scholarly journals In vivo single-cell lineage tracing in zebrafish using high-resolution infrared laser-mediated gene induction microscopy

eLife ◽  
2020 ◽  
Vol 9 ◽  
Author(s):  
Sicong He ◽  
Ye Tian ◽  
Shachuan Feng ◽  
Yi Wu ◽  
Xinwei Shen ◽  
...  
Keyword(s):  
Single Cell ◽  
Zebrafish Embryo ◽  
Cell Lineage ◽  
Cell Types ◽  
Infrared Laser ◽  
Lineage Tracing ◽  
Cell Labeling ◽  
Specific Cell ◽  
Blood Island

Heterogeneity broadly exists in various cell types both during development and at homeostasis. Investigating heterogeneity is crucial for comprehensively understanding the complexity of ontogeny, dynamics, and function of specific cell types. Traditional bulk-labeling techniques are incompetent to dissect heterogeneity within cell population, while the new single-cell lineage tracing methodologies invented in the last decade can hardly achieve high-fidelity single-cell labeling and long-term in-vivo observation simultaneously. In this work, we developed a high-precision infrared laser-evoked gene operator heat-shock system, which uses laser-induced CreERT2 combined with loxP-DsRedx-loxP-GFP reporter to achieve precise single-cell labeling and tracing. In vivo study indicated that this system can precisely label single cell in brain, muscle and hematopoietic system in zebrafish embryo. Using this system, we traced the hematopoietic potential of hemogenic endothelium (HE) in the posterior blood island (PBI) of zebrafish embryo and found that HEs in the PBI are heterogeneous, which contains at least myeloid unipotent and myeloid-lymphoid bipotent subtypes.

scholarly journals Single cell lineage tracing reveals a role for TgfβR2 in intestinal stem cell dynamics and differentiation

2016 ◽  
Vol 113 (43) ◽  
pp. 12192-12197 ◽  
Author(s):  
Jared M. Fischer ◽  
Peter P. Calabrese ◽  
Ashleigh J. Miller ◽  
Nina M. Muñoz ◽  
William M. Grady ◽  
...  
Keyword(s):  
Single Cell ◽  
Transforming Growth Factor ◽  
Critical Role ◽  
Cell Lineage ◽  
Transforming Growth Factor Β ◽  
Lineage Tracing ◽  
Secretory Cells ◽  
Cancer Tissue ◽  
Tgfβ Signaling

Intestinal stem cells (ISCs) are maintained by a niche mechanism, in which multiple ISCs undergo differential fates where a single ISC clone ultimately occupies the niche. Importantly, mutations continually accumulate within ISCs creating a potential competitive niche environment. Here we use single cell lineage tracing following stochastic transforming growth factor β receptor 2 (TgfβR2) mutation to show cell autonomous effects of TgfβR2 loss on ISC clonal dynamics and differentiation. Specifically, TgfβR2 mutation in ISCs increased clone survival while lengthening times to monoclonality, suggesting that Tgfβ signaling controls both ISC clone extinction and expansion, independent of proliferation. In addition, TgfβR2 loss in vivo reduced crypt fission, irradiation-induced crypt regeneration, and differentiation toward Paneth cells. Finally, altered Tgfβ signaling in cultured mouse and human enteroids supports further the in vivo data and reveals a critical role for Tgfβ signaling in generating precursor secretory cells. Overall, our data reveal a key role for Tgfβ signaling in regulating ISCs clonal dynamics and differentiation, with implications for cancer, tissue regeneration, and inflammation.

scholarly journals CellWalker integrates single-cell and bulk data to resolve regulatory elements across cell types in complex tissues

2019 ◽  
Author(s):  
Pawel F. Przytycki ◽  
Katherine S. Pollard
Keyword(s):  
Single Cell ◽  
Cell Types ◽  
Regulatory Elements ◽  
Cell Labeling ◽  
Open Chromatin ◽  
Specific Cell ◽  
Rna Seq ◽  
Data Types ◽  
Bulk Data ◽  
Cell Type Specific

Single-cell and bulk genomics assays have complementary strengths and weaknesses, and alone neither strategy can fully capture regulatory elements across the diversity of cells in complex tissues. We present CellWalker, a method that integrates single-cell open chromatin (scATAC-seq) data with gene expression (RNA-seq) and other data types using a network model that simultaneously improves cell labeling in noisy scATAC-seq and annotates cell-type specific regulatory elements in bulk data. We demonstrate CellWalker’s robustness to sparse annotations and noise using simulations and combined RNA-seq and ATAC-seq in individual cells. We then apply CellWalker to the developing brain. We identify cells transitioning between transcriptional states, resolve enhancers to specific cell types, and observe that autism and other neurological traits can be mapped to specific cell types through their enhancers.

scholarly journals A lineage-tracing tool to map the fate of hypoxic tumour cells

2020 ◽  
Author(s):  
Jenny A.F. Vermeer ◽  
Jonathan Ient ◽  
Bostjan Markelc ◽  
Jakob Kaeppler ◽  
Lydie M.O. Barbeau ◽  
...  
Keyword(s):  
Single Cell ◽  
Intravital Microscopy ◽  
Fusion Gene ◽  
Hypoxia Inducible Factor ◽  
Cell Lineage ◽  
Tumour Cells ◽  
Lineage Tracing ◽  
Spatially Resolved ◽  
Summary Statement

AbstractIntratumoural hypoxia is a common characteristic of malignant treatment-resistant cancers. However, hypoxia-modification strategies for the clinic remain elusive. To date little is known on the behaviour of individual hypoxic tumour cells in their microenvironment. To explore this issue in a spatial and temporally-controlled manner we developed a genetically encoded sensor by fusing the O2-labile Hypoxia-Inducible Factor 1α to eGFP and a tamoxifen-regulated Cre recombinase. Under normoxic conditions HIF-1α is degraded but under hypoxia, the HIF-1α-GFP-Cre-ERT2 fusion protein is stabilised and in the presence of tamoxifen activates a tdTomato reporter gene that is constitutively expressed in hypoxic progeny. We visualise the random distribution of hypoxic tumour cells from hypoxic or necrotic regions and vascularised areas using immunofluorescence and intravital microscopy. Once tdTomato expression is induced, it is stable for at least 4 weeks. Using this system, we could show that the post-hypoxic cells were more proliferative in vivo than non-labelled cells. Our results demonstrate that single-cell lineage tracing of hypoxic tumour cells can allow visualisation of their behaviour in living tumours using intravital microscopy. This tool should prove valuable for the study of dissemination and treatment response of post-hypoxic tumour cells in vivo at single-cell resolution.Summary StatementHere we developed and characterised a novel HIF-1α-Cre fusion gene to trace the progeny of hypoxic tumour cells in a temporal and spatially resolved manner using intravital microscopy.

scholarly journals Massively parallel single cell lineage tracing using CRISPR/Cas9 induced genetic scars

2017 ◽  
Author(s):  
Bastiaan Spanjaard ◽  
Bo Hu ◽  
Nina Mitic ◽  
Jan Philipp Junker
Keyword(s):  
Single Cell ◽  
Computational Analysis ◽  
Systematic Approach ◽  
Single Cells ◽  
Cell Lineage ◽  
Transcriptome Profiling ◽  
Cell Types ◽  
Lineage Tracing ◽  
Lineage Trees ◽  
Different Cell Types

A key goal of developmental biology is to understand how a single cell transforms into a full-grown organism consisting of many different cell types. Single-cell RNA-sequencing (scRNA-seq) has become a widely-used method due to its ability to identify all cell types in a tissue or organ in a systematic manner 1–3. However, a major challenge is to organize the resulting taxonomy of cell types into lineage trees revealing the developmental origin of cells. Here, we present a strategy for simultaneous lineage tracing and transcriptome profiling in thousands of single cells. By combining scRNA-seq with computational analysis of lineage barcodes generated by genome editing of transgenic reporter genes, we reconstruct developmental lineage trees in zebrafish larvae and adult fish. In future analyses, LINNAEUS (LINeage tracing by Nuclease-Activated Editing of Ubiquitous Sequences) can be used as a systematic approach for identifying the lineage origin of novel cell types, or of known cell types under different conditions.

scholarly journals Chemogenetic activation of astrocytes in the hippocampus and cortex changes the transcriptome of microglia and other cell types

2020 ◽  
Author(s):  
Stéphanie Philtjens ◽  
Marion T. Turnbull ◽  
Brian P. Thedy ◽  
Younghye Moon ◽  
Jungsu Kim
Keyword(s):  
Single Cell ◽  
G Protein ◽  
Low Density Lipoprotein ◽  
Ion Homeostasis ◽  
Density Lipoprotein ◽  
Cell Types ◽  
Designer Drugs ◽  
Specific Cell ◽  
G Protein Coupled

AbstractAstrocytes are the most common glial cell type in the brain, yet, it is still not clear how their activation affects the transcriptome of other brain cells such as microglia and neurons. Engineered G protein-coupled receptors called Designer Receptors Exclusively Activated by Designer Drugs (DREADDS) make it possible to selectively activate specific cell types, such as neurons and astrocytes. By combining the selective activation of astrocytes with single cell RNA sequencing, we were able to study transcriptional changes that occur in response to the activation of astrocytes at the single cell level. Interestingly, our data shows that long-term activation of astrocytes in healthy mice results in dramatic alteration in the transcriptome of astrocytes and microglia. Genes that were differentially expressed in these Gq-DREADD-activated astrocytes were involved in neurogenesis and low density lipoprotein particle biology, while those in the microglia were involved in the response to lipoproteins, and the migration and chemotaxis of immune cells. Furthermore, network analysis showed that Gq-DREADD-mediated activation in astrocytes resulted in an upregulation of genes involved in the G protein-coupled receptor signaling pathway and calcium ion homeostasis. This confirmed the activation of astrocytes through the expressed DREADDS. Our findings show the importance of considering the transcriptomic alteration in microglia and neurons after the activation of astrocytes in in vivo models. Therefore, our data will serve as a resource for the broader neuroscience community.

scholarly journals Lymphatic system is the mainstream for breast cancer dissemination and metastasis revealed by single-cell lineage tracing

2021 ◽  
Author(s):  
Kai Miao ◽  
Aiping Zhang ◽  
Fangyuan Shao ◽  
Lijian Wang ◽  
Xin Zhang ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Single Cell ◽  
Cancer Cells ◽  
Cancer Metastasis ◽  
Lymphatic System ◽  
Expression Patterns ◽  
Cell Lineage ◽  
Tumour Cells ◽  
Lineage Tracing

Abstract Cancer metastasis is the primary cause of cancer-related death, yet the forces that drive cancer cells through various steps and different routes to distinct target organs/tissues remain elusive. In this study, we applied a CellTag system-based single-cell lineage tracing approach to show the metastasis rate and route of breast cancer cells and their interactions with the tumour microenvironment (TME) during metastasis. The results indicate that only a small fraction of cells can intravasate from the primary site into the blood circulation, whereas more cells disseminate through the lymphatic system to different organs. Tumour cells derived from the same progenitor cell exhibit different gene expression patterns in different soils, and the cancer cell-TME communication paradigm varies significantly between primary and metastatic tumours. Furthermore, metastable cells require a prewired IL-2 expression ability to migrate in vivo. In summary, leveraging a single-cell lineage tracing system, we demonstrate that the crosstalk between tumour cells and the TME is the driving force controlling the preferential metastatic fate of cancer cells through the lymphatic system and that this metastasis can be suppressed by knockdown of IL-2.

EPCO-26. INTEGRATIVE MULTI-OMICS IDENTIFIES CONVERGING DEVELOPMENTAL ORIGINS OF DISTINCT MEDULLOBLASTOMA SUBGROUPS

2021 ◽  
Vol 23 (Supplement_6) ◽  
pp. vi7-vi7
Author(s):  
Kyle Smith ◽  
Laure Bihannic ◽  
Brian Gudenas ◽  
Qingsong Gao ◽  
Parthiv Haldipur ◽  
...  
Keyword(s):  
Single Cell ◽  
Developmental Trajectories ◽  
Cell Lineage ◽  
Cell Types ◽  
Lineage Tracing ◽  
Group 4 ◽  
Group 3 ◽  
Mechanistic Basis ◽  
Rhombic Lip

Abstract Understanding the interplay between normal development and tumorigenesis, including the identification and characterization of lineage-specific origins of MB, is a fundamental challenge in the field. Recent studies have highlighted novel associations between biologically distinct MB subgroups and diverse murine cerebellar lineages via cross-species single-cell transcriptomics. Specifically, Group 4-MB correlated with the unipolar brush cell lineage and Group 3-MB resembled Nestin+ stem cells of the early cerebellum. However, these analyses were hampered by low resolution due to the sparsity of pertinent cerebellar cell types and the cross-species nature of the approach. Herein, we profoundly expand the depth of these rare developmental populations in the murine cerebellum using a combination of lineage tracing and integrative multi-omics. Isolation and enrichment of spatially and temporally unique developmental trajectories of key rhombic lip-derived glutamatergic lineages provided an enhanced reference for mapping MB subgroups based on molecular overlap, especially for poorly defined Group 3- and Group 4-MB. Further comparisons to a novel single-cell atlas of the human fetal cerebellum, companioned with laser-capture microdissected transcriptional and epigenetic datasets, reinforced developmental insights extracted from the mouse. Characterization of compartment-specific transcriptional programs and co-expression networks identified in the human upper rhombic lip implicated convergent cellular correlates of Group 3- and Group 4-MB, suggestive of a common developmental link. Together, our results strongly implicate developmental lineages of the upper rhombic lip as the probable origins of poorly defined Group 3- and Group 4-MB. These important findings will shape future efforts to accurately model the biological heterogeneity underlying these subgroups and provide unprecedented opportunities to explore their cellular and mechanistic basis.

scholarly journals Long-term in vivo single-cell lineage tracing of deep structures using three-photon activation

2016 ◽  
Vol 5 (6) ◽  
pp. e16084-e16084 ◽  
Author(s):  
Isil Tekeli ◽  
Isabelle Aujard ◽  
Xavier Trepat ◽  
Ludovic Jullien ◽  
Angel Raya ◽  
...  
Keyword(s):  
Single Cell ◽  
Cell Lineage ◽  
Lineage Tracing ◽  
Photon Activation
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