Fumonisin B1 is a mycotoxin produced by Fusarium verticillioides that modifies the membrane properties from animal cells and inhibits complex sphingolipids synthesis through the inhibition of ceramide synthase. The aim of this work was to determine the effect of Fumonisin B1 on the plant plasma membrane when the mycotoxin was added to germinating maize embryos. Fumonisin B1 addition to the embryos diminished plasma membrane fluidity, increased electrolyte leakage, caused a 7-fold increase of sphinganine and a small decrease in glucosylceramide in the plasma membrane, without affecting phytosphingosine levels or fatty acid composition. A 20%–30% inhibition of the plasma membrane H⁺-ATPase activity was observed when embryos were germinated in the presence of the mycotoxin. Such inhibition was only associated to the decrease in glucosylceramide and the addition of exogenous ceramide to the embryos relieved the inhibition of Fumonisin B1. These results indicate that exposure of the maize embryos for 24 h to Fumonisin B1 allowed the mycotoxin to target ceramide synthase at the endoplasmic reticulum, eliciting an imbalance of endogenous sphingolipids. The latter disrupted membrane properties and inhibited the plasma membrane H⁺-ATPase activity. Altogether, these results illustrate the mode of action of the pathogen and a plant defense strategy.

Introduction: Suicide is a significant public health problem, with increased rates in low- and middle-income countries such as Mexico; therefore, suicide prevention is important. Suicide is a complex and multifactorial phenomenon in which biological and social factors are involved. Several studies on the biological mechanisms of suicide have analyzed the proteome of the dorsolateral prefrontal cortex (DLPFC) in people who have died by suicide. The aim of this work was to analyze the protein expression profile in the DLPFC of individuals who died by suicide in comparison to age-matched controls in order to gain information on the molecular basis in the brain of these individuals and the selection of potential biomarkers for the identification of individuals at risk of suicide. In addition, this information was analyzed using machine learning (ML) algorithms to propose a model for predicting suicide.Methods: Brain tissue (Brodmann area 9) was sampled from male cases (n=9) and age-matched controls (n=7). We analyzed the proteomic differences between the groups using two-dimensional polyacrylamide gel electrophoresis and mass spectrometry. Bioinformatics tools were used to clarify the biological relevance of the differentially expressed proteins. In addition, this information was analyzed using machine learning (ML) algorithms to propose a model for predicting suicide.Results: Twelve differentially expressed proteins were also identified (t₁₄ ≤ 0.5). Using Western blotting, we validated the decrease in expression of peroxiredoxin 2 and alpha-internexin in the suicide cases. ML models were trained using densitometry data from the 2D gel images of each selected protein and the models could differentiate between both groups (control and suicide cases).Discussion: Our exploratory pathway analysis highlighted oxidative stress responses and neurodevelopmental pathways as key processes perturbed in the DLPFC of suicides. Regarding ML models, KNeighborsClassifier was the best predicting conditions. Here we show that these proteins of the DLPFC may help to identify brain processes associated with suicide and they could be validated as potential biomarkers of this outcome.