Determining Lineage Pathways from Cellular Barcoding Experiments

Stochastic journeys of cell progenies through compartments and the role of self-renewal, symmetric and asymmetric division

Division and differentiation events by which cell populations with specific functions are generated often take place as part of a developmental programme, which can be represented by a sequence of compartments. A compartment is the set of cells with common characteristics; sharing, for instance, a spatial location or a phenotype. Differentiation events are transitions from one compartment to the next. Cells may also die or divide. We consider three different types of division events: (i) where both daughter cells inherit the mother's phenotype (self-renewal), (ii) where only one of the daughters changes phenotype (asymmetric division), and (iii) where both daughters change phenotype (symmetric division). The self-renewal probability in each compartment determines whether the progeny of a single cell, moving through the sequence of compartments, is finite or grows without bound. We analyse the progeny stochastic dynamics with probability generating functions. In the case of self-renewal, by following one of the daughters after any division event, we may construct lifelines containing only one cell at any time. We analyse the number of divisions along such lines, and the compartment where lines terminate with a death event. Analysis and numerical simulations are applied to a five-compartment model of the gradual differentiation of hematopoietic stem cells and to a model of thymocyte development: from pre-double positive to single positive (SP) cells with a bifurcation to either SP4 or SP8 in the last compartment of the sequence.

Single-cell investigative genetics: Single-cell data produces genotype distributions concentrated at the true genotype across all mixture complexities

In the absence of a suspect the forensic aim is investigative, and the focus is one of discerning what genotypes best explain the evidence. In traditional systems, the list of candidate genotypes may become vast if the sample contains DNA from many donors or the information from a minor contributor is swamped by that of major contributors, leading to lower evidential value for a true donor's contribution and, as a result, possibly overlooked or inefficient investigative leads. Recent developments in single-cell analysis offer a way forward, by producing data capable of discriminating genotypes. This is accomplished by first clustering single-cell data by similarity without reference to a known genotype. With good clustering it is reasonable to assume that the scEPGs in a cluster are of a single contributor. With that assumption we determine the probability of a cluster's content given each possible genotype at each locus, which is then used to determine the posterior probability mass distribution for all genotypes by application of Bayes' rule. A decision criterion is then applied such that the sum of the ranked probabilities of all genotypes falling in the set is at least 1-α. This is the credible genotype set and is used to inform database search criteria. Within this work we demonstrate the salience of single-cell analysis by performance testing a set of 630 previously constructed admixtures containing up to 5 donors of balanced and unbalanced contributions. We use scEPGs that were generated by isolating single cells, employing a direct-to-PCR extraction treatment, amplifying STRs that are compliant with existing national databases and applying post-PCR treatments that elicit a detection limit of one DNA copy. We determined that, for these test data, 99.3% of the true genotypes are included in the 99.8% credible set, regardless of the number of donors that comprised the mixture. We also determined that the most probable genotype was the true genotype for 97% of the loci when the number of cells in a cluster was at least two. Since efficient investigative leads will be borne by posterior mass distributions that are narrow and concentrated at the true genotype, we report that, for this test set, 47,900 (86%) loci returned only one credible genotype and of these 47,551 (99%) were the true genotype. When determining the LR for true contributors, 91% of the clusters rendered LR>1018, showing the potential of single-cell data to positively affect investigative reporting.

Myelodysplasia after clonal hematopoiesis with APOBEC3-mediated CYBB inactivation in retroviral gene therapy for X-CGD

Stem cell gene therapy using the MFGS-gp91phox retroviral vector was performed on a 27-year-old patient with X-linked chronic granulomatous disease (X-CGD) in 2014. The patient's refractory infections were resolved, whereas the oxidase-positive neutrophils disappeared within 6 months. Thirty-two months after gene therapy, the patient developed myelodysplastic syndrome (MDS), and vector integration into the MECOM locus was identified in blast cells. The vector integration into MECOM was detectable in most myeloid cells at 12 months after gene therapy. However, the patient exhibited normal hematopoiesis until the onset of MDS, suggesting that MECOM transactivation contributed to clonal hematopoiesis, and the blast transformation likely arose after the acquisition of additional genetic lesions. In whole-genome sequencing, the biallelic loss of the WT1 tumor suppressor gene, which occurred immediately before tumorigenesis, was identified as a potential candidate genetic alteration. The provirus CYBB cDNA in the blasts contained 108 G-to-A mutations exclusively in the coding strand, suggesting the occurrence of APOBEC3-mediated hypermutations during the transduction of CD34-positive cells. A hypermutation-mediated loss of oxidase activity may have facilitated the survival and proliferation of the clone with MECOM transactivation. Our data provide valuable insights into the complex mechanisms underlying the development of leukemia in X-CGD gene therapy.

Why are cell populations maintained via multiple compartments?

We consider the maintenance of 'product' cell populations from 'progenitor' cells via a sequence of one or more cell types, or compartments, where each cell's fate is chosen stochastically. If there is only one compartment then large amplification, that is, a large ratio of product cells to progenitors comes with disadvantages. The product cell population is dominated by large families (cells descended from the same progenitor) and many generations separate, on average, product cells from progenitors. These disadvantages are avoided using suitably constructed sequences of compartments: the amplification factor of a sequence is the product of the amplification factors of each compartment, while the average number of generations is a sum over contributions from each compartment. Passing through multiple compartments is, in fact, an efficient way to maintain a product cell population from a small flux of progenitors, avoiding excessive clonality and minimizing the number of rounds of division en route. We use division, exit and death rates, estimated from measurements of single-positive thymocytes, to choose illustrative parameter values in the single-compartment case. We also consider a five-compartment model of thymocyte differentiation, from double-negative precursors to single-positive product cells.

CellDestiny: A RShiny application for the visualization and analysis of single-cell lineage tracing data

Single-cell lineage tracing permits the labeling of individual cells with a heritable marker to follow the fate of each cell's progeny. Over the last twenty years, several single-cell lineage tracing methods have emerged, enabling major discoveries in developmental biology, oncology and gene therapies. Analytical tools are needed to draw meaningful conclusions from lineage tracing measurements, which are characterized by high variability, sparsity and technical noise. However, the single cell lineage tracing field lacks versatile and easy-to-use tools for standardized and reproducible analyses, in particular tools accessible to biologists. Here we present CellDestiny, a RShiny app and associated web application developed for experimentalists without coding skills to perform visualization and analysis of single cell lineage-tracing datasets through a graphical user interface. We demonstrate the functionality of CellDestiny through the analysis of (i) lentiviral barcoding datasets of murine hematopoietic progenitors; (ii) published integration site data from Wiskott-Aldrich Symdrome patients undergoing gene-therapy treatment; and (iii) simultaneous barcoding and transcriptomic analysis of murine hematopoietic progenitor differentiation in vitro. In summary, CellDestiny is an easy-to-use and versatile toolkit that enables biologists to visualize and analyze single-cell lineage tracing data.

High-quality data from a forensically relevant single-cell pipeline enabled by low PBS and proteinase K concentrations

Interpreting forensic DNA signal is arduous since the total intensity is a cacophony of signal from noise, artifact, and allele from an unknown number of contributors (NOC). An alternate to traditional bulk-processing pipelines is a single-cell one, where the sample is collected, and each cell is sequestered resulting in n single-source, single-cell EPGs (scEPG) that must be interpreted using applicable strategies. As with all forensic DNA interpretation strategies, high quality electropherograms are required; thus, to enhance the credibility of single-cell forensics, it is necessary to produce an efficient direct-to-PCR treatment that is compatible with prevailing downstream laboratory processes. We incorporated the semi-automated micro-fluidic DEPArray™ technology into the single-cell laboratory and optimized its implementation by testing the effects of four laboratory treatments on single-cell profiles. We focused on testing effects of phosphate buffer saline (PBS) since it is an important reagent that mitigates cell rupture but is also a PCR inhibitor. Specifically, we explored the effect of decreasing PBS concentrations on five electropherogram-quality metrics from 241 leukocytes: profile drop-out, allele drop-out, allele peak heights, peak height ratios, and scEPG sloping. In an effort to improve reagent use, we also assessed two concentrations of proteinase K. The results indicate that decreasing PBS concentrations to 0.5X or 0.25X improves scEPG quality, while modest modifications to proteinase K concentrations did not significantly impact it. We, therefore, conclude that a lower than recommended proteinase K concentration coupled with a lower than recommended PBS concentration results in enhanced scEPGs within the semi-automated single-cell pipeline.

Phylodynamics for cell biologists

Multicellular organisms are composed of cells connected by ancestry and descent from progenitor cells. The dynamics of cell birth, death, and inheritance within an organism give rise to the fundamental processes of development, differentiation, and cancer. Technical advances in molecular biology now allow us to study cellular composition, ancestry, and evolution at the resolution of individual cells within an organism or tissue. Here, we take a phylogenetic and phylodynamic approach to single-cell biology. We explain how "tree thinking" is important to the interpretation of the growing body of cell-level data and how ecological null models can benefit statistical hypothesis testing. Experimental progress in cell biology should be accompanied by theoretical developments if we are to exploit fully the dynamical information in single-cell data.

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).

Recent advances towards deciphering human dendritic cell development

Dendritic cell (DC) populations are the orchestrators of immune responses and arise from hematopoietic progenitors. Studies to unravel DC ontogeny have been conducted mainly in mice due to historical and practical reasons. However, understanding DC development in humans is a prerequisite for manipulating this process for therapeutic design. Here, we review the advantages and limitations of methods used to study human DC development in vitro and in vivo. In particular, we examine the in vitro culture systems that support the differentiation of all or some DC subpopulations. We also review recent discoveries regarding human DC precursors and factors that regulate their differentiation.

Single-cell omics in ageing: a young and growing field

Organismal ageing results from interlinked molecular changes in multiple organs over time. The study of ageing at the molecular level is complicated by varying decay characteristics and kinetics-both between and within organs-driven by intrinsic and extracellular factors. Emerging single-cell omics methods allow for molecular and spatial profiling of cells, and probing of regulatory states and cell-fate determination, thus providing promising tools for unravelling the heterogeneous process of ageing and making it amenable to intervention. These new strategies are enabled by advances in genomic, epigenomic and transcriptomic technologies. Combined with methods for proteome and metabolome analysis, single-cell techniques provide multidimensional, integrated data with unprecedented detail and throughput. Here, we provide an overview of the current state, and perspectives on the future, of this emerging field. We discuss how single-cell approaches can advance understanding of mechanisms underlying organismal ageing and aid in the development of interventions for ageing and ageing-associated diseases.

In vivo single-cell lineage tracing in zebrafish using high-resolution infrared laser-mediated gene induction microscopy

Heterogeneity broadly exists in various cell types both during development and at homeostasis. Investigating heterogeneity is crucial for comprehensively understanding the complexity of ontogeny, dynamics, and function of specific cell types. Traditional bulk-labeling techniques are incompetent to dissect heterogeneity within cell population, while the new single-cell lineage tracing methodologies invented in the last decade can hardly achieve high-fidelity single-cell labeling and long-term in-vivo observation simultaneously. In this work, we developed a high-precision infrared laser-evoked gene operator heat-shock system, which uses laser-induced CreERT2 combined with loxP-DsRedx-loxP-GFP reporter to achieve precise single-cell labeling and tracing. In vivo study indicated that this system can precisely label single cell in brain, muscle and hematopoietic system in zebrafish embryo. Using this system, we traced the hematopoietic potential of hemogenic endothelium (HE) in the posterior blood island (PBI) of zebrafish embryo and found that HEs in the PBI are heterogeneous, which contains at least myeloid unipotent and myeloid-lymphoid bipotent subtypes.

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.

The Pleiotropic Effects of GATA1 and KLF1 in Physiological Erythropoiesis and in Dyserythropoietic Disorders

In the last few years, the advent of new technological approaches has led to a better knowledge of the ontogeny of erythropoiesis during development and of the journey leading from hematopoietic stem cells (HSCs) to mature red blood cells (RBCs). Our view of a well-defined hierarchical model of hematopoiesis with a near-homogeneous HSC population residing at the apex has been progressively challenged in favor of a landscape where HSCs themselves are highly heterogeneous and lineages separate earlier than previously thought. The coordination of these events is orchestrated by transcription factors (TFs) that work in a combinatorial manner to activate and/or repress their target genes. The development of next generation sequencing (NGS) has facilitated the identification of pathological mutations involving TFs underlying hematological defects. The examples of GATA1 and KLF1 presented in this review suggest that in the next few years the number of TF mutations associated with dyserythropoietic disorders will further increase.

The Systems Biology of Single-Cell Aging

Aging is a leading cause of human morbidity and mortality, but efforts to slow or reverse its effects are hampered by an incomplete understanding of its multi-faceted origins. Systems biology, the use of quantitative and computational methods to understand complex biological systems, offers a toolkit well suited to elucidating the root cause of aging. We describe the known components of the aging network and outline innovative techniques that open new avenues of investigation to the aging research community. We propose integration of the systems biology and aging fields, identifying areas of complementarity based on existing and impending technological capabilities.

Proliferation dynamics of acute myeloid leukaemia and haematopoietic progenitors competing for bone marrow space

Leukaemia progressively invades bone marrow (BM), outcompeting healthy haematopoiesis by mechanisms that are not fully understood. Combining cell number measurements with a short-timescale dual pulse labelling method, we simultaneously determine the proliferation dynamics of primitive haematopoietic compartments and acute myeloid leukaemia (AML). We observe an unchanging proportion of AML cells entering S phase per hour throughout disease progression, with substantial BM egress at high levels of infiltration. For healthy haematopoiesis, we find haematopoietic stem cells (HSCs) make a significant contribution to cell production, but we phenotypically identify a quiescent subpopulation with enhanced engraftment ability. During AML progression, we observe that multipotent progenitors maintain a constant proportion entering S phase per hour, despite a dramatic decrease in the overall population size. Primitive populations are lost from BM with kinetics that are consistent with ousting irrespective of cell cycle state, with the exception of the quiescent HSC subpopulation, which is more resistant to elimination.

How leukaemia cells invade the bone marrow by outcompeting haematopoietic cells is still unclear. Here, the authors used detailed cell number measurements in conjunction with a dual pulse labelling method to determine proliferation rates and followed the in vivo dynamics of AML disease progression.

More or less-On the influence of labelling strategies to infer cell population dynamics

The adoptive transfer of labelled cell populations has been an essential tool to determine and quantify cellular dynamics. The experimental methods to label and track cells over time range from fluorescent dyes over congenic markers towards single-cell labelling techniques, such as genetic barcodes. While these methods have been widely used to quantify cell differentiation and division dynamics, the extent to which the applied labelling strategy actually affects the quantification of the dynamics has not been determined so far. This is especially important in situations where measurements can only be obtained at a single time point, as e.g. due to organ harvest. To this end, we studied the appropriateness of various labelling strategies as characterised by the number of different labels and the initial number of cells per label to quantify cellular dynamics. We simulated adoptive transfer experiments in systems of various complexity that assumed either homoeostatic cellular turnover or cell expansion dynamics involving various steps of cell differentiation and proliferation. Re-sampling cells at a single time point, we determined the ability of different labelling strategies to recover the underlying kinetics. Our results indicate that cell transition and expansion rates are differently affected by experimental shortcomings, such as loss of cells during transfer or sampling, dependent on the labelling strategy used. Furthermore, uniformly distributed labels in the transferred population generally lead to more robust and less biased results than non-equal label sizes. In addition, our analysis indicates that certain labelling approaches incorporate a systematic bias for the identification of complex cell expansion dynamics.

Selective Expression of Flt3 within the Mouse Hematopoietic Stem Cell Compartment

The fms-like tyrosine kinase 3 (Flt3) is a cell surface receptor that is expressed by various hematopoietic progenitor cells (HPC) and Flt3-activating mutations are commonly present in acute myeloid and lymphoid leukemias. These findings underscore the importance of Flt3 to steady-state and malignant hematopoiesis. In this study, the expression of Flt3 protein and Flt3 mRNA by single cells within the hematopoietic stem cell (HSC) and HPC bone marrow compartments of C57/BL6 mice was investigated using flow cytometry and the quantitative reverse transcription polymerase chain reaction. Flt3 was heterogeneously expressed by almost all of the populations studied, including long-term reconstituting HSC and short-term reconstituting HSC. The erythropoietin receptor (EpoR) and macrophage colony-stimulating factor receptor (M-CSFR) were also found to be heterogeneously expressed within the multipotent cell compartments. Co-expression of the mRNAs encoding Flt3 and EpoR rarely occurred within these compartments. Expression of both Flt3 and M-CSFR protein at the surface of single cells was more commonly observed. These results emphasize the heterogeneous nature of HSC and HPC and the new sub-populations identified are important to understanding the origin and heterogeneity of the acute myeloid leukemias.

T Cell Development by the Numbers

T cells are continually generated in the thymus in a highly dynamic process comprising discrete steps of lineage commitment, T cell receptor (TCR) gene rearrangement, and selection. These steps are linked to distinct rates of proliferation, survival, and cell death, but a quantitative picture of T cell development is only beginning to emerge. Here we summarize recent technical advances, including genetic fate mapping, barcoding, and molecular timers, that have allowed the implementation of computational models to quantify developmental dynamics in the thymus. Coupling new techniques with mathematical models has recently resulted in the emergence of new paradigms in early hematopoiesis and might similarly open new perspectives on T cell development.

Gene Therapy for X-Linked Severe Combined Immunodeficiency: Where Do We Stand?

More than 20 years ago, X-linked severe combined immunodeficiency (SCID-X1) appeared to be the best condition to test the feasibility of hematopoietic stem cell gene therapy. The seminal SCID-X1 clinical studies, based on first-generation gammaretroviral vectors, demonstrated good long-term immune reconstitution in most treated patients despite the occurrence of vector-related leukemia in a few of them. This gene therapy has successfully enabled correction of the T cell defect. Natural killer and B cell defects were only partially restored, most likely due to the absence of a conditioning regimen. The success of these pioneering trials paved the way for the extension of gene-based treatment to many other diseases of the hematopoietic system, but the unfortunate serious adverse events led to extensive investigations to define the retrovirus integration profiles. This review puts into perspective the clinical experience of gene therapy for SCID-X1, with the development and implementation of new generations of safer vectors such as self-inactivating gammaretroviral or lentiviral vectors as well as major advances in integrome knowledge.

Output without input: the lifelong productivity of hematopoietic stem cells

The hematopoietic stem cell (HSC) compartment must be maintained life-long, while being replenishable only from within. HSC proliferation can compensate for cell loss by differentiation, by cell death, or by mobilization from the bone marrow niches, but the relative use of proliferation to compensate for these distinct depletion sources is unclear. Classifications of HSC states (e.g., as active, dormant, quiescent or parsimonious) have mostly been based on HSC proliferation rather than on actual differentiation arising from HSC. New in vivo fate mapping experiments have shed light on HSC output. The kinetics of label emergence from HSC to progenitor stages uncovered steady, infrequent and low output from large numbers of HSC during normal adult hematopoiesis. Here, we discuss the relative contribution of proliferation to differentiation and self-renewal in hematopoietic stem and progenitor compartments, and propose that kinetic data on HSC output also yield insights into the structure of the hematopoietic hierarchy.

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.

In Vivo Tracking of Human Hematopoiesis Reveals Patterns of Clonal Dynamics during Early and Steady-State Reconstitution Phases

Hematopoietic stem/progenitor cells (HSPCs) are capable of supporting the lifelong production of blood cells exerting a wide spectrum of functions. Lentiviral vector HSPC gene therapy generates a human hematopoietic system stably marked at the clonal level by vector integration sites (ISs). Using IS analysis, we longitudinally tracked >89,000 clones from 15 distinct bone marrow and peripheral blood lineages purified up to 4 years after transplant in four Wiskott-Aldrich syndrome patients treated with HSPC gene therapy. We measured at the clonal level repopulating waves, populations' sizes and dynamics, activity of distinct HSPC subtypes, contribution of various progenitor classes during the early and late post-transplant phases, and hierarchical relationships among lineages. We discovered that in-vitro-manipulated HSPCs retain the ability to return to latency after transplant and can be physiologically reactivated, sustaining a stable hematopoietic output. This study constitutes in vivo comprehensive tracking in humans of hematopoietic clonal dynamics during the early and late post-transplant phases.

•

Hematopoietic reconstitution occurs in two distinct clonal waves

•

A few thousand HSPC clones stably sustain multilineage blood cell production

•

Steady-state hematopoiesis after transplant is maintained by both HSCs and MPPs

•

Natural killer clones have closer relationships to myeloid cells than to lymphoid cells

Stem-cell dynamics and lineage topology from in vivo fate mapping in the hematopoietic system

In recent years, sophisticated fate-mapping tools have been developed to study the behavior of stem cells in the intact organism. These experimental approaches are beginning to yield a quantitative picture of how cell numbers are regulated during steady state and in response to challenges. Focusing on hematopoiesis and immune responses, we discuss how novel mathematical approaches driven by these fate-mapping data have provided insights into the dynamics and topology of cellular differentiation pathways in vivo. The combination of experiment and theory has allowed to quantify the degree of self-renewal in stem and progenitor cells, shown how native hematopoiesis differs fundamentally from post-transplantation hematopoiesis, and uncovered that the diversification of T lymphocytes during immune responses resembles tissue renewal driven by stem cells.

Mathematics in modern immunology

Mathematical and statistical methods enable multidisciplinary approaches that catalyse discovery. Together with experimental methods, they identify key hypotheses, define measurable observables and reconcile disparate results. We collect a representative sample of studies in T-cell biology that illustrate the benefits of modelling–experimental collaborations and that have proven valuable or even groundbreaking. We conclude that it is possible to find excellent examples of synergy between mathematical modelling and experiment in immunology, which have brought significant insight that would not be available without these collaborations, but that much remains to be discovered.

Understanding hematopoiesis from a single-cell standpoint

The cellular diversity of the hematopoietic system has been extensively studied, and a plethora of cell surface markers have been used to discriminate and prospectively purify different blood cell types. However, even within phenotypically identical fractions of hematopoietic stem and progenitor cells or lineage-restricted progenitors, significant functional heterogeneity is observed when single cells are analyzed. To address these challenges, researchers are now using techniques to follow single cells and their progeny to improve our understanding of the underlying functional heterogeneity. On November 19, 2015, Dr. David Kent and Dr. Leïla Perié, two emerging young group leaders, presented their recent efforts to dissect the functional properties of individual cells with a webinar series organized by the International Society for Experimental Hematology. Here, we provide a summary of the presented methods for cell labeling and clonal tracking and discuss how these different techniques have been employed to study hematopoiesis.

Inferring average generation via division-linked labeling

For proliferating cells subject to both division and death, how can one estimate the average generation number of the living population without continuous observation or a division-diluting dye? In this paper we provide a method for cell systems such that at each division there is an unlikely, heritable one-way label change that has no impact other than to serve as a distinguishing marker. If the probability of label change per cell generation can be determined and the proportion of labeled cells at a given time point can be measured, we establish that the average generation number of living cells can be estimated. Crucially, the estimator does not depend on knowledge of the statistics of cell cycle, death rates or total cell numbers. We explore the estimator's features through comparison with physiologically parameterized stochastic simulations and extrapolations from published data, using it to suggest new experimental designs.

Cellular barcoding: a technical appraisal

Cellular barcoding involves the tagging of individual cells of interest with unique genetic heritable identifiers or barcodes and is emerging as a powerful tool to address individual cell fates on a large scale. However, as with many new technologies, diverse technical and analytical challenges have emerged. Here, we review those challenges and highlight both the power and limitations of cellular barcoding. We then illustrate the contribution of cellular barcoding to the understanding of hematopoiesis and outline the future potential of this technology.