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.The authors wish to thank Oguzhan Avci and Jacob Trueb for thoughtful comments and suggestions regarding numerical optimization of the optical system. This work was funded in part by a research contract with ASELSAN, Inc. and the Wallace H. Coulter Foundation 2010 Coulter Translational Award. (ASELSAN, Inc.; Wallace H. Coulter Foundation Coulter Translational Award)Accepted manuscrip

Beating the reaction limits of biosensor sensitivity with dynamic tracking of single binding events

The clinical need for ultrasensitive molecular analysis has motivated the development of several endpoint-assay technologies capable of single-molecule readout. These endpoint assays are now primarily limited by the affinity and specificity of the molecular-recognition agents for the analyte of interest. In contrast, a kinetic assay with single-molecule readout could distinguish between low-abundance, high-affinity (specific analyte) and high-abundance, low-affinity (nonspecific background) binding by measuring the duration of individual binding events at equilibrium. Here, we describe such a kinetic assay, in which individual binding events are detected and monitored during sample incubation. This method uses plasmonic gold nanorods and interferometric reflectance imaging to detect thousands of individual binding events across a multiplex solid-phase sensor with a large area approaching that of leading bead-based endpoint-assay technologies. A dynamic tracking procedure is used to measure the duration of each event. From this, the total rates of binding and debinding as well as the distribution of binding-event durations are determined. We observe a limit of detection of 19 fM for a proof-of-concept synthetic DNA analyte in a 12-plex assay format.First author draf

Field Effect Transistor Nanosensor for Breast Cancer Diagnostics

Silicon nanochannel field effect transistor (FET) biosensors are one of the most promising technologies in the development of highly sensitive and label-free analyte detection for cancer diagnostics. With their exceptional electrical properties and small dimensions, silicon nanochannels are ideally suited for extraordinarily high sensitivity. In fact, the high surface-to-volume ratios of these systems make single molecule detection possible. Further, FET biosensors offer the benefits of high speed, low cost, and high yield manufacturing, without sacrificing the sensitivity typical for traditional optical methods in diagnostics. Top down manufacturing methods leverage advantages in Complementary Metal Oxide Semiconductor (CMOS) technologies, making richly multiplexed sensor arrays a reality. Here, we discuss the fabrication and use of silicon nanochannel FET devices as biosensors for breast cancer diagnosis and monitoring

RNA–protein binding kinetics in an automated microfluidic reactor

Microfluidic chips can automate biochemical assays on the nanoliter scale, which is of considerable utility for RNA–protein binding reactions that would otherwise require large quantities of proteins. Unfortunately, complex reactions involving multiple reactants cannot be prepared in current microfluidic mixer designs, nor is investigation of long-time scale reactions possible. Here, a microfluidic ‘Riboreactor’ has been designed and constructed to facilitate the study of kinetics of RNA–protein complex formation over long time scales. With computer automation, the reactor can prepare binding reactions from any combination of eight reagents, and is optimized to monitor long reaction times. By integrating a two-photon microscope into the microfluidic platform, 5-nl reactions can be observed for longer than 1000 s with single-molecule sensitivity and negligible photobleaching. Using the Riboreactor, RNA–protein binding reactions with a fragment of the bacterial 30S ribosome were prepared in a fully automated fashion and binding rates were consistent with rates obtained from conventional assays. The microfluidic chip successfully combines automation, low sample consumption, ultra-sensitive fluorescence detection and a high degree of reproducibility. The chip should be able to probe complex reaction networks describing the assembly of large multicomponent RNPs such as the ribosome

Bioaffinity detection of pathogens on surfaces

The demand for improved technologies capable of rapidly detecting pathogens with high sensitivity and selectivity in complex environments continues to be a significant challenge that helps drive the development of new analytical techniques. Surface-based detection platforms are particularly attractive as multiple bioaffinity interactions between different targets and corresponding probe molecules can be monitored simultaneously in a single measurement. Furthermore, the possibilities for developing new signal transduction mechanisms alongside novel signal amplification strategies aremuchmore varied. In this article, we describe some of the latest advances in the use of surface bioaffinity detection of pathogens. Three major sections will be discussed: (i) a brief overview on the choice of probe molecules such as antibodies, proteins and aptamers specific to pathogens and surface attachment chemistries to immobilize those probes onto various substrates, (ii) highlighting examples among the current generation of surface biosensors, and (iii) exploring emerging technologies that are highly promising and likely to form the basis of the next generation of pathogenic sensors

From fix to fit into the autoptic human brains.

Formalin-fixed, paraffinembedded (FFPE) human brain tissues are very often stored in formalin for long time. Formalin fixation reduces immunostaining, and the DNA/RNA extraction from FFPE brain tissue becomes suboptimal. At present, there are different protocols of fixation and several procedures and kits to extract DNA/RNA from paraffin embedding tissue, but a gold standard protocol remains distant. In this study, we analyzed four types of fixation systems and compared histo and immuno-staining. Based on our results, we propose a modified method of combined fixation in formalin and formic acid for the autoptic adult brain to obtain easy, fast, safe and efficient immunolabelling of long-stored FFPE tissue. In particular, we have achieved an improved preservation of cellular morphology and obtained success in postmortem immunostaining for NeuN. This nuclear antigen is an important marker for mapping neurons, for example, to evaluate the histopathology of temporal lobe epilepsy or to draw the topography of cardiorespiratory brainstem nuclei in sudden infant death syndrome (SIDS). However, NeuN staining is frequently faint or lost in postmortem human brain tissues. In addition, we attained Fluoro Jade C staining, a marker of neurodegeneration, and immunofluorescent staining for stem cell antigens in the postnatal human brain, utilizing custom fit fixation procedures

Advances in Microfluidics and Lab-on-a-Chip Technologies

Advances in molecular biology are enabling rapid and efficient analyses for effective intervention in domains such as biology research, infectious disease management, food safety, and biodefense. The emergence of microfluidics and nanotechnologies has enabled both new capabilities and instrument sizes practical for point-of-care. It has also introduced new functionality, enhanced sensitivity, and reduced the time and cost involved in conventional molecular diagnostic techniques. This chapter reviews the application of microfluidics for molecular diagnostics methods such as nucleic acid amplification, next-generation sequencing, high resolution melting analysis, cytogenetics, protein detection and analysis, and cell sorting. We also review microfluidic sample preparation platforms applied to molecular diagnostics and targeted to sample-in, answer-out capabilities

VarDict: a novel and versatile variant caller for next-generation sequencing in cancer research

Accurate variant calling in next generation sequencing (NGS) is critical to understand cancer genomes better. Here we present VarDict, a novel and versatile variant caller for both DNA- and RNA-sequencing data. VarDict simultaneously calls SNV, MNV, InDels, complex and structural variants, expanding the detected genetic driver landscape of tumors. It performs local realignments on the fly for more accurate allele frequency estimation. VarDict performance scales linearly to sequencing depth, enabling ultra-deep sequencing used to explore tumor evolution or detect tumor DNA circulating in blood. In addition, VarDict performs amplicon aware variant calling for polymerase chain reaction (PCR)-based targeted sequencing often used in diagnostic settings, and is able to detect PCR artifacts. Finally, VarDict also detects differences in somatic and loss of heterozygosity variants between paired samples. VarDict reprocessing of The Cancer Genome Atlas (TCGA) Lung Adenocarcinoma dataset called known driver mutations in KRAS, EGFR, BRAF, PIK3CA and MET in 16% more patients than previously published variant calls. We believe VarDict will greatly facilitate application of NGS in clinical cancer research

Translational Oncogenomics and Human Cancer Interactome Networks

An overview of translational, human oncogenomics, transcriptomics and cancer interactomic networks is presented together with basic concepts and potential, new applications to Oncology and Integrative Cancer Biology. Novel translational oncogenomics research is rapidly expanding through the application of advanced technology, research findings and computational tools/models to both pharmaceutical and clinical problems. A self-contained presentation is adopted that covers both fundamental concepts and the most recent biomedical, as well as clinical, applications. Sample analyses in recent clinical studies have shown that gene expression data can be employed to distinguish between tumor types as well as to predict outcomes. Potentially important applications of such results are individualized human cancer therapies or, in general, ‘personalized medicine’. Several cancer detection techniques are currently under development both in the direction of improved detection sensitivity and increased time resolution of cellular events, with the limits of single molecule detection and picosecond time resolution already reached. The urgency for the complete mapping of a human cancer interactome with the help of such novel, high-efficiency / low-cost and ultra-sensitive techniques is also pointed out

A Label-Free Platform for Identification of Exosomes from Different Sources.

Exosomes contain cell- and cell-state-specific cargos of proteins, lipids, and nucleic acids and play significant roles in cell signaling and cell-cell communication. Current research into exosome-based biomarkers has relied largely on analyzing candidate biomarkers, i.e., specific proteins or nucleic acids. However, this approach may miss important biomarkers that are yet to be identified. Alternative approaches are to analyze the entire exosome system, either by "omics" methods or by techniques that provide "fingerprints" of the system without identifying each individual biomolecule component. Here, we describe a platform of the latter type, which is based on surface-enhanced Raman spectroscopy (SERS) in combination with multivariate analysis, and demonstrate the utility of this platform for analyzing exosomes derived from different biological sources. First, we examined whether this analysis could use exosomes isolated from fetal bovine serum using a simple, commercially available isolation kit or necessitates the higher purity achieved by the "gold standard" ultracentrifugation/filtration procedure. Our data demonstrate that the latter method is required for this type of analysis. Having established this requirement, we rigorously analyzed the Raman spectral signature of individual exosomes using a unique, hybrid SERS substrate made of a graphene-covered Au surface containing a quasi-periodic array of pyramids. To examine the source of the Raman signal, we used Raman mapping of low and high spatial resolution combined with morphological identification of exosomes by scanning electron microscopy. Both approaches suggested that the spectra were collected from single exosomes. Finally, we demonstrate for the first time that our platform can distinguish among exosomes from different biological sources based on their Raman signature, a promising approach for developing exosome-based fingerprinting. Our study serves as a solid technological foundation for future exploration of the roles of exosomes in various biological processes and their use as biomarkers for disease diagnosis and treatment monitoring