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PubMed2006

From 'omes to biology.

Technologies that have emerged from the genome project have dramatically increased our ability to generate data on the way in which organisms respond to their environments, how they execute their programmes of development and growth, and how these are altered in the development of disease states. However, our ability to analyse these large datasets has not kept pace with our ability to generate them and consequently new strategies must be developed to address the issues associated with their analysis. One approach that we have employed quite successfully is to look at data from microarrays (or proteomics or metabolomics experiments) not as independent datasets, but rather as elements of a much larger body of biological information across various scales that must be integrated with, and interpreted within, the context of such ancillary data. Here we outline the general approach and provide three examples from published studies of the way in which we have applied this strategy.

Animals↗
PubMed2000

Positional cloning utilizing genomic DNA microarrays: the Niemann-Pick type C gene as a model system.

A major obstacle in positional cloning is identifying the specific mutated gene from within a large physical contig. Here we describe the application of DNA microarray technology to a defined genomic region (physical map) to identify: (i) exons without a priori sequence data and (ii) the disease gene based on differential gene expression in a recessive disorder. The feasibility was tested using resources from the positional cloning of the Neimann-Pick Type C (NP-C) disease gene, NPC1. To identify NPC1 exons and optimize the technology, an array was generated from genomic fragments of the 110-kb bacterial artificial chromosome, 108N2, which encodes NPC1. First, as a test case for blindly identifying exons, fluorescently labeled NPC1 cDNA identified 108N2 fragments that contained NPC1 exons, many of which also contained intronic sequences and could be used to determine part of the NPC1 genomic structure. Second, to demonstrate that the NPC1 disease gene could be identified based upon differential gene expression, subarrays of 108N2 fragments were hybridized with fluorescently labeled cDNA probes generated from total RNA from hamster cell lines differentially expressing NPC1. A probe derived from the NP-C cell line CT60 did not detect NPC1 exons or other genomic fragments from 108N2. In contrast, several NPC1 exons were detected by a probe generated from the non-NP-C cell line 911D5A13, which was derived from CT60, and expressed NPC1 as a consequence of stable transduction with a YAC that contains NPC1 and encompasses 108N2. Thus, the array technology identified NPC1 as a candidate gene based on a physical contig and differential NPC1 expression between NP-C and non-NP-C cells. This technique should facilitate gene identification when a physical contig exists for a region of interest and mutations result in changes in the mRNA level of the disease gene or portions thereof.

Animals↗
PubMed2004

Predicting the operon structure of Bacillus subtilis using operon length, intergene distance, and gene expression information.

We predict the operon structure of the Bacillus subtilis genome using the average operon length, the distance between genes in base pairs, and the similarity in gene expression measured in time course and gene disruptant experiments. By expressing the operon prediction for each method as a Bayesian probability, we are able to combine the four prediction methods into a Bayesian classifier in a statistically rigorous manner. The discriminant value for the Bayesian classifier can be chosen by considering the associated cost of misclassifying an operon or a non-operon gene pair. For equal costs, an overall accuracy of 88.7% was found in a leave-one-out analysis for the joint Bayesian classifier, whereas the individual information sources yielded accuracies of 58.1%, 83.1%, 77.3%, and 71.8% respectively. The predicted operon structure based on the joint Bayesian classifier is available from the DBTBS database (http://dbtbs.hgc.jp).

Bacillus subtilis↗
PubMed2006

Gene expression signature-based chemical genomic prediction identifies a novel class of HSP90 pathway modulators.

Although androgen receptor (AR)-mediated signaling is central to prostate cancer, the ability to modulate AR signaling states is limited. Here we establish a chemical genomic approach for discovery and target prediction of modulators of cancer phenotypes, as exemplified by AR signaling. We first identify AR activation inhibitors, including a group of structurally related compounds comprising celastrol, gedunin, and derivatives. To develop an in silico approach for target pathway identification, we apply a gene expression-based analysis that classifies HSP90 inhibitors as having similar activity to celastrol and gedunin. Validating this prediction, we demonstrate that celastrol and gedunin inhibit HSP90 activity and HSP90 clients, including AR. Broadly, this work identifies new modes of HSP90 modulation through a gene expression-based strategy.

Antibiotics, Antineoplastic↗
PubMed2004

Genomic analysis of the nitrate response using a nitrate reductase-null mutant of Arabidopsis.

A nitrate reductase (NR)-null mutant of Arabidopsis was constructed that had a deletion of the major NR gene NIA2 and an insertion in the NIA1 NR gene. This mutant had no detectable NR activity and could not use nitrate as the sole nitrogen source. Starch mobilization was not induced by nitrate in this mutant but was induced by ammonium, indicating that nitrate was not the signal for this process. Microarray analysis of gene expression revealed that 595 genes responded to nitrate (5 mm nitrate for 2 h) in both wild-type and mutant plants. This group of genes was overrepresented most significantly in the functional categories of energy, metabolism, and glycolysis and gluconeogenesis. Because the nitrate response of these genes was NR independent, nitrate and not a downstream metabolite served as the signal. The microarray analysis also revealed that shoots can be as responsive to nitrate as roots, yet there was substantial organ specificity to the nitrate response.

Arabidopsis↗
PubMed2002

Genomic structure of the rat and mouse histamine N-methyltransferase gene.

Northern blotting analysis revealed different tissue distribution patterns of HMT mRNA between mice and rats. In the mouse, mRNA expression was detected in the brain, kidney and liver. In the rat, there was an extremely high mRNA signal only in the kidney. We isolated and characterized the rat and mouse histamine N-methyltransferase (HMT) genes from genomic DNA libraries. The rat HMT gene consists of 6 exons and 5 introns. The mouse HMT gene structure was similar to that of the rat, but had one additional exon 5' upstream from the exon containing a start codon, resulting in seven exons. Several long interspersed repetitive elements were located in the 5' flanking region of the rat and mouse HMT gene. Despite high sequence conservation of the regions around exon 6 and the 3' flanking region, the 5' flanking region had little similarity between the rat and mouse. Marked sequence similarities between rat and mouse introns were present near splice sites and outside the junction residues, suggesting the evolutionary relationship between the structural features of the rat and mouse HMT genes. This observation may explain the species difference of the tissue expression pattern of HMT mRNA.

Animals↗
PubMed2003

Reconstruction of the central carbon metabolism of Aspergillus niger.

The topology of central carbon metabolism of Aspergillus niger was identified and the metabolic network reconstructed, by integrating genomic, biochemical and physiological information available for this microorganism and other related fungi. The reconstructed network may serve as a valuable database for annotation of genes identified in future genome sequencing projects on aspergilli. Based on the metabolic reconstruction, a stoichiometric model was set up that includes 284 metabolites and 335 reactions, of which 268 represent biochemical conversions and 67 represent transport processes between the different intracellular compartments and between the cell and the extracellular medium. The stoichiometry of the metabolic reactions was used in combination with biosynthetic requirements for growth and pseudo-steady state mass balances over intracellular metabolites for the quantification of metabolic fluxes using metabolite balancing. This framework was employed to perform an in silico characterisation of the phenotypic behaviour of A. niger grown on different carbon sources. The effects on growth of single reaction deletions were assessed and essential biochemical reactions were identified for different carbon sources. Furthermore, application of the stoichiometric model for assessing the metabolic capabilities of A. niger to produce metabolites was evaluated by using succinate production as a case study.

Aspergillus niger↗
PubMed2004

Construction of representative transcript and protein sets of human, mouse, and rat as a platform for their transcriptome and proteome analysis.

The number of mammalian transcripts identified by full-length cDNA projects and genome sequencing projects is increasing remarkably. Clustering them into a strictly nonredundant and comprehensive set provides a platform for functional analysis of the transcriptome and proteome, but the quality of the clustering and predictive usefulness have previously required manual curation to identify truncated transcripts and inappropriate clustering of closely related sequences. A Representative Transcript and Protein Sets (RTPS) pipeline was previously designed to identify the nonredundant and comprehensive set of mouse transcripts based on clustering of a large mouse full-length cDNA set (FANTOM2). Here we propose an alternative method that is more robust, requires less manual curation, and is applicable to other organisms in addition to mouse. RTPSs of human, mouse, and rat have been produced by this method and used for validation. Their comprehensiveness and quality are discussed by comparison with other clustering approaches. The RTPSs are available at .

Animals↗
PubMed2001

On reporting fold differences.

As we enter an age in which genomics and bioinformatics make possible the discovery of new knowledge about the biological characteristics of an organism, it is critical that we attempt to report newly discovered "significant" phenotypes only when they are actually of significance. With the relative youth of genome-scale gene expression technologies, how to make such distinctions has yet to be better defined. We present a "mask technology" by which to filter out those levels of gene expression that fall within the noise of the experimental techniques being employed. Conversely, our technique can lend validation to significant fold differences in expression level even when the fold value may appear quite small (e.g. 1.3). Given array-organized expression level results from a pair of identical experiments, our ID Mask Tool enables the automated creation of a two-dimensional "region of insignificance" that can then be used with subsequent data analyses. Fundamentally, this should enable researchers to report on findings that are more likely to be in nature truly meaningful. Moreover, this can prevent major investments of time, energy, and biological resources into the pursuit of candidate genes that represent false positives.

Computational Biology↗
PubMed2004

Genomic and proteomic determinants of outcome in patients undergoing thoracoabdominal aortic aneurysm repair.

Thoracoabdominal aortic aneurysm repair, with its requisite intraoperative mesenteric ischemia-reperfusion, often results in the development of systemic inflammatory response syndrome, multiorgan dysfunction syndrome (MODS), and death. In the present study, an adverse clinical outcome following thoracoabdominal aortic aneurysm repair was identified by blood leukocyte genomic and plasma proteomic responses. Time-dependent changes in the expression of 146 genes from blood leukocytes were observed (p < 0.001). Expression of 138 genes (p < 0.001) and the concentration of seven plasma proteins discriminated between patients who developed MODS and those who did not, and many of these differences were evident even before surgery. These findings suggest that changes in blood leukocyte gene expression and plasma protein concentrations can illuminate pathophysiological processes that are subsequently associated with the clinical sequelae of systemic inflammatory response syndrome and MODS. These changes in gene expression and plasma protein concentrations are often observed before surgery, consistent with either a genetic predisposition or pre-existing inflammatory state.

Aged↗
PubMed2002

A genome-wide screen for methyl methanesulfonate-sensitive mutants reveals genes required for S phase progression in the presence of DNA damage.

We performed a systematic screen of the set of approximately 5,000 viable Saccharomyces cerevisiae haploid gene deletion mutants and have identified 103 genes whose deletion causes sensitivity to the DNA-damaging agent methyl methanesulfonate (MMS). In total, 40 previously uncharacterized alkylation damage response genes were identified. Comparison with the set of genes known to be transcriptionally induced in response to MMS revealed surprisingly little overlap with those required for MMS resistance, indicating that transcriptional regulation plays little, if any, role in the response to MMS damage. Clustering of the MMS response genes on the basis of their cross-sensitivities to hydroxyurea, UV radiation, and ionizing radiation revealed a DNA damage core of genes required for responses to a broad range of DNA-damaging agents. Of particular significance, we identified a subset of genes that show a specific MMS response, displaying defects in S phase progression only in the presence of MMS. These genes may promote replication fork stability or processivity during encounters between replication forks and DNA damage.

DNA Damage↗
PubMed2004

Antimicrobial drug discovery through bacteriophage genomics.

Over evolutionary time bacteriophages have developed unique proteins that arrest critical cellular processes to commit bacterial host metabolism to phage reproduction. Here, we apply this concept of phage-mediated bacterial growth inhibition to antibiotic discovery. We sequenced 26 Staphylococcus aureus phages and identified 31 novel polypeptide families that inhibited growth upon expression in S. aureus. The cellular targets for some of these polypeptides were identified and several were shown to be essential components of the host DNA replication and transcription machineries. The interaction between a prototypic pair, ORF104 of phage 77 and DnaI, the putative helicase loader of S. aureus, was then used to screen for small molecule inhibitors. Several compounds were subsequently found to inhibit both bacterial growth and DNA synthesis. Our results suggest that mimicking the growth-inhibitory effect of phage polypeptides by a chemical compound, coupled with the plethora of phages on earth, will yield new antibiotics to combat infectious diseases.

Anti-Bacterial Agents↗
PubMed2004

An ORFeome-based analysis of human transcription factor genes and the construction of a microarray to interrogate their expression.

Transcription factors (TFs) are essential regulators of gene expression, and mutated TF genes have been shown to cause numerous human genetic diseases. Yet to date, no single, comprehensive database of human TFs exists. In this work, we describe the collection of an essentially complete set of TF genes from one depiction of the human ORFeome, and the design of a microarray to interrogate their expression. Taking 1468 known TFs from TRANSFAC, InterPro, and FlyBase, we used this seed set to search the ScriptSure human transcriptome database for additional genes. ScriptSure's genome-anchored transcript clusters allowed us to work with a nonredundant high-quality representation of the human transcriptome. We used a high-stringency similarity search by using BLASTN, and a protein motif search of the human ORFeome by using hidden Markov models of DNA-binding domains known to occur exclusively or primarily in TFs. Four hundred ninety-four additional TF genes were identified in the overlap between the two searches, bringing our estimate of the total number of human TFs to 1962. Zinc finger genes are by far the most abundant family (762 members), followed by homeobox (199 members) and basic helix-loop-helix genes (117 members). We designed a microarray of 50-mer oligonucleotide probes targeted to a unique region of the coding sequence of each gene. We have successfully used this microarray to interrogate TF gene expression in species as diverse as chickens and mice, as well as in humans.

Gene Expression Profiling↗
PubMed2003

Design and assessment of a fast algorithm for identifying specific probes for human and mouse genes.

MOTIVATION: Mammalian genomes are highly complex. To identify the unique sequences of each gene in a mammalian gene database containing tens of thousands of DNA sequences is a computation intensive task. With the advent of parallel genetic analysis methods such as microarrays and the availability of more and more whole genome sequences of organisms, an algorithm allowing speedy identification of the unique gene probes for functional studies of individual genes will be a very useful tool. RESULTS: We have developed a fast algorithm as well as a software program based on the algorithm for identifying gene specific probes of complex organisms. The algorithm was applied to the assemblies of gene sequences and was highly efficient for large databases such as the TIGR human THC and mouse TC databases. The results were assessed with the BLAST sequence alignment software. Two probe data sets have been compiled to contain specific probes for around 100 000 putative human gene transcripts and 70 000 putative mouse gene transcripts. AVAILABILITY: The gene specific probes for the putative human and mouse genes referenced in the TIGR gene indices are available at: ftp://genestamp.ibms.sinica.edu.tw/pub/SpecificP/. The software program and the source codes are available upon request.

Algorithms↗
PubMed2003

Forward & reverse chemical genetics using SPOS-based combinatorial chemistry.

Combinatorial chemistry is being applied to diverse problems in the biological and pharmaceutical sciences. This review will describe an emerging application called "chemical genetics" or "chemical genomics" - genetics and genomics are often used interchangeably in this context. In forward chemical genomics, chemical libraries are tested in living systems to discover compounds that cause a desirable effect. Subsequently, the protein target is identified using various biochemical and molecular biological tools. By this method, we gain insights into the inner workings of life, and indeed, in some forms this has been the path by which most of the pharmacopoeia was discovered. In reverse chemical genetics, proteins of interest are used to probe compound collections, and those compounds that bind the proteins of interest are used to treat living systems and observed for interesting biological responses. Plausible biological roles of these proteins are inferred from the effects of the compounds because they are assumed to generally inhibit, or more rarely, stimulate, the protein's functions. Interestingly, the reverse genetic approach is emerging as the leading model for drug discovery today. Different methods and cases will be described to illustrate forward and reverse paradigms, including those developed in the author's laboratory.

Combinatorial Chemistry Techniques↗
PubMed2004

Fatty acid synthesis in Xylella fastidiosa: correlations between genome studies, 13C NMR data, and molecular models.

Xylella fastidiosa was the first plant pathogen to have its complete genome sequence elucidated. Routine database analyses suggested that two enzymes essential for fatty acid synthesis were missing, one of these is the holo-acyl-carrier-protein synthase. However, here we demonstrate, using (13)C NMR spectroscopy, that X. fastidiosa is indeed able to synthesize fatty acids from acetate via an apparently conventional metabolic pathway. We further identify a gene product HetI, an alternative phosphopantetheinyl transferase, which we propose to fill the missing link. Homology modeling of HetI shows conservation of the Coenzyme A binding site suggesting it to be an active enzyme and reveals several interesting structural features when compared with the surfactin synthase-activating enzyme, on which the model was built. These include a simplified topology due to N- and C-terminal deletions and the observation of a novel serine ladder.

Acetates↗
PubMed2001

A comparison of genetic network models.

With the completion of the sequencing of the human genome, the need for tools capable of unraveling the interaction and functionality of genes becomes extremely urgent. In answer to this quest, the advent of microarray technology provides the opportunity to perform large scale gene expression analyses. Recently, genetic networks were proposed as a possible methodology for modeling genetic interactions. Since then, a wide variety of different models have been introduced. However, it is, in general, unclear what the strengths and weaknesses of each of these approaches are and where these models overlap and differ. This paper compares different genetic modeling approaches that attempt to extract the gene regulation matrix from expression data. A taxonomy of continuous genetic network models is proposed and the following important characteristics are suggested and employed to compare the models: (1) inferential power; (2) predictive power; (3) robustness; (4) consistency; (5) stability and (6) computational cost. Where possible, synthetic time series data are employed to investigate some of these properties.

Classification↗
PubMed2006

An efficient and high-throughput approach for experimental validation of novel human gene predictions.

A highly automated RT-PCR-based approach has been established to validate novel human gene predictions with no prior experimental evidence of mRNA splicing (ab initio predictions). Ab initio gene predictions were selected for high-throughput validation using predicted protein classification, sequence similarity to other genomes, colocalization with an MPSS tag, or microarray expression. Initial microarray prioritization followed by RT-PCR validation was the most efficient combination, resulting in approximately 35% of the ab initio predictions being validated by RT-PCR. Of the 7252 novel genes that were prioritized and processed, 796 constituted real transcripts. In addition, high-throughput RACE successfully extended the 5' and/or 3' ends of >60% of RT-PCR-validated genes. Reevaluation of these transcripts produced 574 novel transcripts using RefSeq as a reference. RT-PCR sequencing in combination with RACE on ab initio gene predictions could be used to define the transcriptome across all species.

Algorithms↗