cellPLATO - an unsupervised method for identifying cell behaviour in heterogeneous cell trajectory data.

Advances in imaging, segmentation and tracking have led to the routine generation of large and complex microscopy datasets. New tools are required to process this 'phenomics' type data. Here, we present 'Cell PLasticity Analysis Tool' (cellPLATO), a Python-based analysis software designed for measurement and classification of cell behaviours based on clustering features of cell morphology and motility. Used after segmentation and tracking, the tool extracts features from each cell per timepoint, using them to segregate cells into dimensionally reduced behavioural subtypes. Resultant cell tracks describe a 'behavioural ID' at each timepoint, and similarity analysis allows the grouping of behavioural sequences into discrete trajectories with assigned IDs. Here, we use cellPLATO to investigate the role of IL-15 in modulating human natural killer (NK) cell migration on ICAM-1 or VCAM-1. We find eight behavioural subsets of NK cells based on their shape and migration dynamics between single timepoints, and four trajectories based on sequences of these behaviours over time. Therefore, by using cellPLATO, we show that IL-15 increases plasticity between cell migration behaviours and that different integrin ligands induce different forms of NK cell migration.

CRISPR Dependency Screens in Primary Hematopoietic Stem Cells Identify KDM3B as a Genotype Specific Vulnerability in IDH2- and TET2-Mutant Cells.

Clonal hematopoiesis (CH) is a common premalignant state in the blood and confers an increased risk of blood cancers and all-cause mortality. Identification of therapeutic targets in CH has been hindered by the lack of an ex vivo platform amenable for studying primary hematopoietic stem and progenitor cells (HSPCs). Here, we utilize an ex vivo co-culture system of HSPCs with bone marrow endothelial cells to perform CRISPR/Cas9 screens in mutant HSPCs. Our data reveal that loss of the histone demethylase family members Kdm3b and Jmjd1c specifically reduces the fitness of Idh2- and Tet2-mutant HSPCs. Kdm3b loss in mutant cells leads to decreased expression of critical cytokine receptors including Mpl, rendering mutant HSPCs preferentially susceptible to inhibition of downstream JAK2 signaling. Our study nominates an epigenetic regulator and an epigenetically regulated receptor signaling pathway as genotype-specific therapeutic targets and provides a scalable platform to identify genetic dependencies in mutant HSPCs.

Jak2V617F Reversible Activation Shows Its Essential Requirement in Myeloproliferative Neoplasms.

Gain-of-function mutations activating JAK/STAT signaling are seen in the majority of patients with myeloproliferative neoplasms (MPN), most commonly JAK2V617F. Although clinically approved JAK inhibitors improve symptoms and outcomes in MPNs, remissions are rare, and mutant allele burden does not substantively change with chronic therapy. We hypothesized this is due to limitations of current JAK inhibitors to potently and specifically abrogate mutant JAK2 signaling. We therefore developed a conditionally inducible mouse model allowing for sequential activation, and then inactivation, of Jak2V617F from its endogenous locus using a combined Dre-rox/Cre-lox dual-recombinase system. Jak2V617F deletion abrogates MPN features, induces depletion of mutant-specific hematopoietic stem/progenitor cells, and extends overall survival to an extent not observed with pharmacologic JAK inhibition, including when cooccurring with somatic Tet2 loss. Our data suggest JAK2V617F represents the best therapeutic target in MPNs and demonstrate the therapeutic relevance of a dual-recombinase system to assess mutant-specific oncogenic dependencies in vivo. SIGNIFICANCE: Current JAK inhibitors to treat myeloproliferative neoplasms are ineffective at eradicating mutant cells. We developed an endogenously expressed Jak2V617F dual-recombinase knock-in/knock-out model to investigate Jak2V617F oncogenic reversion in vivo. Jak2V617F deletion abrogates MPN features and depletes disease-sustaining MPN stem cells, suggesting improved Jak2V617F targeting offers the potential for greater therapeutic efficacy. See related commentary by Celik and Challen, p. 701. This article is featured in Selected Articles from This Issue, p. 695.

cellPLATO: an unsupervised method for identifying cell behaviour in heterogeneous cell trajectory data.

Advances in imaging, cell segmentation, and cell tracking now routinely produce microscopy datasets of a size and complexity comparable to transcriptomics or proteomics. New tools are required to process this 'phenomics' type data. Cell PLasticity Analysis TOol (cellPLATO) is a Python-based analysis software designed for measurement and classification of diverse cell behaviours based on clustering of parameters of cell morphology and motility. cellPLATO is used after segmentation and tracking of cells from live cell microscopy data. The tool extracts morphological and motility metrics from each cell per timepoint, before being using them to segregate cells into behavioural subtypes with dimensionality reduction. Resultant cell tracks have a 'behavioural ID' for each cell per timepoint corresponding to their changing behaviour over time in a sequence. Similarity analysis allows the grouping of behavioural sequences into discrete trajectories with assigned IDs. Trajectories and underlying behaviours generate a phenotypic fingerprint for each experimental condition, and representative cells are mathematically identified and graphically displayed for human understanding of each subtype. Here, we use cellPLATO to investigate the role of IL-15 in modulating NK cell migration on ICAM-1 or VCAM-1. We find 8 behavioural subsets of NK cells based on their shape and migration dynamics, and 4 trajectories of behaviour. Therefore, using cellPLATO we show that IL-15 increases plasticity between cell migration behaviours and that different integrin ligands induce different forms of NK cell migration.

Deep generative model deciphers derailed trajectories in acute myeloid leukemia.

Single-cell genomics has the potential to map cell states and their dynamics in an unbiased way in response to perturbations like disease. However, elucidating the cell-state transitions from healthy to disease requires analyzing data from perturbed samples jointly with unperturbed reference samples. Existing methods for integrating and jointly visualizing single-cell datasets from distinct contexts tend to remove key biological differences or do not correctly harmonize shared mechanisms. We present Decipher, a model that combines variational autoencoders with deep exponential families to reconstruct derailed trajectories (https://github.com/azizilab/decipher). Decipher jointly represents normal and perturbed single-cell RNA-seq datasets, revealing shared and disrupted dynamics. It further introduces a novel approach to visualize data, without the need for methods such as UMAP or TSNE. We demonstrate Decipher on data from acute myeloid leukemia patient bone marrow specimens, showing that it successfully characterizes the divergence from normal hematopoiesis and identifies transcriptional programs that become disrupted in each patient when they acquire NPM1 driver mutations.

Mapping human natural killer cell development in pediatric tonsil by imaging mass cytometry and high-resolution microscopy.

Natural killer (NK) cells develop from CD34+ progenitors in a stage-specific manner defined by changes in cell surface receptor expression and function. Secondary lymphoid tissues, including tonsil, are sites of human NK cell development. Here we present new insights into human NK cell development in pediatric tonsil using cyclic immunofluorescence and imaging mass cytometry. We show that NK cell subset localization and interactions are dependent on NK cell developmental stage and tissue residency. NK cell progenitors are found in the interfollicular domain in proximity to cytokine-expressing stromal cells that promote proliferation and maturation. Mature NK cells are primarily found in the T-cell rich parafollicular domain engaging in cell-cell interactions that differ depending on their stage and tissue residency. The presence of local inflammation results in changes in NK cell interactions, abundance, and localization. This study provides the first comprehensive atlas of human NK cell development in secondary lymphoid tissue.

Quantifying Human Natural Killer Cell Migration by Imaging and Image Analysis.

Migration is an important function for natural killer cells. Cell motility has implications in development, tissue infiltration, and cytotoxicity, and measuring the properties of natural killer (NK) cell migration using in vitro assays can be highly informative. Many researchers have an interest in studying properties of NK cell migration in the context of genetic mutation, disease, or in specific tissues and microenvironments. Motility assays can also provide information on the localization of proteins during different phases of cell migration. These assays can be performed on different surfaces for migration or coupled with chemoattractants and/or target cells to test functional outcomes or characterize cell migration speeds and phenotypes. NK cells undergo migration during differentiation in tissue, and these conditions can be modeled by culturing NK cells on a confluent bed of stromal cells on glass and imaging cell migration. Alternatively, fibronectin- or ICAM-1-coated surfaces promote NK cell migration and can be used as substrates. Here, we will describe techniques for the experimental setup and analysis of NK cell motility assays by confocal microscopy or in-incubator imaging using commercially available systems. Finally, we describe open-source software for analyzing cell migration using manual tracking or automated approaches and discuss considerations for the implementation of each of these methods.

Cohesin Members Stag1 and Stag2 Display Distinct Roles in Chromatin Accessibility and Topological Control of HSC Self-Renewal and Differentiation.

Transcriptional regulators, including the cohesin complex member STAG2, are recurrently mutated in cancer. The role of STAG2 in gene regulation, hematopoiesis, and tumor suppression remains unresolved. We show that Stag2 deletion in hematopoietic stem and progenitor cells (HSPCs) results in altered hematopoietic function, increased self-renewal, and impaired differentiation. Chromatin immunoprecipitation (ChIP) sequencing revealed that, although Stag2 and Stag1 bind a shared set of genomic loci, a component of Stag2 binding sites is unoccupied by Stag1, even in Stag2-deficient HSPCs. Although concurrent loss of Stag2 and Stag1 abrogated hematopoiesis, Stag2 loss alone decreased chromatin accessibility and transcription of lineage-specification genes, including Ebf1 and Pax5, leading to increased self-renewal and reduced HSPC commitment to the B cell lineage. Our data illustrate a role for Stag2 in transformation and transcriptional dysregulation distinct from its shared role with Stag1 in chromosomal segregation.