Acceleration Strategies to Enhance Metabolic Ensemble Modeling Performance.

Developing reliable, predictive kinetic models of metabolism is a difficult, yet necessary, priority toward understanding and deliberately altering cellular behavior. Constraint-based modeling has enabled the fields of metabolic engineering and systems biology to make great strides in interrogating cellular metabolism but does not provide sufficient insight into regulation or kinetic limitations of metabolic pathways. Moreover, the growth-optimized assumptions that constraint-based models often rely on do not hold when studying stationary or persistor cell populations. However, developing kinetic models provides many unique challenges, as many of the kinetic parameters and rate laws governing individual enzymes are unknown. Ensemble modeling (EM) was developed to circumnavigate this challenge and effectively sample the large kinetic parameter solution space using consistent experimental datasets. Unfortunately, EM, in its base form, requires long solve times to complete and often leads to unstable kinetic model predictions. Furthermore, these limitations scale prohibitively with increasing model size. As larger metabolic models are developed with increasing genetic information and experimental validation, the demand to incorporate kinetic information increases. Therefore, in this work, we have begun to tackle the challenges of EM by introducing additional steps to the existing method framework specifically through reducing computation time and optimizing parameter sampling. We first reduce the structural complexity of the network by removing dependent species, and second, we sample locally stable parameter sets to reflect realistic biological states of cells. Lastly, we presort the screening data to eliminate the most incorrect predictions in the earliest screening stages, saving further calculations in later stages. Our complementary improvements to this EM framework are easily incorporated into concurrent EM efforts and broaden the application opportunities and accessibility of kinetic modeling across the field.

Mass spectrometry-based identification of S-nitrosocysteine in vivo using organic mercury assisted enrichment.

Protein S-nitrosylation is considered as one of the molecular mechanisms by which nitric oxide regulates signaling events and protein function. The present review presents an updated method which allows for the site-specific detection of S-nitrosylated proteins in vivo. The method is based on enrichment of S-nitrosylated proteins or peptides using organomercury compounds followed by LC-MS/MS detection. Technical aspects for determining the reaction and binding efficiency of the mercury resin that assists enrichment of S-nitrosylated proteins are presented and discussed. In addition, emphasis is given to the specificity of the method by providing technical details for the generation of four chemically distinct negative controls. Finally it is provided an overview of the key steps for generation and evaluation of mass spectrometry derived data.

Strategies and tools to explore protein S-nitrosylation.

BACKGROUND: A biochemical pathway by which nitric oxide accomplishes functional diversity is the specific modification of protein cysteine residues to form S-nitrosocysteine. This post-translational modification, S-nitrosylation, impacts protein function, interactions and location. However, comprehensive studies exploring protein signaling pathways or interrelated protein clusters that are regulated by S-nitrosylation have not been performed on a global scale. SCOPE OF REVIEW: To provide insights to these important biological questions, sensitive, validated and quantitative proteomic approaches are required. This review summarizes current approaches for the global identification of S-nitrosylated proteins. MAJOR CONCLUSIONS: The application of novel methods for identifying S-nitrosylated proteins, especially when combined with mass-spectrometry based proteomics to provide site-specific identification of the modified cysteine residues, promises to deliver critical clues for the regulatory role of this dynamic posttranslational modification in cellular processes. GENERAL SIGNIFICANCE: Though several studies have established S-nitrosylation as a regulator of protein function in individual proteins, the biological chemistry and the structural elements that govern the specificity of this modification in vivo are vastly unknown. Additionally, a gap in knowledge exists concerning the potential global regulatory role(s) this modification may play in cellular physiology. By further studying S-nitrosylation at a global scale, a greater appreciation of nitric oxide and protein S-nitrosylation in cellular function can be achieved. This article is part of a Special Issue entitled Regulation of Cellular Processes by S-nitrosylation.

Structural profiling of endogenous S-nitrosocysteine residues reveals unique features that accommodate diverse mechanisms for protein S-nitrosylation.

S-nitrosylation, the selective posttranslational modification of protein cysteine residues to form S-nitrosocysteine, is one of the molecular mechanisms by which nitric oxide influences diverse biological functions. In this study, unique MS-based proteomic approaches precisely pinpointed the site of S-nitrosylation in 328 peptides in 192 proteins endogenously modified in WT mouse liver. Structural analyses revealed that S-nitrosylated cysteine residues were equally distributed in hydrophobic and hydrophilic areas of proteins with an average predicted pK(a) of 10.01 ± 2.1. S-nitrosylation sites were over-represented in α-helices and under-represented in coils as compared with unmodified cysteine residues in the same proteins (χ(2) test, P < 0.02). A quantile-quantile probability plot indicated that the distribution of S-nitrosocysteine residues was skewed toward larger surface accessible areas compared with the unmodified cysteine residues in the same proteins. Seventy percent of the S-nitrosylated cysteine residues were surrounded by negatively or positively charged amino acids within a 6-Å distance. The location of cysteine residues in α-helices and coils in highly accessible surfaces bordered by charged amino acids implies site directed S-nitrosylation mediated by protein-protein or small molecule interactions. Moreover, 13 modified cysteine residues were coordinated with metals and 15 metalloproteins were endogenously modified supporting metal-catalyzed S-nitrosylation mechanisms. Collectively, the endogenous S-nitrosoproteome in the liver has structural features that accommodate multiple mechanisms for selective site-directed S-nitrosylation.

Development and Clinical Evaluation of an mHealth Application for Stress Management.

A large number of individuals experience mental health disorders, with cognitive behavioral therapy (CBT) emerging as a standard practice for reduction in psychiatric symptoms, including stress, anger, anxiety, and depression. However, CBT is associated with significant patient dropout and lacks the means to provide objective data regarding a patient's experience and symptoms between sessions. Emerging wearables and mobile health (mHealth) applications represent an approach that may provide objective data to the patient and provider between CBT sessions. Here, we describe the development of a classifier of real-time physiological stress in a healthy population (n = 35) and apply it in a controlled clinical evaluation for armed forces veterans undergoing CBT for stress and anger management (n = 16). Using cardiovascular and electrodermal inputs from a wearable device, the classifier was able to detect physiological stress in a non-clinical sample with accuracy greater than 90%. In a small clinical sample, patients who used the classifier and an associated mHealth application were less likely to discontinue therapy (p = 0.016, d = 1.34) and significantly improved on measures of stress (p = 0.032, d = 1.61), anxiety (p = 0.050, d = 1.26), and anger (p = 0.046, d = 1.41) compared to controls undergoing CBT alone. Given the large number of individuals that experience mental health disorders and the unmet need for treatment, especially in developing nations, such mHealth approaches have the potential to provide or augment treatment at low cost in the absence of in-person care.

Social and environmental influences on opioid sensitivity in rats: importance of an opioid's relative efficacy at the mu-receptor.

RATIONALE: Evidence indicates that social and environmental enrichment can influence the functional maturation of the central nervous system and may affect an organism's sensitivity to centrally acting drugs. OBJECTIVE: The purpose of the present study was to examine the effects of social and environmental enrichment on sensitivity to mu-opioids possessing a range of relative efficacies at the mu-receptor. METHODS: Rats were obtained at weaning (21 days) and divided into two groups immediately upon arrival. Isolated rats were housed individually in opaque laboratory cages with no visual or tactile contact with other rats; enriched rats were housed socially in groups of four in large cages and given various novel objects on a daily basis. After 6 weeks under these conditions, the effects of morphine, levorphanol, buprenorphine, butorphanol, and nalbuphine were examined in the warm-water, tail-withdrawal procedure and the place-conditioning procedure. RESULTS: In the tail-withdrawal procedure, isolated and enriched rats did not differ in sensitivity to morphine (1.0-30 mg/kg) and levorphanol (0.3-10 mg/kg), but enriched rats were more sensitive to buprenorphine (0.03-3.0 mg/kg), butorphanol (0.3-30 mg/kg), and nalbuphine (0.3-30 mg/kg). In drug combination tests, butorphanol and nalbuphine antagonized the effects of morphine in isolated rats under conditions in which they produced high levels of antinociception in enriched rats. In the place-conditioning procedure, doses of 10 morphine and 3.0 levorphanol established a place preference in both groups of rats, whereas doses of 0.3 buprenorphine, 3.0 butorphanol, and 10 nalbuphine established a place preference only in enriched rats. CONCLUSIONS: These findings may be taken as evidence that enriched rats are more sensitive than isolated rats to the effects of lower-efficacy mu-opioids and that social and environmental enrichment leads to functional alterations in opioid receptor populations.

Nitric oxide regulates mitochondrial fatty acid metabolism through reversible protein S-nitrosylation.

Cysteine S-nitrosylation is a posttranslational modification by which nitric oxide regulates protein function and signaling. Studies of individual proteins have elucidated specific functional roles for S-nitrosylation, but knowledge of the extent of endogenous S-nitrosylation, the sites that are nitrosylated, and the regulatory consequences of S-nitrosylation remains limited. We used mass spectrometry-based methodologies to identify 1011 S-nitrosocysteine residues in 647 proteins in various mouse tissues. We uncovered selective S-nitrosylation of enzymes participating in glycolysis, gluconeogenesis, tricarboxylic acid cycle, and oxidative phosphorylation, indicating that this posttranslational modification may regulate metabolism and mitochondrial bioenergetics. S-nitrosylation of the liver enzyme VLCAD [very long chain acyl-coenzyme A (CoA) dehydrogenase] at Cys(238), which was absent in mice lacking endothelial nitric oxide synthase, improved its catalytic efficiency. These data implicate protein S-nitrosylation in the regulation of ß-oxidation of fatty acids in mitochondria.