PTM-Logo: a program for generation of sequence logos based on position-specific background amino-acid probabilities.

SUMMARY: Identification of the amino-acid motifs in proteins that are targeted for post-translational modifications (PTMs) is of great importance in understanding regulatory networks. Information about targeted motifs can be derived from mass spectrometry data that identify peptides containing specific PTMs such as phosphorylation, ubiquitylation and acetylation. Comparison of input data against a standardized 'background' set allows identification of over- and under-represented amino acids surrounding the modified site. Conventionally, calculation of targeted motifs assumes a random background distribution of amino acids surrounding the modified position. However, we show that probabilities of amino acids depend on (i) the type of the modification and (ii) their positions relative to the modified site. Thus, software that identifies such over- and under-represented amino acids should make appropriate adjustments for these effects. Here we present a new program, PTM-Logo, that generates representations of these amino acid preferences ('logos') based on position-specific amino-acid probability backgrounds calculated either from user-input data or curated databases. AVAILABILITY AND IMPLEMENTATION: PTM-Logo is freely available online at http://sysbio.chula.ac.th/PTMLogo/ or https://hpcwebapps.cit.nih.gov/PTMLogo/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Vitamin D receptor regulates autophagy in the normal mammary gland and in luminal breast cancer cells.

Women in North America have a one in eight lifetime risk of developing breast cancer (BC), and a significant proportion of these individuals will develop recurrent BC and will eventually succumb to the disease. Metastatic, therapy-resistant BC cells are refractory to cell death induced by multiple stresses. Here, we document that the vitamin D receptor (VDR) acts as a master transcriptional regulator of autophagy. Activation of the VDR by vitamin D induces autophagy and an autophagic transcriptional signature in BC cells that correlates with increased survival in patients; strikingly, this signature is present in the normal mammary gland and is progressively lost in patients with metastatic BC. A number of epidemiological studies have shown that sufficient vitamin D serum levels might be protective against BC. We observed that dietary vitamin D supplementation in mice increases basal levels of autophagy in the normal mammary gland, highlighting the potential of vitamin D as a cancer-preventive agent. These findings point to a role of vitamin D and the VDR in modulating autophagy and cell death in both the normal mammary gland and BC cells.

Structural characterization of a putative chitin synthase gene in Phytophthora spp. and analysis of its transcriptional activity during pathogenesis on potato and soybean plants.

Although chitin is a major component of the fungal cell wall, in oomycetes (fungal-like organisms), this compound has only been found in very little amounts, mostly in the cell wall of members of the genera Achlya and Saprolegnia. In the oomycetes Phytophthora infestans and P. sojae the presence of chitin has not been demonstrated; however, the gene putatively encoding chitin synthase (CHS), the enzyme that synthesizes chitin, is present in their genomes. The evolutionary significance of the CHS gene in P. infestans and P. sojae genomes is not fully understood and, therefore, further studies are warranted. We have cloned and characterized the putative CHS genes from two Phytophthora spp. and multiple isolates of P. infestans and P. sojae and analyzed their phylogenetic relationships. We also conducted CHS inhibition assays and measured CHS transcriptional activity in Phytophthora spp. during infection of susceptible plants. Results of our investigations suggest that CHS contains all the motifs that are typical in CHS genes of fungal origin and is expressed, at least at the mRNA level, during in vitro and in planta growth. In infected tissues, the highest levels of expression occurred in the first 12 h post inoculation. In addition, results from our inhibition experiments appear to suggest that CHS activity is important for P. infestans normal vegetative growth. Because of the considerable variation in expression during infection when compared to basal expression observed in in vitro cultures of non-sporulating mycelium, we hypothesize that CHS may have a meaningful role in Phytophthora pathogenicity.

SOHPRED: a new bioinformatics tool for the characterization and prediction of human S-sulfenylation sites.

Protein S-sulfenylation (SOH) is a type of post-translational modification through the oxidation of cysteine thiols to sulfenic acids. It acts as a redox switch to modulate versatile cellular processes and plays important roles in signal transduction, protein folding and enzymatic catalysis. Reversible SOH is also a key component for maintaining redox homeostasis and has been implicated in a variety of human diseases, such as cancer, diabetes, and atherosclerosis, due to redox imbalance. Despite its significance, the in situ trapping of the entire 'sulfenome' remains a major challenge. Yang et al. have recently experimentally identified about 1000 SOH sites, providing an enriched benchmark SOH dataset. In this work, we developed a new ensemble learning tool SOHPRED for identifying protein SOH sites based on the compositions of enriched amino acids and the physicochemical properties of residues surrounding SOH sites. SOHPRED was built based on four complementary predictors, i.e. a naive Bayesian predictor, a random forest predictor and two support vector machine predictors, whose training features are, respectively, amino acid occurrences, physicochemical properties, frequencies of k-spaced amino acid pairs and sequence profiles. Benchmarking experiments on the 5-fold cross validation and independent tests show that SOHPRED achieved AUC values of 0.784 and 0.799, respectively, which outperforms several previously developed tools. As a real application of SOHPRED, we predicted potential SOH sites for 193 S-sulfenylated substrates, which had been experimentally detected through a global sulfenome profiling in living cells, though the actual SOH sites were not determined. The web server of SOHPRED has been made publicly available at for the wider research community. The source codes and the benchmark datasets can be downloaded from the website.

The genome of the yellow potato cyst nematode, Globodera rostochiensis, reveals insights into the basis of parasitism and virulence.

BACKGROUND: The yellow potato cyst nematode, Globodera rostochiensis, is a devastating plant pathogen of global economic importance. This biotrophic parasite secretes effectors from pharyngeal glands, some of which were acquired by horizontal gene transfer, to manipulate host processes and promote parasitism. G. rostochiensis is classified into pathotypes with different plant resistance-breaking phenotypes. RESULTS: We generate a high quality genome assembly for G. rostochiensis pathotype Ro1, identify putative effectors and horizontal gene transfer events, map gene expression through the life cycle focusing on key parasitic transitions and sequence the genomes of eight populations including four additional pathotypes to identify variation. Horizontal gene transfer contributes 3.5 % of the predicted genes, of which approximately 8.5 % are deployed as effectors. Over one-third of all effector genes are clustered in 21 putative 'effector islands' in the genome. We identify a dorsal gland promoter element motif (termed DOG Box) present upstream in representatives from 26 out of 28 dorsal gland effector families, and predict a putative effector superset associated with this motif. We validate gland cell expression in two novel genes by in situ hybridisation and catalogue dorsal gland promoter element-containing effectors from available cyst nematode genomes. Comparison of effector diversity between pathotypes highlights correlation with plant resistance-breaking. CONCLUSIONS: These G. rostochiensis genome resources will facilitate major advances in understanding nematode plant-parasitism. Dorsal gland promoter element-containing effectors are at the front line of the evolutionary arms race between plant and parasite and the ability to predict gland cell expression a priori promises rapid advances in understanding their roles and mechanisms of action.

Improving protein fold recognition and structural class prediction accuracies using physicochemical properties of amino acids.

Predicting the three-dimensional (3-D) structure of a protein is an important task in the field of bioinformatics and biological sciences. However, directly predicting the 3-D structure from the primary structure is hard to achieve. Therefore, predicting the fold or structural class of a protein sequence is generally used as an intermediate step in determining the protein's 3-D structure. For protein fold recognition (PFR) and structural class prediction (SCP), two steps are required - feature extraction step and classification step. Feature extraction techniques generally utilize syntactical-based information, evolutionary-based information and physicochemical-based information to extract features. In this study, we explore the importance of utilizing the physicochemical properties of amino acids for improving PFR and SCP accuracies. For this, we propose a Forward Consecutive Search (FCS) scheme which aims to strategically select physicochemical attributes that will supplement the existing feature extraction techniques for PFR and SCP. An exhaustive search is conducted on all the existing 544 physicochemical attributes using the proposed FCS scheme and a subset of physicochemical attributes is identified. Features extracted from these selected attributes are then combined with existing syntactical-based and evolutionary-based features, to show an improvement in the recognition and prediction performance on benchmark datasets.

In Vivo Chromatin Targets of the Transcription Factor Yin Yang 2 in Trophoblast Stem Cells.

BACKGROUND: Yin Yang 2 (YY2) is a zinc finger protein closely related to the well-characterized Yin Yang 1 (YY1). YY1 is a DNA-binding transcription factor, with defined functions in multiple developmental processes, such as implantation, cell differentiation, X inactivation, imprinting and organogenesis. Yy2 has been treated as a largely immaterial duplication of Yy1, as they share high homology in the Zinc Finger-region and similar if not identical in vitro binding sites. In contrast to these similarities, gene expression alterations in HeLa cells with attenuated levels of either Yy1 or Yy2 were to some extent gene-specific. Moreover, the chromatin binding sites for YY2, except for its association with transposable retroviral elements (RE) and Endogenous Retroviral Elements (ERVs), remain to be identified. As a first step towards defining potential Yy2 functions matching or complementary to Yy1, we considered in vivo DNA binding sites of YY2 in trophoblast stem (TS) cells. RESULTS: We report the presence of YY2 protein in mouse-derived embryonic stem (ES) and TS cell lines. Following up on our previous report on ERV binding by YY2 in TS cells, we investigated the tissue-specificity of REX1 and YY2 binding and confirm binding to RE/ERV targets in both ES cells and TS cells. Because of the higher levels of expression, we chose TS cells to understand the role of Yy2 in gene and chromatin regulation. We used in vivo YY2 association as a measure to identify potential target genes. Sequencing of chromatin obtained in chromatin-immunoprecipitation (ChIP) assays carried out with αYY2 serum allowed us to identify a limited number of chromatin targets for YY2. Some putative binding sites were validated in regular ChIP assays and gene expression of genes nearby was altered in the absence of Yy2. CONCLUSIONS: YY2 binding to ERVs is not confined to TS cells. In vivo binding sites share the presence of a consensus binding motif. Selected sites were uniquely bound by YY2 as opposed to YY1, suggesting that YY2 exerts unique contributions to gene regulation. YY2 binding was not generally associated with gene promoters. However, several YY2 binding sites are linked to long noncoding RNA (lncRNA) genes and we show that the expression levels of a few of those are Yy2-dependent.

Tyrosine Hydroxylation in Betalain Pigment Biosynthesis Is Performed by Cytochrome P450 Enzymes in Beets (Beta vulgaris).

Yellow and red-violet betalain plant pigments are restricted to several families in the order Caryophyllales, where betacyanins play analogous biological roles to anthocyanins. The initial step in betalain biosynthesis is the hydroxylation of tyrosine to form L-DOPA. Using gene expression experiments in beets, yeast, and Arabidopsis, along with HPLC/MS analysis, the present study shows that two novel cytochrome P450 (CYP450) enzymes, CYP76AD6 and CYP76AD5, and the previously described CYP76AD1 can perform this initial step. Co-expressing these CYP450s with DOPA 4,5-dioxygenase in yeast, and overexpression of these CYP450s in yellow beets show that CYP76AD1 efficiently uses L-DOPA leading to red betacyanins while CYP76AD6 and CYP76AD5 lack this activity. Furthermore, CYP76AD1 can complement yellow beetroots to red while CYP76AD6 and CYP76AD5 cannot. Therefore CYP76AD1 uniquely performs the beet R locus function and beets appear to be genetically redundant for tyrosine hydroxylation. These new functional data and ancestral character state reconstructions indicate that tyrosine hydroxylation alone was the most likely ancestral function of the CYP76AD alpha and beta groups and the ability to convert L-DOPA to cyclo-DOPA evolved later in the alpha group.

Prediction of neddylation sites from protein sequences and sequence-derived properties.

BACKGROUND: Neddylation is a reversible post-translational modification that plays a vital role in maintaining cellular machinery. It is shown to affect localization, binding partners and structure of target proteins. Disruption of protein neddylation was observed in various diseases such as Alzheimer's and cancer. Therefore, understanding the neddylation mechanism and determining neddylation targets possibly bears a huge importance in further understanding the cellular processes. This study is the first attempt to predict neddylated sites from protein sequences by using several sequence and sequence-based structural features. RESULTS: We have developed a neddylation site prediction method using a support vector machine based on various sequence properties, position-specific scoring matrices, and disorder. Using 21 amino acid long lysine-centred windows, our model was able to predict neddylation sites successfully, with an average 5-fold stratified cross validation performance of 0.91, 0.91, 0.75, 0.44, 0.95 for accuracy, specificity, sensitivity, Matthew's correlation coefficient and area under curve, respectively. Independent test set results validated the robustness of reported new method. Additionally, we observed that neddylation sites are commonly flexible and there is a significant positively charged amino acid presence in neddylation sites. CONCLUSIONS: In this study, a neddylation site prediction method was developed for the first time in literature. Common characteristics of neddylation sites and their discriminative properties were explored for further in silico studies on neddylation. Lastly, up-to-date neddylation dataset was provided for researchers working on post-translational modifications in the accompanying supplementary material of this article.

TargetFreeze: Identifying Antifreeze Proteins via a Combination of Weights using Sequence Evolutionary Information and Pseudo Amino Acid Composition.

Antifreeze proteins (AFPs) are indispensable for living organisms to survive in an extremely cold environment and have a variety of potential biotechnological applications. The accurate prediction of antifreeze proteins has become an important issue and is urgently needed. Although considerable progress has been made, AFP prediction is still a challenging problem due to the diversity of species. In this study, we proposed a new sequence-based AFP predictor, called TargetFreeze. TargetFreeze utilizes an enhanced feature representation method that weightedly combines multiple protein features and takes the powerful support vector machine as the prediction engine. Computer experiments on benchmark datasets demonstrate the superiority of the proposed TargetFreeze over most recently released AFP predictors. We also implemented a user-friendly web server, which is openly accessible for academic use and is available at http://csbio.njust.edu.cn/bioinf/TargetFreeze. TargetFreeze supplements existing AFP predictors and will have potential applications in AFP-related biotechnology fields.

PredHydroxy: computational prediction of protein hydroxylation site locations based on the primary structure.

Compared to well-known and extensively studied protein phosphorylation, protein hydroxylation attracts much less attention and the molecular mechanism of the hydroxylation is still incompletely understood. And yet annotation of hydroxylation in proteomes is a first-critical step toward decoding protein function and understanding their physiological roles that have been implicated in the pathological processes and providing useful information for the drug designs of various diseases related with hydroxylation. In this work, we present a novel method called PredHydroxy to automate the prediction of the proline and lysine hydroxylation sites based on position weight amino acids composition, 8 high-quality amino acid indices and support vector machines. The PredHydroxy achieved a promising performance with an area under the receiver operating characteristic curve (AUC) of 82.72% and a Matthew's correlation coefficient (MCC) of 69.03% for hydroxyproline as well as an AUC of 87.41% and a MCC of 66.68% for hydroxylysine in jackknife cross-validation. The results obtained from both the cross validation and independent tests suggest that the PredHydroxy might be a powerful and complementary tool for further experimental investigation of protein hydroxylation. Feature analyses demonstrate that hydroxylation and non-hydroxylation have distinct location-specific differences; alpha and turn propensity is of importance for the hydroxylation of proline and lysine residues. A user-friendly server is freely available on the web at: .

Genome-wide characterization and comparative analysis of R2R3-MYB transcription factors shows the complexity of MYB-associated regulatory networks in Salvia miltiorrhiza.

BACKGROUND: MYB is the largest plant transcription factor gene family playing vital roles in plant growth and development. However, it has not been systematically studied in Salvia miltiorrhiza, an economically important medicinal plant. RESULTS: Here we report the genome-wide identification and characterization of 110 R2R3-MYBs, the largest subfamily of MYBs in S. miltiorrhiza. The MYB domain and other motifs of SmMYBs are largely conserved with Arabidopsis AtMYBs, whereas the divergence of SmMYBs and AtMYBs also exists, suggesting the conservation and diversity of plant MYBs. SmMYBs and AtMYBs may be classified into 37 subgroups, of which 31 include proteins from S. miltiorrhiza and Arabidopsis, whereas 6 are specific to a species, indicating that the majority of MYBs play conserved roles, while others may exhibit species-specialized functions. SmMYBs are differentially expressed in various tissues of S. miltiorrhiza. The expression profiles are largely consistent with known functions of their Arabidopsis counterparts. The expression of a subset of SmMYBs is regulated by microRNAs, such as miR159, miR319, miR828 and miR858. Based on functional conservation of MYBs in a subgroup, SmMYBs potentially involved in the biosynthesis of bioactive compounds were identified. CONCLUSIONS: A total of 110 R2R3-MYBs were identified and analyzed. The results suggest the complexity of MYB-mediated regulatory networks in S. miltiorrhiza and provide a foundation for understanding the regulatory mechanism of SmMYBs.

HCFC1 is a common component of active human CpG-island promoters and coincides with ZNF143, THAP11, YY1, and GABP transcription factor occupancy.

In human transcriptional regulation, DNA-sequence-specific factors can associate with intermediaries that orchestrate interactions with a diverse set of chromatin-modifying enzymes. One such intermediary is HCFC1 (also known as HCF-1). HCFC1, first identified in herpes simplex virus transcription, has a poorly defined role in cellular transcriptional regulation. We show here that, in HeLa cells, HCFC1 is observed bound to 5400 generally active CpG-island promoters. Examination of the DNA sequences underlying the HCFC1-binding sites revealed three sequence motifs associated with the binding of (1) ZNF143 and THAP11 (also known as Ronin), (2) GABP, and (3) YY1 sequence-specific transcription factors. Subsequent analysis revealed colocalization of HCFC1 with these four transcription factors at ∼90% of the 5400 HCFC1-bound promoters. These studies suggest that a relatively small number of transcription factors play a major role in HeLa-cell transcriptional regulation in association with HCFC1.

A method to distinguish between lysine acetylation and lysine methylation from protein sequences.

Lysine acetylation and methylation are two major post-translational modifications of lysine residues. They play vital roles in both biological and pathological processes. Specific lysine residues in H3 histone protein tails appear to be targeted for either acetylation or methylation. Hence it is very challenging to distinguish between acetylated and methylated lysine residues using computational methods. This work presents a method that incorporates protein sequence information, secondary structure and amino acid properties to differentiate acetyl-lysine from methyl-lysine. We apply an encoding scheme based on grouped weight and position weight amino acid composition to extract sequence information and physicochemical properties around lysine sites. The proposed method achieves an accuracy of 93.3% using a jackknife test. Feature analysis demonstrates that the prediction model with multiple features can take full advantage of the supplementary information from different features to improve classification performance and prediction robustness. Analysis of the characteristics of lysine residues which can be either methylated or acetylated shows that they are more similar to methyl-lysine than to acetyl-lysine.

Computational protein design: validation and possible relevance as a tool for homology searching and fold recognition.

BACKGROUND: Protein fold recognition usually relies on a statistical model of each fold; each model is constructed from an ensemble of natural sequences belonging to that fold. A complementary strategy may be to employ sequence ensembles produced by computational protein design. Designed sequences can be more diverse than natural sequences, possibly avoiding some limitations of experimental databases. METHODOLOGY/PRINCIPAL FINDINGS: WE EXPLORE THIS STRATEGY FOR FOUR SCOP FAMILIES: Small Kunitz-type inhibitors (SKIs), Interleukin-8 chemokines, PDZ domains, and large Caspase catalytic subunits, represented by 43 structures. An automated procedure is used to redesign the 43 proteins. We use the experimental backbones as fixed templates in the folded state and a molecular mechanics model to compute the interaction energies between sidechain and backbone groups. Calculations are done with the Proteins@Home volunteer computing platform. A heuristic algorithm is used to scan the sequence and conformational space, yielding 200,000-300,000 sequences per backbone template. The results confirm and generalize our earlier study of SH2 and SH3 domains. The designed sequences ressemble moderately-distant, natural homologues of the initial templates; e.g., the SUPERFAMILY, profile Hidden-Markov Model library recognizes 85% of the low-energy sequences as native-like. Conversely, Position Specific Scoring Matrices derived from the sequences can be used to detect natural homologues within the SwissProt database: 60% of known PDZ domains are detected and around 90% of known SKIs and chemokines. Energy components and inter-residue correlations are analyzed and ways to improve the method are discussed. CONCLUSIONS/SIGNIFICANCE: For some families, designed sequences can be a useful complement to experimental ones for homologue searching. However, improved tools are needed to extract more information from the designed profiles before the method can be of general use.