Whole-organism lineage tracing by combinatorial and cumulative genome editing

Barcodes based on nucleic acid sequences: Applications and challenges (Review)

Cells are the fundamental structural and functional units of living organisms and the study of these entities has remained a central focus throughout the history of biological sciences. Traditional cell research techniques, including fluorescent protein tagging and microscopy, have provided preliminary insights into the lineage history and clonal relationships between progenitor and descendant cells. However, these techniques exhibit inherent limitations in tracking the full developmental trajectory of cells and elucidating their heterogeneity, including sensitivity, stability and barcode drift. In developmental biology, nucleic acid barcode technology has introduced an innovative approach to cell lineage tracing. By assigning unique barcodes to individual cells, researchers can accurately identify and trace the origin and differentiation pathways of cells at various developmental stages, thereby illuminating the dynamic processes underlying tissue development and organogenesis. In cancer research, nucleic acid barcoding has played a pivotal role in analyzing the clonal architecture of tumor cells, exploring their heterogeneity and resistance mechanisms and enhancing our understanding of cancer evolution and inter‑clonal interactions. Furthermore, nucleic acid barcodes play a crucial role in stem cell research, enabling the tracking of stem cells from diverse origins and their derived progeny. This has offered novel perspectives on the mechanisms of stem cell self‑renewal and differentiation. The present review presented a comprehensive examination of the principles, applications and challenges associated with nucleic acid barcode technology.

Exploring the untapped potential of single-cell and spatial omics in plant biology

Advances in single-cell and spatial omics technologies have revolutionised biology by revealing the diverse molecular states of individual cells and their spatial organization within tissues. The field of plant biology has widely adopted single-cell transcriptome and chromatin accessibility profiling and spatial transcriptomics, which extend traditional cell biology and genomics analyses and provide unique opportunities to reveal molecular and cellular dynamics of tissues. Using these technologies, comprehensive cell atlases have been generated in several model plant species, providing valuable platforms for discovery and tool development. Other emerging technologies related to single-cell and spatial omics, such as multiomics, lineage tracing, molecular recording, and high-content genetic and chemical perturbation phenotyping, offer immense potential for deepening our understanding of plant biology yet remain underutilised due to unique technical challenges and resource availability. Overcoming plant-specific barriers, such as cell wall complexity and limited antibody resources, alongside community-driven efforts in developing more complete reference atlases and computational tools, will accelerate progress. The synergy between technological innovation and targeted biological questions is poised to drive significant discoveries, advancing plant science. This review highlights the current applications of single-cell and spatial omics technologies in plant research and introduces emerging approaches with the potential to transform the field.

Single-cell phylodynamic inference of stem cell differentiation and tumor evolution

Phylodynamic inference (PI) quantifies population dynamics and evolutionary trajectories using phylogenetic trees. Single-cell lineage tracing enables phylogenetic tree reconstruction for thousands of cells in multicellular organisms, facilitating PI at the cellular level. However, cell differentiation and somatic evolution challenge the direct application of existing PI frameworks to somatic tissues. We introduce scPhyloX, a computational framework modeling structured cell populations by leveraging single-cell phylogenetic trees to infer tissue development and tumor evolution dynamics. A key advancement is its ability to infer time-varying parameters, capturing dynamic biological processes. Simulations demonstrate scPhyloX's accuracy in scenarios including tissue development, disease treatment, and tumor growth. Application to three real datasets reveals insights into somatic dynamics: cycling stem cell overshoot in fly organ development, clonal expansion of multipotent hematopoietic progenitors during human aging, and pronounced subclonal selection in early colorectal tumorigenesis. scPhyloX thus provides a computational approach for investigating somatic tissue development and evolution.

A dynamic and multimodal framework to define microglial states

The widespread use of single-cell RNA sequencing has generated numerous purportedly distinct and novel subsets of microglia. Here, we challenge this fragmented paradigm by proposing that microglia exist along a continuum rather than as discrete entities. We identify a methodological over-reliance on computational clustering algorithms as the fundamental issue, with arbitrary cluster numbers being interpreted as biological reality. Evidence suggests that the observed transcriptional diversity stems from a combination of microglial plasticity and technical noise, resulting in terminology describing largely overlapping cellular states. We introduce a continuous model of microglial states, where cell positioning along the continuum is determined by biological aging and cell-specific molecular contexts. The model accommodates the dynamic nature of microglia. We advocate for a parsimonious approach toward classification and terminology that acknowledges the continuous spectrum of microglial states, toward a robust framework for understanding these essential immune cells of the CNS.

Molecular circuits for genomic recording of cellular events

Advances in precise genome editing are enabling genomic recordings of cellular events. Since the initial demonstration of CRISPR-based genome editing, the field of genomic recording has witnessed key strides in lineage recording, where clonal lineage relationships among cells are indirectly recorded as synthetic mutations. However, methods for directly recording and reconstructing past cellular events are still limited, and their potential for revealing new insights into cell fate decisions has yet to be realized. The field needs new sensing modules and genetic circuit architectures that faithfully encode past cellular states into genomic DNA recordings to achieve such goals. Here we review recently developed strategies to construct diverse sensors and explore how emerging synthetic biology tools may help to build molecular circuits for genomic recording of diverse cellular events.

Advantages and challenges of ex vivo generation and expansion of human hematopoietic stem cells from pluripotent stem cells

Hematopoietic stem cell transplantation (HSCT) is an essential and increasing therapeutic approach for treating conditions such as leukemia, lymphoma, and other blood cancers. However, its widespread use faces significant challenges, including limited donor availability, pathogens, and the risk of immune rejection. The emergence of pluripotent stem cells (PSCs) offers a potential solution to these challenges. By enabling the generation of hematopoietic stem cells (HSCs) and blood cells in vitro, PSCs open pathways to address the limitations of traditional HSC sources. Self-induced or gene-edited PSCs from patients may provide an accessible and personalized option for clinical applications. In this review, we examine the current protocols for differentiating PSCs into HSCs and blood cells, highlighting their benefits and shortcomings. Despite advancements in this field, two primary challenges persist: low differentiation efficiency and difficulties in isolating and enriching functional HSCs. These problems make it difficult to obtain HSCs for long-term survival. Thus, we propose innovative strategies and potential improvements including induction scheme optimization, reprogramming, and cell fate tracking. Future research should prioritize the development of efficient and reliable differentiation protocols for PSCs to obtain more functional HSCs. Additionally, establishing effective methods for enriching functional HSCs and blood cells will be critical for optimizing their use in clinical applications. These efforts hold the promise of overcoming current limitations and advancing the therapeutic potential of PSC-derived blood cells.

Stereotyped Subclones Revealed by High-Density Single-Cell Lineage Tracing Support Robust Development

Robust development is essential for multicellular organisms. While various mechanisms contributing to developmental robustness are identified at the subcellular level, those at the intercellular and tissue level remain underexplored. This question is approached using a well-established in vitro directed differentiation model recapitulating the in vivo development of lung progenitor cells from human embryonic stem cells. An integrated analysis of high-density cell lineage trees (CLTs) and single-cell transcriptomes of differentiating colonies enabled the resolution of known cell types and developmental hierarchies. This dataset showed little support for the contribution of transcriptional memory to developmental robustness. Nevertheless, stable terminal cell type compositions are observed among many subclones, which enhances developmental robustness because the colony can retain a relatively stable composition even if some subclones are abolished by cell death. Furthermore, it is found that many subclones are formed by sub-CLTs resembling each other in terms of both terminal cell type compositions and topological structures. The presence of stereotyped sub-CLTs constitutes a novel basis for developmental robustness. Moreover, these results suggest a unique perspective on individual cells' function in the context of stereotyped sub-CLTs, which can bridge the knowledge of the atlas of cell types and how they are organized into functional tissues.

BASELINE: A CRISPR Base Editing Platform for Mammalian-Scale Single-Cell Lineage Tracing

A cells fate is shaped by its inherited state, or lineage, and the ever-shifting context of its environment. CRISPR-based recording technologies are a promising solution to map the lineage of a developing system, yet challenges remain regarding single-cell recovery, engineering complexity, and scale. Here, we introduce BASELINE, which uses base editing to generate high-resolution lineage trees in conjunction with single-cell profiling. BASELINE uses the Cas12a adenine base editor to irreversibly edit nucleotides within 50 synthetic target sites, which are integrated multiple times into a cells genome. We show that BASELINE accumulates lineage-specific marks over a wide range of biologically relevant intervals, recording more than 4300 bits of information in a model of pancreatic cancer, a 50X increase over existing technologies. Single-cell sequencing reveals high-fidelity capture of these recorders, recovering lineage reconstructions up to 40 cell divisions deep, within the estimated range of mammalian development. We expect BASELINE to apply to a wide range of lineage-tracing projects in development and disease, especially in which cellular engineering makes small, more distributed systems challenging.

Zebrafish as a Versatile Model for Cardiovascular Research: Peering into the Heart of the Matter

Cardiovascular diseases (CVDs) are the leading cause of death in the world. A total of 17.5 million people died of CVDs in the year 2012, accounting for 31% of all deaths globally. Vertebrate animal models have been used to understand cardiac disease biology, as the cellular, molecular, and physiological aspects of human CVDs can be replicated closely in these organisms. Zebrafish is a popular model organism offering an arsenal of genetic tools that allow the rapid in vivo analysis of vertebrate gene function and disease conditions. It has a short breeding cycle, high fecundity, optically transparent embryos, rapid internal organ development, and easy maintenance. This review aims to give readers an overview of zebrafish cardiac biology and a detailed account of heart development in zebrafish and its comparison with humans and the conserved genetic circuitry. We also discuss the contributions made in CVD research using the zebrafish model. The first part of this review focuses on detailed information on the morphogenetic and differentiation processes in early cardiac development. The overlap and divergence of the human heart's genetic circuitry, structure, and physiology are emphasized wherever applicable. In the second part of the review, we overview the molecular tools and techniques available to dissect gene function and expression in zebrafish, with special mention of the use of these tools in cardiac biology.

Open-ended molecular recording of sequential cellular events into DNA

Genetically encoded DNA recorders noninvasively convert transient biological events into durable mutations in a cell's genome, allowing for the later reconstruction of cellular experiences by DNA sequencing. We present a DNA recorder, peCHYRON, that achieves high-information, durable, and temporally resolved multiplexed recording of multiple cellular signals in mammalian cells. In each step of recording, prime editor, a Cas9-reverse transcriptase fusion protein, inserts a variable triplet DNA sequence alongside a constant propagator sequence that deactivates the previous and activates the next step of insertion. Insertions accumulate sequentially in a unidirectional order, editing can continue indefinitely, and high information is achieved by coexpressing a variety of prime editing guide RNAs (pegRNAs), each harboring unique triplet DNA sequences. We demonstrate that the constitutive expression of pegRNA collections generates insertion patterns for the straightforward reconstruction of cell lineage relationships and that the inducible expression of specific pegRNAs results in the accurate recording of exposures to biological stimuli.

Clonal expansion dictates the efficacy of mitochondrial lineage tracing in single cells

BACKGROUND

Mitochondrial DNA (mtDNA) variants hold promise as endogenous barcodes for tracking human cell lineages, but their efficacy as reliable lineage markers are hindered by the complex dynamics of mtDNA in somatic tissues.

RESULTS

Here, we use computational modeling and single-cell genomics to thoroughly interrogate the origin and clonal dynamics of mtDNA variants across various biological settings. Our findings reveal that the majority of mtDNA variants which are specifically present in a cell subpopulation, termed subpopulation-specific variants, are pre-existing heteroplasmies in the first cell instead of de novo somatic mutations during divisions. Moreover, subpopulation-specific variants demonstrate limited discriminatory power among different genuine lineages under weak clonal expansion; however, certain subpopulation-specific variants with consistently high frequencies among a subpopulation are capable of faithfully labeling cell lineages in scenarios of stringent clonal expansion, such as strongly expanded T cell populations in diseased conditions and clonal hematopoiesis in aged individuals. Inspired by our simulations, we introduce a lineage informative score, facilitating the identification of reliable mitochondrial lineage tracing markers across different modalities of single-cell genomic data.

CONCLUSIONS

Combining computational modeling and single-cell sequencing, our study reveals that the performance of mitochondrial lineage tracing is highly dependent on the extent of clonal expansion, which thus should be considered when applying mitochondrial lineage tracing.

DARLIN mouse for in vivo lineage tracing at high efficiency and clonal diversity

Lineage tracing is a powerful tool to study cell history and cell dynamics during tissue development and homeostasis. An increasingly popular approach for lineage tracing is to generate high-frequent mutations at given genomic loci, which can serve as genetic barcodes to label different cell lineages. However, current lineage tracing mouse models suffer from low barcode diversity and limited single-cell lineage coverage. We recently developed the DARLIN mouse model by incorporating three barcoding arrays within defined genomic loci and combining Cas9 and terminal deoxynucleotidyl transferase (TdT) to improve editing diversity in each barcode array. We estimated that DARLIN generates 1018 distinct lineage barcodes in theory, and enables the recovery of lineage barcodes in over 70% of cells in single-cell assays. In addition, DARLIN can be induced with doxycycline to generate stable lineage barcodes across different tissues at a defined stage. Here we provide a step-by-step protocol on applying the DARLIN system for in vivo lineage tracing, including barcode induction, estimation of induction efficiency, barcode analysis with bulk and single-cell sequencing, and computational analysis. The execution time of this protocol is ~1 week for experimental data collection and ~1 d for running the computational analysis pipeline. To execute this protocol, one should be familiar with sequencing library generation and Linux operation. DARLIN opens the door to study the lineage relationships and the underlying molecular regulations across various tissues at physiological context.

The endogenous antigen-specific CD8+ T cell repertoire is composed of unbiased and biased clonotypes with differential fate commitments

Generating balanced populations of CD8+ effector and memory T cells is necessary for immediate and durable immunity to infections and cancer. Yet, a definitive understanding of how a diverse CD8+ T cell repertoire differentiates remains unclear. We identified several hundred T cell receptor (TCR) clonotypes that constitute the polyclonal response against a single antigen and found that a majority of TCR clonotypes were highly biased toward memory or effector fates. TCR-intrinsic biases were not stochastic and were dominant over environmental cues. Differential gene expression analysis of memory- or effector-biased TCR clonotypes showed bifurcation of differential fates at the early effector stage. Additionally, phylogenetic analysis revealed that memory-biased clonotypes retain their fate preferences in subclonal populations but effector-biased subclones can switch to a memory fate. Our study highlights that the polyclonal CD8+ T cell response is a composite of unbiased and biased clonotypes with varying capacity to incorporate environmental cues in their cell fate decisions.

Single-cell lineage tracing techniques in hematology: unraveling the cellular narrative

Lineage tracing is a valuable technique that has greatly facilitated the exploration of cell origins and behavior. With the continuous development of single-cell sequencing technology, lineage tracing technology based on the single-cell level has become an important method to study biological development. Single-cell Lineage tracing technology plays an important role in the hematological system. It can help to answer many important questions, such as the heterogeneity of hematopoietic stem cell function and structure, and the heterogeneity of malignant tumor cells in the hematological system. Many studies have been conducted to explore the field of hematology by applying this technology. This review focuses on the superiority of the emerging single-cell lineage tracing technologies of Integration barcodes, CRISPR barcoding, and base editors, and summarizes their applications in the hematology system. These studies have suggested the vast potential in unraveling complex cellular behaviors and lineage dynamics in both normal and pathological contexts.

From morphology to single-cell molecules: high-resolution 3D histology in biomedicine

High-resolution three-dimensional (3D) tissue analysis has emerged as a transformative innovation in the life sciences, providing detailed insights into the spatial organization and molecular composition of biological tissues. This review begins by tracing the historical milestones that have shaped the development of high-resolution 3D histology, highlighting key breakthroughs that have facilitated the advancement of current technologies. We then systematically categorize the various families of high-resolution 3D histology techniques, discussing their core principles, capabilities, and inherent limitations. These 3D histology techniques include microscopy imaging, tomographic approaches, single-cell and spatial omics, computational methods and 3D tissue reconstruction (e.g. 3D cultures and spheroids). Additionally, we explore a wide range of applications for single-cell 3D histology, demonstrating how single-cell and spatial technologies are being utilized in the fields such as oncology, cardiology, neuroscience, immunology, developmental biology and regenerative medicine. Despite the remarkable progress made in recent years, the field still faces significant challenges, including high barriers to entry, issues with data robustness, ambiguous best practices for experimental design, and a lack of standardization across methodologies. This review offers a thorough analysis of these challenges and presents recommendations to surmount them, with the overarching goal of nurturing ongoing innovation and broader integration of cellular 3D tissue analysis in both biology research and clinical practice.

Hierarchical Lineage Tracing Reveals Diverse Pathways of AML Treatment Resistance

Cancer cells adapt to treatment, leading to the emergence of clones that are more aggressive and resistant to anti-cancer therapies. We have a limited understanding of the development of treatment resistance as we lack technologies to map the evolution of cancer under the selective pressure of treatment. To address this, we developed a hierarchical, dynamic lineage tracing method called FLARE (Following Lineage Adaptation and Resistance Evolution). We use this technique to track the progression of acute myeloid leukemia (AML) cell lines through exposure to Cytarabine (AraC), a front-line treatment in AML, in vitro and in vivo. We map distinct cellular lineages in murine and human AML cell lines predisposed to AraC persistence and/or resistance via the upregulation of cell adhesion and motility pathways. Additionally, we highlight the heritable expression of immunoproteasome 11S regulatory cap subunits as a potential mechanism aiding AML cell survival, proliferation, and immune escape in vivo. Finally, we validate the clinical relevance of these signatures in the TARGET-AML cohort, with a bisected response in blood and bone marrow. Our findings reveal a broad spectrum of resistance signatures attributed to significant cell transcriptional changes. To our knowledge, this is the first application of dynamic lineage tracing to unravel treatment response and resistance in cancer, and we expect FLARE to be a valuable tool in dissecting the evolution of resistance in a wide range of tumor types.

High-resolution, noninvasive single-cell lineage tracing in mice and humans based on DNA methylation epimutations

In vivo lineage tracing holds great potential to reveal fundamental principles of tissue development and homeostasis. However, current lineage tracing in humans relies on extremely rare somatic mutations, which has limited temporal resolution and lineage accuracy. Here, we developed a generic lineage-tracing tool based on frequent epimutations on DNA methylation, enabled by our computational method MethylTree. Using single-cell genome-wide DNA methylation datasets with known lineage and phenotypic labels, MethylTree reconstructed lineage histories at nearly 100% accuracy across different cell types, developmental stages, and species. We demonstrated the epimutation-based single-cell multi-omic lineage tracing in mouse and human blood, where MethylTree recapitulated the differentiation hierarchy in hematopoiesis. Applying MethylTree to human embryos, we revealed early fate commitment at the four-cell stage. In native mouse blood, we identified ~250 clones of hematopoietic stem cells. MethylTree opens the door for high-resolution, noninvasive and multi-omic lineage tracing in humans and beyond.

Decoding the blueprints of embryo development with single-cell and spatial omics

Embryonic development is a complex and intricately regulated process that encompasses precise control over cell differentiation, morphogenesis, and the underlying gene expression changes. Recent years have witnessed a remarkable acceleration in the development of single-cell and spatial omic technologies, enabling high-throughput profiling of transcriptomic and other multi-omic information at the individual cell level. These innovations offer fresh and multifaceted perspectives for investigating the intricate cellular and molecular mechanisms that govern embryonic development. In this review, we provide an in-depth exploration of the latest technical advancements in single-cell and spatial multi-omic methodologies and compile a systematic catalog of their applications in the field of embryonic development. We deconstruct the research strategies employed by recent studies that leverage single-cell sequencing techniques and underscore the unique advantages of spatial transcriptomics. Furthermore, we delve into both the current applications, data analysis algorithms and the untapped potential of these technologies in advancing our understanding of embryonic development. With the continuous evolution of multi-omic technologies, we anticipate their widespread adoption and profound contributions to unraveling the intricate molecular foundations underpinning embryo development in the foreseeable future.

Decoding maize meristems maintenance and differentiation: integrating single-cell and spatial omics

All plant organs are derived from stem cell-containing meristems. In maize, the shoot apical meristem (SAM) is responsible for generating all above-ground structures, including the male and female inflorescence meristems (IMs), which give rise to tassel and ear, respectively. Forward and reverse genetic studies on maize meristem mutants have driven forward our fundamental understanding of meristem maintenance and differentiation mechanisms. However, the high genetic redundancy of the maize genome has impeded progress in functional genomics. This review comprehensively summarizes recent advancements in understanding maize meristem development, with a focus on the integration of single-cell and spatial technologies. We discuss the mechanisms governing stem cell maintenance and differentiation in SAM and IM, emphasizing the roles of gene regulatory networks, hormonal pathways, and cellular omics insights into stress responses and adaptation. Future directions include cross-species comparisons, multi-omics integration, and the application of these technologies to precision breeding and stress adaptation research, with the ultimate goal of translating our understanding of meristem into the development of higher yield varieties.

The lives of cells, recorded

A paradigm for biology is emerging in which cells can be genetically programmed to write their histories into their own genomes. These records can subsequently be read, and the cellular histories reconstructed, which for each cell could include a record of its lineage relationships, extrinsic influences, internal states and physical locations, over time. DNA recording has the potential to transform the way that we study developmental and disease processes. Recent advances in genome engineering are driving the development of systems for DNA recording, and meanwhile single-cell and spatial omics technologies increasingly enable the recovery of the recorded information. Combined with advances in computational and phylogenetic inference algorithms, the DNA recording paradigm is beginning to bear fruit. In this Perspective, we explore the rationale and technical basis of DNA recording, what aspects of cellular biology might be recorded and how, and the types of discovery that we anticipate this paradigm will enable.

The landscape of cell lineage tracing

Cell fate changes play a crucial role in the processes of natural development, disease progression, and the efficacy of therapeutic interventions. The definition of the various types of cell fate changes, including cell expansion, differentiation, transdifferentiation, dedifferentiation, reprogramming, and state transitions, represents a complex and evolving field of research known as cell lineage tracing. This review will systematically introduce the research history and progress in this field, which can be broadly divided into two parts: prospective tracing and retrospective tracing. The initial section encompasses an array of methodologies pertaining to isotope labeling, transient fluorescent tracers, non-fluorescent transient tracers, non-fluorescent genetic markers, fluorescent protein, genetic marker delivery, genetic recombination, exogenous DNA barcodes, CRISPR-Cas9 mediated DNA barcodes, and base editor-mediated DNA barcodes. The second part of the review covers genetic mosaicism, genomic DNA alteration, TCR/BCR, DNA methylation, and mitochondrial DNA mutation. In the final section, we will address the principal challenges and prospective avenues of enquiry in the field of cell lineage tracing, with a particular focus on the sequencing techniques and mathematical models pertinent to single-cell genetic lineage tracing, and the value of pursuing a more comprehensive investigation at both the spatial and temporal levels in the study of cell lineage tracing.

Hematopoietic stem cells undergo bidirectional fate transitions in vivo

Transitions between subsets of differentiating hematopoietic cells are widely regarded as unidirectional in vivo. Here, we introduce clonal phylogenetic tracer (CP-tracer) that sequentially introduces genetic barcodes, enabling high-resolution analysis of ~100,000 subclones derived from ~500 individual hematopoietic stem cells (HSC). This revealed previously uncharacterized HSC functional subsets and identified bidirectional fate transitions between myeloid-biased and lineage-balanced HSC. Contrary to the prevailing view that the more self-renewing My-HSCs unidirectionally transition to balanced-HSCs, phylogenetic tracing revealed durable lineage bidirectionality with the transition favoring My-HSC accumulation over time1,2. Further, balanced-HSCs mature through distinct intermediates My-HSCs and lymphoid-biased-HSCs with lymphoid competence here shown by CRISPR/Cas9 screening to be dependent on the homeobox gene, Hhex. Hhex enables Ly-HSC differentiation, but its expression declines with age. These findings establish HSC plasticity and Hhex as a determinant of myeloid-lymphoid balance with each changing over time to favor the age-related myeloid bias of the elderly.

A Bayesian phylodynamic inference framework for single-cell CRISPR/Cas9 lineage tracing barcode data with dependent target sites

Analysing single-cell lineage relationships of an organism is crucial towards understanding the fundamental cellular dynamics that drive development. Clustered regularly interspaced short palindromic repeats (CRISPR)-based dynamic lineage tracing relies on recent advances in genome editing and sequencing technologies to generate inheritable, evolving genetic barcode sequences that enable reconstruction of such cell lineage trees, also referred to as phylogenetic trees. Recent work generated custom computational strategies to produce robust tree estimates from such data. We further capitalize on these advancements and introduce GESTALT analysis using Bayesian inference (GABI), which extends the analysis of genome editing of synthetic target arrays for lineage tracing (GESTALT) data to a fully integrated Bayesian phylogenetic inference framework in software BEAST 2. This implementation allows users to represent the uncertainty in reconstructed trees and enables their scaling in absolute time. Furthermore, based on such time-scaled lineage trees, the underlying processes of growth, differentiation and apoptosis are quantified through so-called phylodynamic inference, typically relying on a birth-death or coalescent model. After validating its implementation, we demonstrate that our methodology results in robust estimates of growth dynamics characteristic of early Danio rerio development. GABI's codebase is publicly available at https://github.com/azwaans/GABI.This article is part of the theme issue '"A mathematical theory of evolution": phylogenetic models dating back 100 years'.

Cloning and validating systems for high throughput molecular recording

Molecular recording technologies record and store information about cellular history. Lineage tracing is one form of molecular recording and produces information describing cellular trajectories during mammalian development, differentiation and maintenance of adult stem cell niches, and tumor evolution. Our molecular recorder technology utilizes CRISPR-Cas9 barcode editing to generate mutations in genomically integrated, engineered DNA cassettes, which are read out by single-cell RNA sequencing and used to produce high-resolution lineage trees. Here, we describe optimized cloning and validation procedures to construct the molecular recorder lineage tracing system. We include information on considerations of technology design, cloning procedures, the generation of lineage tracing cell lines, and time course experiments to assess their performance.

Deterministic genetic barcoding for multiplexed behavioral and single-cell transcriptomic studies

Advances in single-cell sequencing technologies have provided novel insights into the dynamics of gene expression and cellular heterogeneity within tissues and have enabled the construction of transcriptomic cell atlases. However, linking anatomical information to transcriptomic data and positively identifying the cell types that correspond to gene expression clusters in single-cell sequencing data sets remains a challenge. We describe a straightforward genetic barcoding approach that takes advantage of the powerful genetic tools in Drosophila to allow in vivo tagging of defined cell populations. This method, called Targeted Genetically-Encoded Multiplexing (TaG-EM), involves inserting a DNA barcode just upstream of the polyadenylation site in a Gal4-inducible UAS-GFP construct so that the barcode sequence can be read out during single-cell sequencing, labeling a cell population of interest. By creating many such independently barcoded fly strains, TaG-EM enables positive identification of cell types in cell atlas projects, identification of multiplet droplets, and barcoding of experimental timepoints, conditions, and replicates. Furthermore, we demonstrate that TaG-EM barcodes can be read out using next-generation sequencing to facilitate population-scale behavioral measurements. Thus, TaG-EM has the potential to enable large-scale behavioral screens in addition to improving the ability to multiplex and reliably annotate single-cell transcriptomic experiments.

Dual-nuclease single-cell lineage tracing by Cas9 and Cas12a

Single-cell lineage tracing based on CRISPR-Cas9 gene editing enables the simultaneous linkage of cell states and lineage history at a high resolution. Despite its immense potential in resolving the cell fate determination and genealogy within an organism, existing implementations of this technology suffer from limitations in recording capabilities and considerable barcode dropout. Here, we introduce DuTracer, a versatile tool that utilizes two orthogonal gene editing systems to record cell lineage history at single-cell resolution in an inducible manner. DuTracer shows the ability to enhance lineage recording with minimized target dropouts and potentially deeper tree depths. Applying DuTracer in mouse embryoid bodies and neuromesodermal organoids illustrates the lineage relationship of different cell types and proposes potential lineage-biased molecular drivers, showcased by identifying transcription factor Foxb1 as a modulator in the cell fate determination of neuromesodermal progenitors. Collectively, DuTracer facilitates the precise and regulatory interrogation of cellular lineages of complex biological processes.

Development of an inducible DNA barcoding system to understand lineage changes in Arabidopsis regeneration

Plants demonstrate a high degree of developmental plasticity, capable of regenerating entire individuals from detached somatic tissues-a regenerative phenomenon rarely observed in metazoa. Consequently, elucidating the lineage relationship between somatic founder cells and descendant cells in regenerated plant organs has long been a pursuit. In this study, we developed and optimized both DNA barcode- and multi-fluorescence-based cell-lineage tracing toolsets, employing an inducible method to mark individual cells in Arabidopsis donor somatic tissues at the onset of regeneration. Utilizing these complementary methods, we scrutinized cell identities at the single-cell level and presented compelling evidence that all cells in the regenerated Arabidopsis plants, irrespective of their organ types, originated from a single progenitor cell in the donor somatic tissue. Our discovery suggests a single-cell passage directing the transition from multicellular donor tissue to regenerated plants, thereby creating opportunities for cell-cell competition during plant regeneration-a strategy for maximizing survival.

Recording Lineage History with Cellular Barcodes in the Mammary Epithelium and in Breast Cancer

Lineage tracing methods have extensively advanced our understanding of physiological cell behaviour in vivo and in situ and have vastly contributed to decipher the phylogeny and cellular hierarchies during normal and tumour development. In recent years, increasingly complex systems have been developed to track thousands of cells within a given tissue or even entire organisms. Cellular barcoding comprises all techniques designed to genetically label single cells with unique DNA sequences or with a combination of fluorescent proteins, in order to trace their history and lineage production in space and time. We distinguish these two types of cellular barcoding as genetic or optical barcodes. Furthermore, transcribed cellular barcodes can integrate the lineage information with single-cell profiling of each barcoded cell. This enables the potential identification of specific markers or signalling pathways defining distinct stem cell states during development, but also signals promoting tumour growth and metastasis or conferring therapy resistance.In this chapter, we describe recent advances in cellular barcoding technologies and outline experimental and computational challenges. We discuss the biological questions that can be addressed using single-cell dynamic lineage tracing, with a focus on the study of cellular hierarchies in the mammary epithelium and in breast cancer.

Reconstructing Progenitor State Hierarchy and Dynamics Using Lineage Barcoding Data

Measurements of cell phylogeny based on natural or induced mutations, known as lineage barcodes, in conjunction with molecular phenotype have become increasingly feasible for a large number of single cells. In this chapter, we delve into Quantitative Fate Mapping (QFM) and its computational pipeline, which enables the interrogation of the dynamics of progenitor cells and their fate restriction during development. The methods described here include inferring cell phylogeny with the Phylotime model, and reconstructing progenitor state hierarchy, commitment time, population size, and commitment bias with the ICE-FASE algorithm. Evaluation of adequate sampling based on progenitor state coverage statistics is emphasized for interpreting the QFM results. Overall, this chapter describes a general framework for characterizing the dynamics of cell fate changes using lineage barcoding data.

Punctuational evolution is pervasive in distal site metastatic colonization

The evolution of metastasis, the spread of cancer to distal sites within the body, represents a lethal stage of cancer progression. Yet, the evolutionary dynamics that shape the emergence of metastatic disease remain unresolved. Here, using single-cell lineage tracing data in combination with phylogenetic statistical methods, we show that the evolutionary trajectory of metastatic disease is littered with bursts of rapid molecular change as new cellular subpopulations appear, a pattern known as punctuational evolution. Next, by measuring punctuational evolution across the metastatic cascade, we show that punctuational effects are concentrated within the formation of secondary tumours at distal metastatic sites, suggesting that qualitatively different modes of evolution may drive primary and metastatic tumour progression. Taken as a whole, our findings provide empirical evidence for distinct patterns of molecular evolution at early and late stages of metastatic disease and our approach provides a framework to study the evolution of metastasis at a more nuanced level than has been previously possible.

Advancements in prospective single-cell lineage barcoding and their applications in research

Single-cell lineage tracing (scLT) has emerged as a powerful tool, providing unparalleled resolution to investigate cellular dynamics, fate determination, and the underlying molecular mechanisms. This review thoroughly examines the latest prospective lineage DNA barcode tracing technologies. It further highlights pivotal studies that leverage single-cell lentiviral integration barcoding technology to unravel the dynamic nature of cell lineages in both developmental biology and cancer research. Additionally, the review navigates through critical considerations for successful experimental design in lineage tracing and addresses challenges inherent in this field, including technical limitations, complexities in data analysis, and the imperative for standardization. It also outlines current gaps in knowledge and suggests future research directions, contributing to the ongoing advancement of scLT studies.

Barcoding Notch signaling in the developing brain

Developmental signaling inputs are fundamental for shaping cell fates and behavior. However, traditional fluorescent-based signaling reporters have limitations in scalability and molecular resolution of cell types. We present SABER-seq, a CRISPR-Cas molecular recorder that stores transient developmental signaling cues as permanent mutations in cellular genomes for deconstruction at later stages via single-cell transcriptomics. We applied SABER-seq to record Notch signaling in developing zebrafish brains. SABER-seq has two components: a signaling sensor and a barcode recorder. The sensor activates Cas9 in a Notch-dependent manner with inducible control, while the recorder obtains mutations in ancestral cells where Notch is active. We combine SABER-seq with an expanded juvenile brain atlas to identify cell types derived from Notch-active founders. Our data reveal rare examples where differential Notch activities in ancestral progenitors are detected in terminally differentiated neuronal subtypes. SABER-seq is a novel platform for rapid, scalable and high-resolution mapping of signaling activity during development.

Post-translational digital data encoding into the genomes of mammalian cell populations

High resolution cellular signal encoding is critical for better understanding of complex biological phenomena. DNA-based biosignal encoders alter genomic or plasmid DNA in a signal dependent manner. Current approaches involve the signal of interest affecting a DNA edit by interacting with a signal specific promoter which then results in expression of the effector molecule (DNA altering enzyme). Here, we present the proof of concept of a biosignal encoding system where the enzyme terminal deoxynucleotidyl transferase (TdT) acts as the effector molecule upon directly interacting with the signal of interest. A template independent DNA polymerase (DNAp), TdT incorporates nucleotides at the 3' OH ends of DNA substrate in a signal dependent manner. By employing CRISPR-Cas9 to create double stranded breaks in genomic DNA, we make 3'OH ends available to act as substrate for TdT. We show that this system can successfully resolve and encode different concentrations of various biosignals into the genomic DNA of HEK-293T cells. Finally, we develop a simple encoding scheme associated with the tested biosignals and encode the message "HELLO WORLD" into the genomic DNA of HEK-293T cells at a population level with 91% accuracy. This work demonstrates a simple and engineerable system that can reliably store local biosignal information into the genomes of mammalian cell populations.

Applying single-cell and single-nucleus genomics to studies of cellular heterogeneity and cell fate transitions in the nervous system

Single-cell and single-nucleus genomic approaches can provide unbiased and multimodal insights. Here, we discuss what constitutes a molecular cell atlas and how to leverage single-cell omics data to generate hypotheses and gain insights into cell transitions in development and disease of the nervous system. We share points of reflection on what to consider during study design and implementation as well as limitations and pitfalls.

Polyclonal-to-monoclonal transition in colorectal precancerous evolution

Unravelling the origin and evolution of precancerous lesions is crucial for effectively preventing malignant transformation, yet our current knowledge remains limited1-3. Here we used a base editor-enabled DNA barcoding system4 to comprehensively map single-cell phylogenies in mouse models of intestinal tumorigenesis induced by inflammation or loss of the Apc gene. Through quantitative analysis of high-resolution phylogenies including 260,922 single cells from normal, inflamed and neoplastic intestinal tissues, we identified tens of independent cell lineages undergoing parallel clonal expansions within each lesion. We also found polyclonal origins of human sporadic colorectal polyps through bulk whole-exome sequencing and single-gland whole-genome sequencing. Genomic and clinical data support a model of polyclonal-to-monoclonal transition, with monoclonal lesions representing a more advanced stage. Single-cell RNA sequencing revealed extensive intercellular interactions in early polyclonal lesions, but there was significant loss of interactions during monoclonal transition. Therefore, our data suggest that colorectal precancer is often founded by many different lineages and highlight their cooperative interactions in the earliest stages of cancer formation. These findings provide insights into opportunities for earlier intervention in colorectal cancer.

Time-resolved single-cell transcriptomic sequencing

Cells experience continuous transformation under both physiological and pathological circumstances. Single-cell RNA sequencing (scRNA-seq) is competent in disclosing the disparities of cells; nevertheless, it poses challenges in linking the individual cell state at distinct time points. Although computational approaches based on scRNA-seq data have been put forward for trajectory analysis, the result is based on assumptions and fails to reflect the actual states. Consequently, it is necessary to incorporate a "time anchor" into the scRNA-seq library for the temporal documentation of the dynamic expression pattern. This review comprehensively overviews the time-resolved single-cell transcriptomic sequencing methodologies and applications. As scRNA-seq functions as the basis for profiling single-cell expression patterns, the review initially introduces various scRNA-seq approaches. Subsequently, the review focuses on the different experimental strategies for introducing a "time anchor" to scRNA-seq, highlighting their principles, strengths, weaknesses, and comparing their adaptation in various scenarios. Next, it provides a brief summary of applications in immunity response, cancer progression, and embryo development. Finally, the review concludes with a forward-looking perspective on future advancements in time-resolved single-cell transcriptomic sequencing.

A multimodal zebrafish developmental atlas reveals the state-transition dynamics of late-vertebrate pluripotent axial progenitors

Elucidating organismal developmental processes requires a comprehensive understanding of cellular lineages in the spatial, temporal, and molecular domains. In this study, we introduce Zebrahub, a dynamic atlas of zebrafish embryonic development that integrates single-cell sequencing time course data with lineage reconstructions facilitated by light-sheet microscopy. This atlas offers high-resolution and in-depth molecular insights into zebrafish development, achieved through the sequencing of individual embryos across ten developmental stages, complemented by reconstructions of cellular trajectories. Zebrahub also incorporates an interactive tool to navigate the complex cellular flows and lineages derived from light-sheet microscopy data, enabling in silico fate-mapping experiments. To demonstrate the versatility of our multimodal resource, we utilize Zebrahub to provide fresh insights into the pluripotency of neuro-mesodermal progenitors (NMPs) and the origins of a joint kidney-hemangioblast progenitor population.

An attractor state zone precedes neural crest fate in melanoma initiation

The field cancerization theory suggests that a group of cells containing oncogenic mutations are predisposed to transformation1, 2. We previously identified single cells in BRAF V600E ;p53 -/- zebrafish that reactivate an embryonic neural crest state before initiating melanoma3-5. Here we show that single cells reactivate the neural crest fate from within large fields of adjacent abnormal melanocytes, which we term the "cancer precursor zone." These cancer precursor zone melanocytes have an aberrant morphology, dysplastic nuclei, and altered gene expression. Using single cell RNA-seq and ATAC-seq, we defined a distinct transcriptional cell attractor state for cancer precursor zones and validated the stage-specific gene expression initiation signatures in human melanoma. We identify the cancer precursor zone driver, ID1, which binds to TCF12 and inhibits downstream targets important for the maintenance of melanocyte morphology and cell cycle control. Examination of patient samples revealed precursor melanocytes expressing ID1, often surrounding invasive melanoma, indicating a role for ID1 in early melanomagenesis. This work reveals a surprising field effect of melanoma initiation in vivo in which tumors arise from within a zone of morphologically distinct, but clinically covert, precursors with altered transcriptional fate. Our studies identify novel targets that could improve early diagnosis and prevention of melanoma.

Spatiotemporal lineage tracing reveals the dynamic spatial architecture of tumor growth and metastasis

Tumor progression is driven by dynamic interactions between cancer cells and their surrounding microenvironment. Investigating the spatiotemporal evolution of tumors can provide crucial insights into how intrinsic changes within cancer cells and extrinsic alterations in the microenvironment cooperate to drive different stages of tumor progression. Here, we integrate high-resolution spatial transcriptomics and evolving lineage tracing technologies to elucidate how tumor expansion, plasticity, and metastasis co-evolve with microenvironmental remodeling in a Kras;p53-driven mouse model of lung adenocarcinoma. We find that rapid tumor expansion contributes to a hypoxic, immunosuppressive, and fibrotic microenvironment that is associated with the emergence of pro-metastatic cancer cell states. Furthermore, metastases arise from spatially-confined subclones of primary tumors and remodel the distant metastatic niche into a fibrotic, collagen-rich microenvironment. Together, we present a comprehensive dataset integrating spatial assays and lineage tracing to elucidate how sequential changes in cancer cell state and microenvironmental structures cooperate to promote tumor progression.

Neuronal lineage tracing from progenitors in human cortical organoids reveals mechanisms of neuronal production, diversity, and disease

The contribution of progenitor subtypes to generating the billions of neurons produced during human cortical neurogenesis is not well understood. We developed the cortical organoid lineage-tracing (COR-LT) system for human cortical organoids. Differential fluorescent reporter activation in distinct progenitor cells leads to permanent reporter expression, enabling the progenitor cell lineage of neurons to be determined. Surprisingly, nearly all excitatory neurons produced in cortical organoids were generated indirectly from intermediate progenitor cells. Additionally, neurons of different progenitor lineages were transcriptionally distinct. Isogenic lines made from an autistic individual with and without a likely pathogenic CTNNB1 variant demonstrated that the variant substantially altered the proportion of neurons derived from specific progenitor cell lineages, as well as the lineage-specific transcriptional profiles of these neurons, suggesting a pathogenic mechanism for this mutation. These results suggest individual progenitor subtypes play roles in generating the diverse neurons of the human cerebral cortex.

Reconstructing signaling history of single cells with imaging-based molecular recording

The intensity and duration of biological signals encode information that allows a few pathways to regulate a wide array of cellular behaviors. Despite the central importance of signaling in biomedical research, our ability to quantify it in individual cells over time remains limited. Here, we introduce INSCRIBE, an approach for reconstructing signaling history in single cells using endpoint fluorescence images. By regulating a CRISPR base editor, INSCRIBE generates mutations in genomic target sequences, at a rate proportional to signaling activity. The number of edits is then recovered through a novel ratiometric readout strategy, from images of two fluorescence channels. We engineered human cell lines for recording WNT and BMP pathway activity, and demonstrated that INSCRIBE faithfully recovers both the intensity and duration of signaling. Further, we used INSCRIBE to study the variability of cellular response to WNT and BMP stimulation, and test whether the magnitude of response is a stable, heritable trait. We found a persistent memory in the BMP pathway. Progeny of cells with higher BMP response levels are likely to respond more strongly to a second BMP stimulation, up to 3 weeks later. Together, our results establish a scalable platform for genetic recording and in situ readout of signaling history in single cells, advancing quantitative analysis of cell-cell communication during development and disease.

Clonal Lineage Tracing with Somatic Delivery of Recordable Barcodes Reveals Migration Histories of Metastatic Prostate Cancer

The patterns by which primary tumors spread to metastatic sites remain poorly understood. Here, we define patterns of metastatic seeding in prostate cancer using a novel injection-based mouse model-EvoCaP (Evolution in Cancer of the Prostate), featuring aggressive metastatic cancer to bone, liver, lungs, and lymph nodes. To define migration histories between primary and metastatic sites, we used our EvoTraceR pipeline to track distinct tumor clones containing recordable barcodes. We detected widespread intratumoral heterogeneity from the primary tumor in metastatic seeding, with few clonal populations instigating most migration. Metastasis-to-metastasis seeding was uncommon, as most cells remained confined within the tissue. Migration patterns in our model were congruent with human prostate cancer seeding topologies. Our findings support the view of metastatic prostate cancer as a systemic disease driven by waves of aggressive clones expanding their niche, infrequently overcoming constraints that otherwise keep them confined in the primary or metastatic site. Significance: Defining the kinetics of prostate cancer metastasis is critical for developing novel therapeutic strategies. This study uses CRISPR/Cas9-based barcoding technology to accurately define tumor clonal patterns and routes of migration in a novel somatically engineered mouse model (EvoCaP) that recapitulates human prostate cancer using an in-house developed analytical pipeline (EvoTraceR).

Functionalized Protein Binders in Developmental Biology

Developmental biology has greatly profited from genetic and reverse genetic approaches to indirectly studying protein function. More recently, nanobodies and other protein binders derived from different synthetic scaffolds have been used to directly dissect protein function. Protein binders have been fused to functional domains, such as to lead to protein degradation, relocalization, visualization, or posttranslational modification of the target protein upon binding. The use of such functionalized protein binders has allowed the study of the proteome during development in an unprecedented manner. In the coming years, the advent of the computational design of protein binders, together with further advances in scaffold engineering and synthetic biology, will fuel the development of novel protein binder-based technologies. Studying the proteome with increased precision will contribute to a better understanding of the immense molecular complexities hidden in each step along the way to generate form and function during development.

Molecular recording using DNA Typewriter

Recording molecular information to genomic DNA is a powerful means of investigating topics ranging from multicellular development to cancer evolution. With molecular recording based on genome editing, events such as cell divisions and signaling pathway activity drive specific alterations in a cell's DNA, marking the genome with information about a cell's history that can be read out after the fact. Although genome editing has been used for molecular recording, capturing the temporal relationships among recorded events in mammalian cells remains challenging. The DNA Typewriter system overcomes this limitation by leveraging prime editing to facilitate sequential insertions to an engineered genomic region. DNA Typewriter includes three distinct components: DNA Tape as the 'substrate' to which edits accrue in an ordered manner, the prime editor enzyme, and prime editing guide RNAs, which program insertional edits to DNA Tape. In this protocol, we describe general design considerations for DNA Typewriter, step-by-step instructions on how to perform recording experiments by using DNA Typewriter in HEK293T cells, and example scripts for analyzing DNA Typewriter data ( https://doi.org/10.6084/m9.figshare.22728758 ). This protocol covers two main applications of DNA Typewriter: recording sequential transfection events with programmed barcode insertions by using prime editing and recording lineage information during the expansion of a single cell to many. Compared with other methods that are compatible with mammalian cells, DNA Typewriter enables the recording of temporal information with higher recording capacities and can be completed within 4-6 weeks with basic expertise in molecular cloning, mammalian cell culturing and DNA sequencing data analysis.

Functional analysis of cell plasticity using single-cell technologies

Metazoan organisms are heterocellular systems composed of hundreds of different cell types, which arise from an isogenic genome through differentiation. Cellular 'plasticity' further enables cells to alter their fate in response to exogenous cues and is involved in a variety of processes, such as wound healing, infection, and cancer. Recent advances in cellular model systems, high-dimensional single-cell technologies, and lineage tracing have sparked a renaissance in plasticity research. Here, we discuss the definition of cell plasticity, evaluate state-of-the-art model systems and techniques to study cell-fate dynamics, and explore the application of single-cell technologies to obtain functional insights into cell plasticity in healthy and diseased tissues. The integration of advanced biomimetic model systems, single-cell technologies, and high-throughput perturbation studies is enabling a new era of research into non-genetic plasticity in metazoan systems.

Single-cell sequencing to multi-omics: technologies and applications

Cells, as the fundamental units of life, contain multidimensional spatiotemporal information. Single-cell RNA sequencing (scRNA-seq) is revolutionizing biomedical science by analyzing cellular state and intercellular heterogeneity. Undoubtedly, single-cell transcriptomics has emerged as one of the most vibrant research fields today. With the optimization and innovation of single-cell sequencing technologies, the intricate multidimensional details concealed within cells are gradually unveiled. The combination of scRNA-seq and other multi-omics is at the forefront of the single-cell field. This involves simultaneously measuring various omics data within individual cells, expanding our understanding across a broader spectrum of dimensions. Single-cell multi-omics precisely captures the multidimensional aspects of single-cell transcriptomes, immune repertoire, spatial information, temporal information, epitopes, and other omics in diverse spatiotemporal contexts. In addition to depicting the cell atlas of normal or diseased tissues, it also provides a cornerstone for studying cell differentiation and development patterns, disease heterogeneity, drug resistance mechanisms, and treatment strategies. Herein, we review traditional single-cell sequencing technologies and outline the latest advancements in single-cell multi-omics. We summarize the current status and challenges of applying single-cell multi-omics technologies to biological research and clinical applications. Finally, we discuss the limitations and challenges of single-cell multi-omics and potential strategies to address them.

Inferring cell differentiation maps from lineage tracing data

During development, mulitpotent cells differentiate through a hierarchy of increasingly restricted progenitor cell types until they realize specialized cell types. A cell differentiation map describes this hierarchy, and inferring these maps is an active area of research spanning traditional single marker lineage studies to data-driven trajectory inference methods on single-cell RNA-seq data. Recent high-throughput lineage tracing technologies profile lineages and cell types at scale, but current methods to infer cell differentiation maps from these data rely on simple models with restrictive assumptions about the developmental process. We introduce a mathematical framework for cell differentiation maps based on the concept of potency, and develop an algorithm, Carta, that infers an optimal cell differentiation map from single-cell lineage tracing data. The key insight in Carta is to balance the trade-off between the complexity of the cell differentiation map and the number of unobserved cell type transitions on the lineage tree. We show that Carta more accurately infers cell differentiation maps on both simulated and real data compared to existing methods. In models of mammalian trunk development and mouse hematopoiesis, Carta identifies important features of development that are not revealed by other methods including convergent differentiation of specialized cell types, progenitor differentiation dynamics, and the refinement of routes of differentiation via new intermediate progenitors.

Tracking of lineage mass via quantitative phase imaging and confinement in low refractive index microwells

Measurements of cell lineages are central to a variety of fundamental biological questions, ranging from developmental to cancer biology. However, accurate lineage tracing requires nearly perfect cell tracking, which can be challenging due to cell motion during imaging. Here we demonstrate the integration of microfabrication, imaging, and image processing approaches to demonstrate a platform for cell lineage tracing. We use quantitative phase imaging (QPI), a label-free imaging approach that quantifies cell mass. This gives an additional parameter, cell mass, that can be used to improve tracking accuracy. We confine lineages within microwells fabricated to reduce cell adhesion to sidewalls made of a low refractive index polymer. This also allows the microwells themselves to serve as references for QPI, enabling measurement of cell mass even in confluent microwells. We demonstrate application of this approach to immortalized adherent and nonadherent cell lines as well as stimulated primary B cells cultured ex vivo. Overall, our approach enables lineage tracking, or measurement of lineage mass, in a platform that can be customized to varied cell types.

New frameworks for hematopoiesis derived from single-cell genomics

ABSTRACT

Recent advancements in single-cell genomics have enriched our understanding of hematopoiesis, providing intricate details about hematopoietic stem cell biology, differentiation, and lineage commitment. Technological advancements have highlighted extensive heterogeneity of cell populations and continuity of differentiation routes. Nevertheless, intermediate "attractor" states signify structure in stem and progenitor populations that link state transition dynamics to fate potential. We discuss how innovative model systems quantify lineage bias and how stress accelerates differentiation, thereby reducing fate plasticity compared with native hematopoiesis. We conclude by offering our perspective on the current model of hematopoiesis and discuss how a more precise understanding can translate to strategies that extend healthy hematopoiesis and prevent disease.