Cellular interactions of L-glutamic acid60-L-alanine30-L-tyrosine10 (GAT)-specific suppressor factors. I. Inhibition of the activity of GAT-specific helper T cell clones by monoclonal GAT-specific suppressor T cell factors

Considerable information concerning the serology and biochemistry of antigen-specific, T cell-derived suppressor factors has been obtained with the use of T cell hybridomas as a source of homogeneous material. Similarly, knowledge of helper T cell products and receptors is accumulating from studies of helper T cell clones and hybridomas. Our strategy for studying the mechanisms by which suppressor factors inhibit responses was to determine whether monoclonal suppressor factors could inhibit antibody responses specific for L-glutamic acid60-L-alanine30-L-tyrosine10 (GAT) in cultures containing unprimed splenic B cells, macrophages, and GAT-specific T cell clones as a source of helper activity. The MHC-restricted, two chain suppressor factors, GAT-TsF2, inhibited these responses if the helper T cell clones and suppressor factor were derived from H-2-compatible mice. Furthermore, responses were inhibited by briefly pulsing T cell clones with GAT-TsF2 in the presence of GAT, indicating that suppressor factors need not be present continuously. In addition, helper T cell clones adsorbed syngeneic, but not allogeneic, GAT-TsF2 in the presence of GAT. Adsorption also requires a shared antigenic specificity between the H-2b-derived helper T cells and TsF2 factor. Thus, helper T cells can serve as the cellular target of antigen-specific, MHC-restricted GAT-TsF2, and cloned helper T cells can be used as a homogeneous target population for analysis of the molecular mechanisms of T cell suppression.     

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.     

Radiation-induced IFN-gamma production within the tumor microenvironment influences antitumor immunity

Alterations to the tumor microenvironment following localized irradiation may influence the effectiveness of subsequent immunotherapy. The objective of this study was to determine how IFN-gamma influences the inflammatory response within this dynamic environment following radiotherapy. B16/OVA melanoma cells were implanted into C57BL/6 (wild-type (WT)) and IFN-gamma-deficient (IFN-gamma-/-) mice. Seven days after implantation, mice received 15 Gy of localized tumor irradiation and were assessed 7 days later. Irradiation up-regulated the expression of VCAM-1 on the vasculature of tumors grown in WT but not in IFN-gamma-/- mice. Levels of the IFN-gamma-inducible chemokines MIG and IFN-gamma-inducible protein 10 were decreased in irradiated tumors from IFN-gamma-/- mice compared with WT. In addition to inducing molecular cues necessary for T cell infiltration, surface MHC class I expression is also up-regulated in response to IFN-gamma produced after irradiation. The role of IFN-gamma signaling in tumor cells on class I expression was tested using B16/OVA cells engineered to overexpress a dominant negative mutant IFN-gamma receptor (B16/OVA/DNM). Following implantation and treatment, expression of surface class I on tumor cells in vivo was increased in B16/OVA, but not in B16/OVA/DNM tumors, suggesting IFN-gamma acts directly on tumor cells to induce class I up-regulation. These increases in MHC class I expression correlated with greater levels of activated STAT1. Thus, IFN-gamma is instrumental in creating a tumor microenvironment conducive for T cell infiltration and tumor cell target recognition.     

Mechanistic insight of platelet apoptosis leading to non-surgical bleeding among heart failure patients supported by continuous-flow left ventricular assist devices

Vascular endothelial cells are highly sensitive to oxidative stress, and this is one of the mechanisms by which widespread endothelial dysfunction is induced in most cardiovascular diseases and disorders. However, how these cells can survive in oxidative stress environments remains unclear. Salidroside, a traditional Chinese medicine, has been shown to confer vascular protective effects. We aimed to understand the role of autophagy and its regulatory mechanisms by treating human umbilical vein endothelial cells (HUVECs) with salidroside under oxidative stress. HUVECs were treated with salidroside and exposed to hydrogen peroxide (H₂O₂). The results indicated that salidroside exerted cytoprotective effects in an H₂O₂-induced HUVEC injury model and suppressed H₂O₂-induced apoptosis of HUVECs. Pretreatment with 3-methyladenine (3-MA), an autophagy inhibitor, increased oxidative stress-induced HUVEC apoptosis, while the autophagy activator rapamycin induced anti-apoptosis effects in HUVECs. Salidroside increased autophagy and decreased apoptosis of HUVECs in a dose-dependent manner under oxidative stress. Moreover, 3-MA attenuated salidroside-induced HUVEC autophagy and promoted apoptosis, whereas rapamycin had no additional effects compared with salidroside alone. Salidroside upregulated AMPK phosphorylation but downregulated mTOR phosphorylation under oxidative stress; however, administration of compound C, an AMPK inhibitor, abrogated AMPK phosphorylation and increased mTOR phosphorylation and apoptosis compared with salidroside alone. These results suggest that autophagy is a protective mechanism in HUVECs under oxidative stress and that salidroside might promote autophagy through activation of the AMPK pathway and downregulation of mTOR pathway.     

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.     

Advances in osteoclast biology resulting from the study of osteopetrotic mutations

Osteopetrosis is the result of mutations affecting osteoclast function. Careful analyses of osteopetrosis have provided instrumental information on bone remodeling, including the coupling of bone formation to bone resorption. Based on a range of novel genetic mutations and the resulting osteoclast phenotypes, we discuss how osteopetrosis models have clarified the function of the coupling of bone formation to bone resorption, and the pivotal role of the osteoclast and their function in this phenomenon. We highlight the distinct possibility that osteoclast activities can be divided into two separate avenues: bone resorption and control of bone formation.     

Sensitivity of firing rate to input fluctuations depends on time scale separation between fast and slow variables in single neurons

Neuronal responses are often characterized by the firing rate as a function of the stimulus mean, or the f–I curve. We introduce a novel classification of neurons into Types A, B−, and B+ according to how f–I curves are modulated by input fluctuations. In Type A neurons, the f–I curves display little sensitivity to input fluctuations when the mean current is large. In contrast, Type B neurons display sensitivity to fluctuations throughout the entire range of input means. Type B− neurons do not fire repetitively for any constant input, whereas Type B+ neurons do. We show that Type B+ behavior results from a separation of time scales between a slow and fast variable. A voltage-dependent time constant for the recovery variable can facilitate sensitivity to input fluctuations. Type B+ firing rates can be approximated using a simple “energy barrier” model.     

Dendritic Cells Loaded with Tumor Antigens and a Dual Immunostimulatory and Anti-Interleukin 10-Specific Small Interference RNA Prime T Lymphocytes against Leukemic Cells

Vaccines using dendritic cells (DCs) harboring leukemic antigens to stimulate T cells is a possible treatment of acute myeloid leukemia (AML). Limitations of breaking tolerance to leukemic cells and lack of specific activation of T cell-mediated cytotoxicity may explain the discouraging clinical results with this approach. To break self-tolerance against AML cells, we loaded DCs with AML antigens and a bifunctional small interference (si) RNA targeting interleukin (IL) 10 and simultaneously activating toll-like receptors (TLRs). In vitro, this active siRNA inhibited (P < .05) IL-10 production by silencing the IL-10 gene in DCs. The active siRNA stimulated production of tumor necrosis factor α, implying activation of TLRs. Vaccination in a nonimmunogenic rat model mimicking human AML with the loaded DCs induced a substantial and specific T-cell cytotoxicity. Leukemic rats treated with the active siRNA lived longer and had markedly less leukemic cell mass infiltrating their bone marrow compared with rats given inactive siRNA (P < .05). Furthermore, compared with inactive siRNA treatment, the active siRNA led to significantly less extramedullar leukemic dissemination, evidenced by reduced matrix metalloproteinase activity and smaller spleens. Our data demonstrate that this bifunctional siRNA may work as an immunomodulatory drug with antileukemic properties.