A global review and meta-analysis of applications of the freshwater Fish Invasiveness Screening Kit

Reviews in Fish Biology and Fisheries - The freshwater Fish Invasiveness Screening Kit (FISK) has been applied in 35 risk assessment areas in 45 countries across the six inhabited continents (11...     

Length-weight relationship in adult huchen Hucho hucho (L., 1758) from Drina River, Serbia

Huchen Hucho hucho from the Drina River (Serbia) revealed recently the decrease in breakpoint values for both standard length (Sl) and weight (w) in relation to the values recorded in 1999 from 110 cm to 98.4 cm and from 16.5 kg to 10.5 kg, respectively. That might indicate to the change in certain population parameters that could have an influence to the growth in the adult period of life.     

Free and bound state structures of 6-O-methyl homoerythromycins and epitope mapping of their interactions with ribosomes

The solution and solid state conformations of several 6-O-methyl homoerythromycins 1–4 were studied using a combination of X-ray crystallography, NMR spectroscopy and molecular modelling calculations. In the solid state 1 was found to exist as the two independent molecules with similar structures termed 3-endo-folded-out. In solution a significant conformational flexibility was noticed especially in the C2 to C5 region. The compounds 1 and 2 unlike 14-membered macrolides adopted the 3-endo-folded-out conformation while 3 and 4 existed in the classical folded-out conformation. TrNOESY and STD experiments showed that 1 and 2 bound to the Escherichia coli ribosome while 3 and 4, lacking the cladinose sugar, did not exhibit binding activities, this being in accordance with biochemical data. The bound conformations were found to be very similar to the free ones, some small differences were observed and discussed. The STD experiments provided evidence on binding epitopes. The structural parts of 1 and 2 in close contact with ribosome were similar, however the degree of saturation transfer was higher for 2. The differences between tr-NOE data and STD enhancements in 1 and 2 arouse as a consequence of structural changes upon binding and a closer proximity of 2 to the ribosome surface. An understanding of the molecular mechanisms involved in the interaction of macrolides with ribosomes can help in developing strategies aiming at design of potential inhibitors.     

Length-dependent prediction of protein intrinsic disorder

Background  

Due to the functional importance of intrinsically disordered proteins or protein regions, prediction of intrinsic protein disorder from amino acid sequence has become an area of active research as witnessed in the 6th experiment on Critical Assessment of Techniques for Protein Structure Prediction (CASP6). Since the initial work by Romero et al. (Identifying disordered regions in proteins from amino acid sequences, IEEE Int. Conf. Neural Netw., 1997), our group has developed several predictors optimized for long disordered regions (>30 residues) with prediction accuracy exceeding 85%. However, these predictors are less successful on short disordered regions (≤30 residues). A probable cause is a length-dependent amino acid compositions and sequence properties of disordered regions.     

Extending the coverage of spectral libraries: A neighbor‐based approach to predicting intensities of peptide fragmentation spectra

Searching spectral libraries in MS/MS is an important new approach to improving the quality of peptide and protein identification. The idea relies on the observation that ion intensities in an MS/MS spectrum of a given peptide are generally reproducible across experiments, and thus, matching between spectra from an experiment and the spectra of previously identified peptides stored in a spectral library can lead to better peptide identification compared to the traditional database search. However, the use of libraries is greatly limited by their coverage of peptide sequences: even for well‐studied organisms a large fraction of peptides have not been previously identified. To address this issue, we propose to expand spectral libraries by predicting the MS/MS spectra of peptides based on the spectra of peptides with similar sequences. We first demonstrate that the intensity patterns of dominant fragment ions between similar peptides tend to be similar. In accordance with this observation, we develop a neighbor‐based approach that first selects peptides that are likely to have spectra similar to the target peptide and then combines their spectra using a weighted K‐nearest neighbor method to accurately predict fragment ion intensities corresponding to the target peptide. This approach has the potential to predict spectra for every peptide in the proteome. When rigorous quality criteria are applied, we estimate that the method increases the coverage of spectral libraries available from the National Institute of Standards and Technology by 20–60%, although the values vary with peptide length and charge state. We find that the overall best search performance is achieved when spectral libraries are supplemented by the high quality predicted spectra.     

Evaluating Purifying Selection in the Mitochondrial DNA of Various Mammalian Species

Mitochondrial DNA (mtDNA), the circular DNA molecule inside the mitochondria of all eukaryotic cells, has been shown to be under the effect of purifying selection in several species. Traditional testing of purifying selection has been based simply on ratios of nonsynonymous to synonymous mutations, without considering the relative age of each mutation, which can be determined by phylogenetic analysis of this non-recombining molecule. The incorporation of a mutation time-ordering from phylogeny and of predicted pathogenicity scores for nonsynonymous mutations allow a quantitative evaluation of the effects of purifying selection in human mtDNA. Here, by using this additional information, we show that purifying selection undoubtedly acts upon the mtDNA of other mammalian species/genera, namely Bos sp., Canis lupus, Mus musculus, Orcinus orca, Pan sp. and Sus scrofa. The effects of purifying selection were comparable in all species, leading to a significant major proportion of nonsynonymous variants with higher pathogenicity scores in the younger branches of the tree. We also derive recalibrated mutation rates for age estimates of ancestors of these various species and proposed a correction curve in order to take into account the effects of selection. Understanding this selection is fundamental to evolutionary studies and to the identification of deleterious mutations.     

Quantitative Measurement of Phosphoproteome Response to Osmotic Stress in Arabidopsis Based on Library-Assisted eXtracted Ion Chromatogram (LAXIC)

Global phosphorylation changes in plants in response to environmental stress have been relatively poorly characterized to date. Here we introduce a novel mass spectrometry-based label-free quantitation method that facilitates systematic profiling plant phosphoproteome changes with high efficiency and accuracy. This method employs synthetic peptide libraries tailored specifically as internal standards for complex phosphopeptide samples and accordingly, a local normalization algorithm, LAXIC, which calculates phosphopeptide abundance normalized locally with co-eluting library peptides. Normalization was achieved in a small time frame centered to each phosphopeptide to compensate for the diverse ion suppression effect across retention time. The label-free LAXIC method was further treated with a linear regression function to accurately measure phosphoproteome responses to osmotic stress in Arabidopsis. Among 2027 unique phosphopeptides identified and 1850 quantified phosphopeptides in Arabidopsis samples, 468 regulated phosphopeptides representing 497 phosphosites have shown significant changes. Several known and novel components in the abiotic stress pathway were identified, illustrating the capability of this method to identify critical signaling events among dynamic and complex phosphorylation. Further assessment of those regulated proteins may help shed light on phosphorylation response to osmotic stress in plants.Phosphorylation plays a pivotal role in the regulation of a majority of cellular processes via signaling transduction pathways. During the last decade, quantitative phosphoproteomics has become a powerful and versatile platform to profile signaling pathways at a system-wide scale. Multiple signaling networks in different organisms have been characterized through global phosphorylation profiling (1–3), which has evolved over the years with highly optimized procedures for sample preparation and phosphopeptide enrichment, high resolution mass spectrometry, and data analysis algorithms to identify and quantify thousands of phosphorylation events (4–8).Quantitative phosphoproteomics can be achieved mainly by two major techniques, stable isotope labeling and label-free quantitation. Isotope labeling prior to liquid chromatography-mass spectrometry (LC-MS)¹ has been widely used, including metabolic labeling such as stable isotope labeling by amino acids in cell culture (SILAC), chemical labeling such as multiplexed isobaric tags for relative and absolute quantification (iTRAQ) and isotope-coded affinity tags (ICAT) (9–12). On the other hand, label-free quantitation has gained momentum in recent years (13–15), as no additional chemistry or sample preparation steps are required. Compared with stable isotope labeling, label-free quantitation has higher compatibility with the source of the samples, the number of samples for comparison, and the instrument choice.Many label-free approaches, in particular to phosphoproteomics, are based on ion intensity (16, 17), but they are relatively error-prone because of run-to-run variations in LC/MS performance (18). In theory, such systematic errors can be corrected by spiking an internal standard into every sample to be compared. Several methods based on internal standard spiking have been reported so far. Absolute quantification peptide technology (AQUA) (19), for example, uses synthetic peptides with isotope labeling for absolute quantitation. For a global quantitative proteomics study, it is unrealistic to spike-in all reference peptides. Another labeling reference method, spike-in SILAC appears to be a promising technique to quantify the proteome in vivo with multiplex capability and it can be extended to clinical samples (20). One solution to large-scale quantitation without any isotope labeling is pseudo internal standard approach (21), which selects endogenous house-keeping proteins as the internal standard so that no spike-in reagent is required. However, finding a good pseudo internal standard remains a challenge for phosphoproteome samples. Spike-in experiments are an alternative way to improve normalization profile. Some internal standard peptides such as MassPREP^TM (Waters) were already widely used. Other groups spiked an identical amount of standard protein into samples prior to protein digestion (22–24). There are two major normalization procedures. In one approach, sample peptides were normalized to the total peak intensity of spike-in peptides (25). Alternatively, the digested peptides were compared at first and the normalization factor was determined in different ways such as the median (26) or average of ratios (27). However, spiking an identical amount of standard proteins into phosphoproteomic samples before protein digestion may not be compatible with phosphoproteomic analyses which typically require a phosphopeptide enrichment step. Spectral counting has been extensively applied in large sets of proteomic samples because of its simplicity but the method is often not reliable for the quantitation of phosphoproteins, which are typically identified by single phosphopeptides with few spectra (28–30). Many software packages have been implemented to support the wide variety of those quantitation techniques, including commercial platforms such as Progenesis LC-MS^TM, Mascot Distiller^TM, PEAKS Q^TM, etc., as well as open-source software packages including MaxQuant (31), PEPPeR (32), Skyline (33), etc.In this study, we have devised a novel label-free quantitation strategy termed Library Assisted eXtracted Ion Chromatogram (LAXIC) for plant phosphoproteomic analyses with high accuracy and consistency (Fig. 1). The approach employs synthetic peptide libraries as the internal standard. These peptides were prepared to have proper properties for quality control assessments and mass spectrometric measurements. In particular, peptides were designed to elute sequentially over an entire LC gradient and to have suitable ionization efficiency and m/z values within the normally scanned mass range. Local normalization of peak intensity is performed using Loess Procedure, a data treatment adopted from cDNA microarray data analysis (34). To monitor the diverse ion suppression effect across retention time, the local normalization factors (LNFs) are determined by internal standard pairs in individual time windows. Finally, samples will be quantified with LNFs in order to correct variance of LC-MS conditions. This quantification occurs in a small time frame centered to each target peptide.Open in a separate windowFig. 1.Work flow for the LAXIC strategy to quantify the phosphorylation change in response to osmotic stress. A, Schematic representation of the LAXIC algorithm. First, all the chromatographic peaks were aligned and the ratios were calculated. Second, the normalization factors which equal to ratios of library peptide peaks between MS runs were chosen to construct normalization curve. Third, sample peptide peak ratios were normalized against predicted normalization factor corresponding to certain retention time. B, Schematic representation of quantitative phosphoproteomics. Plants either treated with mannitol or PBS were lysed and mixed proportionally at first. Following peptide digestion and enrichment, phosphopeptides were identified and further quantified through LAXIC incorporated with self-validating process using thelinear regression model to analyze the fold change (fold), linearity (R²) and accuracy (%Acc).Water deficit and salinity causes osmotic stress, which is a major environmental factor limiting plant agricultural productivity. Osmotic stress rapidly changes the metabolism, gene expression and development of plant cells by activating several signaling pathways. Several protein kinases have been characterized as key components in osmotic stress signaling. Arabidopsis histidine kinase AHK1 can complement the histidine kinase mutant yeast, which can act as the osmosensor in yeast (35). Overexpression of AHK1 gene increases the drought tolerance of transgenic plants in Arabidopsis (36). Similar to yeast, the MAPK kinase cascade is also involved in osmotic stress response in plants. It is reported that AtMPK3, AtMPK6, and tobacco SIPK can be activated by NaCl or mannitol, and play positive roles in osmotic signaling (37, 38). MKK7 and MKKK20 may act as the up-stream kinase in the kinase cascade (39). Involvement of some calcium-dependent protein kinases, such as AtCPK21, AtCPK6, and OsCPK7 (CDPK) in osmotic stress signaling has also been reported (40–42). Another kinase family, SNF1-related protein kinase (SnRK) 2, also participates in osmotic stress response. In Arabidopsis, there are ten members in the SnRK2 family. Five from the ten SnRK2s, SnRK2, 3, 6, 7, and 8, can be activated by abscisic acid (ABA) and play central roles in ABA-receptor coupled signaling (43, 44). Furthermore, all SnRK2s except SnRK2.9 can be activated by NaCl or mannitol treatment (43). The decuple mutant of SnRK2 showed a strong osmotic hypersensitive phenotype (45). It is proposed that protein kinases including MAPK and SnRK2s have a critical function in osmotic stress (46), but the detailed mechanism and downstream substrates or target signal components are not yet clarified. We applied, therefore, the LAXIC approach with a self-validating method (47) to profile the osmotic stress-dependent phosphoproteome in Arabidopsis by quantifying phosphorylation events before and after mannitol treatment. Among a total of over 2000 phosphopeptides, more than 400 of them are dependent on osmotic stress. Those phosphoproteins are present on enzymes participating in signaling networks that are involved in many processes such as signal transduction, cytoskeleton development, and apoptosis. Overall, LAXIC represents a powerful tool for label-free quantitative phosphoproteomics.