DETECTING AND SORTING TARGETING PEPTIDES WITH NEURAL NETWORKS AND SUPPORT VECTOR MACHINES

AtIAR1 is a Zn transporter that regulates auxin metabolism in Arabidopsis thaliana

Root growth in Arabidopsis is inhibited by exogenous auxin-amino acid conjugates, and mutants resistant to one such conjugate [indole-3-acetic acid (IAA)-Ala] map to a gene (AtIAR1) that is a member of a metal transporter family. Here, we test the hypothesis that AtIAR1 controls the hydrolysis of stored conjugated auxin to free auxin through zinc transport. AtIAR1 complements a yeast mutant sensitive to zinc, but not manganese- or iron-sensitive mutants, and the transporter is predicted to be localized to the endoplasmic reticulum/Golgi in plants. A previously identified Atiar1 mutant and a non-expressed T-DNA mutant both exhibit altered auxin metabolism, including decreased IAA-glucose conjugate levels in zinc-deficient conditions and insensitivity to the growth effect of exogenous IAA-Ala conjugates. At a high concentration of zinc, wild-type plants show a novel enhanced response to root growth inhibition by exogenous IAA-Ala which is disrupted in both Atiar1 mutants. Furthermore, both Atiar1 mutants show changes in auxin-related phenotypes, including lateral root density and hypocotyl length. The findings therefore suggest a role for AtIAR1 in controlling zinc release from the secretory system, where zinc homeostasis plays a key role in regulation of auxin metabolism and plant growth regulation.

Exploring the genetic landscape of nitrogen uptake in durum wheat: genome-wide characterization and expression profiling of NPF and NRT2 gene families

Nitrate uptake by plants primarily relies on two gene families: Nitrate transporter 1/peptide transporter (NPF) and Nitrate transporter 2 (NRT2). Here, we extensively characterized the NPF and NRT2 families in the durum wheat genome, revealing 211 NPF and 20 NRT2 genes. The two families share many Cis Regulatory Elements (CREs) and Transcription Factor binding sites, highlighting a partially overlapping regulatory system and suggesting a coordinated response for nitrate transport and utilization. Analyzing RNA-seq data from 9 tissues and 20 cultivars, we explored expression profiles and co-expression relationships of both gene families. We observed a strong correlation between nucleotide variation and gene expression within the NRT2 gene family, implicating a shared selection mechanism operating on both coding and regulatory regions. Furthermore, NPF genes showed highly tissue-specific expression profiles, while NRT2s were mainly divided in two co-expression modules, one expressed in roots (NAR2/NRT3 dependent) and the other induced in anthers and/ovaries during maturation. Our evidences confirmed that the majority of these genes were retained after small-scale duplication events, suggesting a neo- or sub-functionalization of many NPFs and NRT2s. Altogether, these findings indicate that the expansion of these gene families in durum wheat could provide valuable genetic variability useful to identify NUE-related and candidate genes for future breeding programs in the context of low-impact and sustainable agriculture.

Deep Learning for Genomics: From Early Neural Nets to Modern Large Language Models

The data explosion driven by advancements in genomic research, such as high-throughput sequencing techniques, is constantly challenging conventional methods used in genomics. In parallel with the urgent demand for robust algorithms, deep learning has succeeded in various fields such as vision, speech, and text processing. Yet genomics entails unique challenges to deep learning, since we expect a superhuman intelligence that explores beyond our knowledge to interpret the genome from deep learning. A powerful deep learning model should rely on the insightful utilization of task-specific knowledge. In this paper, we briefly discuss the strengths of different deep learning models from a genomic perspective so as to fit each particular task with proper deep learning-based architecture, and we remark on practical considerations of developing deep learning architectures for genomics. We also provide a concise review of deep learning applications in various aspects of genomic research and point out current challenges and potential research directions for future genomics applications. We believe the collaborative use of ever-growing diverse data and the fast iteration of deep learning models will continue to contribute to the future of genomics.

Comparative analysis of mitochondrion-related organelles in anaerobic amoebozoans

Archamoebae comprises free-living or endobiotic amoebiform protists that inhabit anaerobic or microaerophilic environments and possess mitochondrion-related organelles (MROs) adapted to function anaerobically. We compared in silico reconstructed MRO proteomes of eight species (six genera) and found that the common ancestor of Archamoebae possessed very few typical components of the protein translocation machinery, electron transport chain and tricarboxylic acid cycle. On the other hand, it contained a sulphate activation pathway and bacterial iron-sulphur (Fe-S) assembly system of MIS-type. The metabolic capacity of the MROs, however, varies markedly within this clade. The glycine cleavage system is widely conserved among Archamoebae, except in Entamoeba, probably owing to its role in catabolic function or one-carbon metabolism. MRO-based pyruvate metabolism was dispensed within subgroups Entamoebidae and Rhizomastixidae, whereas sulphate activation could have been lost in isolated cases of Rhizomastix libera, Mastigamoeba abducta and Endolimax sp. The MIS (Fe-S) assembly system was duplicated in the common ancestor of Mastigamoebidae and Pelomyxidae, and one of the copies took over Fe-S assembly in their MRO. In Entamoebidae and Rhizomastixidae, we hypothesize that Fe-S cluster assembly in both compartments may be facilitated by dual localization of the single system. We could not find evidence for changes in metabolic functions of the MRO in response to changes in habitat; it appears that such environmental drivers do not strongly affect MRO reduction in this group of eukaryotes.

The Late Embryogenesis Abundant Proteins in Soybean: Identification, Expression Analysis, and the Roles of GmLEA4_19 in Drought Stress

Late embryogenesis abundant (LEA) proteins play important roles in regulating plant growth and responses to various abiotic stresses. In this research, a genome-wide survey was conducted to recognize the LEA genes in Glycine max. A total of 74 GmLEA was identified and classified into nine subfamilies based on their conserved domains and the phylogenetic analysis. Subcellular localization, the duplication of genes, gene structure, the conserved motif, and the prediction of cis-regulatory elements and tissue expression pattern were then conducted to characterize GmLEAs. The expression profile analysis indicated that the expression of several GmLEAs was a response to drought and salt stress. The co-expression-based gene network analysis suggested that soybean LEA proteins may exert regulatory effects through the metabolic pathways. We further explored GnLEA4_19 function in Arabidopsis and the results suggests that overexpressed GmLEA4_19 in Arabidopsis increased plant height under mild or serious drought stress. Moreover, the overexpressed GmLEA4_19 soybean also showed a drought tolerance phenotype. These results indicated that GmLEA4_19 plays an important role in the tolerance to drought and will contribute to the development of the soybean transgenic with enhanced drought tolerance and better yield. Taken together, this study provided insight for better understanding the biological roles of LEA genes in soybean.

Characterization of Chlamydomonas voltage-gated calcium channel and its interaction with photoreceptor support VGCC modulated photobehavioral response in the green alga

Calcium (Ca2+) signaling plays a major role in regulating multiple processes in living cells. The photoreceptor potential in Chlamydomonas triggers the generation of all or no flagellar Ca2+ currents that cause membrane depolarization across the eyespot and flagella. Modulation in membrane potential causes changes in the flagellar waveform, and hence, alters the beating patterns of Chlamydomonas flagella. The rhodopsin-mediated eyespot membrane potential is generated by the photoreceptor Ca2+ current or P-current however, the flagellar Ca2+ currents are mediated by unidentified voltage-gated calcium (VGCC or CaV) and potassium channels (VGKC). The voltage-gated ion channel that associates with ChRs to generate Ca2+ influx across the flagella and its cellular distribution has not yet been identified. Here, we identified putative VGCCs from algae and predicted their novel properties through insilico analysis. We further present experimental evidence on Chlamydomonas reinhardtii VGCCs to predict their novel physiological roles. Our experimental evidences showed that CrVGCC4 localizes to the eyespot and flagella of Chlamydomonas and associates with channelrhodopsins (ChRs). Further in silico interactome analysis of CrVGCCs suggested that they putatively interact with photoreceptor proteins, calcium signaling, and intraflagellar transport components. Expression analysis indicated that these VGCCs and their putative interactors can be perturbed by light stimuli. Collectively, our data suggest that VGCCs in general, and VGCC4 in particular, might be involved in the regulation of the photobehavioral response of Chlamydomonas.

Reduced mitochondria provide an essential function for the cytosolic methionine cycle

The loss of mitochondria in oxymonad protists has been associated with the redirection of the essential Fe-S cluster assembly to the cytosol. Yet as our knowledge of diverse free-living protists broadens, the list of functions of their mitochondrial-related organelles (MROs) expands. We revealed another such function in the closest oxymonad relative, Paratrimastix pyriformis, after we solved the proteome of its MRO with high accuracy, using localization of organelle proteins by isotope tagging (LOPIT). The newly assigned enzymes connect to the glycine cleavage system (GCS) and produce folate derivatives with one-carbon units and formate. These are likely to be used by the cytosolic methionine cycle involved in S-adenosyl methionine recycling. The data provide consistency with the presence of the GCS in MROs of free-living species and its absence in most endobionts, which typically lose the methionine cycle and, in the case of oxymonads, the mitochondria.

Subcellular Proteomics as a Unified Approach of Experimental Localizations and Computed Prediction Data for Arabidopsis and Crop Plants

In eukaryotic organisms, subcellular protein location is critical in defining protein function and understanding sub-functionalization of gene families. Some proteins have defined locations, whereas others have low specificity targeting and complex accumulation patterns. There is no single approach that can be considered entirely adequate for defining the in vivo location of all proteins. By combining evidence from different approaches, the strengths and weaknesses of different technologies can be estimated, and a location consensus can be built. The Subcellular Location of Proteins in Arabidopsis database ( http://suba.live/ ) combines experimental data sets that have been reported in the literature and is analyzing these data to provide useful tools for biologists to interpret their own data. Foremost among these tools is a consensus classifier (SUBAcon) that computes a proposed location for all proteins based on balancing the experimental evidence and predictions. Further tools analyze sets of proteins to define the abundance of cellular structures. Extending these types of resources to plant crop species has been complex due to polyploidy, gene family expansion and contraction, and the movement of pathways and processes within cells across the plant kingdom. The Crop Proteins of Annotated Location database ( http://crop-pal.org/ ) has developed a range of subcellular location resources including a species-specific voting consensus for 12 plant crop species that offers collated evidence and filters for current crop proteomes akin to SUBA. Comprehensive cross-species comparison of these data shows that the sub-cellular proteomes (subcellulomes) depend only to some degree on phylogenetic relationship and are more conserved in major biosynthesis than in metabolic pathways. Together SUBA and cropPAL created reference subcellulomes for plants as well as species-specific subcellulomes for cross-species data mining. These data collections are increasingly used by the research community to provide a subcellular protein location layer, inform models of compartmented cell function and protein-protein interaction network, guide future molecular crop breeding strategies, or simply answer a specific question-where is my protein of interest inside the cell?

Ultrastructural, Cytochemical, and Comparative Genomic Evidence of Peroxisomes in Three Genera of Pathogenic Free-Living Amoebae, Including the First Morphological Data for the Presence of This Organelle in Heteroloboseans

Peroxisomes perform various metabolic processes that are primarily related to the elimination of reactive oxygen species and oxidative lipid metabolism. These organelles are present in all major eukaryotic lineages, nevertheless, information regarding the presence of peroxisomes in opportunistic parasitic protozoa is scarce and in many cases it is still unknown whether these organisms have peroxisomes at all. Here, we performed ultrastructural, cytochemical, and bioinformatic studies to investigate the presence of peroxisomes in three genera of free-living amoebae from two different taxonomic groups that are known to cause fatal infections in humans. By transmission electron microscopy, round structures with a granular content limited by a single membrane were observed in Acanthamoeba castellanii, Acanthamoeba griffini, Acanthamoeba polyphaga, Acanthamoeba royreba, Balamuthia mandrillaris (Amoebozoa), and Naegleria fowleri (Heterolobosea). Further confirmation for the presence of peroxisomes was obtained by treating trophozoites in situ with diaminobenzidine and hydrogen peroxide, which showed positive reaction products for the presence of catalase. We then performed comparative genomic analyses to identify predicted peroxin homologues in these organisms. Our results demonstrate that a complete set of peroxins-which are essential for peroxisome biogenesis, proliferation, and protein import-are present in all of these amoebae. Likewise, our in silico analyses allowed us to identify a complete set of peroxins in Naegleria lovaniensis and three novel peroxin homologues in Naegleria gruberi. Thus, our results indicate that peroxisomes are present in these three genera of free-living amoebae and that they have a similar peroxin complement despite belonging to different evolutionary lineages.

Two Independent Plastid accD Transfers to the Nuclear Genome of Gnetum and Other Insights on Acetyl-CoA Carboxylase Evolution in Gymnosperms

Acetyl-CoA carboxylase (ACCase) is the key regulator of fatty acid biosynthesis. In most plants, ACCase exists in two locations (cytosol and plastids) and in two forms (homomeric and heteromeric). Heteromeric ACCase comprises four subunits, three of them (ACCA-C) are nuclear encoded (nr) and the fourth (ACCD) is usually plastid encoded. Homomeric ACCase is encoded by a single nr-gene (ACC). We investigated the ACCase gene evolution in gymnosperms by examining the transcriptomes of newly sequenced Gnetum ula, combined with 75 transcriptomes and 110 plastomes of other gymnosperms. AccD-coding sequences are elongated through the insertion of repetitive DNA in four out of five cupressophyte families (except Sciadopityaceae) and were functionally transferred to the nucleus of gnetophytes and Sciadopitys. We discovered that, among the three genera of gnetophytes, only Gnetum has two copies of nr-accD. Furthermore, using protoplast transient expression assays, we experimentally verified that the nr-accD precursor proteins in Gnetum and Sciadopitys can be delivered to the plastids. Of the two nr-accD copies of Gnetum, one dually targets plastids and mitochondria, whereas the other potentially targets plastoglobuli. The distinct transit peptides, gene architectures, and flanking sequences between the two Gnetum accDs suggest that they have independent origins. Our findings are the first account of two distinctly targeted nr-accDs of any green plants and the most comprehensive analyses of ACCase evolution in gymnosperms to date.

The riddle of mitochondrial alkaline/neutral invertases: A novel Arabidopsis isoform mainly present in reproductive tissues and involved in root ROS production

Alkaline/neutral invertases (A/N-Inv), glucosidases that irreversibly hydrolyze sucrose into glucose and fructose, play significant roles in plant growth, development, and stress adaptation. They occur as multiple isoforms located in the cytosol or organelles. In Arabidopsis thaliana, two mitochondrial A/N-Inv genes (A/N-InvA and A/N-InvC) have already been investigated. In this study, we functionally characterized A/N-InvH, a third Arabidopsis gene coding for a mitochondrial-targeted protein. The phenotypic analysis of knockout mutant plants (invh) showed a severely reduced shoot growth, while root development was not affected. The emergence of the first floral bud and the opening of the first flower were the most affected stages, presenting a significant delay. A/N-InvH transcription is markedly active in reproductive tissues. It is also expressed in the elongation and apical meristem root zones. Our results show that A/N-InvH expression is not evident in photosynthetic tissues, despite being of relevance in developmental processes and mitochondrial functional status. NaCl and mannitol treatments increased A/N-InvH expression twofold in the columella root cap. Moreover, the absence of A/N-InvH prevented ROS formation, not only in invh roots of salt- and ABA-treated seedlings but also in invh control roots. We hypothesize that this isoform may take part in the ROS/sugar (sucrose or its hydrolysis products) signaling pathway network, involved in reproductive tissue development, cell elongation, and abiotic stress responses.

Ancient signal for nitrogen status sensing in the green lineage: Functional evidence of CDPK repertoire in Ostreococcus tauri

Calcium-dependent protein kinases (CDPKs) regulate plant development and many stress signalling pathways through the complex cytosolic [Ca²⁺] signalling. The genome of Ostreococcus tauri (Ot), a model prasinophyte organism that is on the base of the green lineage, harbours three sequences homologous to those encoding plant CDPKs with the three characteristic conserved domains (protein kinase, autoregulatory/autoinhibitory, and regulatory domain). Phylogenetic and structural analyses revealed that putative OtCDPK proteins are closely related to CDPKs from other Chlorophytes. We functionally characterised the first marine picophytoeukaryote CDPK gene (OtCDPK1) and showed that the expression of the three OtCDPK genes is up-regulated by nitrogen depletion. We conclude that CDPK signalling pathway might have originated early in the green lineage and may play a key role in prasinophytes by sensing macronutrient changes in the marine environment.

Complete plastid genome sequence of Primula sinensis (Primulaceae): structure comparison, sequence variation and evidence for accD transfer to nucleus

Species-rich genus Primula L. is a typical plant group with which to understand genetic variance between species in different levels of relationships. Chloroplast genome sequences are used to be the information resource for quantifying this difference and reconstructing evolutionary history. In this study, we reported the complete chloroplast genome sequence of Primula sinensis and compared it with other related species. This genome of chloroplast showed a typical circular quadripartite structure with 150,859 bp in sequence length consisting of 37.2% GC base. Two inverted repeated regions (25,535 bp) were separated by a large single-copy region (82,064 bp) and a small single-copy region (17,725 bp). The genome consists of 112 genes, including 78 protein-coding genes, 30 tRNA genes and four rRNA genes. Among them, seven coding genes, seven tRNA genes and four rRNA genes have two copies due to their locations in the IR regions. The accD and infA genes lacking intact open reading frames (ORF) were identified as pseudogenes. SSR and sequence variation analyses were also performed on the plastome of Primula sinensis, comparing with another available plastome of P. poissonii. The four most variable regions, rpl36–rps8, rps16–trnQ, trnH–psbA and ndhC–trnV, were identified. Phylogenetic relationship estimates using three sub-datasets extracted from a matrix of 57 protein-coding gene sequences showed the identical result that was consistent with previous studies. A transcript found from P. sinensis transcriptome showed a high similarity to plastid accD functional region and was identified as a putative plastid transit peptide at the N-terminal region. The result strongly suggested that plastid accD has been functionally transferred to the nucleus in P. sinensis.

Comparative Genomic Analysis of Drechmeria coniospora Reveals Core and Specific Genetic Requirements for Fungal Endoparasitism of Nematodes

Drechmeria coniospora is an obligate fungal pathogen that infects nematodes via the adhesion of specialized spores to the host cuticle. D. coniospora is frequently found associated with Caenorhabditis elegans in environmental samples. It is used in the study of the nematode's response to fungal infection. Full understanding of this bi-partite interaction requires knowledge of the pathogen's genome, analysis of its gene expression program and a capacity for genetic engineering. The acquisition of all three is reported here. A phylogenetic analysis placed D. coniospora close to the truffle parasite Tolypocladium ophioglossoides, and Hirsutella minnesotensis, another nematophagous fungus. Ascomycete nematopathogenicity is polyphyletic; D. coniospora represents a branch that has not been molecularly characterized. A detailed in silico functional analysis, comparing D. coniospora to 11 fungal species, revealed genes and gene families potentially involved in virulence and showed it to be a highly specialized pathogen. A targeted comparison with nematophagous fungi highlighted D. coniospora-specific genes and a core set of genes associated with nematode parasitism. A comparative gene expression analysis of samples from fungal spores and mycelia, and infected C. elegans, gave a molecular view of the different stages of the D. coniospora lifecycle. Transformation of D. coniospora allowed targeted gene knock-out and the production of fungus that expresses fluorescent reporter genes. It also permitted the initial characterisation of a potential fungal counter-defensive strategy, involving interference with a host antimicrobial mechanism. This high-quality annotated genome for D. coniospora gives insights into the evolution and virulence of nematode-destroying fungi. Coupled with genetic transformation, it opens the way for molecular dissection of D. coniospora physiology, and will allow both sides of the interaction between D. coniospora and C. elegans, as well as the evolutionary arms race that exists between pathogen and host, to be studied.

Cytosolic localization of NADH cytochrome b₅ oxidoreductase (Ncb5or)

Acyl-CoA desaturation in the endoplasmic reticulum (ER) membrane depends on cytosolic NADH or NADPH, whereas NADPH in the ER lumen is utilized by prereceptor glucocorticoid production. It was assumed that NADH cytochrome b5 oxidoreductase (Ncb5or) might connect Acyl-CoA desaturation to ER luminal redox. We aimed to clarify the ambiguous compartmentalization of Ncb5or and test the possible effect of stearoyl-CoA on microsomal NADPH level. Amino acid sequence analysis, fluorescence microscopy of GFP-tagged protein, immunocytochemistry, and western blot analysis of subcellular fractions unequivocally demonstrated that Ncb5or, either endogenous or exogenous, is localized in the cytoplasm and not in the ER lumen in cultured cells and liver tissue. Moreover, the involvement of ER-luminal reducing equivalents in stearoyl-CoA desaturation was excluded.

Evolution of short inverted repeat in cupressophytes, transfer of accD to nucleus in Sciadopitys verticillata and phylogenetic position of Sciadopityaceae

Sciadopitys verticillata is an evergreen conifer and an economically valuable tree used in construction, which is the only member of the family Sciadopityaceae. Acquisition of the S. verticillata chloroplast (cp) genome will be useful for understanding the evolutionary mechanism of conifers and phylogenetic relationships among gymnosperm. In this study, we have first reported the complete chloroplast genome of S. verticillata. The total genome is 138,284 bp in length, consisting of 118 unique genes. The S. verticillata cp genome has lost one copy of the canonical inverted repeats and shown distinctive genomic structure comparing with other cupressophytes. Fifty-three simple sequence repeat loci and 18 forward tandem repeats were identified in the S. verticillata cp genome. According to the rearrangement of cupressophyte cp genome, we proposed one mechanism for the formation of inverted repeat: tandem repeat occured first, then rearrangement divided the tandem repeat into inverted repeats located at different regions. Phylogenetic estimates inferred from 59-gene sequences and cpDNA organizations have both shown that S. verticillata was sister to the clade consisting of Cupressaceae, Taxaceae, and Cephalotaxaceae. Moreover, accD gene was found to be lost in the S. verticillata cp genome, and a nucleus copy was identified from two transcriptome data.

Finding the Subcellular Location of Barley, Wheat, Rice and Maize Proteins: The Compendium of Crop Proteins with Annotated Locations (cropPAL)

Barley, wheat, rice and maize provide the bulk of human nutrition and have extensive industrial use as agricultural products. The genomes of these crops each contains >40,000 genes encoding proteins; however, the major genome databases for these species lack annotation information of protein subcellular location for >80% of these gene products. We address this gap, by constructing the compendium of crop protein subcellular locations called crop Proteins with Annotated Locations (cropPAL). Subcellular location is most commonly determined by fluorescent protein tagging of live cells or mass spectrometry detection in subcellular purifications, but can also be predicted from amino acid sequence or protein expression patterns. The cropPAL database collates 556 published studies, from >300 research institutes in >30 countries that have been previously published, as well as compiling eight pre-computed subcellular predictions for all Hordeum vulgare, Triticum aestivum, Oryza sativa and Zea mays protein sequences. The data collection including metadata for proteins and published studies can be accessed through a search portal http://crop-PAL.org. The subcellular localization information housed in cropPAL helps to depict plant cells as compartmentalized protein networks that can be investigated for improving crop yield and quality, and developing new biotechnological solutions to agricultural challenges.

Broad 4-hydroxyphenylpyruvate dioxygenase inhibitor herbicide tolerance in soybean with an optimized enzyme and expression cassette

With an optimized expression cassette consisting of the soybean (Glycine max) native promoter modified for enhanced expression driving a chimeric gene coding for the soybean native amino-terminal 86 amino acids fused to an insensitive shuffled variant of maize (Zea mays) 4-hydroxyphenylpyruvate dioxygenase (HPPD), we achieved field tolerance in transgenic soybean plants to the HPPD-inhibiting herbicides mesotrione, isoxaflutole, and tembotrione. Directed evolution of maize HPPD was accomplished by progressively incorporating amino acids from naturally occurring diversity and novel substitutions identified by saturation mutagenesis, combined at random through shuffling. Localization of heterologously expressed HPPD mimicked that of the native enzyme, which was shown to be dually targeted to chloroplasts and the cytosol. Analysis of the native soybean HPPD gene revealed two transcription start sites, leading to transcripts encoding two HPPD polypeptides. The N-terminal region of the longer encoded peptide directs proteins to the chloroplast, while the short form remains in the cytosol. In contrast, maize HPPD was found almost exclusively in chloroplasts. Evolved HPPD enzymes showed insensitivity to five inhibitor herbicides. In 2013 field trials, transgenic soybean events made with optimized promoter and HPPD variant expression cassettes were tested with three herbicides and showed tolerance to four times the labeled rates of mesotrione and isoxaflutole and two times the labeled rates of tembotrione.

Annotation of a hybrid partial genome of the coffee rust (Hemileia vastatrix) contributes to the gene repertoire catalog of the Pucciniales

Coffee leaf rust caused by the fungus Hemileia vastatrix is the most damaging disease to coffee worldwide. The pathogen has recently appeared in multiple outbreaks in coffee producing countries resulting in significant yield losses and increases in costs related to its control. New races/isolates are constantly emerging as evidenced by the presence of the fungus in plants that were previously resistant. Genomic studies are opening new avenues for the study of the evolution of pathogens, the detailed description of plant-pathogen interactions and the development of molecular techniques for the identification of individual isolates. For this purpose we sequenced 8 different H. vastatrix isolates using NGS technologies and gathered partial genome assemblies due to the large repetitive content in the coffee rust hybrid genome; 74.4% of the assembled contigs harbor repetitive sequences. A hybrid assembly of 333 Mb was built based on the 8 isolates; this assembly was used for subsequent analyses. Analysis of the conserved gene space showed that the hybrid H. vastatrix genome, though highly fragmented, had a satisfactory level of completion with 91.94% of core protein-coding orthologous genes present. RNA-Seq from urediniospores was used to guide the de novo annotation of the H. vastatrix gene complement. In total, 14,445 genes organized in 3921 families were uncovered; a considerable proportion of the predicted proteins (73.8%) were homologous to other Pucciniales species genomes. Several gene families related to the fungal lifestyle were identified, particularly 483 predicted secreted proteins that represent candidate effector genes and will provide interesting hints to decipher virulence in the coffee rust fungus. The genome sequence of Hva will serve as a template to understand the molecular mechanisms used by this fungus to attack the coffee plant, to study the diversity of this species and for the development of molecular markers to distinguish races/isolates.

Rice DB: an Oryza Information Portal linking annotation, subcellular location, function, expression, regulation, and evolutionary information for rice and Arabidopsis

Omics research in Oryza sativa (rice) relies on the use of multiple databases to obtain different types of information to define gene function. We present Rice DB, an Oryza information portal that is a functional genomics database, linking gene loci to comprehensive annotations, expression data and the subcellular location of encoded proteins. Rice DB has been designed to integrate the direct comparison of rice with Arabidopsis (Arabidopsis thaliana), based on orthology or 'expressology', thus using and combining available information from two pre-eminent plant models. To establish Rice DB, gene identifiers (more than 40 types) and annotations from a variety of sources were compiled, functional information based on large-scale and individual studies was manually collated, hundreds of microarrays were analysed to generate expression annotations, and the occurrences of potential functional regulatory motifs in promoter regions were calculated. A range of computational subcellular localization predictions were also run for all putative proteins encoded in the rice genome, and experimentally confirmed protein localizations have been collated, curated and linked to functional studies in rice. A single search box allows anything from gene identifiers (for rice and/or Arabidopsis), motif sequences, subcellular location, to keyword searches to be entered, with the capability of Boolean searches (such as AND/OR). To demonstrate the utility of Rice DB, several examples are presented including a rice mitochondrial proteome, which draws on a variety of sources for subcellular location data within Rice DB. Comparisons of subcellular location, functional annotations, as well as transcript expression in parallel with Arabidopsis reveals examples of conservation between rice and Arabidopsis, using Rice DB (http://ricedb.plantenergy.uwa.edu.au).

Unravelling mitochondrial retrograde regulation in the abiotic stress induction of rice ALTERNATIVE OXIDASE 1 genes

Mitochondrial retrograde regulation (MRR) is the transduction of mitochondrial signals to mediate nuclear gene expression. It is not clear whether MRR is a common regulation mechanism in plant abiotic stress response. In this study, we analysed the early abiotic stress response of the rice OsAOX1 genes, and the induction of OsAOX1a and OsAOX1b (OsAOX1a/b) was selected as a working model for the stress-induced MRR studies. We found that the induction mediated by the superoxide ion (O2·(-) )-generating chemical methyl viologen was stronger than that of hydrogen peroxide (H2 O2 ). The addition of reactive oxygen species (ROS) scavengers demonstrated that the stress induction was reduced by eliminating O2·(-) . Furthermore, the stress induction did not rely on chloroplast- or cytosol-derived O2·(-) . Next, we generated transgenic plants overexpressing the superoxide dismutase (SOD) gene at different subcellular locations. The results suggest that only the mitochondrial SOD, OsMSD, attenuated the stress induction of OsAOX1a/b specifically. Therefore, our findings demonstrate that abiotic stress initiates the MRR on OsAOX1a/b and that mitochondrial O2·(-) is involved in the process.

Potential functional replacement of the plastidic acetyl-CoA carboxylase subunit (accD) gene by recent transfers to the nucleus in some angiosperm lineages

Eukaryotic cells originated when an ancestor of the nucleated cell engulfed bacterial endosymbionts that gradually evolved into the mitochondrion and the chloroplast. Soon after these endosymbiotic events, thousands of ancestral prokaryotic genes were functionally transferred from the endosymbionts to the nucleus. This process of functional gene relocation, now rare in eukaryotes, continues in angiosperms. In this article, we show that the chloroplastic acetyl-CoA carboxylase subunit (accD) gene that is present in the plastome of most angiosperms has been functionally relocated to the nucleus in the Campanulaceae. Surprisingly, the nucleus-encoded accD transcript is considerably smaller than the plastidic version, consisting of little more than the carboxylase domain of the plastidic accD gene fused to a coding region encoding a plastid targeting peptide. We verified experimentally the presence of a chloroplastic transit peptide by showing that the product of the nuclear accD fused to green fluorescent protein was imported in the chloroplasts. The nuclear gene regulatory elements that enabled the erstwhile plastidic gene to become functional in the nuclear genome were identified, and the evolution of the intronic and exonic sequences in the nucleus is described. Relocation and truncation of the accD gene is a remarkable example of the processes underpinning endosymbiotic evolution.

SUBA3: a database for integrating experimentation and prediction to define the SUBcellular location of proteins in Arabidopsis

The subcellular location database for Arabidopsis proteins (SUBA3, http://suba.plantenergy.uwa.edu.au) combines manual literature curation of large-scale subcellular proteomics, fluorescent protein visualization and protein-protein interaction (PPI) datasets with subcellular targeting calls from 22 prediction programs. More than 14 500 new experimental locations have been added since its first release in 2007. Overall, nearly 650 000 new calls of subcellular location for 35 388 non-redundant Arabidopsis proteins are included (almost six times the information in the previous SUBA version). A re-designed interface makes the SUBA3 site more intuitive and easier to use than earlier versions and provides powerful options to search for PPIs within the context of cell compartmentation. SUBA3 also includes detailed localization information for reference organelle datasets and incorporates green fluorescent protein (GFP) images for many proteins. To determine as objectively as possible where a particular protein is located, we have developed SUBAcon, a Bayesian approach that incorporates experimental localization and targeting prediction data to best estimate a protein's location in the cell. The probabilities of subcellular location for each protein are provided and displayed as a pictographic heat map of a plant cell in SUBA3.

Artificial neural network for the prediction of tyrosine-based sorting signal recognition by adaptor complexes

Sorting of transmembrane proteins to various intracellular compartments depends on specific signals present within their cytosolic domains. Among these sorting signals, the tyrosine-based motif (YXXØ) is one of the best characterized and is recognized by μ-subunits of the four clathrin-associated adaptor complexes (AP-1 to AP-4). Despite their overlap in specificity, each μ-subunit has a distinct sequence preference dependent on the nature of the X-residues. Moreover, combinations of these residues exert cooperative or inhibitory effects towards interaction with the various APs. This complexity makes it impossible to predict a priori, the specificity of a given tyrosine-signal for a particular μ-subunit. Here, we describe the results obtained with a computational approach based on the Artificial Neural Network (ANN) paradigm that addresses the issue of tyrosine-signal specificity, enabling the prediction of YXXØ-μ interactions with accuracies over 90%. Therefore, this approach constitutes a powerful tool to help predict mechanisms of intracellular protein sorting.

Analysis of the subcellular targeting of the smaller replicase protein of Pelargonium flower break virus

Replication of all positive RNA viruses occurs in association with intracellular membranes. In many cases, the mechanism of membrane targeting is unknown and there appears to be no correlation between virus phylogeny and the membrane systems recruited for replication. Pelargonium flower break virus (PFBV, genus Carmovirus, family Tombusviridae) encodes two proteins, p27 and its read-through product p86 (the viral RNA dependent-RNA polymerase), that are essential for replication. Recent reports with other members of the family Tombusviridae have shown that the smaller replicase protein is targeted to specific intracellular membranes and it is assumed to determine the subcellular localization of the replication complex. Using in vivo expression of green fluorescent protein (GFP) fusions in plant and yeast cells, we show here that PFBV p27 localizes in mitochondria. The same localization pattern was found for p86 that contains the p27 sequence at its N-terminus. Cellular fractionation of p27GFP-expressing cells confirmed the confocal microscopy observations and biochemical treatments suggested a tight association of the protein to membranes. Analysis of deletion mutants allowed identification of two regions required for targeting of p27 to mitochondria. These regions mapped toward the N- and C-terminus of the protein, respectively, and could function independently though with distinct efficiency. In an attempt to search for putative cellular factors involved in p27 localization, the subcellular distribution of the protein was checked in a selected series of knockout yeast strains and the outcome of this approach is discussed.

In silico identification and characterization of effector catalogs

Many characterized fungal effector proteins are small secreted proteins. Effectors are defined as those proteins that alter host cell structure and/or function by facilitating pathogen infection. The identification of effectors by molecular and cell biology techniques is a difficult task. However, with the availability of whole-genome sequences, these proteins can now be predicted in silico. Here, we describe in detail how to identify and characterize effectors from a defined fungal proteome using in silico techniques.

Evidence for widespread association of mammalian splicing and conserved long-range RNA structures

Pre-mRNA structure impacts many cellular processes, including splicing in genes associated with disease. The contemporary paradigm of RNA structure prediction is biased toward secondary structures that occur within short ranges of pre-mRNA, although long-range base-pairings are known to be at least as important. Recently, we developed an efficient method for detecting conserved RNA structures on the genome-wide scale, one that does not require multiple sequence alignments and works equally well for the detection of local and long-range base-pairings. Using an enhanced method that detects base-pairings at all possible combinations of splice sites within each gene, we now report RNA structures that could be involved in the regulation of splicing in mammals. Statistically, we demonstrate strong association between the occurrence of conserved RNA structures and alternative splicing, where local RNA structures are generally more frequent at alternative donor splice sites, while long-range structures are more associated with weak alternative acceptor splice sites. As an example, we validated the RNA structure in the human SF1 gene using minigenes in the HEK293 cell line. Point mutations that disrupted the base-pairing of two complementary boxes between exons 9 and 10 of this gene altered the splicing pattern, while the compensatory mutations that reestablished the base-pairing reverted splicing to that of the wild-type. There is statistical evidence for a Dscam-like class of mammalian genes, in which mutually exclusive RNA structures control mutually exclusive alternative splicing. In sum, we propose that long-range base-pairings carry an important, yet unconsidered part of the splicing code, and that, even by modest estimates, there must be thousands of such potentially regulatory structures conserved throughout the evolutionary history of mammals.

SCLpred: protein subcellular localization prediction by N-to-1 neural networks

SUMMARY

Knowledge of the subcellular location of a protein provides valuable information about its function and possible interaction with other proteins. In the post-genomic era, fast and accurate predictors of subcellular location are required if this abundance of sequence data is to be fully exploited. We have developed a subcellular localization predictor (SCLpred), which predicts the location of a protein into four classes for animals and fungi and five classes for plants (secreted, cytoplasm, nucleus, mitochondrion and chloroplast) using machine learning models trained on large non-redundant sets of protein sequences. The algorithm powering SCLpred is a novel Neural Network (N-to-1 Neural Network, or N1-NN) we have developed, which is capable of mapping whole sequences into single properties (a functional class, in this work) without resorting to predefined transformations, but rather by adaptively compressing the sequence into a hidden feature vector. We benchmark SCLpred against other publicly available predictors using two benchmarks including a new subset of Swiss-Prot Release 2010_06. We show that SCLpred surpasses the state of the art. The N1-NN algorithm is fully general and may be applied to a host of problems of similar shape, that is, in which a whole sequence needs to be mapped into a fixed-size array of properties, and the adaptive compression it operates may shed light on the space of protein sequences.

AVAILABILITY

The predictive systems described in this article are publicly available as a web server at http://distill.ucd.ie/distill/.

CONTACT

gianluca.pollastri@ucd.ie.

In silico survey of the mitochondrial protein uptake and maturation systems in the brown alga Ectocarpus siliculosus

The acquisition of mitochondria was a key event in eukaryote evolution. The aim of this study was to identify homologues of the components of the mitochondrial protein import machinery in the brown alga Ectocarpus and to use this information to investigate the evolutionary history of this fundamental cellular process. Detailed searches were carried out both for components of the protein import system and for related peptidases. Comparative and phylogenetic analyses were used to investigate the evolution of mitochondrial proteins during eukaryote diversification. Key observations include phylogenetic evidence for very ancient origins for many protein import components (Tim21, Tim50, for example) and indications of differences between the outer membrane receptors that recognize the mitochondrial targeting signals, suggesting replacement, rearrangement and/or emergence of new components across the major eukaryotic lineages. Overall, the mitochondrial protein import components analysed in this study confirmed a high level of conservation during evolution, indicating that most are derived from very ancient, ancestral proteins. Several of the protein import components identified in Ectocarpus, such as Tim21, Tim50 and metaxin, have also been found in other stramenopiles and this study suggests an early origin during the evolution of the eukaryotes.

In silico methods for identifying organellar and suborganellar targeting peptides in Arabidopsis chloroplast proteins and for predicting the topology of membrane proteins

Numerous experimental and in silico approaches have been developed for attempting to identify the -subcellular localisation of proteins. Approximately 2,000-4,000 proteins are thought to be targeted to plastids in plants, but a complete and unambiguous catalogue has yet to be drawn up. This article reviews the various prediction methods that identify plastid targeting sequences, and those that can help estimate location and topology within the plastid or plastid membranes. The most successful approaches are described in detail, with detailed notes to help avoid common pitfalls and advice on interpreting conflicting or ambiguous results. In most cases, it is best to try multiple approaches, and we also cover the powerful new integrated databases that provide a selected blend of experimental data and predictions.

A comprehensive assessment of N-terminal signal peptides prediction methods

Background

Amino-terminal signal peptides (SPs) are short regions that guide the targeting of secretory proteins to the correct subcellular compartments in the cell. They are cleaved off upon the passenger protein reaching its destination. The explosive growth in sequencing technologies has led to the deposition of vast numbers of protein sequences necessitating rapid functional annotation techniques, with subcellular localization being a key feature. Of the myriad software prediction tools developed to automate the task of assigning the SP cleavage site of these new sequences, we review here, the performance and reliability of commonly used SP prediction tools.

Results

The available signal peptide data has been manually curated and organized into three datasets representing eukaryotes, Gram-positive and Gram-negative bacteria. These datasets are used to evaluate thirteen prediction tools that are publicly available. SignalP (both the HMM and ANN versions) maintains consistency and achieves the best overall accuracy in all three benchmarking experiments, ranging from 0.872 to 0.914 although other prediction tools are narrowing the performance gap.

Conclusion

The majority of the tools evaluated in this study encounter no difficulty in discriminating between secretory and non-secretory proteins. The challenge clearly remains with pinpointing the correct SP cleavage site. The composite scoring schemes employed by SignalP may help to explain its accuracy. Prediction task is divided into a number of separate steps, thus allowing each score to tackle a particular aspect of the prediction.

Chloroplast proteins without cleavable transit peptides: rare exceptions or a major constituent of the chloroplast proteome?

Most chloroplast proteins (cp proteins) are nucleus-encoded, synthesized on cytosolic ribosomes as precursor proteins containing a presequence (cTP), and post-translationally imported via the Tic/Toc complex into the organelle, where the cTP is removed. Only a few unambiguous instances of cp proteins that do not require cTPs (non-canonical cp proteins) have been reported so far. However, the survey of data from large-scale proteomic studies presented here suggests that the fraction of such proteins in the total cp proteome might be as large as approximately 30%. To explore this discrepancy, we chose a representative set of 28 putative non-canonical cp proteins, and used in vitro import and Red Fluorescent Protein (RFP)-fusion assays to determine their sub-cellular destinations. Four proteins, including embryo defective 1211, glycolate oxidase 2, protein disulfide isomerase-like protein (PDII), and a putative glutathione S-transferase, could be unambiguously assigned to the chloroplast. Several others ('potential cp proteins') were found to be imported into chloroplasts in vitro, but failed to localize to the organelle when RFP was fused to their C-terminal ends. Extrapolations suggest that the fraction of cp proteins that enter the inner compartments of the organelle, although they lack a cTP, might be as large as 11.4% of the total cp proteome. Our data also support the idea that cytosolic proteins that associate with the cp outer membrane might account for false positive cp proteins obtained in earlier studies.

Mass spectrometric and computational analysis of cytokine-induced alterations in the astrocyte secretome

The roles of astrocytes in the CNS have been expanding beyond the long held view of providing passive, supportive functions. Recent evidence has identified roles in neuronal development, extracellular matrix maintenance, and response to inflammatory challenges. Therefore, insights into astrocyte secretion are critically important for understanding physiological responses and pathological mechanisms in CNS diseases. Primary astrocyte cultures were treated with inflammatory cytokines for either a short (1 day) or sustained (7 days) exposure. Increased interleukin-6 secretion, nitric oxide production, cyclooxygenase-2 activation, and nerve growth factor (NGF) secretion confirmed the astrocytic response to cytokine treatment. MS/MS analysis, computational prediction algorithms, and functional classification were used to compare the astrocyte protein secretome from control and cytokine-exposed cultures. In total, 169 secreted proteins were identified, including both classically and nonconventionally secreted proteins that comprised components of the extracellular matrix and enzymes involved in processing of glycoproteins and glycosaminoglycans. Twelve proteins were detected exclusively in the secretome from cytokine-treated astrocytes, including matrix metalloproteinase-3 (MMP-3) and members of the chemokine ligand family. This compilation of secreted proteins provides a framework for identifying factors that influence the biochemical environment of the nervous system, regulate development, construct extracellular matrices, and coordinate the nervous system response to inflammation.

Mapping metabolic and transcript temporal switches during germination in rice highlights specific transcription factors and the role of RNA instability in the germination process

Transcriptome and metabolite profiling of rice (Oryza sativa) embryo tissue during a detailed time course formed a foundation for examining transcriptional and posttranscriptional processes during germination. One hour after imbibition (HAI), independent of changes in transcript levels, rapid changes in metabolism occurred, including increases in hexose phosphates, tricarboxylic acid cycle intermediates, and gamma-aminobutyric acid. Later changes in the metabolome, including those involved in carbohydrate, amino acid, and cell wall metabolism, appeared to be driven by increases in transcript levels, given that the large group (over 6,000 transcripts) observed to increase from 12 HAI were enriched in metabolic functional categories. Analysis of transcripts encoding proteins located in the organelles of primary metabolism revealed that for the mitochondrial gene set, a greater proportion of transcripts peaked early, at 1 or 3 HAI, compared with the plastid set, and notably, many of these transcripts encoded proteins involved in transport functions. One group of over 2,000 transcripts displayed a unique expression pattern beginning with low levels in dry seeds, followed by a peak in expression levels at 1 or 3 HAI, before markedly declining at later time points. This group was enriched in transcription factors and signal transduction components. A subset of these transiently expressed transcription factors were further interrogated across publicly available rice array data, indicating that some were only expressed during the germination process. Analysis of the 1-kb upstream regions of transcripts displaying similar changes in abundance identified a variety of common sequence motifs, potential binding sites for transcription factors. Additionally, newly synthesized transcripts peaking at 3 HAI displayed a significant enrichment of sequence elements in the 3' untranslated region that have been previously associated with RNA instability. Overall, these analyses reveal that during rice germination, an immediate change in some metabolite levels is followed by a two-step, large-scale rearrangement of the transcriptome that is mediated by RNA synthesis and degradation and is accompanied by later changes in metabolite levels.

Predicting proteomes of mitochondria and related organelles from genomic and expressed sequence tag data

In eukaryotes, determination of the subcellular location of a novel protein encoded in genomic or transcriptomic data provides useful clues as to its possible function. However, experimental localization studies are expensive and time-consuming. As a result, accurate in silico prediction of subcellular localization from sequence data alone is an extremely important field of study in bioinformatics. This is especially so as genomic studies expand beyond model system organisms to encompass the full diversity of eukaryotes. Here we review some of the more commonly used programs for prediction of proteins that function in mitochondria, or mitochondrion-related organelles in diverse eukaryotic lineages and provide recommendations on how to apply these methods. Furthermore, we compare the predictive performance of these programs on a mixed set of mitochondrial and non-mitochondrial proteins. Although N-terminal targeting peptide prediction programs tend to have the highest accuracy, they cannot be effectively used for partial coding sequences derived from high-throughput expressed sequence tag surveys where data for the N-terminus of the encoded protein is often missing. Therefore methods that do not rely on the presence of an N-terminal targeting sequence alone are extremely useful, especially for expressed sequence tag data. The best strategy for classification of unknown proteins is to use multiple programs, incorporating a variety of prediction strategies, and closely examine the predictions with an understanding of how each of those programs will likely handle the data.

An Rh1-GFP fusion protein is in the cytoplasmic membrane of a white mutant strain of Chlamydomonas reinhardtii

The major Rhesus (Rh) protein of the green alga Chlamydomonas reinhardtii, Rh1, is homologous to Rh proteins of humans. It is an integral membrane protein involved in transport of carbon dioxide. To localize a fusion of intact Rh1 to the green fluorescent protein (GFP), we used as host a white (lts1) mutant strain of C. reinhardtii, which is blocked at the first step of carotenoid biosynthesis. The lts1 mutant strain accumulated normal amounts of Rh1 heterotrophically in the dark and Rh1-GFP was at the periphery of the cell co-localized with the cytoplasmic membrane dye FM4-64. Although Rh1 carries a potential chloroplast targeting sequence at its N-terminus, Rh1-GFP was clearly not associated with the chloroplast envelope membrane. Moreover, the N-terminal half of the protein was not imported into chloroplasts in vitro and N-terminal regions of Rh1 did not direct import of the small subunit of ribulose bisphosphate carboxylase (SSU). Despite caveats to this interpretation, which we discuss, current evidence indicates that Rh1 is a cytoplasmic membrane protein and that Rh1-GFP is among the first cytoplasmic membrane protein fusions to be obtained in C. reinhardtii. Although lts1 (white) mutant strains cannot be used to localize proteins within sub-compartments of the chloroplast because they lack thylakoid membranes, they should nonetheless be valuable for localizing many GFP fusions in Chlamydomonas.

Targeting of nucleus-encoded proteins to chloroplasts in plants

Most chloroplast proteins are encoded in the nucleus and synthesized on free, cytosolic ribosomes in precursor form. Each precursor has an amino-terminal extension called a transit peptide, which directs the protein through a post-translational targeting pathway and is removed upon arrival inside the organelle. This 'protein import' process is mediated by the coordinate action of two multiprotein complexes, one in each of the envelope membranes: the TOC and TIC (Translocon at the Outer/ Inner envelope membrane of Chloroplasts) machines. Many components of these complexes have been identified biochemically in pea; these include transit peptide receptors, channel proteins, and molecular chaperones. Intriguingly, the Arabidopsis genome encodes multiple, homologous genes for receptor components of the TOC complex. Careful analysis indicated that the different receptor isoforms operate in different import pathways with distinct precursor recognition specificities. These 'substrate-specific' import pathways might play a role in the differentiation of different plastid types, and/or act to prevent deleterious competition effects between abundant and nonabundant precursors. Until recently, all proteins destined for internal chloroplast compartments were thought to possess a cleavable transit peptide, and to engage the TOC/TIC machinery. New studies using proteomics and other approaches have revealed that this is far from true. Remarkably, a significant number of chloroplast proteins are transported via a pathway that involves the endoplasmic reticulum and Golgi apparatus. Other recent reports have elucidated an intriguing array of protein targeting routes leading to the envelope membranes themselves.

LocateP: genome-scale subcellular-location predictor for bacterial proteins

Background

In the past decades, various protein subcellular-location (SCL) predictors have been developed. Most of these predictors, like TMHMM 2.0, SignalP 3.0, PrediSi and Phobius, aim at the identification of one or a few SCLs, whereas others such as CELLO and Psortb.v.2.0 aim at a broader classification. Although these tools and pipelines can achieve a high precision in the accurate prediction of signal peptides and transmembrane helices, they have a much lower accuracy when other sequence characteristics are concerned. For instance, it proved notoriously difficult to identify the fate of proteins carrying a putative type I signal peptidase (SPIase) cleavage site, as many of those proteins are retained in the cell membrane as N-terminally anchored membrane proteins. Moreover, most of the SCL classifiers are based on the classification of the Swiss-Prot database and consequently inherited the inconsistency of that SCL classification. As accurate and detailed SCL prediction on a genome scale is highly desired by experimental researchers, we decided to construct a new SCL prediction pipeline: LocateP.

Results

LocateP combines many of the existing high-precision SCL identifiers with our own newly developed identifiers for specific SCLs. The LocateP pipeline was designed such that it mimics protein targeting and secretion processes. It distinguishes 7 different SCLs within Gram-positive bacteria: intracellular, multi-transmembrane, N-terminally membrane anchored, C-terminally membrane anchored, lipid-anchored, LPxTG-type cell-wall anchored, and secreted/released proteins. Moreover, it distinguishes pathways for Sec- or Tat-dependent secretion and alternative secretion of bacteriocin-like proteins. The pipeline was tested on data sets extracted from literature, including experimental proteomics studies. The tests showed that LocateP performs as well as, or even slightly better than other SCL predictors for some locations and outperforms current tools especially where the N-terminally anchored and the SPIase-cleaved secreted proteins are concerned. Overall, the accuracy of LocateP was always higher than 90%. LocateP was then used to predict the SCLs of all proteins encoded by completed Gram-positive bacterial genomes. The results are stored in the database LocateP-DB [1].

Conclusion

LocateP is by far the most accurate and detailed protein SCL predictor for Gram-positive bacteria currently available.

Proteome analysis of Arabidopsis leaf peroxisomes reveals novel targeting peptides, metabolic pathways, and defense mechanisms

We have established a protocol for the isolation of highly purified peroxisomes from mature Arabidopsis thaliana leaves and analyzed the proteome by complementary gel-based and gel-free approaches. Seventy-eight nonredundant proteins were identified, of which 42 novel proteins had previously not been associated with plant peroxisomes. Seventeen novel proteins carried predicted peroxisomal targeting signals (PTS) type 1 or type 2; 11 proteins contained PTS-related peptides. Peroxisome targeting was supported for many novel proteins by in silico analyses and confirmed for 11 representative full-length fusion proteins by fluorescence microscopy. The targeting function of predicted and unpredicted signals was investigated and SSL>, SSI>, and ASL> were established as novel functional PTS1 peptides. In contrast with the generally accepted confinement of PTS2 peptides to the N-terminal domain, the bifunctional transthyretin-like protein was demonstrated to carry internally a functional PTS2. The novel enzymes include numerous enoyl-CoA hydratases, short-chain dehydrogenases, and several enzymes involved in NADP and glutathione metabolism. Seven proteins, including beta-glucosidases and myrosinases, support the currently emerging evidence for an important role of leaf peroxisomes in defense against pathogens and herbivores. The data provide new insights into the biology of plant peroxisomes and improve the prediction accuracy of peroxisome-targeted proteins from genome sequences.

Locating proteins in the cell using TargetP, SignalP and related tools

Determining the subcellular localization of a protein is an important first step toward understanding its function. Here, we describe the properties of three well-known N-terminal sequence motifs directing proteins to the secretory pathway, mitochondria and chloroplasts, and sketch a brief history of methods to predict subcellular localization based on these sorting signals and other sequence properties. We then outline how to use a number of internet-accessible tools to arrive at a reliable subcellular localization prediction for eukaryotic and prokaryotic proteins. In particular, we provide detailed step-by-step instructions for the coupled use of the amino-acid sequence-based predictors TargetP, SignalP, ChloroP and TMHMM, which are all hosted at the Center for Biological Sequence Analysis, Technical University of Denmark. In addition, we describe and provide web references to other useful subcellular localization predictors. Finally, we discuss predictive performance measures in general and the performance of TargetP and SignalP in particular.

Computational classification of classically secreted proteins

The ability to identify classically secreted proteins is an important component of targeted therapeutic studies and the discovery of circulating biomarkers. Here, we review some of the most recent programs available for the in silico prediction of secretory proteins, the performance of which is benchmarked with an independent set of annotated human proteins. The description of these programs and the results of this benchmarking provide insights into the most recently developed prediction programs, which will enable investigators to make more informed decisions about which program best addresses their research needs.