The Human Lung Cell Atlas: A High-Resolution Reference Map of the Human Lung in Health and Disease.

Lung disease accounts for every sixth death globally. Profiling the molecular state of all lung cell types in health and disease is currently revolutionizing the identification of disease mechanisms and will aid the design of novel diagnostic and personalized therapeutic regimens. Recent progress in high-throughput techniques for single-cell genomic and transcriptomic analyses has opened up new possibilities to study individual cells within a tissue, classify these into cell types, and characterize variations in their molecular profiles as a function of genetics, environment, cell-cell interactions, developmental processes, aging, or disease. Integration of these cell state definitions with spatial information allows the in-depth molecular description of cellular neighborhoods and tissue microenvironments, including the tissue resident structural and immune cells, the tissue matrix, and the microbiome. The Human Cell Atlas consortium aims to characterize all cells in the healthy human body and has prioritized lung tissue as one of the flagship projects. Here, we present the rationale, the approach, and the expected impact of a Human Lung Cell Atlas.Supported by the Helmholtz Association and the German Center for Lung Research (DZL) (H.B.S.); the European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement 753039 (L.M.S.); U.K. Medical Research Council grant G0900424 (E.L.R.); National Institutes of Health (NIH) grants ES013995, HL071643, and AG049665, and Veterans Administration grant BX000201 and Department of Defense grant PR141319 (G.R.S.B.); NIH grants HL135124 and AI135964 and Department of Defense grant PR141319 (A.V.M.); NIH grants R01HL141852, R01HL127349, UHHL3123886, U01HL122626, and UG3TR002445, and Department of Defence grant PR151124 (N.K.); and the Netherlands Lung Foundation grants 5.1.14.020 and 4.1.18.226 (M.C.N.)

SARS-CoV-2 Receptor ACE2 Is an Interferon-Stimulated Gene in Human Airway Epithelial Cells and Is Detected in Specific Cell Subsets across Tissues.

There is pressing urgency to understand the pathogenesis of the severe acute respiratory syndrome coronavirus clade 2 (SARS-CoV-2), which causes the disease COVID-19. SARS-CoV-2 spike (S) protein binds angiotensin-converting enzyme 2 (ACE2), and in concert with host proteases, principally transmembrane serine protease 2 (TMPRSS2), promotes cellular entry. The cell subsets targeted by SARS-CoV-2 in host tissues and the factors that regulate ACE2 expression remain unknown. Here, we leverage human, non-human primate, and mouse single-cell RNA-sequencing (scRNA-seq) datasets across health and disease to uncover putative targets of SARS-CoV-2 among tissue-resident cell subsets. We identify ACE2 and TMPRSS2 co-expressing cells within lung type II pneumocytes, ileal absorptive enterocytes, and nasal goblet secretory cells. Strikingly, we discovered that ACE2 is a human interferon-stimulated gene (ISG) in vitro using airway epithelial cells and extend our findings to in vivo viral infections. Our data suggest that SARS-CoV-2 could exploit species-specific interferon-driven upregulation of ACE2, a tissue-protective mediator during lung injury, to enhance infection

Emergence of division of labor in tissues through cell interactions and spatial cues

Summary: Most cell types in multicellular organisms can perform multiple functions. However, not all functions can be optimally performed simultaneously by the same cells. Functions incompatible at the level of individual cells can be performed at the cell population level, where cells divide labor and specialize in different functions. Division of labor can arise due to instruction by tissue environment or through self-organization. Here, we develop a computational framework to investigate the contribution of these mechanisms to division of labor within a cell-type population. By optimizing collective cellular task performance under trade-offs, we find that distinguishable expression patterns can emerge from cell-cell interactions versus instructive signals. We propose a method to construct ligand-receptor networks between specialist cells and use it to infer division-of-labor mechanisms from single-cell RNA sequencing (RNA-seq) and spatial transcriptomics data of stromal, epithelial, and immune cells. Our framework can be used to characterize the complexity of cell interactions within tissues

The effect of screening on the x and Q"2 behaviour of F_2 slopes

A systematic study of #partial deriv#F_2(x,Q"2)/#partial deriv#lnQ"2 and #partial deriv#lnF_2(x,Q"2)/#partial deriv#ln(1/x) is carried out in pQCD taking screening corrections into account. The result of calculations, which are different from the non screened DGLAP prediction, are compared and shown to agree with the available experimental data as well as a pseudo data base generated from the ALLM'97 parameterization. This pseudo data base allows us to study in detail our predictions over a wider kinematic region than is available experimentally, and allows us to give recommendations for a future experiment. Our results are compared with the GRV'94 parameterization (which is used as an input for our calculations) as well as the recently proposed MRST structure functions. (orig.)Available from TIB Hannover: RA 2999(98-102) / FIZ - Fachinformationszzentrum Karlsruhe / TIB - Technische InformationsbibliothekSIGLEDEGerman

The Human Lung Cell Atlas: A High-Resolution Reference Map of the Human Lung in Health and Disease.

Lung disease accounts for every sixth death globally. Profiling the molecular state of all lung cell types in health and disease is currently revolutionizing the identification of disease mechanisms and will aid the design of novel diagnostic and personalized therapeutic regimens. Recent progress in high-throughput techniques for single-cell genomic and transcriptomic analyses has opened up new possibilities to study individual cells within a tissue, classify these into cell types, and characterize variations in their molecular profiles as a function of genetics, environment, cell-cell interactions, developmental processes, aging, or disease. Integration of these cell state definitions with spatial information allows the in-depth molecular description of cellular neighborhoods and tissue microenvironments, including the tissue resident structural and immune cells, the tissue matrix, and the microbiome. The Human Cell Atlas consortium aims to characterize all cells in the healthy human body and has prioritized lung tissue as one of the flagship projects. Here, we present the rationale, the approach, and the expected impact of a Human Lung Cell Atlas.Supported by the Helmholtz Association and the German Center for Lung Research (DZL) (H.B.S.); the European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement 753039 (L.M.S.); U.K. Medical Research Council grant G0900424 (E.L.R.); National Institutes of Health (NIH) grants ES013995, HL071643, and AG049665, and Veterans Administration grant BX000201 and Department of Defense grant PR141319 (G.R.S.B.); NIH grants HL135124 and AI135964 and Department of Defense grant PR141319 (A.V.M.); NIH grants R01HL141852, R01HL127349, UHHL3123886, U01HL122626, and UG3TR002445, and Department of Defence grant PR151124 (N.K.); and the Netherlands Lung Foundation grants 5.1.14.020 and 4.1.18.226 (M.C.N.)

COVID-19 in Patients with Inflammatory Bowel Disease: The Israeli Experience

Background: Crohn’s disease (CD) and ulcerative colitis (UC) are chronic, immune-mediated inflammatory bowel diseases (IBD) affecting millions of people worldwide. IBD therapies, designed for continuous immune suppression, often render patients more susceptible to infections. The effect of the immune suppression on the risk of coronavirus disease-19 (COVID-19) is not fully determined yet. Objective: To describe COVID-19 characteristics and outcomes and to evaluate the association between IBD phenotypes, infection outcomes and immunomodulatory therapies. Methods: In this multi-center study, we prospectively followed IBD patients with proven COVID-19. De-identified data from medical charts were collected including age, gender, IBD type, IBD clinical activity, IBD treatments, comorbidities, symptoms and outcomes of COVID-19. A multivariable regression model was used to examine the effect of immunosuppressant drugs on the risk of infection by COVID-19 and the outcomes. Results: Of 144 IBD patients, 104 (72%) were CD and 40 (28%) were UC. Mean age was 32.2 ± 12.6 years. No mortalities were reported. In total, 94 patients (65.3%) received biologic therapy. Of them, 51 (54%) at escalated doses, 10 (11%) in combination with immunomodulators and 9 (10%) with concomitant corticosteroids. Disease location, behavior and activity did not correlate with the severity of COVID-19. Biologics as monotherapy or with immunomodulators or corticosteroids were not associated with more severe infection. On the contrary, patients receiving biologics had significantly milder infection course (p = 0.001) and were less likely to be hospitalized (p = 0.001). Treatment was postponed in 34.7% of patients until recovery from COVID-19, without consequent exacerbation. Conclusion: We did not witness aggravated COVID-19 outcomes in patients with IBD. Patients treated with biologics had a favorable outcome

Chronic lung diseases are associated with gene expression programs favoring SARS-CoV-2 entry and severity

AbstractPatients with chronic lung disease (CLD) have an increased risk for severe coronavirus disease-19 (COVID-19) and poor outcomes. Here, we analyze the transcriptomes of 611,398 single cells isolated from healthy and CLD lungs to identify molecular characteristics of lung cells that may account for worse COVID-19 outcomes in patients with chronic lung diseases. We observe a similar cellular distribution and relative expression of SARS-CoV-2 entry factors in control and CLD lungs. CLD AT2 cells express higher levels of genes linked directly to the efficiency of viral replication and the innate immune response. Additionally, we identify basal differences in inflammatory gene expression programs that highlight how CLD alters the inflammatory microenvironment encountered upon viral exposure to the peripheral lung. Our study indicates that CLD is accompanied by changes in cell-type-specific gene expression programs that prime the lung epithelium for and influence the innate and adaptive immune responses to SARS-CoV-2 infection.</jats:p