1
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Carlson CK, Loveless TB, Milisavljevic M, Kelly PI, Mills JH, Tyo KEJ, Liu CC. A Massively Parallel In Vivo Assay of TdT Mutants Yields Variants with Altered Nucleotide Insertion Biases. ACS Synth Biol 2024. [PMID: 39302688 DOI: 10.1021/acssynbio.4c00414] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/22/2024]
Abstract
Terminal deoxynucleotidyl transferase (TdT) is a unique DNA polymerase capable of template-independent extension of DNA. TdT's de novo DNA synthesis ability has found utility in DNA recording, DNA data storage, oligonucleotide synthesis, and nucleic acid labeling, but TdT's intrinsic nucleotide biases limit its versatility in such applications. Here, we describe a multiplexed assay for profiling and engineering the bias and overall activity of TdT variants with high throughput. In our assay, a library of TdTs is encoded next to a CRISPR-Cas9 target site in HEK293T cells. Upon transfection of Cas9 and sgRNA, the target site is cut, allowing TdT to intercept the double-strand break and add nucleotides. Each resulting insertion is sequenced alongside the identity of the TdT variant that generated it. Using this assay, 25,623 unique TdT variants, constructed by site-saturation mutagenesis at strategic positions, were profiled. This resulted in the isolation of several altered-bias TdTs that expanded the capabilities of our TdT-based DNA recording system, Cell HistorY Recording by Ordered InsertioN (CHYRON), by increasing the information density of recording through an unbiased TdT and achieving dual-channel recording of two distinct inducers (hypoxia and Wnt) through two differently biased TdTs. Select TdT variants were also tested in vitro, revealing concordance between each variant's in vitro bias and the in vivo bias determined from the multiplexed high throughput assay. Overall, our work and the multiplex assay it features should support the continued development of TdT-based DNA recorders, in vitro applications of TdT, and further study of the biology of TdT.
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Affiliation(s)
- Courtney K Carlson
- Department of Biomedical Engineering, University of California, Irvine, California 92697, United States
- Center for Synthetic Biology, University of California, Irvine, California 92697, United States
| | - Theresa B Loveless
- Department of Biomedical Engineering, University of California, Irvine, California 92697, United States
- Center for Synthetic Biology, University of California, Irvine, California 92697, United States
- Department of BioSciences, Rice University, Houston, Texas 77005, United States
| | - Marija Milisavljevic
- Department of Chemical and Biological Engineering, Northwestern University, Evanston, Illinois 60208, United States
| | - Patrick I Kelly
- Center for Molecular Design and Biomimetics, The Biodesign Institute, Arizona State University, Tempe, Arizona 82587, United States
- School of Molecular Sciences, Arizona State University, Tempe, Arizona 82587, United States
| | - Jeremy H Mills
- Center for Molecular Design and Biomimetics, The Biodesign Institute, Arizona State University, Tempe, Arizona 82587, United States
- School of Molecular Sciences, Arizona State University, Tempe, Arizona 82587, United States
| | - Keith E J Tyo
- Department of Chemical and Biological Engineering, Northwestern University, Evanston, Illinois 60208, United States
| | - Chang C Liu
- Department of Biomedical Engineering, University of California, Irvine, California 92697, United States
- Center for Synthetic Biology, University of California, Irvine, California 92697, United States
- Department of Molecular Biology & Biochemistry, University of California, Irvine, California 92697, United States
- Department of Chemistry, University of California, Irvine, California 92697, United States
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2
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Pedroza DA, Gao Y, Zhang XHF, Rosen JM. Leveraging preclinical models of metastatic breast cancer. Biochim Biophys Acta Rev Cancer 2024; 1879:189163. [PMID: 39084494 PMCID: PMC11390310 DOI: 10.1016/j.bbcan.2024.189163] [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: 11/17/2023] [Revised: 07/24/2024] [Accepted: 07/25/2024] [Indexed: 08/02/2024]
Abstract
Women that present to the clinic with established breast cancer metastases have limited treatment options. Yet, the majority of preclinical studies are actually not directed at developing treatment regimens for established metastatic disease. In this review we will discuss the current state of preclinical macro-metastatic breast cancer models, including, but not limited to syngeneic GEMM, PDX and xenografts. Challenges within these models which are often overlooked include fluorophore-immunogenic neoantigens, differences in experimental vs spontaneous metastasis and tumor heterogeneity. Furthermore, due to cell plasticity in the tumor immune microenvironment (TIME) of the metastatic landscape, the treatment efficacy of newly approved immune checkpoint blockade (ICB) may differ in metastatic sites as compared to primary localized tumors.
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Affiliation(s)
- Diego A Pedroza
- Department of Molecular and Cellular Biology, Baylor College of Medicine, Houston, TX, United States of America; Lester and Sue Smith Breast Center, Baylor College of Medicine, Houston, TX, United States of America; Dan L. Duncan Comprehensive Cancer Center, Baylor College of Medicine, Houston, TX, United States of America
| | - Yang Gao
- Department of Molecular and Cellular Biology, Baylor College of Medicine, Houston, TX, United States of America; Lester and Sue Smith Breast Center, Baylor College of Medicine, Houston, TX, United States of America; Dan L. Duncan Comprehensive Cancer Center, Baylor College of Medicine, Houston, TX, United States of America
| | - Xiang H-F Zhang
- Department of Molecular and Cellular Biology, Baylor College of Medicine, Houston, TX, United States of America; Lester and Sue Smith Breast Center, Baylor College of Medicine, Houston, TX, United States of America; Dan L. Duncan Comprehensive Cancer Center, Baylor College of Medicine, Houston, TX, United States of America
| | - Jeffrey M Rosen
- Department of Molecular and Cellular Biology, Baylor College of Medicine, Houston, TX, United States of America; Dan L. Duncan Comprehensive Cancer Center, Baylor College of Medicine, Houston, TX, United States of America.
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3
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Jang H, Yim SS. Toward DNA-Based Recording of Biological Processes. Int J Mol Sci 2024; 25:9233. [PMID: 39273181 PMCID: PMC11394691 DOI: 10.3390/ijms25179233] [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: 07/02/2024] [Revised: 08/21/2024] [Accepted: 08/24/2024] [Indexed: 09/15/2024] Open
Abstract
Exploiting the inherent compatibility of DNA-based data storage with living cells, various cellular recording approaches have been developed for recording and retrieving biologically relevant signals in otherwise inaccessible locations, such as inside the body. This review provides an overview of the current state of engineered cellular memory systems, highlighting their design principles, advantages, and limitations. We examine various technologies, including CRISPR-Cas systems, recombinases, retrons, and DNA methylation, that enable these recording systems. Additionally, we discuss potential strategies for improving recording accuracy, scalability, and durability to address current limitations in the field. This emerging modality of biological measurement will be key to gaining novel insights into diverse biological processes and fostering the development of various biotechnological applications, from environmental sensing to disease monitoring and beyond.
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Affiliation(s)
- Hyeri Jang
- Department of Biological Sciences, Korea Advanced Institute of Science and Technology (KAIST), Daejeon 34141, Republic of Korea
| | - Sung Sun Yim
- Department of Biological Sciences, Korea Advanced Institute of Science and Technology (KAIST), Daejeon 34141, Republic of Korea
- Graduate School of Engineering Biology, Korea Advanced Institute of Science and Technology (KAIST), Daejeon 34141, Republic of Korea
- KAIST Institute for BioCentury, Korea Advanced Institute of Science and Technology (KAIST), Daejeon 34141, Republic of Korea
- Korea Research Institute of Bioscience and Biotechnology (KRIBB), Daejeon 34141, Republic of Korea
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4
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Liu F, Zhang X, Yang Y. Simulation of CRISPR-Cas9 editing on evolving barcode and accuracy of lineage tracing. Sci Rep 2024; 14:19213. [PMID: 39160220 PMCID: PMC11333585 DOI: 10.1038/s41598-024-70154-7] [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: 04/24/2024] [Accepted: 08/13/2024] [Indexed: 08/21/2024] Open
Abstract
We designed a simulation program that mimics the CRISPR-Cas9 editing on evolving barcode and double strand break repair procedure along with cell divisions. Emerging barcode mutations tend to build upon previously existing mutations, occurring sequentially with each generation. This process results in a unique mutation profile in each cell. We sample the barcodes in leaf cells and reconstruct the lineage, comparing it to the original lineage tree to test algorithm accuracy under different parameter settings. Our computational simulations validate the reasonable assumptions deduced from experimental observations, emphasizing that factors such as sampling size, barcode length, multiple barcodes, indel probabilities, and Cas9 activity are critical for accurate and successful lineage tracing. Among the many factors we found that sampling size and indel probabilities are two major ones that affect lineage tracing accuracy. Large segment deletions in early generations could greatly impact lineage accuracy. These simulation results offer insightful recommendations for enhancing the design and analysis of Cas9-mediated molecular barcodes in actual experiments.
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Affiliation(s)
- Fengshuo Liu
- Graduate Program in Cancer and Cell Biology, Baylor College of Medicine, One Baylor Plaza, Houston, TX, 77030, USA
| | - Xiang Zhang
- Lester and Sue Smith Breast Center, Baylor College of Medicine, One Baylor Plaza, Houston, TX, 77030, USA
| | - Yipeng Yang
- Department of Mathematics and Statistics, University of Houston - Clear Lake, 2700 Bay Area Blvd, Houston, TX, 77058, USA.
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5
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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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6
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Carlson CK, Loveless TB, Milisavljevic M, Kelly PI, Mills JH, Tyo KEJ, Liu CC. A massively parallel in vivo assay of TdT mutants yields variants with altered nucleotide insertion biases. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.06.11.598561. [PMID: 38915690 PMCID: PMC11195295 DOI: 10.1101/2024.06.11.598561] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/26/2024]
Abstract
Terminal deoxynucleotidyl transferase (TdT) is a unique DNA polymerase capable of template-independent extension of DNA with random nucleotides. TdT's de novo DNA synthesis ability has found utility in DNA recording, DNA data storage, oligonucleotide synthesis, and nucleic acid labeling, but TdT's intrinsic nucleotide biases limit its versatility in such applications. Here, we describe a multiplexed assay for profiling and engineering the bias and overall activity of TdT variants in high throughput. In our assay, a library of TdTs is encoded next to a CRISPR-Cas9 target site in HEK293T cells. Upon transfection of Cas9 and sgRNA, the target site is cut, allowing TdT to intercept the double strand break and add nucleotides. Each resulting insertion is sequenced alongside the identity of the TdT variant that generated it. Using this assay, 25,623 unique TdT variants, constructed by site-saturation mutagenesis at strategic positions, were profiled. This resulted in the isolation of several altered-bias TdTs that expanded the capabilities of our TdT-based DNA recording system, Cell History Recording by Ordered Insertion (CHYRON), by increasing the information density of recording through an unbiased TdT and achieving dual-channel recording of two distinct inducers (hypoxia and Wnt) through two differently biased TdTs. Select TdT variants were also tested in vitro , revealing concordance between each variant's in vitro bias and the in vivo bias determined from the multiplexed high throughput assay. Overall, our work, and the multiplex assay it features, should support the continued development of TdT-based DNA recorders, in vitro applications of TdT, and further study of the biology of TdT.
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7
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Aalam SMM, Nguyen LV, Ritting ML, Kannan N. Clonal tracking in cancer and metastasis. Cancer Metastasis Rev 2024; 43:639-656. [PMID: 37910295 DOI: 10.1007/s10555-023-10149-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/01/2023] [Accepted: 10/16/2023] [Indexed: 11/03/2023]
Abstract
The eradication of many cancers has proven challenging due to the presence of functionally and genetically heterogeneous clones maintained by rare cancer stem cells (CSCs), which contribute to disease progression, treatment refractoriness, and late relapse. The characterization of functional CSC activity has necessitated the development of modern clonal tracking strategies. This review describes viral-based and CRISPR-Cas9-based cellular barcoding, lineage tracing, and imaging-based approaches. DNA-based cellular barcoding technology is emerging as a powerful and robust strategy that has been widely applied to in vitro and in vivo model systems, including patient-derived xenograft models. This review also highlights the potential of these methods for use in the clinical and drug discovery contexts and discusses the important insights gained from such approaches.
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Affiliation(s)
| | - Long Viet Nguyen
- Princess Margaret Cancer Centre, University Health Network, Toronto, Ontario, Canada
- Department of Medicine, University of Toronto, Toronto, Ontario, Canada
- Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada
| | - Megan L Ritting
- Department of Laboratory Medicine and Pathology, Mayo Clinic, 200 First St SW, Rochester, MN, 55905, USA
| | - Nagarajan Kannan
- Department of Laboratory Medicine and Pathology, Mayo Clinic, 200 First St SW, Rochester, MN, 55905, USA.
- Mayo Clinic Comprehensive Cancer Center, Mayo Clinic, Rochester, MN, USA.
- Center for Regenerative Biotherapeutics, Mayo Clinic, Rochester, MN, USA.
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8
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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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9
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Manso BA, Rodriguez y Baena A, Forsberg EC. From Hematopoietic Stem Cells to Platelets: Unifying Differentiation Pathways Identified by Lineage Tracing Mouse Models. Cells 2024; 13:704. [PMID: 38667319 PMCID: PMC11048769 DOI: 10.3390/cells13080704] [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: 03/29/2024] [Revised: 04/17/2024] [Accepted: 04/17/2024] [Indexed: 04/28/2024] Open
Abstract
Platelets are the terminal progeny of megakaryocytes, primarily produced in the bone marrow, and play critical roles in blood homeostasis, clotting, and wound healing. Traditionally, megakaryocytes and platelets are thought to arise from multipotent hematopoietic stem cells (HSCs) via multiple discrete progenitor populations with successive, lineage-restricting differentiation steps. However, this view has recently been challenged by studies suggesting that (1) some HSC clones are biased and/or restricted to the platelet lineage, (2) not all platelet generation follows the "canonical" megakaryocytic differentiation path of hematopoiesis, and (3) platelet output is the default program of steady-state hematopoiesis. Here, we specifically investigate the evidence that in vivo lineage tracing studies provide for the route(s) of platelet generation and investigate the involvement of various intermediate progenitor cell populations. We further identify the challenges that need to be overcome that are required to determine the presence, role, and kinetics of these possible alternate pathways.
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Affiliation(s)
- Bryce A. Manso
- Institute for the Biology of Stem Cells, University of California-Santa Cruz, Santa Cruz, CA 95064, USA
- Department of Biomolecular Engineering, University of California-Santa Cruz, Santa Cruz, CA 95064, USA
| | - Alessandra Rodriguez y Baena
- Institute for the Biology of Stem Cells, University of California-Santa Cruz, Santa Cruz, CA 95064, USA
- Program in Biomedical Sciences and Engineering, Department of Molecular, Cell, and Developmental Biology, University of California-Santa Cruz, Santa Cruz, CA 95064, USA
| | - E. Camilla Forsberg
- Institute for the Biology of Stem Cells, University of California-Santa Cruz, Santa Cruz, CA 95064, USA
- Department of Biomolecular Engineering, University of California-Santa Cruz, Santa Cruz, CA 95064, USA
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10
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Wang L, Dong W, Yin Z, Sheng J, Ezeana CF, Yang L, Yu X, Wong SSY, Wan Z, Danforth RL, Han K, Gao D, Wong STC. Charting Single Cell Lineage Dynamics and Mutation Networks via Homing CRISPR. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.01.05.574236. [PMID: 38260351 PMCID: PMC10802354 DOI: 10.1101/2024.01.05.574236] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/24/2024]
Abstract
Single cell lineage tracing, essential for unraveling cellular dynamics in disease evolution is critical for developing targeted therapies. CRISPR-Cas9, known for inducing permanent and cumulative mutations, is a cornerstone in lineage tracing. The novel homing guide RNA (hgRNA) technology enhances this by enabling dynamic retargeting and facilitating ongoing genetic modifications. Charting these mutations, especially through successive hgRNA edits, poses a significant challenge. Our solution, LINEMAP, is a computational framework designed to trace and map these mutations with precision. LINEMAP meticulously discerns mutation alleles at single-cell resolution and maps their complex interrelationships through a mutation evolution network. By utilizing a Markov Process model, we can predict mutation transition probabilities, revealing potential mutational routes and pathways. Our reconstruction algorithm, anchored in the Markov model's attributes, reconstructs cellular lineage pathways, shedding light on the cell's evolutionary journey to the minutiae of single-cell division. Our findings reveal an intricate network of mutation evolution paired with a predictive Markov model, advancing our capability to reconstruct single-cell lineage via hgRNA. This has substantial implications for advancing our understanding of biological mechanisms and propelling medical research forward.
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Affiliation(s)
- Lin Wang
- Department of System Medicine and Bioengineering, Houston Methodist Neal Cancer Center, Houston, Texas 77030
| | - Wenjuan Dong
- Department of System Medicine and Bioengineering, Houston Methodist Neal Cancer Center, Houston, Texas 77030
| | - Zheng Yin
- Department of System Medicine and Bioengineering, Houston Methodist Neal Cancer Center, Houston, Texas 77030
- Biostatistics and Bioinformatics Shared Resource, Houston Methodist Neal Cancer Center, Houston, Texas 77030
| | - Jianting Sheng
- Department of System Medicine and Bioengineering, Houston Methodist Neal Cancer Center, Houston, Texas 77030
| | - Chika F. Ezeana
- Department of System Medicine and Bioengineering, Houston Methodist Neal Cancer Center, Houston, Texas 77030
| | - Li Yang
- T.T. and W. F. Chao Center for BRAIN, Houston Methodist Research Institute, Houston, Texas 77030
| | - Xiaohui Yu
- Department of System Medicine and Bioengineering, Houston Methodist Neal Cancer Center, Houston, Texas 77030
| | | | - Zhihao Wan
- Department of System Medicine and Bioengineering, Houston Methodist Neal Cancer Center, Houston, Texas 77030
| | - Rebecca L. Danforth
- Department of System Medicine and Bioengineering, Houston Methodist Neal Cancer Center, Houston, Texas 77030
| | - Kun Han
- Department of System Medicine and Bioengineering, Houston Methodist Neal Cancer Center, Houston, Texas 77030
| | - Dingcheng Gao
- Department of Cell & Development Biology, Weill Cornell Medical College, New York, NY 10065
| | - Stephen T. C. Wong
- Department of System Medicine and Bioengineering, Houston Methodist Neal Cancer Center, Houston, Texas 77030
- Departments of Radiology, Pathology and Genomic Medicine, Houston Methodist Hospital, Weill Cornell Medical College, Houston, TX 77030
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11
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Kim IS. DNA Barcoding Technology for Lineage Recording and Tracing to Resolve Cell Fate Determination. Cells 2023; 13:27. [PMID: 38201231 PMCID: PMC10778210 DOI: 10.3390/cells13010027] [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: 11/18/2023] [Revised: 12/18/2023] [Accepted: 12/20/2023] [Indexed: 01/12/2024] Open
Abstract
In various biological contexts, cells receive signals and stimuli that prompt them to change their current state, leading to transitions into a future state. This change underlies the processes of development, tissue maintenance, immune response, and the pathogenesis of various diseases. Following the path of cells from their initial identity to their current state reveals how cells adapt to their surroundings and undergo transformations to attain adjusted cellular states. DNA-based molecular barcoding technology enables the documentation of a phylogenetic tree and the deterministic events of cell lineages, providing the mechanisms and timing of cell lineage commitment that can either promote homeostasis or lead to cellular dysregulation. This review comprehensively presents recently emerging molecular recording technologies that utilize CRISPR/Cas systems, base editing, recombination, and innate variable sequences in the genome. Detailing their underlying principles, applications, and constraints paves the way for the lineage tracing of every cell within complex biological systems, encompassing the hidden steps and intermediate states of organism development and disease progression.
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Affiliation(s)
- Ik Soo Kim
- Department of Microbiology, Gachon University College of Medicine, Incheon 21999, Republic of Korea
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12
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Islam M, Yang Y, Simmons AJ, Shah VM, Pavan MK, Xu Y, Tasneem N, Chen Z, Trinh LT, Molina P, Ramirez-Solano MA, Sadien I, Dou J, Chen K, Magnuson MA, Rathmell JC, Macara IG, Winton D, Liu Q, Zafar H, Kalhor R, Church GM, Shrubsole MJ, Coffey RJ, Lau KS. Temporal recording of mammalian development and precancer. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.12.18.572260. [PMID: 38187699 PMCID: PMC10769302 DOI: 10.1101/2023.12.18.572260] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/09/2024]
Abstract
Key to understanding many biological phenomena is knowing the temporal ordering of cellular events, which often require continuous direct observations [1, 2]. An alternative solution involves the utilization of irreversible genetic changes, such as naturally occurring mutations, to create indelible markers that enables retrospective temporal ordering [3-8]. Using NSC-seq, a newly designed and validated multi-purpose single-cell CRISPR platform, we developed a molecular clock approach to record the timing of cellular events and clonality in vivo , while incorporating assigned cell state and lineage information. Using this approach, we uncovered precise timing of tissue-specific cell expansion during murine embryonic development and identified new intestinal epithelial progenitor states by their unique genetic histories. NSC-seq analysis of murine adenomas and single-cell multi-omic profiling of human precancers as part of the Human Tumor Atlas Network (HTAN), including 116 scRNA-seq datasets and clonal analysis of 418 human polyps, demonstrated the occurrence of polyancestral initiation in 15-30% of colonic precancers, revealing their origins from multiple normal founders. Thus, our multimodal framework augments existing single-cell analyses and lays the foundation for in vivo multimodal recording, enabling the tracking of lineage and temporal events during development and tumorigenesis.
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13
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Friedman-DeLuca M, Patel PP, Karadal-Ferrena B, Barth ND, Duran CL, Ye X, Papanicolaou M, Condeelis JS, Oktay MH, Borriello L, Entenberg D. Tracking Tumor Cell Dissemination from Lung Metastases Using Photoconversion. J Vis Exp 2023:10.3791/65732. [PMID: 37486129 PMCID: PMC10832329 DOI: 10.3791/65732] [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: 07/25/2023] Open
Abstract
Metastasis - the systemic spread of cancer - is the leading cause of cancer-related deaths. Although metastasis is commonly thought of as a unidirectional process wherein cells from the primary tumor disseminate and seed metastases, tumor cells in existing metastases can also redisseminate and give rise to new lesions in tertiary sites in a process known as "metastasis-from-metastases" or "metastasis-to-metastasis seeding." Metastasis-to-metastasis seeding may increase the metastatic burden and decrease the patient's quality of life and survival. Therefore, understanding the processes behind this phenomenon is crucial to refining treatment strategies for patients with metastatic cancer. Little is known about metastasis-to-metastasis seeding, due in part to logistical and technological limitations. Studies on metastasis-to-metastasis seeding rely primarily on sequencing methods, which may not be practical for researchers studying the exact timing of metastasis-to-metastasis seeding events or what promotes or prevents them. This highlights the lack of methodologies that facilitate the study of metastasis-to-metastasis seeding. To address this, we have developed - and describe herein - a murine surgical protocol for the selective photoconversion of lung metastases, allowing specific marking and fate tracking of tumor cells redisseminating from the lung to tertiary sites. To our knowledge, this is the only method for studying tumor cell redissemination and metastasis-to-metastasis seeding from the lungs that does not require genomic analysis.
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Affiliation(s)
- Madeline Friedman-DeLuca
- Department of Pathology, Albert Einstein College of Medicine/Montefiore Medical Center; Cancer Dormancy and Tumor Microenvironment Institute, Albert Einstein College of Medicine/Montefiore Medical Center
| | - Prachiben P Patel
- Department of Pathology, Albert Einstein College of Medicine/Montefiore Medical Center; Cancer Dormancy and Tumor Microenvironment Institute, Albert Einstein College of Medicine/Montefiore Medical Center
| | - Burcu Karadal-Ferrena
- Department of Pathology, Albert Einstein College of Medicine/Montefiore Medical Center; Cancer Dormancy and Tumor Microenvironment Institute, Albert Einstein College of Medicine/Montefiore Medical Center
| | - Nicole D Barth
- Department of Pathology, Albert Einstein College of Medicine/Montefiore Medical Center; Cancer Dormancy and Tumor Microenvironment Institute, Albert Einstein College of Medicine/Montefiore Medical Center
| | - Camille L Duran
- Department of Pathology, Albert Einstein College of Medicine/Montefiore Medical Center; Cancer Dormancy and Tumor Microenvironment Institute, Albert Einstein College of Medicine/Montefiore Medical Center
| | - Xianjun Ye
- Department of Pathology, Albert Einstein College of Medicine/Montefiore Medical Center; Cancer Dormancy and Tumor Microenvironment Institute, Albert Einstein College of Medicine/Montefiore Medical Center; Gruss-Lipper Biophotonics Center, Albert Einstein College of Medicine/Montefiore Medical Center
| | - Michael Papanicolaou
- Cancer Dormancy and Tumor Microenvironment Institute, Albert Einstein College of Medicine/Montefiore Medical Center; Department of Cell Biology, Albert Einstein College of Medicine/Montefiore Medical Center
| | - John S Condeelis
- Cancer Dormancy and Tumor Microenvironment Institute, Albert Einstein College of Medicine/Montefiore Medical Center; Gruss-Lipper Biophotonics Center, Albert Einstein College of Medicine/Montefiore Medical Center; Department of Cell Biology, Albert Einstein College of Medicine/Montefiore Medical Center; Montefiore Einstein Cancer Center, Albert Einstein College of Medicine/Montefiore Medical Center; Integrated Imaging Program for Cancer Research, Albert Einstein College of Medicine/Montefiore Medical Center; Department of Surgery, Albert Einstein College of Medicine/Montefiore Medical Center
| | - Maja H Oktay
- Department of Pathology, Albert Einstein College of Medicine/Montefiore Medical Center; Cancer Dormancy and Tumor Microenvironment Institute, Albert Einstein College of Medicine/Montefiore Medical Center; Gruss-Lipper Biophotonics Center, Albert Einstein College of Medicine/Montefiore Medical Center; Montefiore Einstein Cancer Center, Albert Einstein College of Medicine/Montefiore Medical Center; Integrated Imaging Program for Cancer Research, Albert Einstein College of Medicine/Montefiore Medical Center; Department of Surgery, Albert Einstein College of Medicine/Montefiore Medical Center
| | - Lucia Borriello
- Department of Pathology, Albert Einstein College of Medicine/Montefiore Medical Center; Cancer Dormancy and Tumor Microenvironment Institute, Albert Einstein College of Medicine/Montefiore Medical Center; Department of Cancer and Cellular Biology, Lewis Katz School of Medicine, Fox Chase Cancer Center;
| | - David Entenberg
- Department of Pathology, Albert Einstein College of Medicine/Montefiore Medical Center; Cancer Dormancy and Tumor Microenvironment Institute, Albert Einstein College of Medicine/Montefiore Medical Center; Gruss-Lipper Biophotonics Center, Albert Einstein College of Medicine/Montefiore Medical Center; Montefiore Einstein Cancer Center, Albert Einstein College of Medicine/Montefiore Medical Center; Integrated Imaging Program for Cancer Research, Albert Einstein College of Medicine/Montefiore Medical Center;
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14
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Howland KK, Brock A. Cellular barcoding tracks heterogeneous clones through selective pressures and phenotypic transitions. Trends Cancer 2023; 9:591-601. [PMID: 37105856 PMCID: PMC10339273 DOI: 10.1016/j.trecan.2023.03.008] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2023] [Revised: 03/27/2023] [Accepted: 03/28/2023] [Indexed: 04/29/2023]
Abstract
Genomic DNA barcoding has emerged as a sensitive and flexible tool to measure the fates of clonal subpopulations within a heterogeneous cancer cell population. Coupling cellular barcoding with single-cell transcriptomics permits the longitudinal analysis of molecular mechanisms with detailed clone-level resolution. Numerous recent studies have employed these tools to track clonal cell states in cancer progression and treatment response. With these new technologies comes the opportunity to examine longstanding questions about the origins and contributions of tumor cell heterogeneity and the roles of selection and phenotypic plasticity in disease progression and treatment.
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Affiliation(s)
- Kennedy K Howland
- Department of Biomedical Engineering, The University of Texas at Austin, Austin, TX 78734, USA
| | - Amy Brock
- Department of Biomedical Engineering, The University of Texas at Austin, Austin, TX 78734, USA.
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15
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Wang Y, Zhang X, Wang Z. Cellular barcoding: From developmental tracing to anti-tumor drug discovery. Cancer Lett 2023:216281. [PMID: 37336285 DOI: 10.1016/j.canlet.2023.216281] [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: 03/22/2023] [Revised: 05/31/2023] [Accepted: 06/10/2023] [Indexed: 06/21/2023]
Abstract
Clonal evolution has gained immense attention in explaining cancer cell status, history, and fate during cancer progression. Current single-cell or spatial transcriptome technologies have broadened our understanding of various mechanisms underlying cancer initiation, relapse, and drug resistance. However, technical challenges still hinder a better understanding of the dynamics of distinctive phenotypic states and abnormal trajectories from normal physiological transition to malignant stages. Cellular barcoding enabled lineage tracing on parallelly massive cells at single-cell resolution through different mechanisms lately, enabling new insights into exploring developmental trajectories, cancer progression, and targeted therapies. This review summarizes the latest noteworthy and robust strategies for different types of cellular barcodes. To introduce the major characteristics, advantages and limitations of these different strategies, this review will further guide in choosing or improving cellular barcoding technologies and their applications in cancer research.
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Affiliation(s)
- Yuqing Wang
- Medical Center of Hematology, The Second Affiliated Hospital, Army Medical University, Chongqing, 40037, China; State Key Laboratory of Trauma, Burn and Combined Injury, Army Medical University, Chongqing, 40037, China
| | - Xi Zhang
- Medical Center of Hematology, The Second Affiliated Hospital, Army Medical University, Chongqing, 40037, China; State Key Laboratory of Trauma, Burn and Combined Injury, Army Medical University, Chongqing, 40037, China; Jinfeng Laboratory, Chongqing, 401329, China.
| | - Zheng Wang
- Medical Center of Hematology, The Second Affiliated Hospital, Army Medical University, Chongqing, 40037, China; State Key Laboratory of Trauma, Burn and Combined Injury, Army Medical University, Chongqing, 40037, China; Bio-Med Informatics Research Center & Clinical Research Center, The Second Affiliated Hospital, Army Medical University, Chongqing, 400037, China; Jinfeng Laboratory, Chongqing, 401329, China.
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16
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Kalamakis G, Platt RJ. CRISPR for neuroscientists. Neuron 2023:S0896-6273(23)00306-9. [PMID: 37201524 DOI: 10.1016/j.neuron.2023.04.021] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2022] [Revised: 03/14/2023] [Accepted: 04/18/2023] [Indexed: 05/20/2023]
Abstract
Genome engineering technologies provide an entry point into understanding and controlling the function of genetic elements in health and disease. The discovery and development of the microbial defense system CRISPR-Cas yielded a treasure trove of genome engineering technologies and revolutionized the biomedical sciences. Comprising diverse RNA-guided enzymes and effector proteins that evolved or were engineered to manipulate nucleic acids and cellular processes, the CRISPR toolbox provides precise control over biology. Virtually all biological systems are amenable to genome engineering-from cancer cells to the brains of model organisms to human patients-galvanizing research and innovation and giving rise to fundamental insights into health and powerful strategies for detecting and correcting disease. In the field of neuroscience, these tools are being leveraged across a wide range of applications, including engineering traditional and non-traditional transgenic animal models, modeling disease, testing genomic therapies, unbiased screening, programming cell states, and recording cellular lineages and other biological processes. In this primer, we describe the development and applications of CRISPR technologies while highlighting outstanding limitations and opportunities.
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Affiliation(s)
- Georgios Kalamakis
- Department of Biosystems Science and Engineering, ETH Zurich, Mattenstrasse 26, 4058 Basel, Switzerland; Novartis Institutes for BioMedical Research, 4056 Basel, Switzerland
| | - Randall J Platt
- Department of Biosystems Science and Engineering, ETH Zurich, Mattenstrasse 26, 4058 Basel, Switzerland; Department of Chemistry, University of Basel, Petersplatz 1, 4003 Basel, Switzerland; NCCR MSE, Mattenstrasse 24a, 4058 Basel, Switzerland; Botnar Research Center for Child Health, Mattenstrasse 24a, 4058 Basel, Switzerland.
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17
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Hebert JD, Neal JW, Winslow MM. Dissecting metastasis using preclinical models and methods. Nat Rev Cancer 2023; 23:391-407. [PMID: 37138029 DOI: 10.1038/s41568-023-00568-4] [Citation(s) in RCA: 17] [Impact Index Per Article: 17.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 03/27/2023] [Indexed: 05/05/2023]
Abstract
Metastasis has long been understood to lead to the overwhelming majority of cancer-related deaths. However, our understanding of the metastatic process, and thus our ability to prevent or eliminate metastases, remains frustratingly limited. This is largely due to the complexity of metastasis, which is a multistep process that likely differs across cancer types and is greatly influenced by many aspects of the in vivo microenvironment. In this Review, we discuss the key variables to consider when designing assays to study metastasis: which source of metastatic cancer cells to use and where to introduce them into mice to address different questions of metastasis biology. We also examine methods that are being used to interrogate specific steps of the metastatic cascade in mouse models, as well as emerging techniques that may shed new light on previously inscrutable aspects of metastasis. Finally, we explore approaches for developing and using anti-metastatic therapies, and how mouse models can be used to test them.
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Affiliation(s)
- Jess D Hebert
- Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA
| | - Joel W Neal
- Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA
- Stanford Cancer Institute, Stanford University School of Medicine, Stanford, CA, USA
| | - Monte M Winslow
- Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA.
- Stanford Cancer Institute, Stanford University School of Medicine, Stanford, CA, USA.
- Department of Pathology, Stanford University School of Medicine, Stanford, CA, USA.
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18
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Huang Y, Wang H, Yue X, Li X. Bone serves as a transfer station for secondary dissemination of breast cancer. Bone Res 2023; 11:21. [PMID: 37085486 PMCID: PMC10121690 DOI: 10.1038/s41413-023-00260-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2022] [Revised: 02/28/2023] [Accepted: 03/22/2023] [Indexed: 04/23/2023] Open
Abstract
Metastasis is responsible for the majority of deaths among breast cancer patients. Although parallel polyclonal seeding has been shown to contribute to organ-specific metastasis, in the past decade, horizontal cross-metastatic seeding (metastasis-to-metastasis spreading) has also been demonstrated as a pattern of distant metastasis to multiple sites. Bone, as the most frequent first destination of breast cancer metastasis, has been demonstrated to facilitate the secondary dissemination of breast cancer cells. In this review, we summarize the clinical and experimental evidence that bone is a transfer station for the secondary dissemination of breast cancer. We also discuss the regulatory mechanisms of the bone microenvironment in secondary seeding of breast cancer, focusing on stemness regulation, quiescence-proliferation equilibrium regulation, epigenetic reprogramming and immune escape of cancer cells. Furthermore, we highlight future research perspectives and strategies for preventing secondary dissemination from bone.
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Affiliation(s)
- Yufan Huang
- Department of Biochemistry and Molecular Biology, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center of Cancer, Tianjin, 300060, China
- Tianjin's Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center of Cancer, Tianjin, 300060, China
- Key Laboratory of Breast Cancer Prevention and Treatment of the Ministry of Education, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center of Cancer, Tianjin, 300060, China
| | - Hongli Wang
- Department of Biochemistry and Molecular Biology, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center of Cancer, Tianjin, 300060, China
- Tianjin's Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center of Cancer, Tianjin, 300060, China
- Key Laboratory of Breast Cancer Prevention and Treatment of the Ministry of Education, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center of Cancer, Tianjin, 300060, China
| | - Xiaomin Yue
- Department of Biochemistry and Molecular Biology, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center of Cancer, Tianjin, 300060, China
- Tianjin's Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center of Cancer, Tianjin, 300060, China
- Key Laboratory of Breast Cancer Prevention and Treatment of the Ministry of Education, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center of Cancer, Tianjin, 300060, China
| | - Xiaoqing Li
- Department of Biochemistry and Molecular Biology, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center of Cancer, Tianjin, 300060, China.
- Tianjin's Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center of Cancer, Tianjin, 300060, China.
- Key Laboratory of Breast Cancer Prevention and Treatment of the Ministry of Education, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center of Cancer, Tianjin, 300060, China.
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19
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Meng X, Wu T, Lou Q, Niu K, Jiang L, Xiao Q, Xu T, Zhang L. Optimization of CRISPR-Cas system for clinical cancer therapy. Bioeng Transl Med 2023; 8:e10474. [PMID: 36925702 PMCID: PMC10013785 DOI: 10.1002/btm2.10474] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2022] [Revised: 11/24/2022] [Accepted: 12/07/2022] [Indexed: 12/25/2022] Open
Abstract
Cancer is a genetic disease caused by alterations in genome and epigenome and is one of the leading causes for death worldwide. The exploration of disease development and therapeutic strategies at the genetic level have become the key to the treatment of cancer and other genetic diseases. The functional analysis of genes and mutations has been slow and laborious. Therefore, there is an urgent need for alternative approaches to improve the current status of cancer research. Gene editing technologies provide technical support for efficient gene disruption and modification in vivo and in vitro, in particular the use of clustered regularly interspaced short palindromic repeats (CRISPR)-Cas systems. Currently, the applications of CRISPR-Cas systems in cancer rely on different Cas effector proteins and the design of guide RNAs. Furthermore, effective vector delivery must be met for the CRISPR-Cas systems to enter human clinical trials. In this review article, we describe the mechanism of the CRISPR-Cas systems and highlight the applications of class II Cas effector proteins. We also propose a synthetic biology approach to modify the CRISPR-Cas systems, and summarize various delivery approaches facilitating the clinical application of the CRISPR-Cas systems. By modifying the CRISPR-Cas system and optimizing its in vivo delivery, promising and effective treatments for cancers using the CRISPR-Cas system are emerging.
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Affiliation(s)
- Xiang Meng
- College & Hospital of StomatologyAnhui Medical University, Key Laboratory of Oral Diseases Research of Anhui ProvinceHefeiPeople's Republic of China
| | - Tian‐gang Wu
- College & Hospital of StomatologyAnhui Medical University, Key Laboratory of Oral Diseases Research of Anhui ProvinceHefeiPeople's Republic of China
| | - Qiu‐yue Lou
- Anhui Provincial Center for Disease Control and PreventionHefeiPeople's Republic of China
| | - Kai‐yuan Niu
- Clinical Pharmacology, William Harvey Research Institute (WHRI), Barts and The London School of Medicine and DentistryQueen Mary University of London (QMUL) Heart Centre (G23)LondonUK
- Department of OtolaryngologyThe Third Affiliated Hospital of Anhui Medical UniversityHefeiChina
| | - Lei Jiang
- College & Hospital of StomatologyAnhui Medical University, Key Laboratory of Oral Diseases Research of Anhui ProvinceHefeiPeople's Republic of China
| | - Qing‐zhong Xiao
- Clinical Pharmacology, William Harvey Research Institute (WHRI), Barts and The London School of Medicine and DentistryQueen Mary University of London (QMUL) Heart Centre (G23)LondonUK
| | - Tao Xu
- School of Pharmacy, Anhui Key Laboratory of Bioactivity of Natural ProductsAnhui Medical UniversityHefeiChina
- Inflammation and Immune Mediated Diseases Laboratory of Anhui ProvinceHefeiChina
| | - Lei Zhang
- College & Hospital of StomatologyAnhui Medical University, Key Laboratory of Oral Diseases Research of Anhui ProvinceHefeiPeople's Republic of China
- Department of PeriodontologyAnhui Stomatology Hospital Affiliated to Anhui Medical UniversityHefeiChina
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20
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Richman LP, Goyal Y, Jiang CL, Raj A. ClonoCluster: A method for using clonal origin to inform transcriptome clustering. CELL GENOMICS 2023; 3:100247. [PMID: 36819662 PMCID: PMC9932990 DOI: 10.1016/j.xgen.2022.100247] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 03/21/2022] [Revised: 09/22/2022] [Accepted: 12/16/2022] [Indexed: 01/13/2023]
Abstract
Clustering cells based on their high-dimensional profiles is an important data reduction process by which researchers infer distinct cellular states. The advent of cellular barcoding, however, provides an alternative means by which to group cells: by their clonal origin. We developed ClonoCluster, a computational method that combines both clone and transcriptome information to create hybrid clusters that weight both kinds of data with a tunable parameter. We generated hybrid clusters across six independent datasets and found that ClonoCluster generated qualitatively different clusters in all cases. The markers of these hybrid clusters were different but had equivalent fidelity to transcriptome-only clusters. The genes most strongly associated with the rearrangements in hybrid clusters were ribosomal function and extracellular matrix genes. We also developed the complementary tool Warp Factor that incorporates clone information in popular 2D visualization techniques like UMAP. Integrating ClonoCluster and Warp Factor revealed biologically relevant markers of cell identity.
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Affiliation(s)
- Lee P. Richman
- Department of Pathology, Brigham and Women’s Hospital, Boston, MA, USA
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Yogesh Goyal
- Department of Bioengineering, School of Engineering and Applied Sciences, University of Pennsylvania, Philadelphia, PA, USA
- Department of Cell and Developmental Biology, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
- Center for Synthetic Biology, Northwestern University, Chicago, IL, USA
| | - Connie L. Jiang
- Genetics and Epigenetics, Cell and Molecular Biology Graduate Group, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Arjun Raj
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Bioengineering, School of Engineering and Applied Sciences, University of Pennsylvania, Philadelphia, PA, USA
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21
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Monteiro CJ, Heery DM, Whitchurch JB. Modern Approaches to Mouse Genome Editing Using the CRISPR-Cas Toolbox and Their Applications in Functional Genomics and Translational Research. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2023; 1429:13-40. [PMID: 37486514 DOI: 10.1007/978-3-031-33325-5_2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/25/2023]
Abstract
Mice have been used in biological research for over a century, and their immense contribution to scientific breakthroughs can be seen across all research disciplines, with some of the main beneficiaries being the fields of medicine and life sciences. Genetically engineered mouse models (GEMMs), along with other model organisms, are fundamentally important research tools frequently utilised to enhance our understanding of pathophysiology and biological mechanisms behind disease. In the 1980s, it became possible to precisely edit the mouse genome to create gene knockout and knock-in mice, although with low efficacy. Recent advances utilising CRISPR-Cas technologies have considerably improved our ability to do this with ease and precision, while also allowing the generation of desired genetic variants from single nucleotide substitutions to large insertions/deletions. It is now quick and relatively easy to genetically edit somatic cells which were previously more recalcitrant to traditional approaches. Further refinements have created a 'CRISPR toolkit' that has expanded the use of CRISPR-Cas beyond gene knock-ins and knockouts. In this chapter, we review some of the latest applications of CRISPR-Cas technologies in GEMMs, including nuclease-dead Cas9 systems for activation or repression of gene expression, base editing and prime editing. We also discuss improvements in Cas9 specificity, targeting efficacy and delivery methods in mice. Throughout, we provide examples wherein CRISPR-Cas technologies have been applied to target clinically relevant genes in preclinical GEMMs, both to generate humanised models and for experimental gene therapy research.
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Affiliation(s)
- Cintia J Monteiro
- Department of Genetics, Molecular Immunogenetics Group, Ribeirão Preto Medical School, University of São Paulo, Ribeirão Preto, SP, Brazil
| | - David M Heery
- School of Pharmacy, University of Nottingham, Nottingham, UK
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22
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Fang W, Bell CM, Sapirstein A, Asami S, Leeper K, Zack DJ, Ji H, Kalhor R. Quantitative fate mapping: A general framework for analyzing progenitor state dynamics via retrospective lineage barcoding. Cell 2022; 185:4604-4620.e32. [PMID: 36423582 PMCID: PMC9708097 DOI: 10.1016/j.cell.2022.10.028] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2022] [Revised: 08/23/2022] [Accepted: 10/26/2022] [Indexed: 11/24/2022]
Abstract
Natural and induced somatic mutations that accumulate in the genome during development record the phylogenetic relationships of cells; whether these lineage barcodes capture the complex dynamics of progenitor states remains unclear. We introduce quantitative fate mapping, an approach to reconstruct the hierarchy, commitment times, population sizes, and commitment biases of intermediate progenitor states during development based on a time-scaled phylogeny of their descendants. To reconstruct time-scaled phylogenies from lineage barcodes, we introduce Phylotime, a scalable maximum likelihood clustering approach based on a general barcoding mutagenesis model. We validate these approaches using realistic in silico and in vitro barcoding experiments. We further establish criteria for the number of cells that must be analyzed for robust quantitative fate mapping and a progenitor state coverage statistic to assess the robustness. This work demonstrates how lineage barcodes, natural or synthetic, enable analyzing progenitor fate and dynamics long after embryonic development in any organism.
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Affiliation(s)
- Weixiang Fang
- Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA; Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205, USA; Center for Epigenetics, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
| | - Claire M Bell
- Department of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA; Department of Ophthalmology, Wilmer Eye Institute, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
| | - Abel Sapirstein
- Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA; Center for Epigenetics, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA; H. Milton Stewart School of Industrial and Systems Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA
| | - Soichiro Asami
- Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA; Center for Epigenetics, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
| | - Kathleen Leeper
- Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA; Center for Epigenetics, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
| | - Donald J Zack
- Department of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA; Department of Ophthalmology, Wilmer Eye Institute, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA; Department of Neuroscience, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA; Department of Molecular Biology and Genetics, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
| | - Hongkai Ji
- Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205, USA.
| | - Reza Kalhor
- Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA; Center for Epigenetics, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA; Department of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA; Department of Neuroscience, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA; Department of Molecular Biology and Genetics, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA; Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA.
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23
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Seidel S, Stadler T. TiDeTree: a Bayesian phylogenetic framework to estimate single-cell trees and population dynamic parameters from genetic lineage tracing data. Proc Biol Sci 2022; 289:20221844. [PMID: 36350216 PMCID: PMC9653226 DOI: 10.1098/rspb.2022.1844] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022] Open
Abstract
The development of organisms and tissues is dictated by an elaborate balance between cell division, apoptosis and differentiation: the cell population dynamics. To quantify these dynamics, we propose a phylodynamic inference approach based on single-cell lineage recorder data. We developed a Bayesian phylogenetic framework-time-scaled developmental trees (TiDeTree)-that uses lineage recorder data to estimate time-scaled single-cell trees. By implementing TiDeTree within BEAST 2, we enable joint inference of the time-scaled trees and the cell population dynamics. We validated TiDeTree using simulations and showed that performance further improves when including multiple independent sources of information into the inference, such as frequencies of editing outcomes or experimental replicates. We benchmarked TiDeTree against state-of-the-art methods and show comparable performance in terms of tree topology, plus direct assessment of uncertainty and co-estimation of additional parameters. To demonstrate TiDeTree's use in practice, we analysed a public dataset containing lineage data from approximately 100 stem cell colonies. We estimated a time-scaled phylogeny for each colony; as well as the cell division and apoptosis rates underlying the growth dynamics of all colonies. We envision that TiDeTree will find broad application in the analysis of single-cell lineage tracing data, which will improve our understanding of cellular processes during development.
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Affiliation(s)
- Sophie Seidel
- Department of Biosystems Science and Engineering, ETH Zürich, Basel, Switzerland,Swiss Institute of Bioinformatics (SIB), Lausanne, Switzerland
| | - Tanja Stadler
- Department of Biosystems Science and Engineering, ETH Zürich, Basel, Switzerland,Swiss Institute of Bioinformatics (SIB), Lausanne, Switzerland
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24
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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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25
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Pelea O, Fulga TA, Sauka-Spengler T. RNA-Responsive gRNAs for Controlling CRISPR Activity: Current Advances, Future Directions, and Potential Applications. CRISPR J 2022; 5:642-659. [PMID: 36206027 PMCID: PMC9618385 DOI: 10.1089/crispr.2022.0052] [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: 05/14/2022] [Accepted: 08/17/2022] [Indexed: 01/31/2023] Open
Abstract
CRISPR-Cas9 has emerged as a major genome manipulation tool. As Cas9 can cause off-target effects, several methods for controlling the expression of CRISPR systems were developed. Recent studies have shown that CRISPR activity could be controlled by sensing expression levels of endogenous transcripts. This is particularly interesting, as endogenous RNAs could harbor important information about the cell type, disease state, and environmental challenges cells are facing. Single-guide RNA (sgRNA) engineering played a major role in the development of RNA-responsive CRISPR systems. Following further optimizations, RNA-responsive sgRNAs could enable the development of novel therapeutic and research applications. This review introduces engineering strategies that could be employed to modify Streptococcus pyogenes sgRNAs with a focus on recent advances made toward the development of RNA-responsive sgRNAs. Future directions and potential applications of these technologies are also discussed.
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Affiliation(s)
- Oana Pelea
- Radcliffe Department of Medicine, MRC Weatherall Institute of Molecular Medicine, University of Oxford, Oxford, United Kingdom; and Kansas City, Missouri, USA
| | - Tudor A. Fulga
- Radcliffe Department of Medicine, MRC Weatherall Institute of Molecular Medicine, University of Oxford, Oxford, United Kingdom; and Kansas City, Missouri, USA
| | - Tatjana Sauka-Spengler
- Radcliffe Department of Medicine, MRC Weatherall Institute of Molecular Medicine, University of Oxford, Oxford, United Kingdom; and Kansas City, Missouri, USA
- Stowers Institute for Medical Research, Kansas City, Missouri, USA
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26
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Zou RS, Marin-Gonzalez A, Liu Y, Liu HB, Shen L, Dveirin RK, Luo JXJ, Kalhor R, Ha T. Massively parallel genomic perturbations with multi-target CRISPR interrogates Cas9 activity and DNA repair at endogenous sites. Nat Cell Biol 2022; 24:1433-1444. [PMID: 36064968 PMCID: PMC9481459 DOI: 10.1038/s41556-022-00975-z] [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] [Subscribe] [Scholar Register] [Received: 01/21/2022] [Accepted: 07/06/2022] [Indexed: 11/09/2022]
Abstract
Here we present an approach that combines a clustered regularly interspaced short palindromic repeats (CRISPR) system that simultaneously targets hundreds of epigenetically diverse endogenous genomic sites with high-throughput sequencing to measure Cas9 dynamics and cellular responses at scale. This massive multiplexing of CRISPR is enabled by means of multi-target guide RNAs (mgRNAs), degenerate guide RNAs that direct Cas9 to a pre-determined number of well-mapped sites. mgRNAs uncovered generalizable insights into Cas9 binding and cleavage, revealing rapid post-cleavage Cas9 departure and repair factor loading at protospacer adjacent motif-proximal genomic DNA. Moreover, by bypassing confounding effects from guide RNA sequence, mgRNAs unveiled that Cas9 binding is enhanced at chromatin-accessible regions, and cleavage by bound Cas9 is more efficient near transcribed regions. Combined with light-mediated activation and deactivation of Cas9 activity, mgRNAs further enabled high-throughput study of the cellular response to double-strand breaks with high temporal resolution, revealing the presence, extent (under 2 kb) and kinetics (~1 h) of reversible DNA damage-induced chromatin decompaction. Altogether, this work establishes mgRNAs as a generalizable platform for multiplexing CRISPR and advances our understanding of intracellular Cas9 activity and the DNA damage response at endogenous loci.
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Affiliation(s)
- Roger S Zou
- Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Department of Biophysics and Biophysical Chemistry, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Alberto Marin-Gonzalez
- Department of Biophysics and Biophysical Chemistry, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Yang Liu
- Department of Biophysics and Biophysical Chemistry, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Hans B Liu
- Department of Biophysics and Biophysical Chemistry, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Leo Shen
- Department of Biophysics and Biophysical Chemistry, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Rachel K Dveirin
- Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Jay X J Luo
- Department of Biophysics and Biophysical Chemistry, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Reza Kalhor
- Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Taekjip Ha
- Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
- Department of Biophysics and Biophysical Chemistry, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
- Department of Biophysics, Johns Hopkins University, Baltimore, MD, USA.
- Howard Hughes Medical Institute, Baltimore, MD, USA.
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27
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Kim W, Park E, Yoo HS, Park J, Jung YM, Park JH. Recent Advances in Monitoring Stem Cell Status and Differentiation Using Nano-Biosensing Technologies. NANOMATERIALS (BASEL, SWITZERLAND) 2022; 12:2934. [PMID: 36079970 PMCID: PMC9457759 DOI: 10.3390/nano12172934] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/29/2022] [Revised: 08/22/2022] [Accepted: 08/23/2022] [Indexed: 05/14/2023]
Abstract
In regenerative medicine, cell therapies using various stem cells have received attention as an alternative to overcome the limitations of existing therapeutic methods. Clinical applications of stem cells require the identification of characteristics at the single-cell level and continuous monitoring during expansion and differentiation. In this review, we recapitulate the application of various stem cells used in regenerative medicine and the latest technological advances in monitoring the differentiation process of stem cells. Single-cell RNA sequencing capable of profiling the expression of many genes at the single-cell level provides a new opportunity to analyze stem cell heterogeneity and to specify molecular markers related to the branching of differentiation lineages. However, this method is destructive and distorted. In addition, the differentiation process of a particular cell cannot be continuously tracked. Therefore, several spectroscopic methods have been developed to overcome these limitations. In particular, the application of Raman spectroscopy to measure the intrinsic vibration spectrum of molecules has been proposed as a powerful method that enables continuous monitoring of biochemical changes in the process of the differentiation of stem cells. This review provides a comprehensive overview of current analytical methods employed for stem cell engineering and future perspectives of nano-biosensing technologies as a platform for the in situ monitoring of stem cell status and differentiation.
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Affiliation(s)
- Wijin Kim
- Department of Biomedical Science, Kangwon National University, Chuncheon 24341, Gangwon-do, Korea
| | - Eungyeong Park
- Department of Chemistry, Kangwon National University, Chuncheon 24341, Gangwon-do, Korea
| | - Hyuk Sang Yoo
- Department of Biomedical Science, Kangwon National University, Chuncheon 24341, Gangwon-do, Korea
- Kangwon Radiation Convergence Research Support Center, Kangwon National University, Chuncheon 24341, Gangwon-do, Korea
| | - Jongmin Park
- Department of Chemistry, Kangwon National University, Chuncheon 24341, Gangwon-do, Korea
| | - Young Mee Jung
- Department of Chemistry, Kangwon National University, Chuncheon 24341, Gangwon-do, Korea
- Kangwon Radiation Convergence Research Support Center, Kangwon National University, Chuncheon 24341, Gangwon-do, Korea
| | - Ju Hyun Park
- Department of Biomedical Science, Kangwon National University, Chuncheon 24341, Gangwon-do, Korea
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28
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Hughes NW, Qu Y, Zhang J, Tang W, Pierce J, Wang C, Agrawal A, Morri M, Neff N, Winslow MM, Wang M, Cong L. Machine-learning-optimized Cas12a barcoding enables the recovery of single-cell lineages and transcriptional profiles. Mol Cell 2022; 82:3103-3118.e8. [PMID: 35752172 PMCID: PMC10599400 DOI: 10.1016/j.molcel.2022.06.001] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2021] [Revised: 04/27/2022] [Accepted: 05/29/2022] [Indexed: 12/12/2022]
Abstract
The development of CRISPR-based barcoding methods creates an exciting opportunity to understand cellular phylogenies. We present a compact, tunable, high-capacity Cas12a barcoding system called dual acting inverted site array (DAISY). We combined high-throughput screening and machine learning to predict and optimize the 60-bp DAISY barcode sequences. After optimization, top-performing barcodes had ∼10-fold increased capacity relative to the best random-screened designs and performed reliably across diverse cell types. DAISY barcode arrays generated ∼12 bits of entropy and ∼66,000 unique barcodes. Thus, DAISY barcodes-at a fraction of the size of Cas9 barcodes-achieved high-capacity barcoding. We coupled DAISY barcoding with single-cell RNA-seq to recover lineages and gene expression profiles from ∼47,000 human melanoma cells. A single DAISY barcode recovered up to ∼700 lineages from one parental cell. This analysis revealed heritable single-cell gene expression and potential epigenetic modulation of memory gene transcription. Overall, Cas12a DAISY barcoding is an efficient tool for investigating cell-state dynamics.
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Affiliation(s)
- Nicholas W Hughes
- Department of Pathology, Stanford University School of Medicine, Stanford, CA 94305, USA; Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA; Wu Tsai Neuroscience Institute, Stanford Cancer Institute, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Yuanhao Qu
- Department of Pathology, Stanford University School of Medicine, Stanford, CA 94305, USA; Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Jiaqi Zhang
- Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; Laboratory of Information and Decision Systems, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Weijing Tang
- Department of Pathology, Stanford University School of Medicine, Stanford, CA 94305, USA; Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Justin Pierce
- Department of Pathology, Stanford University School of Medicine, Stanford, CA 94305, USA; Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Chengkun Wang
- Department of Pathology, Stanford University School of Medicine, Stanford, CA 94305, USA; Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA
| | | | | | - Norma Neff
- Chan Zuckerberg Biohub, Stanford, CA 94305, USA
| | - Monte M Winslow
- Department of Pathology, Stanford University School of Medicine, Stanford, CA 94305, USA; Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Mengdi Wang
- Department of Electrical and Computer Engineering, Princeton University, Princeton, NJ 08544, USA; Center for Statistics and Machine Learning, Princeton University, Princeton, NJ 08544, USA.
| | - Le Cong
- Department of Pathology, Stanford University School of Medicine, Stanford, CA 94305, USA; Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA; Wu Tsai Neuroscience Institute, Stanford Cancer Institute, Stanford University School of Medicine, Stanford, CA 94305, USA.
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29
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Choi J, Chen W, Minkina A, Chardon FM, Suiter CC, Regalado SG, Domcke S, Hamazaki N, Lee C, Martin B, Daza RM, Shendure J. A time-resolved, multi-symbol molecular recorder via sequential genome editing. Nature 2022; 608:98-107. [PMID: 35794474 PMCID: PMC9352581 DOI: 10.1038/s41586-022-04922-8] [Citation(s) in RCA: 52] [Impact Index Per Article: 26.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2021] [Accepted: 05/31/2022] [Indexed: 01/07/2023]
Abstract
DNA is naturally well suited to serve as a digital medium for in vivo molecular recording. However, contemporary DNA-based memory devices are constrained in terms of the number of distinct 'symbols' that can be concurrently recorded and/or by a failure to capture the order in which events occur1. Here we describe DNA Typewriter, a general system for in vivo molecular recording that overcomes these and other limitations. For DNA Typewriter, the blank recording medium ('DNA Tape') consists of a tandem array of partial CRISPR-Cas9 target sites, with all but the first site truncated at their 5' ends and therefore inactive. Short insertional edits serve as symbols that record the identity of the prime editing guide RNA2 mediating the edit while also shifting the position of the 'type guide' by one unit along the DNA Tape, that is, sequential genome editing. In this proof of concept of DNA Typewriter, we demonstrate recording and decoding of thousands of symbols, complex event histories and short text messages; evaluate the performance of dozens of orthogonal tapes; and construct 'long tape' potentially capable of recording as many as 20 serial events. Finally, we leverage DNA Typewriter in conjunction with single-cell RNA-seq to reconstruct a monophyletic lineage of 3,257 cells and find that the Poisson-like accumulation of sequential edits to multicopy DNA tape can be maintained across at least 20 generations and 25 days of in vitro clonal expansion.
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Affiliation(s)
- Junhong Choi
- Department of Genome Sciences, University of Washington, Seattle, WA, USA.
- Howard Hughes Medical Institute, Seattle, WA, USA.
| | - Wei Chen
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
- Molecular Engineering and Sciences Institute, University of Washington, Seattle, WA, USA
| | - Anna Minkina
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
| | - Florence M Chardon
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
| | - Chase C Suiter
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
- Molecular and Cellular Biology Program, University of Washington, Seattle, WA, USA
| | - Samuel G Regalado
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
| | - Silvia Domcke
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
| | - Nobuhiko Hamazaki
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
- Howard Hughes Medical Institute, Seattle, WA, USA
| | - Choli Lee
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
| | - Beth Martin
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
| | - Riza M Daza
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
| | - Jay Shendure
- Department of Genome Sciences, University of Washington, Seattle, WA, USA.
- Howard Hughes Medical Institute, Seattle, WA, USA.
- Brotman Baty Institute for Precision Medicine, Seattle, WA, USA.
- Allen Discovery Center for Cell Lineage Tracing, Seattle, WA, USA.
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30
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Grillo G, Lupien M. Cancer-associated chromatin variants uncover the oncogenic role of transposable elements. Curr Opin Genet Dev 2022; 74:101911. [PMID: 35487182 DOI: 10.1016/j.gde.2022.101911] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2021] [Revised: 03/08/2022] [Accepted: 03/24/2022] [Indexed: 11/26/2022]
Abstract
The vast array of cell states found across human tissue arises from chromatin variants, which correspond to segments of the genome, known as DNA elements, adopting a different chromatin state over cell state transitions. Oncogenesis stems from alterations to the chromatin states over DNA elements that result in cancer-associated chromatin variants. Here, we review how cancer-associated chromatin variants call attention to repetitive DNA elements, and guide the functional characterization of transposable elements to decode their role in oncogenesis. We further discuss prevailing opportunities in the study of repetitive DNA elements to move towards the 'complete cancer genome' goal for precision medicine in oncology.
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Affiliation(s)
- Giacomo Grillo
- Princess Margaret Cancer Centre, University Health Network, Toronto, Ontario, Canada.
| | - Mathieu Lupien
- Princess Margaret Cancer Centre, University Health Network, Toronto, Ontario, Canada; Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada; Ontario Institute for Cancer Research, Toronto, Ontario, Canada.
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31
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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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32
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Yao M, Ren T, Pan Y, Xue X, Li R, Zhang L, Li Y, Huang K. A New Generation of Lineage Tracing Dynamically Records Cell Fate Choices. Int J Mol Sci 2022; 23:ijms23095021. [PMID: 35563412 PMCID: PMC9105840 DOI: 10.3390/ijms23095021] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2022] [Revised: 04/26/2022] [Accepted: 04/28/2022] [Indexed: 11/16/2022] Open
Abstract
Reconstructing the development of lineage relationships and cell fate mapping has been a fundamental problem in biology. Using advanced molecular biology and single-cell RNA sequencing, we have profiled transcriptomes at the single-cell level and mapped cell fates during development. Recently, CRISPR/Cas9 barcode editing for large-scale lineage tracing has been used to reconstruct the pseudotime trajectory of cells and improve lineage tracing accuracy. This review presents the progress of the latest CbLT (CRISPR-based Lineage Tracing) and discusses the current limitations and potential technical pitfalls in their application and other emerging concepts.
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33
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Jones MG, Rosen Y, Yosef N. Interactive, integrated analysis of single-cell transcriptomic and phylogenetic data with PhyloVision. CELL REPORTS METHODS 2022; 2:100200. [PMID: 35497495 PMCID: PMC9046453 DOI: 10.1016/j.crmeth.2022.100200] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/20/2021] [Revised: 02/19/2022] [Accepted: 03/28/2022] [Indexed: 02/07/2023]
Abstract
Recent advances in CRISPR-Cas9 engineering and single-cell assays have enabled the simultaneous measurement of single-cell transcriptomic and phylogenetic profiles. However, there are few computational tools enabling users to integrate and derive insight from a joint analysis of these two modalities. Here, we describe "PhyloVision": an open-source software for interactively exploring data from both modalities and for identifying and interpreting heritable gene modules whose concerted expression are associated with phylogenetic relationships. PhyloVision provides a feature-rich, interactive, and shareable web-based report for investigating these modules while also supporting several other data and meta-data exploration capabilities. We demonstrate the utility of PhyloVision using a published dataset of metastatic lung adenocarcinoma cells, whose phylogeny was resolved using a CRISPR-Cas9-based lineage-tracing system. Together, we anticipate that PhyloVision and the methods it implements will be a useful resource for scalable and intuitive data exploration for any assay that simultaneously measures cell state and lineage.
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Affiliation(s)
- Matthew G. Jones
- Department of Electrical Engineering and Computer Science, University of California, Berkeley, Berkeley, CA 94720 USA
- Center for Computational Biology, University of California, Berkeley, Berkeley, CA 94720 USA
- Integrative Program in Quantitative Biology, University of California, San Francisco, San Francisco, CA 94143, USA
- Whitehead Institute, Cambridge, MA 02142 USA
| | - Yanay Rosen
- Department of Electrical Engineering and Computer Science, University of California, Berkeley, Berkeley, CA 94720 USA
| | - Nir Yosef
- Department of Electrical Engineering and Computer Science, University of California, Berkeley, Berkeley, CA 94720 USA
- Center for Computational Biology, University of California, Berkeley, Berkeley, CA 94720 USA
- Chan Zuckerberg Biohub Investigator, San Francisco, CA 94158 USA
- Ragon Institute of Massachusetts General Hospital, MIT and Harvard University, Cambridge, MA 02114 USA
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34
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Complex biological questions being addressed using single cell sequencing technologies. SLAS Technol 2022; 27:143-149. [DOI: 10.1016/j.slast.2021.10.013] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
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35
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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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36
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Roy RK, Debashree I, Srivastava S, Rishi N, Srivastava A. CRISPR/ Cas9 Off-targets: Computational Analysis of Causes, Prediction,
Detection, and Overcoming Strategies. Curr Bioinform 2022. [DOI: 10.2174/1574893616666210708150439] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022]
Abstract
:
CRISPR/Cas9 technology is a highly flexible RNA-guided endonuclease (RGEN)
based gene-editing tool that has transformed the field of genomics, gene therapy, and genome/
epigenome imaging. Its wide range of applications provides immense scope for understanding
as well as manipulating genetic/epigenetic elements. However, the RGEN is prone to
off-target mutagenesis that leads to deleterious effects. This review details the molecular and cellular
mechanisms underlying the off-target activity, various available detection tools and prediction
methodology ranging from sequencing to machine learning approaches, and the strategies to
overcome/minimise off-targets. A coherent and concise method increasing target precision would
prove indispensable to concrete manipulation and interpretation of genome editing results that
can revolutionise therapeutics, including clarity in genome regulatory mechanisms during development.
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Affiliation(s)
- Roshan Kumar Roy
- Amity Institute of Virology and Immunology, Amity University Uttar Pradesh, Noida 201313, India
| | - Ipsita Debashree
- Amity Institute of Virology and Immunology, Amity University Uttar Pradesh, Noida 201313, India
| | - Sonal Srivastava
- Amity Institute of Virology and Immunology, Amity University Uttar Pradesh, Noida 201313,India
| | - Narayan Rishi
- Amity Institute of Virology and Immunology, Amity University Uttar Pradesh, Noida 201313,India
| | - Ashish Srivastava
- Amity Institute of Virology and Immunology, Amity University Uttar Pradesh, Noida 201313,India
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37
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Satcher RL, Zhang XHF. Evolving cancer-niche interactions and therapeutic targets during bone metastasis. Nat Rev Cancer 2022; 22:85-101. [PMID: 34611349 DOI: 10.1038/s41568-021-00406-5] [Citation(s) in RCA: 38] [Impact Index Per Article: 19.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 09/02/2021] [Indexed: 12/14/2022]
Abstract
Many cancer types metastasize to bone. This propensity may be a product of genetic traits of the primary tumour in some cancers. Upon arrival, cancer cells establish interactions with various bone-resident cells during the process of colonization. These interactions, to a large degree, dictate cancer cell fates at multiple steps of the metastatic cascade, from single cells to overt metastases. The bone microenvironment may even influence cancer cells to subsequently spread to multiple other organs. Therefore, it is imperative to spatiotemporally delineate the evolving cancer-bone crosstalk during bone colonization. In this Review, we provide a summary of the bone microenvironment and its impact on bone metastasis. On the basis of the microscopic anatomy, we tentatively define a roadmap of the journey of cancer cells through bone relative to various microenvironment components, including the potential of bone to function as a launch pad for secondary metastasis. Finally, we examine common and distinct features of bone metastasis from various cancer types. Our goal is to stimulate future studies leading to the development of a broader scope of potent therapies.
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Affiliation(s)
- Robert L Satcher
- Department of Orthopedic Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Xiang H-F Zhang
- Lester and Sue Smith Breast Center, Baylor College of Medicine, Houston, TX, USA.
- Dan L. Duncan Cancer Center, Baylor College of Medicine, Houston, TX, USA.
- Department of Molecular and Cellular Biology, Baylor College of Medicine, Houston, TX, USA.
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Emerging strategies for the genetic dissection of gene functions, cell types, and neural circuits in the mammalian brain. Mol Psychiatry 2022; 27:422-435. [PMID: 34561609 DOI: 10.1038/s41380-021-01292-x] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/12/2020] [Revised: 08/17/2021] [Accepted: 09/08/2021] [Indexed: 02/08/2023]
Abstract
The mammalian brain is composed of a large number of highly diverse cell types with different molecular, anatomical, and functional features. Distinct cellular identities are generated during development under the regulation of intricate genetic programs and manifested through unique combinations of gene expression. Recent advancements in our understanding of the molecular and cellular mechanisms underlying the assembly, function, and pathology of the brain circuitry depend on the invention and application of genetic strategies that engage intrinsic gene regulatory mechanisms. Here we review the strategies for gene regulation on DNA, RNA, and protein levels and their applications in cell type targeting and neural circuit dissection. We highlight newly emerged strategies and emphasize the importance of combinatorial approaches. We also discuss the potential caveats and pitfalls in current methods and suggest future prospects to improve their comprehensiveness and versatility.
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Gui P, Bivona TG. Evolution of metastasis: new tools and insights. Trends Cancer 2021; 8:98-109. [PMID: 34872888 DOI: 10.1016/j.trecan.2021.11.002] [Citation(s) in RCA: 27] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/10/2021] [Revised: 11/01/2021] [Accepted: 11/05/2021] [Indexed: 02/07/2023]
Abstract
Metastasis is an evolutionary process occurring across multiple organs and timescales. Due to its continuous and dynamic nature, this multifaceted process has been challenging to investigate and remains incompletely understood, in part due to the lack of tools capable of probing genomic evolution at high enough resolution. However, technological advances in genetic sequencing and editing have provided new and powerful methods to refine our understanding of the complex series of events that lead to metastatic dissemination. In this review, we summarize the latest genetic and lineage-tracing approaches developed to unravel the genetic evolution of metastasis. The findings that have emerged have enhanced our comprehension of the mechanistic trajectories and timescales of metastasis and could provide new strategies for therapy.
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Affiliation(s)
- Philippe Gui
- Department of Medicine, University of California, San Francisco, San Francisco, CA, USA; Department of Cellular and Molecular Pharmacology, University of California, San Francisco, San Francisco, CA, USA; Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, San Francisco, CA, USA.
| | - Trever G Bivona
- Department of Medicine, University of California, San Francisco, San Francisco, CA, USA; Department of Cellular and Molecular Pharmacology, University of California, San Francisco, San Francisco, CA, USA; Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, San Francisco, CA, USA.
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40
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Mapping single-cell-resolution cell phylogeny reveals cell population dynamics during organ development. Nat Methods 2021; 18:1506-1514. [PMID: 34857936 DOI: 10.1038/s41592-021-01325-x] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2021] [Accepted: 10/18/2021] [Indexed: 12/20/2022]
Abstract
Mapping the cell phylogeny of a complex multicellular organism relies on somatic mutations accumulated from zygote to adult. Available cell barcoding methods can record about three mutations per barcode, enabling only low-resolution mapping of the cell phylogeny of complex organisms. Here we developed SMALT, a substitution mutation-aided lineage-tracing system that outperforms the available cell barcoding methods in mapping cell phylogeny. We applied SMALT to Drosophila melanogaster and obtained on average more than 20 mutations on a three-kilobase-pair barcoding sequence in early-adult cells. Using the barcoding mutations, we obtained high-quality cell phylogenetic trees, each comprising several thousand internal nodes with 84-93% median bootstrap support. The obtained cell phylogenies enabled a population genetic analysis that estimates the longitudinal dynamics of the number of actively dividing parental cells (Np) in each organ through development. The Np dynamics revealed the trajectory of cell births and provided insight into the balance of symmetric and asymmetric cell division.
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41
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Endo M, Maruoka H, Okabe S. Advanced Technologies for Local Neural Circuits in the Cerebral Cortex. Front Neuroanat 2021; 15:757499. [PMID: 34803616 PMCID: PMC8595196 DOI: 10.3389/fnana.2021.757499] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2021] [Accepted: 10/13/2021] [Indexed: 11/13/2022] Open
Abstract
The neural network in the brain can be viewed as an integrated system assembled from a large number of local neural circuits specialized for particular brain functions. Activities of neurons in local neural circuits are thought to be organized both spatially and temporally under the rules optimized for their roles in information processing. It is well perceived that different areas of the mammalian neocortex have specific cognitive functions and distinct computational properties. However, the organizational principles of the local neural circuits in different cortical regions have not yet been clarified. Therefore, new research principles and related neuro-technologies that enable efficient and precise recording of large-scale neuronal activities and synaptic connections are necessary. Innovative technologies for structural analysis, including tissue clearing and expansion microscopy, have enabled super resolution imaging of the neural circuits containing thousands of neurons at a single synapse resolution. The imaging resolution and volume achieved by new technologies are beyond the limits of conventional light or electron microscopic methods. Progress in genome editing and related technologies has made it possible to label and manipulate specific cell types and discriminate activities of multiple cell types. These technologies will provide a breakthrough for multiscale analysis of the structure and function of local neural circuits. This review summarizes the basic concepts and practical applications of the emerging technologies and new insight into local neural circuits obtained by these technologies.
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Affiliation(s)
| | | | - Shigeo Okabe
- Department of Cellular Neurobiology, Graduate School of Medicine and Faculty of Medicine, The University of Tokyo, Tokyo, Japan
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42
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Lyne AM, Perie L. Comparing Phylogenetic Approaches to Reconstructing Cell Lineage From Microsatellites With Missing Data. IEEE/ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS 2021; 18:2291-2301. [PMID: 32386163 DOI: 10.1109/tcbb.2020.2992813] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/11/2023]
Abstract
Due to the imperfect fidelity of DNA replication, somatic cells acquire DNA mutations at each division which record their lineage history. Microsatellites, tandem repeats of DNA nucleotide motifs, mutate more frequently than other genomic regions and by observing microsatellite lengths in single cells and implementing suitable inference procedures, the cell lineage tree of an organism can be reconstructed. Due to recent advances in single cell Next Generation Sequencing (NGS) and the phylogenetic methods used to infer lineage trees, this work investigates which computational approaches best exploit the lineage information found in single cell NGS data. We simulated trees representing cell division with mutating microsatellites, and tested a range of available phylogenetic algorithms to reconstruct cell lineage. We found that distance-based approaches are fast and accurate with fully observed data. However, Maximum Parsimony and the computationally intensive probabilistic methods are more robust to missing data and therefore better suited to reconstructing cell lineage from NGS datasets. We also investigated how robust reconstruction algorithms are to different tree topologies and mutation generation models. Our results show that the flexibility of Maximum Parsimony and the probabilistic approaches mean they can be adapted to allow good reconstruction across a range of biologically relevant scenarios.
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43
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Wang MY, Zhou Y, Lai GS, Huang Q, Cai WQ, Han ZW, Wang Y, Ma Z, Wang XW, Xiang Y, Fang SX, Peng XC, Xin HW. DNA barcode to trace the development and differentiation of cord blood stem cells (Review). Mol Med Rep 2021; 24:849. [PMID: 34643250 PMCID: PMC8524429 DOI: 10.3892/mmr.2021.12489] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2021] [Accepted: 09/15/2021] [Indexed: 12/05/2022] Open
Abstract
Umbilical cord blood transplantation was first reported in 1980. Since then, additional research has indicated that umbilical cord blood stem cells (UCBSCs) have various advantages, such as multi-lineage differentiation potential and potent renewal activity, which may be induced to promote their differentiation into a variety of seed cells for tissue engineering and the treatment of clinical and metabolic diseases. Recent studies suggested that UCBSCs are able to differentiate into nerve cells, chondrocytes, hepatocyte-like cells, fat cells and osteoblasts. The culture of UCBSCs has developed from feeder-layer to feeder-free culture systems. The classical techniques of cell labeling and tracing by gene transfection and fluorescent dye and nucleic acid analogs have evolved to DNA barcode technology mediated by transposon/retrovirus, cyclization recombination-recombinase and clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated protein 9 strategies. DNA barcoding for cell development tracing has advanced to include single cells and single nucleic acid mutations. In the present study, the latest research findings on the development and differentiation, culture techniques and labeling and tracing of UCBSCs are reviewed. The present study may increase the current understanding of UCBSC biology and its clinical applications.
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Affiliation(s)
- Mo-Yu Wang
- Laboratory of Oncology, Center for Molecular Medicine, School of Basic Medicine, Health Science Center, Yangtze University, Jingzhou, Hubei 434023, P.R. China
| | - Yang Zhou
- Laboratory of Oncology, Center for Molecular Medicine, School of Basic Medicine, Health Science Center, Yangtze University, Jingzhou, Hubei 434023, P.R. China
| | - Guang-Shun Lai
- Department of Digestive Medicine, People's Hospital of Lianjiang, Lianjiang, Guangdong 524400, P.R. China
| | - Qi Huang
- Laboratory of Oncology, Center for Molecular Medicine, School of Basic Medicine, Health Science Center, Yangtze University, Jingzhou, Hubei 434023, P.R. China
| | - Wen-Qi Cai
- Laboratory of Oncology, Center for Molecular Medicine, School of Basic Medicine, Health Science Center, Yangtze University, Jingzhou, Hubei 434023, P.R. China
| | - Zi-Wen Han
- Laboratory of Oncology, Center for Molecular Medicine, School of Basic Medicine, Health Science Center, Yangtze University, Jingzhou, Hubei 434023, P.R. China
| | - Yingying Wang
- Laboratory of Oncology, Center for Molecular Medicine, School of Basic Medicine, Health Science Center, Yangtze University, Jingzhou, Hubei 434023, P.R. China
| | - Zhaowu Ma
- Laboratory of Oncology, Center for Molecular Medicine, School of Basic Medicine, Health Science Center, Yangtze University, Jingzhou, Hubei 434023, P.R. China
| | - Xian-Wang Wang
- Laboratory of Oncology, Center for Molecular Medicine, School of Basic Medicine, Health Science Center, Yangtze University, Jingzhou, Hubei 434023, P.R. China
| | - Ying Xiang
- Laboratory of Oncology, Center for Molecular Medicine, School of Basic Medicine, Health Science Center, Yangtze University, Jingzhou, Hubei 434023, P.R. China
| | - Shu-Xian Fang
- State Key Laboratory of Respiratory Disease, Affiliated Cancer Hospital & Institute of Guangzhou Medical University, Guangzhou, Guangdong 510095, P.R. China
| | - Xiao-Chun Peng
- Laboratory of Oncology, Center for Molecular Medicine, School of Basic Medicine, Health Science Center, Yangtze University, Jingzhou, Hubei 434023, P.R. China
| | - Hong-Wu Xin
- Laboratory of Oncology, Center for Molecular Medicine, School of Basic Medicine, Health Science Center, Yangtze University, Jingzhou, Hubei 434023, P.R. China
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Menche C, Farin HF. Strategies for genetic manipulation of adult stem cell-derived organoids. Exp Mol Med 2021; 53:1483-1494. [PMID: 34663937 PMCID: PMC8569115 DOI: 10.1038/s12276-021-00609-8] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2020] [Revised: 02/21/2021] [Accepted: 03/05/2021] [Indexed: 01/08/2023] Open
Abstract
Organoid technology allows the expansion of primary epithelial cells from normal and diseased tissues, providing a unique model for human (patho)biology. In a three-dimensional environment, adult stem cells self-organize and differentiate to gain tissue-specific features. Accessibility to genetic manipulation enables the investigation of the molecular mechanisms underlying cell fate regulation, cell differentiation and cell interactions. In recent years, powerful methodologies using lentiviral transgenesis, CRISPR/Cas9 gene editing, and single-cell readouts have been developed to study gene function and carry out genetic screens in organoids. However, the multicellularity and dynamic nature of stem cell-derived organoids also present challenges for genetic experimentation. In this review, we focus on adult gastrointestinal organoids and summarize the state-of-the-art protocols for successful transgenesis. We provide an outlook on emerging genetic techniques that could further increase the applicability of organoids and enhance the potential of organoid-based techniques to deepen our understanding of gene function in tissue biology.
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Affiliation(s)
- Constantin Menche
- Georg-Speyer-Haus, Institute for Tumor Biology and Experimental Therapy, Frankfurt am Main, Germany
- Frankfurt Cancer Institute, Goethe University, Frankfurt am Main, Germany
| | - Henner F Farin
- Georg-Speyer-Haus, Institute for Tumor Biology and Experimental Therapy, Frankfurt am Main, Germany.
- Frankfurt Cancer Institute, Goethe University, Frankfurt am Main, Germany.
- German Cancer Consortium (DKTK), Heidelberg, Germany.
- German Cancer Research Center (DKFZ), Heidelberg, Germany.
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45
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Morgan D, Jost TA, De Santiago C, Brock A. Applications of high-resolution clone tracking technologies in cancer. CURRENT OPINION IN BIOMEDICAL ENGINEERING 2021; 19:100317. [PMID: 34901584 PMCID: PMC8658740 DOI: 10.1016/j.cobme.2021.100317] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
Tumors are comprised of dynamic, heterogenous cell populations characterized by numerous genetic and non-genetic alterations that accumulate and change with disease progression and treatment. Retrospective analyses of tumor evolution have relied on the measurement of genetic markers (such as copy number variants) to infer clonal dynamics. However, these approaches neglect the critical contributions of non-genetic drivers of disease. Techniques that harness the power of prospective clone tracking via heritable barcode tags provide an alternative strategy. In this review, we discuss methods for high-resolution, quantitative clone tracking, including recent advancements to pair barcode-specific functionality with scRNA-seq, clonal cell isolation, and in situ hybridization and imaging. We discuss these approaches in the context of cancer cell heterogeneity and treatment resistance.
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Affiliation(s)
- Daylin Morgan
- Department of Biomedical Engineering, The University of Texas at Austin, Austin, Texas, 78712, United States
| | - Tyler A. Jost
- Department of Biomedical Engineering, The University of Texas at Austin, Austin, Texas, 78712, United States
| | - Carolina De Santiago
- Department of Biomedical Engineering, The University of Texas at Austin, Austin, Texas, 78712, United States
| | - Amy Brock
- Department of Biomedical Engineering, The University of Texas at Austin, Austin, Texas, 78712, United States
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46
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Wangsanuwat C, Chialastri A, Aldeguer JF, Rivron NC, Dey SS. A probabilistic framework for cellular lineage reconstruction using integrated single-cell 5-hydroxymethylcytosine and genomic DNA sequencing. CELL REPORTS METHODS 2021; 1:100060. [PMID: 34590075 PMCID: PMC8478284 DOI: 10.1016/j.crmeth.2021.100060] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/07/2019] [Revised: 06/08/2021] [Accepted: 06/30/2021] [Indexed: 11/24/2022]
Abstract
Lineage reconstruction is central to understanding tissue development and maintenance. To overcome the limitations of current techniques that typically reconstruct clonal trees using genetically encoded reporters, we report scPECLR, a probabilistic algorithm to endogenously infer lineage trees at a single-cell-division resolution by using 5-hydroxymethylcytosine (5hmC). When applied to 8-cell pre-implantation mouse embryos, scPECLR predicts the full lineage tree with greater than 95% accuracy. In addition, we developed scH&G-seq to sequence both 5hmC and genomic DNA from the same cell. Given that genomic DNA sequencing yields information on both copy number variations and single-nucleotide polymorphisms, when combined with scPECLR it enables more accurate lineage reconstruction of larger trees. Finally, we show that scPECLR can also be used to map chromosome strand segregation patterns during cell division, thereby providing a strategy to test the "immortal strand" hypothesis. Thus, scPECLR provides a generalized method to endogenously reconstruct lineage trees at an individual-cell-division resolution.
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Affiliation(s)
- Chatarin Wangsanuwat
- Department of Chemical Engineering, University of California Santa Barbara, Santa Barbara, CA 93106, USA
- Center for Bioengineering, University of California Santa Barbara, Santa Barbara, CA 93106, USA
| | - Alex Chialastri
- Department of Chemical Engineering, University of California Santa Barbara, Santa Barbara, CA 93106, USA
- Center for Bioengineering, University of California Santa Barbara, Santa Barbara, CA 93106, USA
| | - Javier F. Aldeguer
- Hubrecht Institute – KNAW and University Medical Center Utrecht, Utrecht, the Netherlands
| | - Nicolas C. Rivron
- Institute of Molecular Biotechnology of the Austrian Academy of Sciences (IMBA), Vienna BioCenter (VBC), Vienna, Austria
| | - Siddharth S. Dey
- Department of Chemical Engineering, University of California Santa Barbara, Santa Barbara, CA 93106, USA
- Center for Bioengineering, University of California Santa Barbara, Santa Barbara, CA 93106, USA
- Neuroscience Research Institute, University of California Santa Barbara, Santa Barbara, CA 93106, USA
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47
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Dujardin P, Baginska AK, Urban S, Grüner BM. Unraveling Tumor Heterogeneity by Using DNA Barcoding Technologies to Develop Personalized Treatment Strategies in Advanced-Stage PDAC. Cancers (Basel) 2021; 13:4187. [PMID: 34439341 PMCID: PMC8394487 DOI: 10.3390/cancers13164187] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2021] [Revised: 08/12/2021] [Accepted: 08/14/2021] [Indexed: 12/14/2022] Open
Abstract
Tumor heterogeneity is a hallmark of many solid tumors, including pancreatic ductal adenocarcinoma (PDAC), and an inherent consequence of the clonal evolution of cancers. As such, it is considered the underlying concept of many characteristics of the disease, including the ability to metastasize, adapt to different microenvironments, and to develop therapy resistance. Undoubtedly, the high mortality of PDAC can be attributed to a high extent to these properties. Despite its apparent importance, studying tumor heterogeneity has been a challenging task, mainly due to its complexity and lack of appropriate methods. However, in recent years molecular DNA barcoding has emerged as a sophisticated tool that allows mapping of individual cells or subpopulations in a cell pool to study heterogeneity and thus devise new personalized treatment strategies. In this review, we provide an overview of genetic and non-genetic inter- and intra-tumor heterogeneity and its impact on (personalized) treatment strategies in PDAC and address how DNA barcoding technologies work and can be applied to study this clinically highly relevant question.
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Affiliation(s)
- Philip Dujardin
- West German Cancer Center, Department of Medical Oncology, University Hospital Essen at the University Duisburg-Essen, 45147 Essen, Germany
| | - Anna K Baginska
- West German Cancer Center, Department of Medical Oncology, University Hospital Essen at the University Duisburg-Essen, 45147 Essen, Germany
| | - Sebastian Urban
- West German Cancer Center, Department of Medical Oncology, University Hospital Essen at the University Duisburg-Essen, 45147 Essen, Germany
| | - Barbara M Grüner
- West German Cancer Center, Department of Medical Oncology, University Hospital Essen at the University Duisburg-Essen, 45147 Essen, Germany
- German Cancer Consortium (DKTK) Partner Site Essen/Düsseldorf, 45147 Essen, Germany
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48
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Tao L, Raz O, Marx Z, Ghosh MS, Huber S, Greindl-Junghans J, Biezuner T, Amir S, Milo L, Adar R, Levy R, Onn A, Chapal-Ilani N, Berman V, Ben Arie A, Rom G, Oron B, Halaban R, Czyz ZT, Werner-Klein M, Klein CA, Shapiro E. Retrospective cell lineage reconstruction in humans by using short tandem repeats. CELL REPORTS METHODS 2021; 1:None. [PMID: 34341783 PMCID: PMC8313865 DOI: 10.1016/j.crmeth.2021.100054] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/29/2020] [Revised: 04/17/2021] [Accepted: 06/24/2021] [Indexed: 12/18/2022]
Abstract
Cell lineage analysis aims to uncover the developmental history of an organism back to its cell of origin. Recently, novel in vivo methods utilizing genome editing enabled important insights into the cell lineages of animals. In contrast, human cell lineage remains restricted to retrospective approaches, which still lack resolution and cost-efficient solutions. Here, we demonstrate a scalable platform based on short tandem repeats targeted by duplex molecular inversion probes. With this human cell lineage tracing method, we accurately reproduced a known lineage of DU145 cells and reconstructed lineages of healthy and metastatic single cells from a melanoma patient who matched the anatomical reference while adding further refinements. This platform allowed us to faithfully recapitulate lineages of developmental tissue formation in healthy cells. In summary, our lineage discovery platform can profile informative somatic mutations efficiently and provides solid lineage reconstructions even in challenging low-mutation-rate healthy single cells.
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Affiliation(s)
- Liming Tao
- Department of Computer Science and Applied Mathematics, Weizmann Institute of Science, Rehovot 761001, Israel
| | - Ofir Raz
- Department of Computer Science and Applied Mathematics, Weizmann Institute of Science, Rehovot 761001, Israel
| | - Zipora Marx
- Department of Computer Science and Applied Mathematics, Weizmann Institute of Science, Rehovot 761001, Israel
| | - Manjusha S. Ghosh
- Experimental Medicine and Therapy Research, University of Regensburg, Franz-Josef-Strauß-Allee 11, 93053 Regensburg, Germany
| | - Sandra Huber
- Experimental Medicine and Therapy Research, University of Regensburg, Franz-Josef-Strauß-Allee 11, 93053 Regensburg, Germany
| | - Julia Greindl-Junghans
- Experimental Medicine and Therapy Research, University of Regensburg, Franz-Josef-Strauß-Allee 11, 93053 Regensburg, Germany
| | - Tamir Biezuner
- Department of Computer Science and Applied Mathematics, Weizmann Institute of Science, Rehovot 761001, Israel
| | - Shiran Amir
- Department of Computer Science and Applied Mathematics, Weizmann Institute of Science, Rehovot 761001, Israel
| | - Lilach Milo
- Department of Computer Science and Applied Mathematics, Weizmann Institute of Science, Rehovot 761001, Israel
| | - Rivka Adar
- Department of Computer Science and Applied Mathematics, Weizmann Institute of Science, Rehovot 761001, Israel
| | - Ron Levy
- Department of Computer Science and Applied Mathematics, Weizmann Institute of Science, Rehovot 761001, Israel
| | - Amos Onn
- Department of Computer Science and Applied Mathematics, Weizmann Institute of Science, Rehovot 761001, Israel
| | - Noa Chapal-Ilani
- Department of Computer Science and Applied Mathematics, Weizmann Institute of Science, Rehovot 761001, Israel
| | - Veronika Berman
- Department of Computer Science and Applied Mathematics, Weizmann Institute of Science, Rehovot 761001, Israel
| | - Asaf Ben Arie
- Department of Computer Science and Applied Mathematics, Weizmann Institute of Science, Rehovot 761001, Israel
| | - Guy Rom
- Department of Computer Science and Applied Mathematics, Weizmann Institute of Science, Rehovot 761001, Israel
| | - Barak Oron
- Department of Computer Science and Applied Mathematics, Weizmann Institute of Science, Rehovot 761001, Israel
| | - Ruth Halaban
- Department of Dermatology, Yale University School of Medicine, New Haven, CT 06520-8059, USA
| | - Zbigniew T. Czyz
- Experimental Medicine and Therapy Research, University of Regensburg, Franz-Josef-Strauß-Allee 11, 93053 Regensburg, Germany
| | - Melanie Werner-Klein
- Experimental Medicine and Therapy Research, University of Regensburg, Franz-Josef-Strauß-Allee 11, 93053 Regensburg, Germany
| | - Christoph A. Klein
- Experimental Medicine and Therapy Research, University of Regensburg, Franz-Josef-Strauß-Allee 11, 93053 Regensburg, Germany
- Division of Personalized Tumor Therapy, Fraunhofer Institute for Experimental Medicine and Toxicology Regensburg, Am Biopark 9, 93053 Regensburg, Germany
| | - Ehud Shapiro
- Department of Computer Science and Applied Mathematics, Weizmann Institute of Science, Rehovot 761001, Israel
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49
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Bode D, Cull AH, Rubio-Lara JA, Kent DG. Exploiting Single-Cell Tools in Gene and Cell Therapy. Front Immunol 2021; 12:702636. [PMID: 34322133 PMCID: PMC8312222 DOI: 10.3389/fimmu.2021.702636] [Citation(s) in RCA: 22] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2021] [Accepted: 06/28/2021] [Indexed: 12/12/2022] Open
Abstract
Single-cell molecular tools have been developed at an incredible pace over the last five years as sequencing costs continue to drop and numerous molecular assays have been coupled to sequencing readouts. This rapid period of technological development has facilitated the delineation of individual molecular characteristics including the genome, transcriptome, epigenome, and proteome of individual cells, leading to an unprecedented resolution of the molecular networks governing complex biological systems. The immense power of single-cell molecular screens has been particularly highlighted through work in systems where cellular heterogeneity is a key feature, such as stem cell biology, immunology, and tumor cell biology. Single-cell-omics technologies have already contributed to the identification of novel disease biomarkers, cellular subsets, therapeutic targets and diagnostics, many of which would have been undetectable by bulk sequencing approaches. More recently, efforts to integrate single-cell multi-omics with single cell functional output and/or physical location have been challenging but have led to substantial advances. Perhaps most excitingly, there are emerging opportunities to reach beyond the description of static cellular states with recent advances in modulation of cells through CRISPR technology, in particular with the development of base editors which greatly raises the prospect of cell and gene therapies. In this review, we provide a brief overview of emerging single-cell technologies and discuss current developments in integrating single-cell molecular screens and performing single-cell multi-omics for clinical applications. We also discuss how single-cell molecular assays can be usefully combined with functional data to unpick the mechanism of cellular decision-making. Finally, we reflect upon the introduction of spatial transcriptomics and proteomics, its complementary role with single-cell RNA sequencing (scRNA-seq) and potential application in cellular and gene therapy.
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Affiliation(s)
- Daniel Bode
- Wellcome Medical Research Council (MRC) Cambridge Stem Cell Institute, University of Cambridge, Cambridge, United Kingdom
- Department of Haematology, University of Cambridge, Cambridge, United Kingdom
| | - Alyssa H. Cull
- York Biomedical Research Institute, Department of Biology, University of York, York, United Kingdom
| | - Juan A. Rubio-Lara
- York Biomedical Research Institute, Department of Biology, University of York, York, United Kingdom
| | - David G. Kent
- York Biomedical Research Institute, Department of Biology, University of York, York, United Kingdom
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50
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Gutierrez C, Al’Khafaji AM, Brenner E, Johnson KE, Gohil SH, Lin Z, Knisbacher BA, Durrett RE, Li S, Parvin S, Biran A, Zhang W, Rassenti L, Kipps TJ, Livak KJ, Neuberg D, Letai A, Getz G, Wu CJ, Brock A. Multifunctional barcoding with ClonMapper enables high-resolution study of clonal dynamics during tumor evolution and treatment. NATURE CANCER 2021; 2:758-772. [PMID: 34939038 PMCID: PMC8691751 DOI: 10.1038/s43018-021-00222-8] [Citation(s) in RCA: 40] [Impact Index Per Article: 13.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/08/2021] [Accepted: 05/17/2021] [Indexed: 12/13/2022]
Abstract
Lineage-tracing methods have enabled characterization of clonal dynamics in complex populations, but generally lack the ability to integrate genomic, epigenomic and transcriptomic measurements with live-cell manipulation of specific clones of interest. We developed a functionalized lineage-tracing system, ClonMapper, which integrates DNA barcoding with single-cell RNA sequencing and clonal isolation to comprehensively characterize thousands of clones within heterogeneous populations. Using ClonMapper, we identified subpopulations of a chronic lymphocytic leukemia cell line with distinct clonal compositions, transcriptional signatures and chemotherapy survivorship trajectories; patterns that were also observed in primary human chronic lymphocytic leukemia. The ability to retrieve specific clones before, during and after treatment enabled direct measurements of clonal diversification and durable subpopulation transcriptional signatures. ClonMapper is a powerful multifunctional approach to dissect the complex clonal dynamics of tumor progression and therapeutic response.
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Affiliation(s)
- Catherine Gutierrez
- Harvard Medical School, Boston, MA, USA
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
- These authors contributed equally: Catherine Gutierrez, Aziz M. Al’Khafaji, Eric Brenner
| | - Aziz M. Al’Khafaji
- Institute of Cellular and Molecular Biology, University of Texas at Austin, Austin, TX, USA
- Department of Biomedical Engineering, University of Texas at Austin, Austin, TX, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- These authors contributed equally: Catherine Gutierrez, Aziz M. Al’Khafaji, Eric Brenner
| | - Eric Brenner
- Institute of Cellular and Molecular Biology, University of Texas at Austin, Austin, TX, USA
- Department of Biomedical Engineering, University of Texas at Austin, Austin, TX, USA
- These authors contributed equally: Catherine Gutierrez, Aziz M. Al’Khafaji, Eric Brenner
| | - Kaitlyn E. Johnson
- Department of Biomedical Engineering, University of Texas at Austin, Austin, TX, USA
| | - Satyen H. Gohil
- Harvard Medical School, Boston, MA, USA
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Academic Haematology, University College London, London, UK
- Department of Clinical Haematology, University College London Hospitals NHS Foundation Trust, London, UK
| | - Ziao Lin
- Harvard Medical School, Boston, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Harvard University, Cambridge, MA, USA
| | | | - Russell E. Durrett
- Institute of Cellular and Molecular Biology, University of Texas at Austin, Austin, TX, USA
- Department of Biomedical Engineering, University of Texas at Austin, Austin, TX, USA
| | - Shuqiang Li
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Translational Immunogenomics Laboratory, Dana-Farber Cancer Institute, Boston, MA, USA
| | - Salma Parvin
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
| | - Anat Biran
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Wandi Zhang
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
| | - Laura Rassenti
- Department of Medicine, University of California at San Diego Moores Cancer Center, La Jolla, CA, USA
| | - Thomas J. Kipps
- Department of Medicine, University of California at San Diego Moores Cancer Center, La Jolla, CA, USA
| | - Kenneth J. Livak
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
- Translational Immunogenomics Laboratory, Dana-Farber Cancer Institute, Boston, MA, USA
| | - Donna Neuberg
- Department of Data Sciences, Dana Farber Cancer Institute, Boston, MA, USA
| | - Anthony Letai
- Harvard Medical School, Boston, MA, USA
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
| | - Gad Getz
- Harvard Medical School, Boston, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Pathology, Massachusetts General Hospital, Boston, MA, USA
- Center for Cancer Research, Massachusetts General Hospital, Boston, MA, USA
| | - Catherine J. Wu
- Harvard Medical School, Boston, MA, USA
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Medicine, Brigham and Women’s Hospital, Boston, MA, USA
| | - Amy Brock
- Institute of Cellular and Molecular Biology, University of Texas at Austin, Austin, TX, USA
- Department of Biomedical Engineering, University of Texas at Austin, Austin, TX, USA
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