Global Gene Expression and Systems Biology Analysis of Bovine Monocyte-Derived Macrophages in Response to In Vitro Challenge with Mycobacterium bovis

peer-reviewedBackground Mycobacterium bovis, the causative agent of bovine tuberculosis, is a major cause of mortality in global cattle populations. Macrophages are among the first cell types to encounter M. bovis following exposure and the response elicited by these cells is pivotal in determining the outcome of infection. Here, a functional genomics approach was undertaken to investigate global gene expression profiles in bovine monocyte-derived macrophages (MDM) purified from seven age-matched non-related females, in response to in vitro challenge with M. bovis (multiplicity of infection 2:1). Total cellular RNA was extracted from non-challenged control and M. bovis-challenged MDM for all animals at intervals of 2 hours, 6 hours and 24 hours post-challenge and prepared for global gene expression analysis using the Affymetrix® GeneChip® Bovine Genome Array. Results Comparison of M. bovis-challenged MDM gene expression profiles with those from the non-challenged MDM controls at each time point identified 3,064 differentially expressed genes 2 hours post-challenge, with 4,451 and 5,267 differentially expressed genes detected at the 6 hour and 24 hour time points, respectively (adjusted P-value threshold ≤0.05). Notably, the number of downregulated genes exceeded the number of upregulated genes in the M. bovis-challenged MDM across all time points; however, the fold-change in expression for the upregulated genes was markedly higher than that for the downregulated genes. Systems analysis revealed enrichment for genes involved in: (1) the inflammatory response; (2) cell signalling pathways, including Toll-like receptors and intracellular pathogen recognition receptors; and (3) apoptosis. Conclusions The increased number of downregulated genes is consistent with previous studies showing that M. bovis infection is associated with the repression of host gene expression. The results also support roles for MyD88-independent signalling and intracellular PRRs in mediating the host response to M. bovis.Science Foundation Ireland (www.sfi.ie) Investigator grants (Nos: SFI/01/F.1/B028 and SFI/08/IN.1/B2038); Department of Agriculture, Fisheries and Food (www.agriculture.ie) Research Stimulus Grant (No: RSF 06 405); European Union Framework 7 (http://cordis.europa.eu/fp7) Project Grant (No: KBBE-211602-MACROSYS); Irish Research Council for Science, Engineering and Technology (IRCSET) funded Bioinformatics and Systems Biology PhD Programme (http://bioinfo-casl.ucd.ie/PhD)

The census as an information source in public policy-making

This paper provides an assessment of the value of national population censuses as information sources with specific reference toUK census data and its use in policy-making. Mixed methods were adopted to collect quantitative and qualitative data from twosources: (1) a content analysis of policy documents, and (2) interviews with policy-makers in Scotland. The findings highlight thatalthough the general value of the census is recognised, policy-makers are not necessarily closely engaged with the census as a toolfor directing the development and implementation of policy. This is evident, for example in a lack of awareness of proposed changesto the census, and infrequent deployment of available data. The opportunity to change perceptions among policy-makers, and toexpand the application of census data in public policy, is identified. With a novel focus on the deployment of censuses as sources ofevidence for policy-making that includes the views of policy-makers from both within and beyond government, this workcontributes to an established body of global research on international censuses

COVID-19 trajectories among 57 million adults in England: a cohort study using electronic health records

BACKGROUND: Updatable estimates of COVID-19 onset, progression, and trajectories underpin pandemic mitigation efforts. To identify and characterise disease trajectories, we aimed to define and validate ten COVID-19 phenotypes from nationwide linked electronic health records (EHR) using an extensible framework. METHODS: In this cohort study, we used eight linked National Health Service (NHS) datasets for people in England alive on Jan 23, 2020. Data on COVID-19 testing, vaccination, primary and secondary care records, and death registrations were collected until Nov 30, 2021. We defined ten COVID-19 phenotypes reflecting clinically relevant stages of disease severity and encompassing five categories: positive SARS-CoV-2 test, primary care diagnosis, hospital admission, ventilation modality (four phenotypes), and death (three phenotypes). We constructed patient trajectories illustrating transition frequency and duration between phenotypes. Analyses were stratified by pandemic waves and vaccination status. FINDINGS: Among 57 032 174 individuals included in the cohort, 13 990 423 COVID-19 events were identified in 7 244 925 individuals, equating to an infection rate of 12·7% during the study period. Of 7 244 925 individuals, 460 737 (6·4%) were admitted to hospital and 158 020 (2·2%) died. Of 460 737 individuals who were admitted to hospital, 48 847 (10·6%) were admitted to the intensive care unit (ICU), 69 090 (15·0%) received non-invasive ventilation, and 25 928 (5·6%) received invasive ventilation. Among 384 135 patients who were admitted to hospital but did not require ventilation, mortality was higher in wave 1 (23 485 [30·4%] of 77 202 patients) than wave 2 (44 220 [23·1%] of 191 528 patients), but remained unchanged for patients admitted to the ICU. Mortality was highest among patients who received ventilatory support outside of the ICU in wave 1 (2569 [50·7%] of 5063 patients). 15 486 (9·8%) of 158 020 COVID-19-related deaths occurred within 28 days of the first COVID-19 event without a COVID-19 diagnoses on the death certificate. 10 884 (6·9%) of 158 020 deaths were identified exclusively from mortality data with no previous COVID-19 phenotype recorded. We observed longer patient trajectories in wave 2 than wave 1. INTERPRETATION: Our analyses illustrate the wide spectrum of disease trajectories as shown by differences in incidence, survival, and clinical pathways. We have provided a modular analytical framework that can be used to monitor the impact of the pandemic and generate evidence of clinical and policy relevance using multiple EHR sources. FUNDING: British Heart Foundation Data Science Centre, led by Health Data Research UK

The number of significantly differentially expressed genes at each time point post-<i>M. bovis</i> challenge.

<p>The number of upregulated and downregulated genes in the <i>M. bovis</i>-challenged MDM relative to the control MDM at each time point are shown (adjusted <i>P</i>-value 0.05).</p

Principal component analysis for all individual control and <i>M. bovis</i>-challenged MDM at the 2 hour, 6 hour and 24 hour time points.

<p>Principal component (PC) 1 and PC2 are shown (accounting for 23.31% and 17.05% of the total variation, respectively). PCA was performed using data for all genes whose probes passed the data filtering process with Euclidean distance as the distance metric.</p

Schematic depicting the experimental design used in the current study.

<p>MDM were cultured in 24-well tissue culture plates (2×10⁵ cells per well) and challenged with <i>M. bovis</i> (MOI 2∶1). RNA was extracted from <i>M.bovis</i>-challenged and non-challenged control MDM at three time points post-challenge: 2 hours, 6 hours and 24 hours. In addition, RNA was extracted from a 0 hour non-challenged control to assess potential non-experimental changes in gene expression. The MDM lysates from replicate tissue culture wells (shaded) were pooled for RNA extraction. Global gene expression for the control and <i>M. bovis</i>-challenged MDM was analysed using the Affymetrix® GeneChip® Bovine Genome Array.</p