High-throughput comparison between 16S rRNA metagenomics analysis pipelines for the identification of archaea

SCK•CEN Mentor

Monsieurs Pieter, pmonsieu@sckcen.be, +32 (0)14 33 21 08

Expert group

Microbiology

SCK•CEN Co-mentor

Van Eesbeeck Valérie, vveesbee@sckcen.be, +32 (0)14 33 27 54

Introduction

The application of high-throughput sequencing technologies to assess microbial diversity is a fast-evolving discipline. The high through-put capacity of those technologies and the absence of the need to culture and isolate microbial species supplies researchers in the field with a very powerful technology. However, bioinformatics intervention is needed to interpret this massive amount of data, thereby requiring different bioinformatics pipelines for different type of samples and sequencing platform, thereby necessitating a wide range of algorithms for pre-processing, clustering the data, etc. Several pipelines have been optimized to analysis 16S rRNA amplicon sequencing data, yet, major focus until has been on the bacterial domain, while less effort has been spent in the analysis of archaeal species. Nevertheless, those are the type of microorganism which are surviving in extreme environments, such as the ones found in nuclear installations (e.g. primary cooling water of nuclear reactors, deep geological layers, etc.).

 

Objective

This work will focus on the bioinformatics processing of 16S rRNA amplicon sequencing data, thereby focussing on the correct interpretation and analysis of Archaeal microorganisms:

- Comparative study of various proposed approaches to pre-process the data (in aligning the reads using a secondary-structure guided approach, as well as the selection of the appropriate clustering algorithm).

- A novel 16S rRNA analysis pipeline will be proposed based on the comparative analysis outcomes, which will serve as a guideline/tool for data handling.

- Gaining experience in state of the art approach of handling high-throughput sequencing data (Illumina MiSeq, PacBio and NanoPore).

 

The minimum diploma level of the candidate needs to be

Academic bachelor

The candidate needs to have a background in

Bio-engineering , Biology , Informatics