Connectivity independent protein-structure alignment: a hierarchical approach

Background  

Protein-structure alignment is a fundamental tool to study protein function, evolution and model building. In the last decade several methods for structure alignment were introduced, but most of them ignore that structurally similar proteins can share the same spatial arrangement of secondary structure elements (SSE) but differ in the underlying polypeptide chain connectivity (non-sequential SSE connectivity).     

SAMMate: a GUI tool for processing short read alignments in SAM/BAM format

Background  

Next Generation Sequencing (NGS) technology generates tens of millions of short reads for each DNA/RNA sample. A key step in NGS data analysis is the short read alignment of the generated sequences to a reference genome. Although storing alignment information in the Sequence Alignment/Map (SAM) or Binary SAM (BAM) format is now standard, biomedical researchers still have difficulty accessing this information.     

Grammar-based distance in progressive multiple sequence alignment

Background  

We propose a multiple sequence alignment (MSA) algorithm and compare the alignment-quality and execution-time of the proposed algorithm with that of existing algorithms. The proposed progressive alignment algorithm uses a grammar-based distance metric to determine the order in which biological sequences are to be pairwise aligned. The progressive alignment occurs via pairwise aligning new sequences with an ensemble of the sequences previously aligned.     

Improvement in accuracy of multiple sequence alignment using novel group-to-group sequence alignment algorithm with piecewise linear gap cost

Background  

Multiple sequence alignment (MSA) is a useful tool in bioinformatics. Although many MSA algorithms have been developed, there is still room for improvement in accuracy and speed. In the alignment of a family of protein sequences, global MSA algorithms perform better than local ones in many cases, while local ones perform better than global ones when some sequences have long insertions or deletions (indels) relative to others. Many recent leading MSA algorithms have incorporated pairwise alignment information obtained from a mixture of sources into their scoring system to improve accuracy of alignment containing long indels.     

Ancestral sequence alignment under optimal conditions

Background  

Multiple genome alignment is an important problem in bioinformatics. An important subproblem used by many multiple alignment approaches is that of aligning two multiple alignments. Many popular alignment algorithms for DNA use the sum-of-pairs heuristic, where the score of a multiple alignment is the sum of its induced pairwise alignment scores. However, the biological meaning of the sum-of-pairs of pairs heuristic is not obvious. Additionally, many algorithms based on the sum-of-pairs heuristic are complicated and slow, compared to pairwise alignment algorithms.     

Automatic detection of anchor points for multiple sequence alignment

Background  

Determining beforehand specific positions to align (anchor points) has proved valuable for the accuracy of automated multiple sequence alignment (MSA) software. This feature can be used manually to include biological expertise, or automatically, usually by pairwise similarity searches. Multiple local similarities are be expected to be more adequate, as more biologically relevant. However, even good multiple local similarities can prove incompatible with the ordering of an alignment.     

Improved accuracy of multiple ncRNA alignment by incorporating structural information into a MAFFT-based framework

Background  

Structural alignment of RNAs is becoming important, since the discovery of functional non-coding RNAs (ncRNAs). Recent studies, mainly based on various approximations of the Sankoff algorithm, have resulted in considerable improvement in the accuracy of pairwise structural alignment. In contrast, for the cases with more than two sequences, the practical merit of structural alignment remains unclear as compared to traditional sequence-based methods, although the importance of multiple structural alignment is widely recognized.     

MaxAlign: maximizing usable data in an alignment

Background  

The presence of gaps in an alignment of nucleotide or protein sequences is often an inconvenience for bioinformatical studies. In phylogenetic and other analyses, for instance, gapped columns are often discarded entirely from the alignment.     

Improved alignment quality by combining evolutionary information, predicted secondary structure and self-organizing maps

Background  

Protein sequence alignment is one of the basic tools in bioinformatics. Correct alignments are required for a range of tasks including the derivation of phylogenetic trees and protein structure prediction. Numerous studies have shown that the incorporation of predicted secondary structure information into alignment algorithms improves their performance. Secondary structure predictors have to be trained on a set of somewhat arbitrarily defined states (e.g. helix, strand, coil), and it has been shown that the choice of these states has some effect on alignment quality. However, it is not unlikely that prediction of other structural features also could provide an improvement. In this study we use an unsupervised clustering method, the self-organizing map, to assign sequence profile windows to "structural states" and assess their use in sequence alignment.     

Noisy: Identification of problematic columns in multiple sequence alignments

Motivation  

Sequence-based methods for phylogenetic reconstruction from (nucleic acid) sequence data are notoriously plagued by two effects: homoplasies and alignment errors. Large evolutionary distances imply a large number of homoplastic sites. As most protein-coding genes show dramatic variations in substitution rates that are not uncorrelated across the sequence, this often leads to a patchwork pattern of (i) phylogenetically informative and (ii) effectively randomized regions. In highly variable regions, furthermore, alignment errors accumulate resulting in sometimes misleading signals in phylogenetic reconstruction.     

MTRAP: Pairwise sequence alignment algorithm by a new measure based on transition probability between two consecutive pairs of residues

Background  

Sequence alignment is one of the most important techniques to analyze biological systems. It is also true that the alignment is not complete and we have to develop it to look for more accurate method. In particular, an alignment for homologous sequences with low sequence similarity is not in satisfactory level. Usual methods for aligning protein sequences in recent years use a measure empirically determined. As an example, a measure is usually defined by a combination of two quantities (1) and (2) below: (1) the sum of substitutions between two residue segments, (2) the sum of gap penalties in insertion/deletion region. Such a measure is determined on the assumption that there is no an intersite correlation on the sequences. In this paper, we improve the alignment by taking the correlation of consecutive residues.     

Island method for estimating the statistical significance of profile-profile alignment scores

Background  

In the last decade, a significant improvement in detecting remote similarity between protein sequences has been made by utilizing alignment profiles in place of amino-acid strings. Unfortunately, no analytical theory is available for estimating the significance of a gapped alignment of two profiles. Many experiments suggest that the distribution of local profile-profile alignment scores is of the Gumbel form. However, estimating distribution parameters by random simulations turns out to be computationally very expensive.     

Detection of Helicobacter pylori in stool samples of young children using real‐time polymerase chain reaction

Background

The aims of this study were to develop and validate a multiplex real‐time polymerase chain reaction (q‐PCR) assay of Helicobacter pylori in stool samples of healthy children. Additionally, we determined the prevalence of clarithromycin resistance and cagA gene in H. pylori‐positive samples.

Materials and methods

Archived stool samples from 188 children aged 6‐9 years and 272 samples of 92 infants aged 2‐18 months were tested for H. pylori antigens using enzyme immunoassay (EIA). A multiplex q‐PCR assay was designed to detect H. pylori 16S rRNA and urease and the human RNase P gene as an internal control. Kappa coefficient was calculated to assess the agreement between q‐PCR and EIA.

Results

Laboratory validation of the q‐PCR assay using quantitated H. pylori ATCC 43504 extracted DNA showed S‐shaped amplification curves for all genes; the limit of detection was 1 CFU/reaction. No cross‐reactivity with other bacterial pathogens was noted. Applying the multiplex q‐PCR to DNA extracted from fecal samples showed clear amplification curves for urease gene, but not for 16S rRNA. The prevalence of H. pylori infection was 50% (95% CI 43%‐57%) by q‐PCR (urease cycle threshold <44) vs 59% (95% CI 52%‐66%) by EIA. Kappa coefficient was .80 (P < .001) and .44 (P < .001) for children aged 6‐9 years and 2‐18 months, respectively. Sixteen samples were positive for cagA and three were positive for clarithromycin resistance mutation (A2143G) as confirmed by sequencing.

Conclusions

The developed q‐PCR can be used as a cotechnique to enhance the accuracy of H. pylori detection in epidemiological studies and in clinical settings.     

MISHIMA - a new method for high speed multiple alignment of nucleotide sequences of bacterial genome scale data

Background  

Large nucleotide sequence datasets are becoming increasingly common objects of comparison. Complete bacterial genomes are reported almost everyday. This creates challenges for developing new multiple sequence alignment methods. Conventional multiple alignment methods are based on pairwise alignment and/or progressive alignment techniques. These approaches have performance problems when the number of sequences is large and when dealing with genome scale sequences.     

Incorporating indel information into phylogeny estimation for rapidly emerging pathogens

Background  

Phylogenies of rapidly evolving pathogens can be difficult to resolve because of the small number of substitutions that accumulate in the short times since divergence. To improve resolution of such phylogenies we propose using insertion and deletion (indel) information in addition to substitution information. We accomplish this through joint estimation of alignment and phylogeny in a Bayesian framework, drawing inference using Markov chain Monte Carlo. Joint estimation of alignment and phylogeny sidesteps biases that stem from conditioning on a single alignment by taking into account the ensemble of near-optimal alignments.     

Genetic analysis of HIV-1 subtypes in Nairobi, Kenya

Background

Genetic analysis of a viral infection helps in following its spread in a given population, in tracking the routes of infection and, where applicable, in vaccine design. Additionally, sequence analysis of the viral genome provides information about patterns of genetic divergence that may have occurred during viral evolution.

Objective

In this study we have analyzed the subtypes of Human Immunodeficiency Virus -1 (HIV-1) circulating in a diverse sample population of Nairobi, Kenya.

Methodology

69 blood samples were collected from a diverse subject population attending the Aga Khan University Hospital in Nairobi, Kenya. Total DNA was extracted from peripheral blood mononuclear cells (PBMCs), and used in a Polymerase Chain Reaction (PCR) to amplify the HIV gag gene. The PCR amplimers were partially sequenced, and alignment and phylogenetic analysis of these sequences was performed using the Los Alamos HIV Database.

Results

Blood samples from 69 HIV-1 infected subjects from varying ethnic backgrounds were analyzed. Sequence alignment and phylogenetic analysis showed 39 isolates to be subtype A, 13 subtype D, 7 subtype C, 3 subtype AD and CRF01_AE, 2 subtype G and 1 subtype AC and 1 AG. Deeper phylogenetic analysis revealed HIV subtype A sequences to be highly divergent as compared to subtypes D and C.

Conclusion

Our analysis indicates that HIV-1 subtypes in the Nairobi province of Kenya are dominated by a genetically diverse clade A. Additionally, the prevalence of highly divergent, complex subtypes, intersubtypes, and the recombinant forms indicates viral mixing in Kenyan population, possibly as a result of dual infections.     

Long‐range quantitative PCR for determining inactivation of adenovirus 2 by ultraviolet light

Aims

An extra‐long‐range quantitative PCR (LR‐qPCR) method was developed for estimating genome damage to adenovirus 2 caused by UV irradiation. The objective was to use LR‐qPCR as a rapid method to determine adenovirus UV inactivation.

Methods

The LR‐qPCR consisted of two steps: a long‐range PCR (up to 10 kb fragment) and a real‐time, quantitative (q) PCR for quantifying the products of the first PCR. We evaluated LR‐qPCR with adenovirus irradiated with medium‐pressure (MP, polychromatic emission) and low‐pressure (LP, 254 nm) mercury vapour lamps and compared results with cell culture infectivity.

Results

Using LR‐qPCR, a fragment of 6 kb estimated DNA damage in a linear relationship to doses between 0 and 20 mJ cm^?2, and a 1‐kb fragment related linearly to doses between 20 and 100 mJ cm^?2. The LR‐qPCR results for the 6‐kb fragment were similar to infectivity assays results for adenovirus exposed to MP UV. For adenovirus irradiated with LP lamps, LR‐qPCR results for the shorter fragment size (1 kb) were similar to reduction in viral infectivity. No difference was observed between 10 and 6 kb LR‐qPCR results.

Conclusion

The LR‐qPCR can be used as a tool for estimating DNA damage caused by UV in adenovirus. The LR‐qPCR results were related to reduction in viral infectivity.

Significance and Impact of the Study

The use of LR‐qPCR to determine DNA damage and estimate inactivation of adenovirus 2 from UV disinfection allows for same‐day results compared with >7 days required for cell culture. This accelerates adenovirus inactivation results for the water industry where adenovirus is used as a representative virus for crediting UV systems. This PCR approach provides a framework that can be used for other viral viability assays using the inhibition of amplification of viral nucleic acid after pretreatments, such as propidium monoazide, and for cellular biology studies of DNA damage.     

GASH: An improved algorithm for maximizing the number of equivalent residues between two protein structures

Background  

We introduce GASH, a new, publicly accessible program for structural alignment and superposition. Alignments are scored by the Number of Equivalent Residues (NER), a quantitative measure of structural similarity that can be applied to any structural alignment method. Multiple alignments are optimized by conjugate gradient maximization of the NER score within the genetic algorithm framework. Initial alignments are generated by the program Local ASH, and can be supplemented by alignments from any other program.     

The meaning of alignment: lessons from structural diversity

Background  

Protein structural alignment provides a fundamental basis for deriving principles of functional and evolutionary relationships. It is routinely used for structural classification and functional characterization of proteins and for the construction of sequence alignment benchmarks. However, the available techniques do not fully consider the implications of protein structural diversity and typically generate a single alignment between sequences.     

<Emphasis Type="Italic">H2r</Emphasis>: Identification of evolutionary important residues by means of an entropy based analysis of multiple sequence alignments

Background  

A multiple sequence alignment (MSA) generated for a protein can be used to characterise residues by means of a statistical analysis of single columns. In addition to the examination of individual positions, the investigation of co-variation of amino acid frequencies offers insights into function and evolution of the protein and residues.