PhD Projects » ESR 14: Computational methods for the analysis of metagenomic datasets to extract viral sequences within the context of commercial data-mining

Lovro Trgovec-Greif

My name is Lovro Trgovec-Greif and I come from Zagreb, the capital of Croatia. For my Bsc I studied molecular biology in Zagreb, but towards the end of my studies I figured out that I’m more attracted to the theoretical and computational side of biology. That led me to pursue my Msc at the University of Amsterdam where I studied systems biology and bioinformatics. During my master studies I gained a lot of practical experience in analyzing various human associated microbiomes. After obtaining my diploma I’ve spent a year working at a research institute back in Zagreb where my main topic of interest was human genetics.

I was always interested in viruses and microbes, but during my studies, when I was upgrading my vision of the (biological) world, viruses became even more interesting to me.  They are everywhere and are able to exploit any other living organism for their propagation while optimizing themselves along the way. It would be cool if we could exploit them in order to solve some of our problems, for example growing antibiotic resistance among pathogenic bacteria. My task is to contribute in that direction by using and developing bioinformatic methods.

In my free time I enjoy doing sports. My favorite are cycling, fencing and badminton. Apart from the healthy pastime, I also like to hang out with friend and party. I read something every now and then and I do a study in economics on the side.


Field:
Bioinformatics
Host institution:
University of Vienna (UV), Austria
Local supervisor:
Prof. Dr. Thomas Rattei (UV)
Local co-supervisor:
Prof. Dr. Matthias Horn (UV)
Project partner:
ESR 7
Work packages:
WP 1.1 Virus identification
WP 1.2 Host prediction
WP 1.5 Virus products

Thomas Rattei
Matthias Horn

Project description

Bacteriophages are increasingly being developed for the treatment of bacterial infections, and their role as modulators of the microbiome is of a growing area of extension of phage use. The sheer number and diversity of phage particles make it impossible to isolate and test each of them individually. This project aims to identify and harness phage sequences for commercial use by developing a method for large- scale identification of phage sequences, functional annotation, and in vitro validation of findings in a bottom-up approach.

We have four specific aims:

  • Identification of phage sequences within >50 metagenomic datasets (including upstream generation of >5 metagenomic datasets by partner UZH and meta-analysis of >45 publicly available datasets). Reconstruction of viral genomes sequences from metagenomic data (assembly, binning, phage classification); Reconstruction of cellular genome sequences (MAGs) from the same/related metagenomic datasets, in order to extract potential phage-host pairs from co-occurrence patterns; Prediction of prophage sequences in MAG in order to facilitate host prediction of phage sequences (in collaboration with ESR 12).
  • Extraction and testing of sequences to validate WP 1 findings ie., hypothesis testing by either isolating the phages themselves or having their genome synthesised (in collaboration with ESR 7).
  • Sub-analysis of geographical and temporal variation in metagenomic datasets that could justify product composition or modification analysis of geographic and temporal variation of phage sequences according to the local epidemiology. Relating these changes to geographic and temporal variation of related microbiome data (in collaboration with ESR 7).
  • Select for sequences with developmental potential (phage sequences with greater pH stability; host range expansion, etc.)
  • Computational modelling of phage stability and host range (in collaboration with ESR 7).