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

Abstract

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.

Fig 1. General work flow.

THP-1 cells were activated using 50 nM PMA and infected with Mtb H37Rv. The infected macrophages were treated with 3 μg of INH and 9 μg of RIF for 1 day (Day 1 Infected) (Mtb remaining in the cells, i.e., infection stage) and 5 days (Day 5 Infected) (no Mtb remaining in the cells 2 days after clearance, i.e., clearance stage). Mtb clearance was confirmed by CFU determination at 3 days post-infection. THP-1 cells treated with drugs (without Mtb) 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 Mtb 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.

Fig 2. Proteome comparisons among conditions.

(Figure A) Venn diagram of the proteome showing the number of unique peptides detected according to each condition. The number in brackets refers to the number of unique identifiable proteins to which the peptides match in the database. Consideration according to presence/absence defined the qualitative markers, see also Table 1. (Figure B) Heatmap depicting the level of expression (absent in blue, lowest in light pink, and highest in burgundy according to the key at the bottom left) across conditions as demarcated at the upper part of the heatmap. Protein names, or peptide names if no match was found for a peptide, are shown to the left, where the symbols ‘<>‘ or ‘><‘ denote detection in the secreted or intracellular proteome, respectively. Colored bars at the right of the heatmap correspond to the classification into seven classes according to qualitative or quantitative criteria. (Figure C) Examples of peptides from each class (denoted by color) of marker are shown with the expression level according to the condition. Each replicate is denoted by a point, and boxes show the median (central line), IQR (outer box) and range (whiskers) in the expression level. The y-axis refers to the protein to which the peptide maps.

Fig 3. Network analyses of protein clearance markers.

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 (Figure A). Network B centers on IFNβ1, NF-κB, ERK1 and MAPK and includes several additional genes involved in antimicrobial responses, such as TLR8 (Figure B). Network C centers on TP53, and TGF-β and is associated with the cell cycle and with proliferation (Figure C). 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 (Figure D). 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.

Fig 4. Validation of proteomic analysis by western blot using a monoclonal antibody to CAECAM 18.

CAECAM was uniquely detected in all 3 independent experiments.