Structural and Enzymatic characterization of the lactonase SisLac from Sulfolobus islandicus

Background

A new member of the Phosphotriesterase-Like Lactonases (PLL) family from the hyperthermophilic archeon Sulfolobus islandicus (SisLac) has been characterized. SisLac is a native lactonase that exhibits a high promiscuous phosphotriesterase activity. SisLac thus represents a promising target for engineering studies, exhibiting both detoxification and bacterial quorum quenching abilities, including human pathogens such as Pseudomonas aeruginosa.

Methodology/Principal Findings

Here, we describe the substrate specificity of SisLac, providing extensive kinetic studies performed with various phosphotriesters, esters, N-acyl-homoserine lactones (AHLs) and other lactones as substrates. Moreover, we solved the X-ray structure of SisLac and structural comparisons with the closely related SsoPox structure highlighted differences in the surface salt bridge network and the dimerization interface. SisLac and SsoPox being close homologues (91% sequence identity), we undertook a mutational study to decipher these structural differences and their putative consequences on the stability and the catalytic properties of these proteins.

Conclusions/Significance

We show that SisLac is a very proficient lactonase against aroma lactones and AHLs as substrates. Hence, data herein emphasize the potential role of SisLac as quorum quenching agent in Sulfolobus. Moreover, despite the very high sequence homology with SsoPox, we highlight key epistatic substitutions that influence the enzyme stability and activity.     

Activation of human mitochondrial lysyl-tRNA synthetase upon maturation of its premitochondrial precursor

The cytoplasmic and mitochondrial species of human lysyl-tRNA synthetase are encoded by a single gene by means of alternative splicing of the KARS1 gene. The cytosolic enzyme possesses a eukaryote-specific N-terminal polypeptide extension that confers on the native enzyme potent tRNA binding properties required for the vectorial transfer of tRNA from the synthetase to elongation factor EF1A within the eukaryotic translation machinery. The mitochondrial enzyme matures from its precursor upon being targeted to that organelle. To understand how the cytosolic and mitochondrial enzymes are adapted to participate in two distinct translation machineries, of eukaryotic or bacterial origin, we characterized the mitochondrial LysRS species. Here we report that cleavage of the precursor of mitochondrial LysRS leads to a mature enzyme with reduced tRNA binding properties compared to those of the cytoplasmic counterpart. This adaptation mechanism may prevent inhibition of translation through sequestration of lysyl-tRNA on the synthetase in a compartment where the bacterial-like elongation factor EF-Tu could not assist in its dissociation from the synthetase. We also observed that the RxxxKRxxK tRNA-binding motif of mitochondrial LysRS is not functional in the precursor form of that enzyme and becomes operational after cleavage of the mitochondrial targeting sequence. The finding that maturation of the precursor is needed to reveal the potent tRNA binding properties of this enzyme has strong implications for the spatiotemporal regulation of its activities and is consistent with previous studies suggesting that the only LysRS species able to promote packaging of tRNA(Lys) into HIV-1 viral particles is the mature form of the mitochondrial enzyme.     

Automatic classification of protein structures relying on similarities between alignments

ABSTRACT: BACKGROUND: Identification of protein structural cores requires isolation of sets of proteins all sharing a same subset of structural motifs. In the context of ever growing number of available 3D protein structures, standard and automatic clustering algorithms require adaptations so as to allow for efficient identification of such sets of proteins. RESULTS: When considering a pair of 3D structures, they are stated as similar or not according to the local similarities of their matching substructures in a structural alignment. This binary relation can be represented in a graph of similarities where a node represents a 3D protein structure and an edge states that two 3D protein structures are similar. Therefore, the classification of proteins into structural families can be viewed as graph clustering task. Unfortunately, because such a graph encodes only pairwise similarity information, clustering algorithms may group in the same cluster a subset of 3D structures that do not share a common substructure. To overcome this drawback we first define a ternary similarity on a triple of 3D structures as a constraint to be satisfied by the graph of similarities. Such a ternary constraint takes into account similarities between pairwise alignments, so as to ensure that the three involved protein structures do have some common substructure. We propose hereunder a modification algorithm that eliminates edges from the original graph of similarities and outputs a reduced graph in which no ternary constraints are violated. Our proposition is then first to build a graph of similarities, then to reduce the graph according to the modification algorithm, and finally to apply to the reduced graph a standard graph clustering algorithm. We applied this method to ASTRAL-40 non-redundant protein domains, identifying significant pairwise similarities with Yakusa, a program devised for rapid 3D structure alignments. CONCLUSIONS: We show that filtering similarities prior to standard graph based clustering process by applying ternary similarity constraints i) improves the separation of proteins of different classes and consequently ii) improves the classification quality of standard graph based clustering algorithms according to the reference classification SCOP.     

New insights into bacterial adaptation through in vivo and in silico experimental evolution

Microbiology research has recently undergone major developments that have led to great progress towards obtaining an integrated view of microbial cell function. Microbial genetics, high-throughput technologies and systems biology have all provided an improved understanding of the structure and function of bacterial genomes and cellular networks. However, integrated evolutionary perspectives are needed to relate the dynamics of adaptive changes to the phenotypic and genotypic landscapes of living organisms. Here, we review evolution experiments, carried out both in vivo with microorganisms and in silico with artificial organisms, that have provided insights into bacterial adaptation and emphasize the potential of bacterial regulatory networks to evolve.