A Multiplexed Single-Cell CRISPR Screening Platform Enables Systematic Dissection of the Unfolded Protein Response.

Functional genomics efforts face tradeoffs between number of perturbations examined and complexity of phenotypes measured. We bridge this gap with Perturb-seq, which combines droplet-based single-cell RNA-seq with a strategy for barcoding CRISPR-mediated perturbations, allowing many perturbations to be profiled in pooled format. We applied Perturb-seq to dissect the mammalian unfolded protein response (UPR) using single and combinatorial CRISPR perturbations. Two genome-scale CRISPR interference (CRISPRi) screens identified genes whose repression perturbs ER homeostasis. Subjecting ∼100 hits to Perturb-seq enabled high-precision functional clustering of genes. Single-cell analyses decoupled the three UPR branches, revealed bifurcated UPR branch activation among cells subject to the same perturbation, and uncovered differential activation of the branches across hits, including an isolated feedback loop between the translocon and IRE1α. These studies provide insight into how the three sensors of ER homeostasis monitor distinct types of stress and highlight the ability of Perturb-seq to dissect complex cellular responses.

Direct observation correlates NFκB cRel in B cells with activating and terminating their proliferative program.

Antibody responses require the proliferative expansion of B cells controlled by affinity-dependent signals. Yet, proliferative bursts are heterogeneous, varying between 0 and 8 divisions in response to the same stimulus. NFκB cRel is activated in response to immune stimulation in B cells and is genetically required for proliferation. Here, we asked whether proliferative heterogeneity is controlled by natural variations in cRel abundance. We developed a fluorescent reporter mTFP1-cRel for the direct observation of cRel in live proliferating B cells. We found that cRel is heterogeneously distributed among naïve B cells, which are enriched for high expressors in a heavy-tailed distribution. We found that high cRel expressors show faster activation of the proliferative program, but do not sustain it well, with population expansion decaying earlier. With a mathematical model of the molecular network, we showed that cRel heterogeneity arises from balancing positive feedback by autoregulation and negative feedback by its inhibitor IκBε, confirmed by mouse knockouts. Using live-cell fluorescence microscopy, we showed that increased cRel primes B cells for early proliferation via higher basal expression of the cell cycle driver cMyc. However, peak cMyc induction amplitude is constrained by incoherent feedforward regulation, decoding the fold change of cRel activity to terminate the proliferative burst. This results in a complex nonlinear, nonmonotonic relationship between cRel expression and the extent of proliferation. These findings emphasize the importance of direct observational studies to complement gene knockout results and to learn about quantitative relationships between biological processes and their key regulators in the context of natural variations.

Cell cycle progression and transmitotic apoptosis resistance promote escape from extrinsic apoptosis.

Extrinsic apoptosis relies on TNF-family receptor activation by immune cells or receptor-activating drugs. Here, we monitored cell cycle progression at a resolution of minutes to relate apoptosis kinetics and cell-to-cell heterogeneities in death decisions to cell cycle phases. Interestingly, we found that cells in S phase delay TRAIL receptor-induced death in favour of mitosis, thereby passing on an apoptosis-primed state to their offspring. This translates into two distinct fates, apoptosis execution post mitosis or cell survival from inefficient apoptosis. Transmitotic resistance is linked to Mcl-1 upregulation and its increased accumulation at mitochondria from mid-S phase onwards, which allows cells to pass through mitosis with activated caspase-8, and with cells escaping apoptosis after mitosis sustaining sublethal DNA damage. Antagonizing Mcl-1 suppresses cell cycle-dependent delays in apoptosis, prevents apoptosis-resistant progression through mitosis and averts unwanted survival after apoptosis induction. Cell cycle progression therefore modulates signal transduction during extrinsic apoptosis, with Mcl-1 governing decision making between death, proliferation and survival. Cell cycle progression thus is a crucial process from which cell-to-cell heterogeneities in fates and treatment outcomes emerge in isogenic cell populations during extrinsic apoptosis. This article has an associated First Person interview with the first author of the paper.

Experimental kS estimation: A comparison of methods for Corynebacterium glutamicum from lab to microfluidic scale.

Knowledge about the specific affinity of whole cells toward a substrate, commonly referred to as kS , is a crucial parameter for characterizing growth within bioreactors. State-of-the-art methodologies measure either uptake or consumption rates at different initial substrate concentrations. Alternatively, cell dry weight or respiratory data like online oxygen and carbon dioxide transfer rates can be used to estimate kS . In this work, a recently developed substrate-limited microfluidic single-cell cultivation (sl-MSCC) method is applied for the estimation of kS values under defined environmental conditions. This method is benchmarked with two alternative microtiter plate methods, namely high-frequency biomass measurement (HFB) and substrate-limited respiratory activity monitoring (sl-RA). As a model system, the substrate affinity kS of Corynebacterium glutamicum ATCC 13032 regarding glucose was investigated assuming a Monod-type growth response. A kS of <70.7 mg/L (with 95% probability) with HFB, 8.55 ± 1.38 mg/L with sl-RA, and 2.66 ± 0.99 mg/L with sl-MSCC was obtained. Whereas HFB and sl-RA are suitable for a fast initial kS estimation, sl-MSCC allows an affinity estimation by determining tD at concentrations less or equal to the kS value. Thus, sl-MSCC lays the foundation for strain-specific kS estimations under defined environmental conditions with additional insights into cell-to-cell heterogeneity.

Spontaneous Mutations in Saccharomyces cerevisiae mtDNA Increase Cell-to-Cell Variation in mtDNA Amount.

In a eukaryotic cell, the ratio of mitochondrial DNA (mtDNA) to nuclear DNA (nDNA) is usually maintained within a specific range. This suggests the presence of a negative feedback loop mechanism preventing extensive mtDNA replication and depletion. However, the experimental data on this hypothetical mechanism are limited. In this study, we suggested that deletions in mtDNA, known to increase mtDNA abundance, can disrupt this mechanism, and thus, increase cell-to-cell variance in the mtDNA copy numbers. To test this, we generated Saccharomyces cerevisiae rho- strains with large deletions in the mtDNA and rho0 strains depleted of mtDNA. Given that mtDNA contributes to the total DNA content of exponentially growing yeast cells, we showed that it can be quantified in individual cells by flow cytometry using the DNA-intercalating fluorescent dye SYTOX green. We found that the rho- mutations increased both the levels and cell-to-cell heterogeneity in the total DNA content of G1 and G2/M yeast cells, with no association with the cell size. Furthermore, the depletion of mtDNA in both the rho+ and rho- strains significantly decreased the SYTOX green signal variance. The high cell-to-cell heterogeneity of the mtDNA amount in the rho- strains suggests that mtDNA copy number regulation relies on full-length mtDNA, whereas the rho- mtDNAs partially escape this regulation.

Single-Cell RNA Sequencing for Plant Research: Insights and Possible Benefits.

In recent years, advances in single-cell RNA sequencing (scRNA-seq) technologies have continued to change our views on biological systems by increasing the spatiotemporal resolution of our analysis to single-cell resolution. Application of scRNA-seq to plants enables the comprehensive characterization of both common and rare cell types and cell states, uncovering new cell types and revealing how cell types relate to each other spatially and developmentally. This review provides an overview of scRNA-seq methodologies, highlights the application of scRNA-seq in plant science, justifies why scRNA-seq is a master player of sequencing, and explains the role of single-cell transcriptomics technologies in environmental stress adaptation, alongside the challenges and prospects of single-cell transcriptomics. Collectively, we put forward a central role of single-cell sequencing in plant research.

stochprofML: stochastic profiling using maximum likelihood estimation in R.

BACKGROUND: Tissues are often heterogeneous in their single-cell molecular expression, and this can govern the regulation of cell fate. For the understanding of development and disease, it is important to quantify heterogeneity in a given tissue. RESULTS: We present the R package stochprofML which uses the maximum likelihood principle to parameterize heterogeneity from the cumulative expression of small random pools of cells. We evaluate the algorithm's performance in simulation studies and present further application opportunities. CONCLUSION: Stochastic profiling outweighs the necessary demixing of mixed samples with a saving in experimental cost and effort and less measurement error. It offers possibilities for parameterizing heterogeneity, estimating underlying pool compositions and detecting differences between cell populations between samples.

Quantification of Tetradesmus obliquus (Chlorophyceae) cell size and lipid content heterogeneity at single-cell level.

Much of our current knowledge of microbial growth is obtained from studies at a population level. Driven by the realization that processes that operate within a population might influence a population's behavior, we sought to better understand Tetradesmus obliquus (formerly Scenedesmus obliquus) physiology at the cellular level. In this work, an accurate pretreatment method to quantitatively obtain single cells of T. obliquus, a coenobia-forming alga, is described. These single cells were examined by flow cytometry for triacylglycerol (TAG), chlorophyll, and protein content, and their cell sizes were recorded by coulter counter. We quantified heterogeneity of size and TAG content at single-cell level for a population of T. obliquus during a controlled standard batch cultivation. Unexpectedly, variability of TAG content per cell within the population increased throughout the batch run, up to 400 times in the final stage of the batch run, with values ranging from 0.25 to 99 pg · cell-1 . Two subpopulations, classified as having low or high TAG content per cell, were identified. Cell size also increased during batch growth with average values from 36 to 70 µm3  · cell-1 ; yet cell size variability increased only up to 16 times. Cell size and cellular TAG content were not correlated at the single-cell level. Our data show clearly that TAG production is affected by cell-to-cell variation, which suggests that its control and better understanding of the underlying processes may improve the productivity of T. obliquus for industrial processes such as biodiesel production.

Plasma membranes as heat stress sensors: from lipid-controlled molecular switches to therapeutic applications.

The classic heat shock (stress) response (HSR) was originally attributed to protein denaturation. However, heat shock protein (Hsp) induction occurs in many circumstances where no protein denaturation is observed. Recently considerable evidence has been accumulated to the favor of the "Membrane Sensor Hypothesis" which predicts that the level of Hsps can be changed as a result of alterations to the plasma membrane. This is especially pertinent to mild heat shock, such as occurs in fever. In this condition the sensitivity of many transient receptor potential (TRP) channels is particularly notable. Small temperature stresses can modulate TRP gating significantly and this is influenced by lipids. In addition, stress hormones often modify plasma membrane structure and function and thus initiate a cascade of events, which may affect HSR. The major transactivator heat shock factor-1 integrates the signals originating from the plasma membrane and orchestrates the expression of individual heat shock genes. We describe how these observations can be tested at the molecular level, for example, with the use of membrane perturbers and through computational calculations. An important fact which now starts to be addressed is that membranes are not homogeneous nor do all cells react identically. Lipidomics and cell profiling are beginning to address the above two points. Finally, we observe that a deregulated HSR is found in a large number of important diseases where more detailed knowledge of the molecular mechanisms involved may offer timely opportunities for clinical interventions and new, innovative drug treatments. This article is part of a Special Issue entitled: Membrane Structure and Function: Relevance in the Cell's Physiology, Pathology and Therapy.

Rate control in yeast protein synthesis at the population and single-cell levels.

Yeast commits approximately 76% of its energy budget to protein synthesis and the efficiency and control of this process are accordingly critical to organism growth and fitness. We now have detailed genetic, biochemical and biophysical knowledge of the components of the eukaryotic translation machinery. However, these kinds of information do not, in themselves, give us a satisfactory picture of how the overall system is controlled. This is where quantitative system analysis can enable a step-change in our understanding of biological resource management and how this relates to cell physiology and evolution. An important aspect of this more system-oriented approach to translational control is the inherent heterogeneity of cell populations that is generated by gene expression noise. In this short review, we address the fact that, although the vast majority of our knowledge of the translation machinery is based on experimental analysis of samples that each contain hundreds of millions of cells, in reality every cell is unique in terms of its composition and control properties. We have entered a new era in which research into the heterogeneity of cell systems promises to provide answers to many (previously unanswerable) questions about cell physiology and evolution.

The fraction of cells that resume growth after acetic acid addition is a strain-dependent parameter of acetic acid tolerance in Saccharomyces cerevisiae.

High acetic acid tolerance of Saccharomyces cerevisiae is a relevant phenotype in industrial biotechnology when using lignocellulosic hydrolysates as feedstock. A screening of 38 S. cerevisiae strains for tolerance to acetic acid revealed considerable differences, particularly with regard to the duration of the latency phase. To understand how this phenotype is quantitatively manifested, four strains exhibiting significant differences were studied in more detail. Our data show that the duration of the latency phase is primarily determined by the fraction of cells within the population that resume growth. Only this fraction contributed to the exponential growth observed after the latency phase, while all other cells persisted in a viable but non-proliferating state. A remarkable variation in the size of the fraction was observed among the tested strains differing by several orders of magnitude. In fact, only 11 out of 10(7)  cells of the industrial bioethanol production strain Ethanol Red resumed growth after exposure to 157 mM acetic acid at pH 4.5, while this fraction was 3.6 × 10(6) (out of 10(7)  cells) in the highly acetic acid tolerant isolate ATCC 96581. These strain-specific differences are genetically determined and represent a valuable starting point to identify genetic targets for future strain improvement.

Investigating Heterogeneous Cell-Cycle Progression Using Single-Cell Imaging Approaches.

Investigating cell-cycle progression has been challenging due to the complex interconnectivity of regulatory processes and inherent cell-to-cell heterogeneity, which often require synchronization procedures. However, recent advancements in cell-cycle sensors and single-cell imaging techniques have turned this heterogeneity into an advantage for investigating the molecular mechanisms underlying diverse responses. This has led to significant progress in our understanding of cell-cycle regulation. In this paper, we present a comprehensive live single-cell imaging workflow that leverages cutting-edge live-cell sensors. These advanced single-cell imaging procedures provide promising opportunities for elucidating the molecular mechanisms underpinnings of heterogeneous responses in cell-cycle progression.

Density physics-informed neural networks reveal sources of cell heterogeneity in signal transduction.

The transduction time between signal initiation and final response provides valuable information on the underlying signaling pathway, including its speed and precision. Furthermore, multi-modality in a transduction-time distribution indicates that the response is regulated by multiple pathways with different transduction speeds. Here, we developed a method called density physics-informed neural networks (Density-PINNs) to infer the transduction-time distribution from measurable final stress response time traces. We applied Density-PINNs to single-cell gene expression data from sixteen promoters regulated by unknown pathways in response to antibiotic stresses. We found that promoters with slower signaling initiation and transduction exhibit larger cell-to-cell heterogeneity in response intensity. However, this heterogeneity was greatly reduced when the response was regulated by slow and fast pathways together. This suggests a strategy for identifying effective signaling pathways for consistent cellular responses to disease treatments. Density-PINNs can also be applied to understand other time delay systems, including infectious diseases.

Cell-to-cell variability in Myc dynamics drives transcriptional heterogeneity in cancer cells.

Cell-to-cell heterogeneity is vital for tumor evolution and survival. How cancer cells achieve and exploit this heterogeneity remains an active area of research. Here, we identify c-Myc as a highly heterogeneously expressed transcription factor and an orchestrator of transcriptional and phenotypic diversity in cancer cells. By monitoring endogenous c-Myc protein in individual living cells, we report the surprising pulsatile nature of c-Myc expression and the extensive cell-to-cell variability in its dynamics. We further show that heterogeneity in c-Myc dynamics leads to variable target gene transcription and that timing of c-Myc expression predicts cell-cycle progression rates and drug sensitivities. Together, our data advocate for a model in which cancer cells increase the heterogeneity of functionally diverse transcription factors such as c-Myc to rapidly survey transcriptional landscapes and survive stress.

Active Efflux Leads to Heterogeneous Dissipation of Proton Motive Force by Protonophores in Bacteria.

Various toxic compounds disrupt bacterial physiology. While bacteria harbor defense mechanisms to mitigate the toxicity, these mechanisms are often coupled to the physiological state of the cells and become ineffective when the physiology is severely disrupted. Here, we characterized such feedback by exposing Escherichia coli to protonophores. Protonophores dissipate the proton motive force (PMF), a fundamental force that drives physiological functions. We found that E. coli cells responded to protonophores heterogeneously, resulting in bimodal distributions of cell growth, substrate transport, and motility. Furthermore, we showed that this heterogeneous response required active efflux systems. The analysis of underlying interactions indicated the heterogeneous response results from efflux-mediated positive feedback between PMF and protonophores' action. Our studies have broad implications for bacterial adaptation to stress, including antibiotics. IMPORTANCE An electrochemical proton gradient across the cytoplasmic membrane, alternatively known as proton motive force, energizes vital cellular processes in bacteria, including ATP synthesis, nutrient uptake, and cell division. Therefore, a wide range of organisms produce the agents that collapse the proton motive force, protonophores, to gain a competitive advantage. Studies have shown that protonophores have significant effects on microbial competition, host-pathogen interaction, and antibiotic action and resistance. Furthermore, protonophores are extensively used in various laboratory studies to perturb bacterial physiology. Here, we have characterized cell growth, substrate transport, and motility of Escherichia coli cells exposed to protonophores. Our findings demonstrate heterogeneous effects of protonophores on cell physiology and the underlying mechanism.

DNA Methylation Profiles of Tph1A and BDNF in Gut and Brain of L. Rhamnosus-Treated Zebrafish.

The bidirectional microbiota-gut-brain axis has raised increasing interest over the past years in the context of health and disease, but there is a lack of information on molecular mechanisms underlying this connection. We hypothesized that change in microbiota composition may affect brain epigenetics leading to long-lasting effects on specific brain gene regulation. To test this hypothesis, we used Zebrafish (Danio Rerio) as a model system. As previously shown, treatment with high doses of probiotics can modulate behavior in Zebrafish, causing significant changes in the expression of some brain-relevant genes, such as BDNF and Tph1A. Using an ultra-deep targeted analysis, we investigated the methylation state of the BDNF and Tph1A promoter region in the brain and gut of probiotic-treated and untreated Zebrafishes. Thanks to the high resolution power of our analysis, we evaluated cell-to-cell methylation differences. At this resolution level, we found slight DNA methylation changes in probiotic-treated samples, likely related to a subgroup of brain and gut cells, and that specific DNA methylation signatures significantly correlated with specific behavioral scores.

Translational control of gene expression noise and its relationship to ageing in yeast.

Gene expression noise influences organism evolution and fitness but is poorly understood. There is increasing evidence that the functional roles of components of the translation machinery influence noise intensity. In addition, modulation of the activities of at least some of these same components affects the replicative lifespan of a broad spectrum of organisms. In a novel comparative approach, we modulate the activities of the translation initiation factors eIFG1 and eIF4G2, both of which are involved in the process of recruiting ribosomal 43S preinitiation complexes to the 5' end of eukaryotic mRNAs. We show that tagging of the cell wall using a fluorescent dye allows us to follow gene expression noise as different yeast strains progress through successive cycles of replicative ageing. This procedure reveals a relationship between global protein synthesis rate and gene expression noise (cell-to-cell heterogeneity), which is accompanied by a parallel correlation between gene expression noise and the replicative age of mother cells. An alternative approach, based on microfluidics, confirms the interdependence between protein synthesis rate, gene expression noise and ageing. We additionally show that it is important to characterize the influence of the design of the microfluidic device on the nutritional state of the cells during such experiments. Analysis of the noise data derived from flow cytometry and fluorescence microscopy measurements indicates that both the intrinsic and the extrinsic noise components increase as a function of ageing.

Single-cell transcriptome atlas of the leaf and root of rice seedlings.

As a multicellular organism, rice flourishes relying on gene expression diversity among cells of various functions. However, cellular-resolution transcriptome features are yet to be fully recognized, let alone cell-specific transcriptional responses to environmental stimuli. In this study, we apply single-cell RNA sequencing to both shoot and root of rice seedlings growing in Kimura B nutrient solution or exposed to various abiotic stresses and characterize transcriptomes for a total of 237,431 individual cells. We identify 15 and 9 cell types in the leaf and root, respectively, and observe that common transcriptome features are often shared between leaves and roots in the same tissue layer, except for endodermis or epidermis. Abiotic stress stimuli alter gene expression largely in a cell type-specific manner, but for a given cell type, different stresses often trigger transcriptional regulation of roughly the same set of genes. Besides, we detect proportional changes in cell populations in response to abiotic stress and investigate the underlying molecular mechanisms through single-cell reconstruction of the developmental trajectory. Collectively, our study represents a benchmark-setting data resource of single-cell transcriptome atlas for rice seedlings and an illustration of exploiting such resources to drive discoveries in plant biology.

Interplay between genetic, epigenetic, and gene expression variability: Considering complexity in evolvability.

Genetic variability, epigenetic variability, and gene expression variability (noise) are generally considered independently in their relationship with phenotypic variation. However, they appear to be intrinsically interconnected and influence it in combination. The study of the interplay between genetic and epigenetic variability has the longest history. This article rather considers the introduction of gene expression variability in its relationships with the two others and reviews for the first time experimental evidences over the four relationships connected to gene expression noise. They show how introducing this third source of variability complicates the way of thinking evolvability and the emergence of biological novelty. Finally, cancer cells are proposed to be an ideal model to decipher the dynamic interplay between genetic, epigenetic, and gene expression variability when one of them is either experimentally increased or therapeutically targeted. This interplay is also discussed in an evolutionary perspective in the context of cancer cell drug resistance.

AMPK and autophagy control embryonic elongation as part of a RhoA-like morphogenic program in nematode.

Autophagy is the process where cytosolic components are digested by the cell. This process is required for cell survival in stressful conditions. It was also shown to control cell division and more recently, cell morphology and migration. We characterized signalling pathways enabling embryonic epidermal cells of the nematode Caenorhabditis elegans to elongate along their antero-posterior axis. Previous studies revealed that epidermal cells can adopt either a RhoA-like or a Rac1-like morphogenic program. We show here that the AMP-activated protein kinase (AMPK) and genes controlling autophagy are required for proper elongation of epidermal cells following the RhoA-like program and are dispensable for other cells. This suggests that AMPK-autophagy is used by the embryo to fuel the most energy-demanding morphogenic processes promoting early elongation.