The discovery and identification of a candidate proteomic biomarker of active tuberculosis

Candidate serum protein biomarkers for active pulmonary tuberculosis diagnosis in tuberculosis endemic settings

BACKGROUND

Identification of non-sputum diagnostic markers for tuberculosis (TB) is urgently needed. This exploratory study aimed to discover potential serum protein biomarkers for the diagnosis of active pulmonary TB (PTB).

METHOD

We employed Proximity Extension Assay (PEA) to measure levels of 92 protein biomarkers related to inflammation in serum samples from three patient groups: 30 patients with active PTB, 29 patients with other respiratory diseases with latent TB (ORD with LTBI+), and 29 patients with other respiratory diseases without latent TB (ORD with LTBI-). To understand the functional mechanisms associated with differentially expressed proteins, we performed Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses. Least absolute shrinkage and selection operator (LASSO) regression was employed to identify potential TB diagnostic protein biomarkers. Network interactions among the identified candidate diagnostic markers were then analyzed, and their diagnostic performance was evaluated using logistic regression and receiver operating characteristic (ROC) analysis.

RESULT

The analysis revealed 37 differentially expressed proteins (DEPs) in the active PTB group compared to both ORD with LTBI + and ORD with LTBI- groups. Gene Ontology analysis indicated that these DEPs were primarily involved in the inflammatory response, while KEGG enrichment analysis highlighted the cytokine-cytokine receptor interaction pathway as the top significant hit. LASSO regression identified eight promising candidate protein biomarkers: IFN-gamma, LIF, uPA, CSF-1, SCF, SIRT2, 4E-BP1, and GDNF. The combined set of these eight proteins yielded an AUC of 0.943 for differentiating active PTB from ORD with LTBI+, and an AUC of 0.927 for distinguishing PTB from ORD with LTBI-.

CONCLUSION

We have identified eight protein markers that reliably differentiate active PTB from ORD irrespective of LTBI presence. Further large-scale validation and translation of these protein markers into a user-friendly and affordable point-of-care test hold the potential to significantly enhance TB control in high-burden regions.

Integrated plasma proteomics identifies tuberculosis-specific diagnostic biomarkers

BACKGROUNDNovel biomarkers to identify infectious patients transmitting Mycobacterium tuberculosis are urgently needed to control the global tuberculosis (TB) pandemic. We hypothesized that proteins released into the plasma in active pulmonary TB are clinically useful biomarkers to distinguish TB cases from healthy individuals and patients with other respiratory infections.METHODSWe applied a highly sensitive non-depletion tandem mass spectrometry discovery approach to investigate plasma protein expression in pulmonary TB cases compared to healthy controls in South African and Peruvian cohorts. Bioinformatic analysis using linear modeling and network correlation analyses identified 118 differentially expressed proteins, significant through 3 complementary analytical pipelines. Candidate biomarkers were subsequently analyzed in 2 validation cohorts of differing ethnicity using antibody-based proximity extension assays.RESULTSTB-specific host biomarkers were confirmed. A 6-protein diagnostic panel, comprising FETUB, FCGR3B, LRG1, SELL, CD14, and ADA2, differentiated patients with pulmonary TB from healthy controls and patients with other respiratory infections with high sensitivity and specificity in both cohorts.CONCLUSIONThis biomarker panel exceeds the World Health Organization Target Product Profile specificity criteria for a triage test for TB. The new biomarkers have potential for further development as near-patient TB screening assays, thereby helping to close the case-detection gap that fuels the global pandemic.FUNDINGMedical Research Council (MRC) (MR/R001065/1, MR/S024220/1, MR/P023754/1, and MR/W025728/1); the MRC and the UK Foreign Commonwealth and Development Office; the UK National Institute for Health Research (NIHR); the Wellcome Trust (094000, 203135, and CC2112); Starter Grant for Clinical Lecturers (Academy of Medical Sciences UK); the British Infection Association; the Program for Advanced Research Capacities for AIDS in Peru at Universidad Peruana Cayetano Heredia (D43TW00976301) from the Fogarty International Center at the US NIH; the UK Technology Strategy Board/Innovate UK (101556); the Francis Crick Institute, which receives funding from UKRI-MRC (CC2112); Cancer Research UK (CC2112); and the NIHR Biomedical Research Centre of Imperial College NHS.

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.

Several Potential Serum Proteomic Biomarkers for Diagnosis of Osteoarticular Tuberculosis Based on Mass Spectrometry

BACKGROUND

Osteoarticular tuberculosis is one of the extrapulmonary tuberculosis (EPTB) diseases, which is mainly caused by infection of Mycobacterium tuberculosis (MTB) in bone and joints. The limitation of current clinical test methods is leading to a high misdiagnosis rate and affecting the treatment and prognosis. This study aims to search serum biomarkers that can assist in the diagnosis of osteoarticular tuberculosis.

METHODS

Proteomics can serve as an important method in the discovery of disease biomarkers. Liquid chromatography-tandem mass spectrometry (LC-MS/MS) was used to analyze proteins in 90 serum samples, which were collected from June 2020 to December 2021, then evaluated by statistical analysis to screen potential biomarkers. After that, potential biomarkers were validated by ELISA and diagnostic models were also established for observation of multi-index diagnostic efficacy.

RESULTS

118 differential expressed proteins (DEPs) were obtained in serum after statistical analysis. After the diagnostic efficacy evaluation and clinical verification, inter-alpha-trypsin inhibitor heavy chain H2 (ITIH2), complement factor H-related protein 2 (CFHR2), complement factor H-related protein 3 (CFHR3) and complement factor H-related protein 5 (CFHR5) were found as potential biomarkers, with 0.7167 (95%CI: 0.5846-0.8487), 0.8600 (95%CI: 0.7701-0.9499), 0.8150 (95%CI: 0.6998-0.9302), and 0.9978 (95%CI: 0.9918-1.0040) AUC value, respectively. The remaining DEPs except CFHR5 were constructed as diagnostic models, the diagnostic model contained CFHR2 and CFHR3 had good diagnostic efficacy with 0.942 (95%CI: 0.872-0.980) AUC value compared to other models.

CONCLUSION

This study provides a reference for the discovery of serum protein markers for osteoarticular tuberculosis diagnosis, and the screened DEPs can also provide directions for subsequent pathogenesis research.

Coronin-1A serves as a serum biomarker for supportive diagnosis of Mycobacterium tuberculosis infection

Introduction

The severity and spread of tuberculosis, a major burden, can be prevented by more rapid and accurate laboratory diagnosis. The purpose of this study is to systematically explore candidate serum proteins in patients with Mycobacterium tuberculosis infection for further application as novel biomarkers.

Methods

Our study was performed in two major steps: screening of the literature for potential biomarkers, and then validation of their levels in patients and controls. Many serum/plasma proteins previously reported to be abnormally expressed in patients with tuberculosis between 2012 and 2021 were comprehensively assembled. The biological role in tuberculosis was also predicted for each using the bioinformatics tool STRING. Candidate proteins found to have the same expression in other related diseases were excluded. Subsequently, the serum level of the candidate serum/plasma protein that met the aforementioned criteria was validated by sandwich ELISA; diagnostic performance was analysed by the area under the curve (AUC) of the receiver operating characteristic (ROC).

Results

From 103 collected serum/plasma proteins, coronin-1A was found to have abnormal expression only in patients with tuberculosis and was associated with tuberculosis. In addition, the validation of coronin-1A in the serum of patients with pulmonary tuberculosis revealed a higher level than in that of healthy individuals. Furthermore, the area under the ROC curve for diagnostic power of coronin-1A was 0.866, with high sensitivity and specificity at a cut-point of approximately 52.7 ng/mL.

Conclusions

We concluded that the level of serum coronin-1A might serve as a novel biomarker for alternative laboratory examination to effectively distinguish patients with tuberculosis from those with other related diseases and healthy individuals.

Diagnostic biomarkers for active tuberculosis: progress and challenges

Tuberculosis (TB) is a leading cause of morbidity and mortality from a single infectious agent, despite being preventable and curable. Early and accurate diagnosis of active TB is critical to both enhance patient care, improve patient outcomes, and break Mycobacterium tuberculosis (Mtb) transmission cycles. In 2020 an estimated 9.9 million people fell ill from Mtb, but only a little over half (5.8 million) received an active TB diagnosis and treatment. The World Health Organization has proposed target product profiles for biomarker- or biosignature-based diagnostics using point-of-care tests from easily accessible specimens such as urine or blood. Here we review and summarize progress made in the development of pathogen- and host-based biomarkers for active TB diagnosis. We describe several unique patient populations that have posed challenges to development of a universal diagnostic TB biomarker, such as people living with HIV, extrapulmonary TB, and children. We also review additional limitations to widespread validation and utilization of published biomarkers. We conclude with proposed solutions to enhance TB diagnostic biomarker validation and uptake.

ALB, HP, OAF and RBP4 as novel protein biomarkers for identifying cured patients with pulmonary tuberculosis by DIA

BACKGROUND

Pulmonary tuberculosis (TB) is a serious infectious disease that lacks robust blood-based biomarkers to identify cured TB. Some discharged patients are not fully cured and may relapse or even develop multidrug-resistant TB. This study is committed to finding proteomic-based plasma biomarkers to support establishing laboratory standards for clinical TB cure.

METHODS

Data-independent acquisition (DIA) was used to obtain the plasma protein expression profiles of TB patients at different treatment stages compared with healthy controls. Multivariate statistical methods and bioinformatics were used to analyze the data.

RESULTS

Bioinformatic analysis suggests coagulation dysfunction and vitamin and lipid metabolism disturbances in TB. Albumin (ALB), haptoglobin (HP), out at first protein homolog (OAF), and retinol-binding protein 4 (RBP4) can be used to establish a diagnostic model for the efficacy evaluation of TB with an area under the curve of 0.963, which could effectively distinguish untreated TB patients from cured patients.

CONCLUSIONS

Our research demonstrated that ALB, HP, OAF and RBP4 can be potential biomarkers for evaluating the efficacy of TB. These findings may provide experimental data for establishing the laboratory indicators of clinical TB cure and providing clinicians with new targets for exploring the underlying mechanisms of TB pathogenesis.

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.

High miRNA-378 expression has high diagnostic values for pulmonary tuberculosis and predicts adverse outcomes

BACKGROUND

Pulmonary tuberculosis (TB) is a chronic infectious disease. microRNA (miR)-378 is involved in TB diagnosis. This study explored the effects of miR-378 on TB patients.

METHODS

A total of 126 TB patients were selected, including 63 active TB and 63 latent TB, with 62 healthy subjects as controls. Serum miR-378 expression was detected. The diagnostic value of miR-378 in TB was analyzed using the ROC curve. Immune inflammatory factor levels were detected and their correlations with miR-378 expression were analyzed. The drug resistance of active TB patients was recorded after standard treatment. miR-378 expression in drug-resistant TB patients was detected. The effects of miR-378 on adverse outcome incidence were analyzed.

RESULTS

miR-378 expression was highly expressed in TB and the expression was higher in the active group than the latent group. Serum miR-378 expression > 1.490 had high sensitivity and specificity in TB diagnosis. miR-378 expression was correlated with TB clinical indexes. IL-4, IL-6, and IL-1β levels were highly expressed, while IFN-γ, TNF-α, and IL-12 levels were lowly expressed in TB patients. Serum miR-378 level in the active group was positively correlated with serum IL-4, IL-6, and IL-1β, and negatively correlated with serum IFN-γ, TNF-α, and IL-12 concentrations. miR-378 expression was downregulated in the TB treated, single (SDR TB) and multi-drug resistance (MDR TB) groups, the miR-378 expression in SDR TB and MDR TB groups was higher than the TB treated group and lower in the SDR TB group than the MDR TB group. High miR-378 expression predicted higher adverse outcome incidence.

CONCLUSIONS

High miR-378 expression assisted TB diagnosis and predicted adverse outcomes.

Evolutionary Views of Tuberculosis: Indoleamine 2,3-Dioxygenase Catalyzed Nicotinamide Synthesis Reflects Shifts in Macrophage Metabolism: Indoleamine 2,3-Dioxygenase Reflects Altered Macrophage Metabolism During Tuberculosis Pathogenesis

Indoleamine 2,3-dioxygenase (IDO) is the rate-limiting enzyme in conversion of tryptophan to kynurenines, feeding de novo nicotinamide synthesis. IDO orchestrates materno-foetal tolerance, increasing human reproductive fitness. IDO mediates immune suppression through depletion of tryptophan required by T lymphocytes and other mechanisms. IDO is expressed by alternatively activated macrophages, suspected to play a key role in tuberculosis (TB) pathogenesis. Unlike its human host, Mycobacterium tuberculosis can synthesize tryptophan, suggesting possible benefit to the host from infection with the microbe. Intriguingly, nicotinamide analogues are used to treat TB. In reviewing this field, it is postulated that flux through the nicotinamide synthesis pathway reflects switching between aerobic glycolysis and oxidative phosphorylation in M. tuberculosis-infected macrophages. The evolutionary cause of such shifts may be ancient mitochondrial behavior related to reproductive fitness. Evolutionary perspectives on the IDO pathway may elucidate why, after centuries of co-existence with the Tubercle bacillus, humans still remain susceptible to TB disease.

Composite Bacterial Infection Index and Serum Amyloid A Protein in Pulmonary Tuberculosis Patients and their Household Contacts in Makassar

BACKGROUND: Early diagnosis of tuberculosis (TB) cases in limited resource remains challenging. It is urgent to identify the new diagnostic tools which can control the spread of disease with accurate and rapid test. AIM: This study aimed to investigate the levels of infection markers: Composite bacterial infection index (CBII) and serum amyloid A (SAA) protein in pulmonary TB (PTB), and their healthy household contacts, as the alternative diagnostic markers for TB. METHODS: CBII and SAA were measured from 44 new PTB patients, and 31 household contact serum samples. The value of CBII was calculated from neutrophils, lymphocytes, monocytes, erythrocyte sedimentation rate, and high-sensitivity C-reactive protein (hs-CRP) level. hs-CRP and SAA levels were quantified from their serum samples using ELISA. QuantiFERON-TB Gold Plus (interferon gamma release assay [IGRA]) was used to screen latent TB infection among household contacts. RESULTS: Among 31 household contacts, there were 24 positive IGRA results and the rest (n = 7) had negative results. PTB patients exhibited significantly higher level CBII in the serum specimens, than those in household contact (p < 0.0001). There was no significant difference in the SAA level between TB cases and household contacts (p = 0.679). CONCLUSIONS: CBII can be used as one of the biomarkers for the identification of PTB from the serum specimens.

Rapid Discrimination and Authentication of Korean Farmstead Mozzarella Cheese through MALDI-TOF and Multivariate Statistical Analysis

Geographical origin and authenticity are the two crucial factors that propel overall cheese perception in terms of quality and price; therefore, they are of great importance to consumers and commercial cheese producers. Herein, we demonstrate a rapid, accurate method for discrimination of domestic and import mozzarella cheeses in the Republic of Korea by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS). The protein profiles' data aided by multivariate statistical analysis successfully differentiated farmstead and import mozzarella cheeses according to their geographical location of origin. A similar investigation within domestic samples (farmsteads/companies) also showed clear discrimination regarding the producer. Using the biomarker discovery tool, we identified seven distinct proteins, of which two (m/z 7407.8 and 11,416.6) were specific in farmstead cheeses, acting as potential markers to ensure authentication and traceability. The outcome of this study can be a good resource in building a database for Korean domestic cheeses. This study also emphasizes the combined utility of MALDI-TOF MS and multivariate analysis in preventing fraudulent practices, thereby ensuring market protection for Korean farmstead cheeses.

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.

Serum sCD14, PGLYRP2 and FGA as potential biomarkers for multidrug-resistant tuberculosis based on data-independent acquisition and targeted proteomics

Multidrug‐resistant tuberculosis (MDR‐TB), defined as tuberculosis (TB) resistant to at least isoniazid and rifampicin, is a major concern of TB control worldwide. However, the diagnosis of MDR‐TB remains a huge challenge to its prevention and control. To identify new diagnostic methods for MDR‐TB, a mass spectrometry strategy of data‐independent acquisition and parallel reaction monitoring was used to detect and validate differential serum proteins. The bioinformatic analysis showed that the functions of differential serum proteins between the MDR‐TB group and the drug‐sensitive tuberculosis group were significantly correlated to the complement coagulation cascade, surface adhesion and extracellular matrix receptor interaction, suggesting a disorder of coagulation in TB. Here, we identified three potential candidate biomarkers such as sCD14, PGLYRP2 and FGA, and established a diagnostic model using these three candidate biomarkers with a sensitivity of 81.2%, a specificity of 90% and the area under the curve value of 0.934 in receiver operation characteristics curve to diagnose MDR‐TB. Our study has paved the way for a novel method to diagnose MDR‐TB and may contribute to elucidate the mechanisms underlying MDR‐TB.

Elevated pulmonary tuberculosis biomarker miR-423-5p plays critical role in the occurrence of active TB by inhibiting autophagosome-lysosome fusion

Rapid diagnosis of pulmonary tuberculosis is an effective measure to prevent the spread of tuberculosis. However, the grim fact is that the new, rapid, and safe methods for clinical diagnosis are lacking. Moreover, although auto-lysosome is critical in clearing Mycobacterium tuberculosis, the pathological significance of microRNAs, as biomarkers of tuberculosis, in autophagosome maturation is unclear. Here, these microRNAs were investigated by Solexa sequencing and qPCR validation, and a potential diagnostic model was established by logistic regression. Besides that, the mechanism of one of the microRNAs involved in the occurrence of tuberculosis was studied. The results showed that the expression of miR-423-5p, miR-17-5p, and miR-20b-5p were significantly increased in the serum of patients with tuberculosis. The combination of these three microRNAs established a model to diagnose tuberculosis with an accuracy of 78.18%, and an area under the curve value of 0.908. Bioinformatics analysis unveiled miR-423-5p as the most likely candidate in regulating autophagosome maturation. The up-regulation of miR-423-5p could inhibit autophagosome maturation through suppressing autophagosome–lysosome fusion in macrophages. Further investigations showed that VPS33A was the direct target of miR-423-5p, and the two CUGCCCCUC domains in VPS33A 3’-UTR were the direct regulatory sites for miR-423-5p. In addition, an inverse correlation between VPS33A and miR-423-5p was found in peripheral blood mononuclear cells of patients with tuberculosis. Since the inhibition of autolysosome formation plays a critical role in tuberculosis occurrence, our findings suggests that miR-423-5p could suppress autophagosome–lysosome fusion by post-transcriptional regulation of VPS33A, which might be important for the occurrence of active tuberculosis.

Recent insights into Mycobacterium tuberculosis through proteomics and implications for the clinic

This review aimed at providing an update on the application of proteomics-based approaches to gain recent insights of Mycobacterium tuberculosis (M.tb) and its relevance to clinic. Proteomics and bioinformatics approaches helped in the identification and characterization of novel proteins. Studying M.tb, causative agent of tuberculosis (TB), at the proteomic level can contribute to the identification of proteins which can be considered as potential targets for developed drugs and can help us in better understanding the pathogen physiology. Areas covered: In this review we have presented a comprehensive literature pertaining to role of proteomics in understanding M.tb. We have also focused on how the development and advancement in technology in the field of proteomics has augmented the research and played a pivotal role in answering many unexplored questions. Lastly, the application of proteomics to clinic has also been discussed. Expert commentary: We envisage that proteomics has gained remarkable momentum over the years. Proteomics can play an important role in the discovery of biomarkers for TB and other diseases. Also, it can aid in development of effective vaccines and simple, rapid and cost-effective test for the diagnosis of TB which is crucial for the management and control of the disease.

Elucidation of a Human Urine Metabolite as a Seryl-Leucine Glycopeptide and as a Biomarker of Effective Anti-Tuberculosis Therapy

The evaluation of new tuberculosis (TB) therapies is limited by the paucity of biomarkers to monitor treatment response. Previous work detected an uncharacterized urine metabolite with a molecular mass of 874.3547 Da that showed promise as a biomarker for successful TB treatment. Using mass spectrometry combined with enzymatic digestions, the metabolite was structurally characterized as a seryl-leucine core 1 O-glycosylated peptide (SLC1G) of human origin. Examination of SLC1G in urine revealed a significant abundance increase in individuals with active TB versus their household contacts and healthy controls. Moreover, differential decreases in SLC1G levels were observed by week one in TB patients during successful treatment versus those that failed treatment. The SLC1G levels were also associated with clinical parameters used to measure bacterial burden (GeneXpert) and inflammation (positron emission tomography-computed tomography (PET-CT)). These results demonstrate the importance of metabolite identification and provide strong evidence for applying SLC1G as a biomarker of TB treatment response.

S-Trap, an Ultrafast Sample-Preparation Approach for Shotgun Proteomics

The success of shotgun proteomic analysis depends largely on how samples are prepared. Current approaches (such as those that are gel-, solution-, or filter-based), although being extensively employed in the field, are time-consuming and less effective with respect to the repetitive sample processing, recovery, and overall yield. As an alternative, the suspension trapping (S-Trap) filter has been commercially available very recently in the format of a single or 96-well filter plate. In contrast to the conventional filter-aided sample preparation (FASP) approach, which utilizes a molecular weight cut-off (MWCO) membrane as the filter and requires hours of processing before digestion-ready proteins can be obtained, the S-Trap employs a three-dimensional porous material as filter media and traps particulate protein suspensions with the subsequent depletion of interfering substances and in-filter digestion. Due to the large (submicron) pore size, each centrifugation cycle of the S-Trap filter only takes 1 min, which significantly reduces the total processing time from approximately 3 h by FASP to less than 15 min, suggesting an ultrafast sample-preparation approach for shotgun proteomics. Here, we comprehensively evaluate the performance of the individual S-Trap filter and 96-well filter plate in the context of global protein identification and quantitation using whole-cell lysate and clinically relevant sputum samples.

Application of multiplexed ion mobility spectrometry towards the identification of host protein signatures of treatment effect in pulmonary tuberculosis

Rationale:

The monitoring of TB treatments in clinical practice and clinical trials relies on traditional sputum-based culture status indicators at specific time points. Accurate, predictive, blood-based protein markers would provide a simpler and more informative view of patient health and response to treatment.

Objective:

We utilized sensitive, high throughput multiplexed ion mobility-mass spectrometry (IM-MS) to characterize the serum proteome of TB patients at the start of and at 8 weeks of rifamycin-based treatment. We sought to identify treatment specific signatures within patients as well as correlate the proteome signatures to various clinical markers of treatment efficacy.

Methods:

Serum samples were collected from 289 subjects enrolled in CDC TB Trials Consortium Study 29 at time of enrollment and at the end of the intensive phase (after 40 doses of TB treatment). Serum proteins were immunoaffinity-depleted of high abundant components, digested to peptides and analyzed for data acquisition utilizing a unique liquid chromatography IM-MS platform (LC-IM-MS). Linear mixed models were utilized to identify serum protein changes in the host response to antibiotic treatment as well as correlations with culture status end points.

Results:

A total of 10,137 peptides corresponding to 872 proteins were identified, quantified, and used for statistical analysis across the longitudinal patient cohort. In response to TB treatment, 244 proteins were significantly altered. Pathway/network comparisons helped visualize the interconnected proteins, identifying up regulated (lipid transport, coagulation cascade, endopeptidase activity) and down regulated (acute phase) processes and pathways in addition to other cross regulated networks (inflammation, cell adhesion, extracellular matrix). Detection of possible lung injury serum proteins such as HPSE, significantly downregulated upon treatment. Analyses of microbiologic data over time identified a core set of serum proteins (TTHY, AFAM, CRP, RET4, SAA1, PGRP2) which change in response to treatment and also strongly correlate with culture status. A similar set of proteins at baseline were found to be predictive of week 6 and 8 culture status.

Conclusion:

A comprehensive host serum protein dataset reflective of TB treatment effect is defined. A repeating set of serum proteins (TTHY, AFAM, CRP, RET4, SAA1, PGRP2, among others) were found to change significantly in response to treatment, to strongly correlate with culture status, and at baseline to be predictive of future culture conversion. If validated in cohorts with long term follow-up to capture failure and relapse of TB, these protein markers could be developed for monitoring of treatment in clinical trials and in patient care.

Label-Free Quantitative Proteomics Identifies Novel Plasma Biomarkers for Distinguishing Pulmonary Tuberculosis and Latent Infection

The lack of effective differential diagnostic methods for active tuberculosis (TB) and latent infection (LTBI) is still an obstacle for TB control. Furthermore, the molecular mechanism behind the progression from LTBI to active TB has been not elucidated. Therefore, we performed label-free quantitative proteomics to identify plasma biomarkers for discriminating pulmonary TB (PTB) from LTBI. A total of 31 overlapping proteins with significant difference in expression level were identified in PTB patients (n = 15), compared with LTBI individuals (n = 15) and healthy controls (HCs, n = 15). Eight differentially expressed proteins were verified using western blot analysis, which was 100% consistent with the proteomics results. Statistically significant differences of six proteins were further validated in the PTB group compared with the LTBI and HC groups in the training set (n = 240), using ELISA. Classification and regression tree (CART) analysis was employed to determine the ideal protein combination for discriminating PTB from LTBI and HC. A diagnostic model consisting of alpha-1-antichymotrypsin (ACT), alpha-1-acid glycoprotein 1 (AGP1), and E-cadherin (CDH1) was established and presented a sensitivity of 81.2% (69/85) and a specificity of 95.2% (80/84) in discriminating PTB from LTBI, and a sensitivity of 81.2% (69/85) and a specificity of 90.1% (64/81) in discriminating PTB from HCs. Additional validation was performed by evaluating the diagnostic model in blind testing set (n = 113), which yielded a sensitivity of 75.0% (21/28) and specificity of 96.1% (25/26) in PTB vs. LTBI, 75.0% (21/28) and 92.3% (24/26) in PTB vs. HCs, and 75.0% (21/28) and 81.8% (27/33) in PTB vs. lung cancer (LC), respectively. This study obtained the plasma proteomic profiles of different M.TB infection statuses, which contribute to a better understanding of the pathogenesis involved in the transition from latent infection to TB activation and provide new potential diagnostic biomarkers for distinguishing PTB and LTBI.

"Tuberculosis in advanced HIV infection is associated with increased expression of IFNγ and its downstream targets"

BACKGROUND

Tuberculosis (TB) is the major cause of death in Human Immunodeficiency Virus (HIV)-infected individuals. However, diagnosis of TB in HIV remains challenging particularly when HIV infection is advanced. Several gene signatures and serum protein biomarkers have been identified that distinguish active TB from latent infection. Our study was designed to assess if gene expression signatures and cytokine levels would distinguish active TB in advanced HIV.

METHODS

We conducted a case-control study of whole blood RNA-Seq and plasma cytokine/chemokine analysis in HIV-infected with CD4+ T cell count of ≤ 100 cells/μl, with and without active TB. Next, the overlap of the differentially expressed genes (DEG) with the published signatures was performed and then receiver operator characteristic (ROC) analysis was done on small gene discriminators to determine their performance in distinguishing TB in advanced HIV. ELISA was performed on plasma to evaluate cytokine and chemokine levels.

RESULTS

Hierarchical clustering of the transcriptional profiles showed that, in general, HIV-infected individuals with TB (TB-HIV) clustered separately from those without TB. IPA indicated that the TB-HIV signature was characterized by an increase in inflammatory signaling pathways. Analysis of overlaps between DEG in our data set with published TB signatures revealed that significant overlap was seen with one TB signature and one TB-IRIS signature. ROC analysis revealed that transcript levels of FcGR1A (AUC = 0.85) and BATF2 (AUC = 0.82), previously reported as consistent single gene classifiers of active TB irrespective of HIV status, performed successfully even in advanced HIV. Plasma protein levels of IFNγ, a stimulator of FcGR1A and BATF2, and CXCL10, also up-regulated by IFNγ, accurately classified active TB (AUC = 0.98 and 0.91, respectively) in advanced HIV. Neither of these genes nor proteins distinguished between TB and TB-IRIS.

CONCLUSIONS

Gene expression of FcGR1A and BATF2, and plasma protein levels of IFNγ and CXCL10 have the potential to independently detect TB in advanced HIV. However, since other lung diseases were not included in this study, these final candidates need to be validated as specific to TB in the advanced HIV population with TB.

Potential Immunological Biomarkers for Detection of Mycobacterium tuberculosis Infection in a Setting Where M. tuberculosis Is Endemic, Ethiopia

Accurate diagnosis and early treatment of tuberculosis (TB) and latent TB infection (LTBI) are vital to prevent and control TB. The lack of specific biomarkers hinders these efforts. This study's purpose was to screen immunological markers that discriminate Mycobacterium tuberculosis infection outcomes in a setting where it is endemic, Ethiopia. Whole blood from 90 participants was stimulated using the ESAT-6/CFP-10 antigen cocktail. The interferon gamma (IFN-γ)-based QuantiFERON diagnostic test was used to distinguish between LTBI and uninfected control cases. Forty cytokines/chemokines were detected from antigen-stimulated plasma supernatants (SPSs) and unstimulated plasma samples (UPSs) using human cytokine/chemokine antibody microarrays. Statistical tests allowed us to identify potential biomarkers that distinguish the TB, LTBI, and healthy control groups. As expected, the levels of IFN-γ in SPSs returned a high area under the receiver operating characteristic curve (AUC) value comparing healthy controls and LTBI cases (Z = 0.911; P < 0.001). The SPS data also indicated that interleukin 17 (IL-17) abundance discriminates LTBI from healthy controls (Z = 0.763; P = 0.001). RANTES and MIP-1β were significantly elevated in SPSs of TB-infected compared to healthy controls (P < 0.05), while IL-12p40 and soluble tumor necrosis factor receptor II (sTNF-RII) were significantly increased in active TB cases compared to the combined LTBI and control groups (P < 0.05). Interestingly, quantitative changes for RANTES were observed using both SPSs and UPSs, with P values of 0.013 and 0.012, respectively, in active TB versus LTBI cases and 0.001 and 0.002, respectively, in active TB versus healthy controls. These results encourage biomarker verification studies for IL-17 and RANTES. Combinations of these cytokines may complement IFN-γ measurements to diagnose LTBI and distinguish active TB from LTBI cases.

Identification of a Novel Serum Biomarker for Tuberculosis Infection in Chinese HIV Patients by iTRAQ-Based Quantitative Proteomics

Tuberculosis (TB) is a major comorbidity in HIV patients as well as a serious co-epidemic. Traditional detection methods are not effective or sensitive for the detection of Mycobacterium tuberculosis at the early stage. TB has become a major cause of lethal on HIV patients. We employed isobaric tags for relative and absolute quantitation (iTRAQ) technology to identify the different host responses in HIV-noTB and HIV-TB patients’ sera. Given the diversity of HIV subtypes, which results in a variety of host responses in different human populations, we focused on the Chinese patients. Of the 25 proteins identified, 7 were increased and 18 were decreased in HIV-TB co-infected patients. These proteins were found to be involved in host immune response processes. We identified a candidate protein, endoglin (ENG), which showed an 4.9 times increase by iTRAQ and 11.5 times increase by ELISA. ENG demonstrated the diagnostic efficacy and presented a novel molecular biomarker for TB in HIV-infected Chinese patients. This study provides new insight into the challenges in the diagnosis and effective management of patients with HIV-TB.

Characterization of plasma proteins in children of different Mycobacterium tuberculosis infection status using label-free quantitative proteomics

Tuberculosis (TB), caused by Mycobacterium tuberculosis (MTB), is an infectious disease found worldwide. Children infected with MTB are more likely to progress to active TB (ATB); however, the molecular mechanism behind this process has long been a mystery. We employed the label-free quantitative proteomic technology to identify and characterize differences in plasma proteins between ATB and latent TB infection (LTBI) in children. To detect differences that are indicative of MTB infection, we first selected proteins whose expressions were markedly different between the ATB and LTBI groups and the control groups (inflammatory disease control (IDC) and healthy control (HC) groups). A total of 521 proteins differed (> 1.5-fold or < 0.6-fold) in the LTBI group, and 318 proteins in the ATB group when compared with the control groups. Of these, 49 overlapping proteins were differentially expressed between LTBI and ATB. Gene Ontology (GO) analysis revealed most proteins had a cellular and organelle distribution. The MTB infection status was mainly related to differences in binding, cellular and metabolic processes. XRCC4, PCF11, SEMA4A and ATP11A were selected and further verified by qPCR and western blot. At the mRNA level, the expression of XRCC4, PCF11and SEMA4A presented an increased trend in ATB group compare with LTBI. At the protein level, the expression of all these proteins by western blot in ATB/LTBI was consistent with the trends from proteomic detection. Our results provide important data for future mechanism studies and biomarker selection for MTB infection in children.

Mass spectrometry applied to the identification of Mycobacterium tuberculosis and biomarker discovery

An adequate and effective tuberculosis (TB) diagnosis system has been identified by the World Health Organization as a priority in the fight against this disease. Over the years, several methods have been developed to identify the bacillus, but bacterial culture remains one of the most affordable methods for most countries. For rapid and accurate identification, however, it is more feasible to implement molecular techniques, taking advantage of the availability of public databases containing protein sequences. Mass spectrometry (MS) has become an interesting technique for the identification of TB. Here, we review some of the most widely employed methods for identifying Mycobacterium tuberculosis and present an update on MS applied for the identification of mycobacterial species.

Serum amyloid A, protein Z, and C4b-binding protein β chain as new potential biomarkers for pulmonary tuberculosis

The aim of this study was to discover novel biomarkers for pulmonary tuberculosis (TB). Differentially expressed proteins in the serum of patients with TB were screened and identified by iTRAQ-two dimensional liquid chromatography tandem mass spectrometry analysis. A total of 79 abnormal proteins were discovered in patients with TB compared with healthy controls. Of these, significant differences were observed in 47 abnormally expressed proteins between patients with TB or pneumonia and chronic obstructive pulmonary disease (COPD). Patients with TB (n = 136) exhibited significantly higher levels of serum amyloid A (SAA), vitamin K-dependent protein Z (PROZ), and C4b-binding protein β chain (C4BPB) than those in healthy controls (n = 66) (P<0.0001 for each) albeit significantly lower levels compared with those in patients with pneumonia (n = 72) (P<0.0001 for each) or COPD (n = 72) (P<0.0001, P<0.0001, P = 0.0016, respectively). After 6 months of treatment, the levels of SAA and PROZ were significantly increased (P = 0.022, P<0.0001, respectively), whereas the level of C4BPB was significantly decreased (P = 0.0038) in treated TB cases (n = 72). Clinical analysis showed that there were significant differences in blood clotting and lipid indices in patients with TB compared with healthy controls, patients with pneumonia or COPD, and treated TB cases (P<0.05). Correlation analysis revealed significant correlations between PROZ and INR (rs = 0.414, P = 0.044), and between C4BPB and FIB (rs = 0.617, P = 0.0002) in patients with TB. Receiver operating characteristic curve analysis revealed that the area under the curve value of the diagnostic model combining SAA, PROZ, and C4BPB to discriminate the TB group from the healthy control, pneumonia, COPD, and cured TB groups was 0.972, 0.928, 0.957, and 0.969, respectively. Together, these results suggested that SAA, PROZ, and C4BPB may serve as new potential biomarkers for TB. Our study may thus provide experimental data for the differential diagnosis of TB.

Diagnostic 'omics' for active tuberculosis

The decision to treat active tuberculosis (TB) is dependent on microbiological tests for the organism or evidence of disease compatible with TB in people with a high demographic risk of exposure. The tuberculin skin test and peripheral blood interferon-γ release assays do not distinguish active TB from a cleared or latent infection. Microbiological culture of mycobacteria is slow. Moreover, the sensitivities of culture and microscopy for acid-fast bacilli and nucleic acid detection by PCR are often compromised by difficulty in obtaining samples from the site of disease. Consequently, we need sensitive and rapid tests for easily obtained clinical samples, which can be deployed to assess patients exposed to TB, discriminate TB from other infectious, inflammatory or autoimmune diseases, and to identify subclinical TB in HIV-1 infected patients prior to commencing antiretroviral therapy. We discuss the evaluation of peripheral blood transcriptomics, proteomics and metabolomics to develop the next generation of rapid diagnostics for active TB. We catalogue the studies published to date seeking to discriminate active TB from healthy volunteers, patients with latent infection and those with other diseases. We identify the limitations of these studies and the barriers to their adoption in clinical practice. In so doing, we aim to develop a framework to guide our approach to discovery and development of diagnostic biomarkers for active TB.

Screening and identification of five serum proteins as novel potential biomarkers for cured pulmonary tuberculosis

Rapid and efficient methods for the determination of cured tuberculosis (TB) are lacking. A total of 85 differentially expressed serum proteins were identified by iTRAQ labeling coupled with two-dimensional liquid chromatography-tandem mass spectrometry (2D LC-MS/MS) analysis (fold change >1.50 or <0.60, P < 0.05). We validated albumin (ALB), Rho GDP-dissociation inhibitor 2 (ARHGDIB), complement 3 (C3), ficolin-2 (FCN2), and apolipoprotein (a) (LPA) using the enzyme-linked immunosorbent assay (ELISA) method. Significantly increased ALB and LPA levels (P = 0.036 and P = 0.012, respectively) and significantly reduced ARHGDIB, C3, and FCN2 levels (P < 0.001, P = 0.035, and P = 0.018, respectively) were observed in cured TB patients compared with untreated TB patients. In addition, changes in ALB and FCN2 levels occurred after 2 months of treatment (P < 0.001 and P = 0.030, respectively). We established a cured TB model with 87.10% sensitivity, 79.49% specificity, and an area under the curve (AUC) of 0.876. The results indicated that ALB, ARHGDIB, C3, FCN2, and LPA levels might serve as potential biomarkers for cured TB. Our study provides experimental data for establishing objective indicators of cured TB and also proposes potential markers for evaluating the efficacy of anti-TB drugs.

Host Protein Biomarkers Identify Active Tuberculosis in HIV Uninfected and Co-infected Individuals

Biomarkers for active tuberculosis (TB) are urgently needed to improve rapid TB diagnosis. The objective of this study was to identify serum protein expression changes associated with TB but not latent Mycobacterium tuberculosis infection (LTBI), uninfected states, or respiratory diseases other than TB (ORD). Serum samples from 209 HIV uninfected (HIV⁻) and co-infected (HIV⁺) individuals were studied. In the discovery phase samples were analyzed via liquid chromatography and mass spectrometry, and in the verification phase biologically independent samples were analyzed via a multiplex multiple reaction monitoring mass spectrometry (MRM-MS) assay. Compared to LTBI and ORD, host proteins were significantly differentially expressed in TB, and involved in the immune response, tissue repair, and lipid metabolism. Biomarker panels whose composition differed according to HIV status, and consisted of 8 host proteins in HIV⁻ individuals (CD14, SEPP1, SELL, TNXB, LUM, PEPD, QSOX1, COMP, APOC1), or 10 host proteins in HIV⁺ individuals (CD14, SEPP1, PGLYRP2, PFN1, VASN, CPN2, TAGLN2, IGFBP6), respectively, distinguished TB from ORD with excellent accuracy (AUC = 0.96 for HIV⁻ TB, 0.95 for HIV⁺ TB). These results warrant validation in larger studies but provide promise that host protein biomarkers could be the basis for a rapid, blood-based test for TB.

•

Active tuberculosis leads to the differential expression of serum proteins involved in associated host processes.

•

Serum protein expression changes in tuberculosis involve the immune response, tissue repair, and lipid metabolism.

•

Panels of 8–10 host proteins can distinguish active tuberculosis from latent infection, and other respiratory diseases.

Accurate biomarkers for active tuberculosis (TB) are urgently needed to improve rapid diagnosis. Current diagnostics for TB rely on microbiologic or molecular confirmation of M. tuberculosis, and are therefore dependent on a specimen from the site of disease which is not always accessible. This study demonstrates that human host proteins are differentially expressed in TB compared to latent M. tuberculosis infection, or respiratory diseases other than TB. Our data thus provide promise that host proteins have the potential to become the basis of rapid blood tests that do not require a sample from the site of disease.

Comparative Proteomics of Activated THP-1 Cells Infected with Mycobacterium tuberculosis Identifies Putative Clearance Biomarkers for Tuberculosis Treatment

Biomarkers for determining clearance of Mycobacterium tuberculosis (Mtb) infection during anti-tuberculosis therapy or following exposure could facilitate enhanced monitoring and treatment. We screened for biomarkers indicating clearance of Mtb infection in vitro. A comparative proteomic analysis was performed using GeLC MSI/MS. Intracellular and secreted proteomes from activated THP-1 cells infected with the Mtb H37Rv strain (MOI = 1) and treated with isoniazid and rifampicin for 1 day (infection stage) and 5 days (clearance stage) were analyzed. Host proteins associated with early infection (n = 82), clearance (n = 121), sustained in both conditions (n = 34) and suppressed by infection (n = 46) were elucidated. Of the potential clearance markers, SSFA2 and CAECAM18 showed the highest and lowest protein intensities, respectively. A western blot of CAECAM18 validated the LC MS/MS result. For three clearance markers (SSFA2, PARP14 and PSME4), in vivo clinical validation was concordantly reported in previous patient cohorts. A network analysis revealed that clearance markers were enriched amongst four protein interaction networks centered on: (i) CD44/CCND1, (ii) IFN-β1/NF-κB, (iii) TP53/TGF-β and (iv) IFN-γ/CCL2. After infection, proteins associated with proliferation, and recruitment of immune cells appeared to be enriched possibly reflecting recruitment of defense mechanisms. Counteracting proteins (CASP3 vs. Akt and NF-κB vs. TP53) associated with apoptosis regulation and its networks were enriched among the early and sustained infection biomarkers, indicating host-pathogen competition. The BRCA1/2 network was suppressed during infection, suggesting that cell proliferation suppression is a feature of Mtb survival. Our study provides insights into the mechanisms of host-Mtb interaction by comparing the stages of infection clearance. The identified clearance biomarkers may be useful in monitoring tuberculosis treatment.

Comparative proteomic analysis of serum diagnosis patterns of sputum smear-positive pulmonary tuberculosis based on magnetic bead separation and mass spectrometry analysis

A major challenge in pulmonary tuberculosis (TB) control is early and accurate diagnosis of sputum smear negative pulmonary TB (SSN-PTB). The patients with SSN-PTB have to wait for a longer period of time before receiving proper treatment than sputum smear positive pulmonary TB (SSP-PTB) patients due to delay in diagnosis. The purpose of this study is to discover potential serum protein biomarkers for SSN-PTB. Surface-enhanced laser desorption/ionization-time of flight mass spectrometry (SELDI-TOF MS) combined with weak cation exchange (WCX) magnetic beads was used to screen serum samples from SSN-PTB patients (N = 66), SSP-PTB patients (N = 49), and healthy volunteers (N = 80). The serum protein profiles were analyzed with Biomarker Wizard system. A classification model was established using Biomarker Pattern Software (BPS). Fifty-eight protein peaks were identified to exhibit significant differences between SSN-PTB, SSP-PTB and healthy control groups (P < 0.05), among which 6 peaks were found to be down-regulated, while 10 peaks were up-regulated gradually in the healthy control, SSN-PTB, and SSP-PTB groups. Twenty-three discriminating m/z peaks were detected between SSN-PTB patients and healthy controls (P < 0.01, Fold ≥ 1.5). The classification tree combined with three protein peaks (2747.0, 4480.0, and 9410.1 Da) could distinguish SSN-PTB patients from healthy controls with a sensitivity of 83.33% and a specificity of 82.50%. Early diagnosis of SSN-PTB disease is critical in order to reduce morbidity and mortality associated with TB. The study will help to clarify the role of differential proteins in the pathogenesis of TB.

Serum complement C3f and fibrinopeptide A are potential novel diagnostic biomarkers for non-alcoholic fatty liver disease: a study in Qingdao Twins

Aims

To compare the different serum peptidome patterns between twins with and without non-alcoholic fatty liver disease (NAFLD) in order to help understand the pathogenesis of NAFLD and to identify potential diagnostic and therapeutic targets.

Methods

The peptidomics patterns of 63 cases with NAFLD were compared with their twin healthy controls in Qingdao, China. Peptides between 800Da and 3500Da were captured and concentrated using C18 reversed-phase columns, followed by MALDI-TOF mass spectrometry. The sequences of peptides associated with NAFLD were further identified by MALDI-TOF-TOF. Further validation studies were conducted. One hundred additional serum samples were detected by commercially available ELISA kits to calculate the concentrations of complement C3f and fibrinopeptide A, respectively. The differences of these two peptides in the NAFLD and control groups were compared using SPSS 17.0, respectively.

Results

Compared with healthy controls, eleven peaks (861.1, 877.07, 904.5, 1206.57, 1350.64, 1518.7, 1690.9, 1777.94, 2931.29, 3190.4, 3261.4) were up-regulated and 7 peaks (942.44, 1020.47, 1060.06, 1211.7, 1263.63, 1449.76, 2768.3) were down-regulated in the NAFLD group. Two peptides derived from complement C3f and fibrinopeptide A, respectively, had the highest ROC values indistinguishing NAFLD cases from their normal controls. In the validation group, the concentrations of complement C3f and fibrinopeptide A (1466.929±78.306 pg/ml, 4.189±0.326 ng/ml, respevtively) in NAFLD group was higher than in control group (complement C3f 1159.357±99.624 pg/ml, FPA 3.039±0.483 ng/ml; P<0.05).

Conclusions

In this study, we established apeptidomics pattern that could help distinguish NAFLD patients from their twin controls. The differently-regulated peptides identified in our study may be potential diagnostic markers or therapeutic targets for NAFLD.