EvoMining reveals the origin and fate of natural product biosynthetic enzymes.

Natural products (NPs), or specialized metabolites, are important for medicine and agriculture alike, and for the fitness of the organisms that produce them. NP genome-mining aims at extracting biosynthetic information from the genomes of microbes presumed to produce these compounds. Typically, canonical enzyme sequences from known biosynthetic systems are identified after sequence similarity searches. Despite this being an efficient process, the likelihood of identifying truly novel systems by this approach is low. To overcome this limitation, we previously introduced EvoMining, a genome-mining approach that incorporates evolutionary principles. Here, we release and use our latest EvoMining version, which includes novel visualization features and customizable databases, to analyse 42 central metabolic enzyme families (EFs) conserved throughout Actinobacteria, Cyanobacteria, Pseudomonas and Archaea. We found that expansion-and-recruitment profiles of these 42 families are lineage specific, opening the metabolic space related to 'shell' enzymes. These enzymes, which have been overlooked, are EFs with orthologues present in most of the genomes of a taxonomic group, but not in all. As a case study of canonical shell enzymes, we characterized the expansion and recruitment of glutamate dehydrogenase and acetolactate synthase into scytonemin biosynthesis, and into other central metabolic pathways driving Archaea and Bacteria adaptive evolution. By defining the origin and fate of enzymes, EvoMining complements traditional genome-mining approaches as an unbiased strategy and opens the door to gaining insights into the evolution of NP biosynthesis. We anticipate that EvoMining will be broadly used for evolutionary studies, and for generating predictions of unprecedented chemical scaffolds and new antibiotics. This article contains data hosted by Microreact.

Uso de redes sociales en las revistas científicas de la Universidad de Los Andes, Venezuela / Use of social networks in the scientific journals of the University of Los Andes, Venezuela

Resumen En una sociedad donde las barreras parecen día a día más difusas, las Redes Sociales (RRSS) constituyen uno los principales vehículos de comunicación directo para acceder, compartir, usar y apropiarse de contenidos que hasta hace algún tiempo implicaba mayores labores. El objetivo de este estudio fue ofrecer un diagnóstico sobre la participación en estos canales, como medios adecuados para la divulgación de conocimientos, en cada una de las 90 revistas científicas de la Universidad de Los Andes (ULA), abordado desde una metodología de trabajo de carácter documental, con diseño no experimental-transversal de tipo descriptivo, donde se determinó la presencia -y sus respectivas características- de los objetos de estudio en dos RRSS horizontales-generalistas: Facebook y Twitter, y dos verticales, de contenido y de perfiles profesionales: Youtube y LinkedIn, dadas sus capacidades de apertura y penetración en una parte importante de la población que tiene conexión a la Red. Sin embargo, se percibió que apenas el 22,3 % de las publicaciones periódicas analizadas es miembro de al menos una de estas RRSS, algunas no cuentan con constante actividad y, por tanto, la cifra de suscriptores es corta y su alcance limitado. Se recomienda al personal que allí hace vida académica procurar esfuerzos para alcanzar mejores índices de visibilidad y difusión, así como el registro en más comunidades virtuales y el trabajo constante en el mantenimiento de ellas.

Abstract In a society where barriers seem to be increasingly diffusive, Social Networks seem to be one of the main methods of direct communication to access, share, use and obtain content that at one time implicated hours of research. The objective of this study was to offer a diagnosis about of the participation in these channels, as appropriate means for the dissemination of knowledge, of each of the 90 scientific journals of the University of Los Andes (ULA). The same was approached from a documentary work methodology, with non-experimental-transverse descriptive design, where a presence was determined -along with its respective characteristics- in two horizontal-general Social Networks -such as Facebook and Twitter-, and two vertical Social Networks, one of the this of professional profile -LinkedIn-, and other of contents: Youtube. This is so given the availability and accessibility to a substantial part of the population with access to the internet. Nevertheless, it was perceived that only 22,3% of journals analyzed were members of at least one of this Social Networks. Of these, some are not consistently active and as such, the list of subscribers is short and its accessibility, limited. It is recommended that their respective personnel make a concerted effort to improve their visibility and broadcasting, such as registration in more Social Networks and a constant maintenance of them.

The genome, transcriptome, and proteome of the nematode Steinernema carpocapsae: evolutionary signatures of a pathogenic lifestyle.

The entomopathogenic nematode Steinernema carpocapsae has been widely used for the biological control of insect pests. It shares a symbiotic relationship with the bacterium Xenorhabdus nematophila, and is emerging as a genetic model to study symbiosis and pathogenesis. We obtained a high-quality draft of the nematode's genome comprising 84,613,633 bp in 347 scaffolds, with an N50 of 1.24 Mb. To improve annotation, we sequenced both short and long RNA and conducted shotgun proteomic analyses. S. carpocapsae shares orthologous genes with other parasitic nematodes that are absent in the free-living nematode C. elegans, it has ncRNA families that are enriched in parasites, and expresses proteins putatively associated with parasitism and pathogenesis, suggesting an active role for the nematode during the pathogenic process. Host and parasites might engage in a co-evolutionary arms-race dynamic with genes participating in their interaction showing signatures of positive selection. Our analyses indicate that the consequence of this arms race is better characterized by positive selection altering specific functions instead of just increasing the number of positively selected genes, adding a new perspective to these co-evolutionary theories. We identified a protein, ATAD-3, that suggests a relevant role for mitochondrial function in the evolution and mechanisms of nematode parasitism.

Phylogenomic Analysis of Natural Products Biosynthetic Gene Clusters Allows Discovery of Arseno-Organic Metabolites in Model Streptomycetes.

Natural products from microbes have provided humans with beneficial antibiotics for millennia. However, a decline in the pace of antibiotic discovery exerts pressure on human health as antibiotic resistance spreads, a challenge that may better faced by unveiling chemical diversity produced by microbes. Current microbial genome mining approaches have revitalized research into antibiotics, but the empirical nature of these methods limits the chemical space that is explored.Here, we address the problem of finding novel pathways by incorporating evolutionary principles into genome mining. We recapitulated the evolutionary history of twenty-three enzyme families previously uninvestigated in the context of natural product biosynthesis in Actinobacteria, the most proficient producers of natural products. Our genome evolutionary analyses where based on the assumption that expanded-repurposed enzyme families-from central metabolism, occur frequently and thus have the potential to catalyze new conversions in the context of natural products biosynthesis. Our analyses led to the discovery of biosynthetic gene clusters coding for hidden chemical diversity, as validated by comparing our predictions with those from state-of-the-art genome mining tools; as well as experimentally demonstrating the existence of a biosynthetic pathway for arseno-organic metabolites in Streptomyces coelicolor and Streptomyces lividans, Using a gene knockout and metabolite profile combined strategy.As our approach does not rely solely on sequence similarity searches of previously identified biosynthetic enzymes, these results establish the basis for the development of an evolutionary-driven genome mining tool termed EvoMining that complements current platforms. We anticipate that by doing so real 'chemical dark matter' will be unveiled.