Rhizobium etli CFN42 proteomes showed isoenzymes in free-living and symbiosis with a different transcriptional regulation inferred from a transcriptional regulatory network.

A comparative proteomic study at 6 h of growth in minimal medium (MM) and bacteroids at 18 days of symbiosis of Rhizobium etli CFN42 with the Phaseolus vulgaris leguminous plant was performed. A gene ontology classification of proteins in MM and bacteroid, showed 31 and 10 pathways with higher or equal than 30 and 20% of proteins with respect to genome content per pathway, respectively. These pathways were for energy and environmental compound metabolism, contributing to understand how Rhizobium is adapted to the different conditions. Metabolic maps based on orthology of the protein profiles, showed 101 and 74 functional homologous proteins in the MM and bacteroid profiles, respectively, which were grouped in 34 different isoenzymes showing a great impact in metabolism by covering 60 metabolic pathways in MM and symbiosis. Taking advantage of co-expression of transcriptional regulators (TF's) in the profiles, by selection of genes whose matrices were clustered with matrices of TF's, Transcriptional Regulatory networks (TRN´s) were deduced by the first time for these metabolic stages. In these clustered TF-MM and clustered TF-bacteroid networks, containing 654 and 246 proteins, including 93 and 46 TFs, respectively, showing valuable information of the TF's and their regulated genes with high stringency. Isoenzymes were specific for adaptation to the different conditions and a different transcriptional regulation for MM and bacteroid was deduced. The parameters of the TRNs of these expected biological networks and biological networks of E. coli and B. subtilis segregate from the random theoretical networks. These are useful data to design experiments on TF gene-target relationships for bases to construct a TRN.

Curation, inference, and assessment of a globally reconstructed gene regulatory network for Streptomyces coelicolor.

Streptomyces coelicolor A3(2) is a model microorganism for the study of Streptomycetes, antibiotic production, and secondary metabolism in general. Even though S. coelicolor has an outstanding variety of regulators among bacteria, little effort to globally study its transcription has been made. We manually curated 29 years of literature and databases to assemble a meta-curated experimentally-validated gene regulatory network (GRN) with 5386 genes and 9707 regulatory interactions (~ 41% of the total expected interactions). This provides the most extensive and up-to-date reconstruction available for the regulatory circuitry of this organism. Only ~ 6% (534/9707) are supported by experiments confirming the binding of the transcription factor to the upstream region of the target gene, the so-called "strong" evidence. While for the remaining interactions there is no confirmation of direct binding. To tackle network incompleteness, we performed network inference using several methods (including two proposed here) for motif identification in DNA sequences and GRN inference from transcriptomics. Further, we contrasted the structural properties and functional architecture of the networks to assess the reliability of the predictions, finding the inference from DNA sequence data to be the most trustworthy approach. Finally, we show two applications of the inferred and the curated networks. The inference allowed us to propose novel transcription factors for the key Streptomyces antibiotic regulatory proteins (SARPs). The curated network allowed us to study the conservation of the system-level components between S. coelicolor and Corynebacterium glutamicum. There we identified the basal machinery as the common signature between the two organisms. The curated networks were deposited in Abasy Atlas ( https://abasy.ccg.unam.mx/ ) while the inferences are available as Supplementary Material.

Calcitriol increases Dicer expression and modifies the microRNAs signature in SiHa cervical cancer cells.

MicroRNAs play important roles in cancer biology. Calcitriol, the hormonal form of vitamin D3, regulates microRNAs expression in tumor cells. In the present study we asked if calcitriol would modify some of the components of the microRNA processing machinery, namely, Drosha and Dicer, in calcitriol-responsive cervical cancer cells. We found that calcitriol treatment did not affect Drosha mRNA; however, it significantly increased Dicer mRNA and protein expression in VDR-positive SiHa and HeLa cells. In VDR-negative C33-A cells, calcitriol had no effect on Dicer mRNA. We also found a vitamin D response element in Dicer promoter that interacts in vitro to vitamin D and retinoid X receptors. To explore the biological plausibility of these results, we asked if calcitriol alters the microRNA expression profile in SiHa cells. Our results revealed that calcitriol regulates the expression of a subset of microRNAs with potential regulatory functions in cancer pathways, such as miR-22, miR-296-3p, and miR-498, which exert tumor-suppressive effects. In summary, the data indicate that in SiHa cells, calcitriol stimulates the expression of Dicer possibly through the vitamin D response element located in its promoter. This may explain the calcitriol-dependent modulation of microRNAs whose target mRNAs are related to anticancer pathways, further adding to the various anticancer mechanisms of calcitriol.

Anti-Sigma Factors in E. coli: Common Regulatory Mechanisms Controlling Sigma Factors Availability.

In bacteria, transcriptional regulation is a key step in cellular gene expression. All bacteria contain a core RNA polymerase that is catalytically competent but requires an additional σ factor for specific promoter recognition and correct transcriptional initiation. The RNAP core is not able to selectively bind to a given σ factor. In contrast, different σ factors have different affinities for the RNAP core. As a consequence, the concentration of alternate σ factors requires strict regulation in order to properly control the delicate interplay among them, which favors the competence for the RNAP core. This control is archived by different σ/anti-σ controlling mechanisms that shape complex regulatory networks and cascades, and enable the response to sudden environmental cues, whose global understanding is a current challenge for systems biology. Although there have been a number of excellent studies on each of these σ/anti-σ post-transcriptional regulatory systems, no comprehensive comparison of these mechanisms in a single model organism has been conducted. Here, we survey all these systems in E. coli dissecting and analyzing their inner workings and highlightin their differences. Then, following an integral approach, we identify their commonalities and outline some of the principles exploited by the cell to effectively and globally reprogram the transcriptional machinery. These principles provide guidelines for developing biological synthetic circuits enabling an efficient and robust response to sudden stimuli.