Defining the ligand-dependent proximatome of the sigma 1 receptor

Sigma 1 Receptor (S1R) is a therapeutic target for a wide spectrum of pathological conditions ranging from neurodegenerative diseases to cancer and COVID-19. S1R is ubiquitously expressed throughout the visceral organs, nervous, immune and cardiovascular systems. It is proposed to function as a ligand-dependent molecular chaperone that modulates multiple intracellular signaling pathways. The purpose of this study was to define the S1R proximatome under native conditions and upon binding to well-characterized ligands. This was accomplished by fusing the biotin ligase, Apex2, to the C terminus of S1R. Cells stably expressing S1R-Apex or a GFP-Apex control were used to map proximal proteins. Biotinylated proteins were labeled under native conditions and in a ligand dependent manner, then purified and identified using quantitative mass spectrometry. Under native conditions, S1R biotinylates over 200 novel proteins, many of which localize within the endomembrane system (endoplasmic reticulum, Golgi, secretory vesicles) and function within the secretory pathway. Under conditions of cellular exposure to either S1R agonist or antagonist, results show enrichment of proteins integral to secretion, extracellular matrix formation, and cholesterol biosynthesis. Notably, Proprotein Convertase Subtilisin/Kexin Type 9 (PCSK9) displays increased binding to S1R under conditions of treatment with Haloperidol, a well-known S1R antagonist; whereas Low density lipoprotein receptor (LDLR) binds more efficiently to S1R upon treatment with (+)-Pentazocine ((+)-PTZ), a classical S1R agonist. Furthermore, we demonstrate that the ligand bound state of S1R correlates with specific changes to the cellular secretome. Our results are consistent with the postulated role of S1R as an intracellular chaperone and further suggest important and novel functionalities related to secretion and cholesterol metabolism

Expanding the metallomics toolbox: Development of chemical and biological methods in understanding copper biochemistry

Copper is an essential trace element and required for various biological processes, but free copper is toxic. Therefore, copper is tightly regulated in living cells and disruptions in this homeostatic machinery are implicated in numerous diseases. The current understanding of copper homeostasis is substantial but incomplete, particularly in regard to storage and exchange at the subcellular level. Intracellular copper is primarily present in the monovalent oxidation state. Therefore, copper(I) selective fluorescent probes can be utilized for imaging exchangeable copper ions in live cells, but these probes are often lipophilic and hence poorly water soluble. To address this problem, water-soluble fluorescent probes with greatly improved contrast ratio and fluorescence quantum yield are characterized in this work. This work also describes a novel application of water-soluble fluorescent probes, in-gel detection of copper proteins with solvent accessible Cu(I) sites under non-denaturing conditions. Knowledge of copper(I) stability constants of proteins is important to elucidate the mechanisms of cellular copper homeostasis. Due to the high affinity of most Cu(I)-binding proteins, the stability constants cannot be determined directly by titration of the apo-protein with Cu(I). Therefore, accurate determination of Cu(I) stability constants of proteins critically depends on the Cu(I) affinity standards. However, the previously reported binding affinity values of the frequently used Cu(I) affinity standards are largely inconsistent impeding reliable data acquisition for the Cu(I) stability constants of proteins. To solve this problem, a set of water-soluble ligands are developed in this work that form colorless, air-stable copper(I)-complexes with 1:1 stoichiometry. These ligands can be applied as copper(I) buffering agents and affinity standards in order to study copper biochemistry. Copper(I) binding proteins are an integral part of the copper homeostatic machinery and they work in conjunction to regulate copper uptake, distribution, and excretion. However, available evidence indicates the existence of putative copper-binding proteins that are yet to be characterized. Therefore, several proteomics-based methods are developed in this work by employing the strategy to label Cu(I)-binding cysteines in a copper-dependent manner which lays the foundation for the identification of new copper proteins from cellular extracts.Ph.D

Dynamic Redox Regulation of IL-4 Signaling

<div><p>Quantifying the magnitude and dynamics of protein oxidation during cell signaling is technically challenging. Computational modeling provides tractable, quantitative methods to test hypotheses of redox mechanisms that may be simultaneously operative during signal transduction. The interleukin-4 (IL-4) pathway, which has previously been reported to induce reactive oxygen species and oxidation of PTP1B, may be controlled by several other putative mechanisms of redox regulation; widespread proteomic thiol oxidation observed via 2D redox differential gel electrophoresis upon IL-4 treatment suggests more than one redox-sensitive protein implicated in this pathway. Through computational modeling and a model selection strategy that relied on characteristic STAT6 phosphorylation dynamics of IL-4 signaling, we identified reversible protein tyrosine phosphatase (PTP) oxidation as the primary redox regulatory mechanism in the pathway. A systems-level model of IL-4 signaling was developed that integrates synchronous pan-PTP oxidation with ROS-independent mechanisms. The model quantitatively predicts the dynamics of IL-4 signaling over a broad range of new redox conditions, offers novel hypotheses about regulation of JAK/STAT signaling, and provides a framework for interrogating putative mechanisms involving receptor-initiated oxidation.</p></div

IL-4 induced ROS is required for STAT6 signaling.

<p>(<b>A</b>) Jurkat cells were pretreated or not with 20 μM DPI for one hour and stimulated with 100 ng/ml IL-4. Cells were incubated with 5 μM CM-H₂DCFDA for 30 min before IL-4 addition. Fluorescence intensity of oxidized dye was recorded for each time point using flow cytometry. The lines are Hill curves fitted to the means. (<b>B</b>) Derivatives of the Hill curves shown in A. (<b>C</b>) Jurkat cells pretreated or not with DPI were stimulated with IL-4 and pSTAT6 was quantified using flow cytometry. (<b>D</b>) Jurkat cells were treated with H₂O₂ (10 μM), IL4 (100 ng/ml) or both and pSTAT6 was measured. Values on y-axis represent background subtracted and normalized mean fluorescence intensities. Graphs represent mean ± standard error of mean. N = 6 experiments for pSTAT6 under IL4 stimulation for all but the 4^th (15 min) and 6^th (25 min) time points where N = 3 experiments; N = 3 experiments for all other experiments; au, arbitrary units.</p

Qualitative model selection from a library indicates to more probable regulatory mechanisms.

<p>(<b>A</b>) The IL-4 network was divided into conceptual modules. The core module (blue box) comprises IL-4 induced receptor (R) activation and subsequent STAT phosphorylation. Activated receptor upregulates ROS which can affect signaling through three different modules: reversible phosphatase (P) oxidation (red box), reversible JAK (assumed to be implicit in the receptor) oxidation (green box), or by modulating nuclear-cytosolic shuttling of the phosphatase (purple box). The last module (yellow box) relates to nuclear-cytosolic translocation of STAT6 representing two possible variations: i) the dashed arrows are absent and STAT6 trafficking is unidirectional and dependent on its phosphorylation state; ii) the dashed arrows are present and STAT6 translocation is independent of its phosphorylation state. Keeping the blue module in place, the other modules were added or not and the dashed arrow in the yellow module were included or not producing a total of 16 different networks representing all possible combinations of the 4 regulatory modules. (<b>B</b>) For each network 50,000 MC simulations were run and dynamics of total phosphorylated STAT6 were analyzed. Counts of simulations that produced pSTAT6 dynamics with two peaks are shown for each of the 16 networks. The dot matrix under each bar indicates the regulatory mechanisms included in the corresponding model. A dot in the last row indicates STAT cycling was phosphorylation dependent. Red line indicates threshold of 0.1% of 50,000.</p

Putative mechanisms of redox regulation in the IL-4 pathway.

<p>(<b>A</b>) Reversible oxidative inhibition of PTPs. (<b>B</b>) Reversible oxidative inhibition of kinases. (<b>C</b>) ROS-dependent subcellular localization of TCPTP. The receptor complex consisting of the IL-4 receptor chains and JAK molecules has been conceptually treated as a single entity in our study. (<b>D</b>) Observed differential proteome-wide oxidation with 30 minute treatment of 100 ng/ml IL-4 (green) over control (red) by Redox-DIGE.</p

The optimal model of IL-4 signaling network includes transient protein tyrosine phosphatase oxidation in combination with shuttling and feedback mechanisms.

<p><b>(A)</b> Regulatory mechanisms including ROS mediated reversible phosphatase oxidation, proteasome mediated degradation of STAT6 and down-regulation by SOCS are incorporated into the model. P1 and P2 represent PTPs acting on STAT6 and the receptor complex, respectively; red edges, dephosphorylation reactions catalyzed by indicated phosphatases; arrows pointing into other edges, enzyme catalyzed reactions; Φ, infinite sources or sinks; purple edges and nodes, points affected by CHX in the model; green edges and nodes, points affected by MG132. Intermediate complexes formed in enzyme catalyzed reactions are not explicitly shown. The model predicts phosphorylation dynamics under extremes of redox state. (<b>B</b>) DPI pretreatment and addition of exogenous H₂O₂ with IL-4 stimulation were simulated using the fitted model. ROS profiles used to simulate both conditions are shown. (<b>C</b>) The predictions of the model overlaid with quantitative experimental data without further parameter fitting. (<b>D</b>) Transient oxidation of PTPs as measured by oxPTP immunoprecipitation.</p

Characteristic pSTAT6 dynamics with two distinct peaks provide quantitative metrics for IL-4 network topology determination.

<p>(<b>A</b>) A smoothing spline (continuous line) was fitted to mean pSTAT6 time course (dots) under IL-4 stimulation and distinguishing features of the curve were extracted. (<b>B</b>) Ratio of final value to height of peak 1 and time separation between peaks are plotted against the ratio of peak heights. Cyan markers show points corresponding to the fitted spline in A, representing experimentally measured (x, y) pairs. The heat maps indicate smoothed bivariate frequency distribution of (x, y) pairs obtained from MC simulations of network shown in D. (<b>C</b>) Same data for the network in E showing poor match. (<b>D</b>) Network with PTP oxidation as only mode of redox regulation; corresponds to first bar in <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1004582#pcbi.1004582.g003" target="_blank">Fig 3B</a>. (<b>E</b>) Network with all mechanisms of redox regulation represented; corresponds to fourth bar in <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1004582#pcbi.1004582.g003" target="_blank">Fig 3B</a>.</p

Loss of cardiac myosin light chain kinase contributes to contractile dysfunction in right ventricular pressure overload

Abstract Nearly 1 in every 100 children born have a congenital heart defect. Many of these defects primarily affect the right heart causing pressure overload of the right ventricle (RV). The RV maintains function by adapting to the increased pressure; however, many of these adaptations eventually lead to RV hypertrophy and failure. In this study, we aim to identify the cellular and molecular mechanisms of these adaptions. We utilized a surgical animal model of pulmonary artery banding (PAB) in juvenile rats that has been shown to accurately recapitulate the physiology of right ventricular pressure overload in young hearts. Using this model, we examined changes in cardiac myocyte protein expression as a result of pressure overload with mass spectrometry 4 weeks post‐banding. We found pressure overload of the RV induced significant downregulation of cardiac myosin light chain kinase (cMLCK). Single myocyte calcium and contractility recordings showed impaired contraction and relaxation in PAB RV myocytes, consistent with the loss of cMLCK. In the PAB myocytes, calcium transients were of smaller amplitude and decayed at a slower rate compared to controls. We also identified miR‐200c, which has been shown to regulate cMLCK expression, as upregulated in the RV in response to pressure overload. These results indicate the loss of cMLCK is a critical maladaptation of the RV to pressure overload and represents a novel target for therapeutic approaches to treat RV hypertrophy and failure associated with congenital heart defects