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The indigenous human microbiota is essential to the health of the host. Although the microbiota can be affected by many features of modern life, we know little about its responses to disturbance, especially repeated disturbances, and how these changes compare with baseline temporal variation. We examined the distal gut microbiota of three individuals over 10 mo that spanned two courses of the antibiotic ciprofloxacin, analyzing more than 1.7 million bacterial 16S rRNA hypervariable region sequences from 52 to 56 samples per subject. Interindividual variation was the major source of variability between samples. Day-to-day temporal variability was evident but constrained around an average community composition that was stable over several months in the absence of deliberate perturbation. The effect of ciprofloxacin on the gut microbiota was profound and rapid, with a loss of diversity and a shift in community composition occurring within 3-4 d of drug initiation. By 1 wk after the end of each course, communities began to return to their initial state, but the return was often incomplete. Although broadly similar, community changes after ciprofloxacin varied among subjects and between the two courses within subjects. In all subjects, the composition of the gut microbiota stabilized by the end of the experiment but was altered from its initial state. As with other ecosystems, the human distal gut microbiome at baseline is a dynamic regimen with a stable average state. Antibiotic perturbation may cause a shift to an alternative stable state, the full consequences of which remain unknown.

Understanding how microbial communities develop is essential for predicting and directing their future states. Ecological theory suggests that community development is often influenced by priority effects, in which the order and timing of species arrival determine how species affect one another. Priority effects can have long-lasting consequences, particularly if species arrival history varies during the early stage of community development, but their importance to the human gut microbiota and host health remains largely unknown. Here, we explore how priority effects might influence microbial communities in the gastrointestinal tract during early childhood and how the strength of priority effects can be estimated from the composition of the microbial species pool. We also discuss factors that alter microbial transmission, such as delivery mode, diet and parenting behaviours such as breastfeeding, which can influence the likelihood of priority effects. An improved knowledge of priority effects has the potential to inform microorganism-based therapies, such as prebiotics and probiotics, which are aimed at guiding the microbiota towards a healthy state.

Background The accuracy of microbial community surveys based on marker-gene and metagenomic sequencing (MGS) suffers from the presence of contaminants—DNA sequences not truly present in the sample. Contaminants come from various sources, including reagents. Appropriate laboratory practices can reduce contamination, but do not eliminate it. Here we introduce decontam ( https://github.com/benjjneb/decontam ), an open-source R package that implements a statistical classification procedure that identifies contaminants in MGS data based on two widely reproduced patterns: contaminants appear at higher frequencies in low-concentration samples and are often found in negative controls. Results Decontam classified amplicon sequence variants (ASVs) in a human oral dataset consistently with prior microscopic observations of the microbial taxa inhabiting that environment and previous reports of contaminant taxa. In metagenomics and marker-gene measurements of a dilution series, decontam substantially reduced technical variation arising from different sequencing protocols. The application of decontam to two recently published datasets corroborated and extended their conclusions that little evidence existed for an indigenous placenta microbiome and that some low-frequency taxa seemingly associated with preterm birth were contaminants. Conclusions Decontam improves the quality of metagenomic and marker-gene sequencing by identifying and removing contaminant DNA sequences. Decontam integrates easily with existing MGS workflows and allows researchers to generate more accurate profiles of microbial communities at little to no additional cost.

Our current understanding of the composition and stability of the human distal gut microbiota is based largely on studies of infants and adults living in developed countries. In contrast, little is known about the gut microbiota and its variation over time in older children and adolescents, especially in developing countries. We compared the diversity, composition, and temporal stability of the fecal microbiota of healthy children, ages 9 to 14 years, living in an urban slum in Bangladesh with that of children of the same age range in an upper-middle class suburban community in the United States. We analyzed >8,000 near full-length 16S rRNA gene sequences and over 845,000 pyrosequencing reads of the 16S rRNA V1-V3 region. The distal gut of Bangladeshi children harbored significantly greater bacterial diversity than that of U.S. children, including novel lineages from several bacterial phyla. Bangladeshi and U.S. children had distinct fecal bacterial community membership and structure; the microbiota of Bangladeshi children was enriched in Prevotella, Butyrivibrio, and Oscillospira and depleted in Bacteroides relative to U.S. children (although similar to Bangladeshi adults). Furthermore, community membership and structure in Bangladeshi children was significantly less stable month-to-month than U.S. children. Together, these results suggest that differing environmental or genetic factors may shape the microbiota of healthy children in the two countries. Further investigation is necessary to understand the mechanisms and factors that underlie these differences, and to incorporate these findings into new strategies for the prevention and treatment of childhood and adolescent diseases.

The spatiotemporal structure of the human microbiome 1 , 2 , proteome 3 and metabolome 4 , 5 reflects and determines regional intestinal physiology and may have implications for disease 6 . Yet, little is known about the distribution of microorganisms, their environment and their biochemical activity in the gut because of reliance on stool samples and limited access to only some regions of the gut using endoscopy in fasting or sedated individuals 7 . To address these deficiencies, we developed an ingestible device that collects samples from multiple regions of the human intestinal tract during normal digestion. Collection of 240 intestinal samples from 15 healthy individuals using the device and subsequent multi-omics analyses identified significant differences between bacteria, phages, host proteins and metabolites in the intestines versus stool. Certain microbial taxa were differentially enriched and prophage induction was more prevalent in the intestines than in stool. The host proteome and bile acid profiles varied along the intestines and were highly distinct from those of stool. Correlations between gradients in bile acid concentrations and microbial abundance predicted species that altered the bile acid pool through deconjugation. Furthermore, microbially conjugated bile acid concentrations exhibited amino acid-dependent trends that were not apparent in stool. Overall, non-invasive, longitudinal profiling of microorganisms, proteins and bile acids along the intestinal tract under physiological conditions can help elucidate the roles of the gut microbiome and metabolome in human physiology and disease. Variations in microbial composition, phage induction, antimicrobial resistance genes and bile acid profiles are identified by using an ingestible device for site-specific sampling along the intestines.

The microbial communities of humans are characteristic and complex mixtures of microorganisms that have co-evolved with their human hosts. The species that make up these communities vary between hosts as a result of restricted migration of microorganisms between hosts and strong ecological interactions within hosts, as well as host variability in terms of diet, genotype and colonization history. The shared evolutionary fate of humans and their symbiotic bacteria has selected for mutualistic interactions that are essential for human health, and ecological or genetic changes that uncouple this shared fate can result in disease. In this way, looking to ecological and evolutionary principles might provide new strategies for restoring and maintaining human health.

Despite the importance of horizontal gene transfer for rapid bacterial evolution, reliable assignment of mobile genetic elements to their microbial hosts in natural communities such as the human gut microbiota is lacking. We used high-throughput chromosomal conformation capture coupled with probabilistic modelling of experimental noise to resolve 88 strain-level metagenome-assembled genomes of distal gut bacteria from two participants, including 12,251 accessory elements. Comparisons of two samples collected 10 years apart for each of the participants revealed extensive in situ exchange of accessory elements as well as evidence of adaptive evolution in core genomes. Accessory elements were predominantly promiscuous and prevalent in the distal gut metagenomes of 218 adult individuals. This research provides a foundation and approach for studying microbial evolution in natural environments. High-throughput chromosomal conformation capture identified changes in the gut microbiome over 10 years, including substantial exchange of accessory elements and adaptive evolution in core genomes.

The human intestinal microbiota is essential to the health of the host and plays a role in nutrition, development, metabolism, pathogen resistance, and regulation of immune responses. Antibiotics may disrupt these coevolved interactions, leading to acute or chronic disease in some individuals. Our understanding of antibiotic-associated disturbance of the microbiota has been limited by the poor sensitivity, inadequate resolution, and significant cost of current research methods. The use of pyrosequencing technology to generate large numbers of 16S rDNA sequence tags circumvents these limitations and has been shown to reveal previously unexplored aspects of the \"rare biosphere.\" We investigated the distal gut bacterial communities of three healthy humans before and after treatment with ciprofloxacin, obtaining more than 7,000 full-length rRNA sequences and over 900,000 pyrosequencing reads from two hypervariable regions of the rRNA gene. A companion paper in PLoS Genetics (see Huse et al., doi: 10.1371/journal.pgen.1000255) shows that the taxonomic information obtained with these methods is concordant. Pyrosequencing of the V6 and V3 variable regions identified 3,300-5,700 taxa that collectively accounted for over 99% of the variable region sequence tags that could be obtained from these samples. Ciprofloxacin treatment influenced the abundance of about a third of the bacterial taxa in the gut, decreasing the taxonomic richness, diversity, and evenness of the community. However, the magnitude of this effect varied among individuals, and some taxa showed interindividual variation in the response to ciprofloxacin. While differences of community composition between individuals were the largest source of variability between samples, we found that two unrelated individuals shared a surprising degree of community similarity. In all three individuals, the taxonomic composition of the community closely resembled its pretreatment state by 4 weeks after the end of treatment, but several taxa failed to recover within 6 months. These pervasive effects of ciprofloxacin on community composition contrast with the reports by participants of normal intestinal function and with prior assumptions of only modest effects of ciprofloxacin on the intestinal microbiota. These observations support the hypothesis of functional redundancy in the human gut microbiota. The rapid return to the pretreatment community composition is indicative of factors promoting community resilience, the nature of which deserves future investigation.

Despite the critical role of the human microbiota in health, our understanding of microbiota compositional dynamics during and after pregnancy is incomplete. We conducted a case-control study of 49 pregnant women, 15 of whom delivered preterm. From 40 of these women, we analyzed bacterial taxonomic composition of 3,767 specimens collected prospectively and weekly during gestation and monthly after delivery from the vagina, distal gut, saliva, and tooth/gum. Linear mixed-effects modeling, medoid-based clustering, and Markov chain modeling were used to analyze community temporal trends, community structure, and vaginal community state transitions. Microbiota community taxonomic composition and diversity remained remarkably stable at all four body sites during pregnancy (P > 0.05 for trends over time). Prevalence of a Lactobacillus-poor vaginal community state type (CST 4) was inversely correlated with gestational age at delivery (P = 0.0039). Risk for preterm birth was more pronounced for subjects with CST 4 accompanied by elevated Gardnerella or Ureaplasma abundances. This finding was validated with a set of 246 vaginal specimens from nine women (four of whom delivered preterm). Most women experienced a postdelivery disturbance in the vaginal community characterized by a decrease in Lactobacillus species and an increase in diverse anaerobes such as Peptoniphilus, Prevotella, and Anaerococcus species. This disturbance was unrelated to gestational age at delivery and persisted for up to 1 y. These findings have important implications for predicting premature labor, a major global health problem, and for understanding the potential impact of a persistent, altered postpartum microbiota on maternal health, including outcomes of pregnancies following short interpregnancy intervals.

Massively parallel pyrosequencing of hypervariable regions from small subunit ribosomal RNA (SSU rRNA) genes can sample a microbial community two or three orders of magnitude more deeply per dollar and per hour than capillary sequencing of full-length SSU rRNA. As with full-length rRNA surveys, each sequence read is a tag surrogate for a single microbe. However, rather than assigning taxonomy by creating gene trees de novo that include all experimental sequences and certain reference taxa, we compare the hypervariable region tags to an extensive database of rRNA sequences and assign taxonomy based on the best match in a Global Alignment for Sequence Taxonomy (GAST) process. The resulting taxonomic census provides information on both composition and diversity of the microbial community. To determine the effectiveness of using only hypervariable region tags for assessing microbial community membership, we compared the taxonomy assigned to the V3 and V6 hypervariable regions with the taxonomy assigned to full-length SSU rRNA sequences isolated from both the human gut and a deep-sea hydrothermal vent. The hypervariable region tags and full-length rRNA sequences provided equivalent taxonomy and measures of relative abundance of microbial communities, even for tags up to 15% divergent from their nearest reference match. The greater sampling depth per dollar afforded by massively parallel pyrosequencing reveals many more members of the \"rare biosphere\" than does capillary sequencing of the full-length gene. In addition, tag sequencing eliminates cloning bias and the sequences are short enough to be completely sequenced in a single read, maximizing the number of organisms sampled in a run while minimizing chimera formation. This technique allows the cost-effective exploration of changes in microbial community structure, including the rare biosphere, over space and time and can be applied immediately to initiatives, such as the Human Microbiome Project.