Portrait of Julie Hussin

Julie Hussin

Associate Academic Member
Associate Professor, Université de Montréal
Research Topics
Computational Biology
Data Mining
Deep Learning
Medical Machine Learning
Multimodal Learning

Biography

Julie Hussin is an associate professor in the Faculty of Medicine at Université de Montréal (UdeM) and a researcher at the Montréal Heart Institute. She is a Junior 2 Research Scholar funded by the Fonds de Recherche du Québec en Santé (FRQS) and chair of the graduate program in bioinformatics at UdeM.

Trained in statistical and evolutionary genomics, Hussin has significant experience in handling multi-omics datasets from large population cohorts. Her work in computational biology is relevant to medical and population genomics, fields in which she has contributed to several methodological advances. Her interdisciplinary work, which aims to develop innovative tools for precision medicine, focuses on improving risk prediction and the management of cardiometabolic disease, particularly heart failure.

Her approaches integrate various data types, such as clinical, genetic, transcriptomic, proteomic and metabolomic data, to uncover new insights into the biological determinants of heart disease, notably through unsupervised learning techniques. In the context of the COVID-19 pandemic, Hussin’s group also led the development of data science algorithms to analyze viral genetic data, aid viral surveillance efforts, and study host-pathogen interactions and viral evolution.

Her work also focuses on the interpretability, generalizability and fairness of machine learning algorithms in health research. Hussin is dedicated to promoting fair, safe and transparent AI in health research, striving for inclusivity and representation to ensure her work benefits all segments of the population. Her expertise also extends to the field of fair, safe and transparent AI for health research. She teaches several undergraduate and graduate courses in computational biology and population genetics, as well as machine learning for genomics. Prior to joining UdeM as a professor, she was a Human Frontier Postdoctoral Fellow at the Wellcome Trust Centre for Human Genetics at the University of Oxford (Linacre College), and a visiting fellow at McGill University.

Current Students

PhD - Université de Montréal
PhD - Université de Montréal
PhD - Université de Montréal
PhD - Université de Montréal
Master's Research - Université de Montréal
PhD - Université de Montréal
Co-supervisor :
PhD - Université de Montréal
Co-supervisor :

Publications

Refining SARS-CoV-2 Intra-host Variation by Leveraging Large-scale Sequencing Data
Fatima Mostefai
Jean-Christophe Grenier
Raphael Poujol
Temperature-dependent Spike-ACE2 interaction of Omicron subvariants is associated with viral transmission
Mehdi Benlarbi
Shilei Ding
Étienne Bélanger
Alexandra Tauzin
Raphael Poujol
Halima Medjahed
Omar El Ferri
Yuxia Bo
Catherine Bourassa
Judith Fafard
Marzena Pazgier
Inès Levade
Cameron Abrams
Marceline Côté
Andrés Finzi
The continued evolution of SARS-CoV-2 requires persistent monitoring of its subvariants. Omicron subvariants are responsible for the vast ma… (see more)jority of SARS-CoV-2 infections worldwide, with XBB and BA.2.86 sublineages representing more than 90% of circulating strains as of January 2024. In this study, we characterized the functional properties of Spike glycoproteins from BA.2.75, CH.1.1, DV.7.1, BA.4/5, BQ.1.1, XBB, XBB.1, XBB.1.16, XBB.1.5, FD.1.1, EG.5.1, HK.3 BA.2.86 and JN.1. We tested their capacity to evade plasma-mediated recognition and neutralization, ACE2 binding, their susceptibility to cold inactivation, Spike processing, as well as the impact of temperature on Spike-ACE2 interaction. We found that compared to the early wild-type (D614G) strain, most Omicron subvariants Spike glycoproteins evolved to escape recognition and neutralization by plasma from individuals who received a fifth dose of bivalent (BA.1 or BA.4/5) mRNA vaccine and improve ACE2 binding, particularly at low temperatures. Moreover, BA.2.86 had the best affinity for ACE2 at all temperatures tested. We found that Omicron subvariants Spike processing is associated with their susceptibility to cold inactivation. Intriguingly, we found that Spike-ACE2 binding at low temperature was significantly associated with growth rates of Omicron subvariants in humans. Overall, we report that Spikes from newly emerged Omicron subvariants are relatively more stable and resistant to plasma-mediated neutralization, present improved affinity for ACE2 which is associated, particularly at low temperatures, with their growth rates.
Intra-Host Evolution Analyses in an Immunosuppressed Patient Supports SARS-CoV-2 Viral Reservoir Hypothesis
Dominique Fournelle
Fatima Mostefai
Elsa Brunet-Ratnasingham
Raphael Poujol
Jean-Christophe Grenier
José Héctor Gálvez
Amélie Pagliuzza
Inès Levade
Sandrine Moreira
Mehdi Benlarbi
Guillaume Beaudoin-Bussières
Gabrielle Gendron-Lepage
Catherine Bourassa
Alexandra Tauzin
Simon Grandjean Lapierre
Nicolas Chomont
Andrés Finzi
Daniel E. Kaufmann
Morgan Craig
Signatures of Co-evolution and Co-regulation in the CYP3A and CYP4F Genes in Humans
Alex Richard-St-Hilaire
Isabel Gamache
Justin Pelletier
Jean-Christophe Grenier
Raphael Poujol
Genetic landscape of an in vivo protein interactome
Savandara Besse
Tatsuya Sakaguchi
Louis Gauthier
Zahra Sahaf
Olivier Péloquin
Lidice Gonzalez
Xavier Castellanos-Girouard
Nazli Koçatug
Chloé Matta
Stephen W. Michnick
Adrian W.R. Serohijos
Gene-metabolite annotation with shortest reactional distance enhances metabolite genome-wide association studies results
Cantin Baron
Sarah Cherkaoui
Sandra Therrien-Laperriere
Yann Ilboudo
Raphael Poujol
Pamela Mehanna
Melanie E. Garrett
Marilyn J. Telen
Allison E. Ashley-Koch
Pablo Bartolucci
John D. Rioux
Guillaume Lettre
Christine Des Rosiers
Matthieu Ruiz
Studies combining metabolomics and genetics, known as metabolite genome-wide association studies (mGWAS), have provided valuable insights in… (see more)to our understanding of the genetic control of metabolite levels. However, the biological interpretation of these associations remains challenging due to a lack of existing tools to annotate mGWAS gene-metabolite pairs beyond the use of conservative statistical significance threshold. Here, we computed the shortest reactional distance (SRD) based on the curated knowledge of the KEGG database to explore its utility in enhancing the biological interpretation of results from three independent mGWAS, including a case study on sickle cell disease patients. Results show that, in reported mGWAS pairs, there is an excess of small SRD values and that SRD values and p-values significantly correlate, even beyond the standard conservative thresholds. The added-value of SRD annotation is shown for identification of potential false negative hits, exemplified by the finding of gene-metabolite associations with SRD ≤1 that did not reach standard genome-wide significance cut-off. The wider use of this statistic as an mGWAS annotation would prevent the exclusion of biologically relevant associations and can also identify errors or gaps in current metabolic pathway databases. Our findings highlight the SRD metric as an objective, quantitative and easy-to-compute annotation for gene-metabolite pairs that can be used to integrate statistical evidence to biological networks.
Toward computing attributions for dimensionality reduction techniques
Matthew Scicluna
Jean-Christophe Grenier
Raphael Poujol
Selection for immune evasion in SARS-CoV-2 revealed by high-resolution epitope mapping and sequence analysis
Arnaud N’Guessan
Senthilkumar Kailasam
Fatima Mostefai
Raphael Poujol
Jean-Christophe Grenier
Nailya Ismailova
Paola Contini
Raffaele De Palma
Carsten Haber
Volker Stadler
Guillaume Bourque
B. Jesse Shapiro
Jörg H. Fritz
Ciriaco A. Piccirillo
The race to understand immunopathology in COVID-19: Perspectives on the impact of quantitative approaches to understand within-host interactions
Sonia Gazeau
Xiaoyan Deng
Hsu Kiang Ooi
Fatima Mostefai
Jane Heffernan
Adrianne L. Jenner
Morgan Craig
Intra-host viral populations of SARS-CoV-2 in immunosuppressed patients with hematologic cancers
Dominique Fournelle
Fatima Mostefai
Elsa Brunet-Ratnasingham
Raphael Poujol
Jean-Christophe Grenier
José Héctor Gálvez
Amélie Pagliuzza
Inès Levade
Sandrine Moreira
Simon Grandjean Lapierre
Nicolas Chomont
Daniel E. Kaufmann
Morgan Craig
Throughout the SARS-CoV-2 pandemic, several variants of concern (VOC) have been identified, many of which share recurrent mutations in the s… (see more)pike protein’s receptor binding domain (RBD). This region coincides with known epitopes and can therefore have an impact on immune escape. Protracted infections in immunosuppressed patients have been hypothesized to lead to an enrichment of such mutations and therefore drive evolution towards VOCs. Here, we show that immunosuppressed patients with hematologic cancers develop distinct populations with immune escape mutations throughout the course of their infection. Notably, by investigating the co-occurrence of substitutions on individual sequencing reads in the RBD, we found quasispecies harboring mutations that confer resistance to known monoclonal antibodies (mAbs) such as S:E484K and S:E484A. Furthermore, we provide the first evidence for a viral reservoir based on intra-host phylogenetics. Our results on viral reservoirs can shed light on protracted infections interspersed with periods where the virus is undetectable as well as an alternative explanation for some long-COVID cases. Our findings also highlight that protracted infections should be treated with combination therapies rather than by a single mAbs to clear pre-existing resistant mutations.
Multiscale PHATE identifies multimodal signatures of COVID-19
Manik Kuchroo
Je-chun Huang
Patrick W. Wong
Jean-Christophe Grenier
Dennis L. Shung
Alexander Tong
C. Lucas
J. Klein
Daniel B. Burkhardt
Scott Gigante
Abhinav Godavarthi
Bastian Rieck
Benjamin Israelow
Michael Simonov
Tianyang Mao
Ji Eun Oh
Julio Silva
Takehiro Takahashi
C. Odio
Arnau Casanovas‐massana … (see 10 more)
John Byrne Fournier
Shelli F. Farhadian
C. D. Dela Cruz
A. Ko
Matthew Hirn
F. Wilson
Akiko Iwasaki
Smita Krishnaswamy
Multiscale PHATE identifies multimodal signatures of COVID-19
Manik Kuchroo
Je-chun Huang
Patrick Wong
Jean-Christophe Grenier
Dennis Shung
Alexander Tong
Carolina Lucas
Jon Klein
Daniel B. Burkhardt
Scott Gigante
Abhinav Godavarthi
Bastian Rieck
Benjamin Israelow
Michael Simonov
Tianyang Mao
Ji Eun Oh
Julio Silva
Takehiro Takahashi
Camila D. Odio
Arnau Casanovas-Massana … (see 10 more)
John Fournier
Shelli Farhadian
Charles S. Dela Cruz
Albert I. Ko
Matthew Hirn
F. Perry Wilson
Akiko Iwasaki
Smita Krishnaswamy