Transcription-replication interactions reveal bacterial genome regulation.

Organisms determine the transcription rates of thousands of genes through a few modes of regulation that recur across the genome1. In bacteria, the relationship between the regulatory architecture of a gene and its expression is well understood for individual model gene circuits2,3. However, a broader perspective of these dynamics at the genome scale is lacking, in part because bacterial transcriptomics has hitherto captured only a static snapshot of expression averaged across millions of cells4. As a result, the full diversity of gene expression dynamics and their relation to regulatory architecture remains unknown. Here we present a novel genome-wide classification of regulatory modes based on the transcriptional response of each gene to its own replication, which we term the transcription-replication interaction profile (TRIP). Analysing single-bacterium RNA-sequencing data, we found that the response to the universal perturbation of chromosomal replication integrates biological regulatory factors with biophysical molecular events on the chromosome to reveal the local regulatory context of a gene. Whereas the TRIPs of many genes conform to a gene dosage-dependent pattern, others diverge in distinct ways, and this is shaped by factors such as intra-operon position and repression state. By revealing the underlying mechanistic drivers of gene expression heterogeneity, this work provides a quantitative, biophysical framework for modelling replication-dependent expression dynamics.

Gene expression in growing cells: A biophysical primer.

Cell growth and gene expression, two essential elements of all living systems, have long been the focus of biophysical interrogation. Advances in experimental single-cell methods have invigorated theoretical studies into these processes. However, until recently, there was little dialog between the two areas of study. In particular, most theoretical models for gene regulation assumed gene activity to be oblivious to the progression of the cell cycle between birth and division. But, in fact, there are numerous ways in which the periodic character of all cellular observables can modulate gene expression. The molecular factors required for transcription and translation-RNA polymerase, transcription factors, ribosomes-increase in number during the cell cycle, but are also diluted due to the continuous increase in cell volume. The replication of the genome changes the dosage of those same cellular players but also provides competing targets for regulatory binding. Finally, cell division reduces their number again, and so forth. Stochasticity is inherent to all these biological processes, manifested in fluctuations in the synthesis and degradation of new cellular components as well as the random partitioning of molecules at each cell division event. The notion of gene expression as stationary is thus hard to justify. In this review, we survey the emerging paradigm of cell-cycle regulated gene expression, with an emphasis on the global expression patterns rather than gene-specific regulation. We discuss recent experimental reports where cell growth and gene expression were simultaneously measured in individual cells, providing first glimpses into the coupling between the two, and motivating several questions. How do the levels of gene expression products - mRNA and protein - scale with the cell volume and cell-cycle progression? What are the molecular origins of the observed scaling laws, and when do they break down to yield non-canonical behavior? What are the consequences of cell-cycle dependence for the heterogeneity ("noise") in gene expression within a cell population? While the experimental findings, not surprisingly, differ among genes, organisms, and environmental conditions, several theoretical models have emerged that attempt to reconcile these differences and form a unifying framework for understanding gene expression in growing cells.

Flagellar dynamics reveal fluctuations and kinetic limit in the Escherichia coli chemotaxis network.

The Escherichia coli chemotaxis network, by which bacteria modulate their random run/tumble swimming pattern to navigate their environment, must cope with unavoidable number fluctuations ("noise") in its molecular constituents like other signaling networks. The probability of clockwise (CW) flagellar rotation, or CW bias, is a measure of the chemotaxis network's output, and its temporal fluctuations provide a proxy for network noise. Here we quantify fluctuations in the chemotaxis signaling network from the switching statistics of flagella, observed using time-resolved fluorescence microscopy of individual optically trapped E. coli cells. This approach allows noise to be quantified across the dynamic range of the network. Large CW bias fluctuations are revealed at steady state, which may play a critical role in driving flagellar switching and cell tumbling. When the network is stimulated chemically to higher activity, fluctuations dramatically decrease. A stochastic theoretical model, inspired by work on gene expression noise, points to CheY activation occurring in bursts, driving CW bias fluctuations. This model also shows that an intrinsic kinetic ceiling on network activity places an upper limit on activated CheY and CW bias, which when encountered suppresses network fluctuations. This limit may also prevent cells from tumbling unproductively in steep gradients.

Physiological stress drives the emergence of a Salmonella subpopulation through ribosomal RNA regulation.

Bacteria undergo cycles of growth and starvation to which they must adapt swiftly. One important strategy for adjusting growth rates relies on ribosomal levels. Although high ribosomal levels are required for fast growth, their dynamics during starvation remain unclear. Here, we analyzed ribosomal RNA (rRNA) content of individual Salmonella cells by using fluorescence in situ hybridization (rRNA-FISH) and measured a dramatic decrease in rRNA numbers only in a subpopulation during nutrient limitation, resulting in a bimodal distribution of cells with high and low rRNA content. During nutritional upshifts, the two subpopulations were associated with distinct phenotypes. Using a transposon screen coupled with rRNA-FISH, we identified two mutants, DksA and RNase I, acting on rRNA transcription shutdown and degradation, which abolished the formation of the subpopulation with low rRNA content. Our work identifies a bacterial mechanism for regulation of ribosomal bimodality that may be beneficial for population survival during starvation.

CO-INFECTING PHAGES IMPEDE EACH OTHER'S ENTRY INTO THE CELL.

Bacteriophage lambda tunes its propensity to lysogenize based on the number of viral genome copies inside the infected cell. Viral self-counting is believed to serve as a way of inferring the abundance of available hosts in the environment. This interpretation is premised on an accurate mapping between the extracellular phage-to-bacteria ratio and the intracellular multiplicity of infection (MOI). However, here we show this premise to be untrue. By simultaneously labeling phage capsids and genomes, we find that, while the number of phages landing on each cell reliably samples the population ratio, the number of phages entering the cell does not. Single-cell infections, followed in a microfluidic device and interpreted using a stochastic model, reveal that the probability and rate of individual phage entries decrease with MOI. This decrease reflects an MOI-dependent perturbation to host physiology caused by phage landing, evidenced by compromised membrane integrity and loss of membrane potential. The dependence of phage entry dynamics on the surrounding medium is found to result in a strong impact of environmental conditions on the infection outcome, while the protracted entry of co-infecting phages increases the cell-to-cell variability in infection outcome at a given MOI. Our findings demonstrate the previously unappreciated role played by entry dynamics in determining the outcome of bacteriophage infection.

Transcription-replication interactions reveal principles of bacterial genome regulation.

Organisms determine the transcription rates of thousands of genes through a few modes of regulation that recur across the genome1. These modes interact with a changing cellular environment to yield highly dynamic expression patterns2. In bacteria, the relationship between a gene's regulatory architecture and its expression is well understood for individual model gene circuits3,4. However, a broader perspective of these dynamics at the genome-scale is lacking, in part because bacterial transcriptomics have hitherto captured only a static snapshot of expression averaged across millions of cells5. As a result, the full diversity of gene expression dynamics and their relation to regulatory architecture remains unknown. Here we present a novel genome-wide classification of regulatory modes based on each gene's transcriptional response to its own replication, which we term the Transcription-Replication Interaction Profile (TRIP). We found that the response to the universal perturbation of chromosomal replication integrates biological regulatory factors with biophysical molecular events on the chromosome to reveal a gene's local regulatory context. While the TRIPs of many genes conform to a gene dosage-dependent pattern, others diverge in distinct ways, including altered timing or amplitude of expression, and this is shaped by factors such as intra-operon position, repression state, or presence on mobile genetic elements. Our transcriptome analysis also simultaneously captures global properties, such as the rates of replication and transcription, as well as the nestedness of replication patterns. This work challenges previous notions of the drivers of expression heterogeneity within a population of cells, and unearths a previously unseen world of gene transcription dynamics.

Bacteriophage self-counting in the presence of viral replication.

When host cells are in low abundance, temperate bacteriophages opt for dormant (lysogenic) infection. Phage lambda implements this strategy by increasing the frequency of lysogeny at higher multiplicity of infection (MOI). However, it remains unclear how the phage reliably counts infecting viral genomes even as their intracellular number increases because of replication. By combining theoretical modeling with single-cell measurements of viral copy number and gene expression, we find that instead of hindering lambda's decision, replication facilitates it. In a nonreplicating mutant, viral gene expression simply scales with MOI rather than diverging into lytic (virulent) and lysogenic trajectories. A similar pattern is followed during early infection by wild-type phage. However, later in the infection, the modulation of viral replication by the decision genes amplifies the initially modest gene expression differences into divergent trajectories. Replication thus ensures the optimal decision-lysis upon single-phage infection and lysogeny at higher MOI.

Spliceosome-targeted therapies trigger an antiviral immune response in triple-negative breast cancer.

Many oncogenic insults deregulate RNA splicing, often leading to hypersensitivity of tumors to spliceosome-targeted therapies (STTs). However, the mechanisms by which STTs selectively kill cancers remain largely unknown. Herein, we discover that mis-spliced RNA itself is a molecular trigger for tumor killing through viral mimicry. In MYC-driven triple-negative breast cancer, STTs cause widespread cytoplasmic accumulation of mis-spliced mRNAs, many of which form double-stranded structures. Double-stranded RNA (dsRNA)-binding proteins recognize these endogenous dsRNAs, triggering antiviral signaling and extrinsic apoptosis. In immune-competent models of breast cancer, STTs cause tumor cell-intrinsic antiviral signaling, downstream adaptive immune signaling, and tumor cell death. Furthermore, RNA mis-splicing in human breast cancers correlates with innate and adaptive immune signatures, especially in MYC-amplified tumors that are typically immune cold. These findings indicate that dsRNA-sensing pathways respond to global aberrations of RNA splicing in cancer and provoke the hypothesis that STTs may provide unexplored strategies to activate anti-tumor immune pathways.

Stochastic simulation and statistical inference platform for visualization and estimation of transcriptional kinetics.

Recent advances in single-molecule fluorescent imaging have enabled quantitative measurements of transcription at a single gene copy, yet an accurate understanding of transcriptional kinetics is still lacking due to the difficulty of solving detailed biophysical models. Here we introduce a stochastic simulation and statistical inference platform for modeling detailed transcriptional kinetics in prokaryotic systems, which has not been solved analytically. The model includes stochastic two-state gene activation, mRNA synthesis initiation and stepwise elongation, release to the cytoplasm, and stepwise co-transcriptional degradation. Using the Gillespie algorithm, the platform simulates nascent and mature mRNA kinetics of a single gene copy and predicts fluorescent signals measurable by time-lapse single-cell mRNA imaging, for different experimental conditions. To approach the inverse problem of estimating the kinetic parameters of the model from experimental data, we develop a heuristic optimization method based on the genetic algorithm and the empirical distribution of mRNA generated by simulation. As a demonstration, we show that the optimization algorithm can successfully recover the transcriptional kinetics of simulated and experimental gene expression data. The platform is available as a MATLAB software package at https://data.caltech.edu/records/1287.

Measuring transcription at a single gene copy reveals hidden drivers of bacterial individuality.

Single-cell measurements of mRNA copy numbers inform our understanding of stochastic gene expression1-3, but these measurements coarse-grain over the individual copies of the gene, where transcription and its regulation take place stochastically4,5. Here, we combine single-molecule quantification of mRNA and gene loci to measure the transcriptional activity of an endogenous gene in individual Escherichia coli bacteria. When interpreted using a theoretical model for mRNA dynamics, the single-cell data allow us to obtain the probabilistic rates of promoter switching, transcription initiation and elongation, mRNA release and degradation. Unexpectedly, we find that gene activity can be strongly coupled to the transcriptional state of another copy of the same gene present in the cell, and to the event of gene replication during the bacterial cell cycle. These gene-copy and cell-cycle correlations demonstrate the limits of mapping whole-cell mRNA numbers to the underlying stochastic gene activity and highlight the contribution of previously hidden variables to the observed population heterogeneity.

Cofilin-Mediated Actin Stress Response Is Maladaptive in Heat-Stressed Embryos.

Environmental stress threatens the fidelity of embryonic morphogenesis. Heat, for example, is a teratogen. Yet how heat affects morphogenesis is poorly understood. Here, we identify a heat-inducible actin stress response (ASR) in Drosophila embryos that is mediated by the activation of the actin regulator Cofilin. Similar to ASR in adult mammalian cells, heat stress in fly embryos triggers the assembly of intra-nuclear actin rods. Rods measure up to a few microns in length, and their assembly depends on elevated free nuclear actin concentration and Cofilin. Outside the nucleus, heat stress causes Cofilin-dependent destabilization of filamentous actin (F-actin) in actomyosin networks required for morphogenesis. F-actin destabilization increases the chance of morphogenesis mistakes. Blocking the ASR by reducing Cofilin dosage improves the viability of heat-stressed embryos. However, improved viability correlates with restoring F-actin stability, not rescuing morphogenesis. Thus, ASR endangers embryos, perhaps by shifting actin from cytoplasmic filaments to an elevated nuclear pool.

Infection by bacteriophage lambda: an evolving paradigm for cellular individuality.

Since the earliest days of molecular biology, bacteriophage lambda has served to illuminate cellular function. Among its many roles, lambda infection is a paradigm for phenotypic heterogeneity among genetically identical cells. Early studies attributed this cellular individuality to random biochemical fluctuations, or 'noise'. More recently, however, attention has turned to the role played by deterministic hidden variables in driving single-cell behavior. Here, I briefly describe how studies in lambda are driving the shift in our understanding of cellular heterogeneity, allowing us to better appreciate the precision at which cells function.

The transcription fidelity factor GreA impedes DNA break repair.

Homologous recombination repairs DNA double-strand breaks and must function even on actively transcribed DNA. Because break repair prevents chromosome loss, the completion of repair is expected to outweigh the transcription of broken templates. However, the interplay between DNA break repair and transcription processivity is unclear. Here we show that the transcription factor GreA inhibits break repair in Escherichia coli. GreA restarts backtracked RNA polymerase and hence promotes transcription fidelity. We report that removal of GreA results in markedly enhanced break repair via the classic RecBCD-RecA pathway. Using a deep-sequencing method to measure chromosomal exonucleolytic degradation, we demonstrate that the absence of GreA limits RecBCD-mediated resection. Our findings suggest that increased RNA polymerase backtracking promotes break repair by instigating RecA loading by RecBCD, without the influence of canonical Chi signals. The idea that backtracked RNA polymerase can stimulate recombination presents a DNA transaction conundrum: a transcription fidelity factor that compromises genomic integrity.

Stochastic Kinetics of Nascent RNA.

The stochastic kinetics of transcription is typically inferred from the distribution of RNA numbers in individual cells. However, cellular RNA reflects additional processes downstream of transcription, hampering this analysis. In contrast, nascent (actively transcribed) RNA closely reflects the kinetics of transcription. We present a theoretical model for the stochastic kinetics of nascent RNA, which we solve to obtain the probability distribution of nascent RNA per gene. The model allows us to evaluate the kinetic parameters of transcription from single-cell measurements of nascent RNA. The model also predicts surprising discontinuities in the distribution of nascent RNA, a feature which we verify experimentally.

Single-Cell Studies of Phage λ: Hidden Treasures Under Occam's Rug.

Studies over more than half a century have resulted in what some consider a complete narrative for the life cycle of bacteriophage λ. However, this narrative is only complete within the limited resolution offered by the traditional genetic and biochemical approaches that were used to create it. A recent series of studies performed at the single-cell and single-phage levels has revealed a wealth of previously unknown features. By pointing to many open questions, these new studies highlight the limitations of our current understanding of λ, but they also initiate the process of forming a more detailed and quantitative narrative for the system.

Membrane Supply and Demand Regulates F-Actin in a Cell Surface Reservoir.

Cells store membrane in surface reservoirs of pits and protrusions. These membrane reservoirs facilitate cell shape change and buffer mechanical stress, but we do not know how reservoir dynamics are regulated. During cellularization, the first cytokinesis in Drosophila embryos, a reservoir of microvilli unfolds to fuel cleavage furrow ingression. We find that regulated exocytosis adds membrane to the reservoir before and during unfolding. Dynamic F-actin deforms exocytosed membrane into microvilli. Single microvilli extend and retract in ∼20 s, while the overall reservoir is depleted in sync with furrow ingression over 60-70 min. Using pharmacological and genetic perturbations, we show that exocytosis promotes microvillar F-actin assembly, while furrow ingression controls microvillar F-actin disassembly. Thus, reservoir F-actin and, consequently, reservoir dynamics are regulated by membrane supply from exocytosis and membrane demand from furrow ingression.

Measurement of gene regulation in individual cells reveals rapid switching between promoter states.

In vivo mapping of transcription-factor binding to the transcriptional output of the regulated gene is hindered by probabilistic promoter occupancy, the presence of multiple gene copies, and cell-to-cell variability. We demonstrate how to overcome these obstacles in the lysogeny maintenance promoter of bacteriophage lambda, P(RM). We simultaneously measured the concentration of the lambda repressor CI and the number of messenger RNAs (mRNAs) from P(RM) in individual Escherichia coli cells, and used a theoretical model to identify the stochastic activity corresponding to different CI binding configurations. We found that switching between promoter configurations is faster than mRNA lifetime and that individual gene copies within the same cell act independently. The simultaneous quantification of transcription factor and promoter activity, followed by stochastic theoretical analysis, provides a tool that can be applied to other genetic circuits.

Single-cell analysis of transcription kinetics across the cell cycle.

Transcription is a highly stochastic process. To infer transcription kinetics for a gene-of-interest, researchers commonly compare the distribution of mRNA copy-number to the prediction of a theoretical model. However, the reliability of this procedure is limited because the measured mRNA numbers represent integration over the mRNA lifetime, contribution from multiple gene copies, and mixing of cells from different cell-cycle phases. We address these limitations by simultaneously quantifying nascent and mature mRNA in individual cells, and incorporating cell-cycle effects in the analysis of mRNA statistics. We demonstrate our approach on Oct4 and Nanog in mouse embryonic stem cells. Both genes follow similar two-state kinetics. However, Nanog exhibits slower ON/OFF switching, resulting in increased cell-to-cell variability in mRNA levels. Early in the cell cycle, the two copies of each gene exhibit independent activity. After gene replication, the probability of each gene copy to be active diminishes, resulting in dosage compensation.

The spliceosome is a therapeutic vulnerability in MYC-driven cancer.

MYC (also known as c-MYC) overexpression or hyperactivation is one of the most common drivers of human cancer. Despite intensive study, the MYC oncogene remains recalcitrant to therapeutic inhibition. MYC is a transcription factor, and many of its pro-tumorigenic functions have been attributed to its ability to regulate gene expression programs. Notably, oncogenic MYC activation has also been shown to increase total RNA and protein production in many tissue and disease contexts. While such increases in RNA and protein production may endow cancer cells with pro-tumour hallmarks, this increase in synthesis may also generate new or heightened burden on MYC-driven cancer cells to process these macromolecules properly. Here we discover that the spliceosome is a new target of oncogenic stress in MYC-driven cancers. We identify BUD31 as a MYC-synthetic lethal gene in human mammary epithelial cells, and demonstrate that BUD31 is a component of the core spliceosome required for its assembly and catalytic activity. Core spliceosomal factors (such as SF3B1 and U2AF1) associated with BUD31 are also required to tolerate oncogenic MYC. Notably, MYC hyperactivation induces an increase in total precursor messenger RNA synthesis, suggesting an increased burden on the core spliceosome to process pre-mRNA. In contrast to normal cells, partial inhibition of the spliceosome in MYC-hyperactivated cells leads to global intron retention, widespread defects in pre-mRNA maturation, and deregulation of many essential cell processes. Notably, genetic or pharmacological inhibition of the spliceosome in vivo impairs survival, tumorigenicity and metastatic proclivity of MYC-dependent breast cancers. Collectively, these data suggest that oncogenic MYC confers a collateral stress on splicing, and that components of the spliceosome may be therapeutic entry points for aggressive MYC-driven cancers.