Single-cell Trajectory Analysis Research Articles

Moxifloxacin induces random migration in human corneal fibroblasts via the protein kinase C epsilon/zonula occludens-1 signaling pathway

Moxifloxacin (MOX) suppresses cell movement in human corneal fibroblasts (HCFs). Zonula occludens-1 (ZO-1) is localized to the leading edge of migrating HCFs. This study explored the role of ZO-1 in MOX-suppressed cell migration in HCFs. A single-cell trajectory analysis revealed that MOX negatively regulated the migratory properties of HCFs including migration distance, migration velocity, and directionality (P < 0.001, P < 0.001, and P = 0.018, respectively). MOX increased endogenous ZO-1 in HCFs in a concentration-dependent manner (P = 0.083, P = 0.005, and P = 0.001 at 10, 50, and 100 μg/ml, respectively), but decreased the phosphorylation of endogenous ZO-1 at serines, threonines, and tyrosines. In contrast, MOX did not alter the expression of protein kinase C epsilon (PKCε), Rac-1, Cdc42, and MRCKβ. However, MOX did also reduce the phosphorylation level of PKCε at serines and threonines (P < 0.001 at 100 μg/ml). In addition, MOX increased the phosphorylation level of Rac-1 in a concentration-dependent manner (P < 0.001 at 100 μg/ml). Compared with the mock cells, the directionality of cell movement increased significantly in ZO-1-expressing HCFs (P = 0.012) and decreased significantly in ZO-1-silenced HCFs (P = 0.002). The directionality did not change significantly in Rac-1-silenced HCFs. ZO-1-expressing HCFs moved faster than mock cells. PKCε, Cdc42, Rac-1, and phosphorylated Rac-1 were decreased in ZO-1-overexpressing HCFs, but increased in ZO-1-silenced HCFs. Finally, silencing ZO-1 blocked MOX hyperactivation of Rac-1. These suggest that MOX might trigger random migration in human corneal stromal cells through PKCε-modulated ZO-1 inactivation and Rac-1 hyperactivation.

Abstract 3201: Single-cell trajectory analysis reveals a melanoma-driven distinct hematopoietic response in murine spleen

Abstract Growing evidence suggests that tumor progression can interfere with normal hematopoiesis and skew the host system to undergo myeloid biased changes. Hematopoietic stem and progenitor cells (HSPCs) are a rare population of precursor cells giving rise to progeny that replenish blood cells throughout life. HSPCs are mainly localized in the bone marrow niche in healthy adults, however pathophysiological conditions such as cancer can cause extramedullary hematopoiesis in organs like the spleen. In this study, we investigated tumor-driven phenotypic and molecular alterations in the HSPC compartment at a single-cell level during extramedullary hematopoiesis using single-cell multiomics. We used a B16-F10 melanoma mouse model to uncover the tumor-mediated changes. Mice with tumor-burden showed splenomegaly and alterations in the composition of the HSPC compartment in the spleen consistent with extramedullary hematopoiesis. We then isolated four HSPC populations, including Lin- Sca1+ cKit+ (LSK), common myeloid progenitor (CMP), granulocyte-macrophage progenitor (GMP) and megakaryocyte-erythrocyte progenitor (MEP) cells from the spleen and bone marrow of melanoma-burdened mice using the BD FACSMelody™ Cell Sorter. Next, we used an integrated workflow on the BD Rhapsody™ Single-Cell Analysis System for the downstream single-cell multiomics analysis. We utilized oligo-conjugated antibodies for NGS-based sample multiplexing and protein detection (BD® Single-Cell Multiplexing Kit, BD® AbSeq Assay), along with whole transcriptome analysis for a comprehensive analysis of mRNA expression. Data analysis using the X-shift algorithm paired with single-cell force-directed layout visualization enabled delineation of the developmental trajectories of HSPC populations and exploration of phenotypic and transcriptomic changes across different hematopoietic subpopulations and across distinct anatomic sites. The analysis also identified unique hematopoietic cell clusters present during melanoma-driven extramedullary hematopoiesis in the spleen. Overall, our findings highlight melanoma-driven perturbations in hematopoiesis by utilizing advanced single-cell multiomics technology. Disclaimers: For Research Use Only. Not for use in diagnostic or therapeutic procedures. Class 1 Laser Product. BD-23277 (v1.0) 1120 BD, the BD Logo, FACSMelody and Rhapsody are trademarks of Becton, Dickinson and Company or its affiliates. © 2020 BD. All rights reserved. Citation Format: Nihan Kara, Nikolay Samusik, Xiaoshan Shi, Chip Lomas, Stephanie Widmann, Aaron J. Tyznik. Single-cell trajectory analysis reveals a melanoma-driven distinct hematopoietic response in murine spleen [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 3201.

Single-cell trajectory analysis reveals a melanoma-driven distinct hematopoietic response in murine spleen

Abstract Hematopoietic stem and progenitor cells (HSPCs) are a rare population of precursor cells residing in bone marrow that replenish blood cells throughout adult life. Growing evidence suggests that tumor progression can interfere with normal hematopoiesis, skew the host system to undergo myeloid biased changes and cause extramedullary hematopoiesis (EMH) in organs such as the spleen. In this study, we investigated tumor-driven phenotypic and molecular alterations in HSPCs during EMH using single-cell multiomics. We used a B16-F10 melanoma mouse model which showed splenomegaly and alterations in the composition of the HSPCs in the spleen consistent with EMH. We then isolated four HSPC populations from the spleen and bone marrow of melanoma-burdened mice using the BD FACSMelody™ Cell Sorter and used the BD Rhapsody™ Single-Cell Analysis System for the downstream single-cell multiomics analysis. We utilized oligo-conjugated antibodies for NGS-based sample multiplexing (BD® Single-Cell Multiplexing Kit) and protein detection (BD® AbSeq Assay), along with whole transcriptome analysis for a comprehensive analysis of mRNA expression. We observed tumor-driven distinct hematopoietic response and alterations in developmental trajectories of HSPCs during EMH using the X-shift algorithm paired with single-cell force-directed layout visualization. Our findings highlight melanoma-driven perturbations in hematopoiesis by utilizing single-cell multiomics in a murine model. Class 1 Laser Product. For Research Use Only. Not for use in diagnostic or therapeutic procedures. BD-24477 (v1.0) 1220 BD, the BD Logo, FACSMelody, Rhapsody and AbSeq are trademarks of Becton, Dickinson and Company or its affiliates ©2020 BD. All rights reserved.

Abstract PD7-02: Estrogen-induced cell cycle arrest as an unexpected outcome of aromatase inhibitor-resistance: Insights from single-cell trajectory analysis of a patient-derived xenograft model

Abstract Background: Estrogen such as estradiol (E2) is known to promote ER+ breast cancer. However, several clinical trials reported the unexpected therapeutic benefit of E2 for aromatase inhibitor (AI)-resistant cases of ER+ postmenopausal breast cancer. The objective of this study is to uncover the mechanisms of E2-induced tumor regression, leading to an unconventional treatment of AI resistance. Methods: An E2-suppressive patient-derived xenograft model (named GS3) was established from an AI resistant ER+/PR-/HER2- brain metastatic breast cancer. Placebo or E2 pellets were implanted in mice carrying GS3 for evaluating the effects of E2. Immunohistochemistry (IHC) and RNA sequencing of GS3 were conducted to decipher molecular changes after E2 treatments. Since the cancer tissue has a heterogeneous structure, the single-cell analysis was further performed to examine gene expression profiles in individual cells. In addition, in vitro cell proliferation analysis was carried out using organoids from GS3. Results: E2 inhibited the growth of GS3 both in vivo and in vitro. ERα and ERβ genes in GS3 are wild-type and not amplified. ERα is involved because E2-mediated inhibition of GS3-organoids can be reversed by the co-treatment of ERα antagonist, not by ERβ antagonist. IHC showed that ER, Ki-67 and CEA expressions decreased and PR expression appeared after E2 treatment. Gene set enrichment analysis (GSEA) using RNAseq results showed that the E2 response gene sets were significantly up-regulated after E2 treatment. However, the cell cycle gene sets and the TNFA/NFKB gene set were down-regulated. GS3 gained an E2 independence after three cycles of intermittent E2 treatment (E2 pellet on/off every 4 weeks; Int-E2). Interestingly, the cell cycle and TNFA/NFKB gene sets were up-regulated after Int-E2 treatment. Single-cell RNAseq analysis revealed that cells from one-week E2-treated and Placebo-treated GS3 were placed in different clusters based on principle component analysis of Highly Variable Genes. Although E2 response genes were up-regulated, the percent of ESR1+ cells decreased after E2 treatment (41.3% vs. 31.5%). The number of cells arrested at the G1 phase increased (+12.5%) after E2 treatment. GSEA using genes expressed in only ESR1+ cells showed that the TNFA/NFKB gene set was significantly down-regulated after E2 treatment. Meanwhile, GSEA using genes expressed in only ESR1– cells showed that cell cycle gene sets were significantly down-regulated. Single-cell trajectory analysis disclosed three major branches; 1) common E2 and placebo, 2) E2, and 3) placebo. In the E2 only branch, the cell cycle arrested at the G1 phase, the E2 response gene sets were up-regulated, and the NFKB gene set was down-regulated in ESR1+ cells. Significantly, E2 response gene sets were also up-regulated and cell cycle genes were down-regulated even in ESR1– cells. In the placebo branch, E2 response gene sets were not up-regulated and cell cycle genes were not down regulated. A group of MKI67+ cells (at G2M phase), including some ESR1+ cells, were present in both E2-treated and placebo-treated tumors. Conclusions: E2-induced suppression is an unexpected outcome of AI resistance. In these cases, elimination of estrogen by AI results in maintaining tumor growth. Analysis of GS3 PDX has revealed that estrogen can induce cell cycle arrest and the expression of estrogen-regulated genes. Our results also suggest the cross-talk between ESR1+ and ESR1- cells as well as potential roles of the TNFA/NFKB pathway. Our findings point out the need of markers for such patients who can benefit from E2 treatment after AI resistance, and measurements of ER and PR expression are not sufficient. An intermittent treatment strategy does not sustain the effect of estrogen-mediated suppression. Citation Format: Hitomi Mori, Kohei Saeki, Gregory Chang, Xiwei Wu, Pei-Yin Hsu, Noriko Kanaya, George Somlo, Shiuan Chen. Estrogen-induced cell cycle arrest as an unexpected outcome of aromatase inhibitor-resistance: Insights from single-cell trajectory analysis of a patient-derived xenograft model [abstract]. In: Proceedings of the 2020 San Antonio Breast Cancer Virtual Symposium; 2020 Dec 8-11; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2021;81(4 Suppl):Abstract nr PD7-02.

Highly sensitive spatial transcriptomics at near-cellular resolution with Slide-seqV2.

Measurement of the location of molecules in tissues is essential for understanding tissue formation and function. Previously, we developed Slide-seq, a technology that enables transcriptome-wide detection of RNAs with a spatial resolution of 10 μm. Here we report Slide-seqV2, which combines improvements in library generation, bead synthesis and array indexing to reach an RNA capture efficiency ~50% that of single-cell RNA-seq data (~10-fold greater than Slide-seq), approaching the detection efficiency of droplet-based single-cell RNA-seq techniques. First, we leverage the detection efficiency of Slide-seqV2 to identify dendritically localized mRNAs in neurons of the mouse hippocampus. Second, we integrate the spatial information of Slide-seqV2 data with single-cell trajectory analysis tools to characterize the spatiotemporal development of the mouse neocortex, identifying underlying genetic programs that were poorly sampled with Slide-seq. The combination of near-cellular resolution and high transcript detection efficiency makes Slide-seqV2 useful across many experimental contexts.

Distinct Evolutionary Patterns in Chronic Lymphocytic Leukemia (CLL) during Resistance to Graft-Versus-Leukemia (GvL)

Distinct Evolutionary Patterns in Chronic Lymphocytic Leukemia (CLL) during Resistance to Graft-Versus-Leukemia (GvL)

TMIC-06. MYELOID POPULATIONS AND THE EFFECT OF NEOADJUVANT PD-1 INHIBITION IN THE GLIOBLASTOMA MICROENVIRONMENT: A SURFACEOMIC AND TRANSCRIPTOMIC DISSECTION AT THE SINGLE-CELL LEVEL

Abstract INTRODUCTION Glioblastoma (GBM) is the most common malignant brain tumor in adults and is associated with a dismal prognosis. Neoadjuvant anti-PD-1 blockade has demonstrated efficacy in melanoma, non-small cell lung cancer and recurrent GBM; however, responses vary. While T cells have garnered considerable attention in the context of immunotherapy, the role of myeloid cells in the GBM microenvironment remains controversial. METHODS We isolated CD45+ immune populations from patients who underwent brain tumor resection at UCLA. We hypothesized that myeloid cells in glioblastoma contribute to T cell dysfunction; however, this immune suppression can be mitigated by neoadjuvant PD-1 inhibition. To test this, we utilized mass cytometry and single-cell RNA sequencing to characterize these immune populations. RESULTS Mass cytometry profiling of tumor infiltrating lymphocytes from patients with GBM demonstrated a preponderance of CD11b+ myeloid populations (75% versus 25% CD3+). At the transcriptomic level, myeloid cells in newly diagnosed GBMs exhibited decreased expression of CCL4 (loge fold change -1.18, Bonferroni-adjusted P = 1.62x10-254) and its ligands compared to anaplastic astrocytoma. In ranked gene set enrichment analysis, patients who received neoadjuvant pembrolizumab demonstrated enrichment in TNFα-, NFκB- and lipid metabolism-related gene sets by bootstrapped Kolmogorov-Smirnov test (Benjamini-Hochberg adjusted P = 4.74x10-3, 1.45x10-2 and 2.48x10-3, respectively) in tumor-associated myeloid populations. Additionally, single-cell trajectory analysis demonstrated increased CCL4 and decreased ISG15 with neoadjuvant checkpoint inhibition. CONCLUSIONS Here, we utilize mass cytometry and single-cell RNA sequencing to demonstrate the predominance and transcriptomic features of myeloid populations in GBM. Myeloid cells in patients who receive neoadjuvant PD-1 blockade re-express increased levels NFκB, TNFα and CCL4, a cytokine crucial for the recruitment of dendritic cells to the tumor for antigen-specific T cell activation. By delving into the GBM microenvironment at the single-cell level, we hope to better delineate the role of myeloid populations in this uniformly fatal tumor.

A pooled single-cell genetic screen identifies regulatory checkpoints in the continuum of the epithelial-to-mesenchymal transition.

Integrating single-cell trajectory analysis with pooled genetic screening could reveal the genetic architecture that guides cellular decisions in development and disease. We applied this paradigm to probe the genetic circuitry that controls epithelial-to-mesenchymal transition (EMT). We profiled epithelial cells undergoing a spontaneous, spatially determined EMT in the presence or absence of TGF-β via single-cell RNA-seq. Pseudospatial trajectory analysis identified continuous waves of gene regulation, as opposed to discrete “partial” stages of EMT. KRAS was connected to exit from the epithelial state and acquisition of a fully mesenchymal phenotype. A pooled single-cell CRISPR-Cas9 screen identified EMT-associated receptors and transcription factors, including regulators of KRAS, whose loss impeded progress along EMT. Inhibiting the KRAS effector MEK, and its upstream activators EGFR and MET, demonstrates that interruption of key signaling events reveals regulatory “checkpoints” in the EMT continuum that mimic discrete stages and reconciles opposing views of the program that controls EMT.

Trajectory Algorithms to Infer Stem Cell Fate Decisions.

Single-cell trajectory analysis is an active research area in single-cell genomics aiming at developing sophisticated algorithms to reconstruct complex cell-state transition trajectories. Here, we present a step-by-step protocol to use CellRouter, a multifaceted single-cell analysis platform that integrates subpopulation identification, gene regulatory networks, and trajectory inference to precisely and flexibly reconstruct complex single-cell trajectories. Subpopulations are either user-defined or identified by a graph-clustering approach in which a k-nearest neighbor graph (kNN) is created from cell-to-cell distances in a low-dimensional embedding. Edges in this graph are weighted by network similarity metrics (e.g., Jaccard index) to robustly encode phenotypic relatedness, creating a representation of single-cell transcriptomes suitable for community detection algorithms to identify clusters of densely connected cells. This subpopulation structure represents a map of putative cell-state transitions. CellRouter implements a flow network algorithm to explore this map and reconstruct cell-state transitions in complex single-cell, multidimensional omics datasets. We describe a step-by-step application of CellRouter to hematopoietic stem and progenitor cell differentiation toward four major lineages-erythrocytes, megakaryocytes, monocytes, and granulocytes-to demonstrate key components of CellRouter for single-cell trajectory analysis.

Single-cell trajectory analysis of human homogenous neurons carrying a rare RELN variant

Reelin is a protein encoded by the RELN gene that controls neuronal migration in the developing brain. Human genetic studies suggest that rare RELN variants confer susceptibility to mental disorders such as schizophrenia. However, it remains unknown what effects rare RELN variants have on human neuronal cells. To this end, the analysis of human neuronal dynamics at the single-cell level is necessary. In this study, we generated human-induced pluripotent stem cells carrying a rare RELN variant (RELN-del) using targeted genome editing; cells were further differentiated into highly homogeneous dopaminergic neurons. Our results indicated that RELN-del triggered an impaired reelin signal and decreased the expression levels of genes relevant for cell movement in human neurons. Single-cell trajectory analysis revealed that control neurons possessed directional migration even in vitro, while RELN-del neurons demonstrated a wandering type of migration. We further confirmed these phenotypes in neurons derived from a patient carrying the congenital RELN-del. To our knowledge, this is the first report of the biological significance of a rare RELN variant in human neurons based on individual neuron dynamics. Collectively, our approach should be useful for studying reelin function and evaluating mental disorder susceptibility, focusing on individual human neuronal migration.

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.

Single-cell analysis delineates a trajectory toward the human early otic lineage

Efficient pluripotent stem cell guidance protocols for the production of human posterior cranial placodes such as the otic placode that gives rise to the inner ear do not exist. Here we use a systematic approach including defined monolayer culture, signaling modulation, and single-cell gene expression analysis to delineate a developmental trajectory for human otic lineage specification in vitro. We found that modulation of bone morphogenetic protein (BMP) and WNT signaling combined with FGF and retinoic acid treatments over the course of 18 days generates cell populations that develop chronological expression of marker genes of non-neural ectoderm, preplacodal ectoderm, and early otic lineage. Gene expression along this differentiation path is distinct from other lineages such as endoderm, mesendoderm, and neural ectoderm. Single-cell analysis exposed the heterogeneity of differentiating cells and allowed discrimination of non-neural ectoderm and otic lineage cells from off-target populations. Pseudotemporal ordering of human embryonic stem cell and induced pluripotent stem cell-derived single-cell gene expression profiles revealed an initially synchronous guidance toward non-neural ectoderm, followed by comparatively asynchronous occurrences of preplacodal and otic marker genes. Positive correlation of marker gene expression between both cell lines and resemblance to mouse embryonic day 10.5 otocyst cells implied reasonable robustness of the guidance protocol. Single-cell trajectory analysis further revealed that otic progenitor cell types are induced in monolayer cultures, but further development appears impeded, likely because of lack of a lineage-stabilizing microenvironment. Our results provide a framework for future exploration of stabilizing microenvironments for efficient differentiation of stem cell-generated human otic cell types.