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

CAPRISA, 2015.Abstract available in pdf

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

Metabolomic analysis of Mycobacterium tuberculosis reveals metabolic profiles for identification of drug-resistant tuberculosis

Abstract The detection of pre-extensively (pre-XDR) and extensively drug-resistant tuberculosis (XDR-TB) is challenging. Drug-susceptibility tests for some anti-TB drugs, especially ethambutol (ETH) and ethionamide (ETO), are problematic due to overlapping thresholds to differentiate between susceptible and resistant phenotypes. We aimed to identify possible metabolomic markers to detect Mycobacterium tuberculosis (Mtb) strains causing pre-XDR and XDR-TB. The metabolic patterns of ETH- and ETO-resistant Mtb isolates were also investigated. Metabolomics of 150 Mtb isolates (54 pre-XDR, 63 XDR-TB and 33 pan-susceptible; pan-S) were investigated. Metabolomics of ETH and ETO phenotypically resistant subgroups were analyzed using UHPLC-ESI-QTOF-MS/MS. Orthogonal partial least-squares discriminant analysis revealed distinct separation in all pairwise comparisons among groups. Two metabolites (meso-hydroxyheme and itaconic anhydride) were able to differentiate the pre-XDR and XDR-TB groups from the pan-S group with 100% sensitivity and 100% specificity. In comparisons of the ETH and ETO phenotypically resistant subsets, sets of increased (ETH = 15, ETO = 7) and decreased (ETH = 1, ETO = 6) metabolites specific for the resistance phenotype of each drug were found. We demonstrated the potential for metabolomics of Mtb to differentiate among types of DR-TB as well as between isolates that were phenotypically resistant to ETO and ETH. Thus, metabolomics might be further applied for DR-TB diagnosis and patient management

Network analyses of protein clearance markers.

<p>The majority of clearance markers belong to one of four networks. Network A centers on CD44 and CCND1 and consists of genes involved in the cell cycle and RNA post-transcriptional modification (<b>Figure A</b>). Network B centers on IFNβ1, NF-κB, ERK1 and MAPK and includes several additional genes involved in antimicrobial responses, such as TLR8 (<b>Figure B</b>). Network C centers on TP53, and TGF-β and is associated with the cell cycle and with proliferation (<b>Figure C</b>). Network D centers on CCL2, CCL4 and IFN-γ, which are associated with cell activation and migration and which play a central role in tuberculosis (<b>Figure D</b>). Solid lines denote a direct protein-protein interaction, such as binding; dotted lines denote other relationships, such as co-expression, regulation and activation, phosphorylation or cleavage relationships. The intensity of protein expression is denoted in shades of red proportionate to the level of expression.</p

Validation of proteomic analysis by western blot using a monoclonal antibody to CAECAM 18.

<p>CAECAM was uniquely detected in all 3 independent experiments.</p

General work flow.

<p>THP-1 cells were activated using 50 nM PMA and infected with <i>Mtb</i> H37Rv. The infected macrophages were treated with 3 μg of INH and 9 μg of RIF for 1 day (Day 1 Infected) (<i>Mtb</i> remaining in the cells, <i>i</i>.<i>e</i>., infection stage) and 5 days (Day 5 Infected) (no <i>Mtb</i> remaining in the cells 2 days after clearance, <i>i</i>.<i>e</i>., clearance stage). <i>Mtb</i> clearance was confirmed by CFU determination at 3 days post-infection. THP-1 cells treated with drugs (without <i>Mtb</i>) for 1 day (Day 1 Uninfected) and 5 days (Day 5 Uninfected) post-infection were used as background controls. The culture supernatant and cell lysates were collected. CFU counts were performed to confirm the clearance stage of <i>Mtb</i> in intracellular and extracellular compartments from all experiments. Three biological replicates of the experiments were performed. The proteomes were analyzed by GeLC MS/MS. A western blot was performed to validate the proteins identified by GeLC MS/MS. The candidate clearance markers were compared to markers from patients treated with anti-TB therapy from previous studies.</p

Classification of peptides according to qualitative or quantitative differences between activated THP-1 cells infected with <i>M</i>. <i>tuberculosis</i> H37Rv or left uninfected and sampled at Day 1 or Day 5.

<p>Classification of peptides according to qualitative or quantitative differences between activated THP-1 cells infected with <i>M</i>. <i>tuberculosis</i> H37Rv or left uninfected and sampled at Day 1 or Day 5.</p