On noise processes and limits of performance in biosensors

In this paper, we present a comprehensive stochastic model describing the measurement uncertainty, output signal, and limits of detection of affinity-based biosensors. The biochemical events within the biosensor platform are modeled by a Markov stochastic process, describing both the probabilistic mass transfer and the interactions of analytes with the capturing probes. To generalize this model and incorporate the detection process, we add noisy signal transduction and amplification stages to the Markov model. Using this approach, we are able to evaluate not only the output signal and the statistics of its fluctuation but also the noise contributions of each stage within the biosensor platform. Furthermore, we apply our formulations to define the signal-to-noise ratio, noise figure, and detection dynamic range of affinity-based biosensors. Motivated by the platforms encountered in practice, we construct the noise model of a number of widely used systems. The results of this study show that our formulations predict the behavioral characteristics of affinity-based biosensors which indicate the validity of the model

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

Analysis of free analyte fractions by rapid affinity chromatography

The invention is generally directed toward an analytical method to determine the concentration of the free analyte fraction in a sample. More particularly, the method encompasses applying a sample comprising a free and bound analyte fraction to an affinity column capable of selectively extracting the free fraction in the millisecond time domain. The signal generated by the free fraction is then quantified by standard analytical detection techniques. The concentration of the free fraction may then be determined by comparison of its signal with that of a calibration curve depicting the signal of known concentration of the same analyte

Multi-channel SPR biosensor based on PCF for multi-analyte sensing applications

This paper presents a theoretical investigation of a novel holey fiber (Photonic Crystal Fiber (PCF)) multi-channel biosensor based on surface plasmon resonance (SPR). The large gold coated micro fluidic channels and elliptical air hole design of our proposed biosensor aided by a high refractive index over layer in two channels enables operation in two modes; multi analyte sensing and self-referencing mode. Loss spectra, dispersion and detection capability of our proposed biosensor for the two fundamental modes (HE x 11 and HE y 11 ) have been elucidated using a Finite Element Method (FEM) and Perfectly Matching Layers (PML)

Selectivity and specificity: pros and cons in sensing

Sensing using specific and selective receptors provides two very different but complementary strategies. This Sensor Issues article will discuss the merits and challenges of specific sensors, and selective sensors based on synthetic arrays. We will examine where each has been successfully applied to a sensing challenge, and then look at how a combined approach could take elements of both to provide new sensor platforms

Introduction of 4-chloro-alpha-cyanocinnamic acid liquid matrices for high sensitivity UV-MALDI MS

Matrix-assisted laser desorption/ionization (MALDI) is a key ionization technique in mass spectrometry (MS) for the analysis of labile macromolecules. An important area of study and improvements in relation to MALDI and its application in high-sensitivity MS is that of matrix design and sample preparation. Recently, 4-chloro-alpha-cyanocinnamic acid (ClCCA) has been introduced as a new rationally designed matrix and reported to provide an improved analytical performance as demonstrated by an increase in sequence coverage of protein digests obtained by peptide mass mapping (PMM) (Jaskolla, T. W.; et al. Proc. Natl. Acad. Sci. U.S.A. 2008, 105, 12200-12205). This new matrix shows the potential to be a superior alternative to the commonly used and highly successful alpha-cyano-4-hydroxycinnamic acid (CHCA). We have taken this design one step further by developing and optimizing an ionic liquid matrix (ILM) and liquid support matrix (LSM) using ClCCA as the principle chromophore and MALDI matrix compound. These new liquid matrices possess greater sample homogeneity and a simpler morphology. The data obtained from our studies show improved sequence coverage for BSA digests compared to the traditional CHCA crystalline matrix and for the ClCCA-containing ILM a similar performance to the ClCCA crystalline matrix down to 1 fmol of BSA digest prepared in a single MALDI sample droplet with current sensitivity levels in the attomole range. The LSMs show a high tolerance to contamination such as ammonium bicarbonate, a commonly used buffering agent

Gas recognition based on the physicochemical parameters determined by monitoring diffusion rates in microfluidic channels

This paper was presented at the 4th Micro and Nano Flows Conference (MNF2014), which was held at University College, London, UK. The conference was organised by Brunel University and supported by the Italian Union of Thermofluiddynamics, IPEM, the Process Intensification Network, the Institution of Mechanical Engineers, the Heat Transfer Society, HEXAG - the Heat Exchange Action Group, and the Energy Institute, ASME Press, LCN London Centre for Nanotechnology, UCL University College London, UCL Engineering, the International NanoScience Community, www.nanopaprika.eu.Monitoring the diffusion progress rates of different gases in a microfluidic channel affords their discrimination by the comparison of their temporal profiles in a high-dimensional feature space. Here, we demonstrate gas recognition by determination of their three important physicochemical parameters via a model-based examination of the experimentally determined diffusion rates in two different cross-section channels. The system utilized comprises two channels with respective cross-sectional diameters of 1000 μm and 50 μm. The open end of both channels are simultaneously exposed to the analyte, and the temporal profiles of the diffusion rates are recorded by continuous resistance measurements on the chemoresistive sensors spliced to the channels at their other ends. Fitting the solutions of the diffusion equation to the experimental profiles obtained from the large cross-section channel results in the diffusivity of the analyte. The results of small cross-section channel, however, fit the solutions of a modified diffusion equation which accounts for the adsorption of the analyte molecules to the channel walls, as well. The latter fitting process results in the adsorption parameter for the analyte-channel wall interactions and the population of the effective adsorption sites on the unit area of the walls. The allocation of these three meaningful parameters to an unknown gaseous analyte affords its recognition

Co-detection: Ultra-reliable Nanoparticle-Based Electrical Detection of Biomolecules in the Presence of Large Background Interference

Contrary to popular belief, we report that background interference in conductimetric biochips can be exploited using a novel "co-detection" principle to significantly improve the reliability of detecting trace quantities of biomolecules. The technique called "co-detection" exploits the non-linear redundancy amongst synthetically patterned biomolecular logic circuits for deciphering the presence or absence of target biomolecules in a sample. In this paper, we demonstrate the "co-detection" principle on gold-nanoparticle based conductimetric soft-logic circuits which uses a silver-enhancement technique for signal amplification. Using co-detection, we have been able to measure a 1000 times improvement in the reliability of detecting mouse IgG at concentration levels that are 10^5^ lower than the concentration of rabbit IgG which serves as background interference

From aptamer-based biomarker discovery to diagnostic and clinical applications: an aptamer-based, streamlined multiplex proteomic assay

Recently, we reported an aptamer-based, highly multiplexed assay for the purpose of biomarker identification. To enable seamless transition from highly multiplexed biomarker discovery assays to a format suitable and convenient for diagnostic and life-science applications, we developed a streamlined, plate-based version of the assay. The plate-based version of the assay is robust, sensitive (sub-picomolar), rapid, can be highly multiplexed (upwards of 60 analytes), and fully automated. We demonstrate that quantification by microarray-based hybridization, Luminex bead-based methods, and qPCR are each compatible with our platform, further expanding the breadth of proteomic applications for a wide user community