A Protein Microarray-Based Respiratory Viral Antigen Testing Platform for COVID-19 Surveillance.

High-throughput and rapid screening testing is highly desirable to effectively combat the rapidly evolving COVID-19 pandemic co-presents with influenza and seasonal common cold epidemics. Here, we present a general workflow for iterative development and validation of an antibody-based microarray assay for the detection of a respiratory viral panel: (a) antibody screening to quickly identify optimal reagents and assay conditions, (b) immunofluorescence assay design including signal amplification for low viral titers, (c) assay characterization with recombinant proteins, inactivated viral samples and clinical samples, and (d) multiplexing to detect a panel of common respiratory viruses. Using RT-PCR-confirmed SARS-CoV-2 positive and negative pharyngeal swab samples, we demonstrated that the antibody microarray assay exhibited a clinical sensitivity and specificity of 77.2% and 100%, respectively, which are comparable to existing FDA-authorized antigen tests. Moreover, the microarray assay is correlated with RT-PCR cycle threshold (Ct) values and is particularly effective in identifying high viral titers. The multiplexed assay can selectively detect SARS-CoV-2 and influenza virus, which can be used to discriminate these viral infections that share similar symptoms. Such protein microarray technology is amenable for scale-up and automation and can be broadly applied as a both diagnostic and research tool.

Rapid isolation of rare targets from large fluid volumes.

Rapidly isolating rare targets from larger, clinically relevant fluid volumes remains an unresolved problem in biomedicine and diagnosis. Here, we describe how 3D particle sorting can enrich targets at ultralow concentrations over 100-fold within minutes not possible with conventional approaches. Current clinical devices based on biochemical extraction and microfluidic solutions typically require high concentrations and/or can only process sub-milliliter volumes in time. In a proof-of-concept application, we isolated bacteria from whole blood as demanded for rapid sepsis diagnosis where minimal numbers of bacteria need to be found in a 1-10 mL blood sample. After sample encapsulation in droplets and target enrichment with the 3D particle sorter within a few minutes, downstream analyses were able to identify bacteria and test for antibiotic susceptibility, information which is critical for successful treatment of bloodstream infections.

A rapid, point-of-care antibiotic susceptibility test for urinary tract infections.

Introduction. The alarming rise in urinary tract infection (UTI) antimicrobial resistance has resulted from a combination of high prevalence, low specificity and the lack of a rapid, point-of-care (POC) antibiotic susceptibility test (AST), which has led to the overuse/inappropriate use of antibiotics.Aim. This study aimed to evaluate the performance of a rapid POC phenotypic AST device in reporting susceptibility information within 2 h.Methodology. Instrument calibration was performed with model bacteria and fluorescent microbeads to determine the dynamic range and limit of detection for quantifying concentrations of bacteria and demonstrate the ability to rapidly differentiate susceptible and resistant model bacteria. We then evaluated 30 presumptive UTI-positive patient urine samples in a clinical pilot study using a panel of 5 common UTI antibiotics plus a growth control and compared our results to the hospital standard of care AST.Results. Our device was able to robustly detect and quantify bacteria concentrations from 50 to 105 colony-forming units (c.f.u.) ml-1. The high sensitivity of this measurement technique enabled the device to differentiate between susceptible and resistant model bacteria with 100 % specificity over a 2 h growth period. In the clinical pilot study, an overall categorical agreement (CA) of 90.7 % was observed (sensitivity=91.4 %, specificity=88.9 %, n=97) with performance for individual drugs ranging from 85 % CA (ceftazidime) to 100 % (nitrofurantoin).Conclusions. By reducing the typical timeframe for susceptibility testing from 2-3 days to 2 h, our POC phenotypic AST can provide critical information to clinicians prior to the administration of antibiotic therapy.

A modular microarray imaging system for highly specific COVID-19 antibody testing.

To detect the presence of antibodies in blood against SARS-CoV-2 in a highly sensitive and specific manner, here we describe a robust, inexpensive ($200), 3D-printable portable imaging platform (TinyArray imager) that can be deployed immediately in areas with minimal infrastructure to read coronavirus antigen microarrays (CoVAMs) that contain a panel of antigens from SARS-CoV-2, SARS-1, MERS, and other respiratory viruses. Application includes basic laboratories and makeshift field clinics where a few drops of blood from a finger prick could be rapidly tested in parallel for the presence of antibodies to SARS-CoV-2 with a test turnaround time of only 2-4 h. To evaluate our imaging device, we probed and imaged coronavirus microarrays with COVID-19-positive and negative sera and achieved a performance on par with a commercial microarray reader 100× more expensive than our imaging device. This work will enable large scale serosurveillance, which can play an important role in the months and years to come to implement efficient containment and mitigation measures, as well as help develop therapeutics and vaccines to treat and prevent the spread of COVID-19.

A Modular Microarray Imaging System for Highly Specific COVID-19 Antibody Testing.

To detect the presence of antibodies in blood against SARS-CoV-2 in a highly sensitive and specific manner, here we describe a robust, inexpensive ($200), 3D-printable portable imaging platform (TinyArray imager) that can be deployed immediately in areas with minimal infrastructure to read coronavirus antigen microarrays (CoVAMs) that contain a panel of antigens from SARS-CoV-2, SARS-1, MERS, and other respiratory viruses. Application includes basic laboratories and makeshift field clinics where a few drops of blood from a finger prick could be rapidly tested in parallel for the presence of antibodies to SARS-CoV-2 with a test turnaround time of only 2-4 h. To evaluate our imaging device, we probed and imaged coronavirus microarrays with COVID-19-positive and negative sera and achieved a performance on par with a commercial microarray reader 100x more expensive than our imaging device. This work will enable large scale serosurveillance, which can play an important role in the months and years to come to implement efficient containment and mitigation measures, as well as help develop therapeutics and vaccines to treat and prevent the spread of COVID-19.

Rapid bacterial detection and antibiotic susceptibility testing in whole blood using one-step, high throughput blood digital PCR.

Sepsis due to antimicrobial resistant pathogens is a major health problem worldwide. The inability to rapidly detect and thus treat bacteria with appropriate agents in the early stages of infections leads to excess morbidity, mortality, and healthcare costs. Here we report a rapid diagnostic platform that integrates a novel one-step blood droplet digital PCR assay and a high throughput 3D particle counter system with potential to perform bacterial identification and antibiotic susceptibility profiling directly from whole blood specimens, without requiring culture and sample processing steps. Using CTX-M-9 family ESBLs as a model system, we demonstrated that our technology can simultaneously achieve unprecedented high sensitivity (10 CFU per ml) and rapid sample-to-answer assay time (one hour). In head-to-head studies, by contrast, real time PCR and BioRad ddPCR only exhibited a limit of detection of 1000 CFU per ml and 50-100 CFU per ml, respectively. In a blinded test inoculating clinical isolates into whole blood, we demonstrated 100% sensitivity and specificity in identifying pathogens carrying a particular resistance gene. We further demonstrated that our technology can be broadly applicable for targeted detection of a wide range of antibiotic resistant genes found in both Gram-positive (vanA, nuc, and mecA) and Gram-negative bacteria, including ESBLs (blaCTX-M-1 and blaCTX-M-2 families) and CREs (blaOXA-48 and blaKPC), as well as bacterial speciation (E. coli and Klebsiella spp.) and pan-bacterial detection, without requiring blood culture or sample processing. Our rapid diagnostic technology holds great potential in directing early, appropriate therapy and improved antibiotic stewardship in combating bloodstream infections and antibiotic resistance.

An ultrasensitive test for profiling circulating tumor DNA using integrated comprehensive droplet digital detection.

Current cancer detection systems lack the required sensitivity to reliably detect minimal residual disease (MRD) and recurrence at the earliest stages when treatment would be most effective. To address this issue, we present a novel liquid biopsy approach that utilizes an integrated comprehensive droplet digital detection (IC3D) digital PCR system which combines microfluidic droplet partitioning, fluorescent multiplex PCR chemistry, and our rapid 3D, large-volume droplet counting technology. The IC3D ddPCR assay can detect cancer-specific, ultra-rare genomic targets due to large sample input and high degree of partitioning. We first demonstrate our droplet digital PCR assay can robustly detect common cancer mutants including KRAS G12D spiked in wild-type genomic background or isolated from patient samples with 100% specificity. We then demonstrate that the IC3D ddPCR system can detect oncogenic KRAS G12D mutant alleles against a background of wild-type genomes at a sensitivity of 0.00125-0.005% with a false positive rate of 0% which is 50 to 1000× more sensitive than existing commercial liquid biopsy ddPCR and qPCR platforms, respectively. In addition, our technology can uniquely enable detection of circulating tumor cells using their genetic markers without a pre-enrichment step, and analysis of total tumor DNA isolated from blood samples, which will increase clinical sensitivity and specificity, and minimize inter-assay variability. Therefore, our technology holds the potential to provide clinicians with a powerful decision-making tool to monitor and treat MRD with unprecedented sensitivity for earlier stage intervention.

Development of a cytology-based multivariate analytical risk index for oral cancer.

OBJECTIVES: The diagnosis and management of oral cavity cancers are often complicated by the uncertainty of which patients will undergo malignant transformation, obligating close surveillance over time. However, serial biopsies are undesirable, highly invasive, and subject to inherent issues with poor inter-pathologist agreement and unpredictability as a surrogate for malignant transformation and clinical outcomes. The goal of this study was to develop and evaluate a Multivariate Analytical Risk Index for Oral Cancer (MARIO) with potential to provide non-invasive, sensitive, and quantitative risk assessments for monitoring lesion progression. MATERIALS AND METHODS: A series of predictive models were developed and validated using previously recorded single-cell data from oral cytology samples resulting in a "continuous risk score". Model development consisted of: (1) training base classification models for each diagnostic class pair, (2) pairwise coupling to obtain diagnostic class probabilities, and (3) a weighted aggregation resulting in a continuous MARIO. RESULTS AND CONCLUSIONS: Diagnostic accuracy based on optimized cut-points for the test dataset ranged from 76.0% for Benign, to 82.4% for Dysplastic, 89.6% for Malignant, and 97.6% for Normal controls for an overall MARIO accuracy of 72.8%. Furthermore, a strong positive relationship with diagnostic severity was demonstrated (Pearson's coefficient = 0.805 for test dataset) as well as the ability of the MARIO to respond to subtle changes in cell composition. The development of a continuous MARIO for PMOL is presented, resulting in a sensitive, accurate, and non-invasive method with potential for enabling monitoring disease progression, recurrence, and the need for therapeutic intervention of these lesions.

Risk Stratification of Oral Potentially Malignant Disorders in Fanconi Anemia Patients Using Autofluorescence Imaging and Cytology-On-A Chip Assay.

Fanconi anemia (FA) is a hereditary genomic instability disorder with a predisposition to leukemia and oral squamous cell carcinomas (OSCCs). Hematopoietic stem cell transplantation (HSCT) facilitates cure of bone marrow failure and leukemia and thus extends life expectancy in FA patients; however, survival of hematologic malignancies increases the risk of OSCC in these patients. We developed a "cytology-on-a-chip" (COC)-based brush biopsy assay for monitoring patients with oral potentially malignant disorders (OPMDs). Using this COC assay, we measured and correlated the cellular morphometry and Minichromosome Maintenance Complex Component 2 (MCM2) expression levels in brush biopsy samples of FA patients' OPMD with clinical risk indicators such as loss of autofluorescence (LOF), HSCT status, and mutational profiles identified by next-generation sequencing. Statistically significant differences were found in several cytology measurements based on high-risk indicators such as LOF-positive and HSCT-positive status, including greater variation in cell area and chromatin distribution, higher MCM2 expression levels, and greater numbers of white blood cells and cells with enlarged nuclei. Higher OPMD risk scores were associated with differences in the frequency of nuclear aberrations and differed based on LOF and HSCT statuses. We identified mutation of FAT1 gene in five and NOTCH-2 and TP53 genes in two cases of FA patients' OPMD. The high-risk OPMD of a non-FA patient harbored FAT1, CASP8, and TP63 mutations. Use of COC assay in combination with visualization of LOF holds promise for the early diagnosis of high-risk OPMD. These minimally invasive diagnostic tools are valuable for long-term surveillance of OSCC in FA patients and avoidance of unwarranted scalpel biopsies.

Innovative Programmable Bio-Nano-Chip Digitizes Biology Using Sensors That Learn Bridging Biomarker Discovery and Clinical Implementation.

The lack of standard tools and methodologies and the absence of a streamlined multimarker approval process have hindered the translation rate of new biomarkers into clinical practice for a variety of diseases afflicting humankind. Advanced novel technologies with superior analytical performance and reduced reagent costs, like the programmable bio-nano-chip system featured in this article, have potential to change the delivery of healthcare. This universal platform system has the capacity to digitize biology, resulting in a sensor modality with a capacity to learn. With well-planned device design, development, and distribution plans, there is an opportunity to translate benchtop discoveries in the genomics, proteomics, metabolomics, and glycomics fields by transforming the information content of key biomarkers into actionable signatures that can empower physicians and patients for a better management of healthcare. While the process is complicated and will take some time, showcased here are three application areas for this flexible platform that combines biomarker content with minimally invasive or non-invasive sampling, such as brush biopsy for oral cancer risk assessment; serum, plasma, and small volumes of blood for the assessment of cardiac risk and wellness; and oral fluid sampling for drugs of abuse testing at the point of need.

'Cytology-on-a-chip' based sensors for monitoring of potentially malignant oral lesions.

UNLABELLED: Despite significant advances in surgical procedures and treatment, long-term prognosis for patients with oral cancer remains poor, with survival rates among the lowest of major cancers. Better methods are desperately needed to identify potential malignancies early when treatments are more effective. OBJECTIVE: To develop robust classification models from cytology-on-a-chip measurements that mirror diagnostic performance of gold standard approach involving tissue biopsy. MATERIALS AND METHODS: Measurements were recorded from 714 prospectively recruited patients with suspicious lesions across 6 diagnostic categories (each confirmed by tissue biopsy -histopathology) using a powerful new 'cytology-on-a-chip' approach capable of executing high content analysis at a single cell level. Over 200 cellular features related to biomarker expression, nuclear parameters and cellular morphology were recorded per cell. By cataloging an average of 2000 cells per patient, these efforts resulted in nearly 13 million indexed objects. RESULTS: Binary "low-risk"/"high-risk" models yielded AUC values of 0.88 and 0.84 for training and validation models, respectively, with an accompanying difference in sensitivity+specificity of 6.2%. In terms of accuracy, this model accurately predicted the correct diagnosis approximately 70% of the time, compared to the 69% initial agreement rate of the pool of expert pathologists. Key parameters identified in these models included cell circularity, Ki67 and EGFR expression, nuclear-cytoplasmic ratio, nuclear area, and cell area. CONCLUSIONS: This chip-based approach yields objective data that can be leveraged for diagnosis and management of patients with PMOL as well as uncovering new molecular-level insights behind cytological differences across the OED spectrum.

Interobserver agreement in dysplasia grading: toward an enhanced gold standard for clinical pathology trials.

OBJECTIVE: Interobserver agreement in the context of oral epithelial dysplasia (OED) grading has been notoriously unreliable and can impose barriers for developing new molecular markers and diagnostic technologies. This paper aimed to report the details of a 3-stage histopathology review and adjudication process with the goal of achieving a consensus histopathologic diagnosis of each biopsy. STUDY DESIGN: Two adjacent serial histologic sections of oral lesions from 846 patients were independently scored by 2 different pathologists from a pool of 4. In instances where the original 2 pathologists disagreed, a third, independent adjudicating pathologist conducted a review of both sections. If a majority agreement was not achieved, the third stage involved a face-to-face consensus review. RESULTS: Individual pathologist pair κ values ranged from 0.251 to 0.706 (fair-good) before the 3-stage review process. During the initial review phase, the 2 pathologists agreed on a diagnosis for 69.9% of the cases. After the adjudication review by a third pathologist, an additional 22.8% of cases were given a consensus diagnosis (agreement of 2 out of 3 pathologists). After the face-to-face review, the remaining 7.3% of cases had a consensus diagnosis. CONCLUSIONS: The use of the defined protocol resulted in a substantial increase (30%) in diagnostic agreement and has the potential to improve the level of agreement for establishing gold standards for studies based on histopathologic diagnosis.