Biology subjects

Olmeda, F.

Publications and source records attributed to Olmeda, F..

3 recordsLinked to original sources

bioRxiv2026

Adult regenerative defects arise from discordant scaling of signal dependent growth and patterning

Orders of magnitude distinguish an organs size in adulthood from its size when patterning was established during embryonic development. The prospect of engineering adult organ regeneration raises the fundamental question of whether regenerative stem cell patterning should be elicited at embryonic or adult scale. Axolotls regenerate their limbs at all stages of post-embryonic life, encompassing an order of magnitude increase in animal size, but the mechanisms allowing this robust capacity remain unclear. Limb regeneration occurs by the formation of an embryonic-like progenitor zone, the blastema, whose dimensions increase with animal size, suggesting that at least some aspects of limb regeneration must scale. Here, by combining spatial transcriptomics, biophysical modelling, quantitative imaging, and functional perturbations, we found distinct scaling signatures among key signaling pathways, arguing against a body-size-dependent hormonal scaling mechanism. SHH signaling showed partial scaling that saturated in largest adult sizes, with a correspondingly early termination of blastema growth while Wnt9a-modulated digit patterning scaled at all animal sizes. As a result of this differential scaling, digit patterning wavelength was mismatched with respect to domain growth in the largest blastemas, preventing the addition of the last digit. In agreement with this model, regenerative failure can be rescued by timed supplementation of SHH. Our results show that coordinated scaling of morphogen signaling is a key requirement for adult organ regeneration.

systems biology↗

bioRxiv2025

Collective Gene Expression Fluctuations Encode the Regulatory State of Cells

Gene expression is inherently stochastic, leading to substantial cell-to-cell variability in mRNA and protein abundances. Variability in the expression of individual genes has been associated both with impaired signal processing and with facilitation of stress responses and differentiation. Here, combining machine learning, theory, and analysis of scRNA-seq data across various organisms and tissues, we show that variability in gene expression can be coordinated cell-wide. We define a statistical score that quantifies this coordination in single-cell data and demonstrate that distinct coordination patterns reflect the regulatory state of cells. We further develop a physics-informed machine-learning framework that identifies and predicts such variability patterns. Coordinated gene-expression variability emerges as a hallmark of stem and progenitor cells and distinguishes intrinsic stochasticity from cell-population heterogeneity. Together, our results establish the structure of gene expression variability as a cellular-scale signature of cell identity and regulatory organization.

biophysics↗

bioRxiv2021

Inference of emergent spatio-temporal processes from single-cell sequencing reveals feedback between de novo DNA methylation and chromatin condensates

Recent breakthroughs in single-cell genomics allow probing molecular states of cells with unprecedented detail along the sequence of the DNA. Biological function relies, however, on emergent processes in the three-dimensional space of the nucleus, such as droplet formation through phase separation. Here, we use single-cell multi-omics sequencing to develop a theoretical framework to rigorously map epigenome profiling along the DNA sequence onto a description of the emergent spatial dynamics in the nucleus. Drawing on scNMT-seq multi-omics sequencing in vitro and in vivo we exemplify our approach in the context of exit from pluripotency and global de novo methylation of the genome. We show how DNA methylation patterns of the embryonic genome are established through the interplay between spatially correlated DNA methylation and topological changes to the DNA. This feedback leads to the predicted formation of 30-40nm sized condensates of methylated DNA and determines genome-scale DNA methylation rates. We verify these findings with orthogonal single cell multi-omics data that combine the methylome with HiC measurements. Notably, this scale of chromatin organization has recently been described by super-resolution microscopy. Using this framework, we identify local methylation correlations in gene bodies that precede transcriptional changes at the exit from pluripotency. Our work provides a general framework of how mechanistic insights into emergent processes underlying cell fate decisions can be gained by the combination of single-cell multi-omics and methods from theoretical physics that have not been applied in the context of genomics before. HighlightsO_LIWe develop methodology to infer collective spatio-temporal processes in the physical space of the nucleus from single-cell methylome sequencing experiments. C_LIO_LIWe show that DNA methylation relies on a feedback between de novo methylation and nanoscale changes in DNA topology, leading to the formation of methylation condensates. C_LIO_LIChromatin condensates at this scale have recently been described by high-resolution microscopy but have remained without mechanistic explanation. C_LIO_LIUsing this framework, we identify changes in the distribution of DNA methylation marks in gene bodies that precede gene silencing at the exit from pluripotency. C_LI

genomics↗