SelGenAmic: An Algorithm for Selenoprotein Gene Assembly

Characterization and Quantification of Selenoprotein P: Challenges to Mass Spectrometry

Selenoprotein P (SELENOP) is an emerging marker of the nutritional status of selenium and of various diseases, however, its chemical characteristics still need to be investigated and methods for its accurate quantitation improved. SELENOP is unique among selenoproteins, as it contains multiple genetically encoded SeCys residues, whereas all the other characterized selenoproteins contain just one. SELENOP occurs in the form of multiple isoforms, truncated species and post-translationally modified variants which are relatively poorly characterized. The accurate quantification of SELENOP is contingent on the availability of specific primary standards and reference methods. Before recombinant SELENOP becomes available to be used as a primary standard, careful investigation of the characteristics of the SELENOP measured by electrospray MS and strict control of the recoveries at the various steps of the analytical procedures are strongly recommended. This review critically discusses the state-of-the-art of analytical approaches to the characterization and quantification of SELENOP. While immunoassays remain the standard for the determination of human and animal health status, because of their speed and simplicity, mass spectrometry techniques offer many attractive and complementary features that are highlighted and critically evaluated.

Bioinformatics of Selenoproteins

Significance: Bioinformatics has brought important insights into the field of selenium research. The progress made in the development of computational tools in the last two decades, coordinated with growing genome resources, provided new opportunities to study selenoproteins. The present review discusses existing tools for selenoprotein gene finding and other bioinformatic approaches to study the biology of selenium. Recent Advances: The availability of complete selenoproteomes allowed assessing a global distribution of the use of selenocysteine (Sec) across the tree of life, as well as studying the evolution of selenoproteins and their biosynthetic pathway. Beyond gene identification and characterization, human genetic variants in selenoprotein genes were used to examine adaptations to selenium levels in diverse human populations and to estimate selective constraints against gene loss. Critical Issues: The synthesis of selenoproteins is essential for development in mice. In humans, several mutations in selenoprotein genes have been linked to rare congenital disorders. And yet, the mechanism of Sec insertion and the regulation of selenoprotein synthesis in mammalian cells are not completely understood. Future Directions: Omics technologies offer new possibilities to study selenoproteins and mechanisms of Sec incorporation in cells, tissues, and organisms.

Bioinformatics of Metalloproteins and Metalloproteomes

Trace metals are inorganic elements that are required for all organisms in very low quantities. They serve as cofactors and activators of metalloproteins involved in a variety of key cellular processes. While substantial effort has been made in experimental characterization of metalloproteins and their functions, the application of bioinformatics in the research of metalloproteins and metalloproteomes is still limited. In the last few years, computational prediction and comparative genomics of metalloprotein genes have arisen, which provide significant insights into their distribution, function, and evolution in nature. This review aims to offer an overview of recent advances in bioinformatic analysis of metalloproteins, mainly focusing on metalloprotein prediction and the use of different metals across the tree of life. We describe current computational approaches for the identification of metalloprotein genes and metal-binding sites/patterns in proteins, and then introduce a set of related databases. Furthermore, we discuss the latest research progress in comparative genomics of several important metals in both prokaryotes and eukaryotes, which demonstrates divergent and dynamic evolutionary patterns of different metalloprotein families and metalloproteomes. Overall, bioinformatic studies of metalloproteins provide a foundation for systematic understanding of trace metal utilization in all three domains of life.