Equine maternal aging affects the metabolomic profile of oocytes and follicular cells during different maturation time points

Correlation in the broadest sense is a measure of an association between variables. In correlated data, the change in the magnitude of 1 variable is associated with a change in the magnitude of another variable, either in the same (positive correlation) or in the opposite (negative correlation) direction. Most often, the term correlation is used in the context of a linear relationship between 2 continuous variables and expressed as Pearson product-moment correlation. The Pearson correlation coefficient is typically used for jointly normally distributed data (data that follow a bivariate normal distribution). For nonnormally distributed continuous data, for ordinal data, or for data with relevant outliers, a Spearman rank correlation can be used as a measure of a monotonic association. Both correlation coefficients are scaled such that they range from -1 to +1, where 0 indicates that there is no linear or monotonic association, and the relationship gets stronger and ultimately approaches a straight line (Pearson correlation) or a constantly increasing or decreasing curve (Spearman correlation) as the coefficient approaches an absolute value of 1. Hypothesis tests and confidence intervals can be used to address the statistical significance of the results and to estimate the strength of the relationship in the population from which the data were sampled. The aim of this tutorial is to guide researchers and clinicians in the appropriate use and interpretation of correlation coefficients.

Metabolite profiling in biomarker discovery, enzyme substrate assignment, drug activity/specificity determination, and basic metabolic research requires new data preprocessing approaches to correlate specific metabolites to their biological origin. Here we introduce an LC/MS-based data analysis approach, XCMS, which incorporates novel nonlinear retention time alignment, matched filtration, peak detection, and peak matching. Without using internal standards, the method dynamically identifies hundreds of endogenous metabolites for use as standards, calculating a nonlinear retention time correction profile for each sample. Following retention time correction, the relative metabolite ion intensities are directly compared to identify changes in specific endogenous metabolites, such as potential biomarkers. The software is demonstrated using data sets from a previously reported enzyme knockout study and a large-scale study of plasma samples. XCMS is freely available under an open-source license at http://metlin.scripps.edu/download/.

As knowledge of cell metabolism has advanced, glutamine has been considered an important amino acid that supplies carbon and nitrogen to fuel biosynthesis. A recent study provided a new perspective on mitochondrial glutamine metabolism, offering mechanistic insights into metabolic adaptation during tumor hypoxia, the emergence of drug resistance, and glutaminolysis-induced metabolic reprogramming and presenting metabolic strategies to target glutamine metabolism in cancer cells. In this review, we introduce the various biosynthetic and bioenergetic roles of glutamine based on the compartmentalization of glutamine metabolism to explain why cells exhibit metabolic reliance on glutamine. Additionally, we examined whether glutamine derivatives contribute to epigenetic regulation associated with tumorigenesis. In addition, in discussing glutamine transporters, we propose a metabolic target for therapeutic intervention in cancer. Insights into how the amino acid glutamine powers cellular metabolism could pave the way for effective therapeutic strategies for ‘starving’ tumor cells. Healthy cells can manufacture enough glutamine to sustain normal function, but cancerous growth creates heavier demand for this important molecule. Jung Min Han and colleagues at Yonsei University in Incheon, South Korea have reviewed the various cellular functions of glutamine, and discuss opportunities to cut off supply and thereby derail tumor proliferation. Glutamine serves as a building block both for amino acids and nucleic acids, and is also consumed during mitochondrial energy production. Several groups are exploring the feasibility of inactivating glutamine synthesis or halting cellular uptake of this amino acid as a means of depriving cancer cells of nutrients. A deeper understanding of glutamine’s metabolic functions should accelerate progress on this front.