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Conference paperGhani R, Gan C, Mullish B, et al., 2019, , AUA 2019, Publisher: Elsevier, ISSN: 0022-5347
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Journal articleAhmed B, Cox M, Cuthbertson L, et al., 2019, , Scientific Reports, Vol: 9, ISSN: 2045-2322
The pathogenesis of airway infection in cystic fibrosis (CF) is poorly understood. We performed a longitudinal study coupling clinical information with frequent sampling of the microbiota to identify changes in the airway microbiota in infancy that could underpin deterioration and potentially be targeted therapeutically. Thirty infants with CF diagnosed on newborn screening (NBS) were followed for up to two years. Two hundred and forty one throat swabs were collected as a surrogate for lower airway microbiota (median 35 days between study visits) in the largest longitudinal study of the CF oropharyngeal microbiota. Quantitative PCR and Illumina sequencing of the 16S rRNA bacterial gene were performed. Data analyses were conducted in QIIME and Phyloseq in R. Streptococcus spp. and Haemophilus spp. were the most common genera (55% and 12.5% of reads respectively) and were inversely related. Only beta (between sample) diversity changed with age (Bray Curtis r2 = 0.15, P = 0.03). Staphylococcus and Pseudomonas were rarely detected. These results suggest that Streptococcus spp. and Haemophilus spp., may play an important role in early CF. Whether they are protective against infection with more typical CF micro-organisms, or pathogenic and thus meriting treatment needs to be determined.
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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, , Human Microbiome Journal, Vol: 11, Pages: 100045-100045, ISSN: 2452-2317
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Journal articleWootton DG, Cox MJ, Gloor GB, et al., 2019, , Scientific Reports, Vol: 9, ISSN: 2045-2322
The 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, , Frontiers in Physiology, Vol: 9, ISSN: 1664-042X
Background: 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, , Clinical Microbiology and Infection, Vol: 25, Pages: 912-913, ISSN: 1198-743X
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Journal articleThomas V, Wang Y, Van Rooij P, et al., 2019, , AMPHIBIA-REPTILIA, Vol: 40, Pages: 265-290, ISSN: 0173-5373
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Journal articleSegal JP, Mullish B, Quraishi MN, et al., 2019, , Therapeutic Advances in Gastroenterology, Vol: 12, Pages: 1-13, ISSN: 1756-2848
The 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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