Research » WP 1.3 Virus-host interactions

@article{nokey,

title = {Parallel evolution and enhanced virulence upon in vivo passage of an RNA virus in \textit{Drosophila melanogaster}.},

author = {Oscar M. Lezcano and Lara Fuhrmann and Gayatri Ramakrishnan and Niko Beerenwinkel and Martijn A. Huynen and Ronald P. van Rij },

doi = {10.1093/ve/vead074},

year  = {2023},

date = {2023-12-15},

urldate = {2023-12-15},

journal = {Virus Evol},

volume = {9},

issue = {2},

pages = {vead074},

abstract = {Virus evolution is strongly affected by antagonistic co-evolution of virus and host. Host immunity positively selects for viruses that evade the immune response, which in turn may drive counter-adaptations in host immune genes. We investigated how host immune pressure shapes virus populations, using the fruit fly Drosophila melanogaster and its natural pathogen Drosophila C virus (DCV), as a model. We performed an experimental evolution study in which DCV was serially passaged for ten generations in three fly genotypes differing in their antiviral RNAi response: wild-type flies and flies in which the endonuclease gene Dicer-2 was either overexpressed or inactivated. All evolved virus populations replicated more efficiently in vivo and were more virulent than the parental stock. The number of polymorphisms increased in all three host genotypes with passage number, which was most pronounced in Dicer-2 knockout flies. Mutational analysis showed strong parallel evolution, as mutations accumulated in a specific region of the VP3 capsid protein in every lineage in a host genotype-independent manner. The parental tyrosine at position ninety-five of VP3 was substituted with either one of five different amino acids in fourteen out of fifteen lineages. However, no consistent amino acid changes were observed in the viral RNAi suppressor gene 1A, nor elsewhere in the genome in any of the host backgrounds. Our study indicates that the RNAi response restricts the sequence space that can be explored by viral populations. Moreover, our study illustrates how evolution towards higher virulence can be a highly reproducible, yet unpredictable process.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{nokey,

title = {The International Virus Bioinformatics Meeting 2023.},

author = {Franziska Hufsky and Ana B. Abecasis and Artem Babaian and Sebastian Beck and Liam Brierley and Simon Dellicour and Christian Eggeling and Santiago F. Elena and Udo Gieraths and Anh D. Ha and Will Harvey and Terry C. Jones and Kevin Lamkiewicz and Gabriel Lencioni Lovate and Dominik Lücking and Martin Machyna and Luca Nishimura and Maximilian K. Nocke and Bernard Y. Renard and Shoichi Sakaguchi and Lygeri Sakellaridi and Jannes Spangenberg and Maria Tarradas-Alemany and Sandra Triebel and Yulia Vakulenko and Yasas Wijesekara and Fernando González-Candelas and Sarah Krautwurst and Alba Pérez-Cataluña and Walter Randazzo and Gloria Sánchez and Manja Marz },

doi = {10.3390/v15102031},

year  = {2023},

date = {2023-09-30},

urldate = {2023-09-30},

journal = {Viruses},

volume = {15},

issue = {10},

pages = {2031},

abstract = {The 2023 International Virus Bioinformatics Meeting was held in Valencia, Spain, from 24-26 May 2023, attracting approximately 180 participants worldwide. The primary objective of the conference was to establish a dynamic scientific environment conducive to discussion, collaboration, and the generation of novel research ideas. As the first in-person event following the SARS-CoV-2 pandemic, the meeting facilitated highly interactive exchanges among attendees. It served as a pivotal gathering for gaining insights into the current status of virus bioinformatics research and engaging with leading researchers and emerging scientists. The event comprised eight invited talks, 19 contributed talks, and 74 poster presentations across eleven sessions spanning three days. Topics covered included machine learning, bacteriophages, virus discovery, virus classification, virus visualization, viral infection, viromics, molecular epidemiology, phylodynamic analysis, RNA viruses, viral sequence analysis, viral surveillance, and metagenomics. This report provides rewritten abstracts of the presentations, a summary of the key research findings, and highlights shared during the meeting.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{nokey,

title = {grandR: a comprehensive package for nucleotide conversion RNA-seq data analysis},

author = {Teresa Rummel and Lygeri Sakellaridi and Florian Erhard

},

doi = {10.1038/s41467-023-39163-4},

year  = {2023},

date = {2023-06-15},

journal = {Nat Commun},

volume = {14},

issue = {1},

pages = {3559},

abstract = {Metabolic labeling of RNA is a powerful technique for studying the temporal dynamics of gene expression. Nucleotide conversion approaches greatly facilitate the generation of data but introduce challenges for their analysis. Here we present grandR, a comprehensive package for quality control, differential gene expression analysis, kinetic modeling, and visualization of such data. We compare several existing methods for inference of RNA synthesis rates and half-lives using progressive labeling time courses. We demonstrate the need for recalibration of effective labeling times and introduce a Bayesian approach to study the temporal dynamics of RNA using snapshot experiments.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{nokey,

title = {Prediction of virus-host association using protein language models and multiple instance learning},

author = {Dan Liu and Francesca Young and David L. Robertson and Ke Yuan},

doi = {10.1101/2023.04.07.536023},

year  = {2023},

date = {2023-04-08},

urldate = {2023-04-08},

journal = {bioRxiv},

abstract = {Predicting virus-host association is essential to understand how viruses interact with host species, and discovering new therapeutics for viral diseases across humans and animals. Currently, the host of the majority of viruses is unknown. Here, we introduce EvoMIL, a deep learning method that predicts virus-host association at the species level from viral sequence only. The method combines a pre-trained large protein language model and attention-based multiple instance learning to allow protein-orientated predictions. Our results show that protein embeddings capture stronger predictive signals than traditional handcrafted features, including amino acids and DNA k-mers, and physio-chemical properties. EvoMIL binary classifiers achieve AUC values of over 0.95 for all prokaryotic and nearly 0.8 for almost all eukaryotic hosts. In multi-host prediction tasks, EvoMIL achieved median performance improvements of 8.6% in prokaryotic hosts and 1.8% in eukaryotic hosts. Furthermore, EvoMIL estimates the importance of single proteins in the prediction and maps them to an embedding landscape of all viral proteins, where proteins with similar functions are distinctly clustered together.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{nokey,

title = {Expanding epidemic of recently acquired HCV in HIV-coinfected patients over a period of 10 years},

author = {Christiana Graf and Lara Fuhrmann and Thomas Lutz and Christoph Stephan and Gaby Knecht and Peter Gute and Markus Bickel and Kai-Henrik Peiffer and Fabian Finkelmeier and Georg Dultz and Antonia Mondorf and Nils Wetzstein and Natalie Filmann and Eva Herrmann and Stefan Zeuzem and Niko Beerenwinkel and Julia Dietz and Christoph Sarrazin},

doi = {10.1016/j.jhepr.2023.100701},

year  = {2023},

date = {2023-02-19},

journal = {JHEP Rep},

volume = {5},

issue = {7},

pages = {100701},

abstract = {Background & aims: Ongoing transmission of HCV infections is associated with risk factors such as drug injection, needlestick injuries, and men who have sex with men (MSM). Ways of transmission, the course of acute infection, changes of virologic features, and incidence over time are not well known.



Methods: Over a period of 10 years, n = 161 patients with recently acquired HCV infection (RAHC) (median follow-up 6.8 years) were prospectively enrolled. NS5B sequencing was performed to re-evaluate the HCV genotype (GT) and for phylogenetic analyses.



Results: Patients with RAHC were mainly male (92.5%), MSM (90.1%), and HIV-coinfected (86.3%). Transmission risk factors for MSM and non-MSM were sexual risk behaviour (100 and 6.3%, respectively), injection drug use (9.7 and 37.5%, respectively), and nasal drug use (15.2 and 0%, respectively). Spontaneous and interferon- or direct-acting antiviral-based clearance rates were 13.6, 84.3 and 93.4%, respectively. Mean RAHC declined from 19.8 in the first to 13.2 in the past five study years. Although the majority of infections was caused by HCV GT1a, the frequency of HCV GT4d and slightly HCV GT3a increased over time. No relevant clustering of HCV isolates was observed in non-MSM. However, 45% of HCV GT1a and 100% of HCV GT4d MSM cases clustered with MSM isolates from other countries. Travel-associated infections were supported by personal data in an MSM subgroup. No international clustering was detected in MSM with HCV GT1b or HCV GT3a.



Conclusions: RAHCs were mainly diagnosed in HIV-coinfected MSM patients and were associated with sexual risk behaviour. Spontaneous clearance rates were low, and phylogenetic clusters were observed in the majority of patients.



Impact and implications: We evaluated the occurrence and transmission of recently acquired HCV infections (RAHCs) over a period of 10 years. Our data demonstrate that the presence of RAHC was mainly found in HIV-coinfected MSM, with internationally connected transmission networks being observed in the majority of patients. Spontaneous clearance rates were low, and reinfection rates increased mainly driven by a small subset of MSM patients with high-risk behaviour.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Rummel2022,

title = {grandR: a comprehensive package for nucleotide conversion sequencing data analysis},

author = {Teresa Rummel and Lygeri Sakellaridi and Florian Erhard },

doi = {10.1101/2022.09.12.507665},

year  = {2022},

date = {2022-09-15},

urldate = {2022-09-15},

journal = {bioRxiv},

abstract = {Metabolic labeling of RNA is a powerful technique for studying the temporal dynamics of gene expression. Nucleotide conversion approaches greatly facilitate the generation of data but introduce challenges for their analysis. We here present grandR, a comprehensive package for quality control, differential gene expression analysis, kinetic modeling, and visualization of such data. We compare several existing methods for inference of RNA synthesis rates and half-lives using progressive labeling time courses. We demonstrate the need for recalibration of effective labeling times and introduce a Bayesian approach to study the temporal dynamics of RNA using snapshot experiments.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{nokey,

title = {Arbovirus-vector protein interactomics identifies Loquacious as a co-factor for dengue virus replication in Aedes mosquitoes},

author = {Benoit Besson and Oscar M. Lezcano and Gijs J Overheul and Kirsten Janssen and Cornelia G. Spruijt and Michiel Vermeulen and Jieqiong Qu and Ronald P. van Rij},

doi = {10.1371/journal.ppat.1010329},

year  = {2022},

date = {2022-09-08},

urldate = {2022-09-08},

journal = {PLoS Pathogens},

volume = {18},

issue = {9},

pages = {e1010329},

abstract = {Efficient virus replication in Aedes vector mosquitoes is essential for the transmission of arboviral diseases such as dengue virus (DENV) in human populations. Like in vertebrates, virus-host protein-protein interactions are essential for viral replication and immune evasion in the mosquito vector. Here, 79 mosquito host proteins interacting with DENV non-structural proteins NS1 and NS5 were identified by label-free mass spectrometry, followed by a functional screening. We confirmed interactions with host factors previously observed in mammals, such as the oligosaccharyltransferase complex, and we identified protein-protein interactions that seem to be specific for mosquitoes. Among the interactors, the double-stranded RNA (dsRNA) binding protein Loquacious (Loqs), an RNA interference (RNAi) cofactor, was found to be essential for efficient replication of DENV and Zika virus (ZIKV) in mosquito cells. Loqs did not affect viral RNA stability or translation of a DENV replicon and its proviral activity was independent of its RNAi regulatory activity. Interestingly, Loqs colocalized with DENV dsRNA replication intermediates in infected cells and directly interacted with high affinity with DENV RNA in the 3' untranslated region in vitro (KD = 48-62 nM). Our study provides an interactome for DENV NS1 and NS5 and identifies Loqs as a key proviral host factor in mosquitoes. We propose that DENV hijacks a factor of the RNAi mechanism for replication of its own RNA.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{nokey,

title = {Early detection and surveillance of SARS-CoV-2 genomic variants in wastewater using COJAC},

author = {Katharina Jahn and David Dreifuss and Ivan Topolsky and Anina Kull and Pravin Ganesanandamoorthy and Xavier Fernandez-Cassi and Carola Bänziger and Alexander J. Devaux and Elyse Stachler and Lea Caduff and Federica Cariti and Alex Tuñas Corzón and Lara Fuhrmann and Chaoran Chen and Kim Philipp Jablonski and Sarah Nadeau and Mirjam Feldkamp and Christian Beisel and Catharine Aquino and Tanja Stadler and Christoph Ort and Tamar Kohn and Timothy R. Julian and Niko Beerenwinkel},

doi = {10.1038/s41564-022-01185-x},

year  = {2022},

date = {2022-07-18},

urldate = {2022-07-18},

journal = {Nat Microbiol},

abstract = {The continuing emergence of SARS-CoV-2 variants of concern and variants of interest emphasizes the need for early detection and epidemiological surveillance of novel variants. We used genomic sequencing of 122 wastewater samples from three locations in Switzerland to monitor the local spread of B.1.1.7 (Alpha), B.1.351 (Beta) and P.1 (Gamma) variants of SARS-CoV-2 at a population level. We devised a bioinformatics method named COJAC (Co-Occurrence adJusted Analysis and Calling) that uses read pairs carrying multiple variant-specific signature mutations as a robust indicator of low-frequency variants. Application of COJAC revealed that a local outbreak of the Alpha variant in two Swiss cities was observable in wastewater up to 13 d before being first reported in clinical samples. We further confirmed the ability of COJAC to detect emerging variants early for the Delta variant by analysing an additional 1,339 wastewater samples. While sequencing data of single wastewater samples provide limited precision for the quantification of relative prevalence of a variant, we show that replicate and close-meshed longitudinal sequencing allow for robust estimation not only of the local prevalence but also of the transmission fitness advantage of any variant. We conclude that genomic sequencing and our computational analysis can provide population-level estimates of prevalence and fitness of emerging variants from wastewater samples earlier and on the basis of substantially fewer samples than from clinical samples. Our framework is being routinely used in large national projects in Switzerland and the UK.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{nokey,

title = {Quantification of the spread of SARS-CoV-2 variant B.1.1.7 in Switzerland},

author = {Chaoran Chen and Sarah Ann Nadeau and Ivan Topolsky and Marc Manceau and Jana S. Huisman and Kim Philipp Jablonski and Lara Fuhrmann and David Dreifuss and Katharina Jahn and Christiane Beckmann and Maurice Redondo and Christoph Noppen and Lorenz Risch and Martin Risch and Nadia Wohlwend and Sinem Kas and Thomas Bodmer and Tim Roloff and Madlen Stange and Adrian Egli and Isabella Eckerle and Laurent Kaiser and Rebecca Denes and Mirjam Feldkamp and Ina Nissen and Natascha Santacroce and Elodie Burcklen and Catharine Aquino and Andreia Cabral de Gouvea and Maria Domenica Moccia and Simon Grüter and Timothy Sykes and Lennart Opitz and Griffin White and Laura Neff and Doris Popovic and Andrea Patrignani and Jay Tracy and Ralph Schlapbach and Emmanouil T Dermitzakis and Keith Harshman and Ioannis Xenarios and Henri Pegeot and Lorenzo Cerutti and Deborah Penet and Anthony Blin and Melyssa Elies and Christian L. Althaus and Christian Beisel and Niko Beerenwinkel and Martin Ackermann and Tanja Stadler},

doi = {10.1016/j.epidem.2021.100480},

year  = {2021},

date = {2021-08-09},

urldate = {2021-08-09},

journal = {Epidemics},

volume = {37},

pages = {100480},

abstract = {Background: In December 2020, the United Kingdom (UK) reported a SARS-CoV-2 Variant of Concern (VoC) which is now named B.1.1.7. Based on initial data from the UK and later data from other countries, this variant was estimated to have a transmission fitness advantage of around 40-80 % (Volz et al., 2021; Leung et al., 2021; Davies et al., 2021).



Aim: This study aims to estimate the transmission fitness advantage and the effective reproductive number of B.1.1.7 through time based on data from Switzerland.



Methods: We generated whole genome sequences from 11.8 % of all confirmed SARS-CoV-2 cases in Switzerland between 14 December 2020 and 11 March 2021. Based on these data, we determine the daily frequency of the B.1.1.7 variant and quantify the variant's transmission fitness advantage on a national and a regional scale.



Results: We estimate B.1.1.7 had a transmission fitness advantage of 43-52 % compared to the other variants circulating in Switzerland during the study period. Further, we estimate B.1.1.7 had a reproductive number above 1 from 01 January 2021 until the end of the study period, compared to below 1 for the other variants. Specifically, we estimate the reproductive number for B.1.1.7 was 1.24 [1.07-1.41] from 01 January until 17 January 2021 and 1.18 [1.06-1.30] from 18 January until 01 March 2021 based on the whole genome sequencing data. From 10 March to 16 March 2021, once B.1.1.7 was dominant, we estimate the reproductive number was 1.14 [1.00-1.26] based on all confirmed cases. For reference, Switzerland applied more non-pharmaceutical interventions to combat SARS-CoV-2 on 18 January 2021 and lifted some measures again on 01 March 2021.



Conclusion: The observed increase in B.1.1.7 frequency in Switzerland during the study period is as expected based on observations in the UK. In absolute numbers, B.1.1.7 increased exponentially with an estimated doubling time of around 2-3.5 weeks. To monitor the ongoing spread of B.1.1.7, our plots are available online.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{nokey,

title = {Quantitative measures of within-host viral genetic diversity},

author = {Lara Fuhrmann and Kim Philipp Jablonski and Niko Beerenwinkel

},

doi = {10.1016/j.coviro.2021.06.002},

year  = {2021},

date = {2021-06-18},

urldate = {2021-06-18},

journal = {Curr Opin Virol},

volume = {49},

pages = {157-163},

abstract = {The genetic diversity of virus populations within their hosts is known to influence disease progression, treatment outcome, drug resistance, cell tropism, and transmission risk, and the study of dynamic changes of genetic heterogeneity can provide insights into the evolution of viruses. Several measures to quantify within-host genetic diversity capturing different aspects of diversity patterns in a sample or population are used, based on incidence, relative frequencies, pairwise distances, or phylogenetic trees. Here, we review and compare several of these measures.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{nokey,

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 von 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 = {2021-04-27},

journal = {Viruses},

volume = {13},

number = {5},

pages = {766},

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 = {},

pubstate = {published},

tppubtype = {article}

}