Biology subjects

Acosta, S.

Publications and source records attributed to Acosta, S..

9 recordsLinked to original sources

bioRxiv2026

MIF overexpression upon SARS-CoV-2 infection induces neural regeneration in human-derived brain organoids

While SARS-CoV-2 primarily targets the respiratory system, its neurological effects have become a significant clinical concern. Postmortem analyses reveal astrogliosis, neuronal death, and blood-brain barrier dysfunction, yet the interplay between neural injury and endogenous repair remains unclear. Here, we employed human embryonic stem cell-derived brain organoids to examine viral tropism, bystander effects, and regenerative responses following infection. Single-cell transcriptomics and histological assays showed that SARS-CoV-2 productively infects neurons, neural progenitors, astroglia, and choroid plexus cells, triggering widespread apoptosis and senescence in both infected and neighboring cells. Despite low infection rates, organoids activated robust regenerative programs, including axon guidance, Wnt pathway signaling in mature neurons, and radial glia proliferation. Importantly, macrophage migration inhibitory factor (MIF) emerged as a key mediator, being strongly upregulated in both infected and uninfected cells, particularly in the choroid plexus. Recombinant MIF promoted dendritic outgrowth and cortical progenitor activation in uninfected organoids. Computational analyses indicated that MIF stimulates neural regenerative via EGFR signaling and upregulates its own expression in non-infected cells. These findings identify MIF as a molecular link between SARS-CoV-2-induced neural damage and regenerative activation in cortical cells.

cell biology↗

bioRxiv2025

Topology-Encoded Polarity in Oppositely Charged Binary IDPP Condensates: Multiphase Organization from Non-Coacervating Partners as a Minimal Model of Complex Coacervation

Synthetic condensates provide a way to engineer compartmentalized microenvironments that mimic the properties and functions of natural ones, yet the principles that govern their phase behavior and internal organization remain incompletely defined. Introducing charged residues into intrinsically disordered protein polymers (IDPPs) with LCST phase behavior typically suppresses phase separation under physiological conditions. Here we show that pairing two such oppositely charged IDPPs restores and programs LCST-driven liquid-liquid phase separation (LLPS), enabling a minimalist two-component platform for constructing synthetic condensates whose formation, size, and internal organization are encoded directly in sequence. LLPS emerges from an asymmetric, entropy-driven interplay between hydrophobic collapse, solvent reorganization, and salt-bridge topology. The balance between inter- and intrachain ionic pairing leads to distinct dense-phase microenvironments with tunable residual charge and micropolarity, thereby controlling condensate formation, and miscibility and the emergence of single-phase or multiphase protein condensates. The condensate interior further alters the ionization thermodynamics of charged residues shifting their apparent pKa and enabling tunable pH responses. Systems dominated by interchain salt bridges form low-polarity condensates that mix uniformly with hydrophobic partners, whereas molecular architectures favoring intrachain pairing retain residual charge and, in the presence of hydrophobic partners, undergo spontaneous internal demixing into multiphase assemblies. These findings establish a mechanistic, sequence-level framework for encoding phase behavior, micropolarity, and mesoscale organization in synthetic condensates, and demonstrate how minimalistic LCST-IDPP pairs can be engineered to create programmable microenvironments, opening avenues toward engineered condensates with higher-order organization and adaptive capabilities.

biophysics↗

bioRxiv2025

CBM KG: A Comorbidity-Centric Knowledge Graph Uncovering Causal Pathomechanisms Between COVID-19 and Neurodegenerative Diseases

SummaryCOVID-19 is increasingly recognized as a potential trigger or accelerator of neurodegenerative diseases such as Alzheimers and Parkinsons. To systematically explore the putative molecular and clinical associations between them, we present CBM KG (Causal Biological Mechanisms Knowledge Graph)--a manually curated, comorbidity-centric resource developed within the EU-funded COMMUTE project. CBM KG integrates over 2,800 cause-and-effect or correlative relationships from 63 peer-reviewed publications, highlighting key mechanisms such as viral entry routes, blood-brain barrier alteration, microglial activation, neuroinflammation, and APOE {varepsilon}4-associated susceptibility. Each relationship in the graph is fully traceable to its source evidence, ensuring transparency and reproducibility. Unlike general-purpose or single disease-focused knowledge graphs, CBM KG is specifically designed to represent causal biological mechanisms spanning both infectious and neurodegenerative processes. By encoding directional, cause-and-effect relationships, it supports the interpretation of clinical co-occurrences through plausible mechanistic links between overlapping disease pathways, offering high-resolution insights at both molecular and clinical levels. Availability and implementationThe BEL files, Neo4j database, and Cytoscape visualization files are publicly available at: https://github.com/SCAI-BIO/CBM-Comorbidity-KG.

bioinformatics↗

bioRxiv2025

Variability vs Phenotype: multimodal analysis of Dravet Syndrome Brain Organoids powered by Deep Learning

Brain organoids (BO) have risen as a reliable model for neurodelopmental disorders (ND), reproducing human brain development milestones. However, their significant intra- and inter-organoid variability compromises their use in advanced tasks such as drug testing. Overcoming experimental variability is crucial for models prone to variation, like unguided BO. BO modelling in Dravet Syndrome, a late-onset epileptic ND, represents a great challenge since BO variability accumulates with time, when phenotype shows in vitro. Leveraging deep learning, we developed ImPheNet, a predictive tool grounded in BO live imaging datasets. ImPheNet accurately classified phenotypes and assessed drug toxicity in BO derived from DS, revealing differences between genotypes and upon antiseizure drug exposure. These results are supported by transcriptomic and functional data, revealing an excitatory-inhibitory imbalance during the maturation of DS organoids. Altogether, our DL-predictive live imaging strategy, ImPheNet, emerges as a powerful tool enhancing BO research and advancing ND treatments.

developmental biology↗

bioRxiv2022

Synergic homology directed recombination by PRDM9 meiotic factor

Genome editing requires precision to broadly move on to industrial and clinical applications. For this reason, homologous directed repair (HDR) is one of the preferred methods for small edits, other than knock-outs. However, HDR has low efficiency. Current investigations to enhance HDR have mainly gone in the direction of finding non-homologous end joining (NHEJ) inhibitors. NHEJ is crucial for cellular integrity, then the inhibition of this pathway is detrimental for the correct survival of living entities. In other studies, a second opportunity is given to HDR by targeting the byproducts of NHEJ, using an extra gRNA. In this study, we propose the use of a meiotic factor, PRDM9, to directly enhance homology recombination. Through the exploration of combinatorial factors and donor design, we have established an optimized protocol for HDR. PRDM9-Cas9 fusion combined with CtIP improves HDR/NHEJ ratio. In addition, we have validated this combinatorial approach for small edits through a traffic light reporter system, as well as for longer edits with a split-GFP reporter system.

synthetic biology↗

bioRxiv2021

Chromosome X-wide analysis of positive selection in human populations: from common and private signals to selection impact on inactivated genes and enhancers-like signatures

The ability of detecting adaptive (positive) selection in the genome has opened the possibility of understanding the genetic bases of population-specific adaptations genome-wide. Here we present the analysis of recent selective sweeps specifically in the X chromosome in different human populations from the third phase of the 1000 Genomes Project using three different haplotype-based statistics. We describe numerous instances of genes under recent positive selection that fit the regimes of hard and soft sweeps, showing a higher amount of detectable sweeps in sub-Saharan Africans than in non-Africans (Europe and East Asia). A global enrichment is seen in neural-related processes while numerous genes related to fertility appear among the top candidates, reflecting the importance of reproduction in human evolution. Commonalities with previously reported genes under positive selection are found, while particularly strong new signals are reported in specific populations or shared across different continental groups. We report an enrichment of signals in genes that escape X chromosome inactivation, which may contribute to the differentiation between sexes. We also provide evidence of a widespread presence of soft-sweep-like signatures across the chromosome and a global enrichment of highly scoring regions that overlap potential regulatory elements. Among these, enhancers-like signatures seem to present putative signals of positive selection that might be in concordance with selection in their target genes. Also, particularly strong signals appear in regulatory regions that show differential activities, which might point to population-specific regulatory adaptations.

evolutionary biology↗

bioRxiv2021

Comparative analysis of mammal genomes unveils key genomic variability for human lifespan.

Mammals vary 100-fold in their maximum lifespan. This enormous variation is the result of the adaptations of each species to their own biological trade-offs and ecological conditions. Comparative genomics studies have demonstrated that the genomic factors underlying the lifespans of species and the longevity of individuals are shared across the tree of life. Here, we set out to compare protein-coding regions across the mammalian phylogeny, aiming to detect individual amino acid changes shared by the most long-lived mammal species and genes whose rates of protein evolution correlate with longevity. We discovered a total of 2,737 amino acid changes in 2,004 genes that distinguish long- and short-lived mammals, significantly more than expected by chance (p=0.003). The detected genes belong to pathways involved in regulating lifespan, such as inflammatory response and hemostasis. Among them, a total 1,157 amino acids, located in 996 different genes, showed a significant association with maximum lifespan in a phylogenetically controlled test. Interestingly, most of the detected amino acids positions do not vary in extant human populations (>81.2%) or have allele frequencies below 1% (99.78%), Consequently, almost none could have been detected by Genome-Wide Association Studies (GWAS). Additionally, we identified four more genes whose rate of protein evolution correlated with longevity in mammals. Crucially, SNPs located in the detected genes explain a larger fraction of human lifespan heritability than expected by chance, successfully demonstrating for the first time that comparative genomics can be used to enhance the interpretation of human GWAS. Finally, we show that the human longevity-associated proteins coded by the detected genes are significantly more stable than the orthologous proteins from short-lived mammals, strongly suggesting that general protein stability is linked to increased lifespan.

genomics↗

bioRxiv2020

Intronic enhancers regulate the expression of genes involved in tissue-specific functions and homeostasis

Tissue function and homeostasis reflect the gene expression signature by which the combination of ubiquitous and tissue-specific genes contribute to the tissue maintenance and stimuli-responsive function. Enhancers are central to control this tissue-specific gene expression pattern. Here, we explore the correlation between the genomic location of enhancers and their role in tissue-specific gene expression. We found that enhancers showing tissue-specific activity are highly enriched in intronic regions and regulate the expression of genes involved in tissue-specific functions, while housekeeping genes are more often controlled by intergenic enhancers. Notably, an intergenic-to-intronic active enhancers continuum is observed in the transition from developmental to adult stages: the most differentiated tissues present higher rates of intronic enhancers, while the lowest rates are observed in embryonic stem cells. Altogether, our results suggest that the genomic location of active enhancers is key for the tissue-specific control of gene expression.

genomics↗

bioRxiv2019

A Human Accelerated Region participates in early human forebrain patterning and expansion

The expansion of the mammalian brain is associated with specific developmental processes; however, not much is known about how evolutionary changes participated in the acquisition of human brain traits during early developmental stages. Here we investigated whether enhancers active during the phylotypic stage show human-specific genomic divergence which could contribute to the evolutionary expansion of the forebrain. Notably, we identified an active enhancer containing a human accelerated region (HAR) located in the Chromosome 14q12, a region enriched with neurodevelopmental genes, such as Foxg1, Nkx2.1 and Nova1. Reporter analysis revealed that the human variant is active in the forebrain in transgenic mice and that it has stronger enhancer activity than the mouse or chimpanzee versions. Humanization of the mouse enhancer variant in transgenic mice and in mouse organoids resulted in an expansion of Foxg1 expressing domains in the forebrain early neural progenitors with a bias towards dorsal identities. Overall, our results suggest that human-specific mutations in critical regulatory elements controlling early brain development impact the expansion and patterning of the forebrain.

developmental biology↗