Biology subjects

Bolondi, A.

Publications and source records attributed to Bolondi, A..

6 recordsLinked to original sources

bioRxiv2025

An advanced head-to-tail mouse embryo model with hypoxia-mediated neural patterning

The developing mammalian embryo is guided by the continuously changing signals that it receives from maternal tissues and its microenvironment. The dynamic cell-cell and cell-environment interactions that together shape the embryo largely remained unexplorable until the advance of stem cell-based embryo models. These revealed the self-organizing properties of cells in response to endogenous and exogenous cues. Among the latter, restricted oxygen (hypoxia) emerged as a critical microenvironmental regulator that influences cell type diversification in multicellular systems. Here we built a modular ESC-based head-to-tail model of mouse embryogenesis by developing an antero-posterior (AP) assembly strategy under hypoxia. These structures called HAP-gastruloids feature stage-appropriate anterior neural tissues that recapitulate the morphological organization and transcriptional identity of fore- and midbrain including spatial organizer regions such as the midbrain-hindbrain boundary. These anterior tissues develop in synchrony with posterior tissues such as the spinal cord, somites, and gut endoderm derivatives, ultimately yielding a unified structure. We show via genetic, environmental, and pharmacological perturbations that timed hypoxia is essential to boost anterior neural cell identities and their patterning through HIF1a and in part by modulating TGF{beta} activity. These results underline the key beneficial role of hypoxia in early development and offer a uniquely modular system to investigate antero-posterior phenotypes for basic discovery and translation.

developmental biology↗

bioRxiv2024

Inferring cell differentiation maps from lineage tracing data

During development, mulitpotent cells differentiate through a hierarchy of increasingly restricted progenitor cell types until they realize specialized cell types. A cell differentiation map describes this hierarchy, and inferring these maps is an active area of research spanning traditional single marker lineage studies to data-driven trajectory inference methods on single-cell RNA-seq data. Recent high-throughput lineage tracing technologies profile lineages and cell types at scale, but current methods to infer cell differentiation maps from these data rely on simple models with restrictive assumptions about the developmental process. We introduce a mathematical framework for cell differentiation maps based on the concept of potency, and develop an algorithm, Carta, that infers an optimal cell differentiation map from single-cell lineage tracing data. The key insight in Carta is to balance the trade-off between the complexity of the cell differentiation map and the number of unobserved cell type transitions on the lineage tree. We show that Carta more accurately infers cell differentiation maps on both simulated and real data compared to existing methods. In models of mammalian trunk development and mouse hematopoiesis, Carta identifies important features of development that are not revealed by other methods including convergent differentiation of specialized cell types, progenitor differentiation dynamics, and the refinement of routes of differentiation via new intermediate progenitors. Code availabilityCarta software is available at https://github.com/raphael-group/CARTA

bioinformatics↗

bioRxiv2023

Integrated Molecular-Phenotypic Profiling Reveals Metabolic Control of Morphological Variation in Stembryos

Mammalian stem-cell-based models of embryo development (stembryos) hold great promise in basic and applied research. However, considerable phenotypic variation despite identical culture conditions limits their potential. The biological processes underlying this seemingly stochastic variation are poorly understood. Here, we investigate the roots of this phenotypic variation by intersecting transcriptomic states and morphological history of individual stembryos across stages modeling post-implantation and early organogenesis. Through machine learning and integration of time-resolved single-cell RNA-sequencing with imaging-based quantitative phenotypic profiling, we identify early features predictive of the phenotypic end-state. Leveraging this predictive power revealed that early imbalance of oxidative phosphorylation and glycolysis results in aberrant morphology and a neural lineage bias that can be corrected by metabolic interventions. Collectively, our work establishes divergent metabolic states as drivers of phenotypic variation, and offers a broadly applicable framework to chart and predict phenotypic variation in organoid systems. The strategy can be leveraged to identify and control underlying biological processes, ultimately increasing the reproducibility of in vitro systems. HighlightsO_LITime-resolved single-cell RNA-sequencing and imaging-based quantitative charting of hundreds of individual stembryos generates molecular and phenotypic fingerprints C_LIO_LIMachine learning and integration of molecular and phenotypic fingerprints identifies features and biological processes predictive of phenotypic end-state C_LIO_LIEarly imbalance of oxidative phosphorylation and glycolysis results in aberrant morphology and cellular composition C_LIO_LIMetabolic interventions tune stembryo end-state and can correct derailment of differentiation outcomes C_LI

developmental biology↗

bioRxiv2022

Discovery and characterization of LNCSOX17 as an essential regulator in human endoderm formation

Long non-coding RNAs (lncRNAs) have emerged as fundamental regulators in various biological processes, including embryonic development and cellular differentiation. Despite much progress over the past decade, the genome-wide annotation of lncRNAs remains incomplete and many known non-coding loci are still poorly characterized. Here, we report the discovery of a previously not annotated lncRNA that is transcribed upstream of the SOX17 gene and located within the same topologically associating domain. We termed it LNCSOX17 and show that it is induced following SOX17 activation but its expression is more tightly restricted to early definitive endoderm. Loss of LNCSOX17 affects crucial functions independent of SOX17 and leads to an aberrant endodermal transcriptome, signaling pathway deregulation and epithelial to mesenchymal transition defects. Consequently, cells lacking the lncRNA cannot further differentiate into more mature endodermal cell types. We identified and characterized LNCSOX17 as an essential new actor in early human endoderm, thereby further expanding the list of functionally important non-coding regulators.

genomics↗

bioRxiv2021

In vivo dissection of a clustered-CTCF domain boundary reveals developmental principles of regulatory insulation

Vertebrate genomes organize into topologically associating domains (TADs), delimited by boundaries that insulate regulatory elements from non-target genes. However, how boundary function is established is not well understood. Here, we combine genome-wide analyses and transgenic mouse assays to dissect the regulatory logic of clustered-CTCF boundaries in vivo, interrogating their function at multiple levels: chromatin interactions, transcription and phenotypes. Individual CTCF binding sites (CBS) deletions revealed that the characteristics of specific sites can outweigh other factors like CBS number and orientation. Combined deletions demonstrated that CBS cooperate redundantly and provide boundary robustness. We show that divergent CBS signatures are not strictly required for effective insulation and that chromatin loops formed by non-convergently oriented sites could be mediated by a loop interference mechanism. Further, we observe that insulation strength constitutes a quantitative modulator of gene expression and phenotypes. Our results highlight the modular nature of boundaries and their control over developmental processes.

developmental biology↗

bioRxiv2020

Mouse embryonic stem cells self-organize into trunk-like structures with neural tube and somites

Post-implantation embryogenesis is a highly dynamic process comprising multiple lineage decisions and morphogenetic changes inaccessible to deep analysis in vivo. Mouse embryonic stem cells (mESCs) can form aggregates reflecting the post-occipital embryo (gastruloids), but lacking proper morphogenesis. Here we show that embedding of aggregates derived from mESCs in an extracellular matrix compound results in Trunk-Like-Structures (TLS) with a high level of organization comprising a neural tube and somites. Comparative single-cell RNA-seq analysis demonstrates that TLS execute gene-regulatory programs in an embryo-like order, and generate primordial germ cell like cells (PGCLCs). TLS lacking Tbx6 form ectopic neural tubes, mirroring the embryonic mutant phenotype. ESC-derived trunk-like structures thus constitute a novel powerful in vitro platform for investigating lineage decisions and morphogenetic processes shaping the post-implantation embryo. One sentence summaryA platform for generating trunk-like-structures with precursors of spinal cord, bone and muscle from stem cells in a dish

developmental biology↗