Walter Pirovano

PRALINEtm: a strategy for improved multiple alignment of transmembrane proteins.

MOTIVATION Membrane-bound proteins are a special class of proteins. The regions that insert into the cell-membrane have a profoundly different hydrophobicity pattern compared with soluble proteins. Multiple alignment techniques use scoring schemes tailored for sequences of soluble proteins and are therefore in principle not optimal to align membrane-bound proteins. RESULTS Transmembrane (TM) regions in protein sequences can be reliably recognized using state-of-the-art sequence prediction techniques. Furthermore, membrane-specific scoring matrices are available. We have developed a new alignment method, called PRALINETM, which integrates these two features to enhance multiple sequence alignment. We tested our algorithm on the TM alignment benchmark set by Bahr et al. (2001), and showed that the quality of TM alignments can be significantly improved compared with the quality produced by a standard multiple alignment technique. The results clearly indicate that the incorporation of these new elements into current state-of-the-art alignment methods is crucial for optimizing the alignment of TM proteins. AVAILABILITY A webserver is available at http://www.ibi.vu.nl/programs/pralinewww.

Protein secondary structure prediction.

While the prediction of a native protein structure from sequence continues to remain a challenging problem, over the past decades computational methods have become quite successful in exploiting the mechanisms behind secondary structure formation. The great effort expended in this area has resulted in the development of a vast number of secondary structure prediction methods. Especially the combination of well-optimized/sensitive machine-learning algorithms and inclusion of homologous sequence information has led to increased prediction accuracies of up to 80%. In this chapter, we will first introduce some basic notions and provide a brief history of secondary structure prediction advances. Then a comprehensive overview of state-of-the-art prediction methods will be given. Finally, we will discuss open questions and challenges in this field and provide some practical recommendations for the user.

Sequence comparison by sequence harmony identifies subtype-specific functional sites

Multiple sequence alignments are often used to reveal functionally important residues within a protein family. They can be particularly useful for the identification of key residues that determine functional differences between protein subfamilies. We present a new entropy-based method, Sequence Harmony (SH) that accurately detects subfamily-specific positions from a multiple sequence alignment. The SH algorithm implements a novel formula, able to score compositional differences between subfamilies, without imposing conservation, in a simple manner on an intuitive scale. We compare our method with the most important published methods, i.e. AMAS, TreeDet and SDP-pred, using three well-studied protein families: the receptor-binding domain (MH2) of the Smad family of transcription factors, the Ras-superfamily of small GTPases and the MIP-family of integral membrane transporters. We demonstrate that SH accurately selects known functional sites with higher coverage than the other methods for these test-cases. This shows that compositional differences between protein subfamilies provide sufficient basis for identification of functional sites. In addition, SH selects a number of sites of unknown function that could be interesting candidates for further experimental investigation.

Sequence harmony: detecting functional specificity from alignments

Multiple sequence alignments are often used for the identification of key specificity-determining residues within protein families. We present a web server implementation of the Sequence Harmony (SH) method previously introduced. SH accurately detects subfamily specific positions from a multiple alignment by scoring compositional differences between subfamilies, without imposing conservation. The SH web server allows a quick selection of subtype specific sites from a multiple alignment given a subfamily grouping. In addition, it allows the predicted sites to be directly mapped onto a protein structure and displayed. We demonstrate the use of the SH server using the family of plant mitochondrial alternative oxidases (AOX). In addition, we illustrate the usefulness of combining sequence and structural information by showing that the predicted sites are clustered into a few distinct regions in an AOX homology model. The SH web server can be accessed at www.ibi.vu.nl/programs/seqharmwww.

Multiple Sequence Alignment

The increasing importance of Next Generation Sequencing (NGS) techniques has highlighted the key role of multiple sequence alignment (MSA) in comparative structure and function analysis of biological sequences. MSA often leads to fundamental biological insight into sequence-structure-function relationships of nucleotide or protein sequence families. Significant advances have been achieved in this field, and many useful tools have been developed for constructing alignments, although many biological and methodological issues are still open. This chapter first provides some background information and considerations associated with MSA techniques, concentrating on the alignment of protein sequences. Then, a practical overview of currently available methods and a description of their specific advantages and limitations are given, to serve as a helpful guide or starting point for researchers who aim to construct a reliable MSA.

Bioinformatics approaches for viral metagenomics in plants using short RNAs: model case of study and application to a Cicer arietinum population

Over the past years deep sequencing experiments have opened novel doors to reconstruct viral populations in a high-throughput and cost-effective manner. Currently a substantial number of studies have been performed which employ next generation sequencing techniques to either analyze known viruses by means of a reference-guided approach or to discover novel viruses using a de novo-based strategy. Taking advantage of the well-known Cymbidium ringspot virus we have carried out a comparison of different bioinformatics tools to reconstruct the viral genome based on 21–27 nt short (s)RNA sequencing with the aim to identify the most efficient pipeline. The same approach was applied to a population of plants constituting an ancient variety of Cicer arietinum with red seeds. Among the discovered viruses, we describe the presence of a Tobamovirus referring to the Tomato mottle mosaic virus (NC_022230), which was not yet observed on C. arietinum nor revealed in Europe and a viroid referring to Hop stunt viroid (NC_001351.1) never reported in chickpea. Notably, a reference sequence guided approach appeared the most efficient in such kind of investigation. Instead, the de novo assembly reached a non-appreciable coverage although the most prominent viral species could still be identified. Advantages and limitations of viral metagenomics analysis using sRNAs are discussed.

Homeologs of the Nicotiana benthamiana Antiviral ARGONAUTE1 Show Different Susceptibilities to microRNA168-Mediated Control

Short insertions/deletions in homeolog genes affect microRNA-mediated posttranscriptional regulation and are important for stresses like viral infections that alter the expression of microRNAs. The plant ARGONAUTE1 protein (AGO1) is a central functional component of the posttranscriptional regulation of gene expression and the RNA silencing-based antiviral defense. By genomic and molecular approaches, we here reveal the presence of two homeologs of the AGO1-like gene in Nicotiana benthamiana, NbAGO1-1H and NbAGO1-1L. Both homeologs retain the capacity to transcribe messenger RNAs (mRNAs), which mainly differ in one 18-nucleotide insertion/deletion (indel). The indel does not modify the frame of the open reading frame, and it is located eight nucleotides upstream of the target site of a microRNA, miR168, which is an important modulator of AGO1 expression. We demonstrate that there is a differential accumulation of the two NbAGO1-1 homeolog mRNAs at conditions where miR168 is up-regulated, such as during a tombusvirus infection. The data reported suggest that the indel affects the miR168-guided regulation of NbAGO1 mRNA. The two AGO1 homeologs show full functionality in reconstituted, catalytically active RNA-induced silencing complexes following the incorporation of small interfering RNAs. Virus-induced gene silencing experiments suggest a specific involvement of the NbAGO1 homeologs in symptom development. The results provide an example of the diversity of microRNA target regions in NbAGO1 homeolog genes, which has important implications for improving resilience measures of the plant during viral infections.

A Feature Selection Algorithm for Detecting Subtype Specific Functional Sites from Protein Sequences for Smad Receptor Binding

Multiple sequence alignments are often used to reveal functionally important residues within a protein family. In particular, they can be very useful for identification of key residues that determine functional differences between protein subclasses (subtype specific sites). This paper proposes a new algorithm for selecting subtype specific sites from a set of aligned protein sequences. The algorithm combines a feature selection technique with neighbor position information for selecting and ranking a set of putative relevant sites. The algorithm is applied to a dataset of protein sequences from the MH2 domain of the SMAD family of transcriptor factors. Validation of the results on the basis of the known interaction and function of the sites shows that the algorithm successfully identifies the known (from literature) subtype specific sites and new putative ones

Structure and function analysis of flexible alignment regions in proteins.

Background Protein structural alignment plays a key role in defining gold standards for a variety of bioinformatics applications. These include homology assessment, phylogenetic tree construction and multiple sequence alignment evaluation. Our recent findings [1] however showed that superposition methods are rather sensitive to structural variation. To sidestep the problem of alignment variability, golden standards are often derived from the more conserved and ‘trusted’ regions. It therefore remains unclear which

Shannon Entropy to Evaluate Substitution Rate Variation Among Viral Nucleotide Positions in Datasets of Viral siRNAs

Next-generation sequencing has opened the door to the reconstruction of viral populations and examination of the composition of mutant spectra in infected cells, tissues, and host organisms. In this chapter we present details on the use of the Shannon entropy method to estimate the site-specific nucleotide relative variability of turnip crinkle virus, a positive (+) stranded RNA plant virus, in a large dataset of short RNAs of Cicer arietinum L., a natural reservoir of the virus. We propose this method as a viral metagenomics tool to provide a more detailed description of the viral quasispecies in infected plant tissue. Viral replicative fitness relates to an optimal composition of variants that provide the molecular basis of virus behavior in the complex environment of natural infections. A complete description of viral quasispecies may have implications in determining fitness landscapes for host-virus coexistence and help to design specific diagnostic protocols and antiviral strategies.