Metabolomic investigations into human apocrine sweat secretions

Human axillary odour is formed by the action of Corynebacteria or Stephyloccui bacteria on odourless axilla sections. Several groups have identified axillary odorants, including 3-methyl-2-hexanoic acid (3M2H) and 3-hydroxy-3-methyl-hexenoic acid (HMHA), and how they are pre-formed and bound to amino acid conjugates. However, there is currently a lack of LC-MS methodologies and no reported NMR methods, that are required to further identify the non-volatile constituents, which would provide further information to allow understanding of the underlying physiological biochemistry of malodour. This work has incorporated a three-pronged approach. Firstly, a global strategy, through the use of NMR and LC-MS, provided a complementary unbiased overview of the metabolite composition. Metabolites were identified based on acquired standards, accurate mass and through the use of in-house or online databases. Furthermore, spectra of biological samples are inherently complex, thus, requiring a multivariate data analysis (MVDA) approach to extract the latent chemical information in the data. Secondly, semi-targeted LC-MS/MS methodologies has been used to identify metabolites with a common structural core (i.e. odour precursors) and provide structural information for the reliable identification of known and unknown metabolites. Finally, a targeted LC-MSIMS method provided an increase in specificity and sensitivity to accurately quantify known metabolites of interest (odour precursors). Initially, all methodologies were developed through the use of either an artificial sweat matrix (global strategy) or through the use of synthetic standards (semi-targeted or targeted strategy). The sample complexity was then increased by applying the methodologies to an ASG5 apocrine cell line, in order to provide further knowledge into apocrine cell metabolism and to identify whether there could be any potential male or female differences due to differences in circulating hormones. Changes in the cell metabolism were identified, and both the NMR and LC-MS data could differentiate between control, tamoxifen- and β-estradiol-treated. However, it is difficult to attribute these changes to specific pathways, as these hormones or the vehicle used (ethanol) are likely to produce a ripple effect across the cell's metabolism. Nonetheless, NMR spectroscopy quantified 25 metabolites with lactate being the most abundant at 19.1 mM, while HILIC-MS could detect a range of lipids, nucleotides, amino acids, fatty acids and vitamins. The methodologies were then applied to human apocrine sweat collected from six volunteers across five days. NMR spectroscopy was able to identify 25 and quantify 19 metabolites, with lactate being the most abundant at 13.2 mM. LC-MS/MS readily identified 12 amino acid conjugates with HMHA being the most abundant. Furthermore, a possible 20 unidentified conjugates were detected (LC-MSIMS semi-targeted methodologies) as well as putatively identifying 473 metabolites (LC-MS global methodologies). MVDA techniques such as principal component analysis (PCA) illustrated that intra-individual variation was greater than inter-individual variation, as well as secretions from both the left and right arm being consistent with one another. Moreover, MVDA illustrated the complementary nature of both NMR and MS, as the data acquired with the two types of instrumentation showed the same trends, even though these trends were based on different subsets of metabolites. The work presented herein, has successfully used a number of analytical technologies to investigate metabolite content of human apocrine sweat. It has been shown that a number of complementary techniques and multivariate analysis can provide a valuable insight into the underlying physiology of malodour. This work was funded by BBSRC and Unilever (Port Sunlight, UK)

Metabolomic investigations into human apocrine sweat secretions

Human axillary odour is formed by the action of Corynebacteria or Stephyloccui bacteria on odourless axilla sections. Several groups have identified axillary odorants, including 3-methyl-2-hexanoic acid (3M2H) and 3-hydroxy-3-methyl-hexenoic acid (HMHA), and how they are pre-formed and bound to amino acid conjugates. However, there is currently a lack of LC-MS methodologies and no reported NMR methods, that are required to further identify the non-volatile constituents, which would provide further information to allow understanding of the underlying physiological biochemistry of malodour. This work has incorporated a three-pronged approach. Firstly, a global strategy, through the use of NMR and LC-MS, provided a complementary unbiased overview of the metabolite composition. Metabolites were identified based on acquired standards, accurate mass and through the use of in-house or online databases. Furthermore, spectra of biological samples are inherently complex, thus, requiring a multivariate data analysis (MVDA) approach to extract the latent chemical information in the data. Secondly, semi-targeted LC-MS/MS methodologies has been used to identify metabolites with a common structural core (i.e. odour precursors) and provide structural information for the reliable identification of known and unknown metabolites. Finally, a targeted LC-MSIMS method provided an increase in specificity and sensitivity to accurately quantify known metabolites of interest (odour precursors). Initially, all methodologies were developed through the use of either an artificial sweat matrix (global strategy) or through the use of synthetic standards (semi-targeted or targeted strategy). The sample complexity was then increased by applying the methodologies to an ASG5 apocrine cell line, in order to provide further knowledge into apocrine cell metabolism and to identify whether there could be any potential male or female differences due to differences in circulating hormones. Changes in the cell metabolism were identified, and both the NMR and LC-MS data could differentiate between control, tamoxifen- and β-estradiol-treated. However, it is difficult to attribute these changes to specific pathways, as these hormones or the vehicle used (ethanol) are likely to produce a ripple effect across the cell's metabolism. Nonetheless, NMR spectroscopy quantified 25 metabolites with lactate being the most abundant at 19.1 mM, while HILIC-MS could detect a range of lipids, nucleotides, amino acids, fatty acids and vitamins. The methodologies were then applied to human apocrine sweat collected from six volunteers across five days. NMR spectroscopy was able to identify 25 and quantify 19 metabolites, with lactate being the most abundant at 13.2 mM. LC-MS/MS readily identified 12 amino acid conjugates with HMHA being the most abundant. Furthermore, a possible 20 unidentified conjugates were detected (LC-MSIMS semi-targeted methodologies) as well as putatively identifying 473 metabolites (LC-MS global methodologies). MVDA techniques such as principal component analysis (PCA) illustrated that intra-individual variation was greater than inter-individual variation, as well as secretions from both the left and right arm being consistent with one another. Moreover, MVDA illustrated the complementary nature of both NMR and MS, as the data acquired with the two types of instrumentation showed the same trends, even though these trends were based on different subsets of metabolites. The work presented herein, has successfully used a number of analytical technologies to investigate metabolite content of human apocrine sweat. It has been shown that a number of complementary techniques and multivariate analysis can provide a valuable insight into the underlying physiology of malodour. This work was funded by BBSRC and Unilever (Port Sunlight, UK)

Metabolomic investigations into human apocrine sweat secretions

Human axillary odour is formed by the action of Corynebacteria or Stephyloccui bacteria on odourless axilla sections. Several groups have identified axillary odorants, including 3-methyl-2-hexanoic acid (3M2H) and 3-hydroxy-3-methyl-hexenoic acid (HMHA), and how they are pre-formed and bound to amino acid conjugates. However, there is currently a lack of LC-MS methodologies and no reported NMR methods, that are required to further identify the non-volatile constituents, which would provide further information to allow understanding of the underlying physiological biochemistry of malodour. This work has incorporated a three-pronged approach. Firstly, a global strategy, through the use of NMR and LC-MS, provided a complementary unbiased overview of the metabolite composition. Metabolites were identified based on acquired standards, accurate mass and through the use of in-house or online databases. Furthermore, spectra of biological samples are inherently complex, thus, requiring a multivariate data analysis (MVDA) approach to extract the latent chemical information in the data. Secondly, semi-targeted LC-MSIMS methodologies has been used to identify metabolites with a common structural core (i.e. odour precursors) and provide structural information for the reliable identification of known and unknown metabolites. Finally, a targeted LC-MSIMS method provided an increase in specificity and sensitivity to accurately quantify known metabolites of interest (odour precursors). Initially, all methodologies were developed through the use of either an artificial sweat matrix (global strategy) or through the use of synthetic standards (semi-targeted or targeted strategy). The sample complexity was then increased by applying the methodologies to an ASG5 apocrine cell line, in order to provide further knowledge into apocrine cell metabolism and to identify whether there could be any potential male or female differences due to differences in circulating hormones. Changes in the cell metabolism were identified, and both the NMR and LC-MS data could differentiate between control, tamoxifen- and β-stradiol-treated. However, it is difficult to attribute these changes to specific pathways, as these hormones or the vehicle used (ethanol) are likely to produce a ripple effect across the cell's metabolism. Nonetheless, NMR spectroscopy quantified 25 metabolites with lactate being the most abundant at 19.1 mM, while HILI C-MS could detect a range of lipids, nucleotides, amino acids, fatty acids and vitamins. The methodologies were then applied to human apocrine sweat collected from six volunteers across five days. NMR spectroscopy was able to identify 25 and quantify 19 metabolites, with lactate being the most abundant at 13.2 mM. LC-MS/MS readily identified 12 amino acid conjugates with HMHA being the most abundant. Furthermore, a possible 20 unidentified conjugates were detected (LC-MSIMS semi- targeted methodologies) as well as putatively identifying 473 metabolites (LC-MS global methodologies). MVDA techniques such as principal component analysis (PCA) illustrated that intra-individual variation was greater than inter-individual variation, as well as secretions from both the left and right arm being consistent with one another. Moreover, MVDA illustrated the complementary nature of both NMR and MS, as the data acquired with the two types of instrumentation showed the same trends, even though these trends were based on different subsets of metabolites. The work presented herein, has successfully used a number of analytical technologies to investigate metabolite content of human apocrine sweat. It has been shown that a number of complementary techniques and multivariate analysis can provide a valuable insight into the underlying physiology of malodour. This work was funded by BBSRC and Unilever (Port Sunlight, UK)EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Adipose tissue, metabolic and inflammatory responses to stroke are altered in obese mice

Obesity is an independent risk factor for stroke, although several clinical studies have reported that obesity improves stroke outcome. Obesity is hypothesised to aid recovery by protecting against post-stroke catabolism. We therefore assessed whether obese mice had an altered metabolic and inflammatory response to stroke. Obese ob/ob mice underwent a 20-min middle cerebral artery occlusion and 24-h reperfusion. Lipid metabolism and expression of inflammatory cytokines were assessed in the plasma, liver and adipose tissue. The obese-specific metabolic response to stroke was assessed in plasma using non-targeted ultra-high performance liquid chromatography-mass spectrometry (UHPLC-MS) metabolomics coupled with univariate and multivariate analysis. Obesity had no effect on the extent of weight loss 24 h after stroke but affected the metabolic and inflammatory responses to stroke, predominantly affecting lipid metabolism. Specifically, obese mice had increases in plasma free fatty acids and expression of adipose lipolytic enzymes. Metabolomics identified several classes of metabolites affected by stroke in obese mice, including fatty acids and membrane lipids (glycerophospholipids, lysophospholipids and sphingolipids). Obesity also featured increases in inflammatory cytokines in the plasma and adipose tissue. Overall, these results demonstrate that obesity affected the acute metabolic and inflammatory response to stroke and suggest a potential role for adipose tissue in this effect. These findings could have implications for longer-term recovery and also further highlight the importance of considering comorbidities in preclinical stroke research, especially when identifying biomarkers for stroke. However, further work is required to assess whether these changes translate into long-term effects on recovery