Abstract
The dbPTM (http://dbPTM.mbc.nctu.edu.tw/) has been maintained for over 10 years with the aim to provide functional and structural analyses for post-translational modifications (PTMs). In ...this update, dbPTM not only integrates more experimentally validated PTMs from available databases and through manual curation of literature but also provides PTM-disease associations based on non-synonymous single nucleotide polymorphisms (nsSNPs). The high-throughput deep sequencing technology has led to a surge in the data generated through analysis of association between SNPs and diseases, both in terms of growth amount and scope. This update thus integrated disease-associated nsSNPs from dbSNP based on genome-wide association studies. The PTM substrate sites located at a specified distance in terms of the amino acids encoded from nsSNPs were deemed to have an association with the involved diseases. In recent years, increasing evidence for crosstalk between PTMs has been reported. Although mass spectrometry-based proteomics has substantially improved our knowledge about substrate site specificity of single PTMs, the fact that the crosstalk of combinatorial PTMs may act in concert with the regulation of protein function and activity is neglected. Because of the relatively limited information about concurrent frequency and functional relevance of PTM crosstalk, in this update, the PTM sites neighboring other PTM sites in a specified window length were subjected to motif discovery and functional enrichment analysis. This update highlights the current challenges in PTM crosstalk investigation and breaks the bottleneck of how proteomics may contribute to understanding PTM codes, revealing the next level of data complexity and proteomic limitation in prospective PTM research.
Anticancer peptides (ACPs) are a kind of bioactive peptides which could be used as a novel type of anticancer drug that has several advantages over chemistry-based drug, including high specificity, ...strong tumor penetration capacity, and low toxicity to normal cells. As the number of experimentally verified bioactive peptides has increased significantly, various of in silico approaches are imperative for investigating the characteristics of ACPs. However, the lack of methods for investigating the differences in physicochemical properties of ACPs. In this study, we compared the N- and C-terminal amino acid composition for each peptide, there are three major subtypes of ACPs that are defined based on the distribution of positively charged residues. For the first time, we were motivated to develop a two-step machine learning model for identification of the subtypes of ACPs, which classify the input data into the corresponding group before applying the classifier. Further, to improve the predictive power, the hybrid feature sets were considered for prediction. Evaluation by five-fold cross-validation showed that the two-step model trained with sequence-based features and physicochemical properties was most effective in discriminating between ACPs and non-ACPs. The two-step model trained with the hybrid features performed well, with a sensitivity of 86.75%, a specificity of 85.75%, an accuracy of 86.08%, and a Matthews Correlation Coefficient value of 0.703. Furthermore, the model also consistently provides the effective performance in independent testing set, with sensitivity of 77.6%, specificity of 94.74%, accuracy of 88.99% and the MCC value reached 0.75. Finally, the two-step model has been implemented as a web-based tool, namely iDACP, which is now freely available at http://mer.hc.mmh.org.tw/iDACP/ .
Owing to the importance of the post-translational modifications (PTMs) of proteins in regulating biological processes, the dbPTM (http://dbPTM.mbc.nctu.edu.tw/) was developed as a comprehensive ...database of experimentally verified PTMs from several databases with annotations of potential PTMs for all UniProtKB protein entries. For this 10th anniversary of dbPTM, the updated resource provides not only a comprehensive dataset of experimentally verified PTMs, supported by the literature, but also an integrative interface for accessing all available databases and tools that are associated with PTM analysis. As well as collecting experimental PTM data from 14 public databases, this update manually curates over 12 000 modified peptides, including the emerging S-nitrosylation, S-glutathionylation and succinylation, from approximately 500 research articles, which were retrieved by text mining. As the number of available PTM prediction methods increases, this work compiles a non-homologous benchmark dataset to evaluate the predictive power of online PTM prediction tools. An increasing interest in the structural investigation of PTM substrate sites motivated the mapping of all experimental PTM peptides to protein entries of Protein Data Bank (PDB) based on database identifier and sequence identity, which enables users to examine spatially neighboring amino acids, solvent-accessible surface area and side-chain orientations for PTM substrate sites on tertiary structures. Since drug binding in PDB is annotated, this update identified over 1100 PTM sites that are associated with drug binding. The update also integrates metabolic pathways and protein-protein interactions to support the PTM network analysis for a group of proteins. Finally, the web interface is redesigned and enhanced to facilitate access to this resource.
Although early detection and treatment of prostate cancer (PCa) improves outcomes, many patients still die of metastatic PCa. Here, we report that metastatic PCa exhibits reduced levels of the ...microRNAsmiR-101 and miR-27a. These micro-RNAs (miRNAs) negatively regulate cell invasion and inhibit the expression of FOXM1 and CENPF, two master regulators of metastasis in PCa. Interestingly, the repression of FOXM1 and CENPF by these miRNAs occurs through COUP-TFII, a member of the orphan nuclear receptors family. Loss of miR-101 positively correlates with the increase of COUP-TFII-FOXM1-CENPF activity in clinical PCa data sets, implicating clinical relevance of such regulation. Further studies show that COUP-TFII is a critical factor controlling metastatic gene networks to promote PCa metastasis. Most importantly, this miRNA-COUP-TFII-FOXM1-CENPF regulatory axis is also involved in the development of enzalutaminde resistance. Taken together, our findings highlight the contribution of specific miRNAs through the regulation of the COUP-TFII-FOXM1-CENPF cascade in PCa metastasis and drug resistance.
Parkinson's disease (PD) is a neurodegenerative disorder featuring progressive loss of midbrain dopaminergic (DA) neurons that leads to motor symptoms. The etiology and pathogenesis of PD are not ...clear. We found that expression of COUP-TFII, an orphan nuclear receptor, in DA neurons is upregulated in PD patients through the analysis of public datasets. We show here that through epigenetic regulation, COUP-TFII contributes to oxidative stress, suggesting that COUP-TFII may play a role in PD pathogenesis. Elevated COUP-TFII expression specifically in DA neurons evokes DA neuronal loss in mice and accelerates the progression of phenotypes in a PD mouse model, MitoPark. Compared to control mice, those with elevated COUP-TFII expression displayed reduced cristae in mitochondria and enhanced cellular electron-dense vacuoles in the substantia nigra pars compacta. Mechanistically, we found that overexpression of COUP-TFII disturbs mitochondrial pathways, resulting in mitochondrial dysfunction. In particular, there is repressed expression of genes encoding cytosolic aldehyde dehydrogenases, which could enhance oxidative stress and interfere with mitochondrial function via 3,4-dihydroxyphenylacetaldehyde (DOPAL) buildup in DA neurons. Importantly, under-expression of COUP-TFII in DA neurons slowed the deterioration in motor functions of MitoPark mice. Taken together, our results suggest that COUP-TFII may be an important contributor to PD development and a potential therapeutic target.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Protein phosphoglycerylation, the addition of a 1,3-bisphosphoglyceric acid (1,3-BPG) to a lysine residue of a protein and thus to form a 3-phosphoglyceryl-lysine, is a reversible and non-enzymatic ...post-translational modification (PTM) and plays a regulatory role in glucose metabolism and glycolytic process. As the number of experimentally verified phosphoglycerylated sites has increased significantly, statistical or machine learning methods are imperative for investigating the characteristics of phosphoglycerylation sites. Currently, research into phosphoglycerylation is very limited, and only a few resources are available for the computational identification of phosphoglycerylation sites.
We present a bioinformatics investigation of phosphoglycerylation sites based on sequence-based features. The TwoSampleLogo analysis reveals that the regions surrounding the phosphoglycerylation sites contain a high relatively of positively charged amino acids, especially in the upstream flanking region. Additionally, the non-polar and aliphatic amino acids are more abundant surrounding phosphoglycerylated lysine following the results of PTM-Logo, which may play a functional role in discriminating between phosphoglycerylation and non-phosphoglycerylation sites. Many types of features were adopted to build the prediction model on the training dataset, including amino acid composition, amino acid pair composition, positional weighted matrix and position-specific scoring matrix. Further, to improve the predictive power, numerous top features ranked by F-score were considered as the final combination for classification, and thus the predictive models were trained using DT, RF and SVM classifiers. Evaluation by five-fold cross-validation showed that the selected features was most effective in discriminating between phosphoglycerylated and non-phosphoglycerylated sites.
The SVM model trained with the selected sequence-based features performed well, with a sensitivity of 77.5%, a specificity of 73.6%, an accuracy of 74.9%, and a Matthews Correlation Coefficient value of 0.49. Furthermore, the model also consistently provides the effective performance in independent testing set, yielding sensitivity of 75.7% and specificity of 64.9%. Finally, the model has been implemented as a web-based system, namely iDPGK, which is now freely available at http://mer.hc.mmh.org.tw/iDPGK/ .
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Chicken ovalbumin upstream promoter-transcription factor II (COUP-TFII) has been shown to inhibit myogenesis and skeletal muscle metabolism in vitro. However, its precise role and in vivo function in ...muscle development has yet to be clearly defined. COUP-TFII protein expression level is high in undifferentiated progenitors and gradually declines during differentiation, raising an important question of whether downregulation of COUP-TFII expression is required for proper muscle cell differentiation. In this study, we generated a mouse model ectopically expressing COUP-TFII in myogenic precursors to maintain COUP-TFII activity during myogenesis and found that elevated COUP-TFII activity resulted in inefficient skeletal muscle development. Using in vitro cell culture and in vivo mouse models, we showed that COUP-TFII hinders myogenic development by repressing myoblast fusion. Mechanistically, the inefficient muscle cell fusion correlates well with the transcriptional repression of Npnt, Itgb1D and Cav3, genes important for cell-cell fusion. We further demonstrated that COUP-TFII also reduces the activation of focal adhesion kinase (FAK), an integrin downstream regulator which is essential for fusion process. Collectively, our studies highlight the importance of down-regulation of COUP-TFII signaling to allow for the induction of factors crucial for myoblast fusion.
Glutarylation, the addition of a glutaryl group (five carbons) to a lysine residue of a protein molecule, is an important post-translational modification and plays a regulatory role in a variety of ...physiological and biological processes. As the number of experimentally identified glutarylated peptides increases, it becomes imperative to investigate substrate motifs to enhance the study of protein glutarylation. We carried out a bioinformatics investigation of glutarylation sites based on amino acid composition using a public database containing information on 430 non-homologous glutarylation sites.
The TwoSampleLogo analysis indicates that positively charged and polar amino acids surrounding glutarylated sites may be associated with the specificity in substrate site of protein glutarylation. Additionally, the chi-squared test was utilized to explore the intrinsic interdependence between two positions around glutarylation sites. Further, maximal dependence decomposition (MDD), which consists of partitioning a large-scale dataset into subgroups with statistically significant amino acid conservation, was used to capture motif signatures of glutarylation sites. We considered single features, such as amino acid composition (AAC), amino acid pair composition (AAPC), and composition of k-spaced amino acid pairs (CKSAAP), as well as the effectiveness of incorporating MDD-identified substrate motifs into an integrated prediction model. Evaluation by five-fold cross-validation showed that AAC was most effective in discriminating between glutarylation and non-glutarylation sites, according to support vector machine (SVM).
The SVM model integrating MDD-identified substrate motifs performed well, with a sensitivity of 0.677, a specificity of 0.619, an accuracy of 0.638, and a Matthews Correlation Coefficient (MCC) value of 0.28. Using an independent testing dataset (46 glutarylated and 92 non-glutarylated sites) obtained from the literature, we demonstrated that the integrated SVM model could improve the predictive performance effectively, yielding a balanced sensitivity and specificity of 0.652 and 0.739, respectively. This integrated SVM model has been implemented as a web-based system (MDDGlutar), which is now freely available at http://csb.cse.yzu.edu.tw/MDDGlutar/ .
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
ABSTRACT
Human CO2 respiration requires rapid conversion between CO2 and HCO3−. Carbonic anhydrase II facilitates this reversible reaction inside red blood cells, and band 3 anion exchanger 1 (AE1) ...provides a passage for HCO3− flux across the cell membrane. These 2 proteins are core components of the CO2 transport metabolon. Intracellular H2O is necessary for CO2/HCO3− conversion. However, abundantly expressed aquaporin 1 (AQP1) in erythrocytes is thought not to be part of band 3 complexes or the CO2 transport metabolon. To solve this conundrum, we used Förster resonance energy transfer (FRET) measured by fluorescence lifetime imaging (FLIM‐FRET) and identified interaction between aquaporin‐1 and band 3 at a distance of 8 nm, within the range of dipole‐dipole interaction. Notably, their interaction was adaptable to membrane tonicity changes. This suggests that the function of AQP1 in tonicity response could be coupled or correlated to its function in band 3‐mediated CO2/HCO3− exchange. By demonstrating AQP1 as a mobile component of the CO2 transport metabolon, our results uncover a potential role of water channel in blood CO2 transport and respiration.—Hsu, K., Lee, T.‐Y., Periasamy, A., Kao, F.‐J., Li, L.‐T., Lin, C.‐Y., Lin, H.‐J., Lin, M. Adaptable interaction between aquaporin‐1 and band 3 reveals a potential role of water channel in blood CO2 transport. FASEB J. 31, 4256–4264 (2017). www.fasebj.org
Goat milk (GM), as compared to cow milk (CM), is easier for humans to digest. It also has antioxidant and anti-inflammatory effects and can improve minor digestive disorders and prevent allergic ...diseases in infants. It is unclear whether GM consumed in pregnant mothers has any protective effects on allergic diseases in infants. In this experimental study with mice, we found GM feeding enhanced immunoglobulin production, antigen-specific (ovalbumin, OVA) immune responses, and phagocytosis activity. The GM-fed mice had an increasing proportion of CD3
T lymphocytes in the spleen. Splenocytes isolated from these animals also showed significantly increased production of cytokines IFN-γ and IL-10. More importantly, GM feeding during pregnancy and lactation periods can confer protective activity onto offspring by alleviating the airway inflammation of allergic asthma induced by mite allergens. There was a remarkably different composition of gut microbiota between offspring of pregnant mice fed with water or with milk (GM or CM). There was a greater proportion of beneficial bacterial species, such as
, and
in the gut microbiota of offspring from GM- or CM-fed pregnant mice compared to the offspring of water-fed pregnant mice. These results suggested that improving the nutrition of pregnant mice can promote immunological maturation and colonization of gut microbiota in offspring. This mother-to-child biological action may provide a protective effect on atopy development and alleviate allergen-induced airway inflammation in offspring.
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