dMissing value category omitted (included in FDR correction).

eDue to multicollinearity both regular intake of organic milk and regular intake of organic yogurt were included in separate models, which included all other variables as listed in this table.

fSignificant association after correction for FDR by Benjamini-Hochberg procedure, also indicated in bold.

produce methane from hydrogen (Gaci et al., 2014). Moreover, colonization by M. smithii and M. stadtmanae might originate from different environmental sources, which could explain their different prevalence. Factors that play a role in the acquisition of methanogenic archaea are largely unknown. However, the environment is assumed to play a crucial role in gut colonization. This view is strengthened by a twin study that indicated that not genetic factors, but shared and unique environmental factors were of importance for the occurrence of methanogens in humans (Florin et al., 2000). The prospective design and long-term follow-up allowed us to examine a wide range of environmental, dietary and life-style associated determinants throughout childhood. Out of the determinants present during infancy, caesarean section compared to vaginal delivery at home, first exposure to antibiotics in the 2nd year of life compared to

no antibiotic treatment during the first 2 years and organic fruit consumption were associated with increased odds of colonization by M. stadtmanae. These findings on M. stadtmanae in the present study need however to be interpreted with great care. Due to the small group of children colonized by M. stadtmanae (n = 39), models for M. stadtmanae were prone to instability. Therefore, these factors need to be verified in other studies with, preferably, larger sample sizes. In particular, the association with birth mode is in contrast with previous findings that intestinal colonization by methanogenic archaea in neonates and infants is very rare (Palmer et al., 2007). However, it could be postulated that the pioneer species associated with caesarian section delivery drive a subsequent colonization pattern that is more favorable for the establishment of M. stadtmanae at a later stage. As such, it is important to study the co-occurrence and co-exclusion of archaea and bacterial taxa in future studies, in order to identify microbial networks that might favor archaeal colonization.

Although one previous study found females to be more often colonized by methanogenic archaea than males (Florin et al., 2000), the current view is that there is no association between methanogenic archaea and gender (Dridi et al., 2011b). In this study, we assessed fecal samples of 244 (51.7%) males and 228 (48.3%) females. Of all males under study 187 (76.6%) were colonized by M. smithii, while 182 (79.8%) females were colonized by M. smithii. Furthermore, 19 (7.8%) males were colonized by M. stadtmanae. This was similar to the colonization by M. stadtmanae in females, as 20 (9.6%) females were colonized. Moreover, we also did not find an association between gender and either M. smithii or M. stadtmanae.

So far, only one study assessed potential carriers of archaea in food, but yogurt and milk have not been assessed herein (Brusa et al., 1998). The present study suggests an association between dietary factors and archaeal colonization, as organic yogurt and milk were significantly associated with the presence of M. smithii. Due to the high correlation between organic milk and yogurt intake, we were however not able to disentangle whether only organic milk or organic yogurt or both were truly responsible for the association with M. smithii during multivariable analyses.

Cheese was however not associated with M. smithii colonization, which is in line with previous findings where no M. smithii or M. stadtmanae were detected in different types of cheese (Brusa et al., 1998). Analyses on the number of dairy products consumed, used to address multicollinearity, indicated that the consumption of multiple different dairy products might be associated with an increased M. smithii presence.

A well-known carrier of M. smithii and M. stadtmanae is the rumen of beef and cows (Carberry et al., 2014; Cersosimo et al., 2016). Therefore, it is likely that products derived from cows, such as dairy products, may contain some of these taxa, which was reflected in our results. Moreover, these specific methanogenic archaea have also been found in soil which could be the route of origin to cows as revealed from the Integrated Microbial Next Generation Sequencing database (Lagkouvardos et al., 2016). The archaeal presence in soil might be the underlying reason that especially organic products were associated with colonization. Organic cows have more outdoor access compared to conventionally farmed cows and could therefore have increased archaea uptake. Additionally, drugs for organic cows are less prescribed whereas conventional cows more often receive antibiotics to prevent microbial infections (Zwald et al., 2004). Methanogens are susceptible to antibiotics such as bacitracin, a commonly used antibiotic in cattle, which might eliminate them (Dridi et al., 2011a). Although the screening of multiple dairy products indicated the presence of M. smithii in both conventional and organic dairy products, the latter could alternatively explain the lack of association of consumption of conventional dairy products with M. smithii colonization within our cohort study.

As the culture-independent techniques applied in the present study do not distinguish viable microbes from cell-free DNA originating from lysed microorganisms, we cannot completely exclude that dairy products only contain archaeal DNA instead of viable archaea. However, we used the concentrated pellet of the microbial cells for downstream analyses of milk products, thereby minimizing the detection of circulating cell-free DNA. It is therefore likely that a living fraction of archaeal cells has been measured.

For milk, the typical neutral pH is viable for both M. smithii and M. stadtmanae, which favor an optimal pH of 6.9–7.4 whereas yogurt has a more acidic environment (Miller and Lin, 2002; Ledenbach and Marshall, 2009; Dridi et al., 2011b), which might explain why we could not detect methanogenic archaea in yogurt samples. In addition, methanogens have been discovered in a wide variety of extreme environments with temperatures until at least 100◦C (Elias et al., 1999; Tung et al., 2005). The latter might indicate that these microbes could resist heat treatments and pasteurization performed for milk products. All in all, this strengthens the possibility that viable methanogenic archaea could indeed be present in milk products, even after thermal processing.

To get definite prove that milk products are a source of archaea, future studies using either culture-based methods or molecular methods that enable differentiation between intracellular and cell-free DNA, such as the use of propidium monoazide (PMA) as a membrane impermeable DNA intercalating dye (Janssen et al., 2016), are warranted. Several studies already identified living bacteria with an implemented PMA-assay in both human feces and processed milk (Bae and Wuertz, 2009; Soejima et al., 2012; Quigley et al., 2013; Cangelosi and Meschke, 2014).

In conclusion, dairy products, in particular organic milk products, may play an influential role in the colonization of the gut by M. smithii in children. Moreover, M. smithii seems to be present in both raw and commonly consumed milk products. For the first time, a large variety of determinants have been explored in association with gut colonization by methanogenic archaea. Although more information is needed to confirm and unravel the mechanisms of archaeal colonization in more detail, it may provide new targets for prevention of diseases associated with the presence of methanogenic archaea.

#### AUTHOR CONTRIBUTIONS

Jv performed the analyses on the cohort, and wrote partly the manuscript together with Nv. Nv designed the laboratory

#### REFERENCES

experiments, performed laboratory isolation, and qPCR techniques on milk products, analyzed the genomic data, and wrote partly the final manuscript as submitted. CM performed the laboratory isolation of fecal DNA and qPCR techniques, data processing, and approved the final manuscript as submitted. JP contributed to the design of the study and collection of the data, supervised the laboratory work, interpreted the data, critically reviewed the manuscript, and approved the final manuscript as submitted. MM contributed to the design of the study and collection of the data, interpreted the data, critically reviewed the manuscript and approved the final manuscript as submitted. CT and IA contributed to the design of the study and collection of the data, critically reviewed and revised the manuscript and approved the final manuscript as submitted. PS and MH critically reviewed and revised the manuscript and approved the final manuscript as submitted.

#### FUNDING

This work was supported by TI Food and Nutrition, public private partnership in food and nutrition research. The mission is to contribute to optimum human nutrition, food safety, and sustainable food production and to increase the competitiveness of the food industry. Partners are key players in the global food industry, leading research institutes, universities, and medical centers. Additional funding for data collection was received from: Netherlands Organization for Health Research and Development (grant 2100.0090), Netherlands Asthma Foundation (grants <IP_ADDRESS>, <IP_ADDRESS>), Netherlands Heart Foundation (grant 2008B112), Triodos Foundation, Phoenix Foundation, Raphaël Foundation, Iona Foundation, Foundation for the Advancement of Heilpedagogiek, Royal Friesland Foods (currently FrieslandCampina), Netherlands Sugar Foundation, and the Ministry of Economic Affairs. The sponsors had no influence on the analysis and reporting of this study. This work has also been supported by the Deutsche Forschungsgemeinschaft (Ho2236/8-1 and Priority Program 1656 to MH) and by ZonMW/JPI HDHL Intestinal Microbiomics (grant 50-52905-98-599 to JP).

#### SUPPLEMENTARY MATERIAL

The Supplementary Material for this article can be found online at: http://journal.frontiersin.org/article/10.3389/fmicb. 2017.00355/full#supplementary-material

stadtmanae in inflammatory bowel diseases. PLoS ONE 9:e87734. doi: 10.1371/journal.pone.0087734

reported antimicrobial usage on conventional and organic dairy farms. J. Dairy Sci. 87, 191–201. doi: 10.3168/jds.S0022-0302(04) 73158-6

**Conflict of Interest Statement:** The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Copyright © 2017 van de Pol, van Best, Mbakwa, Thijs, Savelkoul, Arts, Hornef, Mommers and Penders. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

# First Foods and Gut Microbes

Martin F. Laursen1 , Martin I. Bahl1 , Kim F. Michaelsen2 and Tine R. Licht1 \*

1 National Food Institute, Technical University of Denmark, Søborg, Denmark, 2 Department of Nutrition, Exercise and Sports, University of Copenhagen, Frederiksberg, Denmark

The establishment of the human gut microbiota in early life has been associated with later health and disease. During the 1st months after birth, the microbial composition in the gut is known to be affected by the mode of delivery, use of antibiotics, geographical location and type of feeding (breast/formula). Consequently, the neonatal period and early infancy has attracted much attention. However, after this first period the gut microbial composition continues to develop until the age of 3 years, and these 1st years have been designated "a window of opportunity" for microbial modulation. The beginning and end of this window is currently debated, but it likely coincides with the complementary feeding period, marking the gradual transition from milk-based infant feeding to family diet usually occurring between 6 and 24 months. Furthermore, the 'first 1000 days,' i.e., the period from conception until age 2 years, are generally recognized to be of particular importance for the healthy development of children. While dietary changes are known to affect the adult gut microbiota, there is a gap in our knowledge on how the introduction of new dietary components into the diet of infants/young children affects the gut microbiota development. This perspective paper summarizes the currently very few studies addressing the effects of complementary diet on gut microbiota, and highlights the recent finding that transition to family foods greatly impacts the development of gut microbial diversity. Further, we discuss potential impacts on child health and the need for further studies on this important topic.

#### Edited by:

Maria Carmen Collado, Consejo Superior de Investigaciones Científicas (CSIC), Spain

#### Reviewed by:

M. Pilar Francino, Valencian Health Department, Spain Clara G. De Los Reyes-Gavilan, Consejo Superior de Investigaciones Científicas (CSIC), Spain

#### \*Correspondence:

Tine R. Licht<EMAIL_ADDRESS>
#### Specialty section:

This article was submitted to Food Microbiology, a section of the journal Frontiers in Microbiology

Received: 05 December 2016 Accepted: 21 February 2017 Published: 06 March 2017

#### Citation:

Laursen MF, Bahl MI, Michaelsen KF and Licht TR (2017) First Foods and Gut Microbes. Front. Microbiol. 8:356. doi: 10.3389/fmicb.2017.00356 Keywords: infant gut microbiota, breast feeding, weaning, gut microbial diversity, complementary diet, transition, SKOT cohorts, family foods

#### WHAT DO WE KNOW ABOUT COMPLEMENTARY FEEDING AND GUT MICROBIOTA DEVELOPMENT?

The differential effect of breastfeeding as compared with formula feeding or mixed feeding on the composition of the gut microbiota is well established (Penders et al., 2006; Fallani et al., 2010; Bergström et al., 2014; Jost et al., 2015). However, what happens to the gut microbiota when the first solid foods are introduced and gradually replace the milk-based diet has only scarcely been addressed. Longitudinal studies with repeated sampling in a limited number of infants have indicated that microbial composition changes significantly around the period of introduction to solid foods and cessation of breastfeeding/formula feeding (Favier et al., 2002; Wang et al., 2004; Amarri et al., 2006; Roger and McCartney, 2010; Koenig et al., 2011; Thompson et al., 2015). We have previously monitored the fecal microbiota of 330 Danish children participating in the study designated 'SKOT,' at age 9, 18, and 36 months. It was evident that Lactobacillaceae, Bifidobacteriaceae, Enterococcaceae, and Enterobacteriaceae abundance decreased while Lachnospiraceae, Ruminococcaceae, and Bacteroidaceae species increased during the period

from 9 to 18 months, i.e., during the period characterized by transition from milk-based feeding to family diet (Bergström et al., 2014). This was largely in agreement with a European study including 531 infants from five different countries demonstrating that consistent compositional changes (decrease in Bifidobacteriaceae, Enterobacteriaceae, Clostridiaceae while increase in Ruminococcaceae and Lachnospiraceae species) occurred from 6 weeks of age until 4 weeks after the introduction of solid foods, irrespectively of differences in geographic location, use of antibiotics, mode of delivery (vaginal or C-section) and milk feeding practices (Fallani et al., 2011). Recently Thompson et al. (2015) found increased gut microbial diversity of both exclusively breastfed infants (n = 4) and mixed-fed infants (n = 5) after introduction of solid foods.

The general challenge in longitudinal studies is to differentiate between the effects caused by advancing age (leading to increased exposure to environmental microbes and increased maturity of the gut) and effects induced directly by dietary changes. In order to address this issue, we recently combined a comprehensive analysis of the complementary diet with 16S rRNA gene sequence analysis of the fecal microbiota in two independent Danish cohorts of infants aged 9 months, participating in the previously mentioned SKOT study, and demonstrated that gut microbial diversity correlated significantly with the child's progression toward family foods in both cohorts (Laursen et al., 2016). A Principal Component Analysis of the complete infant dietary records at 9 months, including 23 food groups (recorded in g/day/kg body weight) was performed. The first principal component was defined as "Family Food," since it described the transition from early infant foods, with high content of breastmilk, formula and porridge (low loadings), to family foods introduced during late infancy (high loadings), with high content of meat, milk, cheese, animal fat and rye bread (type of bread commonly used in complementary feeding in Denmark) (**Figure 1A**). We found separately in both cohorts (Laursen et al., 2016), as well as for the compiled data set (n = 217), that the family food parameter was strongly associated with the Shannon index, a commonly used measure of alpha diversity (e.g., within-sample complexity) of the gut microbiota (**Figure 1B**). Other measures of alpha diversity, namely microbial richness (Observed genera) and evenness (Pielou's evenness index) were strongly associated with the progression to family foods, indicating that both the number of different microbes (richness) and the balance between these (evenness) are affected by this progression (**Figure 1C**). These associations seem to be driven both by the cessation of breastfeeding and by the introduction of food items with higher fiber and protein content, such as rye bread, cheese and meat products, as evidenced from a hierarchical clustering of correlation coefficients between dietary factors and alpha diversity metrics from the compiled data set (**Figure 1C**). Further, progression toward family foods at the of age 9 months was negatively associated with abundances of Bifidobacterium, Enterococcus, Enterobacteriaceae (Escherichia, Kluyvera) and to a lesser degree with Clostridiaceae (Clostridium sensu stricto), but positively associated with abundances of several different bacterial genera (**Figure 1D**), most of them within Lachnospiraceae (Blautia, Roseburia, Pseudobutyrivibrio, Dorea, Coprococcus, Lachnospiraceae incertae sedis) and Ruminococcaceae (Faecalibacterium and Ruminococcus), confirming the previous observations from the SKOT cohort (Bergström et al., 2014) as well as other study populations (Fallani et al., 2011; Thompson et al., 2015). Indeed, the relative abundance of species within Lachnospiraceae and Ruminococcaceae increases when dietary fibers from rye bread (arabinoxylans) or protein from dairy/cheese (casein) and meat are included in the diet (Walton et al., 2012; Zhu et al., 2015). Thus, the introduction of these food components may provide selective advantages for specific microbes to establish in the gut, which will increase alpha diversity. However, we also observed in our cohort studies that the duration of exclusive breastfeeding (range 0–6 months) was more determining for microbial diversity at the age of 9 months than the time of first introduction of solid foods (range 3–6 months), reflecting the dominating impact of breastfeeding (Laursen et al., 2016). To further elucidate the influence of breastfeeding in relation to the effect of complementary diet, we performed a subanalysis, stratifying the infants by breastfeeding status (defined as at least 1 breastfeeding per day at age 9 months), and correlating the dietary parameters with gut microbial alpha diversity (**Figure 1E**). Protein, fiber and progression toward family foods were positively correlated with the Shannon index in both subsets, indicating that these associations occurred independently of breastfeeding. Interestingly, while meat, cheese and rye bread represented the specific dietary groups most strongly correlated to diversity in the complete dataset (n = 217) and in the subset of infants no longer breastfed (n = 145), porridge (primarily oatmeal, the most common type of porridge used in complementary feeding in Denmark) was most strongly correlated to diversity in the subset of infants still breastfed at 9 months (n = 72). Oatmeal is rich in dietary fibers such as β-glucans, which can be utilized by gut microbes (Hughes et al., 2008). Our results suggest that while infants are still breastfed, porridge is the dietary factor contributing most to gut microbial diversity, whereas when infants are no longer breastfed, consumption of cheese, meat and rye bread is more important. Formula intake was positively associated with diversity in the breastfed infant subset (**Figure 1E**), supporting the previous observations that mixed-fed infants have higher microbial diversity than exclusively breastfed infants (Thompson et al., 2015). Oppositely, formula feeding was negatively associated with diversity in the infants that were no longer breastfed, indicating that the substitution of formula with solid foods such as meat, cheese and rye bread further increase microbial diversity (**Figure 1E**). Together, these results suggest that effects on gut microbial composition and diversity during the complementary feeding period is not solely mediated by weaning/cessation of breastfeeding, but indeed affected by the introduction of new specific complementary foods with higher protein and fiber content.

The development of the intestinal microbiota is affected by a number of factors including geography, lifestyle and oligosaccharide content of the breastmilk. Although the microbial succession in the infant gut thus greatly varies among individual infants, the general picture emerging

FIGURE 1 | (A) PCA loading plot of the 23 food groups (grams per day per kilogram body weight), with the fist principal component defined as family food, describing the transition from early infancy foods to family foods. (B) Pearson's correlation between family food and the Shannon index of alpha diversity. (C) Heatmap illustrating hierarchical clustering of correlation coefficients between dietary parameters and alpha diversity metrics. (D) Heatmap illustrating correlation coefficients between family food and gut microbial genera showing a p-value below 0.1. (E) Heatmap illustrating hierarchical clustering of correlation coefficients between dietary parameters and Shannon index in partially breastfed (n = 72) and weaned (n = 145) infants aged 9 months. Color key applies to panel (C–E) and represents correlation coefficients of Spearman's rank/Pearson's correlations. Statistical significance is indicated by #p = 0.05, ∗p < 0.05, ∗∗p < 0.01, ∗∗∗p < 0.001. The figure is based on previously published data (Laursen et al., 2016).

(**Figure 2**) is that breast milk keeps the gut microbiota in a state characterized by a high relative abundance of Bifidobacterium (with lower abundance of other breast milk associated bacteria such as Veillonellaceae, Enterococcaceae, Lactobacillaceae, Enterobacteriaceae, and Streptococcaceae) accompanied by low diversity, and that these characteristics are affected only to a limited degree by mixed feeding and introduction of the first solid foods as long as the child is still partially breastfed (Roger and McCartney, 2010; Bäckhed et al., 2015; Laursen et al., 2016). However, as complementary feeding progresses, the gut microbial composition changes (increase in the diverse groups of Lachnospiraceae and Ruminococcaceae species and decrease of Bifidobacterium, Enterobacteriaceae, Enterococcaceae, Lactobacillaceae, Veillonellaceae, Clostridiaceae) and total diversity increases (Favier et al., 2002; Roger and McCartney, 2010; Laursen et al., 2016), probably as a result of the increased fiber and protein content of the diet (Laursen et al., 2016). Finally, cessation of breastfeeding/formula feeding and complete transition to family food marks another important event in gut microbial development (Favier et al., 2002; Roger and McCartney, 2010; Bäckhed et al., 2015), characterized by an increased abundance of Bacteroidaceae, Lachnospiraceae, and Ruminococcaceae and a further reduction in Bifidobacterium as well as increased alpha diversity (Roger and McCartney, 2010; Bergström et al., 2014; Bäckhed et al., 2015).

#### WHAT DOES IT MATTER FOR CHILD HEALTH?

The consistently observed increase in gut microbial alpha diversity during the time period coinciding with complementary feeding (Yatsunenko et al., 2012; Kostic et al., 2015; Avershina et al., 2016) and recent evidence showing that this increase is driven by transition from breastfeeding to family foods (Laursen et al., 2016), raise some key questions: Is the low diversity sustained by breastfeeding beneficial for infant health? Does the increase in microbial diversity observed during complementary feeding characterize healthy gut microbiota development?

Many studies have linked low gut microbial diversity to diseases in adulthood as recently reviewed (Mosca et al., 2016). Conditions associated with low gut microbiota diversity range from gastrointestinal pathologies such as Crohn's disease, ulcerative colitis, irritable bowel syndrome and colorectal cancer to metabolic disorders including obesity, type 2 diabetes, as well as neurological conditions such as autism (Mosca et al.,

2016). Recent studies reveal that an important determinant of high microbial diversity in adult fecal samples is a long intestinal transit time (Vandeputte et al., 2015; Falony et al., 2016; Roager et al., 2016). In this context, we have recently proposed that a high microbial richness and diversity may not imply per se a healthy gut microbial ecosystem, as longer transit times are significantly associated with increased bacterial protein degradation, which results in potentially detrimental bacterial metabolites (Roager et al., 2016). During the complementary feeding period, transition to family foods implies increased protein and fiber intake, which increases microbial diversity (Laursen et al., 2016). While the implications of this transition on intestinal transit time are not known, bowel movement frequency is generally reported not to change significantly during the weaning period (Tunc et al., 2008).

In infants, the major determinant of a low microbial diversity is probably breast milk (Azad et al., 2013a; Thompson et al., 2015; Laursen et al., 2016), which selects efficiently for specific bacterial species capable of degrading particular oligosaccharides present in breastmilk, the so-called human milk oligosaccharides (HMOs). HMO-degrading species include B. bifidum, B. longum ssp. infantis and to a lesser degree B. breve (Sela and Mills, 2010), while, noteworthy, bifidobacterial species common in the adult gut (e.g., B. adolescentis) do not share the capacity to degrade HMOs (Sela and Mills, 2010). In vitro studies suggest that the infant-type bifidobacteria play an important role in the maturation of the child's immune system (Underwood et al., 2014). In line with this, breastfeeding promotes several health effects that are likely to be caused by an improved immune response, such as a reduced incidence of childhood infections (Victora et al., 2016). This suggests that the predomination of infant-type bifidobacteria, implying a low bacterial diversity during breastfeeding, is beneficial for child health. In contrast, some health disorders have been linked to a reduced microbial diversity in early life. Examples include development of eczema (Forno et al., 2008; Wang et al., 2008; Abrahamsson et al., 2012; Ismail et al., 2012) and asthma (Abrahamsson et al., 2014), which have been linked to low microbial diversity in very early life (age 1 week – 4 months). Additionally, in children aged 18–24 months, low microbial diversity has been shown to be a risk factor for development of type 1 diabetes (Giongo et al., 2010; Kostic et al., 2015). Importantly, the low microbial diversity in these studies was not coupled to Bifidobacterium abundance and no negative effects of breastfeeding on prevalence of asthma, allergies or development of type 1 diabetes have been reported (Victora et al., 2016). Thus, even though early life low microbial diversity seems to be associated with diseases later in childhood, this is not likely to be caused by Bifidobacterium predominance or prolonged breastfeeding. Importantly, the microbial taxa that are absent or otherwise driving low diversity in the above-mentioned studies and their causality to diseases remain to be identified. Some studies suggest that an insufficiently developed microbial community in the gut can be "repaired," e.g., it has recently been demonstrated that an immature gut microbiota of stunted children aged 6 months, which is within the aforementioned window of opportunity, may at this age be repaired by introduction of adult-like microbes such as Ruminococcus gnavus and Clostridium symbiosum, both belonging to the Lachnospiraceae (Blanton et al., 2016), a microbial family greatly increasing during introduction of family foods (Laursen et al., 2016). The normally observed development across human populations is an increasing microbial diversity with age during the first 3 years of life (Yatsunenko et al., 2012) and probably characterizes a healthy development. While proteins and fibers were found to increase gut microbial diversity (Laursen et al., 2016), a high-protein intake in the complementary feeding period may increase the risk of obesity later in life (Lind et al., 2017), and defining recommendations for fiber intake in early life is equally challenging (Aggett et al., 2003; Zalewski et al., 2015). Consequently, even though gut microbial diversity increases with protein and fiber intake during the complementary feeding period, there is no evidence to support that excessive intake of these macronutrients in early childhood is beneficial for child health.

In summary, we want to emphasize that findings regarding the diversity of the intestinal microbiota in adults cannot be extrapolated to children, since the factors governing the codevelopment of the microbial ecosystem and the immune system in infanthood are completely different from the factors of importance for adult health. A low diversity of the infant gut microbiota in early life must thus be expected to characterize a healthy gut, if caused by breastfeeding. However, later progression into a diverse gut microbiota during childhood seems to be a fundamental part of the natural succession of the gut ecosystem and characterizes healthy development. One of the main challenges remaining is to identify more accurately the best timing of breastfeeding cessation and of introduction of family foods. This timing is influenced by many other factors than the microbiota, and is likely to be determined by the level of maturation of the infant's immune system.

#### WHAT IS NEEDED TO EXPAND OUR KNOWLEDGE ON COMPLEMENTARY DIET AND GUT MICROBES?

Until now, only a few studies have performed dietary assessment during the complementary feeding period and compared this with gut microbiota development. To decipher the effects of specific food components on gut microbial development, detailed assessments of the complementary diet constituents are needed. If food frequency questionnaires (FFQ) are used, they should be validated before application to minimize the risk of over/underestimation because they are prone to recall bias. Additionally, it should be considered that FFQs are generally developed to depict long-term or habitual diets, which may not be appropriate during a period of rapid dietary changes. Twentyfour hour dietary recalls are less prone to recall bias, but do not capture day-to-day variations in the diet. The most detailed and accurate results are obtained from food records for periods of 5–7 days since they collect actual intake information from a specific short-term period and are not associated with recall bias (Shim et al., 2014). Validated food records that minimize the risk of under/overestimation were used in our SKOT cohort

studies, and because they were conducted during the time period of fecal sample collection, they allowed us to directly assess the impact of the complementary diet on gut microbiota composition (Laursen et al., 2016). Ideally, longitudinal studies should include several diet recordings across the complementary feeding period to capture the individual dynamics during this period of multiple dietary changes.

To capture changes in the gut microbiota, either 16S rRNA amplicon or shot-gun based community sequencing can provide detailed information of the entire microbial community, while shot-gun based sequencing additionally provides direct information on the functional capacity of the bacterial population. However, while these methods generate a large amount of useful data, they lack enough sensitivity for low abundant microbial species. Therefore, complementing these techniques with quantitative PCR approaches and culturebased approaches provide better sensitivity, but are more laborious and time consuming. To minimize confounding effects on the gut microbiota in cross sectional studies, accurate standardization of the age of infants at which the samples are taken is highly desirable. Additionally, it is important to consider adjustments for other factors known to affect infant gut microbiota, including antibiotic intake, C-section, childcare/daycare, geographical location, family environment and exposure to pets and siblings (Yatsunenko et al., 2012; Azad et al., 2013b; Laursen et al., 2015; Thompson et al., 2015; Martin et al., 2016; Yassour et al., 2016). In order to establish causal relationships between specific components of the complementary diet and gut microbial composition, intervention studies are required. This could be done by performing short-term intervention studies, where the effect of specifically designed differences in dietary composition can be tested. Inclusion of the above-mentioned factors in the design of future studies will enable us to expand our knowledge on the impact of the complementary diet on the infant gut microbiota.

#### SUMMARIZING REMARKS

The very first nutrition most infants receive, breastmilk, keeps the microbiota in a state characterized by low diversity and Bifidobacterium domination, which is likely to be beneficial for

#### REFERENCES

child health. Introduction of complementary feeding and the transition to family foods increase gut microbial diversity and is accompanied by an increase of adult-associated microbes belonging to the families Lachnospiraceae and Ruminococcaceae. This increase in diversity occurs across different human populations and is likely to characterize a normal and healthy development of the gut microbiota, since perturbation of the process has been linked to an increased risk of diseases later in life. An important remaining challenge is to determine the optimal age for increasing intestinal microbial diversity by reduction of breastfeeding and introduction of family foods in order to optimize effects on gut microbiota, immune maturation and later health outcomes.

# ETHICS STATEMENT

The present perspective uses data from previous publications based on the SKOT cohorts, in which 311 (SKOT I) and 184 (SKOT II) Danish children were followed for the first 3 years after birth, with the overall aim of investigating relationships between early diet, growth development, and later disease risks, especially obesity and metabolic syndrome. The study protocols were approved by the Committees on Biomedical Research Ethics for the Capital Region of Denmark (H-KF-2007-0003 and H-3- 2010-122).

# AUTHOR CONTRIBUTIONS

ML, MB, KM, and TL conceived the idea for this perspective, and all contributed to the outline. All four authors were significantly involved in the studies resulting in the data presented in **Figure 1**. ML drafted the manuscript and the figures. All authors contributed to the writing, and approved the final manuscript.

# FUNDING

The work that formed the main basis for the discussions in this perspective paper was funded by the Danish Strategic Research Council, Grant numbers 0603-00579B (ProbiComp) and 0603- 00487B (Center for Gut, Grain, and Greens).

Zhu, Y., Lin, X., Zhao, F., Shi, X., Li, H., Li, Y., et al. (2015). Meat, dairy and plant proteins alter bacterial composition of rat gut bacteria. Sci. Rep. 5:15220. doi: 10.1038/srep15220

**Conflict of Interest Statement:** The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Copyright © 2017 Laursen, Bahl, Michaelsen and Licht. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

# Intestinal Microbiota and Weight-Gain in Preterm Neonates

Silvia Arboleya1 †, Pablo Martinez-Camblor 2, 3, Gonzalo Solís 4 , Marta Suárez 4 , Nuria Fernández 4, 5, Clara G. de los Reyes-Gavilán1 and Miguel Gueimonde1 \*

1 Department of Microbiology and Biochemistry of Dairy Products, Instituto de Productos Lácteos de Asturias (CSIC) Villaviciosa, Spain, 2 Geisel School of Medicine at Dartmouth, Dartmouth College, Hanover (NH), USA, 3 Universidad Autónoma de Chile, Santiago, Chile, 4 Pediatrics Service, Hospital Universitario Central de Asturias, Servicio de Salud del Principado de Asturias (SESPA), Oviedo, Spain, 5 Pediatrics Service, Hospital de Cabueñes, Servicio de Salud del Principado de Asturias (SESPA), Gijón, Spain

#### Edited by:

Christophe Lacroix, ETH Zurich, Switzerland

#### Reviewed by:

Marcela Carina Audisio, Instituto de Investigaciones para la Industria Química-CONICET, Argentina Maria De Los Angeles Serradell, Instituto de Ciencias de la Salud-Universidad Nacional Arturo Jauretche (UNAJ), Argentina

#### \*Correspondence: Miguel Gueimonde

<EMAIL_ADDRESS>
#### † Present Address:

Silvia Arboleya, APC Microbiome Institute, University College Cork, Teagasc Food Research Centre, Moorepark, Fermoy, Cork, Ireland

#### Specialty section:

This article was submitted to Food Microbiology, a section of the journal Frontiers in Microbiology

Received: 22 November 2016 Accepted: 25 January 2017 Published: 08 February 2017

#### Citation:

Arboleya S, Martinez-Camblor P, Solís G, Suárez M, Fernández N, de los Reyes-Gavilán CG and Gueimonde M (2017) Intestinal Microbiota and Weight-Gain in Preterm Neonates. Front. Microbiol. 8:183. doi: 10.3389/fmicb.2017.00183 The involvement of the gut microbiota on weight-gain and its relationship with childhood undernutrition and growth has been reported. Thus, the gut microbiota constitutes a potential therapeutic target for preventing growth impairment. However, our knowledge in this area is limited. In this study we aimed at evaluating the relationship among early microbiota, growth, and development in preterm infants. To this end we assessed the levels of specific microorganisms by qPCR, and those of short chain fatty acids by mean of gas-chromatography, in feces from 63 preterm newborns and determined their weight-gain during the first months. The statistical analyses performed indicate an influence of the intestinal microbiota in weight-gain, with the levels of some microorganisms showing a significant association with the weight-gain of the infant. The levels of specific microbial groups during the first days of life were found to affect weight gain by the age of 1 month. Moreover, clustering of the infants on the basis of the microbiota composition at 1 month of age rendered groups which showed differences in weight z-scores. Our results suggest an association between the gut microbiota composition and weight-gain in preterm infants at early life and point out potential microbial targets for favoring growth and maturation in these infants.

Keywords: newborn, premature-infant, weight-gain, colonization, microbiota, probiotics

# INTRODUCTION

Microbial colonization of the neonatal gut provides a stimulus necessary for the development of the intestine and the physiological homeostasis (Hooper and Macpherson, 2010; Sommer and Bäckhed, 2013). The early neonatal period represents the most important moment for this microbiotainduced maturation of the host, being a key determinant for later health (El Aidy et al., 2013). This neonatal colonization is affected by several factors such as gestational age, mode of delivery, antibiotic use, or feeding habits (Faa et al., 2013).

From the pioneering studies showing a reduction of Bacteroidetes and an increase of Firmicutes in obese animals (Ley et al., 2005), and the mechanistic works demonstrating the involvement of the gut microbiota in the regulation of food energy harvesting, fat storage and modulation of the endocrine function (Bäckhed et al., 2004; Cardinelli et al., 2015), the role of the microbiota in weight-gain has attracted increasing attention (Cardinelli et al., 2015). The modulation of the gut microbiota offers a potential therapeutic target for both, weight-management (Dror et al., 2017) and prevention of growth impariment (Blanton et al., 2016). Most data on the relationship between microbiota and weight-gain come from animal models or from studies in adults. Epidemiologycal data in infants are also available, evidencing associations between microbiota composition and later obesity (Koleva et al., 2015). However, these studies have focused on full-term infants and this interaction has not been explored in other populations, such as preterm babies, where weight-gain may be an indicator of maturation and positive outcome.

Preterm infants present an immature immune system and gut barrier, which leads to an increased disease risk. Moreover, the process of microbiota establishment is altered in these infants, who harbor more Enterobacteriaceae and potential pathogens and less commensals than full-terms (Arboleya et al., 2012, 2015). In these infants the nutritional goal is achieving a weight-gain and body composition approximating the fetal intrauterine growth (Brennan et al., 2016). For this reason, the adjustment of the preterm infant growth to the growth-tables, calculated from data on patients born at various gestational ages, is widely used to estimate newborn size and postnatal evolution (Fenton and Kim, 2013). This adjustment would be a positive nutritional outcome but it is difficult to achieve. Thus, developing strategies to enhance growth and maturation of preterm infants could be of clinical interest. Given the relationship between microbiota and weight-gain, the gut microbiota establishment process may constitute an adequate target.

The present study aims at evaluating the potential relationship between early microbiota development and weight-gain in preterm neonates.

# MATERIALS AND METHODS

#### Subjects and Samples

Sixty-three preterm infants born at gestational ages between 28 and 33 weeks were recruited at the Neonatology Units of Cabueñes Hospital and the University Central Hospital of Asturias (Northern Spain). None of the infants had necrotizing enterocolitis or culture positive early onset infection. All infants received mixed feeding (infant formula and some breast-milk administration during the study period). The infants were discharged from the hospital after an average stay of 38 days of hospitalization.

Fecal samples were collected at 2, 10, and 30 days-of-age and weights determined monthly up to 3 months. Weight data were used to calculate weight-gain at different sampling times and weight Z-scores were determined using the growth curves obtained by Fenton (Fenton and Kim, 2013). Fecal samples were immediately frozen and sent to the laboratory for analyses. The Regional Ethical Committee of Asturias Public Health Service approved the study and informed written consent was obtained from the parents.

#### Intestinal Microbiota and SCFA Analyses

The absolute levels of the different bacterial populations analyzed, including the main representatives of the predominant phyla in the infant gut (Bifidobacterium, Streptococcus, Staphylococcus, Enterococcus, Bacteroides-group, Enterobacteriaceae, Lactobacillus-group, Weissella, and total bacteria), were determined by quantitative PCR using primers and conditions previously described (Arboleya et al., 2012). When a sample resulted negative for a certain microbial group, the value of the detection limit obtained for the corresponding primer pair (ranging between 103 and 104 cells per gram depending on the bacterial group) was assigned. For the preparation of standard curves, pure cultures of appropriate strains were used as previously reported (Arboleya et al., 2012).

Analysis of the main short-chain-fatty-acids (SCFA) (acetate, propionate, and butyrate) was carried out in supernatants of homogenized feces by using a 6890N gas chromatograph (Agilent Technologies Inc., Palo Alto, CA, USA) connected to a FID and a MS 5973N detectors (Agilent) as previously reported (Arboleya et al., 2012).

#### Statistical Analyses

Multiple mixed linear models were used to investigate the relationship between the microbial levels and fecal SCFA with weight-gain, adjusting by possible confounders. Backward stepwise analyses based on the Aikaike Information Criterion (AIC) were employed to determine whether the variables were included in predictive models. A forest plot was used in order to show the effect sizes in both the so-labeled univariate and the multivariate models (always adjusting by infant and gestational ages). With the goal of investigating different groups of subjects based on microbiota measures, a Euclidean cluster was performed. Dendrogram was used to determine the number of groups and standard robust Welch tests. Standard parametric robust Welch tests or non-parametric Kruskal-Wallis test, depending on the data distribution, was used to check equality among groups. Analyses were performed with R software, the conventional p-level of 0.05 was used in the interpretation of results.

#### RESULTS

The study included 28 males and 35 females (birth weights from 1,085 to 1,580 g). Twenty-two were vaginally delivered (VD) whilst 41 were born by caesarean section (CS). During the 3 months of duration of the study 35 of the infants received antibiotics at some time, most of them during the first month. The characteristics of the study population and the evolution of the intestinal microbiota in the total cohort and in the cohort subdivided according to delivery mode are reported in Supplementary Tables 1 and 2, respectively. In general, bacterial levels, and the concomitant production of SCFA, increased along the study, which is in good agreement with previously reported data (Arboleya et al., 2012, 2016).

After the first few days, infants' weight increased, fitting well into a linear structure (Supplementary Figure 1). Initial exploratory analyses were conducted by using generalized mixed linear effects model with infant as random effect and gestational age as spline. The model showed a large effect of time (infant age) and gestational age, which together explained 80.5% of variance (determination coefficient, r 2 = 0.805). Therefore, to further assess these associations the model was adjusted for these two variables and analyzed by multivariate regression to

determine the effects of the microbiota-related variables. The results indicated an association of the intestinal microbiota with weight-gain in preterm infants (**Figure 1**). A significant effect of the levels of Staphylococcus (p < 0.001), Enterococcus (p < 0.001), Enterobacteriaceae (p = 0.011), Streptococcus (p = 0.047), Weissella (p < 0.001), and total bacteria (p = 0.002) was observed. In the full multivariate model (using backward elimination stepwise regression based on AIC) three variables remained significant; Enterococcus (p = 0.004), Staphylococcus (p = 0.005), and Weissella (p = 0.004) (**Figure 1**). The other microbial groups analyzed did not show any significant effect. Similarly, none of the SCFA analyzed showed a significant effect.

To evaluate the ability of the early microbiota-related variables for predicting weight-gain, the association of the microbiota variables at 2 and 10 days-of -age with the weight gained at 30 days of age (as percentage of birth-weight) was studied. Gestational age was found to be the major contributing factor, explaining a 55% of variance (r 2 = 0.55). After adjusting for gestational age and birth weight (both together explaining 56% of variance), the levels of Enterobacteriaceae at 2 and 10 daysof-age, Streptococcus and total bacteria levels at 2 days, and those of Bacteroides-group at 10 days were found to have a significant effect upon weight gain (**Table 1**), increasing a 17.6% the percentage of variance explained, up to a total of 73.5%. None of the other microorganisms was found associated with weightgain at 1 month, although a trend was observed for bifidobacterial levels (estimate 3.23 ± 1.64, p = 0.054).

Finally, the microbiota data obtained at 1 month of age were used for performing a cluster analysis, which allowed identifying three microbiota-driven infant groups (Supplementary Figure 2). These groups were not significantly different (p > 0.05) regarding gestational age, birth weight in grams or weight Z-score at birth TABLE 1 | Microbiota-related variables at 2 and 10 days of infant age that were associated with weight-gain at 30 days of life (measured as percentage with regard to birth-weight).

aAdjusted for gestational age and basal weight.

(data not shown). However, infant weight at 3 months of age showed a statistically significant difference among clusters (p = 0.033). At this later time infant weight in group 3 (3003 ± 681 gr) was significantly lower than in the other two infant groups, that did not show statistically significant differences between them (3988 ± 1163 gr for group 1 and 3883 ± 1344 gr for group 2). Similarly, at 3 months of age Z-scores differed among groups (p = 0.013) with group 3 (−2.37 ± 2.24) differing significantly from groups 1 and 2 (−0.62 ± 1.08 and −0.90 ± 1.90, respectively).

When the statistical models used in this study were adjusted for the potential confounders "delivery mode" or "antibiotic exposure" significant effects were not observed, which indicates that these variables are not influencing the associations observed. Actually, in our study delivery mode did not show a large effect on the analyzed microorganisms, since only the Bacteroidesgroup was found to be statistically different between vaginal and C-section babies, with reduced levels in the latter group at 10 and 30 days of life (Supplementary Table 2).

# DISCUSSION

An altered intestinal microbiota during the first year of life, with reduced levels of bifidobacteria and increased number of Staphylococcus aureus, has been observed in infants developing obesity later on (Kalliomäki et al., 2008). Particular microbial species, such as Bacteroides fragilis, have been related with higher BMI z-scores (Vael et al., 2011; Scheepers et al., 2014). However, this evidence is still limited and focuses in full-term infants and obesity prevention, whilst nothing is known on the relationship between microbiota and weight-gain in preterm infants.

Our results indicate an association between the intestinal microbiota and weight-gain. The levels of some microorganisms, such as Staphylococcus and Enterococcus, were negatively associated with weight-gain whilst others such as Weissella did it positively. This last microorganism belongs to the Leuconostoccaceae family from the Lactobacillales order (Fusco et al., 2015), being then related to Lactobacillus, some of whose strains were found to maintain growth of infant mice during chronic undernutrition (Schwarzer et al., 2016). Since lactobacilli are often used as probiotics, their ability, as well as that of nonpathogenic Weissella strains, to promote growth and maturation in preterm infants should be further explored.

Moreover early microbiota was associated with later weightgain, suggesting a potential effect of the early microbiota in weight-gain in preterm infants. Especially, Enterobacteriaceae and Streptococcus levels at 2 days of age and Bacteroides-group levels at day 10 showed a positive association with weight gain at 1 month of age. To this regard, the species B. fragilis has been repeatedly associated to increased BMI (Vael et al., 2011; Scheepers et al., 2014) in infants, pointing out at these microorganisms as potential players in the association intestinal microbiota-weight gain. When infants were clustered on the basis of their microbiota at 30 days of age, differences among the clusters were obtained for infant weight and weight Zscores at 3 months of age, again suggesting a relationship between microbiota and weight-gain. To this regard, certain oligosaccharides have been reported to promote a microbiotadependent increase in body-mass (Charbonneau et al., 2016), and transplanting the microbiota of undernourished children into germ-free mice resulted in growth impairment (Blanton et al., 2016). Similar relationships between intestinal microbiota and growth have also been reported in infants (Gough et al., 2015), and delayed colonization by specific commensals has been related with altered adiposity (Dogra et al., 2015). All these reports suggest the involvement of the gut microbiota in infants' weight-gain and development.

Neither the delivery mode, nor the antibiotic exposure, showed a significant effect in any of the statistical models used in this study. These facts point out that these important potential confounders are not influencing the observed associations

#### REFERENCES

Arboleya, S., Binetti, A., Salazar, N., Fernández, N., Solís, G., Hernández-Barranco, A., et al. (2012). Establishment and development of intestinal microbiota in preterm neonates. FEMS between microbiota and weight-gain. To this regard, in the present study the delivery mode was found to have a limited impact on intestinal microbial levels; Bacteroides was the only group significantly affected by delivery mode, presenting lower counts in babies born by C-section than in those vaginally delivered. The reduced levels observed for this microbial genus is in agreement with previous studies carried out in a similar preterm infants group (Arboleya et al., 2015). In relation to this, reduced levels of Bacteroides in full-term babies born by Csection have also been reported (Jakobsson et al., 2014), although in full-term babies the impact of C-section seem to be larger (Dominguez-Bello et al., 2010) than in our cohort of preterm infants.

Our results underline the interest of exploring the intestinal microbiota as a potential target for favoring growth and maturation in preterm infants. However, the meaning of weightgain in terms of infant maturation, disease risk, and later weight is a matter of concern (Wang et al., 2016) that requires of further, larger, and longer observational and intervention studies.

# AUTHOR CONTRIBUTIONS

PM, GS, MS, NF, CD, and MG. designed the study; GS, MS, and NF recruited the infants and collected the data and samples; SA, CD, and MG. performed the microbiological analyses; PM, GS, and MG analyzed the data; all authors participated in the data interpretation, revised the manuscript and approved its final version. All authors agreed to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.

#### FUNDING

This work was founded by the EU Joint Programming Initiative–A Healthy Diet for a Healthy Life (JPI HDHL, http://www.healthydietforhealthylife.eu/) and the Spanish Ministry of Economy and Competitiveness (MINECO) (Project EarlyMicroHealth). The Grant GRUPIN14-043 from "Plan Regional de Investigación del Principado de Asturias" is also acknowledged.

# ACKNOWLEDGMENTS

We thank all the participating families for their collaboration.

# SUPPLEMENTARY MATERIAL

The Supplementary Material for this article can be found online at: http://journal.frontiersin.org/article/10.3389/fmicb. 2017.00183/full#supplementary-material

Microbiol. Ecol. 79, 763–772. doi: 10.1111/j.1574-6941.2011. 01261.x

Arboleya, S., Sánchez, B., Milani, C., Duranti, S., Solís, G., Fernández, N., et al. (2015). Intestinal microbiota development in preterm neonates and effect of perinatal antibiotics. J. Pediatr. 166, 538–544. doi: 10.1016/j.jpeds.2014.09.041

with Acidaminococcus sp. and community-level changes in the gut microbiota. Microbiome 3:24. doi: 10.1186/s40168-015-0089-2

**Conflict of Interest Statement:** The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Copyright © 2017 Arboleya, Martinez-Camblor, Solís, Suárez, Fernández, de los Reyes-Gavilán and Gueimonde. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

# Trophic Interactions of Infant Bifidobacteria and *Eubacterium hallii* during L-Fucose and Fucosyllactose Degradation

Clarissa Schwab1 \*, Hans-Joachim Ruscheweyh2, 3, 4, Vera Bunesova1, 5, Van Thanh Pham1 , Niko Beerenwinkel 2, 4 and Christophe Lacroix 1

*1 Laboratory of Food Biotechnology, Department of Health Sciences and Technology, ETH Zurich, Zurich, Switzerland, 2 Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland, 3 Scientific IT Services, ETH Zurich, Basel, Switzerland, 4 Swiss Institute of Bioinformatics, Basel, Switzerland, 5 Department of Microbiology, Nutrition, and Dietetics, Czech University of Life Sciences Prague, Prague, Czechia*

#### *Edited by:*

*Andrea Gomez-Zavaglia, Center for Research and Development in Food Cryotechnology (CIDCA, CONICET), Argentina*

#### *Reviewed by:*

*Atte Von Wright, University of Eastern Finland, Finland Catherine Thornton, Swansea University, UK*

> *\*Correspondence: Clarissa Schwab<EMAIL_ADDRESS>
#### *Specialty section:*

*This article was submitted to Food Microbiology, a section of the journal Frontiers in Microbiology*

*Received: 02 December 2016 Accepted: 13 January 2017 Published: 30 January 2017*

#### *Citation:*

*Schwab C, Ruscheweyh H-J, Bunesova V, Pham VT, Beerenwinkel N and Lacroix C (2017) Trophic Interactions of Infant Bifidobacteria and Eubacterium hallii during L-Fucose and Fucosyllactose Degradation. Front. Microbiol. 8:95. doi: 10.3389/fmicb.2017.00095* Fucosyllactoses (2′ - or 3′ -FL) account for up to 20% of human milk oligosaccharides (HMOs). Infant bifidobacteria, such as *Bifidobacterium longum* subsp. *infantis*, utilize the lactose moiety to form lactate and acetate, and metabolize L-fucose to 1,2-propanediol (1,2-PD). *Eubacterium hallii* is a common member of the adult gut microbiota that can produce butyrate from lactate and acetate, and convert 1,2-PD to propionate. Recently, a Swiss cohort study identified *E. hallii* as one of the first butyrate producers in the infant gut. However, the global prevalence of *E. hallii* and its role in utilization of HMO degradation intermediates remains unexplored. Fecal 16S rRNA gene libraries (*n* = 857) of humans of all age groups from Venezuela, Malawi, Switzerland, and the USA were screened for the occurrence of *E. hallii*. Single and co-culture experiments of *B. longum* subsp. *infantis* and *E. hallii* were conducted in modified YCFA containing acetate and glucose, L-fucose, or FL. *Bifidobacterium* spp. (*n* = 56) of different origin were screened for the ability to metabolize L-fucose. Relative abundance of *E. hallii* was low (10−5–10−3%) during the first months but increased and reached adult levels (0.01–10%) at 5–10 years of age in all four populations. In single culture, *B. longum* subsp. *infantis* grew in the presence of all three carbohydrates while *E. hallii* was metabolically active only with glucose. In co-culture *E. hallii* also grew with L-fucose or FL. In co-cultures grown with glucose, acetate, and glucose were consumed and nearly equimolar proportions of formate and butyrate were formed. *B. longum* subsp. *infantis* used L-fucose and produced 1,2-PD, acetate and formate in a ratio of 1:1:1, while 1,2-PD was used by *E. hallii* to form propionate. *E. hallii* consumed acetate, lactate and 1,2-PD released by *B. longum* subsp. *infantis* from FL, and produced butyrate, propionate, and formate. Beside *B. longum* subsp. *infantis*, *Bifidobacterium breve,* and a strain of *B. longum* subsp. *suis* were able to utilize L-fucose. This study identified a trophic interaction of infant *bifidobacteria* and *E. hallii* during L-fucose degradation, and pointed at *E. hallii* as a metabolically versatile species that occurs in infants and utilizes intermediates of bifidobacterial HMO fermentation.

Keywords: *Eubacterium hallii*, trophic interactions, bifidobacterium, fucose, fucosyllactose

# INTRODUCTION

Human milk oligosaccharides (HMOs) are one of the major glycan source of the infant gut microbiota. Primary components of HMOs are D-glucose, D-galactose, L-fucose, N-acetylglucosamine, and sialic acid. Lactose constitutes the reducing end of HMOs, its galactose moiety can be fucosylated or sialylated to form 2′ - or 3′ -fucosyllactose (2′ -FL or 3′ -FL), or 3′ - and 6′ -sialyl-lactose (3′ -SL or 6′ -SL). Lactose can also be elongated with units of N-acetyllactosamine (Gal-β1-4GlcNAc) with its simplest form being Lacto-N-neotetraose (LNnT) (Kunz et al., 2000). The composition of HMOs is individually different and remains stable during different lactation phases (Niñonuevo et al., 2008; de Leoz et al., 2012). FLs can account for up to 20% of all HMOs (Niñonuevo et al., 2008; de Leoz et al., 2012).

 The degradation of HMOs relies on a complex network of extracellular solute binding proteins, transporters, and intra- or extracellular glycosyl hydrolases (GH). B. longum subsp. infantis carries out intracellular degradation while B. bifidum metabolizes HMOs extracellularly (Garrido et al., 2015). Both B. longum subsp. infantis and B. bifidum possess several α-fucosidases that release L-fucose from FL (Sela et al., 2012; Garrido et al., 2015). L-fucose can then be either used by the strain itself or can be released for bacterial cross-feeding (Garrido et al., 2015; Bunesova et al., 2016).

L-fucose is a desoxyhexose that is a common component of many N- and O-linked glycans and of glycolipids produced by mammalian cells (Becker and Lowe, 2003). L-fucose utilization has been investigated in depth in pathogens such as Escherichia coli, Shigella spp. and Bacillus cereus (Staib and Fuchs, 2014). These bacteria employ a fucose isomerase FucI, a fucose aldolase FucA, and a fucose kinase FucK to form L-lactaldehyde which can be further metabolized to 1,2-propanediol (1,2-PD). Recently, we could show that strains of B. longum subsp. infantis and B. longum subsp. suis metabolize L-fucose to 1,2-PD presumably by a pathway that employs non-phosphorylated intermediates similar to Campylobacter and Xanthomonas spp. (Bunesova et al., 2016). Genes related to L-fucose degradation were located on two genomic regions, one is part of the HMO degradation cluster H1 of B. longum subsp. infantis DSM 20088 (LoCascio et al., 2010), while region 2 contained a gene encoding a putative fucose permease (Bunesova et al., 2016).

In the intestine, 1,2-PD is a precursor of propionate by a pathway that employs a glycerol/diol dehydratase as a key enzyme (Reichardt et al., 2014). The frequent detection of genes encoding glycerol/diol dehydratases in fecal metagenomes of adults suggested that 1,2-PD conversion significantly contributes to intestinal propionate formation (Reichardt et al., 2014; Engels et al., 2016). One species with the ability to convert 1,2-PD to propionate is Eubacterium hallii which is a common commensal in adults (Engels et al., 2016). E. hallii formed similar amounts of propionate in the presence or absence of glucose and did not utilize glucose if 1,2-PD was present (Engels et al., 2016). E. hallii can also grow and form butyrate using either glucose, or acetate and lactate as substrates (Duncan et al., 2004).

We hypothesized that a trophic interaction between E. hallii and B. longum subsp. infantis can yield short chain fatty acids (SCFAs) butyrate or propionate from lactate and acetate, or from 1,2-PD, respectively. Both butyrate and propionate are important for gut microbiota/host homeostasis as they interact with the host epithelium and impact the immune system. Butyrate is a main energy source of colonocytes, impacts cell proliferation and differentiation, and lowers the risk of colitis and colorectal cancer (Wong et al., 2006; Plöger et al., 2012). Propionate acts as a precursor for gluconeogenesis in the liver and also impacts cell differentiation with potential health-promoting impact on intestinal inflammation, and cancer development (Reichardt et al., 2014).

Bifidobacterium is the predominant genus of the gut microbiota of breast fed infants. Little data exists on the occurrence of E. hallii in early life. Recently, a Swiss cohort study identified E. hallii as one of the first butyrate producers in the infant gut (Pham et al., 2016). However, the global prevalence of E. hallii and its role in the metabolism of L-fucose sourced from HMOs remains unexplored.

It was therefore the aim of this study to investigate the occurrence and abundance of E. hallii in populations of different age and origin, and to prove trophic interactions of E. hallii and B. longum subsp. infantis during growth in the presence of glucose, L-fucose, and FL. We also screened further Bifidobacterium spp. and strains (n = 56) to investigate whether species other B. longum subsp. infantis or subsp. suis are able to metabolize L-fucose.

# METHODS

#### Bacterial Strains and Culture Conditions

E. hallii DSM 3353 obtained from the Deutsche Sammlung von Mikroorganismen und Zellkulturen (DSMZ) was cultivated in modified YCFA medium (mYCFA) containing 30 mM acetate as described by Duncan et al. (2004) with slight modifications (**Table 1**). All components except L-cysteine-HCL (Sigma-Aldrich) were solubilized in deionized water, and pH was adjusted to pH 7.6 with NaOH. The medium was flushed with CO2 and boiled. When the color changed from blue to pink, L-cysteine-HCl (0.01%, w/v) was added. The medium was transferred to Hungate tubes flushed with CO2, and tubes were sealed and autoclaved. Stab cultures of E. hallii that were frozen at −20◦C in mYCFA agar (1.5% (w/v) agar) were used as stock cultures. For each experiment, a fresh agar stock was thawed; 1 ml of liquid YCFA medium was added and thoroughly shaken before being transferred to 8 ml liquid mYCFA medium. After incubation at 37◦C for 24 h, the culture was transferred at least once to fresh mYCFA broth before the experiment. Bifidobacterium spp. (**Table 2**) were obtained from the culture collections of the Laboratory of Food Biotechnology of ETH Zurich, the Department of Microbiology, Nutrition, and Dietetics, of the Czech University of Life Sciences Prague, or

#### TABLE 1 | mYCFA medium composition.

from DSMZ. Stock cultures of bifidobacteria were maintained at −80◦C in 30% glycerol. To prepare working cultures, bifidobacteria were streaked on Wilkens–Chalgren medium (Oxoid) supplied with soya peptone (5 g L−1 , Biolife, WCSP), Tween 80 (1 mL L−1 , Sigma-Aldrich), and fresh, filter-sterilized L-cysteine-HCl (0.5 g L−1 ). Single colonies were picked and were grown in liquid WCSP supplied with fresh, filter-sterilized L-cysteine-HCl (0.5 g L−1 ) at 37◦C for 24 h. For preparation of co-culture experiments, 100 µL of B. longum subsp. infantis overnight culture grown liquid WCSP were added to mYCFA medium, and the culture was incubated at 37◦C for 24 h. Unless otherwise stated, mYCFA containing 55 mM glucose was used to routinely cultivate E. hallii and B. longum subsp. infantis.

# Single and Co-Culture Studies in the Presence of Different Substrates

Growth kinetics were assessed in mYCFA medium supplied with glucose (50 mM, mYCFA\_glc, Sigma-Aldrich), L-fucose (40 mM, mYCFA\_fuc, Sigma-Aldrich), or FL (6 mM 2′ -FL and 6 mM 3′ - FL, mYCFA\_FL, Glycom A/S). Trace amounts of glucose were added to mYCFA\_fuc to enforce initial growth (Bunesova et al., 2016). Hungate tubes containing 9 ml mYCFA\_glc, mYCFA\_fuc, or mYFA\_FL were inoculated with overnight cultures of E. hallii and B. longum subsp. infantis (0.25 mL each). For comparison, E. hallii and B. longum subsp. infantis were also grown in single cultures. Samples were taken after 0, 4, 8, 12, 24, and 48 h of incubation for substrate and metabolite analysis, and for DNA isolation. Bacterial growth was evaluated by measuring the optical density at 600 nm (OD600). Additionally, 16S rRNA gene copies of E. hallii and B. longum subsp. infantis were determined in the co-cultures as outlined below. Growth was investigated in at least independent triplicates with the exception of B. longum subsp. infantis growth in mYCFA\_glc and mYCFA\_fuc, which was only investigated in duplicates. Therefore, standard deviations are not shown in the respective graphs.

# Screening of Bifidobacteria Strains for L-Fucose Utilization

Overnight bifidobacteria cultures grown in liquid WCSP were washed and resuspended in phosphate buffered saline (PBS). Bifidobacteria (50 µL) were inoculated in 950 µL API medium supplied fresh, filter-sterilized L-cysteine-HCl (0.5 g L−1 ) and with 30 mM glucose, or with 30 mM L-fucose and trace amounts of glucose. Cultures were incubated at 37◦C for 48 h. Growth and utilization of the carbohydrate source was judged by color change of the medium from blue to yellow. For selected strains, L-fucose utilization and metabolite formation were assessed by HLPC-RI as outlined below.

# Analysis of Substrate Utilization and Metabolite Formation

Glucose and L-fucose consumption, and the formation of 1,2-PD, lactate, acetate, formate, butyrate, and propionate was measured using high performance liquid chromatography (Merck-Hitachi) equipped with an Aminex HPX-87H column (300 × 7.8 mm; BioRad) and a refractive index detector (HPLC-RI). Samples were centrifuged at 13,000 g for 5 min at 4◦C. Supernatants (40 µL injection volume) were eluted with 10 mM H2SO4 at a flow rate of 0.6 ml min−1 at 40◦C. Sugars, SCFAs, 1,2-PD, and lactate (all Sigma-Aldrich) were quantified using external standards.

Propanal and propanol were quantified with ion chromatography with pulsed amperometric detection (IC-PAD) on a ICS-5000+ system (Thermo Scientific) equipped with a quaternary gradient pump, a thermoautosampler, and an electrochemical detector with a cell containing an Ag/AgCl reference electrode and a disposable thin-film platinum working electrode tempered at 25◦C. Analytes were separated on a IonPac ICE-AS1 4 × 250 mm ion-exclusion column with guard column (Thermo Scientific) operated at 30◦C using isocratic conditions (0.1 M methanesulfonic acid; 0.2 mL min−1 ) for 36 min. The injection volume was 10 µL. Electrochemical data was obtained using a triple potential waveform consisting of regeneration/detection, oxidation, and reduction potentials: E1 = 0.3 V (t1 = 0.31 s), E2 = 1.25 V (t2 = 0.34 s, tint = 0.02 s), E3 = −0.4 V (t3 = 0.39 s). Currents were measured and integrated with respect to time (tint). Propanal and propanol (Sigma-Aldrich) were quantified using external standards.

#### DNA Isolation and Quantification *E. hallii* and *B. longum* subsp. Infantis in Infant Feces and in Co-Cultivation Studies

Genomic DNA was isolated from 0.5 mL fermented mYCFA using the FastDNA SPIN Kit for Soil (MP Biomedicals). Genomic DNA from stool samples (n = 368) collected as part of an infant cohort study, and of Swiss children and adult had been isolated as described before (Vanderhaeghen et al., 2015; Pham et al., 2016). The abundance of E. hallii was determined using primers EhalF (5′ - GCGTAGGTGGCAGTGCAA -3′ ) and EhalR (5′ - GCACCG RAGCCTATACGG-3′ ) (Ramirez-Farias et al., 2009). B. longum subsp. infantis was quantified using primer pair F (5′ -TCGCGT CYGGTGTGAAAG-3′ ), and R (5′ -CCACATCCAGCRTCCAC-3 ′ ) (Rinttilä et al., 2004). Primers Eub338F (5′ -ACTCCTACG

#### TABLE 2 | L-fucose utilization and 1,2-PD formation of strains of bifidobacteria.

*(Continued)*

#### Schwab et al. Trophic Interactions during L-Fucose and Fucosyllactose Degradation

#### TABLE 2 | Continued

*Utilization was tested in API medium supplied with 5 g L-1 L-fucose and trace amounts of glucose. Color shift of the API medium after 48 h of incubation indicated L-fucose utilization (*+*). 1,2-PD formation was verified by HPLC-RI for selected samples (Table 3). nd, not determined; m, months; w, weeks.*

GGAGGCAGCAG-3′ ) and Eub518R (5′ - ATTACCGCGGCT GCTGG-3′ ) were employed to quantify total bacteria 16S rRNA genes (Fierer et al., 2005). Reactions were performed using a 7500 Fast Real-Time PCR System (Applied Biosystems) and the Kapa SYBR FAST qPCR mastermix (Biolab Scientifics Instruments SA). Thermal cycling started with an initial denaturation step at 95◦C for 3 min, followed by 40 cycles consisting of denaturation at 95◦C for 3 s, annealing at 60◦C for 10 s, and elongation at 72◦C for 25 s. To verify specificity of amplification, melting curve analysis and agarose gel electrophoresis for amplicon size control were performed. To generate standards, PCR amplicons were cloned into PGEMT Easy Vector and heterologously expressed in E. coli according to instructions of the supplier (Promega). Standard curves were prepared from ten-fold dilutions of linearized plasmids harboring the 16S rRNA gene of interest. Linear detection range was between, log 2.3 and log 8.3 gene copies for E. hallii 16S rRNA genes, between log 2.9 and log 8.9 gene copies bifidobacteria 16S rRNA genes, and between log 3.0 and log 8.0 gene copies for total bacteria 16S rRNA genes. A factor of 5.5 and 4 for Eubacterium spp. and B. longum subsp. infantis, (rrnDB, http://rrndb.mmg.msu.edu; Vetrovský ˇ and Baldrian, 2013), respectively, was applied to calculate the numbers of cells accounting for several 16S rRNA gene copies per genome.

#### 16s rRNA Gene Amplicon Libraries Screens

16S rRNA gene sequencing datasets published by Yatsunenko et al. (2012) were downloaded from MG-RAST (MG-RAST ID 401). The 489 datasets with known age of the donor contained in total 1.0∗ 109 sequences and on average 2.1∗ 106 sequences. All reads were aligned against the Silva database (version 123.1, Quast et al., 2013) using MALT in semiglobal alignment mode (Herbig et al., 2016) and only matches with a percent identity >97% were reported. Alignments were then used to assign reads on the Silva taxonomy. A read was placed on the lowest taxon so that at least 90% of the alignments were covered by that taxon (majority vote 90%). Unaligned reads were extracted and placed on the Silva taxonomy by using the rdp classifier with a cutoff of 0.8.

#### Identification of L-Fucose Utilization Related Genes in *B. breve* Genomes

Genomes of Bifidobacterium breve DSM 20213 (PRJDB57) and UCC 2003 (CP000303.1) were screened for genes encoding proteins related to L-fucose metabolism using BlastP and the corresponding proteins of B. longum subsp. infantis DSM 20088 region 1 and 2 for the query (Bunesova et al., 2016, see also below).

#### Screening of Shotgun Sequencing Datasets for Presence of Proteins Encoding L-Fucose Utilization Regions 1 and 2

Metagenomic datasets (n = 111) published by Yatsunenko et al. (2012) were downloaded from MG-RAST (MG-RAST ID 98). The datasets contained in total 16,318,166 sequences and on average 147,010 sequences per sample. The smallest and largest datasets contained 19,587 and 478,588 sequences, respectively, with an average sequence length of 358 bases. All datasets were aligned using DIAMOND blastx in sensitive mode (Buchfink et al., 2015) against a modified bacterial RefSeq database (Pruitt et al., 2007). The modified RefSeq database was composed by adding 24 protein sequences of B. longum subsp. infantis DSM 20088 and B. breve DSM 20213 fucose utilization regions 1 and 2 (Bunesova et al., 2016, WP\_003830405.1, WP\_003830403.1,

WP\_012578537.1) to the standard RefSeq database. Reads were assigned to the best aligning protein sequences which had a bitscore >50. Reads assigned to the 24 proteins sequences of interest were reported.

#### Statistical Analysis

A sigmoidal non-linear regression model [Weibull, 5 Parameter model, f = if(x<=x0-b∗ ln(2)∧(1/c); y0; y0+a ∗ (1-exp(-(abs(xx0+b ∗ ln(2)∧(1/c))/b)∧c))) implemented in SigmaPlot 13, Systat Software] was chosen to fit curves to log% abundance data of E. hallii in the different populations. Student's paired t-test with two-tailed distribution was used to identify significant differences in metabolite formation, OD600 nm, and cell counts between treatments. A p < 0.05 was considered significant.

# RESULTS

# Age and Geographical-Dependent Occurrence of *E. hallii*

We screened 489 previously obtained 16S rRNA gene amplicon libraries from Malawi, Venezuela and USA (Yatsunenko et al., 2012) for the occurrence of E. hallii. Concurrently, we determined E. hallii relative abundance in a Swiss infant cohort study which followed the fecal microbiota of 40 infants for the first 2 years of life (Pham et al., 2016) using qPCR, and compared to Swiss teenagers and Swiss adults (Vanderhaeghen et al., 2015; together n = 368; **Figure 1**). Minimum detection limits were ∼10−4 and 10−5% relative abundance for 16S rRNA gene libraries and qPCR screenings, respectively.

In populations from Venezuela, the USA, and Malawi, E. hallii occurred in all infant samples of 1 year of age or younger

at means of log −2.0 ± 1.2, −2.9 ± 1.0, and −2.9 ± 0.8%, respectively (**Figure 1A**). Relative abundance increased after 1– 1.5 years in donors from Venezuela (100% occurrence), the USA (95% occurrence), and Malawi (100%). In Swiss infants, occurrence levels of E. hallii fluctuated between 13 and 40% until 1 year, and increased to 85% at 2 years of age (log −2.9 ± 0.8%; **Figure 1B**). Between 5 and 10 years, relative abundance of E. hallii reached adult levels in all four populations (Malawi: log −0.4 ± 0.3%, Venezuela: log −0.2 ± 0.3%, USA: log −0.1 ± 0.6%, Switzerland: log 0.8 ± 0.5%).

## Growth of *E. hallii* and *B. longum* subsp. *Infantis* in Single- and Co-Cultures

To investigate trophic interactions between B. longum subsp. infantis and E. hallii in the presence of glucose, L-fucose and FL, B. longum subsp. infantis, and E. hallii were grown in single- and co-cultures in mYCFA.

In single culture, B. longum subsp. infantis reached a final optical density (OD600 nm 1.9) in the presence of glucose, and a lower maximal OD600 nm when grown with L-fucose and FL (1.5 ± 0.1 and 1.5, respectively) after 48 h of incubation (**Figure 2A**). In mYCFA\_glc −25.6 mM glucose was used, and 55.4, 9.9, and 13.1 mM acetate, lactate, and formate were formed (**Figure 2D**). In mYCFA\_fuc, B. longum subsp. infantis used −28.3 ± 2.8 mM L-fucose and produced nearly equimolar amounts of 1,2-PD, acetate and formate (25.5 ± 4.8, 22.4 ± 1.0, and 26.7 ± 0.5 mM, respectively; **Figure 2G**). Lactate was produced at low amounts (2.0 ± 1.0 mM), and mean carbon recovery was 86%. In the presence of FL, B. longum subsp. infantis formed acetate (33.6 mM), lactate (16.8 mM), 1,2-PD (7.8 mM), and low amounts of formate (3.1 mM; **Figure 2J**).

In single culture, E. hallii grew rapidly to OD 600 nm of 1.7 ± 0.2 after 12 h of incubation in mYCFA\_glc (**Figure 2B**). From 1 mol glucose and 0.5 mol acetate, ∼1 mol butyrate and 0.5 mol formate were produced (**Figure 2E**). Maximum optical density in mYCFA\_FL and mYCFA\_fuc was significantly lower than with glucose with OD600 nm 0.9 and 0.5 after 12 and 9 h of incubation, respectively (**Figure 2B**). With L-fucose and FL, E. hallii formed 2.7 ± 1.0 and 6.0 ± 1.1 mM butyrate, respectively (**Figures 2H,K**). No acetate utilization and formate production were detected.

For the co-cultures, qPCR was used in addition to optical density measurements to monitor the growth of both strains (**Figure 3**). Cell counts were calculated based on 16S rRNA genes corrected for several 16S rRNA gene copies per genome. In mYCFA\_glc, cell counts of both strains increased by log 2.8 cells ml−1 during the first 8 h of incubation, after which growth slowed down (**Figure 3A**). Highest OD600 nm was reached after 24 h of incubation (**Figure 2C**). The amount of acetate used, and butyrate and formate formed in the co-cultures was similar to E. hallii single cultures (**Figure 2F**), and only low amounts of lactate (0.6 ± 0.7 mM) were detected after 48 h (**Figure 2F**).

Co-cultures grown in mYCFA\_fuc reached a maximum OD of 1.1 ± 0.1 after 48 h of incubation (**Figure 2C**). During the first 12 h, B. longum subsp. infantis and E. hallii grew exponentially with increased cell counts of log 3 and log 2.7 cells mL−1 , respectively (**Figure 3B**). In co-cultures, B. longum subsp. infantis utilized only ∼35% of L-fucose compared to single cultures (10.4 ± 8 mM). The co-cultures formed propionate (8.2 ± 3.5 mM), butyrate (7.4 ± 0.8 mM), and formate (10.9 ± 1.7 mM; **Figure 2I**). Butyrate formed by the co-cultures was significantly (p < 0.05) higher compared to butyrate formation of E. hallii single culture in mYCFA\_fuc (7.4 ± 0.8 vs. 2.7 ± 1.0 mM). 1,2-PD, propanal, and propanol were not detected during coculture fermentations, and there was no apparent accumulation or consumption of acetate or lactate (**Figure 2I**).

When grown in co-cultures in mYCFA\_FL, cell counts of B. longum subsp. infantis and E. hallii increased by 3.2 and 2.8 log during the first 8 h of incubation (**Figure 3C**), and maximal OD was reached after 24 h of incubation (**Figure 2C**). Acetate (18.2 ± 1.6 mM), propionate (9.7 ± 5.1 mM), and butyrate (5.4 ± 3.1 mM), and formate (19.7 ± 5.0 mM) were detected after 48 h of incubation (**Figure 2L**). 1,2-PD and lactate were only present at low levels <1 mM.

# *Bifidobacterium* Production of 1,2-PD from L-Fucose

To investigate whether L-fucose utilization was a trait limited to B. longum subsp. infantis, or was also present in other infant-, adult-, or animal-associated bifidobacteria, we screened n = 56 Bifidobacterium strains (**Table 2**) for growth in API medium supplied with 30 mM L-fucose and trace amounts of glucose. All isolates were capable of growing in API medium supplied with 30 mM glucose indicating the suitability of the assay. Only strains of B. longum subsp. infantis and subsp. suis, and of B. breve were identified as being able to metabolize L-fucose and to form 1,2- PD. L-fucose was used and 1,2-PD was formed in a ratio of ∼1:1 by all L-fucose-utilizing strains (**Table 3**). Additionally, lactate, acetate, and formate were produced leading to carbon recoveries between 87 and 109% (**Table 3**).

# Genes Related to L-Fucose Utilization in *B. breve* Genomes

We previously identified two genomic regions that encompass genes potentially involved in L-fucose utilization of strains of B. longum subsp. infantis and B. longum subsp. suis (Bunesova et al., 2016). The genome of B. breve DSM 20213 (PRJDB57) possessed a set of genes with slightly differing genome organization to B. longum subsp. infantis and B. longum subsp. suis (**Figure 4**). Region 1 encompassed a gene encoding an α-fucosidase (GH family 95) with 78% homology in 607/783 AA to BLON\_2335 of B. longum subsp. infantis DSM 20088. Region 1 also contained genes encoding a putative L-fuconate dehydratase (96% homology in 284/293 AA to B. longum subsp. infantis DSM 20088 L-fuconate dehydratase, region 1), a L-fucose dehydrogenase (93% homology in 245/262 AA, region 1), L-fuconolactone hydrolase (50% homology in 132/264 AA, region 2), and a 4-hydroxy-tetrahydrodipicolinate synthase (89% homology in 265/296 AA, region 1). B. breve region 2 contained another L-fuconate dehydratase (97% homology in 417/426 AA, region 2), L-fucose dehydrogenase (94% homology in 249/263 AA, region 2), a putative fucose permease (62%

growth in co-culture in mYCFA\_glc (A), mYCFA\_fuc (B), and mYCFA\_FL (C).

*L-fucose utilization and lactate, formate, acetate, and 1,2-PD formation of selected bifidobacteria in API medium supplied with 30 mM L-fucose and trace amounts of glucose after 48 h of incubation at 37*◦*C.*

homology in 262/461 AA, region 2), a L-fuconolactone hydrolase (96% homology in 246/255 AA, region 2), and a 4-hydroxytetrahydrodipicolinate synthase (69% homology in 206/296 AA, region 1; **Figure 4**). B. breve UCC 2003 had an identical genomic set-up to B. breve DSM 20213 (data not shown).

# Coding Potential for Bifidobacteria Fucose Utilization in Fecal Metagenomes

Bifidobacteria were the predominant taxa in feces of infants from Venezuela, Malawi, and the USA during the first 2 years of life based on 16S rRNA gene sequencing data (**Figure 5**). For 111 samples, metagenomic data of the same donor data were also available (Yatsunenko et al., 2012). Metagenomes were screened for the presence of proteins presumably involved in bifidobacterial L-fucose utilization (**Figure 4**). At the threshold of detection allowed by sequencing coverage, the majority of fecal metagenomes of infants under 2 years of all three populations possessed the coding potential for bifidobacterial fucose utilization (**Figure 5**). All infant metagenomes from Venezuela (n = 11, 0.25–2 years) had coding potential for bifidobacteria L-fucose utilization. Eighty-seven and Seventy-one percent of proteins of both regions were recovered for B. longum subsp. infantis and B. breve respectively; all infants were positive for B. longum subsp. infantis while B. breve L-fucose utilization was not detected in 1 infant. Similarly, all infant metagenomes from Malawi (n = 18, 0.05–1.53 years) had coding potential for bifidobacteria L-fucose utilization. On average, 93 and 74% of the proteins of B. longum subsp. infantis and B. breve were detected, respectively. Of the 44 fecal metagenomes of US American infants (0.08–1.6 years), 16 and 28 were negative and positive for bifidobacteria L-fucose utilization, respectively. B. breve assigned proteins were detected in all children while B. longum subsp. infantis L-fucose utilization related proteins were not detected in one infant. The recovery of proteins of region 1 and 2 was 47 and 23% for B. longum subsp. infantis and B. breve, respectively. Bifidobacterial L-fucose utilization related proteins were also detected in feces of a 5 and a 6 year old US American child (**Figure 5**).

#### DISCUSSION

E. hallii is a metabolically versatile species that can contribute to intestinal butyrate and propionate formation (Duncan et al., 2004; Engels et al., 2016). In adults, E. hallii is a regular constituent of the gut microbiota (Engels et al., 2016). As shown in this study, E. hallii persistently occurred in the first months

after birth at low abundance of the fecal microbiota and reached adult levels at ∼5–10 years of age independent of geographical donor origin. Thus, E. hallii is a commensal occurring very early in life which might contribute to metabolic interactions starting at 1–2 years of age when abundance markedly increased in all populations.

B. breve and B. infantis subsp. longum were identified as species capable of metabolizing fucose. Both are two of the most representative species found in breast-milk fed infants (Avershina et al., 2013; Matsuki et al., 2016), and fecal metagenome analysis indicated the coding potential for bifidobacterial fucose utilization in children under 2 years. Trophic interactions of E. hallii and B. longum subsp. infantis and/or B. breve during L-fucose and FL utilization can therefore be considered infant specific (**Figure 6**). Interestingly, general occurrence and the presence of bifidobacteria capable of L-fucose utilization appeared to be higher in Venezuelan and Malawian than in American infants. This might reflect differences in feeding practice, as in Venezuela and Malawi, all analyzed infants below 2 years were breast-fed, while in the USA, 71% received formula (Yatsunenko et al., 2012).

In the infant gut, E. hallii can utilize lactate and acetate produced by bifidobacteria during the degradation of hexoses. Bifidobacteria metabolize hexoses via the "bifid shunt" with fructose-6-phosphoketolase as the key enzyme. Glucose (1 mol) theoretically yields 1.5 mol acetate, 1 mol lactate, and 2.5 ATP (de Vries and Stouthamer, 1967, 1968). However, this ratio depends on whether the intermediate pyruvate is cleaved to acetyl phosphate and formate, or whether it is reduced to lactate (Palframan et al., 2003). B. longum subsp. infantis, B. longum subsp. suis, and B. breve also metabolized the desoxyhexose L-fucose. In mYCFA, nearly equimolar proportions of acetate, formate and 1,2-PD and only little lactate were formed while in API medium, lactate was produced at the expense of formate and acetate. The ratio of acetate, formate, and lactate formed varies for species, substrate source and carbohydrate supply (limitation or excess; Macfarlane and Gibson, 1995; Palframan et al., 2003). Here, ratios differed for the same species when supplied with the same carbohydrate (30 mM L-fucose). In this study, mYCFA was prepared strict anaerobically while API medium was only facultative anaerobic, which could have also impacted pyruvate metabolism. It was shown before that the presence of oxygen changed final metabolites formed by B. longum subsp. infantis (González et al., 2004).

Both bifidobacteria and E. hallii were able to produce formate during the degradation of FL (**Figure 6**). Methanogens, which can produce methane from formate and CO2, are usually not detected in infants (Vanderhaeghen et al., 2015). As feces collected as part of a cohort study following 16 infants from 2 weeks to 2 years of age (Pham et al., 2016, unpublished data) contained no or only very low levels of formate, it can be assumed that the formate produced during HMO degradation is further utilized. Formate together with CO2 can also be used by acetogenic microbes such as Blautia spp. to produce acetate via the Wood-Ljungdal pathway. Little literature exists on formate cross-feeding within the infant gut microbiota. However, as one of the important intermediate metabolites, the effect of formate and formate utilization on infant gut health should be investigated in further studies.

We identified for the first time the ability of B. breve strains to metabolize L-fucose to 1,2-PD. We previously

84), and USA (C, *n* = 307; Yatsunenko et al., 2012). For samples with available metagenomes (Yatsunenko et al., 2012), the presence of genes encoding bifidobacterial L-fucose utilization related proteins. Green symbols, samples that were positive for bifidobacteria L-fucose utilization related proteins, red symbols, samples that were negative, gray samples, no metagenomes available.

suggested a Bifidobacterium L-fucose utilization pathway based on genome comparison which has been also identified by a recent study investigating FL degradation by a strain of B. longum subsp. longum (Bunesova et al., 2016; Garrido et al., 2016). Similar to strains of B. longum subsp. infantis and B. longum subsp. suis, B. breve harbored two genomic regions which encompassed genes putatively encoding enzymes involved in L-fucose degradation with non-phosphorylated intermediates. In contrast, the L-fucose-negative B. kashiwanohense only possessed region 1 (Bunesova et al., 2016), suggesting that both regions are necessary for L-fucose metabolism. In addition, two of the identified genes encoding fucose permease (FucP) and a 4-hydroxy-tetrahydrodipicolinate synthase, were upregulated when B. breve was grown in co-culture with mucin degrading B. bifidum (Egan et al., 2014). B. bifidum releases L-fucose during growth with mucin similar to the release of fucose from FL (Turroni et al., 2014; Garrido et al., 2015; Bunesova et al., 2016), which then can be imported and metabolized by other species such as B. breve or L-fucose-utilizing strains of B. longum.

In adults, B. adolescentis is a predominant Bifidobacterium species, and cross-feeding between B. adolescentis and E. hallii has been reported before (Belenguer et al., 2006). E. hallii was thereby able to form butyrate from lactate and acetate that was produced when B. adolescentis grew in the presence of starch, or to use mono- or dissacharides released by B. adolescentis from fructooligosaccharides. We also observed substrate-dependent routes of metabolic cross-feeding. In the presence of L-fucose, propionate was the main metabolite formed by E. hallii. In co-cultures with B. longum subsp. infantis, the formation of propionate, butyrate, and formate from FL was observed. Here, butyrate and formate could have been produced from lactate and acetate, or directly from glucose released by B. longum subsp. infantis, while propionate again was derived from L-fucose.

FL is a major component of HMOs (de Leoz et al., 2012). Therefore, it can be implied that a substantial proportion of L-fucose is metabolized to propionate if E. hallii is present. However, not all women are able to secrete α-(1-2) fucosylated HMOs due to mutations that render the responsible fucosyltransferase FUT2 inactive. About 20% of the European and African population carry an inactive FUT2 (Kelly et al., 1995; Liu et al., 1998). The activity of FUT2 and with that the presence of fucosylated HMOs has been linked to differences in the establishment of the infant gut microbiota (Lewis et al., 2015). The bifidobacteria community of infants born to nonsecretor mothers was reported to establish later, to carry reduced numbers of bifidobacteria, and to contain a lower percentage of bifidobacteria capable of degrading 2-FL compared to infants of secretor mothers (Lewis et al., 2015). Thus, non-secretor mothers' milk lacks a significant source for intestinal propionate formation. It could therefore be speculated that the SCFA profile of infants of secretor- and non-secretor mothers is different. However, to date, no large scale study compared the fecal SCFA profile of infants born to secretor and non-secretor mothers.

Fucosylated oligosaccharides are not only a carbon source for the intestinal microbes but also play an important role in host-microbe interactions (Pickard et al., 2014). On one hand, fucosylated HMOs protect against invasion of enteric pathogens acting as a decoy for epithelial attachment sites (Morrow et al., 2005). On the other hand, L-fucose released from fucosylated oligosaccharides has been related to virulence and

host colonization of enteric pathogens. It was suggested that Lfucose released by Bacteroides thetaiotamicron was utilized by Salmonella enterica serovar Typhimurium during colonization of a mouse model (Ng et al., 2013). Likewise, L-fucose released by B. thetaiotamicron increased colonization of an enterohaemorrhagic E. coli (EHEC) in comparison to mutants with a knock-out of a fucose sensing two-component system (Pacheco et al., 2012). This fucose sensing two-component system regulates virulence and metabolic gene expression of EHEC (Pacheco et al., 2012). The ability to utilize L-fucose provided Campylobacter jejuni with a competitive advantage during the colonization of birds or pigs compared to fucosenegative mutants (Muraoka and Zhang, 2011; Stahl et al., 2011). Through utilization of L-fucose, the infant bifidobacterial community therefore could enhance colonization resistance toward enteric pathogens.

# CONCLUSION

L-fucose utilization was identified here as a trait of only infant-derived bifidobacteria. Trophic interactions of L-fucose-utilizing infant bifidobacteria and E. hallii yielded different SCFAs from L-fucose or FL pointing at E. hallii as a metabolically versatile species utilizing intermediate metabolites of HMO fermentation. The utilization of L-fucose by the infant bifidobacterial community might enhance colonization resistance toward fucose-dependent enteric pathogens.

# AUTHOR CONTRIBUTIONS

VB and CS designed experiments; VB, CS, VTP, and HR conducted experimental work; VB, CS, VTP, and H-JR analyzed data; CL, NB provided financial support; CS wrote manuscript with the help of all authors.

# FUNDING

VB was supported by SCIEX grant 13.151. VTP and this research were supported by a grant of the Swiss National Science Fond (PN 310030\_146784). H-JR was funded by the European Research Council (ERC Synergy Grant No. 609883 to NB).

# ACKNOWLEDGMENTS

We thank Glycom A/S for supplying 2′ -FL and 3′ -FL. Alfonso Die and Nicole Oberortner are acknowledged for technical assistance.

# REFERENCES

the gut bifidobacterial communities of breasfed infants. Microbiome 3, 13. doi: 10.1186/s40168-015-0071-z

**Conflict of Interest Statement:** The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Copyright © 2017 Schwab, Ruscheweyh, Bunesova, Pham, Beerenwinkel and Lacroix. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

# Sensitive Quantitative Analysis of the Meconium Bacterial Microbiota in Healthy Term Infants Born Vaginally or by Cesarean Section

Ravinder Nagpal1 \*, Hirokazu Tsuji2 , Takuya Takahashi2 , Kazunari Kawashima3 , Satoru Nagata4 , Koji Nomoto2 and Yuichiro Yamashiro1

1 Probiotics Research Laboratory, Graduate School of Medicine, Juntendo University, Tokyo, Japan, 2 Yakult Central Institute, Tokyo, Japan, 3 Gonohashi Obstetrics and Gynecology Hospital, Tokyo, Japan, 4 Department of Pediatrics, School of Medicine, Tokyo Women's Medical University, Tokyo, Japan

For decades, babies were thought to be born germ-free, but recent evidences suggest that they are already exposed to various bacteria in utero. However, the data on population levels of such pioneer gut bacteria, particularly in context to birth mode, is sparse. We herein aimed to quantify such bacteria from the meconium of 151 healthy term Japanese infants born vaginally or by C-section. Neonatal first meconium was obtained within 24–48 h of delivery; RNA was extracted and subjected to reverse-transcription-quantitative PCR using specific primers for Clostridium coccoides group, C. leptum subgroup, Bacteroides fragilis group, Atopobium cluster, Prevotella, Bifidobacterium, Lactobacillus, Enterococcus, Enterobacteriaceae, Staphylococcus, Enterococcus, Streptococcus, C. perfringens, and C. difficile. We detected several bacterial groups in both vaginally- and cesarean-born infants. B. fragilis group, Enterobacteriaceae, Enterococcus, Streptococcus, and Staphylococcus were detected in more than 50% of infants, with counts ranging from 105 to 108 cells/g sample. About 30–35% samples harbored Bifidobacterium and Lactobacillus (104–105 cells/g); whereas C. coccoides group, C. leptum subgroup and C. perfringens were detected in 10–20% infants (103–105 cells/g). Compared to vaginally-born babies, cesareanborn babies were significantly less often colonized with Lactobacillus genus (6% vs. 37%; P = 0.01) and Lactobacillus gasseri subgroup (6% vs. 31%; P = 0.04). Overall, seven Lactobacillus subgroups/species, i.e., L. gasseri subgroup, L. ruminis subgroup, L. casei subgroup, L. reuteri subgroup, L. sakei subgroup, L. plantarum subgroup, and L. brevis were detected in the samples from vaginally-born group, whereas only two members, i.e., L. gasseri subgroup and L. brevis were detected in the cesarean group. These data corroborate that several bacterial clades may already be present before birth in term infants' gut. Further, lower detection rate of lactobacilli in cesareanborn babies suggests that the primary source of lactobacilli in infant gut is mainly from maternal vaginal and–to a lesser extent–anal microbiota during vaginal delivery, and that the colonization by some important Lactobacillus species is delayed in babies delivered via cesarean-section.

Keywords: C-section, dysbiosis, gut bacteria, intestinal microbiota, Lactobacillus, meconium, RT-qPCR

#### Edited by:

Maria Carmen Collado, Spanish National Research Council (CSIC), Spain

#### Reviewed by:

Clarissa Schwab, ETH Zurich, Switzerland M. Pilar Francino, FISABIO-Public Health, Spain

> \*Correspondence: Ravinder Nagpal<EMAIL_ADDRESS>
#### Specialty section:

This article was submitted to Food Microbiology, a section of the journal Frontiers in Microbiology

Received: 14 October 2016 Accepted: 29 November 2016 Published: 15 December 2016

#### Citation:

Nagpal R, Tsuji H, Takahashi T, Kawashima K, Nagata S, Nomoto K and Yamashiro Y (2016) Sensitive Quantitative Analysis of the Meconium Bacterial Microbiota in Healthy Term Infants Born Vaginally or by Cesarean Section. Front. Microbiol. 7:1997. doi: 10.3389/fmicb.2016.01997

# INTRODUCTION

fmicb-07-01997 December 15, 2016 Time: 11:16 # 2

Gut microbiota plays a fundamental role in various aspects of health and numerous diseases, but the multifarious dynamics of early-life intestinal microbiota colonization are only now beginning to come to light. For decades, it had been believed that the fetus as well as the intrauterine environment is universally sterile, and the earliest microbial exposure and colonization of infant gut begins during delivery and promptly thereafter by the acquisition of maternal (vaginal, anal, and skin microbiota) and environmental bacteria. However, some recent studies have elegantly reported the presence of bacteria in placenta (Aagaard et al., 2014; Collado et al., 2016), amniotic fluid (Oh et al., 2010; Collado et al., 2016), and umbilical cord blood (Jimenez et al., 2005), thereby manifesting that the fetus is already exposed to a variety of bacteria in utero. Several studies have also detected various bacteria in the meconium of healthy babies (Gosalbes et al., 2013; Hu et al., 2013; Del Chierico et al., 2015; Hansen et al., 2015; Collado et al., 2016), further evidencing that the gut microbial colonization may already begin before birth. However, quantitative data on the types and particularly the population levels (i.e., the absolute count) of bacteria that may be present in the meconium is still sparse. Also, the information on how the composition of '1st-day flora' differs between infants born vaginally or by cesarean section is limited. Given that the early-life microbiota plays important role in infant's physiological, metabolic and immunological development (Matamoros et al., 2013; Arrieta et al., 2015; Kerr et al., 2015) and is strongly impacted by birth mode (Penders et al., 2006; Tsuji et al., 2012; Backhed et al., 2015; Nagpal and Yamashiro, 2015; Bokulich et al., 2016; Nuriel-Ohayon et al., 2016), the numeric data about the population levels of bacteria present in the first intestinal discharge of vaginally-and cesarean-born newborns could be very informative and relevant. In this milieu, we herein aimed to quantify the bacteria present in the meconium of healthy term infants born vaginally or by C-section. Bacteria were quantified by using a highly sensitive cultureindependent reverse-transcription-quantitative-PCR (RT-qPCR) based analytical method that targets the bacterial 16S rRNA molecules (Matsuda et al., 2009). We applied this method because it provides quantitative data; whereas 16S rRNA genebased sequencing methods are largely qualitative and do not provide numerical data of bacterial population levels. Moreover, it is highly sensitive, whereas DNA-targeted PCR methods have relatively lower sensitivity and hence may overlook several subdominant but important bacteria, especially in neonatal stages when the microbiota is underdeveloped. Another advantage is that it provides information on viable cells, whereas the results of DNA-based analyses might also include background DNA (e.g., free bacterial DNA, or DNA of dead bacteria) that may be present in prenatal niches such as amniotic fluid and placenta and also in meconium. We have previously validated that the counts obtained by this RT-qPCR method are equivalent to the bacterial counts enumerated by culturing and fluorescent in situ hybridization (FISH) methods and that the detection sensitivity of RT-qPCR is approximately 100- to 1000-fold higher than that of other molecular methods such as qPCR and terminal restriction fragment length polymorphism (t-RFLP) (Matsuda et al., 2007, 2009; Kubota et al., 2010; Kurakawa et al., 2015b). Therefore, owing to these advantages, we specifically implemented RT-qPCR for the present study. Herein we demonstrate the quantification of bacteria that are present in the first meconium of healthy term Japanese infants born vaginally or by C-section.

#### MATERIALS AND METHODS

#### Subjects

The details of infants enrolled in this study are provided in **Table 1**. The study included 151 healthy full-term infants [134 vaginally-born (VG); 17 cesarean-born (CS)] whose mothers were recruited at the Gonohashi Obstetrics and Gynecology Hospital, Tokyo. The samples used in this study were part of a large cohort of Japanese infants enrolled in a longitudinal study monitoring the development of intestinal microbiota during the first 3 years of life, as reported in detail elsewhere (Tsuji et al., 2012). However, the meconium bacterial carriage was not previously investigated in detail, particularly in context to the delivery mode. In the present study, none of the babies were exposed to any type of formula-feed up to the point of first meconium; and all the infants as well as their mothers were apparently healthy with no indications of disease or intrauterine infection. All 17 cesarean cases were elective (planned) cesareans. The study design was approved by the ethical committee of Yakult Central Institute, Tokyo. Prior written informed consent was obtained from the parents or legal representatives of infants.

#### Sample Collection

A spoonful (0.5–1.0 g) of the first intestinal discharge (obtained from the first diaper) was collected fresh in a fecal collection tube (Sarstedt AG & Co., Numbrecht, Germany) containing 2 ml RNAlater (Ambion, Austin, TX, USA). Out of total 151 samples, 148 were passed within 24 h after birth whereas the rest three samples were discharged between 24 and 48 h. As described elsewhere (Tsuji et al., 2012), stool samples were also collected at age 3 and 7 days, 1, 3, and 6 months, and 3 years for follow-up analyses. All samples were collected at the hospital by following

routine and standard clean techniques such as the use of sterile sample collection tube and spatula, and handler's mouth masked, hands sanitized and gloved, and head capped while retrieving the sample. Immediately after collection, samples were stored in the refrigerator (3–4◦C) anaerobically by using Anaero Pouch-Anaero (Mitsubishi Gas Chemical Company, Inc., Tokyo, Japan) and were sent immediately in a cooling box with refrigerants and anaero-packs to the research lab where these were stored at 3–4◦C in a Biosafety Category II microbiology laboratory until further processing.

# Sample Processing, RNA Extraction and RT-qPCR

#### Primary Treatment

The samples were subjected to pretreatment according to the methods described previously (Matsuda et al., 2009). Briefly, the fecal samples were weighed and suspended in nine volumes of RNAlater to make a fecal homogenate (100 mg feces/ml). In preparation for RNA extraction, 1ml of PBS(−) was added to 200 µl of fecal homogenate. The fecal homogenate was centrifuged at 4◦C at 13,000 g for 10 min, the supernatant was discarded, and the precipitating pellet was stored at −80◦C until RNA extraction.

#### RNA Extraction

RNA extraction was done by using previously described methods (Matsuda et al., 2009). Briefly, the thawed sample was resuspended in a solution containing 346.5 µl of RLT buffer (Qiagen Sciences, Germantown, MD, USA), 3.5 µl of β-mercaptoethanol (Sigma–Aldrich Co., St. Louis, MO, USA), and 100 µl of Tris-EDTA buffer. Glass beads (BioSpec Products, Inc., Bartlesville, OK, USA) (300 mg; diameter, 0.1 mm) were added to the suspension, and the mixture was subjected to a vigorous vortex procedure for 5 min using a ShakeMaster Auto apparatus (catalog no. BMS-A15; Bio Medical Science Inc., Tokyo, Japan). Acid phenol (Wako Pure Chemical Industries, Ltd., Osaka, Japan) (500 µl) was added, and the mixture was incubated for 10 min at 60◦C. After phenol-chloroform purification and isopropanol precipitation, the nucleic acid fraction was suspended in 0.2 ml of nuclease-free water (Ambion, Inc.).

#### Reverse-Transcription-Quantitative-PCR (RT-qPCR)

Bacterial counts of various bacterial groups including total bacteria, Clostridium coccoides group, C. leptum subgroup, Bacteroides fragilis group, Atopobium cluster, Prevotella, Bifidobacterium, Lactobacillus subgroups and species, Enterobacteriaceae, Enterococcus, Staphylococcus, Streptococcus, C. perfringens, and C. difficile were analyzed by using a sensitive quantitative analytical system based on 16S or 23S rRNA molecules-targeted RT-qPCR, as per the methods described previously (Matsuda et al., 2009, 2012; Sakaguchi et al., 2010; Tsuji et al., 2012). Briefly, RT-qPCR was performed with a Qiagen OneStep RT-PCR kit (Qiagen GmbH, Hilden, Germany). Each reaction mixture (10 µl) was composed of 1X Qiagen OneStep RT-PCR buffer, 0.5X Q-solution buffer, each deoxynucleoside triphosphate at a concentration of 400 µM, a 1:100,000 dilution of SYBR green I (BioWhittaker Molecular Applications, Rockland, ME, USA), 0.4 µl of Qiagen OneStep RT-PCR enzyme mixture, and 5 µl of template RNA. Each primer set was added at a concentration of 0.6 µM. The reaction mixture was incubated at 50◦C for 30 min for reverse transcription. The continuous amplification program consisted of one cycle at 95◦C for 15 min, followed by 45 cycles at 94◦C for 20 s, 55/60◦C for 20 s, and 72◦C for 50 s. The fluorescent products were detected in the last step of each cycle. A melting curve analysis was performed after amplification to distinguish the targeted PCR products from the non-targeted ones. The melting curve was obtained by slow heating at temperatures from 60 to 95◦C at a rate of 0.2◦C/s with continuous fluorescence collection. Amplification and detection were performed in 384-well optical plates with an ABI PRISM R 7900HT sequence detection system (Applied Biosystems, Foster, CA, USA). Standard curves for the corresponding standard bacterial strains were generated by using Cq (quantification cycle) values and the corresponding cell counts, which were determined microscopically with the DAPI (40 ,6-diamidino-2-phenylindole) staining method as previously described (Matsuda et al., 2009). To determine the target bacterial populations in the fecal samples, 1/20,000, 1/200,000, and 1/2,000,000 portions of the RNA solution were subjected to RT-qPCR. The Cq-values in the linear range of the assay were applied to the analytical curve generated in the same experiment to obtain the corresponding bacterial count in each nucleic acid sample; this count was then converted to the count per sample. The details of analytical validation of specificities and sensitivities of these assays have been reported elsewhere (Matsuda et al., 2009, 2012; Sakaguchi et al., 2010). Briefly, the specificity of each primer set was confirmed against the total RNA fractions extracted from 105 cells of the corresponding standard bacterial strain (Matsuda et al., 2009) by using RT-qPCR. The amplified signal was considered positive (+) at >104 standard cells, positive/negative (±) at 104 to 100 standard cells, and negative (−) at <100 standard cells. The amplified signal was also defined as negative (−) when the corresponding melting curve had a peak different from that of the standard strain. To determine the detection sensitivity, RNA fractions were extracted from culture samples of corresponding reference strain in the early stationary phase (24 h), and bacterial counts were determined microscopically by DAPI staining. Serial RNA dilutions corresponding to bacterial counts ranging from 10−3 to 105 cells were assessed by RT-qPCR assay. The range of RNA concentrations at which there was linearity with Cq-value was confirmed (R 2 > 0.99). The details of the 16S or 23S rRNA gene targeted primers and the corresponding primer sequences, annealing temperatures and the minimum detection limits have been provided in the Supplementary Table S2.

#### Statistical Analyses

The results of bacterial count (log10 cells per gram of feces) are expressed as mean ± standard deviation. The detection rate was expressed as the percentage of infants in which the specific bacterium was detected. During analysis in the spreadsheets to calculate the mean bacterial count and the detection

rate, the cells were left blank if the specific bacterium was not detected (i.e., below the detection limit) in a sample. The count of genus Lactobacillus was expressed as the sum of the counts of six subgroups (L. casei subgroup, L. gasseri subgroup, L. plantarum subgroup, L. reuteri subgroup, L. ruminis subgroup, and L. sakei subgroup) and two species (L. brevis and L. fermentum). The comparisons of fecal bacterial counts by the mode of delivery were calculated by unpaired Student's t-test. Differences in the detection rate of bacteria were calculated by Fisher's exact probability test. P < 0.05 was considered statistically significant.

# RESULTS

We detected several bacterial groups in the first meconium samples of both VG and CS infants. There was no significant difference in the birth weight, height or other generic parameters according to the birth mode (**Table 1**). The count and detection rate of intestinal bacteria are presented in **Table 2**. Overall, the meconium of 95% infants were found to harbor one or more types of bacteria; whereas the meconium of remaining 5% infants appeared to be sterile, i.e., no bacteria were detected in these samples. B. fragilis group, Enterobacteriaceae, Enterococcus,

#### TABLE 2 | Count and detection rate of major bacterial groups in the meconium of vaginally- and cesarean-born babies.

1Mean ± SD of Log10 cells/g feces.

2Detection rate (%) was expressed as the percentage of infants in which the specific bacterium was detected.

§ Total bacteria are expressed as the sum of all the other bacteria listed in the table.

#The count of genus Lactobacillus was expressed as the sum of the counts of six subgroups (L. casei subgroup, L. gasseri subgroup, L. plantarum subgroup, L. reuteri subgroup, L. ruminis subgroup, and L. sakei subgroup) and two species (L. brevis, L. fermentum).

∗P = 0.012, vs. vaginally-born (Fisher's exact probability test).

ND, not detected.

#### TABLE 3 | Count and detection rate of Lactobacillus subgroups and species in the meconium of vaginally- and cesarean-born babies.

1Mean ± SD of Log10 cells/g feces.

2Detection rate (%) was expressed as the percentage of infants in which the specific bacterium was detected.

∗P = 0.04, vs. vaginally-born (Fisher's exact probability test).

ND, not detected.

Streptococcus, and Staphylococcus were most prevalent members (detected in more than 50% infants), with counts ranging from 105 to 108 cells/g sample, followed by bifidobacteria, lactobacilli, C. coccoides group, C. leptum subgroup, C. perfringens, Atopobium cluster, and Prevotella (**Table 2**). Of total 151 infants, C. difficile was detected only in one baby (in VG group).

Compared to VG infants, the meconium of CS infants were significantly less often colonized with Lactobacillus genus (6% vs. 37%; P = 0.01) (**Table 2**). Further examination of eight Lactobacillus subgroups and species revealed that L. gasseri subgroup was the most prevalent subgroup in VG infants (detected in 31% babies) whereas rest of the subgroups and species were detected only in less than 6% babies (**Table 3**). The detection rate of L. gasseri subgroup was significantly lower in CS babies compared to those born vaginally (6% vs. 31%; P = 0.04). Overall, total seven Lactobacillus subgroups/species, i.e., L. gasseri subgroup, L. ruminis subgroup, L. casei subgroup, L. reuteri subgroup, L. sakei subgroup, L. plantarum subgroup, and L. brevis were detected in the meconium samples of VG group, whereas only two members, i.e., L. gasseri subgroup and L. brevis were detected in CS group (P = 0.04). Other than lactobacilli, no significant difference was observed in the carriage of any other bacterial group in the meconium samples. However, the count of Enterobacteriacea was insignificantly lower in CS babies compared to VG babies (P = 0.058) (**Table 2**). Also, the overall ratio of facultative vs. obligate anaerobes (in proportion to total bacterial count) was significantly lower in CS babies than those delivered vaginally (P = 0.005) (**Figure 1A**); and accordingly, the overall proportional bacterial composition appeared to be slightly different in VG and CS babies (**Figure 1B**). Follow-up analysis of lactobacilli revealed that, compared to VG infants, the detection rate of Lactobacillus genus and several subgroups and species remained significantly or insignificantly lower in CS infants at different time-points during the first 6 months of life (**Figure 2**); but these differences tended to disappear by age 3 years.

#### DISCUSSION

To our knowledge, this is the largest birth cohort studied demonstrating a quantitative profile of the meconium bacterial microbiota in babies delivered vaginally or via C-section. Several remarkable studies have recently reported the presence of bacteria not only in meconium but also in placenta, amnion, and umbilical cord blood (Gosalbes et al., 2013; Hu et al., 2013; Del Chierico et al., 2015; Collado et al., 2016); but these were primarily based on DNA-based sequencing methods which, while being elegantly elaborative, may overlook several subdominant bacteria (e.g., ≤104 cells/g feces), particularly during the earliest phase of life when the microbiota is immature. In this context, our data should fortify these evidences with important information of population levels of not only the predominant but also the subdominant bacteria that may inhabit the infant gut during critical developmental stages. We detected bacteria in the meconium of 95% babies while rest 5% samples appeared to be sterile (i.e., no bacteria detected). However, previous studies on term infants reported the presence of bacteria in 66% (using 16S rRNA gene-targeted FISH method) (Hansen et al., 2015) and 77% (using 16S/23S rRNA genetargeted qPCR) (Martin et al., 2016) of total babies studied. This difference can most possibly be ascribed to differences in the detection sensitivities of the methods used, and hence could corroborate the advantage of high sensitivity of our RT-qPCR assays. We detected several bacterial clades, albeit with varying detection rates and numbers, in the meconium of both VG and CS infants (**Tables 2** and **3**), which clearly hint that the intrauterine environment harbors several bacterial communities which may provide the early inoculum for intestinal microbiota colonization. Further, these data show that the facultative anaerobes thrive–and hence are the first settlers–in the primitive gut, thereby pointing toward a relatively aerobic intestinal environment (Backhed et al., 2015; Del Chierico et al., 2015; Bokulich et al., 2016; Collado et al., 2016; Martin et al., 2016). This also suggests that the pioneer microbiota core is comprised predominantly of facultative anaerobes such as Proteobacteria, Staphylococci, Streptococci, Enterococci etc.; whereas obligates belonging to Firmicutes, Bacteroidetes, and Actinobacteria take over the predominance later on during infancy and early childhood, as also evident from the followup data of this cohort (Supplementary Table S1). This also concurs well with a recent study by our colleagues who reported that the 1st-day microbiota of healthy infants is by and large predominated by Enterobacteria or Staphylococci, but this predominance is mostly, rapidly transitioned to Bifidobacteriumdominated microbiota within a few days after birth (Matsuki et al., 2016).

Early-life microbiota colonization is strongly impacted by birth mode (Penders et al., 2006). During vaginal delivery, the infant is seeded with certain bacteria from the birth canal; but C-section bypasses this seeding thereby resulting in a different spectrum of pioneering microbiota (Dominguez-Bello et al., 2010; Backhed et al., 2015; Bokulich et al., 2016; Nuriel-Ohayon et al., 2016). Therefore, to determine whether–and how prominently–these differences exist in the first-pass samples, we compared the meconium microbiota of vaginally- vs. cesarean-born infants. The lower detection rate of Lactobacillus genus and the L. gasseri subgroup in the meconium of CS babies was intriguing. To know how long this difference persisted, we followed up the Lactobacillus carriage, and interestingly–albeit not surprisingly–VG and CS infants were found to exhibit dissimilar degrees of Lactobacillus detection rate at several time-points during the first 6 months of life, with detection rate being relatively lower in CS infants (**Figure 2**). It might also be possible that some vaginal materials are also transmitted from mother to baby during vaginal delivery that may have promoted the growth and activity of lactobacilli in vaginally-born babies; however, we were not able to verify this issue because of the unavailability of the maternal samples in this study. Interestingly, by using same RT-qPCR assays, we recently reported that the vaginal microbiota of healthy Japanese women of reproductive age is predominated numerically by Lactobacillus communities among

FIGURE 1 | Comparison of proportional ratio of obligatory anaerobic vs. facultative anaerobic bacteria (A), and relative proportions of different gut bacteria (B) in the meconium samples of vaginally- vs. cesarean-born infants. Proportions were calculated by using the original arithmetical number of the bacterial count and are expressed as the percent of numerical value of the total bacterial count. Obligates: Clostridium coccoides group, C. leptum subgroup, C. perfringens, Bacteroides fragilis group, and Bifidobacterium. Facultatives: Lactobacillus, Enterobacteriacea, Enterococcus, Staphylococcus, and Streptococcus.

detected. The count of genus Lactobacillus was expressed as the sum of the counts of six subgroups (L. casei subgroup, L. gasseri subgroup, L. plantarum subgroup, L. reuteri subgroup, L. ruminis subgroup, and L. sakei subgroup) and two species (L. brevis, L. fermentum). ∗P < 0.05 vs. vaginally-born at same-point (Fisher's exact test). Age (x-axis): 1, 3, and 7 days, 1, 3, and 6 months, 3 years.

which L. gasseri subgroup is a major constituent (Kurakawa et al., 2015a). Also, lactobacilli are rarely detected in amniotic fluid and placenta (DiGiulio et al., 2010; Aagaard et al., 2014). Collectively, these studies suggest a prominent mother-to-baby transmission of vaginal Lactobacillus communities during vaginal delivery, while indicating a delayed sampling of lactobacilli in CS babies' gut. However, given the limitation of large difference between the numbers of vaginally- and cesareanborn infants, this finding needs to be corroborated in studies with comparable number of subjects in the two groups. Also, given that L. gasseri subgroup comprises several beneficial commensal species that can elicit probiotic health benefits such as anti-pathogenic activity, bacteriocin production, immunemodulation, and maintenance of gut homeostasis (Selle and Klaenhammer, 2013); studies are needed to investigate the impact, if any, of its lower/delayed colonization in CS babies. As for the clinical milieu, this delayed sampling does not seem to directly indicate any disease risk, because all these infants were apparently healthy (at least until age 3 years). Nevertheless, differences in Lactobacillus carriage in the 'first flora' justify further research and should be an exciting theme for future studies about viable therapeutic targets (probiotics, prebiotics, etc.) in context to the gut dysbiosis, particularly in cesarean-born and/ or preterm babies.