Synthetic recording and in situ readout of lineage information in single cells

Do plants have a segregated germline?

For the last 100 years, it has been uncontroversial to state that the plant germline is set aside late in development, but there is surprisingly little evidence to support this view. In contrast, much evolutionary theory and several recent empirical studies seem to suggest the opposite-that the germlines of some and perhaps most plants may be set aside early in development. But is this really the case? How much does it matter? How can we reconcile the new evidence with existing knowledge of plant development? And is there a way to reliably establish the timing of germline segregation in both model and nonmodel plants? Answering these questions is vital to understanding one of the most fundamental aspects of plant development and evolution.

Single-Cell Transcriptomics Meets Lineage Tracing

Reconstructing lineage relationships between cells within a tissue or organism is a long-standing aim in biology. Traditionally, lineage tracing has been achieved through the (genetic) labeling of a cell followed by the tracking of its offspring. Currently, lineage trajectories can also be predicted using single-cell transcriptomics. Although single-cell transcriptomics provides detailed phenotypic information, the predicted lineage trajectories do not necessarily reflect genetic relationships. Recently, techniques have been developed that unite these strategies. In this Review, we discuss transcriptome-based lineage trajectory prediction algorithms, single-cell genetic lineage tracing, and the promising combination of these techniques for stem cell and cancer research.

Cell type atlas and lineage tree of a whole complex animal by single-cell transcriptomics

Flatworms of the species Schmidtea mediterranea are immortal-adult animals contain a large pool of pluripotent stem cells that continuously differentiate into all adult cell types. Therefore, single-cell transcriptome profiling of adult animals should reveal mature and progenitor cells. By combining perturbation experiments, gene expression analysis, a computational method that predicts future cell states from transcriptional changes, and a lineage reconstruction method, we placed all major cell types onto a single lineage tree that connects all cells to a single stem cell compartment. We characterized gene expression changes during differentiation and discovered cell types important for regeneration. Our results demonstrate the importance of single-cell transcriptome analysis for mapping and reconstructing fundamental processes of developmental and regenerative biology at high resolution.

Using single-cell genomics to understand developmental processes and cell fate decisions

High-throughput -omics techniques have revolutionised biology, allowing for thorough and unbiased characterisation of the molecular states of biological systems. However, cellular decision-making is inherently a unicellular process to which "bulk" -omics techniques are poorly suited, as they capture ensemble averages of cell states. Recently developed single-cell methods bridge this gap, allowing high-throughput molecular surveys of individual cells. In this review, we cover core concepts of analysis of single-cell gene expression data and highlight areas of developmental biology where single-cell techniques have made important contributions. These include understanding of cell-to-cell heterogeneity, the tracing of differentiation pathways, quantification of gene expression from specific alleles, and the future directions of cell lineage tracing and spatial gene expression analysis.

Rewritable multi-event analog recording in bacterial and mammalian cells

We present two CRISPR-mediated analog multi-event recording apparatus (CAMERA) systems that use base editors and Cas9 nucleases to record cellular events in bacteria and mammalian cells. The devices record signal amplitude or duration as changes in the ratio of mutually exclusive DNA sequences (CAMERA 1) or as single-base modifications (CAMERA 2). We achieved recording of multiple stimuli in bacteria or mammalian cells, including exposure to antibiotics, nutrients, viruses, light, and changes in Wnt signaling. When recording to multicopy plasmids, reliable readout requires as few as 10 to 100 cells. The order of stimuli can be recorded through an overlapping guide RNA design, and memories can be erased and re-recorded over multiple cycles. CAMERA systems serve as "cell data recorders" that write a history of endogenous or exogenous signaling events into permanent DNA sequence modifications in living cells.

Simultaneous lineage tracing and cell-type identification using CRISPR-Cas9-induced genetic scars

A key goal of developmental biology is to understand how a single cell transforms into a full-grown organism comprising many different cell types. Single-cell RNA-sequencing (scRNA-seq) is commonly used to identify cell types in a tissue or organ1. However, organizing the resulting taxonomy of cell types into lineage trees to understand developmental origin of cells remains challenging. Here we present LINNAEUS (LINeage tracing by Nuclease-Activated Editing of Ubiquitous Sequences)—a strategy for simultaneous lineage tracing and transcriptome profiling in thousands of single cells. By combining scRNA-seq with computational analysis of lineage barcodes, generated by genome editing of transgenic reporter genes, we reconstruct developmental lineage trees in zebrafish larvae, and in heart, liver, pancreas and telencephalon of adult fish. LINNAEUS provides a systematic approach for tracing the origin of novel cell types, or known cell types under different conditions.

Harnessing "A Billion Years of Experimentation": The Ongoing Exploration and Exploitation of CRISPR-Cas Immune Systems

The famed physicist-turned-biologist, Max Delbrück, once remarked that, for physicists, "the field of bacterial viruses is a fine playground for serious children who ask ambitious questions." Early discoveries in that playground helped establish molecular genetics, and half a century later, biologists delving into the same field have ushered in the era of precision genome engineering. The focus has of course shifted-from bacterial viruses and their mechanisms of infection to the bacterial hosts and their mechanisms of immunity-but it is the very same evolutionary arms race that continues to awe and inspire researchers worldwide. In this review, we explore the remarkable diversity of CRISPR-Cas adaptive immune systems, describe the molecular components that mediate nucleic acid targeting, and outline the use of these RNA-guided machines for biotechnology applications. CRISPR-Cas research has yielded far more than just Cas9-based genome-editing tools, and the wide-reaching, innovative impacts of this fascinating biological playground are sure to be felt for years to come.

Whole-organism clone tracing using single-cell sequencing

Embryonic development is a crucial period in the life of a multicellular organism, during which limited sets of embryonic progenitors produce all cells in the adult body. Determining which fate these progenitors acquire in adult tissues requires the simultaneous measurement of clonal history and cell identity at single-cell resolution, which has been a major challenge. Clonal history has traditionally been investigated by microscopically tracking cells during development, monitoring the heritable expression of genetically encoded fluorescent proteins and, more recently, using next-generation sequencing technologies that exploit somatic mutations, microsatellite instability, transposon tagging, viral barcoding, CRISPR-Cas9 genome editing and Cre-loxP recombination. Single-cell transcriptomics provides a powerful platform for unbiased cell-type classification. Here we present ScarTrace, a single-cell sequencing strategy that enables the simultaneous quantification of clonal history and cell type for thousands of cells obtained from different organs of the adult zebrafish. Using ScarTrace, we show that a small set of multipotent embryonic progenitors generate all haematopoietic cells in the kidney marrow, and that many progenitors produce specific cell types in the eyes and brain. In addition, we study when embryonic progenitors commit to the left or right eye. ScarTrace reveals that epidermal and mesenchymal cells in the caudal fin arise from the same progenitors, and that osteoblast-restricted precursors can produce mesenchymal cells during regeneration. Furthermore, we identify resident immune cells in the fin with a distinct clonal origin from other blood cell types. We envision that similar approaches will have major applications in other experimental systems, in which the matching of embryonic clonal origin to adult cell type will ultimately allow reconstruction of how the adult body is built from a single cell.

Simultaneous single-cell profiling of lineages and cell types in the vertebrate brain

The lineage relationships among the hundreds of cell types generated during development are difficult to reconstruct. A recent method, GESTALT, used CRISPR-Cas9 barcode editing for large-scale lineage tracing, but was restricted to early development and did not identify cell types. Here we present scGESTALT, which combines the lineage recording capabilities of GESTALT with cell-type identification by single-cell RNA sequencing. The method relies on an inducible system that enables barcodes to be edited at multiple time points, capturing lineage information from later stages of development. Sequencing of ~60,000 transcriptomes from the juvenile zebrafish brain identifies >100 cell types and marker genes. Using these data, we generate lineage trees with hundreds of branches that help uncover restrictions at the level of cell types, brain regions, and gene expression cascades during differentiation. scGESTALT can be applied to other multicellular organisms to simultaneously characterize molecular identities and lineage histories of thousands of cells during development and disease.

The cis-regulatory dynamics of embryonic development at single-cell resolution

Understanding how gene regulatory networks control the progressive restriction of cell fates is a long-standing challenge. Recent advances in measuring single cell gene expression are providing new insights into lineage commitment. However, the regulatory events underlying these changes remain elusive. Here we investigate the dynamics of chromatin regulatory landscapes during embryogenesis at single cell resolution. Using single cell combinatorial indexing assay for transposase accessible chromatin (sci-ATAC-seq)1, we profiled chromatin accessibility in over 20,000 single nuclei from fixed Drosophila embryos spanning three landmark embryonic stages: 2-4 hours (hrs) after egg laying (predominantly stage 5 blastoderm nuclei), when each embryo comprises ~6,000 multipotent cells; 6-8hrs (predominantly stage 10-11), to capture a midpoint in embryonic development when major lineages in the mesoderm and ectoderm are specified; and 10-12hrs (predominantly stage 13), when each of the embryo’s >20,000 cells are undergoing terminal differentiation. Our results reveal spatial heterogeneity in the usage of the regulatory genome prior to gastrulation, a feature that aligns with future cell fate, and nuclei can be temporally ordered along developmental trajectories. During mid-embryogenesis, tissue granularity emerges such that individual cell types can be inferred by their chromatin accessibility, while maintaining a signature of their germ layer of origin. The data reveal overlapping usage of regulatory elements between cells of the endoderm and non-myogenic mesoderm, suggesting a common developmental program reminiscent of the mesendoderm lineage in other species2–4. Altogether, we identify over 30,000 distal regulatory elements exhibiting tissue-specific accessibility. We validated the germ layer specificity of a subset of these predicted enhancers in transgenic embryos, achieving 90% accuracy. Overall, our results demonstrate the power of shotgun single cell profiling of embryos to resolve dynamic changes in the chromatin landscape during development, and to uncover the cis-regulatory programs of metazoan germ layers and cell types.

Learning from Noise: How Observing Stochasticity May Aid Microbiology

For many decades, the wedding of quantitative data with mathematical modeling has been fruitful, leading to important biological insights. Here, we review some of the ongoing efforts to gain insights into problems in microbiology - and, in particular, cell-cycle progression and its regulation - through observation and quantitative analysis of the natural fluctuations in the system. We first illustrate this idea by reviewing a classic example in microbiology - the Luria-Delbrück experiment - and discussing how, in that case, useful information was obtained by looking beyond the mean outcome of the experiment, but instead paying attention to the variability between replicates of the experiment. We then switch gears to the contemporary problem of cell cycle progression and discuss in more detail how insights into cell size regulation and, when relevant, coupling between the cell cycle and the circadian clock, can be gained by studying the natural fluctuations in the system and their statistical properties. We end with a more general discussion of how (in this context) the correct level of phenomenological model should be chosen, as well as some of the pitfalls associated with this type of analysis. Throughout this review the emphasis is not on providing details of the experimental setups or technical details of the models used, but rather, in fleshing out the conceptual structure of this particular approach to the problem. For this reason, we choose to illustrate the framework on a rather broad range of problems, and on organisms from all domains of life, to emphasize the commonality of the ideas and analysis used (as well as their differences).

Asymmetricity Between Sister Cells of Pluripotent Stem Cells at the Onset of Differentiation

Various somatic stem cells divide asymmetrically; however, it is not known whether embryonic stem cells (ESCs) divide symmetrically or asymmetrically, not only while maintaining an undifferentiated state but also at the onset of differentiation. In this study, we observed single ESCs using time-lapse imaging and compared sister cell pairs derived from the same mother cell in either the maintenance or differentiation medium. Mouse ESCs were cultured on E-cadherin-coated glass-based dishes, which allowed us to trace single cells. The undifferentiated cell state was detected by green fluorescent protein (GFP) expression driven by the Nanog promoter, which is active only in undifferentiated cells. Cell population analysis using flow cytometry showed that the peak width indicating distribution of GFP expression broadened when cells were transferred to the differentiation medium compared to when they were in the maintenance medium. This finding suggested that the population of ESCs became more heterogeneous at the onset of differentiation. Using single-cell analysis by time-lapse imaging, we found that although the total survival ratio decreased by changing to differentiation medium, the one-live-one-dead ratio of sister cell pairs was smaller compared with randomly chosen non-sister cell pairs, defined as an unsynchronized cell pair control, in both media. This result suggested that sister cell pairs were more positively synchronized with each other compared to non-sister cell pairs. The differences in interdivision time (the time interval between mother cell division and the subsequent cell division) between sister cells was smaller than that between non-sister cell pairs in both media, suggesting that sister cells divided synchronously. Although the difference in Nanog-GFP intensity between sister cells was smaller than that between non-sister cells in the maintenance medium, it was the same in differentiation medium, suggesting asymmetrical Nanog-GFP intensity. These data suggested that ESCs may divide asymmetrically at the onset of differentiation resulting in heterogeneity.

Single-Cell Computational Strategies for Lineage Reconstruction in Tissue Systems

Function at the organ level manifests itself from a heterogeneous collection of cell types. Cellular heterogeneity emerges from developmental processes by which multipotent progenitor cells make fate decisions and transition to specific cell types through intermediate cell states. Although genetic experimental strategies such as lineage tracing have provided insights into cell lineages, recent developments in single-cell technologies have greatly increased our ability to interrogate distinct cell types, as well as transitional cell states in tissue systems. From single-cell data that describe these intermediate cell states, computational tools have been developed to reconstruct cell-state transition trajectories that model cell developmental processes. These algorithms, although powerful, are still in their infancy, and attention must be paid to their strengths and weaknesses when they are used. Here, we review some of these tools, also referred to as pseudotemporal ordering algorithms, and their associated assumptions and caveats. We hope to provide a rational and generalizable workflow for single-cell trajectory analysis that is intuitive for experimental biologists.

Tracing single-cell histories

Origins of mutations in single cells during human brain development and aging are revealed

The promise of spatial transcriptomics for neuroscience in the era of molecular cell typing

The stereotyped spatial architecture of the brain is both beautiful and fundamentally related to its function, extending from gross morphology to individual neuron types, where soma position, dendritic architecture, and axonal projections determine their roles in functional circuitry. Our understanding of the cell types that make up the brain is rapidly accelerating, driven in particular by recent advances in single-cell transcriptomics. However, understanding brain function, development, and disease will require linking molecular cell types to morphological, physiological, and behavioral correlates. Emerging spatially resolved transcriptomic methods promise to fill this gap by localizing molecularly defined cell types in tissues, with simultaneous detection of morphology, activity, or connectivity. Here, we review the requirements for spatial transcriptomic methods toward these goals, consider the challenges ahead, and describe promising applications.

Single-cell epigenomics: Recording the past and predicting the future

Single-cell multi-omics has recently emerged as a powerful technology by which different layers of genomic output-and hence cell identity and function-can be recorded simultaneously. Integrating various components of the epigenome into multi-omics measurements allows for studying cellular heterogeneity at different time scales and for discovering new layers of molecular connectivity between the genome and its functional output. Measurements that are increasingly available range from those that identify transcription factor occupancy and initiation of transcription to long-lasting and heritable epigenetic marks such as DNA methylation. Together with techniques in which cell lineage is recorded, this multilayered information will provide insights into a cell's past history and its future potential. This will allow new levels of understanding of cell fate decisions, identity, and function in normal development, physiology, and disease.

An evolutionary perspective on field cancerization

Tumorigenesis begins long before the growth of a clinically detectable lesion and, indeed, even before any of the usual morphological correlates of pre-malignancy are recognizable. Field cancerization, which is the replacement of the normal cell population by a cancer-primed cell population that may show no morphological change, is now recognized to underlie the development of many types of cancer, including the common carcinomas of the lung, colon, skin, prostate and bladder. Field cancerization is the consequence of the evolution of somatic cells in the body that results in cells that carry some but not all phenotypes required for malignancy. Here, we review the evidence of field cancerization across organs and examine the biological mechanisms that drive the evolutionary process that results in field creation. We discuss the clinical implications, principally, how measurements of the cancerized field could improve cancer risk prediction in patients with pre-malignant disease.

Leveraging and coping with uncertainty in the response of individual cells to therapy

Non-genetic heterogeneity fluctuates over diverse timescales, ranging from hours to months. In specific cases, such variability can profoundly impact the response of cell populations to therapy, in both antibiotic treatments in bacteria and chemotherapy in cancer. It is thus critical to understand the way phenotypes fluctuate in cell populations and the molecular sources of phenotypic diversity. Technical and analytical breakthroughs in the study of single cells have leveraged cellular heterogeneity to gain phenomenological and mechanistic insights of the phenotypic transitions that occur within isogenic cell populations over time. Such an understanding moves forward our ability to design therapeutic strategies with the explicit goal of preventing and controlling the selective expansion and stabilization of drug-tolerant phenotypic states.

Multiplex recording of cellular events over time on CRISPR biological tape

Although dynamics underlie many biological processes, our ability to robustly and accurately profile time-varying biological signals and regulatory programs remains limited. Here we describe a framework for storing temporal biological information directly in the genomes of a cell population. We developed a "biological tape recorder" in which biological signals trigger intracellular DNA production that is then recorded by the CRISPR-Cas adaptation system. This approach enables stable recording over multiple days and accurate reconstruction of temporal and lineage information by sequencing CRISPR arrays. We further demonstrate a multiplexing strategy to simultaneously record the temporal availability of three metabolites (copper, trehalose, and fucose) in the environment of a cell population over time. This work enables the temporal measurement of dynamic cellular states and environmental changes and suggests new applications for chronicling biological events on a large scale.

Methods for lineage tracing on the organism-wide level

Determining the lineage origin of cell types is a major goal in developmental biology. Furthermore, lineage tracing is a powerful approach for understanding the origin of developmental defects as well as the origin of diseases such as cancer. There is now a variety of complementary approaches for identifying lineage relationships, ranging from direct observation of cell divisions by light microscopy to genetic labeling of cells using inducible recombinases and fluorescent reporters. A recent development, and the main topic of this review article, is the use of high-throughput sequencing data for lineage analysis. This emerging approach holds the promise of increased multiplexing capacity, allowing lineage analysis of large cell numbers up to the organism-wide level combined with simultaneous transcription profiling by single cell RNA sequencing.

Profiling the transcriptome with RNA SPOTs

Single molecule FISH (smFISH) has been the gold standard in quantifying individual transcripts abundances. Here, we demonstrate the scaling up of smFISH to the transcriptome level by profiling of 10,212 different mRNAs from mouse fibroblast and embryonic stem cells. This methods, called RNA SPOTs (Sequential Probing of Targets), provides an accurate and low-cost alternative to sequencing in profiling transcriptomes.

Mapping Brain Activity onto Molecularly Defined Cells

The brain processes information and generates behavior by employing a wide array of different cell types. In this issue of Neuron, Wu et al. (2017) report a novel method that enables the efficient identification of molecularly defined cells that participate in a specific brain function.

CRISPR-Cas encoding of a digital movie into the genomes of a population of living bacteria

DNA is an excellent medium for archiving data. Recent efforts have illustrated the potential for information storage in DNA using synthesized oligonucleotides assembled in vitro. A relatively unexplored avenue of information storage in DNA is the ability to write information into the genome of a living cell by the addition of nucleotides over time. Using the Cas1-Cas2 integrase, the CRISPR-Cas microbial immune system stores the nucleotide content of invading viruses to confer adaptive immunity. When harnessed, this system has the potential to write arbitrary information into the genome. Here we use the CRISPR-Cas system to encode the pixel values of black and white images and a short movie into the genomes of a population of living bacteria. In doing so, we push the technical limits of this information storage system and optimize strategies to minimize those limitations. We also uncover underlying principles of the CRISPR-Cas adaptation system, including sequence determinants of spacer acquisition that are relevant for understanding both the basic biology of bacterial adaptation and its technological applications. This work demonstrates that this system can capture and stably store practical amounts of real data within the genomes of populations of living cells.

De Novo Gene Expression Reconstruction in Space

The biological function of a gene often depends on spatial context, and an atlas of transcriptional regulation could be instrumental in defining functional elements across the genome. Despite recent advances in single-cell RNA sequencing and in situ RNA imaging, fundamental barriers limit the speed, genome-wide coverage, and resolution of de novo transcriptome assembly in space. Here, I discuss potential next-generation approaches for the de novo assembly of the transcriptome in space, and propose more efficient methods of detecting long-range spatial variations in gene expression. Finally, I discuss future in situ sequencing chemistries for visualizing biological pathways and processes in tissues so that genomics technologies might be more easily applied to conditions of human health and disease.

Hysteresis Effects During the Phase Transition in Solutions of Temperature Sensitive Polymers

It is demonstrated, for the first time,that well-known phase transitions induced by changes in temperature in solutions of polymers containing both hydrophilic and hydrophobic functional groups could be followed by noticeable hysteresis effects. A<br />well-known phase transitions accompanied by a sharp change in fluid properties, in particular its optical density can be induced by many external influences, including temperature changes occurring in the solutions of polymers containing both<br />hydrophilic and hydrophobic functional groups. Since intensification subsequent hydrophobic interactions, leading to loss of solubility of the polymer molecules, resulting, in particular, a significant increase in the turbidity of the medium and are accompanied by a pronounced hysteresis phenomena. Hysteresis phenomena in the processes of molecular-scale play an important theoretical and practical interest in linkage with the development of advanced nano-level technology. In particular, the issue of the development of molecular "trigger" switches, and other analog electronic systems, implemented on submolecular level was actively discussed. In fact, under the same physical conditions of the environment of macromolecules system can be in two different states, which resolves the issue of programming such molecules. State of these polymers depends on their way of formation and thermodynamic variables. Observed effect could be utilized directly for information recording into the structure on the basis of stimulus-sensitive macromolecular chains. In fact, it is a first step towards creating memory of quasi-biological elements.

Disruptive non-disruptive applications of CRISPR/Cas9

The bacterial type II Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR)-CRISPR Associated (Cas) systems, and in particular Streptococcus pyogenes CRISPR-Cas9, have been broadly applied to edit the genome of bacterial and eukaryotic cells. Cas9, which is an RNA-guided programmable nuclease, is a powerful tool for disrupting protein-coding genes. Cas9 cleaves target sites to generate a double-strand break (DSB) that is repaired via an error-prone repair process, leading to insertion/deletion mutations and gene knockouts. However, Cas9 can also be used to modulate genome function without gene disruption, enabling base editing, transcriptional and epigenetic reprogramming, genome imaging, cellular barcoding, genetic recording, and genetic computation.

Quantitative Analysis of Synthetic Cell Lineage Tracing Using Nuclease Barcoding

Lineage tracing by the determination and mapping of progeny arising from single cells is an important approach enabling the elucidation of mechanisms underlying diverse biological processes ranging from development to disease. We developed a dynamic sequence-based barcode system for synthetic lineage tracing and have demonstrated its performance in C. elegans, a model organism whose lineage tree is well established. The strategy we use creates lineage trees based upon the introduction of synthetically controlled mutations into cells and the propagation of these mutations to daughter cells at each cell division. We analyzed this experimental proof of concept along with a corresponding simulation and analytical model to gain a deeper understanding of the coding capacity of the system. Our results provide specific bounds on the fidelity of lineage tracing using such approaches.

Modeling the process of human tumorigenesis

Modelling the genesis of human cancers is at a scientific turning point. Starting from primary sources of normal human cells, it is now possible to reproducibly generate several types of malignant cell populations. Powerful methods for clonally tracking and manipulating their appearance and progression in serially transplanted immunodeficient mice are also in place. These developments circumvent historic drawbacks inherent in analyses of cancers produced in model organisms, established human malignant cell lines, or highly heterogeneous patient samples. In this review, we survey the advantages, contributions and limitations of current de novo human tumorigenesis strategies and note several exciting prospects on the horizon.

A better understanding of the earliest stages of human cancer formation can enable future improvements in early detection, diagnosis and treatment. In this review, the authors summarize the methods enabling de novo tumorigenesis protocols to be applied to human cells and the insights derived from them to date, as well as the exciting and relevant technical developments anticipated to extend even further the utility of these strategies.

Shaping development by stochasticity and dynamics in gene regulation

Animal development is orchestrated by spatio-temporal gene expression programmes that drive precise lineage commitment, proliferation and migration events at the single-cell level, collectively leading to large-scale morphological change and functional specification in the whole organism. Efforts over decades have uncovered two 'seemingly contradictory' mechanisms in gene regulation governing these intricate processes: (i) stochasticity at individual gene regulatory steps in single cells and (ii) highly coordinated gene expression dynamics in the embryo. Here we discuss how these two layers of regulation arise from the molecular and the systems level, and how they might interplay to determine cell fate and to control the complex body plan. We also review recent technological advancements that enable quantitative analysis of gene regulation dynamics at single-cell, single-molecule resolution. These approaches outline next-generation experiments to decipher general principles bridging gaps between molecular dynamics in single cells and robust gene regulations in the embryo.

Accelerating Live Single-Cell Signalling Studies

The dynamics of signalling networks that couple environmental conditions with cellular behaviour can now be characterised in exquisite detail using live single-cell imaging experiments. Recent improvements in our abilities to introduce fluorescent sensors into cells, coupled with advances in pipelines for quantifying and extracting single-cell data, mean that high-throughput systematic analyses of signalling dynamics are becoming possible. In this review, we consider current technologies that are driving progress in the scale and range of such studies. Moreover, we discuss novel approaches that are allowing us to explore how pathways respond to changes in inputs and even predict the fate of a cell based upon its signalling history and state.

Multiplexed Dynamic Imaging of Genomic Loci by Combined CRISPR Imaging and DNA Sequential FISH

Visualization of chromosome dynamics allows the investigation of spatiotemporal chromatin organization and its role in gene regulation and other cellular processes. However, current approaches to label multiple genomic loci in live cells have a fundamental limitation in the number of loci that can be labeled and uniquely identified. Here we describe an approach we call “track first and identify later” for multiplexed visualization of chromosome dynamics by combining two techniques: CRISPR imaging and DNA sequential fluorescence in situ hybridization. Our approach first labels and tracks chromosomal loci in live cells with the CRISPR-Cas9 system, then barcodes those loci by DNA sequential fluorescence in situ hybridization in fixed cells and resolves their identities. We demonstrate our approach by tracking telomere dynamics, identifying 12 unique subtelomeric regions with variable detection efficiencies, and tracking back the telomere dynamics of respective chromosomes in mouse embryonic stem cells.

Building a lineage from single cells: genetic techniques for cell lineage tracking

Resolving lineage relationships between cells in an organism is a fundamental interest of developmental biology. Furthermore, investigating lineage can drive understanding of pathological states, including cancer, as well as understanding of developmental pathways that are amenable to manipulation by directed differentiation. Although lineage tracking through the injection of retroviral libraries has long been the state of the art, a recent explosion of methodological advances in exogenous labelling and single-cell sequencing have enabled lineage tracking at larger scales, in more detail, and in a wider range of species than was previously considered possible. In this Review, we discuss these techniques for cell lineage tracking, with attention both to those that trace lineage forwards from experimental labelling, and those that trace backwards across the life history of an organism.

From Reductionism to Holism: Toward a More Complete View of Development Through Genome Engineering

Paradigm shifts in science are often coupled to technological advances. New techniques offer new roads of discovery; but, more than this, they shape the way scientists approach questions. Developmental biology exemplifies this idea both in its past and present. The rise of molecular biology and genetics in the late twentieth century shifted the focus from the anatomical to the molecular, nudging the underlying philosophy from holism to reductionism. Developmental biology is currently experiencing yet another transformation triggered by '-omics' technology and propelled forward by CRISPR genome engineering (GE). Together, these technologies are helping to reawaken a holistic approach to development. Herein, we focus on CRISPR GE and its potential to reveal principles of development at the level of the genome, the epigenome, and the cell. Within each stage we illustrate how GE can move past pure reductionism and embrace holism, ultimately delivering a more complete view of development.

Microfluidics cell sample preparation for analysis: Advances in efficient cell enrichment and precise single cell capture

Single cell analysis has received increasing attention recently in both academia and clinics, and there is an urgent need for effective upstream cell sample preparation. Two extremely challenging tasks in cell sample preparation-high-efficiency cell enrichment and precise single cell capture-have now entered into an era full of exciting technological advances, which are mostly enabled by microfluidics. In this review, we summarize the category of technologies that provide new solutions and creative insights into the two tasks of cell manipulation, with a focus on the latest development in the recent five years by highlighting the representative works. By doing so, we aim both to outline the framework and to showcase example applications of each task. In most cases for cell enrichment, we take circulating tumor cells (CTCs) as the target cells because of their research and clinical importance in cancer. For single cell capture, we review related technologies for many kinds of target cells because the technologies are supposed to be more universal to all cells rather than CTCs. Most of the mentioned technologies can be used for both cell enrichment and precise single cell capture. Each technology has its own advantages and specific challenges, which provide opportunities for researchers in their own area. Overall, these technologies have shown great promise and now evolve into real clinical applications.