Na tropie środków przydatnych w terapii lub profilaktyce choroby Alzheimera

Mimo olbrzymich inwestycji kadrowych i finansowych, próby pozyskiwania nowych przełomowych leków okazują się coraz trudniejsze, a w przypadku choroby Alzheimera wręcz nieskuteczne. Farmakoterapia choroby Alzheimera i innych chorób, w których obserwuje się tworzenie fibryli białka amyloidowego, nie rokuje całkowitego wyleczenia czy poprawy funkcjonowania chorych. Rutynowo stosuje się leczenie paliatywne, objawowe lub substytucyjne. W fazie eksperymentalnej jest terapia skojarzona, z użyciem środków działających plejotropowo oraz substancji, które mają hamować zwyrodnienie neurofibrylarne. Obserwacje epidemiologiczne, kojarzone z paleniem tytoniu, skierowały uwagę badaczy na podjednostkę α7 neuronowego receptora cholinergicznego typu nikotynowego (α7nAChR). Najbardziej obiecujące i racjonalne wydają się jednak próby ingerencji farmakologicznej w proces agregacji amyloidu czy rozpuszczania jego złogów. Istnieją doniesienia o takim działaniu dla różnych środków, szczególnie przyjmowanych długotrwale. Obok nikotyny i pochodnych wchodzących w skład etnograficznie charakterystycznych używek, wskazuje się także na niektóre składniki prawidłowej diety, w tym kwasy tłuszczowe omega-3. W badaniach zainicjowanych w Katedrze Biofarmacji i Farmakodynamiki Gdańskiego Uniwersytetu Medycznego, mierzono nową metodą elektrochemicznospektroskopową powinowactwo wielu związków pirydynowych i piperydynowych, zwłaszcza alkaloidów występujących w używkach i przyprawach, do amyloidu β(1–42). Wykazano silne właściwości wiązania amyloidu z wieloma wytypowanymi do badań związkami. Szczególnie obiecująco z punktu widzenia profilaktyki choroby Alzheimera przedstawia się alkaloid trigonellina, charakterystyczny dla powszechnie spożywanych w Azji (także jako składnik curry) i znanych w Polsce nasion kozieradki, która należy do surowców roślinnych uwzględnionych w obowiązującej Farmakopei Europejskiej

Proteomic analysis of small acid soluble proteins in the spore core of <it>Bacillus subtilis ΔprpE </it>and 168 strains with predictions of peptides liquid chromatography retention times as an additional tool in protein identification

Abstract Background Sporulation, characteristic for some bacteria such as Bacillus subtilis, has not been entirely defined yet. Protein phosphatase E (PrpE) and small, acid soluble spore proteins (SASPs) influence this process. Nevertheless, direct result of PrpE interaction on SASPs content in spore coat of B. subtilis has not been evidenced so far. As proteomic approach enables global analysis of occurring proteins, therefore it was chosen in this experiment to compare SASPs occurrence in two strains of B. subtilis, standard 168 and ΔprpE, lacking PrpE phosphatase. Proteomic analysis is still a challenge, and despite of big approach in mass spectrometry (MS) field, the identification reliability remains unsatisfactory. Therefore there is a rising interest in new methods, particularly bioinformatic tools that would harden protein identification. Most of currently applied algorithms are based on MS-data. Information from separation steps is not still in routine usage, even though they also provide valuable facts about analyzed structures. The aim of this research was to apply a model for peptides retention times prediction, based on quantitative structure-retention relationships (QSRR) in SASPs analysis, obtained from two strains of B. subtilis proteome digests after separation and identification of the peptides by LC-ESI-MS/MS. The QSRR approach was applied as the additional constraint in proteomic research verifying results of MS/MS ion search and confirming the correctness of the peptides identifications along with the indication of the potential false positives and false negatives. Results In both strains of B. subtilis, peptides characteristic for SASPs were found, however their identification confidence varied. According to the MS identity parameter Xcorr and difference between predicted and experimental retention times (ΔtR) four groups could be distinguished: correctly and incorrectly identified, potential false positives and false negatives. The ΔprpE strain was characterized by much higher amount of SASPs peptides than standard 168 and their identification confidence was, mostly for alpha- and beta-type SASP, satisfactory. Conclusions The QSRR-based model for predicting retention times of the peptides, was a useful additional to MS tool, enhancing protein identification. Higher content of SASPs in strain lacking PrpE phosphatase suggests that this enzyme may influence their occurrence in the spores, lowering levels of these proteins.</p

Host-adaptive traits in the plant-colonizing Pseudomonas donghuensis P482 revealed by transcriptomic responses to exudates of tomato and maize

Abstract Pseudomonads are metabolically flexible and can thrive on different plant hosts. However, the metabolic adaptations required for host promiscuity are unknown. Here, we addressed this knowledge gap by employing RNAseq and comparing transcriptomic responses of Pseudomonas donghuensis P482 to root exudates of two plant hosts: tomato and maize. Our main goal was to identify the differences and the common points between these two responses. Pathways upregulated only by tomato exudates included nitric oxide detoxification, repair of iron-sulfur clusters, respiration through the cyanide-insensitive cytochrome bd, and catabolism of amino and/or fatty acids. The first two indicate the presence of NO donors in the exudates of the test plants. Maize specifically induced the activity of MexE RND-type efflux pump and copper tolerance. Genes associated with motility were induced by maize but repressed by tomato. The shared response to exudates seemed to be affected both by compounds originating from the plants and those from their growth environment: arsenic resistance and bacterioferritin synthesis were upregulated, while sulfur assimilation, sensing of ferric citrate and/or other iron carriers, heme acquisition, and transport of polar amino acids were downregulated. Our results provide directions to explore mechanisms of host adaptation in plant-associated microorganisms

Molecular Descriptor Subset Selection in Theoretical Peptide Quantitative Structure–Retention Relationship Model Development Using Nature-Inspired Optimization Algorithms

In this work, performance of five nature-inspired optimization algorithms, genetic algorithm (GA), particle swarm optimization (PSO), artificial bee colony (ABC), firefly algorithm (FA), and flower pollination algorithm (FPA), was compared in molecular descriptor selection for development of quantitative structure–retention relationship (QSRR) models for 83 peptides that originate from eight model proteins. The matrix with 423 descriptors was used as input, and QSRR models based on selected descriptors were built using partial least squares (PLS), whereas root mean square error of prediction (RMSEP) was used as a fitness function for their selection. Three performance criteria, prediction accuracy, computational cost, and the number of selected descriptors, were used to evaluate the developed QSRR models. The results show that all five variable selection methods outperform interval PLS (iPLS), sparse PLS (sPLS), and the full PLS model, whereas GA is superior because of its lowest computational cost and higher accuracy (RMSEP of 5.534%) with a smaller number of variables (nine descriptors). The GA-QSRR model was validated initially through Y-randomization. In addition, it was successfully validated with an external testing set out of 102 peptides originating from <i>Bacillus subtilis</i> proteomes (RMSEP of 22.030%). Its applicability domain was defined, from which it was evident that the developed GA-QSRR exhibited strong robustness. All the sources of the model’s error were identified, thus allowing for further application of the developed methodology in proteomics

Correctness of Protein Identifications of Bacillus subtilis Proteome with the Indication on Potential False Positive Peptides Supported by Predictions of Their Retention Times

The predictive capability of the retention time prediction model based on quantitative structure-retention relationships (QSRR) was tested. QSRR model was derived with the use of set of peptides identified with the highest scores and originated from 8 known proteins annotated as model ones. The predictive ability of the QSRR model was verified with the use of a Bacillus subtilis proteome digest after separation and identification of the peptides by LC-ESI-MS/MS. That ability was tested with three sets of testing peptides assigned to the proteins identified with different levels of confidence. First, the set of peptides identified with the highest scores achieved in the search were considered. Hence, proteins identified on the basis of more than one peptide were taken into account. Furthermore, proteins identified on the basis of just one peptide were also considered and, depending on the possessed scores, both above and below the assumed threshold, were analyzed in two separated sets. The QSRR approach was applied as the additional constraint in proteomic research verifying results of MS/MS ion search and confirming the correctness of the peptides identifications along with the indication of the potential false positives

A targeted mass spectrometry immunoassay to quantify osteopontin in fresh-frozen breast tumors and adjacent normal breast tissues

Osteopontin (OPN) is a multifunctional protein that can activate cell-signaling pathways and lead to cancer development and metastasis. Elevated OPN expression was reported in different cancer types, including breast tumors. Here, we present a new immuno-mass spectrometry method for OPN quantification in fresh-frozen malignant and adjacent normal human breast tissues. For quantification we used two proteotypic peptides: OPN-peptide-1 and OPN-peptide-2. Peptide concentrations were determined by liquid chromatography-tandem mass spectrometry (LC-MS/MS) in multiple reaction monitoring (MRM) mode with stable isotope standards (SIS) and immuno-affinity enrichment for isolation of OPN peptides. Based on the OPN-peptide-1, the average OPN concentration in normal breast tissue was 19.42 μg/g, while the corresponding level in breast tumors was 603.9 μg/g. Based on OPN-peptide-2, the average concentration in normal breast tissue was 19.30 μg/g and in breast tumors 535.0 μg/g. In ER/PR/HER2(−) patients the OPN levels in breast tumors were significantly higher than in corresponding normal breast tissue samples, whereas in the single ER/PR/HER2(+) patient the OPN concentration in tumor samples was lower than in normal breast tissue sample. In conclusion, the current method is considered promising for the quantification of OPN in research and in clinical settings and should be further studied in breast cancer patients

Anti-Candida albicans effect of the protein-carbohydrate fraction obtained from the coelomic fluid of earthworm Dendrobaena veneta.

An antifungal active fraction (AAF) from the coelomic fluid (CF) of the earthworm Dendrobaena veneta was isolated. The aim of the study was to analyze the antifungal activity of the AAF and to carry out chemical characterization of the fraction. The active fraction showed antifungal activity against a clinical C. albicans isolate, C. albicans ATCC 10231, and C. krusei ATCC 6258. It effectively reduced the metabolic activity of C. albicans cells and influenced their morphology after 48 hours of incubation. Scanning electron microscopy (SEM) images revealed loss of integrity of the cell wall induced by the active fraction. Calcofluor White staining showed changes in the structure of the C. albicans cell wall induced by the AAF. The fungal cells died via apoptosis and necrosis after the treatment with the studied fraction. Electrophoresis under native conditions revealed the presence of two compounds in the AAF, while SDS/PAGE gel electrophoresis showed several protein and carbohydrate compounds. The active fraction was analyzed using Raman spectroscopy, MALDI TOF/TOF, and ESI LC-MS. The Raman analysis confirmed the presence of proteins and determined their secondary structure. The MALDI TOF/TOF analysis facilitated detection of four main compounds with a mass of 7694.9 m/z, 12292.3 m/z, 21628.3 m/z, and 42923.2 m/z in the analyzed fraction. The presence of carbohydrate compounds in the preparation was confirmed by nuclear magnetic resonance (NMR) and gas chromatography (GC-MS). The ATR-FTIR spectrum of the AAF exhibited high similarity to the spectrum of egg white lysozyme. The AAF showed no endotoxicity and cytotoxicity towards normal skin fibroblasts (HSF); therefore, it can be used for the treatment of skin and mucous membrane candidiasis in the future. Given its efficient and selective action, the fraction seems to be a promising preparation with antifungal activity against C. albicans

Qualitative and Quantitative Analysis of Proteome and Peptidome of Human Follicular Fluid Using Multiple Samples from Single Donor with LC–MS and SWATH Methodology

Human follicular fluid (hFF) is a natural environment of oocyte maturation, and some components of hFF could be used to judge oocyte capability for fertilization and further development. In our pilot small-scale study three samples from four donors (12 samples in total) were analyzed to determine which hFF proteins/peptides could be used to differentiate individual oocytes and which are patient-specific. Ultrafiltration was used to fractionate hFF to high-molecular-weight (HMW) proteome (>10 kDa) and low-molecular-weight (LMW) peptidome (<10 kDa) fractions. HMW and LMW compositions were analyzed using LC–MS in SWATH data acquisition and processing methodology. In total we were able to identify 158 proteins, from which 59 were never reported before as hFF components. 55 (45 not reported before) proteins were found by analyzing LMW fraction, 67 (14 not reported before) were found by analyzing HMW fraction, and 36 were identified in both fractions of hFF. We were able to perform quantitative analysis for 72 proteins from HMW fraction of hFF. We found that concentrations of 11 proteins varied substantially among hFF samples from single donors, and those proteins are promising targets to identify biomarkers useful in oocyte quality assessment