Biology subjects

Ojeda, S.

Publications and source records attributed to Ojeda, S..

10 recordsLinked to original sources

bioRxiv2026

Assessing the translation of AI-prioritized genome-derived peptide fragments into validated antimicrobial candidates

The emergence of antibiotic-resistant pathogens such as Staphylococcus aureus demands accelerated antimicrobial discovery strategies. Artificial intelligence (AI) enables large-scale inference of candidate antimicrobial peptides (AMPs), yet experimental validation remains essential to determine whether predictions translate into biological function. Genome-guided mining, rather than unconstrained or randomly generated sequence exploration, offers a biologically grounded search space derived from organisms shaped by ecological and evolutionary pressures. Here, we evaluate this principle using Malassezia furfur, a skin-associated yeast that coexists with bacterial colonizers such as S. aureus, as a genomic source for AI-prioritized antimicrobial candidates. Candidate fragments were generated from two M. furfur genomes, filtered by physicochemical properties, prioritized with deep-learning AMP predictors, synthesized, and experimentally characterized. Selected peptides underwent cross-kingdom antimicrobial screening against S. aureus, combining kinetic growth and ultrastructural assays, complemented by in silico structural prediction, lipid-membrane interaction analysis, and human keratinocyte cytotoxicity evaluation. AI-guided genomic mining enriched biologically motivated sequence space for peptides with measurable antimicrobial activity, while revealing biases and generalizability limits of AI-based AMP inference. Closing the loop between genome-derived candidate generation, AI-based inference, synthesis, and functional characterization, this study provides an experimental assessment of model-guided AMP discovery and a reproducible route from computational prediction to validated antimicrobial candidates.

bioengineering↗

bioRxiv2026

A Dimeric Rocaglate Promotes Multivalent eIF4A-RNA Assembly

Ligand dimerization represents a powerful strategy to enhance avidity, potency, and selectivity. Leveraging the natural-product molecular glue Rocaglamide (RocA), we identified BisRoc, a dimeric rocaglate ligand that potently and durably suppresses translation and exhibits greater specificity across a cancer cell line panel than the monomeric RocA. CRISPRi screening revealed that BisRoc activity is influenced by cellular context, including IFITM-mediated uptake, ABC-type efflux transporters, and the translation initiation factor eIF4A2. Mechanistic studies showed that the paralogs eIF4A1 and eIF4A2 are differentially sensitive to BisRoc-induced dimerization. Owing to the presence of multiple binding sites on RNAs, BisRoc-bridged eIF4A-RNA motifs assemble into higher-order complexes that promote stress-granule formation more efficiently than monomeric RocA. Given the widespread multivalency of RNA-RBP interactions, this ligand dimerization strategy may be extended to modulate the higher-order assembly of other RNA-binding proteins. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=95 SRC="FIGDIR/small/710667v1_ufig1.gif" ALT="Figure 1"> View larger version (26K): org.highwire.dtl.DTLVardef@1f0ce69org.highwire.dtl.DTLVardef@7f7fadorg.highwire.dtl.DTLVardef@976e81org.highwire.dtl.DTLVardef@1d7eaf2_HPS_FORMAT_FIGEXP M_FIG C_FIG

biochemistry↗

bioRxiv2024

New algorithms for unsupervised cell clusteringfrom scRNA-seq data

The identification of cell types is a basic step of the pipeline for Single-Cell RNA sequencing data analysis. However, unsupervised clustering of cells from scRNA-seq data has multiple challenges: the high dimensional nature of the data, the sparse nature of the gene expression matrix, and the presence of technical noise that can introduce false zero entries. In this study, we introduce new algorithms for clustering scRNA-seq data. The first algorithm builds a k-MST graph from distances obtained directly from the input data without dimensionality reduction. The computation follows an iterative procedure of k steps in which each step calculates and stores the edges of minimum spanning trees over different subgraphs obtained removing edges selected in previous iterations. The Louvain algorithm is executed on the k-MST graph for cell clustering. We also explored alternatives based on neural networks in which an autoencoder is used to learn the parameters of a Gaussian mixture model, aiming to improve the handling of clusters with different shapes and sizes. Benchmark experiments with simulated data and public datasets show that the algorithms proposed in this work have competitive accuracy, compared to previous solutions, but also that sequencing depth, number of cells and tissue types have important effects on the performance of the algorithms. Moreover, we performed further experiments with scRNA-data taken from a patient with refractory epilepsy. The AE-GMM model achieved the best accuracy for this dataset, and the k-MST ranked first among methods that do not require previous information on the expected number of clusters.

bioinformatics↗

bioRxiv2024

Unveiling the hidden interactome of CRBN molecular glues with chemoproteomics

Targeted protein degradation and induced proximity refer to strategies that leverage the recruitment of proteins to facilitate their modification, regulation or degradation. As prospective design of glues remains challenging, unbiased discovery methods are needed to unveil hidden chemical targets. Here we establish a high throughput affinity purification mass spectrometry workflow in cell lysates for the unbiased identification of molecular glue targets. By mapping the targets of 20 CRBN-binding molecular glues, we identify 298 protein targets and demonstrate the utility of enrichment methods for identifying novel targets overlooked using established methods. We use a computational workflow to estimate target confidence and perform a biochemical screen to identify a lead compound for the new non-ZF target PPIL4. Our study provides a comprehensive inventory of targets chemically recruited to CRBN and delivers a robust and scalable workflow for identifying new drug-induced protein interactions in cell lysates.

cancer biology↗

bioRxiv2024

Targeted Degradation of CDK9 Potently Disrupts the MYC Transcriptional Network

Cyclin-dependent kinase 9 (CDK9) coordinates signaling events that regulate RNA polymerase II (Pol II) pause-release states. It is an important co-factor for transcription factors, such as MYC, that drive aberrant cell proliferation when their expression is deregulated. CDK9 modulation offers an approach for attenuating dysregulation in such transcriptional programs. As a result, numerous drug development campaigns to inhibit CDK9 kinase activity have been pursued. More recently, targeted degradation has emerged as an attractive approach. However, comprehensive evaluation of degradation versus inhibition is still critically needed to assess the biological contexts in which degradation might offer superior therapeutic benefits. We validated that CDK9 inhibition triggers a compensatory mechanism that dampens its effect on MYC expression and found that this feedback mechanism was absent when the kinase is degraded. Importantly, CDK9 degradation is more effective than its inhibition for disrupting MYC transcriptional regulatory circuitry likely through the abrogation of both enzymatic and scaffolding functions of CDK9. Highlights- KI-CDK9d-32 is a highly potent and selective CDK9 degrader. - KI-CDK9d-32 leads to rapid downregulation of MYC protein and mRNA transcripts levels. - KI-CDK9d-32 represses canonical MYC pathways and leads to a destabilization of nucleolar homeostasis. - Multidrug resistance ABCB1 gene emerged as the strongest resistance marker for the CDK9 PROTAC degrader.

cancer biology↗

bioRxiv2024

Evaluating treatments for the protection of grapevine pruning wounds from natural infection by trunk disease fungi

Infection of grapevines by fungal pathogens causing grapevine trunk diseases (GTDs) primarily arises from annual pruning wounds made during the dormant season. While various studies have showcased the efficacy of products in shielding pruning wounds against GTDs infections, most of these investigations hinge on artificial pathogen inoculations, which may not faithfully mirror real field conditions. This study aimed to evaluate and compare the efficacy of various liquid formulation fungicides (pyraclostrobin + boscalid) and paste treatments, as well as biological control agents (BCA: Trichoderma atroviride SC1, T. atroviride I-1237, and T. asperellum ICC012 + T. gamsii ICC080), for their potential to prevent natural infection of grapevine pruning wounds by trunk disease fungi in two field trials located in Samaniego (Northern Spain) and Madiran (Southern France) over three growing seasons. Wound treatments were applied immediately after pruning in February. One year after pruning, canes were harvested from vines and brought to the laboratory for assessment of Trichoderma spp. and fungal trunk pathogens. More than 1,200 fungal isolates associated with five GTDs (esca, Botryophaeria, Diaporthe and Eutypa diebacks, and Cytospora canker) were collected from the two vineyards each growing season. Our findings reveal that none of the products under investigation exhibited complete effectiveness against all the GTDs. The efficacy of these products was particularly influenced by the specific year of study. A notable exception was observed with the biocontrol agent T. atroviride I-1237, which consistently demonstrated effectiveness against Botryosphaeria dieback infections throughout each year of the study, irrespective of the location. The remaining products exhibited efficacy in specific years or locations against particular diseases, with the physical barrier (paste) showing the least overall effectiveness. The recovery rates of Trichoderma spp. in treated plants were highly variable, ranging from 17% to 100%, with both strains of T. atroviride yielding the highest isolation rates. This study underscores the importance of customizing treatments for specific diseases, taking into account the influence of environmental factors for BCA applications.

microbiology↗

bioRxiv2023

DrugMap: A quantitative pan-cancer analysis of cysteine ligandability

Cysteine-focused chemical proteomic platforms have accelerated the clinical development of covalent inhibitors of a wide-range of targets in cancer. However, how different oncogenic contexts influence cysteine targeting remains unknown. To address this question, we have developed DrugMap, an atlas of cysteine ligandability compiled across 416 cancer cell lines. We unexpectedly find that cysteine ligandability varies across cancer cell lines, and we attribute this to differences in cellular redox states, protein conformational changes, and genetic mutations. Leveraging these findings, we identify actionable cysteines in NF{kappa}B1 and SOX10 and develop corresponding covalent ligands that block the activity of these transcription factors. We demonstrate that the NF{kappa}B1 probe blocks DNA binding, whereas the SOX10 ligand increases SOX10-SOX10 interactions and disrupts melanoma transcriptional signaling. Our findings reveal heterogeneity in cysteine ligandability across cancers, pinpoint cell-intrinsic features driving cysteine targeting, and illustrate the use of covalent probes to disrupt oncogenic transcription factor activity.

systems biology↗

bioRxiv2022

Inhibition of vaccinia virus L1 N-myristoylation by the host N-myristoyltransferase inhibitor IMP-1088 generates non-infectious virions defective in cell entry

We have recently shown that the replication of rhinovirus, poliovirus and foot-and-mouth disease virus requires the co-translational N-myristoylation of viral proteins by human host cell N-myristoyltransferases (NMTs), and is inhibited by treatment with IMP-1088, an ultrapotent small molecule NMT inhibitor. Here, we reveal the role of N-myristoylation during vaccinia virus (VACV) infection in human host cells and demonstrate the anti-poxviral effects of IMP-1088. N-myristoylated proteins from VACV and the host were metabolically labelled with myristic acid alkyne during infection using quantitative chemical proteomics. We identified VACV proteins A16, G9 and L1 to be N-myristoylated. Treatment with NMT inhibitor IMP-1088 potently abrogated VACV infection, while VACV gene expression, DNA replication, morphogenesis and EV formation remained unaffected. Importantly, we observed that loss of N-myristoylation resulted in greatly reduced infectivity of assembled mature virus particles, characterized by significantly reduced host cell entry and a decline in membrane fusion activity of progeny virus. While the N-myristoylation of VACV entry proteins L1, A16 and G9 was inhibited by IMP-1088, mutational and genetic studies demonstrated that the N-myristoylation of L1 was the most critical for VACV entry. Given the significant genetic identity between VACV, monkeypox virus and variola virus L1 homologs, our data provides a basis for further investigating the role of N-myristoylation in poxviral infections as well as the potential of selective NMT inhibitors like IMP-1088 as broad-spectrum poxvirus inhibitors.

microbiology↗

bioRxiv2020

Field evaluation of biocontrol agents against black-foot and Petri diseases of grapevine

BACKGROUNDBlack-foot and Petri diseases are the main fungal diseases associated with young grapevine decline. Two field experiments were established to evaluate the preventive effect of two potential biocontrol agents (BCAs), i.e. Streptomyces sp. E1 + R4 and Pythium oligandrum Po37, and three BCA-commercial products containing Trichoderma atroviride SC1, Trichoderma koningii TK7 and Pseudomonas fluorescens+Bacillus atrophaeus on fungal infection in grafted plants and plant growth parameters. RESULTSThe effectiveness of some BCA in reducing the incidence and severity of both diseases was dependent on the plant part analyzed and the plant age. No single BCA application was able to control both diseases. Streptomyces sp. E1+R4 were able to reduce significantly black-foot disease infection while P. oligandrum Po37 and Trichoderma spp. were able to reduce significantly Petri disease infection. BCA treatments had no effect on the shoot weight, and root weight was significantly lower in all BCA treatments with respect to the control. CONCLUSIONSThe combination of the disease-suppressive activity of two or more beneficial microbes in a biocontrol preparation is required to prevent infection by black-foot and Petri disease fungi in vineyards.

plant biology↗

bioRxiv2017

Elucidating the genetic architecture of reproductive ageing in the Japanese population

Population studies over the past decade have successfully elucidated the genetic architecture of reproductive ageing. However, those studies were largely limited to European ancestries, restricting the generalizability of the findings and overlooking possible key genes poorly captured by common European genetic variation. Here, in up to 67,029 women of Japanese ancestry, we report 26 loci (all P<5x10{macron}8) for puberty timing or age at menopause, representing the first loci for reproductive ageing in any non-European population. Highlighted genes for menopause include GNRH1, which supports a primary, rather than passive, role for hypothalamic-pituitary GnRH signalling in the timing of menopause. For puberty timing, we demonstrate an aetiological role for receptor-like protein tyrosine phosphatases by combining evidence across population genetics and pre- and peri-pubertal changes in hypothalamic gene expression in rodent and primate models. Furthermore, our findings demonstrate widespread differences in allele frequencies and effect estimates between Japanese and European populations, highlighting the benefits and challenges of large-scale trans-ethnic approaches.

genetics↗