Biology subjects

Dennis, N.

Publications and source records attributed to Dennis, N..

6 recordsLinked to original sources

bioRxiv2026

A defined microbial community remodels host metabolism and pathogen resistance in Caenorhabditis elegans

The microbiome is an important regulator of metabolism and health, yet the mechanisms by which microbial communities influence host physiological state remain incompletely understood. Here we used a defined host-microbiota model consisting of Caenorhabditis elegans and an 11-member bacterial consortium representative of its natural microbiota (DefNatMta). We investigated how this native microbial community influences host metabolism and physiology relative to the standard laboratory diet, E. coli OP50. Transcriptomic analyses revealed remodelling of host pathways associated with lipid metabolism, immunity and xenobiotic detoxification. Comparison with fasting-responsive transcriptional programmes showed that the DefNatMta response is distinct from fasting or caloric restriction. DefNatMta enhanced resistance to Staphylococcus aureus infection, and this protective effect was consistent with roles for the conserved host defence regulators PMK-1/p38 MAPK and HLH-30/TFEB. Additionally, DefNatMta reduced lipid accumulation, modified expression of lipid metabolism genes, and altered fatty acid composition, including enrichment of monomethyl branched-chain fatty acids and polyunsaturated fatty acids. Together, these findings demonstrate that a defined microbial community can induce transcriptional, metabolic and physiological remodelling in the host. Our results are consistent with microbial communities shaping host metabolic state and immune competence.

physiology↗

bioRxiv2026

Neural correlates of successful relational memory in younger and older adults: An activation likelihood estimation meta-analysis

Relational memory, the ability to encode and retrieve associations among multiple elements of an experience, is a core component of episodic memory that shows disproportionate age-related decline. Despite a substantial neuroimaging literature examining relational memory in aging, findings remain heterogeneous, and no quantitative synthesis has been conducted. The present study addressed this gap using Activation Likelihood Estimation (ALE) meta-analyses to characterize the neural correlates of relational memory success during encoding and retrieval in younger and older adults. Separate within-age-group, conjunction, and subtraction analyses were conducted, along with an exploratory analysis examining a general relational memory network across 70 independent studies. During encoding, younger adults showed robust convergence across medial temporal and prefrontal regions, whereas older adults showed more limited convergence. Shared convergence across age groups was observed in the left hippocampus and right inferior temporal gyrus, and direct age-group contrasts revealed greater prefrontal convergence in younger relative to older adults. During retrieval, younger adults showed convergence in posterior default mode and subcortical regions, whereas older adults showed convergence in the left angular gyrus, with no shared convergence observed across age groups. Across all studies, the hippocampus showed the most robust bilateral convergence across age groups and memory phases, underscoring its critical role in relational binding. Together, these findings provide the first quantitative characterization of the neural correlates of relational memory success in aging and highlight stable hippocampal involvement alongside age-related variability in prefrontal and posterior retrieval-related recruitment.

neuroscience↗

bioRxiv2025

A novel C. elegans respirometry assay using low-cost optical oxygen sensors

Measurement of the oxygen consumption rate (OCR), or respirometry, is a powerful and comprehensive method for assessing mitochondrial function both in vitro and in vivo. Respirometry at the whole-organism level has been repeatedly performed in the model organism Caenorhabditis elegans, typically using high throughput microplate-based systems over traditional Clark-type respirometers. However, these systems are highly specialised, costly to purchase and operate, and inaccessible to many researchers. Here, we develop a respirometry assay using low-cost commercially available optical oxygen sensors (PreSens OxoPlates(R)) and fluorescence plate readers (the BMG FLUOstar), as an alternative to more costly standard respirometry systems. This assay uses standard BMG FLUOstar protocols and a set of custom scripts to perform repeated measurements of the C. elegans OCR, with the optional use of respiratory inhibitors or other interventions. We validate this assay by demonstrating the linearity of basal OCRs in samples with highly variable numbers of animals, and by examining the impact of respiratory inhibitors with previously demonstrated efficacy in C. elegans: carbonyl cyanide 4-(trifluoromethoxy) phenylhydrazone (a mitochondrial uncoupler) and sodium azide (a Complex IV inhibitor). Using this assay, we demonstrate that the sequential use of FCCP and sodium azide leads to an increase in the sodium azide-treated (non-mitochondrial) OCR, indicating that the sequential use of respiratory inhibitors, as standard in intact cell respirometry, may produce erroneous estimates of non-mitochondrial respiration in C. elegans and thus should be avoided.

cell biology↗

bioRxiv2025

Distinct druggable biological processes in early-onset prostate cancer

Despite advances in understanding and treating Prostate Cancer (PCa), there has been little effort to systematically map the biology distinguishing Early-(EOPCa) and Late-(LOPCa) onset PCa. Around 25% of EOPCa cases present with metastatic spread or aggressive disease with earlier metastatic development. Some available lines of therapy are extending treatment trajectories and prolonging lives. However, there remains a critical clinical need to identify new therapeutic targets for EOPCa where life expectancy necessitates safer, more targeted treatment options. To our knowledge, here we present the largest systematic analysis of molecular profiles in EOPCa versus LOPCa, employing machine-learning-enabled algorithms to identify distinguishing biology and druggable targets for each age group. Distinct stromal signatures are uncovered in EOPCa, which are used to propose therapeutic opportunities herein. Moreover, our analysis identifies 50 druggable targets, 11 of which we confirm in PCa cell line genetic/pharmacological perturbation data. These findings provide the first specific, testable hypotheses in EOPCa, offering avenues for experimental validation and potential therapeutic exploitation, and, more generally, shed light on the intricate and distinguished molecular profile of this aggressive, poorly understood disease. One Sentence SummaryMachine learning-enabled algorithms were utilized to identify distinguishing biology and associated druggable targets for early-onset prostate cancers.

cancer biology↗

bioRxiv2024

A gut-microbiota-muscle axis that protects against age-related motor decline by regulating mitochondrial fission in C. elegans

Across diverse taxa, the composition of the microbiota is associated with lifelong host health. A mechanistic understanding of how microbial communities influence host physiology could lead to microbiota-based interventions for lifelong health. Here, we have developed a new host-microbiota model system utilising the model organism C. elegans combined with a defined natural microbiota (DefNatMta) consisting of 11 bacteria isolated from wild C. elegans, to study host-microbiota interactions in a more natural setting. We show that DefNatMta colonises the C. elegans gut, forming a stable and distinct gut microbiota. Using DefNatMta, we find a gut microbiota-muscle axis by which the microbiota affects age-related motility and muscular strength and protects against age-related decline in motor function. The gut microbiota-muscle axis acts by altering metabolism and mitochondrial network dynamics in muscle, and requires dynamin-related protein 1 DRP-1, a regulator of mitochondrial fission to protect against age-related motility decline. Our study demonstrates a gut microbiota-muscle axis and microbiota-mitochondria communication affecting age-related muscle function.

physiology↗

bioRxiv2020

Behavioral and brain signatures of substance use vulnerability in childhood

The prevalence of risky behavior such as substance use increases during adolescence; however, the neurobiological precursors to adolescent substance use remain unclear. Predictive modeling may complement previous work observing associations with known risk factors or substance use outcomes by developing generalizable models that predict early susceptibility. The aims of the current study were to identify and characterize behavioral and brain models of vulnerability to future substance use. Principal components analysis (PCA) of behavioral risk factors were used together with connectome-based predictive modeling (CPM) during rest and task-based functional imaging to generate predictive models in a large cohort of nine- and ten-year-olds enrolled in the Adolescent Brain & Cognitive Development (ABCD) study (NDA release 2.0.1). Dimensionality reduction (n=9,437) of behavioral measures associated with substance use identified two latent dimensions that explained the largest amount of variance: risk-seeking (PC1; e.g., curiosity to try substances) and familial factors (PC2; e.g., family history of substance use disorder). Using cross-validated regularized regression in a subset of data (Year 1 Fast Track data; n>1,500), functional connectivity during rest and task conditions (resting-state; monetary incentive delay task; stop signal task; emotional n-back task) significantly predicted individual differences in risk-seeking (PC1) in held-out participants (partial correlations between predicted and observed scores controlling for motion and number of frames [rp]: 0.07-0.21). By contrast, functional connectivity was a weak predictor of familial risk factors associated with substance use (PC2) (rp: 0.03-0.06). These results demonstrate a novel approach to understanding substance use vulnerability, which--together with mechanistic perspectives--may inform strategies aimed at early identification of risk for addiction.

neuroscience↗