Whole metagenome analysis has the potential to reveal functional triggers of skin diseases, but issues of cost, robustness and sampling efficacy have limited its application. Here, we have established an alternative, clinically practical and robust metagenomic analysis protocol and applied it to 80 skin microbiome samples epidemiologically stratified for atopic dermatitis (AD). We have identified distinct non-flare, baseline skin microbiome signatures enriched for Streptococcus and Gemella but depleted for Dermacoccus in AD-prone versus normal healthy skin. Bacterial challenge assays using keratinocytes and monocyte-derived dendritic cells established distinct IL-1-mediated, innate and Th1-mediated adaptive immune responses with Staphylococcus aureus and Staphylococcus epidermidis. Bacterial differences were complemented by perturbations in the eukaryotic community and functional shifts in the microbiome-wide gene repertoire, which could exacerbate a dry and alkaline phenotype primed for pathogen growth and inflammation in AD-susceptible skin. These findings provide insights into how the skin microbial community, skin surface microenvironment and immune system cross-modulate each other, escalating the destructive feedback cycle between them that leads to AD flare.

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Highlights d Cities possess a consistent ''core'' set of non-human microbes d Urban microbiomes echo important features of cities and city-life d Antimicrobial resistance genes are widespread in cities d Cities contain many novel bacterial and viral species

Understanding the composition and clinical importance of the fungal mycobiome was recently identified as a key topic in a “research priorities” consensus statement for bronchiectasis.Patients were recruited as part of the CAMEB study: an international multicentre cross-sectional Cohort of Asian and Matched European Bronchiectasis patients. The mycobiome was determined in 238 patients by targeted amplicon shotgun sequencing of the 18S–28S rRNA internally transcribed spacer regions ITS1 and ITS2. Specific quantitative PCR for detection of and conidial quantification for a range of airway Aspergillus species was performed. Sputum galactomannan, Aspergillus specific IgE, IgG and TARC (thymus and activation regulated chemokine) levels were measured systemically and associated to clinical outcomes.The bronchiectasis mycobiome is distinct and characterised by specific fungal genera, including Aspergillus, Cryptococcus and Clavispora. Aspergillus fumigatus (in Singapore/Kuala Lumpur) and Aspergillus terreus (in Dundee) dominated profiles, the latter associating with exacerbations. High frequencies of Aspergillus-associated disease including sensitisation and allergic bronchopulmonary aspergillosis were detected. Each revealed distinct mycobiome profiles, and associated with more severe disease, poorer pulmonary function and increased exacerbations.The pulmonary mycobiome is of clinical relevance in bronchiectasis. Screening for Aspergillus-associated disease should be considered even in apparently stable patients.

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BackgroundNanopore sequencing provides a rapid, cheap and portable real-time sequencing platform with the potential to revolutionize genomics. However, several applications are limited by relatively high single-read error rates (>10 %), including RNA-seq, haplotype sequencing and 16S sequencing.ResultsWe developed the Intramolecular-ligated Nanopore Consensus Sequencing (INC-Seq) as a strategy for obtaining long and accurate nanopore reads, starting with low input DNA. Applying INC-Seq for 16S rRNA-based bacterial profiling generated full-length amplicon sequences with a median accuracy >97 %.ConclusionsINC-Seq reads enabled accurate species-level classification, identification of species at 0.1 % abundance and robust quantification of relative abundances, providing a cheap and effective approach for pathogen detection and microbiome profiling on the MinION system.Electronic supplementary materialThe online version of this article (doi:10.1186/s13742-016-0140-7) contains supplementary material, which is available to authorized users.

DNA barcodes are useful for species discovery and species identification, but obtaining barcodes currently requires a well-equipped molecular laboratory and is time-consuming, and/or expensive. We here address these issues by developing a barcoding pipeline for Oxford Nanopore MinION™ and demonstrating that one flow cell can generate barcodes for ~500 specimens despite the high basecall error rates of MinION™ reads. The pipeline overcomes these errors by first summarizing all reads for the same tagged amplicon as a consensus barcode. Consensus barcodes are overall mismatch-free but retain indel errors that are concentrated in homopolymeric regions. They are addressed with an optional error correction pipeline that is based on conserved amino acid motifs from publicly available barcodes. The effectiveness of this pipeline is documented by analysing reads from three MinION™ runs that represent three different stages of MinION™ development. They generated data for (i) 511 specimens of a mixed Diptera sample, (ii) 575 specimens of ants and (iii) 50 specimens of Chironomidae. The run based on the latest chemistry yielded MinION™ barcodes for 490 of the 511 specimens which were assessed against reference Sanger barcodes (N = 471). Overall, the MinION™ barcodes have an accuracy of 99.3%-100% with the number of ambiguous bases after correction ranging from <0.01% to 1.5% depending on which correction pipeline is used. We demonstrate that it requires ~2 hr of sequencing to gather all information needed for obtaining reliable barcodes for most specimens (>90%). We estimate that up to 1,000 barcodes can be generated in one flow cell and that the cost per barcode can be

Although disinfection is key to infection control, the colonization patterns and resistomes of hospital-environment microbes remain underexplored. We report the first extensive genomic characterization of microbiomes, pathogens and antibiotic resistance cassettes in a tertiary-care hospital, from repeated sampling (up to 1.5 years apart) of 179 sites associated with 45 beds. Deep shotgun metagenomics unveiled distinct ecological niches of microbes and antibiotic resistance genes characterized by biofilm-forming and human-microbiome-influenced environments with corresponding patterns of spatiotemporal divergence. Quasi-metagenomics with nanopore sequencing provided thousands of high-contiguity genomes, phage and plasmid sequences (>60% novel), enabling characterization of resistome and mobilome diversity and dynamic architectures in hospital environments. Phylogenetics identified multidrug-resistant strains as being widely distributed and stably colonizing across sites. Comparisons with clinical isolates indicated that such microbes can persist in hospitals for extended periods (>8 years), to opportunistically infect patients. These findings highlight the importance of characterizing antibiotic resistance reservoirs in hospitals and establish the feasibility of systematic surveys to target resources for preventing infections.