Introducing the 2024 cohort of IIDR & DBCAD Undergraduate Summer Student Fellows

Congratulations to the 2024 IIDR/DBCAD Undergraduate Summer Student Fellows! Now in its 12th year, this highly competitive award program continues to provide funding for undergrads to work in IIDR labs over the summer practicum.

This year’s cohort was carefully selected from a competitive pool of applicants — special thanks to all those who applied, to their supervisors, and to the reviewers who took the time to evaluate applications and inform this year’s selection process.

Each award is of $4,000, and with 10 successful applicants this year, the IIDR and DBCAD have proudly invested $40,000 into the next generation of scientists. Continue on to learn more about their exciting research.

Autumn Arnold (Stokes Lab, DBCAD Scholar)
	The ESKAPE pathogens are a group of multi-drug resistant bacteria that have acquired resistance against last-resort antibiotics. These bacteria are responsible for the majority of hospital-acquired infections, and have been prioritized by the World Health Organization for the research and development of novel antibiotics. Alarmingly, no novel antibiotic classes have been discovered since 1987, attributed to bottlenecks in conventional antibiotic discovery pipelines. Machine learning (ML) algorithms can be leveraged to virtually screen vast chemical libraries for antibacterial activity and efficiently prioritize promising molecules to test in the lab, increasing the rate at which we can discover novel antibiotic candidates. Autumn has trained an ensemble of ML models to predict the antibacterial activity of over 12 million molecules against the ESKAPE pathogens and has used these predictions to prioritize molecules to test in the lab. To date, the group has discovered nine molecules that exhibit potent antibacterial activity against various ESKAPE pathogens. Autumn has selected the most promising molecule to elucidate mechanism of action and test toxicity and infection clearance in mice. These models will also be released online, where users can input molecules and receive predictions for each ESKAPE pathogen.
Mei Chiao (Wright Lab, DBCAD Scholar)
	A major barrier in natural product antibiotic discovery is the rediscovery of known compounds, as it impedes progress and costs time and resources. In light of these challenges, the Wright lab has developed an antibiotic resistance platform (ARP). The ARP consists of >90 antimicrobial resistance genes expressed in Escherichia coli that enable the identification of common antimicrobials in bioactive extracts before significant investment in purification. While effective, the current ARP protocol is slow and laborious. Mei’s project will build upon the existing platform to construct a liquid version, allowing for the rapid dereplication (or identification) of known compounds in over 180 bioactive natural product extracts. This research aims to improve the accessibility of the existing ARP constructs and reduce rediscovery within the laboratory, contributing to the development of more effective antimicrobial strategies in the ongoing battle against antibiotic resistance.
Emily D’Agostini (Coombes Lab, IIDR Scholar)
	Crohn’s disease (CD) is an inflammatory bowel disease (IBD) associated with gut inflammation. Current research suggests that the balance of gut bacteria plays a role in the development of CD, with a specific strain of bacteria called adherent-invasive E. coli (AIEC) often overrepresented. Previous work from the Coombes Lab has shown that antibiotic treatment can worsen this imbalance, leading to AIEC expansion and gut inflammation. Recent literature debates the effectiveness of probiotics in restoring microbial balance in the gut. Emily’s research will investigate whether probiotics help to counteract antibiotic-induced AIEC expansion in a mouse model by measuring AIEC levels in stool samples after probiotic supplementation. On a broader scale, this work aims to characterize how post-antibiotic treatment with probiotics affects the overall microbial and inflammatory landscape of the gut. Investigating the role of probiotics in combatting antibiotic-induced gut inflammation and AIEC expansion not only contributes to our understanding of CD, but has implications for the development of novel therapeutics and clinical management strategies to improve the livelihoods of CD patients.
Paankhi Dave (Burrows Lab, IIDR Scholar)
	Opportunistic pathogens like Pseudomonas aeruginosa use surface-exposed appendages called Type IV Pili to infect host cells and facilitate movement across surfaces; however, this makes Type IV Pili targets for other pathogens, like bacteriophages. Phages are viruses that can infect and kill bacteria. Certain phages also produce a protein called Aqs1, which interacts with the pilus and aims to disable it, masking recognition from other phages. Paankhi’s project aims to investigate the interactions between Aqs1 and PilB, a pilus protein. Understanding this interaction could lead to the development of new strategies to combat bacterial infections, ultimately aiding in the development of molecules capable of inhibiting PilB function.
Anna Fan (Coombes Lab, DBCAD Scholar)
	Salmonella enterica is a gram-negative, intracellular bacterium that causes significant morbidity and mortality worldwide. In sub-Saharan Africa, Salmonella Typhimurium sequence type (ST) 313 can cause invasive non-typhoidal Salmonella (iNTS) disease, resulting in bacteremia, systemic infection, and high mortality. This is due to how the bacteria can enter the circulatory system, proliferate in macrophages, and disseminate to other cell types. The high fatality rate can also be attributed to the antibiotic resistance of ST313 isolates. Anna’s project will focus on assessing a machine-learning model for its predictive ability to generate anti-iNTS molecules. This research will test the predicted hits against ST313 and other S. Typhimurium isolates to assess the accuracy and strain specificity of the model. This will be done in hopes of identifying a compound that safely and effectively inhibits ST313.
Esther Jeong (Gillgrass Lab, IIDR Scholar)
	Human immunodeficiency virus (HIV) is a major public health challenge, undermining the immune system and increasing vulnerability to infections, such as tuberculosis. To study HIV, scientists can use special humanized mice that have a human-like immune system. In fact, the Gillgrass laboratory has demonstrated enhanced reconstitution of the human immune system by humanized DRAGA2 mice models; however, the generation of these models is challenging, primarily due to the scarcity of cord blood derived CD34+ hematopoietic stem cells with the necessary human leukocyte antigen profiles. Esther’s project aims to optimize cell expansion and isolation techniques, in order to increase the availability and utility of humanized DRAGA2 mice in the Gillgrass Lab’s ongoing HIV and TB research program.
Tiffany Ta (McArthur Lab, DBCAD Scholar)
	Antimicrobial resistance (AMR) is a growing global public health threat that affects our ability to treat bacterial infections, undermining modern medicine. By adopting a One-Health perspective, Canada has recognized that the health of humans, animals, and ecosystems are closely interlinked through the spread of AMR. Scientific publications are key for identifying environments, pathogens, hosts, and ARGs involved in the uncontrolled spread of infections. Previous MSc work in the McArthur Lab harnessed machine learning to create a dataset of 204,094 AMR-associated abstracts, as available in PubMed. Using this dataset, Tiffany has designed two pipelines to help analyze and visualize transmission patterns of antibiotic resistant genes (ARGs). Upon analysis, there is a lack of data when exploring various hypotheses (i.e., can we analyze ARG transmission within seafood importation routes?). Due to this limitation in the abstract dataset, Tiffany has replicated deep learning methods using natural language processing tasks to extract terms from 34,609 AMR-associated full-text papers from PubMed Central to help create a comprehensive AMR One Health transmission model.
Wesley Ta (Stokes Lab, DBCAD Scholar)
	Antimicrobial resistance is a rapidly progressing global health challenge caused largely by the overuse of antibiotics. To bolster the antibiotic development pipeline, repurposing existing clinical medicines is a promising approach to treating drug-resistant infections, specifically the exploration of new synergistic chemical-chemical interactions; however, current methods of discovering synergistic pairs of drugs like high-throughput screening are too expensive, time consuming, and cannot be scaled effectively. For example, a pairwise screen of 1,000 molecules amounts to 499,500 unique combinations, while a pairwise screen of 2,000 molecules results in 1,999,000 unique combinations. As such, Wesley’s project will focus on leveraging machine learning approaches to predict novel synergistic pairs of existing clinically approved medicines against multidrug resistant gram-negative bacteria, with a strong focus on carbapenem-resistant Klebsiella pneumoniae and carbapenem-resistant Acinetobacter baumannii. Using a pairwise synergy screen of bioactive molecules, Wesley will develop a deep learning model to predict new drug interactions.
Jennifer Tindall (Coombes Lab, IIDR Scholar)
	Crohn’s Disease is a chronic and relapsing inflammatory bowel disease (IBD) associated with the presence of adherent-invasive E. coli (AIEC). Previously, the Coombes lab identified 12 distinct AIEC lineages (WGS1-12) that emerged over a chronic months-long host-to-host transmission model in mice, chronicling AIEC evolution. Preliminary in vivo data suggests differential colonization of these AIEC strains along the mouse gastrointestinal tract, implicating the involvement of host environmental selection in AIEC infection biology. In this project the WGS strains will be cultured in various host-mimicking environmental conditions to determine how potential host selective pressures most greatly influence AIEC in vivo colonization. This knowledge may lead to a characterization of how AIEC adapts to physiological gut environments, which may inform future therapies targeting AIEC virulence traits.
Aunika Venables (Bowdish Lab, IIDR Scholar)
	Streptococcus pneumoniae is the leading cause of bacterial pneumonia and the risk for acquiring the disease is higher among older adults. Macrophages are essential in killing S. pneumoniae by engulfing the pathogen through a process called phagocytosis. Once bacteria have been engulfed by the macrophage it forms a phagosome, which then combines with an organelle called the lysosome. This phagolysosomal fusion is able to kill the S. pneumoniae. Aging negatively impacts this function; a mechanism that could be associated with impaired killing is the phosphatidylinositol 3 kinase (PI3K) signalling pathway because PI3K is needed for phagosome maturation. The first objective of Aunika’s study is to determine if there is an age-effect of PI3K signalling on macrophage S. pneumoniae killing capability by conducting macrophage killing assays. The study will also examine the role of age and PI3K signalling on phagolysosomal fusion by conducting assays to measure phagosome maturation. This mechanistic insight will aid in identifying possible therapeutic targets to boost macrophage function in aging individuals to better fight pneumonia.