Cation-exchange displacement chromatography of proteins with protamine displacers: effect of induced salt gradients.

Protamine was investigated for its utility as a protein displacer in cation-exchange systems. Although the protamine solution contained several variants of the molecule, the high affinity of all of the components in this heterogeneous biopolymer enabled it to act as an efficient protein displacer. To facilitate parameter estimation of the protamine, a preliminary purification was carried out by preparative elution chromatography. Chromatographic parameters of both the feed proteins and protamine displacer were obtained for use in a multicomponent steric mass action ion-exchange displacement model. Model simulations were compared to displacement results under both moderate and intense induced salt gradient conditions. In both cases, excellent agreement was obtained between the displacement experiments and theoretical predictions. In addition, these studies serve to dramatize the importance of induced salt gradients in ion-exchange displacement systems.     

A physiological analogy of the niche for projecting the potential distribution of plants

Aim  To develop a physiologically based model of the plant niche for use in species distribution modelling. Location  Europe. Methods  We link the Thornley transport resistance (TTR) model with functions which describe how the TTR’s model parameters are influenced by abiotic environmental factors. The TTR model considers how carbon and nutrient uptake, and the allocation of these assimilates, influence growth. We use indirect statistical methods to estimate the model parameters from a high resolution data set on tree distribution for 22 European tree species. Results  We infer, from distribution data and abiotic forcing data, the physiological niche dimensions of 22 European tree species. We found that the model fits were reasonable (AUC: 0.79–0.964). The projected distributions were characterized by a false positive rate of 0.19 and a false negative rate 0.12. The fitted models are used to generate projections of the environmental factors that limit the range boundaries of the study species. Main conclusions  We show that physiological models can be used to derive physiological niche dimensions from species distribution data. Future work should focus on including prior information on physiological rates into the parameter estimation process. Application of the TTR model to species distribution modelling suggests new avenues for establishing explicit links between distribution and physiology, and for generating hypotheses about how ecophysiological processes influence the distribution of plants.     

Why spikes? Hebbian learning and retrieval of time-resolved excitation patterns

Hebbian learning allows a network of spiking neurons to store and retrieve spatio-temporal patterns with a time resolution of 1 ms, despite the long postsynaptic and dendritic integration times. To show this, we introduce and analyze a model of spiking neurons, the spike response model, with a realistic distribution of axonal delays and with realistic postsynaptic potentials. Learning is performed by a local Hebbian rule which is based on the synchronism of presynaptic neurotransmitter release and some short-acting postsynaptic process. The time window of this synchronism determines the temporal resolution of pattern retrieval, which can be initiated by applying a short external stimulus pattern. Furthermore, a rate quantization is found in dependence upon the threshold value of the neurons, i.e., in a given time a pattern runsn times as often as learned, wheren is a positive integer (n 0). We show that all information about the spike pattern is lost if only mean firing rates (temporal average) or ensemble activities (spatial average) are considered. An average over several retrieval runs in order to generate a post-stimulus time histogram may also deteriorate the signal. The full information on a pattern is contained in the spike raster of a single run. Our results stress the importance, and advantage, of coding by spatio-temporal spike patterns instead of firing rates and average ensemble activity. The implications regarding modelling and experimental data analysis are discussed.     

The quantitative single-neuron modeling competition

As large-scale, detailed network modeling projects are flourishing in the field of computational neuroscience, it is more and more important to design single neuron models that not only capture qualitative features of real neurons but are quantitatively accurate in silico representations of those. Recent years have seen substantial effort being put in the development of algorithms for the systematic evaluation and optimization of neuron models with respect to electrophysiological data. It is however difficult to compare these methods because of the lack of appropriate benchmark tests. Here, we describe one such effort of providing the community with a standardized set of tests to quantify the performances of single neuron models. Our effort takes the form of a yearly challenge similar to the ones which have been present in the machine learning community for some time. This paper gives an account of the first two challenges which took place in 2007 and 2008 and discusses future directions. The results of the competition suggest that best performance on data obtained from single or double electrode current or conductance injection is achieved by models that combine features of standard leaky integrate-and-fire models with a second variable reflecting adaptation, refractoriness, or a dynamic threshold.     

Recognition of 16S rRNA by ribosomal protein S4 from Bacillus stearothermophilus

Protein S4 is essential for bacterial small ribosomal subunit assembly and recognizes the 5' domain (approximately 500 nt) of small subunit rRNA. This study characterizes the thermodynamics of forming the S4-5' domain rRNA complex from a thermophile, Bacillus stearothermophilus, and points out unexpected differences from the homologous Escherichia coli complex. Upon incubation of the protein and RNA at temperatures between 35 and 50 degrees C under ribosome reconstitution conditions [350 mM KCl, 8 mM MgCl2, and 30 mM Tris (pH 7.5)], a complex with an association constant of > or = 10(9) M(-1) was observed, more than an order of magnitude tighter than previously found for the homologous E. coli complex under similar conditions. This high-affinity complex was shown to be stoichiometric, in equilibrium, and formed at rates on the order of magnitude expected for diffusion-controlled reactions ( approximately 10(7) M(-1) x s(-1)), though at low temperatures the complex became kinetically trapped. Heterologous binding experiments with E. coli S4 and 5' domain RNA suggest that it is the B. stearothermophilus S4, not the rRNA, that is activated by higher temperatures; the E. coli S4 is able to bind 5' domain rRNA equally well at 0 and 37 degrees C. Tight complex formation requires a low Mg ion concentration (1-2 mM) and is very sensitive to KCl concentration [- partial differential[log(K)]/partial differential(log[KCl]) = 9.3]. The protein has an unusually strong nonspecific binding affinity of 3-5 x 10(6) M(-1), detected as a binding of one or two additional proteins to the target 5' domain RNA or two to three proteins binding a noncognate 23S rRNA fragment of the approximately same size. This binding is not as sensitive to monovalent ion concentration [- partial differential[log(K)]/partial differential(log[KCl]) = 6.3] as specific binding and does not require Mg ion. These findings are consistent with S4 stabilizing a compact form of the rRNA 5' domain.     

Structural preordering in the N-terminal region of ribosomal protein S4 revealed by heteronuclear NMR spectroscopy

Protein S4, a component of the 30S subunit of the prokaryotic ribosome, is one of the first proteins to interact with rRNA in the process of ribosome assembly and is known to be involved in the regulation of this process. While the structure of the C-terminal 158 residues of Bacillus stearothermophilus S4 has been solved by both X-ray crystallography and NMR, that of the N-terminal 41 residues is unknown. Evidence suggests that the N-terminus is necessary both for the assembly of functional ribosomes and for full binding to 16S RNA, and so we present NMR data collected on the full-length protein (200 aa). Our data indicate that the addition of the N-terminal residues does not significantly change the structure of the C-terminal 158 residues. The data further indicate that the N-terminus is highly flexible in solution, without discernible secondary structure. Nevertheless, structure calculations based on nuclear Overhauser effect spectroscopic data combined with (15)N relaxation data revealed that two short segments in the N-terminus, S(12)RRL(15) and P(30)YPP(33), adopt transiently ordered states in solution. The major conformation of S(12)RRL(15) appears to orient the arginine side chains outward toward the solvent in a parallel fashion, while that of P(30)YPP(33) forms a nascent turn of a polyproline II helix. These segments contain residues that are highly conserved across many prokaryotic species, and thus they are reasonable candidates respectively for sites of interaction with RNA and other ribosomal proteins within the intact ribosome.     

Bayesian hierarchical models suggest oldest known plant-visiting bat was omnivorous

The earliest record of plant visiting in bats dates to the Middle Miocene of La Venta, the world''s most diverse tropical palaeocommunity. Palynephyllum antimaster is known from molars that indicate nectarivory. Skull length, an important indicator of key traits such as body size, bite force and trophic specialization, remains unknown. We developed Bayesian models to infer skull length based on dental measurements. These models account for variation within and between species, variation between clades, and phylogenetic error structure. Models relating skull length to trophic level for nectarivorous bats were then used to infer the diet of the fossil. The skull length estimate for Palynephyllum places it among the larger lonchophylline bats. The inferred diet suggests Palynephyllum fed on nectar and insects, similar to its living relatives. Omnivory has persisted since the mid-Miocene. This is the first study to corroborate with fossil data that highly specialized nectarivory in bats requires an omnivorous transition.     

Repeatability of Cerebral Perfusion Using Dynamic Susceptibility Contrast MRI in Glioblastoma Patients

OBJECTIVES

This study evaluates the repeatability of brain perfusion using dynamic susceptibility contrast magnetic resonance imaging (DSC-MRI) with a variety of post-processing methods.

METHODS

Thirty-two patients with newly diagnosed glioblastoma were recruited. On a 3-T MRI using a dual-echo, gradient-echo spin-echo DSC-MRI protocol, the patients were scanned twice 1 to 5 days apart. Perfusion maps including cerebral blood volume (CBV) and cerebral blood flow (CBF) were generated using two contrast agent leakage correction methods, along with testing normalization to reference tissue, and application of arterial input function (AIF). Repeatability of CBV and CBF within tumor regions and healthy tissues, identified by structural images, was assessed with intra-class correlation coefficients (ICCs) and repeatability coefficients (RCs). Coefficients of variation (CVs) were reported for selected methods.

RESULTS

CBV and CBF were highly repeatable within tumor with ICC values up to 0.97. However, both CBV and CBF showed lower ICCs for healthy cortical tissues (up to 0.83), healthy gray matter (up to 0.95), and healthy white matter (WM; up to 0.93). The values of CV ranged from 6% to 10% in tumor and 3% to 11% in healthy tissues. The values of RC relative to the mean value of measurement within healthy WM ranged from 22% to 42% in tumor and 7% to 43% in healthy tissues. These percentages show how much variation in perfusion parameter, relative to that in healthy WM, we expect to observe to consider it statistically significant. We also found that normalization improved repeatability, but AIF deconvolution did not.

CONCLUSIONS

DSC-MRI is highly repeatable in high-grade glioma patients.