All Inked Up

All Inked Up was a UCA Research funded programme and event, its principal function and outcome was an enquiry into the notion of the artist book. It composed of an international artist book and print event spread over two venues: the Herbert Read Gallery, UCA Canterbury, and The Brewery Tap Gallery, Folkestone. The event comprised of over 100 artists, universities, studios and galleries, including internationally recognised book artists from Japan, South Korea, Spain, Norway, Holland, Germany, Portugal, Ireland, as well as the UK. It included work of staff and students from European universities who have a research programme involving the artist book: University Barcelona, E.I.N.A Barcelona, Lljota Barcelona, Limerick and Cork Ireland, Camberwell, Glasgow, Dundee and University of Leeds; as well as local galleries, studios and artists within the South East: Resort Studios, Open School East, Limbo, and Folkestone Creative Foundation. A symposium was held at The Cragg Lecture Theatre on Friday 13 October 2017 to coincide with the book fair and again promoted through the Canterbury Festival. Ten artists, practitioners and academics were invited to debate and talk about their practice and what constitutes the artist book; McDonald's main objective for the event, symposium and subsequent exhibition was one of exploring and debating the notion of the artist book. The symposium provided the opportunity to ask what the function of the 'artists' book' is within an artist's and a designer's practice. The exhibition (Unbound) featured five internationally acclaimed artists including McDonald himself. The event's purpose was to build the audience's awareness of the artist book as a primary medium and method in artistic practice and introduce the broad possibilities that the book format covers, from illustrative narrative to sculptural forms through to digital audio / video and performance work. The book can be in the shape of a more personal artefact held and played with, to digital environments that nurture or engulf the audience

Role of the microbiome, probiotics, and 'dysbiosis therapy' in critical illness.

Purpose of reviewLoss of 'health-promoting' microbes and overgrowth of pathogenic bacteria (dysbiosis) in ICU is believed to contribute to nosocomial infections, sepsis, and organ failure (multiple organ dysfunction syndrome). This review discusses new understanding of ICU dysbiosis, new data for probiotics and fecal transplantation in ICU, and new data characterizing the ICU microbiome.Recent findingsICU dysbiosis results from many factors, including ubiquitous antibiotic use and overuse. Despite advances in antibiotic therapy, infections and mortality from often multidrug-resistant organisms (i.e., Clostridium difficile) are increasing. This raises the question of whether restoration of a healthy microbiome via probiotics or other 'dysbiosis therapies' would be an optimal alternative, or parallel treatment option, to antibiotics. Recent clinical data demonstrate probiotics can reduce ICU infections and probiotics or fecal microbial transplant (FMT) can treat Clostridium difficile. This contributes to recommendations that probiotics should be considered to prevent infection in ICU. Unfortunately, significant clinical variability limits the strength of current recommendations and further large clinical trials of probiotics and FMT are needed. Before larger trials of 'dysbiosis therapy' can be thoughtfully undertaken, further characterization of ICU dysbiosis is needed. To addressing this, we conducted an initial analysis demonstrating a rapid and marked change from a 'healthy' microbiome to an often pathogen-dominant microbiota (dysbiosis) in a broad ICU population.SummaryA growing body of evidence suggests critical illness and ubiquitous antibiotic use leads to ICU dysbiosis that is associated with increased ICU infection, sepsis, and multiple organ dysfunction syndrome. Probiotics and FMT show promise as ICU therapies for infection. We hope future-targeted therapies using microbiome signatures can be developed to correct 'illness-promoting' dysbiosis to restore a healthy microbiome post-ICU to improve patient outcomes

Towards large-cohort comparative studies to define the factors influencing the gut microbial community structure of ASD patients.

Differences in the gut microbiota have been reported between individuals with autism spectrum disorders (ASD) and neurotypical controls, although direct evidence that changes in the microbiome contribute to causing ASD has been scarce to date. Here we summarize some considerations of experimental design that can help untangle causality in this complex system. In particular, large cross-sectional studies that can factor out important variables such as diet, prospective longitudinal studies that remove some of the influence of interpersonal variation in the microbiome (which is generally high, especially in children), and studies transferring microbial communities into germ-free mice may be especially useful. Controlling for the effects of technical variables, which have complicated efforts to combine existing studies, is critical when biological effect sizes are small. Large citizen-science studies with thousands of participants such as the American Gut Project have been effective at uncovering subtle microbiome effects in self-collected samples and with self-reported diet and behavior data, and may provide a useful complement to other types of traditionally funded and conducted studies in the case of ASD, especially in the hypothesis generation phase

redbiom: a Rapid Sample Discovery and Feature Characterization System.

Meta-analyses at the whole-community level have been important in microbiome studies, revealing profound features that structure Earth's microbial communities, such as the unique differentiation of microbes from the mammalian gut relative to free-living microbial communities, the separation of microbiomes in saline and nonsaline environments, and the role of pH in driving soil microbial compositions. However, our ability to identify the specific features of a microbiome that differentiate these community-level patterns have lagged behind, especially as ever-cheaper DNA sequencing has yielded increasingly large data sets. One critical gap is the ability to search for samples that contain specific features (for example, sub-operational taxonomic units [sOTUs] identified by high-resolution statistical methods for removing amplicon sequencing errors). Here we introduce redbiom, a microbiome caching layer, which allows users to rapidly query samples that contain a given feature, retrieve sample data and metadata, and search for samples that match specified metadata values or ranges (e.g., all samples with a pH of >7), implemented using an in-memory NoSQL database called Redis. By default, redbiom allows public anonymous sample access for over 100,000 publicly available samples in the Qiita database. At over 100,000 samples, the caching server requires only 35 GB of resident memory. We highlight how redbiom enables a new type of characterization of microbiome samples and provide tutorials for using redbiom with QIIME 2. redbiom is open source under the BSD license, hosted on GitHub, and can be deployed independently of Qiita to enable search of proprietary or clinically restricted microbiome databases.IMPORTANCE Although analyses that combine many microbiomes at the whole-community level have become routine, searching rapidly for microbiomes that contain a particular sequence has remained difficult. The software we present here, redbiom, dramatically accelerates this process, allowing samples that contain microbiome features to be rapidly identified. This is especially useful when taxonomic annotation is limited, allowing users to identify environments in which unannotated microbes of interest were previously observed. This approach also allows environmental or clinical factors that correlate with specific features, or vice versa, to be identified rapidly, even at a scale of billions of sequences in hundreds of thousands of samples. The software is integrated with existing analysis tools to enable fast, large-scale microbiome searches and discovery of new microbiome relationships

Species abundance information improves sequence taxonomy classification accuracy.

Popular naive Bayes taxonomic classifiers for amplicon sequences assume that all species in the reference database are equally likely to be observed. We demonstrate that classification accuracy degrades linearly with the degree to which that assumption is violated, and in practice it is always violated. By incorporating environment-specific taxonomic abundance information, we demonstrate a significant increase in the species-level classification accuracy across common sample types. At the species level, overall average error rates decline from 25% to 14%, which is favourably comparable to the error rates that existing classifiers achieve at the genus level (16%). Our findings indicate that for most practical purposes, the assumption that reference species are equally likely to be observed is untenable. q2-clawback provides a straightforward alternative for samples from common environments

Ghost-tree: creating hybrid-gene phylogenetic trees for diversity analyses.

BackgroundFungi play critical roles in many ecosystems, cause serious diseases in plants and animals, and pose significant threats to human health and structural integrity problems in built environments. While most fungal diversity remains unknown, the development of PCR primers for the internal transcribed spacer (ITS) combined with next-generation sequencing has substantially improved our ability to profile fungal microbial diversity. Although the high sequence variability in the ITS region facilitates more accurate species identification, it also makes multiple sequence alignment and phylogenetic analysis unreliable across evolutionarily distant fungi because the sequences are hard to align accurately. To address this issue, we created ghost-tree, a bioinformatics tool that integrates sequence data from two genetic markers into a single phylogenetic tree that can be used for diversity analyses. Our approach starts with a "foundation" phylogeny based on one genetic marker whose sequences can be aligned across organisms spanning divergent taxonomic groups (e.g., fungal families). Then, "extension" phylogenies are built for more closely related organisms (e.g., fungal species or strains) using a second more rapidly evolving genetic marker. These smaller phylogenies are then grafted onto the foundation tree by mapping taxonomic names such that each corresponding foundation-tree tip would branch into its new "extension tree" child.ResultsWe applied ghost-tree to graft fungal extension phylogenies derived from ITS sequences onto a foundation phylogeny derived from fungal 18S sequences. Our analysis of simulated and real fungal ITS data sets found that phylogenetic distances between fungal communities computed using ghost-tree phylogenies explained significantly more variance than non-phylogenetic distances. The phylogenetic metrics also improved our ability to distinguish small differences (effect sizes) between microbial communities, though results were similar to non-phylogenetic methods for larger effect sizes.ConclusionsThe Silva/UNITE-based ghost tree presented here can be easily integrated into existing fungal analysis pipelines to enhance the resolution of fungal community differences and improve understanding of these communities in built environments. The ghost-tree software package can also be used to develop phylogenetic trees for other marker gene sets that afford different taxonomic resolution, or for bridging genome trees with amplicon trees.Availabilityghost-tree is pip-installable. All source code, documentation, and test code are available under the BSD license at https://github.com/JTFouquier/ghost-tree