Showing papers by "Rainer Breitling published in 2009"

System-wide molecular evidence for phenotypic buffering in Arabidopsis.

Abstract: We profiled 162 lines of Arabidopsis for variation in transcript, protein and metabolite abundance using mRNA microarrays, two-dimensional polyacrylamide gel electrophoresis, gas chromatography time-of-flight mass spectrometry, liquid chromatography quadrupole time-of-flight mass spectrometry, and proton nuclear magnetic resonance. We added all publicly available phenotypic data from the same lines and mapped quantitative trait loci (QTL) for 40,580 molecular and 139 phenotypic traits. We found six QTL hot spots with major, system-wide effects, suggesting there are six breakpoints in a system otherwise buffered against many of the 500,000 SNPs.

Expression quantitative trait loci are highly sensitive to cellular differentiation state

Abstract: Genetical genomics is a strategy for mapping gene expression variation to expression quantitative trait loci (eQTLs). We performed a genetical genomics experiment in four functionally distinct but developmentally closely related hematopoietic cell populations isolated from the BXD panel of recombinant inbred mouse strains. This analysis allowed us to analyze eQTL robustness/sensitivity across different cellular differentiation states. Although we identified a large number (365) of “static” eQTLs that were consistently active in all four cell types, we found a much larger number (1,283) of “dynamic” eQTLs showing cell-type–dependence. Of these, 140, 45, 531, and 295 were preferentially active in stem, progenitor, erythroid, and myeloid cells, respectively. A detailed investigation of those dynamic eQTLs showed that in many cases the eQTL specificity was associated with expression changes in the target gene. We found no evidence for target genes that were regulated by distinct eQTLs in different cell types, suggesting that large-scale changes within functional regulatory networks are uncommon. Our results demonstrate that heritable differences in gene expression are highly sensitive to the developmental stage of the cell population under study. Therefore, future genetical genomics studies should aim at studying multiple well-defined and highly purified cell types in order to construct as comprehensive a picture of the changing functional regulatory relationships as possible.

Probabilistic assignment of formulas to mass peaks in metabolomics experiments

Abstract: Motivation: High-accuracy mass spectrometry is a popular technology for high-throughput measurements of cellular metabolites (metabolomics). One of the major challenges is the correct identification of the observed mass peaks, including the assignment of their empirical formula, based on the measured mass. Results: We propose a novel probabilistic method for the assignment of empirical formulas to mass peaks in high-throughput metabolomics mass spectrometry measurements. The method incorporates information about possible biochemical transformations between the empirical formulas to assign higher probability to formulas that could be created from other metabolites in the sample. In a series of experiments, we show that the method performs well and provides greater insight than assignments based on mass alone. In addition, we extend the model to incorporate isotope information to achieve even more reliable formula identification. Availability: A supplementary document, Matlab code, data and further information are available from http://www.dcs.gla.ac.uk/inference/metsamp. Contact: srogers@dcs.gla.ac.uk

Neurodegenerative diseases: Lessons from genome-wide screens in small model organisms

Abstract: Various age-related neurodegenerative diseases, including Parkinson's disease, polyglutamine expansion diseases and Alzheimer's disease, are associated with the accumulation of misfolded proteins in aggregates in the brain. How and why these proteins form aggregates and cause disease is still poorly understood. Small model organisms—the baker's yeast Saccharomyces cerevisiae, the nematode worm Caenorhabditis elegans and the fruit fly Drosophila melanogaster—have been used to model these diseases and high-throughput genetic screens using these models have led to the identification of a large number of genes that modify aggregation and toxicity of the disease proteins. In this review, we revisit these models and provide a comprehensive comparison of the genetic screens performed so far. Our integrative analysis highlights alterations of a wide variety of basic cellular processes. Not all disease proteins are influenced by alterations in the same cellular processes and despite the unifying theme of protein misfolding and aggregation, the pathology of each of the age-related misfolding disorders can be induced or influenced by a disease-protein-specific subset of molecular processes.

Simple data-reduction method for high-resolution LC–MS data in metabolomics

Abstract: Background: Metabolomics LC–MS experiments yield large numbers of peaks, few of which can be identified by database matching. Many of the remaining peaks correspond to derivatives of identified peaks (e.g., isotope peaks, adducts, fragments and multiply charged molecules). In this article, we present a data-reduction approach that automatically identifies these derivative peaks. Results: Using data-driven clustering based on chromatographic peak shape correlation and intensity patterns across biological replicates, derivative peaks can be reliably identified. Using a test data set obtained from Leishmania donovani extracts, we achieved a 60% reduction of the number of peaks. After quality control filtering, almost 80% of the peaks could putatively be identified by database matching. Conclusion: Automated peak filtering substantially speeds up the data-interpretation process.

Robust signaling networks of the adipose secretome

Abstract: Type 2 diabetes is a prototypical complex systems disease that has a strong hereditary component and etiologic links with a sedentary lifestyle, overeating and obesity. Adipose tissue has been shown to be a central driver of type 2 diabetes progression, establishing and maintaining a chronic state of low-level inflammation. The number and diversity of identified endocrine factors from adipose tissue (adipokines) is growing rapidly. Here, I argue that a systems biology approach to understanding the robust multi-level signaling networks established by the adipose secretome will be crucial for developing efficient type 2 diabetes treatment. Recent advances in whole-genome association studies, global molecular profiling and quantitative modeling are currently fueling the emergence of this novel research strategy.

Chemoresistance acquisition induces a global shift of expression of aniogenesis-associated genes and increased pro-angogenic activity in neuroblastoma cells.

Abstract: Chemoresistance acquisition may influence cancer cell biology. Here, bioinformatics analysis of gene expression data was used to identify chemoresistance-associated changes in neuroblastoma biology. Bioinformatics analysis of gene expression data revealed that expression of angiogenesis-associated genes significantly differs between chemosensitive and chemoresistant neuroblastoma cells. A subsequent systematic analysis of a panel of 14 chemosensitive and chemoresistant neuroblastoma cell lines in vitro and in animal experiments indicated a consistent shift to a more pro-angiogenic phenotype in chemoresistant neuroblastoma cells. The molecular mechanims underlying increased pro-angiogenic activity of neuroblastoma cells are individual and differ between the investigated chemoresistant cell lines. Treatment of animals carrying doxorubicin-resistant neuroblastoma xenografts with doxorubicin, a cytotoxic drug known to exert anti-angiogenic activity, resulted in decreased tumour vessel formation and growth indicating chemoresistance-associated enhanced pro-angiogenic activity to be relevant for tumour progression and to represent a potential therapeutic target. A bioinformatics approach allowed to identify a relevant chemoresistance-associated shift in neuroblastoma cell biology. The chemoresistance-associated enhanced pro-angiogenic activity observed in neuroblastoma cells is relevant for tumour progression and represents a potential therapeutic target.

designGG: an R-package and web tool for the optimal design of genetical genomics experiments

Abstract: Background High-dimensional biomolecular profiling of genetically different individuals in one or more environmental conditions is an increasingly popular strategy for exploring the functioning of complex biological systems. The optimal design of such genetical genomics experiments in a cost-efficient and effective way is not trivial.

An Introduction to BioModel Engineering, Illustrated for Signal Transduction Pathways

Abstract: BioModel Engineering is the science of designing, constructing and analyzing computational models of biological systems. It is inspired by concepts from software engineering and computing science. This paper illustrates a major theme in BioModel Engineering, namely that identifying a quantitative model of a dynamic system means building the structure, finding an initial state, and parameter fitting. In our approach, the structure is obtained by piecewise construction of models from modular parts, the initial state is obtained by analysis of the structure and parameter fitting comprises determining the rate parameters of the kinetic equations. We illustrate this with an example in the area of intracellular signalling pathways.

Anti-cancer effects of artesunate in a panel of chemoresistant neuroblastoma cell lines

Abstract: Neuroblastoma is the most frequent extracranial solid tumour of childhood. About half of all neuroblastoma patients are diagnosed with high-risk disease characterised by overall survival rates below 40% despite intensive multimodal treatment [1]. Therapy failure is basically caused by acquired chemoresistance [2]. Artemisinin derivatives including artemisinin, dihydroartemi-sinin, and artesunate are used as anti-malaria drugs, especially as constituents of drug combinations composed to counteract drug resistance in malaria [3]. Moreover, artemisinin derivatives were shown to exert anti-bacterial, antiviral, and anti-cancer effects [3]. Studies indicated that artemisinin derivatives are active against cells from a broad spectrum of cancer entities [3–11]. Notably, artemisinin derivatives were described to be effective in many drug-resistant cancer cell lines [3]. Prominent resistance mechanisms like high expression of ATP binding cassette (ABC) transporters or p53 loss-of-function mutations did not substantially affect cancer cell sensitivity to artesunate [3,12,13]. Artemisinin derivatives have not been studied for anti-cancer activity in human neuroblastoma cells, yet. To investigate the effects of potential anti-cancer drugs on neuroblastoma cells, we established a panel of chemoresistant neuroblastoma cell lines by adaptation of chemosensitive neuroblastoma to increasing concentrations of cytotoxic drugs [14–20]. Here, we investigated the influence of artemisinin and its derivatives dihydroartemisinin and artesunate on chemosensitive or che-moresistant neuroblastoma cell lines and on primary neuro-blastoma cultures. Moreover, gene expression signatures that correlate with artesunate sensitivity of neuroblastoma cells were established. Artemisinin derivatives are well-tolerated anti-malaria drugs that also exert anti-cancer activity. Here, we investigated artemisinin and its derivatives dihydroartemisinin and artesunate in a panel of chemosensitive and chemoresistant human neuroblastoma cells as well as in primary neuroblastoma cultures. Only dihydroartemisinin and artesunate affected neuroblastoma cell viability with artesunate being more active. Artesunate-induced apoptosis and reactive oxygen species in neuroblastoma cells. Of 16 cell lines and two primary cultures, only UKF-NB-3 r CDDP 1000 showed low sensitivity to artesunate. Characteristic gene expression signatures based on a previous analysis of artesunate resistance in the NCI60 cell line panel clearly separated UKF-NB-3 r CDDP 1000 from the other cell lines. L-Buthionine-S,R-sulfoximine, an inhibitor of GCL (glutamate–cysteine ligase), resensitised in part UKF-NB-3 r CDDP 1000 cells to artesunate. This finding together with bioinformatic analysis of expression of genes involved in glutathione metabolism showed that this pathway is involved in artesunate resistance. These data indicate that neuroblastoma represents an artesunate-sensitive cancer entity and that artesunate is also effective in chemoresistant neuroblastoma cells. Please cite this article in press as: Michaelis M, …

09091 Abstracts Collection -- Formal Methods in Molecular Biology

Abstract: From 23. February to 27. February 2009, the Dagstuhl Seminar 09091 ``Formal Methods in Molecular Biology '' was held in Schloss Dagstuhl~--~Leibniz Center for Informatics. During the seminar, several participants presented their current research, and ongoing work and open problems were discussed. Abstracts of the presentations given during the seminar as well as abstracts of seminar results and ideas are put together in this paper. The first section describes the seminar topics and goals in general. Links to extended abstracts or full papers are provided, if available.