Biology subjects

Govindaraj, V.

Publications and source records attributed to Govindaraj, V..

3 recordsLinked to original sources

bioRxiv2026

Parental B-MYB/FOXM1 controls mitotic E2F to determine daughter cell fate

Mitogens trigger cell-cycle entry by activating E2F at the restriction point, which is followed by B-MYB/FOXM1 activation and progression to mitosis. How mitogens control continued cycling and cell-cycle exit after the restriction point is not well-understood. By developing an E2F and B-MYB/FOXM1 dual transcriptional biosensor system, we show that S/G2 phase duration is set by timed mitogen-regulated B-MYB/FOXM1 activation, while E2F activity gradually declines before mitosis. As a striking consequence, rapid B-MYB/FOXM1 activation shortens S/G2, delivering high mitotic E2F activity to daughter cells which keeps them cycling. Delayed B-MYB/FOXM1 activation prolongs S/G2, depleting mitotic E2F which drives daughters to quiescence. When S/G2 is further prolonged, partially activated B-MYB/FOXM1 frequently reverts, triggering mitotic bypass and polyploid quiescence. Thus, B-MYB/FOXM1 governs a tri-directional (G2 restriction point) where cells commit to continued cycling through early B-MYB/FOXM1 activation; cell-cycle exit through delayed B-MYB/FOXM1 activation; or mitotic bypass by B-MYB/FOXM1 inactivation.

cell biology↗

bioRxiv2022

Transcriptional fluctuations govern the serum dependent cell cycle duration heterogeneities in Mammalian cells

Mammalian cells exhibit a high degree of intercellular variability in cell cycle period and phase durations. However, the factors orchestrating the cell cycle duration heterogeneities remain unclear. Herein, by combining cell cycle network-based mathematical models with live single-cell imaging studies under varied serum conditions, we demonstrate that fluctuating transcription rates of cell cycle regulatory genes across cell lineages and during cell cycle progression in mammalian cells majorly govern the robust correlation patterns of cell cycle period and phase durations among sister, cousin, and mother-daughter lineage pairs. However, for the overall cellular population, alteration in serum level modulates the fluctuation and correlation patterns of cell cycle period and phase durations in a correlated manner. These heterogeneities at the population level can be finetuned under limited serum conditions by perturbing the cell cycle network using a p38-signaling inhibitor without affecting the robust lineage level correlations. Overall, our approach identifies transcriptional fluctuations as the key controlling factor for the cell cycle duration heterogeneities, and predicts ways to reduce cell-to-cell variabilities by perturbing the cell cycle network regulations. Significance statementIn malignant tumors, cells display a diverse pattern in cell division time. This cell-to-cell variability in cell cycle duration had been observed even under culture conditions for various mammalian cells. Here we used live-cell imaging studies to monitor FUCCI-HeLa cells and quantified the cell cycle period and time spent in different phases under varied serum conditions. We proposed a set of stochastic cell cycle network-based mathematical models to investigate the live-cell imaging data and unraveled that the transcription rate variation across cell lineages and during cell cycle phases explains every aspect of the cell cycle duration variabilities. Our models identified how different deterministic effects and stochastic fluctuations control these variabilities and predicted ways to alter these cell cycle duration variabilities.

systems biology↗

bioRxiv2017

Subtle alteration in microRNA dynamics accounts for differential nature of cellular proliferation

In the G1 phase of the mammalian cell cycle, a bi-stable steady state dynamics of the transcription factor E2F ensures that only a certain threshold level of the growth factor can induce a high expression level (on state) of E2F to initiate either normal or abnormal cellular proliferation or even apoptosis. A group of microRNAs known as the mir-17-92 cluster, which specifically inhibits E2F, can simultaneously influence the threshold level of growth factor required for E2F activation, and the corresponding expression level of E2F in the on state. However, mir-17-92 cluster can function as either oncogene or tumor suppressor in a cell-type specific manner for reasons that still remain illusive. Here we put forward a deterministic mathematical model for Myc/E2F/mir-17-92 network that demonstrates how the experimentally observed mir-17-92 mediated differential nature of the cellular proliferation can be reconciled by having conflicting steady state dynamics of E2F for different cell types. While a 2-D bifurcation study of the model rationalizes the reason behind the contrasting E2F dynamics, an intuitive sensitivity analysis of the model parameters predicts that by exclusively altering the mir-17-92 related part of the network, it is possible to experimentally manipulate the cellular proliferation in a cell-type specific fashion for therapeutic intervention.

systems biology↗