Biology subjects

Armstrong, D.

Publications and source records attributed to Armstrong, D..

12 recordsLinked to original sources

bioRxiv2026

Small intestine microbiota development prevents early-life adiposity via IL-22-mediated intestinal PPARα suppression

Perturbation to the early-life microbiota has long-term detrimental effects on health and development, leading to increased risk for metabolic dysfunction and childhood obesity. Despite the central role of the small intestine (SI) in energy balance, the impact of SI microbiota establishment on the regulation of host metabolism and early-life adiposity remains unclear. Here, we report that disruption of a critical SI microbiota-intestinal epithelial cell circuit, specifically during a critical early-life period, drives long-lasting obesity. We demonstrate that the SI microbiota expands in abundance and diversity significantly between 2 and 3 weeks of life, and that segmented filamentous bacteria (SFB) and Lactobacillus intestinalis establish residence. Disruption of the early-life SI microbiota with antibiotics leads to enhanced lipid uptake and adiposity, driven by increased peroxisome proliferator-activated receptor alpha (PPAR) expression and activity in SI epithelial cells (IECs). We demonstrate that SFB and L. intestinalis are key regulators of PPAR in SI IECs by increasing intestinal IL-22 levels specifically during weaning, which is necessary for inhibition of antibiotic-induced adiposity in a PPAR-dependent manner. Together, this work provides mechanistic insights into beneficial microbiota-induced epithelial-immune crosstalk in the SI that is specific to early life, a critical protective mechanism against excessive adiposity in infancy, and offers insight into how antibiotics during infancy may increase the risk of childhood obesity. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=123 SRC="FIGDIR/small/731695v1_ufig1.gif" ALT="Figure 1"> View larger version (29K): org.highwire.dtl.DTLVardef@1b32f07org.highwire.dtl.DTLVardef@d4a5a6org.highwire.dtl.DTLVardef@c76d1borg.highwire.dtl.DTLVardef@cc479d_HPS_FORMAT_FIGEXP M_FIG C_FIG

microbiology↗

bioRxiv2025

Wnt5a-mediated Adipo-Cardiac Interorgan Communication in HFpEF

BackgroundObesity is an important risk factor in heart failure with preserved ejection fraction (HFpEF), but the precise mechanisms that drive obesity-associated cardiac remodeling are not well understood. Our previous work has shown that increased expression of the natriuretic peptide clearance receptor (Nprc) may drive cardiac remodeling in response to high fat diet. In this study, we hypothesized that Nprc plays a central role in preventing and reversing experimental HFpEF. MethodsNprc knockout mice were generated to induce global, cardiomyocyte-specific, or adipocyte-specific disruption of the Nprc (Npr3) gene. HFpEF was induced by the 2-hit stress of L-NAME and high fat diet. Outcomes measured included echocardiography, exercise endurance, invasive catheterization, and histologic assessment. Differential gene expression in adipocyte Nprc knockout visceral adipose tissue was investigated via bulk RNA sequencing and validated by RT-qPCR and culture of H9C2 cells with or without Wnt5a treatment. Adipocyte-mediated Wnt ligand release was interrupted in vivo via LGK974 injection in mice subjected to HFpEF conditions. ResultsGlobal inducible Nprc knockout prevented and reversed structural, hemodynamic, echocardiographic, and exercise tolerance features of HFpEF. This effect was found to be driven by adipocyte-specific, not cardiomyocyte-specific Nprc expression. Bulk RNA sequencing of adipocyte-specific Nprc knockout in peri-gonadal visceral adipose tissue identified downregulation of several secretory pathways, including Wnt pathways. Wnt5a was identified as one of the most downregulated genes by RNA sequencing and specifically validated by qPCR. Wnt5a exposure increased cardiomyocyte hypertrophy in vitro, and LGK974 (PORCN inhibitor) treatment in vivo decreased circulating Wnt5a levels and improved cardiac remodeling in HFpEF. ConclusionsOur study identifies a novel crosstalk mechanism between cardiomyocytes and adipocytes in obesity-associated HFpEF driven by natriuretic peptide-mediated inhibition of release of Wnt5a from adipocytes.

molecular biology↗

bioRxiv2024

A quantitative framework for structural interpretation of DMS reactivity

Dimethyl sulfate (DMS) chemical mapping probes RNA structure, where low reactivity is generally interpreted as Watson-Crick (WC) base pairs and high reactivity as unpaired nucleotides. Studies examining DMS reactivity of RNAs with known 3D structures have identified nucleotides that deviate from this interpretation with distinct solvent accessibility and hydrogen bonding patterns. Understanding the frequency of these outliers and their recurring structural 3D features remains incomplete. To address this knowledge gap, we systematically analyzed DMS reactivity patterns across a library of 7,500 RNA constructs containing two-way junctions with known 3D structures. We observe DMS reactivity exists on a continuum over four orders of magnitude with approximately 10% overlap in reactivity between WC and non-WC nucleotides. We find that non-WC bases with WC-like DMS protection exhibit increased hydrogen bonding and decreased solvent accessibility, whereas WC pairs exhibiting greater DMS reactivity tend to flank junctions, correlating with weaker base stacking and greater junction dynamics. Furthermore, we discover that DMS reactivity values in non-canonical pairs correlate with atomic distances and base pair geometry, enabling discrimination between different 3D conformations. These DMS reactivity patterns indicate that DMS reactivity provides atomic-scale information about RNA 3D conformations, which can be used to model RNA structures and dynamics.

biochemistry↗

bioRxiv2024

MAGE-A4-Responsive Plasma Cells Promote Non-Small Cell Lung Cancer

Adaptive immunity is critical to eliminate malignant cells, while multiple tumor-intrinsic factors can alter this protective function. Melanoma antigen-A4 (MAGE-A4), a cancer-testis antigen, is expressed in several solid tumors and correlates with poor survival in non-small cell lung cancer (NSCLC), but its role in altering antitumor immunity remains unclear. We found that expression of MAGE-A4 was highly associated with the loss of PTEN, a tumor suppressor, in human NSCLC. Here we show that constitutive expression of human MAGE-A4 combined with the loss of Pten in mouse airway epithelial cells results in metastatic adenocarcinoma enriched in CD138+ CXCR4+ plasma cells, predominantly expressing IgA. Consistently, human NSCLC expressing MAGE-A4 showed increased CD138+ IgA+ plasma cell density surrounding tumors. The abrogation of MAGE-A4-responsive plasma cells (MARPs) decreased tumor burden, increased T cell infiltration and activation, and reduced CD163+CD206+ macrophages in mouse lungs. These findings suggest MAGE-A4 promotes NSCLC tumorigenesis, in part, through the recruitment and retention of IgA+ MARPs in the lungs.

immunology↗

bioRxiv2024

Human-in-the-loop approach to identify functionally important residues of proteins from literature

We present a novel system that leverages curators in the loop to develop a dataset and model for detecting residue-level functional annotations and other protein structure features from standard publication text. Our approach involves the integration of data from multiple resources, including PDBe, EuropePMC, PubMedCentral, and PubMed, combined with annotation guidelines from UniProt, while employing LitSuggest and Huggingface models as tools in the annotation process. A team of seven annotators manually curated ten articles for named entities, which we utilized to train a starting PubmedBert model from Huggingface. Using a human-in-the-loop annotation system, we developed the best model with commendable performance metrics of 0.90 for precision, 0.92 for recall, and 0.91 for F1-measure. Our proposed system showcases a successful synergy of machine learning techniques and human expertise in curating a dataset for residue-level functional annotations and protein structure features. The results demonstrate the potential for broader applications in protein research, bridging the gap between advanced machine learning models and the indispensable insights of domain experts.

bioinformatics↗

bioRxiv2024

Evolution Under Thermal Stress Affects Escherichia colis Resistance to Antibiotics

Exposure to both antibiotics and temperature changes can induce similar physiological responses in bacteria. Thus, changes in growth temperature may affect antibiotic resistance. Previous studies have found that evolution under antibiotic stress causes shifts in the optimal growth temperature of bacteria. However, little is known about how evolution under thermal stress affects antibiotic resistance. We examined 100+ heat-evolved strains of Escherichia coli that evolved under thermal stress. We asked whether evolution under thermal stress affects optimal growth temperature, if there are any correlations between evolving in high temperatures and antibiotic resistance, and if these strains antibiotic efficacy changes depending on the local environments temperature. We found that: (1) surprisingly, most of the heat-evolved strains displayed a decrease in optimal growth temperature and overall growth relative to the ancestor strain, (2) there were complex patterns of changes in antibiotic resistance when comparing the heat-evolved strains to the ancestor strain, and (3) there were few significant correlations among changes in antibiotic resistance, optimal growth temperature, and overall growth. ImportanceEscherichia coli, a bacteria species often found within the intestinal tract of warm-blooded organisms, can be harmful to humans. Like all species of bacteria, E. coli can evolve, particularly in the presence of stressful conditions such as extreme temperatures or antibiotic treatments. Recent evidence suggests that when encountering one source of stress, an organisms ability to deal with a different source of stress is also affected. With global climate change and the continued evolution of antibiotic-resistant bacteria, the need to further investigate how temperature and antibiotics interact is clear. The significance of our research is in identifying possible correlations between temperature and antibiotic stress, broadening our understanding of how stressors affect organisms, and allowing for insights into possible future evolutionary pathways.

evolutionary biology↗

bioRxiv2023

Annotating Macromolecular Complexes in the Protein Data Bank: Improving the FAIRness of Structure Data

Macromolecular complexes are essential functional units in nearly all cellular processes, and their atomic-level understanding is critical for elucidating and modulating molecular mechanisms. The Protein Data Bank (PDB) serves as the global repository for experimentally determined structures of macromolecules. Structural data in the PDB offer valuable insights into the dynamics, conformation, and functional states of biological assemblies. However, the current annotation practices lack standardised naming conventions for assemblies in the PDB, complicating the identification of instances representing the same assembly. In this study, we introduce a method leveraging resources external to PDB, such as the Complex Portal, UniProt and Gene Ontology, to describe assemblies and contextualise them within their biological settings accurately. Employing the proposed approach, we assigned standard names and provided value-added annotations to over 90% of unique assemblies in the PDB. This standardisation of assembly data enhances the PDB, facilitating a deeper understanding of these cellular components. Furthermore, the data standardisation improves the PDBs FAIR attributes, fostering more effective basic and translational research and education across scientific disciplines.

bioinformatics↗

bioRxiv2020

Associations between childhood family emotional health, fronto-limbic grey matter volume, and saliva 5mC in young adulthood

BackgroundPoor family emotional health (FEH) during childhood is prevalent and impactful, and likely confers similar neurodevelopmental risks as other adverse social environments. Pointed FEH study efforts are underdeveloped, and the mechanisms by which poor FEH are biologically embedded are unclear. The current exploratory study examined whether variability in DNA methylation (DNAm) and fronto-limbic grey matter volume may represent pathways through which FEH may become biologically embedded. ResultsSelf-reported childhood FEH was nominally associated with right hemisphere hippocampus (b=10.4, p=0.005), left hemisphere amygdala (b=5.3, p=0.009), and right hemisphere amygdala (b=5.8, p=0.016) volumes. Childhood FEH was also nominally associated with 49 DNAm MEs (prange=3x10-6 to 0.047). After limiting analyses to probes correlated between saliva and brain, saliva-derived DNAm MEs partially mediated the association between FEH and right hippocampal volume (Burlywood ME indirect effect b=-111, p=0.014), and fully mediated the FEH and right amygdala volume relationship (Pink4 ME indirect effect b=-48, p=0.026). Modules were enriched with probes falling in genes with immune, CNS, and metabolic functions. ConclusionsFindings extend work highlighting neurodevelopmental variability associated with adverse social environment exposure during childhood by specifically implicating poor FEH, while informing a mechanism of biological embedding. FEH-associated epigenetic signatures could function as proxies of altered fronto-limbic grey matter volume associated with poor childhood FEH and inform further investigation into primarily affected tissues such as endocrine, immune, and CNS cell types.

genomics↗

bioRxiv2020

RANDOMIZE: A Web Server for Data Randomization

SummaryDNA methylation microarray data may suffer from batch effects due to improper handling of the samples during the plating process. RANDOMIZE is a web-based application designed to perform randomization of relevant metadata to evenly distribute samples across the factors typically responsible for batch effects in DNA methylation microarrays, such as row, chips and plates. Randomization helps to reduce the likelihood of bias and impact of difference among groups. AvailabilityThe tool is freely available online at https://coph-usf.shinyapps.io/RANDOMIZE/ and can be accessed using any web browser. Sample data and tutorial is also available with the tool. Contactahwani@usf.edu

bioinformatics↗

bioRxiv2019

Machine learning guided association of adverse drug reactions with in vitro target-based pharmacology

Adverse drug reactions (ADRs) are one of the leading causes of morbidity and mortality in health care. Understanding which drug targets are linked to ADRs can lead to the development of safer medicines. Here, we analyze in vitro secondary pharmacology of common (off) targets for 2134 marketed drugs. To associate these drugs with human ADRs, we utilized FDA Adverse Event Reports and developed random forest models that predict ADR occurrences from in vitro pharmacological profiles. By evaluating Gini importance scores of model features, we identify 221 target-ADR associations, which co-occur in PubMed abstracts to a greater extent than expected by chance. Among these are established relations, such as the association of in vitro hERG binding with cardiac arrhythmias, which further validate our machine learning approach. Evidence on bile acid metabolism supports our identification of associations between the Bile Salt Export Pump and renal, thyroid, lipid metabolism, respiratory tract and central nervous system disorders. Unexpectedly, our model suggests PDE3 is associated with 40 ADRs. These associations provide a comprehensive resource to support drug development and human biology studies.

pharmacology and toxicology↗

bioRxiv2019

Targeting pathogenic Lafora bodies in Lafora disease using an antibody-enzyme fusion

Lafora disease (LD) is a fatal childhood epilepsy and a non-classical glycogen storage disorder with no effective therapy or cure. LD is caused by recessive mutations in the EPM2A or EPM2B genes that encode the glycogen phosphatase laforin and an E3 ubiquitin ligase malin, respectively. A hallmark of LD is the intracellular accumulation of abnormal and insoluble -linked polysaccharide deposits known as Lafora bodies (LBs) in several tissues, including most regions of the brain. In mouse models of LD, genetic reduction of glycogen synthesis eliminates LB formation and rescues the neurological phenotype. Since multiple groups have confirmed that neurodegeneration and epilepsy result from LB accumulation, a major focus in the field has shifted toward the development of therapies that reduce glycogen synthesis or target LBs for degradation with the goal of treating LD. Herein, we identify the optimal enzymes for degrading LBs, and we develop a novel therapeutic agent by fusing human pancreatic -amylase to a cellpenetrating antibody fragment. This antibody-enzyme fusion (VAL-0417) degrades LBs in vitro, shows robust cellular uptake, and significantly reduces the LB load in vivo in Epm2a-/- mice. VAL-0417 is a promising therapeutic for the treatment of LD and a putative precision therapy for an intractable epilepsy. Antibody-enzyme fusions represent a new class of antibody-based drugs that could be utilized to treat glycogen storage disorders and other diseases.\n\nOne Sentence SummaryAn antibody-enzyme fusion delivering an amylase degrades the toxic polyglucosan bodies that cause Lafora disease, a fatal childhood epilepsy.

biochemistry↗

bioRxiv2019

Central Nervous System Delivery and Biodistribution Analysis of an Antibody-Enzyme Fusion for the Treatment of Lafora Disease

Lafora disease is a fatal juvenile epilepsy, characterized by the malignant accumulation of aberrant glucan inclusions called Lafora Bodies (LBs). Cerebral delivery of protein-based therapeutics for the clearance of Lafora Bodies remain a unique challenge in the field. Recently, a humanized antigen-binding fragment (hFab) derived from a murine systemic lupus erythematosus DNA autoantibody (3E10) has been shown to mediate cell penetration and been proposed as a broadly applicable carrier to mediate cellular targeting and uptake. We report studies on cerebral delivery of VAL-0417, an antibody-enzyme fusion composed of the 3E10 hFab and human pancreatic -amylase for the clearance of LBs in a mouse model of lafora disease. Herein, we report development of an enzyme-linked immunosorbant-based bioassay to detect VAL-0417 post treatment as a measure of delivery efficacy. We demonstrate the robust and sensitive detection of the fusion protein in multiple tissue types. Using our method, we measured biodistribution in different methods of delivery. We found intracerebroventricular administration provided the most robust delivery, while intrathecal administration only showed modest biodistribution. These data define critical steps in the translational pipeline of VAL-0417for the treatment of Lafora disease.

bioengineering↗