No abstract

Prokaryotes have developed multiple strategies to survive phage attack and invasive DNA. Recently, a novel genetic program denominated the CRISPR/Cas system was demonstrated to have a role in these biological processes providing genetic immunity. This defense mechanism is widespread in the Archaea and Bacteria, suggesting an ancient origin. In the last few years, progress has been made regarding the functionality of the CRISPR/Cas system; however, many basic aspects of the system remain unknown. For instance, there are few studies about the conditions and regulators involved in its transcriptional control. In this work, we analyzed the transcriptional organization of the CRISPR/Cas system as well as the positive and negative regulators involved in its genetic expression in Salmonella enterica serovar Typhi. The results obtained show that in S. Typhi the CRISPR/Cas system is a LeuO-dependent operon silenced by the global regulator LRP, in addition to the previously known nucleoidassociated protein H-NS; both LRP and H-NS bind upstream and downstream of the transcriptional start site of casA. In this study, relevant nucleotides of the casA regulatory region that mediate its LeuO transcriptional activation were identified. Interestingly, specific growth conditions (N-minimal medium) were found for the LeuOindependent expression of the CRISPR/Cas system in S. Typhi. Thus, our work provides evidence that there are multiple modulators involved in the genetic expression of this immune system in S. Typhi IMSS-1.

No abstract

The transcriptional network of Escherichia coli may well be the most complete experimentally characterized network of a single cell. A rule-based approach was built to assess the degree of consistency between whole-genome microarray experiments in different experimental conditions and the accumulated knowledge in the literature compiled in RegulonDB, a data base of transcriptional regulation and operon organization in E. coli. We observed a high and statistical significant level of consistency, ranging from 70%-87%. When effector metabolites of regulatory proteins are not considered in the prediction of the active or inactive state of the regulators, consistency falls by up to 40%. Similarly, consistency decreases when rules for multiple regulatory interactions are altered or when "on" and "off" entries were assigned randomly. We modified the initial state of regulators and evaluated the propagation of errors in the network that do not correlate linearly with the connectivity of regulators. We interpret this deviation mainly as a result of the existence of redundant regulatory interactions. Consistency evaluation opens a new space of dialogue between theory and experiment, as the consequences of different assumptions can be evaluated and compared.

Metagenomics research has recently thrived due to DNA sequencing technologies improvement, driving the emergence of new analysis tools and the growth of taxonomic databases. However, there is no all-purpose strategy that can guarantee the best result for a given project and there are several combinations of software, parameters and databases that can be tested. Therefore, we performed an impartial comparison, using statistical measures of classification for eight bioinformatic tools and four taxonomic databases, defining a benchmark framework to evaluate each tool in a standardized context. Using in silico simulated data for 16S rRNA amplicons and whole metagenome shotgun data, we compared the results from different software and database combinations to detect biases related to algorithms or database annotation. Using our benchmark framework, researchers can define cut-off values to evaluate the expected error rate and coverage for their results, regardless the score used by each software. A quick guide to select the best tool, all datasets and scripts to reproduce our results and benchmark any new method are available at https://github.com/Ales-ibt/Metagenomic-benchmark. Finally, we stress out the importance of gold standards, database curation and manual inspection of taxonomic profiling results, for a better and more accurate microbial diversity description.