88 research outputs found

    Tracing the Evolution of Competence in Haemophilus influenzae

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    Natural competence is the genetically encoded ability of some bacteria to take up DNA from the environment. Although most of the incoming DNA is degraded, occasionally intact homologous fragments can recombine with the chromosome, displacing one resident strand. This potential to use DNA as a source of both nutrients and genetic novelty has important implications for the ecology and evolution of competent bacteria. However, it is not known how frequently competence changes during evolution, or whether non-competent strains can persist for long periods of time. We have previously studied competence in H. influenzae and found that both the amount of DNA taken up and the amount recombined varies extensively between different strains. In addition, several strains are unable to become competent, suggesting that competence has been lost at least once. To investigate how many times competence has increased or decreased during the divergence of these strains, we inferred the evolutionary relationships of strains using the largest datasets currently available. However, despite the use of three datasets and multiple inference methods, few nodes were resolved with high support, perhaps due to extensive mixing by recombination. Tracing the evolution of competence in those clades that were well supported identified changes in DNA uptake and/or transformation in most strains. The recency of these events suggests that competence has changed frequently during evolution but the poor support of basal relationships precludes the determination of whether non-competent strains can persist for long periods of time. In some strains, changes in transformation have occurred that cannot be due to changes in DNA uptake, suggesting that selection can act on transformation independent of DNA uptake

    The microbiome in bronchiectasis

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    Bronchiectasis is increasing in prevalence worldwide, yet current treatments available are limited to those alleviating symptoms and reducing exacerbations. The pathogenesis of the disease and the inflammatory, infective and molecular drivers of disease progression are not fully understood, making the development of novel treatments challenging. Understanding the role bacteria play in disease progression has been enhanced by the use of next-generation sequencing techniques such as 16S rRNA sequencing. The microbiome has not been extensively studied in bronchiectasis, but existing data show lung bacterial communities dominated by Pseudomonas, Haemophilus and Streptococcus, while exhibiting intraindividual stability and large interindividual variability. Pseudomonas- and Haemophilus-dominated microbiomes have been shown to be linked to severe disease and frequent exacerbations. Studies completed to date are limited in size and do not fully represent all clinically observed disease subtypes. Further research is required to understand the microbiomes role in bronchiectasis disease progression. This review discusses recent developments and future perspectives on the lung microbiome in bronchiectasis

    Heterogeneity of gut microbial responses in healthy household dogs transitioning from an extruded to a mildly cooked diet

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    Background The gut microbiota (GM) is associated with canine health and can be impacted by diet. Dog owners in the U.S. have increasingly shown an interest in feeding their dogs a mildly cooked (MC) diet. However, its impact on canine GM and health remains largely unknown. Methods Healthy household dogs were tracked upon switching from various brands of extruded to MC diets for four weeks. A health assessment was completed and stool samples were collected by each owner before (day 0) and after the diet transition (day 28). Shotgun metagenomic sequencing was performed at both time points to characterize the GM. Results Dogs completed the study by either completing the health assessments (n = 31) or providing stool samples at both time points (n = 28). All owners reported either better or no change in overall health at the end of the study (61% and 39%, respectively), and none reported worse overall health. Defecation frequency was also reported to be lower (58%) or about the same (35%). Principal coordinate (PCo) analysis showed a significant shift (p = 0.004) in the β-diversity of the GM upon diet transition (34.2% and 10.3% explained by the first two axes). The abundances of 70 species increased after the diet change (adjusted p < 0.05), 67% and 24% of which belonged to the Lactobacillales and the Enterobacterales orders respectively. The abundances of 28 species decreased (adjusted p < 0.05), 46%, 18%, and 11% of which belonged to the Clostridiales, Bacillales, and Bacteroidales orders, respectively. Lower Lactobacillales and Enterobacterales, and higher Bacteroidales at baseline were associated with a greater shift along the PCo1 axis. Protein content of the baseline diet was correlated with the shift along the PCo1 axis (ρ = 0.67, p = 0.006). Conclusion Owners reported either improvement or no change in health in dogs transitioning from extruded kibble to MC diets for 4 weeks, but this report of health perception requires further exploration in a controlled trial. Diet change also led to a significant shift in the GM profile of healthy dogs. The magnitude of shift was associated with baseline GM and dietary protein, and warrants further examination of individualized responses and personalized nutrition in companion dogs. These results also support future investigation of the impact of a MC diet on health maintenance given its increasing popularity

    The Upper Respiratory Tract as a Microbial Source for Pulmonary Infections in Cystic Fibrosis. Parallels from Island Biogeography

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    A continuously mixed series of microbial communities inhabits various points of the respiratory tract, with community composition determined by distance from colonization sources, colonization rates, and extinction rates. Ecology and evolution theory developed in the context of biogeography is relevant to clinical microbiology and could reframe the interpretation of recent studies comparing communities from lung explant samples, sputum samples, and oropharyngeal swabs. We propose an island biogeography model of the microbial communities inhabiting different niches in human airways. Island biogeography as applied to communities separated by time and space is a useful parallel for exploring microbial colonization of healthy and diseased lungs, with the potential to inform our understanding of microbial community dynamics and the relevance of microbes detected in different sample types. In this perspective, we focus on the intermixed microbial communities inhabiting different regions of the airways of patients with cystic fibrosis

    The XMM Cluster Survey: X-ray analysis methodology

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    The XMM Cluster Survey (XCS) is a serendipitous search for galaxy clusters using all publicly available data in the XMM-Newton Science Archive. Its main aims are to measure cosmological parameters and trace the evolution of X-ray scaling relations. In this paper we describe the data processing methodology applied to the 5,776 XMM observations used to construct the current XCS source catalogue. A total of 3,675 > 4-sigma cluster candidates with > 50 background-subtracted X-ray counts are extracted from a total non-overlapping area suitable for cluster searching of 410 deg^2. Of these, 993 candidates are detected with > 300 background-subtracted X-ray photon counts, and we demonstrate that robust temperature measurements can be obtained down to this count limit. We describe in detail the automated pipelines used to perform the spectral and surface brightness fitting for these candidates, as well as to estimate redshifts from the X-ray data alone. A total of 587 (122) X-ray temperatures to a typical accuracy of < 40 (< 10) per cent have been measured to date. We also present the methodology adopted for determining the selection function of the survey, and show that the extended source detection algorithm is robust to a range of cluster morphologies by inserting mock clusters derived from hydrodynamical simulations into real XMM images. These tests show that the simple isothermal beta-profiles is sufficient to capture the essential details of the cluster population detected in the archival XMM observations. The redshift follow-up of the XCS cluster sample is presented in a companion paper, together with a first data release of 503 optically-confirmed clusters.Comment: MNRAS accepted, 45 pages, 38 figures. Our companion paper describing our optical analysis methodology and presenting a first set of confirmed clusters has now been submitted to MNRA

    Deciphering colorectal cancer genetics through multi-omic analysis of 100,204 cases and 154,587 controls of European and east Asian ancestries

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    In the version of this article initially published, the author affiliations incorrectly listed “Candiolo Cancer Institute FPO-IRCCS, Candiolo (TO), Italy” as “Candiolo Cancer Institute, Candiolo, Italy.” The change has been made to the HTML and PDF versions of the article

    Risk factors for Coronavirus disease 2019 (Covid-19) death in a population cohort study from the Western Cape province, South Africa

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    Risk factors for coronavirus disease 2019 (COVID-19) death in sub-Saharan Africa and the effects of human immunodeficiency virus (HIV) and tuberculosis on COVID-19 outcomes are unknown. We conducted a population cohort study using linked data from adults attending public-sector health facilities in the Western Cape, South Africa. We used Cox proportional hazards models, adjusted for age, sex, location, and comorbidities, to examine the associations between HIV, tuberculosis, and COVID-19 death from 1 March to 9 June 2020 among (1) public-sector “active patients” (≥1 visit in the 3 years before March 2020); (2) laboratory-diagnosed COVID-19 cases; and (3) hospitalized COVID-19 cases. We calculated the standardized mortality ratio (SMR) for COVID-19, comparing adults living with and without HIV using modeled population estimates.Among 3 460 932 patients (16% living with HIV), 22 308 were diagnosed with COVID-19, of whom 625 died. COVID19 death was associated with male sex, increasing age, diabetes, hypertension, and chronic kidney disease. HIV was associated with COVID-19 mortality (adjusted hazard ratio [aHR], 2.14; 95% confidence interval [CI], 1.70–2.70), with similar risks across strata of viral loads and immunosuppression. Current and previous diagnoses of tuberculosis were associated with COVID-19 death (aHR, 2.70 [95% CI, 1.81–4.04] and 1.51 [95% CI, 1.18–1.93], respectively). The SMR for COVID-19 death associated with HIV was 2.39 (95% CI, 1.96–2.86); population attributable fraction 8.5% (95% CI, 6.1–11.1)
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