Two Protocols of Cryopreservation of Goat Semen with the Use of Computer-Assisted Semen Analysis System

The objective of the study was a comparison of two protocols of goat semen cryopreservation with the use of computer-assisted semen analysis system. Twenty ejaculates obtained with electroejaculation method were assessed. Each ejaculate was divided in half and frozen according to two protocols. In protocol I semen was centrifuged in order to remove its plasma and diluted in Tris buffer extender containing glucose, citric acid and glycerol with 20% addition of egg yolk. Protocol II did not include removal of plasma and the extender contained 1.5% egg yolk. It was shown that the removal of semen plasma improved motility of goat spermatozoa following freezing/thawing with respect to the following motility indicators: motility, average path velocity, amplitude of lateral head displacement at p p < 0.01. In conclusion, the removal of semen plasma through centrifugation improved motility properties of goat semen following the freezing/thawing procedure

Comparison of magnetic and non-magnetic nanoparticles as sonosensitizers in ultrasonic hyperthermia

Nanoparticles have attracted a great interest in scientific world because of the new applications they offer. They are commonly used in medical procedures such as hyperthermia and thermal ablation. Here, we propose, using magnetic and non-magnetic nanoparticles, as sonosensitizers which are the materials that improve the efficiency of heating induced by ultrasound. A comparison between various types of nanomaterials, such as magnetite, silicon dioxide, and Laponite nanoparticles, was done. The results show that both magnetic and non-magnetic nanomaterials can be utilized in ultrasonic heating. However, magnetite nanoparticles without surface modification can strongly interact with each other and are prone to agglomeration that can deteriorate thermal effect in tissuemimicking phantoms

The metabolome regulates the epigenetic landscape during naive-to-primed human embryonic stem cell transition.

For nearly a century developmental biologists have recognized that cells from embryos can differ in their potential to differentiate into distinct cell types. Recently, it has been recognized that embryonic stem cells derived from both mice and humans exhibit two stable yet epigenetically distinct states of pluripotency: naive and primed. We now show that nicotinamide N-methyltransferase (NNMT) and the metabolic state regulate pluripotency in human embryonic stem cells (hESCs).  Specifically, in naive hESCs, NNMT and its enzymatic product 1-methylnicotinamide are highly upregulated, and NNMT is required for low S-adenosyl methionine (SAM) levels and the H3K27me3 repressive state. NNMT consumes SAM in naive cells, making it unavailable for histone methylation that represses Wnt and activates the HIF pathway in primed hESCs. These data support the hypothesis that the metabolome regulates the epigenetic landscape of the earliest steps in human development

Bmi1 Is Down-Regulated in the Aging Brain and Displays Antioxidant and Protective Activities in Neurons

Aging increases the risk to develop several neurodegenerative diseases, although the underlying mechanisms are poorly understood. Inactivation of the Polycomb group gene Bmi1 in mice results in growth retardation, cerebellar degeneration, and development of a premature aging-like phenotype. This progeroid phenotype is characterized by formation of lens cataracts, apoptosis of cortical neurons, and increase of reactive oxygen species (ROS) concentrations, owing to p53-mediated repression of antioxidant response (AOR) genes. Herein we report that Bmi1 expression progressively declines in the neurons of aging mouse and human brains. In old brains, p53 accumulates at the promoter of AOR genes, correlating with a repressed chromatin state, down-regulation of AOR genes, and increased oxidative damages to lipids and DNA. Comparative gene expression analysis further revealed that aging brains display an up-regulation of the senescence-associated genes IL-6, p19Arf and p16Ink4a, along with the pro-apoptotic gene Noxa, as seen in Bmi1-null mice. Increasing Bmi1 expression in cortical neurons conferred robust protection against DNA damage-induced cell death or mitochondrial poisoning, and resulted in suppression of ROS through activation of AOR genes. These observations unveil that Bmi1 genetic deficiency recapitulates aspects of physiological brain aging and that Bmi1 over-expression is a potential therapeutic modality against neurodegeneration

Quantitative evaluation of oligonucleotide surface concentrations using polymerization-based amplification

Quantitative evaluation of minimal polynucleotide concentrations has become a critical analysis among a myriad of applications found in molecular diagnostic technology. Development of high-throughput, nonenzymatic assays that are sensitive, quantitative and yet feasible for point-of-care testing are thus beneficial for routine implementation. Here, we develop a nonenzymatic method for quantifying surface concentrations of labeled DNA targets by coupling regulated amounts of polymer growth to complementary biomolecular binding on array-based biochips. Polymer film thickness measurements in the 20–220 nm range vary logarithmically with labeled DNA surface concentrations over two orders of magnitude with a lower limit of quantitation at 60 molecules/μm2 (∼106 target molecules). In an effort to develop this amplification method towards compatibility with fluorescence-based methods of characterization, incorporation of fluorescent nanoparticles into the polymer films is also evaluated. The resulting gains in fluorescent signal enable quantification using detection instrumentation amenable to point-of-care settings

Frequent Heterogeneous Missense Mutations of GGAP2 in Prostate Cancer: Implications for Tumor Biology, Clonality and Mutation Analysis

Prostate cancer is the most common visceral malignancy in Western men and a major cause of cancer deaths. Increased activation of the AKT and NFkB pathways have been identified as critical steps in prostate cancer initiation and progression. GGAP2 (GTP-binding and GTPase activating protein 2) is a multidomain protein that contains an N-terminal Ras homology domain (GTPase), followed by a PH domain, a C-terminal GAP domain and an ankyrin repeat domain. GGAP2 can directly activate signaling via both the AKT and NFkB pathways and acts as a node of crosstalk between these pathways. Increased GGAP2 expression is present in three quarters of prostate cancers. Mutations of GGAP2 have been reported in cell lines from other malignancies. We therefore analyzed 84 prostate cancer tissues and 43 benign prostate tissues for somatic mutations in GGAP2 by direct sequencing of individual clones derived from the GAP and GTPase domains of normal and tumor tissue. Overall, half of cancers contained mutant GAP domain clones and in 20% of cancers, 30% or more of clones were mutant in the GAP domain. Surprisingly, the mutations were heterogeneous and nonclonal, with multiple different mutations being present in many tumors. Similar findings were observed in the analysis of the GTPase domain. Mutant GGAP2 proteins had significantly higher transcriptional activity using AP-1 responsive reporter constructs when compared to wild-type protein. Furthermore, the presence of these mutations was associated with aggressive clinical behavior. The presence of high frequency nonclonal mutations of a single gene is novel and represents a new mode of genetic alteration that can promote tumor progression. Analysis of mutations in cancer has been used to predict outcome and guide therapeutic target identification but such analysis has focused on clonal mutations. Our studies indicate that in some cases high frequency nonclonal mutations may need to be assessed as well

Evidence of Genetic Instability in Tumors and Normal Nearby Tissues

We have analyzed the sequence heterogeneity of the transcripts of the human HPRT and G6PD single copy genes that are not considered tumor markers. Analyses have been performed on different colon cancers and on the nearby histologically normal tissues of two male patients. Several copies of each cDNA, which were produced by cloning the RT-PCR-amplified fragments of the specific mRNA, have been sequenced. Similar analyses have been performed on blood samples of two ostensibly healthy males as reference controls. The sequence heterogeneity of the HPRT and G6PD genes was also determined on DNA from tumor tissues. The employed analytical approach revealed the presence of low-frequency mutations not detectable by other procedures. The results show that genetic heterogeneity is detectable in HPRT and G6PD transcripts in both tumors and nearby healthy tissues of the two studied colon tumors. Similar frequencies of mutations are observed in patient genomic DNA, indicating that mutations have a somatic origin. HPRT transcripts show genetic heterogeneity also in healthy individuals, in agreement with previous results on human T-cells, while G6PD transcript heterogeneity is a characteristic of the patient tissues. Interestingly, data on TP53 show little, if any, heterogeneity in the same tissues. CONCLUSIONS/SIGNIFICANCE: These findings show that genetic heterogeneity is a peculiarity not only of cancer cells but also of the normal tissue where a tumor arises

Predicting cancer involvement of genes from heterogeneous data

<p>Abstract</p> <p>Background</p> <p>Systematic approaches for identifying proteins involved in different types of cancer are needed. Experimental techniques such as microarrays are being used to characterize cancer, but validating their results can be a laborious task. Computational approaches are used to prioritize between genes putatively involved in cancer, usually based on further analyzing experimental data.</p> <p>Results</p> <p>We implemented a systematic method using the PIANA software that predicts cancer involvement of genes by integrating heterogeneous datasets. Specifically, we produced lists of genes likely to be involved in cancer by relying on: (i) protein-protein interactions; (ii) differential expression data; and (iii) structural and functional properties of cancer genes. The integrative approach that combines multiple sources of data obtained positive predictive values ranging from 23% (on a list of 811 genes) to 73% (on a list of 22 genes), outperforming the use of any of the data sources alone. We analyze a list of 20 cancer gene predictions, finding that most of them have been recently linked to cancer in literature.</p> <p>Conclusion</p> <p>Our approach to identifying and prioritizing candidate cancer genes can be used to produce lists of genes likely to be involved in cancer. Our results suggest that differential expression studies yielding high numbers of candidate cancer genes can be filtered using protein interaction networks. </p

Clonal mutations in primary human glial tumors: evidence in support of the mutator hypothesis

<p>Abstract</p> <p>Background</p> <p>A verifiable consequence of the mutator hypothesis is that even low grade neoplasms would accumulate a large number of mutations that do not influence the tumor phenotype (clonal mutations). In this study, we have attempted to quantify the number of clonal mutations in primary human gliomas of astrocytic cell origin. These alterations were identified in tumor tissue, microscopically confirmed to have over 70% neoplastic cells.</p> <p>Methods</p> <p>Random Amplified Polymorphic DNA (RAPD) analysis was performed using a set of fifteen 10-mer primers of arbitrary but definite sequences in 17 WHO grade II astrocytomas (low grade diffuse astrocytoma or DA) and 16 WHO grade IV astrocytomas (Glioblastoma Multiforme or GBM). The RAPD profile of the tumor tissue was compared with that of the leucocyte DNA of the same patient and alteration(s) scored. A quantitative estimate of the overall genomic changes in these tumors was obtained by 2 different modes of calculation.</p> <p>Results</p> <p>The overall change in the tumors was estimated to be 4.24% in DA and 2.29% in GBM by one method and 11.96% and 6.03% in DA and GBM respectively by the other. The difference between high and lower grade tumors was statistically significant by both methods.</p> <p>Conclusion</p> <p>This study demonstrates the presence of extensive clonal mutations in gliomas, more in lower grade. This is consistent with our earlier work demonstrating that technique like RAPD analysis, unbiased for locus, is able to demonstrate more intra-tumor genetic heterogeneity in lower grade gliomas compared to higher grade. The results support the mutator hypothesis proposed by Loeb.</p

Disease Gene Characterization through Large-Scale Co-Expression Analysis

In the post genome era, a major goal of biology is the identification of specific roles for individual genes. We report a new genomic tool for gene characterization, the UCLA Gene Expression Tool (UGET).Celsius, the largest co-normalized microarray dataset of Affymetrix based gene expression, was used to calculate the correlation between all possible gene pairs on all platforms, and generate stored indexes in a web searchable format. The size of Celsius makes UGET a powerful gene characterization tool. Using a small seed list of known cartilage-selective genes, UGET extended the list of known genes by identifying 32 new highly cartilage-selective genes. Of these, 7 of 10 tested were validated by qPCR including the novel cartilage-specific genes SDK2 and FLJ41170. In addition, we retrospectively tested UGET and other gene expression based prioritization tools to identify disease-causing genes within known linkage intervals. We first demonstrated this utility with UGET using genetically heterogeneous disorders such as Joubert syndrome, microcephaly, neuropsychiatric disorders and type 2 limb girdle muscular dystrophy (LGMD2) and then compared UGET to other gene expression based prioritization programs which use small but discrete and well annotated datasets. Finally, we observed a significantly higher gene correlation shared between genes in disease networks associated with similar complex or Mendelian disorders.UGET is an invaluable resource for a geneticist that permits the rapid inclusion of expression criteria from one to hundreds of genes in genomic intervals linked to disease. By using thousands of arrays UGET annotates and prioritizes genes better than other tools especially with rare tissue disorders or complex multi-tissue biological processes. This information can be critical in prioritization of candidate genes for sequence analysis