Passive Noise Filtering by Cellular Compartmentalization

Size Scaling of Condensates in Multicomponent Phase Separation

Constant proportionalities between cells and their intracellular organelles have been widely observed in various types of cells, known as intracellular size scaling. However, the mechanism underlying the size scaling and its modulation by environmental factors in multicomponent systems remain poorly understood. Here, we study the size scaling of membrane-less condensates using microdroplet-encapsulated minimalistic condensates formed by droplet microfluidics and mean-field theory. We demonstrate that the size scaling of condensates is an inherent characteristic of liquid-liquid phase separation. This concept is supported by experiments showing the occurrence of size scaling phenomena in various condensate systems and a generic lever rule acquired from mean-field theory. Moreover, it is found that the condensate-to-microdroplet scaling ratio can be affected by the solute and salt concentrations, with good agreement between experiments and predictions by theory. Notably, we identify a noise buffering mechanism whereby condensates composed of large macromolecules effectively maintain constant volumes and counteract concentration fluctuations of small molecules. This mechanism is achieved through the dynamic rearrangement of small molecules in and out of membrane-free interfaces. Our work provides crucial insights into understanding mechanistic principles that govern the size of cells and intracellular organelles as well as associated biological functions.

Charge block-driven liquid-liquid phase separation - mechanism and biological roles

Liquid-liquid phase separation (LLPS) has increasingly been found to play pivotal roles in a number of intracellular events and reactions, and has introduced a new paradigm in cell biology to explain protein-protein and enzyme-ligand interactions beyond conventional molecular and biochemical theories. LLPS is driven by the cumulative effects of weak and promiscuous interactions, including electrostatic, hydrophobic and cation-π interactions, among polypeptides containing intrinsically disordered regions (IDRs) and describes the macroscopic behaviours of IDR-containing proteins in an intracellular milieu. Recent studies have revealed that interactions between 'charge blocks' - clusters of like charges along the polypeptide chain - strongly induce LLPS and play fundamental roles in its spatiotemporal regulation. Introducing a new parameter, termed 'charge blockiness', into physicochemical models of disordered polypeptides has yielded a better understanding of how the intrinsic amino acid sequence of a polypeptide determines the spatiotemporal occurrence of LLPS within a cell. Charge blockiness might also explain why some post-translational modifications segregate within IDRs and how they regulate LLPS. In this Review, we summarise recent progress towards understanding the mechanism and biological roles of charge block-driven LLPS and discuss how this new characteristic parameter of polypeptides offers new possibilities in the fields of structural biology and cell biology.

Heterogeneity generating capacity in tumorigenesis and cancer therapeutics

Cells of multicellular organisms generate heterogeneity in a controlled and transient fashion during embryogenesis, which can be reactivated in pathologies such as cancer. Although genomic heterogeneity is an important part of tumorigenesis, continuous generation of phenotypic heterogeneity is central for the adaptation of cancer cells to the challenges of tumorigenesis and response to therapy. Here I discuss the capacity of generating heterogeneity, hereafter called cell hetness, in cancer cells both as the activation of hetness oncogenes and inactivation of hetness tumor suppressor genes, which increase the generation of heterogeneity, ultimately producing an increase in adaptability and cell fitness. Transcriptomic high hetness states in therapy-tolerant cell states denote its importance in cancer resistance to therapy. The definition of the concept of hetness will allow the understanding of its origins, its control during embryogenesis, its loss of control in tumorigenesis and cancer therapeutics and its active targeting.

Nuclear RNA homeostasis promotes systems-level coordination of cell fate and senescence

Understanding cellular coordination remains a challenge despite knowledge of individual pathways. The RNA exosome, targeting a wide range of RNA substrates, is often downregulated in cellular senescence. Utilizing an auxin-inducible system, we observed that RNA exosome depletion in embryonic stem cells significantly affects the transcriptome and proteome, causing pluripotency loss and pre-senescence onset. Mechanistically, exosome depletion triggers acute nuclear RNA aggregation, disrupting nuclear RNA-protein equilibrium. This disturbance limits nuclear protein availability and hinders polymerase initiation and engagement, reducing gene transcription. Concurrently, it promptly disrupts nucleolar transcription, ribosomal processes, and nuclear exporting, resulting in a translational shutdown. Prolonged exosome depletion induces nuclear structural changes resembling senescent cells, including aberrant chromatin compaction, chromocenter disassembly, and intensified heterochromatic foci. These effects suggest that the dynamic turnover of nuclear RNA orchestrates crosstalk between essential processes to optimize cellular function. Disruptions in nuclear RNA homeostasis result in systemic functional decline, altering the cell state and promoting senescence.

Prediction of on-target and off-target activity of CRISPR-Cas13d guide RNAs using deep learning

Transcriptome engineering applications in living cells with RNA-targeting CRISPR effectors depend on accurate prediction of on-target activity and off-target avoidance. Here we design and test ~200,000 RfxCas13d guide RNAs targeting essential genes in human cells with systematically designed mismatches and insertions and deletions (indels). We find that mismatches and indels have a position- and context-dependent impact on Cas13d activity, and mismatches that result in G-U wobble pairings are better tolerated than other single-base mismatches. Using this large-scale dataset, we train a convolutional neural network that we term targeted inhibition of gene expression via gRNA design (TIGER) to predict efficacy from guide sequence and context. TIGER outperforms the existing models at predicting on-target and off-target activity on our dataset and published datasets. We show that TIGER scoring combined with specific mismatches yields the first general framework to modulate transcript expression, enabling the use of RNA-targeting CRISPRs to precisely control gene dosage.

Phase separation reduces cell-to-cell variability of transcriptional bursting

Gene expression is a stochastic and noisy process often occurring in "bursts". Experiments have shown that the compartmentalization of proteins by liquid-liquid phase separation is conducive to reducing the noise of gene expression. Therefore, an important goal is to explore the role of bursts in phase separation noise reduction processes. We propose a coupled model that includes phase separation and a two-state gene expression process. Using the timescale separation method, we obtain approximate solutions for the expectation, variance, and noise strength of the dilute phase. We find that a higher burst frequency weakens the ability of noise reduction by phase separation, but as the burst size increases, this ability first increases and then decreases. This study provides a deeper understanding of phase separation to reduce noise in the stochastic gene expression with burst kinetics.

Gene transcription regulation by ER at the single cell and allele level

In this short review we discuss the current view of how the estrogen receptor (ER), a pivotal member of the nuclear receptor superfamily of transcription factors, regulates gene transcription at the single cell and allele level, focusing on in vitro cell line models. We discuss central topics and new trends in molecular biology including phenotypic heterogeneity, single cell sequencing, nuclear phase separated condensates, single cell imaging, and image analysis methods, with particular focus on the methodologies and results that have been reported in the last few years using microscopy-based techniques. These observations augment the results from biochemical assays that lead to a much more complex and dynamic view of how ER, and arguably most transcription factors, act to regulate gene transcription.

Biomolecular condensates in kidney physiology and disease

The regulation and preservation of distinct intracellular and extracellular solute microenvironments is crucial for the maintenance of cellular homeostasis. In mammals, the kidneys control bodily salt and water homeostasis. Specifically, the urine-concentrating mechanism within the renal medulla causes fluctuations in extracellular osmolarity, which enables cells of the kidney to either conserve or eliminate water and electrolytes, depending on the balance between intake and loss. However, relatively little is known about the subcellular and molecular changes caused by such osmotic stresses. Advances have shown that many cells, including those of the kidney, rapidly (within seconds) and reversibly (within minutes) assemble membraneless, nano-to-microscale subcellular assemblies termed biomolecular condensates via the biophysical process of hyperosmotic phase separation (HOPS). Mechanistically, osmotic cell compression mediates changes in intracellular hydration, concentration and molecular crowding, rendering HOPS one of many related phase-separation phenomena. Osmotic stress causes numerous homo-multimeric proteins to condense, thereby affecting gene expression and cell survival. HOPS rapidly regulates specific cellular biochemical processes before appropriate protective or corrective action by broader stress response mechanisms can be initiated. Here, we broadly survey emerging evidence for, and the impact of, biomolecular condensates in nephrology, where initial concentration buffering by HOPS and its subsequent cellular escalation mechanisms are expected to have important implications for kidney physiology and disease.

The epithelial-mesenchymal plasticity landscape: principles of design and mechanisms of regulation

Epithelial-mesenchymal plasticity (EMP) enables cells to interconvert between several states across the epithelial-mesenchymal landscape, thereby acquiring hybrid epithelial/mesenchymal phenotypic features. This plasticity is crucial for embryonic development and wound healing, but also underlies the acquisition of several malignant traits during cancer progression. Recent research using systems biology and single-cell profiling methods has provided novel insights into the main forces that shape EMP, which include the microenvironment, lineage specification and cell identity, and the genome. Additionally, key roles have emerged for hysteresis (cell memory) and cellular noise, which can drive stochastic transitions between cell states. Here, we review these forces and the distinct but interwoven layers of regulatory control that stabilize EMP states or facilitate epithelial-mesenchymal transitions (EMTs) and discuss the therapeutic potential of manipulating the EMP landscape.

The minimal intrinsic stochasticity of constitutively expressed eukaryotic genes is sub-Poissonian

Stochastic variation in gene products ("noise") is an inescapable by-product of gene expression. Noise must be minimized to allow for the reliable execution of cellular functions. However, noise cannot be suppressed beyond an intrinsic lower limit. For constitutively expressed genes, this limit is believed to be Poissonian, meaning that the variance in mRNA numbers cannot be lower than their mean. Here, we show that several cell division genes in fission yeast have mRNA variances significantly below this limit, which cannot be explained by the classical gene expression model for low-noise genes. Our analysis reveals that multiple steps in both transcription and mRNA degradation are essential to explain this sub-Poissonian variance. The sub-Poissonian regime differs qualitatively from previously characterized noise regimes, a hallmark being that cytoplasmic noise is reduced when the mRNA export rate increases. Our study re-defines the lower limit of eukaryotic gene expression noise and identifies molecular requirements for ultra-low noise which are expected to support essential cell functions.

Cellular compartmentalisation and receptor promiscuity as a strategy for accurate and robust inference of position during morphogenesis

Precise spatial patterning of cell fate during morphogenesis requires accurate inference of cellular position. In making such inferences from morphogen profiles, cells must contend with inherent stochasticity in morphogen production, transport, sensing and signalling. Motivated by the multitude of signalling mechanisms in various developmental contexts, we show how cells may utilise multiple tiers of processing (compartmentalisation) and parallel branches (multiple receptor types), together with feedback control, to bring about fidelity in morphogenetic decoding of their positions within a developing tissue. By simultaneously deploying specific and nonspecific receptors, cells achieve a more accurate and robust inference. We explore these ideas in the patterning of Drosophila melanogaster wing imaginal disc by Wingless morphogen signalling, where multiple endocytic pathways participate in decoding the morphogen gradient. The geometry of the inference landscape in the high dimensional space of parameters provides a measure for robustness and delineates stiff and sloppy directions. This distributed information processing at the scale of the cell highlights how local cell autonomous control facilitates global tissue scale design.

Localization of Noise in Biochemical Networks

Noise, or uncertainty in biochemical networks, has become an important aspect of many biological problems. Noise can arise and propagate from external factors and probabilistic chemical reactions occurring in small cellular compartments. For species survival, it is important to regulate such uncertainties in executing vital cell functions. Regulated noise can improve adaptability, whereas uncontrolled noise can cause diseases. Simulation can provide a detailed analysis of uncertainties, but parameters such as rate constants and initial conditions are usually unknown. A general understanding of noise dynamics from the perspective of network structure is highly desirable. In this study, we extended the previously developed law of localization for characterizing noise in terms of (co)variances and developed noise localization theory. With linear noise approximation, we can expand a biochemical network into an extended set of differential equations representing a fictitious network for pseudo-components consisting of variances and covariances, together with chemical species. Through localization analysis, perturbation responses at the steady state of pseudo-components can be summarized into a sensitivity matrix that only requires knowledge of network topology. Our work allows identification of buffering structures at the level of species, variances, and covariances and can provide insights into noise flow under non-steady-state conditions in the form of a pseudo-chemical reaction. We tested noise localization in various systems, and here we discuss its implications and potential applications. Results show that this theory is potentially applicable in discriminating models, scanning network topologies with interesting noise behavior, and designing and perturbing networks with the desired response.

Coupling Cell Communication and Optogenetics: Implementation of a Light-Inducible Intercellular System in Yeast

Cell communication is a widespread mechanism in biology, allowing the transmission of information about environmental conditions. In order to understand how cell communication modulates relevant biological processes such as survival, division, differentiation, and apoptosis, different synthetic systems based on chemical induction have been successfully developed. In this work, we coupled cell communication and optogenetics in the budding yeast Saccharomyces cerevisiae. Our approach is based on two strains connected by the light-dependent production of α-factor pheromone in one cell type, which induces gene expression in the other type. After the individual characterization of the different variants of both strains, the optogenetic intercellular system was evaluated by combining the cells under contrasting illumination conditions. Using luciferase as a reporter gene, specific co-cultures at a 1:1 ratio displayed activation of the response upon constant blue light, which was not observed for the same cell mixtures grown in darkness. Then, the system was assessed at several dark/blue-light transitions, where the response level varies depending on the moment in which illumination was delivered. Furthermore, we observed that the amplitude of response can be tuned by modifying the initial ratio between both strains. Finally, the two-population system showed higher fold inductions in comparison with autonomous strains. Altogether, these results demonstrated that external light information is propagated through a diffusible signaling molecule to modulate gene expression in a synthetic system involving microbial cells, which will pave the road for studies allowing optogenetic control of population-level dynamics.

Protein condensation diseases: therapeutic opportunities

Condensed states of proteins, including liquid-like membraneless organelles and solid-like aggregates, contribute in fundamental ways to the organisation and function of the cell. Perturbations of these states can lead to a variety of diseases through mechanisms that we are now beginning to understand. We define protein condensation diseases as conditions caused by the disruption of the normal behaviour of the condensed states of proteins. We analyze the problem of the identification of targets for pharmacological interventions for these diseases and explore opportunities for the regulation of the formation and organisation of aberrant condensed states of proteins.

In this review, the authors define protein condensation diseases as conditions caused by aberrant liquid-like or solid-like states of proteins, and describe opportunities for therapeutic interventions to restore the normal phase behaviour of proteins. The review accompanies the related collection of articles published in Nature Communications focusing on possible therapeutic approaches involving liquid-liquid phase separation.

Affinity and Valence Impact the Extent and Symmetry of Phase Separation of Multivalent Proteins

Biomolecular self-assembly spatially segregates proteins with a limited number of binding sites (valence) into condensates that coexist with a dilute phase. We develop a many-body lattice model for a three-component system of proteins with fixed valence in a solvent. We compare the predictions of the model to experimental phase diagrams that we measure in vivo, which allows us to vary specifically a binding site's affinity and valency. We find that the extent of phase separation varies exponentially with affinity and increases with valency. Valency alone determines the symmetry of the phase diagram.

Live Streaming of a Single Cell's Life over a Local pH-Monitoring Nanowire Waveguide

Spatiotemporal pH monitoring of single living cells across rigid cell and organelle membranes has been challenging, despite its significance in understanding cellular heterogeneity. Here, we developed a mechanically robust yet tolerably thin nanowire waveguide that enables in situ monitoring of pH dynamics at desired cellular compartments via direct optical communication. By chemically labeling fluorescein at one end of a poly(vinylbenzyl azide) nanowire, we continuously monitored pH variations of different compartments inside a living cell, successfully observing organelle-exclusive pH homeostasis and stimuli-selective pH regulations. Importantly, it was demonstrated for the first time that, during the mammalian cell cycle, the nucleus displays pH homeostasis in interphase but a tidal pH curve in the mitotic phase, implying the existence of independent pH-regulating activities by the nuclear envelope. The rapid and accurate local pH-reporting capability of our nanowire waveguide would be highly valuable for investigating cellular behaviors under diverse biological situations in living cells.

Comprehensive analysis of the circadian nuclear and cytoplasmic transcriptome in mouse liver

In eukaryotes, RNA is synthesised in the nucleus, spliced, and exported to the cytoplasm where it is translated and finally degraded. Any of these steps could be subject to temporal regulation during the circadian cycle, resulting in daily fluctuations of RNA accumulation and affecting the distribution of transcripts in different subcellular compartments. Our study analysed the nuclear and cytoplasmic, poly(A) and total transcriptomes of mouse livers collected over the course of a day. These data provide a genome-wide temporal inventory of enrichment in subcellular RNA, and revealed specific signatures of splicing, nuclear export and cytoplasmic mRNA stability related to transcript and gene lengths. Combined with a mathematical model describing rhythmic RNA profiles, we could test the rhythmicity of export rates and cytoplasmic degradation rates of approximately 1400 genes. With nuclear export times usually much shorter than cytoplasmic half-lives, we found that nuclear export contributes to the modulation and generation of rhythmic profiles of 10% of the cycling nuclear mRNAs. This study contributes to a better understanding of the dynamic regulation of the transcriptome during the day-night cycle.

Phase Separation: "The Master Key" to Deciphering the Physiological and Pathological Functions of Cells

Phase separation is a hot research field at present. It involves almost all aspects of cells and plays a significant role in cells, promising to be "a master key" in unlocking the mysteries of nature. In this review, the factors that affect phase separation are introduced, such as own component, electrostatic interaction, and chemical modification. Furthermore, the physiological roles of phase separation in cells, including molecules transport channel, gene expression and regulation, cellular division and differentiation, stress response, proteins refolding and degradation, cell connections, construction of skin barrier, and cell signals transmission, are highlighted. However, the disorder of phase separation leads to pathological condensates, which are associated with neurodegenerative diseases, tumors, and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). This relationship is considered the potential target for developing corresponded drugs and therapy. Some drugs targeting phase separation have improved meaningful, such as tankyrase, lipoamide, oligonucleotides, elvitagravir, nilotinib, CVL218, PJ34. All in all, mystery phase separation provides a new viewpoint for researchers to explore cells, and is expected to solve many unknown phenomena in nature.

Analysis of a non-Markov transcription model with nuclear RNA export and RNA nuclear retention

Transcription involves gene activation, nuclear RNA export (NRE) and RNA nuclear retention (RNR). All these processes are multistep and biochemical. A multistep reaction process can create memories between reaction events, leading to non-Markovian kinetics. This raises an unsolved issue: how does molecular memory affect stochastic transcription in the case that NRE and RNR are simultaneously considered? To address this issue, we analyze a non-Markov model, which considers multistep activation, multistep NRE and multistep RNR can interpret many experimental phenomena. In order to solve this model, we introduce an effective transition rate for each reaction. These effective transition rates, which explicitly decode the effect of molecular memory, can transform the original non-Markov issue into an equivalent Markov one. Based on this technique, we derive analytical results, showing that molecular memory can significantly affect the nuclear and cytoplasmic mRNA mean and noise. In addition to the results providing insights into the role of molecular memory in gene expression, our modeling and analysis provide a paradigm for studying more complex stochastic transcription processes.

Noise reduction by upstream open reading frames

Gene expression is prone to burst production, making it a highly noisy process that requires additional controls. Upstream open reading frames (uORFs) are widely present in the 5' leader sequences of 30-50% of eukaryotic messenger RNAs^1-3. The translation of uORFs can repress the translation efficiency of the downstream main coding sequences. Whether the low translation efficiency leads to a different variation, or noise, in gene expression has not been investigated, nor has the direct biological impact of uORF-repressed translation. Here we show that uORFs achieve low but precise protein production in plant cells, possibly by reducing the protein production rate. We also demonstrate that, by buffering a stable TIMING OF CAB EXPRESSION 1 (TOC1) protein production level, uORFs contribute to the robust operation of the plant circadian clock. Our results provide both an action model and the biological impact of uORFs in translational control to mitigate transcriptional noise for precise protein production.

Essence determines phenomenon: Assaying the material properties of biological condensates

Intracellular spaces are partitioned into separate compartments to ensure that numerous biochemical reactions and cellular functions take place in a spatiotemporally controlled manner. Biomacromolecules including proteins and RNAs undergo liquid–liquid phase separation and subsequent phase transition to form biological condensates with diverse material states. The material/physical properties of biological condensates are crucial for fulfilling their distinct physiological functions, and abnormal material properties can cause deleterious effects under pathological conditions. Here, we review recent studies showing the role of the material properties of biological condensates in their physiological functions. We also summarize several classic methods as well as newly emerging techniques for characterization and/or measurement of the material properties of biological condensates.

CTCF-mediated chromatin looping provides a topological framework for the formation of phase-separated transcriptional condensates

CTCF is crucial to the organization of mammalian genomes into loop structures. According to recent studies, the transcription apparatus is compartmentalized and concentrated at super-enhancers to form phase-separated condensates and drive the expression of cell-identity genes. However, it remains unclear whether and how transcriptional condensates are coupled to higher-order chromatin organization. Here, we show that CTCF is essential for RNA polymerase II (Pol II)-mediated chromatin interactions, which occur as hyperconnected spatial clusters at super-enhancers. We also demonstrate that CTCF clustering, unlike Pol II clustering, is independent of liquid-liquid phase-separation and resistant to perturbation of transcription. Interestingly, clusters of Pol II, BRD4, and MED1 were found to dissolve upon CTCF depletion, but were reinstated upon restoration of CTCF, suggesting a potent instructive function for CTCF in the formation of transcriptional condensates. Overall, we provide evidence suggesting that CTCF-mediated chromatin looping acts as an architectural prerequisite for the assembly of phase-separated transcriptional condensates.

Cell-to-cell variability in JAK2/STAT5 pathway components and cytoplasmic volumes defines survival threshold in erythroid progenitor cells

Survival or apoptosis is a binary decision in individual cells. However, at the cell-population level, a graded increase in survival of colony-forming unit-erythroid (CFU-E) cells is observed upon stimulation with erythropoietin (Epo). To identify components of Janus kinase 2/signal transducer and activator of transcription 5 (JAK2/STAT5) signal transduction that contribute to the graded population response, we extended a cell-population-level model calibrated with experimental data to study the behavior in single cells. The single-cell model shows that the high cell-to-cell variability in nuclear phosphorylated STAT5 is caused by variability in the amount of Epo receptor (EpoR):JAK2 complexes and of SHP1, as well as the extent of nuclear import because of the large variance in the cytoplasmic volume of CFU-E cells. 24-118 pSTAT5 molecules in the nucleus for 120 min are sufficient to ensure cell survival. Thus, variability in membrane-associated processes is sufficient to convert a switch-like behavior at the single-cell level to a graded population-level response.

Phase separation in transcription factor dynamics and chromatin organization

Studies over the past decade have highlighted the key role of liquid-liquid phase separation in cellular organization and function. Dynamic compartmentalization of transcription factors and coactivators by such phase-separated condensates regulates the assembly of transcriptional machinery at genomic loci. Although rapid advances in microscopy have demonstrated the ubiquity of such condensates, a rigorous characterization of the physics of phase separation in transcription remains to be carried out. In this review, we discuss theoretical and experimental evidence for biomolecular condensates as dynamic regulators of transcription. Looking beyond, we highlight functional consequences for transcription factor dynamics and gene expression and discuss potential pitfalls of misclassifying biomolecular condensates as liquid droplets in the absence of a rigorous physical description.

TNF stimulation primarily modulates transcriptional burst size of NF-κB-regulated genes

Cell-to-cell heterogeneity is a feature of the tumor necrosis factor (TNF)-stimulated inflammatory response mediated by the transcription factor NF-κB, motivating an exploration of the underlying sources of this noise. Here, we combined single-transcript measurements with computational models to study transcriptional noise at six NF-κB-regulated inflammatory genes. In the basal state, NF-κB-target genes displayed an inverse correlation between mean and noise characteristic of transcriptional bursting. By analyzing transcript distributions with a bursting model, we found that TNF primarily activated transcription by increasing burst size while maintaining burst frequency for gene promoters with relatively high basal histone 3 acetylation (AcH3) that marks open chromatin environments. For promoters with lower basal AcH3 or when AcH3 was decreased with a small molecule drug, the contribution of burst frequency to TNF activation increased. Finally, we used a mathematical model to show that TNF positive feedback amplified gene expression noise resulting from burst size-mediated transcription, leading to a subset of cells with high TNF protein expression. Our results reveal potential sources of noise underlying intercellular heterogeneity in the TNF-mediated inflammatory response.

Deciphering transcriptional and functional heterogeneity in hematopoiesis with single-cell genomics

PURPOSE OF REVIEW

Single-cell genomic approaches have uncovered cell fate biases and heterogeneity within hematopoietic subpopulations. However, standard single-cell transcriptomics suffers from high sampling noise, which particularly skews the distribution of lowly expressed genes, such as transcription factors (TFs). This might preclude the identification of rare transcripts that define cell identity and demarcate cell fate biases. Moreover, these studies need to go hand in hand with relevant functional assays to ensure that observed gene expression changes represent biologically meaningful alterations.

RECENT FINDINGS

Single-cell lineage tracing and functional validation studies have uncovered cell fate bias within transcriptionally distinct hematopoietic stem and progenitor subpopulations. Novel markers identified using these strategies have been proposed to prospectively isolate functionally distinct subpopulations, including long-term hematopoietic stem cells for ex vivo applications. Furthermore, the continuous nature of hematopoiesis has prompted the study of the relationship between stochastic transcriptional noise in hematopoietic TFs and cell fate determination.

SUMMARY

An understanding of the limitations of single-cell genomic approaches and follow-up functional assays is critical to discern the technical and biological contribution of noise in hematopoietic heterogeneity, to identify rare gene expression states, and to uncover functionally distinct subpopulations within hematopoiesis.

SUPPLEMENTARY VIDEO

http://links.lww.com/COH/A23.

Physical theory of biological noise buffering by multicomponent phase separation

Maintaining homeostasis is a fundamental characteristic of living systems. In cells, this is contributed to by the assembly of biochemically distinct organelles, many of which are not membrane bound but form by the physical process of liquid-liquid phase separation (LLPS). By analogy with LLPS in binary solutions, cellular LLPS was hypothesized to contribute to homeostasis by facilitating "concentration buffering," which renders the local protein concentration within the organelle robust to global variations in the average cellular concentration (e.g., due to expression noise). Interestingly, concentration buffering was experimentally measured in vivo in a simple organelle with a single solute, while it was observed not to be obeyed in one with several solutes. Here, we formulate theoretically and solve analytically a physical model of LLPS in a ternary solution of two solutes (ϕ and ψ) that interact both homotypically (ϕ-ϕ attractions) and heterotypically (ϕ-ψ attractions). Our physical theory predicts how the coexisting concentrations in LLPS are related to expression noise and thus, generalizes the concept of concentration buffering to multicomponent systems. This allows us to reconcile the seemingly contradictory experimental observations. Furthermore, we predict that incremental changes of the homotypic and heterotypic interactions among the molecules that undergo LLPS, such as those that are caused by mutations in the genes encoding the proteins, may increase the efficiency of concentration buffering of a given system. Thus, we hypothesize that evolution may optimize concentration buffering as an efficient mechanism to maintain LLPS homeostasis and suggest experimental approaches to test this in different systems.

A framework for understanding the functions of biomolecular condensates across scales

Biomolecular condensates are found throughout eukaryotic cells, including in the nucleus, in the cytoplasm and on membranes. They are also implicated in a wide range of cellular functions, organizing molecules that act in processes ranging from RNA metabolism to signalling to gene regulation. Early work in the field focused on identifying condensates and understanding how their physical properties and regulation arise from molecular constituents. Recent years have brought a focus on understanding condensate functions. Studies have revealed functions that span different length scales: from molecular (modulating the rates of chemical reactions) to mesoscale (organizing large structures within cells) to cellular (facilitating localization of cellular materials and homeostatic responses). In this Roadmap, we discuss representative examples of biochemical and cellular functions of biomolecular condensates from the recent literature and organize these functions into a series of non-exclusive classes across the different length scales. We conclude with a discussion of areas of current interest and challenges in the field, and thoughts about how progress may be made to further our understanding of the widespread roles of condensates in cell biology.

Formation and function of bacterial organelles

Advances in imaging technologies have revealed that many bacteria possess organelles with a proteomically defined lumen and a macromolecular boundary. Some are bound by a lipid bilayer (such as thylakoids, magnetosomes and anammoxosomes), whereas others are defined by a lipid monolayer (such as lipid bodies), a proteinaceous coat (such as carboxysomes) or have a phase-defined boundary (such as nucleolus-like compartments). These diverse organelles have various metabolic and physiological functions, facilitating adaptation to different environments and driving the evolution of cellular complexity. This Review highlights that, despite the diversity of reported organelles, some unifying concepts underlie their formation, structure and function. Bacteria have fundamental mechanisms of organelle formation, through which conserved processes can form distinct organelles in different species depending on the proteins recruited to the luminal space and the boundary of the organelle. These complex subcellular compartments provide evolutionary advantages as well as enabling metabolic specialization, biogeochemical processes and biotechnological advances. Growing evidence suggests that the presence of organelles is the rule, rather than the exception, in bacterial cells.

Mixture distributions in a stochastic gene expression model with delayed feedback: a WKB approximation approach

Noise in gene expression can be substantively affected by the presence of production delay. Here we consider a mathematical model with bursty production of protein, a one-step production delay (the passage of which activates the protein), and feedback in the frequency of bursts. We specifically focus on examining the steady-state behaviour of the model in the slow-activation (i.e. large-delay) regime. Using a formal asymptotic approach, we derive an autonomous ordinary differential equation for the inactive protein that applies in the slow-activation regime. If the differential equation is monostable, the steady-state distribution of the inactive (active) protein is approximated by a single Gaussian (Poisson) mode located at the globally stable fixed point of the differential equation. If the differential equation is bistable (due to cooperative positive feedback), the steady-state distribution of the inactive (active) protein is approximated by a mixture of Gaussian (Poisson) modes located at the stable fixed points; the weights of the modes are determined from a WKB approximation to the stationary distribution. The asymptotic results are compared to numerical solutions of the chemical master equation.

Digital Sensing and Molecular Computation by an Enzyme-Free DNA Circuit

DNA circuits form the basis of programmable molecular systems capable of signal transduction and algorithmic computation. Some classes of molecular programs, such as catalyzed hairpin assembly, enable isothermal, enzyme-free signal amplification. However, current detection limits in DNA amplification circuits are modest, as sensitivity is inhibited by signal leakage resulting from noncatalyzed background reactions inherent to the noncovalent system. Here, we overcome this challenge by optimizing a catalyzed hairpin assembly for single-molecule sensing in a digital droplet assay. Furthermore, we demonstrate digital reporting of DNA computation at the single-molecule level by employing ddCHA as a signal transducer for simple DNA logic gates. By facilitating signal transduction of molecular computation at pM concentration, our approach can improve processing density by a factor of 10⁴ relative to conventional DNA logic gates. More broadly, we believe that digital molecular computing will broaden the scope and efficacy of isothermal amplification circuits within DNA computing, biosensing, and signal amplification in general.

Profiling Cell Signaling Networks at Single-cell Resolution

Signaling networks process intra- and extracellular information to modulate the functions of a cell. Deregulation of signaling networks results in abnormal cellular physiological states and often drives diseases. Network responses to a stimulus or a drug treatment can be highly heterogeneous across cells in a tissue because of many sources of cellular genetic and non-genetic variance. Signaling network heterogeneity is the key to many biological processes, such as cell differentiation and drug resistance. Only recently, the emergence of multiplexed single-cell measurement technologies has made it possible to evaluate this heterogeneity. In this review, we categorize currently established single-cell signaling network profiling approaches by their methodology, coverage, and application, and we discuss the advantages and limitations of each type of technology. We also describe the available computational tools for network characterization using single-cell data and discuss potential confounding factors that need to be considered in single-cell signaling network analyses.

Adenovirus flow in host cell networks

Viruses are obligatory parasites that take advantage of intracellular niches to replicate. During infection, their genomes are carried in capsids across the membranes of host cells to sites of virion production by exploiting cellular behaviour and resources to guide and achieve all aspects of delivery and the downstream virus manufacturing process. Successful entry hinges on execution of a precisely tuned viral uncoating program where incoming capsids disassemble in consecutive steps to ensure that genomes are released at the right time, and in the right place for replication to occur. Each step of disassembly is cell-assisted, involving individual pathways that transmit signals to regulate discrete functions, but at the same time, these signalling pathways are organized into larger networks, which communicate back and forth in complex ways in response to the presence of virus. In this review, we consider the elegant strategy by which adenoviruses (AdVs) target and navigate cellular networks to initiate the production of progeny virions. There are many remarkable aspects about the AdV entry program; for example, the virus gains targeted control of a large well-defined local network neighbourhood by coupling several interacting processes (including endocytosis, autophagy and microtubule trafficking) around a collective reference state centred on the interactional topology and multifunctional nature of protein VI. Understanding the network targeting activity of protein VI, as well as other built-in mechanisms that allow AdV particles to be efficient at navigating the subsystems of the cell, can be used to improve viral vectors, but also has potential to be incorporated for use in entirely novel delivery systems.

microRNA-mediated noise processing in cells: A fight or a game?

In the past decades, microRNAs (miRNA) have much attracted the attention of researchers at the interface between life and theoretical sciences for their involvement in post-transcriptional regulation and related diseases. Thanks to the always more sophisticated experimental techniques, the role of miRNAs as "noise processing units" has been further elucidated and two main ways of miRNA noise-control have emerged by combinations of theoretical and experimental studies. While on one side miRNAs were thought to buffer gene expression noise, it has recently been suggested that miRNAs could also increase the cell-to-cell variability of their targets. In this Mini Review, we focus on the role of miRNAs in molecular noise processing and on the advantages as well as current limitations of theoretical modelling.

Coupled membrane transporters reduce noise

Molecular systems are inherently probabilistic and operate in a noisy environment, yet, despite all these uncertainties, molecular functions are surprisingly reliable and robust. The principles used by natural systems to deal with noise are still not well understood, especially in a nonhomogeneous environment where molecules can diffuse across different compartments. In this paper we show that membrane transport mechanisms have very effective properties of noise reduction. In particular, we show that active transport mechanisms (those that can transport against a gradient of concentration by using energy or by means of the concentration gradient of other substances), such as symporters and antiporters, have surprising efficiency in noise reduction, which outperforms passive diffusion mechanisms and are well below Poisson levels. We link our results to the coupled transport of potassium, sodium, and glucose to show that the noise in internal glucose level can be greatly reduced. Our results show that compartmentalization can be a highly effective mechanism of noise reduction and suggests that membrane transport could give this extra benefit, contributing to the emergence of complex compartmentalization in eukaryotes.

Mammalian gene expression variability is explained by underlying cell state

Gene expression variability in mammalian systems plays an important role in physiological and pathophysiological conditions. This variability can come from differential regulation related to cell state (extrinsic) and allele-specific transcriptional bursting (intrinsic). Yet, the relative contribution of these two distinct sources is unknown. Here, we exploit the qualitative difference in the patterns of covariance between these two sources to quantify their relative contributions to expression variance in mammalian cells. Using multiplexed error robust RNA fluorescent in situ hybridization (MERFISH), we measured the multivariate gene expression distribution of 150 genes related to Ca2+ signaling coupled with the dynamic Ca2+ response of live cells to ATP. We show that after controlling for cellular phenotypic states such as size, cell cycle stage, and Ca2+ response to ATP, the remaining variability is effectively at the Poisson limit for most genes. These findings demonstrate that the majority of expression variability results from cell state differences and that the contribution of transcriptional bursting is relatively minimal.

Phase separation provides a mechanism to reduce noise in cells

Expression of proteins inside cells is noisy, causing variability in protein concentration among identical cells. A central problem in cellular control is how cells cope with this inherent noise. Compartmentalization of proteins through phase separation has been suggested as a potential mechanism to reduce noise, but systematic studies to support this idea have been missing. In this study, we used a physical model that links noise in protein concentration to theory of phase separation to show that liquid droplets can effectively reduce noise. We provide experimental support for noise reduction by phase separation using engineered proteins that form liquid-like compartments in mammalian cells. Thus, phase separation can play an important role in biological signal processing and control.

Distinct Kinetics in Electrophoretic Extraction of Cytoplasmic RNA from Single Cells

The physical fractionation of cytoplasmic versus nuclear components of cells is a key step for studying the subcellular localization of molecules. The application of an electric field is an emerging method for subcellular fractionation of proteins and nucleic acids from single cells. However, the multibiophysical process that involves electrical lysis of cytoplasmic membranes, electrophoresis, and diffusion of charged molecules remains unclear. Here we study RNA dynamics in single cells during the electrophoretic extraction via a microfluidic system that enables stringent fractionation of the subcellular components leveraging a focused electric field. We identified two distinct kinetics in the extraction of RNA molecules, which were respectively associated with soluble RNA and mitochondrial RNA. We show that the extraction kinetics of soluble RNA is dominated by electrophoresis over diffusion and has a time constant of 0.15 s. Interestingly, the extraction of mitochondrial RNA showed unexpected heterogeneity in the extraction with slower kinetics (3.8 s), while reproducibly resulting in the extraction of 98.9% ± 2% after 40 s. Together, we uncover that the microfluidic system uniquely offers length bias-free fractionation of RNA molecules for quantitative analysis of correlations among subcellular compartments by exploiting the homogeneous electrophoretic properties of RNA.

Stochastic transcription in the p53-mediated response to DNA damage is modulated by burst frequency

Discontinuous transcription has been described for different mammalian cell lines and numerous promoters. However, our knowledge of how the activity of individual promoters is adjusted by dynamic signaling inputs from transcription factors is limited. To address this question, we characterized the activity of selected target genes that are regulated by pulsatile accumulation of the tumor suppressor p53 in response to ionizing radiation. We performed time-resolved measurements of gene expression at the single-cell level by smFISH and used the resulting data to inform a mathematical model of promoter activity. We found that p53 target promoters are regulated by frequency modulation of stochastic bursting and can be grouped along three archetypes of gene expression. The occurrence of these archetypes cannot solely be explained by nuclear p53 abundance or promoter binding of total p53. Instead, we provide evidence that the time-varying acetylation state of p53's C-terminal lysine residues is critical for gene-specific regulation of stochastic bursting.

Supramolecular Fuzziness of Intracellular Liquid Droplets: Liquid-Liquid Phase Transitions, Membrane-Less Organelles, and Intrinsic Disorder

Cells are inhomogeneously crowded, possessing a wide range of intracellular liquid droplets abundantly present in the cytoplasm of eukaryotic and bacterial cells, in the mitochondrial matrix and nucleoplasm of eukaryotes, and in the chloroplast’s stroma of plant cells. These proteinaceous membrane-less organelles (PMLOs) not only represent a natural method of intracellular compartmentalization, which is crucial for successful execution of various biological functions, but also serve as important means for the processing of local information and rapid response to the fluctuations in environmental conditions. Since PMLOs, being complex macromolecular assemblages, possess many characteristic features of liquids, they represent highly dynamic (or fuzzy) protein–protein and/or protein–nucleic acid complexes. The biogenesis of PMLOs is controlled by specific intrinsically disordered proteins (IDPs) and hybrid proteins with ordered domains and intrinsically disordered protein regions (IDPRs), which, due to their highly dynamic structures and ability to facilitate multivalent interactions, serve as indispensable drivers of the biological liquid–liquid phase transitions (LLPTs) giving rise to PMLOs. In this article, the importance of the disorder-based supramolecular fuzziness for LLPTs and PMLO biogenesis is discussed.

Dynamic Synthetic Cells Based on Liquid-Liquid Phase Separation

Living cells have long been a source of inspiration for chemists. Their capacity of performing complex tasks relies on the spatiotemporal coordination of matter and energy fluxes. Recent years have witnessed growing interest in the bottom-up construction of cell-like models capable of reproducing aspects of such dynamic organisation. Liquid-liquid phase-separation (LLPS) processes in water are increasingly recognised as representing a viable compartmentalisation strategy through which to produce dynamic synthetic cells. Herein, we highlight examples of the dynamic properties of LLPS used to assemble synthetic cells, including their biocatalytic activity, reversible condensation and dissolution, growth and division, and recent directions towards the design of higher-order structures and behaviour.

Imaging the Life and Death of mRNAs in Single Cells

RNA plays a central role in gene expression from its transcription in the nucleus through translation and degradation in the cytoplasm. Technological advances in fluorescent microscopy and labeling methodologies have made it possible to detect single molecules of RNA in both fixed and living cells. Here, we focus on the recent developments in RNA imaging that have allowed quantitatively measuring the lives of individual transcripts from birth to death and all the events in between in single cells and tissues. Direct observation of RNAs within their native cellular environment has revealed a complex layer of spatial and temporal regulation that has profoundly impacted our understanding of RNA biology.

Buffering and Amplifying Transcriptional Noise During Cell Fate Specification

The molecular processes that drive gene transcription are inherently noisy. This noise often manifests in the form of transcriptional bursts, producing fluctuations in gene activity over time. During cell fate specification, this noise is often buffered to ensure reproducible developmental outcomes. However, sometimes noise is utilized as a “bet-hedging” mechanism to diversify functional roles across a population of cells. Studies of bacteria, yeast, and cultured cells have provided insights into the nature and roles of noise in transcription, yet we are only beginning to understand the mechanisms by which noise influences the development of multicellular organisms. Here we discuss the sources of transcriptional noise and the mechanisms that either buffer noise to drive reproducible fate choices or amplify noise to randomly specify fates.

In Situ SiRNA Assembly in Living Cells for Gene Therapy with MicroRNA Triggered Cascade Reactions Templated by Nucleic Acids

The in situ generation of siRNAs in living cells can greatly enhance the specificity and efficiency of gene therapy. Inspired by the natural molecular machines that organize different compartments sequentially in a limited space to facilitate cellular process, this work constructs a DNA nanomachine (DNM) by alternately hybridizing two pairs of DNA/RNA hybrids to a DNA scaffold generated by rolling circle amplification for highly efficient in situ siRNA assembly in living cells. After target cell-specific delivery of DNM, intracellular specific microRNA can work as a trigger to operate the DNM by initiating DNA cascade displacement reaction between DNA/RNA hybrids along the scaffold for continuous generation of siRNAs. Using miR-21 as a model, efficient siRNAs generation is achieved via DNA templated cascade reaction, which demonstrated impressive suppressions to VEGF mRNA and protein expressions in cells and in vivo tumor growth and indicated promising application of the designed strategy in gene therapy.

RNAs, Phase Separation, and Membrane-Less Organelles: Are Post-Transcriptional Modifications Modulating Organelle Dynamics?

Membranous organelles allow sub-compartmentalization of biological processes. However, additional subcellular structures create dynamic reaction spaces without the need for membranes. Such membrane-less organelles (MLOs) are physiologically relevant and impact development, gene expression regulation, and cellular stress responses. The phenomenon resulting in the formation of MLOs is called liquid-liquid phase separation (LLPS), and is primarily governed by the interactions of multi-domain proteins or proteins harboring intrinsically disordered regions as well as RNA-binding domains. Although the presence of RNAs affects the formation and dissolution of MLOs, it remains unclear how the properties of RNAs exactly contribute to these effects. Here, the authors review this emerging field, and explore how particular RNA properties can affect LLPS and the behavior of MLOs. It is suggested that post-transcriptional RNA modification systems could be contributors for dynamically modulating the assembly and dissolution of MLOs.