Project description:Vertical transmission of bacteria from mother to infant at birth is postulated to initiate a life-long host-microbe symbiosis, playing an important role in early infant development. However, only the tracking of strictly defined unique microbial strains can clarify where the intestinal bacteria come from, how long the initial colonizers persist, and whether colonization by other strains from the environment can replace existing ones. Using rare single nucleotide variants in fecal metagenomes of infants and their family members, we show strong evidence of selective and persistent transmission of maternal strain populations to the vaginally born infant and their occasional replacement by strains from the environment, including those from family members, in later childhood. Only strains from the classes Actinobacteria and Bacteroidia, which are essential components of the infant microbiome, are transmitted from the mother and persist for at least 1 yr. In contrast, maternal strains of Clostridia, a dominant class in the mother's gut microbiome, are not observed in the infant. Caesarean-born infants show a striking lack of maternal transmission at birth. After the first year, strain influx from the family environment occurs and continues even in adulthood. Fathers appear to be more frequently donors of novel strains to other family members than receivers. Thus, the infant gut is seeded by selected maternal bacteria, which expand to form a stable community, with a rare but stable continuing strain influx over time.
Project description:Antibiotic resistance in pathogens is extensively studied, and yet little is known about how antibiotic resistance genes of typical gut bacteria influence microbiome dynamics. Here, we leveraged genomes from metagenomes to investigate how genes of the premature infant gut resistome correspond to the ability of bacteria to survive under certain environmental and clinical conditions. We found that formula feeding impacts the resistome. Random forest models corroborated by statistical tests revealed that the gut resistome of formula-fed infants is enriched in class D beta-lactamase genes. Interestingly, Clostridium difficile strains harboring this gene are at higher abundance in formula-fed infants than C. difficile strains lacking this gene. Organisms with genes for major facilitator superfamily drug efflux pumps have higher replication rates under all conditions, even in the absence of antibiotic therapy. Using a machine learning approach, we identified genes that are predictive of an organism's direction of change in relative abundance after administration of vancomycin and cephalosporin antibiotics. The most accurate results were obtained by reducing annotated genomic data to five principal components classified by boosted decision trees. Among the genes involved in predicting whether an organism increased in relative abundance after treatment are those that encode subclass B2 beta-lactamases and transcriptional regulators of vancomycin resistance. This demonstrates that machine learning applied to genome-resolved metagenomics data can identify key genes for survival after antibiotics treatment and predict how organisms in the gut microbiome will respond to antibiotic administration. IMPORTANCE The process of reconstructing genomes from environmental sequence data (genome-resolved metagenomics) allows unique insight into microbial systems. We apply this technique to investigate how the antibiotic resistance genes of bacteria affect their ability to flourish in the gut under various conditions. Our analysis reveals that strain-level selection in formula-fed infants drives enrichment of beta-lactamase genes in the gut resistome. Using genomes from metagenomes, we built a machine learning model to predict how organisms in the gut microbial community respond to perturbation by antibiotics. This may eventually have clinical applications.
Project description:Commensal gut bacterial communities (microbiomes) are predicted to influence human health and disease1,2. Neonatal gut microbiomes are colonized with maternal and environmental flora and mature toward a stable composition over?2-3 years3,4. To study pre- and postnatal determinants of infant microbiome development, we analyzed 402 fecal metagenomes from 60 infants aged 0-8?months, using longitudinal generalized linear mixed models (GLMMs). Distinct microbiome signatures correlated with breastfeeding, formula ingredients, and maternal gestational weight gain (GWG). Amino acid synthesis pathway accretion in breastfed microbiomes complemented normative breastmilk composition. Prebiotic oligosaccharides, designed to promote breastfed-like microflora5, predicted functional pathways distinct from breastfed infant microbiomes. Soy formula in six infants was positively associated with Lachnospiraceae and pathways suggesting a short-chain fatty acid (SCFA)-rich environment, including glycerol to 1-butanol fermentation, which is potentially dysbiotic. GWG correlated with altered carbohydrate degradation and enriched vitamin synthesis pathways. Maternal and postnatal antibiotics predicted microbiome alterations, while delivery route had no persistent effects. Domestic water source correlates suggest water may be an underappreciated determinant of microbiome acquisition. Clinically important microbial pathways with statistically significant dietary correlates included dysbiotic markers6,7, core enterotype features8, and synthesis pathways for enteroprotective9 and immunomodulatory10,11 metabolites, epigenetic mediators1, and developmentally critical vitamins12, warranting further investigation.
Project description:Bacteriophages (phages) dramatically shape microbial community composition, redistribute nutrients via host lysis and drive evolution through horizontal gene transfer. Despite their importance, much remains to be learned about phages in the human microbiome. We investigated the gut microbiomes of humans from Bangladesh and Tanzania, two African baboon social groups and Danish pigs; many of these microbiomes contain phages belonging to a clade with genomes?>540?kilobases in length, the largest yet reported in the human microbiome and close to the maximum size ever reported for phages. We refer to these as Lak phages. CRISPR spacer targeting indicates that Lak phages infect bacteria of the genus Prevotella. We manually curated to completion 15 distinct Lak phage genomes recovered from metagenomes. The genomes display several interesting features, including use of an alternative genetic code, large intergenic regions that are highly expressed and up to 35 putative transfer RNAs, some of which contain enigmatic introns. Different individuals have distinct phage genotypes, and shifts in variant frequencies over consecutive sampling days reflect changes in the relative abundance of phage subpopulations. Recent homologous recombination has resulted in extensive genome admixture of nine baboon Lak phage populations. We infer that Lak phages are widespread in gut communities that contain the Prevotella species, and conclude that megaphages, with fascinating and underexplored biology, may be common but largely overlooked components of human and animal gut microbiomes.
Project description:The body-wide human microbiome plays a role in health, but its full diversity remains uncharacterized, particularly outside of the gut and in international populations. We leveraged 9,428 metagenomes to reconstruct 154,723 microbial genomes (45% of high quality) spanning body sites, ages, countries, and lifestyles. We recapitulated 4,930 species-level genome bins (SGBs), 77% without genomes in public repositories (unknown SGBs [uSGBs]). uSGBs are prevalent (in 93% of well-assembled samples), expand underrepresented phyla, and are enriched in non-Westernized populations (40% of the total SGBs). We annotated 2.85 M genes in SGBs, many associated with conditions including infant development (94,000) or Westernization (106,000). SGBs and uSGBs permit deeper microbiome analyses and increase the average mappability of metagenomic reads from 67.76% to 87.51% in the gut (median 94.26%) and 65.14% to 82.34% in the mouth. We thus identify thousands of microbial genomes from yet-to-be-named species, expand the pangenomes of human-associated microbes, and allow better exploitation of metagenomic technologies.
Project description:BACKGROUND: The source inoculum of gastrointestinal tract (GIT) microbes is largely influenced by delivery mode in full-term infants, but these influences may be decoupled in very low birth weight (VLBW, <1,500 g) neonates via conventional broad-spectrum antibiotic treatment. We hypothesize the built environment (BE), specifically room surfaces frequently touched by humans, is a predominant source of colonizing microbes in the gut of premature VLBW infants. Here, we present the first matched fecal-BE time series analysis of two preterm VLBW neonates housed in a neonatal intensive care unit (NICU) over the first month of life. RESULTS: Fresh fecal samples were collected every 3 days and metagenomes sequenced on an Illumina HiSeq2000 device. For each fecal sample, approximately 33 swabs were collected from each NICU room from 6 specified areas: sink, feeding and intubation tubing, hands of healthcare providers and parents, general surfaces, and nurse station electronics (keyboard, mouse, and cell phone). Swabs were processed using a recently developed 'expectation maximization iterative reconstruction of genes from the environment' (EMIRGE) amplicon pipeline in which full-length 16S rRNA amplicons were sheared and sequenced using an Illumina platform, and short reads reassembled into full-length genes. Over 24,000 full-length 16S rRNA sequences were produced, generating an average of approximately 12,000 operational taxonomic units (OTUs) (clustered at 97% nucleotide identity) per room-infant pair. Dominant gut taxa, including Staphylococcus epidermidis, Klebsiella pneumoniae, Bacteroides fragilis, and Escherichia coli, were widely distributed throughout the room environment with many gut colonizers detected in more than half of samples. Reconstructed genomes from infant gut colonizers revealed a suite of genes that confer resistance to antibiotics (for example, tetracycline, fluoroquinolone, and aminoglycoside) and sterilizing agents, which likely offer a competitive advantage in the NICU environment. CONCLUSIONS: We have developed a high-throughput culture-independent approach that integrates room surveys based on full-length 16S rRNA gene sequences with metagenomic analysis of fecal samples collected from infants in the room. The approach enabled identification of discrete ICU reservoirs of microbes that also colonized the infant gut and provided evidence for the presence of certain organisms in the room prior to their detection in the gut.
Project description:Type 1 diabetes (T1D) is an autoimmune disease that targets pancreatic islet beta cells and incorporates genetic and environmental factors1, including complex genetic elements2, patient exposures3 and the gut microbiome4. Viral infections5 and broader gut dysbioses6 have been identified as potential causes or contributing factors; however, human studies have not yet identified microbial compositional or functional triggers that are predictive of islet autoimmunity or T1D. Here we analyse 10,913 metagenomes in stool samples from 783 mostly white, non-Hispanic children. The samples were collected monthly from three months of age until the clinical end point (islet autoimmunity or T1D) in the The Environmental Determinants of Diabetes in the Young (TEDDY) study, to characterize the natural history of the early gut microbiome in connection to islet autoimmunity, T1D diagnosis, and other common early life events such as antibiotic treatments and probiotics. The microbiomes of control children contained more genes that were related to fermentation and the biosynthesis of short-chain fatty acids, but these were not consistently associated with particular taxa across geographically diverse clinical centres, suggesting that microbial factors associated with T1D are taxonomically diffuse but functionally more coherent. When we investigated the broader establishment and development of the infant microbiome, both taxonomic and functional profiles were dynamic and highly individualized, and dominated in the first year of life by one of three largely exclusive Bifidobacterium species (B. bifidum, B. breve or B. longum) or by the phylum Proteobacteria. In particular, the strain-specific carriage of genes for the utilization of human milk oligosaccharide within a subset of B. longum was present specifically in breast-fed infants. These analyses of TEDDY gut metagenomes provide, to our knowledge, the largest and most detailed longitudinal functional profile of the developing gut microbiome in relation to islet autoimmunity, T1D and other early childhood events. Together with existing evidence from human cohorts7,8 and a T1D mouse model9, these data support the protective effects of short-chain fatty acids in early-onset human T1D.
Project description:BACKGROUND:Early disruption of the microbial community may influence life-long health. Environmental toxicants can contaminate breast milk and the developing infant gut microbiome is directly exposed. We investigated whether environmental toxicants in breastmilk affect the composition and function of the infant gut microbiome at 1 month. We measured environmental toxicants in breastmilk, fecal short-chain fatty acids (SCFAs), and gut microbial composition from 16S rRNA gene amplicon sequencing using samples from 267 mother-child pairs in the Norwegian Microbiota Cohort (NoMIC). We tested 28 chemical exposures: polychlorinated biphenyls (PCBs), polybrominated flame retardants (PBDEs), per- and polyfluoroalkyl substances (PFASs), and organochlorine pesticides. We assessed chemical exposure and alpha diversity/SCFAs using elastic net regression modeling and generalized linear models, adjusting for confounders, and variation in beta diversity (UniFrac), taxa abundance (ANCOM), and predicted metagenomes (PiCRUSt) in low, medium, and high exposed groups. RESULTS:PBDE-28 and the surfactant perfluorooctanesulfonic acid (PFOS) were associated with less microbiome diversity. Some sub-OTUs of Lactobacillus, an important genus in early life, were lower in abundance in samples from infants with relative "high" (>?80th percentile) vs. "low" (<?20th percentile) toxicant exposure in this cohort. Moreover, breast milk toxicants were associated with microbiome functionality, explaining up to 34% of variance in acetic and propionic SCFAs, essential signaling molecules. Per one standard deviation of exposure, PBDE-28 was associated with less propionic acid (-?24% [95% CI -?35% to -?14%] relative to the mean), and PCB-209 with less acetic acid (-?15% [95% CI -?29% to -?0.4%]). Conversely, PFOA and dioxin-like PCB-167 were associated with 61% (95% CI 35% to 87%) and 22% (95% CI 8% to 35%) more propionic and acetic acid, respectively. CONCLUSIONS:Environmental toxicant exposure may influence infant gut microbial function during a critical developmental window. Future studies are needed to replicate these novel findings and investigate whether this has any impact on child health.
Project description:The spread of antibiotic resistance, originating from the rampant and unrestrictive use of antibiotics in humans and livestock over the past few decades has emerged as a global health problem. This problem has been further compounded by recent reports implicating the gut microbial communities to act as reservoirs of antibiotic resistance. We have profiled the presence of probable antibiotic resistance genes in the gut flora of 275 individuals from eight different nationalities. For this purpose, available metagenomic data sets corresponding to 275 gut microbiomes were analyzed. Sequence similarity searches of the genomic fragments constituting each of these metagenomes were performed against genes conferring resistance to around 240 antibiotics. Potential antibiotic resistance genes conferring resistance against 53 different antibiotics were detected in the human gut microflora analysed in this study. In addition to several geography/country-specific patterns, four distinct clusters of gut microbiomes, referred to as 'Resistotypes', exhibiting similarities in their antibiotic resistance profiles, were identified. Groups of antibiotics having similarities in their resistance patterns within each of these clusters were also detected. Apart from this, mobile multi-drug resistance gene operons were detected in certain gut microbiomes. The study highlighted an alarmingly high abundance of antibiotic resistance genes in two infant gut microbiomes. The results obtained in the present study presents a holistic 'big picture' on the spectra of antibiotic resistance within our gut microbiota across different geographies. Such insights may help in implementation of new regulations and stringency on the existing ones.
Project description:We evaluated the relationship of drinking water salinity to neonatal and infant mortality using Bangladesh Demographic Health Surveys of 2000, 2004, 2007, 2011, and 2014. Point data of groundwater electrical conductivity (EC)- a measure of salinity-were collated from the Bangladesh Water Development Board and digitizing salinity contour map. Data for groundwater dissolved elements (sodium, calcium, magnesium, and potassium) data came from a national hydrochemistry survey in Bangladesh. Point EC and dissolved minerals data were then interpolated over entire Bangladesh and extracted to each cluster location, the primary sampling unit of Bangladesh Demographic Health Surveys. We used restricted cubic splines and survey design-specific logistic regression models to determine the relationship of water salinity to neonatal and infant mortality. A U-shaped association between drinking water salinity and neonatal and infant mortality was found, suggesting higher mortality when salinity was very low and high. Compared to mildly saline (EC ?0.7 and < 2 mS/cm) water drinkers, freshwater (EC < 0.7 mS/cm) drinkers had 1.37 (95% CI: 1.01, 1.84) times higher neonatal mortality and 1.43 (95% CI: 1.08, 1.89) times higher infant mortality. Compared to mildly saline water drinkers, severe-saline (EC ?10 mS/cm) water drinkers had 1.77 (95% CI: 1.17, 2.68) times higher neonatal mortality and 1.93 (95% CI: 1.35, 2.76) times higher infant mortality. We found that mild-salinity water had a high concentration of calcium and magnesium, whereas severe-salinity water had a high concentration of sodium. Freshwater had the least concentrations of salubrious calcium and magnesium.