Biology subjects

Olariu, V.

Publications and source records attributed to Olariu, V..

9 recordsLinked to original sources

bioRxiv2025

Hic2 fast-tracks iPS cell generation by suppressing KLF4-dependent epidermal detour

Reprogramming somatic cells to induced pluripotent stem cells (iPSCs) is the most established cellular conversion by exogenous master transcription factors (TFs). A deeper understanding of this yet inefficient process is critical to extending our capability to control cellular identity for medical applications. Here we report 14 genes essential for efficient iPSC generation, but dispensable for self-renewal. Of those, overexpression of Hic2, a transcriptional suppressor highly expressed in PSCs, enhances iPSC generation [~]10-fold. This is achieved through a more direct transition towards pluripotency, bypassing an intermediate state with KLF4-dependent transient epidermal gene expression during iPSC generation. Mechanistically, HIC2 co-occupies these KLF4 targets and directly inhibits their expression. Our work demonstrates that master TFs necessary for cellular conversions can also activate obstructive genes during cellular reprogramming. We propose that identifying transcriptional suppressors against such side effects, like Hic2, can be a powerful strategy to achieve more efficient TF-mediated cell conversions.

developmental biology↗

bioRxiv2024

Generating human parvalbumin interneurons through 3D glia reprogramming

Parvalbumin (PV) interneurons are crucial for synaptic plasticity, and their damage or loss is linked to various neurological disorders. Yet, generating these cells of human source in vitro is challenging, limiting advancements in cell repair and disease modelling. We introduce a novel approach to derive human PV neurons through direct reprogramming of glial precursor cells (GPCs). Using ectopic expression of GABAergic neuronal genes, GPCs efficiently convert into GABAergic interneurons in 3D culture environment within weeks and achieve functional neuronal maturity. Single-nuclei RNA sequencing identified a distinct PV neuronal cluster with high maturity and characteristics of PV chandelier subclass that are equivalent to bona fide human interneurons. Trajectory analysis revealed a distinct glia-to-PV interneuron conversion pathway, involving several new transitory genes, with potential for functional importance for PV derivation. Our data introduces a new strategy for generating human PV interneurons, promising significant implications for future generation of patient-specific PV neurons both in vitro and in vivo. HighlightsO_LIA novel approach to derive human PV interneurons by direct glia reprogramming. C_LIO_LIFirst comprehensive transcriptomic profiling of induced human PV interneurons. C_LIO_LIInduced PV interneurons are of chandelier subtype with transcriptional similarity to bona fide interneurons. C_LIO_LISuccessful glia-to-PV interneuron conversion passes through a specific reprogramming trajectory and involves key genes with functional potential. C_LI

neuroscience↗

bioRxiv2023

T-cell commitment inheritance - an agent-based multi-scale model

T-cell development provides an excellent model system for studying lineage commitment from a multipotent progenitor. The intrathymic development process has been thoroughly studied. The molecular circuitry controlling it has been dissected and the necessary steps like programmed shut off of progenitor genes and T-cell genes upregulation have been revealed. However, the exact timing between decision-making and commitment stage remains unexplored. To this end, we implemented an agent-based multi-scale model to investigate inheritance in early T-cell development. Treating each cell as an agent provides a powerful tool as it tracks each individual cell of a simulated T-cell colony, enabling the construction of lineage trees. Based on the lineage trees, we introduce the concept of the last common ancestors (LCA) of committed cells and analyse their relations, both at single-cell level and population level. In addition to simulating wild-type development, we also conduct knockdown analysis. Our simulations showed that the commitment is a three-step process over several cell generations where a cell is first prepared by a transcriptional switch. This is followed by the loss of the Bcl11b-opposing function two to three generations later which is when the decision to commit is taken. Finally, after another one to two generations, the cell becomes committed by transitioning to the DN2b state. Our results showed that there is inheritance in the commitment mechanism.

systems biology↗

bioRxiv2022

CELLoGeNe - an Energy Landscape Framework for Logical Networks Controlling Cell Decisions

Experimental and computational efforts are constantly made to elucidate mechanisms controlling cell fate decisions during development and cell reprogramming. One powerful method is to consider cell commitment and reprogramming as movements in an energy landscape. Here, we develop CELLoGeNe (Computation of Energy Landscapes of Logical Gene Networks), which maps Boolean implementation of gene regulatory networks (GRNs) into energy landscapes. CELLoGeNe removes inadvertent symmetries in the energy landscapes normally arising from standard Boolean operators. Furthermore, CELLoGeNe provides a tool for visualising multi-dimensional energy landscapes and a platform to stochastically probe and analyse the shapes of the computed landscapes corresponding to the epigenetic landscapes for development and reprogramming. We demonstrate CELLoGeNe on a GRN governing maintenance and self-renewal of pluripotency, identifying attractors experimentally validated. We also apply CELLoGeNe on a network controlling reprogramming from mouse embryonic fibroblast (MEF) to induced pluripotent stem cells (iPSCs) where we identify potential roadblocks as attractors. CELLoGeNe is a general framework that can be applied to various biological systems offering a broad picture of intracellular dynamics otherwise inaccessible with existing methods.

systems biology↗

bioRxiv2022

B1 SINE-binding ZFP266 impedes reprogramming through suppression of chromatin opening by pioneering factors

Induced pluripotent stem cell reprogramming is inherently inefficient and understanding the molecular mechanisms underlying this inefficiency holds the key to successfully control cellular identity. Here, we report 16 novel reprogramming roadblock genes identified by CRISPR/Cas9-mediated genome-wide knockout (KO) screening. Of these, depletion of the predicted KRAB zinc finger protein (KRAB-ZFP) Zfp266 strongly and consistently enhanced iPSC generation in several iPSC reprogramming settings, emerging as the most robust roadblock. Further analyses revealed that ZFP266 binds Short Interspersed Nuclear Elements (SINEs) adjacent to binding sites of pioneering factors, OCT4 (POU5F1), SOX2 and KLF4, and impedes chromatin opening. Replacing the KRAB co-suppressor with a co-activator domain converted ZFP266 from a reprogramming inhibitor to a potent reprogramming facilitator. This work proposes SINE-KRAB-ZFP interaction to be a critical regulator of chromatin accessibility at enhancers for efficient cellular identity changes and also serves as a resource to further illuminate molecular mechanisms hindering reprogramming.

cell biology↗

bioRxiv2020

Neural tube patterning: from a minimal model for rostrocaudal patterning towards an integrated 3D model

The rostrocaudal patterning of the neural tube is a key event in early brain development. This process is mainly driven by a gradient of WNT, which defines the fate of the present neural progenitor cells in a dose dependent matter and leads to a subdivision of the tube into forebrain, midbrain and hindbrain. Although this process is extensively studied experimentally both in vivo and in vitro, an integrated view of the responsible genetic circuitry is currently lacking. In this work, we present a minimal gene regulatory model for rostrocaudal neural tube patterning. The model's nodes and architecture are determined in a data driven way, leading to a tristable configuration of mutually repressing brain regions. Analysis of the parameter sensitivity and simulations of knockdown and overexpression cases show that repression of hindbrain fate is a promising strategy for the improvement of current protocols for the generation of dopaminergic neurons in vitro. Furthermore, we combine the model with an existing model for dorsoventral neural tube patterning, to test its capabilities in an in vivo setting, by predicting the steady state pattern of a realistic three-dimensional neural tube. This reveals that the rostrocaudal pattern stacks dorsoventrally in the caudal half of the neural tube. Finally, we simulate morphogen secretion overexpression, which highlights the sensitivity of neural tube patterning to the morphogen levels.

systems biology↗

bioRxiv2020

A Quantitative Model of Cellular Decision Making in Direct Neuronal Reprogramming

The direct reprogramming of adult skin fibroblasts to neurons is thought to be controlled by a small set of interacting gene regulators. Here, we investigate how the interaction dynamics between these regulating factors coordinate cellular decision making in direct neuronal reprogramming. We put forward a quantitative model of the governing gene regulatory system, supported by measurements of mRNA expression level dynamics. We find that reinterpreting the interaction between two genes (PTB and nPTB) is necessary to capture quantitative gene interaction dynamics and correctly predict the outcome of various overexpression and knockdown experiments. This analysis is strengthened by a novel analytical technique to dissect system behaviour and reveal the influence of individual factors on resulting gene expression. Overall, we demonstrate that computational analysis is a powerful tool for understanding the mechanisms of direct (neuronal) reprogramming, paving the way for future models that can help improve cell conversion strategies.

systems biology↗

bioRxiv2019

Multi-scale dynamical modelling of T-cell development from an early thymic progenitor state to lineage commitment

Thymic development of committed pro-T-cells from multipotent hematopoietic precursors offers a unique opportunity to dissect the molecular circuitry establishing cell identity in response to environmental signals. This transition encompasses programmed shutoff of stem/progenitor genes, upregulation of T-cell specification genes, extensive proliferation, and commitment after a delay. We have incorporated these factors, as well as new single cell gene expression and developmental kinetics data, into a three-level dynamic model of commitment based upon regulation of the commitment gene Bcl11b. The first level is a core gene regulatory network architecture determined by transcription factor perturbation data, the second a stochastically controlled epigenetic gate, and the third a proliferation model validated by growth and commitment kinetics measured at single-cell levels. Using expression values consistent with single molecule RNA-FISH measurements of key transcription factors, this single-cell model exhibits state switching consistent with measured population and clonal proliferation and commitment times. The resulting multi-scale model provides a powerful mechanistic framework for dissecting commitment dynamics.

systems biology↗

bioRxiv2017

Revisiting the erythroid-myeloid lineage decision - a data-driven dynamical model analysis

It is widely conjectured that the mutually antagonizing pair of transcription factors GATA1 and PU.1, deter-mines the choice between the erythroid and myeloid lineages in hematopoiesis. In theoretical approaches, this appears natural with a bistable switch driving the decision. Recent extensive binding and gene expression experiments with some focus on the triad GATA1, GATA2 and PU.1 indicate that GATA2 may be more involved in this lineage decision than previously anticipated. Here, we analyze these experimental data by modeling regulatory sub-networks with deterministic rate equations. Using network dynamical parameters determined by the data, we deduce from increasing the self-interaction bindings in silico among the triad genes that GATA2 and PU.1 exhibit non-linear behavior with one unstable and one stable state. This is in contrast to GATA1, which shows smoother behavior. We extend the network to include the downstream regulators FOG1 and CEBPA, and extract the nature of the corresponding regulatory interactions, excitatory or suppressing, between this pair and the triad by fitting to experimental gene expression time series. Based on this extended network, we simulate and explore different knockout scenarios, providing insight into the role of these regulators in the process of lineage specification, as well as predictions for future experimental validation. We address the mechanism of GATA switching as a mechanism of lineage differentiation by investigating the dynamics of FOG1 regulation by GATA2 and GATA1. Overall, this analysis strongly suggests that within this network, GATA2 is the key driver of erythroid lineage specification through its repression of PU.1, whereas GATA1 appears to be more relevant for the downstream differentiation events.

systems biology↗