Mir-190b negatively contributes to the Trypanosoma cruzi- infected cell survival by repressing PTEN protein expression

Chagas disease, which is caused by the intracellular protozoanTrypanosoma cruzi, is a serious health problem in Latin America. The heart is one of the major organs affected by this parasitic infection. The pathogenesis of tissue remodelling, particularly regarding cardiomyocyte behaviour after parasite infection, and the molecular mechanisms that occur immediately following parasite entry into host cells are not yet completely understood. Previous studies have reported that the establishment of parasitism is connected to the activation of the phosphatidylinositol-3 kinase (PI3K), which controls important steps in cellular metabolism by regulating the production of the second messenger phosphatidylinositol-3,4,5-trisphosphate. Particularly, the tumour suppressor PTEN is a negative regulator of PI3K signalling. However, mechanistic details of the modulatory activity of PTEN on Chagas disease have not been elucidated. To address this question, H9c2 cells were infected with T. cruzi Berenice 62 strain and the expression of a specific set of microRNAs (miRNAs) were investigated. Our cellular model demonstrated that miRNA-190b is correlated to the decrease of cellular viability rates by negatively modulating PTEN protein expression in T. cruzi-infected cells.     

Preparation of alpha-synuclein fibrils for solid-state NMR: expression, purification, and incubation of wild-type and mutant forms

We report the expression and purification of alpha-synuclein, a protein implicated in Parkinson's disease, from isotopically (13C, 15N) labeled bacterial growth media, as required for solid-state NMR structural studies. Expression from Escherichia coli (BL21(DE3)) was performed with a protocol optimized for time efficiency and yield. Chemical lysis, crude purification by ammonium sulfate precipitation, and two chromatography steps (hydrophobic interaction and size exclusion) yield 30-35 mg/L of growth medium. Purity is confirmed by gel electrophoresis and mass spectrometry. Furthermore, we demonstrate reproducible fibril growth by control of environmental incubation conditions. Highly resolved multidimensional solid-state NMR spectra indicate microscopic order throughout the majority of the AS fibril structure. The number of signals and intensities of well-resolved residue types (Thr, Ser, Ala, Gly, Val, and Ile) are consistent with a single conformation, which is reproducibly prepared by seeding consecutive preparations. Variations in the fibril growth rates and structural polymorphisms exhibited in the solid-state NMR spectra are minimized by careful control of incubation conditions.     

Band-selective 13C Homonuclear 3D Spectroscopy for Solid Proteins at High Field with Rotor-synchronized Soft Pulses

We demonstrate improved 3D ¹³C–¹³C–¹³C chemical shift correlation experiments for solid proteins, utilizing band-selective coherence transfer, scalar decoupling and homonuclear zero-quantum polarization transfer. Judicious use of selective pulses and a z-filter period suppress artifacts with a two-step phase cycle, allowing higher digital resolution in a fixed measurement time. The novel correlation of C^ali–C^ali–CX (C^ali for aliphatic carbons, CX for any carbon) reduces measurement time by an order of magnitude without sacrificing digital resolution. The experiment retains intensity from side-chain carbon resonances whose chemical shift dispersion is critical to minimize spectral degeneracy for large proteins with a predominance of secondary structure, such as β-sheet rich fibrillar proteins and α-helical membrane proteins. We demonstrate the experiment for the β1 immunoglobulin binding domain of protein G (GB1) and fibrils of the A30P mutant of α-synuclein, which is implicated in Parkinson’s disease. Selective pulses of duration comparable the rotor period give optimal performance, but must be synchronized with the spinning in non-trivial ways to minimize chemical shift anisotropy recoupling effects. Soft pulses with a small bandwidth-duration product are best for exciting the ~70 ppm bandwidth required for aliphatic-only dimensions.     

Mutant protein A30P α-synuclein adopts wild-type fibril structure, despite slower fibrillation kinetics

α-Synuclein (AS) is associated with both sporadic and familial forms of Parkinson disease (PD). In sporadic disease, wild-type AS fibrillates and accumulates as Lewy bodies within dopaminergic neurons of the substantia nigra. The accumulation of misfolded AS is associated with the death of these neurons, which underlies many of the clinical features of PD. In addition, a rare missense mutation in AS, A30P, is associated with highly penetrant, autosomal dominant PD, although the pathogenic mechanism is unclear. A30P AS fibrillates more slowly than the wild-type (WT) protein in vitro and has been reported to preferentially adopt a soluble, protofibrillar conformation. This has led to speculation that A30P forms aggregates that are distinct in structure compared with wild-type AS. Here, we perform a detailed comparison of the chemical shifts and secondary structures of these fibrillar species, based upon our recent characterization of full-length WT fibrils. We have assigned A30P AS fibril chemical shifts de novo and used them to determine its secondary structure empirically. Our results illustrate that although A30P forms fibrils more slowly than WT in vitro, the chemical shifts and secondary structure of the resultant fibrils are in high agreement, demonstrating a conserved β-sheet core.     

Flying lemurs – The 'flying tree shrews'? Molecular cytogenetic evidence for a Scandentia-Dermoptera sister clade

Background  

Flying lemurs or Colugos (order Dermoptera) represent an ancient mammalian lineage that contains only two extant species. Although molecular evidence strongly supports that the orders Dermoptera, Scandentia, Lagomorpha, Rodentia and Primates form a superordinal clade called Supraprimates (or Euarchontoglires), the phylogenetic placement of Dermoptera within Supraprimates remains ambiguous.     

Persistence of accuracy of genomic estimated breeding values over generations in layer chickens

Background

The predictive ability of genomic estimated breeding values (GEBV) originates both from associations between high-density markers and QTL (Quantitative Trait Loci) and from pedigree information. Thus, GEBV are expected to provide more persistent accuracy over successive generations than breeding values estimated using pedigree-based methods. The objective of this study was to evaluate the accuracy of GEBV in a closed population of layer chickens and to quantify their persistence over five successive generations using marker or pedigree information.

Methods

The training data consisted of 16 traits and 777 genotyped animals from two generations of a brown-egg layer breeding line, 295 of which had individual phenotype records, while others had phenotypes on 2,738 non-genotyped relatives, or similar data accumulated over up to five generations. Validation data included phenotyped and genotyped birds from five subsequent generations (on average 306 birds/generation). Birds were genotyped for 23,356 segregating SNP. Animal models using genomic or pedigree relationship matrices and Bayesian model averaging methods were used for training analyses. Accuracy was evaluated as the correlation between EBV and phenotype in validation divided by the square root of trait heritability.

Results

Pedigree relationships in outbred populations are reduced by 50% at each meiosis, therefore accuracy is expected to decrease by the square root of 0.5 every generation, as observed for pedigree-based EBV (Estimated Breeding Values). In contrast the GEBV accuracy was more persistent, although the drop in accuracy was substantial in the first generation. Traits that were considered to be influenced by fewer QTL and to have a higher heritability maintained a higher GEBV accuracy over generations. In conclusion, GEBV capture information beyond pedigree relationships, but retraining every generation is recommended for genomic selection in closed breeding populations.     

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.     

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.     

Molecular determinants of phospholipid synergy in blood clotting

Many regulatory processes in biology involve reversible association of proteins with membranes. Clotting proteins bind to phosphatidylserine (PS) on cell surfaces, but a clear picture of this interaction has yet to emerge. We present a novel explanation for membrane binding by GLA domains of clotting proteins, supported by biochemical studies, solid-state NMR analyses, and molecular dynamics simulations. The model invokes a single "phospho-L-serine-specific" interaction and multiple "phosphate-specific" interactions. In the latter, the phosphates in phospholipids interact with tightly bound Ca(2+) in GLA domains. We show that phospholipids with any headgroup other than choline strongly synergize with PS to enhance factor X activation. We propose that phosphatidylcholine and sphingomyelin (the major external phospholipids of healthy cells) are anticoagulant primarily because their bulky choline headgroups sterically hinder access to their phosphates. Following cell damage or activation, exposed PS and phosphatidylethanolamine collaborate to bind GLA domains by providing phospho-L-serine-specific and phosphate-specific interactions, respectively.