84 research outputs found

    MINOMICS:visualizing prokaryote transcriptomics and proteomics data in a genomic context

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    We have developed MINOMICS, a tool that allows facile and in-depth visualization of prokaryotic transcriptomic and proteomic data in conjunction with genomics data. MINOMICS generates interactive linear genome maps in which multiple experimental datasets are displayed together with operon, regulatory motif, transcriptional promoter and transcriptional terminator information

    Transcriptome Analysis of a Spray Drying-Resistant Subpopulation Reveals a Zinc-Dependent Mechanism for Robustness in L. lactis SK11

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    The viability of starter cultures is essential for an adequate contribution to the fermentation process and end-product. Therefore, robustness during processing and storage is an important characteristic of starter culture strains. For instance, during spray drying cells are exposed to heat and oxidative stress, generally resulting in loss of viability. In this study, we exposed the industrially relevant but stress-sensitive Lactococcus lactis strain SK11 to two cycles of heat stress, with intermediate recovery and cultivation at moderate temperatures. After these two cycles of heat exposure, the abundance of robust derivatives was increased as compared with the original culture, which enabled isolation of heat-resistant subpopulations displaying up to 1,000-fold enhanced heat stress survival. Moreover, this heat-resistant subpopulation demonstrated an increased survival during spray drying. Derivatives from two independent lineages displayed different transcriptome changes as compared with the wild type strain, indicating that the increased robustness within these lineages was established by different adaptive strategies. Nevertheless, an overlap in differential gene expression in all five derivatives tested in both lineages included three genes in an operon involved in zinc transport. The link between zinc homeostasis and heat stress survival in L. lactis was experimentally established by culturing of the wild type strain SK11 in medium with various levels of zinc ions, which resulted in alterations in heat stress survival phenotypes. This study demonstrates that robust derivatives of a relatively sensitive L. lactis strain can be isolated by repeated exposure to heat stress. Moreover, this work demonstrates that transcriptome analysis of these robust derivatives can provide clues for improvement of the robustness of the original strain. This could boost the industrial application of strains with specific desirable traits but inadequate robustness characteristics

    Projector 2: contig mapping for efficient gap-closure of prokaryotic genome sequence assemblies

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    With genome sequencing efforts increasing exponentially, valuable information accumulates on genomic content of the various organisms sequenced. Projector 2 uses (un)finished genomic sequences of an organism as a template to infer linkage information for a genome sequence assembly of a related organism being sequenced. The remaining gaps between contigs for which no linkage information is present can subsequently be closed with direct PCR strategies. Compared with other implementations, Projector 2 has several distinctive features: a user-friendly web interface, automatic removal of repetitive elements (repeat-masking) and automated primer design for gap-closure purposes. Moreover, when using multiple fragments of a template genome, primers for multiplex PCR strategies can also be designed. Primer design takes into account that, in many cases, contig ends contain unreliable DNA sequences and repetitive sequences. Closing the remaining gaps in prokaryotic genome sequence assemblies is thereby made very efficient and virtually effortless. We demonstrate that the use of single or multiple fragments of a template genome (i.e. unfinished genome sequences) in combination with repeat-masking results in mapping success rates close to 100%. The web interface is freely accessible at

    PhenoLink - a web-tool for linking phenotype to ~omics data for bacteria: application to gene-trait matching for Lactobacillus plantarum strains

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    Contains fulltext : 109042.pdf (publisher's version ) (Open Access)BACKGROUND: Linking phenotypes to high-throughput molecular biology information generated by ~omics technologies allows revealing cellular mechanisms underlying an organism's phenotype. ~Omics datasets are often very large and noisy with many features (e.g., genes, metabolite abundances). Thus, associating phenotypes to ~omics data requires an approach that is robust to noise and can handle large and diverse data sets. RESULTS: We developed a web-tool PhenoLink (http://bamics2.cmbi.ru.nl/websoftware/phenolink/) that links phenotype to ~omics data sets using well-established as well new techniques. PhenoLink imputes missing values and preprocesses input data (i) to decrease inherent noise in the data and (ii) to counterbalance pitfalls of the Random Forest algorithm, on which feature (e.g., gene) selection is based. Preprocessed data is used in feature (e.g., gene) selection to identify relations to phenotypes. We applied PhenoLink to identify gene-phenotype relations based on the presence/absence of 2847 genes in 42 Lactobacillus plantarum strains and phenotypic measurements of these strains in several experimental conditions, including growth on sugars and nitrogen-dioxide production. Genes were ranked based on their importance (predictive value) to correctly predict the phenotype of a given strain. In addition to known gene to phenotype relations we also found novel relations. CONCLUSIONS: PhenoLink is an easily accessible web-tool to facilitate identifying relations from large and often noisy phenotype and ~omics datasets. Visualization of links to phenotypes offered in PhenoLink allows prioritizing links, finding relations between features, finding relations between phenotypes, and identifying outliers in phenotype data. PhenoLink can be used to uncover phenotype links to a multitude of ~omics data, e.g., gene presence/absence (determined by e.g.: CGH or next-generation sequencing), gene expression (determined by e.g.: microarrays or RNA-seq), or metabolite abundance (determined by e.g.: GC-MS)

    BAGEL:a web-based bacteriocin genome mining tool

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    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:

    Phage-derived protein induces increased platelet activation and is associated with mortality in patients with invasive pneumococcal disease

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    To improve our understanding about the severity of invasive pneumococcal disease (IPD), we investigated the association between the genotype of Streptococcus pneumoniae and disease outcomes for 349 bacteremic patients. A pneumococcal genome-wide association study (GWAS) demonstrated a strong correlation between 30-day mortality and the presence of the phage-derived gene pblB, encoding a platelet-binding protein whose effects on platelet activation were previously unknown. Platelets are increasingly recognized as key players of the innate immune system, and in sepsis, excessive platelet activation contributes to microvascular obstruction, tissue hypoperfusion, and finally multiorgan failure, leading to mortality. Our in vitro studies revealed that pblB expression was induced by fluoroquinolones but not by the beta-lactam antibiotic penicillin G. Subsequently, we determined pblB induction and platelet activation by incubating whole blood with the wild type or a pblB knockout mutant in the presence or absence of antibiotics commonly administered to our patient cohort. pblB-dependent enhancement of platelet activation, as measured by increased expression of the ɑ-granule protein P-selectin, the binding of fibrinogen to the activated ɑ IIbβ3 receptor, and the formation of platelet-monocyte complex occurred irrespective of antibiotic exposure. In conclusion, the presence of pblB on the pneumococcal chromosome potentially leads to increased mortality in patients with an invasive S. pneumoniae infection, which may be explained by enhanced platelet activation. This study highlights the clinical utility of a bacterial GWAS, followed by functional characterization, to identify bacterial factors involved in disease severity. IMPORTANCE The exact mechanisms causing mortality in invasive pneumococcal disease (IPD) patients are not completely understood. We examined 349 patients with IPD and found in a bacterial genome-wide association study (GWAS) that the presence of the phage-derived gene pblB was associated with mortality in the first 30 days after hospitalization. Although pblB has been extensively studied in Streptococcus mitis, its consequence for the interaction between platelets and Streptococcus pneumoniae is largely unknown. Platelets are important in immunity and inflammation, and excessive platelet activation contributes to microvascular obstruction and multiorgan failure, leading to mortality. We therefore developed this study to assess whether the expression of pblB might increase the risk of death for IPD patients through its effect on enhanced platelet activation. This study also shows the value of integrating extensive bacterial genomics and clinical data in predicting and understanding pathogen virulence, which in turn will help to improve prognosis and therapy

    Microbial bioinformatics for food safety and production

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    Item does not contain fulltextIn the production of fermented foods, microbes play an important role. Optimization of fermentation processes or starter culture production traditionally was a trial-and-error approach inspired by expert knowledge of the fermentation process. Current developments in high-throughput 'omics' technologies allow developing more rational approaches to improve fermentation processes both from the food functionality as well as from the food safety perspective. Here, the authors thematically review typical bioinformatics techniques and approaches to improve various aspects of the microbial production of fermented food products and food safety

    Mechanisms and Evolution of Control Logic in Prokaryotic Transcriptional Regulation

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    Summary: A major part of organismal complexity and versatility of prokaryotes resides in their ability to fine-tune gene expression to adequately respond to internal and external stimuli. Evolution has been very innovative in creating intricate mechanisms by which different regulatory signals operate and interact at promoters to drive gene expression. The regulation of target gene expression by transcription factors (TFs) is governed by control logic brought about by the interaction of regulators with TF binding sites (TFBSs) in cis-regulatory regions. A factor that in large part determines the strength of the response of a target to a given TF is motif stringency, the extent to which the TFBS fits the optimal TFBS sequence for a given TF. Advances in high-throughput technologies and computational genomics allow reconstruction of transcriptional regulatory networks in silico. To optimize the prediction of transcriptional regulatory networks, i.e., to separate direct regulation from indirect regulation, a thorough understanding of the control logic underlying the regulation of gene expression is required. This review summarizes the state of the art of the elements that determine the functionality of TFBSs by focusing on the molecular biological mechanisms and evolutionary origins of cis-regulatory regions

    Reconstruction and inference of the Lactococcus lactis MG1363 gene co-expression network

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    Lactic acid bacteria are Gram-positive bacteria used throughout the world in many industrial applications for their acidification, flavor and texture formation attributes. One of the species, Lactococcus lactis, is employed for the production of fermented milk products like cheese, buttermilk and quark. It ferments lactose to lactic acid and, thus, helps improve the shelf life of the products. Many physiological and transcriptome studies have been performed in L. lactis in order to comprehend and improve its biotechnological assets. Using large amounts of transcriptome data to understand and predict the behavior of biological processes in bacterial or other cell types is a complex task. Gene networks enable predicting gene behavior and function in the context of transcriptionally linked processes. We reconstruct and present the gene co-expression network (GCN) for the most widely studied L. lactis strain, MG1363, using publicly available transcriptome data. Several methods exist to generate and judge the quality of GCNs. Different reconstruction methods lead to networks with varying structural properties, consequently altering gene clusters. We compared the structural properties of the MG1363 GCNs generated by five methods, namely Pearson correlation, Spearman correlation, GeneNet, Weighted Gene Co-expression Network Analysis (WGCNA), and Sparse PArtial Correlation Estimation (SPACE). Using SPACE, we generated an L. lactis MG1363 GCN and assessed its quality using modularity and structural and biological criteria. The L. lactis MG1363 GCN has structural properties similar to those of the gold-standard networks of Escherichia coli K-12 and Bacillus subtilis 168. We showcase that the network can be used to mine for genes with similar expression profiles that are also generally linked to the same biological process
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