Karthikeshwar Vangala

Gold nanoparticles (AuNPs) are an attractive delivery vector in biomedicine because of their low toxicity and unique electronic and chemical properties. AuNP bioconjugates can be used in many applications, including nanomaterials, biosensing, and drug delivery. While the phenomenon of spontaneous protein–AuNP adsorption is well-known, the structural and mechanistic details of this interaction remain poorly understood. As a result, predicting the orientation and structure of proteins on the nanoparticle surface remains a challenge. New techniques are therefore needed to characterize the structural properties of proteins as they bind to AuNPs. We have developed a straightforward and rapid NMR-based approach to quantitatively characterize the protein–AuNP interaction. This approach is immune to the inner filter effect, which complicates fluorescence measurements, and it can be performed without prior centrifugation of samples. Using a data set of six proteins, ranging in size from 3 to 583 residues, we measured the stoichiometry of binding to AuNPs with a diameter of 15 nm. The stoichiometry of binding can be predicted based on simple geometric considerations assuming that proteins remain globular on the AuNP surface. Using our approach, we find that a protein lacking cysteine residues can be displaced from AuNPs using a small organothiol compound, but proteins with surface cysteines are resistant to displacement. From this data we develop a model for adsorption consisting of three steps: an initial reversible association step, a rearrangement/reorientation step on the AuNP surface, and a final cysteine-dependent “hardening” step, after which binding becomes irreversible.

The role of cysteine residues in the protein binding kinetics and stability on gold nanoparticles (AuNP) was studied using AuNP localized surface plasmon resonance (LSPR) in combination with an organothiol (OT) displacement method. GB3, the third IgG-binding domain of protein G, was used to model protein-AuNP adsorption. While wild-type GB3 (GB30) contains no cysteine residues, bioengineered GB3 variants containing one (GB31) and two (GB32) cysteine residues were also tested. The cysteine content has no significant effect on GB3 binding kinetics with AuNPs, and most protein adsorption occurs within the first few seconds upon protein/AuNP mixing. However, the stability of GB3 on the AuNP surface against OT displacement depends strongly on the cysteine content and the age of the AuNP/GB3 mixture. The GB30 covered AuNPs can be completely destabilized and aggregated by OTs, regardless of the age of the GB30/AuNP mixtures. Long-time incubation of GB31 or GB32 with AuNPs can stabilize AuNPs against the OT adsorption inducted aggregation. This study indicates that multiple forces involved in the GB3/AuNP interaction, and covalent binding between cysteine and AuNP is essential for a stable protein/AuNP complex.

The protein and gold nanoparticle (AuNP) interfacial interaction has broad implications for biological and biomedical applications of AuNPs. In situ characterization of the morphology and structural evolution of protein on AuNPs is difficult. We have found that the protein coating layer formed by bovine serum albumin (BSA) on AuNP is highly permeable to further organothiol adsorption. Using mercaptobenzimidazole (MBI) as a molecular probe, it is found that BSA interaction with AuNP is an exceedingly lengthy process. Structural modification of BSA coating layer on AuNP continues even after 2 days’ aging of the (AuNP/BSA) mixture. While BSA is in a near full monolayer packing on the AuNPs, it passivates only up to 30% of the AuNP surfaces against MBI adsorption. Aging reduces the kinetics of the MBI adsorption. However, even in the most aged BSA-coated AuNP (3 days), 80% of the MBI adsorption occurs within the first 5 min of the MBI addition to the (AuNP/BSA) mixture. The possibility of MBI displacing the adsorbed BSA was excluded with quantitative BSA adsorption studies. Besides MBI, other organothiols including endogenous amino acid thiols (cysteine, homocysteine, and glutathione) were also shown to penetrate through the protein coating layer and be adsorbed onto AuNPs. In addition to providing critical new understanding of the morphology and structural evolution of protein on AuNPs, this work also provides a new venue for preparation of multicomponent composite nanoparticle with applications in drug delivery, cancer imaging and therapy, and material sciences.

Glycomic analysis is an increasingly important field in biological and biomedical research as glycosylation is one of the most important protein post-translational modifications. We have developed a new technique to detect carbohydrates using surface enhanced Raman spectroscopy (SERS) by designing and applying a Rhodamine B derivative as the SERS tag. Using a reductive amination reaction, the Rhodamine-based tag (RT) was successfully conjugated to three model carbohydrates (glucose, lactose, and glucuronic acid). SERS detection limits obtained with a 633 nm HeNe laser were ∼1 nM in concentration for all the RT-carbohydrate conjugates and ∼10 fmol in total sample consumption. The dynamic range of the SERS method is about 4 orders of magnitude, spanning from 1 nM to 5 μM. Ratiometric SERS quantification using isotope-substituted SERS internal references allows comparative quantifications of carbohydrates labeled with RT and deuterium/hydrogen substituted RT tags, respectively. In addition to enhancing the SERS detection of the tagged carbohydrates, the Rhodamine tagging facilitates fluorescence and mass spectrometric detection of carbohydrates. Current fluorescence sensitivity of RT-carbohydrates is ∼3 nM in concentration while the mass spectrometry (MS) sensitivity is about 1 fmol, achieved with a linear ion trap electrospray ionization (ESI)-MS instrument. Potential applications that take advantage of the high SERS, fluorescence, and MS sensitivity of this SERS tagging strategy are discussed for practical glycomic analysis where carbohydrates may be quantified with a fluorescence and SERS technique and then identified with ESI-MS techniques.