Biomedical subjects

Kathleen Marchal

Publications and source records attributed to Kathleen Marchal.

At least 19 recordsLinked to original sources

PubMed2006

Functional analysis of luxS in the probiotic strain Lactobacillus rhamnosus GG reveals a central metabolic role important for growth and biofilm formation.

Quorum sensing is involved in the regulation of multicellular behavior through communication via small molecules. Given the high number and diversity of the gastrointestinal microbiota, it is postulated that members of this community communicate to coordinate a variety of adaptive processes. AI-2 is suggested to be a universal bacterial signaling molecule synthesized by the LuxS enzyme, which forms an integral part of the activated methyl cycle. We have previously reported that the well-documented probiotic strain Lactobacillus rhamnosus GG, a human isolate, produces AI-2-like molecules. In this study, we identified the luxS homologue of L. rhamnosus GG. luxS seems to be located in an operon with a yxjH gene encoding a putative cobalamin-independent methionine synthase. In silico analysis revealed a methionine-specific T box in the leader sequence of the putative yxjH-luxS operon. However, transcriptional analysis showed that luxS is expressed mainly as a monocistronic transcript. Construction of a luxS knockout mutant confirmed that the luxS gene is responsible for AI-2 production in L. rhamnosus GG. However, this mutation also resulted in pleiotropic effects on the growth of this fastidious strain. Cysteine, pantothenate, folic acid, and biotin could partially complement growth, suggesting a central metabolic role for luxS in L. rhamnosus GG. Interestingly, the luxS mutant also showed a defect in monospecies biofilm formation. Experiments with chemically synthesized (S)-4,5-dihydroxy-2,3-pentanedione, coculture with the wild type, and nutritional complementation suggested that the main cause of this defect has a metabolic nature. Moreover, our data indicate that suppressor mutations are likely to occur in luxS mutants of L. rhamnosus GG. Therefore, results of luxS-related studies should be carefully interpreted.

Bacterial Proteins↗

PubMed2006

Integration of omics data: how well does it work for bacteria?

In the current omics era, innovative high-throughput technologies allow measuring temporal and conditional changes at various cellular levels. Although individual analysis of each of these omics data undoubtedly results into interesting findings, it is only by integrating them that gaining a global insight into cellular behaviour can be aimed at. A systems approach thus is predicated on data integration. However, because of the complexity of biological systems and the specificities of the data-generating technologies (noisiness, heterogeneity, etc.), integrating omics data in an attempt to reconstruct signalling networks is not trivial. Developing its methodologies constitutes a major research challenge. Besides for their intrinsic value towards health care, environment and industry, prokaryotes are ideal model systems to further develop these methods because of their lower regulatory complexity compared with eukaryotes, and the ease with which they can be manipulated. Several successful examples outlined in this review already show the potential of the systems approach for both fundamental and industrial applications, which would be time-consuming or impossible to develop solely through traditional reductionist approaches.

Bacteria↗

PubMed2006

Inferring transcriptional modules from ChIP-chip, motif and microarray data.

'ReMoDiscovery' is an intuitive algorithm to correlate regulatory programs with regulators and corresponding motifs to a set of co-expressed genes. It exploits in a concurrent way three independent data sources: ChIP-chip data, motif information and gene expression profiles. When compared to published module discovery algorithms, ReMoDiscovery is fast and easily tunable. We evaluated our method on yeast data, where it was shown to generate biologically meaningful findings and allowed the prediction of potential novel roles of transcriptional regulators.

Algorithms↗

PubMed2006

More robust detection of motifs in coexpressed genes by using phylogenetic information.

BACKGROUND: Several motif detection algorithms have been developed to discover overrepresented motifs in sets of coexpressed genes. However, in a noisy gene list, the number of genes containing the motif versus the number lacking the motif might not be sufficiently high to allow detection by classical motif detection tools. To still recover motifs which are not significantly enriched but still present, we developed a procedure in which we use phylogenetic footprinting to first delineate all potential motifs in each gene. Then we mutually compare all detected motifs and identify the ones that are shared by at least a few genes in the data set as potential candidates. RESULTS: We applied our methodology to a compiled test data set containing known regulatory motifs and to two biological data sets derived from genome wide expression studies. By executing four consecutive steps of 1) identifying conserved regions in orthologous intergenic regions, 2) aligning these conserved regions, 3) clustering the conserved regions containing similar regulatory regions followed by extraction of the regulatory motifs and 4) screening the input intergenic sequences with detected regulatory motif models, our methodology proves to be a powerful tool for detecting regulatory motifs when a low signal to noise ratio is present in the input data set. Comparing our results with two other motif detection algorithms points out the robustness of our algorithm. CONCLUSION: We developed an approach that can reliably identify multiple regulatory motifs lacking a high degree of overrepresentation in a set of coexpressed genes (motifs belonging to sparsely connected hubs in the regulatory network) by exploiting the advantages of using both coexpression and phylogenetic information.

Algorithms↗

PubMed2006

A calibration method for estimating absolute expression levels from microarray data.

MOTIVATION: We describe an approach to normalize spotted microarray data, based on a physically motivated calibration model. This model consists of two major components, describing the hybridization of target transcripts to their corresponding probes on the one hand, and the measurement of fluorescence from the hybridized, labeled target on the other hand. The model parameters and error distributions are estimated from external control spikes. RESULTS: Using a publicly available dataset, we show that our procedure is capable of adequately removing the typical non-linearities of the data, without making any assumptions on the distribution of differences in gene expression from one biological sample to the next. Since our model links target concentration to measured intensity, we show how absolute expression values of target transcripts in the hybridization solution can be estimated up to a certain degree.

Algorithms↗

PubMed2006

SynTReN: a generator of synthetic gene expression data for design and analysis of structure learning algorithms.

BACKGROUND: The development of algorithms to infer the structure of gene regulatory networks based on expression data is an important subject in bioinformatics research. Validation of these algorithms requires benchmark data sets for which the underlying network is known. Since experimental data sets of the appropriate size and design are usually not available, there is a clear need to generate well-characterized synthetic data sets that allow thorough testing of learning algorithms in a fast and reproducible manner. RESULTS: In this paper we describe a network generator that creates synthetic transcriptional regulatory networks and produces simulated gene expression data that approximates experimental data. Network topologies are generated by selecting subnetworks from previously described regulatory networks. Interaction kinetics are modeled by equations based on Michaelis-Menten and Hill kinetics. Our results show that the statistical properties of these topologies more closely approximate those of genuine biological networks than do those of different types of random graph models. Several user-definable parameters adjust the complexity of the resulting data set with respect to the structure learning algorithms. CONCLUSION: This network generation technique offers a valid alternative to existing methods. The topological characteristics of the generated networks more closely resemble the characteristics of real transcriptional networks. Simulation of the network scales well to large networks. The generator models different types of biological interactions and produces biologically plausible synthetic gene expression data.

Algorithms↗

PubMed2006

Strong antimicrobial activity of Lactobacillus rhamnosus GG against Salmonella typhimurium is due to accumulation of lactic acid.

Spent culture supernatant (SCS) of the probiotic Lactobacillus rhamnosus GG had been reported to exert antibacterial activity against Salmonella typhimurium. However, the chemical identity of the antimicrobial compound(s) responsible remained unknown. A survey of the antimicrobial compounds produced by L. rhamnosus GG was performed. Lactobacillus rhamnosus GG produced a low-molecular weight, heat-stable, non-proteinaceous bactericidal substance, active at acidic pH against a wide range of bacterial species. SCS of L. rhamnosus GG grown in MRS medium contained five compounds that could meet the above description, if present at the appropriate concentration. Based on different experimental approaches, it could be concluded that under the growth conditions tested, the strong antimicrobial activity of L. rhamnosus GG against Salmonella was mediated by lactic acid.

Antibiosis↗

PubMed2005

A novel approach to identifying regulatory motifs in distantly related genomes.

Although proven successful in the identification of regulatory motifs, phylogenetic footprinting methods still show some shortcomings. To assess these difficulties, most apparent when applying phylogenetic footprinting to distantly related organisms, we developed a two-step procedure that combines the advantages of sequence alignment and motif detection approaches. The results on well-studied benchmark datasets indicate that the presented method outperforms other methods when the sequences become either too long or too heterogeneous in size.

Amino Acid Sequence↗

PubMed2005

The effect of a sertoli cell-selective knockout of the androgen receptor on testicular gene expression in prepubertal mice.

To unravel the molecular mechanisms mediating the effects of androgens on spermatogenesis, testicular gene expression was compared in mice with Sertoli cell-selective androgen receptor knockout (SCARKO) and littermate controls on postnatal d 10. Microarray analysis identified 692 genes with significant differences in expression. Of these, 28 appeared to be down-regulated and 12 up-regulated at least 2-fold in SCARKOs compared with controls. For nine of the more than 2-fold down-regulated genes, androgen regulation was confirmed by treatment of wild-type mice with an antiandrogen (flutamide). Some of them were previously described to be androgen regulated or essential for spermatogenesis. Serine-type protease inhibitors were markedly overrepresented in this down-regulated subgroup. A time study (d 8-20), followed by cluster analysis, allowed identification of distinct expression patterns of differentially expressed genes. Three genes with a pattern closely resembling that of Pem, a prototypical androgen-regulated gene expressed in Sertoli cells, were selected for confirmation by quantitative RT-PCR and additional analysis. The data confirm that the SCARKO model allows identification of novel androgen-regulated genes in the testis. Moreover, they suggest that protease inhibitors and other proteins related to tubular restructuring and cell junction dynamics may be controlled in part by androgens.

Androgens↗

PubMed2005

Characterization of the condensin component Cnap1 and protein kinase Melk as novel E2F target genes down-regulated by 1,25-dihydroxyvitamin D3.

1,25-Dihydroxyvitamin D(3) (1,25(OH)(2)D(3)) has potent antiproliferative effects characterized by a hampered G(1)/S transition. cDNA microarrays were used to monitor expression of 21,492 genes in MC3T3-E1 mouse osteoblasts at 1, 6, 12, 24, and 36 h after treatment with 1,25(OH)(2)D(3). Statistical analysis revealed a cluster of genes that were strongly down-regulated by 1,25(OH)(2)D(3) and which not only function in cell cycle regulation and DNA replication but also mediate checkpoint control, DNA repair, chromosome modifications, and mitosis. Because many of these genes were shown earlier to be regulated by the transcriptional repressor E2F4, the intergenic regions of these 1,25(OH)(2)D(3)-down-regulated genes were searched for the presence of E2F binding sites. This led to the characterization of two novel E2F target genes, chromosome condensation-related SMC-associated protein 1 (Cnap1) and maternal embryonic leucine zipper kinase (Melk). Transfection studies and site-directed mutagenesis confirmed Cnap1 and Melk to be bona fide E2F targets. Repression of Cnap1 and Melk by 1,25(OH)(2)D(3) was confirmed not only in MC3T3-E1 cells but also in several other bone-unrelated cell types. This down-regulation as well as the antiproliferative effect of 1,25(OH)(2)D(3) depended on the pocket proteins p107 and p130 because 1,25(OH)(2)D(3) failed to repress these E2F target genes and lost its antiproliferative action in p107(-/-);p130(-/-) cells but not in pRb(-/-) cells.

Animals↗

PubMed2005

M@CBETH: a microarray classification benchmarking tool.

Microarray classification can be useful to support clinical management decisions for individual patients in, for example, oncology. However, comparing classifiers and selecting the best for each microarray dataset can be a tedious and non-straightforward task. The M@CBETH (a MicroArray Classification BEnchmarking Tool on a Host server) web service offers the microarray community a simple tool for making optimal two-class predictions. M@CBETH aims at finding the best prediction among different classification methods by using randomizations of the benchmarking dataset. The M@CBETH web service intends to introduce an optimal use of clinical microarray data classification.

Algorithms↗

PubMed2005

Chemical synthesis of (S)-4,5-dihydroxy-2,3-pentanedione, a bacterial signal molecule precursor, and validation of its activity in Salmonella typhimurium.

We describe an original, short, and convenient chemical synthesis of enantiopure (S)-4,5-dihydroxy-2,3-pentanedione (DPD), starting from commercial methyl (S)-(-)-2,2-dimethyl-1,3-dioxolane-4-carboxylate. DPD is the precursor of autoinducer (AI)-2, the proposed signal for bacterial interspecies communication. AI-2 is synthesized by many bacterial species in three enzymatic steps. The last step, a LuxS-catalyzed reaction, leads to the formation of DPD, which spontaneously cyclizes into AI-2. AI-2-like activity of the synthesized molecule was ascertained by the Vibrio harveyi bioassay. To further validate the biological activity of synthetic DPD and to explore its potential in studying DPD (AI-2)-mediated signaling, a Salmonella typhimurium luxS mutant was constructed. Expression of the AI-2 regulated lsr operon can be rescued in this luxS mutant by addition of synthetic DPD or genetic complementation. Biofilm formation by S. typhimurium has been reported to be defective in a luxS mutant, and this was confirmed in this study to test DPD for chemical complementation. However, biofilm formation of the luxS mutant cannot be restored by addition of DPD. In contrast, introduction of luxS under control of its own promoter complemented biofilm formation. Further results demonstrated that biofilm formation of the luxS mutant cannot be restored with luxS under control of the strong nptII promoter. This indicates that altering the intrinsic promoter activity of luxS affects Salmonella biofilm formation. Conclusively, we synthesized biologically active DPD. Using this chemical compound in combination with genetic approaches opens new avenues in studying AI-2-mediated signaling.

Bacterial Proteins↗

PubMed2005

Comparison of the PhoPQ regulon in Escherichia coli and Salmonella typhimurium.

The PhoPQ two-component system acts as a transcriptional regulator that responds to Mg(2+) starvation both in Escherichia coli and Salmonella typhimurium (Garcia et al. 1996; Kato et al. 1999). By monitoring the availability of extracellular Mg(2+), this two-component system allows S. typhimurium to sense the transition from an extracellular environment to a subcellular location. Concomitantly with this transition, a set of virulence factors essential for survival in the intracellular environment is activated by the PhoPQ system (Groisman et al. 1989; Miller et al. 1989). Compared to nonpathogenic strains, such as E. coli K12, the PhoPQ regulon in pathogens must contain target genes specifically contributing to the virulence phenotype. To verify this hypothesis, we compared the composition of the PhoPQ regulon between E. coli and S. typhimurium using a combination of expression experiments and motif data. PhoPQ-dependent genes in both organisms were identified from PhoPQ-related microarray experiments. To distinguish between direct and indirect targets, we searched for the presence of the regulatory motif in the promoter region of the identified PhoPQ-dependent genes. This allowed us to reconstruct the direct PhoPQ-dependent regulons in E. coli K12 and S. typhimurium LT2. Comparison of both regulons revealed a very limited overlap of PhoPQ-dependent genes between both organisms. These results suggest that the PhoPQ system has acquired a specialized function during evolution in each of these closely related species that allows adaptation to the specificities of their lifestyles (e.g., pathogenesis in S. typhimurium).

Bacterial Proteins↗

PubMed2005

PKA and Sch9 control a molecular switch important for the proper adaptation to nutrient availability.

In the yeast Saccharomyces cerevisiae, PKA and Sch9 exert similar physiological roles in response to nutrient availability. However, their functional redundancy complicates to distinguish properly the target genes for both kinases. In this article, we analysed different phenotypic read-outs. The data unequivocally showed that both kinases act through separate signalling cascades. In addition, genome-wide expression analysis under conditions and with strains in which either PKA and/or Sch9 signalling was specifically affected, demonstrated that both kinases synergistically or oppositely regulate given gene targets. Unlike PKA, which negatively regulates stress-responsive element (STRE)- and post-diauxic shift (PDS)-driven gene expression, Sch9 appears to exert additional positive control on the Rim15-effector Gis1 to regulate PDS-driven gene expression. The data presented are consistent with a cyclic AMP (cAMP)-gating phenomenon recognized in higher eukaryotes consisting of a main gatekeeper, the protein kinase PKA, switching on or off the activities and signals transmitted through primary pathways such as, in case of yeast, the Sch9-controlled signalling route. This mechanism allows fine-tuning various nutritional responses in yeast cells, allowing them to adapt metabolism and growth appropriately.

Adaptation, Physiological↗

PubMed2005

Microarray analysis and motif detection reveal new targets of the Salmonella enterica serovar Typhimurium HilA regulatory protein, including hilA itself.

DNA regulatory motifs reflect the direct transcriptional interactions between regulators and their target genes and contain important information regarding transcriptional networks. In silico motif detection strategies search for DNA patterns that are present more frequently in a set of related sequences than in a set of unrelated sequences. Related sequences could be genes that are coexpressed and are therefore expected to share similar conserved regulatory motifs. We identified coexpressed genes by carrying out microarray-based transcript profiling of Salmonella enterica serovar Typhimurium in response to the spent culture supernatant of the probiotic strain Lactobacillus rhamnosus GG. Probiotics are live microorganisms which, when administered in adequate amounts, confer a health benefit on the host. They are known to antagonize intestinal pathogens in vivo, including salmonellae. S. enterica serovar Typhimurium causes human gastroenteritis. Infection is initiated by entry of salmonellae into intestinal epithelial cells. The expression of invasion genes is tightly regulated by environmental conditions, as well as by many bacterial factors including the key regulator HilA. One mechanism by which probiotics may antagonize intestinal pathogens is by influencing invasion gene expression. Our microarray experiment yielded a cluster of coexpressed Salmonella genes that are predicted to be down-regulated by spent culture supernatant. This cluster was enriched for genes known to be HilA dependent. In silico motif detection revealed a motif that overlaps the previously described HilA box in the promoter region of three of these genes, spi4_H, sicA, and hilA. Site-directed mutagenesis, beta-galactosidase reporter assays, and gel mobility shift experiments indicated that sicA expression requires HilA and that hilA is negatively autoregulated.

Amino Acid Motifs↗

PubMed2005

Discovering transcriptional modules from motif, chip-chip and microarray data.

We present a method for inference of transcriptional modules from heterogeneous data sources. It allows identifying the responsible set of regulators in combination with their corresponding DNA recognition sites (motifs) and target genes. Our approach distinguishes itself from previous work in literature because it fully exploits the knowledge of three independently acquired data sources: ChIP-chip data; motif information as obtained by phylogenetic shadowing; and gene expression profiles obtained using microarray experiments. Moreover, these three data sources are dealt with in a new and fully integrated manner. By avoiding approaches that take the different data sources into account sequentially or iteratively, the transparency of the method and the interpretability of the results are ensured. Using our method on biological data demonstrated the biological relevance of the inference.

Algorithms↗

PubMed2004

Differential regulation of the insulin-like growth factor II mRNA-binding protein genes by architectural transcription factor HMGA2.

The developmentally regulated architectural transcription factor, high mobility group A2 (HMGA2), is involved in growth regulation and plays an important role in embryogenesis and tumorigenesis. Little is known, however, about its downstream targets. We performed a search for genes of which expression is strongly altered during embryonic development in two HMGA2-deficient mouse strains, which display a pygmy-phenotype, as compared to wild-type mice. We found that the insulin-like growth factor II mRNA-binding protein 2 gene (IMP2), but not its family members IMP1 and IMP3, was robustly downregulated in mutant E12.5 embryos. Furthermore, we show that wild-type HMGA2 and its tumor-specific truncated form have opposite effects on IMP2 expression. Our results clearly indicate that HMGA2 differentially regulates expression of IMP family members during embryogenesis.

Amino Acid Sequence↗

PubMed2004

Annotation of the pRhico plasmid of Azospirillum brasilense reveals its role in determining the outer surface composition.

The plant growth-promoting soil bacterium Azospirillum brasilense enhances growth of economically important crops, such as wheat, corn and rice. In order to improve plant growth, a close bacterial association with the plant roots is needed. Genes encoded on a 90-MDa plasmid, denoted pRhico plasmid, present in A. brasilense Sp7, play an important role in plant root interaction. Sequencing, annotation and in silico analysis of this 90-MDa plasmid revealed the presence of a large collection of genes encoding enzymes involved in surface polysaccharide biosynthesis. Analysis of the 90-MDa plasmid genome provided evidence for its essential role in the viability of the bacterial cell.

Azospirillum brasilense↗