Biology subjects

Leyva, A.

Publications and source records attributed to Leyva, A..

10 recordsLinked to original sources

bioRxiv2026

Comprehensive investigation of AAV tropism across human iPSC-derived neuronal subtypes

Recombinant Adeno-associated viruses (AAVs) are widely used for gene delivery in the central nervous system and have become central tools in both gene therapy and basic neuroscience research. However, although AAV serotypes have been extensively characterized in rodent models, their performance in human neurons, particularly those derived from induced pluripotent stem cells (iPSCs), remains poorly characterized. While human iPSC-derived neurons are increasingly used for disease modeling and drug screening, their susceptibility to viral transduction varies and remains difficult to predict. In this study, we systematically evaluated the transduction efficiency and toxicity profiles of 18 wild-type and engineered AAV serotypes across three distinct types of iPSC-derived neurons, relevant to disease modeling and drug discovery: cortical projection neurons, NGN2- induced forebrain-like neurons, and dopaminergic neurons and four doses (1E3, 1E4, 1E5 and 2E5 genome copies per cell). Using automated high-throughput confocal imaging and quantification of reporter gene expression, we identified several serotypes with robust and efficient transduction across all neuronal subtypes. Among these, three serotypes AAV6, AAV6.2 and AAV2.7m8 showed consistently high performance. To assess safety, we quantified cell number and neurite morphology, finding that while high transduction and gene expression correlate with toxicity, sensitivity varied across neuronal subtypes, with NGN2 neurons being most vulnerable and dopaminergic neurons most resilient. Finally, we validated our findings in a more complex 3D model by testing one of the best-performing serotypes, AAV2.7m8, in both whole and dissociated human cerebellar organoids. Together, our results establish a benchmark dataset for AAV performance in human iPSC- derived neurons and provide practical guidance for AAV based gene delivery in human in vitro neural models. This resource will be valuable for both basic research and preclinical applications aiming to manipulate gene expression in human neurons and understanding AAV tropism in disease-relevant cell types.

neuroscience↗

bioRxiv2026

Personalized Morphology, Replication Timing, and RNA based Gene Expression Networks for Basal-like and Classical subtyping genes in Pancreatic Adenocarcinoma

Network biology traditionally identifies gene correlations that reflect biological pathways. While LIONESS enables individualized gene networks, the influence of replication timing on these correlations remains unexplored. Replication timing reflects the temporal order of DNA synthesis and is tightly linked to chromatin state, methylation, and transcriptional stability, all of which affect tumor behavior. Integrating replication-timing proxies derived from methylation data therefore offers a bridge between epigenetic state and functional gene coordination, while morphology provides an additional route for inferring gene expression. This is the first study to integrate replication-timing proxies and morphological embeddings into individualized LIONESS gene networks. The aim is to determine how replication timing and morphology derived from bulk methylation and image embeddings influence gene coexpression in pancreatic cancer. Patient-specific networks were generated for basal and classical pancreatic ductal adenocarcinoma subtypes using TCGA data. Results show an 80% AUC for RNA-replication-timing-based subtype prediction modules and a 75% AUC for morphology-based networks. Incorporating replication timing and morphology increased network robustness while maintaining classification performance. Notably, the 80% AUC was achieved using only 17 of the 50 Moffitt genes, with 16 overlapping the PURIST gene set, indicating that replication timing captures clinically relevant regulatory structure. These findings suggest that replication-timing proxies can act as epigenetic indicators of mechanistic gene coordination and may help identify patients with distinct replication stress or chromatin accessibility profiles relevant to therapeutic response.

bioinformatics↗

bioRxiv2026

Neural Networks as Entropic Systems: Applications in Digital Pathology

Deep learning systems in digital pathology are widely regarded as opaque, limiting clinical trust and interpretability. We present a framework for empirically characterizing training-time learning dynamics in neural networks by directly measuring activation structure, weight evolution, and spectral organization during optimization. Using TCGA-BRCA whole-slide images with replication-timing-derived methylation proxies as regression targets, we trained a Vision Transformer and tracked its intra-epoch behavior across 20 epochs. We observed reproducible structural signatures during training. Correlated groups of neurons formed stable activation modules whose modularity increased as training progressed, accompanied by a reduction in representation entropy of up to 60%. Weight trajectories exhibited bounded diffusion with progressively reduced variance, consistent with a damped stochastic process, and converged toward a stable stationary regime in later epochs. In image space, model attention systematically shifted from collagen-rich stromal regions in early epochs to basophilic, proliferative nuclear regions in later epochs, aligning with known histologic correlates of replicative stress. These findings demonstrate that neural networks develop predictable, quantifiable internal structure during training that can be directly visualized and measured. Framing learning dynamics in terms of entropy, modular organization, and stochastic stabilization provides a practical, mechanistic lens for interpreting how pathology AI models acquire biologically meaningful representations.

pathology↗

bioRxiv2026

Performance of Naiive Spectral Geometric Models in Histopathology AI

There have been no systematic evaluations of purely spectral models for digital pathology tasks. We implemented and benchmarked four pipelines: binary classification on the BreaKHis dataset, multi-class region classification in glioblastoma, spatial transcriptomics, and denoising on Visium 10x. Across all tasks, extensive cross-validation and grouped splits showed that purely spectral models did not improve performance over CNN-only baselines, but offer useful complementary tools for interpretability and processing. Denoising showed strong performance that proves utility in data-scarce or heterogeneous image environments. Equivalence testing confirms that spectral and CNN model performances fall outside {+/-}3% AUC. Fusion models between CNNs and spectral models show higher balanced accuracy. Spectral models failed to generalize across spatial transcriptomics tasks, with low correlation despite stable training loss. These findings represent a systematic negative result: despite their theoretical richness, spectral geometric features and SNO embeddings prove to be complementary features for WSI classification or segmentation. Reporting such outcomes is essential to establish empirical boundaries for spectral methods and to encourage future work on conditions or data modalities where these approaches may hold greater promise.

pathology↗

bioRxiv2025

Quantum Chemical Profiling of Protein Mutations via Fragment-Based DFT

Missense mutations have been extensively studied in tumor-suppressing antigens (TP53) to understand oncogenesis within malignant epithelial cells. Using Whole Exome Sequencing (WXS), missense mutations can be profiled into protein sequences to identify the most common variants in tumor samples. Since nearly 80% of mutations arise randomly, it is necessary to isolate those that produce dysfunctional proteins within large cohorts. Using threading and generative algorithms such as AlphaFold and ColabFold, large cohorts of WXS information can be converted into computationally analyzable structures. By evaluating both highand low-confidence regions in these structures, these antigens can be studied en masse using pipelines that generate analytical inputs for quantum chemistry analysis. we created a pipeline that processed whole-exome sequencing (WXS) data and selected 28 representative TP53 missense mutants from the TCGA-BRCA cohort for quantum-chemical feasibility analysis. These structures were systematically cleaned using tools such as OpenBabel and AmberTools, and each was prepared for Natural Population Analysis (NPA), Electrostatic Potential (ESP) calculations, and Highest and Lowest Occupied Molecular Orbital (HOMO/LUMO) evaluation within Q-Chem. Using this pipeline, population genomics can be integrated with chemoinformatics to analyze electron density concentrations and generate hypothesis-generating electronic descriptors associated with protein dysfunction. By modifying the generated inputs, additional analyses such as Fukui orbitals, chemical shifts, and Raman shifts can also be performed. This provides a computational means to probe electronic properties not readily accessible at scale using experimental techniques.

bioinformatics↗

bioRxiv2025

Engineering substrate selectivity in the human sodium/iodide symporter (NIS)

Iodide (I-) uptake mediated by the Na/I- symporter (NIS) is the first step in the biosynthesis of the thyroid hormones, of which I- is an essential constituent. NIS couples the inward transport of I- against its electrochemical gradient to the inward translocation of Na+ down its electrochemical gradient. NIS also transports oxyanions (XO4-s), such as perrhenate (ReO4-) and the environmental pollutant perchlorate (ClO4-). Furthermore, NIS is the basis for radioiodide ({superscript 1}3{superscript 1}I-) therapy for thyroid cancer (administered after thyroidectomy), the most effective targeted internal radiation cancer therapy available. 131I- selectively targets remnant malignant cells and metastases expressing NIS, causing only minor side effects. There is great interest in expressing NIS exogenously, by gene transfer, in extrathyroidal cancers to render them susceptible to destruction by 131I-. This approach, however, would also harm patients thyroids. Therefore, a strategy is needed for killing non-thyroidal cancer cells exogenously expressing NIS while protecting the thyroid. Addressing this need, we present here an engineered double mutant, L253P/V254F (PF)-NIS, which selectively transports XO4-s but not I-. We used cryo-EM to determine the structure of PF-NIS with ReO4- and Na+ ions bound to it at a 2.58 [A] resolution, and showed that high concentrations of non-radioactive I- protect WT-NIS-expressing cells from radioactive 186ReO4-, whereas PF-NIS-expressing cells are killed. Thus, PF-NIS could potentially be used, together with 186/188ReO4- and non-radioactive I-, to treat non-thyroidal cancers while safeguarding the thyroid. This study establishes a framework for developing therapies using NIS molecules engineered to have selective substrate specificities to extend the clinical use of NIS beyond thyroid cancer.

biophysics↗

bioRxiv2024

Revisiting oxygen toxicity: evolution and adaptation to superoxide in a SOD-deficient bacterial pathogen

Defenses against oxidants are crucial for the virulence of pathogens, with superoxide scavenging enzymes (SOSEs) playing a vital role for most aerobes. However, our knowledge of superoxide adaptation primarily stems from the study of SOSE-encoding bacteria. Here, we investigated the evolution of a naturally SOSE-deficient pathogen (Leptospira spp.), along with the alternative mechanisms it recruits to combat superoxide stress. We demonstrate that emergence of pathogenic Leptospira correlated with SOD loss, but that a long-lasting adaptation to superoxide remains possible. We reveal that cysteine and leucine biosynthesis are the most induced pathways in response to superoxide and demonstrate the importance of sulfur metabolism in superoxide adaptation in this SOSE-deficient model. We also propose cysteine oxidation as a key mediator of superoxide toxicity in the absence of SOSEs. This study challenges our conventional understanding of the oxygen toxicity theory and proposes a new model of superoxide adaptation through metabolic rewiring in bacteria.

microbiology↗

bioRxiv2023

Eukaryotic-like gephyrin and cognate membrane receptor coordinate corynebacterial cell division and polar elongation.

The order Corynebacteriales includes major industrial and pathogenic actinobacteria such as Corynebacterium glutamicum or Mycobacterium tuberculosis. Their elaborate multi-layered cell wall, composed primarily of the mycolyl-arabinogalactan-peptidoglycan complex, and their polar growth mode impose a stringent coordination between the septal divisome, organized around the tubulin-like protein FtsZ, and the polar elongasome, assembled around the tropomyosin-like protein Wag31. Here, we report the identification of two new divisome members, a gephyrin-like repurposed molybdotransferase (GLP) and its membrane receptor (GLPR). We show that the interplay between the GLPR/GLP module, FtsZ and Wag31 is crucial for orchestrating cell cycle progression. Our results provide a detailed molecular understanding of the crosstalk between two essential machineries, the divisome and elongasome, and reveal that Corynebacteriales have evolved a protein scaffold to control cell division and morphogenesis similar to the gephyrin/GlyR system that in higher eukaryotes mediates synaptic signaling through network organization of membrane receptors and the microtubule cytoskeleton.

microbiology↗

bioRxiv2022

Phosphorylation of aldose-6-phosphate reductase from Prunus persica leaves

Sugar-alcohols are major photosynthates in plants from the Rosaceae family. Expression of the gene encoding aldose-6-phosphate reductase (Ald6PRase), the critical enzyme for glucitol synthesis in rosaceous species, is regulated by physiological and environmental cues. Additionally, Ald6PRase is inhibited by small molecules (hexose-phosphates and inorganic orthophosphate) and oxidizing compounds. This work demonstrates that Ald6PRase from peach leaves is phosphorylated in planta at the N-terminus. We also show in vitro phosphorylation of recombinant Ald6PRase by a partially purified kinase extract from peach leaves containing Ca2+-dependent protein kinases (CDPKs). Moreover, phosphorylation of recombinant Ald6PRase was inhibited by hexose-phosphates, phosphoenolpyruvate and pyrophosphate. We further show that phosphorylation of recombinant Ald6PRase was maximal using recombinant CDPKs. Overall, our results suggest that phosphorylation could fine-tune the activity of Ald6PRase.

plant biology↗

bioRxiv2021

Proteome remodeling in the Mycobacterium tuberculosis PknG knockout: molecular evidence for the role of this kinase in cell envelope biogenesis and hypoxia response.

Mycobacterium tuberculosis, the etiological agent of tuberculosis, is among the deadliest human pathogens. One of M. tuberculosiss pathogenic hallmarks is its ability to persist in a dormant state in the host for long periods, reinitiating the infectious cycle when favorable environmental conditions are found. Thus, it is not surprising that this pathogen has developed different mechanisms to withstand the stressful conditions found in the host. In particular, the Ser/Thr protein kinase PknG has gained special relevance since it regulates nitrogen metabolism and facilitates bacterial survival inside macrophages. Nevertheless, the molecular mechanisms underlying these effects are far from being elucidated. To further investigate these issues, we performed quantitative proteomics analyses of protein extracts from M. tuberculosis H37Rv and a mutant derivative lacking pknG. Our results showed that in the absence of PknG the mycobacterial proteome was remodeled since 5.7% of the proteins encoded by M. tuberculosis presented significant changes in its relative abundance when compared to the wild-type strain. The main biological processes affected by pknG deletion were the biosynthesis of cell envelope components and the response to hypoxic conditions. As many as 13 DosR-regulated proteins were underrepresented in the pknG deletion mutant, including the distinctive Hrp-1, which was found to be 12-fold decreased according to Parallel Reaction Monitoring experiments. Altogether, the results presented here allow us to postulate that PknG regulation of bacterial adaptation to stress conditions might be an important mechanism underlying its reported effect on intracellular bacterial survival.

biochemistry↗