Biomedical subjects

Jeremy D Glasner

Publications and source records attributed to Jeremy D Glasner.

14 recordsLinked to original sources

PubMed2006

Analyzing the dose-dependence of the Saccharomyces cerevisiae global transcriptional response to methyl methanesulfonate and ionizing radiation.

BACKGROUND: One of the most crucial tasks for a cell to ensure its long term survival is preserving the integrity of its genetic heritage via maintenance of DNA structure and sequence. While the DNA damage response in the yeast Saccharomyces cerevisiae, a model eukaryotic organism, has been extensively studied, much remains to be elucidated about how the organism senses and responds to different types and doses of DNA damage. We have measured the global transcriptional response of S. cerevisiae to multiple doses of two representative DNA damaging agents, methyl methanesulfonate (MMS) and gamma radiation. RESULTS: Hierarchical clustering of genes with a statistically significant change in transcription illustrated the differences in the cellular responses to MMS and gamma radiation. Overall, MMS produced a larger transcriptional response than gamma radiation, and many of the genes modulated in response to MMS are involved in protein and translational regulation. Several clusters of coregulated genes whose responses varied with DNA damaging agent dose were identified. Perhaps the most interesting cluster contained four genes exhibiting biphasic induction in response to MMS dose. All of the genes (DUN1, RNR2, RNR4, and HUG1) are involved in the Mec1p kinase pathway known to respond to MMS, presumably due to stalled DNA replication forks. The biphasic responses of these genes suggest that the pathway is induced at lower levels as MMS dose increases. The genes in this cluster with a threefold or greater transcriptional response to gamma radiation all showed an increased induction with increasing gamma radiation dosage. CONCLUSION: Analyzing genome-wide transcriptional changes to multiple doses of external stresses enabled the identification of cellular responses that are modulated by magnitude of the stress, providing insights into how a cell deals with genotoxicity.

DNA Damage↗

PubMed2006

Genome-wide detection and analysis of homologous recombination among sequenced strains of Escherichia coli.

BACKGROUND: Comparisons of complete bacterial genomes reveal evidence of lateral transfer of DNA across otherwise clonally diverging lineages. Some lateral transfer events result in acquisition of novel genomic segments and are easily detected through genome comparison. Other more subtle lateral transfers involve homologous recombination events that result in substitution of alleles within conserved genomic regions. This type of event is observed infrequently among distantly related organisms. It is reported to be more common within species, but the frequency has been difficult to quantify since the sequences under comparison tend to have relatively few polymorphic sites. RESULTS: Here we report a genome-wide assessment of homologous recombination among a collection of six complete Escherichia coli and Shigella flexneri genome sequences. We construct a whole-genome multiple alignment and identify clusters of polymorphic sites that exhibit atypical patterns of nucleotide substitution using a random walk-based method. The analysis reveals one large segment (approximately 100 kb) and 186 smaller clusters of single base pair differences that suggest lateral exchange between lineages. These clusters include portions of 10% of the 3,100 genes conserved in six genomes. Statistical analysis of the functional roles of these genes reveals that several classes of genes are over-represented, including those involved in recombination, transport and motility. CONCLUSION: We demonstrate that intraspecific recombination in E. coli is much more common than previously appreciated and may show a bias for certain types of genes. The described method provides high-specificity, conservative inference of past recombination events.

Alleles↗

PubMed2006

CGHScan: finding variable regions using high-density microarray comparative genomic hybridization data.

BACKGROUND: Comparative genomic hybridization can rapidly identify chromosomal regions that vary between organisms and tissues. This technique has been applied to detecting differences between normal and cancerous tissues in eukaryotes as well as genomic variability in microbial strains and species. The density of oligonucleotide probes available on current microarray platforms is particularly well-suited for comparisons of organisms with smaller genomes like bacteria and yeast where an entire genome can be assayed on a single microarray with high resolution. Available methods for analyzing these experiments typically confine analyses to data from pre-defined annotated genome features, such as entire genes. Many of these methods are ill suited for datasets with the number of measurements typical of high-density microarrays. RESULTS: We present an algorithm for analyzing microarray hybridization data to aid identification of regions that vary between an unsequenced genome and a sequenced reference genome. The program, CGHScan, uses an iterative random walk approach integrating multi-layered significance testing to detect these regions from comparative genomic hybridization data. The algorithm tolerates a high level of noise in measurements of individual probe intensities and is relatively insensitive to the choice of method for normalizing probe intensity values and identifying probes that differ between samples. When applied to comparative genomic hybridization data from a published experiment, CGHScan identified eight of nine known deletions in a Brucella ovis strain as compared to Brucella melitensis. The same result was obtained using two different normalization methods and two different scores to classify data for individual probes as representing conserved or variable genomic regions. The undetected region is a small (58 base pair) deletion that is below the resolution of CGHScan given the array design employed in the study. CONCLUSION: CGHScan is an effective tool for analyzing comparative genomic hybridization data from high-density microarrays. The algorithm is capable of accurately identifying known variable regions and is tolerant of high noise and varying methods of data preprocessing. Statistical analysis is used to define each variable region providing a robust and reliable method for rapid identification of genomic differences independent of annotated gene boundaries.

Algorithms↗

PubMed2006

Escherichia coli K-12: a cooperatively developed annotation snapshot--2005.

The goal of this group project has been to coordinate and bring up-to-date information on all genes of Escherichia coli K-12. Annotation of the genome of an organism entails identification of genes, the boundaries of genes in terms of precise start and end sites, and description of the gene products. Known and predicted functions were assigned to each gene product on the basis of experimental evidence or sequence analysis. Since both kinds of evidence are constantly expanding, no annotation is complete at any moment in time. This is a snapshot analysis based on the most recent genome sequences of two E.coli K-12 bacteria. An accurate and up-to-date description of E.coli K-12 genes is of particular importance to the scientific community because experimentally determined properties of its gene products provide fundamental information for annotation of innumerable genes of other organisms. Availability of the complete genome sequence of two K-12 strains allows comparison of their genotypes and mutant status of alleles.

Congresses as Topic↗

PubMed2006

ASAP: a resource for annotating, curating, comparing, and disseminating genomic data.

ASAP is a comprehensive web-based system for community genome annotation and analysis. ASAP is being used for a large-scale effort to augment and curate annotations for genomes of enterobacterial pathogens and for additional genome sequences. New tools, such as the genome alignment program Mauve, have been incorporated into ASAP in order to improve display and analysis of related genomes. Recent improvements to the database and challenges for future development of the system are discussed. ASAP is available on the web at https://asap.ahabs.wisc.edu/asap/logon.php.

Databases, Nucleic Acid↗

PubMed2006

Genomic mining for Aspergillus natural products.

The genus Aspergillus is renowned for its ability to produce a myriad of bioactive secondary metabolites. Although the propensity of biosynthetic genes to form contiguous clusters greatly facilitates assignment of putative secondary metabolite genes in the completed Aspergillus genomes, such analysis cannot predict gene expression and, ultimately, product formation. To circumvent this deficiency, we have examined Aspergillus nidulans microarrays for expressed secondary metabolite gene clusters by using the transcriptional regulator LaeA. Deletion or overexpression of laeA clearly identified numerous secondary metabolite clusters. A gene deletion in one of the clusters eliminated the production of the antitumor compound terrequinone A, a metabolite not described, from A. nidulans. In this paper, we highlight that LaeA-based genome mining helps decipher the secondary metabolome of Aspergilli and provides an unparalleled view to assess secondary metabolism gene regulation.

Aspergillus nidulans↗

PubMed2004

Systematic mutagenesis of the Escherichia coli genome.

A high-throughput method has been developed for the systematic mutagenesis of the Escherichia coli genome. The system is based on in vitro transposition of a modified Tn5 element, the Sce-poson, into linear fragments of each open reading frame. The transposon introduces both positive (kanamycin resistance) and negative (I-SceI recognition site) selectable markers for isolation of mutants and subsequent allele replacement, respectively. Reaction products are then introduced into the genome by homologous recombination via the lambdaRed proteins. The method has yielded insertion alleles for 1976 genes during a first pass through the genome including, unexpectedly, a number of known and putative essential genes. Sce-poson insertions can be easily replaced by markerless mutations by using the I-SceI homing endonuclease to select against retention of the transposon as demonstrated by the substitution of amber and/or in-frame deletions in six different genes. This allows a Sce-poson-containing gene to be specifically targeted for either designed or random modifications, as well as permitting the stepwise engineering of strains with multiple mutations. The promiscuous nature of Tn5 transposition also enables a targeted gene to be dissected by using randomly inserted Sce-posons as shown by a lacZ allelic series. Finally, assessment of the insertion sites by an iterative weighted matrix algorithm reveals that these hyperactive Tn5 complexes generally recognize a highly degenerate asymmetric motif on one end of the target site helping to explain the randomness of Tn5 transposition.

Alleles↗

PubMed2004

Comparative whole-genome hybridization reveals genomic islands in Brucella species.

Brucella species are responsible for brucellosis, a worldwide zoonotic disease causing abortion in domestic animals and Malta fever in humans. Based on host preference, the genus is divided into six species. Brucella abortus, B. melitensis, and B. suis are pathogenic to humans, whereas B. ovis and B. neotomae are nonpathogenic to humans and B. canis human infections are rare. Limited genome diversity exists among Brucella species. Comparison of Brucella species whole genomes is, therefore, likely to identify factors responsible for differences in host preference and virulence restriction. To facilitate such studies, we used the complete genome sequence of B. melitensis 16M, the species highly pathogenic to humans, to construct a genomic microarray. Hybridization of labeled genomic DNA from Brucella species to this microarray revealed a total of 217 open reading frames (ORFs) altered in five Brucella species analyzed. These ORFs are often found in clusters (islands) in the 16M genome. Examination of the genomic context of these islands suggests that many are horizontally acquired. Deletions of genetic content identified in Brucella species are conserved in multiple strains of the same species, and genomic islands missing in a given species are often restricted to that particular species. These findings suggest that, whereas the loss or gain of genetic material may be related to the host range and virulence restriction of certain Brucella species for humans, independent mechanisms involving gene inactivation or altered expression of virulence determinants may also contribute to these differences.

Animals↗

PubMed2004

Regulation of iron transport in Streptococcus pneumoniae by RitR, an orphan response regulator.

RitR (formerly RR489) is an orphan two-component signal transduction response regulator in Streptococcus pneumoniae that has been shown to be required for lung pathogenicity. In the present study, by using the rough strain R800, inactivation of the orphan response regulator gene ritR by allele replacement reduced pathogenicity in a cyclophosphamide-treated mouse lung model but not in a thigh model, suggesting a role for RitR in regulation of tissue-specific virulence factors. Analysis of changes in genome-wide transcript mRNA levels associated with the inactivation of ritR compared to wild-type cells was performed by the use of high-density DNA microarrays. Genes with a change in transcript abundance associated with inactivation of ritR included piuB, encoding an Fe permease subunit, and piuA, encoding an Fe carrier-binding protein. In addition, a dpr ortholog, encoding an H(2)O(2) resistance protein that has been shown to reduce synthesis of reactive oxygen intermediates, was activated in the wild-type (ritR(+)) strain. Microarray experiments suggested that RitR represses Fe uptake in vitro by negatively regulating the Piu hemin-iron transport system. Footprinting experiments confirmed site-specific DNA-binding activity for RitR and identified three binding sites that partly overlap the +1 site for transcription initiation upstream of piuB. Transcripts belonging to other gene categories found to be differentially expressed in our array studies include those associated with (i) H(2)O(2) resistance, (ii) repair of DNA damage, (iii) sugar transport and capsule biosynthesis, and (iv) two-component signal transduction elements. These observations suggest that RitR is an important response regulator whose primary role is to maintain iron homeostasis in S. pneumoniae. The name ritR (repressor of iron transport) for the orphan response regulator gene, rr489, is proposed.

Animals↗

PubMed2003

Gene replacement without selection: regulated suppression of amber mutations in Escherichia coli.

We have developed a method called "gene gorging" to make precise mutations in the Escherichia coli genome at frequencies high enough (1-15%) to allow direct identification of mutants by PCR or other screen rather than by selection. Gene gorging begins by establishing a donor plasmid carrying the desired mutation in the target cell. This plasmid is linearized by in vivo expression of the meganuclease I-SceI, providing a DNA substrate for lambda Red mediated recombination. This results in efficient replacement of the wild type allele on the chromosome with the modified sequence. We demonstrate gene gorging by introducing amber stop codons into the genes xylA, melA, galK, fucI, citA, ybdO, and lacZ. To compliment this approach we developed an arabinose inducible amber suppressor tRNA. Controlled expression mediated by the suppressor was demonstrated for the lacZ and xylA amber mutants.

Anti-Bacterial Agents↗

PubMed2003

ASAP, a systematic annotation package for community analysis of genomes.

ASAP (a systematic annotation package for community analysis of genomes) is a relational database and web interface developed to store, update and distribute genome sequence data and functional characterization (https://asap.ahabs.wisc.edu/annotation/php/ASAP1.htm). ASAP facilitates ongoing community annotation of genomes and tracking of information as genome projects move from preliminary data collection through post-sequencing functional analysis. The ASAP database includes multiple genome sequences at various stages of analysis, corresponding experimental data and access to collections of related genome resources. ASAP supports three levels of users: public viewers, annotators and curators. Public viewers can currently browse updated annotation information for Escherichia coli K-12 strain MG1655, genome-wide transcript profiles from more than 50 microarray experiments and an extensive collection of mutant strains and associated phenotypic data. Annotators worldwide are currently using ASAP to participate in a community annotation project for the Erwinia chrysanthemi strain 3937 genome. Curation of the E. chrysanthemi genome annotation as well as those of additional published enterobacterial genomes is underway and will be publicly accessible in the near future.

Databases, Genetic↗

PubMed2003

Regulatory network of Escherichia coli: consistency between literature knowledge and microarray profiles.

The transcriptional network of Escherichia coli may well be the most complete experimentally characterized network of a single cell. A rule-based approach was built to assess the degree of consistency between whole-genome microarray experiments in different experimental conditions and the accumulated knowledge in the literature compiled in RegulonDB, a data base of transcriptional regulation and operon organization in E. coli. We observed a high and statistical significant level of consistency, ranging from 70%-87%. When effector metabolites of regulatory proteins are not considered in the prediction of the active or inactive state of the regulators, consistency falls by up to 40%. Similarly, consistency decreases when rules for multiple regulatory interactions are altered or when "on" and "off" entries were assigned randomly. We modified the initial state of regulators and evaluated the propagation of errors in the network that do not correlate linearly with the connectivity of regulators. We interpret this deviation mainly as a result of the existence of redundant regulatory interactions. Consistency evaluation opens a new space of dialogue between theory and experiment, as the consequences of different assumptions can be evaluated and compared.

Databases, Genetic↗

PubMed2003

Genome-scale analysis of the uses of the Escherichia coli genome: model-driven analysis of heterogeneous data sets.

The recent availability of heterogeneous high-throughput data types has increased the need for scalable in silico methods with which to integrate data related to the processes of regulation, protein synthesis, and metabolism. A sequence-based framework for modeling transcription and translation in prokaryotes has been established and has been extended to study the expression state of the entire Escherichia coli genome. The resulting in silico analysis of the expression state highlighted three facets of gene expression in E. coli: (i) the metabolic resources required for genome expression and protein synthesis were found to be relatively invariant under the conditions tested; (ii) effective promoter strengths were estimated at the genome scale by using global mRNA abundance and half-life data, revealing genes subject to regulation under the experimental conditions tested; and (iii) large-scale genome location-dependent expression patterns with approximately 600-kb periodicity were detected in the E. coli genome based on the 49 expression data sets analyzed. These results support the notion that a structured model-driven analysis of expression data yields additional information that can be subjected to commonly used statistical analyses. The integration of heterogeneous genome-scale data (i.e., sequence, expression data, and mRNA half-life data) is readily achieved in the context of an in silico model.

Bacterial Proteins↗

PubMed2002

Modelling regulatory pathways in E. coli from time series expression profiles.

MOTIVATION: Cells continuously reprogram their gene expression network as they move through the cell cycle or sense changes in their environment. In order to understand the regulation of cells, time series expression profiles provide a more complete picture than single time point expression profiles. Few analysis techniques, however, are well suited to modelling such time series data. RESULTS: We describe an approach that naturally handles time series data with the capabilities of modelling causality, feedback loops, and environmental or hidden variables using a Dynamic Bayesian network. We also present a novel way of combining prior biological knowledge and current observations to improve the quality of analysis and to model interactions between sets of genes rather than individual genes. Our approach is evaluated on time series expression data measured in response to physiological changes that affect tryptophan metabolism in E. coli. Results indicate that this approach is capable of finding correlations between sets of related genes.

Adaptation, Physiological↗