Evaluation of the models handling heterotachy in phylogenetic inference

Background  

The evolutionary rate at a given homologous position varies across time. When sufficiently pronounced, this phenomenon – called heterotachy – may produce artefactual phylogenetic reconstructions under the commonly used models of sequence evolution. These observations have motivated the development of models that explicitly recognize heterotachy, with research directions proposed along two main axes: 1) the covarion approach, where sites switch from variable to invariable states; and 2) the mixture of branch lengths (MBL) approach, where alignment patterns are assumed to arise from one of several sets of branch lengths, under a given phylogeny.     

An enhanced RNA alignment benchmark for sequence alignment programs

Background  

The performance of alignment programs is traditionally tested on sets of protein sequences, of which a reference alignment is known. Conclusions drawn from such protein benchmarks do not necessarily hold for the RNA alignment problem, as was demonstrated in the first RNA alignment benchmark published so far. For example, the twilight zone – the similarity range where alignment quality drops drastically – starts at 60 % for RNAs in comparison to 20 % for proteins. In this study we enhance the previous benchmark.     

High quality protein sequence alignment by combining structural profile prediction and profile alignment using SABERTOOTH

Background  

Protein alignments are an essential tool for many bioinformatics analyses. While sequence alignments are accurate for proteins of high sequence similarity, they become unreliable as they approach the so-called 'twilight zone' where sequence similarity gets indistinguishable from random. For such distant pairs, structure alignment is of much better quality. Nevertheless, sequence alignment is the only choice in the majority of cases where structural data is not available. This situation demands development of methods that extend the applicability of accurate sequence alignment to distantly related proteins.     

Quantitative sequence-function relationships in proteins based on gene ontology

Background  

The relationship between divergence of amino-acid sequence and divergence of function among homologous proteins is complex. The assumption that homologs share function – the basis of transfer of annotations in databases – must therefore be regarded with caution. Here, we present a quantitative study of sequence and function divergence, based on the Gene Ontology classification of function. We determined the relationship between sequence divergence and function divergence in 6828 protein families from the PFAM database. Within families there is a broad range of sequence similarity from very closely related proteins – for instance, orthologs in different mammals – to very distantly-related proteins at the limit of reliable recognition of homology.     

DIALIGN-T: An improved algorithm for segment-based multiple sequence alignment

Background  

We present a complete re-implementation of the segment-based approach to multiple protein alignment that contains a number of improvements compared to the previous version 2.2 of DIALIGN. This previous version is superior to Needleman-Wunsch-based multi-alignment programs on locally related sequence sets. However, it is often outperformed by these methods on data sets with global but weak similarity at the primary-sequence level.     

A structural study for the optimisation of functional motifs encoded in protein sequences

Background  

A large number of PROSITE patterns select false positives and/or miss known true positives. It is possible that – at least in some cases – the weak specificity and/or sensitivity of a pattern is due to the fact that one, or maybe more, functional and/or structural key residues are not represented in the pattern. Multiple sequence alignments are commonly used to build functional sequence patterns. If residues structurally conserved in proteins sharing a function cannot be aligned in a multiple sequence alignment, they are likely to be missed in a standard pattern construction procedure.     

Islet cell antigens and autoantigen(s): Monoclonal antibodies and further characterization

A novel series of murine monoclonal antibodies to islet cells (1–45, 1–51, 1–52 and 1–39) have been generated using human insulinoma homogenate as the immunogen in order to characterize pathogenetically relevant islet cell autoantigen(s). Differentiation antigens recognized by these islet cell monoclonal antibodies displayed varied cytological distribution (pan-islet or peripheral mantle only). Monoclonal antibody 1–45 reacted with all endocrine subsets of the pancreatic islet, similar to the reactivity of islet cell autoantibody positive sera from type I diabetes subjects. Preexposure to pH2 abolished the immunoreactivity of the autoantigen; 1–45 antigen was also sensitive to low pH. Preexposure to 100° C for 1 h did not significantly alter the immunoreactivity of islet antigens recognized by ICAb positive patient sera and monoclonal antibody 1–39, thus demonstrating the extraordinary heat stability of the corresponding epitopes; those recognized by 1–45 were less heat stable. Islet cells were found to share 1–45 differentiation antigen(s)/epitope(s) with other neuroendocrine cells,viz. amerior pituitary, adrenal medulla and gut endocrine cells.     

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.     

Characterization of Tannase Protein Sequences of Bacteria and Fungi: An In Silico Study

The tannase protein sequences of 149 bacteria and 36 fungi were retrieved from NCBI database. Among them only 77 bacterial and 31 fungal tannase sequences were taken which have different amino acid compositions. These sequences were analysed for different physical and chemical properties, superfamily search, multiple sequence alignment, phylogenetic tree construction and motif finding to find out the functional motif and the evolutionary relationship among them. The superfamily search for these tannase exposed the occurrence of proline iminopeptidase-like, biotin biosynthesis protein BioH, O-acetyltransferase, carboxylesterase/thioesterase 1, carbon–carbon bond hydrolase, haloperoxidase, prolyl oligopeptidase, C-terminal domain and mycobacterial antigens families and alpha/beta hydrolase superfamily. Some bacterial and fungal sequence showed similarity with different families individually. The multiple sequence alignment of these tannase protein sequences showed conserved regions at different stretches with maximum homology from amino acid residues 389–469 and 482–523 which could be used for designing degenerate primers or probes specific for tannase producing bacterial and fungal species. Phylogenetic tree showed two different clusters; one has only bacteria and another have both fungi and bacteria showing some relationship between these different genera. Although in second cluster near about all fungal species were found together in a corner which indicates the sequence level similarity among fungal genera. The distributions of fourteen motifs analysis revealed Motif 1 with a signature amino acid sequence of 29 amino acids, i.e. GCSTGGREALKQAQRWPHDYDGIIANNPA, was uniformly observed in 83.3 % of studied tannase sequences representing its participation with the structure and enzymatic function.     

Fine-tuning structural RNA alignments in the twilight zone

Background  

A widely used method to find conserved secondary structure in RNA is to first construct a multiple sequence alignment, and then fold the alignment, optimizing a score based on thermodynamics and covariance. This method works best around 75% sequence similarity. However, in a "twilight zone" below 55% similarity, the sequence alignment tends to obscure the covariance signal used in the second phase. Therefore, while the overall shape of the consensus structure may still be found, the degree of conservation cannot be estimated reliably.     

Geminiviruses: a tale of a plasmid becoming a virus

Background  

Geminiviruses (family Geminiviridae) are small single-stranded (ss) DNA viruses infecting plants. Their virion morphology is unique in the known viral world – two incomplete T = 1 icosahedra are joined together to form twinned particles. Geminiviruses utilize a rolling-circle mode to replicate their genomes. A limited sequence similarity between the three conserved motifs of the rolling-circle replication initiation proteins (RCR Reps) of geminiviruses and plasmids of Gram-positive bacteria allowed Koonin and Ilyina to propose that geminiviruses descend from bacterial replicons.     

How reliably can we predict the reliability of protein structure predictions?

Background  

Comparative methods have been the standard techniques for in silico protein structure prediction. The prediction is based on a multiple alignment that contains both reference sequences with known structures and the sequence whose unknown structure is predicted. Intensive research has been made to improve the quality of multiple alignments, since misaligned parts of the multiple alignment yield misleading predictions. However, sometimes all methods fail to predict the correct alignment, because the evolutionary signal is too weak to find the homologous parts due to the large number of mutations that separate the sequences.     

Immunochemical characterization of polysaccharide antigens from six clinical strains of Enterococci

Background  

Enterococci have become major nosocomial pathogens due to their intrinsic and acquired resistance to a broad spectrum of antibiotics. Their increasing drug resistance prompts us to search for prominent antigens to develop vaccines against enterococci. Given the success of polysaccharide-based vaccines against various bacterial pathogens, we isolated and characterized the immunochemical properties of polysaccharide antigens from five strains of Enterococcus faecalis and one strain of vancomycin-resistant E. faecium.     

Iterative refinement of structure-based sequence alignments by Seed Extension

Background  

Accurate sequence alignment is required in many bioinformatics applications but, when sequence similarity is low, it is difficult to obtain accurate alignments based on sequence similarity alone. The accuracy improves when the structures are available, but current structure-based sequence alignment procedures still mis-align substantial numbers of residues. In order to correct such errors, we previously explored the possibility of replacing the residue-based dynamic programming algorithm in structure alignment procedures with the Seed Extension algorithm, which does not use a gap penalty. Here, we describe a new procedure called RSE (Refinement with Seed Extension) that iteratively refines a structure-based sequence alignment.     

Amino-terminal sequencing of sheep CD1 antigens and identification of a sheep CD1D gene

 The anti-CD1 monoclonal antibodies IAH-CC14 and SBU-T6 were used to immunopurify CD1 antigens from sheep thymocytes. The amino-terminal sequence of IAH-CC14 yielded 13 amino acids, and 29 amino acids were obtained from the SBU-T6 antigen. The sequence of the IAH-CC14 antigen was 100% identical to the predicted sequence of the sheep CD1B clone, SCD1B-42. The 29 amino acid sequence of the SBU-T6 antigen did not match identically with the derived amino acid sequence of any of the previously reported sheep CD1 genes but had closest similarity to the derived sequence of human CD1E. Degenerate polymerase chain reaction primers based on this sequence identified a group 2 sheep CD1 gene. The predicted amino acid sequence of this gene shows that it is not identical to the SBU-T6 peptide, indicating that a different, CD1D-like gene was cloned. Received: 22 June 1998 / Revised: 16 September 1998     

(PS)2-v2: template-based protein structure prediction server

Background  

Template selection and target-template alignment are critical steps for template-based modeling (TBM) methods. To identify the template for the twilight zone of 15~25% sequence similarity between targets and templates is still difficulty for template-based protein structure prediction. This study presents the (PS)²-v2 server, based on our original server with numerous enhancements and modifications, to improve reliability and applicability.     

Application of protein structure alignments to iterated hidden Markov model protocols for structure prediction

Background  

One of the most powerful methods for the prediction of protein structure from sequence information alone is the iterative construction of profile-type models. Because profiles are built from sequence alignments, the sequences included in the alignment and the method used to align them will be important to the sensitivity of the resulting profile. The inclusion of highly diverse sequences will presumably produce a more powerful profile, but distantly related sequences can be difficult to align accurately using only sequence information. Therefore, it would be expected that the use of protein structure alignments to improve the selection and alignment of diverse sequence homologs might yield improved profiles. However, the actual utility of such an approach has remained unclear.     

A jumping profile Hidden Markov Model and applications to recombination sites in HIV and HCV genomes

Background  

Jumping alignments have recently been proposed as a strategy to search a given multiple sequence alignment A against a database. Instead of comparing a database sequence S to the multiple alignment or profile as a whole, S is compared and aligned to individual sequences from A. Within this alignment, S can jump between different sequences from A, so different parts of S can be aligned to different sequences from the input multiple alignment. This approach is particularly useful for dealing with recombination events.