Publications
Figaschewski, Mirjam; Sürü, Bilge; Tiede, Thorsten; Kohlbacher, Oliver The personalized cancer network explorer (PeCaX) as a visual analytics tool to support molecular tumor boards BMC Bioinformatics, 24 (1), pp. 88, 2023. @article{pmid36890446, title = {The personalized cancer network explorer (PeCaX) as a visual analytics tool to support molecular tumor boards}, author = {Mirjam Figaschewski and Bilge Sürü and Thorsten Tiede and Oliver Kohlbacher}, year = {2023}, date = {2023-03-01}, journal = {BMC Bioinformatics}, volume = {24}, number = {1}, pages = {88}, abstract = {Background: Personalized oncology represents a shift in cancer treatment from conventional methods to target specific therapies where the decisions are made based on the patient specific tumor profile. Selection of the optimal therapy relies on a complex interdisciplinary analysis and interpretation of these variants by experts in molecular tumor boards. With up to hundreds of somatic variants identified in a tumor, this process requires visual analytics tools to guide and accelerate the annotation process. Results: The Personal Cancer Network Explorer (PeCaX) is a visual analytics tool supporting the efficient annotation, navigation, and interpretation of somatic genomic variants through functional annotation, drug target annotation, and visual interpretation within the context of biological networks. Starting with somatic variants in a VCF file, PeCaX enables users to explore these variants through a web-based graphical user interface. The most protruding feature of PeCaX is the combination of clinical variant annotation and gene-drug networks with an interactive visualization. This reduces the time and effort the user needs to invest to get to a treatment suggestion and helps to generate new hypotheses. PeCaX is being provided as a platform-independent containerized software package for local or institution-wide deployment. PeCaX is available for download at https://github.com/KohlbacherLab/PeCaX-docker . Keywords: Clinical decision support; Gene drug interaction networks; Personalized oncology; Precision medicine.}, keywords = {}, pubstate = {published}, tppubtype = {article} } Background: Personalized oncology represents a shift in cancer treatment from conventional methods to target specific therapies where the decisions are made based on the patient specific tumor profile. Selection of the optimal therapy relies on a complex interdisciplinary analysis and interpretation of these variants by experts in molecular tumor boards. With up to hundreds of somatic variants identified in a tumor, this process requires visual analytics tools to guide and accelerate the annotation process. Results: The Personal Cancer Network Explorer (PeCaX) is a visual analytics tool supporting the efficient annotation, navigation, and interpretation of somatic genomic variants through functional annotation, drug target annotation, and visual interpretation within the context of biological networks. Starting with somatic variants in a VCF file, PeCaX enables users to explore these variants through a web-based graphical user interface. The most protruding feature of PeCaX is the combination of clinical variant annotation and gene-drug networks with an interactive visualization. This reduces the time and effort the user needs to invest to get to a treatment suggestion and helps to generate new hypotheses. PeCaX is being provided as a platform-independent containerized software package for local or institution-wide deployment. PeCaX is available for download at https://github.com/KohlbacherLab/PeCaX-docker . Keywords: Clinical decision support; Gene drug interaction networks; Personalized oncology; Precision medicine. |
Mühlenbruch, L; Abou-Kors, T; Dubbelaar, M L; Bichmann, L; Kohlbacher, O; Bens, M; Thomas, J; Ezić, J; Kraus, J M; Kestler, H A; von Witzleben, A; Mytilineos, J; Fürst, D; Engelhardt, D; Doescher, J; Greve, J; Schuler, P J; Theodoraki, M N; Brunner, C; Hoffmann, T K; Rammensee, H G; Walz, J S; Laban, S The HLA ligandome of oropharyngeal squamous cell carcinomas reveals shared tumour-exclusive peptides for semi-personalised vaccination Br J Cancer, pp. 1–11, 2023. @article{pmid36823366, title = {The HLA ligandome of oropharyngeal squamous cell carcinomas reveals shared tumour-exclusive peptides for semi-personalised vaccination}, author = {L Mühlenbruch and T Abou-Kors and M L Dubbelaar and L Bichmann and O Kohlbacher and M Bens and J Thomas and J Ezić and J M Kraus and H A Kestler and A von Witzleben and J Mytilineos and D Fürst and D Engelhardt and J Doescher and J Greve and P J Schuler and M N Theodoraki and C Brunner and T K Hoffmann and H G Rammensee and J S Walz and S Laban}, year = {2023}, date = {2023-02-01}, journal = {Br J Cancer}, pages = {1--11}, abstract = {The immune peptidome of OPSCC has not previously been studied. Cancer-antigen specific vaccination may improve clinical outcome and efficacy of immune checkpoint inhibitors such as PD1/PD-L1 antibodies. 40) using immunoaffinity purification. The cohort included 22 HPV-positive (primarily HPV-16) and 18 HPV-negative samples. A benign reference dataset comprised of the HLA ligandomes of benign haematological and tissue datasets was used to identify tumour-associated antigens. MS analysis led to the identification of naturally HLA-presented peptides in OPSCC tumour tissue. In total, 22,769 peptides from 9485 source proteins were detected on HLA class I. For HLA class II, 15,203 peptides from 4634 source proteins were discovered. By comparative profiling against the benign HLA ligandomic datasets, 29 OPSCC-associated HLA class I ligands covering 11 different HLA allotypes and nine HLA class II ligands were selected to create a peptide warehouse. Tumour-associated peptides are HLA-presented on the cell surfaces of OPSCCs. The established warehouse of OPSCC-associated peptides can be used for downstream immunogenicity testing and peptide-based immunotherapy in (semi)personalised strategies.}, keywords = {}, pubstate = {published}, tppubtype = {article} } The immune peptidome of OPSCC has not previously been studied. Cancer-antigen specific vaccination may improve clinical outcome and efficacy of immune checkpoint inhibitors such as PD1/PD-L1 antibodies. 40) using immunoaffinity purification. The cohort included 22 HPV-positive (primarily HPV-16) and 18 HPV-negative samples. A benign reference dataset comprised of the HLA ligandomes of benign haematological and tissue datasets was used to identify tumour-associated antigens. MS analysis led to the identification of naturally HLA-presented peptides in OPSCC tumour tissue. In total, 22,769 peptides from 9485 source proteins were detected on HLA class I. For HLA class II, 15,203 peptides from 4634 source proteins were discovered. By comparative profiling against the benign HLA ligandomic datasets, 29 OPSCC-associated HLA class I ligands covering 11 different HLA allotypes and nine HLA class II ligands were selected to create a peptide warehouse. Tumour-associated peptides are HLA-presented on the cell surfaces of OPSCCs. The established warehouse of OPSCC-associated peptides can be used for downstream immunogenicity testing and peptide-based immunotherapy in (semi)personalised strategies. |
Renovanz, M; Kurz, S C; Rieger, J; Walter, B; Becker, H; Hille, H; Bombach, P; Rieger, D; Grosse, L; usser, L; Skardelly, M; Merk, D J; Paulsen, F; Hoffmann, E; Gani, C; Neumann, M; Beschorner, R; ß, O; Roggia, C; Schroeder, C; Ossowski, S; Armeanu-Ebinger, S; Gschwind, A; Biskup, S; Schulze, M; Fend, F; Singer, S; Zender, L; Lengerke, C; Brucker, S Y; Engler, T; Forschner, A; Stenzl, A; Kohlbacher, O; Nahnsen, S; Gabernet, G; Fillinger, S; Bender, B; Ernemann, U; ner, Ö; Beha, J; Malek, H S; ller, Y; Ruhm, K; Tatagiba, M; Schittenhelm, J; Bitzer, M; Malek, N; Zips, D; Tabatabai, G Clinical outcome of biomarker-guided therapies in adult patients with tumors of the nervous system Neurooncol Adv, 5 (1), pp. vdad012, 2023. @article{pmid36915613, title = {Clinical outcome of biomarker-guided therapies in adult patients with tumors of the nervous system}, author = {M Renovanz and S C Kurz and J Rieger and B Walter and H Becker and H Hille and P Bombach and D Rieger and L Grosse and L usser and M Skardelly and D J Merk and F Paulsen and E Hoffmann and C Gani and M Neumann and R Beschorner and O ß and C Roggia and C Schroeder and S Ossowski and S Armeanu-Ebinger and A Gschwind and S Biskup and M Schulze and F Fend and S Singer and L Zender and C Lengerke and S Y Brucker and T Engler and A Forschner and A Stenzl and O Kohlbacher and S Nahnsen and G Gabernet and S Fillinger and B Bender and U Ernemann and Ö ner and J Beha and H S Malek and Y ller and K Ruhm and M Tatagiba and J Schittenhelm and M Bitzer and N Malek and D Zips and G Tabatabai}, year = {2023}, date = {2023-01-01}, journal = {Neurooncol Adv}, volume = {5}, number = {1}, pages = {vdad012}, abstract = {The clinical utility of molecular profiling and targeted therapies for neuro-oncology patients outside of clinical trials is not established. We aimed at investigating feasibility and clinical utility of molecular profiling and targeted therapy in adult patients with advanced tumors in the nervous system within a prospective observational study. molecular tumor board (MTB)@ZPM (NCT03503149) is a prospective observational precision medicine study for patients with advanced tumors. After inclusion of patients, we performed comprehensive molecular profiling, formulated ranked biomarker-guided therapy recommendations based on consensus by the MTB, and collected prospective clinical outcome data. 1.3 in 31.3% of patients. Our study supports the clinical utility of biomarker-guided therapies for neuro-oncology patients and indicates clinical benefit in a subset of patients. Our data might inform future clinical trials, translational studies, and even clinical care.}, keywords = {}, pubstate = {published}, tppubtype = {article} } The clinical utility of molecular profiling and targeted therapies for neuro-oncology patients outside of clinical trials is not established. We aimed at investigating feasibility and clinical utility of molecular profiling and targeted therapy in adult patients with advanced tumors in the nervous system within a prospective observational study. molecular tumor board (MTB)@ZPM (NCT03503149) is a prospective observational precision medicine study for patients with advanced tumors. After inclusion of patients, we performed comprehensive molecular profiling, formulated ranked biomarker-guided therapy recommendations based on consensus by the MTB, and collected prospective clinical outcome data. 1.3 in 31.3% of patients. Our study supports the clinical utility of biomarker-guided therapies for neuro-oncology patients and indicates clinical benefit in a subset of patients. Our data might inform future clinical trials, translational studies, and even clinical care. |
Jeong, K; Babović, M; Gorshkov, V; Kim, J; Jensen, O N; Kohlbacher, O FLASHIda enables intelligent data acquisition for top-down proteomics to boost proteoform identification counts Nat Commun, 13 (1), pp. 4407, 2022. @article{pmid35906205, title = {FLASHIda enables intelligent data acquisition for top-down proteomics to boost proteoform identification counts}, author = {K Jeong and M Babović and V Gorshkov and J Kim and O N Jensen and O Kohlbacher}, doi = {10.1038/s41467-022-31922-z}, year = {2022}, date = {2022-07-01}, journal = {Nat Commun}, volume = {13}, number = {1}, pages = {4407}, abstract = {The detailed analysis and structural characterization of proteoforms by top-down proteomics (TDP) has gained a lot of interest in biomedical research. Data-dependent acquisition (DDA) of intact proteins is non-trivial due to the diversity and complexity of proteoforms. Dedicated acquisition methods thus have the potential to greatly improve TDP. Here, we present FLASHIda, an intelligent online data acquisition algorithm for TDP that ensures the real-time selection of high-quality precursors of diverse proteoforms. FLASHIda combines fast charge deconvolution algorithms and machine learning-based quality assessment for optimal precursor selection. In an analysis of E. coli lysate, FLASHIda increases the number of unique proteoform level identifications from 800 to 1500 or generates a near-identical number of identifications in one third of the instrument time when compared to standard DDA mode. Furthermore, FLASHIda enables sensitive mapping of post-translational modifications and detection of chemical adducts. As a software extension module to the instrument, FLASHIda can be readily adopted for TDP studies of complex samples to enhance proteoform identification rates.}, keywords = {}, pubstate = {published}, tppubtype = {article} } The detailed analysis and structural characterization of proteoforms by top-down proteomics (TDP) has gained a lot of interest in biomedical research. Data-dependent acquisition (DDA) of intact proteins is non-trivial due to the diversity and complexity of proteoforms. Dedicated acquisition methods thus have the potential to greatly improve TDP. Here, we present FLASHIda, an intelligent online data acquisition algorithm for TDP that ensures the real-time selection of high-quality precursors of diverse proteoforms. FLASHIda combines fast charge deconvolution algorithms and machine learning-based quality assessment for optimal precursor selection. In an analysis of E. coli lysate, FLASHIda increases the number of unique proteoform level identifications from 800 to 1500 or generates a near-identical number of identifications in one third of the instrument time when compared to standard DDA mode. Furthermore, FLASHIda enables sensitive mapping of post-translational modifications and detection of chemical adducts. As a software extension module to the instrument, FLASHIda can be readily adopted for TDP studies of complex samples to enhance proteoform identification rates. |
Childebayeva, A; Rohrlach, A B; Barquera, R; Rivollat, M; Aron, F; Szolek, A; Kohlbacher, O; Nicklisch, N; Alt, K W; Gronenborn, D; Meller, H; Friederich, S; Prüfer, K; Deguilloux, M F; Krause, J; Haak, W Population Genetics and Signatures of Selection in Early Neolithic European Farmers Mol Biol Evol, 2022. (BibTeX) @article{pmid35578825, title = {Population Genetics and Signatures of Selection in Early Neolithic European Farmers}, author = {A Childebayeva and A B Rohrlach and R Barquera and M Rivollat and F Aron and A Szolek and O Kohlbacher and N Nicklisch and K W Alt and D Gronenborn and H Meller and S Friederich and K Prüfer and M F Deguilloux and J Krause and W Haak}, year = {2022}, date = {2022-05-01}, journal = {Mol Biol Evol}, keywords = {}, pubstate = {published}, tppubtype = {article} } |
Prokosch, H U; Bahls, T; Bialke, M; Eils, J; Fegeler, C; Gruendner, J; Haarbrandt, B; Hampf, C; Hoffmann, W; Hund, H; Kampf, M; Kapsner, L A; Kasprzak, P; Kohlbacher, O; Krefting, D; Mang, J M; Marschollek, M; Mate, S; Müller, A; Prasser, F; Sass, J; Semler, S; Stenzhorn, H; Thun, S; Zenker, S; Eils, R The COVID-19 Data Exchange Platform of the German University Medicine Stud Health Technol Inform, 294 , pp. 674–678, 2022. (BibTeX) @article{pmid35612174, title = {The COVID-19 Data Exchange Platform of the German University Medicine}, author = {H U Prokosch and T Bahls and M Bialke and J Eils and C Fegeler and J Gruendner and B Haarbrandt and C Hampf and W Hoffmann and H Hund and M Kampf and L A Kapsner and P Kasprzak and O Kohlbacher and D Krefting and J M Mang and M Marschollek and S Mate and A Müller and F Prasser and J Sass and S Semler and H Stenzhorn and S Thun and S Zenker and R Eils}, year = {2022}, date = {2022-05-01}, journal = {Stud Health Technol Inform}, volume = {294}, pages = {674--678}, keywords = {}, pubstate = {published}, tppubtype = {article} } |
Elhabashy, Hadeer; Merino, Felipe; Alva, Vikram; Kohlbacher, Oliver; Lupas, Andrei N Exploring protein-protein interactions at the proteome level Structure, 2022. (BibTeX) @article{Elhabashy2022-iw, title = {Exploring protein-protein interactions at the proteome level}, author = {Hadeer Elhabashy and Felipe Merino and Vikram Alva and Oliver Kohlbacher and Andrei N Lupas}, year = {2022}, date = {2022-01-01}, journal = {Structure}, publisher = {Elsevier BV}, keywords = {}, pubstate = {published}, tppubtype = {article} } |
Winkler, Sebastian; Winkler, Ivana; Figaschewski, Mirjam; Tiede, Thorsten; Nordheim, Alfred; Kohlbacher, Oliver De novo identification of maximally deregulated subnetworks based on multi-omics data with DeRegNet BMC Bioinformatics, 23 (1), pp. 139, 2022. @article{Winkler2022-ca, title = {De novo identification of maximally deregulated subnetworks based on multi-omics data with DeRegNet}, author = {Sebastian Winkler and Ivana Winkler and Mirjam Figaschewski and Thorsten Tiede and Alfred Nordheim and Oliver Kohlbacher}, year = {2022}, date = {2022-01-01}, journal = {BMC Bioinformatics}, volume = {23}, number = {1}, pages = {139}, publisher = {Springer Science and Business Media LLC}, abstract = {BACKGROUND: With a growing amount of (multi-)omics data being available, the extraction of knowledge from these datasets is still a difficult problem. Classical enrichment-style analyses require predefined pathways or gene sets that are tested for significant deregulation to assess whether the pathway is functionally involved in the biological process under study. De novo identification of these pathways can reduce the bias inherent in predefined pathways or gene sets. At the same time, the definition and efficient identification of these pathways de novo from large biological networks is a challenging problem. RESULTS: We present a novel algorithm, DeRegNet, for the identification of maximally deregulated subnetworks on directed graphs based on deregulation scores derived from (multi-)omics data. DeRegNet can be interpreted as maximum likelihood estimation given a certain probabilistic model for de-novo subgraph identification. We use fractional integer programming to solve the resulting combinatorial optimization problem. We can show that the approach outperforms related algorithms on simulated data with known ground truths. On a publicly available liver cancer dataset we can show that DeRegNet can identify biologically meaningful subgraphs suitable for patient stratification. DeRegNet can also be used to find explicitly multi-omics subgraphs which we demonstrate by presenting subgraphs with consistent methylation-transcription patterns. DeRegNet is freely available as open-source software. CONCLUSION: The proposed algorithmic framework and its available implementation can serve as a valuable heuristic hypothesis generation tool contextualizing omics data within biomolecular networks.}, keywords = {}, pubstate = {published}, tppubtype = {article} } BACKGROUND: With a growing amount of (multi-)omics data being available, the extraction of knowledge from these datasets is still a difficult problem. Classical enrichment-style analyses require predefined pathways or gene sets that are tested for significant deregulation to assess whether the pathway is functionally involved in the biological process under study. De novo identification of these pathways can reduce the bias inherent in predefined pathways or gene sets. At the same time, the definition and efficient identification of these pathways de novo from large biological networks is a challenging problem. RESULTS: We present a novel algorithm, DeRegNet, for the identification of maximally deregulated subnetworks on directed graphs based on deregulation scores derived from (multi-)omics data. DeRegNet can be interpreted as maximum likelihood estimation given a certain probabilistic model for de-novo subgraph identification. We use fractional integer programming to solve the resulting combinatorial optimization problem. We can show that the approach outperforms related algorithms on simulated data with known ground truths. On a publicly available liver cancer dataset we can show that DeRegNet can identify biologically meaningful subgraphs suitable for patient stratification. DeRegNet can also be used to find explicitly multi-omics subgraphs which we demonstrate by presenting subgraphs with consistent methylation-transcription patterns. DeRegNet is freely available as open-source software. CONCLUSION: The proposed algorithmic framework and its available implementation can serve as a valuable heuristic hypothesis generation tool contextualizing omics data within biomolecular networks. |
Jeong, Kyowon; Kim, Jihyung; Kohlbacher, Oliver Mass deconvolution of top-down mass spectrometry datasets by FLASHDeconv Methods Mol. Biol., 2500 , pp. 145–157, 2022. @article{Jeong2022-ib, title = {Mass deconvolution of top-down mass spectrometry datasets by FLASHDeconv}, author = {Kyowon Jeong and Jihyung Kim and Oliver Kohlbacher}, year = {2022}, date = {2022-01-01}, journal = {Methods Mol. Biol.}, volume = {2500}, pages = {145--157}, abstract = {Mass deconvolution, the determination of proteoform precursor and fragment masses, is crucial for top-down proteomics data analysis. Here we describe the detailed procedure to run FLASHDeconv, an ultrafast, high-quality mass deconvolution tool. Both spectrum- and feature-level deconvolution results are obtainable in various output formats by FLASHDeconv. FLASHDeconv is runnable in different environments such as the command line and OpenMS workflows.}, keywords = {}, pubstate = {published}, tppubtype = {article} } Mass deconvolution, the determination of proteoform precursor and fragment masses, is crucial for top-down proteomics data analysis. Here we describe the detailed procedure to run FLASHDeconv, an ultrafast, high-quality mass deconvolution tool. Both spectrum- and feature-level deconvolution results are obtainable in various output formats by FLASHDeconv. FLASHDeconv is runnable in different environments such as the command line and OpenMS workflows. |
Blum, Corinna; Baur, David; Achauer, Lars-Christian; Berens, Philipp; Biergans, Stephanie; Erb, Michael; Hömberg, Volker; Huang, Ziwei; Kohlbacher, Oliver; Liepert, Joachim; Lindig, Tobias; Lohmann, Gabriele; Macke, Jakob H; Römhild, Jörg; Rösinger-Hein, Christine; Zrenner, Brigitte; Ziemann, Ulf Personalized neurorehabilitative precision medicine: from data to therapies (MWKNeuroReha) - a multi-centre prospective observational clinical trial to predict long-term outcome of patients with acute motor stroke BMC Neurol, 22 (1), pp. 238, 2022. @article{Blum2022-zj, title = {Personalized neurorehabilitative precision medicine: from data to therapies (MWKNeuroReha) - a multi-centre prospective observational clinical trial to predict long-term outcome of patients with acute motor stroke}, author = {Corinna Blum and David Baur and Lars-Christian Achauer and Philipp Berens and Stephanie Biergans and Michael Erb and Volker Hömberg and Ziwei Huang and Oliver Kohlbacher and Joachim Liepert and Tobias Lindig and Gabriele Lohmann and Jakob H Macke and Jörg Römhild and Christine Rösinger-Hein and Brigitte Zrenner and Ulf Ziemann}, year = {2022}, date = {2022-01-01}, journal = {BMC Neurol}, volume = {22}, number = {1}, pages = {238}, address = {England}, abstract = {BACKGROUND: Stroke is one of the most frequent diseases, and half of the stroke survivors are left with permanent impairment. Prediction of individual outcome is still difficult. Many but not all patients with stroke improve by approximately 1.7 times the initial impairment, that has been termed proportional recovery rule. The present study aims at identifying factors predicting motor outcome after stroke more accurately than before, and observe associations of rehabilitation treatment with outcome. METHODS: The study is designed as a multi-centre prospective clinical observational trial. An extensive primary data set of clinical, neuroimaging, electrophysiological, and laboratory data will be collected within 96 h of stroke onset from patients with relevant upper extremity deficit, as indexed by a Fugl-Meyer-Upper Extremity (FM-UE) score $łeq$ 50. At least 200 patients will be recruited. Clinical scores will include the FM-UE score (range 0-66, unimpaired function is indicated by a score of 66), Action Research Arm Test, modified Rankin Scale, Barthel Index and Stroke-Specific Quality of Life Scale. Follow-up clinical scores and applied types and amount of rehabilitation treatment will be documented in the rehabilitation hospitals. Final follow-up clinical scoring will be performed 90 days after the stroke event. The primary endpoint is the change in FM-UE defined as 90 days FM-UE minus initial FM-UE, divided by initial FM-UE impairment. Changes in the other clinical scores serve as secondary endpoints. Machine learning methods will be employed to analyze the data and predict primary and secondary endpoints based on the primary data set and the different rehabilitation treatments. DISCUSSION: If successful, outcome and relation to rehabilitation treatment in patients with acute motor stroke will be predictable more reliably than currently possible, leading to personalized neurorehabilitation. An important regulatory aspect of this trial is the first-time implementation of systematic patient data transfer between emergency and rehabilitation hospitals, which are divided institutions in Germany. TRIAL REGISTRATION: This study was registered at ClinicalTrials.gov ( NCT04688970 ) on 30 December 2020.}, keywords = {}, pubstate = {published}, tppubtype = {article} } BACKGROUND: Stroke is one of the most frequent diseases, and half of the stroke survivors are left with permanent impairment. Prediction of individual outcome is still difficult. Many but not all patients with stroke improve by approximately 1.7 times the initial impairment, that has been termed proportional recovery rule. The present study aims at identifying factors predicting motor outcome after stroke more accurately than before, and observe associations of rehabilitation treatment with outcome. METHODS: The study is designed as a multi-centre prospective clinical observational trial. An extensive primary data set of clinical, neuroimaging, electrophysiological, and laboratory data will be collected within 96 h of stroke onset from patients with relevant upper extremity deficit, as indexed by a Fugl-Meyer-Upper Extremity (FM-UE) score $łeq$ 50. At least 200 patients will be recruited. Clinical scores will include the FM-UE score (range 0-66, unimpaired function is indicated by a score of 66), Action Research Arm Test, modified Rankin Scale, Barthel Index and Stroke-Specific Quality of Life Scale. Follow-up clinical scores and applied types and amount of rehabilitation treatment will be documented in the rehabilitation hospitals. Final follow-up clinical scoring will be performed 90 days after the stroke event. The primary endpoint is the change in FM-UE defined as 90 days FM-UE minus initial FM-UE, divided by initial FM-UE impairment. Changes in the other clinical scores serve as secondary endpoints. Machine learning methods will be employed to analyze the data and predict primary and secondary endpoints based on the primary data set and the different rehabilitation treatments. DISCUSSION: If successful, outcome and relation to rehabilitation treatment in patients with acute motor stroke will be predictable more reliably than currently possible, leading to personalized neurorehabilitation. An important regulatory aspect of this trial is the first-time implementation of systematic patient data transfer between emergency and rehabilitation hospitals, which are divided institutions in Germany. TRIAL REGISTRATION: This study was registered at ClinicalTrials.gov ( NCT04688970 ) on 30 December 2020. |
Bruns, Andreas; Benet-Pages, Anna; Eufinger, Jan; Graessner, Holm; Kohlbacher, Oliver; Molnár-Gábor, Fruzsina; Parker, Simon; Schickhardt, Christoph; Stegle, Oliver; Winkler, Eva Consent Modules for Data Sharing via the German Human Genome-Phenome Archive (GHGA) 2022, (Funding: The GHGA consortium is funded by the German Research Foundation (DFG) within the framework of the National Research Data Infrastructure (NFDI).). @misc{bruns_andreas_2022_6828131, title = {Consent Modules for Data Sharing via the German Human Genome-Phenome Archive (GHGA)}, author = {Andreas Bruns and Anna Benet-Pages and Jan Eufinger and Holm Graessner and Oliver Kohlbacher and Fruzsina Molnár-Gábor and Simon Parker and Christoph Schickhardt and Oliver Stegle and Eva Winkler}, url = {https://doi.org/10.5281/zenodo.6828131}, doi = {10.5281/zenodo.6828131}, year = {2022}, date = {2022-01-01}, publisher = {Zenodo}, note = {Funding: The GHGA consortium is funded by the German Research Foundation (DFG) within the framework of the National Research Data Infrastructure (NFDI).}, keywords = {}, pubstate = {published}, tppubtype = {misc} } |
Fluck, Juliane; Pigeot, Iris; Stegle, Oliver; Kohlbacher, Oliver; Förstner, Konrad; McHardy, Alice; Sure-Vetter, York Rückmeldung der lebenswissenschaftlichen Nationalen Forschungsdateninfrastrukturen NFDI4Health, GHGA und NFDI4Microbiota zu den Positionen und Empfehlungen des Wissenschaftsrats – Digitalisierung und Datennutzung für Gesundheitsforschung und Versorgung 2022, (An die Vorsitzende des Wissenschaftsrats, Frau Professorin Dr. Dorothea Wagner, und alle Mitwirkenden der WR-Veröffentlichung 'Digitalisierung und Datennutzung für Gesundheitsforschung und Versorgung' : Rückmeldung der lebenswissenschaftlichen Nationalen Forschungsdateninfrastrukturen NFDI4Health, GHGA und NFDI4Microbiota zu den Positionen und Empfehlungen des Wissenschaftsrats). @misc{juliane_fluck_2022_6973597, title = {Rückmeldung der lebenswissenschaftlichen Nationalen Forschungsdateninfrastrukturen NFDI4Health, GHGA und NFDI4Microbiota zu den Positionen und Empfehlungen des Wissenschaftsrats – Digitalisierung und Datennutzung für Gesundheitsforschung und Versorgung}, author = {Juliane Fluck and Iris Pigeot and Oliver Stegle and Oliver Kohlbacher and Konrad Förstner and Alice McHardy and York Sure-Vetter}, url = {https://doi.org/10.4126/FRL01-006434341}, doi = {10.4126/FRL01-006434341}, year = {2022}, date = {2022-01-01}, publisher = {Zenodo}, note = {An die Vorsitzende des Wissenschaftsrats, Frau Professorin Dr. Dorothea Wagner, und alle Mitwirkenden der WR-Veröffentlichung 'Digitalisierung und Datennutzung für Gesundheitsforschung und Versorgung' : Rückmeldung der lebenswissenschaftlichen Nationalen Forschungsdateninfrastrukturen NFDI4Health, GHGA und NFDI4Microbiota zu den Positionen und Empfehlungen des Wissenschaftsrats}, keywords = {}, pubstate = {published}, tppubtype = {misc} } |
Buchert, Rebecca; Schenk, Elisabeth; Hentrich, Thomas; Weber, Nico; Rall, Katharina; Sturm, Marc; Kohlbacher, Oliver; Koch, André; Riess, Olaf; Brucker, Sara Y; Schulze-Hentrich, Julia M Genome Sequencing and Transcriptome Profiling in Twins Discordant for Mayer-Rokitansky-Küster-Hauser Syndrome Journal of Clinical Medicine, 11 (19), 2022, ISSN: 2077-0383. @article{jcm11195598, title = {Genome Sequencing and Transcriptome Profiling in Twins Discordant for Mayer-Rokitansky-Küster-Hauser Syndrome}, author = {Rebecca Buchert and Elisabeth Schenk and Thomas Hentrich and Nico Weber and Katharina Rall and Marc Sturm and Oliver Kohlbacher and André Koch and Olaf Riess and Sara Y Brucker and Julia M Schulze-Hentrich}, url = {https://www.mdpi.com/2077-0383/11/19/5598}, doi = {10.3390/jcm11195598}, issn = {2077-0383}, year = {2022}, date = {2022-01-01}, journal = {Journal of Clinical Medicine}, volume = {11}, number = {19}, abstract = {To identify potential genetic causes for Mayer-Rokitansky-Küster-Hauser syndrome (MRKH), we analyzed blood and rudimentary uterine tissue of 5 MRKH discordant monozygotic twin pairs. Assuming that a variant solely identified in the affected twin or affected tissue could cause the phenotype, we identified a mosaic variant in ACTR3B with high allele frequency in the affected tissue, low allele frequency in the blood of the affected twin, and almost absent in blood of the unaffected twin. Focusing on MRKH candidate genes, we detected a pathogenic variant in GREB1L in one twin pair and their unaffected mother showing a reduced phenotypic penetrance. Furthermore, two variants of unknown clinical significance in PAX8 and WNT9B were identified. In addition, we conducted transcriptome analysis of affected tissue and observed perturbations largely similar to those in sporadic cases. These shared transcriptional changes were enriched for terms associated with estrogen and its receptors pointing at a role of estrogen in MRKH pathology. Our genome sequencing approach of blood and uterine tissue of discordant twins is the most extensive study performed on twins discordant for MRKH so far. As no clear pathogenic differences were detected, research to evaluate other regulatory layers are required to better understand the complex etiology of MRKH.}, keywords = {}, pubstate = {published}, tppubtype = {article} } To identify potential genetic causes for Mayer-Rokitansky-Küster-Hauser syndrome (MRKH), we analyzed blood and rudimentary uterine tissue of 5 MRKH discordant monozygotic twin pairs. Assuming that a variant solely identified in the affected twin or affected tissue could cause the phenotype, we identified a mosaic variant in ACTR3B with high allele frequency in the affected tissue, low allele frequency in the blood of the affected twin, and almost absent in blood of the unaffected twin. Focusing on MRKH candidate genes, we detected a pathogenic variant in GREB1L in one twin pair and their unaffected mother showing a reduced phenotypic penetrance. Furthermore, two variants of unknown clinical significance in PAX8 and WNT9B were identified. In addition, we conducted transcriptome analysis of affected tissue and observed perturbations largely similar to those in sporadic cases. These shared transcriptional changes were enriched for terms associated with estrogen and its receptors pointing at a role of estrogen in MRKH pathology. Our genome sequencing approach of blood and uterine tissue of discordant twins is the most extensive study performed on twins discordant for MRKH so far. As no clear pathogenic differences were detected, research to evaluate other regulatory layers are required to better understand the complex etiology of MRKH. |
Singh, J; Elhabashy, H; Muthukottiappan, P; Stepath, M; Eisenacher, M; Kohlbacher, O; Gieselmann, V; Winter, D Cross-linking of the endolysosomal system reveals potential flotillin structures and cargo Nat Commun, 13 (1), pp. 6212, 2022. (BibTeX) @article{pmid36266287, title = {Cross-linking of the endolysosomal system reveals potential flotillin structures and cargo}, author = {J Singh and H Elhabashy and P Muthukottiappan and M Stepath and M Eisenacher and O Kohlbacher and V Gieselmann and D Winter}, year = {2022}, date = {2022-01-01}, journal = {Nat Commun}, volume = {13}, number = {1}, pages = {6212}, keywords = {}, pubstate = {published}, tppubtype = {article} } |
Akgün, Mete; Pfeifer, Nico; Kohlbacher, Oliver Efficient privacy-preserving whole-genome variant queries Bioinform., 38 (8), pp. 2202–2210, 2022. @article{DBLP:journals/bioinformatics/AkgunPK22, title = {Efficient privacy-preserving whole-genome variant queries}, author = {Mete Akgün and Nico Pfeifer and Oliver Kohlbacher}, url = {https://doi.org/10.1093/bioinformatics/btac070}, doi = {10.1093/bioinformatics/btac070}, year = {2022}, date = {2022-01-01}, journal = {Bioinform.}, volume = {38}, number = {8}, pages = {2202--2210}, keywords = {}, pubstate = {published}, tppubtype = {article} } |
-, Hans; Bahls, Thomas; Bialke, Martin; ü, J; Fegeler, Christian; ü, Julian Gr; Haarbrandt, Birger; Hampf, Christopher; Hoffmann, Wolfgang; Hund, Hauke; Kampf, Marvin O; Kapsner, Lorenz A; Kasprzak, Piotr; Kohlbacher, Oliver; Krefting, Dagmar; Mang, Jonathan; Marschollek, Michael; Mate, Sebastian; ü, Armin M; Prasser, Fabian; Sass, Julian; Semler, Sebastian C; Stenzhorn, Holger; Thun, Sylvia; Zenker, Sven; Eils, Roland The COVID-19 Data Exchange Platform of the German University Medicine é, Brigitte S; Weber, Patrick; Dhombres, Ferdinand; Grouin, Cyril; -, Jan; Pelayo, Sylvia; Pinna, Andrea; Rance, Bastien; Sacchi, Lucia; Ugon, Adrien; Benis, Arriel; Gallos, Parisis (Ed.): Challenges of Trustable AI and Added-Value on Health - Proceedings of MIE 2022, Medical Informatics Europe, Nice, France, May 27-30, 2022, pp. 674–678, IOS Press, 2022. @inproceedings{DBLP:conf/mie/ProkoschBBEFGHH22, title = {The COVID-19 Data Exchange Platform of the German University Medicine}, author = {Hans - and Thomas Bahls and Martin Bialke and J ü and Christian Fegeler and Julian Gr ü and Birger Haarbrandt and Christopher Hampf and Wolfgang Hoffmann and Hauke Hund and Marvin O Kampf and Lorenz A Kapsner and Piotr Kasprzak and Oliver Kohlbacher and Dagmar Krefting and Jonathan Mang and Michael Marschollek and Sebastian Mate and Armin M ü and Fabian Prasser and Julian Sass and Sebastian C Semler and Holger Stenzhorn and Sylvia Thun and Sven Zenker and Roland Eils}, editor = {Brigitte S é and Patrick Weber and Ferdinand Dhombres and Cyril Grouin and Jan - and Sylvia Pelayo and Andrea Pinna and Bastien Rance and Lucia Sacchi and Adrien Ugon and Arriel Benis and Parisis Gallos}, url = {https://doi.org/10.3233/SHTI220554}, doi = {10.3233/SHTI220554}, year = {2022}, date = {2022-01-01}, booktitle = {Challenges of Trustable AI and Added-Value on Health - Proceedings of MIE 2022, Medical Informatics Europe, Nice, France, May 27-30, 2022}, volume = {294}, pages = {674--678}, publisher = {IOS Press}, series = {Studies in Health Technology and Informatics}, keywords = {}, pubstate = {published}, tppubtype = {inproceedings} } |
de Herr, Marius Arruda Botelho; Graf, Michael; Placzek, Peter; König, Florian; Bötte, Felix; Stickel, Tyra; Hieber, David; Zimmermann, Lukas; Slupina, Michael; Mohr, Christopher; Biergans, Stephanie; Akgün, Mete; Pfeifer, Nico; Kohlbacher, Oliver Bringing the Algorithms to the Data - Secure Distributed Medical Analytics using the Personal Health Train (PHT-meDIC) CoRR, abs/2212.03481 , 2022. @article{DBLP:journals/corr/abs-2212-03481, title = {Bringing the Algorithms to the Data - Secure Distributed Medical Analytics using the Personal Health Train (PHT-meDIC)}, author = {Marius Arruda Botelho de Herr and Michael Graf and Peter Placzek and Florian König and Felix Bötte and Tyra Stickel and David Hieber and Lukas Zimmermann and Michael Slupina and Christopher Mohr and Stephanie Biergans and Mete Akgün and Nico Pfeifer and Oliver Kohlbacher}, url = {https://doi.org/10.48550/arXiv.2212.03481}, doi = {10.48550/arXiv.2212.03481}, year = {2022}, date = {2022-01-01}, journal = {CoRR}, volume = {abs/2212.03481}, keywords = {}, pubstate = {published}, tppubtype = {article} } |
Jan Eufinger Jan Korbel, Eva Winkler Oliver Kohlbacher ; Stegle, Oliver Genomdaten FAIR und sicher teilen: Das Deutsche Humangenom-Phänom Archiv (GHGA) als Baustein der Nationalen Forschungsdateninfrastruktur Bausteine Forschungsdatenmanagement, 2 , pp. 86-87, 2021. @article{EufingerFDM2021, title = {Genomdaten FAIR und sicher teilen: Das Deutsche Humangenom-Phänom Archiv (GHGA) als Baustein der Nationalen Forschungsdateninfrastruktur}, author = {Jan Eufinger, Jan Korbel, Eva Winkler, Oliver Kohlbacher, and Oliver Stegle}, url = {https://bausteine-fdm.de/article/view/8349}, doi = {https://doi.org/10.17192/bfdm.2021.2.8349}, year = {2021}, date = {2021-07-28}, journal = {Bausteine Forschungsdatenmanagement}, volume = {2}, pages = {86-87}, keywords = {}, pubstate = {published}, tppubtype = {article} } |
Leon Bichmann Shubham Gupta, George Rosenberger Leon Kuchenbecker Timo Sachsenberg Phil Ewels Oliver Alka Julianus Pfeuffer Oliver Kohlbacher ; Röst, Hannes DIAproteomics: A Multifunctional Data Analysis Pipeline for Data-Independent Acquisition Proteomics and Peptidomics J. Proteome Res., 2021. @article{DIAProt2021, title = {DIAproteomics: A Multifunctional Data Analysis Pipeline for Data-Independent Acquisition Proteomics and Peptidomics}, author = {Leon Bichmann, Shubham Gupta, George Rosenberger, Leon Kuchenbecker, Timo Sachsenberg, Phil Ewels, Oliver Alka, Julianus Pfeuffer, Oliver Kohlbacher, and Hannes Röst}, url = {https://pubs.acs.org/doi/10.1021/acs.jproteome.1c00123}, doi = {10.1021/acs.jproteome.1c00123}, year = {2021}, date = {2021-06-21}, journal = {J. Proteome Res.}, abstract = {Data-independent acquisition (DIA) is becoming a leading analysis method in biomedical mass spectrometry. The main advantages include greater reproducibility and sensitivity and a greater dynamic range compared with data-dependent acquisition (DDA). However, the data analysis is complex and often requires expert knowledge when dealing with large-scale data sets. Here we present DIAproteomics, a multifunctional, automated, high-throughput pipeline implemented in the Nextflow workflow management system that allows one to easily process proteomics and peptidomics DIA data sets on diverse compute infrastructures. The central components are well-established tools such as the OpenSwathWorkflow for the DIA spectral library search and PyProphet for the false discovery rate assessment. In addition, it provides options to generate spectral libraries from existing DDA data and to carry out the retention time and chromatogram alignment. The output includes annotated tables and diagnostic visualizations from the statistical postprocessing and computation of fold-changes across pairwise conditions, predefined in an experimental design. DIAproteomics is well documented open-source software and is available under a permissive license to the scientific community at https://www.openms.de/diaproteomics/.}, keywords = {}, pubstate = {published}, tppubtype = {article} } Data-independent acquisition (DIA) is becoming a leading analysis method in biomedical mass spectrometry. The main advantages include greater reproducibility and sensitivity and a greater dynamic range compared with data-dependent acquisition (DDA). However, the data analysis is complex and often requires expert knowledge when dealing with large-scale data sets. Here we present DIAproteomics, a multifunctional, automated, high-throughput pipeline implemented in the Nextflow workflow management system that allows one to easily process proteomics and peptidomics DIA data sets on diverse compute infrastructures. The central components are well-established tools such as the OpenSwathWorkflow for the DIA spectral library search and PyProphet for the false discovery rate assessment. In addition, it provides options to generate spectral libraries from existing DDA data and to carry out the retention time and chromatogram alignment. The output includes annotated tables and diagnostic visualizations from the statistical postprocessing and computation of fold-changes across pairwise conditions, predefined in an experimental design. DIAproteomics is well documented open-source software and is available under a permissive license to the scientific community at https://www.openms.de/diaproteomics/. |
Immel, A; Key, F M; Szolek, A; Barquera, R; Robinson, M K; Harrison, G F; Palmer, W H; Spyrou, M A; Susat, J; Krause-Kyora, B; Bos, K I; Forrest, S; Hernández-Zaragoza, D I; Sauter, J; Solloch, U; Schmidt, A H; Schuenemann, V J; Reiter, E; Kairies, M S; Weiß, R; Arnold, S; Wahl, J; Hollenbach, J A; Kohlbacher, O; Herbig, A; Norman, P J; Krause, J Analysis of genomic ĐNA from medieval plague victims suggests long-term effect of Yersinia pestis on human immunity genes Mol Biol Evol, 2021. @article{pmid34002224, title = {Analysis of genomic ĐNA from medieval plague victims suggests long-term effect of Yersinia pestis on human immunity genes}, author = {A Immel and F M Key and A Szolek and R Barquera and M K Robinson and G F Harrison and W H Palmer and M A Spyrou and J Susat and B Krause-Kyora and K I Bos and S Forrest and D I Hernández-Zaragoza and J Sauter and U Solloch and A H Schmidt and V J Schuenemann and E Reiter and M S Kairies and R Weiß and S Arnold and J Wahl and J A Hollenbach and O Kohlbacher and A Herbig and P J Norman and J Krause}, year = {2021}, date = {2021-05-01}, journal = {Mol Biol Evol}, abstract = {Pathogens and associated outbreaks of infectious disease exert selective pressure on human populations, and any changes in allele frequencies that result may be especially evident for genes involved in immunity. In this regard, the 1346-1353 Yersinia pestis-caused Black Death pandemic, with continued plague outbreaks spanning several hundred years, is one of the most devastating recorded in human history. To investigate the potential impact of Y. pestis on human immunity genes we extracted DNA from 36 plague victims buried in a mass grave in Ellwangen, Germany in the 16th century. We targeted 488 immune-related genes, including HLA, using a novel in-solution hybridization capture approach. In comparison with 50 modern native inhabitants of Ellwangen, we find differences in allele frequencies for variants of the innate immunity proteins Ficolin-2 and NLRP14 at sites involved in determining specificity. We also observed that HLA-DRB1*13 is more than twice as frequent in the modern population, whereas HLA-B alleles encoding an isoleucine at position 80 (I-80+), HLA C*06:02 and HLA-DPB1 alleles encoding histidine at position 9 are half as frequent in the modern population. Simulations show that natural selection has likely driven these allele frequency changes. Thus, our data suggests that allele frequencies of HLA genes involved in innate and adaptive immunity responsible for extracellular and intracellular responses to pathogenic bacteria, such as Y. pestis, could have been affected by the historical epidemics that occurred in Europe.}, keywords = {}, pubstate = {published}, tppubtype = {article} } Pathogens and associated outbreaks of infectious disease exert selective pressure on human populations, and any changes in allele frequencies that result may be especially evident for genes involved in immunity. In this regard, the 1346-1353 Yersinia pestis-caused Black Death pandemic, with continued plague outbreaks spanning several hundred years, is one of the most devastating recorded in human history. To investigate the potential impact of Y. pestis on human immunity genes we extracted DNA from 36 plague victims buried in a mass grave in Ellwangen, Germany in the 16th century. We targeted 488 immune-related genes, including HLA, using a novel in-solution hybridization capture approach. In comparison with 50 modern native inhabitants of Ellwangen, we find differences in allele frequencies for variants of the innate immunity proteins Ficolin-2 and NLRP14 at sites involved in determining specificity. We also observed that HLA-DRB1*13 is more than twice as frequent in the modern population, whereas HLA-B alleles encoding an isoleucine at position 80 (I-80+), HLA C*06:02 and HLA-DPB1 alleles encoding histidine at position 9 are half as frequent in the modern population. Simulations show that natural selection has likely driven these allele frequency changes. Thus, our data suggests that allele frequencies of HLA genes involved in innate and adaptive immunity responsible for extracellular and intracellular responses to pathogenic bacteria, such as Y. pestis, could have been affected by the historical epidemics that occurred in Europe. |
Völkel, G; Fürstberger, A; Schwab, J D; Werle, S D; Ikonomi, N; Gscheidmeier, T; Kraus, J M; Groß, A; Holderried, M; Balig, J; Jobst, F; Kuhn, P; Kuhn, K A; Kohlbacher, O; Kaisers, U X; Seufferlein, T; Kestler, H A Patient empowerment during the COVIĐ-19 pandemic: Ensuring safe and fast communication of test results J Med Internet Res, 2021. @article{pmid33999836, title = {Patient empowerment during the COVIĐ-19 pandemic: Ensuring safe and fast communication of test results}, author = {G Völkel and A Fürstberger and J D Schwab and S D Werle and N Ikonomi and T Gscheidmeier and J M Kraus and A Groß and M Holderried and J Balig and F Jobst and P Kuhn and K A Kuhn and O Kohlbacher and U X Kaisers and T Seufferlein and H A Kestler}, year = {2021}, date = {2021-05-01}, journal = {J Med Internet Res}, abstract = {Overcoming the COVID-19 crisis requires new ideas and strategies for online communication of personal medical information and patient empowerment. Rapid testing of a large number of subjects is essential to monitor, and delay, the spread of SARS-CoV-2 to mitigate the pandemic's consequences. People not knowing that they are infected may not stay in quarantine and, thus, risk infecting others. Unfortunately, the massive number of COVID-19 tests performed is challenging for both laboratories and the units that take the throat swab and communicate the results. Reducing the communication burden for healthcare professionals. We developed a secure and easy-to-use tracking system to report COVID-19 test results online which is simple to understand for the tested subjects as soon as these results become available. Instead of personal calls, the system updates the status and the results of the tests automatically. This aims to reduce the delay when informing testees about their results and, consequently, to slow down the virus spread. The application draws on an existing tracking tool. With this open-source and browser-based online tracking system, we aim to minimize the time required to inform the tested person and the test units, e.g. hospitals or the public healthcare system. The system can be integrated into the clinical workflow with very modest effort and avoids excessive load to telephone hotlines. The test status and results are published on a secured web-page enabling regular status checks by patients not using smartphones, which has some importance as smartphone usage diminishes with age. Stress tests and statistics show the performance of our software. CTest is currently running at two University Hospitals (Ulm, Tübingen; Germany) with thousands of tests each week. Results show a mean number of 10 views per testee. CTest runs independent of existing infrastructures, aims at straight-forward integration, and safe transmission of information. The system is easy-to-use for testees. QR Code links allow for quick accession to the test results. The mean number of views per entry indicates the reduced amount of time for both, healthcare professionals and testees. The system is quite generic and can be extended and adapted to other communication tasks.}, keywords = {}, pubstate = {published}, tppubtype = {article} } Overcoming the COVID-19 crisis requires new ideas and strategies for online communication of personal medical information and patient empowerment. Rapid testing of a large number of subjects is essential to monitor, and delay, the spread of SARS-CoV-2 to mitigate the pandemic's consequences. People not knowing that they are infected may not stay in quarantine and, thus, risk infecting others. Unfortunately, the massive number of COVID-19 tests performed is challenging for both laboratories and the units that take the throat swab and communicate the results. Reducing the communication burden for healthcare professionals. We developed a secure and easy-to-use tracking system to report COVID-19 test results online which is simple to understand for the tested subjects as soon as these results become available. Instead of personal calls, the system updates the status and the results of the tests automatically. This aims to reduce the delay when informing testees about their results and, consequently, to slow down the virus spread. The application draws on an existing tracking tool. With this open-source and browser-based online tracking system, we aim to minimize the time required to inform the tested person and the test units, e.g. hospitals or the public healthcare system. The system can be integrated into the clinical workflow with very modest effort and avoids excessive load to telephone hotlines. The test status and results are published on a secured web-page enabling regular status checks by patients not using smartphones, which has some importance as smartphone usage diminishes with age. Stress tests and statistics show the performance of our software. CTest is currently running at two University Hospitals (Ulm, Tübingen; Germany) with thousands of tests each week. Results show a mean number of 10 views per testee. CTest runs independent of existing infrastructures, aims at straight-forward integration, and safe transmission of information. The system is easy-to-use for testees. QR Code links allow for quick accession to the test results. The mean number of views per entry indicates the reduced amount of time for both, healthcare professionals and testees. The system is quite generic and can be extended and adapted to other communication tasks. |
Neidert, Ana Marcu; Leon Bichmann; Leon Kuchenbecker; Daniel Kowalewski; Lena Freudenmann; Linus Backert; Lena Mühlenbruch; Andras Szolek; Maren Lübke; Philipp Wagner; Tobias Engler; Sabine Matovina; Jian Wang; Mathias Hauri-Hohl; Roland Martin; Konstantina Kapolou; Juliane Walz; Julia Velz; Holger Moch; Luca Regli; Manuela Silginer; Michael Weller; Markus Löffler; Florian Erhard; Andreas Schlosser; Oliver Kohlbacher; Stefan Stevanović; Hans-Georg Rammensee; Marian HLA Ligand Atlas: a benign reference of HLA-presented peptides to improve T-cell-based cancer immunotherapy Journal for the ImmunoTherapy of Cancer, 9 (4), pp. e002071, 2021. @article{A2021, title = {HLA Ligand Atlas: a benign reference of HLA-presented peptides to improve T-cell-based cancer immunotherapy}, author = {Ana Marcu; Leon Bichmann; Leon Kuchenbecker; Daniel Kowalewski; Lena Freudenmann; Linus Backert; Lena Mühlenbruch; Andras Szolek; Maren Lübke; Philipp Wagner; Tobias Engler; Sabine Matovina; Jian Wang; Mathias Hauri-Hohl; Roland Martin; Konstantina Kapolou; Juliane Walz; Julia Velz; Holger Moch; Luca Regli; Manuela Silginer; Michael Weller; Markus Löffler; Florian Erhard; Andreas Schlosser; Oliver Kohlbacher; Stefan Stevanović; Hans-Georg Rammensee; Marian Neidert}, doi = {10.1136/jitc-2020-002071.}, year = {2021}, date = {2021-04-15}, journal = {Journal for the ImmunoTherapy of Cancer}, volume = {9}, number = {4}, pages = {e002071}, keywords = {}, pubstate = {published}, tppubtype = {article} } |
Green, Anna; Elhabashy, Hadeer; Brock, Kelly; Maddamsetti, Rohan; Kohlbacher, Oliver; Marks, Debora S Large-scale discovery of protein interactions at residue resolution using co-evolution calculated from genomic sequences Nat. Commun., 12 (1), pp. 1396, 2021. @article{EVComp_Nat_Comm_2021, title = { Large-scale discovery of protein interactions at residue resolution using co-evolution calculated from genomic sequences}, author = {Anna Green and Hadeer Elhabashy and Kelly Brock and Rohan Maddamsetti and Oliver Kohlbacher and Debora S. Marks}, doi = {10.1038/s41467-021-21636-z}, year = {2021}, date = {2021-03-01}, journal = {Nat. Commun.}, volume = {12}, number = {1}, pages = {1396}, abstract = {Increasing numbers of protein interactions have been identified in high-throughput experiments, but only a small proportion have solved structures. Recently, sequence coevolution-based approaches have led to a breakthrough in predicting monomer protein structures and protein interaction interfaces. Here we address the challenges of large-scale interaction prediction at residue resolution with a fast alignment concatenation method and a probabilistic score for the interaction of residues. Importantly, this method (EVcomplex2) is able to assess the likelihood of a protein interaction, as we show here applied to large-scale experimental datasets where the pairwise interactions are unknown. We predict 504 interactions de novo in the E. coli membrane proteome, including 243 that are newly discovered. While EVcomplex2 does not require available structures, coevolving residue pairs can be used to produce structural models of protein interactions, as done here for membrane complexes including the Flagellar Hook-Filament Junction and the Tol/Pal complex. Predictions: https://marks.hms.harvard.edu/ecolicomplex Code: https://github.com/debbiemarkslab/EVcouplings}, keywords = {}, pubstate = {published}, tppubtype = {article} } Increasing numbers of protein interactions have been identified in high-throughput experiments, but only a small proportion have solved structures. Recently, sequence coevolution-based approaches have led to a breakthrough in predicting monomer protein structures and protein interaction interfaces. Here we address the challenges of large-scale interaction prediction at residue resolution with a fast alignment concatenation method and a probabilistic score for the interaction of residues. Importantly, this method (EVcomplex2) is able to assess the likelihood of a protein interaction, as we show here applied to large-scale experimental datasets where the pairwise interactions are unknown. We predict 504 interactions de novo in the E. coli membrane proteome, including 243 that are newly discovered. While EVcomplex2 does not require available structures, coevolving residue pairs can be used to produce structural models of protein interactions, as done here for membrane complexes including the Flagellar Hook-Filament Junction and the Tol/Pal complex. Predictions: https://marks.hms.harvard.edu/ecolicomplex Code: https://github.com/debbiemarkslab/EVcouplings |
Immel, Alexander; Pierini, Federica; Rinne, Christoph; Meadows, John; Barquera, Rodrigo; Szolek, András; Susat, Julian; Böhme, Lisa; Dose, Janina; Bonczarowska, Joanna; Drummer, Clara; Fuchs, Katharina; Ellinghaus, David; Kässens, Jan Christian; Furholt, Martin; Kohlbacher, Oliver; Schade-Lindig, Sabine; Franke, Andre; Schreiber, Stefan; Krause, Johannes; Müller, Johannes; Lenz, Tobias L; Nebel, Almut; Krause-Kyora, Ben Genome-wide study of a Neolithic Wartberg grave community reveals distinct HLA variation and hunter-gatherer ancestry Communications Biology, 4 (1), pp. 113, 2021, ISSN: 2399-3642. @article{Immel2021, title = {Genome-wide study of a Neolithic Wartberg grave community reveals distinct HLA variation and hunter-gatherer ancestry}, author = {Alexander Immel and Federica Pierini and Christoph Rinne and John Meadows and Rodrigo Barquera and András Szolek and Julian Susat and Lisa Böhme and Janina Dose and Joanna Bonczarowska and Clara Drummer and Katharina Fuchs and David Ellinghaus and Jan Christian Kässens and Martin Furholt and Oliver Kohlbacher and Sabine Schade-Lindig and Andre Franke and Stefan Schreiber and Johannes Krause and Johannes Müller and Tobias L Lenz and Almut Nebel and Ben Krause-Kyora}, url = {https://doi.org/10.1038/s42003-020-01627-4}, doi = {10.1038/s42003-020-01627-4}, issn = {2399-3642}, year = {2021}, date = {2021-01-25}, journal = {Communications Biology}, volume = {4}, number = {1}, pages = {113}, abstract = {The Wartberg culture (WBC, 3500-2800 BCE) dates to the Late Neolithic period, a time of important demographic and cultural transformations in western Europe. We performed genome-wide analyses of 42 individuals who were interred in a WBC collective burial in Niedertiefenbach, Germany (3300-3200thinspacecal. BCE). The results showed that the farming population of Niedertiefenbach carried a surprisingly large hunter-gatherer ancestry component (34--58%). This component was most likely introduced during the cultural transformation that led to the WBC. In addition, the Niedertiefenbach individuals exhibited a distinct human leukocyte antigen gene pool, possibly reflecting an immune response that was geared towards detecting viral infections.}, keywords = {}, pubstate = {published}, tppubtype = {article} } The Wartberg culture (WBC, 3500-2800 BCE) dates to the Late Neolithic period, a time of important demographic and cultural transformations in western Europe. We performed genome-wide analyses of 42 individuals who were interred in a WBC collective burial in Niedertiefenbach, Germany (3300-3200thinspacecal. BCE). The results showed that the farming population of Niedertiefenbach carried a surprisingly large hunter-gatherer ancestry component (34--58%). This component was most likely introduced during the cultural transformation that led to the WBC. In addition, the Niedertiefenbach individuals exhibited a distinct human leukocyte antigen gene pool, possibly reflecting an immune response that was geared towards detecting viral infections. |
Kapsner, Lorenz A; Kampf, Marvin O; Seuchter, Susanne A; Gruendner, Julian; Gulden, Christian; Mate, Sebastian; Mang, Jonathan M; Schüttler, Christina; Deppenwiese, Noemi; Krause, Linda; Zöller, Daniela; Balig, Julien; Fuchs, Timo; Fischer, Patrick; Haverkamp, Christian; Holderried, Martin; Maye, Gerhard; Stenzhorn, Holger; Stolnicu, Ana; Storck, Michael; Storf, Holger; Zohner, Jochen; Kohlbacher, Oliver; Strzelczyk, Adam; Schüttler, Jürgen; Acker, Till; Boeker, Martin; Kaisers, Udo X; Kestler, Hans A; Prokosch, Hans-Ulrich Reduced Rate of Inpatient Hospital Admissions in 18 German University Hospitals during the COVID-19 Lockdown Frontiers in Public Health, 8 , pp. 594117., 2021. @article{CovidLockdown2020, title = {Reduced Rate of Inpatient Hospital Admissions in 18 German University Hospitals during the COVID-19 Lockdown }, author = {Lorenz A. Kapsner and Marvin O. Kampf and Susanne A. Seuchter and Julian Gruendner and Christian Gulden and Sebastian Mate and Jonathan M. Mang and Christina Schüttler and Noemi Deppenwiese and Linda Krause and Daniela Zöller and Julien Balig and Timo Fuchs and Patrick Fischer and Christian Haverkamp and Martin Holderried and Gerhard Maye and Holger Stenzhorn and Ana Stolnicu and Michael Storck and Holger Storf and Jochen Zohner and Oliver Kohlbacher and Adam Strzelczyk and Jürgen Schüttler and Till Acker and Martin Boeker and Udo X. Kaisers and Hans A. Kestler and Hans-Ulrich Prokosch}, url = {https://www.frontiersin.org/articles/10.3389/fpubh.2020.594117/full}, doi = {10.3389/fpubh.2020.594117}, year = {2021}, date = {2021-01-13}, journal = {Frontiers in Public Health}, volume = {8}, pages = {594117.}, abstract = {The COVID-19 pandemic has caused strains on health systems worldwide disrupting routine hospital services for all non-COVID patients. Within this retrospective study, we analyzed inpatient hospital admissions across 18 German university hospitals during the 2020 lockdown period compared to 2018. Patients admitted to hospital between January 1 and May 31, 2020 and the corresponding periods in 2018 and 2019 were included in this study. Data derived from electronic health records were collected and analyzed using the data integration center infrastructure implemented in the university hospitals that are part of the four consortia funded by the German Medical Informatics Initiative. Admissions were grouped and counted by ICD 10 chapters and specific reasons for treatment at each site. Pooled aggregated data were centrally analyzed with descriptive statistics to compare absolute and relative differences between time periods of different years. The results illustrate how care process adoptions depended on the COVID-19 epidemiological situation and the criticality of the disease. Overall inpatient hospital admissions decreased by 35% in weeks 1 to 4 and by 30.3% in weeks 5 to 8 after the lockdown announcement compared to 2018. Even hospital admissions for critical care conditions such as malignant cancer treatments were reduced. We also noted a high reduction of emergency admissions such as myocardial infarction (38.7%), whereas the reduction in stroke admissions was smaller (19.6%). In contrast, we observed a considerable reduction in admissions for non-critical clinical situations, such as hysterectomies for benign tumors (78.8%) and hip replacements due to arthrosis (82.4%). In summary, our study shows that the university hospital admission rates in Germany were substantially reduced following the national COVID-19 lockdown. These included critical care or emergency conditions in which deferral is expected to impair clinical outcomes. Future studies are needed to delineate how appropriate medical care of critically ill patients can be maintained during a pandemic.}, keywords = {}, pubstate = {published}, tppubtype = {article} } The COVID-19 pandemic has caused strains on health systems worldwide disrupting routine hospital services for all non-COVID patients. Within this retrospective study, we analyzed inpatient hospital admissions across 18 German university hospitals during the 2020 lockdown period compared to 2018. Patients admitted to hospital between January 1 and May 31, 2020 and the corresponding periods in 2018 and 2019 were included in this study. Data derived from electronic health records were collected and analyzed using the data integration center infrastructure implemented in the university hospitals that are part of the four consortia funded by the German Medical Informatics Initiative. Admissions were grouped and counted by ICD 10 chapters and specific reasons for treatment at each site. Pooled aggregated data were centrally analyzed with descriptive statistics to compare absolute and relative differences between time periods of different years. The results illustrate how care process adoptions depended on the COVID-19 epidemiological situation and the criticality of the disease. Overall inpatient hospital admissions decreased by 35% in weeks 1 to 4 and by 30.3% in weeks 5 to 8 after the lockdown announcement compared to 2018. Even hospital admissions for critical care conditions such as malignant cancer treatments were reduced. We also noted a high reduction of emergency admissions such as myocardial infarction (38.7%), whereas the reduction in stroke admissions was smaller (19.6%). In contrast, we observed a considerable reduction in admissions for non-critical clinical situations, such as hysterectomies for benign tumors (78.8%) and hip replacements due to arthrosis (82.4%). In summary, our study shows that the university hospital admission rates in Germany were substantially reduced following the national COVID-19 lockdown. These included critical care or emergency conditions in which deferral is expected to impair clinical outcomes. Future studies are needed to delineate how appropriate medical care of critically ill patients can be maintained during a pandemic. |
Arndt, Maike; Rurik, Marc; Drees, Alissa; Ahlers, Christian; Feldmann, Simon; Kohlbacher, Oliver; Fischer, Markus Food Authentication: Determination of the geographical origin of almonds (Prunus dulcis MILL.) via near-infrared spectroscopy Microchem. J., 160 (Part B), pp. 105702, 2021. @article{Arndt2021, title = {Food Authentication: Determination of the geographical origin of almonds (Prunus dulcis MILL.) via near-infrared spectroscopy }, author = {Maike Arndt and Marc Rurik and Alissa Drees and Christian Ahlers and Simon Feldmann and Oliver Kohlbacher and Markus Fischer}, url = {https://www.sciencedirect.com/science/article/abs/pii/S0026265X20325996}, doi = {10.1016/j.microc.2020.105702}, year = {2021}, date = {2021-01-03}, journal = {Microchem. J.}, volume = {160}, number = {Part B}, pages = {105702}, abstract = {The aim of the present study was the prediction of the geographical origin of almonds (Prunus dulcis Mill.) via Fourier transform near-infrared (FT-NIR) spectroscopy. For this purpose, 250 almond samples from six different countries were analyzed. As the year of harvest has a major impact on the metabolome, three different crop years (2017–2019) were considered. In order to predict the geographical origin, a support vector machine (SVM) model was trained. The SVM achieved a mean classification accuracy of 80.3% (± 1.5%). In particular one of the economically relevant questions – the distinction between Mediterranean almonds and American almonds – can be answered with this model. Combining the Spanish and Italian almonds to one Mediterranean class the overall classification accuracy is increased to up to 88.2% ± 1.0%. These results confirmed the suitability of NIR screening for the determination of the geographical origin of almonds and may pave the way for future analytical applications. With regard to potential future applications, the transferability of the developed NIR method to blanched almonds was discussed and evaluated: Even if the classification accuracy of unblanched almonds is higher than the prediction based on blanched almonds, the determination of the geographical origin still seems to be possible with this type of processed almonds.}, keywords = {}, pubstate = {published}, tppubtype = {article} } The aim of the present study was the prediction of the geographical origin of almonds (Prunus dulcis Mill.) via Fourier transform near-infrared (FT-NIR) spectroscopy. For this purpose, 250 almond samples from six different countries were analyzed. As the year of harvest has a major impact on the metabolome, three different crop years (2017–2019) were considered. In order to predict the geographical origin, a support vector machine (SVM) model was trained. The SVM achieved a mean classification accuracy of 80.3% (± 1.5%). In particular one of the economically relevant questions – the distinction between Mediterranean almonds and American almonds – can be answered with this model. Combining the Spanish and Italian almonds to one Mediterranean class the overall classification accuracy is increased to up to 88.2% ± 1.0%. These results confirmed the suitability of NIR screening for the determination of the geographical origin of almonds and may pave the way for future analytical applications. With regard to potential future applications, the transferability of the developed NIR method to blanched almonds was discussed and evaluated: Even if the classification accuracy of unblanched almonds is higher than the prediction based on blanched almonds, the determination of the geographical origin still seems to be possible with this type of processed almonds. |
van van de Aschenbrenner AC Mouktaroudi M, Krämer Oestreich Antonakos Nuesch-Germano Gkizeli Bonaguro Reusch Baßler Saridaki Knoll Pecht Kapellos TS Doulou Kröger Herbert Holsten Horne Gemünd ID Rovina Agrawal Dahm Uelft Drews Lenkeit Bruse Gerretsen Gierlich Becker Händler Kraut Theis Mengiste De Domenico Schulte-Schrepping Seep Raabe Hoffmeister ToVinh Keitel Rieke Talevi Skowasch Aziz NA Pickkers Veerdonk FL Netea MG Schultze JL Kox Breteler MMB Nattermann Koutsoukou Giamarellos-Bourboulis EJ Ulas German COVID-19 Omics Initiative (DeCOI) B M N M K L N K M R T S C M L A N S K M A L N J J M K M H S E J L J C M V G V D P M J A T; Disease severity-specific neutrophil signatures in blood transcriptomes stratify COVID-19 patients Genome Med., 13 (1), pp. 7, 2021. @article{Aschenbrenner2021-ld, title = {Disease severity-specific neutrophil signatures in blood transcriptomes stratify COVID-19 patients}, author = {Aschenbrenner AC, Mouktaroudi M, Krämer B, Oestreich M, Antonakos N, Nuesch-Germano M, Gkizeli K, Bonaguro L, Reusch N, Baßler K, Saridaki M, Knoll R, Pecht T, Kapellos TS, Doulou S, Kröger C, Herbert M, Holsten L, Horne A, Gemünd ID, Rovina N, Agrawal S, Dahm K, van Uelft M, Drews A, Lenkeit L, Bruse N, Gerretsen J, Gierlich J, Becker M, Händler K, Kraut M, Theis H, Mengiste S, De Domenico E, Schulte-Schrepping J, Seep L, Raabe J, Hoffmeister C, ToVinh M, Keitel V, Rieke G, Talevi V, Skowasch D, Aziz NA, Pickkers P, van de Veerdonk FL, Netea MG, Schultze JL, Kox M, Breteler MMB, Nattermann J, Koutsoukou A, Giamarellos-Bourboulis EJ, Ulas T; German COVID-19 Omics Initiative (DeCOI)}, year = {2021}, date = {2021-01-01}, journal = {Genome Med.}, volume = {13}, number = {1}, pages = {7}, abstract = {BACKGROUND: The SARS-CoV-2 pandemic is currently leading to increasing numbers of COVID-19 patients all over the world. Clinical presentations range from asymptomatic, mild respiratory tract infection, to severe cases with acute respiratory distress syndrome, respiratory failure, and death. Reports on a dysregulated immune system in the severe cases call for a better characterization and understanding of the changes in the immune system. METHODS: In order to dissect COVID-19-driven immune host responses, we performed RNA-seq of whole blood cell transcriptomes and granulocyte preparations from mild and severe COVID-19 patients and analyzed the data using a combination of conventional and data-driven co-expression analysis. Additionally, publicly available data was used to show the distinction from COVID-19 to other diseases. Reverse drug target prediction was used to identify known or novel drug candidates based on finding from data-driven findings. RESULTS: Here, we profiled whole blood transcriptomes of 39 COVID-19 patients and 10 control donors enabling a data-driven stratification based on molecular phenotype. Neutrophil activation-associated signatures were prominently enriched in severe patient groups, which was corroborated in whole blood transcriptomes from an independent second cohort of 30 as well as in granulocyte samples from a third cohort of 16 COVID-19 patients (44 samples). Comparison of COVID-19 blood transcriptomes with those of a collection of over 3100 samples derived from 12 different viral infections, inflammatory diseases, and independent control samples revealed highly specific transcriptome signatures for COVID-19. Further, stratified transcriptomes predicted patient subgroup-specific drug candidates targeting the dysregulated systemic immune response of the host. CONCLUSIONS: Our study provides novel insights in the distinct molecular subgroups or phenotypes that are not simply explained by clinical parameters. We show that whole blood transcriptomes are extremely informative for COVID-19 since they capture granulocytes which are major drivers of disease severity.}, keywords = {}, pubstate = {published}, tppubtype = {article} } BACKGROUND: The SARS-CoV-2 pandemic is currently leading to increasing numbers of COVID-19 patients all over the world. Clinical presentations range from asymptomatic, mild respiratory tract infection, to severe cases with acute respiratory distress syndrome, respiratory failure, and death. Reports on a dysregulated immune system in the severe cases call for a better characterization and understanding of the changes in the immune system. METHODS: In order to dissect COVID-19-driven immune host responses, we performed RNA-seq of whole blood cell transcriptomes and granulocyte preparations from mild and severe COVID-19 patients and analyzed the data using a combination of conventional and data-driven co-expression analysis. Additionally, publicly available data was used to show the distinction from COVID-19 to other diseases. Reverse drug target prediction was used to identify known or novel drug candidates based on finding from data-driven findings. RESULTS: Here, we profiled whole blood transcriptomes of 39 COVID-19 patients and 10 control donors enabling a data-driven stratification based on molecular phenotype. Neutrophil activation-associated signatures were prominently enriched in severe patient groups, which was corroborated in whole blood transcriptomes from an independent second cohort of 30 as well as in granulocyte samples from a third cohort of 16 COVID-19 patients (44 samples). Comparison of COVID-19 blood transcriptomes with those of a collection of over 3100 samples derived from 12 different viral infections, inflammatory diseases, and independent control samples revealed highly specific transcriptome signatures for COVID-19. Further, stratified transcriptomes predicted patient subgroup-specific drug candidates targeting the dysregulated systemic immune response of the host. CONCLUSIONS: Our study provides novel insights in the distinct molecular subgroups or phenotypes that are not simply explained by clinical parameters. We show that whole blood transcriptomes are extremely informative for COVID-19 since they capture granulocytes which are major drivers of disease severity. |
Völkel, Gunnar; Fürstberger, Axel; Schwab, Julian D; Werle, Silke D; Ikonomi, Nansi; Gscheidmeier, Thomas; Kraus, Johann M; ß, Alexander Gro; Holderried, Martin; Balig, Julien; Jobst, Franz; Kuhn, Peter; Kuhn, Klaus A; Kohlbacher, Oliver; Kaisers, Udo X; Seufferlein, Thomas; Kestler, Hans A Patient empowerment during the COVID-19 pandemic: Ensuring safe and fast communication of test results (Preprint) Journal of Medical Internet Research, Forthcoming. @article{Vlkel2021, title = {Patient empowerment during the COVID-19 pandemic: Ensuring safe and fast communication of test results (Preprint)}, author = {Gunnar Völkel and Axel Fürstberger and Julian D Schwab and Silke D Werle and Nansi Ikonomi and Thomas Gscheidmeier and Johann M Kraus and Alexander Gro ß and Martin Holderried and Julien Balig and Franz Jobst and Peter Kuhn and Klaus A Kuhn and Oliver Kohlbacher and Udo X Kaisers and Thomas Seufferlein and Hans A Kestler}, url = {https://doi.org/10.2196/27348}, doi = {10.2196/27348}, year = {2021}, date = {2021-01-01}, journal = {Journal of Medical Internet Research}, publisher = {JMIR Publications Inc.}, keywords = {}, pubstate = {forthcoming}, tppubtype = {article} } |
Kittner, M; Lamping, M; Rieke, D T; Götze, J; Bajwa, B; Jelas, I; Rüter, G; Hautow, H; Sänger, M; Habibi, M; Zettwitz, M; de Bortoli, T; Ostermann, L; Ševa, J; Starlinger, J; Kohlbacher, O; Malek, N P; Keilholz, U; Leser, U Annotation and initial evaluation of a large annotated German oncological corpus JAMIA Open, 4 (2), 2021. @article{pmid33898938, title = {Annotation and initial evaluation of a large annotated German oncological corpus}, author = {M Kittner and M Lamping and D T Rieke and J Götze and B Bajwa and I Jelas and G Rüter and H Hautow and M Sänger and M Habibi and M Zettwitz and T de Bortoli and L Ostermann and J Ševa and J Starlinger and O Kohlbacher and N P Malek and U Keilholz and U Leser}, year = {2021}, date = {2021-01-01}, journal = {JAMIA Open}, volume = {4}, number = {2}, abstract = {We present the Berlin-Tübingen-Oncology corpus (BRONCO), a large and freely available corpus of shuffled sentences from German oncological discharge summaries annotated with diagnosis, treatments, medications, and further attributes including negation and speculation. The aim of BRONCO is to foster reproducible and openly available research on Information Extraction from German medical texts. BRONCO consists of 200 manually deidentified discharge summaries of cancer patients. Annotation followed a structured and quality-controlled process involving 2 groups of medical experts to ensure consistency, comprehensiveness, and high quality of annotations. We present results of several state-of-the-art techniques for different IE tasks as baselines for subsequent research. The annotated corpus consists of 11 434 sentences and 89 942 tokens, annotated with 11 124 annotations for medical entities and 3118 annotations of related attributes. We publish 75% of the corpus as a set of shuffled sentences, and keep 25% as held-out data set for unbiased evaluation of future IE tools. On this held-out dataset, our baselines reach depending on the specific entity types F1-scores of 0.72-0.90 for named entity recognition, 0.10-0.68 for entity normalization, 0.55 for negation detection, and 0.33 for speculation detection. Medical corpus annotation is a complex and time-consuming task. This makes sharing of such resources even more important. To our knowledge, BRONCO is the first sizable and freely available German medical corpus. Our baseline results show that more research efforts are necessary to lift the quality of information extraction in German medical texts to the level already possible for English.}, keywords = {}, pubstate = {published}, tppubtype = {article} } We present the Berlin-Tübingen-Oncology corpus (BRONCO), a large and freely available corpus of shuffled sentences from German oncological discharge summaries annotated with diagnosis, treatments, medications, and further attributes including negation and speculation. The aim of BRONCO is to foster reproducible and openly available research on Information Extraction from German medical texts. BRONCO consists of 200 manually deidentified discharge summaries of cancer patients. Annotation followed a structured and quality-controlled process involving 2 groups of medical experts to ensure consistency, comprehensiveness, and high quality of annotations. We present results of several state-of-the-art techniques for different IE tasks as baselines for subsequent research. The annotated corpus consists of 11 434 sentences and 89 942 tokens, annotated with 11 124 annotations for medical entities and 3118 annotations of related attributes. We publish 75% of the corpus as a set of shuffled sentences, and keep 25% as held-out data set for unbiased evaluation of future IE tools. On this held-out dataset, our baselines reach depending on the specific entity types F1-scores of 0.72-0.90 for named entity recognition, 0.10-0.68 for entity normalization, 0.55 for negation detection, and 0.33 for speculation detection. Medical corpus annotation is a complex and time-consuming task. This makes sharing of such resources even more important. To our knowledge, BRONCO is the first sizable and freely available German medical corpus. Our baseline results show that more research efforts are necessary to lift the quality of information extraction in German medical texts to the level already possible for English. |
Dai, C; Füllgrabe, A; Pfeuffer, J; Solovyeva, E M; Deng, J; Moreno, P; Kamatchinathan, S; Kundu, D J; George, N; Fexova, S; Grüning, B; Föll, M C; Griss, J; Vaudel, M; Audain, E; Locard-Paulet, M; Turewicz, M; Eisenacher, M; Uszkoreit, J; Bossche, Van Den T; Schwämmle, V; Webel, H; Schulze, S; Bouyssié, D; Jayaram, S; Duggineni, V K; Samaras, P; Wilhelm, M; Choi, M; Wang, M; Kohlbacher, O; Brazma, A; Papatheodorou, I; Bandeira, N; Deutsch, E W; Vizcaíno, J A; Bai, M; Sachsenberg, T; Levitsky, L I; Perez-Riverol, Y A proteomics sample metadata representation for multiomics integration and big data analysis Nat Commun, 12 (1), pp. 5854, 2021, ([DOI:hrefhttps://dx.doi.org/10.1038/nature1800310.1038/nature18003] [PubMed:hrefhttps://www.ncbi.nlm.nih.gov/pubmed/3166547931665479]). @article{pmid34615866, title = {A proteomics sample metadata representation for multiomics integration and big data analysis}, author = {C Dai and A Füllgrabe and J Pfeuffer and E M Solovyeva and J Deng and P Moreno and S Kamatchinathan and D J Kundu and N George and S Fexova and B Grüning and M C Föll and J Griss and M Vaudel and E Audain and M Locard-Paulet and M Turewicz and M Eisenacher and J Uszkoreit and T Van Den Bossche and V Schwämmle and H Webel and S Schulze and D Bouyssié and S Jayaram and V K Duggineni and P Samaras and M Wilhelm and M Choi and M Wang and O Kohlbacher and A Brazma and I Papatheodorou and N Bandeira and E W Deutsch and J A Vizcaíno and M Bai and T Sachsenberg and L I Levitsky and Y Perez-Riverol}, year = {2021}, date = {2021-01-01}, journal = {Nat Commun}, volume = {12}, number = {1}, pages = {5854}, abstract = {The amount of public proteomics data is rapidly increasing but there is no standardized format to describe the sample metadata and their relationship with the dataset files in a way that fully supports their understanding or reanalysis. Here we propose to develop the transcriptomics data format MAGE-TAB into a standard representation for proteomics sample metadata. We implement MAGE-TAB-Proteomics in a crowdsourcing project to manually curate over 200 public datasets. We also describe tools and libraries to validate and submit sample metadata-related information to the PRIDE repository. We expect that these developments will improve the reproducibility and facilitate the reanalysis and integration of public proteomics datasets.}, note = {[DOI:hrefhttps://dx.doi.org/10.1038/nature1800310.1038/nature18003] [PubMed:hrefhttps://www.ncbi.nlm.nih.gov/pubmed/3166547931665479]}, keywords = {}, pubstate = {published}, tppubtype = {article} } The amount of public proteomics data is rapidly increasing but there is no standardized format to describe the sample metadata and their relationship with the dataset files in a way that fully supports their understanding or reanalysis. Here we propose to develop the transcriptomics data format MAGE-TAB into a standard representation for proteomics sample metadata. We implement MAGE-TAB-Proteomics in a crowdsourcing project to manually curate over 200 public datasets. We also describe tools and libraries to validate and submit sample metadata-related information to the PRIDE repository. We expect that these developments will improve the reproducibility and facilitate the reanalysis and integration of public proteomics datasets. |
E, Netz; TMH, Dijkstra; T, Sachsenberg; L, Zimmermann; M, Walzer; T, Monecke; R, Ficner; O, Dybkov; H, Urlaub; O, Kohlbacher OpenPepXL: An open-source tool for sensitive identification of cross-linked peptides in XL-MS Mol. Cell. Prot., 19 (12), pp. 2157-2168, 2020. @article{OpenPepXLMCP2021, title = {OpenPepXL: An open-source tool for sensitive identification of cross-linked peptides in XL-MS}, author = {Netz E and Dijkstra TMH and Sachsenberg T and Zimmermann L and Walzer M and Monecke T and Ficner R and Dybkov O and Urlaub H and Kohlbacher O}, doi = {10.1074/mcp.TIR120.002186}, year = {2020}, date = {2020-12-19}, journal = {Mol. Cell. Prot.}, volume = {19}, number = {12}, pages = {2157-2168}, keywords = {}, pubstate = {published}, tppubtype = {article} } |
Klare Juliane; Rurik, Marc; Rottmann Eric; Bollen Anke; Kohlbacher Oliver; Fischer Markus; Hackl Thomas Determination of the Geographical Origin of Asparagus officinalis L. by 1H‐NMR‐Spectroscopy J. Agricult. Food Chem., 68 (49), pp. 14353-14363, 2020. @article{Klare2020, title = {Determination of the Geographical Origin of Asparagus officinalis L. by 1H‐NMR‐Spectroscopy}, author = {Klare, Juliane; Rurik, Marc; Rottmann, Eric; Bollen, Anke; Kohlbacher, Oliver; Fischer, Markus; Hackl, Thomas}, url = {https://pubs.acs.org/doi/10.1021/acs.jafc.0c05642}, doi = {10.1021/acs.jafc.0c05642}, year = {2020}, date = {2020-12-09}, journal = {J. Agricult. Food Chem.}, volume = {68}, number = {49}, pages = {14353-14363}, abstract = {Food authenticity concerning the geographical origin becomes increasingly important for consumers, food industries, and food authorities. In this study, nontargeted 1H NMR metabolomics combined with machine learning methodologies was applied to successfully distinguish the geographical origin of 237 samples of white asparagus from Germany, Poland, The Netherlands, Spain, Greece, and Peru. Support vector classification of the geographical origin achieved an accuracy of 91.5% for the entire sample set and 87.8% after undersampling the majority class. Important regions of the spectra could be identified and assigned to potential chemical markers. A subset of samples was compared to isotope-ratio mass spectrometry (IRMS), an established method for the determination of origin of white asparagus in Germany. Here, SVM classification led to accuracies of 79.4% for NMR and 70.9% for IRMS. Finally, the classification of asparagus from different German regions was evaluated, and the influence of year and variety was analyzed.}, keywords = {}, pubstate = {published}, tppubtype = {article} } Food authenticity concerning the geographical origin becomes increasingly important for consumers, food industries, and food authorities. In this study, nontargeted 1H NMR metabolomics combined with machine learning methodologies was applied to successfully distinguish the geographical origin of 237 samples of white asparagus from Germany, Poland, The Netherlands, Spain, Greece, and Peru. Support vector classification of the geographical origin achieved an accuracy of 91.5% for the entire sample set and 87.8% after undersampling the majority class. Important regions of the spectra could be identified and assigned to potential chemical markers. A subset of samples was compared to isotope-ratio mass spectrometry (IRMS), an established method for the determination of origin of white asparagus in Germany. Here, SVM classification led to accuracies of 79.4% for NMR and 70.9% for IRMS. Finally, the classification of asparagus from different German regions was evaluated, and the influence of year and variety was analyzed. |
Alexander Leitner Alexandre M.J.J. Bonvin, Christoph Borchers Robert Chalkley Julia Chamot-Rooke Colin Combe Jürgen Cox Meng-Qiu Dong Lutz Fischer Michael Götze Fabio Gozzo Albert Heck Michael Hoopmann Lan Huang Yasushi Ishihama Andrew Jones Nir Kalisman Oliver Kohlbacher Karl Mechtler Robert Moritz Eugen Netz Petr Novak Evgeniy Petrotchenko Andrej Sali Richard Scheltema Carla Schmidt David Schriemer Andrea Sinz Frank Sobott Florian Stengel Konstantinos Thalassinos Henning Urlaub Rosa Viner Juan Vizcaino Marc Wilkins Juri Rappsilber H J W C J R R R L A A R Toward Increased Reliability, Transparency, and Accessibility in Cross-linking Mass Spectrometry Structure, 28 (11), pp. 1259-1268, 2020. @article{Leitner_Structure_2020, title = {Toward Increased Reliability, Transparency, and Accessibility in Cross-linking Mass Spectrometry}, author = {Alexander Leitner, Alexandre M.J.J. Bonvin, Christoph H. Borchers, Robert J. Chalkley, Julia Chamot-Rooke, Colin W. Combe, Jürgen Cox, Meng-Qiu Dong, Lutz Fischer, Michael Götze, Fabio C. Gozzo, Albert J.R. Heck, Michael R. Hoopmann, Lan Huang, Yasushi Ishihama, Andrew R. Jones, Nir Kalisman, Oliver Kohlbacher, Karl Mechtler, Robert L. Moritz, Eugen Netz, Petr Novak, Evgeniy Petrotchenko, Andrej Sali, Richard A. Scheltema, Carla Schmidt, David Schriemer, Andrea Sinz, Frank Sobott, Florian Stengel, Konstantinos Thalassinos, Henning Urlaub, Rosa Viner, Juan A. Vizcaino, Marc R. Wilkins, Juri Rappsilber}, url = {https://doi.org/10.1016/j.str.2020.09.011}, doi = {10.1016/j.str.2020.09.011}, year = {2020}, date = {2020-11-20}, journal = {Structure}, volume = {28}, number = {11}, pages = {1259-1268}, abstract = {Cross-linking mass spectrometry (MS) has substantially matured as a method over the past 2 decades through parallel development in multiple labs, demonstrating its applicability to protein structure determination, conformation analysis, and mapping protein interactions in complex mixtures. Cross-linking MS has become a much-appreciated and routinely applied tool, especially in structural biology. Therefore, it is timely that the community commits to the development of methodological and reporting standards. This white paper builds on an open process comprising a number of events at community conferences since 2015 and identifies aspects of Cross-linking MS for which guidelines should be developed as part of a Cross-linking MS standards initiative.}, keywords = {}, pubstate = {published}, tppubtype = {article} } Cross-linking mass spectrometry (MS) has substantially matured as a method over the past 2 decades through parallel development in multiple labs, demonstrating its applicability to protein structure determination, conformation analysis, and mapping protein interactions in complex mixtures. Cross-linking MS has become a much-appreciated and routinely applied tool, especially in structural biology. Therefore, it is timely that the community commits to the development of methodological and reporting standards. This white paper builds on an open process comprising a number of events at community conferences since 2015 and identifies aspects of Cross-linking MS for which guidelines should be developed as part of a Cross-linking MS standards initiative. |
Abbas, Syed Saiden; Dijkstra, Tjeerd M H Detection and stage classification of Plasmodium falciparum from images of Giemsa stained thin blood films using random forest classifiers Diagnostic Pathology, 15 (130), 2020. @article{abbas_2020, title = {Detection and stage classification of Plasmodium falciparum from images of Giemsa stained thin blood films using random forest classifiers}, author = {Syed Saiden Abbas and Tjeerd M. H. Dijkstra}, url = {https://diagnosticpathology.biomedcentral.com/articles/10.1186/s13000-020-01040-9}, doi = {10.1186/s13000-020-01040-9}, year = {2020}, date = {2020-10-23}, journal = {Diagnostic Pathology}, volume = {15}, number = {130}, abstract = {Background The conventional method for the diagnosis of malaria parasites is the microscopic examination of stained blood films, which is time consuming and requires expertise. We introduce computer-based image segmentation and life stage classification with a random forest classifier. Segmentation and stage classification are performed on a large dataset of malaria parasites with ground truth labels provided by experts. Methods We made use of Giemsa stained images obtained from the blood of 16 patients infected with Plasmodium falciparum. Experts labeled the parasite types from each of the images. We applied a two-step approach: image segmentation followed by life stage classification. In segmentation, we classified each pixel as a parasite or non-parasite pixel using a random forest classifier. Performance was evaluated with classification accuracy, Dice coefficient and free-response receiver operating characteristic (FROC) analysis. In life stage classification, we classified each of the segmented objects into one of 8 classes: 6 parasite life stages, early ring, late ring or early trophozoite, mid trophozoite, early schizont, late schizont or segmented, and two other classes, white blood cell or debris. Results Our segmentation method gives an average cross-validated Dice coefficient of 0.82 which is a 13% improvement compared to the Otsu method. The Otsu method achieved a True Positive Fraction (TPF) of 0.925 at the expense of a False Positive Rate (FPR) of 2.45. At the same TPF of 0.925, our method achieved an FPR of 0.92, an improvement by more than a factor two. We find that inclusion of average intensity of the whole image as feature for the random forest considerably improves segmentation performance. We obtain an overall accuracy of 58.8% when classifying all life stages. Stages are mostly confused with their neighboring stages. When we reduce the life stages to ring, trophozoite and schizont only, we obtain an accuracy of 82.7%. Conclusion Pixel classification gives better segmentation performance than the conventional Otsu method. Effects of staining and background variations can be reduced with the inclusion of average intensity features. The proposed method and data set can be used in the development of automatic tools for the detection and stage classification of malaria parasites. The data set is publicly available as a benchmark for future studies.}, keywords = {}, pubstate = {published}, tppubtype = {article} } Background The conventional method for the diagnosis of malaria parasites is the microscopic examination of stained blood films, which is time consuming and requires expertise. We introduce computer-based image segmentation and life stage classification with a random forest classifier. Segmentation and stage classification are performed on a large dataset of malaria parasites with ground truth labels provided by experts. Methods We made use of Giemsa stained images obtained from the blood of 16 patients infected with Plasmodium falciparum. Experts labeled the parasite types from each of the images. We applied a two-step approach: image segmentation followed by life stage classification. In segmentation, we classified each pixel as a parasite or non-parasite pixel using a random forest classifier. Performance was evaluated with classification accuracy, Dice coefficient and free-response receiver operating characteristic (FROC) analysis. In life stage classification, we classified each of the segmented objects into one of 8 classes: 6 parasite life stages, early ring, late ring or early trophozoite, mid trophozoite, early schizont, late schizont or segmented, and two other classes, white blood cell or debris. Results Our segmentation method gives an average cross-validated Dice coefficient of 0.82 which is a 13% improvement compared to the Otsu method. The Otsu method achieved a True Positive Fraction (TPF) of 0.925 at the expense of a False Positive Rate (FPR) of 2.45. At the same TPF of 0.925, our method achieved an FPR of 0.92, an improvement by more than a factor two. We find that inclusion of average intensity of the whole image as feature for the random forest considerably improves segmentation performance. We obtain an overall accuracy of 58.8% when classifying all life stages. Stages are mostly confused with their neighboring stages. When we reduce the life stages to ring, trophozoite and schizont only, we obtain an accuracy of 82.7%. Conclusion Pixel classification gives better segmentation performance than the conventional Otsu method. Effects of staining and background variations can be reduced with the inclusion of average intensity features. The proposed method and data set can be used in the development of automatic tools for the detection and stage classification of malaria parasites. The data set is publicly available as a benchmark for future studies. |
Schulte-Schrepping, J; Reusch, N; Paclik, D; Ba?ler, K; Schlickeiser, S; Zhang, B; Kr?mer, B; Krammer, T; Brumhard, S; Bonaguro, L; Domenico, De E; Wendisch, D; Grasshoff, M; Kapellos, T S; Beckstette, M; Pecht, T; Saglam, A; Dietrich, O; Mei, H E; Schulz, A R; Conrad, C; Kunkel, D; Vafadarnejad, E; Xu, C J; Horne, A; Herbert, M; Drews, A; Thibeault, C; Pfeiffer, M; Hippenstiel, S; Hocke, A; M?ller-Redetzky, H; Heim, K M; Machleidt, F; Uhrig, A; de Jarcy, Bosquillon L; J?rgens, L; Stegemann, M; Gl?senkamp, C R; Volk, H D; Goffinet, C; Landthaler, M; Wyler, E; Georg, P; Schneider, M; Dang-Heine, C; Neuwinger, N; Kappert, K; Tauber, R; Corman, V; Raabe, J; Kaiser, K M; Vinh, M T; Rieke, G; Meisel, C; Ulas, T; Becker, M; Geffers, R; Witzenrath, M; Drosten, C; Suttorp, N; von Kalle, C; Kurth, F; H?ndler, K; Schultze, J L; Aschenbrenner, A C; Li, Y; Nattermann, J; Sawitzki, B; Saliba, A E; Sander, L E; Angelov, A; Bals, R; Bartholom?us, A; Becker, A; Bezdan, D; Bonifacio, E; Bork, P; Clavel, T; Colome-Tatche, M; Diefenbach, A; Dilthey, A; Fischer, N; F?rstner, K; Frick, J S; Gagneur, J; Goesmann, A; Hain, T; Hummel, M; Janssen, S; Kalinowski, J; Kallies, R; Kehr, B; Keller, A; Kim-Hellmuth, S; Klein, C; Kohlbacher, O; Korbel, J O; Kurth, I; Landthaler, M; Li, Y; Ludwig, K; Makarewicz, O; Marz, M; McHardy, A; Mertes, C; N?then, M; N?rnberg, P; Ohler, U; Ossowski, S; Overmann, J; Peter, S; Pfeffer, K; Poetsch, A R; P?hler, A; Rajewsky, N; Ralser, M; Rie?, O; Ripke, S; da Rocha, Nunes U; Rosenstiel, P; Saliba, A E; Sander, L E; Sawitzki, B; Schiffer, P; Schulte, E C; Schultze, J L; Sczyrba, A; Stegle, O; Stoye, J; Theis, F; Vehreschild, J; Vogel, J; von Kleist, M; Walker, A; Walter, J; Wieczorek, D; Ziebuhr, J Severe COVID-19 Is Marked by a Dysregulated Myeloid Cell Compartment Cell, 182 (6), pp. 1419-1440.e23, 2020. @article{pmid32810438, title = {Severe COVID-19 Is Marked by a Dysregulated Myeloid Cell Compartment}, author = {J Schulte-Schrepping and N Reusch and D Paclik and K Ba?ler and S Schlickeiser and B Zhang and B Kr?mer and T Krammer and S Brumhard and L Bonaguro and E De Domenico and D Wendisch and M Grasshoff and T S Kapellos and M Beckstette and T Pecht and A Saglam and O Dietrich and H E Mei and A R Schulz and C Conrad and D Kunkel and E Vafadarnejad and C J Xu and A Horne and M Herbert and A Drews and C Thibeault and M Pfeiffer and S Hippenstiel and A Hocke and H M?ller-Redetzky and K M Heim and F Machleidt and A Uhrig and L Bosquillon de Jarcy and L J?rgens and M Stegemann and C R Gl?senkamp and H D Volk and C Goffinet and M Landthaler and E Wyler and P Georg and M Schneider and C Dang-Heine and N Neuwinger and K Kappert and R Tauber and V Corman and J Raabe and K M Kaiser and M T Vinh and G Rieke and C Meisel and T Ulas and M Becker and R Geffers and M Witzenrath and C Drosten and N Suttorp and C von Kalle and F Kurth and K H?ndler and J L Schultze and A C Aschenbrenner and Y Li and J Nattermann and B Sawitzki and A E Saliba and L E Sander and A Angelov and R Bals and A Bartholom?us and A Becker and D Bezdan and E Bonifacio and P Bork and T Clavel and M Colome-Tatche and A Diefenbach and A Dilthey and N Fischer and K F?rstner and J S Frick and J Gagneur and A Goesmann and T Hain and M Hummel and S Janssen and J Kalinowski and R Kallies and B Kehr and A Keller and S Kim-Hellmuth and C Klein and O Kohlbacher and J O Korbel and I Kurth and M Landthaler and Y Li and K Ludwig and O Makarewicz and M Marz and A McHardy and C Mertes and M N?then and P N?rnberg and U Ohler and S Ossowski and J Overmann and S Peter and K Pfeffer and A R Poetsch and A P?hler and N Rajewsky and M Ralser and O Rie? and S Ripke and U Nunes da Rocha and P Rosenstiel and A E Saliba and L E Sander and B Sawitzki and P Schiffer and E C Schulte and J L Schultze and A Sczyrba and O Stegle and J Stoye and F Theis and J Vehreschild and J Vogel and M von Kleist and A Walker and J Walter and D Wieczorek and J Ziebuhr}, url = {https://linkinghub.elsevier.com/retrieve/pii/S0092-8674(20)30992-2}, doi = {10.1016/j.cell.2020.08.001}, year = {2020}, date = {2020-09-17}, journal = {Cell}, volume = {182}, number = {6}, pages = {1419-1440.e23}, abstract = {Coronavirus disease 2019 (COVID-19) is a mild to moderate respiratory tract infection, however, a subset of patients progress to severe disease and respiratory failure. The mechanism of protective immunity in mild forms and the pathogenesis of severe COVID-19 associated with increased neutrophil counts and dysregulated immune responses remain unclear. In a dual-center, two-cohort study, we combined single-cell RNA-sequencing and single-cell proteomics of whole-blood and peripheral-blood mononuclear cells to determine changes in immune cell composition and activation in mild versus severe COVID-19 (242 samples from 109 individuals) over time. HLA-DRhiCD11chi inflammatory monocytes with an interferon-stimulated gene signature were elevated in mild COVID-19. Severe COVID-19 was marked by occurrence of neutrophil precursors, as evidence of emergency myelopoiesis, dysfunctional mature neutrophils, and HLA-DRlo monocytes. Our study provides detailed insights into the systemic immune response to SARS-CoV-2 infection and reveals profound alterations in the myeloid cell compartment associated with severe COVID-19.}, keywords = {}, pubstate = {published}, tppubtype = {article} } Coronavirus disease 2019 (COVID-19) is a mild to moderate respiratory tract infection, however, a subset of patients progress to severe disease and respiratory failure. The mechanism of protective immunity in mild forms and the pathogenesis of severe COVID-19 associated with increased neutrophil counts and dysregulated immune responses remain unclear. In a dual-center, two-cohort study, we combined single-cell RNA-sequencing and single-cell proteomics of whole-blood and peripheral-blood mononuclear cells to determine changes in immune cell composition and activation in mild versus severe COVID-19 (242 samples from 109 individuals) over time. HLA-DRhiCD11chi inflammatory monocytes with an interferon-stimulated gene signature were elevated in mild COVID-19. Severe COVID-19 was marked by occurrence of neutrophil precursors, as evidence of emergency myelopoiesis, dysfunctional mature neutrophils, and HLA-DRlo monocytes. Our study provides detailed insights into the systemic immune response to SARS-CoV-2 infection and reveals profound alterations in the myeloid cell compartment associated with severe COVID-19. |
Nelde, A; Bilich, T; Heitmann, J S; Maringer, Y; Salih, H R; Roerden, M; L?bke, M; Bauer, J; Rieth, J; Wacker, M; Peter, A; H?rber, S; Traenkle, B; Kaiser, P D; Rothbauer, U; Becker, M; Junker, D; Krause, G; Strengert, M; Schneiderhan-Marra, N; Templin, M F; Joos, T O; Kowalewski, D J; Stos-Zweifel, V; Fehr, M; Rabsteyn, A; Mirakaj, V; Karbach, J; J?ger, E; Graf, M; Gruber, L C; Rachfalski, D; Preu?, B; Hagelstein, I; M?rklin, M; Bakchoul, T; Gouttefangeas, C; Kohlbacher, O; Klein, R; Stevanovi?, S; Rammensee, H G; Walz, J S SARS-CoV-2-derived peptides define heterologous and COVIĐ-19-induced Ŧ cell recognition Nat Immunol, 2020. (BibTeX) @article{pmid32999467, title = {SARS-CoV-2-derived peptides define heterologous and COVIĐ-19-induced Ŧ cell recognition}, author = {A Nelde and T Bilich and J S Heitmann and Y Maringer and H R Salih and M Roerden and M L?bke and J Bauer and J Rieth and M Wacker and A Peter and S H?rber and B Traenkle and P D Kaiser and U Rothbauer and M Becker and D Junker and G Krause and M Strengert and N Schneiderhan-Marra and M F Templin and T O Joos and D J Kowalewski and V Stos-Zweifel and M Fehr and A Rabsteyn and V Mirakaj and J Karbach and E J?ger and M Graf and L C Gruber and D Rachfalski and B Preu? and I Hagelstein and M M?rklin and T Bakchoul and C Gouttefangeas and O Kohlbacher and R Klein and S Stevanovi? and H G Rammensee and J S Walz}, year = {2020}, date = {2020-09-01}, journal = {Nat Immunol}, keywords = {}, pubstate = {published}, tppubtype = {article} } |
Nothias, L F; Petras, D; Schmid, R; D?hrkop, K; Rainer, J; Sarvepalli, A; Protsyuk, I; Ernst, M; Tsugawa, H; Fleischauer, M; Aicheler, F; Aksenov, A A; Alka, O; Allard, P M; Barsch, A; Cachet, X; Caraballo-Rodriguez, A M; Silva, Da R R; Dang, T; Garg, N; Gauglitz, J M; Gurevich, A; Isaac, G; Jarmusch, A K; Kamen?k, Z; Kang, K B; Kessler, N; Koester, I; Korf, A; Gouellec, Le A; Ludwig, M; H, Martin C; McCall, L I; McSayles, J; Meyer, S W; Mohimani, H; Morsy, M; Moyne, O; Neumann, S; Neuweger, H; Nguyen, N H; Nothias-Esposito, M; Paolini, J; Phelan, V V; Pluskal, T; Quinn, R A; Rogers, S; Shrestha, B; Tripathi, A; van der Hooft, J J J; Vargas, F; Weldon, K C; Witting, M; Yang, H; Zhang, Z; Zubeil, F; Kohlbacher, O; B?cker, S; Alexandrov, T; Bandeira, N; Wang, M; Dorrestein, P C Feature-based molecular networking in the GNPS analysis environment Nat Methods, 17 (9), pp. 905–908, 2020. (BibTeX) @article{pmid32839597b, title = {Feature-based molecular networking in the GNPS analysis environment}, author = {L F Nothias and D Petras and R Schmid and K D?hrkop and J Rainer and A Sarvepalli and I Protsyuk and M Ernst and H Tsugawa and M Fleischauer and F Aicheler and A A Aksenov and O Alka and P M Allard and A Barsch and X Cachet and A M Caraballo-Rodriguez and R R Da Silva and T Dang and N Garg and J M Gauglitz and A Gurevich and G Isaac and A K Jarmusch and Z Kamen?k and K B Kang and N Kessler and I Koester and A Korf and A Le Gouellec and M Ludwig and C Martin H and L I McCall and J McSayles and S W Meyer and H Mohimani and M Morsy and O Moyne and S Neumann and H Neuweger and N H Nguyen and M Nothias-Esposito and J Paolini and V V Phelan and T Pluskal and R A Quinn and S Rogers and B Shrestha and A Tripathi and J J J van der Hooft and F Vargas and K C Weldon and M Witting and H Yang and Z Zhang and F Zubeil and O Kohlbacher and S B?cker and T Alexandrov and N Bandeira and M Wang and P C Dorrestein}, year = {2020}, date = {2020-09-01}, journal = {Nat Methods}, volume = {17}, number = {9}, pages = {905--908}, keywords = {}, pubstate = {published}, tppubtype = {article} } |
Identifying Đisease-Causing Mutations with Privacy Protection Bioinformatics, 2020. @article{pmid32683440, title = {Identifying Đisease-Causing Mutations with Privacy Protection}, year = {2020}, date = {2020-07-01}, journal = {Bioinformatics}, abstract = {The use of genome data for diagnosis and treatment is becoming increasingly common. Researchers need access to as many genomes as possible to interpret the patient genome, to obtain some statistical patterns, and to reveal disease-gene relationships. The sensitive information contained in the genome data and the high risk of re-identification increase the privacy and security concerns associated with sharing such data. In this paper, we present an approach to identify disease-associated variants and genes while ensuring patient privacy. The proposed method uses secure multi-party computation to find disease-causing mutations under specific inheritance models without sacrificing the privacy of individuals. It discloses only variants or genes obtained as a result of the analysis. Thus, the vast majority of patient data can be kept private. Our prototype implementation performs analyses on thousands of genomic data in milliseconds, and the runtime scales logarithmically with the number of patients. We present the first inheritance model (recessive, dominant, compound heterozygous) based privacy-preserving analyses of genomic data in order to find disease-causing mutations. Furthermore, we reimplement the privacy-preserving methods (MAX, SETDIFF, and INTERSECTION) proposed in a previous study. Our MAX, SETDIFF, and INTERSECTION implementations are 2.5, 1122, and 341 times faster than the corresponding operations of the state-of-the-art protocol, respectively. https://gitlab.com/DIFUTURE/privacy-preserving-genomic-diagnosis. Supplementary data are available at Bioinformatics online.}, keywords = {}, pubstate = {published}, tppubtype = {article} } The use of genome data for diagnosis and treatment is becoming increasingly common. Researchers need access to as many genomes as possible to interpret the patient genome, to obtain some statistical patterns, and to reveal disease-gene relationships. The sensitive information contained in the genome data and the high risk of re-identification increase the privacy and security concerns associated with sharing such data. In this paper, we present an approach to identify disease-associated variants and genes while ensuring patient privacy. The proposed method uses secure multi-party computation to find disease-causing mutations under specific inheritance models without sacrificing the privacy of individuals. It discloses only variants or genes obtained as a result of the analysis. Thus, the vast majority of patient data can be kept private. Our prototype implementation performs analyses on thousands of genomic data in milliseconds, and the runtime scales logarithmically with the number of patients. We present the first inheritance model (recessive, dominant, compound heterozygous) based privacy-preserving analyses of genomic data in order to find disease-causing mutations. Furthermore, we reimplement the privacy-preserving methods (MAX, SETDIFF, and INTERSECTION) proposed in a previous study. Our MAX, SETDIFF, and INTERSECTION implementations are 2.5, 1122, and 341 times faster than the corresponding operations of the state-of-the-art protocol, respectively. https://gitlab.com/DIFUTURE/privacy-preserving-genomic-diagnosis. Supplementary data are available at Bioinformatics online. |
Gleim, L C; Karim, M R; Zimmermann, L; Kohlbacher, O; Stenzhorn, H; Decker, S; Beyan, O Enabling ad-hoc reuse of private data repositories through schema extraction J Biomed Semantics, 11 (1), pp. 6, 2020. @article{pmid32641124, title = {Enabling ad-hoc reuse of private data repositories through schema extraction}, author = {L C Gleim and M R Karim and L Zimmermann and O Kohlbacher and H Stenzhorn and S Decker and O Beyan}, year = {2020}, date = {2020-07-01}, journal = {J Biomed Semantics}, volume = {11}, number = {1}, pages = {6}, abstract = {Sharing sensitive data across organizational boundaries is often significantly limited by legal and ethical restrictions. Regulations such as the EU General Data Protection Rules (GDPR) impose strict requirements concerning the protection of personal and privacy sensitive data. Therefore new approaches, such as the Personal Health Train initiative, are emerging to utilize data right in their original repositories, circumventing the need to transfer data. Circumventing limitations of previous systems, this paper proposes a configurable and automated schema extraction and publishing approach, which enables ad-hoc SPARQL query formulation against RDF triple stores without requiring direct access to the private data. The approach is compatible with existing Semantic Web-based technologies and allows for the subsequent execution of such queries in a safe setting under the data provider's control. Evaluation with four distinct datasets shows that a configurable amount of concise and task-relevant schema, closely describing the structure of the underlying data, was derived, enabling the schema introspection-assisted authoring of SPARQL queries. Automatically extracting and publishing data schema can enable the introspection-assisted creation of data selection and integration queries. In conjunction with the presented system architecture, this approach can enable reuse of data from private repositories and in settings where agreeing upon a shared schema and encoding a priori is infeasible. As such, it could provide an important step towards reuse of data from previously inaccessible sources and thus towards the proliferation of data-driven methods in the biomedical domain.}, keywords = {}, pubstate = {published}, tppubtype = {article} } Sharing sensitive data across organizational boundaries is often significantly limited by legal and ethical restrictions. Regulations such as the EU General Data Protection Rules (GDPR) impose strict requirements concerning the protection of personal and privacy sensitive data. Therefore new approaches, such as the Personal Health Train initiative, are emerging to utilize data right in their original repositories, circumventing the need to transfer data. Circumventing limitations of previous systems, this paper proposes a configurable and automated schema extraction and publishing approach, which enables ad-hoc SPARQL query formulation against RDF triple stores without requiring direct access to the private data. The approach is compatible with existing Semantic Web-based technologies and allows for the subsequent execution of such queries in a safe setting under the data provider's control. Evaluation with four distinct datasets shows that a configurable amount of concise and task-relevant schema, closely describing the structure of the underlying data, was derived, enabling the schema introspection-assisted authoring of SPARQL queries. Automatically extracting and publishing data schema can enable the introspection-assisted creation of data selection and integration queries. In conjunction with the presented system architecture, this approach can enable reuse of data from private repositories and in settings where agreeing upon a shared schema and encoding a priori is infeasible. As such, it could provide an important step towards reuse of data from previously inaccessible sources and thus towards the proliferation of data-driven methods in the biomedical domain. |
Starke, R; Oliphant, K; Jehmlich, N; Sch?pe, S S; Sachsenberg, T; Kohlbacher, O; Allen-Vercoe, E; von Bergen, M Corrigendum to Ŧracing incorporation of heavy water into proteins for species-specific metabolic activity in complex communities J Proteomics, 224 , pp. 103829, 2020. (BibTeX) @article{pmid32467047, title = {Corrigendum to Ŧracing incorporation of heavy water into proteins for species-specific metabolic activity in complex communities}, author = {R Starke and K Oliphant and N Jehmlich and S S Sch?pe and T Sachsenberg and O Kohlbacher and E Allen-Vercoe and M von Bergen}, year = {2020}, date = {2020-07-01}, journal = {J Proteomics}, volume = {224}, pages = {103829}, keywords = {}, pubstate = {published}, tppubtype = {article} } |
Scheidt, T; Alka, O; Gonczarowska-Jorge, H; Gruber, W; Rathje, F; DellÁica, M; Rurik, M; Kohlbacher, O; Zahedi, R P; Aberger, F; Huber, C G Phosphoproteomics of short-term hedgehog signaling in human medulloblastoma cells Cell Commun. Signal, 18 (1), pp. 99, 2020. @article{pmid32576205, title = {Phosphoproteomics of short-term hedgehog signaling in human medulloblastoma cells}, author = {T Scheidt and O Alka and H Gonczarowska-Jorge and W Gruber and F Rathje and M DellÁica and M Rurik and O Kohlbacher and R P Zahedi and F Aberger and C G Huber}, year = {2020}, date = {2020-06-01}, journal = {Cell Commun. Signal}, volume = {18}, number = {1}, pages = {99}, abstract = {Aberrant hedgehog (HH) signaling is implicated in the development of various cancer entities such as medulloblastoma. Activation of GLI transcription factors was revealed as the driving force upon pathway activation. Increased phosphorylation of essential effectors such as Smoothened (SMO) and GLI proteins by kinases including Protein Kinase A, Casein Kinase 1, and Glycogen Synthase Kinase 3 β controls effector activity, stability and processing. However, a deeper and more comprehensive understanding of phosphorylation in the signal transduction remains unclear, particularly during early response processes involved in SMO activation and preceding GLI target gene regulation. We applied temporal quantitative phosphoproteomics to reveal phosphorylation dynamics underlying the short-term chemical activation and inhibition of early hedgehog signaling in HH responsive human medulloblastoma cells. Medulloblastoma cells were treated for 5.0 and 15 min with Smoothened Agonist (SAG) to induce and with vismodegib to inhibit the HH pathway. Our phosphoproteomic profiling resulted in the quantification of 7700 and 10,000 phosphosites after 5.0 and 15 min treatment, respectively. The data suggest a central role of phosphorylation in the regulation of ciliary assembly, trafficking, and signal transduction already after 5.0 min treatment. ERK/MAPK signaling, besides Protein Kinase A signaling and mTOR signaling, were differentially regulated after short-term treatment. Activation of Polo-like Kinase 1 and inhibition of Casein Kinase 2A1 were characteristic for vismodegib treatment, while SAG treatment induced Aurora Kinase A activity. Distinctive phosphorylation of central players of HH signaling such as SMO, SUFU, GLI2 and GLI3 was observed only after 15 min treatment. This study provides evidence that phosphorylation triggered in response to SMO modulation dictates the localization of hedgehog pathway components within the primary cilium and affects the regulation of the SMO-SUFU-GLI axis. The data are relevant for the development of targeted therapies of HH-associated cancers including sonic HH-type medulloblastoma. A deeper understanding of the mechanisms of action of SMO inhibitors such as vismodegib may lead to the development of compounds causing fewer adverse effects and lower frequencies of drug resistance. Video Abstract.}, keywords = {}, pubstate = {published}, tppubtype = {article} } Aberrant hedgehog (HH) signaling is implicated in the development of various cancer entities such as medulloblastoma. Activation of GLI transcription factors was revealed as the driving force upon pathway activation. Increased phosphorylation of essential effectors such as Smoothened (SMO) and GLI proteins by kinases including Protein Kinase A, Casein Kinase 1, and Glycogen Synthase Kinase 3 β controls effector activity, stability and processing. However, a deeper and more comprehensive understanding of phosphorylation in the signal transduction remains unclear, particularly during early response processes involved in SMO activation and preceding GLI target gene regulation. We applied temporal quantitative phosphoproteomics to reveal phosphorylation dynamics underlying the short-term chemical activation and inhibition of early hedgehog signaling in HH responsive human medulloblastoma cells. Medulloblastoma cells were treated for 5.0 and 15 min with Smoothened Agonist (SAG) to induce and with vismodegib to inhibit the HH pathway. Our phosphoproteomic profiling resulted in the quantification of 7700 and 10,000 phosphosites after 5.0 and 15 min treatment, respectively. The data suggest a central role of phosphorylation in the regulation of ciliary assembly, trafficking, and signal transduction already after 5.0 min treatment. ERK/MAPK signaling, besides Protein Kinase A signaling and mTOR signaling, were differentially regulated after short-term treatment. Activation of Polo-like Kinase 1 and inhibition of Casein Kinase 2A1 were characteristic for vismodegib treatment, while SAG treatment induced Aurora Kinase A activity. Distinctive phosphorylation of central players of HH signaling such as SMO, SUFU, GLI2 and GLI3 was observed only after 15 min treatment. This study provides evidence that phosphorylation triggered in response to SMO modulation dictates the localization of hedgehog pathway components within the primary cilium and affects the regulation of the SMO-SUFU-GLI axis. The data are relevant for the development of targeted therapies of HH-associated cancers including sonic HH-type medulloblastoma. A deeper understanding of the mechanisms of action of SMO inhibitors such as vismodegib may lead to the development of compounds causing fewer adverse effects and lower frequencies of drug resistance. Video Abstract. |
Samonig, L; Loipetzberger, A; Bl?chl, C; Rurik, M; Kohlbacher, O; Aberger, F; Huber, C G Proteins and Molecular Pathways Relevant for the Malignant Properties of Ŧumor-Initiating Pancreatic Cancer Cells Cells, 9 (6), 2020. @article{pmid32503348, title = {Proteins and Molecular Pathways Relevant for the Malignant Properties of Ŧumor-Initiating Pancreatic Cancer Cells}, author = {L Samonig and A Loipetzberger and C Bl?chl and M Rurik and O Kohlbacher and F Aberger and C G Huber}, year = {2020}, date = {2020-06-01}, journal = {Cells}, volume = {9}, number = {6}, abstract = {Cancer stem cells (CSCs), a small subset of the tumor bulk with highly malignant properties, are deemed responsible for tumor initiation, growth, metastasis, and relapse. In order to reveal molecular markers and determinants of their tumor-initiating properties, we enriched rare stem-like pancreatic tumor-initiating cells (TICs) by harnessing their clonogenic growth capacity in three-dimensional multicellular spheroid cultures. We compared pancreatic TICs isolated from three-dimensional tumor spheroid cultures with nontumor-initiating cells (non-TICs) enriched in planar cultures. Employing differential proteomics (PTX), we identified more than 400 proteins with significantly different expression in pancreatic TICs and the non-TIC population. By combining the unbiased PTX with mRNA expression analysis and literature-based predictions of pro-malignant functions, we nominated the two calcium-binding proteins S100A8 (MRP8) and S100A9 (MRP14) as well as galactin-3-binding protein LGALS3BP (MAC-2-BP) as putative determinants of pancreatic TICs. In silico pathway analysis followed by candidate-based RNA interference mediated loss-of-function analysis revealed a critical role of S100A8, S100A9, and LGALS3BP as molecular determinants of TIC proliferation, migration, and in vivo tumor growth. Our study highlights the power of combining unbiased proteomics with focused gene expression and functional analyses for the identification of novel key regulators of TICs, an approach that warrants further application to identify proteins and pathways amenable to drug targeting.}, keywords = {}, pubstate = {published}, tppubtype = {article} } Cancer stem cells (CSCs), a small subset of the tumor bulk with highly malignant properties, are deemed responsible for tumor initiation, growth, metastasis, and relapse. In order to reveal molecular markers and determinants of their tumor-initiating properties, we enriched rare stem-like pancreatic tumor-initiating cells (TICs) by harnessing their clonogenic growth capacity in three-dimensional multicellular spheroid cultures. We compared pancreatic TICs isolated from three-dimensional tumor spheroid cultures with nontumor-initiating cells (non-TICs) enriched in planar cultures. Employing differential proteomics (PTX), we identified more than 400 proteins with significantly different expression in pancreatic TICs and the non-TIC population. By combining the unbiased PTX with mRNA expression analysis and literature-based predictions of pro-malignant functions, we nominated the two calcium-binding proteins S100A8 (MRP8) and S100A9 (MRP14) as well as galactin-3-binding protein LGALS3BP (MAC-2-BP) as putative determinants of pancreatic TICs. In silico pathway analysis followed by candidate-based RNA interference mediated loss-of-function analysis revealed a critical role of S100A8, S100A9, and LGALS3BP as molecular determinants of TIC proliferation, migration, and in vivo tumor growth. Our study highlights the power of combining unbiased proteomics with focused gene expression and functional analyses for the identification of novel key regulators of TICs, an approach that warrants further application to identify proteins and pathways amenable to drug targeting. |
Starke, R; Oliphant, K; Jehmlich, N; Sch?pe, S S; Sachsenberg, T; Kohlbacher, O; Allen-Vercoe, E; von Bergen, M Ŧracing incorporation of heavy water into proteins for species-specific metabolic activity in complex communities J Proteomics, 222 , pp. 103791, 2020. @article{pmid32335296, title = {Ŧracing incorporation of heavy water into proteins for species-specific metabolic activity in complex communities}, author = {R Starke and K Oliphant and N Jehmlich and S S Sch?pe and T Sachsenberg and O Kohlbacher and E Allen-Vercoe and M von Bergen}, year = {2020}, date = {2020-06-01}, journal = {J Proteomics}, volume = {222}, pages = {103791}, abstract = {Stable isotope probing (SIP) approaches are a suitable tool to identify active organisms in bacterial communities, but adding isotopically labeled substrate can alter both the structure and the functionality of the community. Here, we validated and demonstrated a substrate-independent protein-SIP protocol using isotopically labeled water that captures the entire microbial activity of a community. We found that 18O yielded a higher incorporation rate into peptides and thus comprised a higher sensitivity. We then applied the method to an in vitro model of a human distal gut microbial ecosystem grown in two medium formulations, to evaluate changes in microbial activity between a high-fiber and high-protein diet. We showed that only little changes are seen in the community structure but the functionality varied between the diets. In conclusion, our approach can detect species-specific metabolic activity in complex bacterial communities and more specifically to quantify the amount of amino acid synthesis. Heavy water makes possible to analyze the activity of bacterial communities for which adding an isotopically labeled energy and nutrient sources is not easily feasible. SIGNIFICANCE: Heavy stable isotopes allow for the detection of active key players in complex ecosystems where many organisms are thought to be dormant. Opposed to the labelling with energy or nutrient sources, heavy water could be a suitable replacement to trace activity, which has been shown for DNA and RNA. Here we validate, quantify and compare the incorporation of heavy water either labeled with deuterium or 18‑oxygen into proteins of Escherichia coli K12 and of an in vitro model of a human gut microbial ecosystem. The significance of our research is in providing a freely available pipeline to analyze the incorporation of deuterium and 18‑oxygen into proteins together with the validation of the applicability of tracing heavy water as a proxy for activity. Our approach unveils the relative functional contribution of microbiota in complex ecosystems, which will improve our understanding of both animal- and environment-associated microbiomes and in vitro models.}, keywords = {}, pubstate = {published}, tppubtype = {article} } Stable isotope probing (SIP) approaches are a suitable tool to identify active organisms in bacterial communities, but adding isotopically labeled substrate can alter both the structure and the functionality of the community. Here, we validated and demonstrated a substrate-independent protein-SIP protocol using isotopically labeled water that captures the entire microbial activity of a community. We found that 18O yielded a higher incorporation rate into peptides and thus comprised a higher sensitivity. We then applied the method to an in vitro model of a human distal gut microbial ecosystem grown in two medium formulations, to evaluate changes in microbial activity between a high-fiber and high-protein diet. We showed that only little changes are seen in the community structure but the functionality varied between the diets. In conclusion, our approach can detect species-specific metabolic activity in complex bacterial communities and more specifically to quantify the amount of amino acid synthesis. Heavy water makes possible to analyze the activity of bacterial communities for which adding an isotopically labeled energy and nutrient sources is not easily feasible. SIGNIFICANCE: Heavy stable isotopes allow for the detection of active key players in complex ecosystems where many organisms are thought to be dormant. Opposed to the labelling with energy or nutrient sources, heavy water could be a suitable replacement to trace activity, which has been shown for DNA and RNA. Here we validate, quantify and compare the incorporation of heavy water either labeled with deuterium or 18‑oxygen into proteins of Escherichia coli K12 and of an in vitro model of a human gut microbial ecosystem. The significance of our research is in providing a freely available pipeline to analyze the incorporation of deuterium and 18‑oxygen into proteins together with the validation of the applicability of tracing heavy water as a proxy for activity. Our approach unveils the relative functional contribution of microbiota in complex ecosystems, which will improve our understanding of both animal- and environment-associated microbiomes and in vitro models. |
Jeong, Kyowon; Kim, Jihyung; Gaikwad, Manasi; Hidayah, Siti Nurul; Heikaus, Laura; Schlüter, Hartmut; Kohlbacher, Oliver FLASHDeconv: Ultrafast, High-Quality Feature Deconvolution for Top-Down Proteomics Cell Systems, 10 (2), pp. 213-218, 2020, ISSN: 2405-4712. @article{FLASHDeconvCellSys2020, title = {FLASHDeconv: Ultrafast, High-Quality Feature Deconvolution for Top-Down Proteomics}, author = {Kyowon Jeong and Jihyung Kim and Manasi Gaikwad and Siti Nurul Hidayah and Laura Heikaus and Hartmut Schlüter and Oliver Kohlbacher}, url = {https://doi.org/10.1016/j.cels.2020.01.003}, doi = {10.1016/j.cels.2020.01.003}, issn = {2405-4712}, year = {2020}, date = {2020-02-26}, journal = {Cell Systems}, volume = {10}, number = {2}, pages = {213-218}, publisher = {Elsevier}, abstract = {Top-down mass spectrometry (TD-MS)-based proteomics analyzes intact proteoforms and thus preserves information about individual protein species. The MS signal of these high-mass analytes is complex and challenges the accurate determination of proteoform masses. Fast and accurate feature deconvolution (i.e., the determination of intact proteoform masses) is, therefore, an essential step for TD data analysis. Here, we present FLASHDeconv, an algorithm achieving higher deconvolution quality, with an execution speed two orders of magnitude faster than existing approaches. FLASHDeconv transforms peak positions (m/z) within spectra into log m/z space. This simple transformation turns the deconvolution problem into a search for constant patterns, thereby greatly accelerating the process. In both simple and complex samples, FLASHDeconv reports more genuine feature masses and substantially fewer artifacts than other existing methods. FLASHDeconv is freely available for download here: https://www.openms.org/flashdeconv/. A record of this paper?s Transparent Peer Review process is included in the Supplemental Information.}, keywords = {}, pubstate = {published}, tppubtype = {article} } Top-down mass spectrometry (TD-MS)-based proteomics analyzes intact proteoforms and thus preserves information about individual protein species. The MS signal of these high-mass analytes is complex and challenges the accurate determination of proteoform masses. Fast and accurate feature deconvolution (i.e., the determination of intact proteoform masses) is, therefore, an essential step for TD data analysis. Here, we present FLASHDeconv, an algorithm achieving higher deconvolution quality, with an execution speed two orders of magnitude faster than existing approaches. FLASHDeconv transforms peak positions (m/z) within spectra into log m/z space. This simple transformation turns the deconvolution problem into a search for constant patterns, thereby greatly accelerating the process. In both simple and complex samples, FLASHDeconv reports more genuine feature masses and substantially fewer artifacts than other existing methods. FLASHDeconv is freely available for download here: https://www.openms.org/flashdeconv/. A record of this paper?s Transparent Peer Review process is included in the Supplemental Information. |
Samuel Wein Byron Andrews, Timo Sachsenberg Helena Santos-Rosa Oliver Kohlbacher Tony Kouzarides Benjamin Garcia ; Weisser, Hendrik A computational platform for high-throughput analysis of RNA sequences and modifications by mass spectrometry Nat. Commun., 11 (1), pp. 926, 2020. @article{Wein_NASE_2020, title = {A computational platform for high-throughput analysis of RNA sequences and modifications by mass spectrometry}, author = {Samuel Wein, Byron Andrews, Timo Sachsenberg, Helena Santos-Rosa, Oliver Kohlbacher, Tony Kouzarides, Benjamin Garcia, and Hendrik Weisser}, url = {https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7026122/}, doi = {10.1038/s41467-020-14665-7}, year = {2020}, date = {2020-02-17}, journal = {Nat. Commun.}, volume = {11}, number = {1}, pages = {926}, abstract = {The field of epitranscriptomics continues to reveal how post-transcriptional modification of RNA affects a wide variety of biological phenomena. A pivotal challenge in this area is the identification of modified RNA residues within their sequence contexts. Mass spectrometry (MS) offers a comprehensive solution by using analogous approaches to shotgun proteomics. However, software support for the analysis of RNA MS data is inadequate at present and does not allow high-throughput processing. Existing software solutions lack the raw performance and statistical grounding to efficiently handle the numerous modifications found on RNA. We present a free and open-source database search engine for RNA MS data, called NucleicAcidSearchEngine (NASE), that addresses these shortcomings. We demonstrate the capability of NASE to reliably identify a wide range of modified RNA sequences in four original datasets of varying complexity. In human tRNA, we characterize over 20 different modification types simultaneously and find many cases of incomplete modification.}, keywords = {}, pubstate = {published}, tppubtype = {article} } The field of epitranscriptomics continues to reveal how post-transcriptional modification of RNA affects a wide variety of biological phenomena. A pivotal challenge in this area is the identification of modified RNA residues within their sequence contexts. Mass spectrometry (MS) offers a comprehensive solution by using analogous approaches to shotgun proteomics. However, software support for the analysis of RNA MS data is inadequate at present and does not allow high-throughput processing. Existing software solutions lack the raw performance and statistical grounding to efficiently handle the numerous modifications found on RNA. We present a free and open-source database search engine for RNA MS data, called NucleicAcidSearchEngine (NASE), that addresses these shortcomings. We demonstrate the capability of NASE to reliably identify a wide range of modified RNA sequences in four original datasets of varying complexity. In human tRNA, we characterize over 20 different modification types simultaneously and find many cases of incomplete modification. |
Pfeuffer Julianus; Sachsenberg, Timo; Dijkstra Tjeerd Serang Oliver; Reinert Knut; Kohlbacher Oliver M H ; EPIFANY - A method for efficient high-confidence protein inference J. Proteome Res., 2020. @article{EPIFANY2020, title = {EPIFANY - A method for efficient high-confidence protein inference}, author = {Pfeuffer, Julianus; Sachsenberg, Timo; Dijkstra, Tjeerd M. H.; Serang, Oliver; Reinert, Knut; Kohlbacher, Oliver}, url = {https://doi.org/10.1021/acs.jproteome.9b00566}, doi = {10.1021/acs.jproteome.9b00566}, year = {2020}, date = {2020-01-24}, journal = {J. Proteome Res.}, abstract = {Accurate protein inference under the presence of shared peptides is still one of the key problems in bottom-up proteomics. Most protein inference tools employing simple heuristic inference strategies are efficient, but exhibit reduced accuracy. More advanced probabilistic methods often exhibit better inference quality but tend to be too slow for large data sets. Here we present a novel protein inference method, EPIFANY, combining a loopy belief propagation algorithm with convolution trees for efficient processing of Bayesian networks. We demonstrate that EPIFANY combines the reliable protein inference of Bayesian methods with significantly shorter runtimes. On the 2016 iPRG protein inference benchmark data EPIFANY is the only tested method which finds all true-positive proteins at a 5% protein FDR without strict pre-filtering on PSM level, yielding an increase in identification performance (+10% in the number of true positives and +14% in partial AUC) compared to previous approaches. Even very large data sets with hundreds of thousands of spectra (which are intractable with other Bayesian and some non-Bayesian tools) can be processed with EPIFANY within minutes. The increased inference quality including shared peptides results in better protein inference results and thus increased robustness of the biological hypotheses generated. EPIFANY is available as open-source software for all major platforms at https://OpenMS.de/epifany. AB - Accurate protein inference under the presence of shared peptides is still one of the key problems in bottom-up proteomics. Most protein inference tools employing simple heuristic inference strategies are efficient, but exhibit reduced accuracy. More advanced probabilistic methods often exhibit better inference quality but tend to be too slow for large data sets. Here we present a novel protein inference method, EPIFANY, combining a loopy belief propagation algorithm with convolution trees for efficient processing of Bayesian networks. We demonstrate that EPIFANY combines the reliable protein inference of Bayesian methods with significantly shorter runtimes. On the 2016 iPRG protein inference benchmark data EPIFANY is the only tested method which finds all true-positive proteins at a 5% protein FDR without strict pre-filtering on PSM level, yielding an increase in identification performance (+10% in the number of true positives and +14% in partial AUC) compared to previous approaches. Even very large data sets with hundreds of thousands of spectra (which are intractable with other Bayesian and some non-Bayesian tools) can be processed with EPIFANY within minutes. The increased inference quality including shared peptides results in better protein inference results and thus increased robustness of the biological hypotheses generated. EPIFANY is available as open-source software for all major platforms at https://OpenMS.de/epifany.}, keywords = {}, pubstate = {published}, tppubtype = {article} } Accurate protein inference under the presence of shared peptides is still one of the key problems in bottom-up proteomics. Most protein inference tools employing simple heuristic inference strategies are efficient, but exhibit reduced accuracy. More advanced probabilistic methods often exhibit better inference quality but tend to be too slow for large data sets. Here we present a novel protein inference method, EPIFANY, combining a loopy belief propagation algorithm with convolution trees for efficient processing of Bayesian networks. We demonstrate that EPIFANY combines the reliable protein inference of Bayesian methods with significantly shorter runtimes. On the 2016 iPRG protein inference benchmark data EPIFANY is the only tested method which finds all true-positive proteins at a 5% protein FDR without strict pre-filtering on PSM level, yielding an increase in identification performance (+10% in the number of true positives and +14% in partial AUC) compared to previous approaches. Even very large data sets with hundreds of thousands of spectra (which are intractable with other Bayesian and some non-Bayesian tools) can be processed with EPIFANY within minutes. The increased inference quality including shared peptides results in better protein inference results and thus increased robustness of the biological hypotheses generated. EPIFANY is available as open-source software for all major platforms at https://OpenMS.de/epifany. AB - Accurate protein inference under the presence of shared peptides is still one of the key problems in bottom-up proteomics. Most protein inference tools employing simple heuristic inference strategies are efficient, but exhibit reduced accuracy. More advanced probabilistic methods often exhibit better inference quality but tend to be too slow for large data sets. Here we present a novel protein inference method, EPIFANY, combining a loopy belief propagation algorithm with convolution trees for efficient processing of Bayesian networks. We demonstrate that EPIFANY combines the reliable protein inference of Bayesian methods with significantly shorter runtimes. On the 2016 iPRG protein inference benchmark data EPIFANY is the only tested method which finds all true-positive proteins at a 5% protein FDR without strict pre-filtering on PSM level, yielding an increase in identification performance (+10% in the number of true positives and +14% in partial AUC) compared to previous approaches. Even very large data sets with hundreds of thousands of spectra (which are intractable with other Bayesian and some non-Bayesian tools) can be processed with EPIFANY within minutes. The increased inference quality including shared peptides results in better protein inference results and thus increased robustness of the biological hypotheses generated. EPIFANY is available as open-source software for all major platforms at https://OpenMS.de/epifany. |
Hentrich, T; Koch, A; Weber, N; Kilzheimer, A; Burkhardt, S; Rall, K; Casadei, N; Kohlbacher, O; Riess, O; Schulze-Hentrich, JM; Brucker, SY The endometrial transcription landscape of MRKH syndrome bioRxiv, 2020. @article{Hentrich2020.02.18.954768, title = {The endometrial transcription landscape of MRKH syndrome}, author = {T Hentrich and A Koch and N Weber and A Kilzheimer and S Burkhardt and K Rall and N Casadei and O Kohlbacher and O Riess and JM Schulze-Hentrich and SY Brucker}, url = {https://www.biorxiv.org/content/early/2020/02/19/2020.02.18.954768}, doi = {10.1101/2020.02.18.954768}, year = {2020}, date = {2020-01-01}, journal = {bioRxiv}, publisher = {Cold Spring Harbor Laboratory}, abstract = {The Mayer-Rokitansky-Küster-Hauser (MRKH) syndrome (OMIM 277000) is characterized by agenesis of the uterus and upper part of the vagina in females with normal ovarian function. While genetic causes have been identified for a small subset of patients and epigenetic mechanisms presumably contribute to the pathogenic unfolding, too, the etiology of the syndrome has remained largely enigmatic. A comprehensive understanding of gene activity in the context of the disease is crucial to identify etiological components and their potential interplay. So far, this understanding is lacking, primarily due to the scarcity of samples and suitable tissue.In order to close this gap, we profiled endometrial tissue of uterus rudiments in a large cohort of MRKH patients using RNA-seq and thereby provide a genome-wide view on the altered transcription landscape of the MRKH syndrome. Differential and co-expression analyses of the data identified cellular processes and candidate genes that converge on a core network of interconnected regulators that emerge as pivotal for the perturbed expression space. With these results and browsable access to the rich data through an online tool we seek to accelerate research to unravel the underlying biology of this syndrome.}, keywords = {}, pubstate = {published}, tppubtype = {article} } The Mayer-Rokitansky-Küster-Hauser (MRKH) syndrome (OMIM 277000) is characterized by agenesis of the uterus and upper part of the vagina in females with normal ovarian function. While genetic causes have been identified for a small subset of patients and epigenetic mechanisms presumably contribute to the pathogenic unfolding, too, the etiology of the syndrome has remained largely enigmatic. A comprehensive understanding of gene activity in the context of the disease is crucial to identify etiological components and their potential interplay. So far, this understanding is lacking, primarily due to the scarcity of samples and suitable tissue.In order to close this gap, we profiled endometrial tissue of uterus rudiments in a large cohort of MRKH patients using RNA-seq and thereby provide a genome-wide view on the altered transcription landscape of the MRKH syndrome. Differential and co-expression analyses of the data identified cellular processes and candidate genes that converge on a core network of interconnected regulators that emerge as pivotal for the perturbed expression space. With these results and browsable access to the rich data through an online tool we seek to accelerate research to unravel the underlying biology of this syndrome. |
Voelkel, Gunnar; Fuerstberger, Axel; Schwab, Julian D; Kuehlwein, Silke D; Gscheidmeier, Thomas; Kraus, Johann M; Gross, Alexander; Kohlmayer, Florian; Kuhn, Peter; Kuhn, Klaus A; Kohlbacher, Oliver; Seufferlein, Thomas; Kestler, Hans A A secure and rapid query-software for COVID-19 test results that can easily be integrated into the clinical workflow to avoid communication overload medRxiv, 2020. @article{Voelkel2020.04.07.20056887, title = {A secure and rapid query-software for COVID-19 test results that can easily be integrated into the clinical workflow to avoid communication overload}, author = {Gunnar Voelkel and Axel Fuerstberger and Julian D Schwab and Silke D Kuehlwein and Thomas Gscheidmeier and Johann M Kraus and Alexander Gross and Florian Kohlmayer and Peter Kuhn and Klaus A Kuhn and Oliver Kohlbacher and Thomas Seufferlein and Hans A Kestler}, url = {https://www.medrxiv.org/content/early/2020/04/11/2020.04.07.20056887}, doi = {10.1101/2020.04.07.20056887}, year = {2020}, date = {2020-01-01}, journal = {medRxiv}, publisher = {Cold Spring Harbor Laboratory Press}, abstract = {Overcoming the COVID-19 crisis requires new ideas and strategies. Rapid testing of a large number of subjects is essential to monitor, and delay, the spread of SARS-CoV-2 to mitigate the consequences of the pandemic. People not knowing that they are infected may not stay in quarantine and, thus, are a risk for infecting others. Unfortunately, the massive number of COVID-19 tests performed is challenging for both laboratories and the units that take the throat swab and have to communicate test results. Here, we present a secure tracking system (CTest) to report COVID-19 test results online as soon as they become available. The system can be integrated into the clinical workflow with very modest effort and avoids excessive load to telephone hotlines. With this open-source and browser-based online tracking system, we aim to minimize the time required to inform the tested person but also the test units, e.g. hospitals or the public healthcare system. Instead of personal calls, CTest updates the status of the test automatically when the test results are available. Test reports are published on a secured web-page enabling regular status checks also by patients not using smartphones with dedicated mobile apps which has some importance as smartphone usage diminishes with age. The source code, as well as further information to integrate CTest into the IT environment of other clinics or test-centres, are freely available from https://github.com/sysbio-bioinf/CTest under the Eclipse Public License v2.0 (EPL2).Competing Interest StatementThe authors have declared no competing interest.Funding StatementKAK, HAK and OK acknowledge, funding from the Germany Federal Ministry of Education and Research (BMBF) as part of the DIFUTURE project (Medical Informatics Initiative, grant numbers 01ZZ1804I and 01ZZ1804D). OK and HAK acknowledge funding from the Ministry of Science and Art Baden-Württemberg (Zentrum für Innovative Versorgung, ZIV). OK and TS acknowledge funding from the Ministry of Social Affairs of the state of Baden-Württemberg (Zentren für Personalisierte Medizin, ZPM), HAK also acknowledges funding from the German Science Foundation (DFG, grant number 217328187).Author DeclarationsAll relevant ethical guidelines have been followed; any necessary IRB and/or ethics committee approvals have been obtained and details of the IRB/oversight body are included in the manuscript.YesAll necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived.YesI understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance).Yes I have followed all appropriate research reporting guidelines and uploaded the relevant EQUATOR Network research reporting checklist(s) and other pertinent material as supplementary files, if applicable.YesA software is freely available from https://github.com/sysbio-bioinf/CTest under the Eclipse Public License v2.0 (EPL2).https://github.com/sysbio-bioinf/CTest}, keywords = {}, pubstate = {published}, tppubtype = {article} } Overcoming the COVID-19 crisis requires new ideas and strategies. Rapid testing of a large number of subjects is essential to monitor, and delay, the spread of SARS-CoV-2 to mitigate the consequences of the pandemic. People not knowing that they are infected may not stay in quarantine and, thus, are a risk for infecting others. Unfortunately, the massive number of COVID-19 tests performed is challenging for both laboratories and the units that take the throat swab and have to communicate test results. Here, we present a secure tracking system (CTest) to report COVID-19 test results online as soon as they become available. The system can be integrated into the clinical workflow with very modest effort and avoids excessive load to telephone hotlines. With this open-source and browser-based online tracking system, we aim to minimize the time required to inform the tested person but also the test units, e.g. hospitals or the public healthcare system. Instead of personal calls, CTest updates the status of the test automatically when the test results are available. Test reports are published on a secured web-page enabling regular status checks also by patients not using smartphones with dedicated mobile apps which has some importance as smartphone usage diminishes with age. The source code, as well as further information to integrate CTest into the IT environment of other clinics or test-centres, are freely available from https://github.com/sysbio-bioinf/CTest under the Eclipse Public License v2.0 (EPL2).Competing Interest StatementThe authors have declared no competing interest.Funding StatementKAK, HAK and OK acknowledge, funding from the Germany Federal Ministry of Education and Research (BMBF) as part of the DIFUTURE project (Medical Informatics Initiative, grant numbers 01ZZ1804I and 01ZZ1804D). OK and HAK acknowledge funding from the Ministry of Science and Art Baden-Württemberg (Zentrum für Innovative Versorgung, ZIV). OK and TS acknowledge funding from the Ministry of Social Affairs of the state of Baden-Württemberg (Zentren für Personalisierte Medizin, ZPM), HAK also acknowledges funding from the German Science Foundation (DFG, grant number 217328187).Author DeclarationsAll relevant ethical guidelines have been followed; any necessary IRB and/or ethics committee approvals have been obtained and details of the IRB/oversight body are included in the manuscript.YesAll necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived.YesI understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance).Yes I have followed all appropriate research reporting guidelines and uploaded the relevant EQUATOR Network research reporting checklist(s) and other pertinent material as supplementary files, if applicable.YesA software is freely available from https://github.com/sysbio-bioinf/CTest under the Eclipse Public License v2.0 (EPL2).https://github.com/sysbio-bioinf/CTest |
Jeong, K; Kim, J; Gaikwad, M; Hidayah, S N; Heikaus, L; Schl?ter, H; Kohlbacher, O FLASĦĐeconv: Ultrafast, Ħigh-Quality Feature Đeconvolution for Ŧop-Đown Proteomics Cell Syst, 10 (2), pp. 213–218, 2020. @article{pmid32078799, title = {FLASĦĐeconv: Ultrafast, Ħigh-Quality Feature Đeconvolution for Ŧop-Đown Proteomics}, author = {K Jeong and J Kim and M Gaikwad and S N Hidayah and L Heikaus and H Schl?ter and O Kohlbacher}, year = {2020}, date = {2020-01-01}, journal = {Cell Syst}, volume = {10}, number = {2}, pages = {213--218}, abstract = {Top-down mass spectrometry (TD-MS)-based proteomics analyzes intact proteoforms and thus preserves information about individual protein species. The MS signal of these high-mass analytes is complex and challenges the accurate determination of proteoform masses. Fast and accurate feature deconvolution (i.e., the determination of intact proteoform masses) is, therefore, an essential step for TD data analysis. Here, we present FLASHDeconv, an algorithm achieving higher deconvolution quality, with an execution speed two orders of magnitude faster than existing approaches. FLASHDeconv transforms peak positions (m/z) within spectra into log m/z space. This simple transformation turns the deconvolution problem into a search for constant patterns, thereby greatly accelerating the process. In both simple and complex samples, FLASHDeconv reports more genuine feature masses and substantially fewer artifacts than other existing methods. FLASHDeconv is freely available for download here: https://www.openms.org/flashdeconv/. A record of this paper's Transparent Peer Review process is included in the Supplemental Information.}, keywords = {}, pubstate = {published}, tppubtype = {article} } Top-down mass spectrometry (TD-MS)-based proteomics analyzes intact proteoforms and thus preserves information about individual protein species. The MS signal of these high-mass analytes is complex and challenges the accurate determination of proteoform masses. Fast and accurate feature deconvolution (i.e., the determination of intact proteoform masses) is, therefore, an essential step for TD data analysis. Here, we present FLASHDeconv, an algorithm achieving higher deconvolution quality, with an execution speed two orders of magnitude faster than existing approaches. FLASHDeconv transforms peak positions (m/z) within spectra into log m/z space. This simple transformation turns the deconvolution problem into a search for constant patterns, thereby greatly accelerating the process. In both simple and complex samples, FLASHDeconv reports more genuine feature masses and substantially fewer artifacts than other existing methods. FLASHDeconv is freely available for download here: https://www.openms.org/flashdeconv/. A record of this paper's Transparent Peer Review process is included in the Supplemental Information. |
Wein, S; Andrews, B; Sachsenberg, T; Santos-Rosa, H; Kohlbacher, O; Kouzarides, T; Garcia, B A; Weisser, H A computational platform for high-throughput analysis of RNA sequences and modifications by mass spectrometry Nat Commun, 11 (1), pp. 926, 2020. @article{pmid32066737, title = {A computational platform for high-throughput analysis of RNA sequences and modifications by mass spectrometry}, author = {S Wein and B Andrews and T Sachsenberg and H Santos-Rosa and O Kohlbacher and T Kouzarides and B A Garcia and H Weisser}, year = {2020}, date = {2020-01-01}, journal = {Nat Commun}, volume = {11}, number = {1}, pages = {926}, abstract = {The field of epitranscriptomics continues to reveal how post-transcriptional modification of RNA affects a wide variety of biological phenomena. A pivotal challenge in this area is the identification of modified RNA residues within their sequence contexts. Mass spectrometry (MS) offers a comprehensive solution by using analogous approaches to shotgun proteomics. However, software support for the analysis of RNA MS data is inadequate at present and does not allow high-throughput processing. Existing software solutions lack the raw performance and statistical grounding to efficiently handle the numerous modifications found on RNA. We present a free and open-source database search engine for RNA MS data, called NucleicAcidSearchEngine (NASE), that addresses these shortcomings. We demonstrate the capability of NASE to reliably identify a wide range of modified RNA sequences in four original datasets of varying complexity. In human tRNA, we characterize over 20 different modification types simultaneously and find many cases of incomplete modification.}, keywords = {}, pubstate = {published}, tppubtype = {article} } The field of epitranscriptomics continues to reveal how post-transcriptional modification of RNA affects a wide variety of biological phenomena. A pivotal challenge in this area is the identification of modified RNA residues within their sequence contexts. Mass spectrometry (MS) offers a comprehensive solution by using analogous approaches to shotgun proteomics. However, software support for the analysis of RNA MS data is inadequate at present and does not allow high-throughput processing. Existing software solutions lack the raw performance and statistical grounding to efficiently handle the numerous modifications found on RNA. We present a free and open-source database search engine for RNA MS data, called NucleicAcidSearchEngine (NASE), that addresses these shortcomings. We demonstrate the capability of NASE to reliably identify a wide range of modified RNA sequences in four original datasets of varying complexity. In human tRNA, we characterize over 20 different modification types simultaneously and find many cases of incomplete modification. |