Natural history of SLC11 genes in vertebrates: tales from the fish world

Background  

The SLC11A1/Nramp1 and SLC11A2/Nramp2 genes belong to the SLC11/Nramp family of transmembrane divalent metal transporters, with SLC11A1 being associated with resistance to pathogens and SLC11A2 involved in intestinal iron uptake and transferrin-bound iron transport. Both members of the SLC11 gene family have been clearly identified in tetrapods; however SLC11A1 has never been documented in teleost fish and is believed to have been lost in this lineage during early vertebrate evolution. In the present work we characterized the SLC11 genes in teleosts and evaluated if the roles attributed to mammalian SLC11 genes are assured by other fish specific SLC11 gene members.     

α-Ketoglutarate coordinates carbon and nitrogen utilization via enzyme I inhibition

Microbes survive in a variety of nutrient environments by modulating their intracellular metabolism. Balanced growth requires coordinated uptake of carbon and nitrogen, the primary substrates for biomass production. Yet the mechanisms that balance carbon and nitrogen uptake are poorly understood. We find in Escherichia coli that a sudden increase in nitrogen availability results in an almost immediate increase in glucose uptake. The concentrations of glycolytic intermediates and known regulators, however, remain homeostatic. Instead, we find that α-ketoglutarate, which accumulates in nitrogen limitation, directly blocks glucose uptake by inhibiting enzyme I, the first step of the sugar-phosphoenolpyruvate phosphotransferase system (PTS). This inhibition enables rapid modulation of glycolytic flux without marked changes in the concentrations of glycolytic intermediates by simultaneously altering import of glucose and consumption of the terminal glycolytic intermediate phosphoenolpyruvate. Quantitative modeling shows that this previously unidentified regulatory connection is, in principle, sufficient to coordinate carbon and nitrogen utilization.     

Thermal robustness of signaling in bacterial chemotaxis

Temperature is a global factor that affects the performance of all intracellular networks. Robustness against temperature variations is thus expected to be an essential network property, particularly in organisms without inherent temperature control. Here, we combine experimental analyses with computational modeling to investigate thermal robustness of signaling in chemotaxis of Escherichia coli, a relatively simple and well-established model for systems biology. We show that steady-state and kinetic pathway parameters that are essential for chemotactic performance are indeed temperature-compensated in the entire physiological range. Thermal robustness of steady-state pathway output is ensured at several levels by mutual compensation of temperature effects on activities of individual pathway components. Moreover, the effect of temperature on adaptation kinetics is counterbalanced by preprogrammed temperature dependence of enzyme synthesis and stability to achieve nearly optimal performance at the growth temperature. Similar compensatory mechanisms are expected to ensure thermal robustness in other systems.     

An excitable cortex and memory model successfully predicts new pseudopod dynamics

Motile eukaryotic cells migrate with directional persistence by alternating left and right turns, even in the absence of external cues. For example, Dictyostelium discoideum cells crawl by extending distinct pseudopods in an alternating right-left pattern. The mechanisms underlying this zig-zag behavior, however, remain unknown. Here we propose a new Excitable Cortex and Memory (EC&M) model for understanding the alternating, zig-zag extension of pseudopods. Incorporating elements of previous models, we consider the cell cortex as an excitable system and include global inhibition of new pseudopods while a pseudopod is active. With the novel hypothesis that pseudopod activity makes the local cortex temporarily more excitable--thus creating a memory of previous pseudopod locations--the model reproduces experimentally observed zig-zag behavior. Furthermore, the EC&M model makes four new predictions concerning pseudopod dynamics. To test these predictions we develop an algorithm that detects pseudopods via hierarchical clustering of individual membrane extensions. Data from cell-tracking experiments agrees with all four predictions of the model, revealing that pseudopod placement is a non-Markovian process affected by the dynamics of previous pseudopods. The model is also compatible with known limits of chemotactic sensitivity. In addition to providing a predictive approach to studying eukaryotic cell motion, the EC&M model provides a general framework for future models, and suggests directions for new research regarding the molecular mechanisms underlying directional persistence.     

Chemotaxis receptor complexes: from signaling to assembly

Complexes of chemoreceptors in the bacterial cytoplasmic membrane allow for the sensing of ligands with remarkable sensitivity. Despite the excellent characterization of the chemotaxis signaling network, very little is known about what controls receptor complex size. Here we use in vitro signaling data to model the distribution of complex sizes. In particular, we model Tar receptors in membranes as an ensemble of different sized oligomer complexes, i.e., receptor dimers, dimers of dimers, and trimers of dimers, where the relative free energies, including receptor modification, ligand binding, and interaction with the kinase CheA determine the size distribution. Our model compares favorably with a variety of signaling data, including dose-response curves of receptor activity and the dependence of activity on receptor density in the membrane. We propose that the kinetics of complex assembly can be measured in vitro from the temporal response to a perturbation of the complex free energies, e.g., by addition of ligand.     

Flexibility of alpha-helices: results of a statistical analysis of database protein structures

Alpha-helices stand out as common and relatively invariant secondary structural elements of proteins. However, alpha-helices are not rigid bodies and their deformations can be significant in protein function (e.g. coiled coils). To quantify the flexibility of alpha-helices we have performed a structural principal-component analysis of helices of different lengths from a representative set of protein folds in the Protein Data Bank. We find three dominant modes of flexibility: two degenerate bend modes and one twist mode. The data are consistent with independent Gaussian distributions for each mode. The mode eigenvalues, which measure flexibility, follow simple scaling forms as a function of helix length. The dominant bend and twist modes and their harmonics are reproduced by a simple spring model, which incorporates hydrogen-bonding and excluded volume. As an application, we examine the amount of bend and twist in helices making up all coiled-coil proteins in SCOP. Incorporation of alpha-helix flexibility into structure refinement and design is discussed.     

Flexibility of beta-sheets: principal component analysis of database protein structures

Protein folds are built primarily from the packing together of two types of structures: alpha-helices and beta-sheets. Neither structure is rigid, and the flexibility of helices and sheets is often important in determining the final fold (e.g., coiled coils and beta-barrels). Recent work has quantified the flexibility of alpha-helices using a principal component analysis (PCA) of database helical structures (J. Mol. Bio. 2003, 327, pp. 229-237). Here, we extend the analysis to beta-sheet flexibility using PCA on a database of beta-sheet structures. For sheets of varying dimension and geometry, we find two dominant modes of flexibility: twist and bend. The distributions of amplitudes for these modes are found to be Gaussian and independent, suggesting that the PCA twist and bend modes can be identified as the soft elastic normal modes of sheets. We consider the scaling of mode eigenvalues with sheet size and find that parallel beta-sheets are more rigid than antiparallel sheets over the entire range studied. Finally, we discuss the application of our PCA results to modeling and design of beta-sheet proteins.