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Biomedical subjects

Anne de Jong

Publications and source records attributed to Anne de Jong.

11 recordsLinked to original sources
PubMed2006

Regulation of gene expression in Streptococcus pneumoniae by response regulator 09 is strain dependent.

Recent murine studies have demonstrated that the role of response regulator 09 (RR09) of Streptococcus pneumoniae in virulence is different in different strains. In the present study, we used a murine pneumonia model of infection to assess the virulence of a TIGR4 rr09 mutant, and we found that TIGR4Deltarr09 was attenuated after intranasal infection. Furthermore, we investigated the in vitro transcriptional changes in pneumococcal rr09 mutants of two strains, D39 and TIGR4, by microarray analysis. The transcriptional profiles of the rr09 mutants of both strains had clear differences compared to the profiles of the parental wild-type strains. In D39Deltarr09, but not in TIGR4Deltarr09, genes involved in competence (e.g., comAB) were upregulated. In TIGR4, genes located on the rlrA pathogenicity islet, which are not present in the D39 genome, appeared to be regulated by RR09. Furthermore, several phosphotransferase systems (PTSs) believed to be involved in sugar uptake (e.g., the PTS encoded by sp0060 to sp0066) were strongly downregulated in D39Deltarr09, while they were not regulated by RR09 in TIGR4. To examine the role of one of these PTSs in virulence, D39Deltasp0063 was constructed and tested in a murine infection model. No difference between the virulence of this strain and the virulence of the wild type was found, indicating that downregulation of the sp0063 gene alone is not the cause of the avirulent phenotype of D39Deltarr09. Finally, expression of rr09 and expression of three of our identified RR09 targets during infection in mice were assessed. This in vivo experiment confirmed that there were differences between expression in wild-type strain TIGR4 and expression in the rr09 mutant, as well as differences between expression in wild-type strain D39 and expression in wild-type strain TIGR4. In conclusion, our results indicate that there is strain-specific regulation of pneumococcal gene expression by RR09.

Animals↗
PubMed2006

BAGEL: a web-based bacteriocin genome mining tool.

A common problem in the annotation of open reading frames (ORFs) is the identification of genes that are functionally similar but have limited or no sequence homology. This is particularly the case for bacteriocins, a very diverse group of antimicrobial peptides produced by bacteria and usually encoded by small, poorly conserved ORFs. ORFs surrounding bacteriocin genes are often biosynthetic genes. This information can be used to locate putative structural bacteriocin genes. Here, we describe BAGEL, a web server that identifies putative bacteriocin ORFs in a DNA sequence using novel, knowledge-based bacteriocin databases and motif databases. Many bacteriocins are encoded by small genes that are often omitted in the annotation process of bacterial genomes. Thus, we have implemented ORF detection using a number of published ORF prediction tools. In addition, BAGEL takes into account the genomic context, i.e. for each potential bacteriocin-encoding ORF, the sequence of the surrounding region on the genome is analyzed for genes that might encode proteins involved in biosynthesis, transport, regulation and/or immunity. These innovations make BAGEL unique in its ability to detect putative bacteriocin gene clusters in (new) bacterial genomes. BAGEL is freely accessible at: http://bioinformatics.biol.rug.nl/websoftware/bagel.

Amino Acid Motifs↗
PubMed2006

LmrCD is a major multidrug resistance transporter in Lactococcus lactis.

When Lactococcus lactis is challenged with drugs it displays a multidrug resistance (MDR) phenotype. In silico analysis of the genome of L. lactis indicates the presence of at least 40 putative MDR transporters, of which only four, i.e. the ABC transporters LmrA, LmrC and LmrD, and the major facilitator LmrP, have been experimentally associated with the MDR. To understand the molecular basis of the MDR phenotype in L. lactis, we have performed a global transcriptome analysis comparing four independently isolated drug-resistant strains of L. lactis with the wild-type strain. The results show a strong and consistent upregulation of the lmrC and lmrD genes in all four strains, while the mRNA levels of other putative MDR transporters were not significantly altered. Deletion of lmrCD renders L. lactis sensitive to several toxic compounds, and this phenotype is associated with a reduced ability to secrete these compounds. Another gene, which is strongly upregulated in all mutant strains, specifies LmrR (YdaF), a local transcriptional repressor of lmrCD that belongs to the PadR family of transcriptional regulators and that binds to the promoter region of lmrCD. These results demonstrate that the heterodimeric MDR ABC transporter LmrCD is a major determinant of both acquired and intrinsic drug resistance of L. lactis.

ATP-Binding Cassette Transporters↗
PubMed2005

A generally applicable validation scheme for the assessment of factors involved in reproducibility and quality of DNA-microarray data.

BACKGROUND: In research laboratories using DNA-microarrays, usually a number of researchers perform experiments, each generating possible sources of error. There is a need for a quick and robust method to assess data quality and sources of errors in DNA-microarray experiments. To this end, a novel and cost-effective validation scheme was devised, implemented, and employed. RESULTS: A number of validation experiments were performed on Lactococcus lactis IL1403 amplicon-based DNA-microarrays. Using the validation scheme and ANOVA, the factors contributing to the variance in normalized DNA-microarray data were estimated. Day-to-day as well as experimenter-dependent variances were shown to contribute strongly to the variance, while dye and culturing had a relatively modest contribution to the variance. CONCLUSION: Even in cases where 90% of the data were kept for analysis and the experiments were performed under challenging conditions (e.g. on different days), the CV was at an acceptable 25%. Clustering experiments showed that trends can be reliably detected also from genes with very low expression levels. The validation scheme thus allows determining conditions that could be improved to yield even higher DNA-microarray data quality.

Analysis of Variance↗
PubMed2004

Genome2D: a visualization tool for the rapid analysis of bacterial transcriptome data.

Genome2D is a Windows-based software tool for visualization of bacterial transcriptome and customized datasets on linear chromosome maps constructed from annotated genome sequences. Genome2D facilitates the analysis of transcriptome data by using different color ranges to depict differences in gene-expression levels on a genome map. Such output format enables visual inspection of the transcriptome data, and will quickly reveal transcriptional units, without prior knowledge of expression level cutoff values. The compiled version of Genome2D is freely available for academic or non-profit use from http://molgen.biol.rug.nl/molgen/research/molgensoftware.php.

Bacterial Proteins↗
PubMed2003

Genome engineering reveals large dispensable regions in Bacillus subtilis.

Bacterial genomes contain 250 to 500 essential genes, as suggested by single gene disruptions and theoretical considerations. If this view is correct, the remaining nonessential genes of an organism, such as Bacillus subtilis, have been acquired during evolution in its perpetually changing ecological niches. Notably, approximately 47% of the approximately 4,100 genes of B. subtilis belong to paralogous gene families in which several members have overlapping functions. Thus, essential gene functions will outnumber essential genes. To answer the question to what extent the most recently acquired DNA contributes to the life of B. subtilis under standard laboratory growth conditions, we initiated a "reconstruction" of the B. subtilis genome by removing prophages and AT-rich islands. Stepwise deletion of two prophages (SPbeta, PBSX), three prophage-like regions, and the largest operon of B. subtilis (pks) resulted in a genome reduction of 7.7% and elimination of 332 genes. The resulting strain was phenotypically characterized by metabolic flux analysis, proteomics, and specific assays for protein secretion, competence development, sporulation, and cell motility. We show that genome engineering is a feasible strategy for functional analysis of large gene clusters, and that removal of dispensable genomic regions may pave the way toward an optimized Bacillus cell factory.

Bacillus Phages↗
PubMed2003

Active lipoprotein precursors in the Gram-positive eubacterium Lactococcus lactis.

Lipid-modified proteins play important roles at the interface between eubacterial cells and their environment. The importance of lipoprotein processing by signal peptidase II (SPase II) is underscored by the fact that this enzyme is essential for viability of the Gram-negative eubacterium Escherichia coli. In contrast, SPase II is not essential for growth and viability of the Gram-positive eubacterium Bacillus subtilis. This could be due to alternative amino-terminal lipoprotein processing, which was shown previously to occur in SPase II mutants of B. subtilis. Alternatively, uncleaved lipoprotein precursors might be functional. To explore further the importance of lipoprotein processing in Gram-positive eubacteria, an SPase II mutant strain of Lactococcus lactis was constructed. Although some of the 39 (predicted) lactococcal lipoproteins, such as PrtM and OppA, are essential for growth in milk, the growth of SPase II mutant L. lactis cells in this medium was not affected. Furthermore, the activity of the strictly PrtM-dependent extracellular protease PrtP, which is required for casein degradation, was not impaired in the absence of SPase II. Importantly, no alternative processing of pre-PrtM and pre-OppA was observed in cells lacking SPase II. Taken together, these findings show for the first time that authentic lipoprotein precursors retain biological activity.

Aspartic Acid Endopeptidases↗
PubMed2002

Improving the predictive value of the competence transcription factor (ComK) binding site in Bacillus subtilis using a genomic approach.

Generally, the presence of a consensus sequence in the promoter of a gene is taken as indication for regulation by the transcription factor that binds to this sequence. In light of the recent developments in genome research, we were interested to what extent this supposition is valid. We examined the relationship between the presence of a binding site for ComK, the competence transcription factor of Bacillus subtilis, and actual transcriptional activation by ComK. Bacillus subtilis contains 1062 putative ComK-binding sites (K-boxes) in its genome. We employed DNA macroarrays to identify ComK-activated genes, and found that the presence of a K-box is an unreliable predictor for regulation. Only approximately 8% of the genes containing a K-box in the putative promoter region are regulated by ComK. The predictive value of a K-box could be improved by taking into consideration the degree of deviation from the K-box consensus sequence, the presence of extra ComK-binding motifs and the positions of RNA polymerase-binding sites. Finally, many of the ComK-activated genes show no apparent function related to the competence process. Based on our findings, we propose that the ComK-dependent activation of several genes might serve no biological purpose and can be considered 'evolutionary noise'.

Bacillus subtilis↗
PubMed2002

Transcriptome analysis and related databases of Lactococcus lactis.

Several complete genome sequences of Lactococcus lactis and their annotations will become available in the near future, next to the already published genome sequence of L. lactis ssp. lactis IL 1403. This will allow intraspecies comparative genomics studies as well as functional genomics studies aimed at a better understanding of physiological processes and regulatory networks operating in lactococci. This paper describes the initial set-up of a DNA-microarray facility in our group, to enable transcriptome analysis of various Gram-positive bacteria, including a ssp. lactis and a ssp. cremoris strain of Lactococcus lactis. Moreover a global description will be given of the hardware and software requirements for such a set-up, highlighting the crucial integration of relevant bioinformatics tools and methods. This includes the development of MolGenIS, an information system for transcriptome data storage and retrieval, and LactococCye, a metabolic pathway/genome database of Lactococcus lactis.

Databases, Nucleic Acid↗
PubMed2001

Detergent-independent in vitro activity of a truncated Bacillus signal peptidase.

The Gram-positive eubacterium Bacillus subtilis contains five chromosomally encoded type I signal peptidases (SPases) for the processing of secretory pre-proteins. Even though four of these SPases, denoted SipS, SipT, SipU and SipV, are homologous to the unique SPase I of Escherichia coli, they are structurally different from that enzyme, being almost half the size and containing one membrane anchor instead of two. To investigate whether the unique membrane anchor of Bacillus SPases is required for in vitro activity, soluble forms of SipS of B. subtilis, SipS of Bacillus amyloliquefaciens and SipC of the thermophile Bacillus caldolyticus were constructed. Of these three proteins, only a hexa-histidine-tagged soluble form of SipS of B. amyloliquefaciens could be isolated in significant quantities. This protein displayed optimal activity at pH 10, which is remarkable considering the fact that the catalytic domain of SPases is located in an acidic environment at the outer surface of the membrane of living cells. Strikingly, in contrast to what has been previously reported for the soluble form of the E. coli SPase, soluble SipS was active in the absence of added detergents. This observation can be explained by the fact that a highly hydrophobic surface domain of the E. coli SPase, implicated in detergent-binding, is absent from SipS.

Amino Acid Sequence↗