Biology subjects

Avila-Pacheco, J.

Publications and source records attributed to Avila-Pacheco, J..

10 recordsLinked to original sources

bioRxiv2026

Microbial-associated acylated putrescines as immunomodulatory molecules in inflammatory bowel diseases

The gut microbiota regulates intestinal immunity through metabolite production, yet most disease-associated metabolites remain functionally uncharacterized. In inflammatory bowel diseases (IBD), where the microbial metabolome is profoundly altered, we identify N-acyl putrescines as microbiome-associated metabolites enriched across two independent cohorts. N-oleoylputrescine (NOP) emerges as the primary immunomodulatory candidate, inducing robust transcriptional responses in dendritic cells and colonic organoids. Enterocloster species harboring nonribosomal peptide synthetase gene clusters synthesize NOP, confirmed by isotope-tracing in vitro and germ-free mouse colonization in vivo. NOP suppresses core IBD inflammatory pathways in mouse dendritic cells and human monocytes, reducing signatures of histologic inflammation and therapy non-response. NOP dampens inflammation in four colitis models, decreases myeloid cell NF-{kappa}B activation, and suppresses type 1 immune responses through a T cell-intrinsic mechanism. That NOP accumulates in IBD despite its anti-inflammatory properties reveals a holobiont defense strategy: the gut microbiota deploys immunomodulatory metabolites as a compensatory response to restore homeostasis.

immunology↗

bioRxiv2026

Blautia wexlerae Transforms Dietary Fatty Acids to Activate Enteroendocrine Signaling and Improve Metabolic Health in Mice and Humans

Metabolites produced by the gut microbiome influence host metabolic health, but how this occurs remains incompletely defined. Here, we report that a common human gut commensal, Blautia wexlerae, converts dietary fats into bioactive metabolites that induce gut hormone production to affect glucose metabolism and suppress appetite. We found that colonization with Blautia wexlerae correlated with healthier eating behaviors in humans. Blautia wexlerae encodes a unique acyl transferase and is capable of producing acyl amines from nutrient substrates. These Blautia acyl amines stimulated human enteroendocrine cells to secrete GLP-1 and other gut peptide hormones more potently than endogenously produced acyl amines. When fed to mice, acyl amines improved glycemic control and decreased appetite. In humans, higher stool levels of Blautia DNA encoding acyl amine synthesis genes correlated with leanness and decreased dietary fat intake. These results define a mechanism of action for how Blautia wexlerae affects host metabolic control.

microbiology↗

bioRxiv2025

Plasma plasmalogen levels and risk of lymph node positive breast cancer

Lymph node involvement is a key predictor of poor breast cancer prognosis. Systemic lipid alterations can contribute to cancer cell survival in lymph nodes, but their relevance in humans remains unclear. Here, we combine human epidemiologic analyses from the Nurses Health Study 2 and complementary mechanistic studies in mouse models to investigate how systemic lipid profiles relate to lymph node positive breast cancer. We show that in pre-diagnostic human plasma (n=511), lower levels of phosphatidylethanolamine (PE) and phosphatidylcholine (PC)-enriched plasmalogens are associated with increased risk of lymph node positivity, with stronger associations in samples collected closer to diagnosis. Consistent with the human data, lower levels of PE and PC-enriched plasma plasmalogens are found in mice with nodal involvement. Furthermore, in mice, dietary PUFA depletion reduces lipid oxidation in breast cancer cells in lymph nodes and promotes their survival and metastatic spread. These findings suggest that reduced levels of PE and PC-plasmalogens and decreased PUFA availability creates a lipid environment that enables breast cancer lymph node involvement.

cancer biology↗

bioRxiv2025

Neural Spectral Prediction for Structure Elucidation with Tandem Mass Spectrometry

Structural elucidation using untargeted tandem mass spectrometry (MS/MS) has played a critical role in advancing scientific discovery [1, 2]. However, differentiating molecular fragmentation patterns between isobaric structures remains a prominent challenge in metabolomics [3-10], drug discovery [11-13], and reaction screening [14-17], presenting a significant barrier to the cost-effective and rapid identification of unknown molecular structures. Here, we present a geometric deep learning model, ICEBERG, that simulates high-energy collision-induced dissociation in mass spectrometry to generate chemically plausible fragments and their relative intensities with awareness of collision energies and polarities. We utilize ICEBERG predictions to facilitate structure elucidation by ranking a set of candidate structures based on the similarity between their predicted in silico MS/MS spectra and an experimental MS/MS spectrum of interest. This integrated elucidation pipeline enables state-of-the-art performance in compound annotation, with 40% top-1 accuracy on the NIST20 [M+H]+ adduct subset and with 92% of correct structures appearing in the top ten predictions in the same dataset. It achieves 46% top-1 and 86% top-10 accuracies when tested on the open-access MassSpecGym benchmark, and outperforms SIRIUS on a recently released test set with previously uncharacterized structures. We demonstrate several real-world case studies, including identifying clinical biomarkers of depression and tuberculous meningitis, annotating an aqueous abiotic degradation product of the pesticide thiophanate methyl, disambiguating isobaric products in pooled reaction screening, and annotating biosynthetic pathways in Withania somnifera. Overall, this deep learning-based paradigm for structural elucidation enables rapid molecular annotation from complex mixtures, driving discoveries across diverse scientific domains.

bioinformatics↗

bioRxiv2025

Distinct Classes of Gut Bacterial Molybdenum-Dependent Enzymes Produce Urolithins

Urolithin A is an anti-aging and anti-inflammatory gut bacterial metabolite derived from ellagic acid (EA), a polyphenol abundant in berries and nuts. The conversion of EA to urolithin A involves multiple chemically challenging phenol dehydroxylation steps that produce urolithins with varying bioactivities. Despite their biological and chemical significance, the bacterial enzymes responsible for urolithin production remain unidentified. Here, we use differential gene expression analysis, anaerobic protein expression, and enzyme assays to identify members of two distinct molybdenum enzyme families (the DMSO reductase family and the xanthine oxidase family) capable of regioselective dehydroxylation and urolithin generation. These two enzyme families have distinct substrate requirements, suggesting they employ different catalytic mechanisms for phenol dehydroxylation. Multi-omics analysis of a human cohort uncovers decreased levels of urolithin A and genes encoding urolithin A-producing enzymes in patients with inflammatory bowel disease (IBD), implying reduced health effects of EA consumption in this setting. Together, this study elucidates the molecular basis of urolithin production, expands the known enzymatic repertoire of the human gut microbiome, and suggests a potential link between gut bacterial urolithin production and host inflammation. Significance statementThe human gut microbiome modulates the health effects of dietary compounds by modifying their chemical structures. For example, gut microbes extensively metabolize polyphenols, a group of diverse plant-derived compounds associated with positive health outcomes. Urolithin A, a gut bacterial metabolite derived from a polyphenol abundant in berries and nuts, exhibits potent anti-inflammatory activity. However, the gut bacterial enzymes involved in its production remain largely unknown. Here, we report urolithin-producing gut bacterial enzymes, including four phenol dehydroxylases from two distinct molybdenum-dependent enzyme families. Analyzing human gut microbiomes suggests a potential link between genes encoding these enzymes and host inflammation. Together, our findings fully map urolithin A production to enzymes, increasing our understanding of how the gut microbiome can alter the impacts of diet on human health.

biochemistry↗

bioRxiv2024

Genetic screening and metabolomics identify glial adenosine metabolism as a therapeutic target in Parkinson's disease

Neuronal alpha-synucleinopathies, including Parkinson's disease (PD) and dementia with Lewy bodies (DLB), lack disease-modifying therapies. We developed a Drosophila model for identifying novel glial-based therapeutic targets for alpha-synucleinopathies. In this model, human alpha-synuclein is expressed in neurons and individual genes are independently knocked down in glia. We performed a forward genetic screen, knocking down the entire Drosophila kinome in glia in alpha-synuclein expressing flies. Among the top hits were five genes (Ak1, Ak6, Adk1, Adk2, and awd) involved in adenosine metabolism. Knockdown of each gene increased brain adenosine levels, improved locomotor dysfunction, reduced alpha-synuclein oligomer levels, and rescued neurodegeneration. We determined that the mechanism of neuroprotection requires adenosine signaling through the neuronal adenosine receptor (AdoR) in Drosophila. These experiments support glial adenosine as a novel therapeutic target in PD.

neuroscience↗

bioRxiv2022

Temporal dynamics of the multi-omic response to endurance exercise training across tissues

Regular exercise promotes whole-body health and prevents disease, yet the underlying molecular mechanisms throughout a whole organism are incompletely understood. Here, the Molecular Transducers of Physical Activity Consortium (MoTrPAC) profiled the temporal transcriptome, proteome, metabolome, lipidome, phosphoproteome, acetylproteome, ubiquitylproteome, epigenome, and immunome in whole blood, plasma, and 18 solid tissues in Rattus norvegicus over 8 weeks of endurance exercise training. The resulting data compendium encompasses 9466 assays across 19 tissues, 25 molecular platforms, and 4 training time points in young adult male and female rats. We identified thousands of shared and tissue- and sex-specific molecular alterations. Temporal multi-omic and multi-tissue analyses demonstrated distinct patterns of tissue remodeling, with widespread regulation of immune, metabolism, heat shock stress response, and mitochondrial pathways. These patterns provide biological insights into the adaptive responses to endurance training over time. For example, exercise training induced heart remodeling via altered activity of the Mef2 family of transcription factors and tyrosine kinases. Translational analyses revealed changes that are consistent with human endurance training data and negatively correlated with disease, including increased phospholipids and decreased triacylglycerols in the liver. Sex differences in training adaptation were widespread, including those in the brain, adrenal gland, lung, and adipose tissue. Integrative analyses generated novel hypotheses of disease relevance, including candidate mechanisms that link training adaptation to non-alcoholic fatty liver disease, inflammatory bowel disease, cardiovascular health, and tissue injury and recovery. The data and analysis results presented in this study will serve as valuable resources for the broader community and are provided in an easily accessible public repository (https://motrpac-data.org/). HighlightsO_LIMulti-tissue resource identifies 35,439 analytes regulated by endurance exercise training at 5% FDR across 211 combinations of tissues and molecular platforms. C_LIO_LIInterpretation of systemic and tissue-specific molecular adaptations produced hypotheses to help describe the health benefits induced by exercise. C_LIO_LIRobust sex-specific responses to endurance exercise training are observed across multiple organs at the molecular level. C_LIO_LIDeep multi-omic profiling of six tissues defines regulatory signals for tissue adaptation to endurance exercise training. C_LIO_LIAll data are available in a public repository, and processed data, analysis results, and code to reproduce major analyses are additionally available in convenient R packages. C_LI

molecular biology↗

bioRxiv2021

Human gut bacteria produce TH17-modulating bile acid metabolites

The microbiota plays a pivotal role in gut immune homeostasis. Bacteria influence the development and function of host immune cells, including T helper cells expressing interleukin-17a (TH17 cells). We previously reported that the bile acid metabolite 3-oxolithocholic acid (3-oxoLCA) inhibits TH17 cell differentiation1. While it was suggested that gut-residing bacteria produce 3-oxoLCA, the identity of such bacteria was unknown. Furthermore, it was not clear whether 3-oxoLCA and other immunomodulatory bile acids are associated with gut inflammatory pathologies in humans. Using a high-throughput screen, we identified human gut bacteria and corresponding enzymes that convert the secondary bile acid lithocholic acid into 3-oxoLCA as well as the abundant gut metabolite isolithocholic acid (isoLCA). Like 3-oxoLCA, isoLCA suppressed TH17 differentiation by inhibiting ROR{gamma}t (retinoic acid receptor-related orphan nuclear receptor {gamma}t), a key TH17 cell-promoting transcription factor. Levels of both 3-oxoLCA and isoLCA and the 3-hydroxysteroid dehydrogenase (3-HSDH) genes required for their biosynthesis were significantly reduced in patients with inflammatory bowel diseases (IBD). Moreover, levels of these bile acids were inversely correlated with expression of TH17 cell-associated genes. Overall, our data suggest that bacterially produced TH17 cell-inhibitory bile acids may reduce the risk of autoimmune and inflammatory disorders such as IBD.

immunology↗

bioRxiv2020

In Silico Modeling of Metabolic State in Single Th17 Cells Reveals Novel Regulators of Inflammation and Autoimmunity

Cellular metabolism, a key regulator of immune responses, is difficult to study with current technologies in individual cells Here, we present Compass, an algorithm to characterize the metabolic state of cells based on single-cell RNA-Seq and flux balance analysis. We applied Compass to associate metabolic states with functional variability (pathogenic potential) amongst Th17 cells and recovered a metabolic switch between glycolysis and fatty acid oxidation, akin to known differences between Th17 and Treg cells, as well as novel targets in amino-acid pathways, which we tested through targeted metabolic assays. Compass further predicted a particular glycolytic reaction (phosphoglycerate mutase -- PGAM) that promotes an anti-inflammatory Th17 phenotype, contrary to the common understanding of glycolysis as pro-inflammatory. We demonstrate that PGAM inhibition leads non-pathogenic Th17 cells to adopt a pro-inflammatory transcriptome and induce autoimmunity in vivo. Compass is broadly applicable for characterizing metabolic states of cells and relating metabolic heterogeneity to other cellular phenotypes.

genomics↗

bioRxiv2020

Metabolic and Epigenomic Regulation of Th17/Treg Balance by the Polyamine Pathway

Cellular metabolism can orchestrate immune cell function. We previously demonstrated that lipid biosynthesis represents one such gatekeeper to Th17 cell functional state. Utilizing Compass, a transcriptome-based algorithm for prediction of metabolic flux, we constructed a comprehensive metabolic circuitry for Th17 cell function and identified the polyamine pathway as a candidate metabolic node, the flux of which regulates the inflammatory function of T cells. Testing this prediction, we found that expression and activities of enzymes of the polyamine pathway were enhanced in pathogenic Th17 cells and suppressed in regulatory T cells. Perturbation of the polyamine pathway in Th17 cells suppressed canonical Th17 cell cytokines and promoted the expression of Foxp3, accompanied by dramatic shift in transcriptome and epigenome, transitioning Th17 cells into a Treg-like state. Genetic and chemical perturbation of the polyamine pathway resulted in attenuation of tissue inflammation in an autoimmune disease model of central nervous system, with changes in T cell effector phenotype.

immunology↗