Pse-in-One 2.0: An Improved Package of Web Servers for Generating Various Modes of Pseudo Components of DNA, RNA, and Protein Sequences

Pse-in-One 2.0 is a package of web-servers evolved from Pse-in-One (Liu, B., Liu, F., Wang, X., Chen, J. Fang, L. & Chou, K.C. Nucleic Acids Research, 2015, 43:W65-W71). In order to make it more flexible and comprehensive as suggested by many users, the updated package has incorporated 23 new pseudo component modes as well as a series of new feature analysis approaches. It is available at http://bioinformatics.hitsz.edu.cn/Pse-in-One2.0/. Moreover, to maximize the convenience of users, provided is also the stand-alone version called “Pse-in-One-Analysis”, by which users can significantly speed up the analysis of massive sequences.

Proteins:From sequence to structure

Protein sequences as special heterogeneous sequences are rare in the amino acid sequence space. The specific sequen- tial order of amino acids of a protein is essential to its 3D structure. On the whole, the correlation between sequence and structure of a protein is not so strong. How well would a protein sequence contain its structural information？ How does a sequence determine its native structure？ Keeping the globular proteins in mind, we discuss several problems from sequence to structure.

Chaos game representation walk model for the protein sequences

A new chaos game representation of protein sequences based on the detailed hydrophobic-hydrophilic （HP） model has been proposed by Yu et al （Physica A 337（2004） 171）. A CGR-walk model is proposed based on the new CGR coordinates for the protein sequences from complete genomes in the present paper. The new CCR coordinates based on the detailed HP model are converted into a time series, and a long-memory ARFIMA（p, d, q） model is introduced into the protein sequence analysis. This model is applied to simulating real CCR-walk sequence data of twelve protein sequences. Remarkably long-range correlations are uncovered in the data and the results obtained from these models are reasonably consistent with those available from the ARFIMA（p, d, q） model.

The structural analysis of protein sequences based on the quasi-amino acids code

Proteomics is the study of proteins and their interactions in a cell. With the successful completion of the Human Cenome Project, it comes the postgenome era when the proteomics technology is emerging. This paper studies protein molecule from the algebraic point of view. The algebraic system （∑, ＋, ＊） is introduced, where ∑ is the set of 64 codons. According to the characteristics of （∑, ＋, ＊）, a novel quasi-amino acids code classification method is introduced and the corresponding algebraic operation table over the set ZU of the 16 kinds of quasi-amino acids is established. The internal relation is revealed about quasi-amino acids. The results show that there exist some very close correlations between the properties of the quasi-amino acids and the codon. All these correlation relationships may play an important part in establishing the logic relationship between codons and the quasi-amino acids during the course of life origination. According to Ma F et al （2003 J. Anhui Agricultural University 30 439）, the corresponding relation and the excellent properties about amino acids code are very difficult to observe. The present paper shows that （ZU, ＋,×） is a field. Furthermore, the operational results display that the eodon tga has different property from other stop codons. In fact, in the mitochondrion from human and ox genomic codon, tga is just tryptophane, is not the stop codon like in other genetic code, it is the case of the Chen W C et al （2002 Acta Biophysiea Siniea 18（1） 87）. The present theory avoids some inexplicable events of the 20 kinds of amino acids code, in other words it solves the problem of ＇the 64 codon assignments of mRNA to amino acids is probably completely wrong＇ proposed by Yang （2006 Progress in Modern Biomedicine 6 3）.

Multiple Sequence Alignment of the M Protein in SARS-Associated and Other Known Coronaviruses

In this paper, we report a multiple sequence alignment result on the basis of 10 amino acid sequences of the M protein, which come from different coronaviruses (4 SARS associated and 6 others known). The alignment model was based on the profile HMM (Hidden Markov Model), and the model training was implemented through the SAHMM (Self Adapting Hidden Markov Model) software developed by the authors.

Special AT-rich sequence-binding protein 1 promotes cell growth and metastasis in colorectal cancer

AIM: To evaluate the expression of special AT-rich sequence-binding protein 1 (SATB1 ) gene in colorectal cancer and its role in colorectal cancer cell proliferation and invasion.METHODS: Immunohistochemistry was used to detect the protein expression of SATB1 in 30 colorectal cancer (CRC) tissue samples and pair-matched adjacent nontumor samples. Cell growth was investigated after enhancing expression of SATB1. Wound-healing assay and Transwell assay were used to investigate the impact of SATB1 on migratory and invasive abilities of SW480 cells in vitro . Nude mice that received subcutaneous implantation or lateral tail vein were used to study the effects of SATB1 on tumor growth or metastasis in vivo . RESULTS: SATB1 was over-expressed in CRC tissues and CRC cell lines. SATB1 promotes cell proliferation and cell cycle progression in CRC SW480 cells. SATB1 over-expression could promote cell growth in vivo . In addition, SATB1 could significantly raise the ability of cell migration and invasion in vitro and promote the ability of tumor metastasis in vivo . SATB1 could up-regulate matrix metalloproteases 2, 9, cyclin D1 and vimentin, meanwhile SATB1 could down-regulate E-cadherin in CRC. CONCLUSION: SATB1 acts as a potential growth and metastasis promoter in CRC. SATB1 may be useful as a therapeutic target for CRC.

Special AT-rich sequence-binding protein 2 acts as a negative regulator of stemness in colorectal cancer cells

AIM To find the mechanisms by which special AT-rich sequence-binding protein 2(SATB2) influences colorectal cancer(CRC) metastasis.METHODS Cell growth assay, colony-forming assay, cell adhesion assay and cell migration assay were used to evaluate the biological characteristics of CRC cells with gain or loss of SATB2. Sphere formation assay was used to detect the self-renewal ability of CRC cells. The m RNA expression of stem cell markers in CRC cells with upregulated or downregulated SATB2 expression was detected by quantitative real-time polymerase chain reaction. Chromatin immunoprecipitation(Ch IP) was used to verify the binding loci of SATB2 on genomic sequences of stem cell markers. The Cancer Genome Atlas(TCGA) database and our clinical samples wereanalyzed to find the correlation between SATB2 and some key stem cell markers.RESULTS Downregulation of SATB2 led to an aggressive phenotype in SW480 and DLD-1 cells, which was characterized by increased migration and invasion abilities. Overexpression of SATB2 suppressed the migration and invasion abilities in SW480 and SW620 cells. Using sequential sphere formation assay to detect the selfrenewal abilities of CRC cells, we found more secondary sphere formation but not primary sphere formation in SW480 and DLD-1 cells after SATB2 expression was knocked down. Moreover, most markers for stem cells such as CD133, CD44, AXIN2, MEIS2 and NANOG were increased in cells with SATB2 knockdown and decreased in cells with SATB2 overexpression. Ch IP assay showed that SATB2 bound to regulatory elements of CD133, CD44, MEIS2 and AXIN2 genes. Using TCGA database and our clinical samples, we found that SATB2 was correlated with some key stem cell markers including CD44 and CD24 in clinical tissues of CRC patients.CONCLUSION SATB2 can directly bind to the regulatory elements in the genetic loci of several stem cell markers and consequently inhibit the progression of CRC by negatively regulating stemness of CRC cells.

On the Angular Distribution of the Representative Points of Bases of Human Protein Coding Sequences

A novel diagrammtic method is proposed to show the angular distribution of bases of human protein sequences. Using this method, the distribution sphere[1-4] is divided into four regions with same volume. The picture is clearer and more intuitive than that in [1] .A rule on the angular distribution of the representative points of bases of protein sequences is given. Besides, in 300 representative pointS of human protein sequence samples we find that there are three (not only one) points outside the sphere.

Cloning and Sequence Analysis of Y-box Binding Protein Gene in Min Pig

In order to study the gene sequence of Min pig Y-box binding protein （YB-1） gene, the complete coding sequence of Min pig YB-1 gene was cloned by RT-PCR, the sequence features were analyzed by some software and online website. The results showed that the complete CDS of Min pig Y-box was found to be 975 bp long, encoding 324 amino acids. It contained a conserved cold shock domain and several phosphorylation sites, but had no transmembrane domains, and was consistent with a protein found in the cytoplasm. Min pig YB-1 nucleotides shared high similarity （61.37%- 97.66%） with other mammals.

Improving Protein Sequence Classification Performance Using Adjacent and Overlapped Segments on Existing Protein Descriptors

In protein sequence classification research, it is popular to convert a variable length sequence of protein into a fixed length numerical vector by using various descriptors, for instance, composition of k-mer composition. Such position-independent descriptors are useful since they are applicable to any length of sequence;however, positional information of subsequence is discarded even though it might have high contribution to classification performance. To solve this problem, we divided the original sequence into some segments, and then calculated the numerical features for them. It enables us to partially introduce positional information (for instance, compositions of serine in anterior and posterior segments of a sequence). Through comprehensive experiments on the number of segments and length of overlapping region, we found our classification approach with sequence segmentation and feature selection is effective to improve the performance. We evaluated our approach on three protein classification problems and achieved significant improvement in all cases which have a dataset with sufficient amino acid in each sequence. This result has shown the great potential of using additional segments in protein sequence classification to solve other sequence problems in bioinformatics.

Cloning and Sequence Analysis of the 28.5ku Movement Protein of Frangipani Mosaic Virus (FMV)

Based on conserved regions among genomic RNA of tobamoviruses, a pair of primers spanning the sequence encoding the movement protein were synthesized. A cDNA fragment of 1700bp was thus amplified by RT-PCR(reverse transcription-polymerase chain reaction). The fragment was cloned into pGEM-T easy vector and sequenced. DNA sequence analysis showed that the fragment contained a region of 768 nucleotides encoding protein of 256 amino acid of frangipani mosaic virus (FMV) and also partial sequence corresponding to 180ku and 17. 5ku protein.

Cloning and Sequence Analysis of Carbonic Anhydrase-related Protein 10-like in Apis mellifera

[ Objective ] This study aimed to clone and analyze the gene sequence encoding carbonic anhydrase-related protein lO-like （ CARP X） from Apis mellif era. [Method] The cDNA sequence of CARPX gene was cloned through RT-PCR, and then analyzed with bioinformatic method. [Result] The full-length cDNA sequence of CARPX was 972 bp long and encoded 324 amino acid residues, including a signal peptide and two transmembrane domains. The predicted molecular mass was 37.1 kDa and the predicted isoeleetric point was 7.458. The CARP X from A. mellifera shared close relationship with proteins from Apisflorae, Bombtas impatiens, Bombus terrestris, Nasonia vitripennis and Acyrthosiphon pisum. The insect CARP X family may include two subfamilies. [ Conclusion] The results pro- vide basis for studying CARPs family.

Artificial Fish Swarm for Multi Protein Sequences Alignment in Bioinformatics

The alignment operation between many protein sequences or DNAsequences related to the scientific bioinformatics application is very complex.There is a trade-off in the objectives in the existing techniques of MultipleSequence Alignment (MSA). The techniques that concern with speed ignoreaccuracy, whereas techniques that concern with accuracy ignore speed. Theterm alignment means to get the similarity in different sequences with highaccuracy. The more growing number of sequences leads to a very complexand complicated problem. Because of the emergence;rapid development;anddependence on gene sequencing, sequence alignment has become importantin every biological relationship analysis process. Calculating the numberof similar amino acids is the primary method for proving that there is arelationship between two sequences. The time is a main issue in any alignmenttechnique. In this paper, a more effective MSA method for handling themassive multiple protein sequences alignment maintaining the highest accuracy with less time consumption is proposed. The proposed method dependson Artificial Fish Swarm (AFS) algorithm that can break down the mostchallenges of MSA problems. The AFS is exploited to obtain high accuracyin adequate time. ASF has been increasing popularly in various applicationssuch as artificial intelligence, computer vision, machine learning, and dataintensive application. It basically mimics the behavior of fish trying to getthe food in nature. The proposed mechanisms of AFS that is like preying,swarming, following, moving, and leaping help in increasing the accuracy andconcerning the speed by decreasing execution time. The sense organs that aidthe artificial fishes to collect information and vision from the environmenthelp in concerning the accuracy. These features of the proposed AFS make thealignment operation more efficient and are suitable especially for large-scaledata. The implementation and experimental results put the proposed AFS as afirst choice in the queue of alignment compared to the well-known algorithmsin multiple sequence alignment.

Phosphatidylinositol transfer proteins: sequence motifs in structural and evolutionary analyses

Phosphatidylinositol transfer proteins (PITP) are a family of monomeric proteins that bind and transfer phosphatidylinositol and phosphatidylcholine between membrane compartments. They are required for production of inositol and diacylglycerol second messengers, and are found in most metazoan organisms. While PITPs are known to carry out crucial cell-signaling roles in many organisms, the structure, function and evolution of the majority of family members remains unexplored;primarily because the ubiquity and diversity of the family thwarts traditional methods of global alignment. To surmount this obstacle, we instead took a novel approach, using MEME and a parsimony-based analysis to create a cladogram of conserved sequence motifs in 56 PITP family proteins from 26 species. In keeping with previous functional annotations, three clades were supported within our evolutionary analysis;two classes of soluble proteins and a class of membrane-associat- ed proteins. By, focusing on conserved regions, the analysis allowed for in depth queries regarding possible functional roles of PITP proteins in both intra- and extra- cellular signaling.

Analysis of the N Protein Sequence Variability in 13 Isolated PRRSV Strains from China

Object: To analyze porcine reproductive and respiratory syndrome virus (PRRSV) strains from 13 infection cases via the N protein gene and its encoded amino acid sequence and to provide a theoretical basis for the epidemiological study, prevention and control of porcine reproductive and respiratory syndrome (PRRS). Methods: In clinically suspected PRRSV infections, viruses were isolated by extracting viral nucleic acid and amplifying the N protein gene by RT-PCR. Then, the product was purified and sequenced to acquire the whole gene sequence of the N protein and its encoded amino acid sequence. DNASTAR software was used to analyze the homology, the genetic evolution and the derivation of the variability of amino acids of the N protein gene from 13 PRRSV strains and classical domestic and foreign strains. Results: Among the thirteen strains of PRRSV isolated from this study, ten strains had the greatest homology with the JXA1 strain (98.9% - 100%), and they belonged to the sublineage 8.7. The remaining three strains had the greatest homology with the NADC30 strain (95.4% - 97.1%), and they belonged to lineage one. The analysis of the variability of N protein amino acids showed that there were high frequency mutations in the five loci of 13 isolated strains of PRRSV as follows: 15th amino acid (10/13), 46th amino acid (11/13), 91st amino acid (10/13), 109th amino acid (10/13), and 117th amino acid (10/13). Conclusion: In recent years, sublineage 8.7 was the dominant pedigree in field PRRSV epidemic strains in China with lineage one occupying a certain proportion of the field. Four high frequency mutations existed in N protein antigen epitopes of isolated strains from the region. The nuclear localization signal (NLS) structure, specifically the 46th amino acid residue of the N protein, was mutated and genetically stable.

PFP-RFSM: Protein fold prediction by using random forests and sequence motifs

Protein tertiary structure is indispensible in revealing the biological functions of proteins. De novo perdition of protein tertiary structure is dependent on protein fold recognition. This study proposes a novel method for prediction of protein fold types which takes primary sequence as input. The proposed method, PFP-RFSM, employs a random forest classifier and a comprehensive feature representation, including both sequence and predicted structure descriptors. Particularly, we propose a method for generation of features based on sequence motifs and those features are firstly employed in protein fold prediction. PFP-RFSM and ten representative protein fold predictors are validated in a benchmark dataset consisting of 27 fold types. Experiments demonstrate that PFP-RFSM outperforms all existing protein fold predictors and improves the success rates by 2%-14%. The results suggest sequence motifs are effective in classification and analysis of protein sequences.

Role of the PEST sequence in the long-type GATA-6 DNA-binding protein expressed in human cancer cell lines

GATA-6 mRNA utilizes two Met-codons in frame as translational initiation codons in cultured mammalian cells. Deletion of the nucleotide sequence encoding the PEST sequence between the two initiation codons unusually reduced the protein molecular size on SDS-polyacrylamide gel-electrophoresis. The reduced molecular size is ascribed to the molecular property of GATA-6, since both amino-and carboxy-lterminal tags introduced into GATA-6 were detected on the gel. This PEST sequence seems to contribute to expansion of the long-type GATA-6 molecule. The long-type GATA-6 containing the PEST sequence exhibits more activation potential than that without this sequence, the latter’s activity being similar to that of the short-type GATA-6. We further demonstrated that human colon and lung cancer cell lines express both the long-type GATA-6 and the short-type GATA-6 in their nuclei.

Analysis on n-gram statistics and linguistic features of whole genome protein sequences

To obtain the statistical sequence analysis on a large number of genomic and proteomic sequences available for different organisms, the n-grams of whole genome protein sequences from 20 organisms were extracted. Their linguistic features were analyzed by two tests: Zipf power law and Shannon entropy, developed for analysis of natural languages and symbolic sequences. The natural genome proteins and the artificial genome proteins were compared with each other and some statistical features of n-grams were discovered. The results show that: the n-grams of whole genome protein sequences approximately follow the Zipf law when n is larger than 4; the Shannon n-gram entropy of natural genome proteins is lower than that of artificial proteins; a simple uni-gram model can distinguish different organisms; there exist organism-specific usages of "phrases" in protein sequences. It is suggested that further detailed analysis on n-gram of whole genome protein sequences will result in a powerful model for mapping the relationship of protein sequence, structure and function.

Molecular Cloning and Sequence Analysis of FullLength cDNA Encoding Human Bone Morphogenetic Protein—7

Objective:To clone the full-length human bane morphogenetic protein-7 (BMP-7 ) gene and analyse its sequence, to aid in investigation of its function and structure. Methods : Total RNA was isolated from Chinese fetal kidney by the acid gmnidinium thiocyanate phenol-chloroform method. Two overlapping segments of human BMP- 1 cDNA were obtained by reverse transcription (RT)-PCR. Following application, the two segments were ligated to each other and subcloned into POEM-T easy vector to form PEGM-T easy/hBMP-7 recombinant plasmid. Sanger dideoxy chain-termination method was used to sequence the cDNA. Results. There was 750 bp fragment obtained RT-PCR using #2 primer from 5' end of BMP-7 gene (PCR by using # 2 and # 1) ,and 540 bp fragment from 3' end was generated by KT-PCR using # 4 primer (PCR using # 3 and # 4). Full-length cDNA encoding BMP-7 was obtained by religation of two segments. When compared with hBMP-7 sequence in Gene bank (XM30619) ,our full-length BMP-7 cDNA has a G instead of a T at nucleotide 862. This change results in valine substituting for phenylalanine in the protein. Conclusion. This is the first time that BMP-7 cDNA was successfully cloned from Chinese fetal kidney. BMP-7 cDNA plays an important role in healing injuries of the osteo-articular system. This makes BMP-7 is an attractive target far various clinical applications.

Rationally designed synthetic peptide as versatile calibrant to improve the accuracy of protein sequence analysis using MALDI mass spectrometry

Matrix-assisted laser desorption/ionization(MALDI)mass spectrometry(MS)plays an indispensable role in analyzing protein covalent structures.The reliable identification of amino acid residues and modifications relies on the mass accuracy,which is highly dependent on calibration.However,the accuracy provided by the currently available calibrants still needs further improvement in terms of compatibility with multiple tandem MS modes or ion polarity modes,calibratable range,and minimizing suppression of and interference with analyte signals.Here aiming at developing a versatile calibrant to solve these problem,we designed a synthetic peptide format of calibrant R_x(GDP_n)_m(referred to as“Gly-Asp-Pro,GDP”)according to the chemical natures of amino acids and polypeptide fragmentation rules in tandem MS.With four types of amino acid residues selected and arranged through rational designs,a GDP peptide produces highly regulated fragments that give rise to evenly spaced signals in each tandem MS mode and is compatible with both positive and negative ion modes.In internal calibration,its regulated fragmentation pattern minimizes interference with analyte signals,and using a single peptide as the input minimizes suppression of the analyte signals.As demonstrated by analyses of proteins including monoclonal antibody and Aβ-42,these features allowed significant increase of the mass accuracy and precision,which improved sequence coverage and sequence resolution in sequence analyses(including de novo sequencing).This rational design strategy may also inspire further development of synthetic calibrants that benefit structural analysis of biomolecules.