NMR-spectroscopic analysis of mixtures: from structure to function

Universal quantitative NMR analysis of complex natural samples

Nuclear Magnetic Resonance (NMR) is a universal and quantitative analytical technique. Being a unique structural tool, NMR also competes with metrological techniques for purity determination and reference material analysis. In pharmaceutical research, applications of quantitative NMR (qNMR) cover mostly the identification and quantification of drug and biological metabolites. Offering an unbiased view of the sample composition, and the possibility to simultaneously quantify multiple compounds, qNMR has become the method of choice for metabolomic studies and quality control of complex natural samples such as foods, plants or herbal remedies, and biofluids. In this regard, NMR-based metabolomic studies, dedicated to both the characterization of herbal remedies and clinical diagnosis, have increased considerably.

Anthranilate fluorescence marks a calcium-propagated necrotic wave that promotes organismal death in C. elegans

Death of the nematode Caenorhabditis elegans involves a conserved necrotic cell death cascade which generates endogenous blue anthranilate fluorescence, allowing death to be visualized.

For cells the passage from life to death can involve a regulated, programmed transition. In contrast to cell death, the mechanisms of systemic collapse underlying organismal death remain poorly understood. Here we present evidence of a cascade of cell death involving the calpain-cathepsin necrosis pathway that can drive organismal death in Caenorhabditis elegans. We report that organismal death is accompanied by a burst of intense blue fluorescence, generated within intestinal cells by the necrotic cell death pathway. Such death fluorescence marks an anterior to posterior wave of intestinal cell death that is accompanied by cytosolic acidosis. This wave is propagated via the innexin INX-16, likely by calcium influx. Notably, inhibition of systemic necrosis can delay stress-induced death. We also identify the source of the blue fluorescence, initially present in intestinal lysosome-related organelles (gut granules), as anthranilic acid glucosyl esters—not, as previously surmised, the damage product lipofuscin. Anthranilic acid is derived from tryptophan by action of the kynurenine pathway. These findings reveal a central mechanism of organismal death in C. elegans that is related to necrotic propagation in mammals—e.g., in excitotoxicity and ischemia-induced neurodegeneration. Endogenous anthranilate fluorescence renders visible the spatio-temporal dynamics of C. elegans organismal death.

In the nematode Caenorhabditis elegans, intestinal lysosome-related organelles (or “gut granules”) contain a bright blue fluorescent substance of unknown identity. This has similar spectral properties to lipofuscin, a product of oxidative damage known to accumulate with age in postmitotic mammalian cells. Blue fluorescence seems to increase in aging worm populations, and lipofuscin has been proposed to be the source. To analyze this further, we measure fluorescence levels after exposure to oxidative stress and during aging in individually tracked worms. Surprisingly, neither of these conditions increases fluorescence levels; instead blue fluorescence increases in a striking and rapid burst at death. Such death fluorescence (DF) also appears in young worms when killed, irrespective of age or cause of death. We chemically identify DF as anthranilic acid glucosyl esters derived from tryptophan, and not lipofuscin. In addition, we show that DF generation in the intestine is dependent upon the necrotic cell death cascade, previously characterized as a driver of neurodegeneration. We find that necrosis spreads in a rapid wave along the intestine by calcium influx via innexin ion channels, accompanied by cytosolic acidosis. Inhibition of necrosis pathway components can delay stress-induced death, supporting its role as a driver of organismal death. This necrotic cascade provides a model system to study neurodegeneration and organismal death.

Defective glucose metabolism in polycystic kidney disease identifies a new therapeutic strategy

Autosomal dominant polycystic kidney disease (ADPKD) is a common genetic disorder characterized by bilateral renal cyst formation. Recent identification of signaling cascades deregulated in ADPKD has led to the initiation of several clinical trials, but an approved therapy is still lacking. Using a metabolomic approach, we identify a pathogenic pathway in this disease that can be safely targeted for therapy. We show that mutation of PKD1 results in enhanced glycolysis in cells in a mouse model of PKD and in kidneys from humans with ADPKD. Glucose deprivation resulted in lower proliferation and higher apoptotic rates in PKD1-mutant cells than in nondeprived cells. Notably, two distinct PKD mouse models treated with 2-deoxyglucose (2DG), to inhibit glycolysis, had lower kidney weight, volume, cystic index and proliferation rates as compared to nontreated mice. These metabolic alterations depend on the extracellular signal-related kinase (ERK) pathway acting in a dual manner by inhibiting the liver kinase B1 (LKB1)-AMP-activated protein kinase (AMPK) axis on the one hand while activating the mTOR complex 1 (mTORC1)-glycolytic cascade on the other. Enhanced metabolic rates further inhibit AMPK. Forced activation of AMPK acts in a negative feedback loop, restoring normal ERK activity. Taken together, these data indicate that defective glucose metabolism is intimately involved in the pathobiology of ADPKD. Our findings provide a strong rationale for a new therapeutic strategy using existing drugs, either individually or in combination.

A nonribosomal peptide synthetase-derived iron(III) complex from the pathogenic fungus Aspergillus fumigatus

Small molecules (SMs) play central roles as virulence factors of pathogenic fungi and bacteria; however, genomic analyses suggest that the majority of microbial SMs have remained uncharacterized. Based on microarray analysis followed by comparative metabolomics of overexpression/knockout mutants, we identified a tryptophan-derived iron(III)-complex, hexadehydro-astechrome (HAS), as the major product of the cryptic has nonribosomal peptide synthetase (NRPS) gene cluster in the human pathogen Aspergillus fumigatus. Activation of the has cluster created a highly virulent A. fumigatus strain that increased mortality of infected mice. Comparative metabolomics of different mutant strains allowed to propose a pathway for HAS biosynthesis and further revealed cross-talk with another NRPS pathway producing the anticancer fumitremorgins.

A family of indoles regulate virulence and Shiga toxin production in pathogenic E. coli

Enteropathogenic Escherichia coli (EPEC), enterohemorrhagic E. coli (EHEC) and enteroaggregative E. coli (EAEC) are intestinal pathogens that cause food and water-borne disease in humans. Using biochemical methods and NMR-based comparative metabolomics in conjunction with the nematode Caenorhabditis elegans, we developed a bioassay to identify secreted small molecules produced by these pathogens. We identified indole, indole-3-carboxaldehyde (ICA), and indole-3-acetic acid (IAA), as factors that only in combination are sufficient to kill C. elegans. Importantly, although lethal to C. elegans, these molecules downregulate several bacterial processes important for pathogenesis in mammals. These include motility, biofilm formation and production of Shiga toxins. Some pathogenic E. coli strains are known to contain a Locus of Enterocyte Effacement (LEE), which encodes virulence factors that cause “attaching and effacing” (A/E) lesions in mammals, including formation of actin pedestals. We found that these indole derivatives also downregulate production of LEE virulence factors and inhibit pedestal formation on mammalian cells. Finally, upon oral administration, ICA inhibited virulence and promoted survival in a lethal mouse infection model. In summary, the C. elegans model in conjunction with metabolomics has facilitated identification of a family of indole derivatives that broadly regulate physiology in E. coli, and virulence in pathogenic strains. These molecules may enable development of new therapeutics that interfere with bacterial small-molecule signaling.

Carbon backbone topology of the metabolome of a cell

The complex metabolic makeup of a biological system, such as a cell, is a key determinant of its biological state providing unique insights into its function. Here we characterize the metabolome of a cell by a novel homonuclear (13)C 2D NMR approach applied to a nonfractionated uniformly (13)C-enriched lysate of E. coli cells and determine de novo their carbon backbone topologies that constitute the "topolome". A protocol was developed, which first identifies traces in a constant-time (13)C-(13)C TOCSY NMR spectrum that are unique for individual mixture components and then assembles for each trace the corresponding carbon-bond topology network by consensus clustering. This led to the determination of 112 topologies of unique metabolites from a single sample. The topolome is dominated by carbon topologies of carbohydrates (34.8%) and amino acids (45.5%) that can constitute building blocks of more complex structures.

Substrate/Product-targeted NMR monitoring of pyrimidine catabolism and its inhibition by a clinical drug

We report the application of one-dimensional triple-resonance NMR to metabolic analysis and thereon-based evaluation of drug activity. Doubly (13)C/(15)N-labeled uracil ([(15)N1,(13)C6]-uracil) was prepared. Its catabolic (degradative) conversion to [(13)C3,(15)N4]-β-alanine and inhibition thereof by gimeracil, a clinical co-drug used with the antitumor agent 5-fluorouracil, in mouse liver lysates were monitored specifically using one-dimensional triple-resonance ((1)H-{(13)C-(15)N}) NMR, but not double-resonance ((1)H-{(13)C}) NMR, in a ratiometric manner. The administration of labeled uracil to a mouse resulted in its non-selective distribution in various organs, with efficient catabolism to labeled β-alanine exclusively in the liver. The co-administration of gimeracil inhibited the catabolic conversion of uracil in the liver. In marked contrast to in vitro results, however, gimeracil had practically no effect on the level of uracil in the liver. The potentiality of triple-resonance NMR in the analysis of in vivo pharmaceutical activity of drugs targeting particular metabolic reactions is discussed.

NMR in metabolomics and natural products research: two sides of the same coin

Small molecules are central to biology, mediating critical phenomena such as metabolism, signal transduction, mating attraction, and chemical defense. The traditional categories that define small molecules, such as metabolite, secondary metabolite, pheromone, hormone, and so forth, often overlap, and a single compound can appear under more than one functional heading. Therefore, we favor a unifying term, biogenic small molecules (BSMs), to describe any small molecule from a biological source.

In a similar vein, two major fields of chemical research,natural products chemistry and metabolomics, have as their goal the identification of BSMs, either as a purified active compound (natural products chemistry) or as a biomarker of a particular biological state (metabolomics). Natural products chemistry has a long tradition of sophisticated techniques that allow identification of complex BSMs, but it often fails when dealing with complex mixtures. Metabolomics thrives with mixtures and uses the power of statistical analysis to isolate the proverbial “needle from a haystack”, but it is often limited in the identification of active BSMs. We argue that the two fields of natural products chemistry and metabolomics have largely overlapping objectives: the identification of structures and functions of BSMs, which in nature almost inevitably occur as complex mixtures.

Nuclear magnetic resonance (NMR) spectroscopy is a central analytical technique common to most areas of BSM research. In this Account, we highlight several different NMR approaches to mixture analysis that illustrate the commonalities between traditional natural products chemistry and metabolomics. The primary focus here is two-dimensional (2D) NMR; because of space limitations, we do not discuss several other important techniques, including hyphenated methods that combine NMR with mass spectrometry and chromatography.

We first describe the simplest approach of analyzing 2D NMR spectra of unfractionated mixtures to identify BSMs that are unstable to chemical isolation. We then show how the statistical method of covariance can be used to enhance the resolution of 2D NMR spectra and facilitate the semi-automated identification of individual components in a complex mixture. Comparative studies can be used with two or more samples, such as active vs inactive, diseased vs healthy, treated vs untreated, wild type vs mutant, and so on. We present two overall approaches to comparative studies: a simple but powerful method for comparing two 2D NMR spectra and a full statistical approach using multiple samples. The major bottleneck in all of these techniques is the rapid and reliable identification of unknown BSMs; the solution will require all the traditional approaches of both natural products chemistry and metabolomics as well as improved analytical methods, databases, and statistical tools.

Correlating secondary metabolite production with genetic changes using differential analysis of 2D NMR spectra

For many fungi the number of known secondary metabolites is surprisingly small compared to the -astonishingly large number of terpene cyclase, polyketide synthase (PKS), and non-ribosomal peptide synthetase (NRPS) secondary metabolite gene clusters found in their genomes. Correspondingly, the majority of fungal secondary metabolite genes have not yet been associated with the biosynthesis of any known small molecules, and it seems likely that for many more PKS and NRPS known small molecule products represent but a fraction of the entire spectrum of metabolites produced by the associated pathways. Comparative metabolomics based on differential analysis by 2D NMR spectroscopy (DANS) in conjunction with LC-MS analyses is emerging as a highly effective tool for pursuing small molecule structures and biosynthetic pathways associated with orphan PKS and NRPS gene clusters. Here we describe the use of DANS paired with LC-MS analyses for the comparison of the metabolomes of various fungal strains including wild-type (WT), PKS/NRPS overexpressing, and/or corresponding PKS/NRPS knock-out (KO) strains.

Informatic strategies for the discovery of polyketides and nonribosomal peptides

A modern challenge and opportunity exists for in the ability to link genomic and metabolomic data, using novel informatic methods to find new bioactive natural products.

Deconvolution of chemical mixtures with high complexity by NMR consensus trace clustering

Identification and quantification of analytes in complex solution-state mixtures are critical procedures in many areas of chemistry, biology, and molecular medicine. Nuclear magnetic resonance (NMR) is a unique tool for this purpose providing a wealth of atomic-detail information without requiring extensive fractionation of the samples. We present three new multidimensional-NMR based approaches that are geared toward the analysis of mixtures with high complexity at natural (13)C abundance, including approaches that are encountered in metabolomics. Common to all three approaches is the concept of the extraction of one-dimensional (1D) consensus spectral traces or 2D consensus planes followed by clustering, which significantly improves the capability to identify mixture components that are affected by strong spectral overlap. The methods are demonstrated for covariance (1)H-(1)H TOCSY and (13)C-(1)H HSQC-TOCSY spectra and triple-rank correlation spectra constructed from pairs of (13)C-(1)H HSQC and (13)C-(1)H HSQC-TOCSY spectra. All methods are first demonstrated for an eight-compound metabolite model mixture before being applied to an extract from E. coli cell lysate.

Identification of cryptic products of the gliotoxin gene cluster using NMR-based comparative metabolomics and a model for gliotoxin biosynthesis

Gliotoxin, a major product of the gli non-ribosomal peptide synthetase gene cluster, is strongly associated with virulence of the opportunistic human pathogen Aspergillus fumigatus. Despite identification of the gli cluster, the pathway of gliotoxin biosynthesis has remained elusive, in part because few potential intermediates have been identified. In addition, previous studies suggest that knowledge of gli-dependent metabolites is incomplete. Here we use differential analysis by 2D NMR spectroscopy (DANS) of metabolite extracts derived from gli knock-out and wild-type (WT) strains to obtain a detailed inventory of gli-dependent metabolites. DANS-based comparison of the WT metabolome with that of ΔgliZ, a knock-out strain devoid of the gene encoding the transcriptional regulator of the gli cluster, revealed nine novel gliZ-dependent metabolites including unexpected structural motifs. Their identification provides insight into gliotoxin biosynthesis and may benefit studies of the role of the gli cluster in A. fumigatus virulence. Our study demonstrates the utility of DANS for correlating gene expression and metabolite biosynthesis in microorganisms.