Isotopomics: A Top-Down Systems Biology Approach for Understanding Dynamic Metabolism in Rats Using [1,2-13C2] Acetate

A novel quantification method for sulfur-containing biomarkers of formaldehyde and acetaldehyde exposure in human urine and plasma samples

A novel method for the quantification of the sulfur-containing metabolites of formaldehyde (thiazolidine carboxylic acid (TCA) and thiazolidine carbonyl glycine (TCG)) and acetaldehyde (methyl thiazolidine carboxylic acid (MTCA) and methyl thiazolidine carbonyl glycine (MTCG)) was developed and validated for human urine and plasma samples. Targeting the sulfur-containing metabolites of formaldehyde and acetaldehyde in contrast to the commonly used biomarkers formate and acetate overcomes the high intra- and inter-individual variance. Due to their involvement in various endogenous processes, formate and acetate lack the required specificity for assessing the exposure to formaldehyde and acetaldehyde, respectively. Validation was successfully performed according to FDA's Guideline for Bioanalytical Method Validation (2018), showing excellent performance with regard to accuracy, precision, and limits of quantification (LLOQ). TCA, TCG, and MTCG proved to be stable under all investigated conditions, whereas MTCA showed a depletion after 21 months. The method was applied to a set of pilot samples derived from smokers who consumed unfiltered cigarettes spiked with ¹³C-labeled propylene glycol and ¹³C-labeled glycerol. These compounds were used as potential precursors for the formation of ¹³C-formaldehyde and ¹³C-acetaldehyde during combustion. Plasma concentrations were significantly lower as compared to urine, suggesting urine as suitable matrix for a biomonitoring. A smoking-related increase of unlabeled biomarker concentrations could not be shown due to the ubiquitous distribution in the environment. While the metabolites of ¹³C-acetaldehyde were not detected, the described method allowed for the quantification of ¹³C-formaldehyde uptake from cigarette smoking by targeting the biomarkers ¹³C-TCA and ¹³C-TCG in urine.Graphical abstract.

Stable carbon isotope diagnostics of mammalian metabolism, a high-resolution isotomics approach using amino acid carboxyl groups

The carbon isotopic compositions of amino acids are increasingly measured to characterize diets and metabolic response to diets. We report a new high-resolution system to measure the stable carbon isotopic composition of carboxyl atoms within amino acids. The automated system used HPLC to separate amino acids followed by addition of ninhydrin for decarboxylation and transfer of the evolved CO2 to a stable isotope ratio mass spectrometer for δ13CCARBOXYL measurement. The ninhydrin reaction was conducted at acidic pH (1.5) and elevated temperature (160 oC) giving yields close to 100% for most common amino acids. Eight mammalian keratin samples from herbivores (kudu and caribou), omnivores (humans) and carnivores (bowhead and humpback zooplanktivorous whales) were analysed with this new system. The data provide an initial calibration of reference materials to be used in studies of this type and is the first report of carboxyl carbon isotope distributions in mammals. Results showed widespread 13C enrichments in both essential and non-essential amino acid carboxyl groups, likely linked to decarboxylation of amino acids during normal metabolism. Analyses of non-essential amino acid isotope profiles showed (1) consistent and general taxon-level metabolic differences between the herbivore, human and whale samples, (2) marked differences among individual humans, ruminants and whales (3) evidence for gluconeogenesis in the wildlife samples, and (4) extensive 13C enrichment likely associated with fasting in the humpback whale sample. Future mammalian research related to the metabolism of growth, reproduction, aging and disease may benefit from using this technique. Values obtained for internationally available samples USGS42 and USGS43 (Tibetan and Indian human hair) provide a first characterization of reference materials for δ13CCARBOXYL profiles.

Comparison of gas chromatography-mass spectrometry and gas chromatography-combustion-isotope ratio mass spectrometry analysis for in vivo estimates of metabolic fluxes

Gas chromatography-mass spectrometry (GC-MS) was compared with gas chromatography-combustion-isotope ratio mass spectrometry (GC-C-IRMS) for measurements of cholesterol (13)C enrichment after infusion of labeled precursor ([(13)C1,2]acetate). Paired results were significantly correlated, although GC-MS was less accurate than GC-C-IRMS for higher enrichments. Nevertheless, only GC-MS was able to provide information on isotopologue distribution, bringing new insights to lipid metabolism. Therefore, we assessed the isotopologue distribution of cholesterol in humans and dogs known to present contrasted cholesterol metabolic pathways. The labeled tracer incorporation was different in both species, highlighting the subsidiarity of GC-MS and GC-C-IRMS to analyze in vivo stable isotope studies.

Natural carbon isotope abundance of plasma metabolites and liver tissue differs between diabetic and non-diabetic Zucker diabetic fatty rats

Background

‘You are what you eat’ is an accurate summary for humans and animals when it comes to carbon isotope abundance. In biological material, natural¹³C/¹²C ratio is subject to minute variations due to diet composition (mainly from ingestion of C₃ and C₄ metabolism plants) and to the discrimination between ‘light’ and ‘heavy’ isotopes during biochemical reactions (isotope effects and isotopic fractionation).

Methodology/Principal Findings

Carbon isotopic abundance was measured in ZDF (fa/+) and ZDF (fa/fa), (lean and obese-diabetic rats respectively) fed the same diet. By analysing plasma metabolites (glucose and non-esterified fatty acids), breath and liver tissue by high-precision isotope ratio mass spectrometry, we demonstrate for the first time statistically distinguishable metabolic carbon isotope abundance between ZDF (fa/+) and ZDF (fa/fa) rats based on plasma glucose, palmitic, oleic, linoleic, arachidonic acids and bulk analysis of liver tissue (P<0.005) resulting into clear isotopic fingerprints using principal component analysis. We studied the variation of isotopic abundance between both groups for each metabolite and through the metabolic pathways using the precursor/product approach. We confirmed that lipids were depleted in ¹³C compared to glucose in both genotypes. We found that isotopic abundance of linoleic acid (C18: 2n-6), even though both groups had the same feed, differed significantly between both groups. The likely reason for these changes between ZDF (fa/+) and ZDF (fa/fa) are metabolic dysregulation associated with various routing and fluxes of metabolites.

Conclusion/Significance

This work provides evidence that measurement of natural abundance isotope ratio of both bulk tissue and individual metabolites can provide meaningful information about metabolic changes either associated to phenotype or to genetic effects; irrespective of concentration. In the future measuring the natural abundance δ¹³C of key metabolites could be used as endpoints for studying in vivo metabolism, especially with regards to metabolic dysregulation, and development and progression of metabolic diseases.

1H NMR-based metabonomic applications to decipher gut microbial metabolic influence on mammalian health

Recent advances in molecular biology and microbiology have increased awareness on the importance of the gut microbiota to the overall mammalian host's health status. There is therefore increasing interest in nutrition research to characterise the molecular foundations of the gut microbial mammalian crosstalk at both physiological and biochemical pathway levels. Tackling these challenges can be achieved through systems biology strategies based on the measurement of metabolites to assess the highly complex metabolic exchanges between diverse biological compartments, including organs, biofluids and microbial symbionts. By opening a direct biochemical window into the metabolome, metabonomics is uniquely suited for the identification of biomarkers providing better understanding of these complex metabolic processes. Recent applications of top-down system biology based on (1)H NMR spectroscopy coupled to advanced chemometric modelling approaches provided compelling evidence that system-wide and organ-specific changes in biochemical processes may be finely tuned by gut microbial activities. This review aims at describing current advances in NMR-based metabonomics where the main objective is to discern the molecular pathways and biochemical mechanisms under the influence of the gut microbiota. Furthermore, emphasis is given on nutritional approaches, where the quest for homeostatic balance is dependent not only on the host but also on the nutritional modulation of the gut microbiota-host metabolic interactions, using, for instance, probiotics and prebiotics.

13C metabolic flux analysis in complex systems

Experimental determination of in vivo metabolic rates by methods of (13)C metabolic flux analysis is a pivotal approach to unravel structure and regulation of metabolic networks, in particular with microorganisms grown in minimal media. However, the study of real-life and eukaryotic systems calls for the quantification of fluxes also in cellular compartments, rich media, cell-wide metabolic networks, dynamic systems or single cells. These scenarios drastically increase the complexity of the task, which is only partly dealt by existing approaches that rely on rigorous simulations of label propagation through metabolic networks and require multiple labeling experiments or a priori information on pathway inactivity to simplify the problem. Albeit qualitative and largely driven by human interpretation, statistical analysis of measured (13)C-patterns remains the exclusive alternative to comprehensively handle such complex systems. In the future, this practice will be complemented by novel modeling frameworks to assay particular fluxes within a network by stable isotopic tracer for targeted validation of well-defined hypotheses.