Complete genome sequence of the hyperthermophilic chemolithoautotroph Pyrolobus fumarii type strain (1A)

Identification of Exoenzymes Secreted by Entomopathogenic Fungus Beauveria pseudobassiana RGM 2184 and Their Effect on the Degradation of Cocoons and Pupae of Quarantine Pest Lobesia botrana

Beauveria pseudobassiana RGM 2184 has shown 80% maximum efficacy against the pest Lobesia botrana in the autumn and winter seasons. This suggests that the strain possesses an interesting battery of enzymes that are cold-adapted to penetrate the thick and hydrophobic cocoon of L. botrana. In this study, screening of the proteolytic, lipolytic, and chitinolytic activity of enzyme extracts secreted by the RGM 2184 strain was carried out in various culture media. The enzyme extracts with the highest activity were subjected to zymography and mass spectrometry. These analyses allowed the identification of two proteases, two lipases, and three chitinases. Comparative analysis indicated that the degree of similarity between these enzymes was substantially reduced when the highest degree of taxonomic relatedness between RGM 2184 and the entomopathogenic fungus strain was at the family level. These results suggest that there is a wide variety of exoenzymes in entomopathogenic fungi species belonging to the order Hypocreales. On the other hand, exoenzyme extract exposure of cocoons and pupae of L. botrana provoked damage at 10 °C. Additionally, an analysis of the amino acid composition of the RGM 2184 exoenzyme grouped them close to the cold-adapted protein cluster. These results support the use of this strain to control pests in autumn and winter. Additionally, these antecedents can form a scaffold for the future characterization of these exoenzymes along with the optimization of the strain’s biocontrol ability by overexpressing them.

Screening of potential genes contributing to the macrocycle drug resistance of C. albicans via microarray analysis

The aim of the present study was to investigate the potential genes involved in drug resistance of Candida albicans (C. albicans) by performing microarray analysis. The gene expression profile of GSE65396 was downloaded from the Gene Expression Omnibus, including a control, 15-min and 45-min macrocyclic compound RF59-treated group with three repeats for each. Following preprocessing using RAM, the differentially expressed genes (DEGs) were screened using the Limma package. Subsequently, the Kyoto Encyclopedia of Genes and Genomes pathways of these genes were analyzed using the Database for Annotation, Visualization and Integrated Discovery. Based on interactions estimated by the Search Tool for Retrieval of Interacting Gene, the protein-protein interaction (PPI) network was visualized using Cytoscape. Subnetwork analysis was performed using ReactomeFI. A total of 154 upregulated and 27 downregulated DEGs were identified in the 15-min treated group, compared with the control, and 235 upregulated and 233 downregulated DEGs were identified in the 45-min treated group, compared with the control. The upregulated DEGs were significantly enriched in the ribosome pathway. Based on the PPI network, PRP5, RCL1, NOP13, NOP4 and MRT4 were the top five nodes in the 15-min treated comparison. GIS2, URA3, NOP58, ELP3 and PLP7 were the top five nodes in the 45-min treated comparison, and its subnetwork was significantly enriched in the ribosome pathway. The macrocyclic compound RF59 had a notable effect on the ribosome and its associated pathways of C. albicans. RCL1, NOP4, MRT4, GIS2 and NOP58 may be important in RF59-resistance.

Genome-Scale Modeling of Thermophilic Microorganisms

Thermophilic microorganisms are of increasing interest for many industries as their enzymes and metabolisms are highly efficient at elevated temperatures. However, their metabolic processes are often largely different from their mesophilic counterparts. These differences can lead to metabolic engineering strategies that are doomed to fail. Genome-scale metabolic modeling is an effective and highly utilized way to investigate cellular phenotypes and to test metabolic engineering strategies. In this review we chronicle a number of thermophilic organisms that have recently been studied with genome-scale models. The microorganisms spread across archaea and bacteria domains, and their study gives insights that can be applied in a broader context than just the species they describe. We end with a perspective on the future development and applications of genome-scale models of thermophilic organisms.

Pyrodictium delaneyi sp. nov., a hyperthermophilic autotrophic archaeon that reduces Fe(III) oxide and nitrate

A hyperthermophilic, autotrophic iron and nitrate reducer, strain Su06T, was isolated from an active deep-sea hydrothermal vent chimney on the Endeavour Segment in the north-eastern Pacific Ocean. It was obligately anaerobic, hydrogenotrophic and reduced Fe(III) oxide to magnetite and NO3- to N2. Phylogenetic analysis based on 16S rRNA gene sequences indicated that the strain was more than 97 % similar to other species of the genera Pyrodictium and Hyperthermus. Therefore, overall genome relatedness index analyses were performed to establish whether strain Su06T represents a novel species. For each analysis, strain Su06T was most similar to Pyrodictium occultum PL-19T. Relative to this strain, the average nucleotide identity score for strain Su06T was 72 %, the genome-to-genome direct comparison score was 13-19 % and the species identification score at the protein level was 89 %. For each analysis, strain Su06T was below the species delineation cutoff. Based on its whole genome sequence and its unique phenotypic characteristics, strain Su06T is suggested to represent a novel species of the genus Pyrodictium, for which the name Pyrodictium delaneyi is proposed. The type strain is Su06T (=DSM 28599T=ATCC BAA-2559T).

Origin and evolution of the eukaryotic SSU processome revealed by a comprehensive genomic analysis and implications for the origin of the nucleolus

As a nucleolar complex for small-subunit (SSU) ribosomal RNA processing, SSU processome has been extensively studied mainly in Saccharomyces cerevisiae but not in diverse organisms, leaving open the question of whether it is a ubiquitous mechanism across eukaryotes and how it evolved in the course of the evolution of eukaryotes. Genome-wide survey and identification of SSU processome components showed that the majority of all 77 yeast SSU processome proteins possess homologs in almost all of the main eukaryotic lineages, and 14 of them have homologs in archaea but few in bacteria, suggesting that the complex is ubiquitous in eukaryotes, and its evolutionary history began with abundant protein homologs being present in archaea and then a fairly complete form of the complex emerged in the last eukaryotic common ancestor (LECA). Phylogenetic analysis indicated that ancient gene duplication and functional divergence of the protein components of the complex occurred frequently during the evolutionary origin of the LECA from prokaryotes. We found that such duplications not only increased the complex’s components but also produced some new functional proteins involved in other nucleolar functions, such as ribosome biogenesis and even some nonnucleolar (but nuclear) proteins participating in pre-mRNA splicing, implying the evolutionary emergence of the subnuclear compartment—the nucleolus—has occurred in the LECA. Therefore, the LECA harbored not only complicated SSU processomes but also a nucleolus. Our analysis also revealed that gene duplication, innovation, and loss, caused further divergence of the complex during the divergence of eukaryotes.

Phylogeny-driven target selection for large-scale genome-sequencing (and other) projects

Despite the steadily decreasing costs of genome sequencing, prioritizing organisms for sequencing remains important in large-scale projects. Phylogeny-based selection is of interest to identify those organisms whose genomes can be expected to differ most from those that have already been sequenced. Here, we describe a method that infers a phylogenetic scoring independent of which set of organisms has previously been targeted, which is computationally simple and easy to apply in practice. The scoring itself, as well as pre- and post-processing of the data, is illustrated using two real-world examples in which the method has already been applied for selecting targets for genome sequencing. These projects are the JGI CSP Genomic Encyclopedia of Bacteria and Archaea phase I, targeting 1,000 type strains, and, on a smaller-scale, the phylogenomics of the Roseobacter clade. Potential artifacts of the method are discussed and compared to a selection approach based on the taxonomic classification.