Uncertainty budgeting in fold change determination and implications for non-targeted metabolomics studies in model systems

Ortmayr, Karin; Charwat, Verena; Kasper, Cornelia; Hann, Stephan; Koellensperger, Gunda

doi:10.1039/c6an01342b

Cited by 26 publications

(23 citation statements)

References 40 publications

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“…Compounds in P‐stress treatments were assessed by relative changes in abundance as response ratios, in comparison to a control condition. Twofold change and larger with t test probability limits of p < .05 between P stress and control were considered reliable and significant (Ortmayr, Charwat, Kasper, Hann, & Koellensperger, 2017).…”

Section: Methodsmentioning

confidence: 99%

Transcriptional, metabolic, physiological and developmental responses of switchgrass to phosphorus limitation

Ding

Huertas

Torres‐Jerez

et al. 2020

Plant Cell & Environment

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Knowing how switchgrass (Panicum virgatum L.) responds and adapts to phosphorus (P)-limitation will aid efforts to optimize P acquisition and use in this species for sustainable biomass production. This integrative study investigated the impacts of mild, moderate, and severe P-stress on genome transcription and whole-plant metabolism, physiology and development in switchgrass. P-limitation reduced overall plant growth, increased root/shoot ratio, increased root branching at moderate P-stress, and decreased root diameter with increased density and length of root hairs at severe P-stress. RNA-seq analysis revealed thousands of genes that were differentially expressed under moderate and severe P-stress in roots and/or shoots compared to P-replete plants, with many stress-induced genes involved in transcriptional and other forms of regulation, primary and secondary metabolism, transport, and other processes involved in P-acquisition and homeostasis. Amongst the latter were multiple miRNA399 genes and putative targets of these. Metabolite profiling showed that levels of most sugars and sugar alcohols decreased with increasing P stress, while organic and amino acids increased under mild and moderate P-stress in shoots and roots, although this trend reversed under severe P-stress, especially in shoots.

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Section: Methodsmentioning

confidence: 99%

Transcriptional, metabolic, physiological and developmental responses of switchgrass to phosphorus limitation

Ding

Huertas

Torres‐Jerez

et al. 2020

Plant Cell & Environment

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“…The general biological variability is commonly estimated as approximately 15% [ 31 ], and hence has a major influence on uncertainty. Since the cell is highly complex in terms of its metabolism, controlling the metabolic state during the experiment is vital.…”

Section: Resultsmentioning

confidence: 99%

Comprehensive assessment of measurement uncertainty in 13C-based metabolic flux experiments

et al. 2018

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In the field of metabolic engineering 13C-based metabolic flux analysis experiments have proven successful in indicating points of action. As every step of this approach is affected by an inherent error, the aim of the present work is the comprehensive evaluation of factors contributing to the uncertainty of nonnaturally distributed C-isotopologue abundances as well as to the absolute flux value calculation. For this purpose, a previously published data set, analyzed in the course of a 13C labeling experiment studying glycolysis and the pentose phosphate pathway in a yeast cell factory, was used. Here, for isotopologue pattern analysis of these highly polar metabolites that occur in multiple isomeric forms, a gas chromatographic separation approach with preceding derivatization was used. This rendered a natural isotope interference correction step essential. Uncertainty estimation of the resulting C-isotopologue distribution was performed according to the EURACHEM guidelines with Monte Carlo simulation. It revealed a significant increase for low-abundance isotopologue fractions after application of the necessary correction step. For absolute flux value estimation, isotopologue fractions of various sugar phosphates, together with the assessed uncertainties, were used in a metabolic model describing the upper part of the central carbon metabolism. The findings pinpointed the influence of small isotopologue fractions as sources of error and highlight the need for improved model curation. Graphical abstractᅟ Electronic supplementary materialThe online version of this article (10.1007/s00216-018-1017-7) contains supplementary material, which is available to authorized users.

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“…We used R 2 to evaluate the fit of the model, Q 2 to assess the predictability of the model, and FC to show the importance of each metabolite. FC is a quantitative measure for changes in metabolite concentrations relative to a reference group 41 . A larger absolute value of FC indicates a more significant difference in the average peak area (metabolite intensity) between lung cancer patients and patients with nonmalignant disease as controls.…”

Section: Discussionmentioning

confidence: 99%

The Investigation of the Volatile Metabolites of Lung Cancer From the Microenvironment of Malignant Pleural Effusion

Chen

Tsai

Zhang

et al. 2021

Preprint

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Lung cancer is the leading cause of cancer death. For malignant pleural effusions, pleural fluid cytology is a diagnostic method, but sensitivity is low. Many patients need to undergo invasive diagnostic tests such as thoracoscopic pleural biopsy. Pleural space is an enclosed microenvironment, and the pleural fluid contains metabolites directly released from cancer cells. The objective of this study was to diagnose lung cancer with malignant pleural effusion using the volatilomic profiling method. We recruited lung cancer patients with malignant pleural effusion and patients with nonmalignant diseases with pleural effusion as controls. We analyzed the headspace air of the pleural effusion by gas chromatography-mass spectrometry. We used partial least squares discriminant analysis (PLS-DA) to identify metabolites and the support vector machine (SVM) to establish the prediction model. We split data into a training set (80%) and a testing set (20%) to validate the accuracy. A total of 68 subjects were included in the final analysis. The PLS-DA showed high discrimination with an R2 of 0.95 and Q2 of 0.58. The accuracy of the SVM in the test set was 0.93 (95% CI: 0.66, 0.998), and kappa was 0.85, and the area under the receiver operating characteristic curve was 0.96 (95% CI: 0.86, 1.00). Pathway analysis revealed disturbances in pyruvate metabolism, the tricarboxylic acid, glycolysis, and lysine degradation. The volatile metabolites identified from malignant pleural effusion of lung cancer were primarily methylated alkanes. The pleural effusion contained volatile metabolites that have high accuracy in diagnosing lung cancer with malignant pleural effusion.

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Uncertainty budgeting in fold change determination and implications for non-targeted metabolomics studies in model systems

Cited by 26 publications

References 40 publications

Transcriptional, metabolic, physiological and developmental responses of switchgrass to phosphorus limitation

Transcriptional, metabolic, physiological and developmental responses of switchgrass to phosphorus limitation

Comprehensive assessment of measurement uncertainty in 13C-based metabolic flux experiments

The Investigation of the Volatile Metabolites of Lung Cancer From the Microenvironment of Malignant Pleural Effusion

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