Social environment and genetics underlie body site-specific microbiomes of Yellowstone National Park gray wolves (Canis lupus).
ABSTRACT: The host-associated microbiome is an important player in the ecology and evolution of species. Despite growing interest in the medical, veterinary, and conservation communities, there remain numerous questions about the primary factors underlying microbiota, particularly in wildlife. We bridged this knowledge gap by leveraging microbial, genetic, and observational data collected in a wild, pedigreed population of gray wolves (Canis lupus) inhabiting Yellowstone National Park. We characterized body site-specific microbes across six haired and mucosal body sites (and two fecal samples) using 16S rRNA amplicon sequencing. At the phylum level, we found that the microbiome of gray wolves primarily consists of Actinobacteria, Bacteroidetes, Firmicutes, Fusobacteria, and Proteobacteria, consistent with previous studies within Mammalia and Canidae. At the genus level, we documented body site-specific microbiota with functions relevant to microenvironment and local physiological processes. We additionally employed observational and RAD sequencing data to examine genetic, demographic, and environmental correlates of skin and gut microbiota. We surveyed individuals across several levels of pedigree relationships, generations, and social groups, and found that social environment (i.e., pack) and genetic relatedness were two primary factors associated with microbial community composition to differing degrees between body sites. We additionally reported body condition and coat color as secondary factors underlying gut and skin microbiomes, respectively. We concluded that gray wolf microbiota resemble similar host species, differ between body sites, and are shaped by numerous endogenous and exogenous factors. These results provide baseline information for this long-term study population and yield important insights into the evolutionary history, ecology, and conservation of wild wolves and their associated microbes.
Project description:<h4>Background</h4>Understanding the normal temporal variation in the human microbiome is critical to developing treatments for putative microbiome-related afflictions such as obesity, Crohn’s 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.<h4>Results</h4>We find that despite stable differences between body sites and individuals, there is pronounced variability in an individual’s 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.<h4>Conclusions</h4>DNA 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.
Project description:Microbiome research has increased dramatically in recent years, driven by advances in technology and significant reductions in the cost of analysis. Such research has unlocked a wealth of data, which has yielded tremendous insight into the nature of the microbial communities, including their interactions and effects, both within a host and in an external environment as part of an ecological community. Understanding the role of microbiota, including their dynamic interactions with their hosts and other microbes, can enable the engineering of new diagnostic techniques and interventional strategies that can be used in a diverse spectrum of fields, spanning from ecology and agriculture to medicine and from forensics to exobiology. From June 19-23 in 2017, the NIH and NSF jointly held an Innovation Lab on Quantitative Approaches to Biomedical Data Science Challenges in our Understanding of the Microbiome. This review is inspired by some of the topics that arose as priority areas from this unique, interactive workshop. The goal of this review is to summarize the Innovation Lab's findings by introducing the reader to emerging challenges, exciting potential, and current directions in microbiome research. The review is broken into five key topic areas: (1) interactions between microbes and the human body, (2) evolution and ecology of microbes, including the role played by the environment and microbe-microbe interactions, (3) analytical and mathematical methods currently used in microbiome research, (4) leveraging knowledge of microbial composition and interactions to develop engineering solutions, and (5) interventional approaches and engineered microbiota that may be enabled by selectively altering microbial composition. As such, this review seeks to arm the reader with a broad understanding of the priorities and challenges in microbiome research today and provide inspiration for future investigation and multi-disciplinary collaboration.
Project description:The recent recolonization of Central Europe by the European gray wolf (Canis lupus) provides an opportunity to study the dynamics of parasite transmission for cases when a definitive host returns after a phase of local extinction. We investigated whether a newly established wolf population increased the prevalence of those parasites in ungulate intermediate hosts representing wolf prey, whether some parasite species are particularly well adapted to wolves, and the potential basis for such adaptations. We recorded Sarcocystis species richness in wolves and Sarcocystis prevalence in ungulates harvested in study sites with and without permanent wolf presence in Germany using microscopy and DNA metabarcoding. Sarcocystis prevalence in red deer (Cervus elaphus) was significantly higher in wolf areas (79.7%) than in control areas (26.3%) but not in roe deer (Capreolus capreolus) (97.2% vs. 90.4%) or wild boar (Sus scrofa) (82.8% vs. 64.9%). Of 11 Sarcocystis species, Sarcocystis taeniata and Sarcocystis grueneri occurred more often in wolves than expected from the Sarcocystis infection patterns of ungulate prey. Both Sarcocystis species showed a higher increase in prevalence in ungulates in wolf areas than other Sarcocystis species, suggesting that they are particularly well adapted to wolves, and are examples of "wolf specialists". Sarcocystis species richness in wolves was significantly higher in pups than in adults. "Wolf specialists" persisted during wolf maturation. The results of this study demonstrate that (1) predator-prey interactions influence parasite prevalence, if both predator and prey are part of the parasite life cycle, (2) mesopredators do not necessarily replace the apex predator in parasite transmission dynamics for particular parasites of which the apex predator is the definitive host, even if meso- and apex predators were from the same taxonomic family (here: Canidae, e.g., red foxes Vulpes vulpes), and (3) age-dependent immune maturation contributes to the control of protozoan infection in wolves.
Project description:The Greenland wolf, <i>Canis lupus orion</i> as s subspecies of the gray wolf, is native to Greenland. Here, we assembled a complete 16,650?bp genome for the <i>C. l. orion</i> mitochondrion by employing Illumina HiSeq platform. The complete mitochondrial genome contained 13 protein-coding genes (PCGs), 22 transfer RNA (tRNA) genes, two ribosomal RNA (rRNA) genes, and one control region. Overall DNA sequence of the <i>C. l. orion</i> mitochondrion was identical to that of gray wolf <i>C. l. lupus</i>, although slight difference was observed in their control regions. The genomic structure of <i>C. l. orion</i> mitochondrion was conserved with the gene arrangements of mitogenomes published in Canidae, and phylogenetic analysis confirmed the sister relationship among <i>Canis</i> sp. This information will provide essential molecular reference to elucidate biogeography, phylogenetic distance, and evolutionary history in gray wolves.
Project description:UNLABELLED:DNA from phylogenetically diverse microbes is routinely recovered from healthy human lungs and used to define the lung microbiome. The proportion of this DNA originating from microbes adapted to the lungs, as opposed to microbes dispersing to the lungs from other body sites and the atmosphere, is not known. We use a neutral model of community ecology to distinguish members of the lung microbiome whose presence is consistent with dispersal from other body sites and those that deviate from the model, suggesting a competitive advantage to these microbes in the lungs. We find that the composition of the healthy lung microbiome is consistent with predictions of the neutral model, reflecting the overriding role of dispersal of microbes from the oral cavity in shaping the microbial community in healthy lungs. In contrast, the microbiome of diseased lungs was readily distinguished as being under active selection. We also assessed the viability of microbes from lung samples by cultivation with a variety of media and incubation conditions. Bacteria recovered by cultivation from healthy lungs represented species that comprised 61% of the 16S rRNA-encoding gene sequences derived from bronchoalveolar lavage samples. IMPORTANCE:Neutral distribution of microbes is a distinguishing feature of the microbiome in healthy lungs, wherein constant dispersal of bacteria from the oral cavity overrides differential growth of bacteria. No bacterial species consistently deviated from the model predictions in healthy lungs, although representatives of many of the dispersed species were readily cultivated. In contrast, bacterial populations in diseased lungs were identified as being under active selection. Quantification of the relative importance of selection and neutral processes such as dispersal in shaping the healthy lung microbiome is a first step toward understanding its impacts on host health.
Project description:Humans are living ecosystems composed of human cells and microbes. The microbiome is the collection of microbes (microbiota) and their genes. Recent breakthroughs in the high-throughput sequencing technologies have made it possible for us to understand the composition of the human microbiome. Launched by the National Institutes of Health in USA, the human microbiome project indicated that our bodies harbor a wide array of microbes, specific to each body site with interpersonal and intrapersonal variabilities. Numerous studies have indicated that several factors influence the development of the microbiome including genetics, diet, use of antibiotics, and lifestyle, among others. The microbiome and its mediators are in a continuous cross talk with the host immune system; hence, any imbalance on one side is reflected on the other. Dysbiosis (microbiota imbalance) was shown in many diseases and pathological conditions such as inflammatory bowel disease, celiac disease, multiple sclerosis, rheumatoid arthritis, asthma, diabetes, and cancer. The microbial composition mirrors inflammation variations in certain disease conditions, within various stages of the same disease; hence, it has the potential to be used as a biomarker.
Project description:Next Generation Sequencing has been widely used to characterize the prevalence of fecal bacteria in many different species. In this study, we attempted to employ a low-cost and high-throughput sequencing model to discern information pertaining to the wolf microbiota. It is hoped that this model will allow researchers to elucidate potential protective factors in relation to endangered wolf species. We propose three high-throughput sequencing models to reveal information pertaining to the micro-ecology of the wolf. Our analyses advised that, among the three models, more than 100,000 sequences are more appropriate to retrieve the communities' richness and diversity of micro-ecology. In addition, the top five wolf microbiome OTUs (99%) were members of the following five phyla: Bacteroidetes, Fusobacteria, Firmicutes, Proteobacteria, and Actinobacteria. While Alloprevotella, Clostridium_sensu_stricto_1, Anaerobiospirillum, Faecalibactreium and Streptococcus were shared by all samples, their relative abundances were differentially represented between domestic dogs and other wolves. Our findings suggest that altitude, human interference, age, and climate all contribute towards the micro-ecology of the wolf. Specifically, we observed that genera Succinivibrio and Turicibacter are significantly related to altitude and human interference (including hunting practices).
Project description:Species of <i>Canis</i> (Carnivora, Canidae) have similar morphology and distinguishing sympatric species is challenging. We present data on morphometry of skull, body and hair of three wild <i>Canis</i> species that occur in India, which include two wolves (Indian wolf, <i>Canislupuspallipes</i>; and Himalayan wolf, <i>Canishimalayensis</i>) and the golden jackal (<i>Canisaureus</i>). A total of 20 cranial and six body measurements and microscopic characteristics of guard hair were analysed, using multivariate ordination to differentiate between species. Cranial measures of the Himalayan wolves were found to be the largest followed by Indian wolves and golden jackals. However, many measures overlapped amongst the three species. Two Principal Components each, for body measures and cranial measures, explained 86 and 91% of the variation in the data, respectively. These Components discriminated the two wolves from golden jackals, but could not distinguish between wolves. Hair medullary patterns were simple and wide type, whereas hair cuticular patterns showed crenate scale margins, near scale distance and irregular wavey scale patterns for all <i>Canis</i> taxa and were not useful to distinguish species. Data reported in this study further contribute to the existing global data on wild canids for a holistic understanding of the variation within the genus and show that distinguishing between all sympatric species from morphology alone may not be possible.
Project description:Oral microbiota ecology is influenced by environmental and host conditions, but few studies have evaluated associations between untargeted measures of the entire oral microbiome and potentially relevant environmental and host factors. This study aimed to identify salivary microbiota cluster groups using hierarchical cluster analyses (Wards method) based on 16S rRNA gene amplicon sequencing, and identify lifestyle and host factors which were associated with these groups. Group members (n = 175) were distinctly separated by microbiota profiles and differed in reported sucrose intake and allelic variation in the taste-preference-associated genes TAS1R1 (rs731024) and GNAT3 (rs2074673). Groups with higher sucrose intake were either characterized by a wide panel of species or phylotypes with fewer aciduric species, or by a narrower profile that included documented aciduric- and caries-associated species. The inferred functional profiles of the latter type were dominated by metabolic pathways associated with the carbohydrate metabolism with enrichment of glycosidase functions. In conclusion, this study supported in vivo associations between sugar intake and oral microbiota ecology, but it also found evidence for a variable microbiota response to sugar, highlighting the importance of modifying host factors and microbes beyond the commonly targeted acidogenic and acid-tolerant species. The results should be confirmed under controlled settings with comprehensive phenotypic and genotypic data.
Project description:ABSTRACT The aerodigestive tract (ADT) is the primary portal through which pathogens and other invading microbes enter the body. As the direct interface with the environment, we hypothesize that the ADT microbiota possess biosynthetic gene clusters (BGCs) for antibiotics and other specialized metabolites to compete with both endogenous and exogenous microbes. From 1,214 bacterial genomes, representing 136 genera and 387 species that colonize the ADT, we identified 3,895 BGCs. To determine the distribution of BGCs and bacteria in different ADT sites, we aligned 1,424 metagenomes, from nine different ADT sites, onto the predicted BGCs. We show that alpha diversity varies across the ADT and that each site is associated with distinct bacterial communities and BGCs. We identify specific BGC families enriched in the buccal mucosa, external naris, gingiva, and tongue dorsum despite these sites harboring closely related bacteria. We reveal BGC enrichment patterns indicative of the ecology at each site. For instance, aryl polyene and resorcinol BGCs are enriched in the gingiva and tongue, which are colonized by many anaerobes. In addition, we find that streptococci colonizing the tongue and cheek possess different ribosomally synthesized and posttranslationally modified peptide BGCs. Finally, we highlight bacterial genera with BGCs but are underexplored for specialized metabolism and demonstrate the bioactivity of Actinomyces against other bacteria, including human pathogens. Together, our results demonstrate that specialized metabolism in the ADT is extensive and that by exploring these microbiomes further, we will better understand the ecology and biogeography of this system and identify new bioactive natural products. IMPORTANCE Bacteria produce specialized metabolites to compete with other microbes. Though the biological activities of many specialized metabolites have been determined, our understanding of their ecology is limited, particularly within the human microbiome. As the aerodigestive tract (ADT) faces the external environment, bacteria colonizing this tract must compete both among themselves and with invading microbes, including human pathogens. We analyzed the genomes of ADT bacteria to identify biosynthetic gene clusters (BGCs) for specialized metabolites. We found that the majority of ADT BGCs are uncharacterized and the metabolites they encode are unknown. We mapped the distribution of BGCs across the ADT and determined that each site is associated with its own distinct bacterial community and BGCs. By further characterizing these BGCs, we will inform our understanding of ecology and biogeography across the ADT, and we may uncover new specialized metabolites, including antibiotics.