Biomedical subjects

Richard Bertram

Publications and source records attributed to Richard Bertram.

6 recordsLinked to original sources

PubMed2003

A minimal model for G protein-mediated synaptic facilitation and depression.

G protein-coupled receptors are ubiquitous in neurons, as well as other cell types. Activation of receptors by hormones or neurotransmitters splits the G protein heterotrimer into Galpha and Gbetagamma subunits. It is now clear that Gbetagamma directly inhibits Ca2+ channels, putting them into a reluctant state. The effects of Gbetagamma depend on the specific beta and gamma subunits present, as well as the beta subunit isoform of the N-type Ca2+ channel. We describe a minimal mathematical model for the effects of G protein action on the dynamics of synaptic transmission. The model is calibrated by data obtained by transfecting G protein and Ca2+ channel subunits into tsA-201 cells. We demonstrate with numerical simulations that G protein action can provide a mechanism for either short-term synaptic facilitation or depression, depending on the manner in which G protein-coupled receptors are activated. The G protein action performs high-pass filtering of the presynaptic signal, with a filter cutoff that depends on the combination of G protein and Ca2+ channel subunits present. At stimulus frequencies above the cutoff, trains of single spikes are transmitted, while only doublets are transmitted at frequencies below the cutoff. Finally, we demonstrate that relief of G protein inhibition can contribute to paired-pulse facilitation.

Cell Line↗

PubMed2003

The Ca2+ dynamics of isolated mouse beta-cells and islets: implications for mathematical models.

[Ca(2+)](i) and electrical activity were compared in isolated beta-cells and islets using standard techniques. In islets, raising glucose caused a decrease in [Ca(2+)](i) followed by a plateau and then fast (2-3 min(-1)), slow (0.2-0.8 min(-1)), or a mixture of fast and slow [Ca(2+)](i) oscillations. In beta-cells, glucose transiently decreased and then increased [Ca(2+)](i), but no islet-like oscillations occurred. Simultaneous recordings of [Ca(2+)](i) and electrical activity suggested that differences in [Ca(2+)](i) signaling are due to differences in islet versus beta-cell electrical activity. Whereas islets exhibited bursts of spikes on medium/slow plateaus, isolated beta-cells were depolarized and exhibited spiking, fast-bursting, or spikeless plateaus. These electrical patterns in turn produced distinct [Ca(2+)](i) patterns. Thus, although isolated beta-cells display several key features of islets, their oscillations were faster and more irregular. beta-cells could display islet-like [Ca(2+)](i) oscillations if their electrical activity was converted to a slower islet-like pattern using dynamic clamp. Islet and beta-cell [Ca(2+)](i) changes followed membrane potential, suggesting that electrical activity is mainly responsible for the [Ca(2+)] dynamics of beta-cells and islets. A recent model consisting of two slow feedback processes and passive endoplasmic reticulum Ca(2+) release was able to account for islet [Ca(2+)](i) responses to glucose, islet oscillations, and conversion of single cell to islet-like [Ca(2+)](i) oscillations. With minimal parameter variation, the model could also account for the diverse behaviors of isolated beta-cells, suggesting that these behaviors reflect natural cell heterogeneity. These results support our recent model and point to the important role of beta-cell electrical events in controlling [Ca(2+)](i) over diverse time scales in islets.

Action Potentials↗

PubMed2003

Atomic refinement with correlated solid-state NMR restraints.

The orientation data provided by solid-state NMR can provide a great deal of structural information about membrane proteins. The quality of the information provided is, however, somewhat degraded by sign degeneracies in measurements of the dipolar coupling tensor. This is reflected in the dipolar coupling penalty function used in atomic refinement, which is less capable of properly restraining atoms when dipolar sign degeneracies are present. In this report we generate simulated solid-state NMR data using a variety of procedures, including back-calculation from crystal structures of alpha-helical and beta-sheet membrane proteins. We demonstrate that a large fraction of the dipolar sign degeneracies are resolved if anisotropic dipolar coupling measurements are correlated with anisotropic chemical shift measurements, and that all sign degeneracies can be resolved if three data types are correlated. The advantages of correlating data are demonstrated with atomic refinement of two test membrane proteins. When refinement is performed using correlated dipolar couplings and chemical shifts, perturbed structures converge to conformations with a larger fraction of correct dipolar signs than when data are uncorrelated. In addition, the final structures are closer to the original unperturbed structures when correlated data are used in the refinement. Thus, refinement with correlated data leads to improved atomic structures. The software used to correlate dipolar coupling and chemical shift data and to set up energy functions and their derivatives for refinement, CNS-SS02, is available at our web site.

Algorithms↗

PubMed2002

Simulated-annealing real-space refinement as a tool in model building.

Methods have been developed that further automate the building of macromolecular structures into electron-density maps. The software supports molecular-dynamics real-space refinement of an atomic model to local regions of a map within the context of a popular molecular-modeling program, O [Jones et al. (1991), Acta Cryst. A47, 110-119]. It is implemented as a module to the CNS refinement package [Brünger et al. (1998), Acta Cryst. D54, 905-921], controlled by a graphical user interface and commands executed directly through the molecular-graphics package. The method is illustrated with examples of the building and rebuilding of protein and nucleic acid models in which laborious manual adjustments are avoided. The resulting models show improved convergence during subsequent reciprocal-space refinement. The novel feature of the RSRef2000 software is the combination of simulated-annealing optimization with local real-space refinement, allowing several local minima to be explored quickly and automatically within the context of interactive model building.

Arginine Kinase↗

PubMed2002

An improved hydrogen bond potential: impact on medium resolution protein structures.

A new semi-empirical force field has been developed to describe hydrogen-bonding interactions with a directional component. The hydrogen bond potential supports two alternative target angles, motivated by the observation that carbonyl hydrogen bond acceptor angles have a bimodal distribution. It has been implemented as a module for a macromolecular refinement package to be combined with other force field terms in the stereochemically restrained refinement of macromolecules. The parameters for the hydrogen bond potential were optimized to best fit crystallographic data from a number of protein structures. Refinement of medium-resolution structures with this additional restraint leads to improved structure, reducing both the free R-factor and over-fitting. However, the improvement is seen only when stringent hydrogen bond selection criteria are used. These findings highlight common misconceptions about hydrogen bonding in proteins, and provide explanations for why the explicit hydrogen bonding terms of some popular force field sets are often best switched off.

Animals↗

PubMed2002

Role for G protein Gbetagamma isoform specificity in synaptic signal processing: a computational study.

Computational modeling is used to investigate the functional impact of G protein-mediated presynaptic autoinhibition on synaptic filtering properties. It is demonstrated that this form of autoinhibition, which is relieved by depolarization, acts as a high-pass filter. This contrasts with vesicle depletion, which acts as a low-pass filter. Model parameters are adjusted to reproduce kinetic slowing data from different Gbetagamma dimeric isoforms, which produce different degrees of slowing. With these sets of parameter values, we demonstrate that the range of frequencies filtered out by the autoinhibition varies greatly depending on the Gbetagamma isoform activated by the autoreceptors. It is shown that G protein autoinhibition can enhance the spatial contrast between a spatially distributed high-frequency signal and surrounding low-frequency noise, providing an alternate mechanism to lateral inhibition. It is also shown that autoinhibition can increase the fidelity of coincidence detection by increasing the signal-to-noise ratio in the postsynaptic cell. The filter cut, the input frequency below which signals are filtered, depends on several biophysical parameters in addition to those related to Gbetagamma binding and unbinding. By varying one such parameter, the rate at which transmitter unbinds from autoreceptors, we show that the filter cut can be adjusted up or down for several of the Gbetagamma isoforms. This allows for great synapse-to-synapse variability in the distinction between signal and noise.

Artifacts↗