Project description:Human skin microbiota has been described as a "microbial fingerprint" due to observed differences between individuals. Current understanding of the cutaneous microbiota is based on sampling the outermost layers of the epidermis, while the microbiota in the remaining skin layers has not yet been fully characterized. Environmental conditions can vary drastically between the cutaneous compartments and give rise to unique communities. We demonstrate that the dermal microbiota is surprisingly similar among individuals and contains a specific subset of the epidermal microbiota. Variability in bacterial community composition decreased significantly from the epidermal to the dermal compartment but was similar among anatomic locations (hip and knee). The composition of the epidermal microbiota was more strongly affected by environmental factors than that of the dermal community. These results indicate a well-conserved dermal community that is functionally distinct from the epidermal community, challenging the current dogma. Future studies in cutaneous disorders and chronic infections may benefit by focusing on the dermal microbiota as a persistent microbial community.IMPORTANCE Human skin microbiota is thought to be unique according to the individual's lifestyle and genetic predisposition. This is true for the epidermal microbiota, while our findings demonstrate that the dermal microbiota is universal between healthy individuals. The preserved dermal microbial community is compositionally unique and functionally distinct to the specific environment in the depth of human skin. It is expected to have direct contact with the immune response of the human host, and research in the communication between host and microbiota should be targeted to this cutaneous compartment. This novel insight into specific microbial adaptation can be used advantageously in the research of chronic disorders and infections of the skin. It can enlighten the alteration between health and disease to the benefit of patients suffering from long-lasting socioeconomic illnesses.
Project description:Functional metagenomics is a powerful method that allows the isolation of genes whose role may not have been predicted from DNA sequence. In this approach, first, environmental DNA is cloned to generate metagenomic libraries that are maintained in Escherichia coli, and second, the cloned DNA is screened for activities of interest. Typically, functional screens are carried out using E. coli as a surrogate host, although there likely exist barriers to gene expression, such as lack of recognition of native promoters. Here, we describe efforts to develop Bacteroides thetaiotaomicron as a surrogate host for screening metagenomic DNA from the human gut. We construct a B. thetaiotaomicron-compatible fosmid cloning vector, generate a fosmid clone library using DNA from the human gut, and show successful functional complementation of a B. thetaiotaomicron glycan utilization mutant. Though we were unable to retrieve the physical fosmid after complementation, we used genome sequencing to identify the complementing genes derived from the human gut microbiome. Our results demonstrate that the use of B. thetaiotaomicron to express metagenomic DNA is promising, but they also exemplify the challenges that can be encountered in the development of new surrogate hosts for functional screening. IMPORTANCE Human gut microbiome research has been supported by advances in DNA sequencing that make it possible to obtain gigabases of sequence data from metagenomes but is limited by a lack of knowledge of gene function that leads to incomplete annotation of these data sets. There is a need for the development of methods that can provide experimental data regarding microbial gene function. Functional metagenomics is one such method, but functional screens are often carried out using hosts that may not be able to express the bulk of the environmental DNA being screened. We expand the range of current screening hosts and demonstrate that human gut-derived metagenomic libraries can be introduced into the gut microbe Bacteroides thetaiotaomicron to identify genes based on activity screening. Our results support the continuing development of genetically tractable systems to obtain information about gene function.
Project description:Buruli ulcer (BU) is an infectious disease caused by Mycobacterium ulcerans and considered the third most prevalent mycobacterial disease in humans. Secondary bacterial infections in open BU lesions are the main cause of pain, delayed healing and systemic illness, resulting in prolonged hospital stay. Thus, understanding the diversity of bacteria, termed the microbiome, in these open lesions is important for proper treatment. However, adequately studying the human microbiome in a clinical setting can prove difficult when investigating a neglected tropical skin disease due to its rarity and the setting.Using 16S rRNA sequencing, we determined the microbial composition of 5 BU lesions, 3 non-BU lesions and 3 healthy skin samples. Although no significant differences in diversity were found between BU and non-BU lesions, the former were characterized by an increase of Bacteroidetes compared to the non-BU wounds and the BU lesions also contained significantly more obligate anaerobes. With this molecular-based study, we were also able to detect bacteria that were missed by culture-based methods in previous BU studies.Our study suggests that BU may lead to changes in the skin bacterial community within the lesions. However, in order to determine if such changes hold true across all BU cases and are either a cause or consequence of a specific wound environment, further microbiome studies are necessary. Such skin microbiome analysis requires large sample sizes and lesions from the same body site in many patients, both of which can be difficult for a rare disease. Our study proposes a pipeline for such studies and highlights several drawbacks that must be considered if microbiome analysis is to be utilized for neglected tropical diseases.
Project description:A variety of microbial communities and their genes (the microbiome) exist throughout the human body, with fundamental roles in human health and disease. The National Institutes of Health (NIH)-funded Human Microbiome Project Consortium has established a population-scale framework to develop metagenomic protocols, resulting in a broad range of quality-controlled resources and data including standardized methods for creating, processing and interpreting distinct types of high-throughput metagenomic data available to the scientific community. Here we present resources from a population of 242 healthy adults sampled at 15 or 18 body sites up to three times, which have generated 5,177 microbial taxonomic profiles from 16S ribosomal RNA genes and over 3.5 terabases of metagenomic sequence so far. In parallel, approximately 800 reference strains isolated from the human body have been sequenced. Collectively, these data represent the largest resource describing the abundance and variety of the human microbiome, while providing a framework for current and future studies.
Project description:Biogeography and individuality shape the structural and functional composition of the human skin microbiome. To explore these factors' contribution to skin microbial community stability, we generated metagenomic sequence data from longitudinal samples collected over months and years. Analyzing these samples using a multi-kingdom, reference-based approach, we found that despite the skin's exposure to the external environment, its bacterial, fungal, and viral communities were largely stable over time. Site, individuality, and phylogeny were all determinants of stability. Foot sites exhibited the most variability; individuals differed in stability; and transience was a particular characteristic of eukaryotic viruses, which showed little site-specificity in colonization. Strain and single-nucleotide variant-level analysis showed that individuals maintain, rather than reacquire, prevalent microbes from the environment. Longitudinal stability of skin microbial communities generates hypotheses about colonization resistance and empowers clinical studies exploring alterations observed in disease states.
Project description:The nematode Caenorhabditis elegans is used as a central model system across biological disciplines. Surprisingly, almost all research with this worm is performed in the absence of its native microbiome, possibly affecting generality of the obtained results. In fact, the C. elegans microbiome had been unknown until recently. This review brings together results from the first three studies on C. elegans microbiomes, all published in 2016. Meta-analysis of the data demonstrates a considerable conservation in the composition of the microbial communities, despite the distinct geographical sample origins, study approaches, labs involved and perturbations during worm processing. The C. elegans microbiome is enriched and in some cases selective for distinct phylotypes compared to corresponding substrate samples (e.g., rotting fruits, decomposing plant matter, and compost soil). The dominant bacterial groups include several Gammaproteobacteria (Enterobacteriaceae, Pseudomonaceae, and Xanthomonodaceae) and Bacteroidetes (Sphingobacteriaceae, Weeksellaceae, Flavobacteriaceae). They are consistently joined by several rare putative keystone taxa like Acetobacteriaceae. The bacteria are able to enhance growth of nematode populations, as well as resistance to biotic and abiotic stressors, including high/low temperatures, osmotic stress, and pathogenic bacteria and fungi. The associated microbes thus appear to display a variety of effects beneficial for the worm. The characteristics of these effects, their relevance for C. elegans fitness, the presence of specific co-adaptations between microbiome members and the worm, and the molecular underpinnings of microbiome-host interactions represent promising areas of future research, for which the advantages of C. elegans as an experimental system should prove of particular value.
Project description:BackgroundThe past decade of microbiome research has concentrated on cataloging the diversity of taxa in different environments. The next decade is poised to focus on microbial traits and function. Most existing methods for doing this perform pathway analysis using reference databases. This has both benefits and drawbacks. Function can go undetected if reference databases are coarse-grained or incomplete. Likewise, detection of a pathway does not guarantee expression of the associated function. Finally, function cannot be connected to specific microbial constituents, making it difficult to ascertain the types of organisms exhibiting particular traits-something that is important for understanding microbial success in specific environments. A complementary approach to pathway analysis is to use the wealth of microbial trait information collected over years of lab-based, culture experiments.MethodsHere, we use journal articles and Bergey's Manual of Systematic Bacteriology to develop a trait-based database for 971 human skin bacterial taxa. We then use this database to examine functional traits that are over/underrepresented among skin taxa. Specifically, we focus on three trait classes-binary, categorical, and quantitative-and compare trait values among skin taxa and microbial taxa more broadly. We compare binary traits using a Chi-square test, categorical traits using randomization trials, and quantitative traits using a nonparametric relative effects test based on global rankings using Tukey contrasts.ResultsWe find a number of traits that are over/underrepresented within the human skin microbiome. For example, spore formation, acid phosphatase, alkaline phosphatase, pigment production, catalase, and oxidase are all less common among skin taxa. As well, skin bacteria are less likely to be aerobic, favoring, instead, a facultative strategy. They are also less likely to exhibit gliding motility, less likely to be spirillum or rod-shaped, and less likely to grow in chains. Finally, skin bacteria have more difficulty at high pH, prefer warmer temperatures, and are much less resilient to hypotonic conditions.ConclusionsOur analysis shows how an approach that relies on information from culture experiments can both support findings from pathway analysis, and also generate new insights into the structuring principles of microbial communities.
Project description:Due to its lack of both innate and acquired immune responses to human cells, the NODSCIDIl2r?-/- (NSG) mouse model has become an important tool for human stem cell research. When compared with the mouse, the rat is physiologically more similar to humans and offers advantages in preclinical efficacy studies on human stem cells, particularly in evaluating neural, hepatic, and cardiac functions. Therefore, we generated a human SIRP?+Prdkc-/-Il2r?-/- rat model, denoted NSG-like (NSGL) rat, which expresses human SIRP? and is abolished in the development of B, T, and natural killer cells. When compared with Prdkc-/-Il2r?-/- (SG) rats, NSGL rats allow more efficient engraftment of human cancer cells and human pluripotent stem cells. In addition, only NSGL rats, but not SG rats, can be engrafted with human hematopoietic stem cells to reconstitute the human immune system. Therefore, NSGL rats represent an improved xenotransplantation model for efficacy studies of human stem cells.
Project description:BackgroundThe human skin microbiome has been recently investigated as a potential forensic tool, as people leave traces of their potentially unique microbiomes on objects and surfaces with which they interact. In this metagenomic study of four people in Hong Kong, their homes, and public surfaces in their neighbourhoods, we investigated the stability and identifiability of these microbiota traces on a timescale of hours to days.ResultsUsing a Canberra distance-based method of comparing skin and surface microbiomes, we found that a person could be accurately matched to their household in 84% of tests and to their neighbourhood in 50% of tests, and that matching accuracy did not decay for household surfaces over the 10-day study period, although it did for public surfaces. The time of day at which a skin or surface sample was taken affected matching accuracy, and 160 species across all sites were found to have a significant variation in abundance between morning and evening samples. We hypothesised that daily routines drive a rhythm of daytime dispersal from the pooled public surface microbiome followed by normalisation of a person's microbiome by contact with their household microbial reservoir, and Dynamic Bayesian Networks (DBNs) supported dispersal from public surfaces to skin as the major dispersal route among all sites studied.ConclusionsThese results suggest that in addition to considering the decay of microbiota traces with time, diurnal patterns in microbiome exposure that contribute to the human skin microbiome assemblage must also be considered in developing this as a potential forensic method. Video Abstract.