Probing the self-assembly dynamics and internal structure of amphiphilic hyaluronic acid conjugates by fluorescence spectroscopy and molecular dynamics simulations

Fast and accurate identification of pathogenic bacteria using excitation-emission spectroscopy and machine learning

Fast and reliable identification of pathogenic bacteria is of upmost importance to human health and safety. Methods that are currently used in clinical practice are often time consuming, require expensive equipment, trained personnel, and therefore have limited applications in low resource environments. Molecular identification methods address some of these shortcomings. At the same time, they often use antibodies, their fragments, or other biomolecules as recognition units, which makes such tests specific to a particular target. In contrast, array-based methods use a combination of reporters that are not specific to a single pathogen. These methods provide a more data-rich and universal response that can be used for identification of a variety of bacteria of interest. In this report, we demonstrate the application of the excitation-emission spectroscopy of an environmentally sensitive fluorescent dye for identification of pathogenic bacterial species. 2-(4'-Dimethylamino)-3-hydroxyflavone (DMAF) interacts with the bacterial cell envelope resulting in a distinct spectral response that is unique to each bacterial species. The dynamics of dye-bacteria interaction were thoroughly investigated, and the limits of detection and identification were determined. Neural network classification algorithm was used for pattern recognition analysis and classification of spectral data. The sensor successfully discriminated between eight representative pathogenic bacteria, achieving a classification accuracy of 85.8% at the species level and 98.3% at the Gram status level. The proposed method based on excitation-emission spectroscopy of an environmentally sensitive fluorescent dye is a powerful and versatile diagnostic tool with high accuracy in identification of bacterial pathogens.

Binding interactions of hydrophobically-modified flavonols with β-glucosidase: fluorescence spectroscopy and molecular modelling study

Natural flavonoids are capable of inhibiting glucosidase activity, so they can be used for treating diabetes mellitus and hypertension. However, molecular-level details of their interactions with glucosidase enzymes remain poorly understood. This paper describes the synthesis and spectral characterization of a series of fluorescent flavonols and their interaction with the β-glucosidase enzyme. To tune flavonol-enzyme interaction modes and affinity, we introduced different polar halogen-containing groups or bulky aromatic/alkyl substituents in the peripheral 2-aryl ring of a flavonol moiety. Using fluorescence spectroscopy methods in combination with molecular docking and molecular dynamics simulations, we examined the binding affinity and identified probe binding patterns, which are critical for steric blockage of the key catalytic residues of the enzyme. Using a fluorescent assay, we demonstrated that the binding of flavonol 2e to β-glucosidase decreased its enzymatic activity up to 3.5 times. In addition, our molecular docking and all-atom molecular dynamics simulations suggest that the probe binding is driven by hydrophobic interactions with aromatic Trp and Tyr residues within the catalytic glycone binding pockets of β-glucosidase. Our study provides a new insight into structure-property relations for flavonol-protein interactions, which govern their enzyme binding, and outlines a framework for a rational design of new flavonol-based potent inhibitors for β-glucosidases.

Structure and dynamics of the hyaluronan oligosaccharides and their solvation shell in water: organic mixed solvents

Hyaluronan (HA) is a natural polysaccharide occurring ubiquitously in the connective tissues of vertebrates widely used in the cosmetic and pharmaceutic industries. In numerous applications HA oligosaccharides are being chemically modified using reactions incompatible with aqueous solutions, often carried out in water:organic mixed solvents. We carry out molecular-dynamics (MD) simulations of HA oligosaccharides in water:1,4-dioxane and water:tert-butanol mixtures of different compositions. HA molecule causes a separation of the solvent components in its surroundings, especially in tert-butanol containing solutions, constituting thus a solvation shell enriched by water. Furthermore, interactions with ions are stronger than in pure water and depend on the solvent composition. Consequently, the dynamics of the HA chain varies with the solvent composition and causes observable conformational changes of the HA oligosaccharide. Composition of mixed solvents thus enables us to modify the interaction of HA with other molecules as well as its reactivity.

Atomic-Resolution Experimental Structural Biology and Molecular Dynamics Simulations of Hyaluronan and Its Complexes

This review summarizes the atomic-resolution structural biology of hyaluronan and its complexes available in the Protein Data Bank, as well as published studies of atomic-resolution explicit-solvent molecular dynamics simulations on these and other hyaluronan and hyaluronan-containing systems. Advances in accurate molecular mechanics force fields, simulation methods and software, and computer hardware have supported a recent flourish in such simulations, such that the simulation publications now outnumber the structural biology publications by an order of magnitude. In addition to supplementing the experimental structural biology with computed dynamic and thermodynamic information, the molecular dynamics studies provide a wealth of atomic-resolution information on hyaluronan-containing systems for which there is no atomic-resolution structural biology either available or possible. Examples of these summarized in this review include hyaluronan pairing with other hyaluronan molecules and glycosaminoglycans, with ions, with proteins and peptides, with lipids, and with drugs and drug-like molecules. Despite limitations imposed by present-day computing resources on system size and simulation timescale, atomic-resolution explicit-solvent molecular dynamics simulations have been able to contribute significant insight into hyaluronan's flexibility and capacity for intra- and intermolecular non-covalent interactions.

Simpler Procedure and Improved Performance for Pathogenic Bacteria Analysis with a Paper-Based Ratiometric Fluorescent Sensor Array

Bacterial infections are the leading cause of morbidity and mortality in the world, particularly due to a delay in treatment and misidentification of the bacterial species causing the infection. Therefore, rapid and accurate identification of these pathogens has been of prime importance. The conventional diagnostic techniques include microbiological, biochemical, and genetic analyses, which are time-consuming, require large sample volumes, expensive equipment, reagents, and trained personnel. In response, we have now developed a paper-based ratiometric fluorescent sensor array. Environment-sensitive fluorescent dyes (3-hydroxyflavone derivatives) pre-adsorbed on paper microzone plates fabricated using photolithography, upon interaction with bacterial cell envelopes, generate unique fluorescence response patterns. The stability and reproducibility of the sensor array response were thoroughly investigated, and the analysis procedure was refined for optimal performance. Using neural networks for response pattern analysis, the sensor was able to identify 16 bacterial species and recognize their Gram status with an accuracy rate greater than 90%. The paper-based sensor was stable for up to 6 months after fabrication and required 30 times lower dye and sample volumes as compared to the analogous solution-based sensor. Therefore, this approach opens avenues to a state-of-the-art diagnostic tool that can be potentially translated into clinical applications in low-resource environments.

Water-Soluble Blue Fluorescent Nonconjugated Polymer Dots from Hyaluronic Acid and Hydrophobic Amino Acids

Fluorescent polymers have been increasingly investigated to improve their water solubility and biocompatibility to enhance their performance in drug delivery and theranostic applications. However, the environmentally friendly synthesis and dual functionality of such systems remain a challenge due to the complicated synthesis of conventional fluorescent materials. Herein, we generated a novel blue fluorescent polymer dot through chemical conjugation of hydrophobic amino acids to hyaluronic acid (HA) under one-pot green chemistry conditions. These nonconjugated fluorescent polymer dots (NCPDs) are water soluble, nontoxic to cells, have high fluorescence quantum yield, and can be used for in vitro bioimaging. HA-derived NCPDs exhibit excitation wavelength-dependent fluorescent properties. In addition, the NCPDs also show enhanced doxorubicin loading and delivery in naive and drug-resistant breast cancer cells in 2D and 3D tumor cellular systems. These results demonstrate the potential for successful synthetic scale-up and applications for HA-derived NCPDs.

A Cost-Effective Nano-Sized Curcumin Delivery System with High Drug Loading Capacity Prepared via Flash Nanoprecipitation

Flash nanoprecipitation (FNP) is an efficient technique for encapsulating drugs in particulate carriers assembled by amphiphilic polymers. In this study, a novel nanoparticular system of a model drug curcumin (CUR) based on FNP technique was developed by using cheap and commercially available amphiphilic poly(vinyl pyrrolidone) (PVP) as stabilizer and natural polymer chitosan (CS) as trapping agent. Using this strategy, high encapsulation efficiency (EE > 95%) and drug loading capacity (DLC > 40%) of CUR were achieved. The resulting CUR-loaded nanoparticles (NPs) showed a long-term stability (at least 2 months) and pH-responsive release behavior. This work offers a new strategy to prepare cost-effective drug-loaded NPs with high drug loading capacity and opens a unique opportunity for industrial scale-up.

Nanoparticle Formulation of Indocyanine Green Improves Image-Guided Surgery in a Murine Model of Breast Cancer

PURPOSE

Negative surgical margins (NSMs) have favorable prognostic implications in breast tumor resection surgery. Fluorescence image-guided surgery (FIGS) has the ability to delineate surgical margins in real time, potentially improving the completeness of tumor resection. We have recently developed indocyanine green (ICG)-loaded self-assembled hyaluronic acid (HA) nanoparticles (NanoICG) for solid tumor imaging, which were shown to enhance intraoperative contrast.

PROCEDURES

This study sought to assess the efficacy of NanoICG on completeness of breast tumor resection and post-surgical survival. BALB/c mice bearing iRFP+/luciferase+ 4T1 syngeneic breast tumors were administered NanoICG or ICG, underwent FIGS, and were compared to bright light surgery (BLS) and sham controls.

RESULTS

NanoICG increased the number of complete resections and improved tumor-free survival. This was a product of improved intraoperative contrast enhancement and the identification of a greater number of small, occult lesions than ICG and BLS. Additionally, NanoICG identified chest wall invasion and predicted recurrence in a model of late-stage breast cancer.

CONCLUSIONS

NanoICG is an efficacious intraoperative contrast agent and could potentially improve surgical outcomes in breast cancer.

Image-guided tumor surgery: The emerging role of nanotechnology

Surgical resection is a mainstay treatment for solid tumors. Yet, methods to distinguish malignant from healthy tissue are primarily limited to tactile and visual cues as well as the surgeon's experience. As a result, there is a possibility that a positive surgical margin (PSM) or the presence of residual tumor left behind after resection may occur. It is well-documented that PSMs can negatively impact treatment outcomes and survival, as well as pose an economic burden. Therefore, surgical tumor imaging techniques have emerged as a promising method to decrease PSM rates. Nanoparticles (NPs) have unique characteristics to serve as optical contrast agents during image-guided surgery (IGS). Recently, there has been tremendous growth in the volume and types of NPs used for IGS, including clinical trials. Herein, we describe the most recent contributions of nanotechnology for surgical tumor identification. This article is categorized under: Therapeutic Approaches and Drug Discovery > Nanomedicine for Oncologic Disease Implantable Materials and Surgical Technologies > Nanoscale Tools and Techniques in Surgery Diagnostic Tools > in vivo Nanodiagnostics and Imaging.

Martini Coarse-Grained Model of Hyaluronic Acid for the Structural Change of Its Gel in the Presence of Monovalent and Divalent Salts

Hyaluronic acid (HA) has a wide range of biomedical applications including the formation of hydrogels, microspheres, sponges, and films. The modeling of HA to understand its behavior and interaction with other biomolecules at the atomic level is of considerable interest. The atomistic representation of long HA polymers for the study of the macroscopic structural formation and its interactions with other polyelectrolytes is computationally demanding. To overcome this limitation, we developed a coarse grained (CG) model for HA adapting the Martini scheme. A very good agreement was observed between the CG model and all-atom simulations for both local (bonded interactions) and global properties (end-to-end distance, a radius of gyration, RMSD). Our CG model successfully demonstrated the formation of HA gel and its structural changes at high salt concentrations. We found that the main role of CaCl₂ is screening the electrostatic repulsion between chains. HA gel did not collapse even at high CaCl₂ concentrations, and the osmotic pressure decreased, which agrees well with the experimental results. This is a distinct property of HA from other proteins or polynucleic acids which ensures the validity of our CG model. Our HA CG model is compatible with other CG biomolecular models developed under the Martini scheme, which allows for large-scale simulations of various HA-based complex systems.

Fluorescent Sensor Arrays Can Predict and Quantify the Composition of Multicomponent Bacterial Samples

Fast and reliable identification of infectious disease agents is among the most important challenges for the healthcare system. The discrimination of individual components of mixed infections represents a particularly difficult task. In the current study we further expand the functionality of a ratiometric sensor array technology based on small-molecule environmentally-sensitive organic dyes, which can be successfully applied for the analysis of mixed bacterial samples. Using pattern recognition methods and data from pure bacterial species, we demonstrate that this approach can be used to quantify the composition of mixtures, as well as to predict their components with the accuracy of ~80% without the need to acquire additional reference data. The described approach significantly expands the functionality of sensor arrays and provides important insights into data processing for the analysis of other complex samples.

Atomistic molecular dynamics simulations of the LCST conformational transition in poly(N-vinylcaprolactam) in water

Thermoresponsive poly(N-vinylcaprolactam) (PVCL) has received growing interest due to a temperature-induced phase transition, which switches its solubility in aqueous solutions. However, the lower critical solution temperature (LCST) of PVCL is greatly influenced by the molecular weight, morphology and the environment. Therefore, despite of numerous experimental studies of the thermal response of PVCL, a driving force and a molecular origin of conformation transitions in solution remain far less studied. To get a better understanding of the coil-to-globule conformation transition of PVCL in aqueous solution, we examined the structure and conformation dynamics of a single-chain PVCL₃₀ in a temperature range of 280-360 K by using atomistic molecular dynamics (MD) simulations. The united-atom GROMOS G53a6 force field was re-parameterized and fine-tuned by DFT calculations to reproduce the experimental LCST transition of PVCL. Our MD model reproduces the LCST transition of PVCL₃₀ to occur within a temperature range of 34.6-38.5°. MD simulation results suggest a significant difference between the hydration state of the carbonyl group of PVCL below and above the LCST threshold. The analysis of the number of hydrogen bonds of PVCL with water molecules demonstrates that dehydration of the polymer plays an important role and drives the temperature-induced polymer collapse. Finally, the developed MD model and FF parameters were successfully tested for large-scale systems, such as mixture PVCL₃₀ oligomer and single-chain PVCL₈₁₆ polymer, respectively.