Plakinamine P, A Steroidal Alkaloid with Bactericidal Activity against Mycobacterium tuberculosis.

Tuberculosis is the leading cause of death due to infectious disease worldwide. There is an urgent need for more effective compounds against this pathogen to control the disease. Investigation of the anti-mycobacterial activity of a deep-water sponge of the genus Plakina revealed the presence of a new steroidal alkaloid of the plakinamine class, which we have given the common name plakinamine P. Its structure is most similar to plakinamine L, which also has an acyclic side chain. Careful dissection of the nuclear magnetic resonance data, collected in multiple solvents, suggests that the dimethyl amino group at the 3 position is in an equatorial rather than axial position unlike previously reported plakinamines. Plakinamine P was bactericidal against M. tuberculosis, and exhibited moderate activity against other mycobacterial pathogens, such as M. abscessus and M. avium. Furthermore, it had low toxicity against J774 macrophages, yielding a selectivity index (SI, or IC50/MIC) of 8.4. In conclusion, this work provides a promising scaffold to the tuberculosis drug discovery pipeline. Future work to determine the molecular target of this compound may reveal a pathway essential for M. tuberculosis survival during infection.

Flux Balance Analysis with Objective Function Defined by Proteomics Data-Metabolism of Mycobacterium tuberculosis Exposed to Mefloquine.

We present a study of the metabolism of the Mycobacterium tuberculosis after exposure to antibiotics using proteomics data and flux balance analysis (FBA). The use of FBA to study prokaryotic organisms is well-established and allows insights into the metabolic pathways chosen by the organisms under different environmental conditions. To apply FBA a specific objective function must be selected that represents the metabolic goal of the organism. FBA estimates the metabolism of the cell by linear programming constrained by the stoichiometry of the reactions in an in silico metabolic model of the organism. It is assumed that the metabolism of the organism works towards the specified objective function. A common objective is the maximization of biomass. However, this goal is not suitable for situations when the bacterium is exposed to antibiotics, as the goal of organisms in these cases is survival and not necessarily optimal growth. In this paper we propose a new approach for defining the FBA objective function in studies when the bacterium is under stress. The function is defined based on protein expression data. The proposed methodology is applied to the case when the bacterium is exposed to the drug mefloquine, but can be easily extended to other organisms, conditions or drugs. We compare our method with an alternative method that uses experimental data for adjusting flux constraints. We perform comparisons in terms of essential enzymes and agreement using enzyme abundances. Results indicate that using proteomics data to define FBA objective functions yields less essential reactions with zero flux and lower error rates in prediction accuracy. With flux variability analysis we observe that overall variability due to alternate optima is reduced with the incorporation of proteomics data. We believe that incorporating proteomics data in the objective function used in FBA may help obtain metabolic flux representations that better support experimentally observed features.