Biology subjects

Hisey, C. L.

Publications and source records attributed to Hisey, C. L..

9 recordsLinked to original sources

bioRxiv2026

Engineering Carbon Nanotube Quantum Well Defects with Recognition Tripeptides for Optical Detection of Extracellular Vesicles in Plasma

Extracellular vesicles (EVs) carry molecular signatures of their originating cells and have thus emerged as promising biomarkers. However, their clinical utility remains limited due to their low abundance and the modest sensitivity of current EV detection methods in complex biological environments. Here, we present a quantum well defect functionalized carbon nanotube sensor coupled with integrin-recognition RGD tripeptide for EV detection in human plasma. Leveraging the abundance of integrins on EV surfaces, we targeted 5{beta}1, V{beta}1, and V{beta}3 subtypes. The nanosensor exhibited robust hypsochromic shifts in defect emission upon integrin binding, achieving sub-picomolar detection limits for integrin subunits and quantifying EVs at concentrations as low as 104 EVs{middle dot}mL-1 for glioblastoma, ovarian cancer, and fibroblast cell-derived EV types. Molecular dynamics simulation indicated that integrin docking at the RGD-coupled quantum defect can substantially reshape the interfacial environments of the quantum defects, explaining the high sensitivity in EV detection in complex biological media. Finally, transmembrane protein analysis validated the expression of surface integrins across the tested EV types. The modular nanosensor construct can be targeted to detect disease-associated EV subpopulations, advancing EV-based diagnostics.

biochemistry↗

bioRxiv2024

Placental extracellular vesicles from early-onset but not late-onset preeclampsia induce a pro-vasoconstrictive and anti-vasodilatory state in resistance arteries

BackgroundThe human placenta releases large numbers of extracellular vesicles (EVs) into the maternal circulation throughout pregnancy. In preeclampsia, a hypertensive disorder of pregnancy, the number of EVs increases and the cargo they carry is altered. We investigated whether human placental EVs from pregnancies complicated by preeclampsia directly alter maternal vascular function, a hallmark of the disorder, and if EVs from early-onset or late-onset variants of preeclampsia have different effects on the vasculature. MethodsMacro-EVs, micro-EVs and nano-EVs were isolated from cultured explants of human placentae from women with early-onset or late-onset preeclampsia, or from normotensive women. EVs were injected intravenously into pregnant mice and either at 30 minutes or 24 hours after injection, the mice were euthanized and the function of second order mesenteric arteries were assessed using wire myography. ResultsPlacental EVs from pregnancies with early-onset preeclampsia enhanced vasoconstriction to PE, AngII, and ET-1 whilst impairing vasodilation to ACh and SNP in a time-dependent fashion, most prominently at 24 hours. In contrast, placental EVs from pregnancies with late-onset preeclampsia induced few differences compared to arteries taken from control mice injected with EVs from women with normotensive pregnancies. ConclusionsTo the best of our knowledge, this is the first comparison of vascular function after exposure to the full range of EVs produced by placentae from women with early-onset and late-onset preeclampsia and normotensive women. Placental EVs from early-onset preeclampsia demonstrated the ability to contribute to the development of the high-resistance haemodynamic profiles of women affected by early-onset preeclampsia.

physiology↗

bioRxiv2024

Light-induced Extracellular Vesicle Adsorption

The role of extracellular vesicles (EVs) in human health and disease has garnered considerable attention over the past two decades. However, while several types of EVs are known to interact dynamically with the extracellular matrix and there is great potential value in producing high-fidelity EV micropatterns, there are currently no label-free, high-resolution, and tunable platform technologies with this capability. We introduce Light-induced Extracellular Vesicle Adsorption (LEVA) as a powerful solution to rapidly advance the study of matrix- and surface-bound EVs and other particles. The versatility of LEVA is demonstrated using commercial GFP-EV standards, EVs from glioblastoma bioreactors, and E. coli outer membrane vesicles (OMVs), with the resulting patterns used for single EV characterization, single cell migration on migrasome-mimetic trails, and OMV-mediated neutrophil swarming. LEVA will enable rapid advancements in the study of matrix- and surface-bound EVs and other particles, and should encourage researchers from many disciplines to create novel diagnostic, biomimetic, immunoengineering, and therapeutic screening assays.

bioengineering↗

bioRxiv2024

Limiting Brownian Motion to Enhance Immunogold Phenotyping and Superimpose Optical and Non-Optical Single-EP Analyses

Optical and non-optical techniques propelled the field of single extracellular particle (EP) research through phenotypic and morphological analyses, revealing the similarities, differences, and co-isolation of EP subpopulations. Overcoming the challenges of optical and non-optical techniques motivates the use of orthogonal techniques while analyzing extracellular particles (EPs), which require varying concentrations and preparations. Herein, we introduce the nano-positioning matrix (NPMx) technique capable of superimposing optical and non-optical modalities for a single-EP orthogonal analysis. The NPMx technique is realized by ultraviolet-mediated micropatterning to reduce the stochasticity of Brownian motion. While providing a systematic orthogonal measurement of a single EP via total internal reflection fluorescence microscopy and transmission electron microscopy, the NPMx technique is compatible with low-yield samples and can be utilized for non-biased electrostatic capture and enhanced positive immunogold sorting. The success of the NPMx technique thus provides a novel platform by marrying already trusted optical and non-optical techniques at a single-EP resolution.

bioengineering↗

bioRxiv2023

Manifold Learning Enables Interpretable Analysis of Raman Spectra from Extracellular Vesicle and Other Mixtures

Extracellular vesicles (EVs) have emerged as promising diagnostic and therapeutic candidates in many biomedical applications. However, EV research continues to rely heavily on in vitro cell cultures for EV production, where the exogenous EVs present in fetal bovine (FBS) or other required serum supplementation can be difficult to remove entirely. Despite this and other potential applications involving EV mixtures, there are currently no rapid, robust, inexpensive, and label-free methods for determining the relative concentrations of different EV subpopulations within a sample. In this study, we demonstrate that surface-enhanced Raman spectroscopy (SERS) can biochemically fingerprint fetal bovine serum-derived and bioreactor-produced EVs, and after applying a novel manifold learning technique to the acquired spectra, enables the quantitative detection of the relative amounts of different EV populations within an unknown sample. We first developed this method using known ratios of Rhodamine B to Rhodamine 6G, then using known ratios of FBS EVs to breast cancer EVs from a bioreactor culture. In addition to quantifying EV mixtures, the proposed deep learning architecture provides some knowledge discovery capabilities which we demonstrate by applying it to dynamic Raman spectra of a chemical milling process. This label-free characterization and analytical approach should translate well to other EV SERS applications, such as monitoring the integrity of semipermeable membranes within EV bioreactors, ensuring the quality or potency of diagnostic or therapeutic EVs, determining relative amounts of EVs produced in complex co-culture systems, as well as many Raman spectroscopy applications.

bioengineering↗

bioRxiv2022

Investigating the Consistency of Extracellular Vesicle Production from Breast Cancer Subtypes Using CELLine Adherent Bioreactors

Extracellular vesicle (EV) research has grown rapidly in recent years, largely due to the potential use of EVs as liquid biopsy biomarkers or therapeutics. However, in-depth characterisation and validation of EVs produced using conventional in vitro cultures can be challenging due to the large area of cell monolayers and volumes of culture media required. To overcome this obstacle, multiple bioreactor designs have been tested for EV production with varying success, but the consistency of EVs produced over time in these systems has not been reported previously. In this study, we demonstrate that several breast cancer cell lines of different subtypes can be cultured simultaneously in space, resource, and time efficient manner using CELLine AD 1000 systems, allowing the consistent production of vast amounts of EVs for downstream experimentation. We report an improved workflow used for inoculating, maintaining, and monitoring the bioreactors, their EV production, and the characterisation of the EVs produced. Lastly, our proteomic analyses of the EVs produced throughout the lifetime of the bioreactors show that core EV-associated proteins are relatively consistent, with few minor variations over time, and that tracking the production of EVs may be a convenient method for indirectly monitoring the bioreactors health. These findings will aid future studies requiring the simultaneous production of large amounts of EVs from several cell lines of different subtypes of a disease and other EV biomanufacturing applications.

cancer biology↗

bioRxiv2021

Classification of Preeclamptic Placental Extracellular Vesicles Using Femtosecond Laser-fabricated Nanoplasmonic Sensors and Machine Learning

Placental extracellular vesicles (EVs) play an essential role in pregnancy by protecting and transporting diverse biomolecules that aid in fetomaternal communication. However, in preeclampsia, they have also been implicated in contributing to disease progression. Despite their potential clinical value, most current technologies cannot provide a rapid and effective means of differentiating between healthy and diseased placental EVs. To address this, we developed a fabrication process called laser-induced nanostructuring of SERS-active thin films (LINST), which produces nanoplasmonic substrates that provide exceptional Raman signal enhancement and allow the biochemical fingerprinting of EVs. After validating LINST performance with chemical standards, we used placental EVs from tissue explant cultures and demonstrated that preeclamptic and normotensive placental EVs have classifiably distinct Raman spectra following the application of both conventional and advanced machine learning algorithms. Given the abundance of placental EVs in maternal circulation, these findings will encourage immediate exploration of surface-enhanced Raman spectroscopy (SERS) as a promising method for preeclampsia liquid biopsies, while our novel fabrication process can provide a versatile and scalable substrate for many other SERS applications.

bioengineering↗

bioRxiv2021

Automated Parallel Pattern Search Optimisation of Microfluidic Geometry for Extracellular Vesicle Liquid Biopsies

Microfluidic liquid biopsies using affinity-based capture of extracellular vesicles (EVs) have demonstrated great potential for providing rapid disease diagnosis and monitoring. However, little effort has been devoted to optimising the geometry of the microfluidic channels for maximum EV capture due to the inherent challenges of physically testing many geometric designs. To address this, we developed an automated parallel pattern search (PPS) optimiser by combining a Python optimiser, COMSOL Multiphysics, and high performance computing. This unique approach was applied to a triangular micropillar array geometry by parameterising repeating unit cells, making several assumptions, and optimising for maximum particle capture efficiency. We successfully optimised the triangular pillar arrays and surprisingly found that simply maximising the total number of pillars and effective surface area did not result in maximum EV capture, as devices with slightly larger pillars and more spacing between pillars allowed contact with slower moving EVs that followed the pillar contours more closely. We then experimentally validated this finding using bioreactor-produced EVs in the best and worst channel designs that were functionalised with an antibody against CD63. Captured EVs were quantified using a fluorescent plate reader, followed by an established elution method and nanoparticle tracking analysis. These results demonstrate the power of automated microfluidic geometry optimisations for EV liquid biopsies and will support further development of this rapidly growing field.

bioengineering↗

bioRxiv2020

Towards establishing Extracellular Vesicle-associated RNAs as biomarkers for HER2+ breast cancer

Extracellular vesicles (EVs) are emerging as key players in breast cancer progression and hold immense promise as cancer biomarkers. However, difficulties in obtaining sufficient quantities of EVs for the identification of potential biomarkers hampers progress in this area. To circumvent this obstacle, we cultured BT-474 breast cancer cells in a two chambered bioreactor with CDM-HD serum replacement to significantly improve the yield of cancer cell-associated EVs and eliminate bovine EV contamination. Cancer-relevant mRNAs BIRC5 (Survivin) and YBX1 as well as long-noncoding RNAs HOTAIR, ZFAS1, and AGAP2-AS1 were detected in BT-474 EVs by quantitative RT-PCR. Bioinformatics meta-analyses showed that BIRC5 and HOTAIR RNAs were substantially upregulated compared to non-tumour breast tissue, encouraging further studies to explore their usefulness as biomarkers in patient EV samples. We contend that this effective procedure for obtaining large amounts of cancer-specific EVs will accelerate discovery of EV-associated RNA biomarkers for detection of HER2+ breast cancer.

cancer biology↗