In vitro effects of bisphenol A on the quality parameters,oxidative stress,DNA integrity and adenosine triphosphate content in sterlet (Acipenser ruthenus) spermatozoa

Among endocrine disruptors, the xenoestrogen bisphenol A (BPA) deserves particular attention due to widespread human exposure. Besides hormonal effects, BPA has been suspected to be responsible for adverse effect on reproductive ability of various species. In the present study the effect of BPA on the quality parameters, oxidative stress, the DNA integrity and intracellular ATP content of sterlet (Acipenser ruthenus) spermatozoa were investigated in vitro. Fish spermatozoa were exposed to concentrations of BPA possibly occurring in nature (0.5, 1.75, 2.5, 5 and 10 μg/L) for 2 h. Results revealed that BPA significantly decreased spermatozoa motility and velocity of spermatozoa at concentration of BPA 2.5–10 μg/L. Significant positive correlation (r = 0.713, P < 0.05) was found between percent motile spermatozoa and ATP content. Oxidative stress was observed at concentrations 1.75–10 μg/L, as reflected by significantly higher levels of protein and lipid oxidation and superoxide dismutase activity. Intracellular ATP content of spermatozoa decreased with increasing concentrations of BPA. A dramatic increase in DNA fragmentation expressed as percent tail DNA (2.2% ± 0.46) and Olive tail moment (0.37 ± 0.09 arbitrary units) was recorded at concentrations of 1.75 μg/L and above. The present study confirms that concentrations of BPA that can be encountered in nature are capable to induce oxidative stress, leading to impaired sperm quality, DNA fragmentation and intracellular ATP content.     

Biomarker responses and accumulation of hazardous substances in mussels (Mytilus trossulus) transplanted along a pollution gradient close to an oil terminal in the Gulf of Finland (Baltic Sea)

Baltic Sea blue mussels (Mytilus trossulus) were used as sentinel organisms to detect the biological effects of chemical contamination in the low salinity environment. Mussels naturally adapted to a salinity of ca. 6.0 PSU were caged for 30 days at four sites along an assumed pollution gradient (salinity ca. 4.5 PSU) in the vicinity of Finland's largest oil refinery and harbor Kilpilahti in the Gulf of Finland. Tissue concentrations and accumulation rates of especially organic contaminants (PAHs, PCBs and organotins) were clearly elevated at the innermost coastal stations near the harbor area. Biological effects of contaminant exposure on caged mussels were evaluated by measuring a suite of biomarkers including catalase, glutathione S-transferase, superoxide dismutase, glutathione reductase, lipid peroxidation, acetylcholinesterase activity and lysosomal membrane stability. Mussels transplanted near the harbor area were able to elevate their antioxidant defense in response to environmental contamination. Reduced morphometric condition index and soft tissue growth rate together with increased lipid peroxidation and low lysosomal membrane stability were also observed at the most contaminated site. The results suggest that caging of M. trossulus for four weeks at lower salinity is a feasible method for the detection of environmental pollution also in low salinity areas of the Baltic Sea.     

A Fast Workflow for Identification and Quantification of Proteomes

The current in-depth proteomics makes use of long chromatography gradient to get access to more peptides for protein identification, resulting in covering of as many as 8000 mammalian gene products in 3 days of mass spectrometer running time. Here we report a fast sequencing (Fast-seq) workflow of the use of dual reverse phase high performance liquid chromatography - mass spectrometry (HPLC-MS) with a short gradient to achieve the same proteome coverage in 0.5 day. We adapted this workflow to a quantitative version (Fast quantification, Fast-quan) that was compatible to large-scale protein quantification. We subjected two identical samples to the Fast-quan workflow, which allowed us to systematically evaluate different parameters that impact the sensitivity and accuracy of the workflow. Using the statistics of significant test, we unraveled the existence of substantial falsely quantified differential proteins and estimated correlation of false quantification rate and parameters that are applied in label-free quantification. We optimized the setting of parameters that may substantially minimize the rate of falsely quantified differential proteins, and further applied them on a real biological process. With improved efficiency and throughput, we expect that the Fast-seq/Fast-quan workflow, allowing pair wise comparison of two proteomes in 1 day may make MS available to the masses and impact biomedical research in a positive way.The performance of mass spectrometry has been improved tremendously over the last few years (1–3), making mass spectrometry-based proteomics a viable approach for large-scale protein analysis in biological research. Scientists around the world are striving to fulfill the promise of identifying and quantifying almost all gene products expressed in a cell line or tissue. This would make mass spectrometry-based protein analysis an approach that is compatible to the second-generation mRNA deep-seq technique (4, 5).Two liquid chromatography (LC)-MS strategies have been employed to achieve deep proteome coverage. One is a single run with a long chromatography column and gradient to take advantage of the resolving power of HPLC to reduce the complexity of peptide mixtures; the other is a sequential run with two-dimensional separation (typically ion-exchange and reverse phase) to reduce peptide complexity. It was reported by two laboratories that 2761 and 4500 proteins were identified with a 10 h chromatography gradient on a dual pressure linear ion-trap orbitrap mass spectrometer (LTQ Orbitrap Velos)(6–8). Similarly, 3734 proteins were identified using a 8 h gradient on a 2 m long column with a hybrid triple quadrupole - time of flight (Q-TOF, AB sciex 5600 Q-TOF)(9) mass spectrometer. The two-dimensional approach has yielded more identification with longer time. For example, 10,006 proteins (representing over 9000 gene products, GPs)¹ were identified in U2OS cell (10), and 10,255 proteins (representing 9207 GPs) from HeLa cells (11). It took weeks (for example, 2–3 weeks) of machine running time to achieve such proteome coverage, pushing proteome analysis to the level that is comparable to mRNA-seq. With the introduction of faster machines, human proteome coverage now has reached the level of 7000–8500 proteins (representing 7000–8000 GPs) in 3 days (12). Notwithstanding the impressive improvement, the current approach using long column and long gradient suffers from inherent limitations: it takes long machine running time and it is challenging to keep reproducibility among repeated runs. Thus, current throughput and reproducibility have hindered the application of in-depth proteomics to traditional biological researches. A timesaving approach is in urgent need.In this study, we used the first-dimension (1D) short pH 10 RP prefractionation to reduce the complexity of the proteome (13), followed by sequential 30 min second-dimension (2D) short pH 3 reverse phase-(RP)-LC-MS/MS runs for protein identification (14). The results demonstrated that it is possible to identify 8000 gene products from mammalian cells within 12 h of total MS measurement time by applying this dual-short 2D-RPLC-MS/MS strategy (Fast sequencing, Fast-seq). The robustness of the strategy was revealed by parallel testing on different MS systems including quadrupole orbitrap mass spectrometer (Q-Exactive), hybrid Q-TOF (Triple-TOF 5600), and dual pressure linear ion-trap orbitrap mass spectrometer (LTQ-Orbitrap Velos), indicating the inherent strength of the approach as to merely taking advantage of the better MS instruments. This strategy increases the efficiency of MS sequencing in unit time for the identification of proteins. We achieved identification of 2200 proteins/30 mins on LTQ-Orbitrap Velos, 2800 proteins/30 mins on Q-Exactive and Triple-TOF 5600 respectively. We further optimized Fast-seq and worked out a quantitative-version of the Fast-seq workflow: Fast-quantification (Fast-quan) and applied it for protein abundance quantification in HUVEC cell that was treated with a drug candidate MLN4924 (a drug in phase III clinical trial). We were able to quantify > 6700 GPs in 1 day of MS running time and found 99 proteins were up-regulated with high confidence. We expect this efficient alternative approach for in-depth proteome analysis will make the application of MS-based proteomics more accessible to biological applications.     

Molecular cytogenetic characterisation of Salix viminalis L. using repetitive DNA sequences

Salix viminalis L. (2n?=?38) is a diploid dicot species belonging to the Salix genus of the Salicaceae family. This short-rotation woody crop is one of the most important renewable bioenergy resources worldwide. In breeding for high biomass productivity, limited knowledge is available on the molecular cytogenetics of willow, which could be combined with genetic linkage mapping. The present paper describes the adaptation of a fluorescence in situ hybridisation (FISH) protocol as a new approach to analyse the genomic constitution of Salix viminalis using the heterologous DNA clones pSc119.2, pTa71, pTa794, pAs1, Afa-family, pAl1, HT100.3, ZCF1 and the GAA microsatellite marker. Three of the nine probes showed unambiguous signals on the metaphase chromosomes. FISH analysis with the pTa71 probe detected one major 18S-5.8S-26S rDNA locus on the short arm of one chromosome pair; however, the pTa794 rDNA site was not visible. One chromosome pair showed a distinct signal around the centromeric region after FISH with the telomere-specific DNA clone HT100.3. Two chromosome pairs were found to have pAs1 FISH signals, which represent a D-genome-specific insert from Aegilops tauschii. Based on the FISH study, a set of chromosomes with characteristic patterns is presented, which could be used to establish the karyotype of willow species.     

Mutational analysis in podocin-associated hereditary nephrotic syndrome in Polish patients: founder effect in the Kashubian population

Hereditary nephrotic syndrome is caused by mutations in a number of different genes, the most common being NPHS2. The aim of the study was to identify the spectrum of NPHS2 mutations in Polish patients with the disease. A total of 141 children with steroid-resistant nephrotic syndrome (SRNS) were enrolled in the study. Mutational analysis included the entire coding sequence and intron boundaries of the NPHS2 gene. Restriction fragment length polymorphism (RFLP) and TaqMan genotyping assay were applied to detect selected NPHS2 sequence variants in 575 population-matched controls. Twenty patients (14 %) had homozygous or compound heterozygous NPHS2 mutations, the most frequent being c.1032delT found in 11 children and p.R138Q found in four patients. Carriers of the c.1032delT allele were exclusively found in the Pomeranian (Kashubian) region, suggesting a founder effect origin. The 14 % NPHS2 gene mutation detection rate is similar to that observed in other populations. The heterogeneity of mutations detected in the studied group confirms the requirement of genetic testing the entire NPHS2 coding sequence in Polish patients, with the exception of Kashubs, who should be initially screened for the c.1032delT deletion.     

LigandRNA: computational predictor of RNA–ligand interactions

RNA molecules have recently become attractive as potential drug targets due to the increased awareness of their importance in key biological processes. The increase of the number of experimentally determined RNA 3D structures enabled structure-based searches for small molecules that can specifically bind to defined sites in RNA molecules, thereby blocking or otherwise modulating their function. However, as of yet, computational methods for structure-based docking of small molecule ligands to RNA molecules are not as well established as analogous methods for protein-ligand docking. This motivated us to create LigandRNA, a scoring function for the prediction of RNA–small molecule interactions. Our method employs a grid-based algorithm and a knowledge-based potential derived from ligand-binding sites in the experimentally solved RNA–ligand complexes. As an input, LigandRNA takes an RNA receptor file and a file with ligand poses. As an output, it returns a ranking of the poses according to their score. The predictive power of LigandRNA favorably compares to five other publicly available methods. We found that the combination of LigandRNA and Dock6 into a “meta-predictor” leads to further improvement in the identification of near-native ligand poses. The LigandRNA program is available free of charge as a web server at http://ligandrna.genesilico.pl.     

Ghrelin induces apoptosis in colon adenocarcinoma cells via proteasome inhibition and autophagy induction

Ghrelin is a metabolism-regulating hormone recently investigated for its role in cancer survival and progression. Controversially, ghrelin may act as either anti-apoptotic or pro-apoptotic factor in different cancer cells, suggesting that the effects are cell type dependent. Limited data are currently available on the effects exerted by ghrelin on intracellular proteolytic pathways in cancer. Both the lysosomal and the proteasomal systems are fundamental in cellular proliferation and apoptosis regulation. With the aim of exploring if the proteasome and autophagy may be possible targets of ghrelin in cancer, we exposed human colorectal adenocarcinoma cells to ghrelin. Preliminary in vitro fluorimetric assays evidenced for the first time a direct inhibition of 20S proteasomes by ghrelin, particularly evident for the trypsin-like activity. Moreover, 1 μM ghrelin induced apoptosis in colorectal adenocarcinoma cells by inhibiting the ubiquitin–proteasome system and by activating autophagy, with p53 having an “interactive” role.