Author response: Light-dependent single-cell heterogeneity in the chloroplast redox state regulates cell fate in a marine diatom

Recent studies have revealed that extensive heterogeneity of biological systems arises through various routes ranging from intracellular chromosome segregation to spatiotemporally varying biochemical stimulations. However, the contribution of physical microenvironments to single-cell heterogeneity remains largely unexplored. Here, we show that a homogeneous population of non–small-cell lung carcinoma develops into heterogeneous subpopulations upon application of a homogeneous physical compression, as shown by single-cell transcriptome profiling. The generated subpopulations stochastically gain the signature genes associated with epithelial–mesenchymal transition (EMT; VIM, CDH1, EPCAM, ZEB1, and ZEB2) and cancer stem cells (MKI67, BIRC5, and KLF4), respectively. Trajectory analysis revealed two bifurcated paths as cells evolving upon the physical compression, along each path the corresponding signature genes (epithelial or mesenchymal) gradually increase. Furthermore, we show that compression increases gene expression noise, which interplays with regulatory network architecture and thus generates differential cell-fate outcomes. The experimental observations of both single-cell sequencing and single-molecule fluorescent in situ hybridization agrees well with our computational modeling of regulatory network in the EMT process. These results demonstrate a paradigm of how mechanical stimulations impact cell-fate determination by altering transcription dynamics; moreover, we show a distinct path that the ecology and evolution of cancer interplay with their physical microenvironments from the view of mechanobiology and systems biology, with insight into the origin of single-cell heterogeneity.

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Single-cell analyses uncover granularity of muscle stem cells

F1000Research ◽

10.12688/f1000research.20856.1 ◽

2020 ◽

Vol 9 ◽

pp. 31 ◽

Cited By ~ 1

Author(s):

John Saber ◽

Alexander Y.T. Lin ◽

Michael A. Rudnicki

Keyword(s):

Single Cell ◽

Cell Fate ◽

Satellite Cells ◽

Muscle Regeneration ◽

Single Cell Analysis ◽

Cell Analysis ◽

Cell Heterogeneity ◽

Muscle Stem Cells ◽

Cell Fate Decisions ◽

Cell Groups

Satellite cells are the main muscle-resident cells responsible for muscle regeneration. Much research has described this population as being heterogeneous, but little is known about the different roles each subpopulation plays. Recent advances in the field have utilized the power of single-cell analysis to better describe and functionally characterize subpopulations of satellite cells as well as other cell groups comprising the muscle tissue. Furthermore, emerging technologies are opening the door to answering as-yet-unresolved questions pertaining to satellite cell heterogeneity and cell fate decisions.

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Single-cell transcriptome reveals the redifferentiation trajectories of the early stage of de novo shoot regeneration in Arabidopsis thaliana

10.1101/2022.01.01.474510 ◽

2022 ◽

Author(s):

Guangyu Liu ◽

Jie Li ◽

Jiming Li ◽

Zhiyong Chen ◽

Peisi Yuan ◽

...

Keyword(s):

Single Cell ◽

Cell Fate ◽

Shoot Regeneration ◽

De Novo ◽

Developmental Process ◽

Early Stage ◽

Cell Populations ◽

Cell Heterogeneity ◽

Cell Transcriptome ◽

Single Cell Transcriptome

De novo shoot regeneration from a callus plays a crucial role in both plant biotechnology and the fundamental research of plant cell totipotency. Recent studies have revealed many regulatory factors involved in this developmental process. However. our knowledge of the cell heterogeneity and cell fate transition during de novo shoot regeneration is still limited. Here, we performed time-series single-cell transcriptome experiments to reveal the cell heterogeneity and redifferentiation trajectories during the early stage of de novo shoot regeneration. Based on the single-cell transcriptome data of 35,669 cells at five-time points, we successfully determined seven major cell populations in this developmental process and reconstructed the redifferentiation trajectories. We found that all cell populations resembled root identities and undergone gradual cell-fate transitions. In detail, the totipotent callus cells differentiated into pluripotent QC-like cells and then gradually developed into less differentiated cells that have multiple root-like cell identities, such as pericycle-like cells. According to the reconstructed redifferentiation trajectories, we discovered that the canonical regeneration-related genes were dynamically expressed at certain stages of the redifferentiation process. Moreover, we also explored potential transcription factors and regulatory networks that might be involved in this process. The transcription factors detected at the initial stage, QC-like cells, and the end stage provided a valuable resource for future functional verifications. Overall, this dataset offers a unique glimpse into the early stages of de novo shoot regeneration, providing a foundation for a comprehensive analysis of the mechanism of de novo shoot regeneration.

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A lineage tree-based hidden Markov model to quantify cellular heterogeneity and plasticity

10.1101/2021.06.25.449922 ◽

2021 ◽

Author(s):

Farnaz Mohammadi ◽

Shakthi Visagan ◽

Sean M Gross ◽

Luka Karginov ◽

JC Lagarde ◽

...

Keyword(s):

Markov Model ◽

Hidden Markov Model ◽

Single Cell ◽

Cell Fate ◽

Drug Response ◽

Hidden Markov ◽

Single Cells ◽

State Transitions ◽

Cycle Phase ◽

Cell Heterogeneity

Cell plasticity, or the ability of cells within a population to reversibly alter their phenotype, is an important feature of tissue homeostasis during processes such as wound healing and cancer. Plasticity operates alongside other sources of cell-to-cell heterogeneity such as genetic mutations and variation in signaling. Ultimately these processes prevent most cancer therapies from being curative. The predominant methods of quantifying tumor-drug response operate on snapshot population-level measurements and therefore lack evolutionary dynamics, which are particularly critical for dynamic processes such as plasticity. Here we apply a tree-based adaptation of a hidden Markov model (tHMM) that employs single cell lineages as input to learn the characteristic patterns of single cell heterogeneity and state transitions in an unsupervised fashion. This model enables single cell classification based on the phenotype of individual cells and their relatives for improved specificity in pinpointing the structure and dynamics of variability in drug response. Integrating this model with a modular interface for defining observed phenotypes allows the model to easily be adapted to any phenotype measured in single cells. To benchmark our model, we paired cell fate with either cell lifetimes or individual cell cycle phase lengths (G1 and S/G2) as our observed phenotypes on synthetic data and demonstrated that the model successfully classifies cells within experimentally tractable dataset sizes. As an application, we analyzed experimental measurements of cell fate and phase duration in cancer cell populations treated with chemotherapies to determine the number of distinct subpopulations. In total, this tHMM framework allows for the flexible classification of single cell heterogeneity across lineages.

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Single-cell heterogeneity in the chloroplast redox state mediates acclimation to stress in a marine diatom

10.1101/319517 ◽

2018 ◽

Author(s):

Avia Mizrachi ◽

Shiri Graff van Creveld ◽

Orr H. Shapiro ◽

Shilo Rosenwasser ◽

Assaf Vardi

Keyword(s):

Single Cell ◽

Cell Fate ◽

Stress Responses ◽

Population Level ◽

Marine Diatom ◽

Photosynthetic Microorganisms ◽

Metabolic Heterogeneity ◽

Cell To Cell Variability ◽

Level Analysis ◽

Redox Dynamics

AbstractDiatoms are photosynthetic microorganisms of great ecological and biogeochemical importance, forming vast blooms in diverse aquatic ecosystems. Current understanding of phytoplankton acclimation to stress is based on population-level analysis, masking cell-to-cell variability. Here we investigated heterogeneity within Phaeodactylum tricornutum populations in response to oxidative stress, which is induced by environmental stress conditions. We combined flow cytometry and a microfluidics system for live imaging to measure redox dynamics at the single-cell level using the roGFP sensor. Chloroplast-targeted roGFP exhibited a light-dependent, bi-stable oxidation pattern in response to H2O2, revealing distinct subpopulations of sensitive oxidized cells and resilient reduced cells. Subpopulation proportions depended on growth phase, linking the bi-stable phenotype to proliferation. Oxidation of chloroplast-targeted roGFP preceded commitment to cell death and was used as a novel cell fate predictor. We propose that light-dependent metabolic heterogeneity results in differential stress responses that regulate cell fate within diatom populations.

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Light-dependent single-cell heterogeneity in the chloroplast redox state regulates cell fate in a marine diatom

eLife ◽

10.7554/elife.47732 ◽

2019 ◽

Vol 8 ◽

Cited By ~ 2

Author(s):

Avia Mizrachi ◽

Shiri Graff van Creveld ◽

Orr H Shapiro ◽

Shilo Rosenwasser ◽

Assaf Vardi

Keyword(s):

Single Cell ◽

Cell Fate ◽

Phaeodactylum Tricornutum ◽

Marine Diatom ◽

Redox Sensor ◽

Fundamental Understanding ◽

Photosynthetic Microorganisms ◽

Sense And Respond ◽

Metabolic Heterogeneity ◽

Cell To Cell Variability

Diatoms are photosynthetic microorganisms of great ecological and biogeochemical importance, forming vast blooms in aquatic ecosystems. However, we are still lacking fundamental understanding of how individual cells sense and respond to diverse stress conditions, and what acclimation strategies are employed during bloom dynamics. We investigated cellular responses to environmental stress at the single-cell level using the redox sensor roGFP targeted to various organelles in the diatom Phaeodactylum tricornutum. We detected cell-to-cell variability using flow cytometry cell sorting and a microfluidics system for live imaging of oxidation dynamics. Chloroplast-targeted roGFP exhibited a light-dependent, bi-stable oxidation pattern in response to H2O2 and high light, revealing distinct subpopulations of sensitive oxidized cells and resilient reduced cells. Early oxidation in the chloroplast preceded commitment to cell death, and can be used for sensing stress cues and regulating cell fate. We propose that light-dependent metabolic heterogeneity regulates diatoms’ sensitivity to environmental stressors in the ocean.

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