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Imoukhuede, P. I.

Publications and source records attributed to Imoukhuede, P. I..

5 recordsLinked to original sources

Cross-family interactions of vascular endothelial growth factors and platelet-derived growth factors on the endothelial cell surface: A computational model

Angiogenesis, the formation of new vessels from existing vessels, is mediated by vascular endothelial growth factor (VEGF) and platelet-derived growth factor (PDGF). Despite discoveries supporting the cross-family interactions between VEGF and PDGF families, sharing the binding partners between them makes it challenging to identify growth factors that predominantly affect angiogenesis. Systems biology offers promises to untangle this complexity. Thus, in this study, we developed a mass-action kinetics-based computational model for cross-family interactions between VEGFs (VEGF-A, VEGF-B, and PlGF) and PDGFs (PDGF-AA, PDGF-AB, and PDGF-BB) with their receptors (VEGFR1, VEGFR2, NRP1, PDGFR, and PDGFR{beta}). The model, parametrized with our literature mining and surface resonance plasmon assays, was validated by comparing the concentration of VEGFR1 complexes with a previously constructed angiogenesis model. The model predictions include five outcomes: 1) the percentage of free or bound ligands and 2) receptors, 3) the concentration of free ligands, 4) the percentage of ligands occupying each receptor, and 5) the concentration of ligands that is bound to each receptor. We found that at equimolar ligand concentrations (1 nM), PlGF and VEGF-A were the main binding partners of VEGFR1 and VEGFR2, respectively. Varying the density of receptors resulted in the following five outcomes: 1) Increasing VEGFR1 density depletes the free PlGF concentration, 2) increasing VEGFR2 density decreases PDGF:PDGFR complexes, 3) increased NRP1 density generates a biphasic concentration of the free PlGF, 4) increased PDGFR density increases PDGFs:PDGFR binding, and 5) increasing PDGFR{beta} density increases VEGF-A:PDGFR{beta}. Our model offers a reproducible, fundamental framework for exploring cross-family interactions that can be extended to the tissue level or intracellular molecular level. Also, our model may help develop therapeutic strategies in pathological angiogenesis by identifying the dominant complex in the cell signaling. Author summaryNew blood vessel formation from existing ones is essential for growth, healing, and reproduction. However, when this process is disrupted--either too much or too little--it can contribute to diseases such as cancer and peripheral arterial disease. Two key families of proteins, vascular endothelial growth factors (VEGFs) and platelet-derived growth factors (PDGFs), regulate this process. Traditionally, scientists believed that VEGFs only bind to VEGF receptors and PDGFs to PDGF receptors. However, recent findings show that these proteins can interact with each others receptors, making it more challenging to understand and control blood vessel formation. To clarify these complex interactions, we combined computer modeling with biological data to map out which proteins bind to which receptors and to what extent. Our findings show that when VEGFs and PDGFs are present in equal amounts, VEGFs are the primary binding partners for VEGF receptors. We also explored how changes in receptor levels affect these interactions in disease-like conditions. This work provides a foundational computational model for studying cross-family interactions, which can be expanded to investigate tissue-level effects and processes inside cells. Ultimately, our model may help develop better treatments for diseases linked to abnormal blood vessel growth by identifying key protein-receptor interactions.

systems biology↗

Cultured endothelial cells present organ-specific RTK distributions: advancing receptor measurement and data standardization via quantitative flow cytometry

PurposeReceptor tyrosine kinase (RTK) concentrations on the plasma membrane correlate with angiogenic functions in vitro and in rodent models. The intracellular RTK pool also regulates plasma membrane receptor availability and signaling pathways. Organs have specialized angiogenic functions essential to their distinct roles, supporting the hypothesis that plasma membrane and intracellular RTK concentrations vary across endothelial cells (ECs) from different organs. MethodsUsing quantitative flow cytometry on human ECs derived from dermis, umbilical vein, kidney, liver, and brain, we measured and statistically analyzed the concentrations of selected RTKs within ECs and on their plasma membranes. ResultsVEGFR1 exhibited the lowest concentrations on the plasma membrane (300-900 VEGFR1/cell) among VEGFRs. HDMECs (dermis) showed the lowest VEGFR1 level among the examined EC types. Whole-cell VEGFR1 concentrations were 2500-7500 VEGFR1/cell, with 12-26% located on the plasma membrane. The proportion of VEGFR2 located on the plasma membrane was higher at > 30%, except in HGMECs (kidney) where it was 24%. Plasma membrane VEGFR2 was significantly lower in HDMECs and HGMECs compared with HBMECs (brain), whereas whole-cell VEGFR2 levels were consistently in the range of 14,100-22,500 molecules/cell. VEGFR3 was the least localized to the plasma membrane, from 2% in HGMECs to 14% in HDMECs at the highest level of 4400 VEGFR3/cell. Whole-cell VEGFR3 concentrations ranged from 32,400 in HDMECs to 62,000 VEGFR3/cell in HLiSMECs (liver), with no significant differences among EC types. NRP1 was most abundant on the plasma membrane of HUVECs (umbilical vein) at 39,700 NRP1/cell; other ECs displayed 26,000-29,900 NRP1/cell, approximately 5-fold higher than the numbers of VEGFRs. Across EC types, Axl was present on the plasma membrane at levels (6900-12,200 Axl/cell) similar to those of VEGFR2. ConclusionsWe quantified and statistically analyzed plasma membrane and whole-cell expression of angiogenic RTKs across cultured human ECs from five different organs. Our findings suggest that RTK protein distribution might not fully reflect the differential angiogenic capacities in cultured ECs. In vitro monoculture conditions might reduce EC organ-specific features essential for refining vascular models.

bioengineering↗

Sex Differences in VEGF and PDGF Ligand and Receptor Protein Expression during Adipose Tissue Expansion and Regression

Inadequate angiogenesis in obesogenic adipose tissue (AT) has been implicated in disrupted adipogenesis and metabolic disorders. Yet, key cellular and molecular regulators of AT angiogenesis remain largely unidentified. This study sought to identify the dysregulated elements within the Vascular Endothelial Growth Factor (VEGF) and Platelet-Derived Growth Factor (PDGF) systems during obesity progression. We employ a mouse model, comprising both male and female mice, to investigate the changes in the VEGF/PDGF concentration and their receptor distribution in AT during short- and long-term weight gain and weight loss. Our results reveal pronounced sex-specific differences in obesity progression, with male and female mice exhibiting distinct angiogenic ligand and receptor profiles under identical dietary interventions. This data also lays the groundwork for developing computational models of VEGF/PDGF signaling networks in AT, allowing for the simulation of complex biological interactions and the prediction of therapeutic outcomes.

cell biology↗

Integrative analysis of angiogenic signaling in obesity: capillary features and VEGF binding kinetics

Obesity is a global health crisis, with its prevalence particularly severe in the United States, where over 42% of adults are classified as obese. Obesity is driven by complex molecular and tissue-level mechanisms that remain poorly understood. Among these, angiogenesis--primarily mediated by vascular endothelial growth factor (VEGF-A)--is critical for adipose tissue expansion but presents unique challenges for therapeutic targeting due to its intricate regulation. Systems biology approaches have advanced our understanding of VEGF-A signaling in vascular diseases, but their application to obesity is limited by scattered and sometimes contradictory data. To address this gap, we performed a comprehensive analysis of the existing literature to synthesize key findings, standardize data, and provide a holistic perspective on the adipose vascular microenvironment. The data mining revealed five key findings: (1) obesity increases adipocyte size by 78%; (2) vessel density in adipose tissue decreases by 51% in obese mice, with vessels being 47-58% smaller and 4-9 times denser in comparison with tumor vessels; (3) capillary basement membrane thickness remains similar regardless of obesity; (4) VEGF-A shows the strongest binding affinity for VEGFR1, with four times stronger affinity for VEGFR2 than for NRP1; and (5) binding affinities measured by radioligand binding assay and surface plasmon resonance (SPR) are significantly different. These consolidated findings provide essential parameters for systems biology modeling, new insights into obesity-induced changes in adipose tissue, and a foundation for developing angiogenesis-targeting therapies for obesity.

bioengineering↗

Understanding the effects of oxytocin receptor variants on OXT-OXT receptor binding: A mathematical model

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 Kd = 1.6 nM, kon = 6.8 x 105 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 Kd = 0.52 - 9.32 nM and mean Kd = 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 {micro}M 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 Ca2+ 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.

systems biology↗