Quantitative Proteomics Reveals Cellular Targets of Celastrol

Celastrol, a natural substance isolated from plant extracts used in traditional Chinese medicine, has been extensively investigated as a possible drug for treatment of cancer, autoimmune diseases, and protein misfolding disorders. Although studies focusing on celastrol's effects in specific cellular pathways have revealed a considerable number of targets in a diverse array of in vitro models there is an essential need for investigations that can provide a global view of its effects. To assess cellular effects of celastrol and to identify target proteins as biomarkers for monitoring treatment regimes, we performed large-scale quantitative proteomics in cultured human lymphoblastoid cells, a cell type that can be readily prepared from human blood samples. Celastrol substantially modified the proteome composition and 158 of the close to 1800 proteins with robust quantitation showed at least a 1.5 fold change in protein levels. Up-regulated proteins play key roles in cytoprotection with a prominent group involved in quality control and processing of proteins traversing the endoplasmic reticulum. Increased levels of proteins essential for the cellular protection against oxidative stress including heme oxygenase 1, several peroxiredoxins and thioredoxins as well as proteins involved in the control of iron homeostasis were also observed. Specific analysis of the mitochondrial proteome strongly indicated that the mitochondrial association of certain antioxidant defense and apoptosis-regulating proteins increased in cells exposed to celastrol. Analysis of selected mRNA transcripts showed that celastrol activated several different stress response pathways and dose response studies furthermore showed that continuous exposure to sub-micromolar concentrations of celastrol is associated with reduced cellular viability and proliferation. The extensive catalog of regulated proteins presented here identifies numerous cellular effects of celastrol and constitutes a valuable biomarker tool for the development and monitoration of disease treatment strategies

Mitochondrial proteomics on human fibroblasts for identification of metabolic imbalance and cellular stress

<p>Abstract</p> <p>Background</p> <p>Mitochondrial proteins are central to various metabolic activities and are key regulators of apoptosis. Disturbance of mitochondrial proteins is therefore often associated with disease. Large scale protein data are required to capture the mitochondrial protein levels and mass spectrometry based proteomics is suitable for generating such data. To study the relative quantities of mitochondrial proteins in cells from cultivated human skin fibroblasts we applied a proteomic method based on nanoLC-MS/MS analysis of iTRAQ-labeled peptides.</p> <p>Results</p> <p>When fibroblast cultures were exposed to mild metabolic stress – by cultivation in galactose medium- the amount of mitochondria appeared to be maintained whereas the levels of individual proteins were altered. Proteins of respiratory chain complex I and IV were increased together with NAD⁺-dependent isocitrate dehydrogenase of the citric acid cycle illustrating cellular strategies to cope with altered energy metabolism. Furthermore, quantitative protein data, with a median standard error below 6%, were obtained for the following mitochondrial pathways: fatty acid oxidation, citric acid cycle, respiratory chain, antioxidant systems, amino acid metabolism, mitochondrial translation, protein quality control, mitochondrial morphology and apoptosis.</p> <p>Conclusion</p> <p>The robust analytical platform in combination with a well-defined compendium of mitochondrial proteins allowed quantification of single proteins as well as mapping of entire pathways. This enabled characterization of the interplay between metabolism and stress response in human cells exposed to mild stress.</p

An inventory of interactors of the human HSP60/HSP10 chaperonin in the mitochondrial matrix space

The HSP60/HSP10 chaperonin assists folding of proteins in the mitochondrial matrix space by enclosing them in its central cavity. The chaperonin forms part of the mitochondrial protein quality control system. It is essential for cellular survival and mutations in its subunits are associated with rare neurological disorders. Here we present the first survey of interactors of the human mitochondrial HSP60/HSP10 chaperonin. Using a protocol involving metabolic labeling of HEK293 cells, cross-linking, and immunoprecipitation of HSP60, we identified 323 interacting proteins. As expected, the vast majority of these proteins are localized to the mitochondrial matrix space. We find that approximately half of the proteins annotated as mitochondrial matrix proteins interact with the HSP60/HSP10 chaperonin. They cover a broad spectrum of functions and metabolic pathways including the mitochondrial protein synthesis apparatus, the respiratory chain, and mitochondrial protein quality control. Many of the genes encoding HSP60 interactors are annotated as disease genes. There is a correlation between relative cellular abundance and relative abundance in the HSP60 immunoprecipitates. Nineteen abundant matrix proteins occupy more than 60% of the HSP60/HSP10 chaperonin capacity. The reported inventory of interactors can form the basis for interrogating which proteins are especially dependent on the chaperonin

FAPRI Environmental Projects 2000

Since 1995, the Food and Agricultural Policy Research Institute at the University of Missouri (FAPRI) has been providing analytical support in several areas around the state as communities try to come to grips with various water quality issues thought to derive from production agriculture's two underlying facts of life. This report provides a summary of the lessons learned as the unit has looked at and worked with these communities. It also discusses the specific projects underway in the unit, again focusing on issues directly related to the interface problem.This project is a cooperative effort of the Food and Agricultural Policy Research Institute at the University of Missouri and the Natural Resource Conservation Service. The work is supported by EPA grant X997396-01, Region VII U.S. Environmental Protection Agency, under section 104 (b) (3). The Missouri Department of Agriculture appropriated funds to support the work in this report

Identification of elements that dictate the specificity of mitochondrial Hsp60 for its co-chaperonin

Type I chaperonins (cpn60/Hsp60) are essential proteins that mediate the folding of proteins in bacteria, chloroplast and mitochondria. Despite the high sequence homology among chaperonins, the mitochondrial chaperonin system has developed unique properties that distinguish it from the widely-studied bacterial system (GroEL and GroES). The most relevant difference to this study is that mitochondrial chaperonins are able to refold denatured proteins only with the assistance of the mitochondrial co-chaperonin. This is in contrast to the bacterial chaperonin, which is able to function with the help of co-chaperonin from any source. The goal of our work was to determine structural elements that govern the specificity between chaperonin and co-chaperonin pairs using mitochondrial Hsp60 as model system. We used a mutagenesis approach to obtain human mitochondrial Hsp60 mutants that are able to function with the bacterial co-chaperonin, GroES. We isolated two mutants, a single mutant (E321K) and a double mutant (R264K/E358K) that, together with GroES, were able to rescue an E. coli strain, in which the endogenous chaperonin system was silenced. Although the mutations are located in the apical domain of the chaperonin, where the interaction with co-chaperonin takes place, none of the residues are located in positions that are directly responsible for co-chaperonin binding. Moreover, while both mutants were able to function with GroES, they showed distinct functional and structural properties. Our results indicate that the phenotype of the E321K mutant is caused mainly by a profound increase in the binding affinity to all co-chaperonins, while the phenotype of R264K/E358K is caused by a slight increase in affinity toward co-chaperonins that is accompanied by an alteration in the allosteric signal transmitted upon nucleotide binding. The latter changes lead to a great increase in affinity for GroES, with only a minor increase in affinity toward the mammalian mitochondrial co-chaperonin

A search for charged massive long-lived particles

We report on a search for charged massive long-lived particles (CMLLPs), based on 5.2 fb$^{-1}$ of integrated luminosity collected with the D0 detector at the Fermilab Tevatron $p\bar{p}$ collider. We search for events in which one or more particles are reconstructed as muons but have speed and ionization energy loss $(dE/dx)$ inconsistent with muons produced in beam collisions. CMLLPs are predicted in several theories of physics beyond the standard model. We exclude pair-produced long-lived gaugino-like charginos below 267 GeV and higgsino-like charginos below 217 GeV at 95% C.L., as well as long-lived scalar top quarks with mass below 285 GeV.Comment: submitted to Phys. Rev. Letter

Predictive Power Estimation Algorithm (PPEA) - A New Algorithm to Reduce Overfitting for Genomic Biomarker Discovery

Toxicogenomics promises to aid in predicting adverse effects, understanding the mechanisms of drug action or toxicity, and uncovering unexpected or secondary pharmacology. However, modeling adverse effects using high dimensional and high noise genomic data is prone to over-fitting. Models constructed from such data sets often consist of a large number of genes with no obvious functional relevance to the biological effect the model intends to predict that can make it challenging to interpret the modeling results. To address these issues, we developed a novel algorithm, Predictive Power Estimation Algorithm (PPEA), which estimates the predictive power of each individual transcript through an iterative two-way bootstrapping procedure. By repeatedly enforcing that the sample number is larger than the transcript number, in each iteration of modeling and testing, PPEA reduces the potential risk of overfitting. We show with three different cases studies that: (1) PPEA can quickly derive a reliable rank order of predictive power of individual transcripts in a relatively small number of iterations, (2) the top ranked transcripts tend to be functionally related to the phenotype they are intended to predict, (3) using only the most predictive top ranked transcripts greatly facilitates development of multiplex assay such as qRT-PCR as a biomarker, and (4) more importantly, we were able to demonstrate that a small number of genes identified from the top-ranked transcripts are highly predictive of phenotype as their expression changes distinguished adverse from nonadverse effects of compounds in completely independent tests. Thus, we believe that the PPEA model effectively addresses the over-fitting problem and can be used to facilitate genomic biomarker discovery for predictive toxicology and drug responses

Spatial heterogeneity in Bayesian disease mapping

© 2018, The Author(s). Disease mapping applications generally assume homogeneous regression effects and use random intercepts to account for residual spatial dependence. However, there may be local variation in the association between disease and area risk factors. We consider implications for model fit, estimated regression coefficients, and substantive inferences of allowing spatial variability in impacts of area risk factors. An application to suicide in 6791 English small areas shows that average regression coefficients and substantive inferences (e.g. about relative risk) may be considerably affected by allowing spatially varying predictor effects, while fit is improved

Combined Forward-Backward Asymmetry Measurements in Top-Antitop Quark Production at the Tevatron

The CDF and D0 experiments at the Fermilab Tevatron have measured the asymmetry between yields of forward- and backward-produced top and antitop quarks based on their rapidity difference and the asymmetry between their decay leptons. These measurements use the full data sets collected in proton-antiproton collisions at a center-of-mass energy of $\sqrt s =1.96$ TeV. We report the results of combinations of the inclusive asymmetries and their differential dependencies on relevant kinematic quantities. The combined inclusive asymmetry is $A_{\mathrm{FB}}^{t\bar{t}} = 0.128 \pm 0.025$. The combined inclusive and differential asymmetries are consistent with recent standard model predictions