Nanoparticle protein corona evolution: from biological impact to biomarker discovery

On the behavior of sub-micrometer polystyrene particles subjected to AC insulator-based dielectrophoresis

Polymer beads, especially polystyrene particles, have been extensively used as model species in insulator-based dielectrophoresis (iDEP) studies. Their use in alternating current iDEP (AC-iDEP) is less explored; however, an assessment in the low-frequency regime (≤10 kHz) allows to link surface conduction effects with the surface properties of polymer particles. Here, we provide a case study for various experimental conditions assessing sub-micrometer polystyrene particles with AC-iDEP and link to accepted surface conduction theory to predict and experimentally verify the observed AC-iDEP trapping behavior based on apparent zeta potential and solution conductivity. We find excellent agreement with the theoretical predictions, but also the occurrence of concentration polarization electroosmotic flow under the studied conditions, which have the potential to confound acting dielectrophoresis conditions. Furthermore, we study a case relevant to the assessment of microplastics in human and animal body fluids by mimicking the protein adsorption of high abundant proteins in blood by coating polystyrene beads with bovine serum albumin, a highly abundant protein in blood. Theoretical predictions and experimental observations confirm a difference in observed AC-iDEP behavior between coated and non-coated particles, which might be exploited for future studies of microplastics in blood to assess their exposure to humans and animals.

Biomolecular Corona of Gold Nanoparticles: The Urgent Need for Strong Roots to Grow Strong Branches

Gold nanoparticles (GNPs) are largely employed in diagnostics/biosensors and are among the most investigated nanomaterials in biology/medicine. However, few GNP-based nanoformulations have received FDA approval to date, and promising in vitro studies have failed to translate to in vivo efficacy. One key factor is that biological fluids contain high concentrations of proteins, lipids, sugars, and metabolites, which can adsorb/interact with the GNP's surface, forming a layer called biomolecular corona (BMC). The BMC can mask prepared functionalities and target moieties, creating new surface chemistry and determining GNPs' biological fate. Here, the current knowledge is summarized on GNP-BMCs, analyzing the factors driving these interactions and the biological consequences. A partial fingerprint of GNP-BMC analyzing common patterns of composition in the literature is extrapolated. However, a red flag is also risen concerning the current lack of data availability and regulated form of knowledge on BMC. Nanomedicine is still in its infancy, and relying on recently developed analytical and informatic tools offers an unprecedented opportunity to make a leap forward. However, a restart through robust shared protocols and data sharing is necessary to obtain "stronger roots". This will create a path to exploiting BMC for human benefit, promoting the clinical translation of biomedical nanotools.

Serum Protein Fishing for Machine Learning-Boosted Diagnostic Classification of Small Nodules of Lung

Diagnosis of benign and malignant small nodules of the lung remains an unmet clinical problem which is leading to serious false positive diagnosis and overtreatment. Here, we developed a serum protein fishing-based spectral library (ProteoFish) for data independent acquisition analysis and a machine learning-boosted protein panel for diagnosis of early Non-Small Cell Lung Cancer (NSCLC) and classification of benign and malignant small nodules. We established an extensive NSCLC protein bank consisting of 297 clinical subjects. After testing 5 feature extraction algorithms and six machine learning models, the Lasso algorithm for a 15-key protein panel selection and Random Forest was chosen for diagnostic classification. Our random forest classifier achieved 91.38% accuracy in benign and malignant small nodule diagnosis, which is superior to the existing clinical assays. By integrating with machine learning, the 15-key protein panel may provide insights to multiplexed protein biomarker fishing from serum for facile cancer screening and tackling the current clinical challenge in prospective diagnostic classification of small nodules of the lung.

Evaluation of Interfacial Structure of Self-Assembled Nanoparticle Layers: Use of Standard Deviation between Calculated and Experimental Drop Profiles as a Novel Method

The self-assembly of nanoparticles (NPs) at interfaces is currently a topic of increasing interest due to numerous applications in food technology, pharmaceuticals, cosmetology, and oil recovery. It is possible to create tunable interfacial structures with desired characteristics using tailored nanoparticles that can be precisely controlled with respect to shape, size, and surface chemistry. To address these functionalities, it is essential to develop techniques to study the properties of the underlying structure. In this work, we propose an experimental approach utilizing the standard deviation of drop profiles calculated by the Laplace equation from experimental drop profiles (STD), as an alternative to the Langmuir trough or precise microscopic methods, to detect the initiation of closely packed conditions and the collapse of the adsorbed layers of CTAB-nanosilica complexes. The experiments consist of dynamic surface/interfacial tension measurements using drop profile analysis tensiometry (PAT) and large-amplitude drop surface area compression/expansion cycles. The results demonstrate significant changes in STD values at the onset of the closely packed state of nanoparticle-surfactant complexes and the monolayer collapse. The STD trend was explained in detail and shown to be a powerful tool for analyzing the adsorption and interfacial structuring of nanoparticles. Different collapse mechanisms were reported for NP monolayers at the liquid/liquid and air/liquid interfaces. We show that the interfacial tension (IFT) is solely dependent on the extent of interfacial coverage by nanoparticles, while the surfactants regulate only the hydrophobicity of the self-assembled complexes. Also, the irreversible adsorption of nanoparticles and the increasing number of adsorbed complexes after the collapse were observed by performing consecutive drop surface compression/expansion cycles. In addition to a qualitative characterization of adsorption layers, the potential of a quantitative calculation of the parameter STD such as the number of adsorbed nanoparticles at the interface and the distance between them at different states of the interfacial layer was discussed.

Designed Nanomaterials-Assisted Proteomics and Metabolomics Analysis for In Vitro Diagnosis

In vitro diagnosis (IVD) is pivotal in modern medicine, enabling early disease detection and treatment optimization. Omics technologies, particularly proteomics and metabolomics, offer profound insights into IVD. Despite its significance, omics analyses for IVD face challenges, including low analyte concentrations and the complexity of biological environments. In addition, the direct omics analysis by mass spectrometry (MS) is often hampered by issues like large sample volume requirements and poor ionization efficiency. Through manipulating their size, surface charge, and functionalization, as well as the nanoparticle-fluid incubation conditions, nanomaterials have emerged as a promising solution to extract biomolecules and enhance the desorption/ionization efficiency in MS detection. This review delves into the last five years of nanomaterial applications in omics, focusing on their role in the enrichment, separation, and ionization analysis of proteins and metabolites for IVD. It aims to provide a comprehensive update on nanomaterial design and application in omics, highlighting their potential to revolutionize IVD.

Peptide Orientation Strongly Affected by the Nanoparticle Size as Revealed by Sum Frequency Scattering Spectroscopy

The orientation of proteins at interfaces has a profound effect on the function of proteins. For nanoparticles (NPs) in a biological environment, protein orientation determines the toxicity, function, and identity of the NP. Thus, understanding how proteins orientate at NP surfaces is a critical parameter in controlling NP biochemistry. While planar surfaces are often used to model NP interfaces for protein orientation studies, it has been shown recently that proteins can orient very differently on NP surfaces. This study uses sum frequency scattering vibrational spectroscopy of the model helical leucine-lysine (LK) peptide on NPs of different sizes to determine the cause for the orientation effects. The data show that, for low dielectric constant materials, the orientation of the helical LK peptide is a function of the coulombic forces between peptides across different particle volumes. This finding strongly suggests that flat model systems are only of limited use for determining protein orientation at NP interfaces and that charge interactions should be considered when designing medical NPs or assessing NP biocompatibility.

Establishment and clinical application evaluations of a deep mining strategy of plasma proteomics based on nanomaterial protein coronas

Research on plasma proteomics has received extensive attention, because human plasma is an important sample for disease biomarker research due to its easy clinical accessibility and richness in biological information. Plasma samples contain a large number of leaked proteins from different tissues in the body, immune proteins and communication signal proteins. However, MS signal suppression from high-abundance proteins results in a large number of proteins that are present in low abundance in plasma not being detected by the LC-MS method. This situation makes it more difficult to study neurological diseases, where tissue sampling is difficult and body fluid samples such as plasma or cerebrospinal fluid are both affected by signal suppression. A large number of methods have been developed to deeply mine plasma proteomics information; however, their application limitations remain to some extent. Traditional immuno- or affinity-based depletion, fractionation and subproteome enrichment methods cannot meet the challenges of large clinical cohort applications due to limited time efficiency. In this study, a deep mining strategy of plasma proteomics was established by combing the protein corona formed by deep mining beads (DMB beads, hereafter referred to as magnetic covalent organic frameworks Fe3O4@TpPa-1), DIA-MS detection and the DIA-NN library searching method. By optimizing the enrichment step, mass spectrometry acquisition and data processing, the evaluation results of the deep mining strategy showed the following: depth, the strategy identified and quantified results of 2000+ proteins per plasma sample; stability, more than 87% of the enriched low-abundance proteins had CV < 20%; accuracy, good agreement between measured and theoretical values (1.81/2, 8.68/10, 38.36/50) for the gradient addition of E. coli proteins to a plasma sample; time efficiency, the processing time was reduced from >12h in the traditional method to <5h (incubation 30 min, washing 15 min, reductive/alkylation/digestion/desalting 4 h), and more importantly, 96 samples can be processed simultaneously in combination with the magnetic module of the automated device. The optimal strategy enables greater enrichment of neurological disease-related proteins, including SNCA and BDNF. Finally, the deep mining strategy was applied in a pilot study of multiple system atrophy (MSA) for biomarker discovery. The results showed that a total of 215 proteins were upregulated and 184 proteins were downregulated (p < 0.05) in the MSA group compared with the healthy control group. Eighteen proteins of these differentially expressed proteins were reported to be associated with neurological diseases or expressed specifically in brain tissue, 8 and 4 of which have reference concentrations of μg/L and ng/L, respectively. The alterations of ENPP2 and SLC2A1/Glut1 were reanalyzed by ELISA, further supporting the results of mass spectrometry. In conclusion, the results of the evaluation and application of the deep mining strategy showed promise for clinical research applications.

Cholesterol modulates the physiological response to nanoparticles by changing the composition of protein corona

Nanoparticles (NPs) in biological fluids form a layer of biomolecules known as the protein corona. The protein corona has been shown to determine the biological identity and in vivo fate of NPs, but whether and how metabolites, especially disease-related small molecules, regulate the protein corona and subsequently impact NP fate in vivo is relatively poorly understood. Here we report on the effects of cholesterol on the generation of protein corona and subsequent effects. We find that high levels of cholesterol, as in hypercholesterolemia, result in a protein corona with enriched apolipoproteins and reduced complement proteins by altering the binding affinity of the proteins to the NPs. The cholesterol-mediated protein corona can induce stronger inflammatory responses to NPs in macrophages and promote the cellular uptake of NPs in hepatocytes by enhancing the recognition of lipoprotein receptors when compared with normal protein corona. The result of in vivo biodistribution assays shows that, compared with healthy mice, NPs in hypercholesterolemic mice were more likely to be delivered to the liver, spleen and brain, and less likely to be delivered to the lungs. Our findings reveal that the metabolome profile is an unexploited factor impacting the target efficacy and safety of nanomedicines, providing a way to develop personalized nanomedicines by harnessing disease-related metabolites.

Cellular Alterations in Carbohydrate and Lipid Metabolism Due to Interactions with Nanomaterials

Nanoparticles (NPs) have unique physicochemical properties that are useful for a broad range of biomedical and industrial applications; nevertheless, increasing concern exists about their biosafety. This review aims to focus on the implications of nanoparticles in cellular metabolism and their outcomes. In particular, some NPs have the ability to modify glucose and lipid metabolism, and this feature is especially interesting to treat diabetes and obesity and to target cancer cells. However, the lack of specificity to reach target cells and the toxicological evaluation of nontargeted cells can potentially induce detrimental side effects, closely related to inflammation and oxidative stress. Therefore, identifying the metabolic alterations caused by NPs, independent of their application, is highly needed. To our knowledge, this increase would lead to the improvement and safer use with a reduced toxicity, increasing the number of available NPs for diagnosis and treatment of human diseases.

Influence of Green Synthesized Zinc Oxide Nanoparticles on Molecular Interaction and Comparative Binding of Azure Dye with Chymotrypsin: Novel Nano-Conjugate for Cancer Phototherapy

Till date, different types of conventional drugs have been used to fight tumors. However, they have significant flaws, including their usage being constrained because of their low bioavailability, poor supply, and serious side effects. The modern combination therapy has been viewed as a potent strategy for treating serious illnesses, including cancer-type feared diseases. The nanoparticles are a promising choice for cancer therapeutic and diagnostic applications because of their fascinating optoelectronic and physicochemical features. Among the metallic nanoparticles, Zinc oxide nanoparticles possess interesting physicochemical and anti-cancer characteristics, such as ROS generation, high retention, enhanced permeability etc., making them attractive candidates for the treatment and diagnosis of cancer. Zinc oxide nanoparticles showed anti-cancer property via excessive reactive oxygen species (ROS) production, and by the destruction of mitochondrial membrane. Here, we have synthesized organic/inorganic hybrid nanosystem composed of chymotrypsin protein (Chymo) with AzureC (AzC) conjugated with Zinc oxide nanoparticles (ZnONPs). The conjugation of AzureC with ZnONPs was confirmed by transmission electron microscopy (TEM), zeta potential, and dynamic light scattering (DLS) experiment. The interaction of Chymo with AzC alone and AzC-ZnONPs was investigated, and it was observed that the interaction was enhanced in the presence of ZnONPs, which was concluded by the results obtained from different spectroscopic techniques such as UV-Visible spectroscopy, fluorescence spectroscopy and circular dichroism in combination with molecular docking. UV-Visible spectroscopic studies and the corresponding binding parameters showed that the binding of AzC-ZnONPs complex with Chymo is much higher than that of AzC alone. Moreover, the fluorescence measurement showed enhancement in static quenching during titration of Chymo with AzC-ZnONPs as compared to dye alone. In addition to this, circular dichroism results show that the dye and dye-NPs conjugate do not cause much structural change in α-Chymo. The molecular docking and thermodynamic studies showed the predominance of hydrogen bonding, Van der Waal force, and hydrophobic forces during the interactions. After correlation of all the data, interaction of Chymo with AzC-ZnONPs complex showed strong interaction as compared to dye alone. The moderate binding with chymo without any alteration in the structure makes it desirable for the distribution and pharmacokinetics. In addition, the in vitro cytotoxicity of the AzC-ZnONPs was demonstrated on A-549 adenocarcinoma cell line. Our findings from physiochemical investigations suggested that the chymotrypsin coated AzC conjugated ZnONPs could be used as the novel nanoconjugates for various cancer phototherapies.

A highly efficient protein corona-based proteomic analysis strategy for the discovery of pharmacodynamic biomarkers

The composition of serum is extremely complex, which complicates the discovery of new pharmacodynamic biomarkers via serum proteome for disease prediction and diagnosis. Recently, nanoparticles have been reported to efficiently reduce the proportion of high-abundance proteins and enrich low-abundance proteins in serum. Here, we synthesized a silica-coated iron oxide nanoparticle and developed a highly efficient and reproducible protein corona (PC)-based proteomic analysis strategy to improve the range of serum proteomic analysis. We identified 1,070 proteins with a median coefficient of variation of 12.56% using PC-based proteomic analysis, which was twice the number of proteins identified by direct digestion. There were also more biological processes enriched with these proteins. We applied this strategy to identify more pharmacodynamic biomarkers on collagen-induced arthritis (CIA) rat model treated with methotrexate (MTX). The bioinformatic results indicated that 485 differentially expressed proteins (DEPs) were found in CIA rats, of which 323 DEPs recovered to near normal levels after treatment with MTX. This strategy can not only help enhance our understanding of the mechanisms of disease and drug action through serum proteomics studies, but also provide more pharmacodynamic biomarkers for disease prediction, diagnosis, and treatment.

Nano-omics: nanotechnology-based multidimensional harvesting of the blood-circulating cancerome

Over the past decade, the development of 'simple' blood tests that enable cancer screening, diagnosis or monitoring and facilitate the design of personalized therapies without the need for invasive tumour biopsy sampling has been a core ambition in cancer research. Data emerging from ongoing biomarker development efforts indicate that multiple markers, used individually or as part of a multimodal panel, are required to enhance the sensitivity and specificity of assays for early stage cancer detection. The discovery of cancer-associated molecular alterations that are reflected in blood at multiple dimensions (genome, epigenome, transcriptome, proteome and metabolome) and integration of the resultant multi-omics data have the potential to uncover novel biomarkers as well as to further elucidate the underlying molecular pathways. Herein, we review key advances in multi-omics liquid biopsy approaches and introduce the 'nano-omics' paradigm: the development and utilization of nanotechnology tools for the enrichment and subsequent omics analysis of the blood-circulating cancerome.

Comprehensive and systematic characterization of multi-functionalized cisplatin nano-conjugate: from the chemistry and proteomic biocompatibility to the animal model

Background

Nowadays, nanoparticles (NPs) have evolved as multifunctional systems combining different custom anchorages which opens a wide range of applications in biomedical research. Thus, their pharmacological involvements require more comprehensive analysis and novel nanodrugs should be characterized by both chemically and biological point of view. Within the wide variety of biocompatible nanosystems, iron oxide nanoparticles (IONPs) present mostly of the required features which make them suitable for multifunctional NPs with many biopharmaceutical applications.

Results

Cisplatin-IONPs and different functionalization stages have been broadly evaluated. The potential application of these nanodrugs in onco-therapies has been assessed by studying in vitro biocompatibility (interactions with environment) by proteomics characterization the determination of protein corona in different proximal fluids (human plasma, rabbit plasma and fetal bovine serum),. Moreover, protein labeling and LC–MS/MS analysis provided more than 4000 proteins de novo synthetized as consequence of the nanodrugs presence defending cell signaling in different tumor cell types (data available via ProteomeXchanges with identified PXD026615). Further in vivo studies have provided a more integrative view of the biopharmaceutical perspectives of IONPs.

Conclusions

Pharmacological proteomic profile different behavior between species and different affinity of protein coating layers (soft and hard corona). Also, intracellular signaling exposed differences between tumor cell lines studied. First approaches in animal model reveal the potential of theses NPs as drug delivery vehicles and confirm cisplatin compounds as strengthened antitumoral agents.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12951-022-01546-y.

The Janus of Protein Corona on nanoparticles for tumor targeting, immunotherapy and diagnosis

The therapeutics based on nanoparticles (NPs) are considered as the promising strategy for tumor detection and treatment. However, one of the most challenges is the adsorption of biomolecules on NPs after their exposition to biological medium, leading unpredictable in vivo behaviors. The interactions caused by protein corona (PC) will influence the biological fate of NPs in either negative or positive ways, including (i) blood circulation, accumulation and penetration of NPs at targeting sites, and further cellular uptake in tumor targeting delivery; (ii) interactions between NPs and receptors on immune cells for immunotherapy. Besides, PC on NPs could be utilized as new biomarker in tumor diagnosis by identifying the minor change of protein concentration led by tumor growth and invasion in blood. Herein, the mechanisms of these PC-mediated effects will be introduced. Moreover, the recent advances about the strategies will be reviewed to reduce negative effects caused by PC and/or utilize positive effects of PC on tumor targeting, immunotherapy and diagnosis, aiming to provide a reasonable perspective to recognize PC with their applications.