Melissa L. Kemp

A Model of Redox Kinetics Implicates the Thiol Proteome in Cellular Hydrogen Peroxide Responses

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.

Imaging single-cell signaling dynamics with a deterministic high-density single-cell trap array

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/mm(2). The dense array allows up to 800 cells to be imaged simultaneously with a 4x objective and a typical camera setup. Capture occurs with low shear and 94% viability after 24 h. 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.

Quantitative Network Signal Combinations Downstream of TCR Activation Can Predict IL-2 Production Response

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.

Fluorescent coumarin thiols measure biological redox couples.

In this report we present a new chemical probe, 3-HTC, that can reversibly and ratiometrically measure the thiol-disulfide equilibrium of biological systems. 3-HTC is composed of a coumarin that has a thiolate directly conjugated to its extended aromatic π system while formation of a disulfide attenuates this conjugation. The fluorescence and absorption properties of 3-HTC are therefore very sensitive to the redox state of its thiol. 3-HTC reacts reversibly with thiols and disulfides enabling its use to measure dynamic GSH/GSSH ratios in vitro as well as to monitor the reversible redox status of whole cell lysates.

Spatial Pattern Dynamics of 3D Stem Cell Loss of Pluripotency via Rules-Based Computational Modeling

Pluripotent embryonic stem cells (ESCs) have the unique ability to differentiate into cells from all germ lineages, making them a potentially robust cell source for regenerative medicine therapies, but difficulties in predicting and controlling ESC differentiation currently limit the development of therapies and applications from such cells. A common approach to induce the differentiation of ESCs in vitro is via the formation of multicellular aggregates known as embryoid bodies (EBs), yet cell fate specification within EBs is generally considered an ill-defined and poorly controlled process. Thus, the objective of this study was to use rules-based cellular modeling to provide insight into which processes influence initial cell fate transitions in 3-dimensional microenvironments. Mouse embryonic stem cells (D3 cell line) were differentiated to examine the temporal and spatial patterns associated with loss of pluripotency as measured through Oct4 expression. Global properties of the multicellular aggregates were accurately recapitulated by a physics-based aggregation simulation when compared to experimentally measured physical parameters of EBs. Oct4 expression patterns were analyzed by confocal microscopy over time and compared to simulated trajectories of EB patterns. The simulations demonstrated that loss of Oct4 can be modeled as a binary process, and that associated patterns can be explained by a set of simple rules that combine baseline stochasticity with intercellular communication. Competing influences between Oct4+ and Oct4− neighbors result in the observed patterns of pluripotency loss within EBs, establishing the utility of rules-based modeling for hypothesis generation of underlying ESC differentiation processes. Importantly, the results indicate that the rules dominate the emergence of patterns independent of EB structure, size, or cell division. In combination with strategies to engineer cellular microenvironments, this type of modeling approach is a powerful tool to predict stem cell behavior under a number of culture conditions that emulate characteristics of 3D stem cell niches.

Trans-spliced Cas9 allows cleavage of HBB and CCR5 genes in human cells using compact expression cassettes

CRISPR/Cas9 systems have been used in a wide variety of biological studies; however, the large size of CRISPR/Cas9 presents challenges in packaging it within adeno-associated viruses (AAVs) for clinical applications. We identified a two-cassette system expressing pieces of the S. pyogenes Cas9 (SpCas9) protein which splice together in cellula to form a functional protein capable of site-specific DNA cleavage. With specific CRISPR guide strands, we demonstrated the efficacy of this system in cleaving the HBB and CCR5 genes in human HEK-293T cells as a single Cas9 and as a pair of Cas9 nickases. The trans-spliced SpCas9 (tsSpCas9) displayed ~35% of the nuclease activity compared with the wild-type SpCas9 (wtSpCas9) at standard transfection doses, but had substantially decreased activity at lower dosing levels. The greatly reduced open reading frame length of the tsSpCas9 relative to wtSpCas9 potentially allows for more complex and longer genetic elements to be packaged into an AAV vector including tissue-specific promoters, multiplexed guide RNA expression, and effector domain fusions to SpCas9. For unknown reasons, the tsSpCas9 system did not work in all cell types tested. The use of protein trans-splicing may help facilitate exciting new avenues of research and therapeutic applications through AAV-based delivery of CRISPR/Cas9 systems.

A Switching Mechanism in Doxorubicin Bioactivation Can Be Exploited to Control Doxorubicin Toxicity

Although doxorubicin toxicity in cancer cells is multifactorial, the enzymatic bioactivation of the drug can significantly contribute to its cytotoxicity. Previous research has identified most of the components that comprise the doxorubicin bioactivation network; however, adaptation of the network to changes in doxorubicin treatment or to patient-specific changes in network components is much less understood. To investigate the properties of the coupled reduction/oxidation reactions of the doxorubicin bioactivation network, we analyzed metabolic differences between two patient-derived acute lymphoblastic leukemia (ALL) cell lines exhibiting varied doxorubicin sensitivities. We developed computational models that accurately predicted doxorubicin bioactivation in both ALL cell lines at high and low doxorubicin concentrations. Oxygen-dependent redox cycling promoted superoxide accumulation while NADPH-dependent reductive conversion promoted semiquinone doxorubicin. This fundamental switch in control is observed between doxorubicin sensitive and insensitive ALL cells and between high and low doxorubicin concentrations. We demonstrate that pharmacological intervention strategies can be employed to either enhance or impede doxorubicin cytotoxicity in ALL cells due to the switching that occurs between oxygen-dependent superoxide generation and NADPH-dependent doxorubicin semiquinone formation.

Interactions between mesenchymal stem cells, adipocytes, and osteoblasts in a 3D tri-culture model of hyperglycemic conditions in the bone marrow microenvironment

Recent studies have found that uncontrolled diabetes and consequential hyperglycemic conditions can lead to an increased incidence of osteoporosis. Osteoblasts, adipocytes, and mesenchymal stem cells (MSCs) are all components of the bone marrow microenvironment and thus may have an effect on diabetes-related osteoporosis. However, few studies have investigated the influence of these three cell types on each other, especially in the context of hyperglycemia. Thus, we developed a hydrogel-based 3D culture platform engineered to allow live-cell retrieval in order to investigate the interactions between MSCs, osteoblasts, and adipocytes in mono-, co-, and tri-culture configurations under hyperglycemic conditions for 7 days of culture. Gene expression, histochemical analysis of differentiation markers, and cell viability were measured for all cell types, and MSC-laden hydrogels were degraded to retrieve cells to assess their colony-forming capacity. Multivariate models of gene expression data indicated that primary discrimination was dependent on the neighboring cell type, validating the need for co-culture configurations to study conditions modeling this disease state. MSC viability and clonogenicity were reduced when mono- and co-cultured with osteoblasts at high glucose levels. In contrast, MSCs showed no reduction of viability or clonogenicity when cultured with adipocytes under high glucose conditions, and the adipogenic gene expression indicates that cross-talk between MSCs and adipocytes may occur. Thus, our unique culture platform combined with post-culture multivariate analysis provided a novel insight into cellular interactions within the MSC microenvironment and highlights the necessity of multi-cellular culture systems for further investigation of complex pathologies such as diabetes and osteoporosis.

Predicting Cytotoxic T-cell Age from Multivariate Analysis of Static and Dynamic Biomarkers

Adoptive T-cell transfer therapy relies upon in vitro expansion of autologous cytotoxic T cells that are capable of tumor recognition. The success of this cell-based therapy depends on the specificity and responsiveness of the T cell clones before transfer. During ex vivo expansion, CD8+ T cells present signs of replicative senescence and loss of function. The transfer of nonresponsive senescent T cells is a major bottleneck for the success of adoptive T-cell transfer therapy. Quantitative methods for assessing cellular age and responsiveness will facilitate the development of appropriate cell expansion and selection protocols. Although several biomarkers of lymphocyte senescence have been identified, these proteins in isolation are not sufficient to determine the age-dependent responsiveness of T cells. We have developed a multivariate model capable of extracting combinations of markers that are the most informative to predict cellular age. To acquire signaling information with high temporal resolution, we designed a microfluidic chip enabling parallel lysis and fixation of stimulated cell samples on-chip. The acquisition of 25 static biomarkers and 48 dynamic signaling measurements at different days in culture, integrating single-cell and population based information, allowed the multivariate regression model to accurately predict CD8+ T-cell age. From surface marker expression and early phosphorylation events following T-cell receptor stimulation, the model successfully predicts days in culture and number of population doublings with R2 = 0.91 and 0.98, respectively. Furthermore, we found that impairment of early signaling events following T cell receptor stimulation because of long term culture allows prediction of costimulatory molecules CD28 and CD27 expression levels and the number of population divisions in culture from a limited subset of signaling proteins. The multivariate analysis highlights the information content of both averaged biomarker values and heterogeneity metrics for prediction of cellular age within a T cell population.

Spatially-resolved intracellular sensing of hydrogen peroxide in living cells.

Understanding intracellular redox chemistry requires new tools for the site-specific visualization of intracellular oxidation. We have developed a spatially-resolved intracellular sensor of hydrogen peroxide, HyPer-Tau, for time-resolved imaging in live cells. This sensor consists of a hydrogen peroxide-sensing protein tethered to microtubules. We demonstrate the use of the HyPer-Tau sensor for three applications; dose-dependent response of human cells to exogenous hydrogen peroxide, a model immune response of mouse macrophages to stimulation by bacterial toxin, and a spatially-resolved response to localized delivery of hydrogen peroxide. These results demonstrate that HyPer-Tau can be used as an effective tool for tracking changes in spatially localized intracellular hydrogen peroxide and for future applications in redox signaling.