Immune Biomarkers for Diagnosis and Treatment Monitoring of Tuberculosis: Current Developments and Future Prospects

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

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

Loss of T cells expressing CD27 at the site of active tuberculosis - A prospective diagnostic study

The lack of a rapid and reliable diagnostic test for active tuberculosis is still a burden to the control of the infection. The accumulation of Mycobacterium tuberculosis (MTB)-specific CD4⁺ T cells at the site of infection and the increase of MTB-specific CD27^- cells seem to be characteristic for active tuberculosis. We evaluated CD27 expression of non-stimulated T cells at the site of infection compared to peripheral blood of seventy-two patients (n = 72) presenting with symptoms of active MTB-infection. Twenty patients (n = 20, 27.8%) were actually confirmed to have active tuberculosis. Overall, a significant increase of terminally differentiated CD27^- CD4⁺ T cells at the site of disease was noted when compared to peripheral blood (<0.001). However, the loss of CD27 at the site of disease was not restricted to active tuberculosis (p = 0.253). The CD27 expression profile of tuberculosis patients was only discriminative to patients with malignancy.

Pediatric Tuberculosis: The Impact of "Omics" on Diagnostics Development

Tuberculosis (TB) is a major public health concern for all ages. However, the disease presents a larger challenge in pediatric populations, partially owing to the lack of reliable diagnostic standards for the early identification of infection. Currently, there are no biomarkers that have been clinically validated for use in pediatric TB diagnosis. Identification and validation of biomarkers could provide critical information on prognosis of disease, and response to treatment. In this review, we discuss how the “omics” approach has influenced biomarker discovery and the advancement of a next generation rapid point-of-care diagnostic for TB, with special emphasis on pediatric disease. Limitations of current published studies and the barriers to their implementation into the field will be thoroughly reviewed within this article in hopes of highlighting future avenues and needs for combating the problem of pediatric tuberculosis.

Genetic Diversity in Mycobacterium tuberculosis Clinical Isolates and Resulting Outcomes of Tuberculosis Infection and Disease

Tuberculosis claims more human lives than any other bacterial infectious disease and represents a clear and present danger to global health as new tools for vaccination, treatment, and interruption of transmission have been slow to emerge. Additionally, tuberculosis presents with notable clinical heterogeneity, which complicates diagnosis, treatment, and the establishment of nonrelapsing cure. How this heterogeneity is driven by the diversity ofclinical isolates of the causative agent, Mycobacterium tuberculosis, has recently garnered attention. Herein, we review advances in the understanding of how naturally occurring variation in clinical isolates affects transmissibility, pathogenesis, immune modulation, and drug resistance. We also summarize how specific changes in transcriptional responses can modulate infection or disease outcome, together with strain-specific effects on gene essentiality. Further understanding of how this diversity of M. tuberculosis isolates affects disease and treatment outcomes will enable the development of more effective therapeutic options and vaccines for this dreaded disease.

Gene network in pulmonary tuberculosis based on bioinformatic analysis

BACKGROUND

Pulmonary tuberculosis (PTB) is one of the serious infectious diseases worldwide; however, the gene network involved in the host response remain largely unclear.

METHODS

This study integrated two cohorts profile datasets GSE34608 and GSE83456 to elucidate the potential gene network and signaling pathways in PTB. Differentially expressed genes (DEGs) were obtained for Gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis using Metascape database. Protein-Protein Interaction (PPI) network of DEGs was constructed by the online database the Search Tool for the Retrieval of Interacting Genes (STRING). Modules were identified by the plug-in APP Molecular Complex Detection (MCODE) in Cytoscape. GO and KEGG pathway of Module 1 were further analyzed by STRING. Hub genes were selected for further expression validation in dataset GSE19439. The gene expression level was also investigated in the dataset GSE31348 to display the change pattern during the PTB treatment.

RESULTS

Totally, 180 shared DEGs were identified from two datasets. Gene function and KEGG pathway enrichment revealed that DEGs mainly enriched in defense response to other organism, response to bacterium, myeloid leukocyte activation, cytokine production, etc. Seven modules were clustered based on PPI network. Module 1 contained 35 genes related to cytokine associated functions, among which 14 genes, including chemokine receptors, interferon-induced proteins and Toll-like receptors, were identified as hub genes. Expression levels of the hub genes were validated with a third dataset GSE19439. The signature of this core gene network showed significant response to Mycobacterium tuberculosis (Mtb) infection, and correlated with the gene network pattern during anti-PTB therapy.

CONCLUSIONS

Our study unveils the coordination of causal genes during PTB infection, and provides a promising gene panel for PTB diagnosis. As major regulators of the host immune response to Mtb infection, the 14 hub genes are also potential molecular targets for developing PTB drugs.

Identification of candidate host serum and saliva biomarkers for a better diagnosis of active and latent tuberculosis infection

In our work, we aim to identify new candidate host biomarkers to discriminate between active TB patients (n = 28), latent infection (LTBI; n = 27) and uninfected (NoTBI; n = 42) individuals. For that, active TB patients and their contacts were recruited that donated serum and saliva samples. A multiplex assay was performed to study the concentration of different cytokines, chemokines and growth factors. Proteins with significant differences between groups were selected and logistic regression and the area under the ROC curve (AUC) was used to assess the diagnostic accuracy. The best marker combinations that discriminate active TB from NoTBI contacts were [IP-10 + IL-7] in serum and [Fractalkine + IP-10 + IL-1α + VEGF] in saliva. Best discrimination between active TB and LTBI was achieved using [IP-10 + BCA-1] in serum (AUC = 0.83) and IP-10 in saliva (p = 0.0007; AUC = 0.78). The levels of TNFα (p = 0.003; AUC = 0.73) in serum and the combination of [Fractalkine+IL-12p40] (AUC = 0.83) in saliva, were able to differentiate between NoTBI and LTBI contacts. In conclusion, different individual and combined protein markers could help to discriminate between active TB and both uninfected and latently-infected contacts. The most promising ones include [IP-10 + IL-7], [IP-10 + BCA-1] and TNFα in serum and [Fractalkine + IP-10 + IL-1α + VEGF], IP-10 and [Fractalkine+IL-12p40] in saliva.

Proteomic analysis of infected primary human leucocytes revealed PSTK as potential treatment-monitoring marker for active and latent tuberculosis

Markers for monitoring clearance of Mycobacterium tuberculosis (Mtb) infection during anti-TB drug treatment could facilitate management of tuberculosis (TB) treatment, but are lacking. We aimed to screen for Mtb clearance markers from in-vitro-infected leucocytes and to evaluate these markers in followed-up active TB (ATB) patients and latent TB (LTBI) cases after anti-TB drug treatment. Extracellular proteins from primary leucocytes infected with each of the Mtb lineages (East-Asian, Indo-Oceanic, Euro-American and the laboratory strain H37Rv) were screened as possible clearance markers. Leucocytes infected with Staphylococcus aureus acted as controls. The proteomic analysis was performed using GeLC-MS/MS. Several quantitative and qualitative candidate clearance markers were found. These proteins were suppressed during the infection stage of all Mtb lineages and re-expressed after bacillary clearance. PSTK, FKBP8 and MGMT were common clearance markers among the four Mtb lineages in our model. Only PSTK was a potential clearance marker based on western blot validation analysis from culture supernatants. The PSTK marker was further validated with western blot analysis using serum samples (n = 6) from ATB patients and LTBI cases during anti-TB drug treatment, and from healthy controls (n = 3). Time-dependent increase of PSTK was found both in ATB and LTBI patients during the course of anti-TB drug treatment, but not in healthy controls. We have demonstrated that PSTK is a potential treatment-monitoring marker for active and latent TB.