Biology subjects

Barnett, D.

Publications and source records attributed to Barnett, D..

7 recordsLinked to original sources

bioRxiv2024

Mitochondrial complex III-derived ROS amplify immunometabolic changes in astrocytes and promote dementia pathology

Neurodegenerative disorders alter mitochondrial functions, including the production of reactive oxygen species (ROS). Mitochondrial complex III (CIII) generates ROS implicated in redox signaling, but its triggers, targets, and disease relevance are not clear. Using site-selective suppressors and genetic manipulations together with mitochondrial ROS imaging and multiomic profiling, we found that CIII is the dominant source of ROS production in astrocytes exposed to neuropathology-related stimuli. Astrocytic CIII-ROS production was dependent on nuclear factor-{kappa}B (NF-{kappa}B) and the mitochondrial sodium-calcium exchanger (NCLX) and caused oxidation of select cysteines within immune and metabolism-associated proteins linked to neurological disease. CIII-ROS amplified metabolomic and pathology-associated transcriptional changes in astrocytes, with STAT3 activity as a major mediator, and facilitated neuronal toxicity in a non-cell- autonomous manner. As proof-of-concept, suppression of CIII-ROS in mice decreased dementia-linked tauopathy and neuroimmune cascades and extended lifespan. Our findings establish CIII-ROS as an important immunometabolic signal transducer and tractable therapeutic target in neurodegenerative disease.

neuroscience↗

bioRxiv2023

PP1β opposes classic PP1 function, inhibiting spine maturation and promoting LTP

Protein phosphatase 1 (PP1) regulates synaptic plasticity and has been described as a molecular constraint on learning and memory. There are three neuronal isoforms, PP1, PP1{beta}, and PP1{gamma}, but little is known about their individual functions. PP1 and PP1{gamma} are assumed to mediate the effects of PP1 on learning and memory based on their enrichment at dendritic spines and their preferential binding to neurabin and spinophilin, major PP1 synaptic scaffolding proteins. However, it was recently discovered that human de novo PP1{beta} mutations cause intellectual disability, suggesting an important but ill-defined role for PP1{beta}. In this study, we investigated the functions of each PP1 isoform in hippocampal synaptic physiology using conditional CA1-specific knockout mice. In stark contrast to classic PP1 function, we found that PP1{beta} promotes synaptic plasticity as well as spatial memory. These changes in synaptic plasticity and memory are accompanied by changes in GluA1 phosphorylation, GluN2A levels, and dendritic spine density and morphology, including silent synapse number. These functions of PP1{beta} reveal a previously unidentified signaling pathway regulating spine maturation and plasticity, broadening our understanding of the complex role of PP1 in synaptic physiology.

neuroscience↗

bioRxiv2022

Astrocytes regulate spatial memory in a sex-specific manner

Cognitive processes and neurocognitive disorders are regulated by astrocytes and have prominent sex differences. However, the contribution of astrocytes to sex differences is not known. We leveraged astrocyte-targeted gene editing and chemogenetics in adult mice to reveal that astrocytic glutamate receptors and other G protein-coupled receptors (GPCRs) modulate hippocampus-dependent cognitive function in a sexually dimorphic manner. In females, spatial memory was improved by increasing metabotropic glutamate receptor 3 (mGluR3) in astrocytes or stimulating astrocytic Gi/o-coupled signaling, whereas stimulating Gs-coupled signaling impaired memory. However, in males, memory was improved by reducing mGluR3 or stimulating Gs-coupled signaling, whereas stimulating Gi/o-coupled signaling impaired memory. Thus, memory requires a sex-specific balance of astrocytic Gs-coupled and Gi/o-coupled receptor activities, and disease-associated alterations or therapeutic targeting of these pathways may cause opposing sex-dependent effects on cognitive function. SummaryGlia cause sex-specific changes in cognition

neuroscience↗

bioRxiv2021

Cysteine induces mitochondrial reductive stress in glioblastoma through hydrogen peroxide production

Glucose and amino acid metabolism are critical for glioblastoma (GBM) growth, but little is known about the specific metabolic alterations in GBM that are targetable with FDA-approved compounds. To investigate tumor metabolism signatures unique to GBM, we interrogated The Cancer Genome Atlas for alterations in glucose and amino acid signatures in GBM relative to other human cancers and found that GBM exhibits the highest levels of cysteine and methionine pathway gene expression of 32 human cancers. Treatment of patient-derived GBM cells with the FDA-approved cysteine compound N-acetylcysteine (NAC) reduce GBM cell growth and mitochondrial oxygen consumption, which was worsened by glucose starvation. Mechanistic experiments revealed that cysteine compounds induce rapid mitochondrial H2O2 production and reductive stress in GBM cells, an effect blocked by oxidized glutathione, thioredoxin, and redox enzyme overexpression. These findings indicate that GBM is uniquely susceptible to NAC-driven reductive stress and could synergize with glucose-lowering treatments for GBM.

cancer biology↗

bioRxiv2021

Early low-level developmental arsenic exposure impacts mouse hippocampal synapticfunction

BackgroundArsenic is a well-established carcinogen known to increase all-cause mortality, but its effects on the central nervous system are less well understood. Recent epidemiological studies suggest that early life exposure to arsenic is associated with learning deficits and behavioral changes, and increased arsenic exposure continues to affect an estimated 200 million individuals worldwide. Previous studies on arsenic exposure and synaptic function have demonstrated a decrease in synaptic transmission and long-term potentiation in adult rodents, but have relied on in vitro or extended exposure in adulthood. Therefore, little is known about the effect of arsenic exposure in development. ObjectiveHere, we studied the effects of gestational and early developmental arsenic exposure in juvenile mice. Specifically, our objective was to investigate the impact of arsenic exposure on synaptic transmission and plasticity in the hippocampus. MethodsC57BL/6 females were exposed to arsenic (0, 50ppb, 36ppm) in their drinking water two weeks prior to mating and continued to be exposed to arsenic throughout gestation and after parturition. We then performed field recordings in acute hippocampal slices from the juvenile offspring prior to weaning (P17-P23). In this paradigm, the juvenile mice are only exposed to arsenic in utero and via the mothers milk. ResultsHigh (36ppm) and relatively low (50ppb) arsenic exposure both lead to decreased basal synaptic transmission in the hippocampus of juvenile mice. There was a mild decrease in paired-pulse facilitation in juvenile mice exposed to high, but not low, arsenic, suggesting the alterations in synaptic transmission are primarily post-synaptic. Finally, high developmental arsenic exposure led to a significant increase in long-term potentiation. DiscussionThese results suggest that indirect, ecologically-relevant arsenic exposure in early development impacts hippocampal synaptic transmission and plasticity that could underlie learning deficits reported in epidemiological studies.

neuroscience↗

bioRxiv2020

Detection of Chemotherapy-Resistant Pancreatic Cancer Using a Glycan Biomarker

Background and AimsA subset of pancreatic ductal adenocarcinomas (PDACs) is highly resistant to systemic chemotherapy, but no markers are available in clinical settings to identify this subset. We hypothesized that chemotherapy-resistant PDACs express a glycan biomarker called sTRA. Methods. We tested this marker to identify treatment-resistant PDAC in multiple systems: sets of cell lines, organoids, and isogenic cell lines; primary tumors; and blood plasma from cohorts of human subjects. Results. Among a panel of 27 cell lines, high levels of cell-surface sTRA identified higher resistance to seven chemotherapeutics used against PDAC. Using primary tumors from two different cohorts, patients who were positive for a gene-expression classifier for sTRA received no statistically significant benefit from adjuvant chemotherapy, in contrast to those negative for the signature. In another cohort, using direct measurements of sTRA in tissue microarrays by quantitative immunofluorescence, patients who were high in sTRA again had no statistically significant benefit from adjuvant chemotherapy. Further, a blood-plasma test for the sTRA glycan identified the PDACs that showed rapid relapse following neoadjuvant chemotherapy. This blood test performed with 96% specificity and 56% sensitivity in a blinded cohort using samples collected before the start of treatment. Conclusion. These findings establish that tissue or plasma sTRA can identify PDACs that are resistant to neoadjuvant or adjuvant chemotherapy. This capability could help apply systemic treatments more precisely and facilitate biomarker-guided trials targeting resistant PDAC.

cancer biology↗

bioRxiv2018

Using digital epidemiology methods to monitor influenza-like illness in the Netherlands in real-time: the 2017-2018 season

IntroductionDespite the early development of Google Flu Trends in 2009, digital epidemiology methods have not been adopted widely, with most research focusing on the USA. In this article we demonstrate the prediction of real-time trends in influenza-like illness (ILI) in the Netherlands using search engine query data.\n\nMethodsWe used flu-related search query data from Google Trends in combination with traditional surveillance data from 40 general sentinel practices to build our predictive models. We introduced an artificial 4-week delay in the use of GP data in the models, in order to test the predictive performance of the search engine data.\n\nSimulating the weekly use of a prediction model across the 2017/2018 flu season we used lasso regression to fit 52 prediction models (one for each week) for weekly ILI incidence. We used rolling forecast cross-validation for lambda optimization in each model, minimizing the maximum absolute error.\n\nResultsThe models accurately predicted the number of ILI cases during the 2017/18 ILI epidemic in real time with a mean absolute error of 1.40 (per 10,000 population) and a maximum absolute error of 6.36. The model would also have identified the onset, peak, and end of the epidemic with reasonable accuracy\n\nThe number of predictors that were retained in the prediction models was small, ranging from 3 to 5, with a single keyword ( Griep = Flu) having by far the most weight in all models.\n\nDiscussionThis study demonstrates the feasibility of accurate real-time ILI incidence predictions in the Netherlands using internet search query data. Digital ILI monitoring strategies may be useful in countries with poor surveillance systems, or for monitoring emergent diseases, including influenza pandemics. We hope that this transparent and accessible case study inspires and supports further developments in field of digital epidemiology in Europe and beyond.

epidemiology↗