Prebiotics Mediate Microbial Interactions in a Consortium of the Infant Gut Microbiome

2'-FL and cross-feeding bifidobacteria reshaped the gut microbiota of infants with atopic dermatitis ex vivo and prevented dermatitis in mice post-microbiota transplantation through retinol metabolism activation

2'-Fucosyllactose (2'-FL), a predominant human milk oligosaccharide, plays a crucial role in the development of the infant gut microbiota and immune system. However, the microbiota of infants with atopic dermatitis (AD) often has difficulty utilizing 2'-FL. Here, we found that strains from human milk, Bifidobacterium bifidum FN120 and Bifidobacterium longum subsp. longum FN103, utilized 2'-FL for growth by cross-feeding. Through an ex vivo continuous fermentation system, we found that 2'-FL and cross-feeding bifidobacteria synergistically enhanced the production of short-chain fatty acids (SCFAs), particularly acetate and propionate, while reshaping the gut microbiota in infants with AD. The reshaped microbiota was then transplanted into oxazolone-induced mice. We observed that AD symptoms in mice were effectively prevented, with significant changes in the ileum microbiota and increased intestinal SCFA levels. RNA sequencing analysis of Peyer's patches in the small intestine revealed activation of the retinol metabolic pathway. Nontargeted metabolomics analysis revealed a significant increase in plasma retinoate levels, which correlated markedly with AD-related markers. Collectively, our study demonstrated that supplementation with cross-feeding bifidobacteria and 2'-FL reshaped the gut microbiota, activated retinol metabolic pathways, promoted immune tolerance, and thereby prevented AD. Our findings provide novel insights into the therapeutic potential of combining prebiotics and probiotics to modulate the gut - skin axis and support immune tolerance in early life, offering a promising strategy for infantile AD management and prevention.

Identification of carbohydrate gene clusters obtained from in vitro fermentations as predictive biomarkers of prebiotic responses

BACKGROUND

Prebiotic fibers are non-digestible substrates that modulate the gut microbiome by promoting expansion of microbes having the genetic and physiological potential to utilize those molecules. Although several prebiotic substrates have been consistently shown to provide health benefits in human clinical trials, responder and non-responder phenotypes are often reported. These observations had led to interest in identifying, a priori, prebiotic responders and non-responders as a basis for personalized nutrition. In this study, we conducted in vitro fecal enrichments and applied shotgun metagenomics and machine learning tools to identify microbial gene signatures from adult subjects that could be used to predict prebiotic responders and non-responders.

RESULTS

Using short chain fatty acids as a targeted response, we identified genetic features, consisting of carbohydrate active enzymes, transcription factors and sugar transporters, from metagenomic sequencing of in vitro fermentations for three prebiotic substrates: xylooligosacharides, fructooligosacharides, and inulin. A machine learning approach was then used to select substrate-specific gene signatures as predictive features. These features were found to be predictive for XOS responders with respect to SCFA production in an in vivo trial.

CONCLUSIONS

Our results confirm the bifidogenic effect of commonly used prebiotic substrates along with inter-individual microbial responses towards these substrates. We successfully trained classifiers for the prediction of prebiotic responders towards XOS and inulin with robust accuracy (≥ AUC 0.9) and demonstrated its utility in a human feeding trial. Overall, the findings from this study highlight the practical implementation of pre-intervention targeted profiling of individual microbiomes to stratify responders and non-responders.

Decoding host-microbiome interactions through co-expression network analysis within the non-human primate intestine

The gut microbiome affects the health status of the host through complex interactions with the host's intestinal wall. These host-microbiome interactions may spatially vary along the physical and chemical environment of the intestine, but these changes remain unknown. This study investigated these intricate relationships through a gene co-expression network analysis based on dual transcriptome profiling of different intestinal sites-cecum, transverse colon, and rectum-of the primate common marmoset. We proposed a gene module extraction algorithm based on the graph theory to find tightly interacting gene modules of the host and the microbiome from a vast co-expression network. The 27 gene modules identified by this method, which include both host and microbiome genes, not only produced results consistent with previous studies regarding the host-microbiome relationships, but also provided new insights into microbiome genes acting as potential mediators in host-microbiome interplays. Specifically, we discovered associations between the host gene FBP1, a cancer marker, and polysaccharide degradation-related genes (pfkA and fucI) coded by Bacteroides vulgatus, as well as relationships between host B cell-specific genes (CD19, CD22, CD79B, and PTPN6) and a tryptophan synthesis gene (trpB) coded by Parabacteroides distasonis. Furthermore, our proposed module extraction algorithm surpassed existing approaches by successfully defining more functionally related gene modules, providing insights for understanding the complex relationship between the host and the microbiome.IMPORTANCEWe unveiled the intricate dynamics of the host-microbiome interactions along the colon by identifying closely interacting gene modules from a vast gene co-expression network, constructed based on simultaneous profiling of both host and microbiome transcriptomes. Our proposed gene module extraction algorithm, designed to interpret inter-species interactions, enabled the identification of functionally related gene modules encompassing both host and microbiome genes, which was challenging with conventional modularity maximization algorithms. Through these identified gene modules, we discerned previously unrecognized bacterial genes that potentially mediate in known relationships between host genes and specific bacterial species. Our findings underscore the spatial variations in host-microbiome interactions along the colon, rather than displaying a uniform pattern throughout the colon.

Positive modulation of a new reconstructed human gut microbiota by Maitake extract helpfully boosts the intestinal environment in vitro

The human gut is a complex environment where the microbiota and its metabolites play a crucial role in the maintenance of a healthy state. The aim of the present work is the reconstruction of a new in vitro minimal human gut microbiota resembling the microbe-microbe networking comprising the principal phyla (Bacillota, Bacteroidota, Pseudomonadota, and Actinomycetota), to comprehend the intestinal ecosystem complexity. In the reductionist model, we mimicked the administration of Maitake extract as prebiotic and a probiotic formulation (three strains belonging to Lactobacillus and Bifidobacterium genera), evaluating the modulation of strain levels, the release of beneficial metabolites, and their health-promoting effects on human cell lines of the intestinal environment. The administration of Maitake and the selected probiotic strains generated a positive modulation of the in vitro bacterial community by qPCR analyses, evidencing the prominence of beneficial strains (Lactiplantibacillus plantarum and Bifidobacterium animalis subsp. lactis) after 48 hours. The bacterial community growths were associated with the production of metabolites over time through GC-MSD analyses such as lactate, butyrate, and propionate. Their effects on the host were evaluated on cell lines of the intestinal epithelium and the immune system, evidencing positive antioxidant (upregulation of SOD1 and NQO1 genes in HT-29 cell line) and anti-inflammatory effects (production of IL-10 from all the PBMCs). Therefore, the results highlighted a positive modulation induced by the synergic activities of probiotics and Maitake, inducing a tolerogenic microenvironment.

Screening competition and cross-feeding interactions during utilization of human milk oligosaccharides by gut microbes

Background: The infant gut microbiome is a complex community that influences short- and long-term health. Its assembly and composition are governed by variables such as the feeding type. Breast milk provides infants an important supply of human milk oligosaccharides (HMO), a broad family of carbohydrates comprising neutral, fucosylated, and sialylated molecules. There is a positive association between HMOs and the overrepresentation of Bifidobacterium species in the infant gut, which is sustained by multiple molecular determinants present in the genomes of these species. Infant-gut-associated Bifidobacterium species usually share a similar niche and display similar HMO inclinations, suggesting they compete for these resources. There is also strong evidence of cross-feeding interactions between HMO-derived molecules and bifidobacteria. Methods: In this study, we screened for unidirectional and bidirectional interactions between Bifidobacterium and other species using individual HMO. Bifidobacterium bifidum and Bacteroides thetaiotaomicron increased the growth of several other species when their supernatants were used, probably mediated by the partial degradation of HMO. In contrast, Bifidobacterium longum subsp. infantis. supernatants did not exhibit positive growth. Results: Bifidobacterium species compete for lacto-N-tetraose, which is associated with reduced bidirectional growth. The outcome of these interactions was HMO-dependent, in which the two species could compete for one substrate but cross-feed on another. 2'-fucosyllactose and lacto-N-neotetraose are associated with several positive interactions that generally originate from the partial degradation of these HMOs. Conclusion: This study presents evidence for complex interactions during HMO utilization, which can be cooperative or competitive, depending on the nature of the HMO. This information could be useful for understanding how breast milk supports the growth of some Bifidobacterium species, shaping the ecology of this important microbial community.

Precision modulation of dysbiotic adult microbiomes with a human-milk-derived synbiotic reshapes gut microbial composition and metabolites

Manipulation of the gut microbiome using live biotherapeutic products shows promise for clinical applications but remains challenging to achieve. Here, we induced dysbiosis in 56 healthy volunteers using antibiotics to test a synbiotic comprising the infant gut microbe, Bifidobacterium longum subspecies infantis (B. infantis), and human milk oligosaccharides (HMOs). B. infantis engrafted in 76% of subjects in an HMO-dependent manner, reaching a relative abundance of up to 81%. Changes in microbiome composition and gut metabolites reflect altered recovery of engrafted subjects compared with controls. Engraftment associates with increases in lactate-consuming Veillonella, faster acetate recovery, and changes in indolelactate and p-cresol sulfate, metabolites that impact host inflammatory status. Furthermore, Veillonella co-cultured in vitro and in vivo with B. infantis and HMO converts lactate produced by B. infantis to propionate, an important mediator of host physiology. These results suggest that the synbiotic reproducibly and predictably modulates recovery of a dysbiotic microbiome.

Developing a Fluorescent Inducible System for Free Fucose Quantification in Escherichia coli

L-Fucose is a monosaccharide abundant in mammalian glycoconjugates. In humans, fucose can be found in human milk oligosaccharides (HMOs), mucins, and glycoproteins in the intestinal epithelium. The bacterial consumption of fucose and fucosylated HMOs is critical in the gut microbiome assembly of infants, dominated by Bifidobacterium. Fucose metabolism is important for the production of short-chain fatty acids and is involved in cross-feeding microbial interactions. Methods for assessing fucose concentrations in complex media are lacking. Here we designed and developed a molecular quantification method of free fucose using fluorescent Escherichia coli. For this, low- and high-copy plasmids were evaluated with and without the transcription factor fucR and its respective fucose-inducible promoter controlling the reporter gene sfGFP. E. coli BL21 transformed with a high copy plasmid containing pFuc and fucR displayed a high resolution across increasing fucose concentrations and high fluorescence/OD values after 18 h. The molecular circuit was specific against other monosaccharides and showed a linear response in the 0-45 mM range. Adjusting data to the Hill equation suggested non-cooperative, simple regulation of FucR to its promoter. Finally, the biosensor was tested on different concentrations of free fucose and the supernatant of Bifidobacterium bifidum JCM 1254 supplemented with 2-fucosyl lactose, indicating the applicability of the method in detecting free fucose. In conclusion, a bacterial biosensor of fucose was validated with good sensitivity and precision. A biological method for quantifying fucose could be useful for nutraceutical and microbiological applications, as well as molecular diagnostics.

Infant Fecal Fermentations with Galacto-Oligosaccharides and 2′-Fucosyllactose Show Differential Bifidobacterium longum Stimulation at Subspecies Level

The objective of the current study was to evaluate the potential of 2′-FL and GOS, individually and combined, in beneficially modulating the microbial composition of infant and toddler (12–18 months) feces using the micro-Matrix bioreactor. In addition, the impacts of GOS and 2′-FL, individually and combined, on the outgrowth of fecal bifidobacteria at (sub)species level was investigated using the baby M-SHIME® model. For young toddlers, significant increases in the genera Bifidobacterium, Veillonella, and Streptococcus, and decreases in Enterobacteriaceae, Clostridium XIVa, and Roseburia were observed in all supplemented fermentations. In addition, GOS, and combinations of GOS and 2′-FL, increased Collinsella and decreased Salmonella, whereas 2′-FL, and combined GOS and 2′-FL, decreased Dorea. Alpha diversity increased significantly in infants with GOS and/or 2′-FL, as well as the relative abundances of the genera Veillonella and Akkermansia with 2′-FL, and Lactobacillus with GOS. Combinations of GOS and 2′-FL significantly stimulated Veillonella, Lactobacillus, Bifidobacterium, and Streptococcus. In all supplemented fermentations, Proteobacteria decreased, with the most profound decreases accomplished by the combination of GOS and 2′-FL. When zooming in on the different (sub)species of Bifidobacterium, GOS and 2’-FL were shown to be complementary in stimulating breast-fed infant-associated subspecies of Bifidobacterium longum in a dose-dependent manner: GOS stimulated Bifidobacterium longum subsp. longum, whereas 2′-FL supported outgrowth of Bifidobacterium longum subsp. infantis.

Metabolic Modeling and Bidirectional Culturing of Two Gut Microbes Reveal Cross-Feeding Interactions and Protective Effects on Intestinal Cells

The gut microbiota is constituted by thousands of microbial interactions, some of which correspond to the exchange of metabolic by-products or cross-feeding. Inulin and xylan are two major dietary polysaccharides that are fermented by members of the human gut microbiota, resulting in different metabolic profiles. Here, we integrated community modeling and bidirectional culturing assays to study the metabolic interactions between two gut microbes, Phocaeicola dorei and Lachnoclostridium symbiosum, growing in inulin or xylan, and how they provide a protective effect in cultured cells. P. dorei (previously belonging to the Bacteroides genus) was able to consume inulin and xylan, while L. symposium only used certain inulin fractions to produce butyrate as a major end product. Constrained-based flux simulations of refined genome-scale metabolic models of both microbes predicted high lactate and succinate cross-feeding fluxes between P. dorei and L. symbiosum when growing in each fiber. Bidirectional culture assays in both substrates revealed that L. symbiosum growth increased in the presence of P. dorei. Carbohydrate consumption analyses showed a faster carbohydrate consumption in cocultures compared to monocultures. Lactate and succinate concentrations in bidirectional cocultures were lower than in monocultures, pointing to cross-feeding as initially suggested by the model. Butyrate concentrations were similar across all conditions. Finally, supernatants from both bacteria cultured in xylan in bioreactors significantly reduced tumor necrosis factor-α-induced inflammation in HT-29 cells and exerted a protective effect against the TcdB toxin in Caco-2 epithelial cells. Surprisingly, this effect was not observed in inulin cocultures. Overall, these results highlight the predictive value of metabolic models integrated with microbial culture assays for probing microbial interactions in the gut microbiota. They also provide an example of how metabolic exchange could lead to potential beneficial effects in the host. IMPORTANCE Microbial interactions represent the inner connections in the gut microbiome. By integrating mathematical modeling tools and microbial bidirectional culturing, we determined how two gut commensals engage in the exchange of cross-feeding metabolites, lactate and succinate, for increased growth in two fibers. These interactions underpinned butyrate production in cocultures, resulting in a significant reduction in cellular inflammation and protection against microbial toxins when applied to cellular models.

A Multiscale Spatiotemporal Model Including a Switch from Aerobic to Anaerobic Metabolism Reproduces Succession in the Early Infant Gut Microbiota

The human intestinal microbiota starts to form immediately after birth and is important for the health of the host. During the first days, facultatively anaerobic bacterial species generally dominate, such as Enterobacteriaceae. These are succeeded by strictly anaerobic species, particularly Bifidobacterium species. An early transition to Bifidobacterium species is associated with health benefits; for example, Bifidobacterium species repress growth of pathogenic competitors and modulate the immune response. Succession to Bifidobacterium is thought to be due to consumption of intracolonic oxygen present in newborns by facultative anaerobes, including Enterobacteriaceae. To study if oxygen depletion suffices for the transition to Bifidobacterium species, here we introduced a multiscale mathematical model that considers metabolism, spatial bacterial population dynamics, and cross-feeding. Using publicly available metabolic network data from the AGORA collection, the model simulates ab initio the competition of strictly and facultatively anaerobic species in a gut-like environment under the influence of lactose and oxygen. The model predicts that individual differences in intracolonic oxygen in newborn infants can explain the observed individual variation in succession to anaerobic species, in particular Bifidobacterium species. Bifidobacterium species became dominant in the model by their use of the bifid shunt, which allows Bifidobacterium to switch to suboptimal yield metabolism with fast growth at high lactose concentrations, as predicted here using flux balance analysis. The computational model thus allows us to test the internal plausibility of hypotheses for bacterial colonization and succession in the infant colon. IMPORTANCE The composition of the infant microbiota has a great impact on infant health, but its controlling factors are still incompletely understood. The frequently dominant anaerobic Bifidobacterium species benefit health, e.g., they can keep harmful competitors under control and modulate the intestinal immune response. Controlling factors could include nutritional composition and intestinal mucus composition, as well as environmental factors, such as antibiotics. We introduce a modeling framework of a metabolically realistic intestinal microbial ecology in which hypothetical scenarios can be tested and compared. We present simulations that suggest that greater levels of intraintestinal oxygenation more strongly delay the dominance of Bifidobacterium species, explaining the observed variety of microbial composition and demonstrating the use of the model for hypothesis generation. The framework allowed us to test a variety of controlling factors, including intestinal mixing and transit time. Future versions will also include detailed modeling of oligosaccharide and mucin metabolism.

Dosing a synbiotic of human milk oligosaccharides and B. infantis leads to reversible engraftment in healthy adult microbiomes without antibiotics

Predictable and sustainable engraftment of live biotherapeutic products into the human gut microbiome is being explored as a promising way to modulate the human gut microbiome. We utilize a synbiotic approach pairing the infant gut microbe Bifidobacterium longum subspecies infantis (B. infantis) and human milk oligosaccharides (HMO). B. infantis, which is typically absent in adults, engrafts into healthy adult microbiomes in an HMO-dependent manner at a relative abundance of up to 25% of the bacterial population without antibiotic pretreatment or adverse effects. Corresponding changes in metabolites are detected. Germ-free mice transplanted with dysbiotic human microbiomes also successfully engraft with B. infantis in an HMO-dependent manner, and the synbiotic augments butyrate levels both in this in vivo model and in in vitro cocultures of the synbiotic with specific Firmicutes species. Finally, the synbiotic inhibits the growth of enteropathogens in vitro. Our findings point to a potential safe mechanism for ameliorating dysbioses characteristic of numerous human diseases.

The final fate of food: On the establishment of in vitro colon models

The search for life/health quality has driven the search for a better understanding of food components on the overall individual health, which turns to be intrinsically related to the digestive system. In vitro digestion models are considered an alternative for the in vivo studies for a variety of practical reasons, but further research is still needed concerning the colon model establishment. An effective in vitro colon model should consider all unit operations and transport phenomena, together with chemical and biochemical reactions, material handling and reactor design. Due to the different techniques and dependence on the donor microbiota, it is difficult to obtain a standard protocol with results reproductible in time and space. Furthermore, the colon model should be fed with a representative substrate, thus what happens in upper digestion tract and absorption prior to colon is also of crucial importance. Essentially, there are two ways to think about how to achieve a good and useful in vitro colon model: a complex biomimetic system that provides results comparable with the in vivo studies or a simple system, that despite the fact it could not give physiologically relevant data, it is sufficient to understand the fate of some specific components.

Probiotic low-fat fermented goat milk with passion fruit by-product: In vitro effect on obese individuals' microbiota and on metabolites production

This study aimed to evaluate the impact of a two-week treatment period with probiotic low-fat fermented goat milk by Lactobacillus casei Lc-1, supplemented with passion fruit by-product (1%), on the modulation of gut microbiota from obese individuals using the Simulator of Human Intestinal Microbial Ecosystem (SHIME) system. The effects were carried out through the study of gut microbiota composition, using 16S rRNA next generation sequencing, quantification of short-chain fatty acids (SCFA) and ammonium ions. The microbiota composition changed across three vessels representing the colon regions, because of fermented milk treatment. Fermented goat milk administration caused a reduction of bacteria belonging to genera Prevotella, Megamonas and Succinivibrio, which can produce SCFA, and an increase of Lactobacillus and Bifidobacterium genera in all simulated colon regions. There was no effect on SCFA and on ammonium ions concentration during treatment period. Fermented milk shifted the obese donors' microbiota without changing metabolites production. It happens, possibly, due to a balance in abundances among bacterial genera that can produce or not SCFA, and among bacterial genera with high or low proteolytic activity. Our outcomes help to clarify the effects of the ingestion of a probiotic low-fat fermented goat milk product on colon microbiota composition.

Applying Differential Neural Networks to Characterize Microbial Interactions in an Ex Vivo Gastrointestinal Gut Simulator

The structure of mixed microbial cultures—such as the human gut microbiota—is influenced by a complex interplay of interactions among its community members. The objective of this study was to propose a strategy to characterize microbial interactions between particular members of the community occurring in a simulator of the human gastrointestinal tract used as the experimental system. Four runs were carried out separately in the simulator: two of them were fed with a normal diet (control system), and two more had the same diet supplemented with agave fructans (fructan-supplemented system). The growth kinetics of Lactobacillus spp., Bifidobacterium spp., Salmonella spp., and Clostridium spp. were assessed in the different colon sections of the simulator for a nine-day period. The time series of microbial concentrations were used to estimate specific growth rates and pair-wise interaction coefficients as considered by the generalized Lotka-Volterra (gLV) model. A differential neural network (DNN) composed of a time-adaptive set of differential equations was applied for the nonparametric identification of the mixed microbial culture, and an optimization technique was used to determine the interaction parameters, considering the DNN identification results and the structure of the gLV model. The assessment of the fructan-supplemented system showed that microbial interactions changed significantly after prebiotics administration, demonstrating their modulating effect on microbial interactions. The strategy proposed here was applied satisfactorily to gain quantitative and qualitative knowledge of a broad spectrum of microbial interactions in the gut community, as described by the gLV model. In the future, it may be utilized to study microbial interactions within mixed cultures using other experimental approaches and other mathematical models (e.g., metabolic models), which will yield crucial information for optimizing mixed microbial cultures to perform certain processes—such as environmental bioremediation or modulation of gut microbiota—and to predict their dynamics.

Nutraceuticals as modulators of gut microbiota: Role in therapy

As our knowledge of the various roles of the gut microbiota in the maintenance of homeostasis grows and as we learn how a disrupted microbiota may contribute to disease, therapeutic strategies that target our microbial fellow-travellers become ever more attractive. Most appealing are those interventions that seek to modify or supplement our diet through the addition of nutraceuticals. We now know that our diet, whether in the short or long term, is a major modifier of microbiota composition and function. Of the various nutraceuticals, two categories, prebiotics and probiotics, have received the greatest attention in basic research and product development. While our understanding of the impacts of prebiotics and probiotics on the indigenous microbiota and host biology have been described in great detail in vitro and in animal models, the clinical literature leaves much to be desired. While many claims have been made, few are supported by high quality clinical trials. LINKED ARTICLES: This article is part of a themed section on The Pharmacology of Nutraceuticals. To view the other articles in this section visit http://onlinelibrary.wiley.com/doi/10.1111/bph.v177.6/issuetoc.

Regulation of Gut Microbiota and Metabolic Endotoxemia with Dietary Factors

Metabolic endotoxemia is a condition in which blood lipopolysaccharide (LPS) levels are elevated, regardless of the presence of obvious infection. It has been suggested to lead to chronic inflammation-related diseases such as obesity, type 2 diabetes mellitus, non-alcoholic fatty liver disease (NAFLD), pancreatitis, amyotrophic lateral sclerosis, and Alzheimer’s disease. In addition, it has attracted attention as a target for the prevention and treatment of these chronic diseases. As metabolic endotoxemia was first reported in mice that were fed a high-fat diet, research regarding its relationship with diets has been actively conducted in humans and animals. In this review, we summarize the relationship between fat intake and induction of metabolic endotoxemia, focusing on gut dysbiosis and the influx, kinetics, and metabolism of LPS. We also summarize the recent findings about dietary factors that attenuate metabolic endotoxemia, focusing on the regulation of gut microbiota. We hope that in the future, control of metabolic endotoxemia using dietary factors will help maintain human health.

The effect of 2'-fucosyllactose on simulated infant gut microbiome and metabolites; a pilot study in comparison to GOS and lactose

Human milk oligosaccharides (HMOs) shape gut microbiota during infancy by acting as fermentable energy source. Using a semi-continuous colon simulator, effect of an HMO, 2'-fucosyllactose (2'-FL), on composition of the infant microbiota and microbial metabolites was evaluated in comparison to galacto-oligosaccharide (GOS) and lactose and control without additional carbon source. Data was analysed according to faecal sample donor feeding type: breast-fed (BF) or formula-fed (FF), and to rate of 2'-FL fermentation: fast or slow. Variation was found between the simulations in the ability to utilise 2'-FL. The predominant phyla regulated by 2'-FL, GOS and lactose were significant increase in Firmicutes, numerical in Actinobacteria, and numerical decrease in Proteobacteria compared to control. Verrucomicrobia increased in FF accounted for Akkermansia, whereas in fast-fermenting simulations Actinobacteria increased with trend for higher Bifidobacterium, and Proteobacteria decrease accounted for Enterobacteriaceae. Short-chain fatty acids and lactic acid with 2'-FL were produced in intermediate levels being between ones generated by the control and GOS or lactose. In 2'-FL fast-fermenting group, acetic acid specifically increased with 2'-FL, whereas lactose and GOS also increased lactic acid. The results highlight specificity of 2'-FL as energy source for only certain microbes over GOS and lactose in the simulated gut model.

The honey bee gut microbiota: strategies for study and characterization

Gut microbiota research is an emerging field that improves our understanding of the ecological and functional dynamics of gut environments. The honey bee gut microbiota is a highly rewarding community to study, as honey bees are critical pollinators of many crops for human consumption and produce valuable commodities such as honey and wax. Most significantly, unique characteristics of the Apis mellifera gut habitat make it a valuable model system. This review discusses methods and pipelines used in the study of the gut microbiota of Ap. mellifera and closely related species for four main purposes: identifying microbiota taxonomy, characterizing microbiota genomes (microbiome), characterizing microbiota-microbiota interactions and identifying functions of the microbial community in the gut. The purpose of this contribution is to increase understanding of honey bee gut microbiota, to facilitate bee microbiota and microbiome research in general and to aid design of future experiments in this growing field.

Immunomodulatory and Prebiotic Effects of 2'-Fucosyllactose in Suckling Rats

Human milk oligosaccharides are unconjugated complex glycans present in high concentration in human milk that serve as pre-biotics and immunomodulators. They are not primarily absorbed or metabolized by the infant and reach the lower part of the intestinal tract unaltered. One of the main oligosaccharides found in human milk is 2'-fucosyllactose (2'-FL). This study aimed to investigate the effects of daily oral administration of 2'-FL in healthy suckling rats. From days 2 to 16 of life, rats were daily given the oligosaccharide (2'-FL) or vehicle (REF), weighed and their stool characteristics were assessed. On days 8 and 16 of life the morphometry, intestinal architecture, and cytokine release, mesenteric lymph nodes cell composition, plasma immunoglobulin concentrations, fecal microbiota composition, cecal short-chain fatty acids content, and the urinary metabolic profile were assessed. Animals given 2'-FL showed higher plasma IgG and IgA and more T cell subsets in the mesenteric lymph nodes on day 16. Moreover, at intestinal level, villus heights, and areas were increased on day 8. Cecal samples displayed a higher Lactobacillus proportion and a different urinary metabolic profile was observed on day 8, and a higher proportion of butyrate on day 16. In conclusion, supplementation of 2'-FL in early life has a pre-biotic and intestinal trophic effect and promotes maturation of the immune system.

Species Deletions from Microbiome Consortia Reveal Key Metabolic Interactions between Gut Microbes

The gut microbiome is a complex microbial community that plays a key role in human health. Diet is an important factor dictating gut microbiome composition. This is mediated by multiple microbe-microbe interactions that result in the fermentation of nondigestible carbohydrates and the production of short-chain fatty acids. Certain species play key metabolic roles in the microbiome, and their disappearance could result in dysbiosis. In this work, a synthetic consortium of 14 gut microbes was studied during the utilization of prebiotic inulin in batch bioreactors. Fermentations were repeated leaving one species out every time, in order to evaluate the impact of their elimination on the system. Substrate consumption, microbial composition, and metabolite production were determined. Single deletions never resulted in a complete loss of bacterial growth or inulin consumption, suggesting functional redundancy. Deletions of Bacteroides dorei and Lachnoclostridium clostridioforme resulted in lower biomass and higher residual inulin. The absence of B. dorei impacted the abundance of the other 10 species negatively. Lachnoclostridium symbiosum, a butyrate producer, appeared to be the most sensitive species to deletions, being stimulated by the presence of Escherichia coli, Bifidobacterium adolescentis, B. dorei, and Lactobacillus plantarum Conversely, bioreactors without these species did not show butyrate production. L. clostridioforme was observed to be essential for propionate production, and B. dorei for lactate production. Our analysis identified specific members that were essential for the function of the consortium. In conclusion, species deletions from microbial consortia could be a useful approach to identify relevant interactions between microorganisms and defining metabolic roles in the gut microbiome.IMPORTANCE Gut microbes associate, compete for, and specialize in specific metabolic tasks. These interactions are dictated by the cross-feeding of degradation or fermentation products. However, the individual contribution of microbes to the function of the gut microbiome is difficult to evaluate. It is essential to understand the complexity of microbial interactions and how the presence or absence of specific microorganisms affects the stability and functioning of the gut microbiome. The experimental approach of this study could be used for identifying keystone species, in addition to redundant functions and conditions that contribute to community stability. Redundancy is an important feature of the microbiome, and its reduction could be useful for the design of microbial consortia with desired metabolic properties enhancing the tasks of the keystone species.

Longitudinal microbiome profiling reveals impermanence of probiotic bacteria in domestic pigeons

Probiotics are bacterial species or assemblages that are applied to animals and plants with the intention of altering the microbiome in a beneficial way. Probiotics have been linked to positive health effects such as faster disease recovery times in humans and increased weight gain in poultry. Pigeon fanciers often feed their show pigeons probiotics with the intention of increasing flight performance. The objective of our study was to determine the effect of two different probiotics, alone and in combination, on the fecal microbiome of Birmingham Roller pigeons. We sequenced fecal samples from 20 pigeons divided into three probiotic treatments, including prior to, during, and after treatment. Pre-treatment and control group samples were dominated by Actinobacteria, Firmicutes, Proteobacteria, and Cyanobacteria. Administration of a probiotic pellet containing Enterococcus faecium and Lactobacillus acidophilus resulted in increase in average relative abundance of Lactobacillus spp. from 4.7 ± 2.0% to 93.0 ± 5.3%. No significant effects of Enterococcus spp. were detected. Probiotic-induced shifts in the microbiome composition were temporary and disappeared within 2 days of probiotic cessation. Administration of a probiotic powder in drinking water that contained Enterococcus faecium and three Lactobacillus species had minimal effect on the microbiome. We conclude that supplementing Birmingham roller pigeons with the probiotic pellets, but not the probiotic powder, temporarily changed the microbiome composition. A next step is to experimentally test the effect of these changes in microbiome composition on host health and physical performance.

A quantitative model of Bacillus cereus ATCC 9634 growth inhibition by bifidobacteria for synbiotic effect evaluation

The present study is dedicated to the development of novel criteria for assessing the synbiotic effect of prebiotic and probiotic composition against a specific pathogen. These criteria were obtained from the quantitative model of Bifidobacterium adolescentis ATCC 15703 and Bacillus cereus ATCC 9634 (as a model food contaminant) competition in co-culture fermentation. The model is based on the hypothesis that probiotics can reduce the specific growth rate of non-probiotics by producing short-chain fatty acids. To define the relationship between the specific growth rate of non-probiotics and short-chain fatty acid yields, the inhibition constants were determined separately for each inhibitor produced by bifidobacteria (lactic, acetic and propionic acids) in a pure culture of bacilli. Two different equations based on the minimum inhibitor concentration (MIC) and inhibition constant (K_i) were used to connect the specific growth rate and concentrations of inhibitors. The yields of the inhibitors mentioned above were obtained from co-culture experiments. The experimental values and the values predicted by the model of Bacillus count did not differ significantly (R² not less than 0.83) in the competition experiments. Therefore, the general criterion of the synbiotic effect was derived from the model and presents the coefficient of non-probiotic specific growth rate reduction as a result of probiotic growth and inhibitor formation in the final co-culture fermentation. This criterion has been examined for different commercial prebiotics coupled with the Bifidobacterium adolescentis strain. The synergistic combination of inulin GR with bifidobacteria had the best effect against Bacillus cereus ATCC 9634.

Effects of prebiotics on sepsis, necrotizing enterocolitis, mortality, feeding intolerance, time to full enteral feeding, length of hospital stay, and stool frequency in preterm infants: a meta-analysis

BACKGROUND/OBJECTIVES

Prebiotics are increasingly recognized as an effective measure to promote health and prevent adverse health outcomes in preterm infants. We aimed to systematically review the randomized controlled trials (RCTs) in this area.

SUBJECTS/METHODS

Relevant studies from January 2000 to June 2018 were searched and selected from PubMed, Medline, Scopus, and the Cochrane Library. RCTs were included if they involved preterm infant participants, included a prebiotic intervention group, measured incidence of sepsis, feeding intolerance, mortality, time to full enteral feeding, necrotizing enterocolitis (NEC), length of hospital stay, and stool frequency as outcomes.

RESULTS

Eighteen RCTs (n = 1322) were included in the final meta-analysis. Participants who took prebiotics showed significant decreases in the incidence of sepsis (with a risk ratio (RR) of 0.64, 95% CI: 0.51, 0.78), mortality (RR = 0.58. 95% CI: 0.36, 0.94), length of hospital stay (mean difference (MD): -5.18, 95% CI: -8.94, -1.11), and time to full enteral feeding (MD: -0.99, 95% CI: -1.15, 0.83). The pooled effects showed no significant differences between intervention and control groups in relation to the morbidity rate of NEC (RR = 0.79, 95% CI: 0.44, 1.44) or feeding intolerance (RR = 0.87, 95% CI: 0.52, 1.45).

CONCLUSIONS

The results showed that the use of prebiotics with preterm infants is safe and can decrease the incidence of sepsis, mortality, length of hospital stay, and time to full enteral feeding but not NEC.

Development of the Gut Microbiome in Children, and Lifetime Implications for Obesity and Cardiometabolic Disease

Emerging evidence suggests that microbiome composition and function is associated with development of obesity and metabolic disease. Microbial colonization expands rapidly following birth, and microbiome composition is particularly variable during infancy. Factors that influence the formation of the gut microbiome during infancy and childhood may have a significant impact on development of obesity and metabolic dysfunction, with life-long consequences. In this review, we examine the determinants of gut microbiome composition during infancy and childhood, and evaluate the potential impact on obesity and cardiometabolic risk.

Human Milk: An Ideal Food for Nutrition of Preterm Newborn

Human milk is the best food for newborn nutrition. There is no ideal composition of human milk and also no easy way to control the complexity of its nutritional quality and the quantity received by breastfed infants. Pediatricians and nutritionists use charts of infant growth (weight, size, head circumference) and neurodevelopment criteria that reflect the food that these infants receive. These charts reflect first the infant physiology and likely reflect the composition of human milk when infants are breastfed. In a situation of preterm birth, mother physiology impacts partly breast milk composition and this explains how this is more difficult to correlate infant growth or neurodevelopment with milk composition. Some biomarkers (lipids, oligosaccharides) have been identified in breast milk but their function is not always yet known. A better knowledge on how human milk could act on infant development to the mid- and long-term participating thus to nutritional programming is a challenging question for a better management of infants' nutrition, especially for preterm infants who are most fragile.

Anti-inflammatory effect of microbial consortia during the utilization of dietary polysaccharides

The gut microbiome has a significant impact on host health, especially at the metabolic level. Dietary compounds arriving at the colon have a large influence on the composition of the gut microbiome. High fiber diets have been associated to health benefits that are mediated in great part by short chain fatty acids (SCFA). Gut microbial interactions are relevant for the utilization of complex carbohydrates in the gut microbiome. In this work we characterized the utilization of two dietary polysaccharides by combinations of representative adult gut microbes, and the impact of their activities on a cellular inflammation model. Paired combinations of Bifidobacterium adolescentis, Bacteroides dorei, Lactobacillus plantarum, Escherichia coli and Clostridium symbiosum were grown in inulin or xylan as carbon source. Their relative abundance, substrate consumption and major SCFAs produced were determined. Higher cell growth was observed during inulin consumption, and B. adolescentis and L. plantarum were dominant in co-cultures. The co-culture of B. dorei and C. symbiosum was dominant in xylan. In several cases the combined bacterial growth was lower in co-cultures than monocultures, with a few exceptions of synergistic growth between microorganisms. Inulin fermentation resulted in larger acetate and lactate concentrations, and several combinations grown in xylan containing C. symbiosum were characterized by high amounts of butyrate. These microbial consortia were scaled to batch bioreactor fermentations reaching high cell densities and similar profiles to co-culture experiments. Interestingly, a microbial combination producing high amounts of butyrate was able to reduce IL-8 expression in HT-29 cells co-incubated with TNFα. In summary, this work shows that microbial interactions during the utilization of dietary polysaccharides are complex and substrate dependent. Moreover, certain combinations deploy potent anti-inflammatory effects, which are independent of individual microbial growth, and could be mediated in part by higher butyrate production.

Modeling Metabolic Interactions in a Consortium of the Infant Gut Microbiome

The gut microbiome is a complex microbial community that has a significant influence on the host. Microbial interactions in the gut are mediated by dietary substrates, especially complex polysaccharides. In this environment, breakdown products from larger carbohydrates and short chain fatty acids are commonly shared among gut microbes. Understanding the forces that guide microbiome development and composition is important to determine its role in health and in the intervention of the gut microbiome as a therapeutic tool. Recently, modeling approaches such as genome-scale models and time-series analyses have been useful to predict microbial interactions. In this study, a bottom-up approach was followed to develop a mathematical model based on microbial growth equations that incorporate metabolic sharing and inhibition. The model was developed using experimental in vitro data from a system comprising four microorganisms of the infant gut microbiome (Bifidobacterium longum subsp. infantis, Lactobacillus acidophilus, Escherichia coli, and Bacteroides vulgatus), one substrate (fructooligosaccharides, FOS), and evaluating two metabolic products (acetate and lactate). After parameter optimization, the model accurately predicted bacterial abundance in co-cultures from mono-culture data. In addition, a good correlation was observed between the experimental data with predicted FOS consumption and acid production. B. infantis and L. acidophilus were dominant under these conditions. Further model validation included cultures with the four-species in a bioreactor using FOS. The model was able to predict the predominance of the two aforementioned species, as well as depletion of acetate and lactate. Finally, the model was tested for parameter identifiability and sensitivity. These results suggest that variations in microbial abundance and activities in the infant gut were mainly explained by metabolic interactions, and could be properly modeled using Monod kinetics with metabolic interactions. The model could be scaled to include data from larger consortia, or be applied to microbial communities where sharing metabolic resources is important in shaping bacterial abundance. Moreover, the model could be useful in designing microbial consortia with desired properties such as higher acid production.