Bioinformatics and molecular modeling in glycobiology

The field of glycobiology is concerned with the study of the structure, properties, and biological functions of the family of biomolecules called carbohydrates. Bioinformatics for glycobiology is a particularly challenging field, because carbohydrates exhibit a high structural diversity and their chains are often branched. Significant improvements in experimental analytical methods over recent years have led to a tremendous increase in the amount of carbohydrate structure data generated. Consequently, the availability of databases and tools to store, retrieve and analyze these data in an efficient way is of fundamental importance to progress in glycobiology. In this review, the various graphical representations and sequence formats of carbohydrates are introduced, and an overview of newly developed databases, the latest developments in sequence alignment and data mining, and tools to support experimental glycan analysis are presented. Finally, the field of structural glycoinformatics and molecular modeling of carbohydrates, glycoproteins, and protein–carbohydrate interaction are reviewed

Guidelines for the use and interpretation of assays for monitoring autophagy (4th edition)1.

In 2008, we published the first set of guidelines for standardizing research in autophagy. Since then, this topic has received increasing attention, and many scientists have entered the field. Our knowledge base and relevant new technologies have also been expanding. Thus, it is important to formulate on a regular basis updated guidelines for monitoring autophagy in different organisms. Despite numerous reviews, there continues to be confusion regarding acceptable methods to evaluate autophagy, especially in multicellular eukaryotes. Here, we present a set of guidelines for investigators to select and interpret methods to examine autophagy and related processes, and for reviewers to provide realistic and reasonable critiques of reports that are focused on these processes. These guidelines are not meant to be a dogmatic set of rules, because the appropriateness of any assay largely depends on the question being asked and the system being used. Moreover, no individual assay is perfect for every situation, calling for the use of multiple techniques to properly monitor autophagy in each experimental setting. Finally, several core components of the autophagy machinery have been implicated in distinct autophagic processes (canonical and noncanonical autophagy), implying that genetic approaches to block autophagy should rely on targeting two or more autophagy-related genes that ideally participate in distinct steps of the pathway. Along similar lines, because multiple proteins involved in autophagy also regulate other cellular pathways including apoptosis, not all of them can be used as a specific marker for bona fide autophagic responses. Here, we critically discuss current methods of assessing autophagy and the information they can, or cannot, provide. Our ultimate goal is to encourage intellectual and technical innovation in the field

Metabolic responses of clams, Ruditapes decussatus and Ruditapes philippinarum, to short-term exposure to lead and zinc

This study investigated the effects of 48h heavy metal exposure upon the metabolic profiles of Ruditapes decussatus and Ruditapes philippinarum using 1H NMR metabolomics. Both species were exposed to increasing concentrations of lead nitrate (10, 40, 60 and 100μg/L) and zinc chloride (20, 50, 100 and 150μg/L), under laboratory conditions. ICP-OES analysis was further performed on the clams' samples in order to verify the occurrence of heavy metal bioaccumulation. With respect to the controls, the metabolic profiles of treated R. decussatus exhibited higher levels of organic osmolytes and lower contents of free amino acids. An opposite behavior was shown by R. philippinarum. In terms of heavy metal, the exposure effects were more evident in the case of Pb rather than Zn. These findings show that NMR-based metabolomics has the required sensitivity and specificity for the identification of metabolites that can act as sensitive indicators of contaminant-induced stres

A NMR metabolomics study of the ripening process of the Fiore Sardo cheese produced with autochthonous adjunct cultures

Fiore Sardo (FS) is a traditional Italian raw ewe’s milk cheese carrying a Protected Designation of Origin (PDO). This study investigated the kinetic of FS cheese ripening by physicochemical parameters, microbial counting, and NMR metabolomics using aqueous extracts. Four Fiore Sardo cheeses, manufactured from milk with deliberately added autochthonous lactic acid bacteria (LAB) or commercial starters were studied during a period of 90 days of ripening. Major differences in the metabolic profiles were observed amongst the samples as a function of the adjunct culture utilized. 1H NMR metabolomics in combination with multivariate data analysis was able to classify cheese samples on the basis of their maturation age and the type of added cultures. These findings lay the metabolic basis for the authentication of Fiore Sardo cheese produced in compliance with PDO specifications which allow the use of only native LAB cultures