MicroRNAs associated with the mir-17-92 cluster are crucial regulators of the mammalian cell cycle, as they inhibit transcription factors related to the E2F family that tightly control decision-making events for a cell to commit for active cellular proliferation. Intriguingly, in many solid cancers, these mir-17-92 cluster members are overexpressed, whereas in some hematopoietic cancers they are down-regulated. Our proposed model of the Myc/E2F/mir-17-92 network demonstrates that the differential expression pattern of mir-17-92 in different cell types can be conceived due to having a contrasting E2F dynamics induced by mir-17-92. The model predicts that by explicitly altering the mir-17-92-related part of the network, experimentally it is possible to control cellular proliferation in a cell type-dependent manner for therapeutic intervention.

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 the 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 fine-tuned 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.

Dimethyl-2,5-bis(4-methoxyphenylamino)terephthalate (DBMPT) is a water-insoluble fluorogenic molecule, which has been rendered water-soluble in physiological conditions, by the addition of triblock copolymers (TBPs), P123 (PEO 19 PPO 69 PEO 19 ), and F127 (PEO 100 PPO 65 PEO 100 ). DBMPT-TBP mixed aggregates, formed in the process, exhibit significant aggregation-induced enhancement of emission, with nanosecond fluorescence lifetimes. Dynamics involved in suppression of nonradiative pathways and consequent enhancement of fluorescence are followed by femtosecond transient absorption and time-resolved fluorescence spectroscopic techniques. Interestingly, shapes of the aggregates formed with the two TBPs are found to be very different, even though they differ only in the length of hydrophilic blocks. DBMPT-P123 aggregates are micrometer-sized and spherical, while DBMPT-F127 aggregates form nanorods. Evolution of their morphologies, as a function of TBP concentration, is monitored using cryo-TEM, FESEM, and fluorescence lifetime imaging microscopy. Fluorescence lifetime distribution provides useful insight into microheterogeneity in these mixed aggregates. Excellent cell permeability is observed for DBMPT-F127 nanorods, in contrast to DBMPT-P123 microspheres. These fluorescent nanorods exhibit the ability to mark lipid droplets within the cell and hence bear the promise for application in intracellular imaging.

MicroRNAs (miRNAs) often govern the cell fate decision‐making events associated with oncogenesis. miRNAs repress the target genes either by degrading the target mRNA or inhibiting the process of translation. However, mathematical and computational modeling of miRNA‐mediated target gene regulation in various cellular network motifs indicates that miRNAs play a much more complex role in cellular decision‐making events. In this review, we give an overview of the quantitative insights obtained from mathematical modeling of miRNA‐mediated gene regulations by highlighting the various factors associated with it that are pivotal in diversifying the cell fate decisions related to oncogenesis. Intriguingly, recent experiments suggest that under certain circumstances, miRNAs can lead to more complex gene regulatory dynamics by causing target gene upregulation. We discuss these modeling approaches that can help in understanding the subtleties of miRNA effects in oncogenesis.

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 fine-tuned 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.