Residual toxins on aquatic animals in the Pacific areas: Current findings and potential health effects

Mitochondrial toxic prediction of marine alga toxins using a predictive model based on feature coupling and ensemble learning algorithms

Alga toxins have recently emerged as environmental risk factors to multiple human health issues. Mitochondrial toxicity is an essential element in the field of ecotoxicology, it is necessary to screen and manage mitochondrial toxicants from common alga toxins. To overcome the limitations of traditional animal and cell experiments, computational toxicology is increasingly emphasized. In this study, all the publicly available datasets were compiled to create the largest mitochondrial toxicity dataset to date, establishing a robust and high-performance QSAR screening model. The model couples and filters 12 molecular fingerprints and 318 descriptors as features, capturing more information about molecular structure and properties. By comparing 8 machine learning algorithms and using a weighted soft voting method to integrate the two optimal algorithms, we established 108 prediction models and identified the best ensemble learning model MACCS_LK for screening and defining its application domain. Additionally, the efficacy of MACCS fingerprints in representing mitochondrial toxicants was established, and a mechanistic analysis of the identified model based on the SHAP method and 11 structural alerts uncovered in this study was conducted, enhancing the interpretability of this model. This study highlights the key roles of lipophilic structures such as aromatic rings and long hydrocarbon chains and their related physicochemical properties in predicting toxicity outcomes. The mitochondrial toxicity of six algal toxins was predicted by employing this model, and the results indicating that two of them possess mitochondrial toxic effects. This model has high reliability and accuracy, making it applicable for predicting mitochondrial toxicity of more marine biotoxins.

Electrochemical molecularly imprinted polymer sensor for simple and fast analysis of tetrodotoxin in seafood

Tetrodotoxin (TTX) is a marine biotoxin whose biosynthesis is associated with the pufferfish. Its distribution is primarily focused in Asian and tropical marine areas. Currently, this group of toxins is classified as emerging in Europe, and its presence could be related to climate change. This incidence has prompted the European Union, with the European Food Safety Authority, to establish control and monitoring mechanisms for TTX in marine products in Europe. In this context, the development of analytical tools capable of ensuring the safety of food products, especially seafood and fish, is a crucial task. This study describes the development of a molecularly imprinted polymer (MIP) based electrochemical sensor for the analysis of TTX. The MIP was synthesized through the electropolymerization of a functional monomer, ortho-phenylenediamine in the presence of a dummy template, voglibose. The MIP sensor was constructed on a screen-printed gold electrode and characterized by cyclic voltammetry. Differential pulse voltammetry, using a redox probe ([Fe(CN)6]3-/4-), was used in the analysis protocol. The developed sensor exhibited a linear response between 5.0 μg mL-1 and 25.0 μg mL-1, with a limit of detection of 1.14 μg mL-1. Its high imprinting efficiency conferred outstanding selectivity towards TTX. The sensor's applicability was confirmed through recovery assays on spiked mussel samples, achieving recoveries of 81.0 %, 110.2 %, and 102.5 % for external standard addition at 30.0, 44.0, and 60.0 μg kg-1, respectively, with relative standard deviations below 15 %. These results are comparable to those obtained using Hydrophilic Interaction Liquid Chromatography coupled with Tandem Mass Spectrometry, a validated method carried out by the European Reference Laboratory for Marine Biotoxins. Thus, the MIP sensor represents a portable, simple, and fast tool with essential analytical functionalities for the sampling phase and pre-selection of laboratory samples for analysis.

Unforeseen current and future benefits of uncommon yeast: the Metschnikowia genus

Metschnikowia, the single-cell yeast form, is a genus of 85 species in the Saccharomycetales order that developed in both aquatic and terrestrial ecosystems after being found in 1899. This yeast is commonly used to control microbial populations in many biological and artificial conditions, such as fermentation. However, current study of Metschnikowia is limited to biological control features rather than researching on lucrative sectors such as beverage production, bioconversion manufacturing, cosmetics, and the pharmaceutical industry. This review summarizes numerous possible applications of Metschnikowia in human life, including potential secondary metabolites in industrial fields such as cosmetics and pharmaceuticals. Furthermore, Metschnikowia-yeast interaction is mentioned as a potential area for further exploration in terms of co-cultured microbes as biocontrol. Since Metschnikowia yeast arose in a variety of ecosystems, more discussion will be held regarding the interactions between Metschnikowia and their surroundings, particularly in fruits. Finally, the current regulatory challenges of Metschnikowia-based products are examined, and future research opportunities on Metschnikowia utilization are presented. KEY POINTS: • Utilization of Metschnikowia genus in various human aspects. • Promising secondary metabolites produced by Metschnikowia. • Challenge and opportunity on developing Metschnikowia-based products.