The draft genome of Andean Rhodopseudomonas sp. strain AZUL predicts genome plasticity and adaptation to chemical homeostasis.

The genus Rhodopseudomonas comprises purple non-sulfur bacteria with extremely versatile metabolisms. Characterization of several strains revealed that each is a distinct ecotype highly adapted to its specific micro-habitat. Here we present the sequencing, genomic comparison and functional annotation of AZUL, a Rhodopseudomonas strain isolated from a high altitude Andean lagoon dominated by extreme conditions and fluctuating levels of chemicals. Average nucleotide identity (ANI) analysis of 39 strains of this genus showed that the genome of AZUL is 96.2% identical to that of strain AAP120, which suggests that they belong to the same species. ANI values also show clear separation at the species level with the rest of the strains, being more closely related to R. palustris. Pangenomic analyses revealed that the genus Rhodopseudomonas has an open pangenome and that its core genome represents roughly 5 to 12% of the total gene repertoire of the genus. Functional annotation showed that AZUL has genes that participate in conferring genome plasticity and that, in addition to sharing the basal metabolic complexity of the genus, it is also specialized in metal and multidrug resistance and in responding to nutrient limitation. Our results also indicate that AZUL might have evolved to use some of the mechanisms involved in resistance as redox reactions for bioenergetic purposes. Most of those features are shared with strain AAP120, and mainly involve the presence of additional orthologs responsible for the mentioned processes. Altogether, our results suggest that AZUL, one of the few bacteria from its habitat with a sequenced genome, is highly adapted to the extreme and changing conditions that constitute its niche.

Computational Functional Analysis of Lipid Metabolic Enzymes.

The computational analysis of enzymes that participate in lipid metabolism has both common and unique challenges when compared to the whole protein universe. Some of the hurdles that interfere with the functional annotation of lipid metabolic enzymes that are common to other pathways include the definition of proper starting datasets, the construction of reliable multiple sequence alignments, the definition of appropriate evolutionary models, and the reconstruction of phylogenetic trees with high statistical support, particularly for large datasets. Most enzymes that take part in lipid metabolism belong to complex superfamilies with many members that are not involved in lipid metabolism. In addition, some enzymes that do not have sequence similarity catalyze similar or even identical reactions. Some of the challenges that, albeit not unique, are more specific to lipid metabolism refer to the high compartmentalization of the routes, the catalysis in hydrophobic environments and, related to this, the function near or in biological membranes.In this work, we provide guidelines intended to assist in the proper functional annotation of lipid metabolic enzymes, based on previous experiences related to the phospholipase D superfamily and the annotation of the triglyceride synthesis pathway in algae. We describe a pipeline that starts with the definition of an initial set of sequences to be used in similarity-based searches and ends in the reconstruction of phylogenies. We also mention the main issues that have to be taken into consideration when using tools to analyze subcellular localization, hydrophobicity patterns, or presence of transmembrane domains in lipid metabolic enzymes.

Analysis of triglyceride synthesis unveils a green algal soluble diacylglycerol acyltransferase and provides clues to potential enzymatic components of the chloroplast pathway.

BACKGROUND: Microalgal triglyceride (TAG) synthesis has attracted considerable attention. Particular emphasis has been put towards characterizing the algal homologs of the canonical rate-limiting enzymes, diacylglycerol acyltransferase (DGAT) and phospholipid:diacylglycerol acyltransferase (PDAT). Less work has been done to analyze homologs from a phylogenetic perspective. In this work, we used HMMER iterative profiling and phylogenetic and functional analyses to determine the number and sequence characteristics of algal DGAT and PDAT, as well as related sequences that constitute their corresponding superfamilies. We included most algae with available genomes, as well as representative eukaryotic and prokaryotic species. RESULTS: Amongst our main findings, we identified a novel clade of DGAT1-like proteins exclusive to red algae and glaucophyta and a previously uncharacterized subclade of DGAT2 proteins with an unusual number of transmembrane segments. Our analysis also revealed the existence of a novel DGAT exclusive to green algae with moderate similarity to plant soluble DGAT3. The DGAT3 clade shares a most recent ancestor with a group of uncharacterized proteins from cyanobacteria. Subcellular targeting prediction suggests that most green algal DGAT3 proteins are imported to the chloroplast, evidencing that the green algal chloroplast might have a soluble pathway for the de novo synthesis of TAGs. Heterologous expression of C. reinhardtii DGAT3 produces an increase in the accumulation of TAG, as evidenced by thin layer chromatography. CONCLUSIONS: Our analysis contributes to advance in the knowledge of complex superfamilies involved in lipid metabolism and provides clues to possible enzymatic players of chloroplast TAG synthesis.