A rapid triage test for active pulmonary tuberculosis in adult patients with persistent cough

Revolutionizing the capture efficiency of ultrasensitive digital ELISA via an antibody oriented-immobilization strategy

Bead-based digital ELISA, the most sensitive protein quantification method, has drawn much attention to exploring ultra-low abundance biomarkers in the life sciences and clinical applications. However, its major challenge refers to the low antigen capture efficiency in the immunoreaction process due to the low probability of collision between the deficient concentration of the analytes and the captured antibody-immobilized on the beads. Here, we achieved significantly improved reaction efficiency in the digital signal formation by fixing the orientation of antibodies and revealed the kinetic mechanism for the first time. A facile and fast antibody conjugation strategy that formed boronate ester complexes was designed to retain the uniform orientation of antibodies with controllable antibody density. Remarkably, the oriented immobilized antibody exhibited stronger antigen-binding capacity and faster antigen-binding speed compared to randomly immobilized antibodies, with capture efficiency increasing approximately 14-fold at 15 μg of antibody per 1 mg microbeads (0.035 antibody nm-2) under 0.5 h incubation. Combined with theoretical analysis, we verified that the improved capture efficiency of the oriented antibodies mainly originated from the considerable rise in the binding rate constant (kon) rather than the increase in antigen-binding sites, which further prominently decreased the limit of detection (LoD) in a shorter incubation time compared with the randomly immobilized antibody. In conclusion, the antibody oriented conjugation method effectively overcomes the low capture efficiency challenge of bead-based digital ELISA. It paves a promising way for further improving the digital immunoassay performance and promotes the early diagnosis of diseases by recognizing more ultra-low abundance significant biomarkers.

Applications of Digital Enzyme-Linked Immunosorbent Assays in Ophthalmology

Digital enzyme-linked immunosorbent assays (dELISAs) very sensitively detect biomarkers that cannot be measured using traditional methods. The molecules are confined within a small volume, their counts accurately computed, and the results rapidly delivered. Digital ELISAs find many applications. In recent years, such ELISAs have become increasingly used to aid ophthalmological diagnoses and treatments, and have revolutionized the field. This article reviews the applications of dELISAs in clinical practice, especially in the sphere of ophthalmology.

Flow cytometry-based method using diversity of cytokine production differentiates between Mycobacterium tuberculosis infection and disease

Authors present a pilot study of the development of innovative flow cytometry-based assay with a potential for use in tuberculosis diagnostics. Currently available tests do not provide robust discrimination between latent tuberculosis infection (TBI) and tuberculosis disease (TB). The desired application is to distinguish between the two conditions by evaluating the production of a combination of three cytokines: IL-2 (interleukin-2), IFNɣ (interferon gamma) and TNFɑ (tumor necrosis factor alpha) in CD4+ and CD8+ T cells. The study was conducted on 68 participants, divided into two arms according to age (paediatric and adults). Each arm was further split into three categories (non-infection (NI), TBI, TB) based on the immune reaction to Mycobacterium tuberculosis (M.tb) after a close contact with pulmonary TB. Each blood sample was stimulated with specific M.tb antigens present in QuantiFERON tubes (TB1 and TB2). We inferred TBI or TB based on the predominant cytokine response of the CD4+ and/or CD8+ T cells. Significant differences were detected between the NI, TBI and the TB groups in TB1 in the CD4+TNFɑ+parameter in children. Along with IL-2, TNFɑ seems to be the most promising diagnostic marker in both CD4+and CD8+ T cells. However, more detailed analyses on larger cohorts are needed to confirm the observed tendencies.

C1q and HBHA-specific IL-13 levels as surrogate plasma biomarkers for monitoring tuberculosis treatment efficacy: a cross-sectional cohort study in Paraguay

Introduction

New diagnostic tools are needed to rapidly assess the efficacy of pulmonary tuberculosis (PTB) treatment. The aim of this study was to evaluate several immune biomarkers in an observational and cross-sectional cohort study conducted in Paraguay.

Methods

Thirty-two patients with clinically and microbiologically confirmed PTB were evaluated before starting treatment (T0), after 2 months of treatment (T1) and at the end of treatment (T2). At each timepoint plasma levels of IFN-y, 17 pro- and anti-inflammatory cytokines/chemokines and complement factors C1q, C3 and C4 were assessed in unstimulated and Mtb-specific stimulated whole blood samples using QuantiFERON-TB gold plus and recombinant Mycobacterium smegmatis heparin binding hemagglutinin (rmsHBHA) as stimulation antigen. Complete blood counts and liver enzyme assays were also evaluated and correlated with biomarker levels in plasma.

Results

In unstimulated plasma, C1q (P<0.001), C4 (P<0.001), hemoglobin (P<0.001), lymphocyte proportion (P<0.001) and absolute white blood cell count (P=0.01) were significantly higher in PTB patients at baseline than in cured patients. C1q and C4 levels were found to be related to Mycobacterium tuberculosis load in sputum. Finally, a combinatorial analysis identified a plasma host signature comprising the detection of C1q and IL-13 levels in response to rmsHBHA as a tool differentiating PTB patients from cured TB profiles, with an AUC of 0.92 (sensitivity 94% and specificity 79%).

Conclusion

This observational study provides new insights on host immune responses throughout anti-TB treatment and emphasizes the role of host C1q and HBHA-specific IL-13 response as surrogate plasma biomarkers for monitoring TB treatment efficacy.

From simple to complex: Protein-based biomarker discovery in tuberculosis

Tuberculosis (TB) is a deadly infectious disease that affects millions of people globally. TB proteomics signature discovery has been a rapidly growing area of research that aims to identify protein biomarkers for the early detection, diagnosis, and treatment monitoring of TB. In this review, we have highlighted recent advances in this field and how it is moving from the study of single proteins to high-throughput profiling and from only using proteomics to include additional types of data in multi-omics studies. We have further covered the different sample types and experimental technologies used in TB proteomics signature discovery, focusing on studies of HIV-negative adults. The published signatures were defined as either coming from hypothesis-based protein targeting or from unbiased discovery approaches. The methodological approaches influenced the type of proteins identified and were associated with the circulating protein abundance. However, both approaches largely identified proteins involved in similar biological pathways, including acute-phase responses and T-helper type 1 and type 17 responses. By analysing the frequency of proteins in the different signatures, we could also highlight potential robust biomarker candidates. Finally, we discuss the potential value of integration of multi-omics data and the importance of control cohorts and signature validation.

Collected Thoughts on Mycobacterial Lipoarabinomannan, a Cell Envelope Lipoglycan

The presence of lipoarabinomannan (LAM) in the Mycobacterium tuberculosis (Mtb) cell envelope was first reported close to 100 years ago. Since then, numerous studies have been dedicated to the isolation, purification, structural definition, and elucidation of the biological properties of Mtb LAM. In this review, we present a brief historical perspective on the discovery of Mtb LAM and the herculean efforts devoted to structurally characterizing the molecule because of its unique structural and biological features. The significance of LAM remains high to this date, mainly due to its distinct immunological properties in conjunction with its role as a biomarker for diagnostic tests due to its identification in urine, and thus can serve as a point-of-care diagnostic test for tuberculosis (TB). In recent decades, LAM has been thoroughly studied and massive amounts of information on this intriguing molecule are now available. In this review, we give the readers a historical perspective and an update on the current knowledge of LAM with information on the inherent carbohydrate composition, which is unique due to the often puzzling sugar residues that are specifically found on LAM. We then guide the readers through the complex and myriad immunological outcomes, which are strictly dependent on LAM's chemical structure. Furthermore, we present issues that remain unresolved and represent the immediate future of LAM research. Addressing the chemistry, functions, and roles of LAM will lead to innovative ways to manipulate the processes that involve this controversial and fascinating biomolecule.

Single-molecule immunoassay technology: Recent advances

Detecting diseases at the molecular level aids in early diagnosis and treatment. However, traditional immunological detection techniques, such as enzyme-linked immunosorbent assay (ELISA) and chemiluminescence, have detection sensitivities between 10^-16 and 10^-12 mol/L, which are inadequate for early diagnosis. Single-molecule immunoassays can reach detection sensitivities of 10^-18 mol/L and can detect biomarkers that are difficult to measure using conventional detection techniques. It can confine molecules to be detected in a small spatial area and provide absolute counting of the detected signal, offering the advantage of high efficiency and accuracy. Herein, we demonstrate the principles and equipment of two single-molecule immunoassay techniques and discuss their applications. It is shown that the detection sensitivity can be improved by 2-3 orders of magnitude compared to common chemiluminescence or ELISA assays. The microarray-based single-molecule immunoassay technique can test 66 samples in 1 h, which is more efficient than conventional immunological detection techniques. In contrast, microdroplet-based single-molecule immunoassay techniques can generate 107 droplets in 10 min, which is more than 100 times faster than a single droplet generator. By comparing the two single-molecule immunoassay techniques, we highlight our personal perspectives on the current limitations of point-of-care applications and future development trends.

Engineering Innovative Interfaces for Point-of-Care Diagnostics

The ongoing Coronavirus disease 2019 (COVID-19) pandemic illustrates the need for sensitive and reliable tools to diagnose and monitor diseases. Traditional diagnostic approaches rely on centralized laboratory tests that result in long wait times to results and reduce the number of tests that can be given. Point-of-care tests (POCTs) are a group of technologies that miniaturize clinical assays into portable form factors that can be run both in clinical areas --in place of traditional tests-- and outside of traditional clinical settings --to enable new testing paradigms. Hallmark examples of POCTs are the pregnancy test lateral flow assay and the blood glucose meter. Other uses for POCTs include diagnostic assays for diseases like COVID-19, HIV, and malaria but despite some successes, there are still unsolved challenges for fully translating these lower cost and more versatile solutions. To overcome these challenges, researchers have exploited innovations in colloid and interface science to develop various designs of POCTs for clinical applications. Herein, we provide a review of recent advancements in lateral flow assays, other paper based POCTs, protein microarray assays, microbead flow assays, and nucleic acid amplification assays. Features that are desirable to integrate into future POCTs, including simplified sample collection, end-to-end connectivity, and machine learning, are also discussed in this review.

Machine learning approaches in diagnosing tuberculosis through biomarkers - A systematic review

Biomarker-based tests may facilitate Tuberculosis (TB) diagnosis, accelerate treatment initiation, and thus improve outcomes. This review synthesizes the literature on biomarker-based detection for TB diagnosis using machine learning. The systematic review approach follows the PRISMA guideline. Articles were sought using relevant keywords from Web of Science, PubMed, and Scopus, resulting in 19 eligible studies after a meticulous screening. All the studies were found to have focused on the supervised learning approach, with Support Vector Machine (SVM) and Random Forest emerging as the top two algorithms, with the highest accuracy, sensitivity and specificity reported to be 97.0%, 99.2%, and 98.0%, respectively. Further, protein-based biomarkers were widely explored, followed by gene-based such as RNA sequence and, Spoligotypes. Publicly available datasets were observed to be popularly used by the studies reviewed whilst studies targeting specific cohorts such as HIV patients or children gathering their own data from healthcare facilities, leading to smaller datasets. Of these, most studies used the leave one out cross validation technique to mitigate overfitting. The review shows that machine learning is increasingly assessed in research to improve TB diagnosis through biomarkers, as promising results were shown in terms of model's detection performance. This provides insights on the possible application of machine learning approaches to diagnose TB using biomarkers as opposed to the traditional methods that can be time consuming. Low-middle income settings, where access to basic biomarkers could be provided as compared to sputum-based tests that are not always available, could be a major application of such models.

Biofabrication of Multiplexed Electrochemical Immunosensors for Simultaneous Detection of Clinical Biomarkers in Complex Fluids

Simultaneous detection of multiple disease biomarkers in unprocessed whole blood is considered the gold standard for accurate clinical diagnosis. Here, this study reports the development of a 4-plex electrochemical (EC) immunosensor with on-chip negative control capable of detecting a range of biomarkers in small volumes (15 µL) of complex biological fluids, including serum, plasma, and whole blood. A framework for fabricating and optimizing multiplexed sandwich immunoassays is presented that is enabled by use of EC sensor chips coated with an ultra-selective, antifouling, and nanocomposite coating. Cyclic voltammetry evaluation of sensor performance is carried out by monitoring the local precipitation of an electroactive product generated by horseradish peroxidase linked to a secondary antibody. EC immunosensors demonstrate high sensitivity and specificity without background signal with a limit of detection in single-digit picogram per milliliter in multiple complex biological fluids. These multiplexed immunosensors enable the simultaneous detection of four different biomarkers in plasma and whole blood with excellent sensitivity and selectivity. This rapid and cost-effective biosensor platform can be further adapted for use with different high affinity probes for any biomarker, and thereby create for a new class of highly sensitive and specific multiplexed diagnostics.

A protein signature associated with active tuberculosis identified by plasma profiling and network-based analysis

Annually, approximately 10 million people are diagnosed with active tuberculosis (TB), and 1.4 million die of the disease. If left untreated, each person with active TB will infect 10-15 new individuals. The lack of non-sputum-based diagnostic tests leads to delayed diagnoses of active pulmonary TB cases, contributing to continued disease transmission. In this exploratory study, we aimed to identify biomarkers associated with active TB. We assessed the plasma levels of 92 proteins associated with inflammation in individuals with active TB (n = 20), latent TB (n = 14), or healthy controls (n = 10). Using co-expression network analysis, we identified one module of proteins with strong association with active TB. We removed proteins from the module that had low abundance or were associated with non-TB diseases in published transcriptomic datasets, resulting in a 12-protein plasma signature that was highly enriched in individuals with pulmonary and extrapulmonary TB and was further associated with disease severity.

The expression of prolyl isomerase Pin1 is expanded in the skin of patients with atopic dermatitis and facilitates IL ‐33 expression in HaCaT cells

Atopic dermatitis (AD) is attributable to both a genetic predisposition and environmental factors. Among numerous cytokines involved in the pathogenesis of AD, interleukin-33 (IL-33), reportedly escaping exocytotically in response to a scratch, is abundantly expressed in the skin tissues of patients with AD and is postulated to induce inflammatory and autoimmune responses. In this study, we first demonstrated that peptidylprolyl cis/trans isomerase, NIMA-interacting 1 (Pin1), a unique enzyme which isomerizes the proline residues of target proteins, is abundantly expressed in keratinocytes, and that the areas where it is present in the skin tissues of AD patients became expanded due to hyperkeratosis. Thus, we investigated the effects of Pin1 on the regulation of IL-33 expression using the human keratinocyte cell line HaCaT. Interestingly, silencing of the Pin1 gene or treatment with Pin1 inhibitors dramatically reduced IL-33 expressions in HaCaT cells, although Pin1 overexpression did not elevate it. Subsequently, we showed that Pin1 binds to STAT1 and the nuclear factor-kappaB (NF-κB) subunit p65. Silencing the Pin1 gene with small interfering RNAs significantly reduced the phosphorylation of p65, while no marked effects of Pin1 on the STAT1 pathway were detected. Thus, it is likely that Pin1 contributes to increased expression of IL-33 via the NF-κB subunit p65 in HaCaT cells, at least modestly. Nevertheless, further study is necessary to demonstrate the pathogenic roles of Pin1 and IL-33 in AD development.

Vascular endothelial growth factor levels in tuberculosis: A systematic review and meta-analysis

Background

Changes in endothelial function are implicated in the spread of tuberculosis (TB). Studies suggest a role for the vascular endothelial growth factor (VEGF) in TB-related endothelial function changes. However, the findings of studies investigating the VGEF profile in TB are not consistent, and no formal systematic review and meta-analysis exists summarizing these studies.

Methods

We did a meta-analysis of studies assessing VEGF levels in patients with TB. A systematic search on June 25, 2021, was conducted for eligible studies that made VEGF measurements in an unstimulated sample, e.g., a blood fraction (plasma or serum), cerebrospinal fluid (CSF), pleural effusion (PE), or bronchoalveolar lavage fluid, and ascites or pericardial fluid for patients with TB and controls without TB. Also, studies that made simultaneous measurements of VEGF in blood and PE or CSF in the same patients with TB were included. Longitudinal studies that provided these data at baseline or compared pre-post anti-tuberculosis treatment (ATT) levels of VEGF were included. The primary outcome was the standardized mean difference (SMD) of VEGF levels between the comparison groups.

Results

52 studies were included in the meta-analysis. There were 1787 patients with TB and 3352 control subjects of eight categories: 107 patients with transudative pleural effusion, 228 patients with congestive heart failure (CHF)/chronic renal failure (CRF), 261 patients with empyema and parapneumonic effusion (PPE), 241 patients with cirrhosis, 694 healthy controls (with latent TB infection or uninfected individuals), 20 patients with inactive tuberculous meningitis (TBM), 123 patients with non-TBM, and 1678 patients with malignancy. The main findings are as follows: (1) serum levels of VEGF are higher in patients with active TB compared with healthy controls without other respiratory diseases, including those with latent TB infection or uninfected individuals; (2) both serum and pleural levels of VEGF are increased in patients with TPE compared with patients with transudative, CHF/CRF, or cirrhotic pleural effusion; (3) ascitic/pericardial fluid, serum, and pleural levels of VEGF are decreased in patients with TB compared with patients with malignancy; (4) pleural levels of VEGF are lower in patients with TPE compared with those with empyema and PPE, whereas serum levels of VEGF are not different between these patients; (5) both CSF and serum levels of VEGF are increased in patients with active TBM compared with controls, including patients with inactive TBM or non-TBM subjects; (6) post-ATT levels of VEGF are increased compared with pre-ATT levels of VEGF; and (7) the mean age and male percentage of the TB group explained large and total amount of heterogeneity for the meta-analysis of blood and pleural VEGF levels compared with healthy controls and patients with PPE, respectively, whereas these moderators did not show any significant interaction with the effect size for other analyses.

Discussion

The important limitation of the study is that we could not address the high heterogeneity among studies. There might be unmeasured factors behind this heterogeneity that need to be explored in future research. Meta-analysis findings align with the hypothesis that TB may be associated with abnormal vascular function, and both local and systemic levels of VEGF can be used to trace this abnormality.

Validation of host cerebrospinal fluid protein biomarkers for early diagnosis of tuberculous meningitis in children: a replication and new biosignature discovery study

The diagnosis of tuberculous meningitis (TBM) in children is often delayed due to diagnostic difficulties. New tools are urgently needed to improve the diagnosis of the disease in this vulnerable group. The present study aimed to validate the accuracy of recently identified host cerebrospinal (CSF) biomarkers as candidates for the diagnosis of TBM in children. We collected CSF samples from 87 children aged 3 months to 13 years, that were consecutively admitted at a tertiary hospital in Cape Town, South Africa, on suspicion of having TBM. We evaluated the concentrations of 67 selected host protein biomarkers using a multiplex platform. Previously identified 3-marker (VEGF-A + IFN-γ + MPO) and 4-marker (IFN-γ + MPO + ICAM-1 + IL-8) signatures diagnosed TBM with AUCs of 0.89 (95% CI, 0.81-0.97) and 0.87 (95% CI, 0.79-0.95) respectively; sensitivities of 80.6% (95% CI, 62.5-92.5%) and 81.6% (95% CI, 65.7-92.3%), and specificities of 86.8% (71.9-95.6%) and 83.7% (70.4-92.7%) respectively. Furthermore, a new combination between the analytes (CC4b + CC4 + procalcitonin + CCL1) showed promise, with an AUC of 0.98 (95% CI, 0.94-1.00). We have shown that the accuracies of previously identified candidate CSF biomarkers for childhood TBM was reproducible. Our findings augur well for the future development of a simple bedside test for the rapid diagnosis of TBM in children.

High Immunogenicity of a T-Cell Epitope-Rich Recombinant Protein Rv1566c-444 From Mycobacterium tuberculosis in Immunized BALB/c Mice, Despite Its Low Diagnostic Sensitivity

The discovery of immunodominant antigens is of great significance for the development of new especially sensitive diagnostic reagents and effective vaccines in controlling tuberculosis (TB). In the present study, we targeted the T-Cell epitope-rich fragment (nucleotide position 109-552) of Rv1566c from Mycobacterium tuberculosis (MTB) and got a recombinant protein Rv1566c-444 and the full-length protein Rv1566c with Escherichia coli expression system, then compared their performances for TB diagnosis and immunogenicity in a mouse model. The results showed that Rv1566c-444 had similar sensitivity with Rv1566c (44.44% Vs 30.56%) but lower sensitivity than ESAT-6&CFP-10&Rv3615c (44.4% Vs. 94.4%) contained in a commercial kit for distinguishing TB patients from healthy donors. In immunized BALB/c mice, Rv1566c-444 elicited stronger T-helper 1 (Th1) cellular immune response over Rv1566c with higher levels of Th1 cytokine IFN-γ and IFN-γ/IL-4 expression ratio by ELISA; more importantly, with a higher proliferation of CD4⁺ T cells and a higher proportion of CD4⁺ TNF-α⁺ T cells with flow cytometry. Rv1566c-444 also induced a higher level of IL-6 by ELISA and a higher proportion of Rv1566c-444-specific CD8⁺ T cells and a lower proportion of CD8⁺ IL-4⁺ T cells by flow cytometry compared with the Rv1566c group. Moreover, the Rv1566c-444 group showed a high IgG secretion level and the same type of CD4+ Th cell immune response (both IgG1/IgG2a >1) as its parental protein group. Our results showed the potential of the recombinant protein Rv1566c-444 enriched with T-Cell epitopes from Rv1566c as a host T cell response measuring biomarker for TB diagnosis and support further evaluation of Rv1566c-444 as vaccine antigen against MTB challenge in animal models in the form of protein mixture or fusion protein.

Point-of-care diagnostic tests for tuberculosis disease

Rapid diagnosis is one key pillar to end tuberculosis (TB). Point-of-care tests (POCTs) facilitate early detection, immediate treatment, and reduced transmission of TB disease. This Review evaluates current diagnostic assays endorsed by the World Health Organization and identifies the gaps between existing conventional tests and the ideal POCT. We discuss the commercial development of new rapid tests and research studies on nonsputum-based diagnostic biomarkers from both pathogen and host. Last, we highlight advances in integrated microfluidics technology that may aid the development of new POCTs.

Reimagining the status quo: How close are we to rapid sputum-free tuberculosis diagnostics for all?

Rapid, accurate, sputum-free tests for tuberculosis (TB) triage and confirmation are urgently needed to close the widening diagnostic gap. We summarise key technologies and review programmatic, systems, and resource issues that could affect the impact of diagnostics. Mid-to-early-stage technologies like artificial intelligence-based automated digital chest X-radiography and capillary blood point-of-care assays are particularly promising. Pitfalls in the diagnostic pipeline, included a lack of community-based tools. We outline how these technologies may complement one another within the context of the TB care cascade, help overturn current paradigms (eg, reducing syndromic triage reliance, permitting subclinical TB to be diagnosed), and expand options for extra-pulmonary TB. We review challenges such as the difficulty of detecting paucibacillary TB and the limitations of current reference standards, and discuss how researchers and developers can better design and evaluate assays to optimise programmatic uptake. Finally, we outline how leveraging the urgency and innovation applied to COVID-19 is critical to improving TB patients' diagnostic quality-of-care.

Immuno-Diagnosis of Active Tuberculosis by a Combination of Cytokines/Chemokines Induced by Two Stage-Specific Mycobacterial Antigens: A Pilot Study in a Low TB Incidence Country

Active tuberculosis (aTB) remains a major killer from infectious disease, partially due to delayed diagnosis and hence treatment. Classical microbiological methods are slow and lack sensitivity, molecular techniques are costly and often unavailable. Moreover, available immuno-diagnostic tests lack sensitivity and do not differentiate between aTB and latent TB infection (LTBI). Here, we evaluated the performance of the combined measurement of different chemokines/cytokines induced by two different stage-specific mycobacterial antigens, Early-secreted-antigenic target-6 (ESAT-6) and Heparin-binding-haemagglutinin (HBHA), after a short in vitro incubation of either peripheral blood mononuclear cells (PBMC) or whole blood (WB). Blood samples were collected from a training cohort comprising 22 aTB patients, 22 LTBI subjects and 17 non-infected controls. The concentrations of 13 cytokines were measured in the supernatants. Random forest analysis identified the best markers to differentiate M. tuberculosis-infected from non-infected subjects, and the most appropriate markers to differentiate aTB from LTBI. Logistic regression defined predictive abilities of selected combinations of cytokines, first on the training and then on a validation cohort (17 aTB, 27 LTBI, 25 controls). Combining HBHA- and ESAT-6-induced IFN-γ concentrations produced by PBMC was optimal to differentiate infected from non-infected individuals in the training cohort (100% correct classification), but 2/16 (13%) patients with aTB were misclassified in the validation cohort. ESAT-6-induced-IP-10 combined with HBHA-induced-IFN-γ concentrations was selected to differentiate aTB from LTBI, and correctly classified 82%/77% of infected subjects as aTB or LTBI in the training/validation cohorts, respectively. Results obtained on WB also selected ESAT-6- and HBHA-induced IFN-γ concentrations to provided discrimination between infected and non-infected subjects (89%/90% correct classification in the training/validation cohorts). Further identification of aTB patients among infected subjects was best achieved by combining ESAT-6-induced IP-10 with HBHA-induced IL-2 and GM-CSF. Among infected subjects, 90%/93% of the aTB patients were correctly identified in the training/validation cohorts. We therefore propose a two steps strategy performed on 1 mL WB for a rapid identification of patients with aTB. After elimination of most non-infected subjects by combining ESAT-6 and HBHA-induced IFN-γ, the combination of IP-10, IL-2 and GM-CSF released by either ESAT-6 or HBHA correctly identifies most patients with aTB.

High-Throughput, High-Multiplex Digital Protein Detection with Attomolar Sensitivity

A major challenge in many clinical diagnostic applications is the measurement of low-abundance proteins and other biomolecules in biological fluids. Digital technologies such as the digital enzyme-linked immunosorbent assay (ELISA) have enabled 1000-fold increases in sensitivity over conventional protein detection methods. However, current digital ELISA technologies still possess insufficient sensitivities for many rare protein biomarkers and require specialized instrumentation or time-consuming workflows that have limited their widespread implementation. To address these challenges, we have developed a more sensitive and streamlined digital ELISA platform, Molecular On-bead Signal Amplification for Individual Counting (MOSAIC), which attains low attomolar limits of detection, with an order of magnitude enhancement in sensitivity over these other methods. MOSAIC uses a rapid, automatable flow cytometric readout that vastly increases throughput and is easily integrated into existing laboratory infrastructure. As MOSAIC provides high sampling efficiencies for rare target molecules, assay bead number can readily be tuned to enhance signal-to-background with high measurement precision. Furthermore, the solution-based signal readout of MOSAIC expands the number of analytes that can simultaneously be measured for higher-order multiplexing with femtomolar sensitivities or below, compared with microwell- or droplet-based digital methods. As a proof of principle, we apply MOSAIC toward improving the detectability of low-abundance cytokines in saliva and ultrasensitive multiplexed measurements of eight protein analytes in plasma and saliva. The attomolar sensitivity, high throughput, and broad multiplexing abilities of MOSAIC provide highly accessible and versatile ultrasensitive capabilities that can potentially accelerate protein biomarker discovery and diagnostic testing for diverse disease applications.

Quantitative Rapid Test for Detection and Monitoring of Active Pulmonary Tuberculosis in Nonhuman Primates

Nonhuman primates (NHPs) are relevant models to study the pathogenesis of tuberculosis (TB) and evaluate the potential of TB therapies, but rapid tools allowing diagnosis of active pulmonary TB in NHPs are lacking. This study investigates whether low complexity lateral flow assays utilizing upconverting reporter particles (UCP-LFAs) developed for rapid detection of human serum proteins can be applied to detect and monitor active pulmonary TB in NHPs. UCP-LFAs were used to assess serum proteins levels and changes in relation to the MTB challenge dosage, lung pathology, treatment, and disease outcome in experimentally MTB-infected macaques. Serum levels of SAA1, IP-10, and IL-6 showed a significant increase after MTB infection in rhesus macaques and correlated with disease severity as determined by pathology scoring. Moreover, these biomarkers could sensitively detect the reduction of bacterial levels in the lungs of macaques due to BCG vaccination or drug treatment. Quantitative measurements by rapid UCP-LFAs specific for SAA1, IP-10, and IL-6 in serum can be utilized to detect active progressive pulmonary TB in macaques. The UCP-LFAs thus offer a low-cost, convenient, and minimally invasive diagnostic tool that can be applied in studies on TB vaccine and drug development involving macaques.

Serum Biomarker Profile Including CCL1, CXCL10, VEGF, and Adenosine Deaminase Activity Distinguishes Active From Remotely Acquired Latent Tuberculosis

Introduction

There is an urgent medical need to differentiate active tuberculosis (ATB) from latent tuberculosis infection (LTBI) and prevent undertreatment and overtreatment. The aim of this study was to identify biomarker profiles that may support the differentiation between ATB and LTBI and to validate these signatures.

Materials and Methods

The discovery cohort included adult individuals classified in four groups: ATB (n = 20), LTBI without prophylaxis (untreated LTBI; n = 20), LTBI after completion of prophylaxis (treated LTBI; n = 20), and healthy controls (HC; n = 20). Their sera were analyzed for 40 cytokines/chemokines and activity of adenosine deaminase (ADA) isozymes. A prediction model was designed to differentiate ATB from untreated LTBI using sparse partial least squares (sPLS) and logistic regression analyses. Serum samples of two independent cohorts (national and international) were used for validation.

Results

sPLS regression analyses identified C-C motif chemokine ligand 1 (CCL1), C-reactive protein (CRP), C-X-C motif chemokine ligand 10 (CXCL10), and vascular endothelial growth factor (VEGF) as the most discriminating biomarkers. These markers and ADA(2) activity were significantly increased in ATB compared to untreated LTBI (p ≤ 0.007). Combining CCL1, CXCL10, VEGF, and ADA2 activity yielded a sensitivity and specificity of 95% and 90%, respectively, in differentiating ATB from untreated LTBI. These findings were confirmed in the validation cohort including remotely acquired untreated LTBI participants.

Conclusion

The biomarker signature of CCL1, CXCL10, VEGF, and ADA2 activity provides a promising tool for differentiating patients with ATB from non-treated LTBI individuals.

Counting of enzymatically amplified affinity reactions in hydrogel particle-templated drops

Counting of numerous compartmentalized enzymatic reactions underlies quantitative and high sensitivity immunodiagnostic assays. However, digital enzyme-linked immunosorbent assays (ELISA) require specialized instruments which have slowed adoption in research and clinical labs. We present a lab-on-a-particle solution to digital counting of thousands of single enzymatic reactions. Hydrogel particles are used to bind enzymes and template the formation of droplets that compartmentalize reactions with simple pipetting steps. These hydrogel particles can be made at a high throughput, stored, and used during the assay to create ∼500 000 compartments within 2 minutes. These particles can also be dried and rehydrated with sample, amplifying the sensitivity of the assay by driving affinity interactions on the hydrogel surface. We demonstrate digital counting of β-galactosidase enzyme at a femtomolar detection limit with a dynamic range of 3 orders of magnitude using standard benchtop equipment and experiment techniques. This approach can faciliate the development of digital ELISAs with reduced need for specialized microfluidic devices, instruments, or imaging systems.

Digital immunoassay for biomarker concentration quantification using solid-state nanopores

Single-molecule counting is the most accurate and precise method for determining the concentration of a biomarker in solution and is leading to the emergence of digital diagnostic platforms enabling precision medicine. In principle, solid-state nanopores—fully electronic sensors with single-molecule sensitivity—are well suited to the task. Here we present a digital immunoassay scheme capable of reliably quantifying the concentration of a target protein in complex biofluids that overcomes specificity, sensitivity, and consistency challenges associated with the use of solid-state nanopores for protein sensing. This is achieved by employing easily-identifiable DNA nanostructures as proxies for the presence (“1”) or absence (“0”) of the target protein captured via a magnetic bead-based sandwich immunoassay. As a proof-of-concept, we demonstrate quantification of the concentration of thyroid-stimulating hormone from human serum samples down to the high femtomolar range. Further optimization to the method will push sensitivity and dynamic range, allowing for development of precision diagnostic tools compatible with point-of-care format.

The concentration of a biomarker in solution can be determined by counting single molecules. Here the authors report a digital immunoassay scheme with solid-state nanopore readout to quantify a target protein and use this to measure thyroid-stimulating hormone from human serum.

New management approaches to tuberculosis in people living with HIV

PURPOSE OF REVIEW

People living with HIV (PLWH) are commonly coinfected with Mycobacterium tuberculosis, particularly in high-transmission resource-limited regions. Despite expanded access to antiretroviral therapy and tuberculosis (TB) treatment, TB remains the leading cause of death among PLWH. This review discusses recent advances in the management of TB in PLWH and examines emerging therapeutic approaches to improve outcomes of HIV-associated TB.

RECENT FINDINGS

Three recent key developments have transformed the management of HIV-associated TB. First, the scaling-up of rapid point-of-care urine-based tests for screening and diagnosis of TB in PLWH has facilitated early case detection and treatment. Second, increasing the availability of potent new and repurposed drugs to treat drug-resistant TB has generated optimism about the treatment and outcome of multidrug-resistant and extensively drug-resistant TB. Third, expanded access to the integrase inhibitor dolutegravir to treat HIV in resource-limited regions has simplified the management of TB/HIV coinfected patients and minimized serious adverse events.

SUMMARY

While it is unequivocal that substantial progress has been made in early detection and treatment of HIV-associated TB, significant therapeutic challenges persist. To optimize the management and outcomes of TB in HIV, therapeutic approaches that target the pathogen as well as enhance the host response should be explored.

CXCL1: A new diagnostic biomarker for human tuberculosis discovered using Diversity Outbred mice

More humans have died of tuberculosis (TB) than any other infectious disease and millions still die each year. Experts advocate for blood-based, serum protein biomarkers to help diagnose TB, which afflicts millions of people in high-burden countries. However, the protein biomarker pipeline is small. Here, we used the Diversity Outbred (DO) mouse population to address this gap, identifying five protein biomarker candidates. One protein biomarker, serum CXCL1, met the World Health Organization’s Targeted Product Profile for a triage test to diagnose active TB from latent M.tb infection (LTBI), non-TB lung disease, and normal sera in HIV-negative, adults from South Africa and Vietnam. To find the biomarker candidates, we quantified seven immune cytokines and four inflammatory proteins corresponding to highly expressed genes unique to progressor DO mice. Next, we applied statistical and machine learning methods to the data, i.e., 11 proteins in lungs from 453 infected and 29 non-infected mice. After searching all combinations of five algorithms and 239 protein subsets, validating, and testing the findings on independent data, two combinations accurately diagnosed progressor DO mice: Logistic Regression using MMP8; and Gradient Tree Boosting using a panel of 4: CXCL1, CXCL2, TNF, IL-10. Of those five protein biomarker candidates, two (MMP8 and CXCL1) were crucial for classifying DO mice; were above the limit of detection in most human serum samples; and had not been widely assessed for diagnostic performance in humans before. In patient sera, CXCL1 exceeded the triage diagnostic test criteria (>90% sensitivity; >70% specificity), while MMP8 did not. Using Area Under the Curve analyses, CXCL1 averaged 94.5% sensitivity and 88.8% specificity for active pulmonary TB (ATB) vs LTBI; 90.9% sensitivity and 71.4% specificity for ATB vs non-TB; and 100.0% sensitivity and 98.4% specificity for ATB vs normal sera. Our findings overall show that the DO mouse population can discover diagnostic-quality, serum protein biomarkers of human TB.

More humans die of tuberculosis (TB) than any other infectious disease, yet diagnostic tools remain limited. Here, we used the Diversity Outbred mouse population to discover candidate protein biomarkers of human TB. By applying statistical methods and machine learning to multidimensional data, we identified CXCL1 and MMP8 as the two most promising protein biomarker candidates. When evaluated in samples from human patients, CXCL1 achieved the World Health Organization’s targeted profile for a triage diagnostic test, discriminating active TB from important clinical differential diagnoses: latent Mtb infection and non-TB lung disease in HIV-negative adults. Overall, our studies show how a translationally relevant animal population model can accelerate TB biomarker discovery, validation, and testing for humans.

Evaluation of Triage Tests When Existing Test Capacity Is Constrained: Application to Rapid Diagnostic Testing in COVID-19

Objectives

A triage test is used to determine which patients will undergo an existing or “reference” test. This article explores the potential value of using triage tests before reference tests when the capacity of the reference test is constrained.

Methods

We developed a simple model with inputs: prevalence, sensitivity, specificity, and reference test capacity. We included a case study of rapid diagnostic tests for SARS-CoV-2 antigens used as triage tests before a reference polymerase chain reaction test. Performance data were obtained from an evaluation performed by an academic center on 425 samples from testing centers in the United Kingdom and Germany.

Results

When reference test capacity is constrained, the use of a triage test leads to a relative expansion of the population tested and cases identified; both are higher with a high-specificity triage test. When reference test capacity is not constrained, the potential advantages of introducing a triage test can be assessed using a standard cost-utility framework, balancing the utility of the reduction in the number of reference tests required against the disutility of missed cases associated with the use of a lower-sensitivity triage test. In the constrained case, the advantage of a triage testing strategy in terms of population covered and cases identified is reduced as the prevalence increases. In the unconstrained case, the reduction in reference tests required is reduced and the number of cases missed increase as the prevalence rises.

Conclusion

When the availability of the reference test is constrained, tests added in a triage position do not need high levels of accuracy to increase the number of cases diagnosed. This has implications in many disease areas, including COVID-19.

Evaluation of Host Serum Protein Biomarkers of Tuberculosis in sub-Saharan Africa

Accurate and affordable point-of-care diagnostics for tuberculosis (TB) are needed. Host serum protein signatures have been derived for use in primary care settings, however validation of these in secondary care settings is lacking. We evaluated serum protein biomarkers discovered in primary care cohorts from Africa reapplied to patients from secondary care. In this nested case-control study, concentrations of 22 proteins were quantified in sera from 292 patients from Malawi and South Africa who presented predominantly to secondary care. Recruitment was based upon intention of local clinicians to test for TB. The case definition for TB was culture positivity for Mycobacterium tuberculosis; and for other diseases (OD) a confirmed alternative diagnosis. Equal numbers of TB and OD patients were selected. Within each group, there were equal numbers with and without HIV and from each site. Patients were split into training and test sets for biosignature discovery. A nine-protein signature to distinguish TB from OD was discovered comprising fibrinogen, alpha-2-macroglobulin, CRP, MMP-9, transthyretin, complement factor H, IFN-gamma, IP-10, and TNF-alpha. This signature had an area under the receiver operating characteristic curve in the training set of 90% (95% CI 86–95%), and, after adjusting the cut-off for increased sensitivity, a sensitivity and specificity in the test set of 92% (95% CI 80–98%) and 71% (95% CI 56–84%), respectively. The best single biomarker was complement factor H [area under the receiver operating characteristic curve 70% (95% CI 64–76%)]. Biosignatures consisting of host serum proteins may function as point-of-care screening tests for TB in African hospitals. Complement factor H is identified as a new biomarker for such signatures.

Triaging abnormal cervical cancer screening tests using p16INK4a detection by ELISA on fresh cervical samples

PROBLEM

Cervical cancer screening strategies in the United States include cotesting (human papillomavirus (HPV) with cytology), primary HPV with genotyping and reflex cytology, and cytology alone. An ongoing challenge is the appropriate triage of patients to colposcopy to those at highest risk. We investigated whether incorporation of p16INK4a immunodetection by enzyme-linked immunosorbent assay (ELISA) on fresh cervical samples obtained at the time of screening could improve appropriate referral to colposcopy.

METHOD OF STUDY

A derivation group comprised of cervical swabs collected from subjects with high-grade dysplasia or cancer (positive control) and from subjects with negative screening history (negative control). Samples collected from colposcopy were used to evaluate the existing screening strategies individually and with incorporation of p16INK4a ELISA. Histology was used as the gold standard.

RESULTS

Among 163 subjects recruited, 138 were included. In the derivation group, mean p16INK4a level was 2.86 ng/mL (n = 31) and 0.58 ng/mL (n = 20) among positive and negative controls respectively (p = 0.002) with an area under the receiver operator characteristic curve of 0.79 (p < 0.001). Among colposcopy subjects, sensitivity/specificity for cotesting, primary HPV, and cytology were 94%/42%, 88%/45%, and 88%/49%, respectively. Incorporation of p16INK4a resulted in similar sensitivity and improved specificity (cotesting+p16 88%/58%, primary HPV+p16 88%/57%, cytology+p16 81%/62%; p = 0.23/p = 0.008) with decrease in colposcopy referrals by 15% to 22% (p = 0.01).

CONCLUSIONS

These results demonstrate the feasibility of quantifying p16INK4a by ELISA in fresh cervical samples, and its potential as an adjunct to existing screening strategies in the identification of high grade-dysplasia while reducing the number of colposcopic referrals.

Host Blood RNA Transcript and Protein Signatures for Sputum-Independent Diagnostics of Tuberculosis in Adults

To achieve the ambitious targets for tuberculosis (TB) prevention, care, and control stated by the End TB Strategy, new health care strategies, diagnostic tools are warranted. Host-derived biosignatures are explored for their TB diagnostic potential in accordance with the WHO target product profiles (TPPs) for point-of-care (POC) testing. We aimed to identify sputum-independent TB diagnostic signatures in newly diagnosed adult pulmonary-TB (PTB) patients recruited in the context of a prospective household contact cohort study conducted in Andhra Pradesh, India. Whole-blood mRNA samples from 158 subjects (PTB, n = 109; age-matched household controls, n = 49) were examined by dual-color Reverse-Transcriptase Multiplex Ligation-dependent Probe-Amplification (dcRT-MLPA) for the expression of 198 pre-defined genes and a Mesoscale discovery assay for the concentration of 18 cytokines/chemokines in TB-antigen stimulated QuantiFERON supernatants. To identify signatures, we applied a two-step approach; in the first step, univariate filtering was used to identify and shortlist potentially predictive biomarkers; this step may be seen as removing redundant biomarkers. In the second step, a logistic regression approach was used such that group membership (PTB vs. household controls) became the binary response in a Lasso regression model. We identified an 11-gene signature that distinguished PTB from household controls with AUCs of ≥0.98 (95% CIs: 0.94–1.00), and a 4-protein signature (IFNγ, GMCSF, IL7 and IL15) that differentiated PTB from household controls with AUCs of ≥0.87 (95% CIs: 0.75–1.00), in our discovery cohort. Subsequently, we evaluated the performance of the 11-gene signature in two external validation data sets viz, an independent cohort at the Glenfield Hospital, University Hospitals of Leicester NHS Trust, Leicester, UK (GSE107994 data set), and the Catalysis treatment response cohort (GSE89403 data set) from South Africa. The 11-gene signature validated and distinguished PTB from healthy and asymptomatic M. tuberculosis infected household controls in the GSE107994 data set, with an AUC of 0.95 (95% CI: 0.91–0.98) and 0.94 (95% CI: 0.89–0.98). More interestingly in the GSE89403 data set, the 11-gene signature distinguished PTB from household controls and patients with other lung diseases with an AUC of 0.93 (95% CI: 0.87–0.99) and 0.73 (95% CI: 0.56–0.89). These criteria meet the WHO TTP benchmarks for a non–sputum-based triage test for TB diagnosis. We suggest that further validation is required before clinical implementation of the 11-gene signature we have identified markers will be possible.

Sequential Protein Capture in Multiplex Single Molecule Arrays: A Strategy for Eliminating Assay Cross-Reactivity

Measurements of multiple biomolecules within the same biological sample are important for many clinical applications to enable accurate disease diagnosis or classification. These disease-related biomarkers often exist at very low levels in biological fluids, necessitating ultrasensitive measurement methods. Single-molecule arrays (Simoa), a bead-based digital enzyme-linked immunosorbent assay, is the current state of the art for ultrasensitive protein detection and can detect sub-femtomolar protein concentrations, but its ability to achieve high-order multiplexing without cross-reactivity remains a challenge. Here, a sequential protein capture approach for multiplex Simoa assays is implemented to eliminate cross-reactivity between binding reagents by sequentially capturing each protein analyte and then incubating each capture bead with only its corresponding detection antibody. This strategy not only reduces cross-reactivity to background levels and significantly improves measurement accuracies, but also enables higher-order multiplexing. As a proof of concept, the sequential multiplex Simoa assay is used to measure five different cytokines in plasma samples from Coronavirus Disease 2019 (COVID-19) patients. The ultrasensitive sequential multiplex Simoa assays will enable the simultaneous measurements of multiple low-abundance analytes in a time- and cost-effective manner and will prove especially critical in many cases where sample volumes are limited.

Host-Based Biomarkers in Saliva for the Diagnosis of Pulmonary Tuberculosis in Children: A Mini-Review

The diagnosis of pulmonary tuberculosis (TB) in children remains a significant challenge due to its paucibacillary nature, non-specificity of symptoms and suboptimal sensitivity of available diagnostic methods. In young children particularly, it is difficult to obtain high-quality sputum specimens for testing, with this group the least likely to be diagnosed, while most at risk of severe disease. The World Health Organization (WHO) has prioritized research into rapid biomarker-based tests for TB using easily obtainable non-sputum samples, such as saliva. However, the role of biomarkers in saliva for diagnosing TB in children has not been fully explored. In this mini-review, we discuss the value of saliva as a diagnostic specimen in children given its ready availability and non-invasive nature of collection, and review the literature on the use of host-based biomarkers in saliva for diagnosing active pulmonary TB in adults and children. Based on available data from adult studies, we highlight that combinations of cytokines and other proteins show promise in reaching WHO-endorsed target product profiles for new TB triage tests. Given the lack of pediatric research on host biomarkers in saliva and the differing immune response to TB infection between children and adults, we recommend that pediatric studies are now performed to discover and validate salivary host biosignatures for diagnosing pulmonary TB in children. Future directions for pediatric saliva studies are discussed, with suggestions for technologies that can be applied for salivary biomarker discovery and point-of-care test development.

Bayesian Spatial Survival Analysis of Duration to Cure among New Smear-Positive Pulmonary Tuberculosis (PTB) Patients in Iran, during 2011-2018

Mycobacterium tuberculosis is the causative agent of tuberculosis (TB), and pulmonary TB is the most prevalent form of the disease worldwide. One of the most concrete actions to ensure an effective TB control program is monitoring TB treatment outcomes, particularly duration to cure; but, there is no strong evidence in this respect. Thus, the primary aim of this study was to examine the possible spatial variations of duration to cure and its associated factors in Iran using the Bayesian spatial survival model. All new smear-positive PTB patients have diagnosed from March 2011 to March 2018 were included in the study. Out of 34,744 patients, 27,752 (79.90%) patients cured and 6992 (20.10%) cases were censored. For inferential purposes, the Markov chain Monte Carlo algorithms are applied in a Bayesian framework. According to the Bayesian estimates of the regression parameters in the proposed model, a Bayesian spatial log-logistic model, the variables gender (male vs. female, TR = 1.09), altitude (>750 m vs. ≤750 m, TR = 1.05), bacilli density in initial smear (3+ and 2+ vs. 1–9 Basil & 1+, TR = 1.09 and TR = 1.02, respectively), delayed diagnosis (>3 months vs. <1 month, TR = 1.02), nationality (Iranian vs. other, TR = 1.02), and location (urban vs. rural, TR = 1.02) had a significant influence on prolonging the duration to cure. Indeed, pretreatment weight (TR = 0.99) was substantially associated with shorter duration to cure. In summary, the spatial log-logistic model with convolution prior represented a better performance to analyze the duration to cure of PTB patients. Also, our results provide valuable information on critical determinants of duration to cure. Prolonged duration to cure was observed in provinces with low TB incidence and high average altitude as well. Accordingly, it is essential to pay a special attention to such provinces and monitor them carefully to reduce the duration to cure while maintaining a focus on high-risk provinces in terms of TB prevalence.

An Aptamer Linked Immobilized Sorbent Assay (ALISA) to Detect Circulatory IFN-α, an Inflammatory Protein among Tuberculosis Patients

Dysregulation of IFN-α is the basis for pathogenesis of autoimmune as well as infectious diseases. Identifying inflammatory signatures in peripheral blood of patients is an approach for monitoring active infection. Hence, estimation of type I IFNs as an inflammatory biomarker to scrutinize disease status after treatment is useful. Accordingly, an Aptamer Linked Immobilized Sorbent Assay (ALISA) for the detection of IFN-α in serum samples was developed. Sixteen aptamers were screened for their ability to bind IFN-α. Aptamer IFNα-3 exhibited specificity for IFN-α with no cross-reactivity with interferons β and γ and human serum albumin. The disassociation constant (K_d) was determined to be 3.96 ± 0.36 nM, and the limit of detection was ∼2 ng. The characterized IFNα-3 aptamer was used in ALISA to screen tuberculosis (TB) patients' sera. An elevated IFN-α level in sera derived from untreated TB patients (median = 0.31), compared to nontuberculous household contacts (median = 0.13) and healthy volunteers (median = 0.12), and further a decline in IFN-α level among treated patients (median = 0.13) were seen. The ALISA assay facilitates direct estimation of inflammatory protein(s) in circulation unlike mRNA estimation by real time PCR. Designing of aptamers similar to the IFNα-3 aptamer provides a novel approach to assess other inflammatory protein(s) in patients before, during, and after completion of treatment and would denote clinical improvement in successfully treated patients.

Zirconia Hybrid Nanoshells for Nutrient and Toxin Detection

Monitoring milk quality is of fundamental importance in food industry, because of the nutritional value and resulting position of milk in daily diet. The detection of small nutrients and toxins in milk is challenging, considering high sample complexity and low analyte abundance. In addition, the slow analysis and tedious sample preparation hinder the large-scale application of conventional detection techniques. Herein, zirconia hybrid nanoshells are constructed to enhance the performance of laser desorption/ionization mass spectrometry (LDI MS). Zirconia nanoshells with the optimized structures and compositions are used as matrices in LDI MS and achieve direct analysis of small molecules from 5 nL of native milk in ≈1 min, without any purification or separation. Accurate quantitation of small nutrient is achieved by introducing isotope into the zirconia nanoshell-assisted LDI MS as the internal standard, offering good consistency to biochemical analysis (BCA) with R²  = 0.94. Further, trace toxin is enriched and identified with limit-of-detection (LOD) down to 4 pm, outperforming the current analytical methods. This work sheds light on the personalized design of material-based tool for real-case bioanalysis and opens up new opportunities for the simple, fast, and cost-effective detection of various small molecules in a broad field.

Simplified Digital Enzyme-Linked Immunosorbent Assay Using Tyramide Signal Amplification and Fibrin Hydrogels

Many protein biomarkers occur at very low concentrations in biofluids like blood and saliva, and ultrasensitive detection methods are required in order to measure them. Approaches such as digital enzyme-linked immunosorbent assays (ELISA) and single molecule arrays (Simoa) have been developed to accurately quantitate protein concentrations as low as attomolar levels. Although these techniques are being implemented in research and clinical laboratories to develop ultrasensitive clinical diagnostic assays, the size and cost of the instruments required to run these digital assays have precluded them from being implemented into point-of-care diagnostic formats. Here, we report the development of a simplified digital ELISA format that is more amenable to point-of-care technologies, referred to as catalyzed reporter deposition digital ELISA (CARD-dELISA). On-bead signal generation using the CARD tyramide signal amplification technique is combined with bead immobilization in fibrin hydrogels for single molecule counting in a simplified workflow format. CARD-dELISA allows for ultrasensitive protein detection (IL-6: ∼1 fM) with a dynamic range similar to the conventional Simoa assay. We use CARD-dELISA to measure IL-6 in saliva samples and show good agreement with conventional Simoa.

Comprehensive plasma proteomic profiling reveals biomarkers for active tuberculosis

BACKGROUNDTuberculosis (TB) kills more people than any other infection, and new diagnostic tests to identify active cases are required. We aimed to discover and verify novel markers for TB in nondepleted plasma.METHODSWe applied an optimized quantitative proteomics discovery methodology based on multidimensional and orthogonal liquid chromatographic separation combined with high-resolution mass spectrometry to study nondepleted plasma of 11 patients with active TB compared with 10 healthy controls. Prioritized candidates were verified in independent UK (n = 118) and South African cohorts (n = 203).RESULTSWe generated the most comprehensive TB plasma proteome to date, profiling 5022 proteins spanning 11 orders-of-magnitude concentration range with diverse biochemical and molecular properties. We analyzed the predominantly low-molecular weight subproteome, identifying 46 proteins with significantly increased and 90 with decreased abundance (peptide FDR ≤ 1%, q ≤ 0.05). Verification was performed for novel candidate biomarkers (CFHR5, ILF2) in 2 independent cohorts. Receiver operating characteristics analyses using a 5-protein panel (CFHR5, LRG1, CRP, LBP, and SAA1) exhibited discriminatory power in distinguishing TB from other respiratory diseases (AUC = 0.81).CONCLUSIONWe report the most comprehensive TB plasma proteome to date, identifying novel markers with verification in 2 independent cohorts, leading to a 5-protein biosignature with potential to improve TB diagnosis. With further development, these biomarkers have potential as a diagnostic triage test.FUNDINGColciencias, Medical Research Council, Innovate UK, NIHR, Academy of Medical Sciences, Program for Advanced Research Capacities for AIDS, Wellcome Centre for Infectious Diseases Research.

Single Molecule Protein Detection with Attomolar Sensitivity Using Droplet Digital Enzyme-Linked Immunosorbent Assay

Many proteins are present at low concentrations in biological samples, and therefore, techniques for ultrasensitive protein detection are necessary. To overcome challenges with sensitivity, the digital enzyme-linked immunosorbent assay (ELISA) was developed, which is 1000× more sensitive than conventional ELISA and allows sub-femtomolar protein detection. However, this sensitivity is still not sufficient to measure many proteins in various biological samples, thereby limiting our ability to detect and discover biomarkers. To overcome this limitation, we developed droplet digital ELISA (ddELISA), a simple approach for detecting low protein levels using digital ELISA and droplet microfluidics. ddELISA achieves maximal sensitivity by improving the sampling efficiency and counting more target molecules. ddELISA can detect proteins in the low attomolar range and is up to 25-fold more sensitive than digital ELISA using Single Molecule Arrays (Simoa), the current gold standard tool for ultrasensitive protein detection. Using ddELISA, we measured the LINE1/ORF1 protein, a potential cancer biomarker that has not been previously measured in serum. Additionally, due to the simplicity of our device design, ddELISA is promising for point-of-care applications. Thus, ddELISA will facilitate the discovery of biomarkers that have never been measured before for various clinical applications.

Machine learning of serum metabolic patterns encodes early-stage lung adenocarcinoma

Early cancer detection greatly increases the chances for successful treatment, but available diagnostics for some tumours, including lung adenocarcinoma (LA), are limited. An ideal early-stage diagnosis of LA for large-scale clinical use must address quick detection, low invasiveness, and high performance. Here, we conduct machine learning of serum metabolic patterns to detect early-stage LA. We extract direct metabolic patterns by the optimized ferric particle-assisted laser desorption/ionization mass spectrometry within 1 s using only 50 nL of serum. We define a metabolic range of 100-400 Da with 143 m/z features. We diagnose early-stage LA with sensitivity~70-90% and specificity~90-93% through the sparse regression machine learning of patterns. We identify a biomarker panel of seven metabolites and relevant pathways to distinguish early-stage LA from controls (p < 0.05). Our approach advances the design of metabolic analysis for early cancer detection and holds promise as an efficient test for low-cost rollout to clinics.

Evaluation of multi-antigen serological screening for active tuberculosis among people living with HIV

Better triage tests for screening tuberculosis (TB) disease are needed for people living with HIV (PLHIV). We performed the first evaluation of a previously-validated 8-antigen serological panel to screen PLHIV for pulmonary TB in Kampala, Uganda. We selected a random 1:1 sample with and without TB (defined by sputum culture) from a cohort of PLHIV initiating antiretroviral therapy. We used a multiplex microbead immunoassay and an ensemble machine learning classifier to determine the area under the receiver operating characteristic curve (AUC) for Ag85A, Ag85B, Ag85C, Rv0934-P38, Rv3881, Rv3841-BfrB, Rv3873, and Rv2878c. We then assessed the performance with the addition of four TB-specific antigens ESAT-6, CFP-10, Rv1980-MPT64, and Rv2031-HSPX, and every antigen combination. Of 262 participants (median CD4 cell-count 152 cells/μL [IQR 65-279]), 138 (53%) had culture-confirmed TB. The 8-antigen panel had an AUC of 0.53 (95% CI 0.40-0.66), and the additional 4 antigens did not improve performance (AUC 0.51, 95% CI 0.39-0.64). When sensitivity was restricted to ≥90% for the 8- and 12-antigen panel, specificity was 2.2% (95% CI 0-17.7%) and 8.1% (95% CI 0-23.9%), respectively. A three-antigen combination (Rv0934-P38, Ag85A, and Rv2031-HSPX) outperformed both panels, with an AUC of 0.60 (95% CI 0.48-0.73), 90% sensitivity (95% CI 78.2-96.7%) and 29.7% specificity (95% CI 15.9-47%). The multi-antigen panels did not achieve the target accuracy for a TB triage test among PLHIV. We identified a new combination that improved performance for TB screening in an HIV-positive sample compared to an existing serological panel in Uganda, and suggests an approach to identify novel antigen combinations specifically for screening TB in PLHIV.