Purification and functional characterization of type II DNA topoisomerase from rat testis and comparison with topoisomerase II from liver

A number of studies in yeast have shown that DNA topoisomerase TI is essential for chromosome condensation and disjunction during mitosis at the metaphase/anaphase transition and meiosis I. Accordingly, kinetic and mechanistic studies have implied a role for topoisomerase rr in chromosome disjunction. As a step toward understanding the nature and role of topoisomerase II in a mammalian germline in vivo, we have purified topoisomerase II from rat testis to homogeneity and ascertained several of its catalytic activities in conjunction with that of the purified enzyme from liver. The purified enzymes appeared to be monomers under denaturing conditions; however, they differed in their relative molecular mass. Topoisomerase II from testis and liver have apparent molecular masses of 150 +/- 10 kDa and 160 +/- 10 kDa, respectively. The native molecular mass of testis topoisomerase II as assayed by immunoblot analysis of cell-foe extracts, prepared in the presence of SDS and a number of protease inhibitors, corroborated with the size of the purified enzyme. Both enzymes are able to promote decatenation and relax supercoiled DNA substrates in an ATP and Mg2+-dependent manner. However, quantitative comparison of catalytic properties of topoisomerase II from testis with that of the enzyme from liver displayed significant differences in their efficiencies. Optimal pH values for testis enzyme are 6.5 to 8.5 while they are 6 to 7.5 for the liver enzyme. Intriguingly, the relaxation activity of liver topoisomerase II was inhibited by potassium glutamate at 1 M, whereas testis enzyme required about half its concentration. These findings argue that topoisomerase II from rat testis is structurally distinct from that of its somatic form and the functional differences between the two enzymes parallels with the physiological environment that is unique to these two tissues.

Distress call-induced gene expression in the brain of the Indian short-nosed fruit bat, Cynopterus sphinx

Individuals in distress emit audible vocalizations to either warn or inform conspecifics. The Indian short-nosed fruit bat, Cynopterus sphinx, emits distress calls soon after becoming entangled in mist nets, which appear to attract conspecifics. Phase I of these distress calls is longer and louder, and includes a secondary peak, compared to phase II. Activity-dependent expression of egr-1 was examined in free-ranging C. sphinx following the emissions and responses to a distress call. We found that the level of expression of egr-1 was higher in bats that emitted a distress call, in adults that responded, and in pups than in silent bats. Up-regulated cDNA was amplified to identify the target gene (TOE1) of the protein Egr-1. The observed expression pattern Toe1 was similar to that of egr-1. These findings suggest that the neuronal activity related to recognition of a distress call and an auditory feedback mechanism induces the expression of Egr-1. Co-expression of egr-1 with Toe1 may play a role in initial triggering of the genetic mechanism that could be involved in the consolidation or stabilization of distress call memories.

How do heterogametic females survive without gene dosage compensation?

When the male is the heterogametic sex (XX♀-XY♂ or XX♀-XO♂), as inDrosophila, orthopteran insects, mammals andCaenorhabditis elegans, X-linked genes are subject to dosage compensation: the single X in the male is functionally equivalent to the two Xs in the female. However, when the female is heterogametic (ZZ♂-ZW♀), as in birds, butterflies and moths, Z-linked genes are apparently not dosage-compensated. This difference between X-linked and Z-linked genes raises fundamental questions about the role of dosage compensation. It is argued that (i) genes which require dosage compensation are primarily those that control morphogenesis and the prospective body plan; (ii) the products of these genes are required in disomic doses especially during oogenesis and early embryonic development; (iii) heterogametic females synthesize and store during oogenesis itself morphogenetically essential gene products - including those encoded by Z-linked genes — in large quantities; (iv) the abundance of these gene products in the egg and their persistence relatively late into embryogenesis enables heterogametic females to overcome the monosomic state of the Z chromosome in ZW embryos. Female heterogamety is predominant in birds, reptiles and amphibians, all of which have megalecithal eggs containing several thousand times more maternal RNA and other maternal messages than eggs of mammals,Caenorhabditis elegans, orDrosophila. This increase in egg size, yolk content and, concomitantly, the size of the maternal legacy to the embryo, may have facilitated female heterogamety and the absence of dosage compensation.

NETGEM: Network Embedded Temporal GEnerative Model for gene expression data

Background: Temporal analysis of gene expression data has been limited to identifying genes whose expression varies with time and/or correlation between genes that have similar temporal profiles. Often, the methods do not consider the underlying network constraints that connect the genes. It is becoming increasingly evident that interactions change substantially with time. Thus far, there is no systematic method to relate the temporal changes in gene expression to the dynamics of interactions between them. Information on interaction dynamics would open up possibilities for discovering new mechanisms of regulation by providing valuable insight into identifying time-sensitive interactions as well as permit studies on the effect of a genetic perturbation. Results: We present NETGEM, a tractable model rooted in Markov dynamics, for analyzing the dynamics of the interactions between proteins based on the dynamics of the expression changes of the genes that encode them. The model treats the interaction strengths as random variables which are modulated by suitable priors. This approach is necessitated by the extremely small sample size of the datasets, relative to the number of interactions. The model is amenable to a linear time algorithm for efficient inference. Using temporal gene expression data, NETGEM was successful in identifying (i) temporal interactions and determining their strength, (ii) functional categories of the actively interacting partners and (iii) dynamics of interactions in perturbed networks. Conclusions: NETGEM represents an optimal trade-off between model complexity and data requirement. It was able to deduce actively interacting genes and functional categories from temporal gene expression data. It permits inference by incorporating the information available in perturbed networks. Given that the inputs to NETGEM are only the network and the temporal variation of the nodes, this algorithm promises to have widespread applications, beyond biological systems. The source code for NETGEM is available from https://github.com/vjethava/NETGEM

Transcriptional Repression of Tumor Suppressor CDC73, Encoding an RNA Polymerase II Interactor, by Wilms Tumor 1 Protein (WT1) Promotes Cell Proliferation IMPLICATION FOR CANCER THERAPEUTICS

The Wilms tumor 1 gene (WT1) can either repress or induce the expression of genes. Inconsistent with its tumor suppressor role, elevated WT1 levels have been observed in leukemia and solid tumors. WT1 has also been suggested to act as an oncogene by inducing the expression of MYC and BCL-2. However, these are only the correlational studies, and no functional study has been performed to date. Consistent with its tumor suppressor role, CDC73 binds to RNA polymerase II as part of a PAF1 transcriptional regulatory complex and causes transcriptional repression of oncogenes MYC and CCND1. It also represses beta-catenin-mediated transcription. Based on the reduced level of CDC73 in oral squamous cell carcinoma (OSCC) samples in the absence of loss-of-heterozygosity, promoter methylation, and mutations, we speculated that an inhibitory transcription factor is regulating its expression. The bioinformatics analysis predicted WT1 as an inhibitory transcription factor to regulate the CDC73 level. Our results showed that overexpression of WT1 decreased CDC73 levels and promoted proliferation of OSCC cells. ChIP and EMSA results demonstrated binding of WT1 to the CDC73 promoter. The 5-azacytidine treatment of OSCC cells led to an up-regulation of WT1 with a concomitant down-regulation of CDC73, further suggesting regulation of CDC73 by WT1. Exogenous CDC73 attenuated the protumorigenic activity of WT1 by apoptosis induction. An inverse correlation between expression levels of CDC73 and WT1 was observed in OSCC samples. These observations indicated that WT1 functions as an oncogene by repressing the expression of CDC73 in OSCC. We suggest that targeting WT1 could be a therapeutic strategy for cancer, including OSCC.