Human gut microbiomes are known to change with age, yet the relative value of human microbiomes across the body as predictors of age, and prediction robustness across populations is unknown. In this study, we tested the ability of the oral, gut, and skin (hand and forehead) microbiomes to predict age in adults using random forest regression on data combined from multiple publicly available studies, evaluating the models in each cohort individually. Intriguingly, the skin microbiome provides the best prediction of age (mean ± standard deviation, 3.8 ± 0.45 years, versus 4.5 ± 0.14 years for the oral microbiome and 11.5 ± 0.12 years for the gut microbiome). This also agrees with forensic studies showing that the skin microbiome predicts postmortem interval better than microbiomes from other body sites. Age prediction models constructed from the hand microbiome generalized to the forehead and vice versa, across cohorts, and results from the gut microbiome generalized across multiple cohorts (United States, United Kingdom, and China). Interestingly, taxa enriched in young individuals (18 to 30 years) tend to be more abundant and more prevalent than taxa enriched in elderly individuals (>60 yrs), suggesting a model in which physiological aging occurs concomitantly with the loss of key taxa over a lifetime, enabling potential microbiome-targeted therapeutic strategies to prevent aging.IMPORTANCE Considerable evidence suggests that the gut microbiome changes with age or even accelerates aging in adults. Whether the age-related changes in the gut microbiome are more or less prominent than those for other body sites and whether predictions can be made about a person’s age from a microbiome sample remain unknown. We therefore combined several large studies from different countries to determine which body site’s microbiome could most accurately predict age. We found that the skin was the best, on average yielding predictions within 4 years of chronological age. This study sets the stage for future research on the role of the microbiome in accelerating or decelerating the aging process and in the susceptibility for age-related diseases.
The horseshoe effect is a phenomenon that has long intrigued ecologists. The effect was commonly thought to be an artifact of dimensionality reduction, and multiple techniques were developed to unravel this phenomenon and simplify interpretation. Here, we provide evidence that horseshoes arise as a consequence of distance metrics that saturate-a familiar concept in other fields but new to microbial ecology. This saturation property loses information about community dissimilarity, simply because it cannot discriminate between samples that do not share any common features. The phenomenon illuminates niche differentiation in microbial communities and indicates species turnover along environmental gradients. Here we propose a rationale for the observed horseshoe effect from multiple dimensionality reduction techniques applied to simulations, soil samples, and samples from postmortem mice. An in-depth understanding of this phenomenon allows targeting of niche differentiation patterns from high-level ordination plots, which can guide conventional statistical tools to pinpoint microbial niches along environmental gradients. IMPORTANCE The horseshoe effect is often considered an artifact of dimensionality reduction. We show that this is not true in the case for microbiome data and that, in fact, horseshoes can help analysts discover microbial niches across environments.
Recent studies of mammalian microbiomes have identified strong phylogenetic effects on bacterial community composition. Bats (Mammalia: Chiroptera) are among the most speciose mammals on the planet and the only mammal capable of true flight. We examined 1,236 16S rRNA amplicon libraries of the gut, oral, and skin microbiota from 497 Afrotropical bats (representing 9 families, 20 genera, and 31 species) to assess the extent to which host ecology and phylogeny predict microbial community similarity in bats. In contrast to recent studies of host-microbe associations in other mammals, we found no correlation between chiropteran phylogeny and bacterial community dissimilarity across the three anatomical sites sampled. For all anatomical sites, we found host species identity and geographic locality to be strong predictors of microbial community composition and observed a positive correlation between elevation and bacterial richness. Last, we identified significantly different bacterial associations within the gut microbiota of insectivorous and frugivorous bats. We conclude that the gut, oral, and skin microbiota of bats are shaped predominantly by ecological factors and do not exhibit the same degree of phylosymbiosis observed in other mammals.IMPORTANCE This study is the first to provide a comprehensive survey of bacterial symbionts from multiple anatomical sites across a broad taxonomic range of Afrotropical bats, demonstrating significant associations between the bat microbiome and anatomical site, geographic locality, and host identity-but not evolutionary history. This study provides a framework for future systems biology approaches to examine host-symbiont relationships across broad taxonomic scales, emphasizing the need to elucidate the interplay between host ecology and evolutionary history in shaping the microbiome of different anatomical sites.
The pulmonary system is a common site for bacterial infections in cetaceans, but very little is known about their respiratory microbiome. We used a small, unmanned hexacopter to collect exhaled breath condensate (blow) from two geographically distinct populations of apparently healthy humpback whales (Megaptera novaeangliae), sampled in the Massachusetts coastal waters off Cape Cod (n = 17) and coastal waters around Vancouver Island (n = 9). Bacterial and archaeal small-subunit rRNA genes were amplified and sequenced from blow samples, including many of sparse volume, as well as seawater and other controls, to characterize the associated microbial community. The blow microbiomes were distinct from the seawater microbiomes and included 25 phylogenetically diverse bacteria common to all sampled whales. This core assemblage comprised on average 36% of the microbiome, making it one of the more consistent animal microbiomes studied to date. The closest phylogenetic relatives of 20 of these core microbes were previously detected in marine mammals, suggesting that this core microbiome assemblage is specialized for marine mammals and may indicate a healthy, noninfected pulmonary system. Pathogen screening was conducted on the microbiomes at the genus level, which showed that all blow and few seawater microbiomes contained relatives of bacterial pathogens; no known cetacean respiratory pathogens were detected in the blow. Overall, the discovery of a shared large core microbiome in humpback whales is an important advancement for health and disease monitoring of this species and of other large whales. IMPORTANCE The conservation and management of large whales rely in part upon health monitoring of individuals and populations, and methods generally necessitate invasive sampling. Here, we used a small, unmanned hexacopter drone to noninvasively fly above humpback whales from two populations, capture their exhaled breath (blow), and examine the associated microbiome. In the first extensive examination of the large-whale blow microbiome, we present surprising results about the discovery of a large core microbiome that was shared across individual whales from geographically separated populations in two ocean basins. We suggest that this core microbiome, in addition to other microbiome characteristics, could be a useful feature for health monitoring of large whales worldwide.
Distinct microbial communities inhabit individuals as part of the human skin microbiome and are continually shed to the surrounding environment. Microbial communities from 17 skin sites of 10 sexually active cohabiting couples (20 individuals) were sampled to test whether cohabitation impacts an individual’s skin microbiome, leading to shared skin microbiota among partner pairs. Amplified 16S rRNA genes of bacteria and archaea from a total of 340 skin swabs were analyzed by high-throughput sequencing, and the results demonstrated that cohabitation was significantly associated with microbial community composition, although this association was greatly exceeded by characteristics of body location and individuality. Random forest modeling demonstrated that the partners could be predicted 86% of the time (P < 0.001) based on their skin microbiome profiles, which was always greater than combinations of incorrectly matched partners. Cohabiting couples had the most similar overall microbial skin communities on their feet, according to Bray-Curtis distances. In contrast, thigh microbial communities were strongly associated with biological sex rather than cohabiting partner. Additional factors that were associated with the skin microbiome of specific body locations included the use of skin care products, pet ownership, allergies, and alcohol consumption. These baseline data identified links between the skin microbiome and daily interactions among cohabiting individuals, adding to known factors that shape the human microbiome and, by extension, its relation to human health. IMPORTANCE Our work characterizes the influence of cohabitation as a factor influencing the composition of the skin microbiome. Although the body site and sampled individual were stronger influences than other factors collected as metadata in this study, we show that modeling of detected microbial taxa can help with correct identifications of cohabiting partners based on skin microbiome profiles using machine learning approaches. These results show that a cohabiting partner can significantly influence our microbiota. Follow-up studies will be important for investigating the implications of shared microbiota on dermatological health and the contributions of cohabiting parents to the microbiome profiles of their infants.
Understanding underlying mechanisms involved in microbial persistence in the built environment (BE) is essential for strategically mitigating potential health risks. To test the hypothesis that BEs impose selective pressures resulting in characteristic adaptive responses, we performed a pangenomics meta-analysis leveraging 189 genomes (accessed from GenBank) of two epidemiologically important taxa, Bacillus cereus and Staphylococcus aureus, isolated from various origins: the International Space Station (ISS; a model BE), Earth-based BEs, soil, and humans. Our objectives were to (i) identify differences in the pangenomic composition of generalist and host-associated organisms, (ii) characterize genes and functions involved in BE-associated selection, and (iii) identify genomic signatures of ISS-derived strains of potential relevance for astronaut health. The pangenome of B. cereus was more expansive than that of S. aureus, which had a dominant core component. Genomic contents of both taxa significantly correlated with isolate origin, demonstrating an importance for biogeography and potential niche adaptations. ISS/BE-enriched functions were often involved in biosynthesis, catabolism, materials transport, metabolism, and stress response. Multiple origin-enriched functions also overlapped across taxa, suggesting conserved adaptive processes. We further characterized two mobile genetic elements with local neighborhood genes encoding biosynthesis and stress response functions that distinctively associated with B. cereus from the ISS. Although antibiotic resistance genes were present in ISS/BE isolates, they were also common in counterparts elsewhere. Overall, despite differences in microbial lifestyle, some functions appear common to remaining viable in the BE, and those functions are not typically associated with direct impacts on human health. IMPORTANCE The built environment contains a variety of microorganisms, some of which pose critical human health risks (e.g., hospital-acquired infection, antibiotic resistance dissemination). We uncovered a combination of complex biological functions that may play a role in bacterial survival under the presumed selective pressures in a model built environment-the International Space Station-by using an approach to compare pangenomes of bacterial strains from two clinically relevant species (B. cereus and S. aureus) isolated from both built environments and humans. Our findings suggest that the most crucial bacterial functions involved in this potential adaptive response are specific to bacterial lifestyle and do not appear to have direct impacts on human health.
To describe a microbe’s physiology, including its metabolism, environmental roles, and growth characteristics, it must be grown in a laboratory culture. Unfortunately, many phylogenetically novel groups have never been cultured, so their physiologies have only been inferred from genomics and environmental characteristics. Although the diversity, or number of different taxonomic groups, of uncultured clades has been studied well, their global abundances, or numbers of cells in any given environment, have not been assessed. We quantified the degree of similarity of 16S rRNA gene sequences from diverse environments in publicly available metagenome and metatranscriptome databases, which we show have far less of the culture bias present in primer-amplified 16S rRNA gene surveys, to those of their nearest cultured relatives. Whether normalized to scaffold read depths or not, the highest abundances of metagenomic 16S rRNA gene sequences belong to phylogenetically novel uncultured groups in seawater, freshwater, terrestrial subsurface, soil, hypersaline environments, marine sediment, hot springs, hydrothermal vents, nonhuman hosts, snow, and bioreactors (22% to 87% uncultured genera to classes and 0% to 64% uncultured phyla). The exceptions were human and human-associated environments, which were dominated by cultured genera (45% to 97%). We estimate that uncultured genera and phyla could comprise 7.3 × 1029 (81%) and 2.2 × 1029 (25%) of microbial cells, respectively. Uncultured phyla were overrepresented in metatranscriptomes relative to metagenomes (46% to 84% of sequences in a given environment), suggesting that they are viable. Therefore, uncultured microbes, often from deeply phylogenetically divergent groups, dominate nonhuman environments on Earth, and their undiscovered physiologies may matter for Earth systems. IMPORTANCE In the past few decades, it has become apparent that most of the microbial diversity on Earth has never been characterized in laboratory cultures. We show that these unknown microbes, sometimes called “microbial dark matter,” are numerically dominant in all major environments on Earth, with the exception of the human body, where most of the microbes have been cultured. We also estimate that about one-quarter of the population of microbial cells on Earth belong to phyla with no cultured relatives, suggesting that these never-before-studied organisms may be important for ecosystem functions. Author Video: An author video summary of this article is available.
Humans purposefully and inadvertently introduce antimicrobial chemicals into buildings, resulting in widespread compounds, including triclosan, triclocarban, and parabens, in indoor dust. Meanwhile, drug-resistant infections continue to increase, raising concerns that buildings function as reservoirs of, or even select for, resistant microorganisms. Support for these hypotheses is limited largely since data describing relationships between antimicrobials and indoor microbial communities are scant. We combined liquid chromatography-isotope dilution tandem mass spectrometry with metagenomic shotgun sequencing of dust collected from athletic facilities to characterize relationships between indoor antimicrobial chemicals and microbial communities. Elevated levels of triclosan and triclocarban, but not parabens, were associated with distinct indoor microbiomes. Dust of high triclosan content contained increased Gram-positive species with diverse drug resistance capabilities, whose pangenomes were enriched for genes encoding osmotic stress responses, efflux pump regulation, lipid metabolism, and material transport across cell membranes; such triclosan-associated functional shifts have been documented in laboratory cultures but not yet from buildings. Antibiotic-resistant bacterial isolates were cultured from all but one facility, and resistance often increased in buildings with very high triclosan levels, suggesting links between human encounters with viable drug-resistant bacteria and local biocide conditions. This characterization uncovers complex relationships between antimicrobials and indoor microbiomes: some chemicals elicit effects, whereas others may not, and no single functional or resistance factor explained chemical-microbe associations. These results suggest that anthropogenic chemicals impact microbial systems in or around buildings and their occupants, highlighting an emergent need to identify the most important indoor, outdoor, and host-associated sources of antimicrobial chemical-resistome interactions. IMPORTANCE The ubiquitous use of antimicrobial chemicals may have undesired consequences, particularly on microbes in buildings. This study shows that the taxonomy and function of microbes in indoor dust are strongly associated with antimicrobial chemicals-more so than any other feature of the buildings. Moreover, we identified links between antimicrobial chemical concentrations in dust and culturable bacteria that are cross-resistant to three clinically relevant antibiotics. These findings suggest that humans may be influencing the microbial species and genes that are found indoors through the addition and removal of particular antimicrobial chemicals.
Human-associated microbial communities include prokaryotic and eukaryotic organisms across high-level clades of the tree of life. While advances in high-throughput sequencing technology allow for the study of diverse lineages, the vast majority of studies are limited to bacteria, and very little is known on how eukaryote microbes fit in the overall microbial ecology of the human gut. As recent studies consider eukaryotes in their surveys, it is becoming increasingly clear that eukaryotes play important ecological roles in the microbiome as well as in host health. In this perspective, we discuss new evidence on eukaryotes as fundamental species of the human gut and emphasize that future microbiome studies should characterize the multitrophic interactions between microeukaryotes, other microorganisms, and the host.
The number of sequenced genomes is growing exponentially, profoundly shifting the bottleneck from data generation to genome interpretation. Traits are often used to characterize and distinguish bacteria and are likely a driving factor in microbial community composition, yet little is known about the traits of most microbes. We describe Traitar, the microbial trait analyzer, which is a fully automated software package for deriving phenotypes from a genome sequence. Traitar provides phenotype classifiers to predict 67 traits related to the use of various substrates as carbon and energy sources, oxygen requirement, morphology, antibiotic susceptibility, proteolysis, and enzymatic activities. Furthermore, it suggests protein families associated with the presence of particular phenotypes. Our method uses L1-regularized L2-loss support vector machines for phenotype assignments based on phyletic patterns of protein families and their evolutionary histories across a diverse set of microbial species. We demonstrate reliable phenotype assignment for Traitar to bacterial genomes from 572 species of eight phyla, also based on incomplete single-cell genomes and simulated draft genomes. We also showcase its application in metagenomics by verifying and complementing a manual metabolic reconstruction of two novel Clostridiales species based on draft genomes recovered from commercial biogas reactors. Traitar is available at https://github.com/hzi-bifo/traitar. IMPORTANCE Bacteria are ubiquitous in our ecosystem and have a major impact on human health, e.g., by supporting digestion in the human gut. Bacterial communities can also aid in biotechnological processes such as wastewater treatment or decontamination of polluted soils. Diverse bacteria contribute with their unique capabilities to the functioning of such ecosystems, but lab experiments to investigate those capabilities are labor-intensive. Major advances in sequencing techniques open up the opportunity to study bacteria by their genome sequences. For this purpose, we have developed Traitar, software that predicts traits of bacteria on the basis of their genomes. It is applicable to studies with tens or hundreds of bacterial genomes. Traitar may help researchers in microbiology to pinpoint the traits of interest, reducing the amount of wet lab work required.