• Seqenv: Linking sequences to environments through text mining

      BRICS, Braunschweiger Zentrum für Systembiologie, Rebenring 56, 38106 Braunschweig, Germany.
      Understanding the distribution of taxa and associated traits across different environments is one of the central questions in microbial ecology. High-throughput sequencing (HTS) studies are presently generating huge volumes of data to address this biogeographical topic. However, these studies are often focused on specific environment types or processes leading to the production of individual, unconnected datasets. The large amounts of legacy sequence data with associated metadata that exist can be harnessed to better place the genetic information found in these surveys into a wider environmental context. Here we introduce a software program, seqenv, to carry out precisely such a task. It automatically performs similarity searches of short sequences against the ``nt'' nucleotide database provided by NCBI and, out of every hit, extracts-if it is available-the textual metadata field. After collecting all the isolation sources from all the search results, we run a text mining algorithm to identify and parse words that are associated with the Environmental Ontology (EnvO) controlled vocabulary. This, in turn, enables us to determine both in which environments individual sequences or taxa have previously been observed and, by weighted summation of those results, to summarize complete samples. We present two demonstrative applications of seqenv to a survey of ammonia oxidizing archaea as well as to a plankton paleome dataset from the Black Sea. These demonstrate the ability of the tool to reveal novel patterns in HTS and its utility in the fields of environmental source tracking, paleontology, and studies of microbial biogeography. To install seqenv, go to: https://github.com/xapple/seqenv. (c) 2016 Sinclair et al
    • Severe COVID-19 Is Marked by a Dysregulated Myeloid Cell Compartment.

      Schulte-Schrepping, Jonas; Reusch, Nico; Paclik, Daniela; Baßler, Kevin; Schlickeiser, Stephan; Zhang, Bowen; Krämer, Benjamin; Krammer, Tobias; Brumhard, Sophia; Bonaguro, Lorenzo; et al. (Elsevier /Cell Press), 2020-08-05)
      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.
    • Snowball: strain aware gene assembly of metagenomes.

      Gregor, I; Schönhuth, A; McHardy, A C; [BRICS] Braunschweiger Zentrum für Systembiology, Rebenring 56, 38106 Braunschweig, Germany. (2016-09-01)
      Gene assembly is an important step in functional analysis of shotgun metagenomic data. Nonetheless, strain aware assembly remains a challenging task, as current assembly tools often fail to distinguish among strain variants or require closely related reference genomes of the studied species to be available.
    • Structures and functions linked to genome-wide adaptation of human influenza A viruses.

      Klingen, Thorsten R; Loers, Jens; Stanelle-Bertram, Stephanie; Gabriel, Gülsah; McHardy, Alice C; BRICS, Braunschweiger Zentrum für Systembiologie, Rebenring 56,38106 Braunschweig, Germany. (Springer-Nature, 2019-04-18)
      Human influenza A viruses elicit short-term respiratory infections with considerable mortality and morbidity. While H3N2 viruses circulate for more than 50 years, the recent introduction of pH1N1 viruses presents an excellent opportunity for a comparative analysis of the genome-wide evolutionary forces acting on both subtypes. Here, we inferred patches of sites relevant for adaptation, i.e. being under positive selection, on eleven viral protein structures, from all available data since 1968 and correlated these with known functional properties. Overall, pH1N1 have more patches than H3N2 viruses, especially in the viral polymerase complex, while antigenic evolution is more apparent for H3N2 viruses. In both subtypes, NS1 has the highest patch and patch site frequency, indicating that NS1-mediated viral attenuation of host inflammatory responses is a continuously intensifying process, elevated even in the longtime-circulating subtype H3N2. We confirmed the resistance-causing effects of two pH1N1 changes against oseltamivir in NA activity assays, demonstrating the value of the resource for discovering functionally relevant changes. Our results represent an atlas of protein regions and sites with links to host adaptation, antiviral drug resistance and immune evasion for both subtypes for further study.
    • Survival trade-offs in plant roots during colonization by closely related beneficial and pathogenic fungi.

      Hacquard, Stéphane; Kracher, Barbara; Hiruma, Kei; Münch, Philipp C; Garrido-Oter, Ruben; Thon, Michael R; Weimann, Aaron; Damm, Ulrike; Dallery, Jean-Félix; Hainaut, Matthieu; et al. (2016-05-06)
      The sessile nature of plants forced them to evolve mechanisms to prioritize their responses to simultaneous stresses, including colonization by microbes or nutrient starvation. Here, we compare the genomes of a beneficial root endophyte, Colletotrichum tofieldiae and its pathogenic relative C. incanum, and examine the transcriptomes of both fungi and their plant host Arabidopsis during phosphate starvation. Although the two species diverged only 8.8 million years ago and have similar gene arsenals, we identify genomic signatures indicative of an evolutionary transition from pathogenic to beneficial lifestyles, including a narrowed repertoire of secreted effector proteins, expanded families of chitin-binding and secondary metabolism-related proteins, and limited activation of pathogenicity-related genes in planta. We show that beneficial responses are prioritized in C. tofieldiae-colonized roots under phosphate-deficient conditions, whereas defense responses are activated under phosphate-sufficient conditions. These immune responses are retained in phosphate-starved roots colonized by pathogenic C. incanum, illustrating the ability of plants to maximize survival in response to conflicting stresses.
    • Sweep Dynamics (SD) plots: Computational identification of selective sweeps to monitor the adaptation of influenza A viruses.

      Klingen, Thorsten R; Reimering, Susanne; Loers, Jens; Mooren, Kyra; Klawonn, Frank; Krey, Thomas; Gabriel, Gülsah; McHardy, Alice Carolyn; BRICS, Braunschweiger Zentrum für Systembiologie, Rebenring 56, 38106 Braunschweig, Germany. (2018-01-10)
      Monitoring changes in influenza A virus genomes is crucial to understand its rapid evolution and adaptation to changing conditions e.g. establishment within novel host species. Selective sweeps represent a rapid mode of adaptation and are typically observed in human influenza A viruses. We describe Sweep Dynamics (SD) plots, a computational method combining phylogenetic algorithms with statistical techniques to characterize the molecular adaptation of rapidly evolving viruses from longitudinal sequence data. SD plots facilitate the identification of selective sweeps, the time periods in which these occurred and associated changes providing a selective advantage to the virus. We studied the past genome-wide adaptation of the 2009 pandemic H1N1 influenza A (pH1N1) and seasonal H3N2 influenza A (sH3N2) viruses. The pH1N1 influenza virus showed simultaneous amino acid changes in various proteins, particularly in seasons of high pH1N1 activity. Partially, these changes resulted in functional alterations facilitating sustained human-to-human transmission. In the evolution of sH3N2 influenza viruses, we detected changes characterizing vaccine strains, which were occasionally revealed in selective sweeps one season prior to the WHO recommendation. Taken together, SD plots allow monitoring and characterizing the adaptive evolution of influenza A viruses by identifying selective sweeps and their associated signatures. - - all data is published on GitHub: https://github.com/hzi-bifo/SDplots/tree/v1.0.0
    • Taxator-tk: precise taxonomic assignment of metagenomes by fast approximation of evolutionary neighborhoods.

      Dröge, J; Gregor, I; McHardy, A C; Department for Algorithmic Bioinformatics, Heinrich Heine University, Universitätsstraße 1, 40225 Düsseldorf, Germany, Max-Planck Research Group for Computational Genomics and Epidemiology, Max-Planck Institute for Informatics, University Campus E1 4, 66123 Saarbrücken, Germany and Computational Biology of Infection Research, Helmholtz Centre for Infection Research, Inhoffenstraße 7, 38124 Braunschweig, Germany Department for Algorithmic Bioinformatics, Heinrich Heine University, Universitätsstraße 1, 40225 Düsseldorf, Germany, Max-Planck Research Group for Computational Genomics and Epidemiology, Max-Planck Institute for Informatics, University Campus E1 4, 66123 Saarbrücken, Germany and Computational Biology of Infection Research, Helmholtz Centre for Infection Research, Inhoffenstraße 7, 38124 Braunschweig, Germany. (2014-11-10)
      Metagenomics characterizes microbial communities by random shotgun sequencing of DNA isolated directly from an environment of interest. An essential step in computational metagenome analysis is taxonomic sequence assignment, which allows identifying the sequenced community members and reconstructing taxonomic bins with sequence data for the individual taxa. For the massive datasets generated by next-generation sequencing technologies, this cannot be performed with de-novo phylogenetic inference methods. We describe an algorithm and the accompanying software, taxator-tk, which performs taxonomic sequence assignment by fast approximate determination of evolutionary neighbors from sequence similarities.
    • Temporally feathered intensity-modulated radiation therapy: A planning technique to reduce normal tissue toxicity.

      López Alfonso, Juan Carlos; Parsai, Shireen; Joshi, Nikhil; Godley, Andrew; Shah, Chirag; Koyfman, Shlomo A; Caudell, Jimmy J; Fuller, Clifton D; Enderling, Heiko; Scott, Jacob G; et al. (Wiley, 2018-06-08)
      Purpose: Intensity-modulated radiation therapy (IMRT) has allowed optimization of three-dimensional spatial radiation dose distributions permitting target coverage while reducing normal tissue toxicity. However, radiation-induced normal tissue toxicity is a major contributor to patients' quality of life and often a dose-limiting factor in the definitive treatment of cancer with radiation therapy. We propose the next logical step in the evolution of IMRT using canonical radiobiological principles, optimizing the temporal dimension through which radiation therapy is delivered to further reduce radiation-induced toxicity by increased time for normal tissue recovery. We term this novel treatment planning strategy "temporally feathered radiation therapy" (TFRT). Methods: Temporally feathered radiotherapy plans were generated as a composite of five simulated treatment plans each with altered constraints on particular hypothetical organs at risk (OARs) to be delivered sequentially. For each of these TFRT plans, OARs chosen for feathering receive higher doses while the remaining OARs receive lower doses than the standard fractional dose delivered in a conventional fractionated IMRT plan. Each TFRT plan is delivered a specific weekday, which in effect leads to a higher dose once weekly followed by four lower fractional doses to each temporally feathered OAR. We compared normal tissue toxicity between TFRT and conventional fractionated IMRT plans by using a dynamical mathematical model to describe radiation-induced tissue damage and repair over time. Results: Model-based simulations of TFRT demonstrated potential for reduced normal tissue toxicity compared to conventionally planned IMRT. The sequencing of high and low fractional doses delivered to OARs by TFRT plans suggested increased normal tissue recovery, and hence less overall radiation-induced toxicity, despite higher total doses delivered to OARs compared to conventional fractionated IMRT plans. The magnitude of toxicity reduction by TFRT planning was found to depend on the corresponding standard fractional dose of IMRT and organ-specific recovery rate of sublethal radiation-induced damage. Conclusions: TFRT is a novel technique for treatment planning and optimization of therapeutic radiotherapy that considers the nonlinear aspects of normal tissue repair to optimize toxicity profiles. Model-based simulations of TFRT to carefully conceptualized clinical cases have demonstrated potential for radiation-induced toxicity reduction in a previously described dynamical model of normal tissue complication probability (NTCP).
    • Toward unrestricted use of public genomic data.

      Amann, Rudolf I; Baichoo, Shakuntala; Blencowe, Benjamin J; Bork, Peer; Borodovsky, Mark; Brooksbank, Cath; Chain, Patrick S G; Colwell, Rita R; Daffonchio, Daniele G; Danchin, Antoine; et al. (AAAS, 2019-01-25)
      Despite some notable progress in data sharing policies and practices, restrictions are still often placed on the open and unconditional use of various genomic data after they have received official approval for release to the public domain or to public databases. These restrictions, which often conflict with the terms and conditions of the funding bodies who supported the release of those data for the benefit of the scientific community and society, are perpetuated by the lack of clear guiding rules for data usage. Existing guidelines for data released to the public domain recognize but fail to resolve tensions between the importance of free and unconditional use of these data and the “right” of the data producers to the first publication. This self-contradiction has resulted in a loophole that allows different interpretations and a continuous debate between data producers and data users on the use of public data. We argue that the publicly available data should be treated as open data, a shared resource with unrestricted use for analysis, interpretation, and publication.
    • Transcriptome-wide analysis uncovers the targets of the RNA-binding protein MSI2 and effects of MSI2's RNA-binding activity on IL-6 signaling.

      Duggimpudi, Sujitha; Kloetgen, Andreas; Maney, Sathish Kumar; Münch, Philipp C; Hezaveh, Kebria; Shaykhalishahi, Hamed; Hoyer, Wolfgang; McHardy, Alice C; Lang, Philipp A; Borkhardt, Arndt; et al. (American Society for Biochemistry and Molecular Biology, 2018-08-20)
      The RNA-binding protein Musashi 2 (MSI2) has emerged as an important regulator in cancer initiation, progression, and drug resistance. Translocations and deregulation of the MSI2 gene are diagnostic of certain cancers, including chronic myeloid leukemia (CML) with translocation t(7;17), acute myeloid leukemia (AML) with translocation t(10;17), and some cases of B-precursor acute lymphoblastic leukemia (pB-ALL). To better understand the function of MSI2 in leukemia, the mRNA targets that are bound and regulated by MSI2 and their MSI2-binding motifs need to be identified. To this end, using photoactivatable ribonucleoside cross-linking and immunoprecipitation (PAR-CLIP) and the multiple EM for motif elicitation (MEME) analysis tool, here we identified MSI2's mRNA targets and the consensus RNA-recognition element (RRE) motif recognized by MSI2 (UUAG). Of note, MSI2 knockdown altered the expression of several genes with roles in eukaryotic initiation factor 2 (eIF2), hepatocyte growth factor (HGF), and epidermal growth factor (EGF) signaling pathways. We also show that MSI2 regulates classic interleukin-6 (IL-6) signaling by promoting the degradation of the mRNA of IL-6 signal transducer (IL6ST or GP130), which, in turn, affected the phosphorylation statuses of signal transducer and activator of transcription 3 (STAT3) and the mitogen-activated protein kinase ERK. In summary, we have identified multiple MSI2-regulated mRNAs and provided evidence that MSI2 controls IL6ST activity that control oncogenic signaling networks. Our findings may help inform strategies for unraveling the role of MSI2 in leukemia to pave the way for the development of targeted therapies.
    • Tumor Necrosis Factor-Mediated Survival of CD169 Cells Promotes Immune Activation during Vesicular Stomatitis Virus Infection.

      Shinde, Prashant V; Xu, Haifeng C; Maney, Sathish Kumar; Kloetgen, Andreas; Namineni, Sukumar; Zhuang, Yuan; Honke, Nadine; Shaabani, Namir; Bellora, Nicolas; Doerrenberg, Mareike; et al. (2018-02-01)
      Innate immune activation is essential to mount an effective antiviral response and to prime adaptive immunity. Although a crucial role of CD169
    • Tutorial: assessing metagenomics software with the CAMI benchmarking toolkit.

      Meyer, Fernando; Lesker, Till-Robin; Koslicki, David; Fritz, Adrian; Gurevich, Alexey; Darling, Aaron E; Sczyrba, Alexander; Bremges, Andreas; McHardy, Alice C; BRICS, Braunschweiger Zentrum für Systembiologie, Rebenring 56,38106 Braunschweig, Germany. (Nature Research, 2021-03-01)
      Computational methods are key in microbiome research, and obtaining a quantitative and unbiased performance estimate is important for method developers and applied researchers. For meaningful comparisons between methods, to identify best practices and common use cases, and to reduce overhead in benchmarking, it is necessary to have standardized datasets, procedures and metrics for evaluation. In this tutorial, we describe emerging standards in computational meta-omics benchmarking derived and agreed upon by a larger community of researchers. Specifically, we outline recent efforts by the Critical Assessment of Metagenome Interpretation (CAMI) initiative, which supplies method developers and applied researchers with exhaustive quantitative data about software performance in realistic scenarios and organizes community-driven benchmarking challenges. We explain the most relevant evaluation metrics for assessing metagenome assembly, binning and profiling results, and provide step-by-step instructions on how to generate them. The instructions use simulated mouse gut metagenome data released in preparation for the second round of CAMI challenges and showcase the use of a repository of tool results for CAMI datasets. This tutorial will serve as a reference for the community and facilitate informative and reproducible benchmarking in microbiome research.
    • YBX1 Indirectly Targets Heterochromatin-Repressed Inflammatory Response-Related Apoptosis Genes through Regulating CBX5 mRNA.

      Kloetgen, Andreas; Duggimpudi, Sujitha; Schuschel, Konstantin; Hezaveh, Kebria; Picard, Daniel; Schaal, Heiner; Remke, Marc; Klusmann, Jan-Henning; Borkhardt, Arndt; McHardy, Alice C; et al. (MDPI, 2020-06-23)
      Medulloblastomas arise from undifferentiated precursor cells in the cerebellum and account for about 20% of all solid brain tumors during childhood; standard therapies include radiation and chemotherapy, which oftentimes come with severe impairment of the cognitive development of the young patients. Here, we show that the posttranscriptional regulator Y-box binding protein 1 (YBX1), a DNA- and RNA-binding protein, acts as an oncogene in medulloblastomas by regulating cellular survival and apoptosis. We observed different cellular responses upon YBX1 knockdown in several medulloblastoma cell lines, with significantly altered transcription and subsequent apoptosis rates. Mechanistically, PAR-CLIP for YBX1 and integration with RNA-Seq data uncovered direct posttranscriptional control of the heterochromatin-associated gene CBX5; upon YBX1 knockdown and subsequent CBX5 mRNA instability, heterochromatin-regulated genes involved in inflammatory response, apoptosis and death receptor signaling were de-repressed. Thus, YBX1 acts as an oncogene in medulloblastoma through indirect transcriptional regulation of inflammatory genes regulating apoptosis and represents a promising novel therapeutic target in this tumor entity.