Biology subjects

Yanes, O.

Publications and source records attributed to Yanes, O..

10 recordsLinked to original sources

bioRxiv2026

Multi-omic dissection of reversible and persistent molecular alterations in diet-induced obesity

Diet-induced obesity drives broad molecular remodeling across host and microbial systems, but why lifestyle intervention reverses some of these alterations while others persist remains unclear. To address this, we performed a multi-omic characterization of diet-induced obese mice after a combined nutritional and exercise intervention, integrating liver transcriptomics, epigenomics, metabolomics and metallomics with gut metagenomics and metallomics. Multi-omics factor analysis resolved two dominant axes of variation. The first captured a broadly reversible response (~72% of altered variables), restored by dietary restriction and exercise, involving coordinated remodeling of hepatic metal homeostasis, epigenetic regulation, and immune and cell-turnover pathways. The second comprised persistent alterations resistant to intervention and driven primarily by microbial functional profiles: notably, functional diversity remained reduced despite substantial taxonomic recovery. Using germ-free mice to define the microbiota-responsive hepatic space, we found that a significant fraction of the persistent liver features fell within it, enriched in lipid metabolism (PPAR signaling, steroid and cholesterol biosynthesis, peroxisomal activity) and retinol metabolism. Sequential correlation analysis traced these changes to the loss of specific low-abundance taxa and their biosynthetic capacities, particularly vitamin (folate, biotin, cobalamin, pantothenate, thiamine) and cofactor metabolism, implicating microbiota-derived vitamin metabolism in sustained hepatic dysfunction. Cobalt was the sole essential element that remained persistently dysregulated and tracked dietary cobalt content, suggesting a diet--microbiota route to the persistent phenotype. These findings establish a dual regulatory framework in which metabolic plasticity is governed by reversible host-intrinsic and persistent microbiota-dependent processes, providing a systems-level explanation for obesogenic memory.

systems biology↗

bioRxiv2025

Solid Ionic Matrices applied via Low-Temperature Evaporation enable High-Resolution and Sensitive MALDI Imaging of Metabolites

Matrix-Assisted Laser Desorption/Ionization Mass Spectrometry Imaging (MALDI-MSI) has become a key technology for spatially resolved molecular analysis. However, imaging of low molecular weight compounds remains challenging due to spectral interferences in the low m/z range caused by conventional organic matrices. Ionic matrices (IMs), in contrast, reduce matrix-related background signals, improve spectral reproducibility, and enhance sensitivity for detecting metabolites and lipids, but their use in MALDI-MSI has so far been limited, primarily focusing on lipid imaging above m/z 500. Here, we present a novel approach combining solid ionic matrices (ISMs) with low-temperature thermal evaporation (LTE) to enhance MALDI-MSI performance for small metabolites. ISMs based on -cyano-4-hydroxycinnamic acid (CHCA) and 2,5-dihydroxybenzoic acid (DHB) provided superior sensitivity, with CHCA + N,N-diethylaniline enabling the detection and annotation of 73 small metabolites (m/z <500) in mouse brain at 20 {micro}m spatial resolution. When applied to the pancreas, this matrix enabled the first specific localization of melatonin and 3-iodotyrosine within the islets of Langerhans, opening new avenues for spatial metabolomics in endocrine research.

bioengineering↗

bioRxiv2025

The Multiomics Blueprint of Extreme Human Lifespan

The indexed individual, from now on termed M116, was the worlds oldest verified living person from January 17th 2023 until her passing on August 19th 2024, reaching the age of 117 years and 168 days (https://www.supercentenarian.com/records.html). She was a Caucasian woman born on March 4th 1907 in San Francisco, USA, from Spanish parents and settled in Spain since she was 8. A timeline of her life events and her genealogical tree are shown in Supplementary Fig. 1a-b. Although centenarians are becoming more common in the demographics of human populations, the so-called supercentenarians (over 110 years old) are still a rarity. In Catalonia, the historic nation where M116 lived, the life-expectancy for women is 86 years, so she exceeded the average by more than 30 years (https://www.idescat.cat). In a similar manner to premature aging syndromes, such as Hutchinson-Gilford Progeria and Werner syndrome, which can provide relevant clues about the mechanisms of aging, the study of supercentenarians might also shed light on the pathways involved in lifespan. To unfold the biological properties exhibited by such a remarkable human being, we developed a comprehensive multiomics analysis of her genomic, transcriptomic, metabolomic, proteomic, microbiomic and epigenomic landscapes in different tissues, as depicted in Fig. 1a, comparing the results with those observed in non-supercentenarian populations. The picture that emerges from our study shows that extremely advanced age and poor health are not intrinsically linked and that both processes can be distinguished and dissected at the molecular level. O_FIG O_LINKSMALLFIG WIDTH=156 HEIGHT=200 SRC="FIGDIR/small/639740v1_fig1.gif" ALT="Figure 1"> View larger version (63K): org.highwire.dtl.DTLVardef@1705be6org.highwire.dtl.DTLVardef@1a16e4borg.highwire.dtl.DTLVardef@15005f1org.highwire.dtl.DTLVardef@b6297b_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOFig. 1C_FLOATNO Chromosomes and genes.a, Schematic representation of all -omics studied in the supercentenarian. b, Telomeres marked with Cy3 (yellow) in nuclei stained with DAPI (blue) observed in HT-qFISH from M116 and younger womens PBMCs. Scale bars: 20 {micro}m. c, Telomere length (Kb) calculation (left) and percentage of extremely short telomeres (below the 20th percentile) (right) in M116 (orange) using standard curve from samples previously analyzed (black) and control women (blue) (Online Methods). d, Circos plot with chromosomal alterations detected through optical genome mapping in supercentenarian. e, Variants of interest (VOI)-harboring genes found in supercentenarians genomic DNA contributing to immune function, cardiovascular health, neuroprotection, metabolism, and DNA dynamics. f, Significantly enriched functions of VOI-harboring genes in the supercentenarian. g, VOI-harbouring genes significantly contributing to enriched functions. h, VOI-harboring genes found in supercentenarians genomic and mitochondrial DNA contributing to mitochondrial function. i, Mean fluorescence intensity of TMRE (a marker of mitochondrial membrane potential) and SOX (a marker of mitochondrial superoxide ion) in PBMCs from the supercentenarian (orange) and healthy controls across various ages (gray). Unpaired t-test was used to statistically compare M116 to the mean of all control women. *p < 0.05. C_FIG

genomics↗

bioRxiv2025

ChemEmbed: A deep learning framework for metabolite identification using enhanced MS/MS data and multidimensional molecular embeddings

Machine learning tools have become essential for annotating the vast number of unidentified MS/MS spectra in metabolomics, addressing the limitations of current reference spectral libraries. However, these tools often struggle with the high dimensionality and sparsity of MS/MS spectra and metabolite structures. ChemEmbed introduces a novel approach by combining multidimensional and continuous vector representations of chemical structures with enhanced MS/MS spectra. This enhancement is achieved by merging spectra from multiple collision energies and incorporating calculated neutral losses from 38,472 distinct compounds, providing richer input for a convolutional neural network (CNN). ChemEmbed achieves top-ranked candidate annotations in over 42% of cases and identifies the correct compound within the top five in more than 76% of cases in a test dataset. Against external benchmarks such as CASMI 2016 and 2022, ChemEmbed outperforms SIRIUS, the current state-of-the-art in computational metabolomics. In a validation experiment with the Annotated Recurrent Unidentified Spectra (ARUS) dataset-- including over 25,000 spectra from human plasma and 68,000 from urine-- ChemEmbed successfully identified 24 previously unannotated compounds. By aligning with the advanced capabilities of modern mass spectrometry instrumentation, ChemEmbed balances accuracy, computational efficiency, and scalability, making it a powerful solution for high-throughput metabolomics applications.

bioinformatics↗

bioRxiv2025

Improving MALDI Mass Spectrometry Imaging Performance: Low-Temperature Thermal Evaporation for Controlled Matrix Deposition and Improved Image Quality

The deposition of matrix compounds significantly influences the effectiveness of matrix-assisted laser desorption/ionization (MALDI) Mass Spectrometry Imaging (MSI) experiments, impacting sensitivity, spatial resolution, and reproducibility. Dry deposition methods offer advantages by producing homogeneous matrix layers and minimizing analyte delocalization without the use of solvents. However, refining these techniques to precisely control matrix thickness, minimize heating temperatures, and ensure high-purity matrix layers is crucial for optimizing MALDI-MSI performance. Here, we present a novel approach utilizing low-temperature thermal evaporation (LTE) for organic matrix deposition under reduced vacuum pressure. Our method allows for reproducible control of matrix layer thickness, as demonstrated by linear calibration for two organic matrices, 2,5-dihydroxybenzoic acid (DHB), and 1,5-Diaminonaphthalene (DAN). The environmental scanning electron microscopy images reveal a uniform distribution of small-sized matrix crystals, consistently on the submicrometer scale, across tissue slides following LTE deposition. Remarkably, LTE serves as an additional purification step for organic matrices, producing very pure layers irrespective of initial matrix purity. Furthermore, stability assessment of MALDI-MSI data from mouse brain sections coated with LTE-deposited DHB or DAN matrix indicates minimal impact on ionization efficiency, signal intensity, and image quality even after storage at - 80{degrees}C for two weeks, underscoring the robustness of LTE-deposited matrices for MSI applications. Comparative analysis with the spray-coating method highlights several advantages of LTE deposition, including enhanced ionization, reduced analyte diffusion, and improved MSI image quality.

bioengineering↗

bioRxiv2024

SingleFrag: A deep learning tool for MS/MS fragment and spectral prediction and metabolite annotation

Metabolite and small molecule identification via MS/MS involves matching experimental spectra with prerecorded spectra of known compounds. This process is hindered by the current lack of comprehensive reference spectral libraries. To address this gap, we need accurate in silico fragmentation tools for predicting MS/MS spectra of compounds for which empirical spectra do not exist. Here, we present SingleFrag, a novel deep learning tool that predicts individual fragments separately, rather than attempting to predict the entire fragmentation spectrum at once. Our results demonstrate that SingleFrag surpasses state-of-the-art in silico fragmentation tools, providing a powerful method for annotating unknown MS/MS spectra of known compounds. As a proof of concept, we successfully annotate three previously unidentified compounds frequently found in human samples.

bioinformatics↗

bioRxiv2024

Persister cancer cells are characterized by H4K20me3 heterochromatin that defines a low inflammatory profile

Anti-cancer therapies may induce proliferative arrest in cancer cells in the form of senescence or drug-tolerant persistency, the latter being a reversible arrest with similarities to embryonic diapause. Here, we use mTOR/PI3K inhibition to develop and characterize a model of persistency/diapause-like arrest in human cancer cells of various origins. We show that persister and senescent cancer cells share an expanded lysosomal compartment and hypersensitivity to BCL-XL inhibition. However, persister cells do not exhibit other features of senescence, such as the loss of Lamin B1, senescence-associated b-galactosidase activity, and an inflammatory phenotype. Compared to senescent cells, persister cells have a profoundly diminished senescence-associated secretory phenotype (SASP), low activation of interferon signaling pathways and lack upregulation of MHC-I presentation. Based on a genome-wide CRISPR/Cas9 screen performed in diapause mouse embryonic stem cells (mESC), we discover that persister human cancer cells are hypersensitive to the inhibition of one-carbon metabolism. This finding led us to uncover that the repressive heterochromatic mark H4K20me3 is enriched at promoters of SASP and interferon response genes in persister cells, but not in senescent cells. Collectively, we define novel features and vulnerabilities of persister cancer cells and we provide insight into the epigenetic mechanisms underlying their low inflammatory and immunogenic activity.

cancer biology↗

bioRxiv2023

A targeted metabolomic method to detect epigenetically relevant metabolites

Metabolites play a central role in the chemical crosstalk between metabolism and epigenetic marks. Epigenetically relevant metabolites are substrates, products and cofactors that can act as activators or inhibitors of epigenetic enzymes, which control gene expression by adding or removing chemical marks in the DNA, RNA and histones. Diet composition, and biosynthetic pathways encoded in the gut microbiome and the host genome are the main sources of these metabolites for mammals. Despite the increasing interest in the study of the microbiota-nutrient metabolism-host epigenetic axis to understand health and disease, there is a lack of a sensitive and easy analytical method to detect epigenetically relevant metabolites simultaneously. Here, we show an straightforward biphasic extraction where the organic phase is directly analyzed by GC-EI MS to detect short-chain fatty acids and formate without chemical derivatization, and the aqueous phase is analyzed by HILIC coupled to ESI-MS/MS, which together can cover >30 epigenetically relevant metabolites in biological samples such as liver, plasma or feces. In addition, we propose a stable isotope tracing method based on multiple-reaction monitoring (MRM) transitions by LC-QqQ MS to understand how 13C-labeled glucose or glutamine are used to build SAM and acetyl-CoA, the main methyl and acetyl group donors in epigenetic modifications, respectively. We anticipate that our methods will complement epigenomic and proteomic analyses adding another layer of molecular information towards mechanistic insights. HighlightsO_LIHost and microbiota metabolites link metabolism with epigenetic regulation. C_LIO_LIChemical structure diversity in epigenetically relevant metabolites challenges its analysis with a single method. C_LIO_LIA biphasic extraction with no chemical derivatization is able to recover SCFAs and other epigenetically relevant metabolites. C_LIO_LIA novel isotope trace experiment approach allows isotopomer resolution using MS2 data. C_LI

biochemistry↗

bioRxiv2021

HERMES: a molecular formula-oriented method to target the metabolome

Comprehensive metabolome analyses are hampered by low identification rates of metabolites due to suboptimal strategies in MS and MS2 acquisition, and data analysis. Here we present a molecular formula-oriented and peak detection-free method, HERMES, that improves sensitivity and selectivity for metabolite profiling in MS and structural annotation in MS2. An analysis of environmental water, E. coli, and human plasma extracts by HERMES showed increased biological specificity of MS2 scans, leading to improved mass spectral similarity scoring and identification rates when compared to iterative data-dependent acquisition (DDA). HERMES is available as an R package with a user-friendly graphical interface to allow data analysis and interactive tracking of compound annotations.

bioinformatics↗

bioRxiv2020

SAICAr-dependent and independent effects of ADSL deficiency on neurodevelopment

Adenylosuccinate Lyase (ADSL) functions in the de novo purine biosynthesis pathway. ADSL deficiency (ADSLD) causes numerous neurodevelopmental pathologies, including microcephaly and autism spectrum disorder. ADSLD patients have normal purine nucleotide levels but exhibit accumulation of the dephosphorylated ADSL substrates SAICAr and S-Ado. SAICAr was implicated in the neurotoxic effects of ADSLD, although its role remains unknown. We examined the effects of ADSL depletion in human cells and found increased DNA damage signaling, that was rescued by nucleosides, and impaired primary ciliogenesis, that was rescued by reducing SAICAr. By analyzing ADSL deficient chicken and zebrafish embryos we observed impaired neurogenesis and microcephaly, and neuroprogenitor attrition in zebrafish was rescued by reducing SAICAr. Zebrafish embryos also displayed phenotypes commonly linked to ciliopathies. Our results suggest that both reduced purine levels and SAICAr accumulation contribute to neurodevelopmental pathology in ADSLD and defective ciliogenesis may influence the ADSLD phenotypic spectrum.

developmental biology↗