Gregory D. Tredwell

A software complement to AMDIS for processing GC-MS metabolomic data.

The software package AMDIS performs gas chromatography-mass spectrometry (GC-MS) peak deconvolution but tends to produce false positives and leaves missing values where peaks are found in only a proportion of a set of chromatograms. We have developed a software complement to AMDIS that (i) allows rapid manual inspection of chromatographic peaks across all samples to confirm data quality and (ii) for a given sample set, integrates peak areas across all samples even where AMDIS deconvolution would leave missing values. The freely available package runs within the commercial Matlab environment and is useful where GC-MS is used to profile complex mixtures.

The Development of Metabolomic Sampling Procedures for Pichia pastoris, and Baseline Metabolome Data

Metabolic profiling is increasingly being used to investigate a diverse range of biological questions. Due to the rapid turnover of intracellular metabolites it is important to have reliable, reproducible techniques for sampling and sample treatment. Through the use of non-targeted analytical techniques such as NMR and GC-MS we have performed a comprehensive quantitative investigation of sampling techniques for Pichia pastoris. It was clear that quenching metabolism using solutions based on the standard cold methanol protocol caused some metabolite losses from P. pastoris cells. However, these were at a low level, with the NMR results indicating metabolite increases in the quenching solution below 5% of their intracellular level for 75% of metabolites identified; while the GC-MS results suggest a slightly higher level with increases below 15% of their intracellular values. There were subtle differences between the four quenching solutions investigated but broadly, they all gave similar results. Total culture extraction of cells + broth using high cell density cultures typical of P. pastoris fermentations, was an efficient sampling technique for NMR analysis and provided a gold standard of intracellular metabolite levels; however, salts in the media affected the GC-MS analysis. Furthermore, there was no benefit in including an additional washing step in the quenching process, as the results were essentially identical to those obtained just by a single centrifugation step. We have identified the major high-concentration metabolites found in both the extra- and intracellular locations of P. pastoris cultures by NMR spectroscopy and GC-MS. This has provided us with a baseline metabolome for P. pastoris for future studies. The P. pastoris metabolome is significantly different from that of Saccharomyces cerevisiae, with the most notable difference being the production of high concentrations of arabitol by P. pastoris.

Artificial microRNA-mediated knockdown of pyruvate formate lyase (PFL1) provides evidence for an active 3-hydroxybutyrate production pathway in the green alga Chlamydomonas reinhardtii

Artificial microRNA technology was investigated as a means of down regulating metabolic pathways in the green alga Chlamydomonas reinhardtii, targeting pyruvate formate lyase (PFL1), which catalyzes the conversion of pyruvate to acetyl-CoA and formate during anoxic conditions. Two transformants with an 80-90% reduction in target protein and mRNA levels were identified. Nuclear magnetic resonance spectroscopy confirmed a substantial decrease in the production of formate in the knockdown lines during dark anoxic conditions and a re-routing of metabolism leading to enhanced production of ethanol and lactate. Under microaerobic conditions in the light, induced by sulphur-deprivation, knock-down of PFL1 resulted in reduced formate and ethanol production, increased net consumption of acetate and the excretion of lactate but no increase in the production of hydrogen. In addition the production of 3-hydroxybutyrate was identified in knock-down line cultures during the transition between microaerobic and anoxic conditions. Overall our results indicate that microRNA knock-down is a useful tool to manipulate anaerobic metabolism in C. reinhardtii.

Systematic integration of molecular profiles identifies miR-22 as a regulator of lipid and folate metabolism in breast cancer cells

Dysregulated microRNA (miRNA) mediate malignant phenotypes, including metabolic reprogramming. By performing an integrative analysis of miRNA and metabolome data for the NCI-60 cell line panel, we identified an miRNA cluster strongly associated with both c-Myc expression and global metabolic variation. Within this cluster the cancer-associated and cardioprotective miR-22 was shown to repress fatty acid synthesis and elongation in tumour cells by targeting ATP citrate lyase and fatty acid elongase 6, as well as impairing mitochondrial one-carbon metabolism by suppression of methylene tetrahydrofolate dehydrogenase/cyclohydrolase. Across several data sets, expression of these target genes were associated with poorer outcomes in breast cancer patients. Importantly, a beneficial effect of miR-22 on clinical outcomes in breast cancer was shown to depend on the expression levels of the identified target genes, demonstrating the relevance of miRNA/mRNA interactions to disease progression in vivo. Our systematic analysis establishes miR-22 as a novel regulator of tumour cell metabolism, a function that could contribute to the role of this miRNA in cellular differentiation and cancer development. Moreover, we provide a paradigmatic example of effect modification in outcome analysis as a consequence of miRNA-directed gene targeting, a phenomenon that could be exploited to improve patient prognosis and treatment.

Metabolomic Characterization of Nipple Aspirate Fluid by 1H NMR Spectroscopy and GC-MS

Nipple aspirate fluid (NAF) is a noninvasively obtained biofluid from the duct openings of the breast. NAF components are constantly secreted, metabolized, and reabsorbed by the epithelial lining of the lactiferous ducts of the breast. NAF has been studied as a potential breast tissue surrogate for the discovery of novel breast cancer risk, early detection, and treatment response biomarkers. We report the first unsupervised metabolite characterization of nipple aspirate fluid using NMR and GC-MS using convenience samples previously collected from four premenopausal and four postmenopausal women. A total of 38 metabolites were identified using the two analytical techniques, including amino acids, organic acids, fatty acids, and carbohydrates. Analytical reproducibility of metabolites in NAF by GC-MS was high across different extraction and analysis days. Overall, 31 metabolites had a coefficient of variation below 20%. By GC-MS, there were eight metabolites unique to NAF, 19 unique to plasma, and 24 shared metabolites. Correlative analysis of shared metabolites between matched NAF and plasma samples from pre- and postmenopausal women shows almost no correlations, with the exception being lactic acid, which was significantly negatively correlated (R(2) = 0.57; P = 0.03). These results suggest that NAF is metabolically distinct from plasma and that the application of metabolomic strategies may be useful for future studies investigating breast cancer risk and intervention response biomarkers.

Modelling the acid/base 1H NMR chemical shift limits of metabolites in human urine

IntroductionDespite the use of buffering agents the 1H NMR spectra of biofluid samples in metabolic profiling investigations typically suffer from extensive peak frequency shifting between spectra. These chemical shift changes are mainly due to differences in pH and divalent metal ion concentrations between the samples. This frequency shifting results in a correspondence problem: it can be hard to register the same peak as belonging to the same molecule across multiple samples. The problem is especially acute for urine, which can have a wide range of ionic concentrations between different samples.ObjectivesTo investigate the acid, base and metal ion dependent 1H NMR chemical shift variations and limits of the main metabolites in a complex biological mixture.MethodsUrine samples from five different individuals were collected and pooled, and pre-treated with Chelex-100 ion exchange resin. Urine samples were either treated with either HCl or NaOH, or were supplemented with various concentrations of CaCl2, MgCl2, NaCl or KCl, and their 1H NMR spectra were acquired.ResultsNonlinear fitting was used to derive acid dissociation constants and acid and base chemical shift limits for peaks from 33 identified metabolites. Peak pH titration curves for a further 65 unidentified peaks were also obtained for future reference. Furthermore, the peak variations induced by the main metal ions present in urine, Na+, K+, Ca2+ and Mg2+, were also measured.ConclusionThese data will be a valuable resource for 1H NMR metabolite profiling experiments and for the development of automated metabolite alignment and identification algorithms for 1H NMR spectra.

Translational Arrest Due to Cytoplasmic Redox Stress Delays Adaptation to Growth on Methanol and Heterologous Protein Expression in a Typical Fed-Batch Culture of Pichia pastoris

Results We have followed a typical fed-batch induction regime for heterologous protein production under the control of the AOX1 promoter using both microarray and metabolomic analysis. The genetic constructs involved 1 and 3 copies of the TRY1 gene, encoding human trypsinogen. In small-scale laboratory cultures, expression of the 3 copy-number construct induced the unfolded protein response (UPR) sufficiently that titres of extracellular trypsinogen were lower in the 3-copy construct than with the 1-copy construct. In the fed-batch-culture, a similar pattern was observed, with higher expression from the 1-copy construct, but in this case there was no significant induction of UPR with the 3-copy strain. Analysis of the microarray and metabolomic information indicates that the 3-copy strain was undergoing cytoplasmic redox stress at the point of induction with methanol. In this Crabtree-negative yeast, this redox stress appeared to delay the adaptation to growth on methanol and supressed heterologous protein production, probably due to a block in translation. Conclusion Although redox imbalance as a result of artificially imposed hypoxia has previously been described, this is the first time that it has been characterised as a result of a transient metabolic imbalance and shown to involve a stress response which can lead to translational arrest. Without detailed analysis of the underlying processes it could easily have been mis-interpreted as secretion stress, transmitted through the UPR.

convISA: A simple, convoluted method for isotopomer spectral analysis of fatty acids and cholesterol

Isotopomer spectral analysis (ISA) is a simple approach for modelling the cellular synthesis of fatty acids and cholesterol in a stable isotope labelling experiment. In the simplest model, fatty acid biosynthesis is described by two key parameters: the fractional enrichment of acetyl-CoA from the labelled substrate, D, and the fractional de novo synthesis of the fatty acid during the exposure to the labelled substrate, g(t). The model can also be readily extended to include synthesis via elongation of unlabelled shorter fatty acids. This modelling strategy is less complex than metabolic flux analysis and only requires the measurement of the mass isotopologues of a single metabolite. However, software tools to perform these calculations are not freely available. We have developed an algorithm (convISA), implemented in MATLAB(™), which employs the convolution (Cauchy product) of mass isotopologue distributions (MIDs) for ISA of fatty acids and cholesterol. In our method, the MIDs of each molecule are constructed as a single entity rather than deriving equations for individual isotopologues. The flexibility of this method allows the model to be applied to raw data as well as to data that has been corrected for natural isotope abundance. To test the algorithm, convISA was applied to 238 MIDs of methyl palmitate available from the literature, for which ISA parameters had been calculated via other methods. A very high correlation was observed between estimates of the D and g(t) parameters from convISA with both published values, and estimates generated by our own metabolic flux analysis using a simplified stoichiometric model (r=0.981 and 0.944, and 0.996 and 0.942). We also demonstrate the application of the convolution ISA approach to cholesterol biosynthesis; the model was applied to measurements made on MCF7 cells cultured in U-(13)C-glucose. In conclusion, we believe that convISA offers a convenient, flexible and transparent framework for metabolic modelling that will help facilitate the application of ISA to future experiments.

Lipid degradation promotes prostate cancer cell survival

Prostate cancer is the most common male cancer and androgen receptor (AR) is the major driver of the disease. Here we show that Enoyl-CoA delta isomerase 2 (ECI2) is a novel AR-target that promotes prostate cancer cell survival. Increased ECI2 expression predicts mortality in prostate cancer patients (p = 0.0086). ECI2 encodes for an enzyme involved in lipid metabolism, and we use multiple metabolite profiling platforms and RNA-seq to show that inhibition of ECI2 expression leads to decreased glucose utilization, accumulation of fatty acids and down-regulation of cell cycle related genes. In normal cells, decrease in fatty acid degradation is compensated by increased consumption of glucose, and here we demonstrate that prostate cancer cells are not able to respond to decreased fatty acid degradation. Instead, prostate cancer cells activate incomplete autophagy, which is followed by activation of the cell death response. Finally, we identified a clinically approved compound, perhexiline, which inhibits fatty acid degradation, and replicates the major findings for ECI2 knockdown. This work shows that prostate cancer cells require lipid degradation for survival and identifies a small molecule inhibitor with therapeutic potential.

Rapid screening of cellular stress responses in recombinant Pichia pastoris strains using metabolite profiling

Heterologous protein production in the yeast Pichia pastoris can be limited by biological responses to high expression levels; the unfolded protein response (UPR) is a key determinant of the success of protein production in this organism. Here, we used untargeted NMR metabolic profiling (metabolomics) of a number of different recombinant strains, carried out in a miniaturized format suitable for screening-level experiments. We identified a number of metabolites (from both cell extracts and supernatants) which correlated well with UPR-relevant gene transcripts, and so could be potential biomarkers for future high-throughput screening of large numbers of P. pastoris clones.