RESUMO
Predicting a multicellular organisms phenotype quantitatively from its genotype is challenging, as genetic effects must propagate across scales. Circadian clocks are intracellular regulators that control temporal gene expression patterns and hence metabolism, physiology and behaviour. Here we explain and predict canonical phenotypes of circadian timing in a multicellular, model organism. We used diverse metabolic and physiological data to combine and extend mathematical models of rhythmic gene expression, photoperiod-dependent flowering, elongation growth and starch metabolism within a Framework Model for the vegetative growth of Arabidopsis thaliana, sharing the model and data files in a structured, public resource. The calibrated model predicted the effect of altered circadian timing upon each particular phenotype in clock-mutant plants under standard laboratory conditions. Altered night-time metabolism of stored starch accounted for most of the decrease in whole-plant biomass, as previously proposed. Mobilisation of a secondary store of malate and fumarate was also mis-regulated, accounting for any remaining biomass defect. We test three candidate mechanisms for the accumulation of these organic acids. Our results link genotype through specific processes to higher-level phenotypes, formalising our understanding of a subtle, pleiotropic syndrome at the whole-organism level, and validating the systems approach to understand complex traits starting from intracellular circuits. This work updates the first biorXiv version, February 2017, https://doi.org/10.1101/105437, with an expanded description and additional analysis of the same core data sets and the same FMv2 model, summary tables and supporting, follow-on data from three further studies with further collaborators. This biorXiv revision constitutes the second version of this report.
RESUMO
Infection with SARS-CoV-2 has caused a pandemic of unprecedented dimensions. SARS-CoV-2 infects airway and lung cells causing viral pneumonia. The importance of type I interferon (IFN) production for the control of SARS-CoV-2 infection is highlighted by the increased severity of COVID-19 in patients with inborn errors of type I IFN response or auto-antibodies against IFN-. Plasmacytoid dendritic cells (pDCs) are a unique immune cell population specialized in recognizing and controlling viral infections through the production of high concentrations of type I IFN. In this study, we isolated pDCs from healthy donors and showed that pDCs are able to recognize SARS-CoV-2 and rapidly produce large amounts of type I IFN. Sensing of SARS-CoV-2 by pDCs was independent of viral replication since pDCs were also able to recognize UV-inactivated SARS-CoV-2 and produce type I IFN. Transcriptional profiling of SARS-CoV-2 and UV-SARS-CoV-2 stimulated pDCs also showed a rapid type I and III IFN response as well as induction of several chemokines, and the induction of apoptosis in pDCs. Moreover, we modeled SARS-CoV-2 infection in the lung using primary human airway epithelial cells (pHAEs) and showed that co-culture of pDCs with SARS-CoV-2 infected pHAEs induces an antiviral response and upregulation of antigen presentation in pHAE cells. Importantly, the presence of pDCs in the co-culture results in control of SARS-CoV-2 replication in pHAEs. Our study identifies pDCs as one of the key cells that can recognize SARS-CoV-2 infection, produce type I and III IFN and control viral replication in infected cells. ImportanceType I interferons (IFNs) are a major part of the innate immune defense against viral infections. The importance of type I interferon (IFN) production for the control of SARS-CoV-2 infection is highlighted by the increased severity of COVID-19 in patients with defects in the type I IFN response. Interestingly, many cells are not able to produce type I IFN after being infected with SARS-CoV-2 and cannot control viral infection. In this study we show that plasmacytoid dendritic cells are able to recognize SARS-CoV-2 and produce type I IFN, and that pDCs are able to help control viral infection in SARS-CoV-2 infected airway epithelial cells.