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Chambers, B.

Publications and source records attributed to Chambers, B..

3 recordsLinked to original sources

Stimulation with mycobacterial glycolipids and PPD reveals different innate immune response profiles in active and latent TB

Upon infection with Mycobacterium tuberculosis (Mtb) the host immune response might clear the bacteria, control its growth leading to latent tuberculosis (LTB), or fail to control its growth resulting in active TB (ATB). There is however no clear understanding of the features underlying a more or less effective response. Mtb glycolipids are abundant in the bacterial cell envelope and modulate the immune response to Mtb, but the patterns of response to glycolipids are still underexplored. To identify the CD45+ leukocyte activation landscape induced by Mtb glycolipids in peripheral blood of ATB and LTB, we performed a detailed assessment of the immune response of PBMCs to the Mtb glycolipids lipoarabinomannan (LAM) and its biosynthetic precursor phosphatidyl-inositol mannoside (PIM), and PPD. At 24 h and 5 days of stimulation, cell profiling and secretome analysis was done using mass cytometry and high-multiplex immunoassay. PIM mainly affected antigen-presenting cells to produce both proinflammatory (IL-2, IL-6, IL-17A, TNF- and GM-CSF), and IL-4 and IL-10 cytokines, but not IFN-{gamma}. LAM triggered a similar, albeit weaker, response. By contrast, PPD induced an increase in IFN-{gamma}-producing cells. Moreover, PPD also led to increased numbers of IL-2, IL-6, IL-10, IL-17A, TNF- and GrzB-producing cells. Treatment with an anti-TLR2 antibody led to partial inhibition of PIM-induced IL-6 production in myeloid cells, suggesting that PIM induces IL-6 production through TLR2. Expansion of monocyte subsets in response to PIM or LAM was reduced in both ATB and LTB as compared to healthy controls, suggesting a hyporesponsive/tolerance pattern in Mtb-infected individuals.

immunology↗

FOXO1 and FOXO3 cooperatively regulate innate lymphoid cell development

The natural killer (NK) and non-cytotoxic innate lymphoid cells (ILC) lineages play vital role in the regulation of the immune system. Yet understanding of mechanisms controlling NK/ILC development remains incomplete. The evolutionary conserved FOXO family of forkhead transcription factors are critical regulators of cellular processes. We found that the loss of FOXO1 and FOXO3 together caused impaired activation of the NK gene expression program and reduced ETS binding already at the common lymphoid progenitor (CLP) level and a block at the ILC progenitor (ILCP) to NK progenitor transition. FOXO controlled NK cell maturation in organ specific manner and their ability to respond to IL-15. At the ILCP level, disruption of the ILC lineage specific gene programs was associated with broad perturbation of the generation of the non-cytotoxic ILC subsets. We concluded that FOXO1 and FOXO3 cooperatively regulate ILC lineage specification at the progenitor level as well as the generation of mature ILCs.

cell biology↗

NERO: A Biomedical Named-entity (Recognition) Ontology with a Large, Annotated Corpus Reveals Meaningful Associations Through Text Embedding

Machine reading is essential for unlocking valuable knowledge contained in the millions of existing biomedical documents. Over the last two decades 1,2, the most dramatic advances in machine-reading have followed in the wake of critical corpus development3. Large, well-annotated corpora have been associated with punctuated advances in machine reading methodology and automated knowledge extraction systems in the same way that ImageNet 4 was fundamental for developing machine vision techniques. This study contributes six components to an advanced, named-entity analysis tool for biomedicine: (a) a new, Named-Entity Recognition Ontology (NERO) developed specifically for describing entities in biomedical texts, which accounts for diverse levels of ambiguity, bridging the scientific sublanguages of molecular biology, genetics, biochemistry, and medicine; (b) detailed guidelines for human experts annotating hundreds of named-entity classes; (c) pictographs for all named entities, to simplify the burden of annotation for curators; (d) an original, annotated corpus comprising 35,865 sentences, which encapsulate 190,679 named entities and 43,438 events connecting two or more entities; (e) validated, off-the-shelf, named-entity recognition automated extraction, and; (f) embedding models that demonstrate the promise of biomedical associations embedded within this corpus.

systems biology↗