Calculating metalation in cells reveals CobW acquires Co(II) for vitamin B12 biosynthesis while related proteins prefer Zn(II)

Protein metal-occupancy (metalation) in vivo has been elusive. To address this challenge, the available free energies of metals have recently been determined from the responses of metal sensors. Here, we use these free energy values to develop a metalation-calculator which accounts for inter-metal competition and changing metal-availabilities inside cells. We use the calculator to understand the function and mechanism of GTPase CobW, a predicted CoII-chaperone for vitamin B12. Upon binding nucleotide (GTP) and MgII, CobW assembles a high-affinity site that can obtain CoII or ZnII from the intracellular milieu. In idealised cells with sensors at the mid-points of their responses, competition within the cytosol enables CoII to outcompete ZnII for binding CobW. Thus, CoII is the cognate metal. However, after growth in different [CoII], CoII-occupancy ranges from 10 to 97% which matches CobW-dependent B12 synthesis. The calculator also reveals that related GTPases with comparable ZnII affinities to CobW, preferentially acquire ZnII due to their relatively weaker CoII affinities. The calculator is made available here for use with other proteins

Predicting Transcription Factor Specificity with All-Atom Models

The binding of a transcription factor (TF) to a DNA operator site can initiate or repress the expression of a gene. Computational prediction of sites recognized by a TF has traditionally relied upon knowledge of several cognate sites, rather than an ab initio approach. Here, we examine the possibility of using structure-based energy calculations that require no knowledge of bound sites but rather start with the structure of a protein-DNA complex. We study the PurR E. coli TF, and explore to which extent atomistic models of protein-DNA complexes can be used to distinguish between cognate and non-cognate DNA sites. Particular emphasis is placed on systematic evaluation of this approach by comparing its performance with bioinformatic methods, by testing it against random decoys and sites of homologous TFs. We also examine a set of experimental mutations in both DNA and the protein. Using our explicit estimates of energy, we show that the specificity for PurR is dominated by direct protein-DNA interactions, and weakly influenced by bending of DNA.Comment: 26 pages, 3 figure

Local Gene Regulation Details a Recognition Code within the LacI Transcriptional Factor Family

The specific binding of regulatory proteins to DNA sequences exhibits no clear patterns of association between amino acids (AAs) and nucleotides (NTs). This complexity of protein-DNA interactions raises the question of whether a simple set of wide-coverage recognition rules can ever be identified. Here, we analyzed this issue using the extensive LacI family of transcriptional factors (TFs). We searched for recognition patterns by introducing a new approach to phylogenetic footprinting, based on the pervasive presence of local regulation in prokaryotic transcriptional networks. We identified a set of specificity correlations –determined by two AAs of the TFs and two NTs in the binding sites– that is conserved throughout a dominant subgroup within the family regardless of the evolutionary distance, and that act as a relatively consistent recognition code. The proposed rules are confirmed with data of previous experimental studies and by events of convergent evolution in the phylogenetic tree. The presence of a code emphasizes the stable structural context of the LacI family, while defining a precise blueprint to reprogram TF specificity with many practical applications.Ministerio de Ciencia e Innovación, Spain (Formación de Profesorado Universitario fellowship)Ministerio de Ciencia e Innovación, Spain (grant BFU2008-03632/BMC)Madrid (Spain : Region) (grant CCG08-CSIC/SAL-3651