Multimodal screen identifies noise-regulatory proteins.

Gene-expression noise can influence cell-fate choices across pathology and physiology. However, a crucial question persists: do regulatory proteins or pathways exist that control noise independently of mean expression levels? Our integrative approach, combining single-cell RNA sequencing with proteomics and regulator enrichment analysis, identifies 32 putative noise regulators. SON, a nuclear speckle-associated protein, alters transcriptional noise without changing mean expression levels. Furthermore, SON's noise control can propagate to the protein level. Long-read and total RNA sequencing shows that SON's noise control does not significantly change isoform usage or splicing efficiency. Moreover, SON depletion reduces state switching in pluripotent mouse embryonic stem cells and impacts their fate choice during differentiation. Collectively, we demonstrate a class of proteins that control noise orthogonally to mean expression levels. This work serves as a proof of concept that can identify other functional noise regulators throughout development and disease progression.

Protocol for simultaneous detection of mRNAs and (phospho-)proteins with ARTseq-FISH in mouse embryonic stem cells.

Understanding the molecular signatures of individual cells within complex biological systems is crucial for deciphering cellular heterogeneity and uncovering regulatory mechanisms. Here, we present a protocol for simultaneous multiplexed detection of selected mRNAs and (phospho-)proteins in mouse embryonic stem cells using spatial single-cell profiling. We describe steps for employing single-stranded DNA (ssDNA)-labeled antibo'dies, padlock probes, and rolling circle amplification to achieve simultaneous visualization of mRNAs and (phospho-)proteins at subcellular resolution. This protocol has potential application in identifying cells in heterogeneous biological microenvironments. For complete details on the use and execution of this protocol, please refer to Hu et al.1.

Protocol for in vitro transcribing mRNAs with defined poly(A)-tail lengths and visualizing sequential PABP binding.

Quantifying the number of proteins that interact with mRNAs, in particular with poly(A) tails of mRNAs, is crucial for understanding gene regulation. Biochemical assays offer significant advantages for this purpose. Here, we present a protocol for synthesizing mRNAs with accurate, length-specific poly(A) tails through a PCR-based approach. We also describe steps for an in vitro (i.e., cell-free) approach for visualizing the sequential binding of Cytoplasmic Poly(A)-Binding Proteins (PABPCs) to these poly(A) tails. We detail quality control steps throughout the procedure. For complete details on the use and execution of this protocol, please refer to Grandi et al.1.

Decoupled degradation and translation enables noise modulation by poly(A) tails.

Poly(A) tails are crucial for mRNA translation and degradation, but the exact relationship between tail length and mRNA kinetics remains unclear. Here, we employ a small library of identical mRNAs that differ only in their poly(A)-tail length to examine their behavior in human embryonic kidney cells. We find that tail length strongly correlates with mRNA degradation rates but is decoupled from translation. Interestingly, an optimal tail length of ∼100 nt displays the highest translation rate, which is identical to the average endogenous tail length measured by nanopore sequencing. Furthermore, poly(A)-tail length variability-a feature of endogenous mRNAs-impacts translation efficiency but not mRNA degradation rates. Stochastic modeling combined with single-cell tracking reveals that poly(A) tails provide cells with an independent handle to tune gene expression fluctuations by decoupling mRNA degradation and translation. Together, this work contributes to the basic understanding of gene expression regulation and has potential applications in nucleic acid therapeutics.

ARTseq-FISH reveals position-dependent differences in gene expression of micropatterned mESCs.

Differences in gene-expression profiles between individual cells can give rise to distinct cell fate decisions. Yet how localisation on a micropattern impacts initial changes in mRNA, protein, and phosphoprotein abundance remains unclear. To identify the effect of cellular position on gene expression, we developed a scalable antibody and mRNA targeting sequential fluorescence in situ hybridisation (ARTseq-FISH) method capable of simultaneously profiling mRNAs, proteins, and phosphoproteins in single cells. We studied 67 (phospho-)protein and mRNA targets in individual mouse embryonic stem cells (mESCs) cultured on circular micropatterns. ARTseq-FISH reveals relative changes in both abundance and localisation of mRNAs and (phospho-)proteins during the first 48 hours of exit from pluripotency. We confirm these changes by conventional immunofluorescence and time-lapse microscopy. Chemical labelling, immunofluorescence, and single-cell time-lapse microscopy further show that cells closer to the edge of the micropattern exhibit increased proliferation compared to cells at the centre. Together these data suggest that while gene expression is still highly heterogeneous position-dependent differences in mRNA and protein levels emerge as early as 12 hours after LIF withdrawal.

Proteomic analysis of SARS-CoV-2 particles unveils a key role of G3BP proteins in viral assembly.

Considerable progress has been made in understanding the molecular host-virus battlefield during SARS-CoV-2 infection. Nevertheless, the assembly and egress of newly formed virions are less understood. To identify host proteins involved in viral morphogenesis, we characterize the proteome of SARS-CoV-2 virions produced from A549-ACE2 and Calu-3 cells, isolated via ultracentrifugation on sucrose cushion or by ACE-2 affinity capture. Bioinformatic analysis unveils 92 SARS-CoV-2 virion-associated host factors, providing a valuable resource to better understand the molecular environment of virion production. We reveal that G3BP1 and G3BP2 (G3BP1/2), two major stress granule nucleators, are embedded within virions and unexpectedly favor virion production. Furthermore, we show that G3BP1/2 participate in the formation of cytoplasmic membrane vesicles, that are likely virion assembly sites, consistent with a proviral role of G3BP1/2 in SARS-CoV-2 dissemination. Altogether, these findings provide new insights into host factors required for SARS-CoV-2 assembly with potential implications for future therapeutic targeting.

Exploring the role of transcriptional and post-transcriptional processes in mRNA co-expression.

Co-expression of two or more genes at the single-cell level is usually associated with functional co-regulation. While mRNA co-expression-measured as the correlation in mRNA levels-can be influenced by both transcriptional and post-transcriptional events, transcriptional regulation is typically considered dominant. We review and connect the literature describing transcriptional and post-transcriptional regulation of co-expression. To enhance our understanding, we integrate four datasets spanning single-cell gene expression data, single-cell promoter activity data and individual transcript half-lives. Confirming expectations, we find that positive co-expression necessitates promoter coordination and similar mRNA half-lives. Surprisingly, negative co-expression is favored by differences in mRNA half-lives, contrary to initial predictions from stochastic simulations. Notably, this association manifests specifically within clusters of genes. We further observe a striking compensation between promoter coordination and mRNA half-lives, which additional stochastic simulations suggest might give rise to the observed co-expression patterns. These findings raise intriguing questions about the functional advantages conferred by this compensation between distal kinetic steps.

Noise Minimization in Cell-Free Gene Expression.

Biochemical reactions that involve small numbers of molecules are accompanied by a degree of inherent randomness that results in noisy reaction outcomes. In synthetic biology, the ability to minimize noise particularly during the reconstitution of future synthetic protocells is an outstanding challenge to secure robust and reproducible behavior. Here we show that by encapsulation of a bacterial cell-free gene expression system in water-in-oil droplets, in vitro-synthesized MazF reduces cell-free gene expression noise >2-fold. With stochastic simulations we identify that this noise minimization acts through both increased degradation and the autoregulatory feedback of MazF. Specifically, we find that the expression of MazF enhances the degradation rate of mRNA up to 18-fold in a sequence-dependent manner. This sequence specificity of MazF would allow targeted noise control, making it ideal to integrate into synthetic gene networks. Therefore, including MazF production in synthetic biology can significantly minimize gene expression noise, impacting future design principles of more complex cell-free gene circuits.

TASOR epigenetic repressor cooperates with a CNOT1 RNA degradation pathway to repress HIV.

The Human Silencing Hub (HUSH) complex constituted of TASOR, MPP8 and Periphilin recruits the histone methyl-transferase SETDB1 to spread H3K9me3 repressive marks across genes and transgenes in an integration site-dependent manner. The deposition of these repressive marks leads to heterochromatin formation and inhibits gene expression, but the underlying mechanism is not fully understood. Here, we show that TASOR silencing or HIV-2 Vpx expression, which induces TASOR degradation, increases the accumulation of transcripts derived from the HIV-1 LTR promoter at a post-transcriptional level. Furthermore, using a yeast 2-hybrid screen, we identify new TASOR partners involved in RNA metabolism including the RNA deadenylase CCR4-NOT complex scaffold CNOT1. TASOR and CNOT1 synergistically repress HIV expression from its LTR. Similar to the RNA-induced transcriptional silencing complex found in fission yeast, we show that TASOR interacts with the RNA exosome and RNA Polymerase II, predominantly under its elongating state. Finally, we show that TASOR facilitates the association of RNA degradation proteins with RNA polymerase II and is detected at transcriptional centers. Altogether, we propose that HUSH operates at the transcriptional and post-transcriptional levels to repress HIV proviral expression.

A DNA repair pathway can regulate transcriptional noise to promote cell fate transitions.

Stochastic fluctuations in gene expression ("noise") are often considered detrimental, but fluctuations can also be exploited for benefit (e.g., dither). We show here that DNA base excision repair amplifies transcriptional noise to facilitate cellular reprogramming. Specifically, the DNA repair protein Apex1, which recognizes both naturally occurring and unnatural base modifications, amplifies expression noise while homeostatically maintaining mean expression levels. This amplified expression noise originates from shorter-duration, higher-intensity transcriptional bursts generated by Apex1-mediated DNA supercoiling. The remodeling of DNA topology first impedes and then accelerates transcription to maintain mean levels. This mechanism, which we refer to as "discordant transcription through repair" ("DiThR," which is pronounced "dither"), potentiates cellular reprogramming and differentiation. Our study reveals a potential functional role for transcriptional fluctuations mediated by DNA base modifications in embryonic development and disease.

Transcription and Translation in Cytomimetic Protocells Perform Most Efficiently at Distinct Macromolecular Crowding Conditions.

The formation of cytomimetic protocells that capture the physicochemical aspects of living cells is an important goal in bottom-up synthetic biology. Here, we recreated the crowded cytoplasm in liposome-based protocells and studied the kinetics of cell-free gene expression in these crowded containers. We found that diffusion of key components is affected not only by macromolecular crowding but also by enzymatic activity in the protocell. Surprisingly, size-dependent diffusion in crowded conditions yielded two distinct maxima for protein synthesis, reflecting the differential impact of crowding on transcription and translation. Our experimental data show, for the first time, that macromolecular crowding induces a switch from reaction to diffusion control and that this switch depends on the sizes of the macromolecules involved. These results highlight the need to control the physical environment in the design of synthetic cells.

Post-Transcriptional Noise Control.

Recent evidence indicates that transcriptional bursts are intrinsically amplified by messenger RNA cytoplasmic processing to generate large stochastic fluctuations in protein levels. These fluctuations can be exploited by cells to enable probabilistic bet-hedging decisions. But large fluctuations in gene expression can also destabilize cell-fate commitment. Thus, it is unclear if cells temporally switch from high to low noise, and what mechanisms enable this switch. Here, the discovery of a post-transcriptional mechanism that attenuates noise in HIV is reviewed. Early in its life cycle, HIV amplifies transcriptional fluctuations to probabilistically select alternate fates, whereas at late times, HIV utilizes a post-transcriptional feedback mechanism to commit to a specific fate. Reanalyzing various reported post-transcriptional negative feedback architectures reveals that they attenuate noise more efficiently than classic transcriptional autorepression, leading to the derivation of an assay to detect post-transcriptional motifs. It is hypothesized that coupling transcriptional and post-transcriptional autoregulation enables efficient temporal noise control to benefit developmental bet-hedging decisions.

HIV Latency: Stochastic across Multiple Scales.

Proviral latency is a major barrier to a cure for HIV. In this issue of Cell Host & Microbe, Hataye et al. (2019) show that reactivation of HIV latency is a non-deterministic, highly stochastic (i.e., noisy) process and propose that stochastic transitions to exponential viral expansion require a critical threshold of virus.

Cytoplasmic Amplification of Transcriptional Noise Generates Substantial Cell-to-Cell Variability.

Transcription is an episodic process characterized by probabilistic bursts, but how the transcriptional noise from these bursts is modulated by cellular physiology remains unclear. Using simulations and single-molecule RNA counting, we examined how cellular processes influence cell-to-cell variability (noise). The results show that RNA noise is higher in the cytoplasm than the nucleus in ∼85% of genes across diverse promoters, genomic loci, and cell types (human and mouse). Measurements show further amplification of RNA noise in the cytoplasm, fitting a model of biphasic mRNA conversion between translation- and degradation-competent states. This multi-state translation-degradation of mRNA also causes substantial noise amplification in protein levels, ultimately accounting for ∼74% of intrinsic protein variability in cell populations. Overall, the results demonstrate how noise from transcriptional bursts is intrinsically amplified by mRNA processing, leading to a large super-Poissonian variability in protein levels.

A Post-Transcriptional Feedback Mechanism for Noise Suppression and Fate Stabilization.

Diverse biological systems utilize fluctuations ("noise") in gene expression to drive lineage-commitment decisions. However, once a commitment is made, noise becomes detrimental to reliable function, and the mechanisms enabling post-commitment noise suppression are unclear. Here, we find that architectural constraints on noise suppression are overcome to stabilize fate commitment. Using single-molecule and time-lapse imaging, we find that-after a noise-driven event-human immunodeficiency virus (HIV) strongly attenuates expression noise through a non-transcriptional negative-feedback circuit. Feedback is established through a serial cascade of post-transcriptional splicing, whereby proteins generated from spliced mRNAs auto-deplete their own precursor unspliced mRNAs. Strikingly, this auto-depletion circuitry minimizes noise to stabilize HIV's commitment decision, and a noise-suppression molecule promotes stabilization. This feedback mechanism for noise suppression suggests a functional role for delayed splicing in other systems and may represent a generalizable architecture of diverse homeostatic signaling circuits.

Nonlatching positive feedback enables robust bimodality by decoupling expression noise from the mean.

Fundamental to biological decision-making is the ability to generate bimodal expression patterns where 2 alternate expression states simultaneously exist. Here, we use a combination of single-cell analysis and mathematical modeling to examine the sources of bimodality in the transcriptional program controlling HIV's fate decision between active replication and viral latency. We find that the HIV transactivator of transcription (Tat) protein manipulates the intrinsic toggling of HIV's promoter, the long terminal repeat (LTR), to generate bimodal ON-OFF expression and that transcriptional positive feedback from Tat shifts and expands the regime of LTR bimodality. This result holds for both minimal synthetic viral circuits and full-length virus. Strikingly, computational analysis indicates that the Tat circuit's noncooperative "nonlatching" feedback architecture is optimized to slow the promoter's toggling and generate bimodality by stochastic extinction of Tat. In contrast to the standard Poisson model, theory and experiment show that nonlatching positive feedback substantially dampens the inverse noise-mean relationship to maintain stochastic bimodality despite increasing mean expression levels. Given the rapid evolution of HIV, the presence of a circuit optimized to robustly generate bimodal expression appears consistent with the hypothesis that HIV's decision between active replication and latency provides a viral fitness advantage. More broadly, the results suggest that positive-feedback circuits may have evolved not only for signal amplification but also for robustly generating bimodality by decoupling expression fluctuations (noise) from mean expression levels.

Protein Synthesis in Coupled and Uncoupled Cell-Free Prokaryotic Gene Expression Systems.

Secondary structure formation of mRNA, caused by desynchronization of transcription and translation, is known to impact gene expression in vivo. Yet, inactivation of mRNA by secondary structures in cell-free protein expression is frequently overlooked. Transcription and translation rates are often not highly synchronized in cell-free expression systems, leading to a temporal mismatch between the processes and a drop in efficiency of protein production. By devising a cell-free gene expression platform in which transcriptional and translational elongation are successfully performed independently, we determine that sequence-dependent mRNA secondary structures are the main cause of mRNA inactivation in in vitro gene expression.

Cell-Like Nanostructured Environments Alter Diffusion and Reaction Kinetics in Cell-Free Gene Expression.

In highly crowded and viscous intracellular environments, the kinetics of complex enzymatic reactions are determined by both reaction and diffusion rates. However in vitro studies on transcription and translation often fail to take into account the density of the prokaryotic cytoplasm. Here we mimic the cellular environment by using a porous hydrogel matrix, to study the effects of macromolecular crowding on gene expression. We found that within microgels gene expression is localized, transcription is enhanced up to fivefold, and translation is enhanced up to fourfold. Our results highlight the need to consider the role of the physical environment on complex biochemical reactions, in this case macromolecular crowding, nanoscale spatial organization, and confinement.

Macromolecular crowding creates heterogeneous environments of gene expression in picolitre droplets.

Understanding the dynamics of complex enzymatic reactions in highly crowded small volumes is crucial for the development of synthetic minimal cells. Compartmentalized biochemical reactions in cell-sized containers exhibit a degree of randomness due to the small number of molecules involved. However, it is unknown how the physical environment contributes to the stochastic nature of multistep enzymatic processes. Here, we present a robust method to quantify gene expression noise in vitro using droplet microfluidics. We study the changes in stochasticity in the cell-free gene expression of two genes compartmentalized within droplets as a function of DNA copy number and macromolecular crowding. We find that decreased diffusion caused by a crowded environment leads to the spontaneous formation of heterogeneous microenvironments of mRNA as local production rates exceed the diffusion rates of macromolecules. This heterogeneity leads to a higher probability of the molecular machinery staying in the same microenvironment, directly increasing the system's stochasticity.

Enhanced transcription rates in membrane-free protocells formed by coacervation of cell lysate.

Liquid-liquid phase transitions in complex mixtures of proteins and other molecules produce crowded compartments supporting in vitro transcription and translation. We developed a method based on picoliter water-in-oil droplets to induce coacervation in Escherichia coli cell lysate and follow gene expression under crowded and noncrowded conditions. Coacervation creates an artificial cell-like environment in which the rate of mRNA production is increased significantly. Fits to the measured transcription rates show a two orders of magnitude larger binding constant between DNA and T7 RNA polymerase, and five to six times larger rate constant for transcription in crowded environments, strikingly similar to in vivo rates. The effect of crowding on interactions and kinetics of the fundamental machinery of gene expression has a direct impact on our understanding of biochemical networks in vivo. Moreover, our results show the intrinsic potential of cellular components to facilitate macromolecular organization into membrane-free compartments by phase separation.