Defining and Directing Gut Microbiota Maturation in Early Life: A Nutrition Perspective

18 min read
Caroline Le Roy

The development of the microbiome within the human digestive tract starts at birth and continues up to approximately 3 years of age when the microbial ecosystem resembles a more adulthood-like state. The pace of colonization and diversification of the gut microbiota in the early stages of life has been linked to short- and long-term health outcomes. Characterizing optimal maturation of the ecosystem may help identifying adverse events that impair the process and also factors that support and guide it, such as diet. To date, researchers have looked at the evolution over time of gut microbiota parameters such as diversity, taxa abundance, or specific functions. A more global approach has used “microbiota age” to capture maturation trajectory through machine learning models. In this review, the use and limitations of the latest methods to capture and understand microbiota maturation will be discussed. Then the role of nutrition in directing gut microbiota maturation in early life will be described together with the challenges that limit our comprehension of the effects of diet on the gut microbiota.

The Human Gut Microbiota in Early Life 

From birth, infants undergo a sequence of development steps that contribute to the programming of their long-term health. The gut microbiota, defined as the collection of microorganisms residing in the human intestinal tract [1], play an integrated role within this multifactorial and complex process. The modifiable nature of the gut microbiota, together with its connection to multiple aspects of health (e.g., immune, metabolic, cognitive) and its essential role in energy harvest and protection against pathogens, makes it an ideal target to support healthy maturation. 

The colonization process of the gut starts from birth and continues in a dynamic manner up until 3 years of age, when the microbial ecosystem stabilizes in a conformation resembling adultlike composition. This period is mostly characterized by a gradual increase in alpha diversity that starts to plateau at around 1 year of age. From a taxonomic perspective, the composition of the ecosystem becomes more individualized with time, demonstrated by an increase in beta diversity across subjects.

Globally, common features of the colonization cascade have been identified, such as a global decrease in Enterobacteriaceae, increased relative abundance of Bacteroidaceae and Ruminococcaceae, and a transitional bloom of Bifidobacteriaceae before 1 year of age [2, 3]. Functionally, the gut microbiota transitions from a predominant capability to degrade simple carbohydrates, while producing vitamins, toward an increased aptitude for complex carbohydrate degradation and production of short-chain fatty acids. Although the optimal pace of progression remains to be clarified, it is evident that they are tightly linked to the overall maturation process of the host while responding to changes of feeding regimen. A parameter that captures current maturation status of the microbiome may therefore bring new insights to the links between diet and healthy development. Hence, the interest in developing metrics that can capture the age appropriateness of the maturation process of the gut microbiota.

Capturing Normal Maturation

There have been several attempts to address such a standardized metric during the first 1,000 days of life. Mirroring the growth curve standards of the WHO, “relative microbiota maturity” or “microbiota-for-age z-scores” have been generated to model the maturation trajectory of the gut microbiota in early life. First developed in 2014 to compare the evolution of the gut microbiota of infants suffering from severe acute malnutrition to those of healthy infants, the method was successful in capturing a delayed maturation of the ecosystem in the undernourished group as well as the effect of a nutritional intervention in this same study group [4].

The main advantage of this method lies in its ability to summarize the complexity of the microbial ecology, and its evolution during infancy, within one variable. It then becomes possible to evaluate at any specific time point if the level of maturation of the ecosystem deviates from an age-appropriate reference. Additionally, it is possible to extract from the model the microbial features that contribute most to the process. This can provide indications of certain microbes to target in order to support age-appropriate microbiota maturation (Fig. 1).

Although such a method promises to assess the effects of an intervention or a risk factor on gut microbiota maturation, several limitations need to be considered. First, the method relies on the access to data from “healthy” infants to build a reference maturation curve. It is commonly accepted that exclusively breastfed and vaginally born infants are considered as gold standard in terms of microbiome maturation [2–4].

Other factors to include in a definition of “health” will be progressively subjective, although it is commonly accepted to account for antibiotic use and adverse events [5]. Other potentially relevant factors defining a “healthy” reference set may be inadvertently excluded as gut microbiota variance between subjects remains poorly explained and understood. This highlights the need to include accurate, extensive metadata along with sequencing data on submission to public repositories in order to facilitate and enable this filtering process, which will evolve with time.

Geographic specificity of gut microbiota maturation may need to be considered and complicate generalization of results. A universal approach may be possible considering only higher taxonomic levels such as phyla or family or functions when building the models [5]. However, this will sacrifice the identification of subtle microbial changes at lower taxonomical levels that may be of relevance to host physiology. This conflict applies to any use of summary metrics, rather than their component parameters, when characterizing gut microbiota maturation. Hence, further in-depth analysis may complement this approach in order to explain deviations from normal of the gut microbiota in infancy.

Using Diet to Direct Microbiome Maturation

Evidence of the Importance of Nutrition in Shaping Early Life Microbiota Maturation
Among environmental factors, diet may be the most relevant in shaping the gut microbiota at all stages of life. Starting at birth, significant and consistent variations in the gut microbiota composition have been observed between breastfed and formula-fed infants [3]. The gut microbiota of the first group is characterized by a greater abundance of Bifidobacteriaceae, lower levels of Enterobacteriaceae, and slower diversification of the ecosystem compared to their formula-fed counterparts up until 6 months of age.

Along with its striking effects on gut microbiota maturation, breastfeeding has also been associated with numerous health benefits compared to formula feeding, including lower prevalence of infection in early life and reduced chances of developing cardiometabolic diseases such as type 1 diabetes [2]. Although the causal role of the microbiota in the programming of these health benefits remains to be demonstrated, it highlights the potential importance of the diet–gut microbiota duo in health and diseases. It is consequently of paramount importance to identify the elements of breast milk that can influence the maturation process of the gut microbiota in order to develop suitable alternatives where breastfeeding is not an option.

To date, human milk oligosaccharides (HMOs) have been identified as one of the most potent breast milk components to selectively modulate the growth of certain microbes, including Bifidobacteriaceae [6, 7], as well as gut microbiota maturation [8, 9]. In addition to human milk oligosaccharides, sphingolipids are another family of compounds found in breast milk but absent in formula milk that could offer potential benefits in early life. Indeed, some studies have suggested that these lipids, beside their importance in immune development, may also be able to impact the composition of the gut microbiota [10, 11]. More importantly, the metabolism and production of this class of compounds by microorganisms may impact host physiology [12–14]

The introduction of complementary food after the exclusive breastfeeding period, starting from 6 months onward (according to WHO recommendations), induces a rapid and drastic reorientation of the gut microbiota composition and diversification [15, 16]. Observational studies have shed light on this process, identifying associations between certain nutrients or ingredients and components of the gut microbiota. Together with the studies conducted in adults, they provide guidance on how diet may be used to shape the gut microbiota. However, our understanding of the way by which diet could be used to reshape the gut microbiota remains limited. The nature of diet gut microbiota interactions is complex, as illustrated by the analytical considerations discussed below.

Capturing the Temporal Effect of Complementary Feeding on Gut Microbiota Maturation
First, observational microbiome studies in infants have not always captured complementary food intake. In addition, methods to capture complementary feeding patterns for microbiome studies have not yet been standardized within the field. Hence, dietary information is captured heterogeneously between studies, ranging from simplified food frequency questionnaires (FFQs) providing low data granularity to food diaries that only capture food intake for a short period of time. Consequently, the possibilities to conduct meta analysis and cross results comparison remain limited. Poor capture of dietary intake may relate to the fact that most microbiome studies in infancy have focused on the link with health outcomes rather than diet.

To add to the complexity of including standardized dietary questionnaires to microbiome studies, the dynamic temporal aspect of gut microbiota maturation requires longitudinal fecal sampling mirrored by a continuous monitoring of the evolution of feeding patterns in the first few years of life. Accordingly, both dietary exposures together with timing and speed of food introduction and diversification would need to be recorded. FFQs should be collected regularly to accurately capture such a process, to evaluate the typical foods consumed on average by infants from introduction of complementary food to full adoption of the family diet. Additional indications of time of introduction of each food should also be collected to enable a close follow-up of the introduction and diversification process while capturing how well new foods may establish themselves within the habitual diet of the child (Fig. 2). Additionally, these records should capture the mode of food introduction to the baby and significant differences in gut microbiota diversity have been observed between spoon-fed and baby-led introduction of solid food infants [17]. Although collection of such dense dietary data would surely enable better capture of the effects of diet on gut microbiota maturation and therefore inform future dietary guidelines, the burden on participants may be an unavoidable drawback that could impair data quality [18, 19].

Geographical Considerations

Nutrition and its effects on the host and its gut microbiota have traditionally been explored through the prism of nutrient intake and dietary patterns. Although this has proven useful in depicting how diet may affect health and diseases in adults and infants, it has shown limited success when adapted to gut microbiota ecology [20, 21]. Johnson et al. demonstrated elegantly that looking at food rather than nutrient intake better explained gut microbiota variance across subjects [22]. Arguably, metabolic composition of food is more complex than the ∼100 nutrients traditionally studied. For instance, Barabási et al. displayed that a food may contain over 1,000 different compounds [23]. Knowing the extent of the metabolic capacity of the gut microbiota compared to its host, it is easy to imagine how these non regarded food components may biochemically interact with the gut microbial ecosystem. In addition, food processing has a major impact on metabolic composition and bioavailability of compounds, which is known to differentially impact the gut microbiota [24]. Hence, looking at food in its globality rather than as a restricted combination of nutrients could improve our characterization of the effects of diet on the gut microbiota.

However, looking at diet from a food perspective comes with one major drawback. While all nutrients are consumed universally, enabling meta-analysis of datasets across the globe, their food sources within one diet are highly geography and culture dependent. Hence, looking at food rather than nutrients may lessen transfer of knowledge and learning across populations. A more promising avenue would be to extend the characterization of the molecular composition of foods within current databases. One prime candidate to start such initiative would be fiber. Fiber consumption has been shown to impact gut microbiota composition in numerous studies [25]. Besides the importance of the quantity of fiber consumed, their quality, meaning their chemical conformation, appears to play an important role in how fiber intake can shape the gut microbiota [26]. Future studies may focus on exploring the effects of individual fiber types or other understudied food compounds on the gut microbiota in early life to inform future intervention strategies to support gut microbiota maturation.

Demonstrating that Gut Microbiota Maturation Can Be Framed by Appropriate Feeding Practices

Besides longitudinal data analysis, cross-sectional evaluation of the effects of diet on the gut microbiota may also bring some insights. Once the maturation process of the gut microbiota is well defined, the next step would be to understand how certain dietary components may support the growth of taxa relevant to the maturation steps in different time windows. The best approach for such an evaluation would be to define the effects of acute and chronic exposure of food elements on the gut microbiota through collection of both FFQ (chronic) and food records (acute) [27, 28]. Taken together, the data can provide guidance on how to elicit rapid reshaping of the gut microbiota ecology while defining feeding strategies to sustain those changes in the long run (Fig. 2)

Interventional studies could then be implemented to demonstrate the causal role of a food or a specific nutrient on gut microbiota maturation. Interventional studies have demonstrated that diet can be used to reshape infant gut microbiota. For instance, in a randomized control trial conducted on 250 infants between 4 and 7 months, Plaza-Diaz et al. demonstrated that whole grain versus refine grain consumption could alter the composition of the gut microbiota [29].

Finally, studies exploring more long-term effects of diet on the gut microbiota would be highly valuable as they may enable demonstration of how appropriate feeding interventions at a given time point may be able to durably impact the composition of the gut ecosystem with potential long-term consequences on health (Fig. 2). For instance, a recent study looking at the long-term effects of probiotics has demonstrated that effects of their administration could still be observed up to 1 year after the intervention period, provided that no adverse events had occurred in the meantime [30]. Taken together, this evidence suggests that long-term programming of the gut microbiota through relatively short interventions may be possible.

Conclusion and Way Forward

Accurate definition of the maturation steps of the gut microbiota opens up the possibility to identify risk factors that may interfere with appropriate development. In ideal circumstances, this would lead to the development of a maturation trajectory that would highlight if the gut microbiota of an infant deviate from the healthy reference. Development of such summary measures requires further work to ensure that they can be used universally and that they are sensitive enough to capture changes that are physiologically relevant to the host. Once a microbiota reference trajectory is established, diet appears to be the most potent way to support the maturation process. However, the way that diet can be used to selectively impact the maturation of the gut microbiota is still poorly understood. This is mostly due to lack of standardization of dietary capture diet within the field. The way we capture food when studying the gut microbiota should be revised to match the metabolic potential of the ecosystem. Future studies in early life should prioritize collection of dense dietary data to enable the characterization of the effects of food introduction, diversification, and establishment on gut microbiota maturation. Such studies would frame the development of nutritional guidelines and interventions to support appropriate gut microbiota maturation.



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