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.

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.

Decision making at a subcellular level determines the outcome of bacteriophage infection.

When the process of cell-fate determination is examined at single-cell resolution, it is often observed that individual cells undergo different fates even when subject to identical conditions. This "noisy" phenotype is usually attributed to the inherent stochasticity of chemical reactions in the cell. Here we demonstrate how the observed single-cell heterogeneity can be explained by a cascade of decisions occurring at the subcellular level. We follow the postinfection decision in bacteriophage lambda at single-virus resolution, and show that a choice between lysis and lysogeny is first made at the level of the individual virus. The decisions by all viruses infecting a single cell are then integrated in a precise (noise-free) way, such that only a unanimous vote by all viruses leads to the establishment of lysogeny. By detecting and integrating over the subcellular "hidden variables," we are able to predict the level of noise measured at the single-cell level.

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.

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.

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.

Combining protein and mRNA quantification to decipher transcriptional regulation.

We combine immunofluorescence and single-molecule fluorescence in situ hybridization (smFISH), followed by automated image analysis, to quantify the concentration of nuclear transcription factors, number of transcription factors bound, and number of nascent mRNAs synthesized at individual gene loci. A theoretical model is used to decipher how transcription factor binding modulates the stochastic kinetics of mRNA production. We demonstrate this approach by examining the regulation of hunchback in the early Drosophila embryo.

DksA involvement in transcription fidelity buffers stochastic epigenetic change.

DksA is an auxiliary transcription factor that interacts with RNA polymerase and influences gene expression. Depending on the promoter, DksA can be a positive or negative regulator of transcription initiation. Moreover, DksA has a substantial effect on transcription elongation where it prevents the collision of transcription and replication machineries, plays a key role in maintaining transcription elongation when translation and transcription are uncoupled and has been shown to be involved in transcription fidelity. Here, we assessed the role of DksA in transcription fidelity by monitoring stochastic epigenetic switching in the lac operon (with and without an error-prone transcription slippage sequence), partial phenotypic suppression of a lacZ nonsense allele, as well as monitoring the number of lacI mRNA transcripts produced in the presence and absence of DksA via an operon fusion and single molecule fluorescent in situ hybridization studies. We present data showing that DksA acts to maintain transcription fidelity in vivo and the role of DksA seems to be distinct from that of the GreA and GreB transcription fidelity factors.

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.

Removal of 8-oxo-GTP by MutT hydrolase is not a major contributor to transcriptional fidelity.

Living in an oxygen-rich environment is dangerous for a cell. Reactive oxygen species can damage DNA, RNA, protein and lipids. The MutT protein in Escherichia coli removes 8-oxo-deoxyguanosine triphosphate (8-oxo-dGTP) and 8-oxo-guanosine triphosphate (8-oxo-GTP) from the nucleotide pools precluding incorporation into DNA and RNA. While 8-oxo-dGTP incorporation into DNA is mutagenic, it is not clear if 8-oxo-GTP incorporation into RNA can have phenotypic consequences for the cell. We use a bistable epigenetic switch sensitive to transcription errors in the Escherichia coli lacI transcript to monitor transient RNA errors. We do not observe any increase in epigenetic switching in mutT cells. We revisit the original observation of partial phenotypic suppression of a lacZamber allele in a mutT background that was attributed to RNA errors. We find that Lac+ revertants can completely account for the increase in ß-galactosidase levels in mutT lacZamber cultures, without invoking participation of transient transcription errors. Moreover, we observe a fluctuation type of distribution of ß-galactosidase appearance in a growing culture, consistent with Lac+ DNA revertant events. We conclude that the absence of MutT produces a DNA mutator but does not equally create an RNA mutator.

The maternal-to-zygotic transition targets actin to promote robustness during morphogenesis.

Robustness is a property built into biological systems to ensure stereotypical outcomes despite fluctuating inputs from gene dosage, biochemical noise, and the environment. During development, robustness safeguards embryos against structural and functional defects. Yet, our understanding of how robustness is achieved in embryos is limited. While much attention has been paid to the role of gene and signaling networks in promoting robust cell fate determination, little has been done to rigorously assay how mechanical processes like morphogenesis are designed to buffer against variable conditions. Here we show that the cell shape changes that drive morphogenesis can be made robust by mechanisms targeting the actin cytoskeleton. We identified two novel members of the Vinculin/α-Catenin Superfamily that work together to promote robustness during Drosophila cellularization, the dramatic tissue-building event that generates the primary epithelium of the embryo. We find that zygotically-expressed Serendipity-α (Sry-α) and maternally-loaded Spitting Image (Spt) share a redundant, actin-regulating activity during cellularization. Spt alone is sufficient for cellularization at an optimal temperature, but both Spt plus Sry-α are required at high temperature and when actin assembly is compromised by genetic perturbation. Our results offer a clear example of how the maternal and zygotic genomes interact to promote the robustness of early developmental events. Specifically, the Spt and Sry-α collaboration is informative when it comes to genes that show both a maternal and zygotic requirement during a given morphogenetic process. For the cellularization of Drosophilids, Sry-α and its expression profile may represent a genetic adaptive trait with the sole purpose of making this extreme event more reliable. Since all morphogenesis depends on cytoskeletal remodeling, both in embryos and adults, we suggest that robustness-promoting mechanisms aimed at actin could be effective at all life stages.

Chemotactic adaptation kinetics of individual Escherichia coli cells.

Escherichia coli chemotaxis serves as a paradigm for the way living cells respond and adapt to changes in their environment. The chemotactic response has been characterized at the level of individual flagellar motors and in populations of swimming cells. However, it has not been previously possible to quantify accurately the adaptive response of a single, multiflagellated cell. Here, we use our recently developed optical trapping technique to characterize the swimming behavior of individual bacteria as they respond to sudden changes in the chemical environment. We follow the adaptation kinetics of E. coli to varying magnitudes of step-up and step-down changes in concentration of chemoattractant. We quantify two features of adaptation and how they vary with stimulus strength: abruptness (the degree to which return to prestimulus behavior occurs within a small number of run/tumble events) and overshoot (the degree of excessive response before the return to prestimulus behavior). We also characterize the asymmetry between step-up and step-down responses, observed at the single-cell level. Our findings provide clues to an improved understanding of chemotactic adaptation.

Optical measurement of cycle-dependent cell growth.

Determining the growth patterns of single cells offers answers to some of the most elusive questions in contemporary cell biology: how cell growth is regulated and how cell size distributions are maintained. For example, a linear growth in time implies that there is no regulation required to maintain homeostasis; an exponential pattern indicates the opposite. Recently, there has been great effort to measure single cells using microelectromechanical systems technology, and several important questions have been explored. However, a unified, easy-to-use methodology to measure the growth rate of individual adherent cells of various sizes has been lacking. Here we demonstrate that a newly developed optical interferometric technique, known as spatial light interference microscopy, can measure the cell dry mass of many individual adherent cells in various conditions, over spatial scales from micrometers to millimeters, temporal scales ranging from seconds to days, and cell types ranging from bacteria to mammalian cells. We found evidence of exponential growth in Escherichia coli, which agrees very well with other recent reports. Perhaps most importantly, combining spatial light interference microscopy with fluorescence imaging provides a unique method for studying cell cycle-dependent growth. Thus, by using a fluorescent reporter for the S phase, we measured single cell growth over each phase of the cell cycle in human osteosarcoma U2OS cells and found that the G2 phase exhibits the highest growth rate, which is mass-dependent and can be approximated by an exponential.

Coinfecting phages impede each other's entry into the cell.

The developmental choice made by temperate phages, between cell death (lysis) and viral dormancy (lysogeny), is influenced by the relative abundance of viruses and hosts in the environment. The paradigm for this abundance-driven decision is phage lambda of E. coli, whose propensity to lysogenize increases with the number of viruses coinfecting the same bacterium. It is believed that lambda uses this number to infer whether phages or bacteria outnumber each other. However, this interpretation is premised on an accurate mapping between the extracellular phage-to-bacteria ratio and the intracellular multiplicity of infection (MOI). Here, we show this premise to be faulty. 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, performed in a microfluidic device and interpreted using a stochastic model, reveal that the probability and rate of phage entry decrease with the number of adsorbed phages. This decrease reflects an MOI-dependent perturbation to host physiology caused by phage attachment, as evidenced by compromised membrane integrity and loss of membrane potential. The dependence of entry dynamics on the surrounding medium results in a strong impact on the infection outcome, while the protracted entry of coinfecting phages increases the heterogeneity in infection outcome at a given MOI. Our findings in lambda, and similar results we obtained for phages T5 and P1, demonstrate the previously unappreciated role played by entry dynamics in determining the outcome of bacteriophage infection.

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.

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.

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.