Biomedical subjects

Lars Rohlin

Publications and source records attributed to Lars Rohlin.

5 recordsLinked to original sources

PubMed2005

Heat shock response of Archaeoglobus fulgidus.

The heat shock response of the hyperthermophilic archaeon Archaeoglobus fulgidus strain VC-16 was studied using whole-genome microarrays. On the basis of the resulting expression profiles, approximately 350 of the 2,410 open reading frames (ORFs) (ca. 14%) exhibited increased or decreased transcript abundance. These span a range of cell functions, including energy production, amino acid metabolism, and signal transduction, where the majority are uncharacterized. One ORF called AF1298 was identified that contains a putative helix-turn-helix DNA binding motif. The gene product, HSR1, was expressed and purified from Escherichia coli and was used to characterize specific DNA recognition regions upstream of two A. fulgidus genes, AF1298 and AF1971. The results indicate that AF1298 is autoregulated and is part of an operon with two downstream genes that encode a small heat shock protein, Hsp20, and cdc48, an AAA+ ATPase. The DNase I footprints using HSR1 suggest the presence of a cis-binding motif upstream of AF1298 consisting of CTAAC-N5-GTTAG. Since AF1298 is negatively regulated in response to heat shock and encodes a protein only distantly related to the N-terminal DNA binding domain of Phr of Pyrococcus furiosus, these results suggest that HSR1 and Phr may belong to an evolutionarily diverse protein family involved in heat shock regulation in hyperthermophilic and mesophilic Archaea organisms.

Amino Acid Sequence↗

PubMed2004

Vocabulon: a dictionary model approach for reconstruction and localization of transcription factor binding sites.

MOTIVATION: Gene expression arrays enable measurements of transcription values for a large number or all genes in the genome. In order to better interpret these results and to use them to reconstruct transcription networks, information on location of binding sites for regulatory proteins in the entire genome is needed. In particular, this represents an open problem in Escherichia coli. RESULTS: We describe the first implementation of dictionary-style models to the study of transcription factors binding sites in an entire genome. Vocabulon's unique feature is that it can both reconstruct binding sites characterized by unknown motifs and impute locations of known binding sites in long sequences by simultaneous search. On one hand, the dictionary model specifies a probability for the entire sequence taking simultaneously into account all the possible binding sites. This greatly reduces the number of false positives. On the other hand, the possibility of refining motif description, as an increasing number of binding sites are identified, augments the sensitivity of the method. We illustrate these properties with examples in E.coli. The results of gene expression arrays are used both to guide the search and corroborate it.

Algorithms↗

PubMed2003

A software package for cDNA microarray data normalization and assessing confidence intervals.

DNA microarray data are affected by variations from a number of sources. Before these data can be used to infer biological information, the extent of these variations must be assessed. Here we describe an open source software package, lcDNA, that provides tools for filtering, normalizing, and assessing the statistical significance of cDNA microarray data. The program employs a hierarchical Bayesian model and Markov Chain Monte Carlo simulation to estimate gene-specific confidence intervals for each gene in a cDNA microarray data set. This program is designed to perform these primary analytical operations on data from two-channel spotted, or in situ synthesized, DNA microarrays.

Bayes Theorem↗

PubMed2002

Co-expression pattern from DNA microarray experiments as a tool for operon prediction.

The prediction of operons, the smallest unit of transcription in prokaryotes, is the first step towards reconstruction of a regulatory network at the whole genome level. Sequence information, in particular the distance between open reading frames, has been used to predict if adjacent Escherichia coli genes are in an operon. While appreciably successful, these predictions need to be validated and refined experimentally. As a growing number of gene expression array experiments on E.coli became available, we investigated to what extent they could be used to improve and validate these predictions. To this end, we examined a large collection of published microarry data. The correlation between expression ratios of adjacent genes was used in a Bayesian classification scheme to predict whether the genes are in an operon or not. We found that for the genes whose expression levels change significantly across the experiments in the data set, the currently available gene expression data allowed a significant refinement of the sequenced-based predictions. We report these co-expression correlations in an E.coli genomic map. For a significant portion of gene pairs, however, the set of array experiments considered did not contain sufficient information to determine whether they are in the same transcriptional unit. This is not due to unreliability of the array data per se, but to the design of the experiments analyzed. In general, experiments that perturb a large number of genes offer more information for operon prediction than confined perturbations. These results provide a rationale for conducting expression studies comparing conditions that cause global changes in gene expression.

Chromosome Mapping↗

PubMed2002

Global expression profiling of acetate-grown Escherichia coli.

This study characterized the transcript profile of Escherichia coli in acetate cultures using DNA microarray on glass slides. Glucose-grown cultures were used as a reference. At the 95% confidence level, 354 genes were up-regulated in acetate, while 370 genes were down-regulated compared with the glucose-grown culture. Generally, more metabolic genes were up-regulated in acetate than other gene groups, while genes involved in cell replication, transcription, and translation machinery tended to be down-regulated. It appears that E. coli commits more resources to metabolism at the expense of growth when cultured in the poor carbon source. The expression profile confirms many known features in acetate metabolism such as the induction of the glyoxylate pathway, tricarboxylic acid cycle, and gluconeogenic genes. It also provided many previously unknown features, including induction of malic enzymes, ppsA, and the glycolate pathway and repression of glycolytic and glucose phosphotransferase genes in acetate. The carbon flux delivered from the malic enzymes and PpsA in acetate was further confirmed by deletion mutations. In general, the gene expression profiles qualitatively agree with the metabolic flux changes and may serve as a predictor for gene function and metabolic flux distribution.

Acetates↗