DC5: Marcus Yee

About Marcus and His Academic Background

Marcus Yee is a Canadian researcher specialising in microbiology, metagenomics, and bioinformatics.

He obtained his undergraduate degree from McGill University in Quebec, where he majored in Microbiology and Immunology. During his honours thesis, he studied a specific bacterial species using both laboratory experiments and computational analyses. This experience allowed him to discover a particular interest in the dry-lab component of microbiological research.

Marcus then completed a master’s degree at Simon Fraser University in British Columbia. His research focused on genetic exchanges between bacteria in environmental samples using metagenomic sequencing and computational pipelines.

Through this academic pathway, he developed expertise in microbial genomics, metagenomic data analysis, and the development of bioinformatics methods.

About His Research

Marcus’s PhD research is part of the SpoilControl project, an international doctoral network funded by the Horizon Europe Marie Skłodowska-Curie Actions.

As Doctoral Candidate 5, he is based at the Barcelona Supercomputing Center, where he investigates microorganisms with pathogenic potential in non-alcoholic fermented beverages, particularly products such as kombucha and kefir.

These beverages generally contain complex microbial communities composed of bacteria, yeasts, viruses, and other microorganisms. Although many of them are beneficial or harmless, some products may contain microorganisms that could represent a risk to consumers, especially when production conditions are poorly controlled.

Marcus’s research aims to determine whether potentially dangerous microorganisms are present in fermented beverages by analysing the DNA sequences found in samples. His work is entirely computational and relies on metagenomic data rather than the cultivation of microorganisms in a laboratory.

One of the main objectives of his PhD is to establish a genomic database containing reference sequences for bacteria and fungi with pathogenic potential in humans. This database will support the development of a computational pipeline capable of detecting and quantifying these microorganisms in next-generation sequencing data.

Marcus will analyse samples collected from fermented beverage industries as well as publicly available metagenomic datasets. This will allow him to investigate the prevalence of potential pathogens in industrial and natural environments and to better understand the origins of microbial contamination.

His work specifically focuses on:

• Creating a genomic reference database for bacteria and fungi with pathogenic potential.
• Developing a bioinformatics pipeline to detect and quantify pathogens in metagenomic datasets.
• Analysing non-alcoholic fermented beverages such as kombucha and kefir.
• Assessing the prevalence of rare pathogenic yeasts and bacteria.
• Comparing samples from industrial, environmental, and publicly available datasets.
• Investigating the origins and dispersal of microbial contamination.
• Studying how potentially pathogenic microorganisms adapt to different environments.
• Supporting the development of strategies to prevent or eliminate contamination in the fermentation industry.

In his daily work, Marcus uses command-line scripting, Python, and R for data analysis and visualisation. He also uses workflow-management tools such as Nextflow to build reproducible computational pipelines.

To evaluate existing detection methods, he creates simulated metagenomic datasets in which the exact microbial composition is known. He then tests taxonomic classification tools to determine whether they correctly identify the microorganisms present. Based on these results, he can adjust existing tools or develop new approaches that are better suited to the detection of pathogens present at very low levels.

As part of the project, Marcus will complete a secondment at the Molecular Genetics, Genomics and Microbiology laboratory at the University of Strasbourg. This stay will focus on developing bioinformatics approaches for detecting weak signals in complex datasets.

He will also complete a short secondment at ADERA-MICROFLORA in Bordeaux to transfer and test the analytical pipeline in a laboratory specialising in food microbiology.

Ultimately, the project aims to provide a reliable computational tool that can help producers determine whether a beverage sample may be contaminated. The results could support improvements in production practices, microbial monitoring, and consumer safety.