Human Endogenous Natural Products
333
urine metabolome using NMR, GC/MS, ICPMS, NMR, GC/MS, ICPMS, direct
infusion, and LC/MS/MS was conducted, and 445 unique urine metabolites were
identified. The potential of
1 H NMR metabolic profiling to identify the trace level of
body fluids was demonstrated and validated as a rapid and non-destructive tool for
forensic analysis.
Plant metabolomic studies have addressed the effects of genotype, ecotype, and
environmental stressors, such as drought and submergence, which can provide
metabolic phenotype information for chemical genomics studies in plants. In addition
to the primary metabolome, plants also produce an immense number of secondary
metabolites (ca. 200,000) that can interact with beneficial or harmful organisms.
Nuclear magnetic resonance metabolomics is also useful in discovery-oriented
natural products chemistry. 2D-NMR spectra of unfractionated sample extracts can
facilitate the identification of novel compounds that might be lost during chromatographic fractionation due to the low abundance or instability of the natural products. A common approach, activity-guided fractionation in natural product research,
may fail to characterize synergistically interacting biogenic small molecules. Using
NMR metabolomics, unique spectral features can be identified and correlated to a
phenotype of the biological property of interest.
In summary, efficient metabolite identification is one of the central challenges
in metabolomics. Given the chemical diversity of human metabolites, new techniques that make metabolite identification easier and more robust are still necessary. Over the past 10 years, significant advances in the methodology and software/databases used hat are associated with these platforms have greatly improved
compound identification.
6 Conclusions
This contribution provides an overview of the research progress made on human
endogenous compounds. In summary, the natural products produced by humans
are relatively well understood and only minor enhancements in the laboratory techniques used for their study are required for their complete understanding. In contrast,
those natural products produced from microbes are not well understood and further
information on their functional and causal relationships is needed. Considering the
complexity of microbiota, a better comprehension of their variations due to sampling
sites, health conditions, sampling times, and ethnic group diversity are all required.
Proper animal models, precise experiment design, and appropriate biochemical characterization are needed as well. Many non-canonical mechanisms, including the gut
brain axis and microbiota microbiota interactions also occur due to the action of
microbiota natural products, and these also require further investigation. A better
understanding of the “dark matter” will not only reveal more biological mechanisms that can be described with known methods and well-studied factors as
“known knowns” but also elucidate even more biological mechanisms that cannot
be described with either known methods or known factors as “unknown unknowns.”
333
urine metabolome using NMR, GC/MS, ICPMS, NMR, GC/MS, ICPMS, direct
infusion, and LC/MS/MS was conducted, and 445 unique urine metabolites were
identified. The potential of
1 H NMR metabolic profiling to identify the trace level of
body fluids was demonstrated and validated as a rapid and non-destructive tool for
forensic analysis.
Plant metabolomic studies have addressed the effects of genotype, ecotype, and
environmental stressors, such as drought and submergence, which can provide
metabolic phenotype information for chemical genomics studies in plants. In addition
to the primary metabolome, plants also produce an immense number of secondary
metabolites (ca. 200,000) that can interact with beneficial or harmful organisms.
Nuclear magnetic resonance metabolomics is also useful in discovery-oriented
natural products chemistry. 2D-NMR spectra of unfractionated sample extracts can
facilitate the identification of novel compounds that might be lost during chromatographic fractionation due to the low abundance or instability of the natural products. A common approach, activity-guided fractionation in natural product research,
may fail to characterize synergistically interacting biogenic small molecules. Using
NMR metabolomics, unique spectral features can be identified and correlated to a
phenotype of the biological property of interest.
In summary, efficient metabolite identification is one of the central challenges
in metabolomics. Given the chemical diversity of human metabolites, new techniques that make metabolite identification easier and more robust are still necessary. Over the past 10 years, significant advances in the methodology and software/databases used hat are associated with these platforms have greatly improved
compound identification.
6 Conclusions
This contribution provides an overview of the research progress made on human
endogenous compounds. In summary, the natural products produced by humans
are relatively well understood and only minor enhancements in the laboratory techniques used for their study are required for their complete understanding. In contrast,
those natural products produced from microbes are not well understood and further
information on their functional and causal relationships is needed. Considering the
complexity of microbiota, a better comprehension of their variations due to sampling
sites, health conditions, sampling times, and ethnic group diversity are all required.
Proper animal models, precise experiment design, and appropriate biochemical characterization are needed as well. Many non-canonical mechanisms, including the gut
brain axis and microbiota microbiota interactions also occur due to the action of
microbiota natural products, and these also require further investigation. A better
understanding of the “dark matter” will not only reveal more biological mechanisms that can be described with known methods and well-studied factors as
“known knowns” but also elucidate even more biological mechanisms that cannot
be described with either known methods or known factors as “unknown unknowns.”