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UGent Faculteit Diergeneeskunde, departement virologie, parasitologie en immunologie

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Proposal item traineeship banaba 2017-2018:

Our research group is focusing on the validation of novel sequencing technologies as a diagnostic tool for viral infections, mainly in pigs. A bioinformatics pipeline is being developed and needs to process raw nanopore sequencing reads into an understandable report. 

This involves different computational steps which needs to be validated, including quality control, viral database assembly, finding the best and most sensitive tool to identify viral sequences, de novo assembly of viral genomes, mapping of viral genomes, visualisation… A high performant in house computing system is available, but also HPC of Ghent University can be used for data analysis.

Abstract advanced bachelor of bioinformatics 2019-2020: Development of bioinformatics applications for real-time geographical tracing of viral and bacterial infectious diseases

In the late 1980s, the syndrome that caused reproductive and respiratory problems in pigs was first referred to as 'Mystery Swine Disease' and today as 'Porcine Reproductive and Respiratory Syndrome (PRRS)'. To this day, this disease remains one of the most widespread and economically devastating diseases in pig industry1. The PRRS virus (PRRSV) is a member of the genus Porarterivirus belonging to the family Arteriviridae within the order Nidovirales. This relatively small enveloped virus contains a single-stranded positive sense RNA genome with a length of about 15 kb, encoding 10 ORF’s(open reading frames)2,3. The first characterization of circulating European (type 1) and North American (type 2) genotype isolates turned out to be surprisingly genetically different. Although the general disease phenotype, broad clinical symptoms, genomic organization and time of onset were all similar, these strains differed by ~ 40% at the nucleotide level4.

The rapid evolution of the virus makes it possible to derive the history of an epidemic from its genomic data. But with such mutation speed, backmutations can complicate phylogenic and genomic conclusions. In addition, the increased availability of novel sequencing technologies has allowed to perform rapid genome sequencing of pathogens. Such genomic information can be linked and plotted on a spatiotemporal map. This shows the spreading of the virus at a population level and helps to understand the evolution of the virus.

For setting up the spatiotemporal analysis pipeline the Nextstrain5 software package was completely adapted towards PRRSV genomes. Nextstrain consists of data curation, analysis and visualization components. Python scripts maintain a database with available sequences and associated metadata. A set of instruments performs phylodynamic analyses6, including sub-sampling, multiple-sequence alignment, phylogenetic inferences, temporal dating of ancestor nodes, and discrete geographical reconstruction of features, including inferences of the most likely transmission events. This uses the maximum probability analyses implemented in TreeTime and allowed a complete analysis of the entire PRRSV orf5 dataset (n = 768 samples) in 20 minutes7. Multiple views in different panels of the data are presented and remain synchronized when interacting with the data. From the orf5 dataset it could be concluded that most sequences do not differ that much from each other. The highest number of strains can be found in Italy, Spain and the United Kingdom. These are also located mostly in the same clade. Other countries contain a mixture of different clades. This can probably be explained by the large free transport of pigs throughout Europe, which allows the virus to spread quickly over large areas. When looking at whole genome sequences, much less data was available (n = 113). Here, the observed clusters were mainly regionally bound. Nevertheless, further addition of whole genome sequences are required to further support this hypothesis.

Finally, from these samples, a vaccinology analysis was performed. With the help of peptide-specific serum antibodies the antigenic regions in the envelope proteins were characterized and neutralizing regions were mapped8. Through the use of emboss scripts and the python-based visualization tool; Plotly, these regions were compared with known vaccination strains. By implementation of a scoring system, the most appropriate vaccine strain can be proposed. When these results can be linked to in vitro data from neutralization studies, we can evaluate whether this approach can be used to predict vaccine effectiveness.

References

  1. Lunney, J. K., Benfield, D. A. & Rowland, R. R. R. Porcine reproductive and respiratory syndrome virus: An update on an emerging and re-emerging viral disease of swine. Virus Res. 154, 1–6 (2010).
  2. Cavanagh, D. N. A new order comprising Coronaviridae and Arteriviridae. Arch. Virol. 142, 629–633 (1997).
  3. Snijder, E. J. & Meulenberg, J. J. M. the Molecular Biology of. J. Gen. Virol. 79, 961–979 (1998).
  4. Morrison, R.B., Collins, J.E., Harris, L., Christianson, W.T., Benfield, D.A., Chladek, D. W., Gorcyca, D.E., Joo, H.S., 1992. Serologic evidence incriminating a recently isolated virus (ATCC VR-2332) as the cause of swine infertility and respiratory syndrome (SIRS). J. Vet. Diagn. Investig. 4, 186–188.
  5. Hadfield et al., Nextstrain: real-time tracking of pathogen evolution, Bioinformatics (2018)
  6. Volz,E.M. et al. (2013) Viral phylodynamics. PLoS Comput. Biol., 9, e1002947
  7. Sagulenko,P. et al. (2018) Treetime: maximum-likelihood phylodynamic analysis. Virus Evol., 4, vex042
  8. Vanhee, M., Van Breedam, W., Costers, S., Geldhof, M., Noppe, Y., & Nauwynck, H. (2011). Characterization of antigenic regions in the porcine reproductive and respiratory syndrome virus by the use of peptide-specific serum antibodies. Vaccine29(29-30), 4794–4804. https://doi.org/10.1016/j.vaccine.2011.04.071

 

Abstract Bachelor Project FBT 2018-2019Development and optimization of ddPCR for detection and qualification of a SNP linked to anthelmintic resistance in Trichuris trichiura

Soil-transmitted helminths (Ascaris lumbricoides, Trichuris trichiura and the hookworms Ancylostoma duodenale and Necator americanus) are a group of intestinal parasitic nematodes that infect one fifth of the world’s population and cause significant morbidity. Preventive chemotherapy with benzimidazoles (BZ, i.e. albendazole or mebendazole) is implemented as the main strategy for controlling Soil-transmitted helminthiasis. However, there is grounded fear that drug resistance may develop as a result of (1) the high degree of drug pressure, (2) the suboptimal doses and (3) the reliance on only two drugs that have a common mode of action.

Experience from the veterinary field has further ratified these concerns. In veterinary nematodes, BZ-resistance is caused by single nucleotide polymorphisms (SNPs) located in the β-tubulin isotype 1 gene at codon position 167, 198 and/or 200. Therefore, the development of a system to monitor the emergence and spread of anthelmintic resistance is crucial. In this study, a novel competitive digital droplet PCR (ddPCR) assay was designed for the detection of both the wildtype and the SNP 200 in the β-tubulin isotype 1 gene of T. trichiura. This species was chosen based on data that indicate that BZ efficacy against T. trichiura is unsatisfactory, hence likely the biggest chance of finding resistance. The newly developed ddPCR assays were first optimized using quantitative Polymerase Chain Reaction (qPCR). The results indicate that the final assay allows specific detection and quantification of mutant and wild-type targets.

Further optimization is necessary to make the assay even more efficient, as it may be valuable for the detection and monitoring of anthelminthic resistance in the future.

Address

Salisburylaan 133
9820 Merelbeke
Belgium

Contacts

Traineeship supervisor
Dr. Sebastiaan Theuns
+32 9 264 73 87
Sebastiaan.Theuns@UGent.be
Traineeship supervisor
Piet Cools
piet.cools@ugent.be
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