1
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Rood JE, Hupalowska A, Regev A. Toward a foundation model of causal cell and tissue biology with a Perturbation Cell and Tissue Atlas. Cell 2024; 187:4520-4545. [PMID: 39178831 DOI: 10.1016/j.cell.2024.07.035] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2024] [Revised: 07/15/2024] [Accepted: 07/21/2024] [Indexed: 08/26/2024]
Abstract
Comprehensively charting the biologically causal circuits that govern the phenotypic space of human cells has often been viewed as an insurmountable challenge. However, in the last decade, a suite of interleaved experimental and computational technologies has arisen that is making this fundamental goal increasingly tractable. Pooled CRISPR-based perturbation screens with high-content molecular and/or image-based readouts are now enabling researchers to probe, map, and decipher genetically causal circuits at increasing scale. This scale is now eminently suitable for the deployment of artificial intelligence and machine learning (AI/ML) to both direct further experiments and to predict or generate information that was not-and sometimes cannot-be gathered experimentally. By combining and iterating those through experiments that are designed for inference, we now envision a Perturbation Cell Atlas as a generative causal foundation model to unify human cell biology.
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Affiliation(s)
| | | | - Aviv Regev
- Genentech, South San Francisco, CA, USA.
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2
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Chen W, Choi J, Li X, Nathans JF, Martin B, Yang W, Hamazaki N, Qiu C, Lalanne JB, Regalado S, Kim H, Agarwal V, Nichols E, Leith A, Lee C, Shendure J. Symbolic recording of signalling and cis-regulatory element activity to DNA. Nature 2024; 632:1073-1081. [PMID: 39020177 PMCID: PMC11357993 DOI: 10.1038/s41586-024-07706-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2021] [Accepted: 06/12/2024] [Indexed: 07/19/2024]
Abstract
Measurements of gene expression or signal transduction activity are conventionally performed using methods that require either the destruction or live imaging of a biological sample within the timeframe of interest. Here we demonstrate an alternative paradigm in which such biological activities are stably recorded to the genome. Enhancer-driven genomic recording of transcriptional activity in multiplex (ENGRAM) is based on the signal-dependent production of prime editing guide RNAs that mediate the insertion of signal-specific barcodes (symbols) into a genomically encoded recording unit. We show how this strategy can be used for multiplex recording of the cell-type-specific activities of dozens to hundreds of cis-regulatory elements with high fidelity, sensitivity and reproducibility. Leveraging signal transduction pathway-responsive cis-regulatory elements, we also demonstrate time- and concentration-dependent genomic recording of WNT, NF-κB and Tet-On activities. By coupling ENGRAM to sequential genome editing via DNA Typewriter1, we stably record information about the temporal dynamics of two orthogonal signalling pathways to genomic DNA. Finally we apply ENGRAM to integratively record the transient activity of nearly 100 transcription factor consensus motifs across daily windows spanning the differentiation of mouse embryonic stem cells into gastruloids, an in vitro model of early mammalian development. Although these are proof-of-concept experiments and much work remains to fully realize the possibilities, the symbolic recording of biological signals or states within cells, to the genome and over time, has broad potential to complement contemporary paradigms for how we make measurements in biological systems.
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Affiliation(s)
- Wei Chen
- Department of Genome Sciences, University of Washington, Seattle, WA, USA.
- Molecular Engineering and Sciences Institute, University of Washington, Seattle, WA, USA.
| | - Junhong Choi
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
- Howard Hughes Medical Institute, Seattle, WA, USA
- Developmental Biology Program, Memorial Sloan Kettering Cancer Center, New York, NY, USA
- Seattle Hub for Synthetic Biology, Seattle, WA, USA
| | - Xiaoyi Li
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
- Seattle Hub for Synthetic Biology, Seattle, WA, USA
| | - Jenny F Nathans
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
- Seattle Hub for Synthetic Biology, Seattle, WA, USA
- Medical Scientist Training Program, University of Washington, Seattle, WA, USA
| | - Beth Martin
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
- Seattle Hub for Synthetic Biology, Seattle, WA, USA
| | - Wei Yang
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
- Seattle Hub for Synthetic Biology, Seattle, WA, USA
| | - Nobuhiko Hamazaki
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
- Seattle Hub for Synthetic Biology, Seattle, WA, USA
- Department of Obstetrics & Gynecology, University of Washington, Seattle, WA, USA
- Institute for Stem Cell & Regenerative Medicine, University of Washington, Seattle, WA, USA
- Brotman Baty Institute for Precision Medicine, University of Washington, Seattle, WA, USA
| | - Chengxiang Qiu
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
- Seattle Hub for Synthetic Biology, Seattle, WA, USA
| | | | - Samuel Regalado
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
- Seattle Hub for Synthetic Biology, Seattle, WA, USA
| | - Haedong Kim
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
- Seattle Hub for Synthetic Biology, Seattle, WA, USA
| | - Vikram Agarwal
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
| | - Eva Nichols
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
| | - Anh Leith
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
| | - Choli Lee
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
- Seattle Hub for Synthetic Biology, Seattle, WA, USA
| | - Jay Shendure
- Department of Genome Sciences, University of Washington, Seattle, WA, USA.
- Howard Hughes Medical Institute, Seattle, WA, USA.
- Seattle Hub for Synthetic Biology, Seattle, WA, USA.
- Brotman Baty Institute for Precision Medicine, University of Washington, Seattle, WA, USA.
- Allen Discovery Center for Cell Lineage Tracing, Seattle, WA, USA.
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3
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Metzner E, Southard KM, Norman TM. Multiome Perturb-seq unlocks scalable discovery of integrated perturbation effects on the transcriptome and epigenome. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.07.26.605307. [PMID: 39091800 PMCID: PMC11291144 DOI: 10.1101/2024.07.26.605307] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 08/04/2024]
Abstract
Single-cell CRISPR screens link genetic perturbations to transcriptional states, but high-throughput methods connecting these induced changes to their regulatory foundations are limited. Here we introduce Multiome Perturb-seq, extending single-cell CRISPR screens to simultaneously measure perturbation-induced changes in gene expression and chromatin accessibility. We apply Multiome Perturb-seq in a CRISPRi screen of 13 chromatin remodelers in human RPE-1 cells, achieving efficient assignment of sgRNA identities to single nuclei via an improved method for capturing barcode transcripts from nuclear RNA. We organize expression and accessibility measurements into coherent programs describing the integrated effects of perturbations on cell state, finding that ARID1A and SUZ12 knockdowns induce programs enriched for developmental features. Pseudotime analysis of perturbations connects accessibility changes to changes in gene expression, highlighting the value of multimodal profiling. Overall, our method provides a scalable and simply implemented system to dissect the regulatory logic underpinning cell state.
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Affiliation(s)
- Eli Metzner
- Computational and Systems Biology Program, Memorial Sloan Kettering Cancer Center, New York, NY, USA
- Tri-Institutional Training Program in Computational Biology and Medicine, New York, NY, USA
| | - Kaden M. Southard
- Computational and Systems Biology Program, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Thomas M. Norman
- Computational and Systems Biology Program, Memorial Sloan Kettering Cancer Center, New York, NY, USA
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4
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Kabaria SR, Bae Y, Ehmann ME, Beitz AM, Lende-Dorn BA, Peterman EL, Love KS, Ploessl DS, Galloway KE. Programmable promoter editing for precise control of transgene expression. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.06.19.599813. [PMID: 38948694 PMCID: PMC11212971 DOI: 10.1101/2024.06.19.599813] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/02/2024]
Abstract
Subtle changes in gene expression direct cells to distinct cellular states. Identifying and controlling dose-dependent transgenes require tools for precisely titrating expression. To this end, we developed a highly modular, extensible framework called DIAL for building editable promoters that allow for fine-scale, heritable changes in transgene expression. Using DIAL, we increase expression by recombinase-mediated excision of spacers between the binding sites of a synthetic zinc finger transcription factor and the core promoter. By nesting varying numbers and lengths of spacers, DIAL generates a tunable range of unimodal setpoints from a single promoter. Through small-molecule control of transcription factors and recombinases, DIAL supports temporally defined, user-guided control of transgene expression that is extensible to additional transcription factors. Lentiviral delivery of DIAL generates multiple setpoints in primary cells and iPSCs. As promoter editing generates stable states, DIAL setpoints are heritable, facilitating mapping of transgene levels to phenotypes. The DIAL framework opens new opportunities for tailoring transgene expression and improving the predictability and performance of gene circuits across diverse applications.
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Affiliation(s)
- Sneha R. Kabaria
- Department of Chemical Engineering, MIT, Cambridge, MA 02139, USA
| | - Yunbeen Bae
- Department of Chemical Engineering, MIT, Cambridge, MA 02139, USA
| | - Mary E. Ehmann
- Department of Chemical Engineering, MIT, Cambridge, MA 02139, USA
| | - Adam M. Beitz
- Department of Chemical Engineering, MIT, Cambridge, MA 02139, USA
| | | | - Emma L. Peterman
- Department of Chemical Engineering, MIT, Cambridge, MA 02139, USA
| | - Kasey S. Love
- Department of Biological Engineering, MIT, Cambridge, MA 02139, USA
| | - Deon S. Ploessl
- Department of Chemical Engineering, MIT, Cambridge, MA 02139, USA
| | - Kate E. Galloway
- Department of Chemical Engineering, MIT, Cambridge, MA 02139, USA
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5
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Li X, Chen W, Martin BK, Calderon D, Lee C, Choi J, Chardon FM, McDiarmid TA, Daza RM, Kim H, Lalanne JB, Nathans JF, Lee DS, Shendure J. Chromatin context-dependent regulation and epigenetic manipulation of prime editing. Cell 2024; 187:2411-2427.e25. [PMID: 38608704 PMCID: PMC11088515 DOI: 10.1016/j.cell.2024.03.020] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2023] [Revised: 01/05/2024] [Accepted: 03/14/2024] [Indexed: 04/14/2024]
Abstract
We set out to exhaustively characterize the impact of the cis-chromatin environment on prime editing, a precise genome engineering tool. Using a highly sensitive method for mapping the genomic locations of randomly integrated reporters, we discover massive position effects, exemplified by editing efficiencies ranging from ∼0% to 94% for an identical target site and edit. Position effects on prime editing efficiency are well predicted by chromatin marks, e.g., positively by H3K79me2 and negatively by H3K9me3. Next, we developed a multiplex perturbational framework to assess the interaction of trans-acting factors with the cis-chromatin environment on editing outcomes. Applying this framework to DNA repair factors, we identify HLTF as a context-dependent repressor of prime editing. Finally, several lines of evidence suggest that active transcriptional elongation enhances prime editing. Consistent with this, we show we can robustly decrease or increase the efficiency of prime editing by preceding it with CRISPR-mediated silencing or activation, respectively.
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Affiliation(s)
- Xiaoyi Li
- Department of Genome Sciences, University of Washington, Seattle, WA 98195, USA.
| | - Wei Chen
- Department of Genome Sciences, University of Washington, Seattle, WA 98195, USA; Molecular Engineering and Sciences Institute, University of Washington, Seattle, WA 98195, USA
| | - Beth K Martin
- Department of Genome Sciences, University of Washington, Seattle, WA 98195, USA
| | - Diego Calderon
- Department of Genome Sciences, University of Washington, Seattle, WA 98195, USA
| | - Choli Lee
- Department of Genome Sciences, University of Washington, Seattle, WA 98195, USA
| | - Junhong Choi
- Department of Genome Sciences, University of Washington, Seattle, WA 98195, USA; Howard Hughes Medical Institute, Seattle, WA 98195, USA
| | - Florence M Chardon
- Department of Genome Sciences, University of Washington, Seattle, WA 98195, USA
| | - Troy A McDiarmid
- Department of Genome Sciences, University of Washington, Seattle, WA 98195, USA
| | - Riza M Daza
- Department of Genome Sciences, University of Washington, Seattle, WA 98195, USA
| | - Haedong Kim
- Department of Genome Sciences, University of Washington, Seattle, WA 98195, USA
| | - Jean-Benoît Lalanne
- Department of Genome Sciences, University of Washington, Seattle, WA 98195, USA
| | - Jenny F Nathans
- Department of Genome Sciences, University of Washington, Seattle, WA 98195, USA; Medical Scientist Training Program, University of Washington, Seattle, WA 98195, USA
| | - David S Lee
- Department of Genome Sciences, University of Washington, Seattle, WA 98195, USA; Institute for Protein Design, University of Washington, Seattle, WA 98195, USA
| | - Jay Shendure
- Department of Genome Sciences, University of Washington, Seattle, WA 98195, USA; Howard Hughes Medical Institute, Seattle, WA 98195, USA; Brotman Baty Institute for Precision Medicine, Seattle, WA 98195, USA; Allen Discovery Center for Cell Lineage Tracing, Seattle, WA 98109, USA; Seattle Hub for Synthetic Biology, Seattle, WA 98109, USA.
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6
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Sánchez Rivera FJ, Dow LE. How CRISPR Is Revolutionizing the Generation of New Models for Cancer Research. Cold Spring Harb Perspect Med 2024; 14:a041384. [PMID: 37487630 PMCID: PMC11065179 DOI: 10.1101/cshperspect.a041384] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/26/2023]
Abstract
Cancers arise through acquisition of mutations in genes that regulate core biological processes like cell proliferation and cell death. Decades of cancer research have led to the identification of genes and mutations causally involved in disease development and evolution, yet defining their precise function across different cancer types and how they influence therapy responses has been challenging. Mouse models have helped define the in vivo function of cancer-associated alterations, and genome-editing approaches using CRISPR have dramatically accelerated the pace at which these models are developed and studied. Here, we highlight how CRISPR technologies have impacted the development and use of mouse models for cancer research and discuss the many ways in which these rapidly evolving platforms will continue to transform our understanding of this disease.
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Affiliation(s)
- Francisco J Sánchez Rivera
- David H. Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, Massachusetts 02142, USA
- Department of Biology, Massachusetts Institute of Technology, Cambridge, Massachusetts 02142, USA
| | - Lukas E Dow
- Sandra and Edward Meyer Cancer Center, Weill Cornell Medicine, New York, New York 10065, USA
- Department of Biochemistry, Weill Cornell Medicine, New York, New York 10065, USA
- Department of Medicine, Weill Cornell Medicine, New York, New York 10065, USA
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7
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Nathans JF, Ayers JL, Shendure J, Simpson CL. Genetic Tools for Cell Lineage Tracing and Profiling Developmental Trajectories in the Skin. J Invest Dermatol 2024; 144:936-949. [PMID: 38643988 PMCID: PMC11034889 DOI: 10.1016/j.jid.2024.02.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2023] [Revised: 01/28/2024] [Accepted: 02/08/2024] [Indexed: 04/23/2024]
Abstract
The epidermis is the body's first line of protection against dehydration and pathogens, continually regenerating the outermost protective skin layers throughout life. During both embryonic development and wound healing, epidermal stem and progenitor cells must respond to external stimuli and insults to build, maintain, and repair the cutaneous barrier. Recent advances in CRISPR-based methods for cell lineage tracing have remarkably expanded the potential for experiments that track stem and progenitor cell proliferation and differentiation over the course of tissue and even organismal development. Additional tools for DNA-based recording of cellular signaling cues promise to deepen our understanding of the mechanisms driving normal skin morphogenesis and response to stressors as well as the dysregulation of cell proliferation and differentiation in skin diseases and cancer. In this review, we highlight cutting-edge methods for cell lineage tracing, including in organoids and model organisms, and explore how cutaneous biology researchers might leverage these techniques to elucidate the developmental programs that support the regenerative capacity and plasticity of the skin.
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Affiliation(s)
- Jenny F Nathans
- Medical Scientist Training Program, University of Washington, Seattle, Washington, USA; Department of Genome Sciences, University of Washington, Seattle, Washington, USA
| | - Jessica L Ayers
- Molecular Medicine and Mechanisms of Disease PhD Program, Department of Laboratory Medicine and Pathology, University of Washington, Seattle, Washington, USA; Department of Dermatology, University of Washington, Seattle, Washington, USA
| | - Jay Shendure
- Department of Genome Sciences, University of Washington, Seattle, Washington, USA; Institute for Stem Cell & Regenerative Medicine, University of Washington, Seattle, Washington, USA
| | - Cory L Simpson
- Department of Dermatology, University of Washington, Seattle, Washington, USA; Institute for Stem Cell & Regenerative Medicine, University of Washington, Seattle, Washington, USA.
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8
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Tran M, Askary A, Elowitz MB. Lineage motifs as developmental modules for control of cell type proportions. Dev Cell 2024; 59:812-826.e3. [PMID: 38359830 DOI: 10.1016/j.devcel.2024.01.017] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2023] [Revised: 10/10/2023] [Accepted: 01/19/2024] [Indexed: 02/17/2024]
Abstract
In multicellular organisms, cell types must be produced and maintained in appropriate proportions. One way this is achieved is through committed progenitor cells or extrinsic interactions that produce specific patterns of descendant cell types on lineage trees. However, cell fate commitment is probabilistic in most contexts, making it difficult to infer these dynamics and understand how they establish overall cell type proportions. Here, we introduce Lineage Motif Analysis (LMA), a method that recursively identifies statistically overrepresented patterns of cell fates on lineage trees as potential signatures of committed progenitor states or extrinsic interactions. Applying LMA to published datasets reveals spatial and temporal organization of cell fate commitment in zebrafish and rat retina and early mouse embryonic development. Comparative analysis of vertebrate species suggests that lineage motifs facilitate adaptive evolutionary variation of retinal cell type proportions. LMA thus provides insight into complex developmental processes by decomposing them into simpler underlying modules.
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Affiliation(s)
- Martin Tran
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA 91125, USA
| | - Amjad Askary
- Department of Molecular, Cell and Developmental Biology, University of California, Los Angeles, Los Angeles, CA 90095, USA.
| | - Michael B Elowitz
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA 91125, USA; Howard Hughes Medical Institute, Chevy Chase, MD 20815, USA.
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9
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Pinglay S, Lalanne JB, Daza RM, Koeppel J, Li X, Lee DS, Shendure J. Multiplex generation and single cell analysis of structural variants in a mammalian genome. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.01.22.576756. [PMID: 38405830 PMCID: PMC10888807 DOI: 10.1101/2024.01.22.576756] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 02/27/2024]
Abstract
The functional consequences of structural variants (SVs) in mammalian genomes are challenging to study. This is due to several factors, including: 1) their numerical paucity relative to other forms of standing genetic variation such as single nucleotide variants (SNVs) and short insertions or deletions (indels); 2) the fact that a single SV can involve and potentially impact the function of more than one gene and/or cis regulatory element; and 3) the relative immaturity of methods to generate and map SVs, either randomly or in targeted fashion, in in vitro or in vivo model systems. Towards addressing these challenges, we developed Genome-Shuffle-seq, a straightforward method that enables the multiplex generation and mapping of several major forms of SVs (deletions, inversions, translocations) throughout a mammalian genome. Genome-Shuffle-seq is based on the integration of "shuffle cassettes" to the genome, wherein each shuffle cassette contains components that facilitate its site-specific recombination (SSR) with other integrated shuffle cassettes (via Cre-loxP), its mapping to a specific genomic location (via T7-mediated in vitro transcription or IVT), and its identification in single-cell RNA-seq (scRNA-seq) data (via T7-mediated in situ transcription or IST). In this proof-of-concept, we apply Genome-Shuffle-seq to induce and map thousands of genomic SVs in mouse embryonic stem cells (mESCs) in a single experiment. Induced SVs are rapidly depleted from the cellular population over time, possibly due to Cre-mediated toxicity and/or negative selection on the rearrangements themselves. Leveraging T7 IST of barcodes whose positions are already mapped, we further demonstrate that we can efficiently genotype which SVs are present in association with each of many single cell transcriptomes in scRNA-seq data. Finally, preliminary evidence suggests our method may be a powerful means of generating extrachromosomal circular DNAs (ecDNAs). Looking forward, we anticipate that Genome-Shuffle-seq may be broadly useful for the systematic exploration of the functional consequences of SVs on gene expression, the chromatin landscape, and 3D nuclear architecture. We further anticipate potential uses for in vitro modeling of ecDNAs, as well as in paving the path to a minimal mammalian genome.
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Affiliation(s)
- Sudarshan Pinglay
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
- Brotman Baty Institute for Precision Medicine, Seattle, WA, USA
- Seattle Hub for Synthetic Biology, Seattle, WA, USA
| | | | - Riza M Daza
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
- Seattle Hub for Synthetic Biology, Seattle, WA, USA
| | | | - Xiaoyi Li
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
| | - David S Lee
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
- Institute for Protein Design, University of Washington, Seattle, WA, USA
| | - Jay Shendure
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
- Brotman Baty Institute for Precision Medicine, Seattle, WA, USA
- Seattle Hub for Synthetic Biology, Seattle, WA, USA
- Allen Discovery Center for Cell Lineage Tracing, Seattle, WA, USA
- Howard Hughes Medical Institute, Seattle, WA, USA
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10
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Gu J, Iyer A, Wesley B, Taglialatela A, Leuzzi G, Hangai S, Decker A, Gu R, Klickstein N, Shuai Y, Jankovic K, Parker-Burns L, Jin Y, Zhang JY, Hong J, Niu S, Chou J, Landau DA, Azizi E, Chan EM, Ciccia A, Gaublomme JT. CRISPRmap: Sequencing-free optical pooled screens mapping multi-omic phenotypes in cells and tissue. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.12.26.572587. [PMID: 38234835 PMCID: PMC10793456 DOI: 10.1101/2023.12.26.572587] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/19/2024]
Abstract
Pooled genetic screens are powerful tools to study gene function in a high-throughput manner. Typically, sequencing-based screens require cell lysis, which limits the examination of critical phenotypes such as cell morphology, protein subcellular localization, and cell-cell/tissue interactions. In contrast, emerging optical pooled screening methods enable the investigation of these spatial phenotypes in response to targeted CRISPR perturbations. In this study, we report a multi-omic optical pooled CRISPR screening method, which we have named CRISPRmap. Our method combines a novel in situ CRISPR guide identifying barcode readout approach with concurrent multiplexed immunofluorescence and in situ RNA detection. CRISPRmap barcodes are detected and read out through combinatorial hybridization of DNA oligos, enhancing barcode detection efficiency, while reducing both dependency on third party proprietary sequencing reagents and assay cost. Notably, we conducted a multi-omic base-editing screen in a breast cancer cell line on core DNA damage repair genes involved in the homologous recombination and Fanconi anemia pathways investigating how nucleotide variants in those genes influence DNA damage signaling and cell cycle regulation following treatment with ionizing radiation or DNA damaging agents commonly used for cancer therapy. Approximately a million cells were profiled with our multi-omic approach, providing a comprehensive phenotypic assessment of the functional consequences of the studied variants. CRISPRmap enabled us to pinpoint likely-pathogenic patient-derived mutations that were previously classified as variants of unknown clinical significance. Furthermore, our approach effectively distinguished barcodes of a pooled library in tumor tissue, and we coupled it with cell-type and molecular phenotyping by cyclic immunofluorescence. Multi-omic spatial analysis of how CRISPR-perturbed cells respond to various environmental cues in the tissue context offers the potential to significantly expand our understanding of tissue biology in both health and disease.
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Affiliation(s)
- Jiacheng Gu
- Department of Biological Sciences, Columbia University, NY, USA
| | - Abhishek Iyer
- Department of Biological Sciences, Columbia University, NY, USA
| | - Ben Wesley
- Department of Biological Sciences, Columbia University, NY, USA
| | - Angelo Taglialatela
- Department of Genetics and Development, Columbia University Irving Medical Center, NY, USA
| | - Giuseppe Leuzzi
- Department of Genetics and Development, Columbia University Irving Medical Center, NY, USA
- Herbert Irving Comprehensive Cancer Center, Columbia University Irving Medical Center, NY, USA
- Institute for Cancer Genetics, Columbia University Irving Medical Center, NY, USA
| | - Sho Hangai
- Herbert Irving Comprehensive Cancer Center, Columbia University Irving Medical Center, NY, USA
| | | | - Ruoyu Gu
- Department of Biological Sciences, Columbia University, NY, USA
| | | | - Yuanlong Shuai
- Department of Biological Sciences, Columbia University, NY, USA
| | - Kristina Jankovic
- Herbert Irving Comprehensive Cancer Center, Columbia University Irving Medical Center, NY, USA
| | - Lucy Parker-Burns
- Herbert Irving Comprehensive Cancer Center, Columbia University Irving Medical Center, NY, USA
| | - Yinuo Jin
- Department of Biomedical Engineering, Columbia University, NY, USA
| | - Jia Yi Zhang
- Department of Biomedical Engineering, Columbia University, NY, USA
| | - Justin Hong
- Department of Computer Science, Columbia University, NY, USA
| | - Steve Niu
- Weill Cornell Medicine, NY, USA
- Genentech Research and Early Development, CA, USA
| | - Jacqueline Chou
- Department of Biological Sciences, Columbia University, NY, USA
- Weill Cornell Medicine, NY, USA
| | - Dan A. Landau
- Weill Cornell Medicine, NY, USA
- New York Genome Center, NY, USA
| | - Elham Azizi
- Department of Biomedical Engineering, Columbia University, NY, USA
- Department of Computer Science, Columbia University, NY, USA
- Irving Institute for Cancer Dynamics, Columbia University, NY, USA
| | - Edmond M. Chan
- Herbert Irving Comprehensive Cancer Center, Columbia University Irving Medical Center, NY, USA
- New York Genome Center, NY, USA
- Department of Medicine, Division of Hematology/Oncology, Columbia University Irving Medical Center, NY, USA
| | - Alberto Ciccia
- Department of Genetics and Development, Columbia University Irving Medical Center, NY, USA
- Herbert Irving Comprehensive Cancer Center, Columbia University Irving Medical Center, NY, USA
- Institute for Cancer Genetics, Columbia University Irving Medical Center, NY, USA
| | - Jellert T. Gaublomme
- Department of Biological Sciences, Columbia University, NY, USA
- Herbert Irving Comprehensive Cancer Center, Columbia University Irving Medical Center, NY, USA
- New York Genome Center, NY, USA
- Irving Institute for Cancer Dynamics, Columbia University, NY, USA
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11
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Coughlin GM, Borsos M, Appling N, Barcelona BH, Mayfield AMH, Mackey ED, Eser RA, Chen X, Kumar SR, Gradinaru V. Spatial genomics of AAVs reveals mechanism of transcriptional crosstalk that enables targeted delivery of large genetic cargo. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.12.23.573214. [PMID: 38187707 PMCID: PMC10769433 DOI: 10.1101/2023.12.23.573214] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/09/2024]
Abstract
Integrating cell type-specific regulatory elements (e.g. enhancers) with recombinant adeno-associated viruses (AAVs) can provide broad and efficient genetic access to specific cell types. However, the packaging capacity of AAVs restricts the size of both the enhancers and the cargo that can be delivered. Transcriptional crosstalk offers a novel paradigm for cell type-specific expression of large cargo, by separating distally-acting regulatory elements into a second AAV genome. Here, we identify and profile transcriptional crosstalk in AAV genomes carrying 11 different enhancers active in mouse brain. To understand transcriptional crosstalk, we develop spatial genomics methods to identify and localize AAV genomes and their concatemeric forms in cultured cells and in tissue. Using these methods, we construct detailed views of the dynamics of AAV transduction and demonstrate that transcriptional crosstalk is dependent upon concatemer formation. Finally, we leverage transcriptional crosstalk to drive expression of a large Cas9 cargo in a cell type-specific manner with systemically-administered engineered AAVs and demonstrate AAV-delivered, minimally-invasive, cell type-specific gene editing in wildtype animals that recapitulates known disease phenotypes.
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Affiliation(s)
- Gerard M. Coughlin
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA
| | - Máté Borsos
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA
| | - Nathan Appling
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA
| | - Bre’Anna H. Barcelona
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA
| | - Acacia M. H. Mayfield
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA
| | - Elisha D. Mackey
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA
| | - Rana A. Eser
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA
| | - Xinhong Chen
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA
| | - Sripriya Ravindra Kumar
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA
| | - Viviana Gradinaru
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA
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12
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Walsh LA, Quail DF. Decoding the tumor microenvironment with spatial technologies. Nat Immunol 2023; 24:1982-1993. [PMID: 38012408 DOI: 10.1038/s41590-023-01678-9] [Citation(s) in RCA: 11] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2023] [Accepted: 10/10/2023] [Indexed: 11/29/2023]
Abstract
Visualization of the cellular heterogeneity and spatial architecture of the tumor microenvironment (TME) is becoming increasingly important to understand mechanisms of disease progression and therapeutic response. This is particularly relevant in the era of cancer immunotherapy, in which the contexture of immune cell positioning within the tumor landscape has been proven to affect efficacy. Although single-cell technologies have mostly replaced conventional approaches to analyze specific cellular subsets within tumors, those that integrate a spatial dimension are now on the rise. In this Review, we assess the strengths and limitations of emerging spatial technologies with a focus on their applications in tumor immunology, as well as forthcoming opportunities for artificial intelligence (AI) and the value of integrating multiomics datasets to achieve a holistic picture of the TME.
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Affiliation(s)
- Logan A Walsh
- Rosalind and Morris Goodman Cancer Institute, McGill University, Montreal, Quebec, Canada.
- Department of Human Genetics, Faculty of Medicine, McGill University, Montreal, Quebec, Canada.
| | - Daniela F Quail
- Rosalind and Morris Goodman Cancer Institute, McGill University, Montreal, Quebec, Canada.
- Department of Physiology, Faculty of Medicine, McGill University, Montreal, Quebec, Canada.
- Department of Medicine, Division of Experimental Medicine, McGill University, Montreal, Quebec, Canada.
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13
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Binan L, Danquah S, Valakh V, Simonton B, Bezney J, Nehme R, Cleary B, Farhi SL. Simultaneous CRISPR screening and spatial transcriptomics reveals intracellular, intercellular, and functional transcriptional circuits. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.11.30.569494. [PMID: 38076932 PMCID: PMC10705493 DOI: 10.1101/2023.11.30.569494] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/17/2023]
Abstract
Pooled optical screens have enabled the study of cellular interactions, morphology, or dynamics at massive scale, but have not yet leveraged the power of highly-plexed single-cell resolved transcriptomic readouts to inform molecular pathways. Here, we present Perturb-FISH, which bridges these approaches by combining imaging spatial transcriptomics with parallel optical detection of in situ amplified guide RNAs. We show that Perturb-FISH recovers intracellular effects that are consistent with Perturb-seq results in a screen of lipopolysaccharide response in cultured monocytes, and uncover new intercellular and density-dependent regulation of the innate immune response. We further pair Perturb-FISH with a functional readout in a screen of autism spectrum disorder risk genes, showing common calcium activity phenotypes in induced pluripotent stem cell derived astrocytes and their associated genetic interactions and dysregulated molecular pathways. Perturb-FISH is thus a generally applicable method for studying the genetic and molecular associations of spatial and functional biology at single-cell resolution.
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Affiliation(s)
- Loϊc Binan
- Spatial Technology Platform, Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA
| | - Serwah Danquah
- Spatial Technology Platform, Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA
- Stanley Center for Psychiatric Research, Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA
| | - Vera Valakh
- Spatial Technology Platform, Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA
- Stanley Center for Psychiatric Research, Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA
| | - Brooke Simonton
- Present address: The Ken & Ruth Davee Department of Neurology, Northwestern University Feinberg School of Medicine, Chicago, IL, USA. (Klarman Cell Observatory, Broad Institute of Harvard and MIT, Cambridge, MA, USA)
| | - Jon Bezney
- Present address: Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA. (Klarman Cell Observatory, Broad Institute of Harvard and MIT, Cambridge, MA, USA)
| | - Ralda Nehme
- Spatial Technology Platform, Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA
- Stanley Center for Psychiatric Research, Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA
| | - Brian Cleary
- Faculty of Computing and Data Sciences, Boston University, Boston, MA, USA; Department of Biology, Boston University, Boston, MA, USA; Department of Biomedical Engineering, Boston University, Boston, MA, USA; Program in Bioinformatics, Boston University, Boston, MA, USA; Biological Design Center, Boston University, Boston, MA, USA
| | - Samouil L Farhi
- Spatial Technology Platform, Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA
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14
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Tseng KC, Crump JG. Craniofacial developmental biology in the single-cell era. Development 2023; 150:dev202077. [PMID: 37812056 PMCID: PMC10617621 DOI: 10.1242/dev.202077] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/10/2023]
Abstract
The evolution of a unique craniofacial complex in vertebrates made possible new ways of breathing, eating, communicating and sensing the environment. The head and face develop through interactions of all three germ layers, the endoderm, ectoderm and mesoderm, as well as the so-called fourth germ layer, the cranial neural crest. Over a century of experimental embryology and genetics have revealed an incredible diversity of cell types derived from each germ layer, signaling pathways and genes that coordinate craniofacial development, and how changes to these underlie human disease and vertebrate evolution. Yet for many diseases and congenital anomalies, we have an incomplete picture of the causative genomic changes, in particular how alterations to the non-coding genome might affect craniofacial gene expression. Emerging genomics and single-cell technologies provide an opportunity to obtain a more holistic view of the genes and gene regulatory elements orchestrating craniofacial development across vertebrates. These single-cell studies generate novel hypotheses that can be experimentally validated in vivo. In this Review, we highlight recent advances in single-cell studies of diverse craniofacial structures, as well as potential pitfalls and the need for extensive in vivo validation. We discuss how these studies inform the developmental sources and regulation of head structures, bringing new insights into the etiology of structural birth anomalies that affect the vertebrate head.
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Affiliation(s)
- Kuo-Chang Tseng
- Department of Stem Cell Biology and Regenerative Medicine, Keck School of Medicine of University of Southern California, Los Angeles, CA 90033, USA
| | - J. Gage Crump
- Department of Stem Cell Biology and Regenerative Medicine, Keck School of Medicine of University of Southern California, Los Angeles, CA 90033, USA
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15
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Jang MJ, Coughlin GM, Jackson CR, Chen X, Chuapoco MR, Vendemiatti JL, Wang AZ, Gradinaru V. Spatial transcriptomics for profiling the tropism of viral vectors in tissues. Nat Biotechnol 2023; 41:1272-1286. [PMID: 36702899 PMCID: PMC10443732 DOI: 10.1038/s41587-022-01648-w] [Citation(s) in RCA: 19] [Impact Index Per Article: 19.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2022] [Accepted: 12/15/2022] [Indexed: 01/27/2023]
Abstract
A barrier to advancing engineered adeno-associated viral vectors (AAVs) for precision access to cell subtypes is a lack of high-throughput, high-resolution assays to characterize in vivo transduction profiles. In this study, we developed an ultrasensitive, sequential fluorescence in situ hybridization (USeqFISH) method for spatial transcriptomic profiling of endogenous and viral RNA with a short barcode in intact tissue volumes by integrating hydrogel-based tissue clearing, enhanced signal amplification and multiplexing using sequential labeling. Using USeqFISH, we investigated the transduction and cell subtype tropisms across mouse brain regions of six systemic AAVs, including AAV-PHP.AX, a new variant that transduces robustly and efficiently across neurons and astrocytes. Here we reveal distinct cell subtype biases of each AAV variant, including a bias of AAV-PHP.N toward excitatory neurons. USeqFISH also enables profiling of pooled regulatory cargos, as we show for a 13-variant pool of microRNA target sites in AAV genomes. Lastly, we demonstrate potential applications of USeqFISH for in situ AAV profiling and multimodal single-cell analysis in non-human primates.
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Affiliation(s)
- Min J Jang
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA, USA
| | - Gerard M Coughlin
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA, USA
| | - Cameron R Jackson
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA, USA
| | - Xinhong Chen
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA, USA
| | - Miguel R Chuapoco
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA, USA
| | - Julia L Vendemiatti
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA, USA
| | - Alexander Z Wang
- Division of Engineering and Applied Science, California Institute of Technology, Pasadena, CA, USA
| | - Viviana Gradinaru
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA, USA.
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16
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Tran M, Askary A, Elowitz MB. Lineage motifs: developmental modules for control of cell type proportions. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.06.06.543925. [PMID: 37333085 PMCID: PMC10274800 DOI: 10.1101/2023.06.06.543925] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/20/2023]
Abstract
In multicellular organisms, cell types must be produced and maintained in appropriate proportions. One way this is achieved is through committed progenitor cells that produce specific sets of descendant cell types. However, cell fate commitment is probabilistic in most contexts, making it difficult to infer progenitor states and understand how they establish overall cell type proportions. Here, we introduce Lineage Motif Analysis (LMA), a method that recursively identifies statistically overrepresented patterns of cell fates on lineage trees as potential signatures of committed progenitor states. Applying LMA to published datasets reveals spatial and temporal organization of cell fate commitment in zebrafish and rat retina and early mouse embryo development. Comparative analysis of vertebrate species suggests that lineage motifs facilitate adaptive evolutionary variation of retinal cell type proportions. LMA thus provides insight into complex developmental processes by decomposing them into simpler underlying modules.
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Affiliation(s)
- Martin Tran
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA 91125, USA
| | - Amjad Askary
- Department of Molecular, Cell and Developmental Biology, University of California Los Angeles, Los Angeles, CA 90095, USA
| | - Michael B. Elowitz
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA 91125, USA
- Howard Hughes Medical Institute, Chevy Chase, MD 20815, USA
- Lead contact
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17
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Li X, Chen W, Martin BK, Calderon D, Lee C, Choi J, Chardon FM, McDiarmid T, Kim H, Lalanne JB, Nathans JF, Shendure J. Chromatin context-dependent regulation and epigenetic manipulation of prime editing. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.04.12.536587. [PMID: 37090511 PMCID: PMC10120711 DOI: 10.1101/2023.04.12.536587] [Citation(s) in RCA: 13] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/25/2023]
Abstract
Prime editing is a powerful means of introducing precise changes to specific locations in mammalian genomes. However, the widely varying efficiency of prime editing across target sites of interest has limited its adoption in the context of both basic research and clinical settings. Here, we set out to exhaustively characterize the impact of the cis- chromatin environment on prime editing efficiency. Using a newly developed and highly sensitive method for mapping the genomic locations of a randomly integrated "sensor", we identify specific epigenetic features that strongly correlate with the highly variable efficiency of prime editing across different genomic locations. Next, to assess the interaction of trans -acting factors with the cis -chromatin environment, we develop and apply a pooled genetic screening approach with which the impact of knocking down various DNA repair factors on prime editing efficiency can be stratified by cis -chromatin context. Finally, we demonstrate that we can dramatically modulate the efficiency of prime editing through epigenome editing, i.e. altering chromatin state in a locus-specific manner in order to increase or decrease the efficiency of prime editing at a target site. Looking forward, we envision that the insights and tools described here will broaden the range of both basic research and therapeutic contexts in which prime editing is useful.
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18
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Espinosa-Medina I, Feliciano D, Belmonte-Mateos C, Linda Miyares R, Garcia-Marques J, Foster B, Lindo S, Pujades C, Koyama M, Lee T. TEMPO enables sequential genetic labeling and manipulation of vertebrate cell lineages. Neuron 2023; 111:345-361.e10. [PMID: 36417906 DOI: 10.1016/j.neuron.2022.10.035] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2022] [Revised: 08/15/2022] [Accepted: 10/26/2022] [Indexed: 11/24/2022]
Abstract
During development, regulatory factors appear in a precise order to determine cell fates over time. Consequently, to investigate complex tissue development, it is necessary to visualize and manipulate cell lineages with temporal control. Current strategies for tracing vertebrate cell lineages lack genetic access to sequentially produced cells. Here, we present TEMPO (Temporal Encoding and Manipulation in a Predefined Order), an imaging-readable genetic tool allowing differential labeling and manipulation of consecutive cell generations in vertebrates. TEMPO is based on CRISPR and powered by a cascade of gRNAs that drive orderly activation and inactivation of reporters and/or effectors. Using TEMPO to visualize zebrafish and mouse neurogenesis, we recapitulated birth-order-dependent neuronal fates. Temporally manipulating cell-cycle regulators in mouse cortex progenitors altered the proportion and distribution of neurons and glia, revealing the effects of temporal gene perturbation on serial cell fates. Thus, TEMPO enables sequential manipulation of molecular factors, crucial to study cell-type specification.
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Affiliation(s)
| | - Daniel Feliciano
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA 20147, USA
| | - Carla Belmonte-Mateos
- Department of Experimental and Health Sciences, Universitat Pompeu Fabra, PRBB, Barcelona 08003, Spain
| | - Rosa Linda Miyares
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA 20147, USA
| | - Jorge Garcia-Marques
- Centro Nacional de Biotecnologia, Consejo Superior de Investigaciones Cientificas, Madrid 28049, Spain
| | - Benjamin Foster
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA 20147, USA
| | - Sarah Lindo
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA 20147, USA
| | - Cristina Pujades
- Department of Experimental and Health Sciences, Universitat Pompeu Fabra, PRBB, Barcelona 08003, Spain
| | - Minoru Koyama
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA 20147, USA; Department of Biological Sciences, University of Toronto Scarborough, Toronto, ON M1C 1A4, Canada
| | - Tzumin Lee
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA 20147, USA.
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19
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Rovira-Clavé X, Drainas AP, Jiang S, Bai Y, Baron M, Zhu B, Dallas AE, Lee MC, Chu TP, Holzem A, Ayyagari R, Bhattacharya D, McCaffrey EF, Greenwald NF, Markovic M, Coles GL, Angelo M, Bassik MC, Sage J, Nolan GP. Spatial epitope barcoding reveals clonal tumor patch behaviors. Cancer Cell 2022; 40:1423-1439.e11. [PMID: 36240778 PMCID: PMC9673683 DOI: 10.1016/j.ccell.2022.09.014] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/29/2021] [Revised: 07/22/2022] [Accepted: 09/21/2022] [Indexed: 01/09/2023]
Abstract
Intratumoral heterogeneity is a seminal feature of human tumors contributing to tumor progression and response to treatment. Current technologies are still largely unsuitable to accurately track phenotypes and clonal evolution within tumors, especially in response to genetic manipulations. Here, we developed epitopes for imaging using combinatorial tagging (EpicTags), which we coupled to multiplexed ion beam imaging (EpicMIBI) for in situ tracking of barcodes within tissue microenvironments. Using EpicMIBI, we dissected the spatial component of cell lineages and phenotypes in xenograft models of small cell lung cancer. We observed emergent properties from mixed clones leading to the preferential expansion of clonal patches for both neuroendocrine and non-neuroendocrine cancer cell states in these models. In a tumor model harboring a fraction of PTEN-deficient cancer cells, we observed a non-autonomous increase of clonal patch size in PTEN wild-type cancer cells. EpicMIBI facilitates in situ interrogation of cell-intrinsic and cell-extrinsic processes involved in intratumoral heterogeneity.
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Affiliation(s)
- Xavier Rovira-Clavé
- Department of Pathology, Stanford University, Stanford, CA 94305, USA; Department of Microbiology and Immunology, Stanford University, Stanford, CA 94305, USA
| | - Alexandros P Drainas
- Department of Pediatrics, Stanford University, Stanford, CA 94305, USA; Department of Genetics, Stanford University, Stanford, CA 94305, USA
| | - Sizun Jiang
- Department of Pathology, Stanford University, Stanford, CA 94305, USA
| | - Yunhao Bai
- Department of Pathology, Stanford University, Stanford, CA 94305, USA
| | - Maya Baron
- Department of Pediatrics, Stanford University, Stanford, CA 94305, USA; Department of Genetics, Stanford University, Stanford, CA 94305, USA
| | - Bokai Zhu
- Department of Pathology, Stanford University, Stanford, CA 94305, USA; Department of Microbiology and Immunology, Stanford University, Stanford, CA 94305, USA
| | - Alec E Dallas
- Department of Pediatrics, Stanford University, Stanford, CA 94305, USA; Department of Genetics, Stanford University, Stanford, CA 94305, USA
| | - Myung Chang Lee
- Department of Pediatrics, Stanford University, Stanford, CA 94305, USA; Department of Genetics, Stanford University, Stanford, CA 94305, USA
| | - Theresa P Chu
- Department of Pathology, Stanford University, Stanford, CA 94305, USA
| | - Alessandra Holzem
- Department of Pediatrics, Stanford University, Stanford, CA 94305, USA; Department of Genetics, Stanford University, Stanford, CA 94305, USA
| | - Ramya Ayyagari
- Department of Pediatrics, Stanford University, Stanford, CA 94305, USA; Department of Genetics, Stanford University, Stanford, CA 94305, USA
| | - Debadrita Bhattacharya
- Department of Pediatrics, Stanford University, Stanford, CA 94305, USA; Department of Genetics, Stanford University, Stanford, CA 94305, USA
| | - Erin F McCaffrey
- Department of Pathology, Stanford University, Stanford, CA 94305, USA
| | - Noah F Greenwald
- Department of Pathology, Stanford University, Stanford, CA 94305, USA
| | - Maxim Markovic
- Department of Pathology, Stanford University, Stanford, CA 94305, USA
| | - Garry L Coles
- Department of Pediatrics, Stanford University, Stanford, CA 94305, USA; Department of Genetics, Stanford University, Stanford, CA 94305, USA
| | - Michael Angelo
- Department of Pathology, Stanford University, Stanford, CA 94305, USA
| | - Michael C Bassik
- Department of Genetics, Stanford University, Stanford, CA 94305, USA
| | - Julien Sage
- Department of Pediatrics, Stanford University, Stanford, CA 94305, USA; Department of Genetics, Stanford University, Stanford, CA 94305, USA.
| | - Garry P Nolan
- Department of Pathology, Stanford University, Stanford, CA 94305, USA.
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20
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Lu T, Ang CE, Zhuang X. Spatially resolved epigenomic profiling of single cells in complex tissues. Cell 2022; 185:4448-4464.e17. [PMID: 36272405 PMCID: PMC9691621 DOI: 10.1016/j.cell.2022.09.035] [Citation(s) in RCA: 59] [Impact Index Per Article: 29.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2021] [Revised: 08/22/2022] [Accepted: 09/26/2022] [Indexed: 11/06/2022]
Abstract
The recent development of spatial omics methods has enabled single-cell profiling of the transcriptome and 3D genome organization with high spatial resolution. Expanding the repertoire of spatial omics tools, a spatially resolved single-cell epigenomics method will accelerate understanding of the spatial regulation of cell and tissue functions. Here, we report a method for spatially resolved epigenomic profiling of single cells using in situ tagmentation and transcription followed by multiplexed imaging. We demonstrated the ability to profile histone modifications marking active promoters, putative enhancers, and silent promoters in individual cells, and generated high-resolution spatial atlas of hundreds of active promoters and putative enhancers in embryonic and adult mouse brains. Our results suggested putative promoter-enhancer pairs and enhancer hubs regulating developmentally important genes. We envision this approach will be generally applicable to spatial profiling of epigenetic modifications and DNA-binding proteins, advancing our understanding of how gene expression is spatiotemporally regulated by the epigenome.
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Affiliation(s)
- Tian Lu
- Howard Hughes Medical Institute, Harvard University, Cambridge, MA 02138, USA; Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA 02138, USA; Department of Physics, Harvard University, Cambridge, MA 02138, USA
| | - Cheen Euong Ang
- Howard Hughes Medical Institute, Harvard University, Cambridge, MA 02138, USA; Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA 02138, USA; Department of Physics, Harvard University, Cambridge, MA 02138, USA
| | - Xiaowei Zhuang
- Howard Hughes Medical Institute, Harvard University, Cambridge, MA 02138, USA; Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA 02138, USA; Department of Physics, Harvard University, Cambridge, MA 02138, USA.
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21
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Serrano A, Berthelet J, Naik SH, Merino D. Mastering the use of cellular barcoding to explore cancer heterogeneity. Nat Rev Cancer 2022; 22:609-624. [PMID: 35982229 DOI: 10.1038/s41568-022-00500-2] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 07/13/2022] [Indexed: 11/09/2022]
Abstract
Tumours are often composed of a multitude of malignant clones that are genomically unique, and only a few of them may have the ability to escape cancer therapy and grow as symptomatic lesions. As a result, tumours with a large degree of genomic diversity have a higher chance of leading to patient death. However, clonal fate can be driven by non-genomic features. In this context, new technologies are emerging not only to track the spatiotemporal fate of individual cells and their progeny but also to study their molecular features using various omics analysis. In particular, the recent development of cellular barcoding facilitates the labelling of tens to millions of cancer clones and enables the identification of the complex mechanisms associated with clonal fate in different microenvironments and in response to therapy. In this Review, we highlight the recent discoveries made using lentiviral-based cellular barcoding techniques, namely genetic and optical barcoding. We also emphasize the strengths and limitations of each of these technologies and discuss some of the key concepts that must be taken into consideration when one is designing barcoding experiments. Finally, we suggest new directions to further improve the use of these technologies in cancer research.
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Affiliation(s)
- Antonin Serrano
- Olivia Newton-John Cancer Research Institute, Heidelberg, Victoria, Australia
- School of Cancer Medicine, La Trobe University, Bundoora, Victoria, Australia
- Immunology Division, The Walter and Eliza Hall Institute of Medical Research, Parkville, Victoria, Australia
- Department of Medical Biology, Faculty of Medicine, Dentistry and Health Science, The University of Melbourne, Parkville, Victoria, Australia
| | - Jean Berthelet
- Olivia Newton-John Cancer Research Institute, Heidelberg, Victoria, Australia
- School of Cancer Medicine, La Trobe University, Bundoora, Victoria, Australia
| | - Shalin H Naik
- Immunology Division, The Walter and Eliza Hall Institute of Medical Research, Parkville, Victoria, Australia
- Department of Medical Biology, Faculty of Medicine, Dentistry and Health Science, The University of Melbourne, Parkville, Victoria, Australia
| | - Delphine Merino
- Olivia Newton-John Cancer Research Institute, Heidelberg, Victoria, Australia.
- School of Cancer Medicine, La Trobe University, Bundoora, Victoria, Australia.
- Immunology Division, The Walter and Eliza Hall Institute of Medical Research, Parkville, Victoria, Australia.
- Department of Medical Biology, Faculty of Medicine, Dentistry and Health Science, The University of Melbourne, Parkville, Victoria, Australia.
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22
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Walton RT, Singh A, Blainey PC. Pooled genetic screens with image-based profiling. Mol Syst Biol 2022; 18:e10768. [PMID: 36366905 PMCID: PMC9650298 DOI: 10.15252/msb.202110768] [Citation(s) in RCA: 8] [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] [Received: 10/22/2021] [Revised: 09/12/2022] [Accepted: 09/16/2022] [Indexed: 11/13/2022] Open
Abstract
Spatial structure in biology, spanning molecular, organellular, cellular, tissue, and organismal scales, is encoded through a combination of genetic and epigenetic factors in individual cells. Microscopy remains the most direct approach to exploring the intricate spatial complexity defining biological systems and the structured dynamic responses of these systems to perturbations. Genetic screens with deep single-cell profiling via image features or gene expression programs have the capacity to show how biological systems work in detail by cataloging many cellular phenotypes with one experimental assay. Microscopy-based cellular profiling provides information complementary to next-generation sequencing (NGS) profiling and has only recently become compatible with large-scale genetic screens. Optical screening now offers the scale needed for systematic characterization and is poised for further scale-up. We discuss how these methodologies, together with emerging technologies for genetic perturbation and microscopy-based multiplexed molecular phenotyping, are powering new approaches to reveal genotype-phenotype relationships.
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Affiliation(s)
- Russell T Walton
- Broad Institute of MIT and HarvardCambridgeMAUSA
- Department of Biological EngineeringMITCambridgeMAUSA
| | - Avtar Singh
- Broad Institute of MIT and HarvardCambridgeMAUSA
- Present address:
Department of Cellular and Tissue GenomicsGenentechSouth San FranciscoCAUSA
| | - Paul C Blainey
- Broad Institute of MIT and HarvardCambridgeMAUSA
- Department of Biological EngineeringMITCambridgeMAUSA
- Koch Institute for Integrative Cancer ResearchMITCambridgeMAUSA
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23
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Zhong L, Li J, Zu B, Zhu X, Lei D, Wang G, Hu X, Zhang T, Dou X. Highly Retentive, Anti-Interference, and Covert Individual Marking Taggant with Exceptional Skin Penetration. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2022; 9:e2201497. [PMID: 35748174 PMCID: PMC9443463 DOI: 10.1002/advs.202201497] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 04/02/2022] [Revised: 05/10/2022] [Indexed: 06/15/2023]
Abstract
The development of high-performance individual marking taggants is of great significance. However, the interaction between taggant and skin is not fully understood, and a standard for marking taggants has yet to be realized. To achieve a highly retentive, anti-interference, and covert individual marking fluorescent taggant, Mn2+ -doped NaYF4 :Yb/Er upconversion nanoparticles (UCNPs), are surface-functionalized with polyethyleneimine (PEI) to remarkably enhance the interaction between the amino groups and skin, and thus to facilitate the surface adhesion and chemical penetration of the taggant. Electrostatic interaction between PEI600 -UCNPs and skin as well as remarkable penetration inside the epidermis is responsible for excellent taggant retention capability, even while faced with robust washing, vigorous wiping, and rubbing for more than 100 cycles. Good anti-interference capability and reliable marking performance in real cases are ensured by an intrinsic upconversion characteristic with a distinct red luminescent emission under 980 nm excitation. The present methodology is expected to shed light on the design of high-performance individual marking taggants from the perspective of the underlying interaction between taggant and skin, and to help advance the use of fluorescent taggants for practical application, such as special character tracking.
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Affiliation(s)
- Lianggen Zhong
- Xinjiang Key laboratory of Explosives Safety ScienceXinjiang Technical Institute of Physics & ChemistryChinese Academy of SciencesUrumqi830011China
- Center of Materials Science and Optoelectronics EngineeringUniversity of Chinese Academy of SciencesBeijing100049China
| | - Jiguang Li
- Xinjiang Key laboratory of Explosives Safety ScienceXinjiang Technical Institute of Physics & ChemistryChinese Academy of SciencesUrumqi830011China
- Center of Materials Science and Optoelectronics EngineeringUniversity of Chinese Academy of SciencesBeijing100049China
| | - Baiyi Zu
- Xinjiang Key laboratory of Explosives Safety ScienceXinjiang Technical Institute of Physics & ChemistryChinese Academy of SciencesUrumqi830011China
| | - Xiaodan Zhu
- Xinjiang Key laboratory of Explosives Safety ScienceXinjiang Technical Institute of Physics & ChemistryChinese Academy of SciencesUrumqi830011China
- Center of Materials Science and Optoelectronics EngineeringUniversity of Chinese Academy of SciencesBeijing100049China
| | - Da Lei
- Xinjiang Key laboratory of Explosives Safety ScienceXinjiang Technical Institute of Physics & ChemistryChinese Academy of SciencesUrumqi830011China
| | - Guangfa Wang
- Xinjiang Key laboratory of Explosives Safety ScienceXinjiang Technical Institute of Physics & ChemistryChinese Academy of SciencesUrumqi830011China
| | - Xiaoyun Hu
- Xinjiang Key laboratory of Explosives Safety ScienceXinjiang Technical Institute of Physics & ChemistryChinese Academy of SciencesUrumqi830011China
- Center of Materials Science and Optoelectronics EngineeringUniversity of Chinese Academy of SciencesBeijing100049China
| | - Tianshi Zhang
- Xinjiang Key laboratory of Explosives Safety ScienceXinjiang Technical Institute of Physics & ChemistryChinese Academy of SciencesUrumqi830011China
- Center of Materials Science and Optoelectronics EngineeringUniversity of Chinese Academy of SciencesBeijing100049China
| | - Xincun Dou
- Xinjiang Key laboratory of Explosives Safety ScienceXinjiang Technical Institute of Physics & ChemistryChinese Academy of SciencesUrumqi830011China
- Center of Materials Science and Optoelectronics EngineeringUniversity of Chinese Academy of SciencesBeijing100049China
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24
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Liang Y, Wu S, Han W, Wang J, Xu C, Shi J, Zhang Z, Gao H, Zhang K, Li J. Visualizing Single-Nucleotide Variations in a Nuclear Genome Using Colocalization of Dual-Engineered CRISPR Probes. Anal Chem 2022; 94:11745-11752. [PMID: 35975698 DOI: 10.1021/acs.analchem.2c01208] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/29/2022]
Abstract
Direct visualization of single-nucleotide variation (SNV) in single cells is of great importance for understanding the spatial organization of genomes and their relationship with cell phenotypes. Herein, we developed a new strategy for visualizing SNVs in a nuclear genome using colocalization of dual-engineered CRISPR probes (CoDEC). By engineering the structure of sgRNA, we incorporated a hairpin in the spacer domain for improving SNV recognition specificity and a loop in the nonfunctional domain for localized signal amplification. Using guide probe-based colocalization strategy, we can successfully distinguish on-target true positive signals from the off-target false positives with high accuracy. Comparing with a proximity ligation-based assay (CasPLA), the probe colocalization strategy extended applicable target gene sites (the distance between two designed probes can be extended to around 200nt) and improved detection efficiency. This newly developed method provides a facile way for studying in situ information on SNVs in individual cells for basic research and clinical applications with single-molecule and single-nucleotide resolutions.
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Affiliation(s)
- Yan Liang
- School of Pharmaceutical Sciences, Collaborative Innovation Center of New Drug Research and Safety Evaluation, Key Laboratory of Targeting Therapy and Diagnosis for Critical Diseases, Zhengzhou University, Zhengzhou 450001, China
| | - Sixuan Wu
- School of Pharmaceutical Sciences, Collaborative Innovation Center of New Drug Research and Safety Evaluation, Key Laboratory of Targeting Therapy and Diagnosis for Critical Diseases, Zhengzhou University, Zhengzhou 450001, China
| | - Wenshuai Han
- School of Pharmaceutical Sciences, Collaborative Innovation Center of New Drug Research and Safety Evaluation, Key Laboratory of Targeting Therapy and Diagnosis for Critical Diseases, Zhengzhou University, Zhengzhou 450001, China
| | - Jinjin Wang
- School of Pharmaceutical Sciences, Collaborative Innovation Center of New Drug Research and Safety Evaluation, Key Laboratory of Targeting Therapy and Diagnosis for Critical Diseases, Zhengzhou University, Zhengzhou 450001, China
| | - Chenlu Xu
- School of Pharmaceutical Sciences, Collaborative Innovation Center of New Drug Research and Safety Evaluation, Key Laboratory of Targeting Therapy and Diagnosis for Critical Diseases, Zhengzhou University, Zhengzhou 450001, China
| | - Jinjin Shi
- School of Pharmaceutical Sciences, Collaborative Innovation Center of New Drug Research and Safety Evaluation, Key Laboratory of Targeting Therapy and Diagnosis for Critical Diseases, Zhengzhou University, Zhengzhou 450001, China
| | - Zhenzhong Zhang
- School of Pharmaceutical Sciences, Collaborative Innovation Center of New Drug Research and Safety Evaluation, Key Laboratory of Targeting Therapy and Diagnosis for Critical Diseases, Zhengzhou University, Zhengzhou 450001, China
| | - Hua Gao
- Department of Pathogen Biology, School of Basic Medical Sciences, Zhengzhou University, Zhengzhou 450001, China
| | - Kaixiang Zhang
- School of Pharmaceutical Sciences, Collaborative Innovation Center of New Drug Research and Safety Evaluation, Key Laboratory of Targeting Therapy and Diagnosis for Critical Diseases, Zhengzhou University, Zhengzhou 450001, China.,State Key Laboratory of Esophageal Cancer Prevention and Treatment, Zhengzhou 450001, China
| | - Jinghong Li
- Department of Chemistry, Key Laboratory of Bioorganic Phosphorus Chemistry and Chemical Biology, Beijing Key Laboratory for Microanalytical Methods and Instrumentation, Tsinghua University, Beijing 100084, China
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25
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Gutierrez C, Vilas CK, Wu CJ, Al'Khafaji AM. Functionalized Lineage Tracing Can Enable the Development of Homogenization-Based Therapeutic Strategies in Cancer. Front Immunol 2022; 13:859032. [PMID: 35603167 PMCID: PMC9120583 DOI: 10.3389/fimmu.2022.859032] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2022] [Accepted: 03/22/2022] [Indexed: 11/13/2022] Open
Abstract
The therapeutic landscape across many cancers has dramatically improved since the introduction of potent targeted agents and immunotherapy. Nonetheless, success of these approaches is too often challenged by the emergence of therapeutic resistance, fueled by intratumoral heterogeneity and the immense evolutionary capacity inherent to cancers. To date, therapeutic strategies have attempted to outpace the evolutionary tempo of cancer but frequently fail, resulting in lack of tumor response and/or relapse. This realization motivates the development of novel therapeutic approaches which constrain evolutionary capacity by reducing the degree of intratumoral heterogeneity prior to treatment. Systematic development of such approaches first requires the ability to comprehensively characterize heterogeneous populations over the course of a perturbation, such as cancer treatment. Within this context, recent advances in functionalized lineage tracing approaches now afford the opportunity to efficiently measure multimodal features of clones within a tumor at single cell resolution, enabling the linkage of these features to clonal fitness over the course of tumor progression and treatment. Collectively, these measurements provide insights into the dynamic and heterogeneous nature of tumors and can thus guide the design of homogenization strategies which aim to funnel heterogeneous cancer cells into known, targetable phenotypic states. We anticipate the development of homogenization therapeutic strategies to better allow for cancer eradication and improved clinical outcomes.
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Affiliation(s)
- Catherine Gutierrez
- Department of Medicine, Harvard Medical School, Boston, MA, United States
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, United States
| | - Caroline K Vilas
- Department of Molecular Biosciences, The University of Texas at Austin, Austin, TX, United States
- Division of Chemical Biology and Medicinal Chemistry, College of Pharmacy, The University of Texas at Austin, Austin, TX, United States
| | - Catherine J Wu
- Department of Medicine, Harvard Medical School, Boston, MA, United States
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, United States
- Department of Medicine, Brigham and Women's Hospital, Boston, MA, United States
- Broad Institute of MIT and Harvard, Cambridge, MA, United States
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26
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Abstract
Over the past decade, CRISPR has become as much a verb as it is an acronym, transforming biomedical research and providing entirely new approaches for dissecting all facets of cell biology. In cancer research, CRISPR and related tools have offered a window into previously intractable problems in our understanding of cancer genetics, the noncoding genome and tumour heterogeneity, and provided new insights into therapeutic vulnerabilities. Here, we review the progress made in the development of CRISPR systems as a tool to study cancer, and the emerging adaptation of these technologies to improve diagnosis and treatment.
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Affiliation(s)
- Alyna Katti
- Meyer Cancer Center, Weill Cornell Medicine, New York, NY, USA
- Weill Cornell Graduate School of Medical Science, Weill Cornell Medicine, New York, NY, USA
| | - Bianca J Diaz
- Meyer Cancer Center, Weill Cornell Medicine, New York, NY, USA
- Weill Cornell Graduate School of Medical Science, Weill Cornell Medicine, New York, NY, USA
| | - Christina M Caragine
- Department of Biology, New York University, New York, NY, USA
- New York Genome Center, New York, NY, USA
| | - Neville E Sanjana
- Department of Biology, New York University, New York, NY, USA.
- New York Genome Center, New York, NY, USA.
| | - Lukas E Dow
- Meyer Cancer Center, Weill Cornell Medicine, New York, NY, USA.
- Department of Medicine, Weill Cornell Medicine, New York, NY, USA.
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27
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Clonal relations in the mouse brain revealed by single-cell and spatial transcriptomics. Nat Neurosci 2022; 25:285-294. [PMID: 35210624 PMCID: PMC8904259 DOI: 10.1038/s41593-022-01011-x] [Citation(s) in RCA: 45] [Impact Index Per Article: 22.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2021] [Accepted: 01/11/2022] [Indexed: 01/02/2023]
Abstract
The mammalian brain contains many specialized cells that develop from a thin sheet of neuroepithelial progenitor cells. Single-cell transcriptomics revealed hundreds of molecularly diverse cell types in the nervous system, but the lineage relationships between mature cell types and progenitor cells are not well understood. Here we show in vivo barcoding of early progenitors to simultaneously profile cell phenotypes and clonal relations in the mouse brain using single-cell and spatial transcriptomics. By reconstructing thousands of clones, we discovered fate-restricted progenitor cells in the mouse hippocampal neuroepithelium and show that microglia are derived from few primitive myeloid precursors that massively expand to generate widely dispersed progeny. We combined spatial transcriptomics with clonal barcoding and disentangled migration patterns of clonally related cells in densely labeled tissue sections. Our approach enables high-throughput dense reconstruction of cell phenotypes and clonal relations at the single-cell and tissue level in individual animals and provides an integrated approach for understanding tissue architecture. Ratz et al. present an easy-to-use method to barcode progenitor cells, enabling profiling of cell phenotypes and clonal relations using single-cell and spatial transcriptomics, providing an integrated approach for understanding brain architecture.
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28
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Qiu X, Xu J, Cardoso Dos Santos M, Hildebrandt N. Multiplexed Biosensing and Bioimaging Using Lanthanide-Based Time-Gated Förster Resonance Energy Transfer. Acc Chem Res 2022; 55:551-564. [PMID: 35084817 DOI: 10.1021/acs.accounts.1c00691] [Citation(s) in RCA: 38] [Impact Index Per Article: 19.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Abstract
The necessity to scrutinize more and more biological molecules and interactions both in solution and on the cellular level has led to an increasing demand for sensitive and specific multiplexed diagnostic analysis. Photoluminescence (PL) detection is ideally suited for multiplexed biosensing and bioimaging because it is rapid and sensitive and there is an almost unlimited choice of fluorophores that provide a large versatility of photophysical properties, including PL intensities, spectra, and lifetimes.The most frequently used technique to detect multiple parameters from a single sample is spectral (or color) multiplexing with different fluorophores, such as organic dyes, fluorescent proteins, quantum dots, or lanthanide nanoparticles and complexes. In conventional PL biosensing approaches, each fluorophore requires a distinct detection channel and excitation wavelength. This drawback can be overcome by Förster resonance energy transfer (FRET) from lanthanide donors to other fluorophore acceptors. The lanthanides' multiple and spectrally narrow emission bands over a broad spectral range can overlap with several different acceptors at once, thereby allowing FRET from one donor to multiple acceptors. The lanthanides' extremely long PL lifetimes provide two important features. First, time-gated (TG) detection allows for efficient suppression of background fluorescence from the biological environment or directly excited acceptors. Second, temporal multiplexing, for which the PL lifetimes are adjusted by the interaction with the FRET acceptor, can be used to determine specific biomolecules and/or their conformation via distinct PL decays. The high signal-to-background ratios, reproducible and precise ratiometric and homogeneous (washing-free) sensing formats, and higher-order multiplexing capabilities of lanthanide-based TG-FRET have resulted in significant advances in the analysis of biomolecular recognition. Applications range from fundamental analysis of biomolecular interactions and conformations to high-throughput and point-of-care in vitro diagnostics and DNA sequencing to advanced optical encoding, using both liquid and solid samples and in situ, in vitro, and in vivo detection with high sensitivity and selectivity.In this Account, we discuss recent advances in lanthanide-based TG-FRET for the development and application of advanced immunoassays, nucleic acid sensing, and fluorescence imaging. In addition to the different spectral and temporal multiplexing approaches, we highlight the importance of the careful design and combination of different biological, organic, and inorganic molecules and nanomaterials for an adjustable FRET donor-acceptor distance that determines the ultimate performance of the diagnostic assays and conformational sensors in their physiological environment. We conclude by sharing our vision on how progress in the development of new sensing concepts, material combinations, and instrumentation can further advance TG-FRET multiplexing and accelerate its translation into routine clinical practice and the investigation of challenging biological systems.
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Affiliation(s)
- Xue Qiu
- School of Medicine and Pharmacy, Ocean University of China, Qingdao 266003, China
- Laboratory for Marine Drugs and Bioproducts of Qingdao National Laboratory for Marine Science and Technology, Qingdao 266237, China
| | - Jingyue Xu
- nanofret.com, Laboratoire COBRA, Université de Rouen Normandie, Normandie Université, CNRS, INSA Rouen, 76000 Rouen, France
| | - Marcelina Cardoso Dos Santos
- Institute for Integrative Biology of the Cell (I2BC), Université Paris-Saclay, CEA, CNRS, 91198 Gif-sur-Yvette, France
| | - Niko Hildebrandt
- nanofret.com, Laboratoire COBRA, Université de Rouen Normandie, Normandie Université, CNRS, INSA Rouen, 76000 Rouen, France
- Department of Chemistry, Seoul National University, Seoul 08826, South Korea
- Université Paris-Saclay, 91405 Orsay Cedex, France
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29
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Lohoff T, Ghazanfar S, Missarova A, Koulena N, Pierson N, Griffiths JA, Bardot ES, Eng CHL, Tyser RCV, Argelaguet R, Guibentif C, Srinivas S, Briscoe J, Simons BD, Hadjantonakis AK, Göttgens B, Reik W, Nichols J, Cai L, Marioni JC. Integration of spatial and single-cell transcriptomic data elucidates mouse organogenesis. Nat Biotechnol 2022; 40:74-85. [PMID: 34489600 PMCID: PMC8763645 DOI: 10.1038/s41587-021-01006-2] [Citation(s) in RCA: 140] [Impact Index Per Article: 70.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2021] [Accepted: 07/07/2021] [Indexed: 02/07/2023]
Abstract
Molecular profiling of single cells has advanced our knowledge of the molecular basis of development. However, current approaches mostly rely on dissociating cells from tissues, thereby losing the crucial spatial context of regulatory processes. Here, we apply an image-based single-cell transcriptomics method, sequential fluorescence in situ hybridization (seqFISH), to detect mRNAs for 387 target genes in tissue sections of mouse embryos at the 8-12 somite stage. By integrating spatial context and multiplexed transcriptional measurements with two single-cell transcriptome atlases, we characterize cell types across the embryo and demonstrate that spatially resolved expression of genes not profiled by seqFISH can be imputed. We use this high-resolution spatial map to characterize fundamental steps in the patterning of the midbrain-hindbrain boundary (MHB) and the developing gut tube. We uncover axes of cell differentiation that are not apparent from single-cell RNA-sequencing (scRNA-seq) data, such as early dorsal-ventral separation of esophageal and tracheal progenitor populations in the gut tube. Our method provides an approach for studying cell fate decisions in complex tissues and development.
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Affiliation(s)
- T Lohoff
- Wellcome-Medical Research Council Cambridge Stem Cell Institute, University of Cambridge, Cambridge, UK
- Department of Physiology, Development and Neuroscience, University of Cambridge, Cambridge, UK
- Epigenetics Programme, Babraham Institute, Cambridge, UK
| | - S Ghazanfar
- Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, UK
| | - A Missarova
- Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, UK
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Cambridge, UK
| | - N Koulena
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA, USA
| | - N Pierson
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA, USA
| | - J A Griffiths
- Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, UK
- Genomics Plc, Cambridge, UK
| | - E S Bardot
- Developmental Biology Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - C-H L Eng
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA, USA
| | - R C V Tyser
- Department of Physiology, Anatomy and Genetics, University of Oxford, Oxford, UK
| | - R Argelaguet
- Epigenetics Programme, Babraham Institute, Cambridge, UK
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Cambridge, UK
| | - C Guibentif
- Wellcome-Medical Research Council Cambridge Stem Cell Institute, University of Cambridge, Cambridge, UK
- Department of Haematology, University of Cambridge, Cambridge, UK
- Sahlgrenska Center for Cancer Research, Department of Microbiology and Immunology, University of Gothenburg, Gothenburg, Sweden
| | - S Srinivas
- Department of Physiology, Anatomy and Genetics, University of Oxford, Oxford, UK
| | - J Briscoe
- The Francis Crick Institute, London, UK
| | - B D Simons
- Wellcome-Medical Research Council Cambridge Stem Cell Institute, University of Cambridge, Cambridge, UK
- The Wellcome/Cancer Research UK Gurdon Institute, University of Cambridge, Cambridge, UK
- Department of Applied Mathematics and Theoretical Physics, Centre for Mathematical Sciences, University of Cambridge, Cambridge, UK
| | - A-K Hadjantonakis
- Developmental Biology Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - B Göttgens
- Wellcome-Medical Research Council Cambridge Stem Cell Institute, University of Cambridge, Cambridge, UK
- Department of Haematology, University of Cambridge, Cambridge, UK
| | - W Reik
- Wellcome-Medical Research Council Cambridge Stem Cell Institute, University of Cambridge, Cambridge, UK.
- Epigenetics Programme, Babraham Institute, Cambridge, UK.
- Centre for Trophoblast Research, University of Cambridge, Cambridge, UK.
- Wellcome Sanger Institute, Wellcome Genome Campus, Cambridge, UK.
| | - J Nichols
- Wellcome-Medical Research Council Cambridge Stem Cell Institute, University of Cambridge, Cambridge, UK.
- Department of Physiology, Development and Neuroscience, University of Cambridge, Cambridge, UK.
| | - L Cai
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA, USA.
| | - J C Marioni
- Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, UK.
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Cambridge, UK.
- Wellcome Sanger Institute, Wellcome Genome Campus, Cambridge, UK.
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30
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Foster B, Attwood M, Gibbs-Seymour I. Tools for Decoding Ubiquitin Signaling in DNA Repair. Front Cell Dev Biol 2021; 9:760226. [PMID: 34950659 PMCID: PMC8690248 DOI: 10.3389/fcell.2021.760226] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2021] [Accepted: 11/09/2021] [Indexed: 12/21/2022] Open
Abstract
The maintenance of genome stability requires dedicated DNA repair processes and pathways that are essential for the faithful duplication and propagation of chromosomes. These DNA repair mechanisms counteract the potentially deleterious impact of the frequent genotoxic challenges faced by cells from both exogenous and endogenous agents. Intrinsic to these mechanisms, cells have an arsenal of protein factors that can be utilised to promote repair processes in response to DNA lesions. Orchestration of the protein factors within the various cellular DNA repair pathways is performed, in part, by post-translational modifications, such as phosphorylation, ubiquitin, SUMO and other ubiquitin-like modifiers (UBLs). In this review, we firstly explore recent advances in the tools for identifying factors involved in both DNA repair and ubiquitin signaling pathways. We then expand on this by evaluating the growing repertoire of proteomic, biochemical and structural techniques available to further understand the mechanistic basis by which these complex modifications regulate DNA repair. Together, we provide a snapshot of the range of methods now available to investigate and decode how ubiquitin signaling can promote DNA repair and maintain genome stability in mammalian cells.
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Affiliation(s)
| | | | - Ian Gibbs-Seymour
- Department of Biochemistry, University of Oxford, Oxford, United Kingdom
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31
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Muto Y, Humphreys BD. Recent advances in lineage tracing for the kidney. Kidney Int 2021; 100:1179-1184. [PMID: 34217781 PMCID: PMC8608712 DOI: 10.1016/j.kint.2021.05.040] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2021] [Revised: 05/19/2021] [Accepted: 05/20/2021] [Indexed: 11/19/2022]
Abstract
Lineage tracing was originally developed by developmental biologists to identify all progeny of a single cell during morphogenesis. More recently this approach has been applied to other fields, including organ homeostasis and recovery from injury. Modern lineage tracing techniques typically rely on reporter gene expression induced by cell-specific DNA recombination. There have been important scientific advances in the last 10 years that have impacted lineage tracing approaches, including intersectional genetics, optical clearing techniques, and the use of sequencing-based genomic lineage tracing. The latter combines CRISPR-Cas9-based genetic scarring with single-cell RNA-sequencing that, in theory, could allow comprehensive reconstruction of a lineage tree for an entire organism. This review summarizes recent advances in lineage tracing technologies and outlines potential applications for kidney research.
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Affiliation(s)
- Yoshiharu Muto
- Division of Nephrology, Department of Medicine, Washington University in St. Louis School of Medicine, St. Louis, Missouri, USA
| | - Benjamin D Humphreys
- Division of Nephrology, Department of Medicine, Washington University in St. Louis School of Medicine, St. Louis, Missouri, USA; Department of Developmental Biology, Washington University in St. Louis School of Medicine, St. Louis, Missouri, USA.
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32
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Wolf S, Wan Y, McDole K. Current approaches to fate mapping and lineage tracing using image data. Development 2021; 148:dev198994. [PMID: 34498046 DOI: 10.1242/dev.198994] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
Visualizing, tracking and reconstructing cell lineages in developing embryos has been an ongoing effort for well over a century. Recent advances in light microscopy, labelling strategies and computational methods to analyse complex image datasets have enabled detailed investigations into the fates of cells. Combined with powerful new advances in genomics and single-cell transcriptomics, the field of developmental biology is able to describe the formation of the embryo like never before. In this Review, we discuss some of the different strategies and applications to lineage tracing in live-imaging data and outline software methodologies that can be applied to various cell-tracking challenges.
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Affiliation(s)
- Steffen Wolf
- MRC Laboratory of Molecular Biology, Cambridge Biomedical Campus, Cambridge CB2 0QH, UK
| | - Yinan Wan
- Biozentrum, University of Basel, Basel, 4056, Switzerland
| | - Katie McDole
- MRC Laboratory of Molecular Biology, Cambridge Biomedical Campus, Cambridge CB2 0QH, UK
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33
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Beitz AM, Oakes CG, Galloway KE. Synthetic gene circuits as tools for drug discovery. Trends Biotechnol 2021; 40:210-225. [PMID: 34364685 DOI: 10.1016/j.tibtech.2021.06.007] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2021] [Revised: 06/24/2021] [Accepted: 06/25/2021] [Indexed: 12/19/2022]
Abstract
Within mammalian systems, there exists enormous opportunity to use synthetic gene circuits to enhance phenotype-based drug discovery, to map the molecular origins of disease, and to validate therapeutics in complex cellular systems. While drug discovery has relied on marker staining and high-content imaging in cell-based assays, synthetic gene circuits expand the potential for precision and speed. Here we present a vision of how circuits can improve the speed and accuracy of drug discovery by enhancing the efficiency of hit triage, capturing disease-relevant dynamics in cell-based assays, and simplifying validation and readouts from organoids and microphysiological systems (MPS). By tracking events and cellular states across multiple length and time scales, circuits will transform how we decipher the causal link between molecular events and phenotypes to improve the selectivity and sensitivity of cell-based assays.
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Affiliation(s)
- Adam M Beitz
- Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA
| | - Conrad G Oakes
- Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA
| | - Kate E Galloway
- Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA.
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34
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Lewis SM, Asselin-Labat ML, Nguyen Q, Berthelet J, Tan X, Wimmer VC, Merino D, Rogers KL, Naik SH. Spatial omics and multiplexed imaging to explore cancer biology. Nat Methods 2021; 18:997-1012. [PMID: 34341583 DOI: 10.1038/s41592-021-01203-6] [Citation(s) in RCA: 238] [Impact Index Per Article: 79.3] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2021] [Accepted: 06/04/2021] [Indexed: 01/19/2023]
Abstract
Understanding intratumoral heterogeneity-the molecular variation among cells within a tumor-promises to address outstanding questions in cancer biology and improve the diagnosis and treatment of specific cancer subtypes. Single-cell analyses, especially RNA sequencing and other genomics modalities, have been transformative in revealing novel biomarkers and molecular regulators associated with tumor growth, metastasis and drug resistance. However, these approaches fail to provide a complete picture of tumor biology, as information on cellular location within the tumor microenvironment is lost. New technologies leveraging multiplexed fluorescence, DNA, RNA and isotope labeling enable the detection of tens to thousands of cancer subclones or molecular biomarkers within their native spatial context. The expeditious growth in these techniques, along with methods for multiomics data integration, promises to yield a more comprehensive understanding of cell-to-cell variation within and between individual tumors. Here we provide the current state and future perspectives on the spatial technologies expected to drive the next generation of research and diagnostic and therapeutic strategies for cancer.
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Affiliation(s)
- Sabrina M Lewis
- Advanced Technology and Biology Division, The Walter and Eliza Hall Institute of Medical Research, Parkville, Victoria, Australia.,Immunology Division, The Walter and Eliza Hall Institute of Medical Research, Parkville, Victoria, Australia.,Department of Medical Biology, Faculty of Medicine, Dentistry and Health Sciences, The University of Melbourne, Melbourne, Victoria, Australia
| | - Marie-Liesse Asselin-Labat
- Department of Medical Biology, Faculty of Medicine, Dentistry and Health Sciences, The University of Melbourne, Melbourne, Victoria, Australia.,Personalised Oncology Division, The Walter and Eliza Hall Institute of Medical Research, Parkville, Victoria, Australia
| | - Quan Nguyen
- Division of Genetics and Genomics, Institute for Molecular Bioscience, The University of Queensland, Brisbane, Queensland, Australia
| | - Jean Berthelet
- Olivia Newton-John Cancer Research Institute, Heidelberg, Victoria, Australia.,School of Cancer Medicine, La Trobe University, Bundoora, Victoria, Australia
| | - Xiao Tan
- Division of Genetics and Genomics, Institute for Molecular Bioscience, The University of Queensland, Brisbane, Queensland, Australia
| | - Verena C Wimmer
- Advanced Technology and Biology Division, The Walter and Eliza Hall Institute of Medical Research, Parkville, Victoria, Australia.,Department of Medical Biology, Faculty of Medicine, Dentistry and Health Sciences, The University of Melbourne, Melbourne, Victoria, Australia
| | - Delphine Merino
- Immunology Division, The Walter and Eliza Hall Institute of Medical Research, Parkville, Victoria, Australia.,Department of Medical Biology, Faculty of Medicine, Dentistry and Health Sciences, The University of Melbourne, Melbourne, Victoria, Australia.,Olivia Newton-John Cancer Research Institute, Heidelberg, Victoria, Australia.,School of Cancer Medicine, La Trobe University, Bundoora, Victoria, Australia
| | - Kelly L Rogers
- Advanced Technology and Biology Division, The Walter and Eliza Hall Institute of Medical Research, Parkville, Victoria, Australia. .,Department of Medical Biology, Faculty of Medicine, Dentistry and Health Sciences, The University of Melbourne, Melbourne, Victoria, Australia.
| | - Shalin H Naik
- Immunology Division, The Walter and Eliza Hall Institute of Medical Research, Parkville, Victoria, Australia. .,Department of Medical Biology, Faculty of Medicine, Dentistry and Health Sciences, The University of Melbourne, Melbourne, Victoria, Australia.
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35
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Mattiazzi Usaj M, Yeung CHL, Friesen H, Boone C, Andrews BJ. Single-cell image analysis to explore cell-to-cell heterogeneity in isogenic populations. Cell Syst 2021; 12:608-621. [PMID: 34139168 PMCID: PMC9112900 DOI: 10.1016/j.cels.2021.05.010] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2020] [Revised: 04/26/2021] [Accepted: 05/12/2021] [Indexed: 12/26/2022]
Abstract
Single-cell image analysis provides a powerful approach for studying cell-to-cell heterogeneity, which is an important attribute of isogenic cell populations, from microbial cultures to individual cells in multicellular organisms. This phenotypic variability must be explained at a mechanistic level if biologists are to fully understand cellular function and address the genotype-to-phenotype relationship. Variability in single-cell phenotypes is obscured by bulk readouts or averaging of phenotypes from individual cells in a sample; thus, single-cell image analysis enables a higher resolution view of cellular function. Here, we consider examples of both small- and large-scale studies carried out with isogenic cell populations assessed by fluorescence microscopy, and we illustrate the advantages, challenges, and the promise of quantitative single-cell image analysis.
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Affiliation(s)
- Mojca Mattiazzi Usaj
- Department of Chemistry and Biology, Ryerson University, Toronto, ON M5B 2K3, Canada
| | - Clarence Hue Lok Yeung
- The Donnelly Centre, University of Toronto, Toronto, ON M5S 3E1, Canada; Department of Molecular Genetics, University of Toronto, Toronto, ON M5S 3E1, Canada
| | - Helena Friesen
- The Donnelly Centre, University of Toronto, Toronto, ON M5S 3E1, Canada
| | - Charles Boone
- The Donnelly Centre, University of Toronto, Toronto, ON M5S 3E1, Canada; Department of Molecular Genetics, University of Toronto, Toronto, ON M5S 3E1, Canada; RIKEN Centre for Sustainable Resource Science, Wako, Saitama 351-0198, Japan
| | - Brenda J Andrews
- The Donnelly Centre, University of Toronto, Toronto, ON M5S 3E1, Canada; Department of Molecular Genetics, University of Toronto, Toronto, ON M5S 3E1, Canada.
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Chow KHK, Budde MW, Granados AA, Cabrera M, Yoon S, Cho S, Huang TH, Koulena N, Frieda KL, Cai L, Lois C, Elowitz MB. Imaging cell lineage with a synthetic digital recording system. Science 2021; 372:eabb3099. [PMID: 33833095 DOI: 10.1126/science.abb3099] [Citation(s) in RCA: 59] [Impact Index Per Article: 19.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2020] [Accepted: 02/25/2021] [Indexed: 12/13/2022]
Abstract
During multicellular development, spatial position and lineage history play powerful roles in controlling cell fate decisions. Using a serine integrase-based recording system, we engineered cells to record lineage information in a format that can be read out in situ. The system, termed integrase-editable memory by engineered mutagenesis with optical in situ readout (intMEMOIR), allowed in situ reconstruction of lineage relationships in cultured mouse cells and flies. intMEMOIR uses an array of independent three-state genetic memory elements that can recombine stochastically and irreversibly, allowing up to 59,049 distinct digital states. It reconstructed lineage trees in stem cells and enabled simultaneous analysis of single-cell clonal history, spatial position, and gene expression in Drosophila brain sections. These results establish a foundation for microscopy-readable lineage recording and analysis in diverse systems.
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Affiliation(s)
- Ke-Huan K Chow
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA 91125, USA
| | - Mark W Budde
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA 91125, USA
| | - Alejandro A Granados
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA 91125, USA
| | - Maria Cabrera
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA 91125, USA
| | - Shinae Yoon
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA 91125, USA
| | - Soomin Cho
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA 91125, USA
| | - Ting-Hao Huang
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA 91125, USA
| | - Noushin Koulena
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA 91125, USA
| | | | - Long Cai
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA 91125, USA
| | - Carlos Lois
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA 91125, USA.
| | - Michael B Elowitz
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA 91125, USA.
- Howard Hughes Medical Institute, California Institute of Technology, Pasadena, CA 91125, USA
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37
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Lawson M, Elf J. Imaging-based screens of pool-synthesized cell libraries. Nat Methods 2021; 18:358-365. [PMID: 33589838 DOI: 10.1038/s41592-020-01053-8] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2020] [Accepted: 12/21/2020] [Indexed: 01/30/2023]
Abstract
Mapping a genetic perturbation to a change in phenotype is at the core of biological research. Advances in microscopy have transformed these studies, but they have largely been confined to examining a few strains or cell lines at a time. In parallel, there has been a revolution in creating synthetic libraries of genetically altered cells with relative ease. Here we describe methods that combine these powerful tools to perform live-cell imaging of pool-generated strain libraries for improved biological discovery.
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Affiliation(s)
- Michael Lawson
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA, USA.
| | - Johan Elf
- Department of Cell and Molecular Biology Science for Life Laboratory, Uppsala University, Uppsala, Sweden.
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38
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Quinn JJ, Jones MG, Okimoto RA, Nanjo S, Chan MM, Yosef N, Bivona TG, Weissman JS. Single-cell lineages reveal the rates, routes, and drivers of metastasis in cancer xenografts. Science 2021; 371:eabc1944. [PMID: 33479121 PMCID: PMC7983364 DOI: 10.1126/science.abc1944] [Citation(s) in RCA: 138] [Impact Index Per Article: 46.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2020] [Revised: 09/23/2020] [Accepted: 12/17/2020] [Indexed: 12/11/2022]
Abstract
Detailed phylogenies of tumor populations can recount the history and chronology of critical events during cancer progression, such as metastatic dissemination. We applied a Cas9-based, single-cell lineage tracer to study the rates, routes, and drivers of metastasis in a lung cancer xenograft mouse model. We report deeply resolved phylogenies for tens of thousands of cancer cells traced over months of growth and dissemination. This revealed stark heterogeneity in metastatic capacity, arising from preexisting and heritable differences in gene expression. We demonstrate that these identified genes can drive invasiveness and uncovered an unanticipated suppressive role for KRT17 We also show that metastases disseminated via multidirectional tissue routes and complex seeding topologies. Overall, we demonstrate the power of tracing cancer progression at subclonal resolution and vast scale.
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Affiliation(s)
- Jeffrey J Quinn
- Department of Cellular and Molecular Pharmacology, University of California, San Francisco, San Francisco, CA, USA
- Howard Hughes Medical Institute, University of California, San Francisco, San Francisco, CA, USA
- Inscripta, Inc., Boulder, CO, USA
| | - Matthew G Jones
- Department of Cellular and Molecular Pharmacology, University of California, San Francisco, San Francisco, CA, USA
- Howard Hughes Medical Institute, University of California, San Francisco, San Francisco, CA, USA
- Biological and Medical Informatics Graduate Program, University of California, San Francisco, San Francisco, CA, USA
- Integrative Program in Quantitative Biology, University of California, San Francisco, San Francisco, CA, USA
- Center for Computational Biology, University of California, Berkeley, Berkeley, CA, USA
| | - Ross A Okimoto
- UCSF Department of Medicine, University of California, San Francisco, San Francisco, CA, USA
- Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, San Francisco, CA, USA
| | - Shigeki Nanjo
- UCSF Department of Medicine, University of California, San Francisco, San Francisco, CA, USA
- Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, San Francisco, CA, USA
| | - Michelle M Chan
- Department of Cellular and Molecular Pharmacology, University of California, San Francisco, San Francisco, CA, USA
- Howard Hughes Medical Institute, University of California, San Francisco, San Francisco, CA, USA
- Department of Molecular Biology, Princeton University, Princeton, NJ, USA
| | - Nir Yosef
- Center for Computational Biology, University of California, Berkeley, Berkeley, CA, USA.
- Department of Electrical Engineering and Computer Science, University of California, Berkeley, Berkeley, CA, USA
- Chan Zuckerberg Biohub Investigator, San Francisco, CA, USA
- Ragon Institute of Massachusetts General Hospital, MIT and Harvard University, Cambridge, MA, USA
| | - Trever G Bivona
- Department of Cellular and Molecular Pharmacology, University of California, San Francisco, San Francisco, CA, USA.
- UCSF Department of Medicine, University of California, San Francisco, San Francisco, CA, USA
- Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, San Francisco, CA, USA
| | - Jonathan S Weissman
- Department of Cellular and Molecular Pharmacology, University of California, San Francisco, San Francisco, CA, USA.
- Howard Hughes Medical Institute, University of California, San Francisco, San Francisco, CA, USA
- Whitehead Institute, Cambridge, MA, USA
- Department of Biology, Massachusetts Institute of Technology, Cambridge, MA, USA
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Wang NB, Beitz AM, Galloway KE. Engineering cell fate: Applying synthetic biology to cellular reprogramming. ACTA ACUST UNITED AC 2020; 24:18-31. [PMID: 36330198 PMCID: PMC9629175 DOI: 10.1016/j.coisb.2020.09.002] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Abstract
Cellular reprogramming drives cells from one stable identity to a new cell fate. By generating a diversity of previously inaccessible cell types from diverse genetic backgrounds, cellular reprogramming is rapidly transforming how we study disease. However, low efficiency and limited maturity have limited the adoption of in vitro-derived cellular models. To overcome these limitations and improve mechanistic understanding of cellular reprogramming, a host of synthetic biology tools have been deployed. Recent synthetic biology approaches have advanced reprogramming by tackling three significant challenges to reprogramming: delivery of reprogramming factors, epigenetic roadblocks, and latent donor identity. In addition, emerging insight from the molecular systems biology of reprogramming reveal how systems-level drivers of reprogramming can be harnessed to further advance reprogramming technologies. Furthermore, recently developed synthetic biology tools offer new modes for engineering cell fate.
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Affiliation(s)
- Nathan B Wang
- Department of Chemical Engineering, MIT, 25 Ames St., Cambridge, MA, 02139, USA
| | - Adam M Beitz
- Department of Chemical Engineering, MIT, 25 Ames St., Cambridge, MA, 02139, USA
| | - Kate E Galloway
- Department of Chemical Engineering, MIT, 25 Ames St., Cambridge, MA, 02139, USA
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40
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The art of lineage tracing: From worm to human. Prog Neurobiol 2020; 199:101966. [PMID: 33249090 DOI: 10.1016/j.pneurobio.2020.101966] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2020] [Revised: 11/03/2020] [Accepted: 11/22/2020] [Indexed: 12/20/2022]
Abstract
Reconstructing the genealogy of every cell that makes up an organism remains a long-standing challenge in developmental biology. Besides its relevance for understanding the mechanisms underlying normal and pathological development, resolving the lineage origin of cell types will be crucial to create these types on-demand. Multiple strategies have been deployed towards the problem of lineage tracing, ranging from direct observation to sophisticated genetic approaches. Here we discuss the achievements and limitations of past and current technology. Finally, we speculate about the future of lineage tracing and how to reach the next milestones in the field.
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41
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Zhang K, Deng R, Gao H, Teng X, Li J. Lighting up single-nucleotide variation in situ in single cells and tissues. Chem Soc Rev 2020; 49:1932-1954. [PMID: 32108196 DOI: 10.1039/c9cs00438f] [Citation(s) in RCA: 35] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
The ability to 'see' genetic information directly in single cells can provide invaluable insights into complex biological systems. In this review, we discuss recent advances of in situ imaging technologies for visualizing the subtlest sequence alteration, single-nucleotide variation (SNV), at single-cell level. The mechanism of recently developed methods for SNV discrimination are summarized in detail. With recent developments, single-cell SNV imaging methods have opened a new door for studying the heterogenous and stochastic genetic information in individual cells. Furthermore, SNV imaging can be used on morphologically preserved tissue, which can provide information on histological context for gene expression profiling in basic research and genetic diagnosis. Moreover, the ability to visualize SNVs in situ can be further developed into in situ sequencing technology. We expect this review to inspire more research work into in situ SNV imaging technologies for investigating cellular phenotypes and gene regulation at single-nucleotide resolution, and developing new clinical and biomedical applications.
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Affiliation(s)
- Kaixiang Zhang
- Department of Chemistry, Key Laboratory of Bioorganic Phosphorus Chemistry & Chemical Biology, Beijing Key Laboratory for Microanalytical Methods and Instrumentation, Tsinghua University, Beijing 100084, China. and School of Pharmaceutical Sciences, Zhengzhou University, Zhengzhou 450001, China
| | - Ruijie Deng
- Department of Chemistry, Key Laboratory of Bioorganic Phosphorus Chemistry & Chemical Biology, Beijing Key Laboratory for Microanalytical Methods and Instrumentation, Tsinghua University, Beijing 100084, China.
| | - Hua Gao
- Department of Chemistry, Key Laboratory of Bioorganic Phosphorus Chemistry & Chemical Biology, Beijing Key Laboratory for Microanalytical Methods and Instrumentation, Tsinghua University, Beijing 100084, China. and Department of Pathogeny Biology, Medical College, Zhengzhou University, Zhengzhou 450001, China
| | - Xucong Teng
- Department of Chemistry, Key Laboratory of Bioorganic Phosphorus Chemistry & Chemical Biology, Beijing Key Laboratory for Microanalytical Methods and Instrumentation, Tsinghua University, Beijing 100084, China.
| | - Jinghong Li
- Department of Chemistry, Key Laboratory of Bioorganic Phosphorus Chemistry & Chemical Biology, Beijing Key Laboratory for Microanalytical Methods and Instrumentation, Tsinghua University, Beijing 100084, China.
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42
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Tang W, Bronner ME. Neural crest lineage analysis: from past to future trajectory. Development 2020; 147:147/20/dev193193. [PMID: 33097550 DOI: 10.1242/dev.193193] [Citation(s) in RCA: 27] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
Since its discovery 150 years ago, the neural crest has intrigued investigators owing to its remarkable developmental potential and extensive migratory ability. Cell lineage analysis has been an essential tool for exploring neural crest cell fate and migration routes. By marking progenitor cells, one can observe their subsequent locations and the cell types into which they differentiate. Here, we review major discoveries in neural crest lineage tracing from a historical perspective. We discuss how advancing technologies have refined lineage-tracing studies, and how clonal analysis can be applied to questions regarding multipotency. We also highlight how effective progenitor cell tracing, when combined with recently developed molecular and imaging tools, such as single-cell transcriptomics, single-molecule fluorescence in situ hybridization and high-resolution imaging, can extend the scope of neural crest lineage studies beyond development to regeneration and cancer initiation.
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Affiliation(s)
- Weiyi Tang
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA 91125, USA
| | - Marianne E Bronner
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA 91125, USA
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43
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Zhou Y, Jia E, Pan M, Zhao X, Ge Q. Encoding Method of Single-cell Spatial Transcriptomics Sequencing. Int J Biol Sci 2020; 16:2663-2674. [PMID: 32792863 PMCID: PMC7415427 DOI: 10.7150/ijbs.43887] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2020] [Accepted: 07/20/2020] [Indexed: 12/11/2022] Open
Abstract
Despite significant advances in parallel single-cell RNA sequencing revealing astonishing cellular heterogeneity in many tissue types, the spatial information in the tissue context remains missing. Spatial transcriptome sequencing technology is designed to distinguish the gene expression of individual cells in their original location. The technology is important for the identification of tissue function, tracking developmental processes, and pathological and molecular detection. Encoding the position information is the key to spatial transcriptomics because different methods have different encoding efficiencies and application scenarios. In this review, we focus on the latest technologies of single-cell spatial transcriptomics, including technologies based on microwell plates, barcoded bead arrays, microdissection, in situ hybridization, and barcode in situ targeting, as well as mixed separation-based technologies. Moreover, we compare these encoding methods for use as a reference when choosing the appropriate technology.
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Affiliation(s)
- Ying Zhou
- State Key Laboratory of Bioelectronics, School of Biological Science & Medical Engineering, Southeast University, Nanjing 210096, China
| | - Erteng Jia
- State Key Laboratory of Bioelectronics, School of Biological Science & Medical Engineering, Southeast University, Nanjing 210096, China
| | - Min Pan
- School of Medicine, Southeast University, Nanjing 210097, China
| | - Xiangwei Zhao
- State Key Laboratory of Bioelectronics, School of Biological Science & Medical Engineering, Southeast University, Nanjing 210096, China
| | - Qinyu Ge
- State Key Laboratory of Bioelectronics, School of Biological Science & Medical Engineering, Southeast University, Nanjing 210096, China
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44
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Naseri G, Koffas MAG. Application of combinatorial optimization strategies in synthetic biology. Nat Commun 2020; 11:2446. [PMID: 32415065 PMCID: PMC7229011 DOI: 10.1038/s41467-020-16175-y] [Citation(s) in RCA: 71] [Impact Index Per Article: 17.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2019] [Accepted: 04/15/2020] [Indexed: 12/26/2022] Open
Abstract
In the first wave of synthetic biology, genetic elements, combined into simple circuits, are used to control individual cellular functions. In the second wave of synthetic biology, the simple circuits, combined into complex circuits, form systems-level functions. However, efforts to construct complex circuits are often impeded by our limited knowledge of the optimal combination of individual circuits. For example, a fundamental question in most metabolic engineering projects is the optimal level of enzymes for maximizing the output. To address this point, combinatorial optimization approaches have been established, allowing automatic optimization without prior knowledge of the best combination of expression levels of individual genes. This review focuses on current combinatorial optimization methods and emerging technologies facilitating their applications.
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Affiliation(s)
- Gita Naseri
- Institut für Chemie, Humboldt Universität zu Berlin, 12489, Berlin, Germany.
| | - Mattheos A G Koffas
- Center for Biotechnology, Rensselaer Polytechnic Institute, Troy, NY, USA.
- Department of Chemical and Biological Engineering, Rensselaer Polytechnic Institute, Troy, NY, USA.
- Department of Biological Sciences, Rensselaer Polytechnic Institute, Troy, NY, USA.
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45
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McKinley KL, Castillo-Azofeifa D, Klein OD. Tools and Concepts for Interrogating and Defining Cellular Identity. Cell Stem Cell 2020; 26:632-656. [PMID: 32386555 PMCID: PMC7250495 DOI: 10.1016/j.stem.2020.03.015] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Abstract
Defining the mechanisms that generate specialized cell types and coordinate their functions is critical for understanding organ development and renewal. New tools and discoveries are challenging and refining our definitions of a cell type. A rapidly growing toolkit for single-cell analyses has expanded the number of markers that can be assigned to a cell simultaneously, revealing heterogeneity within cell types that were previously regarded as homogeneous populations. Additionally, cell types defined by specific molecular markers can exhibit distinct, context-dependent functions; for example, between tissues in homeostasis and those responding to damage. Here we review the current technologies used to identify and characterize cells, and we discuss how experimental and pathological perturbations are adding increasing complexity to our definitions of cell identity.
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Affiliation(s)
- Kara L McKinley
- Department of Cellular and Molecular Pharmacology, University of California, San Francisco, San Francisco, CA, USA
| | - David Castillo-Azofeifa
- Department of Orofacial Sciences, University of California, San Francisco, San Francisco, CA, USA; Program in Craniofacial Biology, University of California, San Francisco, San Francisco, CA, USA
| | - Ophir D Klein
- Department of Orofacial Sciences, University of California, San Francisco, San Francisco, CA, USA; Program in Craniofacial Biology, University of California, San Francisco, San Francisco, CA, USA; Department of Pediatrics, University of California, San Francisco, San Francisco, CA, USA; Institute for Human Genetics, University of California, San Francisco, San Francisco, CA, USA.
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47
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Espinosa-Medina I, Garcia-Marques J, Cepko C, Lee T. High-throughput dense reconstruction of cell lineages. Open Biol 2019; 9:190229. [PMID: 31822210 PMCID: PMC6936253 DOI: 10.1098/rsob.190229] [Citation(s) in RCA: 14] [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: 09/20/2019] [Accepted: 11/12/2019] [Indexed: 12/11/2022] Open
Abstract
The first meeting exclusively dedicated to the 'High-throughput dense reconstruction of cell lineages' took place at Janelia Research Campus (Howard Hughes Medical Institute) from 14 to 18 April 2019. Organized by Tzumin Lee, Connie Cepko, Jorge Garcia-Marques and Isabel Espinosa-Medina, this meeting echoed the recent eruption of new tools that allow the reconstruction of lineages based on the phylogenetic analysis of DNA mutations induced during development. Combined with single-cell RNA sequencing, these tools promise to solve the lineage of complex model organisms at single-cell resolution. Here, we compile the conference consensus on the technological and computational challenges emerging from the use of the new strategies, as well as potential solutions.
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Affiliation(s)
- Isabel Espinosa-Medina
- Howard Hughes Medical Institute, Janelia Research Campus, 19700 Helix Drive, Ashburn, VA 20147, USA
| | - Jorge Garcia-Marques
- Howard Hughes Medical Institute, Janelia Research Campus, 19700 Helix Drive, Ashburn, VA 20147, USA
| | - Connie Cepko
- Department of Genetics and Ophthalmology, Harvard Medical School, Boston, MA 02115, USA
| | - Tzumin Lee
- Howard Hughes Medical Institute, Janelia Research Campus, 19700 Helix Drive, Ashburn, VA 20147, USA
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