Differences in conductance of M2 proton channels of two influenza viruses at low and high pH

The M2 protein of influenza A viruses forms a proton channel involved in modifying virion and trans Golgi pH during infection. Previous studies of the proton current using whole-cell patch clamp of mouse erythroleukaemia (MEL) cells expressing the M2 protein of the ‘Weybridge’ strain provided evidence for two protonation sites, one involved in permeation, the other in activation by acid pH. The present report compares the M2 channels of two different strains of influenza virus, ‘Weybridge’ (WM2) and ‘Rostock’ (RM2). Whereas with external acid pH the current-voltage relations showed similar small degrees of inward rectification, a similar apparent Kd of approximately 10 μm for proton permeation and a high selectivity for protons over Na+, the two M2 proteins differed in whole-cell conductance at low and high pH. The proton conductance of unit membrane area was on average 7-fold greater in RM2- than WM2-expressing MEL cells. At high external pH WM2 was shown previously to have small conductance for outward current at positive driving potential. In contrast, RM2 shows high conductance for outward current with high external pH, but shows small conductance for inward current with high internal pH, conditions in which WM2 shows high conductance for inward current. The different properties of the conductances due to the two channels at high pH were determined by three amino acids in their transmembrane domains. All intermediate mutants possessed one or other property and transformation of the WM2 phenotype into that of RM2 required substitution in all three residues V27I, F38L and D44N; single substitutions in RM2 effected the opposite phenotypic change. The significance of this difference for virus replication is not clear and it may be that the higher proton flux associated with RM2 is the main factor determining its increased ability to dissipate pH gradients. It is apparent, however, from the specific differences in the sidedness of the pH-induced changes in voltage dependence of the whole-cell current that this is an intrinsic property of the virus proton channel which may have parallels with regulation of other proton channels

Modulation of NMDA Receptor Channels by Intracellular Calcium

In the mammalian central nervous system (CNS) excitatory synaptic transmission is mediated by glutamate which co-activates N-methyl-D-aspartate receptor (NMDAR) and α-amino-3-hydroxy-5-methyl-4-isoxazole-propionate receptor (AMPAR) channels, co-localized in the postsynaptic membrane. Fast synaptic currents are mediated by AMPAR channels whereas NMDAR channels generate slower, longer lasting currents (Forsythe & Westbrook, 1988; Bekkers & Stevens, 1989; Stern et al., 1992; Spruston et al., 1995). NMDAR channels are highly permeable for Ca2+ (MacDermott et al., 1986; Mayer & Westbrook, 1987; Ascher & Nowak, 1988) and contribute to the synaptically evoked elevation of Ca2+ in dendritic spines (Müller & Connor, 1991; Perkel et al., 1993; Malinow et al., 1994). Native NMDAR are heteromeric channels composed of NR1 and one or more of the four NR2 subunits belonging to the NMDAR family of ionotropic glutamate receptors (Hollmann & Heinemann, 1994). Each of the subunit imparts specific functional property to the channel providing a wide spectrum for the regulation of the NMDAR channel function. The NMDAR is a subject to modulation by a number of extracellular and intracellular agents including Mg2+, Zn2+, glycine, polyamines, protons, reducing agents, protein kinases and Ca2

How Computational Models Enable Mechanistic Insights into Virus Infection

An implicit aim in cellular infection biology is to understand the mechanisms how viruses, microbes, eukaryotic parasites, and fungi usurp the functions of host cells and cause disease. Mechanistic insight is a deep understanding of the biophysical and biochemical processes that give rise to an observable phenomenon. It is typically subject to falsification, that is, it is accessible to experimentation and empirical data acquisition. This is different from logic and mathematics, which are not empirical, but built on systems of inherently consistent axioms. Here, we argue that modeling and computer simulation, combined with mechanistic insights, yields unprecedented deep understanding of phenomena in biology and especially in virus infections by providing a way of showing sufficiency of a hypothetical mechanism. This ideally complements the necessity statements accessible to empirical falsification by additional positive evidence. We discuss how computational implementations of mathematical models can assist and enhance the quantitative measurements of infection dynamics of enveloped and non-enveloped viruses and thereby help generating causal insights into virus infection biology