The Convergence of Cell-Based Surface Plasmon Resonance and Biomaterials: The Future of Quantifying Bio-molecular Interactions-A Review

Trends in surface plasmon resonance biosensing: materials, methods, and machine learning

Surface plasmon resonance (SPR) proves to be one of the most effective methods of label-free detection and has been integral for the study of biomolecular interactions and the development of biosensors. This trend delves into the latest SPR research and progress built upon the Kretschmann configuration, a pivotal platform, and highlights three key developments that have enhanced the capabilities of the technique. We will first cover a range of explorations of novel plasmonic materials that have shaped SPR performance. Innovative signal transduction and collection, which leverages traditional materials and emerging alternatives, will then be discussed. Finally, the evolving landscape of data analysis, including the integration of machine learning algorithms to navigate complex SPR datasets, will be reviewed. We will also discuss the implementation of these improvements that have enabled new biosensing functions. These advancements not only pave the way for enhanced biosensing in general but also open new avenues for the technique to play a more significant role in research concerning human health.

Label-free LC-MS based assay to characterize small molecule compound binding to cells

Study of small molecule binding to live cells provides important information on the characterization of ligands pharmacologically. Here we developed and validated a label-free, liquid chromatography-mass spectrometry (LC-MS) based cell binding assay, using centrifugation to separate binders from non-binders. This assay was applied to various target classes, with particular emphasis on those for which protein-based binding assay can be difficult to achieve. In one example, to study a G protein coupled receptor (GPCR), we used one antagonist as probe and multiple other antagonists as competitor ligands. Binding of the probe was confirmed to be specific and saturable, reaching a fast equilibrium. Competition binding analysis by titration of five known ligands suggested a good correlation with their inhibition potency. In another example, this assay was applied to an ion channel target with its agonists, of which the determined binding affinity was consistent with functional assays. This versatile method allows quantitative characterization of ligand binding to cell surface expressed targets in a physiologically relevant environment.

Ginger nanoparticles mediated induction of Foxa2 prevents high-fat diet-induced insulin resistance

Rationale: The obesity epidemic has expanded globally, due in large part to the increased consumption of high-fat diets (HFD), and has increased the risk of major chronic diseases, including type 2 diabetes. Diet manipulation is the foundation of prevention and treatment of obesity and diabetes. The molecular mechanisms that mediate the diet-based prevention of insulin resistance, however, remain to be identified. Here, we report that treatment with orally administered ginger-derived nanoparticles (GDNP) prevents insulin resistance by restoring homeostasis in gut epithelial Foxa2 mediated signaling in mice fed a high-fat diet (HFD). Methods: Ginger-derived nanoparticles (GDNP) were added into drinking water to treat high-fat diet fed mice for at least one year or throughout their life span. A micro array profile of intestinal, liver and fat tissue of GDNP treated mice was used to analyze their gene expression profile. Genes associated with metabolism or insulin signaling were further quantified using the real time polymerase chain reaction (RT-PCR). Surface plasmon resonance (SPR) was used for determining the interaction between Foxa2 protein and phosphatic acid lipid nanoparticles. Results: HFD-feeding inhibited the expression of Foxa2; the GDNPs increased the expression of Foxa2 and protected Foxa2 against Akt-1 mediated phosphorylation and subsequent inactivation of Foxa2. Increasing expression of Foxa2 leads to altering the composition of intestinal epithelial cell (IEC) exosomes of mice fed a HFD and prevents IEC exosome mediated insulin resistance. Collectively, oral administration of GDNP prevents insulin resistance in HFD mice. Interestingly, oral administration of GDNP also extended the life span of the mice and inhibited skin inflammation. Conclusion: Our findings showed that GDNP treatment can prevent HFD-induced obesity and insulin resistance via protecting the Foxa2 from Akt-1 mediated phosphorylation. GDNP treatment provides an alternative approach based on diet manipulation for the development of therapeutic interventions for obesity.

Unlocking the secret of lignin-enzyme interactions: Recent advances in developing state-of-the-art analytical techniques

Bioconversion of renewable lignocellulosics to produce liquid fuels and chemicals is one of the most effective ways to solve the problem of fossil resource shortage, energy security, and environmental challenges. Among the many biorefinery pathways, hydrolysis of lignocellulosics to fermentable monosaccharides by cellulase is arguably the most critical step of lignocellulose bioconversion. In the process of enzymatic hydrolysis, the direct physical contact between enzymes and cellulose is an essential prerequisite for the hydrolysis to occur. However, lignin is considered one of the most recalcitrant factors hindering the accessibility of cellulose by binding to cellulase unproductively, which reduces the saccharification rate and yield of sugars. This results in high costs for the saccharification of carbohydrates. The various interactions between enzymes and lignin have been explored from different perspectives in literature, and a basic lignin inhibition mechanism has been proposed. However, the exact interaction between lignin and enzyme as well as the recently reported promotion of some types of lignin on enzymatic hydrolysis is still unclear at the molecular level. Multiple analytical techniques have been developed, and fully unlocking the secret of lignin-enzyme interactions would require a continuous improvement of the currently available analytical techniques. This review summarizes the current commonly used advanced research analytical techniques for investigating the interaction between lignin and enzyme, including quartz crystal microbalance with dissipation (QCM-D), surface plasmon resonance (SPR), attenuated total reflectance-Fourier transform infrared (ATR-FTIR) spectroscopy, atomic force microscopy (AFM), nuclear magnetic resonance (NMR) spectroscopy, fluorescence spectroscopy (FLS), and molecular dynamics (MD) simulations. Interdisciplinary integration of these analytical methods is pursued to provide new insight into the interactions between lignin and enzymes. This review will serve as a resource for future research seeking to develop new methodologies for a better understanding of the basic mechanism of lignin-enzyme binding during the critical hydrolysis process.

Label-free methods for optical in vitro characterization of protein-protein interactions

Protein-protein interactions are involved in the regulation and function of the majority of cellular processes. As a result, much effort has been aimed at the development of methodologies capable of quantifying protein-protein interactions, with label-free methods being of particular interest due to the associated simplified workflows and minimisation of label-induced perturbations. Here, we review recent advances in optical technologies providing label-free in vitro measurements of affinities and kinetics. We provide an overview and comparison of existing techniques and their principles, discussing advantages, limitations, and recent applications.

Systems Biology Will Direct Vascular-Targeted Therapy for Obesity

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.