Highly Multiplexed Proteomic Analysis of Quantiferon Supernatants To Identify Biomarkers of Latent Tuberculosis Infection

Multiple cytokine analysis based on QuantiFERON-TB gold plus in different tuberculosis infection status: an exploratory study

BACKGROUND

More efficient and convenient diagnostic method is a desperate need to reduce the burden of tuberculosis (TB). This study explores the multiple cytokines secretion based on QuantiFERON-TB Gold Plus (QFT-Plus), and screens for optimal cytokines with diagnostic potential to differentiate TB infection status.

METHODS

Twenty active tuberculosis (ATB) patients, fifteen patients with latent TB infection (LTBI), ten patients with previous TB and ten healthy controls (HC) were enrolled. Whole blood samples were collected and stimulated by QFT-Plus TB1 and TB2 antigens. The levels of IFN-γ, TNF-α, IL-2, IL-6, IL-5, IL-10, IP-10, IL-1Ra, CXCL-1 and MCP-1 in supernatant were measured by Luminex bead-based multiplex assays. The receiver operating characteristic curve was used to evaluate the diagnostic accuracy of cytokine for distinguishing different TB infection status.

RESULTS

After stimulation with QFT-Plus TB1 and TB2 antigens, the levels of all cytokines, except IL-5 in TB2 tube, in ATB group were significantly higher than that in HC group. The levels of IL-1Ra concurrently showed the equally highest AUC for distinguishing TB infection from HC, followed by the levels of IP-10 in both TB1 tube and TB2 tube. Moreover, IP-10 levels displayed the largest AUC for distinguishing ATB patients from non-ATB patients. Meanwhile, the levels of IP-10 also demonstrated the largest AUC in both TB1 tube and TB2 tube for distinguishing ATB patients from LTBI.

CONCLUSIONS

In addition to conventional detection of IFN-γ, measuring IP-10 and IL-1Ra based on QFT-Plus may have the more tremendous potential to discriminate different TB infection status.

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.

Proteomics in Biomarker Discovery for Tuberculosis: Current Status and Future Perspectives

Tuberculosis (TB) continues to threaten many peoples' health worldwide, regardless of their country of residence or age. The current diagnosis of TB still uses mainly traditional, time-consuming, and/or culture-based techniques. Efforts have focused on discovering new biomarkers with higher efficiency and accuracy for TB diagnosis. Proteomics-the systematic study of protein diversity-is being applied to the discovery of novel protein biomarkers for different types of diseases. Mass spectrometry (MS) technology plays a revolutionary role in proteomics, and its applicability benefits from the development of other technologies, such as matrix-based and immune-based methods. MS and derivative strategies continuously contribute to disease-related discoveries, and some promising proteomic biomarkers for efficient TB diagnosis have been identified, but challenges still exist. For example, there are discrepancies in the biomarkers identified among different reports and the diagnostic accuracy of clinically applied proteomic biomarkers. The present review summarizes the current status and future perspectives of proteomics in the field of TB biomarker discovery and aims to elicit more promising findings for rapid and accurate TB diagnosis.

Comprehensive aptamer-based screen of 1317 proteins uncovers improved stool protein markers of colorectal cancer

BACKGROUND

To screen and validate novel stool protein biomarkers of colorectal cancer (CRC).

METHODS

A novel aptamer-based screen of 1317 proteins was used to uncover elevated proteins in the stool of patients with CRC, as compared to healthy controls (HCs) in a discovery cohort. Selected biomarker candidates from the discovery cohort were ELISA validated in three independent cross-sectional cohorts comprises 76 CRC patients, 15 adenoma patients, and 63 healthy controls, from two different ethnicities. The expression of the potential stool biomarkers within CRC tissue was evaluated using single-cell RNA-seq datasets.

RESULTS

A total of 92 proteins were significantly elevated in CRC samples as compared to HCs in the discovery cohort. Among Caucasians, the 5 most discriminatory proteins among the 16 selected proteins, ordered by their ability to distinguish CRC from adenoma and healthy controls, were MMP9, haptoglobin, myeloperoxidase, fibrinogen, and adiponectin. Except myeloperoxidase, the others were significantly associated with depth of tumor invasion. The 8 stool proteins with the highest AUC values were also discriminatory in a second cohort of Indian CRC patients. Several of the stool biomarkers elevated in CRC were also expressed within CRC tissue, based on the single-cell RNA-seq analysis.

CONCLUSIONS

Stool MMP9, fibrinogen, myeloperoxidase, and haptoglobin emerged as promising CRC stool biomarkers, outperforming stool Hemoglobin. Longitudinal studies are warranted to assess the clinical utility of these novel biomarkers in early diagnosis of CRC.

Engineered Mycobacterium tuberculosis antigen assembly into core-shell nanobeads for diagnosis of tuberculosis

Despite recent advances in diagnosis, tuberculosis (TB) remains one of the ten leading causes of death worldwide. Here, we engineered Mycobacterium tuberculosis (Mtb) proteins (ESAT6, CFP10, and MTB7.7) to self-assemble into core-shell nanobeads for enhanced TB diagnosis. Respective purified Mtb antigen-coated polyester beads were characterized and their functionality in TB diagnosis was tested in whole blood cytokine release assays. Sensitivity and specificity were studied in 11 pulmonary TB patients (PTB) and 26 healthy individuals composed of 14 Tuberculin Skin Test negative (TSTn) and 12 TST positive (TSTp). The production of 6 cytokines was determined (IFNγ, IP10, IL2, TNFα, CCL3, and CCL11). To differentiate PTB from healthy individuals (TSTp + TSTn), the best individual cytokines were IL2 and CCL11 (>80% sensitivity and specificity) and the best combination was IP10 + IL2 (>90% sensitivity and specificity). We describe an innovative approach using full-length antigens attached to biopolyester nanobeads enabling sensitive and specific detection of human TB.

IL-1RA in the supernatant of QuantiFERON-TB Gold In-Tube and QuantiFERON-TB Gold Plus is useful for discriminating active tuberculosis from latent infection

INTRODUCTION

The new-generation QuantiFERON (QFT)-TB Gold Plus (QFT-Plus) is expected to be useful because it includes a new peptide that is supposed to induce a CD8⁺ T cell response. There is a need for a new marker with sensitivity higher than that of the conventional IFN-γ release assays owing to false-negative results in the latter. This study aimed to compare cytokines in QFT-plus and QuantiFERON-Gold In-Tube (QFT-GIT) supernatants to discriminate between active tuberculosis and latent tuberculosis infection (LTBI).

METHODS

A cross-sectional study was conducted at Tokyo National Hospital, wherein 21 LTBI patients and age and sex-matched active TB patients were randomly selected. The levels of various cytokines were measured and compared using the MAGPIX System, and receiver operating characteristic (ROC) curves were generated.

RESULTS

IL-1RA, IFN-γ, CXCL10/IP-10, and CCL4/MIP-1β levels were higher in the active TB group than in the LTBI group in QFT-GIT antigen (GIT Ag) tubes. In QFT-plus tubes, IL-1RA was higher in TB1 and TB2 tubes, while CCL2/MCP-1 was higher only in TB2 tubes. In Nil tubes, CCL5/RANTES, TNF-α, PDGF-BB, and IL-2 levels were significantly higher in the active TB group. IL-1RA in GIT Ag tubes showed the highest area under the curve of 0.8367. The sensitivity and specificity of IL-1RA were 66.7% (95% confidence interval [CI]: 43.0-85.4) and 90.5% (95% CI: 69.6-98.8), respectively, which were the highest among the cytokines.

CONCLUSIONS

IL-1RA level in the QFT-GIT supernatant can be a good marker for discriminating active TB from LTBI.

Differences in plasma proteomes for active tuberculosis, latent tuberculosis and non-tuberculosis mycobacterial lung disease patients with and without ESAT-6/CFP10 stimulation

BACKGROUND

Tuberculosis (TB) is one of the world's most problematic infectious diseases. The pathogen Mycobacterium tuberculosis (Mtb) is contained by the immune system in people with latent TB infection (LTBI). No overt disease symptoms occur. The environmental and internal triggers leading to reactivation of TB are not well understood. Non-tuberculosis Mycobacteria (NTM) can also cause TB-like lung disease. Comparative analysis of blood plasma proteomes from subjects afflicted by these pathologies in an endemic setting may yield new differentiating biomarkers and insights into inflammatory and immunological responses to Mtb and NTM.

METHODS

Blood samples from 40 human subjects in a pastoral region of Ethiopia were treated with the ESAT-6/CFP-10 antigen cocktail to stimulate anti-Mtb and anti-NTM immune responses. In addition to those of active TB, LTBI, and NTM cohorts, samples from matched healthy control (HC) subjects were available. Following the generation of sample pools, proteomes were analyzed via LC-MS/MS. These experiments were also performed without antigen stimulation steps. Statistically significant differences using the Z-score method were determined and interpreted in the context of the proteins' functions and their contributions to biological pathways.

RESULTS

More than 200 proteins were identified from unstimulated and stimulated plasma samples (UPSs and SPSs, respectively). Thirty-four and 64 proteins were differentially abundant with statistical significance (P < 0.05; Benjamini-Hochberg correction with an FDR < 0.05) comparing UPS and SPS proteomic data of four groups, respectively. Bioinformatics analysis of such proteins via the Gene Ontology Resource was indicative of changes in cellular and metabolic processes, responses to stimuli, and biological regulations. The m7GpppN-mRNA hydrolase was increased in abundance in the LTBI group compared to HC subjects. Charged multivesicular body protein 4a and platelet factor-4 were increased in abundance in NTM as compared to HC and decreased in abundance in NTM as compared to active TB. C-reactive protein, α-1-acid glycoprotein 1, sialic acid-binding Ig-like lectin 16, and vitamin K-dependent protein S were also increased (P < 0.05; fold changes≥2) in SPSs and UPSs comparing active TB with LTBI and NTM cases. These three proteins, connected in a STRING functional network, contribute to the acute phase response and influence blood coagulation.

CONCLUSION

Plasma proteomes are different comparing LTBI, TB, NTM and HC cohorts. The changes are augmented following prior blood immune cell stimulation with the ESAT-6/CFP-10 antigen cocktail. The results encourage larger-cohort studies to identify specific biomarkers to diagnose NTM infection, LTBI, and to predict the risk of TB reactivation.

Chemical Modification of Aptamers for Increased Binding Affinity in Diagnostic Applications: Current Status and Future Prospects

Aptamers are short single stranded DNA or RNA oligonucleotides that can recognize analytes with extraordinary target selectivity and affinity. Despite their promising properties and diagnostic potential, the number of commercial applications remains scarce. In order to endow them with novel recognition motifs and enhanced properties, chemical modification of aptamers has been pursued. This review focuses on chemical modifications, aimed at increasing the binding affinity for the aptamer's target either in a non-covalent or covalent fashion, hereby improving their application potential in a diagnostic context. An overview of current methodologies will be given, thereby distinguishing between pre- and post-SELEX (Systematic Evolution of Ligands by Exponential Enrichment) modifications.

Comprehensive aptamer-based screening identifies a spectrum of urinary biomarkers of lupus nephritis across ethnicities

Emerging urinary biomarkers continue to show promise in evaluating lupus nephritis (LN). Here, we screen urine from active LN patients for 1129 proteins using an aptamer-based platform, followed by ELISA validation in two independent cohorts comprised of 127 inactive lupus, 107 active LN, 67 active non-renal lupus patients and 74 healthy controls, of three different ethnicities. Urine proteins that best distinguish active LN from inactive disease are ALCAM, PF-4, properdin, and VCAM-1 among African-Americans, sE-selectin, VCAM-1, BFL-1 and Hemopexin among Caucasians, and ALCAM, VCAM-1, TFPI and PF-4 among Asians. Most of these correlate significantly with disease activity indices in the respective ethnic groups, and surpass conventional metrics in identifying active LN, with better sensitivity, and negative/positive predictive values. Several elevated urinary molecules are also expressed within the kidneys in LN, based on single-cell RNAseq analysis. Longitudinal studies are warranted to assess the utility of these biomarkers in tracking lupus nephritis.

Precision immunoprofiling to reveal diagnostic signatures for latent tuberculosis infection and reactivation risk stratification

Latent tuberculosis infection (LTBI) is estimated in nearly one quarter of the world's population, and of those immunocompetent and infected ~10% will proceed to active tuberculosis (TB). Current diagnostics cannot definitively identify LTBI and provide no insight into reactivation risk, thereby defining an unmet diagnostic challenge of incredible global significance. We introduce a new machine-learning-driven approach to LTBI diagnostics that leverages a high throughput, multiplexed cytokine detection technology and powerful bioinformatics to reveal multi-marker signatures for LTBI diagnosis and risk stratification. This approach is enabled through an individualized normalization procedure that allows disease-relevant biomarker signatures to be revealed despite heterogeneity in basal immune response. Specifically, cytokines secreted from antigen-challenged peripheral blood mononuclear cells were detected using silicon photonic sensor arrays and multidimensional data correlation of individually-normalized immune responses revealed signatures important for LTBI status. These results demonstrate a powerful combination of multiplexed biomarker detection technologies, precision immune normalization, and feature selection algorithms that revealed positively correlated multi-biomarker signatures for LTBI status and reactivation risk stratification from a relatively simple blood-based assay.

Diagnostic Accuracy of Monocyte Chemotactic Protein (MCP)-2 as Biomarker in Response to PE35/PPE68 Proteins: A Promising Diagnostic Method for the Discrimination of Active and Latent Tuberculosis

INTRODUCTION

Several studies have been conducted to find new biomarkers for the discrimination of Latent Tuberculosis Infection (LTBI) from active TB (ATB); however, their findings are inconsistent. The aim of the current study was to evaluate the potential of in vitro antigenspecific expression of Monocyte Chemotactic Protein (MCP)-2 for discrimination of ATB and LTBI after stimulation of whole blood with PE35 and PPE68 recombinant proteins.

MATERIALS AND METHODS

The recombinant PE35 and PPE68 proteins were evaluated at a final concentration of 5 µg/ml by a 3-day whole blood assay. Secreted MCP-2 from the culture supernatants were measured by commercially available Human MCP2 ELISA Kit. The diagnostic performance of MCP-2 was ascertained by Receiver Operator Characteristic (ROC) curve and measuring the Area Under the Curve (AUC) and their 95% Confidence Intervals (CI). Cut-offs was estimated at various sensitivities and specificities and at the maximum Youden's index (YI), i.e. sensitivity specificity-1.

RESULTS

The median MCP-2 response to both PE35 and PPE68 in those with LTBI was significantly higher than patients with ATB. The discrimination performance of MCP-2 response following stimulation of PE35 (assessed by AUC) between LTBI and patients with ATB was 0.98 (95%CI: 0.94-1.00). Maximum discrimination was reached at a cut-off of 86pg/mL with 100% sensitivity and 97% specificity. The highest sensitivity and specificity was obtained using cut off 58 pg/mL following stimulation with PPE68 (100% and 90%, respectively; AUC: 0.94, 95%CI: 0.85- 1.00).

CONCLUSION

MCP-2 induced by PE35 and PPE68 shows good discriminatory power for discrimination of ATB and LTBI. Additional studies with a larger sample size are needed to confirm the advantage of this marker, alone or combined with other markers; however, these findings present a promising method, which can discriminate between ATB and LTBI.

Prospective evaluation of host biomarkers other than interferon gamma in QuantiFERON Plus supernatants as candidates for the diagnosis of tuberculosis in symptomatic individuals

BACKGROUND

There is an urgent need for new tools for the diagnosis of TB. We evaluated the usefulness recently described host biomarkers in supernatants from the newest generation of the QuantiFERON test (QuantiFERON Plus) as tools for the diagnosis of active TB.

METHODS

We recruited individuals presenting at primary health care clinics in Cape Town, South Africa with symptoms requiring investigation for TB disease, prior to the establishment of a clinical diagnosis. Participants were later classified as TB or other respiratory diseases (ORD) based on the results of clinical and laboratory tests. Using a multiplex platform, we evaluated the concentrations of 37 host biomarkers in QuantiFERON Plus supernatants from study participants as tools for the diagnosis of TB.

RESULTS

Out of 120 study participants, 35(29.2%) were diagnosed with active TB, 69(57.5%) with ORD whereas 16(13.3%) were excluded. 14(11.6%) of the study participants were HIV infected. Although individual host markers showed potential as diagnostic candidates, the main finding of the study was the identification of a six-marker biosignature in unstimulated supernatants (Apo-ACIII, CXCL1, CXCL9, CCL8, CCL-1, CD56) which diagnosed TB with sensitivity and specificity of 73.9%(95% CI; 51.6-87.8) and 87.6%(95% CI; 77.2-94.5), respectively, after leave-one-out cross validation. Combinations between TB-antigen specific biomarkers also showed potential (sensitivity of 77.3% and specificity of 69.2%, respectively), with multiple biomarkers being significantly different between TB patients, Quantiferon Plus Positive and Quantiferon Plus negative individuals with ORD, regardless of HIV status.

CONCLUSIONS

Biomarkers detected in QuantiFERON Plus supernatants may contribute to adjunctive diagnosis of TB.

Reproducibility and Variability of Protein Analytes Measured Using a Multiplexed Modified Aptamer Assay

BACKGROUND

There is growing interest in the use of multiplexed aptamer-based assays for large-scale proteomic studies. However, the analytic, short- and long-term variation of the measured proteins is largely uncharacterized.

METHODS

We quantified 4001 plasma protein analytes from 42 participants in the Atherosclerosis Risk in Communities (ARIC) Study in split samples and at multiple visits using a multiplexed modified aptamer assay. We calculated the CV, Spearman correlation, and intraclass correlation (ICC) between split samples and evaluated the short-term (4-9 weeks) and long-term (approximately 20 years) variability using paired t-tests with log-transformed protein concentrations and Bonferroni-corrected significance thresholds. We performed principal component (PC) analysis of protein analyte concentrations and evaluated their associations with age, sex, race, and estimated glomerular filtration rate (eGFR).

RESULTS

The mean baseline age was 57 years at the first visit, 43% of participants were male and 57% were white. Among 3693 protein analytes that passed quality control, half (n = 1846) had CVs < 5.0%, Spearman correlations > 0.89, and ICCs > 0.96 among the split samples. Over the short term, only 1 analyte had a statistically significant difference between the 2 time points, whereas, over approximately 20 years, 866 analytes (23.4%) had statistically significant differences (P < 1.4 × 10^-5, 681 increased, 185 decreased). PC1 had high correlations with age (-0.73) and eGFR (0.60). PC2 had moderate correlation with male sex (0.18) and white race (0.31).

CONCLUSIONS

Multiplexed modified aptamer technology can assay thousands of proteins with excellent precision. Our results support the potential for large-scale studies of the plasma proteome over the lifespan.

Increased levels of circulating MMP3 correlate with severe rejection in face transplantation

Face transplantation is a viable treatment option for carefully selected patients with devastating injuries to the face. However, acute rejection episodes occur in more than 80% of recipients in the first postoperative year. Unfortunately, neither a correlation between histological grades of rejection and anti-rejection treatment nor systemic surrogate markers of rejection in face transplantation are established in clinical routine. Therefore, we utilized next generation aptamer-based SOMAscan proteomics platform for non-invasive rejection biomarker discovery. Longitudinal serum samples from face transplant recipients with long-term follow-up were included in this study. From the 1,310 proteins analyzed by SOMAscan, a 5-protein signature (MMP3, ACY1, IL1R2, SERPINA4, CPB2) was able to discriminate severe rejection from both no-rejection and nonsevere rejection samples. Technical validation on ELISA platform showed high correlation with the SOMAscan data for the MMP3 protein (r_s = 0.99). Additionally, MMP3 levels were significantly increased during severe rejection as compared to no-rejection (p = 0.0009) and nonsevere rejection (p = 0.0173) episodes. Pathway analyses revealed significant activation of the metallopeptidase activity during severe face transplant rejection. This pilot study demonstrates the feasibility of SOMAscan to identify non-invasive candidate biomarkers of rejection in face transplantation. Further validation in a larger independent patient cohort is needed.

Aptamer-based search for correlates of plasma and serum water T2: implications for early metabolic dysregulation and metabolic syndrome

Background

Metabolic syndrome is a cluster of abnormalities that increases the risk for type 2 diabetes and atherosclerosis. Plasma and serum water T₂ from benchtop nuclear magnetic resonance relaxometry are early, global and practical biomarkers for metabolic syndrome and its underlying abnormalities. In a prior study, water T₂ was analyzed against ~ 130 strategically selected proteins and metabolites to identify associations with insulin resistance, inflammation and dyslipidemia. In the current study, the analysis was broadened ten-fold using a modified aptamer (SOMAmer) library, enabling an unbiased search for new proteins correlated with water T₂ and thus, metabolic health.

Methods

Water T₂ measurements were recorded using fasting plasma and serum from non-diabetic human subjects. In parallel, plasma samples were analyzed using a SOMAscan assay that employed modified DNA aptamers to determine the relative concentrations of 1310 proteins. A multi-step statistical analysis was performed to identify the biomarkers most predictive of water T₂. The steps included Spearman rank correlation, followed by principal components analysis with variable clustering, random forests for biomarker selection, and regression trees for biomarker ranking.

Results

The multi-step analysis unveiled five new proteins most predictive of water T₂: hepatocyte growth factor, receptor tyrosine kinase FLT3, bone sialoprotein 2, glucokinase regulatory protein and endothelial cell-specific molecule 1. Three of the five strongest predictors of water T₂ have been previously implicated in cardiometabolic diseases. Hepatocyte growth factor has been associated with incident type 2 diabetes, and endothelial cell specific molecule 1, with atherosclerosis in subjects with diabetes. Glucokinase regulatory protein plays a critical role in hepatic glucose uptake and metabolism and is a drug target for type 2 diabetes. By contrast, receptor tyrosine kinase FLT3 and bone sialoprotein 2 have not been previously associated with metabolic conditions. In addition to the five most predictive biomarkers, the analysis unveiled other strong correlates of water T₂ that would not have been identified in a hypothesis-driven biomarker search.

Conclusions

The identification of new proteins associated with water T₂ demonstrates the value of this approach to biomarker discovery. It provides new insights into the metabolic significance of water T₂ and the pathophysiology of metabolic syndrome.

Electronic supplementary material

The online version of this article (10.1186/s40364-018-0143-x) contains supplementary material, which is available to authorized users.

Diagnostic performance of GM-CSF and IL-2 in response to long-term specific-antigen cell stimulation in patients with active and latent tuberculosis infection

BACKGROUND

A simple blood test for detecting active tuberculosis (TB) could be key to this epidemic containment, given that a large proportion of patients are unable to produce sputum for testing. Currently available interferon-γ release assays (IGRAs) are inadequate to diagnose active TB, with reported pooled sensitivity and specificity both under 81%.

OBJECTIVE

To explore whether cytokines/chemokines other than interferon-γ in response to long-term cell stimulation could improve the ability to distinguish between different TB infection status.

METHODS

We prospectively enrolled subjects with newly diagnosed pulmonary TB and their household contacts in Santiago. All contacts were tested with IGRA. Peripheral blood mononuclear cells were obtained and antigen-specific stimulated for 72 h before collecting their culture supernatants.

RESULTS

Subjects with active TB displayed markedly low cytokines/chemokines secretion upon PBMC stimulation, with lower GM-CSF being the best differentiator from IGRA(+) contacts, with 71% (95% CI 53-85) sensitivity, 86% (95% CI 65-97) specificity and AUC = 0.79 (p = 0.0003). On the other hand, when compared to the uninfected IGRA(-) contacts, higher level of IL-2 secretion was the best indicator of active TB, with 73.5% (95% CI 56-87) sensitivity, 85% (95% CI 66-96) specificity and AUC = 0.79 (p = 0.0001). No single cytokine/chemokine released upon stimulation could accurately differentiate between active TB and all TB contacts grouped together.

CONCLUSION

GM-CSF and IL-2 provided the best yield to differentiate active TB from latent TB and from TB uninfected, respectively, with higher specificities than that reported for IGRAs. However, none of both resulted sensitive enough to be used as a stand-alone biomarker for active TB.

Probing the colorectal cancer proteome for biomarkers: Current status and perspectives

Colorectal cancer (CRC) is one of the most prevalent malignancies worldwide. Biomarkers that can facilitate better clinical management of CRC are in high demand to improve patient outcome and to reduce mortality. In this regard, proteomic analysis holds a promising prospect in the hunt of novel biomarkers for CRC and in understanding the mechanisms underlying tumorigenesis. This review aims to provide an overview of the current progress of proteomic research, focusing on discovery and validation of diagnostic biomarkers for CRC. We will summarize the contributions of proteomic strategies to recent discoveries of protein biomarkers for CRC and also briefly discuss the potential and challenges of different proteomic approaches in biomarker discovery and translational applications.

Nano-biosensing approaches on tuberculosis: Defy of aptamers

Tuberculosis is a major global health problem caused by the bacterium Mycobacterium tuberculosis (Mtb) complex. According to WHO reports, 53 million TB patients died from 2000 to 2016. Therefore, early diagnosis of the disease is of great importance for global health care programs. The restrictions of traditional methods have encouraged the development of innovative methods for rapid, reliable, and cost-effective diagnosis of tuberculosis. In recent years, aptamer-based biosensors or aptasensors have drawn great attention to sensitive and accessible detection of tuberculosis. Aptamers are small short single-stranded molecules of DNA or RNA that fold to a unique form and bind to targets. Once combined with nanomaterials, nano-scale aptasensors provide powerful analytical platforms for diagnosing of tuberculosis. Various groups designed and studied aptamers specific for the whole cells of M. tuberculosis, mycobacterial proteins and IFN-γ for early diagnosis of TB. Advantages such as high specificity and strong affinity, potential for binding to a larger variety of targets, increased stability, lower costs of synthesis and storage requirements, and lower probability of contamination make aptasensors pivotal alternatives for future TB diagnostics. In recent years, the concept of SOMAmer has opened new horizons in high precision detection of tuberculosis biomarkers. This review article provides a description of the research progresses of aptamer-based and SOMAmer-based biosensors and nanobiosensors for the detection of tuberculosis.

Stability and reproducibility of proteomic profiles measured with an aptamer-based platform

The feasibility of SOMAscan, a multiplex, high sensitivity proteomics platform, for use in studies using archived plasma samples has not yet been assessed. We quantified 1,305 proteins from plasma samples donated by 16 Nurses’ Health Study (NHS) participants, 40 NHSII participants, and 12 local volunteers. We assessed assay reproducibility using coefficients of variation (CV) from duplicate samples and intra-class correlation coefficients (ICC) and Spearman correlation coefficients (r) of samples processed (i.e., centrifuged and aliquoted into separate components) immediately, 24, and 48 hours after collection, as well as those of samples collected from the same individuals 1 year apart. CVs were <20% for 99% of proteins overall and <10% for 92% of proteins in heparin samples compared to 66% for EDTA samples. We observed ICC or Spearman r (comparing immediate vs. 24-hour delayed processing) ≥0.75 for 61% of proteins, with some variation by anticoagulant (56% for heparin and 70% for EDTA) and protein class (ranging from 49% among kinases to 83% among hormones). Within-person stability over 1 year was good (ICC or Spearman r ≥ 0.4) for 91% of proteins. These results demonstrate the feasibility of SOMAscan for analyses of archived plasma samples.

Aptamer-Based Proteomics Identifies Mortality-Associated Serum Biomarkers in Dialysis-Dependent AKI Patients

Introduction

Currently, no effective therapies exist to reduce the high mortality associated with dialysis-dependent acute kidney injury (AKI-D). Serum biomarkers may be useful in understanding the pathophysiological processes involved with AKI and the severity of injury, and point to novel therapeutic targets.

Methods

Study day 1 serum samples from 100 patients and day 8 samples from 107 patients enrolled in the Veteran’s Affairs/National Institutes of Health Acute Renal Failure Trial Network study were analyzed by the slow off-rate modified aptamers scan proteomic platform to profile 1305 proteins in each sample. Patients in each cohort were classified into tertiles based on baseline biomarker measurements. Cox regression analyses were performed to examine the relationships between serum levels of each biomarker and mortality.

Results

Changes in the serum levels of 54 proteins, 33 of which increased and 21 of which decreased, were detected when comparing samples of patients who died in the first 8 days versus patients who survived >8 days. Among the 33 proteins that increased, higher serum levels of fibroblast growth factor-23 (FGF23), tissue plasminogen activator (tPA), neutrophil collagenase (matrix metalloproteinase-8), and soluble urokinase plasminogen activator receptor, when stratified by tertiles, were associated with higher mortality. The association with mortality persisted for each of these proteins after adjusting for other potential risk factors, including age, sex, cardiovascular sequential organ failure assessment score, congestive heart failure, and presence of diabetes. Upper tertile levels of FGF23, tPA, and interleukin-6 on day 8 were associated with increased mortality; however, FGF23 barely lost significance after multivariable adjustment.

Conclusions

Our results underscore an emerging proteomics tool capable of identifying low-abundance serum proteins important not only in the pathogenesis of AKI-D, but which is also helpful in discriminating AKI-D patients with high mortality.

Nucleic acid aptamer-based methods for diagnosis of infections

Infectious diseases are a serious global problem, which not only take an enormous human toll but also incur tremendous economic losses. In combating infectious diseases, rapid and accurate diagnostic tests are required for pathogen identification at the point of care (POC). In this review, investigations of diagnostic strategies for infectious diseases that are based on aptamers, especially nucleic acid aptamers, oligonucleotides that have high affinities and specificities toward their targets, are described. Owing to their unique features including low cost of production, easy chemical modification, high chemical stability, reproducibility, and low levels of immunogenicity and toxicity, aptamers have been widely utilized as bio-recognition elements (bio-receptors) for the development of infection diagnostic systems. We discuss nucleic acid aptamer-based methods that have been developed for diagnosis of infections using a format that organizes discussion according to the target pathogenic analytes including toxins or proteins, whole cells and nucleic acids. Also included is, a summary of recent advances made in the sensitive detection of pathogenic bacteria utilizing the isothermal nucleic acid amplification method. Lastly, a nucleic acid aptamer-based POC system is described and future directions of studies in this area are discussed.

Recent insights into human bronchial proteomics - how are we progressing and what is next?

The human respiratory system is highly prone to diseases and complications. Many lung diseases, including lung cancer (LC), tuberculosis (TB), and chronic obstructive pulmonary disease (COPD) have been among the most common causes of death worldwide. Cystic fibrosis (CF), the most common genetic disease in Caucasians, has adverse impacts on the lungs. Bronchial proteomics plays a significant role in understanding the underlying mechanisms and pathogenicity of lung diseases and provides insights for biomarker and therapeutic target discoveries. Areas covered: We overview the recent achievements and discoveries in human bronchial proteomics by outlining how some of the different proteomic techniques/strategies are developed and applied in LC, TB, COPD, and CF. Also, the future roles of bronchial proteomics in predictive proteomics and precision medicine are discussed. Expert commentary: Much progress has been made in bronchial proteomics. Owing to the advances in proteomics, we now have better ability to isolate proteins from desired cellular compartments, greater protein separation methods, more powerful protein detection technologies, and more sophisticated bioinformatic techniques. These all contributed to our further understanding of lung diseases and for biomarker and therapeutic target discoveries.

New concepts in understanding latent tuberculosis

PURPOSE OF REVIEW

Mycobacterium tuberculosis (M.tb), the etiologic agent of tuberculosis, is a prominent global health threat because of the enormous reservoir of subclinical latent tuberculosis infection (LTBI). Current diagnostic approaches are limited in their ability to predict reactivation risk and LTBI is recalcitrant to antibiotic treatment. The present review summarizes recent advances in our ability to detect, treat and model LTBI as well as our understanding of bacterial physiology during latency.

RECENT FINDINGS

T-cell subsets and circulating proteins have been identified which could serve as biomarkers for LTBI or indicators of reactivation risk. In addition, experimental and in-silico models have enabled discoveries regarding bacterial physiology during latency and the host immune response following infection with latent M.tb.

SUMMARY

Despite recent advances, much more research is needed to bolster our ability to detect, implement treatment and model LTBI. The present work is crucial for the eradication of this global problem.

Th1 cytokines, true functional signatures for protective immunity against TB?

The lack of an effective preventative vaccine against tuberculosis (TB) presents a great challenge to TB control. Since it takes an extremely long time to accurately determine the protective efficacy of TB vaccines, there is a great need to identify the surrogate signatures of protection to facilitate vaccine development. Unfortunately, antigen-specific Th1 cytokines that are currently used to evaluate the protective efficacy of the TB vaccine, do not align with the protection and failure of TB vaccine candidates in clinical trials. In this review, we discuss the limitation of current Th1 cytokines as surrogates of protection and address the potential elements that should be considered to finalize the true functional signatures of protective immunity against TB.

Discovery and Validation of a Six-Marker Serum Protein Signature for the Diagnosis of Active Pulmonary Tuberculosis

New non-sputum biomarker tests for active tuberculosis (TB) diagnostics are of the highest priority for global TB control. We performed in-depth proteomic analysis using the 4,000-plex SOMAscan assay on 1,470 serum samples from seven countries where TB is endemic. All samples were from patients with symptoms and signs suggestive of active pulmonary TB that were systematically confirmed or ruled out for TB by culture and clinical follow-up. HIV coinfection was present in 34% of samples, and 25% were sputum smear negative. Serum protein biomarkers were identified by stability selection using L1-regularized logistic regression and by Kolmogorov-Smirnov (KS) statistics. A naive Bayes classifier using six host response markers (HR6 model), including SYWC, kallistatin, complement C9, gelsolin, testican-2, and aldolase C, performed well in a training set (area under the sensitivity-specificity curve [AUC] of 0.94) and in a blinded verification set (AUC of 0.92) to distinguish TB and non-TB samples. Differential expression was also highly significant (P < 10⁻²⁰) for previously described TB markers, such as IP-10, LBP, FCG3B, and TSP4, and for many novel proteins not previously associated with TB. Proteins with the largest median fold changes were SAA (serum amyloid protein A), NPS-PLA2 (secreted phospholipase A2), and CA6 (carbonic anhydrase 6). Target product profiles (TPPs) for a non-sputum biomarker test to diagnose active TB for treatment initiation (TPP#1) and for a community-based triage or referral test (TPP#2) have been published by the WHO. With 90% sensitivity and 80% specificity, the HR6 model fell short of TPP#1 but reached TPP#2 performance criteria. In conclusion, we identified and validated a six-marker signature for active TB that warrants diagnostic development on a patient-near platform.