Using a gas chromatography-mass spectrometry-time of flight technique, we determined major metabolite changes during induction of the carbon-concentrating mechanism in the unicellular green alga Chlamydomonas reinhardtii. In total, 128 metabolites with significant differences between high- and low-CO(2)-grown cells were detected, of which 82 were wholly or partially identified, including amino acids, lipids, and carbohydrates. In a 24-h time course experiment, we show that the amino acids serine and phenylalanine increase transiently while aspartate and glutamate decrease after transfer to low CO(2). The biggest differences were typically observed 3 h after transfer to low-CO(2) conditions. Therefore, we made a careful metabolomic examination at the 3-h time point, comparing low-CO(2) treatment to high-CO(2) control. Five metabolites involved in photorespiration, 11 amino acids, and one lipid were increased, while six amino acids and, interestingly, 21 lipids were significantly lower. Our conclusion is that the metabolic pattern during early induction of the carbon-concentrating mechanism fit a model where photorespiration is increasing.
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http://dx.doi.org/10.1104/pp.110.157651 | DOI Listing |
BMC Plant Biol
January 2025
Department of Integrative Agriculture, College of Agriculture and Veterinary Medicine, United Arab Emirates University, P.O. Box 15551, Al Ain, Abu Dhabi, United Arab Emirates.
This study investigated the effects of non-thermal atmospheric plasma (NTAP) treatment on the growth, chemical composition, and biological activity of geranium (Pelargonium graveolens L'Herit) leaves. NTAP was applied at a frequency of 13.56 MHz, exposure time of 15 s, discharge temperature of 25 °C, and power levels (T1 = 50, T2 = 80, and T3 = 120 W).
View Article and Find Full Text PDFPituitary
January 2025
Departments of Endocrinology, Diabetology and Metabolism, University Hospital Basel, Petersgraben 4, 4031, Basel, Switzerland.
Background: Arginine infusion stimulates copeptin secretion, a surrogate marker of arginine vasopressin (AVP), thereby serving as a diagnostic test in the differential diagnosis of suspected AVP deficiency (AVP-D). Yet, the precise mechanism underlying the stimulatory effect of arginine on the vasopressinergic system remains elusive. Arginine plays a significant role in the urea cycle and increases the production of urea.
View Article and Find Full Text PDFMetabolomics
January 2025
Center for Child, Adolescent and Maternal Health Research, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland.
Introduction: Preeclampsia (PE) is a common vascular pregnancy disorder affecting maternal and fetal metabolism with severe immediate and long-term consequences in mothers and infants. During pregnancy, metabolites in the maternal circulation pass through the placenta to the fetus. Meconium, a first stool of the neonate, offers a view to maternal and fetoplacental unit metabolism and could add to knowledge on the effects of PE on the fetus and newborn.
View Article and Find Full Text PDFMetabolomics
January 2025
Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
Background: Gestational exposure to non-persistent endocrine-disrupting chemicals (EDCs) may be associated with adverse pregnancy outcomes. While many EDCs affect the endocrine system, their effects on endocrine-related metabolic pathways remain unclear. This study aims to explore the global metabolome changes associated with EDC biomarkers at delivery.
View Article and Find Full Text PDFSci Rep
January 2025
Center for Cancer Immunotherapy and Immunobiology, Kyoto University Graduate School of Medicine, Kyoto, Japan.
Menstrual pain affects women's quality of life and productivity, yet objective molecular markers for its severity have not been established owing to the variability in blood levels and chemical properties of potential markers such as plasma steroid hormones, lipid mediators, and hydrophilic metabolites. To address this, we conducted a metabolomics study using five analytical methods to identify biomarkers that differentiate menstrual pain severity. This study included 20 women, divided into mild (N = 12) and severe (N = 8) pain groups based on their numerical pain rating scale.
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