Single-Cell Tracing Dissects Regulation of Maintenance and Inheritance of Transcriptional Reinduction Memory

GTP-dependent regulation of heterochromatin fluctuations at subtelomeric regions in Saccharomyces cerevisiae

In eukaryotes, single cells in a population display different transcriptional profiles. One of the factors regulating this heterogeneity is the chromatin state in each cell. However, the mechanisms of epigenetic chromatin regulation of specific chromosomal regions remain unclear. Therefore, we used single-cell tracking system to analyze IMD2. IMD2 is located at the subtelomeric region of budding yeast, and its expression is epigenetically regulated by heterochromatin fluctuations. Treatment with mycophenolic acid, an inhibitor of de novo GTP biosynthesis, triggered a decrease in GTP, which caused heterochromatin fluctuations at the IMD2 locus. Interestingly, within individually tracked cells, IMD2 expression state underwent repeated switches even though IMD2 is positioned within the heterochromatin region. We also found that 30% of the cells in a population always expressed IMD2. Furthermore, the addition of nicotinamide, a histone deacetylase inhibitor, or guanine, the GTP biosynthesis factor in salvage pathway of GTP biosynthesis, regulated heterogeneity, resulting in IMD2 expression being uniformly induced or suppressed in the population. These results suggest that gene expression heterogeneity in the IMD2 region is regulated by changes in chromatin structure triggered by slight decreases in GTP.

Remembering foods and foes: emerging principles of transcriptional memory

Transcriptional memory is characterized by a primed cellular state, induced by an external stimulus that results in an altered expression of primed genes upon re-exposure to the inducing signal. Intriguingly, the primed state is heritably maintained across somatic cell divisions even after the initial stimulus and target gene transcription cease. This phenomenon is widely observed across various organisms and appears to enable cells to retain a memory of external signals, thereby adapting to environmental changes. Signals range from nutrient supplies (food) to a variety of stress signals, including exposure to pathogens (foes), leading to long-term memory such as in the case of trained immunity in plants and mammals. Here, we review these priming phenomena and our current understanding of transcriptional memory. We consider different mechanistic models for how memory can work and discuss existing evidence for potential carriers of memory. Key molecular signatures include: the poising of RNA polymerase II machinery, maintenance of histone marks, as well as alterations in nuclear positioning and long-range chromatin interactions. Finally, we discuss the potential adaptive roles of transcriptional memory in the organismal response to its environment from nutrient sensing to trained immunity.

Towards a Synthesis of the Non-Genetic and Genetic Views of Cancer in Understanding Pancreatic Ductal Adenocarcinoma Initiation and Prevention

While much of the research in oncogenesis and cancer therapy has focused on mutations in key cancer driver genes, more recent work suggests a complementary non-genetic paradigm. This paradigm focuses on how transcriptional and phenotypic heterogeneity, even in clonally derived cells, can create sub-populations associated with oncogenesis, metastasis, and therapy resistance. We discuss this complementary paradigm in the context of pancreatic ductal adenocarcinoma. A better understanding of cellular transcriptional heterogeneity and its association with oncogenesis can lead to more effective therapies that prevent tumor initiation and slow progression.

Differential regulation of mRNA stability modulates transcriptional memory and facilitates environmental adaptation

Transcriptional memory, by which cells respond faster to repeated stimuli, is key for cellular adaptation and organism survival. Chromatin organization has been shown to play a role in the faster response of primed cells. However, the contribution of post-transcriptional regulation is not yet explored. Here we perform a genome-wide screen to identify novel factors modulating transcriptional memory in S. cerevisiae in response to galactose. We find that depletion of the nuclear RNA exosome increases GAL1 expression in primed cells. Our work shows that gene-specific differences in intrinsic nuclear surveillance factor association can enhance both gene induction and repression in primed cells. Finally, we show that primed cells present altered levels of RNA degradation machinery and that both nuclear and cytoplasmic mRNA decay modulate transcriptional memory. Our results demonstrate that mRNA post-transcriptional regulation, and not only transcription regulation, should be considered when investigating gene expression memory.

Altered expression response upon repeated gene repression in single yeast cells

Cells must continuously adjust to changing environments and, thus, have evolved mechanisms allowing them to respond to repeated stimuli. While faster gene induction upon a repeated stimulus is known as reinduction memory, responses to repeated repression have been less studied so far. Here, we studied gene repression across repeated carbon source shifts in over 1,500 single Saccharomyces cerevisiae cells. By monitoring the expression of a carbon source-responsive gene, galactokinase 1 (Gal1), and fitting a mathematical model to the single-cell data, we observed a faster response upon repeated repressions at the population level. Exploiting our single-cell data and quantitative modeling approach, we discovered that the faster response is mediated by a shortened repression response delay, the estimated time between carbon source shift and Gal1 protein production termination. Interestingly, we can exclude two alternative hypotheses, i) stronger dilution because of e.g., increased proliferation, and ii) a larger fraction of repressing cells upon repeated repressions. Collectively, our study provides a quantitative description of repression kinetics in single cells and allows us to pinpoint potential mechanisms underlying a faster response upon repeated repression. The computational results of our study can serve as the starting point for experimental follow-up studies.

Cells have to continuously adjust to their environment and cope with changing temperature, stress conditions, or metabolic resources. Yeast cells exposed to repeated carbon source shifts have shown to be “primed” by their first exposure, exhibiting enhanced gene expression of specific genes later on. However, how cells respond to a repeated repressive stimulus, e.g., withdrawal of metabolic resources, has been so far much less studied.

For this, we investigated the expression kinetics of a carbon source-responsive gene across repeated repressions. We measured single-cell expression and used mathematical modeling to evaluate potential causes underlying an observed faster repression response upon a repeated stimulus. Specifically, we investigated whether i) an increased dilution due to e.g., proliferation, ii) an increased fraction of repressing cells, or iii) different kinetic parameters in the repeated repression cause the observed faster response in the second repression. Leveraging quantitative mathematical model comparison, we discovered that the faster response is mediated by a shortened estimated time between carbon source shift and protein production termination at the single-cell level.

Our study provides a quantitative description of repression kinetics in single cells and allows us to pinpoint potential mechanisms underlying a faster response upon repeated repression.

Do microbes have a memory? History-dependent behavior in the adaptation to variable environments

Microbes are constantly confronted with changes and challenges in their environment. A proper response to these environmental cues is needed for optimal cellular functioning and fitness. Interestingly, past exposure to environmental cues can accelerate or boost the response when this condition returns, even in daughter cells that have not directly encountered the initial cue. Moreover, this behavior is mostly epigenetic and often goes hand in hand with strong heterogeneity in the strength and speed of the response between isogenic cells of the same population, which might function as a bet-hedging strategy. In this review, we discuss examples of history-dependent behavior (HDB) or “memory,” with a specific focus on HDB in fluctuating environments. In most examples discussed, the lag time before the response to an environmental change is used as an experimentally measurable proxy for HDB. We highlight different mechanisms already implicated in HDB, and by using HDB in fluctuating carbon conditions as a case study, we showcase how the metabolic state of a cell can be a key determining factor for HDB. Finally, we consider possible evolutionary causes and consequences of such HDB.

DetecDiv, a generalist deep-learning platform for automated cell division tracking and survival analysis

Automating the extraction of meaningful temporal information from sequences of microscopy images represents a major challenge to characterize dynamical biological processes. So far, strong limitations in the ability to quantitatively analyze single-cell trajectories have prevented large-scale investigations to assess the dynamics of entry into replicative senescence in yeast. Here, we have developed DetecDiv, a microfluidic-based image acquisition platform combined with deep learning-based software for high-throughput single-cell division tracking. We show that DetecDiv can automatically reconstruct cellular replicative lifespans with high accuracy and performs similarly with various imaging platforms and geometries of microfluidic traps. In addition, this methodology provides comprehensive temporal cellular metrics using time-series classification and image semantic segmentation. Last, we show that this method can be further applied to automatically quantify the dynamics of cellular adaptation and real-time cell survival upon exposure to environmental stress. Hence, this methodology provides an all-in-one toolbox for high-throughput phenotyping for cell cycle, stress response, and replicative lifespan assays.

Proteasome-dependent truncation of the negative heterochromatin regulator Epe1 mediates antifungal resistance

Epe1 histone demethylase restricts H3K9-methylation-dependent heterochromatin, preventing it from spreading over, and silencing, gene-containing regions in fission yeast. External stress induces an adaptive response allowing heterochromatin island formation that confers resistance on surviving wild-type lineages. Here we investigate the mechanism by which Epe1 is regulated in response to stress. Exposure to caffeine or antifungals results in Epe1 ubiquitylation and proteasome-dependent removal of the N-terminal 150 residues from Epe1, generating truncated Epe1 (tEpe1) which accumulates in the cytoplasm. Constitutive tEpe1 expression increases H3K9 methylation over several chromosomal regions, reducing expression of underlying genes and enhancing resistance. Reciprocally, constitutive non-cleavable Epe1 expression decreases resistance. tEpe1-mediated resistance requires a functional JmjC demethylase domain. Moreover, caffeine-induced Epe1-to-tEpe1 cleavage is dependent on an intact cell integrity MAP kinase stress signaling pathway, mutations in which alter resistance. Thus, environmental changes elicit a mechanism that curtails the function of this key epigenetic modifier, allowing heterochromatin to reprogram gene expression, thereby bestowing resistance to some cells within a population. H3K9me-heterochromatin components are conserved in human and crop-plant fungal pathogens for which a limited number of antifungals exist. Our findings reveal how transient heterochromatin-dependent antifungal resistant epimutations develop and thus inform on how they might be countered.

Live cell microscopy: From image to insight

Live-cell microscopy is a powerful tool that can reveal cellular behavior as well as the underlying molecular processes. A key advantage of microscopy is that by visualizing biological processes, it can provide direct insights. Nevertheless, live-cell imaging can be technically challenging and prone to artifacts. For a successful experiment, many careful decisions are required at all steps from hardware selection to downstream image analysis. Facing these questions can be particularly intimidating due to the requirement for expertise in multiple disciplines, ranging from optics, biophysics, and programming to cell biology. In this review, we aim to summarize the key points that need to be considered when setting up and analyzing a live-cell imaging experiment. While we put a particular focus on yeast, many of the concepts discussed are applicable also to other organisms. In addition, we discuss reporting and data sharing strategies that we think are critical to improve reproducibility in the field.

Single-cell image analysis to explore cell-to-cell heterogeneity in isogenic populations

Single-cell image analysis provides a powerful approach for studying cell-to-cell heterogeneity, which is an important attribute of isogenic cell populations, from microbial cultures to individual cells in multicellular organisms. This phenotypic variability must be explained at a mechanistic level if biologists are to fully understand cellular function and address the genotype-to-phenotype relationship. Variability in single-cell phenotypes is obscured by bulk readouts or averaging of phenotypes from individual cells in a sample; thus, single-cell image analysis enables a higher resolution view of cellular function. Here, we consider examples of both small- and large-scale studies carried out with isogenic cell populations assessed by fluorescence microscopy, and we illustrate the advantages, challenges, and the promise of quantitative single-cell image analysis.

Microfluidics for single-cell lineage tracking over time to characterize transmission of phenotypes in Saccharomyces cerevisiae

The budding yeast Saccharomyces cerevisiae is an excellent model organism to dissect the maintenance and inheritance of phenotypes due to its asymmetric division. This requires following individual cells over time as they go through divisions to define pedigrees. Here, we provide a detailed protocol for collecting and analyzing time-lapse imaging data of yeast cells. The microfluidics protocol can achieve improved time resolution for single-cell tracking to enable characterization of maintenance and inheritance of phenotypes. For complete details on the use and execution of this protocol, please refer to Bheda et al. (2020a).

Sustained TNF-α stimulation leads to transcriptional memory that greatly enhances signal sensitivity and robustness

Transcriptional memory allows certain genes to respond to previously experienced signals more robustly. However, whether and how the key proinflammatory cytokine TNF-α mediates transcriptional memory are poorly understood. Using HEK293F cells as a model system, we report that sustained TNF-α stimulation induces transcriptional memory dependent on TET enzymes. The hypomethylated status of transcriptional regulatory regions can be inherited, facilitating NF-κB binding and more robust subsequent activation. A high initial methylation level and CpG density around κB sites are correlated with the functional potential of transcriptional memory modules. Interestingly, the CALCB gene, encoding the proven migraine therapeutic target CGRP, exhibits the best transcriptional memory. A neighboring primate-specific endogenous retrovirus stimulates more rapid, more strong, and at least 100-fold more sensitive CALCB induction in subsequent TNF-α stimulation. Our study reveals that TNF-α-mediated transcriptional memory is governed by active DNA demethylation and greatly sensitizes memory genes to much lower doses of inflammatory cues.

Genes are the instruction manuals of life and contain the information needed to build the building blocks that keep cells alive. To read these instructions, cells use specific signals that activate genes. The process, known as gene expression, is tightly controlled and for the most part, fairly stable. But gene expression can be modified in various ways.

Epigenetics is a broad term for describing reversible changes made to genes to switch them on and off. Sometimes, certain genes even develop a kind of ‘transcriptional memory’ where over time, their expression is enhanced and speeds up with repeated activation signals. But this may also have harmful effects.

For example, the signalling molecule called tumour necrosis factor α (TNF-α) is an essential part of the immune system. But it is also implicated in chronic inflammatory diseases, such as rheumatoid arthritis. In these conditions, cell signalling pathways triggering inflammation are overactive. One possibility is that TNF-α could be inducing the transcriptional memory of certain genes, amplifying their expression. But little is known about which fraction of genes exhibits transcriptional memory, and what differentiates memory genes from genes with stable expression.

Here, Zhao et al. treated cells grown in the laboratory with TNF-α to investigate its role in transcriptional memory and find out what epigenetic features might govern the process. The experiments showed that mimicking a sustained inflammation by stimulating TNF-α, triggered a transcriptional memory in some genes, and enabled them to respond to much lower levels of TNF-α on subsequent exposure.

Zhao et al. also discovered that genes tagged with methyl groups are more likely to show transcriptional memory when stimulated by TNF-α. However, they also found that these groups must be removed to consolidate any transcriptional memory.

This work shows how TNF-α influences can alter the expression of certain genes. It also suggests that transcriptional memory, stimulated by TNF-α, may be a possible mechanism underlying chronic inflammatory conditions. This could help future research in identifying more genes with transcriptional memory.

Activation of Clustered IFNγ Target Genes Drives Cohesin-Controlled Transcriptional Memory

Cytokine activation of cells induces gene networks involved in inflammation and immunity. Transient gene activation can have a lasting effect even in the absence of ongoing transcription, known as long-term transcriptional memory. Here we explore the nature of the establishment and maintenance of interferon γ (IFNγ)-induced priming of human cells. We find that, although ongoing transcription and local chromatin signatures are short-lived, the IFNγ-primed state stably propagates through at least 14 cell division cycles. Single-cell analysis reveals that memory is manifested by an increased probability of primed cells to engage in target gene expression, correlating with the strength of initial gene activation. Further, we find that strongly memorized genes tend to reside in genomic clusters and that long-term memory of these genes is locally restricted by cohesin. We define the duration, stochastic nature, and molecular mechanisms of IFNγ-induced transcriptional memory, relevant to understanding enhanced innate immune signaling.

The past determines the future: sugar source history and transcriptional memory

Transcriptional reinduction memory is a phenomenon whereby cells “remember” their transcriptional response to a previous stimulus such that subsequent encounters with the same stimulus can result in altered gene expression kinetics. Chromatin structure is thought to play a role in certain transcriptional memory mechanisms, leading to questions as to whether and how memory can be actively maintained and inherited to progeny through cell division. Here we summarize efforts towards dissecting chromatin-based transcriptional memory inheritance of GAL genes in Saccharomyces cerevisiae. We focus on methods and analyses of GAL (as well as MAL and INO) memory in single cells and discuss the challenges in unraveling the underlying mechanisms in yeast and higher eukaryotes.