Biology subjects

Marinopoulou, E.

Publications and source records attributed to Marinopoulou, E..

6 recordsLinked to original sources

bioRxiv2025

Oscillatory Co-expression of HES1 and HES5 Enables a Hybrid State in a Bistable Transcription Factor Regulatory Motif

Many cell fate decisions in the developing neural tube are directed by cross-repressive transcription factor (TF) motifs that generate bistability, enforcing expression of one dominant TF. However, evidence of hybrid states, where cells co-express opposing fate determinants, challenges this model. We hypothesised that oscillatory expression enables co-existence of cross-repressive TFs within single cells, allowing hybrid states in bistable motifs. To test this, we focused on HES1 and HES5, oscillatory, cross-repressive TFs that regulate neural progenitor maintenance and are expressed in adjacent dorsoventral domains in the developing spinal cord. Using live-cell imaging of fluorescent reporters and computational modelling, we show that HES1 and HES5 co-express and oscillate in-phase within single cells. Differences in protein stability result in distinct free-running periodicity, but co-expression results in entrainment and phase-locking. Modulating cross-repression strength and/or abundance shifts the system towards bistability and dominance of a single TF oscillator. Consistent with this, we observe progressive separation of the HES expression domains in vivo, through a decrease in oscillatory co-expression. Our findings provide a mechanism for hybrid states to emerge in a developmental bistable motif.

developmental biology↗

bioRxiv2024

NGN3 oscillatory expression controls the timing of human pancreatic endocrine differentiation

Understanding protein expression dynamics is crucial for the mechanistic understanding of cell differentiation. We investigate the dynamics of NGN3, a transcription factor critical for pancreatic endocrine development, including their function and decoding mechanisms. A knock-in endogenous reporter shows that the expression of NGN3 protein oscillates with a 13-hour periodicity in human iPS-derived endocrine progenitors and is switched off as cells differentiate to {beta}-like and -like cells. Increasing the stability of NGN3 protein results in one broad peak of expression instead of oscillations, with a larger peak to trough fold-change. This leads to precocious endocrine differentiation to both {beta}-like and -like cells and precocious expression of key NGN3 target genes. Single-cell analysis of dynamics, mathematical modelling and bioinformatics suggest that decoding of NGN3 oscillations occurs by fold-change detection via an incoherent feedforward motif that explains both normal and precocious differentiation. Our findings suggest that oscillatory NGN3 dynamics control the timing of differentiation, but not fate specification.

developmental biology↗

bioRxiv2023

Identification of genes with oscillatory expression in glioblastoma: The paradigm of SOX2

Quiescence, a reversible state of cell-cycle arrest, is an important state during both normal development and cancer progression. For example, in glioblastoma (GBM) quiescent glioblastoma stem cells (GSCs) play an important role in re-establishing the tumour, leading to relapse. While most studies have focused on identifying differentially expressed genes between proliferative and quiescent cells as potential drivers of this transition, recent studies have shown the importance of protein oscillations in controlling the exit from quiescence of neural stem cells. Here, we have undertaken a genome-wide bioinformatic inference approach to identify genes whose expression oscillates and which may be good candidates for controlling the transition to and from the quiescent cell state in GBM. Our analysis identified, among others, a list of important transcription regulators as potential oscillators, including the stemness gene SOX2, which we verified to oscillate in quiescent GSCs. These findings expand on the way we think about gene regulation and introduce new candidate genes as key regulators of quiescence.

cancer biology↗

bioRxiv2022

Cell coupling compensates for changes in single-cell Her6 dynamics and provides phenotypic robustness

her6 is a zebrafish ortholog of Hes1, known for its role in maintaining neural progenitors during neural development. Here, we characterise the population-level effect of altering Her6 protein expression dynamics at the single-cell level in the embryonic zebrafish telencephalon. Using an endogenous Her6:Venus reporter and 4D single-cell tracking, we show that Her6 oscillates in neural telencephalic progenitors and that fusion of a protein destabilisation domain (PEST) to Her6:Venus alters its expression dynamics causing most cells to downregulate Her6 prematurely. However, in PEST mutants, a higher proportion of cells exhibit Her6 oscillations and while expression is reduced in most cells, some cells express Her6 at wild-type levels resulting in increased heterogeneity of Her6 expression in the population. Despite the profound differences in the single-cell Her6 dynamics, differentiation markers do not exhibit major differences early on, while an increase in differentiation is observed at later developmental stages (vglut2a, gad1 and gad2). At the same time, at late stage the overall size of the telencephalon remains the same. Computational modelling that simulates changes in Her6 protein stability reveals that the increase in population Her6 expression heterogeneity is an emergent property of finely tuned Notch signalling coupling between single cells. Our study suggests that such cell coupling provides a compensation strategy whereby a normal phenotype is maintained while single-cell dynamics are abnormal, although the limit of this compensation is reached at late developmental stages. We conclude that in the neural progenitor population, cell coupling controls Her6 expression heterogeneity and in doing so, it provides phenotypic robustness when individual cells lose Her6 expression prematurely.

developmental biology↗

bioRxiv2021

HES1 protein oscillations are necessary for neural stem cells to exit from quiescence

Quiescence is a dynamic process of reversible cell-cycle arrest. High-level sustained expression of the HES1 transcriptional repressor, which oscillates with an ultradian periodicity in proliferative neural stem cells (NSCs), is thought to mediate quiescence. However, it is not known whether this is due to a change in levels or in dynamics. Here, we induce quiescence in NSCs with BMP4, which does not increase HES1 level, and we find that HES1 continues to oscillate. To assess the role of HES1 dynamics, we express sustained HES1 under a moderate-strength promoter, which overrides the endogenous oscillations while maintaining the total HES1 level within physiological range. We find that sustained HES1 does not affect proliferation or entry into quiescence, however, exit from quiescence is impeded. Thus, oscillatory expression of HES1 is specifically required for NSCs to exit quiescence, a finding of potential importance for controlling reactivation of stem cells in tissue regeneration and cancer.

cell biology↗

bioRxiv2019

OscoNet: Inferring oscillatory gene networks

MotivationOscillatory genes, with periodic expression at the mRNA and/or protein level, have been shown to play a pivotal role in many biological contexts. However, with the exception of the circadian clock and cell cycle, only a few such genes are known. Detecting oscillatory genes from snapshot single-cell experiments is a challenging task due to the lack of time information. Oscope is a recently proposed method to identify co-oscillatory gene pairs using single-cell RNA-seq data. Although promising, the current implementation of Oscope does not provide a principled statistical criterion for selecting oscillatory genes.\n\nResultsWe improve the optimisation scheme underlying Oscope and provide a well-calibrated non-parametric hypothesis test to select oscillatory genes at a given FDR threshold. We evaluate performance on synthetic data and three real datasets and show that our approach is more sensitive than the original Oscope formulation, discovering larger sets of known oscillators while-avoiding the need for less interpretable thresholds. We also describe how our proposed pseudo-time estimation method is more accurate in recovering the true cell order for each gene cluster while-requiring substantially less computation time than the extended nearest insertion approach.\n\nConclusionOscoNet is a robust and versatile approach to detect oscillatory gene networks from snapshot single-cell data addressing many of the limitations of the original Oscope method.

bioinformatics↗