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The necessity of combining genomic and enzymatic data to infer metabolic function and pathways in the smallest bacteria: amino acid, purine and pyrimidine metabolism in Mollicutes.

Bacteria of the class Mollicutes have no cell wall. One species, Mycoplasma genitalium is the personification of the simplest form of independent cell-free life. Its small genome (580 kbp) is the smallest of any cell. Mollicutes have unique metabolic properties, perhaps because of their limited coding space and high mutability. Based on 16S rRNA analyses the Mollicutes Mycoplasma gallisepticum is thought to be the most mutable bacteria. Enzyme activities found in most Bacteria are absent from Mollicutes. The functions of apparently absent genes and enzymes can apparently be fulfilled by other genes and their expression products that have multiple capabilities. Because of these and other properties predictions of their metabolism based only on, e.g., either annotation, enzymatic assay, proteomic studies or structural analyses is problematic. To obtain a more confident appraisal of the functional capabilities of these simplest cells genomic and enzymatic data were combined to obtain a "metabolic consensus". The consensus is represented by a biochemical circuit for central metabolism involving purine and pyrimidine interconversions and their linkages to amino acid metabolism, glycolysis and the pentose phosphate pathway in three human Mollicutes pathogens: Mycoplasma pneumoniae, Mycoplasma genitalium and Ureaplasma urealyticum.

Amino Acids↗

LMSD: LIPID MAPS structure database.

The LIPID MAPS Structure Database (LMSD) is a relational database encompassing structures and annotations of biologically relevant lipids. Structures of lipids in the database come from four sources: (i) LIPID MAPS Consortium's core laboratories and partners; (ii) lipids identified by LIPID MAPS experiments; (iii) computationally generated structures for appropriate lipid classes; (iv) biologically relevant lipids manually curated from LIPID BANK, LIPIDAT and other public sources. All the lipid structures in LMSD are drawn in a consistent fashion. In addition to a classification-based retrieval of lipids, users can search LMSD using either text-based or structure-based search options. The text-based search implementation supports data retrieval by any combination of these data fields: LIPID MAPS ID, systematic or common name, mass, formula, category, main class, and subclass data fields. The structure-based search, in conjunction with optional data fields, provides the capability to perform a substructure search or exact match for the structure drawn by the user. Search results, in addition to structure and annotations, also include relevant links to external databases. The LMSD is publicly available at www.lipidmaps.org/data/structure/.

Databases, Factual↗

Annotating large genomes with exact word matches.

We have developed a tool for rapidly determining the number of exact matches of any word within large, internally repetitive genomes or sets of genomes. Thus we can readily annotate any sequence, including the entire human genome, with the counts of its constituent words. We create a Burrows-Wheeler transform of the genome, which together with auxiliary data structures facilitating counting, can reside in about one gigabyte of RAM. Our original interest was motivated by oligonucleotide probe design, and we describe a general protocol for defining unique hybridization probes. But our method also has applications for the analysis of genome structure and assembly. We demonstrate the identification of chromosome-specific repeats, and outline a general procedure for finding undiscovered repeats. We also illustrate the changing contents of the human genome assemblies by comparing the annotations built from different genome freezes.

Algorithms↗

Automated testing of arrhythmia monitors using annotated databases.

Arrhythmia-algorithm performance is typically tested using the AHA and MIT/BIH databases. The tools for this test are simulation software programs. While these simulations provide rapid results, they neglect hardware and software effects in the monitor. To provide a more accurate measure of performance in the actual monitor, a system has been developed for automated arrhythmia testing. The testing system incorporates an IBM-compatible personal computer, a digital-to-analog converter, an RS232 board, a patient-simulator interface to the monitor, and a multi-tasking software package for data conversion and communication with the monitor. This system "plays" patient data files into the monitor and saves beat classifications in detection files. Tests were performed using the MIT/BIH and AHA databases. Statistics were generated by comparing the detection files with the annotation files. These statistics were marginally different from those that resulted from the simulation. Differences were then examined. As expected, the differences were related to monitor hardware effects.

Algorithms↗

Counting the zinc-proteins encoded in the human genome.

Metalloproteins are proteins capable of binding one or more metal ions, which may be required for their biological function, or for regulation of their activities or for structural purposes. Genome sequencing projects have provided a huge number of protein primary sequences, but, even though several different elaborate analyses and annotations have been enabled by a rich and ever-increasing portfolio of bioinformatic tools, metal-binding properties remain difficult to predict as well as to investigate experimentally. Consequently, the present knowledge about metalloproteins is only partial. The present bioinformatic research proposes a strategy to answer the question of how many and which proteins encoded in the human genome may require zinc for their physiological function. This is achieved by a combination of approaches, which include: (i) searching in the proteome for the zinc-binding patterns that, on their turn, are obtained from all available X-ray data; (ii) using libraries of metal-binding protein domains based on multiple sequence alignments of known metalloproteins obtained from the Pfam database; and (iii) mining the annotations of human gene sequences, which are based on any type of information available. It is found that 1684 proteins in the human proteome are independently identified by all three approaches as zinc-proteins, 746 are identified by two, and 777 are identified by only one method. By assuming that all proteins identified by at least two approaches are truly zinc-binding and inspecting the proteins identified by a single method, it can be proposed that ca. 2800 human proteins are potentially zinc-binding in vivo, corresponding to 10% of the human proteome, with an uncertainty of 400 sequences. Available functional information suggests that the large majority of human zinc-binding proteins are involved in the regulation of gene expression. The most abundant class of zinc-binding proteins in humans is that of zinc-fingers, with Cys4 and Cys2His2 being the most common types of coordination environment.

Computational Biology↗

Microarray analyses of gene expression during chondrocyte differentiation identifies novel regulators of hypertrophy.

Ordered chondrocyte differentiation and maturation is required for normal skeletal development, but the intracellular pathways regulating this process remain largely unclear. We used Affymetrix microarrays to examine temporal gene expression patterns during chondrogenic differentiation in a mouse micromass culture system. Robust normalization of the data identified 3300 differentially expressed probe sets, which corresponds to 1772, 481, and 249 probe sets exhibiting minimum 2-, 5-, and 10-fold changes over the time period, respectively. GeneOntology annotations for molecular function show changes in the expression of molecules involved in transcriptional regulation and signal transduction among others. The expression of identified markers was confirmed by RT-PCR, and cluster analysis revealed groups of coexpressed transcripts. One gene that was up-regulated at later stages of chondrocyte differentiation was Rgs2. Overexpression of Rgs2 in the chondrogenic cell line ATDC5 resulted in accelerated hypertrophic differentiation, thus providing functional validation of microarray data. Collectively, these analyses provide novel information on the temporal expression of molecules regulating endochondral bone development.

Animals↗

MolMovDB: analysis and visualization of conformational change and structural flexibility.

The Database of Macromolecular Movements (http://MolMovDB.org) is a collection of data and software pertaining to flexibility in protein and RNA structures. The database is organized into two parts. Firstly, a collection of 'morphs' of solved structures representing different states of a molecule provides quantitative data for flexibility and a number of graphical representations. Secondly, a classification of known motions according to type of conformational change (e.g. 'hinged domain' or 'allosteric') incorporates textual annotation and information from the literature relating to the motion, linking together many of the morphs. A variety of subsets of the morphs are being developed for use in statistical analyses. In particular, for each subset it is possible to derive distributions of various motional quantities (e.g. maximum rotation) that can be used to place a specific motion in context as being typical or atypical for a given population. Over the past year, the database has been greatly expanded and enhanced to incorporate new structures and to improve the quality of data. The 'morph server', which enables users of the database to add new morphs either from their own research or the PDB, has also been enhanced to handle nucleic acid structures and multi-chain complexes.

Computer Graphics↗

The Australian Twin Registry.

The Australian Twin Registry (ATR), established in the late 1970s, is a volunteer registry of over 30,000 pairs of Australian twins of all zygosity types and ages unselected for their health or medical history. The ATR does not undertake research itself but acts as facilitator, providing an important national and international resource for medical and scientific researchers across a broad range of disciplines. Its core functions are the maintenance of an up-to-date database containing basic contact details and baseline information, and the management of access to the resource in ways that enhance research capacity within Australia while protecting the rights of twins. The ATR has facilitated more than 200 studies using a variety of designs, including classic biometrical twin and twin family studies, co-twin control studies, intervention studies, longitudinal studies, and studies of issues relevant specifically to twins. These have yielded more than 300 peer-reviewed publications to date. Areas of major research include studies of behavior, musculoskeletal conditions, teeth and face patterns, cardiovascular risk factors, substance abuse, and risk factors for melanoma and breast cancer. Extensive longitudinal data are available for around 10,000 pairs. DNA samples have been obtained from more than 6000 twins. Considerable efforts are devoted to maintaining the commitment of registry members and recruitment. The ATR hopes to secure funding to expand its activities, including the systematic collection of DNA samples, so that it can continue to play a major role in the development of twin research and contribute to the annotation of the human genome.

Adolescent↗

Development of an integrated genome informatics, data management and workflow infrastructure: a toolbox for the study of complex disease genetics.

The genetic dissection of complex disease remains a significant challenge. Sample-tracking and the recording, processing and storage of high-throughput laboratory data with public domain data, require integration of databases, genome informatics and genetic analyses in an easily updated and scaleable format. To find genes involved in multifactorial diseases such as type 1 diabetes (T1D), chromosome regions are defined based on functional candidate gene content, linkage information from humans and animal model mapping information. For each region, genomic information is extracted from Ensembl, converted and loaded into ACeDB for manual gene annotation. Homology information is examined using ACeDB tools and the gene structure verified. Manually curated genes are extracted from ACeDB and read into the feature database, which holds relevant local genomic feature data and an audit trail of laboratory investigations. Public domain information, manually curated genes, polymorphisms, primers, linkage and association analyses, with links to our genotyping database, are shown in Gbrowse. This system scales to include genetic, statistical, quality control (QC) and biological data such as expression analyses of RNA or protein, all linked from a genomics integrative display. Our system is applicable to any genetic study of complex disease, of either large or small scale.

Animals↗

PRED-CLASS: cascading neural networks for generalized protein classification and genome-wide applications.

A cascading system of hierarchical, artificial neural networks (named PRED-CLASS) is presented for the generalized classification of proteins into four distinct classes-transmembrane, fibrous, globular, and mixed-from information solely encoded in their amino acid sequences. The architecture of the individual component networks is kept very simple, reducing the number of free parameters (network synaptic weights) for faster training, improved generalization, and the avoidance of data overfitting. Capturing information from as few as 50 protein sequences spread among the four target classes (6 transmembrane, 10 fibrous, 13 globular, and 17 mixed), PRED-CLASS was able to obtain 371 correct predictions out of a set of 387 proteins (success rate approximately 96%) unambiguously assigned into one of the target classes. The application of PRED-CLASS to several test sets and complete proteomes of several organisms demonstrates that such a method could serve as a valuable tool in the annotation of genomic open reading frames with no functional assignment or as a preliminary step in fold recognition and ab initio structure prediction methods. Detailed results obtained for various data sets and completed genomes, along with a web sever running the PRED-CLASS algorithm, can be accessed over the World Wide Web at http://o2.biol.uoa.gr/PRED-CLASS.

Computational Biology↗

Associative database of protein sequences.

MOTIVATION: We present a new concept that combines data storage and data analysis in genome research, based on an associative network memory. As an illustration, 115 000 conserved regions from over 73 000 published sequences (i.e. from the entire annotated part of the SWISSPROT sequence database) were identified and clustered by a self-organizing network. Similarity and kinship, as well as degree of distance between the conserved protein segments, are visualized as neighborhood relationship on a two-dimensional topographical map. RESULTS: Such a display overcomes the restrictions of linear list processing and allows local and global sequence relationships to be studied visually. Families are memorized as prototype vectors of conserved regions. On a massive parallel machine, clustering and updating of the database take only a few seconds; a rapid analysis of incoming data such as protein sequences or ESTs is carried out on present-day workstations. AVAILABILITY: Access to the database is available at http://www.bioinf.mdc-berlin.de/unter2.html++ + CONTACT: (hanke,lehmann,reich)@mdc-berlin.de; bork@embl-heidelberg.de

Amino Acid Sequence↗

The Yeast Proteome Database (YPD): a model for the organization and presentation of genome-wide functional data.

The Yeast Proteome Database (YPD) is a model for the organization and presentation of comprehensive protein information. Based on the detailed curation of the scientific literature for the yeast Saccharomyces cerevisiae, YPD contains more than 50 000 annotations lines derived from the review of 8500 research publications. The information concerning each of the approximately 6100 yeast proteins is structured around a convenient one-page format, the Yeast Protein Report, with additional information provided as pop-up windows. Protein classification schema have been revised this year, defining each protein's cellular role, function and pathway, and adding a Functional to the Yeast Protein Report. These changes provide the user with a succinct summary of the protein's function and its place in the biology of the cell, and they enhance the power of YPD Search functions. Precalculated sequence alignments have been added, to provide a crossover point for comparative genomics. The first transcript profiling data has been integrated into the YPD Protein Reports, providing the framework for the presentation of genome-wide functional data. The Yeast Proteome Database can be accessed on the Web at http://www.proteome.com/YPDhome.html

Computational Biology↗

Analysis of curated and predicted plastid subproteomes of Arabidopsis. Subcellular compartmentalization leads to distinctive proteome properties.

Carefully curated proteomes of the inner envelope membrane, the thylakoid membrane, and the thylakoid lumen of chloroplasts from Arabidopsis were assembled based on published, well-documented localizations. These curated proteomes were evaluated for distribution of physical-chemical parameters, with the goal of extracting parameters for improved subcellular prediction and subsequent identification of additional (low abundant) components of each membrane system. The assembly of rigorously curated subcellular proteomes is in itself also important as a parts list for plant and systems biology. Transmembrane and subcellular prediction strategies were evaluated using the curated data sets. The three curated proteomes differ strongly in average isoelectric point and protein size, as well as transmembrane distribution. Removal of the cleavable, N-terminal transit peptide sequences greatly affected isoelectric point and size distribution. Unexpectedly, the Cys content was much lower for the thylakoid proteomes than for the inner envelope. This likely relates to the role of the thylakoid membrane in light-driven electron transport and helps to avoid unwanted oxidation-reduction reactions. A rule of thumb for discriminating between the predicted integral inner envelope membrane and integral thylakoid membrane proteins is suggested. Using a combination of predictors and experimentally derived parameters, four plastid subproteomes were predicted from the fully annotated Arabidopsis genome. These predicted subproteomes were analyzed for their properties and compared to the curated proteomes. The sensitivity and accuracy of the prediction strategies are discussed. Data can be extracted from the new plastid proteome database (http://ppdb.tc.cornell.edu).

Arabidopsis↗

Molecular dynamics of the Shewanella oneidensis response to chromate stress.

Temporal genomic profiling and whole-cell proteomic analyses were performed to characterize the dynamic molecular response of the metal-reducing bacterium Shewanella oneidensis MR-1 to an acute chromate shock. The complex dynamics of cellular processes demand the integration of methodologies that describe biological systems at the levels of regulation, gene and protein expression, and metabolite production. Genomic microarray analysis of the transcriptome dynamics of midexponential phase cells subjected to 1 mm potassium chromate (K(2)CrO(4)) at exposure time intervals of 5, 30, 60, and 90 min revealed 910 genes that were differentially expressed at one or more time points. Strongly induced genes included those encoding components of a TonB1 iron transport system (tonB1-exbB1-exbD1), hemin ATP-binding cassette transporters (hmuTUV), TonB-dependent receptors as well as sulfate transporters (cysP, cysW-2, and cysA-2), and enzymes involved in assimilative sulfur metabolism (cysC, cysN, cysD, cysH, cysI, and cysJ). Transcript levels for genes with annotated functions in DNA repair (lexA, recX, recA, recN, dinP, and umuD), cellular detoxification (so1756, so3585, and so3586), and two-component signal transduction systems (so2426) were also significantly up-regulated (p < 0.05) in Cr(VI)-exposed cells relative to untreated cells. By contrast, genes with functions linked to energy metabolism, particularly electron transport (e.g. so0902-03-04, mtrA, omcA, and omcB), showed dramatic temporal alterations in expression with the majority exhibiting repression. Differential proteomics based on multidimensional HPLC-MS/MS was used to complement the transcriptome data, resulting in comparable induction and repression patterns for a subset of corresponding proteins. In total, expression of 2,370 proteins were confidently verified with 624 (26%) of these annotated as hypothetical or conserved hypothetical proteins. The initial response of S. oneidensis to chromate shock appears to require a combination of different regulatory networks that involve genes with annotated functions in oxidative stress protection, detoxification, protein stress protection, iron and sulfur acquisition, and SOS-controlled DNA repair mechanisms.

Anion Transport Proteins↗

A novel database of disulfide patterns and its application to the discovery of distantly related homologs.

Disulfide bonds are conserved strongly among proteins of related structure and function. Despite the explosive growth of protein sequence databases and the vast numbers of sequence search tools, no tool exists to draw relations between the disulfide patterns of homologous proteins. We present a comprehensive database of disulfide bonding patterns and a search method to find proteins with similar disulfide patterns. The disulfide database was constructed using disulfide annotations extracted from SwissProt, and was expanded significantly from 16,736 to 94,499 disulfide-containing domains by an inference method that combines SwissProt annotations with Pfam multiple alignments. To search the database, we define a disulfide description, called the disulfide signature, which encodes both spacings between cysteine residues and cysteine connectivity. A web tool was developed that allows users to search for related disulfide patterns and for subpatterns resulting from the removal of one or more disulfides from the pattern. We explore the possibility of using disulfide pattern conservation to identify protein homologs that are undetectable by PSI-BLAST. Examples include the homology between a sea anemone antihypertensive/antiviral protein and a sea anemone neurotoxin, and the homology between tick anticoagulant peptide and bovine trypsin inhibitor. In both examples, there is a clear structural similarity and a functional relationship. We used the database to find structural homologs for the Cripto CFC domain. The identification of a von Willebrand Factor C (VWFC)-like domain agrees with its functional role and explains mutation data. We believe that the rapid increase in structure determinations arising from structural genomics efforts and advances in mass spectrometry techniques will greatly increase the number of disulfide annotations. This information will become a valuable resource for structural and functional annotations of proteins. The availability of a searchable disulfide pattern database will thus provide a powerful new addition to existing homolog discovery methods.

Amino Acid Sequence↗

X chromosome-wide association studies for quantitative trait loci based on the mixture of general pedigrees and additional unrelated individuals.

Genome-wide association studies have successfully identified many genetic variants associated with complex traits. However, most existing methods target autosomes rather than X chromosome, and several existing X chromosome-wide association studies (XWAS) at quantitative trait loci (QTL) largely focus on unrelated individuals, with limited attention to general pedigrees or mixture of general pedigrees and additional unrelated individuals (called the mixed data for brevity). In this study, we propose nine novel methods for XWAS at QTL in the mixed data (${\mathrm{MQX}}_{\mathrm{cat}}$, ${\mathrm{MQZ}}_{\mathrm{max}}$, ${\mathrm{MT}}_{\mathrm{plinkw}}$, ${\mathrm{MT}}_{\mathrm{chenw}}$, $\mathrm{MwM}3\mathrm{VNA}$, ${\mathrm{MQMVX}}_{\mathrm{cat}}$, ${\mathrm{MQMVZ}}_{\mathrm{max}}$, $\mathrm{MpMV}$, and $\mathrm{McMV}$), also applicable to general pedigrees alone. The first four methods test for mean differences across genotypes; the latter four test for differences in both means and variances; $\mathrm{MwM}3\mathrm{VNA}$ tests for variance differences only. All mean-based and mean-variance-based methods incorporate X chromosome inactivation information, and all nine methods consider genetic relatedness in pedigrees. Simulation studies confirm well-controlled type I error rates, and inclusion of pedigrees significantly improves statistical power. Note that there has been no study focusing on X chromosome for the mixed data or general pedigrees from UK Biobank database, so we apply our proposed methods to this dataset, which identify five total cholesterol (TC)-associated and 13 low-density lipoprotein cholesterol (LDL-C)-associated single nucleotide polymorphisms (SNPs). Linkage disequilibrium (LD) analysis reveals that these SNPs fall into three distinct LD blocks. Functional annotation and gene ontology enrichment analysis reveal 16 and 28 enriched pathways for TC-associated and LDL-C-associated genes, respectively. These methods provide robust and powerful tools for XWAS at QTL in both mixed data and general pedigrees.

Quantitative Trait Loci↗

The IARC TP53 database: new online mutation analysis and recommendations to users.

Mutations in the tumor suppressor gene TP53 are frequent in most human cancers. Comparison of the mutation patterns in different cancers may reveal clues on the natural history of the disease. Over the past 10 years, several databases of TP53 mutations have been developed. The most extensive of these databases is maintained and developed at the International Agency for Research on Cancer. The database compiles all mutations (somatic and inherited), as well as polymorphisms, that have been reported in the published literature since 1989. The IARC TP53 mutation dataset is the largest dataset available on the variations of any human gene. The database is available at www.iarc.fr/P53/. In this paper, we describe recent developments of the database. These developments include restructuring of the database, which is now patient-centered, with more detailed annotations on the patient (carcinogen exposure, virus infection, genetic background). In addition, a new on-line application to retrieve somatic mutation data and analyze mutation patterns is now available. We also discuss limitations on the use of the database and provide recommendations to users.

Computational Biology↗

Discovering hidden candidate plastic-degrading enzymes: Combined multi-omics and machine learning strategy.

Plastic pollution poses a major threat to the stability of natural ecosystems as well as human health. Microbial enzymes have long been considered a potential resource for targeted biodegradation but, except for a few successful cases, the discovery of efficient enzymes has proved challenging. Aiming to accelerate the process, we propose an approach combining metagenomics, metatranscriptomics and semi-supervised learning that selects promising plastic-degrading candidate enzymes from the proteome of relevant microorganisms. Tested on a dataset of over 10,000 microbial proteins, ranking models consistently prioritize known plastic-degrading enzymes, achieving an area under the cumulative distribution function curve above 0.96, with leave-one-family-out cross-validation indicating that performance is largely retained across protein families. As a case study, this work focuses on mixed microbial cultures exposed for extended periods to polyethylene, polyethylene terephthalate, and polyurethane substrates. The prevalent species after selective enrichment were functionally characterized, finding Rhodococcus aetherivorans as the most relevant species in two of the five cultures under investigation. Among the top-ranked proteins, several have high structural similarity with known enzymes despite not being identified by sequence similarity search. Moreover, according to metatranscriptomics results, several of these enzymes were found to be expressed at the same level or above that of annotated enzymes, suggesting that they may have functional relevance. Overall, this work highlights the potential of integrating multi-omics with data-driven methods for enzyme discovery and for accelerating the development of biotechnological solutions to plastic pollution.

Biodegradation, Environmental↗