The origin of correlations in metabolomics data

A phenomenon observed earlier in the development of metabolomics as a systems biology methodology, consists of a small but significant number of metabolites whose levels are highly correlated between biological replicates. Contrary to initial interpretations, these correlations are not necessarily only between neighboring metabolites in the metabolic network. Most metabolites that participate in common reactions are not correlated in this way, while some non-neighboring metabolites are highly correlated. Here we investigate the origin of such correlations using metabolic control analysis and computer simulation of biochemical networks. A series of cases is identified which lead to high correlation between metabolite pairs in replicate measurement. These are (1) chemical equilibrium, (2) mass conservation, (3) asymmetric control distribution, and (4) unusually high variance in the expression of a single gene. The importance of identifying metabolite correlations within a physiological state and changes of correlation between different states is discussed in the context of systems biology.     

Metabolite annotations based on the integration of mass spectral information

A large number of metabolites are found in each plant, most of which have not yet been identified. Development of a methodology is required to deal systematically with unknown metabolites, and to elucidate their biological roles in an integrated 'omics' framework. Here we report the development of a 'metabolite annotation' procedure. The metabolite annotation is a process by which structures and functions are inferred for metabolites. Tomato ( Solanum lycopersicum cv. Micro-Tom) was used as a model for this study using LC-FTICR-MS. Collected mass spectral features, together with predicted molecular formulae and putative structures, were provided as metabolite annotations for 869 metabolites. Comparison with public databases suggests that 494 metabolites are novel. A grading system was introduced to describe the evidence supporting the annotations. Based on the comprehensive characterization of tomato fruit metabolites, we identified chemical building blocks that are frequently found in tomato fruit tissues, and predicted novel metabolic pathways for flavonoids and glycoalkaloids. These results demonstrate that metabolite annotation facilitates the systematic analysis of unknown metabolites and biological interpretation of their relationships, which provide a basis for integrating metabolite information into the system-level study of plant biology.     

Observing and interpreting correlations in metabolomic networks

MOTIVATION: Metabolite profiling aims at an unbiased identification and quantification of all the metabolites present in a biological sample. Based on their pair-wise correlations, the data obtained from metabolomic experiments are organized into metabolic correlation networks and the key challenge is to deduce unknown pathways based on the observed correlations. However, the data generated is fundamentally different from traditional biological measurements and thus the analysis is often restricted to rather pragmatic approaches, such as data mining tools, to discriminate between different metabolic phenotypes. METHODS AND RESULTS: We investigate to what extent the data generated networks reflect the structure of the underlying biochemical pathways. The purpose of this work is 2-fold: Based on the theory of stochastic systems, we first introduce a framework which shows that the emergent correlations can be interpreted as a 'fingerprint' of the underlying biophysical system. This result leads to a systematic relationship between observed correlation networks and the underlying biochemical pathways. In a second step, we investigate to what extent our result is applicable to the problem of reverse engineering, i.e. to recover the underlying enzymatic reaction network from data. The implications of our findings for other bioinformatics approaches are discussed.     

Age and circadian influences on picolinic acid concentrations in human cerebrospinal fluid

It has been suggested that picolinic acid (PIC), an endogenous metabolite of l -tryptophan, possesses neuro-protective and anti-proliferative effects within the CNS. However, the literature surrounding PIC is limited, and its exact endogenous function is not known. Picolinic acid is produced via the kynurenine pathway which has been implicated in the pathogenesis of a range of neuro-inflammatory diseases. Although not extensively studied, there have been reports of altered PIC production alongside other kynurenine metabolites in inflammatory disorders. In order to investigate whether PIC concentrations are altered with disease in the CNS, we analysed PIC levels in the CSF of 241 patients who underwent lumbar puncture as part of their standard clinical evaluation. In patients with no apparent CNS disease, CSF PIC levels were 10-fold higher in samples taken between 20:00 and 16:00 h compared with those collected between 04:00 and 12:00 h. This result suggests a diurnal variation in PIC synthesis within the CNS. In addition, we observed a direct correlation between a patient's age and their PIC concentration. No significant correlations were observed between CSF PIC levels and any specific disease state.     

Adaptive changes in bacteria: a consequence of nonlinear transitions in chromosome topology?

Adaptive changes in bacteria are generally considered to result from random mutations selected by the environment. This interpretation is challenged by the non-randomness of genomic changes observed following ageing or starvation in bacterial colonies. A theory of adaptive targeting of sequences for enzymes involved in DNA transactions is proposed here. It is assumed that the sudden leakage of cAMP consecutive to starvation induces a rapid drop in the ATP/ADP ratio that inactivates the homeostasis in control of the level of DNA supercoiling. This phase change enables the emergence of local modifications in chromosome topology in relation to the missing metabolites, a first stage in expression of an adaptive status in which DNA transactions are induced. The nonlinear perspective proposed here is homologous to that already suggested for adaptation of pluricellular organisms during their development. In both cases, phases of robustness in regulation networks for genetic expression are interspaced by critical periods of breakdown of the homeostatic regulations during which, through isolation of nodes from a whole network, specific changes with adaptive value may locally occur.     

Metabolic signature associated with parameters of the complete blood count in apparently healthy individuals

Metabolomics studies now approach large sample sizes and the health characterization of the study population often include complete blood count (CBC) results. Upon careful interpretation the CBC aids diagnosis and provides insight into the health status of the patient within a clinical setting. Uncovering metabolic signatures associated with parameters of the CBC in apparently healthy individuals may facilitate interpretation of metabolomics studies in general and related to diseases. For this purpose 879 subjects from the population‐based Study of Health in Pomerania (SHIP)‐TREND were included. Using metabolomics data resulting from mass‐spectrometry based measurements in plasma samples associations of specific CBC parameters with metabolites were determined by linear regression models. In total, 118 metabolites significantly associated with at least one of the CBC parameters. Strongest associations were observed with metabolites of heme degradation and energy production/consumption. Inverse association seen with mean corpuscular volume and mean corpuscular haemoglobin comprised metabolites potentially related to kidney function. The presently identified metabolic signatures are likely derived from the general function and formation/elimination of blood cells. The wealth of associated metabolites strongly argues to consider CBC in the interpretation of metabolomics studies, in particular if mutual effects on those parameters by the disease of interest are known.     

Metabolite profiling of mycorrhizal roots of Medicago truncatula

Metabolite profiling of soluble primary and secondary metabolites, as well as cell wall-bound phenolic compounds from roots of barrel medic (Medicago truncatula) was carried out by GC-MS, HPLC and LC-MS. These analyses revealed a number of metabolic characteristics over 56 days of symbiotic interaction with the arbuscular mycorrhizal (AM) fungus Glomus intraradices, when compared to the controls, i.e. nonmycorrhizal roots supplied with low and high amounts of phosphate. During the most active stages of overall root mycorrhization, elevated levels of certain amino acids (Glu, Asp, Asn) were observed accompanied by increases in amounts of some fatty acids (palmitic and oleic acids), indicating a mycorrhiza-specific activation of plastidial metabolism. In addition, some accumulating fungus-specific fatty acids (palmitvaccenic and vaccenic acids) were assigned that may be used as markers of fungal root colonization. Stimulation of the biosynthesis of some constitutive isoflavonoids (daidzein, ononin and malonylononin) occurred, however, only at late stages of root mycorrhization. Increase of the levels of saponins correlated AM-independently with plant growth. Only in AM roots was the accumulation of apocarotenoids (cyclohexenone and mycorradicin derivatives) observed. The structures of the unknown cyclohexenone derivatives were identified by spectroscopic methods as glucosides of blumenol C and 13-hydroxyblumenol C and their corresponding malonyl conjugates. During mycorrhization, the levels of typical cell wall-bound phenolics (e.g. 4-hydroxybenzaldehyde, vanillin, ferulic acid) did not change; however, high amounts of cell wall-bound tyrosol were exclusively detected in AM roots. Principal component analyses of nonpolar primary and secondary metabolites clearly separated AM roots from those of the controls, which was confirmed by an hierarchical cluster analysis. Circular networks of primary nonpolar metabolites showed stronger and more frequent correlations between metabolites in the mycorrhizal roots. The same trend, but to a lesser extent, was observed in nonmycorrhizal roots supplied with high amounts of phosphate. These results indicate a tighter control of primary metabolism in AM roots compared to control plants. Network correlation analyses revealed distinct clusters of amino acids and sugars/aliphatic acids with strong metabolic correlations among one another in all plants analyzed; however, mycorrhizal symbiosis reduced the cluster separation and enlarged the sugar cluster size. The amino acid clusters represent groups of metabolites with strong correlations among one another (cliques) that are differently composed in mycorrhizal and nonmycorrhizal roots. In conclusion, the present work shows for the first time that there are clear differences in development- and symbiosis-dependent primary and secondary metabolism of M. truncatula roots.     

Corn hybrids display lower metabolite variability and complex metabolite inheritance patterns

We conducted a comparative analysis of the root metabolome of six parental maize inbred lines and their 14 corresponding hybrids showing fresh weight heterosis. We demonstrated that the metabolic profiles not only exhibit distinct features for each hybrid line compared with its parental lines, but also separate reciprocal hybrids. Reconstructed metabolic networks, based on robust correlations between metabolic profiles, display a higher network density in most hybrids as compared with the corresponding inbred lines. With respect to metabolite level inheritance, additive, dominant and overdominant patterns are observed with no specific overrepresentation. Despite the observed complexity of the inheritance pattern, for the majority of metabolites the variance observed in all 14 hybrids is lower compared with inbred lines. Deviations of metabolite levels from the average levels of the hybrids correlate negatively with biomass, which could be applied for developing predictors of hybrid performance based on characteristics of metabolite patterns.     

Linking microbial diversity and functionality of arctic glacial surface habitats

Distinct microbial habitats on glacial surfaces are dominated by snow and ice algae, which are the critical players and the dominant primary colonisers and net producers during the melt season. Here for the first time we have evaluated the role of these algae in association with the full microbial community composition (i.e., algae, bacteria, archaea) in distinct surface habitats and on 12 glaciers and permanent snow fields in Svalbard and Arctic Sweden. We cross‐correlated these data with the analyses of specific metabolites such as fatty acids and pigments, and a full suite of potential critical physico‐chemical parameters including major and minor nutrients, and trace metals. It has been shown that correlations between single algal species, metabolites, and specific geochemical parameters can be used to unravel mixed metabolic signals in complex communities, further assign them to single species and infer their functionality. The data also clearly show that the production of metabolites in snow and ice algae is driven mainly by nitrogen and less so by phosphorus limitation. This is especially important for the synthesis of secondary carotenoids, which cause a darkening of glacial surfaces leading to a decrease in surface albedo and eventually higher melting rates.     

Isotope effects reveal that para-substituted benzylamines are poor reactivity probes of the quinoprotein mechanism for aromatic amine dehydrogenase

Structure-activity correlations have been employed previously in the mechanistic interpretation of TTQ-dependent amine dehydrogenases using a series of para-substituted benzylamines. However, by combining the use of kinetic isotope effects (KIEs) and crystallographic analysis, in conjunction with structure-reactivity correlation studies, we show that para-substituted benzylamines are poor reactivity probes for TTQ-dependent aromatic amine dehydrogenase (AADH). Stopped-flow kinetic studies of the reductive half-reaction, with para-substituted benzylamines and their dideuterated counterparts, demonstrate that C-H or C-D bond breakage is not fully rate limiting (KIEs approximately unity). Contrary to previous reports, Hammett plots exhibit a poor correlation of structure-reactivity data with electronic substituent effects for para-substituted benzylamines and phenylethylamines. Crystallographic studies of enzyme-substrate complexes reveal that the observed structure-reactivity correlations are not attributed to distinct binding modes for para-substituted benzylamines in the active site, although two binding sites for p-nitrobenzylamine are identified. We identify structural rearrangements, prior to the H-transfer step, which are likely to limit the rate of TTQ reduction by benzylamines. This work emphasizes (i) the need for caution when applying structure-activity correlations to enzyme-catalyzed reactions and (ii) the added benefit of using both isotope effects and structural analysis, in conjunction with structure-reactivity relationships, to study chemical steps in enzyme reaction cycles.     

植物次生代谢及其与环境的关系

人类对植物次生代谢产物（天然产物）的早期研究源于它们的应用价值,近些年来人们越来越认识到植物次生代谢产物广泛的生物学效应,开始重新评价这些化合物在植物生命活动以及生态系统中可能扮演的角色。植物的次生代谢是植物在长期进化中与环境（生物的和非生物的）相互作用的结果,次生代谢产物在植物提高自身保护和生存竞争能力、协调与环境关系上充当着重要的角色。介绍了植物次生代谢及其产物的特点,概述了植物次生代谢与温度、水分、光照、养分、CO2浓度、UV-B辐射、环境污染等非生物环境以及与化学防御、化感作用、菌根共生、微生物病害的关系。研究植物次生代谢与环境的关系,可以从更深的层次发掘植物与环境的内在联系,为全面、深入认识植物与环境的相互关系提供新的研究途径,同时也有利于人类更有效、合理地利用植物的次生代谢产物。     

Quantum chemical studies of polycyclic aromatic hydrocarbons and their metabolites: correlations to carcinogenicity.

In the context of the bay region hypothesis for polycyclic aromatic hydrocarbon (PAH) carcinogenesis, molecular properties were calculated for seventeen polycyclic aromatic hydrocarbons related to (1) intrinsic substrate reactivities towards activating and detoxifying metabolism and (2) the stabilities of the putative carbocation ultimate carcinogens. All-valence electron methods were used, avoiding the inherent difficulties found in the pi-electron methods. The calculated substrate reactivities were found to predict major metabolites successfully, supporting the validity of their use in attempted correlations with observed carcinogenic potencies. Positive correlations were found between observed carcinogenic potencies and (1) the reactivities of the parent polycyclic aromatic hydrocarbons towards the initial distal bay region epoxidation and (2) the stabilities of the diol epoxide carbocations. The reactivities of the distal bay region diol epoxides, were high for both carcinogenic and non-carcinogenic compounds, implying that the second epoxidation does not determine relative carcinogenic activity. Support for a possible alternative hypothesis, that polycyclic aromatic hydrocarbons are activated by one electron oxidation, was also found.     

The Influence of Genotype and Environment on the Physiological and Metabolic Diversity ofFusarium compactum

Talbot, N. J., Vincent, P., and Wildman, H. G. 1996. The influence of genotype and environment on the physiological and metabolic diversity ofFusarium compactum. Fungal Genetics and Biology20,254–267. Fungal species produce a large variety of secondary metabolites which are of considerable interest to the pharmaceutical industry. It is clear that the secondary metabolite production of a species varies significantly in strains from different geographic locations and from different habitats. The influence of genotype and environment on metabolite production is, however, poorly understood. In this study we examined the influence of genotypic variability, physiological variability, environmental location, and habitat on metabolite production byFusarium compactum.Isolates of the fungus from two geographic locations and two distinct habitat types were examined for growth on 95 different carbon sources, and genotypic variability was determined using RAPDs and rDNA–RFLP analysis. In a blind test secondary metabolite production was assessed using HPLC profiles of methanolic cell extracts. A number of correlations were observed between genotypic groupings, as determined using parsimony, and specific metabolite production. Similar correlations were also observed with physiological groups although genotypic analysis proved to be a more sensitive predictor of metabolite variability. The data suggest a complex relationship between environment, genotype, and metabolite production but highlight the use of genetic screening as a means of optimizing the chances of identifying a wide range of metabolites from a given species.     

Stability of Metabolic Correlations under Changing Environmental Conditions in Escherichia coli – A Systems Approach

Background

Biological systems adapt to changing environments by reorganizing their cellular and physiological program with metabolites representing one important response level. Different stresses lead to both conserved and specific responses on the metabolite level which should be reflected in the underlying metabolic network.

Methodology/Principal Findings

Starting from experimental data obtained by a GC-MS based high-throughput metabolic profiling technology we here develop an approach that: (1) extracts network representations from metabolic condition-dependent data by using pairwise correlations, (2) determines the sets of stable and condition-dependent correlations based on a combination of statistical significance and homogeneity tests, and (3) can identify metabolites related to the stress response, which goes beyond simple observations about the changes of metabolic concentrations. The approach was tested with Escherichia coli as a model organism observed under four different environmental stress conditions (cold stress, heat stress, oxidative stress, lactose diauxie) and control unperturbed conditions. By constructing the stable network component, which displays a scale free topology and small-world characteristics, we demonstrated that: (1) metabolite hubs in this reconstructed correlation networks are significantly enriched for those contained in biochemical networks such as EcoCyc, (2) particular components of the stable network are enriched for functionally related biochemical pathways, and (3) independently of the response scale, based on their importance in the reorganization of the correlation network a set of metabolites can be identified which represent hypothetical candidates for adjusting to a stress-specific response.

Conclusions/Significance

Network-based tools allowed the identification of stress-dependent and general metabolic correlation networks. This correlation-network-based approach does not rely on major changes in concentration to identify metabolites important for stress adaptation, but rather on the changes in network properties with respect to metabolites. This should represent a useful complementary technique in addition to more classical approaches.     

Evolution of secondary metabolites from an ecological and molecular phylogenetic perspective

Secondary metabolites, at least the major ones present in a plant, apparently function as defence (against herbivores, microbes, viruses or competing plants) and signal compounds (to attract pollinating or seed dispersing animals). They are thus important for the plant's survival and reproductive fitness. Secondary metabolites therefore represent adaptive characters that have been subjected to natural selection during evolution. Molecular phylogenies of the Fabaceae, Solanaceae and Lamiaceae were reconstructed and employed as a framework to map and to interpret the distribution of some major defence compounds that are typical for the respective plant families; quinolizidine alkaloids and non-protein amino acids for legumes; tropane and steroidal alkaloids for Solanaceae, and iridoids and essential oils for labiates. The distribution of the respective compounds appears to be almost mutually exclusive in the families studied, implying a strong phylogenetic and ecological component. However, on a closer look, remarkable exceptions can be observed, in that certain metabolites are absent (or present) in a given taxon, although all the neighbouring and ancestral taxa express (or do not express, respectively) the particular trait. It is argued that these patterns might reflect differential expression of the corresponding genes that have evolved earlier in plant evolution. The inconsistent secondary metabolite profiles mean that the systematic value of chemical characters becomes a matter of interpretation in the same way as traditional morphological markers. Thus, the distribution of secondary metabolites has some value for taxonomy but their occurrence apparently reflects adaptations and particular life strategies embedded in a given phylogenetic framework.     

Analysis of metabolic network based on conservation of molecular structure

Recent work has revealed much about chemical reactions inside hundreds of organisms as well as universal characteristics of metabolic networks, which shed light on the evolution of the networks. However, characteristics of individual metabolites have been neglected. For example, some carbohydrates have structures that are decomposed into small molecules by metabolic reactions, but coenzymes such as ATP are mostly preserved. Such differences in metabolite characteristics are important for understanding the universal characteristics of metabolic networks. To quantify the structure conservation of metabolites, we defined the "structure conservation index" (SCI) for each metabolite as the fraction of metabolite atoms restored to their original positions through metabolic reactions. As expected, coenzymes and coenzyme-like metabolites that have reaction loops in the network show a higher SCI. Using the index, we found that the sum of metabolic fluxes is negatively correlated with the structure preservation of metabolite. Also, we found that each reaction path around high SCI metabolites changes independently, while changes in reaction paths involving low SCI metabolites coincide through evolution processes. These correlations may provide a clue to universal properties of metabolic networks.     

The mutational structure of metabolism in Caenorhabditis elegans

A properly functioning organism must maintain metabolic homeostasis. Deleterious mutations degrade organismal function, presumably at least in part via effects on metabolic function. Here we present an initial investigation into the mutational structure of the Caenorhabditis elegans metabolome by means of a mutation accumulation experiment. We find that pool sizes of 29 metabolites vary greatly in their vulnerability to mutation, both in terms of the rate of accumulation of genetic variance (the mutational variance, VM) and the rate of change of the trait mean (the mutational bias, ΔM). Strikingly, some metabolites are much more vulnerable to mutation than any other trait previously studied in the same way. Although we cannot statistically assess the strength of mutational correlations between individual metabolites, principal component analysis provides strong evidence that some metabolite pools are genetically correlated, but also that there is substantial scope for independent evolution of different groups of metabolites. Averaged over mutation accumulation lines, PC3 is positively correlated with relative fitness, but a model in which metabolites are uncorrelated with fitness is nearly as good by Akaike's Information Criterion.     

Correlation between gliadin bands

Summary Starch gel electrophoresis of gliadins was carried out for 37 bread wheat cultivars chosen for their distant relationships. Simple correlations were calculated between each of the 41 bands (variates) observed with these wheats. It was found that a band is usually negatively correlated with the two neighbouring mobility bands. The number of bands positively or negatively correlated with a given band varies from 2 to 8. Taking the bands significantly positively correlated with each-other 32 groups were constituted. It appears likely that these correlations result from the fact that the genes determining the bands of a given group are situated on one chromosome. Study of the distribution of 15 gliadin bands from 312 F₂ grains indicated that 2/3 of the correlations calculated for this progeny were due to linkages.