Multi-sequence Alignment Research Articles

Cloning, expression, identification and bioinformatics analysis of Rv3265c gene from Mycobacterium tuberculosis in Escherichia coli

Objective To clone and express Rv3265c gene of Mycobacterium tuberculosis in Escherichia coli (E. coli) under optimistic conditions, obtain and identify protein expressed, analyze the structure and characteristics of the protein using bioinformatics methods for future applications. Methods Rv3265c gene from Mycobacterium tuberculosis H37Rv was amplified by polymerase chain reaction, and was cloned into the pET-30a vector after purification and recovery. The recombinant plasmid was sequenced and expressed in E. coli BL21(DE3), and then purified and identified by western blotting. The essential physical-chemical properties of the protein were predicated by bioinformatics tools, including subcellular location, secondary structure, domains, antigenic epitopes, etc. Tertiary structure of the protein based on homology modeling was established, while multi-sequence homological alignment and phylogenetic analysis were proformed. Results The recombinant protein was obtained in soluble fraction from expression system in E. coli BL21(DE3) carrying pET30- Rv3265c plasmid, and Rv3265c gene was expressed correctly. Bioinformatics analysis showed the protein contained no signal peptide and transmembrane helices, located outside of membrane. Secondary structure analysis revealed it contained α-helix, extended strand and random coil, 46.8%, 14.6%, 38.6%, respectively. Furthermore, it possessed six potential antigenic epitopes, one glycosyl transferase domain. A simple three-dimensional model of this protein was constructed by Swiss-model sever. Both sequences and structures were conservative and especial either in gene or in protein. Conclusions Rv3265c gene might be a desirable molecular target for anti-tuberculosis drug and vaccine. The purified protein from expression will be utilized to study the kinetics of L-rhamnosyltransferase and to develope an enzyme assay for screening vaccine or drug.

Development of chromosome 6D-specific markers for α-gliadin genes and their use in assessing dynamic changes at the Gli-2 loci

To develop chromosome 6D-specific point mutation (PM) markers for α-gliadin genes, 79 α-gliadin sequences cloned from Aegilops tauschii and another 40 α-gliadin genes with known chromosome locations were used in multi-sequence alignment and phylogenic analysis. Additional multiple alignment adjustments were performed manually to facilitate discovery of putative chromosome 6D-specific point mutations. A total of 85 PM primers were designed to detect 68 candidate chromosome 6D-specific point mutations. Experimental tests revealed 11 chromosome 6D-specific PM markers by using genomic DNA from homoeologous group 6 nullisomic–tetrasomic lines of Chinese Spring and putative diploid and tetraploid ancestors of hexaploid wheat as PCR templates. Detection of PM markers in one synthetic hexaploid wheat and its parental lines indicated that some α-gliadin genes were lost from Gli-2 loci during the formation of hexaploid wheat by amphidiploidization of the genomes of Triticum turgidum and Ae. tauschii. Detection of these PM markers in Ae. tauschii, T. aestivum and its four subspecies indicated that at least two genetically distinct sources of Ae. tauschii contributed germplasm to the D genome of T. aestivum.

SHV Lactamase Engineering Database: a reconciliation tool for SHV β-lactamases in public databases

BackgroundSHV β-lactamases confer resistance to a broad range of antibiotics by accumulating mutations. The number of SHV variants is steadily increasing. 117 SHV variants have been assigned in the SHV mutation table (http://www.lahey.org/Studies/). Besides, information about SHV β-lactamases can be found in the rapidly growing NCBI protein database. The SHV β-Lactamase Engineering Database (SHVED) has been developed to collect the SHV β-lactamase sequences from the NCBI protein database and the SHV mutation table. It serves as a tool for the detection and reconciliation of inconsistencies, and for the identification of new SHV variants and amino acid substitutions.DescriptionThe SHVED contains 200 protein entries with distinct sequences and 20 crystal structures. 83 protein sequences are included in the both the SHV mutation table and the NCBI protein database, while 35 and 82 protein sequences are only in the SHV mutation table and the NCBI protein database, respectively. Of these 82 sequences, 41 originate from microbial sources, and 22 of them are full-length sequences that harbour a mutation profile which has not been classified yet in the SHV mutation table. 27 protein entries from the NCBI protein database were found to have an inconsistency in SHV name identification. These inconsistencies were reconciled using information from the SHV mutation table and stored in the SHVED.The SHVED is accessible at http://www.LacED.uni-stuttgart.de/classA/SHVED/. It provides sequences, structures, and a multisequence alignment of SHV β-lactamases with the corrected annotation. Amino acid substitutions at each position are also provided. The SHVED is updated monthly and supplies all data for download.ConclusionsThe SHV β-Lactamase Engineering Database (SHVED) contains information about SHV variants with reconciled annotation. It serves as a tool for detection of inconsistencies in the NCBI protein database, helps to identify new mutations resulting in new SHV variants, and thus supports the investigation of sequence-function relationships of SHV β-lactamases.

Analyzing taxonomic classification using extensible Markov models

As next generation sequencing is rapidly adding new genomes, their correct placement in the taxonomy needs verification. However, the current methods for confirming classification of a taxon or suggesting revision for a potential misplacement relies on computationally intense multi-sequence alignment followed by an iterative adjustment of the distance matrix. Due to intra-heterogeneity issues with the 16S rRNA marker, no classifier is available for sub-genus level, which could readily suggest a classification for a novel 16S rRNA sequence. Metagenomics further complicates the issue by generating fragmented 16S rRNA sequences. This article proposes a novel alignment-free method for representing the microbial profiles using extensible Markov models (EMMs) with an extended Karlin-Altschul statistical framework similar to the classic alignment paradigm. We propose a log odds (LODs) score classifier based on Gumbel difference distribution that confirms correct classifications with statistical significance qualifications and suggests revisions where necessary. We tested our method by generating a sub-genus level classifier with which we re-evaluated classifications of 676 microbial organisms using the NCBI FTP database for the 16S rRNA. The results confirm current classification for all genera while ascertaining significance at 95%. Furthermore, this novel classifier isolates heterogeneity issues to a mere 12 strains while confirming classifications with significance qualification for the remaining 98%. The models require less memory than that needed by multi-sequence alignments and have better time complexity than the current methods. The classifier operates at sub-genus level, and thus outperforms the naive Bayes classifier of the RNA Database Project where much of the taxonomic analysis is available online. Finally, using information redundancy in model building, we show that the method applies to metagenomic fragment classification of 19 Escherichia coli strains. Source code and binaries freely available for download at http://lyle.smu.edu/IDA/EMMSA/, implemented in JAVA and supported on MS Windows.

Crystal Structure of Yeast Rpn14, a Chaperone of the 19 S Regulatory Particle of the Proteasome

The ubiquitin-proteasome pathway is a major proteolytic system in eukaryotic cells and regulates various cellular processes. The 26 S proteasome, the central enzyme of this pathway, consists of a proteolytic core particle and two 19 S regulatory particles (RPs) composed of ATPase (Rpt) and non-ATPase (Rpn) subunits. Growing evidence indicates that proteasome assembly is assisted by a variety of chaperones. In particular, it has been reported recently that Nas2, Nas6, Rpn14, and Hsm3 bind specific Rpt subunits, thereby contributing to the formation of 19 S RP. Rpn14 transiently binds to the C-terminal domain of the Rpt6 subunit (Rpt6-C) during maturation of the ATPase ring of 19 S RP. In this study, we determined the crystal structure of yeast Rpn14 at 2.0 A resolution, which revealed that this chaperone consists of a unique N-terminal domain with unknown function and a C-terminal domain assuming a canonical seven-bladed beta-propeller fold. The Rpt6-binding site on Rpn14 was predicted based on structural comparison with the complex formed between Nas6 and Rpt3-C. The top face of Rpn14 exhibits a highly acidic surface area, whereas the putative interacting surface of Rpt6-C is basic. By inspection of structural data along with genetic and biochemical data, we determined the specific residues of Rpn14 and Rpt6 for complementary charge interactions that are required for 19 S RP assembly.

Structural classification by the Lipase Engineering Database: a case study of Candida antarctica lipase A

BackgroundThe Lipase Engineering Database (LED) integrates information on sequence, structure and function of lipases, esterases and related proteins with the α/β hydrolase fold. A new superfamily for Candida antarctica lipase A (CALA) was introduced including the recently published crystal structure of CALA. Since CALA has a highly divergent sequence in comparison to other α/β hydrolases, the Lipase Engineering Database was used to classify CALA in the frame of the already established classification system. This involved the comparison of CALA to similar structures as well as sequence-based comparisons against the content of the LED.ResultsThe new release 3.0 (December 2009) of the Lipase Engineering Database contains 24783 sequence entries for 18585 proteins as well as 656 experimentally determined protein structures, including the structure of CALA. In comparison to the previous release [1] with 4322 protein and 167 structure entries this update represents a significant increase in data volume. By comparing CALA to representative structures from all superfamilies, a structure from the deacetylase superfamily was found to be most similar to the structure of CALA. While the α/β hydrolase fold is conserved in both proteins, the major difference is found in the cap region. Sequence alignments between both proteins show a sequence similarity of only 15%. A multisequence alignment of both protein families was used to create hidden Markov models for the cap region of CALA and showed that the cap region of CALA is unique among all other proteins of the α/β hydrolase fold. By specifically comparing the substrate binding pocket of CALA to other binding pockets of α/β hydrolases, the binding pocket of Candida rugosa lipase was identified as being highly similar. This similarity also applied to the lid of Candida rugosa lipase in comparison to the potential lid of CALA.ConclusionThe LED serves as a valuable tool for the systematic analysis of single proteins or protein families. The updated release 3.0 was used for the evaluation of α/β hydrolases. The HTML version of the database with new features is available at http://www.led.uni-stuttgart.de and provides sequences, structures and a set of analysis tools including phylogenetic trees and HMM profiles

PlantsUPS: a database of plants' Ubiquitin Proteasome System

BackgroundThe ubiquitin 26S/proteasome system (UPS), a serial cascade process of protein ubiquitination and degradation, is the last step for most cellular proteins. There are many genes involved in this system, but are not identified in many species. The accumulating availability of genomic sequence data is generating more demands in data management and analysis. Genomics data of plants such as Populus trichocarpa, Medicago truncatula, Glycine max and others are now publicly accessible. It is time to integrate information on classes of genes for complex protein systems such as UPS.ResultsWe developed a database of higher plants' UPS, named 'plantsUPS'. Both automated search and manual curation were performed in identifying candidate genes. Extensive annotations referring to each gene were generated, including basic gene characterization, protein features, GO (gene ontology) assignment, microarray probe set annotation and expression data, as well as cross-links among different organisms. A chromosome distribution map, multi-sequence alignment, and phylogenetic trees for each species or gene family were also created. A user-friendly web interface and regular updates make plantsUPS valuable to researchers in related fields.ConclusionThe plantsUPS enables the exploration and comparative analysis of UPS in higher plants. It now archives > 8000 genes from seven plant species distributed in 11 UPS-involved gene families. The plantsUPS is freely available now to all users at .

A molecular screening method for unisexual Ambystoma using mitochondrial DNA

The geographical range of unisexual Ambystoma overlaps with four bisexual species that also breed in spring ponds. Several of these species are of conservation concern, and both adults and larvae can be difficult to distinguish morphologically from unisexuals. Here we present a rapid molecular method for screening unisexuals, whose mtDNA is most similar to Ambystoma barbouri. A 258 bp segment of the cytochrome b gene was amplified in six Ambystoma species and exemplar unisexuals by PCR using taxon-specific primers. An internal 113 bp segment was amplified only in unisexuals and A. barbouri using Universal forward and Hybrid reverse primers. Multisequence alignment comparing the nucleotide sequence where Hybrid reverse primer anneals revealed nucleotide diversity in this region among Ambystoma species. This simple method for discriminating between unisexuals and bisexuals, excluding A. barbouri, can be applied prior to further research on these declining species.

Human influenza: a virus classification using a probabilistic neural network

PurposeThe traditional method to distinguish the serotype of influenza A virus was based on the antigen reaction of HA and NA with their antibodies. The antibody of specific subtype virus was difficult to get and the reaction was not easy to be done. To be a complementation to the traditional classification methods based on the serological reaction, aims to present a novel method for viral classification.Design/methodology/approachThe similarity values of all subtype HA genes in vector space were considered and classified using a probabilistic neural network (PNN). The PNN model was trained by the 132 viral sequences in the training set and the classification quality was examined using 28 viral sequences in the testing set.FindingsA novel technique for the serotype classification of influenza A virus isolated from human was proposed in the paper. The system achieved 100 per cent accuracy with all serotypes of human influenza A virus.Research limitations/implicationsThe time for the large‐scale calculations of the average similarity based on multisequence alignment is the main limitation.Practical implicationsThis is a supplementation to the traditional virology research.Originality/valueThe novel classification method based on the similarity of viral nucleotide sequences and the PNN model would be useful for the epidemic supervision and prevention.

Inquilinus limosusand Cystic Fibrosis

<i>Inquilinus limosus</i>and Cystic Fibrosis

PROTEUS2: a web server for comprehensive protein structure prediction and structure-based annotation

PROTEUS2 is a web server designed to support comprehensive protein structure prediction and structure-based annotation. PROTEUS2 accepts either single sequences (for directed studies) or multiple sequences (for whole proteome annotation) and predicts the secondary and, if possible, tertiary structure of the query protein(s). Unlike most other tools or servers, PROTEUS2 bundles signal peptide identification, transmembrane helix prediction, transmembrane β-strand prediction, secondary structure prediction (for soluble proteins) and homology modeling (i.e. 3D structure generation) into a single prediction pipeline. Using a combination of progressive multi-sequence alignment, structure-based mapping, hidden Markov models, multi-component neural nets and up-to-date databases of known secondary structure assignments, PROTEUS is able to achieve among the highest reported levels of predictive accuracy for signal peptides (Q2 = 94%), membrane spanning helices (Q2 = 87%) and secondary structure (Q3 score of 81.3%). PROTEUS2's homology modeling services also provide high quality 3D models that compare favorably with those generated by SWISS-MODEL and 3D JigSaw (within 0.2 Å RMSD). The average PROTEUS2 prediction takes ∼3 min per query sequence. The PROTEUS2 server along with source code for many of its modules is accessible a http://wishart.biology.ualberta.ca/proteus2.

Confidence in comparative genomics

Confidence in comparative genomics

An Algorithm for Generation of Attack Signatures Based on Sequences Alignment

This paper presents a new algorithm for generation of attack signatures based on sequence alignment. The algorithm is composed of two parts: a local alignment algorithm-GASBSLA (Generation of Attack Signatures Based on Sequence Local Alignment) and a multi-sequence alignment algorithm-TGMSA (Tri-stage Gradual Multi-Sequence Alignment). With the inspiration of sequence alignment used in Bioinformatics, GASBSLA replaces global alignment and constant weight penalty model by local alignment and affine penalty model to improve the generality of attack signatures. TGMSA presents a new pruning policy to make the algorithm more insensitive to noises in the generation of attack signatures. In this paper, GASBSLA and TGMSA are described in detail and validated by experiments.

Computation and Analysis of Genomic Multi-Sequence Alignments

Multi-sequence alignments of large genomic regions are at the core of many computational genome-annotation approaches aimed at identifying coding regions, RNA genes, regulatory regions, and other functional features. Such alignments also underlie many genome-evolution studies. Here we review recent computational advances in the area of multi-sequence alignment, focusing on methods suitable for aligning whole vertebrate genomes. We introduce the key algorithmic ideas in use today, and identify publicly available resources for computing, accessing, and visualizing genomic alignments. Finally, we describe the latest alignment-based approaches to identify and characterize various types of functional sequences. Key areas of research are identified and directions for future improvements are suggested.

Comprehensive Mutation Screening in 55 Probands with Type 1 Primary Hyperoxaluria Shows Feasibility of a Gene-Based Diagnosis

Mutations in AGXT, a locus mapped to 2q37.3, cause deficiency of liver-specific alanine:glyoxylate aminotransferase (AGT), the metabolic error in type 1 primary hyperoxaluria (PH1). Genetic analysis of 55 unrelated probands with PH1 from the Mayo Clinic Hyperoxaluria Center, to date the largest with availability of complete sequencing across the entire AGXT coding region and documented hepatic AGT deficiency, suggests that a molecular diagnosis (identification of two disease alleles) is feasible in 96% of patients. Unique to this PH1 population was the higher frequency of G170R, the most common AGXT mutation, accounting for 37% of alleles, and detection of a new 3' end deletion (Ex 11_3'UTR del). A described frameshift mutation (c.33_34insC) occurred with the next highest frequency (11%), followed by F152I and G156R (frequencies of 6.3 and 4.5%, respectively), both surpassing the frequency (2.7%) of I244T, the previously reported third most common pathogenic change. These sequencing data indicate that AGXT is even more variable than formerly believed, with 28 new variants (21 mutations and seven polymorphisms) detected, with highest frequencies on exons 1, 4, and 7. When limited to these three exons, molecular analysis sensitivity was 77%, compared with 98% for whole-gene sequencing. These are the first data in support of comprehensive AGXT analysis for the diagnosis of PH1, obviating a liver biopsy in most well-characterized patients. Also reported here is previously unavailable evidence for the pathogenic basis of all AGXT missense variants, including evolutionary conservation data in a multisequence alignment and use of a normal control population.

A new platinum complex of triazine demonstrates G1 arrest with novel biological profile in human breast cancer cell line, MDA-MB-468

A novel class of platinum(II) complexes of pyridine sulfide derivatives of triazine was synthesized, characterized, and investigated using the human breast cancer cell line, MDA-MB-468. S-30 was one of the most potent derivatives of its class (IC 50, 0.39 μM) eliciting the greatest biological response. S-30 induced arrest in the G1 phase and apoptosis (TUNEL assay) in a p53/p21 WAF1/CIP1-consistent manner. Modeling and docking experiments were performed for three known targets for cisplatin, d(GpG), d(ApG), and a protein (Cu/Zn superoxide dismutase, SOD) from bovine origin. A Blast search of bovine SOD was performed to identify analogous human protein targets resulting in about 22 human proteins. A multi-sequence alignment of those targets showed >80% sequence identity and >88% similarity. One of them is SOD1 that is differentially expressed (based on global gene expression pattern) in various forms of cancer and other diseases. SOD1 controls apoptosis via p53/BAD/BAX/BCL2 in the amyotrophic lateral sclerosis (ALS) pathway and is also involved in various other KEGG’s pathways. Results suggest that the S-30 is a potential cytotoxic agent.

Differences between pair-wise and multi-sequence alignment methods affect vertebrate genome comparisons

Producing complete and accurate alignments of multiple genomic sequences is complex and prone to errors, especially with sequences generated from highly diverged species. In this article, we show that multi-sequence (as opposed to pair-wise) alignment methods are substantially better at aligning (or 'capturing') all of the available orthologous sequence from phylogenetically diverse vertebrates (i.e. those separated by relatively long branch lengths). Maximum gains are obtained only when sequences from many species are aligned. Such multi-sequence alignments contain significant amounts of exonic and highly conserved non-exonic sequences that are not captured in pair-wise alignments, thus illustrating the importance of the alignment method used for performing comparative genome analyses.

Aligning Biological Sequences on Distributed Bus Networks: A Divisible Load Scheduling Approach

In this paper, we design a multiprocessor strategy that exploits the computational characteristics of the algorithms used for biological sequence comparison proposed in the literature. We employ divisible load theory (DLT) that is suitable for handling large scale processing on network based systems. For the first time in the domain of DLT, the problem of aligning biological sequences is attempted. The objective is to minimize the total processing time of the alignment process. In designing our strategy, DLT facilitates a clever partitioning of the entire computation process involved in such a way that the overall time consumed for aligning the sequences is a minimum. The partitioning takes into account the computation speeds of the nodes and the underlying communication network. Since this is a real-life application, the post-processing phase becomes important, and hence we consider propagating the results back in order to generate an exact alignment. We consider several cases in our analysis such as deriving closed-form solutions for the processing time for heterogeneous, homogeneous, and networks with slow links. Further, we attempt to employ a multiinstallment strategy to distribute the tasks such that a higher degree of parallelism can be achieved. For slow networks, our strategy recommends near-optimal solutions. We derive an important condition to identify such cases and propose two heuristic strategies. Also, our strategy can be extended for multisequence alignment by utilizing a clustering strategy such as the Berger-Munson algorithm proposed in the literature. Finally, we use real-life DNA samples of house mouse mitochondrion (Mus Musculus Mitochondrion, NC_001569) consisting of 16,295 residues and the DNA of human mitochondrion (Homo Sapiens Mitochondrion, NC_001807) consisting of 16,571 residues, obtainable from the GenBank, in our rigorous simulation experiments to illustrate all the theoretical findings.

Sentence Fusion for Multidocument News Summarization

A system that can produce informative summaries, highlighting common information found in many online documents, will help Web users to pinpoint information that they need without extensive reading. In this article, we introduce sentence fusion, a novel text-to-text generation technique for synthesizing common information across documents. Sentence fusion involves bottom-up local multisequence alignment to identify phrases conveying similar information and statistical generation to combine common phrases into a sentence. Sentence fusion moves the summarization field from the use of purely extractive methods to the generation of abstracts that contain sentences not found in any of the input documents and can synthesize information across sources.

A comprehensive expression analysis of the starch synthase gene family in rice (Oryza sativa L.).

To elucidate the roles of the isogenes encoding starch synthase (EC 2.4.1.21) in rice (Oryza sativa L.), a comprehensive expression analysis of the gene family was conducted. Extensive searches for starch synthase genes were done in the databases of both the whole genome and full-length cDNAs of rice, and ten genes were revealed to comprise the starch synthase gene family. Multi-sequence alignment analysis of the starch synthase proteins from rice and other plant species suggested that they were grouped into five classes, soluble starch synthase I (SSI), SSII, SSIII, SSIV and granule-bound starch synthase (GBSS). In rice, there was one gene for SSI, three for SSII and two each for SSIII, IV and GBSS. The expression pattern of the ten genes in the developing caryopsis was examined by semi-quantitative RT-PCR analysis. Based on the temporal expression patterns, the ten genes could be divided into three groups: (i) early expressers ( SSII-2, III-1, GBSSII), which are expressed in the early stage of grain filling; (ii) late expressers ( SSII-3, III-2, GBSSI), which are expressed in the mid to later stage of grain filling; and (iii) steady expressers ( SSI, II-1, IV-1, IV-2), which are expressed relatively constantly during grain filling. Within a caryopsis, the three gene groups spatially share their expression, i.e. "early expressers" in the pericarp, the "late expressers" in the endosperm" and the "steady expressers" in both tissues. In addition, this grouping was reflected in the expression pattern of various rice tissues: expression in non-endosperm, endosperm or all tissues examined. The implications in this spatio-temporal work sharing of starch synthesis isogenes are discussed.