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TB or not TB? Improving the understanding and diagnosis of tuberculosis through metabolomics
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...metabolomics has resulted in an exponential increase in the
number of newly identified tuberculosis biomarkers, which has not
only shed light on previously unknown disease mechanisms, but could
potentially contribute to all aspects of tuberculosis clinical care...
New insights into the survival mechanisms of rifampicin-resistant Mycobacterium tuberculosis
No full textObjectives: Rifampicin is considered the most important antibiotic for treating TB, but unfortunately Mycobacterium tuberculosis is rapidly developing resistance to this drug. Despite the fervent research efforts to date, TB is still a major global problem, and hence new approaches are necessary to better characterize this disease, especially the mechanisms relating to drug resistance.
Methods: Using a two-dimensional GC-coupled time-of-flight MS metabolomics approach, the most important metabolite markers characterizing rifampicin-resistant M. tuberculosis were identified.
Results: The metabolite markers identified indicate instability in rifampicin-resistant M. tuberculosis mRNA, induced by the rpoB mutation. This results in a total depletion of aconitic acid, due to a shift in aconitase functionality towards mRNA binding and stability, and away from energy production and growth, and a subsequent increased dependency on alternative energy sources, fatty acids in particular. A number of other metabolic changes were observed, confirming an additional survival response for maintaining/remodelling the cell wall.
Conclusions: This study shows the value of a metabolomics approach to biological investigations in a quest to better understand disease-causing organisms and their tolerance to existing medications, which would in the future undoubtedly assist in the development of alternative treatment approache
An altered mycobacterium tuberculosis metabolome induced by katG mutations resulting in isoniazid resistance
Get PDFThe most common form of drug resistance found in tuberculosis (TB)-positive clinical samples is monoresistance to isoniazid.
Various genomics and proteomics studies to date have investigated this phenomenon; however, the exact mechanisms relating to
how this occurs, as well as the implications of this on the TB-causing organisms function and structure, are only partly understood.
Considering this, we followed a metabolomics research approach to identify potential new metabolic pathways and metabolite
markers, which when interpreted in context would give a holistic explanation for many of the phenotypic characteristics
associated with a katG mutation and the resulting isoniazid resistance in Mycobacterium tuberculosis. In order to achieve these
objectives, gas chromatography-time of flight mass spectrometry (GCxGC-TOFMS)-generated metabolite profiles from two isoniazid-
resistant strains were compared to a wild-type parent strain. Principal component analyses showed clear differentiation
between the groups, and the metabolites best describing the separation between these groups were identified. It is clear from the
data that due to a mutation in the katG gene encoding catalase, the isoniazid-resistant strains experience increased susceptibility
to oxidative stress and have consequently adapted to this by upregulating the synthesis of a number of compounds involved in (i)
increased uptake and use of alkanes and fatty acids as a source of carbon and energy and (ii) the synthesis of a number of compounds
directly involved in reducing oxidative stress, including an ascorbic acid degradation pathway, which to date hasn’t been
proposed to exist in these organism
Food antioxidant capacity and its use in food selection
Get PDFIn the current issue of the Journal, Louwrens and co-workers determine the per capita South African daily dietary total antioxidant capacity (TAC)1 using published data by Nel and Steyn (2002) which summarises the food consumption studies conducted in SA from 1983–2000. The data reflect the daily per capita intake of food and beverages as based on those foods and beverages consumed by more than 3% of South African adults of all ages and ethnic groups.2 Using this dietary data, they calculate the Total Antioxidant Capacity (TAC) using the Oxygen Radical Absorbance Capacity (ORAC) values for the closest matching foods as reported by the United States Department of Agriculture (compiled for typical foods available in the US).3 For foods not found in the USDA (US Department of Agriculture) ORAC database and for which no equivalents could be found, ORAC analyses were done (for the hydrophilic chain breaking antioxidant capacity only). The authors report TAC values ranging from as low as 7 635 µmoles Trolox Equivalents (TE) (for the Lebowa study) to 15 934 µmoles TE (for the CORIS study) and an average of 11 433 µmoles TE for all the 11 studies summarised. The authors conclude that a TAC of 20 513 µmoles TE per person per day is the recommended TAC objective (based on a diet compiled using the five-a-day concept) and that diet choices should be made with this in mind. Due to the fact that the estimated South African dietary TAC, as calculated from the secondary data published by Nel and Steyn, is 11 433 µmoles TE, the authors further conclude that the average estimated adult South African dietary TAC is only about half of what it should be.
Effects of dieatry onion (Allium cepa L.) in a rodent model of high-fat diet streptozotocin-induced diabetes
No full textBackground/Aims: The present study was conducted to investigate the effects of two dietary doses of freeze-dried onion powder on diabetes-related symptoms in a high-fat (HF) diet streptozotocin (STZ)-induced diabetes rat model. Methods: Five-week-old male Sprague-Dawley rats were fed a HF diet for 2 weeks and then randomly divided into 4 groups as follows: HF control (HFC), diabetic control (DBC), onion low (ONL; 0.5%) and onion high (ONH; 2.0%). Diabetes was induced by an intraperitoneal injection of STZ (40 mg/kg body weight) in all groups except the HFC group. Results: After 4 weeks on the experimental diets, fasting blood glucose levels for both onion-fed groups were higher than in the DBC and HFC groups, albeit only significantly so (p < 0.05) in the ONL group. Serum insulin concentrations and insulin resistance were dose-dependently increased (however, not significantly so) in the onion-fed groups compared to the DBC group. Pancreatic β-cell function and liver glycogen concentrations were nonsignificantly higher in the DBC and ONH groups compared to the ONL group. Additionally, the ONH group had significantly higher lipid concentrations (except for high-density lipoprotein cholesterol) compared to all other groups. The ONL group showed a similar hyperlipidemic trend, however to a lesser extent, with only triglycerides significantly differing from those of the DBC and HFC groups. Conclusion: The results suggest that the HF onion diet may increase insulin secretion and consequently insulin resistance in a dose-dependent manner, resulting in a worsened hyperglycemic and hyperlipidemic diabetic state. We conclude that higher dietary fat may impair the antidiabetic effects of dietary onion intake as has been previously reported
A metabolomics approach to characterise and identify various Mycobacterium species
No full textWe investigated the potential use of gas chromatography mass spectrometry (GC–MS), in combination with multivariate statistical data processing, to build a model for the classification of various tuberculosis (TB) causing, and non-TB Mycobacterium species, on the basis of their characteristic metabolite profiles. A modified Bligh–Dyer extraction procedure was used to extract lipid components from Mycobacterium tuberculosis, Mycobacterium avium, Mycobacterium bovis, and Mycobacterium kansasii cultures. Principle component analyses (PCA) of the GC–MS generated data showed a clear differentiation between all the Mycobacterium species tested. Subsequently, the 12 compounds best describing the variation between the sample groups were identified as potential metabolite markers, using PCA and partial least-squares discriminant analysis (PLS-DA). These metabolite markers were then used to build a discriminant classification model based on Bayes' theorem, in conjunction with multivariate kernel density estimation. This model subsequently correctly classified 2 “unknown” samples for each of the Mycobacterium species analysed, with probabilities ranging from 72 to 100%. Furthermore, Mycobacterium species classification could be achieved in less than 16 h, and the detection limit for this approach was 1 × 103 bacteria mL− 1. This study proves the capacity of a GC–MS, metabolomics pattern recognition approach for its possible use in TB diagnostics and disease characterisation
A comparison of two extraction methods for differentiating and characterising various Mycobacterium species and Pseudomonas aeruginosa using GC-MS metabolomics
Get PDFWe investigated the capacity of a metabolomics research approach to characterise and differentiate between various infectious Mycobacterium species and Pseudomonas aeruginosa, and compared two extraction procedures; 1) extracting the fatty acid metabolome, and 2) extracting the total metabolome, prior to gas chromatography mass spectrometry (GC-MS) and statistical data analyses. Both extraction procedures, as part of a metabolomics study, were able to successfully differentiate between all bacterial groups investigated. The total metabolome extraction method proved the better of the two methods due to its comparative: simplicity; speed (taking less than 4 h), repeatability; extraction capacity (considering the range of compounds extracted and their relative concentrations), and; ability to extract those compounds which allow a better differentiation and characterisation of the investigated sample groups
Experimental rodent models of type 2 diabetes: A review
No full textDue to the high prevalence of diabetes worldwide, extensive research is still being performed to develop new antidiabetic agents and determine their mechanisms of action. Consequently, a number of diabetic animal models have been developed and improved over the years, of which rodent models are the most thoroughly described. These rodent models can be classified into two broad categories: 1) genetically induced spontaneous diabetes models; and 2) experimentally induced nonspontaneous diabetes models. The popularity of using experimentally induced nonspontaneous models for diabetes research over that of the genetically induced spontaneous models is due to their comparatively lower cost, ease of diabetes induction, ease of maintenance and wider availability. The various experimentally induced type 2 diabetes (T2D) rodent models developed over the last 30-plus years for both routine pharmacological screening and mechanistic diabetes-linked research trials include: adult streptozotocin (STZ)/alloxan rat models, neonatal STZ/alloxan models, partial pancreatectomy models, long-term high-fat (HF) diet-fed models, HF diet-fed STZ models, nicotinamide/STZ models, intrauterine growth retardation (IUGR) models, the STZ-induced progressive diabetic model and monosodium glutamate (MSG)-induced model. The use of these models, however, is not without limitations. A T2D model should ideally portray an identical biochemical blood profile and pathogenesis to T2D in humans. Hence, this review will comparatively evaluate experimentally induced rodent T2D models considering the above-mentioned criteria, in order to guide diabetes research groups to more accurately select the most appropriate models given their specific research requirement
Novel insights into the pharmacometabonomics of first-line tuberculosis drugs relating to metabolism, mechanism of action and drug-resistance
No full textThe World Health Organization recommends the directly observed therapy short-course (DOTS) regimen, a combination of four first-line antibiotics (isoniazid, rifampicin, pyrazinamide and ethambutol), for the treatment of active pulmonary tuberculosis (TB). However, despite the fact that this treatment regimen is commonly used worldwide, the metabolism and anti-bacterial mechanisms of these drugs are not yet fully understood. This lack of information ultimately contributes to the poor patient compliance and the subsequent treatment failure and post treatment relapse seen in some TB patients. Pharmacometabonomics, the latest addition to the omics research domain, focuses on the identification of drug-induced metabolome variations. The observed metabolite changes can be used to better understand drug metabolism, drug action and drug-resistance mechanisms. In this review, we summarize the generally known biological mechanisms of the first-line TB drugs included in the DOTS program, and we additionally elaborate on the contribution that pharmacometabonomics has made to the expansion of this knowledg
Can metabolomics improve tuberculosis diagnostics?
No full textWith one third of the global human population
suffering from tuberculosis (TB) in 2001, the disease was
officially declared a worldwide emergency by the World
Health Organization. Since then this disease has grown to
epidemic proportions and the recent emergence of drug
resistance, the rising incidence of HIV/TB co-infection,
and the inability of the currently used vaccination, diagnostic
and treatment protocols to control this pandemic, has
made TB a research topic inviting urgent attention. The
implementation of metabolomics, a relatively new research
approach, which is defined as the study of all the small
molecular weight compounds or metabolites in a system or
sample, using highly sensitive and specific analytical
techniques, shows promise in the quest to eradicate this
disease. In this context, we describe here the advantages
and limitations of the currently available TB diagnostic
techniques, and the role that metabolomics has played in
the identification of new biomarkers, not only leading to
innovative approaches for TB diagnostics, but also to a
better understanding of the intra-host changes induced by
Mycobacterium tuberculosis infection and active diseas
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