Structures of Phytophthora RXLR Effector Proteins: a conserved but adaptable fold underpins functional diversity

Phytopathogens deliver effector proteins inside host plant cells to promote infection. These proteins can also be sensed by the plant immune system, leading to restriction of pathogen growth. Effector genes can display signatures of positive selection and rapid evolution, presumably a consequence of their co-evolutionary arms race with plants. The molecular mechanisms underlying how effectors evolve to gain new virulence functions and/or evade the plant immune system are poorly understood. Here, we report the crystal structures of the effector domains from two oomycete RXLR proteins, Phytophthora capsici AVR3a11 and Phytophthora infestans PexRD2. Despite sharin

DeepSig: Deep learning improves signal peptide detection in proteins

Motivation: The identification of signal peptides in protein sequences is an important step toward protein localization and function characterization. Results: Here, we present DeepSig, an improved approach for signal peptide detection and cleavage-site prediction based on deep learning methods. Comparative benchmarks performed on an updated independent dataset of proteins show that DeepSig is the current best performing method, scoring better than other available state-of-the-art approaches on both signal peptide detection and precise cleavage-site identification. Availability and implementation: DeepSig is available as both standalone program and web server at https://deepsig.biocomp.unibo.it. All datasets used in this study can be obtained from the same website

Plastid proteome prediction for diatoms and other algae with secondary plastids of the red lineage

The plastids of ecologically and economically important algae from phyla such as stramenopiles, dinoflagellates and cryptophytes were acquired via a secondary endosymbiosis and are surrounded by three or four membranes. Nuclear-encoded plastid-localized proteins contain N-terminal bipartite targeting peptides with the conserved amino acid sequence motif ‘ASAFAP’. Here we identify the plastid proteomes of two diatoms, Thalassiosira pseudonana and Phaeodactylum tricornutum, using a customized prediction tool (ASAFind) that identifies nuclear-encoded plastid proteins in algae with secondary plastids of the red lineage based on the output of SignalP and the identification of conserved ‘ASAFAP’ motifs and transit peptides. We tested ASAFind against a large reference dataset of diatom proteins with experimentally confirmed subcellular localization and found that the tool accurately identified plastid-localized proteins with both high sensitivity and high specificity. To identify nucleus-encoded plastid proteins of T. pseudonana and P. tricornutum we generated optimized sets of gene models for both whole genomes, to increase the percentage of full-length proteins compared with previous assembly model sets. ASAFind applied to these optimized sets revealed that about 8% of the proteins encoded in their nuclear genomes were predicted to be plastid localized and therefore represent the putative plastid proteomes of these algae

Automatically extracting functionally equivalent proteins from SwissProt

In summary, FOSTA provides an automated analysis of annotations in UniProtKB/Swiss-Prot to enable groups of proteins already annotated as functionally equivalent, to be extracted. Our results demonstrate that the vast majority of UniProtKB/Swiss-Prot functional annotations are of high quality, and that FOSTA can interpret annotations successfully. Where FOSTA is not successful, we are able to highlight inconsistencies in UniProtKB/Swiss-Prot annotation. Most of these would have presented equal difficulties for manual interpretation of annotations. We discuss limitations and possible future extensions to FOSTA, and recommend changes to the UniProtKB/Swiss-Prot format, which would facilitate text-mining of UniProtKB/Swiss-Prot

Discovery of noncanonical translation initiation sites through mass spectrometric analysis of protein N termini

Translation initiation generally occurs at AUG codons in eukaryotes, although it has been shown that non-AUG or non-canonical translation initiation can also occur. However, the evidence for noncanonical translation initiation sites (TISs) is largely indirect and based on ribosome profiling (Ribo-seq) studies. Here, using a strategy specifically designed to enrich N termini of proteins, we demonstrate that many human proteins are translated at noncanonical TISs. The large majority of TISs that mapped to 5' untranslated regions were noncanonical and led to N-terminal extension of annotated proteins or translation of upstream small open reading frames (uORF). It has been controversial whether the amino acid corresponding to the start codon is incorporated at the TIS or methionine is still incorporated. We found that methionine was incorporated at almost all noncanonical TISs identified in this study. Comparison of the TISs determined through mass spectrometry with ribosome profiling data revealed that about two-thirds of the novel annotations were indeed supported by the available ribosome profiling data. Sequence conservation across species and a higher abundance of noncanonical TISs than canonical ones in some cases suggests that the noncanonical TISs can have biological functions. Overall, this study provides evidence of protein translation initiation at noncanonical TISs and argues that further studies are required for elucidation of functional implications of such noncanonical translation initiation

Integration and mining of malaria molecular, functional and pharmacological data: how far are we from a chemogenomic knowledge space?

The organization and mining of malaria genomic and post-genomic data is highly motivated by the necessity to predict and characterize new biological targets and new drugs. Biological targets are sought in a biological space designed from the genomic data from Plasmodium falciparum, but using also the millions of genomic data from other species. Drug candidates are sought in a chemical space containing the millions of small molecules stored in public and private chemolibraries. Data management should therefore be as reliable and versatile as possible. In this context, we examined five aspects of the organization and mining of malaria genomic and post-genomic data: 1) the comparison of protein sequences including compositionally atypical malaria sequences, 2) the high throughput reconstruction of molecular phylogenies, 3) the representation of biological processes particularly metabolic pathways, 4) the versatile methods to integrate genomic data, biological representations and functional profiling obtained from X-omic experiments after drug treatments and 5) the determination and prediction of protein structures and their molecular docking with drug candidate structures. Progresses toward a grid-enabled chemogenomic knowledge space are discussed.Comment: 43 pages, 4 figures, to appear in Malaria Journa

Proteomic Analysis to Identify Tightly-Bound Cell Wall Protein in Rice Calli.

Rice is a model plant widely used for basic and applied research programs. Plant cell wall proteins play key roles in a broad range of biological processes. However, presently, knowledge on the rice cell wall proteome is rudimentary in nature. In the present study, the tightly-bound cell wall proteome of rice callus cultured cells using sequential extraction protocols was developed using mass spectrometry and bioinformatics methods, leading to the identification of 1568 candidate proteins. Based on bioinformatics analyses, 389 classical rice cell wall proteins, possessing a signal peptide, and 334 putative non-classical cell wall proteins, lacking a signal peptide, were identified. By combining previously established rice cell wall protein databases with current data for the classical rice cell wall proteins, a comprehensive rice cell wall proteome, comprised of 496 proteins, was constructed. A comparative analysis of the rice and Arabidopsis cell wall proteomes revealed a high level of homology, suggesting a predominant conservation between monocot and eudicot cell wall proteins. This study importantly increased information on cell wall proteins, which serves for future functional analyses of these identified rice cell wall proteins

Structural basis of severe acute respiratory syndrome coronavirus ADP-ribose-1''-phosphate dephosphorylation by a conserved domain of nsP3.

The crystal structure of a conserved domain of nonstructural protein 3 (nsP3) from severe acute respiratory syndrome coronavirus (SARS-CoV) has been solved by single-wavelength anomalous dispersion to 1.4 A resolution. The structure of this "X" domain, seen in many single-stranded RNA viruses, reveals a three-layered alpha/beta/alpha core with a macro-H2A-like fold. The putative active site is a solvent-exposed cleft that is conserved in its three structural homologs, yeast Ymx7, Archeoglobus fulgidus AF1521, and Er58 from E. coli. Its sequence is similar to yeast YBR022W (also known as Poa1P), a known phosphatase that acts on ADP-ribose-1''-phosphate (Appr-1''-p). The SARS nsP3 domain readily removes the 1'' phosphate group from Appr-1''-p in in vitro assays, confirming its phosphatase activity. Sequence and structure comparison of all known macro-H2A domains combined with available functional data suggests that proteins of this superfamily form an emerging group of nucleotide phosphatases that dephosphorylate Appr-1''-p