Trimethyloxonium modification of single batrachotoxin-activated sodium channels in planar bilayers. Changes in unit conductance and in block by saxitoxin and calcium

Single batrachotoxin-activated sodium channels from rat brain were modified by trimethyloxonium (TMO) after incorporation in planar lipid bilayers. TMO modification eliminated saxitoxin (STX) sensitivity, reduced the single channel conductance by 37%, and reduced calcium block of inward sodium currents. These effects always occurred concomitantly, in an all-or-none fashion. Calcium and STX protected sodium channels from TMO modification with potencies similar to their affinities for block. Calcium inhibited STX binding to rat brain membrane vesicles and relieved toxin block of channels in bilayers, apparently by competing with STX for the toxin binding site. These results suggest that toxins, permeant cations, and blocking cations can interact with a common site on the sodium channel near the extracellular surface. It is likely that permeant cations transiently bind to this superficial site, as the first of several steps in passing inward through the channel.     

Relative apparent synapomorphy analysis (RASA). I: The statistical measurement of phylogenetic signal

We have developed a new approach to the measurement of phylogenetic signal in character state matrices called relative apparent synapomorphy analysis (RASA). RASA provides a deterministic, statistical measure of natural cladistic hierarchy (phylogenetic signal) in character state matrices. The method works by determining whether a measure of the rate of increase of cladistic similarity among pairs of taxa as a function of phenetic similarity is greater than a null equiprobable rate of increase. Our investigation of the utility and limitations of RASA using simulated and bacteriophage T7 data sets indicates that the method has numerous advantages over existing measures of signal. A first advantage is computational efficiency. A second advantage is that RASA employs known methods of statistical inference, providing measurable sensitivity and power. The performance of RASA is examined under various conditions of branching evolution as the number of characters, character states per character, and mutations per branch length are varied. RASA appears to provide an unbiased and reliable measure of phylogenetic signal, and the general approach promises to be useful in the development of new techniques that should increase the rigor and reliability of phylogenetic estimates.      

Structural and evolutionary division of phosphotyrosine binding (PTB) domains

Proteins encoding phosphotyrosine binding (PTB) domains function as adaptors or scaffolds to organize the signaling complexes involved in wide-ranging physiological processes including neural development, immunity, tissue homeostasis and cell growth. There are more than 200 proteins in eukaryotes and nearly 60 human proteins having PTB domains. Six PTB domain encoded proteins have been found to have mutations that contribute to inherited human diseases including familial stroke, hypercholesteremia, coronary artery disease, Alzheimer's disease and diabetes, demonstrating the importance of PTB scaffold proteins in organizing critical signaling complexes. PTB domains bind both peptides and headgroups of phosphatidylinositides, utilizing two distinct binding motifs to mediate spatial organization and localization within cells. The structure of PTB domains confers specificity for binding peptides having a NPXY motif with differing requirements for phosphorylation of the tyrosine within this recognition sequence. In this review, we use structural, evolutionary and functional analysis to divide PTB domains into three groups represented by phosphotyrosine-dependent Shc-like, phosphotyrosine-dependent IRS-like and phosphotyrosine-independent Dab-like PTBs, with the Dab-like PTB domains representing nearly 75% of proteins encoding PTB domains. In addition, we further define the binding characteristics of the cognate ligands for each group of PTB domains. The signaling complexes organized by PTB domain encoded proteins are largely unknown and represents an important challenge in systems biology for the future.     

The GoLoco motif: heralding a new tango between G protein signaling and cell division

The Galpha and Gbetagamma components of heterotrimeric G proteins, typically associated with cell-surface receptor signaling, also partake in the macromolecular interactions that underlie cell polarity and cell division. Proteins with Galpha-binding GoLoco motifs, such as Drosophila melanogaster Pins (for Partner of Inscuteable) and its mammalian counterpart LGN, participate in multi-protein complexes that maintain cellular asymmetry and orderly segregation of chromosomal content and daughter cell bodies. The GoLoco motif was recently identified as a selective Galpha-binding partner: the GoLoco-Galpha interaction can displace Gbetagamma and inhibit guanine nucleotide release from the bound Galpha subunit. Recent x-ray crystallographic studies suggest ways in which GoLoco-motif peptides may modulate heterotrimeric G protein signaling. Such peptides could be exploited to help dissect the signals that underpin cell polarity and cell division processes.     

The diabetic rat kidney mediates inosituria and selective urinary partitioning of D-chiro-inositol

Diabetic nephropathy is a serious complication of diabetes mellitus with a pressing need for effective metabolic markers to detect renal impairment. Of potential significance are the inositol compounds, myo-inositol (MI), and the less abundant stereoisomer, D-chiro-inositol (DCI), which are excreted at increased levels in the urine in diabetes mellitus, a phenomenon known as inosituria. There is also a selective urinary excretion of DCI compared to MI. As the biological origins of altered inositol metabolism in diabetes mellitus are unknown, the aim of this study was to determine whether the diabetic kidney was directly responsible. Kidneys isolated from four-week streptozotocin-induced diabetic rats were characterized by a 3-fold reduction in glomerular filtration rate (GFR) compared to matched non-diabetic kidneys. When perfused with fixed quantities of MI (50 µM) and DCI (5 µM) under normoglycemic conditions (5 mM glucose), GFR-normalized urinary excretion of MI was increased by 1.7-fold in diabetic vs. non-diabetic kidneys. By comparison, GFR-normalized urinary excretion of DCI was increased by 4-fold. Perfusion conditions replicating hyperglycemia (20 mM glucose) potentiated DCI but not MI urinary excretion in both non-diabetic and diabetic kidneys. Overall, there was a 2.4-fold increase in DCI urinary excretion compared to MI in diabetic kidneys that was independent of glucose ambience. This increased urinary excretion of DCI and MI in diabetic kidneys occurred despite increased renal expression of the inositol transporters, sodium myo-inositol transporter subtype 1 and 2 (SMIT1 and SMIT2). These findings show that the diabetic kidney primarily mediates inosituria and altered urinary partitioning of MI and DCI. Urinary inositol levels might therefore serve as an indicator of impaired renal function in diabetes mellitus with wider implications for monitoring chronic kidney disease.     

Use of the EM algorithm to detect QTL affecting multiple-traits in an across half-sib family analysis

QTL detection experiments in livestock species commonly use the half-sib design. Each male is mated to a number of females, each female producing a limited number of progeny. Analysis consists of attempting to detect associations between phenotype and genotype measured on the progeny. When family sizes are limiting experimenters may wish to incorporate as much information as possible into a single analysis. However, combining information across sires is problematic because of incomplete linkage disequilibrium between the markers and the QTL in the population. This study describes formulæ for obtaining MLEs via the expectation maximization (EM) algorithm for use in a multiple-trait, multiple-family analysis. A model specifying a QTL with only two alleles, and a common within sire error variance is assumed. Compared to single-family analyses, power can be improved up to fourfold with multi-family analyses. The accuracy and precision of QTL location estimates are also substantially improved. With small family sizes, the multi-family, multi-trait analyses reduce substantially, but not totally remove, biases in QTL effect estimates. In situations where multiple QTL alleles are segregating the multi-family analysis will average out the effects of the different QTL alleles.