Quantitative analysis of the bioenergetics of Mycobacterium tuberculosis along with Glyoxylate cycle as a drug target under inhibition of enzymes using Petri net.

The bacteria Mycobacterium tuberculosis is responsible for the infectious disease Tuberculosis. Targeting the tubercule bacteria is an important challenge in developing the antimycobacterials. The glyoxylate cycle is considered as a potential target for the development of anti-tuberculosis agents, due to its absence in the humans. Humans only possess tricarboxylic acid cycle, while this cycle gets connected to glyoxylate cycle in microbes. Glyoxylate cycle is essential to the Mycobacterium for its growth and survival. Due to this reason, it is considered as a potential therapeutic target for the development of anti-tuberculosis agents. Here, we explore the effect on the behavior of the tricarboxylic acid cycle, glyoxylate cycle and their integrated pathway with the bioenergetics of the Mycobacterium, under the inhibition of key glyoxylate cycle enzymes using Continuous Petri net. Continuous Petri net is a special Petri net used to perform the quantitative analysis of the networks. We first study the tricarboxylic acid cycle and glyoxylate cycle of the tubercule bacteria by simulating its Continuous Petri net model under different scenarios. Both the cycles are then integrated with the bioenergetics of the bacteria and the integrated pathway is again simulated under different conditions. The simulation graphs show the metabolic consequences of inhibiting the key glyoxylate cycle enzymes and adding the uncouplers on the individual as well as integrated pathway. The uncouplers that inhibit the synthesis of adenosine triphosphate, play an important role as anti-mycobacterials. The simulation study done here validates the proposed Continuous Petri net model as compared with the experimental outcomes and also explains the consequences of the enzyme inhibition on the biochemical reactions involved in the metabolic pathways of the mycobacterium.

Multi-drug resistant Pseudomonas aeruginosa keratitis and its effective treatment with topical colistimethate.

The purpose was to evaluate the clinical outcome in multi-drug resistant Pseudomonas aeruginosa (MDR-PA) bacterial keratitis and report the successful use of an alternative antibiotic, topical colistimethate in some of them. The medical records of 12 culture-proven MDR-PA keratitis patients, all exhibiting in vitro resistance by Kirby-Bauer disc diffusion method to ≥ three classes of routinely used topical antibiotics were reviewed. Eight patients were treated with 0.3% ciprofloxacin or ofloxacin, 1 patient with 5% imipenem/cilastatin and 3 patients with 1.6% colistimethate. The outcomes in 8 eyes treated with only fluoroquinolones were evisceration in 4 eyes, therapeutic corneal graft in 1 eye, phthisis bulbi in 1 eye, and no improvement in 2 eyes. The eye treated with imipenem/cilastin required a therapeutic corneal graft. All the three eyes treated with 1.6% colistimethate healed. Colistimethate may prove to be an effective alternative antibiotic in the treatment of MDR-PA keratitis.

Coupling calcium dynamics and mitochondrial bioenergetic: an in silico study to simulate cardiomyocyte dysfunction.

The coupling of intracellular Ca(2+) dynamics with mitochondrial bioenergetic is crucial for the functioning of cardiomyocytes both in healthy and disease conditions. The pathophysiological signature of the Cardiomyocyte Dysfunction (CD) is commonly related to decreased ATP production due to mitochondrial functional impairment and to an increased mitochondrial calcium content ([Ca(2+)]m). These features advanced the therapeutic approaches which aim to reduce [Ca(2+)]m. But whether [Ca(2+)]m overload is the pathological trigger for CD or a physiological consequence, remained controversial. We addressed this issue in silico and showed that [Ca(2+)]m might not directly cause CD. Through model parameter recalibration, we demonstrated how mitochondria cope up with functionally impaired processes and consequently accumulate calcium. A strong coupling of the [Ca(2+)]m oscillations with the ATP synthesis rate ensures robust calcium cycling and avoids CD. We suggested a cardioprotective role of the mitochondrial calcium uniporter and predicted that a mitochondrial sodium calcium exchanger could be a potential therapeutic target to restore the normal functioning of the cardiomyocyte.

Molecular signatures for obesity and associated disorders identified through partial least square regression models.

BACKGROUND: Obesity is now a worldwide epidemic disease and poses a major risk for diet related diseases like type 2 diabetes, cardiovascular disease, stroke and fatty liver among others. In the present study we employed the murine model of diet-induced obesity to determine the early, tissue-specific, gene expression signatures that characterized progression to obesity and type 2 diabetes. RESULTS: We used the C57BL/6 J mouse which is known as a counterpart for diet-induced human diabetes and obesity model. Our initial experiments involved two groups of mice, one on normal diet (ND) and the other on high-fat and high-sucrose (HFHSD). The later were then further separated into subgroups that either received no additional treatment, or were treated with different doses of the Ayurvedic formulation KAL-1. At different time points (week3, week6, week9, week12, week15 and week18) eight different tissues were isolated from mice being fed on different diet compositions. These tissues were used to extract gene-expression data through microarray experiment. Simultaneously, we also measured different body parameters like body weight, blood Glucose level and cytokines profile (anti-inflammatory & pro-inflammatory) at each time point for all the groups. Using partial least square discriminant analysis (PLS-DA) method we identified gene-expression signatures that predict physiological parameters like blood glucose levels, body weight and the balance of pro- versus anti-inflammatory cytokines. The resulting models successfully predicted diet-induced changes in body weight and blood glucose levels, although the predictive power for cytokines profiles was relatively poor. In the former two instances, however, we could exploit the models to further extract the early gene-expression signatures that accurately predict the onset of diabetes and obesity. These extracted genes allowed definition of the regulatory network involved in progression of disease. CONCLUSION: We identified the early gene-expression signature for the onset of obesity and type 2 diabetes. Further analysis of this data suggests that some of these genes could be used as potential biomarkers for these two disease-states.