Concepts and limitations for learning developmental trajectories from single cell genomics

Tritschler, Sophie; Büttner, Maren; Fischer, David; Lange, Marius; Bergen, Volker; Lickert, Heiko; Theis, Fabian J.

doi:10.1242/dev.170506

Cited by 190 publications

(202 citation statements)

References 93 publications

(132 reference statements)

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“…Trajectory inference using pseudotemporal ordering requires an assumption on an initial cell state (i.e. the "root" of the trajectory) and direction of the trajectory (33). Here, we based our analysis on the assumption that between day 1 and 5 after MI, macrophages in the infarcted heart essentially derive from recruited Ly6C hi monocytes, a notion supported by previous literature (2), (6) and our own observations.…”

Section: Trajectory Inference Analysis Reveals Two Main Pathways Of Mmentioning

confidence: 80%

Single-cell transcriptomic profiling maps monocyte/macrophage transitions after myocardial infarction in mice

Rizzo

Vafadarnejad

Arampatzi

et al. 2020

Preprint

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RationaleMonocytes and macrophages have a critical and dual role in post-ischemic cardiac repair, as they can foster both tissue healing and damage. To decipher how monocytes/macrophages acquire heterogeneous functional phenotypes in the ischemic myocardium, we profiled the gene expression dynamics at the single-cell level in circulating and cardiac monocytes/macrophages following experimental myocardial infarction (MI) in mice. Methods and resultsUsing time-series single-cell transcriptome and cell surface epitope analysis of blood and cardiac monocytes/macrophages, as well as the integration of publicly available and independently generated single-cell RNA-seq data, we tracked the transitions in circulating and cardiac monocyte/macrophage states from homeostatic conditions up to 11 days after MI in mice. We show that MI induces marked and rapid transitions in the cardiac mononuclear phagocyte population, with almost complete disappearance of tissue resident macrophages 1 day after ischemia, and rapid infiltration of monocytes that locally acquire discrete and timedependent transcriptional states within 3 to 7 days. Ischemic injury induced a shift of circulating monocytes towards granulocyte-like transcriptional features (Chil3, Lcn2, Prtn3). Trajectory inference analysis indicated that while conversion to Ly6C low monocytes appears as the default fate of Ly6C hi monocytes in the blood, infiltrated monocytes acquired diverse gene expression signatures in the injured heart, notably transitioning to two main MI-associated macrophage populations characterized by MHCII hi and Trem2 hi Igf1 hi gene expression signatures. Minor ischemia-associated macrophage populations with discrete gene expression signature suggesting specialized functions in e.g. iron handling or lipid metabolism were also observed.We further identified putative transcriptional regulators and new cell surface markers of cardiac monocyte/macrophage states. ConclusionsAltogether, our work provides a comprehensive landscape of circulating and cardiac monocyte/macrophage states and their regulators after MI, and will help to further understand their contribution to post-myocardial infarction heart repair.

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Section: Trajectory Inference Analysis Reveals Two Main Pathways Of Mmentioning

confidence: 80%

Single-cell transcriptomic profiling maps monocyte/macrophage transitions after myocardial infarction in mice

Rizzo

Vafadarnejad

Arampatzi

et al. 2020

Preprint

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“…We used a staged approach by first conducting a 'bird's-eye' experiment surveying whole-lung single cell suspensions at 6 timepoints, followed by a targeted 'sky dive' analysis 31 of epithelial cells with a higher longitudinal resolution at 18 timepoints after injury. Leveraging the power of pseudotemporal modeling 20,21,56,57 , we analyzed gene regulation during epithelial transdifferentiation, laying out the sequence of gene expression programs and highlighting key transcriptional regulators. Our inferred cell fate model was validated by correspondence with the real timepoints of sampling, RNA velocities of individual cells and lineage tracing experiments.…”

Section: Discussionmentioning

confidence: 99%

Longitudinal single cell transcriptomics reveals Krt8+ alveolar epithelial progenitors in lung regeneration

Strunz

Ansari

et al. 2019

Preprint

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Lung disease is a major health burden accounting for one in six deaths globally 1 . The lung's large surface area is exposed to a great variety of environmental and microbial insults causing injuries to its epithelium that require a regenerative response mediated by tissue-resident stem and progenitor Lung injury activates quiescent stem and progenitor cells to regenerate alveolar structures. The sequence and coordination of transcriptional programs during this process has largely remained elusive. Using single cell RNA-seq, we first generated a whole-organ bird's-eye view on cellular dynamics and cell-cell communication networks during mouse lung regeneration from ~30,000 cells at six timepoints. We discovered an injury-specific progenitor cell state characterized by Krt8 in flat epithelial cells covering alveolar surfaces. The number of these cells peaked during fibrogenesis in independent mouse models, as well as in human acute lung injury and fibrosis. Krt8+ progenitors featured a highly distinct connectome of receptor-ligand pairs with endothelial cells, fibroblasts, and macrophages. To 'sky dive' into epithelial differentiation dynamics, we sequenced >30,000 sorted epithelial cells at 18 timepoints and computationally derived cell state trajectories that were validated by lineage tracing genetic reporter mice. Airway stem cells within the club cell lineage and alveolar type-2 cells underwent transcriptional convergence onto the same Krt8+ progenitor cell state, which later resolved by terminal differentiation into alveolar type-1 cells. We derived distinct transcriptional regulators as key switch points in this process and show that induction of TNF-alpha/NFkappaB, p53, and hypoxia driven gene expression programs precede a Sox4, Ctnnb1, and Wwtr1 driven switch towards alveolar type-1 cell fate. We show that epithelial cell plasticity can induce non-gradual transdifferentiation, involving intermediate progenitor cell states that may persist and promote disease if checkpoint signals for terminal differentiation are perturbed.

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“…Monocle and related algorithms have since been applied to reveal the relationships of different immune cells and their progenitors during hematopoiesis, infection, and tumorigenesis 8,47,48 . Although these trajectory inferences can connect developmental pathways, the biological interpretation of these data is limited by the need for prior knowledge and the assumption that pseudotemporal ordering is largely based on similarity 49 . In some cases, these inferences may reflect the continuum of cellular states, rather than real developmental relationships.…”

Section: Single‐cell Sequencing Technologiesmentioning

confidence: 99%

Unravelling the heterogeneity and dynamic relationships of tumor-infiltrating T cells by single-cell RNA sequencing analysis

Chaudhry

Rapaport

et al. 2020

Journal of Leukocyte Biology

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T cells are crucial for the success of immune‐based cancer therapy. Reinvigorating antitumor T cell activity by blocking checkpoint inhibitory receptors has provided clinical benefits for many cancer patients. However, the efficacy of these treatments varies in cancer patients and the mechanisms underlying these diverse responses remain elusive. The density and status of tumor‐infiltrating T cells have been shown to positively correlate with patient response to checkpoint blockades. Therefore, further understanding of the heterogeneity, clonal expansion, migration, and effector functions of tumor‐infiltrating T cells will provide fundamental insights into antitumor immune responses. To this end, recent advances in single‐cell RNA sequencing technology have enabled profound and extensive characterization of intratumoral immune cells and have improved our understanding of their dynamic relationships. Here, we summarize recent progress in single‐cell RNA sequencing technology and current strategies to uncover heterogeneous tumor‐infiltrating T cell subsets. In particular, we discuss how the coupling of deep transcriptome information with T cell receptor (TCR)‐based lineage tracing has furthered our understanding of intratumoral T cell populations. We also discuss the functional implications of various T cell subsets in tumors and highlight the identification of novel T cell markers with therapeutic or prognostic potential.

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Concepts and limitations for learning developmental trajectories from single cell genomics

Cited by 190 publications

References 93 publications

Single-cell transcriptomic profiling maps monocyte/macrophage transitions after myocardial infarction in mice

Single-cell transcriptomic profiling maps monocyte/macrophage transitions after myocardial infarction in mice

Longitudinal single cell transcriptomics reveals Krt8+ alveolar epithelial progenitors in lung regeneration

Unravelling the heterogeneity and dynamic relationships of tumor-infiltrating T cells by single-cell RNA sequencing analysis

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