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 = {Identification of altered miRNAs and their targets in placenta accreta},

author = {José M Murrieta-Coxca and Emanuel Barth and Paulina Fuentes-Zacarias and Ruby N Gutiérrez-Samudio and Tanja Groten and Alexandra Gellhaus and Angela Köninger and Manja Marz and Udo R Markert and Diana M Morales-Prieto

},

doi = {10.3389/fendo.2023.1021640},

year  = {2023},

date = {2023-03-03},

journal = {Front Endocrinol},

volume = {14},

pages = {1021640},

abstract = {Placenta accreta spectrum (PAS) is one of the major causes of maternal morbidity and mortality worldwide with increasing incidence. PAS refers to a group of pathological conditions ranging from the abnormal attachment of the placenta to the uterus wall to its perforation and, in extreme cases, invasion into surrounding organs. Among them, placenta accreta is characterized by a direct adhesion of the villi to the myometrium without invasion and remains the most common diagnosis of PAS. Here, we identify the potential regulatory miRNA and target networks contributing to placenta accreta development. Using small RNA-Seq followed by RT-PCR confirmation, altered miRNA expression, including that of members of placenta-specific miRNA clusters (e.g., C19MC and C14MC), was identified in placenta accreta samples compared to normal placental tissues. In situ hybridization (ISH) revealed expression of altered miRNAs mostly in trophoblast but also in endothelial cells and this profile was similar among all evaluated degrees of PAS. Kyoto encyclopedia of genes and genomes (KEGG) analyses showed enriched pathways dysregulated in PAS associated with cell cycle regulation, inflammation, and invasion. mRNAs of genes associated with cell cycle and inflammation were downregulated in PAS. At the protein level, NF-κB was upregulated while PTEN was downregulated in placenta accreta tissue. The identified miRNAs and their targets are associated with signaling pathways relevant to controlling trophoblast function. Therefore, this study provides miRNA:mRNA associations that could be useful for understanding PAS onset and progression.},

keywords = {ncRNAs, pregnancy, RNA / transcriptomics},

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 = {Automatic, fast, hierarchical, and non-overlapping gating of flow cytometric data with flowEMMi v2},

author = {Carmen Bruckmann and Susann Müller and Christian {Höner zu Siederdissen}

},

doi = {10.1016/j.csbj.2022.11.033},

year  = {2022},

date = {2022-11-17},

urldate = {2022-11-17},

journal = {Comput Struct Biotechnol J},

volume = {20},

pages = {6473-6489},

abstract = {Flow cytometry has become a powerful technology for studying microbial community dynamics and ecology. These dynamics are tracked over long periods of time based on two-parameter community fingerprints consisting of subsets of cell distributions with similar cell properties. These subsets are highlighted by cytometric gates which are assembled into a gate template. Gate templates then are used to compare samples over time or between sites. The template is usually created manually by the operator which is time consuming, prone to human error and dependent on human expertise. Manual gating thus lacks reproducibility, which in turn might impact ecological downstream analyses such as various diversity parameters, turnover and nestedness or stability measures. We present a new version of our flowEMMi algorithm - originally designed for an automated construction of a gate template, which now (i) generates non-overlapping elliptical gates within a few minutes. Gate templates (ii) can be created for both single measurements and time-series measurements, allowing immediate downstream data analyses and on-line evaluation. Furthermore, it is possible to (iii) adjust gate sizes to Gaussian distribution confidence levels. This automatic approach (iv) makes the gate template creation objective and reproducible. Moreover, it can (v) generate hierarchies of gates. flowEMMi v2 is essential not only for exploratory studies, but also for routine monitoring and control of biotechnological processes. Therefore, flowEMMi v2 bridges a crucial bottleneck between automated cell sample collection and processing, and automated flow cytometric measurement on the one hand as well as automated downstream statistical analysis on the other hand.},

keywords = {},

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{Mock2022,

title = {Taxonomic classification of DNA sequences beyond sequence similarity using deep neural networks},

author = {Florian Mock and Fleming Kretschmer and Anton Kriese and Sebastian Böcker and Manja Marz

},

doi = {10.1073/pnas.2122636119},

year  = {2022},

date = {2022-08-30},

journal = {Proc Natl Acad Sci},

volume = {119},

issue = {35},

pages = {e2122636119},

abstract = {Taxonomic classification, that is, the assignment to biological clades with shared ancestry, is a common task in genetics, mainly based on a genome similarity search of large genome databases. The classification quality depends heavily on the database, since representative relatives must be present. Many genomic sequences cannot be classified at all or only with a high misclassification rate. Here we present BERTax, a deep neural network program based on natural language processing to precisely classify the superkingdom and phylum of DNA sequences taxonomically without the need for a known representative relative from a database. We show BERTax to be at least on par with the state-of-the-art approaches when taxonomically similar species are part of the training data. For novel organisms, however, BERTax clearly outperforms any existing approach. Finally, we show that BERTax can also be combined with database approaches to further increase the prediction quality in almost all cases. Since BERTax is not based on similar entries in databases, it allows precise taxonomic classification of a broader range of genomic sequences, thus increasing the overall information gain.},

keywords = {classification, DNA / genomics, machine learning},

pubstate = {published},

tppubtype = {article}

}

@article{nokey,

title = {Network analysis of hepatocellular carcinoma liquid biopsies augmented by single-cell sequencing data},

author = {Aram Safrastyan and Damian Wollny},

doi = {10.3389/fgene.2022.921195},

year  = {2022},

date = {2022-08-25},

journal = {Front Genet},

volume = {13},

pages = {921195},

abstract = {Liquid biopsy, the analysis of body fluids, represents a promising approach for disease diagnosis and prognosis with minimal intervention. Sequencing cell-free RNA derived from liquid biopsies has been very promising for the diagnosis of several diseases. Cancer research, in particular, has emerged as a prominent candidate since early diagnosis has been shown to be a critical determinant of disease prognosis. Although high-throughput analysis of liquid biopsies has uncovered many differentially expressed genes in the context of cancer, the functional connection between these genes is not investigated in depth. An important approach to remedy this issue is the construction of gene networks which describes the correlation patterns between different genes, thereby allowing to infer their functional organization. In this study, we aimed at characterizing extracellular transcriptome gene networks of hepatocellular carcinoma patients compared to healthy controls. Our analysis revealed a number of genes previously associated with hepatocellular carcinoma and uncovered their association network in the blood. Our study thus demonstrates the feasibility of performing gene co-expression network analysis from cell-free RNA data and its utility in studying hepatocellular carcinoma. Furthermore, we augmented cell-free RNA network analysis with single-cell RNA sequencing data which enables the contextualization of the identified network modules with cell-type specific transcriptomes from the liver.},

keywords = {cancer, single-cell sequencing},

pubstate = {published},

tppubtype = {article}

}

@article{nokey,

title = {Comparative transcriptomics identifies candidate genes involved in the evolutionary transition from dehiscent to indehiscent fruits in Lepidium (Brassicaceae)},

author = {Lydia Gramzow and Katharina Klupsch and Noé Fernández-Pozo and Martin Hölzer and Manja Marz and Stefan A Rensing and Günter Theißen},

doi = {10.1186/s12870-022-03631-8},

year  = {2022},

date = {2022-07-14},

journal = {BMC Plant Biol},

volume = {22},

issue = {1},

pages = {340},

abstract = {Background: Fruits are the seed-bearing structures of flowering plants and are highly diverse in terms of morphology, texture and maturation. Dehiscent fruits split open upon maturation to discharge their seeds while indehiscent fruits are dispersed as a whole. Indehiscent fruits evolved from dehiscent fruits several times independently in the crucifer family (Brassicaceae). The fruits of Lepidium appelianum, for example, are indehiscent while the fruits of the closely related L. campestre are dehiscent. Here, we investigate the molecular and genetic mechanisms underlying the evolutionary transition from dehiscent to indehiscent fruits using these two Lepidium species as model system.



Results: We have sequenced the transcriptomes and small RNAs of floral buds, flowers and fruits of L. appelianum and L. campestre and analyzed differentially expressed genes (DEGs) and differently differentially expressed genes (DDEGs). DEGs are genes that show significantly different transcript levels in the same structures (buds, flowers and fruits) in different species, or in different structures in the same species. DDEGs are genes for which the change in expression level between two structures is significantly different in one species than in the other. Comparing the two species, the highest number of DEGs was found in flowers, followed by fruits and floral buds while the highest number of DDEGs was found in fruits versus flowers followed by flowers versus floral buds. Several gene ontology terms related to cell wall synthesis and degradation were overrepresented in different sets of DEGs highlighting the importance of these processes for fruit opening. Furthermore, the fruit valve identity genes FRUITFULL and YABBY3 were among the DEGs identified. Finally, the microRNA miR166 as well as the TCP transcription factors BRANCHED1 (BRC1) and TCP FAMILY TRANSCRIPTION FACTOR 4 (TCP4) were found to be DDEGs.



Conclusions: Our study reveals differences in gene expression between dehiscent and indehiscent fruits and uncovers miR166, BRC1 and TCP4 as candidate genes for the evolutionary transition from dehiscent to indehiscent fruits in Lepidium.},

keywords = {RNA / transcriptomics},

pubstate = {published},

tppubtype = {article}

}

@article{nokey,

title = {Women in the European Virus Bioinformatics Center},

author = {Franziska Hufsky and Ana Abecasis and Patricia Agudelo-Romero and Magda Bletsa and Katherine Brown and Claudia Claus and Stefanie Deinhardt-Emmer and Li Deng and Caroline C. Friedel and María Inés Gismondi and Evangelia Georgia Kostaki and Denise Kühnert and Urmila Kulkarni-Kale and Karin J. Metzner and Irmtraud M. Meyer and Laura Miozzi and Luca Nishimura and Sofia Paraskevopoulou and Alba Pérez-Cataluña and Janina Rahlff and Emma Thomson and Charlotte Tumescheit and Lia van der Hoek and Lore Van Espen and Anne-Mieke Vandamme and Maryam Zaheri and Neta Zuckerman and Manja Marz},

doi = {10.3390/v14071522},

year  = {2022},

date = {2022-07-12},

journal = {Viruses},

volume = {14},

issue = {7},

pages = {1522},

abstract = {Viruses are the cause of a considerable burden to human, animal and plant health, while on the other hand playing an important role in regulating entire ecosystems. The power of new sequencing technologies combined with new tools for processing “Big Data” offers unprecedented opportunities to answer fundamental questions in virology. Virologists have an urgent need for virus-specific bioinformatics tools. These developments have led to the formation of the European Virus Bioinformatics Center, a network of experts in virology and bioinformatics who are joining forces to enable extensive exchange and collaboration between these research areas. The EVBC strives to provide talented researchers with a supportive environment free of gender bias, but the gender gap in science, especially in math-intensive fields such as computer science, persists. To bring more talented women into research and keep them there, we need to highlight role models to spark their interest, and we need to ensure that female scientists are not kept at lower levels but are given the opportunity to lead the field. Here we showcase the work of the EVBC and highlight the achievements of some outstanding women experts in virology and viral bioinformatics.},

keywords = {viruses},

pubstate = {published},

tppubtype = {article}

}

@article{Fuesslin2022,

title = {Prediction of Antibiotic Susceptibility Profiles of \textit{Vibrio cholerae} Isolates From Whole Genome Illumina and Nanopore Sequencing Data: CholerAegon},

author = {Valeria Fuesslin and Sebastian Krautwurst and Akash Srivastava and Doris Winter and Britta Liedigk and Thorsten Thye and Silvia Herrera-León and Shirlee Wohl and Jürgen May and Julius N. Fobil and Daniel Eibach and Manja Marz and Kathrin Schuldt},

url = {https://github.com/RaverJay/CholerAegon },

doi = {10.3389/fmicb.2022.909692},

year  = {2022},

date = {2022-06-22},

journal = {Front Microbiol},

volume = {13},

pages = {909692},

abstract = {During the last decades, antimicrobial resistance (AMR) has become a global public health concern. Nowadays multi-drug resistance is commonly observed in strains of Vibrio cholerae, the etiological agent of cholera. In order to limit the spread of pathogenic drug-resistant bacteria and to maintain treatment options the analysis of clinical samples and their AMR profiles are essential. Particularly, in low-resource settings a timely analysis of AMR profiles is often impaired due to lengthy culturing procedures for antibiotic susceptibility testing or lack of laboratory capacity. In this study, we explore the applicability of whole genome sequencing for the prediction of AMR profiles of V. cholerae. We developed the pipeline CholerAegon for the in silico prediction of AMR profiles of 82 V. cholerae genomes assembled from long and short sequencing reads. By correlating the predicted profiles with results from phenotypic antibiotic susceptibility testing we show that the prediction can replace in vitro susceptibility testing for five of seven antibiotics. Because of the relatively low costs, possibility for real-time data analyses, and portability, the Oxford Nanopore Technologies MinION sequencing platform—especially in light of an upcoming less error-prone technology for the platform—appears to be well suited for pathogen genomic analyses such as the one described here. Together with CholerAegon, it can leverage pathogen genomics to improve disease surveillance and to control further spread of antimicrobial resistance.},

keywords = {bacteria, DNA / genomics, nanopore},

pubstate = {published},

tppubtype = {article}

}

@article{nokey,

title = {Characterization of RNA content in individual phase-separated coacervate microdroplets},

author = {Damian Wollny and Benjamin Vernot and Jie Wang and Maria Hondele and Aram Safrastyan and Franziska Aron and Julia Micheel and Zhisong He and Anthony Hyman and Karsten Weis and J Gray Camp and T-Y Dora Tang and Barbara Treutlein},

url = {10.1038/s41467-022-30158-1},

year  = {2022},

date = {2022-05-12},

journal = {Nat Commun},

volume = {13},

issue = {1},

pages = {2626},

abstract = {Condensates formed by complex coacervation are hypothesized to have played a crucial part during the origin-of-life. In living cells, condensation organizes biomolecules into a wide range of membraneless compartments. Although RNA is a key component of biological condensates and the central component of the RNA world hypothesis, little is known about what determines RNA accumulation in condensates and to which extend single condensates differ in their RNA composition. To address this, we developed an approach to read the RNA content from single synthetic and protein-based condensates using high-throughput sequencing. We find that certain RNAs efficiently accumulate in condensates. These RNAs are strongly enriched in sequence motifs which show high sequence similarity to short interspersed elements (SINEs). We observe similar results for protein-derived condensates, demonstrating applicability across different in vitro reconstituted membraneless organelles. Thus, our results provide a new inroad to explore the RNA content of phase-separated droplets at single condensate resolution.},

keywords = {RNA / transcriptomics},

pubstate = {published},

tppubtype = {article}

}

@article{nokey,

title = {The Role of Non-Coding RNAs in the Human Placenta},

author = {Milena Žarković and Franziska Hufsky and Udo R Markert and Manja Marz},

doi = {10.3390/cells11091588},

year  = {2022},

date = {2022-05-09},

journal = {Cells},

volume = {11},

issue = {9},

pages = {1588},

abstract = {Non-coding RNAs (ncRNAs) play a central and regulatory role in almost all cells, organs, and species, which has been broadly recognized since the human ENCODE project and several other genome projects. Nevertheless, a small fraction of ncRNAs have been identified, and in the placenta they have been investigated very marginally. To date, most examples of ncRNAs which have been identified to be specific for fetal tissues, including placenta, are members of the group of microRNAs (miRNAs). Due to their quantity, it can be expected that the fairly larger group of other ncRNAs exerts far stronger effects than miRNAs. The syncytiotrophoblast of fetal origin forms the interface between fetus and mother, and releases permanently extracellular vesicles (EVs) into the maternal circulation which contain fetal proteins and RNA, including ncRNA, for communication with neighboring and distant maternal cells. Disorders of ncRNA in placental tissue, especially in trophoblast cells, and in EVs seem to be involved in pregnancy disorders, potentially as a cause or consequence. This review summarizes the current knowledge on placental ncRNA, their transport in EVs, and their involvement and pregnancy pathologies, as well as their potential for novel diagnostic tools.},

keywords = {extracellular vesicles, ncRNAs, pregnancy, RNA / transcriptomics},

pubstate = {published},

tppubtype = {article}

}

@article{Hufsky2022,

title = {The International Virus Bioinformatics Meeting 2022},

author = {Franziska Hufsky and Denis Beslic and Dimitri Boeckaerts and Sebastian Duchene and Enrique González-Tortuero and Andreas J Gruber and Jiarong Guo and Daan Jansen and John Juma and Kunaphas Kongkitimanon and Antoni Luque and Muriel Ritsch and Gabriel Lencioni Lovate and Luca Nishimura and Célia Pas and Esteban Domingo and Emma Hodcroft and Philippe Lemey and Matthew B Sullivan and Friedemann Weber and Fernando González-Candelas and Sarah Krautwurst and Alba Pérez-Cataluña and Walter Randazzo and Gloria Sánchez and Manja Marz },

doi = {10.3390/v14050973},

year  = {2022},

date = {2022-05-05},

urldate = {2022-05-05},

journal = {Viruses},

volume = {14},

issue = {5},

pages = {973},

abstract = {The International Virus Bioinformatics Meeting 2022 took place online, on 23-25 March 2022, and has attracted about 380 participants from all over the world. The goal of the meeting was to provide a meaningful and interactive scientific environment to promote discussion and collaboration and to inspire and suggest new research directions and questions. The participants created a highly interactive scientific environment even without physical face-to-face interactions. This meeting is a focal point to gain an insight into the state-of-the-art of the virus bioinformatics research landscape and to interact with researchers in the forefront as well as aspiring young scientists. The meeting featured eight invited and 18 contributed talks in eight sessions on three days, as well as 52 posters, which were presented during three virtual poster sessions. The main topics were: SARS-CoV-2, viral emergence and surveillance, virus-host interactions, viral sequence analysis, virus identification and annotation, phages, and viral diversity. This report summarizes the main research findings and highlights presented at the meeting.},

keywords = {annotation, software, virus host interaction, viruses},

pubstate = {published},

tppubtype = {article}

}

@article{nokey,

title = {Nanopore sequencing for mapping of retrotransposon integration sites in the \textit{Dictyostelium discoideum} genome},

author = {Emanuel Barth and Johannes Burggraaff and Akash Srivastava and Thomas Winckler

},

doi = {10.17912/micropub.biology.000543},

year  = {2022},

date = {2022-03-18},

journal = {MicroPubl Biol},

abstract = {The unicellular eukaryote \textit{Dictyostelium discoideum} has a gene-dense haploid genome. This configuration presents mobile elements with the particular challenge of replicating without causing excessive damage to the host through insertional mutagenesis or recombination between repetitive sequences. \textit{D. discoideum} harbors an active population of the retrotransposon TRE5-A that integrates in a narrow window of ~50 bp upstream of tRNA genes. We assume that this integration preference was developed to avoid the disruption of protein-coding genes. Therefore, we recently mapped new integrations of a genetically tagged TRE5-A element at tRNA genes using PCR-based enrichment of integration junctions. However, the PCR-based enrichment produced several artificial DNA fusions that prevented the mapping of integration sites in unknown places of the genome. Here, we reanalyzed the previous experiment using nanopore sequencing. We summarize the advantages and limitations of direct genome resequencing for the mapping of mobile element integrations.},

keywords = {DNA / genomics, nanopore},

pubstate = {published},

tppubtype = {article}

}

@article{nokey,

title = {Draft genome assembly and sequencing dataset of the marine diatom Skeletonema cf. costatum RCC75},

author = {Maria Sorokina and Emanuel Barth and Mahnoor Zulfiqar and Michiel Kwantes and Georg Pohnert and Christoph Steinbeck

},

doi = {10.1016/j.dib.2022.107931},

year  = {2022},

date = {2022-02-19},

urldate = {2022-02-05},

journal = {Data Brief},

volume = {41},

pages = {107931},

abstract = {Diatoms (Bacillariophyceae) are a major constituent of the phytoplankton and have a universally recognized ecological importance. Between 1,000 and 1,300 diatom genera have been described in the literature, but only 10 nuclear genomes have been published and made available to the public up to date. Skeletonema costatum is a cosmopolitan marine diatom, principally occurring in coastal regions, and is one of the most abundant members of the Skeletonema genus. Here we present a draft assembly of the Skeletonema cf. costatum RCC75 genome, obtained from PacBio and Illumina NovaSeq data. This dataset will expand the knowledge of the Bacillariophyceae genetics and contribute to the global understanding of phytoplankton's physiological, ecological, and environmental functioning.},

keywords = {DNA / genomics},

pubstate = {published},

tppubtype = {article}

}

@article{Sofer2022,

title = {A genome-wide CRISPR activation screen reveals Hexokinase 1 as a critical factor in promoting resistance to multi-kinase inhibitors in hepatocellular carcinoma cells},

author = {Summer Sofer and Kevin Lamkiewicz and Shir Armoza Eilat and Shirly Partouche and Manja Marz and Neta Moskovits and Salomon M Stemmer and Amir Shlomai and Ella H Sklan},

doi = {10.1096/fj.202101507RR},

year  = {2022},

date = {2022-02-11},

urldate = {2022-02-11},

journal = {FASEB J },

volume = {36},

issue = {3},

pages = {e22191},

abstract = {Hepatocellular carcinoma (HCC) is often diagnosed at an advanced stage and is, therefore, treated with systemic drugs, such as tyrosine-kinase inhibitors (TKIs). These drugs, however, offer only modest survival benefits due to the rapid development of drug resistance. To identify genes implicated in TKI resistance, a cluster of regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated protein 9 activation screen was performed in hepatoma cells treated with regorafenib, a TKI used as second-line therapy for advanced HCC. The screen results show that Hexokinase 1 (HK1), catalyzing the first step in glucose metabolism, is a top candidate for conferring TKI resistance. Compatible with this, HK1 was upregulated in regorafenib-resistant cells. Using several experimental approaches, both in vitro and in vivo, we show that TKI resistance correlates with HK1 expression. Furthermore, an HK inhibitor resensitized resistant cells to TKI treatment. Together, our data indicate that HK1 may function as a critical factor modulating TKI resistance in hepatoma cells and, therefore, may serve as a biomarker for treatment success.},

keywords = {cancer, DNA / genomics},

pubstate = {published},

tppubtype = {article}

}

@article{nokey,

title = {Small Extracellular Vesicles from Peripheral Blood of Aged Mice Pass the Blood-Brain Barrier and Induce Glial Cell Activation.},

author = {Diana M Morales-Prieto and José M Murrieta-Coxca and Milan Stojiljkovic and Celia Diezel and Priska E Streicher and Julian A Henao-Restrepo and Franziska Röstel and Julia Lindner and Otto W Witte and Sebastian Weis and Christian Schmeer and Manja Marz},

doi = {10.3390/cells11040625},

year  = {2022},

date = {2022-02-11},

journal = {Cells},

volume = {11},

issue = {4},

pages = {625},

abstract = {Extracellular vesicles (EVs), including small EVs (sEVs), are involved in neuroinflammation and neurodegenerative diseases, including Alzheimer's disease, Parkinson's disease, and amyotrophic lateral sclerosis. Yet, increased neuroinflammation can also be detected in the aging brain, and it is associated with increased glial activation. Changes in EV concentration are reported in aging tissues and senescence cells, suggesting a role of EVs in the process of aging. Here, we investigated the effect of peripheral sEVs from aged animals on neuroinflammation, specifically on glial activation. sEVs were isolated from the peripheral blood of young (3 months) and aged (24 months) C57BL/6J wildtype mice and injected into the peripheral blood from young animals via vein tail injections. The localization of EVs and the expression of selected genes involved in glial cell activation, including Gfap, Tgf-β, Cd68, and Iba1, were assessed in brain tissue 30 min, 4 h, and 24 h after injection. We found that sEVs from peripheral blood of aged mice but not from young mice altered gene expression in the brains of young animals. In particular, the expression of the specific astrocyte marker, Gfap, was significantly increased, indicating a strong response of this glial cell type. Our study shows that sEVs from aged mice can pass the blood-brain barrier (BBB) and induce glial cell activation.},

keywords = {aging, extracellular vesicles},

pubstate = {published},

tppubtype = {article}

}

@article{nokey,

title = {Comparative study of ten thogotovirus isolates and their distinct in vivo characteristics},

author = {Jonas Fuchs and Kevin Lamkiewicz and Larissa Kolesnikova and Martin Hölzer and Manja Marz and Georg Kochs},

doi = {10.1128/JVI.01556-21},

year  = {2022},

date = {2022-01-12},

journal = {J Virol},

abstract = {Thogotoviruses are tick-borne arboviruses that comprise a unique genus within the Orthomyxoviridae family. Infections with thogotoviruses primarily cause disease in livestock with occasional reports of human infections suggesting a zoonotic potential. In the past, multiple genetically distinct thogotoviruses were isolated mostly from collected ticks. However, many aspects regarding their phylogenetic relationships, morphological characteristics and virulence in mammals remain unclear. For the present comparative study, we used a collection of ten different thogotovirus isolates from different geographic areas. Next generation sequencing and subsequent phylogenetic analyses revealed a distinct separation of these viruses into two major clades - the Thogoto-like and Dhori-like viruses. Electron microscopy demonstrated a heterogeneous morphology with spherical and filamentous particles being present in virus preparations. To study their pathogenicity, we analyzed the viruses in a small animal model system. In intraperitoneally infected C57BL/6 mice, all isolates showed a tropism for liver, lung and spleen. Importantly, we did not observe horizontal transmission to uninfected, highly susceptible contact mice. The isolates enormously differed in their capacity to induce disease, ranging from subclinical to fatal outcomes. In vivo multi-step passaging experiments of two low-pathogenic isolates showed no increased virulence and sequence analyses of the passaged viruses indicated a high stability of the viral genomes after ten mouse passages. In summary, our analysis demonstrates the broad genetic and phenotypic variability within the thogotovirus genus. Moreover, thogotoviruses are well adapted to mammals but their horizontal transmission seems to depend on ticks as their vectors. Importance Since their discovery over sixty years ago, fifteen genetically distinct members of the thogotovirus genus have been isolated. These arboviruses belong to the Orthomyxovirus family and share many features with influenza viruses. However, numerous of these isolates have not been characterized in depth. In the present study, we comparatively analyzed a collection of ten different thogotovirus isolates to answer basic questions about their phylogenetic relationships, morphology and pathogenicity in mice. Our results highlight shared and unique characteristics of this diverse genus. Taken together, these observations provide a framework for the phylogenic classification and phenotypic characterization of newly identified thogotovirus isolates that could potentially cause severe human infections as exemplified by the recently reported, fatal Bourbon virus cases in the United States.},

keywords = {phylogenetics, 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 = {Age-dependent expression changes of circadian system-related genes reveal a potentially conserved link to aging},

author = {Emanuel Barth and Akash Srivastava and Diane Wengerodt and Milan Stojiljkovic and Hubertus Axer and Otto W Witte and Alexandra Kretz and Manja Marz

},

doi = {10.18632/aging.203788},

year  = {2021},

date = {2021-12-19},

journal = {Aging},

volume = {13},

number = {24},

pages = {25694-25716},

abstract = {The circadian clock system influences the biology of life by establishing circadian rhythms in organisms, tissues, and cells, thus regulating essential biological processes based on the day/night cycle. Circadian rhythms change over a lifetime due to maturation and aging, and disturbances in the control of the circadian system are associated with several age-related pathologies. However, the impact of chronobiology and the circadian system on healthy organ and tissue aging remains largely unknown. Whether aging-related changes of the circadian system's regulation follow a conserved pattern across different species and tissues, hence representing a common driving force of aging, is unclear. Based on a cross-sectional transcriptome analysis covering 329 RNA-Seq libraries, we provide indications that the circadian system is subjected to aging-related gene alterations shared between evolutionarily distinct species, such as Homo sapiens, Mus musculus, Danio rerio, and Nothobranchius furzeri. We discovered differentially expressed genes by comparing tissue-specific transcriptional profiles of mature, aged, and old-age individuals and report on six genes (per2, dec2, cirp, klf10, nfil3, and dbp) of the circadian system, which show conserved aging-related expression patterns in four organs of the species examined. Our results illustrate how the circadian system and aging might influence each other in various tissues over a long lifespan and conceptually complement previous studies tracking short-term diurnal and nocturnal gene expression oscillations.},

keywords = {aging, RNA / transcriptomics},

pubstate = {published},

tppubtype = {article}

}

@article{nokey,

title = {The economical lifestyle of CPR bacteria in groundwater allows little preference for environmental drivers},

author = {Narendrakumar M Chaudhari and Will A Overholt and Perla Abigail Figueroa-Gonzalez and Martin Taubert and Till L V Bornemann and Alexander J Probst and Martin Hölzer and Manja Marz and Kirsten Küsel},

doi = {10.1186/s40793-021-00395-w},

year  = {2021},

date = {2021-12-14},

urldate = {2021-12-14},

journal = {Environ Microbiome},

volume = {16},

number = {1},

pages = {24},

abstract = {Background: The highly diverse Cand. Patescibacteria are predicted to have minimal biosynthetic and metabolic pathways, which hinders understanding of how their populations differentiate in response to environmental drivers or host organisms. Their mechanisms employed to cope with oxidative stress are largely unknown. Here, we utilized genome-resolved metagenomics to investigate the adaptive genome repertoire of Patescibacteria in oxic and anoxic groundwaters, and to infer putative host ranges.



Results: Within six groundwater wells, Cand. Patescibacteria was the most dominant (up to 79%) super-phylum across 32 metagenomes sequenced from DNA retained on 0.2 and 0.1 µm filters after sequential filtration. Of the reconstructed 1275 metagenome-assembled genomes (MAGs), 291 high-quality MAGs were classified as Cand. Patescibacteria. Cand. Paceibacteria and Cand. Microgenomates were enriched exclusively in the 0.1 µm fractions, whereas candidate division ABY1 and Cand. Gracilibacteria were enriched in the 0.2 µm fractions. On average, Patescibacteria enriched in the smaller 0.1 µm filter fractions had 22% smaller genomes, 13.4% lower replication measures, higher proportion of rod-shape determining proteins, and of genomic features suggesting type IV pili mediated cell-cell attachments. Near-surface wells harbored Patescibacteria with higher replication rates than anoxic downstream wells characterized by longer water residence time. Except prevalence of superoxide dismutase genes in Patescibacteria MAGs enriched in oxic groundwaters (83%), no major metabolic or phylogenetic differences were observed. The most abundant Patescibacteria MAG in oxic groundwater encoded a nitrate transporter, nitrite reductase, and F-type ATPase, suggesting an alternative energy conservation mechanism. Patescibacteria consistently co-occurred with one another or with members of phyla Nanoarchaeota, Bacteroidota, Nitrospirota, and Omnitrophota. Among the MAGs enriched in 0.2 µm fractions,, only 8% Patescibacteria showed highly significant one-to-one correlation, mostly with Omnitrophota. Motility and transport related genes in certain Patescibacteria were highly similar to genes from other phyla (Omnitrophota, Proteobacteria and Nanoarchaeota).



Conclusion: Other than genes to cope with oxidative stress, we found little genomic evidence for niche adaptation of Patescibacteria to oxic or anoxic groundwaters. Given that we could detect specific host preference only for a few MAGs, we speculate that the majority of Patescibacteria is able to attach multiple hosts just long enough to loot or exchange supplies.},

keywords = {groundwater, metagenomics},

pubstate = {published},

tppubtype = {article}

}

@article{Christ2021,

title = {Hepatectomy-Induced Alterations in Hepatic Perfusion and Function - Toward Multi-Scale Computational Modeling for a Better Prediction of Post-hepatectomy Liver Function},

author = {Bruno Christ and Maximilian Collatz and Uta Dahmen and Karl-Heinz Herrmann and Sebastian Höpfl and Matthias König and Lena Lambers and Manja Marz and Daria Meyer and Nicole Radde and Jürgen R. Reichenbach and Tim Ricken and Hans-Michael Tautenhahn},

doi = {10.3389/fphys.2021.733868},

year  = {2021},

date = {2021-11-18},

urldate = {2021-11-18},

journal = {Front Physiol},

volume = {12},

pages = {733868},

abstract = {Liver resection causes marked perfusion alterations in the liver remnant both on the organ scale (vascular anatomy) and on the microscale (sinusoidal blood flow on tissue level). These changes in perfusion affect hepatic functions via direct alterations in blood supply and drainage, followed by indirect changes of biomechanical tissue properties and cellular function. Changes in blood flow impose compression, tension and shear forces on the liver tissue. These forces are perceived by mechanosensors on parenchymal and non-parenchymal cells of the liver and regulate cell-cell and cell-matrix interactions as well as cellular signaling and metabolism. These interactions are key players in tissue growth and remodeling, a prerequisite to restore tissue function after PHx. Their dysregulation is associated with metabolic impairment of the liver eventually leading to liver failure, a serious post-hepatectomy complication with high morbidity and mortality. Though certain links are known, the overall functional change after liver surgery is not understood due to complex feedback loops, non-linearities, spatial heterogeneities and different time-scales of events. Computational modeling is a unique approach to gain a better understanding of complex biomedical systems. This approach allows (i) integration of heterogeneous data and knowledge on multiple scales into a consistent view of how perfusion is related to hepatic function; (ii) testing and generating hypotheses based on predictive models, which must be validated experimentally and clinically. In the long term, computational modeling will (iii) support surgical planning by predicting surgery-induced perfusion perturbations and their functional (metabolic) consequences; and thereby (iv) allow minimizing surgical risks for the individual patient. Here, we review the alterations of hepatic perfusion, biomechanical properties and function associated with hepatectomy. Specifically, we provide an overview over the clinical problem, preoperative diagnostics, functional imaging approaches, experimental approaches in animal models, mechanoperception in the liver and impact on cellular metabolism, omics approaches with a focus on transcriptomics, data integration and uncertainty analysis, and computational modeling on multiple scales. Finally, we provide a perspective on how multi-scale computational models, which couple perfusion changes to hepatic function, could become part of clinical workflows to predict and optimize patient outcome after complex liver surgery.},

keywords = {liver, RNA / transcriptomics},

pubstate = {published},

tppubtype = {article}

}

@article{nokey,

title = {Advances in Non-Coding RNA Sequencing},

author = {Julia Micheel and Aram Safrastyan and Damian Wollny

},

doi = {10.3390/ncrna7040070},

year  = {2021},

date = {2021-10-30},

journal = {Noncoding RNA},

volume = {7},

number = {4},

pages = {70},

abstract = {Non-coding RNAs (ncRNAs) comprise a set of abundant and functionally diverse RNA molecules. Since the discovery of the first ncRNA in the 1960s, ncRNAs have been shown to be involved in nearly all steps of the central dogma of molecular biology. In recent years, the pace of discovery of novel ncRNAs and their cellular roles has been greatly accelerated by high-throughput sequencing. Advances in sequencing technology, library preparation protocols as well as computational biology helped to greatly expand our knowledge of which ncRNAs exist throughout the kingdoms of life. Moreover, RNA sequencing revealed crucial roles of many ncRNAs in human health and disease. In this review, we discuss the most recent methodological advancements in the rapidly evolving field of high-throughput sequencing and how it has greatly expanded our understanding of ncRNA biology across a large number of different organisms.},

keywords = {ncRNAs, RNA / transcriptomics},

pubstate = {published},

tppubtype = {article}

}

@article{Martín-Hernández2021,

title = {Chromosome-level genome assembly and transcriptome-based annotation of the oleaginous yeast Rhodotorula toruloides CBS 14},

author = {Giselle C Martín-Hernández and Bettina Müller and Mikołaj Chmielarz and Christian Brandt and Martin Hölzer and Adrian Viehweger and Volkmar Passoth

},

doi = {10.1016/j.ygeno.2021.10.006},

year  = {2021},

date = {2021-10-11},

urldate = {2021-10-11},

journal = {Genomics},

volume = {113},

number = {6},

pages = {4022-4027},

abstract = {Rhodotorula toruloides is an oleaginous yeast with high biotechnological potential. In order to understand the molecular physiology of lipid synthesis in R. toruloides and to advance metabolic engineering, a high-resolution genome is required. We constructed a genome draft of R. toruloides CBS 14, using a hybrid assembly approach, consisting of short and long reads generated by Illumina and Nanopore sequencing, respectively. The genome draft consists of 23 contigs and 3 scaffolds, with a N50 length of 1,529,952 bp, thus largely representing chromosomal organization. The total size of the genome is 20,534,857 bp and the overall GC content is 61.83%. Transcriptomic data from different growth conditions was used to aid species-specific gene annotation. We annotated 9464 genes and identified 11,691 transcripts. Furthermore, we demonstrated the presence of a potential plasmid, an extrachromosomal circular structure of about 11 kb with a copy number about three times as high as the other chromosomes.},

keywords = {annotation, assembly, DNA / genomics, fungi, nanopore},

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{Mock:21a,

title = {BERTax: taxonomic classification of DNA sequences with Deep Neural Networks},

author = {Florian Mock and Fleming Kretschmer and Anton Kriese and Sebastian Böcker and Manja Marz},

url = {https://github.com/f-kretschmer/bertax},

doi = {10.1101/2021.07.09.451778},

year  = {2021},

date = {2021-07-10},

urldate = {2021-07-10},

journal = {bioRxiv},

publisher = {Cold Spring Harbor Laboratory},

abstract = {Taxonomic classification, i.e., the identification and assignment to groups of biological organisms with the same origin and characteristics, is a common task in genetics. Nowadays, taxonomic classification is mainly based on genome similarity search to large genome databases. In this process, the classification quality depends heavily on the database since representative relatives have to be known already. Many genomic sequences cannot be classified at all or only with a high misclassification rate.



Here we present BERTax, a program that uses a deep neural network to pre-cisely classify the superkingdom, phylum, and genus of DNA sequences taxonomically without the need for a known representative relative from a database. For this, BERTax uses the natural language processing model BERT trained to represent DNA. We show BERTax to be at least on par with the state-of-the-art approaches when taxonomically similar species are part of the training data. In case of an entirely novel organism, however, BERTax clearly outperforms any existing approach. Finally, we show that BERTax can also be combined with database approaches to further increase the prediction quality.



Since BERTax is not based on homologous entries in databases, it allows precise taxonomic classification of a broader range of genomic sequences. This leads to a higher number of correctly classified sequences and thus increases the overall information gain.},

keywords = {classification, DNA / genomics, machine learning, software},

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 6and 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},

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{Yates:21,

title = {The evolution and changing ecology of the African hominid oral microbiome},

author = {James A. Fellows Yates and Irina M. Velsko and Franziska Aron and Cosimo Posth and Courtney A. Hofman and Rita M. Austin and Cody E. Parker and Allison E. Mann and Kathrin Nägele and Kathryn Weedman Arthur and John W. Arthur and Catherine C. Bauer and Isabelle Crevecoeur and Christophe Cupillard and Matthew C. Curtis and Love Dalén and Marta Díaz-Zorita Bonilla and J. Carlos Díez Fernández-Lomana and Dorothée G. Drucker and Elena Escribano Escrivá and Michael Francken and Victoria E. Gibbon and Manuel R. González Morales and Ana Grande Mateu and Katerina Harvati and Amanda G. Henry and Louise Humphrey and Mario Menéndez and Dušan Mihailović and Marco Peresani and Sofía Rodríguez Moroder and Mirjana Roksandic and Hélène Rougier and Sandra Sázelová and Jay T. Stock and Lawrence Guy Straus and Jiří Svoboda and Barbara Teßmann and Michael J. Walker and Robert C. Power and Cecil M. Lewis and Krithivasan Sankaranarayanan and Katerina Guschanski and Richard W. Wrangham and Floyd E. Dewhirst and Domingo C. Salazar-García and Johannes Krause and Alexander Herbig and Christina Warinner},

doi = {10.1073/pnas.2021655118},

year  = {2021},

date = {2021-05-18},

urldate = {2021-05-18},

journal = {Proc Natl Acad Sci},

volume = {118},

number = {20},

pages = {e2021655118},

publisher = {Proceedings of the National Academy of Sciences},

abstract = {The oral microbiome plays key roles in human biology, health, and disease, but little is known about the global diversity, variation, or evolution of this microbial community. To better understand the evolution and changing ecology of the human oral microbiome, we analyzed 124 dental biofilm metagenomes from humans, including Neanderthals and Late Pleistocene to present-day modern humans, chimpanzees, and gorillas, as well as New World howler monkeys for comparison. We find that a core microbiome of primarily biofilm structural taxa has been maintained throughout African hominid evolution, and these microbial groups are also shared with howler monkeys, suggesting that they have been important oral members since before the catarrhine–platyrrhine split ca. 40 Mya. However, community structure and individual microbial phylogenies do not closely reflect host relationships, and the dental biofilms of Homo and chimpanzees are distinguished by major taxonomic and functional differences. Reconstructing oral metagenomes from up to 100 thousand years ago, we show that the microbial profiles of both Neanderthals and modern humans are highly similar, sharing functional adaptations in nutrient metabolism. These include an apparent Homo-specific acquisition of salivary amylase-binding capability by oral streptococci, suggesting microbial coadaptation with host diet. We additionally find evidence of shared genetic diversity in the oral bacteria of Neanderthal and Upper Paleolithic modern humans that is not observed in later modern human populations. Differences in the oral microbiomes of African hominids provide insights into human evolution, the ancestral state of the human microbiome, and a temporal framework for understanding microbial health and disease.},

keywords = {ancient DNA, bacteria, evolution, phylogenetics},

pubstate = {published},

tppubtype = {article}

}

@article{Brandt:21,

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 = {10.1101/2021.05.07.443089},

year  = {2021},

date = {2021-05-07},

urldate = {2021-05-07},

journal = {bioRxiv},

publisher = {Cold Spring Harbor Laboratory},

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.



},

note = {Now published in Frontiers in Genetics: https://dx.doi.org/10.3389/fgene.2021.711437},

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

pubstate = {published},

tppubtype = {article}

}

@article{Goettsch:21,

title = {ITN—VIROINF: Understanding (Harmful) Virus-Host Interactions by Linking Virology and Bioinformatics},

author = {Winfried Goettsch and Niko Beerenwinkel and Li Deng and Lars Dölken and Bas E. Dutilh and Florian Erhard and Lars Kaderali and Max Kleist and Roland Marquet and Jelle Matthijnssens and Shawna McCallin and Dino McMahon and Thomas Rattei and Ronald P. Van Rij and David L. Robertson and Martin Schwemmle and Noam Stern-Ginossar and Manja Marz},

doi = {10.3390/v13050766},

year  = {2021},

date = {2021-04-27},

urldate = {2021-01-01},

journal = {Viruses},

volume = {13},

number = {5},

pages = {766},

publisher = {MDPI AG},

abstract = {Many recent studies highlight the fundamental importance of viruses. Besides their important role as human and animal pathogens, their beneficial, commensal or harmful functions are poorly understood. By developing and applying tailored bioinformatical tools in important virological models, the Marie Skłodowska-Curie Initiative International Training Network VIROINF will provide a better understanding of viruses and the interaction with their hosts. This will open the door to validate methods of improving viral growth, morphogenesis and development, as well as to control strategies against unwanted microorganisms. The key feature of VIROINF is its interdisciplinary nature, which brings together virologists and bioinformaticians to achieve common goals. },

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

pubstate = {published},

tppubtype = {article}

}

@article{MartinHernandez:21,

title = {Chromosome-level genome assembly and transcriptome- based annotation of the oleaginous yeast \textit{Rhodotorula toruloides} CBS 14},

author = {Giselle C. Martín-Hernández and Bettina Müller and Mikołaj Chmielarz and Christian Brandt and Martin Hölzer and Adrian Viehweger and Volkmar Passoth},

doi = {10.1101/2021.04.09.439123},

year  = {2021},

date = {2021-04-10},

urldate = {2021-01-01},

journal = {bioRxiv},

publisher = {Cold Spring Harbor Laboratory},

abstract = {Rhodotorula toruloides is an oleaginous yeast with high biotechnological potential. In order to understand the molecular physiology of lipid synthesis in R. toruloides and to advance metabolic engineering, a high-resolution genome is required. We constructed a genome draft of R. toruloides CBS 14, using a hybrid assembly approach, consisting of short and long reads generated by Illumina and Nanopore sequencing, respectively. The genome draft consists of 23 contigs and 3 scaffolds, with a N50 length of 1,529,952 bp, thus largely representing chromosomal organization. The total size is 20,534,857 bp with a GC content of 61.83%. Transcriptomic data from different growth conditions was used to aid species-specific gene annotation. In total we annotated 9,464 genes and identified 11,691 transcripts. Furthermore, we demonstrated the presence of a potential plasmid, an extrachromosomal circular structure of about 11 kb with a copy number about three times as high as the other chromosomes.},

keywords = {annotation, assembly, DNA / genomics, fungi, nanopore},

pubstate = {published},

tppubtype = {article}

}

@article{Wollny:21,

title = {Characterization of RNA content in individual phase-separated coacervate microdroplets},

author = {Damian Wollny and Benjamin Vernot and Jie Wang and Maria Hondele and Anthony Hyman and Karsten Weis and J. Gray Camp and T. -Y. Dora Tang and Barbara Treutlein},

doi = {10.1101/2021.03.08.434405},

year  = {2021},

date = {2021-03-08},

urldate = {2021-01-01},

journal = {bioRxiv},

publisher = {Cold Spring Harbor Laboratory},

abstract = {Liquid-liquid phase separation or condensation is a form of macromolecular compartmentalization. Condensates formed by complex coacervation were hypothesized to have played a crucial part during the origin-of-life. In living cells, condensation organizes biomolecules into a wide range of membraneless compartments. Although RNA is a key component of condensation in cells and the central component of the RNA world hypothesis, little is known about what determines RNA accumulation in condensates and how single condensates differ in their RNA composition. Therefore, we developed an approach to read the RNA content from single condensates using high-throughput sequencing. We find that RNAs which are enriched for specific sequence motifs efficiently accumulate in condensates. These motifs show high sequence similarity to short interspersed elements (SINEs). We observed similar results for protein-derived condensates, demonstrating applicability across different in vitro reconstituted membraneless organelles. Thus, our results provide a new inroad to explore the RNA content of phase-separated droplets at single condensate resolution.},

keywords = {RNA / transcriptomics},

pubstate = {published},

tppubtype = {article}

}

@article{VanDamme:21,

title = {Metagenomics workflow for hybrid assembly, differential coverage binning, metatranscriptomics and pathway analysis (MUFFIN)},

author = {Renaud Van Damme and Martin Hölzer and Adrian Viehweger and Bettina Müller and Erik Bongcam-Rudloff and Christian Brandt},

editor = {Mihaela Pertea},

url = {https://github.com/RVanDamme/MUFFIN},

doi = {10.1371/journal.pcbi.1008716},

year  = {2021},

date = {2021-02-09},

urldate = {2021-02-09},

journal = {PLOS Comput Biol},

volume = {17},

number = {2},

pages = {e1008716},

publisher = {Public Library of Science (PLoS)},

abstract = {Metagenomics has redefined many areas of microbiology. However, metagenome-assembled genomes (MAGs) are often fragmented, primarily when sequencing was performed with short reads. Recent long-read sequencing technologies promise to improve genome reconstruction. However, the integration of two different sequencing modalities makes downstream analyses complex. We, therefore, developed MUFFIN, a complete metagenomic workflow that uses short and long reads to produce high-quality bins and their annotations. The workflow is written by using Nextflow, a workflow orchestration software, to achieve high reproducibility and fast and straightforward use. This workflow also produces the taxonomic classification and KEGG pathways of the bins and can be further used for quantification and annotation by providing RNA-Seq data (optionally). We tested the workflow using twenty biogas reactor samples and assessed the capacity of MUFFIN to process and output relevant files needed to analyze the microbial community and their function. MUFFIN produces functional pathway predictions and, if provided de novo metatranscript annotations across the metagenomic sample and for each bin. MUFFIN is available on github under GNUv3 licence: https://github.com/RVanDamme/MUFFIN.},

keywords = {annotation, assembly, classification, DNA / genomics, metagenomics, RNA / transcriptomics, software},

pubstate = {published},

tppubtype = {article}

}

@article{Heinze:21,

title = {RUNX3 Transcript Variants Have Distinct Roles in Ovarian Carcinoma and Differently Influence Platinum Sensitivity and Angiogenesis},

author = {Karolin Heinze and Martin Hölzer and Martin Ungelenk and Melanie Gerth and Jürgen Thomale and Regine Heller and Claire R. Morden and Kirk J. McManus and Alexander S. Mosig and Matthias Dürst and Ingo B. Runnebaum and Norman Häfner},

doi = {10.3390/cancers13030476},

year  = {2021},

date = {2021-01-26},

urldate = {2021-01-26},

journal = {Cancers},

volume = {13},

number = {3},

pages = {476},

publisher = {MDPI AG},

abstract = {The prognosis of late-stage epithelial ovarian cancer (EOC) patients is affected by chemotherapy response and the malignant potential of the tumor cells. In earlier work, we identified hypermethylation of the runt-related transcription factor 3 gene (RUNX3) as a prognostic biomarker and contrary functions of transcript variants (TV1 and TV2) in A2780 and SKOV3 cells. The aim of the study was to further validate these results and to increase the knowledge about RUNX3 function in EOC. New RUNX3 overexpression models of high-grade serous ovarian cancer (HGSOC) were established and analyzed for phenotypic (IC50 determination, migration, proliferation and angiogenesis assay, DNA damage analysis) and transcriptomic consequences (NGS) of RUNX3 TV1 and TV2 overexpression. Platinum sensitivity was affected by a specific transcript variant depending on BRCA background. RUNX3 TV2 induced an increased sensitivity in BRCA1wt cells (OVCAR3), whereas TV1 increased the sensitivity and induced a G2/M arrest under treatment in BRCA1mut cells (A13-2-12). These different phenotypes relate to differences in DNA repair: homologous recombination deficient A13-2-12 cells show less γH2AX foci despite higher levels of Pt-DNA adducts. RNA-Seq analyses prove transcript variant and cell-line-specific RUNX3 effects. Pathway analyses revealed another clinically important function of RUNX3—regulation of angiogenesis. This was confirmed by thrombospondin1 analyses, HUVEC spheroid sprouting assays and proteomic profiling. Importantly, conditioned media (CM) from RUNX3 TV1 overexpressing A13-2-12 cells induced an increased HUVEC sprouting. Altogether, the presented data support the hypothesis of different functions of RUNX3 transcript variants related to the clinically relevant processes—platinum resistance and angiogenesis. },

keywords = {cancer, differential expression analysis, proteins, RNA / transcriptomics},

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{Kotolloshi:21,

title = {SLC35F2, a Transporter Sporadically Mutated in the Untranslated Region, Promotes Growth, Migration, and Invasion of Bladder Cancer Cells},

author = {Roland Kotolloshi and Martin Hölzer and Mieczyslaw Gajda and Marc-Oliver Grimm and Daniel Steinbach},

doi = {10.3390/cells10010080},

year  = {2021},

date = {2021-01-06},

urldate = {2021-01-01},

journal = {Cells},

volume = {10},

number = {1},

pages = {80},

publisher = {MDPI AG},

abstract = {Bladder cancer is a very heterogeneous disease and the molecular mechanisms of carcinogenesis and progression are insufficiently investigated. From the DNA sequencing analysis of matched non-muscle-invasive bladder cancer (NMIBC) and muscle-invasive bladder cancer (MIBC) samples from eight patients, we identified the tumour-associated gene SLC35F2 to be mutated in the 5′ and 3′ untranslated region (UTR). One mutation in 3′UTR increased the luciferase activity reporter, suggesting its influence on the protein expression of SLC35F2. The mRNA level of SLC35F2 was increased in MIBC compared with NMIBC. Furthermore, in immunohistochemical staining, we observed a strong intensity of SLC35F2 in single tumour cells and in the border cells of solid tumour areas with an atypical accumulation around the nucleus, especially in the MIBC. This suggests that SLC35F2 might be highly expressed in aggressive and invasive tumour cells. Moreover, knockdown of SLC35F2 repressed the growth of bladder cancer cells in the monolayer and spheroid model and suppressed migration and invasion of bladder cancer cells. In conclusion, we suggest that SLC35F2 is involved in bladder cancer progression and might provide a new therapeutic approach, for example, by the anti-cancer drug YM155, a cargo of the SLC35F2 transporter.},

keywords = {cancer, DNA / genomics},

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 = {2010-12-15},

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{Lataretu:20,

title = {RNAflow: An Effective and Simple RNA-Seq Differential Gene Expression Pipeline Using Nextflow},

author = {Marie Lataretu and Martin Hölzer},

url = {https://github.com/hoelzer-lab/rnaflow},

doi = {10.3390/genes11121487},

year  = {2020},

date = {2020-12-10},

urldate = {2020-01-01},

journal = {Genes},

volume = {11},

number = {12},

pages = {1487},

publisher = {MDPI AG},

abstract = {RNA-Seq enables the identification and quantification of RNA molecules, often with the aim of detecting differentially expressed genes (DEGs). Although RNA-Seq evolved into a standard technique, there is no universal gold standard for these data’s computational analysis. On top of that, previous studies proved the irreproducibility of RNA-Seq studies. Here, we present a portable, scalable, and parallelizable Nextflow RNA-Seq pipeline to detect DEGs, which assures a high level of reproducibility. The pipeline automatically takes care of common pitfalls, such as ribosomal RNA removal and low abundance gene filtering. Apart from various visualizations for the DEG results, we incorporated downstream pathway analysis for common species as Homo sapiens and Mus musculus. We evaluated the DEG detection functionality while using qRT-PCR data serving as a reference and observed a very high correlation of the logarithmized gene expression fold changes.},

keywords = {differential expression analysis, RNA / transcriptomics, software},

pubstate = {published},

tppubtype = {article}

}

@article{Hufsky:20b,

title = {The International Virus Bioinformatics Meeting 2020},

author = {Franziska Hufsky and Niko Beerenwinkel and Irmtraud M. Meyer and Simon Roux and Georgia May Cook and Cormac M. Kinsella and Kevin Lamkiewicz and Mike Marquet and David F. Nieuwenhuijse and Ingrida Olendraite and Sofia Paraskevopoulou and Francesca Young and Ronald Dijkman and Bashar Ibrahim and Jenna Kelly and Philippe Le Mercier and Manja Marz and Alban Ramette and Volker Thiel},

doi = {10.3390/v12121398},

year  = {2020},

date = {2020-12-06},

urldate = {2020-01-01},

journal = {Viruses},

volume = {12},

number = {12},

pages = {1398},

publisher = {MDPI AG},

abstract = {The International Virus Bioinformatics Meeting 2020 was originally planned to take place in Bern, Switzerland, in March 2020. However, the COVID-19 pandemic put a spoke in the wheel of almost all conferences to be held in 2020. After moving the conference to 8–9 October 2020, we got hit by the second wave and finally decided at short notice to go fully online. On the other hand, the pandemic has made us even more aware of the importance of accelerating research in viral bioinformatics. Advances in bioinformatics have led to improved approaches to investigate viral infections and outbreaks. The International Virus Bioinformatics Meeting 2020 has attracted approximately 120 experts in virology and bioinformatics from all over the world to join the two-day virtual meeting. Despite concerns being raised that virtual meetings lack possibilities for face-to-face discussion, the participants from this small community created a highly interactive scientific environment, engaging in lively and inspiring discussions and suggesting new research directions and questions. The meeting featured five invited and twelve contributed talks, on the four main topics: (1) proteome and RNAome of RNA viruses, (2) viral metagenomics and ecology, (3) virus evolution and classification and (4) viral infections and immunology. Further, the meeting featured 20 oral poster presentations, all of which focused on specific areas of virus bioinformatics. This report summarizes the main research findings and highlights presented at the meeting.},

keywords = {classification, conference report, evolution, metagenomics, software, 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}

}