Dramatic down-regulation of oxidoreductases in human hepatocellular carcinoma hepG2 cells: proteomics and gene ontology unveiling new frontiers in cancer enzymology

Background

Oxidoreductases are enzymes that catalyze many redox reactions in normal and neoplastic cells. Their actions include catalysis of the transformation of free, neutral oxygen gas into oxygen free radicals, superoxide, hydroperoxide, singlet oxygen and hydrogen peroxide. These activated forms of oxygen contribute to oxidative stress that modifies lipids, proteins, DNA and carbohydrates. On the other hand, oxidoreductases constitute one of the most important free radical scavenger systems typified by catalase, superoxide dismutase and glutathione peroxidase. In this work, proteomics, Gene Ontology mapping and Directed Acyclic Graphs (DAG) are employed to detect and quantify differential oxidoreductase enzyme expressions between HepG2 cells and normal human liver tissues.

Results

For the set of bioinformatics calculations whose BLAST searches are performed using the BLAST program BLASTP 2.2.13 [Nov-27-2005], DAG of the Gene Ontology's Molecular Function annotations show that oxidoreductase activity parent node of the liver proteome contains 331 annotated protein sequences, 7 child nodes and an annotation score of 188.9, whereas that of HepG2 cells has 188 annotated protein sequences, 3 child nodes and an annotation score of only 91.9. Overwhelming preponderance of oxidoreductases in the liver is additionally supported by the isomerase DAGs: nearly all the reactions described in the normal liver isomerase DAG are oxidoreductase isomerization reactions, whereas only one of the three child nodes in the HepG2 isomerase DAG is oxidoreductase. Upon normalization of the annotation scores to the parent Molecular Function nodes, oxidoreductases are down-regulated in HepG2 cells by 58%. Similarly, for the set of bioinformatics calculations whose BLAST searches are carried out using BLASTP 2.2.15 [Oct-15-2006], oxidoreductases are down-regulated in HepG2 cells by 56%.

Conclusion

Proteomics and Gene Ontology reveal, for the first time, differential enzyme activities between HepG2 cells and normal human liver tissues, which may be a promising new prognostic marker of Hepatocellular carcinoma. Two independent sets of bioinformatics calculations that employ two BLAST program versions, and searched different databases, arrived at essentially the same conclusion: oxidoreductases are down-regulated in HepG2 cells by approximately 57%, when compared to normal human liver tissues. Down-regulation of oxidoreductases in hepatoma is additionally supported by Gene Ontology analysis of isomerises.     

Sample prep for proteomics of breast cancer: proteomics and gene ontology reveal dramatic differences in protein solubilization preferences of radioimmunoprecipitation assay and urea lysis buffers

Background

An important step in the proteomics of solid tumors, including breast cancer, consists of efficiently extracting most of proteins in the tumor specimen. For this purpose, Radio-Immunoprecipitation Assay (RIPA) buffer is widely employed. RIPA buffer's rapid and highly efficient cell lysis and good solubilization of a wide range of proteins is further augmented by its compatibility with protease and phosphatase inhibitors, ability to minimize non-specific protein binding leading to a lower background in immunoprecipitation, and its suitability for protein quantitation.

Results

In this work, the insoluble matter left after RIPA buffer extraction of proteins from breast tumors are subjected to another extraction step, using a urea-based buffer. It is shown that RIPA and urea lysis buffers fractionate breast tissue proteins primarily on the basis of molecular weights. The average molecular weight of proteins that dissolve exclusively in urea buffer is up to 60% higher than in RIPA. Gene Ontology (GO) and Directed Acyclic Graphs (DAG) are used to map the collective biological and biophysical attributes of the RIPA and urea proteomes. The Cellular Component and Molecular Function annotations reveal protein solubilization preferences of the buffers, especially the compartmentalization and functional distributions. It is shown that nearly all extracellular matrix proteins (ECM) in the breast tumors and matched normal tissues are found, nearly exclusively, in the urea fraction, while they are mostly insoluble in RIPA buffer. Additionally, it is demonstrated that cytoskeletal and extracellular region proteins are more soluble in urea than in RIPA, whereas for nuclear, cytoplasmic and mitochondrial proteins, RIPA buffer is preferred. Extracellular matrix proteins are highly implicated in cancer, including their proteinase-mediated degradation and remodelling, tumor development, progression, adhesion and metastasis. Thus, if they are not efficiently extracted by RIPA buffer, important information may be missed in cancer research.

Conclusion

For proteomics of solid tumors, a two-step extraction process is recommended. First, proteins in the tumor specimen should be extracted with RIPA buffer. Second, the RIPA-insoluble material should be extracted with the urea-based buffer employed in this work.     

Reduced mismatch repair of heteroduplexes reveals "non"-interfering crossing over in wild-type Saccharomyces cerevisiae

Using small palindromes to monitor meiotic double-strand-break-repair (DSBr) events, we demonstrate that two distinct classes of crossovers occur during meiosis in wild-type yeast. We found that crossovers accompanying 5:3 segregation of a palindrome show no conventional (i.e., positive) interference, while crossovers with 6:2 or normal 4:4 segregation for the same palindrome, in the same cross, do manifest interference. Our observations support the concept of a "non"-interference class and an interference class of meiotic double-strand-break-repair events, each with its own rules for mismatch repair of heteroduplexes. We further show that deletion of MSH4 reduces crossover tetrads with 6:2 or normal 4:4 segregation more than it does those with 5:3 segregation, consistent with Msh4p specifically promoting formation of crossovers in the interference class. Additionally, we present evidence that an ndj1 mutation causes a shift of noncrossovers to crossovers specifically within the "non"-interference class of DSBr events. We use these and other data in support of a model in which meiotic recombination occurs in two phases-one specializing in homolog pairing, the other in disjunction-and each producing both noncrossovers and crossovers.     

A comparison of alternative methods to compute conditional genotype probabilities for genetic evaluation with finite locus models

An increased availability of genotypes at marker loci has prompted the development of models that include the effect of individual genes. Selection based on these models is known as marker-assisted selection (MAS). MAS is known to be efficient especially for traits that have low heritability and non-additive gene action. BLUP methodology under non-additive gene action is not feasible for large inbred or crossbred pedigrees. It is easy to incorporate non-additive gene action in a finite locus model. Under such a model, the unobservable genotypic values can be predicted using the conditional mean of the genotypic values given the data. To compute this conditional mean, conditional genotype probabilities must be computed. In this study these probabilities were computed using iterative peeling, and three Markov chain Monte Carlo (MCMC) methods – scalar Gibbs, blocking Gibbs, and a sampler that combines the Elston Stewart algorithm with iterative peeling (ESIP). The performance of these four methods was assessed using simulated data. For pedigrees with loops, iterative peeling fails to provide accurate genotype probability estimates for some pedigree members. Also, computing time is exponentially related to the number of loci in the model. For MCMC methods, a linear relationship can be maintained by sampling genotypes one locus at a time. Out of the three MCMC methods considered, ESIP, performed the best while scalar Gibbs performed the worst.     

Haplotype inference in crossbred populations without pedigree information

Background

Current methods for haplotype inference without pedigree information assume random mating populations. In animal and plant breeding, however, mating is often not random. A particular form of nonrandom mating occurs when parental individuals of opposite sex originate from distinct populations. In animal breeding this is called crossbreeding and hybridization in plant breeding. In these situations, association between marker and putative gene alleles might differ between the founding populations and origin of alleles should be accounted for in studies which estimate breeding values with marker data. The sequence of alleles from one parent constitutes one haplotype of an individual. Haplotypes thus reveal allele origin in data of crossbred individuals.

Results

We introduce a new method for haplotype inference without pedigree that allows nonrandom mating and that can use genotype data of the parental populations and of a crossbred population. The aim of the method is to estimate line origin of alleles. The method has a Bayesian set up with a Dirichlet Process as prior for the haplotypes in the two parental populations. The basic idea is that only a subset of the complete set of possible haplotypes is present in the population.

Conclusion

Line origin of approximately 95% of the alleles at heterozygous sites was assessed correctly in both simulated and real data. Comparing accuracy of haplotype frequencies inferred with the new algorithm to the accuracy of haplotype frequencies inferred with PHASE, an existing algorithm for haplotype inference, showed that the DP algorithm outperformed PHASE in situations of crossbreeding and that PHASE performed better in situations of random mating.     

Effects of activation of μ-, κ<Subscript>1</Subscript>-, δ<Subscript>1</Subscript>-, δ<Subscript>2</Subscript>-, and ORL<Subscript>1</Subscript>-receptors on heart resistance to the pathogenic action of delayed ischemia and reperfusion

Different subtypes of opioid receptors (OR) were activated in rats in vivo to study the activation effect on the heart’s resistance to ischemia and reperfusion. It has been established that administration of deltorphin II, a selective δ₂-OR agonist, lowered the infarct size/area at risk index (IS/AAR) by 23%. Naltrexone, naloxone methiodide (an OR inhibitor not penetrating the blood-brain barrier (BBB)), and naltriben (δ₂-antagonist) eliminated the cardioprotective effect of deltorphin II, while BNTX (a δ₁-antagonist) produced no effect on the cardioprotective action of the δ₂-agonist. The infarct-reducing effect of deltorphin II was eliminated by administration of chelerythrine (a protein kinase C (PKC) inhibitor), glibenclamide (a K_ATP-channels inhibitor), and 5-hydroxydecanoate (a mitochondrial K_ATP-channel blocker). Administration of other opioids did not reduce the IS/AAR index. It has been established that all the deltorphins manifest antiarrhythmic potency. Other opioids do not produce any effect on the incidence of arrhythmia occurrences. The antiarrhythmic effect of deltorphin II was eliminated by preliminary administration of naltrexone, naloxone methiodide, and naltriben, but BNTX did not affect the δ₂-agonist’s anti-arrhythmic effect. The preliminary administration of chelerythrine, a PKC inhibitor, eliminated the δ₂ agonist’s antiarrhythmic action. However, glibenclamide and 5-hydroxydecanoate did not alter the antiarrhythmic effect by deltorphin II. Therefore, activation of the peripheral δ₂-ORs reduces the infarct size and prevents the onset of arrhythmias. The antiarrhythmic effect of the δ₂-OR stimulation is mediated by activating PKC and opening the mitochondrial K_ATP-channels. PKC participates in the antiarrhythmic effect of the δ₂-OR activation, but this effect does not depend on the condition of K_ATP-channels.     

Application of NMR based metabolomics for mapping metabolite variation in European wheat

In this study, we report on the use of NMR-based metabolomics to access variation in low molecular weight polar metabolites between the European wheat cultivars Apache, Charger, Claire and Orvantis. Previous unassigned resonances in the published NMR spectra of wheat extracts were identified using ¹³C NMR and two dimensional proton-carbon NMR. These included a peak for trans-aconitate (δ3.43) and resonances corresponding to fructose in the crowded carbohydrate region of the spectra. Large metabolite differences were observed between two different growth stages, namely the coleoptile and two week old leaf tissue extracts which were consistent across cultivars. Two week old leaf tissue extracts had higher abundances of glutamine, glutamate, sucrose and trans-aconitate and less glucose and fructose than were observed in the coleoptile extracts. Across both growth stages the cultivars Apache and Charger showed the greatest differences in metabolite profiles. Charger had higher abundances of betaine, the single most influential metabolite in the principal component analysis, in addition to fructose and sucrose. However, Charger had lower levels of aspartate, choline and glucose than Apache. These findings demonstrate the potential for a biochemical mapping approach using NMR, across European wheat germplasm, for metabolites of known importance to functional characteristics.     

You can't always get what you want: size assortative mating by mutual mate choice as a resolution of sexual conflict

Background  

Assortative mating patterns for mate quality traits like body size are often observed in nature. However, the underlying mechanisms that cause assortative mating patterns are less well known. Sexual selection is one important explanation for assortment, suggesting that i) one (usually the female) or both sexes could show preferences for mates of similar size or ii) mutual mate choice could resolve sexual conflict over quality traits into assortment. We tested these hypotheses experimentally in the socially monogamous cichlid fish Pelvicachromis taeniatus, in which mate choice is mutual.