Understanding the dynamics of redox elements in biologic systems remains a major challenge for redox signaling and oxidative stress research. Central redox elements include evolutionarily conserved subsets of cysteines and methionines of proteins which function as sulfur switches and labile reactive oxygen species (ROS) and reactive nitrogen species (RNS) which function in redox signaling. The sulfur switches depend upon redox environments in which rates of oxidation are balanced with rates of reduction through the thioredoxins, glutathione/glutathione disulfide and cysteine/cystine redox couples. These central couples, which we term redox control nodes, are maintained at stable but non-equilibrium steady states, are largely independently regulated in different subcellular compartments and are quasi-independent from each other within compartments. Disruption of the redox control nodes can differentially affect sulfur switches, thereby creating a diversity of oxidative stress responses. Systems biology provides approaches to address the complexity of these responses. In the present review, we summarize thiol/disulfide pathway, redox potential and rate information as a basis for kinetic modeling of sulfur switches. The summary identifies gaps in knowledge especially related to redox communication between compartments, definition of redox pathways and discrimination between types of sulfur switches. A formulation for kinetic modeling of GSH/GSSG redox control indicates that systems biology could encourage novel therapeutic approaches to protect against oxidative stress by identifying specific redox-sensitive sites which could be targeted for intervention.

Hydrogen peroxide is appreciated as a cellular signaling molecule with second-messenger properties, yet the mechanisms by which the cell protects against intracellular H 2 O 2 accumulation are not fully understood. We introduce a network model of H 2 O 2 clearance that includes the pseudo-enzymatic oxidative turnover of protein thiols, the enzymatic actions of catalase, glutathione peroxidase, peroxiredoxin, and glutaredoxin, and the redox reactions of thioredoxin and glutathione. Simulations reproduced experimental observations of the rapid and transient oxidation of glutathione and the rapid, sustained oxidation of thioredoxin on exposure to extracellular H 2 O 2 . The model correctly predicted early oxidation profiles for the glutathione and thioredoxin redox couples across a range of initial extracellular [H 2 O 2 ] and highlights the importance of cytoplasmic membrane permeability to the cellular defense against exogenous sources of H 2 O 2 . The protein oxidation profile predicted by the model suggests that approximately 10% of intracellular protein thiols react with hydrogen peroxide at substantial rates, with a majority of these proteins forming protein disulfides as opposed to protein S-glutathionylated adducts. A steady-state flux analysis predicted an unequal distribution of the intracellular anti-oxidative burden between thioredoxin-dependent and glutathione-dependent antioxidant pathways, with the former contributing the majority of the cellular antioxidant defense due to peroxiredoxins and protein disulfides. Antioxid. Redox Signal. 13, 731-743.

Stochasticity in gene expression, protein or metabolite levels contributes to cell-cell variations, the analysis of which could lead to a better understanding of cellular processes and drug responses. Current technologies are limited in their throughput, resolution (in space, time, and tracking individual cells instead of population average) and the ability to control cellular environment. A few microfluidic tools have been developed to trap and image cells; however, in most designs available to date, there is a compromise among loading efficiency, speed, the ability to trap single cells, and density or number of trapped cells. To meet the needs of single-cell imaging studies, we developed a microfluidic platform for high-throughput capture and imaging of thousands of single cells. The optimized trapping mechanism enables 95% of the traps to be occupied with single cells, with a trap density of 860 traps / mm2. The dense array allows up to 800 cells to be imaged simultaneously with a 4× objective and a typical camera setup. Capture occurs with low shear and 94% viability after 24h. This platform is compatible with other upstream microfluidic components for complex cell stimulation patterns, and we show here the ability to measure heterogeneity in calcium oscillatory behavior in genetically identical cells and monitor kinetic cellular response to chemical stimuli.

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Titanium dioxide nanoparticles (TiO2 NPs), used as pigments and photocatalysts, are ubiquitous in our daily lives. Previous work has observed cellular oxidative stress in response to the UV-excitation of photocatalytic TiO2 NPs. In comparison, most human exposure to TiO2 NPs takes place in the dark, in the lung following inhalation or in the gut following consumption of TiO2 NP food pigment. Our spectroscopic characterization shows that both photocatalytic and food grade TiO2 NPs, in the dark, generate low levels of reactive oxygen species (ROS), specifically hydroxyl radicals and superoxides. These ROS oxidize serum proteins that form a corona of proteins on the NP surface. This protein layer is the interface between the NP and the cell. An oxidized protein corona triggers an oxidative stress response, detected with PCR and western blotting. Surface modification of TiO2 NPs to increase or decrease surface defects correlates with ROS generation and oxidative stress, suggesting that NP surface defects, likely oxygen vacancies, are the underlying cause of TiO2 NP-induced oxidative stress.

Recent technological breakthroughs in our ability to derive and differentiate induced pluripotent stem cells, organoid biology, organ-on-chip assays, and 3-D bioprinting have all contributed to a heightened interest in the design, assembly, and manufacture of living systems with a broad range of potential uses. This white paper summarizes the state of the emerging field of “multi-cellular engineered living systems,” which are composed of interacting cell populations. Recent accomplishments are described, focusing on current and potential applications, as well as barriers to future advances, and the outlook for longer term benefits and potential ethical issues that need to be considered.

Cellular metabolites are moieties defined by their specific binding constants to H+, Mg2+, and K+ or anions without ligands. As a consequence, every biochemical reaction in the cytoplasm has an associated proton stoichiometry that is generally noninteger- and pH-dependent. Therefore, with metabolic flux, pH is altered in a medium with finite buffer capacity. Apparent equilibrium constants and maximum enzyme velocities, which are functions of pH, are also altered. We augmented an earlier mathematical model of skeletal muscle glycogenolysis with pH-dependent enzyme kinetics and reaction equilibria to compute the time course of pH changes. Analysis shows that kinetics and final equilibrium states of the closed system are highly constrained by the pH-dependent parameters. This kinetic model of glycogenolysis, coupled to creatine kinase and adenylate kinase, simulated published experiments made with a cell-free enzyme mixture to reconstitute the network and to synthesize PCr and lactate in vitro. Using the enzyme kinetic and thermodynamic data in the literature, the simulations required minimal adjustments of parameters to describe the data. These results show that incorporation of appropriate physical chemistry of the reactions with accurate kinetic modeling gives a reasonable simulation of experimental data and is necessary for a physically correct representation of the metabolic network. The approach is general for modeling metabolic networks beyond the specific pathway and conditions presented here.

Proximal signaling events activated by TCR-peptide/MHC (TCR-pMHC) binding have been the focus of intense ongoing study, but understanding how the consequent downstream signaling networks integrate to govern ultimate avidity-appropriate TCR-pMHC T cell responses remains a crucial next challenge. We hypothesized that a quantitative combination of key downstream network signals across multiple pathways must encode the information generated by TCR activation, providing the basis for a quantitative model capable of interpreting and predicting T cell functional responses. To this end, we measured 11 protein nodes across six downstream pathways, along five time points from 10 min to 4 h, in a 1B6 T cell hybridoma stimulated by a set of three myelin proteolipid protein 139–151 altered peptide ligands. A multivariate regression model generated from this data compendium successfully comprehends the various IL-2 production responses and moreover successfully predicts a priori the response to an additional peptide treatment, demonstrating that TCR binding information is quantitatively encoded in the downstream network. Individual node and/or time point measurements less effectively accounted for the IL-2 responses, indicating that signals must be integrated dynamically across multiple pathways to adequately represent the encoded TCR signaling information. Of further importance, the model also successfully predicted a priori direct experimental tests of the effects of individual and combined inhibitors of the MEK/ERK and PI3K/Akt pathways on this T cell response. Together, our findings show how multipathway network signals downstream of TCR activation quantitatively integrate to translate pMHC stimuli into functional cell responses.