91ÉçÇø

The motor proteins kinesin and dynein move along microtubules to transport cargoes and organize microtubules in the cell. Our goal is to understand how multiple motor proteins operate in teams, and how they are regulated to perform complex functions like cell division and directed transport. Through extending single-molecule techniques to native organelles and living cells, we have developed advanced microscopy tools to measure the regulation, motility, and forces exerted by motor proteins with unprecedented resolution, and to manipulate the system by applying external forces to the cargoes through optical tweezers and controlling motor activity using optogenetics. We will image and manipulate ensembles of kinesin and dynein as they transport native cargoes in reconstituted systems and living cells to understand how kinesin and dynein motors interact, how they are controlled to direct intracellular trafficking, and how motor proteins are misregulated in neurodegenerative disease.

Student 1: Quantify the number and type of motor proteins associated with organelles using superresolution fluorescence microscopy (SIM and STORM). Student 2: Use the optogenetic inhibitors we developed to test the role of kinesin-1, -2, and -3 in the motility of endoplasmic reticulum-associated organelles.

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Optical tweezers (or optical traps) use a tightly-focused laser beam to exert forces on micron-sized refractive objects. By attaching motor proteins to small latex beads, we can measure the forces exerted by single molecules. Our lab has also developed techniques to measure the forces exerted by motor proteins and characterize the viscoelastic environment in living cells. Here, we will modify our current optical trapping systems to develop a force-feedback optical trap that allows us to exert constant forces on motor proteins as they move along cytoskeletal filaments. The force is measured by collecting the light that passes through the bead onto a quadrant photodiode, and the position of the trap is controlled through an acousto-optic deflector. We'll then use this system to test how exerting constant forces along the microtubule alters the movement of cargoes transported by the motor proteins kinesin and dynein.

Student 1: (1) Develop optical tweezers capable of manipulating single molecules and measuring their nanometer-sized displacements and pN-level forces. (2) Program a simple feedback controller to maintain constant forces.

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Taxol is one of the best anticancer drugs ever developed, used against ovarian, breast, lung and other cancers. Its effectiveness combined with anticipated further therapeutic applications has generated huge demand of the drug, which outpace current supply. Yet, a reasonable taxol production method is lacking, raising the cost of treatment for one patient to $9000 for 6 cycles of chemotherapy. Taxol extraction or chemical synthesis are non-sustainable, hence not suitable for industrial scale, while current production methods are yet inefficient. A sustainable and inexpensive solution is production of taxol in simple organisms, such as baker’s yeast. For this purpose, the early route of taxol formation that naturally occurs in plants will be transplanted in yeast to produce enough amounts of intermediate compounds, which could be further modified to taxol or other promising analogs in cell free system or by chemical conversion.

Biochemistry and Molecular biology knowledge (requested), Know-how laboratory techniques (requested), Metabolic pathways regulation - to be developed, DNA Sequence-based design strategies - to be developed, Microbiology techniques - to be developed.

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Carotenoids are major constituents in plants, bacteria or fungi that play roles in pigmentation, protection or photosynthesis. They are precursors of Vitamin A, strong antioxidants or protective agents against various conditions, such as inflammation, aging, cataract, cancer, obesity, cardiovascular and neurodegenerative diseases. Owing to these biological activities, carotenoids are essential ingredients for human and animal health that must be ingested by food. This need has generated a growing commercial interest for carotenoid-based products as food supplements, nutraceuticals, colorants, cosmetics or aquaculture and animal feed. To fulfill the market demands, synthetic carotenoids are used in 80-90% of applications. These are chemically produced from raw petrochemicals and have shown reduced bioactivities and health issues. Consequently, synthetic carotenoids are not approved for human consumption and mainly used for coloration purposes in the aquaculture and animal feed sector. Natural carotenoids are obtained by extraction from plants and algae or biologically produced in microbes by fermentation, and the associated procedures are more expensive than organic synthesis. Here, we will develop a cost-effective strategy for production of natural carotenoids using baker’s yeast, aiming to replace synthetic carotenoids in major applications. We will reconstruct the biosynthetic pathways of commercially vital carotenoids, β-carotene or lutein, and develop dedicated yeast platforms for future production of other carotenoids (fucoxanthin), currently not yet amenable for engineering in non-producing organisms. We will integrate cutting edge approaches in metabolic engineering and computational biology to improve the activity of carotenogenic enzymes and redirect metabolite fluxes in yeast toward carotenoid production.

Biochemistry and Molecular biology knowledge (requested), Know-how laboratory techniques (requested), Metabolic pathways regulation - to be developed, Bioinformatics - to be developed, Microbiology techniques - to be developed.

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Paclitaxel (trademark Taxol) derived from the stem bark of the Pacific yew tree, Taxus brevifolia, is a widely used chemotherapeutic agent possessing significant anticancer activity. Recently, the development of synthetic biology has allowed for the biomanufacturing of several plant-based terpenoids in the Saccharomyces cerevisiae, with the most recent breakthrough achieved by production of the anticancer drug vinblastine. In this project, a multi-disciplinary approach spanning computational structural biology, enzymology and synthetic biology, will be applied to optimize the catalytic activity, product specificity and substrate selectivity of enzymes involved in early steps of taxol biosynthesis for efficient reconstruction of these steps in yeast. The following objective will be pursued: 1. Machine learning-assisted directed evolution of taxadiene synthase (TS) and taxadiene 5α- hydroxylase (T5αH). 2. Homology modelling or molecular docking for rational and semi-rational mutagenesis to identify stabilized candidate variants. 3. Engineering TS and T5αH variants and evaluated their activity in a yeast available platform.

Biochemistry and Molecular biology knowledge (requested), Know-how laboratory techniques (requested), Enzyme function, kinetics and regulation - to be developed, Protein Sequence-based design strategies - to be developed, Enzyme engineering - to be developed.

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This project aims to engineer efficient modules for CRISPR-based genome editing for multiplex engineering of target metabolic pathways in a set of industrially-relevant yeast hosts. These include Saccharomyces cerevisiae, Yarrowia lypolitica, Pichia pastoris and Rhodosporidium toruloides. CRISPR modules of interest are CRISPR-associated endonuclease, intracellular availability of donor DNA, ssgRNA design, repair mechanism.

CRISPR-based genome editing, ssgRNA design, yeast transformation

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Manipulation of microbial systems for repurposing their metabolism to new functionalities it generally follow the engineering cycle of design-buid-test-learn and it goes through iterative cycles of trial and error. Consequently, this process is generally time consuming and require many years to move a synthetic biology application from the proof-of-concept stage to industrial scale. For example, production of the antimalarial drug artemisinin in yeast heterologous host required ~150 person/year of efforts. In this project, we aim to develop standardized biological parts as engineering tools of bacteria and yeast hosts for enabled rapid switch between genetic elements to control gene expression level for for modulation of biosynthetic pathways.

molecular biology approaches, Gibson cloning, bacteria and yeast transformations

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Recent advances in Synthetic Biology enables the engineering of microbial systems into efficient platforms for production of target compounds with a wide broad range of applications. Here we will engineer cholesterol non-producing unicellular organisms to mimic the metabolism of higher eukaryotes for the development of a "humanized" chassis for investigation of cholesterol-related diseases.

molecular biology approaches, Gibson cloning, bacteria and yeast transformations

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Immune cell infiltration into diseased tissues requires coordinated biomechanical and biochemical reactions and responses. In solid tumors this requires that cells breach the dense fibrous barrier of the basement membrane before reaching the target cells. This project aims to model the mechanisms of infiltration and migration using a bioprinted tumor model and mathematical tools.

Perform and maintain sterile cell cultures in 2D and 3D Perform cell and molecular biology experiments and data analysis Develop materials and measure their mechanical and chemical properties Evaluate mathematical models of cell migration, infiltration, and biomechanics Perform bioprinting and tissue engineering experiments Read current research in the topic and present in journal club

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Functional magnetic resonance imaging (fMRI) is currently viewed as the gold standard for imaging the human brain owing to its excellent spatial resolution (millimeter level). However, the fMRI signal is indirectly related to the underlying neural activity (through neurovascular coupling mechanisms) and it is influenced by motion and systemic physiological fluctuations (heart rate, respiration, arterial blood pressure and gases). One of the most promising approaches to understand these relations is to use neuroimaging modalities that complement each other. In this context, our group collects and analyzes multimodal neuroimaging data (fMRI, simultaneous EEG-fMRI, fNIRS) combined with physiological data during resting-state conditions as well as physiological and sensory tasks (CO2 inhalation, breath holds, eyes open/closed, visual stimuli, cold pressor tests). In the present project, we will use these data to investigate the regional patterns of physiological response functions (PRFs), which quantify the dynamic effects of physiological fluctuations on the fMRI signal, as well as the hemodynamic response function (HRF), which quantifies neurovascular coupling mechanisms. More specifically, we will examine the relation of these patterns to the underlying brain anatomy (venous and arterial density) as captured by structural MRI performed in the same subjects. The proposed work yields promise for identifying more robust biomarkers for earlier/more accurate diagnosis of brain disorders as well as targets for therapeutic interventions (e.g. noninvasive brain stimulation).

The students will preprocess and analyze the experimental data, using signal processing and systems identification methods. They will also help in the collection of experimental data at 91ÉçÇø’s General Hospital. The aim will be to better understand how physiological and neural signals are coupled with the fMRI signal and the link between these couplings and the underlying brain anatomy.

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This is a creative open-ended modeling project that aims at parametric design of 3D tessellated structures. Two-dimensional tessellated arrays have evolved independently in multiple clades of animals and plants. They exist as a microstructural feature of the skeleton and the integument (skeletons of sharks and rays, carapace in turtles, seedcoats in plants). The numerous regular interfaces inbetween the repetitive tiles ensure flexibility and extraordinary toughness, fatigue-resistant behavior, and even autexicity of entire structures. It has recently been discovered that mineral in mammalian bones (including human bone) forms micrometer-scale tessellations of prolate ellipsoids (geometric approximation) that stagger in close-packing and collectively form vast 3D space-filling arrays throughout the organic matrix of bone tissue. This project seeks to determine and quantify the mechanical advantages of such 3D tessellations on skeletal biomechanics through modeling and mechanical testing of 3D-printed structures

Design a generic 3D ellipsoid packing array using Rhinoceros/Grasshopper software. Identify variable parameters: oblateness/prolateness, stagger, ellipsoid-to-matrix ratio. Test the 3D models using simulated loading and FEA. Mechanically test 3D-printed models.

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Mucosal barriers are key components of the innate immune system that influence disease transmission by interacting with and sequestering pathogens, and by influencing pathogen survival at the point of transmission. To date, our understanding of the biophysical mechanisms governing interactions between pathogens and mucin glycoproteins, the primary structural components of mucus that largely determine its mechanical and biochemical properties, remains incomplete. This hinders our ability to understand and model pathogen dynamics in-host, particularly during the initial stages of infection with respiratory viruses, where causative pathogenic agents must traverse mucosal barriers and overcome host innate immune responses. Here, we will address this important gap by studying interactions between mucins and a library of fluorescent virus-like particles (VLPs) engineered to display the surface proteins of relevant respiratory viruses in the context of the early stages of host-infection. We will characterize the motion of these VLPs in both native mucus and in gels reconstituted from purified native mucins. The goal is to assess the role of mucin molecules in the binding/sequestering of pathogens and their impact on infection of host cells.

Support a Master’s student in the generation of experimental data (particle tracks for the VLPs in the various gels). Apply and adapt existing particle tracking code to study the transport of the VLPs through the gels.

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The uncontrolled spread of infectious pathogens can cause substantial public health and socioeconomic harm, as recently illustrated by the COVID-19 pandemic. There are a variety of public health interventions (e.g., lockdowns, symptom-based quarantining, contact tracing, and PCR testing) that can help mitigate infectious disease outbreaks but each has its own public health, economic, and societal tradeoffs. Wearable sensors that monitor physiological signals have potential to continuously and passively detect respiratory infections before or absent symptoms. These emerging tools could enable novel outbreak containment strategies that complement or improve upon the existing set of available interventions (e.g., by reducing the number of infections but with fewer unnecessary quarantines). In this project, we will use agent-based models to simulate infectious disease outbreaks and study the potential utility of wearable sensors as a pathogen-agnostic infection detection tool. We will compare wearable sensor-based containment strategies to conventional containment strategies, measuring performance across an array of outcome measures (e.g., number of infections, economic costs, number of quarantines). The goal is to identify epidemiological, technological, and policy assumptions that would need to be true for wearable sensor-based infection detection to be a useful containment strategy.

• Use our team’s agent-based model (Python) to simulate infectious disease outbreaks and different containment strategies • Work with collaborators to define outcome measures (e.g., cost of diagnostic tests in a simulated outbreak) and implement the calculation of these measures (Python) • Run simulations to conduct experiments and synthesise findings into bi-weekly summaries that will be circulated across the team

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The cell is the fundamental unit of life, yet the inner workings of the cell are far more complex than we ever imagined. Without a good model of the cell, it is difficult to develop new drugs to repair diseased cells, or build new cells to produce much-needed chemicals and materials. A key step towards building a working model of the cell is to map the complex network of interactions between thousands of tiny molecular machines in the cell called proteins. This project will focus on computer modeling of protein structures and networks. Various experimental and computational datasets on protein structures and networks will be integrated and visualized. The resulting integrated protein structures and networks will then be annotated with evolutionary and disease properties, with the aim to understand how protein structures and networks evolve, and how disruptions in protein structures and networks lead to disease.

Literature review. Becoming familiar with publicly-available datasets on protein structures and networks. Becoming familiar with existing computational tools on modeling protein structures and networks. Computer programming.

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