Biology subjects

Saez, M.

Publications and source records attributed to Saez, M..

9 recordsLinked to original sources

bioRxiv2026

Minimal essential requirements for neural tube self-organisation

The reliable generation of diverse cell types in precise proportions is essential for the formation of functional tissues during embryonic development. Three-dimensional organoid models derived from pluripotent stem cells (PSCs) provide powerful systems for identifying principles governing tissue self-organisation. Neural tube organoids (NTOs), initiated from single PSCs with a pulse of retinoic acid (RA), self-organise into structures containing floorplate cells that secrete SHH morphogen to pattern adjacent neural tissue. Yet, how the initial cellular diversity arises and how appropriate cell-type proportions are allocated has remained unclear. Here, using time-resolved single-cell transcriptomics, quantitative immunofluorescence, and dynamical systems modelling we show that RA triggers a transient co-expression state of the transcription factors PAX6 and FOXA2 from which cells asynchronously resolve into two opposing fates: PAX6 neural precursors and FOXA2 floorplate precursors. PAX6 and FOXA2 are both necessary and sufficient to reconstitute self-organisation, establishing these transcription factors as key determinants of emergent tissue pattern. Rather than operating as a simple feed-forward system in which cells are guided solely by RA, feedback between the alternative cell fates, mediated by BMP signalling from floorplate precursors, determines cell type proportions and ensures reproducible cell-type diversity in each NTO. This dual expression state was also identified in mouse embryos, demonstrating how in vitro models inform in vivo biology. These findings establish a general design strategy - symmetry breaking through opposing fate determinants coupled to proportioning via signal feedback control - that may operate broadly across developmental contexts to generate tissues with predictable cellular compositions.

developmental biology↗

bioRxiv2026

Measuring developmental information encoded by a dynamicallandscape

During embryogenesis, as cells proliferate and assemble into tissues, they undergo a sequence of transitions between distinct molecular states eventually giving rise to a cellular population consisting of an appropriate distribution of specific functional cell types. Recent progress on the dynamics underlying decision-making in developmental landscape makes it feasible to start analysing the amount of information involved in constructing such systems. To explore this we introduce the notion of potency of a developmental landscape and attempt to calculate it for two development systems of current interest, in-vitro differentiation of epiblast-like cells into neural and mesodermal progenitors and the worm vulva patterning system. Our approach integrates concepts from developmental biology, information theory and dynamical systems to estimate both the number and identity of signalling regimes that give rise to distinguishable temporal response patterns.

developmental biology↗

bioRxiv2025

Dynamic Landscape Analysis of Cell Fate Decisions: Predictive Models of Neural Development From Single-Cell Data

Building a mechanistic understanding of cell fate decisions remains a fundamental goal of developmental biology, with implications for stem cell therapies, regenerative medicine and understanding disease mechanisms. Single-cell transcriptomics provides a detailed picture of the cellular states observed during these decisions, but building dynamic and predictive models from these data remains a challenge. Here, we present dynamic landscape analysis (DLA), a framework that applies dynamical systems theory to identify stable cell states, map transition pathways, and generate a predictive cell fate decision landscape from single-cell data. Applying this framework to vertebrate neural tube development, revealed that progenitor specification by Sonic Hedgehog (Shh) can be captured in a landscape with an unexpected topology in which initially divergent lineages converge to the same fate through multiple distinct routes. The model accurately predicted cellular responses and cell fate allocation for unseen dynamic signalling regimes. Cross-species validation using human embryonic organoid data demonstrated conservation of this decision-making architecture. By modelling the dynamic responses that drive cell fate decisions, the DLA framework provides a quantitative and generative framework for extracting mechanistic insights from high-dimensional single-cell data.

developmental biology↗

bioRxiv2024

Global and local nature of cortical slow waves

Explaining the macroscopic activity of a recorded neuronal population from its known microscopic properties still poses a great challenge, not just because of the many local agents that shape the output of a circuit, but due to the impact of long-range connections from other brain regions. Here we use a computational model to explore how local and global components of a network shape the Slow Wave Activity (SWA). We performed a sensitivity analysis of multiple cellular and synaptic features in models of isolated and connected networks. This allowed us to explore how the interaction of local properties and long-range connections shape the SWA of a population and its neighbors, as well as how the sequential propagation of active "Up" states lead to the emergence of preferred modes of propagation. We described relevant features of cortical Up states that are modulated by "stiff" combinations of parameters of the local circuit as opposed to other that are sensitive to the level of excitability of the whole network and the input coming from neighbor populations. We found that while manipulations in the synaptic excitatory/inhibitory balance can create local changes, cellular components that modulate the excitability or adaptation of a population have a long-range effect that leads to changes in neighbor populations too. Additionally, our simulations guided in vivo experiments that showed how heterogeneities in excitability between cortical areas can determine the directionality of travelling waves during SWA. We expect these results to motivate future research exploring and comparing cortical circuits through the analysis of their Up states.

neuroscience↗

bioRxiv2023

Dopamine enhances multisensory responses in the dorsomedial striatum

The brain operates with simultaneous different sensory modalities in order to engage adaptive responses. However, the question of how (and where) multisensory information is integrated remains unanswered. In the dorsomedial striatum, single medium spiny neurons (MSNs) are excited by tactile and visual inputs; however, the mechanism which allows the integration of these responses and how they are shaped by dopamine is unknown. Using in vivo optopatch-clamp recordings, we study how dopamine modulates tactile, visual and simultaneous bimodal responses in identified MSNs and their spontaneous activity. Results show that dopamine enhances bimodal responses, specifically in direct pathway MSNs, through the acceleration of the visual responses. We provide anatomical and computational evidence suggesting that this relies on the disinhibition of direct MSNs by a cell-type-specific corticostriatal pathway. Altogether, our in vivo, in silico and tracing results propose a new mechanism underlying the synchronization of multimodal information mediated by dopamine.

neuroscience↗

bioRxiv2023

Random Forest approach for the identification of relationships between epigenetic marks and its application to robust assignment of chromatin states

Structural changes of chromatin modulate access to DNA for all proteins involved in transcription. These changes are linked to variations in epigenetic marks that allow to classify chromatin in different functional states depending on the pattern of these marks. Importantly, alterations in chromatin states are known to be linked with various diseases. For example, there are abnormalities in epigenetic patterns in different types of cancer. For most of these diseases, there is not enough epigenomic data available to accurately determine chromatin states for the cells affected in each of them, mainly due to high costs of performing this type of experiments but also because of lack of a sufficient amount of sample or degradation thereof. In this work we describe a cascade method based on a random forest algorithm to infer epigenetic marks, and by doing so, to reduce the number of experimentally determined marks required to assign chromatin states. Our approach identified several relationships between patterns of different marks, which strengthens the evidence in favor of a redundant epigenetic code.

genomics↗

bioRxiv2022

Cholecystokinin exerts a major control on corticostriatal synapse and motor behavior

Cholecystokinin (CCK) is a neuropeptide detected and produced at high concentrations in the brain. To date it was mainly used as a neuronal marker of neuronal subtypes and its role as a neuromodulator was poorly known. However, few studies showed that it could be an essential neuromodulator in various brain structures, playing a role on synaptic plasticity and memory consolidation. In order to better understand the processes by which CCK impacts plasticity, we focus our attention on the striatum, a nucleus involved in procedural learning and motor behavior, with a rich expression of CCK receptor type 2 (CCK2R). By using in-vivo and ex-vivo electrophysiological approaches, we show that CCK is involved in the corticostriatal synaptic transmission and has a key role in its plasticity. Using in-vivo optopatch-clamp of identified MSNs, we observe a decrease of corticostriatal synaptic transmission after an injection of CCK2R antagonist, leading to a reduction of evoked excitatory post synaptic potential recorded on both MSNs populations (direct and indirect pathways). In addition, we evaluate the impact of CCK2R antagonist on corticostriatal synaptic plasticity using Spike Timing Dependent Plasticity (STDP) protocols on MSNs of acute rat brain slices. Results demonstrate that the CCK2R antagonist is able to reverse the corticostriatal synaptic plasticity (i.e. LTP protocol leads to LTD). Finally, we evaluate the effect of CCK2R antagonist on the motor behavior of juvenile rats challenged with different locomotor tests and show a sex-dependent impairment of motor behavior. Overall, our results demonstrate that CCK and its receptor CCK2R are essential for inputs processing encoding in the corticostriatal network with consequences on motor activity. Significant statementCholecystokinin (CCK) is considered to be one of the most abundant neuropeptides in the brain but its role as a neuromodulator is not well understood. In our study we investigate its role on the corticostriatal transmission which is a well characterized synapse highly involved in motor and cognitive functions. Here, we show that CCK2R is crucial for the corticostriatal synaptic transmission and plasticity. Indeed, CCK binding on CCK2R is essential for LTP induction by STDP. Finally, we demonstrate that the blockage of CCK2R affects corticostriatal synaptic transmission and motor ability in male rats.

neuroscience↗

bioRxiv2021

A quantitative landscape of cell fate transitions identifies principles of cellular decision-making

Fate decisions in developing tissues involve cells transitioning between a set of discrete cell states, each defined by a distinct gene expression profile. Geometric models, often referred to as Waddington landscapes, in which developmental paths are given by the gradient and cell states by the minima of the model, are an appealing way to describe differentiation dynamics and developmental decisions. To construct and validate accurate dynamical landscapes, quantitative methods based on experimental data are necessary. To this end we took advantage of the differentiation of neural and mesodermal cells from pluripotent mouse embryonic stem cells exposed to different combinations and durations of signalling factors. We developed a principled statistical approach using flow cytometry data to quantify differentiating cell states. Then, using a framework based on Catastrophe Theory and approximate Bayesian computation, we constructed the corresponding dynamical landscape. The result was a quantitative model that accurately predicted the proportions of neural and mesodermal cells differentiating in response to specific signalling regimes. Analysis of the geometry of the landscape revealed two distinct ways in which cells make a binary choice between one of two fates. We discuss the biological relevance of these mechanisms and suggest that they represent general archetypal designs for developmental decisions. Taken together, the approach we describe is broadly applicable for the quantitative analysis of differentiation dynamics and for determining the logic of developmental cell fate decisions.

developmental biology↗

bioRxiv2020

Slow Wave Oscillation reveals the discrete segregation of dorsal striatum

Behavioural studies differentiate the rodent dorsal striatum (DS) into lateral and medial regions based on their particular roles; however, anatomical evidence suggest that it is a unified structure. To understand striatal dynamics and basal ganglia functions, it is essential to clarify the circuitry that supports this behavioural-based segregation. Here, we show that the mouse DS is made of two non-overlapping functional circuits divided by a sharp boundary. Combining in vivo optopatch-clamp and extracellular recordings of spontaneous activity, we demonstrate different coupling of lateral and medial striatum to the cortex together with an independent integration of the slow and fast oscillations, due to particular cortico-striatal connectivity and local properties of each region. Additionally, distinct properties between striatonigral and striatopallidal neurons were revealed along DS. These results demonstrate that the rodent DS is segregated in two neuronal circuits, in homology with the caudate and putamen nuclei of primates.

neuroscience↗