Osmotic adjustment in tobacco plantlets

UsingNicotiana tabacum L. plantlets cultivatedin vitro as a model system it was proved that osmotic adjustment may be caused by a decrease in water potential of substrate as well as by a decrease in air humidity.     

Chromosome aberrations caused by the effect of ultrasound in the meristematic cells ofvicia faba

In our present work the formation of chromosome aberrations has been studied in dependence on the tima interval between sonication and fixation of the primary root tips of Vicia faba. Maximum occurrence of aberrations was recorded immediately after sonication. The results of our experiments pointed to the fact that the frequency of the induced changes was independent on the sonic waves intensity within the range of 0-2—3-0 W/cm² and on ultrasond treatment duration within the range of 1—20 min. Studies of the distribution of chromosome abnormalities caused by ultrasound between the large and small chromosomes of theVicia faba meristematic cells in various time intervals showed that the frequency of the aberrations in both chromosome groups was proportional to its total metaphase lengths. Analysis of the type of aberrations observed in various time intervals after sonication indicated the simultaneous formation of chromosome and chromatide abnormalities.     

GST-His purification: A Two-step Affinity Purification Protocol Yielding Full-length Purified Proteins

Key assays in enzymology for the biochemical characterization of proteins in vitro necessitate high concentrations of the purified protein of interest. Protein purification protocols should combine efficiency, simplicity and cost effectiveness¹. Here, we describe the GST-His method as a new small-scale affinity purification system for recombinant proteins, based on a N-terminal Glutathione Sepharose Tag (GST)^2,3 and a C-terminal 10xHis tag⁴, which are both fused to the protein of interest. The latter construct is used to generate baculoviruses, for infection of Sf9 infected cells for protein expression⁵. GST is a rather long tag (29 kDa) which serves to ensure purification efficiency. However, it might influence physiological properties of the protein. Hence, it is subsequently cleaved off the protein using the PreScission enzyme⁶. In order to ensure maximum purity and to remove the cleaved GST, we added a second affinity purification step based on the comparatively small His-Tag. Importantly, our technique is based on two different tags flanking the two ends of the protein, which is an efficient tool to remove degraded proteins and, therefore, enriches full-length proteins. The method presented here does not require an expensive instrumental setup, such as FPLC. Additionally, we incorporated MgCl₂ and ATP washes to remove heat shock protein impurities and nuclease treatment to abolish contaminating nucleic acids. In summary, the combination of two different tags flanking the N- and the C-terminal and the capability to cleave off one of the tags, guaranties the recovery of a highly purified and full-length protein of interest.     

Identification of novel benzimidazole derivatives as inhibitors of leukotriene biosynthesis by virtual screening targeting 5-lipoxygenase-activating protein (FLAP)

Pharmacological suppression of leukotriene biosynthesis by 5-lipoxygenase (5-LO)-activating protein (FLAP) inhibitors is a promising strategy to intervene with inflammatory, allergic and cardiovascular diseases. Virtual screening targeting FLAP based on a combined ligand- and structure-based pharmacophore model led to the identification of 1-(2-chlorobenzyl)-2-(1-(4-isobutylphenyl)ethyl)-1H-benzimidazole (7) as developable candidate. Compound 7 potently suppressed leukotriene formation in intact neutrophils (IC(50)=0.31 μM) but essentially failed to directly inhibit 5-LO suggesting that interaction with FLAP causes inhibition of leukotriene synthesis. For structural optimization, a series of 46 benzimidazole-based derivatives of 7 were synthesized leading to more potent analogues (70-72, 82) with IC(50)=0.12-0.19 μM in intact neutrophils. Together, our results disclose the benzimidazole scaffold bearing an ibuprofen fingerprint as a new chemotype for further development of anti-leukotriene agents.     

Methods to account for spatial autocorrelation in the analysis of species distributional data: a review

Species distributional or trait data based on range map (extent‐of‐occurrence) or atlas survey data often display spatial autocorrelation, i.e. locations close to each other exhibit more similar values than those further apart. If this pattern remains present in the residuals of a statistical model based on such data, one of the key assumptions of standard statistical analyses, that residuals are independent and identically distributed (i.i.d), is violated. The violation of the assumption of i.i.d. residuals may bias parameter estimates and can increase type I error rates (falsely rejecting the null hypothesis of no effect). While this is increasingly recognised by researchers analysing species distribution data, there is, to our knowledge, no comprehensive overview of the many available spatial statistical methods to take spatial autocorrelation into account in tests of statistical significance. Here, we describe six different statistical approaches to infer correlates of species’ distributions, for both presence/absence (binary response) and species abundance data (poisson or normally distributed response), while accounting for spatial autocorrelation in model residuals: autocovariate regression; spatial eigenvector mapping; generalised least squares; (conditional and simultaneous) autoregressive models and generalised estimating equations. A comprehensive comparison of the relative merits of these methods is beyond the scope of this paper. To demonstrate each method's implementation, however, we undertook preliminary tests based on simulated data. These preliminary tests verified that most of the spatial modeling techniques we examined showed good type I error control and precise parameter estimates, at least when confronted with simplistic simulated data containing spatial autocorrelation in the errors. However, we found that for presence/absence data the results and conclusions were very variable between the different methods. This is likely due to the low information content of binary maps. Also, in contrast with previous studies, we found that autocovariate methods consistently underestimated the effects of environmental controls of species distributions. Given their widespread use, in particular for the modelling of species presence/absence data (e.g. climate envelope models), we argue that this warrants further study and caution in their use. To aid other ecologists in making use of the methods described, code to implement them in freely available software is provided in an electronic appendix.     

Striatal pre- and postsynaptic profile of adenosine A(2A) receptor antagonists

Striatal adenosine A(2A) receptors (A(2A)Rs) are highly expressed in medium spiny neurons (MSNs) of the indirect efferent pathway, where they heteromerize with dopamine D(2) receptors (D(2)Rs). A(2A)Rs are also localized presynaptically in cortico-striatal glutamatergic terminals contacting MSNs of the direct efferent pathway, where they heteromerize with adenosine A(1) receptors (A(1)Rs). It has been hypothesized that postsynaptic A(2A)R antagonists should be useful in Parkinson's disease, while presynaptic A(2A)R antagonists could be beneficial in dyskinetic disorders, such as Huntington's disease, obsessive-compulsive disorders and drug addiction. The aim or this work was to determine whether selective A(2A)R antagonists may be subdivided according to a preferential pre- versus postsynaptic mechanism of action. The potency at blocking the motor output and striatal glutamate release induced by cortical electrical stimulation and the potency at inducing locomotor activation were used as in vivo measures of pre- and postsynaptic activities, respectively. SCH-442416 and KW-6002 showed a significant preferential pre- and postsynaptic profile, respectively, while the other tested compounds (MSX-2, SCH-420814, ZM-241385 and SCH-58261) showed no clear preference. Radioligand-binding experiments were performed in cells expressing A(2A)R-D(2)R and A(1)R-A(2A)R heteromers to determine possible differences in the affinity of these compounds for different A(2A)R heteromers. Heteromerization played a key role in the presynaptic profile of SCH-442416, since it bound with much less affinity to A(2A)R when co-expressed with D(2)R than with A(1)R. KW-6002 showed the best relative affinity for A(2A)R co-expressed with D(2)R than co-expressed with A(1)R, which can at least partially explain the postsynaptic profile of this compound. Also, the in vitro pharmacological profile of MSX-2, SCH-420814, ZM-241385 and SCH-58261 was is in accordance with their mixed pre- and postsynaptic profile. On the basis of their preferential pre- versus postsynaptic actions, SCH-442416 and KW-6002 may be used as lead compounds to obtain more effective antidyskinetic and antiparkinsonian compounds, respectively.     

Fungal antagonists of the plant pathogen Rhizoctonia solani: selection, control efficacy and influence on the indigenous microbial community

A broad spectrum of fungal antagonists was evaluated as potential biocontrol agents (BCAs) against the soil-borne pathogen Rhizoctonia solani using a new combination of in vitro and in vivo assays. The in vitro characterisation of diverse parameters including the ability to parasitise mycelium and to inhibit the germination of Rhizoctonia sclerotia at different temperatures resulted in the selection of six potential fungal antagonists. These were genotypically characterised by their BOX-PCR fingerprints, and identified as Trichoderma reesei and T. viride by partial 18S rDNA sequencing. When potato sprouts were treated with Trichoderma, all isolates significantly reduced the incidence of Rhizoctonia symptoms. Evaluated under growth chamber conditions, the selected Trichoderma isolates either partly or completely controlled the dry mass loss of lettuce caused by R. solani. Furthermore, the antagonistic Trichoderma strains were active under field conditions. To analyse the effect of Trichoderma treatment on indigenous root-associated microbial communities, we performed a DNA-dependent SSCP (Single-Strand Conformation Polymorphism) analysis of 16S rDNA/ITS sequences. In this first assessment study for Trichoderma it was shown that the pathogen and the vegetation time had much more influence on the composition of the microbiota than the BCA treatment. After evaluation of all results, three Trichoderma strains originally isolated from Rhizoctonia sclerotia were selected as promising BCAs.     

Decimal Place Slope,A Fast and Precise Method for Quantifying 13C Incorporation Levels for Detecting the Metabolic Activity of Microbial Species

The metabolic incorporation of stable isotopes such as ¹³C or ¹⁵N into proteins has become a powerful tool for qualitative and quantitative proteome studies. We recently introduced a method that monitors heavy isotope incorporation into proteins and presented data revealing the metabolic activity of various species in a microbial consortium using this technique. To further develop our method using an liquid chromatography (LC)-mass spectrometry (MS)-based approach, we present here a novel approach for calculating the incorporation level of ¹³C into peptides by using the information given in the decimal places of peptide masses obtained by modern high-resolution MS. In the present study, the applicability of this approach is demonstrated using Pseudomonas putida ML2 proteins uniformly labeled via the consumption of [¹³C₆]benzene present in the medium at concentrations of 0, 10, 25, 50, and 100 atom %. The incorporation of ¹³C was calculated on the basis of several labeled peptides derived from one band on an SDS-PAGE gel. The accuracy of the calculated incorporation level depended upon the number of peptide masses included in the analysis, and it was observed that at least 100 peptide masses were required to reduce the deviation below 4 atom %. This accuracy was comparable with calculations of incorporation based on the isotope envelope. Furthermore, this method can be extended to the calculation of the labeling efficiency for a wide range of biomolecules, including RNA and DNA. The technique will therefore allow a highly accurate determination of the carbon flux in microbial consortia with a direct approach based solely on LC-MS.The metabolic incorporation of stable isotopes such as ¹³C or ¹⁵N into proteins has become a powerful component of qualitative and quantitative proteome studies (1). Incorporation of heavy isotopes can be used to analyze microbial processes such as turnover rates and also to help to establish structure-function relationships within microbial communities. Stable isotope probing (SIP¹) techniques based on DNA-SIP (2) and RNA-SIP (3) have been used for this purpose previously. With the introduction of protein-SIP (4), the need for an accurate alternative method for calculating label incorporation into biomolecules arose. Protein-SIP has several advantages compared with DNA/RNA-SIP, the most important being its capacity to detect dynamic levels of incorporation, whereas only labeled or unlabeled states can be categorized by means of DNA/RNA-SIP because of the need to separate ¹³C-DNA/RNA by density gradient centrifugation. Quantitative analysis of ¹³C incorporation levels is of the utmost importance, especially when unraveling carbon fluxes through either microbial communities or food webs with different trophic levels.In contrast to the incorporation of isotopically labeled amino acids, which is often used in quantitative proteomics (5), metabolic labeling by growth substrates and nutrients (e.g. salts) is often imperfect and makes the processing of mass spectrometry (MS) data difficult. For example, when the incorporation of ¹³C exceeds ∼2 atom %, common database search algorithms fail to identify peptides and proteins. The problem can only be managed successfully if a stable, known degree of ¹³C incorporation can be achieved during the experiment (6). Using a low labeling efficiency of roughly 5 atom %, Huttlin et al. (6) chose the altered envelope chain for calculating the incorporation and simultaneously used the signal intensity for a quantitative comparison with the sample that had a natural abundance of ¹³C. Database approaches for peptide identification can cope only with the natural abundance of carbon isotopes; they fail if the incorporation of ¹³C significantly exceeds the natural isotope abundance or if incorporation patterns occur in unpredictable ways (7).The simplest method for determining the incorporation level is to compare the unlabeled average mass of the monoisotopic peptide with the mass of the labeled protein, as estimated by matrix-assisted laser desorption/ionization or electrospray ionization MS (8, 9). A more advanced approach for determining the isotopic mass distribution of peptides is based on the isotopic distribution of the peaks of a peptide envelope (10, 11). Here, for a given isotopomer, the incorporation efficiency is defined as the percentage of incorporated ¹³C atoms with relation to the total number of carbon atoms with the natural isotope abundance (approximately 1.01 atom % ¹³C). As a reference, the theoretical isotopic distribution of a peptide is calculated based upon an algorithm described elsewhere (12). The isotope distribution of both unlabeled and labeled peptides can subsequently be used to calculate the incorporation level. For this method, an Excel spreadsheet (ProSIPQuant.xls) was developed (4). A similar approach, also based on the calculation of isotopic distributions, has been used in other studies (7). In these studies, however, the identification of the peptides is limited to those that have unlabeled counterparts; in addition, an exact calculation can be hampered by overlapping signals coming from additional peaks with similar masses.In the present study, we describe a new way of determining the isotope incorporation level. Our method makes use of characteristic patterns in the digits after the decimal point of the peptide masses generated by high-accuracy instruments such as the linear ion trap LTQ-Orbitrap (Thermo Fisher Scientific, Bremen, Germany). For tryptic peptides, typical regularities in the decimal places of the monoisotopic masses have been observed (13, 14). These observations have been explored in detail for theoretical and experimental data of proteins originating from Helicobacter pylori (15). As a result, a rule called the “half decimal place rule” (HDPR) was defined; it states that the decimal place is nearly half of the first digit for tryptic peptides with masses in the range of 500–1,000 Da. In other words, the exact mass of a peptide is equal to its nominal mass times ∼1.005. Because the difference between ¹²C and ¹³C is slightly greater than 1 Da, exactly 1.0033548378, the decimal places of a tryptic peptide''s mass are shifted in a regular manner by the incorporation level and lead to a significantly increased slope for the digits in the third and fourth place after the decimal point. This shift can be used to estimate the incorporation level of heavy isotopes into the protein. Detecting such shifts requires the highly accurate measurement possible with modern mass spectrometers such as the LTQ-Orbitrap, the Fourier transform ion cyclotron resonance, or the quadrupole time of flight. In this communication, we demonstrate the applicability of this approach using Pseudomonas putida ML2 proteins labeled uniformly via the consumption of [¹³C₆]benzene with five different substrate concentrations (0, 10, 25, 50, and 100 atom % of ¹³C). The ¹³C incorporation was calculated based on several labeled peptides derived from different proteins in one SDS-PAGE band. By these means, we have established a method that allows the determination of ¹³C incorporation into proteins and can be used to assess the metabolic activity of a given species within a mixed community.     

Genome mining reveals the evolutionary origin and biosynthetic potential of basidiomycete polyketide synthases

Numerous polyketides are known from bacteria, plants, and fungi. However, only a few have been isolated from basidiomycetes. Large scale genome sequencing projects now help anticipate the capacity of basidiomycetes to synthesize polyketides. In this study, we identified and annotated 111 type I and three type III polyketide synthase (PKS) genes from 35 sequenced basidiomycete genomes. Phylogenetic analysis of PKS genes suggests that all main types of fungal iterative PKS had already evolved before the Ascomycota and Basidiomycota diverged. A comparison of genomic and metabolomic data shows that the number of polyketide genes exceeds the number of known polyketide structures by far. Exploiting these results to design degenerate PCR primers, we amplified and cloned the complete sequence of armB, a PKS gene from the melleolide producer Armillaria mellea. We expect this study will serve as a guide for future genomic mining projects to discover structurally diverse mushroom-derived polyketides.