Sensitive single-molecule protein quantification and protein complex detection in a microarray format

Single-Molecule Protein Analysis by Centrifugal Droplet Immuno-PCR with Magnetic Nanoparticles

Detecting proteins in ultralow concentrations in complex media is important for many applications but often relies on complicated techniques. Herein, a single-molecule protein analyzer with the potential for high-throughput applications is reported. Gold-coated magnetic nanoparticles with DNA-labeled antibodies were used for target recognition and separation. The immunocomplex was loaded into microdroplets generated with centrifugation. Immuno-PCR amplification of the DNA enabled the quantification of proteins at the level of single molecules. As an example, ultrasensitive detection of α-synuclein, a biomarker for neurodegenerative diseases, is achieved. The limit of detection was determined to be ∼50 aM in buffer and ∼170 aM in serum. The method exhibited high specificity and could be used to analyze post-translational modifications such as protein phosphorylation. This study will inspire wider studies on single-molecule protein detection, especially in disease diagnostics, biomarker discovery, and drug development.

A theoretical analysis of single molecule protein sequencing via weak binding spectra

We propose and theoretically study an approach to massively parallel single molecule peptide sequencing, based on single molecule measurement of the kinetics of probe binding (Havranek, et al., 2013) to the N-termini of immobilized peptides. Unlike previous proposals, this method is robust to both weak and non-specific probe-target affinities, which we demonstrate by applying the method to a range of randomized affinity matrices consisting of relatively low-quality binders. This suggests a novel principle for proteomic measurement whereby highly non-optimized sets of low-affinity binders could be applicable for protein sequencing, thus shifting the burden of amino acid identification from biomolecular design to readout. Measurement of probe occupancy times, or of time-averaged fluorescence, should allow high-accuracy determination of N-terminal amino acid identity for realistic probe sets. The time-averaged fluorescence method scales well to weakly-binding probes with dissociation constants of tens or hundreds of micromolar, and bypasses photobleaching limitations associated with other fluorescence-based approaches to protein sequencing. We argue that this method could lead to an approach with single amino acid resolution and the ability to distinguish many canonical and modified amino acids, even using highly non-optimized probe sets. This readout method should expand the design space for single molecule peptide sequencing by removing constraints on the properties of the fluorescent binding probes.

Ultrasensitive quantification of tumor mRNAs in extracellular vesicles with an integrated microfluidic digital analysis chip

Extracellular vesicles (EVs) present a promising liquid biopsy for cancer diagnosis. However, it remains a daunting challenge to quantitatively measure molecular contents of EVs including tumor-associated mRNAs. Herein, we report a configurable microwell-patterned microfluidic digital analysis platform combined with a dual-probe hybridization assay for PCR-free, single-molecule detection of specific mRNAs in EVs. The microwell array in our device is configurable between the flow-through assay mode for enhanced hybridization capture and tagging of mRNAs and the digital detection mode based on femtoliter-scale enzymatic signal amplification for single-molecule counting of surface-bound targets. Furthermore, a dual-probe hybridization assay has been developed to enhance the sensitivity of the digital single-molecule detection of EV mRNAs. Combining the merits of the chip design and the dual-probe digital mRNA hybridization assay, the integrated microfluidic system has been demonstrated to afford quantitative detection of synthetic GAPDH mRNA with a LOD as low as 20 aM. Using this technology, we quantified the level of GAPDH and EWS-FLI1 mRNAs in EVs derived from two cell lines of peripheral primitive neuroectodermal tumor (PNET), CHLA-9 and CHLA-258. Our measurements detected 64.6 and 43.5 copies of GAPDH mRNA and 6.5 and 0.277 copies of EWS-FLI1 fusion transcripts per 105 EVs derived from CHLA-9 and CHLA-258 cells, respectively. To our knowledge, this is the first demonstration of quantitative measurement of EWS-FLI1 mRNA copy numbers in Ewing Sarcoma (EWS)-derived EVs. These results highlight the ultralow frequency of tumor-specific mRNA markers in EVs and the necessity of developing highly sensitive methods for analysis of EV mRNAs. The microfluidic digital mRNA analysis platform presented here would provide a useful tool to facilitate quantitative analysis of tumor-associated EV mRNAs for liquid biopsy-based cancer diagnosis and monitoring.

Fluorescence-based kinetic analysis of miniaturized protein microarrays

Ideal monitoring devices should enjoy a combination of characteristics, e.g. high sensitivity, multiplexing, portability, short time-to-result (TTR). Typically, no device meets all of these demands since some of them are contradictory, to some extent. Herein, we present a miniaturized platform based on fluorescent detection, which is sensitive, readily allows multiplexing, and allows real-time monitoring of the signal, thus allowing extraction of kinetic information as well as drastic reduction of TTR. This is achieved via miniaturization of active spots, integration with microfluidics, and algorithmic approaches. We validate its performance by comparing with evanescent field excitation, which obtains similar results, however without the addition of the necessary complex hardware.

Digital Microarrays: Single-Molecule Readout with Interferometric Detection of Plasmonic Nanorod Labels

DNA and protein microarrays are a high-throughput technology that allow the simultaneous quantification of tens of thousands of different biomolecular species. The mediocre sensitivity and limited dynamic range of traditional fluorescence microarrays compared to other detection techniques have been the technology's Achilles' heel and prevented their adoption for many biomedical and clinical diagnostic applications. Previous work to enhance the sensitivity of microarray readout to the single-molecule ("digital") regime have either required signal amplifying chemistry or sacrificed throughput, nixing the platform's primary advantages. Here, we report the development of a digital microarray which extends both the sensitivity and dynamic range of microarrays by about 3 orders of magnitude. This technique uses functionalized gold nanorods as single-molecule labels and an interferometric scanner which can rapidly enumerate individual nanorods by imaging them with a 10× objective lens. This approach does not require any chemical signal enhancement such as silver deposition and scans arrays with a throughput similar to commercial fluorescence scanners. By combining single-nanoparticle enumeration and ensemble measurements of spots when the particles are very dense, this system achieves a dynamic range of about 6 orders of magnitude directly from a single scan. As a proof-of-concept digital protein microarray assay, we demonstrated detection of hepatitis B virus surface antigen in buffer with a limit of detection of 3.2 pg/mL. More broadly, the technique's simplicity and high-throughput nature make digital microarrays a flexible platform technology with a wide range of potential applications in biomedical research and clinical diagnostics.

Sensitive and simultaneous surface plasmon resonance detection of free and p53-bound MDM2 proteins from human sarcomas

Murine double minute 2 (MDM2) is an oncoprotein mediating the degradation of the tumor suppressor p53 protein. The physiological levels of MDM2 protein are closely related to malignant transformation and tumor growth. In this work, the simultaneous and label-free determination of free and p53-bound MDM2 proteins from sarcoma tissue extracts was conducted using a dual-channel surface plasmon resonance (SPR) instrument. Free MDM2 protein was measured in one fluidic channel covered with the consensus double-stranded (ds)-DNA/p53 conjugate, while MDM2 bound to p53 was captured by the consensus ds-DNA immobilized onto the other channel. To achieve higher sensitivity and to confirm specificity, an MDM2-specific monoclonal antibody (2A10) was used to recognize both the free and p53-bound MDM2 proteins. The resultant method afforded a detection limit of 0.55 pM of MDM2. The amenability of the method to the analysis of free and p53-bound MDM2 proteins was demonstrated for normal and sarcoma tissue extracts from three patients. Our data reveal that both free and total MDM2 (free and bound forms combined) proteins from sarcoma tissue extracts are of much higher concentrations than those from normal tissue extracts and the p53-bound MDM2 protein only constitutes a small fraction of the total MDM2 concentration. In comparison with enzyme-linked immunosorbent assay (ELISA), the proposed method possesses higher sensitivity, is more cost-effective, and is capable of determining free and p53-bound MDM2 proteins in clinical samples.

Mathematical Modeling of Bioassays

The high affinity and specificity of biological receptors determine the demand for and the intensive development of analytical systems based on use of these receptors. Therefore, theoretical concepts of the mechanisms of these systems, quantitative parameters of their reactions, and relationships between their characteristics and ligand-receptor interactions have become extremely important. Many mathematical models describing different bioassay formats have been proposed. However, there is almost no information on the comparative characteristics of these models, their assumptions, and predictive insights. In this review we suggested a set of criteria to classify various bioassays and reviewed classical and contemporary publications on these bioassays with special emphasis on immunochemical analysis systems as the most common and in-demand techniques. The possibilities of analytical and numerical modeling are discussed, as well as estimations of the minimum concentrations that may be detected in bioassays and recommendations for the choice of assay conditions.

Multiplex single molecule counting technology used to generate interleukin 4, interleukin 6, and interleukin 10 reference limits

Detecting biomarkers at pg/ml concentrations or below is, in many situations, critical for quantifying levels in healthy individuals as well as the changes that can occur in the progression of disease states. The ability to detect multiple biomarkers from the same sample allows for better diagnoses, more efficient testing, and lower volumes of sample required. Based on single molecule counting technology, a multiplex instrument was designed and built that is capable of detecting cytokines and other low-abundance proteins at sub-pg/ml quantities in human plasma samples. The multiplex single molecule counting instrument was used to generate 95% reference limits for interleukin 4 (IL-4, <0.61 pg/ml), interleukin 6 (IL-6, <6.53 pg/ml), and interleukin 10 (IL-10, <1.08 pg/ml) from 100 healthy human donor plasma samples, with more than 90% of IL-4 concentrations and 100% of IL-6 and IL-10 concentrations above the limit of detection.

Theoretical limitations of quantification for noncompetitive sandwich immunoassays

Immunoassays exploit the highly selective interaction between antibodies and antigens to provide a vital method for biomolecule detection at low concentrations. Developers and practitioners of immunoassays have long known that non-specific binding often restricts immunoassay limits of quantification (LOQs). Aside from non-specific binding, most efforts by analytical chemists to reduce the LOQ for these techniques have focused on improving the signal amplification methods and minimizing the limitations of the detection system. However, with detection technology now capable of sensing single-fluorescence molecules, this approach is unlikely to lead to dramatic improvements in the future. Here, fundamental interactions based on the law of mass action are analytically connected to signal generation, replacing the four- and five-parameter fittings commercially used to approximate sigmoidal immunoassay curves and allowing quantitative consideration of non-specific binding and statistical limitations in order to understand the ultimate detection capabilities of immunoassays. The restrictions imposed on limits of quantification by instrumental noise, non-specific binding, and counting statistics are discussed based on equilibrium relations for a sandwich immunoassay. Understanding the maximal capabilities of immunoassays for each of these regimes can greatly assist in the development and evaluation of immunoassay platforms. While many studies suggest that single molecule detection is possible through immunoassay techniques, here, it is demonstrated that the fundamental limit of quantification (precision of 10 % or better) for an immunoassay is approximately 131 molecules and this limit is based on fundamental and unavoidable statistical limitations.

Computer-aided design of a catalyst for Edman degradation utilizing substrate-assisted catalysis

Molecular biology has been revolutionized by the miniaturization and parallelization of DNA sequencing assays previously performed on bulk samples. Many of these technologies rely on biomolecular reagents to facilitate detection, synthesis, or labeling of samples. To aid in the construction of analogous experimental approaches for proteins and peptides, we have used computer-aided design to engineer an enzyme capable of catalyzing the cleavage step of the Edman degradation. We exploit the similarity between the sulfur nucleophile on the Edman reagent and the catalytic cysteine in a naturally occurring protease to adopt a substrate-assisted mechanism for achieving controlled, step-wise removal of N-terminal amino acids. The ability to expose amino acids iteratively at the N-terminus of peptides is a central requirement for protein sequencing techniques that utilize processive degradation of the peptide chain. While this can be easily accomplished using the chemical Edman degradation, achieving this activity enzymatically in aqueous solution removes the requirement for harsh acid catalysis, improving compatibility with low adsorption detection surfaces, such as those used in single molecule assays.

Development and validation of protein microarray technology for simultaneous inflammatory mediator detection in human sera

Biomarkers, including cytokines, can help in the diagnosis, prognosis, and prediction of treatment response across a wide range of disease settings. Consequently, the recent emergence of protein microarray technology, which is able to quantify a range of inflammatory mediators in a large number of samples simultaneously, has become highly desirable. However, the cost of commercial systems remains somewhat prohibitive. Here we show the development, validation, and implementation of an in-house microarray platform which enables the simultaneous quantitative analysis of multiple protein biomarkers. The accuracy and precision of the in-house microarray system were investigated according to the Food and Drug Administration (FDA) guidelines for pharmacokinetic assay validation. The assay fell within these limits for all but the very low-abundant cytokines, such as interleukin- (IL-) 10. Additionally, there were no significant differences between cytokine detection using our microarray system and the “gold standard” ELISA format. Crucially, future biomarker detection need not be limited to the 16 cytokines shown here but could be expanded as required. In conclusion, we detail a bespoke protein microarray system, utilizing well-validated ELISA reagents, that allows accurate, precise, and reproducible multiplexed biomarker quantification, comparable with commercial ELISA, and allowing customization beyond that of similar commercial microarrays.

Popular computational methods to assess multiprotein complexes derived from label-free affinity purification and mass spectrometry (AP-MS) experiments

Advances in sensitivity, resolution, mass accuracy, and throughput have considerably increased the number of protein identifications made via mass spectrometry. Despite these advances, state-of-the-art experimental methods for the study of protein-protein interactions yield more candidate interactions than may be expected biologically owing to biases and limitations in the experimental methodology. In silico methods, which distinguish between true and false interactions, have been developed and applied successfully to reduce the number of false positive results yielded by physical interaction assays. Such methods may be grouped according to: (1) the type of data used: methods based on experiment-specific measurements (e.g., spectral counts or identification scores) versus methods that extract knowledge encoded in external annotations (e.g., public interaction and functional categorisation databases); (2) the type of algorithm applied: the statistical description and estimation of physical protein properties versus predictive supervised machine learning or text-mining algorithms; (3) the type of protein relation evaluated: direct (binary) interaction of two proteins in a cocomplex versus probability of any functional relationship between two proteins (e.g., co-occurrence in a pathway, sub cellular compartment); and (4) initial motivation: elucidation of experimental data by evaluation versus prediction of novel protein-protein interaction, to be experimentally validated a posteriori. This work reviews several popular computational scoring methods and software platforms for protein-protein interactions evaluation according to their methodology, comparative strengths and weaknesses, data representation, accessibility, and availability. The scoring methods and platforms described include: CompPASS, SAINT, Decontaminator, MINT, IntAct, STRING, and FunCoup. References to related work are provided throughout in order to provide a concise but thorough introduction to a rapidly growing interdisciplinary field of investigation.

Opportunities for sensitive plasma proteome analysis

Despite great interest, investments, and efforts, the ongoing search for plasma protein biomarkers for disease so far has come up surprisingly empty-handed. Although discovery programs have revealed large numbers of biomarker candidates, the clinical utility has been validated for only a very small number of these. While this disappointing state of affairs may suggest that plasma protein biomarkers have little more to offer for diagnostics, we take the perspective that experimental conditions might not have been optimal and that analyses will be required that offer far greater sensitivity than currently available, in terms of numbers of molecules needed for unambiguous detection. Accordingly, techniques are needed to search deep and wide for protein biomarker candidates. The requirements and feasibility of such assays will be discussed.