Proteomic Analysis of M. tuberculosis

M. tuberculosis has the ability to become latent and persist for decades without initiating symptoms of active tuberculosis. To better understand the mechanism behind this adaptive ability, the Peter Andersen and Ida Rosenkrands groups performed a proteomic analysis of M. tuberculosis.¹

The analysis of these groups focused on the secretome of M. tuberculosis. The secretome plays an important role in host-pathogen interactions including the initiation of immune response through the production of T-cell antigens. Additionally, the study of the secretome may lead to the discovery of diagnostic biomarkers.^2,3

For this study, bacterial cultures of M. tuberculosis H37Rv were obtained from frozen seed stocks and grown for seven days to log phase. Cultures were pelleted and washed. A portion of the cultures were incubated for 6 weeks under nutrient-starvation conditions as described previously with the use of Sauton medium instead of 7H9 medium, which contains protein additions that could interfere with the proteomic analysis.^4,5 Cultures grown to log phase were used as controls.

Three log-phase and three starvation-culture filtrates were fractionated using SDS-PAGE and in-gel digestion and separated by reverse-phase chromatography. Peptides were followed by analysis of the mixture using a LTQ-FT hybrid mass spectrometer (Thermo Scientific). The Peptide Prophet algorithm was used to validate protein identifications and were only accepted if a 95% probability was reached.

12,399 unique peptides were derived from 1362 proteins. LTQ-FT files were analyzed using the Proteome Discoverer 1.3.0.339 data analysis package (Thermo Scientific). 1176 proteins were identified in the nutrient starved filtrates. Comparison of nutrient starvation samples and log growth samples using spectral counting and the Beta-Binominal statistical analysis test revealed 438 proteins differed in abundance ( >1.5-fold difference, p < 0.01) Furthermore, 230 proteins were elevated and 208 proteins were less abundant.

Decreased proteins were representative of metabolism and respiration pathways, while increased proteins were broadly identified as involved in virulence, detoxification and adaptation, and lipid metabolism.

Gene Ontology aided the characterization of protein trends. This analysis included proteins found in all three log-phase or starvation samples. Gene ontology for identified proteins was extracted from the uniprot database.⁶

2D DIGE was performed, validating the proteomic analysis by label-free LC-MS/MS. Twenty-six proteins were identified by both methods; however, there were seven proteins found to be decreased in 2D DIGE, including DnaK (Rv0350), Fba (Rv0363c), GroEL2 (Rv0440), FadA3 (Rv1074c), PrcA (Rv2109c), aRv2258c, and NdkA (Rv2445c). These proteins were not statistically significant using LC-MS/MS. Furthermore, there were four proteins that did not agree: LpdC (Rv0462), Fum (Rv1098c), CysK1 (Rv2334), and the hypothetical protein, Rv2716. The reasoning behind these disagreements is likely due to the ability of 2D DIGE to detect variants of the same protein species, including those with different posttranslational modifications, whereas LC-MS/MS forms an average of the proteins identified.

References

1. Albrethsen, J., et al. (2013) ‘Proteomic profiling of the Mycobacterium tuberculosis identifies nutrient starvation responsive toxin-antitoxin systems‘, Molecular and Cellular Proteomics, published online Jan 23, 2013. doi: 10.1074/mcp.M112.018846

2. Andersen, P. (1994) ‘Effective vaccination of mice against Mycobacterium tuberculosis infection with a soluble mixture of secreted mycobacterial proteins‘, Infection and Immunity, 62 (6), (pp. 2536-2544)

3. Andersen, P., et al. (2000) ‘Specific immune-based diagnosis of tuberculosis‘, Lancet 356 (9235), (pp. 1099-1104)

4. Loebel, R.O., Shorr, E., and Richardson, H.B. (1933) ‘The Influence of Adverse Conditions upon the Respiratory Metabolism and Growth of Human Tubercle Bacilli‘, Journal of Bacteriology, 26 (2), (pp. 167-200)

5. Betts, J. C., et al. (2002) ‘Evaluation of a nutrient starvation model of Mycobacterium tuberculosis persistence by gene and protein expression profiling‘, Molecular Microbiology, 43 (3), (pp. 717-731)

6. Uniprot database: http://www.uniprot.org/