Biology subjects

Serrano, L.

Publications and source records attributed to Serrano, L..

At least 19 recordsLinked to original sources

bioRxiv2026

Bottom-up engineering of EV-mimetic vesicles reveals selective protein loading and modulates cellular uptake and biodistribution

Biological systems such as extracellular vesicles (EVs) are highly sophisticated and functionally diverse. Despite growing recognition of EVs' roles in health and disease through mediating intercellular communication, their inherent heterogeneity and challenges in purity and yield hinder their mechanistic research and clinical translation. To address this gap, we sought to translate essential EV properties into a controllable and simplified platform by engineering biomimetic synthetic vesicles (SVs) incorporating defined proteins and lipids. Using microfluidics, we generated SVs loaded with bulk membrane and cytosolic proteins from cancer cells, as well as individual organotropism-associated integrins. Bulk membrane protein incorporation into SVs reduced surface charge, modified lipid profiles, and enhanced cellular uptake, while integrin incorporation altered biodistribution. To investigate protein loading, we profiled input materials and SVs by mass spectrometry, identifying features linked to high incorporation, such as low molecular weight, positive charge, high isoelectric point, and predicted stability, globularity, lipidation, and amphipathic helices. This work presents a synthetic platform for dissecting the roles of EV-associated features and cargo, while providing insights into protein properties relevant to the optimization of delivery systems.

bioengineering↗

bioRxiv2026

Mechanistic pathway modeling reveals how IL-10 generates pleiotropic immune responses

IL-10 is a key anti-inflammatory cytokine whose activity is impaired in autoimmune diseases. However, IL-10 also promotes inflammation under certain conditions, limiting the efficacy of IL-10-based therapies. Because the principles underlying these opposing effects remain unclear, we developed a mathematical model of the IL-10 signaling pathway to understand how such pleiotropic responses arise. Considering that STAT3 signaling is buffered against changes in IL-10RB receptor affinity, we provide a minimal mechanistic explanation for IL-10 variants with anti-inflammatory or pro-inflammatory biased responses produced by an altered receptor affinity. By linking model-predicted pSTAT1 and pSTAT3 abundances with transcriptomic changes, we identified IL-10-responsive genes that are regulated at different pSTAT thresholds. This could explain how IL-10 elicits distinct downstream responses at different signaling strengths, and suggests that, depending on the required response, the affinity of IL10 for its receptors should not always be enhanced. Overall, our study highlights how modeling can help disentangle IL-10 pleiotropy to support the rational development of more effective IL-10-based therapies.

systems biology↗

bioRxiv2026

Multidimensional analysis of drought response in an inter-specific tomato population (ToMAGIC)

Drought stress poses a significant threat to agricultural productivity, particularly in regions with limited water availability. This study delves into the drought response in a multiparental interspecific tomato MAGIC population (ToMAGIC), developed by intercrossing Solanum pimpinellifolium (SP) and S. lycopersicum var. cerasiforme (SLC). A core collection of 139 recombinant lines, selected for their genetic diversity, was evaluated under both control and water stress conditions over two consecutive years. Phenotypic data were collected for 25 traits, including vegetative growth, flowering, fruit production, and physiological traits, providing a comprehensive assessment of drought response. Genome-wide association studies (GWAS) identified 15 significant genomic regions associated with drought response across eight chromosomes, highlighting key loci related to growth, earliness, fruit set, and physiological traits such as stomatal conductance and proline accumulation. Transgressive lines, such as S5_T_600 and S5_T_601, which exhibit enhanced drought resilience compared to the parental lines, were identified through genomic assisted selection, highlighting their potential as valuable breeding materials. The study emphasizes the importance of the ToMAGIC population in uncovering the polygenic nature of drought response. These findings offer valuable insights for developing drought-resilient tomato cultivars supporting agricultural sustainability in water-limited environments.

genomics↗

bioRxiv2025

Targeting Pseudomonas aeruginosa Ventilator-associated pneumonia with a non-antibiotic and biolfilm-disrupting Live Biotherapeutic: Preclinical Safety and Efficacy study

Background.Ventilator-associated pneumonia (VAP) is the second most common hospital-acquired infection and is associated with high morbidity and mortality. The insertion of the endotracheal tube (ETT) compromises the hosts bronchial defenses and facilitates the formation of microbial biofilms and VAP. Although antibiotics remain the cornerstone treatment, their efficacy is often compromised by poor biofilm penetration and the prevalence of multidrug-resistant bacteria. This reveals the need to develop novel non-antibiotic therapeutic strategies. We engineered a non-pathogenic strain of the pulmonary bacteria Mycoplasma pneumoniae CV2 to express anti-biofilm and bactericidal enzymes (VAP platform). The therapeutic effect was validated in a murine model of Pseudomonas aeruginosa infection and ex vivo in ETTs of patients with P. aeruginosa-induced VAP. Methods.We evaluated the safety of an improved version of CV2 (CV8, Mycochassis) in a miniature pig model, and its efficacy with the VAP therapeutic platform (CV8_VAP) in a piglet model of P. aeruginosa-induced VAP. CV8_VAP was administered via intralobe instillation or nebulization. We assessed the platforms ability to degrade biofilms formed on ETTs in vivo and its impact on the airway microbiota. We evaluated bacterial load in the lungs, inflammatory responses, histopathological and the clinical outcomes to provide a comprehensive characterization of therapeutic efficacy and safety. Findings.VAP platform reduced biofilm thickness and P. aeruginosa load in ETTs and lungs, with the nebulized route showing enhanced efficacy. CV8_VAP contributed on microbiome diversity restoration. Inflammatory markers in the lung were markedly decreased, suggesting a local immunomodulatory effect. Interpretation.These findings support that CV8_VAP as a promising, non-antibiotic therapeutic strategy for treating VAP caused by P. aeruginosa. Funding.The project that gave rise to these results has received funding from "La Caixa" Foundation (HR18-00058), and the European Research Council under the European Unions Horizon 2020 research and innovation program (670216).

synthetic biology↗

bioRxiv2025

Translational repression of viral RNA mediates arbovirus persistence in mosquitoes

Persistent infection of mosquito cells is essential for the transmission of arboviruses, yet how these viruses produce sufficient progeny without compromising host cell fitness remains unclear. Arbovirus genomes exhibit suboptimal codon usage for both human and mosquito hosts, raising questions about how they achieve efficient translation in such distinct cellular environments. Using chikungunya virus (CHIKV) as a model, we conducted a temporal, genome-wide analysis of transcription, translation, and tRNA modifications in Aedes albopictus C6/36 cells. Unlike in human cells, CHIKV infection does not alter the tRNA modification landscape in mosquitoes to overcome codon bias, nor does it induce widespread degradation of host transcripts. Instead, viral persistence is marked by a progressive, virus-specific repression of CHIKV RNA translation, occurring alongside a recovery of host mRNA translation. This translational balance, maintained independently of the RNAi system, enables sustained viral production without major disruption to host gene expression. Our findings identify translational control as a central mechanism underlying persistent arbovirus infection in mosquito cells.

microbiology↗

bioRxiv2025

Quantitative essentiality in a reduced genome: a functional, regulatory and structural fitness map

Essentiality studies have traditionally focused on coding regions, often overlooking other small genetic regulatory elements. To address this, we obtained a high-resolution essentiality map at near-single-nucleotide precision of the genome-reduced bacterium Mycoplasma pneumoniae, combining transposon libraries containing promoter or terminator sequences. By integrating temporal transposon-sequencing data, we developed a novel method of essentiality assessment based on k-means unsupervised clustering, which provides dynamic and quantitative information on the fitness contribution of different genomic regions. We compared the insertion tolerance and persistence of the two engineered libraries, assessing the local impact of transcription and termination on cell fitness. Essentiality assessment at the local base-level revealed essential protein domains and small genomic regions that are either essential or inaccessible to transposon insertion. We also identified structural regions within essential genes that tolerate transposon disruptions, resulting in functionally split proteins. Overall, this study presents a nuanced view of gene essentiality, shifting from static and binary models to a more accurate perspective. Additionally, it provides valuable insights for genome engineering and enhances our understanding of the biology of genome-reduced cells.

systems biology↗

bioRxiv2025

Using single-cell perturbation screens to decode the regulatory architecture of splicing factor programs

Splicing factors shape the isoform pool of most transcribed genes, playing a critical role in cellular physiology. Their dysregulation is a hallmark of diseases like cancer, where aberrant splicing contributes to progression. While exon inclusion signatures accurately assess changes in splicing factor activity, systematically mapping disease-driver regulatory interactions at scale remains challenging. Perturb-seq, which combines CRISPR-based perturbations with single-cell RNA sequencing, enables high-throughput measurement of perturbed gene expression signatures but lacks exon-level resolution, limiting its application for splicing factor activity analysis. Here, we show that shallow artificial neural networks (ANNs) can estimate splicing factor activity from gene expression signatures, bypassing the need for exon-level data. As a case study, we map the genetic interactions regulating splicing factors during carcinogenesis, using the shift in splicing program activity -where oncogenic-like splicing factors become more active than tumor suppressor-like factors- as a molecular reporter of a Perturb-seq screen. Our analysis reveals a cross-regulatory loop among splicing factors, involving protein-protein and splicing-mediated interactions, with MYC linking cancer driver mutations to splicing regulation. This network recapitulates splicing factor modulation during development. Altogether, we establish a versatile framework for studying splicing factor regulation and demonstrate its utility for uncovering disease mechanisms. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=79 SRC="FIGDIR/small/637061v1_ufig1.gif" ALT="Figure 1"> View larger version (37K): org.highwire.dtl.DTLVardef@4f02ddorg.highwire.dtl.DTLVardef@14538e0org.highwire.dtl.DTLVardef@198ffe7org.highwire.dtl.DTLVardef@1c8cee7_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOGRAPHICAL ABSTRACTC_FLOATNO C_FIG

systems biology↗

bioRxiv2024

Disentangling the splicing factor programs underlying complex molecular phenotypes

Splicing factors control exon inclusion in messenger RNAs, shaping transcriptome and proteome diversity. Their catalytic activity is regulated by multiple layers, making single-omic measurements on their own fall short in identifying which splicing factors underlie a phenotype. Here, we posit that splicing factor activity can be estimated from changes in exon inclusion. To test this hypothesis, we benchmarked methods for constructing splicing factor[->]exon networks and estimating splicing factor activity. We found that combining RNA-seq perturbation-based networks with VIPER (Virtual Inference of Protein Activity by Enriched Regulon analysis) accurately captures splicing factor activation as modulated by multiple regulatory layers. This approach integrates splicing factor regulation into a single score derived solely from exon inclusion signatures, allowing functional interpretation of heterogeneous conditions. As a proof of concept, we identify recurrent cancer splicing programs, revealing oncogenic- and tumor suppressor-like splicing factors missed by conventional methods. These programs correlate with patient survival and key cancer hallmarks: initiation, proliferation, and immune evasion. Altogether, we show splicing factor activity can be accurately estimated from exon inclusion changes, enabling comprehensive analyses of splicing regulation with minimal data requirements.

systems biology↗

bioRxiv2024

Finding Fluorescence: Utilizing community science to document novel biofluorescence occurrences and encourage community engagement in science

Fluorescence, a form of photoluminescence, is the emission of light at a longer wavelength by a substance when exposed to shorter-wavelength energy. Biofluorescence, which can be observed in living organisms, involves the absorption of light at one wavelength and re-emission at a longer wavelength due to fluorophores in specialized cells or structures. While initially studied in marine organisms, attention has shifted to exploring biofluorescence in terrestrial organisms, revealing roles in reproduction, camouflage, communication, and prey attraction across phyla. Community science databases engage the public in data collection, fostering scientific discovery and strengthening the science-society connection. Such databases have become valuable tools and have aided scientists in understanding the natural history of many different traits in organisms. This paper introduces Finding Fluorescence, the first biofluorescence-based community science website established in 2020 to gather public observations of biofluorescent organisms. The study presents at least 15 novel biofluorescence accounts spanning five phyla, 15 families, and 15 species. The observations collected from Finding Fluorescence contribute to our understanding of fluorescence in organisms and provide insight into possible ecological functions. We emphasize the importance of community engagement in scientific exploration and encourage future studies to incorporate such aspects into their research.

ecology↗

bioRxiv2024

Peptidoform analysis of IP-MS data allows detection of differentially present bait proteoforms

While it is recognised that protein functions are determined by their proteoform state, such as mutations and post-translational modifications, methods to determine their differential abundance between conditions are limited. Here, we present a novel workflow for classical immunoprecipitation coupled to mass spectrometry (IP-MS) data that focuses on identifying differential peptidoforms of the bait protein between conditions, providing additional information about protein function.

bioinformatics↗

bioRxiv2023

Wnt binding to Coatomer proteins directs secretion on exosomes independently of palmitoylation

Wnt proteins are secreted hydrophobic glycoproteins that act over long distances through poorly understood mechanisms. We discovered that Wnt7a is secreted on extracellular vesicles (EVs) following muscle injury. Structural analysis identified the motif responsible for Wnt7a secretion on EVs that we term the Exosome Binding Peptide (EBP). Addition of the EBP to an unrelated protein directed secretion on EVs. Disruption of palmitoylation, knockdown of WLS, or deletion of the N-terminal signal peptide did not affect Wnt7a secretion on purified EVs. Bio-ID analysis identified Coatomer proteins as candidates responsible for loading Wnt7a onto EVs. The crystal structure of EBP bound to the COPB2 coatomer subunit, the binding thermodynamics, and mutagenesis experiments, together demonstrate that a dilysine motif in the EBP mediates binding to COPB2. Other Wnts contain functionally analogous structural motifs. Mutation of the EBP results in a significant impairment in the ability of Wnt7a to stimulate regeneration, indicating that secretion of Wnt7a on exosomes is critical for normal regeneration in vivo. Our studies have defined the structural mechanism that mediates binding of Wnt7a to exosomes and elucidated the singularity of long-range Wnt signalling.

molecular biology↗

bioRxiv2023

Integrating physics in deep learning algorithms: A force field as a PyTorch module

Deep learning algorithms applied to structural biology often struggle to converge to meaningful solutions when limited data is available, since they are required to learn complex physical rules from examples. State-of-the-art force-fields, however, cannot interface with deep learning algorithms due to their implementation. We present MadraX, a forcefield implemented as a differentiable PyTorch module, able to interact with deep learning algorithms in an end-to-end fashion. MadraX is available at madrax.readthedocs.io

bioinformatics↗

bioRxiv2022

SIRT1 regulates DNA damage signaling through the PP4phosphatase complex

The Sirtuin family of NAD+-dependent enzymes plays an important role in maintaining genome stability upon stress. Several mammalian Sirtuins have been linked directly or indirectly to the regulation of DNA damage during replication through Homologous recombination (HR). The role of one of them, SIRT1, is intriguing as it seems to have a general regulatory role in the DNA damage response (DDR) that has not yet been addressed. SIRT1-deficient cells show impaired DDR reflected in a decrease in repair capacity, increased genome instability and decreased levels of {gamma}H2AX. Here we unveil a close functional antagonism between SIRT1 and the PP4 phosphatase multiprotein complex in the regulation of the DDR. Upon DNA damage, SIRT1 interacts specifically with the catalytical subunit PP4c and promotes its inhibition by deacetylating the WH1 domain of the regulatory subunits PP4R3/{beta}. This in turn regulates {gamma}H2AX and RPA2 phosphorylation, two key events in the signaling of DNA damage and repair by HR. We propose a mechanism whereby during stress, SIRT1 signaling ensures a global control of DNA damage signaling through PP4.

molecular biology↗

bioRxiv2022

Exploring the adaptability and robustness of the central carbon metabolism of Mycoplasma pneumoniae

In this study we explored the adaptability and robustness of glycolysis and pyruvate metabolism of Mycoplasma pneumoniae (MPN). We used a dual approach, we analysed metabolomics data collected for a large number of OE and KO mutants and perturbation samples. Furthermore, we trained a dynamic model of central carbon metabolism and tested the models capacity to predict these mutants and perturbation samples as well as identify key controlling factors in central carbon metabolism. Our analysis of metabolite data as well as our model analysis indicate MPN metabolism is inherently robust against perturbations due to its network structure. Two key control hubs of central carbon metabolism were identified.

systems biology↗

bioRxiv2022

The BRD4S-LOXL2-MED1 interaction at the forefront of cell cycle transcriptional control in triple-negative breast cancer

Triple-negative breast cancer often develops resistance to single-agent treatments, which can be circumvented with targeted combinatorial approaches. Here, we demonstrate that the simultaneous inhibition of LOXL2 and BRD4 cooperate to reduce triple-negative breast cancer proliferation in vitro and in vivo. Mechanistically, we reveal that LOXL2 interacts in the nucleus with the short isoform of BRD4 and MED1 to control cell cycle progression at the gene expression level via sustaining the formation of BRD4-MED1 nuclear transcriptional foci. Indeed, the pharmacological or transcriptional repression of LOXL2 provokes downregulation of cell cycle gene expression, G1-S cell cycle arrest, and loss of BRD4-MED1 foci. Our results indicate that the BRD4S-LOXL2-MED1 interaction is fundamental for the proliferation of triple-negative breast cancer. Therefore, targeting such interaction holds potential for the development of novel triple-negative breast cancer therapies.

cancer biology↗

bioRxiv2022

Early Endosome Capture Proteomics and its Application to Amyloid Precursor Protein Intramembrane Processing by β and γ-Secretases

Degradation and recycling of plasma membrane-localized proteins occurs via the endolysosomal system, wherein endosomes bud into the cytosol from the plasma membrane and subsequently mature into degradative lysosomal compartments. The endolysosomal system also participates in intracellular membrane protein trafficking, signaling, and protein degradation via autophagy. Our understanding of the endolysosomal system has been significantly advanced through the development of methods for selective capture of lysosomes (termed Lyso-IP), but methods for analogous isolation of early intermediates in the endolysosomal system are lacking. Here, we develop an approach for rapid isolation of early/sorting endosomes through affinity capture of the early endosome-associated protein EEA1 (Endo-IP) and provide proteomic and lipidomic snapshots of early endosomes in action. In addition to resident endosomal components, we identify numerous recycling, regulatory and membrane fusion complexes as well as candidate cargo, providing a proteomic landscape of early/sorting endosomes that we distinguished from lysosomes via comparative proteomics. The approach allows capture of internalized transferrin within minutes of its addition to cells, indicating the utility of the approach for dynamic analysis of early/sorting endosomes. Among the endocytic cargo identified by Endo-IP was the amyloid precursor protein (APP) genetically linked with Alzheimers disease. Processing of APP to amyloidogenic A{beta} peptides by {beta}- and {gamma}-Secretases can occur within the endolysosomal system among other compartments, but methods for spatial quantification of A{beta} products in individual organelles are lacking. We combined Endo- and Lyso-IP with targeted proteomics to provide a spatial digital snapshot of A{beta} products. This analysis revealed that products of A{beta} processing by {beta}- and {gamma}-Secretases, and alterations in the specificity of cleavage by small molecule {gamma}-Secretase modulators, can be quantified in both early/sorting endosomes and lysosomes. We anticipate that the Endo-IP approach will facilitate systematic interrogation of the many processes that are coordinated on early endosomes.

cell biology↗

bioRxiv2022

Using protein-per-mRNA differences among human tissues in codon optimization

Codon usage and nucleotide composition of coding sequences have profound effects on protein expression. However, while it is recognized that different tissues have distinct tRNA profiles and codon usages in their transcriptomes, the effect of tissue-specific codon optimality on protein synthesis remains elusive. Here, we leverage existing state-of-the-art transcriptomics and proteomics datasets from the GTEx project and the Human Protein Atlas to compute the protein-to-mRNA ratios of 36 human tissues. Using this as a proxy of translational efficiency, we build a machine learning model that identifies codons enriched or depleted in specific tissues. In particular, we detect two clusters of tissues with an opposite pattern of codon preferences. We then use the identified patterns for the development of CUSTOM, a codon optimizer algorithm which suggests a synonymous codon design in order to optimize protein production in a tissue-specific manner. In a human cell model, we provide evidence that codon optimization should indeed take into account particularities of the translational machinery of the tissues in which the target proteins are expressed and that our approach can design genes with tissue-optimized expression profiles. Altogether, CUSTOM could benefit biological and biotechnological research, such as the design of tissue-targeted therapies and vaccines.

systems biology↗

bioRxiv2022

Evolutionary conservation of A/T-ending codons reflects co-regulation of expression and complex formation.

BackgroundIn a wide variety of organisms, synonymous codons are used with different frequencies, a phenomenon known as codon bias that plays an important role in determining expression levels. However, the importance of codon bias to facilitate the simultaneous turnover of thousands of protein-coding transcripts to bring about phenotypic changes in cellular programs such as development, has not yet been investigated in detail. ResultsHere, we discover that genes with A/T-ending codon preferences are expressed coordinately and display a high codon conservation in mammals. This feature is not observed in genes enriched in G/C-ending codons. A paradigmatic case of this phenomenon is KRAS, from the RAS family, an A/T-rich gene with a high codon conservation (95%) in comparison to HRAS (76%). Also, we find that genes with similar codon composition are more likely to be part of the same protein complex, and that genes with A/T-ending codons are more prone to form protein complexes than those rich in G/C. The codon preferences of genes with A/T-ending codons are conserved among vertebrates. We propose that codon conservation, a feature of expression-coordinated transcripts, is linked to the high expression variation and coordination of tRNA isoacceptors reading A/T-ending codons. ConclusionsOur data indicate that cells exploit A/T-ending codons to generate coordinated, fine-tuned changes of protein-coding transcripts. We suggest that this orchestration contributes to tissue-specific and ontogenetic-specific expression, which can facilitate, for instance, timely protein complex formation.

evolutionary biology↗