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Vasilescu, D.

Publications and source records attributed to Vasilescu, D..

3 recordsLinked to original sources

Lung spatial profiling reveals a T cell signature in COPD patients with fatal SARS-CoV-2 infection

RationalePeople with pre-existing lung diseases like chronic obstructive pulmonary disease (COPD) are more likely to get very sick from SARS-CoV-2 disease 2019 (COVID-19), but an interrogation of the immune response to COVID-19 infection, spatial throughout the lung structure is lacking in patients with COPD. ObjectivesTo profile the immune microenvironment of lung parenchyma, airways, and vessels of never- and ever-smokers with or without COPD, whom all died of COVID-19, using spatial transcriptomic and proteomic profiling. FindingsThe parenchyma, airways, and vessels of COPD patients, compared to control lungs had: 1) significant enrichment for lung resident CD45RO+ memory T cells; 2) downregulation of genes associated with T cell antigen-priming and memory T cell differentiation; 3) higher expression of proteins associated with SARS-CoV-2 entry and major receptor ubiquitously across the ROIs and in particular the lung parenchyma, despite similar SARS-CoV-2 structural gene expression levels. ConclusionsThe lung parenchyma, airways, and vessels of COPD patients have increased T-lymphocytes with a blunted memory T cell response and a more invasive SARS-CoV-2 infection pattern, and may underlie the higher death toll observed with COVID-19.

immunology↗

Molecular Process Diagram: a precise, scalable and compact visualization of rule-based models

Rule-based modeling allows representation and simulation of biological systems where molecular features (such as protein domains) and feature-specific details of molecular interactions are accounted for. The rule-based description is precise and can define very fine molecular details (e.g. how phosphorylation status of a single residue in a multi-protein complex can affect affinity of another binding site of another protein within the same complex), but makes it difficult to effectively combine the assumptions scribed within the multiple rules of a model into a diagrammatic view. Various visualization schemas have been suggested, but they are all highly rule-based centric (e.g. a visual list of unconnected rules, extended contact maps, or atom-rule graphs). None of them match the clarity of traditional reaction/pathway diagrams, where a researcher can easily visually track the transitions and modifications of chemical species occurring in the biological systems being modeled. Here we present a novel approach and software for precise, scalable and compact representation of rule-based models that we call Molecular Process Diagram. It is based on the three basic elements: interacting molecular complexes, molecular sites directly modified by a rule, and molecular sites that are not modified but contribute to a rule mechanism (e.g. a site that in a phosphorylated state changes binding affinity of another site). Multiple levels of resolution are available: pathway-like diagram of interactions among molecules, optional site-specific interactions, and additional contingencies for interactions. Inclusion of molecular sites enables unambiguous reconstruction of the rule descriptions from the visual diagram without additional supporting documentation, while still keeping a pathway-like visual appearance. The proposed approach for visualization has been implemented in the Virtual Cell (VCell) modeling and simulation framework. Our Molecular Process Diagrams extend the notion of Systems Biology Graphical Notation (SBGN) process diagrams and use SBGN-compliant conventions.\n\nSummaryKinetic models have provided significant insights into biological regulatory mechanisms even though they typically did not take into consideration the details of protein subcomponents such as binding domains and phosphorylation sites. However, these details are often required for an accurate understanding of the events that occur during cell signaling. Without such detailed understanding, intervention strategies to act on signaling pathways in pathological conditions are bound to have limited success. This need to include site-specific details into models led to the advance of rule-based modeling. While rules describe the details of interactions with unmatched precision, they often obscure the \"big picture\", i.e. a pathway-like description of the information flow through the biological system. An intuitive visual diagram is crucial for understanding the assumptions embodied into a model. Here we present a novel approach and software for precise, scalable and compact representation of rule-based models that we call Molecular Process Diagram. It allows visualizing in a pathway-like diagram of the interacting molecules, the molecular sites modified, and the molecular sites that affect the interactions. The approach is implemented in the Virtual Cell (VCell) modeling and simulation framework and suggested as an extension for the Systems Biology Graphical Notations (SBGN) standard.

systems biology↗

Compartmental and spatial rule-based modeling with Virtual cell (VCell)

In rule-based modeling, molecular interactions are systematically specified in the form of reaction rules that serve as generators of reactions. This provides a way to account for all the potential molecular complexes and interactions among multivalent or multistate molecules. Recently, we introduced rule- based modeling into the Virtual Cell (VCell) modeling framework, permitting graphical specification of rules and merger of networks generated automatically (using the BioNetGen modeling engine) with hand-specified reaction networks. VCell provides a number of ordinary differential equation (ODE) and stochastic numerical solvers for single-compartment simulations of the kinetic systems derived from these networks, and agent-based network-free simulation of the rules. In this work, compartmental and spatial modeling of rule-based models has been implemented within VCell. To enable rule-based deterministic and stochastic spatial simulations and network-free agent-based compartmental simulations, the BioNetGen and NFSim engines were each modified to support compartments. In the new rule-based formalism, every reactant and product pattern and every reaction rule are assigned locations. We also introduce the novel rule-based concept of molecular anchors. This assures that any species that has a molecule anchored to a predefined compartment will remain in this compartment. Importantly, in addition to formulation of compartmental models, this now permits VCell users to seamlessly connect reaction networks derived from rules to explicit geometries to automatically generate a system of reaction-diffusion equations. These may then be simulated using either the VCell partial differential equations (PDE) deterministic solvers or the Smoldyn stochastic simulator.

biophysics↗