Biology subjects

Davenport, E.

Publications and source records attributed to Davenport, E..

8 recordsLinked to original sources

bioRxiv2025

A phenotypic screen identified KEAP1-kelch domain blockade as a mechanism to restore cardiac function in the setting of chronic severe hemodynamic stress

A bespoke gene expression (GE) based small molecule screen in human induced pluripotent stem cell derived cardiomyocytes (iPSC-CM) was conducted with the aim of identifying drug targets and pathways with the potential to reverse heart failure (HF) pathologic GE and the resultant decompensated HF phenotype. The screen utilized a composite human-murine HF gene expression signature, a target annotated compound set, and a HF gene expression reversal scoring algorithm to identify small molecules and their associated targets as potential modulators of HF pathologic GE. Following hit triage, a lead optimization program, and compound characterization in preclinical rodent models of HF and human iPSC-CM contractility assays, KEAP1 kelch domain blockers were identified as potent efficacious agents in the restoration of contractile function in the setting of oxidant stress and pressure overload induced cardiac dysfunction.

molecular biology↗

bioRxiv2024

Variant-to-function dissection of rare non-coding GWAS loci with high impact on blood traits

Understanding the function of genetic variants associated with human traits and diseases remains a significant challenge. Here we combined analyses based on natural genetic variation and genetic engineering to dissect the function of 94 non-coding variants associated with haematological traits. We describe 22 genetic variants impacting haematological variation through gene expression. Further, through in-depth functional analysis, we illustrate how a rare, non-coding variant near the CUX1 transcription factor impacts megakaryopoiesis through modulation of the CUX1 transcriptional cascade. Collectively, our findings enhance the functional interpretation of genetic association studies and advance understanding of how non-coding variants contribute to blood and immune system variation.

genetics↗

bioRxiv2022

Surface SV2A-Syt1 nanoclusters act as a sequestration hub that limits dynamin-1 recruitment and targeting to recycling synaptic vesicles

Following exocytosis, the recapture of plasma membrane-stranded vesicular proteins into recycling synaptic vesicles (SVs) is essential for sustaining neurotransmission. Surface clustering of vesicular proteins has been postulated as a pre-assembly mechanism for endocytosis - ensuring high-fidelity retrieval. Here, we used single-molecule imaging to examine the nanoclustering of synaptotagmin-1 (Syt1) and synaptic vesicle protein 2A (SV2A) in hippocampal neurons. Syt1 forms surface nanoclusters through interaction of its C2B domain with SV2A, that are sensitive to mutations in this domain (Syt1K326A/K328A) and knocking down SV2A. SV2A co-cluster with Syt1 and blocking SV2As cognate interaction with Syt1 (SV2AT84A) also decreased SV2A clustering. Surprisingly, impairing SV2A-Syt1 nanoclustering enhanced plasma membrane recruitment of key endocytic protein dynamin-1, leading to accelerated Syt1 endocytosis, altered intracellular sorting and decreased trafficking of Syt1 to Rab5-positive endocytic compartments. SV2A-Syt1 surface nanoclusters therefore negatively regulate the rate of their own re-entry into recycling SVs by controlling the recruitment of the endocytic machinery.

neuroscience↗

bioRxiv2022

The Microbiome and Volatile Organic Compounds Reflect the State of Decomposition in an Indoor Environment

Because of the variety of factors that can affect the decomposition process, it can be difficult to determine the post-mortem interval (PMI). The process is highly dependent on microbial activity, and volatile organic compounds (VOCs) are a by-product of this activity. Given both have been proposed to assist in PMI determination, a deeper understanding of this relationship is needed. The current study investigates the temporal evolution of the microbiome and VOC profile of a decomposing human analog (swine) in a controlled, indoor environment. Microbial communities and VOCs were sampled at six-time points, up to the active decay phase. Sampling locations included the abdominal area, anus, right ear canal, and right nostril. Bacterial communities were found to significantly change during decomposition (p-value < 0.001), and communities evolved differently based on sampling location. The families Moraxellaceae, Planococcaceae, Lactobacillaceae, and Staphylococcaceae drove these community shifts. From random forest analysis, the nostril sampling location was determined to be the best location to predict stage of decomposition. Individual VOCs exhibited large temporal shifts through decomposition stage in contrast to smaller shifts when evaluated based on functional groups. Finally, pairwise linear regression models between abdominal area bacteria and selected VOCs were assessed; Planococcaceae and Tissierellaceae were significantly correlated to indole. Overall, this study provides an exploratory analysis to support the connection between the microbiome, VOCs, and their relationship throughout decomposition. ImportanceThis research provides valuable insight into the complex process of decomposition, which is pertinent to forensic death investigations. The temporal evolution of both the microbiome and volatile organic compounds (VOCs) were characterized as a function of stage of decomposition and evaluated their interdependency upon one another. In turn, this information may assist in determining time since death, and fill a knowledge gap about VOC-bacteria associations during the decay process.

microbiology↗

bioRxiv2021

SV2A-Syt1 interaction controls surface nanoclustering and access to recycling synaptic vesicles

Following exocytosis, the recapture of vesicular proteins stranded at the plasma membrane in recycling synaptic vesicles (SVs) is essential to sustain neurotransmission. Nanoclustering is emerging as a mechanism through which proteins may be pre-assembled prior to endocytosis, to ensure high fidelity of retrieval for subsequent rounds of vesicle fusion. Here, we used single molecule imaging to examine the nanoclustering of synaptotagmin-1 (Syt1) and synaptic vesicle protein 2A (SV2A). Syt1 forms surface nanoclusters through interaction of its C2B domain (K326/K328) with SV2A, as demonstrated by mutating Syt1 (K326A/K328A) and knocking down endogenous SV2A. Blocking cognate interaction with Syt1 (SV2AT84A) also decreased SV2A clustering. Impaired nanoclustering of Syt1 and SV2A leads to accelerated endocytosis of Syt1, altered intracellular sorting and decreased trafficking of Syt1 to a Rab5-positive endocytic pathway. We conclude that the interaction between SV2A and Syt1 locks both molecules into surface nanoclusters, controlling their entry into recycling SVs.

neuroscience↗

bioRxiv2020

Leveraging phenotypic variability to identify genetic interactions in human phenotypes

While thousands of loci have been associated with human phenotypes, the role of gene-environment (GxE) interactions in determining individual risk of human diseases remains unclear. This is partly due to the severe erosion of statistical power resulting from the massive number of statistical tests required to detect such interactions. Here, we focus on improving the power of GxE tests by developing a statistical framework for assessing quantitative trait loci (QTLs) associated with the trait means and/or trait variances. When applying this framework to body mass index (BMI), we find that GxE discovery and replication rates are significantly higher when prioritizing genetic variants associated with the variance of the phenotype (vQTLs) compared to assessing all genetic variants. Moreover, we find that vQTLs are enriched for associations with other non-BMI phenotypes having strong environmental influences, such as diabetes or ulcerative colitis. We show that GxE effects first identified in quantitative traits such as BMI can be used for GxE discovery in disease phenotypes such as diabetes. A clear conclusion is that strong GxE interactions mediate the genetic contribution to body weight and diabetes risk.

genetics↗

bioRxiv2019

BrainNET: Inference of brain network topology using Machine Learning

ObjectiveTo develop a new fMRI network inference method, BrainNET, that utilizes an efficient machine learning algorithm to quantify contributions of various regions of interests (ROIs) in the brain to a specific ROI. MethodsBrainNET is based on Extremely Randomized Trees (ERT) to estimate network topology from fMRI data and modified to generate an adjacency matrix representing brain network topology, without reliance on arbitrary thresholds. Open source simulated fMRI data of fifty subjects in twenty-eight different simulations under various confounding conditions with known ground truth was used to validate the method. Performance was compared with correlation and partial correlation (PC). The real-world performance was then evaluated in a publicly available Attention-deficit/hyperactivity disorder (ADHD) dataset including 134 Typically Developing Children (mean age: 12.03, males: 83), 75 ADHD Inattentive (mean age: 11.46, males: 56) and 93 ADHD Combined (mean age: 11.86, males: 77) subjects. Network topologies in ADHD were inferred using BrainNET, correlation, and PC. Graph metrics were extracted to determine differences between the ADHD groups. ResultsBrainNET demonstrated excellent performance across all simulations and varying confounders in identifying true presence of connections. In the ADHD dataset, BrainNET was able to identify significant changes (p< 0.05) in graph metrics between groups. No significant changes in graph metrics between ADHD groups was identified using correlation and PC.

bioengineering↗

bioRxiv2017

Neutrophil adhesion in brain capillaries contributes to cortical blood flow decreases and impaired memory function in a mouse model of Alzheimer’s disease

The existence of cerebral blood flow (CBF) reductions in Alzheimers disease (AD) patients and related mouse models has been known for decades, but the underlying mechanisms and the resulting impacts on cognitive function and AD pathogenesis remain poorly understood. In the APP/PS1 mouse model of AD we found that an increased number of cortical capillaries had stalled blood flow as compared to wildtype animals, largely due to leukocytes that adhered in capillary segments and blocked blood flow. These capillary stalls were an early feature of disease development, appearing before amyloid deposits. Administration of antibodies against the neutrophil marker Ly6G reduced the number of stalled capillaries, leading to an immediate increase in CBF and to rapidly improved performance in spatial and working memory tasks. Our work has thus identified a cellular mechanism that explains the majority of the CBF reduction seen in a mouse model of AD and has also demonstrated that improving CBF rapidly improved short-term memory function. Restoring cerebral perfusion by preventing the leukocyte adhesion that plugs capillaries may provide a novel strategy for improving cognition in AD patients.

neuroscience↗