A model of estrogen-related gene expression reveals non-linear effects in transcriptional response to tamoxifen

SynthSys is a Centre for Integrative Systems Biology (CISB) funded by BBSRC and EPSRC, reference BB/D019621/1.Background: Estrogen receptors alpha (ER) are implicated in many types of female cancers, and are the common target for anti-cancer therapy using selective estrogen receptor modulators (SERMs, such as tamoxifen). However, cell-type specific and patient-to-patient variability in response to SERMs (from suppression to stimulation of cancer growth), as well as frequent emergence of drug resistance, represents a serious problem. The molecular processes behind mixed effects of SERMs remain poorly understood, and this strongly motivates application of systems approaches. In this work, we aimed to establish a mathematical model of ER-dependent gene expression to explore potential mechanisms underlying the variable actions of SERMs. Results: We developed an equilibrium model of ER binding with 17 beta-estradiol, tamoxifen and DNA, and linked it to a simple ODE model of ER-induced gene expression. The model was parameterised on the broad range of literature available experimental data, and provided a plausible mechanistic explanation for the dual agonism/antagonism action of tamoxifen in the reference cell line used for model calibration. To extend our conclusions to other cell types we ran global sensitivity analysis and explored model behaviour in the wide range of biologically plausible parameter values, including those found in cancer cells. Our findings suggest that transcriptional response to tamoxifen is controlled in a complex non-linear way by several key parameters, including ER expression level, hormone concentration, amount of ER-responsive genes and the capacity of ER-tamoxifen complexes to stimulate transcription (e. g. by recruiting co-regulators of transcription). The model revealed non-monotonic dependence of ER-induced transcriptional response on the expression level of ER, that was confirmed experimentally in four variants of the MCF-7 breast cancer cell line. Conclusions: We established a minimal mechanistic model of ER-dependent gene expression, that predicts complex non-linear effects in transcriptional response to tamoxifen in the broad range of biologically plausible parameter values. Our findings suggest that the outcome of a SERM's action is defined by several key components of cellular micro-environment, that may contribute to cell-type-specific effects of SERMs and justify the need for the development of combinatorial biomarkers for more accurate prediction of the efficacy of SERMs in specific cell types.Publisher PDFPeer reviewe

Numerical studies of confinement in the lattice Landau gauge

Critical conjectures on confinement in the Landau gauge is numerically tested in focus to Gribov copy effects. One of the subjects is of the Kugo-Ojima confinement criterion and the other is of various viewpoints in the Gribov-Zwanziger theory. We use the smearing gauge as a reference gauge free of Gribov copy, and performed three types of simulations, log U, U-linear and log U in the smearing gauge. It is found that Gribov copy effect on the Kugo-Ojima parameter is small. log U and U-linear simulations yield only global scale factor difference in gluon propagator and in ghost propagator, and about 10% difference in Kugo-Ojima parameter. The horizon function defined by Zwanziger is evaluated in three types of gauge field and compared. All data show the negative horizon function as expected.Comment: 4 pages, 2 eps figures, espcrc2.sty included, Lattice 2000 contribution(Confinement and Strings

Landau Gauge Fixing supported by Genetic Algorithm

A class of algorithms for the Landau gauge fixing is proposed, which makes the steepest ascent (SA) method be more efficient by concepts of genetic algorithm. Main concern is how to incorporate random gauge transformation (RGT) %, mutation in genetic algorithm (GA) terminology, to gain higher achievement of the minimal Landau gauge fixing, and to keep lower time consumption. One of these algorithms uses the block RGT, and another uses RGT controlled by local fitness density, and the last uses RGT determined by Ising Monte Carlo process. We tested these algorithms on SU(2) lattice gauge theory in 4 dimension with small $\beta$s, 2.0, 1.75 and 1.5, and report improvements in hit rate and/or in time consumption, compared to other methods.Comment: 3 pages, 3 figures LATTICE'99(ALGORITHM

Dynamics of 5-methylcytosine and 5-hydroxymethylcytosine during germ cell reprogramming

Previous studies have revealed that mouse primordial germ cells (PGCs) undergo genome-wide DNA methylation reprogramming to reset the epigenome for totipotency. However, the precise 5-methylcytosine (5mC) dynamics and its relationship with the generation of 5-hydroxymethylcytosine (5hmC) are not clear. Here we analyzed the dynamics of 5mC and 5hmC during PGC reprograming and germ cell development. Unexpectedly, we found a specific period (E8.5-9.5) during which both 5mC and 5hmC levels are low. Subsequently, 5hmC levels increase reaching its peak at E11.5 and gradually decrease until E13.5 likely by replication-dependent dilution. Interestingly, 5hmC is enriched in chromocenters during this period. While this germ cell-specific 5hmC subnuclear localization pattern is maintained in female germ cells even in mature oocytes, such pattern is gradually lost in male germ cells as mitotic proliferation resumes during the neonatal stage. Pericentric 5hmC plays an important role in silencing major satellite repeat, especially in female PGCs. Global transcriptome analysis by RNA-seq revealed that the great majority of differentially expressed genes from E9.5 to 13.5 are upregulated in both male and female PGCs. Although only female PGCs enter meiosis during the prenatal stage, meiosis-related and a subset of imprinted genes are significantly upregulated in both male and female PGCs at E13.5. Thus, our study not only reveals the dynamics of 5mC and 5hmC during PGC reprogramming and germ cell development, but also their potential role in epigenetic reprogramming and transcriptional regulation of meiotic and imprinted genes

Tet1 controls meiosis by regulating meiotic gene expression

Meiosis is a germ cell-specific cell division process through which haploid gametes are produced for sexual reproduction1. Prior to initiation of meiosis, mouse primordial germ cells (PGCs) undergo a series of epigenetic reprogramming steps2,3, including global erasure of DNA methylation on the 5-position of cytosine (5mC) at CpG4,5. Although several epigenetic regulators, such as Dnmt3l, histone methyltransferases G9a and Prdm9, have been reported to be critical for meiosis6, little is known about how the expression of meiotic genes is regulated and how their expression contributes to normal meiosis. Using a loss of function approach, here we demonstrate that the 5mC-specific dioxygenase Tet1 plays an important role in regulating meiosis in mouse oocytes. Tet1 deficiency significantly reduces female germ cell numbers and fertility. Univalent chromosomes and unresolved DNA double strand breaks are also observed in Tet1-deficient oocytes. Tet1 deficiency does not greatly affect the genome-wide demethylation that takes place in PGCs but leads to defective DNA demethylation and decreased expression of a subset of meiotic genes. Our study thus establishes a function for Tet1 in meiosis and meiotic gene activation in female germ cells