551
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Affiliation(s)
- Sungjin Ko
- Department of Pathology, University of Pittsburgh School of Medicine and University of Pittsburgh Medical Center, Pittsburgh, PA, USA
| | - Satdarshan P Monga
- Department of Pathology, University of Pittsburgh School of Medicine and University of Pittsburgh Medical Center, Pittsburgh, PA, USA,Pittsburgh Liver Research CenterUniversity of Pittsburgh School of Medicine and University of Pittsburgh Medical Center, Pittsburgh, PA, USA,Department of Medicine, University of Pittsburgh School of Medicine and University of Pittsburgh Medical Center, Pittsburgh, PA, USA
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552
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Lin Q, Deng D, Song X, Dai B, Yang X, Luo Q, Zhang Z. Self-Assembled "Off/On" Nanopomegranate for In Vivo Photoacoustic and Fluorescence Imaging: Strategic Arrangement of Kupffer Cells in Mouse Hepatic Lobules. ACS NANO 2019; 13:1526-1537. [PMID: 30716272 DOI: 10.1021/acsnano.8b07283] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/09/2023]
Abstract
Kupffer cells (KCs), potent scavenger cells located in hepatic sinusoids, constantly phagocytize and degrade foreign materials to maintain metabolism and clearance. Understanding the strategic KC arrangement which links to their spatial location and function in hepatic lobules, the basic functional unit in the liver, is highly valuable for characterizing liver function. However, selectively labeling KCs and characterizing their function in vivo remains challenging. Herein, a fast self-assembled pomegranate structure-like nanoparticle with "nanopomegranate seeds" of dye aggregates has been developed, which has dual-modality "off/on" capability. This nanopomegranate shows good photostability, a high extinction coefficient, a high KC labeling efficiency (98.8%), and better visualization of KC morphology than commercial FluoSpheres. In vivo photoacoustic (PA) and fluorescence imaging consistently visualize that KCs are strategically distributed along the central vein (CV)-portal triad (PT) axis in each liver lobule: more and larger KCs exist in areas closer to the PTs. The high-resolution PA quantitative data further revealed that the density of KCs was linearly dependent on the r n/ rmax ratio (their relative location along the CV-PT axis) ( R2 = 0.7513), and the KC density at the outermost layer is almost 246-fold that at the innermost layer (each layer is 8 μm). Notably, the phagocytic ability of KCs located in layers with r n/ rmax ratios of 0.167-0.3 varies in a zigzag pattern, as evidenced by their different PA intensities. Additionally, the fluorescence imaging quantitation suggests similar fluorescence activation of nanopomegranate in KCs. Nanopomegranates combined with dual-modality imaging reveal the strategic arrangement of KCs in vivo, greatly extending our understanding of liver physiology.
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Affiliation(s)
- Qiaoya Lin
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics , Huazhong University of Science and Technology , Wuhan , Hubei 430074 , China
- MoE Key Laboratory for Biomedical Photonics, Collaborative Innovation Center for Biomedical Engineering, School of Engineering Sciences , Huazhong University of Science and Technology , Wuhan , Hubei , 430074 , China
| | - Deqiang Deng
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics , Huazhong University of Science and Technology , Wuhan , Hubei 430074 , China
- MoE Key Laboratory for Biomedical Photonics, Collaborative Innovation Center for Biomedical Engineering, School of Engineering Sciences , Huazhong University of Science and Technology , Wuhan , Hubei , 430074 , China
| | - Xianlin Song
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics , Huazhong University of Science and Technology , Wuhan , Hubei 430074 , China
- MoE Key Laboratory for Biomedical Photonics, Collaborative Innovation Center for Biomedical Engineering, School of Engineering Sciences , Huazhong University of Science and Technology , Wuhan , Hubei , 430074 , China
| | - Bolei Dai
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics , Huazhong University of Science and Technology , Wuhan , Hubei 430074 , China
- MoE Key Laboratory for Biomedical Photonics, Collaborative Innovation Center for Biomedical Engineering, School of Engineering Sciences , Huazhong University of Science and Technology , Wuhan , Hubei , 430074 , China
| | - Xiaoquan Yang
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics , Huazhong University of Science and Technology , Wuhan , Hubei 430074 , China
- MoE Key Laboratory for Biomedical Photonics, Collaborative Innovation Center for Biomedical Engineering, School of Engineering Sciences , Huazhong University of Science and Technology , Wuhan , Hubei , 430074 , China
| | - Qingming Luo
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics , Huazhong University of Science and Technology , Wuhan , Hubei 430074 , China
- MoE Key Laboratory for Biomedical Photonics, Collaborative Innovation Center for Biomedical Engineering, School of Engineering Sciences , Huazhong University of Science and Technology , Wuhan , Hubei , 430074 , China
| | - Zhihong Zhang
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics , Huazhong University of Science and Technology , Wuhan , Hubei 430074 , China
- MoE Key Laboratory for Biomedical Photonics, Collaborative Innovation Center for Biomedical Engineering, School of Engineering Sciences , Huazhong University of Science and Technology , Wuhan , Hubei , 430074 , China
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553
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Donato MT, Tolosa L. Stem-cell derived hepatocyte-like cells for the assessment of drug-induced liver injury. Differentiation 2019; 106:15-22. [PMID: 30844688 DOI: 10.1016/j.diff.2019.02.004] [Citation(s) in RCA: 22] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2018] [Revised: 01/30/2019] [Accepted: 02/14/2019] [Indexed: 12/26/2022]
Abstract
Drug-induced liver injury is a major cause of drug discovery failure in clinical trials and a leading cause of liver disease. Current preclinical drug testing does not predict hepatotoxicity which highlights the importance of developing highly predictive cell-based models. The use of stem cell technology and differentiation into hepatocyte-like cells (HLCs) could provide a stable source of hepatocytes for multiple applications, including drug screening. HLCs derived from both embryonic and induced pluripotent stem cells have been used to accurately predict hepatotoxicity as well as to test individual-specific toxicity. Although there are still many limitations, mainly related to the lack of fully maturity of the HLCs derived from pluripotent stem cells, they could provide a relative unlimited and consistent supply of cells with stable phenotype, that could be obtained from different donors, enabling the generation of a library of HLCs representative of the variability of human population.
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Affiliation(s)
- M Teresa Donato
- Unidad de Hepatología Experimental, Instituto de Investigación Sanitaria La Fe, Valencia, 46026, Spain; Departamento de Bioquímica y Biología Molecular, Facultad de Medicina y Odontología, Universidad de Valencia, Valencia, 46010, Spain.
| | - Laia Tolosa
- Unidad de Hepatología Experimental, Instituto de Investigación Sanitaria La Fe, Valencia, 46026, Spain
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554
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Han X, Wang Y, Pu W, Huang X, Qiu L, Li Y, Yu W, Zhao H, Liu X, He L, Zhang L, Ji Y, Lu J, Lui KO, Zhou B. Lineage Tracing Reveals the Bipotency of SOX9 + Hepatocytes during Liver Regeneration. Stem Cell Reports 2019; 12:624-638. [PMID: 30773487 PMCID: PMC6409431 DOI: 10.1016/j.stemcr.2019.01.010] [Citation(s) in RCA: 65] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2018] [Revised: 01/14/2019] [Accepted: 01/16/2019] [Indexed: 02/07/2023] Open
Abstract
Elucidation of the role of different cell lineages in the liver could offer avenues to drive liver regeneration. Previous studies showed that SOX9+ hepatocytes can differentiate into ductal cells after liver injuries. It is unclear whether SOX9+ hepatocytes are uni- or bipotent progenitors at a single-cell level during liver injury. Here, we developed a genetic tracing system to delineate the lineage potential of SOX9+ hepatocytes during liver homeostasis and regeneration. Fate-mapping data showed that these SOX9+ hepatocytes respond specifically to different liver injuries, with some contributing to a substantial number of ductal cells. Clonal analysis demonstrated that a single SOX9+ hepatocyte gives rise to both hepatocytes and ductal cells after liver injury. This study provides direct evidence that SOX9+ hepatocytes can serve as bipotent progenitors after liver injury, producing both hepatocytes and ductal cells for liver repair and regeneration. SOX9+ hepatocytes respond distinctly to different liver injuries Generation of a Confetti reporter responsive to dual recombinases SOX9+ hepatocytes can serve as bipotent progenitors after liver injury
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Affiliation(s)
- Ximeng Han
- The State Key Laboratory of Cell Biology, CAS Center for Excellence in Molecular Cell Science, Shanghai Institute of Biochemistry and Cell Biology, Chinese Academy of Sciences, University of Chinese Academy of Sciences, Shanghai 200031, China; Key Laboratory of Nutrition and Metabolism, Institute of Nutrition and Health, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, University of Chinese Academy of Sciences, Shanghai 200031, China; School of Life Science and Technology, ShanghaiTech University, Shanghai 201210, China
| | - Yue Wang
- The State Key Laboratory of Cell Biology, CAS Center for Excellence in Molecular Cell Science, Shanghai Institute of Biochemistry and Cell Biology, Chinese Academy of Sciences, University of Chinese Academy of Sciences, Shanghai 200031, China; Key Laboratory of Nutrition and Metabolism, Institute of Nutrition and Health, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, University of Chinese Academy of Sciences, Shanghai 200031, China
| | - Wenjuan Pu
- The State Key Laboratory of Cell Biology, CAS Center for Excellence in Molecular Cell Science, Shanghai Institute of Biochemistry and Cell Biology, Chinese Academy of Sciences, University of Chinese Academy of Sciences, Shanghai 200031, China; Key Laboratory of Nutrition and Metabolism, Institute of Nutrition and Health, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, University of Chinese Academy of Sciences, Shanghai 200031, China
| | - Xiuzhen Huang
- The State Key Laboratory of Cell Biology, CAS Center for Excellence in Molecular Cell Science, Shanghai Institute of Biochemistry and Cell Biology, Chinese Academy of Sciences, University of Chinese Academy of Sciences, Shanghai 200031, China; Key Laboratory of Nutrition and Metabolism, Institute of Nutrition and Health, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, University of Chinese Academy of Sciences, Shanghai 200031, China
| | - Lin Qiu
- Key Laboratory of Nutrition and Metabolism, Institute of Nutrition and Health, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, University of Chinese Academy of Sciences, Shanghai 200031, China
| | - Yan Li
- The State Key Laboratory of Cell Biology, CAS Center for Excellence in Molecular Cell Science, Shanghai Institute of Biochemistry and Cell Biology, Chinese Academy of Sciences, University of Chinese Academy of Sciences, Shanghai 200031, China; Key Laboratory of Nutrition and Metabolism, Institute of Nutrition and Health, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, University of Chinese Academy of Sciences, Shanghai 200031, China
| | - Wei Yu
- The State Key Laboratory of Cell Biology, CAS Center for Excellence in Molecular Cell Science, Shanghai Institute of Biochemistry and Cell Biology, Chinese Academy of Sciences, University of Chinese Academy of Sciences, Shanghai 200031, China; Key Laboratory of Nutrition and Metabolism, Institute of Nutrition and Health, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, University of Chinese Academy of Sciences, Shanghai 200031, China
| | - Huan Zhao
- The State Key Laboratory of Cell Biology, CAS Center for Excellence in Molecular Cell Science, Shanghai Institute of Biochemistry and Cell Biology, Chinese Academy of Sciences, University of Chinese Academy of Sciences, Shanghai 200031, China; Key Laboratory of Nutrition and Metabolism, Institute of Nutrition and Health, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, University of Chinese Academy of Sciences, Shanghai 200031, China
| | - Xiuxiu Liu
- The State Key Laboratory of Cell Biology, CAS Center for Excellence in Molecular Cell Science, Shanghai Institute of Biochemistry and Cell Biology, Chinese Academy of Sciences, University of Chinese Academy of Sciences, Shanghai 200031, China
| | - Lingjuan He
- The State Key Laboratory of Cell Biology, CAS Center for Excellence in Molecular Cell Science, Shanghai Institute of Biochemistry and Cell Biology, Chinese Academy of Sciences, University of Chinese Academy of Sciences, Shanghai 200031, China; Key Laboratory of Nutrition and Metabolism, Institute of Nutrition and Health, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, University of Chinese Academy of Sciences, Shanghai 200031, China
| | - Libo Zhang
- The State Key Laboratory of Cell Biology, CAS Center for Excellence in Molecular Cell Science, Shanghai Institute of Biochemistry and Cell Biology, Chinese Academy of Sciences, University of Chinese Academy of Sciences, Shanghai 200031, China; Key Laboratory of Nutrition and Metabolism, Institute of Nutrition and Health, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, University of Chinese Academy of Sciences, Shanghai 200031, China
| | - Yong Ji
- The Collaborative Innovation Center for Cardiovascular Disease Translational Medicine, Nanjing Medical University, Nanjing 211100, China; Key Laboratory of Cardiovascular and Cerebrovascular Medicine, Nanjing Medical University, Nanjing 211100, China
| | - Jie Lu
- Department of Gastroenterology, Shanghai 10th People's Hospital, Tongji University School of Medicine, Shanghai 200072, China.
| | - Kathy O Lui
- Department of Chemical Pathology; Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong SAR 999077, China
| | - Bin Zhou
- The State Key Laboratory of Cell Biology, CAS Center for Excellence in Molecular Cell Science, Shanghai Institute of Biochemistry and Cell Biology, Chinese Academy of Sciences, University of Chinese Academy of Sciences, Shanghai 200031, China; Key Laboratory of Nutrition and Metabolism, Institute of Nutrition and Health, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, University of Chinese Academy of Sciences, Shanghai 200031, China; School of Life Science and Technology, ShanghaiTech University, Shanghai 201210, China; The Collaborative Innovation Center for Cardiovascular Disease Translational Medicine, Nanjing Medical University, Nanjing 211100, China; Key Laboratory of Regenerative Medicine of Ministry of Education, Institute of Aging and Regenerative Medicine, Jinan University, Guangzhou 510632, China; Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing 100101, China.
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555
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Sakamoto S, Mae SI, Osafune K, Okada C, Kabai R, Watanabe A. [Dissecting early development of the kidney by single cell transcriptomics]. Nihon Yakurigaku Zasshi 2019; 153:61-66. [PMID: 30745515 DOI: 10.1254/fpj.153.61] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/27/2022]
Abstract
Each of the billions of the cells in our body exhibits their identity with unique gene expression profile. Recent advances in single cell transcriptomics enable to conduct cell taxonomy identifying new cell types and to re-arrange cells in order of pseudo-time course describing differentiation status of each cell. Even though the cost is still high, the single cell transcriptomics now becomes one of the conventional assays. We have applied the single cell gene expression analysis to dissect human development. In this article, we show our recent progress on a study describing early development of the kidney using human iPS cells by the single cell transcriptomics.
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Affiliation(s)
- Satoko Sakamoto
- Department of Life Science Frontiers, Center for iPS Cell Research and Application, Kyoto University
| | - Shin-Ichi Mae
- Department of Cell Growth and Differentiation, Center for iPS Cell Research and Application, Kyoto University
| | - Kenji Osafune
- Department of Cell Growth and Differentiation, Center for iPS Cell Research and Application, Kyoto University
| | - Chihiro Okada
- Department of Life Science Frontiers, Center for iPS Cell Research and Application, Kyoto University
| | - Ryotaro Kabai
- Department of Life Science Frontiers, Center for iPS Cell Research and Application, Kyoto University
| | - Akira Watanabe
- Department of Life Science Frontiers, Center for iPS Cell Research and Application, Kyoto University
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556
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Senni N, Savall M, Cabrerizo Granados D, Alves-Guerra MC, Sartor C, Lagoutte I, Gougelet A, Terris B, Gilgenkrantz H, Perret C, Colnot S, Bossard P. β-catenin-activated hepatocellular carcinomas are addicted to fatty acids. Gut 2019; 68:322-334. [PMID: 29650531 DOI: 10.1136/gutjnl-2017-315448] [Citation(s) in RCA: 93] [Impact Index Per Article: 18.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/11/2017] [Revised: 03/26/2018] [Accepted: 04/01/2018] [Indexed: 12/26/2022]
Abstract
OBJECTIVES CTNNB1-mutated hepatocellular carcinomas (HCCs) constitute a major part of human HCC and are largely inaccessible to target therapy. Yet, little is known about the metabolic reprogramming induced by β-catenin oncogenic activation in the liver. We aimed to decipher such reprogramming and assess whether it may represent a new avenue for targeted therapy of CTNNB1-mutated HCC. DESIGN We used mice with hepatocyte-specific oncogenic activation of β-catenin to evaluate metabolic reprogramming using metabolic fluxes on tumourous explants and primary hepatocytes. We assess the role of Pparα in knock-out mice and analysed the consequences of fatty acid oxidation (FAO) using etomoxir. We explored the expression of the FAO pathway in an annotated human HCC dataset. RESULTS β-catenin-activated HCC were not glycolytic but intensively oxidised fatty acids. We found that Pparα is a β-catenin target involved in FAO metabolic reprograming. Deletion of Pparα was sufficient to block the initiation and progression of β-catenin-dependent HCC development. FAO was also enriched in human CTNNB1-mutated HCC, under the control of the transcription factor PPARα. CONCLUSIONS FAO induced by β-catenin oncogenic activation in the liver is the driving force of the β-catenin-induced HCC. Inhibiting FAO by genetic and pharmacological approaches blocks HCC development, showing that inhibition of FAO is a suitable therapeutic approach for CTNNB1-mutated HCC.
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Affiliation(s)
- Nadia Senni
- INSERM, U1016, Institut Cochin, Paris, France.,CNRS, UMR8104, Paris, France.,Université Paris Descartes, Sorbonne Paris Cité, Paris, France.,Equipe Labellisée Ligne Nationale Contre le Cancer, Paris, France
| | - Mathilde Savall
- INSERM, U1016, Institut Cochin, Paris, France.,CNRS, UMR8104, Paris, France.,Université Paris Descartes, Sorbonne Paris Cité, Paris, France.,Equipe Labellisée Ligne Nationale Contre le Cancer, Paris, France
| | - David Cabrerizo Granados
- INSERM, U1016, Institut Cochin, Paris, France.,CNRS, UMR8104, Paris, France.,Université Paris Descartes, Sorbonne Paris Cité, Paris, France.,Equipe Labellisée Ligne Nationale Contre le Cancer, Paris, France
| | - Marie-Clotilde Alves-Guerra
- INSERM, U1016, Institut Cochin, Paris, France.,CNRS, UMR8104, Paris, France.,Université Paris Descartes, Sorbonne Paris Cité, Paris, France.,Equipe Labellisée Ligne Nationale Contre le Cancer, Paris, France
| | - Chiara Sartor
- INSERM, U1016, Institut Cochin, Paris, France.,CNRS, UMR8104, Paris, France.,Université Paris Descartes, Sorbonne Paris Cité, Paris, France.,Equipe Labellisée Ligne Nationale Contre le Cancer, Paris, France
| | - Isabelle Lagoutte
- INSERM, U1016, Institut Cochin, Paris, France.,CNRS, UMR8104, Paris, France.,Université Paris Descartes, Sorbonne Paris Cité, Paris, France
| | - Angélique Gougelet
- INSERM, U1016, Institut Cochin, Paris, France.,CNRS, UMR8104, Paris, France.,Université Paris Descartes, Sorbonne Paris Cité, Paris, France.,Equipe Labellisée Ligne Nationale Contre le Cancer, Paris, France
| | - Benoit Terris
- INSERM, U1016, Institut Cochin, Paris, France.,CNRS, UMR8104, Paris, France.,Université Paris Descartes, Sorbonne Paris Cité, Paris, France.,Equipe Labellisée Ligne Nationale Contre le Cancer, Paris, France.,Pathology Department, APHP, Hôpitaux Universitaires Paris Centre, Hôpital Cochin, Paris, France
| | - Hélène Gilgenkrantz
- INSERM, U1016, Institut Cochin, Paris, France.,CNRS, UMR8104, Paris, France.,Université Paris Descartes, Sorbonne Paris Cité, Paris, France.,Equipe Labellisée Ligne Nationale Contre le Cancer, Paris, France
| | - Christine Perret
- INSERM, U1016, Institut Cochin, Paris, France.,CNRS, UMR8104, Paris, France.,Université Paris Descartes, Sorbonne Paris Cité, Paris, France.,Equipe Labellisée Ligne Nationale Contre le Cancer, Paris, France
| | - Sabine Colnot
- INSERM, U1016, Institut Cochin, Paris, France.,CNRS, UMR8104, Paris, France.,Université Paris Descartes, Sorbonne Paris Cité, Paris, France.,Equipe Labellisée Ligne Nationale Contre le Cancer, Paris, France
| | - Pascale Bossard
- INSERM, U1016, Institut Cochin, Paris, France.,CNRS, UMR8104, Paris, France.,Université Paris Descartes, Sorbonne Paris Cité, Paris, France.,Equipe Labellisée Ligne Nationale Contre le Cancer, Paris, France
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557
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Fujii M, Clevers H, Sato T. Modeling Human Digestive Diseases With CRISPR-Cas9-Modified Organoids. Gastroenterology 2019; 156:562-576. [PMID: 30476497 DOI: 10.1053/j.gastro.2018.11.048] [Citation(s) in RCA: 89] [Impact Index Per Article: 17.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/11/2018] [Revised: 11/10/2018] [Accepted: 11/14/2018] [Indexed: 02/06/2023]
Abstract
Insights into the stem cell niche have allowed researchers to cultivate adult tissue stem cells as organoids that display structural and phenotypic features of healthy and diseased epithelial tissues. Organoids derived from patients' tissues are used as models of disease and to test drugs. CRISPR-Cas9 technology can be used to genetically engineer organoids for studies of monogenic diseases and cancer. We review the derivation of organoids from human gastrointestinal tissues and how CRISPR-Cas9 technology can be used to study these organoids. We discuss burgeoning technologies that are broadening our understanding of diseases of the digestive system.
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Affiliation(s)
- Masayuki Fujii
- Department of Gastroenterology, Keio University School of Medicine, Tokyo, Japan
| | - Hans Clevers
- Hubrecht Institute, University Medical Center Utrecht and Princess Maxima Center, Utrecht, The Netherlands
| | - Toshiro Sato
- Department of Gastroenterology, Keio University School of Medicine, Tokyo, Japan.
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558
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Identification of Enteroendocrine Regulators by Real-Time Single-Cell Differentiation Mapping. Cell 2019; 176:1158-1173.e16. [PMID: 30712869 DOI: 10.1016/j.cell.2018.12.029] [Citation(s) in RCA: 190] [Impact Index Per Article: 38.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2018] [Revised: 09/21/2018] [Accepted: 12/17/2018] [Indexed: 01/22/2023]
Abstract
Homeostatic regulation of the intestinal enteroendocrine lineage hierarchy is a poorly understood process. We resolved transcriptional changes during enteroendocrine differentiation in real time at single-cell level using a novel knockin allele of Neurog3, the master regulator gene briefly expressed at the onset of enteroendocrine specification. A bi-fluorescent reporter, Neurog3Chrono, measures time from the onset of enteroendocrine differentiation and enables precise positioning of single-cell transcriptomes along an absolute time axis. This approach yielded a definitive description of the enteroendocrine hierarchy and its sub-lineages, uncovered differential kinetics between sub-lineages, and revealed time-dependent hormonal plasticity in enterochromaffin and L cells. The time-resolved map of transcriptional changes predicted multiple novel molecular regulators. Nine of these were validated by conditional knockout in mice or CRISPR modification in intestinal organoids. Six novel candidate regulators (Sox4, Rfx6, Tox3, Myt1, Runx1t1, and Zcchc12) yielded specific enteroendocrine phenotypes. Our time-resolved single-cell transcriptional map presents a rich resource to unravel enteroendocrine differentiation.
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559
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Allele-specific RNA imaging shows that allelic imbalances can arise in tissues through transcriptional bursting. PLoS Genet 2019; 15:e1007874. [PMID: 30625149 PMCID: PMC6342324 DOI: 10.1371/journal.pgen.1007874] [Citation(s) in RCA: 22] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2018] [Revised: 01/22/2019] [Accepted: 12/04/2018] [Indexed: 12/03/2022] Open
Abstract
Extensive cell-to-cell variation exists even among putatively identical cells, and there is great interest in understanding how the properties of transcription relate to this heterogeneity. Differential expression from the two gene copies in diploid cells could potentially contribute, yet our ability to measure from which gene copy individual RNAs originated remains limited, particularly in the context of tissues. Here, we demonstrate quantitative, single molecule allele-specific RNA FISH adapted for use on tissue sections, allowing us to determine the chromosome of origin of individual RNA molecules in formaldehyde-fixed tissues. We used this method to visualize the allele-specific expression of Xist and multiple autosomal genes in mouse kidney. By combining these data with mathematical modeling, we evaluated models for allele-specific heterogeneity, in particular demonstrating that apparent expression from only one of the alleles in single cells can arise as a consequence of low-level mRNA abundance and transcriptional bursting. In mammals, most cells of the body contain two genetic datasets: one from the mother and one from the father, and—in theory—these two sets of information could contribute equally to produce the molecules in a given cell. In practice, however, this is not always the case, which can have dramatic implications for many traits, including visible features (such as fur color) and even disease outcomes. However, it remains difficult to measure the parental origin of individual molecules in a given cell and thus to assess what processes lead to an imbalance of the maternal and paternal contribution. We adapted a microscopy technique—called allele-specific single molecule RNA FISH—that uses a combination of fluorescent tags to specifically label one type of molecule, RNA, depending on its origin, for use in mouse kidney sections. Focusing on RNAs that were previously reported to show imbalance, we performed measurements and combined these with mathematical modeling to quantify imbalance in tissues and explain how these can arise. We found that we could recapitulate the observed imbalances using models that only take into account the random processes that produce RNA, without the need to invoke special regulatory mechanisms to create unequal contributions.
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560
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Adler M, Korem Kohanim Y, Tendler A, Mayo A, Alon U. Continuum of Gene-Expression Profiles Provides Spatial Division of Labor within a Differentiated Cell Type. Cell Syst 2019; 8:43-52.e5. [DOI: 10.1016/j.cels.2018.12.008] [Citation(s) in RCA: 34] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2018] [Revised: 11/01/2018] [Accepted: 12/12/2018] [Indexed: 02/07/2023]
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561
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Saito S, Lin YC, Nakamura Y, Eckner R, Wuputra K, Kuo KK, Lin CS, Yokoyama KK. Potential application of cell reprogramming techniques for cancer research. Cell Mol Life Sci 2019; 76:45-65. [PMID: 30283976 PMCID: PMC6326983 DOI: 10.1007/s00018-018-2924-7] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2018] [Revised: 09/15/2018] [Accepted: 09/19/2018] [Indexed: 02/07/2023]
Abstract
The ability to control the transition from an undifferentiated stem cell to a specific cell fate is one of the key techniques that are required for the application of interventional technologies to regenerative medicine and the treatment of tumors and metastases and of neurodegenerative diseases. Reprogramming technologies, which include somatic cell nuclear transfer, induced pluripotent stem cells, and the direct reprogramming of specific cell lineages, have the potential to alter cell plasticity in translational medicine for cancer treatment. The characterization of cancer stem cells (CSCs), the identification of oncogene and tumor suppressor genes for CSCs, and the epigenetic study of CSCs and their microenvironments are important topics. This review summarizes the application of cell reprogramming technologies to cancer modeling and treatment and discusses possible obstacles, such as genetic and epigenetic alterations in cancer cells, as well as the strategies that can be used to overcome these obstacles to cancer research.
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Affiliation(s)
- Shigeo Saito
- Saito Laboratory of Cell Technology, Yaita, Tochigi, 329-1571, Japan
- College of Engineering, Nihon University, Koriyama, Fukushima, 963-8642, Japan
| | - Ying-Chu Lin
- School of Dentistry, College of Dental Medicine, Kaohsiung Medical University, Kaohsiung, 807, Taiwan
| | - Yukio Nakamura
- Cell Engineering Division, RIKEN BioResource Center, Tsukuba, Ibaraki, 305-0074, Japan
| | - Richard Eckner
- Department of Biochemistry and Molecular Biology, Rutgers, New Jersey Medical School-Rutgers, The State University of New Jersey, Newark, NJ, 07101, USA
| | - Kenly Wuputra
- Graduate Institute of Medicine, College of Medicine, Kaohsiung Medical University, Kaohsiung, 807, Taiwan
| | - Kung-Kai Kuo
- Department of Surgery, Kaohsiung Medical University Hospital, Kaohsiung, 807, Taiwan
| | - Chang-Shen Lin
- Graduate Institute of Medicine, College of Medicine, Kaohsiung Medical University, Kaohsiung, 807, Taiwan.
- Department of Biological Sciences, National Sun Yat-sen University, Kaohsiung, 804, Taiwan.
| | - Kazunari K Yokoyama
- Graduate Institute of Medicine, College of Medicine, Kaohsiung Medical University, Kaohsiung, 807, Taiwan.
- Faculty of Molecular Preventive Medicine, Graduate School of Medicine, The University of Tokyo, Tokyo, 113-0033, Japan.
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562
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Grøntved L, Goldstein I. Editorial: Regulating Liver Transcriptional Networks by Endocrine, Extracellular, and Intrinsic Cues. Front Endocrinol (Lausanne) 2019; 10:878. [PMID: 31920987 PMCID: PMC6923206 DOI: 10.3389/fendo.2019.00878] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/12/2019] [Accepted: 11/29/2019] [Indexed: 11/13/2022] Open
Affiliation(s)
- Lars Grøntved
- Department of Biochemistry and Molecular Biology, Center for Functional Genomics and Tissue Plasticity, University of Southern Denmark, Odense, Denmark
| | - Ido Goldstein
- Institute of Biochemistry, Food Science and Nutrition, The Robert H. Smith Faculty of Agriculture, Food and Environment, The Hebrew University of Jerusalem, Rehovot, Israel
- *Correspondence: Ido Goldstein
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563
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Giladi A, Amit I. Single-Cell Genomics: A Stepping Stone for Future Immunology Discoveries. Cell 2018; 172:14-21. [PMID: 29328909 DOI: 10.1016/j.cell.2017.11.011] [Citation(s) in RCA: 114] [Impact Index Per Article: 19.0] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2017] [Revised: 11/01/2017] [Accepted: 11/06/2017] [Indexed: 02/08/2023]
Abstract
The immunology field has invested great efforts and ingenuity to characterize the various immune cell types and elucidate their functions. However, accumulating evidence indicates that current technologies and classification schemes are limited in their ability to account for the functional heterogeneity of immune processes. Single-cell genomics hold the potential to revolutionize the way we characterize complex immune cell assemblies and study their spatial organization, dynamics, clonal distribution, pathways, function, and crosstalks. In this Perspective, we consider recent and forthcoming technological and analytical advances in single-cell genomics and the potential impact of those advances on the future of immunology research and immunotherapy.
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Affiliation(s)
- Amir Giladi
- Department of Immunology, Weizmann Institute, Rehovot 76100, Israel
| | - Ido Amit
- Department of Immunology, Weizmann Institute, Rehovot 76100, Israel.
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564
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Abstract
The essential liver exocrine and endocrine functions require a precise spatial arrangement of the hepatic lobule consisting of the central vein, portal vein, hepatic artery, intrahepatic bile duct system, and hepatocyte zonation. This allows blood to be carried through the liver parenchyma sampled by all hepatocytes and bile produced by the hepatocytes to be carried out of the liver through the intrahepatic bile duct system composed of cholangiocytes. The molecular orchestration of multiple signaling pathways and epigenetic factors is required to set up lineage restriction of the bipotential hepatoblast progenitor into the hepatocyte and cholangiocyte cell lineages, and to further refine cell fate heterogeneity within each cell lineage reflected in the functional heterogeneity of hepatocytes and cholangiocytes. In addition to the complex molecular regulation, there is a complicated morphogenetic choreography observed in building the refined hepatic epithelial architecture. Given the multifaceted molecular and cellular regulation, it is not surprising that impairment of any of these processes can result in acute and chronic hepatobiliary diseases. To enlighten the development of potential molecular and cellular targets for therapeutic options, an understanding of how the intricate hepatic molecular and cellular interactions are regulated is imperative. Here, we review the signaling pathways and epigenetic factors regulating hepatic cell lineages, fates, and epithelial architecture.
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Affiliation(s)
- Stacey S Huppert
- Division of Gastroenterology, Hepatology & Nutrition, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, United States; Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH, United States.
| | - Makiko Iwafuchi-Doi
- Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH, United States; Division of Developmental Biology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, United States
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565
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Manco R, Leclercq IA, Clerbaux LA. Liver Regeneration: Different Sub-Populations of Parenchymal Cells at Play Choreographed by an Injury-Specific Microenvironment. Int J Mol Sci 2018; 19:E4115. [PMID: 30567401 PMCID: PMC6321497 DOI: 10.3390/ijms19124115] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2018] [Revised: 12/05/2018] [Accepted: 12/13/2018] [Indexed: 02/06/2023] Open
Abstract
Liver regeneration is crucial for the maintenance of liver functional mass during homeostasis and diseases. In a disease context-dependent manner, liver regeneration is contributed to by hepatocytes or progenitor cells. As long as they are replicatively competent, hepatocytes are the main cell type responsible for supporting liver size homeostasisand regeneration. The concept that all hepatocytes within the lobule have the same proliferative capacity but are differentially recruited according to the localization of the wound, or whether a yet to be defined sub-population of hepatocytes supports regeneration is still debated. In a chronically or severely injured liver, hepatocytes may enter a state of replicative senescence. In such conditions, small biliary cells activate and expand, a process called ductular reaction (DR). Work in the last few decades has demonstrated that DR cells can differentiate into hepatocytes and thereby contribute to parenchymal reconstitution. In this study we will review the molecular mechanisms supporting these two processes to determine potential targets that would be amenable for therapeutic manipulation to enhance liver regeneration.
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Affiliation(s)
- Rita Manco
- Laboratory of Hepato-Gastroenterology, Institut de Recherche Expérimentale et Clinique, UCLouvain, Brussels, Belgium.
| | - Isabelle A Leclercq
- Laboratory of Hepato-Gastroenterology, Institut de Recherche Expérimentale et Clinique, UCLouvain, Brussels, Belgium.
| | - Laure-Alix Clerbaux
- Laboratory of Hepato-Gastroenterology, Institut de Recherche Expérimentale et Clinique, UCLouvain, Brussels, Belgium.
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566
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Abstract
Cellular heterogeneity within and across tumors has been a major obstacle in understanding and treating cancer, and the complex heterogeneity is masked if bulk tumor tissues are used for analysis. The advent of rapidly developing single-cell sequencing technologies, which include methods related to single-cell genome, epigenome, transcriptome, and multi-omics sequencing, have been applied to cancer research and led to exciting new findings in the fields of cancer evolution, metastasis, resistance to therapy, and tumor microenvironment. In this review, we discuss recent advances and limitations of these new technologies and their potential applications in cancer studies.
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Affiliation(s)
- Xianwen Ren
- Beijing Advanced Innovation Centre for Genomics, Peking-Tsinghua Centre for Life Sciences, Biomedical Pioneering Innovation Center (BIOPIC), School of Life Sciences, Peking University, Beijing, 100871, China.
| | - Boxi Kang
- Beijing Advanced Innovation Centre for Genomics, Peking-Tsinghua Centre for Life Sciences, Biomedical Pioneering Innovation Center (BIOPIC), School of Life Sciences, Peking University, Beijing, 100871, China
| | - Zemin Zhang
- Beijing Advanced Innovation Centre for Genomics, Peking-Tsinghua Centre for Life Sciences, Biomedical Pioneering Innovation Center (BIOPIC), School of Life Sciences, Peking University, Beijing, 100871, China.
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567
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Traeger L, Gallitz I, Sekhri R, Bäumer N, Kuhlmann T, Kemming C, Holtkamp M, Müller JC, Karst U, Canonne-Hergaux F, Muckenthaler MU, Bloch DB, Olschewski A, Bartnikas TB, Steinbicker AU. ALK3 undergoes ligand-independent homodimerization and BMP-induced heterodimerization with ALK2. Free Radic Biol Med 2018; 129:127-137. [PMID: 30227271 PMCID: PMC6842210 DOI: 10.1016/j.freeradbiomed.2018.09.021] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/11/2018] [Revised: 09/09/2018] [Accepted: 09/14/2018] [Indexed: 01/09/2023]
Abstract
The bone morphogenetic protein (BMP) type I receptors ALK2 and ALK3 are essential for expression of hepcidin, a key iron regulatory hormone. In mice, hepatocyte-specific Alk2 deficiency leads to moderate iron overload with periportal liver iron accumulation, while hepatocyte-specific Alk3 deficiency leads to severe iron overload with centrilobular liver iron accumulation and a more marked reduction of basal hepcidin levels. The objective of this study was to investigate whether the two receptors have additive roles in hepcidin regulation. Iron overload in mice with hepatocyte-specific Alk2 and Alk3 (Alk2/3) deficiency was characterized and compared to hepatocyte-specific Alk3 deficient mice. Co-immunoprecipitation studies were performed to detect the formation of ALK2 and ALK3 homodimer and heterodimer complexes in vitro in the presence and absence of ligands. The iron overload phenotype of hepatocyte-specific Alk2/3-deficient mice was more severe than that of hepatocyte-specific Alk3-deficient mice. In vitro co-immunoprecipitation studies in Huh7 cells showed that ALK3 can homodimerize in absence of BMP2 or BMP6. In contrast, ALK2 did not homodimerize in either the presence or absence of BMP ligands. However, ALK2 did form heterodimers with ALK3 in the presence of BMP2 or BMP6. ALK3-ALK3 and ALK2-ALK3 receptor complexes induced hepcidin expression in Huh7 cells. Our data indicate that: (I) ALK2 and ALK3 have additive functions in vivo, as Alk2/3 deficiency leads to a greater degree of iron overload than Alk3 deficiency; (II) ALK3, but not ALK2, undergoes ligand-independent homodimerization; (III) the formation of ALK2-ALK3 heterodimers is ligand-dependent and (IV) both receptor complexes functionally induce hepcidin expression in vitro.
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Affiliation(s)
- Lisa Traeger
- Department of Anesthesiology, Intensive Care and Pain Medicine, University Hospital Muenster, University of Muenster, Muenster, Germany.
| | - Inka Gallitz
- Department of Anesthesiology, Intensive Care and Pain Medicine, University Hospital Muenster, University of Muenster, Muenster, Germany.
| | - Rohit Sekhri
- Department of Anesthesiology, Intensive Care and Pain Medicine, University Hospital Muenster, University of Muenster, Muenster, Germany.
| | - Nicole Bäumer
- Department of Medicine A, Molecular Hematology and Oncology, University Hospital Muenster, University of Muenster, Muenster, Germany.
| | - Tanja Kuhlmann
- Institute of Neuropathology, University Hospital Muenster, University of Muenster, Muenster, Germany.
| | - Claudia Kemming
- Institute of Neuropathology, University Hospital Muenster, University of Muenster, Muenster, Germany.
| | - Michael Holtkamp
- Institute of Inorganic and Analytical Chemistry, University of Muenster, Muenster, Germany.
| | | | - Uwe Karst
- Institute of Inorganic and Analytical Chemistry, University of Muenster, Muenster, Germany.
| | | | - Martina U Muckenthaler
- Department of Pediatric Oncology, Hematology and Immunology, University of Heidelberg, Heidelberg, Germany; Molecular Medicine Partnership Unit (MMPU), Heidelberg, Germany.
| | - Donald B Bloch
- Anaesthesia Center for Critical Care Research, Department of Anesthesia, Critical Care and Pain Medicine, and the Division of Rheumatology, Allergy and Immunology, Department of Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA.
| | - Andrea Olschewski
- Institute of Physiology, Medical University of Graz, Graz, Austria; Ludwig Boltzmann Institute for Lung Vascular Research, Graz, Austria.
| | - Thomas B Bartnikas
- Department of Pathology and Laboratory Medicine, Brown University, Providence, RI, USA.
| | - Andrea U Steinbicker
- Department of Anesthesiology, Intensive Care and Pain Medicine, University Hospital Muenster, University of Muenster, Muenster, Germany.
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568
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Brazovskaja A, Treutlein B, Camp JG. High-throughput single-cell transcriptomics on organoids. Curr Opin Biotechnol 2018; 55:167-171. [PMID: 30504008 DOI: 10.1016/j.copbio.2018.11.002] [Citation(s) in RCA: 52] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2018] [Accepted: 11/07/2018] [Indexed: 01/08/2023]
Abstract
Three-dimensional (3D) tissues grown in culture from human stem cells offer the incredible opportunity to analyze and manipulate human development, and to generate patient-specific models of disease. Methods to sequence DNA and RNA in single cells are being used to analyze these so-called 'organoid' systems in high-resolution. Single-cell transcriptomics has been used to quantitate the similarity of organoid cells to primary tissue counterparts in the brain, intestine, liver, and kidney, as well as identify cell-specific responses to environmental variables and disease conditions. The merging of these two technologies, single-cell genomics and organoids, will have profound impact on personalized medicine in the near future.
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Affiliation(s)
| | - Barbara Treutlein
- Max Planck Institute for Evolutionary Anthropology, 04103 Leipzig, Germany; Max Planck Institute of Molecular Cell Biology and Genetics, 01307 Dresden, Germany; Technical University Munich, 80333 Munich, Germany.
| | - J Gray Camp
- Max Planck Institute for Evolutionary Anthropology, 04103 Leipzig, Germany.
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569
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Farack L, Golan M, Egozi A, Dezorella N, Bahar Halpern K, Ben-Moshe S, Garzilli I, Tóth B, Roitman L, Krizhanovsky V, Itzkovitz S. Transcriptional Heterogeneity of Beta Cells in the Intact Pancreas. Dev Cell 2018; 48:115-125.e4. [PMID: 30503750 DOI: 10.1016/j.devcel.2018.11.001] [Citation(s) in RCA: 55] [Impact Index Per Article: 9.2] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2018] [Revised: 09/14/2018] [Accepted: 10/31/2018] [Indexed: 12/27/2022]
Abstract
Pancreatic beta cells have been shown to be heterogeneous at multiple levels. However, spatially interrogating transcriptional heterogeneity in the intact tissue has been challenging. Here, we developed an optimized protocol for single-molecule transcript imaging in the intact pancreas and used it to identify a sub-population of "extreme" beta cells with elevated mRNA levels of insulin and other secretory genes. Extreme beta cells contain higher ribosomal and proinsulin content but lower levels of insulin protein in fasted states, suggesting they may be tuned for basal insulin secretion. They exhibit a distinctive intra-cellular polarization pattern, with elevated mRNA concentrations in an apical ER-enriched compartment, distinct from the localization of nascent and mature proteins. The proportion of extreme cells increases in db/db diabetic mice, potentially facilitating the required increase in basal insulin. Our results thus highlight a sub-population of beta cells that may carry distinct functional roles along physiological and pathological timescales.
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Affiliation(s)
- Lydia Farack
- Department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot 7610001, Israel
| | - Matan Golan
- Department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot 7610001, Israel
| | - Adi Egozi
- Department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot 7610001, Israel
| | - Nili Dezorella
- Department of Chemical Research Support, Weizmann Institute of Science, Rehovot 7610001, Israel
| | - Keren Bahar Halpern
- Department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot 7610001, Israel
| | - Shani Ben-Moshe
- Department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot 7610001, Israel
| | - Immacolata Garzilli
- Department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot 7610001, Israel
| | - Beáta Tóth
- Department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot 7610001, Israel
| | - Lior Roitman
- Department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot 7610001, Israel
| | - Valery Krizhanovsky
- Department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot 7610001, Israel
| | - Shalev Itzkovitz
- Department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot 7610001, Israel.
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570
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Machine learning based classification of cells into chronological stages using single-cell transcriptomics. Sci Rep 2018; 8:17156. [PMID: 30464314 PMCID: PMC6249247 DOI: 10.1038/s41598-018-35218-5] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2018] [Accepted: 10/30/2018] [Indexed: 12/11/2022] Open
Abstract
Age-associated deterioration of cellular physiology leads to pathological conditions. The ability to detect premature aging could provide a window for preventive therapies against age-related diseases. However, the techniques for determining cellular age are limited, as they rely on a limited set of histological markers and lack predictive power. Here, we implement GERAS (GEnetic Reference for Age of Single-cell), a machine learning based framework capable of assigning individual cells to chronological stages based on their transcriptomes. GERAS displays greater than 90% accuracy in classifying the chronological stage of zebrafish and human pancreatic cells. The framework demonstrates robustness against biological and technical noise, as evaluated by its performance on independent samplings of single-cells. Additionally, GERAS determines the impact of differences in calorie intake and BMI on the aging of zebrafish and human pancreatic cells, respectively. We further harness the classification ability of GERAS to identify molecular factors that are potentially associated with the aging of beta-cells. We show that one of these factors, junba, is necessary to maintain the proliferative state of juvenile beta-cells. Our results showcase the applicability of a machine learning framework to classify the chronological stage of heterogeneous cell populations, while enabling detection of candidate genes associated with aging.
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571
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Xavier da Silveira Dos Santos A, Liberali P. From single cells to tissue self-organization. FEBS J 2018; 286:1495-1513. [PMID: 30390414 PMCID: PMC6519261 DOI: 10.1111/febs.14694] [Citation(s) in RCA: 37] [Impact Index Per Article: 6.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2018] [Revised: 10/10/2018] [Accepted: 11/02/2018] [Indexed: 12/16/2022]
Abstract
Self-organization is a process by which interacting cells organize and arrange themselves in higher order structures and patterns. To achieve this, cells must have molecular mechanisms to sense their complex local environment and interpret it to respond accordingly. A combination of cell-intrinsic and cell-extrinsic cues are decoded by the single cells dictating their behaviour, their differentiation and symmetry-breaking potential driving development, tissue remodeling and regenerative processes. A unifying property of these self-organized pattern-forming systems is the importance of fluctuations, cell-to-cell variability, or noise. Cell-to-cell variability is an inherent and emergent property of populations of cells that maximize the population performance instead of the individual cell, providing tissues the flexibility to develop and maintain homeostasis in diverse environments. In this review, we will explore the role of self-organization and cell-to-cell variability as fundamental properties of multicellularity-and the requisite of single-cell resolution for its understanding. Moreover, we will analyze how single cells generate emergent multicellular dynamics observed at the tissue level 'travelling' across different scales: spatial, temporal and functional.
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Affiliation(s)
| | - Prisca Liberali
- Friedrich Miescher Institute for Biomedical Research (FMI), Basel, Switzerland.,University of Basel, Switzerland
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572
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Gangalum RK, Kim D, Kashyap RK, Mangul S, Zhou X, Elashoff D, Bhat SP. Spatial Analysis of Single Fiber Cells of the Developing Ocular Lens Reveals Regulated Heterogeneity of Gene Expression. iScience 2018; 10:66-79. [PMID: 30508719 PMCID: PMC6277220 DOI: 10.1016/j.isci.2018.11.024] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2018] [Revised: 11/08/2018] [Accepted: 11/13/2018] [Indexed: 01/19/2023] Open
Abstract
The developing eye lens presents an exceptional paradigm for spatial transcriptomics. It is composed of highly organized long, slender transparent fiber cells, which differentiate from the edges of the anterior epithelium of the lens (equator), attended by high expression of crystallins, which generates transparency. Every fiber cell, therefore, is an optical unit whose refractive properties derive from its gene activity. Here, we probe this tangible relationship between the gene activity and the phenotype by studying the expression of all known 17 crystallins and 77 other non-crystallin genes in single fiber cells isolated from three states/regions of differentiation, allowing us to follow molecular progression at the single-cell level. The data demonstrate highly variable gene activity in cortical fibers, interposed between the nascent and the terminally differentiated fiber cell transcription. These data suggest that the so-called stochastic, highly heterogeneous gene activity is a regulated intermediate in the realization of a functional phenotype.
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Affiliation(s)
- Rajendra K Gangalum
- Stein Eye Institute, Geffen School of Medicine, University of California, Los Angeles, CA 90095-7000, USA
| | - Dongjae Kim
- Stein Eye Institute, Geffen School of Medicine, University of California, Los Angeles, CA 90095-7000, USA
| | - Raj K Kashyap
- Stein Eye Institute, Geffen School of Medicine, University of California, Los Angeles, CA 90095-7000, USA
| | - Serghei Mangul
- Department of Computer Science and Human Genetics, University of California, Los Angeles, CA 90095-7000, USA
| | - Xinkai Zhou
- Department of Medicine, University of California, Los Angeles, CA 90095-7000, USA
| | - David Elashoff
- Department of Medicine, University of California, Los Angeles, CA 90095-7000, USA
| | - Suraj P Bhat
- Stein Eye Institute, Geffen School of Medicine, University of California, Los Angeles, CA 90095-7000, USA; Brain Research Institute, University of California, Los Angeles, CA 90095-7000, USA; Molecular Biology Institute, University of California, Los Angeles, CA 90095-7000, USA.
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573
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Lafzi A, Moutinho C, Picelli S, Heyn H. Tutorial: guidelines for the experimental design of single-cell RNA sequencing studies. Nat Protoc 2018; 13:2742-2757. [DOI: 10.1038/s41596-018-0073-y] [Citation(s) in RCA: 102] [Impact Index Per Article: 17.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
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574
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Halpern KB, Shenhav R, Massalha H, Toth B, Egozi A, Massasa EE, Medgalia C, David E, Giladi A, Moor AE, Porat Z, Amit I, Itzkovitz S. Paired-cell sequencing enables spatial gene expression mapping of liver endothelial cells. Nat Biotechnol 2018; 36:962-970. [PMID: 30222169 PMCID: PMC6546596 DOI: 10.1038/nbt.4231] [Citation(s) in RCA: 201] [Impact Index Per Article: 33.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2018] [Accepted: 07/19/2018] [Indexed: 02/08/2023]
Abstract
Spatially resolved single-cell RNA sequencing (scRNAseq) is a powerful approach for inferring connections between a cell's identity and its position in a tissue. We recently combined scRNAseq with spatially mapped landmark genes to infer the expression zonation of hepatocytes. However, determining zonation of small cells with low mRNA content, or without highly expressed landmark genes, remains challenging. Here we used paired-cell sequencing, in which mRNA from pairs of attached mouse cells were sequenced and gene expression from one cell type was used to infer the pairs' tissue coordinates. We applied this method to pairs of hepatocytes and liver endothelial cells (LECs). Using the spatial information from hepatocytes, we reconstructed LEC zonation and extracted a landmark gene panel that we used to spatially map LEC scRNAseq data. Our approach revealed the expression of both Wnt ligands and the Dkk3 Wnt antagonist in distinct pericentral LEC sub-populations. This approach can be used to reconstruct spatial expression maps of non-parenchymal cells in other tissues.
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Affiliation(s)
- Keren Bahar Halpern
- Department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot, Israel
| | - Rom Shenhav
- Department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot, Israel
| | - Hassan Massalha
- Department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot, Israel
| | - Beata Toth
- Department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot, Israel
| | - Adi Egozi
- Department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot, Israel
| | - Efi E. Massasa
- Department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot, Israel
| | - Chiara Medgalia
- Department of Immunology, Weizmann Institute of Science, Rehovot, Israel
| | - Eyal David
- Department of Immunology, Weizmann Institute of Science, Rehovot, Israel
| | - Amir Giladi
- Department of Immunology, Weizmann Institute of Science, Rehovot, Israel
| | - Andreas E. Moor
- Department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot, Israel
| | - Ziv Porat
- The Flow Cytometry Unit, Life Sciences Faculty, Weizmann Institute of Science, Rehovot, Israel
| | - Ido Amit
- Department of Immunology, Weizmann Institute of Science, Rehovot, Israel
| | - Shalev Itzkovitz
- Department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot, Israel
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575
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Hu H, Gehart H, Artegiani B, LÖpez-Iglesias C, Dekkers F, Basak O, van Es J, Chuva de Sousa Lopes SM, Begthel H, Korving J, van den Born M, Zou C, Quirk C, Chiriboga L, Rice CM, Ma S, Rios A, Peters PJ, de Jong YP, Clevers H. Long-Term Expansion of Functional Mouse and Human Hepatocytes as 3D Organoids. Cell 2018; 175:1591-1606.e19. [DOI: 10.1016/j.cell.2018.11.013] [Citation(s) in RCA: 340] [Impact Index Per Article: 56.7] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2018] [Revised: 07/27/2018] [Accepted: 11/12/2018] [Indexed: 12/14/2022]
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576
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Raj B, Gagnon JA, Schier AF. Large-scale reconstruction of cell lineages using single-cell readout of transcriptomes and CRISPR-Cas9 barcodes by scGESTALT. Nat Protoc 2018; 13:2685-2713. [PMID: 30353175 PMCID: PMC6279253 DOI: 10.1038/s41596-018-0058-x] [Citation(s) in RCA: 45] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
Lineage relationships among the large number of heterogeneous cell types generated during development are difficult to reconstruct in a high-throughput manner. We recently established a method, scGESTALT, that combines cumulative editing of a lineage barcode array by CRISPR-Cas9 with large-scale transcriptional profiling using droplet-based single-cell RNA sequencing (scRNA-seq). The technique generates edits in the barcode array over multiple timepoints using Cas9 and pools of single-guide RNAs (sgRNAs) introduced during early and late zebrafish embryonic development, which distinguishes it from similar Cas9 lineage-tracing methods. The recorded lineages are captured, along with thousands of cellular transcriptomes, to build lineage trees with hundreds of branches representing relationships among profiled cell types. Here, we provide details for (i) generating transgenic zebrafish; (ii) performing multi-timepoint barcode editing; (iii) building scRNA-seq libraries from brain tissue; and (iv) concurrently amplifying lineage barcodes from captured single cells. Generating transgenic lines takes 6 months, and performing barcode editing and generating single-cell libraries involve 7 d of hands-on time. scGESTALT provides a scalable platform to map lineage relationships between cell types in any system that permits genome editing during development, regeneration, or disease.
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Affiliation(s)
- Bushra Raj
- Department of Molecular and Cellular Biology, Harvard University, Cambridge, MA, USA.
- Allen Discovery Center for Cell Lineage Tracing, Seattle, WA, USA.
| | - James A Gagnon
- Department of Molecular and Cellular Biology, Harvard University, Cambridge, MA, USA
- Allen Discovery Center for Cell Lineage Tracing, Seattle, WA, USA
- Department of Biology, University of Utah, Salt Lake City, UT, USA
| | - Alexander F Schier
- Department of Molecular and Cellular Biology, Harvard University, Cambridge, MA, USA
- Allen Discovery Center for Cell Lineage Tracing, Seattle, WA, USA
- Biozentrum, University of Basel, Basel, Switzerland
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Harvard Stem Cell Institute, Harvard University, Cambridge, MA, USA
- Center for Brain Science, Harvard University, Cambridge, MA, USA
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577
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Zhu Q, Shah S, Dries R, Cai L, Yuan GC. Identification of spatially associated subpopulations by combining scRNAseq and sequential fluorescence in situ hybridization data. Nat Biotechnol 2018; 36:nbt.4260. [PMID: 30371680 PMCID: PMC6488461 DOI: 10.1038/nbt.4260] [Citation(s) in RCA: 124] [Impact Index Per Article: 20.7] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2017] [Accepted: 08/27/2018] [Indexed: 01/03/2023]
Abstract
How intrinsic gene-regulatory networks interact with a cell's spatial environment to define its identity remains poorly understood. We developed an approach to distinguish between intrinsic and extrinsic effects on global gene expression by integrating analysis of sequencing-based and imaging-based single-cell transcriptomic profiles, using cross-platform cell type mapping combined with a hidden Markov random field model. We applied this approach to dissect the cell-type- and spatial-domain-associated heterogeneity in the mouse visual cortex region. Our analysis identified distinct spatially associated, cell-type-independent signatures in the glutamatergic and astrocyte cell compartments. Using these signatures to analyze single-cell RNA sequencing data, we identified previously unknown spatially associated subpopulations, which were validated by comparison with anatomical structures and Allen Brain Atlas images.
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Affiliation(s)
- Qian Zhu
- Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute and Harvard T.H.Chan School of Public Health, Boston, MA 02215, USA
| | - Sheel Shah
- Division of Biology and Biological Engineering, Caltech, Pasadena USA 91125
- UCLA-Caltech Medical Scientist Training Program, David Geffen School of Medicine, University of California at Los Angeles, Los Angeles, CA 90095, USA
| | - Ruben Dries
- Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute and Harvard T.H.Chan School of Public Health, Boston, MA 02215, USA
| | - Long Cai
- Division of Biology and Biological Engineering, Caltech, Pasadena USA 91125
| | - Guo-Cheng Yuan
- Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute and Harvard T.H.Chan School of Public Health, Boston, MA 02215, USA
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578
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MacParland SA, Liu JC, Ma XZ, Innes BT, Bartczak AM, Gage BK, Manuel J, Khuu N, Echeverri J, Linares I, Gupta R, Cheng ML, Liu LY, Camat D, Chung SW, Seliga RK, Shao Z, Lee E, Ogawa S, Ogawa M, Wilson MD, Fish JE, Selzner M, Ghanekar A, Grant D, Greig P, Sapisochin G, Selzner N, Winegarden N, Adeyi O, Keller G, Bader GD, McGilvray ID. Single cell RNA sequencing of human liver reveals distinct intrahepatic macrophage populations. Nat Commun 2018; 9:4383. [PMID: 30348985 PMCID: PMC6197289 DOI: 10.1038/s41467-018-06318-7] [Citation(s) in RCA: 832] [Impact Index Per Article: 138.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2018] [Accepted: 08/24/2018] [Indexed: 12/02/2022] Open
Abstract
The liver is the largest solid organ in the body and is critical for metabolic and immune functions. However, little is known about the cells that make up the human liver and its immune microenvironment. Here we report a map of the cellular landscape of the human liver using single-cell RNA sequencing. We provide the transcriptional profiles of 8444 parenchymal and non-parenchymal cells obtained from the fractionation of fresh hepatic tissue from five human livers. Using gene expression patterns, flow cytometry, and immunohistochemical examinations, we identify 20 discrete cell populations of hepatocytes, endothelial cells, cholangiocytes, hepatic stellate cells, B cells, conventional and non-conventional T cells, NK-like cells, and distinct intrahepatic monocyte/macrophage populations. Together, our study presents a comprehensive view of the human liver at single-cell resolution that outlines the characteristics of resident cells in the liver, and in particular provides a map of the human hepatic immune microenvironment. The development of single cell RNA sequencing technologies has been instrumental in advancing our understanding of tissue biology. Here, MacParland et al. performed single cell RNA sequencing of human liver samples, and identify distinct populations of intrahepatic macrophages that may play specific roles in liver disease.
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Affiliation(s)
- Sonya A MacParland
- Multi-Organ Transplant Program, Toronto General Hospital Research Institute, Toronto, ON, M5G 2C4, Canada. .,Department of Immunology, University of Toronto, Toronto, ON, M5S 1A8, Canada. .,Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, M5G 1L7, Canada.
| | - Jeff C Liu
- The Donnelly Centre, University of Toronto, Toronto, ON, M5S 3E1, Canada
| | - Xue-Zhong Ma
- Multi-Organ Transplant Program, Toronto General Hospital Research Institute, Toronto, ON, M5G 2C4, Canada
| | - Brendan T Innes
- The Donnelly Centre, University of Toronto, Toronto, ON, M5S 3E1, Canada.,Department of Molecular Genetics, University of Toronto, Toronto, M5G 1A8, Canada
| | - Agata M Bartczak
- Multi-Organ Transplant Program, Toronto General Hospital Research Institute, Toronto, ON, M5G 2C4, Canada
| | - Blair K Gage
- McEwen Centre for Regenerative Medicine, University Health Network, Toronto, ON, M5G 1L7, Canada
| | - Justin Manuel
- Multi-Organ Transplant Program, Toronto General Hospital Research Institute, Toronto, ON, M5G 2C4, Canada
| | - Nicholas Khuu
- Princess Margaret Genomics Centre, University Health Network, Toronto, ON, M5G 1L7, Canada
| | - Juan Echeverri
- Multi-Organ Transplant Program, Toronto General Hospital Research Institute, Toronto, ON, M5G 2C4, Canada
| | - Ivan Linares
- Multi-Organ Transplant Program, Toronto General Hospital Research Institute, Toronto, ON, M5G 2C4, Canada
| | - Rahul Gupta
- Multi-Organ Transplant Program, Toronto General Hospital Research Institute, Toronto, ON, M5G 2C4, Canada
| | - Michael L Cheng
- Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, M5G 1L7, Canada
| | - Lewis Y Liu
- Department of Immunology, University of Toronto, Toronto, ON, M5S 1A8, Canada
| | - Damra Camat
- Multi-Organ Transplant Program, Toronto General Hospital Research Institute, Toronto, ON, M5G 2C4, Canada
| | - Sai W Chung
- Department of Immunology, University of Toronto, Toronto, ON, M5S 1A8, Canada
| | - Rebecca K Seliga
- Multi-Organ Transplant Program, Toronto General Hospital Research Institute, Toronto, ON, M5G 2C4, Canada
| | - Zigong Shao
- Multi-Organ Transplant Program, Toronto General Hospital Research Institute, Toronto, ON, M5G 2C4, Canada
| | - Elizabeth Lee
- Multi-Organ Transplant Program, Toronto General Hospital Research Institute, Toronto, ON, M5G 2C4, Canada
| | - Shinichiro Ogawa
- McEwen Centre for Regenerative Medicine, University Health Network, Toronto, ON, M5G 1L7, Canada
| | - Mina Ogawa
- McEwen Centre for Regenerative Medicine, University Health Network, Toronto, ON, M5G 1L7, Canada
| | - Michael D Wilson
- Department of Molecular Genetics, University of Toronto, Toronto, M5G 1A8, Canada.,Genetics and Genome Biology, Hospital for Sick Children, Toronto, M5G 0A4, Canada
| | - Jason E Fish
- Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, M5G 1L7, Canada.,Division of Advanced Diagnostics, Toronto General Hospital Research Institute, Toronto, ON, M5G 2C4, Canada
| | - Markus Selzner
- Multi-Organ Transplant Program, Toronto General Hospital Research Institute, Toronto, ON, M5G 2C4, Canada
| | - Anand Ghanekar
- Multi-Organ Transplant Program, Toronto General Hospital Research Institute, Toronto, ON, M5G 2C4, Canada
| | - David Grant
- Multi-Organ Transplant Program, Toronto General Hospital Research Institute, Toronto, ON, M5G 2C4, Canada
| | - Paul Greig
- Multi-Organ Transplant Program, Toronto General Hospital Research Institute, Toronto, ON, M5G 2C4, Canada
| | - Gonzalo Sapisochin
- Multi-Organ Transplant Program, Toronto General Hospital Research Institute, Toronto, ON, M5G 2C4, Canada
| | - Nazia Selzner
- Multi-Organ Transplant Program, Toronto General Hospital Research Institute, Toronto, ON, M5G 2C4, Canada
| | - Neil Winegarden
- Princess Margaret Genomics Centre, University Health Network, Toronto, ON, M5G 1L7, Canada
| | - Oyedele Adeyi
- Multi-Organ Transplant Program, Toronto General Hospital Research Institute, Toronto, ON, M5G 2C4, Canada.,Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, M5G 1L7, Canada.,Laboratory Medicine Program, University Health Network, Toronto, Ontario, M5G 1L7, Canada
| | - Gordon Keller
- McEwen Centre for Regenerative Medicine, University Health Network, Toronto, ON, M5G 1L7, Canada.,Princess Margaret Cancer Centre, University Health Network, Toronto, Ontario, M5G 1L7, Canada.,Department of Medical Biophysics, University of Toronto, Toronto, ON, M5G 1L7, Canada
| | - Gary D Bader
- The Donnelly Centre, University of Toronto, Toronto, ON, M5S 3E1, Canada. .,Department of Molecular Genetics, University of Toronto, Toronto, M5G 1A8, Canada.
| | - Ian D McGilvray
- Multi-Organ Transplant Program, Toronto General Hospital Research Institute, Toronto, ON, M5G 2C4, Canada.
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579
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Verma A, Antony AN, Ogunnaike BA, Hoek JB, Vadigepalli R. Causality Analysis and Cell Network Modeling of Spatial Calcium Signaling Patterns in Liver Lobules. Front Physiol 2018; 9:1377. [PMID: 30337879 PMCID: PMC6180170 DOI: 10.3389/fphys.2018.01377] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2018] [Accepted: 09/11/2018] [Indexed: 01/21/2023] Open
Abstract
Dynamics as well as localization of Ca2+ transients plays a vital role in liver function under homeostatic conditions, repair, and disease. In response to circulating hormonal stimuli, hepatocytes exhibit intracellular Ca2+ responses that propagate through liver lobules in a wave-like fashion. Although intracellular processes that control cell autonomous Ca2+ spiking behavior have been studied extensively, the intra- and inter-cellular signaling factors that regulate lobular scale spatial patterns and wave-like propagation of Ca2+ remain to be determined. To address this need, we acquired images of cytosolic Ca2+ transients in 1300 hepatocytes situated across several mouse liver lobules over a period of 1600 s. We analyzed this time series data using correlation network analysis, causal network analysis, and computational modeling, to characterize the spatial distribution of heterogeneity in intracellular Ca2+ signaling components as well as intercellular interactions that control lobular scale Ca2+ waves. Our causal network analysis revealed that hepatocytes are causally linked to multiple other co-localized hepatocytes, but these influences are not necessarily aligned uni-directionally along the sinusoids. Our computational model-based analysis showed that spatial gradients of intracellular Ca2+ signaling components as well as intercellular molecular exchange are required for lobular scale propagation of Ca2+ waves. Additionally, our analysis suggested that causal influences of hepatocytes on Ca2+ responses of multiple neighbors lead to robustness of Ca2+ wave propagation through liver lobules.
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Affiliation(s)
- Aalap Verma
- Department of Biomedical Engineering, University of Delaware, Newark, DE, United States.,Department of Pathology, Anatomy and Cell Biology, Daniel Baugh Institute for Functional Genomics and Computational Biology, Thomas Jefferson University, Philadelphia, PA, United States
| | - Anil Noronha Antony
- Department of Pathology, Anatomy and Cell Biology, Daniel Baugh Institute for Functional Genomics and Computational Biology, Thomas Jefferson University, Philadelphia, PA, United States
| | - Babatunde A Ogunnaike
- Department of Chemical and Biomolecular Engineering, University of Delaware, Newark, DE, United States
| | - Jan B Hoek
- Department of Pathology, Anatomy and Cell Biology, Daniel Baugh Institute for Functional Genomics and Computational Biology, Thomas Jefferson University, Philadelphia, PA, United States
| | - Rajanikanth Vadigepalli
- Department of Pathology, Anatomy and Cell Biology, Daniel Baugh Institute for Functional Genomics and Computational Biology, Thomas Jefferson University, Philadelphia, PA, United States
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580
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Brosch M, Kattler K, Herrmann A, von Schönfels W, Nordström K, Seehofer D, Damm G, Becker T, Zeissig S, Nehring S, Reichel F, Moser V, Thangapandi RV, Stickel F, Baretton G, Röcken C, Muders M, Matz-Soja M, Krawczak M, Gasparoni G, Hartmann H, Dahl A, Schafmayer C, Walter J, Hampe J. Epigenomic map of human liver reveals principles of zonated morphogenic and metabolic control. Nat Commun 2018; 9:4150. [PMID: 30297808 PMCID: PMC6175862 DOI: 10.1038/s41467-018-06611-5] [Citation(s) in RCA: 59] [Impact Index Per Article: 9.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2018] [Accepted: 09/14/2018] [Indexed: 12/21/2022] Open
Abstract
A deeper epigenomic understanding of spatial organization of cells in human tissues is an important challenge. Here we report the first combined positional analysis of transcriptomes and methylomes across three micro-dissected zones (pericentral, intermediate and periportal) of human liver. We identify pronounced anti-correlated transcriptional and methylation gradients including a core of 271 genes controlling zonated metabolic and morphogen networks and observe a prominent porto-central gradient of DNA methylation at binding sites of 46 transcription factors. The gradient includes an epigenetic and transcriptional Wnt signature supporting the concept of a pericentral hepatocyte regeneration pathway under steady-state conditions. While donors with non-alcoholic fatty liver disease show consistent gene expression differences corresponding to the severity of the disease across all zones, the relative zonated gene expression and DNA methylation patterns remain unchanged. Overall our data provide a wealth of new positional insights into zonal networks controlled by epigenetic and transcriptional gradients in human liver. Spatial mapping of genomic programs in tissue cells is an important step in the understanding of organ function and disease. Here, the authors provide a spatially resolved epigenomic and transcriptomic map of human liver and show porto-central gradients in metabolic and morphogen networks and transcription factor binding sites as a basis to better understand liver regeneration and function.
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Affiliation(s)
- Mario Brosch
- Medical Department 1, University Hospital Dresden, Technische Universität Dresden (TU Dresden), Dresden, Germany.,Center for Regenerative Therapies Dresden (CRTD), Technische Universität Dresden (TU Dresden), Dresden, Germany
| | - Kathrin Kattler
- Department of Genetics and Epigenetics, Universität des Saarlandes, Saarbrücken, Germany
| | - Alexander Herrmann
- Medical Department 1, University Hospital Dresden, Technische Universität Dresden (TU Dresden), Dresden, Germany.,Center for Regenerative Therapies Dresden (CRTD), Technische Universität Dresden (TU Dresden), Dresden, Germany
| | - Witigo von Schönfels
- Department of Visceral Surgery, University Hospital Schleswig-Holstein, Christian-Albrechts-University Kiel, Kiel, Germany
| | - Karl Nordström
- Department of Genetics and Epigenetics, Universität des Saarlandes, Saarbrücken, Germany
| | - Daniel Seehofer
- Department of Hepatobiliary Surgery and Visceral Transplantation, University of Leipzig, Leipzig, Germany
| | - Georg Damm
- Department of Hepatobiliary Surgery and Visceral Transplantation, University of Leipzig, Leipzig, Germany
| | - Thomas Becker
- Department of Visceral Surgery, University Hospital Schleswig-Holstein, Christian-Albrechts-University Kiel, Kiel, Germany
| | - Sebastian Zeissig
- Medical Department 1, University Hospital Dresden, Technische Universität Dresden (TU Dresden), Dresden, Germany
| | - Sophie Nehring
- Medical Department 1, University Hospital Dresden, Technische Universität Dresden (TU Dresden), Dresden, Germany
| | - Fabian Reichel
- Medical Department 1, University Hospital Dresden, Technische Universität Dresden (TU Dresden), Dresden, Germany
| | - Vincent Moser
- Medical Department 1, University Hospital Dresden, Technische Universität Dresden (TU Dresden), Dresden, Germany
| | - Raghavan Veera Thangapandi
- Medical Department 1, University Hospital Dresden, Technische Universität Dresden (TU Dresden), Dresden, Germany
| | - Felix Stickel
- Department of Gastroenterology, University of Zürich, Zürich, Switzerland
| | - Gustavo Baretton
- Institute of Pathology, University Hospital Dresden, Technische Universität Dresden (TU Dresden), Dresden, Germany
| | - Christoph Röcken
- Institute of Pathology, University Hospital Schleswig-Holstein, Christian-Albrechts-University Kiel, Kiel, Germany
| | - Michael Muders
- Institute of Pathology, University Hospital Dresden, Technische Universität Dresden (TU Dresden), Dresden, Germany
| | - Madlen Matz-Soja
- Rudolf-Schönheimer-Institute for Biochemistry, University of Leipzig, Leipzig, Germany
| | - Michael Krawczak
- Institute of Medical Informatics and Statistics, Christian-Albrechts University, Kiel, Germany
| | - Gilles Gasparoni
- Department of Genetics and Epigenetics, Universität des Saarlandes, Saarbrücken, Germany
| | - Hella Hartmann
- Center for Molecular and Cellular Bioengineering (CMCB), Technische Universität Dresden (TU Dresden), Dresden, Germany
| | - Andreas Dahl
- Center for Regenerative Therapies Dresden (CRTD), Technische Universität Dresden (TU Dresden), Dresden, Germany
| | - Clemens Schafmayer
- Department of Visceral Surgery, University Hospital Schleswig-Holstein, Christian-Albrechts-University Kiel, Kiel, Germany
| | - Jörn Walter
- Department of Genetics and Epigenetics, Universität des Saarlandes, Saarbrücken, Germany
| | - Jochen Hampe
- Medical Department 1, University Hospital Dresden, Technische Universität Dresden (TU Dresden), Dresden, Germany. .,Center for Regenerative Therapies Dresden (CRTD), Technische Universität Dresden (TU Dresden), Dresden, Germany.
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581
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Tzfadia O, Bocobza S, Defoort J, Almekias-Siegl E, Panda S, Levy M, Storme V, Rombauts S, Jaitin DA, Keren-Shaul H, Van de Peer Y, Aharoni A. The 'TranSeq' 3'-end sequencing method for high-throughput transcriptomics and gene space refinement in plant genomes. THE PLANT JOURNAL : FOR CELL AND MOLECULAR BIOLOGY 2018; 96:223-232. [PMID: 29979480 DOI: 10.1111/tpj.14015] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/18/2017] [Revised: 06/19/2018] [Accepted: 06/25/2018] [Indexed: 05/26/2023]
Abstract
High-throughput RNA sequencing has proven invaluable not only to explore gene expression but also for both gene prediction and genome annotation. However, RNA sequencing, carried out on tens or even hundreds of samples, requires easy and cost-effective sample preparation methods using minute RNA amounts. Here, we present TranSeq, a high-throughput 3'-end sequencing procedure that requires 10- to 20-fold fewer sequence reads than the current transcriptomics procedures. TranSeq significantly reduces costs and allows a greater increase in size of sample sets analyzed in a single experiment. Moreover, in comparison with other 3'-end sequencing methods reported to date, we demonstrate here the reliability and immediate applicability of TranSeq and show that it not only provides accurate transcriptome profiles but also produces precise expression measurements of specific gene family members possessing high sequence similarity. This is difficult to achieve in standard RNA-seq methods, in which sequence reads cover the entire transcript. Furthermore, mapping TranSeq reads to the reference tomato genome facilitated the annotation of new transcripts improving >45% of the existing gene models. Hence, we anticipate that using TranSeq will boost large-scale transcriptome assays and increase the spatial and temporal resolution of gene expression data, in both model and non-model plant species. Moreover, as already performed for tomato (ITAG3.0; www.solgenomics.net), we strongly advocate its integration into current and future genome annotations.
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Affiliation(s)
- Oren Tzfadia
- Center for Plant Systems Biology, VIB, Ghent, Belgium
- Department of Plant Biotechnology and Bioinformatics, Ghent University, Ghent, Belgium
- Bioinformatics Institute Ghent, Ghent University, Ghent, Belgium
| | - Samuel Bocobza
- Department of Plant and Environmental Sciences, Weizmann Institute of Science, Rehovot, Israel
| | - Jonas Defoort
- Center for Plant Systems Biology, VIB, Ghent, Belgium
- Department of Plant Biotechnology and Bioinformatics, Ghent University, Ghent, Belgium
- Bioinformatics Institute Ghent, Ghent University, Ghent, Belgium
| | - Efrat Almekias-Siegl
- Department of Plant and Environmental Sciences, Weizmann Institute of Science, Rehovot, Israel
| | - Sayantan Panda
- Department of Plant and Environmental Sciences, Weizmann Institute of Science, Rehovot, Israel
| | - Matan Levy
- Department of Plant and Environmental Sciences, Weizmann Institute of Science, Rehovot, Israel
| | - Veronique Storme
- Center for Plant Systems Biology, VIB, Ghent, Belgium
- Department of Plant Biotechnology and Bioinformatics, Ghent University, Ghent, Belgium
- Bioinformatics Institute Ghent, Ghent University, Ghent, Belgium
| | - Stephane Rombauts
- Center for Plant Systems Biology, VIB, Ghent, Belgium
- Department of Plant Biotechnology and Bioinformatics, Ghent University, Ghent, Belgium
- Bioinformatics Institute Ghent, Ghent University, Ghent, Belgium
| | | | - Hadas Keren-Shaul
- Department of Immunology, Weizmann Institute of Science, Rehovot, Israel
| | - Yves Van de Peer
- Center for Plant Systems Biology, VIB, Ghent, Belgium
- Department of Plant Biotechnology and Bioinformatics, Ghent University, Ghent, Belgium
- Bioinformatics Institute Ghent, Ghent University, Ghent, Belgium
- Genomics Research Institute (GRI), University of Pretoria, Pretoria, 0028, South Africa
| | - Asaph Aharoni
- Department of Plant and Environmental Sciences, Weizmann Institute of Science, Rehovot, Israel
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582
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Lu WY, Forbes SJ. Telomerase Activity Links to Regenerative Capacity of Hepatocytes. Transplantation 2018; 102:1587-1588. [PMID: 30247437 DOI: 10.1097/tp.0000000000002346] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Affiliation(s)
- Wei-Yu Lu
- Centre for Liver and Gastrointestinal Research, University of Birmingham, Birmingham, United Kingdom
| | - Stuart J Forbes
- MRC Centre for Regenerative Medicine, University of Edinburgh, Edinburgh, United Kingdom
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583
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Schaum N, Karkanias J, Neff NF, May AP, Quake SR, Wyss-Coray T, Darmanis S, Batson J, Botvinnik O, Chen MB, Chen S, Green F, Jones R, Maynard A, Penland L, Pisco AO, Sit RV, Stanley GM, Webber JT, Zanini F, Baghel AS, Bakerman I, Bansal I, Berdnik D, Bilen B, Brownfield D, Cain C, Chen MB, Chen S, Cho M, Cirolia G, Conley SD, Darmanis S, Demers A, Demir K, de Morree A, Divita T, du Bois H, Dulgeroff LBT, Ebadi H, Espinoza FH, Fish M, Gan Q, George BM, Gillich A, Green F, Genetiano G, Gu X, Gulati GS, Hang Y, Hosseinzadeh S, Huang A, Iram T, Isobe T, Ives F, Jones R, Kao KS, Karnam G, Kershner AM, Kiss BM, Kong W, Kumar ME, Lam J, Lee DP, Lee SE, Li G, Li Q, Liu L, Lo A, Lu WJ, Manjunath A, May AP, May KL, May OL, Maynard A, McKay M, Metzger RJ, Mignardi M, Min D, Nabhan AN, Neff NF, Ng KM, Noh J, Patkar R, Peng WC, Penland L, Puccinelli R, Rulifson EJ, Schaum N, Sikandar SS, Sinha R, Sit RV, Szade K, Tan W, Tato C, Tellez K, Travaglini KJ, Tropini C, Waldburger L, van Weele LJ, Wosczyna MN, Xiang J, Xue S, Youngyunpipatkul J, Zanini F, Zardeneta ME, Zhang F, Zhou L, Bansal I, Chen S, Cho M, Cirolia G, Darmanis S, Demers A, Divita T, Ebadi H, Genetiano G, Green F, Hosseinzadeh S, Ives F, Lo A, May AP, Maynard A, McKay M, Neff NF, Penland L, Sit RV, Tan W, Waldburger L, oungyunpipatkul JY, Batson J, Botvinnik O, Castro P, Croote D, Darmanis S, DeRisi JL, Karkanias J, Pisco AO, Stanley GM, Webber JT, Zanini F, Baghel AS, Bakerman I, Batson J, Bilen B, Botvinnik O, Brownfield D, Chen MB, Darmanis S, Demir K, de Morree A, Ebadi H, Espinoza FH, Fish M, Gan Q, George BM, Gillich A, Gu X, Gulati GS, Hang Y, Huang A, Iram T, Isobe T, Karnam G, Kershner AM, Kiss BM, Kong W, Kuo CS, Lam J, Lehallier B, Li G, Li Q, Liu L, Lu WJ, Min D, Nabhan AN, Ng KM, Nguyen PK, Patkar R, Peng WC, Penland L, Rulifson EJ, Schaum N, Sikandar SS, Sinha R, Szade K, Tan SY, Tellez K, Travaglini KJ, Tropini C, van Weele LJ, Wang BM, Wosczyna MN, Xiang J, Yousef H, Zhou L, Batson J, Botvinnik O, Chen S, Darmanis S, Green F, May AP, Maynard A, Pisco AO, Quake SR, Schaum N, Stanley GM, Webber JT, Wyss-Coray T, Zanini F, Beachy PA, Chan CKF, de Morree A, George BM, Gulati GS, Hang Y, Huang KC, Iram T, Isobe T, Kershner AM, Kiss BM, Kong W, Li G, Li Q, Liu L, Lu WJ, Nabhan AN, Ng KM, Nguyen PK, Peng WC, Rulifson EJ, Schaum N, Sikandar SS, Sinha R, Szade K, Travaglini KJ, Tropini C, Wang BM, Weinberg K, Wosczyna MN, Wu SM, Yousef H, Barres BA, Beachy PA, Chan CKF, Clarke MF, Darmanis S, Huang KC, Karkanias J, Kim SK, Krasnow MA, Kumar ME, Kuo CS, May AP, Metzger RJ, Neff NF, Nusse R, Nguyen PK, Rando TA, Sonnenburg J, Wang BM, Weinberg K, Weissman IL, Wu SM, Quake SR, Wyss-Coray T. Single-cell transcriptomics of 20 mouse organs creates a Tabula Muris. Nature 2018; 562:367-372. [PMID: 30283141 PMCID: PMC6642641 DOI: 10.1038/s41586-018-0590-4] [Citation(s) in RCA: 1576] [Impact Index Per Article: 262.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2017] [Accepted: 08/20/2018] [Indexed: 12/12/2022]
Abstract
Here we present a compendium of single-cell transcriptomic data from the model organism Mus musculus that comprises more than 100,000 cells from 20 organs and tissues. These data represent a new resource for cell biology, reveal gene expression in poorly characterized cell populations and enable the direct and controlled comparison of gene expression in cell types that are shared between tissues, such as T lymphocytes and endothelial cells from different anatomical locations. Two distinct technical approaches were used for most organs: one approach, microfluidic droplet-based 3'-end counting, enabled the survey of thousands of cells at relatively low coverage, whereas the other, full-length transcript analysis based on fluorescence-activated cell sorting, enabled the characterization of cell types with high sensitivity and coverage. The cumulative data provide the foundation for an atlas of transcriptomic cell biology.
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Affiliation(s)
- Nicholas Schaum
- Institute for Stem Cell Biology and Regenerative Medicine, Stanford University School of Medicine, Stanford, California, USA
| | - Jim Karkanias
- Chan Zuckerberg Biohub, San Francisco, California, USA
| | - Norma F. Neff
- Chan Zuckerberg Biohub, San Francisco, California, USA
| | - Andrew P. May
- Chan Zuckerberg Biohub, San Francisco, California, USA
| | - Stephen R. Quake
- Chan Zuckerberg Biohub, San Francisco, California, USA
- Department of Bioengineering, Stanford University, Stanford, California, USA
| | - Tony Wyss-Coray
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, California, USA
- Paul F. Glenn Center for the Biology of Aging, Stanford University School of Medicine, Stanford, California, USA
- Center for Tissue Regeneration, Repair, and Restoration, V.A. Palo Alto Healthcare System, Palo Alto, California, USA
| | | | - Joshua Batson
- Chan Zuckerberg Biohub, San Francisco, California, USA
| | | | - Michelle B. Chen
- Department of Bioengineering, Stanford University, Stanford, California, USA
| | - Steven Chen
- Chan Zuckerberg Biohub, San Francisco, California, USA
| | - Foad Green
- Chan Zuckerberg Biohub, San Francisco, California, USA
| | - Robert Jones
- Department of Bioengineering, Stanford University, Stanford, California, USA
| | | | | | | | - Rene V. Sit
- Chan Zuckerberg Biohub, San Francisco, California, USA
| | - Geoffrey M. Stanley
- Department of Bioengineering, Stanford University, Stanford, California, USA
| | | | - Fabio Zanini
- Department of Bioengineering, Stanford University, Stanford, California, USA
| | - Ankit S Baghel
- Institute for Stem Cell Biology and Regenerative Medicine, Stanford University School of Medicine, Stanford, California, USA
| | - Isaac Bakerman
- Institute for Stem Cell Biology and Regenerative Medicine, Stanford University School of Medicine, Stanford, California, USA
- Stanford Cardiovascular Institute, Stanford University School of Medicine, Stanford, California, USA
- Department of Medicine, Division of Cardiology, Stanford University School of Medicine, Stanford, California, USA
| | - Ishita Bansal
- Chan Zuckerberg Biohub, San Francisco, California, USA
| | - Daniela Berdnik
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, California, USA
| | - Biter Bilen
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, California, USA
| | - Douglas Brownfield
- Department of Biochemistry, Stanford University School of Medicine, Stanford, California, USA
| | - Corey Cain
- Flow Cytometry Core, V.A. Palo Alto Healthcare System, Palo Alto, California, USA
| | - Michelle B. Chen
- Department of Bioengineering, Stanford University, Stanford, California, USA
| | - Steven Chen
- Chan Zuckerberg Biohub, San Francisco, California, USA
| | - Min Cho
- Chan Zuckerberg Biohub, San Francisco, California, USA
| | - Giana Cirolia
- Chan Zuckerberg Biohub, San Francisco, California, USA
| | - Stephanie D. Conley
- Institute for Stem Cell Biology and Regenerative Medicine, Stanford University School of Medicine, Stanford, California, USA
| | | | - Aaron Demers
- Chan Zuckerberg Biohub, San Francisco, California, USA
| | - Kubilay Demir
- Institute for Stem Cell Biology and Regenerative Medicine, Stanford University School of Medicine, Stanford, California, USA
- Howard Hughes Medical Institute, USA
| | - Antoine de Morree
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, California, USA
| | - Tessa Divita
- Chan Zuckerberg Biohub, San Francisco, California, USA
| | - Haley du Bois
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, California, USA
| | - Laughing Bear Torrez Dulgeroff
- Institute for Stem Cell Biology and Regenerative Medicine, Stanford University School of Medicine, Stanford, California, USA
| | - Hamid Ebadi
- Chan Zuckerberg Biohub, San Francisco, California, USA
| | - F. Hernán Espinoza
- Department of Biochemistry, Stanford University School of Medicine, Stanford, California, USA
| | - Matt Fish
- Institute for Stem Cell Biology and Regenerative Medicine, Stanford University School of Medicine, Stanford, California, USA
- Howard Hughes Medical Institute, USA
- Department of Developmental Biology, Stanford University School of Medicine, Stanford, California, USA
| | - Qiang Gan
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, California, USA
| | - Benson M. George
- Institute for Stem Cell Biology and Regenerative Medicine, Stanford University School of Medicine, Stanford, California, USA
| | - Astrid Gillich
- Department of Biochemistry, Stanford University School of Medicine, Stanford, California, USA
| | - Foad Green
- Chan Zuckerberg Biohub, San Francisco, California, USA
| | | | - Xueying Gu
- Department of Developmental Biology, Stanford University School of Medicine, Stanford, California, USA
| | - Gunsagar S. Gulati
- Institute for Stem Cell Biology and Regenerative Medicine, Stanford University School of Medicine, Stanford, California, USA
| | - Yan Hang
- Department of Developmental Biology, Stanford University School of Medicine, Stanford, California, USA
| | | | - Albin Huang
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, California, USA
| | - Tal Iram
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, California, USA
| | - Taichi Isobe
- Institute for Stem Cell Biology and Regenerative Medicine, Stanford University School of Medicine, Stanford, California, USA
| | - Feather Ives
- Chan Zuckerberg Biohub, San Francisco, California, USA
| | - Robert Jones
- Department of Bioengineering, Stanford University, Stanford, California, USA
| | - Kevin S. Kao
- Institute for Stem Cell Biology and Regenerative Medicine, Stanford University School of Medicine, Stanford, California, USA
| | - Guruswamy Karnam
- Department of Medicine and Liver Center, University of California San Francisco, San Francisco, California, USA
| | - Aaron M. Kershner
- Institute for Stem Cell Biology and Regenerative Medicine, Stanford University School of Medicine, Stanford, California, USA
| | - Bernhard M. Kiss
- Institute for Stem Cell Biology and Regenerative Medicine, Stanford University School of Medicine, Stanford, California, USA
- Department of Urology, Stanford University School of Medicine, Stanford, California, USA
| | - William Kong
- Institute for Stem Cell Biology and Regenerative Medicine, Stanford University School of Medicine, Stanford, California, USA
| | - Maya E. Kumar
- Sean N. Parker Center for Asthma and Allergy Research, Stanford University School of Medicine, Stanford, California, USA
- Department of Medicine, Division of Pulmonary and Critical Care, Stanford University School of Medicine, Stanford, California, USA
| | - Jonathan Lam
- Department of Developmental Biology, Stanford University School of Medicine, Stanford, California, USA
| | - Davis P. Lee
- Center for Tissue Regeneration, Repair, and Restoration, V.A. Palo Alto Healthcare System, Palo Alto, California, USA
| | - Song E. Lee
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, California, USA
| | - Guang Li
- Department of Medicine, Division of Cardiovascular Medicine, Stanford University, Stanford, California, USA
| | - Qingyun Li
- Department of Neurobiology, Stanford University School of Medicine, Stanford, CA USA
| | - Ling Liu
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, California, USA
| | - Annie Lo
- Chan Zuckerberg Biohub, San Francisco, California, USA
| | - Wan-Jin Lu
- Institute for Stem Cell Biology and Regenerative Medicine, Stanford University School of Medicine, Stanford, California, USA
- Department of Biochemistry, Stanford University School of Medicine, Stanford, California, USA
| | - Anoop Manjunath
- Institute for Stem Cell Biology and Regenerative Medicine, Stanford University School of Medicine, Stanford, California, USA
| | - Andrew P. May
- Chan Zuckerberg Biohub, San Francisco, California, USA
| | - Kaia L. May
- Chan Zuckerberg Biohub, San Francisco, California, USA
| | - Oliver L. May
- Chan Zuckerberg Biohub, San Francisco, California, USA
| | | | - Marina McKay
- Chan Zuckerberg Biohub, San Francisco, California, USA
| | - Ross J. Metzger
- Vera Moulton Wall Center for Pulmonary and Vascular Disease, Stanford University School of Medicine, Stanford, California, USA
- Department of Pediatrics, Division of Cardiology, Stanford University School of Medicine, Stanford, California, USA
| | - Marco Mignardi
- Department of Bioengineering, Stanford University, Stanford, California, USA
| | - Dullei Min
- Department of Pediatrics, Stanford University school of Medicine, Stanford, California, USA
| | - Ahmad N. Nabhan
- Department of Biochemistry, Stanford University School of Medicine, Stanford, California, USA
| | - Norma F. Neff
- Chan Zuckerberg Biohub, San Francisco, California, USA
| | - Katharine M. Ng
- Department of Bioengineering, Stanford University, Stanford, California, USA
| | - Joseph Noh
- Institute for Stem Cell Biology and Regenerative Medicine, Stanford University School of Medicine, Stanford, California, USA
| | - Rasika Patkar
- Department of Medicine and Liver Center, University of California San Francisco, San Francisco, California, USA
| | - Weng Chuan Peng
- Department of Developmental Biology, Stanford University School of Medicine, Stanford, California, USA
| | | | | | - Eric J. Rulifson
- Department of Developmental Biology, Stanford University School of Medicine, Stanford, California, USA
| | - Nicholas Schaum
- Institute for Stem Cell Biology and Regenerative Medicine, Stanford University School of Medicine, Stanford, California, USA
| | - Shaheen S. Sikandar
- Institute for Stem Cell Biology and Regenerative Medicine, Stanford University School of Medicine, Stanford, California, USA
| | - Rahul Sinha
- Institute for Stem Cell Biology and Regenerative Medicine, Stanford University School of Medicine, Stanford, California, USA
- Department of Pathology, Stanford University School of Medicine, Stanford, California, USA
- Ludwig Center for Cancer Stem Cell Research and Medicine, Stanford University School of Medicine, Stanford, California, USA
- Stanford Cancer Institute, Stanford University School of Medicine, Stanford, California, USA
| | - Rene V. Sit
- Chan Zuckerberg Biohub, San Francisco, California, USA
| | - Krzysztof Szade
- Institute for Stem Cell Biology and Regenerative Medicine, Stanford University School of Medicine, Stanford, California, USA
- Department of Medical Biotechnology, Faculty of Biophysics, Biochemistry and Biotechnology, Jagiellonian University, Poland
| | - Weilun Tan
- Chan Zuckerberg Biohub, San Francisco, California, USA
| | - Cristina Tato
- Chan Zuckerberg Biohub, San Francisco, California, USA
| | - Krissie Tellez
- Department of Developmental Biology, Stanford University School of Medicine, Stanford, California, USA
| | - Kyle J. Travaglini
- Department of Biochemistry, Stanford University School of Medicine, Stanford, California, USA
| | - Carolina Tropini
- Department of Microbiology & Immunology, Stanford University School of Medicine, Stanford, California, USA
| | | | - Linda J. van Weele
- Institute for Stem Cell Biology and Regenerative Medicine, Stanford University School of Medicine, Stanford, California, USA
| | - Michael N. Wosczyna
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, California, USA
| | - Jinyi Xiang
- Institute for Stem Cell Biology and Regenerative Medicine, Stanford University School of Medicine, Stanford, California, USA
| | - Soso Xue
- Department of Bioengineering, Stanford University, Stanford, California, USA
| | | | - Fabio Zanini
- Department of Bioengineering, Stanford University, Stanford, California, USA
| | - Macy E. Zardeneta
- Center for Tissue Regeneration, Repair, and Restoration, V.A. Palo Alto Healthcare System, Palo Alto, California, USA
| | - Fan Zhang
- Vera Moulton Wall Center for Pulmonary and Vascular Disease, Stanford University School of Medicine, Stanford, California, USA
- Department of Pediatrics, Division of Cardiology, Stanford University School of Medicine, Stanford, California, USA
| | - Lu Zhou
- Department of Neurobiology, Stanford University School of Medicine, Stanford, CA USA
| | - Ishita Bansal
- Chan Zuckerberg Biohub, San Francisco, California, USA
| | - Steven Chen
- Chan Zuckerberg Biohub, San Francisco, California, USA
| | - Min Cho
- Chan Zuckerberg Biohub, San Francisco, California, USA
| | - Giana Cirolia
- Chan Zuckerberg Biohub, San Francisco, California, USA
| | | | - Aaron Demers
- Chan Zuckerberg Biohub, San Francisco, California, USA
| | - Tessa Divita
- Chan Zuckerberg Biohub, San Francisco, California, USA
| | - Hamid Ebadi
- Chan Zuckerberg Biohub, San Francisco, California, USA
| | | | - Foad Green
- Chan Zuckerberg Biohub, San Francisco, California, USA
| | | | - Feather Ives
- Chan Zuckerberg Biohub, San Francisco, California, USA
| | - Annie Lo
- Chan Zuckerberg Biohub, San Francisco, California, USA
| | - Andrew P. May
- Chan Zuckerberg Biohub, San Francisco, California, USA
| | | | - Marina McKay
- Chan Zuckerberg Biohub, San Francisco, California, USA
| | - Norma F. Neff
- Chan Zuckerberg Biohub, San Francisco, California, USA
| | | | - Rene V. Sit
- Chan Zuckerberg Biohub, San Francisco, California, USA
| | - Weilun Tan
- Chan Zuckerberg Biohub, San Francisco, California, USA
| | | | | | - Joshua Batson
- Chan Zuckerberg Biohub, San Francisco, California, USA
| | | | - Paola Castro
- Chan Zuckerberg Biohub, San Francisco, California, USA
| | - Derek Croote
- Department of Bioengineering, Stanford University, Stanford, California, USA
| | | | - Joseph L. DeRisi
- Chan Zuckerberg Biohub, San Francisco, California, USA
- Department of Biochemistry and Biophysics, University of California San Francisco, San Francisco, California USA
| | - Jim Karkanias
- Chan Zuckerberg Biohub, San Francisco, California, USA
| | | | - Geoffrey M. Stanley
- Department of Bioengineering, Stanford University, Stanford, California, USA
| | | | - Fabio Zanini
- Department of Bioengineering, Stanford University, Stanford, California, USA
| | - Ankit S. Baghel
- Institute for Stem Cell Biology and Regenerative Medicine, Stanford University School of Medicine, Stanford, California, USA
| | - Isaac Bakerman
- Institute for Stem Cell Biology and Regenerative Medicine, Stanford University School of Medicine, Stanford, California, USA
- Stanford Cardiovascular Institute, Stanford University School of Medicine, Stanford, California, USA
- Department of Medicine, Division of Cardiology, Stanford University School of Medicine, Stanford, California, USA
| | - Joshua Batson
- Chan Zuckerberg Biohub, San Francisco, California, USA
| | - Biter Bilen
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, California, USA
| | | | - Douglas Brownfield
- Department of Biochemistry, Stanford University School of Medicine, Stanford, California, USA
| | - Michelle B. Chen
- Department of Bioengineering, Stanford University, Stanford, California, USA
| | | | - Kubilay Demir
- Institute for Stem Cell Biology and Regenerative Medicine, Stanford University School of Medicine, Stanford, California, USA
- Howard Hughes Medical Institute, USA
| | - Antoine de Morree
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, California, USA
| | - Hamid Ebadi
- Chan Zuckerberg Biohub, San Francisco, California, USA
| | - F. Hernán Espinoza
- Department of Biochemistry, Stanford University School of Medicine, Stanford, California, USA
| | - Matt Fish
- Institute for Stem Cell Biology and Regenerative Medicine, Stanford University School of Medicine, Stanford, California, USA
- Howard Hughes Medical Institute, USA
- Department of Developmental Biology, Stanford University School of Medicine, Stanford, California, USA
| | - Qiang Gan
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, California, USA
| | - Benson M. George
- Institute for Stem Cell Biology and Regenerative Medicine, Stanford University School of Medicine, Stanford, California, USA
| | - Astrid Gillich
- Department of Biochemistry, Stanford University School of Medicine, Stanford, California, USA
| | - Xueying Gu
- Department of Developmental Biology, Stanford University School of Medicine, Stanford, California, USA
| | - Gunsagar S. Gulati
- Institute for Stem Cell Biology and Regenerative Medicine, Stanford University School of Medicine, Stanford, California, USA
| | - Yan Hang
- Department of Developmental Biology, Stanford University School of Medicine, Stanford, California, USA
| | - Albin Huang
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, California, USA
| | - Tal Iram
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, California, USA
| | - Taichi Isobe
- Institute for Stem Cell Biology and Regenerative Medicine, Stanford University School of Medicine, Stanford, California, USA
| | - Guruswamy Karnam
- Department of Medicine and Liver Center, University of California San Francisco, San Francisco, California, USA
| | - Aaron M. Kershner
- Institute for Stem Cell Biology and Regenerative Medicine, Stanford University School of Medicine, Stanford, California, USA
| | - Bernhard M. Kiss
- Institute for Stem Cell Biology and Regenerative Medicine, Stanford University School of Medicine, Stanford, California, USA
- Department of Urology, Stanford University School of Medicine, Stanford, California, USA
| | - William Kong
- Institute for Stem Cell Biology and Regenerative Medicine, Stanford University School of Medicine, Stanford, California, USA
| | - Christin S. Kuo
- Department of Biochemistry, Stanford University School of Medicine, Stanford, California, USA
- Howard Hughes Medical Institute, USA
- Department of Pediatrics, Stanford University school of Medicine, Stanford, California, USA
| | - Jonathan Lam
- Department of Developmental Biology, Stanford University School of Medicine, Stanford, California, USA
| | - Benoit Lehallier
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, California, USA
| | - Guang Li
- Department of Medicine, Division of Cardiovascular Medicine, Stanford University, Stanford, California, USA
| | - Qingyun Li
- Department of Neurobiology, Stanford University School of Medicine, Stanford, CA USA
| | - Ling Liu
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, California, USA
| | - Wan-Jin Lu
- Institute for Stem Cell Biology and Regenerative Medicine, Stanford University School of Medicine, Stanford, California, USA
- Department of Biochemistry, Stanford University School of Medicine, Stanford, California, USA
| | - Dullei Min
- Department of Pediatrics, Stanford University school of Medicine, Stanford, California, USA
| | - Ahmad N. Nabhan
- Department of Biochemistry, Stanford University School of Medicine, Stanford, California, USA
| | - Katharine M. Ng
- Department of Bioengineering, Stanford University, Stanford, California, USA
| | - Patricia K. Nguyen
- Institute for Stem Cell Biology and Regenerative Medicine, Stanford University School of Medicine, Stanford, California, USA
- Stanford Cardiovascular Institute, Stanford University School of Medicine, Stanford, California, USA
- Department of Medicine, Division of Cardiology, Stanford University School of Medicine, Stanford, California, USA
- Department of Medicine, Division of Cardiovascular Medicine, Stanford University, Stanford, California, USA
| | - Rasika Patkar
- Department of Medicine and Liver Center, University of California San Francisco, San Francisco, California, USA
| | - Weng Chuan Peng
- Department of Developmental Biology, Stanford University School of Medicine, Stanford, California, USA
| | | | - Eric J. Rulifson
- Department of Developmental Biology, Stanford University School of Medicine, Stanford, California, USA
| | - Nicholas Schaum
- Institute for Stem Cell Biology and Regenerative Medicine, Stanford University School of Medicine, Stanford, California, USA
| | - Shaheen S. Sikandar
- Institute for Stem Cell Biology and Regenerative Medicine, Stanford University School of Medicine, Stanford, California, USA
| | - Rahul Sinha
- Institute for Stem Cell Biology and Regenerative Medicine, Stanford University School of Medicine, Stanford, California, USA
- Department of Pathology, Stanford University School of Medicine, Stanford, California, USA
- Ludwig Center for Cancer Stem Cell Research and Medicine, Stanford University School of Medicine, Stanford, California, USA
- Stanford Cancer Institute, Stanford University School of Medicine, Stanford, California, USA
| | - Krzysztof Szade
- Institute for Stem Cell Biology and Regenerative Medicine, Stanford University School of Medicine, Stanford, California, USA
- Department of Medical Biotechnology, Faculty of Biophysics, Biochemistry and Biotechnology, Jagiellonian University, Poland
| | - Serena Y. Tan
- Department of Pathology, Stanford University School of Medicine, Stanford, California, USA
| | - Krissie Tellez
- Department of Developmental Biology, Stanford University School of Medicine, Stanford, California, USA
| | - Kyle J. Travaglini
- Department of Biochemistry, Stanford University School of Medicine, Stanford, California, USA
| | - Carolina Tropini
- Department of Microbiology & Immunology, Stanford University School of Medicine, Stanford, California, USA
| | - Linda J. van Weele
- Institute for Stem Cell Biology and Regenerative Medicine, Stanford University School of Medicine, Stanford, California, USA
| | - Bruce M. Wang
- Department of Medicine and Liver Center, University of California San Francisco, San Francisco, California, USA
| | - Michael N. Wosczyna
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, California, USA
| | - Jinyi Xiang
- Institute for Stem Cell Biology and Regenerative Medicine, Stanford University School of Medicine, Stanford, California, USA
| | - Hanadie Yousef
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, California, USA
| | - Lu Zhou
- Department of Neurobiology, Stanford University School of Medicine, Stanford, CA USA
| | - Joshua Batson
- Chan Zuckerberg Biohub, San Francisco, California, USA
| | | | - Steven Chen
- Chan Zuckerberg Biohub, San Francisco, California, USA
| | | | - Foad Green
- Chan Zuckerberg Biohub, San Francisco, California, USA
| | - Andrew P. May
- Chan Zuckerberg Biohub, San Francisco, California, USA
| | | | | | - Stephen R. Quake
- Chan Zuckerberg Biohub, San Francisco, California, USA
- Department of Bioengineering, Stanford University, Stanford, California, USA
| | - Nicholas Schaum
- Institute for Stem Cell Biology and Regenerative Medicine, Stanford University School of Medicine, Stanford, California, USA
| | - Geoffrey M. Stanley
- Department of Bioengineering, Stanford University, Stanford, California, USA
| | | | - Tony Wyss-Coray
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, California, USA
- Paul F. Glenn Center for the Biology of Aging, Stanford University School of Medicine, Stanford, California, USA
- Center for Tissue Regeneration, Repair, and Restoration, V.A. Palo Alto Healthcare System, Palo Alto, California, USA
| | - Fabio Zanini
- Department of Bioengineering, Stanford University, Stanford, California, USA
| | - Philip A. Beachy
- Institute for Stem Cell Biology and Regenerative Medicine, Stanford University School of Medicine, Stanford, California, USA
- Department of Biochemistry, Stanford University School of Medicine, Stanford, California, USA
- Howard Hughes Medical Institute, USA
- Department of Developmental Biology, Stanford University School of Medicine, Stanford, California, USA
| | - Charles K. F. Chan
- Department of Surgery, Division of Plastic and Reconstructive Surgery, Stanford University, Stanford, California USA
| | - Antoine de Morree
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, California, USA
| | - Benson M. George
- Institute for Stem Cell Biology and Regenerative Medicine, Stanford University School of Medicine, Stanford, California, USA
| | - Gunsagar S. Gulati
- Institute for Stem Cell Biology and Regenerative Medicine, Stanford University School of Medicine, Stanford, California, USA
| | - Yan Hang
- Department of Developmental Biology, Stanford University School of Medicine, Stanford, California, USA
| | - Kerwyn Casey Huang
- Chan Zuckerberg Biohub, San Francisco, California, USA
- Department of Bioengineering, Stanford University, Stanford, California, USA
- Department of Microbiology & Immunology, Stanford University School of Medicine, Stanford, California, USA
| | - Tal Iram
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, California, USA
| | - Taichi Isobe
- Institute for Stem Cell Biology and Regenerative Medicine, Stanford University School of Medicine, Stanford, California, USA
| | - Aaron M. Kershner
- Institute for Stem Cell Biology and Regenerative Medicine, Stanford University School of Medicine, Stanford, California, USA
| | - Bernhard M. Kiss
- Institute for Stem Cell Biology and Regenerative Medicine, Stanford University School of Medicine, Stanford, California, USA
- Department of Urology, Stanford University School of Medicine, Stanford, California, USA
| | - William Kong
- Institute for Stem Cell Biology and Regenerative Medicine, Stanford University School of Medicine, Stanford, California, USA
| | - Guang Li
- Department of Medicine, Division of Cardiovascular Medicine, Stanford University, Stanford, California, USA
| | - Qingyun Li
- Department of Neurobiology, Stanford University School of Medicine, Stanford, CA USA
| | - Ling Liu
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, California, USA
| | - Wan-Jin Lu
- Institute for Stem Cell Biology and Regenerative Medicine, Stanford University School of Medicine, Stanford, California, USA
- Department of Biochemistry, Stanford University School of Medicine, Stanford, California, USA
| | - Ahmad N. Nabhan
- Department of Biochemistry, Stanford University School of Medicine, Stanford, California, USA
| | - Katharine M. Ng
- Department of Bioengineering, Stanford University, Stanford, California, USA
| | - Patricia K. Nguyen
- Institute for Stem Cell Biology and Regenerative Medicine, Stanford University School of Medicine, Stanford, California, USA
- Stanford Cardiovascular Institute, Stanford University School of Medicine, Stanford, California, USA
- Department of Medicine, Division of Cardiology, Stanford University School of Medicine, Stanford, California, USA
- Department of Medicine, Division of Cardiovascular Medicine, Stanford University, Stanford, California, USA
| | - Weng Chuan Peng
- Department of Developmental Biology, Stanford University School of Medicine, Stanford, California, USA
| | - Eric J. Rulifson
- Department of Developmental Biology, Stanford University School of Medicine, Stanford, California, USA
| | - Nicholas Schaum
- Institute for Stem Cell Biology and Regenerative Medicine, Stanford University School of Medicine, Stanford, California, USA
| | - Shaheen S. Sikandar
- Institute for Stem Cell Biology and Regenerative Medicine, Stanford University School of Medicine, Stanford, California, USA
| | - Rahul Sinha
- Institute for Stem Cell Biology and Regenerative Medicine, Stanford University School of Medicine, Stanford, California, USA
- Department of Pathology, Stanford University School of Medicine, Stanford, California, USA
- Ludwig Center for Cancer Stem Cell Research and Medicine, Stanford University School of Medicine, Stanford, California, USA
- Stanford Cancer Institute, Stanford University School of Medicine, Stanford, California, USA
| | - Krzysztof Szade
- Institute for Stem Cell Biology and Regenerative Medicine, Stanford University School of Medicine, Stanford, California, USA
- Department of Medical Biotechnology, Faculty of Biophysics, Biochemistry and Biotechnology, Jagiellonian University, Poland
| | - Kyle J. Travaglini
- Department of Biochemistry, Stanford University School of Medicine, Stanford, California, USA
| | - Carolina Tropini
- Department of Microbiology & Immunology, Stanford University School of Medicine, Stanford, California, USA
| | - Bruce M. Wang
- Department of Medicine and Liver Center, University of California San Francisco, San Francisco, California, USA
| | - Kenneth Weinberg
- Department of Pediatrics, Stanford University school of Medicine, Stanford, California, USA
| | - Michael N. Wosczyna
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, California, USA
| | - Sean M. Wu
- Department of Medicine, Division of Cardiovascular Medicine, Stanford University, Stanford, California, USA
| | - Hanadie Yousef
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, California, USA
| | - Ben A. Barres
- Department of Neurobiology, Stanford University School of Medicine, Stanford, CA USA
| | - Philip A. Beachy
- Institute for Stem Cell Biology and Regenerative Medicine, Stanford University School of Medicine, Stanford, California, USA
- Department of Biochemistry, Stanford University School of Medicine, Stanford, California, USA
- Howard Hughes Medical Institute, USA
- Department of Developmental Biology, Stanford University School of Medicine, Stanford, California, USA
| | - Charles K. F. Chan
- Department of Surgery, Division of Plastic and Reconstructive Surgery, Stanford University, Stanford, California USA
| | - Michael F. Clarke
- Institute for Stem Cell Biology and Regenerative Medicine, Stanford University School of Medicine, Stanford, California, USA
| | | | - Kerwyn Casey Huang
- Chan Zuckerberg Biohub, San Francisco, California, USA
- Department of Bioengineering, Stanford University, Stanford, California, USA
- Department of Microbiology & Immunology, Stanford University School of Medicine, Stanford, California, USA
| | - Jim Karkanias
- Chan Zuckerberg Biohub, San Francisco, California, USA
| | - Seung K. Kim
- Department of Developmental Biology, Stanford University School of Medicine, Stanford, California, USA
- Department of Medicine and Stanford Diabetes Research Center, Stanford University, Stanford, California USA
| | - Mark A. Krasnow
- Department of Biochemistry, Stanford University School of Medicine, Stanford, California, USA
- Howard Hughes Medical Institute, USA
| | - Maya E. Kumar
- Sean N. Parker Center for Asthma and Allergy Research, Stanford University School of Medicine, Stanford, California, USA
- Department of Medicine, Division of Pulmonary and Critical Care, Stanford University School of Medicine, Stanford, California, USA
| | - Christin S. Kuo
- Department of Biochemistry, Stanford University School of Medicine, Stanford, California, USA
- Howard Hughes Medical Institute, USA
- Department of Pediatrics, Stanford University school of Medicine, Stanford, California, USA
| | - Andrew P. May
- Chan Zuckerberg Biohub, San Francisco, California, USA
| | - Ross J. Metzger
- Vera Moulton Wall Center for Pulmonary and Vascular Disease, Stanford University School of Medicine, Stanford, California, USA
- Department of Pediatrics, Division of Cardiology, Stanford University School of Medicine, Stanford, California, USA
| | - Norma F. Neff
- Chan Zuckerberg Biohub, San Francisco, California, USA
| | - Roel Nusse
- Department of Biochemistry, Stanford University School of Medicine, Stanford, California, USA
- Howard Hughes Medical Institute, USA
- Department of Developmental Biology, Stanford University School of Medicine, Stanford, California, USA
| | - Patricia K. Nguyen
- Institute for Stem Cell Biology and Regenerative Medicine, Stanford University School of Medicine, Stanford, California, USA
- Stanford Cardiovascular Institute, Stanford University School of Medicine, Stanford, California, USA
- Department of Medicine, Division of Cardiology, Stanford University School of Medicine, Stanford, California, USA
- Department of Medicine, Division of Cardiovascular Medicine, Stanford University, Stanford, California, USA
| | - Thomas A. Rando
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, California, USA
- Paul F. Glenn Center for the Biology of Aging, Stanford University School of Medicine, Stanford, California, USA
- Center for Tissue Regeneration, Repair, and Restoration, V.A. Palo Alto Healthcare System, Palo Alto, California, USA
| | - Justin Sonnenburg
- Department of Microbiology & Immunology, Stanford University School of Medicine, Stanford, California, USA
| | - Bruce M. Wang
- Department of Medicine and Liver Center, University of California San Francisco, San Francisco, California, USA
| | - Kenneth Weinberg
- Department of Pediatrics, Stanford University school of Medicine, Stanford, California, USA
| | - Irving L. Weissman
- Institute for Stem Cell Biology and Regenerative Medicine, Stanford University School of Medicine, Stanford, California, USA
- Department of Pathology, Stanford University School of Medicine, Stanford, California, USA
- Ludwig Center for Cancer Stem Cell Research and Medicine, Stanford University School of Medicine, Stanford, California, USA
- Stanford Cancer Institute, Stanford University School of Medicine, Stanford, California, USA
| | - Sean M. Wu
- Institute for Stem Cell Biology and Regenerative Medicine, Stanford University School of Medicine, Stanford, California, USA
- Stanford Cardiovascular Institute, Stanford University School of Medicine, Stanford, California, USA
- Department of Medicine, Division of Cardiovascular Medicine, Stanford University, Stanford, California, USA
| | - Stephen R. Quake
- Chan Zuckerberg Biohub, San Francisco, California, USA
- Department of Bioengineering, Stanford University, Stanford, California, USA
| | - Tony Wyss-Coray
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, California, USA
- Paul F. Glenn Center for the Biology of Aging, Stanford University School of Medicine, Stanford, California, USA
- Center for Tissue Regeneration, Repair, and Restoration, V.A. Palo Alto Healthcare System, Palo Alto, California, USA
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584
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Moor AE, Harnik Y, Ben-Moshe S, Massasa EE, Rozenberg M, Eilam R, Bahar Halpern K, Itzkovitz S. Spatial Reconstruction of Single Enterocytes Uncovers Broad Zonation along the Intestinal Villus Axis. Cell 2018; 175:1156-1167.e15. [PMID: 30270040 DOI: 10.1016/j.cell.2018.08.063] [Citation(s) in RCA: 242] [Impact Index Per Article: 40.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2018] [Revised: 07/29/2018] [Accepted: 08/29/2018] [Indexed: 12/24/2022]
Abstract
The intestinal epithelium is a highly structured tissue composed of repeating crypt-villus units. Enterocytes perform the diverse tasks of absorbing a wide range of nutrients while protecting the body from the harsh bacterium-rich environment. It is unknown whether these tasks are spatially zonated along the villus axis. Here, we extracted a large panel of landmark genes characterized by transcriptomics of laser capture microdissected villus segments and utilized it for single-cell spatial reconstruction, uncovering broad zonation of enterocyte function along the villus. We found that enterocytes at villus bottoms express an anti-bacterial gene program in a microbiome-dependent manner. They next shift to sequential expression of carbohydrates, peptides, and fat absorption machineries in distinct villus compartments. Finally, they induce a Cd73 immune-modulatory program at the villus tips. Our approach can be used to uncover zonation patterns in other organs when prior knowledge of landmark genes is lacking.
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Affiliation(s)
- Andreas E Moor
- Department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot, Israel.
| | - Yotam Harnik
- Department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot, Israel
| | - Shani Ben-Moshe
- Department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot, Israel
| | - Efi E Massasa
- Department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot, Israel
| | - Milena Rozenberg
- Department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot, Israel
| | - Raya Eilam
- Department of Veterinary Resources, Weizmann Institute of Science, Rehovot, Israel
| | - Keren Bahar Halpern
- Department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot, Israel
| | - Shalev Itzkovitz
- Department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot, Israel.
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585
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Kaserman JE, Wilson AA. Patient-Derived Induced Pluripotent Stem Cells for Alpha-1 Antitrypsin Deficiency Disease Modeling and Therapeutic Discovery. CHRONIC OBSTRUCTIVE PULMONARY DISEASES-JOURNAL OF THE COPD FOUNDATION 2018; 5:258-266. [PMID: 30723783 DOI: 10.15326/jcopdf.5.4.2017.0179] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
Abstract
PIZZ alpha-1 antitrypsin deficiency (AATD) is an autosomal recessive disease affecting approximately 100,000 individuals in the United States and one of the most common hereditary causes of liver disease.1 The most common form of the disease results from a single base pair mutation (Glu342Lys), known as the "Z" mutation, that encodes a mutant protein (Z alpha-1 antritypsin [AAT]) that is prone to misfolding and is retained in the endoplasmic reticulum (ER) rather than appropriately secreted. Some of the retained mutant protein attains an unusual aggregated or polymerized conformation. Retained polymeric ZAAT aggregates are hepatotoxic and lead to downstream liver disease in a subset of PiZZ neonates and adults through a gain-of-function mechanism. PiZZ individuals are likewise highly predisposed to developing chronic obstructive pulmonary disease (COPD)/emphysema as a result of low circulating levels of AAT protein and associated protease-antiprotease imbalance. Much of our understanding of the molecular pathogenesis of AATD is based on studies employing either transgenic mice that express the mutant human Z allele or immortalized cell lines transduced to overexpress ZAAT. While they have been quite informative, these models fail to capture the patient-to-patient variability in disease phenotype that clinicians observe in their AATD patients, raising the question of whether alternative models might provide new insight. Induced pluripotent stem cells (iPSCs), first described in 2006, have the capacity to differentiate into a broad array of cell types from all 3 germ layers, including hepatocytes. Disease-specific iPSCs have been derived from patients with a variety of monogenic disorders and have been found to faithfully recapitulate features of such diseases as spinal muscular atrophy, familial dysautonomia, Rett syndrome, polycythemia vera, type 1A glycogen storage disease, familial hypercholesterolemia, long QT syndrome, and others. This discussion reviews the potential applications of iPSCs for understanding AATD-associated liver disease as well as for development of potential therapeutic strategies.
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Affiliation(s)
- Joseph E Kaserman
- Center for Regenerative Medicine of Boston University and Boston Medical Center, Boston, Massachusetts
| | - Andrew A Wilson
- Center for Regenerative Medicine of Boston University and Boston Medical Center, Boston, Massachusetts
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586
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Yang L, Li LC, Wang X, Wang WH, Wang YC, Xu CR. The contributions of mesoderm-derived cells in liver development. Semin Cell Dev Biol 2018; 92:63-76. [PMID: 30193996 DOI: 10.1016/j.semcdb.2018.09.003] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2018] [Revised: 08/31/2018] [Accepted: 09/02/2018] [Indexed: 02/07/2023]
Abstract
The liver is an indispensable organ for metabolism and drug detoxification. The liver consists of endoderm-derived hepatobiliary lineages and various mesoderm-derived cells, and interacts with the surrounding tissues and organs through the ventral mesentery. Liver development, from hepatic specification to liver maturation, requires close interactions with mesoderm-derived cells, such as mesothelial cells, hepatic stellate cells, mesenchymal cells, liver sinusoidal endothelial cells and hematopoietic cells. These cells affect liver development through precise signaling events and even direct physical contact. Through the use of new techniques, emerging studies have recently led to a deeper understanding of liver development and its related mechanisms, especially the roles of mesodermal cells in liver development. Based on these developments, the current protocols for in vitro hepatocyte-like cell induction and liver-like tissue construction have been optimized and are of great importance for the treatment of liver diseases. Here, we review the roles of mesoderm-derived cells in the processes of liver development, hepatocyte-like cell induction and liver-like tissue construction.
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Affiliation(s)
- Li Yang
- Ministry of Education Key Laboratory of Cell Proliferation and Differentiation, College of Life Sciences, Peking-Tsinghua Center for Life Sciences, China; Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, 100871, China
| | - Lin-Chen Li
- Ministry of Education Key Laboratory of Cell Proliferation and Differentiation, College of Life Sciences, Peking-Tsinghua Center for Life Sciences, China; Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, 100871, China
| | - Xin Wang
- Ministry of Education Key Laboratory of Cell Proliferation and Differentiation, College of Life Sciences, Peking-Tsinghua Center for Life Sciences, China
| | - Wei-Hua Wang
- Ministry of Education Key Laboratory of Cell Proliferation and Differentiation, College of Life Sciences, Peking-Tsinghua Center for Life Sciences, China; Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, 100871, China
| | - Yan-Chun Wang
- Haidian Maternal & Child Health Hospital, Beijing, 100080, China
| | - Cheng-Ran Xu
- Ministry of Education Key Laboratory of Cell Proliferation and Differentiation, College of Life Sciences, Peking-Tsinghua Center for Life Sciences, China.
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587
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Tam PKH, Yiu RS, Lendahl U, Andersson ER. Cholangiopathies - Towards a molecular understanding. EBioMedicine 2018; 35:381-393. [PMID: 30236451 PMCID: PMC6161480 DOI: 10.1016/j.ebiom.2018.08.024] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2018] [Revised: 08/06/2018] [Accepted: 08/09/2018] [Indexed: 12/14/2022] Open
Abstract
Liver diseases constitute an important medical problem, and a number of these diseases, termed cholangiopathies, affect the biliary system of the liver. In this review, we describe the current understanding of the causes of cholangiopathies, which can be genetic, viral or environmental, and the few treatment options that are currently available beyond liver transplantation. We then discuss recent rapid progress in a number of areas relevant for decoding the disease mechanisms for cholangiopathies. This includes novel data from analysis of transgenic mouse models and organoid systems, and we outline how this information can be used for disease modeling and potential development of novel therapy concepts. We also describe recent advances in genomic and transcriptomic analyses and the importance of such studies for improving diagnosis and determining whether certain cholangiopathies should be viewed as distinct or overlapping disease entities.
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Affiliation(s)
- Paul K H Tam
- Department of Surgery, Li Ka Shing Faculty of Medicine, and Dr. Li Dak-Sum Research Centre, The University of Hong Kong - Karolinska Institutet Collaboration in Regenerative Medicine, and The University of Hong Kong, Hong Kong.
| | - Rachel S Yiu
- Department of Surgery, Li Ka Shing Faculty of Medicine, and Dr. Li Dak-Sum Research Centre, The University of Hong Kong - Karolinska Institutet Collaboration in Regenerative Medicine, and The University of Hong Kong, Hong Kong
| | - Urban Lendahl
- Department of Cell and Molecular Biology, Karolinska Institute, Stockholm, Sweden
| | - Emma R Andersson
- Department of Cell and Molecular Biology, Karolinska Institute, Stockholm, Sweden; Department of Biosciences and Nutrition, Karolinska Institute, Huddinge, Sweden.
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588
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Farack L, Egozi A, Itzkovitz S. Single molecule approaches for studying gene regulation in metabolic tissues. Diabetes Obes Metab 2018; 20 Suppl 2:145-156. [PMID: 30230176 DOI: 10.1111/dom.13390] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/17/2018] [Revised: 05/16/2018] [Accepted: 05/30/2018] [Indexed: 12/25/2022]
Abstract
Gene expression in metabolic tissues can be regulated at multiple levels, ranging from the control of promoter accessibilities, transcription rates, mRNA degradation rates and mRNA localization. Modulating these processes can differentially affect important performance criteria of cells. These include precision, cellular economy, rapid response and maintenance of DNA integrity. In this review we will describe how distinct strategies of gene regulation impact the trade-offs between the cells' performance criteria. We will highlight tools based on single molecule visualization of transcripts that can be used to measure promoter states, transcription rates and mRNA degradation rates in intact tissues. These approaches revealed surprising recurrent patterns in mammalian tissues, that include transcriptional bursting, nuclear retention of mRNA, and coordination of mRNA lifetimes to facilitate rapid adaptation to changing metabolic inputs. The ability to characterize gene expression at the single molecule level can uncover the design principles of gene regulation in metabolic tissues such as the liver and the pancreas.
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Affiliation(s)
- Lydia Farack
- Department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot, Israel
| | - Adi Egozi
- Department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot, Israel
| | - Shalev Itzkovitz
- Department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot, Israel
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589
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Nault JC, Couchy G, Caruso S, Meunier L, Caruana L, Letouzé E, Rebouissou S, Paradis V, Calderaro J, Zucman-Rossi J. Argininosuccinate synthase 1 and periportal gene expression in sonic hedgehog hepatocellular adenomas. Hepatology 2018; 68:964-976. [PMID: 29572896 DOI: 10.1002/hep.29884] [Citation(s) in RCA: 33] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/05/2017] [Revised: 01/29/2018] [Accepted: 02/28/2018] [Indexed: 12/25/2022]
Abstract
UNLABELLED Genetic alterations define different molecular subclasses of hepatocellular adenoma (HCA) linked with risk factors, histology and clinical behavior. Recently, Argininosuccinate Synthase 1 (ASS1), a major periportal protein, was proposed as a marker of HCA with a high risk of hemorrhage. We aimed to assess the significance of ASS1 expression through the scope of the HCA molecular classification. ASS1 expression was evaluated using RNAseq, quantitative reverse transcriptase polymerase chain reaction (RT-PCR) and Immunohistochemistry. ASS1 and glioma-associated oncogene 1 (GLI1) expression were analyzed in vitro after modulation of GLI1 expression. Using RNAseq in 27 HCA and five nontumor liver samples, ASS1 expression was highly correlated with GLI1 expression (P<0.0001, R=0.75). In the overall series of 408 HCA, ASS1 overexpression was significantly associated with sonic hedgehog HCA (shHCA) compared to other molecular subgroups (P<0.0001), suggesting that sonic hedgehog signaling controls ASS1 expression. GLI1 expression silencing by siRNA induced a downregulation of ASS1 in PLC/PFR5 and SNU878 cell lines. In 390 HCA, we showed that ASS1 expression belonged to the periportal expression program that was maintained in shHCA but down-regulated in all the other HCA subtypes. In contrast, HCA with β-catenin activation showed an activation of a perivenous program. Despite the significant association between GLI1 and ASS1 expression, ASS1 mRNA expression was not associated with specific clinical features. At the protein level using immunohistochemistry, prostaglandin D synthase (PTGDS) was strongly and specifically overexpressed in shHCA. CONCLUSION ASS1 is associated with sonic hedgehog activation as part of a periportal program expressed in shHCA, a molecular subgroup defined by INHBE-GLI1 gene fusion. (Hepatology 2018).
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Affiliation(s)
- Jean-Charles Nault
- Inserm UMR-1162, Génomique fonctionnelle des Tumeurs solides, Université Paris Descartes, Université Paris Diderot, Université Paris 13, Labex Immuno-Oncology, Paris, France.,Liver unit, Hôpital Jean Verdier, Hôpitaux Universitaires Paris-Seine-Saint-Denis, Assistance-Publique Hôpitaux de Paris, APHP, Bondy, France.,Unité de Formation et de Recherche Santé Médecine et Biologie Humaine, Université Paris 13, Communauté d'Universités et Etablissements Sorbonne Paris Cité, Paris, France
| | - Gabrielle Couchy
- Inserm UMR-1162, Génomique fonctionnelle des Tumeurs solides, Université Paris Descartes, Université Paris Diderot, Université Paris 13, Labex Immuno-Oncology, Paris, France
| | - Stefano Caruso
- Inserm UMR-1162, Génomique fonctionnelle des Tumeurs solides, Université Paris Descartes, Université Paris Diderot, Université Paris 13, Labex Immuno-Oncology, Paris, France
| | - Léa Meunier
- Inserm UMR-1162, Génomique fonctionnelle des Tumeurs solides, Université Paris Descartes, Université Paris Diderot, Université Paris 13, Labex Immuno-Oncology, Paris, France
| | - Laure Caruana
- Inserm UMR-1162, Génomique fonctionnelle des Tumeurs solides, Université Paris Descartes, Université Paris Diderot, Université Paris 13, Labex Immuno-Oncology, Paris, France
| | - Eric Letouzé
- Inserm UMR-1162, Génomique fonctionnelle des Tumeurs solides, Université Paris Descartes, Université Paris Diderot, Université Paris 13, Labex Immuno-Oncology, Paris, France
| | - Sandra Rebouissou
- Inserm UMR-1162, Génomique fonctionnelle des Tumeurs solides, Université Paris Descartes, Université Paris Diderot, Université Paris 13, Labex Immuno-Oncology, Paris, France
| | - Valérie Paradis
- Service d'anatomopathologie, Hôpital Beaujon, Clichy, Centre de Recherche sur l'inflammation, UMR 1149, INSERM-Paris Diderot University, Paris, France
| | - Julien Calderaro
- Inserm UMR-1162, Génomique fonctionnelle des Tumeurs solides, Université Paris Descartes, Université Paris Diderot, Université Paris 13, Labex Immuno-Oncology, Paris, France.,Service d'anatomopathologie, Hôpital Henri Mondor, Créteil; Université Paris Est Créteil, Inserm U955, Team 18, Institut Mondor de Recherche Biomédicale, Paris, France
| | - Jessica Zucman-Rossi
- Inserm UMR-1162, Génomique fonctionnelle des Tumeurs solides, Université Paris Descartes, Université Paris Diderot, Université Paris 13, Labex Immuno-Oncology, Paris, France.,Hôpital Europeen Georges Pompidou, HEGP, F-75015, Assistance Publique-Hôpitaux de Paris, APHP, Paris, France
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590
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Packer J, Trapnell C. Single-Cell Multi-omics: An Engine for New Quantitative Models of Gene Regulation. Trends Genet 2018; 34:653-665. [PMID: 30007833 PMCID: PMC6097890 DOI: 10.1016/j.tig.2018.06.001] [Citation(s) in RCA: 65] [Impact Index Per Article: 10.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2018] [Revised: 06/05/2018] [Accepted: 06/07/2018] [Indexed: 12/12/2022]
Abstract
Cells in a multicellular organism fulfill specific functions by enacting cell-type-specific programs of gene regulation. Single-cell RNA sequencing technologies have provided a transformative view of cell-type-specific gene expression, the output of cell-type-specific gene regulatory programs. This review discusses new single-cell genomic technologies that complement single-cell RNA sequencing by providing additional readouts of cellular state beyond the transcriptome. We highlight regression models as a simple yet powerful approach to relate gene expression to other aspects of cellular state, and in doing so, gain insights into the biochemical mechanisms that are necessary to produce a given gene expression output.
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Affiliation(s)
- Jonathan Packer
- Department of Genome Sciences, Room S333, Foege Building, Box 355065, Seattle, WA 98105, USA
| | - Cole Trapnell
- Department of Genome Sciences, Room S333, Foege Building, Box 355065, Seattle, WA 98105, USA.
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591
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Camp JG, Wollny D, Treutlein B. Single-cell genomics to guide human stem cell and tissue engineering. Nat Methods 2018; 15:661-667. [PMID: 30171231 DOI: 10.1038/s41592-018-0113-0] [Citation(s) in RCA: 40] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2018] [Accepted: 08/02/2018] [Indexed: 12/15/2022]
Abstract
To understand human development and disease, as well as to regenerate damaged tissues, scientists are working to engineer certain cell types in vitro and to create 3D microenvironments in which cells behave physiologically. Single-cell genomics (SCG) technologies are being applied to primary human organs and to engineered cells and tissues to generate atlases of cell diversity in these systems at unparalleled resolution. Moving beyond atlases, SCG methods are powerful tools for gaining insight into the engineering and disease process. Here we discuss how scientists can use single-cell sequencing to optimize human cell and tissue engineering by measuring precision, detecting inefficiencies, and assessing accuracy. We also provide a perspective on how emerging SCG methods can be used to reverse-engineer human cells and tissues and unravel disease mechanisms.
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Affiliation(s)
- J Gray Camp
- Max Planck Institute for Evolutionary Anthropology, Leipzig, Germany.
| | - Damian Wollny
- Max Planck Institute for Evolutionary Anthropology, Leipzig, Germany
| | - Barbara Treutlein
- Max Planck Institute for Evolutionary Anthropology, Leipzig, Germany. .,Max Planck Institute of Molecular Cell Biology and Genetics, Dresden, Germany. .,Department of Biosciences, Technical University Munich, Freising, Germany.
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592
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Li X, George SM, Vernetti L, Gough AH, Taylor DL. A glass-based, continuously zonated and vascularized human liver acinus microphysiological system (vLAMPS) designed for experimental modeling of diseases and ADME/TOX. LAB ON A CHIP 2018; 18:2614-2631. [PMID: 30063238 PMCID: PMC6113686 DOI: 10.1039/c8lc00418h] [Citation(s) in RCA: 83] [Impact Index Per Article: 13.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/06/2023]
Abstract
The vLAMPS is a human, biomimetic liver MPS, in which the ECM and cell seeding of the intermediate layer prior to assembly, simplifies construction of the model and makes the platform user-friendly. This primarily glass microfluidic device is optimal for real-time imaging, while minimizing the binding of hydrophobic drugs/biologics to the materials that constitute the device. The assembly of the three layered device with primary human hepatocytes and liver sinusoidal endothelial cells (LSECs), and human cell lines for stellate and Kupffer cells, creates a vascular channel separated from the hepatic channel (chamber) by a porous membrane that allows communication between channels, recapitulating the 3D structure of the liver acinus. The vascular channel can be used to deliver drugs, immune cells, as well as various circulating cells and other factors to a stand-alone liver MPS and/or to couple the liver MPS to other organ MPS. We have successfully created continuous oxygen zonation by controlling the flow rates of media in the distinct vascular and hepatic channels and validated the computational modeling of zonation with oxygen sensitive and insensitive beads. This allows the direct investigation of the role of zonation in physiology, toxicology and disease progression. The vascular channel is lined with human LSECs, recapitulating partial immunologic functions within the liver sinusoid, including the activation of LSECs, promoting the binding of polymorphonuclear leukocytes (PMNs) followed by transmigration into the hepatic chamber. The vLAMPS is a valuable platform to investigate the functions of the healthy and diseased human liver using all primary human cell types and/or iPSC-derived cells.
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Affiliation(s)
- Xiang Li
- Drug Discovery Institute, University of Pittsburgh, Pittsburgh, PA 15260, USA.
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593
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Leibing T, Géraud C, Augustin I, Boutros M, Augustin HG, Okun JG, Langhans C, Zierow J, Wohlfeil SA, Olsavszky V, Schledzewski K, Goerdt S, Koch P. Angiocrine Wnt signaling controls liver growth and metabolic maturation in mice. Hepatology 2018; 68:707-722. [PMID: 29059455 PMCID: PMC6099291 DOI: 10.1002/hep.29613] [Citation(s) in RCA: 64] [Impact Index Per Article: 10.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/03/2017] [Revised: 09/08/2017] [Accepted: 10/19/2017] [Indexed: 12/21/2022]
Abstract
UNLABELLED Postnatal liver development is characterized by hepatocyte growth, proliferation, and functional maturation. Notably, canonical Wnt signaling in hepatocytes has been identified as an important regulator of final adult liver size and metabolic liver zonation. The cellular origin of Wnt ligands responsible for homeostatic liver/body weight ratio (LW/BW) remained unclear, which was also attributable to a lack of suitable endothelial Cre driver mice. To comprehensively analyze the effects of hepatic angiocrine Wnt signaling on liver development and metabolic functions, we used endothelial subtype-specific Stab2-Cre driver mice to delete Wls from hepatic endothelial cells (HECs). The resultant Stab2-Cretg/wt ;Wlsfl/fl (Wls-HECKO) mice were viable, but showed a significantly reduced LW/BW. Specifically, ablation of angiocrine Wnt signaling impaired metabolic zonation in the liver, as shown by loss of pericentral, β-catenin-dependent target genes such as glutamine synthase (Glul), RhBg, Axin2, and cytochrome P450 2E1, as well as by extended expression of periportal genes such as arginase 1. Furthermore, endothelial subtype-specific expression of a c-terminally YFP-tagged Wls fusion protein in Wls-HECKO mice (Stab2-Cretg/wt ;Wlsfl/fl ;Rosa26:Wls-YFPfl/wt [Wls-rescue]) restored metabolic liver zonation. Interestingly, lipid metabolism was altered in Wls-HECKO mice exhibiting significantly reduced plasma cholesterol levels, while maintaining normal plasma triglyceride and blood glucose concentrations. On the contrary, zonal expression of Endomucin, LYVE1, and other markers of HEC heterogeneity were not altered in Wls-HECKO livers. CONCLUSION Angiocrine Wnt signaling controls liver growth as well as development of metabolic liver zonation in mice, whereas intrahepatic HEC zonation is not affected. (Hepatology 2017).
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Affiliation(s)
- Thomas Leibing
- Department of Dermatology, Venereology, and AllergologyUniversity Medical Center and Medical Faculty Mannheim, Heidelberg University, and Center of Excellence in DermatologyMannheimGermany
| | - Cyrill Géraud
- Department of Dermatology, Venereology, and AllergologyUniversity Medical Center and Medical Faculty Mannheim, Heidelberg University, and Center of Excellence in DermatologyMannheimGermany
| | - Iris Augustin
- German Cancer Research Center (DKFZ), Division of Signaling and Functional Genomics and Heidelberg University, Faculty of Medicine Mannheim, Department of Cell and Molecular BiologyHeidelbergGermany,Molecular Cell Biology and Plant Cell TechnologyUniversity of Applied Sciences Weihenstephan‐TriesdorfFreisingGermany
| | - Michael Boutros
- German Cancer Research Center (DKFZ), Division of Signaling and Functional Genomics and Heidelberg University, Faculty of Medicine Mannheim, Department of Cell and Molecular BiologyHeidelbergGermany
| | - Hellmut G. Augustin
- Division of Vascular Oncology and Metastasis (DKFZ‐ZMBH Alliance)DKFZHeidelbergGermany,Department of Vascular Biology and Tumor Angiogenesis (CBTM), Medical Faculty MannheimHeidelberg UniversityMannheimGermany
| | - Jürgen G. Okun
- Department of General Pediatrics, Division of Inherited Metabolic DiseasesUniversity Children's HospitalHeidelbergGermany
| | - Claus‐Dieter Langhans
- Department of General Pediatrics, Division of Inherited Metabolic DiseasesUniversity Children's HospitalHeidelbergGermany
| | - Johanna Zierow
- Department of Dermatology, Venereology, and AllergologyUniversity Medical Center and Medical Faculty Mannheim, Heidelberg University, and Center of Excellence in DermatologyMannheimGermany
| | - Sebastian A. Wohlfeil
- Department of Dermatology, Venereology, and AllergologyUniversity Medical Center and Medical Faculty Mannheim, Heidelberg University, and Center of Excellence in DermatologyMannheimGermany
| | - Victor Olsavszky
- Department of Dermatology, Venereology, and AllergologyUniversity Medical Center and Medical Faculty Mannheim, Heidelberg University, and Center of Excellence in DermatologyMannheimGermany
| | - Kai Schledzewski
- Department of Dermatology, Venereology, and AllergologyUniversity Medical Center and Medical Faculty Mannheim, Heidelberg University, and Center of Excellence in DermatologyMannheimGermany
| | - Sergij Goerdt
- Department of Dermatology, Venereology, and AllergologyUniversity Medical Center and Medical Faculty Mannheim, Heidelberg University, and Center of Excellence in DermatologyMannheimGermany,European Center for AngioscienceMedical Faculty Mannheim, University of HeidelbergMannheimGermany
| | - Philipp‐Sebastian Koch
- Department of Dermatology, Venereology, and AllergologyUniversity Medical Center and Medical Faculty Mannheim, Heidelberg University, and Center of Excellence in DermatologyMannheimGermany
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594
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Knittelfelder O, Traikov S, Vvedenskaya O, Schuhmann A, Segeletz S, Shevchenko A, Shevchenko A. Shotgun Lipidomics Combined with Laser Capture Microdissection: A Tool To Analyze Histological Zones in Cryosections of Tissues. Anal Chem 2018; 90:9868-9878. [PMID: 30004672 DOI: 10.1021/acs.analchem.8b02004] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
Shotgun analysis provides a quantitative snapshot of the lipidome composition of cells, tissues, or model organisms; however, it does not elucidate the spatial distribution of lipids. Here we demonstrate that shotgun analysis could quantify low-picomole amounts of lipids isolated by laser capture microdissection (LCM) of hundred micrometer-sized histological zones visualized at the cryosections of tissues. We identified metabolically distinct periportal (pp) and pericentral (pc) zones by immunostaining of 20 μm thick cryosections of a healthy mouse liver. LCM was used to ablate, catapult, and collect the tissue material from 10 to 20 individual zones covering a total area of 0.3-0.5 mm2 and containing ca. 500 cells. Top-down shotgun profiling relying upon computational stitching of 61 targeted selective ion monitoring ( t-SIM) spectra quantified more than 200 lipid species from 17 lipid classes including glycero- and glycerophospholipids, sphingolipids, cholesterol esters, and cholesterol. Shotgun LCM revealed the overall commonality of the full lipidome composition of pp and pc zones along with significant ( p < 0.001) difference in the relative abundance of 13 lipid species. Follow-up proteomics analyses of pellets recovered from an aqueous phase saved after the lipid extraction identified 13 known and 7 new protein markers exclusively present in pp or in pc zones and independently validated the specificity of their visualization, isolation, and histological assignment.
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Affiliation(s)
- Oskar Knittelfelder
- Max Planck Institute of Molecular Cell Biology and Genetics , Pfotenhauerstrasse 108 , 01307 Dresden , Germany
| | - Sofia Traikov
- Max Planck Institute of Molecular Cell Biology and Genetics , Pfotenhauerstrasse 108 , 01307 Dresden , Germany
| | - Olga Vvedenskaya
- Max Planck Institute of Molecular Cell Biology and Genetics , Pfotenhauerstrasse 108 , 01307 Dresden , Germany
| | - Andrea Schuhmann
- Max Planck Institute of Molecular Cell Biology and Genetics , Pfotenhauerstrasse 108 , 01307 Dresden , Germany
| | - Sandra Segeletz
- Max Planck Institute of Molecular Cell Biology and Genetics , Pfotenhauerstrasse 108 , 01307 Dresden , Germany
| | - Anna Shevchenko
- Max Planck Institute of Molecular Cell Biology and Genetics , Pfotenhauerstrasse 108 , 01307 Dresden , Germany
| | - Andrej Shevchenko
- Max Planck Institute of Molecular Cell Biology and Genetics , Pfotenhauerstrasse 108 , 01307 Dresden , Germany
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595
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Dolan PT, Whitfield ZJ, Andino R. Mechanisms and Concepts in RNA Virus Population Dynamics and Evolution. Annu Rev Virol 2018; 5:69-92. [PMID: 30048219 DOI: 10.1146/annurev-virology-101416-041718] [Citation(s) in RCA: 78] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
RNA viruses are unique in their evolutionary capacity, exhibiting high mutation rates and frequent recombination. They rapidly adapt to environmental changes, such as shifts in immune pressure or pharmacological challenge. The evolution of RNA viruses has been brought into new focus with the recent developments of genetic and experimental tools to explore and manipulate the evolutionary dynamics of viral populations. These studies have uncovered new mechanisms that enable viruses to overcome evolutionary challenges in the environment and have emphasized the intimate relationship of viral populations with evolution. Here, we review some of the emerging viral and host mechanisms that underlie the evolution of RNA viruses. We also discuss new studies that demonstrate that the relationship between evolutionary dynamics and virus biology spans many spatial and temporal scales, affecting transmission dynamics within and between hosts as well as pathogenesis.
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Affiliation(s)
- Patrick T Dolan
- Department of Biology, Stanford University, Stanford, California 94305, USA.,Department of Microbiology and Immunology, University of California, San Francisco, California 94143, USA;
| | - Zachary J Whitfield
- Department of Microbiology and Immunology, University of California, San Francisco, California 94143, USA;
| | - Raul Andino
- Department of Microbiology and Immunology, University of California, San Francisco, California 94143, USA;
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596
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Sezgin S, Hassan R, Zühlke S, Kuepfer L, Hengstler JG, Spiteller M, Ghallab A. Spatio-temporal visualization of the distribution of acetaminophen as well as its metabolites and adducts in mouse livers by MALDI MSI. Arch Toxicol 2018; 92:2963-2977. [DOI: 10.1007/s00204-018-2271-3] [Citation(s) in RCA: 37] [Impact Index Per Article: 6.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2018] [Accepted: 07/17/2018] [Indexed: 01/20/2023]
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597
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Alon S, Huynh GH, Boyden ES. Expansion microscopy: enabling single cell analysis in intact biological systems. FEBS J 2018; 286:1482-1494. [PMID: 29938896 DOI: 10.1111/febs.14597] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2018] [Revised: 05/23/2018] [Accepted: 06/21/2018] [Indexed: 12/17/2022]
Abstract
There is a need for single cell analysis methods that enable the identification and localization of different kinds of biomolecules throughout cells and intact tissues, thereby allowing characterization and classification of individual cells and their relationships to each other within intact systems. Expansion microscopy (ExM) is a technology that physically magnifies tissues in an isotropic way, thereby achieving super-resolution microscopy on diffraction-limited microscopes, enabling rapid image acquisition and large field of view. As a result, ExM is well-positioned to integrate molecular content and cellular morphology, with the spatial precision sufficient to resolve individual biological building blocks, and the scale and accessibility required to deploy over extended 3-D objects like tissues and organs.
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Affiliation(s)
- Shahar Alon
- Media Lab, Massachusetts Institute of Technology (MIT), Cambridge, MA, USA.,McGovern Institute, MIT, Cambridge, MA, USA
| | - Grace H Huynh
- Media Lab, Massachusetts Institute of Technology (MIT), Cambridge, MA, USA.,McGovern Institute, MIT, Cambridge, MA, USA.,Microsoft Research, Seattle, WA, USA
| | - Edward S Boyden
- Media Lab, Massachusetts Institute of Technology (MIT), Cambridge, MA, USA.,McGovern Institute, MIT, Cambridge, MA, USA.,Department of Biological Engineering, MIT, Cambridge, MA, USA.,Department of Brain and Cognitive Sciences, MIT, Cambridge, MA, USA.,Koch Institute, MIT, Cambridge, MA, USA
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598
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Hon CC, Shin JW, Carninci P, Stubbington MJT. The Human Cell Atlas: Technical approaches and challenges. Brief Funct Genomics 2018; 17:283-294. [PMID: 29092000 PMCID: PMC6063304 DOI: 10.1093/bfgp/elx029] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022] Open
Abstract
The Human Cell Atlas is a large, international consortium that aims to identify and describe every cell type in the human body. The comprehensive cellular maps that arise from this ambitious effort have the potential to transform many aspects of fundamental biology and clinical practice. Here, we discuss the technical approaches that could be used today to generate such a resource and also the technical challenges that will be encountered.
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Affiliation(s)
- Chung-Chau Hon
- RIKEN Center for Life Science Technologies, Division of Genomic Technologies, Yokohama, Kanagawa, Japan
| | - Jay W Shin
- RIKEN Center for Life Science Technologies, Division of Genomic Technologies, Yokohama, Kanagawa, Japan
| | - Piero Carninci
- RIKEN Center for Life Science Technologies, Division of Genomic Technologies, Yokohama, Kanagawa, Japan
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599
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Limi S, Senecal A, Coleman R, Lopez-Jones M, Guo P, Polumbo C, Singer RH, Skoultchi AI, Cvekl A. Transcriptional burst fraction and size dynamics during lens fiber cell differentiation and detailed insights into the denucleation process. J Biol Chem 2018; 293:13176-13190. [PMID: 29959226 DOI: 10.1074/jbc.ra118.001927] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2018] [Revised: 06/11/2018] [Indexed: 01/05/2023] Open
Abstract
Genes are transcribed in irregular pulses of activity termed transcriptional bursts. Cellular differentiation requires coordinated gene expression; however, it is unknown whether the burst fraction (i.e. the number of active phases of transcription) or size/intensity (the number of RNA molecules produced within a burst) changes during cell differentiation. In the ocular lens, the positions of lens fiber cells correlate precisely with their differentiation status, and the most advanced cells degrade their nuclei. Here, we examined the transcriptional parameters of the β-actin and lens differentiation-specific α-, β-, and γ-crystallin genes by RNA fluorescent in situ hybridization (FISH) in the lenses of embryonic day (E) E12.5, E14.5, and E16.5 mouse embryos and newborns. We found that cellular differentiation dramatically alters the burst fraction in synchronized waves across the lens fiber cell compartment with less dramatic changes in burst intensity. Surprisingly, we observed nascent transcription of multiple genes in nuclei just before nuclear destruction. Nuclear condensation was accompanied by transfer of nuclear proteins, including histone and nonhistone proteins, to the cytoplasm. Although lens-specific deletion of the chromatin remodeler SWI/SNF-related matrix-associated actin-dependent regulator of chromatin subfamily A member 5 (Smarca5/Snf2h) interfered with denucleation, persisting nuclei remained transcriptionally competent and exhibited changes in both burst intensity and fraction depending on the gene examined. Our results uncover the mechanisms of nascent transcriptional control during differentiation and chromatin remodeling, confirm the burst fraction as the major factor adjusting gene expression levels, and reveal transcriptional competence of fiber cell nuclei even as they approach disintegration.
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Affiliation(s)
| | | | | | | | | | | | - Robert H Singer
- Anatomy and Structural Biology.,Cell Biology.,Neuroscience, and
| | | | - Ales Cvekl
- From the Departments of Genetics, .,Ophthalmology and Visual Sciences, Albert Einstein College of Medicine, Bronx, New York 10461
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600
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Stévant I, Nef S. Single cell transcriptome sequencing: A new approach for the study of mammalian sex determination. Mol Cell Endocrinol 2018; 468:11-18. [PMID: 29371022 DOI: 10.1016/j.mce.2018.01.013] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/03/2017] [Revised: 01/21/2018] [Accepted: 01/21/2018] [Indexed: 10/18/2022]
Abstract
Mammalian sex determination is a highly complex developmental process that is particularly difficult to study due to the limited number of gonadal cells present at the bipotential stage, the large cellular heterogeneity in both testis and ovaries and the rapid sex-dependent differentiation processes. Single-cell RNA-sequencing (scRNA-seq) circumvents the averaging artifacts associated with methods traditionally used to profile bulk populations of cells. It is a powerful tool that allows the identification and classification of cell populations in a comprehensive and unbiased manner. In particular, scRNA-seq enables the tracing of cells along developmental trajectories and characterization of the transcriptional dynamics controlling their differentiation. In this review, we describe the current state-of-the-art experimental methods used for scRNA-seq and discuss their strengths and limitations. Additionally, we summarize the multiple key insights that scRNA-seq has provided to the understanding of mammalian sex determination. Finally, we briefly discuss the future of this technology, as well as complementary applications in single cell -omics in the context of mammalian sex determination.
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Affiliation(s)
- Isabelle Stévant
- Department of Genetic Medicine and Development, University of Geneva, 1211 Geneva, Switzerland; iGE3, Institute of Genetics and Genomics of Geneva, University of Geneva, 1211 Geneva, Switzerland; SIB, Swiss Institute of Bioinformatics, University of Geneva, 1211 Geneva, Switzerland
| | - Serge Nef
- Department of Genetic Medicine and Development, University of Geneva, 1211 Geneva, Switzerland; iGE3, Institute of Genetics and Genomics of Geneva, University of Geneva, 1211 Geneva, Switzerland.
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