Time-resolved phosphoproteomics reveals scaffolding and catalysis-responsive patterns of SHP2-dependent signaling.

SHP2 is a protein tyrosine phosphatase that normally potentiates intracellular signaling by growth factors, antigen receptors, and some cytokines, yet is frequently mutated in human cancer. Here, we examine the role of SHP2 in the responses of breast cancer cells to EGF by monitoring phosphoproteome dynamics when SHP2 is allosterically inhibited by SHP099. The dynamics of phosphotyrosine abundance at more than 400 tyrosine residues reveal six distinct response signatures following SHP099 treatment and washout.

Receptor-Driven ERK Pulses Reconfigure MAPK Signaling and Enable Persistence of Drug-Adapted BRAF-Mutant Melanoma Cells.

Targeted inhibition of oncogenic pathways can be highly effective in halting the rapid growth of tumors but often leads to the emergence of slowly dividing persister cells, which constitute a reservoir for the selection of drug-resistant clones. In BRAF melanomas, RAF and MEK inhibitors efficiently block oncogenic signaling, but persister cells emerge. Here, we show that persister cells escape drug-induced cell-cycle arrest via brief, sporadic ERK pulses generated by transmembrane receptors and growth factors operating in an autocrine/paracrine manner.

Considerations for the Selection and Use of Disinfectants Against SARS-CoV-2 in a Health Care Setting.

Proper disinfection using adequate disinfecting agents will be necessary for infection control strategies against coronavirus disease 2019 (COVID-19). However, limited guidance exists on effective surface disinfectants or best practices for their use against severe acute respiratory coronavirus 2. We outlined a process of fully characterizing over 350 products on the Environmental Protection Agency List N, including pH, method of delivery, indication for equipment sterilization, and purchase availability.

Using Mechanistic Models for Analysis of Proteomic Data.

A goal of systems biology is to develop an integrated picture of how the myriad components of a biological system work together to produce responses to environmental inputs. Achieving this goal requires (1) assembling a list of the component parts of a cellular regulatory system, and (2) understanding how the connections between these components enable information processing. To work toward these ends, a number of methods have matured in parallel.

Using Equation-Free Computation to Accelerate Network-Free Stochastic Simulation of Chemical Kinetics.

The chemical kinetics of many complex systems can be concisely represented by reaction rules, which can be used to generate reaction events via a kinetic Monte Carlo method that has been termed network-free simulation. Here, we demonstrate accelerated network-free simulation through a novel approach to equation-free computation. In this process, variables are introduced that approximately capture system state.

Timescale Separation of Positive and Negative Signaling Creates History-Dependent Responses to IgE Receptor Stimulation.

The high-affinity receptor for IgE expressed on the surface of mast cells and basophils interacts with antigens, via bound IgE antibody, and triggers secretion of inflammatory mediators that contribute to allergic reactions. To understand how past inputs (memory) influence future inflammatory responses in mast cells, a microfluidic device was used to precisely control exposure of cells to alternating stimulatory and non-stimulatory inputs. We determined that the response to subsequent stimulation depends on the interval of signaling quiescence.

BioNetFit: a fitting tool compatible with BioNetGen, NFsim and distributed computing environments.

Unlabelled: Rule-based models are analyzed with specialized simulators, such as those provided by the BioNetGen and NFsim open-source software packages. Here, we present BioNetFit, a general-purpose fitting tool that is compatible with BioNetGen and NFsim. BioNetFit is designed to take advantage of distributed computing resources.

Modeling for (physical) biologists: an introduction to the rule-based approach.

Models that capture the chemical kinetics of cellular regulatory networks can be specified in terms of rules for biomolecular interactions. A rule defines a generalized reaction, meaning a reaction that permits multiple reactants, each capable of participating in a characteristic transformation and each possessing certain, specified properties, which may be local, such as the state of a particular site or domain of a protein. In other words, a rule defines a transformation and the properties that reactants must possess to participate in the transformation.

Modeling biomolecular site dynamics in immunoreceptor signaling systems.

The immune system plays a central role in human health. The activities of immune cells, whether defending an organism from disease or triggering a pathological condition such as autoimmunity, are driven by the molecular machinery of cellular signaling systems. Decades of experimentation have elucidated many of the biomolecules and interactions involved in immune signaling and regulation, and recently developed technologies have led to new types of quantitative, systems-level data.

Phosphorylation site dynamics of early T-cell receptor signaling.

In adaptive immune responses, T-cell receptor (TCR) signaling impacts multiple cellular processes and results in T-cell differentiation, proliferation, and cytokine production. Although individual protein-protein interactions and phosphorylation events have been studied extensively, we lack a systems-level understanding of how these components cooperate to control signaling dynamics, especially during the crucial first seconds of stimulation. Here, we used quantitative proteomics to characterize reshaping of the T-cell phosphoproteome in response to TCR/CD28 co-stimulation, and found that diverse dynamic patterns emerge within seconds.

An Interaction Library for the FcεRI Signaling Network.

Antigen receptors play a central role in adaptive immune responses. Although the molecular networks associated with these receptors have been extensively studied, we currently lack a systems-level understanding of how combinations of non-covalent interactions and post-translational modifications are regulated during signaling to impact cellular decision-making. To fill this knowledge gap, it will be necessary to formalize and piece together information about individual molecular mechanisms to form large-scale computational models of signaling networks.

Rule-based modeling: a computational approach for studying biomolecular site dynamics in cell signaling systems.

Rule-based modeling was developed to address the limitations of traditional approaches for modeling chemical kinetics in cell signaling systems. These systems consist of multiple interacting biomolecules (e.g.

Decoding the language of phosphorylation site dynamics.

Immune defenses depend on the ability of immunoreceptors to recognize foreign antigens and initiate intracellular signaling when a pathogen is detected. Signal initiation requires spatial reorganization of proteins and site-specific receptor phosphorylation, which leads to engagement of feedback loops. This Journal Club discusses recent work using combined experimental and computational approaches to investigate these processes in B cell antigen receptor (BCR) signaling.

Guidelines for visualizing and annotating rule-based models.

Rule-based modeling provides a means to represent cell signaling systems in a way that captures site-specific details of molecular interactions. For rule-based models to be more widely understood and (re)used, conventions for model visualization and annotation are needed. We have developed the concepts of an extended contact map and a model guide for illustrating and annotating rule-based models.