Pharmacodynamic modelling of in vitro activity of tetracycline against a representative, naturally occurring population of porcine Escherichia coli

Background The complex relationship between drug concentrations and bacterial growth rates require not only the minimum inhibitory concentration but also other parameters to capture the dynamic nature of the relationship. To analyse this relationship between tetracycline concentration and growth of Escherichia coli representative of those found in the Danish pig population, we compared the growth of 50 randomly selected strains. The observed net growth rates were used to describe the in vitro pharmacodynamic relationship between drug concentration and net growth rate based on E max model with three parameters: maximum net growth rate (α max ); concentration for a half-maximal response (E max ); and the Hill coefficient (γ). Results The net growth rate in the absence of antibiotic did not differ between susceptible and resistant isolates (P = 0.97). The net growth rate decreased with increasing tetracycline concentrations, and this decline was greater in susceptible strains than resistant strains. The lag phase, defined as the time needed for the strain to reach an OD 600 value of 0.01, increased exponentially with increasing tetracycline concentration. The pharmacodynamic parameters confirmed that the αmax between susceptible and resistant strains in the absence of a drug was not different. EC 50 increased linearly with MIC on a log–log scale, and γ was different between susceptible and resistant strains. Conclusions The in vitro model parameters described the inhibition effect of tetracycline on E. coli when strains were exposed to a wide range of tetracycline concentrations. These parameters, along with in vivo pharmacokinetic data, may be useful in mathematical models to predict in vivo competitive growth of many different strains and for development of optimal dosing regimens for preventing selection of resistance

Analyzing the Binding of Co(II)-specific Inhibitors to the Methionyl Aminopeptidases from \u3cem\u3eEscherichia coli\u3c/em\u3e and \u3cem\u3ePyrococcus furiosus\u3c/em\u3e

Methionine aminopeptidases (MetAPs) represent a unique class of protease that is capable of the hydrolytic removal of an N-terminal methionine residue from nascent polypeptide chains. MetAPs are physiologically important enzymes; hence, there is considerable interest in developing inhibitors that can be used as antiangiogenic and antimicrobial agents. A detailed kinetic and spectroscopic study has been performed to probe the binding of a triazole-based inhibitor and a bestatin-based inhibitor to both Mn(II)- and Co(II)-loaded type-I (Escherichia coli) and type-II (Pyrococcus furiosus) MetAPs. Both inhibitors were found to be moderate competitive inhibitors. The triazole-type inhibitor was found to interact with both active-site metal ions, while the bestatin-type inhibitor was capable of switching its mode of binding depending on the metal in the active site and the type of MetAP enzyme

The porin and the permeating antibiotic: A selective diffusion barrier in gram-negative bacteria

Gram-negative bacteria are responsible for a large proportion of antibiotic resistant bacterial diseases. These bacteria have a complex cell envelope that comprises an outer membrane and an inner membrane that delimit the periplasm. The outer membrane contains various protein channels, called porins, which are involved in the influx of various compounds, including several classes of antibiotics. Bacterial adaptation to reduce influx through porins is an increasing problem worldwide that contributes, together with efflux systems, to the emergence and dissemination of antibiotic resistance. An exciting challenge is to decipher the genetic and molecular basis of membrane impermeability as a bacterial resistance mechanism. This Review outlines the bacterial response towards antibiotic stress on altered membrane permeability and discusses recent advances in molecular approaches that are improving our knowledge of the physico-chemical parameters that govern the translocation of antibiotics through porin channel

Model of Transcriptional Activation by MarA in Escherichia coli

We have developed a mathematical model of transcriptional activation by MarA in Escherichia coli, and used the model to analyze measurements of MarA-dependent activity of the marRAB, sodA, and micF promoters in mar-rob- cells. The model rationalizes an unexpected poor correlation between the mid-point of in vivo promoter activity profiles and in vitro equilibrium constants for MarA binding to promoter sequences. Analysis of the promoter activity data using the model yielded the following predictions regarding activation mechanisms: (1) MarA activation of the marRAB, sodA, and micF promoters involves a net acceleration of the kinetics of transitions after RNA polymerase binding, up to and including promoter escape and message elongation; (2) RNA polymerase binds to these promoters with nearly unit occupancy in the absence of MarA, making recruitment of polymerase an insignificant factor in activation of these promoters; and (3) instead of recruitment, activation of the micF promoter might involve a repulsion of polymerase combined with a large acceleration of the kinetics of polymerase activity. These predictions are consistent with published chromatin immunoprecipitation assays of interactions between polymerase and the E. coli chromosome. A lack of recruitment in transcriptional activation represents an exception to the textbook description of activation of bacterial sigma-70 promoters. However, use of accelerated polymerase kinetics instead of recruitment might confer a competitive advantage to E. coli by decreasing latency in gene regulation.Comment: 30 pages, 2 figure

Crosstalk and the Dynamical Modularity of Feed-Forward Loops in Transcriptional Regulatory Networks

Network motifs, such as the feed-forward loop (FFL), introduce a range of complex behaviors to transcriptional regulatory networks, yet such properties are typically determined from their isolated study. We characterize the effects of crosstalk on FFL dynamics by modeling the cross regulation between two different FFLs and evaluate the extent to which these patterns occur in vivo. Analytical modeling suggests that crosstalk should overwhelmingly affect individual protein-expression dynamics. Counter to this expectation we find that entire FFLs are more likely than expected to resist the effects of crosstalk (approximate to 20% for one crosstalk interaction) and remain dynamically modular. The likelihood that cross-linked FFLs are dynamically correlated increases monotonically with additional crosstalk, but is independent of the specific regulation type or connectivity of the interactions. Just one additional regulatory interaction is sufficient to drive the FFL dynamics to a statistically different state. Despite the potential for modularity between sparsely connected network motifs, Escherichia coli (E. coli) appears to favor crosstalk wherein at least one of the cross-linked FFLs remains modular. A gene ontology analysis reveals that stress response processes are significantly overrepresented in the cross-linked motifs found within E. coli. Although the daunting complexity of biological networks affects the dynamical properties of individual network motifs, some resist and remain modular, seemingly insulated from extrinsic perturbations-an intriguing possibility for nature to consistently and reliably provide certain network functionalities wherever the need arise