In vivo generation of DNA sequence diversity for cellular barcoding

Best Practices in Designing, Sequencing, and Identifying Random DNA Barcodes

Random DNA barcodes are a versatile tool for tracking cell lineages, with applications ranging from development to cancer to evolution. Here, we review and critically evaluate barcode designs as well as methods of barcode sequencing and initial processing of barcode data. We first demonstrate how various barcode design decisions affect data quality and propose a new design that balances all considerations that we are currently aware of. We then discuss various options for the preparation of barcode sequencing libraries, including inline indices and Unique Molecular Identifiers (UMIs). Finally, we test the performance of several established and new bioinformatic pipelines for the extraction of barcodes from raw sequencing reads and for error correction. We find that both alignment and regular expression-based approaches work well for barcode extraction, and that error-correction pipelines designed specifically for barcode data are superior to generic ones. Overall, this review will help researchers to approach their barcoding experiments in a deliberate and systematic way.

Connecting past and present: single-cell lineage tracing

Central to the core principle of cell theory, depicting cells’ history, state and fate is a fundamental goal in modern biology. By leveraging clonal analysis and single-cell RNA-seq technologies, single-cell lineage tracing provides new opportunities to interrogate both cell states and lineage histories. During the past few years, many strategies to achieve lineage tracing at single-cell resolution have been developed, and three of them (integration barcodes, polylox barcodes, and CRISPR barcodes) are noteworthy as they are amenable in experimentally tractable systems. Although the above strategies have been demonstrated in animal development and stem cell research, much care and effort are still required to implement these methods. Here we review the development of single-cell lineage tracing, major characteristics of the cell barcoding strategies, applications, as well as technical considerations and limitations, providing a guide to choose or improve the single-cell barcoding lineage tracing.

How Lineage Tracing Studies Can Unveil Tumor Heterogeneity in Breast Cancer

Lineage tracing studies have become a well-suited approach to reveal cellular hierarchies and tumor heterogeneity. Cellular heterogeneity, particularly in breast cancer, is still one of the main concerns regarding tumor progression and resistance to anti-cancer therapies. Here, we review the current knowledge about lineage tracing analyses that have contributed to an improved comprehension of the complexity of mammary tumors, highlighting how targeting different mammary epithelial cells and tracing their progeny can be useful to explore the intra- and inter-heterogeneity observed in breast cancer. In addition, we examine the strategies used to identify the cell of origin in different breast cancer subtypes and summarize how cellular plasticity plays an important role during tumorigenesis. Finally, we evaluate the clinical implications of lineage tracing studies and the challenges remaining to address tumor heterogeneity in breast cancer.

A DNA Inversion System in Eukaryotes Established via Laboratory Evolution

DNA inversion is a type of site-specific recombination system that plays an important role in the generation of genetic diversity and phenotypic adaptation by programmed rearrangements in bacteria. However, no such inversion system exhibiting a strong directionality bias has been identified or developed in eukaryotes yet. Here, using directed evolution of Rci recombinase, a tyrosine recombinase from a bacterial DNA inversion system, we identified a mutant Rci8 with a ratio of inversion/deletion up to ∼4320 in yeast. Based on Rci8 recombinase and sfxa101 sites, we have established a DNA inversion system in yeast and mammalian cells, enabling specificity for DNA inversions between inverted sites over deletions between directly repeated sites. Our results validated that the reversible DNA inversion system can act as an on/off transcriptional switch. Moreover, we demonstrate that the inversion system can also work on linear chromosomes. The eukaryotic DNA inversion system would provide a new tool for fields of genetic circuits, cellular barcoding, and synthetic genomes.

Unraveling Tumor Heterogeneity by Using DNA Barcoding Technologies to Develop Personalized Treatment Strategies in Advanced-Stage PDAC

Tumor heterogeneity is a hallmark of many solid tumors, including pancreatic ductal adenocarcinoma (PDAC), and an inherent consequence of the clonal evolution of cancers. As such, it is considered the underlying concept of many characteristics of the disease, including the ability to metastasize, adapt to different microenvironments, and to develop therapy resistance. Undoubtedly, the high mortality of PDAC can be attributed to a high extent to these properties. Despite its apparent importance, studying tumor heterogeneity has been a challenging task, mainly due to its complexity and lack of appropriate methods. However, in recent years molecular DNA barcoding has emerged as a sophisticated tool that allows mapping of individual cells or subpopulations in a cell pool to study heterogeneity and thus devise new personalized treatment strategies. In this review, we provide an overview of genetic and non-genetic inter- and intra-tumor heterogeneity and its impact on (personalized) treatment strategies in PDAC and address how DNA barcoding technologies work and can be applied to study this clinically highly relevant question.

Genetic Tools to Study Cardiovascular Biology

Progress in biomedical science is tightly associated with the improvement of methods and genetic tools to manipulate and analyze gene function in mice, the most widely used model organism in biomedical research. The joint effort of numerous individual laboratories and consortiums has contributed to the creation of a large genetic resource that enables scientists to image cells, probe signaling pathways activities, or modify a gene function in any desired cell type or time point, à la carte. However, as these tools significantly increase in number and become more sophisticated, it is more difficult to keep track of each tool's possibilities and understand their advantages and disadvantages. Knowing the best currently available genetic technology to answer a particular biological question is key to reach a higher standard in biomedical research. In this review, we list and discuss the main advantages and disadvantages of available mammalian genetic technology to analyze cardiovascular cell biology at higher cellular and molecular resolution. We start with the most simple and classical genetic approaches and end with the most advanced technology available to fluorescently label cells, conditionally target their genes, image their clonal expansion, and decode their lineages.

genBaRcode: a comprehensive R-package for genetic barcode analysis

MOTIVATION

Genetic barcodes have been established as an efficient method to trace clonal progeny of uniquely labeled cells by introducing artificial genetic sequences into the corresponding genomes. The assessment of those sequences relies on next generation sequencing and the subsequent analysis aiming to identify sequences of interest and correctly quantifying their abundance.

RESULTS

We developed the genBaRcode package as a toolbox combining the flexibility of digesting next generation sequencing reads with or without a sophisticated barcode structure, with a variety of error-correction approaches and the availability of several types of visualization routines. Furthermore, a graphical user interface was incorporated to allow also less experienced R users package-based analyses. Finally, the provided tool is intended to bridge the gap between generating and analyzing barcode data and thereby supporting the establishment of standardized and reproducible analysis strategies.

AVAILABILITY AND IMPLEMENTATION

The genBaRcode package is available at CRAN (https://cran.r-project.org/package=genBaRcode).

Deciphering Cell Fate Decision by Integrated Single-Cell Sequencing Analysis

Cellular differentiation is a common underlying feature of all multicellular organisms through which naïve cells progressively become fate restricted and develop into mature cells with specialized functions. A comprehensive understanding of the regulatory mechanisms of cell fate choices during de- velopment, regeneration, homeostasis, and disease is a central goal of mod- ern biology. Ongoing rapid advances in single-cell biology are enabling the exploration of cell fate specification at unprecedented resolution. Here, we review single-cell RNA sequencing and sequencing of other modalities as methods to elucidate the molecular underpinnings of lineage specification. We specifically discuss how the computational tools available to reconstruct lineage trajectories, quantify cell fate bias, and perform dimensionality re- duction for data visualization are providing new mechanistic insights into the process of cell fate decision. Studying cellular differentiation using single- cell genomic tools is paving the way for a detailed understanding of cellular behavior in health and disease.

Chromosomal barcoding of E. coli populations reveals lineage diversity dynamics at high resolution

Evolutionary dynamics in large asexual populations is strongly influenced by multiple competing beneficial lineages, most of which segregate at very low frequencies. However, technical barriers to tracking a large number of these rare lineages in bacterial populations have so far prevented a detailed elucidation of evolutionary dynamics. Here, we overcome this hurdle by developing a chromosomal-barcoding technique that allows simultaneous tracking of approximately 450,000 distinct lineages in Escherichia coli, which we use to test the effect of sub-inhibitory concentrations of common antibiotics on the evolutionary dynamics of low-frequency lineages. We find that populations lose lineage diversity at distinct rates that correspond to their antibiotic regimen. We also determine that some lineages have similar fates across independent experiments. By analysing the trajectory dynamics, we attribute the reproducible fates of these lineages to the presence of pre-existing beneficial mutations, and we demonstrate how the relative contribution of pre-existing and de novo mutations varies across drug regimens. Finally, we reproduce the observed lineage dynamics by simulations. Altogether, our results provide a valuable methodology for studying bacterial evolution as well as insights into evolution under sub-inhibitory antibiotic levels.

Recording development with single cell dynamic lineage tracing

Every animal grows from a single fertilized egg into an intricate network of cell types and organ systems. This process is captured in a lineage tree: a diagram of every cell's ancestry back to the founding zygote. Biologists have long sought to trace this cell lineage tree in individual organisms and have developed a variety of technologies to map the progeny of specific cells. However, there are billions to trillions of cells in complex organisms, and conventional approaches can only map a limited number of clonal populations per experiment. A new generation of tools that use molecular recording methods integrated with single cell profiling technologies may provide a solution. Here, we summarize recent breakthroughs in these technologies, outline experimental and computational challenges, and discuss biological questions that can be addressed using single cell dynamic lineage tracing.

DNA sequencing in high-throughput neuroanatomy

Mapping brain connectivity at single cell resolution is critical for understanding brain structure. For decades, such mapping has been principally approached with microscopy techniques, aiming to visualize neurons and their connections. However, these techniques are often very labor intensive and do not scale well to the complexity of mammalian brains. We recently leveraged the speed and parallelization of DNA sequencing to map the projections of thousands of single neurons in single experiments, and to map cortical mesoscale connectivity in single mice. Here, I review the state of sequencing-based neuroanatomy, and discuss future directions in synaptic connectivity mapping and comparative connectomics.

Using Cre-recombinase-driven Polylox barcoding for in vivo fate mapping in mice

Fate mapping is a powerful genetic tool for linking stem or progenitor cells with their progeny, and hence for defining cell lineages in vivo. The resolution of fate mapping depends on the numbers of distinct markers that are introduced in the beginning into stem or progenitor cells; ideally, numbers should be sufficiently large to allow the tracing of output from individual cells. Highly diverse genetic barcodes can serve this purpose. We recently developed an endogenous genetic barcoding system, termed Polylox. In Polylox, random DNA recombination can be induced by transient activity of Cre recombinase in a 2.1-kb-long artificial recombination substrate that has been introduced into a defined locus in mice (Rosa26^Polylox reporter mice). Here, we provide a step-by-step protocol for the use of Polylox, including barcode induction and estimation of induction efficiency, barcode retrieval with single-molecule real-time (SMRT) DNA sequencing followed by computational barcode identification, and the calculation of barcode-generation probabilities, which is key for estimations of single-cell labeling for a given number of stem cells. Thus, Polylox barcoding enables high-resolution fate mapping in essentially all tissues in mice for which inducible Cre driver lines are available. Alternative methods include ex vivo cell barcoding, inducible transposon insertion and CRISPR-Cas9-based barcoding; Polylox currently allows combining non-invasive and cell-type-specific labeling with high label diversity. The execution time of this protocol is ~2-3 weeks for experimental data generation and typically <2 d for computational Polylox decoding and downstream analysis.

Cellular barcoding: lineage tracing, screening and beyond

Cellular barcoding is a technique in which individual cells are labeled with unique nucleic acid sequences, termed barcodes, so that they can be tracked through space and time. Cellular barcoding can be used to track millions of cells in parallel, and thus is an efficient approach for investigating heterogeneous populations of cells. Over the past 25 years, cellular barcoding has been used for fate mapping, lineage tracing and high-throughput screening, and has led to important insights into developmental biology and gene function. Driven by plummeting sequencing costs and the power of synthetic biology, barcoding is now expanding beyond traditional applications and into diverse fields such as neuroanatomy and the recording of cellular activity. In this review, we discuss the fundamental principles of cellular barcoding, including the underlying mathematics, and its applications in both new and established fields.

Developmental barcoding of whole mouse via homing CRISPR

In vivo barcoding using nuclease-induced mutations is a powerful approach for recording biological information, including developmental lineages; however, its application in mammalian systems has been limited. We present in vivo barcoding in the mouse with multiple homing guide RNAs that each generate hundreds of mutant alleles and combine to produce an exponential diversity of barcodes. Activation upon conception and continued mutagenesis through gestation resulted in developmentally barcoded mice wherein information is recorded in lineage-specific mutations. We used these recordings for reliable post hoc reconstruction of the earliest lineages and investigation of axis development in the brain. Our results provide an enabling and versatile platform for in vivo barcoding and lineage tracing in a mammalian model system.

Feasibility of 3D Reconstruction of Neural Morphology Using Expansion Microscopy and Barcode-Guided Agglomeration

We here introduce and study the properties, via computer simulation, of a candidate automated approach to algorithmic reconstruction of dense neural morphology, based on simulated data of the kind that would be obtained via two emerging molecular technologies-expansion microscopy (ExM) and in-situ molecular barcoding. We utilize a convolutional neural network to detect neuronal boundaries from protein-tagged plasma membrane images obtained via ExM, as well as a subsequent supervoxel-merging pipeline guided by optical readout of information-rich, cell-specific nucleic acid barcodes. We attempt to use conservative imaging and labeling parameters, with the goal of establishing a baseline case that points to the potential feasibility of optical circuit reconstruction, leaving open the possibility of higher-performance labeling technologies and algorithms. We find that, even with these conservative assumptions, an all-optical approach to dense neural morphology reconstruction may be possible via the proposed algorithmic framework. Future work should explore both the design-space of chemical labels and barcodes, as well as algorithms, to ultimately enable routine, high-performance optical circuit reconstruction.

Using high-throughput barcode sequencing to efficiently map connectomes

The function of a neural circuit is determined by the details of its synaptic connections. At present, the only available method for determining a neural wiring diagram with single synapse precision-a 'connectome'-is based on imaging methods that are slow, labor-intensive and expensive. Here, we present SYNseq, a method for converting the connectome into a form that can exploit the speed and low cost of modern high-throughput DNA sequencing. In SYNseq, each neuron is labeled with a unique random nucleotide sequence-an RNA 'barcode'-which is targeted to the synapse using engineered proteins. Barcodes in pre- and postsynaptic neurons are then associated through protein-protein crosslinking across the synapse, extracted from the tissue, and joined into a form suitable for sequencing. Although our failure to develop an efficient barcode joining scheme precludes the widespread application of this approach, we expect that with further development SYNseq will enable tracing of complex circuits at high speed and low cost.

Limitations and challenges of genetic barcode quantification

Genetic barcodes are increasingly used to track individual cells and to quantitatively assess their clonal contributions over time. Although barcode quantification relies entirely on counting sequencing reads, detailed studies about the method’s accuracy are still limited. We report on a systematic investigation of the relation between barcode abundance and resulting read counts after amplification and sequencing using cell-mixtures that contain barcodes with known frequencies (“miniBulks”). We evaluated the influence of protocol modifications to identify potential sources of error and elucidate possible limitations of the quantification approach. Based on these findings we designed an advanced barcode construct (BC32) to improved barcode calling and quantification, and to ensure a sensitive detection of even highly diluted barcodes. Our results emphasize the importance of using curated barcode libraries to obtain interpretable quantitative data and underline the need for rigorous analyses of any utilized barcode library in terms of reliability and reproducibility.

Rapidly evolving homing CRISPR barcodes

We present an approach for engineering evolving DNA barcodes in living cells. A homing guide RNA (hgRNA) scaffold directs the Cas9-hgRNA complex to the DNA locus of the hgRNA itself. We show that this homing CRISPR-Cas9 system acts as an expressed genetic barcode that diversifies its sequence and that the rate of diversification can be controlled in cultured cells. We further evaluate these barcodes in cell populations and show that they can be used to record lineage history and that the barcode RNA can be amplified in situ, a prerequisite for in situ sequencing. This integrated approach will have wide-ranging applications, such as in deep lineage tracing, cellular barcoding, molecular recording, dissecting cancer biology, and connectome mapping.

Site-specific recombinatorics: in situ cellular barcoding with the Cre Lox system

BACKGROUND

Cellular barcoding is a recently developed biotechnology tool that enables the familial identification of progeny of individual cells in vivo. In immunology, it has been used to track the burst-sizes of multiple distinct responding T cells over several adaptive immune responses. In the study of hematopoiesis, it revealed fate heterogeneity amongst phenotypically identical multipotent cells. Most existing approaches rely on ex vivo viral transduction of cells with barcodes followed by adoptive transfer into an animal, which works well for some systems, but precludes barcoding cells in their native environment such as those inside solid tissues.

RESULTS

With a view to overcoming this limitation, we propose a new design for a genetic barcoding construct based on the Cre Lox system that induces randomly created stable barcodes in cells in situ by exploiting inherent sequence distance constraints during site-specific recombination. We identify the cassette whose provably maximal code diversity is several orders of magnitude higher than what is attainable with previously considered Cre Lox barcoding approaches, exceeding the number of lymphocytes or hematopoietic progenitor cells in mice.

CONCLUSIONS

Its high diversity and in situ applicability, make the proposed Cre Lox based tagging system suitable for whole tissue or even whole animal barcoding. Moreover, it can be built using established technology.

Reproducibility of Illumina platform deep sequencing errors allows accurate determination of DNA barcodes in cells

Background

Next generation sequencing (NGS) of amplified DNA is a powerful tool to describe genetic heterogeneity within cell populations that can both be used to investigate the clonal structure of cell populations and to perform genetic lineage tracing. For applications in which both abundant and rare sequences are biologically relevant, the relatively high error rate of NGS techniques complicates data analysis, as it is difficult to distinguish rare true sequences from spurious sequences that are generated by PCR or sequencing errors. This issue, for instance, applies to cellular barcoding strategies that aim to follow the amount and type of offspring of single cells, by supplying these with unique heritable DNA tags.

Results

Here, we use genetic barcoding data from the Illumina HiSeq platform to show that straightforward read threshold-based filtering of data is typically insufficient to filter out spurious barcodes. Importantly, we demonstrate that specific sequencing errors occur at an approximately constant rate across different samples that are sequenced in parallel. We exploit this observation by developing a novel approach to filter out spurious sequences.

Conclusions

Application of our new method demonstrates its value in the identification of true sequences amongst spurious sequences in biological data sets.

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-016-0999-4) contains supplementary material, which is available to authorized users.

Clonal Analysis of Cells with Cellular Barcoding: When Numbers and Sizes Matter

Cellular barcoding is a recently rediscovered tool to trace the clonal output of individual cells with genetically distinct and heritable DNA sequences. Each year a few dozens of papers are published using the cellular barcoding technique. Those publications largely focus on mutually related issues, namely: counting cells capable of clonal proliferation and expansion, monitoring clonal dynamics in time, tracing the origin of differentiated cells, characterizing the differentiation potential of stem cells and similar topics. Apart from their biological content, claims and conclusions, these studies show remarkable diversity in technical aspects of the barcoding method and sometimes in major conclusions. Although a diversity of approaches is quite usual in data analysis, deviant handling of barcode data might directly affect experimental results and their biological interpretation. Here, we will describe typical challenges and caveats in cellular barcoding publications available so far.

Puzzle Imaging: Using Large-Scale Dimensionality Reduction Algorithms for Localization

Current high-resolution imaging techniques require an intact sample that preserves spatial relationships. We here present a novel approach, "puzzle imaging," that allows imaging a spatially scrambled sample. This technique takes many spatially disordered samples, and then pieces them back together using local properties embedded within the sample. We show that puzzle imaging can efficiently produce high-resolution images using dimensionality reduction algorithms. We demonstrate the theoretical capabilities of puzzle imaging in three biological scenarios, showing that (1) relatively precise 3-dimensional brain imaging is possible; (2) the physical structure of a neural network can often be recovered based only on the neural connectivity matrix; and (3) a chemical map could be reproduced using bacteria with chemosensitive DNA and conjugative transfer. The ability to reconstruct scrambled images promises to enable imaging based on DNA sequencing of homogenized tissue samples.

An overhang-based DNA block shuffling method for creating a customized random library

We present an overhang-based DNA block shuffling method to create a customized random DNA library with flexible sequence design and length. Our method enables the efficient and seamless assembly of short DNA blocks with dinucleotide overhangs through a simple ligation process. Next generation sequencing analysis of the assembled DNA library revealed that ligation was accurate, directional and unbiased. This straightforward DNA assembly method should fulfill the versatile needs of both in vivo and in vitro functional screening of random peptides and RNA created with a desired amino acid and nucleotide composition, as well as making highly repetitive gene constructs that are difficult to synthesize de novo.

DNA Barcoding on Bacteria: A Review

Bacteria are omnipotent and they can be found everywhere. The study of bacterial pathogens has been happening from olden days to prevent epidemics, food spoilage, losses in agricultural production, and loss of lives. Modern techniques in DNA based species identification are considered. So, there is a need to acquire simple and quick identification technique. Hence, this review article covers the efficacy of DNA barcoding of bacteria. Routine DNA barcoding involves the production of PCR amplicons from particular regions to sequence them and these sequence data are used to identify or “barcode” that organism to make a distinction from other species.