To examine the contributions of impaired gut microbial community development to childhood undernutrition, we combined metabolomic and proteomic analyses of plasma samples with metagenomic analyses of fecal samples to characterize the biological state of Bangladeshi children with severe acute malnutrition (SAM) as they transitioned, after standard treatment, to moderate acute malnutrition (MAM) with persistent microbiota immaturity. Host and microbial effects of microbiota-directed complementary food (MDCF) prototypes targeting weaning-phase bacterial taxa underrepresented in SAM and MAM microbiota were characterized in gnotobiotic mice and gnotobiotic piglets colonized with age- and growth-discriminatory bacteria. A randomized, double-blind controlled feeding study identified a lead MDCF that changes the abundances of targeted bacteria and increases plasma biomarkers and mediators of growth, bone formation, neurodevelopment, and immune function in children with MAM.

Characterizing the organization of the human gut microbiota is a formidable challenge given the number of possible interactions between its components. Using a statistical approach initially applied to financial markets, we measured temporally conserved covariance among bacterial taxa in the microbiota of healthy members of a Bangladeshi birth cohort sampled from 1 to 60 months of age. The results revealed an “ecogroup” of 15 covarying bacterial taxa that provide a concise description of microbiota development in healthy children from this and other low-income countries, and a means for monitoring community repair in undernourished children treated with therapeutic foods. Features of ecogroup population dynamics were recapitulated in gnotobiotic piglets as they transitioned from exclusive milk feeding to a fully weaned state consuming a representative Bangladeshi diet.

Background Detrimental effects of diarrhea on child growth and survival are well documented, but details of the underlying mechanisms remain poorly understood. Recent evidence demonstrates that perturbations to normal development of the gut microbiota in early life may contribute to growth faltering and susceptibility to related childhood diseases. We assessed associations between diarrhea, gut microbiota configuration, and childhood growth in the Peruvian Amazon. Methods Growth, diarrhea incidence, illness, pathogen infection, and antibiotic exposure were assessed monthly in a birth cohort of 271 children aged 0–24 months. Gut bacterial diversity and abundances of specific bacterial taxa were quantified by sequencing 16S rRNA genes in fecal samples collected at 6, 12, 18, and 24 months. Linear and generalized linear models were used to determine whether diarrhea was associated with altered microbiota and, in turn, if features of the microbiota were associated with the subsequent risk of diarrhea. Results Diarrheal frequency, duration, and severity were negatively associated with bacterial diversity and richness (P < .05). Children born stunted (length-for-age z-score [LAZ] ≤ −2) who were also severely stunted (LAZ ≤ −3) at the time of sampling exhibited the greatest degree of diarrhea-associated reductions in bacterial diversity and the slowest recovery of bacterial diversity after episodes of diarrhea. Increased bacterial diversity was predictive of reduced subsequent diarrhea from age 6 to 18 months. Conclusions Persistent, severe growth faltering may reduce the gut microbiota's resistance and resilience to diarrhea, leading to greater losses of diversity and longer recovery times. This phenotype, in turn, denotes an increased risk of future diarrheal disease and growth faltering.

A long-standing challenge in human microbiome research is achieving the taxonomic and functional resolution needed to generate testable hypotheses about the gut microbiota’s impact on health and disease. With a growing number of live microbial interventions in clinical development, this challenge is renewed by a need to understand the pharmacokinetics and pharmacodynamics of therapeutic candidates. While short-read sequencing of the bacterial 16S rRNA gene has been the standard for microbiota profiling, recent improvements in the fidelity of long-read sequencing underscores the need for a re-evaluation of the value of distinct microbiome-sequencing approaches. We leveraged samples from participants enrolled in a phase 1b clinical trial of a novel live biotherapeutic product to perform a comparative analysis of short-read and long-read amplicon and metagenomic sequencing approaches to assess their utility for generating clinical microbiome data. Across all methods, overall community taxonomic profiles were comparable and relationships between samples were conserved. Comparison of ubiquitous short-read 16S rRNA amplicon profiling to long-read profiling of the 16S-ITS-23S rRNA amplicon showed that only the latter provided strain-level community resolution and insight into novel taxa. All methods identified an active ingredient strain in treated study participants, though detection confidence was higher for long-read methods. Read coverage from both metagenomic methods provided evidence of active-ingredient strain replication in some treated participants. Compared to short-read metagenomics, approximately twice the proportion of long reads were assigned functional annotations. Finally, compositionally similar bacterial metagenome-assembled genomes (MAGs) were recovered from short-read and long-read metagenomic methods, although a greater number and more complete MAGs were recovered from long reads. Despite higher costs, both amplicon and metagenomic long-read approaches yielded added microbiome data value in the form of higher confidence taxonomic and functional resolution and improved recovery of microbial genomes compared to traditional short-read methodologies.

A longstanding challenge in human microbiome research is achieving the taxonomic and functional resolution needed to generate testable hypotheses about the gut microbiome's impact on health and disease. More recently, this challenge has extended to a need for in-depth understanding of the pharmacokinetics and pharmacodynamics of clinical microbiome-based interventions. Whole genome metagenomic sequencing provides high taxonomic resolution and information on metagenome functional capacity, but the required deep sequencing is costly. For this reason, short-read sequencing of the bacterial 16S ribosomal RNA (rRNA) gene is the standard for microbiota profiling, despite its poor taxonomic resolution. The recent falling costs and improved fidelity of long-read sequencing warrant an evaluation of this approach for clinical microbiome analysis. We used samples from participants enrolled in a Phase 1b clinical trial of a novel live biotherapeutic product to perform a comparative analysis of short-read and long-read amplicon and metagenomic sequencing approaches to assess their value for generating informative and actionable clinical microbiome data. Comparison of ubiquitous short-read 16S rRNA amplicon profiling to long-read profiling of the 16S-ITS-23S rRNA amplicon showed that only the latter provided strain-level community resolution and insight into novel taxa. Across all methods, overall community taxonomic profiles were comparable and relationships between samples were conserved, highlighting the accuracy of modern microbiome analysis pipelines. All methods identified an active ingredient strain in treated study participants, though detection confidence was higher for long-read methods. Read coverage from both metagenomic methods provided evidence of active ingredient strain replication in some treated participants. Compared to short-read metagenomics, approximately twice the proportion of long reads were assigned functional annotations (63% vs. 34%). Finally, similar bacterial metagenome-assembled genomes (MAGs) were recovered across short-read and long-read metagenomic methods, although MAGs recovered from long reads were more complete. Overall, despite higher costs, long-read microbiome characterization provides added scientific value for clinical microbiome research in the form of higher taxonomic and functional resolution and improved recovery of microbial genomes compared to traditional short-read methodologies.

Traditional metagenome binning methods cluster contiguous DNA sequences (contigs) based on uncontextualized features of the sequences which ignores both the semantic relationship between genes and the positional embedding of k-mers. This thesis presents a novel binning method that addresses these concerns. Firstly, taken from natural language processing literature, a sequence representation model - Bidirectional Encoder Representations from Transformers(BERT) - is utilized to generate semantic and positional contig embeddings. Secondly, two workflows are presented; one which applies a hierarchical density-based clustering algorithm to find metagenomic bins and the other which incorporates contig embedding into a state-of-the-art binner. Experimental results on a publicly available metagenomic dataset show superior clustering for shorter contigs compared to traditionally used tetranucleotide frequency (TNF),reconstruction of up to 17% more high-precision genomes, and improved semantic understanding of contigs.

The human gut microbiota is central to early-life immune system education, including the establishment of immune tolerance, and thus represents an important target for the development of preventative interventions against food allergy (FA). The composition of the gut microbiota, and specific bacterial members within the microbiota, have been shown to impact allergic disease development in animal models by limiting basophil hematopoiesis, influencing macrophage polarization, and enhancing regulatory T cell activity. With a growing body of evidence showing the gut microbiota is an important environmental factor contributing to FA development comes an opportunity to translate this knowledge into novel approaches for treating and preventing FA. Using a proprietary human gut microbiota consortium, we have developed a mixed species live biotherapeutic product (LBP) to alleviate FA development and severity. We show that this LBP can directly interact with human immune cell populations modulating immune signaling pathways including TGF-beta, FFARs, chemotaxis, and NFkB inhibition. We also demonstrate that supplementation with this LBP can reduce OVA induced oral anaphylactic severity in mice with humanized gut microbiota. This protective effect may be attributed to increased fecal antigen-specific IgA levels and enhanced intestinal TGFb levels. These data describe immunological mechanism of a mixed species LBP that is protective in mouse FA model.

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