Biology subjects

Biondo, M.

Publications and source records attributed to Biondo, M..

4 recordsLinked to original sources

bioRxiv2026

Human SHED-derived extracellular cues activate a specialized neuroprotective and regenerative program in developing retinal ganglion cells

Axonal degeneration and insufficient neuronal survival remain major barriers to central nervous system repair. Stem cells from human exfoliated deciduous teeth (SHED) represent an accessible, developmentally immature, neural crest-derived mesenchymal stem cell population with potential relevance for neuroregenerative medicine. Here, we show that SHED display enhanced proliferative stability, preserved mesenchymal identity, and more sustained expansion capacity than adult dental pulp stem cells, supporting their suitability for scalable regenerative applications. Using embryonic chick retinal explants at neurogenic and post-neurogenic stages, we demonstrate that SHED robustly promote retinal ganglion cell axonogenesis, axonal regeneration, and neuronal survival. At embryonic day 5, SHED enhanced axonal outgrowth in both newly generated EdU/TUJ1 neurons and pre-existing EdU-/TUJ1 retinal ganglion cells. At embryonic day 13, when retinal neurons are post-mitotic and intrinsically less regenerative, SHED still significantly increased regenerative axonal extension and reduced developmental cell death. To investigate the molecular mechanisms underlying the neuroprotective and axogenic effects of SHED, proteomic profiling of SHED-retina co-culture secretomes was performed, revealing a highly enriched extracellular environment containing matrix-associated and neurodevelopmental proteins, including thrombospondin-1 (THBS1), galectin1 and 3, and multiple proteins associated with IGF2 pathway. Proteomic analysis of the SHED secretome, together with prior evidence implicating thrombospondin signaling in neuronal development and synaptogenesis, identified THBS1 as a strong candidate mediator of SHED-induced effects in chick retinal co-culture systems. Neutralization of THBS1, particularly in combination with gabapentin-mediated blockade of 2{delta}-1-dependent thrombospondin signaling, markedly reduced SHED-induced axonal growth and induced neuritic swellings consistent with impaired axonal integrity. In contrast, inhibition of THBS1 signaling did not significantly abolish the neuroprotective effect of SHED on neuronal survival, suggesting that distinct paracrine mechanisms independently regulate axonal regeneration and cell survival. Together, these findings demonstrate that SHED-derived combined secreted factors promote neuronal survival and axonal regeneration through partially divergent extracellular matrix-associated developmental pathways, positioning SHED and their secretome as promising candidates for cell-based and cell-free neuroregenerative strategies.

cell biology↗

bioRxiv2025

Intrinsic dimensionality of single-cell transcriptomic data reveals potency landscapes during cell reprogramming

Cell potency, the ability of a cell to generate other cell types, is a fundamental property that drives development, regeneration, and reprogramming. Recent computational advances have enabled estimation of potency directly from single-cell RNA sequencing (scRNA-seq) data, with intrinsic dimensionality (ID) emerging as a promising, data-driven measure of transcriptional complexity linked to developmental potential. While ID offers an unbiased and interpretable framework, existing implementations have two main limitations: they have been applied in only a narrow range of biological contexts, and rely on clustering, which restricts resolution at the single-cell level. Here, we introduce IDEAS (Intrinsic Dimensionality Estimation Analysis of single-cell RNA sequencing data), a Python-based toolkit that computes both global and single-cell ID from scRNA-seq data, enabling potency scoring without requiring predefined clusters. IDEAS extends ID-based potency estimation to single cells, showing its usefulness in a new biological setting. It offers a clear and reliable way to study cell plasticity, simplifies ID score calculation, and makes the method easier to use across different biological systems, speeding up research on this approach to measuring cell potency. We apply IDEAS to multiple datasets of cellular reprogramming, a dynamic and heterogeneous process in which cells transition between identities. Our analysis reveals that ID scores effectively capture changes in potency, identify partially reprogrammed intermediates, and delineate alternative reprogramming trajectories.

systems biology↗

bioRxiv2024

The intrinsic dimension of gene expression during cell differentiation

Waddingtons epigenetic landscape has long served as a conceptual framework for understanding cell fate decisions. The landscapes geometry encodes the molecular mechanisms that guide the gene expression profiles of uncommitted cells toward terminally differentiated cell types. In this study, we demonstrate that applying the concept of intrinsic dimension to single-cell transcriptomic data can effectively capture trends in expression trajectories, supporting this framework. This approach allows us to define a robust cell potency score without relying on prior biological information. By analyzing an extensive collection of datasets from various species, experimental protocols, and differentiation processes, we validate our method and successfully reproduce established hierarchies of cell type potency.

systems biology↗

bioRxiv2023

Out-of-equilibrium gene expression fluctuations in presence of extrinsic noise

Cell-to-cell variability in protein concentrations is strongly affected by extrinsic noise, especially for highly expressed genes. Extrinsic noise can be due to fluctuations of several possible cellular factors connected to cell physiology and to the level of key enzymes in the expression process. However, how to identify the predominant sources of extrinsic noise in a biological system is still an open question. This work considers a general stochastic model of gene expression with extrinsic noise represented as colored fluctuations of the different model rates, and focuses on the out-of-equilibrium expression dynamics. Combining analytical calculations with stochastic simulations, we fully characterize how extrinsic noise shapes the protein variability during gene activation or inactivation, depending on the prevailing source of extrinsic variability, on its intensity and timescale. In particular, we show that qualitatively different noise profiles can be identified depending on which are the fluctuating parameters. This indicates an experimentally accessible way to pinpoint the dominant sources of extrinsic noise using time-coarse experiments. Author summaryGenetically identical cells living in the same environment may differ in their phenotypic traits. These differences originate from the inherent stochasticity in all cellular processes, starting from the basic process of gene expression. At this level, large part of the variability comes from cell-to-cell differences in the rates of the molecular reactions due to stochasticity in the level of key enzymes or in physiological parameters such as cell volume or growth rate. Which expression rates are predominantly affected by these so-called "extrinsic" fluctuations and how they impact the level of protein concentration are still open research questions. In this work, we tackle the protein fluctuation dynamics while approaching a steady state after gene activation or repression in presence of extrinsic noise. Our analytical results and simulations show the different consequences of alternative dominant sources of extrinsic noise, thus providing an experimentally-accessible way to distinguish them in specific systems.

systems biology↗