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PubMed2004

HemoPDB: Hematopoiesis Promoter Database, an information resource of transcriptional regulation in blood cell development.

Hematopoiesis describes the process of the normal formation and development of blood cells, involving both proliferation and differentiation from stem cells. Abnormalities in this developmental program yield blood cell diseases, such as leukemia. Although, in recent years, extensive molecular research in normal hematopoietic development has characterized transcription factors and their binding sites in the target gene promoters, the information generated is highly fragmented. In order to integrate this important regulatory information with the corresponding genomic sequences, we have developed a new database called Hematopoiesis Promoter Database (HemoPDB). HemoPDB is a comprehensive resource focused on transcriptional regulation during hematopoietic development and associated aberrances that result in malignancy. HemoPDB (version 1.0) contains 246 promoter sequences and 604 experimentally known cis-regulatory elements of 187 different transcription factors, with links to published references. Orthologous promoters from different species are linked with each other and displayed in the same database record, accompanied by a visual image of the promoters and corresponding annotations of cis-regulatory elements. HemoPDB may be searched for the promoter of a specific gene, transcription factors and target genes, and genes that are expressed in a certain cell type or lineage, through a user-friendly web interface at http://bioinformatics.med.ohio-state.edu/HemoPDB. Links to the documentation and other technical details are provided on this website.

Animals↗
PubMed2002

Transitive functional annotation by shortest-path analysis of gene expression data.

Current methods for the functional analysis of microarray gene expression data make the implicit assumption that genes with similar expression profiles have similar functions in cells. However, among genes involved in the same biological pathway, not all gene pairs show high expression similarity. Here, we propose that transitive expression similarity among genes can be used as an important attribute to link genes of the same biological pathway. Based on large-scale yeast microarray expression data, we use the shortest-path analysis to identify transitive genes between two given genes from the same biological process. We find that not only functionally related genes with correlated expression profiles are identified but also those without. In the latter case, we compare our method to hierarchical clustering, and show that our method can reveal functional relationships among genes in a more precise manner. Finally, we show that our method can be used to reliably predict the function of unknown genes from known genes lying on the same shortest path. We assigned functions for 146 yeast genes that are considered as unknown by the Saccharomyces Genome Database and by the Yeast Proteome Database. These genes constitute around 5% of the unknown yeast ORFome.

Cell Nucleus↗
PubMed2002

Transcription profiling of renal cell carcinoma.

AIMS: Our aim was to prepare a comprehensive catalogue of the changes in gene expression accompanying the development and progression of renal cell carcinoma, and to correlate these with histo-pathological, cytogenetic and clinical findings. METHODS: mRNA samples from paired neoplastic and non-cancerous human kidney tissue were labeled and hybridized in duplicate against high-density cDNA arrays. Two array technologies were used: 31,500-element transcriptome-wide nylon arrays for hybridization with 37 radioactively labelled sample pairs, and 4200-element kidney- and cancer-specific glass microarrays for hybridization with 19 fluorescently labelled sample pairs. RESULTS: We identified more than 1700 cDNA clones that show differential transcription levels in kidney tumor tissue compared to normal kidney tissue. The functional classification of 389 annotated genes provided views of the changes in the activities of specific biological processes in renal cancer. Among the biological processes with a large proportion of up-regulated genes we found cell adhesion, signal transduction, and nucleotide metabolism. Down-regulated processes included small molecule transport, ion homeostasis, and oxygen and radical metabolism. Furthermore, we explored the feasibility of molecular diagnosis for renal cell tumors using cDNA microarrays on glass slides, investigating the association of transcription levels with tumor type, progression, and a putative prognostic variable. The experimental data is available from the GEO gene expression database (http://www.ncbi.nlm.nih.gov/geo; accession no. GSE3), and a comprehensive presentation of the results is available in the web supplement (http://www.dkfz-heidelberg.de/abt0840/whuber/rcc). CONCLUSION: Transcription profiling using high-density cDNA arrays is a powerful method with the potential to improve cancer diagnosis and prognosis. The identification and classification of differentially transcribed genes, as described in our study, is the beginning of a more complete understanding of kidney cancer.

Carcinoma, Renal Cell↗
PubMed2000

Theory for the systemic definition of metabolic pathways and their use in interpreting metabolic function from a pathway-oriented perspective.

Cellular metabolism is most often described and interpreted in terms of the biochemical reactions that make up the metabolic network. Genomics is providing near complete information regarding the genes/gene products participating in cellular metabolism for a growing number of organisms. As the true functional units of metabolic systems are its pathways, the time has arrived to define metabolic pathways in the context of whole-cell metabolism for the analysis of the structural design and capabilities of the metabolic network. In this study, we present the theoretical foundations for the identification of the unique set of systemically independent biochemical pathways, termed extreme pathways, based on system stochiometry and limited thermodynamics. These pathways represent the edges of the steady-state flux cone derived from convex analysis, and they can be used to represent any flux distribution achievable by the metabolic network. An algorithm is presented to determine the set of extreme pathways for a system of any complexity and a classification scheme is introduced for the characterization of these pathways. The property of systemic independence is discussed along with its implications for issues related to metabolic regulation and the evolution of cellular metabolic networks. The underlying pathway structure that is determined from the set of extreme pathways now provides us with the ability to analyse, interpret, and perhaps predict metabolic function from a pathway-based perspective in addition to the traditional reaction-based perspective. The algorithm and classification scheme developed can be used to describe the pathway structure in annotated genomes to explore the capabilities of an organism.

Algorithms↗
PubMed2006

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↗
PubMed2002

A defect in a novel Nek-family kinase causes cystic kidney disease in the mouse and in zebrafish.

The murine autosomal recessive juvenile cystic kidney (jck) mutation results in polycystic kidney disease. We have identified in jck mice a mutation in Nek8, a novel and highly conserved member of the Nek kinase family. In vitro expression of mutated Nek8 results in enlarged, multinucleated cells with an abnormal actin cytoskeleton. To confirm that a defect in the Nek8 gene can cause cystic disease, we performed a cross-species analysis: injection of zebrafish embryos with a morpholino anti-sense oligonucleotide corresponding to the ortholog of Nek8 resulted in the formation of pronephric cysts. These results demonstrate that comparative analysis of gene function in different model systems represents a powerful means to annotate gene function.

Amino Acid Sequence↗
PubMed2002

Expression of human smooth muscle calponin in transgenic mice revealed with a bacterial artificial chromosome.

Defining regulatory elements governing cell-restricted gene expression can be difficult because cis-elements may reside tens of kilobases away from start site(s) of transcription. Artificial chromosomes, which harbor hundreds of kilobases of genomic DNA, preserve a large sequence landscape containing most, if not all, regulatory elements controlling the expression of a particular gene. Here, we report on the use of a bacterial artificial chromosome (BAC) to begin understanding the in vivo regulation of smooth muscle calponin (SM-Calp). Long and accurate polymerase chain reaction, sequencing, and in silico analyses facilitated the complete sequence annotation of a BAC harboring human SM-Calp (hSM-Calp). RNase protection, in situ hybridization, Western blotting, and immunohistochemistry assays showed the BAC clone faithfully expressed hSM-Calp in both cultured cells and transgenic mice. Moreover, expression of hSM-Calp mirrored that of endogenous mouse SM-Calp suggesting that all cis-regulatory elements governing hSM-Calp expression in vivo were contained within the BAC. These BAC mice represent a new model system in which to systematically assess regulatory elements governing SM-Calp transcription in vivo.

Animals↗
PubMed2004

Peptidomics of CNS-associated neurohemal systems of adult Drosophila melanogaster: a mass spectrometric survey of peptides from individual flies.

Neuropeptides are important messenger molecules that influence nearly all physiological processes. In insects, they can be released as neuromodulators within the central nervous system (CNS) or as neurohormones into the hemolymph. We analyzed the peptidome of neurohormonal release sites and associated secretory peptidergic neurons of adult Drosophila melanogaster. MALDI-TOF mass spectrometric analyzes were performed on single organs or cell cluster from individual flies. This first peptidomic characterization in adult fruit flies revealed 32 different neuropeptides. Peptides not directly predictable from previously cloned or annotated precursor genes were sequenced by tandem mass spectrometry. These peptides turned out to be either intermediate products of neuropeptide processing or shorter versions of known peptides. We found that the peptidome of the CNS-associated neurohemal organs is tagma-specific in Drosophila. Abdominal neurohemal organs and their supplying peptidergic neurons contain the capa gene products periviscerokinins and pyrokinin-1, thoracic neurohemal organs contain FMRFamides, and the neurohemal release sites of the brain contain pyrokinin-1(2-15), pyrokinin-2, corazonin, myosuppressin, and sNPF as their major putative release products. Our results show that peptidomic approaches are well suited to study differential neuropeptide expression or posttranslational modifications in morphologically defined parts of the nervous system and in a developmental and physiological context in animals as small as Drosophila melanogaster.

Animals↗
PubMed2004

Serial analysis of gene expression (SAGE) of host-plant resistance to the cassava mosaic disease (CMD).

Cassava mosaic disease (CMD) is a viral disease of the important tropical staple crop cassava (Manihot esculenta) and preferred management involves use of host-plant resistance. The best available resistance is controlled by a single dominant gene. Serial analysis of gene expression (SAGE) was used to analyze the gene expression pattern in a bulk of 40 each of CMD resistant and susceptible genotypes drawn from a gene mapping progeny. Messenger RNA used for the SAGE analysis came from plants that were exposed to heavy disease pressure over a period of 2 years in the field. A total of 12,786 tags were studied, divided into 5733 and 7053 tags from the resistant and susceptible genotypes, respectively. Tag annotation was by PCR amplification using the tag sequence as sense primer and 4000 cassava ESTs generated from the bulk of CMD resistant genotypes. Annotation of more than 30 differentially expressed tags revealed several genes expressed during systemic acquired resistance (SAR) in plants and other genes involved in cell-to-cell and cytoplasm-to-nucleus virus trafficking. Differential expression of the most abundantly expressed tag, corresponding to a beta-tubulin gene, was confirmed by Northern Analysis. RFLP analysis of the tags in the parents and bulks of the CMD mapping progeny revealed only one tag, a WRKY transcription factor, associated with the region bearing the dominant CMD gene.

Base Sequence↗
PubMed2005

The Drosophila gene CG9918 codes for a pyrokinin-1 receptor.

The database from the Drosophila Genome Project contains a gene, CG9918, annotated to code for a G protein-coupled receptor. We cloned the cDNA of this gene and functionally expressed it in Chinese hamster ovary cells. We tested a library of about 25 Drosophila and other insect neuropeptides, and seven insect biogenic amines on the expressed receptor and found that it was activated by low concentrations of the Drosophila neuropeptide, pyrokinin-1 (TGPSASSGLWFGPRLamide; EC50, 5 x 10(-8) M). The receptor was also activated by other Drosophila neuropeptides, terminating with the sequence PRLamide (Hug-gamma, ecdysis-triggering-hormone-1, pyrokinin-2), but in these cases about six to eight times higher concentrations were needed. The receptor was not activated by Drosophila neuropeptides, containing a C-terminal PRIamide sequence (such as ecdysis-triggering-hormone-2), or PRVamide (such as capa-1 and -2), or other neuropeptides and biogenic amines not related to the pyrokinins. This paper is the first conclusive report that CG9918 is a Drosophila pyrokinin-1 receptor gene.

Amino Acid Sequence↗
PubMed2006

Large-scale predictions of gram-negative bacterial protein subcellular locations.

Many species of Gram-negative bacteria are pathogenic bacteria that can cause disease in a host organism. This pathogenic capability is usually associated with certain components in Gram-negative cells. Therefore, developing an automated method for fast and reliable prediction of Gram-negative protein subcellular location will allow us to not only timely annotate gene products, but also screen candidates for drug discovery. However, protein subcellular location prediction is a very difficult problem, particularly when more location sites need to be involved and when unknown query proteins do not have significant homology to proteins of known subcellular locations. PSORT-B, a recently updated version of PSORT, widely used for predicting Gram-negative protein subcellular location, only covers five location sites. Also, the data set used to train PSORT-B contains many proteins with high degrees of sequence identity in a same location group and, hence, may bear a strong homology bias. To overcome these problems, a new predictor, called "Gneg-PLoc", is developed. Featured by fusing many basic classifiers each being trained with a stringent data set containing proteins with strictly less than 25% sequence identity to one another in a same location group, the new predictor can cover eight subcellular locations; that is, cytoplasm, extracellular space, fimbrium, flagellum, inner membrane, nucleoid, outer membrane, and periplasm. In comparison with PSORT-B, the new predictor not only covers more subcellular locations, but also yields remarkably higher success rates. Gneg-PLoc is available as a Web server at http://202.120.37.186/bioinf/Gneg. To support the demand of people working in the relevant areas, a downloadable file is provided at the same Web site to list the results identified by Gneg-PLoc for 49 907 Gram-negative protein entries in the Swiss-Prot database that have no subcellular location annotations or are annotated with uncertain terms. The large-scale results will be updated twice a year to cover the new entries of Gram-negative bacterial proteins and reflect the new development of Gneg-PLoc.

Bacterial Proteins↗
PubMed2003

Identification of temporal patterns of gene expression in the uteri of immature, ovariectomized mice following exposure to ethynylestradiol.

Estrogen induction of uterine wet weight provides an excellent model to investigate relationships between changes in global gene expression and well-characterized physiological responses. In this study, time course microarray GeneChip data were analyzed using a novel approach to identify temporal changes in uterine gene expression following treatment of immature ovariectomized C57BL/6 mice with 0.1 mg/kg 17alpha-ethynylestradiol. Functional gene annotation information from public databases facilitated the association of changes in gene expression with physiological outcomes, which allowed detailed mechanistic inferences to be drawn regarding cell cycle control and proliferation, transcription and translation, structural tissue remodeling, and immunologic responses. These systematic approaches confirm previously established responses, identify novel estrogen-regulated transcriptional effects, and disclose the coordinated activation of multiple modes of action that support the uterotrophic response elicited by estrogen. In particular, it was possible to elucidate the physiological significance of the dramatic induction of arginase, a classic estrogenic response, by elucidating its mechanistic relevance and delineating the role of arginine and ornithine utilization in the estrogen-stimulated induction of uterine wet weight.

Animals↗
PubMed2026

Deciphering the Role of LNX2 as a Potential Contributor to Neurodevelopmental Disorders.

BACKGROUND/OBJECTIVES: Attention-deficit/hyperactivity disorder (ADHD) is a common neurodevelopmental condition characterized by a complex and multifactorial genetic architecture. In this study, we report a male patient, born to non-consanguineous healthy parents, presenting with ADHD and oppositional defiant disorder (ODD). METHODS: Trio-based whole-exome sequencing (WES) was performed in the proband and both parents. Variant classification was performed according to American College of Medical Genetics and Genomics (ACMG) guidelines, and the potential pathogenicity of the identified variant was further assessed through multiple in silico prediction algorithms and protein structural analyses. RESULTS: WES identified a homozygous variant in the LNX2 gene (NM_153371.4: c.1165G>A, p.Ala389Thr), classified as a variant of uncertain significance (VUS) and supported by multiple in silico predictions. LNX2 is expressed during brain development and encodes an E3 ubiquitin ligase involved in neuronal differentiation and synaptic function. The identified variant is located within the PDZ2 domain, a functionally relevant region involved in protein-protein interactions. Although the variant is reported in population databases (gnomAD ID: rs148429804), it has not been associated with any clinical phenotype, and its presence in the homozygous state has been reported only once, remaining extremely rare and lacking clinical annotation. Structural modelling predicted localized rearrangement of the hydrogen-bonding network within the PDZ2 domain without major conformational changes. Integrative transcriptomic, and single-cell analyses further supported the biological relevance of LNX2 in neurodevelopment, highlighting its preferential association with neuronal projection-cell networks, synaptic vesicle trafficking pathways, and neuron-specific regulatory programs. CONCLUSION: Although the identified LNX2 variant cannot be considered causative for the patient's phenotype and a definitive disease-gene relationship cannot be established based on a single individual, the complementary genetic, structural, and transcriptomic findings support the biological plausibility of LNX2 as a candidate gene for neurodevelopmental disorders. Additional independent patients and functional studies will be required to clarify its contribution to human disease.

Child↗
PubMed2001

GlycoSuiteDB: a new curated relational database of glycoprotein glycan structures and their biological sources.

GlycoSuiteDB is a relational database that curates information from the scientific literature on glyco-protein derived glycan structures, their biological sources, the references in which the glycan was described and the methods used to determine the glycan structure. To date, the database includes most published O:-linked oligosaccharides from the last 50 years and most N:-linked oligosaccharides that were published in the 1990s. For each structure, information is available concerning the glycan type, linkage and anomeric configuration, mass and composition. Detailed information is also provided on native and recombinant sources, including tissue and/or cell type, cell line, strain and disease state. Where known, the proteins to which the glycan structures are attached are reported, and cross-references to the SWISS-PROT/TrEMBL protein sequence databases are given if applicable. The GlycoSuiteDB annotations include literature references which are linked to PubMed, and detailed information on the methods used to determine each glycan structure are noted to help the user assess the quality of the structural assignment. GlycoSuiteDB has a user-friendly web interface which allows the researcher to query the database using mono-isotopic or average mass, monosaccharide composition, glycosylation linkages (e.g. N:- or O:-linked), reducing terminal sugar, attached protein, taxonomy, tissue or cell type and GlycoSuiteDB accession number. Advanced queries using combinations of these parameters are also possible. GlycoSuiteDB can be accessed on the web at http://www.glycosuite.com.

Animals↗
PubMedDate not supplied

A theory of optimal differential gene expression.

We investigate a model of optimal regulation, intended to describe large-scale differential gene expression. Relations between the optimal expression patterns and the function of genes are deduced from an optimality principle: the regulators have to maximise a fitness function which they influence directly via a cost term, and indirectly via their control on important cell variables, such as metabolic fluxes. According to the model, the optimal linear response to small perturbations reflects the regulators' functions, namely their linear influences on the cell variables. The optimal behaviour can be realised by a linear feedback mechanism. Known or assumed properties of response coefficients lead to predictions about regulation patterns. A symmetry relation predicted for deletion experiments is verified with gene expression data. Where the optimality assumption is valid, our results justify the use of expression data for functional annotation and for pathway reconstruction and suggest the use of linear factor models for the analysis of gene expression data.

Adaptation, Physiological↗
PubMedDate not supplied

A survey of canine expressed sequence tags and a display of their annotations through a flexible web-based interface.

We have initially sequenced approximately 8,000 canine expressed sequence tags (ESTs) from several complementary DNA (cDNA) libraries: testes, whole brain, and Madin-Darby canine kidney (MDCK) cells. Analysis of these sequences shows that they provide partial sequence information for about 5%-10% of the canine genes. An analysis pipeline has been created to cluster the ESTs and to map individual ESTs as well as clustered ESTs to both the human genome and the human proteome. Gene ontology (GO) terms have been assigned to the ESTs and clusters based on their top matches to the International Protein Index (IPI) set of human proteins. The data generated is stored in a MySQL relational database for analysis and display. A Web-based Perl script has been written to display the analyzed data to the scientific community.

Animals↗
PubMed2025

High-quality peptide evidence for annotating non-canonical open reading frames as human proteins.

A major scientific drive is to characterize the protein-coding genome as it provides the primary basis for the study of human health. But the fundamental question remains: what has been missed in prior genomic analyses? Over the past decade, the translation of non-canonical open reading frames (ncORFs) has been observed across human cell types and disease states, with major implications for proteomics, genomics, and clinical science. However, the impact of ncORFs has been limited by the absence of a large-scale understanding of their contribution to the human proteome. Here, we report the collaborative efforts of stakeholders in proteomics, immunopeptidomics, Ribo-seq ORF discovery, and gene annotation, to produce a consensus landscape of protein-level evidence for ncORFs. We show that at least 25% of a set of 7,264 ncORFs give rise to translated gene products, yielding over 3,000 peptides in a pan-proteome analysis encompassing 3.8 billion mass spectra from 95,520 experiments. With these data, we developed an annotation framework for ncORFs and created public tools for researchers through GENCODE and PeptideAtlas. This work will provide a platform to advance ncORF-derived proteins in biomedical discovery and, beyond humans, diverse animals and plants where ncORFs are similarly observed.

GENCODE↗
PubMed2005

Assessing the precision of high-throughput computational and laboratory approaches for the genome-wide identification of protein subcellular localization in bacteria.

BACKGROUND: Identification of a bacterial protein's subcellular localization (SCL) is important for genome annotation, function prediction and drug or vaccine target identification. Subcellular fractionation techniques combined with recent proteomics technology permits the identification of large numbers of proteins from distinct bacterial compartments. However, the fractionation of a complex structure like the cell into several subcellular compartments is not a trivial task. Contamination from other compartments may occur, and some proteins may reside in multiple localizations. New computational methods have been reported over the past few years that now permit much more accurate, genome-wide analysis of the SCL of protein sequences deduced from genomes. There is a need to compare such computational methods with laboratory proteomics approaches to identify the most effective current approach for genome-wide localization characterization and annotation. RESULTS: In this study, ten subcellular proteome analyses of bacterial compartments were reviewed. PSORTb version 2.0 was used to computationally predict the localization of proteins reported in these publications, and these computational predictions were then compared to the localizations determined by the proteomics study. By using a combined approach, we were able to identify a number of contaminants and proteins with dual localizations, and were able to more accurately identify membrane subproteomes. Our results allowed us to estimate the precision level of laboratory subproteome studies and we show here that, on average, recent high-precision computational methods such as PSORTb now have a lower error rate than laboratory methods. CONCLUSION: We have performed the first focused comparison of genome-wide proteomic and computational methods for subcellular localization identification, and show that computational methods have now attained a level of precision that is exceeding that of high-throughput laboratory approaches. We note that analysis of all cellular fractions collectively is required to effectively provide localization information from laboratory studies, and we propose an overall approach to genome-wide subcellular localization characterization that capitalizes on the complementary nature of current laboratory and computational methods.

Bacterial Proteins↗