Biology subjects

Dwyer, B.

Publications and source records attributed to Dwyer, B..

5 recordsLinked to original sources

bioRxiv2024

Adult honey bee queens consume pollen and nectar

Despite the queens crucial reproductive role in honey bee colonies, queen diet and feeding behavior remain remarkably enigmatic, with most studies assuming they are solely fed nutritious glandular secretions (i.e., royal jelly) by workers. This colors our understanding of basic honey bee biology and how governmental agencies assess pesticide risk. We hypothesized that adult queens also consume honey and pollen. Through experiments with queenright laboratory microcolonies fed with marked diets, we demonstrate that queens are fed pollen and nectar by workers and can also feed directly. We then measured pollen content in mature, unmanipulated queens sacrificed from 43 conventional field colonies from two distinct geographical regions. Similar to workers, we found pollen in almost all queens guts, though at expectedly lower quantities than in young workers. These findings suggest queens have a more complex, dynamic diet than previously thought, raising new questions about how dietary habits and feeding behaviors influence pesticide risk and other aspects of queen biology.

ecology↗

bioRxiv2023

"Cortical Delta" In The Medulla Of Sleeping Infant Rats

In early development, active sleep is the predominant sleep state before it is supplanted by quiet sleep. In rats, the developmental increase in quiet sleep is accompanied by the sudden emergence of the cortical delta rhythm (0.5-4 Hz) around postnatal day 12 (P12). We sought to explain the emergence of cortical delta by assessing developmental changes in the activity of the parafacial zone (PZ), a medullary structure thought to regulate quiet sleep in adults. We recorded from PZ in P10 and P12 rats and predicted an age-related increase in neural activity during increasing periods of delta-rich cortical activity. Instead, during quiet sleep we discovered sleep-dependent rhythmic spiking activity--with intervening periods of total silence--phase-locked to a local delta rhythm. Moreover, PZ and cortical delta were coherent at P12, but not at P10. PZ delta was also phase-locked to respiration, suggesting sleep-dependent modulation of PZ activity by respiratory pacemakers in the ventral medulla. Disconnecting the main olfactory bulbs from the cortex did not diminish cortical delta, indicating that the influence of respiration on delta at this age is not mediated indirectly through nasal breathing. Finally, we observed an increase in parvalbumin-expressing terminals in PZ across these ages, supporting a role for GABAergic inhibition in PZs rhythmicity. The discovery of delta-rhythmic neural activity in the medulla--when cortical delta is also emerging--opens a new path to understanding the brainstems role in regulating sleep and synchronizing rhythmic activity throughout the brain.

neuroscience↗

bioRxiv2023

Borrowing Transcriptional Kinases to Activate Apoptosis

Protein kinases are disease drivers whose therapeutic targeting traditionally centers on inhibition of enzymatic activity. Here chemically induced proximity is leveraged to convert kinase inhibitors into context-specific activators of therapeutic genes. Bivalent molecules that link ligands of the transcription factor B-cell lymphoma 6 (BCL6) to ATP-competitive inhibitors of cyclin-dependent kinases (CDKs) were developed to re-localize CDK to BCL6-bound loci on chromatin and direct phosphorylation of RNA Pol II. The resulting BCL6-target proapoptotic gene expression translated into killing of diffuse large B-cell lymphoma (DLBCL) cells at 72 h with EC50s of 0.9 - 10 nM and highly specific ablation of the BCL6-regulated germinal center response in mice. The molecules exhibited 10,000-fold lower cytotoxicity in normal lymphocytes and are well tolerated in mice. Genomic and proteomic evidence corroborated a gain-of-function mechanism where, instead of global enzyme inhibition, a fraction of total kinase activity is borrowed and re-localized to BCL6-bound loci. The strategy demonstrates how kinase inhibitors can be used to context-specifically activate transcription, accessing new therapeutic space.

cancer biology↗

bioRxiv2023

Development of LIBRA-seq for the Guinea Pig Model System as a Tool for the Evaluation of Antibody Responses to Multivalent HIV-1 Vaccines

Consistent elicitation of serum antibody responses that neutralize diverse clades of HIV-1 remains a primary goal of HIV-1 vaccine research. Prior work has defined key features of soluble HIV-1 Envelope (Env) immunogen cocktails that influence the neutralization breadth and potency of multivalent vaccine-elicited antibody responses including the number of Env strains in the regimen. We designed immunization groups that consisted of different numbers of Env strains to be used in a cocktail immunization strategy: the smallest cocktail (group 2) consisted of a set of two Env strains, which were a subset of the three Env strains that made up group 3, which in turn were a subset of the six Env strains that made up group 4. Serum neutralizing titers were broadest in guinea pigs that were immunized with a cocktail of three Envs compared to cocktails of two and six, suggesting that multivalent Env immunization provides a benefit but may be detrimental when the cocktail size is too large. We then adapted the LIBRA-seq platform for antibody discovery to be compatible with guinea pigs, and isolated several tier 2 neutralizing monoclonal antibodies. Three antibodies isolated from two separate guinea pigs were similar in their gene usage and CDR3s, establishing evidence for a guinea pig public clonotype elicited through vaccination. Taken together, this work investigated multivalent HIV-1 Env immunization strategies and provides a novel methodology for screening guinea pig B cell receptor antigen specificity at a high throughput level using LIBRA-seq. IMPORTANCEMultivalent vaccination with soluble Env immunogens is at the forefront of HIV-1 vaccination strategies, but little is known about the influence of the number of Env strains included in vaccine cocktails. Our results suggest that adding more strains is sometimes beneficial but may be detrimental when the number of strains is too high. Additionally, we adapted the LIBRA-seq platform to be compatible with guinea pig samples and isolated several tier 2 neutralizing monoclonal antibodies, some of which share V and J gene usage and >80% CDR3 identity, thus establishing the existence of public clonotypes in guinea pigs elicited through vaccination.

immunology↗

bioRxiv2019

Development and validation of a deep learning framework for Alzheimers disease classification

Alzheimers disease (AD) is the primary cause of dementia worldwide (1), with an increasing morbidity burden that may outstrip diagnosis and management capacity as the population ages. Current methods integrate patient history, neuropsychological testing and magnetic resonance imaging (MRI) to identify likely cases, yet effective practices remain variably-applied and lacking in sensitivity and specificity (2). Here we report an explainable deep learning strategy that delineates unique AD signatures from multimodal inputs of MRI, age, gender, and mini-mental state examination (MMSE) score. Our framework linked a fully convolutional network (FCN) to a multilayer perceptron (MLP) to construct high resolution maps of disease probability from local brain structure. This enabled precise, intuitive visualization of individual AD risk en route to accurate diagnosis. The model was trained using clinically-diagnosed AD and cognitively normal (NC) subjects from the Alzheimers Disease Neuroimaging Initiative (ADNI) dataset (n=417) (3), and validated on three independent cohorts: the Australian Imaging, Biomarker & Lifestyle Flagship Study of Ageing (AIBL, n=382) (4), the Framingham Heart Study (FHS, n=102) (5), and the National Alzheimers Coordinating Center (NACC, n=582) (6). Model performance was consistent across datasets, with mean accuracy values of 0.966, 0.948, 0.815, and 0.916 for ADNI, AIBL, FHS and NACC, respectively. Moreover, our approach exceeded the diagnostic performance of a multi-institutional team of practicing neurologists (n=11), and high-risk cerebral regions predicted by the model closely tracked postmortem histopathological findings. This framework provides a clinically-adaptable strategy for using routinely available imaging techniques such as MRI to generate nuanced neuroimaging signatures for AD diagnosis, as well as a generalizable approach for linking deep learning to pathophysiological processes in human disease.

neuroscience↗