Biology subjects

Santos, A.

Publications and source records attributed to Santos, A..

At least 19 recordsLinked to original sources

bioRxiv2026

Cldn18 evolution reveals pleiotropic constraints in vertebrate stomach loss

Understanding the origins of anatomical innovations is central to elucidate the evolution of phenotypic diversity, as novel body plans often underpin the colonization of new ecological niches. The stomach, with its acid-secreting glands, evolved in the gnathostome ancestor and has been lost repeatedly. Claudin 18 (CLDN18) is a tight-junction protein that preserves gastric epithelial integrity against extreme H gradients and, in mammals, also acts in the lung through alternative first-exon isoforms. This dual role suggests that pleiotropy may shape the fate of CLDN18 after stomach loss. Here, we provide a detailed analysis of CLDN18 evolution across jawed vertebrates. CLDN18 originated in the gnathostome ancestor and is expressed in the stomach of elasmobranchs. We found no evidence of the gene in chimaeras or lungfishes, two additional agastric lineages, extending the loss of cldn18a previously described in agastric teleosts. Exon 1 architecture indicates a tandem duplication in the Euteleostomi ancestor, whereas stomach- and lung-associated isoforms are partitioned in most tetrapods examined. Monotremes, although agastric, retain only the lung-associated exon 1, consistent with lung function sustaining selection on the locus. Together, these findings reveal a complex evolutionary history involving gene loss, alternative splicing, tissue-specific regulation, and secondary exon loss, highlighting how pleiotropy and regulatory partitioning shaped the evolution of epithelia in jawed vertebrates.

evolutionary biology↗

bioRxiv2026

Metabolic engineering of Salmonella enterica for coupled kynurenine sensing and depletion enhances antitumor efficacy

Immunosuppressive tumor metabolic microenvironment remains a major barrier to effective cancer therapy. Tumor-targeting Salmonella enterica strains were engineered to deplete the intratumoral immunosuppressive kynurenine, triggering metabolic rewiring and fostering an active antitumor immune microenvironment. Equipping S. enterica VNP20009 with bacterial kynureninase enzyme (KynU) and a kynurenine transporter enabled efficient intratumoral kynurenine degradation. We then developed a next-generation strain, AD51, combining quorum-sensing controlled KynU expression with kynurenine-dependent growth and tumor targeting. AD51 induced robust immune activation and exhibited better anti-tumor efficacy. The addition of intratumoral exogenous IFN{gamma} to AD51 synergistically enhanced immune activation and antitumor efficacy in murine ovarian cancer and melanoma models, reducing tumor burden by 75% and 84%, respectively, compared with untreated controls (p<0.0001 for both). Our data establishes a framework for engineering bacteria to target and degrade tumor immunosuppressive metabolites while coupling bacterial growth to metabolite availability, paving the way for more precise and programmable microbial therapies.

cancer biology↗

bioRxiv2026

CFTR dysfunction in the intestinal epithelium is sufficient to promote pathogenic expansion of E. coli and enhanced barrier permeability in cystic fibrosis

Changes in the gut microbiome in cystic fibrosis (CF) are well characterized, yet their causes and downstream effects remain largely unknown. Well-documented alterations include reduced overall complexity (i.e. alpha diversity) of the gut microbiota and increased relative abundance of E. coli, which are associated with greater inflammation and shorter stature in infants. Previous results from our laboratory using a germ-free cystic fibrosis transmembrane conductance regulator (Cftr) mutant mouse model (CF mouse) demonstrated that the observed fecal microbiome dysbiosis is driven by mutated Cftr independent of factors such as diet or antibiotic treatment. We expand on these results in this report by using the defined 8-member community Altered Schaedler Flora (ASF) with and without E. coli, to show that E. coli is pathogenic in the context of the CF gut microbiome, resulting in increased intestinal permeability. We also show that Cftr deletion in intestinal epithelial cells alone, using a Villin-Cre targeted model, is sufficient to raise E. coli abundance in the fecal microbiome, increase intestinal permeability, and amplify the number of TH17 cells in the mesenteric lymph nodes. Together, our results demonstrate that the intestinal epithelium plays a dominant role in fecal microbiome alterations in CF and that the resultant dysbiosis contributes to CF pathogenesis.

microbiology↗

bioRxiv2026

DeepVir: A reproducible workflow for large-scale viral dark matter discovery

High-throughput sequencing (HTS) has revolutionized virosphere exploration. However, characterizing highly divergent viral sequences remains a bottleneck known as Viral Dark Matter (VDM). Numerous tools were developed to unravel such diversity, but they usually require complex prior HTS data analysis processes. Consequently, a common bottleneck to VDM exploration is the manual, chained execution of complex command-line applications. To address the need for automated and scalable viral discovery, we developed DeepVir, a reproducible Snakemake pipeline that integrates classical homology-based alignments with profile Hidden Markov Model (HMM) mining of the RNA-dependent RNA polymerase (RdRp). To validate the pipelines efficacy, we analyzed 385.23 GB of publicly available transcriptomic data (203 Sequence Read Archive libraries) from 49 American bat species. DeepVir successfully identified 179 distinct viral groups. This included 903 contigs spanning nine known viral families, enabling the characterization of novel genomes within Orthomyxoviridae (Influenza A H7N9), Picornaviridae, Alphaflexiviridae, Retroviridae (Spumaretrovirinae), Papillomaviridae, Herpesviridae, and Adenoviridae. Furthermore, the pipeline uncovered 170 putative novel VDM lineages. By employing deep homology searches and Sequence Similarity Network (SSN) visualization, we contextualized these highly divergent VDM sequences, revealing significant evolutionary relationships with the orders Mononegavirales and Bunyavirales. Notably, human-driven curation of the pipelines outputs allowed for the cross-library assembly of the first putative exogenous Spumavirus in the Americas. Ultimately, by automating complex bioinformatic processing steps, scalable pipelines like DeepVir empower researchers to prioritize the biological and epidemiological interpretation of their findings, accelerating the characterization of wildlife virospheres and enhancing pathogen genomic surveillance.

bioinformatics↗

bioRxiv2026

Learning from tandem mass spectra at scale with a self-supervised foundation model for proteomics

Mass spectrometry-based proteomics increasingly relies on machine learning, yet existing models are trained for defined supervised tasks such as peptide identification, de novo sequencing or fragment intensity prediction, limiting transfer across datasets, instruments and acquisition methods. Here we present InstaNovo-FM, a self-supervised foundation model for bottom-up proteomics trained to reconstruct masked regions of tandem mass spectra. We assemble a diverse training corpus spanning 1.63 billion MS/MS spectra and 184.6 million high-confidence annotations. We train an encoder-only transformer on the annotated tier using a physics-aware masked reconstruction objective. We demonstrate that the InstaNovo-FM embeddings encode fundamental experimental and biological properties, including fragmentation method, sequence properties and post-translational modifications, without requiring peptide labels. Furthermore, this foundation model directly enables diverse downstream applications, including de novo peptide sequencing, database-free identification and analytical run classification. InstaNovo-FM establishes a unified representation space for peptide fragmentation spectra, enabling robust transferability across the proteomics ecosystem.

bioinformatics↗

bioRxiv2026

Single-Cell Metagenomics Links Plasmid-Derived Antimicrobial Resistance to Hosts in the Pig Gut Microbiome

Antimicrobial exposure can alter gut resistance reservoirs, but bulk metagenomics alone often cannot distinguish whether observed changes reflect expansion of bacterial hosts, altered abundance of plasmid-derived sequences, or redistribution of mobile elements across host backgrounds. Here, we combined longitudinal bulk short-read metagenomics with selected bulk long-read and single-cell shotgun metagenomic sequencing to analyse faecal samples from six Danish pigs over 11 weeks, including an unplanned tiamulin exposure affecting the three pigs housed on the right side of the stable. We constructed a catalogue of 885 plasmid-derived sequences collapsed into 195 bins. Twenty-eight bins and 212 contigs carried resistance annotations, including ribosomal-target markers relevant to pleuromutilin exposure. Single-cell evidence linked subsets of plasmid-derived bins and contigs to bacterial host taxa, enabling host-resolved inspection of resistance-associated plasmid-derived features in longitudinal bulk metagenomes. The microbiome-wide plasmid-derived-sequence prevalence screen identified two bins with post-event associations, whereas resistance-gene abundance and host-attributed plasmid-derived-sequence abundance screens identified no significant host-resolved associations. Because exposure was unplanned and confounded with pen side and disease signs, treatment-response results are exploratory. The main contribution is a single-cell-informed microbial ecology workflow for linking plasmid-derived resistance features to host backgrounds and longitudinal abundance patterns in complex gut

microbiology↗

bioRxiv2026

Advanced microfluidic strategy for In-Bead MSC spheroid formation and co-encapsulation of necrosis inhibitor-loaded nanoparticles

Mesenchymal stem/stromal cells (MSCs) are key players in regenerative medicine due to their immunomodulatory properties and ability to promote tissue repair. However, their therapeutic efficacy is often limited by rapid clearance following transplantation. MSC spheroids have shown enhanced functional properties, and we hypothesize that encapsulating them within hydrogel microbeads could offer additional protection and improve their viability. In this study, we developed a novel droplet-based microfluidic protocol for human MSCs derived from the apical papilla (SCAP) encapsulation and In-Bead spheroid formation within alginate microbeads. Optimization of the protocol allowed the formation of MSC spheroids in alginate droplets overnight (In-Bead), before alginate cross-linking and retrieval of alginate beads loaded with MSC spheroids. SCAP were successfully encapsulated within 275 {micro}m alginate microbeads, forming spheroids of approximately 80 {micro}m in diameter. Encapsulated SCAP spheroids retained their immunomodulatory properties. The process was further optimized by incorporating nanomedicines into the alginate solution before the formation of droplets and then spheroids, forming thus hybrid beads (Sph.Beads/NP). Nanomedicines were loaded with NecroX-5, a necrosis inhibitor, to improve SCAP viability further. Live/Dead assays indicated a protective effect of the nanomedicines, supporting the potential of this system for advanced cell delivery in regenerative applications. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=150 SRC="FIGDIR/small/732109v1_ufig1.gif" ALT="Figure 1"> View larger version (30K): org.highwire.dtl.DTLVardef@1625a4eorg.highwire.dtl.DTLVardef@16c6faorg.highwire.dtl.DTLVardef@161819aorg.highwire.dtl.DTLVardef@83c0d7_HPS_FORMAT_FIGEXP M_FIG C_FIG Graphical abstractA combination strategy enhancing MSC viability through spheroid formation, microencapsulation, and nanomedicine association achieved by microfluidic encapsulation with In-Bead spheroid formation. Created with BioRender

bioengineering↗

bioRxiv2026

Toward understanding drivers of specialized metabolism in Actinomycetota: insights from 1432 transcriptomics datasets for 132 strains

Actinomycetota are major sources of specialized metabolites with applications in drug discovery and agriculture, yet much of their biosynthetic potential remains silent under standard laboratory conditions. Limited understanding of the mechanisms controlling biosynthetic gene cluster (BGC) activation constrains metabolite discovery and production. Here, we generated 1432 RNA-seq datasets from 132 Actinomycetota strains grown in eight media to identify patterns associated with BGC expression. On average, strains expressed 44% of their encoded BGCs across the tested conditions, with more expression observed among known BGCs (61%) compared to uncharacterized BGCs (35%). Co-expression analyses revealed frequent associations between BGCs and transporters, transcriptional regulators, and proteins containing DUF397 and DUF742 domains. Targeted overexpression of candidate genes selected from BGC-associated co-expression modules increased metabolite production, with DUF397- and DUF742-containing operons showing the broadest effects by boosting the levels of several different specialized metabolites. Other genes boosted levels in a metabolite-specific manner. Together, our results support a multilayered model of BGC regulation in Actinomycetota in which BGC expression is shaped by medium composition, BGC-specific regulators, and integration of BGCs into broader transcriptional network modules. By connecting BGC expression to specific media and co-expressed genes, this study also provides a resource for selecting growth conditions and engineering specialized metabolism.

microbiology↗

bioRxiv2025

αTAT1 defines a microtubule mechanosensing axis that drives fibroblast durotaxis and fibrosis across organs

Durotaxis, the directed migration of cells along gradients of extracellular stiffness, drives tissue fibrosis by recruiting fibroblasts to stiffened injury sites where hey differentiate into myofibroblasts and deposit scar tissue. While actin cytoskeletal tension and focal adhesion dynamics have been implicated in this process, the contribution of microtubules to cellular mechanosensing and durotaxis has remained undefined. Here, we uncover TAT1-mediated microtubule acetylation as a master regulator of fibroblast mechanosensing and stiffness-directed durotaxis. By catalyzing -tubulin K40 acetylation, TAT1 confers the structural flexibility required for directional microtubule alignment and persistent polarity along stiffness gradients, enabling fibroblasts to sense mechanical cues and initiate profibrotic programs. Loss of TAT1 abolishes K40 acetylation, disrupts focal adhesion FAK signaling, and suppresses YAP nuclear localization, thereby uncoupling extracellular matrix stiffness from downstream mechanotransduction. Global or fibroblast-specific deletion of TAT1 markedly reduces fibroblast durotaxis and myofibroblast accumulation, and protects mice from lung, dermal, and kidney fibrosis in experimental models, without affecting inflammation or vascular integrity. Together, our findings define TAT1-dependent microtubule mechanosensing as a central cytoskeletal pathway coupling fibroblast mechanobiology to organ fibrosis in vivo, positioning the TAT1 catalytic domain as a novel mechano-therapeutic target in fibrotic disease.

cell biology↗

bioRxiv2025

ABaCo: Addressing Heterogeneity Challenges in Metagenomic Data Integration with Adversarial Generative Models

The rapid advancement of high-throughput metagenomics has produced extensive and heterogeneous datasets with significant implications for environmental and human health. Integrating these datasets is crucial for understanding the functional roles of microbiomes and the interactions within microbial communities. However, this integration remains challenging due to technical heterogeneity and the inherent complexity of these biological systems. To address these challenges, we introduce ABaCo, a generative model that combines a Variational Autoencoder (VAE) with an adversarial discriminator specifically designed to handle the unique characteristics of metagenomic data. Our results demonstrate that ABaCo effectively integrates metagenomic data from multiple studies, corrects technical heterogeneity, outperforms existing methods, and preserves taxonomic-level biological signals. We have developed ABaCo as an open-source, fully documented Python library to facilitate, support and enhance metagenomics research in the scientific community.

bioinformatics↗

bioRxiv2025

Molecular Insights into ANPEP in Gastric Adenocarcinoma

Alanyl aminopeptidase (ANPEP) has been implicated in various cancers, but its specific role in gastric adenocarcinoma (GC) remains incompletely understood. This study analyzed ANPEP gene expression in gastric cancer (GC), peritumoral tissue (PTT), metaplasia (M), and normal tissue (N). Total RNA was extracted, libraries were prepared and sequenced on the Illumina NextSeq 500. Data was processed using the nf-core/rnaseq pipeline. Transcript quantifications were imported with tximport and normalized using DESeq2. Differential expression (|log2FC| >2; adj. p < 0.05) and Kruskal-Wallis tests identified key genes. ANPEP was significantly upregulated in GC, PTT, and M compared to normal tissue (p < 0.01), suggesting its involvement in early mucosal transformation and malignant progression. Heatmap analysis revealed upregulation of genes related to immune function and oxidative stress, indicating an immunosuppressive and apoptosis-resistant tumor microenvironment. Correlation analyses identified strong positive associations between ANPEP and genes involved in cytoskeletal remodeling, immune modulation, and metabolic regulation, suggesting that ANPEP supports both the invasive potential of tumor cells and the establishment of an immunosuppressive niche. These findings position ANPEP as a promising biomarker for early detection and a candidate for targeted therapies.

cancer biology↗

bioRxiv2025

Generalizable direct protein sequencing with InstaNexus

Protein-based therapeutics, such as antibodies and nanobodies, are not encoded in reference genomes, challenging their accurate characterization via standard proteomics. Current methods rely on indirect inference, fragmented outputs, and labor-intensive workflows, which hinder functional insights and routine application. Here, we present a generalizable, end-to-end workflow for direct protein sequencing, combining streamlined sample preparation, AI-driven de novo peptide sequencing, and tailored assembly to reconstruct contiguous protein sequences. A novel composite scoring framework prioritises longer assemblies and coverage, enhancing accuracy and reducing ambiguity. Validation across diverse protein modalities demonstrates its utility and ability to robustly sequence functionally critical regions of selected proteins. This workflow represents an advance in precision proteomics with promising applications in therapeutic discovery, immune profiling, and protein science.

bioinformatics↗

bioRxiv2025

C9orf72 polyGA knock-in mice exhibit mild motor and proteomic changes consistent with ALS/FTD

A GGGGCC repeat expansion in C9orf72 is the most common genetic cause of amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD). The repeat expansion is translated into five different dipeptide repeat proteins: polyGA, polyGP, polyGR, polyAP and polyPR. To investigate the effect of polyGA, which is the most abundant dipeptide repeat protein in patient brains, we used CRISPR/Cas9 to insert 400 codon-optimized polyGA repeats immediately downstream of the mouse C9orf72 start codon. This generated (GA)400 knock-in mice driven by the endogenous mouse C9orf72 promoter, coupled with heterozygous C9orf72 reduction. (GA)400 mice develop subtle pathology including mild motor dysfunction characterized by impaired rotarod performance. Quantitative proteomics revealed polyGA expression caused protein alterations in the spinal cord, including changes in previously identified polyGA interactors. Our findings show that (GA)400 mice are a complementary in vivo model to better understand C9ALS/FTD pathology and determine the specific role of single DPRs in disease.

neuroscience↗

bioRxiv2025

Resolving the full set of human polymorphic inversions and other complex variants from ultra-long read data

Inversions are a unique type of balanced structural variants (SVs) with important consequences in multiple organisms. However, despite considerable effort, this and other complex SVs remain poorly characterized due to the presence of large repeats. New techniques are finally allowing us to identify the full spectrum of human inversions, but the number of individuals analyzed is still quite limited. Here, we take advantage of Oxford Nanopore Technologies (ONT) long reads to characterize an exhaustive catalogue of 612 candidate inversions between 197 bp and 4.4 Mb of length and flanked by <190-kb long inverted repeats (IRs). For that, we developed a bioinformatic package to identify inversion alleles reliably from long read data. Next, using a combination of different DNA extraction, library preparation, and ONT sequencing protocols, we showed that ultra-long reads (50-100 kb) and adaptive sampling are an efficient method to detect most human inversions. Lastly, by analyzing ONT data from 54 diverse individuals, 87-99% of the inversions could be genotyped in each sample, depending mainly on read and IR length and genome coverage. Both orientations were observed for 155 of the analyzed regions (frequency 0.01-0.49), which multiplies by three the polymorphic IR-mediated inversions studied in detail so far. Moreover, we found more than 300 additional independent SVs in the studied regions and resolved several complex rearrangements. Our work therefore provides an accurate benchmark of those inversions that typically escape most analyses, improving existing resources, such as the Pangenome. In addition, it demonstrates the potential of nanopore sequencing to determine the functional impact of missing human genomic variation.

genomics↗

bioRxiv2025

Intratumoral expression of IL-12 and CD40 ligand (CD154) from plasmids generates antitumor responses that eliminate tumoral T regs

Intratumoral immunotherapy (ITIT) strives to generate effective antitumor immunity by directly stimulating the immune system in tumors to reverse local tumor-mediated immune suppression. In vivo expression of Interleukin-12 (IL-12) using in vivo plasmid transfection as an intratumoral cancer immunotherapy entered Phase II clinical trials for metastatic melanoma but to limited clinical success. We sought to improve the efficacy of in vivo IL-12 electroporation by the addition of a CD154 (CD40 ligand)- expressing plasmid to the IL-12 encoding plasmid treatment and assessing efficacy against solid tumors. Mice with intradermal B16F10 melanoma or MC38 murine colon carcinoma tumors received 2 weekly intratumoral (IT) injections of plasmids encoding IL-12 and CD154, followed by in vivo electroporation. The addition of CD154 to IL-12 was superior to IL-12 alone and resulted in frequent tumor clearance of treated tumors, marked by an increase in CD8 T cells and a drastic reduction in T regulatory cells in the tumor microenvironment. Tumor treatment responses were abrogated in mice which lack conventional DC1 cells (BatF3 KO) or lack CD8 T cells. These findings highlight the potential of adding CD154 to IL-12 plasmid electroporation as a cancer immunotherapy and suggest that other combinations would be therapeutically valuable.

immunology↗

bioRxiv2025

FMO4 drives lung adenocarcinoma by stabilizing the MAT2A/MAT2B complex and hindering ferroptosis

Lung cancer is the leading cause of death by cancer in the world and finding new targets is a major medical need to tackle this disease. Here, upon proteomic analysis to identify common players in oncogenic EGFR- and KRAS-driven lung adenocarcinoma mouse models, we uncovered a largely unknown protein in cancer, flavin-containing monooxygenase 4 (FMO4), whose expression was increased in lung tumors compared with adjacent lung tissue. FMO4 expression was strongly increased also in lung cancer samples from patients compared with healthy lung, and its expression level was inversely correlated with overall survival. Remarkably, in vivo deletion of FMO4 greatly decreased tumor burden and increased survival in oncogenic KRAS-driven lung adenocarcinoma mice unveiling its crucial role in tumor biology. Mechanistically, we found that FMO4 loss of function promotes ferroptosis and cooperates with ferroptosis inducers in vitro and in vivo. Moreover, FMO4 facilitates the interaction between MAT2A and MAT2B, promoting the generation of cysteine from methionine, which in turn boosts the generation of glutathione, thus protecting lung adenocarcinoma against ferroptosis. In summary we identified a new target in lung adenocarcinoma with important implications in cancer biology.

cancer biology↗

bioRxiv2025

The dispersal of domestic cats from Northern Africa and their introduction to Europe over the last two millennia

The domestic cat (Felis catus) descends from the African wildcat subspecies Felis lybica lybica. Its global distribution alongside humans testifies to its successful adaptation to anthropogenic environments. Uncertainty remains regarding whether domestic cats originated in the Levant, Egypt or elsewhere in its natural range, and on the timing and circumstances of their dispersal into Europe. By analysing 87 ancient and modern cat genomes, we demonstrate that domestic cats did not spread to Europe with Neolithic farmers, as previously thought. Conversely, our results suggest that they were introduced to Europe over the last 2,000 years, most likely from North Africa. We also demonstrate that a separate earlier (1st millennium BCE) introduction of wildcats from Northwest Africa originated the present-day wild population in Sardinia.

evolutionary biology↗

bioRxiv2025

VueGen: Automating the generation of scientific reports

MotivationThe analysis of omics data typically involves multiple bioinformatics tools and methods, each producing distinct output files. However, compiling these results into comprehensive reports often requires additional effort and technical skills. This creates a barrier for non-bioinformaticians, limiting their ability to produce reports from their findings. Moreover, the lack of streamlined reporting workflows impacts reproducibility and transparency, making it difficult to communicate results and track analytical processes. ResultsWe present VueGen, a tool that automates the creation of reports from bioinformatics outputs, allowing researchers with minimal coding experience to communicate their results effectively. With VueGen, users can produce reports by simply specifying a directory containing output files, such as plots, tables, networks, Markdown text, and HTML components, along with the report format. Supported formats include documents (PDF, HTML, DOCX, ODT), presentations (PPTX, Reveal.js), Jupyter notebooks, and Streamlit web applications. To showcase VueGens functionality, we present two case studies and provide detailed documentation to help users generate customized reports. Availability and implementationVueGen is distributed as a Python package, Docker image, nf-core module, and desktop application. The source code is freely available on https://github.com/Multiomics-Analytics-Group/vuegen under the MIT license. Documentation is provided at https://vuegen.readthedocs.io/.

bioinformatics↗