Oliver Rinner - Academia.edu (original) (raw)

Papers by Oliver Rinner

Bioinformatics, Aug 12, 2003

We present a www server for homology-based gene prediction. The user enters a pair of evolutionar... more We present a www server for homology-based gene prediction. The user enters a pair of evolutionary related genomic sequences, for example from human and mouse. Our software system uses CHAOS and DIALIGN to calculate an alignment of the input sequences and then searches for conserved splicing signals and start/stop codons around regions of local sequence similarity. This way, candidate exons are identified that are used, in turn, to calculate optimal gene models. The server returns the constructed gene model by email, together with a graphical representation of the underlying genomic alignment.

HAL (Le Centre pour la Communication Scientifique Directe), Oct 23, 2007

Protein complexes have largely been studied by immunoaffinity purification and (mass spectrometri... more Protein complexes have largely been studied by immunoaffinity purification and (mass spectrometric) analysis. Although this approach has been widely and successfully used it is limited because it has difficulties reliably discriminating true from false protein complex components, identifying post-translational modifications, and detecting quantitative changes in complex composition or state of modification of complex components. We have developed a protocol that enables us to determine, in a single LC-MALDI-TOF/TOF analysis, the true protein constituents of a complex, to detect changes in the complex composition, and to localize phosphorylation sites and estimate their respective stoichiometry. The method is based on the combination of fourplex iTRAQ (isobaric tags for relative and absolute quantification) isobaric labeling and protein phosphatase treatment of substrates. It was evaluated on model peptides and proteins and on the complex Ccl1-Kin28-Tfb3 isolated by tandem affinity purification from yeast cells. The two known phosphosites in Kin28 and Tfb3 could be reproducibly shown to be fully modified. The protocol was then applied to the analysis of samples immunopurified from Drosophila melanogaster cells expressing an epitope-tagged form of the insulin receptor substrate homologue Chico. These experiments allowed us to identify 14-3-3epsilon, 14-3-3zeta, and the insulin receptor as specific Chico interactors. In a further experiment, we compared the immunopurified materials obtained from tagged Chico-expressing cells that were either treated with insulin or left unstimulated. This analysis showed that hormone stimulation increases the association of 14-3-3 proteins with Chico and modulates several phosphorylation sites of the bait, some of which are located within predicted recognition motives of 14-3-3 proteins.

Nature, Jan 20, 2013

Complete reference maps or datasets, like the genomic map of an organism, are highly beneficial t... more Complete reference maps or datasets, like the genomic map of an organism, are highly beneficial tools for biological and biomedical research. Attempts to generate such reference datasets for a proteome so far failed to reach complete proteome coverage, with saturation apparent at approximately two thirds of the proteomes tested, even for the most thoroughly characterized proteomes. Here, we used a strategy based on high-throughput peptide synthesis and mass spectrometry to generate a close to complete reference map (97% of the genome-predicted proteins) of the S. cerevisiae proteome. We generated two versions of this mass spectrometric map one supporting discovery-(shotgun) and the other hypothesis-driven (targeted) proteomic measurements. The two versions of the map, therefore, constitute a complete set of proteomic assays to support most studies performed with contemporary proteomic technologies. The reference libraries can be browsed via a web-based repository and associated navigation tools. To demonstrate the utility of the reference libraries we applied them to a protein quantitative trait locus (pQTL) analysis, which requires measurement of the same peptides over a large number of samples with high precision. Protein measurements over a set of 78 S. cerevisiae strains revealed a complex relationship between independent genetic loci, impacting on the levels of related proteins. Our results suggest that selective pressure favors the acquisition of sets of polymorphisms that maintain the stoichiometry of protein complexes and pathways.

Investigative Ophthalmology & Visual Science, 2006

PROTEOMICS, 2012

Multiple reaction monitoring (MRM) has recently become the method of choice for targeted quantita... more Multiple reaction monitoring (MRM) has recently become the method of choice for targeted quantitative measurement of proteins using mass spectrometry. The method, however, is limited in the number of peptides that can be measured in one run. This number can be markedly increased by scheduling the acquisition if the accurate retention time (RT) of each peptide is known. Here we present iRT, an empirically derived dimensionless peptide‐specific value that allows for highly accurate RT prediction. The iRT of a peptide is a fixed number relative to a standard set of reference iRT‐peptides that can be transferred across laboratories and chromatographic systems. We show that iRT facilitates the setup of multiplexed experiments with acquisition windows more than four times smaller compared to in silico RT predictions resulting in improved quantification accuracy. iRTs can be determined by any laboratory and shared transparently. The iRT concept has been implemented in Skyline, the most wid...

Molecular & Cellular Proteomics, 2010

Bioinformatics, 2003

Summary: We present a www server for homology-based gene prediction. The user enters a pair of ev... more Summary: We present a www server for homology-based gene prediction. The user enters a pair of evolutionary related genomic sequences, for example from human and mouse. Our software system uses CHAOS and DIALIGN to calculate an alignment of the input sequences and then searches for conserved splicing signals and start/stop codons around regions of local sequence similarity. This way, candidate exons are identified that are used, in turn, to calculate optimal gene models. The server returns the constructed gene model by email, together with a graphical representation of the underlying genomic alignment. Availability: http://bibiserv.TechFak.Uni-Bielefeld.DE/agenda/ Contact: ltaher@TechFak.Uni-Bielefeld.DE * To whom correspondence should be addressed.

Molecular & Cellular Proteomics, 2019

We established a robust capillary-flow data-independent acquisition MS platform capable of measur... more We established a robust capillary-flow data-independent acquisition MS platform capable of measuring 31 plasma proteomes per day without the need of repeated acquisition of the same sample. We acquired 1508 samples of the DiOGenes study (multicentered, Europa-wide caloric restriction weight loss and maintenance study of overweight and obese, non-diabetic participants). This was achieved using a single analytical column. Comprehensive biological reactions to weight loss and maintenance were observed.

Poster Highlights - Proffered Abstracts

The H2020 project CanPathPro is building and validating a computational predictive modelling plat... more The H2020 project CanPathPro is building and validating a computational predictive modelling platform applied to cancer. To this end, we develop and refine bioinformatic and experimental tools, utilized in generation and evaluation of systems biology modeling predictions. The presented work employs the following technologies and methodologies: biologic systems representing 3 levels of biologic complexity (genetically engineered mouse models—GEMMs—of breast or lung cancer, organoids and cell lines derived thereof); next-generation sequencing and SWATH-based phospho/proteomics; and two large-scale computational mechanistic models. The highly defined biologic systems are used (i) to activate selected oncogenic stimuli that modulate pathway components in a systematic manner; (ii) to characterize the signaling changes occurring during cancer development—thus generating temporally resolved datasets for model training; and (iii) to validate, in vitro and in vivo, the modeling predictions. The mechanistic models, based on ordinary differential equations, enable prediction of phenotypes and drug response in mouse or human. Model parameters are defined using project-derived experimental data, either via parameter estimation strategies or via selection of parameter distributions by a Monte Carlo approach. For simulations, the models are initialized with transcriptome data, either from GEMM-derived cell lines grown under variable conditions or from GEMM-derived neoplastic and tumor tissue, representing lesion progression. The models also integrate the relevant mutations. Results, obtained by iterative rounds of in silico predictions and in vitro validation, include in silico identification (i) of the activation status of oncogenic pathways in GEMMs, organoids, and cell lines; (ii) of the signaling changes induced by the in vitro growth conditions (e.g., growth factor modulation, drug treatments) and by the mutational profile of cell lines/organoids, or by the mutational profile and lesion stage of each GEMM; and (iii) of the drug response of cell lines and GEMMs. In conclusion, this work encompasses a highly integrative systems biology approach generating and validating new hypotheses on cancer pathways signaling and crosstalk, identifying new signal flow, and suggests new ways to interfere with tumor growth. This abstract is also being presented as Poster B49. Citation Format: Julio Banga, Lucien Frappart, Jan Hasenauer, Yann Herault, Jos Jonkers, David Koubi, Bodo Lange, Glenn Terje Lines, Aspasia Plouidou, Oliver Rinner. Predictive modeling, applied to genetically engineered mouse models of breast or lung cancer, provides insights into major oncogenic pathways [abstract]. In: Proceedings of the AACR Special Conference on the Evolving Landscape of Cancer Modeling; 2020 Mar 2-5; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2020;80(11 Suppl):Abstract nr PHB04.

Clinical Research (Excluding Clinical Trials)

Bioinformatics and Systems Biology

Omics technologies are generating complex molecular datasets that are exponentially increasing th... more Omics technologies are generating complex molecular datasets that are exponentially increasing the cancer knowledge base and opening up new therapeutic possibilities. However, current approaches to analysing such data are often confined to statistical and pattern recognition techniques, or at best modelling of a single cellular signalling pathway, rather than the complex cross-talks of pathways that determine cancer onset and progression and response to therapy. New solutions to optimally exploit this wealth of data for basic research, better treatment and stratification of patients, as well as more efficient targeted drug development are required. CanPathPro (www.canpathpro.eu), an EU Horizon 2020 project, is addressing the challenge of predictive modelling of biological data by developing and refining bioinformatic and experimental tools for the evaluation and control of systems biology modelling predictions. Components comprise highly defined mouse and organotypic experimental systems, next-generation sequencing, SWATH-based proteomics and a systems biology computational model for data integration, visualisation and predictive modelling. Within CanPathPro, genetically engineered mouse models are used to follow the temporal changes occurring during cancer development, including the histology of the tumour, the genome and transcriptome using next-generation sequencing and the (phospho-)proteome using SWATH technology. The systems biology computational model is optimised in an iterative fashion through perturbation experiments of tumor-tissue-derived cell lines and organoids, permitting the validation of pathway and parameter information. In this way, CanPathPro takes a unique approach combining classic cancer research with omics data and systems biology tools, to develop and validate a new biotechnological application: a combined systems and experimental biology platform for generating and testing cancer signalling hypotheses in biomedical research. The CanPathPro-generated platform will enable in silico identification of cancer signalling networks critical for tumour development and will allow users to predict activation status of individual pathways, following integration of user (or public) data sets in the pathway models. The innovative approach taken by CanPathPro is set to have broad and significant impact on diverse areas, from cancer research and personalised medicine to drug discovery and development, and ultimately improving outcomes for cancer patients. Citation Format: Christoph Wierling, Yann Herault, Jos Jonkers, Aspasia Ploubidou, Lucien Frappart, Jan Hasenauer, Julio Banga, Oliver Rinner, Valeriya Naumova, David Koubi, Bodo Lange. CanPathPro—development of a platform for predictive pathway modelling using genetically engineered mouse models [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 1296.

Cell, Jan 28, 2016

The ability to reliably and reproducibly measure any protein of the human proteome in any tissue ... more The ability to reliably and reproducibly measure any protein of the human proteome in any tissue or cell type would be transformative for understanding systems-level properties as well as specific pathways in physiology and disease. Here, we describe the generation and verification of a compendium of highly specific assays that enable quantification of 99.7% of the 20,277 annotated human proteins by the widely accessible, sensitive, and robust targeted mass spectrometric method selected reaction monitoring, SRM. This human SRMAtlas provides definitive coordinates that conclusively identify the respective peptide in biological samples. We report data on 166,174 proteotypic peptides providing multiple, independent assays to quantify any human protein and numerous spliced variants, non-synonymous mutations, and post-translational modifications. The data are freely accessible as a resource at http://www.srmatlas.org/, and we demonstrate its utility by examining the network response to i...

Gcb, 2001

Comparative sequence analysis is a powerful approach for detecting functional regions in genomic ... more Comparative sequence analysis is a powerful approach for detecting functional regions in genomic sequences. Herein, we propose a novel method for gene prediction that is based on the DIALIGN sequence alignment program. Local similarities identified by DIALIGN are combined with ...