Expression of enzymatically inactive wasp venom phospholipase A1 in Pichia pastoris.

Wasp venom allergy is the most common insect venom allergy in Europe. It is manifested by large local reaction or anaphylactic shock occurring after a wasp sting. The allergy can be treated by specific immunotherapy with whole venom extracts. Wasp venom is difficult and costly to obtain and is a subject to composition variation, therefore it can be advantageous to substitute it with a cocktail of recombinant allergens. One of the major venom allergens is phospholipase A1, which so far has been expressed in Escherichia coli and in insect cells. Our aim was to produce the protein in secreted form in yeast Pichia pastoris, which can give high yields of correctly folded protein on defined minimal medium and secretes relatively few native proteins simplifying purification.Residual amounts of enzymatically active phospholipase A1 could be expressed, but the venom protein had a deleterious effect on growth of the yeast cells. To overcome the problem we introduced three different point mutations at the critical points of the active site, where serine137, aspartate165 or histidine229 were replaced by alanine (S137A, D165A and H229A). All the three mutated forms could be expressed in P. pastoris. The H229A mutant did not have any detectable phospholipase A1 activity and was secreted at the level of several mg/L in shake flask culture. The protein was purified by nickel-affinity chromatography and its identity was confirmed by MALDI-TOF mass spectrometry. The protein could bind IgE antibodies from wasp venom allergic patients and could inhibit the binding of wasp venom to IgE antibodies specific for phospholipase A1 as shown by Enzyme Allergo-Sorbent Test (EAST). Moreover, the recombinant protein was allergenic in a biological assay as demonstrated by its capability to induce histamine release of wasp venom-sensitive basophils.The recombinant phospholipase A1 presents a good candidate for wasp venom immunotherapy.

Associations between fungal species and water-damaged building materials.

Fungal growth in damp or water-damaged buildings worldwide is an increasing problem, which has adverse effects on both the occupants and the buildings. Air sampling alone in moldy buildings does not reveal the full diversity of fungal species growing on building materials. One aim of this study was to estimate the qualitative and quantitative diversity of fungi growing on damp or water-damaged building materials. Another was to determine if associations exist between the most commonly found fungal species and different types of materials. More than 5,300 surface samples were taken by means of V8 contact plates from materials with visible fungal growth. Fungal identifications and information on building material components were analyzed using multivariate statistic methods to determine associations between fungi and material components. The results confirmed that Penicillium chrysogenum and Aspergillus versicolor are the most common fungal species in water-damaged buildings. The results also showed Chaetomium spp., Acremonium spp., and Ulocladium spp. to be very common on damp building materials. Analyses show that associated mycobiotas exist on different building materials. Associations were found between (i) Acremonium spp., Penicillium chrysogenum, Stachybotrys spp., Ulocladium spp., and gypsum and wallpaper, (ii) Arthrinium phaeospermum, Aureobasidium pullulans, Cladosporium herbarum, Trichoderma spp., yeasts, and different types of wood and plywood, and (iii) Aspergillus fumigatus, Aspergillus melleus, Aspergillus niger, Aspergillus ochraceus, Chaetomium spp., Mucor racemosus, Mucor spinosus, and concrete and other floor-related materials. These results can be used to develop new and resistant building materials and relevant allergen extracts and to help focus research on relevant mycotoxins, microbial volatile organic compounds (MVOCs), and microparticles released into the indoor environment.

High-yield production of hydrophobins RodA and RodB from Aspergillus fumigatus in Pichia pastoris.

Hydrophobins are small fungal proteins with amphipatic properties and the ability to self-assemble on a hydrophobic/hydrophilic interface; thus, many technical applications for hydrophobins have been suggested. The pathogenic fungus Aspergillus fumigatus expresses the hydrophobins RodA and RodB on the surface of its conidia. RodA is known to be of importance to the pathogenesis of the fungus, while the biological role of RodB is currently unknown. Here, we report the successful expression of both hydrophobins in Pichia pastoris and present fed-batch fermentation yields of 200-300 mg/l fermentation broth. Protein bands of expected sizes were detected by SDS-PAGE and western blotting, and the identity was further confirmed by tandem mass spectrometry. Both proteins were purified using his-affinity chromatography, and the high level of purity was verified by silver-stained SDS-PAGE. Recombinant RodA as well as rRodB were able to convert a glass surface from hydrophilic to hydrophobic similar to native RodA, but only rRodB was able to decrease the hydrophobicity of a Teflon-like surface to the same extent as native RodA, while rRodA showed this ability to a lesser extent. Recombinant RodA and native RodA showed a similar ability to emulsify air in water, while recombinant RodB could also emulsify oil in water better than the control protein bovine serum albumin (BSA). This is to our knowledge the first successful expression of hydrophobins from A. fumigatus in a eukaryote host, which makes it possible to further characterize both hydrophobins. Furthermore, the expression strategy and fed-batch production using P. pastoris may be transferred to hydrophobins from other species.

Implications of high-temperature events and water deficits on protein profiles in wheat (Triticum aestivum L. cv. Vinjett) grain.

Increased climatic variability is resulting in an increase of both the frequency and the magnitude of extreme climate events. Therefore, cereals may be exposed to more than one stress event in the growing season, which may ultimately affect crop yield and quality. Here, effects are reported of interaction of water deficits and/or a high-temperature event (32°C) during vegetative growth (terminal spikelet) with either of these stress events applied during generative growth (anthesis) in wheat. Influence of combinations of stress on protein fractions (albumins, globulins, gliadins and glutenins) in grains and stress-induced changes on the albumin and gliadin proteomes were investigated by 2-DE and MS. The synthesis of individual protein fractions was shown to be affected by both the type and time of the applied stresses. Identified drought or high-temperature-responsive proteins included proteins involved in primary metabolism, storage and stress response such as late embryogenesis abundant proteins, peroxiredoxins and α-amylase/trypsin inhibitors. Several proteins, e.g. heat shock protein and 14-3-3 protein changed in abundance only under multiple high temperatures.

Hydrophobins from Aspergillus species cannot be clearly divided into two classes.

BACKGROUND: Hydrophobins are a family of small secreted proteins with a characteristic pattern of eight cysteine residues found exclusively in filamentous fungi. They have originally been divided into two classes based on their physical properties and hydropathy patterns, and are involved in the attachment of hyphae to hydrophobic structures, the formation of aerial structures and appear to be involved in pathogenicity. FINDINGS: Analysis of nine genome sequences from seven Aspergilli revealed fifty hydrophobins, where each species displayed between two to eight hydrophobins. Twenty of the identified hydrophobins have not previously been described from these species. Apart from the cysteines, very little amino acid sequence homology was observed. Twenty-three of the identified hydrophobins could be classified as class I hydrophobins based on their conserved cysteine spacing pattern and hydropathy pattern. However twenty-six of the identified hydrophobins were intermediate forms. Notably, a single hydrophobin, ATEG_04730, from Aspergillus terreus displayed class II cysteine spacing and had a class II hydropathy pattern. CONCLUSION: Fifty hydrophobins were identified in Aspergillus, all containing the characteristic eight cysteine pattern. Aspergillus terreus exhibited both class I and class II hydrophobins. This is the first report of an Aspergillus species with the potential to express both class I and class II hydrophobins. Many of the identified hydrophobins could not directly be allocated to either class I or class II.

Display of wasp venom allergens on the cell surface of Saccharomyces cerevisiae.

BACKGROUND: Yeast surface display is a technique, where the proteins of interest are expressed as fusions with yeast surface proteins and thus remain attached to the yeast cell wall after expression. Our purpose was to study whether allergens expressed on the cell surface of baker's yeast Saccharomyces cerevisiae preserve their native allergenic properties and whether the yeast native surface glycoproteins interfere with IgE binding. We chose to use the major allergens from the common wasp Vespula vulgaris venom: phospholipase A1, hyaluronidase and antigen 5 as the model. RESULTS: The proteins were expressed on the surface as fusions with a-agglutinin complex protein AGA2. The expression was confirmed by fluorescent cytometry (FACS) after staining the cells with antibody against a C-tag attached to the C-terminal end of the allergens. Phospholipase A1 and hyaluronidase retained their enzymatic activities. Phospholipase A1 severely inhibited the growth of the yeast cells. Antigen 5 - expressing yeast cells bound IgE antibodies from wasp venom allergic patient sera but not from control sera as demonstrated by FACS. Moreover, antigen 5 - expressing yeast cells were capable of mediating allergen-specific histamine release from human basophils. CONCLUSIONS: All the three major wasp venom allergens were expressed on the yeast surface. A high-level expression, which was observed only for antigen 5, was needed for detection of IgE binding by FACS and for induction of histamine release. The non-modified S. cerevisiae cells did not cause any unspecific reaction in FACS or histamine release assay despite the expression of high-mannose oligosaccharides.In perspective the yeast surface display may be used for allergen discovery from cDNA libraries and possibly for sublingual immunotherapy as the cells can serve as good adjuvant and can be produced in large amounts at a low price.

Determination of adsorbed protein concentration in aluminum hydroxide suspensions by near-infrared transmittance spectroscopy.

Analysis of aluminum hydroxide based vaccines is difficult after antigen adsorption. Adsorbed protein is often assessed by measuring residual unadsorbed protein for quality control. A new method for the direct determination of adsorbed protein concentration in suspension using near-infrared (NIR) transmittance spectroscopy is proposed here. A simple adsorption system using albumin from bovine serum (BSA) and aluminum hydroxide as a model system is employed. The results show that the NIR absorbance at 700-1300 nm is correlated to the adsorbed BSA concentration, measured by the ultraviolet (UV) method, using the partial least square regression (PLSR) method to construct a calibration model. The linear concentration range of adsorbed BSA is from 0 to 1.75 mg/mL by using 10 mm path length cuvettes. The influence of the sedimentation in suspension, different buffers, and different aluminum hydroxide batches was investigated in this study. It shows that the batch variation is the main influence factor of this method, while the buffer variation has no influence. However, the pretreatment of spectral data by subtracting spectra of BSA blank control (aluminum hydroxide without BSA) can significantly reduce the batch influence, and the NIR predicted results show good agreement with the reference values. The NIR method might be the only direct method for the determination of adsorbed protein concentration in suspension so far. It is a nondestructive method, and it has great advantage for use in vaccine production as a method for quality control and quality assurance.

Combination of statistical approaches for analysis of 2-DE data gives complementary results.

Five methods for finding significant changes in proteome data have been used to analyze a two-dimensional gel electrophoresis data set. We used both univariate (ANOVA) and multivariate (Partial Least Squares with jackknife, Cross Model Validation, Power-PLS and CovProc) methods. The gels were taken from a time-series experiment exploring the changes in metabolic enzymes in bovine muscle at five time-points after slaughter. The data set consisted of 1377 protein spots, and for each analysis, the data set were preprocessed to fit the requirements of the chosen method. The generated results were one list from each analysis method of proteins found to be significantly changed according to the experimental design. Although the number of selected variables varied between the methods, we found that this was dependent on the specific aim of each method. CovProc and P-PLS focused more on getting the minimum necessary subset of proteins to explain properties of the samples. These methods ended up with less selected proteins. There was also a correlation between level of significance and frequency of selection for the selected proteins.

Determination of moisture content of lyophilized allergen vaccines by NIR spectroscopy.

Moisture content is an important parameter for lyophilized vaccines. Currently, Karl Fischer titration is widely used for moisture determination in routine analysis. However, this method is time-consuming, sample destructive and requires environment polluting reagents, as well as the results rely on the random samplings. In this study, near infrared spectroscopy was used as a fast, non-invasive and non-destructive method to determine the moisture content in lyophilized allergy vaccines. Five different vaccine products were investigated, which contained water in the range of 0.17-1.51% (w/w, KF). Different data pre-treatments, wavelength selection and partial least squares regression were applied to construct calibration models. Multi-products model and product-specific models were obtained, which show the possibility of NIR as a rapid method to discriminate whether moisture content fit into the specifications of a pharmaceutical company.

Particle size determination in aluminum hydroxide suspensions using near-infrared transmittance spectroscopy.

A new method for particle size determination in polystyrene and aluminum hydroxide suspensions using near-infrared transmittance spectroscopy is described. Mono-dispersed polystyrene particle size standards were used to establish the calibration model. The particle sizes used in the study are similar to the wavelength range of 700-1300 nm, where light scattering is wavelength dependent. The wavelength dependency of near-infrared (NIR) absorbance is found to be linear with the particle size when the analysis is based on the same spectrum starting point (the same absorbance at 700 nm). Partial least squares regression (PLSR) is applied to model this linear relationship. Compared to laser diffraction (LD) the NIR method has similar accuracy and precision in the measurement of particles with a uniform size. For a sample containing multiple sizes of particles, the mean size measured by the NIR method is shown to be weighted by the particle mass. The application of the model to aluminum hydroxide suspension shows that the NIR method is suitable for the detection of particle size changes during the production process and storage. The advantages of the NIR method are that no knowledge of the refractive index and the concentration of a sample are necessary and that the method is fast and easy to operate.

Determination of aluminium content in aluminium hydroxide formulation by FT-NIR transmittance spectroscopy.

A method for determining the aluminium content of an aluminium hydroxide suspension using near infrared (NIR) transmittance spectroscopy has been developed. Inductively coupled plasma-atomic emission spectroscopy (ICP-AES) was used as reference method. The factors influencing the NIR analysis, such as different sample containers (transmission cell and cuvette), sedimentation in the suspension, day-to-day variation and batch-to-batch variation have been studied before constructing a calibration model. Seven dilutions (0-4100 mg Al/L) of five batches of aluminium hydroxide suspension samples were measured by NIR transmission each on five different days, with total of 175 spectra used for the calibration set. The multivariate data analysis technique partial least square regression (PLSR) was applied to build the calibration model. Six batches of aluminium hydroxide samples were used for the test set. ICP-AES and NIR transmittance spectroscopy exhibit comparable precision and accuracy. The NIR method provides several advantages: no complicated sample preparation; easy to operate; fast and non-destructive. In conclusion, NIR transmittance spectroscopy can be an alternative analytical method for determining aluminium content in aluminium hydroxide suspension.

Analysis of protein structures and interactions in complex food by near-infrared spectroscopy. 1. Gluten powder.

The potential of near-infrared (NIR) spectroscopy in detailed food analysis was tested in a model system consisting of gluten powder treated with moisture and heat. Second-derivative transformation and extended multiplicative signal correction were applied for improving the band resolution and removing physical and quantitative spectral variations. Subsequent chemometric analyses gave loading spectra, which were interpreted as spectral effects of altered protein structures, induced by the treatments. Moistening of the gluten powder resulted in shifts and intensity changes in the protein bands, which could be explained by a combination of minor secondary structure changes, water binding, and changed microenvironments of the amino acid side chains. Heat denaturation induced increases at 2209 nm and decreases at 2167-2182 nm, indicating an alpha-helix to beta-sheet transformation, in agreement with the expectations.

Analysis of protein structures and interactions in complex food by near-infrared spectroscopy. 2. Hydrated gluten.

Hydrated gluten, treated with various salts, was analyzed by near-infrared (NIR) spectroscopy to assess the ability of this method to reveal protein structure and interaction changes in perturbed food systems. The spectra were pretreated with second-derivative transformation and extended multiplicative signal correction for improving the band resolution and removing physical and quantitative spectral variations. Principal component analysis of the preprocessed spectra showed spectral effects that depended on salt type and concentration. Although both gluten texture and the NIR spectra were little influenced by treatment with salt solutions of low concentrations (0.1-0.2 M), they were significantly and diversely affected by treatment with 1.0 M salt solutions. Compared to hydration in water, hydration in 1.0 M sulfate salts caused spectral effects similar to a drying-out effect, which could be explained by salting-out.

Multivariate analysis of 2-DE protein patterns--practical approaches.

Practical approaches to the use of multivariate data analysis of 2-DE protein patterns are demonstrated by three independent strategies for the image analysis and the multivariate analysis on the same set of 2-DE data. Four wheat varieties were selected on the basis of their baking quality. Two of the varieties were of strong baking quality and hard wheat kernel and two were of weak baking quality and soft kernel. Gliadins at different stages of grain development were analyzed by the application of multivariate data analysis on images of 2-DEs. Patterns related to the wheat varieties, harvest times and quality were detected on images of 2-DE protein patterns for all the three strategies. The use of the multivariate methods was evaluated in the alignment and matching procedures of 2-DE gels. All the three strategies were able to discriminate the samples according to quality, harvest time and variety, although different subsets of protein spots were selected. The explorative approach of using multivariate data analysis and variable selection in the analyses of 2-DEs seems to be promising as a fast, reliable and convenient way of screening and transforming many gel images into spot quantities.

Multivariate data analysis of proteome data.

We present the background for multivariate data analysis on proteomics data with a hands-on section on how to transfer data between different software packages. The techniques can also be used for other biological and biochemical problems in which structures have to be found in a large amount of data. Digitalization of the 2D gels, analysis using image processing software, transfer of data, multivariate data analysis, interpretation of the results, and finally we return to biology.

Monitoring lipase-catalyzed interesterification for bulky fat modification with FT-IR/NIR spectroscopy.

This work demonstrates the application of FT-IR and FT-NIR spectroscopy to monitor the enzymatic interesterification process for bulky fat modification. The reaction was conducted between palm stearin and coconut oil (70:30, w/w) with the catalysis of Lipozyme TL IM at 70 degrees C in a batch reactor. The blends and interesterified fat samples in liquid form were measured by attenuated total reflectance based FT-IR (spectra region, 1516-781 cm(-1)) and transmission mode based FT-NIR (spectra region, 5369-4752 cm(-1)) with the temperature of both controlled at 70 degrees C. The samples in solid form were also measured by reflectance-based FT-NIR (spectra regions, 7037-6039 and 5995-5612 cm(-1)) at room temperature. Calibrations of FT-IR and FT-NIR for conversion degrees (evaluated by triglyceride profile), solid fat contents (SFC), and dropping points of interesterified products were carried out by using partial least-squares regression. High correlations (r > 0.96) were obtained from cross validations of the data estimated by FT-IR, FT-NIR, and the above-mentioned conventional analytical methods, except for correlations (r = 0.90-0.95) between FT-IR and SFC profiles. Overall, FT-NIR spectroscopy coupled with transmission mode measured at 70 degrees C had the highest correlations, which also had the closest conditions to the sampled products in the process, indicating a great potential for implementation as an on-line control for monitoring the enzymatic interesterification process.

Early prediction of wheat quality: analysis during grain development using mass spectrometry and multivariate data analysis.

Matrix-assisted laser desorption/ionisation time-of-flight mass spectrometry and multivariate data analysis have been used for the determination of wheat quality at different stages of grain development. Wheat varieties with one of two different end-use qualities (i.e. suitable or not suitable for bread-making purposes) were investigated. The samples were collected from grains from 15 until 45 days post-anthesis (dpa). Gluten proteins from wheat grains were extracted and subsequently analysed by mass spectrometry. Discrimination partial least-squares regression and soft independent modelling of class analogy were used to determine the quality of new and unknown wheat samples. With these methods, we were able to predict correctly the end-use qualities at every stage investigated. This new fast technique, based on the rapidity of mass spectrometry combined with the objectivity of multivariate data analysis, offers a method that can replace the traditional rather time-consuming ones such as gel electrophoresis. This study focused on the determination of wheat quality at 15 dpa, when the grain is due for harvest 1 month later.

Spontaneous T-cell responses against peptides derived from the Taxol resistance-associated gene-3 (TRAG-3) protein in cancer patients.

Expression of the cancer-testis antigen Taxol resistance-associated gene-3 (TRAG-3) protein is associated with acquired paclitaxel (Taxol) resistance, and is expressed in various cancer types; e.g., breast cancer, leukemia, and melanoma. Thus, TRAG-3 represents an attractive target for immunotherapy of cancer. To identify HLA-A*02.01-restricted epitopes from TRAG-3, we screened cancer patients for spontaneous cytotoxic T-cell responses against TRAG-3-derived peptides. The TRAG-3 protein sequence was screened for 9mer and 10mer peptides possessing HLA-A*02.01-binding motifs. Of 12 potential binders, 9 peptides were indeed capable of binding to the HLA-A*02.01 molecule, with binding affinities ranging from strong to weak binders. Subsequently, lymphocytes from cancer patients (9 breast cancer patients, 12 melanoma patients, and 13 patients with hematopoietic malignancies) were analyzed for spontaneous reactivity against the panel of peptides by ELISpot assay. Spontaneous immune responses were detected against 8 epitope candidates in 7 of 9 breast cancer patients, 7 of 12 melanoma patients, and 5 of 13 patients with hematopoietic malignancies. In several cases, TRAG-3-specific CTL responses were scattered over several epitopes. Hence, no immunodominance of any single peptide was observed. Furthermore, single-peptide responses were detected in 2 of 12 healthy HLA-A2(+) donors, but no responses were detectable in 9 HLA-A2(-) healthy donors or 4 HLA-A2(-) melanoma patients. The identified HLA-A*02.01-restricted TRAG-3-derived epitopes are targets for spontaneous immune responses in breast cancer, hematopoietic cancer, and melanoma patients. Hence, these epitopes represent potential target structures for future therapeutic vaccinations against cancer, possibly appropriate for strategies that combine vaccination and chemotherapy; i.e., paclitaxel treatment.

Multivariate approaches in plant science.

The objective of proteomics is to get an overview of the proteins expressed at a given point in time in a given tissue and to identify the connection to the biochemical status of that tissue. Therefore sample throughput and analysis time are important issues in proteomics. The concept of proteomics is to encircle the identity of proteins of interest. However, the overall relation between proteins must also be explained. Classical proteomics consist of separation and characterization, based on two-dimensional electrophoresis, trypsin digestion, mass spectrometry and database searching. Characterization includes labor intensive work in order to manage, handle and analyze data. The field of classical proteomics should therefore be extended to also include handling of large datasets in an objective way. The separation obtained by two-dimensional electrophoresis and mass spectrometry gives rise to huge amount of data. We present a multivariate approach to the handling of data in proteomics with the advantage that protein patterns can be spotted at an early stage and consequently the proteins selected for sequencing can be selected intelligently. These methods can also be applied to other data generating protein analysis methods like mass spectrometry and near infrared spectroscopy and examples of application to these techniques are also presented. Multivariate data analysis can unravel complicated data structures and may thereby relieve the characterization phase in classical proteomics. Traditionally statistical methods are not suitable for analysis of the huge amounts of data, where the number of variables exceed the number of objects. Multivariate data analysis, on the other hand, may uncover the hidden structures present in these data. This study takes its starting point in the field of classical proteomics and shows how multivariate data analysis can lead to faster ways of finding interesting proteins. Multivariate analysis has shown interesting results as a supplement to classical proteomics and added a new dimension to the field of proteomics.

Mass spectrometry and partial least-squares regression: a tool for identification of wheat variety and end-use quality.

Rapid methods for the identification of wheat varieties and their end-use quality have been developed. The methods combine the analysis of wheat protein extracts by mass spectrometry with partial least-squares regression in order to predict the variety or end-use quality of unknown wheat samples. The whole process takes approximately 30 min. Extracts of alcohol-soluble storage proteins (gliadins) from wheat were analysed by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry. Partial least-squares regression was subsequently applied using these mass spectra for making models that could predict the wheat variety or end-use quality. Previously, an artificial neural network was used to identify wheat varieties based on their protein mass spectra profiles. The present study showed that partial least-squares regression is at least as useful as neural networks for this identification. Furthermore, it was demonstrated that partial least-squares regression could be used to predict wheat end-use quality, which has not been possible using neural networks.