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Conference paperOvadia C, Perdones-Montero A, Mullish B, et al., 2019,
Ursodeoxycholic acid treatment of cholestatic pregnancy can alter the gut microbiota to enhance bile acid modification and production of metabolically-active secondary bile acids - an explanation for 'responders' and 'non-responders'?
, Publisher: WILEY, Pages: 17-17, ISSN: 1470-0328 -
Journal articleMcilroy JR, Segal JP, Mullish BH, et al., 2019,
Current and future targets for faecal microbiota transplantation
, Human Microbiome Journal, Vol: 11, Pages: 100045-100045, ISSN: 2452-2317 -
Journal articleWootton DG, Cox MJ, Gloor GB, et al., 2019,
A haemophilus sp. dominates the microbiota of sputum from UK adults with non-severe community acquired pneumonia and chronic lung disease
, Scientific Reports, Vol: 9, ISSN: 2045-2322The demographics and comorbidities of patients with community acquired pneumonia (CAP) vary enormously but stratified treatment is difficult because aetiological studies have failed to comprehensively identify the pathogens. Our aim was to describe the bacterial microbiota of CAP and relate these to clinical characteristics in order to inform future trials of treatment stratified by co-morbidity. CAP patients were prospectively recruited at two UK hospitals. We used 16S rRNA gene sequencing to identify the dominant bacteria in sputum and compositional data analysis to determine associations with patient characteristics. We analysed sputum samples from 77 patients and found a Streptococcus sp. and a Haemophilus sp. were the most relatively abundant pathogens. The Haemophilus sp. was more likely to be dominant in patients with pre-existing lung disease, and its relative abundance was associated with qPCR levels of Haemophilus influenzae. The most abundant Streptococcus sp. was associated with qPCR levels of Streptococcus pneumoniae but dominance could not be predicted from clinical characteristics. These data suggest chronic lung disease influences the microbiota of sputum in patients with CAP. This finding could inform a trial of stratifying empirical CAP antibiotics to target Haemophilus spp. in addition to Streptococcus spp. in those with chronic lung disease.
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Journal articleGhani R, Gan C, Mullish B, et al., 2019,
Prevalence of recurrent extended-spectrum beta-lactamase (ESBL) urinary tract infections (UTIs) in patients within a urology service. Introducing the concept of Faecal Microbiota transplantation (FMT) as a treatment modality.
, Journal of Clinical Urology -
Journal articleDao MC, Sokolovska N, Brazeilles R, et al., 2019,
A data integration multi-omics approach to study calorie restriction-induced changes in insulin sensitivity
, Frontiers in Physiology, Vol: 9, ISSN: 1664-042XBackground: The mechanisms responsible for calorie restriction (CR)-induced improvement in insulin sensitivity (IS) have not been fully elucidated. Greater insight can be achieved through deep biological phenotyping of subjects undergoing CR, and integration of big data.Materials and Methods: An integrative approach was applied to investigate associations between change in IS and factors from host, microbiota, and lifestyle after a 6-week CR period in 27 overweight or obese adults (ClinicalTrials.gov: NCT01314690). Partial least squares regression was used to determine associations of change (week 6 – baseline) between IS markers and lifestyle factors (diet and physical activity), subcutaneous adipose tissue (sAT) gene expression, metabolomics of serum, urine and feces, and gut microbiota composition. ScaleNet, a network learning approach based on spectral consensus strategy (SCS, developed by us) was used for reconstruction of biological networks.Results: A spectrum of variables from lifestyle factors (10 nutrients), gut microbiota (10 metagenomics species), and host multi-omics (metabolic features: 84 from serum, 73 from urine, and 131 from feces; and 257 sAT gene probes) most associated with IS were identified. Biological network reconstruction using SCS, highlighted links between changes in IS, serum branched chain amino acids, sAT genes involved in endoplasmic reticulum stress and ubiquitination, and gut metagenomic species (MGS). Linear regression analysis to model how changes of select variables over the CR period contribute to changes in IS, showed greatest contributions from gut MGS and fiber intake.Conclusion: This work has enhanced previous knowledge on links between host glucose homeostasis, lifestyle factors and the gut microbiota, and has identified potential biomarkers that may be used in future studies to predict and improve individual response to weight-loss interventions. Furthermore, this is the first study showing integration of the wide ra
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Journal articleMullish BH, Ghani R, McDonald J, et al., 2019,
Faecal microbiota transplant for eradication of multidrug-resistant Enterobacteriaceae: a lesson in applying best practice? Re: 'A five-day course of oral antibiotics followed by faecal transplantation to eradicate carriage of multidrug-resistant Enterobacteriaceae: A Randomized Clinical Trial'
, Clinical Microbiology and Infection, Vol: 25, Pages: 912-913, ISSN: 1198-743X -
Journal articleThomas V, Wang Y, Van Rooij P, et al., 2019,
Mitigating Batrachochytrium salamandrivorans in Europe
, AMPHIBIA-REPTILIA, Vol: 40, Pages: 265-290, ISSN: 0173-5373 -
Journal articleSegal JP, Mullish B, Quraishi MN, et al., 2019,
The application of omics techniques to understand the role of the gut microbiota in inflammatory bowel disease
, Therapeutic Advances in Gastroenterology, Vol: 12, Pages: 1-13, ISSN: 1756-2848The aetiopathogenesis of inflammatory bowel diseases (IBD) involves the complex interaction between a patient’s genetic predisposition, environment, gut microbiota and immune system. Currently, however, it is not known if the distinctive perturbations of the gut microbiota that appear to accompany both Crohn’s disease and ulcerative colitis are the cause of, or the result of, the intestinal inflammation that characterizes IBD.With the utilization of novel systems biology technologies, we can now begin to understand not only details about compositional changes in the gut microbiota in IBD, but increasingly also the alterations in microbiota function that accompany these. Technologies such as metagenomics, metataxomics, metatranscriptomics, metaproteomics and metabonomics are therefore allowing us a deeper understanding of the role of the microbiota in IBD. Furthermore, the integration of these systems biology technologies through advancing computational and statistical techniques are beginning to understand the microbiome interactions that both contribute to health and diseased states in IBD.This review aims to explore how such systems biology technologies are advancing our understanding of the gut microbiota, and their potential role in delineating the aetiology, development and clinical care of IBD.
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Journal articleEyerich K, Brown S, Perez White B, et al., 2019,
Human and computational models of atopic dermatitis: a review and perspectives by an expert panel of the International Eczema Council
, Journal of Allergy and Clinical Immunology, Vol: 143, Pages: 36-45, ISSN: 0091-6749Atopic dermatitis (AD) is a prevalent disease worldwide and is associated with systemic comorbidities representing a significant burden on patients, their families, and society. Therapeutic options for AD remain limited, in part because of a lack of well-characterized animal models. There has been increasing interest in developing experimental approaches to study the pathogenesis of human AD in vivo, in vitro, and in silico to better define pathophysiologic mechanisms and identify novel therapeutic targets and biomarkers that predict therapeutic response. This review critically appraises a range of models, including genetic mutations relevant to AD, experimental challenge of human skin in vivo, tissue culture models, integration of “omics” data sets, and development of predictive computational models. Although no one individual model recapitulates the complex AD pathophysiology, our review highlights insights gained into key elements of cutaneous biology, molecular pathways, and therapeutic target identification through each approach. Recent developments in computational analysis, including application of machine learning and a systems approach to data integration and predictive modeling, highlight the applicability of these methods to AD subclassification (endotyping), therapy development, and precision medicine. Such predictive modeling will highlight knowledge gaps, further inform refinement of biological models, and support new experimental and systems approaches to AD.
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Journal articleYalchin M, Segal JP, Mullish BH, et al., 2019,
Gaps in knowledge and future directions for the use of faecal microbiota transplant in the treatment of inflammatory bowel disease
, Therapeutic Advances in Gastroenterology, Vol: 12, Pages: 175628481989103-175628481989103, ISSN: 1756-2848<jats:p> Faecal microbiota transplant (FMT) has now been established into clinical guidelines for the treatment of recurrent and refractory Clostridioides difficile infection (CDI). Its therapeutic application in inflammatory bowel disease (IBD) is currently at an early stage. To date, there have been four randomized controlled trials for FMT in IBD and a multitude of observational studies. However, significant gaps in our knowledge regarding optimum methods for FMT preparation, technical aspects and logistics of its administration, as well as mechanistic underpinnings, still remain. In this article, we aim to highlight these gaps by reviewing evidence and making key recommendations on the direction of future studies in this field. In addition, we provide an overview of the current evidence of potential mechanisms of FMT in treating IBD. </jats:p>
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