Replicative history marks transcriptional and functional disparity in the CD8+ T cell memory pool.

Clonal expansion is a core aspect of T cell immunity. However, little is known with respect to the relationship between replicative history and the formation of distinct CD8+ memory T cell subgroups. To address this issue, we developed a genetic-tracing approach, termed the DivisionRecorder, that reports the extent of past proliferation of cell pools in vivo. Using this system to genetically 'record' the replicative history of different CD8+ T cell populations throughout a pathogen-specific immune response, we demonstrate that the central memory T (TCM) cell pool is marked by a higher number of prior divisions than the effector memory T cell pool, owing to the combination of strong proliferative activity during the acute immune response and selective proliferative activity after pathogen clearance. Furthermore, by combining DivisionRecorder analysis with single-cell transcriptomics and functional experiments, we show that replicative history identifies distinct cell pools within the TCM compartment. Specifically, we demonstrate that lowly divided TCM cells display enriched expression of stem-cell-associated genes, exist in a relatively quiescent state, and are superior in eliciting a proliferative recall response upon activation. These data provide the first evidence that a stem-cell-like memory T cell pool that reconstitutes the CD8+ T cell effector pool upon reinfection is marked by prior quiescence.

Clonal multi-omics reveals Bcor as a negative regulator of emergency dendritic cell development.

Despite advances in single-cell multi-omics, a single stem or progenitor cell can only be tested once. We developed clonal multi-omics, in which daughters of a clone act as surrogates of the founder, thereby allowing multiple independent assays per clone. With SIS-seq, clonal siblings in parallel "sister" assays are examined either for gene expression by RNA sequencing (RNA-seq) or for fate in culture. We identified, and then validated using CRISPR, genes that controlled fate bias for different dendritic cell (DC) subtypes. This included Bcor as a suppressor of plasmacytoid DC (pDC) and conventional DC type 2 (cDC2) numbers during Flt3 ligand-mediated emergency DC development. We then developed SIS-skew to examine development of wild-type and Bcor-deficient siblings of the same clone in parallel. We found Bcor restricted clonal expansion, especially for cDC2s, and suppressed clonal fate potential, especially for pDCs. Therefore, SIS-seq and SIS-skew can reveal the molecular and cellular mechanisms governing clonal fate.

Non-genetic determinants of malignant clonal fitness at single-cell resolution.

All cancers emerge after a period of clonal selection and subsequent clonal expansion. Although the evolutionary principles imparted by genetic intratumour heterogeneity are becoming increasingly clear1, little is known about the non-genetic mechanisms that contribute to intratumour heterogeneity and malignant clonal fitness2. Here, using single-cell profiling and lineage tracing (SPLINTR)-an expressed barcoding strategy-we trace isogenic clones in three clinically relevant mouse models of acute myeloid leukaemia. We find that malignant clonal dominance is a cell-intrinsic and heritable property that is facilitated by the repression of antigen presentation and increased expression of the secretory leukocyte peptidase inhibitor gene (Slpi), which we genetically validate as a regulator of acute myeloid leukaemia. Increased transcriptional heterogeneity is a feature that enables clonal fitness in diverse tissues and immune microenvironments and in the context of clonal competition between genetically distinct clones. Similar to haematopoietic stem cells3, leukaemia stem cells (LSCs) display heritable clone-intrinsic properties of high, and low clonal output that contribute to the overall tumour mass. We demonstrate that LSC clonal output dictates sensitivity to chemotherapy and, although high- and low-output clones adapt differently to therapeutic pressure, they coordinately emerge from minimal residual disease with increased expression of the LSC program. Together, these data provide fundamental insights into the non-genetic transcriptional processes that underpin malignant clonal fitness and may inform future therapeutic strategies.

A risk-reward examination of sample multiplexing reagents for single cell RNA-Seq.

Single-cell RNA sequencing (scRNA-Seq) has emerged as a powerful tool for understanding cellular heterogeneity and function. However the choice of sample multiplexing reagents can impact data quality and experimental outcomes. In this study, we compared various multiplexing reagents, including MULTI-Seq, Hashtag antibody, and CellPlex, across diverse sample types such as human peripheral blood mononuclear cells (PBMCs), mouse embryonic brain and patient-derived xenografts (PDXs). We found that all multiplexing reagents worked well in cell types robust to ex vivo manipulation but suffered from signal-to-noise issues in more delicate sample types. We compared multiple demultiplexing algorithms which differed in performance depending on data quality. We find that minor improvements to laboratory workflows such as titration and rapid processing are critical to optimal performance. We also compared the performance of fixed scRNA-Seq kits and highlight the advantages of the Parse Biosciences kit for fragile samples. Highly multiplexed scRNA-Seq experiments require more sequencing resources, therefore we evaluated CRISPR-based destruction of non-informative genes to enhance sequencing value. Our comprehensive analysis provides insights into the selection of appropriate sample multiplexing reagents and protocols for scRNA-Seq experiments, facilitating more accurate and cost-effective studies.

Benchmarking single cell RNA-sequencing analysis pipelines using mixture control experiments.

Single cell RNA-sequencing (scRNA-seq) technology has undergone rapid development in recent years, leading to an explosion in the number of tailored data analysis methods. However, the current lack of gold-standard benchmark datasets makes it difficult for researchers to systematically compare the performance of the many methods available. Here, we generated a realistic benchmark experiment that included single cells and admixtures of cells or RNA to create 'pseudo cells' from up to five distinct cancer cell lines. In total, 14 datasets were generated using both droplet and plate-based scRNA-seq protocols. We compared 3,913 combinations of data analysis methods for tasks ranging from normalization and imputation to clustering, trajectory analysis and data integration. Evaluation revealed pipelines suited to different types of data for different tasks. Our data and analysis provide a comprehensive framework for benchmarking most common scRNA-seq analysis steps.

Sample path properties of the average generation of a Bellman-Harris process.

Motivated by a recently proposed design for a DNA coded randomised algorithm that enables inference of the average generation of a collection of cells descendent from a common progenitor, here we establish strong convergence properties for the average generation of a super-critical Bellman-Harris process. We further extend those results to a two-type Bellman-Harris process where one type can give rise to the other, but not vice versa. These results further affirm the estimation method's potential utility by establishing its long run accuracy on individual sample-paths, and significantly expanding its remit to encompass cellular development that gives rise to differentiated offspring with distinct population dynamics.

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.

Broad volume distributions indicate nonsynchronized growth and suggest sudden collapses of germinal center B cell populations.

Immunization with a T cell-dependent Ag leads to the formation of several hundred germinal centers (GCs) within secondary lymphoid organs, a key process in the maturation of the immune response. Although prevailing perceptions about affinity maturation intuitively assume simultaneous seeding, growth, and decay of GCs, our previous mathematical simulations led us to hypothesize that their growth might be nonsynchronized. To investigate this, we performed computer-aided three-dimensional reconstructions of splenic GCs to measure size distributions at consecutive time points following immunization of BALB/c mice with a conjugate of 2-phenyl-oxazolone and chicken serum albumin. Our analysis reveals a broad volume distribution of GCs, indicating that individual GCs certainly do not obey the average time course of the GC volumes and that their growth is nonsynchronized. To address the cause and implications of this behavior, we compared our empirical data with simulations of a stochastic mathematical model that allows for frequent and sudden collapses of GCs. Strikingly, this model succeeds in reproducing the empirical average kinetics of GC volumes as well as the underlying broad size distributions. Possible causes of GC B cell population collapses are discussed in the context of the affinity-maturation process.

Single-cell analyses reveal the clonal and molecular aetiology of Flt3L-induced emergency dendritic cell development.

Regulation of haematopoietic stem and progenitor cell (HSPC) fate is crucial during homeostasis and under stress conditions. Here we examine the aetiology of the Flt3 ligand (Flt3L)-mediated increase of type 1 conventional dendritic cells (cDC1s). Using cellular barcoding we demonstrate this occurs through selective clonal expansion of HSPCs that are primed to produce cDC1s and not through activation of cDC1 fate by other HSPCs. In particular, multi/oligo-potent clones selectively amplify their cDC1 output, without compromising the production of other lineages, via a process we term tuning. We then develop Divi-Seq to simultaneously profile the division history, surface phenotype and transcriptome of individual HSPCs. We discover that Flt3L-responsive HSPCs maintain a proliferative 'early progenitor'-like state, leading to the selective expansion of multiple transitional cDC1-primed progenitor stages that are marked by Irf8 expression. These findings define the mechanistic action of Flt3L through clonal tuning, which has important implications for other models of 'emergency' haematopoiesis.

Cell Cycle-Associated CXCR4 Expression in Germinal Center B Cells and Its Implications on Affinity Maturation.

Adaptation of antibody-mediated immunity occurs in germinal centers (GC). It is where affinity maturation, class switching, memory and plasma cell differentiation synergize to generate specific high-affinity antibodies that aid both to clear and protect against reinfection of invading pathogens. Within GCs, light and dark zone are two compartments instrumental in regulating this process, by segregating T cell-dependent selection and differentiation from generation of GC B cells bearing hypermutated antigen receptors. Spatial segregation of GC B cells into the two zones relies on the chemokine receptor CXCR4, with textbooks attributing high and low expression to a dark and light zone phenotype. Interestingly, this bipolarity is not reflected in the CXCR4 expression profile of GC B cells, which is highly variable and unimodal, indicating a continuum of intermediate CXCR4 levels rather than a binary dark or light zone phenotype. Here, analysis of published BrdU pulse-chase data reveals that throughout cell cycle, average CXCR4 expression in GC B cells steadily increases close to twofold, scaling with cell surface area. CXCR4 expression in recently divided GC B cells in G0/G1 or early S phase shows intermediate levels compared to cells in G2M phase, consistent with their smaller size. The lowest number of CXCR4 receptors are displayed by relatively aged GC B cells in G0/G1 or early S phase. The latter, upon progressing through S phase, however, ramp up relative CXCR4 expression twice as much as recently divided cells. Twelve hours after the BrdU pulse, labeled GC B cells, while initially in S phase, are desynchronized in terms of cell cycle and match the CXCR4 profile of unlabeled cells. A model is discussed in which CXCR4 expression in GC B cell increases with cell cycle and cell surface area, with highest levels in G2 and M phase, coinciding with GC B cell receptor signaling in G2 and immediately preceding activation-induced cytidine deaminase (AID) activity in early G1. In the model, GC B cells compete for CXCL12 expression on the basis of their CXCR4 expression, gaining a relative advantage as they progress in cell cycle, but loosing the advantage at the moment they divide.

Inhibition of Endosteal Vascular Niche Remodeling Rescues Hematopoietic Stem Cell Loss in AML.

Bone marrow vascular niches sustain hematopoietic stem cells (HSCs) and are drastically remodeled in leukemia to support pathological functions. Acute myeloid leukemia (AML) cells produce angiogenic factors, which likely contribute to this remodeling, but anti-angiogenic therapies do not improve AML patient outcomes. Using intravital microscopy, we found that AML progression leads to differential remodeling of vasculature in central and endosteal bone marrow regions. Endosteal AML cells produce pro-inflammatory and anti-angiogenic cytokines and gradually degrade endosteal endothelium, stromal cells, and osteoblastic cells, whereas central marrow remains vascularized and splenic vascular niches expand. Remodeled endosteal regions have reduced capacity to support non-leukemic HSCs, correlating with loss of normal hematopoiesis. Preserving endosteal endothelium with the small molecule deferoxamine or a genetic approach rescues HSCs loss, promotes chemotherapeutic efficacy, and enhances survival. These findings suggest that preventing degradation of the endosteal vasculature may improve current paradigms for treating AML.

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.