Identification and characterization of subfamily-specific signatures in a large protein superfamily by a hidden Markov model approach

Background  

Most profile and motif databases strive to classify protein sequences into a broad spectrum of protein families. The next step of such database studies should include the development of classification systems capable of distinguishing between subfamilies within a structurally and functionally diverse superfamily. This would be helpful in elucidating sequence-structure-function relationships of proteins.     

Incorporation of the red copper nitrosocyanin binding loop into blue copper azurin

Abstract  

Loop-directed mutagenesis was applied to the blue copper protein azurin to replace its copper binding loop with that from the red copper protein nitrosocyanin. A ten amino acid long loop that provides three of the four copper ligands from nitrosocyanin was incorporated into azurin to make a variant called NC-azurin. The chimeric protein displayed a red color, and UV–vis absorption and EPR spectra that closely resembled those of the loop parent, nitrosocyanin. We added the fourth ligand from nitrosocyanin into NC-azurin, a carboxylate-containing amino acid, but the proteins had altered stability and spectroscopic properties that did not resemble those of either parent copper protein. The loop alone, however, was enough to impart red copper site characteristics to the NC-azurin protein. Finally, the reduction potential of the variant was found to be between the reduction potentials of the parent proteins and about 50 mV below that of wild-type azurin.     

Genomic clustering and homology between HET-S and the NWD2 STAND protein in various fungal genomes

Background

Prions are infectious proteins propagating as self-perpetuating amyloid polymers. The [Het-s] prion of Podospora anserina is involved in a cell death process associated with non-self recognition. The prion forming domain (PFD) of HET-s adopts a β-solenoid amyloid structure characterized by the two fold repetition of an elementary triangular motif. [Het-s] induces cell death when interacting with HET-S, an allelic variant of HET-s. When templated by [Het-s], HET-S undergoes a trans-conformation, relocates to the cell membrane and induces toxicity.

Methodology/Principal Findings

Here, comparing HET-s homologs from different species, we devise a consensus for the HET-s elementary triangular motif. We use this motif to screen genomic databases and find a match to the N-terminus of NWD2, a STAND protein, encoded by the gene immediately adjacent to het-S. STAND proteins are signal transducing ATPases which undergo ligand-induced oligomerisation. Homology modelling predicts that the NWD2 N-terminal region adopts a HET-s-like fold. We propose that upon NWD2 oligomerisation, these N-terminal extensions adopt the β-solenoid fold and template HET-S to adopt the amyloid fold and trigger toxicity. We extend this model to a putative prion, the σ infectious element in Nectria haematococca, because the s locus controlling propagation of σ also encodes a STAND protein and displays analogous features. Comparative genomic analyses indicate evolutionary conservation of these STAND/prion-like gene pairs, identify a number of novel prion candidates and define, in addition to the HET-s PFD motif, two distinct, novel putative PFD-like motifs.

Conclusions/Significance

We suggest the existence, in the fungal kingdom, of a widespread and evolutionarily conserved mode of signal transduction based on the transmission of an amyloid-fold from a NOD-like STAND receptor protein to an effector protein.     

Molecular phylogeny of the kelch-repeat superfamily reveals an expansion of BTB/kelch proteins in animals

Background  

The kelch motif is an ancient and evolutionarily-widespread sequence motif of 44–56 amino acids in length. It occurs as five to seven repeats that form a β-propeller tertiary structure. Over 28 kelch-repeat proteins have been sequenced and functionally characterised from diverse organisms spanning from viruses, plants and fungi to mammals and it is evident from expressed sequence tag, domain and genome databases that many additional hypothetical proteins contain kelch-repeats. In general, kelch-repeat β-propellers are involved in protein-protein interactions, however the modest sequence identity between kelch motifs, the diversity of domain architectures, and the partial information on this protein family in any single species, all present difficulties to developing a coherent view of the kelch-repeat domain and the kelch-repeat protein superfamily. To understand the complexity of this superfamily of proteins, we have analysed by bioinformatics the complement of kelch-repeat proteins encoded in the human genome and have made comparisons to the kelch-repeat proteins encoded in other sequenced genomes.     

Intracellular delivery of peptides via association with ubiquitin or SUMO-1 coupled to protein transduction domains

Background  

We previously developed small hybrid proteins consisting of SUMO-1 linked to an heptapeptide fused to the Tat protein transduction domain (PTD). The heptapeptide motif was selected from a library of random sequences to specifically bind HIV-1 regulatory proteins Tat or Rev. These constructs, named SHP, are able to enter primary lymphocytes and some of them inhibit HIV-1 replication. Considering these positive results and other data from the literature, we further tested the ability of ubiquitin or SUMO-1 linked to various PTD at their N-terminus to deliver within cells proteins or peptides fused downstream of their diglycine motif. In this system it is expected that the intracellular ubiquitin or SUMO-1 hydrolases cleave the PTD-Ub or PTD-SUMO-1 modules from the cargo polypeptide, thereby allowing its delivery under an unmodified form.     

Transcriptional responses of Arabidopsis thaliana plants to As (V) stress

Background

Plants encode a large number of leucine-rich repeat receptor-like kinases. Legumes encode several LRR-RLK linked to the process of root nodule formation, the ligands of which are unknown. To identify ligands for these receptors, we used a combination of profile hidden Markov models and position-specific iterative BLAST, allowing us to detect new members of the CLV3/ESR (CLE) protein family from publicly available sequence databases.

Results

We identified 114 new members of the CLE protein family from various plant species, as well as five protein sequences containing multiple CLE domains. We were able to cluster the CLE domain proteins into 13 distinct groups based on their pairwise similarities in the primary CLE motif. In addition, we identified secondary motifs that coincide with our sequence clusters. The groupings based on the CLE motifs correlate with known biological functions of CLE signaling peptides and are analogous to groupings based on phylogenetic analysis and ectopic overexpression studies. We tested the biological function of two of the predicted CLE signaling peptides in the legume Medicago truncatula. These peptides inhibit the activity of the root apical and lateral root meristems in a manner consistent with our functional predictions based on other CLE signaling peptides clustering in the same groups.

Conclusion

Our analysis provides an identification and classification of a large number of novel potential CLE signaling peptides. The additional motifs we found could lead to future discovery of recognition sites for processing peptidases as well as predictions for receptor binding specificity.     

An SVM-based system for predicting protein subnuclear localizations

Background  

The large gap between the number of protein sequences in databases and the number of functionally characterized proteins calls for the development of a fast computational tool for the prediction of subnuclear and subcellular localizations generally applicable to protein sequences. The information on localization may reveal the molecular function of novel proteins, in addition to providing insight on the biological pathways in which they function. The bulk of past work has been focused on protein subcellular localizations. Furthermore, no specific tool has been dedicated to prediction at the subnuclear level, despite its high importance. In order to design a suitable predictive system, the extraction of subtle sequence signals that can discriminate among proteins with different subnuclear localizations is the key.     

A reinforced merging methodology for mapping unique peptide motifs in members of protein families

Background  

Members of a protein family often have highly conserved sequences; most of these sequences carry identical biological functions and possess similar three-dimensional (3-D) structures. However, enzymes with high sequence identity may acquire differential functions other than the common catalytic ability. It is probable that each of their variable regions consists of a unique peptide motif (UPM), which selectively interacts with other cellular proteins, rendering additional biological activities. The ability to identify and localize such UPMs is paramount in recognizing the characteristic role of each member of a protein family.     

A combinatorial optimization approach for diverse motif finding applications

Background  

Discovering approximately repeated patterns, or motifs, in biological sequences is an important and widely-studied problem in computational molecular biology. Most frequently, motif finding applications arise when identifying shared regulatory signals within DNA sequences or shared functional and structural elements within protein sequences. Due to the diversity of contexts in which motif finding is applied, several variations of the problem are commonly studied.     

PHYMYCO-DB: A Curated Database for Analyses of Fungal Diversity and Evolution

Background

In environmental sequencing studies, fungi can be identified based on nucleic acid sequences, using either highly variable sequences as species barcodes or conserved sequences containing a high-quality phylogenetic signal. For the latter, identification relies on phylogenetic analyses and the adoption of the phylogenetic species concept.Such analysis requires that the reference sequences are well identified and deposited in public-access databases. However, many entries in the public sequence databases are problematic in terms of quality and reliability and these data require screening to ensure correct phylogenetic interpretation.

Methods and Principal Findings

To facilitate phylogenetic inferences and phylogenetic assignment, we introduce a fungal sequence database. The database PHYMYCO-DB comprises fungal sequences from GenBank that have been filtered to satisfy stringent sequence quality criteria. For the first release, two widely used molecular taxonomic markers were chosen: the nuclear SSU rRNA and EF1-α gene sequences. Following the automatic extraction and filtration, a manual curation is performed to remove problematic sequences while preserving relevant sequences useful for phylogenetic studies. As a result of curation, ∼20% of the automatically filtered sequences have been removed from the database. To demonstrate how PHYMYCO-DB can be employed, we test a set of environmental Chytridiomycota sequences obtained from deep sea samples.

Conclusion

PHYMYCO-DB offers the tools necessary to: (i) extract high quality fungal sequences for each of the 5 fungal phyla, at all taxonomic levels, (ii) extract already performed alignments, to act as ‘reference alignments’, (iii) launch alignments of personal sequences along with stored data. A total of 9120 SSU rRNA and 672 EF1-α high-quality fungal sequences are now available.The PHYMYCO-DB is accessible through the URL http://phymycodb.genouest.org/.     

Morphological,ultrastructural, and chemical changes induced in Cunninghamella blakesleeana by copper and cobalt

Summary Scanning and transmission electron microscopy of Cunninghamella blakesleeana grown in the presence of toxic concentrations of copper and cobalt indicated that copper, but not cobalt, induced both morphological and ultrastructural changes. In contrast to the control or cobalt-grown cultures, the hyphae of copper-grown cultures (called blue mycelia) were larger in diameter, had a rough and granular surface, and the cell wall was thicker. The cytoplasm of the blue mycelia was also abnormal and was in a compressed state. X-Ray microprobe analysis indicated a lower content of magnesium and calcium in the blue mycelia and an elevated content of sulphur in both the blue and cobalt-grown mycelia. The protein composition of the cell walls of the blue mycelia, fractionated on a Sepharose-4B column saturated with copper, was different from that of control or cobalt-grown cultures, as shown by their amino acid composition. Hydroxyproline was present only in the cell wall proteins of the blue mycelia, citrulline and cystathionine were present only in the proteins of cobalt-grown cultures, and proline was absent in the cell wall protiens of the control cultures.     

An analysis of the Sargasso Sea resource and the consequences for database composition

Background  

The environmental sequencing of the Sargasso Sea has introduced a huge new resource of genomic information. Unlike the protein sequences held in the current searchable databases, the Sargasso Sea sequences originate from a single marine environment and have been sequenced from species that are not easily obtainable by laboratory cultivation. The resource also contains very many fragments of whole protein sequences, a side effect of the shotgun sequencing method.     

MimoSA: a system for minimotif annotation

Background  

Minimotifs are short peptide sequences within one protein, which are recognized by other proteins or molecules. While there are now several minimotif databases, they are incomplete. There are reports of many minimotifs in the primary literature, which have yet to be annotated, while entirely novel minimotifs continue to be published on a weekly basis. Our recently proposed function and sequence syntax for minimotifs enables us to build a general tool that will facilitate structured annotation and management of minimotif data from the biomedical literature.     

WildSpan: mining structured motifs from protein sequences

Background  

Automatic extraction of motifs from biological sequences is an important research problem in study of molecular biology. For proteins, it is desired to discover sequence motifs containing a large number of wildcard symbols, as the residues associated with functional sites are usually largely separated in sequences. Discovering such patterns is time-consuming because abundant combinations exist when long gaps (a gap consists of one or more successive wildcards) are considered. Mining algorithms often employ constraints to narrow down the search space in order to increase efficiency. However, improper constraint models might degrade the sensitivity and specificity of the motifs discovered by computational methods. We previously proposed a new constraint model to handle large wildcard regions for discovering functional motifs of proteins. The patterns that satisfy the proposed constraint model are called W-patterns. A W-pattern is a structured motif that groups motif symbols into pattern blocks interleaved with large irregular gaps. Considering large gaps reflects the fact that functional residues are not always from a single region of protein sequences, and restricting motif symbols into clusters corresponds to the observation that short motifs are frequently present within protein families. To efficiently discover W-patterns for large-scale sequence annotation and function prediction, this paper first formally introduces the problem to solve and proposes an algorithm named WildSpan (sequential pattern mining across large wildcard regions) that incorporates several pruning strategies to largely reduce the mining cost.     

Gene and protein nomenclature in public databases

Background  

Frequently, several alternative names are in use for biological objects such as genes and proteins. Applications like manual literature search, automated text-mining, named entity identification, gene/protein annotation, and linking of knowledge from different information sources require the knowledge of all used names referring to a given gene or protein. Various organism-specific or general public databases aim at organizing knowledge about genes and proteins. These databases can be used for deriving gene and protein name dictionaries. So far, little is known about the differences between databases in terms of size, ambiguities and overlap.