Local nitric oxide levels reflect the degree of allergic airway inflammation after segmental allergen challenge in asthmatics.

Nitric oxide (NO) levels are increased in the exhaled air of asthmatics. As NO levels correlate with allergic airway inflammation, NO measurement has been suggested for disease monitoring. In patients with asthma, we previously demonstrated that intrabronchial treatment with a natural porcine surfactant enhanced airway inflammation after segmental allergen provocation. We studied whether local levels of NO reflect the degree of allergic airway inflammation following segmental allergen challenge with or without surfactant pretreatment. Segmental NO, as well as nitrite and nitrate in bronchoalveolar lavage (BAL) fluid, was measured before and after segmental challenge with either saline, saline plus allergen, or surfactant plus allergen in 16 patients with asthma and five healthy subjects. The data were compared with inflammatory BAL cells. Segmental NO levels were increased after instillation of saline (p < 0.05), or surfactant plus allergen in asthmatics (p < 0.05), and values were higher after surfactant plus allergen compared to saline challenge. Nitrate BAL levels were not altered after saline challenge but increased after allergen challenge (p < 0.05) and further raised by surfactant (p < 0.05), whereas nitrite levels were not altered by any treatment. Segmental NO and nitrate levels correlated with the degree of eosinophilic airway inflammation, and nitrate levels also correlated with neutrophil and lymphocyte numbers in BAL. In healthy subjects, NO, nitrite, and nitrate were unaffected. Thus, segmental NO and nitrate levels reflect the degree of allergic airway inflammation in patients with asthma. Measurement of both markers can be useful in studies using segmental allergen provocation, to assess local effects of potential immunomodulators.     

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.     

Divergent genetic and epigenetic post-zygotic isolation mechanisms in Mus and Peromyscus

Interspecific hybridization in the rodent genera Peromyscus and Mus results in abnormal placentation. In the Peromyscus interspecies hybrids, abnormal allelic interaction between an X-linked locus and the imprinted paternally expressed Peg3 locus was shown to cause the placental defects. In addition, loss-of-imprinting (LOI) of Peg3 was positively correlated with increased placental size. As in extreme cases this placental dysplasia constitutes a post-zygotic barrier against interspecies hybridization, this finding was the first direct proof that imprinted genes may be important in speciation and thus in evolution. In the Mus interspecies hybrids, a strong role of an X-linked locus in placental dysplasia has also been detected. However, here we show by backcross and allele specific expression analyses that neither LOI of Peg3 nor abnormal interactions between Peg3 and an X-linked locus are involved in generating placental dysplasia in Mus hybrids, although the placental phenotypes observed in the two genera seem to be identical. In contrast to this, another dysgenesis effect common to Peromyscus and Mus hybrids, altered foetal growth, is caused at least in part by the same X-chromosomal regions in both genera. These findings first underline the strong involvement of the X-chromosome in the genetics of speciation. Secondly, they indicate that disruption of epigenetic states, such as LOI, at specific loci may be involved in hybrid dysgenesis effects in one group, but not in another. Thus, we conclude that even in closely related groups divergent molecular mechanisms may be involved in the production of phenotypically similar post-zygotic barriers against hybridization.     

German network on life cycle inventory data

Reliability of Life Cycle Assessment (LCA) results depends on the availability and quality of Life Cycle Inventory (LCI) data. In order to provide high-quality LCI data for background systems in LCA and to make it applicable to a wider range of fields, harmonization strategies for already existing datasets and databases are required. In view of the high significance of LCI data as a basis of major fields of action within a sustainability strategy, the German Helmholtz Association (HGF), under the leadership of the Forschungszentrum Karlsruhe (FZK) has taken up this issue in its research programme. In 2002, the FZK conducted a preliminary study on ‘Quality Assurance and User-oriented Supply of a Life Cycle Inventory Data’ funded by the Federal Ministry of Education and Research (BMBF). Within the framework of this study, a long-term concept for improving the scientific fundamentals and practical use of LCI data was developed in association with external experts. The focus is on establishing a permanent German ‘Network on Life Cycle Inventory Data’ which will serve as the German information and cooperation platform for all scientific and non-scientific actors in the field of life cycle analysis. This network will integrate expertise on LCA in Germany, harmonise methodology and data, and use the comprehensive expert panel as an efficient basis for further scientific development and practical use of LCA. At the same time, this network will serve as a platform for cooperation on an international level. Current developments address methodological definitions for the initial information infrastructure. As a novel element, user needs are differentiated in parallel according to the broad application fields of LCI-data from product declaration to process design. Case studies will be used to define tailored interfaces for the database, since different data quality levels will be encountered.     

Evaluation of CuO oxidation parameters for determining the source and stage of lignin degradation in soil

The composition of phenols and other aromatic compounds in organic and mineral soil horizons and their respective source vegetation from different climatic zones of the Canadian Prairies were analyzed using CuO oxidation and gas chromatography-mass spectrometry (GC-MS) to investigate the stage of lignin degradation. Parameters based on the CuO oxidation products were calculated for the soils and corresponding vegetation to determine the lignin sources and to monitor the lignin degradation. In addition to the widely used lignin monomer parameters, parameters resulting from lignin-derived phenolic dimers are used for the first time to assess lignin degradation in soils. The composition of lignin-derived phenols (S/V, C/V) in soil closely matches the composition observed in their respective source plants (grass, Aspen, Pine) reflecting the preservation of characteristic lignin patterns in soils. Degradation parameters based on lignin phenols and benzenes derived from tannins or other phenolic biomolecules indicate a progressive degradation from the vegetation to the soil horizons. In addition to commonly used lignin monomer indicators, parameters based on the lignin dimers are applied. Lignin degradation is found to be lowest in the Pine forest, intermediate in the grassland soils and highest in the Aspen-grassland transition soil. Degradation parameters based on non-lignin aromatic derivatives (3,5-dihydroxybenzoic acid, benzenepolycarboxylic acids) demonstrate a similar trend. The lignin from samples in the cooler climate (Black Chernozems) is observed to be more oxidized than in the soils from the warmer climate (Brown Chernozems) suggesting that abiotic processes may be in involved in the alteration of lignin and other phenolic biomolecules in soils. The results indicate that the comparative analysis of CuO oxidation products of soils and source vegetation is a valuable tool to assess the sources and degradation of lignin in soils.     

Recent approaches to probe functional groups in ribonuclease P RNA by modification interference

Modification interference is a powerful method to identify important functional groups in RNA molecules. We review here recent developments of techniques to screen for chemical modifications that interfere with (i) binding of(pre-)tRNA to bacterial RNase P RNA or (ii) pre-tRNA cleavage by this ribozyme. For example, two studies have analyzed positions at which a substitution of sulfur for thepro-Rp oxygen affects tRNA binding [1] or catalysis [2]. The results emphasize the functional key role of a central core element present in all known RNase P RNA subunits. The four sulfur substitutions identified in one study [2] to inhibit the catalytic step also interfered with binding of tRNA toE. coli RNase P RNA [1]. This suggests that losses in binding energy due to the modification at these positions affect the enzyme-substrate and the enzyme-transition state complex. In addition, the two studies have revealed, for the first time, sites of direct metal ion coordination in RNase P RNA. The potentials, limitations and interpretational ambiguities of modification interference experiments as well as factors influencing their outcome are discussed.Abbreviations nt nucleotide(s) - PAGE polyacrylamide gel electrophoresis     

Primary metabolism in the new human cell line AGE1.HN at various substrate levels: increased metabolic efficiency and α1-antitrypsin production at reduced pyruvate load

Metabolic responses of the new neuronal human cell line AGE1.HN to various substrate levels were analyzed in this study showing that reduced substrate and especially pyruvate load improves metabolic efficiency, leading to improved growth and α₁-antitrypsin (A1AT) production. The adaptation of the metabolism to different pyruvate and glutamine concentrations was analyzed in detail using a full factorial design. The most important finding was an increasingly inefficient use of substrates as well as the reduction of cell proliferation with increasing pyruvate concentrations in the medium. Cultivations with different feeding profiles showed that the highest viable cell density and A1AT concentration (167% of batch) was reached in the culture with the lowest glucose level and without pyruvate feeding. Analysis of metabolic fluxes in the differently fed cultures revealed a more efficient metabolic phenotype in the cultures without pyruvate feeding. The measured in vitro enzyme activities of the selected enzymes involved in pyruvate metabolism were lower in AGE1.HN compared with CHO cells, which might explain the higher sensitivity and different adaptation of AGE1.HN to increased pyruvate concentrations. The results indicate on the one hand that increasing the connectivity between glycolysis and the TCA cycle might improve substrate use and, finally, the production of A1AT. On the other hand, a better balanced substrate uptake promises a reduction of energy spilling which is increased with increasing substrate levels in this cell line. Overall, the results of this study provide important insights into the regulation of primary metabolism and into the adaptation of AGE1.HN to different substrate levels, providing guidance for further optimization of production cell lines and applied process conditions.     

A systems-level approach for metabolic engineering of yeast cell factories

The generation of novel yeast cell factories for production of high-value industrial biotechnological products relies on three metabolic engineering principles: design, construction, and analysis. In the last two decades, strong efforts have been put on developing faster and more efficient strategies and/or technologies for each one of these principles. For design and construction, three major strategies are described in this review: (1) rational metabolic engineering; (2) inverse metabolic engineering; and (3) evolutionary strategies. Independent of the selected strategy, the process of designing yeast strains involves five decision points: (1) choice of product, (2) choice of chassis, (3) identification of target genes, (4) regulating the expression level of target genes, and (5) network balancing of the target genes. At the construction level, several molecular biology tools have been developed through the concept of synthetic biology and applied for the generation of novel, engineered yeast strains. For comprehensive and quantitative analysis of constructed strains, systems biology tools are commonly used and using a multi-omics approach. Key information about the biological system can be revealed, for example, identification of genetic regulatory mechanisms and competitive pathways, thereby assisting the in silico design of metabolic engineering strategies for improving strain performance. Examples on how systems and synthetic biology brought yeast metabolic engineering closer to industrial biotechnology are described in this review, and these examples should demonstrate the potential of a systems-level approach for fast and efficient generation of yeast cell factories.