Nitrogen Mineralization by Acanthamoeba polyphaga in Grazed Pseudomonas paucimobilis Populations

Nitrogen mineralization was studied in a simple grazing system in which the protozoan Acanthamoeba polyphaga was grown with the bacterium Pseudomonas paucimobilis (two soil organisms isolated from the shortgrass prairie in northern Colorado). In different experiments, either carbon or nitrogen was adjusted to be in limiting amounts. When carbon was limiting, grazers were almost entirely responsible for nitrogen mineralization, with bacteria themselves contributing little. When nitrogen was limiting, nitrogen mineralization by grazers permitted continued growth by the grazed bacteria and a greater bacterial biomass production. The increased growth of the grazed bacteria did not result in an increased total amount of carbon used, but the grazed bacteria used carbon more efficiently than the ungrazed bacteria.     

The induction of liver tumors by 239Pu citrate or 239PuO2 particles in the Chinese hamster

The influence of radiation dose distribution on the frequency of 239Pu-induced liver tumors was evaluated in the Chinese hamster. Different concentrations of 239Pu citrate 239PuO2 particles of known sizes were injected intravenously via the jugular vein. About 60% of the injected 239Pu citrate was deposited in the liver and 40% in the bone. The 239Pu citrate was rather uniformly distributed throughout the liver parenchyma. Injected plutonium oxide particles were taken up by the reticuloendothelial system with 90% of the body burden deposited in the liver. The 239PuO2 particles were localized in the Kupffer cells and produced nonuniform dose distributions that were dependent on particle size. There was an activity- and dose-dependent increase in the incidence of total liver parenchymal cell tumors following injection with either plutonium particles or citrate. For animals that received 14.0-, 2.7-, 0.3-, and 0.04-Gy dose to liver from 239Pu citrate the cumulative tumor incidence was 39, 32, 5, and 0%, respectively. Animals that were injected with the 0.24 micron 239PuO2 particles had doses of 42.0, 7.2, and 0.8 Gy to the liver and tumor incidences of 34, 26, and 5%, respectively. Plutonium citrate also produced hemangiosarcomas of the liver and tumors in bone and bone marrow. The latent period for liver tumor appearance in animals exposed to 239Pu citrate or 239PuO2 particles increased as the injected activity decreased. For animals injected with a similar total activity (7.4 Bq/g), the lifetime cumulative liver tumor incidence was similar for animals exposed to either 239Pu citrate (32%) or 239PuO2 (26%). There was little effect of particle size on liver tumor incidence. These data indicate that, in Chinese hamster liver, local radiation dose distribution is less important in altering tumor incidence than injected activity or average dose. However, the more uniform irradiation from 239Pu citrate administration was more effective in cancer production than the nonuniform irradiation from 239PuO2 particles.     

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.