A fluorescent plasmonic biochip assay for multiplex screening of diagnostic serum antibody targets in human Lyme disease

Microfluidic systems for infectious disease diagnostics

Microorganisms, encompassing both uni- and multicellular entities, exhibit remarkable diversity as omnipresent life forms in nature. They play a pivotal role by supplying essential components for sustaining biological processes across diverse ecosystems, including higher host organisms. The complex interactions within the human gut microbiota are crucial for metabolic functions, immune responses, and biochemical signalling, particularly through the gut-brain axis. Viruses also play important roles in biological processes, for example by increasing genetic diversity through horizontal gene transfer when replicating inside living cells. On the other hand, infection of the human body by microbiological agents may lead to severe physiological disorders and diseases. Infectious diseases pose a significant burden on global healthcare systems, characterized by substantial variations in the epidemiological landscape. Fast spreading antibiotic resistance or uncontrolled outbreaks of communicable diseases are major challenges at present. Furthermore, delivering field-proven point-of-care diagnostic tools to the most severely affected populations in low-resource settings is particularly important and challenging. New paradigms and technological approaches enabling rapid and informed disease management need to be implemented. In this respect, infectious disease diagnostics taking advantage of microfluidic systems combined with integrated biosensor-based pathogen detection offers a host of innovative and promising solutions. In this review, we aim to outline recent activities and progress in the development of microfluidic diagnostic tools. Our literature research mainly covers the last 5 years. We will follow a classification scheme based on the human body systems primarily involved at the clinical level or on specific pathogen transmission modes. Important diseases, such as tuberculosis and malaria, will be addressed more extensively.

Immunoblot Criteria for Diagnosis of Lyme Disease: A Comparison of CDC Criteria to Alternative Interpretive Approaches

The current Centers for Disease Control and Prevention (CDC) interpretive criteria for serodiagnosis of Lyme disease (LD) involve a two-tiered approach, consisting of a first-tier EIA, IFA, or chemiluminescent assay, followed by confirmation of positive or equivocal results by either immunoblot or a second-tier EIA. To increase overall sensitivity, single-tier alternative immunoblot assays have been proposed, often utilizing antigens from multiple Borrelia burgdorferi strains or genospecies in a single immunoblot; including OspA and OspB in their antigen panel; requiring fewer positive bands than permitted by current CDC criteria; and reporting equivocal results. Published reports concerning alternative immunoblot assays have used relatively small numbers of LD patients and controls to evaluate novel multi-antigen assays and interpretive criteria. We compared the two most commonly used alternative immunoblot interpretive criteria (labeled A and B) to CDC criteria using data from multiple FDA-cleared IgG and IgM immunoblot test kits. These single-tier alternative interpretive criteria, applied to both IgG and IgM immunoblots, demonstrated significantly more false-positive or equivocal results in healthy controls than two-tiered CDC criteria (12.4% and 35.0% for Criteria A and B, respectively, versus 1.0% for CDC criteria). Due to limited standardization and high false-positive rates, the presently evaluated single-tier alternative immunoblot interpretive criteria appear inferior to CDC two-tiered criteria.

Development of a biomarker signature using grating-coupled fluorescence plasmonic microarray for diagnosis of MIS-C

Multisystem inflammatory syndrome in children (MIS-C) is a rare but serious condition that can develop 4–6 weeks after a school age child becomes infected by SARS-CoV-2. To date, in the United States more than 8,862 cases of MIS-C have been identified and 72 deaths have occurred. This syndrome typically affects children between the ages of 5–13; 57% are Hispanic/Latino/Black/non-Hispanic, 61% of patients are males and 100% have either tested positive for SARS-CoV-2 or had direct contact with someone with COVID-19. Unfortunately, diagnosis of MIS-C is difficult, and delayed diagnosis can lead to cardiogenic shock, intensive care admission, and prolonged hospitalization. There is no validated biomarker for the rapid diagnosis of MIS-C. In this study, we used Grating-coupled Fluorescence Plasmonic (GCFP) microarray technology to develop biomarker signatures in pediatric salvia and serum samples from patients with MIS-C in the United States and Colombia. GCFP measures antibody-antigen interactions at individual regions of interest (ROIs) on a gold-coated diffraction grating sensor chip in a sandwich immunoassay to generate a fluorescent signal based on analyte presence within a sample. Using a microarray printer, we designed a first-generation biosensor chip with the capability of capturing 33 different analytes from 80 μL of sample (saliva or serum). Here, we show potential biomarker signatures in both saliva and serum samples in six patient cohorts. In saliva samples, we noted occasional analyte outliers on the chip within individual samples and were able to compare those samples to 16S RNA microbiome data. These comparisons indicate differences in relative abundance of oral pathogens within those patients. Microsphere Immunoassay (MIA) of immunoglobulin isotypes was also performed on serum samples and revealed MIS-C patients had several COVID antigen-specific immunoglobulins that were significantly higher than other cohorts, thus identifying potential new targets for the second-generation biosensor chip. MIA also identified additional biomarkers for our second-generation chip, verified biomarker signatures generated on the first-generation chip, and aided in second-generation chip optimization. Interestingly, MIS-C samples from the United States had a more diverse and robust signature than the Colombian samples, which was also illustrated in the MIA cytokine data. These observations identify new MIS-C biomarkers and biomarker signatures for each of the cohorts. Ultimately, these tools may represent a potential diagnostic tool for use in the rapid identification of MIS-C.

Dual detection of COVID-19 antigens and antibodies using nanoscale fluorescent plasmonic substrates

There is a continuing need for biosensors that can be used in the diagnosis of COVID-19 infection and to measure a subject's immune response to the virus itself (SARS-CoV-2). In this study, grating-coupled fluorescent plasmonic (GC-FP)-based detection of SARS-CoV-2 antigens was coupled with antibody detection to yield a dual-mode detection assay. Pairs of capture and detection antibodies were screened for direct detection of the SARS-CoV-2 nucleocapsid (Nuc) antigen, which were then combined with an existing GC-FP antibody detection assay. Nuc could be detected as low as 1 µg/mL concentrations, while antibodies were detectable to 50 ng/mL. The dual detection assay was tested by adding purified Nuc antigen to serum from a polymerase chain reaction (PCR)-positive COVID-19-infected individual. Using this sample, co-detection of Nuc antigen and anti-spike protein antibodies was successfully performed on a single GC-FP chip. Total assay time was 1 h, making this the first known example of rapid dual antibody and antigen detection on the same biosensor chip.

Acute lyme disease IgG N-linked glycans contrast the canonical inflammatory signature

Lyme disease (LD) infection is caused by Borrelia burgdorferi sensu lato (Bb). Due to the limited presence of this pathogen in the bloodstream in humans, diagnosis of LD relies on seroconversion. Immunoglobulins produced in response to infection are differentially glycosylated to promote or inhibit downstream inflammatory responses by the immune system. Immunoglobulin G (IgG) N-glycan responses to LD have not been characterized. In this study, we analyzed IgG N-glycans from cohorts of healthy controls, acute LD patient serum, and serum collected after acute LD patients completed a 2- to 3-week course of antibiotics and convalesced for 70-90 days. Results indicate that during the acute phase of Bb infection, IgG shifts its glycosylation profile to include structures that are not associated with the classic proinflammatory IgG N-glycan signature. This unexpected result is in direct contrast to what is reported for other inflammatory diseases. Furthermore, IgG N-glycans detected during acute LD infection discriminated between control, acute, and treated cohorts with a sensitivity of 75-100% and specificity of 94.7-100%.

Modified ELISA for Ultrasensitive Diagnosis

An enzyme-linked immunosorbent assay (ELISA) can be used for quantitative measurement of proteins, and improving the detection sensitivity to the ultrasensitive level would facilitate the diagnosis of various diseases. In the present review article, we first define the term 'ultrasensitive'. We follow this with a survey and discussion of the current literature regarding modified ELISA methods with ultrasensitive detection and their application for diagnosis. Finally, we introduce our own newly devised system for ultrasensitive ELISA combined with thionicotinamide adenine dinucleotide cycling and its application for the diagnosis of infectious diseases and lifestyle-related diseases. The aim of the present article is to expand the application of ultrasensitive ELISAs in the medical and biological fields.

Rapid and Quantitative Detection of Human Antibodies against the 2019 Novel Coronavirus SARS CoV2 and Its Variants as a Result of Vaccination and Infection

Measuring the antibody response to 2019 SARS CoV2 is critical for diagnostic purposes, for monitoring the prevalence of infection, and for gauging the efficacy of the worldwide vaccination effort for COVID-19. In this study, a microchip-based grating-coupled fluorescent plasmonic (GC-FP) assay was used to measure antibody levels that resulted from COVID-19 infection and vaccination. In addition, we measured the relative antibody binding toward antigens from the CoV2 virus variants strains B.1.1.7 (Alpha) and B.1.351 (Beta). Antibody levels against multiple antigens within the SARS CoV2 spike protein were significantly elevated for both vaccinated and infected individuals, while those against the nucleocapsid (N) protein were only elevated for infected individuals. GC-FP was effective for monitoring the IgG-based serological response to vaccination throughout the vaccination sequence and also resolved acute (within hours) increases in antibody levels. A significant decrease in antibody binding to antigens from the B.1.351 variant, but not B.1.1.7, was observed for all vaccinated subjects when measured by GC-FP compared to the 2019 SARS CoV2 antigens. These results were corroborated by competitive enzyme-linked immunosorbent assay (ELISA). Collectively, the findings suggest that GC-FP is a viable, rapid, and accurate method for measuring both overall antibody levels to SARS CoV2 and relative antibody binding to viral variants during infection or vaccination. IMPORTANCE In this work, a novel biosensor technology was used to measure antibody levels that resulted from vaccination against COVID-19 and/or from infection with the virus. Importantly, this approach enables quantification of antibody levels, which can provide information about the timing and level of immune response. Due the multiplexed nature of this approach, antibody binding to both the original 2019 SARS CoV-2 strain and variant strains can be performed simultaneously and in a short (30-min) time frame.

Early Warning Diagnostics for Emerging Infectious Diseases in Developing into Late-Stage Pandemics

The spread of infectious diseases due to travel and trade can be seen throughout history, whether from early settlers or traveling businessmen. Increased globalization has allowed infectious diseases to quickly spread to different parts of the world and cause widespread infection. Posthoc analysis of more recent outbreaks-SARS, MERS, swine flu, and COVID-19-has demonstrated that the causative viruses were circulating through populations for days or weeks before they were first detected, allowing disease to spread before quarantines, contact tracing, and travel restrictions could be implemented. Earlier detection of future novel pathogens could decrease the time before countermeasures are enacted. In this Account, we examined a variety of novel technologies from the past 10 years that may allow for earlier detection of infectious diseases. We have arranged these technologies chronologically from pre-human predictive technologies to population-level screening tools. The earliest detection methods utilize artificial intelligence to analyze factors such as climate variation and zoonotic spillover as well as specific species and geographies to identify where the infection risk is high. Artificial intelligence can also be used to monitor health records, social media, and various publicly available data to identify disease outbreaks faster than traditional epidemiology. Secondary to predictive measures is monitoring infection in specific sentinel animal species, where domestic animals or wildlife are indicators of potential disease hotspots. These hotspots inform public health officials about geographic areas where infection risk in humans is high. Further along the timeline, once the disease has begun to infect humans, wastewater epidemiology can be used for unbiased sampling of large populations. This method has already been shown to precede spikes in COVID-19 diagnoses by 1 to 2 weeks. As total infections increase in humans, bioaerosol sampling in high-traffic areas can be used for disease monitoring, such as within an airport. Finally, as disease spreads more quickly between humans, rapid diagnostic technologies such as lateral flow assays and nucleic acid amplification become very important. Minimally invasive point-of-care methods can allow for quick adoption and use within a population. These individual diagnostic methods then transfer to higher-throughput methods for more intensive population screening as an infection spreads. There are many promising early warning technologies being developed. However, no single technology listed herein will prevent every future outbreak. A combination of technologies from across our infection timeline would offer the most benefit in preventing future widespread disease outbreaks and pandemics.

Quantitative multiplexed strategies for human Lyme disease serological testing

Lyme disease, which is primarily caused by infection with the bacterium Borrelia burgdorferi in the United States or other Borrelia species internationally, presents an ongoing challenge for diagnostics. Serological testing is the primary means of diagnosis but testing approaches differ widely, with varying degrees of sensitivity and specificity. Moreover, there is currently no reliable test to determine disease resolution following treatment. A distinct challenge in Lyme disease diagnostics is the variable patterns of human immune response to a plurality of antigens presented by Borrelia spp. during the infection. Thus, multiplexed testing approaches that capture these patterns and detect serological response against multiple antigens may be the key to prompt, accurate Lyme disease diagnosis. In this review, current state-of-the-art multiplexed diagnostic approaches are presented and compared with respect to their diagnostic accuracy and their potential for monitoring response to treatment.

Multiplexed detection and quantification of human antibody response to COVID-19 infection using a plasmon enhanced biosensor platform

The 2019 SARS CoV-2 (COVID-19) pandemic has illustrated the need for rapid and accurate diagnostic tests. In this work, a multiplexed grating-coupled fluorescent plasmonics (GC-FP) biosensor platform was used to rapidly and accurately measure antibodies against COVID-19 in human blood serum and dried blood spot samples. The GC-FP platform measures antibody-antigen binding interactions for multiple targets in a single sample, and has 100% selectivity and sensitivity (n = 23) when measuring serum IgG levels against three COVID-19 antigens (spike S1, spike S1S2, and the nucleocapsid protein). The GC-FP platform yielded a quantitative, linear response for serum samples diluted to as low as 1:1600 dilution. Test results were highly correlated with two commercial COVID-19 antibody tests, including an enzyme linked immunosorbent assay (ELISA) and a Luminex-based microsphere immunoassay. To demonstrate test efficacy with other sample matrices, dried blood spot samples (n = 63) were obtained and evaluated with GC-FP, yielding 100% selectivity and 86.7% sensitivity for diagnosing prior COVID-19 infection. The test was also evaluated for detection of multiple immunoglobulin isotypes, with successful detection of IgM, IgG and IgA antibody-antigen interactions. Last, a machine learning approach was developed to accurately score patient samples for prior COVID-19 infection, using antibody binding data for all three COVID-19 antigens used in the test.

Lyme Disease Biosensors: A Potential Solution to a Diagnostic Dilemma

Over the past four decades, Lyme disease has remained a virulent and pervasive illness, persisting throughout North America and many other regions of the world. Recent increases in illness in many countries has sparked a renewed interest in improved Lyme diagnostics. While current standards of diagnosis are acceptable for the late stages of the disease, it remains difficult to accurately diagnose early forms of the illness. In addition, current diagnostic methods tend to be relatively expensive and require a large degree of laboratory-based analysis. Biosensors represent the fusion of biological materials with chemical techniques to provide simple, inexpensive alternatives to traditional diagnostic methods. Lyme disease biosensors have the potential to better diagnose early stages of the illness and provide possible patients with an inexpensive, commercially available test. This review examines the current state of Lyme disease biosensing, with a focus on previous biosensor development and essential future considerations.