Elizabeth K. Costello

QIIME allows analysis of high-throughput community sequencing data

Supplementary Figure 1 Overview of the analysis pipeline. Supplementary Table 1 Details of conventionally raised and conventionalized mouse samples. Supplementary Discussion Expanded discussion of QIIME analyses presented in the main text; Sequencing of 16S rRNA gene amplicons; QIIME analysis notes; Expanded Figure 1 legend; Links to raw data and processed output from the runs with and without denoising.

Delivery mode shapes the acquisition and structure of the initial microbiota across multiple body habitats in newborns

Upon delivery, the neonate is exposed for the first time to a wide array of microbes from a variety of sources, including maternal bacteria. Although prior studies have suggested that delivery mode shapes the microbiotas establishment and, subsequently, its role in child health, most researchers have focused on specific bacterial taxa or on a single body habitat, the gut. Thus, the initiation stage of human microbiome development remains obscure. The goal of the present study was to obtain a community-wide perspective on the influence of delivery mode and body habitat on the neonates first microbiota. We used multiplexed 16S rRNA gene pyrosequencing to characterize bacterial communities from mothers and their newborn babies, four born vaginally and six born via Cesarean section. Mothers’ skin, oral mucosa, and vagina were sampled 1 h before delivery, and neonates’ skin, oral mucosa, and nasopharyngeal aspirate were sampled <5 min, and meconium <24 h, after delivery. We found that in direct contrast to the highly differentiated communities of their mothers, neonates harbored bacterial communities that were undifferentiated across multiple body habitats, regardless of delivery mode. Our results also show that vaginally delivered infants acquired bacterial communities resembling their own mothers vaginal microbiota, dominated by Lactobacillus, Prevotella, or Sneathia spp., and C-section infants harbored bacterial communities similar to those found on the skin surface, dominated by Staphylococcus, Corynebacterium, and Propionibacterium spp. These findings establish an important baseline for studies tracking the human microbiomes successional development in different body habitats following different delivery modes, and their associated effects on infant health.

Bacterial Community Variation in Human Body Habitats Across Space and Time

Growing on You The human gut and skin harbor diverse microbial communities that are known to vary strikingly among individuals. Here, Costello et al. (p. 1694, published online 5 November) analyzed microbial diversity among several distinct body habitats (including the gut, mouth, inside the ears and nose, and skin) of the same person at different times. They found that body habitat had more influence on microbial community composition than temporal differences and variation among people. Some skin locations, such as the index finger, back of the knee, and sole of the foot, on occasion harbored higher microbial diversity than the gut or oral cavity. The composition of microbial communities on the human body is primarily determined by their location. Elucidating the biogeography of bacterial communities on the human body is critical for establishing healthy baselines from which to detect differences associated with diseases. To obtain an integrated view of the spatial and temporal distribution of the human microbiota, we surveyed bacteria from up to 27 sites in seven to nine healthy adults on four occasions. We found that community composition was determined primarily by body habitat. Within habitats, interpersonal variability was high, whereas individuals exhibited minimal temporal variability. Several skin locations harbored more diverse communities than the gut and mouth, and skin locations differed in their community assembly patterns. These results indicate that our microbiota, although personalized, varies systematically across body habitats and time; such trends may ultimately reveal how microbiome changes cause or prevent disease.

The Application of Ecological Theory Toward an Understanding of the Human Microbiome

The human-microbial ecosystem plays a variety of important roles in human health and disease. Each person can be viewed as an island-like “patch” of habitat occupied by microbial assemblages formed by the fundamental processes of community ecology: dispersal, local diversification, environmental selection, and ecological drift. Community assembly theory, and metacommunity theory in particular, provides a framework for understanding the ecological dynamics of the human microbiome, such as compositional variability within and between hosts. We explore three core scenarios of human microbiome assembly: development in infants, representing assembly in previously unoccupied habitats; recovery from antibiotics, representing assembly after disturbance; and invasion by pathogens, representing assembly in the context of invasive species. Judicious application of ecological theory may lead to improved strategies for restoring and maintaining the microbiota and the crucial health-associated ecosystem services that it provides.

Moving pictures of the human microbiome

BackgroundUnderstanding the normal temporal variation in the human microbiome is critical to developing treatments for putative microbiome-related afflictions such as obesity, Crohns disease, inflammatory bowel disease and malnutrition. Sequencing and computational technologies, however, have been a limiting factor in performing dense time series analysis of the human microbiome. Here, we present the largest human microbiota time series analysis to date, covering two individuals at four body sites over 396 timepoints.ResultsWe find that despite stable differences between body sites and individuals, there is pronounced variability in an individuals microbiota across months, weeks and even days. Additionally, only a small fraction of the total taxa found within a single body site appear to be present across all time points, suggesting that no core temporal microbiome exists at high abundance (although some microbes may be present but drop below the detection threshold). Many more taxa appear to be persistent but non-permanent community members.ConclusionsDNA sequencing and computational advances described here provide the ability to go beyond infrequent snapshots of our human-associated microbial ecology to high-resolution assessments of temporal variations over protracted periods, within and between body habitats and individuals. This capacity will allow us to define normal variation and pathologic states, and assess responses to therapeutic interventions.

Forensic identification using skin bacterial communities

Recent work has demonstrated that the diversity of skin-associated bacterial communities is far higher than previously recognized, with a high degree of interindividual variability in the composition of bacterial communities. Given that skin bacterial communities are personalized, we hypothesized that we could use the residual skin bacteria left on objects for forensic identification, matching the bacteria on the object to the skin-associated bacteria of the individual who touched the object. Here we describe a series of studies de-monstrating the validity of this approach. We show that skin-associated bacteria can be readily recovered from surfaces (including single computer keys and computer mice) and that the structure of these communities can be used to differentiate objects handled by different individuals, even if those objects have been left untouched for up to 2 weeks at room temperature. Furthermore, we demonstrate that we can use a high-throughput pyrosequencing-based ap-proach to quantitatively compare the bacterial communities on objects and skin to match the object to the individual with a high degree of certainty. Although additional work is needed to further establish the utility of this approach, this series of studies introduces a forensics approach that could eventually be used to independently evaluate results obtained using more traditional forensic practices.

Cohabiting family members share microbiota with one another and with their dogs.

Human-associated microbial communities vary across individuals: possible contributing factors include (genetic) relatedness, diet, and age. However, our surroundings, including individuals with whom we interact, also likely shape our microbial communities. To quantify this microbial exchange, we surveyed fecal, oral, and skin microbiota from 60 families (spousal units with children, dogs, both, or neither). Household members, particularly couples, shared more of their microbiota than individuals from different households, with stronger effects of co-habitation on skin than oral or fecal microbiota. Dog ownership significantly increased the shared skin microbiota in cohabiting adults, and dog-owning adults shared more ‘skin’ microbiota with their own dogs than with other dogs. Although the degree to which these shared microbes have a true niche on the human body, vs transient detection after direct contact, is unknown, these results suggest that direct and frequent contact with our cohabitants may significantly shape the composition of our microbial communities. DOI: http://dx.doi.org/10.7554/eLife.00458.001

Time series community genomics analysis reveals rapid shifts in bacterial species, strains, and phage during infant gut colonization

The gastrointestinal microbiome undergoes shifts in species and strain abundances, yet dynamics involving closely related microorganisms remain largely unknown because most methods cannot resolve them. We developed new metagenomic methods and utilized them to track species and strain level variations in microbial communities in 11 fecal samples collected from a premature infant during the first month of life. Ninety six percent of the sequencing reads were assembled into scaffolds of >500 bp in length that could be assigned to organisms at the strain level. Six essentially complete (∼99%) and two near-complete genomes were assembled for bacteria that comprised as little as 1% of the community, as well as nine partial genomes of bacteria representing as little as 0.05%. In addition, three viral genomes were assembled and assigned to their hosts. The relative abundance of three Staphylococcus epidermidis strains, as well as three phages that infect them, changed dramatically over time. Genes possibly related to these shifts include those for resistance to antibiotics, heavy metals, and phage. At the species level, we observed the decline of an early-colonizing Propionibacterium acnes strain similar to SK137 and the proliferation of novel Propionibacterium and Peptoniphilus species late in colonization. The Propionibacterium species differed in their ability to metabolize carbon compounds such as inositol and sialic acid, indicating that shifts in species composition likely impact the metabolic potential of the community. These results highlight the benefit of reconstructing complete genomes from metagenomic data and demonstrate methods for achieving this goal.

Global patterns in the biogeography of bacterial taxa.

Bacteria control major nutrient cycles and directly influence plant, animal and human health. However, we know relatively little about the forces shaping their large-scale ecological ranges. Here, we reveal patterns in the distribution of individual bacterial taxa at multiple levels of phylogenetic resolution within and between Earths major habitat types. Our analyses suggest that while macro-scale habitats structure bacterial distribution to some degree, abundant bacteria (i.e. detectable using 16S rRNA gene sequencing methods) are confined to single assemblages. Additionally, we show that the most cosmopolitan taxa are also the most abundant in individual assemblages. These results add to the growing body of data that support that the diversity of the overall bacterial metagenome is tremendous. The mechanisms governing microbial distribution remain poorly understood, but our analyses provide a framework with which to test the importance of macro-ecological environmental gradients, relative abundance, neutral processes and the ecological strategies of individual taxa in structuring microbial communities.

BIOGEOCHEMICAL CONSEQUENCES OF RAPID MICROBIAL TURNOVER AND SEASONAL SUCCESSION IN SOIL

Soil microbial communities have the metabolic and genetic capability to adapt to changing environmental conditions on very short time scales. In this paper we combine biogeochemical and molecular approaches to reveal this potential, showing that microbial biomass can turn over on time scales of days to months in soil, resulting in a succession of microbial communities over the course of a year. This new understanding of the year-round turnover and succession of microbial communities allows us for the first time to propose a temporally explicit N cycle that provides mechanistic hypotheses to explain both the loss and retention of dissolved organic N (DON) and inorganic N (DIN) throughout the year in terrestrial ecosystems. In addition, our results strongly support the hypothesis that turnover of the microbial community is the largest source of DON and DIN for plant uptake during the plant growing season. While this model of microbial biogeochemistry is derived from observed dynamics in the alpine, we present several examples from other ecosystems to indicate that the general ideas of biogeochemical fluxes being linked to turnover and succession of microbial communities are applicable to a wide range of terrestrial ecosystems.