Anne de Jong

BAGEL3: automated identification of genes encoding bacteriocins and (non-)bactericidal posttranslationally modified peptides

Identifying genes encoding bacteriocins and ribosomally synthesized and posttranslationally modified peptides (RiPPs) can be a challenging task. Especially those peptides that do not have strong homology to previously identified peptides can easily be overlooked. Extensive use of BAGEL2 and user feedback has led us to develop BAGEL3. BAGEL3 features genome mining of prokaryotes, which is largely independent of open reading frame (ORF) predictions and has been extended to cover more (novel) classes of posttranslationally modified peptides. BAGEL3 uses an identification approach that combines direct mining for the gene and indirect mining via context genes. Especially for heavily modified peptides like lanthipeptides, sactipeptides, glycocins and others, this genetic context harbors valuable information that is used for mining purposes. The bacteriocin and context protein databases have been updated and it is now easy for users to submit novel bacteriocins or RiPPs. The output has been simplified to allow user-friendly analysis of the results, in particular for large (meta-genomic) datasets. The genetic context of identified candidate genes is fully annotated. As input, BAGEL3 uses FASTA DNA sequences or folders containing multiple FASTA formatted files. BAGEL3 is freely accessible at http://bagel.molgenrug.nl.

Adaptation of Hansenula polymorpha to methanol: a transcriptome analysis

BackgroundMethylotrophic yeast species (e.g. Hansenula polymorpha, Pichia pastoris) can grow on methanol as sole source of carbon and energy. These organisms are important cell factories for the production of recombinant proteins, but are also used in fundamental research as model organisms to study peroxisome biology. During exponential growth on glucose, cells of H. polymorpha typically contain a single, small peroxisome that is redundant for growth while on methanol multiple, enlarged peroxisomes are present. These organelles are crucial to support growth on methanol, as they contain key enzymes of methanol metabolism.In this study, changes in the transcriptional profiles during adaptation of H. polymorpha cells from glucose- to methanol-containing media were investigated using DNA-microarray analyses.ResultsTwo hours after the shift of cells from glucose to methanol nearly 20% (1184 genes) of the approximately 6000 annotated H. polymorpha genes were significantly upregulated with at least a two-fold differential expression. Highest upregulation (> 300-fold) was observed for the genes encoding the transcription factor Mpp1 and formate dehydrogenase, an enzyme of the methanol dissimilation pathway. Upregulated genes also included genes encoding other enzymes of methanol metabolism as well as of peroxisomal ?-oxidation.A moderate increase in transcriptional levels (up to 4-fold) was observed for several PEX genes, which are involved in peroxisome biogenesis. Only PEX11 and PEX32 were higher upregulated. In addition, an increase was observed in expression of the several ATG genes, which encode proteins involved in autophagy and autophagy processes. The strongest upregulation was observed for ATG8 and ATG11.Approximately 20% (1246 genes) of the genes were downregulated. These included glycolytic genes as well as genes involved in transcription and translation.ConclusionTranscriptional profiling of H. polymorpha cells shifted from glucose to methanol showed the expected downregulation of glycolytic genes together with upregulation of the methanol utilisation pathway. This serves as a confirmation and validation of the array data obtained. Consistent with this, also various PEX genes were upregulated. The strong upregulation of ATG genes is possibly due to induction of autophagy processes related to remodeling of the cell architecture required to support growth on methanol. These processes may also be responsible for the enhanced peroxisomal ?-oxidation, as autophagy leads to recycling of membrane lipids. The prominent downregulation of transcription and translation may be explained by the reduced growth rate on methanol (td glucose 1 h vs td methanol 4.5 h).

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: .

CodY of Streptococcus pneumoniae: Link between Nutritional Gene Regulation and Colonization

CodY is a nutritional regulator mainly involved in amino acid metabolism. It has been extensively studied in Bacillus subtilis and Lactococcus lactis. We investigated the role of CodY in gene regulation and virulence of the human pathogen Streptococcus pneumoniae. We constructed a codY mutant and examined the effect on gene and protein expression by microarray and two-dimensional differential gel electrophoresis analysis. The pneumococcal CodY regulon was found to consist predominantly of genes involved in amino acid metabolism but also several other cellular processes, such as carbon metabolism and iron uptake. By means of electrophoretic mobility shift assays and DNA footprinting, we showed that most of the targets identified are under the direct control of CodY. By mutating DNA predicted to represent the CodY box based on the L. lactis consensus, we demonstrated that this sequence is indeed required for in vitro DNA binding to target promoters. Similar to L. lactis, DNA binding of CodY was enhanced in the presence of branched-chain amino acids, but not by GTP. We observed in experimental mouse models that codY is transcribed in the murine nasopharynx and lungs and is specifically required for colonization. This finding was underscored by the diminished ability of the codY mutant to adhere to nasopharyngeal cells in vitro. Furthermore, we found that pcpA, activated by CodY, is required for adherence to nasopharyngeal cells, suggesting a direct link between nutritional regulation and adherence. In conclusion, pneumococcal CodY predominantly regulates genes involved in amino acid metabolism and contributes to the early stages of infection, i.e., colonization of the nasopharynx.

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

BackgroundIn 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.ResultsA 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.ConclusionEven 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.

BAGEL2: mining for bacteriocins in genomic data

Mining bacterial genomes for bacteriocins is a challenging task due to the substantial structure and sequence diversity, and generally small sizes, of these antimicrobial peptides. Major progress in the research of antimicrobial peptides and the ever-increasing quantities of genomic data, varying from (un)finished genomes to meta-genomic data, led us to develop the significantly improved genome mining software BAGEL2, as a follow-up of our previous BAGEL software. BAGEL2 identifies putative bacteriocins on the basis of conserved domains, physical properties and the presence of biosynthesis, transport and immunity genes in their genomic context. The software supports parameter-free, class-specific mining and has high-throughput capabilities. Besides building an expert validated bacteriocin database, we describe the development of novel Hidden Markov Models (HMMs) and the interpretation of combinations of HMMs via simple decision rules for prediction of bacteriocin (sub-)classes. Furthermore, the genetic context is automatically annotated based on (combinations of) PFAM domains and databases of known context genes. The scoring system was fine-tuned using expert knowledge on data derived from screening all bacterial genomes currently available at the NCBI. BAGEL2 is freely accessible at http://bagel2.molgenrug.nl.

Identification of Differentially Expressed Genes during Bacillus subtilis Spore Outgrowth in High-Salinity Environments Using RNA Sequencing

In its natural habitat, the soil bacterium Bacillus subtilis often has to cope with fluctuating osmolality and nutrient availability. Upon nutrient depletion it can form dormant spores, which can revive to form vegetative cells when nutrients become available again. While the effects of salt stress on spore germination have been analyzed previously, detailed knowledge on the salt stress response during the subsequent outgrowth phase is lacking. In this study, we investigated the changes in gene expression during B. subtilis outgrowth in the presence of 1.2 M NaCl using RNA sequencing. In total, 402 different genes were upregulated and 632 genes were downregulated during 90 min of outgrowth in the presence of salt. The salt stress response of outgrowing spores largely resembled the osmospecific response of vegetative cells exposed to sustained high salinity and included strong upregulation of genes involved in osmoprotectant uptake and compatible solute synthesis. The σB-dependent general stress response typically triggered by salt shocks was not induced, whereas the σW regulon appears to play an important role for osmoadaptation of outgrowing spores. Furthermore, high salinity induced many changes in the membrane protein and transporter transcriptome. Overall, salt stress seemed to slow down the complex molecular reorganization processes (“ripening”) of outgrowing spores by exerting detrimental effects on vegetative functions such as amino acid metabolism.

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.

PePPER : A webserver for prediction of prokaryote promoter elements and regulons

BackgroundAccurate prediction of DNA motifs that are targets of RNA polymerases, sigma factors and transcription factors (TFs) in prokaryotes is a difficult mission mainly due to as yet undiscovered features in DNA sequences or structures in promoter regions. Improved prediction and comparison algorithms are currently available for identifying transcription factor binding sites (TFBSs) and their accompanying TFs and regulon members.ResultsWe here extend the current databases of TFs, TFBSs and regulons with our knowledge on Lactococcus lactis and developed a webserver for prediction, mining and visualization of prokaryote promoter elements and regulons via a novel concept. This new approach includes an all-in-one method of data mining for TFs, TFBSs, promoters, and regulons for any bacterial genome via a user-friendly webserver. We demonstrate the power of this method by mining WalRK regulons in Lactococci and Streptococci and, vice versa, use L. lactis regulon data (CodY) to mine closely related species.ConclusionsThe PePPER webserver offers, besides the all-in-one analysis method, a toolbox for mining for regulons, promoters and TFBSs and accommodates a new L. lactis regulon database in addition to already existing regulon data. Identification of putative regulons and full annotation of intergenic regions in any bacterial genome on the basis of existing knowledge on a related organism can now be performed by biologists and it can be done for a wide range of regulons. On the basis of the PePPER output, biologist can design experiments to further verify the existence and extent of the proposed regulons. The PePPER webserver is freely accessible at http://pepper.molgenrug.nl.

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.