Ca(2+) signals coordinate zygotic polarization and cell cycle progression in the brown alga Fucus serratus

Zygotes of the fucoid brown algae provide excellent models for addressing fundamental questions about zygotic symmetry breaking. Although the acquisition of polarity is tightly coordinated with the timing and orientation of the first asymmetric division-with zygotes having to pass through a G1/S-phase checkpoint before the polarization axis can be fixed -the mechanisms behind the interdependence of polarization and cell cycle progression remain unclear. In this study, we combine in vivo Ca(2+) imaging, single cell monitoring of S-phase progression and multivariate analysis of high-throughput intracellular Ca(2+) buffer loading to demonstrate that Ca(2+) signals coordinate polarization and cell cycle progression in the Fucus serratus zygote. Consistent with earlier studies on this organism, and in contrast to animal models, we observe no fast Ca(2+) wave following fertilization. Rather, we show distinct slow localized Ca(2+) elevations associated with both fertilization and S-phase progression, and we show that both S-phase and zygotic polarization are dependent on pre-S-phase Ca(2+) increases. Surprisingly, this Ca(2+) requirement cannot be explained by co-dependence on a single G1/ S-phase checkpoint, as S phase and zygotic polarization are differentially sensitive to pre-S-phase Ca(2+) elevations and can be uncoupled. Furthermore, subsequent cell cycle progression through M phase is independent of localized actin polymerization and zygotic polarization. This absence of a morphogenesis checkpoint, together with the observed Ca(2+)dependences of S phase and polarization, show that the regulation of zygotic division in the brown algae differs from that in other eukaryotic model systems, such as yeast and Drosophila.

Evolutionary agglomeration theory: increasing returns, diminishing returns, and the industry life cycle

According to Marshall’s agglomeration theory, Krugman’s New Economic Geography models, and Porter’s cluster policies, firms should receive increasing returns from a trinity of agglomeration economies: a local pool of skilled labour, local supplier linkages, and local knowledge spillovers. Recent evolutionary theories suggest that whether agglomeration economies generate increasing returns or diminishing returns depends on time, and especially the evolution of the industry life cycle. At the start of the twenty-first century, we re-examine Marshall’s trinity of agglomeration economies in the city-region where he discovered them. The econometric results from our multivariate regression models are the polar opposite of Marshall’s. During the later stages of the industry life cycle, Marshall’s agglomeration economies decrease the economic performance of firms and create widespread diminishing returns for the economic development of the city-region, which has evolved to become one of the poorest city-regions in Europe.

Comet sensitivity in assessing DNA damage and repair in different cell cycle stages

The comet assay is a sensitive tool for estimation of DNA damage and repair at the cellular level, requiring only a very small number of cells. In comparing the levels of damage or repair in different cell samples, it is possible that small experimental effects could be confounded by different cell cycle states in the samples examined, if sensitivity to DNA damage, and repair capacity, varies with the cell cycle. We assessed this by arresting HeLa cells in various cell cycle stages and then exposing them to ionizing radiation. Unirradiated cells demonstrated significant differences in strand break levels measured by the comet assay (predominantly single-strand breaks) at different cell cycle stages, increasing from G1 into S and falling again in G2. Over and above this variation in endogenous strand break levels, a significant difference in susceptibility to breaks induced by 3.5 Gy ionizing radiation was also evident in different cell cycle phases. Levels of induced DNA damage fluctuate throughout the cycle, with cells in G1 showing slightly lower levels of damage than an asynchronous population. Damage increases as cells progress through S phase before falling again towards the end of S phase and reaching lowest levels in M phase. The results from repair experiments (where cells were allowed to repair for 10 min after exposure to ionizing radiation) also showed differences throughout the cell cycle with G1-phase cells apparently being the most efficient at repair and M-phase cells the least efficient. We suggest, therefore, that in experiments where small differences in DNA damage and repair are to be investigated with the comet assay, it may be desirable to arrest cells in a specific stage of the cell cycle or to allow for differential cycle distribution.

The Deubiquitinating Enzyme USP17 Is Highly Expressed in Tumor Biopsies, Is Cell Cycle Regulated, and Is Required for G1-S Progression

Ubiquitination is a reversible posttranslational modification that is essential for cell cycle control, and it is becoming increasingly clear that the removal of ubiquitin from proteins by deubiquitinating enzymes (DUB) is equally important. In this study, we have identified high levels of the DUB USP17 in several tumor-derived cell lines and primary lung, colon, esophagus, and cervix tumor biopsies. We also report that USP17 is tightly regulated during the cell cycle in all the cells examined, being abundantly evident in G1 and absent in S phase. Moreover, regulated USP17 expression was necessary for cell cycle progression because its depletion significantly impaired G1-S transition and blocked cell proliferation. Previously, we have shown that USP17 regulates the intracellular translocation and activation of the GTPase Ras by controlling Ras-converting enzyme 1 (RCE1) activation. RCE1 also regulates the processing of other proteins with a CAAX motif, including Rho family GTPases. We now show that USP17 depletion blocks Ras and RhoA localization and activation. Moreover, our results confirm that USP17-depleted cells have constitutively elevated levels of the cyclin-dependent kinase inhibitors p21cip1 and p27kip1, known downstream targets of Ras and RhoA signaling. These observations clearly show that USP17 is tightly regulated during cell division and that its expression is necessary to coordinate cell cycle progression, and thus, it may be considered a promising novel cancer therapeutic target. Cancer Res; 70(8); 3329–39. ©2010 AACR.

Hierarchical coordination of periodic genes in the cell cycle of Saccharomyces cerevisiae

Background: Gene networks are a representation of molecular interactions among genes or products thereof and, hence, are forming causal networks. Despite intense studies during the last years most investigations focus so far on inferential methods to reconstruct gene networks from experimental data or on their structural properties, e.g., degree distributions. Their structural analysis to gain functional insights into organizational principles of, e.g., pathways remains so far under appreciated.

Predicting Cell Cycle Regulated Genes by Causal Interactions

The fundamental difference between classic and modern biology is that technological innovations allow to generate high-throughput data to get insights into molecular interactions on a genomic scale. These high-throughput data can be used to infer gene networks, e. g., the transcriptional regulatory or signaling network, representing a blue print of the current dynamical state of the cellular system. However, gene networks do not provide direct answers to biological questions, instead, they need to be analyzed to reveal functional information of molecular working mechanisms. In this paper we propose a new approach to analyze the transcriptional regulatory network of yeast to predict cell cycle regulated genes. The novelty of our approach is that, in contrast to all other approaches aiming to predict cell cycle regulated genes, we do not use time series data but base our analysis on the prior information of causal interactions among genes. The major purpose of the present paper is to predict cell cycle regulated genes in S. cerevisiae. Our analysis is based on the transcriptional regulatory network, representing causal interactions between genes, and a list of known periodic genes. No further data are used. Our approach utilizes the causal membership of genes and the hierarchical organization of the transcriptional regulatory network leading to two groups of periodic genes with a well defined direction of information flow. We predict genes as periodic if they appear on unique shortest paths connecting two periodic genes from different hierarchy levels. Our results demonstrate that a classical problem as the prediction of cell cycle regulated genes can be seen in a new light if the concept of a causal membership of a gene is applied consequently. This also shows that there is a wealth of information buried in the transcriptional regulatory network whose unraveling may require more elaborate concepts than it might seem at first.