Kinetic and thermodynamic parameters for oxygen binding to the allosteric states of Panulirus interruptus hemocyanin

The temperature dependence of the oxygen binding equilibria and kinetics of Panulirus interruptus hemocyanin has been analyzed within the context of the two-state allosteric model. Oxygenation of the T-state is characterized by a more negative value of DeltaH than that of the R-state; therefore, cooperative effects in oxygen binding to P. interruptus hemocyanin are thermodynamically governed by favorable entropy changes. The allosteric transition in the unliganded derivative shows an enthalpy-entropy compensation effect. The activation enthalpies for oxygenation and deoxygenation of the T-state are larger than those for the R-state, while the activation entropies are favorable for the T-state and unfavorable for the R-state. Thus, the activation free energies for oxygen binding to the T- and R-states are similar, while for the deoxygenation reaction DeltaG++ is smaller for the T-state. The analysis reported confirms the applicability of the Monod-Wyman-Changeux two-state allosteric model to P. interruptus hemocyanin and yields a complete thermodynamic characterization of oxygen binding under both equilibrium and dynamic regimes.     

Creatine Kinase–Mediated ATP Supply Fuels Actin-Based Events in Phagocytosis

Phagocytosis requires locally coordinated cytoskeletal rearrangements driven by actin polymerization and myosin motor activity. How this actomyosin dynamics is dependent upon systems that provide access to ATP at phagosome microdomains has not been determined. We analyzed the role of brain-type creatine kinase (CK-B), an enzyme involved in high-energy phosphoryl transfer. We demonstrate that endogenous CK-B in macrophages is mobilized from the cytosolic pool and coaccumulates with F-actin at nascent phagosomes. Live cell imaging with XFP-tagged CK-B and β-actin revealed the transient and specific nature of this partitioning process. Overexpression of a catalytic dead CK-B or CK-specific cyclocreatine inhibition caused a significant reduction of actin accumulation in the phagocytic cup area, and reduced complement receptor–mediated, but not Fc-γR–mediated, ingestion capacity of macrophages. Finally, we found that inhibition of CK-B affected phagocytosis already at the stage of particle adhesion, most likely via effects on actin polymerization behavior. We propose that CK-B activity in macrophages contributes to complement-induced F-actin assembly events in early phagocytosis by providing local ATP supply.     

Partitioning of fish and insect antifreeze proteins into ice suggests they bind with comparable affinity

Antifreeze proteins (AFPs) inhibit the growth of ice by binding to the surface of ice crystals, preventing the addition of water molecules to cause a local depression of the freezing point. AFPs from insects are much more effective at depressing the freezing point than fish AFPs. Here, we have investigated the possibility that insect AFPs bind more avidly to ice than fish AFPs. Because it is not possible to directly measure the affinity of an AFP for ice, we have assessed binding indirectly by examining the partitioning of proteins into a slowly growing ice hemisphere. AFP molecules adsorbed to the surface and became incorporated into the ice as they were overgrown. Solutes, including non-AFPs, were very efficiently excluded from ice, whereas AFPs became incorporated into ice at a concentration roughly equal to that of the original solution, and this was independent of the AFP concentration in the range (submillimolar) tested. Despite their >10-fold difference in antifreeze activity, fish and insect AFPs partitioned into ice to a similar degree, suggesting that insect AFPs do not bind to ice with appreciably higher affinity. Additionally, we have demonstrated that steric mutations on the ice binding surface that decrease the antifreeze activity of an AFP also reduce its inclusion into ice, supporting the validity of using partitioning measurements to assess a protein's affinity for ice.     

Two high-density AFLP® linkage maps of Zea mays L.: analysis of distribution of AFLP markers

This study demonstrates the relative ease of generating high-density linkage maps using the AFLP® technology. Two high-density AFLP linkage maps of Zea mays L. were generated based on: (1) a B73 × Mo17 recombinant inbred population and (2) a D32 × D145 immortalized F₂ population. Although AFLP technology is in essence a mono-allelic marker system, markers can be scored quantitatively and used to deduce zygosity. AFLP markers were generated using the enzyme combinations EcoRI/MseI and PstI/MseI. A total of 1539 and 1355 AFLP markers have been mapped in the two populations, respectively. Among the mapped PstI/MseIAFLP markers we have included fragments bounded by a methylated PstI site (^mAFLP markers). Mapping these ^mAFLP markers shows that the presence of C-methylation segregates in perfect accordance with the primary target sequence, leading to Mendelian inheritance. Simultaneous mapping of PstI/MseIAFLP and PstI/MseI ^mAFLP markers allowed us to identify a number of epi-alleles, showing allelic variation in the CpNpG methylation only. However, their frequency in maize is low. Map comparison shows that, despite some rearrangements, most of the AFLP markers that are common in both populations, map at similar positions. This would indicate that AFLP markers are predominantly single-locus markers. Changes in map order occur mainly in marker-dense regions. These marker-dense regions, representing clusters of mainly EcoRI/MseI AFLP and PstI/MseI ^mAFLP markers, co- localize well with the putative centromeric regions of the maize chromosomes. In contrast, PstI/MseImarkers are more uniformly distributed over the genome.     

Responses to internal nitrogen and phosphorus concentrations of two Taraxacum microspecies of contrasting mineral ecology: critical N and P concentrations of whole plants

Of the two Taraxacum microspecies used. Taraxacum sellandii Dahlst. usually occurs in grasslands with a high nutrient level; Taraxacum nordstedtii Dahlst. is generally restricted to undisturbed and mineral-poor habitats. Growth response curves for internal N and P were established, based on relative yield of (whole) plant tissue water and (whole plant) internal mineral concentration on a tissue water basis. Critical nutrient concentrations of N and P were determined from the response curves derived. For both macroelements, T. nordstedtii showed lower critical nutrient concentrations. The difference in critical N concentrations coincided with differences in internal NO₃^-₃ concentrations between the microspecies. Finally, we discuss the use of tissue water as a (whole) plant growth parameter and internal mineral concentration on tissue water basis as a parameter describing the mineral status.     

Genetic differentiation and phenotypic plasticity in Plantago major ssp major. I. The effect of differences in level of irradiance on growth, photosynthesis, respiration and chlorophyll content

Growth, root respiration, photosynthesis, dark respiration, chlorophyll content and chlorophyll alb ratio were followed in two genotypes of Plantago major L. ssp major L., originating from an exposed and a shaded habitat, respectively, at two levels of irradiance. In addition, responses of these processes to a transfer of plants from one light condition to the other were studied. Genetic differentiation between the two genotypes was reflected in growth rate, photosynthetic activity, dark respiration and chlorophyll content. Individuals of the genotype originating from a shaded habitat were less inhibited by low irradiance: growth was less depressed at low irradiance, while the genotype of the exposed habitat seemed to be more restricted to exposed conditions. The adaptive plastic response of growth and physiological parameters upon an alteration in irradiance was very small. The shoot to root ratio was a stable plant characteristic in these experiments. Plants of both genotypes were probably damaged after a transfer from the low to the high level of irradiance; the growth of these plants was not stimulated by high irradiance, and the photosynthetic activity was even decreased. Plants, which were transferred to the low level of irradiance, showed an immediate effect of the change and no adaptive response was observed. Obviously, the ability to perform adaptive plastic responses, which was demonstrated in the non-transferred plants after pretreatment, had been lost during the experiment and was confined to the seedling stage of individuals of the two genotypes.     

Discovery of Drug Synergies in Gastric Cancer Cells Predicted by Logical Modeling

Discovery of efficient anti-cancer drug combinations is a major challenge, since experimental testing of all possible combinations is clearly impossible. Recent efforts to computationally predict drug combination responses retain this experimental search space, as model definitions typically rely on extensive drug perturbation data. We developed a dynamical model representing a cell fate decision network in the AGS gastric cancer cell line, relying on background knowledge extracted from literature and databases. We defined a set of logical equations recapitulating AGS data observed in cells in their baseline proliferative state. Using the modeling software GINsim, model reduction and simulation compression techniques were applied to cope with the vast state space of large logical models and enable simulations of pairwise applications of specific signaling inhibitory chemical substances. Our simulations predicted synergistic growth inhibitory action of five combinations from a total of 21 possible pairs. Four of the predicted synergies were confirmed in AGS cell growth real-time assays, including known effects of combined MEK-AKT or MEK-PI3K inhibitions, along with novel synergistic effects of combined TAK1-AKT or TAK1-PI3K inhibitions. Our strategy reduces the dependence on a priori drug perturbation experimentation for well-characterized signaling networks, by demonstrating that a model predictive of combinatorial drug effects can be inferred from background knowledge on unperturbed and proliferating cancer cells. Our modeling approach can thus contribute to preclinical discovery of efficient anticancer drug combinations, and thereby to development of strategies to tailor treatment to individual cancer patients.