GWAS of butyrylcholinesterase activity identifies four novel loci, independent effects within BCHE and secondary associations with metabolic risk factors

Serum butyrylcholinesterase (BCHE) activity is associated with obesity, blood pressure and biomarkers of cardiovascular and diabetes risk. We have conducted a genome-wide association scan to discover genetic variants affecting BCHE activity, and to clarify whether the associations between BCHE activity and cardiometabolic risk factors are caused by variation in BCHE or whether BCHE variation is secondary to the metabolic abnormalities. We measured serum BCHE in adolescents and adults from three cohorts of Australian twin and family studies. The genotypes from approximately 2.4 million single-nucleotide polymorphisms (SNPs) were available in 8791 participants with BCHE measurements. We detected significant associations with BCHE activity at three independent groups of SNPs at the BCHE locus (P = 5.8 x 10(-262), 7.8 x 10(-47), 2.9 x 10(-12)) and at four other loci: RNPEP (P = 9.4 x 10(-16)), RAPH1-ABI2 (P = 4.1 x 10(-18)), UGT1A1 (P = 4.0 x 10(-8)) and an intergenic region on chromosome 8 (P = 1.4 x 10(-8)). These loci affecting BCHE activity were not associated with metabolic risk factors. On the other hand, SNPs in genes previously associated with metabolic risk had effects on BCHE activity more often than can be explained by chance. In particular, SNPs within FTO and GCKR were associated with BCHE activity, but their effects were partly mediated by body mass index and triglycerides, respectively. We conclude that variation in BCHE activity is due to multiple variants across the spectrum from uncommon/large effect to common/small effect, and partly results from (rather than causes) metabolic abnormalities.

Animal model and molecular interactions of Cln5

Neuronal ceroid lipofuscinoses (NCLs) are a family of inherited pediatric neurodegenerative disorders, leading to retinal degeneration, death of selective neuronal populations and accumulation of autofluorscent ceroid-lipopigments. The clinical manifestations are generally similar in all forms. The Finnish variant late infantile neuronal ceroid lipofuscinosis (vLINCLFin) is a form of NCL, especially enriched in the Finnish population. The aim of this thesis was to analyse the brain pathology of vLINCLFin utilising the novel Cln5-/- mouse model. Gene expression profiling of the brains of already symptomatic Cln5-/- mice revealed that inflammation, neurodegeneration and defects in myelinization are the major characteristics of the later stages of the disease. Histological characterization of the brain pathology confirmed that the thalamocortical system is affected in Cln5-/- mice, similarly to the other NCL mouse models. However, whereas the brain pathology in all other analyzed NCL mice initiate in the thalamus and spread only months later to the cortex, we observed that the sequence of events is uniquely reversed in Cln5-/- mice; beginning in the cortex and spreading to the thalamus only months later. We could also show that even though neurodegeneration is inititated in the cortex, reactive gliosis and loss of myelin are evident in specific nuclei of the thalamus already in the 1 month old brain. To obtain a deeper insight into the disturbed metabolic pathways, we performed gene expression profiling of presymptomatic mouse brains. We validated these findings with immunohistological analyses, and could show that cytoskeleton and myelin were affected in Cln5-/- mice. Comparison of gene expression profiling results of Cln5-/- and Cln1-/- mice, further highlighted that these two NCL models share a common defective pathway, leading to disturbances in the neuronal growth cone and cytoskeleton. Encouraged by the evidence of this defected pathway, we analyzed the molecular interactions of NCL-proteins and observed that Cln5 and Cln1/Ppt1 proteins interact with each other. Furthermore, we demonstrated that Cln5 and Cln1/Ppt1 share an interaction partner, the F1-ATP synthase, potentially linking both vLINCLFIN and INCL diseases to disturbed lipid metabolism. In addition, Cln5 was shown to interact with other NCL proteins; Cln2, Cln3, Cln6 and Cln8, implicating a central role for Cln5 in the NCL pathophysiology. This study is the first to describe the brain pathology and gene expression changes in the Cln5-/- mouse. Together the findings presented in this thesis represent novel information of the disease processes and the molecular mechanisms behind vLINCLFin and have highlighted that vLINCLFin forms a very important model to analyze the pathophysiology of NCL diseases.

Microarrays in Molecular Profiling of Ewing Sarcoma Family of Tumors and CDKN2A Aberrations

Background: The Ewing sarcoma family of tumors (ESFT) are rare but highly malignant neoplasms that occur mainly in bone or but also in soft tissue. ESFT affects patients typically in their second decade of life, whereby children and adolescents bear the heaviest incidence burden. Despite recent advances in the clinical management of ESFT patients, their prognosis and survival are still disappointingly poor, especially in cases with metastasis. No targeted therapy for ESFT patients is currently available. Moreover, based merely on current clinical and biological characteristics, accurate classification of ESFT patients often fails at the time of diagnosis. Therefore, there is a constant need for novel molecular biomarkers to be applied in tandem with conventional parameters to further intensify ESFT risk-stratification and treatment selection, and ultimately to develop novel targeted therapies. In this context, a greater understanding of the genetics and immune characteristics of ESFT is needed. Aims: This study sought to open novel insights into gene copy number changes and gene expression in ESFT and, further, to enlighten the role of inflammation in ESFT. For this purpose, microarrays were used to provide gene-level information on a genomewide scale. In addition, this study focused on screening of 9p21.3 deletion sizes and frequencies in ESFT and, in another pediatric cancer, acute lymphocytic leukemia (ALL), in order to define more exact criteria for highrisk patient selection and to provide data for developing a more reliable diagnostic method to detect CDKN2A deletions. Results: In study I, 20 novel ESFT-associated suppressor genes and oncogenes were pinpointed using combined array CGH and expression analysis. In addition, interesting chromosomal rearrangements were identified: (1) Duplication of derivative chromosome der(22)(11;22) was detected in three ESFT patients. This duplication included the EWSR1-FLI1 fusion gene leading to increase in its copy number; (2) Cryptic amplifications on chromosomes 20 and 22 were detected, suggesting a novel translocation between chromosomes 20 and 22, which most probably produces a fusion between EWSR1 and NFATC2. In study II, bioinformatic analysis of ESFT expression profiles showed that inflammatory gene activation is detectable in ESFT patient samples and that the activation is characterized by macrophage gene expression. Most interestingly, ESFT patient samples were shown to express certain inflammatory genes that were prognostically significant. High local expression of C5 and JAK1 at the tumor site was shown to associate with favorable clinical outcome, whereas high local expression of IL8 was shown to be detrimental. Studies III and IV showed that the smallest overlapping region of deletion in 9p21.3 includes CDKN2A in all cases and that the length of this region is 12.2 kb in both Ewing sarcoma and ALL. Furthermore, our results showed that the most widely used commercial CDKN2A FISH probe creates false negative results in the narrowest microdeletion cases (<190 kb). Therefore, more accurate methods should be developed for the detection of deletions in the CDKN2A locus. Conclusions: This study provides novel insights into the genetic changes involved in the biology of ESFT, in the interaction between ESFT cells and immune system, and in the inactivation of CDKN2A. Novel ESFT biomarker genes identified in this study serve as a useful resource for future studies and in developing novel therapeutic strategies to improve the survival of patients with ESFT.

Molecular profiling of malignant pleural mesothelioma and pulmonary fibrosis

Malignant mesothelioma (MM) is a rare, usually incurable, disease mainly caused by former exposure to asbestos. Even though MM has a strong etiological link, genetic factors may play a role, since not all cases can be linked to former asbestos exposure. This thesis focuses on lung diseases, mainly malignant mesothelioma (MM), and idiopathic pulmonary fibrosis (IPF), which resembles asbestosis. The specific asbestos-related pathways associated with malignant as well as non-malignant lung diseases, still need to be clarified. Since most patients diagnosed with MM or asbestosis/fibrosis have a dismal prognosis and few therapeutic options are available, early diagnosis and better understanding of the disease pathogenesis are of the utmost importance. The first objective of this thesis was to identify asbestos specific differentially expressed genes. This was approached by using high-resolution gene expression arrays, and three different human lung cell lines, as well as with three different bioinformatics approaches. Since the first study aimed to elucidate potential early changes, the second study was used to screen DNA copy number changes in MM tumour samples. This was performed using genome wide microarrays for identification of DNA copy number changes characterstic for MM. Study III focused on the role of gremlin in the regulation of bone morphogenetic protein (BMPs) in IPF. Further studies were conducted in asbestos-exposed cell cultures as well as in an asbestos-induced mouse model. Furthermore, GATA-6 was studied in MM and metastatic pleural adenocarcinoma. The GATA transcription factors are important during embryonic development, but their role in cancer is still unclear. GATA-6 is a co-factor/target of thyroid transcription factor 1 (TTF-1), which is used in differential diagnostics of pleural MM and adenocarcinoma. Bioinformatics probed the genes and biological processes ordered in terms of significance, clusters, and highly enriched chromosomal regions. The study revealed several already identified targets, produced new ideas about genes which are central for asbestos exposure, as well as provided supplementary data for researchers to check their own novel findings or ideas. The analysis revealed DNA copy number changes characteristic for MM tumors. The most common regions of loss were detected in 1p, 3p, 6q, 9p, 13, 14, and 22, and gains at 17q. The histological features in asbestosis and IPF are very similar, wherefore IPF can be studied in asbestos models. The BMP antagonist gremlin was up-regulated by asbestos exposure in human epithelial cell lines, which was also observed in Study I. The transforming growth factor (TGF) -β and BMP expression and signaling activities were measured from murine and human fibrotic lungs. BMP-7 signaling was down-regulated in response to up-regulation of gremlin, and restoration of BMP-7 signaling prevented progression of fibrosis in mice. Therefore, the study suggests that the restoration of BMP-7 signaling in fibrotic lung could potentially aid in the treatment of IPF patients. Study IV revealed that GATA-6 was strongly expressed in the majority of the MM cases, and correlated statistically significant with longer survival in subgroups of MM.

Genomic and functional profiling of gastric cancer

Helicobacter pylori infection is a risk factor for gastric cancer, which is a major health issue worldwide. Gastric cancer has a poor prognosis due to the unnoticeable progression of the disease and surgery is the only available treatment in gastric cancer. Therefore, gastric cancer patients would greatly benefit from identifying biomarker genes that would improve diagnostic and prognostic prediction and provide targets for molecular therapies. DNA copy number amplifications are the hallmarks of cancers in various anatomical locations. Mechanisms of amplification predict that DNA double-strand breaks occur at the margins of the amplified region. The first objective of this thesis was to identify the genes that were differentially expressed in H. pylori infection as well as the transcription factors and signal transduction pathways that were associated with the gene expression changes. The second objective was to identify putative biomarker genes in gastric cancer with correlated expression and copy number, and the last objective was to characterize cancers based on DNA copy number amplifications. DNA microarrays, an in vitro model and real-time polymerase chain reaction were used to measure gene expression changes in H. pylori infected AGS cells. In order to identify the transcription factors and signal transduction pathways that were activated after H. pylori infection, gene expression profiling data from the H. pylori experiments and a bioinformatics approach accompanied by experimental validation were used. Genome-wide expression and copy number microarray analysis of clinical gastric cancer samples and immunohistochemistry on tissue microarray were used to identify putative gastric cancer genes. Data mining and machine learning techniques were applied to study amplifications in a cross-section of cancers. FOS and various stress response genes were regulated by H. pylori infection. H. pylori regulated genes were enriched in the chromosomal regions that are frequently changed in gastric cancer, suggesting that molecular pathways of gastric cancer and premalignant H. pylori infection that induces gastritis are interconnected. 16 transcription factors were identified as being associated with H. pylori infection induced changes in gene expression. NF-κB transcription factor and p50 and p65 subunits were verified using elecrophoretic mobility shift assays. ERBB2 and other genes located in 17q12- q21 were found to be up-regulated in association with copy number amplification in gastric cancer. Cancers with similar cell type and origin clustered together based on the genomic localization of the amplifications. Cancer genes and large genes were co-localized with amplified regions and fragile sites, telomeres, centromeres and light chromosome bands were enriched at the amplification boundaries. H. pylori activated transcription factors and signal transduction pathways function in cellular mechanisms that might be capable of promoting carcinogenesis of the stomach. Intestinal and diffuse type gastric cancers showed distinct molecular genetic profiles. Integration of gene expression and copy number microarray data allowed the identification of genes that might be involved in gastric carcinogenesis and have clinical relevance. Gene amplifications were demonstrated to be non-random genomic instabilities. Cell lineage, properties of precursor stem cells, tissue microenvironment and genomic map localization of specific oncogenes define the site specificity of DNA amplifications, whereas labile genomic features define the structures of amplicons. These conclusions suggest that the definition of genomic changes in cancer is based on the interplay between the cancer cell and the tumor microenvironment.

Gene Expression Profiling of the Cephalothorax and Eyestalk in Penaeus Monodon during Ovarian Maturation.

In crustaceans, a range of physiological processes involved in ovarian maturation occurs in organs of the cephalothorax including the hepatopancrease, mandibular and Y-organ. Additionally, reproduction is regulated by neuropeptide hormones and other proteins released from secretory sites within the eyestalk. Reproductive dysfunction in captive-reared prawns, Penaeus monodon, is believed to be due to deficiencies in these factors. In this study, we investigated the expression of gene transcripts in the cephalothorax and eyestalk from wild-caught and captive-reared animals throughout ovarian maturation using custom oligonucleotide microarray screening. We have isolated numerous transcripts that appear to be differentially expressed throughout ovarian maturation and between wild-caught and captive-reared animals. In the cephalothorax, differentially expressed genes included the 1,3-beta-D-glucan-binding high-density lipoprotein, 2/3-oxoacyl-CoA thiolase and vitellogenin. In the eyestalk, these include gene transcripts that encode a protein that modulates G-protein coupled receptor activity and another that encodes an architectural transcription factor. Each may regulate the expression of reproductive neuropeptides, such as the crustacean hyperglycaemic hormone and molt-inhibiting hormone. We could not identify differentially expressed transcripts encoding known reproductive neuropeptides in the eyestalk of either wild-caught or captive-reared prawns at any ovarian maturation stage, however, this result may be attributed to low relative expression levels of these transcripts. In summary, this study provides a foundation for the study of target genes involved in regulating penaeid reproduction.

A core metabolic enzyme mediates resistance to phosphine gas

Phosphine is a small redox-active gas that is used to protect global grain reserves, which are threatened by the emergence of phosphine resistance in pest insects. We find that polymorphisms responsible for genetic resistance cluster around the redox-active catalytic disulfide or the dimerization interface of dihydrolipoamide dehydrogenase (DLD) in insects (Rhyzopertha dominica and Tribolium castaneum) and nematodes (Caenorhabditis elegans). DLD is a core metabolic enzyme representing a new class of resistance factor for a redox-active metabolic toxin. It participates in four key steps of core metabolism, and metabolite profiles indicate that phosphine exposure in mutant and wild-type animals affects these steps differently. Mutation of DLD in C. elegans increases arsenite sensitivity. This specific vulnerability may be exploited to control phosphine-resistant insects and safeguard food security.

Profiling of carotenoids and antioxidant capacity of microalgae from subtropical coastal and brackish waters

Carotenoids are associated with various health benefits, such as prevention of age-related macular degeneration, cataract, certain cancers, rheumatoid arthritis, muscular dystrophy and cardiovascular problems. As microalgae contain considerable amounts of carotenoids, there is a need to find species with high carotenoid content. Out of hundreds of Australian isolates, twelve microalgal species were screened for carotenoid profiles, carotenoid productivity, and in vitro antioxidant capacity (total phenolic content (TPC) and ORAC). The top four carotenoid producers at 4.68-6.88 mg/g dry weight (DW) were Dunaliella salina, Tetraselmis suecica, Isochrysis galbana, and Pavlova salina. TPC was low, with D. salina possessing the highest TPC (1.54 mg Gallic Acid Equivalents/g DW) and ORAC (577 μmol Trolox Equivalents/g DW). Results indicate that T. suecica, D. salina, P. salina and I. galbana could be further developed for commercial carotenoid production.

Profiling ellagic acid content: The importance of form and ascorbic acid levels

As the importance of plant-based antioxidants to human health becomes clearer there is a rapidly expanding search for rich sources of these compounds. Much attention is currently focussed on the antioxidant potential of ellagic acid (EA). Making assessment difficult is that EA occurs in different forms: free EA, EA glycosides and polymeric ellagitannins. The overall structure of these forms has a pronounced effect on their antioxidant efficiency and is responsible for widely differing reactivity, solubility and hence bioavailability properties. Often associated with EA is vitamin C which also contributes to the plant foods total antioxidant activity. Previous studies have suggested that ascorbic acid may have protective effects on the polyphenol content of plants. With a view to gaining evidence that the bioactive forms of vitamin C influence EA content, several fruits with a range of EA and vitamin C contents were examined. To facilitate a more detailed assessment of the selected fruits antioxidant potential the relative proportions of EA forms were also determined. In strawberries and boysenberries EA content was predominantly in the polymeric form (21% and 12% free EA plus EA glycoside vs total EA levels for strawberry and boysenberry respectively), while in Kakadu plum it was mainly in the free form (70% of total EA). An increasing percentage of dehydroascorbic acid (9 to 14% of total vitamin C) indicating enhanced transformation of ascorbic acid to its oxidative degradation product together with stable free EA levels (≈ 950 mg/100 g DW) over the 4 month frozen storage period for the Kakadu plum samples are consistent with a possible protective effect of EA by ascorbic acid.

Cyanidin 3-glucoside improves diet-induced metabolic syndrome in rats

Increased consumption of dark-coloured fruits and vegetables may mitigate metabolic syndrome. This study has determined the changes in metabolic parameters, and in cardiovascular and liver structure and function, following chronic administration of either cyanidin 3-glucoside (CG) or Queen Garnet plum juice (QG) containing cyanidin glycosides to rats fed either a corn starch (C) or a high-carbohydrate, high-fat (H) diet. Eight to nine-week-old male Wistar rats were randomly divided into six groups for 16-week feeding with C, C with CG or QG, H or H with CG or QG. C or H were supplemented with CG or QG at a dose of ∼8 mg/kg/day cyanidin glycosides from week 8 to 16. H rats developed signs of metabolic syndrome including visceral adiposity, impaired glucose tolerance, hypertension, cardiovascular remodelling, increased collagen depots in left ventricle, non-alcoholic fatty liver disease, increased plasma liver enzymes and increased inflammatory cell infiltration in the heart and liver. Both CG and QG reversed these cardiovascular, liver and metabolic signs. However, no intact anthocyanins or common methylated/conjugated metabolites could be detected in the plasma samples and plasma hippuric acid concentrations were unchanged. Our results suggest CG is the most likely mediator of the responses to QG but that further investigation of the pharmacokinetics of oral CG in rats is required.

Stable expression of silencing-suppressor protein enhances the performance and longevity of an engineered metabolic pathway

Transgenic engineering of plants is important in both basic and applied research. However, the expression of a transgene can dwindle over time as the plant's small (s)RNA-guided silencing pathways shut it down. The silencing pathways have evolved as antiviral defence mechanisms, and viruses have co-evolved viral silencing-suppressor proteins (VSPs) to block them. Therefore, VSPs have been routinely used alongside desired transgene constructs to enhance their expression in transient assays. However, constitutive, stable expression of a VSP in a plant usually causes pronounced developmental abnormalities, as their actions interfere with endogenous microRNA-regulated processes, and has largely precluded the use of VSPs as an aid to stable transgene expression. In an attempt to avoid the deleterious effects but obtain the enhancing effect, a number of different VSPs were expressed exclusively in the seeds of Arabidopsis thaliana alongside a three-step transgenic pathway for the synthesis of arachidonic acid (AA), an ω-6 long chain polyunsaturated fatty acid. Results from independent transgenic events, maintained for four generations, showed that the VSP-AA-transformed plants were developmentally normal, apart from minor phenotypes at the cotyledon stage, and could produce 40% more AA than plants transformed with the AA transgene cassette alone. Intriguingly, a geminivirus VSP, V2, was constitutively expressed without causing developmental defects, as it acts on the siRNA amplification step that is not part of the miRNA pathway, and gave strong transgene enhancement. These results demonstrate that VSP expression can be used to protect and enhance stable transgene performance and has significant biotechnological application.

Computational Methods for Reconstruction and Analysis of Genome-Scale Metabolic Networks

Metabolism is the cellular subsystem responsible for generation of energy from nutrients and production of building blocks for larger macromolecules. Computational and statistical modeling of metabolism is vital to many disciplines including bioengineering, the study of diseases, drug target identification, and understanding the evolution of metabolism. In this thesis, we propose efficient computational methods for metabolic modeling. The techniques presented are targeted particularly at the analysis of large metabolic models encompassing the whole metabolism of one or several organisms. We concentrate on three major themes of metabolic modeling: metabolic pathway analysis, metabolic reconstruction and the study of evolution of metabolism. In the first part of this thesis, we study metabolic pathway analysis. We propose a novel modeling framework called gapless modeling to study biochemically viable metabolic networks and pathways. In addition, we investigate the utilization of atom-level information on metabolism to improve the quality of pathway analyses. We describe efficient algorithms for discovering both gapless and atom-level metabolic pathways, and conduct experiments with large-scale metabolic networks. The presented gapless approach offers a compromise in terms of complexity and feasibility between the previous graph-theoretic and stoichiometric approaches to metabolic modeling. Gapless pathway analysis shows that microbial metabolic networks are not as robust to random damage as suggested by previous studies. Furthermore the amino acid biosynthesis pathways of the fungal species Trichoderma reesei discovered from atom-level data are shown to closely correspond to those of Saccharomyces cerevisiae. In the second part, we propose computational methods for metabolic reconstruction in the gapless modeling framework. We study the task of reconstructing a metabolic network that does not suffer from connectivity problems. Such problems often limit the usability of reconstructed models, and typically require a significant amount of manual postprocessing. We formulate gapless metabolic reconstruction as an optimization problem and propose an efficient divide-and-conquer strategy to solve it with real-world instances. We also describe computational techniques for solving problems stemming from ambiguities in metabolite naming. These techniques have been implemented in a web-based sofware ReMatch intended for reconstruction of models for 13C metabolic flux analysis. In the third part, we extend our scope from single to multiple metabolic networks and propose an algorithm for inferring gapless metabolic networks of ancestral species from phylogenetic data. Experimenting with 16 fungal species, we show that the method is able to generate results that are easily interpretable and that provide hypotheses about the evolution of metabolism.

Algorithms for 13C metabolic flux analysis

The metabolism of an organism consists of a network of biochemical reactions that transform small molecules, or metabolites, into others in order to produce energy and building blocks for essential macromolecules. The goal of metabolic flux analysis is to uncover the rates, or the fluxes, of those biochemical reactions. In a steady state, the sum of the fluxes that produce an internal metabolite is equal to the sum of the fluxes that consume the same molecule. Thus the steady state imposes linear balance constraints to the fluxes. In general, the balance constraints imposed by the steady state are not sufficient to uncover all the fluxes of a metabolic network. The fluxes through cycles and alternative pathways between the same source and target metabolites remain unknown. More information about the fluxes can be obtained from isotopic labelling experiments, where a cell population is fed with labelled nutrients, such as glucose that contains 13C atoms. Labels are then transferred by biochemical reactions to other metabolites. The relative abundances of different labelling patterns in internal metabolites depend on the fluxes of pathways producing them. Thus, the relative abundances of different labelling patterns contain information about the fluxes that cannot be uncovered from the balance constraints derived from the steady state. The field of research that estimates the fluxes utilizing the measured constraints to the relative abundances of different labelling patterns induced by 13C labelled nutrients is called 13C metabolic flux analysis. There exist two approaches of 13C metabolic flux analysis. In the optimization approach, a non-linear optimization task, where candidate fluxes are iteratively generated until they fit to the measured abundances of different labelling patterns, is constructed. In the direct approach, linear balance constraints given by the steady state are augmented with linear constraints derived from the abundances of different labelling patterns of metabolites. Thus, mathematically involved non-linear optimization methods that can get stuck to the local optima can be avoided. On the other hand, the direct approach may require more measurement data than the optimization approach to obtain the same flux information. Furthermore, the optimization framework can easily be applied regardless of the labelling measurement technology and with all network topologies. In this thesis we present a formal computational framework for direct 13C metabolic flux analysis. The aim of our study is to construct as many linear constraints to the fluxes from the 13C labelling measurements using only computational methods that avoid non-linear techniques and are independent from the type of measurement data, the labelling of external nutrients and the topology of the metabolic network. The presented framework is the first representative of the direct approach for 13C metabolic flux analysis that is free from restricting assumptions made about these parameters.In our framework, measurement data is first propagated from the measured metabolites to other metabolites. The propagation is facilitated by the flow analysis of metabolite fragments in the network. Then new linear constraints to the fluxes are derived from the propagated data by applying the techniques of linear algebra.Based on the results of the fragment flow analysis, we also present an experiment planning method that selects sets of metabolites whose relative abundances of different labelling patterns are most useful for 13C metabolic flux analysis. Furthermore, we give computational tools to process raw 13C labelling data produced by tandem mass spectrometry to a form suitable for 13C metabolic flux analysis.