WP 1.1 Virus identification

Despite large ongoing efforts to identify viruses in humans, animals and the environment, there are still multiple challenges remaining in the identification of novel viruses. These challenges remain both in the wet-lab as well as on the bioinformatical side. On the wet-lab side, divergent viruses can now be identified from an infected sample en masse, but different research groups use different protocols to analyse these samples and prepare them for sequencing. All the current approaches result in relative distributions, which lack (not only clinically important) absolute quantitation. Sample preparation, methods and standardisation are prerequisites for meaningful and comparable work. On the bioinformatical side, the most frequently used similarity-based virus identification approaches are largely limited by available databases, which are incomplete and often poorly annotated. VIROINF (together with the European Virus Bioinformatics Center) aims to set up a multiple-layer database for phages and their hosts (WP 1.2).

VIROINF aims to quantify viruses by four approaches (ESR 11):

spiking in known amounts of selected viruses into a sample;
developing qPCR assays for a selection of abundant viruses in particular sample sets;
counting virus particles using flow cytometric approaches in collaboration with Corina Brussaard from the Netherlands Institute for Sea Research; and
NGS-based quantification developed in collaboration with Baseclear.

The novel wet-lab approaches will be combined with newly developed advanced bioinformatical tools to identify viruses from metagenomic datasets (ESR 12), using sequence-dependent and -independent approaches. Motif searches, k-mer frequencies, and genome organisation are de novo approaches that will complement homology-based methods, allowing the detection of known and unknown viruses, yielding a comprehensive detection pipeline of all types of viruses ranging from well-studied human pathogens to completely novel bacteriophages. A range of available tools for taxonomic classification will be combined into a rapid pipeline.

PhD Projects

Main projects:

Side projects:

Journal Articles

Wu, Ling-Yi; Pappas, Nikolaos; Wijesekara, Yasas; Piedade, Gonçalo J.; Brussaard, Corina P. D.; Dutilh, Bas E.

Benchmarking Bioinformatic Virus Identification Tools Using Real-World Metagenomic Data across Biomes Journal Article

In: bioRxiv, 2023.

Abstract | Links | BibTeX

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

ITN -- VIROINF: Understanding (Harmful) Virus-Host Interactions by Linking Virology and Bioinformatics Journal Article

In: Viruses, vol. 13, no. 5, pp. 766, 2021.

Abstract | Links | BibTeX

Presentations

Basler, Nikolas; de Graaf, Dirk C.; Smet, Lina De; Matthijnssens, Jelle

The honey bee gut microbiome – a diversity profile of different gut parts and seasons across eight European countries Presentation

Oral presentation at 9th European Congress of Apidology (EurBee9), 20.09.2022, (Best Oral Presentation).

Abstract | BibTeX

@misc{nokey,

title = {The honey bee gut microbiome – a diversity profile of different gut parts and seasons across eight European countries},

author = {Nikolas Basler and Dirk C. de Graaf and Lina De Smet and Jelle Matthijnssens},

year  = {2022},

date = {2022-09-20},

urldate = {2022-09-20},

abstract = {As a highly productive pollinator of flowering plants, the honey bee (Apis mellifera) plays an important role in ecology and agriculture. However, managed honey bee colonies are suffering from a number of stressors, including pathogens, parasites, and the use of pesticides. Studying and improving the health of honey bees is therefore of great ecologic and economic interest. Previous studies have shown that the honey bee gut houses a stable bacterial microbiome of only approximately eight core species. On the other hand, recent studies described a higher diversity in bacteria on the sub-species level as well as in bacteriophages (or phages, i.e. viruses that infect bacteria). Additionally, it has been shown that the gut microbiome affects the bees’ development, immune signalling and behaviour. 

This project is part of the EU-funded Innovative Training Network VIROINF (grant agreement No 955974) which revolves around virus-host interactions and aims to facilitate the connections between the fields of virology and bioinformatics. Honey bees from eight different European countries (Belgium, France, Germany, Netherlands, Portugal, Romania, Switzerland and United Kingdom) were collected during spring, summer and autumn 2020 as part of the EU-funded B-GOOD project (grant agreement No 817622). From each sample, midguts, ileums and rectums of 10 individual bees have been pooled and processed to generate Illumina libraries for shotgun sequencing. From the resulting data, the diversity of the microbiome was assessed based on species-level abundances as well as shared fractions of single-nucleotide variations (SNVs) in orthologous core genes within species. Preliminary analysis of the core species abundance profiles suggests that the rectum contains the entire bacterial community, of which ileum and midgut contain nested subsets. Unlike species abundances, SNV profiles within some core species appear to separate by geographic origin. 

These findings will also inform future experiments to gain more insight into the complex interactions between the honey bee, its gut bacteria and their viruses. We thereby aim to contribute to a better understanding of honey bee health and disease.},

howpublished = {Oral presentation at 9th European Congress of Apidology (EurBee9)},

note = {Best Oral Presentation},

keywords = {},

pubstate = {published},

tppubtype = {presentation}

}

As a highly productive pollinator of flowering plants, the honey bee (Apis mellifera) plays an important role in ecology and agriculture. However, managed honey bee colonies are suffering from a number of stressors, including pathogens, parasites, and the use of pesticides. Studying and improving the health of honey bees is therefore of great ecologic and economic interest. Previous studies have shown that the honey bee gut houses a stable bacterial microbiome of only approximately eight core species. On the other hand, recent studies described a higher diversity in bacteria on the sub-species level as well as in bacteriophages (or phages, i.e. viruses that infect bacteria). Additionally, it has been shown that the gut microbiome affects the bees’ development, immune signalling and behaviour.
This project is part of the EU-funded Innovative Training Network VIROINF (grant agreement No 955974) which revolves around virus-host interactions and aims to facilitate the connections between the fields of virology and bioinformatics. Honey bees from eight different European countries (Belgium, France, Germany, Netherlands, Portugal, Romania, Switzerland and United Kingdom) were collected during spring, summer and autumn 2020 as part of the EU-funded B-GOOD project (grant agreement No 817622). From each sample, midguts, ileums and rectums of 10 individual bees have been pooled and processed to generate Illumina libraries for shotgun sequencing. From the resulting data, the diversity of the microbiome was assessed based on species-level abundances as well as shared fractions of single-nucleotide variations (SNVs) in orthologous core genes within species. Preliminary analysis of the core species abundance profiles suggests that the rectum contains the entire bacterial community, of which ileum and midgut contain nested subsets. Unlike species abundances, SNV profiles within some core species appear to separate by geographic origin.
These findings will also inform future experiments to gain more insight into the complex interactions between the honey bee, its gut bacteria and their viruses. We thereby aim to contribute to a better understanding of honey bee health and disease.

Research » WP 1.1 Virus identification

PhD Projects

Journal Articles

Presentations