Christelle Yammine

Christelle Yammine
Email: christelleyammine96@gmail.com

Affiliation:

Education and experience:

In 2018, I earned my bachelor's degree in Medical Laboratory Sciences from the University of Balamand in Lebanon. During my academic journey, I completed an internship at Saint George Hospital University Medical Center in Beirut, where I gained valuable hands-on experience in conducting diagnostic tests across diverse areas such as serology, hematology, anatomic pathology, and blood banking. It was during the parasitology and bacteriology rotations that I discovered a deep fascination with microbiology.

Subsequently, I pursued a Master of Science in microbiology and immunology at the American University of Beirut. During this period, I had the opportunity to work under the supervision of Prof. Ghassan Matar and Dr. Antoine Abou Fayad on drug discovery, specifically focusing on identifying antibacterial compounds from natural products. My research involved isolating Actinomycetes from soil samples in Lebanon, cultivating them in 14 different stress-inducing production media, and extracting secondary metabolites for further testing. These secondary metabolites were screened against a panel of ESKAPE pathogens and extracts of interest were fractionated and re-tested. Simultaneously, I conducted phenotypic and molecular characterization of the producer strains to identify Biosynthetic Gene Clusters (BGCs) of significance.

After obtaining my Master of Science degree in 2020, I joined the group of Prof. Jörg Vogel at the Helmholtz Institute for RNA-based Infection Research (HIRI) in Würzburg, Germany to work on mechanism discovery and regulation of cancer-associated pathogen, Fusobacterium nucleatum. During my time there, I was exposed to new techniques in bacteriology including working with anaerobic bacteria, plasmid design and insertion, Northern blotting, cloning and Gibson transformation. It was a great experience that helped me develop my knowledge and skills in the field of microbiology and molecular biology.

Project Description:  Identification of bioactive molecules with antimicrobial activity

Patterns of emerging resistance to antimicrobials can be anticipated and there is a need to provide new antimicrobial agents that do not show cross-resistance with clinically approved drugs. One way to achieve this objective is to employ previously unexploited targets like the central bacterial metabolism which might be a new and innovative approach to uncover antibacterial compounds belonging to rarer classes and harboring fewer opportunity for emerging resistance. Therefore, the objective of this project is to create a screening platform for the detection of bioactive compounds that can target redundant enzyme pairs involved in bacterial metabolism of Salmonella enterica.

The screening platform consists of two elements: a large chemical diversity of microbial metabolites; and a way to identify compounds targeting redundant enzyme pairs. The reason behind targeting redundant enzyme pairs lies in synthetic lethal pairs, which are pairs of genes that when altered individually, have minimal effect, but when targeted together, will render the cell lethal. Thus, the main goal of the screening will be to identify bioactive compound(s) that can target the AsnA/AsnB enzyme pair which is responsible for the synthesis of asparagine. The primary screen should be able to pinpoint extracts with activity against Salmonella. Extracts with promising results will be subjected to further testing, to check whether growth inhibition by the bioactive extract is rescued by the addition of asparagine to the medium.

Using metabolomics and the metabolic fingerprints for the extracts of interest, identification and purification of compounds with dual target affinity will be done, in addition to structure elucidation. For what concerns the chemical diversity of microbial metabolites, part of my project will involve identifying novel metabolites from uncommon genera of Actinobacteria by using a combination of genomic and metabolomic data mining.