D. Medicine Translational Research [D. Medicine/Translational Research] D-1 Identification of causal genes for nonalcoholic fatty liver disease using multi-omics based single-cell analysis Sung Eun Hong¹, Kyung-Suk Suh², Won Kim³*, Murim Choi¹* ¹Biomedical Sciences, Seoul National University College of Medicine, Seoul 03080, Korea, ²Surgery, Seoul National University College of Medicine, Seoul 03080, Korea, ³Internal medicine, Seoul National University College of Medicine, Seoul Metropolitan Government Boramae Medical Center, Seoul 07061, Korea Background and aims Nonalcoholic fatty liver
disease (NAFLD) is an emerging liver disease associated with metabolic syndrome. Lack of effective treatment drugs urges the discovery of novel therapeutic targets. This study utilizes multi-omics-based single-cell analysis to discover biomarkers and therapeutic targets of NAFLD. Methods Liver biopsy samples obtained from 23 control individuals and 25 NAFLD patients were subjected to single nucleus RNA- sequencing (snRNA-seq). DNA samples obtained from the same participants were genotyped by low coverage whole genome sequencing. snRNA-seq profiles of the NAFLD liver were analyzed using various
bioinformatics tools. Genotype and single-cell gene expression data were integrated to map single-cell expression quantitative trait loci (sc-eQTL). Results A total of 250K cells were detected, including hepatocytes and various non-parenchymal cells. Pseudotime analysis recovered the zonation information in hepatocytes, differentiation pattern in cholangiocytes, and activation process in stellate cells. Differentially expressed genes revealed cell type-specific changes in NAFLD. Multiple sc-eQTL signals in each cell type were detected. Conclusions We present transcriptomic profile of NAFLD in
a single-cell resolution. sc-eQTL analysis identified NAFLD-associated genes and their regulatory variants in relevant cell types. The role of putative regulatory genes and variants will be subjected to functional validation. Identification of causal genes for nonalcoholic fatty liver disease using multi-omics based single-cell analysis 1* Sung Eun Hong , Kyung-Suk Suh , Won Kim , Murim Choi 1 3 2 1. Department of Biomedical Sciences, Seoul National University College of Medicine, Seoul, Republic of Korea 2. Department of Surgery, Seoul National University College of Medicine, Seoul, Republic
of Korea 3. Department of Internal medicine, Seoul National University College of Medicine, Seoul Metropolitan Government Boramae Medical Center, Seoul, Republic of Korea ABSTRACT SAMPLES & METHODS Background and aims Data generation snRNA-seq analysis Nonalcoholic fatty liver disease (NAFLD) is an emerging liver disease associated with metabolic syndrome. Lack of effective treatment drugs urges the discovery of novel therapeutic targets. This study NAFLD (n=25) Cell type 2 utilizes multi-omics-based single-cell analysis to discover biomarkers and therapeutic targets of NAFLD. Control (n=23)
Cell type 3 Methods Matched blood & Liver biopsy sample Alignment Liver biopsy samples obtained from 23 control individuals and 25 NAFLD patients were subjected to QA/QC Normalization single nucleus RNA-sequencing (snRNA-seq). DNA samples obtained from the same participants were Batch correction Cell type 1 genotyped by low coverage whole genome sequencing. snRNA-seq profiles of the NAFLD liver were Clustering analyzed using various bioinformatics tools. Genotype and single-cell gene expression data were integrated to map single-cell expression quantitative trait loci (sc-eQTL). DNA extraction
Single nucleus dissociation Results A total of 250K cells were detected, including hepatocytes and various non-parenchymal cells. Cell-cell Differential Pseudotime analysis recovered the zonation information in hepatocytes, differentiation pattern in Trajectory Gene expression interaction inference cholangiocytes, and activation process in stellate cells. Differentially expressed genes revealed cell type- Low-cov WGS 10X Chromium specific changes in NAFLD. Multiple sc-eQTL signals in each cell type were detected. G eQTL calling A < < Conclusions ACGTTACCGGGAATTAA • Linear regression with NAFLD
Control We present transcriptomic profile of NAFLD in a single-cell resolution. sc-eQTL analysis identified interaction term NAFLD-associated genes and their regulatory variants in relevant cell types. The role of putative • Cell type specific & eGene expression regulatory genes and variants will be subjected to functional validation. Genotype snRNA-seq • Disease specific eQTL eSNP genotype RESULTS & DISCUSSION 1. High resolution map of liver cell populations from NAFLD patients *ctrl = no steatosis, no inflammation *NAFL = simple steatosis without NASH *eNASH = NASH, fibrosis stage 0-1 *aNASH
= NASH, fibrosis stage 2-4 UMAP of liver cell populations obtained from 23 normal individuals and Dotplot of cell type marker genes in each cell type clusters Cell type proportion in each disease groups. Difference in hepatocyte and 25 NAFLD patients. A total of 249k cells and 25k genes were profilled. immune cell proportion between control and advanced NASH is notable. 2. Hepatocytes: zone specific gene expression changes in NAFLD 3. Hepatic stellate cells(HSC) : dynamic process of activation and fibrogenesis is observed from single cell transcriptomics Pseudotime analysis on hepatocytes
Pseudotime analysis on HSC DEG of activated HSC: GO enrichment Periportal Activated /"'-% $POUSPM Periportal Pericentral Lineage 1 Lineage 2 &$. DPOTUJUVFOU Inactivated (SPXUI GBDUPS CJOEJOH 3FTQPOTF UP 5('C Pericentral Quiescent Quiescent #MPPE WFTTFM EFWFMPQNFOU Gene expression Pseudotime Sample origin of cells PV Quiescent /"'-% $POUSPM Pericentral hepatocytes DEG: Gene ontology (GO) enrichment CV NAFLD > Control NAFLD < Control Fraction of cells $FMM BEIFTJPO Lipid metabolic process Fibrinogen complex Activated Liver development Drug metabolic process Hepatic lobule Collagen containing ECM
Cellular response to insulin stimulus Low pt High pt = = 4. Interactions between cell types are altered during NAFLD progression Quiescent Activated 5. sc-NAFLD-eQTL: genetic variants that are associated with cell type NASH (n=19) – ctrl (n=23) Prioritized Ligands (NASH vs ctrl) Predicted Targets specific gene expression changes in NAFLD patients • sc-NAFLD-eQTL= sc-eQTL + NAFLD specific eQTL • Hepatocytes (figure below), cholangiocytes, stellate cells, endothelial cells and immune cells (data not shown) Hepatocyte eQTL NAFLD Hepatocyte eQTL Prioritized Ligands $:1 ' FYQSFTTJPO IFQBUPDZUF $:1
' FYQSFTTJPO #VML 3/" TFR TO3/" TFR (5&Y CVML Significant eGenes (n = 117, hepatocyte) GO enrichment 0 0.005 • Cellular response to DNA damage stimulus • Cell-Cell interaction quantification: CellPhone DB • Ligand prioritization: Nichenet $:1 7 FYQSFTTJPO $:1 7 FYQSFTTJPO • • Intracellular protein transport • Differences in number of significant interactions between • Ligand-receptor interactions that might drive • Nuclear protein-containing complex Regulation of cholesterol storage NASH and control samples gene expression changes between NASH vs • Extrinsic component of mitochondrial inner
membrane control. • NASH > ctrl o Endothelial cell – Stellate cell o Monocyte – Cholangiocyte • Ligand sender: pericentral hepatocyte REFERENCES o Pericentral hepatocyte – Stellate cell o DC – T cells, Macrophage, Monocyte • Receiver: activated stellate cell 1. SA MacParland et al., Single cell RNA sequencing of human liver reveals distinct intrahepatic macrophage populations,, Nat Commun, 2018 • NASH < ctrl 2. N Aizarani et al., A human liver cell atlas reveals heterogeneity and epithelial progenitors, Nature, 2019 o DC – Stellate cell • Prioritized ligands: OCLN, CALM2, ANGPTL3, o Macrophage
– Stellate cell SERPINC1, INHBA, HMGB1 etc 3. P Ramachandran et al., Resolving the fibrotic niche of human liver cirrhosis at single-cell level, Nature, 2019 • Periportal hepatocytes – inactivated Stellate cell 4. K street et al., Slingshot: cell lineage and pseudotime inference for single-cell transcriptomics, BMC Genomics, 2018 5. L Garcia-Alonso et al., Mapping the temporal and spatial dynamics of the human endometrium in vivo and in vitro, Nat Genet, 2021 6. R Borowaeys et al., Nichenet: modeling intercellular communication by linking ligands to target genes, Nat Methods, 2020 [D.
Medicine/Translational Research] D-2 Notch-1 suppressor conjugated Cell membrane-derived nanoparticles promote hypoxic cell–cell packing and suppress angiogenesis as a two-edged sword # Hye-Seon Kim¹ , Young Min Shin¹ , Seyong Chung¹, Dan Bi Park², Sewoom Baek¹, Jeongeun Park¹, Si # Yeong Kim¹, Dae-Hyun Kim³, Se Won Yi², Songhyun Lee¹, Jung Bok Lee⁴, Seong Mi Yu¹, Hyun-Su Ha¹, Chan Hee Lee¹, Mi-Lan Kang²*, Hak-Joon Sung¹* ¹Department of Medical Engineering, Yonsei University College of Medicine, Seoul 03722, Korea, ²TMD LAB Co., Ltd, TMD LAB Co., Ltd, Seoul 04799, Korea, ³Department of
Veterinary Surgery, Chungnam National University College of Veterinary Medicine, Daejeon 34134, Korea, ⁴Department of Biological Science, Sookmyung Women’s University, Seoul 04310, Korea Cell–cell interactions regulate intracellular signaling for tissue regeneration and cancer growth. Because the cell membrane is a key regulator of this process, there is an unmet need to employ a membrane-derived tool to study cell–cell interactions. Hence, cell membrane-derived nanoparticles (CMNPs) were produced using tonsil-derived mesenchymal stem cells (TMSCs) from children owing to their efficient cell
growth and short doubling time. As target cell types, laryngeal cancer cells were compared to bone marrow-derived MSCs (BMSCs) because of their cartilage-damageable and chondrogenic characteristics, respectively. When CMNPs treated in spheroids of these cell types, the exacerbating internal hypoxia of spheroid and robust maintenance of the cell–cell interaction signature were observed during the 7-day culture. Hypoxia represents a common environmental preference of both cell types as opposed to angiogenesis, which is absent in cartilage but is required for cancer growth. Hence, angiogenesis
was inhibited by conjugating the Notch-1 antagonistic aptamer on CMNPs. Consequently, laryngeal cancer growth was suppressed efficiently in contrast to clear improvement of protecting cartilage, as seen in a series of in vitro and in vivo experiments with a xenograft mouse model of laryngeal cancer. This study presents a new perspective for using CMNPs as a previously unexplored therapeutic strategy. Notch-1 suppressor conjugated Cell membrane-derived nanoparticles promote hypoxic cell–cell packing and suppress angiogenesis as a two-edged sword Hye-Seon Kim , Young Min Shin , Seyong Chung ,
Dan Bi Park , Sewoom Baek , Jeongeun Park , Si Yeong Kim , Dae-Hyun Kim , Ӭ 1 Ӭ 2 1 1 3 1 2, Se Won Yi , Songhyun Lee , Jung Bok Lee , Seong Mi Yu , Hyun-Su Ha , Chan Hee Lee , Mi-Lan Kang *, and Hak-Joon Sung * 1 1 1 4 2 1 1, 1 Yonsei University College of Medicine, 2 TMD LAB Co., Ltd., 3 Chungnam National University, and 4 Sookmyung Women’s University INTRODUCTION In this study, we introduce antagonistic Nothch1 aptamer conjugated mesenchymal stem cell (MSC) membrane derived nanoparticle (CMNP) as the platform to execute a two-edged sword function of inducing hypoxic cell–cell packing,
followed by suppressing angiogenesis to promote laryngeal cancer death and chondrogenesis simultaneously. Cells interact with one another to communicate through the mutual transfer of signaling molecules, thereby establishing their mass characteristics cell-cell interaction consequently affects tissue regeneration and tumorigenesis from development to maturation. Cells are packed in a limited space by tightening membrane–membrane contacts, followed by generating oxygen depletion or hypoxia. The Notch-1 antagonistic aptamer (apt) was displayed on CMNPs. Inhibition of Notch signaling inducing
angiogenesis leads to chondropro
