Search

Designing nanoparticles with desired properties is a challenging endeavor, due to the large combinatorial space and complex structure–function relationships. High throughput methodologies and machine learning approaches are attractive and emergent strategies to accelerate nanoparticle composition design. To date, how to combine nanoparticle formulation, screening, and computational decision-making into a single effective workflow is underexplored. In this study, we showcase the integration of three key technologies, namely microfluidic-based formulation, high content imaging, and active machine learning. As a case study, we apply our approach for designing PLGA-PEG nanoparticles with high uptake in human breast cancer cells. Starting from a small set of nanoparticles for model training, our approach led to an increase in uptake from ∼5-fold to ∼15-fold in only two machine learning guided iterations, taking one week each. To the best of our knowledge, this is the first time that these three technologies have been successfully integrated to optimize a biological response through nanoparticle composition. Our results underscore the potential of the proposed platform for rapid and unbiased nanoparticle optimization.

The performance of single-chain polymeric nanoparticles (SCPNs) in biomedical applications highly depends on their conformational stability in cellular environments. Until now, such stability studies are limited to 2D cell culture models, which do not recapitulate the 3D tumor microenvironment well. Here, a microfluidic tumor-on-a-chip model is introduced that recreates the tumor milieu and allows in-depth insights into the diffusion, cellular uptake, and stability of SCPNs. The chip contains Matrigel/collagen-hyaluronic acid as extracellular matrix (ECM) models and is seeded with cancer cell MCF7 spheroids. With this 3D platform, it is assessed how the polymer's microstructure affects the SCPN's behavior when crossing the ECM, and evaluates SCPN internalization in 3D cancer cells. A library of SCPNs varying in microstructure is prepared. All SCPNs show efficient ECM penetration but their cellular uptake/stability behavior depends on the microstructure. Glucose-based nanoparticles display the highest spheroid uptake, followed by charged nanoparticles. Charged nanoparticles possess an open conformation while nanoparticles stabilized by internal hydrogen bonding retain a folded structure inside the tumor spheroids. The 3D microfluidic tumor-on-a-chip platform is an efficient tool to elucidate the interplay between polymer microstructure and SCPN's stability, a key factor for the rational design of nanoparticles for targeted biological applications.

Single-chain polymeric nanoparticles (SCPNs) have been extensively explored as a synthetic alternative to enzymes for catalytic applications. However, the inherent structural heterogeneity of SCPNs, arising from the dispersity of the polymer backbone and stochastic incorporation of different monomers as well as catalytic moieties, is expected to lead to variations in catalytic activity between individual particles. To understand the effect of structural heterogeneities on the catalytic performance of SCPNs, techniques are required that permit researchers to directly monitor SCPN activity at the single-polymer level. In this study, we introduce the use of single-molecule fluorescence microscopy to study the kinetics of Cu(I)-containing SCPNs towards depropargylation reactions. We developed Cu(I)-containing SCPNs that exhibit fast kinetics towards depropargylation and Cu-catalyzed azide-alkyne click reactions, making them suitable for single-particle kinetic studies. SCPNs were then immobilized on the surface of glass coverslips and the catalytic reactions were monitored at a single-particle level using total internal reflection fluorescence (TIRF) microscopy. Our studies revealed the interparticle turnover dispersity for Cu(I)-catalyzed depropargylations. In the future, our approach can be extended to different polymer designs which can give insights into the intrinsic heterogeneity of SCPN catalysis and can further aid in the rational development of SCPN-based catalysts.

The development of contrast agents based on fluorescent nanoparticles with high brightness and stability is a key factor to improve the resolution and signal-to-noise ratio of current fluorescence imaging techniques. However, the design of bright fluorescent nanoparticles remains challenging due to fluorescence self-quenching at high concentrations. Developing bright nanoparticles showing FRET emission adds several advantages to the system, including an amplified Stokes shift, the possibility of ratiometric measurements, and of verifying the nanoparticle stability. Herein, we have developed Förster resonance energy transfer (FRET)-based nanovesicles at different dye loadings and investigated them through complementary experimental techniques, including conventional fluorescence spectroscopy and super-resolution microscopy supported by molecular dynamics calculations. We show that the optical properties can be modulated by dye loading at the nanoscopic level due to the dye's molecular diffusion in fluid-like membranes. This work shows the first proof of a FRET pair dye's dynamism in liquid-like membranes, resulting in optimized nanoprobes that are 120-fold brighter than QDot 605 and exhibit >80% FRET efficiency with vesicle-to-vesicle variations that are mostly below 10%.

MicroRNAs (miRNAs) are small non-coding endogenous RNAs, which are attracting a growing interest as therapeutic molecules due to their central role in major diseases. However, the transformation of these biomolecules into drugs is limited due to their unstability in the bloodstream, caused by nucleases abundantly present in the blood, and poor capacity to enter cells. The conjugation of miRNAs to nanoparticles (NPs) could be an effective strategy for their clinical delivery. Herein, the engineering of non-liposomal lipid nanovesicles, named quatsomes (QS), for the delivery of miRNAs and other small RNAs into the cytosol of tumor cells, triggering a tumor-suppressive response is reported. The engineered pH-sensitive nanovesicles have controlled structure (unilamellar), size (<150 nm) and composition. These nanovesicles are colloidal stable (>24 weeks), and are prepared by a green, GMP compliant, and scalable one-step procedure, which are all unavoidable requirements for the arrival to the clinical practice of NP based miRNA therapeutics. Furthermore, QS protect miRNAs from RNAses and when injected intravenously, deliver them into liver, lung, and neuroblastoma xenografts tumors. These stable nanovesicles with tunable pH sensitiveness constitute an attractive platform for the efficient delivery of miRNAs and other small RNAs with therapeutic activity and their exploitation in the clinics.

Item does not contain fulltext

The formation of a protein corona, where proteins spontaneously adhere to the surface of nanomaterials in biological environments, leads to changes in their physicochemical properties and subsequently affects their intended biomedical functionalities. Most current methods to study protein corona formation are ensemble-averaging and either require fluorescent labeling, washing steps, or are only applicable to specific types of particles. Here we introduce real-time all-optical nanoparticle analysis by scattering microscopy (RONAS) to track the formation of protein corona in full serum, at the single-particle level, without any labeling. RONAS uses optical scattering microscopy and enables real-time and in situ tracking of protein adsorption on metallic and dielectric nanoparticles with different geometries directly in blood serum. We analyzed the adsorbed protein mass, the affinity, and the kinetics of the protein adsorption at the single particle level. While there is a high degree of heterogeneity from particle to particle, the predominant factor in protein adsorption is surface chemistry rather than the underlying nanoparticle material or size. RONAS offers an in-depth understanding of the mechanisms related to protein coronas and, thus, enables the development of strategies to engineer efficient bionanomaterials.

Degradable polymeric micelles are promising drug delivery systems due to their hydrophobic core and responsive design. When applying micellar nanocarriers for tumor delivery, one of the bottlenecks encountered in vivo is the tumor tissue barrier: crossing the dense mesh of cells and the extracellular matrix (ECM). Sometimes overlooked, the extracellular matrix can trap nanoformulations based on charge, size, and hydrophobicity. Here, we used a simple design of a microfluidic chip with two types of ECM and MCF7 spheroids to allow “high-throughput” screening of the interactions between biological interfaces and polymeric micelles. To demonstrate the applicability of the chip, a small library of fluorescently labeled polymeric micelles varying in their hydrophilic shell and hydrophobic core forming blocks was studied. Three widely used hydrophilic shells were tested and compared, namely, poly(ethylene glycol), poly(2-ethyl-2-oxazoline), and poly(acrylic acid), along with two enzymatically degradable dendritic hydrophobic cores (based on hexyl or nonyl end groups). Using ratiometric imaging of unimer:micelle fluorescence and FRAP inside the chip model, we obtained the local assembly state and dynamics inside the chip. Notably, we observed different micelle behaviors in the basal lamina ECM, from avoidance of the ECM structure to binding of the poly(acrylic acid) formulations. Binding to the basal lamina correlated with higher uptake into MCF7 spheroids. Overall, we proposed a simple microfluidic chip containing dual ECM and spheroids for the assessment of the interactions of polymeric nanocarriers with biological interfaces and evaluating nanoformulations’ capacity to cross the tumor tissue barrier.

Biodegradable periodic mesoporous organosilica nanoparticles (nanoPMOs) are widely used as responsive drug delivery platforms for targeted chemotherapy of cancer. However, the evaluation of their properties such as surface functionality and biodegradability is still challenging, which has a significant impact on the efficiency of chemotherapy. In this study, we have applied direct stochastic optical reconstruction microscopy (dSTORM), a single-molecule super-resolution microscopy technique, to quantify the degradation of nanoPMOs triggered by glutathione and the multivalency of antibody-conjugated nanoPMOs. Subsequently, the effect of these properties on cancer cell targeting, drug loading and release capability, and anticancer activity is also studied. Due to the higher spatial resolution at the nanoscale, dSTORM imaging is able to reveal the structural properties (i.e., size and shape) of fluorescent and biodegradable nanoPMOs. The quantification of nanoPMOs’ biodegradation using dSTORM imaging demonstrates their excellent structure-dependent degradation behavior at a higher glutathione concentration. The surface functionality of anti-M6PR antibody-conjugated nanoPMOs as quantified by dSTORM imaging plays a key role in prostate cancer cell labeling: oriented antibody is more effective than random ones, while high multivalency is also effective. The higher biodegradability and cancer cell-targeting properties of nanorods conjugated with oriented antibody (EAB4H) effectively deliver the anticancer drug doxorubicin to cancer cells, exhibiting potent anticancer effects.

In the last decade, point accumulation for imaging in nanoscale topography (PAINT) has emerged as a versatile tool for single-molecule localization microscopy (SMLM). Currently, DNA-PAINT is the most widely used, in which a transient stochastically binding DNA docking-imaging pair is used to reconstruct specific characteristics of biological or synthetic materials on a single-molecule level. Slowly, the need for PAINT probes that are not dependent on DNA has emerged. These probes can be based on (i) endogenous interactions, (ii) engineered binders, (iii) fusion proteins, or (iv) synthetic molecules and provide complementary applications for SMLM. Therefore, researchers have been expanding the PAINT toolbox with new probes. In this review, we provide an overview of the currently existing probes that go beyond DNA and their applications and challenges.

Nanoparticles (NPs) are used to encapsulate therapeutic cargos and deliver them specifically to the target site. The intracellular trafficking of NPs dictates the NP-cargo distribution within different cellular compartments, and thus governs their efficacy and safety. Knowledge in this field is crucial to understand their biological fate and improve their rational design. However, there is a lack of methods that allow precise localization and quantification of individual NPs within distinct cellular compartments simultaneously. Here, we address this issue by proposing a correlative light and electron microscopy (CLEM) method combining direct stochastic optical reconstruction microscopy (dSTORM) and transmission electron microscopy (TEM). We aim at combining the advantages of both techniques to precisely address NP localization in the context of the cell ultrastructure. Individual fluorescently-labelled poly(lactide-co-glycolide)-poly(ethylene glycol) (PLGA-PEG) NPs were directly visualized by dSTORM and assigned to cellular compartments by TEM. We first tracked NPs along the endo-lysosomal pathway at different time points, then demonstrated the effect of chloroquine on their intracellular distribution (i.e. endosomal escape). The proposed protocol can be applied to fluorescently labelled NPs and/or cargo, including those not detectable by TEM alone. Our studies are of great relevance to obtain important information on NP trafficking, and crucial for the design of more complex nanomaterials aimed at cytoplasmic/nucleic drug delivery.

The exploitation of low-affinity molecular interactions in protein labeling is an emerging topic in optical microscopy. Such non-covalent and low-affinity interactions can be realized with various concepts from chemistry and for different molecule classes, and lead to a constant renewal of fluorescence signals at target sites. Further benefits are a versatile use across microscopy methods, in 3D, live and many-target applications. In recent years, several classes of low-affinity labels were developed and a variety of powerful applications demonstrated. Still, this research field is underdeveloped, while the potential is huge.

Biodegradable periodic mesoporous organosilica nanoparticles (nanoPMOs) are widely used as responsive drug delivery platforms for targeted chemotherapy of cancer. However, the evaluation of their properties such as surface functionality and biodegradability is still challenging, which has a significant impact on the efficiency of chemotherapy. In this study, we have applied direct stochastic optical reconstruction microscopy (dSTORM), a single-molecule super-resolution microscopy technique, to quantify the degradation of nanoPMOs triggered by glutathione and the multivalency of antibody-conjugated nanoPMOs. Subsequently, the effect of these properties on cancer cell targeting, drug loading and release capability, and anticancer activity is also studied. Due to the higher spatial resolution at the nanoscale, dSTORM imaging is able to reveal the structural properties (i.e., size and shape) of fluorescent and biodegradable nanoPMOs. The quantification of nanoPMOs' biodegradation using dSTORM imaging demonstrates their excellent structure-dependent degradation behavior at a higher glutathione concentration. The surface functionality of anti-M6PR antibody-conjugated nanoPMOs as quantified by dSTORM imaging plays a key role in prostate cancer cell labeling: oriented antibody is more effective than random ones, while high multivalency is also effective. The higher biodegradability and cancer cell-targeting properties of nanorods conjugated with oriented antibody (EAB4H) effectively deliver the anticancer drug doxorubicin to cancer cells, exhibiting potent anticancer effects.

Barcoding of nano- and micro-particles allows distinguishing multiple targets at the same time within a complex mixture and is emerging as a powerful tool to increase the throughput of many assays. Fluorescent barcoding is one of the most used strategies, where microparticles are labeled with dyes and classified based on fluorescence color, intensity, or other features. Microparticles are ideal targets due to their relative ease of detection, manufacturing, and higher homogeneity. Barcoding is considerably more challenging in the case of nanoparticles (NPs), where their small size results in a lower signal and greater heterogeneity. This is a significant limitation since many bioassays require the use of nano-sized carriers. In this study, we introduce a machine-learning-assisted workflow to write, read, and classify barcoded PLGA-PEG NPs at a single-particle level. This procedure is based on the encapsulation of fluorescent markers without modifying their physicochemical properties (writing), the optimization of their confocal imaging (reading), and the implementation of a machine learning-based barcode reader (classification). We found nanoparticle heterogeneity as one of the main factors that challenges barcode separation, and that information extracted from the dyes' nanoscale confinement effects (such as Förster Resonance Energy Transfer, FRET) can aid barcode identification. Moreover, we provide a guide to reaching the optimal trade-off between the number of simultaneous barcodes and classification accuracy supporting the use of this workflow for a variety of bioassays.

Nanoparticles (NPs) are used to encapsulate therapeutic cargos and deliver them specifically to the target site. The intracellular trafficking of NPs dictates the NP-cargo distribution within different cellular compartments, and thus governs their efficacy and safety. Knowledge in this field is crucial to understand their biological fate and improve their rational design. However, there is a lack of methods that allow precise localization and quantification of individual NPs within distinct cellular compartments simultaneously. Here, we address this issue by proposing a correlative light and electron microscopy (CLEM) method combining direct stochastic optical reconstruction microscopy (dSTORM) and transmission electron microscopy (TEM). We aim at combining the advantages of both techniques to precisely address NP localization in the context of the cell ultrastructure. Individual fluorescently-labelled poly(lactide-co-glycolide)-poly(ethylene glycol) (PLGA-PEG) NPs were directly visualized by dSTORM and assigned to cellular compartments by TEM. We first tracked NPs along the endo-lysosomal pathway at different time points, then demonstrated the effect of chloroquine on their intracellular distribution (i.e. endosomal escape). The proposed protocol can be applied to fluorescently labelled NPs and/or cargo, including those not detectable by TEM alone. Our studies are of great relevance to obtain important information on NP trafficking, and crucial for the design of more complex nanomaterials aimed at cytoplasmic/nucleic drug delivery.

The properties of nanoparticles (NPs) can change upon contact with serum components, occluding the NP surface by forming a biomolecular corona. It is believed that targeted NPs can lose their functionality due to this biological coating, thus losing specificity and selectivity toward target cells and leading to poor therapeutic efficiency. A better understanding of how the biomolecular corona affects NP ligand functionality is needed to maintain NP targeting capabilities. However, techniques that can quantify the functionality of NPs at a single-particle level in a complex medium are limited and often laborious in sample preparation, measurement, and analysis. In this work, the influence of serum exposure on the functionality of antibody-functionalized NPs was quantified using a straightforward total internal reflection fluorescence (TIRF) microscopy method and evaluated in cell uptake studies. The single-particle resolution of TIRF reveals the interparticle functionality heterogeneity and the substantial differences between NPs conjugated with covalent and noncovalent methods. Notably, only NPs covalently conjugated with a relatively high amount of antibodies maintain their functionality to a certain extent and still showed cell specificity and selectivity toward high receptor density cells after incubation in full serum. The presented study emphasizes the importance of single-particle functional characterization of NPs in complex media, contributing to the understanding and design of targeted NPs that retain their cell specificity and selectivity in biologically relevant conditions.

The concept of selective tumor targeting using nanomedicines has been around for decades; however, no targeted nanoparticle has yet reached the clinic. A key bottleneck is the non-selectivity of targeted nanomedicines in vivo, which is attributed to the lack of characterization of their surface properties, especially the ligand number, thereby calling for robust techniques that allow quantifiable outcomes for an optimal design. Multivalent interactions comprise multiple copies of ligands attached to scaffolds, allowing simultaneous binding to receptors, and they play an important role in targeting. As such, ‘multivalent’ nanoparticles facilitate simultaneous interaction of weak surface ligands with multiple target receptors resulting in higher avidity and enhanced cell selectivity. Therefore, the study of weak binding ligands for membrane-exposed biomarkers is crucial for the successful development of targeted nanomedicines. Here we carried out a study of a cell targeting peptide known as WQP having weak binding affinity for prostate specific membrane antigen, a known prostate cancer biomarker. We evaluated the effect of its multivalent targeting using polymeric NPs over its monomeric form on the cellular uptake in different prostate cancer cell lines. We developed a method of specific enzymatic digestion to quantify the number of WQPs on NPs having different surface valencies and observed that increasing valencies resulted in a higher cellular uptake of WQP-NPs over the peptide alone. We also found that WQP-NPs showed higher uptake in PSMA over-expressing cells, attributed to a stronger avidity for selective PSMA targeting. This kind of strategy can be useful for improving the binding affinity of a weak ligand as a means for selective tumor targeting.

Characterization of the number and distribution of biological molecules on 2D surfaces is of foremost importance in biology and biomedicine. Synthetic surfaces bearing recognition motifs are a cornerstone of biosensors, while receptors on the cell surface are critical/vital targets for the treatment of diseases. However, the techniques used to quantify their abundance are qualitative or semi-quantitative and usually lack sensitivity, accuracy, or precision. Detailed herein a simple and versatile workflow based on super-resolution microscopy (DNA-PAINT) was standardized to improve the quantification of the density and distribution of molecules on synthetic substrates and cell membranes. A detailed analysis of accuracy and precision of receptor quantification is presented, based on simulated and experimental data. We demonstrate enhanced accuracy and sensitivity by filtering out non-specific interactions and artifacts. While optimizing the workflow to provide faithful counting over a broad range of receptor densities. We validated the workflow by specifically quantifying the density of docking strands on a synthetic sensor surface and the densities of PD1 and EGF receptors (EGFR) on two cellular models.

The concept of selective tumor targeting using nanomedicines has been around for decades; however, no targeted nanoparticle has yet reached the clinic. A key bottleneck is the non-selectivity of targeted nanomedicines in vivo, which is attributed to the lack of characterization of their surface properties, especially the ligand number, thereby calling for robust techniques that allow quantifiable outcomes for an optimal design. Multivalent interactions comprise multiple copies of ligands attached to scaffolds, allowing simultaneous binding to receptors, and they play an important role in targeting. As such, 'multivalent' nanoparticles facilitate simultaneous interaction of weak surface ligands with multiple target receptors resulting in higher avidity and enhanced cell selectivity. Therefore, the study of weak binding ligands for membrane-exposed biomarkers is crucial for the successful development of targeted nanomedicines. Here we carried out a study of a cell targeting peptide known as WQP having weak binding affinity for prostate specific membrane antigen, a known prostate cancer biomarker. We evaluated the effect of its multivalent targeting using polymeric NPs over its monomeric form on the cellular uptake in different prostate cancer cell lines. We developed a method of specific enzymatic digestion to quantify the number of WQPs on NPs having different surface valencies and observed that increasing valencies resulted in a higher cellular uptake of WQP-NPs over the peptide alone. We also found that WQP-NPs showed higher uptake in PSMA over-expressing cells, attributed to a stronger avidity for selective PSMA targeting. This kind of strategy can be useful for improving the binding affinity of a weak ligand as a means for selective tumor targeting.

Degradable polymeric micelles are promising drug delivery systems due to their hydrophobic core and responsive design. When applying micellar nanocarriers for tumor delivery, one of the bottlenecks encountered in vivo is the tumor tissue barrier: crossing the dense mesh of cells and the extracellular matrix (ECM). Sometimes overlooked, the extracellular matrix can trap nanoformulations based on charge, size, and hydrophobicity. Here, we used a simple design of a microfluidic chip with two types of ECM and MCF7 spheroids to allow "high-throughput" screening of the interactions between biological interfaces and polymeric micelles. To demonstrate the applicability of the chip, a small library of fluorescently labeled polymeric micelles varying in their hydrophilic shell and hydrophobic core forming blocks was studied. Three widely used hydrophilic shells were tested and compared, namely, poly(ethylene glycol), poly(2-ethyl-2-oxazoline), and poly(acrylic acid), along with two enzymatically degradable dendritic hydrophobic cores (based on hexyl or nonyl end groups). Using ratiometric imaging of unimer:micelle fluorescence and FRAP inside the chip model, we obtained the local assembly state and dynamics inside the chip. Notably, we observed different micelle behaviors in the basal lamina ECM, from avoidance of the ECM structure to binding of the poly(acrylic acid) formulations. Binding to the basal lamina correlated with higher uptake into MCF7 spheroids. Overall, we proposed a simple microfluidic chip containing dual ECM and spheroids for the assessment of the interactions of polymeric nanocarriers with biological interfaces and evaluating nanoformulations' capacity to cross the tumor tissue barrier.