Summary Pleiotropic regulatory mutations affect diverse cellular processes, posing a challenge to our understanding of genotype-phenotype relationships across multiple biological scales. Adaptive Laboratory Evolution (ALE) allows for such mutations to be found and characterized in the context of clear selection pressures. Here, several ALE-selected single-mutation variants in Escherichia coli's RNA polymerase (RNAP) are detailed using an integrated multi-scale experimental and computational approach. While these mutations increase cellular growth rates in steady environments, they reduce tolerance to stress and environmental fluctuations. We detail structural changes in the RNAP that rewire the transcriptional machinery to rebalance proteome and energy allocation towards growth and away from several hedging and stress functions. We find that while these mutations occur in diverse locations in the RNAP, they share a common adaptive mechanism. In turn, these findings highlight the resource allocation tradeoffs organisms face and suggest how the structure of the regulatory network enhances evolvability.

Gene regulation at the transcriptional level is a central process in all organisms, and DNA-binding transcription factors, known as TFs, play a fundamental role. This class of proteins usually binds at specific DNA sequences, activating or repressing gene expression. In general, TFs are composed of two domains: the DNA-binding domain (DBD) and an extra domain, which in this work we have named “companion domain” (CD). This latter could be involved in one or more functions such as ligand binding, protein-protein interactions or even with enzymatic activity. In contrast to DBDs, which have been widely characterized both experimentally and bioinformatically, information on the abundance, distribution, variability and possible role of the CDs is scarce. Here, we investigated these issues associated with the domain architectures of TFs in prokaryotic genomes. To this end, 19 families of TFs in 761 non-redundant bacterial and archaeal genomes were evaluated. In this regard we found four main groups based on the abundance and distribution in the analyzed genomes: i) LysR and TetR/AcrR; ii) AraC/XylS, SinR, and others; iii) Lrp, Fis, ArsR, and others; and iv) a group that included only two families, ArgR and BirA. Based on a classification of the organisms according to the life-styles, a major abundance of regulatory families in free-living organisms, in contrast with pathogenic, extremophilic or intracellular organisms, was identified. Finally, the protein architecture diversity associated to the 19 families considering a weight score for domain promiscuity evidenced which regulatory families were characterized by either a large diversity of CDs, here named as “promiscuous” families given the elevated number of variable domains found in those TFs, or a low diversity of CDs. Altogether this information helped us to understand the diversity and distribution of the 19 Prokaryotes TF families. Moreover, initial steps were taken to comprehend the variability of the extra domain in those TFs, which eventually might assist in evolutionary and functional studies.

BackgroundNucleotide metabolism is central to all biological systems, due to their essential role in genetic information and energy transfer, which in turn suggests its possible presence in the last common ancestor (LCA) of Bacteria, Archaea and Eukarya. In this context, elucidation of the contribution of the origin and diversification of de novo and salvage pathways of nucleotide metabolism will allow us to understand the links between the enzymatic steps associated with the LCA and the emergence of the first metabolic pathways.ResultsIn this work, the taxonomical distribution of the enzymes associated with nucleotide metabolism was evaluated in 1,606 complete genomes. 151 sequence profiles associated with 120 enzymatic reactions were used. The evaluation was based on profile comparisons, using RPS-Blast. Organisms were clustered based on their taxonomical classifications, in order to obtain a normalized measure of the taxonomical distribution of enzymes according to the average of presence/absence of enzymes per genus, which in turn was used for the second step, to calculate the average presence/absence of enzymes per Clade.ConclusionFrom these analyses, it was suggested that divergence at the enzymatic level correlates with environmental changes and related modifications of the cell wall and membranes that took place during cell evolution. Specifically, the divergence of the 5-(carboxyamino) imidazole ribonucleotide mutase to phosphoribosylaminoimidazole carboxylase could be related to the emergence of multicellularity in eukaryotic cells. In addition, segments of salvage and de novo pathways were probably complementary in the LCA to the synthesis of purines and pyrimidines. We also suggest that a large portion of the pathway to inosine 5’-monophosphate (IMP) in purines could have been involved in thiamine synthesis or its derivatives in early stages of cellular evolution, correlating with the fact that these molecules may have played an active role in the protein-RNA world. The analysis presented here provides general observations concerning the adaptation of the enzymatic steps in the early stages of the emergence of life and the LCA.Electronic supplementary materialThe online version of this article (doi:10.1186/1471-2164-15-800) contains supplementary material, which is available to authorized users.

Malate-efflux from roots, which is regulated by the transcription factor STOP1 (SENSITIVE-TO-PROTON-RHIZOTOXICITY1), which mediates aluminum-induced expression of ALUMINUM-ACTIVATED-MALATE-TRANSPORTER1 (AtALMT1), is critical for aluminum-resistance in Arabidopsis thaliana. Several studies showed that root AtALMT1 expression is rapidly observed in response to aluminum (within 1-hour), this early induction is an important mechanism to immediately protect roots from aluminum-toxicity. Additionally, identifying the molecular mechanisms that underlie rapid aluminum-resistance responses should lead to a better understanding of plant aluminum-sensing and -signal transduction mechanisms. In this study, histochemical analyses using GFP-tagged STOP1 proteins showed that STOP1 proteins were accumulated in the nucleus soon after aluminum-treatment. The rapid aluminum-induced STOP1-nuclear localization and AtALMT1-induction were observed in the presence of the protein synthesis inhibitor, suggesting that post-translational regulation is involved in these events. STOP1 also regulated rapid aluminum-induced expression for other genes that carry a functional/high-affinity STOP1-binding site in their promoter, including STOP2, GLUTAMATE-DEHYDROGENASE1 and 2 (GDH1 and 2), but not for Al resistance genes which have no functional STOP1-binding site such as ALUMINUM-SENSITIVE3, suggesting that the binding of STOP1 in the promoter is essential for the early induction. Finally, we report that GDH1 and 2 which are the target of STOP1 are novel aluminum-resistance genes in Arabidopsis.

Based on integrative computational hybrid approaches that combined statistical coupling analysis (SCA), molecular dynamics (MD), and normal mode analysis (NMA), evolutionarily coupled residues involved in functionally relevant motion in the adenylate kinase protein family were identified. The hybrids identified four top-ranking site pairs that belong to a conserved hydrogen bond network that is involved in the enzyme's flexibility. A second group of top-ranking site pairs was identified in critical regions for functional dynamics, such as those related to enzymatic turnover. The high consistency of the results obtained by SCA with NMA (SCA.NMA) and by SCA.MD hybrid analyses suggests that suitable replacement of the matrix of cross-correlation analysis of atomic fluctuations (derived by using NMA) with those based on MD contributes to the identification of such sites by means of a fast computational calculation. The analysis presented here strongly supports the hypothesis that evolutionary forces, such as coevolution at the sequence level, have promoted functional dynamic properties of the adenylate kinase protein family. Finally, these hybrid approaches can be used to identify, at the residue level, protein motion coordination patterns not previously observed, such as in hinge regions.

Many virulence genes have been detected in attenuated mutants of Brucella melitensis 16 M; nevertheless, a complete report of these genes, including the main Cluster of Orthologous Groups (COG) represented as well as the taxonomical distribution among all complete bacterial and archaeal genomes, has not been analyzed. In this work a total of 160 virulence genes that have been reported in attenuated mutants in B. melitensis were included and analyzed. Additionally, we obtained 250 B. melitensis randomly selected genes as a reference group for the taxonomical comparisons. The COGs and the taxonomical distribution profile for 789 nonredundant bacterial and archaeal genomes were obtained and compared with the whole-genome COG distribution and with the 250 randomly selected genes, respectively. The main COGs associated with virulence genes corresponded to the following: intracellular trafficking, secretion and vesicular transport (U); cell motility (N); nucleotide transport and metabolism (F); transcription (K); and cell wall/membrane/envelope biogenesis (M). In addition, we found that virulence genes presented a higher proportion of orthologs in the Euryarchaeota and Proteobacteria phyla, with a significant decrease in Chlamydiae, Bacteroidetes, Tenericutes, Firmicutes and Thermotogae. In conclusion, we found that genes related to specific functions are more relevant to B. melitensis virulence, with the COG U the most significant. Additionally, the taxonomical distribution of virulence genes highlights the importance of these genes in the related Proteobacteria, being less relevant in distant groups of organisms with the exception of Euryarchaeota.

Bioinformatics is a very important informatics tool for health and biological sciences, focusing on biological data management. The objective of this work was to perform a bibliometric analysis regarding the development of Mexican bioinformatics. An exhaustive revision of the literature associated with Mexican bioinformatics in a period of 25-years was performed. Bibliometric tools, such as performance analysis and science mapping were included in the analysis. We identified the main actors as well as the structure and dynamics of Mexican bioinformatics. Some of the main findings were as follows: the thematic structure in the field is defined by the research lines of outstanding authors; the outstanding collaborations of Mexican institutions with foreign countries and institutions are influenced by the geographic proximity and binational agreements, as well as philanthropic and academic programs that promote collaborations, and there is an inclination for health issues promoted by public health financing and philanthropic organizations. It is identified that publications had an explosion since 2012, we consider that this growth may be influenced by the democratization of data, derived from the mass sequencing of biological molecules stored in public databases.

In this work, an exhaustive revision is given of the literature associated with advanced information and communication technologies in agriculture within a window of 25 years using bibliometric tools enabled to detect of the main actors, structure, and dynamics in the scientific papers. The main findings are a trend of growth in the dynamics of publications associated with advanced information and communication technologies in agriculture productivity. Another assertion is that countries, like the USA, China, and Brazil, stand out in many publications due to allocating more resources to research, development, and agricultural productivity. In addition, the collaboration networks between countries are frequently in regions with closer cultural and idiomatic ties; additionally, terms’ occurrence are obtained with Louvain algorithm predominating four clusters: precision agriculture, smart agriculture, remote sensing, and climate smart agriculture. Finally, the thematic-map characterization with Callon’s density and centrality is applied in three periods. The first period of thematic analysis shows a transition in detecting the variability of a nutrient, such as nitrogen, through the help of immature georeferenced techniques, towards greater remote sensing involvement. In the transition from the second to the third stage, the maturation of technologies, such as unmanned aerial vehicles, wireless sensor networks, and the machine learning area, is observed.