Cell and molecular transitions during efficient dedifferentiation

Continuous emergence of phototaxis in Dictyostelium discoideum

The evolutionary transition from uni- to multicellularity is associated with new properties resulting from collective cell behavior. The social amoeba Dictyostelium discoideum alternating between individual cells and multicellular forms of varying size provides a powerful biological system to characterize such emergent properties. Multicellular forms coined slugs have long been described as chemotactic towards cAMP, and also as phototactic. While chemotaxis is also well-documented at the single-cell level, which explains slug chemotaxis, we asked whether slug phototaxis is an emergent property of multicellularity. For this, we developed an automated microscopy setup to quantify and compare the migration trajectories of single cells and slugs moving in the dark or illuminated with lateral light. We find that single cells, either extracted from phototactic slugs or taken prior to multicellular aggregation, are not phototactic, implying that slug phototaxis results from interactions between cells that lack this property. Further, by analysing slugs composed of a varying number of cells, we find that phototaxis efficiency increases continuously with slug size. Cell-cell interactions combined with self-organization are thus key elements for this property to emerge.

Multi-color fluorescence live-cell imaging in Dictyostelium discoideum

The cellular slime mold Dictyostelium discoideum, a member of the Amoebozoa, has been extensively studied in cell and developmental biology. D. discoideum is unique in that they are genetically tractable, with a wealth of data accumulated over half a century of research. Fluorescence live-cell imaging of D. discoideum has greatly facilitated studies on fundamental topics, including cytokinesis, phagocytosis, and cell migration. Additionally, its unique life cycle places Dictyostelium at the forefront of understanding aggregative multicellularity, a recurring evolutionary trait found across the Opisthokonta and Amoebozoa clades. The use of multiple fluorescent proteins (FP) and labels with separable spectral properties is critical for tracking cells in aggregates and identifying co-occurring biomolecular events and factors that underlie the dynamics of the cytoskeleton, membrane lipids, second messengers, and gene expression. However, in D. discoideum, the number of frequently used FP species is limited to two or three. In this study, we explored the use of new-generation FP for practical 4- to 5-color fluorescence imaging of D. discoideum. We showed that the yellow fluorescent protein Achilles and the red fluorescent protein mScarlet-I both yield high signals and allow sensitive detection of rapid gene induction. The color palette was further expanded to include blue (mTagBFP2 and mTurquosie2), large Stoke-shift LSSmGFP, and near-infrared (miRFP670nano3) FPs, in addition to the HaloTag ligand SaraFluor 650T. Thus, we demonstrated the feasibility of deploying 4- and 5- color imaging of D. discoideum using conventional confocal microscopy.Key words: fluorescence imaging, organelle, cytoskeleton, small GTPase, Dictyostelium.

Evolutionary stability of developmental commitment

Evolution of unicellular to multicellular organisms must resolve conflicts in reproductive interests between individual cells and the group. The social amoeba Dictyostelium discoideum is a soil-living eukaryote with facultative sociality. While cells grow in the presence of nutrients, cells aggregate under starvation to form fruiting bodies containing spores and altruistic stalk cells. Once cells socially committed, they complete formation of fruiting bodies, even if a new source of nutrients becomes available. The persistence of this social commitment raises questions as it inhibits individual cells from swiftly returning to solitary growth. I hypothesize that traits enabling premature de-commitment are hindered from being selected. Recent work has revealed outcomes of the premature de-commitment through forced refeeding; The de-committed cells take an altruistic prestalk-like position due to their reduced cohesiveness through interactions with socially committed cells. I constructed an evolutionary model assuming their division of labor. The results revealed a valley in the fitness landscape that prevented invasion of de-committing mutants, indicating evolutionary stability of the social commitment. The findings provide a general scheme that maintains multicellularity by evolving a specific division of labor, in which less cohesive individuals become altruists.

The indispensable role of time in autonomous development

Advances in single-cell analysis have led to a picture of development largely in agreement with Waddington's eponymous epigenetic landscape, in which a cell's fate is determined by its basin of attraction in a high-dimensional gene-expression space. Yet conceptual gaps remain as to how a single progenitor can simultaneously generate multiple endpoints, and why time should be required of the process at all. We propose a theoretical model based on the Hamiltonian mechanics of n-dimensional rotational motion, which resolves these paradoxes. We derive the result that systems which become different from themselves over time must initially move in a direction not towards their ultimate endpoints, and propose that this process of resolving ambiguity can be quantified (in an information-theoretic sense) by the volume subtended in gene-expression space by the trajectories taken by the system towards its endpoints. We discuss the implications of this theory for the analysis of single-cell gene-expression data in studies of development.

Multi-omics analysis of aggregative multicellularity

All organisms have to carefully regulate their gene expression, not least during development. mRNA levels are often used as proxy for protein output; however, this approach ignores post-transcriptional effects. In particular, mRNA-protein correlation remains elusive for organisms that exhibit aggregative rather than clonal multicellularity. We addressed this issue by generating a paired transcriptomics and proteomics time series during the transition from uni-to multicellular stage in the social ameba Dictyostelium discoideum. Our data reveals that mRNA and protein levels correlate highly during unicellular growth, but decrease when multicellular development is initiated. This accentuates that transcripts alone cannot accurately predict protein levels. The dataset provides a useful resource to study gene expression during aggregative multicellular development. Additionally, our study provides an example of how to analyze and visualize mRNA and protein levels, which should be broadly applicable to other organisms and conditions.

Dissecting reversible and irreversible single cell state transitions from gene regulatory networks

Understanding cell state transitions and their governing regulatory mechanisms remains one of the fundamental questions in biology. We develop a computational method, state transition inference using cross-cell correlations (STICCC), for predicting reversible and irreversible cell state transitions at single-cell resolution by using gene expression data and a set of gene regulatory interactions. The method is inspired by the fact that the gene expression time delays between regulators and targets can be exploited to infer past and future gene expression states. From applications to both simulated and experimental single-cell gene expression data, we show that STICCC-inferred vector fields capture basins of attraction and irreversible fluxes. By connecting regulatory information with systems' dynamical behaviors, STICCC reveals how network interactions influence reversible and irreversible state transitions. Compared to existing methods that infer pseudotime and RNA velocity, STICCC provides complementary insights into the gene regulation of cell state transitions.

Single Cell Transcriptome Analysis During Development in Dictyostelium

Dictyostelium represents a stripped-down model for understanding how cells make decisions during development. The complete life cycle takes around a day and the fully differentiated structure is composed of only two major cell types. With this apparent reduction in "complexity," single cell transcriptomics has proven to be a valuable tool in defining the features of developmental transitions and cell fate separation events, even providing causal information on how mechanisms of gene expression can feed into cell decision-making. These scientific outputs have been strongly facilitated by the ease of non-disruptive single cell isolation-allowing access to more physiological measures of transcript levels. In addition, the limited number of cell states during development allows the use of more straightforward analysis tools for handling the ensuing large datasets, which provides enhanced confidence in inferences made from the data. In this chapter, we will outline the approaches we have used for handling Dictyostelium single cell transcriptomic data, illustrating how these approaches have contributed to our understanding of cell decision-making during development.

Collective signalling drives rapid jumping between cell states

Development can proceed in 'fits and starts', with rapid transitions between cell states involving concerted transcriptome-wide changes in gene expression. However, it is not clear how these transitions are regulated in complex cell populations, in which cells receive multiple inputs. We address this issue using Dictyostelium cells undergoing development in their physiological niche. A continuous single cell transcriptomics time series identifies a sharp 'jump' in global gene expression marking functionally different cell states. By simultaneously imaging the physiological dynamics of transcription and signalling, we show the jump coincides with the onset of collective oscillations of cAMP. Optogenetic control of cAMP pulses shows that different jump genes respond to distinct dynamic features of signalling. Late jump gene expression changes are almost completely dependent on cAMP, whereas transcript changes at the onset of the jump require additional input. The coupling of collective signalling with gene expression is a potentially powerful strategy to drive robust cell state transitions in heterogeneous signalling environments. Based on the context of the jump, we also conclude that sharp gene expression transitions may not be sufficient for commitment.

Evidence for close molecular proximity between reverting and undifferentiated cells

BACKGROUND

According to Waddington's epigenetic landscape concept, the differentiation process can be illustrated by a cell akin to a ball rolling down from the top of a hill (proliferation state) and crossing furrows before stopping in basins or "attractor states" to reach its stable differentiated state. However, it is now clear that some committed cells can retain a certain degree of plasticity and reacquire phenotypical characteristics of a more pluripotent cell state. In line with this dynamic model, we have previously shown that differentiating cells (chicken erythrocytic progenitors (T2EC)) retain for 24 h the ability to self-renew when transferred back in self-renewal conditions. Despite those intriguing and promising results, the underlying molecular state of those "reverting" cells remains unexplored. The aim of the present study was therefore to molecularly characterize the T2EC reversion process by combining advanced statistical tools to make the most of single-cell transcriptomic data. For this purpose, T2EC, initially maintained in a self-renewal medium (0H), were induced to differentiate for 24H (24H differentiating cells); then, a part of these cells was transferred back to the self-renewal medium (48H reverting cells) and the other part was maintained in the differentiation medium for another 24H (48H differentiating cells). For each time point, cell transcriptomes were generated using scRT-qPCR and scRNAseq.

RESULTS

Our results showed a strong overlap between 0H and 48H reverting cells when applying dimensional reduction. Moreover, the statistical comparison of cell distributions and differential expression analysis indicated no significant differences between these two cell groups. Interestingly, gene pattern distributions highlighted that, while 48H reverting cells have gene expression pattern more similar to 0H cells, they are not completely identical, which suggest that for some genes a longer delay may be required for the cells to fully recover. Finally, sparse PLS (sparse partial least square) analysis showed that only the expression of 3 genes discriminates 48H reverting and 0H cells.

CONCLUSIONS

Altogether, we show that reverting cells return to an earlier molecular state almost identical to undifferentiated cells and demonstrate a previously undocumented physiological and molecular plasticity during the differentiation process, which most likely results from the dynamic behavior of the underlying molecular network.

Cell plasticity in regeneration in the stomach and beyond

Recent studies using cell lineage-tracing techniques, organoids, and single-cell RNA sequencing analyses have revealed: 1) adult organs use cell plasticity programs to recruit progenitor cells to regenerate tissues after injury, and 2) plasticity is far more common than previously thought, even in homeostasis. Here, we focus on the complex interplay of normal stem cell differentiation and plasticity in homeostasis and after injury, using the gastric epithelium as a touchstone. We also examine common features of regenerative programs and discuss the evolutionarily conserved, stepwise process of paligenosis which reprograms mature cells into progenitors that can repair damaged tissue. Finally, we discuss how conserved plasticity programs may help us better understand pathological processes like metaplasia.

Paligenosis: Cellular Remodeling During Tissue Repair

Complex multicellular organisms have evolved specific mechanisms to replenish cells in homeostasis and during repair. Here, we discuss how emerging technologies (e.g., single-cell RNA sequencing) challenge the concept that tissue renewal is fueled by unidirectional differentiation from a resident stem cell. We now understand that cell plasticity, i.e., cells adaptively changing differentiation state or identity, is a central tissue renewal mechanism. For example, mature cells can access an evolutionarily conserved program (paligenosis) to reenter the cell cycle and regenerate damaged tissue. Most tissues lack dedicated stem cells and rely on plasticity to regenerate lost cells. Plasticity benefits multicellular organisms, yet it also carries risks. For one, when long-lived cells undergo paligenotic, cyclical proliferation and redif-ferentiation, they can accumulate and propagate acquired mutations that activate oncogenes and increase the potential for developing cancer. Lastly, we propose a new framework for classifying patterns of cell proliferation in homeostasis and regeneration, with stem cells representing just one of the diverse methods that adult tissues employ.

Cell state transitions: definitions and challenges

A fundamental challenge when studying biological systems is the description of cell state dynamics. During transitions between cell states, a multitude of parameters may change - from the promoters that are active, to the RNAs and proteins that are expressed and modified. Cells can also adopt different shapes, alter their motility and change their reliance on cell-cell junctions or adhesion. These parameters are integral to how a cell behaves and collectively define the state a cell is in. Yet, technical challenges prevent us from measuring all of these parameters simultaneously and dynamically. How, then, can we comprehend cell state transitions using finite descriptions? The recent virtual workshop organised by The Company of Biologists entitled 'Cell State Transitions: Approaches, Experimental Systems and Models' attempted to address this question. Here, we summarise some of the main points that emerged during the workshop's themed discussions. We also present examples of cell state transitions and describe models and systems that are pushing forward our understanding of how cells rewire their state.

Transcriptional milestones in Dictyostelium development

Dictyostelium development begins with single-cell starvation and ends with multicellular fruiting bodies. Developmental morphogenesis is accompanied by sweeping transcriptional changes, encompassing nearly half of the 13,000 genes in the genome. We performed time-series RNA-sequencing analyses of the wild type and 20 mutants to explore the relationships between transcription and morphogenesis. These strains show developmental arrest at different stages, accelerated development, or atypical morphologies. Considering eight major morphological transitions, we identified 1371 milestone genes whose expression changes sharply between consecutive transitions. We also identified 1099 genes as members of 21 regulons, which are groups of genes that remain coordinately regulated despite the genetic, temporal, and developmental perturbations. The gene annotations in these groups validate known transitions and reveal new developmental events. For example, DNA replication genes are tightly coregulated with cell division genes, so they are expressed in mid-development although chromosomal DNA is not replicated. Our data set includes 486 transcriptional profiles that can help identify new relationships between transcription and development and improve gene annotations. We show its utility by showing that cycles of aggregation and disaggregation in allorecognition-defective mutants involve dedifferentiation. We also show sensitivity to genetic and developmental conditions in two commonly used actin genes, act6 and act15, and robustness of the coaA gene. Finally, we propose that gpdA is a better mRNA quantitation standard because it is less sensitive to external conditions than commonly used standards. The data set is available for democratized exploration through the web application dictyExpress and the data mining environment Orange.

Identification of long regulatory elements in the genome of Plasmodium falciparum and other eukaryotes

Long regulatory elements (LREs), such as CpG islands, polydA:dT tracts or AU-rich elements, are thought to play key roles in gene regulation but, as opposed to conventional binding sites of transcription factors, few methods have been proposed to formally and automatically characterize them. We present here a computational approach named DExTER (Domain Exploration To Explain gene Regulation) dedicated to the identification of candidate LREs (cLREs) and apply it to the analysis of the genomes of P. falciparum and other eukaryotes. Our analyses show that all tested genomes contain several cLREs that are somewhat conserved along evolution, and that gene expression can be predicted with surprising accuracy on the basis of these long regions only. Regulation by cLREs exhibits very different behaviours depending on species and conditions. In P. falciparum and other Apicomplexan organisms as well as in Dictyostelium discoideum, the process appears highly dynamic, with different cLREs involved at different phases of the life cycle. For multicellular organisms, the same cLREs are involved in all tissues, but a dynamic behavior is observed along embryonic development stages. In P. falciparum, whose genome is known to be strongly depleted of transcription factors, cLREs are predictive of expression with an accuracy above 70%, and our analyses show that they are associated with both transcriptional and post-transcriptional regulation signals. Moreover, we assessed the biological relevance of one LRE discovered by DExTER in P. falciparum using an in vivo reporter assay. The source code (python) of DExTER is available at https://gite.lirmm.fr/menichelli/DExTER.

Phytocannabinoid-dependent mTORC1 regulation is dependent upon inositol polyphosphate multikinase activity

BACKGROUND AND PURPOSE

Cannabidiol (CBD) has been shown to differentially regulate the mechanistic target of rapamycin complex 1 (mTORC1) in preclinical models of disease, where it reduces activity in models of epilepsies and cancer and increases it in models of multiple sclerosis (MS) and psychosis. Here, we investigate the effects of phytocannabinoids on mTORC1 and define a molecular mechanism.

EXPERIMENTAL APPROACH

A novel mechanism for phytocannabinoids was identified using the tractable model system, Dictyostelium discoideum. Using mouse embryonic fibroblasts, we further validate this new mechanism of action. We demonstrate clinical relevance using cells derived from healthy individuals and from people with MS (pwMS).

KEY RESULTS

Both CBD and the more abundant cannabigerol (CBG) enhance mTORC1 activity in D. discoideum. We identify a mechanism for this effect involving inositol polyphosphate multikinase (IPMK), where elevated IPMK expression reverses the response to phytocannabinoids, decreasing mTORC1 activity upon treatment, providing new insight on phytocannabinoids' actions. We further validated this mechanism using mouse embryonic fibroblasts. Clinical relevance of this effect was shown in primary human peripheral blood mononuclear cells, where CBD and CBG treatment increased mTORC1 activity in cells derived from healthy individuals and decreased mTORC1 activity in cells derived from pwMS.

CONCLUSION AND IMPLICATIONS

Our findings suggest that both CBD and the abundant CBG differentially regulate mTORC1 signalling through a mechanism dependent on the activity of the upstream IPMK signalling pathway, with potential relevance to the treatment of mTOR-related disorders, including MS.

Decanoic acid inhibits mTORC1 activity independent of glucose and insulin signaling

The mTORC1 complex provides a critical role in cell function, regulating a variety of processes including growth and autophagy. mTORC1 signaling is hyperactivated in a range of common diseases including cancer, epilepsy, and neurodegenerative disorders. Hence, mTORC1 signaling provides an important target for regulation in many contexts. Here, we show that decanoic acid, a key component of a widely used medicinal diet, reduces mTORC1 activity. We identify this in a tractable model system, and validate it in ex vivo rat brain tissue and in human iPSC-derived astrocytes from patients with a clinically relevant disease. Thus, we provide insight into an easily accessible therapeutic approach for a range of diseases.

Low-glucose and -insulin conditions, associated with ketogenic diets, can reduce the activity of the mechanistic target of rapamycin complex 1 (mTORC1) signaling pathway, potentially leading to a range of positive medical and health-related effects. Here, we determined whether mTORC1 signaling is also a target for decanoic acid, a key component of the medium-chain triglyceride (MCT) ketogenic diet. Using a tractable model system, Dictyostelium, we show that decanoic acid can decrease mTORC1 activity, under conditions of constant glucose and in the absence of insulin, measured by phosphorylation of eukaryotic translation initiation factor 4E-binding protein 1 (4E-BP1). We determine that this effect of decanoic acid is dependent on a ubiquitin regulatory X domain-containing protein, mediating inhibition of a conserved Dictyostelium AAA ATPase, p97, a homolog of the human transitional endoplasmic reticulum ATPase (VCP/p97) protein. We then demonstrate that decanoic acid decreases mTORC1 activity in the absence of insulin and under high-glucose conditions in ex vivo rat hippocampus and in tuberous sclerosis complex (TSC) patient-derived astrocytes. Our data therefore indicate that dietary decanoic acid may provide a new therapeutic approach to down-regulate mTORC1 signaling.

A Dedicated Evolutionarily Conserved Molecular Network Licenses Differentiated Cells to Return to the Cell Cycle

Differentiated cells can re-enter the cell cycle to repair tissue damage via a series of discrete morphological and molecular stages coordinated by the cellular energetics regulator mTORC1. We previously proposed the term "paligenosis" to describe this conserved cellular regeneration program. Here, we detail a molecular network regulating mTORC1 during paligenosis in both mouse pancreatic acinar and gastric chief cells. DDIT4 initially suppresses mTORC1 to induce autodegradation of differentiated cell components and damaged organelles. Later in paligenosis, IFRD1 suppresses p53 accumulation. Ifrd1^-/- cells do not complete paligenosis because persistent p53 prevents mTORC1 reactivation and cell proliferation. Ddit4^-/- cells never suppress mTORC1 and bypass the IFRD1 checkpoint on proliferation. Previous reports and our current data implicate DDIT4/IFRD1 in governing paligenosis in multiple organs and species. Thus, we propose that an evolutionarily conserved, dedicated molecular network has evolved to allow differentiated cells to re-enter the cell cycle (i.e., undergo paligenosis) after tissue injury. VIDEO ABSTRACT.