Metabolic profiling metabolite levels

Additional experiments have been conducted in severely head-injured cats to assess the effects of U-74006F on brain energy metabolites [61]. A 1 mg/kg i.v. dose administered at 30 minutes post-injury, plus a second 0.5 mg/kg dose 2 hours later, resulted in an improved metabolic profile within the injured hemisphere measured at 4 hours. Most notably, U-74006F significantly reduced post-traumatic accumulation of lactic acid in both the cerebral cortex and the sub-cortical white matter. This biochemical effect suggests an improved maintenance of cerebral blood flow in the injured brain. As noted above, U-74006F does very effectively reduce progressive development of post-traumatic ischemia in experimental cat spinal-cord injury [24,27] which may also provide the explanation for the reduction of post-traumatic lactate levels in the injured brain. 

Although considerable progress has been made in the metabolic profile approach, a number of problems remain to be overcome. Many of these centre around the fluctuations in component composition, not from metabolic disorders, but brought about by other influences. These are principally due to diet and the metabolic variations in individuals in relation to activity. Drugs can also affect the excretion levels of compounds, in addition to the production of their own metabolites. These factors all make quantitative data difficult to obtain and evaluate. Careful statistical analysis of the results are necessary and a population of 500 subjects, grouped in age and sex, has been studied with a view to obtaining a suitable data base for urinary organic acids [370]. 

Metabolites produced in microorganisms (referred to as secondary metabolites) are also an invaluable source of useful compounds, including pharmaceuticals, toxins, and other chemicals (Peric-Concha and Long, 2003). Only recently have analytical techniques progressed to a level that broad metabolic profiling has become a reality and has evolved into the science of metabolomics. For instance, over 700 different biochemical compounds have been identified within a single bacterial species alone (Nobeli et al., 2003). How to measure these compounds, how to identify the molecular structure of each individual compound, how to place each individual compound in the relevant biosynthesis pathway, and how each compound relates to functional properties within an organism or for human/animal health and nutrition are all different aspects of metabolomics. 

The quantitative abilities of the LC-TOF, although limited in the linear dynamic range, often allow measurement of metabolic profiles and PK profiles from the same samples. Zhang and co-workers [37] provide such an example. Quantitative results for a co-administration of five compounds to rats, with assay limits of quantitation (LOQ) between 1 and 5 ng/mL, and an upper limit of quantitation (ULQ) at 100 ng/mL were described. In this study, precision and accuracy were better than 20% for all five analytes, and comparable to triple-quadrupole quantitative data. More importantly, in addition to following the levels of dosed compound, the authors were able to identify several metabolites from the same full-scan data using the accurate mass capabilities ofthe LC/TOF-MS. 

A subsequent fermentation might also lead to additional, different compounds because, for a number of possible reasons, the secondary metabolic profile of a repeat fermentation may be different. Such reasons might include the effects of scale-up (e.g., oxygenation, shear forces), changes in the organism strain, subtle undetectable differences in the growth of the seed culture, inoculation into growth culture, and so on, all of which can lead to variations in levels and types of secondary metabolite expression. 

In order to enable holistic metabolic assessment of living organisms, one requires methods that can acquire metabolic profiles in a rapid, reproducible and comprehensive manner, without bias towards compound classes. NMR meets these requirements effectively, and can assess metabolites down to the tens of pM level . This may seem high when compared to more targeted methods such as LC(MS) and GC(MS), but NMR has the imique advantage that hundreds of metabolites can be assessed in a reproducible and quantitative manner in a single shot. Metabolite identification is a notorious bottleneck in metabonomics. In anticipation of this challenge, we built a pH dependent AMIX H NMR spectral database for gut polyphenols fermentation products for which literature provided clues on their abundance in faeces and urine. 

Most of the assays of isoprostanes to date have focused on assessing 8-iso-PGF levels in body fluids, since this is a major product of the total peroxidation process in vivo. When measuring the urinary metabolites of S-iso-PGF, the correct choice of the appropriate metabolite is important since the metabolic profile and appearance of the different metabolites vary between species (Roberts et al, 1996 Basu, 1998c Chiabrando et al, 1999). The tetranor metabolite of 8-iso-PGFj is the major urinary product in the rabbit, whereas the dinor metabolite is the dominant product in humans. 

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