A compendium of 32,277 metagenome-assembled genomes and over 80 million genes from the early-life human gut microbiome

Gut microbial genomes with paired isolates from China illustrate probiotic and cardiometabolic effects

The gut microbiome displays genetic differences among populations, and characterization of the genomic landscape of the gut microbiome in China remains limited. Here, we present the Chinese Gut Microbial Reference (CGMR) set, comprising 101,060 high-quality metagenomic assembled genomes (MAGs) of 3,707 nonredundant species from 3,234 fecal samples across primarily rural Chinese locations, 1,376 live isolates mainly from lactic acid bacteria, and 987 novel species relative to worldwide databases. We observed region-specific coexisting MAGs and MAGs with probiotic and cardiometabolic functionalities. Preliminary mouse experiments suggest a probiotic effect of two Faecalibacillus intestinalis isolates in alleviating constipation, cardiometabolic influences of three Bacteroides fragilis_A isolates in obesity, and isolates from the genera Parabacteroides and Lactobacillus in host lipid metabolism. Our study expands the current microbial genomes with paired isolates and demonstrates potential host effects, contributing to the mechanistic understanding of host-microbe interactions.

Genome plasticity shapes the ecology and evolution of Phocaeicola dorei and Phocaeicola vulgatus

Phocaeicola dorei and Phocaeicola vulgatus are very common and abundant members of the human gut microbiome and play an important role in the infant gut microbiome. These species are closely related and often confused for one another; yet, their genome comparison, interspecific diversity, and evolutionary relationships have not been studied in detail so far. Here, we perform phylogenetic analysis and comparative genomic analyses of these two Phocaeicola species. We report that P. dorei has a larger genome yet a smaller pan-genome than P. vulgatus. We found that this is likely because P. vulgatus is more plastic than P. dorei, with a larger repertoire of genetic mobile elements and fewer anti-phage defense systems. We also found that P. dorei directly descends from a clade of P. vulgatus¸ and experienced genome expansion through genetic drift and horizontal gene transfer. Overall, P. dorei and P. vulgatus have very different functional and carbohydrate utilisation profiles, hinting at different ecological strategies, yet they present similar antimicrobial resistance profiles.

Preclinical Atopic Dermatitis Skin in Infants: An Emerging Research Area

Whereas clinically apparent atopic dermatitis (AD) can be confirmed by validated diagnostic criteria, the preclinical phenotype of infants who eventually develop AD is less well-characterized. Analogous to unaffected or nonlesional skin in established AD, clinically normal-appearing skin in infants who will develop clinical AD has distinct changes. Prospective studies have revealed insights into this preclinical AD phenotype. In this study, we review the structural, immunologic, and microbiome nature of the preclinical AD phenotype. Determination of markers that predict the development of AD will facilitate targeting of interventions to prevent the development or reduce the severity of AD in infants.

Metagenome-assembled genomes (MAGs) suggest an acetate-driven protective role in gut microbiota disrupted by Clostridioides difficile

Clostridioides difficile may have a negative impact on gut microbiota composition in terms of diversity and abundance, thereby triggering functional changes supported by the differential presence of genes involved in significant metabolic pathways, such as short-chain fatty acids (SCFA). This work has evaluated shotgun metagenomics data regarding 48 samples from four groups classified according to diarrhea acquisition site (community- and healthcare facility-onset) and positive or negative Clostridioides difficile infection (CDI) result. The metagenomic-assembled genomes (MAGs) obtained from each sample were taxonomically assigned for preliminary comparative analysis concerning differences in composition among groups. The predicted genes involved in metabolism, transport, and signaling remained constant in microbiota members; characteristic patterns were observed in MAGs and genes involved in SCFA butyrate and acetate metabolic pathways for each study group. A decrease in genera and species, as well as relative MAG abundance with the presence of the acetate metabolism-related gene, was evident in the HCFO/- group. Increased antibiotic resistance markers (ARM) were observed in MAGs along with the genes involved in acetate metabolism. The results highlight the need to explore the role of acetate in greater depth as a potential protector of the imbalances produced by CDI, as occurs in other inflammatory intestinal diseases.

Lipid Metabolites as Potential Regulators of the Antibiotic Resistome in Tetramorium caespitum

Antibiotic resistance genes (ARGs) are ancient but have become a modern critical threat to health. Gut microbiota, a dynamic reservoir for ARGs, transfer resistance between individuals. Surveillance of the antibiotic resistome in the gut during different host growth phases is critical to understanding the dynamics of the resistome in this ecosystem. Herein, we disentangled the ARG profiles and the dynamic mechanism of ARGs in the egg and adult phases of Tetramorium caespitum. Experimental results showed a remarkable difference in both gut microbiota and gut resistome with the development of T. caespitum. Meta-based metagenomic results of gut microbiota indicated the generalizability of gut antibiotic resistome dynamics during host development. By using Raman spectroscopy and metabolomics, the metabolic phenotype and metabolites indicated that the biotic phase significantly changed lipid metabolism as T. caespitum aged. Lipid metabolites were demonstrated as the main factor driving the enrichment of ARGs in T. caespitum. Cuminaldehyde, the antibacterial lipid metabolite that displayed a remarkable increase in the adult phase, was demonstrated to strongly induce ARG abundance. Our findings show that the gut resistome is host developmental stage-dependent and likely modulated by metabolites, offering novel insights into possible steps to reduce ARG dissemination in the soil food chain.

A metagenomic catalog of the early-life human gut virome

Early-life human gut microbiome is a pivotal driver of gut homeostasis and infant health. However, the viral component (known as "virome") remains mostly unexplored. Here, we establish the Early-Life Gut Virome (ELGV), a catalog of 160,478 non-redundant DNA and RNA viral sequences from 8130 gut virus-like particles (VLPs) enriched or bulk metagenomes in the first three years of life. By clustering, 82,141 viral species are identified, 68.3% of which are absent in existing databases built mainly from adults, and 64 and 8 viral species based on VLPs-enriched and bulk metagenomes, respectively, exhibit potentials as biomarkers to distinguish infants from adults. With the largest longitudinal population of infants profiled by either VLPs-enriched or bulk metagenomic sequencing, we track the inherent instability and temporal development of the early-life human gut virome, and identify differential viruses associated with multiple clinical factors. The mother-infant shared virome and interactions between gut virome and bacteriome early in life are further expanded. Together, the ELGV catalog provides the most comprehensive and complete metagenomic blueprint of the early-life human gut virome, facilitating the discovery of pediatric disease-virome associations in future.

Synergistic horizontal transfer of antibiotic resistance genes and transposons in the infant gut microbial genome

Transposons, plasmids, bacteriophages, and other mobile genetic elements facilitate horizontal gene transfer in the gut microbiota, allowing some pathogenic bacteria to acquire antibiotic resistance genes (ARGs). Currently, the relationship between specific ARGs and specific transposons in the comprehensive infant gut microbiome has not been elucidated. In this study, ARGs and transposons were annotated from the Unified Human Gastrointestinal Genome (UHGG) and the Early-Life Gut Genomes (ELGG). Association rules mining was used to explore the association between specific ARGs and specific transposons in UHGG, and the robustness of the association rules was validated using the external database in ELGG. Our results suggested that ARGs and transposons were more likely to be relevant in infant gut microbiota compared to adult gut microbiota, and nine robust association rules were identified, among which Klebsiella pneumoniae, Enterobacter hormaechei_A, and Escherichia coli_D played important roles in this association phenomenon. The emphasis of this study is to investigate the synergistic transfer of specific ARGs and specific transposons in the infant gut microbiota, which can contribute to the study of microbial pathogenesis and the ARG dissemination dynamics.IMPORTANCEThe transfer of transposons carrying antibiotic resistance genes (ARGs) among microorganisms accelerates antibiotic resistance dissemination among infant gut microbiota. Nonetheless, it is unclear what the relationship between specific ARGs and specific transposons within the infant gut microbiota. K. pneumoniae, E. hormaechei_A, and E. coli_D were identified as key players in the nine robust association rules we discovered. Meanwhile, we found that infant gut microorganisms were more susceptible to horizontal gene transfer events about specific ARGs and specific transposons than adult gut microorganisms. These discoveries could enhance the understanding of microbial pathogenesis and the ARG dissemination dynamics within the infant gut microbiota.

MAGICIAN: MAG simulation for investigating criteria for bioinformatic analysis

BACKGROUND

The possibility of recovering metagenome-assembled genomes (MAGs) from sequence reads allows for further insights into microbial communities and their members, possibly even analyzing such sequences with tools designed for single-isolate genomes. As result quality depends on sequence quality, performance of tools for single-isolate genomes on MAGs should be tested beforehand. Bioinformatics can be leveraged to quickly create varied synthetic test sets with known composition for this purpose.

RESULTS

We present MAGICIAN, a flexible, user-friendly pipeline for the simulation of MAGs. MAGICIAN combines a synthetic metagenome simulator with a metagenomic assembly and binning pipeline to simulate MAGs based on user-supplied input genomes, allowing users to test performance of tools on MAGs while having a ground truth to compare results to. Using MAGICIAN, we found that even very slight (1%) changes in depth of coverage can drastically affect whether a genome can be recovered. We also demonstrate the use of simulated MAGs by evaluating the suitability of such genomes obtained with MAGICIAN's current default pipeline for analysis with the antimicrobial resistance gene identification tool ResFinder.

CONCLUSIONS

Using MAGICIAN, it is possible to simulate MAGs which, while generally high in quality, reflect issues encountered with real-world data, thus providing realistic best-case data. Evaluating the results of ResFinder analysis of these genomes revealed a risk for plausible-looking false positives, which underlines the need for pipeline validation so that researchers are aware of the potential issues when interpreting real-world data. Furthermore, the effects of fluctuations in depth of coverage on genome recovery in our simulated "random sequencing" warrant further investigation and indicate random subsampling of reads may affect discovery of more genomes.

Influence of age, socioeconomic status, and location on the infant gut resistome across populations

Antibiotic resistance is a growing global concern, with many ecological niches showing a high abundance of antibiotic resistance genes (ARGs), including the human gut. With increasing indications of ARGs in infants, this study aims to investigate the gut resistome profile during early life at a wider geographic level. To achieve this objective, we utilized stool samples data from 26 studies involving subjects aged up to 3 years from different geographical locations. The 32,277 Metagenome Assembled Genomes (MAGs) previously generated from shotgun sequencing reads from these studies were used for resistome analysis using RGI with the CARD database. This analysis showed that the distribution of ARGs across the countries in our study differed in alpha diversity and compositionally. In particular, the abundance of ARGs was found to vary by socioeconomic status and healthcare access and quality (HAQ) index. Surprisingly, countries having lower socioeconomic status and HAQ indices showed lower ARG abundance, which was contradictory to previous reports. Gram-negative genera, including Escherichia, Enterobacter, Citrobacter, and Klebsiella harbored a particularly rich set of ARGs, which included antibiotics that belong to the Reserve, Access or Watch category, such as glycopeptides, fluoroquinolones, sulfonamides, macrolides, and tetracyclines. We showed that ARG abundance exponentially decreased with time during the first 3 years of life. Many highly ARG-abundant species including Escherichia, Klebsiella, Citrobacter species that we observed are well-known pathobionts found in the infant gut in early life. High abundance of these species and a diverse range of ARGs in their genomes point toward the infant gut, acting as an ARG reservoir. This is a concern and further studies are needed to examine the causal effect and its consequences on long-term health.

A genome catalog of the early-life human skin microbiome

BACKGROUND

Metagenome-assembled genomes have greatly expanded the reference genomes for skin microbiome. However, the current reference genomes are largely based on samples from adults in North America and lack representation from infants and individuals from other continents.

RESULTS

Here we use deep shotgun metagenomic sequencing to profile the skin microbiota of 215 infants at age 2-3 months and 12 months who are part of the VITALITY trial in Australia as well as 67 maternally matched samples. Based on the infant samples, we present the Early-Life Skin Genomes (ELSG) catalog, comprising 9483 prokaryotic genomes from 1056 species, 206 fungal genomes from 13 species, and 39 eukaryotic viral sequences. This genome catalog substantially expands the diversity of species previously known to comprise human skin microbiome and improves the classification rate of sequenced data by 21%. The protein catalog derived from these genomes provides insights into the functional elements such as defense mechanisms that distinguish early-life skin microbiome. We also find evidence for microbial sharing at the community, bacterial species, and strain levels between mothers and infants.

CONCLUSIONS

Overall, the ELSG catalog uncovers the skin microbiome of a previously underrepresented age group and population and provides a comprehensive view of human skin microbiome diversity, function, and development in early life.

Fast and robust metagenomic sequence comparison through sparse chaining with skani

Sequence comparison tools for metagenome-assembled genomes (MAGs) struggle with high-volume or low-quality data. We present skani ( https://github.com/bluenote-1577/skani ), a method for determining average nucleotide identity (ANI) via sparse approximate alignments. skani outperforms FastANI in accuracy and speed (>20× faster) for fragmented, incomplete MAGs. skani can query genomes against >65,000 prokaryotic genomes in seconds and 6 GB memory. skani unlocks higher-resolution insights for extensive, noisy metagenomic datasets.

Expanded microbiome niches of RAG-deficient patients

The complex interplay between microbiota and immunity is important to human health. To explore how altered adaptive immunity influences the microbiome, we characterize skin, nares, and gut microbiota of patients with recombination-activating gene (RAG) deficiency-a rare genetically defined inborn error of immunity (IEI) that results in a broad spectrum of clinical phenotypes. Integrating de novo assembly of metagenomes from RAG-deficient patients with reference genome catalogs provides an expansive multi-kingdom view of microbial diversity. RAG-deficient patient microbiomes exhibit inter-individual variation, including expansion of opportunistic pathogens (e.g., Corynebacterium bovis, Haemophilus influenzae), and a relative loss of body site specificity. We identify 35 and 27 bacterial species derived from skin/nares and gut microbiomes, respectively, which are distinct to RAG-deficient patients compared to healthy individuals. Underscoring IEI patients as potential reservoirs for viral persistence and evolution, we further characterize the colonization of eukaryotic RNA viruses (e.g., Coronavirus 229E, Norovirus GII) in this patient population.

Mediterranean diet and olive oil, microbiota, and obesity-related cancers. From mechanisms to prevention

Olive oil (OO) is the main source of added fat in the Mediterranean diet (MD). It is a mix of bioactive compounds, including monounsaturated fatty acids, phytosterols, simple phenols, secoiridoids, flavonoids, and terpenoids. There is a growing body of evidence that MD and OO improve obesity-related factors. In addition, obesity has been associated with an increased risk for several cancers: endometrial, oesophageal adenocarcinoma, renal, pancreatic, hepatocellular, gastric cardia, meningioma, multiple myeloma, colorectal, postmenopausal breast, ovarian, gallbladder, and thyroid cancer. However, the epidemiological evidence linking MD and OO with these obesity-related cancers, and their potential mechanisms of action, especially those involving the gut microbiota, are not clearly described or understood. The goals of this review are 1) to update the current epidemiological knowledge on the associations between MD and OO consumption and obesity-related cancers, 2) to identify the gut microbiota mechanisms involved in obesity-related cancers, and 3) to report the effects of MD and OO on these mechanisms.

Uncultured prokaryotic genomes in the spotlight: An examination of publicly available data from metagenomics and single-cell genomics

Owing to the ineffectiveness of traditional culture techniques for the vast majority of microbial species, culture-independent analyses utilizing next-generation sequencing and bioinformatics have become essential for gaining insight into microbial ecology and function. This mini-review focuses on two essential methods for obtaining genetic information from uncultured prokaryotes, metagenomics and single-cell genomics. We analyzed the registration status of uncultured prokaryotic genome data from major public databases and assessed the advantages and limitations of both the methods. Metagenomics generates a significant quantity of sequence data and multiple prokaryotic genomes using straightforward experimental procedures. However, in ecosystems with high microbial diversity, such as soil, most genes are presented as brief, disconnected contigs, and lack association of highly conserved genes and mobile genetic elements with individual species genomes. Although technically more challenging, single-cell genomics offers valuable insights into complex ecosystems by providing strain-resolved genomes, addressing issues in metagenomics. Recent technological advancements, such as long-read sequencing, machine learning algorithms, and in silico protein structure prediction, in combination with vast genomic data, have the potential to overcome the current technical challenges and facilitate a deeper understanding of uncultured microbial ecosystems and microbial dark matter genes and proteins. In light of this, it is imperative that continued innovation in both methods and technologies take place to create high-quality reference genome databases that will support future microbial research and industrial applications.

A comprehensive genomic catalog from global cold seeps

Cold seeps harbor abundant and diverse microbes with tremendous potential for biological applications and that have a significant influence on biogeochemical cycles. Although recent metagenomic studies have expanded our understanding of the community and function of seep microorganisms, knowledge of the diversity and genetic repertoire of global seep microbes is lacking. Here, we collected a compilation of 165 metagenomic datasets from 16 cold seep sites across the globe to construct a comprehensive gene and genome catalog. The non-redundant gene catalog comprised 147 million genes, and 36% of them could not be assigned to a function with the currently available databases. A total of 3,164 species-level representative metagenome-assembled genomes (MAGs) were obtained, most of which (94%) belonged to novel species. Of them, 81 ANME species were identified that cover all subclades except ANME-2d, and 23 syntrophic SRB species spanned the Seep-SRB1a, Seep-SRB1g, and Seep-SRB2 clades. The non-redundant gene and MAG catalog is a valuable resource that will aid in deepening our understanding of the functions of cold seep microbiomes.

SemiBin2: self-supervised contrastive learning leads to better MAGs for short- and long-read sequencing

MOTIVATION

Metagenomic binning methods to reconstruct metagenome-assembled genomes (MAGs) from environmental samples have been widely used in large-scale metagenomic studies. The recently proposed semi-supervised binning method, SemiBin, achieved state-of-the-art binning results in several environments. However, this required annotating contigs, a computationally costly and potentially biased process.

RESULTS

We propose SemiBin2, which uses self-supervised learning to learn feature embeddings from the contigs. In simulated and real datasets, we show that self-supervised learning achieves better results than the semi-supervised learning used in SemiBin1 and that SemiBin2 outperforms other state-of-the-art binners. Compared to SemiBin1, SemiBin2 can reconstruct 8.3-21.5% more high-quality bins and requires only 25% of the running time and 11% of peak memory usage in real short-read sequencing samples. To extend SemiBin2 to long-read data, we also propose ensemble-based DBSCAN clustering algorithm, resulting in 13.1-26.3% more high-quality genomes than the second best binner for long-read data.

AVAILABILITY AND IMPLEMENTATION

SemiBin2 is available as open source software at https://github.com/BigDataBiology/SemiBin/ and the analysis scripts used in the study can be found at https://github.com/BigDataBiology/SemiBin2_benchmark.

A genome catalog of the early-life human skin microbiome

Metagenome-assembled genomes have greatly expanded the reference genomes for skin microbiome. However, the current reference genomes are largely based on samples from adults in North America and lack representation from infants and individuals from other continents. Here we used ultra-deep shotgun metagenomic sequencing to profile the skin microbiota of 215 infants at age 2-3 months and 12 months who were part of the VITALITY trial in Australia as well as 67 maternally-matched samples. Based on the infant samples, we present the Early-Life Skin Genomes (ELSG) catalog, comprising 9,194 bacterial genomes from 1,029 species, 206 fungal genomes from 13 species, and 39 eukaryotic viral sequences. This genome catalog substantially expands the diversity of species previously known to comprise human skin microbiome and improves the classification rate of sequenced data by 25%. The protein catalog derived from these genomes provides insights into the functional elements such as defense mechanisms that distinguish early-life skin microbiome. We also found evidence for vertical transmission at the microbial community, individual skin bacterial species and strain levels between mothers and infants. Overall, the ELSG catalog uncovers the skin microbiome of a previously underrepresented age group and population and provides a comprehensive view of human skin microbiome diversity, function, and transmission in early life.

Exploring Bifidobacterium species community and functional variations with human gut microbiome structure and health beyond infancy

Aim: The human gut Bifidobacterium community has been studied in detail in infants and following dietary interventions in adults. However, the variability of the distribution of Bifidobacterium species and intra-species functions have been little studied, particularly beyond infancy. Here, we explore the ecology of Bifidobacterium communities in a large public dataset of human gut metagenomes, mostly corresponding to adults. Methods: We selected 9.515 unique gut metagenomes from curatedMetagenomicData. Samples were partitioned by applying Dirichlet's multinomial mixture to Bifidobacterium species. A functional analysis was performed on > 2.000 human-associated Bifidobacterium metagenome-assembled genomes (MAGs) paired with participant gut microbiome and health features. Results: We identified several Bifidobacterium-based partitions in the human gut microbiome differing in terms of the presence and abundance of Bifidobacterium species. The partitions enriched in both B. longum and B. adolescentis were associated with gut microbiome diversity and a higher abundance of butyrate producers and were more prevalent in healthy individuals. B. bifidum MAGs harboring a set of genes potentially related to phages were more prevalent in partitions associated with a lower gut microbiome diversity and were genetically more closely related. Conclusion: This study expands our knowledge of the ecology and variability of the Bifidobacterium community, particularly in adults, and its specific association with the gut microbiota and health. Its findings may guide the rational selection of Bifidobacterium strains for gut microbiome complementation according to the individual's endogenous Bifidobacterium community. Our results also suggest that gut microbiome stratification for particular genera may be relevant for studies of variations of species and associations with the gut microbiome and health.

Role of human milk oligosaccharide metabolizing bacteria in the development of atopic dermatitis/eczema

Despite affecting up to 20% of infants in the United States, there is no cure for atopic dermatitis (AD), also known as eczema. Atopy usually manifests during the first six months of an infant's life and is one predictor of later allergic health problems. A diet of human milk may offer protection against developing atopic dermatitis. One milk component, human milk oligosaccharides (HMOs), plays an important role as a prebiotic in establishing the infant gut microbiome and has immunomodulatory effects on the infant immune system. The purpose of this review is to summarize the available information about bacterial members of the intestinal microbiota capable of metabolizing HMOs, the bacterial genes or metabolic products present in the intestinal tract during early life, and the relationship of these genes and metabolic products to the development of AD/eczema in infants. We find that specific HMO metabolism gene sets and the metabolites produced by HMO metabolizing bacteria may enable the protective role of human milk against the development of atopy because of interactions with the immune system. We also identify areas for additional research to further elucidate the relationship between the human milk metabolizing bacteria and atopy. Detailed metagenomic studies of the infant gut microbiota and its associated metabolomes are essential for characterizing the potential impact of human milk-feeding on the development of atopic dermatitis.

Deduplication Improves Cost-Efficiency and Yields of De Novo Assembly and Binning of Shotgun Metagenomes in Microbiome Research

In the last decade, metagenomics has greatly revolutionized the study of microbial communities. However, the presence of artificial duplicate reads raised mainly from the preparation of metagenomic DNA sequencing libraries and their impacts on metagenomic assembly and binning have never been brought to attention. Here, we explicitly investigated the effects of duplicate reads on metagenomic assemblies and binning based on analyses of five groups of representative metagenomes with distinct microbiome complexities. Our results showed that deduplication considerably increased the binning yields (by 3.5% to 80%) for most of the metagenomic data sets examined thanks to the improved contig length and coverage profiling of metagenome-assembled contigs, whereas it slightly decreased the binning yields of metagenomes with low complexity (e.g., human gut metagenomes). Specifically, 411 versus 397, 331 versus 317, 104 versus 88, and 9 versus 5 metagenome-assembled genomes (MAGs) were recovered from MEGAHIT assemblies of bioreactor sludge, surface water, lake sediment, and forest soil metagenomes, respectively. Noticeably, deduplication significantly reduced the computational costs of the metagenomic assembly, including the elapsed time (9.0% to 29.9%) and the maximum memory requirement (4.3% to 37.1%). Collectively, we recommend the removal of duplicate reads in metagenomes with high complexity before assembly and binning analyses, for example, the forest soil metagenomes examined in this study. IMPORTANCE Duplicated reads in shotgun metagenomes are usually considered technical artifacts. Their presence in metagenomes would theoretically not only introduce bias into the quantitative analysis but also result in mistakes in the coverage profile, leading to adverse effects on or even failures in metagenomic assembly and binning, as the widely used metagenome assemblers and binners all need coverage information for graph partitioning and assembly binning, respectively. However, this issue was seldom noticed, and its impacts on downstream essential bioinformatic procedures (e.g., assembly and binning) remained unclear. In this study, we comprehensively evaluated for the first time the implications of duplicate reads for the de novo assembly and binning of real metagenomic data sets by comparing the assembly qualities, binning yields, and requirements for computational resources with and without the removal of duplicate reads. It was revealed that deduplication considerably increased the binning yields of metagenomes with high complexity and significantly reduced the computational costs, including the elapsed time and the maximum memory requirement, for most of the metagenomes studied. These results provide empirical references for more cost-efficient metagenomic analyses in microbiome research.

Gut microbiome function and composition in infants from rural Kenya and association with human milk oligosaccharides

The gut microbiota evolves rapidly after birth, responding dynamically to environmental factors and playing a key role in short- and long-term health. Lifestyle and rurality have been shown to contribute to differences in the gut microbiome, including Bifidobacterium levels, between infants. We studied the composition, function and variability of the gut microbiomes of 6- to 11-month-old Kenyan infants (n = 105). Shotgun metagenomics showed Bifidobacterium longum to be the dominant species. A pangenomic analysis of B. longum in gut metagenomes revealed a high prevalence of B. longum subsp. infantis (B. infantis) in Kenyan infants (80%), and possible co-existence of this subspecies with B. longum subsp. longum. Stratification of the gut microbiome into community (GMC) types revealed differences in composition and functional features. GMC types with a higher prevalence of B. infantis and abundance of B. breve also had a lower pH and a lower abundance of genes encoding pathogenic features. An analysis of human milk oligosaccharides (HMOs) classified the human milk (HM) samples into four groups defined on the basis of secretor and Lewis polymorphisms revealed a higher prevalence of HM group III (Se+, Le-) (22%) than in most previously studied populations, with an enrichment in 2'-fucosyllactose. Our results show that the gut microbiome of partially breastfed Kenyan infants over the age of six months is enriched in bacteria from the Bifidobacterium community, including B. infantis, and that the high prevalence of a specific HM group may indicate a specific HMO-gut microbiome association. This study sheds light on gut microbiome variation in an understudied population with limited exposure to modern microbiome-altering factors.

Translating neonatal microbiome science into commercial innovation: metabolism of human milk oligosaccharides as a basis for probiotic efficacy in breast-fed infants

For over a century, physicians have witnessed a common enrichment of bifidobacteria in the feces of breast-fed infants that was readily associated with infant health status. Recent advances in bacterial genomics, metagenomics, and glycomics have helped explain the nature of this unique enrichment and enabled the tailored use of probiotic supplementation to restore missing bifidobacterial functions in at-risk infants. This review documents a 20-year span of discoveries that set the stage for the current use of human milk oligosaccharide-consuming bifidobacteria to beneficially colonize, modulate, and protect the intestines of at-risk, human milk-fed, neonates. This review also presents a model for probiotic applications wherein bifidobacterial functions, in the form of colonization and HMO-related catabolic activity in situ, represent measurable metabolic outcomes by which probiotic efficacy can be scored toward improving infant health.

New research frontiers pertaining to the infant gut microbiota

The human gut microbiota is believed to be responsible for multiple health-impacting host effects. The influence of gut microorganisms on the human host begins immediately after birth, having long-lasting health effects, while the gut microbiota itself continues to develop throughout the host's entire life. The purported health-associated effects of the gut microbiota have fueled extensive and ongoing research efforts. Nonetheless, the precise mode of action of functionalities exerted by microbial colonizers of the infant intestine is still largely unknown. The current perspective intends to illustrate major future investigative directions concerning the human gut microbiota with a specific focus on infant-associated gut microbes.