Antonio del Sol

Leigh syndrome (Leigh) is an untreatable mitochondrial disorder characterized by lactic acidosis and basal ganglia and midbrain pathology, leading to psychomotor regression and early death. We previously uncovered impaired neuronal morphogenesis in Leigh cerebral organoids carrying SURF1 gene variants. Leveraging this phenotype, we here develop a deep learning algorithm tailored for cell type-specific drug repurposing screening. In parallel, we perform a survival drug screen in a yeast model of Leigh. The two approaches independently converge on azole compounds, two of which - talarozole and sertaconazole - rescue neuronal morphogenesis in Leigh neurons and lower lactate release and improve growth rate in Leigh midbrain organoids. Mechanistically, these compounds modulate the retinoic acid pathway and membrane-associate lipid metabolism. The findings highlight azoles as promising candidates for Leigh and demonstrate the potential of combining in silico screens with human brain organoids as new approach methodologies (NAMs) to advance the discovery of therapeutics addressing rare neurodevelopmental disorders.

Müller glia arise from late-stage retinal progenitor cells (RPCs) as a distinct lineage that diverges from neurogenic trajectories. Here, we identify the maternally imprinted gene Plagl1 as a key transcriptional regulator of gliogenesis in the murine retina. Plagl1 is expressed during the RPC-to-glia transition and is dynamically regulated in Müller glia following injury. To define its developmental role, we analyzed Plagl1 ^⁺/⁻pat null mutant retinas at postnatal day 7 (P7), when central retinal gliogenesis is complete. In the absence of Plagl1 , Sox9 ⁺ glial/precursor cells were displaced and proliferated ectopically, with structural dysmorphologies, reactive gliosis, and impaired visual processing persisting into later postnatal stages. Bulk RNA-seq and ATAC-seq revealed widespread reductions in chromatin accessibility and transcriptional dysregulation affecting epigenetic modifiers, translational machinery, fate-specifying transcription factors, cell cycle regulators, and signaling pathways. Single-cell pseudobulk analysis showed that Plagl1 loss disrupts chromatin, transcriptional, and translational programs specifically within Sox9 ⁺ cells, encompassing Müller glia and precursor populations, pinpointing these cells as the source of defects in Plagl1 ^⁺/⁻pat retinas. Notch signaling was elevated in Plagl1 -deficient glia, and genetic activation at P14 displaced Sox9 ⁺ glial cells, without inducing proliferation. Similarly, conditional deletion of Plagl1 in postnatal Müller glia at P14 disrupted positioning and not cell cycle exit, confirming a cell-autonomous requirement for Müller glia positioning that is independent of proliferation control. Since these conditional manipulations could only be performed at P14 at the earliest, they reveal Plagl1 ’s later functions in postmitotic glia and complement, rather than mirror, the earlier P7 mixed RPC/glial null phenotype. Together these findings establish Plagl1 as a critical regulator of the late-stage RPC to Müller glia transition, acting through coordinated control of chromatin accessibility and gene expression programs to ensure timely cell cycle exit. This function aligns with Plagl1 ’s broader tumor suppressor role in stabilizing postmitotic, differentiated cell states across tissues.

Aged hematopoietic stem cells (HSCs) expand in clusters over time, while reducing their regenerative capacity and their ability to preserve the homeostasis of the hematopoietic system. The expression of Notch ligands in the bone marrow (BM) niche is essential for hematopoiesis. However, the impact of Notch signaling on adult HSC function and its involvement in HSC aging remains controversial. Here, we show that Notch activation in young HSCs is not homogeneous, and it is triggered by sinusoidal expression of the Notch ligand Jagged2 (Jag2). Sinusoidal Jag2 deletion in young mice recapitulates the decrease in Notch activity observed in aged HSCs and alters HSC divisional symmetry and fate priming, promoting myeloid-biased HSCs (My-HSCs) expansion. Mechanistically, our data reveals that upon decreasing sinusoidal Jag2 expression, HSCs themselves upregulate Jag2, which cis-inhibits Notch signaling, resulting in the expansion of My-HSCs and in reduced hematopoietic regeneration. Collectively, these findings identify the crosstalk between BM niche-driven and HSC intrinsic features in regulating HSC fate priming and regenerative potential and reveal an extrinsic Notch trans-activation to intrinsic cis-inhibition switch underlying HSC aging.

Neuronal reprogramming using adeno-associated viruses with a GFAP mini-promoter offers a promising strategy for astrocyte-to-neuron conversion; however, specificity remains a challenge due to off-target transgene expression in endogenous neurons. To address this issue, here we incorporated microRNA-124 target sequences (124T) into a transcriptional cassette containing the GFAP mini-promoter and Ascl1^SA6, a potent reprogramming transcription factor. Lineage tracing via Slc1a3-CreERT and Aldh1l1-CreERT2, used to pre-label astrocytes prior to conversion, confirmed the glial derivation of reprogrammed neuron-like cells, even with 124T. Single-cell transcriptomics identified a transitional cluster emerging from a proliferative astrocyte population with low GSK3 signaling, which branched towards hybrid neuronal and oligodendrocyte fates. Pseudotime trajectory analysis revealed that Ascl1^SA6 drives rapid neuronal transitions, whereas 124T delays conversion and introduces lineage bifurcation. Ascl1^SA6 favors a GABAergic interneuron-like identity, while Ascl1^SA6 -124T biases fate transitions towards an oligodendrocyte-like fate, and to a lesser extent, glutamatergic neuronal-like cells. SeeSawPred linked these distinct trajectories to transcription factor shifts, including Foxo1 in neuron-like cell fates and Stat1 in oligodendrocyte lineages. 124 T thus effectively detargets endogenous neurons, refining target cell specificity, while further guiding reprogramming outcomes. This approach establishes a foundation for precision reprogramming platforms aimed at restoring specific neural cell types.

Great efforts have been devoted to discovering rejuvenation strategies that counteract age-related functional decline and improve cellular functions in humans. However, new discoveries are currently driven by expert knowledge and require large amounts of resources. Here, we present REVIVE (Rejuvenation Estimation Via Insightful Virtual Experiments), the first computational framework for systematically predicting chemical and genetic perturbations that can restore a youthful transcriptional state based on gene expression data. REVIVE leverages age predictions to detect significant rejuvenating effects and quantifies the impact of perturbations on the hallmarks of aging. When applied to a large-scale in silico screen of more than 10000 compounds and genetic perturbations, REVIVE recapitulates known interventions as well as 477 novel compounds that restore a more youthful transcriptional state improving multiple aging hallmarks. Finally, we demonstrate the utility of REVIVE for repurposing perturbations to revert aged transcriptional states.

Boolean networks provide robust, explainable, and predictive models of cellular dynamics, especially for cellular differentiation and fate decision processes. Yet, the construction of such models is extremely challenging, as it requires integrating prior knowledge with experimental observation of the transcriptome, potentially relating thousands of genes. We present a general methodology for integrating transcriptome data and prior knowledge on the underlying gene regulatory network in order to generate automatically ensembles of Boolean networks able to reproduce the modeled qualitative behavior. Our methodology builds on the software BoNesis, which implements the automatic construction of Boolean networks from a specification of their expected structural and dynamical properties. We show how to transform transcriptome data into such a qualitative specification, and then how to exploit the generated ensembles of Boolean networks for identifying families of candidate models, and for predicting robust cellular reprogramming targets. We illustrate the scalability and versatility of our overall approach with two applications: the modeling of hematopoiesis from single-cell RNA-Seq data, and modeling the differentiation of bone marrow stromal cells into adipocytes and osteoblasts from bulk RNA-seq time series data. For this latter case, we took advantage of ensemble modeling to predict combinations of reprogramming factors for trans-differentiation that are robust to model uncertainties due to variations in experimental replicates and choice of binarization method. Moreover, we performed an in silico assessment of the fidelity and efficiency of the reprogramming and conducted preliminary experimental validation.

The increase in life expectancy has caused a rise in age‐related brain disorders. Although brain rejuvenation is a promising strategy to counteract brain functional decline, systematic discovery methods for efficient interventions are lacking. A computational platform based on a transcriptional brain aging clock capable of detecting age‐ and neurodegeneration‐related changes is developed. Applied to neurodegeneration‐positive samples, it reveals that neurodegenerative disease presence and severity significantly increase predicted age. By screening 43840 transcriptional profiles of chemical and genetic perturbations, it identifies 453 unique rejuvenating interventions, several of which are known to extend lifespan in animal models. Additionally, the identified interventions include drugs already used to treat neurological disorders, Alzheimer's disease among them. A combination of compounds predicted by the platform reduced anxiety, improved memory, and rejuvenated the brain cortex transcriptome in aged mice. These results demonstrate the platform's ability to identify brain‐rejuvenating interventions, offering potential treatments for neurodegenerative diseases.

Metabolic pathways are remodeled in response to energy and other homeostatic demands and are dynamically regulated during embryonic development, suggesting a role in guiding cellular differentiation. Here, we show that glycolytic flux is required and sufficient to bias multipotent retinal progenitor cells (RPCs) to acquire a rod photoreceptor fate in the murine retina. In RPC-specific Phosphatase and tensin homolog conditional knockout (Pten-cKO) and RPC-specific conditional gain-of-function of dominant active PFKFB3 (cytoPFKFB3) mice, glycolytic gene expression and activity are elevated, correlating with precocious rod photoreceptor differentiation and outer segment (OS) maturation. Conversely, glycolytic inhibition in retinal explants suppresses RPC proliferation and photoreceptor differentiation, achieved either with 2-deoxy-D-glucose, a competitive inhibitor of glucose metabolism, by lowering media pH, which disables PKM2, a rate-limiting enzyme, or by inhibiting lactate/H⁺ symporters, which lowers intracellular pH. Mechanistically, we show that Wnt signaling, the top-upregulated pathway in Pten-cKO retinas, is a glycolysis-dependent pathway. Pharmacological and genetic perturbation of Wnt signaling by knocking-out Ctnnb1, encoding β-catenin, phenocopies glycolytic inhibition, suppressing RPC proliferation, photoreceptor differentiation, and OS maturation. Thus, developmental rewiring of glycolytic flux modulates Wnt signaling to drive rod photoreceptor differentiation and maturation, an instructive role that may be exploited therapeutically for cell replacement strategies.