COVID-19 represents a global crisis, yet major knowledge gaps remain about human immunity to SARS-CoV-2. We analyzed immune responses in 76 COVID-19 patients and 69 healthy individuals from Hong Kong and Atlanta. In PBMCs of COVID-19 patients, there was reduced expression of HLA-DR and pro-inflammatory cytokines by myeloid cells, and impaired mTOR-signaling and IFN-α production by plasmacytoid DCs. In contrast, there were enhanced plasma levels of inflammatory mediators, including EN-RAGE, TNFSF14, and oncostatin-M, which correlated with disease severity and increased bacterial products in human plasma. Single-cell transcriptomics revealed no type-I IFN, reduced HLA-DR in myeloid cells of severe patients, and transient expression of IFN-stimulated genes. This was consistent with bulk PBMC transcriptomics, and transient, low plasma IFN-α levels during infection. These results reveal mechanisms and potential therapeutic targets for COVID-19.
Interventional studies on genetic modulators of longevity have significantly changed gerontology. While available lifespan data is continually accumulating, further understanding of the aging process is still limited by the poor understanding of epistasis and of the non-linear interactions between multiple longevity-associated genes. Unfortunately, based on observations so far, there is no simple method to predict the cumulative impact of genes on lifespan. As a step towards applying predictive methods, but also to provide information for a guided design of epistasis lifespan experiments, we developed SynergyAge - a database containing genetic and lifespan data for animal models obtained through multiple longevity-modulating interventions. The studies included in SynergyAge focus on the lifespan of animal strains which are modified by at least two genetic interventions, with single gene mutants included as reference. SynergyAge, which is publicly available at www.synergyage.info, provides an easy to use web-platform for browsing, searching and filtering through the data, as well as a network-based interactive module for visualization and analysis. Database URL: http://www.synergyage.info/### Competing Interest StatementThe authors have declared no competing interest.
The transition from mitosis into the first gap phase of the cell cycle in budding yeast is controlled by the Mitotic Exit Network (MEN). The network interprets spatio-temporal cues about the progression of mitosis and ensures that release of Cdc14 phosphatase occurs only after completion of key mitotic events. The MEN has been studied intensively however a unified understanding of how localization and protein activity function together as a system is lacking. In this paper we present a compartmental, logical model of the MEN that is capable of representing spatial aspects of regulation in parallel to control of enzymatic activity. Through optimization of the model, we reveal insights into role of Cdc5 in Cdc15 localization and the importance of Lte1 regulation in control of Bfa1. We show that our model is capable of correctly predicting the phenotype of ∼80% of mutants we tested, including mutants representing mislocalizing proteins. We use a continuous time implementation of the model to demonstrate the role of Cdc14 Early Anaphase Release (FEAR) to ensure robust timing of anaphase and verify our findings in living cells. We show that our model can represent measured cell-cell variation in Spindle Position Checkpoint (SPoC) mutants. Finally, we use the model to predict the impact of forced localization of MEN proteins and validate these predictions experimentally. This model represents a unified view of the mechanism of mitotic exit control### Competing Interest StatementThe authors have declared no competing interest.
Time-lapse live cell imaging of a growing cell population is routine in many biological investigations. A major challenge in imaging analysis is accurate segmentation, a process to define the boundaries of cells based on raw image data. Current segmentation methods relying on single boundary features have problems in robustness when dealing with inhomogeneous foci which invariably happens in cell population imaging. Here, we demonstrated that combined with multi-layer training set strategy, a neural-network-based algorithm Cellbow can achieve accurate and robust segmentation of cells in broad and general settings. It can also facilitate long-term tracking of cell growth and division. Furthermore, Cellbow is customizable and generalizable. It is broadly applicable to segmenting fluorescent images of diverse cell types with no further training needed. For bright- field images, only a small set of sample images of the specific cell type from the user may be needed for training. To facilitate the application of Cellbow, we provide a website on which one can online test the software, as well as an ImageJ plugin for the user to visualize the performance before software installation.### Competing Interest StatementThe authors have declared no competing interest.
Osteocytes are master regulators of the skeleton. We map the transcriptome of osteocytes at different skeletal sites, across age and sexes in mice to reveal genes and molecular programs that control this complex cell-network. We define an osteocyte transcriptome signature, 1239 genes that distinguishes osteocytes from other cells. 77% have no known role in the skeleton. We show they are enriched for genes controlling neuronal network formation, suggesting this program is important in the osteocyte network. We evaluated 19 skeletal parameters in 733 mouse lines with functional-gene-deletions and reveal 26 osteocyte transcriptome signature genes that control bone structure and function. We showed osteocyte transcriptome signature genes are enriched for human homologues that cause monogenic skeletal dysplasias (P=6x10-17), and associated with polygenic diseases, osteoporosis (P=1.8x10-13), and osteoarthritis (P=2.6x10-6). This reveals the molecular landscape that regulates osteocyte network formation and function, and establishes the importance of osteocytes in human skeletal disease.### Competing Interest StatementT.G.P is a consultant for Imugene Pty Ltd, an Australian biotech working in cancer immunotherapy. P.I.C has funding from AMGEN for studies of cancer dormancy. Neither competing interests are the subject of this manuscript.
Sara Suzuki, Beverly Errede, Henrik Dohlman, Timothy Elston
Published: Apr 2020
Cells rely on mitogen-activated protein kinases (MAPKs) to survive environmental stress. In yeast, activation of the MAPK Hog1 is known to mediate the response to high osmotic conditions. Recent studies of Hog1 revealed that its temporal activity is subject to both negative and positive feedback regulation, yet the mechanisms of feedback remain unclear. By designing mathematical models of increasing complexity for the Hog1 MAPK cascade, we identified pathway circuitry sufficient to capture Hog1 dynamics observed in vivo. We used these models to optimize experimental designs for distinguishing potential feedback loops. Performing experiments based on these models revealed mutual inhibition between Hog1 and its phosphatases as the likely positive feedback mechanism underlying switch-like, dose-dependent MAPK activation. Importantly, our findings reveal a new signaling function for MAPK phosphatases. More broadly, they demonstrate the value using mathematical models to infer targets of feedback regulation in signaling pathways.### Competing Interest StatementThe authors have declared no competing interest.
mRNA splicing is one of the key processes in eukaryotic gene expression. Most Intron-containing genes are constitutively spliced, and hence must undergo splicing in order to produce a functional mature mRNA. Therefore, regulation of splicing efficiency greatly affects broader gene expression regulation. Here we use a large synthetic oligo library of ~25,000 variants to explore how different intronic sequence determinants affect splicing efficiency and mRNA expression levels in yeast. We found that the three splice sites (donor, acceptor, and branching point) differ in how deviations from the consensus sequence affect functionality. We also use intronic sequences from other yeast species with modified splicing machinery to show that intron architecture has co-evolved with the splicing machinery to adapt to the presence or absence of a specific splicing factor. Finally, we show that synthetic sequences containing two introns give rise to diverse RNA isoforms, which enables us to elucidate intronic features that control and enable alternative splicing. Our study reveals novel mechanisms by which introns are shaped in evolution to allow cells to regulate their transcriptome.### Competing Interest StatementThe authors have declared no competing interest.
We dissect the mechanism of SARS-CoV-2 in human lung host from the initial phase of receptor binding to viral replication machinery. We constructed two independent lung protein interactome to reveal the signaling process on receptor activation and host protein hijacking machinery in the pathogenesis of virus. Further, we test the functional role of the hubs derived from both interactome. Most hubs proteins were differentially regulated on SARS-CoV-2 infection. Also, the proteins of viral replication hubs were related with cardiovascular disease, diabetes and hypertension confirming the vulnerability and severity of infection in the risk individual. Additionally, the hub proteins were closely linked with other viral infection, including MERS and HCoVs which suggest similar infection pattern in SARS-CoV-2. We identified five interconnecting cascades between hubs of both networks that show the preparation of optimal environment in the host for viral replication process upon receptor attachment. Interestingly, we propose that seven potential miRNAs, targeting the intermediate phase that connects receptor and viral replication process a better choice as a drug for SARS-CoV-2.### Competing Interest StatementThe authors have declared no competing interest.
Gregory Kimmel, Mark Dane, Laura Heiser, Philipp Altrock, Noemi Andor
Published: Apr 2020
Breast cancer progresses in a multistep process from primary tumor growth and stroma invasion to metastasis. Progression is accompanied by a switch to an invasive cell phenotype. Nutrient-limiting environments exhibit chemotaxis with aggressive morphologies characteristic of invasion. The mTOR pathway senses essential nutrients, informing the cell to respond with either increased chemotaxis and nutrient uptake or cell cycle progression. Randomized clinical trials have shown that mTOR inhibitors (mTOR-I) improve the outcome of metastatic breast cancer patients. However, there are considerable differences between and within tumors that impact the effectiveness of mTOR-I, including differences in access to nutrients. It is unknown how co-existing cells differ in their response to nutrient limitations and how this impacts invasion of the metapopulation as a whole. We integrate modeling with microenvironmental perturbations data to investigate invasion in nutrient-limiting environments inhabited by one or two cancer cell subpopulations. Hereby subpopulations are defined by their energy efficiency and chemotactic ability. We calculate the invasion-distance traveled by a homogeneous population. For heterogeneous populations, our results suggest that an imbalance between nutrient efficacy and chemotactic superiority accelerates invasion. Such imbalance will segregate the two populations spatially and only one type will dominate at the invasion front. Only if these two phenotypes are balanced do the two populations compete for the same space, which decelerates invasion. We investigate ploidy as a candidate biomarker of this phenotypic heterogeneity to discern circumstances when inhibiting chemotaxis amplifies innternal competition and decelerates tumor progression, from circumstances that render clinical consequences of chemotactic inhibition unfavorable.### Competing Interest StatementThe authors have declared no competing interest.