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  1. Abu Bakar MH, Sarmidi MR
    Mol Biosyst, 2017 Aug 22;13(9):1838-1853.
    PMID: 28726959 DOI: 10.1039/c7mb00333a
    Accumulating evidence implicates mitochondrial dysfunction-induced insulin resistance in skeletal muscle as the root cause for the greatest hallmarks of type 2 diabetes (T2D). However, the identification of specific metabolite-based markers linked to mitochondrial dysfunction in T2D has not been adequately addressed. Therefore, we sought to identify the markers-based metabolomics for mitochondrial dysfunction associated with T2D. First, a cellular disease model was established using human myotubes treated with antimycin A, an oxidative phosphorylation inhibitor. Non-targeted metabolomic profiling of intracellular-defined metabolites on the cultured myotubes with mitochondrial dysfunction was then determined. Further, a targeted MS-based metabolic profiling of fasting blood plasma from normal (n = 32) and T2D (n = 37) subjects in a cross-sectional study was verified. Multinomial logical regression analyses for defining the top 5% of the metabolites within a 95% group were employed to determine the differentiating metabolites. The myotubes with mitochondrial dysfunction exhibited insulin resistance, oxidative stress and inflammation with impaired insulin signalling activities. Four metabolic pathways were found to be strongly associated with mitochondrial dysfunction in the cultured myotubes. Metabolites derived from these pathways were validated in an independent pilot investigation of the fasting blood plasma of healthy and diseased subjects. Targeted metabolic analysis of the fasting blood plasma with specific baseline adjustment revealed 245 significant features based on orthogonal partial least square discriminant analysis (PLS-DA) with a p-value < 0.05. Among these features, 20 significant metabolites comprised primarily of branched chain and aromatic amino acids, glutamine, aminobutyric acid, hydroxyisobutyric acid, pyroglutamic acid, acylcarnitine species (acetylcarnitine, propionylcarnitine, dodecenoylcarnitine, tetradecenoylcarnitine hexadecadienoylcarnitine and oleylcarnitine), free fatty acids (palmitate, arachidonate, stearate and linoleate) and sphingomyelin (d18:2/16:0) were identified as predictive markers for mitochondrial dysfunction in T2D subjects. The current study illustrates how cellular metabolites provide potential signatures associated with the biochemical changes in the dysregulated body metabolism of diseased subjects. Our finding yields additional insights into the identification of robust biomarkers for T2D associated with mitochondrial dysfunction in cultured myotubes.
  2. Abu Bakar MH, Sarmidi MR, Cheng KK, Ali Khan A, Suan CL, Zaman Huri H, et al.
    Mol Biosyst, 2015 Jul;11(7):1742-74.
    PMID: 25919044 DOI: 10.1039/c5mb00158g
    Metabolomic studies on obesity and type 2 diabetes mellitus have led to a number of mechanistic insights into biomarker discovery and comprehension of disease progression at metabolic levels. This article reviews a series of metabolomic studies carried out in previous and recent years on obesity and type 2 diabetes, which have shown potential metabolic biomarkers for further evaluation of the diseases. Literature including journals and books from Web of Science, Pubmed and related databases reporting on the metabolomics in these particular disorders are reviewed. We herein discuss the potential of reported metabolic biomarkers for a novel understanding of disease processes. These biomarkers include fatty acids, TCA cycle intermediates, carbohydrates, amino acids, choline and bile acids. The biological activities and aetiological pathways of metabolites of interest in driving these intricate processes are explained. The data from various publications supported metabolomics as an effective strategy in the identification of novel biomarkers for obesity and type 2 diabetes. Accelerating interest in the perspective of metabolomics to complement other fields in systems biology towards the in-depth understanding of the molecular mechanisms underlying the diseases is also well appreciated. In conclusion, metabolomics can be used as one of the alternative approaches in biomarker discovery and the novel understanding of pathophysiological mechanisms in obesity and type 2 diabetes. It can be foreseen that there will be an increasing research interest to combine metabolomics with other omics platforms towards the establishment of detailed mechanistic evidence associated with the disease processes.
  3. Yap IK, Kho MT, Lim SH, Ismail NH, Yam WK, Chong CW
    Mol Biosyst, 2015 Jan;11(1):297-306.
    PMID: 25382376 DOI: 10.1039/c4mb00463a
    Understanding the basal gut bacterial community structure and the host metabolic composition is pivotal for the interpretation of laboratory treatments designed to answer questions pertinent to host-microbe interactions. In this study, we report for the first time the underlying gut microbiota and systemic metabolic composition in BALB/c mice during the acclimatisation period. Our results showed that stress levels were reduced in the first three days of the study when the animals were subjected to repetitive handling daily but the stress levels were increased when handling was carried out at lower frequencies (weekly). We also observed a strong influence of stress on the host metabolism and commensal compositional variability. In addition, temporal biological compartmental variations in the responses were observed. Based on these results, we suggest that consistency in the frequency and duration of laboratory handling is crucial in murine models to minimise the impact of stress levels on the commensal and host metabolism dynamics. Furthermore, caution is advised in consideration of the temporal delay effect when integrating metagenomics and metabonomics data across different biological matrices (i.e. faeces and urine).
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