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Dubey P, Fang Y, Tukei KL, Kuila S, Liu X, Sahota A, Frolova AI, Reinl EL, Malik M, England SK, Imoukhuede PI. Understanding the effects of oxytocin receptor variants on OXT-OXT receptor binding: A mathematical model. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.02.28.582600. [PMID: 38559157 PMCID: PMC10979843 DOI: 10.1101/2024.02.28.582600] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/04/2024]
Abstract
Approximately half of U.S. women giving birth annually receive Pitocin, the synthetic form of oxytocin (OXT), yet its effective dose can vary significantly. This variability presents safety concerns due to unpredictable responses, which may lead to adverse outcomes for both mother and baby. To address the need for improved dosing, we developed a data-driven mathematical model to predict OXT receptor (OXTR) binding. Our study focuses on five prevalent OXTR variants (V45L, P108A, L206V, V281M, and E339K) and their impact on OXT-OXTR binding dynamics in two distinct cell types: human embryonic kidney cells (HEK293T), commonly used in experimental systems, and human myometrial smooth muscle cells, containing endogenous OXTR. We parameterized the model with cell-specific OXTR surface localization measurements. To strengthen the robustness of our study, we conducted a comprehensive meta-analysis of OXT- OXTR binding, enabling parameterization of our model with cell-specific OXT-OXTR binding kinetics (myometrial OXT-OXTR K d = 1.6 nM, kon = 6.8 × 10 5 M -1 min -1 , and koff = 0.0011 min -1 ). Our meta-analysis revealed significant homogeneity in OXT-OXTR affinity across experiments and species with a K d = 0.52 - 9.32 nM and mean K d = 1.48 ± 0.36 nM. Our model achieves several valuable insights into designing dosage strategies. First, we predicted that the OXTR complex reaches maximum occupancy at 10 nM OXT in myometrial cells and at 1 µM in HEK293T cells. This information is pivotal for guiding experimental design and data interpretation when working with these distinct cell types, emphasizing the need to consider effects for specific cell types when choosing OXTR-transfected cell lines. Second, our model recapitulated the significant effects of genetic variants for both experimental and physiologically relevant systems, with V281M and E339K substantially compromising OXT-OXTR binding capacity. These findings suggest the need for personalized oxytocin dosing based on individual genetic profiles to enhance therapeutic efficacy and reduce risks, especially in the context of labor and delivery. Third, we demonstrated the potential for rescuing the attenuated cell response observed in V281M and E339K variants by increasing the OXT dosage at specific, early time points. Cellular responses to OXT, including Ca 2+ release, manifest within minutes. Our model indicates that providing V281M- and E339K-expressing cells with doubled OXT dose during the initial minute of binding can elevate OXT-OXTR complex formation to levels comparable to wild-type OXTR. In summary, our study provides a computational framework for precision oxytocin dosing strategies, paving the way for personalized medicine.
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Choi S, Woo SH, Park I, Lee S, Yeo KI, Lee SH, Lee SY, Yang S, Lee G, Chang WJ, Bashir R, Kim YS, Lee SW. Cellular subpopulations identified using an ensemble average of multiple dielectrophoresis measurements. Comput Biol Med 2024; 170:108011. [PMID: 38271838 DOI: 10.1016/j.compbiomed.2024.108011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2023] [Revised: 01/11/2024] [Accepted: 01/16/2024] [Indexed: 01/27/2024]
Abstract
While the average value measurement approach can successfully analyze and predict the general behavior and biophysical properties of an isogenic cell population, it fails when significant differences among individual cells are generated in the population by intracellular changes such as the cell cycle, or different cellular responses to certain stimuli. Detecting such single-cell differences in a cell population has remained elusive. Here, we describe an easy-to-implement and generalizable platform that measures the dielectrophoretic cross-over frequency of individual cells by decreasing measurement noise with a stochastic method and computing ensemble average statistics. This platform enables multiple, real-time, label-free detection of individual cells with significant dielectric variations over time within an isogenic cell population. Using a stochastic method in combination with the platform, we distinguished cell subpopulations from a mixture of drug-untreated and -treated isogenic cells. Furthermore, we demonstrate that our platform can identify drug-treated isogenic cells with different recovery rates.
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Affiliation(s)
- Seungyeop Choi
- Department of Biomedical Engineering, Yonsei University, Wonju, 26493, Republic of Korea; School of Biomedical Engineering, Korea University, Seoul, 02481, Republic of Korea; BK21 Four Institute of Precision Public Health, Korea University, Seoul, 02841, Republic of Korea
| | - Sung-Hun Woo
- Department of Biomedical Laboratory Science, Yonsei University, Wonju, 26493, Republic of Korea
| | - Insu Park
- Holonyak Micro and Nanotechnology Laboratory, University of Illinois at Urbana-Champaign, Urbana, IL, 61801, USA; Department of Biomedical Engineering, Konyang University, Daejeon, 35365, Republic of Korea
| | - Sena Lee
- Department of Precision Medicine, Wonju College of Medicine, Yonsei University, Wonju, 26426, Republic of Korea
| | - Kang In Yeo
- Department of Biomedical Engineering, Yonsei University, Wonju, 26493, Republic of Korea
| | - Sang Hyun Lee
- Department of Biomedical Engineering, Yonsei University, Wonju, 26493, Republic of Korea
| | - Sei Young Lee
- Department of Biomedical Engineering, Yonsei University, Wonju, 26493, Republic of Korea; Department of Medical Informatics and Biostatistics, Graduate School, Yonsei University, Wonju, 26426, Republic of Korea
| | - Sejung Yang
- Department of Precision Medicine, Wonju College of Medicine, Yonsei University, Wonju, 26426, Republic of Korea
| | - Gyudo Lee
- Department of Biotechnology and Bioinformatics, Korea University, Sejong, 30019, Republic of Korea; Interdisciplinary Graduate Program for Artificial Intelligence Smart Convergence Technology, Korea University, Sejong, 30019, Republic of Korea
| | - Woo-Jin Chang
- Mechanical Engineering Department, University of Wisconsin-Milwaukee, Milwaukee, WI, 53211, USA
| | - Rashid Bashir
- Holonyak Micro and Nanotechnology Laboratory, University of Illinois at Urbana-Champaign, Urbana, IL, 61801, USA; Department of Mechanical Science and Engineering, University of Illinois at Urbana-Champaign, Urbana, IL, 61801, USA; Department of Bioengineering, University of Illinois at Urbana-Champaign, Urbana, IL, 61801, USA; Materials Research Laboratory, University of Illinois at Urbana-Champaign, Urbana, IL, 61801, USA
| | - Yoon Suk Kim
- Department of Biomedical Laboratory Science, Yonsei University, Wonju, 26493, Republic of Korea.
| | - Sang Woo Lee
- Department of Biomedical Engineering, Yonsei University, Wonju, 26493, Republic of Korea.
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Fang Y, Reinl EL, Liu A, Prochaska TD, Malik M, Frolova AI, England SK, Imoukhuede PI. Quantification of surface-localized and total oxytocin receptor in myometrial smooth muscle cells. Heliyon 2024; 10:e25761. [PMID: 38384573 PMCID: PMC10878913 DOI: 10.1016/j.heliyon.2024.e25761] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2023] [Revised: 01/31/2024] [Accepted: 02/01/2024] [Indexed: 02/23/2024] Open
Abstract
Oxytocin acts through the oxytocin receptor (OXTR) to modulate uterine contractility. We previously identified OXTR genetic variants and showed that, in HEK293T cells, two of the OXTR protein variants localized to the cell surface less than wild-type OXTR. Here, we sought to measure OXTR in the more native human myometrial smooth muscle cell (HMSMC) line on both the cell-surface and across the whole cell, and used CRISPR editing to add an HA tag to the endogenous OXTR gene for anti-HA measurement. Quantitative flow cytometry revealed that these cells possessed 55,000 ± 3200 total OXTRs and 4900 ± 390 cell-surface OXTRs per cell. To identify any differential wild-type versus variant localization, we transiently transfected HMSMCs to exogenously express wild-type or variant OXTR with HA and green fluorescent protein tags. Total protein expression of wild-type OXTR and all tested variants were similar. However, the two variants with lower surface localization in HEK293T cells also presented lower surface localization in HMSMCs. Overall, we confirm the differential surface localization of variant OXTR in a more native cell type, and further demonstrate that the quantitative flow cytometry technique is adaptable to whole-cell measurements.
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Affiliation(s)
- Yingye Fang
- Department of Bioengineering, University of Washington, Seattle, WA, 98109, USA
| | - Erin L. Reinl
- Department of Obstetrics and Gynecology, Center for Reproductive Health Sciences, Washington University School of Medicine in St. Louis, St. Louis, MO, 63110, USA
| | - Audrey Liu
- Department of Obstetrics and Gynecology, Center for Reproductive Health Sciences, Washington University School of Medicine in St. Louis, St. Louis, MO, 63110, USA
| | - Trinidi D. Prochaska
- Department of Obstetrics and Gynecology, Center for Reproductive Health Sciences, Washington University School of Medicine in St. Louis, St. Louis, MO, 63110, USA
| | - Manasi Malik
- Department of Obstetrics and Gynecology, Center for Reproductive Health Sciences, Washington University School of Medicine in St. Louis, St. Louis, MO, 63110, USA
| | - Antonina I. Frolova
- Department of Obstetrics and Gynecology, Center for Reproductive Health Sciences, Washington University School of Medicine in St. Louis, St. Louis, MO, 63110, USA
| | - Sarah K. England
- Department of Obstetrics and Gynecology, Center for Reproductive Health Sciences, Washington University School of Medicine in St. Louis, St. Louis, MO, 63110, USA
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Fang Y, Imoukhuede PI. Axl and Vascular Endothelial Growth Factor Receptors Exhibit Variations in Membrane Localization and Heterogeneity Across Monolayer and Spheroid High-Grade Serous Ovarian Cancer Models. GEN BIOTECHNOLOGY 2023; 2:43-56. [PMID: 36873811 PMCID: PMC9976349 DOI: 10.1089/genbio.2022.0034] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/22/2022] [Accepted: 01/05/2023] [Indexed: 02/18/2023]
Abstract
Vascular endothelial growth factor receptors (VEGFRs) and Axl are receptor tyrosine kinases (RTK) that are targeted in ovarian cancer therapy. Two-dimensional monolayer culture and three-dimensional spheroids are common models for RTK-targeted drug screening: monolayers are simple and economical while spheroids include several genetic and histological tumor features. RTK membrane localization dictates RTK signaling and drug response, however, it is not characterized in these models. We quantify plasma membrane RTK concentrations and show differential RTK abundance and heterogeneity in monolayers versus spheroids. We show VEGFR1 concentrations on the plasma membrane to be 10 times higher in OVCAR8 spheroids than in monolayers; OVCAR8 spheroids are more heterogeneous than monolayers, exhibiting a bimodal distribution of a low-Axl (6200/cell) and a high-Axl subpopulation (25,000/cell). In addition, plasma membrane Axl concentrations differ by 100 times between chemosensitive (OVCAR3) and chemoresistant (OVCAR8) cells and by 10 times between chemoresistant cell lines (OVCAR5 vs. OVCAR8). These systematic findings can guide ovarian cancer model selection for drug screening.
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Affiliation(s)
- Yingye Fang
- Department of Bioengineering, University of Washington, Seattle, Washington, USA
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Tan SY, Jing Q, Leung Z, Xu Y, Cheng LKW, Tam SST, Wu AR. Transcriptomic analysis of 3D vasculature-on-a-chip reveals paracrine factors affecting vasculature growth and maturation. LAB ON A CHIP 2022; 22:3885-3897. [PMID: 36093896 DOI: 10.1039/d2lc00570k] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
In vitro models of vasculature are of great importance for modelling vascular physiology and pathology. However, there is usually a lack of proper spatial patterning of interacting heterotypic cells in conventional vasculature dish models, which might confound results between contact and non-contact interactions. We use a microfluidic platform with structurally defined separation between human microvasculature and fibroblasts to probe their dynamic, paracrine interactions. We also develop a novel, versatile technique to retrieve cells embedded in extracellular matrix from the microfluidic device for downstream transcriptomic analysis, and uncover growth factor and cytokine expression profiles associated with improved vasculature growth. Paired receptor-ligand analysis further reveals paracrine signaling molecules that could be supplemented into the medium for vasculatures models where fibroblast coculture is undesirable or infeasible. These findings also provide deeper insights into the molecular cues for more physiologically relevant vascular mimicry and vascularized organoid model for clinical applications such as drug screening and disease modeling.
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Affiliation(s)
- Sin Yen Tan
- Department of Chemical and Biological Engineering, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong.
| | - Qiuyu Jing
- Division of Life Science, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong
| | - Ziuwin Leung
- Department of Electrical and Computer Engineering, Centre for Applied Synthetic Biology, Concordia University, Montréal, Québec H3G1M8, Canada
| | - Ying Xu
- Division of Life Science, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong
| | - Lily Kwan Wai Cheng
- Division of Life Science, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong
| | - Sindy Sing Ting Tam
- Division of Life Science, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong
| | - Angela Ruohao Wu
- Department of Chemical and Biological Engineering, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong.
- Division of Life Science, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong
- State Key Laboratory of Molecular Neuroscience, The Hong Kong University of Science and Technology, Hong Kong S.A.R., China
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Fang Y, Malik M, England SK, Imoukhuede PI. Absolute Quantification of Plasma Membrane Receptors Via Quantitative Flow Cytometry. Methods Mol Biol 2022; 2475:61-77. [PMID: 35451749 PMCID: PMC9261967 DOI: 10.1007/978-1-0716-2217-9_4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/03/2023]
Abstract
Plasma membrane receptors are transmembrane proteins that initiate cellular response following the binding of specific ligands (e.g., growth factors, hormones, and cytokines). The abundance of plasma membrane receptors can be a diagnostic or prognostic biomarker in many human diseases. One of the best techniques for measuring plasma membrane receptors is quantitative flow cytometry (qFlow). qFlow employs fluorophore-conjugated antibodies against the receptors of interest and corresponding fluorophore-loaded calibration beads offers standardized and reproducible measurements of plasma membrane receptors. More importantly, qFlow can achieve absolute quantification of plasma membrane receptors when phycoerythrin (PE) is the fluorophore of choice. Here we describe a detailed qFlow protocol to obtain absolute receptor quantities on the basis of PE calibration. This protocol is foundational for many previous and ongoing studies in quantifying tyrosine kinase receptors and G-protein-coupled receptors with in vitro cell models and ex vivo cell samples.
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Affiliation(s)
- Yingye Fang
- Department of Biomedical Engineering, Washington University in St. Louis, St. Louis, MO, USA
- University of Washington, Department of Bioengineering, Seattle, WA, USA
| | - Manasi Malik
- Center for Reproductive Health Sciences, Department of Obstetrics and Gynecology, Washington University School of Medicine, St. Louis, MO, USA
| | - Sarah K England
- Center for Reproductive Health Sciences, Department of Obstetrics and Gynecology, Washington University School of Medicine, St. Louis, MO, USA
| | - P I Imoukhuede
- Department of Biomedical Engineering, Washington University in St. Louis, St. Louis, MO, USA.
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A quantitative view on multivalent nanomedicine targeting. Adv Drug Deliv Rev 2021; 169:1-21. [PMID: 33264593 DOI: 10.1016/j.addr.2020.11.010] [Citation(s) in RCA: 41] [Impact Index Per Article: 13.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2020] [Revised: 11/11/2020] [Accepted: 11/21/2020] [Indexed: 12/17/2022]
Abstract
Although the concept of selective delivery has been postulated over 100 years ago, no targeted nanomedicine has been clinically approved so far. Nanoparticles modified with targeting ligands to promote the selective delivery of therapeutics towards a specific cell population have been extensively reported. However, the rational design of selective particles is still challenging. One of the main reasons for this is the lack of quantitative theoretical and experimental understanding of the interactions involved in cell targeting. In this review, we discuss new theoretical models and experimental methods that provide a quantitative view of targeting. We show the new advancements in multivalency theory enabling the rational design of super-selective nanoparticles. Furthermore, we present the innovative approaches to obtain key targeting parameters at the single-cell and single molecule level and their role in the design of targeting nanoparticles. We believe that the combination of new theoretical multivalent design and experimental methods to quantify receptors and ligands aids in the rational design and clinical translation of targeted nanomedicines.
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Fang Y, Kaszuba T, Imoukhuede PI. Systems Biology Will Direct Vascular-Targeted Therapy for Obesity. Front Physiol 2020; 11:831. [PMID: 32760294 PMCID: PMC7373796 DOI: 10.3389/fphys.2020.00831] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2020] [Accepted: 06/22/2020] [Indexed: 12/12/2022] Open
Abstract
Healthy adipose tissue expansion and metabolism during weight gain require coordinated angiogenesis and lymphangiogenesis. These vascular growth processes rely on the vascular endothelial growth factor (VEGF) family of ligands and receptors (VEGFRs). Several studies have shown that controlling vascular growth by regulating VEGF:VEGFR signaling can be beneficial for treating obesity; however, dysregulated angiogenesis and lymphangiogenesis are associated with several chronic tissue inflammation symptoms, including hypoxia, immune cell accumulation, and fibrosis, leading to obesity-related metabolic disorders. An ideal obesity treatment should minimize adipose tissue expansion and the advent of adverse metabolic consequences, which could be achieved by normalizing VEGF:VEGFR signaling. Toward this goal, a systematic investigation of the interdependency of vascular and metabolic systems in obesity and tools to predict personalized treatment ranges are necessary to improve patient outcomes through vascular-targeted therapies. Systems biology can identify the critical VEGF:VEGFR signaling mechanisms that can be targeted to regress adipose tissue expansion and can predict the metabolic consequences of different vascular-targeted approaches. Establishing a predictive, biologically faithful platform requires appropriate computational models and quantitative tissue-specific data. Here, we discuss the involvement of VEGF:VEGFR signaling in angiogenesis, lymphangiogenesis, adipogenesis, and macrophage specification – key mechanisms that regulate adipose tissue expansion and metabolism. We then provide useful computational approaches for simulating these mechanisms, and detail quantitative techniques for acquiring tissue-specific parameters. Systems biology, through computational models and quantitative data, will enable an accurate representation of obese adipose tissue that can be used to direct the development of vascular-targeted therapies for obesity and associated metabolic disorders.
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Affiliation(s)
- Yingye Fang
- Imoukhuede Systems Biology Laboratory, Department of Biomedical Engineering, McKelvey School of Engineering, Washington University in St. Louis, St. Louis, MO, United States
| | - Tomasz Kaszuba
- Imoukhuede Systems Biology Laboratory, Department of Biomedical Engineering, McKelvey School of Engineering, Washington University in St. Louis, St. Louis, MO, United States
| | - P I Imoukhuede
- Imoukhuede Systems Biology Laboratory, Department of Biomedical Engineering, McKelvey School of Engineering, Washington University in St. Louis, St. Louis, MO, United States
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