Novel strategies based on natural products and synthetic derivatives to overcome resistance in Mycobacterium tuberculosis

One of the biggest health challenges of today's world is the emergence of antimicrobial resistance (AMR), which renders conventional therapeutics insufficient and urgently demands the generation of novel antimicrobial strategies. Mycobacterium tuberculosis (M. tuberculosis), the pathogen causing tuberculosis (TB), is among the most successful bacteria producing drug-resistant infections. The versatility of M. tuberculosis allows it to evade traditional anti-TB agents through various acquired and intrinsic mechanisms, rendering TB among the leading causes of infectious disease-related mortality. In this context, researchers worldwide focused on establishing novel approaches to address drug resistance in M. tuberculosis, developing diverse alternative treatments with varying effectiveness and in different testing phases. Overviewing the current progress, this paper aims to briefly present the mechanisms involved in M. tuberculosis drug-resistance, further reviewing in more detail the under-development antibiotics, nanotechnological approaches, and natural therapeutic solutions that promise to overcome current treatment limitations.

Study of drug interaction, mutant frequency and mutant prevention concentration of DFMBT against Mycobacterium tuberculosis H37RV

In the present study 7,7-Dimethyl-4-(4-trifluoromethyl-phenylamino)-2,4,4a,6,7,8-hexahydro-benzo[d] [1,3]thiazin-5-one (DFMBT) was synthesized and evaluated for in vitro activity against Mycobacterium tuberculosis (M.tb) H37RV. Results demonstrated that at 64x MIC, DFMBT completely sterilized the TB culture from day 4 of the incubation whereas at 32 and 16x MIC, it sterilized the TB culture from day 8. The bacterial cultures were completely sterilized by DFMBT at 8x MIC from day 16 of incubation. DFMBT showed 1.5 μg/mL MIC value as compared to the standard anti-tuberculosis drugs using broth macro-dilution method. The MBC value of DFMBT was found to be 6.0 μg/mL whereas for INH, RIF, AMK and LVX the values were found to be 0.312, 0.156, 5.0 and 5.0 μg/mL, respectively. The DFMBT in combination with INH/RIF or AMK showed the ∑FIC value of 0.258, 0.252 and 0.453, respectively indicating synergistic interaction. Moreover, the value of ∑FIC for the combination of DFMBT with LVX was found to be 1.33 suggesting and additive interaction. The post antibiotic effect of DFMBT at 1x and 64x MIC was found to be 29.89 ± 10.12 and 158.75 ± 17.50 h, respectively. The DFMBT showed an MPC value of 150 μg/mL which was intermediate between INH and RIF. In summary, DFMBT exhibits bacteriostatic as well as bactericidal effect on Mycobacterium tuberculosis H37RV. It has synergistic interaction with INH, RIF and AMK anti-TB drugs, descent post antibiotic effect, mutation frequency and mutant prevention concentration. Thus, DFMBT may be developed as an effective agent as anti-TB compound.

Preclinical models to optimize treatment of tuberculous meningitis - A systematic review

Tuberculous meningitis (TBM) is the most devastating form of TB, resulting in death or neurological disability in up to 50% of patients affected. Treatment is similar to that of pulmonary TB, despite poor cerebrospinal fluid (CSF) penetration of the cornerstone anti-TB drug rifampicin. Considering TBM pathology, it is critical that optimal drug concentrations are reached in the meninges, brain and/or the surrounding CSF. These type of data are difficult to collect in TBM patients. This review aims to identify and describe a preclinical model representative for human TBM which can provide the indispensable data needed for future pharmacological characterization and prioritization of new TBM regimens in the clinical setting. We reviewed existing literature on treatment of TBM in preclinical models: only eight articles, all animal studies, could be identified. None of the animal models completely recapitulated human disease and in most of the animal studies key pharmacokinetic data were missing, making the comparison with human exposure and CNS distribution, and the study of pharmacokinetic-pharmacodynamic relationships impossible. Another 18 articles were identified using other bacteria to induce meningitis with treatment including anti-TB drugs (predominantly rifampicin, moxifloxacin and levofloxacin). Of these articles the pharmacokinetics, i.e. plasma exposure and CSF:plasma ratios, of TB drugs in meningitis could be evaluated. Exposures (except for levofloxacin) agreed with human exposures and also most CSF:plasma ratios agreed with ratios in humans. Considering the lack of an ideal preclinical pharmacological TBM model, we suggest a combination of 1. basic physicochemical drug data combined with 2. in vitro pharmacokinetic and efficacy data, 3. an animal model with adequate pharmacokinetic sampling, microdialysis or imaging of drug distribution, all as a base for 4. physiologically based pharmacokinetic (PBPK) modelling to predict response to TB drugs in treatment of TBM.