DISCLOSE : DISsection of CLusters Obtained by SEries of transcriptome data using functional annotations and putative transcription factor binding sites

Background: A typical step in the analysis of gene expression data is the determination of clusters of genes that exhibit similar expression patterns. Researchers are confronted with the seemingly arbitrary choice between numerous algorithms to perform cluster analysis. Results: We developed an exploratory application that benchmarks the results of clustering methods using functional annotations. In addition, a de novo DNA motif discovery algorithm is integrated in our program which identifies overrepresented DNA binding sites in the upstream DNA sequences of genes from the clusters that are indicative of sites of transcriptional control. The performance of our program was evaluated by comparing the original results of a time course experiment with the findings of our application. Conclusion: DISCLOSE assists researchers in the prokaryotic research community in systematically evaluating results of the application of a range of clustering algorithms to transcriptome data. Different performance measures allow to quickly and comprehensively determine the best suited clustering approach for a given dataset.

Computational genomics for prokaryotes : novel applications

The use of DNA microarray-based transcription profiling techniques is providing large quantities of genome-wide data on gene-expression patterns. This transcriptome data provides researchers with alternative ways to address and interpret biological questions in a functional and regulatory context. Although its application is ubiquitous in various areas of research, the analysis of the data that result from these experiments still remain a challenge. The main research theme of this thesis is the development of analytical software approaches and tools to analyze, visualize and exploit the information contained in global gene expression data. We have addressed the analysis of trancriptome data using various applications that were developed in-house; ranging from functional enrichment analyses, identification and visualization of regulatory elements, annotation of clustering results and the inference of putative gene functions using gene expression data. The last experimental chapter describes the results of the analysis of a large time-resolved transcriptome dataset (40 timepoints) of the model bacterium B. subtilis using several of the earlier described tools. The most remarkable outcome of our analysis is the occurrence of stress during the transitions between the different growth phases. These stress responses are not induced by added external stimuli of artificially induced starvation conditions, but are naturally occurring during the growth phases of B. subtilis on rich medium.

Iron Starvation Triggers the Stringent Response and Induces Amino Acid Biosynthesis for Bacillibactin Production in Bacillus subtilis

Iron deprivation in bacteria causes the derepression of genes controlled by the ferric uptake regulator (Fur). The present microarray analysis of iron-starved Bacillus subtilis cells grown in minimal medium unveils additional physiological effects on a large number of genes linked to stringent-response regulation and to genes involved in amino acid biosynthesis associated with pathways essential for bacillibactin production

Production and Secretion Stress Caused by Overexpression of Heterologous α-Amylase Leads to Inhibition of Sporulation and a Prolonged Motile Phase in Bacillus subtilis▿ †

Transcriptome analysis was used to investigate the global stress response of the gram-positive bacterium Bacillus subtilis caused by overproduction of the well-secreted AmyQ α-amylase from Bacillus amyloliquefaciens. Analyses of the control and overproducing strains were carried out at the end of exponential growth and in stationary phase, when protein secretion from B. subtilis is optimal. Among the genes that showed increased expression were htrA and htrB, which are part of the CssRS regulon, which responds to high-level protein secretion and heat stress. The analysis of the transcriptome profiles of a cssS mutant compared to the wild type, under identical secretion stress conditions, revealed several genes with altered transcription in a CssRS-dependent manner, for example, citM, ylxF, yloA, ykoJ, and several genes of the flgB operon. However, high-affinity CssR binding was observed only for htrA, htrB, and, possibly, citM. In addition, the DNA macroarray approach revealed that several genes of the sporulation pathway are downregulated by AmyQ overexpression and that a group of motility-specific (σD-dependent) transcripts were clearly upregulated. Subsequent flow-cytometric analyses demonstrate that, upon overproduction of AmyQ as well as of a nonsecretable variant of the α-amylase, the process of sporulation is severely inhibited. Similar experiments were performed to investigate the expression levels of the hag promoter, a well-established reporter for σD-dependent gene expression. This approach confirmed the observations based on our DNA macroarray analyses and led us to conclude that expression levels of several genes involved in motility are maintained at high levels under all conditions of α-amylase overproduction

MOVE: A Multi-Level Ontology-Based Visualization and Exploration Framework for Genomic Networks

Among the various research areas that comprise bioinformatics, systems biology is gaining increasing attention. An important goal of systems biology is the unraveling of dynamic interactions between components of living cells (e.g., proteins, genes). These interactions exist among others on genomic, transcriptomic, proteomic and metabolomic levels. The levels themselves are heavily interconnected, resulting in complex networks of different interacting biological entities. Currently, various bioinformatics tools exist which are able to perform a particular analysis on a particular type of network. Unfortunately, each tool has its own disadvantages hampering it to be used consistently for different types of networks or analytical methods. This paper describes the conceptual development of an open source extensible software framework that supports visualization and exploration of highly complex genomic networks, like metabolic or gene regulatory networks. The focus is on the conceptual foundations, starting from requirements, a description of the state of the art of network visualization systems, and an analysis of their shortcomings. We describe the implementation of some initial modules of the framework and apply them to a biological test case in bacterial regulation, which shows the relevance and feasibility of the proposed approach.

Association between organizational characteristics and adequate pain management at the intensive care unit

Purpose Half of the patients experience pain during their ICU stay which is known to influence their outcomes. Nurses and physicians encounter organizational barriers towards pain assessment and treatment. We aimed to evaluate the association between adequate pain management and nurse to patient ratio, bed occupancy rate, and fulltime presence of an intensivist. Materials and methods We performed unadjusted and case-mix adjusted mixed-effect logistic regression modeling on data from thirteen Dutch ICUs to investigate the association between ICU organizational characteristics and adequate pain management, i.e. patient-shift observations in which patients' pain was measured and acceptable, or unacceptable and normalized within 1 h.All ICU patients admitted between December 2017 and June 2018 were included, excluding patients who were delirious, comatose or had a Glasgow coma score < 8 at the first day of ICU admission. Results Case-mix adjusted nurse to patient ratios of 0.70 to 0.80 and over 0.80 were significantly associated with adequate pain management (OR [95% confidence interval] of respectively 1.14 [1.07–1.21] and 1.16 [1.08–1.24]). Bed occupancy rate and intensivist presence showed no association. Conclusion Higher nurse to patient ratios increase the percentage of patients with adequate pain management especially in medical and mechanically ventilated patients

Adult Antarctic krill feeding at abyssal depths

Antarctic krill (Euphausia superba) is a large euphausiid, widely distributed within the Southern Ocean [1], and a key species in the Antarctic food web [2]. The Discovery Investigations in the early 20(th) century, coupled with subsequent work with both nets and echosounders, indicated that the bulk of the population of postlarval krill is typically confined to the top 150 m of the water column [1, 3, 4]. Here, we report for the first time the existence of significant numbers of Antarctic krill feeding actively at abyssal depths in the Southern Ocean. Biological observations from the deep-water remotely operated vehicle Isis in the austral summer of 2006/07 have revealed the presence of adult krill (Euphausia superba Dana), including gravid females, at unprecedented depths in Marguerite Bay, western Antarctic Peninsula. Adult krill were found close to the seabed at all depths but were absent from fjords close inshore. At all locations where krill were detected they were seen to be actively feeding, and at many locations there were exuviae (cast molts). These observations revise significantly our understanding of the depth distribution and ecology of Antarctic krill, a central organism in the Southern Ocean ecosystem