skip to main content

Title: Rapid single-molecule digital detection of protein biomarkers for continuous monitoring of systemic immune disorders
Abstract Digital protein assays have great potential to advance immunodiagnostics because of their single-molecule sensitivity, high precision, and robust measurements. However, translating digital protein assays to acute clinical care has been challenging because it requires deployment of these assays with a rapid turnaround. Herein, we present a technology platform for ultrafast digital protein biomarker detection by using single-molecule counting of immune-complex formation events at an early, pre-equilibrium state. This method, which we term “pre-equilibrium digital enzyme-linked immunosorbent assay” (PEdELISA), can quantify a multiplexed panel of protein biomarkers in 10 µL of serum within an unprecedented assay incubation time of 15 to 300 seconds over a 104 dynamic range. PEdELISA allowed us to perform rapid monitoring of protein biomarkers in patients manifesting post-chimeric antigen receptor T-cell therapy cytokine release syndrome, with ∼30-minute sample-to-answer time and a sub–picograms per mL limit of detection. The rapid, sensitive, and low-input volume biomarker quantification enabled by PEdELISA is broadly applicable to timely monitoring of acute disease, potentially enabling more personalized treatment.
; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; more » ; « less
Award ID(s):
Publication Date:
Journal Name:
Page Range or eLocation-ID:
1591 to 1602
Sponsoring Org:
National Science Foundation
More Like this
  1. Despite widespread concern regarding cytokine storms leading to severe morbidity in COVID-19, rapid cytokine assays are not routinely available for monitoring critically ill patients. We report the clinical application of a digital protein microarray platform for rapid multiplex quantification of cytokines from critically ill COVID-19 patients admitted to the intensive care unit (ICU) at the University of Michigan Hospital. The platform comprises two low-cost modules: (i) a semi-automated fluidic dispensing/mixing module that can be operated inside a biosafety cabinet to minimize the exposure of the technician to the virus infection and (ii) a 12–12–15 inch compact fluorescence optical scanner formore »the potential near-bedside readout. The platform enabled daily cytokine analysis in clinical practice with high sensitivity (<0.4 pg mL −1 ), inter-assay repeatability (∼10% CV), and rapid operation providing feedback on the progress of therapy within 4 hours. This test allowed us to perform serial monitoring of two critically ill patients with respiratory failure and to support immunomodulatory therapy using the selective cytopheretic device (SCD). We also observed clear interleukin-6 (IL-6) elevations after receiving tocilizumab (IL-6 inhibitor) while significant cytokine profile variability exists across all critically ill COVID-19 patients and to discover a weak correlation between IL-6 to clinical biomarkers, such as ferritin and C-reactive protein (CRP). Our data revealed large subject-to-subject variability in patients' response to COVID-19, reaffirming the need for a personalized strategy guided by rapid cytokine assays.« less
  2. To sensitively detect multiple and cross-species disease-related targets from a single biological sample in a quick and reliable manner is of high importance in accurately diagnosing and monitoring diseases. Herein, a surface-enhanced Raman scattering (SERS) sensor based on a functionalized multiple-armed tetrahedral DNA nanostructure (FMTDN) immobilized silver nanorod (AgNR) array substrate and Au nanoparticle (AuNP) SERS tags is constructed to achieve both multiplex detection and enhanced sensitivity using a sandwich strategy. The sensor can achieve single, dual, and triple biomarker detections of three lung cancer-related nucleic acid and protein biomarkers, i.e. , miRNA-21, miRNA-486 and carcinoembryonic antigen (CEA) in humanmore »serum. The enhanced SERS signals in multiplex detections are due to the DNA self-assembled AuNP clusters on the silver nanorod array during the assay, and the experimentally obtained relative enhancement factor ratios, 150 for AuNP dimers and 840 for AuNP trimers, qualitatively agree with the numerically calculated local electric field enhancements. The proposed FMTDN-functionalized AgNR SERS sensor is capable of multiplex and cross-species detection of nucleic acid and protein biomarkers with improved sensitivity, which has great potential for the screening and clinical diagnosis of cancer in the early stage.« less
  3. Introduction: Vaso-occlusive crises (VOCs) are a leading cause of morbidity and early mortality in individuals with sickle cell disease (SCD). These crises are triggered by sickle red blood cell (sRBC) aggregation in blood vessels and are influenced by factors such as enhanced sRBC and white blood cell (WBC) adhesion to inflamed endothelium. Advances in microfluidic biomarker assays (i.e., SCD Biochip systems) have led to clinical studies of blood cell adhesion onto endothelial proteins, including, fibronectin, laminin, P-selectin, ICAM-1, functionalized in microchannels. These microfluidic assays allow mimicking the physiological aspects of human microvasculature and help characterize biomechanical properties of adhered sRBCsmore »under flow. However, analysis of the microfluidic biomarker assay data has so far relied on manual cell counting and exhaustive visual morphological characterization of cells by trained personnel. Integrating deep learning algorithms with microscopic imaging of adhesion protein functionalized microfluidic channels can accelerate and standardize accurate classification of blood cells in microfluidic biomarker assays. Here we present a deep learning approach into a general-purpose analytical tool covering a wide range of conditions: channels functionalized with different proteins (laminin or P-selectin), with varying degrees of adhesion by both sRBCs and WBCs, and in both normoxic and hypoxic environments. Methods: Our neural networks were trained on a repository of manually labeled SCD Biochip microfluidic biomarker assay whole channel images. Each channel contained adhered cells pertaining to clinical whole blood under constant shear stress of 0.1 Pa, mimicking physiological levels in post-capillary venules. The machine learning (ML) framework consists of two phases: Phase I segments pixels belonging to blood cells adhered to the microfluidic channel surface, while Phase II associates pixel clusters with specific cell types (sRBCs or WBCs). Phase I is implemented through an ensemble of seven generative fully convolutional neural networks, and Phase II is an ensemble of five neural networks based on a Resnet50 backbone. Each pixel cluster is given a probability of belonging to one of three classes: adhered sRBC, adhered WBC, or non-adhered / other. Results and Discussion: We applied our trained ML framework to 107 novel whole channel images not used during training and compared the results against counts from human experts. As seen in Fig. 1A, there was excellent agreement in counts across all protein and cell types investigated: sRBCs adhered to laminin, sRBCs adhered to P-selectin, and WBCs adhered to P-selectin. Not only was the approach able to handle surfaces functionalized with different proteins, but it also performed well for high cell density images (up to 5000 cells per image) in both normoxic and hypoxic conditions (Fig. 1B). The average uncertainty for the ML counts, obtained from accuracy metrics on the test dataset, was 3%. This uncertainty is a significant improvement on the 20% average uncertainty of the human counts, estimated from the variance in repeated manual analyses of the images. Moreover, manual classification of each image may take up to 2 hours, versus about 6 minutes per image for the ML analysis. Thus, ML provides greater consistency in the classification at a fraction of the processing time. To assess which features the network used to distinguish adhered cells, we generated class activation maps (Fig. 1C-E). These heat maps indicate the regions of focus for the algorithm in making each classification decision. Intriguingly, the highlighted features were similar to those used by human experts: the dimple in partially sickled RBCs, the sharp endpoints for highly sickled RBCs, and the uniform curvature of the WBCs. Overall the robust performance of the ML approach in our study sets the stage for generalizing it to other endothelial proteins and experimental conditions, a first step toward a universal microfluidic ML framework targeting blood disorders. Such a framework would not only be able to integrate advanced biophysical characterization into fast, point-of-care diagnostic devices, but also provide a standardized and reliable way of monitoring patients undergoing targeted therapies and curative interventions, including, stem cell and gene-based therapies for SCD. Disclosures Gurkan: Dx Now Inc.: Patents & Royalties; Xatek Inc.: Patents & Royalties; BioChip Labs: Patents & Royalties; Hemex Health, Inc.: Consultancy, Current Employment, Patents & Royalties, Research Funding.« less
  4. Highly sensitive, specific, and point-of-care (POC) serological assays are an essential tool to manage coronavirus disease 2019 (COVID-19). Here, we report on a microfluidic POC test that can profile the antibody response against multiple severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) antigens—spike S1 (S1), nucleocapsid (N), and the receptor binding domain (RBD)—simultaneously from 60 μl of blood, plasma, or serum. We assessed the levels of antibodies in plasma samples from 31 individuals (with longitudinal sampling) with severe COVID-19, 41 healthy individuals, and 18 individuals with seasonal coronavirus infections. This POC assay achieved high sensitivity and specificity, tracked seroconversion, and showedmore »good concordance with a live virus microneutralization assay. We can also detect a prognostic biomarker of severity, IP-10 (interferon-γ–induced protein 10), on the same chip. Because our test requires minimal user intervention and is read by a handheld detector, it can be globally deployed to combat COVID-19.« less
  5. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the cause of the coronavirus disease that began in 2019 (COVID-19), has been responsible for 1.4 million deaths worldwide as of 13 November 2020. Because at the time of writing no vaccine is yet available, a rapid diagnostic assay is very urgently needed. Herein, we present the development of anti-spike antibody attached gold nanoparticles for the rapid diagnosis of specific COVID-19 viral antigen or virus via a simple colorimetric change observation within a 5 minute time period. For rapid and highly sensitive identification, surface enhanced Raman spectroscopy (SERS) was employed using 4-aminothiophenol asmore »a reporter molecule, which is attached to the gold nanoparticle via an Au–S bond. In the presence of COVID-19 antigen or virus particles, owing to the antigen–antibody interaction, the gold nanoparticles undergo aggregation, changing color from pink to blue, which allows for the determination of the presence of antigen or virus very rapidly by the naked eye, even at concentrations of 1 nanogram (ng) per mL for COVID-19 antigen and 1000 virus particles per mL for SARS-CoV-2 spike protein pseudotyped baculovirus. Importantly, the aggregated gold nanoparticles form “hot spots” to provide very strong SERS signal enhancement from anti-spike antibody and 4-aminothiophenol attached gold nanoparticles via light–matter interactions. Finite-difference time-domain (FDTD) simulation data indicate a 4-orders-of-magnitude Raman enhancement in “hot spot” positions when gold nanoparticles form aggregates. Using a portable Raman analyzer, our reported data demonstrate that our antibody and 4-aminothiophenol attached gold nanoparticle-based SERS probe has the capability to detect COVID-19 antigen even at a concentration of 4 picograms (pg) per mL and virus at a concentration of 18 virus particles per mL within a 5 minute time period. Using HEK293T cells, which express angiotensin-converting enzyme 2 (ACE2), by which SARS-CoV-2 enters human cells, we show that anti-spike antibody attached gold nanoparticles have the capability to inhibit infection by the virus. Our reported data show that antibody attached gold nanoparticles bind to SARS-CoV-2 spike protein, thereby inhibiting the virus from binding to cell receptors, which stops virus infection and spread. It also has the capability to destroy the lipid membrane of the virus.« less