A.; Karlsson, N. G. Higher Energy Collisional Dissociation Mass Spectrometry of Sulfated OLinked Oligosaccharides. J. Proteome Res. 2018, 17, 3259−3267. (51) Cederlund, A.; Kai-Larsen, Y.; Printz, G.; Yoshio, H.; Alvelius, G.; Lagercrantz, H.; Strömberg, R.; Jörnvall, H.; Gudmundsson, G. H.; Agerberth, B. Lactose in Human Breast Milk an Inducer of Innate Immunity with Implications for a Role in Intestinal Homeostasis. PLoS One 2013, 8, No. e53876. (52) Newburg, D. S.; Walker, W. A. Protection of the Neonate by the Innate Immune System of Developing Gut and of Human Milk. Pediatr. Res. 2007, 61, 2. (53) Wang, R.-F.; Cao, W.-W.; Cerniglia, C. E. PCR Detection and Quantitation of Predominant Anaerobic Bacteria in Human and Animal Fecal Samples. Appl. Environ. Microbiol. 1996, 62, 1242−1247. (54) Matsuda, K.; Tsuji, H.; Asahara, T.; Matsumoto, K.; Takada, T.; Nomoto, K. Establishment of an Analytical System for the Human Fecal Microbiota, Based on Reverse Transcription-Quantitative PCR Targeting of Multicopy rRNA Molecules. Appl. Environ. Microbiol. 2009, 75, 1961−1969. (55) Matsuda, K.; Tsuji, H.; Asahara, T.; Kado, Y.; Nomoto, K. Sensitive Quantitative Detection of Commensal Bacteria by rRNATargeted Reverse Transcription-PCR. Appl. Environ. Microbiol. 2007, 73, 32−39. (56) Huijsdens, X. W.; Linskens, R. K.; Mak, M.; Meuwissen, S. G. M.; Vandenbroucke-Grauls, C. M. J. E.; Savelkoul, P. H. M. Quantification of Bacteria Adherent to Gastrointestinal Mucosa by Real-Time PCR. J. Clin. Microbiol. 2002, 40, 4423−4427.


DOI: 10.1021/acs.jproteome.9b00211 J. Proteome Res. XXXX, XXX, XXX−XXX