Biology subjects

Powell, S. M.

Publications and source records attributed to Powell, S. M..

5 recordsLinked to original sources

bioRxiv2025

Discovery of non-opioid receptor protein targets of fentanyl across tissues from animal models and humans using photoaffinity probes

Synthetic opioids such as fentanyl and related analogs have been widely used for pain management. However, their negative side effects, including respiratory depression and high potential for addiction, underscore the need for a deeper understanding of fentanyls interactions with proteins throughout the human body. Fentanyl analogs bind and activate opioid receptors in the central and peripheral nervous systems, triggering numerous downstream signaling pathways. Increasingly, fentanyl has been shown to interact with non-opioid receptors, and elucidation of these non-canonical fentanyl-protein interactions may provide insights into the mechanisms contributing to fentanyls adverse effects and illuminate novel countermeasure strategies. To identify proteins in mammalian tissues that may interact with fentanyl, we designed and synthesized three affinity-based probes (AfBPs) that include the fentanyl core and feature a diazirine photoaffinity group and alkyne handle for click chemistry at different positions. Molecular docking simulations predicted that these AfBPs bind the mu opioid receptor similarly to fentanyl. Affinity-based protein profiling using the FA-T1 probe in vitro in tissues from six animal species identified histamine N-methyltransferase (HNMT), endophilin-B1 (SH3GLB1), fructosamine-3-kinase (FN3K), cutA divalent cation tolerance analog (CUTA), and monoamine oxidase B (MAOB) among the top proteins that bind fentanyl in multiple species and tissue types. Molecular docking of fentanyl and remifentanil with these protein structures identified putative binding sites. The interaction of fentanyl with specific proteins was empirically assessed through protein structural analyses. These findings highlight potential fentanyl-protein interactions that may contribute to the acute and long-term impacts of fentanyl exposures.

pharmacology and toxicology↗

bioRxiv2024

A fast and sensitive size-exclusion chromatography method for plasma extracellular vesicle proteomic analysis

Extracellular vesicles (EVs) carry diverse biomolecules derived from their parental cells, making their components excellent biomarker candidates. However, purifying EVs is a major hurdle in biomarker discovery since current methods require large amounts of samples, are time-consuming and typically have poor reproducibility. Here we describe a simple, fast, and sensitive EV fractionation method using size exclusion chromatography (SEC) on a fast protein liquid chromatography (FPLC) system. Our method uses a Superose 6 Increase 5/150, which has a bed volume of 2.9 mL. The FPLC system and small column size enable reproducible separation of only 50 {micro}L of human plasma in 15 minutes. To demonstrate the utility of our method, we used longitudinal samples from a group of individuals that underwent intense exercise. A total of 838 proteins were identified, of which, 261 were previously characterized as EV proteins, including classical markers, such as cluster of differentiation (CD)9 and CD81. Quantitative analysis showed low technical variability with correlation coefficients greater than 0.9 between replicates. The analysis captured differences in relevant EV-proteins involved in response to physical activity. Our method enables fast and sensitive fractionation of plasma EVs with low variability, which will facilitate biomarker studies in large clinical cohorts.

biochemistry↗

bioRxiv2022

Detection of YAP1 and AR-V7 mRNA for Prostate Cancer prognosis using an ISFET Lab-On-Chip platform

Prostate cancer (PCa) is the second most common cause of male cancer-related death worldwide. The gold standard of treatment for advanced PCa is androgen deprivation therapy (ADT). However, eventual failure of ADT is common and leads to lethal metastatic castration resistant PCa (mCRPC). As such, the detection of relevant biomarkers in the blood for drug resistance in mCRPC patients could lead to personalized treatment options. mRNA detection is often limited by the low specificity of qPCR assays which are restricted to specialised laboratories. Here, we present a novel reversetranscription loop-mediated isothermal amplification (RT-LAMP) assay and have demonstrated its capability for sensitive detection of AR-V7 and YAP1 RNA (3x101 RNA copies per reaction). This work presents a foundation for the detection of circulating mRNA in PCa on a non-invasive Lab-on-chip (LoC) device for use at point-of-care. This technique was implemented onto a Lab-on-Chip platform integrating an array of chemical sensors (ion-sensitive field-effect transistors - ISFETs) for real-time detection of RNA. Detection of RNA presence was achieved through the translation of chemical signals into electrical readouts. Validation of this technique was conducted with rapid detection (<15 min) of extracted RNA from prostate cancer cell lines 22Rv1s and DU145s.

bioengineering↗

bioRxiv2021

AutoMicroED: A semi-automated MicroED processing pipeline

Despite rapid adaptation of micro-electron diffraction (MicroED) for protein and small molecule structure determination to sub-angstrom resolution, the lack of automation tools for easy MicroED data processing remains a challenge for expanding to the broader scientific community. In particular, automation tools, which are novice user friendly, compatible with heterogenous datasets and can be run in unison with data collection to judge the quality of incoming data (similar to cryosparc LIVE for single particle cryoEM) do not exist. Here, we present AutoMicroED, a cohesive and semi-automatic MicroED data processing pipeline that runs through image conversion, indexing, integration and scaling of data, followed by merging of successful datasets that are pushed through phasing and final structure determination. AutoMicroED is compatible with both small molecule and protein datasets and creates a straightforward and reproducible method to solve single structures from pure samples, or multiple structures from mixed populations. The immediate feedback on data quality, data completeness and more parameters, aids users to identify whether they have collected enough data for their needs. Overall, AutoMicroED permits efficient structure elucidation for both novice and experienced users with comparable results to more laborious manual processing.

biophysics↗

bioRxiv2019

In vivo imaging defines vascular interplay in the development of lymphocytic leukemia in zebrafish models

The vascular microenvironment at the primary tumor site is represented by functionally diverse types of vessels that contribute to metabolic supply, trafficking/dissemination of tumor cells, and delivery of chemotherapeutics. However, the role of leukemia-associated vascular networks in leukemia progression remains poorly understood. We utilized a MYC-induced T cell leukemia model in zebrafish to assess the involvement of vascular endothelial growth factor A-dependent (VEGFR2+), VEGFA-independent vasculature (VEGFR2-), and lymphatics in the initial stages of leukemia cell dissemination using intravital microscopy. Leukemogenesis underwent sequential progression, from initial successive emigration of single leukemic cells from the thymus towards the kidney marrow, followed by collective migration in a dorsal-lateral direction with scattered migration from the ventral thymus towards the aortic arches, before streaming towards the rostral kidney area. Trafficking appeared independent of VEGFR2+ vasculature but was closely associated with VEGFR2-microvessels, and, interestingly, leukemic cells did not utilize lymphatics during initial dissemination. Overall, leukemic cells appeared to utilize the same routes as normal T cell progenitors during development but in a reverse order, and primarily recruited VEGFR2-microvessels during the initial stages of progression. Ultimately, interfering with leukemia cell migration by targeting vascular networks may represent a new therapeutic strategy to control leukemia progression.

cancer biology↗