Gerhard Koekemoer

A metabolomics investigation of a hyper- and hypo-virulent phenotype of Beijing lineage M. tuberculosis

Despite a number investigations using rapid sequencing and comparative genomic techniques, attempting to characterise the phenomenon of varying degrees of virulence within the Mycobacterium tuberculosis species, the underlying causes for this still remain largely unexplained. The Beijing lineage of M. tuberculosis has received much attention due to a reported increased pathogenicity and global dissemination. In order to better understand these varying states of virulence, a GCxGC-TOFMS metabolomics research approach was used to compare the varying metabolomes of a hyper- and hypo-virulent Beijing strain of M. tuberculosis, and subsequently identify those metabolite markers differing between these strains. Multi- and univariate statistical analysis of the analysed metabolome data was used to identify those metabolites contributing most to the differences seen between the two sample groups. A general decrease in various carbohydrates, amino acids and lipids associated with cell wall structure and function, were detected in the hyper-virulent Beijing strain, comparatively. Additionally, components of mycothiol metabolism, virulence protein formation and energy production in mycobacteria, were also seen to differ when comparing the two groups. This metabolomics investigation is the first to identify the metabolite markers associated with an increased state of virulence, indicating increased metabolic activity, increased growth/replication rates, increased cell wall synthesis and an altered antioxidant mechanism, all of which would contribute to this organisms increased pathogenicity and survival ability.

Assessing the DNA methylation status of single cells with the comet assay.

The comet assay (single cell gel electrophoresis) is a cost-effective, sensitive, and simple technique that is traditionally used for analyzing and quantifying DNA damage in individual cells. The aim of this study was to determine whether the comet assay could be modified to detect changes in the levels of DNA methylation in single cells. We used the difference in methylation sensitivity of the isoschizomeric restriction endonucleases HpaII and MspI to demonstrate the feasibility of the comet assay to measure the global DNA methylation level of individual cells. The results were verified with the well-established cytosine extension assay. We were able to show variations in DNA methylation after treatment of cultured cells with 5-azacytidine and succinylacetone, an accumulating metabolite in human tyrosinemia type I.

Hereditary tyrosinemia type 1 metabolites impair DNA excision repair pathways

Hereditary tyrosinemia type 1 is an autosomal recessive metabolic disorder, which is caused by a defective fumarylacetoacetate hydrolase enzyme, and consequently metabolites such as succinylacetone and p-hydroxyphenylpyruvate accumulate. We used a modified comet assay to determine the effect of these metabolites on base- and nucleotide excision repair pathways. Our results indicate that the metabolites affected the repair mechanisms differently, since the metabolites had a bigger detrimental effect on BER than on NER.

Concurrent class analysis identifies discriminatory variables from metabolomics data on isovaleric acidemia

Metabolomics data are typically complex and high dimensional. Multivariate dimension-reducing techniques have thus been developed for analysing metabolomics data to disclose underlying relationships, with principal component analysis (PCA) as the technique mostly applied. Despite its widespread use in metabolomics, PCA has shortcomings that limit its applicability. Several approaches have been made to overcome these limitations and we describe an advanced disjoint PCA (DPCA) model, termed concurrent class analysis and abbreviated as CONCA. CONCA is a new model, and is unique in linking DPCA models to a traditional PCA model. This is accomplished by restructuring the input data matrix, applying DPCA group models to the restructured data, and combining the DPCA models in order to replicate a traditional PCA. We applied the CONCA model to a metabolomics data set on isovaleric acidaemia (IVA), a rare inherited metabolic disorder. The outcome showed that three of the variables with high discrimination value identified through the CONCA analysis are prominent organic acid biomarkers for IVA. Moreover, three further minor metabolites associated with the disease, and two as a consequence of treatment, were likewise identified as important discriminatory variables. The benefit of the CONCA model thus is its ability to disclose information concerning each individual group and to identify the variables important in discrimination (VIDs) which are also responsible for group separation.

Transformation Kernel Density Estimation With Applications

One of the main objectives of this article is to derive efficient nonparametric estimators for an unknown density fX. It is well known that the ordinary kernel density estimator has, despite several good properties, some serious drawbacks. For example, it suffers from boundary bias and it also exhibits spurious bumps in the tails. We propose a semiparametric transformation kernel density estimator to overcome these defects. It is based on a new semiparametric transformation function that transforms data to normality. A generalized bandwidth adaptation procedure is also developed. It is found that the newly proposed semiparametric transformation kernel density estimator performs well for unimodal, low, and high kurtosis densities. Moreover, it detects and estimates densities with excessive curvature (e.g., modes and valleys) more effectively than existing procedures. In conclusion, practical examples based on real-life data are presented.

Cardiometabolic markers to identify cardiovascular disease risk in HIV-infected black South Africans

BACKGROUND The prevalence of HIV is the highest in sub-Saharan Africa; South Africa (SA) is one of the most affected countries with the highest number of adults living with HIV infection in the world. Besides the traditional risk factors for cardiovascular disease (CVD) in the general population, in people living with HIV there are specific factors - chronic inflammation, metabolic changes associated with the infection, therapy, and lipodystrophy - that potentially increase the risk for developing CVD. OBJECTIVE This study proposes a screening discriminant model to identify the most important risk factors for the development of CVD in a cohort of 140 HIV-infected black Africans from the North West Province, SA. METHODS Anthropometric measures, systolic blood pressure, diastolic blood pressure and the carotid-dorsalis pedis pulse wave velocity were determined. Blood was analysed to determine the levels of total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol, triglycerides (TGs) and glucose. Partial least squares discriminant analysis was performed as a supervised pattern recognition method. Independent Students t-tests were further employed to compare the means of risk factors on interval scales; for comparison of categorical risk factors between groups, chi2 tests were used. RESULTS A TG:HDL-C ratio > or = 1.49, TC:HDL-C ratio > or = 5.4 and an HDL-C level < or = 0.76 mmol/l indicated CVD risk in this cohort of patients living with HIV. CONCLUSION The results have important health implications for black Africans living with HIV as these lipid levels may be a useful indicator of the risk for CVD.

Silent ischemia is associated with subclinical atherosclerosis in African males: the sympathetic activity and ambulatory blood pressure in Africans study

Silent myocardial ischemia is a predictor of subclinical atherosclerosis driven by increased cardiovascular risk markers, although still unknown in Africans. The aim of this study was to assess if cardiovascular risk markers will be associated with subclinical atherosclerosis. African men were stratified into (i) 24-hour silent ischemia (SI, n = 38) and (ii) without (nSI, n = 40) groups. Ambulatory blood pressure (BP), SI, 12-lead resting electrocardiogram, ultrasound carotid intima-media thickness (CIMT) measurements, and fasting blood samples were obtained. Above-normal cardiovascular risk markers, that is, glucose level, heart rate, BP, and CIMT, were evident in men with SI. Hypertension prevalence was 89% in the African SI men as opposed to 64% in the nSI men. Regression analyses revealed that only SI events in SI men explained 35% (95% confidence interval [CI]: 0.22;0.52) of the variance in CIMT, while in all African men it explained 29% (95% CI: 0.19;0.39). In conclusion, SI was associated with structural vascular disease in African men. This could imply that SI is not necessarily driven by hypertension in African men but through other possible mechanisms such as increased sympathetic nervous system activity.