Diseño de un modelo bioinformática para la detección, identificación y clasificación de genes codificantes de b-lactamasas, como herramienta para el cruce de datos moleculares con datos clínicos

El seguimiento epidemiológico y farmacológico de la resistencia a antibióticos b-lactámicos mediada por la presencia de b-lactamasas requiere identificación precisa, lo cual es posible mediante la secuencia del gen, que es identificado con herramientas bioinformáticas que se incorporan a sistemas de información. Para implementar un prototipo de sistema de información que permite clasificar secuencias de genes de b-lactamasas producidas por microorganismos resistentes aislados en hospitales y realizar su cruce con los datos clínicos, se obtuvieron las secuencias de b-lactamasas reportadas a escala mundial en la base de datos Uniprot utilizando el sistema de recuperación de secuencias (SRS) del Instituto Europeo de Bioinformática (EBI), se diseñó un sistema de datos moleculares y clínicos usando “Unified Modeling Languageâ€� (UML), y se generó un modelo implementado en un servidor con sistema operativo UNIX, gestor de bases de datos MySQL para realizar la creación de la base de datos y lenguajes de programación Perl y PHP para implementar programas y cruzar datos. El sistema de información BLA_ID_CLINIC permite hacer el cruce de datos moleculares y clínicos, de tal forma que se puedan identificar las b-lactamasas de microorganismos resistentes en hospitales y hacer un seguimiento del manejo de los antibióticos y el comportamiento epidemiológico, modelo bioinformático permanentemente actualizado, disponible a través de Internet en http://bioinf.ibun.unal.edu.oc/BLA_ID_CLINIC.The epidemiology and pharmacology of the b-lactamic antibiotics resistance at hospital level mediate by the presence of b-lactamasas requires of their precise identification, possible through the gene sequence that can be identified using bioinformatics tools and incorporated into the information systems. Prototype of information system BAL_ID_CLINIC was implemented for allowing genes sequences classification of b-lactamases produced by isolated resistant microorganisms in hospitals and their crossing with the clinical data. The information system was development using Unified Modeling Language UML and the prototype was implemented in an Unix server, using MySQL management system for data base building and Perl and PHP as a programming languages for writing scripts that obtain cross relationship between the different kind of data inside the system and the result report presentation. BLA_ID_CLINIC allows crossing of molecular and clinical data. It can identify b-lactamasas produced by resistant microorganisms isolated in hospital patients and can give information related with the antibiotics management and the epidemiologic behavior. The bioinformatics prototype BLA_ID_CLINIC is permanently updated and available through Internet in http://bioinf.ibun.unal.edu.oc/BLA_ID_CLINIC

Impact of rice straw management strategies on rice rhizosphere microbiomes

Rice is the third most important crop worldwide. Unfortunately, in most rice-producing countries, crop residues are burned, increasing emissions of greenhouse gases and toxic compounds. Incorporation of rice straw (RS) into the soil, either or not accompanied by a microbial inoculum, may offer a viable alternative. However, the effects of such treatments on soil, including the microbial community structure and function in the next crop cycle, still remain largely unknown. Here, we studied the effect of four different RS management strategies (leaving RS as mulch with or without a microbial inoculum, incorporation of RS into the soil with microbial inoculum, and RS burning) on rice growth and flowering-stage rhizosphere microbiomes. The relevant microbiomes were examined by amplicon sequencing based on the 16S rRNA and ITS1 gene regions. In comparison to the zero situation, all four treatments tended to increase the soil organic carbon content, albeit without significant differences. Furthermore, none of the treatments had major effects on either (rice) crop yield or phytopathogen incidence in the next cycle. However, leaving RS as a mulch incited a decrease in soil pH, and showed a trend of reducing yield by up to 1 ton·ha−1. Moreover, the different RS treatments affected the structures and predicted functions of the bacteriomes and fungomes in the rice rhizosphere. The mulching treatment was associated with an enhanced abundance of Acidobacteria, particularly Bryobacter spp. In contrast, the non-mulch treatments incited raised abundances of GammaProteobacteria, Bacteroidia and Campylobacteria. The rice rhizosphere fungomes, consisting mostly of Ascomycota, were less affected by the treatments, although the microbial inoculum was shown to drive the respective fungome structures

Colombia's cyberinfrastructure for biodiversity: Building data infrastructure in emerging countries to foster socioeconomic growth

Science and innovation are not a luxury but a prerequisite for social and economic development (Annan, 2003)

Guidelines for the use and interpretation of assays for monitoring autophagy (4th edition)

In 2008, we published the first set of guidelines for standardizing research in autophagy. Since then, this topic has received increasing attention, and many scientists have entered the field. Our knowledge base and relevant new technologies have also been expanding. Thus, it is important to formulate on a regular basis updated guidelines for monitoring autophagy in different organisms. Despite numerous reviews, there continues to be confusion regarding acceptable methods to evaluate autophagy, especially in multicellular eukaryotes. Here, we present a set of guidelines for investigators to select and interpret methods to examine autophagy and related processes, and for reviewers to provide realistic and reasonable critiques of reports that are focused on these processes. These guidelines are not meant to be a dogmatic set of rules, because the appropriateness of any assay largely depends on the question being asked and the system being used. Moreover, no individual assay is perfect for every situation, calling for the use of multiple techniques to properly monitor autophagy in each experimental setting. Finally, several core components of the autophagy machinery have been implicated in distinct autophagic processes (canonical and noncanonical autophagy), implying that genetic approaches to block autophagy should rely on targeting two or more autophagy-related genes that ideally participate in distinct steps of the pathway. Along similar lines, because multiple proteins involved in autophagy also regulate other cellular pathways including apoptosis, not all of them can be used as a specific marker for bona fide autophagic responses. Here, we critically discuss current methods of assessing autophagy and the information they can, or cannot, provide. Our ultimate goal is to encourage intellectual and technical innovation in the field