Biology subjects

Thibault, G.

Publications and source records attributed to Thibault, G..

26 records · Page 2Linked to original sources

bioRxiv2019

RESTORE: Robust intEnSiTy nORmalization mEthod for Multiplexed Imaging

Recent advances in multiplexed imaging technologies promise to improve the understanding of the functional states of individual cells and the interactions between the cells in tissues. This often requires compilation of results from multiple samples. However, quantitative integration of information between samples is complicated by variations in staining intensity and background fluorescence that obscure biological variations. Failure to remove these unwanted artefacts will complicate downstream analysis and diminish the value of multiplexed imaging for clinical applications. Here, to compensate for unwanted variations, we automatically identify negative control cells for each marker within the same tissue and use their expression levels to infer background signal level. The intensity profile is normalized by the inferred level of the negative control cells to remove between-sample variation. Using a tissue microarray data and a pair of longitudinal biopsies sample, we demonstrated that the proposed approach can remove unwanted variations effectively and shows robust performance.

systems biology↗

bioRxiv2019

ER stress sensor Ire1 deploys a divergent transcriptional program in response to lipid bilayer stress

Membrane integrity at the endoplasmic reticulum (ER) is tightly regulated and is implicated in metabolic diseases when compromised. Using an engineered sensor that exclusively activates the unfolded protein response (UPR) during aberrant ER membrane lipid composition, we identified pathways beyond lipid metabolism that are necessary to maintain ER integrity in yeast and are conserved in C. elegans. To systematically validate yeast mutants disrupting ER membrane homeostasis, we identified a lipid bilayer stress (LBS) sensing switch in the UPR transducer protein Ire1, located at the interface of the amphipathic and transmembrane helices. Furthermore, transcriptome and chromatin immunoprecipitation (ChIP) analyses pinpoint the UPR as a broad-spectrum compensatory pathway in which LBS and proteotoxic stress-induced UPR deploy divergent transcriptional programs. Together, these findings reveal the UPR program as the sum of two independent stress events and could be exploited for future therapeutic intervention.

cell biology↗

bioRxiv2019

SHIFT: speedy histological-to-immunofluorescent translation of whole slide images enabled by deep learning

Spatially-resolved molecular profiling by immunostaining tissue sections is a key feature in cancer diagnosis, subtyping, and treatment, where it complements routine histopathological evaluation by clarifying tumor phenotypes. In this work, we present a deep learning-based method called speedy histological-to-immunofluorescent translation (SHIFT) which takes histologic images of hematoxylin and eosin-stained tissue as input, then in near-real time returns inferred virtual immunofluorescence (IF) images that accurately depict the underlying distribution of phenotypes without requiring immunostaining of the tissue being tested. We show that deep learning-extracted feature representations of histological images can guide representative sample selection, which improves SHIFT generalizability. SHIFT could serve as an efficient preliminary, auxiliary, or substitute for IF by delivering multiplexed virtual IF images for a fraction of the cost and in a fraction of the time required by nascent multiplexed imaging technologies.\n\nKEY POINTSO_LISpatially-resolved molecular profiling is an essential complement to histopathological evaluation of cancer tissues.\nC_LIO_LIInformation obtained by immunofluorescence imaging is encoded by features in histological images.\nC_LIO_LISHIFT leverages previously unappreciated features in histological images to facilitate virtual immunofluorescence staining.\nC_LIO_LIFeature representations of images guide sample selection, improving model generalizability.\nC_LI

systems biology↗

bioRxiv2019

Predicting Primary Site of Secondary Liver Cancer with a Neural Estimator of Metastatic Origin (NEMO)

Pathologists rely on clinical information, tissue morphology, and sophisticated molecular diagnostics to accurately infer the metastatic origin of secondary liver cancer. In this paper, we introduce a deep learning approach to identify spatially localized regions of cancerous tumor within hematoxylin and eosin stained tissue sections of liver cancer and to generate predictions of the cancers metastatic origin. Our approach achieves an accuracy of 90.2% when classifying metastatic origin of whole slide images into three distinct classes, which compares favorably to an established clinical benchmark by three board-certified pathologists whose accuracies ranged from 90.2% to 94.1% on the same prediction task. This approach illustrates the potential impact of deep learning systems to leverage morphological and structural features of H&E stained tissue sections to guide pathological and clinical determination of the metastatic origin of secondary liver cancers.

cancer biology↗

bioRxiv2019

A workflow for visualizing human cancer biopsies using large-format electron microscopy

Recent developments in large format electron microscopy have enabled generation of images that provide detailed ultrastructural information on normal and diseased cells and tissues. Analyses of these images increase our understanding of cellular organization and interactions and disease-related changes therein. In this manuscript, we describe a workflow for two-dimensional (2D) and three-dimensional (3D) imaging, including both optical and scanning electron microscopy (SEM) methods, that allow pathologists and cancer biology researchers to identify areas of interest from human cancer biopsies. The protocols and mounting strategies described in this workflow are compatible with 2D large format EM mapping, 3D focused ion beam-SEM and serial block face-SEM. The flexibility to use diverse imaging technologies available at most academic institutions makes this workflow useful and applicable for most life science samples. Volumetric analysis of the biopsies studied here revealed morphological, organizational and ultrastructural aspects of the tumor cells and surrounding environment that cannot be revealed by conventional 2D EM imaging. Our results indicate that although 2D EM is still an important tool in many areas of diagnostic pathology, 3D images of ultrastructural relationships between both normal and cancerous cells, in combination with their extracellular matrix, enables cancer researchers and pathologists to better understand the progression of the disease and identify potential therapeutic targets.

cancer biology↗

bioRxiv2018

Glucose increases the lifespan of post-reproductive C. elegans independently of FOXO

Aging is one of the most critical risk factors for the development of metabolic syndromes1. Prominent metabolic diseases, namely type 2 diabetes and insulin resistance, have a strong association with endoplasmic reticulum (ER) stress2. Upon ER stress, the unfolded protein response (UPR) is activated to limit cellular damage by adapting to stress conditions and restoring ER homeostasis3,4. However, adaptive genes upregulated from the UPR tend to decrease with age5. Although stress resistance correlates with increased longevity in a variety of model organisms, the links between the UPR, ER stress resistance, and longevity remain poorly understood. Here, we show that supplementing bacteria diet with 2% glucose (high glucose diet, HGD) in post-reproductive 7-day-old (7DO) C. elegans significantly extend their lifespan in contrast to shortening the lifespan of reproductive 3-day-old (3DO) animals. The insulin-IGF receptor DAF-2 and its immediate downstream target, phosphoinositide 3-kinase (PI3K) AGE-1, were found to be critical factors in extending the lifespan of 7DO worms on HGD. The downstream transcription factor forkhead box O (FOXO) DAF-16 did not extend the lifespan of 7DO worms on HGD in contrast of its previously reported role in modulating lifespan of 3DO worms6. Furthermore, we identified that UPR activation through the highly conserved ATF-6 and PEK-1 sensors significantly extended the longevity of 7DO worms on HGD but not through the IRE-1 sensor. Our results demonstrate that HGD extends lifespan of post-reproductive worms in a UPR-dependent manner but independently of FOXO. Based on these observations, we hypothesise that HGD activates the otherwise quiescent UPR in aged worms to overcome age-related stress and to restore ER homeostasis. In contrast, young adult animals subjected to HGD leads to unresolved ER stress, conversely leading to a deleterious stress response.

cell biology↗

bioRxiv2018

Lipid perturbation-activated IRE-1 modulates autophagy and lipolysis during endoplasmic reticulum stress

Metabolic disorders such as obesity and nonalcoholic fatty liver disease (NAFLD) are emerging diseases that affect the global population. One facet of these disorders is attributed to the disturbance of membrane lipid composition. Perturbation of endoplasmic reticulum (ER) homeostasis through changes in membrane phospholipid composition results in activation of the unfolded protein response (UPR) and causes dramatic translational and transcriptional changes in the cell. To restore cellular homeostasis, the three highly conserved UPR transducers ATF6, IRE1, and PERK mediate cellular processes upon ER stress. The role of the UPR in proteotoxic stress caused by the accumulation of misfolded proteins is well understood but much less so under lipid perturbation-induced UPR (UPRLP). We found that genetically disrupted phosphatidylcholine synthesis in C. elegans causes, lipid perturbation, lipid droplet accumulation, and induced ER stress, all hallmarks of NAFLD. Transcriptional profiling of UPRLP animals shows a unique subset of genes modulated in an UPR-dependent manner that is unaffected by proteotoxic stress (UPRPT). Among these, we identified autophagy genes bec-1 and lgg-1 and the lipid droplet-associated lipase atgl-1 to be modulated by IRE-1. Considering the important role of lipid homeostasis and how its impairment contributes to the pathology of metabolic diseases, our data uncovers the indispensable role of a fully functional UPR program in regulating lipid homeostasis in the face of chronic ER stress and lipotoxicity.

cell biology↗

bioRxiv2017

Lipid perturbation compromises UPR-mediated ER homeostasis as a result of premature degradation of membrane proteins

BackgroundPhospholipid homeostasis in biological membranes is essential to maintain functions of organelles such as the endoplasmic reticulum. Phospholipid perturbation has been associated to non-alcoholic fatty liver disease, obesity and other metabolic disorders. However, in most cases, the biological significance of lipid disequilibrium remains unclear. Previously, we reported that Saccharomyces cerevisiae adapts to lipid disequilibrium by upregulating several protein quality control pathways such as the endoplasmic reticulum-associated degradation (ERAD) pathway and the unfolded protein response (UPR).\n\nResultsSurprisingly, we observed certain ER-resident transmembrane proteins (TPs), which form part of the UPR programme, to be destabilised under lipid perturbation (LP). Among these, Sbh1 was prematurely degraded by fatty acid remodelling and membrane stiffening of the ER. Moreover, the protein translocon subunit Sbh1 is targeted for degradation through its transmembrane domain in an unconventional Doa10-dependent manner.\n\nConclusionPremature removal of key ER-resident TPs might be an underlying cause of chronic ER stress in metabolic disorders.

cell biology↗