Prof. Eva Hemmer (Chemistry and Biomolecular Sciences) and Prof. Nicolas Bordenave (School of Nutrition), are combining their expertise to unravel the mysterious interplay between gut microbiota and the brain. Evidence exists that the microbiota influences mental health and even neurological diseases. To confirm the verity of this gut-brain axis, the bacteria that make up the microbiota must be characterized. Prof. Hemmer’s team will achieve this using novel rare-earth based nanoparticles bonded to specific aptamers (RE-NP@apta), where the aptamers will form surface bonds with bacteria. Near infrared light emitted by the RE-NP@apta will then be detected and analysed using hyperspectral imaging (HSI). HSI allows for fingerprint characterisation and provides information about the chemistry or biological species present. Results from this project could help develop new therapies for mental illnesses. With further research, RE-NP@apta could be used to detect other medical conditions, such as cancer.
Prof. François-Xavier Campbell-Valois (Chemistry and Biomolecular Sciences) is developing an Antimicrobial Peptide (AMP) Secretion (AMPSEC) platform to identify alternatives to antibiotics. AMPs are peptides of a few amino acids, expressed in all kingdoms of life, which could be used to tackle antibiotic resistance. The project will identify new AMPs and use synthetic biology to express and characterize them. The resulting platform will allow the secretion of AMPs from various organisms in the bacteria Escherichia coli and may lead to the development of a new generation of probiotics. Prof. Weng In Siu (University of Saint Joseph) will use machine learning to uncover hidden properties governing the potency and specificity of AMPs against different bacteria. This will facilitate the development of novel AMPs that may contribute to reducing the use of conventional antibiotics, thereby fighting off microbial resistance. PhD student Kyle Tomaro has made this project a reality and will expand his expertise in bioinformatics and synthetic biology through this international collaboration.
Prof. Augusto Gerolin (Mathematics and Statistics) and collaborators Profs. Kribs (University of Guelph), Ayers (McMaster University) and Heidar-Zadeh (Queen’s University) have a common dream: to make computational chemistry and computational materials science truly predictive. Their research objectives hold potential for enormous consequences in terms of both economic and environmental sustainability. Their original approach directly faces the electronic-electronic component of many electronic systems, a significant problem in computational chemistry and a burden in quantum chemistry simulations. Prof. Gerolin and collaborators combine sophisticated tools and concepts from mathematics, chemistry, physics and engineering to develop new quantum chemistry and machine learning algorithms to face that challenge. Their methodology merges a key concept from physics (reduced density matrix) with mathematical tools from Optimal Transport Theory. Such a mathematically rigorous approach may not only improve the field of computational chemistry, but surprising new connections (and challenges!) will arise due to the highly interdisciplinary nature of this research.
Read more:
