Stochastic activation of a DNA damage response causes cell-to-cell mutation rate variation

Alkylative damage of mRNA leads to ribosome stalling and rescue by trans translation in bacteria

Similar to DNA replication, translation of the genetic code by the ribosome is hypothesized to be exceptionally sensitive to small chemical changes to its template mRNA. Here we show that the addition of common alkylating agents to growing cultures of Escherichia coli leads to the accumulation of several adducts within RNA, including N(1)-methyladenosine (m¹A). As expected, the introduction of m¹A to model mRNAs was found to reduce the rate of peptide bond formation by three orders of magnitude in a well-defined in vitro system. These observations suggest that alkylative stress is likely to stall translation in vivo and necessitates the activation of ribosome-rescue pathways. Indeed, the addition of alkylation agents was found to robustly activate the transfer-messenger RNA system, even when transcription was inhibited. Our findings suggest that bacteria carefully monitor the chemical integrity of their mRNA and they evolved rescue pathways to cope with its effect on translation.

Preexisting variation in DNA damage response predicts the fate of single mycobacteria under stress

Clonal microbial populations are inherently heterogeneous, and this diversification is often considered as an adaptation strategy. In clinical infections, phenotypic diversity is found to be associated with drug tolerance, which in turn could evolve into genetic resistance. Mycobacterium tuberculosis, which ranks among the top ten causes of mortality with high incidence of drug-resistant infections, exhibits considerable phenotypic diversity. In this study, we quantitatively analyze the cellular dynamics of DNA damage responses in mycobacteria using microfluidics and live-cell fluorescence imaging. We show that individual cells growing under optimal conditions experience sporadic DNA-damaging events manifested by RecA expression pulses. Single-cell responses to these events occur as transient pulses of fluorescence expression, which are dependent on the gene-network structure but are triggered by extrinsic signals. We demonstrate that preexisting subpopulations, with discrete levels of DNA damage response, are associated with differential susceptibility to fluoroquinolones. Our findings reveal that the extent of DNA integrity prior to drug exposure impacts the drug activity against mycobacteria, with conceivable therapeutic implications.

Occurrence and repair of alkylating stress in the intracellular pathogen Brucella abortus

It is assumed that intracellular pathogenic bacteria have to cope with DNA alkylating stress within host cells. Here we use single-cell reporter systems to show that the pathogen Brucella abortus does encounter alkylating stress during the first hours of macrophage infection. Genes encoding direct repair and base-excision repair pathways are required by B. abortus to face this stress in vitro and in a mouse infection model. Among these genes, ogt is found to be under the control of the conserved cell-cycle transcription factor GcrA. Our results highlight that the control of DNA repair in B. abortus displays distinct features that are not present in model organisms such as Escherichia coli.

It is assumed that intracellular pathogenic bacteria must cope with DNA alkylating stress within host cells. Here, Poncin et al. show that the pathogen Brucella abortus does encounter alkylating stress within macrophages, and shed light into the pathways required for DNA repair in this organism.

A Quantitative Model Explains Single-Cell Dynamics of the Adaptive Response in Escherichia coli

DNA damage caused by alkylating chemicals induces an adaptive response in Escherichia coli that increases the tolerance of cells to further damage. Signaling of the response occurs through irreversible methylation of the Ada protein, which acts as a DNA repair protein and damage sensor. Methylated Ada induces its own gene expression through a positive feedback loop. However, random fluctuations in the abundance of Ada jeopardize the reliability of the induction signal. I developed a quantitative model to test how gene expression noise and feedback amplification affect the fidelity of the adaptive response. A remarkably simple model accurately reproduced experimental observations from single-cell measurements of gene expression dynamics in a microfluidic device. Stochastic simulations showed that delays in the adaptive response are a direct consequence of the very low number of Ada molecules present to signal DNA damage. For cells that have zero copies of Ada, response activation becomes a memoryless process that is dictated by an exponential waiting time distribution between basal Ada expression events. Experiments also confirmed the model prediction that the strength of the adaptive response drops with an increasing growth rate of cells.

Bounding the stationary distributions of the chemical master equation via mathematical programming

The stochastic dynamics of biochemical networks are usually modeled with the chemical master equation (CME). The stationary distributions of CMEs are seldom solvable analytically, and numerical methods typically produce estimates with uncontrolled errors. Here, we introduce mathematical programming approaches that yield approximations of these distributions with computable error bounds which enable the verification of their accuracy. First, we use semidefinite programming to compute increasingly tighter upper and lower bounds on the moments of the stationary distributions for networks with rational propensities. Second, we use these moment bounds to formulate linear programs that yield convergent upper and lower bounds on the stationary distributions themselves, their marginals, and stationary averages. The bounds obtained also provide a computational test for the uniqueness of the distribution. In the unique case, the bounds form an approximation of the stationary distribution with a computable bound on its error. In the nonunique case, our approach yields converging approximations of the ergodic distributions. We illustrate our methodology through several biochemical examples taken from the literature: Schlögl's model for a chemical bifurcation, a two-dimensional toggle switch, a model for bursty gene expression, and a dimerization model with multiple stationary distributions.

Transcription fidelity: New paradigms in epigenetic inheritance, genome instability and disease

RNA transcription errors are transient, yet frequent, events that do have consequences for the cell. However, until recently we lacked the tools to empirically measure and study these errors. Advances in RNA library preparation and next generation sequencing (NGS) have allowed the spectrum of transcription errors to be empirically measured over the entire transcriptome and in nascent transcripts. Combining these powerful methods with forward and reverse genetic strategies has refined our understanding of transcription factors known to enhance RNA accuracy and will enable the discovery of new candidates. Furthermore, these approaches will shed additional light on the complex interplay between transcription fidelity and other DNA transactions, such as replication and repair, and explore a role for transcription errors in cellular evolution and disease.

From single bacterial cell imaging towards in vivo single-molecule biochemistry studies

Bacteria as single-cell organisms are important model systems to study cellular mechanisms and functions. In recent years and with the help of advanced fluorescence microscopy techniques, immense progress has been made in characterizing and quantifying the behavior of single bacterial cells on the basis of molecular interactions and assemblies in the complex environment of live cultures. Importantly, single-molecule imaging enables the in vivo determination of the stoichiometry and molecular architecture of subcellular structures, yielding detailed, quantitative, spatiotemporally resolved molecular maps and unraveling dynamic heterogeneities and subpopulations on the subcellular level. Nevertheless, open challenges remain. Here, we review the past and current status of the field, discuss example applications and give insights into future trends.

Transcription-Coupled Repair: From Cells to Single Molecules and Back Again

Transcription-coupled repair is mediated by the Mfd protein. TCR is defined as the preferential repair of DNA lesions in the transcribed strand of actively transcribed genes, and is opposed to the strand-aspecific global genome repair. The Mfd protein mediates TCR by binding to and displacing RNA polymerase, which is stalled at a DNA lesion on the transcribed strand of DNA, then recruiting UvrA and UvrB. The repair cascade results in the recruitment of, and DNA excision by, UvrC; removal of the damage-bearing oligonucleotide by UvrD; "filling-in" of the DNA by DNA polymerase; and sealing of the strands by DNA ligase. The gene required for Mfd was originally identified as a gene needed for the "mutation frequency decline" phenotype in which the repair of certain UV-induced lesions in the transcribed strand of tRNA genes is increased when cells are forced to delay replication immediately following UV exposure. This review will focus on the genetics that led to the discovery of the Mfd gene; summarize the subsequent biochemical, structural and single-molecule interrogations of the Mfd protein; and explore the more recent findings of Mfd in mutagenesis.

Enhanced emergence of antibiotic-resistant pathogenic bacteria after in vitro induction with cancer chemotherapy drugs

BACKGROUND

Infections with antibiotic-resistant pathogens in cancer patients are a leading cause of mortality. Cancer patients are treated with compounds that can damage bacterial DNA, potentially triggering the SOS response, which in turn enhances the bacterial mutation rate. Antibiotic resistance readily occurs after mutation of bacterial core genes. Thus, we tested whether cancer chemotherapy drugs enhance the emergence of resistant mutants in commensal bacteria.

METHODS

Induction of the SOS response was tested after the incubation of Escherichia coli biosensors with 39 chemotherapeutic drugs at therapeutic concentrations. The mutation frequency was assessed after induction with the SOS-inducing chemotherapeutic drugs. We then tested the ability of the three most highly inducing drugs to drive the emergence of resistant mutants of major bacterial pathogens to first-line antibiotics.

RESULTS

Ten chemotherapeutic drugs activated the SOS response. Among them, eight accelerated the evolution of the major commensal E. coli, mostly through activation of the SOS response, with dacarbazine, azacitidine and streptozotocin enhancing the mutation rate 21.3-fold (P < 0.001), 101.7-fold (P = 0.01) and 1158.7-fold (P = 0.02), respectively. These three compounds also spurred the emergence of imipenem-resistant Pseudomonas aeruginosa (up to 6.21-fold; P = 0.05), ciprofloxacin-resistant Staphylococcus aureus (up to 57.72-fold; P = 0.016) and cefotaxime-resistant Enterobacteria cloacae (up to 4.57-fold; P = 0.018).

CONCLUSIONS

Our results suggest that chemotherapy could accelerate evolution of the microbiota and drive the emergence of antibiotic-resistant mutants from bacterial commensals in patients. This reveals an additional level of complexity of the interactions between cancer, chemotherapy and the gut microbiota.

Quantification of very low-abundant proteins in bacteria using the HaloTag and epi-fluorescence microscopy

Cell biology is increasingly dependent on quantitative methods resulting in the need for microscopic labelling technologies that are highly sensitive and specific. Whilst the use of fluorescent proteins has led to major advances, they also suffer from their relatively low brightness and photo-stability, making the detection of very low abundance proteins using fluorescent protein-based methods challenging. Here, we characterize the use of the self-labelling protein tag called HaloTag, in conjunction with an organic fluorescent dye, to label and accurately count endogenous proteins present in very low numbers (<7) in individual Escherichia coli cells. This procedure can be used to detect single molecules in fixed cells with conventional epifluorescence illumination and a standard microscope. We show that the detection efficiency of proteins labelled with the HaloTag is ≥80%, which is on par or better than previous techniques. Therefore, this method offers a simple and attractive alternative to current procedures to detect low abundance molecules.

Gene Expression Noise Produces Cell-to-Cell Heterogeneity in Eukaryotic Homologous Recombination Rate

Variation in gene expression among genetically identical individual cells (called gene expression noise) directly contributes to phenotypic diversity. Whether such variation can impact genome stability and lead to variation in genotype remains poorly explored. We addressed this question by investigating whether noise in the expression of genes affecting homologous recombination (HR) activity either directly (RAD52) or indirectly (RAD27) confers cell-to-cell heterogeneity in HR rate in Saccharomyces cerevisiae. Using cell sorting to isolate subpopulations with various expression levels, we show that spontaneous HR rate is highly heterogeneous from cell-to-cell in clonal populations depending on the cellular amount of proteins affecting HR activity. Phleomycin-induced HR is even more heterogeneous, showing that RAD27 expression variation strongly affects the rate of recombination from cell-to-cell. Strong variations in HR rate between subpopulations are not correlated to strong changes in cell cycle stage. Moreover, this heterogeneity occurs even when simultaneously sorting cells at equal expression level of another gene involved in DNA damage response (BMH1) that is upregulated by DNA damage, showing that the initiating DNA damage is not responsible for the observed heterogeneity in HR rate. Thus gene expression noise seems mainly responsible for this phenomenon. Finally, HR rate non-linearly scales with Rad27 levels showing that total amount of HR cannot be explained solely by the time- or population-averaged Rad27 expression. Altogether, our data reveal interplay between heterogeneity at the gene expression and genetic levels in the production of phenotypic diversity with evolutionary consequences from microbial to cancer cell populations.

Heterogeneity in efflux pump expression predisposes antibiotic-resistant cells to mutation

Antibiotic resistance is often the result of mutations that block drug activity; however, bacteria also evade antibiotics by transiently expressing genes such as multidrug efflux pumps. A crucial question is whether transient resistance can promote permanent genetic changes. Previous studies have established that antibiotic treatment can select tolerant cells that then mutate to achieve permanent resistance. Whether these mutations result from antibiotic stress or preexist within the population is unclear. To address this question, we focused on the multidrug pump AcrAB-TolC. Using time-lapse microscopy, we found that cells with higher acrAB expression have lower expression of the DNA mismatch repair gene mutS, lower growth rates, and higher mutation frequencies. Thus, transient antibiotic resistance from elevated acrAB expression can promote spontaneous mutations within single cells.

The fate of cells undergoing spontaneous DNA damage during development

Embryonic development involves extensive and often rapid cell proliferation. An unavoidable side effect of cell proliferation is DNA damage. The consequences of spontaneous DNA damage during development are not clear. Here, we define an approach to determine the effects of DNA damage on cell fate choice. Using single cell transcriptomics, we identified a subpopulation of Dictyostelium cells experiencing spontaneous DNA damage. Damaged cells displayed high expression of rad51, with the gene induced by multiple types of genotoxic stress. Using live imaging, we tracked high Rad51 cells from differentiation onset until cell fate assignment. High Rad51 cells were shed from multicellular structures, excluding damaged cells from the spore population. Cell shedding resulted from impaired cell motility and defective cell-cell adhesion, with damaged cells additionally defective in activation of spore gene expression. These data indicate DNA damage is not insulated from other aspects of cell physiology during development and multiple features of damaged cells prevent propagation of genetic error. Our approach is generally applicable for monitoring rare subpopulations during development, and permits analysis of developmental perturbations occurring within a physiological dynamic range.

Guidelines for DNA recombination and repair studies: Mechanistic assays of DNA repair processes

Genomes are constantly in flux, undergoing changes due to recombination, repair and mutagenesis. In vivo, many of such changes are studies using reporters for specific types of changes, or through cytological studies that detect changes at the single-cell level. Single molecule assays, which are reviewed here, can detect transient intermediates and dynamics of events. Biochemical assays allow detailed investigation of the DNA and protein activities of each step in a repair, recombination or mutagenesis event. Each type of assay is a powerful tool but each comes with its particular advantages and limitations. Here the most commonly used assays are reviewed, discussed, and presented as the guidelines for future studies.

Opposing effects of final population density and stress on Escherichia coli mutation rate

Evolution depends on mutations. For an individual genotype, the rate at which mutations arise is known to increase with various stressors (stress-induced mutagenesis-SIM) and decrease at high final population density (density-associated mutation-rate plasticity-DAMP). We hypothesised that these two forms of mutation-rate plasticity would have opposing effects across a nutrient gradient. Here we test this hypothesis, culturing Escherichia coli in increasingly rich media. We distinguish an increase in mutation rate with added nutrients through SIM (dependent on error-prone polymerases Pol IV and Pol V) and an opposing effect of DAMP (dependent on MutT, which removes oxidised G nucleotides). The combination of DAMP and SIM results in a mutation rate minimum at intermediate nutrient levels (which can support 7 × 108 cells ml-1). These findings demonstrate a strikingly close and nuanced relationship of ecological factors-stress and population density-with mutation, the fuel of all evolution.

Systemic signalling and local effectors in developmental stability, body symmetry, and size

Symmetric growth and the origins of fluctuating asymmetry are unresolved phenomena of biology. Small, and sometimes noticeable, deviations from perfect bilateral symmetry reflect the vulnerability of development to perturbations. The degree of asymmetry is related to the magnitude of the perturbations and the ability of an individual to cope with them. As the left and right sides of an individual were presumed to be genetically identical, deviations of symmetry were traditionally attributed to non-genetic effects such as environmental and developmental noise. In this review, we draw attention to other possible sources of variability, especially to somatic mutations and transposons. Mutations are a major source of phenotypic variability and recent genomic data have highlighted somatic mutations as ubiquitous, even in phenotypically normal individuals. We discuss the importance of factors that are responsible for buffering and stabilizing the genome and for maintaining size robustness and quality through elimination of less-fit or damaged cells. However, the important question that arises from these studies is whether this self-correcting capacity and intrinsic organ size controls are sufficient to explain how symmetric structures can reach an identical size and shape. Indeed, recent discoveries in the fruit fly have uncovered a conserved hormone of the insulin/IGF/relaxin family, Dilp8, that is responsible for stabilizing body size and symmetry in the face of growth perturbations. Dilp8 alarm signals periphery growth status to the brain, where it acts on its receptor Lgr3. Loss of Dilp8-Lgr3 signaling renders flies incapable of detecting growth perturbations and thus maintaining a stable size and symmetry. These findings help to understand how size and symmetry of somatic tissues remain undeterred in noisy environments, after injury or illnesses, and in the presence of accumulated somatic mutations.

Understanding Protein Mobility in Bacteria by Tracking Single Molecules

Protein diffusion is crucial for understanding the formation of protein complexes in vivo and has been the subject of many fluorescence microscopy studies in cells; however, such microscopy efforts are often limited by low sensitivity and resolution. During the past decade, these limitations have been addressed by new super-resolution imaging methods, most of which rely on single-particle tracking and single-molecule detection; these methods are revolutionizing our understanding of molecular diffusion inside bacterial cells by directly visualizing the motion of proteins and the effects of the local and global environment on diffusion. Here we review key methods that made such experiments possible, with particular emphasis on versions of single-molecule tracking based on photo-activated fluorescent proteins. We also discuss studies that provide estimates of the time a diffusing protein takes to locate a target site, as well as studies that examined the stoichiometries of diffusing species, the effect of stable and weak interactions on diffusion, and the constraints of large macromolecular structures on the ability of proteins and their complexes to access the entire cytoplasm.

Single-Molecule Kinetics in Living Cells

In the past decades, advances in microscopy have made it possible to study the dynamics of individual biomolecules in vitro and resolve intramolecular kinetics that would otherwise be hidden in ensemble averages. More recently, single-molecule methods have been used to image, localize, and track individually labeled macromolecules in the cytoplasm of living cells, allowing investigations of intermolecular kinetics under physiologically relevant conditions. In this review, we illuminate the particular advantages of single-molecule techniques when studying kinetics in living cells and discuss solutions to specific challenges associated with these methods.

Rediscovering Bacteria through Single-Molecule Imaging in Living Cells

Bacteria are microorganisms central to health and disease, serving as important model systems for our understanding of molecular mechanisms and for developing new methodologies and vehicles for biotechnology. In the past few years, our understanding of bacterial cell functions has been enhanced substantially by powerful single-molecule imaging techniques. Using single fluorescent molecules as a means of breaking the optical microscopy limit, we can now reach resolutions of ∼20 nm inside single living cells, a spatial domain previously accessible only by electron microscopy. One can follow a single bacterial protein complex as it performs its functions and directly observe intricate cellular structures as they move and reorganize during the cell cycle. This toolbox enables the use of in vivo quantitative biology by counting molecules, characterizing their intracellular location and mobility, and identifying functionally distinct molecular distributions. Crucially, this can all be achieved while imaging large populations of cells, thus offering detailed views of the heterogeneity in bacterial communities. Here, we examine how this new scientific domain was born and discuss examples of applications to bacterial cellular mechanisms as well as emerging trends and applications.

Real-time dynamics of mutagenesis reveal the chronology of DNA repair and damage tolerance responses in single cells

Evolutionary processes are driven by diverse molecular mechanisms that act in the creation and prevention of mutations. It remains unclear how these mechanisms are regulated because limitations of existing mutation assays have precluded measuring how mutation rates vary over time in single cells. Toward this goal, I detected nascent DNA mismatches as a proxy for mutagenesis and simultaneously followed gene expression dynamics in single Escherichia coli cells using microfluidics. This general microscopy-based approach revealed the real-time dynamics of mutagenesis in response to DNA alkylation damage and antibiotic treatments. It also enabled relating the creation of DNA mismatches to the chronology of the underlying molecular processes. By avoiding population averaging, I discovered cell-to-cell variation in mutagenesis that correlated with heterogeneity in the expression of alternative responses to DNA damage. Pulses of mutagenesis are shown to arise from transient DNA repair deficiency. Constitutive expression of DNA repair pathways and induction of damage tolerance by the SOS response compensate for delays in the activation of inducible DNA repair mechanisms, together providing robustness against the toxic and mutagenic effects of DNA alkylation damage.

Microfluidics and single-cell microscopy to study stochastic processes in bacteria

Bacteria have molecules present in low and fluctuating numbers that randomize cell behaviors. Understanding these stochastic processes and their impact on cells has, until recently, been limited by the lack of single-cell measurement methods. Here, we review recent developments in microfluidics that enable following individual cells over long periods of time under precisely controlled conditions, and counting individual fluorescent molecules in many cells. We showcase discoveries that were made possible using these devices in various aspects of microbiology, such as antibiotic tolerance/persistence, cell-size control, cell-fate determination, DNA damage response, and synthetic biology.

Visualizing bacterial DNA replication and repair with molecular resolution

Although DNA replication and repair in bacteria have been extensively studied for many decades, in recent years the development of single-molecule microscopy has provided a new perspective on these fundamental processes. Because single-molecule imaging super-resolves the nanometer-scale dynamics of molecules, and because single-molecule imaging is sensitive to heterogeneities within a sample, this nanoscopic microscopy technique measures the motions, localizations, and interactions of proteins in real time without averaging ensemble observations, both in vitro and in vivo. In this Review, we provide an overview of several recent single-molecule fluorescence microscopy studies on DNA replication and repair. These experiments have shown that, in both Escherichia coli and Bacillus subtilis the DNA replication proteins are highly dynamic. In particular, even highly processive replicative DNA polymerases exchange to and from the replication fork on the scale of a few seconds. Furthermore, single-molecule investigations of the DNA mismatch repair (MMR) pathway have measured the complex interactions between MMR proteins, replication proteins, and DNA. Single-molecule imaging will continue to improve our understanding of fundamental processes in bacteria including DNA replication and repair.

Heterogeneity of spontaneous DNA replication errors in single isogenic Escherichia coli cells

Despite extensive knowledge of the molecular mechanisms that control mutagenesis, it is not known how spontaneous mutations are produced in cells with fully operative mutation-prevention systems. By using a mutation assay that allows visualization of DNA replication errors and stress response transcriptional reporters, we examined populations of isogenic Escherichia coli cells growing under optimal conditions without exogenous stress. We found that spontaneous DNA replication errors in proliferating cells arose more frequently in subpopulations experiencing endogenous stresses, such as problems with proteostasis, genome maintenance, and reactive oxidative species production. The presence of these subpopulations of phenotypic mutators is not expected to affect the average mutation frequency or to reduce the mean population fitness in a stable environment. However, these subpopulations can contribute to overall population adaptability in fluctuating environments by serving as a reservoir of increased genetic variability.

Increased gene expression noise in human cancers is correlated with low p53 and immune activities as well as late stage cancer

Gene expression in metazoans is delicately organized. As genetic information transmits from DNA to RNA and protein, expression noise is inevitably generated. Recent studies begin to unveil the mechanisms of gene expression noise control, but the changes of gene expression precision in pathologic conditions like cancers are unknown. Here we analyzed the transcriptomic data of human breast, liver, lung and colon cancers, and found that the expression noise of more than 74.9% genes was increased in cancer tissues as compared to adjacent normal tissues. This suggested that gene expression precision controlling collapsed during cancer development. A set of 269 genes with noise increased more than 2-fold were identified across different cancer types. These genes were involved in cell adhesion, catalytic and metabolic functions, implying the vulnerability of deregulation of these processes in cancers. We also observed a tendency of increased expression noise in patients with low p53 and immune activity in breast, liver and lung caners but not in colon cancers, which indicated the contributions of p53 signaling and host immune surveillance to gene expression noise in cancers. Moreover, more than 53.7% genes had increased noise in patients with late stage than early stage cancers, suggesting that gene expression precision was associated with cancer outcome. Together, these results provided genomic scale explorations of gene expression noise control in human cancers.

Single-cell microscopy of suspension cultures using a microfluidics-assisted cell screening platform

Studies that rely on fluorescence imaging of nonadherent cells that are cultured in suspension, such as Escherichia coli, are often hampered by trade-offs that must be made between data throughput and imaging resolution. We developed a platform for microfluidics-assisted cell screening (MACS) that overcomes this trade-off by temporarily immobilizing suspension cells within a microfluidics chip. This enables high-throughput and automated single-cell microscopy for a wide range of cell types and sizes. As cells can be rapidly sampled directly from a suspension culture, MACS bypasses the need for sample preparation, and therefore allows measurements without perturbing the native cell physiology. The setup can also be integrated with complex growth chambers, and can be used to enrich or sort the imaged cells. Furthermore, MACS facilitates the visualization of individual cytoplasmic fluorescent proteins (FPs) in E. coli, allowing low-abundance proteins to be counted using standard total internal reflection fluorescence (TIRF) microscopy. Finally, MACS can be used to impart mechanical pressure for assessing the structural integrity of individual cells and their response to mechanical perturbations, or to make cells take up chemicals that otherwise would not pass through the membrane. This protocol describes the assembly of electronic control circuitry, the construction of liquid-handling components and the creation of the MACS microfluidics chip. The operation of MACS is described, and automation software is provided to integrate MACS control with image acquisition. Finally, we provide instructions for extending MACS using an external growth chamber (1 d) and for how to sort rare cells of interest.

The ultimate picture-the combination of live cell superresolution microscopy and single molecule tracking yields highest spatio-temporal resolution

We are witnessing a breathtaking development in light (fluorescence) microscopy, where structures can be resolved down to the size of a ribosome within cells. This has already yielded surprising insight into the subcellular structure of cells, including the smallest cells, bacteria. Moreover, it has become possible to visualize and track single fluorescent protein fusions in real time, and quantify molecule numbers within individual cells. Combined, super resolution and single molecule tracking are pushing the limits of our understanding of the spatio-temporal organization even of the smallest cells to an unprecedented depth.

Single-molecule live-cell imaging of bacterial DNA repair and damage tolerance

Genomic DNA is constantly under threat from intracellular and environmental factors that damage its chemical structure. Uncorrected DNA damage may impede cellular propagation or even result in cell death, making it critical to restore genomic integrity. Decades of research have revealed a wide range of mechanisms through which repair factors recognize damage and co-ordinate repair processes. In recent years, single-molecule live-cell imaging methods have further enriched our understanding of how repair factors operate in the crowded intracellular environment. The ability to follow individual biochemical events, as they occur in live cells, makes single-molecule techniques tremendously powerful to uncover the spatial organization and temporal regulation of repair factors during DNA-repair reactions. In this review, we will cover practical aspects of single-molecule live-cell imaging and highlight recent advances accomplished by the application of these experimental approaches to the study of DNA-repair processes in prokaryotes.

In situ genotyping of a pooled strain library after characterizing complex phenotypes

In this work, we present a proof-of-principle experiment that extends advanced live cell microscopy to the scale of pool-generated strain libraries. We achieve this by identifying the genotypes for individual cells in situ after a detailed characterization of the phenotype. The principle is demonstrated by single-molecule fluorescence time-lapse imaging of Escherichia coli strains harboring barcoded plasmids that express a sgRNA which suppresses different genes in the E. coli genome through dCas9 interference. In general, the method solves the problem of characterizing complex dynamic phenotypes for diverse genetic libraries of cell strains. For example, it allows screens of how changes in regulatory or coding sequences impact the temporal expression, location, or function of a gene product, or how the altered expression of a set of genes impacts the intracellular dynamics of a labeled reporter.

What's Luck Got to Do with It: Single Cells, Multiple Fates, and Biological Nondeterminism

The field of single-cell biology has morphed from a philosophical digression at its inception, to a playground for quantitative biologists, to a major area of biomedical research. The last several years have witnessed an explosion of new technologies, allowing us to apply even more of the modern molecular biology toolkit to single cells. Conceptual progress, however, has been comparatively slow. Here, we provide a framework for classifying both the origins of the differences between individual cells and the consequences of those differences. We discuss how the concept of "random" differences is context dependent, and propose that rigorous definitions of inputs and outputs may bring clarity to the discussion. We also categorize ways in which probabilistic behavior may influence cellular function, highlighting studies that point to exciting future directions in the field.

Spontaneous mutation rate is a plastic trait associated with population density across domains of life

Rates of random, spontaneous mutation can vary plastically, dependent upon the environment. Such plasticity affects evolutionary trajectories and may be adaptive. We recently identified an inverse plastic association between mutation rate and population density at 1 locus in 1 species of bacterium. It is unknown how widespread this association is, whether it varies among organisms, and what molecular mechanisms of mutagenesis or repair are required for this mutation-rate plasticity. Here, we address all 3 questions. We identify a strong negative association between mutation rate and population density across 70 years of published literature, comprising hundreds of mutation rates estimated using phenotypic markers of mutation (fluctuation tests) from all domains of life and viruses. We test this relationship experimentally, determining that there is indeed density-associated mutation-rate plasticity (DAMP) at multiple loci in both eukaryotes and bacteria, with up to 23-fold lower mutation rates at higher population densities. We find that the degree of plasticity varies, even among closely related organisms. Nonetheless, in each domain tested, DAMP requires proteins scavenging the mutagenic oxidised nucleotide 8-oxo-dGTP. This implies that phenotypic markers give a more precise view of mutation rate than previously believed: having accounted for other known factors affecting mutation rate, controlling for population density can reduce variation in mutation-rate estimates by 93%. Widespread DAMP, which we manipulate genetically in disparate organisms, also provides a novel trait to use in the fight against the evolution of antimicrobial resistance. Such a prevalent environmental association and conserved mechanism suggest that mutation has varied plastically with population density since the early origins of life.

Iron and thiol redox signaling in cancer: An exquisite balance to escape ferroptosis

Epidemiological data indicate a constant worldwide increase in cancer mortality, although the age of onset is increasing. Recent accumulation of genomic data on human cancer via next-generation sequencing confirmed that cancer is a disease of genome alteration. In many cancers, the Nrf2 transcription system is activated via mutations either in Nrf2 or Keap1 ubiquitin ligase, leading to persistent activation of the genes with antioxidative functions. Furthermore, deep sequencing of passenger mutations is clarifying responsible cancer causative agent(s) in each case, including aging, APOBEC activation, smoking and UV. Therefore, it is most likely that oxidative stress is the principal initiating factor in carcinogenesis, with the involvement of two essential molecules for life, iron and oxygen. There is evidence based on epidemiological and animal studies that excess iron is a major risk for carcinogenesis, suggesting the importance of ferroptosis-resistance. Microscopic visualization of catalytic Fe(II) has recently become available. Although catalytic Fe(II) is largely present in lysosomes, proliferating cells harbor catalytic Fe(II) also in the cytosol and mitochondria. Oxidative stress catalyzed by Fe(II) is counteracted by thiol systems at different functional levels. Nitric oxide, carbon monoxide and hydrogen (per)sulfide modulate these reactions. Mitochondria generate not only energy but also heme/iron sulfur cluster cofactors and remain mostly dysfunctional in cancer cells, leading to Warburg effects. Cancer cells are under persistent oxidative stress with a delicate balance between catalytic iron and thiols, thereby escaping ferroptosis. Thus, high-dose L-ascorbate and non-thermal plasma as well as glucose/glutamine deprivation may provide additional benefits as cancer therapies over preexisting therapeutics.

Aneuploidy Causes Non-genetic Individuality

Phenotypic variability is a hallmark of diseases involving chromosome gains and losses, such as Down syndrome and cancer. Allelic variances have been thought to be the sole cause of this heterogeneity. Here, we systematically examine the consequences of gaining and losing single or multiple chromosomes to show that the aneuploid state causes non-genetic phenotypic variability. Yeast cell populations harboring the same defined aneuploidy exhibit heterogeneity in cell-cycle progression and response to environmental perturbations. Variability increases with degree of aneuploidy and is partly due to gene copy number imbalances, suggesting that subtle changes in gene expression impact the robustness of biological networks and cause alternate behaviors when they occur across many genes. As inbred trisomic mice also exhibit variable phenotypes, we further propose that non-genetic individuality is a universal characteristic of the aneuploid state that may contribute to variability in presentation and treatment responses of diseases caused by aneuploidy.

Intrinsic Molecular Processes: Impact on Mutagenesis

Mutations provide resources for genome evolution by generating genetic variability. In addition, mutations act as a driving force leading to disease pathogenesis, and thus have important implications for disease diagnosis, prognosis, and treatment. Understanding the mechanisms underlying how mutations occur is therefore of prime importance for elucidating evolutionary and pathogenic processes. Recent genomics studies have revealed that mutations occur non-randomly across the human genome. In particular, the distribution of mutations is highly associated with intrinsic molecular processes including transcription, chromatin organization, DNA replication timing, and DNA repair. Interplay between intrinsic processes and extrinsic mutagenic exposure may thus imprint a characteristic mutational landscape on tumors. We discuss the impact of intrinsic molecular processes on mutation acquisition in cancer.

Stochasticity of gene expression as a motor of epigenetics in bacteria: from individual to collective behaviors

Measuring gene expression at the single cell and single molecule level has recently made possible the quantitative measurement of stochasticity of gene expression. This enables identification of the probable sources and roles of noise. Gene expression noise can result in bacterial population heterogeneity, offering specific advantages for fitness and survival in various environments. This trait is therefore selected during the evolution of the species, and is consequently regulated by a specific genetic network architecture. Examples exist in stress-response mechanisms, as well as in infection and pathogenicity strategies, pointing to advantages for multicellularity of bacterial populations.

Single-Molecule Analysis of Bacterial DNA Repair and Mutagenesis

Ubiquitous conserved processes that repair DNA damage are essential for the maintenance and propagation of genomes over generations. Then again, inaccuracies in DNA transactions and failures to remove mutagenic lesions cause heritable genome changes. Building on decades of research using genetics and biochemistry, unprecedented quantitative insight into DNA repair mechanisms has come from the new-found ability to measure single proteins in vitro and inside individual living cells. This has brought together biologists, chemists, engineers, physicists, and mathematicians to solve long-standing questions about the way in which repair enzymes search for DNA lesions and form protein complexes that act in DNA repair pathways. Furthermore, unexpected discoveries have resulted from capabilities to resolve molecular heterogeneity and cell subpopulations, provoking new questions about the role of stochastic processes in DNA repair and mutagenesis. These studies are leading to new technologies that will find widespread use in basic research, biotechnology, and medicine.

Population Heterogeneity in Mutation Rate Increases the Frequency of Higher-Order Mutants and Reduces Long-Term Mutational Load

Mutation rate is a crucial evolutionary parameter that has typically been treated as a constant in population genetic analyses. However, the propensity to mutate is likely to vary among co-existing individuals within a population, due to genetic polymorphisms, heterogeneous environmental influences, and random physiological fluctuations. We review the evidence for mutation rate heterogeneity and explore its consequences by extending classic population genetic models to allow an arbitrary distribution of mutation rate among individuals, either with or without inheritance. With this general new framework, we rigorously establish the effects of heterogeneity at various evolutionary timescales. In a single generation, variation of mutation rate about the mean increases the probability of producing zero or many simultaneous mutations on a genome. Over multiple generations of mutation and selection, heterogeneity accelerates the appearance of both deleterious and beneficial multi-point mutants. At mutation-selection balance, higher-order mutant frequencies are likewise boosted, while lower-order mutants exhibit subtler effects; nonetheless, population mean fitness is always enhanced. We quantify the dependencies on moments of the mutation rate distribution and selection coefficients, and clarify the role of mutation rate inheritance. While typical methods of estimating mutation rate will recover only the population mean, analyses assuming mutation rate is fixed to this mean could underestimate the potential for multi-locus adaptation, including medically relevant evolution in pathogenic and cancerous populations. We discuss the potential to empirically parameterize mutation rate distributions, which have to date hardly been quantified.

Predicting cell viability within tissue scaffolds under equiaxial strain: multi-scale finite element model of collagen-cardiomyocytes constructs

Successful tissue engineering and regenerative therapy necessitate having extensive knowledge about mechanical milieu in engineered tissues and the resident cells. In this study, we have merged two powerful analysis tools, namely finite element analysis and stochastic analysis, to understand the mechanical strain within the tissue scaffold and residing cells and to predict the cell viability upon applying mechanical strains. A continuum-based multi-length scale finite element model (FEM) was created to simulate the physiologically relevant equiaxial strain exposure on cell-embedded tissue scaffold and to calculate strain transferred to the tissue scaffold (macro-scale) and residing cells (micro-scale) upon various equiaxial strains. The data from FEM were used to predict cell viability under various equiaxial strain magnitudes using stochastic damage criterion analysis. The model validation was conducted through mechanically straining the cardiomyocyte-encapsulated collagen constructs using a custom-built mechanical loading platform (EQUicycler). FEM quantified the strain gradients over the radial and longitudinal direction of the scaffolds and the cells residing in different areas of interest. With the use of the experimental viability data, stochastic damage criterion, and the average cellular strains obtained from multi-length scale models, cellular viability was predicted and successfully validated. This methodology can provide a great tool to characterize the mechanical stimulation of bioreactors used in tissue engineering applications in providing quantification of mechanical strain and predicting cellular viability variations due to applied mechanical strain.

Effects of cell-cycle-dependent expression on random fluctuations in protein levels

Expression of many genes varies as a cell transitions through different cell-cycle stages. How coupling between stochastic expression and cell cycle impacts cell-to-cell variability (noise) in the level of protein is not well understood. We analyse a model where a stable protein is synthesized in random bursts, and the frequency with which bursts occur varies within the cell cycle. Formulae quantifying the extent of fluctuations in the protein copy number are derived and decomposed into components arising from the cell cycle and stochastic processes. The latter stochastic component represents contributions from bursty expression and errors incurred during partitioning of molecules between daughter cells. These formulae reveal an interesting trade-off: cell-cycle dependencies that amplify the noise contribution from bursty expression also attenuate the contribution from partitioning errors. We investigate the existence of optimum strategies for coupling expression to the cell cycle that minimize the stochastic component. Intriguingly, results show that a zero production rate throughout the cell cycle, with expression only occurring just before cell division, minimizes noise from bursty expression for a fixed mean protein level. By contrast, the optimal strategy in the case of partitioning errors is to make the protein just after cell division. We provide examples of regulatory proteins that are expressed only towards the end of the cell cycle, and argue that such strategies enhance robustness of cell-cycle decisions to the intrinsic stochasticity of gene expression.

Pseudomonas syringae Differentiates into Phenotypically Distinct Subpopulations During Colonization of a Plant Host

Bacterial microcolonies with heterogeneous sizes are formed during colonization of Phaseolus vulgaris by Pseudomonas syringae. Heterogeneous expression of structural and regulatory components of the P. syringae type III secretion system (T3SS), essential for colonization of the host apoplast and disease development, is likewise detected within the plant apoplast. T3SS expression is bistable in the homogeneous environment of nutrient-limited T3SS-inducing medium, suggesting that subpopulation formation is not a response to different environmental cues. T3SS bistability is reversible, indicating a non-genetic origin, and the T3SS^HIGH and T3SS^LOW subpopulations show differences in virulence. T3SS bistability requires the transcriptional activator HrpL, the double negative regulatory loop established by HrpV and HrpG, and may be enhanced through a positive feedback loop involving HrpA, the main component of the T3SS pilus. To our knowledge, this is the first example of phenotypic heterogeneity in the expression of virulence determinants during colonization of a non-mammalian host.

Exploiting Single-Cell Quantitative Data to Map Genetic Variants Having Probabilistic Effects

Despite the recent progress in sequencing technologies, genome-wide association studies (GWAS) remain limited by a statistical-power issue: many polymorphisms contribute little to common trait variation and therefore escape detection. The small contribution sometimes corresponds to incomplete penetrance, which may result from probabilistic effects on molecular regulations. In such cases, genetic mapping may benefit from the wealth of data produced by single-cell technologies. We present here the development of a novel genetic mapping method that allows to scan genomes for single-cell Probabilistic Trait Loci that modify the statistical properties of cellular-level quantitative traits. Phenotypic values are acquired on thousands of individual cells, and genetic association is obtained from a multivariate analysis of a matrix of Kantorovich distances. No prior assumption is required on the mode of action of the genetic loci involved and, by exploiting all single-cell values, the method can reveal non-deterministic effects. Using both simulations and yeast experimental datasets, we show that it can detect linkages that are missed by classical genetic mapping. A probabilistic effect of a single SNP on cell shape was detected and validated. The method also detected a novel locus associated with elevated gene expression noise of the yeast galactose regulon. Our results illustrate how single-cell technologies can be exploited to improve the genetic dissection of certain common traits. The method is available as an open source R package called ptlmapper.

Synthetic Biology: fostering the cyber-biological revolution

Since the description, in 2000, of two artificial gene networks, synthetic biology has emerged as a new engineering discipline that catalyzes a change of culture in the life sciences. Recombinant DNA can now be fabricated rather than cloned. Instead of focusing on the development of ad-hoc assembly strategies, molecular biologists can outsource the fabrication of synthetic DNA molecules to a network of DNA foundries. Model-driven product development cycles that clearly identify design, build, and test phases are becoming as common in the life sciences as they have been in other engineering fields. A movement of citizen scientists with roots in community labs throughout the world is trying to democratize genetic engineering. It challenges the life science establishment just like visionaries in the 70s advocated that computing should be personal at a time when access to computers was mostly the privilege of government scientists. Synthetic biology is a cultural revolution that will have far reaching implications for the biotechnology industry. The work of synthetic biologists today prefigures a new generation of cyber-biological systems that may to lead to the 5^th industrial revolution. By catering to the scientific publishing needs of all members of a diverse community, Synthetic Biology hopes to do its part to support the development of this new engineering discipline, catalyze the culture changes it calls for, and foster the development of a new industry far into the twenty first century.

The Design and Transformation of Biofundamentals: A Nonsurvey Introductory Evolutionary and Molecular Biology Course

Many introductory biology courses amount to superficial surveys of disconnected topics. Often, foundational observations and the concepts derived from them and students' ability to use these ideas appropriately are overlooked, leading to unrealistic expectations and unrecognized learning obstacles. The result can be a focus on memorization at the expense of the development of a meaningful framework within which to consider biological phenomena. About a decade ago, we began a reconsideration of what an introductory course should present to students and the skills they need to master. The original Web-based course's design presaged many of the recommendations of the Vision and Change report; in particular, a focus on social evolutionary mechanisms, stochastic (evolutionary and molecular) processes, and core ideas (cellular continuity, evolutionary homology, molecular interactions, coupled chemical reactions, and molecular machines). Inspired by insights from the Chemistry, Life, the Universe & Everything general chemistry project, we transformed the original Web version into a (freely available) book with a more unified narrative flow and a set of formative assessments delivered through the beSocratic system. We outline how student responses to course materials are guiding future course modifications, in particular a more concerted effort at helping students to construct logical, empirically based arguments, explanations, and models.