Determination of cell mass and polymyxin using multi-wavelength fluorescence

Multi-wavelength fluorescence was applied for on-line monitoring of cell mass and the antibiotic polymyxin B in Bacillus polymyxa cultivations. By varying the phosphate and nitrogen content of the medium different polymyxin-cell mass ratios could be obtained. Using this strategy, it was possible to investigate if multi-wavelength fluorescence is able to give independent prediction of the two parameters. Partial least square (PLS) regression was applied to establish mathematical relationships between off-line determined cell mass and polymyxin concentrations and on-line collected fluorescence data. For polymyxin one universal PLS model, with a correlation of 0.95 and a root mean square error of cross validation (RMSECV) of 35 mgl(-1), could be constructed. However, correlation between fluorescence and cell mass dry weight could not be established including data from all three types of cultivations. For data from each type of cultivation, separate models with high correlation and low RMSECV values were built. A large variation in cellular composition as a result of the different levels of nitrogen and phosphorus in the cultivations was the probable reason to the necessity of building three models. The results of the present investigation indicate that production of polymyxin is concomitantly regulated by phosphate and nitrogen as the highest polymyxin yield on cell mass, 0.17+/-0.01 gg(-1), was reached in the cultivations where both nitrogen and phosphate concentrations were kept low.     

The expanded octarepeat domain selectively binds prions and disrupts homomeric prion protein interactions

Insertion of additional octarepeats into the prion protein gene has been genetically linked to familial Creutzfeldt Jakob disease and hence to de novo generation of infectious prions. The pivotal event during prion formation is the conversion of the normal prion protein (PrPC) into the pathogenic conformer PrPSc, which subsequently induces further conversion in an autocatalytic manner. Apparently, an expanded octarepeat domain directs folding of PrP toward the PrPSc conformation and initiates a self-replicating conversion process. Here, based on three main observations, we have provided a model on how altered molecular interactions between wild-type and mutant PrP set the stage for familial Creutzfeldt Jakob disease with octarepeat insertions. First, we showed that wild-type octarepeat domains interact in a copper-dependent and reversible manner, a "copper switch." This interaction becomes irreversible upon domain expansion, possibly reflecting a loss of function. Second, expanded octarepeat domains of increasing length gradually form homogenous globular multimers of 11-21 nm in the absence of copper ions when expressed as soluble glutathione S-transferase fusion proteins. Third, octarepeat domain expansion causes a gain of function with at least 10 repeats selectively binding PrPSc in a denaturant-resistant complex in the absence of copper ions. Thus, the combination of both a loss and gain of function profoundly influences homomeric interaction behavior of PrP with an expanded octarepeat domain. A multimeric cluster of prion proteins carrying expanded octarepeat domains may therefore capture and incorporate spontaneously arising short-lived PrPSc-like conformers, thereby providing a matrix for their conversion.     

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.     

Local diversity of arable weeds increases with landscape complexity

Patterns of plant diversity are often related to local site conditions and to competitive interactions, but landscape context may also be important for local plant species richness. This is shown here by analysing the relationship between landscape complexity and local species richness of arable weeds in wheat fields. The fields were located in 18 landscapes characterised by a gradient in landscape complexity from structurally complex to structurally simple (39–94% arable land). We quantified local site conditions, field management intensity and landscape characteristics, and used principle component analyses to ordinate the environmental variables. The percentage of arable land was negatively correlated with perimeter–area ratio, habitat-type diversity and topographical heterogeneity, but landscape characteristics did not correlate with local site conditions and field management intensity. The number of plant species was mainly related to landscape characteristics and to a lesser extent to field management intensity (nitrogen fertilisation), whereas local soil characteristics did not contribute to the explanation of arable weed richness. In a geographic scale analysis using circular landscape sectors ranging from 1 km up to 5 km diameter, the predictive power of landscape complexity for local plant species richness was strongest at 2 km indicating a scale-dependent relationship between landscape context and plant species richness. Our results support the hypothesis that local plant species richness in arable fields is greatly influenced by processes operating at the landscape scale. Seed rain from ruderal source habitats and disturbed edges may be the most important underlying process.     

Characterisation of the Nucleotide Exchange Factor ITSN1L: Evidence for a Kinetic Discrimination of GEF-Stimulated Nucleotide Release from Cdc42

Cdc42, a member of the Ras superfamily of small guanine nucleotide binding proteins, plays an important role in regulating the actin cytoskeleton, intracellular trafficking, and cell polarity. Its activation is controlled by guanine nucleotide exchange factors (GEFs), which stimulate the dissociation of bound guanosine-5′-diphosphate (GDP) to allow guanosine-5′-triphosphate (GTP) binding. Here, we investigate the exchange factor activity of the Dbl-homology domain containing constructs of the adaptor protein Intersectin1L (ITSN1L), which is a specific GEF for Cdc42. A detailed kinetic characterisation comparing ITSN1L-mediated nucleotide exchange on Cdc42 in its GTP- versus GDP-bound state reveals a kinetic discrimination for GEF-stimulated dissociation of GTP: The maximum acceleration of the intrinsic mGDP [2′/3′-O-(N-methyl-anthraniloyl)-GDP] release from Cdc42 by ITSN1L is accelerated at least 68,000-fold, whereas the exchange of mGTP [2′/3′-O-(N-methyl-anthraniloyl)-GTP] is stimulated only up to 6000-fold at the same GEF concentration. The selectivity in nucleotide exchange kinetics for GDP over GTP is even more pronounced when a Cdc42 mutant, F28L, is used, which is characterised by fast intrinsic dissociation of nucleotides. We furthermore show that both GTP and Mg²⁺ ions are required for the interaction with effectors. We suggest a novel model for selective nucleotide exchange residing on a conformational change of Cdc42 upon binding of GTP, which enables effector binding to the Cdc42 · GTP complex but, at the same time, excludes efficient modulation by the GEF. The higher exchange activity of ITSN1L towards the GDP-bound conformation of Cdc42 could represent an evolutionary adaptation of this GEF that ensures nucleotide exchange towards the formation of the signalling-active GTP-bound form of Cdc42 and avoids dissociation of the active complex.     

Deep Proteomic Evaluation of Primary and Cell Line Motoneuron Disease Models Delineates Major Differences in Neuronal Characteristics

The fatal neurodegenerative disorders amyotrophic lateral sclerosis and spinal muscular atrophy are, respectively, the most common motoneuron disease and genetic cause of infant death. Various in vitro model systems have been established to investigate motoneuron disease mechanisms, in particular immortalized cell lines and primary neurons. Using quantitative mass-spectrometry-based proteomics, we compared the proteomes of primary motoneurons to motoneuron-like cell lines NSC-34 and N2a, as well as to non-neuronal control cells, at a depth of 10,000 proteins. We used this resource to evaluate the suitability of murine in vitro model systems for cell biological and biochemical analysis of motoneuron disease mechanisms. Individual protein and pathway analysis indicated substantial differences between motoneuron-like cell lines and primary motoneurons, especially for proteins involved in differentiation, cytoskeleton, and receptor signaling, whereas common metabolic pathways were more similar. The proteins associated with amyotrophic lateral sclerosis also showed distinct differences between cell lines and primary motoneurons, providing a molecular basis for understanding fundamental alterations between cell lines and neurons with respect to neuronal pathways with relevance for disease mechanisms. Our study provides a proteomics resource for motoneuron research and presents a paradigm of how mass-spectrometry-based proteomics can be used to evaluate disease model systems.Motoneurons are extremely extended neurons that mediate the control of all muscle types by the central nervous system. Therefore, diseases involving progressive motoneuron degeneration such as amyotrophic lateral sclerosis (ALS)¹ (OMIM: 105400) or spinal muscle atrophy (OMIM: 253300) are particularly devastating and generally fatal disorders. Today, ALS is believed to form a phenotypic continuum with the disease entity frontotemporal lobe degeneration (OMIM: 600274) (1, 2). About 10% of ALS cases are known to be inherited, but the vast majority are considered sporadic. The number of inherited cases might be underestimated because of incomplete family histories, non-paternity, early death of family members, or incomplete penetrance (3).Mutations in several genes have been reported for the familial form, including in Sod1 (4), Als2 (5), Setx (6), Vapb (7), Tardbp (8, 9), Fus/Tls (10, 11), Vcp (12), Pfn1 (13), and several others (reviewed in Ref. 14). The most frequent genetic cause of inherited ALS was recently shown to be a hexanucleotide repeat expansion in an intron of a gene of unknown function called C9orf72 (15–17). Based on the spectrum of known mutations, several disease mechanisms for ALS have been proposed, including dysfunction of protein folding, axonal transport, RNA splicing, and metabolism (reviewed in Refs. 14, 18, and 19). Despite intensive research, it is still unclear whether a main common molecular pathway or mechanism underlies motoneuron degeneration in ALS and frontotemporal lobe degeneration. Spinal muscle atrophy is caused by homozygous mutations or deletions in the survival of motor neuron gene (Smn1) that presumably impair the RNA metabolism through diminished functionality of the Smn1 gene product (20). Over recent decades several model systems have been established to investigate ALS (21). These include transgenic animal models such as mouse (22), drosophila (23), and zebrafish (24). In cell-based studies, primary motoneurons cultured from rodent embryos (25) or motoneuron-like cell lines are employed. Primary cells are considered to more closely mimic the in vivo situation, but they are more challenging to establish and maintain. In contrast, the degree of functional relevance of cell lines can be difficult to establish, but they can be propagated without limitation and are well suited for high-throughput analysis. In particular, the spinal cord neuron–neuroblastoma hybrid cell line NSC-34 (26) and the mouse neuroblastoma cell line N2a (27) are widely used not only to assess motoneuron function, but also to study disease mechanisms in motoneurons (28, 29).As proteins are the functional actors in cells, proteomics should be able to make important contributions to the characterization and evaluation of cellular models. In particular, by identifying and quantifying the expressed proteins and bioinformatically interpreting the results, one can obtain enough information to infer functional differences. Our laboratory has previously shown proof of concept of such an approach by comparing the expression levels of about 4,000 proteins between primary hepatocytes and a hepatoma cell line (30). Very recently, mass-spectrometry-based proteomics has achieved sufficient depth and accuracy to quantify almost the entire proteome of mammalian cell lines (31–33). Furthermore, new instrumentation and algorithms now make it possible to perform label-free quantification between multiple cellular systems and with an accuracy previously associated only with stable isotope labeling techniques (34, 35).To evaluate the suitability of motoneuron-like cell lines as cellular model systems for research on ALS and related disorders, we characterized the proteomes of two widely used cell lines, NSC-34 and N2a, and compared them with the proteomes of mouse primary motoneurons and non-neuronal control cell lines. To generate primary motoneurons, we employed a recently described culturing system that makes it possible to isolate highly enriched motoneuron populations in less than 8 h (25). We identified more than 10,000 proteins and investigated differences in quantitative levels of individual neuron-associated proteins and pathways related to motoneuron function and disease mechanisms.     

Polyglutamylation: a fine‐regulator of protein function?

Polyglutamylation is a post-translational modification in which glutamate side chains of variable lengths are formed on the modified protein. It is evolutionarily conserved from protists to mammals and its most prominent substrate is tubulin, the microtubule (MT) building block. Various polyglutamylation states of MTs can be distinguished within a single cell and they are also characteristic of specific cell types or organelles. Polyglutamylation has been proposed to be involved in the functional adaptation of MTs, as it occurs within the carboxy-terminal tubulin tails that participate directly in the binding of many structural and motor MT-associated proteins. The discovery of a new family of enzymes that catalyse this modification has brought new insight into the mechanism of polyglutamylation and now allows for direct functional studies of the role of tubulin polyglutamylation. Moreover, the recent identification of new substrates of polyglutamylation indicates that this post-translational modification could be a potential regulator of diverse cellular processes.