Lithium transport across isolated frog skin epithelium

Summary Transepithelial Li⁺ influx was studied in the isolated epithelium from abdominal skin ofRana catesbeiana. With Na⁺-Ringer's as inside medium and Li⁺-Ringer's as outside medium, the Li⁺ influx across the epithelium was 15.6 A/cm². This influx was considerably reduced by removal of either Na⁺ or K⁺ from the inside bath or by the addition of ouabain or amiloride. Epithelial K⁺ or Na⁺ concentration was respectively lower in epithelia bathed in K⁺-free Ringer's or Na⁺-free Ringer's. In conditions of negligible Na⁺ transport, a 20mm Li⁺ gradient (outin) produced across the short-circuited epithelium a Li⁺ influx of 11.8 A/cm² and a mean short-circuit current of 10.2 A/cm². The same Li⁺ gradient in the opposite direction produced a Li⁺ outflux of only 1.9 A/cm². With equal Li⁺ concentration (10.3 and 20.6mm) on both sides of the epithelium, plus Na⁺ in the inside solution only, a stable Li⁺-dependent short-circuit current was observed. Net Li⁺ movement (outin) was also indirectly determined in the presence of an opposing Li⁺ gradient. Although Li⁺ does not substitute for Na⁺ as an activator of the (Na⁺+K⁺)-ATPase from frog skin epithelium, Li⁺ influx appears to be related to Na⁺–K⁺ pump activity. It is proposed that the permeability of the outer barrier to Na⁺ and Li⁺ is regulated by the electrical gradient produced by electrogenic Na⁺–K⁺ pumps located in the membrane of the deeper epithelial cells.     

Creation of an allosteric phosphofructokinase starting with a nonallosteric enzyme. The case of dictyostelium discoideum phosphofructokinase.

An allosteric phosphofructokinase (PFK) was created by sequence manipulation of the nonallosteric enzyme from the slime mold Dictyostelium discoideum (DdPFK). Most amino acid residues proposed as important for catalytic and allosteric sites are conserved in DdPFK except for a few of them, and their reversion did not modify its kinetic behavior. However, deletions at the unique C-terminal extension of this PFK produced a markedly allosteric enzyme. Thus, a mutant lacking the last 26 C-terminal residues exhibited hysteresis in the time course, intense cooperativity (n(H) = 3.8), and a 200-fold decrease in the apparent affinity for fructose 6-phosphate (S(0.5) = 4500 microm), strong activation by fructose 2,6-bisphosphate (K(act) = 0.1 microm) and fructose 1,6-bisphosphate (K(act) = 40 microm), dependence on enzyme concentration, proton inhibition, and subunit association-dissociation in response to fructose 6-phosphate versus the nonhysteretic and hyperbolic wild-type enzyme (n(H) = 1.0; K(m) = 22 microm) that remained as a stable tetramer. Systematic deletions and point mutations at the C-tail region of DdPFK identified the last C-terminal residue, Leu(834), as critical to produce a nonallosteric enzyme. All allosteric mutants were practically insensitive to MgATP inhibition, suggesting that this effect does not involve the same allosteric transition as that responsible for fructose 6-phosphate cooperativity and fructose bisphosphate activation.     

Inter-Network Interactions: Impact of Connections between Oscillatory Neuronal Networks on Oscillation Frequency and Pattern

Oscillations in electrical activity are a characteristic feature of many brain networks and display a wide variety of temporal patterns. A network may express a single oscillation frequency, alternate between two or more distinct frequencies, or continually express multiple frequencies. In addition, oscillation amplitude may fluctuate over time. The origin of this complex repertoire of activity remains unclear. Different cortical layers often produce distinct oscillation frequencies. To investigate whether interactions between different networks could contribute to the variety of oscillation patterns, we created two model networks, one generating on its own a relatively slow frequency (20 Hz; slow network) and one generating a fast frequency (32 Hz; fast network). Taking either the slow or the fast network as source network projecting connections to the other, or target, network, we systematically investigated how type and strength of inter-network connections affected target network activity. For high inter-network connection strengths, we found that the slow network was more effective at completely imposing its rhythm on the fast network than the other way around. The strongest entrainment occurred when excitatory cells of the slow network projected to excitatory or inhibitory cells of the fast network. The fast network most strongly imposed its rhythm on the slow network when its excitatory cells projected to excitatory cells of the slow network. Interestingly, for lower inter-network connection strengths, multiple frequencies coexisted in the target network. Just as observed in rat prefrontal cortex, the target network could express multiple frequencies at the same time, alternate between two distinct oscillation frequencies, or express a single frequency with alternating episodes of high and low amplitude. Together, our results suggest that input from other oscillating networks may markedly alter a network''s frequency spectrum and may partly be responsible for the rich repertoire of temporal oscillation patterns observed in the brain.