Portrait de Julie Hussin

Julie Hussin

Membre académique associé

Professeure adjointe, Université de Montréal

Biographie

Julie Hussin est professeure agrégée à la Faculté de médecine de l'Université de Montréal (UdeM) et chercheuse à l'Institut de cardiologie de Montréal (ICM). Elle est aussi chercheuse-boursière junior 2 du Fonds de recherche du Québec - Santé (FRQS) et responsable des programmes d'études supérieures en bio-informatique à l'UdeM.

Julie Hussin a été formée en génomique statistique et évolutive et possède une vaste expérience dans l'analyse de données multi-omiques issues de vastes cohortes populationnelles. Ses travaux en biologie computationnelle se concentrent principalement sur la génomique médicale et des populations, contribuant à plusieurs avancées méthodologiques dans ces domaines. Son travail interdisciplinaire vise à développer des outils novateurs pour la médecine de précision.

Ses projets de recherche se focalisent sur l'amélioration de la prédiction de risques et la gestion des maladies cardiométaboliques, en particulier dans le cas de l'insuffisance cardiaque. Les méthodologies utilisées dans son groupe intègrent différentes sources de données, notamment des données cliniques, génétiques, transcriptomiques, protéomiques et métabolomiques, pour permettre la découverte de nouvelles informations sur les déterminants biologiques des maladies cardiaques, notamment par des techniques d’apprentissage non supervisé. Dans le contexte de la pandémie de COVID-19, son équipe a également développé des approches d’analyse de données génétiques des virus, pour la surveillance virale et l’étude des interactions hôte-pathogène ainsi que l'évolution virale.

Ses intérêts de recherche comprennent également l'interprétabilité, la généralisation et l'équité des algorithmes d'apprentissage automatique dans la recherche en santé. Julie Hussin s'engage à promouvoir activement une IA équitable, sûre et transparente dans la recherche en santé et s'efforce d'assurer l'inclusivité et la représentativité des individus dans sa recherche, pour que son travail bénéficie à l'ensemble de la population. Elle partage son expertise en donnant plusieurs cours de bio-informatique et de génétique des populations, ainsi que d’apprentissage automatique en génomique. Avant de se joindre à l'Université de Montréal en tant que professeure, elle a été boursière postdoctorale du Human Frontier Science Program au Wellcome Trust Centre for Human Genetics de l'Université d'Oxford (Linacre College) et chercheuse postdoctorale invitée à l'Université McGill.

Étudiants actuels

Alexis Nolin-Lapalme

Doctorat - Université de Montréal

alexis.nolin-lapalme@mila.quebec

Camille Rochefort-Boulanger

Doctorat - Université de Montréal

Co-superviseur⋅e :

rochefoc@mila.quebec

Doctorat - Université de Montréal

cantin.baron@mila.quebec

Doctorat - Université de Montréal

david.hamelin@mila.quebec

Fatima Mostefai

Doctorat - Université de Montréal

fatima.mostefai@mila.quebec

Matthew Scicluna

Doctorat - Université de Montréal

Co-superviseur⋅e :

Sébastien Lemieux

matthew.scicluna@mila.quebec

Maîtrise recherche - Université de Montréal

simon.paquette@mila.quebec

Publications

Refining SARS-CoV-2 Intra-host Variation by Leveraging Large-scale Sequencing Data

Fatima Mostefai

Jean-Christophe Grenier

Raphael Poujol

2024-05-01

bioRxiv (prépublication)

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

2024-02-23

Viruses (publié)

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… (voir plus)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.

2024-01-23

bioRxiv (prépublication)

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

2024-01-11

Genome Biology and Evolution (publié)

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

2023-12-15

bioRxiv (prépublication)

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… (voir plus)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.

2023-11-01

iScience (publié)

Toward computing attributions for dimensionality reduction techniques

Matthew Scicluna

Jean-Christophe Grenier

Raphael Poujol

Sébastien Lemieux

2023-08-03

Bioinformatics Advances (publié)

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

2023-07-13

iScience (publié)

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

2023-01-01

ImmunoInformatics (publié)

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… (voir plus)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.

2022-10-20

bioRxiv (prépublication)

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 … (voir 10 de plus)

John Byrne Fournier

Shelli F. Farhadian

C. D. Dela Cruz

A. Ko

Matthew Hirn

F. Wilson

Akiko Iwasaki

Smita Krishnaswamy

2022-02-28

Nature Biotechnology (published)

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 … (voir 10 de plus)

John Fournier

Shelli Farhadian

Charles S. Dela Cruz

Albert I. Ko

Matthew Hirn

F. Perry Wilson

Akiko Iwasaki

Smita Krishnaswamy

2022-02-28

Nature Biotechnology (publié)