Dr. Shan Zhang is a microbiologist and bioinformatician. She obtained her Ph.D. in Microbiology and Immunology from the School of Biotechnology and Biomolecular Sciences at the University of New South Wales (UNSW), Sydney, Australia, in 2022. During her Ph.D. program, she visited the Medical Systems Biology Lab at Christian-Albrechts-University in Kiel, Germany, in 2019 as a visiting scholar. After completing her Ph.D. degree, she pursued postdoctoral fellowships at UNSW (from March 2022 to July 2023) and at HKUST (from August 2024 to March 2025). In March 2025, she joined the Department of Pharmacology and Pharmacy, LKS Faculty of Medicine at the University of Hong Kong (HKU), as a Research Assistant Professor.

During her Ph.D. program and postdoctoral research, her projects focused on the evolutionary adaptation of microbial symbionts to a symbiotic lifestyle, particularly through the integration of multi-omics approaches (e.g., metagenomics and metabolomics) to study sponges, the common ancestor of all animals, which allows to identify ancestral and conserved features in animal host-microbiome symbioses. Her expertise in cutting-edge bioinformatics techniques, such as genome-scale metabolic modeling, facilitates the exploration of metabolic interactions within host-microbiome symbioses. Additionally, she excels in integrating both culture-independent and culture-dependent approaches to investigate these topics and applies them to various host systems, ranging from animals (e.g., sponges and corals) to plants (e.g., seaweeds and wheat).

After joining the Department of Pharmacology and Pharmacy, Dr. Zhang’s research has focused on the symbiotic relationships between the host gut and its associated eukaryotic and prokaryotic microorganisms, aiming to better understand host health and microbial physiology. She is currently involved in two research projects:

• Discovery of novel drugs from natural bioactive products. This project integrates metabolomics and machine learning to identify both known and novel bioactive compounds from marine sponges—one of the richest sources of new marine natural products reported annually, offering a diverse array of biologically significant compounds.
• Dysregulated gut-microbiome co-metabolism in metabolic-associated fatty liver disease (MAFLD). This project employs metabolic modeling approaches to investigate the interactions between the host gut and the microbiome in the context of MAFLD. Ultimately, machine learning will be applied to provide insights in disease prediction based on the state-specific microbial signatures.

The research projects will be approached from the following perspectives:

• Identifying key players in the microbial community that underpins host fitness.
• Uncovering the essential roles of microbiome in nutrient cycling.
• Isolating yet-uncultured beneficial microorganisms associated with host health.
• Investigating colonization mechanisms of microorganisms compared to their bulk community counterparts.
• Developing tailored growth media to enhance the production of target bioactive compounds.
• Applying machine learning to predict microbiome fingerprint features associated with metabolic-associated diseases.

Dr. Zhang has published six first-author papers, with her research featured in journals such as Nature Communications, mSystems and Microbiome and Extremophiles. Additionally, she has co-authored four publications in Nature Microbiology, Microbiome, Environmental Microbiology and Bioinformatics.