The Swiss-Prot protein knowledgebase and ExPASy: providing the plant community with high quality proteomic data and tools

Genome assembly and resequencing shed light on evolution, population selection, and sex identification in Vernicia montana

Vernicia montana is a dioecious plant widely cultivated for high-quality tung oil production and ornamental purposes in the Euphorbiaceae family. The lack of genomic information has severely hindered molecular breeding for genetic improvement and early sex identification in V. montana. Here, we present a chromosome-level reference genome of a male V. montana with a total size of 1.29 Gb and a contig N50 of 3.69 Mb. Genome analysis revealed that different repeat lineages drove the expansion of genome size. The model of chromosome evolution in the Euphorbiaceae family suggests that polyploidization-induced genomic structural variation reshaped the chromosome structure, giving rise to the diverse modern chromosomes. Based on whole-genome resequencing data and analyses of selective sweep and genetic diversity, several genes associated with stress resistance and flavonoid synthesis such as CYP450 genes and members of the LRR-RLK family, were identified and presumed to have been selected during the evolutionary process. Genome-wide association studies were conducted and a putative sex-linked insertion and deletion (InDel) (Chr 2: 102 799 917-102 799 933 bp) was identified and developed as a polymorphic molecular marker capable of effectively detecting the gender of V. montana. This InDel is located in the second intron of VmBASS4, suggesting a possible role of VmBASS4 in sex determination in V. montana. This study sheds light on the genome evolution and sex identification of V. montana, which will facilitate research on the development of agronomically important traits and genomics-assisted breeding.

Metabolite-based genome-wide association studies enable the dissection of the genetic bases of flavonoids, betaine and spermidine in wolfberry (Lycium)

Wolfberry is a plant with medicinal and food values. However, its bioactive ingredients and the corresponding genetic bases have not been determined. Here, we de novo generated a chromosome-level genome assembly for wolfberry, yielding a genome sequence of ~1.77 Gb with contig N50 of 50.55 Mb and 39 224 predicted gene models. A variation map, using 307 re-sequenced accessions, was called based on this genome assembly. Furthermore, the fruit metabolome of these accessions was profiled using 563 annotated metabolites, which separated Lycium barbarum L. and non-L. barbarum L. The flavonoids, coumarins, alkaloids and nicotinic acid contents were higher in the former than in the latter. A metabolite-based genome-wide association study mapped 156 164 significant single nucleotide polymorphisms corresponding to 340 metabolites. This included 19 219 unique lead single nucleotide polymorphisms in 1517 significant association loci, of which three metabolites, flavonoids, betaine and spermidine, were highlighted. Two candidate genes, LbUGT (evm.TU.chr07.2692) and LbCHS (evm.TU.chr07.2738), with non-synonymous mutations, were associated with the flavonoids content. LbCHS is a structural gene that interacts with a nearby MYB transcription factor (evm.TU.chr07.2726) both in L. barbarum and L. ruthenicum. Thus, these three genes might be involved in the biosynthesis/metabolism of flavonoids. LbSSADH (evm.TU.chr09.627) was identified as possibly participating in betaine biosynthesis/metabolism. Four lycibarbarspermidines (E-G and O) were identified, and only the lycibarbarspermidines O content was higher in L. barbarum varieties than in non-L. barbarum varieties. The evm.TU.chr07.2680 gene associated with lycibarbarspermidines O was annotated as an acetyl-CoA-benzylalcohol acetyltransferase, suggesting that it is a candidate gene for spermidine biosynthesis. These results provide novel insights into the specific metabolite profile of non-L. barbarum L. and the genetic bases of flavonoids, betaine and spermidine biosynthesis/metabolism.

Identification of annotation artifacts concerning the chalcone synthase (CHS)

OBJECTIVE

Chalcone synthase (CHS) catalyzes the initial step of the flavonoid biosynthesis. The CHS encoding gene is well studied in numerous plant species. Rapidly growing sequence databases contain hundreds of CHS entries that are the result of automatic annotation. In this study, we evaluated apparent multiplication of CHS domains in CHS gene models of four plant species.

MAIN FINDINGS

CHS genes with an apparent triplication of the CHS domain encoding part were discovered through database searches. Such genes were found in Macadamia integrifolia, Musa balbisiana, Musa troglodytarum, and Nymphaea colorata. A manual inspection of the CHS gene models in these four species with massive RNA-seq data suggests that these gene models are the result of artificial fusions in the annotation process. While there are hundreds of seemingly correct CHS records in the databases, it is not clear why these annotation artifacts appeared.

Genome-Wide Characterization and Analysis of bHLH Transcription Factors Related to Anthocyanin Biosynthesis in Cinnamomum camphora ('Gantong 1')

Cinnamomum camphora is one of the most commonly used tree species in landscaping. Improving its ornamental traits, particularly bark and leaf colors, is one of the key breeding goals. The basic helix-loop-helix (bHLH) transcription factors (TFs) are crucial in controlling anthocyanin biosynthesis in many plants. However, their role in C. camphora remains largely unknown. In this study, we identified 150 bHLH TFs (CcbHLHs) using natural mutant C. camphora 'Gantong 1', which has unusual bark and leaf colors. Phylogenetic analysis revealed that 150 CcbHLHs were divided into 26 subfamilies which shared similar gene structures and conserved motifs. According to the protein homology analysis, we identified four candidate CcbHLHs that were highly conserved compared to the TT8 protein in A. thaliana. These TFs are potentially involved in anthocyanin biosynthesis in C. camphora. RNA-seq analysis revealed specific expression patterns of CcbHLHs in different tissue types. Furthermore, we verified expression patterns of seven CcbHLHs (CcbHLH001, CcbHLH015, CcbHLH017, CcbHLH022, CcbHLH101, CcbHLH118, and CcbHLH134) in various tissue types at different growth stages using qRT-PCR. This study opens a new avenue for subsequent research on anthocyanin biosynthesis regulated by CcbHLH TFs in C. camphora.

Cyclitol metabolism is a central feature of Burkholderia leaf symbionts

The symbioses between plants of the Rubiaceae and Primulaceae families with Burkholderia bacteria represent unique and intimate plant-bacterial relationships. Many of these interactions have been identified through PCR-dependent typing methods, but there is little information available about their functional and ecological roles. We assembled 17 new endophyte genomes representing endophytes from 13 plant species, including those of two previously unknown associations. Genomes of leaf endophytes belonging to Burkholderia s.l. show extensive signs of genome reduction, albeit to varying degrees. Except for one endophyte, none of the bacterial symbionts could be isolated on standard microbiological media. Despite their taxonomic diversity, all endophyte genomes contained gene clusters linked to the production of specialized metabolites, including genes linked to cyclitol sugar analog metabolism and in one instance non-ribosomal peptide synthesis. These genes and gene clusters are unique within Burkholderia s.l. and are likely horizontally acquired. We propose that the acquisition of secondary metabolite gene clusters through horizontal gene transfer is a prerequisite for the evolution of a stable association between these endophytes and their hosts.

Utilizing Proteomic Approach to Analyze Potential Antioxidant Proteins in Plant against Irradiation

Gamma-ray irradiation is an effective and clean method of sterilization by inactivating microorganisms. It can also be applied to induce anti-oxidants for future application. In this study, the mung bean (Vigna radiata) was exposed to gamma-ray irradiation under the dose of 0, 5 or 10 kGy. With increasing irradiation doses, the concentrations of malondiadehyde decreased while the levels of total flavonoids and DPPH (1,1-diphenyl-2-picrylhydrazyl) radical scavenging activity increased. It has been shown that consuming flavonoids can provide protective effects. In addition, proteomic analysis identified several proteins having anti-oxidant activities in the 5 kGy irradiated group. These proteins are Apocytochrome f, Systemin receptor SR 160, DELLA protein DWARF8, DEAD-box ATP-dependent RNA helicase 9, ζ-carotene desaturase (ZDS), and Floral homeotic protein AGAMOUS. Our findings indicate that plants contain a variety of phytochemicals and antioxidant proteins which may effectively prevent oxidative stress caused by irradiated peroxidation.

Comparative Proteomics Reveals the Difference in Root Cold Resistance between Vitis. riparia × V. labrusca and Cabernet Sauvignon in Response to Freezing Temperature

Grapevines, bearing fruit containing large amounts of bioactive metabolites that offer health benefits, are widely cultivated around the world. However, the cold damage incurred when grown outside in extremely low temperatures during the overwintering stage limits the expansion of production. Although the morphological, biochemical, and molecular levels in different Vitis species exposed to different temperatures have been investigated, differential expression of proteins in roots is still limited. Here, the roots of cold-resistant (Vitis. riparia × V. labrusca, T1) and cold-sensitive varieties (Cabernet Sauvignon, T3) at -4 °C, and also at -15 °C for the former (T2), were measured by iTRAQ-based proteomic analysis. Expression levels of genes encoding candidate proteins were validated by qRT-PCR, and the root activities during different treatments were determined using a triphenyl tetrazolium chloride method. The results show that the root activity of the cold-resistant variety was greater than that of the cold-sensitive variety, and it declined with the decrease in temperature. A total of 25 proteins were differentially co-expressed in T2 vs. T1 and T1 vs. T3, and these proteins were involved in stress response, bio-signaling, metabolism, energy, and translation. The relative expression levels of the 13 selected genes were consistent with their fold-change values of proteins. The signature translation patterns for the roots during spatio-temporal treatments of different varieties at different temperatures provide insight into the differential mechanisms of cold resistance of grapevine.

A High-Density Genetic Map Enables Genome Synteny and QTL Mapping of Vegetative Growth and Leaf Traits in Gardenia

The gardenia is a traditional medicinal horticultural plant in China, but its molecular genetic research has been largely hysteretic. Here, we constructed an F₁ population with 200 true hybrid individuals. Using the genotyping-by-sequencing method, a high-density sex-average genetic map was generated that contained 4,249 SNPs with a total length of 1956.28 cM and an average genetic distance of 0.46 cM. We developed 17 SNP-based Kompetitive Allele-Specific PCR markers and found that 15 SNPs were successfully genotyped, of which 13 single-nucleotide polymorphism genotypings of 96 F₁ individuals showed genotypes consistent with GBS-mined genotypes. A genomic collinearity analysis between gardenia and the Rubiaceae species Coffea arabica, Coffea canephora and Ophiorrhiza pumila showed the relativity strong conservation of LG11 with NC_039,919.1, HG974438.1 and Bliw01000011.1, respectively. Lastly, a quantitative trait loci analysis at three phenotyping time points (2019, 2020, and 2021) yielded 18 QTLs for growth-related traits and 31 QTLs for leaf-related traits, of which qBSBN7-1, qCD8 and qLNP2-1 could be repeatably detected. Five QTL regions (qCD8 and qSBD8, qBSBN7 and qSI7, qCD4-1 and qLLLS4, qLNP10 and qSLWS10-2, qSBD10 and qLLLS10) with potential pleiotropic effects were also observed. This study provides novel insight into molecular genetic research and could be helpful for further gene cloning and marker-assisted selection for early growth and development traits in the gardenia.

NLPEI: A Novel Self-Interacting Protein Prediction Model Based on Natural Language Processing and Evolutionary Information

The study of protein self-interactions (SIPs) can not only reveal the function of proteins at the molecular level, but is also crucial to understand activities such as growth, development, differentiation, and apoptosis, providing an important theoretical basis for exploring the mechanism of major diseases. With the rapid advances in biotechnology, a large number of SIPs have been discovered. However, due to the long period and high cost inherent to biological experiments, the gap between the identification of SIPs and the accumulation of data is growing. Therefore, fast and accurate computational methods are needed to effectively predict SIPs. In this study, we designed a new method, NLPEI, for predicting SIPs based on natural language understanding theory and evolutionary information. Specifically, we first understand the protein sequence as natural language and use natural language processing algorithms to extract its features. Then, we use the Position-Specific Scoring Matrix (PSSM) to represent the evolutionary information of the protein and extract its features through the Stacked Auto-Encoder (SAE) algorithm of deep learning. Finally, we fuse the natural language features of proteins with evolutionary features and make accurate predictions by Extreme Learning Machine (ELM) classifier. In the SIPs gold standard data sets of human and yeast, NLPEI achieved 94.19% and 91.29% prediction accuracy. Compared with different classifier models, different feature models, and other existing methods, NLPEI obtained the best results. These experimental results indicated that NLPEI is an effective tool for predicting SIPs and can provide reliable candidates for biological experiments.

Probing periodontal microbial dark matter using metataxonomics and metagenomics

Our view of the periodontal microbial community has been shaped by a century or more of cultivation-based and microscopic investigations. While these studies firmly established the infection-mediated etiology of periodontal diseases, it was apparent from the very early days that periodontal microbiology suffered from what Staley and Konopka described as the "great plate count anomaly", in that these culturable bacteria were only a minor part of what was visible under the microscope. For nearly a century, much effort has been devoted to finding the right tools to investigate this uncultivated majority, also known as "microbial dark matter". The discovery that DNA was an effective tool to "see" microbial dark matter was a significant breakthrough in environmental microbiology, and oral microbiologists were among the earliest to capitalize on these advances. By identifying the order in which nucleotides are arranged in a stretch of DNA (DNA sequencing) and creating a repository of these sequences, sequence databases were created. Computational tools that used probability-driven analysis of these sequences enabled the discovery of new and unsuspected species and ascribed novel functions to these species. This review will trace the development of DNA sequencing as a quantitative, open-ended, comprehensive approach to characterize microbial communities in their native environments, and explore how this technology has shifted traditional dogmas on how the oral microbiome promotes health and its role in disease causation and perpetuation.

Bacterial Metabolites Produced Under Iron Limitation Kill Pinewood Nematode and Attract Caenorhabditis elegans

Pine Wilt Disease (PWD) is caused by Bursaphelenchus xylophilus, the pinewood nematode, and affects several species of pine trees worldwide. The ecosystem of the Pinus pinaster trees was investigated as a source of bacteria producing metabolites affecting this ecosystem: P. pinaster trees as target-plant, nematode as disease effector and its insect-vector as shuttle. For example, metals and metal-carrying compounds contribute to the complex tree-ecosystems. This work aimed to detect novel secondary metabolites like metallophores and related molecules produced under iron limitation by PWD-associated bacteria and to test their activity on nematodes. After screening 357 bacterial strains from Portugal and United States, two promising metallophore-producing strains Erwinia sp. A41C3 and Rouxiella sp. Arv20#4.1 were chosen and investigated in more detail. The genomes of these strains were sequenced, analyzed, and used to detect genetic potential for secondary metabolite production. A combinatorial approach of liquid chromatography-coupled tandem mass spectrometry (LC-MS) linked to molecular networking was used to describe these compounds. Two major metabolites were detected by HPLC analyses and described. One HPLC fraction of strain Arv20#4.1 showed to be a hydroxamate-type siderophore with higher affinity for chelation of Cu. The HPLC fraction of strain A41C3 with highest metal affinity showed to be a catecholate-type siderophore with higher affinity for chelation of Fe. LC-MS allowed the identification of several desferrioxamines from strain Arv20#4.1, in special desferrioxamine E, but no hit was obtained in case of strain A41C3 which might indicate that it is something new. Bacteria and their culture supernatants showed ability to attract C. elegans. HPLC fractions of those supernatant-extracts of Erwinia strain A41C3, enriched with secondary metabolites such as siderophores, were able to kill pinewood nematode. These results suggest that metabolites secreted under iron limitation have potential to biocontrol B. xylophilus and for management of Pine Wilt Disease.

Design, recombinant expression, and antibacterial activity of a novel hybrid magainin-thanatin antimicrobial peptide

Antimicrobial peptides are small molecule polypeptides with biological activity, which can avoid the drug resistance. Magainin and thanatin are antimicrobial peptides with a broad spectrum of inhibitory microbes, and the core sequence of magainin is linked to a core sequence of thanatin. Here, the hybrid magainin-thanatin (MT) antimicrobial peptide was designed through bioinformatics analysis. The recombinant MT antimicrobial peptide was successfully expressed and purified in Escherichia coli BL21 (DE3). The molecular weight of the hybrid MT antimicrobial peptide was about 3.35 kDa. Moreover, the target protein indeed has an inhibitory effect on Staphylococcus aureus, E. coli DH5α, and Bacillus subtilis, with the minimum inhibitory concentrations 16.5, 20, and 9 μM, respectively. The rational designed hybrid MT antimicrobial peptide will hopefully provide large-scale fermentable antimicrobial peptides in the industrial production in the future.

The pomegranate (Punica granatum L.) genome provides insights into fruit quality and ovule developmental biology

Pomegranate (Punica granatum L.) has an ancient cultivation history and has become an emerging profitable fruit crop due to its attractive features such as the bright red appearance and the high abundance of medicinally valuable ellagitannin-based compounds in its peel and aril. However, the limited genomic resources have restricted further elucidation of genetics and evolution of these interesting traits. Here, we report a 274-Mb high-quality draft pomegranate genome sequence, which covers approximately 81.5% of the estimated 336-Mb genome, consists of 2177 scaffolds with an N50 size of 1.7 Mb and contains 30 903 genes. Phylogenomic analysis supported that pomegranate belongs to the Lythraceae family rather than the monogeneric Punicaceae family, and comparative analyses showed that pomegranate and Eucalyptus grandis share the paleotetraploidy event. Integrated genomic and transcriptomic analyses provided insights into the molecular mechanisms underlying the biosynthesis of ellagitannin-based compounds, the colour formation in both peels and arils during pomegranate fruit development, and the unique ovule development processes that are characteristic of pomegranate. This genome sequence provides an important resource to expand our understanding of some unique biological processes and to facilitate both comparative biology studies and crop breeding.

Genome-wide survey of heat shock factors and heat shock protein 70s and their regulatory network under abiotic stresses in Brachypodium distachyon

The heat shock protein 70s (Hsp70s) and heat shock factors (Hsfs) play key roles in protecting plant cells or tissues from various abiotic stresses. Brachypodium distachyon, recently developed an excellent model organism for functional genomics research, is related to the major cereal grain species. Although B. distachyon genome has been fully sequenced, the information of Hsf and Hsp70 genes and especially the regulatory network between Hsfs and Hsp70s remains incomplete. Here, a total of 24 BdHsfs and 29 BdHsp70s were identified in the genome by bioinformatics analysis and the regulatory network between Hsfs and Hsp70s were performed in this study. Based on highly conserved domain and motif analysis, BdHsfs were grouped into three classes, and BdHsp70s divided into six groups, respectively. Most of Hsf proteins contain five conserved domains: DBD, HR-A/B region, NLS and NES motifs and AHA domain, while Hsp70 proteins have three conserved domains: N-terminal nucleotide binding domain, peptide binding domain and a variable C-terminal lid region. Expression data revealed a large number of BdHsfs and BdHsp70s were induced by HS challenge, and a previous heat acclimation could induce the acquired thermotolerance to help seedling suffer the severe HS challenge, suggesting that the BdHsfs and BdHsp70s played a role in alleviating the damage by HS. The comparison revealed that, most BdHsfs and BdHsp70s genes responded to multiple abiotic stresses in an overlapping relationship, while some of them were stress specific response genes. Moreover, co-expression relationships and predicted protein-protein interaction network implied that class A and B Hsfs played as activator and repressors, respectively, suggesting that BdHsp70s might be regulated by both the activation and the repression mechanisms under stress condition. Our genomics analysis of BdHsfs and BdHsp70s provides important evolutionary and functional characterization for further investigation of the accurate regulatory mechanisms among Hsfs and Hsp70s in herbaceous plants.

Functional interpretation and structural insights of Arabidopsis lyrata cytochrome P450 CYP71A13 involved in auxin synthesis

Cytochrome P450 CYP71A13 of Arabidopsis lyrata is a heme protein involved in biosynthesis of indole-3-acetonitrile which leads to the formation of indolyl-3-acetic acid. It catalyzes a unique reaction: formation of a carbon-nitrogen triple bond and dehydration of indolyl-3-acetaldoxime. Homology model of this 57 kDa polypeptide revealed that the heme existed between H-helix and J- helix in the hydrophobic pocket, although both helixes are involved in catalytic activity, where Gly305 and Thr308, 311 of H- helix were involved in its stabilization. The substrate indole-3-acetaldoxime was tightly fitted into the substrate pocket with the aromatic ring being surrounded by amino acid residues creating a hydrophobic environment. The smaller size of the substrate binding pocket in cytochrome P450 CYP71A13 was due to the bulkiness of the two amino acid residues Phe182 and Trp315 pointing into the substrate binding cavity. The apparent role of the heme in cytochrome P450 CYP71A13 was to tether the substrate in the catalysis by indole-3-acetaldoxime dehydratase. Since the crystal structure of cytochrome P450 CYP71A13 has not yet been solved, the modeled structure revealed mechanism of substrate recognition and catalysis.

Utilization of multiple "omics" studies in microbial pathogeny for microbiology insights

In the present day, bioinformatics becomes the modern science with several advantages. Several new "omics" sciences have been introduced for a few years and those sciences can be applied in biomedical work. Here, the author will summarize and discuss on important applications of omics studies in microbiology focusing on microbial pathogeny. It can be seen that genomics and proteinomics can be well used in this area of biomedical studies.

Large-scale modelling of the divergent spectrin repeats in nesprins: giant modular proteins

Nesprin-1 and nesprin-2 are nuclear envelope (NE) proteins characterized by a common structure of an SR (spectrin repeat) rod domain and a C-terminal transmembrane KASH [Klarsicht-ANC-Syne-homology] domain and display N-terminal actin-binding CH (calponin homology) domains. Mutations in these proteins have been described in Emery-Dreifuss muscular dystrophy and attributed to disruptions of interactions at the NE with nesprins binding partners, lamin A/C and emerin. Evolutionary analysis of the rod domains of the nesprins has shown that they are almost entirely composed of unbroken SR-like structures. We present a bioinformatical approach to accurate definition of the boundaries of each SR by comparison with canonical SR structures, allowing for a large-scale homology modelling of the 74 nesprin-1 and 56 nesprin-2 SRs. The exposed and evolutionary conserved residues identify important pbs for protein-protein interactions that can guide tailored binding experiments. Most importantly, the bioinformatics analyses and the 3D models have been central to the design of selected constructs for protein expression. 1D NMR and CD spectra have been performed of the expressed SRs, showing a folded, stable, high content α-helical structure, typical of SRs. Molecular Dynamics simulations have been performed to study the structural and elastic properties of consecutive SRs, revealing insights in the mechanical properties adopted by these modules in the cell.

Linking genome-scale metabolic modeling and genome annotation

Genome-scale metabolic network reconstructions, assembled from annotated genomes, serve as a platform for integrating data from heterogeneous sources and generating hypotheses for further experimental validation. Implementing constraint-based modeling techniques such as flux balance analysis (FBA) on network reconstructions allows for interrogating metabolism at a systems level, which aids in identifying and rectifying gaps in knowledge. With genome sequences for various organisms from prokaryotes to eukaryotes becoming increasingly available, a significant bottleneck lies in the structural and functional annotation of these sequences. Using topologically based and biologically inspired metabolic network refinement, we can better characterize enzymatic functions present in an organism and link annotation of these functions to candidate transcripts; both steps can be experimentally validated.

Correlation between protein sequence similarity and crystallization reagents in the biological macromolecule crystallization database

The protein structural entries grew far slower than the sequence entries. This is partly due to the bottleneck in obtaining diffraction quality protein crystals for structural determination using X-ray crystallography. The first step to achieve protein crystallization is to find out suitable chemical reagents. However, it is not an easy task. Exhausting trial and error tests of numerous combinations of different reagents mixed with the protein solution are usually necessary to screen out the pursuing crystallization conditions. Therefore, any attempts to help find suitable reagents for protein crystallization are helpful. In this paper, an analysis of the relationship between the protein sequence similarity and the crystallization reagents according to the information from the existing databases is presented. We extracted information of reagents and sequences from the Biological Macromolecule Crystallization Database (BMCD) and the Protein Data Bank (PDB) database, classified the proteins into different clusters according to the sequence similarity, and statistically analyzed the relationship between the sequence similarity and the crystallization reagents. The results showed that there is a pronounced positive correlation between them. Therefore, according to the correlation, prediction of feasible chemical reagents that are suitable to be used in crystallization screens for a specific protein is possible.

Frontiers in metabolic reconstruction and modeling of plant genomes

A major goal of post-genomic biology is to reconstruct and model in silico the metabolic networks of entire organisms. Work on bacteria is well advanced, and is now under way for plants and other eukaryotes. Genome-scale modelling in plants is much more challenging than in bacteria. The challenges come from features characteristic of higher organisms (subcellular compartmentation, tissue differentiation) and also from the particular severity in plants of a general problem: genome content whose functions remain undiscovered. This problem results in thousands of genes for which no function is known ('undiscovered genome content') and hundreds of enzymatic and transport functions for which no gene is yet identified. The severity of the undiscovered genome content problem in plants reflects their genome size and complexity. To bring the challenges of plant genome-scale modelling into focus, we first summarize the current status of plant genome-scale models. We then highlight the challenges - and ways to address them - in three areas: identifying genes for missing processes, modelling tissues as opposed to single cells, and finding metabolic functions encoded by undiscovered genome content. We also discuss the emerging view that a significant fraction of undiscovered genome content encodes functions that counter damage to metabolites inflicted by spontaneous chemical reactions or enzymatic mistakes.

Systems medicine and metabolic modelling

Several complex diseases are caused by the malfunction of human metabolism, and deciphering the underlying molecular mechanisms can elucidate their aetiology. Systems biology is an integrative approach combining experimental and computational biology to identify and describe the molecular mechanisms of complex biological systems. Systems medicine has the potential to elucidate the onset and progression of complex metabolic diseases through the use of computational approaches. Advances in biotechnology have resulted in the provision of high-throughput data, which provide information about different metabolic processes. The systems medicine approach can utilize such data to reconstruct genome-scale metabolic models that can be used to study the function of specific enzymes and pathways in the context of the complete metabolic network. In this review, we outline the importance of genome-scale models in systems medicine and discuss how they may contribute towards the development of personalized medicine.

Bacterial genome annotation

Annotation of prokaryotic sequences can be separated into structural and functional annotation. Structural annotation is dependent on algorithmic interrogation of experimental evidence to discover the physical characteristics of a gene. This is done in an effort to construct accurate gene models, so understanding function or evolution of genes among organisms is not impeded. Functional annotation is dependent on sequence similarity to other known genes or proteins in an effort to assess the function of the gene. Combining structural and functional annotation across genomes in a comparative manner promotes higher levels of accurate annotation as well as an advanced understanding of genome evolution. As the availability of bacterial sequences increases and annotation methods improve, the value of comparative annotation will increase.

An integrated bioinformatics analysis of mouse testis protein profiles with new understanding

The testis is major male gonad responsible for spermatogenesis and steroidogenesis. Much knowledge is still remained to be learned about the control of these events. In this study, we performed a comprehensive bioinformatics analysis on 1,196 mouse testis proteins screened from public protein database. Integrated function and pathway analysis were performed through Database for Annotation, Visualization and Integrated Discovery (DAVID) and ingenuity Pathway Analysis (IPA), and significant features were clustered. Protein membrane organization and gene density on chromosomes were analyzed and discussed. The enriched bioinformatics analysis could provide clues and basis to the development of diagnostic markers and therapeutic targets for infertility and male contraception.

FungalRV: adhesin prediction and immunoinformatics portal for human fungal pathogens

Background

The availability of sequence data of human pathogenic fungi generates opportunities to develop Bioinformatics tools and resources for vaccine development towards benefitting at-risk patients.

Description

We have developed a fungal adhesin predictor and an immunoinformatics database with predicted adhesins. Based on literature search and domain analysis, we prepared a positive dataset comprising adhesin protein sequences from human fungal pathogens Candida albicans, Candida glabrata, Aspergillus fumigatus, Coccidioides immitis, Coccidioides posadasii, Histoplasma capsulatum, Blastomyces dermatitidis, Pneumocystis carinii, Pneumocystis jirovecii and Paracoccidioides brasiliensis. The negative dataset consisted of proteins with high probability to function intracellularly. We have used 3945 compositional properties including frequencies of mono, doublet, triplet, and multiplets of amino acids and hydrophobic properties as input features of protein sequences to Support Vector Machine. Best classifiers were identified through an exhaustive search of 588 parameters and meeting the criteria of best Mathews Correlation Coefficient and lowest coefficient of variation among the 3 fold cross validation datasets. The "FungalRV adhesin predictor" was built on three models whose average Mathews Correlation Coefficient was in the range 0.89-0.90 and its coefficient of variation across three fold cross validation datasets in the range 1.2% - 2.74% at threshold score of 0. We obtained an overall MCC value of 0.8702 considering all 8 pathogens, namely, C. albicans, C. glabrata, A. fumigatus, B. dermatitidis, C. immitis, C. posadasii, H. capsulatum and P. brasiliensis thus showing high sensitivity and specificity at a threshold of 0.511. In case of P. brasiliensis the algorithm achieved a sensitivity of 66.67%. A total of 307 fungal adhesins and adhesin like proteins were predicted from the entire proteomes of eight human pathogenic fungal species. The immunoinformatics analysis data on these proteins were organized for easy user interface analysis. A Web interface was developed for analysis by users. The predicted adhesin sequences were processed through 18 immunoinformatics algorithms and these data have been organized into MySQL backend. A user friendly interface has been developed for experimental researchers for retrieving information from the database.

Conclusion

FungalRV webserver facilitating the discovery process for novel human pathogenic fungal adhesin vaccine has been developed.

The complete genome sequence of Haloferax volcanii DS2, a model archaeon

BACKGROUND

Haloferax volcanii is an easily culturable moderate halophile that grows on simple defined media, is readily transformable, and has a relatively stable genome. This, in combination with its biochemical and genetic tractability, has made Hfx. volcanii a key model organism, not only for the study of halophilicity, but also for archaeal biology in general.

METHODOLOGY/PRINCIPAL FINDINGS

We report here the sequencing and analysis of the genome of Hfx. volcanii DS2, the type strain of this species. The genome contains a main 2.848 Mb chromosome, three smaller chromosomes pHV1, 3, 4 (85, 438, 636 kb, respectively) and the pHV2 plasmid (6.4 kb).

CONCLUSIONS/SIGNIFICANCE

The completed genome sequence, presented here, provides an invaluable tool for further in vivo and in vitro studies of Hfx. volcanii.

Proteomics: challenges, techniques and possibilities to overcome biological sample complexity

Proteomics is the large-scale study of the structure and function of proteins in complex biological sample. Such an approach has the potential value to understand the complex nature of the organism. Current proteomic tools allow large-scale, high-throughput analyses for the detection, identification, and functional investigation of proteome. Advances in protein fractionation and labeling techniques have improved protein identification to include the least abundant proteins. In addition, proteomics has been complemented by the analysis of posttranslational modifications and techniques for the quantitative comparison of different proteomes. However, the major limitation of proteomic investigations remains the complexity of biological structures and physiological processes, rendering the path of exploration paved with various difficulties and pitfalls. The quantity of data that is acquired with new techniques places new challenges on data processing and analysis. This article provides a brief overview of currently available proteomic techniques and their applications, followed by detailed description of advantages and technical challenges. Some solutions to circumvent technical difficulties are proposed.

FIGfams: yet another set of protein families

We present FIGfams, a new collection of over 100 000 protein families that are the product of manual curation and close strain comparison. Using the Subsystem approach the manual curation is carried out, ensuring a previously unattained degree of throughput and consistency. FIGfams are based on over 950 000 manually annotated proteins and across many hundred Bacteria and Archaea. Associated with each FIGfam is a two-tiered, rapid, accurate decision procedure to determine family membership for new proteins. FIGfams are freely available under an open source license. These can be downloaded at ftp://ftp.theseed.org/FIGfams/. The web site for FIGfams is http://www.theseed.org/wiki/FIGfams/

Analysis of Domains in Selected Plant and Animal Food Proteins - Precursors of Biologically Active Peptides - In Silico Approach

In silico methods are useful tool in protein structure-functional relationships analysis. BIOPEP and InterPro databases were applied to analyze the presence of bioactive fragments in the domains occurring in the sequences representing the major groups of proteins. Domains found in the proteins analyzed had mostly transporting (bovine β-lactoglobulin), immunoglobulin-like (chicken connectin), alpha-amylase inhibitor (a/β-wheat gliadin), calcium binding (chicken myosin) functions, or allowed straightly to assign the protein to an appropriate superfamily (bovine casein). It confirmed the thesis about the existence of the functional relations between the structure (sequence) and the domains with identified conformation. Amongst the domains present in the protein sequences we revealed the presence of fragments with the activities: antihypertensive, opioid, dipeptidylpeptidase IV inhibitors, immunomodulating, and neuropeptides. In the chicken connectin within the immunoglobulin-like domain we found immunomodulating fragments. InterPro analysis did not reveal the existence of any domains in a soybean globulin. It can be explained by the lack of the key structure information helpful in the defining the structure-function relationships. As the number of information in the applied databases will continue to increase we can expect to find stronger relationships between bioactivity of fragments encrypted in proteins and the functionality of domains. This might allow in the future to find evolutionary similarity between different origin food proteins - sources of bioactive peptides.

Genome Projector: zoomable genome map with multiple views

BACKGROUND

Molecular biology data exist on diverse scales, from the level of molecules to -omics. At the same time, the data at each scale can be categorised into multiple layers, such as the genome, transcriptome, proteome, metabolome, and biochemical pathways. Due to the highly multi-layer and multi-dimensional nature of biological information, software interfaces for database browsing should provide an intuitive interface that allows for rapid migration across different views and scales. The Zoomable User Interface (ZUI) and tabbed browsing have proven successful for this purpose in other areas, especially to navigate the vast information in the World Wide Web.

RESULTS

This paper presents Genome Projector, a Web-based gateway for genomics information with a zoomable user interface using Google Maps API, equipped with four seamlessly accessible and searchable views: a circular genome map, a traditional genome map, a biochemical pathways map, and a DNA walk map. The Web application for 320 bacterial genomes is available at http://www.g-language.org/GenomeProjector/. All data and software including the source code, documentations, and development API are freely available under the GNU General Public License. Zoomable maps can be easily created from any image file using the development API, and an online data mapping service for Genome Projector is also available at our Web site.

CONCLUSION

Genome Projector is an intuitive Web application for browsing genomics information, implemented with a zoomable user interface and tabbed browsing utilising Google Maps API and Asynchronous JavaScript and XML (AJAX) technology.

OxyGene: an innovative platform for investigating oxidative-response genes in whole prokaryotic genomes

Background

Oxidative stress is a common stress encountered by living organisms and is due to an imbalance between intracellular reactive oxygen and nitrogen species (ROS, RNS) and cellular antioxidant defence. To defend themselves against ROS/RNS, bacteria possess a subsystem of detoxification enzymes, which are classified with regard to their substrates. To identify such enzymes in prokaryotic genomes, different approaches based on similarity, enzyme profiles or patterns exist. Unfortunately, several problems persist in the annotation, classification and naming of these enzymes due mainly to some erroneous entries in databases, mistake propagation, absence of updating and disparity in function description.

Description

In order to improve the current annotation of oxidative stress subsystems, an innovative platform named OxyGene has been developed. It integrates an original database called OxyDB, holding thoroughly tested anchor-based signatures associated to subfamilies of oxidative stress enzymes, and a new anchor-driven annotator, for ab initio detection of ROS/RNS response genes. All complete Bacterial and Archaeal genomes have been re-annotated, and the results stored in the OxyGene repository can be interrogated via a Graphical User Interface.

Conclusion

OxyGene enables the exploration and comparative analysis of enzymes belonging to 37 detoxification subclasses in 664 microbial genomes. It proposes a new classification that improves both the ontology and the annotation of the detoxification subsystems in prokaryotic whole genomes, while discovering new ORFs and attributing precise function to hypothetical annotated proteins. OxyGene is freely available at:

Structural analysis of linear and conformational epitopes of allergens

In many countries regulatory agencies have adopted safety guidelines, based on bioinformatics rules from the WHO/FAO and EFSA recommendations, to prevent potentially allergenic novel foods or agricultural products from reaching consumers. We created the Structural Database of Allergenic Proteins (SDAP, http://fermi.utmb.edu/SDAP/) to combine data that had previously been available only as flat files on Web pages or in the literature. SDAP was designed to be user friendly, to be of maximum use to regulatory agencies, clinicians, as well as to scientists interested in assessing the potential allergenic risk of a protein. We developed methods, unique to SDAP, to compare the physicochemical properties of discrete areas of allergenic proteins to known IgE epitopes. We developed a new similarity measure, the property distance (PD) value that can be used to detect related segments in allergens with clinical observed cross-reactivity. We have now expanded this work to obtain experimental validation of the PD index as a quantitative predictor of IgE cross-reactivity, by designing peptide variants with predetermined PD scores relative to known IgE epitopes. In complementary work we show how sequence motifs characteristic of allergenic proteins in protein families can be used as fingerprints for allergenicity.

Minimotif miner: a computational tool to investigate protein function, disease, and genetic diversity

The Minimotif Miner Web site contains information on several hundred short functional motifs in a single database, and allows the user to search protein queries for the presence of these motifs. Scoring based on evolutionary conservation, protein surface prediction, and motif frequency can be used in conjunction with other motif programs and the known biology of the query to reduce false-positive predictions and select short motifs for experimental pursuit.

The RAST Server: rapid annotations using subsystems technology

BACKGROUND

The number of prokaryotic genome sequences becoming available is growing steadily and is growing faster than our ability to accurately annotate them.

DESCRIPTION

We describe a fully automated service for annotating bacterial and archaeal genomes. The service identifies protein-encoding, rRNA and tRNA genes, assigns functions to the genes, predicts which subsystems are represented in the genome, uses this information to reconstruct the metabolic network and makes the output easily downloadable for the user. In addition, the annotated genome can be browsed in an environment that supports comparative analysis with the annotated genomes maintained in the SEED environment. The service normally makes the annotated genome available within 12-24 hours of submission, but ultimately the quality of such a service will be judged in terms of accuracy, consistency, and completeness of the produced annotations. We summarize our attempts to address these issues and discuss plans for incrementally enhancing the service.

CONCLUSION

By providing accurate, rapid annotation freely to the community we have created an important community resource. The service has now been utilized by over 120 external users annotating over 350 distinct genomes.

Evaluation of resequencing on number of tag SNPs of 13 atherosclerosis-related genes in Thai population

In the candidate gene approach, information about the distribution of single nucleotide polymorphisms (SNPs) is a crucial requirement for choosing efficient markers necessary for a case-control association study. To obtain such information, we discovered SNPs in 13 genes related to atherosclerosis by resequencing exon-flanking regions of 32 healthy Thai individuals. In total, 194 polymorphisms were identified, 184 of them SNPs, four insertions, and the rest deletions. Fifty-nine of the SNPs were characterized as novel polymorphisms, and these accounted for 30% of the identified SNPs. Comparing allele frequency distributions of the Thai population with other Asian populations shows similar patterns. In contrast, a low correlation pattern (r = 0.521) was found when comparing with either Caucasian or African populations. However, some rare alleles (rs11574541 and rs10874913) are found in the Thai population but not in other Asian populations. Most of the novel SNPs found were located outside the haplotype blocks generated by known SNPs in the Thai population. Only 5.77% of the novel SNPs lies in these defined haplotype blocks. The selection of haplotype-tagging SNPs shows that 8 of 13 genes benefited from the ethnic-specific genotype information. That is, when at least one novel SNP was present, the tagging SNPs chosen were altered. Functional prediction of 16 nonsynonymous SNPs (nsSNPs) by three different algorithm tools demonstrated that five nsSNPs possibly alter their corresponding protein functions. These results provide necessary information for conducting further genetic association studies involving the Thai population and demonstrate that resequencing of candidate genes provides more complete information for full genetic studies.

Generation of ESTs in Vitis vinifera wine grape (Cabernet Sauvignon) and table grape (Muscat Hamburg) and discovery of new candidate genes with potential roles in berry development

We report the generation and analysis of a total of 77,583 expressed sequence tags (ESTs) from two grapevine (Vitis vinifera L.) cultivars, Cabernet Sauvignon (wine grape) and Muscat Hamburg (table grape) with a focus on EST sequence quality and assembly optimization. The majority of the ESTs were derived from normalized cDNA libraries representing berry pericarp and seed developmental series, pooled non-berry tissues including root, flower, and leaf in Cabernet Sauvignon, and pooled tissues of berry, seed, and flower in Muscat Hamburg. EST and unigene sequence quality were determined by computational filtering coupled with small-scale contig reassembly, manual review, and BLAST analyses. EST assembly was optimized to better discriminate among closely related paralogs using two independent grape sequence sets, a previously published set of Vitis spp. gene families and our EST dataset derived from pooled leaf, flower, and root tissues of Cabernet Sauvignon. Sequence assembly within individual libraries indicated that those prepared from pooled tissues contributed the most to gene discovery. Annotations based upon searches against multiple databases including tomato and strawberry sequences helped to identify putative functions of ESTs and unigenes, particularly with respect to fleshy fruit development. Sequence comparison among the three wine grape libraries identified a number of genes preferentially expressed in the pericarp tissue, including transcription factors, receptor-like protein kinases, and hexose transporters. Gene ontology (GO) classification in the biological process aspect showed that GO categories corresponding to 'transport' and 'cell organization and biogenesis', which are associated with metabolite movement and cell wall structural changes during berry ripening, were higher in pericarp than in other tissues in the wine grape studied. The sequence data were used to characterize potential roles of new genes in berry development and composition.

Analysis on the protein structure and function of retinoic acid induced 16

AIM: To analyze the protein structure and function of Homo sapiens retinoic acid induced 16 (RAI16) cDNA nucleotides sequence.

METHODS: Using some related computer software and database, RAI16 cDNA sequence and the deduced amino acid (AA) sequence were analyzed and compared with those of other species, and the secondary structure and hydrophobicity of the protein were determined and predicted.

RESULTS: RAI16 cDNA sequence consisted of 2863 nucleotides encoding a 759-AA protein. RAI16 protein included a 31-AA signal peptide. The protein had no transmembrane domain, and its subcellular localization was in endoplasmic reticulum. The secondary structure contained several kinds of conformations. RAI16 protein appeared as a compact and globular domain, and was a secretory and hydrophilicity protein (grand average of hydropathicity: -0.136). The protein was also unstable (the unstable coefficient: 53.11), with many phosphorylation and proteinase sites.

CONCLUSION: As a new signal protein, RAI16 may be involved in the signal transduction and transcription of hepatoma cell differentiation by interacting with Tec protein.

UniProtKB/Swiss-Prot

The Swiss Institute of Bioinformatics (SIB), the European Bioinformatics Institute (EBI), and the Protein Information Resource (PIR) form the Universal Protein Resource (UniProt) consortium. Its main goal is to provide the scientific community with a central resource for protein sequences and functional information. The UniProt consortium maintains the UniProt KnowledgeBase (UniProtKB) and several supplementary databases including the UniProt Reference Clusters (UniRef) and the UniProt Archive (UniParc). (1) UniProtKB is a comprehensive protein sequence knowledgebase that consists of two sections: UniProtKB/Swiss-Prot, which contains manually annotated entries, and UniProtKB/TrEMBL, which contains computer-annotated entries. UniProtKB/Swiss-Prot entries contain information curated by biologists and provide users with cross-links to about 100 external databases and with access to additional information or tools. (2) The UniRef databases (UniRef100, UniRef90, and UniRef50) define clusters of protein sequences that share 100, 90, or 50% identity. (3) The UniParc database stores and maps all publicly available protein sequence data, including obsolete data excluded from UniProtKB. The UniProt databases can be accessed online (http://www.uniprot.org/) or downloaded in several formats (ftp://ftp.uniprot.org/pub). New releases are published every 2 weeks. The purpose of this chapter is to present a guided tour of a UniProtKB/Swiss-Prot entry, paying particular attention to the specificities of plant protein annotation. We will also present some of the tools and databases that are linked to each entry.

SUBA: the Arabidopsis Subcellular Database

Knowledge of protein localisation contributes towards our understanding of protein function and of biological inter-relationships. A variety of experimental methods are currently being used to produce localisation data that need to be made accessible in an integrated manner. Chimeric fluorescent fusion proteins have been used to define subcellular localisations with at least 1100 related experiments completed in Arabidopsis. More recently, many studies have employed mass spectrometry to undertake proteomic surveys of subcellular components in Arabidopsis yielding localisation information for approximately 2600 proteins. Further protein localisation information may be obtained from other literature references to analysis of locations (AmiGO: approximately 900 proteins), location information from Swiss-Prot annotations (approximately 2000 proteins); and location inferred from gene descriptions (approximately 2700 proteins). Additionally, an increasing volume of available software provides location prediction information for proteins based on amino acid sequence. We have undertaken to bring these various data sources together to build SUBA, a SUBcellular location database for Arabidopsis proteins. The localisation data in SUBA encompasses 10 distinct subcellular locations, >6743 non-redundant proteins and represents the proteins encoded in the transcripts responsible for 51% of Arabidopsis expressed sequence tags. The SUBA database provides a powerful means by which to assess protein subcellular localisation in Arabidopsis (http://www.suba.bcs.uwa.edu.au).

Combining algorithms to predict bacterial protein sub-cellular location: Parallel versus concurrent implementations

We describe a novel and potentially important tool for candidate subunit vaccine selection through in silico reverse-vaccinology. A set of Bayesian networks able to make individual predictions for specific subcellular locations is implemented in three pipelines with different architectures: a parallel implementation with a confidence level-based decision engine and two serial implementations with a hierarchical decision structure, one initially rooted by prediction between membrane types and another rooted by soluble versus membrane prediction. The parallel pipeline outperformed the serial pipeline, but took twice as long to execute. The soluble-rooted serial pipeline outperformed the membrane-rooted predictor. Assessment using genomic test sets was more equivocal, as many more predictions are made by the parallel pipeline, yet the serial pipeline identifies 22 more of the 74 proteins of known location.

Toward bacterial protein sub-cellular location prediction: single-class discrimminant models for all gram- and gram+ compartments

Based on Bayesian Networks, methods were created that address protein sequence-based bacterial subcellular location prediction. Distinct predictive algorithms for the eight bacterial subcellular locations were created. Several variant methods were explored. These variations included differences in the number of residues considered within the query sequence - which ranged from the N-terminal 10 residues to the whole sequence - and residue representation - which took the form of amino acid composition, percentage amino acid composition, or normalised amino acid composition. The accuracies of the best performing networks were then compared to PSORTB. All individual location methods outperform PSORTB except for the Gram+ cytoplasmic protein predictor, for which accuracies were essentially equal, and for outer membrane protein prediction, where PSORTB outperforms the binary predictor. The method described here is an important new approach to method development for subcellular location prediction. It is also a new, potentially valuable tool for candidate subunit vaccine selection.

Multi-class subcellular location prediction for bacterial proteins

Two algorithms, based onBayesian Networks (BNs), for bacterial subcellular location prediction, are explored in this paper: one predicts all locations for Gram+ bacteria and the other all locations for Gram- bacteria. Methods were evaluated using different numbers of residues (from the N-terminal 10 residues to the whole sequence) and residue representation (amino acid-composition, percentage amino acid-composition or normalised amino acid-composition). The accuracy of the best resulting BN was compared to PSORTB. The accuracy of this multi-location BN was roughly comparable to PSORTB; the difference in predictions is low, often less than 2%. The BN method thus represents both an important new avenue of methodological development for subcellular location prediction and a potentially value new tool of true utilitarian value for candidate subunit vaccine selection.

Comparative genomic evidence for a close relationship between the dimorphic prosthecate bacteria Hyphomonas neptunium and Caulobacter crescentus

The dimorphic prosthecate bacteria (DPB) are alpha-proteobacteria that reproduce in an asymmetric manner rather than by binary fission and are of interest as simple models of development. Prior to this work, the only member of this group for which genome sequence was available was the model freshwater organism Caulobacter crescentus. Here we describe the genome sequence of Hyphomonas neptunium, a marine member of the DPB that differs from C. crescentus in that H. neptunium uses its stalk as a reproductive structure. Genome analysis indicates that this organism shares more genes with C. crescentus than it does with Silicibacter pomeroyi (a closer relative according to 16S rRNA phylogeny), that it relies upon a heterotrophic strategy utilizing a wide range of substrates, that its cell cycle is likely to be regulated in a similar manner to that of C. crescentus, and that the outer membrane complements of H. neptunium and C. crescentus are remarkably similar. H. neptunium swarmer cells are highly motile via a single polar flagellum. With the exception of cheY and cheR, genes required for chemotaxis were absent in the H. neptunium genome. Consistent with this observation, H. neptunium swarmer cells did not respond to any chemotactic stimuli that were tested, which suggests that H. neptunium motility is a random dispersal mechanism for swarmer cells rather than a stimulus-controlled navigation system for locating specific environments. In addition to providing insights into bacterial development, the H. neptunium genome will provide an important resource for the study of other interesting biological processes including chromosome segregation, polar growth, and cell aging.

Cataloging the relationships between proteins: a review of interaction databases

By organizing and making widely accessible the increasing amounts of data from high-throughput analyses, protein interaction databases have become an integral resource for the biological community in relating sequence data with higher-order function. To provide a sense of the use and applicability of these databases, we describe each of the major comprehensive interaction databases as well as some of the more specialized ones. Content description, search/browse functionalities, and data presentation are discussed. A succinct explanation of database contents helps the user quickly identify whether the database contains applicable information to their research interest. Broad levels of search/browse functions as well as descriptions/examples allow users to quickly find and access pertinent data. At this point, clear presentation of search results as well as the primary content is necessary. Many databases display information graphically or divided into smaller digestible parts over a number of tabbed/linked pages. In addition, cross-linking between the databases promotes interconnectivity of the data and is an added layer of relational data for the user. Overall, although these protein interaction databases are under continual improvement, their current state shows that much time and effort has gone into organizing and presenting these large sets of data-describing protein interactions.

Combining experimental and predicted datasets for determination of the subcellular location of proteins in Arabidopsis

Substantial experimental datasets defining the subcellular location of Arabidopsis (Arabidopsis thaliana) proteins have been reported in the literature in the form of organelle proteomes built from mass spectrometry data (approximately 2,500 proteins). Subcellular location for specific proteins has also been published based on imaging of chimeric fluorescent fusion proteins in intact cells (approximately 900 proteins). Further, the more diverse history of biochemical determination of subcellular location is stored in the entries of the Swiss-Prot database for the products of many Arabidopsis genes (approximately 1,800 proteins). Combined with the range of bioinformatic targeting prediction tools and comparative genomic analysis, these experimental datasets provide a powerful basis for defining the final location of proteins within the wide variety of subcellular structures present inside Arabidopsis cells. We have analyzed these published experimental and prediction data to answer a range of substantial questions facing researchers about the veracity of these approaches to determining protein location and their interrelatedness. We have merged these data to form the subcellular location database for Arabidopsis proteins (SUBA), providing an integrated understanding of protein location, encompassing the plastid, mitochondrion, peroxisome, nucleus, plasma membrane, endoplasmic reticulum, vacuole, Golgi, cytoskeleton structures, and cytosol (www.suba.bcs.uwa.edu.au). This includes data on more than 4,400 nonredundant Arabidopsis protein sequences. We also provide researchers with an online resource that may be used to query protein sets or protein families and determine whether predicted or experimental location data exist; to analyze the nature of contamination between published proteome sets; and/or for building theoretical subcellular proteomes in Arabidopsis using the latest experimental data.