Research Overview
Decoding Stress Responses to Promote Health and Combat Disease
At the Thibault Lab, we take a multi-organism approach to uncover the evolutionarily conserved stress response pathways that underpin both cellular resilience and dysfunction. Our work spans basic mechanistic biology, clinically relevant disease models, and computational tool development, with the goal of advancing both fundamental understanding and therapeutic innovation.
Key Areas of Research
Lipid Regulation and ER Stress
Many human diseases, ranging from cancer and neurodegeneration to autoimmune and metabolic disorders, involve stress in the endoplasmic reticulum (ER). While traditionally associated with proteotoxic stress, ER stress can also stem from lipid bilayer stress (LBS) caused by membrane perturbation. Both stress types activate the unfolded protein response (UPR), a key regulator of cellular adaptation or apoptosis.
Our lab has made seminal contributions in this area, revealing:
How the ER senses LBS, distinct from classical unfolded protein sensing.
That the UPR transcriptional program is tailored to the specific type of ER stress.
Our current work expands these insights into aging biology using C. elegans and mammalian cells. We recently reported that UPR activity declines with age, compromising stress resistance and metabolic function. Our current work focuses on mechanistic explanation for UPR dysfunction in aged cells.
Clinically Relevant Stress Pathways
We are actively translating our fundamental research on cellular stress responses into clinically meaningful contexts.
Our work investigates how ER stress and the UPR impact wound healing, immune modulation, and tissue regeneration. Using in vitro systems, model organisms, and transcriptomic profiling, we explore how stress pathways influence outcomes in conditions such as chronic wounds and age-related degeneration.
Through these efforts, we aim to identify new molecular targets and inform the development of novel therapeutic strategies that harness cellular stress responses for improved patient outcomes.
Integrative Bioinformatics and Systems Tools
As biology becomes increasingly data-rich, our lab is embracing computational approaches to extract meaningful insights from complex datasets.
We are developing pipelines that combine natural language processing, gene interaction mining, and multi-species transcriptomics to better understand how stress responses like the UPR are regulated across different organisms and conditions.
By integrating data from scientific literature, public RNA-seq datasets, and experimental models, we aim to uncover the core gene networks that govern ER stress adaptation—and how they can be precisely modulated in a disease- or context-specific manner.
Research Vision
Our goal is to uncover how stress responses—particularly the UPR—can be selectively tuned to protect against cellular damage without causing systemic side effects. This requires pinpointing key regulators, understanding their context-specific roles, and building computational tools to map their activity across systems.