A Multiplexed Serologic Test for Diagnosis of Lyme Disease for Point-of-Care Use

Identification of reactive Borrelia burgdorferi peptides associated with Lyme disease

Borrelia burgdorferi, the agent of Lyme disease, is estimated to cause >400,000 annual infections in the United States. Serology is the primary laboratory method to support the diagnosis of Lyme disease, but current methods have intrinsic limitations that require alternative approaches or targets. We used a high-density peptide array that contains >90,000 short overlapping peptides to catalog immunoreactive linear epitopes from >60 primary antigens of B. burgdorferi. We then pursued a machine learning approach to identify immunoreactive peptide panels that provide optimal Lyme disease serodiagnosis and can differentiate antibody responses at various stages of disease. We examined 226 serum samples from the Lyme Biobank and the National Institutes of Health, which included sera from 110 individuals diagnosed with Lyme disease, 31 probable cases from symptomatic individuals, and 85 healthy controls. Cases were grouped based on disease stage and presentation and included individuals with early localized, early disseminated, and late Lyme disease. We identified a peptide panel originating from 14 different epitopes that differentiated cases versus controls, whereas another peptide panel built from 12 unique epitopes differentiated subjects with various disease manifestations. Our method demonstrated an improvement in B. burgdorferi antibody detection over the current two-tiered testing approach and confirmed the key diagnostic role of VlsE and FlaB antigens at all stages of Lyme disease. We also uncovered epitopes that triggered a temporal antibody response that was useful for differentiation of early and late disease. Our findings can be used to streamline serologic targets and improve antibody-based diagnosis of Lyme disease.

IMPORTANCE

Serology is the primary method of Lyme disease diagnosis, but this approach has limitations, particularly early in disease. Currently employed antibody detection assays can be improved by the identification of alternative immunodominant epitopes and the selection of optimal diagnostic targets. We employed high-density peptide arrays that enabled precise epitope mapping for a wide range of B. burgdorferi antigens. In combination with machine learning, this approach facilitated the selection of serologic targets early in disease and the identification of serological indicators associated with different manifestations of Lyme disease. This study provides insights into differential antibody responses during infection and outlines a new approach for improved serologic diagnosis of 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.

Direct Detection of Lyme Borrelia: Recent Advancement and Use of Aptamer Technology

Borrelia burgdorferi sensu lato (B. burgdorferi s.l.), which is predominantly spread by ticks, is the cause of Lyme disease (LD), also known as Lyme borreliosis, one of the zoonotic diseases affecting people. In recent years, LD has become more prevalent worldwide, even in countries with no prior records. Currently, Lyme Borrelia detection is achieved through nucleic acid amplification, antigen detection, microscopy, and in vitro culture. Nevertheless, these methods lack sensitivity in the early phase of the disease and, thus, are unable to confirm active infection. This review briefly discusses the existing direct detection methods of LD. Furthermore, this review also introduces the use of aptamer technology integrated with biosensor platforms to detect the Borrelia antigen. This aptamer technology could be explored using other biosensor platforms targeting whole Borrelia cells or specific molecules to enhance Borrelia detection in the future.

Cholesterol Contributes to Risk, Severity, and Machine Learning-Driven Diagnosis of Lyme Disease

BACKGROUND

Lyme disease is the most prevalent vector-borne disease in the US, yet its host factors are poorly understood and diagnostic tests are limited. We evaluated patients in a large health system to uncover cholesterol's role in the susceptibility, severity, and machine learning-based diagnosis of Lyme disease.

METHODS

A longitudinal health system cohort comprised 1 019 175 individuals with electronic health record data and 50 329 with linked genetic data. Associations of blood cholesterol level, cholesterol genetic scores comprising common genetic variants, and burden of rare loss-of-function (LoF) variants in cholesterol metabolism genes with Lyme disease were investigated. A portable machine learning model was constructed and tested to predict Lyme disease using routine lipid and clinical measurements.

RESULTS

There were 3832 cases of Lyme disease. Increasing cholesterol was associated with greater risk of Lyme disease and hypercholesterolemia was more prevalent in Lyme disease cases than in controls. Cholesterol genetic scores and rare LoF variants in CD36 and LDLR were associated with Lyme disease risk. Serological profiling of cases revealed parallel trajectories of rising cholesterol and immunoglobulin levels over the disease course, including marked increases in individuals with LoF variants and high cholesterol genetic scores. The machine learning model predicted Lyme disease solely using routine lipid panel, blood count, and metabolic measurements.

CONCLUSIONS

These results demonstrate the value of large-scale genetic and clinical data to reveal host factors underlying infectious disease biology, risk, and prognosis and the potential for their clinical translation to machine learning diagnostics that do not need specialized assays.

Lyme borreliosis diagnosis: state of the art of improvements and innovations

With almost 700 000 estimated cases each year in the United States and Europe, Lyme borreliosis (LB), also called Lyme disease, is the most common tick-borne illness in the world. Transmitted by ticks of the genus Ixodes and caused by bacteria Borrelia burgdorferi sensu lato, LB occurs with various symptoms, such as erythema migrans, which is characteristic, whereas others involve blurred clinical features such as fatigue, headaches, arthralgia, and myalgia. The diagnosis of Lyme borreliosis, based on a standard two-tiered serology, is the subject of many debates and controversies, since it relies on an indirect approach which suffers from a low sensitivity depending on the stage of the disease. Above all, early detection of the disease raises some issues. Inappropriate diagnosis of Lyme borreliosis leads to therapeutic wandering, inducing potential chronic infection with a strong antibody response that fails to clear the infection. Early and proper detection of Lyme disease is essential to propose an adequate treatment to patients and avoid the persistence of the pathogen. This review presents the available tests, with an emphasis on the improvements of the current diagnosis, the innovative methods and ideas which, ultimately, will allow more precise detection of LB.

Electrochemical Detection of Borrelia burgdorferi Using a Biomimetic Flow Cell System

Lyme disease, caused by infection with pathogenic Borrelia bacteria, has emerged as a pervasive illness throughout North America and many other regions of the world in recent years, owing in part to climate-mediated habitat expansion of the tick vectors. Standard diagnostic testing has remained largely unchanged over the past several decades and is indirect, relying on detection of antibodies against the Borrelia pathogen, rather than detection of the pathogen itself. The development of new rapid, point-of-care tests for Lyme disease that directly detects the pathogen could drastically improve patient health by enabling faster and more frequent testing that could better inform patient treatment. Here, we describe a proof-of-concept electrochemical sensing approach to the detection of the Lyme disease-causing bacteria, which utilizes a biomimetic electrode to interact with the Borrelia bacteria that induce impedance alterations. In addition, the catch-bond mechanism between bacterial BBK32 protein and human fibronectin protein, which exhibits improved bond strength with increased tensile force, is tested within an electrochemical injection flow-cell to achieve Borrelia detection under shear stress.

A portable immunosensor provides sensitive and rapid detection of Borrelia burgdorferi antigen in spiked blood

There are no assays for detecting B. burgdorferi antigen in blood of infected Lyme disease individuals. Here, we provide proof-of-principle evidence that we can quantify B. burgdorferi antigen in spiked blood using a portable smartphone-based fluorescence microscope that measures immunoagglutination on a paper microfluidic chip. We targeted B. burgdorferi OspA to develop a working prototype and added examples of two antigens (OspC and VlsE) that have diagnostic value for discrimination of Lyme disease stage. Using an extensively validated monoclonal antibody to OspA (LA-2), detection of OspA antigen had a broad linear range up to 100 pg/mL in 1% blood and the limit of detection (LOD) was 100 fg/mL (= 10 pg/mL in undiluted blood), which was 1000 times lower than our target of 10 ng/mL. Analysis of the two other targets was done using polyclonal and monoclonal antibodies. OspC antigen was detected at LOD 100 pg/mL (= 10 ng/mL of undiluted blood) and VlsE antigen was detected at LOD 1-10 pg/mL (= 0.1-1 ng/mL of undiluted blood). The method is accurate and was performed in 20 min from sample to answer. When optimized for detecting several B. burgdorferi antigens, this assay may differentiate active from past infections and facilitate diagnosis of Lyme disease in the initial weeks of infection, when antibody presence is typically below the threshold to be detected by serologic methods.

Recent Advances in the Immunologic Method Applied to Tick-Borne Diseases in Brazil

Zoonotic-origin infectious diseases are one of the major concerns of human and veterinary health systems. Ticks, as vectors of several zoonotic diseases, are ranked second only to mosquitoes as vectors. Many ticks’ transmitted infections are still endemic in the Americas, Europe, and Africa and represent approximately 17% of their infectious diseases population. Although our scientific capacity to identify and diagnose diseases is increasing, it remains a challenge in the case of tick-borne conditions. For example, in 2017, 160 cases of the Brazilian Spotted Fever (BSF, a tick-borne illness) were confirmed, alarming the notifiable diseases information system. Conversely, Brazilian borreliosis and ehrlichiosis do not require notification. Still, an increasing number of cases in humans and dogs have been reported in southeast and northeastern Brazil. Immunological methods applied to human and dog tick-borne diseases (TBD) show low sensitivity and specificity, cross-reactions, and false IgM positivity. Thus, the diagnosis and management of TBD are hampered by the personal tools and indirect markers used. Therefore, specific and rapid methods urgently need to be developed to diagnose the various types of tick-borne bacterial diseases. This review presents a brief historical perspective on the evolution of serological assays and recent advances in diagnostic tests for TBD (ehrlichiosis, BSF, and borreliosis) in humans and dogs, mainly applied in Brazil. Additionally, this review covers the emerging technologies available in diagnosing TBD, including biosensors, and discusses their potential for future use as gold standards in diagnosing these diseases.

Predicting Antigenic Peptides from Rocio Virus NS1 Protein for Immunodiagnostic Testing Using Immunoinformatics and Molecular Dynamics Simulation

The mosquito-borne disease caused by the Rocio virus is a neglected threat, and new immune inputs for serological testing are urgently required for diagnosis in low-resource settings and epidemiological surveillance. We used in silico approaches to identify a specific antigenic peptide (p_ROCV2) in the NS1 protein of the Rocio virus that was theoretically predicted to be stable and exposed on its surface, where it demonstrated key properties allowing it to interact with antibodies. These findings related to the molecular dynamics of this peptide provide important insights for advancing diagnostic platforms and investigating therapeutic alternatives.

Retrospective Evaluation of Various Serological Assays and Multiple Parameters for Optimal Diagnosis of Lyme Neuroborreliosis in a Routine Clinical Setting

Laboratory diagnosis of Lyme neuroborreliosis (LNB) is challenging, and validated diagnostic algorithms are lacking. Therefore, this retrospective cross-sectional study aimed to compare the diagnostic performance of seven commercial antibody assays for LNB diagnosis. Random forest (RF) modeling was conducted to investigate whether the diagnostic performance using the antibody assays could be improved by including several routine cerebrospinal fluid (CSF) parameters (i.e., leukocyte count, total protein, blood-CSF barrier functionality, and intrathecal total antibody synthesis), two-tier serology on serum, the CSF level of the B-cell chemokine (C-X-C motif) ligand 13 (CXCL13), and a Borrelia species PCR on CSF. In total, 156 patients were included who were classified as definite LNB (n = 10), possible LNB (n = 7), or non-LNB patient (n = 139) according to the criteria of the European Federation of Neurological Societies using a consensus strategy for intrathecal Borrelia-specific antibody synthesis. The seven antibody assays showed sensitivities ranging from 47.1% to 100% and specificities ranging from 95.7% to 100%. RF modeling demonstrated that the sensitivities of most antibody assays could be improved by including other parameters to the diagnostic repertoire for diagnosing LNB (range: 94.1% to 100%), although with slightly lower specificities (range: 92.8% to 96.4%). The most important parameters for LNB diagnosis are the detection of intrathecally produced Borrelia-specific antibodies, two-tier serology on serum, CSF-CXCL13, Reibergram classification, and pleocytosis. In conclusion, this study shows that LNB diagnosis is best supported using multiparameter analysis. Furthermore, a collaborative prospective study is proposed to investigate if a standardized diagnostic algorithm can be developed for improved LNB diagnosis. IMPORTANCE The diagnosis of LNB is established by clinical symptoms, pleocytosis, and proof of intrathecal synthesis of Borrelia-specific antibodies. Laboratory diagnosis of LNB is challenging, and validated diagnostic algorithms are lacking. Therefore, this retrospective cross-sectional study aimed to compare the diagnostic performance of seven commercial antibody assays for LNB diagnosis. Multiparameter analysis was conducted to investigate whether the diagnostic performance using the antibody assays could be improved by including several routine (CSF) parameters. The results of this study show that LNB diagnosis is best supported using the detection of intrathecally produced Borrelia-specific antibodies, two-tier serology on serum, CSF-CXCL13, Reibergram classification, and pleocytosis. Furthermore, we propose a collaborative prospective study to investigate the potential role of constructing a diagnostic algorithm using multiparameter analysis for improved LNB diagnosis.

A focused review on Lyme disease diagnostic testing: An update on serology algorithms, current ordering practices, and practical considerations for laboratory implementation of a new testing algorithm

Lyme borreliosis or Lyme disease (LD) is the most prevalent tick-borne illness in the United States. Diagnosing LD can be challenging as symptoms can be nonspecific and the ability of laboratory tests to detect infection varies based on the duration of infection and the methodology used. To date, serology testing is the primary laboratory tool employed to aid in diagnosing LD. Since the mid-1990's, a two-tiered algorithm has been recommended for the optimization of specificity while maintaining high sensitivity. This mini-review aims to provide an overview of LD diagnostic testing in North America, with an emphasis on serologic algorithms, in particular the modified two-tiered testing (MTTT) algorithm, along with a discussion on provider ordering patterns and practical considerations for implementation of MTTT.

Point-of-care diagnostics: recent developments in a pandemic age

In this review, we provide an overview of developments in point-of-care (POC) diagnostics during the COVID-19 pandemic. We review these advances within the framework of a holistic POC ecosystem, focusing on points of interest - both technological and non-technological - to POC researchers and test developers. Technologically, we review design choices in assay chemistry, microfluidics, and instrumentation towards nucleic acid and protein detection for severe acute respiratory coronavirus 2 (SARS-CoV-2), and away from the lab bench, developments that supported the unprecedented rapid development, scale up, and deployment of POC devices. We describe common features in the POC technologies that obtained Emergency Use Authorization (EUA) for nucleic acid, antigen, and antibody tests, and how these tests fit into four distinct POC use cases. We conclude with implications for future pandemics, infectious disease monitoring, and digital health.

Identification of Immunogenic Linear B-Cell Epitopes in C. burnetii Outer Membrane Proteins Using Immunoinformatics Approaches Reveals Potential Targets of Persistent Infections

Coxiella burnetii is a global, highly infectious intracellular bacterium, able to infect a wide range of hosts and to persist for months in the environment. It is the etiological agent of Q fever—a zoonosis of global priority. Currently, there are no national surveillance data on C. burnetii’s seroprevalence for any South American country, reinforcing the necessity of developing novel and inexpensive serological tools to monitor the prevalence of infections among humans and animals—especially cattle, goats, and sheep. In this study, we used immunoinformatics and computational biology tools to predict specific linear B-cell epitopes in three C. burnetii outer membrane proteins: OMP-H (CBU_0612), Com-1 (CBU_1910), and OMP-P1 (CBU_0311). Furthermore, predicted epitopes were tested by ELISA, as synthetic peptides, against samples of patients reactive to C. burnetii in indirect immunofluorescence assay, in order to evaluate their natural immunogenicity. In this way, two linear B-cell epitopes were identified in each studied protein (OMP-H_(51–59), OMP-H_(91–106), Com-1_(57–76), Com-1_(191–206), OMP-P1_(197–209), and OMP-P1_(215–227)); all of them were confirmed as naturally immunogenic by the presence of specific antibodies in 77% of studied patients against at least one of the identified epitopes. Remarkably, a higher frequency of endocarditis cases was observed among patients who presented an intense humoral response to OMP-H and Com-1 epitopes. These data confirm that immunoinformatics applied to the identification of specific B-cell epitopes can be an effective strategy to improve and accelerate the development of surveillance tools against neglected diseases.

Optimizing use of multi-antibody assays for Lyme disease diagnosis: A bioinformatic approach

Multiple different recombinant and peptide antigens are now available for serodiagnosis of Lyme disease (LD), but optimizing test utilization remains challenging. Since 1995 the Centers for Disease Control and Prevention (CDC) has recommended a 2-tiered serologic approach consisting of a first-tier whole-cell enzyme immunoassay (EIA) for polyvalent antibodies to Borrelia burgdorferi followed by confirmation of positive or equivocal results by IgG and IgM immunoblots [standard 2-tiered (STT) approach]. Newer modified 2-tiered (MTT) approaches employ a second-tier EIA to detect antibodies to B. burgdorferi rather than immunoblotting. We applied modern bioinformatic techniques to a large public database of recombinant and peptide antigen-based immunoassays to improve testing strategy. A retrospective CDC collection of 280 LD samples and 559 controls had been tested using the STT approach as well as kinetic-EIAs for VlsE1-IgG, C6-IgG, VlsE1-IgM, and pepC10-IgM antibodies. When used individually, the cutoff for each kinetic-EIA was set to generate 99% specificity. Utilizing logistic-likelihood regression analysis and receiver operating characteristic (ROC) techniques we determined that VlsE1-IgG, C6-IgG, and pepC10-IgM antibodies each contributed significant diagnostic information; a single-tier diagnostic score (DS) was generated for each sample using a weighted linear combination of antibody levels to these 3 antigens. DS performance was then compared to the STT and to MTT models employing different combinations of kinetic-EIAs. After setting the DS cutoff to match STT specificity (99%), the DS was 22.5% more sensitive than the STT for early-acute-phase disease (95% CI: 11.8% to 32.2%), 16.0% more sensitive for early-convalescent-phase disease (95% CI: 7.2% to 24.7%), and equivalent for detection of disseminated infection. The DS was also significantly more sensitive for early-acute-phase LD than MTT models whose specificity met or exceeded 99%. Prospective validation of this single-tier diagnostic score for Lyme disease will require larger studies using a broader range of potential cross-reacting conditions.

Recent Progress in Lyme Disease and Remaining Challenges

Lyme disease (also known as Lyme borreliosis) is the most common vector-borne disease in the United States with an estimated 476,000 cases per year. While historically, the long-term impact of Lyme disease on patients has been controversial, mounting evidence supports the idea that a substantial number of patients experience persistent symptoms following treatment. The research community has largely lacked the necessary funding to properly advance the scientific and clinical understanding of the disease, or to develop and evaluate innovative approaches for prevention, diagnosis, and treatment. Given the many outstanding questions raised into the diagnosis, clinical presentation and treatment of Lyme disease, and the underlying molecular mechanisms that trigger persistent disease, there is an urgent need for more support. This review article summarizes progress over the past 5 years in our understanding of Lyme and tick-borne diseases in the United States and highlights remaining challenges.

Serologic response to Borrelia antigens varies with clinical phenotype in children and young adults with Lyme disease

Lyme disease is commonly diagnosed by serologic response to Borrelia burgdorferi and related species, but the relationship between serologic targets and clinical features is unknown. We developed a multi-antigen Luminex-based panel and evaluated IgG responses in 527 children 1 to 21 years of age assessed for Lyme disease across 4 Pedi Lyme Net emergency departments, including 127 Lyme cases defined by either an erythema migrans (EM) lesion or positive C6 enzyme immunoassay followed by immunoblot and 400 patients considered clinical mimics. Of 42 antigens tested, 26 elicited specific reactivity in Lyme patients, without marked age-dependent variation. Children with single EM lesions typically lacked Borrelia-specific IgG. By principal component analysis, children with early disseminated and late Lyme disease clustered separately from clinical mimics and also from each other. Neurological disease and arthritis exhibited distinct serologic responses, with OspC variants overrepresented in neurological disease and p100, BmpA, p58 and p45 overrepresented in arthritis. Machine learning identified a 3-antigen panel (VlsE_Bb, p41_Bb, OspC_Bafz) that distinguished Lyme disease from clinical mimics with a sensitivity of 86.6% (95% confidence interval [CI] 80.3-92.1) and a specificity of 95.5% (95% CI 93.4-97.4). Sensitivity was much lower in early Lyme disease (38.5%, 95% CI 15.4-69.2). Interestingly, 17 children classified as Lyme mimics had a positive 3-antigen panel, suggesting that more comprehensive serologic analysis could help refine Lyme diagnosis. In conclusion, multiplex antigen panels provide a novel approach to understanding the immune response in Lyme disease, potentially helping to facilitate accurate diagnosis and to understand differences between clinical stages.

Discovery and Surveillance of Tick-Borne Pathogens

Within the past 30 yr molecular assays have largely supplanted classical methods for detection of tick-borne agents. Enhancements provided by molecular assays, including speed, throughput, sensitivity, and specificity, have resulted in a rapid increase in the number of newly characterized tick-borne agents. The use of unbiased high throughput sequencing has enabled the prompt identification of new pathogens and the examination of tick microbiomes. These efforts have led to the identification of hundreds of new tick-borne agents in the last decade alone. However, little is currently known about the majority of these agents beyond their phylogenetic classification. Our article outlines the primary methods involved in tick-borne agent discovery and the current status of our understanding of tick-borne agent diversity.

Metabolomic Laboratory-Developed Tests: Current Status and Perspectives

Laboratory-developed tests (LDTs) are a subset of in vitro diagnostic devices, which the US Food and Drug Administration defines as "tests that are manufactured by and used within a single laboratory". The review describes the emergence and history of LDTs. The current state and development prospects of LDTs based on metabolomics are analyzed. By comparing LDTs with the scientific metabolomics study of human bio samples, the characteristic features of metabolomic LDT are shown, revealing its essence, strengths, and limitations. The possibilities for further developments and scaling of metabolomic LDTs and their potential significance for healthcare are discussed. The legal aspects of LDT regulation in the United States, European Union, and Singapore, demonstrating different approaches to this issue, are also provided. Based on the data presented in the review, recommendations were made on the feasibility and ways of further introducing metabolomic LDTs into practice.

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.

Laboratory Diagnosis of Lyme Borreliosis

Lyme borreliosis is caused by a growing list of related, yet distinct, spirochetes with complex biology and sophisticated immune evasion mechanisms. It may result in a range of clinical manifestations involving different organ systems, and can lead to persistent sequelae in a subset of cases. The pathogenesis of Lyme borreliosis is incompletely understood, and laboratory diagnosis, the focus of this review, requires considerable understanding to interpret the results correctly. Direct detection of the infectious agent is usually not possible or practical, necessitating a continued reliance on serologic testing. Still, some important advances have been made in the area of diagnostics, and there are many promising ideas for future assay development. This review summarizes the state of the art in laboratory diagnostics for Lyme borreliosis, provides guidance in test selection and interpretation, and highlights future directions.

Serum Epitope Repertoire Analysis Enables Early Detection of Lyme Disease with Improved Sensitivity in an Expandable Multiplex Format

Widely employed diagnostic antibody serology for Lyme disease, known as standard two-tier testing (STTT), exhibits insufficient sensitivity in early Lyme disease, yielding many thousands of false-negative test results each year. Given this problem, we applied serum antibody repertoire analysis (SERA), or next-generation sequencing (NGS)-based serology, to discover IgG and IgM antibody epitope motifs capable of detecting Lyme disease-specific antibodies with high sensitivity and specificity. Iterative motif discovery and bioinformatic analysis of epitope repertoires from subjects with Lyme disease (n = 264) and controls (n = 391) yielded a set of 28 epitope motifs representing 20 distinct IgG antibody epitopes and a set of 38 epitope motifs representing 21 distinct IgM epitopes, which performed equivalently in a large validation cohort of STTT-positive samples. In a second validation set from subjects with clinically defined early Lyme disease (n = 119) and controls (n = 257), the SERA Lyme IgG and IgM assay exhibited significantly improved sensitivity relative to STTT (77% versus 62%; Z-test; P = 0.013) and improved specificity (99% versus 97%). Early Lyme disease subjects exhibited significantly fewer reactive epitopes (Mann-Whitney U test; P < 0.0001) relative to subjects with Lyme arthritis. Thus, SERA Lyme IgG and M panels provided increased accuracy in early Lyme disease in a readily expandable multiplex assay format.

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.

Micro-fabrication by wax spraying for rapid smartphone-based quantification of bio-markers

A cheap/rapid technique for the fabrication of μPADs is presented for point of care analysis. Hydrophobic channels were formed across the width of the paper by spraying hot pure wax. This biocompatible novel process yielded uniform 300 ± 5 μm hydrophilic microchannels on paper, without the use of the cleanroom, UV lamp, or organic solvents and was completed in a single step without the need for a hotplate. Hot wax is properly impregnated across paper thickness by spraying under optimized temperature and pressure. Our method is advantageous in the cost and ease of fabrication, process time (<1 min), the feasibility of mass-fabrication, readout, environmental considerations and multiplexing due to the embossed structure of remnant wax. The performance of the resulting μPAD was assessed on a multiplexed Uric acid and Nitride assay, bearing 95% of confidence level in the readout against standardized tests. A novel RGB processing app was developed for smart-phones to quantify colorimetric read-outs through a heuristic normalization equation that converts RGB to integer systems. This combinatorial sensor demonstrates a good linear range (up to 800 μM for Uric acid and 1250 μM for Nitride), low detection limit (100 μM for uric acid and 156 μM for nitride).

Expanding Access to Biospecimens for Lyme Disease Test Development

The laboratory diagnosis of Lyme disease relies upon serologic testing. A standard or modified two-tiered testing algorithm is used to enhance the accuracy of antibody detection. However, this approach suffers from a lack of sensitivity in early Lyme disease. Ongoing efforts to develop more sensitive antibody detection technologies and other diagnostic approaches are dependent upon the availability of quality-assured biospecimens linked to reliable clinical data. In this issue of the Journal of Clinical Microbiology, Horn et al. (E. J. Horn, G. Dempsey, A. M. Schotthoefer, U. L. Prisco, et al., J Clin Microbiol 58:e00032-20, 2020, https://doi.org/10.1128/JCM.00032-20) described the development of the Lyme Disease Biobank. Clinically categorized case patients with early Lyme disease and healthy controls were identified (without laboratory diagnostic testing) from three sites where Lyme disease is endemic. Subjects provided whole blood and urine, which were processed and stored at a central biorepository. Whole blood, serum, and urine aliquots were prepared and are available to investigators developing laboratory diagnostics for Lyme disease. After obtaining samples, extensive laboratory testing was performed, including serologic and nucleic acid amplification testing for B. burgdorferi and other tick-borne pathogens. Direct detection methods yielded few positive results. Relative to the findings for another commonly used biorepository cohort, the results of this testing demonstrated a low seropositive rate, as determined by standard two-tiered testing. Additionally, relatively few subjects demonstrated seroconversion with testing of convalescent-phase samples. This clinical and serologically defined cohort of samples from Lyme disease and control cases from areas of Lyme disease endemicity offers an additional valuable resource for novel test development that includes alternate specimen types.

Point-of-Care Serodiagnostic Test for Early-Stage Lyme Disease Using a Multiplexed Paper-Based Immunoassay and Machine Learning

Caused by the tick-borne spirochete Borrelia burgdorferi, Lyme disease (LD) is the most common vector-borne infectious disease in North America and Europe. Though timely diagnosis and treatment are effective in preventing disease progression, current tests are insensitive in early stage LD, with a sensitivity of <50%. Additionally, the serological testing currently recommended by the U.S. Center for Disease Control has high costs (>$400/test) and extended sample-to-answer timelines (>24 h). To address these challenges, we created a cost-effective and rapid point-of-care (POC) test for early-stage LD that assays for antibodies specific to seven Borrelia antigens and a synthetic peptide in a paper-based multiplexed vertical flow assay (xVFA). We trained a deep-learning-based diagnostic algorithm to select an optimal subset of antigen/peptide targets and then blindly tested our xVFA using human samples (N₍₊₎ = 42, N_(-) = 54), achieving an area-under-the-curve (AUC), sensitivity, and specificity of 0.950, 90.5%, and 87.0%, respectively, outperforming previous LD POC tests. With batch-specific standardization and threshold tuning, the specificity of our blind-testing performance improved to 96.3%, with an AUC and sensitivity of 0.963 and 85.7%, respectively.