Vacuolar ion currents in the primitive green algaEremosphaera viridis: The electrical properties are suggestive of both the Characeae and higher plants

Summary The electrical properties of the vacuolar membrane of the primitive green algaEremosphaera virdis were investigated using the patch-clamp technique. In whole vacuole measurements two types of transport systems with long activation time-constants were identified. The first, showing marked outward rectification, was activated by an increase in the cytosolic calcium concentration. Furthermore, it displayed sensitivity to micromolar concentrations of the anion channel blocker Zn²⁺ and to acidification of the cytosol. In contrast, the second time-activated current component was almost insensitive to changes in cytosolic pH and was blocked by the potassium channel inhibitor TEA. In addition to these slowly activating current components, the vacuolar membrane contained at least two further transport systems, responsible for an instantaneous current. These two current components were distinguished by their different sensitivity to protons, cytosolic calcium, and TEA. Comparing these electrical properties to those observed in vacuoles of higher plants or in cytoplasmic droplets from characean algae, respectively, it seems thatEremosphaera is intermediate, corresponding to the systematic position of this simple green alga.Abbreviations [Ca²⁺]_cyt cytosolic free calcium concentration - EGTA ethyleneglycol-bis(-aminoethylether)N,N,N,N-tetraacetic acid - HEPES N-[2-hydroxyethyl]piperazine-N-[2-ethanesulfonic acid] - I electric current - IRC inward rectifying current - MES 2-[N-morpholino]ethanesulfonic acid - ORC outward rectifying current - pH_cyt cytosolic pH - pH_vac vacuolar pH - P_o open probability - P_x permeability coefficient of ion species X - TEA tetraethylammonium chloride - Tris tris[hydroxymethyl]aminomethane - V voltage     

Best Linear Unbiased Prediction (BLUP) for regional yield trials: a comparison to additive main effects and multiplicative interaction (AMMI) analysis

Multilocation trials are often used to analyse the adaptability of genotypes in different environments and to find for each environment the genotype that is best adapted; i.e. that is highest yielding in that environment. For this purpose, it is of interest to obtain a reliable estimate of the mean yield of a cultivar in a given environment. This article compares two different statistical estimation procedures for this task: the Additive Main Effects and Multiplicative Interaction (AMMI) analysis and Best Linear Unbiased Prediction (BLUP). A modification of a cross validation procedure commonly used with AMMI is suggested for trials that are laid out as a randomized complete block design. The use of these procedure is exemplified using five faba bean datasets from German registration trails. BLUP was found to outperform AMMI in four of five faba bean datasets.     

Lipophilicity of amino acids

Summary The lipophilicity (or hydrophobicity) of amino acids is an important property relevant for protein folding and therefore of great interest in protein engineering. For peptides or peptidomimetics of potential therapeutic interest, lipophilicity is related to absorption and distribution, and thus indirectly relates to their bioactivity. A rationalization of peptide lipophilicity requires basic knowledge of the lipophilicity of the constituting amino acids. In the present contribution we will review methods to measure or calculate the lipophilicities of amino acids, including unusual amino acids, and we will make a comparison between various lipophilicity scales.     

A method for α-helical integral membrane protein fold prediction

Integral membrane proteins (of the α-helical class) are of central importance in a wide variety of vital cellular functions. Despite considerable effort on methods to predict the location of the helices, little attention has been directed toward developing an automatic method to pack the helices together. In principle, the prediction of membrane proteins should be easier than the prediction of globular proteins: there is only one type of secondary structure and all helices pack with a common alignment across the membrane. This allows all possible structures to be represented on a simple lattice and exhaustively enumerated. Prediction success lies not in generating many possible folds but in recognizing which corresponds to the native. Our evaluation of each fold is based on how well the exposed surface predicted from a multiple sequence alignment fits its allocated position. Just as exposure to solvent in globular proteins can be predicted from sequence variation, so exposure to lipid can be recognized by variable-hydrophobic (variphobic) positions. Application to both bacteriorhodopsin and the eukaryotic rhodopsin/opsin families revealed that the angular size of the lipid-exposed faces must be predicted accurately to allow selection of the correct fold. With the inherent uncertainties in helix prediction and parameter choice, this accuracy could not be guaranteed but the correct fold was typically found in the top six candidates. Our method provides the first completely automatic method that can proceed from a scan of the protein sequence databanks to a predicted three-dimensional structure with no intervention required from the investigator. Within the limited domain of the seven helix bundle proteins, a good chance can be given of selecting the correct structure. However, the limited number of sequences available with a corresponding known structure makes further characterization of the method difficult. © 1994 John Wiley & Sons, Inc.     

Monte carlo simulations of protein folding. II. Application to protein A,ROP, and crambin

The hierarchy of lattice Monte Carlo models described in the accompanying paper (Kolinski, A., Skolnick, J. Monte Carlo simulations of protein folding. I. Lattice model and interaction scheme. Proteins 18:338–352, 1994) is applied to the simulation of protein folding and the prediction of 3-dimensional structure. Using sequence information alone, three proteins have been successfully folded: the B domain of staphylococcal protein A, a 120 residue, monomeric version of ROP dimer, and crambin. Starting from a random expanded conformation, the model proteins fold along relatively well-defined folding pathways. These involve a collection of early intermediates, which are followed by the final (and rate-determining) transition from compact intermediates closely resembling the molten globule state to the native-like state. The predicted structures are rather unique, with native-like packing of the side chains. The accuracy of the predicted native conformations is better than those obtained in previous folding simulations. The best (but by no means atypical) folds of protein A have a coordinate rms of 2.25 Å from the native Cα trace, and the best coordinate rms from crambin is 3.18 Å. For ROP monomer, the lowest coordinate rms from equivalent Cαs of ROP dimer is 3.65 Å. Thus, for two simple helical proteins and a small α/β protein, the ability to predict protein structure from sequence has been demonstrated. © 1994 John Wiley & Sons, Inc.     

Energy minimization method using automata network for sequence and side-chain conformation prediction from given backbone geometry

Globular proteins have high packing densities as a result of residue side chains in the core achieving a tight, complementary packing. The internal packing is considered the main determinant of native protein structure. From that point of view, we present here a method of energy minimization using an automata network to predict a set of amino acid sequences and their side-chain conformations from a desired backbone geometry for de novo design of proteins. Using discrete side-chain conformations, that is, rotamers, the sequence generation problem from a given backbone geometry becomes one of combinatorial problems. We focused on the residues composing the interior core region and predicted a set of amino acid Sequences and their side-chain conformations only from a given backbone geometry. The kinds of residues were restricted to six hydrophobic amino acids (Ala, Ile, Met, Leu, Phe, and Val) because the core regions are almost always composed of hydrophobic residues. The obtained sequences were well packed as was the native sequence. The method can be used for automated sequence generation in the de novo design of proteins. © 1994 Wiley-Liss, Inc.     

The effect of pulsed microwaves on passive electrical properties and interspike intervals of snail neurons

The effects of pulsed microwaves (2.45 GHz, 10 μs, 100 pps, SAR: 81.5 kW/kg peak, 81.5 W/kg average) on membrane input resistance and action potential (AP) interval statistics were studied in spontaneously active ganglion neurons of land snails (Helix aspersa), at strictly constant temperature (20.8±.07°C worst case). Statistical comparison with sham-irradiated neurons revealed a significant increase in the mean input resistance of neurons exposed to pulsed microwaves (P ? .05 ). Pulsed microwaves had no visible effect on mean AP firing rate; this observation was confirmed by analysis of interspike intervals (ISIs). Using an integrator model for spontaneously active neurons, we found the net input current to be more variable in neurons exposed to pulsed microwaves. The mean input current was not affected. The standard deviation of ISIs and the autocorrelation of the input current were marginally affected, but these changes were not consistent across neurons. Although the observed effects were less obvious than those reported in other studies, they represent evidence of a direct interaction between neurons and pulsed microwaves, in the absence of macroscopic temperature changes. The data do not suggest a single, specific mechanism for such interaction. © 1993 Wiley-Liss, Inc.     

Discrimination of folding types of globular proteins based on average distance maps constructed from their sequences

It has been shown that probable portions which form contacts in a protein can be predicted by means of an average distance map (ADM) as well as regular structures (-helices and -turns) defined as short-range compact regions (Kikuchiet al., 1988a,c). In this paper, we analyze the occurrence of those portions and short-range compact regions on ADMs for various proteins regarding their folding types. We have found out that each folding type of proteins shows characteristic distribution of such parts on ADMS. We also discuss the possibility of the prediction of folding types of proteins by ADMs.     

Detrending climate data prior to climate–growth analyses in dendroecology: A common best practice?

Tree growth varies closely with high–frequency climate variability. Since the 1930s detrending climate data prior to comparing them with tree growth data has been shown to better capture tree growth sensitivity to climate. However, in a context of increasingly pronounced trends in climate, this practice remains surprisingly rare in dendroecology. In a review of Dendrochronologia over the 2018–2021 period, we found that less than 20 % of dendroecological studies detrended climate data prior to climate-growth analyses. With an illustrative study, we want to remind the dendroecology community that such a procedure is still, if not more than ever, rational and relevant. We investigated the effects of detrending climate data on climate–growth relationships across North America over the 1951–2000 period. We used a network of 2536 tree individual ring-width series from the Canadian and Western US forest inventories. We compared correlations between tree growth and seasonal climate data (Tmin, Tmax, Prec) both raw and detrended. Detrending approaches included a linear regression, 30-yr and 100-yr cubic smoothing splines. Our results indicate that on average the detrending of climate data increased climate–growth correlations. In addition, we observed that strong trends in climate data translated to higher variability in inferred correlations based on raw vs. detrended climate data. We provide further evidence that our results hold true for the entire spectrum of dendroecological studies using either mean site chronologies and correlations coefficients, or individual tree time series within a mixed-effects model framework where regression coefficients are used more commonly. We show that even without a change in correlation, regression coefficients can change a lot and we tend to underestimate the true climate impact on growth in case of climate variables containing trends. This study demonstrates that treating climate and tree-ring time series “like-for-like” is a necessary procedure to reduce false negatives and positives in dendroecological studies. Concluding, we recommend using the same detrending for climate and tree growth data when tree-ring time series are detrended with splines or similar frequency-based filters.