Biology subjects

Davis, R. L.

Publications and source records attributed to Davis, R. L..

17 recordsLinked to original sources

bioRxiv2026

Proximity labelling of D1-like dopamine receptors reveals distinct cellular environments and uncovers trafficking proteins that regulate DA mediated behaviors in Drosophila

The neurotransmitter dopamine (DA) is central to synaptic regulation that support diverse behavioral functions, including both learning and forgetting. This multi-functional role of DA is due to receptor specific signaling in specific subcellular environments that remain uncharacterized. Here we utilized proximity labelling proteomics in human cells to characterize the proximal environments of two Drosophila D1-like DA receptors (Dop1R1 and Dop1R2) in basal and DA activation environments. While DA drives both receptors to recruit Beta-Arrestin 2, Dop1R1 alone showed ligand driven recruitment of G-protein Receptor Kinase 2/3, proximity to clathrin mediated endocytosis, and WASH complex mediated endosomal trafficking. Additionally, we show evidence that Dop1R1 and Dop1R2 reside in distinct domains at the cell surface. In vivo disruption of Drosophila orthologs of Dop1R proximal proteins revealed three trafficking proteins, Sec24AB, Krz, and CG13887, that regulate R1-mediated learning, starvation induced attraction to odors, and DA-mediated cAMP responses in memory circuits. In addition to revealing DA receptor trafficking proteins that support learning, our comparative characterization of the cellular environments D1-like receptors offers insights into how DA differentially regulates diverse behavioral and synaptic functions. For TOC only O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=110 SRC="FIGDIR/small/728438v1_ufig1.gif" ALT="Figure 1"> View larger version (29K): org.highwire.dtl.DTLVardef@656e56org.highwire.dtl.DTLVardef@12f0084org.highwire.dtl.DTLVardef@cb05cdorg.highwire.dtl.DTLVardef@e9d623_HPS_FORMAT_FIGEXP M_FIG C_FIG

neuroscience↗

bioRxiv2026

Pharmacological rescue of mitochondrial dysfunction, neurite degeneration, and premature death of ALS and AD iPSC-derived neurons

Mitochondrial (MT) dysfunction is a key driver of ALS pathology. Without a healthy MT system, motor neurons (MN) function at sub-optimal levels and die. In addition, other effects of ALS, like axon/dendrite degeneration, may occur from a pathophysiological cascade spurred by MT dysfunction. A phenotypic screen identified Dipyridamole (DPM), an FDA-approved and safe drug, as having extraordinary effects on ALS patient induced pluripotent stem cell (iPSC)-derived MNs. The drug prevented MT fragmentation, loss of MT content, impaired MT bioenergetics, axon/dendrite degeneration, and premature MN death, extending neuronal survival by more than fivefold. Importantly, its efficacy extended across iPSC-derived neurons representing two different familial forms of ALS (C9orf72, TDP43) and Alzheimers disease (PSEN1), implying broad neuroprotection across ALS forms and other neurodegenerative diseases. DPM increased MT respiration and pyruvate uptake in a mechanism requiring the Mitochondrial Pyruvate Carrier (MPC), mechanistically explaining its biological activities. Thus, DPM is a promising drug to repurpose or refine for treating neurodegenerative diseases or other diseases that would benefit by augmenting pyruvate uptake into MT. TeaserDipyridamole, an FDA-approved drug, restores mitochondrial function and protects neurons in ALS and Alzheimers disease.

neuroscience↗

bioRxiv2025

Atypical developmental remodeling of dopamine neurons involves AKT-GSK3β signaling and glia-mediated axon degeneration

Neuronal remodeling is essential for sculpting neural circuits, and its disruption has been implicated in neurodevelopmental and neuropsychiatric disorders. Yet the molecular and cellular diversity of remodeling across neuron types remains incompletely understood. Here, we uncover a distinct remodeling mode in a subtype of Drosophila dopamine neurons (DANs) critical for learning, memory, sleep, and locomotion. Unlike the stereotypical pruning-then-regrowth paradigm, these DANs undergo a transient axon overgrowth followed by selective pruning during metamorphosis. Remarkably, DAN axon pruning proceeds independently of canonical ecdysone signaling and instead involves neuron-intrinsic AKT-GSK3{beta} signaling and extrinsic glial activity. Disruption of AKT-GSK3{beta} signaling alters microtubule stability and impairs glial recruitment and clearance of axonal debris. Notably, the role of AKT-GSK3{beta} is cell-type specific, underscoring mechanistic diversity in remodeling programs. These findings reveal an unexpected overgrowth-then-pruning developmental trajectory, establishing DANs as a powerful model to uncover the mechanisms underlying neuronal remodeling, circuit maturation, and neurodegeneration.

neuroscience↗

bioRxiv2025

Identity-by-descent captures Shared Environmental Factors at Biobank Scale

Genealogical ties leave traces beyond shared genetic material: relatives tend to share environmental exposures and cultural practices that persist across generations. Using genomic and electronic health record data from 13,143 individuals in the Biorepository for Integrative Genomics, we applied a hierarchical community detection algorithm to group individuals into four major communities and 17 subcommunities based on the proportion of their genome shared identical by descent (IBD). This approach captured a fine-scale demographic structure beyond traditional ancestry classifications. By integrating neighborhood-level geographic data with census-derived environmental metrics, we revealed unequal exposure to environmental stressors between subcommunities, which correlated with differential rates of health conditions, including elevated respiratory condition prevalence in subcommunities under greater pollution burden. Through an interventional mediation analysis we found that excess risk at the subcommunity-level substantially exceeded what measured environmental factors alone could explain. thus showing the contribution of unmeasured shared exposures that IBD-based grouping captures. Subcommunity-level disparities persisted in sensitivity analyses adjusting for self-reported race, indicating that IBD-based clustering captures health-relevant information beyond demographic categories commonly used as proxies for social determinants of health. We implemented an open-source dashboard for interactive exploration of IBD-defined communities, disease prevalence, and environmental exposures. Together, we demonstrate that IBD-based clustering jointly captures genetic and environmental determinants of health, offering a scalable framework for precision health and population genetics that translates biobank data into actionable insights.

genomics↗

bioRxiv2025

Picornaviridae and Caliciviridae diversity in Madagascar fruit bats is driven by cross-continental genetic exchange

Bats are reservoir hosts for numerous well-known zoonotic viruses, but their broader virus-hosting capacities remain understudied. Picornavirales are an order of enteric viruses known to cause disease across a wide range of mammalian hosts, including Hepatitis A in humans and foot-and-mouth disease in ungulates. Host-switching and recombination drive the diversification of Picornavirales worldwide. Divergent Caliciviridae and Picornaviridae (families within the Picornavirales) have been described in bats across mainland Africa, but surveillance for these viruses has been rare in the Southwest Indian Ocean Islands. Bats live in close proximity to and are consumed widely as a food source by humans in Madagascar, providing opportunities for zoonotic transmission. Prior work in Madagascar has described numerous evolutionarily divergent bat viruses, some with zoonotic potential. Using metagenomic Next Generation Sequencing of urine and fecal samples obtained from three species of endemic Malagasy fruit bats (Eidolon dupreanum, Pteropus rufus, and Rousettus madagascariensis), we recovered 13 full-length and 37 partial-length genomic sequences within the order Picornavirales (36 Picornaviridae and 14 Caliciviridae sequences), which we identify and describe here. We find evidence that genetic exchange between mainland African bat and Madagascar bat Picornavirales likely shaped the diversification patterns of these novel sequences through recombination events between closely related Picornavirales; thus far, high host fidelity appears to have limited these viruses from spilling over into other species.

evolutionary biology↗

bioRxiv2024

Mitochondrial Dynamics and Bioenergetics in iPSC-Derived Neurons with Familial Alzheimer's Disease Mutations

Mitochondrial (MT) dysfunction is a hallmark of Alzheimers Disease (AD), but the specific defects across forms of AD are unknown. We measured multiple parameters of MT dynamics and function, and neurite degeneration, in iPSC-derived human neurons possessing natural and engineered mutations in PS1, PS2, and APP genes. Mutations in all three genes altered MT function measured by basal, ATP-linked, and maximal oxygen consumption rate; and spare respiratory capacity, with PS1/PS2 alleles being more severe than APP mutations. Electron flow through Complexes I-IV was decreased in PS1/PS2 mutations but; in contrast, APP alleles had only modest impairments of CI and CII. We measured aspects of MT dynamics including fragmentation, and neurite degeneration, both of which were dramatic in PS1/PS2 alleles, but essentially absent in APP alleles. The marked differences in MT pathology may occur from the distinct ways APP is processed into A{beta} and may correlate with the disease severity.

neuroscience↗

bioRxiv2022

Control of cell proliferation by memories of mitosis

Mitotic duration is tightly constrained, with extended mitotic duration being a characteristic of potentially problematic cells prone to chromosome missegregation and genomic instability. We show that memories of mitotic duration are integrated by a p53-based mitotic stopwatch pathway to exert tight control over proliferation. The stopwatch halts proliferation of the products of a single significantly extended mitosis or of successive modestly extended mitoses. Time in mitosis is monitored via mitotic kinase-regulated assembly of stopwatch complexes that are transmitted to daughter cells. The stopwatch is inactivated in p53-mutant cancers, as well as in a significant proportion of p53-wildtype cancers, consistent with classification of stopwatch complex subunits as tumor suppressors. Stopwatch status additionally influences efficacy of anti-mitotic agents currently used or in development for cancer therapy. One-Sentence SummaryTime spent in mitosis is carefully monitored to halt the proliferation of potentially dangerous cells in a population.

cancer biology↗

bioRxiv2022

Convergent epitope specificities, V gene usage and public clones elicited by primary exposure to SARS-CoV-2 variants

An important consequence of infection with a SARS-CoV-2 variant is protective humoral immunity against other variants. The basis for such cross-protection at the molecular level is incompletely understood. Here we characterized the repertoire and epitope specificity of antibodies elicited by Beta, Gamma and ancestral variant infection and assessed their cross-reactivity to these and the more recent Delta and Omicron variants. We developed a high-throughput approach to obtain immunoglobulin sequences and produce monoclonal antibodies for functional assessment from single B cells. Infection with any variant elicited similar cross-binding antibody responses exhibiting a remarkably conserved hierarchy of epitope immunodominance. Furthermore, convergent V gene usage and similar public B cell clones were elicited regardless of infecting variant. These convergent responses despite antigenic variation may represent a general immunological principle that accounts for the continued efficacy of vaccines based on a single ancestral variant.

immunology↗

bioRxiv2022

Computational study of the furin cleavage domain of SARS-CoV-2: delta binds strongest of extant variants

We demonstrate that AlphaFold and AlphaFold Multimer, implemented within the ColabFold suite, can accurately predict the structures of the furin enzyme with known six residue inhibitory peptides. Noting the similarity of the peptide inhibitors to polybasic furin cleavage domain insertion region of the SARS-CoV-2, which begins at P681, we implement this approach to study the wild type furin cleavage domain for the virus and several mutants. We introduce mutations in silico for alpha, omicron, and delta variants, for several sequences which have been rarely observed, for sequences which have not yet been observed, for other coronaviruses (NL63, OC43, HUK1a, HUK1b, MERS, and 229E), and for the H5N1 flu. We show that interfacial hydrogen bonds between the furin cleavage domain and furin are a good measure of binding strength that correlate well with endpoint binding free energy estimates, and conclude that among all candidate viral sequences studied, delta is near the very top binding strength within statistical accuracy. However, the binding strength of several rare sequences match delta within statistical accuracy. We find that the furin S1 pocket is optimized for binding arginine as opposed to lysine. This residue, typically at sequence position five, contains the most hydrogen bonds to the furin, and hydrogen bond count for just this residue shows a strong positive correlation with the overall hydrogen bond count. We demonstrate that the root mean square backbone C-alpha fluctuation of the first residue in the furin cleavage domain has a strong negative correlation with the interfacial hydrogen bond count. We show by considering the variation with the number of basic residues that the maximum mean number of interfacial hydrogen bonds expected is 15.7 at 4 basic residues.

biophysics↗

bioRxiv2021

Simulation of the omicron variant of SARS-CoV-2 shows broad antibody escape, weakened ACE2 binding, and modest increase in furin binding

The recent emergence of the omicron variant of the SARS-CoV-2 virus with large numbers of mutations has raised concern about a potential new surge in infections. Here we use molecular dynamics to study the biophysics of the interface of the omicron spike protein binding to (i) the ACE2 receptor protein, (ii) antibodies from all known binding regions, and (iii) the furin binding domain. Our simulations suggest that while there is significant reduction of antibody binding strength corresponding to escape, the omicron spike pays a cost in terms of weaker receptor binding. The furin cleavage domain is the same or weaker binding than the alpha variant, suggesting less viral load and disease intensity than the extant delta variant.

biophysics↗

bioRxiv2021

Protection against SARS-CoV-2 Beta Variant in mRNA-1273 Boosted Nonhuman Primates

Neutralizing antibody responses gradually wane after vaccination with mRNA-1273 against several variants of concern (VOC), and additional boost vaccinations may be required to sustain immunity and protection. Here, we evaluated the immune responses in nonhuman primates that received 100 {micro}g of mRNA-1273 vaccine at 0 and 4 weeks and were boosted at week 29 with mRNA-1273 (homologous) or mRNA-1273.{beta} (heterologous), which encompasses the spike sequence of the B.1.351 (beta or {beta}) variant. Reciprocal ID50 pseudovirus neutralizing antibody geometric mean titers (GMT) against live SARS-CoV-2 D614G and the {beta} variant, were 4700 and 765, respectively, at week 6, the peak of primary response, and 644 and 553, respectively, at a 5-month post-vaccination memory time point. Two weeks following homologous or heterologous boost {beta}-specific reciprocal ID50 GMT were 5000 and 3000, respectively. At week 38, animals were challenged in the upper and lower airway with the {beta} variant. Two days post-challenge, viral replication was low to undetectable in both BAL and nasal swabs in most of the boosted animals. These data show that boosting with the homologous mRNA-1273 vaccine six months after primary immunization provides up to a 20-fold increase in neutralizing antibody responses across all VOC, which may be required to sustain high-level protection against severe disease, especially for at-risk populations. One-sentence summarymRNA-1273 boosted nonhuman primates have increased immune responses and are protected against SARS-CoV-2 beta infection.

immunology↗

bioRxiv2021

Associative learning drives longitudinally-graded presynaptic plasticity of neurotransmitter release along axonal compartments

Anatomical and physiological compartmentalization of neurons is a mechanism to increase the computational capacity of a circuit, and a major question is what role axonal compartmentalization plays. Axonal compartmentalization may enable localized, presynaptic plasticity to alter neuronal output in a flexible, experience-dependent manner. Here we show that olfactory learning generates compartmentalized, bidirectional plasticity of acetylcholine release that varies across the longitudinal compartments of Drosophila mushroom body (MB) axons. The directionality of the learning-induced plasticity depends on the valence of the learning event (aversive vs. appetitive), varies linearly across proximal to distal compartments following appetitive conditioning, and correlates with learning-induced changes in downstream mushroom body output neurons (MBONs) that modulate behavioral action selection. Potentiation of acetylcholine release was dependent on the CaV2.1 calcium channel subunit cacophony. In addition, contrast between the positive conditioned stimulus and other odors required the inositol triphosphate receptor (IP3R), which was required to maintain responsivity to odors in untrained conditions. Downstream from the mushroom body, a set of MBONs that receive their input from the {gamma}3 MB compartment were required for normal appetitive learning, suggesting that they represent a key node through which discriminative effects influence appetitive memory and decision-making. These data demonstrate that learning drives valence-correlated, compartmentalized, bidirectional potentiation and depression of synaptic neurotransmitter release, which rely on distinct mechanisms and are distributed across axonal compartments in a learning circuit.

neuroscience↗

bioRxiv2021

Vaccination with SARS-CoV-2 Spike Protein and AS03 Adjuvant Induces Rapid Anamnestic Antibodies in the Lung and Protects Against Virus Challenge in Nonhuman Primates

Adjuvanted soluble protein vaccines have been used extensively in humans for protection against various viral infections based on their robust induction of antibody responses. Here, soluble prefusion-stabilized spike trimers (preS dTM) from the severe acute respiratory syndrome coronavirus (SARS-CoV-2) were formulated with the adjuvant AS03 and administered twice to nonhuman primates (NHP). Binding and functional neutralization assays and systems serology revealed that NHP developed AS03-dependent multi-functional humoral responses that targeted multiple spike domains and bound to a variety of antibody FC receptors mediating effector functions in vitro. Pseudovirus and live virus neutralizing IC50 titers were on average greater than 1000 and significantly higher than a panel of human convalescent sera. NHP were challenged intranasally and intratracheally with a high dose (3x106 PFU) of SARS-CoV-2 (USA-WA1/2020 isolate). Two days post-challenge, vaccinated NHP showed rapid control of viral replication in both the upper and lower airways. Notably, vaccinated NHP also had increased spike-specific IgG antibody responses in the lung as early as 2 days post challenge. Moreover, vaccine-induced IgG mediated protection from SARS-CoV-2 challenge following passive transfer to hamsters. These data show that antibodies induced by the AS03-adjuvanted preS dTM vaccine are sufficient to mediate protection against SARS-CoV-2 and support the evaluation of this vaccine in human clinical trials.

immunology↗

bioRxiv2019

mity: A highly sensitive mitochondrial variant analysis pipeline for whole genome sequencing data

MotivationMitochondrial diseases (MDs) are the most common group of inherited metabolic disorders and are often challenging to diagnose due to extensive genotype-phenotype heterogeneity. MDs are caused by mutations in the nuclear or mitochondrial genome, where pathogenic mitochondrial variants are usually heteroplasmic and typically at much lower allelic fraction in the blood than affected tissues. Both genomes can now be readily analysed using unbiased whole genome sequencing (WGS), but most nuclear variant detection methods fail to detect low heteroplasmy variants in the mitochondrial genome. ResultsWe present mity, a bioinformatics pipeline for detecting and interpreting heteroplasmic SNVs and INDELs in the mitochondrial genome using WGS data. In 2,980 healthy controls, we observed on average 3,166x coverage in the mitochondrial genome using WGS from blood. mity utilises this high depth to detect pathogenic mitochondrial variants, even at low heteroplasmy. mity enables easy interpretation of mitochondrial variants and can be incorporated into existing diagnostic WGS pipelines. This could simplify the diagnostic pathway, avoid invasive tissue biopsies and increase the diagnostic rate for MDs and other conditions caused by impaired mitochondrial function. Availabilitymity is available from https://github.com/KCCG/mityunder an MIT license. Contactclare.puttick@crick.ac.uk, carolyn.sue@sydney.edu.au, MCowley@ccia.org.au

bioinformatics↗

bioRxiv2019

Machine learning predicts early-onset acute organ failure in critically ill patients with sickle cell disease

BackgroundSickle cell disease (SCD) is a genetic disorder of the red blood cells, resulting in multiple acute and chronic complications including pain episodes, stroke, and kidney disease. Patients with SCD develop chronic organ dysfunction, which may progress to organ failure during disease exacerbations. Early detection of acute physiological deterioration leading to organ failure is not always attainable. Machine learning techniques that allow for prediction of organ failure may enable earlier identification and treatment, and potentially reduce mortality. We tested the hypothesis that machine learning physiomarkers could predict the development of organ dysfunction in an adult sample of patients with SCD admitted to intensive care units.\n\nMethods and FindingsWe studied 63 sequential SCD patients with 163 patient encounters, mean age 33.0{+/-}11.0 years, admitted to intensive care units, some of whom (6.7%) had pre-existing cardiovascular or kidney disease. A subset of these patient encounters (37; 23%) met sequential organ failure assessment (SOFA) criteria. The site of organ failure included: central nervous system (32), cardiovascular (11), renal (10), liver (7), respiratory (5) and coagulation (2) systems. Most (81.5%) of the patient encounters who experienced organ failure had single organ failure. The other 126 SCD patient encounters served as controls. A set of signal processing features (such as fast fourier transform, energy, continuous wavelet transform, etc.) derived from heart rate, blood pressure, and respiratory rate were identified to distinguish patients with SCD who developed acute physiological deterioration leading to organ failure, from SCD patients who did not meet the criteria. A random forest model accurately predicted organ failure up to six hours prior to onset, with a five-fold cross-validation accuracy of 94.57% (average sensitivity and specificity of 90.24% and 98.9% respectively).\n\nConclusionsThis study demonstrates the viability of using machine learning to predict acute physiological deterioration heralded organ failure among hospitalized adults with SCD. The discovery of salient physiomarkers through machine learning techniques has the potential to further accelerate the development and implementation of innovative care delivery protocols and strategies for medically vulnerable patients.

bioinformatics↗

bioRxiv2018

Physiomarkers in Real-Time Physiological Data Streams Predict Adult Sepsis Onset Earlier Than Clinical Practice

Rationale: Sepsis is a life-threatening condition with high mortality rates and expensive treatment costs. To improve short- and long-term outcomes, it is critical to detect at-risk sepsis patients at an early stage.\n\nObjective: Our primary goal was to develop machine learning models capable of predicting sepsis using streaming physiological data in real-time.\n\nMethods: A dataset consisting of high-frequency physiological data from 1,161 critically ill patients admitted to the intensive care unit (ICU) was analyzed in this IRB-approved retrospective observational cohort study. Of that total, 634 patients were identified to have developed sepsis. In this paper, we define sepsis as meeting the Systemic Inflammatory Response Syndrome (SIRS) criteria in the presence of the suspicion of infection. In addition to the physiological data, we include white blood cell count (WBC) to develop a model that can signal the future occurrence of sepsis. A random forest classifier was trained to discriminate between sepsis and non-sepsis patients using a total of 108 features extracted from 2-hour moving time-windows. The models were trained on 80% of the patients and were tested on the remaining 20% of the patients, for two observational periods of lengths 3 and 6 hours.\n\nResults: The models, respectively, resulted in F1 scores of 75% and 69% half-hour before sepsis onset and 79% and 76% ten minutes before sepsis onset. On average, the models were able to predict sepsis 210 minutes (3.5 hours) before the onset.\n\nConclusions: The use of robust machine learning algorithms, continuous streams of physiological data, and WBC, allows for early identification of at-risk patients in real-time with high accuracy.

bioinformatics↗

bioRxiv2018

Drosophila mef2 is essential for normal mushroom body and wing development.

MEF2 (myocyte enhancer factor 2) transcription factors are found in the brain and muscle of insects and vertebrates and are essential for the differentiation of multiple cell types. We show that in the fruitfly Drosophila, MEF2 is essential for normal development of wing veins, and for mushroom body formation in the brain. In embryos mutant for D-mef2, there was a striking reduction in the number of mushroom body neurons and their axon bundles were not detectable. D-MEF2 expression coincided with the formation of embryonic mushroom bodies and, in larvae, expression onset was confirmed to be in post-mitotic neurons. With a D-mef2 point mutation that disrupts nuclear localization, we find that D-MEF2 is restricted to a subset of Kenyon cells that project to the /{beta}, and {gamma} axonal lobes of the mushroom bodies, but not to those forming the /{beta} lobes. Our findings that ancestral mef2 is specifically important in dopamine-receptive neurons has broad implications for its function in mammalian neurocircuits.

developmental biology↗