Chk1 Inhibits E2F6 Repressor Function in Response to Replication Stress to Maintain Cell-Cycle Transcription

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E2F7 and E2F8 keep the E2F family in balance

An article by Li and colleagues (in this issue of Developmental Cell) shows that the atypical E2Fs, E2F7 and E2F8, are critical for mouse development. One of the important functions of these family members stems from a negative feedback loop in which E2F7 and E2F8 limit the expression of E2F1 and prevent E2F1-dependent apoptosis.     

DNA-damage response control of E2F7 and E2F8

Here, we report that the two recently identified E2F subunits, E2F7 and E2F8, are induced in cells treated with DNA-damaging agents where they have an important role in dictating the outcome of the DNA-damage response. The DNA-damage-dependent induction coincides with the binding of E2F7 and E2F8 to the promoters of certain E2F-responsive genes, most notably that of the E2F1 gene, in which E2F7 and E2F8 coexist in a DNA-binding complex. As a consequence, E2F7 and E2F8 repress E2F target genes, such as E2F1, and reducing the level of each subunit results in an increase in E2F1 expression and activity. Importantly, depletion of either E2F7 or E2F8 prevents the cell-cycle effects that occur in response to DNA damage. Thus, E2F7 and E2F8 act upstream of E2F1, and influence the ability of cells to undergo a DNA-damage response. E2F7 and E2F8, therefore, underpin the DNA-damage response.     

Specificity of E2F1, E2F2, and E2F3 in mediating phenotypes induced by loss of Rb.

The Rb/E2F pathway plays a critical role in the control ofcellular proliferation. Here, we report that E2F1, E2F2, and E2F3 make major individual contributions toward the in vivo phenotypic consequences of Rb deficiency. In the developing lens of Rb(-/-) embryos, loss of E2F1, E2F2, or E2F3 reduces the unscheduled proliferation of fiber cells, with the loss of E2F3 having the most pronounced effect. In Rb-deficient retinas, all three E2Fs contribute equally to the ectopic proliferation of postmitotic neuronal cells. In contrast, E2F1 is unique in mediating apoptosis in both Rb(-/-) lenses and retinas. In the central nervous system, loss of E2F1 or E2F3 can almost completely eliminate the ectopic DNA replication and apoptosis observed in Rb(-/-) embryos, and loss of E2F2 partially reduces the unscheduled DNA replication and has no effect on apoptosis. These results provide clear evidence for functional specificity among E2Fs in the control of Rb-dependent proliferation and apoptosis in a tissue-specific manner.     

E2F1 and E2F2 Determine Thresholds for Antigen-Induced T-Cell Proliferation and Suppress Tumorigenesis

E2F activity is critical for the control of the G(1) to S phase transition. We show that the combined loss of E2F1 and E2F2 results in profound effects on hematopoietic cell proliferation and differentiation, as well as increased tumorigenesis and decreased lymphocyte tolerance. The loss of E2F1 and E2F2 impedes B-cell differentiation, and hematopoietic progenitor cells in the bone marrow of mice lacking E2F1 and E2F2 exhibit increased cell cycling. Importantly, we show that E2F1 and E2F2 double-knockout T cells exhibit more rapid entry into S phase following antigenic stimulation. Furthermore, T cells lacking E2F1 and E2F2 proliferate much more extensively in response to subthreshold antigenic stimulation. Consistent with these observations, E2F1/E2F2 mutant mice are highly predisposed to the development of tumors, and some mice exhibit signs of autoimmunity.     

E2F1 and E2F3 activate ATM through distinct mechanisms to promote E1A-induced apoptosis

Deregulation of the Rb-E2F pathway occurs in many cancers and results in aberrant cell proliferation as well as an increased propensity to undergo apoptosis. In most cases, apoptosis in response to Rb inactivation involves the activation of p53 but the molecular details of the signaling pathway connecting Rb loss to p53 are poorly understood. Here we demonstrate that the E1A oncoprotein, which binds and inhibits Rb family members, induces the accumulation and phosphorylation of p53 through the DNA damage-responsive ATM kinase. As a result, E1A-induced apoptosis is significantly impaired in cells lacking ATM. In contrast, inactivation of ARF, which is widely believed to activate p53 in response to oncogenic stress, has no effect on p53 induction and only a modest effect on apoptosis in response to E1A. Both E2F1 and E2F3 contribute to ATM-dependent phosphorylation of p53 and apoptosis in cells expressing E1A. However, deregulated E2F3 activity is implicated in the DNA damage caused by E1A while E2F1 stimulates ATM- and NBS1-dependent p53 phosphorylation and apoptosis through a mechanism that does not involve DNA damage.     

Endocycle and E2F-Dependent Transcriptional Activation and Repression

No abstract available.     

Stochastic Models of Soil Denitrification

Soil denitrification is a highly variable process that appears to be lognormally distributed. This variability is manifested by large sample coefficients of variation for replicate estimates of soil core denitrification rates. Deterministic models for soil denitrification have been proposed in the past, but none of these models predicts the approximate lognormality exhibited by natural denitrification rate estimates. In this study, probabilistic (stochastic) models were developed to understand how positively skewed distributions for field denitrification rate estimates result from the combined influences of variables known to affect denitrification. Three stochastic models were developed to describe the distribution of measured soil core denitrification rates. The driving variables used for all the models were denitrification enzyme activity and CO₂ production rates. The three models were distinguished by the functional relationships combining these driving variables. The functional relationships used were (i) a second-order model (model 1), (ii) a second-order model with a threshold (model 2), and (iii) a second-order saturation model (model 3). The parameters of the models were estimated by using 12 separate data sets (24 replicates per set), and their abilities to predict denitrification rate distributions were evaluated by using three additional independent data sets of 180 replicates each. Model 2 was the best because it produced distributions of denitrification rate which were not significantly different (P > 0.1) from distributions of measured denitrification rates. The generality of this model is unknown, but it accurately predicted the mean denitrification rates and accounted for the stochastic nature of this variable at the site studied. The approach used in this study may be applicable to other areas of ecological research in which accounting for the high spatial variability of microbiological processes is of interest.