Recherche - Nouveaux entrants - 2025

Staphylococcus aureus, including both MRSA and non-MRSA strains, represent a serious threat to global health being responsible for a range of infectious diseases, such as mild skin and soft tissue infections, infective endocarditis, osteomyelitis, bacteremia, and fatal pneumonia. It is commonly associated with significant morbidity, hospital mortality, length of stay and economic burden. The resistance rates of S. aureus infection and multidrug resistant strains are increasing, making the clinical anti-infective treatment more difficult. The development of new antimicrobial drugs has remained virtually stagnant over the past decade. The resulting prolonged hospitalizations and high mortality among patients with MRSA infections have substantially increased the medical costs.

Rates of S. aureus infections are particularly high in patients with diabetes, highlighting the ability of this pathogen to survive in the presence of high glucose concentration. This condition is generally detrimental for bacteria as it leads to excessive production of reactive oxygen species (ROS) that cause DNA and protein damages, interfere with oxidative phosphorylation and compromise envelope integrity and function. Little is known about how S. aureus adapts to glucose levels. Recently, I showed that ribosome hibernation, a widespread phenomenon among bacteria, is critical for S. aureus adaptation to glucose metabolism. Ribosome hibernation-deficient cells exhibit low viability in glucose rich condition.

The primary goal of my projects is to understand the molecular mechanisms underlying these adaptation processes mediated by ribosome hibernation.  I believe that analyzing the molecular bases of S. aureus survival can help provide a basis for designing effective prevention and treatment measures against infections caused by S. aureus.

A plant phenotyping chamber is a chamber in which several environmental parameters need to be controlled simultaneously. Usually, this is achieved using PID loops that adjust actions (heating, cooling, ventilation, etc.) to maintain target setpoints (temperature, humidity, CO₂ concentration, etc.), which can be interrelated. Unfortunately, this approach does not allow for achieving multi-objective optimization, such as maintaining a certain set of parameters while minimizing others (like energy consumption). This project aims to support the development of intelligent algorithms for a plant phenotyping chamber. An approach based on deep reinforcement learning will be explored, as well as the acquisition of equipment enabling the development of open-source code.

This project explores the magnetosensing capabilities of magnetotactic bacteria (MTB), microorganisms that synthesize magnetosome chains, enabling passive alignment with magnetic field lines to aid their navigation toward microoxic environments. Recent findings reveal that MTB can exhibit active magnetosensing, where they modulate swimming speed in response to magnetic stimuli. The MTB strain SS-5 demonstrates changes in velocity corresponding to magnetic field intensity fold-changes, highlighting its potential for active magnetosensing. Leveraging these unique magnetic properties, MTB offer promising applications in biomedicine, particularly in targeted cancer therapy, where precise control over bacterial navigation is essential.

This project aims to identify and characterize additional magnetosensitive MTB strains and investigate how growth conditions and external stimuli influence their behavior. Key MTB strains (MSR-1, AMB-1, MC-1, RS-1) will be cultivated under oxygen-controlled conditions to determine whether growth in gradients enhances magnetosensing. The study will examine flagellar motor dynamics, rotational torque, and swimming patterns under varying chemical environments and magnetic fields. Microfluidic devices will be developed to generate localized gradients, enabling controlled experimentation. A custom-built magnetic microscope with Helmholtz coils, along with Python-based tracking tools, will allow precise observation and tracking at both single-cell and population levels in controlled magnetic environments. The insights gained will refine models of MTB navigation and inform future developments in precision biomedicine.

As a cost of civilization, the massive usage of nitrogen−containing fertilizers ultimately leading to detrimental environmental impacts. One reason behind is being the nitrification (biological oxidation of NH₃ to NO₂⁻ and NO₃⁻). These anions ultimately leached into water bodies, leading to downstream eutrophication. Another pathway is denitrification (reduction of NO₂⁻ and NO₃⁻ to N₂O and N₂). During the denitrification process, substantial amounts of greenhouse gas, N₂O escape into the atmosphere. In line with such an emergency, this proposal is set to tackle this grand challenge to convert oxidized form of nitrogen usually abbreviated as NOx to its ultimate reduced form i.e., NH₃. This project is constructed on a two−legged strategy; development of functional artificial proteins to replicate to its best the active sites of the natural enzymes involved in the NOx transformations. The second part deals with the development of cost efficient synthetic systems holding the appropriate chemical functionalities to reproduce the unmatched catalytic power of natural enzymes.