In vitro selection of RNA aptamers against a conserved region of the Plasmodium falciparum erythrocyte membrane protein 1

The var-gene encoding Plasmodium falciparum erythrocyte membrane protein 1 (PfEMP1) is known to play a major role in the pathogenicity of the P. falciparum parasite. The protein enables the parasite to adhere to the endothelial linings of small blood vessels (cytoadherence) as well as to non-infected erythrocytes (rosetting), thus preventing clearance from the bloodstream. The development and spread of resistance towards most anti-malarial drugs used for treatment and prevention of the most severe form of malaria truly emphasise the importance of a continuous research and development of new drugs. In this study we use Systematic Evolution of Ligands by EXponential enrichment (SELEX) methodology to isolate high-affinity ligands (aptamers). To validate the results from the SELEX in vitro selection, different aptamers have been selected against PfEMP1 in a live cell assay of P. falciparum strain FCR3S1.2, a highly rosetting strain. We have been able to show the rosette disrupting capacity of these SELEX-aptamers at concentrations of 33 nM and with 100% disruption at 387 nM. The described results show that RNA aptamers are promising candidates for adjunct therapy in severe malaria

rMotifGen: random motif generator for DNA and protein sequences

<p>Abstract</p> <p>Background</p> <p>Detection of short, subtle conserved motif regions within a set of related DNA or amino acid sequences can lead to discoveries about important regulatory domains such as transcription factor and DNA binding sites as well as conserved protein domains. In order to help assess motif detection algorithms on motifs with varying properties and levels of conservation, we have developed a computational tool, rMotifGen, with the sole purpose of generating a number of random DNA or protein sequences containing short sequence motifs. Each motif consensus can be user-defined, randomly generated, or created from a position-specific scoring matrix (PSSM). Insertions and mutations within these motifs are created according to user-defined parameters and substitution matrices. The resulting sequences can be helpful in mutational simulations and in testing the limits of motif detection algorithms.</p> <p>Results</p> <p>Two implementations of rMotifGen have been created, one providing a graphical user interface (GUI) for random motif construction, and the other serving as a command line interface. The second implementation has the added advantages of platform independence and being able to be called in a batch mode. rMotifGen was used to construct sample sets of sequences containing DNA motifs and amino acid motifs that were then tested against the Gibbs sampler and MEME packages.</p> <p>Conclusion</p> <p>rMotifGen provides an efficient and convenient method for creating random DNA or amino acid sequences with a variable number of motifs, where the instance of each motif can be incorporated using a position-specific scoring matrix (PSSM) or by creating an instance mutated from its corresponding consensus using an evolutionary model based on substitution matrices. rMotifGen is freely available at: <url>http://bioinformatics.louisville.edu/brg/rMotifGen/</url>.</p

Using structural motif descriptors for sequence-based binding site prediction

All authors are with the Biotechnological Center, TU Dresden, Tatzberg 47-51, 01307 Dresden, Germany and -- Wan Kyu Kim is with the Institute for Cellular and Molecular Biology, University of Texas at Austin, Austin, TX 78712, USABackground: Many protein sequences are still poorly annotated. Functional characterization of a protein is often improved by the identification of its interaction partners. Here, we aim to predict protein-protein interactions (PPI) and protein-ligand interactions (PLI) on sequence level using 3D information. To this end, we use machine learning to compile sequential segments that constitute structural features of an interaction site into one profile Hidden Markov Model descriptor. The resulting collection of descriptors can be used to screen sequence databases in order to predict functional sites. -- Results: We generate descriptors for 740 classified types of protein-protein binding sites and for more than 3,000 protein-ligand binding sites. Cross validation reveals that two thirds of the PPI descriptors are sufficiently conserved and significant enough to be used for binding site recognition. We further validate 230 PPIs that were extracted from the literature, where we additionally identify the interface residues. Finally we test ligand-binding descriptors for the case of ATP. From sequences with Swiss-Prot annotation "ATP-binding", we achieve a recall of 25% with a precision of 89%, whereas Prosite's P-loop motif recognizes an equal amount of hits at the expense of a much higher number of false positives (precision: 57%). Our method yields 771 hits with a precision of 96% that were not previously picked up by any Prosite-pattern. -- Conclusion: The automatically generated descriptors are a useful complement to known Prosite/InterPro motifs. They serve to predict protein-protein as well as protein-ligand interactions along with their binding site residues for proteins where merely sequence information is available.Institute for Cellular and Molecular [email protected]

Phamerator: a bioinformatic tool for comparative bacteriophage genomics

Background: Bacteriophage genomes have mosaic architectures and are replete with small open reading frames of unknown function, presenting challenges in their annotation, comparative analysis, and representation.Results: We describe here a bioinformatic tool, Phamerator, that assorts protein-coding genes into phamilies of related sequences using pairwise comparisons to generate a database of gene relationships. This database is used to generate genome maps of multiple phages that incorporate nucleotide and amino acid sequence relationships, as well as genes containing conserved domains. Phamerator also generates phamily circle representations of gene phamilies, facilitating analysis of the different evolutionary histories of individual genes that migrate through phage populations by horizontal genetic exchange.Conclusions: Phamerator represents a useful tool for comparative genomic analysis and comparative representations of bacteriophage genomes. © 2011 Cresawn et al; licensee BioMed Central Ltd

Accelerated Profile HMM Searches

Profile hidden Markov models (profile HMMs) and probabilistic inference methods have made important contributions to the theory of sequence database homology search. However, practical use of profile HMM methods has been hindered by the computational expense of existing software implementations. Here I describe an acceleration heuristic for profile HMMs, the “multiple segment Viterbi” (MSV) algorithm. The MSV algorithm computes an optimal sum of multiple ungapped local alignment segments using a striped vector-parallel approach previously described for fast Smith/Waterman alignment. MSV scores follow the same statistical distribution as gapped optimal local alignment scores, allowing rapid evaluation of significance of an MSV score and thus facilitating its use as a heuristic filter. I also describe a 20-fold acceleration of the standard profile HMM Forward/Backward algorithms using a method I call “sparse rescaling”. These methods are assembled in a pipeline in which high-scoring MSV hits are passed on for reanalysis with the full HMM Forward/Backward algorithm. This accelerated pipeline is implemented in the freely available HMMER3 software package. Performance benchmarks show that the use of the heuristic MSV filter sacrifices negligible sensitivity compared to unaccelerated profile HMM searches. HMMER3 is substantially more sensitive and 100- to 1000-fold faster than HMMER2. HMMER3 is now about as fast as BLAST for protein searches

Molecular subtypes and phenotypic expression of Beckwith-Wiedemann syndrome

Beckwith-Wiedemann Syndrome (BWS) results from mutations or epigenetic events involving imprinted genes at 11p15.5. Most BWS cases are sporadic and uniparental disomy (UPD) or putative imprinting errors predominate in this group. Sporadic cases with putative imprinting defects may be subdivided into (a) those with loss of imprinting (LOI) of IGF2 and H19 hypermethylation and silencing due to a defect in a distal 11p15.5 imprinting control element (IC1) and (b) those with loss of methylation at KvDMR1, LOI of KCNQ1OT1 (LIT1) and variable LOI of IGF2 in whom there is a defect at a more proximal imprinting control element (IC2). We investigated genotype/epigenotype-phenotype correlations in 200 cases with a confirmed molecular genetic diagnosis of BWS (16 with CDKN1C mutations, 116 with imprinting centre 2 defects, 14 with imprinting centre 1 defects and 54 with UPD). Hemihypertrophy was strongly associated with UPD (P < 0.0001) and exomphalos was associated with an IC2 defect or CDKN1C mutation but not UPD or IC1 defect (P < 0.0001). When comparing birth weight centile, IC1 defect cases were significantly heavier than the patients with CDKN1C mutations or IC2 defect (P = 0.018). The risk of neoplasia was significantly higher in UPD and IC1 defect cases than in IC2 defect and CDKN1C mutation cases. Kaplan-Meier analysis revealed a risk of neoplasia for all patients of 9% at age 5 years, but 24% in the UPD subgroup. The risk of Wilms' tumour in the IC2 defect subgroup appears to be minimal and intensive screening for Wilms' tumour appears not to be indicated. In UPD patients, UPD extending to WTI was associated with renal neoplasia (P = 0.054). These findings demonstrate that BWS represents a spectrum of disorders. Identification of the molecular subtype allows more accurate prognostic predictions and enhances the management and surveillance of BWS children such that screening for Wilms' tumour and hepatoblastoma can be focused on those at highest risk. © 2005 Nature Publishing Group All rights reserved