Effects of Targeted Foods on the Microbiota in Gnotobiotic Animals and Undernourished Children | EXCLUSIVE OFFER !

Malnutrition and food relief

Malnutrition in children accompanies stunting and immaturity of the gut microbiota. Even after a therapeutic intervention with standard commercial complementary foods, children may not flourish. Gehrig et al. and Raman et al. monitoring of metabolic parameters in healthy Bangladeshi children and in those recovering from severe acute malnutrition. The authors investigated interactions between therapeutic diet, microbiota development, and growth recovery. The diets were then designed using pork and mouse models to induce the microbiota to reach a mature post-weaning state that could promote a child's growth. These were first tested in mice inoculated with a gut microbiota characteristic of age. Diets designed lead to the maturation of children's microbiota and put their metabolic and growth profiles on a healthier trajectory.

Science, this number p. eaau4732, p. eaau4735

Structured abstract


Postnatal human development involves a dimension that involves the assembly of microbial communities in different body habitats, including the intestine. Children with acute malnutrition have hindered the development of their intestinal microbiota, leaving them in communities that appear younger (more immature) than those of healthy individuals, matched chronologically. Current therapeutic foods administered to children with acute malnutrition have not been formulated on the basis of knowledge of their effects on the developmental biology of the gut microbiota. In addition, they are largely ineffective in alleviating the long-term sequelae of malnutrition, including persistent growth retardation, neurodevelopmental abnormalities, and immune dysfunction.


To repair the immaturity of the microbiota and determine the extent to which this repair restores healthy growth, it is necessary to identify microbial targets that are not only biomarkers of community assembly, but also mediators of various aspects of microbiota. the growth. Identifying the ingredients in complementary foods consumed during the transition from an exclusive milk diet to a fully weaned state increasing the representation and expressing the beneficial functions of bacterial taxa promoting growth in the developing microbiota could provide an effective way, affordable, culturally acceptable and sustainable approach to treatment.


Metabolomic and proteomic analyzes of serum plasma samples were combined with metagenomic analyzes of serial faecal specimens of Bangladeshi children with severe acute malnutrition (SAM) treated with standard therapy. The results provided a reading of their biological characteristics during their transition from SAM to persistent moderate acute malnutrition (MAM), accompanied by persistent immaturity of the microbiota. Significant correlations were identified between plasma protein levels, anthropometry, plasma metabolites and the representation of bacteria in their microbiota. The gnotobiotic mice were then colonized with a defined consortium of bacterial strains representing different phases of microbiota development in healthy Bangladeshi children. The administration of different combinations of complementary food ingredients from Bangladesh to colonized mice and to controls without germs revealed an increase in diet-related abundance and changes in the metabolic activities of targeted strains in humans. weaning phase, as well as an increase in regime-dependent growth and colonization. promote the signaling pathways of the host. The host and microbial effects of microbiota-mediated complementary food prototypes were then examined in gnotobiotic mice colonized with an immature microbiota of children with post-SAM MAM and colonized gnotobiotic piglets with a defined consortium of taxa targeting a microbiota. discrimination based on age and growth. A randomized, double-blind study of standard therapy versus various MDCF prototypes from these preclinical models in Bangladeshi children with MAM identified a primary MDCF increasing levels of biomarkers and mediators of growth, bone formation, neurodevelopment, and immune function. a state resembling healthy children. Using an approach inspired by the statistical methods applied to the financial markets, we show in the accompanying document of Raman et al. that this main MDCF was the most effective at repairing the microbiota.


These results demonstrate the translatability of the results obtained in humans in preclinical gnotobiotic animal models, directly corroborate the hypothesis that the development of a healthy microbiota is related to healthy growth, illustrate an approach allowing to treat infant undernutrition and suggest deliberately reconfiguring an immature microbiota. a way to decipher how elements of the intestinal microbial community act to regulate various host systems involved in healthy growth.

Overview of the discovery and testing of therapeutic foods.

The approach used to integrate preclinical gnotobiotic animal models with human studies to understand the contributions of disturbed gut microbiota development to malnutrition in children and to identify MDCFs.


To examine the contributions of impaired intestinal microbial community development to undernutrition in children, we combined metabolomic and proteomic analyzes of plasma samples with metagenomic analyzes of fecal samples to to characterize the biological status of Bangladeshi children suffering from severe acute malnutrition during their transition, after normalization. treatment for moderate acute malnutrition with persistent immaturity of the microbiota. The host and microbial effects of microbiota-directed complementary food (MDCF) prototypes targeting under-represented weaning bacterial taxons in SAM and MAM microbiota were characterized in gnotobiotic mice and gnotobiotic piglets colonized with discriminant bacteria for age and growth. A randomized, double-blind, controlled feeding study identified a major MDCF that alters the abundance of targeted bacteria and increases plasma biomarkers and mediators of growth, bone formation, neurodevelopment, and growth. immune function in children with MAM.

Evidence accumulates that disrupting the "normal" development of an intestinal community (microbiota) can contribute to the pathogenesis of undernutrition. With the help of independent surveys of culture, bacteriality was defined in faecal samples collected each month during the first two postnatal years in healthy members of a cohort of birth in an urban slum (Mirpur) in Dhaka, Bangladesh (1, 2). Applying Automatic Learning (Random Forest (RF)) to the Resultant 16S Ribosomal DNA data (rDNA) yielded a "sparse" model composed of the most discriminating bacterial strains for age; changes in the relative abundances of these organisms described a program of normal microbiota development (2). This radiofrequency-derived model was then used to characterize stool samples taken from Bangladeshi children with severe acute malnutrition (SAM), defined as a weight-to-height ratio. z-score (WHZ)> 3 standard deviations below the median for a healthy growth reference cohort of the World Health Organization (WHO) (3)). The results revealed intestinal communities that resembled those of chronologically younger healthy children. This "immaturity" of the microbiota was more pronounced in children with SAM compared to moderate acute malnutrition (MAM, WHZ score between -2 and -3) and was not repaired during the course of the study. a clinical study that tested the effects of two therapeutic foods (2).

Impaired microbiota development has also been documented in malnourished Malawian children (4). To examine the functional significance of this deficiency, microbial communities of malawian children aged 6 and 18 months in good health, with growth failure or underweight, were transplanted into groups of mice free of newly weaned germs. and fed with a diet representing that consumed by the human population. . The results revealed that, compared to mice colonized with the microbiota of normal healthy and healthy donors, immature microbiota carriers showed reduced rates of lean body mass gain, alterations in bone growth, and metabolic abnormalities (4). These studies provided preclinical evidence of a causal link between the immaturity of the microbiota and undernutrition; they also revealed that a subset of discriminant strains based on age is discriminatory for growth. In addition, a consortium of cultures of these taxons discriminating age and growth improved the phenotype of altered growth transmitted to the recipient gnotobiotic mice by an immature microbiota (4).

One question that arises from these observations is: how to design optimal foods that direct a microbiota into a healthy and age-appropriate state? Breastfeeding plays a major role in reducing malnutrition in children. As such, WHO and the United Nations Children's Fund (UNICEF) recommend exclusive breastfeeding for the first six months of postnatal life and continued breastfeeding after food introduction. up to 24 months (5). Suboptimal complementary feeding practices are important factors of malnutrition in children under 2 years of age (6). However, current recommendations for complementary feeding are not based on knowledge of how foods affect the developmental biology of the gut microbiota during the weaning process. Together, these observations raise the question: do certain complementary food ingredients or combinations have the ability to selectively increase the representation and beneficial functions expressed of discriminant strains due to age and growth, which are deficient? in microbiota associated with SAM or MAM? If the answer is yes, then a prescribed diet of these ingredients could help "repair" or prevent the development of immature microbiota in children, with potentially long-term adverse health effects.

Here we describe a process of identification of microbiota-directed complementary foods for the treatment of children with acute malnutrition. We first characterized the responses of the intestinal microbial community and the host over a 12-month period in Bangladeshi children treated for MAS with one of three conventional therapeutic foods. Measurement of the levels of 1305 human plasma proteins – including regulators and effectors of physiological, metabolic and immune functions – combined with mass spectrometric profiling of plasma metabolites and independent analyzes of the culture of fecal samples taken from series allowed to "read" the biological characteristics passage of SAM to an incomplete recovery state (post-SAM MAM) with persistent immaturity of the microbiota. This reading included correlations between plasma proteins, anthropometry, plasma metabolites and the representation of their members of their microbiota discriminating according to age. We then examined complementary foods in colonized gnotobiotic mice with a consortium of bacterial strains cultured in children living in Mirpur to identify ingredients that promote the representation of age-defining discriminant strains that are under- represented in the context of acute malnutrition. Subsequently, a representative microbiota of a child with post-SAM MAM was transplanted into gnotobiotic mice. The recipient animals received a diet similar to that of the Mirpur children, but supplemented with the ingredients identified in the screening, to determine if one or more of these MDCF formulations could repair the microbiota of a subject who had already received a microbiota. conventional treatment. The lead formulations were then tested on colonized gnotobiotic piglets with a defined consortium of age and growth discriminating strains to test their biological effects on a host species physiologically and metabolically more similar to humans than the mouse. . Finally, three prototypes of MDCF were administered to children with MAM and their effects on the microbiota and the biological status of the host were determined.

Effects of conventional therapeutic foods on the biological status of children with SAM

A total of 343 Bangladeshi children aged 6 to 36 months with SAM were enrolled in a double-blind, randomized, multi-center, non-inferiority study comparing two locally produced therapeutic foods (supplemental materials, materials and methods) with a single product. ready to use commercially available. Therapeutic use (RUTF) (7) (the scheme of the study is shown in Fig. 1A and the compositions of these therapeutic foods in Table S1A). Children received standard care for SAM during the acute stabilization phase of treatment at the hospital, including short-term antibiotic treatment. Eligible children were then randomized into one of three therapeutic food groups (~ 200 kcal / kg / day, mean duration 16.1 ± 10.3 days) (Table S1B). The children were released after meeting the criteria described in the supplementary documents, materials and methods. In a subset of 54 children, stool samples were collected at the time of enrollment (15.2 ± 5.1 months (mean ± standard deviation)) prior to randomization, twice during treatment with a therapeutic food and at regular intervals up to 12 months after discharge (Fig. 1A). clinical metadata are available in Table S1B). Blood samples (plasma) were also obtained at the time of recruitment, at discharge and six months after discharge for metabolic profiling based on mass spectrometry (MS); a sufficient amount of blood was obtained from eight children at three time points for aptamer-based proteomic analysis (8ten). Of these children, 44% had MAM at 12 months of follow-up. None of the therapeutic foods had a significant effect on their severe growth retardation (height for age z-score (HAZ)) (Fig. 1B and Table S1B).

Fig. 1 Longitudinal study of Bangladeshi children with SAM treated with therapeutic foods.

(A) Study the design. (B) Anthropometry and MAZ scores. The gray bars represent the three moments at which the blood samples were taken. (C) Summary of MAZ scores in children with SAM (WHZ <-3; not = 96 faecal samples) and then (after SAM) MAM (WHZ> -3 and <-2; not = 151 stool samples), plus healthy children aged 6 to 24 months living in the same area as the SAM study (not = 450 faecal samples). The average values ​​for WHZ, WAZ, HAZ and MAZ ± SEM are plotted on the X axes of (B) and (C). ****P <0.0001 (unidirectional ANOVA followed by Tukey multiple comparison test).

Metabolic phenotypes

The MS-targeted plasma samples obtained at registration revealed elevated levels of ketones, non-esterified fatty acids (NEFAs) and medium and long chain acylcarnitines (Fig 2, A and B, and Table S2), which is consistent with known acute toxicity. Malnutrition-induced lipolytic response that raises circulating fatty acids and activates oxidation of fatty acids (11). In discharge, this metabolic characteristic was normalized, while the levels of several amino acids had increased significantly, including the gluconeogenic amino acid, alanine; branched chain amino acids, leucine, isoleucine and valine; plus branched-chain amino acid metabolism products (C3 (propionyl) carnitine and their ketoacids) (Fig. 2, A-C). These results suggest that the increase in protein provided by therapeutic foods has prompted switching from fatty acid oxidation to amino acid oxidation, resulting in repletion of fatty deposits, a increased plasma leptin (Fig 2A) and weight gain (Table S1B). However, six months after treatment, multiple plasma amino acids and their metabolites had decreased to levels comparable to those observed at intake, while fatty acids and metabolites derived from fatty acids remained at concentrations similar to those observed at the outlet (Fig. 2, A to C). ). The insulin-like growth factor 1 (IGF-1) levels did not change significantly during this period (Fig. 2A), which could explain the lack of signature of pronounced lipolysis observed at inclusion. Although the suppression of lipolysis six months after discharge from the hospital suggests a prolonged effect of nutritional resuscitation, the decline in essential amino acids and the decrease in IGF-1 levels compared to those observed in healthy children of the same age belonging to the same community (44.5 vs 69.4 ng). / ml; P = 0.02, t test) can contribute to the inability to achieve catch-up growth.

Fig. 2 Metabolic characteristics of children with SAM before and after treatment.

(A at CLevels of (A) standard clinical metabolites and selected hormones, (B) acylcarnitines and (C) amino acids and ketoacids in plasma collected from children at enrollment (Fig. 1A, B1) blood test), exit (Fig. 1A, B2 sample) and 6 months after discharge (Fig. 1A, sample B3). Abbreviations for (C) branched chain ketoacids are KIC, α-ketoisocaproate; KIV, α-ketoisovalerate; and KMV, α-keto-β-methylvalerate. Mean values ​​± SEM are plotted. *P <0.05; **P <0.01; ***P <0.001; ****P <0.0001 (paired t test followed by an FDR correction).

The plasma proteome

Significant correlations between plasma protein levels, anthropometric indices, plasma metabolites, and host signaling pathways regulating the major facets of growth are described in the accompanying text, Results (Tables S3, A, and B). for example, the components of growth hormone (GH). The IGF axis, including the soluble growth hormone receptor (also known as growth hormone binding protein), multiple IGF binding proteins (IGFBPs), and IGFBP (pappalysin-1 metalloprotease and its inhibitor, stanniocalcin-1).

The intestinal microbiome

A model of development of the normal intestinal microbiota derived from RF, comprising 30 bacterial taxa (operational taxonomic units) and obtained from 25 healthy members of a birth cohort living in Mirpur (Tables S4, A to C) was applied to V4- 16 bacteriaS The rDNA databases generated from faecal specimens collected serially from children in the SAM study (not = 539 samples). This model allowed us to define the microbiota for the age zscores (MAZ) by treatment group and time (9.3 ± 3.7 samples / child (mean ± standard deviation)). The MAZ score measures the development gap of a child's microbiota relative to that of chronologically matched healthy reference children based on the representation of all age-discriminant strains in the child's microbiota. the derived model of RF (2). Significant microbiota immaturity was apparent in SAM and MAM post-SAM groups (Fig 1C and Table S5A). In addition, MAZ scores in this SAM cohort were significantly correlated with WHZ, HAZ, and WAZ (Pearson correlationr) = 0.16, P = 0.0004; r = 0.13, P = 0.003; and r = 0.10, P = 0.02, respectively). The MAZ score was no different at the exit but improved 1 month later (P = 0.0051 versus admission, Mann-Whitney test). This improvement could reflect increased dietary diversity, a reduction in the use of antibiotics (Table S1B) and / or other factors associated with returning home. MAZ scores did not change significantly thereafter (Fig 1B).

A number of age-discriminating strains were significantly correlated with anthropometric indices as well as plasma proteins involved in the biological processes leading to growth. We also identified significant negative correlations between these taxa and mediators of systemic inflammation and anorexia / cachexia. Bifidobacterium longum (OTU 559527) had the highest number of significant correlations (114) (Table S3C, additional information is available in the supplementary text, results).

The effects of therapeutic food interventions on the representation of metabolic pathways in the gut microbiome were defined by sputum-sequencing of 331 faecal DNA samples obtained from 30 members of the Mirpur birth cohort with an always healthy anthropometry and 15 of the 54 children included in the SAM. study (Table S5B); these 15 children were selected based on their age (12 to 18 months) and the fact that we had the corresponding metabolomic and plasma proteomic databases for at least two of the three sampled time points. The abundance of microbial genes mapped in the SEED database pathways (mcSEED) of microbial communities (12) – linked to the metabolism of amino acids, carbohydrates, fermentation products, group B vitamins and associated cofactors – were first defined for healthy children sampled every month from birth to 2 years . A set of age-discriminating metabolic pathways (mcSEED subsystems or pathway modules) has been identified. The resulting derivative-derived model of RF (Figs S1, A and B, and materials and methods) allowed us to assign a stage of development (functional age or "maturity") to the fecal microbiomes of the 15 children treated for MAS. Relative functional maturity was significantly correlated with MAZ, WHZ and WAZ scores during the trial (Pearson r and P the values ​​are MAZ, r = 0.55, P <0.0001; WHZ, r = 0.30, P = 0.0011; WAZ r = 0.23, P = 0.013). At the time of registration and just prior to the administration of therapeutic foods, children with SAM had a more immature microbiome (one-way analysis of variance (ANOVA) P = 0.0002; Dunnett's multiple comparison test for health versus adjusted SAM P values ​​at two instants, 0.027 and 0.0001, respectively). A statistically significant improvement in functional maturity was observed from initiation of therapy at the time of discharge, to 1 and 6 months after discharge (Tukey multiple comparison test; P values ​​= 0.039, 0.0028 and 0.025, respectively). However, this improvement was not maintained later (Figure S1D). Comparing the relative abundances of the six most discriminating age-specific pathways at six moments revealed that the MAS microbiome had a significantly reduced representation of metabolic (i) pathways, including those implicated in the biosynthesis of HIV. Isoleucine, leucine, valine and absorption; (ii) several ways of using carbohydrates (arabinose and arabinosides, rhamnose and rhamnogalacturonan and sialic acid); and (iii) multiple pathways involved in vitamin B metabolism, including "niacin / NADP (nicotinamide adenine dinucleotide phosphate) biosynthesis" (Fig S1E and Table S5C). The observed underrepresentation of OTUs and age-discriminating metabolic pathways in intestinal communities of children with post-SAM MAM provided the rationale for the development of a pipeline to test complementary food ingredients for their ability to repair this immaturity.

Screening of complementary food ingredients

Nine age-discriminating bacterial strains were cultured from the fecal microbiota of three healthy children aged 6 to 23 months and resident in Mirpur, and the genomes of these isolates were sequenced (Tables S6, A and C). Seven of the nine isolates had V4-16S The rDNA sequences that corresponded to age-discriminant UTOs whose representation is associated with the consumption period of complementary foods (weaning UTO) (Figure S2A), while two, Bifidobacterium longum subsp. infantis and Bifidobacterium breve, are most important during the exclusive predominant milk-feeding period (Figure S2A) (13). UTOs representing seven of the nine strains cultured were significantly depleted in the fecal microbiota of Bangladeshi children with SAM prior to treatment (Table S7 and Fig. S3). Seven other age-discriminant strains were cultured from the immature fecal microbiota of a 24-month-old child with SAM enrolled in the same study as the subcohort shown in Figure 1 (Tables 1 and 2). S6, A and C). Together, the 16-strain consortium represented OTUs directly corresponding to 65.6 ± 22.8% (mean ± standard deviation) of V4-16.S RDNA sequencing readings generated from 1039 faecal samples taken from 53 healthy members of the Mirpur birth cohort during their first 2 postnatal years, and 74.2 ± 25.2% of readings produced from fecal samples from 38 children with SAM (Table S7).

To identify complementary foods selectively increasing the representation of discriminating strains in the weaning phase and devoid of immature microbiota associated with SAM, we colonized 5-week old C57Bl / 6J mice with the consortium of cultured and sequenced bacterial strains. After colonization, an "alternation" of 8 weeks diet was initiated (Fig S2B). We have incorporated 12 complementary food ingredients commonly consumed in Mirpur (6) in 14 different regimes using a random sampling strategy (Table S8, A to E, and materials and methods). The composition of these complementary food combinations (CFCs) and their order of administration to the mice were based on the considerations described in the legend of FIG. S2, B and C.

Spearman rank correlation coefficients were calculated between the relative abundance of the 14 bacterial strains colonizing mice and the levels of complementary food ingredients in the 14 CFCs tested (Figure S2D and Table S9A). Chickpea and banana had strong positive correlations with the largest number of strains representing discriminating UTOs in the weaning phase. Tilapia had a narrower range of significant positive effects (Figure S2D). Chickpeas, bananas and tilapia also had significant negative correlations with pre-weaning levels, adapted to milk B. longum subsp. infantis isolate. Une observation préoccupante a été faite: un certain nombre d&#39;ingrédients alimentaires complémentaires généralement représentés dans les régimes alimentaires des enfants de 18 mois vivant à Mirpur présentaient des corrélations négatives significatives avec six souches discriminantes en phase de sevrage, notamment le riz, le lait en poudre, la pomme de terre, épinards et citrouille sucrée (fig. S2D). Le gruau de riz au lait est le premier aliment complémentaire le plus souvent donné aux enfants bangladais (14). De plus, les œufs, inclus dans un certain nombre de schémas thérapeutiques destinés à la réhabilitation nutritionnelle des enfants atteints de malnutrition aiguë (15), avait une corrélation négative avec l’abondance de deux souches en phase de sevrage, Dorea formicigenerans and Blautia luti.

Test d&#39;un prototype initial de MDCF

Khichuri-halwa (KH) est un aliment thérapeutique couramment administré avec du lait-suji (MS) aux enfants de Mirpur atteints de MAS. Une étude antérieure a montré l’incapacité de cette intervention à réparer l’immaturité du microbiote intestinal (2). Nous avons préparé un régime imitant MS et KH (MS / KH) (tableaux S8, D et E); 7 de ses 16 ingrédients sont des aliments complémentaires couramment consommés qui ont peu ou pas d&#39;effet sur la représentation des souches discriminantes en fonction de l&#39;âge en phase de sevrage (riz, lentilles rouges, pommes de terre, potiron, épinards, farine de blé entier et lait en poudre) (fig. S2D). Les effets de MS / KH sur les membres du consortium de 14 membres et l&#39;hôte ont été comparés à ceux produits par un prototype initial de MDCF contenant pois chiches, banane et tilapia (tableau S9B). Des souris C57Bl / 6J exemptes de germes âgées de cinq semaines colonisées avec le consortium ont été nourries de façon monotone par l&#39;un ou l&#39;autre des deux régimes diététiques ad libitum pendant 25 jours.

Réponses de la communauté microbienne

Le profilage de la communauté au moyen du séquençage à la lecture de séquences courtes (COPRO-seq) de l&#39;ADN cecal a révélé que, comparée à la MS / KH, la consommation du prototype de MDCF entraînait une abondance relative beaucoup plus élevée d&#39;un certain nombre de taxons discriminatoires en fonction de l&#39;âge, notamment: Faecalibacterium prausnitzii, Dorea Longicatena, and B. luti (P <0,01; Test de Mann-Whitney) (Fig. 3A et tableau S9B). Ce prototype n’a pas favorisé la bonne condition des souches dérivées du donneur SAM, à l’exception de Escherichia fergusonii.

Fig. 3 Comparaison des effets sur la communauté microbienne et sur l&#39;hôte d&#39;un prototype initial de MDCF par rapport à MS / KH.

Des groupes séparés de souris ou d&#39;animaux exempts de germes colonisés avec le consortium défini de 14 souches bactériennes ont été nourris de façon monotone aux deux régimes pendant 25 jours, après quoi ils ont été euthanasiés et leur contenu caecal a été analysé. (A) L’abondance relative des souches dans le microbiote cæcal de souris colonisées. Valeurs moyennes ± SD affichées. (B and C) Effets sur la concentration (B) cécale d’acides gras à chaîne courte et d’acides aminés essentiels (C), liés au régime alimentaire et à la colonisation, plus le métabolite du tryptophane, l’acide indole 3-lactique. Chaque point représente un échantillon d&#39;une souris du groupe de traitement indiqué. Les valeurs moyennes ± SD sont affichées. ***P <0,001; ****P <0,0001 (ANOVA à 2 voies suivie du test de comparaisons multiples de Tukey pour (A) à (C)). (re) Effets dépendant de la diète et de la colonisation sur les taux sériques d’IGF-1. (E) Effets de l’alimentation sur les taux de protéines hépatiques impliqués dans la signalisation et la production d’IGF-1. Les niveaux de protéines phosphorylées ont été normalisés à la quantité totale de la protéine non phosphorylée correspondante ou à la glycéraldéhyde-3-phosphate déshydrogénase (GAPDH). (F) Effet de l’alimentation et de l’état de la colonisation sur l’épaisseur corticale de l’os fémoral. (g) Effets du régime alimentaire chez les souris gnotobiotiques colonisées sur les acides aminés à chaîne ramifiée présents dans le sérum et les acylcarnitines des muscles et du foie. (C5-OH / C3 sont des isobares qui ne sont pas résolus par injection en flux MS / MS. C5-OH est un mélange de 3-hydroxy-2-méthylbutyryl carnitine (dérivé de l’intermédiaire classique 3-hydroxy-2-méthylbutyryl-co-acide isoleucine) ) et la 3-hydroxyisovaléryl carnitine (un métabolite de la leucine non canonique)). Pour (D) à (G), les valeurs moyennes ± SD sont indiquées. ns, non significatif. *P <0,05; **P <0,01; ****P <0,0001 pour (D) à (G) (test de Mann-Whitney).

Nous avons utilisé la SEP ciblée pour quantifier les niveaux cecaux de glucides, d&#39;acides gras à chaîne courte, ainsi que d&#39;acides aminés et de leurs catabolites (tableaux S10, A à D). Les animaux sans germes ont servi de témoins de référence pour définir les niveaux de nutriments cæcaux qui, par déduction, seraient disponibles pour une utilisation bactérienne dans différents contextes de régime. Plusieurs résultats remarquables ont été constatés: (i) Les niveaux de butyrate et de succinate étaient significativement plus élevés chez les animaux colonisés consommant du MDCF par rapport à MS / KH (Fig. 3B et tableau S10B). (ii) Il n&#39;y avait pas de différences statistiquement significatives associées au régime alimentaire dans les niveaux des acides aminés mesurés chez les animaux sans germe, mais par rapport à leurs homologues colonisés nourris avec MS / KH, les animaux colonisés consommateurs de MDCF avaient des niveaux de cécal significativement élevés de six acides aminés classés comme essentiels chez l’homme (les trois acides aminés à chaîne ramifiée leucine, isoleucine et valine plus phénylalanine et tryptophane) (figure 3C et tableau S10C). Et (iii) deux métabolites microbiens dérivés du tryptophane qui jouent un rôle important dans la suppression de l&#39;inflammation et sont l&#39;acide 3-hydroxyanthranillique neuroprotecteur (3-HAA) et l&#39;acide indole-3-lactique (1621), étaient significativement élevés chez les animaux colonisés nourris de MDCF par rapport à leurs homologues traités par MS / KH (tableau S10D).

Résultats de l&#39;analyse par séquençage de l&#39;ARN (ARN-seq) des réponses transcriptionnelles des membres de la communauté aux deux régimes à l&#39;aide des annotations KEGG (Encyclopédie des gènes et génomes de Kyoto) et des dérivés de mcSEED des 40 735 gènes codant les protéines prédites présents dans le consortium les membres sont décrits dans les tableaux S9C et S11, de A à C, et un texte supplémentaire, les résultats et les prédictions in silico de leur capacité à produire, utiliser et / ou partager des éléments nutritifs sont présentés dans les tableaux S6, D et E. L’analyse de niveau a révélé que des membres spécifiques manifestaient des augmentations de l’expression de gènes impliqués dans la biosynthèse des acides aminés essentiels, y compris les acides aminés à chaîne ramifiée, associées au MDCF (Ruminococcus obeum and Couples de ruminocoques) et la production de métabolites d’acides aminés aromatiques (R. obeum, R. Torques, and F. prausnitzii) (tableau S11C, ii).

Effets d&#39;accueil

Serum levels of IGF-1 were significantly higher in colonized mice that consumed the initial MDCF prototype compared with those that consumed MS/KH. This effect was diet- and colonization-dependent, with germ-free animals exhibiting significantly lower levels of IGF-1 in both diet contexts (Fig. 3D). Serum insulin levels were also higher in colonized animals that consumed MDCF compared with MS/KH (800.7 ± 302.9 ng/mL (mean ± SD) versus 518.7 ± 135.1 ng/mL, respectively; P = 0.06; non jumelé t test).

IGF-1 binding to its receptor tyrosine kinase, IGF-1R, affects a variety of signal transduction pathways, including one involving the serine/threonine kinase Akt/PKB, phosphatidylinositol-3 kinase (PI3K), and the mammalian target of rapamycin (mTOR). Absorption of several amino acids from the gut—notably, branched-chain amino acids and tryptophan—leads to activation of mTOR (22). Colonized animals fed MDCF had significantly higher levels of hepatic phosphoSer473-Akt, which is consistent with activation of Akt by IGF-1 signaling through the PI-3K pathway (Fig. 3E). Levels of phospho–AMPK (5′ adenosine monophosphate-activated protein kinase) were not significantly affected by diet (Fig. 3E), suggesting that Akt phosphorylation is not caused indirectly by altered hepatic energy status. Phosphorylation of hepatic Jak 2 (Tyr1007/1008) and mTOR (Ser2448), which are involved in IGF-1 production, was significantly increased in colonized mice consuming MDCF (Fig. 3E), whereas phosphorylation of STAT5, also implicated in IGF-1 production, was not significantly altered.

Previous studies of adult germ-free mice reported increases in serum IGF-1 after their colonization with gut microbiota from conventionally raised mice; increased IGF-1 levels were also associated with increased bone formation (23, 24). Micro-computed tomography (μCT) of mouse femurs revealed a significant increase in femoral cortical bone area in MDCF-fed animals; the effect was both diet- and microbiota-dependent (Fig. 3F).

We used targeted MS to quantify levels of amino acids, acyl–coenzyme As (acylCoAs), acylcarnitines, and organic acids in serum, liver, and gastrocnemius muscle (table S12). Products of nonoxidative metabolism of glucose and pyruvate (lactate from glycolysis and alanine from transamination of pyruvate, respectively) were significantly lower in mice fed MDCF compared with mice fed MS/KH; this was true for alanine in serum, skeletal muscle, and liver and for lactate in liver (table S12, A to C and H). Oxidative metabolism of glucose is associated with nutritionally replete, anabolic conditions. These findings are consistent with the observed elevations of the anabolic hormone IGF-1 in MDCF-fed compared with MS/KH–fed mice. MDCF-fed mice had significantly higher circulating levels of branched-chain amino acids than those of their MS/KH–fed counterparts (Fig. 3G and table S12, A to C). Skeletal muscle C5 carnitine and the closely related metabolite C5-OH/C3 carnitine were significantly higher in animals consuming MDCF (Fig. 3G and table S12F). In liver, C3 and C5 acylcarnitines were significantly lower in MDCF-treated mice (Fig. 3G and table S12E), suggesting that the more nutritionally replete state associated with MDCF may act to limit branched-chain amino acid oxidation in this tissue.

Testing additional MDCF prototypes in gnotobiotic mice

Incorporating tilapia into MDCF prototypes poses several problems: Its organoleptic properties are not desirable, and its cost is higher than commonly consumed plant-based sources of protein. To identify alternatives to tilapia, we selected an additional 16 plant-derived complementary food ingredients with varied levels and quality of protein (25) that are culturally acceptable, affordable, and readily available in Bangladesh (fig. S4A and table S13, A and B). Their effects were tested in gnotobiotic mice colonized with a defined, expanded consortium of 18 age- and growth-discriminatory bacterial strains (table S6A). We generated 48 mouse diets by supplementing a prototypic base diet representative of that consumed by 18-month-old children living in Mirpur (Mirpur-18), with each of the individual ingredients incorporated at three different concentrations (fig. S4A and table S13A). The results revealed that in this defined community context, peanut flour had the greatest effect on the largest number of targeted weaning-phase age-discriminatory taxa, followed by chickpea flour (fig. S4B and table S13C). Soy flour, which promoted the representation of two of these taxa, had the second-highest percentage protein after peanut flour (fig. S4A), and its protein quality was among the highest of the ingredients tested (table S13B). On the basis of these observations, we chose soy and peanut flours as replacements for tilapia in subsequent MDCF formulations.

We reasoned that by transplanting a representative immature intact microbiota into young, germ-free mice, we could investigate whether gut health (defined by relative abundances of community members, expression of microbial genes in mcSEED metabolic pathways, and biomarkers and mediators of gut barrier function) was improved by supplementing the Mirpur-18 diet with one or more complementary food ingredients that target weaning-phase age-discriminatory taxa. Fifteen fecal samples from 12 different children, obtained during or after treatment for SAM, were screened in gnotobiotic mice to identify samples containing the greatest number of transmissible weaning-phase age-discriminatory taxa and to assess their response to supplementation of Mirpur-18 (table S14A). We selected a sample obtained from a donor (PS.064) who had post-SAM MAM; in addition to the successful transmission of targeted taxa, 88.7 ± 1.3% (mean ± SD) of the recipient animals’ gut communities consisted of OTUs that were detected at >0.1% relative abundance in the donor sample (table S14B). Three groups of mice were colonized with this microbiota and monotonously fed one of three diets: unsupplemented Mirpur-18, Mirpur-18 supplemented with peanut flour (Mirpur(P)), or Mirpur-18 supplemented with four of the lead ingredients (Mirpur(PCSB), with peanut flour, chickpea flour, soy flour, and banana) (Fig. 4A and table S15A). Three control groups were maintained as germ-free; each group was fed one of the three diets.

Fig. 4 Effects of Mirpur-18 diet supplementation on a post-SAM MAM donor microbiota transplanted into gnotobiotic mice.

(A) Experimental design. dpg, days post gavage of the donor microbiota; Mirpur(P), Mirpur-18 supplemented with peanut flour; Mirpur(PCSB), Mirpur-18 supplemented with peanut flour, chickpea flour, soy flour, and banana. (B) Expression of microbial mcSEED metabolic pathway/modules in the ceca of gnotobiotic mouse recipients of the post-SAM MAM donor gut community as a function of diet treatment. *P < 0.05; **P < 0.001; ***P < 0.0001 (statistical comparisons indicate results of gene set enrichment analysis expression on a per-gene basis across the indicated mcSEED subsystem/pathway module; all P values are FDR-adjusted). (C) Effects of supplementing Mirpur-18 with one or all four complementary food ingredients on the relative abundances of a weaning-phase– and a milk-phase–associated taxon in feces obtained at dpg 21 (one-way ANOVA followed by Tukey’s multiple comparisons test). (re) Relative abundances of the two taxa in mucosa harvested by means of LCM from the proximal, middle, and distal thirds of the small intestine. (Right) Schematic of locations in the small intestine where LCM was performed. The same color code for diets is used in (A) to (D). *P < 0.05; **P < 0.01; ****P < 0.0001 (Mann-Whitney test).

We characterized the effects of diet supplementation on cecal and serum levels of metabolites as well as on expression of genes in various microbial metabolic pathways (tables S15, B, D, and E, and S16 and supplementary text, results). Eighteen mcSEED pathway modules involved in amino acid metabolism were significantly up-regulated in the cecal microbiomes of mice consuming Mirpur(PCSB) or Mirpur(P) compared with those consuming Mirpur-18, with the most up-regulated being “isoleucine, leucine, valine biosynthesis” (other age-discriminatory mcSEED pathway modules that showed significantly lower abundances in the fecal microbiomes of Bangladeshi children with SAM and whose expression was increased by Mirpur(PCSB) or Mirpur(P) in gnotobiotic mice are provided in Fig. 4B and fig. S1E). Serum levels of a product of branched-chain amino acid metabolism, C5:1-acylcarnitine, were significantly higher in mice consuming Mirpur(PCSB) compared with unsupplemented Mirpur-18 (0.148 ± 0.015 versus 0.086 ± 0.0098 μM, respectively; P = 0.014, unpaired t test). Findings from mass spectrometric analysis of cecal contents, isolation, and comparative genomic analysis of an F. prausnitzii strain prominently represented in the transplanted community, and characterization of the in vivo transcriptional responses of this strain to the different diets, are described in table S15F and supplementary text results.

Gut mucosal barrier function

Epithelium and overlying mucus from the proximal, middle, and distal thirds of the small intestine were recovered with laser capture microdissection (LCM) (Fig. 4D). Listed in table S15C are the 30 most abundant OTUs identified by means of V4-16S rDNA analysis of LCM mucosal DNA obtained from the different small intestinal segments within a given diet group and between similarly positioned segments across the different diet treatments. For example, Mirpur(PCSB) produced a statistically significant increase in the relative abundance of F. prausnitzii in the proximal two-thirds of the small intestine, without significantly affecting the proportional representation of a milk-associated age-discriminatory Bifidobacteria OTU (Fig. 4, C and D).

Gene expression was characterized in the jejunal mucosa (Fig. 4D, SI-2 segment) recovered by LCM from mice belonging to all six treatment groups. Significant differences in expression were categorized based on enriched Gene Ontology (GO) terms for “Molecular Function.” In colonized mice, Mirpur(P) and Mirpur(PCSB) significantly up-regulated genes assigned to “cadherin binding” (GO: 0045296) and “cell adhesion molecule binding” (GO: 0050839) compared with Mirpur-18 (table S17A). The diet effect was colonization-dependent; there were no significant differences in expression of these genes or these GO categories in germ-free mice consuming supplemented versus unsupplemented diets (table S17). (Further discussion is available in the supplementary text, results, and histochemical and immunohistochemical analyses of tissue sections prepared along the length of the small intestines of these mice are provided in fig. S6). On the basis of its effects on microbial community organismal composition, gene expression, and gut barrier function, we deemed Mipur-18 supplemented with the four lead complementary foods (Mirpur(PCSB)) superior to that supplemented with just peanut flour (Mirpur(P)).

Characterizing MDCF prototypes in gnotobiotic piglets

We examined the effects of MDCF prototypes in a second host species whose physiology and metabolism are more similar to that of humans. Gnotobiotic piglets provide an attractive model for these purposes; piglets manifest rapid growth rates in the weeks after birth (26), and methods for conducting experiments with gnotobiotic piglets have been described (27).

On the basis of the results from the gnotobiotic mouse studies, we designed two MDCF prototypes. One prototype was formulated to be analogous to Mirpur-18, which contains milk powder; this prototype was supplemented with peanut flour, chickpea flour, soy flour, and banana (MDCF(PCSB)). The other diet lacked milk powder and was supplemented with just chickpea flour and soy flour (MDCF(CS)). The two MDCFs were isocaloric, matched in lipid levels and total protein content (with equivalent representation of amino acids), and also met current ready-to-use therapeutic food guidelines for children with respect to macro- and micronutrient content (table S18A) (28).

Four-day-old germ-free piglets fed a sow milk–based formula were colonized with a 14-member consortium of bacterial strains that consisted of the same nine Bangladeshi age-discriminatory strains used for the diet oscillation experiments described in fig. S2, plus five weaning-phase age-discriminatory strains cultured from Malawian children (table S6B). In an earlier study, several members of this consortium (B. longum, F. prausnitzii, Clostridium, Ruminococcus gnavus, and D. formicigenerans) had been classified as growth-discriminatory by means of a RF-based analysis of their representation in gnotobiotic mouse recipients of healthy and undernourished donor microbiota and the animals’ weight and lean body mass gain phenotypes (4). After gavage, the two groups of piglets were weaned over the course of 10 days (supplementary materials, materials and methods) onto one or the other irradiated MDCF prototypes, which they consumed ad libitum for the remainder of the experiment (n = 4 piglets/treatment arm) (Fig. 5A). Animals were euthanized on day 31 after a 6-hour fast.

Fig. 5 Effects of two different MDCF prototypes in gnotobiotic piglets.

(A) Experimental design. (B) Weight gain in piglets weaned onto isocaloric MDCF prototypes containing either peanut flour, chickpea flour, soy flour, and banana (MDCF(PCSB)) or chickpea and soy flours (MDCF(CS)). (C) μCT of femoral bone obtained at euthanasia. (re) Effects of the MDCFs on the relative abundances of community members in cecal and distal colonic contents. (E) Examples of serum proteins with significantly different post-treatment levels between the two diet groups. (F) Effect of diet on serum C3 acylcarnitine levels. Mean values ± SD are plotted. *P < 0.05; **P < 0.01; ***P < 0.005, ****P < 0.001 (two-way ANOVA in (B), unpaired t test in (C), (D), and (F)). The color code provided in (B) also applies to (C), (D), and (F).

Piglets fed MDCF(PCSB) exhibited significantly greater weight gain than those receiving MDCF(CS) (Fig. 5B). Micro-computed tomography of their femurs revealed that they also had significantly greater cortical bone volume (Fig. 5C). COPRO-seq analysis disclosed that piglets fed MDCF(PCSB) had significantly higher relative abundances of C. symbiosum, R. gnavus, D. formicigenerans, R. torques, and Bacteroides fragilis in their cecum and distal colon compared with those of piglets consuming MDCF(CS) (Fig. 5D and table S18B); all are weaning-phase age-discriminatory strains, and the former three were, as noted above, also defined as growth-discriminatory. Conversely, the relative abundances of three members of Bifidobacteria (including two milk-associated age-discriminatory strains, B. breve and B. longum subsp. infantis) were significantly higher in the ceca and distal colons of piglets fed MDCF(CS) (table S18B). These findings led us to conclude that MDCF(PCSB) promoted a more weaning-phase–like (mature) community configuration than MDCF(CS). (genome annotations, microbial RNA-seq, and targeted MS analyses of cecal metabolites are provided in tables S18, C and D, and S19A and supplementary text, results).

The effects of the two MDCF prototypes on host biology were defined by means of MS-based serum metabolomic and proteomic analyses (tables S19 and S20). Notable findings included significant increases in levels of tryptophan, methionine, and C3-acylcarnitine with MDCF(PCSB) as well as changes produced in the serum proteome that are shared with children in the SAM trial (Fig. 5, E and F, and supplementary text, results).

Testing MDCFs in Bangladeshi children with MAM

To assess the degree to which results obtained from the gnotobiotic mouse and piglet models translate to humans, we performed a pilot randomized, double-blind controlled feeding study of the effects of three MDCF formulations. The formulations (MDCF-1, -2, and -3) were designed to be similar in protein energy ratio and fat energy ratio and provide 250 kcal/day (divided over two servings). MDCF-2 contained all four lead ingredients (chickpea flour, soy flour, peanut flour, and banana) at higher concentrations than in MDCF-1. MDCF-3 contained two lead ingredients (chickpea flour and soy flour). A rice- and lentil-based ready-to-use supplementary food (RUSF), included as a control arm, lacked all four ingredients but was otherwise similar in energy density, protein energy ratio, fat energy ratio, and macro- and micronutrient content to those of the MDCFs (Fig. 6A). Milk powder was included in MDCF-1 and RUSF. All formulations were supplemented with a micronutrient mixture designed to provide 70% of the recommended daily allowances for 12- to 18-month-old children. The formulations were produced locally and tested for organoleptic acceptability before initiating the trial (table S21A).

Fig. 6 Comparing the effects of MDCF formulations on the health status of Bangladeshi children with MAM.

(A) Study design and composition of diets. Total carbohydrate includes all components except added sugar. (B) Quantitative proteomic analysis of the average fold-change, per treatment group, in the abundances of the 50 plasma proteins most discriminatory for healthy growth and the 50 plasma proteins most discriminatory for SAM (protein abundance is column-normalized across treatment groups). (C) Average fold-change in abundances of plasma proteins that significantly positively or negatively correlate with HAZ (absolute value of Pearson correlation > 0.25, FDR-corrected P value < 0.05; abundance is column-normalized as in (B)).

Children from Mirpur with MAM and no prior history of SAM were enrolled (mean age at enrollment, 15.2 ± 2.1 months, mean WHZ –2.3 ± 0.3). Participants were randomized into one of the four treatment groups (14 to 17 children per group) and received 4 weeks of twice-daily feeding under supervision at the study center, preceded and followed by 2 weeks of observation and sample collection. Mothers were encouraged to continue their normal breastfeeding pactices throughout the study (Fig. 6A). There were no significant differences in the mean daily amount of each MDCF or RUSF consumed per child or in the mean incidence of morbidity across the four treatment groups (table S21, B to D). All three MDCFs and the RUSF control improved WHZ scores (–1.9 ± 0.5 (mean ± SD) at the completion of intervention compared with –2.2 ± 0.4 at the start of intervention; n = 63 children, P = 2.06 × 10−11 for all groups combined, paired t test). There were no statistically significant differences between the four interventions in the change in WHZ (P = 0.31, one-way ANOVA). Despite the small group size and the short length of the study, there were significant differences in treatment effects on another anthropometric indicator, with MDCF-2 producing a significantly greater increase in mid-upper arm circumference (MUAC) than MDCF-3 (one-way ANOVA, P = 0.022; with Tukey’s multiple comparisons test, P = 0.017) (table S21E).

Effects on biological state

To contextualize the biological effects of the dietary interventions, we performed quantitative proteomics (SOMAscan) on plasma collected from 21 12- to 24-month-old Mirpur children with healthy growth phenotypes (mean age, 19.2 ± 5.1 months; WHZ, 0.08 ± 0.58; HAZ, –0.41 ± 0.56, WAZ, –0.12 ± 0.60) and 30 children with SAM before treatment (Fig. 1A, B1 sample; WHZ < –3; mean age 15.2 ± 5.1 months) (metadata associated with the healthy, SAM, and MAM (MDCF trial) cohorts are provided in table S22). We rank-ordered all detected proteins according to fold differences in their abundances in plasma collected from healthy children compared with children with untreated SAM. The top 50 most differentially abundant proteins (P < 10−7; R package “limma”) that were significantly higher in healthy children were designated “healthy growth-discriminatory,” whereas the top 50 differentially abundant proteins that were significantly higher in children with SAM were designated “SAM-discriminatory” (table S23A). We next compared the mean difference for each protein in the pre- versus post-intervention plasma samples for all children in each MDCF/RUSF treatment group. Proteins were then ranked according to the fold differences of the pre- versus post-treatment levels in each of the four groups (table S23B), and these treatment effects were mapped onto the 50 most healthy growth-discriminatory and 50 most SAM-discriminatory proteins. Strikingly, MDCF-2 elicited a biological response characterized by a marked shift in the plasma proteome toward that of healthy children and away from that of children with SAM; MDCF-2 increased the abundance of proteins that are higher in plasma from healthy children and reduced the levels of proteins elevated in SAM plasma samples (Fig. 6B).

Aggregating proteomic datasets from the combined cohort of 113 children with SAM, MAM, and healthy growth phenotypes for whom plasma samples were available, we identified a total of 27 plasma proteins that were significantly positively correlated with HAZ and 57 plasma proteins that were significantly negatively correlated with HAZ (absolute value of Pearson correlation > 0.25, false discovery rate (FDR)–corrected P value < 0.05). Among the treatments, MDCF-2 was distinctive in its ability to increase the abundances of a broad range of proteins positively correlated with HAZ, including the major IGF-1 binding protein IGFBP-3, growth hormone receptor (GHR), and leptin (LEP) (Fig. 6C). Growth differentiation factor 15 (GDF15) was reduced after 4 weeks of dietary supplementation with MDCF-2 (Fig. 6C). This transforming growth factor–β superfamily member, which was negatively correlated with HAZ, has been implicated in the anorexia and muscle wasting associated with cancer and with chronic heart failure in children; it was elevated in children with SAM and positively correlated with their lipolytic biomarkers NEFA and ketones (supplementary text, results). Peptide YY, an enteroendocrine cell product elevated in SAM plasma that reduces appetite and negatively correlated with HAZ, was also decreased by MDCF-2.

We identified GO terms that were enriched among the group of treatment-responsive proteins and ranked them according to the P value of their enrichment (table S23C). Proteins belonging to GO terms significantly higher in healthy compared with SAM plasma samples were deemed “healthy growth-discriminatory,” whereas those that were significantly higher in SAM were deemed “SAM-discriminatory” (fold-difference >30%; FDR-adjusted P value <0.05). This analysis revealed multiple healthy growth-discriminatory proteins associated with GO processes “osteoblast differentiation” and “ossification” that were increased by supplementation with MDCF-2 (Fig. 7A and table S23C). Examples include key markers or mediators of osteoblast differentiation (osteopontin (SPP1), bone sialoprotein 2 (IBSP), and bone morphogenetic protein 7 (BMP7)) as well as matrix metalloproteases (MMP-2 and MMP-13) involved in terminal differentiation of osteoblasts into osteocytes and bone mineralization.

Fig. 7 The effects of different MDCF formulations on biomarkers and mediators of bone and CNS development, plus NF-κB signaling.

(A at C) Average fold-change (normalized across treatment groups) in the abundances of plasma proteins belonging to GO categories related to (A) bone, (B) CNS development, and (C) agonists and components of the NF-ĸB signaling pathway. Proteins in the GO category that were significantly higher in the plasma of healthy compared with SAM children (fold-difference >30%; FDR-adjusted P value < 0.05) are labeled “healthy growth-discriminatory,” whereas those higher in SAM compared with healthy children (fold-difference >30%; FDR-adjusted P value < 0.05) are labeled “SAM-discriminatory.” Levels of multiple “healthy growth-discriminatory” proteins associated with (A) GO processes “osteoblast differentiation” and “ossification”, and (B) the GO process “CNS development” are enhanced by MDCF-2 treatment while (C) NF-kB signaling is suppressed.

A number of plasma proteins categorized under the GO process “CNS development,” including those involved in axon guidance and neuronal differentiation, were also affected by MDCF-2 supplementation. Levels of the SAM-discriminatory semaphorin SEMA3A, a potent inhibitor of axonal growth, decreased with this treatment, whereas healthy growth-discriminatory semaphorins (SEMA5A, SEMA6A, and SEMA6B) increased (Fig. 7B). Other healthy growth-discriminatory proteins whose abundances increased with MDCF-2 included receptors for neurotrophin (NTRK2 and NTRK3) plus various axonal guidance proteins (netrin (UNC5D), ephrin A5 (EFNA5), roundabout homolog 2 (ROBO2), and SLIT and NTRK-like protein 5 (SLITRK5)) (Fig. 7B). Expression of a number of neurotrophic proteins belonging to these families has been reported to be influenced by nutrient availability in primates (29).

Compared with healthy children, the plasma proteome of children with SAM was characterized by elevated levels of acute phase proteins (such as C-reactive protein (CRP) or interleukin-6 (IL-6)) and inflammatory mediators, including several agonists and components of the nuclear factor–κB (NF-κB) signaling pathway (Fig. 7C). These components include the pro-inflammatory cytokines IL-1β, tumor necrosis factor–α (TNF-α), and CD40L, plus ubiquitin-conjugating enzyme E2 N (UBE2N), which is involved in induction of NF-κB– and mitogen-activated protein kinase (MAPK)–responsive inflammatory genes (30). MDCF-2 supplementation was associated with reductions in the levels of all of these SAM-associated proteins (Fig. 7C).

Effects on the microbiota

Our analysis of fecal microbiota samples revealed no significant change in the representation of enteropathogens within and across the four treatment groups (fig. S7A and table S21F). MDCF-2–induced changes in biological state were accompanied by increases in the relative abundances of several weaning-phase taxa, including OTUs assigned to F. prausnitzii (OTU 851865) and a Clostridiales sp. (OTU 338992) that are closely related to taxa ranked first and second in feature importance in the sparse Bangladeshi RF-derived model of gut microbiota maturation (fig. S7, B and C). MDCF-2 supplementation was associated with a significant decrease in B. longum (OTU 559527) (fig. S7B), which is ranked third in feature importance in the RF-derived model and discriminatory for a young, milk-oriented microbiota. None of the other members of the 30 OTU model showed significant changes. By contrast, MDCF-1 did not produce significant increases in any of the taxa in the model. The other two formulations were each associated with a significant change in just one member (an increase in the relative abundance of an early age-discriminatory OTU (Streptococcus; ranked 30th) with MDCF-3 supplementation, and a decrease in another OTU (Enterococcus faecalis; ranked 29th) with RUSF supplementation) (table S4B).

MAZ scores were not significantly different between groups at enrollment, nor were they significantly improved by any of the formulations. Interpretation of this finding was confounded by unexpectedly high baseline microbiota maturity scores in this group of children with MAM (MAZ, –0.01 ± 1.12 (mean ± SD)) (table S22) compared with a small, previously characterized Mirpur cohort with untreated MAM (2). Hence, we developed an additional measure of microbiota repair (31). This involved a statistical analysis of covariance among bacterial taxa in the fecal microbiota of anthropometrically healthy members of a Mirpur birth cohort who had been sampled monthly over a 5-year period. Using approaches developed in the fields of econophysics and protein evolution to characterize the underlying organization of interacting systems with seemingly intractable complexity, such as financial markets, we found that the gut community in healthy children could be decomposed into a sparse unit of 15 covarying bacterial taxa termed an “ecogroup” (31). These ecogroup taxa include a number of age-discriminatory strains in the Bangladeshi RF-derived model (such as B. longum, F. prausnitzii, and Prevotella copri). We used the ecogroup to show that in addition to its effects on host biological state, MDCF-2 was also the most effective of the four treatments in reconfiguring the gut bacterial community to a mature state similar to that characteristic of healthy Bangladeshi children.


We have integrated preclinical gnotobiotic animal models with human studies to understand the contributions of perturbed gut microbiota development to childhood undernutrition and to identify new microbiota-directed therapeutic approaches. We identified a set of proteins that distinguish the plasma proteomes of healthy children from those with SAM. Using these data, we have developed a supplemental food prototype, MDCF-2, that shifted the plasma proteome of children with MAM toward that of healthy individuals, including proteins involved in linear growth, bone development, neurodevelopment, and immune function. MDCF-2 is a tool for investigating, in larger studies across different populations with varying degrees of undernutrition, how repair of gut microbiota immaturity affects various facets of child growth.

Overview of methods

Human studies

Children aged 6 to 59 months with SAM (n = 343 participants) were enrolled in a study entitled “Development and field testing of ready-to-use therapeutic foods (RUTF) made of local ingredients in Bangladesh for the treatment of children with severe acute malnutrition.” The study was approved by the Ethical Review Committee at icddr,b (ClinicalTrials.gov identifier NCT01889329). Written informed consent was obtained from their parent or guardian. A subset of 54 children were included in a substudy that involved regular fecal sampling and three blood draws for up to 1 year after discharge. Children aged 12 to 18 months with MAM who were no longer exclusively breastfed (n = 63 participants) were enrolled in a double-blind, randomized, four-group, parallel assignment interventional trial study (ClinicalTrials.gov identifier NCT03084731) approved by the Ethical Review Committee at icddr,b. Fecal and plasma samples were collected as described in the supplementary materials, materials and methods, and stored at –80°C. Samples were shipped to Washington University with associated clinical metadata and maintained in a dedicated biospecimen repository with approval from the Washington University Human Research Protection Office.

Analysis of plasma samples

Methods for targeted MS-based metabolomics are described in the supplementary materials. The SOMAscan 1.3K Proteomic Assay plasma/serum kit (SomaLogic, Boulder, Colorado,) was used to measure 1305 proteins. The R package “limma” (Bioconductor) was used to analyze differential protein abundances (32). Spearman correlation analyses were performed between measured proteins and anthropometric scores, plasma metabolites, and the abundances of bacterial taxa in fecal samples. Plasma proteins in children with healthy growth phenotypes or SAM (before treatment) were rank-ordered according to the fold-difference in their levels between these two groups. The top 50 most differentially abundant proteins in healthy compared with SAM were designated as healthy growth-discriminatory proteins, and the top 50 most differentially abundant in SAM compared with healthy were designated as SAM-discriminatory proteins. The average fold-change for these healthy growth- and SAM-discriminatory proteins was then calculated for each treatment arm in the MDCF trial (before versus after MDCF/RUSF treatment) and normalized to the mean fold-change across all four arms. Limma was used to calculate statistical significance. All 1305 proteins were mapped to all GO “Biological Processes” in the GO database (www.geneontology.org). SetRank, a gene set enrichment analysis (GSEA) algorithm (33), was used to identify GO Biological Processes that were significantly enriched for proteins that exhibited changes in abundance from before to after treatment with MDCF/RUSF. Enrichment was calculated by using the setRankAnalysis function in the SetRank R library (parameters were use.ranks = TRUE; setPCutoff = 0.01; and fdrCutoff = 0.05). The average fold-change for each protein in the statistically significant Biological Process category was calculated for each treatment arm and normalized to the mean fold-change across all four arms. We defined proteins within the GO Biological Process as “healthy growth-discriminatory” if they were at least 30% more abundant in healthy individuals compared with those with SAM and “SAM-discriminatory” if they were at least 30% more abundant in children with SAM compared with those who were classified as healthy.

Characterizing human fecal microbial communities

Methods for V4-16S rRNA gene sequencing and data analysis, calculation of MAZ scores and functional microbiome maturity, and quantification of enteropathogen burden by means of multiplex quantitative polymerase chain reaction (qPCR) are described in the supplementary materials.

Animal studies

Gnotobiotic mice

All mouse experiments were performed by using protocols approved by the Washington University Animal Studies Committee. Mice were housed in plastic flexible film gnotobiotic isolators under a 12-hour light cycle. Male germ-free C57BL/6 mice were initially weaned onto an autoclaved, low-fat, high-plant polysaccharide chow that was administered ad libitum (diet 2018S, Envigo). Animals were maintained on this diet until 3 days before the beginning of experiments involving tests of the effects of complementary food ingredients. Defined consortia of sequenced bacterial strains cultured from Bangladeshi children, or intact uncultured microbiota from donors with post-SAM MAM, were introduced by means of gavage into recipient mice at 5 weeks of age. Methods for identifying and characterizing the effects MDCF prototypes—including (i) design and preparation of diets; (ii) culturing of age-discriminatory and SAM-associated bacterial strains; (iii) shotgun sequencing of DNA isolated from serially collected fecal samples; (iv) microbial RNA-seq of cecal contents; (v) targeted MS of cecal contents, liver, gastrocnemius muscle, and serum samples for measurement of amino acids, acylcarnitines, organic acids, and acylCoAs; (vi) Western blot analysis of IGF-1 pathway components in liver; (vii) μCT of bone; and (viii) characterizing the effects of a transplanted fecal microbiome from a donor with post-SAM MAM in recipient gnotobiotic mice as a function of diet treatment by histochemical and immunohistochemical analysis of their intestinal segments, LCM of their small intestinal epithelium, and RNA-seq analysis of gene expression in LCM mucosa—are all described in the supplementary materials.

Gnotobiotic piglets

Experiments were performed under the supervision of a veterinarian by using protocols approved by the Washington University Animal Studies Committee and that followed American Veterinary Medical Association guidelines for euthanasia. The protocol for generating germ-free piglets; preparing diets, feeding, colonization, and husbandry of piglets; measurement of weight gain; μCT of femurs; and liquid chromatography–MS (LC-MS)/MS–based serum proteomics are all described in the supplementary materials.

Remerciements: We are grateful to the families of members of the human studies described in this work for their participation and assistance. We are indebted to the staff and health care workers at icddr,b for their contributions to the recruitment and enrollment of mothers as well as the collection of biospecimens and data from their offspring. We thank M. Karlsson, M. Meier, S. Wagoner, S. Deng, J. Serugo, and J. Hoisington-López for superb technical assistance; K. Ahsan for assistance with maintaining the biospecimen repository and associated database; J. Guruge for help with anaerobic microbiology; O. Delannoy-Bruno for assistance with the gnotobiotic piglet experiment; Mars, Inc. for their assistance with manufacturing the MDCF(PCSB) and MDCF(CS) diets; A. Lutz and J. Yu (Genome Technology Access Center at Washington University) for their contributions to generating SOMAscan datasets; R. Olson and other members of RAST/SEED development team at the Argonne National Laboratory for support with the mcSEED-based genome analysis and subsystem curation; and D. Leib for developing the computer program to quantify CT scan data obtained from the femurs of gnotobiotic piglets. Le financement: This work was supported by the Bill & Melinda Gates Foundation as part of the Breast Milk, gut Microbiome, and Immunity (BMMI) Project. As members of Washington University’s Medical Scientist Training Program, R.Y.C. and S.S. received support from NIH grant GM007200. μCT of femoral bone was performed using resources provided by the Washington University Musculoskeletal Research Center (NIH P30 AR057235). Histochemical and immunohistochemical processing of tissue sections was performed at the Washington University Digestive Diseases Research Core Center, funded by NIH P30 DK052574. Plasma proteomic datasets were generated by the Genome Technology Access Center at Washington University School of Medicine, which is supported in part by NIH Grants P30 CA91842 and UL1TR002345. D.A.R., A.A.A., and S.A.L. were supported in part by the Russian Science Foundation (grants 14-14-00289 and 19-14-00305). J.I.G. is the recipient of a Thought Leader Award from Agilent Technologies. This work is licensed under a Creative Commons Attribution 4.0 International (CC BY 4.0) license, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0. This license does not apply to figures/photos/artwork or other content included in the article that is credited to a third party; obtain authorization from the rights holder before using such material. Author contributions: T.A., I.H., M.I., N.C., S.H., I.Ma., M.Ma., S.A.S., and I.Mo. were responsible for the design and conduct of the human studies plus collection of biospecimens and clinical metadata. M.J.B. established and maintained biospecimen repositories and associated databases of de-identified metadata. J.L.G. and M.F.M. generated the 16S rDNA and shotgun sequencing datasets from human fecal samples, and J.L.G. and M.C.H. analyzed the data. S.V., J.L.G., M.J.B., and J.I.G. designed the gnotobiotic mouse studies. H.-W.C., M.J.B., and J.I.G. designed the gnotobiotic piglet experiments. J.L.G., S.V., and S.S. cultured bacterial strains. J.L.G., S.V., H.-W.C., and M.C.H. sequenced and assembled the genomes of bacterial strains used in gnotobiotic animal experiments. D.A.R., A.A.A., S.A.L., and A.L.O. performed in silico metabolic reconstructions with the genomes of the cultured strains. B.H. provided updated CAZyme annotations. S.V. and J.L.G. performed gnotobiotic mouse experiments with cultured bacterial strains and intact uncultured communities, respectively. H.-W.C., D.O.D, and M.T. conducted the gnotobiotic piglet experiments. S.V. and H.-W.C. generated COPRO-Seq datasets. S.V., J.L.G., M.C.H., and H.-W.C. produced microbial RNA-seq datasets. V.L.K. performed laser capture microdissection, V4-16S rDNA analysis of intestinal mucosa-associated bacterial community composition, RNA-seq–based characterization of mouse small intestinal mucosal gene expression, and histochemical assays of intestinal morphometry. J.C., S.V., J.L.G., H.-W.C., M.Mu., O.I., and C.B.N. conducted metabolomic analyses of mouse, piglet and human biospecimens. C.A.C. performed μCT of femurs; measured serum IGF-1 levels in gnotobiotic mice; and quantified leptin, IGF-1, and insulin in plasma obtained from children in the SAM trial. H.-W.C. generated microcomputed tomographic datasets from piglet femurs. L.D.S. and C.F.S. characterized levels of IGF-1 pathway components in the livers of gnotobiotic mice. R.J.G. and R.L.H. were responsible for MS-based proteomics of piglet serum samples. R.D.H. and M.J.B. produced the quantitative proteomic datasets from plasma samples with DNA aptamer-based arrays, and R.Y.C., M.J.B., J.L.G., and M.C.H. analyzed the data. C.S. and M.C.H. performed and analyzed qPCR assays for enteropathogens. J.L.G., S.V., H.-W.C., M.J.B., and J.I.G. wrote the paper with assistance provided by co-authors. Intérêts concurrents: J.I.G. is a cofounder of Matatu, a company characterizing the role of diet-by-microbiota interactions in animal health. L.D.S. is currently a scientific sales representative at STEMCELL Technologies. Disponibilité des données et des matériaux: V4-16S rDNA sequences in raw format prior to post-processing and data analysis, COPRO-seq, microbial RNA-seq, and proteomics datasets, plus shotgun sequencing datasets produced from human fecal DNA, cecal contents of gnotobiotic mice with a post-SAM MAM human donor community and cultured bacterial strains, have been deposited at the European Nucleotide Archive (ENA) under study accession no. PRJEB26419. SOMAscan-generated human plasma proteomic datasets have been deposited in the Gene Expression Omnibus (GEO) database under accession no. GSE119641. All raw mass spectra for quantification of serum proteins in gnotobiotic piglets have been deposited in the MassIVE and ProteomeXchange data repositories under accession nos. MSV000082286 (MassIVE) and PXD009534 (ProteomeXchange), with data files available at ftp://massive.ucsd.edu/MSV000082286. Fecal and plasma specimens from the SAM and MDCF studies used for the analyses described in this study were provided to Washington University under materials transfer agreements with icddr,b.

Correction (11 July 2019): The clarifying sentence “Total carbohydrate includes all components except added sugar.” has been added to the Fig. 6A caption.

Effects of Targeted Foods on the Microbiota in Gnotobiotic Animals and Undernourished Children | EXCLUSIVE OFFER !
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