Extracellular Self-DNA Effects on Yeast Cell Cycle and Transcriptome during Batch Growth.

G1 Phase Regulation, Area-Specific Cell Cycle Control, and Cytoarchitectonics in the Primate Cortex

The ability of biological systems to adapt to genetic and environmental perturbations is a fundamental but poorly understood process at the molecular level. By quantifying metabolic fluxes and global mRNA abundance, we investigated the genetic and metabolic mechanisms that underlie adaptive evolution of four metabolic gene deletion mutants of Escherichia coli (delta pgi, delta ppc, delta pta, and delta tpi) in parallel evolution experiments of each mutant. The initial response to the gene deletions was flux rerouting through local bypass reactions or normally latent pathways. The principal effect of evolution was improved capacity of already active pathways, whereas new flux distributions were not observed. Combinatorial changes in capacity and pathway activation, however, led to different intracellular flux states that enabled evolution in three of the four parallel cases tested. The molecular bases of the evolved phenotypes were then elucidated by global mRNA transcript analyses. Activation of latent pathways and flux changes in the tricarboxylic acid cycle were found to correlate well with molecular changes at the transcriptional level. Flux alterations in other central metabolic pathways, in contrast, were apparently not connected to changes in the transcriptional network. These results give new insight into the dynamics of the evolutionary process by demonstrating the flexibility of the metabolic network of E. coli to compensate for genetic perturbations and the utility of combining multiple high throughput data sets to differentiate between causal and noncausal mechanistic changes.

HIV/gp120 Decreases Adult Neural Progenitor Cell Proliferation via Checkpoint Kinase-Mediated Cell-Cycle Withdrawal and G1 Arrest

This chapter describes the major Candida albicans morphologies and the current understanding of the cell biological and cell cycle features that distinguish them. It highlights recent insights into how cell cycle regulators influence the formation of hypha-specific cellular features in particular. Since morphogenesis and cell cycle regulation have been studied most extensively in C. albicans, the chapter primarily focuses on work in C. albicans. The important distinction between yeast and pseudohyphae is that pseudohyphae spend more time in G2 phase of the cell cycle than yeast cells , and they continue to elongate during this time. There has long been a controversy as to how pseudohyphae are related to true hyphae. Initial models suggested that yeast cells, pseudohyphae, and true hyphae reside along a continuum. Later, based on differences in cell cycle dynamics and subcellular structures, it was proposed that pseudohyphae and hyphae represent two distinct morphological states, with pseudohyphae being more like yeast form growth with respect to cell cycle progression and cell biological markers. Recent work has shed light on cell biological features associated with cell cycle progression in chlamydospores and is discussed in theis chapter. In the C. albicans genome sequence, there are three G1 cyclins (Ccn1, Cln3, and Hgc1) and two G2 or B-type/mitotic cyclins (Clb2 and Clb4) that are predicted to associate with Cdc28.

Binge alcohol exposure in adolescent rats potently inhibits adult hippocampal neurogenesis by altering neural progenitor cell (NPC) proliferation and survival; however, it is not clear whether alcohol results in an increase or decrease in net proliferation. Thus, the effects of alcohol on hippocampal NPC cell cycle phase distribution and kinetics were assessed in an adolescent rat model of an alcohol use disorder. Cell cycle distribution was measured using a combination of markers (Ki-67, bromodeoxyuridine incorporation, and phosphohistone H3) to determine the proportion of NPCs within G1, S, and G2/M phases of the cell cycle. Cell cycle kinetics were calculated using a cumulative bromodeoxyuridine injection protocol to determine the effect of alcohol on cell cycle length and S-phase duration. Binge alcohol exposure reduced the proportion of NPCs in S-phase, but had no effect on G1 or G2/M phases, indicating that alcohol specifically targets S-phase of the cell cycle. Cell cycle kinetics studies revealed that alcohol reduced NPC cell cycle duration by 36% and shortened S-phase by 62%, suggesting that binge alcohol exposure accelerates progression through the cell cycle. This effect would be expected to increase NPC proliferation, which was supported by a slight, but significant increase in the number of Sox-2+ NPCs residing in the hippocampal subgranular zone following binge alcohol exposure. These studies suggest the mechanism of alcohol inhibition of neurogenesis and also reveal the earliest evidence of the compensatory neurogenesis reaction that has been observed a week after binge alcohol exposure.

Kinetic parameters are a crucial aspect when studying reactions involving proteins. Unfortunately, these are often unknown or hard to measure in the laboratory. Therefore, modeling phenomena involving protein reactions without using kinetic parameters can be a significant advantage. In this work, an agent-based model of the budding yeast (Saccharomyces cerevisiae) cell cycle was created based on a cell cycle regulatory network, to obtain the correct sequence of states of the regulatory proteins. Comparing the results to a Boolean network model, having similar results, following the correct sequence of phases and reaching in 71% of the cases the biological G1 stationary state of the cell. Yeast cell cycle is highly conservated among other eukaryotes, meaning that is regulators works similar than the ones in humans; knowing that, yeast cells can be mutated to have behavior related to a specific tumor and then treated with different drugs to check which is better to kill that particular tumor. This model could be a starting point for being used in the development of cancer drugs adding cell cycle mutations that match a specific type of tumor cell cycle and an agent representing the medication or treatment.

During embryonic development, changes in cell cycle kinetics have been associated with neurogenesis. This observation suggests that specific cell cycle regulators may be recruited to modify cell cycle dynamics and influence the decision between proliferation and differentiation. In the present study, we investigate the role of core positive cell cycle regulators, the CDC25 phosphatases, in this process. We report that, in the developing chicken spinal cord, only CDC25A is expressed in domains where neural progenitors undergo proliferative self-renewing divisions, whereas the combinatorial expression of CDC25A and CDC25B correlates remarkably well with areas where neurogenesis occurs. We also establish that neural progenitors expressing both CDC25A and CDC25B have a shorter G2 phase than those expressing CDC25A alone. We examine the functional relevance of these correlations using an RNAi-based method that allows us to knock down CDC25B efficiently and specifically. Reducing CDC25B expression results in a specific lengthening of the G2 phase, whereas the S-phase length and the total cell cycle time are not significantly modified. This modification of cell cycle kinetics is associated with a reduction in neuron production that is due to the altered conversion of proliferating neural progenitor cells to post-mitotic neurons. Thus, expression of CDC25B in neural progenitors has two functions: to change cell cycle kinetics and in particular G2-phase length and also to promote neuron production, identifying new roles for this phosphatase during neurogenesis.

During embryonic development, changes in cell cycle kinetics have been associated with neurogenesis. This observation suggests that specific cell cycle regulators may be recruited to modify cell cycle dynamics and influence the decision between proliferation and differentiation. In the present study, we investigate the role of core positive cell cycle regulators, the CDC25 phosphatases, in this process. We report that, in the developing chicken spinal cord, only CDC25A is expressed in domains where neural progenitors undergo proliferative self-renewing divisions, whereas the combinatorial expression of CDC25A and CDC25B correlates remarkably well with areas where neurogenesis occurs. We also establish that neural progenitors expressing both CDC25A and CDC25B have a shorter G2 phase than those expressing CDC25A alone. We examine the functional relevance of these correlations using an RNAi-based method that allows us to knock down CDC25B efficiently and specifically. Reducing CDC25B expression results in a specific lengthening of the G2 phase, whereas the S-phase length and the total cell cycle time are not significantly modified. This modification of cell cycle kinetics is associated with a reduction in neuron production that is due to the altered conversion of proliferating neural progenitor cells to post-mitotic neurons. Thus, expression of CDC25B in neural progenitors has two functions: to change cell cycle kinetics and in particular G2-phase length and also to promote neuron production, identifying new roles for this phosphatase during neurogenesis.

The E3 ubiquitin-protein ligase Chfr is a mitotic stress checkpoint protein that delays mitotic entry in response to microtubule damage; however, the molecular mechanism by which Chfr accomplishes this remains elusive. Here, we show that Chfr levels are elevated in response to microtubule-damaging stress. Moreover, G(2)/M transition is associated with cell cycle-dependent turnover of Chfr accompanied by high autoubiquitylation activity, suggesting that regulation of Chfr levels and auto-ubiquitylation activity are functionally significant. To test this, we generated Chfr mutants Chfr-K2A and Chfr-K5A in which putative lysine target sites of auto-ubiquitylation were replaced with alanine. Chfr-K2A did not undergo cell cycle-dependent degradation, and its levels remained high during G(2)/M phase. The elevated levels of Chfr-K2A caused a significant reduction in phosphohistone H3 levels and cyclinB1/Cdk1 kinase activities, leading to mitotic entry delay. Notably, polo-like kinase 1 levels at G(2) phase, but not at S phase, were ∼2-3-fold lower in cells expressing Chfr-K2A than in wild-type Chfr-expressing cells. Consistent with this, ubiquitylation of Plk1 at G(2) phase was accelerated in Chfr-K2A-expressing cells. In contrast, Aurora A levels remained constant, indicating that Plk1 is a major target of Chfr in controlling the timing of mitotic entry. Indeed, overexpression of Plk1 in Chfr-K2A-expressing cells restored cyclin B1/Cdk1 kinase activity and promoted mitotic entry. Collectively, these data indicate that Chfr auto-ubiquitylation is required to allow Plk1 to accumulate to levels necessary for activation of cyclin B1/Cdk1 kinase and mitotic entry. Our results provide the first evidence that Chfr auto-ubiquitylation and degradation are important for the G(2)/M transition.

We propose an integrated computational model for the network of cyclin-dependent kinases (Cdks) that controls the dynamics of the mammalian cell cycle. The model contains four Cdk modules regulated by reversible phosphorylation, Cdk inhibitors, and protein synthesis or degradation. Growth factors (GFs) trigger the transition from a quiescent, stable steady state to self-sustained oscillations in the Cdk network. These oscillations correspond to the repetitive, transient activation of cyclin D/Cdk4-6 in G(1), cyclin E/Cdk2 at the G(1)/S transition, cyclin A/Cdk2 in S and at the S/G(2) transition, and cyclin B/Cdk1 at the G(2)/M transition. The model accounts for the following major properties of the mammalian cell cycle: (i) repetitive cell cycling in the presence of suprathreshold amounts of GF; (ii) control of cell-cycle progression by the balance between antagonistic effects of the tumor suppressor retinoblastoma protein (pRB) and the transcription factor E2F; and (iii) existence of a restriction point in G(1), beyond which completion of the cell cycle becomes independent of GF. The model also accounts for endoreplication. Incorporating the DNA replication checkpoint mediated by kinases ATR and Chk1 slows down the dynamics of the cell cycle without altering its oscillatory nature and leads to better separation of the S and M phases. The model for the mammalian cell cycle shows how the regulatory structure of the Cdk network results in its temporal self-organization, leading to the repetitive, sequential activation of the four Cdk modules that brings about the orderly progression along cell-cycle phases.

Lee Hartwell: rebel with a cause

Recent studies have suggested that Bcl-2 can affect cell cycle re-entry by inhibiting the transition from G0/G1 to S phase. In this study, we have taken a novel route to the study of the relationship between Bcl-2 expression and cell cycle progression. Continuous cultures of pEF (control) and Bcl-2 transfected murine hybridoma cells were operated at a range of dilution rates from 0.8 day-1 down to 0.2 day-1. The specific growth rate of the pEF cell line was the same as the dilution rate down to a value of 0.6 day-1. However, as the dilution rate was reduced stepwise to 0.2 day-1, the growth rate levelled-off at approximately 0.55 day-1 and this coincided with a fall in culture viability. By contrast, the specific growth rate of the Bcl-2 transfected cell line followed the dilution rate down to a value of 0.3 day-1 with high levels of cell survival. At high dilution rates, the cell cycle distributions were very similar for both cell lines. However, the distributions diverged as the dilution rate was reduced and, at a rate of 0.2 day-1, the percentage of G1 cells in the Bcl-2 culture was 80%, compared to only 56% in the pEF cell population. This corresponded with a greater extension in the duration of the G1 phase in the Bcl-2 cells, which was 1.7 days at the lowest dilution rate tested, compared to only 0.6 day for the pEF cell line. The durations of the G2/M and S phases remained constant throughout the culture. The maximum doubling time was 1.2 days in the pEF culture compared to 2.3 days in the Bcl-2 culture. Analysis of amino acids, ammonia and lactate concentrations indicated that the observed effects on cell cycle dynamics were probably not due to differences in the culture environment. It is suggested that the expression of Bcl-2 can effect G1 to S phase transition in continuously cycling cells, but this is only apparent at suboptimal growth rates.

Background: Precision medicine emphasizes individualized cancer treatment, particularly for elderly lung cancer patients facing unique chemotherapy challenges. Age-related changes in cell cycle dynamics significantly influence therapeutic outcomes, yet their role in optimizing personalized therapies remains underexplored. This study investigates these age-related dynamics to inform personalized therapeutic strategies for elderly lung cancer patients. Methods: Single-cell RNA sequencing data from 166 healthy individuals (aged 25-85 years) were analyzed to explore age-associated changes in cell cycle distribution, differentially expressed genes (DEGs), and enriched pathways. Young (9-11 weeks) and aged (17 months) mice received weekly cisplatin for four cycles. Peripheral blood and hematopoietic stem cells (HSCs) were monitored dynamically for cell cycle phases, DNA damage (γ-H2AX), and vascular leakiness using immunofluorescence. RNA sequencing of HSCs identified DEGs and enriched pathways after treatment cycles. Results: Single-cell analysis revealed a linear decrease in S-phase proportions with age (r=−0.681, p=0.0026) and identified 28 DEGs, including PAXB-AS1, BABAM1, and DONSON, enriched in immune regulation and cell cycle pathways. In murine models, aged mice showed impaired immune recovery, with persistently higher neutrophil proportions (post-cycle 1: 14.75% vs. 6.1%, p<0.05) and lower lymphocyte proportions (post-cycle 1: 65.73% vs. 79.98%, post-cycle 4: 60.5% vs. 63.8%) compared to young mice. Moreover, aged mice exhibited delayed neutrophil recovery (Day 4 vs. Day 2), accompanied by persistent G1-phase arrest in HSCs (Day 4: 86% vs. 82%) and reduced G2/M-phase proportions (Day 4: 3% vs. 6%). RNA sequencing of aged HSCs further revealed significant enrichment in the DNA_DAMAGE_TELOMERE_STRESS_INDUCED_SENESCENCE pathway after four treatment cycles (|NSE| = 1.98, p < 0.05), a pattern absent in young mice. Finally, γ-H2AX flow cytometry confirmed increased DNA damage in aged HSCs, while immunofluorescence demonstrated heightened bone marrow vascular leakiness in aged mice. Conclusion: Aging significantly alters cell cycle dynamics, hematopoietic recovery, and chemotherapy responses, highlighting the need to integrate cell cycle-based insights into personalized treatment strategies. These findings provide a foundation for future research on age-specific therapeutic interventions in lung cancer. Citation Format: Jianxing He,Yue Pan,Hao Liu,Ying Huang,Hongsheng Deng,Chao Yang,Qi Cai,Shan Xiong,Huiting Liu,Wenhua Liang. Age-dependent changes in cell cycle dynamics and hematopoietic responses to chemotherapy [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 622.

How cells coordinate their metabolism with division determines the rate of cell proliferation. Dynamic patterns of metabolite synthesis during the cell cycle are unexplored. We report the first isotope tracing analysis in synchronous, growing budding yeast cells. Synthesis of leucine, a branched‐chain amino acid (BCAA), increases through the G1 phase of the cell cycle, peaking later during DNA replication. Cells lacking Bat1, a mitochondrial aminotransferase that synthesizes BCAAs, grow slower, are smaller, and are delayed in the G1 phase, phenocopying cells in which the growth‐promoting kinase complex TORC1 is moderately inhibited. Loss of Bat1 lowers the levels of BCAAs and reduces TORC1 activity. Exogenous provision of valine and, to a lesser extent, leucine to cells lacking Bat1 promotes cell division. Valine addition also increases TORC1 activity. In wild‐type cells, TORC1 activity is dynamic in the cell cycle, starting low in early G1 but increasing later in the cell cycle. These results suggest a link between BCAA synthesis from glucose to TORC1 activation in the G1 phase of the cell cycle.

Wavelet analysis has been applied to yeast cell cycle expression microchip data to reveal large-scale temporal structures and ubiquitous oscillations in mRNA levels. Discrete intervals in time within the cell cycle when expression levels changed were visualized as contour maps in which points of transition in gene expression among all 6178 genes were plotted as a function of cell cycle time. Time-frequency analysis using wavelet transforms supported the direct visualization and led to the conclusion that the predominant period is not the cell cycle but a higher frequency, 40 min, submultiple of the cycle. Each of the 6178 gene expression profiles was dissected by wavelet decomposition into all permitted frequencies from the Nyquist limit to roughly twice the cell cycle length. Transitions associated with maximum up- or down-regulation of mRNA levels appear as bands at circa 40-min intervals, half the length of the cycle, through two cell cycles. More than two thirds of the genes, including many of the cyclins, showed this half-cycle periodicity. Gene expression and events within the yeast cell cycle may be regulated by an attractor whose fundamental period is an emergent property of dynamic interactions within the yeast transcriptome.