Publications
Kohlbacher, Oliver; Burchardt, Andreas; Moll, Andreas; Hildebrandt, Andreas; Bayer, Peter; Lenhof, Hans-Peter Structure prediction of protein complexes by a NMR-based protein docking algorithm J. Biomol. NMR, 20 , pp. 15-21, 2001. @article{articleKBM2001, title = {Structure prediction of protein complexes by a NMR-based protein docking algorithm}, author = {Oliver Kohlbacher and Andreas Burchardt and Andreas Moll and Andreas Hildebrandt and Peter Bayer and Hans-Peter Lenhof}, url = {https://link.springer.com/article/10.1023/A:1011216130486}, year = {2001}, date = {2001-01-01}, journal = {J. Biomol. NMR}, volume = {20}, pages = {15-21}, abstract = {Protein docking algorithms can be used to study the driving forces and reaction mechanisms of docking processes. They are also able to speed up the lengthy process of experimental structure elucidation of protein complexes by proposing potential structures. In this paper, we are discussing a variant of the protein-protein docking problem, where the input consists of the tertiary structures of proteins A and B plus an unassigned one-dimensional 1H-NMR spectrum of the complex AB. We present a new scoring function for evaluating and ranking potential complex structures produced by a docking algorithm. The scoring function computes a `theoretical' 1H-NMR spectrum for each tentative complex structure and subtracts the calculated spectrum from the experimental one. The absolute areas of the difference spectra are then used to rank the potential complex structures. In contrast to formerly published approaches (e.g. [Morelli et al. (2000) Biochemistry, 39, 2530–2537]) we do not use distance constraints (intermolecular NOE constraints). We have tested the approach with four protein complexes whose three-dimensional structures are stored in the PDB data bank [Bernstein et al. (1977)] and whose 1H-NMR shift assignments are available from the BMRB database. The best result was obtained for an example, where all standard scoring functions failed completely. Here, our new scoring function achieved an almost perfect separation between good approximations of the true complex structure and false positives.}, keywords = {}, pubstate = {published}, tppubtype = {article} } Protein docking algorithms can be used to study the driving forces and reaction mechanisms of docking processes. They are also able to speed up the lengthy process of experimental structure elucidation of protein complexes by proposing potential structures. In this paper, we are discussing a variant of the protein-protein docking problem, where the input consists of the tertiary structures of proteins A and B plus an unassigned one-dimensional 1H-NMR spectrum of the complex AB. We present a new scoring function for evaluating and ranking potential complex structures produced by a docking algorithm. The scoring function computes a `theoretical' 1H-NMR spectrum for each tentative complex structure and subtracts the calculated spectrum from the experimental one. The absolute areas of the difference spectra are then used to rank the potential complex structures. In contrast to formerly published approaches (e.g. [Morelli et al. (2000) Biochemistry, 39, 2530–2537]) we do not use distance constraints (intermolecular NOE constraints). We have tested the approach with four protein complexes whose three-dimensional structures are stored in the PDB data bank [Bernstein et al. (1977)] and whose 1H-NMR shift assignments are available from the BMRB database. The best result was obtained for an example, where all standard scoring functions failed completely. Here, our new scoring function achieved an almost perfect separation between good approximations of the true complex structure and false positives. |
Turner, Russell J; Chaturvedi, Kabir; Edwards, Nathan J; Fasulo, Daniel; Halpern, Aaron L; Huson, Daniel H; Remington, Karin A; Schwartz, Russell; Walenz, Brian; Yooseph, Shibu; Istrail, Sorin Visualization Challenges for a New Cyberpharmaceutical Computing Paradigm Proceedings of the IEEE Symposium on Parallel and Large-Data Visualization and Graphics (PVG2001), pp. 7–18, San Diego, USA,, 2001. (BibTeX) @inproceedings{procTur2001, title = {Visualization Challenges for a New Cyberpharmaceutical Computing Paradigm}, author = {Russell J Turner and Kabir Chaturvedi and Nathan J Edwards and Daniel Fasulo and Aaron L Halpern and Daniel H Huson and Karin A Remington and Russell Schwartz and Brian Walenz and Shibu Yooseph and Sorin Istrail}, year = {2001}, date = {2001-01-01}, booktitle = {Proceedings of the IEEE Symposium on Parallel and Large-Data Visualization and Graphics (PVG2001)}, pages = {7--18}, address = {San Diego, USA,}, keywords = {}, pubstate = {published}, tppubtype = {inproceedings} } |
Kohlbacher, Oliver; Burchardt, Andreas; Hildebrandt, Andreas; Moll, Andreas; Bayer, Peter; Lenhof, Hans-Peter A NMR-spectra-based scoring function for protein docking Sankoff, David; Lengauer, Thomas (Ed.): RECOMB 2001, Proceedings of the Fifth Annual International Conference on Computational Molecular Biology, pp. 169-177, ACM press, 2001. @inproceedings{KBHMBL2000, title = {A NMR-spectra-based scoring function for protein docking}, author = {Oliver Kohlbacher and Andreas Burchardt and Andreas Hildebrandt and Andreas Moll and Peter Bayer and Hans-Peter Lenhof}, editor = {David Sankoff and Thomas Lengauer}, url = {http://portal.acm.org/citation.cfm?doid=369133.369194}, year = {2001}, date = {2001-01-01}, booktitle = {RECOMB 2001, Proceedings of the Fifth Annual International Conference on Computational Molecular Biology}, pages = {169-177}, publisher = {ACM press}, keywords = {}, pubstate = {published}, tppubtype = {inproceedings} } |
Kohlbacher, Oliver BALL - A Framework for Rapid Application Development in Molecular Modeling Beiträge zum Heinz-Billing-Preis 2000, pp. 13-28, Gesellschaft für wissenschaftliche Datenverarbeitung mbH, Göttingen, 2001. @incollection{Koh2000, title = {BALL - A Framework for Rapid Application Development in Molecular Modeling}, author = {Oliver Kohlbacher}, url = {http://www.billingpreis.mpg.de/hbp00/kohlbacher.pdf}, year = {2001}, date = {2001-01-01}, booktitle = {Beiträge zum Heinz-Billing-Preis 2000}, pages = {13-28}, publisher = {Gesellschaft für wissenschaftliche Datenverarbeitung mbH}, address = {Göttingen}, keywords = {}, pubstate = {published}, tppubtype = {incollection} } |
Neumann, Dirk; Kohlbacher, Oliver; Haltner, Eleonore; Lenhof, Hans-Peter; Lehr, Claus-Michael Modeling the Sugar Lectin Interaction by Computational Chemistry Relevant to Drug Design Proc. 3rd World Meeting on Pharmaceutics, Biopharmaceutics and Pharmaceutical Technology, pp. 233, 2000. (BibTeX) @inproceedings{procNKH2000, title = {Modeling the Sugar Lectin Interaction by Computational Chemistry Relevant to Drug Design}, author = {Dirk Neumann and Oliver Kohlbacher and Eleonore Haltner and Hans-Peter Lenhof and Claus-Michael Lehr}, year = {2000}, date = {2000-01-01}, booktitle = {Proc. 3rd World Meeting on Pharmaceutics, Biopharmaceutics and Pharmaceutical Technology}, pages = {233}, keywords = {}, pubstate = {published}, tppubtype = {inproceedings} } |
Kohlbacher, Oliver; Lenhof, Hans-Peter BALL - Rapid Software Prototyping in Computational Molecular Biology Bioinformatics, 16 (9,), pp. 815–824, 2000. @article{articleKL2000, title = {BALL - Rapid Software Prototyping in Computational Molecular Biology}, author = {Oliver Kohlbacher and Hans-Peter Lenhof}, url = {https://www.ncbi.nlm.nih.gov/pubmed/11108704}, year = {2000}, date = {2000-01-01}, journal = {Bioinformatics}, volume = {16}, number = {9,}, pages = {815--824}, abstract = {MOTIVATION: Rapid software prototyping can significantly reduce development times in the field of computational molecular biology and molecular modeling. Biochemical Algorithms Library (BALL) is an application framework in C++ that has been specifically designed for this purpose. RESULTS: BALL provides an extensive set of data structures as well as classes for molecular mechanics, advanced solvation methods, comparison and analysis of protein structures, file import/export, and visualization. BALL has been carefully designed to be robust, easy to use, and open to extensions. Especially its extensibility which results from an object-oriented and generic programming approach distinguishes it from other software packages. BALL is well suited to serve as a public repository for reliable data structures and algorithms. We show in an example that the implementation of complex methods is greatly simplified when using the data structures and functionality provided by BALL.}, keywords = {}, pubstate = {published}, tppubtype = {article} } MOTIVATION: Rapid software prototyping can significantly reduce development times in the field of computational molecular biology and molecular modeling. Biochemical Algorithms Library (BALL) is an application framework in C++ that has been specifically designed for this purpose. RESULTS: BALL provides an extensive set of data structures as well as classes for molecular mechanics, advanced solvation methods, comparison and analysis of protein structures, file import/export, and visualization. BALL has been carefully designed to be robust, easy to use, and open to extensions. Especially its extensibility which results from an object-oriented and generic programming approach distinguishes it from other software packages. BALL is well suited to serve as a public repository for reliable data structures and algorithms. We show in an example that the implementation of complex methods is greatly simplified when using the data structures and functionality provided by BALL. |
Boghossian, N P; Kohlbacher, O; Lenhof, H P Rapid software prototyping in molecular modeling using the biochemical algorithms library (BALL) J. Exp. Algorithmics, 5 , pp. 16, 2000. (BibTeX) @article{articleBKL2000, title = {Rapid software prototyping in molecular modeling using the biochemical algorithms library (BALL)}, author = {N P Boghossian and O Kohlbacher and H P Lenhof}, year = {2000}, date = {2000-01-01}, journal = {J. Exp. Algorithmics}, volume = {5}, pages = {16}, keywords = {}, pubstate = {published}, tppubtype = {article} } |
Althaus, Ernst; Kohlbacher, Oliver; Lenhof, Hans-Peter; Müller, Peter A Combinatorial Approach to Protein Docking with Flexible Side-Chains Shamir, Ron; Miyano, Satoru; Istrail, Sorin; Pevzner, Pavel; Waterman, Michael (Ed.): RECOMB 2000 -- Proceedings of the Fourth Annual International Conference on Computational Molecular Biology, pp. 15–24, ACM press, 2000. (BibTeX) @inproceedings{procAKL2000, title = {A Combinatorial Approach to Protein Docking with Flexible Side-Chains}, author = {Ernst Althaus and Oliver Kohlbacher and Hans-Peter Lenhof and Peter Müller}, editor = {Ron Shamir and Satoru Miyano and Sorin Istrail and Pavel Pevzner and Michael Waterman}, year = {2000}, date = {2000-01-01}, booktitle = {RECOMB 2000 -- Proceedings of the Fourth Annual International Conference on Computational Molecular Biology}, pages = {15--24}, publisher = {ACM press}, keywords = {}, pubstate = {published}, tppubtype = {inproceedings} } |
Althaus, Ernst; Kohlbacher, Oliver; Lenhof, Hans-Peter; Müller, Peter A branch and cut algorithm for the optimal solution of the side-chain placement problem Max-Planck-Institute für Informatik Stuhlsatzenhausweg 85, 66123 Saarbrücken, Germany, (MPI-I-2000-1-001), 2000. @techreport{AKLM2000, title = {A branch and cut algorithm for the optimal solution of the side-chain placement problem}, author = {Ernst Althaus and Oliver Kohlbacher and Hans-Peter Lenhof and Peter Müller}, url = {http://domino.mpi-sb.mpg.de/internet/reports.nsf/NumberView/2000-1-001}, year = {2000}, date = {2000-01-01}, number = {MPI-I-2000-1-001}, address = {Stuhlsatzenhausweg 85, 66123 Saarbrücken, Germany}, institution = {Max-Planck-Institute für Informatik}, keywords = {}, pubstate = {published}, tppubtype = {techreport} } |
Kohlbacher, O; Lenhof, H -P Rapid Software Prototyping in Computational Molecular Biology Proceedings of the German Conference on Bioinformatics (GCB'99), 1999. (BibTeX) @inproceedings{procKL1999, title = {Rapid Software Prototyping in Computational Molecular Biology}, author = {O Kohlbacher and H -P Lenhof}, year = {1999}, date = {1999-01-01}, booktitle = {Proceedings of the German Conference on Bioinformatics (GCB'99)}, keywords = {}, pubstate = {published}, tppubtype = {inproceedings} } |
Boghossian, Nicolas Pascal; Kohlbacher, Oliver; Lenhof, Hans-Peter BALL: Biochemical Algorithms Library Vitter, J S; Zaroliagis, C D (Ed.): Algorithm Engineering, 3rd International Workshop, WAE'99, Proceedings, pp. 330-344, Springer, 1999. (BibTeX) @incollection{BKL1999b, title = {BALL: Biochemical Algorithms Library}, author = {Nicolas Pascal Boghossian and Oliver Kohlbacher and Hans-Peter Lenhof}, editor = {J S Vitter and C D Zaroliagis}, year = {1999}, date = {1999-01-01}, booktitle = {Algorithm Engineering, 3rd International Workshop, WAE'99, Proceedings}, pages = {330-344}, publisher = {Springer}, keywords = {}, pubstate = {published}, tppubtype = {incollection} } |
Boghossian, Nicolas Pascal; Kohlbacher, Oliver; Lenhof, Hans-Peter BALL: Biochemical Algorithms Library Max-Planck-Institut für Informatik Saarbrücken, Germany, (MPI-I-99-1-002), 1999. @techreport{BKL1999a, title = {BALL: Biochemical Algorithms Library}, author = {Nicolas Pascal Boghossian and Oliver Kohlbacher and Hans-Peter Lenhof}, url = {http://domino.mpi-sb.mpg.de/internet/reports.nsf/NumberView/1999-1-002}, year = {1999}, date = {1999-01-01}, number = {MPI-I-99-1-002}, address = {Saarbrücken, Germany}, institution = {Max-Planck-Institut für Informatik}, keywords = {}, pubstate = {published}, tppubtype = {techreport} } |
Neumann, Dirk; Haltner, Elleonore; Lehr, Claus-Michael; Kohlbacher, Oliver; Lenhof, Hans-Peter Investigating the Sugar-Lectin Interaction by Computational Chemistry: Tunneling the Epithelial Barrier Abstracts of the 18th Interlec Meeting, pp. 549, 1998. (BibTeX) @inproceedings{procNHL1998, title = {Investigating the Sugar-Lectin Interaction by Computational Chemistry: Tunneling the Epithelial Barrier}, author = {Dirk Neumann and Elleonore Haltner and Claus-Michael Lehr and Oliver Kohlbacher and Hans-Peter Lenhof}, year = {1998}, date = {1998-01-01}, booktitle = {Abstracts of the 18th Interlec Meeting}, pages = {549}, keywords = {}, pubstate = {published}, tppubtype = {inproceedings} } |
Friedrich, Andreas; de la Garza, Luis; Kohlbacher, Oliver 0000. (BibTeX) @proceedings{MultiFactorial_DILS2018, author = {Andreas Friedrich and Luis de la Garza and Oliver Kohlbacher}, keywords = {}, pubstate = {published}, tppubtype = {proceedings} } |
Lara Schneider Tim Kehl, Kristina Thedinga Nadja Grammes Christina Backes Christopher Mohr Benjamin Schubert Kerstin Lenhof Nico Gerstner Andreas Daniel Hartkopf Markus Wallwiener Oliver Kohlbacher Andreas Keller Eckart Meese Norbert Graf Hans-Peter Lenhof L ClinOmicsTrailbc: a visual analytics tool for breast cancer treatment stratification Bioinformatics, Forthcoming. (BibTeX) @article{SchneiderClinOmics2019, title = {ClinOmicsTrailbc: a visual analytics tool for breast cancer treatment stratification}, author = {Lara Schneider, Tim Kehl, Kristina Thedinga, Nadja L. Grammes, Christina Backes, Christopher Mohr, Benjamin Schubert, Kerstin Lenhof, Nico Gerstner, Andreas Daniel Hartkopf, Markus Wallwiener, Oliver Kohlbacher, Andreas Keller, Eckart Meese, Norbert Graf, Hans-Peter Lenhof}, journal = {Bioinformatics}, keywords = {}, pubstate = {forthcoming}, tppubtype = {article} } |
Bernadette Richter Marc Rurik, Stephanie Gurk Oliver Kohlbacher Markus Fischer Food monitoring: Screening of the geographical origin of white asparagus using FT-NIR and machine learning Food Control, Forthcoming. (BibTeX) @article{Richter2019, title = {Food monitoring: Screening of the geographical origin of white asparagus using FT-NIR and machine learning}, author = {Bernadette Richter, Marc Rurik, Stephanie Gurk, Oliver Kohlbacher, Markus Fischer}, journal = {Food Control}, keywords = {}, pubstate = {forthcoming}, tppubtype = {article} } |
Choobdar, Sarvenaz; Ahsen, Mehmet E; Crawford, Jake; Tomasoni, Mattia; Fang, Tao; Lamparter, David; Lin, Junyuan; Hescott, Benjamin; Hu, Xiaozhe; Mercer, Johnathan; Natoli, Ted; Narayan, Rajiv; and Subramanian, Aravind; Zhang, Jitao D; Stolovitzky, Gustavo; Kutalik, Zoltán; Lage, Kasper; Slonim, Donna K; Saez-Rodriguez, Julio; Cowen, Lenore J; Bergmann, Sven; Marbach, Daniel Assessment of network module identification across complex diseases Nat. Methods, 16 , pp. 843–852, 0000. @article{Choobdar265553b, title = {Assessment of network module identification across complex diseases}, author = {Sarvenaz Choobdar and Mehmet E Ahsen and Jake Crawford and Mattia Tomasoni and Tao Fang and David Lamparter and Junyuan Lin and Benjamin Hescott and Xiaozhe Hu and Johnathan Mercer and Ted Natoli and Rajiv Narayan and and Aravind Subramanian and Jitao D Zhang and Gustavo Stolovitzky and Zoltán Kutalik and Kasper Lage and Donna K Slonim and Julio Saez-Rodriguez and Lenore J Cowen and Sven Bergmann and Daniel Marbach}, url = {https://www.nature.com/articles/s41592-019-0509-5.pdf}, doi = {10.1038/s41592-019-0509-5}, journal = {Nat. Methods}, volume = {16}, pages = {843–852}, publisher = {Cold Spring Harbor Laboratory}, abstract = {Identification of modules in molecular networks is at the core of many current analysis methods in biomedical research. However, how well different approaches identify disease-relevant modules in different types of gene and protein networks remains poorly understood. We launched the textquotedblleftDisease Module Identification DREAM Challengetextquotedblright, an open competition to comprehensively assess module identification methods across diverse protein-protein interaction, signaling, gene co-expression, homology, and cancer-gene networks. Predicted network modules were tested for association with complex traits and diseases using a unique collection of 180 genome-wide association studies (GWAS). Our critical assessment of 75 contributed module identification methods reveals novel top-performing algorithms, which recover complementary trait-associated modules. We find that most of these modules correspond to core disease-relevant pathways, which often comprise therapeutic targets and correctly prioritize candidate disease genes. This community challenge establishes benchmarks, tools and guidelines for molecular network analysis to study human disease biology (https://synapse.org/modulechallenge).}, keywords = {}, pubstate = {published}, tppubtype = {article} } Identification of modules in molecular networks is at the core of many current analysis methods in biomedical research. However, how well different approaches identify disease-relevant modules in different types of gene and protein networks remains poorly understood. We launched the textquotedblleftDisease Module Identification DREAM Challengetextquotedblright, an open competition to comprehensively assess module identification methods across diverse protein-protein interaction, signaling, gene co-expression, homology, and cancer-gene networks. Predicted network modules were tested for association with complex traits and diseases using a unique collection of 180 genome-wide association studies (GWAS). Our critical assessment of 75 contributed module identification methods reveals novel top-performing algorithms, which recover complementary trait-associated modules. We find that most of these modules correspond to core disease-relevant pathways, which often comprise therapeutic targets and correctly prioritize candidate disease genes. This community challenge establishes benchmarks, tools and guidelines for molecular network analysis to study human disease biology (https://synapse.org/modulechallenge). |
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., Forthcoming. (BibTeX) @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}, journal = {Nat. Commun.}, keywords = {}, pubstate = {forthcoming}, tppubtype = {article} } |
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, Forthcoming, 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}, journal = {Cell Systems}, 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 = {forthcoming}, 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. |
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 COVIĐ-19 Is Marked by a Đysregulated Myeloid Cell Compartment Cell, 0000. @article{pmid32810438, title = {Severe COVIĐ-19 Is Marked by a Đysregulated 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}, journal = {Cell}, 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. |