Publications

@article{nokey,

title = {Magnipore: Prediction of differential single nucleotide changes in the Oxford Nanopore Technologies sequencing signal of SARS-CoV-2 samples},

author = {Jannes Spangenberg and Christian {Höner zu Siederdissen} and Milena Žarković and Sandra Triebel and Ruben Rose and Christina Martínez Christophersen and Lea Paltzow and Mohsen M. Hegab and Anna Wansorra and Akash Srivastava and Andi Krumbholz and Manja Marz},

doi = {10.1101/2023.03.17.533105},

year  = {2023},

date = {2023-03-17},

urldate = {2023-03-17},

journal = {bioRxiv},

abstract = {Oxford Nanopore Technologies (ONT) allows direct sequencing of ribonucleic acids (RNA) and, in addition, detection of possible RNA modifications due to deviations from the expected ONT signal. The software available so far for this purpose can only detect a small number of modifications. Alternatively, two samples can be compared for different RNA modifications. We present Magnipore, a novel tool to search for significant signal shifts between samples of Oxford Nanopore data from similar or related species. Magnipore classifies them into mutations and potential modifications. We use Magnipore to compare SARS-CoV-2 samples. Included were representatives of the early 2020s Pango lineages (n=6), samples from Pango lineages B.1.1.7 (n=2, Alpha), B.1.617.2 (n=1, Delta), and B.1.529 (n=7, Omicron). Magnipore utilizes position-wise Gaussian distribution models and a comprehensible significance threshold to find differential signals. In the case of Alpha and Delta, Magnipore identifies 55 detected mutations and 15 sites that hint at differential modifications. We predicted potential virus-variant and variant-group-specific differential modifications. Magnipore contributes to advancing RNA modification analysis in the context of viruses and virus variants.},

keywords = {coronavirus, nanopore, nucleic acid modifications, RNA / transcriptomics, software, viruses},

pubstate = {published},

tppubtype = {article}

}

@article{nokey,

title = {Genome Structure, Life Cycle, and Taxonomy of Coronaviruses and the Evolution of SARS-CoV-2},

author = {Kevin Lamkiewicz and Luis Roger Esquivel Gomez and Denise Kühnert and Manja Marz

},

doi = {10.1007/978-3-031-15640-3_9},

year  = {2023},

date = {2023-01-03},

journal = {Curr Top Microbiol Immunol},

volume = {439},

pages = {305-339},

abstract = {Coronaviruses have a broad host range and exhibit high zoonotic potential. In this chapter, we describe their genomic organization in terms of encoded proteins and provide an introduction to the peculiar discontinuous transcription mechanism. Further, we present evolutionary conserved genomic RNA secondary structure features, which are involved in the complex replication mechanism. With a focus on computational methods, we review the emergence of SARS-CoV-2 starting with the 2019 strains. In that context, we also discuss the debated hypothesis of whether SARS-CoV-2 was created in a laboratory. We focus on the molecular evolution and the epidemiological dynamics of this recently emerged pathogen and we explain how variants of concern are detected and characterised. COVID-19, the disease caused by SARS-CoV-2, can spread through different transmission routes and also depends on a number of risk factors. We describe how current computational models of viral epidemiology, or more specifically, phylodynamics, have facilitated and will continue to enable a better understanding of the epidemic dynamics of SARS-CoV-2.},

keywords = {coronavirus, DNA / genomics, evolution, phylogenetics, RNA / transcriptomics},

pubstate = {published},

tppubtype = {article}

}

@article{nokey,

title = {Integrated genomic surveillance enables tracing of person-to-person SARS-CoV-2 transmission chains during community transmission and reveals extensive onward transmission of travel-imported infections, Germany, June to July 2021},

author = {Torsten Houwaart and Samir Belhaj and Emran Tawalbeh and Dirk Nagels and Yara Fröhlich and Patrick Finzer and Pilar Ciruela and Aurora Sabrià and Mercè Herrero and Cristina Andrés and Andrés Antón and Assia Benmoumene and Dounia Asskali and Hussein Haidar and Janina von Dahlen and Jessica Nicolai and Mygg Stiller and Jacqueline Blum and Christian Lange and Carla Adelmann and Britta Schroer and Ute Osmers and Christiane Grice and Phillipp P Kirfel and Hassan Jomaa and Daniel Strelow and Lisanna Hülse and Moritz Pigulla and Pascal Kreuzer and Alona Tyshaieva and Jonas Weber and Tobias Wienemann and Malte Kohns Vasconcelos and Katrin Hoffmann and Nadine Lübke and Sandra Hauka and Marcel Andree and Claus Jürgen Scholz and Nathalie Jazmati and Klaus Göbels and Rainer Zotz and Klaus Pfeffer and Jörg Timm and Lutz Ehlkes and Andreas Walker and Alexander T Dilthey and Deutsche COVID-19 OMICS Initiative (DeCOI)},

doi = {10.2807/1560-7917.ES.2022.27.43.2101089},

year  = {2022},

date = {2022-10-27},

urldate = {2022-10-27},

journal = {Euro Surveill},

volume = {27},

issue = {43},

pages = {2101089},

abstract = {BackgroundTracking person-to-person SARS-CoV-2 transmission in the population is important to understand the epidemiology of community transmission and may contribute to the containment of SARS-CoV-2. Neither contact tracing nor genomic surveillance alone, however, are typically sufficient to achieve this objective.AimWe demonstrate the successful application of the integrated genomic surveillance (IGS) system of the German city of Düsseldorf for tracing SARS-CoV-2 transmission chains in the population as well as detecting and investigating travel-associated SARS-CoV-2 infection clusters.MethodsGenomic surveillance, phylogenetic analysis, and structured case interviews were integrated to elucidate two genetically defined clusters of SARS-CoV-2 isolates detected by IGS in Düsseldorf in July 2021.ResultsCluster 1 (n = 67 Düsseldorf cases) and Cluster 2 (n = 36) were detected in a surveillance dataset of 518 high-quality SARS-CoV-2 genomes from Düsseldorf (53% of total cases, sampled mid-June to July 2021). Cluster 1 could be traced back to a complex pattern of transmission in nightlife venues following a putative importation by a SARS-CoV-2-infected return traveller (IP) in late June; 28 SARS-CoV-2 cases could be epidemiologically directly linked to IP. Supported by viral genome data from Spain, Cluster 2 was shown to represent multiple independent introduction events of a viral strain circulating in Catalonia and other European countries, followed by diffuse community transmission in Düsseldorf.ConclusionIGS enabled high-resolution tracing of SARS-CoV-2 transmission in an internationally connected city during community transmission and provided infection chain-level evidence of the downstream propagation of travel-imported SARS-CoV-2 cases.},

keywords = {coronavirus, nanopore, RNA / transcriptomics, viruses},

pubstate = {published},

tppubtype = {article}

}

@article{nokey,

title = {SARS-CoV-2 infection triggers profibrotic macrophage responses and lung fibrosis},

author = {Daniel Wendisch and Oliver Dietrich and Tommaso Mari and Saskia von Stillfried and Ignacio L. Ibarra and Mirja Mittermaier and Christin Mache and Robert Lorenz Chua and Rainer Knoll and Sara Timm and Sophia Brumhard and Tobias Krammer and Henrik Zauber and Anna Luisa Hiller and Anna Pascual-Reguant and Ronja Mothes and Roman David Bülow and Jessica Schulze and Alexander M. Leipold and Sonja Djudjaj and Florian Erhard and Robert Geffers and Fabian Pott and Julia Kazmierski and Josefine Radke and Panagiotis Pergantis and Kevin Baßler and Claudia Conrad and Anna C. Aschenbrenner and Birgit Sawitzki and Markus Landthaler and Emanuel Wyler and David Horst and Deutsche COVID-19 OMICS Initiative (DeCOI) and Stefan Hippenstiel and Andreas Hocke and Frank L. Heppner and Alexander Uhrig and Carmen Garcia and Felix Machleidt and Susanne Herold and Sefer Elezkurtaj and Charlotte Thibeault and Martin Witzenrath and Clément Cochain and Norbert Suttorp and Christian Drosten and Christine Goffinet and Florian Kurth and Joachim L. Schultze and Helena Radbruch and Matthias Ochs and Roland Eils and Holger Müller-Redetzky and Anja E. Hauser and Malte D. Luecken and Fabian J. Theis and Christian Conrad and Thorsten Wolff and Peter Boor and Matthias Selbach and Antoine-Emmanuel Saliba and Leif Erik Sander},

doi = {10.1016/j.cell.2021.11.033},

year  = {2021},

date = {2021-12-22},

journal = {Cell},

volume = {184},

number = {26},

pages = { 6243-6261},

abstract = {COVID-19-induced "acute respiratory distress syndrome" (ARDS) is associated with prolonged respiratory failure and high mortality, but the mechanistic basis of lung injury remains incompletely understood. Here, we analyze pulmonary immune responses and lung pathology in two cohorts of patients with COVID-19 ARDS using functional single-cell genomics, immunohistology, and electron microscopy. We describe an accumulation of CD163-expressing monocyte-derived macrophages that acquired a profibrotic transcriptional phenotype during COVID-19 ARDS. Gene set enrichment and computational data integration revealed a significant similarity between COVID-19-associated macrophages and profibrotic macrophage populations identified in idiopathic pulmonary fibrosis. COVID-19 ARDS was associated with clinical, radiographic, histopathological, and ultrastructural hallmarks of pulmonary fibrosis. Exposure of human monocytes to SARS-CoV-2, but not influenza A virus or viral RNA analogs, was sufficient to induce a similar profibrotic phenotype in vitro. In conclusion, we demonstrate that SARS-CoV-2 triggers profibrotic macrophage responses and pronounced fibroproliferative ARDS.},

keywords = {coronavirus, virus host interaction, viruses},

pubstate = {published},

tppubtype = {article}

}

@article{nokey,

title = {Early IFN-α signatures and persistent dysfunction are distinguishing features of NK cells in severe COVID-19},

author = {Benjamin Krämer and Rainer Knoll and Lorenzo Bonaguro and Michael ToVinh and Jan Raabe and Rosario Astaburuaga-García and Jonas Schulte-Schrepping and Kim Melanie Kaiser and Gereon J. Rieke and Jenny Bischoff and Malte B. Monin and Christoph Hoffmeister and Stefan Schlabe and Elena De Domenico and Nico Reusch and Kristian Händler and Gary Reynolds and Nils Blüthgen and Gudrun Hack and Claudia Finnemann and Hans D. Nischalke and Christian P. Strassburg and Emily Stephenson and Yapeng Su and Louis Gardner and Dan Yuan and Daniel Chen and Jason Goldman and Philipp Rosenstiel and Susanne V. Schmidt and Eicke Latz and Kevin Hrusovsky and Andrew J. Ball and Joe M. Johnson and Paul-Albert Koenig and Florian I. Schmidt and Muzlifah Haniffa and James R. Heath and Beate M. Kümmerer and Verena Keitel and Björn Jensen and Paula Stubbemann and Florian Kurth and Leif E. Sander and Birgit Sawitzki and Deutsche COVID-19 OMICS Initiative (DeCOI) and Anna C. Aschenbrenner and Joachim L. Schultze and Jacob Nattermann },

doi = {10.1016/j.immuni.2021.09.002},

year  = {2021},

date = {2021-09-04},

urldate = {2021-09-04},

journal = {Immunity},

volume = {S1074-7613},

number = {21},

pages = {00365-4},

abstract = {Longitudinal analyses of the innate immune system, including the earliest time points, are essential to understand the immunopathogenesis and clinical course of coronavirus disease (COVID-19). Here, we performed a detailed characterization of natural killer (NK) cells in 205 patients (403 samples; days 2 to 41 after symptom onset) from four independent cohorts using single-cell transcriptomics and proteomics together with functional studies. We found elevated interferon (IFN)-α plasma levels in early severe COVD-19 alongside increased NK cell expression of IFN-stimulated genes (ISGs) and genes involved in IFN-α signaling, while upregulation of tumor necrosis factor (TNF)-induced genes was observed in moderate diseases. NK cells exert anti-SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) activity but are functionally impaired in severe COVID-19. Further, NK cell dysfunction may be relevant for the development of fibrotic lung disease in severe COVID-19, as NK cells exhibited impaired anti-fibrotic activity. Our study indicates preferential IFN-α and TNF responses in severe and moderate COVID-19, respectively, and associates a prolonged IFN-α-induced NK cell response with poorer disease outcome.},

keywords = {coronavirus, viruses},

pubstate = {published},

tppubtype = {article}

}

@article{Brandt2021,

title = {poreCov - An Easy to Use, Fast, and Robust Workflow for SARS-CoV-2 Genome Reconstruction via Nanopore Sequencing},

author = {Christian Brandt and Sebastian Krautwurst and Riccardo Spott and Mara Lohde and Mateusz Jundzill and Mike Marquet and Martin Hölzer},

url = {https://github.com/replikation/poreCov},

doi = {10.3389/fgene.2021.711437},

year  = {2021},

date = {2021-07-28},

urldate = {2021-07-28},

journal = {Front Genet},

volume = {12},

pages = {711437},

abstract = {In response to the SARS-CoV-2 pandemic, a highly increased sequencing effort has been established worldwide to track and trace ongoing viral evolution. Technologies, such as nanopore sequencing via the ARTIC protocol are used to reliably generate genomes from raw sequencing data as a crucial base for molecular surveillance. However, for many labs that perform SARS-CoV-2 sequencing, bioinformatics is still a major bottleneck, especially if hundreds of samples need to be processed in a recurring fashion. Pipelines developed for short-read data cannot be applied to nanopore data. Therefore, specific long-read tools and parameter settings need to be orchestrated to enable accurate genotyping and robust reference-based genome reconstruction of SARS-CoV-2 genomes from nanopore data. Here we present poreCov, a highly parallel workflow written in Nextflow, using containers to wrap all the tools necessary for a routine SARS-CoV-2 sequencing lab into one program. The ease of installation, combined with concise summary reports that clearly highlight all relevant information, enables rapid and reliable analysis of hundreds of SARS-CoV-2 raw sequence data sets or genomes. poreCov is freely available on GitHub under the GNUv3 license: github.com/replikation/poreCov.},

keywords = {coronavirus, nanopore, RNA / transcriptomics, software, viruses},

pubstate = {published},

tppubtype = {article}

}

@article{Walker:21,

title = {Characterization of SARS-CoV-2 infection clusters based on integrated genomic surveillance, outbreak analysis and contact tracing in an urban setting},

author = {Andreas Walker and Torsten Houwaart and Patrick Finzer and Lutz Ehlkes and Alona Tyshaieva and Maximilian Damagnez and Daniel Strelow and Ashley Duplessis and Jessica Nicolai and Tobias Wienemann and Teresa Tamayo and Malte Kohns Vasconcelos and Lisanna Hülse and Katrin Hoffmann and Nadine Lübke and Sandra Hauka and Marcel Andree and Martin P Däumer and Alexander Thielen and Susanne Kolbe-Busch and Klaus Göbels and Rainer Zotz and Klaus Pfeffer and Jörg Timm and Alexander T Dilthey and Deutsche COVID-19 OMICS Initiative (DeCOI)},

doi = {10.1093/cid/ciab588},

year  = {2021},

date = {2021-06-28},

urldate = {2021-06-28},

journal = {Clin Infect Dis},

pages = {ciab588},

publisher = {Oxford University Press (OUP)},

abstract = {Background: Tracing of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission chains is still a major challenge for public health authorities, when incidental contacts are not recalled or are not perceived as potential risk contacts. Viral sequencing can address key questions about SARS-CoV-2 evolution and may support reconstruction of viral transmission networks by integration of molecular epidemiology into classical contact tracing.



Methods: In collaboration with local public health authorities, we set up an integrated system of genomic surveillance in an urban setting, combining a) viral surveillance sequencing, b) genetically based identification of infection clusters in the population, c) integration of public health authority contact tracing data, and d) a user-friendly dashboard application as a central data analysis platform.



Results: Application of the integrated system from August to December 2020 enabled a characterization of viral population structure, analysis of 4 outbreaks at a maximum care hospital, and genetically based identification of 5 putative population infection clusters, all of which were confirmed by contact tracing. The system contributed to the development of improved hospital infection control and prevention measures and enabled the identification of previously unrecognized transmission chains, involving a martial arts gym and establishing a link between the hospital to the local population.



Conclusions: Integrated systems of genomic surveillance could contribute to the monitoring and, potentially, improved management of SARS-CoV-2 transmission in the population.},

keywords = {coronavirus, evolution, nanopore, viruses},

pubstate = {published},

tppubtype = {article}

}

@article{nokey,

title = {SARS-CoV-2 infection paralyzes cytotoxic and metabolic functions of the immune cells},

author = {Yogesh Singh and Christoph Trautwein and Rolf Fendel and Naomi Krickeberg and Georgy Berezhnoy and Rosi Bissinger and Stephan Ossowski and Madhuri S Salker and Nicolas Casadei and Olaf Riess and Deutsche COVID-19 OMICS Initiative (DeCOI)},

doi = {10.1016/j.heliyon.2021.e07147},

year  = {2021},

date = {2021-05-28},

urldate = {2021-05-28},

journal = {Heliyon},

volume = {7},

number = {6},

pages = {e07147},

abstract = {The SARS-CoV-2 virus is the causative agent of the global COVID-19 infectious disease outbreak, which can lead to acute respiratory distress syndrome (ARDS). However, it is still unclear how the virus interferes with immune cell and metabolic functions in the human body. In this study, we investigated the immune response in acute or convalescent COVID-19 patients. We characterized the peripheral blood mononuclear cells (PBMCs) using flow cytometry and found that CD8+ T cells were significantly subsided in moderate COVID-19 and convalescent patients. Furthermore, characterization of CD8+ T cells suggested that convalescent patients have significantly diminished expression of both perforin and granzyme A. Using 1H-NMR spectroscopy, we characterized the metabolic status of their autologous PBMCs. We found that fructose, lactate and taurine levels were elevated in infected (mild and moderate) patients compared with control and convalescent patients. Glucose, glutamate, formate and acetate levels were attenuated in COVID-19 (mild and moderate) patients. In summary, our report suggests that SARS-CoV-2 infection leads to disrupted CD8+ T cytotoxic functions and changes the overall metabolic functions of immune cells.},

keywords = {coronavirus, viruses},

pubstate = {published},

tppubtype = {article}

}

@article{nokey,

title = {Swarm Learning for decentralized and confidential clinical machine learning},

author = {Stefanie Warnat-Herresthal and Hartmut Schultze and Krishnaprasad Lingadahalli Shastry and Sathyanarayanan Manamohan and Saikat Mukherjee and Vishesh Garg and Ravi Sarveswara and Kristian Händler and Peter Pickkers and N. Ahmad Aziz and Sofia Ktena and Florian Tran and Michael Bitzer and Stephan Ossowski and Nicolas Casadei and Christian Herr and Daniel Petersheim and Uta Behrends and Fabian Kern and Tobias Fehlmann and Philipp Schommers and Clara Lehmann and Max Augustin and Jan Rybniker and Janine Altmüller and Neha Mishra and Joana P. Bernardes and Benjamin Krämer and Lorenzo Bonaguro and Jonas Schulte-Schrepping and Elena De Domenico and Christian Siever and Michael Kraut and Milind Desai and Bruno Monnet and Maria Saridaki and Charles Martin Siegel and Anna Drews and Melanie Nuesch-Germano and Heidi Theis and Jan Heyckendorf and Stefan Schreiber and Sarah Kim-Hellmuth and COVID- Aachen Study (COVAS) and Jacob Nattermann and Dirk Skowasch and Ingo Kurth and Andreas Keller and Robert Bals and Peter Nürnberg and Olaf Rieß and Philip Rosenstiel and Mihai G. Netea and Fabian Theis and Sach Mukherjee and Michael Backes and Anna C. Aschenbrenner and Thomas Ulas and Deutsche COVID-19 Omics Initiative (DeCOI) and Monique M. B. Breteler and Evangelos J. Giamarellos-Bourboulis and Matthijs Kox and Matthias Becker and Sorin Cheran and Michael S. Woodacre and Eng Lim Goh and Joachim L. Schultze },

doi = {10.1038/s41586-021-03583-3},

year  = {2021},

date = {2021-05-26},

urldate = {2021-05-26},

journal = {Nature},

volume = {594},

number = {7862},

pages = {265-270},

abstract = {Fast and reliable detection of patients with severe and heterogeneous illnesses is a major goal of precision medicine1,2. Patients with leukaemia can be identified using machine learning on the basis of their blood transcriptomes3. However, there is an increasing divide between what is technically possible and what is allowed, because of privacy legislation4,5. Here, to facilitate the integration of any medical data from any data owner worldwide without violating privacy laws, we introduce Swarm Learning-a decentralized machine-learning approach that unites edge computing, blockchain-based peer-to-peer networking and coordination while maintaining confidentiality without the need for a central coordinator, thereby going beyond federated learning. To illustrate the feasibility of using Swarm Learning to develop disease classifiers using distributed data, we chose four use cases of heterogeneous diseases (COVID-19, tuberculosis, leukaemia and lung pathologies). With more than 16,400 blood transcriptomes derived from 127 clinical studies with non-uniform distributions of cases and controls and substantial study biases, as well as more than 95,000 chest X-ray images, we show that Swarm Learning classifiers outperform those developed at individual sites. In addition, Swarm Learning completely fulfils local confidentiality regulations by design. We believe that this approach will notably accelerate the introduction of precision medicine.



},

keywords = {coronavirus, machine learning, viruses},

pubstate = {published},

tppubtype = {article}

}

@article{nokey,

title = {Disease severity-specific neutrophil signatures in blood transcriptomes stratify COVID-19 patients},

author = {Anna C. Aschenbrenner and Maria Mouktaroudi and Benjamin Krämer and Marie Oestreich and Nikolaos Antonakos and Melanie Nuesch-Germano and Konstantina Gkizeli and Lorenzo Bonaguro and Nico Reusch and Kevin Baßler and Maria Saridaki and Rainer Knoll and Tal Pecht and Theodore S. Kapellos and Sarandia Doulou and Charlotte Kröger and Miriam Herbert and Lisa Holsten and Arik Horne and Ioanna D. Gemünd and Nikoletta Rovina and Shobhit Agrawal and Kilian Dahm and Martina van Uelft and Anna Drews and Lena Lenkeit and Niklas Bruse and Jelle Gerretsen and Jannik Gierlich and Matthias Becker and Kristian Händler and Michael Kraut and Heidi Theis and Simachew Mengiste and Elena De Domenico and Jonas Schulte-Schrepping and Lea Seep and Jan Raabe and Christoph Hoffmeister and Michael ToVinh and Verena Keitel and Gereon Rieke and Valentina Talevi and Dirk Skowasch and N. Ahmad Aziz and Peter Pickkers and Frank L. van de Veerdonk and Mihai G. Netea and Joachim L. Schultze and Matthijs Kox and Monique M. B. Breteler and Jacob Nattermann and Antonia Koutsoukou and Evangelos J. Giamarellos-Bourboulis and Thomas Ulas and Deutsche COVID-19 OMICS Initiative (DeCOI)},

doi = {10.1186/s13073-020-00823-5},

year  = {2021},

date = {2021-01-13},

urldate = {2021-01-13},

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 = {coronavirus, RNA / transcriptomics, viruses},

pubstate = {published},

tppubtype = {article}

}

@article{nokey,

title = {Longitudinal Multi-omics Analyses Identify Responses of Megakaryocytes, Erythroid Cells, and Plasmablasts as Hallmarks of Severe COVID-19},

author = {Joana P. Bernardes and Neha Mishra and Florian Tran and Thomas Bahmer and Lena Best and Johanna I. Blase and Dora Bordoni and Jeanette Franzenburg and Ulf Geisen and Jonathan Josephs-Spaulding and Philipp Köhler and Axel Künstner and Elisa Rosati and Anna C. Aschenbrenner and Petra Bacher and Nathan Baran and Teide Boysen and Burkhard Brandt and Niklas Bruse and Jonathan Dörr and Andreas Dräger and Gunnar Elke and David Ellinghaus and Julia Fischer and Michael Forster and Andre Franke and Sören Franzenburg and Norbert Frey and Anette Friedrichs and Janina Fuß and Andreas Glück and Jacob Hamm and Finn Hinrichsen and Marc P. Hoeppner and Simon Imm and Ralf Junker and Sina Kaiser and Ying H. Kan and Rainer Knoll and Christoph Lange and Georg Laue and Clemens Lier and Matthias Lindner and Georgios Marinos and Robert Markewitz and Jacob Nattermann and Rainer Noth and Peter Pickkers and Klaus F. Rabe and Alina Renz and Christoph Röcken and Jan Rupp and Annika Schaffarzyk and Alexander Scheffold and Jonas Schulte-Schrepping and Domagoj Schunk and Dirk Skowasch and Thomas Ulas and Klaus-Peter Wandinger and Michael Wittig and Johannes Zimmermann and Hauke Busch and Bimba F. Hoyer and Christoph Kaleta and Jan Heyckendorf and Matthijs Kox and Jan Rybniker and Stefan Schreiber and Joachim L. Schultze and Philip Rosenstiel and HCA Lung Biological Network and Deutsche COVID-19 Omics Initiative (DeCOI)

},

doi = {10.1016/j.immuni.2020.11.017},

year  = {2020},

date = {2020-12-15},

urldate = {2020-12-15},

journal = {Immunity},

volume = {53},

number = {6},

pages = {1296-1314.e9},

abstract = {Temporal resolution of cellular features associated with a severe COVID-19 disease trajectory is needed for understanding skewed immune responses and defining predictors of outcome. Here, we performed a longitudinal multi-omics study using a two-center cohort of 14 patients. We analyzed the bulk transcriptome, bulk DNA methylome, and single-cell transcriptome (>358,000 cells, including BCR profiles) of peripheral blood samples harvested from up to 5 time points. Validation was performed in two independent cohorts of COVID-19 patients. Severe COVID-19 was characterized by an increase of proliferating, metabolically hyperactive plasmablasts. Coinciding with critical illness, we also identified an expansion of interferon-activated circulating megakaryocytes and increased erythropoiesis with features of hypoxic signaling. Megakaryocyte- and erythroid-cell-derived co-expression modules were predictive of fatal disease outcome. The study demonstrates broad cellular effects of SARS-CoV-2 infection beyond adaptive immune cells and provides an entry point toward developing biomarkers and targeted treatments of patients with COVID-19.},

keywords = {coronavirus, viruses},

pubstate = {published},

tppubtype = {article}

}

@article{Kalvari:21,

title = {Rfam 14: expanded coverage of metagenomic, viral and microRNA families},

author = {Ioanna Kalvari and Eric P Nawrocki and Nancy Ontiveros-Palacios and Joanna Argasinska and Kevin Lamkiewicz and Manja Marz and Sam Griffiths-Jones and Claire Toffano-Nioche and Daniel Gautheret and Zasha Weinberg and Elena Rivas and Sean R Eddy and Robert D Finn and Alex Bateman and Anton I Petrov},

url = {https://rfam.org/},

doi = {10.1093/nar/gkaa1047},

year  = {2020},

date = {2020-11-19},

urldate = {2020-11-19},

journal = {Nucleic Acids Res},

volume = {49},

number = {D1},

pages = {D192--D200},

publisher = {Oxford University Press (OUP)},

abstract = {Rfam is a database of RNA families where each of the 3444 families is represented by a multiple sequence alignment of known RNA sequences and a covariance model that can be used to search for additional members of the family. Recent developments have involved expert collaborations to improve the quality and coverage of Rfam data, focusing on microRNAs, viral and bacterial RNAs. We have completed the first phase of synchronising microRNA families in Rfam and miRBase, creating 356 new Rfam families and updating 40. We established a procedure for comprehensive annotation of viral RNA families starting with Flavivirus and Coronaviridae RNAs. We have also increased the coverage of bacterial and metagenome-based RNA families from the ZWD database. These developments have enabled a significant growth of the database, with the addition of 759 new families in Rfam 14. To facilitate further community contribution to Rfam, expert users are now able to build and submit new families using the newly developed Rfam Cloud family curation system. New Rfam website features include a new sequence similarity search powered by RNAcentral, as well as search and visualisation of families with pseudoknots. Rfam is freely available at https://rfam.org.},

keywords = {alignment, annotation, bacteria, coronavirus, database, metagenomics, ncRNAs, RNA / transcriptomics, software, viruses},

pubstate = {published},

tppubtype = {article}

}

@article{Hufsky:20a,

title = {Computational strategies to combat COVID-19: useful tools to accelerate SARS-CoV-2 and coronavirus research},

author = {Franziska Hufsky and Kevin Lamkiewicz and Alexandre Almeida and Abdel Aouacheria and Cecilia Arighi and Alex Bateman and Jan Baumbach and Niko Beerenwinkel and Christian Brandt and Marco Cacciabue and Sara Chuguransky and Oliver Drechsel and Robert D Finn and Adrian Fritz and Stephan Fuchs and Georges Hattab and Anne-Christin Hauschild and Dominik Heider and Marie Hoffmann and Martin Hölzer and Stefan Hoops and Lars Kaderali and Ioanna Kalvari and Max Kleist and Renó Kmiecinski and Denise Kühnert and Gorka Lasso and Pieter Libin and Markus List and Hannah F Löchel and Maria J Martin and Roman Martin and Julian Matschinske and Alice C McHardy and Pedro Mendes and Jaina Mistry and Vincent Navratil and Eric P Nawrocki and Áine Niamh O'Toole and Nancy Ontiveros-Palacios and Anton I Petrov and Guillermo Rangel-Pineros and Nicole Redaschi and Susanne Reimering and Knut Reinert and Alejandro Reyes and Lorna Richardson and David L Robertson and Sepideh Sadegh and Joshua B Singer and Kristof Theys and Chris Upton and Marius Welzel and Lowri Williams and Manja Marz},

url = {http://evbc.uni-jena.de/tools/coronavirus-tools/},

doi = {10.1093/bib/bbaa232},

year  = {2020},

date = {2020-11-04},

urldate = {2020-11-04},

journal = {Brief Bioinform},

volume = {22},

number = {2},

pages = {642--663},

publisher = {Oxford University Press (OUP)},

abstract = {SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) is a novel virus of the family Coronaviridae. The virus causes the infectious disease COVID-19. The biology of coronaviruses has been studied for many years. However, bioinformatics tools designed explicitly for SARS-CoV-2 have only recently been developed as a rapid reaction to the need for fast detection, understanding and treatment of COVID-19. To control the ongoing COVID-19 pandemic, it is of utmost importance to get insight into the evolution and pathogenesis of the virus. In this review, we cover bioinformatics workflows and tools for the routine detection of SARS-CoV-2 infection, the reliable analysis of sequencing data, the tracking of the COVID-19 pandemic and evaluation of containment measures, the study of coronavirus evolution, the discovery of potential drug targets and development of therapeutic strategies. For each tool, we briefly describe its use case and how it advances research specifically for SARS-CoV-2. All tools are free to use and available online, either through web applications or public code repositories.},

keywords = {coronavirus, evolution, review, software, viruses},

pubstate = {published},

tppubtype = {article}

}

@article{Schulte-Schrepping:20,

title = {Severe COVID-19 Is Marked by a Dysregulated Myeloid Cell Compartment},

author = {Jonas Schulte-Schrepping and Nico Reusch and Daniela Paclik and Kevin Baßler and Stephan Schlickeiser and Bowen Zhang and Benjamin Krämer and Tobias Krammer and Sophia Brumhard and Lorenzo Bonaguro and Elena De Domenico and Daniel Wendisch and Martin Grasshoff and Theodore S. Kapellos and Michael Beckstette and Tal Pecht and Adem Saglam and Oliver Dietrich and Henrik E. Mei and Axel R. Schulz and Claudia Conrad and Désirée Kunkel and Ehsan Vafadarnejad and Cheng-Jian Xu and Arik Horne and Miriam Herbert and Anna Drews and Charlotte Thibeault and Moritz Pfeiffer and Stefan Hippenstiel and Andreas Hocke and Holger Müller-Redetzky and Katrin-Moira Heim and Felix Machleidt and Alexander Uhrig and Laure Bosquillon Jarcy and Linda Jürgens and Miriam Stegemann and Christoph R. Glösenkamp and Hans-Dieter Volk and Christine Goffinet and Markus Landthaler and Emanuel Wyler and Philipp Georg and Maria Schneider and Chantip Dang-Heine and Nick Neuwinger and Kai Kappert and Rudolf Tauber and Victor Corman and Jan Raabe and Kim Melanie Kaiser and Michael To Vinh and Gereon Rieke and Christian Meisel and Thomas Ulas and Matthias Becker and Robert Geffers and Martin Witzenrath and Christian Drosten and Norbert Suttorp and Christof Kalle and Florian Kurth and Kristian Händler and Joachim L. Schultze and Anna C. Aschenbrenner and Yang Li and Jacob Nattermann and Birgit Sawitzki and Antoine-Emmanuel Saliba and Leif Erik Sander and Deutsche COVID-19 OMICS Initiative (DeCOI)

},

doi = {10.1016/j.cell.2020.08.001},

year  = {2020},

date = {2020-08-05},

urldate = {2020-01-01},

journal = {Cell},

volume = {182},

number = {6},

pages = {1419-1440.e23},

publisher = {Elsevier BV},

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 = {coronavirus, RNA / transcriptomics, viruses},

pubstate = {published},

tppubtype = {article}

}

@article{Hufsky:20,

title = {Computational Strategies to Combat COVID-19: Useful Tools to Accelerate SARS-CoV-2 and Coronavirus Research},

author = {Franziska Hufsky and Kevin Lamkiewicz and Alexandre Almeida and Abdel Aouacheria and Cecilia Arighi and Alex Bateman and Jan Baumbach and Niko Beerenwinkel and Christian Brandt and Marco Cacciabue and Sara Chuguransky and Oliver Drechsel and Robert D. Finn and Adrian Fritz and Stephan Fuchs and Georges Hattab and Anne-Christin Hauschild and Dominik Heider and Marie Hoffmann and Martin Hölzer and Stefan Hoops and Lars Kaderali and Ioanna Kalvari and Max Kleist and Rene Kmiecinski and Denise Kühnert and Gorka Lasso and Pieter Libin and Markus List and Hannah F. Löchel and Maria J. Martin and Roman Martin and Julian Matschinske and Alice C. McHardy and Pedro Mendes and Jaina Mistry and Vincent Navratil and Eric Nawrocki and Áine Niamh O'Toole and Nancy Palacios-Ontiveros and Anton I. Petrov and Guillermo Rangel-Piñeros and Nicole Redaschi and Susanne Reimering and Knut Reinert and Alejandro Reyes and Lorna Richardson and David L. Robertson and Sepideh Sadegh and Joshua B. Singer and Kristof Theys and Chris Upton and Marius Welzel and Lowri Williams and Manja Marz},

doi = {10.20944/preprints202005.0376.v1},

year  = {2020},

date = {2020-05-23},

urldate = {2020-05-23},

journal = {Preprints},

publisher = {MDPI AG},

abstract = {SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) is a novel virus of the family Coronaviridae. The virus causes the infectious disease COVID-19. The biology of coronaviruses has been studied for many years. However, bioinformatics tools designed explicitly for SARS-CoV-2 have only recently been developed as a rapid reaction to the need for fast detection, understanding, and treatment of COVID-19. To control the ongoing COVID-19 pandemic, it is of utmost importance to get insight into the evolution and pathogenesis of the virus. In this review, we cover bioinformatics workflows and tools for the routine detection of SARS-CoV-2 infection, the reliable analysis of sequencing data, the tracking of the COVID-19 pandemic and evaluation of containment measures, the study of coronavirus evolution, the discovery of potential drug targets and development of therapeutic strategies. For each tool, we briefly describe its use case and how it advances research specifically for SARS-CoV-2. All tools are freely available online, either through web applications or public code repositories.

},

note = {Now published in Brief Bioinform: https://dx.doi.org/10.1093/bib/bbaa232},

keywords = {coronavirus, evolution, review, software, viruses},

pubstate = {published},

tppubtype = {article}

}

@article{Viehweger:19a,

title = {Direct RNA nanopore sequencing of full-length coronavirus genomes provides novel insights into structural variants and enables modification analysis.},

author = {Adrian Viehweger and Sebastian Krautwurst and Kevin Lamkiewicz and Ramakanth Madhugiri and John Ziebuhr and Martin Hölzer and Manja Marz},

doi = {10.1101/gr.247064.118},

year  = {2019},

date = {2019-08-22},

urldate = {2019-08-22},

journal = {Genome Res},

volume = {29},

pages = {1545-1554},

publisher = {Cold Spring Harbor Laboratory},

abstract = {Sequence analyses of RNA virus genomes remain challenging owing to the exceptional genetic plasticity of these viruses. Because of high mutation and recombination rates, genome replication by viral RNA-dependent RNA polymerases leads to populations of closely related viruses, so-called “quasispecies.” Standard (short-read) sequencing technologies are ill-suited to reconstruct large numbers of full-length haplotypes of (1) RNA virus genomes and (2) subgenome-length (sg) RNAs composed of noncontiguous genome regions. Here, we used a full-length, direct RNA sequencing (DRS) approach based on nanopores to characterize viral RNAs produced in cells infected with a human coronavirus. By using DRS, we were able to map the longest (∼26-kb) contiguous read to the viral reference genome. By combining Illumina and Oxford Nanopore sequencing, we reconstructed a highly accurate consensus sequence of the human coronavirus (HCoV)-229E genome (27.3 kb). Furthermore, by using long reads that did not require an assembly step, we were able to identify, in infected cells, diverse and novel HCoV-229E sg RNAs that remain to be characterized. Also, the DRS approach, which circumvents reverse transcription and amplification of RNA, allowed us to detect methylation sites in viral RNAs. Our work paves the way for haplotype-based analyses of viral quasispecies by showing the feasibility of intra-sample haplotype separation. Even though several technical challenges remain to be addressed to exploit the potential of the nanopore technology fully, our work illustrates that DRS may significantly advance genomic studies of complex virus populations, including predictions on long-range interactions in individual full-length viral RNA haplotypes.},

keywords = {assembly, coronavirus, nanopore, nucleic acid modifications, RNA / transcriptomics, viruses},

pubstate = {published},

tppubtype = {article}

}

@article{Madhugiri:18,

title = {Structural and functional conservation of cis-acting RNA elements in coronavirus 5'-terminal genome regions},

author = {Ramakanth Madhugiri and Nadja Karl and Daniel Petersen and Kevin Lamkiewicz and Markus Fricke and Ulrike Wend and Robina Scheuer and Manja Marz and John Ziebuhr},

doi = {10.1016/j.virol.2017.11.025},

year  = {2017},

date = {2017-12-06},

urldate = {2017-12-06},

journal = {Virology},

volume = {517},

pages = {44--55},

abstract = {Structure predictions suggest a partial conservation of RNA structure elements in coronavirus terminal genome regions. Here, we determined the structures of stem-loops (SL) 1 and 2 of two alphacoronaviruses, human coronavirus (HCoV) 229E and NL63, by RNA structure probing and studied the functional relevance of these putative cis-acting elements. HCoV-229E SL1 and SL2 mutants generated by reverse genetics were used to study the effects on viral replication of single-nucleotide substitutions predicted to destabilize the SL1 and SL2 structures. The data provide conclusive evidence for the critical role of SL1 and SL2 in HCoV-229E replication and, in some cases, revealed parallels with previously characterized betacoronavirus SL1 and SL2 elements. Also, we were able to rescue viable HCoV-229E mutants carrying replacements of SL2 with equivalent betacoronavirus structural elements. The data obtained in this study reveal a remarkable degree of structural and functional conservation of 5'-terminal RNA structural elements across coronavirus genus boundaries.},

keywords = {coronavirus, phylogenetics, RNA / transcriptomics, RNA structure, viruses},

pubstate = {published},

tppubtype = {article}

}

@article{Madhugiri:14,

title = {RNA structure analysis of alphacoronavirus terminal genome regions},

author = {Ramakanth Madhugiri and Markus Fricke and Manja Marz and John Ziebuhr},

doi = {10.1016/j.virusres.2014.10.001},

year  = {2014},

date = {2014-10-13},

urldate = {2014-10-13},

journal = {Virus Res},

volume = {194},

pages = {76--89},

abstract = {Coronavirus genome replication is mediated by a multi-subunit protein complex that is comprised of more than a dozen virally encoded and several cellular proteins. Interactions of the viral replicase complex with cis-acting RNA elements located in the 5' and 3'-terminal genome regions ensure the specific replication of viral RNA. Over the past years, boundaries and structures of cis-acting RNA elements required for coronavirus genome replication have been extensively characterized in betacoronaviruses and, to a lesser extent, other coronavirus genera. Here, we review our current understanding of coronavirus cis-acting elements located in the terminal genome regions and use a combination of bioinformatic and RNA structure probing studies to identify and characterize putative cis-acting RNA elements in alphacoronaviruses. The study suggests significant RNA structure conservation among members of the genus Alphacoronavirus but also across genus boundaries. Overall, the conservation pattern identified for 5' and 3'-terminal RNA structural elements in the genomes of alpha- and betacoronaviruses is in agreement with the widely used replicase polyprotein-based classification of the Coronavirinae, suggesting co-evolution of the coronavirus replication machinery with cognate cis-acting RNA elements.},

keywords = {classification, coronavirus, evolution, RNA / transcriptomics, RNA structure, viruses},

pubstate = {published},

tppubtype = {article}

}