Grant: DRA: Canada Impact+ Research Training Awards - Doctoral
Université de Sherbrooke
$120,000.00
Identification and Validation of Novel Antibiotic Resistance Genes.
FY 2025-26
Summary
"Antibiotics have saved millions of lives and remain essential to healthcare in Canada. However, their effectiveness is increasingly threatened by antimicrobial resistance (AMR), a process by which bacteria evolve ways to survive antibiotic treatment. If left unaddressed, AMR could lead to more severe infections, higher healthcare costs, and increased strain on Canadian hospitals. Global estimates suggest that by 2050, deaths linked to AMR could rival those caused by cancer today, making it one of the most serious public health challenges facing Canadians and populations worldwide.
At the heart of this problem are AMR genes (ARGs), which allow bacteria to resist antibiotics. These genes often emerge outside hospitals, in the human gut, animals, and natural environments. From there, they can transfer into disease-causing bacteria, accelerating AMR’s spread and making common infections harder to treat in Canadian communities.
A major challenge is that many ARGs remain unknown. Current screening methods looking for new ARGs often fail to detect them, limiting Canada’s ability to anticipate and prevent emerging AMR threats.
This PhD project aims to address this gap by using advances in computer science and biology. By examining the three-dimensional shapes of proteins and combining this information with genetic data using machine-learning tools, the research will improve the identification of new ARGs before they become widespread.
The outcomes of this research will: 1. Improve Canada’s ability to detect emerging ARGs that pose a risk to human health; 2. Strengthen monitoring of AMR across human, animal, and environmental settings; 3. Provide evidence to inform Canadian public health and environmental policies aimed at reducing the drivers of AMR; and 4. Support the development of future treatments and interventions against resistant infections.
Together, this work will help protect the effectiveness of life-saving antibiotics, strengthen Canada’s public health preparedness, and support evidence-based responses to one of the most important health challenges of the 21st century."
Department
Program
DRA: Canada Impact+ Research Training Awards - Doctoral
Recipient
Location
Quebec, Canada
Recipient Type
Academia
Type
Grant
Source
CIHR Funding Decisions Database
As published
Id
568217
Name
Choukair Dayana
Region
Québec
Country
Canada
Orgtype
Institution Paid; Research Institution
Prcname2
Canada Impact+ Research Training Awards - Doctoral
Projecttitle
Identification and Validation of Novel Antibiotic Resistance Genes.
Programtype2
Studentship Programs
Orgnameinp2
Université de Sherbrooke
Cihramount2
$120,000
Cihrequipment2
$0
Programname2
DRA: Canada Impact+ Research Training Awards - Doctoral
Keyworddelim
Antimicrobial Resistance; Machine Learning-Driven Functional Genomics; Novel Antibiotic Resistance Genes
Abstract
"Antibiotics have saved millions of lives and remain essential to healthcare in Canada. However, their effectiveness is increasingly threatened by antimicrobial resistance (AMR), a process by which bacteria evolve ways to survive antibiotic treatment. If left unaddressed, AMR could lead to more severe infections, higher healthcare costs, and increased strain on Canadian hospitals. Global estimates suggest that by 2050, deaths linked to AMR could rival those caused by cancer today, making it one of the most serious public health challenges facing Canadians and populations worldwide.
At the heart of this problem are AMR genes (ARGs), which allow bacteria to resist antibiotics. These genes often emerge outside hospitals, in the human gut, animals, and natural environments. From there, they can transfer into disease-causing bacteria, accelerating AMR’s spread and making common infections harder to treat in Canadian communities.
A major challenge is that many ARGs remain unknown. Current screening methods looking for new ARGs often fail to detect them, limiting Canada’s ability to anticipate and prevent emerging AMR threats.
This PhD project aims to address this gap by using advances in computer science and biology. By examining the three-dimensional shapes of proteins and combining this information with genetic data using machine-learning tools, the research will improve the identification of new ARGs before they become widespread.
The outcomes of this research will: 1. Improve Canada’s ability to detect emerging ARGs that pose a risk to human health; 2. Strengthen monitoring of AMR across human, animal, and environmental settings; 3. Provide evidence to inform Canadian public health and environmental policies aimed at reducing the drivers of AMR; and 4. Support the development of future treatments and interventions against resistant infections.
Together, this work will help protect the effectiveness of life-saving antibiotics, strengthen Canada’s public health preparedness, and support evidence-based responses to one of the most important health challenges of the 21st century."
Competitiondate
202603
Approvedterm2
3 yrs 0 mth
Pinamesdelim
Choukair, Dayana
Approvedterm
3 ans 0 mois
Cihrcontribution2
~ $120,000~ $0~