The Role of Gene Duplication in the Divergence of Enzyme Function: A Comparative Approach

Study of two glycosyltransferases related to polysaccharide biosynthesis in Rhodococcus jostii RHA1

The bacterial genus Rhodococcus comprises organisms performing oleaginous behaviors under certain growth conditions and ratios of carbon and nitrogen availability. Rhodococci are outstanding producers of biofuel precursors, where lipid and glycogen metabolisms are closely related. Thus, a better understanding of rhodococcal carbon partitioning requires identifying catalytic steps redirecting sugar moieties to storage molecules. Here, we analyzed two GT4 glycosyl-transferases from Rhodococcus jostii (RjoGlgAb and RjoGlgAc) annotated as α-glucan-α-1,4-glucosyl transferases, putatively involved in glycogen synthesis. Both enzymes were produced in Escherichia coli cells, purified to homogeneity, and kinetically characterized. RjoGlgAb and RjoGlgAc presented the "canonical" glycogen synthase activity and were actives as maltose-1P synthases, although to a different extent. Then, RjoGlgAc is a homologous enzyme to the mycobacterial GlgM, with similar kinetic behavior and glucosyl-donor preference. RjoGlgAc was two orders of magnitude more efficient to glucosylate glucose-1P than glycogen, also using glucosamine-1P as a catalytically efficient aglycon. Instead, RjoGlgAb exhibited both activities with similar kinetic efficiency and preference for short-branched α-1,4-glucans. Curiously, RjoGlgAb presented a super-oligomeric conformation (higher than 15 subunits), representing a novel enzyme with a unique structure-to-function relationship. Kinetic results presented herein constitute a hint to infer on polysaccharides biosynthesis in rhodococci from an enzymological point of view.

Phoenix dactylifera (date palm; Arecaceae) putative lectin homologs: Genome-wide search, architecture analysis, and evolutionary relationship

The date palm, Phoenix dactylifera, is a vital crop in nations in the Middle East and North Africa. The date palm was thought to have outstanding traditional medicinal value because it was abundant in phytochemicals with diverse chemical structures. The date palm's ability to withstand harsh environments could be partly attributed to a class of proteins known as lectins, which are carbohydrate-binding proteins that can bind sugar moieties reversibly and without changing their chemical structures. After scanning the genome of P. dactylifera (GCF 009389715.1), this in silico study discovered 196 possible lectin homologs from 11 different families, some specific to plants. At the same time, others could also be found in other kingdoms of life. Their domain architectures and functional amino acid residues were investigated, and they yielded a 40% true-lectin with known conserved carbohydrate-binding residues. Further, their probable subcellular localization, physiochemical and phylogenetic analyses were also performed. Scanning all putative lectin homologs against the anticancer peptide (ACP) dataset found in the AntiCP2.0 webpage identified 26 genes with protein kinase receptors (Lec-KRs) belonging to 5 lectin families, which are reported to have at least one ACP motif. Our study offers the first account of Phoenix-lectins and their organization that can be used for further structural and functional analysis and investigating their potential as anticancer proteins.

Evolutionary genomics analysis reveals gene expansion and functional diversity of arylalkylamine N-acetyltransferases in the Culicinae subfamily of mosquitoes

Arylalkylamine N-acetyltransferase (aaNAT), considered a potential new insecticide target, catalyzes the acetylation of arylalkylamine substrates such as serotonin and dopamine and, hence, mediates diverse functions in insects. However, the origin of insect aaNATs (iaaNATs) and the evolutionary process that generates multiple aaNATs in mosquitoes remain largely unknown. Here, we have analyzed the genomes of 33 species to explore and expand our understanding of the molecular evolution of this gene family in detail. We show that aaNAT orthologs are present in Bacteria, Cephalochordata, Chondrichthyes, Cnidaria, Crustacea, Mammalia, Placozoa, and Teleoste, as well as those from a number of insects, but are absent in some species of Annelida, Echinozoa, and Mollusca as well as Arachnida. Particularly, more than 10 aaNATs were detected in the Culicinae subfamily of mosquitoes. Molecular evolutionary analysis of aaNAT/aaNAT-like genes in mosquitoes reveals that tandem duplication events led to gene expansion in the Culicinae subfamily of mosquitoes more than 190 million years ago. Further selection analysis demonstrates that mosquito aaNATs evolved under strongly positive pressures that generated functional diversity following gene duplication events. Overall, this study may provide novel insights into the molecular evolution of the aaNAT family in mosquitoes.

The Fate of Duplicated Enzymes in Prokaryotes: The Case of Isomerases

The isomerases are a unique enzymatic class of enzymes that carry out a great diversity of chemical reactions at the intramolecular level. This class comprises about 300 members, most of which are involved in carbohydrate and terpenoid/polyketide metabolism. Along with oxidoreductases and translocases, isomerases are one of the classes with the highest ratio of paralogous enzymes. Due to its relatively small number of members, it is plausible to explore it in greater detail to identify specific cases of gene duplication. Here, we present an analysis at the level of individual isomerases and identify different members that seem to be involved in duplication events in prokaryotes. As was suggested in a previous study, there is no homogeneous distribution of paralogs, but rather they accumulate into a few subcategories, some of which differ between Archaea and Bacteria. As expected, the metabolic processes with more paralogous isomerases have to do with carbohydrate metabolism but also with RNA modification (a particular case involving an rRNA-modifying isomerase is thoroughly discussed and analyzed in detail). Overall, our findings suggest that the most common fate for paralogous enzymes is the retention of the original enzymatic function, either associated with a dosage effect or with differential expression in response to changing environments, followed by subfunctionalization and, to a much lesser degree, neofunctionalization, which is consistent with what has been reported elsewhere.

Function, structure, evolution, regulation of a potent drug target, arylalkylamine N-acetyltransferase

Arylalkylamine N-acetyltransferase (aaNAT) catalyzes the transacetylation of acetyl coenzyme A to arylamines and arylalkylamines. Based on three-dimensional structural information, aaNAT belongs to the GCN5-related N-acetyltransferases superfamily with a conserved acetyl-CoA binding domain (Dyda et al., 2000). By comparison of sequence similarity, aaNAT is usually divided into vertebrate aaNAT (VT-aaNAT) and non-vertebrate aaNAT (NV-aaNAT) (Cazaméa-Catalan et al., 2014). Insects have evolved multiple aaNATs in comparison to mammals, thus more diverse functions are also reflected in insects. This chapter will summarize previous studies on the function, regulation, structure and evolution of aaNAT, and provide insight into future pest management.

Computational prediction of plant metabolic pathways

Uncovering genes encoding enzymes responsible for the biosynthesis of diverse plant metabolites is essential for metabolic engineering and production of plant metabolite-derived medicine. With the availability of multi-omics data for an ever-increasing number of plant species and the development of computational approaches, the metabolic pathways of many important plant compounds can be predicted, complementing a more traditional genetic and/or biochemical approach. Here, we summarize recent progress in predicting plant metabolic pathways using genome, transcriptome, proteome, interactome, and/or metabolome data, and the utility of integrating these data with machine learning to further improve metabolic pathway predictions.

Reconstructing Gene Gains and Losses with BadiRate

Estimating gene gain and losses is paramount to understand the molecular mechanisms underlying adaptive evolution. Despite the advent of high-throughput sequencing, such analyses have been so far hampered by the poor contiguity of genome assemblies. The increasing affordability of long-read sequencing technologies will however revolutionize our capacity to identify gene gains and losses at an unprecedented resolution, even in non-model organisms. To thoroughly exploit all such multigene family variation, the software BadiRate implements a collection of birth-and-death stochastic models, aiming at estimating by maximum likelihood the gene turnover rates along the internal and external branches of a given phylogenetic species tree. Its statistical framework also provides versatility for inferring the gene family content at the internal phylogenetic nodes (and to estimate the minimum number of gene gains and losses in each branch), for statistically contrasting competing hypotheses (e.g., accelerations of the gene turnover rates at pre-defined clades), and for pinpointing gene family expansions or contractions likely driven by natural selection. In this chapter we review the theoretical models implemented in BadiRate and illustrate their applicability by analyzing a hypothetical data set of 14 microbial species.