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Indole-3-acetic acid (IAA), the most common form of auxin, is involved in a great range of plant physiological processes. IAA is synthesized from the amino acid tryptophan and can be transported and inactivated in a myriad of ways. Despite intense research efforts, there are still dark corners in our comprehension of IAA metabolism and its interplays with other pathways. Genetic screens are a powerful tool for unbiasedly looking for new players in a given biological process. However, pleiotropism of auxin-related phenotypes and indirect effects make it necessary to incorporate additional screening steps to specifically find mutants affected in IAA homeostasis. We previously developed and validated a high-throughput methodology to simultaneously quantify IAA, key precursors, and inactive forms from as little as 10 mg of fresh tissue. We have carried out a genetic screening to identify mutants involved in IAA metabolism. Auxin reporters DR5pro:VENUS and 35Spro:DII-VENUS were EMS-mutagenized and subjected to a parallel morphological and reporter-signal pre-screen. We then obtained the auxin metabolite profile of 325 M3 selected lines and used multivariate data analysis to identify potential IAA-metabolism mutants. To test the screening design, we identified the causal mutations in three of the candidate lines by mapping-by-sequencing: dii365.3, dii571.1 and dr693. These carry new alleles of CYP83A1, MIAO, and SUPERROOT2, respectively, all of which have been previously involved in auxin homeostasis. Our results support the suitability of this approach to find new genes involved in IAA metabolism.

Auxin (indole-3-acetic acid, IAA) plays fundamental roles as a signalling molecule during numerous plant growth and development processes. The formation of local auxin gradients and auxin maxima/minima, which is very important for these processes, is regulated by auxin metabolism (biosynthesis, degradation, and conjugation) as well as transport. When studying auxin metabolism pathways it is crucial to combine data obtained from genetic investigations with the identification and quantification of individual metabolites. Thus, to facilitate efforts to elucidate auxin metabolism and its roles in plants, we have developed a high-throughput method for simultaneously quantifying IAA and its key metabolites in minute samples (<10 mg FW) of Arabidopsis thaliana tissues by in-tip micro solid-phase extraction and fast LC-tandem MS. As a proof of concept, we applied the method to a collection of Arabidopsis mutant lines and identified lines with altered IAA metabolite profiles using multivariate data analysis. Finally, we explored the correlation between IAA metabolite profiles and IAA-related phenotypes. The developed rapid analysis of large numbers of samples (>100 samples d(-1)) is a valuable tool to screen for novel regulators of auxin metabolism and homeostasis among large collections of genotypes.

BACKGROUND: Coronary artery ectasia (CAE) is not an uncommon clinical condition, which could be associated with adverse outcome. The exact pathophysiology of the disease is poorly understood and is commonly interpreted as a variant of atherosclerosis. In this study, we sought to undertake lipidomic profiling of a group of CAE patients in an attempt to achieve better understanding of its disturbed metabolism.

METHODS: Untargeted lipid profiling and complementary modelling strategies were employed to compare serum samples from 16 patients with CAE (mean age 63.5±10.1years, 6 female) and 26 controls with normal smooth coronary arteries (mean age 59.2±6.6years and 7 female). Sample preparation, LC-MS analysis and metabolite identification were performed at the Swedish Metabolomics Centre, Umeå, Sweden.

RESULTS: Phosphatidylcholine levels were significantly distorted in the CAE patients (p=0.001-0.04). Specifically, 16-carbon fatty acyl chain phosphatidylcholines (PC) were detected in lower levels. Similarly, 11 meioties of Sphyngomyelin (SM) species were detected at lower concentrations (p=0.000001-0.01) in the same group. However, only three metabolites were significantly higher in the pure CAE subgroup (6 patients) when compared with the 10 mixed CAE patients (two meioties of SM species and one of PC). Atherosclerosis risk factors were not different between groups.

CONCLUSION: This is the first lipid profiling study reported in coronary artery ectasia. While the lower concentration and dysregulation of sphyngomyelin suggests an evidence for premature apoptosis, that of phosphatidylcholines suggests perturbed fatty acid elongation/desaturation, thus may be indicative of non-atherogenic process in CAE.

Introduction: Neurodegenerative parkinsonian syndromes have significant clinical and pathological overlap, making early diagnosis difficult. Cerebrospinal fluid (CSF) biomarkers may aid the differentiation of these disorders, but other than a-synuclein and neurofilament light chain protein, which have limited diagnostic power, specific protein biomarkers remain elusive. Objectives: To study disease mechanisms and identify possible CSF diagnostic biomarkers through discovery proteomics, which discriminate parkinsonian syndromes from healthy controls. Methods: CSF was collected consecutively from 134 participants; Parkinson's disease (n = 26), atypical parkinsonian syndromes (n = 78, including progressive supranuclear palsy (n = 36), multiple system atrophy (n = 28), corticobasal syndrome (n = 14)), and elderly healthy controls (n = 30). Participants were divided into a discovery and a validation set for analysis. The samples were subjected to tryptic digestion, followed by liquid chromatography-mass spectrometry analysis for identification and relative quantification by isobaric labelling. Candidate protein biomarkers were identified based on the relative abundances of the identified tryptic peptides. Their predictive performance was evaluated by analysis of the validation set. Results: 79 tryptic peptides, derived from 26 proteins were found to differ significantly between atypical parkinsonism patients and controls. They included acute phase/inflammatory markers and neuronal/synaptic markers, which were respectively increased or decreased in atypical parkinsonism, while their levels in PD subjects were intermediate between controls and atypical parkinsonism. Conclusion: Using an unbiased proteomic approach, proteins were identified that were able to differentiate atypical parkinsonian syndrome patients from healthy controls. Our study indicates that markers that may reflect neuronal function and/or plasticity, such as the amyloid precursor protein, and inflammatory markers may hold future promise as candidate biomarkers in parkinsonism.

It is challenging to measure dietary exposure with techniques that are both accurate and applicable to free-living individuals. We performed a cross-over intervention, with 24 healthy individuals, to capture the acute metabolic response of a cereal breakfast (CB) and an egg and ham breakfast (EHB). Fasting and postprandial urine samples were analyzed using H-1 nuclear magnetic resonance (NMR) spectroscopy and multivariate data analysis. Metabolic profiles were distinguished in relation to ingestion of either CB or EHB. Phosphocreatine/creatine and citrate were identified at higher concentrations after consumption of EHB. Beverage consumption (i.e., tea or coffee) could clearly be seen in the data. 2-furoylglycine and 5-hydroxymethyl-2-furoic acid - potential biomarkers for coffee consumption were identified at higher concentrations in coffee drinkers. Thus H-1 NMR urine metabolomics is applicable in the characterization of acute metabolic fingerprints from meal consumption and in the identification of metabolites that may serve as potential biomarkers.

The study of postprandial metabolism is relevant for understanding metabolic diseases and characterizing personal responses to diet. We combined three analytical platforms – gas chromatography-mass spectrometry (GC-MS), liquid chromatography-mass spectrometry (LC-MS) and nuclear magnetic resonance (NMR) – to validate a multi-platform approach for characterizing individual variation in the postprandial state. We analyzed the postprandial plasma metabolome by introducing, at three occasions, meal challenges on a usual diet, and 1.5 years later, on a modified background diet. The postprandial response was stable over time and largely independent of the background diet as revealed by all three analytical platforms. Coverage of the metabolome between NMR and GC-MS included more polar metabolites detectable only by NMR and more hydrophobic compounds detected by GC-MS. The variability across three separate testing occasions among the identified metabolites was in the range of 1.1–86% for GC-MS and 0.9–42% for NMR in the fasting state at baseline. For the LC-MS analysis, the coefficients of variation of the detected compounds in the fasting state at baseline were in the range of 2–97% for the positive and 4–69% for the negative mode. Multivariate analysis (MVA) of metabolites detected with GC-MS revealed that for both background diets, levels of postprandial amino acids and sugars increased whereas those of fatty acids decreased at 0.5 h after the meal was consumed, reflecting the expected response to the challenge meal. MVA of NMR data revealed increasing postprandial levels of amino acids and other organic acids together with decreasing levels of acetoacetate and 3-hydroxybutanoic acid, also independent of the background diet. Together these data show that the postprandial response to the same challenge meal was stable even though it was tested 1.5 years apart, and that it was largely independent of background diet. This work demonstrates the efficacy of a multi-platform metabolomics approach followed by multivariate and univariate data analysis for a broad-scale screen of the individual metabolome, particularly for studies using repeated measures to determine dietary response phenotype.

BACKGROUND: Recently a lipidomics approach was able to identify perturbed fatty acyl chain (FAC) and sphingolipid moieties that could stratify patients according to the severity of coronary calcification, a form of subclinical atherosclerosis. Nevertheless, these findings have not yet been reproduced before generalising their application. The aim of this study was to evaluate the reproducibility of lipidomics approaches by replicating previous lipidomic findings in groups of patients with calcific coronary artery disease (CCAD).

METHODS: Patients were separated into the following groups based on their calcium score (CS); no calcification (CS: 0; n=26), mild calcification (CS: 1-250; n=27) and severe calcification (CS: >250; n=17). Two serum samples were collected from each patient and used for comparative analyses by 2 different laboratories, in different countries and time points using liquid chromatography coupled to mass spectrometry untargeted lipidomics methods.

RESULTS: Six identical metabolites differentiated patients with severe coronary artery calcification from those with no calcification were found by both laboratories independently. Additionally, relative intensities from the two analyses demonstrated high correlation coefficients. Phosphatidylcholine moieties with 18-carbon FAC were identified in lower intensities and 20:4 FAC in higher intensities in the serum of diseased group. Moreover, 3 common sphingomyelins were detected.

CONCLUSION: This is the first interlaboratory reproducibility study utilising lipidomics applications in general and specifically in patients with CCAD. Lipid profiling applications in patients with CCAD are very reproducible in highly specialised and experienced laboratories and could be applied in clinical practice in order to spare patients diagnostic radiation.

The prognosis for diffuse large B-cell lymphoma (DLBCL) patients with early relapse or refractory disease is dismal. To determine if clinical outcome correlated to diverse serum metabolomic profiles, we used H-1 nuclear magnetic resonance (NMR) spectroscopy and compared two groups of DLBCL patients treated with immunochemotherapy: i) refractory/early relapse (REF/REL; n=27) and ii) long-term progression-free (CURED; n=60). A supervised multivariate analysis showed a separation between the groups. Among discriminating metabolites higher in the REF/REL group were the amino acids lysine and arginine, the degradation product cadaverine and a compound in oxidative stress (2-hydroxybutyrate). In contrast, the amino acids aspartate, valine and ornithine, and a metabolite in the glutathione cycle, pyroglutamate, were higher in CURED patients. Together, our data indicate that NMR-based serum metabolomics can identify a signature for DLBCL patients with high-risk of failing immunochemotherapy, prompting for larger validating studies which could lead to more individualized treatment of this disease.