Showing papers by "Rainer Breitling published in 2011"
TL;DR: This work presents the first comprehensive pipeline capable of identifying biosynthetic loci covering the whole range of known secondary metabolite compound classes, and integrates or cross-links all previously available secondary-metabolite specific gene analysis methods in one interactive view.
Abstract: Bacterial and fungal secondary metabolism is a rich source of novel bioactive compounds with potential pharmaceutical applications as antibiotics, anti-tumor drugs or cholesterol-lowering drugs To find new drug candidates, microbiologists are increasingly relying on sequencing genomes of a wide variety of microbes However, rapidly and reliably pinpointing all the potential gene clusters for secondary metabolites in dozens of newly sequenced genomes has been extremely challenging, due to their biochemical heterogeneity, the presence of unknown enzymes and the dispersed nature of the necessary specialized bioinformatics tools and resources Here, we present antiSMASH (antibiotics & Secondary Metabolite Analysis Shell), the first comprehensive pipeline capable of identifying biosynthetic loci covering the whole range of known secondary metabolite compound classes (polyketides, non-ribosomal peptides, terpenes, aminoglycosides, aminocoumarins, indolocarbazoles, lantibiotics, bacteriocins, nucleosides, beta-lactams, butyrolactones, siderophores, melanins and others) It aligns the identified regions at the gene cluster level to their nearest relatives from a database containing all other known gene clusters, and integrates or cross-links all previously available secondary-metabolite specific gene analysis methods in one interactive view antiSMASH is available at http://antismashsecondarymetabolitesorg
1,496 citations
TL;DR: It is demonstrated that a retention time prediction model can improve metabolite identification on a hydrophilic interaction chromatography-high-resolution mass spectrometry metabolomics platform, allowing identified metabolites to be mapped onto an organism-wide metabolic network, providing opportunities for future studies of cellular metabolism from a global systems biology perspective.
Abstract: Metabolomics is an emerging field of postgenomic biology concerned with comprehensive analysis of small molecules in biological systems. However, difficulties associated with the identification of detected metabolites currently limit its application. Here we demonstrate that a retention time prediction model can improve metabolite identification on a hydrophilic interaction chromatography (HILIC)–high-resolution mass spectrometry metabolomics platform. A quantitative structure retention relationship (QSRR) model, incorporating six physicochemical variables in a multiple-linear regression based on 120 authentic standard metabolites, shows good predictive ability for retention times of a range of metabolites (cross-validated R2 = 0.82 and mean squared error = 0.14). The predicted retention times improved metabolite identification by removing 40% of the false identifications that occurred with identification by accurate mass alone. The importance of this procedure was demonstrated by putative identification ...
336 citations
TL;DR: The PeakML format in particular enables the flexible exchange of processed data between software created by different groups or companies, as it is illustrated by providing a PeakML-based integration of the widely used XCMS package with mzMatch data processing tools.
Abstract: The recent proliferation of high-resolution mass spectrometers has generated a wealth of new data analysis methods. However, flexible integration of these methods into configurations best suited to the research question is hampered by heterogeneous file formats and monolithic software development. The mzXML, mzData, and mzML file formats have enabled uniform access to unprocessed raw data. In this paper we present our efforts to produce an equally simple and powerful format, PeakML, to uniformly exchange processed intermediary and result data. To demonstrate the versatility of PeakML, we have developed an open source Java toolkit for processing, filtering, and annotating mass spectra in a customizable pipeline (mzMatch), as well as a user-friendly data visualization environment (PeakML Viewer). The PeakML format in particular enables the flexible exchange of processed data between software created by different groups or companies, as we illustrate by providing a PeakML-based integration of the widely used...
300 citations
TL;DR: A wide range of strategies that control the activity of biosynthetic modules in the cell in space and time are surveyed, and how these strategies can be used to design efficient cellular synthetic production systems are illustrated.
Abstract: One of the most promising applications of synthetic biology is the biosynthesis of new drugs from secondary metabolites. Here, we survey a wide range of strategies that control the activity of biosynthetic modules in the cell in space and time, and illustrate how these strategies can be used to design efficient cellular synthetic production systems. Re-engineered versions of secondary metabolite biosynthetic pathways identified from any genomic sequence can then be inserted into these systems in a plug-and-play fashion.
171 citations
TL;DR: It is shown that nutlin-3 induces de novo p53 mutations not initially present in the original cell population, and cancer patients should be carefully monitored for the emergence of p53-mutated, multi-drug-resistant cells.
Abstract: Six p53 wild-type cancer cell lines from infrequently p53-mutated entities (neuroblastoma, rhabdomyosarcoma, and melanoma) were continuously exposed to increasing concentrations of the murine double minute 2 inhibitor nutlin-3, resulting in the emergence of nutlin-3-resistant, p53-mutated sublines displaying a multi-drug resistance phenotype. Only 2 out of 28 sublines adapted to various cytotoxic drugs harboured p53 mutations. Nutlin-3-adapted UKF-NB-3 cells (UKF-NB-3rNutlin10 μM, harbouring a G245C mutation) were also radiation resistant. Analysis of UKF-NB-3 and UKF-NB-3rNutlin10 μM cells by RNA interference experiments and lentiviral transduction of wild-type p53 into p53-mutated UKF-NB-3rNutlin10 μM cells revealed that the loss of p53 function contributes to the multi-drug resistance of UKF-NB-3rNutlin10 μM cells. Bioinformatics PANTHER pathway analysis based on microarray measurements of mRNA abundance indicated a substantial overlap in the signalling pathways differentially regulated between UKF-NB-3rNutlin10 μM and UKF-NB-3 and between UKF-NB-3 and its cisplatin-, doxorubicin-, or vincristine-resistant sublines. Repeated nutlin-3 adaptation of neuroblastoma cells resulted in sublines harbouring various p53 mutations with high frequency. A p53 wild-type single cell-derived UKF-NB-3 clone was adapted to nutlin-3 in independent experiments. Eight out of ten resulting sublines were p53-mutated harbouring six different p53 mutations. This indicates that nutlin-3 induces de novo p53 mutations not initially present in the original cell population. Therefore, nutlin-3-treated cancer patients should be carefully monitored for the emergence of p53-mutated, multi-drug-resistant cells.
155 citations
TL;DR: This chapter provides an overview of the synthetic biology challenges in Streptomyces and then presents the existing toolbox of molecular methods that can be employed in this organism.
Abstract: Actinomycete bacteria of the genus Streptomyces are major producers of bioactive compounds for the biotechnology industry. They are the source of most clinically used antibiotics, as well as of several widely used drugs against common diseases, including cancer . Genome sequencing has revealed that the potential of Streptomyces species for the production of valuable secondary metabolites is even larger than previously realized. Accessing this rich genomic resource to discover new compounds by activating “cryptic” pathways is an interesting challenge for synthetic biology. This approach is facilitated by the inherent natural modularity of secondary metabolite biosynthetic pathways, at the level of individual enzymes (such as modular polyketide synthases), but also of gene cassettes/operons and entire biosynthetic gene clusters. It also benefits from a long tradition of molecular biology in Streptomyces, which provides a number of specific tools, ranging from cloning vectors to inducible promoters and translational control elements. In this chapter, we first provide an overview of the synthetic biology challenges in Streptomyces and then present the existing toolbox of molecular methods that can be employed in this organism.
62 citations
TL;DR: It is found that the majority of the changes contributed not to a complex rewiring of primary metabolism but consisted of a simple upregulation of various antibiotic biosynthesis gene clusters, which demonstrates that functional genomic analysis can provide new leads for strain improvement in biotechnology.
Abstract: To increase production of the important pharmaceutical compound clavulanic acid, a β-lactamase inhibitor, both random mutagenesis approaches and rational engineering of Streptomyces clavuligerus strains have been extensively applied. Here, for the first time, we compared genome-wide gene expression of an industrial S. clavuligerus strain, obtained through iterative mutagenesis, with that of the wild-type strain. Intriguingly, we found that the majority of the changes contributed not to a complex rewiring of primary metabolism but consisted of a simple upregulation of various antibiotic biosynthesis gene clusters. A few additional transcriptional changes in primary metabolism at key points seem to divert metabolic fluxes to the biosynthetic precursors for clavulanic acid. In general, the observed changes largely coincide with genes that have been targeted by rational engineering in recent years, yet the presence of a number of previously unexplored genes clearly demonstrates that functional genomic analysis can provide new leads for strain improvement in biotechnology.
47 citations
TL;DR: How in the new field of synthetic biology, random mutagenesis and rational engineering can be implemented complementarily in ways which may enable one to go beyond the status quo that has now been reached by each method independently is discussed.
Abstract: Natural products derived from the secondary metabolism of microbes constitute a cornerstone of modern medicine. Engineering bugs to produce these products in high quantities is a major challenge for biotechnology, which has usually been tackled by either one of two strategies: iterative random mutagenesis or rational design. Recently, we analyzed the transcriptome of a Streptomyces clavuligerus strain optimized for production of the β-lactamase inhibitor clavulanic acid by multiple rounds of mutagenesis and selection, and discovered that the observed changes matched surprisingly well with simple changes that have been introduced into these strains by rational engineering. Here, we discuss how in the new field of synthetic biology, random mutagenesis and rational engineering can be implemented complementarily in ways which may enable one to go beyond the status quo that has now been reached by each method independently.
35 citations
TL;DR: A comparative analysis of genome‐scale metabolic models of 37 species of actinomycetes and constructed a global enzyme association network to identify both a conserved “core network” and an “essential core network’ of the entire group.
32 citations
TL;DR: A strong perturbation in the expression of three pigmented antibiotic clusters in the mutant throughout the growth curve is reported, thus providing a molecular explanation for the antibiotic phenotype observed previously.
Abstract: Streptomycetes have high biotechnological relevance as producers of diverse metabolites widely used in medical and agricultural applications. The biosynthesis of these metabolites is controlled by signalling molecules, γ‐butyrolactones, that act as bacterial hormones. In Streptomyces coelicolor, a group of signalling molecules called SCBs (S. coelicolorbutanolides) regulates production of the pigmented antibiotics coelicolor polyketide (CPK), actinorhodin and undecylprodigiosin. The γ‐butyrolactone synthase ScbA is responsible for the biosynthesis of SCBs. Here we show the results of a genome‐wide transcriptome analysis of a scbA deletion mutant prior to and during the transition to antibiotic production. We report a strong perturbation in the expression of three pigmented antibiotic clusters in the mutant throughout the growth curve, thus providing a molecular explanation for the antibiotic phenotype observed previously. Our study also revealed, for the first time, that the secondary metabolite cluster responsible for synthesis of the siderophore desferrioxamine is under the control of SCB signalling. Moreover, expression of the genes encoding enzymes for primary metabolism pathways, which supply antibiotic precursors and genes for morphological differentiation, was found shifted earlier in time in the mutant. In conclusion, our time series analysis demonstrates new details of the regulatory effects of the γ‐butyrolactone system in Streptomyces.
29 citations
TL;DR: Production of human CFTR in the prokaryotic expression host Lactococcus lactis and the reported consequences of membrane protein overexpression in Escherichia coli indicate that different strategies are needed to overcome low expression yields and toxicity.
TL;DR: It is shown that the overexpression of an antisense non‐coding RNA targeting glutamine synthetase I results in a major reorganization of the metabolism of Streptomyces coelicolor, the model species of antibiotic‐producing bacteria.
Abstract: The global analysis of metabolism by liquid chromatography coupled to mass spectrometry is often hampered by a large amount of biological and technical variability. Here, we introduce an experimental and analytical strategy that can produce robust metabolome profiles in the face of this challenge. By applying a new computational approach based on concordance analysis to an extremely large number of analytical replicates, we are able to show that the overexpression of an antisense non-coding RNA targeting glutamine synthetase I results in a major reorganization of the metabolism of Streptomyces coelicolor, the model species of antibiotic-producing bacteria. We identified 97 metabolites with statistically significant reproducible dynamic behavior across the time series. The observed metabolic changes are very rapid, specific and widespread across metabolism, but focus on the nitrogen assimilation pathways. Our results demonstrate the power of highly replicated experimental designs for the robust characterization of metabolite dynamics. The identified global rearrangement of metabolism suggests the usefulness of RNA interference as an efficient strategy to manipulate the physiology of bacteria with wider biotechnological applicability in microorganisms.
TL;DR: This review presents an overview of the diverse metabolomics approaches recently adopted to explore the metabolism of a wide variety of microorganisms and discusses the important complementary information provided by computational methods such as genome-scale metabolic modeling.
Abstract: Microorganisms depend on their ability to modulate their metabolic composition according to specific circumstances, such as different phases of the growth cycle and circadian rhythms, fluctuations in environmental conditions, as well as experimental perturbations. A thorough understanding of these metabolic adaptations requires the ability to comprehensively identify and quantify the metabolome of bacterial cells in different states. In this review, we present an overview of the diverse metabolomics approaches recently adopted to explore the metabolism of a wide variety of microorganisms. Focusing on a selection of illustrative case studies, we assess the different experimental designs used and explore the major achievements and remaining challenges in the field. We conclude by discussing the important complementary information provided by computational methods such as genome-scale metabolic modeling, which enable an integrated analysis of metabolic state changes in the context of overall cellular physiology.
TL;DR: All functionally orphan genes of Streptomyces coelicolor are analyzed and a list of "high priority" orphans are identified by combining gene expression analysis and additional phylogenetic information (i.e. the level of evolutionary conservation of each protein).
Abstract: Streptomyces coelicolor, a model organism of antibiotic producing bacteria, has one of the largest genomes of the bacterial kingdom, including 7825 predicted protein coding genes. A large number of these genes, nearly 34%, are functionally orphan (hypothetical proteins with unknown function). However, in gene expression time course data, many of these functionally orphan genes show interesting expression patterns. In this paper, we analyzed all functionally orphan genes of Streptomyces coelicolor and identified a list of "high priority" orphans by combining gene expression analysis and additional phylogenetic information (i.e. the level of evolutionary conservation of each protein). The prioritized orphan genes are promising candidates to be examined experimentally in the lab for further characterization of their function.
TL;DR: Erratum to: Towards an unbiased metabolic profiling of protozoan parasites: optimisation of a Leishmania sampling protocol for HILIC-orbitrap analysis.
Abstract: Erratum to: Towards an unbiased metabolic profiling of protozoan parasites: optimisation of a Leishmania sampling protocol for HILIC-orbitrap analysis
12 Sep 2011