McGill-UAE USRI Projects

Below are the projects available for the McGill-UAE Undergraduate Summer Research Internship. Please select up to three projects and fill out the form here. We encourage you to look into related areas to search for projects, as many projects are multi-disciplinary.

For information about eligibility and more information, visit our main McGill - UAE Summer Undergraduate Research Awards website.

*Note that some projects are shown in several categories.

Human Disease

Project code: PR01

Supervisor: Guillaume Durandau

Project: Insulin signaling is an important regulator of metabolism and physiology. While the core components of this pathway are known, there are many regulators that are still being identified that provide new means of intervention. Genetic studies in the nematode C. elegans have made important contributions to our understanding of the insulin signaling pathway where it is important for regulating lifespan, fat storage and various stress responses. We have found that a mutant in which results in recruitment of insulin signaling components to endosomes and results in increased signaling activity. An UAE undergraduate will work alongside a graduate students to understand the mechanisms by which this mutant results in increased insulin signaling using genetics and cell biological approaches. The student will learn some basic molecular biology and microscopy as well as image analysis skills.

Project code: PR02

Supervisor: Jeremy Cooperstock

Project: The Ai-Digital Nurse Avatar (ADiNA) is an avatar technology intended for interaction with older adults in nursing homes, home care, or retirement communities. The primary objective is to leverage AI-based tools that will provide assistance to nurses and other care staff, helping reduce workload by serving as a possible initial point of communication with clients, and triaging communications during periods of overload. The avatars, potentially presenting different on-screen human appearances and voices, as best-suited to the preferences of each client, collect information through natural conversation and video-based interaction. The relevant information can then be conveyed to nursing staff in an appropriate format, without necessitating travel to every client for every interaction. A possible use-case scenario is that of answering a client in distress. This would be much like a nurse responding to a hospital "call button", but with the potential of having the AI address non-critical issues, and otherwise, forwarding the calls to nursing staff by level of urgency. Another such scenario is to have the AI avatar carry out a subset of tasks required during regular staff rounds, serving as the nurse's assistant by checking vitals and verifying the client's general psychosocial state, to the degree that this is feasible through basic visual observation and dialog. We aim, through the next year, to refine several aspects of the prototype, which heavily leverages GPT and employs multi-lingual speech recognition and synthesis frameworks. Some of these, which are opportunities for the selected undergraduate research trainees, as per their interests and skills, relate to audio signal processing to demonstrate greater flexibility for interruptions and multi-speaker scenarios, improved LLM-prompt generation and testing of locally run LLMs, and improving the emotional expressions of the avatar in response to sentiment and facial expression detection.

Project code: PR03

Supervisor: Piotr Pater

Project: Our Department of Radiation Oncology at the McGill University Health Centre has embraced a digital approach to patient documentation. Our ARIA oncology software allows us to manage patient documents in Word and PDF formats. Despite being a paperless clinic, this static documentation style mirrors the limitations of a paper-based system. We lack the tools to enforce standards and mandatory fields to prevent errors. Word and PDF formats don’t lend themselves well to data extraction for clinical decision-making and research. So we are faced with unchecked inefficiencies in documentation and rigid patient records. Even minor typos can cascade into critical treatment setbacks, miscommunications, and delays in treatment, challenging our goal of delivering optimal patient care. The dynamic landscape of cancer care requires robust, reliable, and minable documentation systems. Our proposed solution, called Oncoflow, is a web-based platform usable by all RO medical personnel and aimed at addressing these challenges. This innovative system will not only convert our existing documents into more dynamic digital formats but also introduce additional features including visualization of lab results, integrated nomenclature checks, templates by disease site as well as be a communication tool between professionals and existing oncology platforms. We have a twofold vision for the sustainability and advancement of Oncoflow. Aims and Goals for Undergraduate Students 1. Development and Compliance Monitoring Module - The first student will be integral in developing a module or dashboard within Oncoflow, focusing on monitoring compliance and patient care standards. This module will leverage the database-driven nature of Oncoflow to quantify the reduction in documentation errors, measure efficiency gains in document processing, and evaluate compliance metrics. This task provides a significant and independent contribution to the project, allowing the student to gain hands-on experience in database management and healthcare software development. 2. Survey Development and Analysis - The second student's role involves crafting and analyzing surveys for upcoming document types in the transition pipeline. This project allows the student to delve into user experience research, understanding the needs and preferences of healthcare professionals. This role also includes formulating post-implementation surveys for existing document types in Oncoflow, focusing on user satisfaction and feedback. The insights gathered will be pivotal in refining Oncoflow, ensuring it meets the end-users' requirements effectively.

Project code: PR04

Supervisor: Brian Chen

Project: Molecules Involved in Wiring Up a Neural Circuit What molecules give a brain cell its unique identity to make it wire up a specific way? Very little is known about how instructions encoded somehow within the genome can allow a brain to self-assemble and wire up to function correctly. Our goal is to uncover the exact molecular code that can be used to wire up a neural circuit. We address this by using the fruit fly genetic model organism because of its long history of use in biology and neurobiology research, and because of its hard-wired, or innate behaviors. Using a specific hard-wired neural circuit, we identify the exact same neuron between different animals, image the neuron’s unique wiring pattern, and activate the neuron using the animal’s behaviour, all within a single animal. We will isolate these single neurons, and use DNA sequencing to identify its molecular pattern inside of the cell. To understand what each of these molecules does in a neuron, we will characterize each one of them by deleting it and examining how the neuron’s wiring pattern is disrupted and how the animal’s behavior is impaired. By systematically testing each molecule, we will create an important database on what each molecule does for the neuron. Our project will be a crucial first step molecularly for our understanding of how miswiring occurs in brain disorders such as autism spectrum and schizophrenia.

Project code: PR05

Supervisor: Thomas Durcan

Project: Parkinson’s disease (PD) is a neurodegenerative disease whose prevalence is estimated at 1-2 per 1000 at any time. Genetic causes of PD have been identified in 10 to 15% of PD cases. It is is notably characterized by a progressive of loss of dopaminergic neurons in the substantia nigra leading to neurological symptoms such as tremors, rigidity, and dementia. In our group, we use induced pluripotent stem cells (IPSCs) to generate in vitro neuronal cultures from patients diagnosed with PD. IPSCs are stem cells obtained from control or patients’ somatic samples (white blood cells, fibroblasts or epithelial cells) that once reprogrammed can provide all cell types from the human body. One of the genes whose mutation causes PD is GBA (Glucosylceramidase Beta 1) which codes for an enzyme that contributes to lysosomal function in the cells. Past studies have shown on non-neuronal cells that GBA enzymatic activity is regulated by the microRNA Hsa-miR-22-3p. During the past month, we were able to show that GBA expression and activity from a control line can be modulated by the microRNA 22 3P in IPSC-derived dopaminergic neurons. We are now planning to investigate the regulation of GBA activity in IPSC-derived GBA mutant lines through modulation of the microRNA 22 3P or other non-coding RNA. The trainee will be involved in extracting RNA (which includes microRNAs; noncoding and messenger RNAs) and proteins from the mutant lines. Their role will involve using real-time PCR or western blot techniques, to determine if the modulation of microRNA or non-coding RNA in IPSC-derived dopaminergic neurons contributes to restoring GBA expression and/or activity in GBA mutant lines.

Project code: PR06

Supervisor: Pedro Rosa

Project: Biomarkers of neuroinflammation will be part of the 2024 research operational definition of Alzheimer's disease. However, there is a debate on how biomarkers of neuroinflammation will characterize disease staging. Hypothesis: We hypothesize that reactive astrocytes will characterize the early disease stage, whereas microglia activation dominates in more advanced disease stages. Methods: In conjunction with a team composed of a post-doctoral fellow, a PhD student, and an MSc student, the UAE trainee will conduct experiments to assess the association between Positron Emission Tomography (PET) and cerebrospinal fluid biomarkers AD core biomarkers and neuroinflammation biomarkers. Learning objectives: The UAE trainee will learn the clinical aspects of Alzheimer's disease. Regarding biomarkers, the undergraduate will be familiarized with amyloid, tau, microglia, and astrocyte PET imaging. The UAE trainee will receive instructions on conducting statistical analysis with biomarkers. We expect to finalize the data collection of this project by February 2024. The UAE trainee will access the research database from the Translational Biomarker for Aging and dementia cohort (TRIAD) cohort.

Project code: PR07

Supervisor: Ahmad Haidar

Project: We run clinical trials to assess novel diabetes drug and devices in people with type 1 diabetes. We are currently focusing on assessing empagliflozin, semaglutide, and artificial pancreas systems. The student will help running these studies (recruitment, documentation, patients follow-up, data analysis, etc).

Project code: PR08

Supervisor: Christian Rocheleau

Project code: PR09

Supervisor: Anna Naoumova

Project: Males and females differ in many aspects of their biology from different sex chromosome (chr.) complements (XX in females and XY in males) to different behavioral patterns. Moreover, sex differences in gene expression levels are present across different tissues and developmental stages. Males and females also differ in their epigenetic profiles. DNA methylation levels at X chr. and autosomal loci vary between the sexes, however the mechanisms responsible for sexual dimorphism in autosomal DNA methylation are poorly understood. In this project, we will investigate the roles of the sex chr. in shaping the mammalian epigenome using mouse models with different combination of sex chr. complement and phenotypic sex as well as mutations in X-linked genes encoding epigenetic modifiers. We will also use human fibroblasts from individuals with X-linked mutations. The Summer student will work on testing DNA methylation levels in mouse or human cells using pyrosequencing methylation assays.

The successful applicant will have good knowledge of basic chemistry, be familiar with calculating concentrations, have a good grasp of basic mathematics. Previous experience with PCR or work with other multicomponent systems is an asset.

Project code: PR10

Supervisor: Sabrina Wurzba

Project: Problem status: Head and neck cancer (HNC) represents a significant global health concern, with its incidence exponentially increasing in the last three decades. Recent research has investigated the intricate relationship between HNC development and several risk factors, including tobacco, alcohol and human papilloma virus (HPV) infection. However, e-cigarettes and marijuana consumption have become a concern because of their popularity in the young population. This project aims explore the epigenetic mechanisms underlying these new risk factors in order to understand the molecular intricacies that drive HNC progression. Objectives: 1. Examine the epigenetic consequences of e-cigarette exposure on cancer cells in the head and neck region. By elucidating these molecular changes, the project aims to contribute valuable insights into the association between e-cigarette usage and HNC development. 2. Explore the epigenetic alterations induced by marijuana use in the context of HNC. This research will provide a comprehensive understanding of how marijuana, a substance with increasing societal acceptance, may contribute to the epigenetic landscape associated with HNC. Methodology: Utilizing cutting-edge epigenetic profiling techniques, the study will analyze a large panel of HNC cell lines to identify specific DNA methylation patterns and microRNA alterations associated with marijuana and e-cigarette exposure in HNC. Expected Outcomes: The project anticipates uncovering novel epigenetic biomarkers that can serve as indicators for HNC susceptibility and progression. By elucidating the molecular alterations caused by these risk factors, the project will contribute to the development of effective prevention strategies and personalized therapeutic approaches for individuals at risk of or patients affected by HNC.

Note: this is a 9-week project.

Project code: PR11

Supervisor: Qihuang Zhang

Project: Integrating Genomics and Cell Localization in Kidney Research Using Supervised Machine Learning Project Overview: Understanding the cell structure of the kidney and its relation with genomics data is pivotal for the development of personalized medical treatments. Current technological limitations impose a significant challenge in investigating the relationship between genomic sequencing data and specific cell locations within the kidney. This project aims to bridge this gap by developing a supervised machine-learning model that accurately maps cell locations based on genomic information, extending the prior successful projects in my lab conducted on other types of tissues. Research Objectives: 1) To create a deep learning neural network that characterizes the relationship between genomics data and cell spatial locations, and addresses the challenge of synthesizing multi-dimensional data, encompassing genomic information, cellular data, and demographic variables such as age and biological sex. 2) To develop a robust predictive model and then implement the model in kidney datasets. Methodology: • Utilizing cutting-edge machine learning techniques and tools, primarily Python and libraries like Pytorch. • Analyzing and processing complex datasets to construct an effective deep-learning model. • Iterative testing and refinement of the model to enhance predictive accuracy. Expected Outcomes: • A novel model providing insights into the spatial-genomic relationship in kidney cells. • Potential contributions to international conferences and publications in journals like Bioinformatics and Frontiers of Epigenetics. Opportunities for UAE Students: • Engaging in hands-on application of advanced machine learning techniques. • Gaining invaluable experience in interdisciplinary research, spanning biology, genomics, and data science. • Developing skills in data analysis, coding, and problem-solving. Supervisor Profile: Qihuang Zhang is an assistant professor of Epidemiology, Biostatistics, and Occupational Health (EBOH) at McGill University. His research interests focus on developing statistical and machine learning methodologies to address challenges in genetics and genomics data. His recent research has been centered around developing methods to process medical images, spatial omics, and single-cell RNA-seq data, which can gain new insights into Alzheimer’s disease and cancer. Matching Eligibility: This research project is ideally suited for students with backgrounds in statistics, biostatistics, and computer science who are interested in conducting projects with biomedical applications.

Project code: PR12

Supervisor: Jennifer Ronholm

Project: Antibiotic resistance is a growing concern globally. In recent years there has been an increase in the number of human antibiotic resistant infections observed in Canada and globally. The increase in antibiotic resistance in bacteria is primarily driven by the use of antibiotics in both human medicine and in food production. Antibiotics are commonly used to control infections in both agriculture and aquaculture. Food may be a common vehicle to transport antibiotic resistant bacteria and resistance genes to humans; however, the prevalence of antibiotic resistant bacteria and antibiotic resistance genes in domestic and imported food is unclear. In this investigation we will conduct a large scale surveillance project to determine the abundance and identity of antibiotic resistant bacteria and antibiotic resistance genes in domestic Atlantic salmon, imported Atlantic salmon, imported shrimp, fresh pork, fresh beef, and fresh chicken across Canada. A total of 360 food samples will be purchased by the Living Oceans Society and World Animal Protection from grocery stores in Vancouver, Toronto, and Halifax in early 2024 and shipped to McGill for analysis. The presence of important food borne pathogens Campylobacter spp., Escherichia coli, Salmonella enterica, and Enterococcus spp. will be quantified in each sample. Bacterial pathogens from each sample will be whole genome sequenced and assessed for both antibiotic resistance genes and phenotypic antibiotic resistance against a panel of 15 antibiotics. Each of the 360 food samples will also be analyzed by hybrid capture and high quality DNA sequencing, which allows for targeted enrichment, sequencing, and detection of over 2780 unique antibiotic resistant genes. This project is the most comprehensive short-term assessment of the abundance of antibiotic resistant bacteria and antibiotic resistance genes present in Canadian foods conducted to date. The results will be used to better understand the current situation in Canada and inform public policy about the possible roles of food in transmitting antibiotic resistance. An undergraduate student will be recruited to help in culturing bacterial pathogens from food items, and next generation sequencing antibiotic resistance genes. This project will provide extensive cutting edge training in microbiology and molecular biology for undergraduate participants.

Project code: PR13

Supervisor: Sampath Kumar Loganathan

Project: Head and neck cancer is one of the deadliest cancers in the world with poor overall survival of 50% after 5 years. Hence, understanding the molecular mechanisms of disease progression is necessarily to develop novel therapeutic strategies. Recent reports show that NOTCH pathway disruption is a major factor in this cancer. The project aims to uncover the link between AJUBA and NOTCH through protein interaction studies in cell culture models.

Project code: PR14

Supervisor: Ryan Mailloux

Project: Dihydroorotate dehydrogenase (DHODH) is a mitochondrial enzyme that couples pyrimidine biosynthesis to the electron transport chain (ETC). The enzyme is overexpressed in many cancer types, but is highest in hepatocellular carcinoma and pancreatic cancers. Notably, our group has discovered it also produces large quantities of hydrogen peroxide (H2O2), a signaling molecule that is vital for tumorigenesis. Our group is currently delineating the signaling function of DHODH in cancer. We are seeking a candidate with basic lab experience that can work with a postdoctoral fellow that is jointly supervised to develop cell lines to investigate these functions. The student will develop skills in cell culture, gene editing, redox biology, and mitochondrial bioenergetics.

Must have basic wet lab skills, basic biochemistry and metabolism.

Project code: PR15

Supervisor: Igor Cestari

Project: Infectious parasitic diseases affect millions of people worldwide. Trypanosomes are single-celled protozoan parasites that cause disease in humans and animals. Challenges to controlling the diseases caused by these parasites include a lack of effective drugs, drugs that are too toxic and are not effective, and no vaccines available. We work to understand the molecular mechanisms by which trypanosomes evade the host immune response by antigenic variation, i.e., periodically changing the surface coat to escape host antibody recognition and clearance. We also work on the development of drugs and vaccines. The projects available will be investingating: 1) how trypanosomes evade the host immune response by antigenic variation to cause disease and 2) the development of vaccines against trypanosomes.

Project code: PR16

Supervisor: Thavy Long

Project: Schistosomiasis, caused by the trematode Schistosoma, is a major neglected tropical disease in humans, second only to malaria in terms of morbidity and mortality. Generally endemic to tropical and subtropical areas, this disease threatens to spread to new regions due to climate change and population migration. No recombinant vaccine is available. Praziquantel is the only drug available to treat schistosomiasis. However, its efficacy is incomplete and its prolonged and intensive use in monotherapy justifies the fear of resistance development. Therefore, there is an urgent need to find alternative treatment strategies to combat schistosomiasis. Nuclear receptors (NRs) are ligand-activated transcription factors that regulate gene expression in a variety of biological processes such as sterol homeostasis, development, and reproduction. Because of their central role in those functions, NRs are well-known therapeutic targets in humans and recently in worm parasites. Although NRs have been isolated in the genome of the flatworm parasite S. mansoni, little is known about their function. Elucidating the role of SmaNRs would provide insights on novel signaling pathways that govern the development and reproduction in schistosomes. Our lab research focuses on characterizing the function of the 21 NRs in S. mansoni and on validating their potential as new targets. This proposal aims to elucidate the mechanism of activation of SmaCAR (S. mansoni Constitutive Androstane Receptor), a NR that may play a role in the reproductive biology of schistosomes. We will screen and identify putative ligands via a mammalian luciferase assay. This project will advance our knowledge on the physiology of schistosomes but it will also open up exciting possibilities for uncovering novel strategies to combat schistosomiasis by identifying modulators of these NRs.

Project code: PR17

Supervisor: Noemi Dahan Oliel

Project: Until now, there has been no functional classification system for the assessment of gross motor function in Arthrogryposis Multiplex Congenita (AMC). The Gross Motor Function Classification System (GMFCS) was created for use in children with cerebral palsy (CP) to stratify children on the basis of functional abilities and limitations despite the heterogeneity in CP. Since its publication in 1997, the GMFCS has become the international standard to classify children’s motor function in clinical practice and research. Since the GMFCS was constructed according to expert consensus to represent clinically meaningful distinctions in daily mobility-based functioning in CP specifically, its application to children with other congenital and/or orthopedic conditions has not been validated. This new tool will be used to monitor gross motor function after treatments and provide a reliable and valid standardized assessment of gross motor function in a group of rare conditions, which can be used for the description of the natural course of the disease and for the evaluation of treatments. The aim of this project will be to create knowledge translation tools to guide the understanding of a newly developed gross motor classification system for AMC. Methods to be used include synthesis of the literature, expert opinion with clinicians and people with lived experience, creation of knowledge translation tools, such as infographic and/or short video. The developed tools will be shared with key stakeholders using social media and support group websites.

Experimental Psychology

Project code: PR28

Supervisor: Jorge Armony

Project: The student will be in charge of developing and piloting a new design for an experiment studying emotional body sensations and interoceptive processes. Previous work from our group and others has investigated individual differences in emotional body sensations (feelings in the body associated with emotional experience) in relation to psychiatric diagnoses and subclinical personality traits, using the “bodily maps of emotion” task. This task, in which participants “paint” areas of their body where they feel different emotions, relies on interoceptive and somatosensory processes. Previous research has made a crucial distinction between interoceptive attention and interoceptive accuracy: the former refers to the salience of interoceptive signals in consciousness, while the latter refers to the accurate perception of interoceptive signals. While conceptually similar, research has shown that these processes are uncorrelated or even anticorrelated, and have different psychological correlates. Thus, the present project will center around distinguishing interoceptive attention and interoceptive accuracy in the perception of emotional body sensations. The research project will use an emotion-induction paradigm in combination with physiological recordings, self-reported emotion, and the bodily maps of emotion task to investigate the correspondence of actual physiological changes, self-reported emotion, and self-reported somatic sensation, in order to investigate how differences in interoceptive processes manifest in emotional body sensations, and how these relate to personality and emotional experience. The student will be responsible for testing materials for this study (emotion induction procedures, physiological equipment, questionnaires and aspects of the experimental design), piloting it on a small sample to ensure its effectiveness, and analyzing the data. Time permitting, the student will expand the project to larger samples and train future trainees in the operation of the paradigm.

Physical Therapy

Project code: PR17

Supervisor: Noemi Dahan Oliel

Clinical Studies

Project code: PR07

Supervisor: Ahmad Haidar

Cancer

Project code: PR10

Supervisor: Sabrina Wurzba

Note: this is a 9-week project.

Project code: PR13

Supervisor: Sampath Kumar Loganathan

Project code: PR14

Supervisor: Ryan Mailloux

Must have basic wet lab skills, basic biochemistry and metabolism.

Infection

Project code: PR15

Supervisor: Igor Cestari

Project code: PR16

Supervisor: Thavy Long

Molecular Biology

Project code: PR30

Supervisor: Shuaiqi Guo

Project: Our research program aims to better understand the mechanisms of microbial adhesion. Our objectives are twofold: while resolving the molecular structures of adhesion proteins and their secretion systems of pathogenic bacteria may help identify new therapeutic strategies alternative to conventional antibiotics, elucidation of mutualistic interactions between environmental bacteria and microalgae will provide insight into in reducing global greenhouse gases through microalgae-based carbon-neutral solutions. Thus our interconnected research programs will contribute to address two of the most pressing global crises: the emerging threats of antimicrobial drug resistance and climate change. The project will involve molecular cloning, recombinantly producing adhesion proteins by E. coli, purification of proteins for structure determination in the future.

Preference to students with basic molecular biology skills.

Molecular Basis of Human Disease

Project code: PR04

Supervisor: Brian Chen

Project code: PR08

Supervisor: Christian Rocheleau

Molecular Neuroscience

Project code: PR04

Supervisor: Brian Chen

Project code: PR05

Supervisor: Thomas Durcan

Neuroscience

Project code: PR04

Supervisor: Brian Chen

Project code: PR05

Supervisor: Thomas Durcan

Project code: PR27

Supervisor: Suresh Krishna

Project: For this program, there are two kinds of ongoing projects that will be suitable and available, depending on the students' background, skills and interests. Combinations of these two kinds are also possible. Students with a strong quantitative and/or programming background can do data-analysis projects based either on laboratory data, or on openly available data related to different kinds of neuronal responses (field potentials, neuronal responses from animals and humans undergoing epilepsy surgery, non-invasive neuroimaging responses) or behavioral data (eye-tracking, behavioral surveys, etc). In the second stream, students with a more experimental bent can design, perform and analyze the results of a human behavioral experiment (psychophysics). The topics will generally be in the areas of vision, hearing, eye-movements, sensorimotor co-ordination and attention. The areas involved are sensory/motor/cognitive neuroscience, psychology and AI - experimental, computational and based on data-analysis.

Computational Biology

Project code: PR26

Supervisor: Khanh Huy Bui

Project: Cilia are hair-like structures protruding out of the cell, taking part in a wide variety of biological processes. Since the cilia play an essential role in the development and function of the cell, cilia-related malfunction usually has detrimental effects on the development and the health of patients, such as retardation, blindness and chronic respiratory diseases. Understanding how cilia function will provide opportunities to effectively diagnose and treat cilia-related diseases. Dr. Huy Bui’s research focuses on elucidating the three-dimensional structure of the cilia and the underlying logistic system used to dynamically maintain and assemble the cilia using cryo-electron microscopy. In our lab, we use cryo-electron microscopy and cryo-electron tomography to obtain the high-resolution structures of various cilia-related structures. Using molecular modelling, we can build the atomic models of the cilia and test their function through knock-out or in vitro approaches. The undergraduate research project will focus on using image analysis tools to analyze cryo-electron microscopy and cryo-electron tomography data of cilia-related samples from our lab to build three-dimensional structures of the sample. In addition, the project will also focus on using molecular modelling software such as AlphaFold to build the atomic model of the structures obtained. The training will help students to gain a solid knowledge of structural biology. Apart from the computational training, the student can also learn wet lab experiments and shadow our graduate students doing electron microscopy if time permits.

Project code: PR27

Supervisor: Suresh Krishna

Project code: PR30

Supervisor: Shuaiqi Guo

Preference to students with basic molecular biology skills.

Project code: PR31

Supervisor: Codruta Ignea

Project: Taxol is one of the most effective anticancer drugs ever developed, currently used extensively in clinical practice. Despite being present naturally in the bark of yew trees, existing methods for taxol production are insufficient for the current and foreseen demand, maintaining a high price of the drug and its derivatives. A sustainable solution is production of taxol in microbial cell factories by reconstruction of its biosynthetic pathway. Through evolution, taxol biosynthesis synchronizes several enzymatic activities in a multi-step, multi-compartment and non-linear fashion that is highly challenging to fully reproduce in simple microbes. However, the majority of taxol biosynthetic enzymes are known and can be easily employed in cell free or whole cell systems supplemented with specific taxol intermediates. The students will employ combinatorial biosynthesis to produce intermediates for semi-synthesis of novel taxol analogues. Standing on enzyme promiscuity widely occurring in specialized metabolism, we will identify enzymes from different species to introduce non-canonical taxane modifications, aiming to improve the bioavailability of these class of compounds for the development of better therapies. Moreover, we will produce new-to-nature taxane derivatives by engineering unnatural taxane building blocks and scaffolds that will be used for library screening and subsequent combinatorial biosynthesis to produce intermediates for semi-synthesis of next-generation taxol analogues. Finally, a library of taxol analogues will be screened by computational docking to predict new or improved activities, broader anticancer spectrum and lower side effects. Taxol has had a lasting impact on the scientific community and society at large, spawning more interest and efforts than any other natural product. Following recent developments in genome sequencing and DNA synthesis, this project aids capitalizing on the potent bioactivity and the significant therapeutic value of taxol and will have a strong impact in the cost of patient treatment and the associated expenses of the public health.

Project code: PR32

Supervisor: Codruta Ignea

Project: Cannabis has been cultivated and used throughout recorded history for its various therapeutic properties. There are more than 120 cannabinoids with various therapeutic effects identified in the research of the last few decades. The two most abundant cannabinoids are trans-D9-tetrahydrocannabinol (D9-THC) and cannabidiol (CBD). Consequently, the research on their pharmacological activities and production strategies is also very abundant. Minor cannabinoids are any meroterpenoids (21- and 22-C terpenophenolic molecules with an alkyl (usually propyl or pentyl) side chain) compounds that are produced in Cannabis beside D9-THC and CBD. Such cannabinoids have not been explored extensively in research because of their limited production in plant systems that do not provide industrial production capacities. Nonetheless, such cannabinoids and their unnatural derivates are strong pharmaceutical targets for various diseases. In this research, various unnatural cannabinoids will be designed using Artificial Intelligence (AI) driven computational biology approaches such as molecular docking and random forest modeling. The AI-driven design will be based on their binding efficiency with the cannabinoid receptors (CB1 and CB2) or other G protein-coupled receptors (GPCRs) and rational selection of unnatural modifications that could subsequently introduced by biological synthesis. Once strong drug targets are identified, their synthetic pathway will be constructed in yeast. The fermentation optimization of the precursor molecules will then be used to maximize the production of these unnatural cannabinoids and for scale-up of the fermentation process. This research will generate a platform strain for the production of unnatural cannabinoids and their validation on different target receptors in the human body. The bioactivity assays will ensure the experimental verification of the proposed novel cannabinoids. Thus, the successful implementation of this project will open up a new line of pharmaceutical agents for various diseases including cancer, diabetes, HIV, and arthritis.

Project code: PR52

Supervisor: Kyle Elliott

Project: Increasingly, studies of wildlife biology use technology to acquire Big Datasets. One common application is the use of accelerometer data. You will examine accelerometer and magnetometer data collected from biologgers attached to Arctic seabirds (thick-billed murres) to determine when prey capture events happen. You will learn skills such as how to analyze biologging data on wildlife and how to approach Big Data questions. The student will work closely alongside a PhD student, who will provide the relevant training, especially proficiency in the statistical program R which is the most widely used statistical program in wildlife biology.

Digital Medicine

Project code: PR03

Supervisor: Piotr Pater

Artificial Intelligence

Project code: PR02

Supervisor: Jeremy Cooperstock

Project code: PR11

Supervisor: Qihuang Zhang

Project code: PR18

Supervisor: Samuel Huberman

Project: 1-"What does ChatGPT know about chemical engineering?": Working with LLMs on core Chemical Engineering concepts via systematic prompt engineering Project 2-"A large time limit study of the Fermi Ulam Pasta Tsingou problem": Working with high performance computing to reach the large time limits of the FPUT problem Project 3-"GPU-based solutions to the Phonon Boltzmann Transport Equation": Working with Parallelization, High performance computing, Linear Algebra, GPUs Project 4-"Machine learning algorithm for phonon branch sorting": Working Machine learning, Parallelization, High performance computing, Linear Algebra, GPUs

The projects are open to students in Physics and Computer Science. Indicate in the comments at the end of the form if a preference between the 4 sub-projects.

Material Science

Project code: PR20

Supervisor: Damiano Pasini

Project: We are working on origami metamaterials capable of reconfiguring their shape during folding hence capable of providing shape shifting and multifunctionality. The student will be investigating their motion and mechanical properties through an approach that involves experiments on proof-of-concept prototypes and basic simulations that are tailored to undergraduate student knowledge.

Project code: PR23

Supervisor: Daniele Malomo

Project: Existing structures built in Canada before 1970 are particularly susceptible to aging and climate change-related hazards, and their seismic performance are often sub-standard due to the use of non-engineered construction techniques. This research project seeks to test in the Jamieson Structures Lab the mechanical response of material samples extracted from actual masonry and concrete buildings in Montreal, to determine their residual strength. Tests will include destructive bending, compression and tension experiments on bricks, stone, concrete cylinders and rebars. Another group of students are expected to model numerically these tests using 3D Finite Element Method programs. McGill | struct-lab and Prof. Malomo will provide safety, technical and teamwork training to all incoming research assistants.

Project code: PR24

Supervisor: Idaresit Ekaette

Project: Biopolymer synthesis and modification for enhanced functionality. Biopolymers are large molecules sourced from plants, animals, and microbes. Biopolymers are characteristic of renewable nature, low cost, biocompatibility, and biodegradability compared to polymers derived from fossil fuels, but their independent application in materials is limited because of poor mechanical properties. Biopolymer examples are starch, cellulose, pectin, collagen, and chitosan. To improve the mechanical properties of a biopolymer, its crystal structure can be modified using innovative physical and chemical methods. The objectives of this research project are to: 1. Determine the effects of crosslinking on the crystallinity of a biopolymer blend, and 2. Evaluate the physicochemical properties of the new polymeric material obtained in objective 1. Methods and experiments will include select biopolymers, chemicals, thermal and non-thermal technologies. Characterization techniques will include but not limited to crystallinity by X-ray diffraction (XRD), thermal properties by differential scanning calorimetry (DSC), thermogravimetric analysis (TGA), and viscoelastic behavior by a rheometer, and dynamic mechanical analysis. The results from these characterizations will show tailorable properties and functionalities of biopolymer blends, thereby introducing novel high-performance biomaterials into the bio-based industry. These biopolymers will find applications in food design, food packaging, pharmaceuticals, tissue engineering, agriculture, drug delivery, textile, and water treatment. This research project is significant for students to acquire in-depth scientific knowledge and research protocols in biopolymer synthesis, properties, and applications. Students will also develop technical skills for advanced analytical methods and instrumentation. The production of biopolymers contributes to overall environmental sustainability and food security.

Project code: PR25

Supervisor: Abdolhamid Akbarzadeh

Project: Increasing global concerns about energy production, environmental pollution, and economy growth demand groundbreaking avenues for highly efficient structural and energy materials. Load-bearing, shape-transforming, energy converting, and autonomous sensing properties should coexist in multipurpose smart materials to unlock an unprecedented material property space for addressing the challenging demands. Multifunctional metamaterials can meet multiple functional requirements and deliver properties beyond what are found in naturally occurring materials. The unrivalled properties of metamaterials are mainly derived from their intricate underlying architecture. Additive manufacturing has also emerged as a frontrunner for facile fabrication of this new class of mechanical metamaterials. The majority of rational designs of metamaterials have relied on intuition; however, tuning the unmatched properties of multifunctional metamaterials, comprised of mechanics and smart material realms, calls for understanding their programmability and size-effect traits. With roots in cellular solids and smart materials, Professor Akbarzadeh and his research team at AM3L lab at McGill University are creating programmable, reconfigurable, and sustainable metamaterials. The interns in this program will join ground-breaking activities in AM3L lab on developing alternative multifunctional metamaterials where they resort to delicate topological design of cellular architecture, structural stability analyses, generalized continuum theory, multiphysics simulation and experimental characterization, and 3D printing to realize these rationally-designed advanced materials for a wide range of applications from lightweight and reusable intelligent structures/infrastructures to soft robotics and energy harvesters. The undergraduate interns will have the chance of collaborating with a professional team and multiple experts in the field of metamaterial design (theoretical, computational, 3D printing, and experimentation), with possibilities to joint the AM3L for their graduate studies.

Project code: PR53

Supervisor: Michael Hilke

Project: Novel properties in twisted bilayer graphene: The goal of the project is to synthesize and characterize twisted bilayer graphene devices in terms of their optical and electronic properties. Twisted graphene bilayers are two atomic sheets of graphite that have a twist angle between the two layers. It was found that depending on the twist angle, these bilayer devices can have very different properties, including superconductivity, strong optical non-linearities, as well as novel topological features. In this project the student will learn to fabricate these twisted bilayer devices by synthesis through chemical vapour deposition, and subsequent transfer. The student will further characterize these devices by optical spectroscopy and transport measurements in order to unravel some of the fascinating new properties.

Engineering

Project code: PR18

Supervisor: Samuel Huberman

The projects are open to students in Physics and Computer Science. Indicate in the comments at the end of the form if a preference between the 4 sub-projects.

Project code: PR19

Supervisor: Jovan Nedic

Project: Our applied aerodynamics research focusses on the interaction of propellers/rotors with unsteady and turbulent inflows, as one would expect to find in helicopters and unmanned aerial vehicles. We have several experimental projects in this field, where the student would work closely with either a graduate student or the professor directly, to take measurements of pressure, forces, and velocity in either our water or wind tunnel. Part of the work is funded by an industrial client, and depending on the project, the student may have to present their work at an update meeting with them.

Project code: PR20

Supervisor: Damiano Pasini

Project code: PR21

Supervisor: Ahmed Elgeneidy

Project: In 2016, the Caisse de dépôt et placement du Québec (CDPQ) announced plans to build the Réseau express métropolitain (REM), a state-of-the-art, fully automated 67-kilometer light-rail network that will fundamentally reshape transport in areas on and off the island of Montreal. When complete, the $6.3 billion project will link numerous suburbs—and Montréal-Pierre Elliott Trudeau International Airport —to downtown with frequent, high-speed rail service, that is universally accessible, altering travel and land-use patterns throughout the region for various groups of population. These changes are likely to have impacts on the health, social, economic, physical, and psychological well-being of all Montreal residents for the coming decades. The first branch, connecting Montreal’s South Shore, is expected to open in 2022, with additional segments coming online in 2023 and a final opening in 2024 for the full system. As one of the most ambitious—and costly—public transport projects in Canada in decades, the REM provides a unique opportunity to gauge the impacts of the types of major public endeavours that will become increasingly common and necessary as governments seek to decarbonize the transport sector. The REM's rapid advancement will allow us to pursue a comprehensive "before, during, and after intervention" research design to rapidly distill key lessons for future projects in Montreal and elsewhere in Canada. As part of research, we are collecting multiple waves of built environment data at the street level in a 1000-meter area around all future REM stations to understand the current level of accessibility and walkability around the network. Data will be used to monitor changes in the built environment over time around the stations as well as to provide policy recommendations for the REM and other transportation projects of various scale across Canada on beneficial practices in the implementation of accessible and walkable public transit stations. These insights will prove immediately valuable for cities where small and large transport infrastructures are currently being studied or proposed. The findings will also shape the province's future REM expansions, which the government of Quebec is already studying for eastern and northern areas of the metropolitan region. Interested students should send a cover letter, a resume, and unofficial transcript.

Project code: PR22

Supervisor: Ali Seifitokaldani

Project: Our team is focused on electrocatalytic conversion of CO2, NOx, and biomass tom value-added chemicals and fuels such as hydrocarbons (methane, formate, ethanol, etc.), ammonia, urea, amids, hydrogen, and upgraded biomass. We have experimental lab for those who are interested in having hands on experiments in electrocatalysis, and computational team who are interested in running density functional theory (DFT) computations to understand the underlying mechanism of the electrochemical reactions. For each stream there is a learning curve to be able to lead a project which most likely will not happen during a short visit, but we help students to learn the skills to be able to work independently in the future if they decide to pursue their interest in this field.

Urban Planning

Project code: PR21

Supervisor: Ahmed Elgeneidy

Biomanufacturing

Project code: PR31

Supervisor: Codruta Ignea

Project code: PR32

Supervisor: Codruta Ignea

Project code: PR33

Supervisor: Codruta Ignea

Project: Can you imagine running a milk farm feeding the cows with only sunlight and air instead of fresh grass? Scientists of synthetic biology are doing a similar thing. Since more than one thousand years ago, yeast (S. cerevisiae ) has contributed to the food industry, e.g., the bakery and wine-making industries. Nowadays, assisted by gene engineering, yeast cell factories have been evolutionarily changing the industrial production efficiency and mode in terms of non-native compound synthesis, ranging from chemicals, and drugs to complex natural products. We are developing the next generation of yeast production platforms in our lab. In the current project, we’ll explore the way of running yeast cell factories using mainly renewable energy sources, that is, to establish phototrophic yeast strains. Phototrophy means yeast will act as green plants, and survive on air and sunlight, which will significantly reduce yeast industrial production costs and will help to deal with the global greenhouse problem. Phototrophy includes two crucial processes: photo-reaction and CO2 fixation. Based on the yeast strains established in our lab, we propose to realize the project goal by building a retinal-driven CO2 fixation circuit using gene engineering tools. The present project will prove the possibility of feeding yeast using light as the sole energy source and using CO2 as the main nutrient input. The successful conduction of the project will foster many innovations, including new host cell strains, new metabolism pathway for the developed host cell, the new set-up for the developed yeast strain culture, etc. The knowledge developed in this project will foster innovations in yeast engineering and will advance the frontiers of advanced microbial production.

Project code: PR34

Supervisor: Codruta Ignea

Project: Due to the high efficiency and specialty features of enzyme in treating specific diseases, enzyme-based drug and therapies have been increasing in these years (The global market value will reach 2,100,000,000 USD in 2028). However, enzymes are vulnerable to the environment. Therefore, they need to be immobilized or capsulated. Currently, encapsulating enzymes in lipid nano/microstructures and immobilizing enzymes on porous silica surfaces are the two commonly used loading strategies. But still, they are in vitro methods. In most cases, enzymes have to be modified to get effectively loaded, which causes significant loss of enzyme activity. Moreover, the current “surface-modification” strategy for loading enzymes has wasted enormous inner pore surface area. Therefore, in this project, a bio-encapsulating strategy will be developed to wrap the alive, freshly produced enzymes in-situ. To be specific, yeast strains will be engineered genetically to obtain a capacity of generating a porous silica shell during their growth, resulting in the secretory enzymes trapped or loaded inside the silica capsules. This strategy is expected to be a high-efficiency way of producing “alive” enzyme capsules by preserving the enzyme activity to the largest extend.The successful conduction of the project will foster many innovations, including new host cell strains, new metabolism pathway for the bio-silica formation in yeast, novel scale-up technology for enzyme encapsulation industry etc.

Project code: PR35

Supervisor: Amine Kamen

Project: Method of determination of Full, Partial and Empty Capsid Ratios for Adeno-Associated Virus (AAV) Analysis using Raman Spectroscopy Background- When developing gene therapy, one of the most widely used delivery systems (vectors) is the adeno-associated virus (AAV). AAV is made up of several proteins called capsids that enclose a transgene, which is a single strand of DNA, in a closed shell. Three types of capsids are produced during the manufacturing of AAV vectors: empty, partial, and full. Empty and partial AAVs are regarded as manufacturing impurities because they are either devoid of genomic material or only contain small amounts of it. Since the full AAV contains the desired genomic material in its entirety, it is the desired product. The presence of these impurities may compromise the safety and effectiveness of AAV vector products because of the possibility of increased immunogenicity in the final product. Moreover, complete transduction of complete AAVs can be prevented by competing with the vector binding sites on the transfected cells. Therefore, it is essential to determine the quantity of these contaminants and the ratio of full to empty capsids, a critical quality attribute (CQA) during AAV production. Existing technologies employed to evaluate full to empty ratio include transmission electron microscopy (TEM, analytical ultracentrifugation (AUC), amongst a few. But these conventional approaches come with their own set of difficulties, which makes an orthogonal approach that is quicker and simpler to use necessary. Raman spectroscopy (RS) is a modern and information-rich technology for simultaneous identification of multiple CQAs in biomanufacturing. RS applications in biomedicine have multiplied exponentially as a result of major advancements in laser and detector technologies over the past two decades. A Raman spectrum provides quantitative, multivariate compositional information at the level of nucleic acids, lipids, proteins and carbohydrates. Therefore, it is possible to translate specific features of Raman spectrum into fundamental information on the molecular structures. This project will develop a modality of purity quantification of viral titer using Raman spectroscopy and machine learning. The hypothesis guiding this project is “ presence of full capsid and empty capsid can be identified by spectral analysis of the titer”. Specific Aim- Identification of features of separation between full vs empty capsid. Generation of regression model using various proportions of full and empty capsids in the titer. Generation of a calibration curve. Prediction of full and empty capsid ratio in the titer. Methodology- AAV Serotype 2, 6 or 8 (Full and Empty) Sample will be purchased (Charles Rivers). The titer of empty enriched packaged AAV, and the titer of full enriched packaged AAV will be mixed with master mix and used for Raman analysis. Spectra of empty and full capsids and its mixtures in the ratio of 10:90, 20:80 ---- 80:20 and 90:10 will be taken. A regression training model will be established and accuracy of prediction of AAV titre purity will be assessed. Reproducibility of the method will also be analyzed. Significance- Empty/ versus full is an important CQA that needs to be monitored throughout the development and production of the viral vector-based therapy. While a number of techniques can be used for empty full analysis, there are still limitation to these workflows. Machine learning-based Raman spectroscopy has potential to robustly analyze purity of the titre without the need to separate empty and full capsids. This methodology has potential to be applied at-line and the results will be available in less than 1 hour per sample. Future Direction- Successful completion of this project will generate training data which can be used for developing real-time process analytical technology for AAV downstream processing.

Synthetic Chemistry

Project code: PR36

Supervisor: Mark P. Andrews

Project: My laboratory offers experiences in 2 project areas: (1) three-dimensional architectures of cellulose nanocrystals (CNC) to make scaffolds for human tissue repair; and (2) properties of cellulose microbeads prepared from CNC as replacements for environmentally damaging micro plastics. Cellulose nanocrystals are the biological building blocks of almost all plant life. The student(s) will first be introduced to the principles of Green Chemistry as they learn how wood products, sustainably harvested from Quebec forests, are converted into CNC, and how the chemistry leads to a low planetary carbon footprint. Project (1) will teach the student how to convert the CNC into tissue scaffolds. A scaffold is a very porous structure that resembles a sponge but remains stiff even as it takes up water and nutrients to host living cells for tissue repair. The student(s) will receive hands-on training in the techniques of small angle X-ray scattering (SAXS), Scanning Electron Microscopy (SEM) and several other methods to measure the pore structure. The study will introduce the student(s) to the importance of interdisciplinary research involving the medical community. Project (2) will select from an area of application in consultation with the student(s). Possible applications are drug delivery, agriculture, water purification, or color cosmetics based on natural dyes. The student(s) will be taught how prepare dry powders of microbeads from (vapour phase) aerosols of cellulose nanocrystals. The student(s) will be trained in the techniques and interpretation of SAXS, atomic force microscopy, X-ray photoelectron spectroscopy and SEM. The student(s) will learn how these techniques provide information relevant to the type of application. The summer experience will include a tour of the research facilities of McGill start-up company, Anomera. The student(s) will learn how the methods of Green Chemistry can be translated from the research laboratory for positive impact on the environment.

Nanotechnology

Project code: PR36

Supervisor: Mark P. Andrews

Project code: PR39

Supervisor: Saji George

Project: Nanotechnology enabled biostimulant for plant growth and productivity. The world food bank estimates that feeding a world population of 9.1 billion people in 2050 would require raising overall food production by 70% between 2005/07 and 2050. The increasing global demand for food forces the agriculture sector to rely on heavy use of agrochemicals for increasing crop protection and productivity. The exorbitant use of fertilizers and pesticides, however, is unsustainable and causes irreparable damage to the environment and organisms. Consequently, there is an emphasize on developing cost-efficient, high-performing biostimulants that are less harmful to the environment and humans. A prototype of a nano-enabled bacterial-based biostimulant (nOB9) was developed from our group using active compounds (mostly Lipopeptides produced by a bacterium Bacillus velengensis strain OB9) encapsulated in nanoparticles of halloysite (HNT) clay. The encapsulation of lipopeptides in HNT increased its stability, shelf-life and improved the performance. The product was successfully tested under controlled conditions and field conditions that demonstrated significant improvement in seed germination, plant growth, root nodules and overall growth performance yield increase and infection control when tested in yellow beans. While the commercial prospects of this product are high, the inhibitory cost of production can only be reduced if the bacterial yield of lipopeptide production is increased. The proposed project aims at improving the bacterial yield by genetic manipulation of the bacteria. The aim is to increase the production of the lipopeptide from its current titer of 1g/L to reach a target of 5-10g/L to be market viable. Students absorbed in this project will be trained to use CRISPR/Cas 9 to enhance yields of the identified secondary by inserting a promoter sequence upstream of the lipopeptide genes and/or identifying major metabolites produced by the bacteria.

Project code: PR536

Supervisor: Mark P. Andrews

Project: My laboratory offers experiences in 2 project areas: Project (2) will select from an area of application in consultation with the student(s). Possible applications are drug delivery, agriculture, water purification, or color cosmetics based on natural dyes. The student(s) will be taught how prepare dry powders of microbeads from (vapour phase) aerosols of cellulose nanocrystals. The student(s) will be trained in the techniques and interpretation of SAXS, atomic force microscopy, X-ray photoelectron spectroscopy and SEM. The student(s) will learn how these techniques provide information relevant to the type of application. The summer experience will include a tour of the research facilities of McGill start-up company, Anomera. The student(s) will learn how the methods of Green Chemistry can be translated from the research laboratory for positive impact on the environment.

Biotechnology

Project code: PR12

Supervisor: Jennifer Ronholm

Project code: PR24

Supervisor: Idaresit Ekaette

Project code: PR29

Supervisor: Elias Georges

Project: Compare Binding Affinity and Specificity of anti-tubulin antibody to that of Tubulin-specific Binding Peptide sequence Summary of Project Antibody-antigen interaction is one example of protein-protein interactions. The binding domains that determine the binding affinity and specificity between an antibody and its antigen is determined mainly by the complementarity determining regions (CDRs) that are part of the variable domains of the heavy (CDR-H1-3) and light (CDR-L1-3) chains of an IgG. There 3 CDR sequences in each of the heavy and light chains and each CDR sequence is roughly 6 – 15 amino acid residues. It is well accepted now that the amino acid sequence composition and the spatial organization of both heavy and light chains’ CDR sequences determine the binding affinity and specificity of a given antibody towards it antigen. Over the past several decades, we have used high-resolution peptide mapping approaches to identify high-affinity binding sequences between two interacting proteins. Using this approach, we have shown that such peptides encoding for high-affinity binding sequences (HABS) that have the capacity to bind its interacting protein with high-affinity and specificity much better than the original full-length protein. The size of HABS is roughly 6 -15 amino acid residues. To build on our understanding of these HABS binding entities, the objective of this project is to fuse one or more of these HABS to human antibody constant sequence (hFc) with a linker domain and compare the binding affinity and specificity of such constructs (HABS-Linker-hFc) to a monoclonal antibody specific to the same protein. Earlier work in the lab has identified several HABS that bind beta-tubulin with high-affinity and specificity. Therefore, the specific aims of this project are to compare the binding of tubulin-specific HABS-Linker-hFc construct to tubulin specific monoclonal antibody for binding affinity and specificity.

Project code: PR37

Supervisor: Valerio Hoyos-Villegas

Project: Development of novel plant breeding methods for screening breeding populations. Hybridity testing in breeding populations developed by plant breeding programs using DNA markers derived from next-generation sequencing arrays has the potential to increase the effectiveness and efficiency of breeding programs. Students will learn methods around marker development and screening, as well as procedures for validating markers experimentally to implement them in commercially driven plant breeding programs. Using pulse crops as a model species, but skills are extendable to any crop species. Students will be exposed to field, computational and laboratory techniques as part of a breeding program aimed at developing commercial pulse crop varieties.

Students have to be prepared to work in the field under variable environmental conditions as well as to engage in repetitive tasks.

Project code: PR38

Supervisor: Jaswinder Singh

Project: One of the great challenges of the 21st century is to provide sufficient, nutritionally- rich and sustainably produced food for the rapidly expanding global population. Genome Editing can be used to introduce genetic variation without transgenesis and can even be used to recreate naturally occurring mutations into elite varieties of crops and animals. Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR)-associated endonuclease and its derived technologies allow direct modification of genes or their regulatory sequences. Recently, our team has developed complete reference-quality genome sequences of four important oat varieties. Many traits such as fungal resistance, height, beta-glucan, oil content, drought resistance, and flowering time can show large-magnitude effects resulting from changes at a single or few genes. We have identified important genes which are associated with beta-glucan content (TLP-8) and flowering time (VRN3-7D). We aim to use CRISPR/Cas9 based gene editing approach to study the regulation of VRN3 and TLP-8 thus understanding the association of flowering time and beta-glucan content. The information gained will allow the identification of natural variability in existing wild or cultivated oat that could be introgressed through precisely targeted conventional selection. Our proposed work will lay the foundation for a new genome editing method in oat. Genome editing allows plant breeders to make targeted improvements within a plant’s existing DNA. We will initially standardize the method with specific gene constructs associated with β-glucan regulation and flowering time. Our short-term objective is to ensure the agility of the oat research community to respond to new opportunities. Our longer-term objective is to integrate CRISPR- based genome editing approaches with oat breeding for the development of oat varieties that address new challenges in food security and environmental stress.

Project code: PR39

Supervisor: Saji George

Project code: PR40

Supervisor: Xiaonan Lu

Project: Campylobacter is a major foodborne pathogen worldwide, and highly associated with agri-ecosystem and food processing environment. Campylobacteriosis is the most frequently reported bacterial illness in Canada, outnumbering the reported cases of Listeria monocytogenes, Shiga toxigenic Escherichia coli and Salmonella infections combined. The contamination of this pathogenic microbe has a significant economic impact on the poultry industry. Current methods for the detection of Campylobacter in poultry products have various disadvantages, such as time consuming and labor intensive. In this project, we aim to develop an isothermal amplification-CRISPR/Cas12a based lateral flow assay for rapid detection of Campylobacter in poultry products. CRISPR/Cas systems have been extensively used for gene editing and transcriptional regulation, and show great promise in molecular diagnosis. This new assay will be more rapid, accurate, sensitive and affordable than the current commercial ones, and brings benefits to the government agencies and industry stakeholders performing regular testing of Campylobacter contamination.

Project code: PR41

Supervisor: Codruta Ignea

Project: To produce electricity from solar energy is of global importance to address the energy crisis and achieve sustainable development. Although cyanobacteria have always been the expert utilizing and converting solar energy, they barely have an effective circuit to export the generated electrons to form electricity on the electrode. No successful attempts of building artificial circuits in cyanobacteria have yet been reported. Recently, a syntrophic system consisting of cyanobacteria and electro-genic bacteria was demonstrated to be efficient in power generation (135~ 150 mW·m−2), which is quite inspiring. However, compared to electro-genic bacteria, which is vulnerable to growth conditions, yeast is considered more safe and quite robust under a wide range of growth conditions. Moreover, its mature genetic manipulation and broad substrate spectrum make yeast good candidate for exploring the engineered production of electricity. Therefore, in this project, we will build a consortium system, where cyanobacteria were engineered to produce lactate in high-efficiency, which could be further used by membrane-engineered yeast to produce electricity. Thereby, the charging (active electrons generation) and discharging (electrons export to out electrode) sector are assigned to photosynthetic and electro-genic microorganisms, respectively. Furthermore, nanomaterials would be explored to improve the innate electro-generation/transportation capacities of the yeast. This project will provide an alternative biological strategy to construct solar cells/panels. Once this technology and equipment achieve practical efficiency. They can significantly reduce the cost of electricity used in industrial production, and eventually benefit everyone. The knowledge developed in this project will foster innovations in yeast engineering and will advance the frontiers of advanced microbial production.

Project code: PR42

Supervisor: Codruta Ignea

Project: The current agricultural sector releases 25% of the greenhouse gases (GHGs); but is not efficient to meet the increasing demands of food for 10 billion people worldwide by 2050. Increased accumulation of GHGs is causing drastic events such as droughts, forest fires, floods, and unpredictable temperatures. Cereal crops contribute 63% of human-food calories and require massive amounts of synthetic nitrogen fertilizers (SNF) that release nitrous oxide (GHG), having a global warming effect of 3-fold greater than carbon dioxide. Wheat is currently feeding 35% of the world's population as a staple food. Biofertilizers are microbial communities capable of biological nitrogen fixation (BNF); but they are inefficient in cereals, in the presence of SNF, or under free-living conditions. Cyanobacteria are photosynthetic microorganisms that can utilize CO2 for their growth, and they possess mild BNF capabilities. The application of pesticides incites drastic changes in crop fields, local microbial communities, and the environment. Biopesticides such as natural products engineered in yeast are ideal targets for wheat crops, but these microorganisms cannot grow efficiently in the field in the absence of specific nutrients. Therefore, a microbial consortium of cyanobacteria with enhanced BNF and biopesticide-producing yeast designed specifically for wheat soil can provide dual capabilities in one application. However, such a co-culture cannot survive in wheat soil without the initial screening and selection of symbiotic microbes to the wheat roots as the CO2-utilizing partner. This research will generate microbial consortia with dual benefits of BNF and biopesticides that will also use atmospheric CO2 and can self-sustain in wheat fields because of their nutrient-based mutualistic relationship with each other. Thus, it will investigate the long-lasting problem of biological nitrogen fixation in cereals in an unprecedented manner, directly targeting the reduction of GHG emissions.

Project code: PR44

Supervisor: Jacqueline Bede

Project: Upon exposure to pesticides, Insect genes that encode detoxification enzymes can result in insecticide resistance. Thus, it is critical that we understand what genes are most important for pesticide resistance and how they are regulated. This internship will involve exposing Trichoplusia ni caterpillars to pesticides and/or plant natural products and then measuring the expression of detoxification genes. Cabbage looper (Trichoplusia ni) caterpillars are generalist herbivores of a number of important crops such as crucifers (i.e. canola, broccoli), legumes and cotton. These insects are economically important pests both in Canada and Saudi Arabia. Recently the genome of this caterpillar has been sequenced allowing us to investigate the dynamic expression of detoxification genes in response to pesticides or plant defensive compounds. This project will involve conducting insect toxicity assays to determine the lethal dose of the pesticides or plant natural products. Using sublethal doses, the effect of the compound on inducing insect detoxification genes will be measured by RT-PCR. This will involve analysing transcriptomic data (RNA-Seq; the data is already in hand) to identify potential pesticide-induced detoxification genes, designing and optimizing primers to target key genes, exposing the insect to sublethal doses of toxic compounds, extracting total RNA and evaluating expression of the detoxification genes by reverse-transcriptase PCR.

Given that this is a short project (2 months), we want to balance a student-driven project with experience with different techniques. Thus, there may be other opportunities for the student (such as training in plant-pathogen assays).

Agriculture

Project code: PR37

Supervisor: Valerio Hoyos-Villegas

Students have to be prepared to work in the field under variable environmental conditions as well as to engage in repetitive tasks.

Project code: PR38

Supervisor: Jaswinder Singh

Project code: PR39

Supervisor: Saji George

Project code: PR40

Supervisor: Xiaonan Lu

Project code: PR44

Supervisor: Jacqueline Bede

Project code: PR45

Supervisor: Philippe Seguin

Project: Quinoa is a crop for which interest and demand has considerably grown in recent years in part due to unique nutritional properties. Production is currently concentrated in South America and the production in Canada is limited and restricted to western provinces. Preliminary trials conducted in eastern Canada have demonstrated that local quinoa production is possible, however, there are several factors limiting production including limited knowledge of optimal agronomic practices and prevalence of pests. For quinoa production to be expended in eastern Canada it is essential to reduce this variability and define best management practices; a research project is being conducted at the Agronomic Research Station of McGill University to address these issues. Specific objectives are to: 1) Evaluate a range of cultivars to determine their adaptation to Quebec, 2) Identify environmental factors affecting seed yields and most susceptible growth stages, 3) Evaluate different strategies to control most problematic pests in quinoa, 4) Determine the impact of plant density on incidence of fungal pathogens, plant development and seed yields. These specific objectives are addressed by conducting a series of field experiments and will allow us to ultimately develop best field management practices. We are looking for an undergraduate student that could assist a graduate student during her project in maintaining plots and collecting data during part of the growing season. The student will gain hands-on knowledge in agronomical research.

Project code: PR47

Supervisor: Yixiang Wang

Project: The amount of biomass waste is rapidly increasing, which leads to numerous disposal problems and governance issues. The disposal of biomass waste via landfill or incineration also represents a waste of useful resources. As part of the circular economy, biomass waste should be utilized by either reusing (same purpose/application), recycling (repurposed for further use, typically in an application of similar value or below), or up-cycling/valorizing (repurposed for an application of higher value). Cellulose is the most abundant natural polymer, representing approximately 40–50% of plant and woody biomass by weight. However, it is difficult to dissolve cellulose in water and common organic solvents to recycle. In this project, cellulosic waste will be collected and recycled into biodegradable packaging films through ‘green’ solvent systems. The student will learn the dissolution and regeneration of cellulose and the preparation and characterization of cellulose films. The student will have the access to our equipment to test the mechanical properties, oxygen/water vapor barrier properties, and biodegradability. After the training, the student will have knowledge of natural polymer, cellulose dissolution theory, and materials fabrication and characterization, and be aware of the importance to develop biodegradable materials.

There is a current UAE student from UAEU that will be actively helping the undergraduate student during the traineeship.

Project code: PR48

Supervisor: Zhiming Qi

Project: We will conduct a simulation on hydrologic cycle, phosphorus loss and/or greenhouse gas emission using computer models; to build a database for large scale hydrologic, environmental, and crop modeling.

Sustainability

Project code: PR43

Supervisor: Djordje Romanic

Project: The UAE Climate Change Risks & Resilience report outlines the necessity of improving the resilience of UAE communities to climate change. In particular, the report suggests that one of the largest areas of uncertainty is the increase in severity and frequency of occurrence of sandstorms and heavy fogs. The authors of the report request further research in this field. de Villiers and Heerden (2007) examined conditions associated with dust storms at the Abu Dhabi International Airport from 1994 to 2003. Here, we propose the extension of their study up to the end of 2023 (Student 1) and the inclusion of fog events (Student 2). Our study will statistically investigate these events (duration, intensity, spatial extent), correlation with other meteorological parameters (wind speed and direction, temperature and humidity profiles, etc.) as well as classifying weather conditions leading to dust storms and heavy fog events in UAE. As such, this research will directly contribute to addressing the pressing conclusions of the UAE Climate Change Risks & Resilience report concerning the reduction of the uncertainty associated with sandstorms and heavy fog in the UAE.

Project code: PR51

Supervisor: Kakali Mukhopadhyay

Project: ACHIEVING NET DECARBONIZATION IN THE UAE: A CASE STUDY The United Arab Emirates’ (UAE) commitment towards Net Zero Emissions by 2050 makes it the first country in the Middle East and North Africa (MENA) bloc to announce such an ambitious plan. The COP28 being held in Dubai further strengthens its stand towards collaborative efforts for restricting the global warming related disasters that the world is witnessing regularly. One of the key aspects in this regard is mobilizing green financing solutions in which UAE is expected to be a key leader, with significant investments already announced towards climate change initiatives in collaboration with the IMF, the EU and other international financial institutions and countries across the world. With its entry into the green and sustainable bond market and ESG financing, the UAE is becoming a recognized destination for innovative green financing alternatives. UAE which is also part of the G20 set forth its priorities, highlighting not only energy transition, but also efforts towards climate-smart agricultural and food systems, financial inclusion, and digital health innovations which directly or indirectly contribute towards the Sustainable Development Goals. The students' task will involve conducting a brief overview and evaluation of the energy and agriculture industries in UAE, while also considering their current status and potential for green alternatives. By examining green alternatives for both the energy and agriculture sectors, this study will aid in the formulation of decarbonization pathways. Students will gain exposure to modelling the UAE’s decarbonization trajectory focusing on the energy transition roadmap and climate-smart agriculture and food systems for building resilience. The UAE, a major oil producer and supplier globally, is poised to become a pioneering example for the MENA region and other oil-producing nations with its economic strategy towards achieving net-zero goals.

Climate Change

Project code: PR43

Supervisor: Djordje Romanic

Project code: PR50

Supervisor: Jeffrey Cardille

Project: In my research lab at McGill in the Faculty of Agriculture and Environmental Sciences, we study tropical deforestation, carbon storage, and climate change. Using satellite images and advanced pattern recognition techniques, we develop new ways of detecting and tracking these important changes that influence Earth’s future. These positions will combine advances in image vision with remote sensing, and may well become publishable articles for motivated students. I have a strong history of success with undergraduates, shepherding several to their first peer-reviewed publications based on summer projects. The remote sensing of land resources – looking down at Earth from satellites – is undergoing a transformation. After decades of only one or two satellites in orbit returning data for a large fee, the past few years have seen more launches and a transformation to free data. This means that as in other fields transitioning to a “big data” outlook, remote-sensing analysts can now confront new problems using much more information. Meanwhile, the domain of pattern recognition is undergoing its own revolution. For example, Facebook’s parent company Meta recently unveiled a new algorithm with clear potential to allow human-caliber pattern recognition. Designed to find faces and objects in images, in remote sensing this offers the possibility of enormous improvements in detecting land use and land cover changes. The proposed summer students will need to be highly technical with strong understanding of programming, image processing, with experience with Google Earth Engine a significant plus. This summer’s project will involve exploring the potential of this and other new algorithms on satellite images from around the world. The results will be of very definite use to the scientific community. The work of these students is also likely to be of interest to policymakers seeking to mitigate climate change, notably through the recently announced Alterra effort led by UAE.

Project code: PR51

Supervisor: Kakali Mukhopadhyay

Environment

Project code: PR46

Supervisor: Peter Douglas

Project: This research is part of an interdisciplinary project to understand the spatial and temporal distribution of greenhouse gas emissions in the Montreal metropolitan area. The overall goals of this project are to link a more detailed understanding of greenhouse gas emissions sources with studies of the atmospheric distribution of these gases above the city. The projects described here are focused on understanding emissions processes and their distribution around the city, with a primary focus on methane. The student projects would be specifically involved in two project objectives: 1) Bicycle based surveys of ground-level methane concentrations across different Montreal neighborhoods. This would involve carrying out bicycle surveys on a regular basis, and then analyzing the geospatial patterns in the data. This will inform our understanding of the spatial distribution of methane sources in in the city and identify unknown methane hot spots. 2) Periodic sampling of landfill gas emissions. This would involve approximately weekly trips to active and abandoned landfills around the city to carry out gas chamber sampling. Gas samples would be collected and returned to the lab to measure the concentration and isotopic composition of methane and carbon dioxide. These data would be used to identify the emission rate of these greenhouse gases and their sources, and how they vary spatially and temporally across different landfills. A key goal is to understand how differences in methane oxidation control methane emissions from these environments. The two projects would provide experience in greenhouse gas and trace gas analysis, geospatial data analysis, isotopic analysis, and environmental sampling techniques in an urban setting. These are valuable techniques for future careers in climate change mitigation and greenhouse gas monitoring.

Project code: PR47

Supervisor: Yixiang Wang

There is a current UAE student from UAEU that will be actively helping the undergraduate student during the traineeship.

Project code: PR48

Supervisor: Zhiming Qi

Project code: PR49

Supervisor: Nastasia Freyria

Project: The objective of the study is to investigate the impact of nutrient amendment and dispersant on Arctic hydrocarbon-biodegradative strains at sub-zero and extremely cold temperatures. Baseline data will be established by conducting a 6-month laboratory column mesocosm experiment, which has been scheduled for the beginning of 2024. The experiment will simulate an oil spill on an Arctic beach and replicate daily tidal cycles. In the summer of 2022, sediments from a pristine beach located in Resolute Bay, Nunavut, Canada, were collected for this purpose. This study evaluates the effects of biostimulation treatments (nitrate and phosphate amendments) and added dispersants (washing agent and biosurfactants) on the degradation of hydrocarbons in beach sediments. The student will assist in isolating Arctic sediment strains from the mesocosms in the ex-situ column experiment and culture them under varying conditions, including temperature fluctuations, changes in salinity, nutrient concentration, and more. The aim is to assess the isolates' adaptability to a dynamic surrounding. Additionally, the student will assist in extracting cell DNA, and sequencing the 16S rRNA gene. The student will help the team in preparing for the field season while gaining insight into the scientific materials and methods employed to collect samples in challenging Arctic conditions. The collected data will facilitate comprehension of the response to bioremediation procedures and the potential persisting toxicity.

Project code: PR50

Supervisor: Jeffrey Cardille

Project code: PR51

Supervisor: Kakali Mukhopadhyay

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