Biology subjects

Neal, C.

Publications and source records attributed to Neal, C..

6 recordsLinked to original sources

bioRxiv2026

MOSAIC: a longitudinal phenotypic clock to dissect organismal aging trajectories in C. elegans

Interventions that extend lifespan do not necessarily preserve healthspan, the portion of life spent in good health. This disconnect has intensified interest in biological aging clocks as quantitative proxies of organismal health. However, most existing clocks rely on invasive or endpoint measurements, providing static estimates that capture biological age at a single time point and offer limited insight into aging trajectories - the dynamic patterns through which physiological resilience and functional capacity change within individuals over time. Here we combine standardized, high-frequency imaging of individual Caenorhabditis elegans across the lifespan with machine learning to develop MOSAIC (Modular Organismal Signature of Aging In C. elegans), a non-invasive phenotypic clock that estimates biological age longitudinally at single-organism resolution. Leveraging [~]3750 animals, [~]230000 observations and 29 phenotypic features, MOSAIC predicts biological age with high accuracy and resolves organism-wide aging trajectories at high temporal resolution. Beyond age prediction, MOSAIC decomposes biological age into contributions from distinct physiological modules, enabling mechanistic interpretation of organismal decline. Applying MOSAIC to natural lifespan variation, dietary restriction, longevity mutants and pharmacological interventions reveals that lifespan extension can emerge through distinct, time-dependent phenotypic trajectories rather than a uniform slowing of aging. Interventions with similar effects on longevity produce divergent biological-age trajectories and distinct combinations of younger and older traits, highlighting context-dependent physiological trade-offs. MOSAIC provides a scalable, non-invasive framework to repeatedly quantify biological age across the lifespan and to compare interventions based on how they reshape aging trajectories.

bioinformatics↗

bioRxiv2022

Rapid expansion and visual specialization of learning and memory centers in Heliconiini butterflies

How do neural systems evolve to support new behaviors? Changes in the abundance and diversity of neural cell types, and their connectivity, shape brain composition and provide the substrate for behavioral variation. We describe a striking example of neural elaboration in an ecologically diverse tribe of Heliconiini butterflies. By building extensive new datasets of neural traits across the tribe, we identify major bursts in the size and cellular composition of the mushroom bodies, central brain structures essential for learning and memory. These expansion events are associated with increased innervation form visual centers and coincide with enhanced performance in multiple cognitive assays. This suite of neural and cognitive changes is likely tied to the emergence of derived foraging behaviors, facilitated by localized specialization of neural networks. One-Sentence SummaryMajor shifts in brain composition and behavior in butterflies with unique foraging and dietary behaviors.

evolutionary biology↗

bioRxiv2021

AttentionSiteDTI: Attention Based Model for Predicting Drug-Target Interaction Using 3D Structure of Protein Binding Sites

In this study, we introduce and implement an interpretable graph-based deep learning prediction model, which utilizes protein binding sites along with self-attention to learn which protein binding sites interact with a given ligand. Our proposed model enables interpretability by identifying the protein binding sites that contribute the most towards the Drug-Target Interaction. Results on three benchmark datasets show improved performance compared to previous graph-based models. More significantly, unlike previous studies our model performance remains close to the optimal performance when tested with new proteins (ie., high generalizablity). Through multidisciplinary collaboration, we further experimentally evaluate the practical potential of our proposed approach. To achieve this, we first computationally predict binding interaction of some candidate compounds with a target protein, then experimentally validate the binding interactions for these pairs in the laboratory. The high agreement between the computationally-predicted and experimentally-observed (measured) DTIs illustrates the potential of our method as an effective pre-screening tool in drug re-purposing applications.

bioinformatics↗

bioRxiv2021

Interleukin-33 regulates metabolic reprogramming of the retinal pigment epithelium in response to immune stressors.

It remains unresolved how retinal pigment epithelial (RPE) cell metabolism is regulated following immune activation to maintain retinal homeostasis and retinal function. We exposed RPE to several stress signals, particularly toll-like receptor stimulation, and uncovered an ability of RPE to adapt their metabolic preference on aerobic glycolysis or oxidative glucose metabolism in response to different immune stimuli. We have identified interleukin-33 (IL-33) as a key metabolic checkpoint that antagonises the Warburg effect to ensure the functional stability of the RPE. The identification of IL-33 as a key regulator of mitochondrial metabolism suggests roles for the cytokine that go beyond its extracellular "alarmin" activities. IL-33 exerts control over mitochondrial respiration in RPE by facilitating oxidative pyruvate catabolism. We have also revealed that in the absence of IL-33, mitochondrial function declines and resultant bioenergetic switching is aligned with altered mitochondrial morphology. Our data not only sheds new light in the molecular pathway of activation of mitochondrial respiration in RPE in response to immune stressors, but also uncovers a novel role of nuclear intrinsic IL-33 as a metabolic checkpoint regulator.

immunology↗

bioRxiv2021

Maintenance of Complex I and respiratory super-complexes by NDUF-11 is essential for respiratory function, mitochondrial structure and health in C. elegans

Mitochondrial super-complexes form around a conserved core of monomeric complex I and dimeric complex III; wherein subunit NDUFA11, of the former, is conspicuously situated at the interface. We identified B0491.5 (NDUF-11) as the C. elegans homologue, of which animals homozygous for a CRISPR-Cas9 generated knockout allele arrested at the L2 development stage. Reducing expression by RNAi allowed development to the adult stage, enabling characterisation of the consequences: destabilisation of complex I and its super-complexes, and perturbation of respiratory function. The loss of NADH-dehydrogenase activity is compensated by enhanced complex II activity, resulting in excessive detrimental ROS production. Meanwhile, electron cryo-tomography highlight aberrant cristae morphology and widening of the inter-membrane space and cristae junctions. The requirement of NDUF-11 for balanced respiration, mitochondrial morphology and development highlights the importance of complex I/ super-complex maintenance. Their perturbation by this, or other means, is likely to be the cause of metabolic stress and disease.

molecular biology↗

bioRxiv2017

Components Of Alcohol Use And All-Cause Mortality

ImportanceCurrent recommendations for low-risk drinking are based on drinking quantity: up to one drink daily for women and two drinks daily for men. Drinking frequency has not been independently examined for its contribution to mortality.\n\nObjectiveTo evaluate the impact of drinking frequency on all-cause mortality after adjusting for drinks per day and binge drinking behavior.\n\nDesignTwo independent observational studies with self-reported alcohol use and subsequent all-cause mortality: the National Health Interview Survey (NHIS), and data from Veterans Health Administration clinics (VA).\n\nSettingEpidemiological sample (NHIS) and VA outpatient database (VA Corporate Data Warehouse).\n\nParticipants208,661 individuals from the NHIS interviewed between 1997 and 2009 at the age of 30 to 70 with mortality follow-up in the last quarter of 2011; 75,515 VA outpatients born between 1948 and 1968 who completed an alcohol survey in 2008 with mortality follow-up in June 2016.\n\nExposuresQuantity of alcohol use when not binging (1-2 drinks on typical day, 3-4 drinks on typical day), frequency of non-binge drinking (never, weekly or less, 2-3 times weekly, 4 or more times weekly), and frequency of binge drinking (never, less than weekly, 1-3 times weekly, 4 or more times weekly). Covariates included age, sex, race, and comorbidity.\n\nMain Outcomes and MeasuresAll-cause mortality.\n\nResultsAfter adjusting for binge drinking behavior, survival analysis showed an increased risk for all-cause mortality among people who typically drink 1-2 drinks four or more times weekly, relative to people who typically drink 1-2 drinks at a time weekly or less (NHIS dataset HR=1.15, 95% CI 1.06-1.26; VA dataset HR=1.31, 95% CI 1.15-1.49).\n\nConclusions and RelevanceDrinking four or more times weekly increased risk of all-cause mortality, even among those who drank only 1 or 2 drinks daily. This was seen in both a large epidemiological database and a large hospital-based database, suggesting that the results can be generalized.

epidemiology↗