SPdb--a signal peptide database

Characteristics of Corynespora cassiicola, the causal agent of tobacco Corynespora leaf spot, revealed by genomic and metabolic phenomic analysis

Corynespora cassiicola is a highly diverse fungal pathogen that commonly occurs in tropical, subtropical, and greenhouse environments worldwide. In this study, the isolates were identified as C. cassiicola, and the optimum growth and sporulation were studied. The phenotypic characteristics of C. cassiicola, concerning 950 different growth conditions, were tested using Biolog PM plates 1-10. In addition, the strain of C. cassiicola DWZ from tobacco hosts was sequenced for the using Illumina PE150 and Pacbio technologies. The host resistance of tobacco Yunyan 87 with different maturity levels was investigated. In addition, the resistance evaluation of 10 common tobacco varieties was investigated. The results showed that C. cassiicola metabolized 89.47% of the tested carbon source, 100% of the nitrogen source, 100% of the phosphorus source, and 97.14% of the sulfur source. It can adapt to a variety of different osmotic pressure and pH environments, and has good decarboxylase and deaminase activities. The optimum conditions for pathogen growth and sporulation were 25-30 °C, and the growth was better on AEA and OA medium. The total length of the genome was 45.9 Mbp, the GC content was 51.23%, and a total of 13,061 protein-coding genes, 202 non-coding RNAs and 2801 and repeat sequences were predicted. Mature leaves were more susceptible than proper mature and immature leaves, and the average diameter of diseased spots reached 17.74 mm at 12 days. None of the tested ten cultivars exhibited obvious resistance to Corynespora leaf spot of tobacco, whereby all disease spot diameters reached > 10 mm and > 30 mm when at 5 and 10 days after inoculation, respectively. The phenotypic characteristics, genomic analysis of C. cassiicola and the cultivar resistance assessment of this pathogen have increased our understanding of Corynespora leaf spot of tobacco.

Secretome Analysis: Reading Cellular Sign Language to Understand Intercellular Communication

A significant portion of mammalian proteomes is secreted to the extracellular space to fulfill crucial roles in cell-to-cell communication. To best recapitulate the intricate and multi-faceted crosstalk between cells in a live organism, there is an ever-increasing need for methods to study protein secretion in model systems that include multiple cell types. In addition, posttranslational modifications further expand the complexity and versatility of cellular communication. This review aims to summarize recent strategies and model systems that employ cellular coculture, chemical biology tools, protein enrichment, and proteomic methods to characterize the composition and function of cellular secretomes. This is all geared towards gaining better understanding of organismal biology in vivo mediated by secretory signaling.

Increasing the Efficiency of the Accumulation of Recombinant Proteins in Plant Cells: The Role of Transport Signal Peptides

The problem with increasing the yield of recombinant proteins is resolvable using different approaches, including the transport of a target protein to cell compartments with a low protease activity. In the cell, protein targeting involves short-signal peptide sequences recognized by intracellular protein transport systems. The main systems of the protein transport across membranes of the endoplasmic reticulum and endosymbiotic organelles are reviewed here, as are the major types and structure of the signal sequences targeting proteins to the endoplasmic reticulum and its derivatives, to plastids, and to mitochondria. The role of protein targeting to certain cell organelles depending on specific features of recombinant proteins and the effect of this targeting on the protein yield are discussed, in addition to the main directions of the search for signal sequences based on their primary structure. This knowledge makes it possible not only to predict a protein localization in the cell but also to reveal the most efficient sequences with potential biotechnological utility.

DGPD: a knowledge database of dense granule proteins of the Apicomplexa

Apicomplexan parasites cause severe diseases in human and livestock. Dense granule proteins (GRAs), specific to the Apicomplexa, participate in the maintenance of intracellular parasitism of host cells. GRAs have better immunogenicity and they can be emerged as important players in vaccine development. Although studies on GRAs have increased gradually in recent years, due to incompleteness and complexity of data collection, biologists have difficulty in the comprehensive utilization of information. Thus, there is a desperate need of user-friendly resource to integrate with existing GRAs. In this paper, we developed the Dense Granule Protein Database (DGPD), the first knowledge database dedicated to the integration and analysis of typical GRAs properties. The current version of DGPD includes annotated GRAs metadata of 245 samples derived from multiple web repositories and literature mining, involving five species that cause common diseases (Plasmodium falciparum, Toxoplasma gondii, Hammondia hammondi, Neospora caninum and Cystoisospora suis). We explored the baseline characteristics of GRAs and found that the number of introns and transmembrane domains in GRAs are markedly different from those of non-GRAs. Furthermore, we utilized the data in DGPD to explore the prediction algorithms for GRAs. We hope DGPD will be a good database for researchers to study GRAs.

Database URL: http://dgpd.tlds.cc/DGPD/index/

Rational Discovery of Antimicrobial Peptides by Means of Artificial Intelligence

Antibiotic resistance is a worldwide public health problem due to the costs and mortality rates it generates. However, the large pharmaceutical industries have stopped searching for new antibiotics because of their low profitability, given the rapid replacement rates imposed by the increasingly observed resistance acquired by microorganisms. Alternatively, antimicrobial peptides (AMPs) have emerged as potent molecules with a much lower rate of resistance generation. The discovery of these peptides is carried out through extensive in vitro screenings of either rational or non-rational libraries. These processes are tedious and expensive and generate only a few AMP candidates, most of which fail to show the required activity and physicochemical properties for practical applications. This work proposes implementing an artificial intelligence algorithm to reduce the required experimentation and increase the efficiency of high-activity AMP discovery. Our deep learning (DL) model, called AMPs-Net, outperforms the state-of-the-art method by 8.8% in average precision. Furthermore, it is highly accurate to predict the antibacterial and antiviral capacity of a large number of AMPs. Our search led to identifying two unreported antimicrobial motifs and two novel antimicrobial peptides related to them. Moreover, by coupling DL with molecular dynamics (MD) simulations, we were able to find a multifunctional peptide with promising therapeutic effects. Our work validates our previously proposed pipeline for a more efficient rational discovery of novel AMPs.

Synthetic Biology and Computer-Based Frameworks for Antimicrobial Peptide Discovery

Antibiotic resistance is one of the greatest challenges of our time. This global health problem originated from a paucity of truly effective antibiotic classes and an increased incidence of multi-drug-resistant bacterial isolates in hospitals worldwide. Indeed, it has been recently estimated that 10 million people will die annually from drug-resistant infections by the year 2050. Therefore, the need to develop out-of-the-box strategies to combat antibiotic resistance is urgent. The biological world has provided natural templates, called antimicrobial peptides (AMPs), which exhibit multiple intrinsic medical properties including the targeting of bacteria. AMPs can be used as scaffolds and, via engineering, can be reconfigured for optimized potency and targetability toward drug-resistant pathogens. Here, we review the recent development of tools for the discovery, design, and production of AMPs and propose that the future of peptide drug discovery will involve the convergence of computational and synthetic biology principles.

The endoplasmic reticulum P5A-ATPase is a transmembrane helix dislocase

Organelle identity depends on protein composition. How mistargeted proteins are selectively recognized and removed from organelles is incompletely understood. Here, we found that the orphan P5A-adenosine triphosphatase (ATPase) transporter ATP13A1 (Spf1 in yeast) directly interacted with the transmembrane segment (TM) of mitochondrial tail-anchored proteins. P5A-ATPase activity mediated the extraction of mistargeted proteins from the endoplasmic reticulum (ER). Cryo-electron microscopy structures of Saccharomyces cerevisiae Spf1 revealed a large, membrane-accessible substrate-binding pocket that alternately faced the ER lumen and cytosol and an endogenous substrate resembling an α-helical TM. Our results indicate that the P5A-ATPase could dislocate misinserted hydrophobic helices flanked by short basic segments from the ER. TM dislocation by the P5A-ATPase establishes an additional class of P-type ATPase substrates and may correct mistakes in protein targeting or topogenesis.

Two Tachykinin-Related Peptides with Antimicrobial Activity Isolated from Triatoma infestans Hemolymph

Antimicrobial peptides and proteins (AMPs) are molecules that can interact with microbial cells and lead to membrane disruption or intracellular molecule interactions and death. Several molecules with antimicrobial effects also present other biological activities. One such protein group representing the duplicity of activities is the tachykinin family. Tachykinins (TKs) form a family of neuropeptides in vertebrates with a consensus C-terminal region (F-X-G-Y-R-NH2). Invertebrate TKs and TK-related peptides (TKRPs) are subfamilies found in invertebrates that present high homology with TKs and have similar biological effects. Several of these molecules have already been described but reports of TKRP in Hemiptera species are limited. By analyzing the Triatoma infestans hemolymph by reversed-phase high-performance liquid chromatography, biological assays, and mass spectrometry, two antimicrobial molecules were isolated and identified as TKRPs, which we named as TRP1-TINF and TRP2-TINF (tachykinin-related peptides I and II from T. infestans). TRP1-TINF is a random secondary structure peptide with 9 amino acid residues. It is susceptible to aminopeptidases degradation and is active mainly against Micrococcus luteus (32 μM). TRP2-TINF is a 10-amino acid peptide with a 310 helix secondary structure and is susceptible to carboxypeptidases degradation. It has major antimicrobial activity against both Pseudomonas aeruginosa and Escherichia coli (45 μM). Neither molecule is toxic to human erythrocytes and both present minor toxicity toward Vero cells at a concentration of 1000 μM. As the first description of TKRPs with antimicrobial activity in T. infestans, this work contributes to the wider comprehension of the insects’ physiology and describes pharmacological relevant molecules.

MtSSPdb: The Medicago truncatula Small Secreted Peptide Database

A growing number of small secreted peptides (SSPs) in plants are recognized as important regulatory molecules with roles in processes such as growth, development, reproduction, stress tolerance, and pathogen defense. Recent discoveries further implicate SSPs in regulating root nodule development, which is of particular significance for legumes. SSP-coding genes are frequently overlooked, because genome annotation pipelines generally ignore small open reading frames, which are those most likely to encode SSPs. Also, SSP-coding small open reading frames are often expressed at low levels or only under specific conditions, and thus are underrepresented in non-tissue-targeted or non-condition-optimized RNA-sequencing projects. We previously identified 4,439 SSP-encoding genes in the model legume Medicago truncatula To support systematic characterization and annotation of these putative SSP-encoding genes, we developed the M. truncatula Small Secreted Peptide Database (MtSSPdb; https://mtsspdb.noble.org/). MtSSPdb currently hosts (1) a compendium of M. truncatula SSP candidates with putative function and family annotations; (2) a large-scale M. truncatula RNA-sequencing-based gene expression atlas integrated with various analytical tools, including differential expression, coexpression, and pathway enrichment analyses; (3) an online plant SSP prediction tool capable of analyzing protein sequences at the genome scale using the same protocol as for the identification of SSP genes; and (4) information about a library of synthetic peptides and root and nodule phenotyping data from synthetic peptide screens in planta. These datasets and analytical tools make MtSSPdb a unique and valuable resource for the plant research community. MtSSPdb also has the potential to become the most complete database of SSPs in plants.

Analysis of Soybean Long Non-Coding RNAs Reveals a Subset of Small Peptide-Coding Transcripts

Long non-coding RNAs (lncRNAs) are defined as non-protein-coding transcripts that are at least 200 nucleotides long. They are known to play pivotal roles in regulating gene expression, especially during stress responses in plants. We used a large collection of in-house transcriptome data from various soybean (Glycine max and Glycine soja) tissues treated under different conditions to perform a comprehensive identification of soybean lncRNAs. We also retrieved publicly available soybean transcriptome data that were of sufficient quality and sequencing depth to enrich our analysis. In total, RNA-sequencing data of 332 samples were used for this analysis. An integrated reference-based, de novo transcript assembly was developed that identified ∼69,000 lncRNA gene loci. We showed that lncRNAs are distinct from both protein-coding transcripts and genomic background noise in terms of length, number of exons, transposable element composition, and sequence conservation level across legume species. The tissue-specific and time-specific transcriptional responses of the lncRNA genes under some stress conditions may suggest their biological relevance. The transcription start sites of lncRNA gene loci tend to be close to their nearest protein-coding genes, and they may be transcriptionally related to the protein-coding genes, particularly for antisense and intronic lncRNAs. A previously unreported subset of small peptide-coding transcripts was identified from these lncRNA loci via tandem mass spectrometry, which paved the way for investigating their functional roles. Our results also highlight the present inadequacy of the bioinformatic definition of lncRNA, which excludes those lncRNA gene loci with small open reading frames from being regarded as protein-coding.

Extension of the Pompe mutation database by linking disease-associated variants to clinical severity

Pompe disease is an autosomal recessive lysosomal storage disorder caused by disease‐associated variants in the acid alpha‐glucosidase (GAA) gene. The current Pompe mutation database provides a severity rating of GAA variants based on in silico predictions and expression studies. Here, we extended the database with clinical information of reported phenotypes. We added additional in silico predictions for effects on splicing and protein function and for cross reactive immunologic material (CRIM) status, minor allele frequencies, and molecular analyses. We analyzed 867 patients and 562 GAA variants. Based on their combination with a GAA null allele (i.e., complete deficiency of GAA enzyme activity), 49% of the 422 disease‐associated variants could be linked to classic infantile, childhood, or adult phenotypes. Predictions and immunoblot analyses identified 131 CRIM negative and 216 CRIM positive variants. While disease‐associated missense variants were found throughout the GAA protein, they were enriched up to seven‐fold in the catalytic site. Fifteen percent of disease‐associated missense variants were predicted to affect splicing. This should be confirmed using splicing assays. Inclusion of clinical severity rating in the Pompe mutation database provides an invaluable tool for diagnosis, prognosis of disease progression, treatment regimens, and the future development of personalized medicine for Pompe disease.

A comprehensive in silico characterization of bacterial signal peptides for the excretory production of Anabaena variabilis phenylalanine ammonia lyase in Escherichia coli

Anabaena variabilis double mutant (C503S/C565S) phenylalanine ammonia-lyase (PAL) is an appealing enzyme in the enzyme-replacement therapy of phenylketonuria. Yet abundant production of this enzyme has been of concern for industrial production. In this study, we have characterized 1175 bacterial signal peptides (SPs) and identified the most efficient ones for the excretory production of mutant AvPAL. Analysis by SignalP 4.1 revealed that more than 61% of SPs had a D-score greater than 0.7, denoting to be highly efficient. The optimum length of a bacterial SP was 25-30. The preferable net positive charge and the second residue of N-region were + 2 and Lys/Arg, respectively. Highly efficient SPs possessed 3-5 Leus in their H-region and A/L/VXA-FF cleavage site. Highly efficient SPs were from Escherichia coli, corroborating the necessity of an agreement between SPs and the host. Physiochemical characterization of mutant AvPAL conjugates via ProtParam and PROSOII, revealed that ~ 99.5% of proteins would not be entraped in inclusion bodies. Secretory pathways were identified by EffectiveDB and more than 98% of SPs were cleavable. Chimeras were modeled using the I-TASSER program, being evaluated by the Ramachandran plots. The mRNA secondary structure of mutant AvPAL upon linkage to SPs was assessed using the mfold program. It was shown that the linkage of a SP does not affect mutant AvPAL's stability at the protein or mRNA level. AllergenFP tool demonstrated that chimeras were not allergen. SPs, including FMF4_ECOLX, E2BB_ECOLX, and LPTA_ECOLI exhibited the highest propensity for secretion and appropriate features in all analyses.

In Silico Tools and Databases for Designing Peptide-Based Vaccine and Drugs

The prolonged conventional approaches of drug screening and vaccine designing prerequisite patience, vigorous effort, outrageous cost as well as additional manpower. Screening and experimentally validating thousands of molecules for a specific therapeutic property never proved to be an easy task. Similarly, traditional way of vaccination includes administration of either whole or attenuated pathogen, which raises toxicity and safety issues. Emergence of sequencing and recombinant DNA technology led to the epitope-based advanced vaccination concept, i.e., small peptides (epitope) can stimulate specific immune response. Advent of bioinformatics proved to be an adjunct in vaccine and drug designing. Genomic study of pathogens aid to identify and analyze the protective epitope. A number of in silico tools have been developed to design immunotherapy as well as peptide-based drugs in the last two decades. These tools proved to be a catalyst in drug and vaccine designing. This review solicits therapeutic peptide databases as well as in silico tools developed for designing peptide-based vaccine and drugs.

Bovine Milk Comparative Proteome Analysis from Early, Mid, and Late Lactation in the Cattle Breed, Malnad Gidda (Bos indicus)

Bovine milk is important for both veterinary medicine and human nutrition. Understanding the bovine milk proteome at different stages of lactation has therefore broad significance for integrative biology and clinical medicine as well. Indeed, different lactation stages have marked influence on the milk yield, milk constituents, and nourishment of the neonates. We performed a comparative proteome analysis of the bovine milk obtained at different stages of lactation from the Indian indigenous cattle Malnad Gidda (Bos indicus), a widely available breed. The milk differential proteome during the lactation stages in B. indicus has not been investigated to date. Using high-resolution mass spectrometry-based quantitative proteomics of the bovine whey proteins at early, mid, and late lactation stages, we identified a total of 564 proteins, out of which 403 proteins were found to be differentially abundant at different lactation stages. As is expected of any body fluid proteome, 51% of the proteins identified in the milk were found to have signal peptides. Gene ontology analyses were carried out to categorize proteins altered across different lactation stages based on biological process and molecular function, which enabled us to correlate their significance in each lactation stage. We also investigated the potential pathways enriched in different lactation stages using bioinformatics pathway analysis tools. To the best of our knowledge, this study represents the first and largest inventory of milk proteins identified to date for an Indian cattle breed. We believe that the current study broadly informs both veterinary omics research and the emerging field of nutriproteomics during lactation stages.

Identification and analysis of the cleavage site in a signal peptide using SMOTE, dagging, and feature selection methods

Several machine learning algorithms were adopted to investigate cleavage sites in a signal peptide. An optimal dagging based classifier was constructed and 870 important features were deemed to be important for this classifier.

Structure and topology around the cleavage site regulate post-translational cleavage of the HIV-1 gp160 signal peptide

Like all other secretory proteins, the HIV-1 envelope glycoprotein gp160 is targeted to the endoplasmic reticulum (ER) by its signal peptide during synthesis. Proper gp160 folding in the ER requires core glycosylation, disulfide-bond formation and proline isomerization. Signal-peptide cleavage occurs only late after gp160 chain termination and is dependent on folding of the soluble subunit gp120 to a near-native conformation. We here detail the mechanism by which co-translational signal-peptide cleavage is prevented. Conserved residues from the signal peptide and residues downstream of the canonical cleavage site form an extended alpha-helix in the ER membrane, which covers the cleavage site, thus preventing cleavage. A point mutation in the signal peptide breaks the alpha helix allowing co-translational cleavage. We demonstrate that postponed cleavage of gp160 enhances functional folding of the molecule. The change to early cleavage results in decreased viral fitness compared to wild-type HIV.

An att site-based recombination reporter system for genome engineering and synthetic DNA assembly

Background

Direct manipulation of the genome is a widespread technique for genetic studies and synthetic biology applications. The tyrosine and serine site-specific recombination systems of bacteriophages HK022 and ΦC31 are widely used for stable directional exchange and relocation of DNA sequences, making them valuable tools in these contexts. We have developed site-specific recombination tools that allow the direct selection of recombination events by embedding the attB site from each system within the β-lactamase resistance coding sequence (bla).

Results

The HK and ΦC31 tools were developed by placing the attB sites from each system into the signal peptide cleavage site coding sequence of bla. All possible open reading frames (ORFs) were inserted and tested for recombination efficiency and bla activity. Efficient recombination was observed for all tested ORFs (3 for HK, 6 for ΦC31) as shown through a cointegrate formation assay. The bla gene with the embedded attB site was functional for eight of the nine constructs tested.

Conclusions

The HK/ΦC31 att-bla system offers a simple way to directly select recombination events, thus enhancing the use of site-specific recombination systems for carrying out precise, large-scale DNA manipulation, and adding useful tools to the genetics toolbox. We further show the power and flexibility of bla to be used as a reporter for recombination.

Neprosin, a Selective Prolyl Endoprotease for Bottom-up Proteomics and Histone Mapping

Trypsin dominates bottom-up proteomics, but there are reasons to consider alternative enzymes. Improving sequence coverage, exposing proteomic "dark matter," and clustering post-translational modifications in different ways and with higher-order drive the pursuit of reagents complementary to trypsin. Additionally, enzymes that are easy to use and generate larger peptides that capitalize upon newer fragmentation technologies should have a place in proteomics. We expressed and characterized recombinant neprosin, a novel prolyl endoprotease of the DUF239 family, which preferentially cleaves C-terminal to proline residues under highly acidic conditions. Cleavage also occurs C-terminal to alanine with some frequency, but with an intriguingly high "skipping rate." Digestion proceeds to a stable end point, resulting in an average peptide mass of 2521 units and a higher dependence upon electron-transfer dissociation for peptide-spectrum matches. In contrast to most proline-cleaving enzymes, neprosin effectively degrades proteins of any size. For 1251 HeLa cell proteins identified in common using trypsin, Lys-C, and neprosin, almost 50% of the neprosin sequence contribution is unique. The high average peptide mass coupled with cleavage at residues not usually modified provide new opportunities for profiling clusters of post-translational modifications. We show that neprosin is a useful reagent for reading epigenetic marks on histones. It generates peptide 1-38 of histone H3 and peptide 1-32 of histone H4 in a single digest, permitting the analysis of co-occurring post-translational modifications in these important N-terminal tails.

Kingdom-Wide Analysis of Fungal Small Secreted Proteins (SSPs) Reveals their Potential Role in Host Association

Fungal secretome consists of various functional groups of proteins, many of which participate in nutrient acquisition, self-protection, or manipulation of the environment and neighboring organisms. The least characterized component of the secretome is small secreted proteins (SSPs). Some SSPs have been reported to function as effectors, but most remain to be characterized. The composition of major secretome components, such as carbohydrate-active enzymes, proteases, lipases, and oxidoreductases, appear to reflect the lifestyle and ecological niche of individual species. We hypothesize that many SSPs participate in manipulating plants as effectors. Obligate biotrophs likely encode more and diverse effector-like SSPs to suppress host defense compared to necrotrophs, which generally use cell wall degrading enzymes and phytotoxins to kill hosts. Because different secretome prediction workflows have been used in different studies, available secretome data are difficult to integrate for comprehensive comparative studies to test this hypothesis. In this study, SSPs encoded by 136 fungal species were identified from data archived in Fungal Secretome Database (FSD) via a refined secretome workflow. Subsequently, compositions of SSPs and other secretome components were compared in light of taxa and lifestyles. Those species that are intimately associated with host cells, such as biotrophs and symbionts, usually have higher proportion of species-specific SSPs (SSSPs) than hemibiotrophs and necrotrophs, but the latter groups displayed higher proportions of secreted enzymes. Results from our study established a foundation for functional studies on SSPs and will also help understand genomic changes potentially underpinning different fungal lifestyles.

LocSigDB: a database of protein localization signals

LocSigDB (http://genome.unmc.edu/LocSigDB/) is a manually curated database of experimental protein localization signals for eight distinct subcellular locations; primarily in a eukaryotic cell with brief coverage of bacterial proteins. Proteins must be localized at their appropriate subcellular compartment to perform their desired function. Mislocalization of proteins to unintended locations is a causative factor for many human diseases; therefore, collection of known sorting signals will help support many important areas of biomedical research. By performing an extensive literature study, we compiled a collection of 533 experimentally determined localization signals, along with the proteins that harbor such signals. Each signal in the LocSigDB is annotated with its localization, source, PubMed references and is linked to the proteins in UniProt database along with the organism information that contain the same amino acid pattern as the given signal. From LocSigDB webserver, users can download the whole database or browse/search for data using an intuitive query interface. To date, LocSigDB is the most comprehensive compendium of protein localization signals for eight distinct subcellular locations.

Database URL: http://genome.unmc.edu/LocSigDB/

BactPepDB: a database of predicted peptides from a exhaustive survey of complete prokaryote genomes

With the recent progress in complete genome sequencing, mining the increasing amount of genomic information available should in theory provide the means to discover new classes of peptides. However, annotation pipelines often do not consider small reading frames likely to be expressed. BactPepDB, available online at http://bactpepdb.rpbs.univ-paris-diderot.fr, is a database that aims at providing an exhaustive re-annotation of all complete prokaryotic genomes—chromosomal and plasmid DNA—available in RefSeq for coding sequences ranging between 10 and 80 amino acids. The identified peptides are classified as (i) previously identified in RefSeq, (ii) entity-overlapping (intragenic) or intergenic, and (iii) potential pseudogenes—intergenic sequences corresponding to a portion of a previously annotated larger gene. Additional information is related to homologs within order, predicted signal sequence, transmembrane segments, disulfide bonds, secondary structure, and the existence of a related 3D structure in the Protein Databank. As a result, BactPepDB provides insights about candidate peptides, and provides information about their conservation, together with some of their expected biological/structural features. The BactPepDB interface allows to search for candidate peptides in the database, or to search for peptides similar to a query, according to the multiple properties predicted or related to genomic localization.

Database URL:http://www.yeastgenome.org/

Secretome analysis reveals effector candidates associated with broad host range necrotrophy in the fungal plant pathogen Sclerotinia sclerotiorum

BACKGROUND

The white mold fungus Sclerotinia sclerotiorum is a devastating necrotrophic plant pathogen with a remarkably broad host range. The interaction of necrotrophs with their hosts is more complex than initially thought, and still poorly understood.

RESULTS

We combined bioinformatics approaches to determine the repertoire of S. sclerotiorum effector candidates and conducted detailed sequence and expression analyses on selected candidates. We identified 486 S. sclerotiorum secreted protein genes expressed in planta, many of which have no predicted enzymatic activity and may be involved in the interaction between the fungus and its hosts. We focused on those showing (i) protein domains and motifs found in known fungal effectors, (ii) signatures of positive selection, (iii) recent gene duplication, or (iv) being S. sclerotiorum-specific. We identified 78 effector candidates based on these properties. We analyzed the expression pattern of 16 representative effector candidate genes on four host plants and revealed diverse expression patterns.

CONCLUSIONS

These results reveal diverse predicted functions and expression patterns in the repertoire of S. sclerotiorum effector candidates. They will facilitate the functional analysis of fungal pathogenicity determinants and should prove useful in the search for plant quantitative disease resistance components active against the white mold.

Enhanced functional expression of aquaporin Z via fusion of in situ cleavable leader peptides in Escherichia coli cell-free system

Aquaporin Z (AqpZ) is a water channel protein from Escherichia coli and has attracted many attentions to develop the biomimetic water filtration technology. Cell-free protein synthesis (CFPS) system, one of the most complex multi-enzymatic systems, has the ability of producing the integral membrane protein in vitro. To enhance the synthesis of AqpZ in E. coli cell-free system, several natural leader peptides were respectively fused at the N-terminus and were verified to enhance the expression level significantly. Moreover, the supplementation of detergents or liposome could activate leader peptidase from the cell-free extract and provide hydrophobic environment for proper folding of AqpZ. Thus, the release of mature AqpZ via the in situ removal of leader peptide was achieved, with a specific water transport activity of (2.1 ± 0.1) × 10⁻¹⁴ cm³ s⁻¹ monomer⁻¹. Using this in situ removable leader peptide strategy, the transcription-translation, leader sequence cleavage and membrane protein folding were integrated into a simple process in the cell-free system, providing a convenient approach to enhance the expression of target proteins, especially those membrane proteins difficult to achieve.

Structure and mechanism of Escherichia coli type I signal peptidase

Type I signal peptidase is the enzyme responsible for cleaving off the amino-terminal signal peptide from proteins that are secreted across the bacterial cytoplasmic membrane. It is an essential membrane bound enzyme whose serine/lysine catalytic dyad resides on the exo-cytoplasmic surface of the bacterial membrane. This review discusses the progress that has been made in the structural and mechanistic characterization of Escherichia coli type I signal peptidase (SPase I) as well as efforts to develop a novel class of antibiotics based on SPase I inhibition. This article is part of a Special Issue entitled: Protein trafficking and secretion in bacteria. Guest Editors: Anastassios Economou and Ross Dalbey.

Simple re-instantiation of small databases using cloud computing

Background

Small bioinformatics databases, unlike institutionally funded large databases, are vulnerable to discontinuation and many reported in publications are no longer accessible. This leads to irreproducible scientific work and redundant effort, impeding the pace of scientific progress.

Results

We describe a Web-accessible system, available online at http://biodb100.apbionet.org, for archival and future on demand re-instantiation of small databases within minutes. Depositors can rebuild their databases by downloading a Linux live operating system (http://www.bioslax.com), preinstalled with bioinformatics and UNIX tools. The database and its dependencies can be compressed into an ".lzm" file for deposition. End-users can search for archived databases and activate them on dynamically re-instantiated BioSlax instances, run as virtual machines over the two popular full virtualization standard cloud-computing platforms, Xen Hypervisor or vSphere. The system is adaptable to increasing demand for disk storage or computational load and allows database developers to use the re-instantiated databases for integration and development of new databases.

Conclusions

Herein, we demonstrate that a relatively inexpensive solution can be implemented for archival of bioinformatics databases and their rapid re-instantiation should the live databases disappear.

TIMPs of parasitic helminths - a large-scale analysis of high-throughput sequence datasets

BACKGROUND

Tissue inhibitors of metalloproteases (TIMPs) are a multifunctional family of proteins that orchestrate extracellular matrix turnover, tissue remodelling and other cellular processes. In parasitic helminths, such as hookworms, TIMPs have been proposed to play key roles in the host-parasite interplay, including invasion of and establishment in the vertebrate animal hosts. Currently, knowledge of helminth TIMPs is limited to a small number of studies on canine hookworms, whereas no information is available on the occurrence of TIMPs in other parasitic helminths causing neglected diseases.

METHODS

In the present study, we conducted a large-scale investigation of TIMP proteins of a range of neglected human parasites including the hookworm Necator americanus, the roundworm Ascaris suum, the liver flukes Clonorchis sinensis and Opisthorchis viverrini, as well as the schistosome blood flukes. This entailed mining available transcriptomic and/or genomic sequence datasets for the presence of homologues of known TIMPs, predicting secondary structures of defined protein sequences, systematic phylogenetic analyses and assessment of differential expression of genes encoding putative TIMPs in the developmental stages of A. suum, N. americanus and Schistosoma haematobium which infect the mammalian hosts.

RESULTS

A total of 15 protein sequences with high homology to known eukaryotic TIMPs were predicted from the complement of sequence data available for parasitic helminths and subjected to in-depth bioinformatic analyses.

CONCLUSIONS

Supported by the availability of gene manipulation technologies such as RNA interference and/or transgenesis, this work provides a basis for future functional explorations of helminth TIMPs and, in particular, of their role/s in fundamental biological pathways linked to long-term establishment in the vertebrate hosts, with a view towards the development of novel approaches for the control of neglected helminthiases.

How many signal peptides are there in bacteria?

Over the last 5 years proteogenomics (using mass spectroscopy to identify proteins predicted from genomic sequences) has emerged as a promising approach to the high-throughput identification of protein N-termini, which remains a problem in genome annotation. Comparison of the experimentally determined N-termini with those predicted by sequence analysis tools allows identification of the signal peptides and therefore conclusions on the cytoplasmic or extracytoplasmic (periplasmic or extracellular) localization of the respective proteins. We present here the results of a proteogenomic study of the signal peptides in Escherichia coli K-12 and compare its results with the available experimental data and predictions by such software tools as SignalP and Phobius. A single proteogenomics experiment recovered more than a third of all signal peptides that had been experimentally determined during the past three decades and confirmed at least 31 additional signal peptides, mostly in the known exported proteins, which had been previously predicted but not validated. The filtering of putative signal peptides for the peptide length and the presence of an eight-residue hydrophobic patch and a typical signal peptidase cleavage site proved sufficient to eliminate the false-positive hits. Surprisingly, the results of this proteogenomics study, as well as a re-analysis of the E. coli genome with the latest version of SignalP program, show that the fraction of proteins containing signal peptides is only about 10%, or half of previous estimates.

OrysPSSP: a comparative platform for small secreted proteins from rice and other plants

Plants have large diverse families of small secreted proteins (SSPs) that play critical roles in the processes of development, differentiation, defense, flowering, stress response, symbiosis, etc. Oryza sativa is one of the major crops worldwide and an excellent model for monocotyledonous plants. However, there had not been any effort to systematically analyze rice SSPs. Here, we constructed a comparative platform, OrysPSSP (http://www.genoportal.org/PSSP/index.do), involving >100 000 SSPs from rice and 25 plant species. OrysPSSP is composed of a core SSP database and a dynamic web interface that integrates a variety of user tools and resources. The current release (v0530) of core SSP database contains a total of 101 048 predicted SSPs, which were generated through a rigid computation/curation pipeline. The web interface consists of eight different modules, providing users with rich resources/functions, e.g. browsing SSP by chromosome, searching and filtering SSP, validating SSP with omics data, comparing SSP among multiple species and querying core SSP database with BLAST. Some cases of application are discussed to demonstrate the utility of OrysPSSP. OrysPSSP serves as a comprehensive resource to explore SSP on the genome scale and across the phylogeny of plant species.

A deep exploration of the transcriptome and "excretory/secretory" proteome of adult Fascioloides magna

Parasitic liver flukes of the family Fasciolidae are responsible for major socioeconomic losses worldwide. However, at present, knowledge of the fundamental molecular biology of these organisms is scant. Here, we characterize, for the first time, the transcriptome and secreted proteome of the adult stage of the "giant liver fluke," Fascioloides magna, using Illumina sequencing technology and one-dimensional SDS-PAGE and OFFGEL protein electrophoresis, respectively. A total of ∼54,000,000 reads were generated and assembled into ∼39,000 contiguous sequences (contigs); ∼20,000 peptides were predicted and classified based on homology searches, protein motifs, gene ontology, and biological pathway mapping. From the predicted proteome, 48.1% of proteins could be assigned to 384 biological pathway terms, including "spliceosome," "RNA transport," and "endocytosis." Putative proteins involved in amino acid degradation were most abundant. Of the 835 secreted proteins predicted from the transcriptome of F. magna, 80 were identified in the excretory/secretory products from this parasite. Highly represented were antioxidant proteins, followed by peptidases (particularly cathepsins) and proteins involved in carbohydrate metabolism. The integration of transcriptomic and proteomic datasets generated herein sets the scene for future studies aimed at exploring the potential role(s) that molecules might play at the host-parasite interface and for establishing novel strategies for the treatment or control of parasitic fluke infections.

Identification of Peptide lv, a novel putative neuropeptide that regulates the expression of L-type voltage-gated calcium channels in photoreceptors

Neuropeptides are small protein-like signaling molecules with diverse roles in regulating neural functions such as sleep/wake cycles, pain modulation, synaptic plasticity, and learning and memory. Numerous drugs designed to target neuropeptides, their receptors, or relevant pathways have been developed in the past few decades. Hence, the discovery and characterization of new neuropeptides and their functions have received considerable attention from scientific research. Computational bioinformatics coupled with functional assays are powerful tools to address the difficulties in discovering new bioactive peptides. In this study, a new bioinformatic strategy was designed to screen full length human and mouse cDNA databases to search for novel peptides. One was discovered and named peptide Lv because of its ability to enhance L-type voltage-gated calcium channel (L-VGCC) currents in retinal photoreceptors. Using matrix-assisted laser desorption/ionization-time of flight mass spectrometry (MALDI-TOF MS), peptide Lv was detected in the culture media, which indicated that it was secreted from 661W cells transfected with the gene. In vitro treatments with either glutathione S-transferase (GST) fusion peptide Lv or synthesized peptide Lv enhanced L-VGCC channel activities in cone photoreceptors. At the molecular level, peptide Lv stimulated cAMP production, enhanced phosphorylation of extracellular signal-regulated kinase (ERK), and increased the protein expression of L-VGCCα1 subunits in cone photoreceptors. Therefore, the biological activities of peptide Lv may be very important in the modulation of L-VGCC dependent neural plasticity.

Computational comparative study of tuberculosis proteomes using a model learned from signal peptide structures

Secretome analysis is important in pathogen studies. A fundamental and convenient way to identify secreted proteins is to first predict signal peptides, which are essential for protein secretion. However, signal peptides are highly complex functional sequences that are easily confused with transmembrane domains. Such confusion would obviously affect the discovery of secreted proteins. Transmembrane proteins are important drug targets, but very few transmembrane protein structures have been determined experimentally; hence, prediction of the structures is essential. In the field of structure prediction, researchers do not make assumptions about organisms, so there is a need for a general signal peptide predictor.To improve signal peptide prediction without prior knowledge of the associated organisms, we present a machine-learning method, called SVMSignal, which uses biochemical properties as features, as well as features acquired from a novel encoding, to capture biochemical profile patterns for learning the structures of signal peptides directly.We tested SVMSignal and five popular methods on two benchmark datasets from the SPdb and UniProt/Swiss-Prot databases, respectively. Although SVMSignal was trained on an old dataset, it performed well, and the results demonstrate that learning the structures of signal peptides directly is a promising approach. We also utilized SVMSignal to analyze proteomes in the entire HAMAP microbial database. Finally, we conducted a comparative study of secretome analysis on seven tuberculosis-related strains selected from the HAMAP database. We identified ten potential secreted proteins, two of which are drug resistant and four are potential transmembrane proteins.SVMSignal is publicly available at http://bio-cluster.iis.sinica.edu.tw/SVMSignal. It provides user-friendly interfaces and visualizations, and the prediction results are available for download.

Crystal structure of Bacillus subtilis signal peptide peptidase A

Signal peptide peptidase A (SppA) is a membrane-bound self-compartmentalized serine protease that functions to cleave the remnant signal peptides left behind after protein secretion and cleavage by signal peptidases. SppA is found in plants, archaea and bacteria. Here, we report the first crystal structure of a Gram-positive bacterial SppA. The 2.4-Å-resolution structure of Bacillus subtilis SppA (SppA(BS)) catalytic domain reveals eight SppA(BS) molecules in the asymmetric unit, forming a dome-shaped octameric complex. The octameric state of SppA(BS) is supported by analytical size-exclusion chromatography and multi-angle light scattering analysis. Our sequence analysis, mutagenesis and activity assays are consistent with Ser147 serving as the nucleophile and Lys199 serving as the general base; however, they are located in different region of the protein, more than 29 Å apart. Only upon assembling the octamer do the serine and lysine come within close proximity, with neighboring protomers each providing one-half of the catalytic dyad, thus producing eight separate active sites within the complex, twice the number seen within Escherichia coli SppA (SppA(EC)). The SppA(BS) S1 substrate specificity pocket is deep, narrow and hydrophobic, but with a polar bottom. The S3 pocket, which is constructed from two neighboring proteins, is shallower, wider and more polar than the S1 pocket. A comparison of these pockets to those seen in SppA(EC) reveals a significant difference in the size and shape of the S1 pocket, which we show is reflected in the repertoire of peptides the enzymes are capable of cleaving.

Insights into SCP/TAPS proteins of liver flukes based on large-scale bioinformatic analyses of sequence datasets

BACKGROUND

SCP/TAPS proteins of parasitic helminths have been proposed to play key roles in fundamental biological processes linked to the invasion of and establishment in their mammalian host animals, such as the transition from free-living to parasitic stages and the modulation of host immune responses. Despite the evidence that SCP/TAPS proteins of parasitic nematodes are involved in host-parasite interactions, there is a paucity of information on this protein family for parasitic trematodes of socio-economic importance.

METHODOLOGY/PRINCIPAL FINDINGS

We conducted the first large-scale study of SCP/TAPS proteins of a range of parasitic trematodes of both human and veterinary importance (including the liver flukes Clonorchis sinensis, Opisthorchis viverrini, Fasciola hepatica and F. gigantica as well as the blood flukes Schistosoma mansoni, S. japonicum and S. haematobium). We mined all current transcriptomic and/or genomic sequence datasets from public databases, predicted secondary structures of full-length protein sequences, undertook systematic phylogenetic analyses and investigated the differential transcription of SCP/TAPS genes in O. viverrini and F. hepatica, with an emphasis on those that are up-regulated in the developmental stages infecting the mammalian host.

CONCLUSIONS

This work, which sheds new light on SCP/TAPS proteins, guides future structural and functional explorations of key SCP/TAPS molecules associated with diseases caused by flatworms. Future fundamental investigations of these molecules in parasites and the integration of structural and functional data could lead to new approaches for the control of parasitic diseases.

Signal peptidase I: cleaving the way to mature proteins

Signal peptidase I (SPase I) is critical for the release of translocated preproteins from the membrane as they are transported from a cytoplasmic site of synthesis to extracytoplasmic locations. These proteins are synthesized with an amino-terminal extension, the signal sequence, which directs the preprotein to the Sec- or Tat-translocation pathway. Recent evidence indicates that the SPase I cleaves preproteins as they emerge from either pathway, though the steps involved are unclear. Now that the structure of many translocation pathway components has been elucidated, it is critical to determine how these components work in concert to support protein translocation and cleavage. Molecular modeling and NMR studies have provided insight on how the preprotein docks on SPase I in preparation for cleavage. This is a key area for future work since SPase I enzymes in a variety of species have now been identified and the inhibition of these enzymes by antibiotics is being pursued. The eubacterial SPase I is essential for cell viability and belongs to a unique group of serine endoproteases which utilize a Ser-Lys catalytic dyad instead of the prototypical Ser-His-Asp triad used by eukaryotes. As such, SPase I is a desirable antimicrobial target. Advances in our understanding of how the preprotein interfaces with SPase I during the final stages of translocation will facilitate future development of inhibitors that display a high efficacy against SPase I function.

SProtP: a web server to recognize those short-lived proteins based on sequence-derived features in human cells

Protein turnover metabolism plays important roles in cell cycle progression, signal transduction, and differentiation. Those proteins with short half-lives are involved in various regulatory processes. To better understand the regulation of cell process, it is important to study the key sequence-derived factors affecting short-lived protein degradation. Until now, most of protein half-lives are still unknown due to the difficulties of traditional experimental methods in measuring protein half-lives in human cells. To investigate the molecular determinants that affect short-lived proteins, a computational method was proposed in this work to recognize short-lived proteins based on sequence-derived features in human cells. In this study, we have systematically analyzed many features that perhaps correlated with short-lived protein degradation. It is found that a large fraction of proteins with signal peptides and transmembrane regions in human cells are of short half-lives. We have constructed an SVM-based classifier to recognize short-lived proteins, due to the fact that short-lived proteins play pivotal roles in the control of various cellular processes. By employing the SVM model on human dataset, we achieved 80.8% average sensitivity and 79.8% average specificity, respectively, on ten testing dataset (TE1-TE10). We also obtained 89.9%, 99% and 83.9% of average accuracy on an independent validation datasets iTE1, iTE2 and iTE3 respectively. The approach proposed in this paper provides a valuable alternative for recognizing the short-lived proteins in human cells, and is more accurate than the traditional N-end rule. Furthermore, the web server SProtP (http://reprod.njmu.edu.cn/sprotp) has been developed and is freely available for users.