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

Proteomic Serum Profiling of Holstein Friesian Cows with Different Pathological Forms of Bovine Paratuberculosis Reveals Changes in the Acute-Phase Response and Lipid Metabolism

The lack of sensitive diagnostic methods to detect Mycobacterium avium subsp. paratuberculosis (Map) subclinical infections has hindered the control of paratuberculosis (PTB). The serum proteomic profiles of naturally infected cows presenting focal and diffuse pathological forms of PTB and negative controls (n = 4 per group) were analyzed using TMT-6plex quantitative proteomics. Focal and diffuse are the most frequent pathological forms in subclinical and clinical stages of PTB, respectively. One (focal versus (vs.) control), eight (diffuse vs. control), and four (focal vs. diffuse) differentially abundant (DA) proteins (q-value < 0.05) were identified. Ingenuity pathway analysis of the DA proteins revealed changes in the acute-phase response and lipid metabolism. Six candidate biomarkers were selected for further validation by specific ELISA using serum from animals with focal, multifocal, and diffuse PTB-associated lesions (n = 108) and controls (n = 56). Overall, the trends of the serum expression levels of the selected proteins were consistent with the proteomic results. Alpha-1-acid glycoprotein (ORM1)-based ELISA, insulin-like growth factor-binding protein 2 (IGFBP2)-based ELISA, and the anti-Map ELISA had the best diagnostic performance for detection of animals with focal, multifocal, and diffuse lesions, respectively. Our findings identify potential biomarkers that improve diagnostic sensitivity of PTB and help to elucidate the mechanisms involved in PTB pathogenesis.

Progress in mechanism-based diagnosis and treatment of tuberculosis comorbid with tumor

Tuberculosis (TB) and tumor, with similarities in immune response and pathogenesis, are diseases that are prone to produce autoimmune stress response to the host immune system. With a symbiotic relationship between the two, TB can facilitate the occurrence and development of tumors, while tumor causes TB reactivation. In this review, we systematically sorted out the incidence trends and influencing factors of TB and tumor, focusing on the potential pathogenesis of TB and tumor, to provide a pathway for the co-pathogenesis of TB comorbid with tumor (TCWT). Based on this, we summarized the latest progress in the diagnosis and treatment of TCWT, and provided ideas for further exploration of clinical trials and new drug development of TCWT.

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.

Exploration of key factors in Gingival Crevicular fluids from patients undergoing Periodontally Accelerated Osteogenic Orthodontics (PAOO) using proteome analysis

BACKGROUND

The aims of this study are to explore protein changes in gingival crevicular fluid at different time points after PAOO by proteomics method and to select significant bone metabolization-related biomarkers.

METHODS

This study included 10 adult patients experiencing PAOO. After orthodontic alignment and leveling, the maxillary anterior teeth were treated with PAOO, which is classified as the experimental area. The traditional orthodontic treatment was performed in the mandibular dentition as the control. Gingival crevicular fluid samples were collected at the following time points: the day before the PAOO (T1) and at 1 week, 2 weeks, 1 month, 2 months and 6 months after PAOO (T2, T3, T4, T5 and T6, respectively). The label-free quantitative proteomic assay was used to evaluate the gingival crevicular fluid in PAOO and control areas at time point T1, T2, and T4. Bioinformatics analysis was carried out to categorize proteins based on biological processes, cellular component and molecular function, which is in compliance with gene ontology (GO) standards. The changes of proteins were confirmed by ELISA.

RESULTS

A total of 134 proteins were selected by keywords (Osteoblast markers, Osteoclast markers, Osteoclastogenesis regulating genes and inflammatory marker). 33 of them were statistically different between groups, and 12 were related to bone metabolism. 5 proteins selected by label-free quantitative proteomics were KLF10, SYT7, APOA1, FBN1 and NOTCH1. KLF10 decreased after PAOO, hitting a trough at T4, and then leveled off. SYT7 increased after PAOO, reaching a peak at T3, and then stabilized until T6. APOA1 ascended to a peak at T4 after PAOO, and then remained stable until T6. The FBN1 rose after PAOO, reaching a peak at T4, and then went down slowly. NOTCH1 ascended rapidly in the first two weeks after PAOO and continued its slow growth trend.

CONCLUSION

In this study, protein changes in gingival crevicular fluid were detected by proteomics method, and significant bone metabolization-related proteins were selected. It is speculated that APOA1, FBN1, NOTCH1, SYT7 and KLF10 played key roles in regulating bone metabolic balance and in reversible osteopenia after PAOO, which might be involved in the accelerated tooth movement.

TRIAL REGISTRATION

This study was registered in the Chinese Clinical Trial Registry (Clinical trial registration number: ChiCTR-ONRC-13,004,129) (26/04/2013).

Proteomic-based identification of APCS as candidate protein for diagnosis of patients exhibiting anti-tubercular drug induced liver injury

Traditional markers evaluate anti-tubercular drug-induced liver injury (AT-DILI). However, these markers have certain limitations and studies are in progress to characterize AT-DILI at an early stage. In the present study, 40 patients were categorized and equally distributed into healthy controls, newly diagnosed tuberculosis (TB), TB without hepatotoxicity and TB with hepatotoxicity groups based on their conventional liver function tests. Relative protein quantification was performed on depleted pooled serum samples of each representative group by LC-MS/MS, and validation of shortlisted protein was done by ELISA. Levels of all analysed biochemical parameters showed a statistical increment in the hepatotoxicity group compared to the other three groups, representing AT-DILI. Comparative proteomic analysis between TB with hepatotoxicity versus TB without hepatotoxicity groups highlighted 24 significant differentially expressed proteins, including PROS1, KNG1, CFH, LCAT, APCS and ADIPOQ. Identified proteins were involved in complement activation, triglyceride-rich lipoprotein particle remodelling and pathways comprising complement, coagulation cascades and cholesterol metabolism. Based on functional relevance, the serum amyloid P component (APCS) was shortlisted for validation, and it showed a similar trend as observed in the discovery phase with 100% sensitivity and 87% specificity; however, findings need exploration in larger cohorts.

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.

Latent tuberculosis and computational biology: A less-talked affair

Tuberculosis (TB) is a pervasive and devastating air-borne disease caused by the organisms belonging to the Mycobacterium tuberculosis (Mtb) complex. Currently, it is the global leader in infectious disease-related death in adults. The proclivity of TB to enter the latent state has become a significant impediment to the global effort to eradicate TB. Despite decades of research, latent tuberculosis (LTB) mechanisms remain poorly understood, making it difficult to develop efficient treatment methods. In this review, we seek to shed light on the current understanding of the mechanism of LTB, with an accentuation on the insights gained through computational biology. We have outlined various well-established computational biology components, such as omics, network-based techniques, mathematical modelling, artificial intelligence, and molecular docking, to disclose the crucial facets of LTB. Additionally, we highlighted important tools and software that may be used to conduct a variety of systems biology assessments. Finally, we conclude the article by addressing the possible future directions in this field, which might help a better understanding of LTB progression.

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.

High Procalcitonin, C-Reactive Protein, and α-1 Acid Glycoprotein Levels in Whole Blood Samples Could Help Rapid Discrimination of Active Tuberculosis from Latent Tuberculosis Infection and Healthy Individuals

Tuberculosis (TB) management is important for prompt discrimination of latent TB infection (LTBI) from active TB and proper treatment. Whole blood Interferon-gamma (IFN-γ) release assay (IGRA) is used to diagnose LTBI based on the secretion of IFN-γ by T-cells in the whole blood by using a specific antigen of Mycobacterium tuberculosis. However, the ability of IGRA to distinguish active TB from LTBI is considerably limited. Distinguishing active TB from LTBI is necessary to identify indicators that can be used to effectively manage TB and develop diagnostic methods. In the present study, we used a Luminex multiplex bead array (a bead-based antibody−antigen sandwich method). The whole blood level of acute phase proteins (APPs), such as endoglin (ENG), procalcitonin (PCT), C-reactive protein (CRP), and α1-acid glycoprotein (AGP), in active TB, LTBI, and healthy individuals were analyzed and quantified. The APP test results for the serum and whole blood samples showed that the levels of PCT, CRP, and AGP were significantly increased (p < 0.0500; area under curve = 0.955) in active TB. The level of these markers in the whole blood of active TB, LTBI, and healthy individuals could provide data for effective diagnosis and treatment of TB.

Identification of protein biomarkers in host cerebrospinal fluid for differential diagnosis of tuberculous meningitis and other meningitis

Background and purpose

The diagnosis of tuberculous meningitis (TBM) is difficult due to the lack of sensitive methods. Identification of TBM-specific biomarkers in the cerebrospinal fluid (CSF) may help diagnose and improve our understanding of TBM pathogenesis.

Patients and methods

Of the 112 suspected patients with TBM prospectively enrolled in the study, 32 patients with inconclusive diagnosis, non-infectious meningitis, and long-term treatment with hormones and immunosuppressants were excluded. The expression of 8 proteins in the CSF was analyzed using ELISA in 22 patients with definite TBM, 18 patients with probable TBM, and 40 patients with non-TBM.

Results

Significant differences in the expression of 7 proteins were detected between the TBM and non-TBM groups (P < 0.01). Unsupervised hierarchical clustering (UHC) analysis revealed a disease-specific profile consisting of 7 differentially expressed proteins for TBM diagnosis, with an accuracy of 82.5% (66/80). Logistic regression with forward stepwise analysis indicated that a combination of 3 biomarkers (APOE_APOAI_S100A8) showed a better ability to discriminate TBM from patients with non-TBM [area under the curve (AUC) = 0.916 (95%CI: 0.857–0.976)], with a sensitivity of 95.0% (95%CI: 83.1–99.4%) and a specificity of 77.5% (95%CI: 61.5–89.2%).

Conclusion

Our results confirmed the potential ability of CSF proteins to distinguish TBM from patients with non-TBM and provided a useful panel for the diagnosis of TBM.

Validation of Serotransferrin in the Serum as Candidate Biomarkers for the Diagnosis of Pulmonary Tuberculosis by Label-Free LC/MS

This study aimed to identify secreted protein biomarkers in serum from the label-free LC/MS proteomics of neutrophils in pulmonary tuberculosis (TB) patients for the diagnosis biomarkers of TB label-free LC/MS. The proteomic profiles of neutrophils from 15 active TB patients and 15 healthy controls (HCs) were analyzed using label-free LC/MS. We identified 358 differentially expressed proteins preliminarily, including 279 up-regulated proteins and 79 down-regulated proteins. Thirty-eight differentially expressed secreted proteins involved in the progress of platelet degranulation between TB patients and HCs were focused. Of these, serotransferrin (TRF), alpha-2-macroglobulin (AMG), alpha-1-antitrypsin (AAT), alpha-1-acid glycoprotein 1 (AAG), alpha-1-acid glycoprotein 2 (AGP2), and alpha-1B-glycoprotein (A1BG) were selected for further verification in the serum of additional 134 TB patients and 138 HCs by nephelometry and ELISA in the training set. Statistically significant differences of TRF (P < 0.0001), AAT (P < 0.0001), AAG (P < 0.0001), AGP2 (P < 0.0001), and A1BG (P = 0.0003) were observed. The serum concentration of TRF was down-regulated in TB patients compared with healthy controls, which was coincident with the proteomics results. An additional validation of TRF was performed in an independent cohort of patients with active TB (n = 46), patients with lung cancer (n = 37), 20 HCs, and patients with pneumonia (n = 35) in the test set by nephelometry. The serum expression levels of TRF in the TB patients showed lower levels compared with those in patients with pneumonia (P = 0.0125), lung cancer (P = 0.0005), HCs (P < 0.0001), and the non-TB controls (P < 0.0001). Furthermore, the AUC value of TRF was 0.647 with 90.22% sensitivity and 42.86% specificity in discriminating the TB group from the pneumonia group, 0.702 with 93.48% sensitivity and 47.16% specificity in discriminating the TB group from the lung cancer group, 0.894 with 91.30% sensitivity and 71.62% specificity in discriminating the TB group from all HCs, and 0.792 with 91.30% sensitivity and 58.90% specificity in discriminating the TB group from the non-TB controls. This study obtained the proteomic profiles of neutrophils in the TB patients and HCs, which contribute to a better understanding of the pathogenesis molecules existing in the neutrophils of pulmonary tuberculosis and provide candidate biomarkers for the diagnosis of pulmonary tuberculosis.

Alpha-1-antichymotrypsin as a novel biomarker for diagnosis, prognosis, and therapy prediction in human diseases

The glycoprotein alpha-1-antichymotrypsin (AACT), a serine protease inhibitor, is mainly synthesized in the liver and then secreted into the blood and is involved in the acute phase response, inflammation, and proteolysis. The dysregulation of AACT and its glycosylation levels are associated with tumor progression and recurrence, and could be used as a biomarker for tumor monitoring. In this review, we summarized the expression level, glycosylation modification, and biological characteristics of AACT during inflammation, neurodegenerative or other elderly diseases, and tumorigenesis, as well as, focused on the biological roles of AACT in cancer. The aberrant expression of AACT in cancer might be due to genetic alterations and/or immune by bioinformatics analysis. Moreover, AACT may serve as a diagnostic or prognostic biomarker or therapeutic target in tumors. Furthermore, we found that the expression of AACT was associated with the overall survival of patients with human cancers. Decreased AACT expression was associated with poor survival in patients with liver cancer, increased AACT expression was associated with shorter survival in patients with pancreatic cancer, and decreased AACT expression was associated with shorter survival in patients with early lung cancer. The review confirmed the key roles of AACT in tumorigenesis, suggesting that the glycoprotein AACT may serve as a biomarker for tumor diagnosis and prognosis, and could be a potential therapeutic target for human diseases.

Using Omics to Study Leprosy, Tuberculosis, and Other Mycobacterial Diseases

Mycobacteria are members of the Actinomycetales order, and they are classified into one family, Mycobacteriaceae. More than 20 mycobacterial species cause disease in humans. The Mycobacterium group, called the Mycobacterium tuberculosis complex (MTBC), has nine closely related species that cause tuberculosis in animals and humans. TB can be detected worldwide and one-fourth of the world's population is contaminated with tuberculosis. According to the WHO, about two million dies from it, and more than nine million people are newly infected with TB each year. Mycobacterium tuberculosis (M. tuberculosis) is the most potential causative agent of tuberculosis and prompts enormous mortality and morbidity worldwide due to the incompletely understood pathogenesis of human tuberculosis. Moreover, modern diagnostic approaches for human tuberculosis are inefficient and have many lacks, while MTBC species can modulate host immune response and escape host immune attacks to sustain in the human body. "Multi-omics" strategies such as genomics, transcriptomics, proteomics, metabolomics, and deep sequencing technologies could be a comprehensive strategy to investigate the pathogenesis of mycobacterial species in humans and offer significant discovery to find out biomarkers at the early stage of disease in the host. Thus, in this review, we attempt to understand an overview of the mission of "omics" approaches in mycobacterial pathogenesis, including tuberculosis, leprosy, and other mycobacterial diseases.

Plasma host protein biomarkers correlating with increasing Mycobacterium tuberculosis infection activity prior to tuberculosis diagnosis in people living with HIV

BACKGROUND

Biomarkers correlating with Mycobacterium tuberculosis infection activity/burden in asymptomatic individuals are urgently needed to identify and treat those at highest risk for developing active tuberculosis (TB). Our main objective was to identify plasma host protein biomarkers that change over time prior to developing TB in people living with HIV (PLHIV).

METHODS

Using multiplex MRM-MS, we investigated host protein expressions from 2 years before until time of TB diagnosis in longitudinally collected (every 3-6 months) and stored plasma from PLHIV with incident TB, identified within a South African (SA) and US cohort. We performed temporal trend and discriminant analyses for proteins, and, to assure clinical relevance, we further compared protein levels at TB diagnosis to interferon-gamma release assay (IGRA; SA) or tuberculin-skin test (TST; US) positive and negative cohort subjects without TB. SA and US exploratory data were analyzed separately.

FINDINGS

We identified 15 proteins in the SA (n=30) and 10 in the US (n=24) incident TB subjects which both changed from 2 years prior until time of TB diagnosis after controlling for 10% false discovery rate, and were significantly different at time of TB diagnosis compared to non-TB subjects (p<0.01). Five proteins, CD14, A2GL, NID1, SCTM1, and A1AG1, overlapped between both cohorts. Furthermore, after cross-validation, panels of 5 - 12 proteins were able to predict TB up to two years before diagnosis.

INTERPRETATION

Host proteins can be biomarkers for increasing Mycobacterium tuberculosis infection activity/burden, incipient TB, and predict TB development in PLHIV.

FUNDING

NIH/NIAID AI117927, AI146329, and AI127173 to JMA.

Differential Diagnosis of Latent Tuberculosis Infection and Active Tuberculosis: A Key to a Successful Tuberculosis Control Strategy

As an ancient infectious disease, tuberculosis (TB) is still the leading cause of death from a single infectious agent worldwide. Latent TB infection (LTBI) has been recognized as the largest source of new TB cases and is one of the biggest obstacles to achieving the aim of the End TB Strategy. The latest data indicate that a considerable percentage of the population with LTBI and the lack of differential diagnosis between LTBI and active TB (aTB) may be potential reasons for the high TB morbidity and mortality in countries with high TB burdens. The tuberculin skin test (TST) has been used to diagnose TB for > 100 years, but it fails to distinguish patients with LTBI from those with aTB and people who have received Bacillus Calmette–Guérin vaccination. To overcome the limitations of TST, several new skin tests and interferon-gamma release assays have been developed, such as the Diaskintest, C-Tb skin test, EC-Test, and T-cell spot of the TB assay, QuantiFERON-TB Gold In-Tube, QuantiFERON-TB Gold-Plus, LIAISON QuantiFERON-TB Gold Plus test, and LIOFeron TB/LTBI. However, these methods cannot distinguish LTBI from aTB. To investigate the reasons why all these methods cannot distinguish LTBI from aTB, we have explained the concept and definition of LTBI and expounded on the immunological mechanism of LTBI in this review. In addition, we have outlined the research status, future directions, and challenges of LTBI differential diagnosis, including novel biomarkers derived from Mycobacterium tuberculosis and hosts, new models and algorithms, omics technologies, and microbiota.

Dissecting Host-Pathogen Interactions in TB Using Systems-Based Omic Approaches

Tuberculosis (TB) is a devastating infectious disease that kills over a million people every year. There is an increasing burden of multi drug resistance (MDR) and extensively drug resistance (XDR) TB. New and improved therapies are urgently needed to overcome the limitations of current treatment. The causative agent, Mycobacterium tuberculosis (Mtb) is one of the most successful pathogens that can manipulate host cell environment for adaptation, evading immune defences, virulence, and pathogenesis of TB infection. Host-pathogen interaction is important to establish infection and it involves a complex set of processes. Metabolic cross talk between the host and pathogen is a facet of TB infection and has been an important topic of research where there is growing interest in developing therapies and drugs that target these interactions and metabolism of the pathogen in the host. Mtb scavenges multiple nutrient sources from the host and has adapted its metabolism to survive in the intracellular niche. Advancements in systems-based omic technologies have been successful to unravel host-pathogen interactions in TB. In this review we discuss the application and usefulness of omics in TB research that provides promising interventions for developing anti-TB therapies.

Quantitative proteomics by iTRAQ-PRM based reveals the new characterization for gout

Background

Gout is a common and complex form of immunoreactive arthritis based on hyperuricemia, while the symptoms would turn to remission or even got worse. So, it is hard to early identify whether an asymptomatic hyperuricemia (AHU) patient will be susceptible to get acute gout attack and it is also hard to predict the process of gout remission to flare. Here, we report that the plasma proteins profile can distinguish among acute gout (AG), remission of gout (RG), AHU patients, and healthy controls.

Methods

We established an isobaric tags for relative and absolute quantification (iTRAQ) and parallel reaction monitoring (PRM) based method to measure the plasma proteins for AG group (n = 8), RG group (n = 7), AHU group (n = 7) and healthy controls (n = 8).

Results

Eleven differentially expressed proteins such as Histone H2A, Histone H2B, Thrombospondin-1 (THBS1), Myeloperoxidase (MPO), Complement C2, Complement component C8 beta chain (C8B), Alpha-1-acid glycoprotein 1 (ORM1), Inter-alpha-trypsin inhibitor heavy chain H4 (ITIH4), Carbonic anhydrase 1 (CA1), Serum albumin (ALB) and Multimerin-1 (MMRN1) were identified. Histone H2A, Histone H2B and THBS1 might be the strongest influential regulator to maintain the balance and stability of the gout process. The complement and coagulation cascades is one of the main functional pathways in the mechanism of gout process.

Conclusions

Histone H2A, Histone H2B and THBS1 are potential candidate genes for novel biomarkers in discriminating gout attack from AHU or RG, providing new theoretical insights for the prognosis, treatment, and management of gout process.

Trial registration

This study is not a clinical trial.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12953-021-00180-0.

Revisiting tuberculosis screening: An insight to complementary diagnosis and prospective molecular approaches for the recognition of the dormant TB infection in human and cattle hosts

Tuberculosis (TB) is defined as a chronic infection in both human and cattle hosts and many subclinical cases remain undetected. After the pathogen is inhaled by a host, phagocyted bacilli can persist inside macrophages surviving intracellularly. Hosts develop granulomatous lesions in the lungs or lymph nodes, limiting infection. However, bacilli become persister cells. Immunological diagnosis of TB is performed basically by routine tuberculin skin test (TST), and in some cases, by ancillary interferon-gamma release assay (IGRA). The concept of human latent TB infection (LTBI) by M. tuberculosis is recognized in cohorts without symptoms by routine clinical diagnostic tests, and nowadays IGRA tests are used to confirm LTBI with either active or latent specific antigens of M. tuberculosis. On the other hand, dormant infection in cattle by M. bovis has not been described by TST or IGRA testing as complications occur by cross-reactive immune responses to homolog antigens of environmental mycobacteria or a false-negative test by anergic states of a wained bovine immunity, evidencing the need for deciphering more specific biomarkers by new-generation platforms of analysis for detection of M. bovis dormant infection. The study and description of bovine latent TB infection (boLTBI) would permit the recognition of hidden animal infection with an increase in the sensitivity of routine tests for an accurate estimation of infected dairy cattle. Evidence of immunological and experimental analysis of LTBI should be taken into account to improve the study and the description of the still neglected boLTBI.

Combined analysis of whole blood interferon gamma release assay and complete blood count analysis for rapid discrimination of active tuberculosis and latent tuberculosis infection

Tuberculosis (TB), which is caused by Mycobacterium tuberculosis (MTB), is a serious infectious disease with high infection and mortality rates and is a public health problem around the world. According to the World Health Organization (WHO) report, one-third of the world's population is latently infected with MTB, and 5 to 10% of those with latent TB infection (LTBI) have the potential to develop active TB once in their lifetime. Therefore, TB management for promptly distinguishing LTBI from active TB and for proper treatment is important. LTBI is currently diagnosed using the tuberculin skin test (TST) and interferon gamma (IFN-γ) release assay (IGRA). However, this test is substantially limited by its inability to distinguish active TB from LTBI. It is necessary to discover indicators that can be used for effective TB management and to develop diagnostic methods. In the present study, we used IGRA and complete blood count (CBC) analysis for discrimination of active TB, LTBI, and healthy control groups. The results showed that the number of WBC was significantly increased in the group with active TB (p < 0.0100) and level of hemoglobin (Hb) was significantly decreased (p < 0.0010) in the CBC than those of the healthy control and LTBI groups. In the WBC differential count, the number of neutrophils and monocytes were increased (p < 0.0010) in active TB group, where as those of lymphocytes were significantly decreased (p < 0.0100) in active TB group compared healthy control group. Results verified that the levels of total WBC, Hb, neutrophils, lymphocytes and monocytes were statistically significant (p < 0.0500) and the AUC was approximately 0.8613. In addition, receiver operating characteristic (ROC) curve analysis was performed to confirm the clinical usefulness between active TB and healthy control groups. In conclusion, based on these data demonstrated that the usefulness of these potential indicators for differential diagnosis, according to the result can be provided for effective diagnosis and treatment by comparing the expression patterns of the markers in the whole blood of the active TB, LTBI, and healthy control groups. Furthermore, this study needs to investigate a larger number of clinical specimens later to develop biomarkers according to the state of infection with MTB such as LTBI and active TB, as well as after treatment.

Human tuberculosis and Mycobacterium tuberculosis complex: A review on genetic diversity, pathogenesis and omics approaches in host biomarkers discovery

Mycobacterium tuberculosis complex (MTBC) refers to a group of mycobacteria encompassing nine members of closely related species that causes tuberculosis in animals and humans. Among the nine members, Mycobacterium tuberculosis (M. tuberculosis) remains the main causative agent for human tuberculosis that results in high mortality and morbidity globally. In general, MTBC species are low in diversity but exhibit distinctive biological differences and phenotypes among different MTBC lineages. MTBC species are likely to have evolved from a common ancestor through insertions/deletions processes resulting in species speciation with different degrees of pathogenicity. The pathogenesis of human tuberculosis is complex and remains poorly understood. It involves multi-interactions or evolutionary co-options between host factors and bacterial determinants for survival of the MTBC. Granuloma formation as a protection or survival mechanism in hosts by MTBC remains controversial. Additionally, MTBC species are capable of modulating host immune response and have adopted several mechanisms to evade from host immune attack in order to survive in humans. On the other hand, current diagnostic tools for human tuberculosis are inadequate and have several shortcomings. Numerous studies have suggested the potential of host biomarkers in early diagnosis of tuberculosis, in disease differentiation and in treatment monitoring. "Multi-omics" approaches provide holistic views to dissect the association of MTBC species with humans and offer great advantages in host biomarkers discovery. Thus, in this review, we seek to understand how the genetic variations in MTBC lead to species speciation with different pathogenicity. Furthermore, we also discuss how the host and bacterial players contribute to the pathogenesis of human tuberculosis. Lastly, we provide an overview of the journey of "omics" approaches in host biomarkers discovery in human tuberculosis and provide some interesting insights on the challenges and directions of "omics" approaches in host biomarkers innovation and clinical implementation.

Comprehensive plasma proteomic profiling reveals biomarkers for active tuberculosis

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

Changes in T-lymphocyte subsets and risk factors in human immunodeficiency virus-negative patients with active tuberculosis

Purpose

Immune function imbalance is closely associated with the occurrence and development of infectious diseases. We studied the characteristics of changes in T-lymphocyte subsets and their risk factors in HIV-negative patients with active tuberculosis (ATB).

Methods

T-lymphocyte subsets in 275 HIV-negative ATB patients were quantitatively analyzed and compared with an Mycobacteriumtuberculosis-free control group. Single-factor and multifactor analyses of clinical and laboratory characteristics of patients were also conducted.

Results

In ATB patients, CD4 and CD8 T-cell counts decreased, and the levels were positively interrelated (r = 0.655, P < 0.0001). After 4 weeks of antituberculosis treatment, CD4 and CD8 T-cell counts increased significantly but remained lower than in the control group. CD4 and CD8 cell counts were negatively associated with the extent of lesions detected in the chest by computed tomography (all P < 0.05). Although not reflected in the CD4/CD8 ratio, CD4 and CD8 cell counts differed between drug-resistant TB patients and drug-susceptible TB patients (P = 0.030). The multivariate analysis showed prealbumin, alpha-1 globulin, body mass index, and platelet count were independent risk factors for decreased CD4 cell count (all P < 0.05), while age and platelet count were independent risk factors for decreased CD8 cell count (all P < 0.05).

Conclusion

CD4 and CD8 T-cell counts showed the evident value in predicting ATB severity. An increase in the CD4/CD8 ratio may be a critical clue of drug resistance in ATB. Although the factors influencing CD4 and CD8 are not identical, our results indicated the importance of serum protein and platelets to ATB patients’ immune function.

Electronic supplementary material

The online version of this article (10.1007/s15010-020-01451-2) contains supplementary material, which is available to authorized users.

Label-Free Quantitative Proteomics Identifies Novel Biomarkers for Distinguishing Tuberculosis Pleural Effusion from Malignant Pleural Effusion

PURPOSE

To identify potential protein biomarkers for distinguishing tuberculosis plural effusion (TBPE) from malignant plural effusion (MPE).

EXPERIMENTAL DESIGN

Five independent samples from each group (TBPE and MPE) are enrolled for label-free quantitative proteomics analyses. The differentially expressed proteins are validated by western blot and ELISA. Logistic regression analysis is used to obtain the optimal diagnostic model.

RESULTS

In total, 14 proteins with significant difference are identified between TBPE and MPE. Seven differentially expressed proteins are validated using western blot, and the expression patterns of these seven proteins are similar with those in proteomics analysis. Statistically significant differences in four proteins (AGP1, ORM2, C9, and SERPING1) are noted between TBPE and MPE in the training set (n = 230). Logistic regression analysis shows the combination of AGP1-ORM2-C9 presents a sensitivity of 73.0% (92/126) and specificity of 89.4% (93/104) in discriminating TBPE from MPE. Additional validation is performed to evaluate the diagnostic model in an independent blind testing set (n = 80), and yielded a sensitivity of 74.4% (32/43) and specificity of 91.9% (34/37) in discriminating TBPE from MPE.

CONCLUSION

The study uncovers the proteomic profiles of TBPE and MPE, and provides new potential diagnostic biomarkers for distinguishing TBPE from MPE.

The E-Cadherin Cleavage Associated to Pathogenic Bacteria Infections Can Favor Bacterial Invasion and Transmigration, Dysregulation of the Immune Response and Cancer Induction in Humans

Once bound to the epithelium, pathogenic bacteria have to cross epithelial barriers to invade their human host. In order to achieve this goal, they have to destroy the adherens junctions insured by cell adhesion molecules (CAM), such as E-cadherin (E-cad). The invasive bacteria use more or less sophisticated mechanisms aimed to deregulate CAM genes expression or to modulate the cell-surface expression of CAM proteins, which are otherwise rigorously regulated by a molecular crosstalk essential for homeostasis. Apart from the repression of CAM genes, a drastic decrease in adhesion molecules on human epithelial cells can be obtained by induction of eukaryotic endoproteases named sheddases or through synthesis of their own (prokaryotic) sheddases. Cleavage of CAM by sheddases results in the release of soluble forms of CAM. The overexpression of soluble CAM in body fluids can trigger inflammation and pro-carcinogenic programming leading to tumor induction and metastasis. In addition, the reduction of the surface expression of E-cad on epithelia could be accompanied by an alteration of the anti-bacterial and anti-tumoral immune responses. This immune response dysfunction is likely to occur through the deregulation of immune cells homing, which is controlled at the level of E-cad interaction by surface molecules α_E integrin (CD103) and lectin receptor KLRG1. In this review, we highlight the central role of CAM cell-surface expression during pathogenic microbial invasion, with a particular focus on bacterial-induced cleavage of E-cad. We revisit herein the rapidly growing body of evidence indicating that high levels of soluble E-cad (sE-cad) in patients’ sera could serve as biomarker of bacterial-induced diseases.

Genome-Wide miRNA Analysis Identifies Potential Biomarkers in Distinguishing Tuberculous and Viral Meningitis

Tuberculous meningitis (TBM) is the most common and severe form of central nervous system tuberculosis. Due to the non-specific clinical presentation and lack of efficient diagnosis methods, it is difficult to discriminate TBM from other frequent types of meningitis, especially viral meningitis (VM). In order to identify the potential biomarkers for discriminating TBM and VM and to reveal the different pathophysiological processes between TBM and VM, a genome-wide miRNA screening of PBMCs from TBM, VM, and healthy controls (HCs) using microarray assay was performed (12 samples). Twenty-eight differentially expressed miRNAs were identified between TBM and VM, and 11 differentially expressed miRNAs were identified between TBM and HCs. The 6 overlapping miRNAs detected in both TBM vs. VM and TBM vs. HCs were verified by qPCR analysis and showed a 100% consistent expression patterns with that in microarray test. Statistically significant differences of 4 miRNAs (miR-126-3p, miR-130a-3p, miR-151a-3p, and miR-199a-5p) were further confirmed in TBM compared with VM and HCs in independent PBMCs sample set (n = 96, P < 0.01). Three of which were also showed significantly different between TBM and VM in CSF samples (n = 70, P < 0.05). The receiver operating characteristic curve (ROC) analysis showed that the area under the ROC curve (AUC) of these 4 miRNAs in PBMCs were more than 0.70 in discriminating TBM from VM. Combination of these 4 miRNAs could achieve better discriminative capacity [AUC = 0.893 (0.788-0.957)], with a sensitivity of 90.6% (75.0-98.0%), and a specificity of 86.7% (69.3-96.2%). Additional validation was performed to evaluate the diagnostic panel in another independent sample set (n = 49), which yielded a sensitivity of 81.8% (9/11), and specificity of 90.0% (9/10) in distinguishing TBM and VM, and a sensitivity of 81.8% (9/11), and a specificity of 84.6% (11/13) in discriminating TBM from other non-TBM patients. This study uncovered the miRNA profiles of TBM and VM patients, which can facilitate better understanding of the pathogenesis involved in these two diseases and identified 4 novel miRNAs in distinguishing TBM and VM.

Tuberculosis in the 21th century: Current status of diagnostic methods

Tuberculosis is an infectious bacterial disease with a high mortality rate worldwide constituting a serious public health problem. The diagnostic methods commonly used by health professionals are slow and expensive and the results may take about sixty days which will cause a delay in administrating the most proper treatment to the patient, as well as increase health care costs and infection transmission possibility. Patients infected simultaneously with human immunodeficiency virus and Mycobacterium tuberculosis are a constant and worrying challenge for the scientific community which will research and develop new methods of diagnosis, new drugs and new therapies. Nowadays there are new tuberculosis diagnosis methods and some of which are already in clinical trial phases. These methods have high sensitivity, but do not replace the microbiological examination for isolation and culture of Mycobacterium spp. However, in clinical practice, microbiological, imaging, clinical and epidemiological data integration provide the best diagnosis and treatment possible. Consequently, throughout this paper, the different methods of diagnosis of human tuberculosis with its advantages and disadvantages will be covered, describing new omics and ultra-fast methods to increase knowledge and obtain a rapid diagnosis of tuberculosis.