Biology subjects

Villanueva, E.

Publications and source records attributed to Villanueva, E..

9 recordsLinked to original sources

bioRxiv2026

Network-scale disruption of RNA-protein interactions by a bioaccumulating small-molecule drug

Many small-molecule drugs accumulate in both host and gut microbial cells. Yet, the molecular consequences of intracellular drug accumulation are largely unknown. Here we show that the antidepressant duloxetine broadly disrupts RNA-protein interactions revealing a previously unrecognized mode of drug effect. Across phylogenetically diverse bacteria and human intestinal cells, duloxetine consistently reduced RNA-binding capacity, with approximately 80% of RNA-binding proteins responding to duloxetine in bacteria (E. coli IAI1) and human (Caco-2) cells. As a mechanistic example, we show how duloxetine disrupts interactions between the pyrimidine biosynthesis enzyme PyrB and transcripts encoding metabolically linked functions. Biochemical and structural analyses show that duloxetine competes with aspartate, the natural substrate of PyrB, weakening the enzymes binding with 3' UTR-localized stem-loop structures in its RNA partners. Overall, our results uncover the off-target disruption of RNA-protein interactions due to drug accumulation and have implications for understanding molecular basis of variation in drug efficacy and toxicity.

systems biology↗

bioRxiv2026

CSF-Seq enables transcriptome-wide profiling of cerebrospinal fluid and identifies prognostic signature of leptomeningeal disease

Leptomeningeal disease (LMD) is a rapidly fatal complication of systemic cancer for which sensitive diagnostic tools and informative biomarkers remain limited. Here, we introduce CSF-Seq, a method for whole-transcriptome sequencing of cell-free RNA (cfRNA) from human cerebrospinal fluid (CSF), designed to enable molecular profiling of LMD and other central nervous system (CNS) conditions. Using a prospectively collected CSF biobank, we analyzed 125 samples spanning multiple pathologies, including breast and lung LMD, glioblastoma, traumatic brain injury, and non-cancer neurological controls. Through optimized RNA extraction, library preparation, and deep sequencing, CSF-Seq generated robust and reproducible transcriptome-wide profiles despite the low abundance and fragmentation of cfRNA in CSF. CSF transcriptomes exhibited disease-specific expression, separating LMD from non-cancer controls and from non-LMD cancers, independent of CSF collection modality. Tumor-associated epithelial transcripts, including CEACAM6 and MUC1, were consistently enriched in LMD samples, whereas immune and CNS-associated transcripts were broadly detected across disease states, consistent with contributions from both tumor and non-tumor sources. Cross-site processing of matched samples demonstrated high concordance, indicating preservation of sample-specific transcriptional signatures across independent workflows. Importantly, we identified a collection method- independent LMD gene expression signature that was significantly associated with overall survival, supporting its potential prognostic relevance. Together, these findings establish CSF-Seq as a technically robust and clinically informative platform for transcriptomic biomarker discovery in CNS metastatic disease, offering a minimally invasive approach for disease characterization, risk stratification, and longitudinal monitoring in patients with LMD.

cancer biology↗

bioRxiv2026

High throughput single-cell RNA sequencing of intact adult cardiomyocytes and non-myocytes using a split-pool approach

MOTIVATIONAdult cardiomyocytes are difficult to profile by whole-cell single-cell RNA sequencing because of their large size and fragility, which make them poorly compatible with standard workflows. Current approaches for adult cardiomyocyte transcriptomics often require a trade-off between data quality and throughput, thus, studies instead rely heavily on sequencing of nuclei alone. Therefore, we set out to develop a high-quality and scalable workflow for adult heart cells using in-cell ligation and split-pool barcoding strategies to address this methodological gap. This workflow may be further generalisable to other large cell types or samples containing cell populations with highly unequal RNA content. SUMMARYAdult cardiomyocytes are difficult to profile by whole-cell single-cell RNA sequencing (scRNA-seq). Here, we developed a high-quality and scalable workflow for adult heart cells using in-cell ligation and split-pool barcoding. We identified per-cell RNA content as a significant variable that must be accounted for. Separation of cardiomyocytes (large cells) and non-cardiomyocytes (small cells) before library construction, and allocation of deeper sequencing to cardiomyocytes, produced high-quality whole-cell datasets for both compartments. Compared with single-nucleus RNA sequencing, whole-cell cardiomyocyte profiling better recovered metabolic, mitochondrial, cytoplasmic translational, and contractile gene programs. This workflow provides a practical method for scalable, high-quality cardiomyocyte whole-cell scRNA-seq and offers general strategies for other large cell types or samples containing cell populations with highly unequal RNA content.

cell biology↗

bioRxiv2025

Macrophage-like vascular smooth muscle cells dominate early atherosclerosis and are inhibited by targeting iron regulation

Vascular smooth muscle cells (VSMCs) contribute dynamically to atherosclerosis at all stages but the molecular drivers of their phenotypic switching, especially during early plaque development, and how they contribute to plaque progression remain unclear. We performed spatial transcriptomics on 12 human aortic tissues with and without atherosclerotic plaque. Macrophage-like SMCs were the predominant cell-type in the atheroma, displaying high iron storage and dysregulation, confirmed by spatial elemental mapping with nuclear microscopy. The combination of soluble iron and oxidized LDL promoted foamy macrophage-like VSMC cell state transition, while chelation inhibited this switching. In vivo, iron dysregulation induced neointimal thickening and macrophage-like switching in wire-injured Ldlr-/- mice, which was significantly reversed by ferrostatin-1, a ferroptosis inhibitor. These data show how targeting iron regulation modifies the macrophage-like VSMC cell state, and inhibits disease progression in atherogenesis.

genomics↗

bioRxiv2023

Interrogation of RNA-protein interaction dynamics in bacterial growth

Characterising RNA-protein interaction dynamics is fundamental to understand how bacteria respond to their environment. In this study, we have analysed the dynamics of 91% of the Escherichia coli expressed proteome and the RNA-interaction properties of 271 RNA-binding proteins (RBPs) at different growth phases. We find that 68% of RBPs differentially bind RNA across growth phases and characterise 17 previously unannotated proteins as bacterial RBPs including YfiF, a ncRNA-binding protein. While these new RBPs are mostly present in Proteobacteria, two of them have human orthologs in the form of mitochondrial proteins associated with rare metabolic disorders. Moreover, we reveal novel RBP functions for proteins such as the chaperone HtpG, a new stationary phase tRNA-binding protein. Altogether, we provide the first dynamic RBPome of a bacterium, showcasing how this approach can reveal the function of uncharacterised proteins, and identify critical RNA-protein interactions for cell growth which could inform new antimicrobial therapies.

microbiology↗

bioRxiv2023

Plant Expression Omnibus - a comparative transcriptomic database for 103 Archaeplastida

The Plant Expression Omnibus (PEO) is a web application that provides biologists with access to gene expression insights across over 100 plant species, [~]60,000 manually annotated RNA-seq samples, and more than four million genes. The tool allows users to explore the expression patterns of genes across different organs, identify organ-specific genes, and discover top co-expressed genes for any gene of interest. PEO also provides functional annotations for each gene, allowing for the identification of genetic modules and pathways. PEO is designed to facilitate comparative kingdom-wide gene expression analysis and provide a valuable resource for plant biology research. We provide two case studies to demonstrate the utility of PEO in identifying candidate genes in pollen coat biosynthesis and investigating the biosynthetic pathway components of capsaicin in Capsicum annuum. The database is freely available at https://expression.plant.tools/.

plant biology↗

bioRxiv2022

A system-wide quantitative map of RNA and protein subcellular localisation dynamics

Existing methods to analyse RNA localisation are constrained to specific RNAs or subcellular niches, precluding the cell-wide mapping of RNA. We present Localisation of RNA (LoRNA), which maps, at once, RNAs to membranous (nucleus, ER and mitochondria) and membraneless compartments (cytosol, nucleolus and phase-separated granules). Simultaneous interrogation of all RNA locations allows the system-wide quantification of RNA proportional distribution and the comprehensive analysis of RNA subcellular dynamics. Moreover, we have re-engineered the LOPIT (Localisation Of Proteins by Isotope Tagging) method, enabling integration with LoRNA, to jointly map RNA and protein subcellular localisation. Applying this framework, we obtain a global re-localisation map for 31839 transcripts and 5314 proteins during the unfolded protein response, uncovering that ER-localised transcripts are more efficiently recruited to stress granules than cytosolic RNAs, and revealing eIF3d is key to sustain cytoskeletal function. Overall, we provide the most exhaustive map to date of RNA and protein subcellular dynamics.

cell biology↗

bioRxiv2020

Transgene codon usage drives viral fitness and therapeutic efficacy in oncolytic adenoviruses

Arming oncolytic adenoviruses with therapeutic transgenes is a well-established strategy for multimodal tumour attack. However, this strategy sometimes leads to unexpected attenuated viral replication and a loss of oncolytic effects, preventing these viruses from reaching the clinic. Previous work has shown that altering codon usage in viral genes can hamper viral fitness. Here, we have analysed how transgene codon usage impacts viral replication and oncolytic activity. We observe that, although transgenes with optimised codons show high expression levels at a first round of infection, they impair viral fitness and are therefore not expressed in a sustained manner. Conversely, transgenes encoded by suboptimal codons do not compromise viral replication and are thus stably expressed over time allowing a greater oncolytic activity both in vitro and in vivo. Altogether, our work shows that fine-tuning codon usage leads to a concerted optimisation of transgene expression and viral replication paving the way for the rational design of more efficacious oncolytic therapies.Competing Interest StatementM.FS is a VCN Biosciences S.L. employee. All the other authors declare no conflict of interest.View Full Text

bioengineering↗

bioRxiv2018

Unbiased dynamic characterization of RNA-protein interactions by OOPS

Current methods for the identification of RNA-protein interactions require a quantity and quality of sample that hinders their application, especially for dynamic biological systems or when sample material is limiting. Here, we present a new approach to enrich RNA-Binding Proteins (RBPs): Orthogonal Organic Phase Separation (OOPS), which is compatible with downstream proteomics and RNA sequencing. OOPS enables recovery of RBPs and free protein, or protein-bound RNA and free RNA, from a single sample in an unbiased manner. By applying OOPS to human cell lines, we extract the majority of known RBPs, and importantly identify additional novel RBPs, including those from previously under-represented cellular compartments. The high yield and unbiased nature of OOPS facilitates its application in both dynamic and inaccessible systems. Thus, we have identified changes in RNA-protein interactions in mammalian cells following nocodazole cell-cycle arrest, and defined the first bacterial RNA-interactome. Overall, OOPS provides an easy-to-use and flexible technique that opens new opportunities to characterize RNA-protein interactions and explore their dynamic behaviour.

cell biology↗