Biocompatible surface functionalization architecture for a diamond quantum sensor.

Quantum metrology enables some of the most precise measurements. In the life sciences, diamond-based quantum sensing has led to a new class of biophysical sensors and diagnostic devices that are being investigated as a platform for cancer screening and ultrasensitive immunoassays. However, a broader application in the life sciences based on nanoscale NMR spectroscopy has been hampered by the need to interface highly sensitive quantum bit (qubit) sensors with their biological targets. Here, we demonstrate an approach that combines quantum engineering with single-molecule biophysics to immobilize individual proteins and DNA molecules on the surface of a bulk diamond crystal that hosts coherent nitrogen vacancy qubit sensors. Our thin (sub-5 nm) functionalization architecture provides precise control over the biomolecule adsorption density and results in near-surface qubit coherence approaching 100 µs. The developed architecture remains chemically stable under physiological conditions for over 5 d, making our technique compatible with most biophysical and biomedical applications.

Broadband Dynamics of Ubiquitin by Anionic and Cationic Nanoparticle Assisted NMR Spin Relaxation.

The quantitative and comprehensive description of the internal dynamics of proteins is critical for understanding their function. Nanoparticle-assisted 15 N NMR spin relaxation spectroscopy is a new method for the observation of picosecond to microsecond dynamics of proteins when transiently interacting with the surface of the nanoparticles (NPs). The method is applied here to the protein ubiquitin in the presence of anionic and cationic silica NPs (SNPs) of different sizes. The backbone dynamics profiles are reproducible and strikingly similar to each other, indicating that specific protein-SNP interactions are unimportant. The dynamics profiles closely match the sub-nanosecond dynamics S2 values observed by model-free analysis of standard 15 N relaxation of ubiquitin in free solution, indicating that the bulk of the ubiquitin backbone dynamics in solution is confined to sub-nanosecond timescales and, hence, it is dynamically more restrained than previous NMR studies have suggested.

Degree of N-Methylation of Nucleosides and Metabolites Controls Binding Affinity to Pristine Silica Surfaces.

Biological molecules interact with silica (SiO2) surfaces with binding affinities that greatly vary depending on their physical-chemical properties. However, the quantitative characterization of biological compounds adsorbed on silica surfaces, especially of compounds involved in fast, reversible interactions, has been challenging, and the driving forces are not well understood. Here, we show how carbon-13 NMR spin relaxation provides quantitative atomic-detail information about the transient molecular binding to pristine silica surfaces, represented by colloidally dispersed silica nanoparticles (SNPs). Based on the quantitative analysis of almost two dozen biological molecules, we find that the addition of N-methyl motifs systematically increases molecular binding affinities to silica in a nearly quantitatively predictable manner. Among the studied compounds are methylated nucleosides, which are common in epigenetic signaling in nucleic acids. The quantitative understanding of N-methylation may open up new ways to detect and separate methylated nucleic acids or even regulate their cellular functions.

Quantitative Cooperative Binding Model for Intrinsically Disordered Proteins Interacting with Nanomaterials.

Intrinsically disordered proteins (IDPs) can display a broad spectrum of binding modes and highly variable binding affinities when interacting with both biological and nonbiological materials. A quantitative model of such behavior is important for the better understanding of the function of IDPs when encountering inorganic nanomaterials with the potential to control their behavior in vivo and in vitro. Depending on their amino acid composition and chain length, binding properties can vary strongly between different IDPs. Moreover, due to differences in the physical chemical properties of clusters of amino acid residues along the IDP primary sequence, individual residues can adopt a wide range of bound state populations. Quantitative experimental binding affinities with synthetic silica nanoparticles (SNPs) at residue-level resolution, which were obtained for a set of IDPs by solution NMR relaxation experiments, are explained here by a first-principle analytical statistical mechanical model termed SILC. SILC quantitatively predicts residue-specific binding affinities to nanoparticles and it expresses binding cooperativity as the cumulative result of pairwise residue effects. The model, which was parametrized for anionic SNPs and applied to experimental data of four IDP systems with distinctive binding behavior, successfully predicts differences in overall binding affinities, fine details of IDP-SNP affinity profiles, and site-directed mutagenesis effects with a spatial resolution at the individual residue level. The SILC model provides an analytical description of such types of fuzzy IDP-SNP complexes and may help advance understanding nanotoxicity and in vivo targeting of IDPs by specifically designed nanomaterials.

Functional protein dynamics on uncharted time scales detected by nanoparticle-assisted NMR spin relaxation.

Protein function depends critically on intrinsic internal dynamics, which is manifested in distinct ways, such as loop motions that regulate protein recognition and catalysis. Under physiological conditions, dynamic processes occur on a wide range of time scales from subpicoseconds to seconds. Commonly used NMR spin relaxation in solution provides valuable information on very fast and slow motions but is insensitive to the intermediate nanosecond to microsecond range that exceeds the protein tumbling correlation time. Presently, very little is known about the nature and functional role of these motions. It is demonstrated here how transverse spin relaxation becomes exquisitely sensitive to these motions at atomic resolution when studying proteins in the presence of nanoparticles. Application of this novel cross-disciplinary approach reveals large-scale dynamics of loops involved in functionally critical protein-protein interactions and protein-calcium ion recognition that were previously unobservable.

Quantitative Binding Behavior of Intrinsically Disordered Proteins to Nanoparticle Surfaces at Individual Residue Level.

The quantitative and predictive understanding how intrinsically disordered proteins (IDPs) interact with engineered nanoparticles has potentially important implications for new therapeutics as well as nanotoxicology. Based on a recently developed solution 15 N NMR relaxation approach, the interactions between four representative IDPs with silica nanoparticles are reported at atomic detail. Each IDP possesses distinct binding modes, which can be quantitatively explained by the local amino-acid residue composition using a "free residue interaction model". The model was parameterized using the binding affinities of free proteinogenic amino acids along with long-range effects, derived by site-specific mutagenesis, that exponentially scale with distance along the primary sequence. The model, which is accessible through a web server, can be applied to predict the residue-specific binding affinities of a large number of IDPs.

The Intracellular Loop of the Na+/Ca2+ Exchanger Contains an "Awareness Ribbon"-Shaped Two-Helix Bundle Domain.

The Na+/Ca2+ exchanger (NCX) is a ubiquitous single-chain membrane protein that plays a major role in regulating the intracellular Ca2+ homeostasis by the counter transport of Na+ and Ca2+ across the cell membrane. Other than its prokaryotic counterpart, which contains only the transmembrane domain and is self-sufficient as an active ion transporter, the eukaryotic NCX protein possesses in addition a large intracellular loop that senses intracellular calcium signals and controls the activation of ion transport across the membrane. This provides a necessary layer of regulation for the more complex function of eukaryotic cells. The Ca2+ sensor in the intracellular loop is known as the Ca2+-binding domain (CBD12). However, how the signaling of the allosteric intracellular Ca2+ binding propagates and results in transmembrane ion transportation still lacks a detailed explanation. Further structural and dynamics characterization of the intracellular loop flanking both sides of CBD12 is therefore imperative. Here, we report the identification and characterization of another structured domain that is N-terminal to CBD12 in the intracellular loop using solution nuclear magnetic resonance (NMR) spectroscopy. The atomistic structure of this domain reveals that two tandem long α-helices, connected by a short linker, form a stable crossover two-helix bundle (THB), resembling an "awareness ribbon". Considering the highly conserved amino acid sequence of the THB domain, the detailed structural and dynamics properties of the THB domain will be common among NCXs from different species and will contribute toward the understanding of the regulatory mechanism of eukaryotic Na+/Ca2+ exchangers.

Nanoparticle-Assisted Metabolomics.

Understanding and harnessing the interactions between nanoparticles and biological molecules is at the forefront of applications of nanotechnology to modern biology. Metabolomics has emerged as a prominent player in systems biology as a complement to genomics, transcriptomics and proteomics. Its focus is the systematic study of metabolite identities and concentration changes in living systems. Despite significant progress over the recent past, important challenges in metabolomics remain, such as the deconvolution of the spectra of complex mixtures with strong overlaps, the sensitive detection of metabolites at low abundance, unambiguous identification of known metabolites, structure determination of unknown metabolites and standardized sample preparation for quantitative comparisons. Recent research has demonstrated that some of these challenges can be substantially alleviated with the help of nanoscience. Nanoparticles in particular have found applications in various areas of bioanalytical chemistry and metabolomics. Their chemical surface properties and increased surface-to-volume ratio endows them with a broad range of binding affinities to biomacromolecules and metabolites. The specific interactions of nanoparticles with metabolites or biomacromolecules help, for example, simplify metabolomics spectra, improve the ionization efficiency for mass spectrometry or reveal relationships between spectral signals that belong to the same molecule. Lessons learned from nanoparticle-assisted metabolomics may also benefit other emerging areas, such as nanotoxicity and nanopharmaceutics.

Emerging new strategies for successful metabolite identification in metabolomics.

This review discusses strategies for the identification of metabolites in complex biological mixtures, as encountered in metabolomics, which have emerged in the recent past. These include NMR database-assisted approaches for the identification of commonly known metabolites as well as novel combinations of NMR and MS analysis methods for the identification of unknown metabolites. The use of certain chemical additives to the NMR tube can permit identification of metabolites with specific physical chemical properties.

Nanoparticle-Assisted Removal of Protein in Human Serum for Metabolomics Studies.

Among human body fluids, serum plays a key role for diagnostic tests and, increasingly, for metabolomics analysis. However, the high protein content of serum poses significant challenges for nuclear magnetic resonance (NMR)-based metabolomics studies because it can strongly interfere with metabolite signal detection and quantitation. Although several methods for protein removal have been proposed, including ultrafiltration and organic-solvent-induced protein precipitation, there is currently no standard operating procedure for the elimination of protein from human serum samples. Here, we introduce novel procedures for the removal of protein from serum by the addition of nanoparticles. It is demonstrated how serum protein can be efficiently, cost-effectively, and environmentally friendly removed at physiological pH (pH 7.4) through attractive interactions with silica nanoparticles. It is further shown how serum can be processed with nanoparticles prior to ultrafiltration or organic-solvent-induced protein precipitation for optimal protein removal. After examination of all of the procedures, the combination of nanoparticle treatment and ultrafiltration is found to have a minimal effect on the metabolite content, leading to remarkably clean homo- and heteronuclear NMR spectra of the serum metabolome that compare favorably to other methods for protein removal.

Residue-Specific Interactions of an Intrinsically Disordered Protein with Silica Nanoparticles and their Quantitative Prediction.

Elucidation of the driving forces that govern interactions between nanoparticles and intrinsically disordered proteins (IDP) is important for the understanding of the effect of nanoparticles in living systems and for the design of new nanoparticle-based assays to monitor health and combat disease. The quantitative interaction profile of the intrinsically disordered transactivation domain of p53 and its mutants with anionic silica nanoparticles is reported at atomic resolution using nuclear magnetic spin relaxation experiments. These profiles are analyzed with a novel interaction model that is based on a quantitative nanoparticle affinity scale separately derived for the 20 natural amino acids. The results demonstrate how the interplay of attractive and repulsive Coulomb interactions with hydrophobic effects is responsible for the sequence-dependent binding of a disordered protein to nanoparticles.

Use of Charged Nanoparticles in NMR-Based Metabolomics for Spectral Simplification and Improved Metabolite Identification.

Metabolomics aims at a complete characterization of all metabolites in biological samples in terms of both their identities and concentrations. Because changes of metabolites and their concentrations are a direct reflection of cellular activity, it allows for a better understanding of cellular processes and function to be obtained. Although NMR spectroscopy is routinely applied to complex biological mixtures without purification, overlapping NMR peaks often pose a challenge for the comprehensive and accurate identification of the underlying metabolites. To address this problem, we present a novel nanoparticle-based strategy that differentiates between metabolites based on their electric charge. By adding electrically charged silica nanoparticles to the solution NMR sample, metabolites of opposite charge bind to the nanoparticles and their NMR signals are weakened or entirely suppressed due to peak broadening caused by the slow rotational tumbling of the nanometer-sized nanoparticles. Comparison of the edited with the original spectrum significantly facilitates analysis and reduces ambiguities in the identification of metabolites. This method makes NMR directly sensitive to the detection of molecular charges at constant pH, as demonstrated here both for model mixtures and human urine. The simplicity of the approach should make it useful for a wide range of metabolomics applications.