Project description:Microbiome data predictive analysis within a machine learning (ML) workflow presents numerous domain-specific challenges involving preprocessing, feature selection, predictive modeling, performance estimation, model interpretation, and the extraction of biological information from the results. To assist decision-making, we offer a set of recommendations on algorithm selection, pipeline creation and evaluation, stemming from the COST Action ML4Microbiome. We compared the suggested approaches on a multi-cohort shotgun metagenomics dataset of colorectal cancer patients, focusing on their performance in disease diagnosis and biomarker discovery. It is demonstrated that the use of compositional transformations and filtering methods as part of data preprocessing does not always improve the predictive performance of a model. In contrast, the multivariate feature selection, such as the Statistically Equivalent Signatures algorithm, was effective in reducing the classification error. When validated on a separate test dataset, this algorithm in combination with random forest modeling, provided the most accurate performance estimates. Lastly, we showed how linear modeling by logistic regression coupled with visualization techniques such as Individual Conditional Expectation (ICE) plots can yield interpretable results and offer biological insights. These findings are significant for clinicians and non-experts alike in translational applications.
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: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: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: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: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:Skin is a major administration route for drugs, and all transdermal formulations must be tested for their capability to overcome the cutaneous barrier. Therefore, developing highly reliable skin models is crucial for preclinical studies. The current in vitro models are unable to replicate the living skin in all its complexity; thus, to date, excised human skin is considered the gold standard for in vitro permeation studies. However, skin explants have a limited life span. In an attempt to overcome this problem, we used an innovative bioreactor that allowed us to achieve good structural and functional preservation in vitro of explanted human skin for up to 72 h. This device was then used to set up an in vitro inflammatory model by applying two distinct agents mimicking either exogenous or endogenous stimuli: i.e., dithranol, inducing the contact dermatitis phenotype, and the substance P, mimicking neurogenic inflammation. Our in vitro system proved to reproduce inflammatory events observed in vivo, such as vasodilation, increased number of macrophages and mast cells, and increased cytokine secretion. This bioreactor-based system may therefore be suitably and reliably used to simulate in vitro human skin inflammation and may be foreseen as a promising tool to test the efficacy of drugs and cosmetics.
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:Humanized mice are widely used to study the human immune system in vivo and investigate therapeutic targets for various human diseases. Immunodeficient NOD/Shi-scid-IL2rγnull (NOG) mice transferred with human hematopoietic stem cells are a useful model for studying human immune systems and analyzing engrafted human immune cells. The gut microbiota plays a significant role in the development and function of immune cells and the maintenance of immune homeostasis; however, there is currently no available animal model that has been reconstituted with human gut microbiota and immune systems in vivo. In this study, we established a new model of CD34+ cell-transferred humanized germ-free NOG mice using an aseptic method. Flow cytometric analysis revealed that the germ-free humanized mice exhibited a lower level of human CD3+ T cells than the SPF humanized mice. Additionally, we found that the human CD3+ T cells slightly increased after transplanting human gut microbiota into the germ-free humanized mice, suggesting that the human microbiota supports T cell proliferation or maintenance in humanized mice colonized by the gut microbiota. Consequently, the dual-humanized mice may be useful for investigating the physiological role of the gut microbiota in human immunity in vivo and for application as a new humanized mouse model in cancer immunology.