Noisy Response to Antibiotic Stress Predicts Subsequent Single-Cell Survival in an Acidic Environment

Density physics-informed neural networks reveal sources of cell heterogeneity in signal transduction

The transduction time between signal initiation and final response provides valuable information on the underlying signaling pathway, including its speed and precision. Furthermore, multi-modality in a transduction-time distribution indicates that the response is regulated by multiple pathways with different transduction speeds. Here, we developed a method called density physics-informed neural networks (Density-PINNs) to infer the transduction-time distribution from measurable final stress response time traces. We applied Density-PINNs to single-cell gene expression data from sixteen promoters regulated by unknown pathways in response to antibiotic stresses. We found that promoters with slower signaling initiation and transduction exhibit larger cell-to-cell heterogeneity in response intensity. However, this heterogeneity was greatly reduced when the response was regulated by slow and fast pathways together. This suggests a strategy for identifying effective signaling pathways for consistent cellular responses to disease treatments. Density-PINNs can also be applied to understand other time delay systems, including infectious diseases.

Gene expression tradeoffs determine bacterial survival and adaptation to antibiotic stress

To optimize their fitness, cells face the crucial task of efficiently responding to various stresses. This necessitates striking a balance between conserving resources for survival and allocating resources for growth and division. The fundamental principles governing these tradeoffs is an outstanding challenge in the physics of living systems. In this study, we introduce a coarse-grained theoretical framework for bacterial physiology that establishes a connection between the physiological state of cells and their survival outcomes in dynamic environments, particularly in the context of antibiotic exposure. Predicting bacterial survival responses to varying antibiotic doses proves challenging due to the profound influence of the physiological state on critical parameters, such as the Minimum Inhibitory Concentration (MIC) and killing rates, even within an isogenic cell population. Our proposed theoretical model bridges the gap by linking extracellular antibiotic concentration and nutrient quality to intracellular damage accumulation and gene expression. This framework allows us to predict and explain the control of cellular growth rate, death rate, MIC and survival fraction in a wide range of time-varying environments. Surprisingly, our model reveals that cell death is rarely due to antibiotic levels being above the maximum physiological limit, but instead survival is limited by the inability to alter gene expression sufficiently quickly to transition to a less susceptible physiological state. Moreover, bacteria tend to overexpress stress response genes at the expense of reduced growth, conferring greater protection against further antibiotic exposure. This strategy is in contrast to those employed in different nutrient environments, in which bacteria allocate resources to maximize growth rate. This highlights an important tradeoff between the cellular capacity for growth and the ability to survive antibiotic exposure.

Exploitation of microbial activities at low pH to enhance planetary health

Awareness is growing that human health cannot be considered in isolation but is inextricably woven with the health of the environment in which we live. It is, however, under-recognized that the sustainability of human activities strongly relies on preserving the equilibrium of the microbial communities living in/on/around us. Microbial metabolic activities are instrumental for production, functionalization, processing, and preservation of food. For circular economy, microbial metabolism would be exploited to produce building blocks for the chemical industry, to achieve effective crop protection, agri-food waste revalorization, or biofuel production, as well as in bioremediation and bioaugmentation of contaminated areas. Low pH is undoubtedly a key physical-chemical parameter that needs to be considered for exploiting the powerful microbial metabolic arsenal. Deviation from optimal pH conditions has profound effects on shaping the microbial communities responsible for carrying out essential processes. Furthermore, novel strategies to combat contaminations and infections by pathogens rely on microbial-derived acidic molecules that suppress/inhibit their growth. Herein, we present the state-of-the-art of the knowledge on the impact of acidic pH in many applied areas and how this knowledge can guide us to use the immense arsenal of microbial metabolic activities for their more impactful exploitation in a Planetary Health perspective.

LTP2 hypomorphs show genotype-by-environment interaction in early seedling traits in Arabidopsis thaliana

Isogenic individuals can display seemingly stochastic phenotypic differences, limiting the accuracy of genotype-to-phenotype predictions. The extent of this phenotypic variation depends in part on genetic background, raising questions about the genes involved in controlling stochastic phenotypic variation. Focusing on early seedling traits in Arabidopsis thaliana, we found that hypomorphs of the cuticle-related gene LIPID TRANSFER PROTEIN 2 (LTP2) greatly increased variation in seedling phenotypes, including hypocotyl length, gravitropism and cuticle permeability. Many ltp2 hypocotyls were significantly shorter than wild-type hypocotyls while others resembled the wild-type. Differences in epidermal properties and gene expression between ltp2 seedlings with long and short hypocotyls suggest a loss of cuticle integrity as the primary determinant of the observed phenotypic variation. We identified environmental conditions that reveal or mask the increased variation in ltp2 hypomorphs and found that increased expression of its closest paralog LTP1 is necessary for ltp2 phenotypes. Our results illustrate how decreased expression of a single gene can generate starkly increased phenotypic variation in isogenic individuals in response to an environmental challenge.

Ribosome profiling reveals the fine-tuned response of Escherichia coli to mild and severe acid stress

IMPORTANCE

Bacteria react very differently to survive in acidic environments, such as the human gastrointestinal tract. Escherichia coli is one of the extremely acid-resistant bacteria and has a variety of acid-defense mechanisms. Here, we provide the first genome-wide overview of the adaptations of E. coli K-12 to mild and severe acid stress at both the transcriptional and translational levels. Using ribosome profiling and RNA sequencing, we uncover novel adaptations to different degrees of acidity, including previously hidden stress-induced small proteins and novel key transcription factors for acid defense, and report mRNAs with pH-dependent differential translation efficiency. In addition, we distinguish between acid-specific adaptations and general stress response mechanisms using denoising autoencoders. This workflow represents a powerful approach that takes advantage of next-generation sequencing techniques and machine learning to systematically analyze bacterial stress responses.

Chaos in a bacterial stress response

Cellular responses to environmental changes are often highly heterogeneous and exhibit seemingly random dynamics. The astonishing insight of chaos theory is that such unpredictable patterns can, in principle, arise without the need for any random processes, i.e., purely deterministically without noise. However, while chaos is well understood in mathematics and physics, its role in cell biology remains unclear because the complexity and noisiness of biological systems make testing difficult. Here, we show that chaos explains the heterogeneous response of Escherichia coli cells to oxidative stress. We developed a theoretical model of the gene expression dynamics and demonstrate that chaotic behavior arises from rapid molecular feedbacks that are coupled with cell growth dynamics and cell-cell interactions. Based on theoretical predictions, we then designed single-cell experiments to show we can shift gene expression from periodic oscillations to chaos on demand. Our work suggests that chaotic gene regulation can be employed by cell populations to generate strong and variable responses to changing environments.

Pervasive gene deregulation underlies adaptation and maladaptation in trimethoprim-resistant E. coli

IMPORTANCE

Bacteria employ a number of mechanisms to adapt to antibiotics. Mutations in transcriptional regulators alter the expression levels of genes that can change the susceptibility of bacteria to antibiotics. Two-component signaling proteins are a major class of signaling molecule used by bacteria to regulate transcription. In previous work, we found that mutations in MgrB, a feedback regulator of the PhoQP two-component system, conferred trimethoprim tolerance to Escherichia coli. Here, we elucidate how mutations in MgrB have a domino-like effect on the gene regulatory network of E. coli. As a result, pervasive perturbation of gene regulation ensues. Depending on the environmental context, this pervasive deregulation is either adaptive or maladaptive. Our study sheds light on how deregulation of gene expression can be beneficial for bacteria when challenged with antibiotics, and why regulators like MgrB may have evolved in the first place.

Single-cell massively-parallel multiplexed microbial sequencing (M3-seq) identifies rare bacterial populations and profiles phage infection

Bacterial populations are highly adaptive. They can respond to stress and survive in shifting environments. How the behaviours of individual bacteria vary during stress, however, is poorly understood. To identify and characterize rare bacterial subpopulations, technologies for single-cell transcriptional profiling have been developed. Existing approaches show some degree of limitation, for example, in terms of number of cells or transcripts that can be profiled. Due in part to these limitations, few conditions have been studied with these tools. Here we develop massively-parallel, multiplexed, microbial sequencing (M3-seq)-a single-cell RNA-sequencing platform for bacteria that pairs combinatorial cell indexing with post hoc rRNA depletion. We show that M3-seq can profile bacterial cells from different species under a range of conditions in single experiments. We then apply M3-seq to hundreds of thousands of cells, revealing rare populations and insights into bet-hedging associated with stress responses and characterizing phage infection.

Bacterial acid stress response: from cellular changes to antibiotic tolerance and phenotypic heterogeneity

Most bacteria are neutralophiles but can survive fluctuations in pH in their environment. Herein, we provide an overview of the adaptation of several human, soil, and food bacteria to acid stress, mainly based on next-generation sequencing studies, highlighting common and specific strategies. We also discuss the interplay between acid stress response and antibiotic tolerance, as well as the response of individual cells.

LTP2 hypomorphs show genotype-by-environment interaction in early seedling traits in Arabidopsis thaliana

Isogenic individuals can display seemingly stochastic phenotypic differences, limiting the accuracy of genotype-to-phenotype predictions. The extent of this phenotypic variation depends in part on genetic background, raising questions about the genes involved in controlling stochastic phenotypic variation. Focusing on early seedling traits in Arabidopsis thaliana, we found that hypomorphs of the cuticle-related gene LTP2 greatly increased variation in seedling phenotypes, including hypocotyl length, gravitropism and cuticle permeability. Many ltp2 hypocotyls were significantly shorter than wild-type hypocotyls while others resembled the wild type. Differences in epidermal properties and gene expression between ltp2 seedlings with long and short hypocotyls suggest a loss of cuticle integrity as the primary determinant of the observed phenotypic variation. We identified environmental conditions that reveal or mask the increased variation in ltp2 hypomorphs, and found that increased expression of its closest paralog LTP1 is necessary for ltp2 phenotypes. Our results illustrate how decreased expression of a single gene can generate starkly increased phenotypic variation in isogenic individuals in response to an environmental challenge.

Phenotypic heterogeneity in the bacterial oxidative stress response is driven by cell-cell interactions

Genetically identical bacterial cells commonly display different phenotypes. This phenotypic heterogeneity is well known for stress responses, where it is often explained as bet hedging against unpredictable environmental threats. Here, we explore phenotypic heterogeneity in a major stress response of Escherichia coli and find it has a fundamentally different basis. We characterize the response of cells exposed to hydrogen peroxide (H2O2) stress in a microfluidic device under constant growth conditions. A machine-learning model reveals that phenotypic heterogeneity arises from a precise and rapid feedback between each cell and its immediate environment. Moreover, we find that the heterogeneity rests upon cell-cell interaction, whereby cells shield each other from H2O2 via their individual stress responses. Our work shows how phenotypic heterogeneity in bacterial stress responses can emerge from short-range cell-cell interactions and result in a collective phenotype that protects a large proportion of the population.

Navigating Environmental Transitions: the Role of Phenotypic Variation in Bacterial Responses

The ability of bacteria to respond to changes in their environment is critical to their survival, allowing them to withstand stress, form complex communities, and induce virulence responses during host infection. A remarkable feature of many of these bacterial responses is that they are often variable across individual cells, despite occurring in an isogenic population exposed to a homogeneous environmental change, a phenomenon known as phenotypic heterogeneity. Phenotypic heterogeneity can enable bet-hedging or division of labor strategies that allow bacteria to survive fluctuating conditions. Investigating the significance of phenotypic heterogeneity in environmental transitions requires dynamic, single-cell data. Technical advances in quantitative single-cell measurements, imaging, and microfluidics have led to a surge of publications on this topic. Here, we review recent discoveries on single-cell bacterial responses to environmental transitions of various origins and complexities, from simple diauxic shifts to community behaviors in biofilm formation to virulence regulation during infection. We describe how these studies firmly establish that this form of heterogeneity is prevalent and a conserved mechanism by which bacteria cope with fluctuating conditions. We end with an outline of current challenges and future directions for the field. While it remains challenging to predict how an individual bacterium will respond to a given environmental input, we anticipate that capturing the dynamics of the process will begin to resolve this and facilitate rational perturbation of environmental responses for therapeutic and bioengineering purposes.

Bacterial battle against acidity

The Earth is home to environments characterized by low pH, including the gastrointestinal tract of vertebrates and large areas of acidic soil. Most bacteria are neutralophiles, but can survive fluctuations in pH. Herein, we review how Escherichia, Salmonella, Helicobacter, Brucella, and other acid-resistant Gram-negative bacteria adapt to acidic environments. We discuss the constitutive and inducible defense mechanisms that promote survival, including proton-consuming or ammonia-producing processes, cellular remodeling affecting membranes and chaperones, and chemotaxis. We provide insights into how Gram-negative bacteria sense environmental acidity using membrane-integrated and cytosolic pH sensors. Finally, we address in more detail the powerful proton-consuming decarboxylase systems by examining the phylogeny of their regulatory components and their collective functionality in a population.

Intracellular acidification is a hallmark of thymineless death in E. coli

Thymidine starvation causes rapid cell death. This enigmatic process known as thymineless death (TLD) is the underlying killing mechanism of diverse antimicrobial and antineoplastic drugs. Despite decades of investigation, we still lack a mechanistic understanding of the causal sequence of events that culminate in TLD. Here, we used a diverse set of unbiased approaches to systematically determine the genetic and regulatory underpinnings of TLD in Escherichia coli. In addition to discovering novel genes in previously implicated pathways, our studies revealed a critical and previously unknown role for intracellular acidification in TLD. We observed that a decrease in cytoplasmic pH is a robust early event in TLD across different genetic backgrounds. Furthermore, we show that acidification is a causal event in the death process, as chemical and genetic perturbations that increase intracellular pH substantially reduce killing. We also observe a decrease in intracellular pH in response to exposure to the antibiotic gentamicin, suggesting that intracellular acidification may be a common mechanistic step in the bactericidal effects of other antibiotics.

Growth-mediated negative feedback shapes quantitative antibiotic response

Dose–response relationships are a general concept for quantitatively describing biological systems across multiple scales, from the molecular to the whole‐cell level. A clinically relevant example is the bacterial growth response to antibiotics, which is routinely characterized by dose–response curves. The shape of the dose–response curve varies drastically between antibiotics and plays a key role in treatment, drug interactions, and resistance evolution. However, the mechanisms shaping the dose–response curve remain largely unclear. Here, we show in Escherichia coli that the distinctively shallow dose–response curve of the antibiotic trimethoprim is caused by a negative growth‐mediated feedback loop: Trimethoprim slows growth, which in turn weakens the effect of this antibiotic. At the molecular level, this feedback is caused by the upregulation of the drug target dihydrofolate reductase (FolA/DHFR). We show that this upregulation is not a specific response to trimethoprim but follows a universal trend line that depends primarily on the growth rate, irrespective of its cause. Rewiring the feedback loop alters the dose–response curve in a predictable manner, which we corroborate using a mathematical model of cellular resource allocation and growth. Our results indicate that growth‐mediated feedback loops may shape drug responses more generally and could be exploited to design evolutionary traps that enable selection against drug resistance.

Bacterial Stress Responses as Potential Targets in Overcoming Antibiotic Resistance

Bacteria can be adapted to adverse and detrimental conditions that induce general and specific responses to DNA damage as well as acid, heat, cold, starvation, oxidative, envelope, and osmotic stresses. The stress-triggered regulatory systems are involved in bacterial survival processes, such as adaptation, physiological changes, virulence potential, and antibiotic resistance. Antibiotic susceptibility to several antibiotics is reduced due to the activation of stress responses in cellular physiology by the stimulation of resistance mechanisms, the promotion of a resistant lifestyle (biofilm or persistence), and/or the induction of resistance mutations. Hence, the activation of bacterial stress responses poses a serious threat to the efficacy and clinical success of antibiotic therapy. Bacterial stress responses can be potential targets for therapeutic alternatives to antibiotics. An understanding of the regulation of stress response in association with antibiotic resistance provides useful information for the discovery of novel antimicrobial adjuvants and the development of effective therapeutic strategies to control antibiotic resistance in bacteria. Therefore, this review discusses bacterial stress responses linked to antibiotic resistance in Gram-negative bacteria and also provides information on novel therapies targeting bacterial stress responses that have been identified as potential candidates for the effective control of Gram-negative antibiotic-resistant bacteria.

Division of labor and collective functionality in Escherichia coli under acid stress

The acid stress response is an important factor influencing the transmission of intestinal microbes such as the enterobacterium Escherichia coli. E. coli activates three inducible acid resistance systems - the glutamate decarboxylase, arginine decarboxylase, and lysine decarboxylase systems to counteract acid stress. Each system relies on the activity of a proton-consuming reaction catalyzed by a specific amino acid decarboxylase and a corresponding antiporter. Activation of these three systems is tightly regulated by a sophisticated interplay of membrane-integrated and soluble regulators. Using a fluorescent triple reporter strain, we quantitatively illuminated the cellular individuality during activation of each of the three acid resistance (AR) systems under consecutively increasing acid stress. Our studies highlight the advantages of E. coli in possessing three AR systems that enable division of labor in the population, which ensures survival over a wide range of low pH values.

Dynamic gene expression and growth underlie cell-to-cell heterogeneity in Escherichia coli stress response

Individual bacteria that share identical genomes and growth environments can display substantial cell-to-cell differences in expression of stress-response genes and single-cell growth rates. This phenotypic heterogeneity can impact the survival of single cells facing sudden stress. However, the windows of time that cells spend in vulnerable or tolerant states are often unknown. We quantify the temporal expression of a suite of stress-response reporters, while simultaneously monitoring growth. We observe pulsatile expression across genes with a range of stress-response functions, finding that single-cell growth rates are often anticorrelated with reporter levels. These dynamic phenotypic differences have a concrete link to function, in which individual cells undergoing a pulse of elevated expression and slow growth are predisposed to survive antibiotic exposure.

Cell-to-cell heterogeneity in gene expression and growth can have critical functional consequences, such as determining whether individual bacteria survive or die following stress. Although phenotypic variability is well documented, the dynamics that underlie it are often unknown. This information is important because dramatically different outcomes can arise from gradual versus rapid changes in expression and growth. Using single-cell time-lapse microscopy, we measured the temporal expression of a suite of stress-response reporters in Escherichia coli, while simultaneously monitoring growth rate. In conditions without stress, we found several examples of pulsatile expression. Single-cell growth rates were often anticorrelated with reporter levels, with changes in growth preceding changes in expression. These dynamics have functional consequences, which we demonstrate by measuring survival after challenging cells with the antibiotic ciprofloxacin. Our results suggest that fluctuations in both gene expression and growth dynamics in stress-response networks have direct consequences on survival.

Systematic inference identifies a major source of heterogeneity in cell signaling dynamics: The rate-limiting step number

Identifying the sources of cell-to-cell variability in signaling dynamics is essential to understand drug response variability and develop effective therapeutics. However, it is challenging because not all signaling intermediate reactions can be experimentally measured simultaneously. This can be overcome by replacing them with a single random time delay, but the resulting process is non-Markovian, making it difficult to infer cell-to-cell heterogeneity in reaction rates and time delays. To address this, we developed an efficient and scalable moment-based Bayesian inference method (MBI) with a user-friendly computational package that infers cell-to-cell heterogeneity in the non-Markovian signaling process. We applied MBI to single-cell expression profiles from promoters responding to antibiotics and discovered a major source of cell-to-cell variability in antibiotic stress response: the number of rate-limiting steps in signaling cascades. This knowledge can help identify effective therapies that destroy all pathogenic or cancer cells, and the approach can be applied to precision medicine.

A mouse model of occult intestinal colonization demonstrating antibiotic-induced outgrowth of carbapenem-resistant Enterobacteriaceae

BACKGROUND

The human intestinal microbiome is a complex community that contributes to host health and disease. In addition to normal microbiota, pathogens like carbapenem-resistant Enterobacteriaceae may be asymptomatically present. When these bacteria are present at very low levels, they are often undetectable in hospital surveillance cultures, known as occult or subclinical colonization. Through the receipt of antibiotics, these subclinical pathogens can increase to sufficiently high levels to become detectable, in a process called outgrowth. However, little is known about the interaction between gut microbiota and Enterobacteriaceae during occult colonization and outgrowth.

RESULTS

We developed a clinically relevant mouse model for studying occult colonization. Conventional wild-type mice without antibiotic pre-treatment were exposed to Klebsiella pneumoniae but rapidly tested negative for colonization. This occult colonization was found to perturb the microbiome as detected by both 16S rRNA amplicon and shotgun metagenomic sequencing. Outgrowth of occult K. pneumoniae was induced either by a four-antibiotic cocktail or by individual receipt of ampicillin, vancomycin, or azithromycin, which all reduced overall microbial diversity. Notably, vancomycin was shown to trigger K. pneumoniae outgrowth in only a subset of exposed animals (outgrowth-susceptible). To identify factors that underlie outgrowth susceptibility, we analyzed microbiome-encoded gene functions and were able to classify outgrowth-susceptible microbiomes using pathways associated with mRNA stability. Lastly, an evolutionary approach illuminated the importance of xylose metabolism in K. pneumoniae colonization, supporting xylose abundance as a second susceptibility indicator. We showed that our model is generalizable to other pathogens, including carbapenem-resistant Escherichia coli and Enterobacter cloacae.

CONCLUSIONS

Our modeling of occult colonization and outgrowth could help the development of strategies to mitigate the risk of subsequent infection and transmission in medical facilities and the wider community. This study suggests that microbiota mRNA and small-molecule metabolites may be used to predict outgrowth-susceptibility. Video Abstract.

The physiology and genetics of bacterial responses to antibiotic combinations

Several promising strategies based on combining or cycling different antibiotics have been proposed to increase efficacy and counteract resistance evolution, but we still lack a deep understanding of the physiological responses and genetic mechanisms that underlie antibiotic interactions and the clinical applicability of these strategies. In antibiotic-exposed bacteria, the combined effects of physiological stress responses and emerging resistance mutations (occurring at different time scales) generate complex and often unpredictable dynamics. In this Review, we present our current understanding of bacterial cell physiology and genetics of responses to antibiotics. We emphasize recently discovered mechanisms of synergistic and antagonistic drug interactions, hysteresis in temporal interactions between antibiotics that arise from microbial physiology and interactions between antibiotics and resistance mutations that can cause collateral sensitivity or cross-resistance. We discuss possible connections between the different phenomena and indicate relevant research directions. A better and more unified understanding of drug and genetic interactions is likely to advance antibiotic therapy.

Myxopyronin B inhibits growth of a Fidaxomicin-resistant Clostridioides difficile isolate and interferes with toxin synthesis

The anaerobic, gastrointestinal pathogen Clostridioides difficile can cause severe forms of enterocolitis which is mainly mediated by the toxins it produces. The RNA polymerase inhibitor Fidaxomicin is the current gold standard for the therapy of C. difficile infections due to several beneficial features including its ability to suppress toxin synthesis in C. difficile. In contrast to the Rifamycins, Fidaxomicin binds to the RNA polymerase switch region, which is also the binding site for Myxopyronin B. Here, serial broth dilution assays were performed to test the susceptibility of C. difficile and other anaerobes to Myxopyronin B, proving that the natural product is considerably active against C. difficile and that there is no cross-resistance between Fidaxomicin and Myxopyronin B in a Fidaxomicin-resistant C. difficile strain. Moreover, mass spectrometry analysis indicated that Myxopyronin B is able to suppress early phase toxin synthesis in C. difficile to the same degree as Fidaxomicin. Conclusively, Myxopyronin B is proposed as a new lead structure for the design of novel antibiotics for the therapy of C. difficile infections.

Effect of sublethal concentrations of bactericidal antibiotics on mutation frequency and stress response of Listeria monocytogenes

The purpose of this study was to investigate sublethal concentrations (SLC) of bactericidal antibiotics (ampicillin, gentamicin, kanamycin, and vancomycin) on the mutation frequency and stress response of antibiotic-induced-mutated (AIM) Listeria monocytogenes. Three L. monocytogenes strains (reference, clinical, and food isolate strains) were used in this study. SLC of bactericidal antibiotics significantly increased the mutation frequency in L. monocytogenes. It was found that AIM L. monocytogenes had a superior biofilm-forming ability than nontreated L. monocytogenes. This result correlated with the amounts of EPS produced (polysaccharide and protein) in the early stage of biofilm formation. AIM L. monocytogenes showed strong viability under food-associated stress (thermal, osmotic, and acidic) compared to nontreated L. monocytogenes. In addition, expression levels of motility (flaA) and virulence genes (hlyA, actA, and prfA) of AIM L. monocytogenes were significantly downregulated in the reference strain but significantly upregulated or similar to the expression levels in the clinical and food isolate strains compared to nontreated L. monocytogenes. Based on our results, SLC of bactericidal antibiotics increased the mutation frequency in L. monocytogenes, facilitated the adaptation of the bacterium to food-associated stress, and led to an increase in its pathogenicity.

Uncovering Key Metabolic Determinants of the Drug Interactions Between Trimethoprim and Erythromycin in Escherichia coli

Understanding interactions between antibiotics used in combination is an important theme in microbiology. Using the interactions between the antifolate drug trimethoprim and the ribosome-targeting antibiotic erythromycin in Escherichia coli as a model, we applied a transcriptomic approach for dissecting interactions between two antibiotics with different modes of action. When trimethoprim and erythromycin were combined, the transcriptional response of genes from the sulfate reduction pathway deviated from the dominant effect of trimethoprim on the transcriptome. We successfully altered the drug interaction from additivity to suppression by increasing the sulfate level in the growth environment and identified sulfate reduction as an important metabolic determinant that shapes the interaction between the two drugs. Our work highlights the potential of using prioritization of gene expression patterns as a tool for identifying key metabolic determinants that shape drug-drug interactions. We further demonstrated that the sigma factor-binding protein gene crl shapes the interactions between the two antibiotics, which provides a rare example of how naturally occurring variations between strains of the same bacterial species can sometimes generate very different drug interactions.

Hyperosmotic Shock Transiently Accelerates Constriction Rate in Escherichia coli

Bacterial cells in their natural environments encounter rapid and large changes in external osmolality. For instance, enteric bacteria such as Escherichia coli experience a rapid decrease when they exit from host intestines. Changes in osmolality alter the mechanical load on the cell envelope, and previous studies have shown that large osmotic shocks can slow down bacterial growth and impact cytoplasmic diffusion. However, it remains unclear how cells maintain envelope integrity and regulate envelope synthesis in response to osmotic shocks. In this study, we developed an agarose pad-based protocol to assay envelope stiffness by measuring population-averaged cell length before and after a hyperosmotic shock. Pad-based measurements exhibited an apparently larger length change compared with single-cell dynamics in a microfluidic device, which we found was quantitatively explained by a transient increase in division rate after the shock. Inhibiting cell division led to consistent measurements between agarose pad-based and microfluidic measurements. Directly after hyperosmotic shock, FtsZ concentration and Z-ring intensity increased, and the rate of septum constriction increased. These findings establish an agarose pad-based protocol for quantifying cell envelope stiffness, and demonstrate that mechanical perturbations can have profound effects on bacterial physiology.

Water-Soluble Humic Materials Modulating Metabolism and Triggering Stress Defense in Sinorhizobium fredii

Bacteria have evolved a series of mechanisms to maintain their survival and reproduction in changeable and stressful environments. In-depth understanding of these mechanisms can allow for better developing and utilizing of bacteria with various biological functions. In this study, we found that water-soluble humic materials (WSHM), a well-known environment-friendly plant growth biostimulant, significantly promoted the free-living growth and survival of Sinorhizobium fredii CCBAU45436 in a bell-shaped, dose-dependent manner, along with more-efficient carbon source consumption and relief of medium acidification. By using RNA-Seq analysis, a total of 1,136 genes significantly up-/downregulated by external addition of WSHM were identified under test conditions. These differentially expressed genes (DEGs) were enriched in functional categories related to carbon/nitrogen metabolism, cellular stress response, and genetic information processing. Further protein-protein interaction (PPI) network analysis and reverse genetic engineering indicated that WSHM might reprogram the transcriptome through inhibiting the expression of key hub gene rsh, which encodes a bifunctional enzyme catalyzing synthesis and hydrolysis of the "magic spot" (p)ppGpp. In addition, the root colonization and viability in soil of S. fredii CCBAU45436 were increased by WSHM. These findings provide us with new insights into how WSHM benefit bacterial adaptations and demonstrate great application value to be a unique inoculant additive. IMPORTANCE Sinorhizobium fredii CCBAU45436 is a highly effective, fast-growing rhizobium that can establish symbiosis with multiple soybean cultivars. However, it is difficult to maintain the high-density effective viable cells in the rhizobial inoculant for the stressful conditions during production, storage, transport, and application. Here, we showed that WSHM greatly increased the viable cells of S. fredii CCBAU45436 in culture, modulating metabolism and triggering stress defense. The root colonization and viability in soil of S. fredii CCBAU45436 were also increased by WSHM. Our results shed new insights into the effects of WSHM on bacteria and the importance of metabolism and stress defense during the bacteria's whole life. In addition, the functional mechanism of WSHM may provide candidate genes for improving environmental adaptability and application potential of bacteria through genetic engineering.

C Group-Mediated Antibiotic Stress Mimics the Cold Shock Response

A temperature downshift results in stabilized secondary structure formation in mRNA that halts translation to which Escherichia coli responds by synthesizing a set of proteins termed as cold shock proteins (Csps). To cope with the sudden temperature drop, gene expression patterns are reprogrammed to induce Csps at the cost of other proteins. Out of the nine homologous proteins in the CspA family, CspA, CspB, CspG, and CspI have major roles in protecting the cell under a cold shock. Additionally, a subset of Csps has conferred the organism an ability to adapt to various stresses along the lines of nutrient deprivation, oxidative, heat, acid, and antibiotic stresses. Stressors like C group translational inhibitors stall the translational apparatus and produce a response similar to that observed under a temperature downshift. Conditions set by the antibiotic therefore elicit a cold shock response and induce the major Csps, thereby pointing out to a common mechanism existing between the two. In the current review, we briefly describe the induction of E. coli Csps under an antibiotic stress acquired from data published previously and help establish the role of Csps in protecting the cell against the inducing agents and as a participant in the organisms' complex stress response network.

Tunable phenotypic variability through an autoregulatory alternative sigma factor circuit

Genetically identical individuals in bacterial populations can display significant phenotypic variability. This variability can be functional, for example by allowing a fraction of stress prepared cells to survive an otherwise lethal stress. The optimal fraction of stress prepared cells depends on environmental conditions. However, how bacterial populations modulate their level of phenotypic variability remains unclear. Here we show that the alternative sigma factor σV circuit in Bacillus subtilis generates functional phenotypic variability that can be tuned by stress level, environmental history and genetic perturbations. Using single-cell time-lapse microscopy and microfluidics, we find the fraction of cells that immediately activate σV under lysozyme stress depends on stress level and on a transcriptional memory of previous stress. Iteration between model and experiment reveals that this tunability can be explained by the autoregulatory feedback structure of the sigV operon. As predicted by the model, genetic perturbations to the operon also modulate the response variability. The conserved sigma-anti-sigma autoregulation motif is thus a simple mechanism for bacterial populations to modulate their heterogeneity based on their environment.

Insights into Emergence of Antibiotic Resistance in Acid-Adapted Enterohaemorrhagic Escherichia coli

The emergence of multidrug-resistant pathogens presents a global challenge for treating and preventing disease spread through zoonotic transmission. The water and foodborne Enterohaemorrhagic Escherichia coli (EHEC) are capable of causing intestinal and systemic diseases. The root cause of the emergence of these strains is their metabolic adaptation to environmental stressors, especially acidic pH. Acid treatment is desired to kill pathogens, but the protective mechanisms employed by EHECs cross-protect against antimicrobial peptides and thus facilitate opportunities for survival and pathogenesis. In this review, we have discussed the correlation between acid tolerance and antibiotic resistance, highlighting the identification of novel targets for potential production of antimicrobial therapeutics. We have also summarized the molecular mechanisms used by acid-adapted EHECs, such as the two-component response systems mediating structural modifications, competitive inhibition, and efflux activation that facilitate cross-protection against antimicrobial compounds. Moving beyond the descriptive studies, this review highlights low pH stress as an emerging player in the development of cross-protection against antimicrobial agents. We have also described potential gene targets for innovative therapeutic approaches to overcome the risk of multidrug-resistant diseases in healthcare and industry.

Analysis of temporal gene regulation of Listeria monocytogenes revealed distinct regulatory response modes after exposure to high pressure processing

BACKGROUND

The pathogen Listeria (L.) monocytogenes is known to survive heat, cold, high pressure, and other extreme conditions. Although the response of this pathogen to pH, osmotic, temperature, and oxidative stress has been studied extensively, its reaction to the stress produced by high pressure processing HPP (which is a preservation method in the food industry), and the activated gene regulatory network (GRN) in response to this stress is still largely unknown.

RESULTS

We used RNA sequencing transcriptome data of L. monocytogenes (ScottA) treated at 400 MPa and 8∘C, for 8 min and combined it with current information in the literature to create a transcriptional regulation database, depicting the relationship between transcription factors (TFs) and their target genes (TGs) in L. monocytogenes. We then applied network component analysis (NCA), a matrix decomposition method, to reconstruct the activities of the TFs over time. According to our findings, L. monocytogenes responded to the stress applied during HPP by three statistically different gene regulation modes: survival mode during the first 10 min post-treatment, repair mode during 1 h post-treatment, and re-growth mode beyond 6 h after HPP. We identified the TFs and their TGs that were responsible for each of the modes. We developed a plausible model that could explain the regulatory mechanism that L. monocytogenes activated through the well-studied CIRCE operon via the regulator HrcA during the survival mode.

CONCLUSIONS

Our findings suggest that the timely activation of TFs associated with an immediate stress response, followed by the expression of genes for repair purposes, and then re-growth and metabolism, could be a strategy of L. monocytogenes to survive and recover extreme HPP conditions. We believe that our results give a better understanding of L. monocytogenes behavior after exposure to high pressure that may lead to the design of a specific knock-out process to target the genes or mechanisms. The results can help the food industry select appropriate HPP conditions to prevent L. monocytogenes recovery during food storage.

Pulses and delays, anticipation and memory: seeing bacterial stress responses from a single-cell perspective

Stress responses are crucial for bacteria to survive harmful conditions that they encounter in the environment. Although gene regulatory mechanisms underlying stress responses in bacteria have been thoroughly characterised for decades, recent advances in imaging technologies helped to uncover previously hidden dynamics and heterogeneity that become visible at the single-cell level. Despite the diversity of stress response mechanisms, certain dynamic regulatory features are frequently seen in single cells, such as pulses, delays, stress anticipation and memory effects. Often, these dynamics are highly variable across cells. While any individual cell may not achieve an optimal stress response, phenotypic diversity can provide a benefit at the population level. In this review, we highlight microscopy studies that offer novel insights into how bacteria sense stress, regulate protective mechanisms, cope with response delays and prepare for future environmental challenges. These studies showcase developments in the single-cell imaging toolbox including gene expression reporters, FRET, super-resolution microscopy and single-molecule tracking, as well as microfluidic techniques to manipulate cells and create defined stress conditions.

Functional roles of microbial cell-to-cell heterogeneity and emerging technologies for analysis and control

Clonal cell populations often display significant cell-to-cell phenotypic heterogeneity, even when maintained under constant external conditions. This variability can result from the inherently stochastic nature of transcription and translation processes, which leads to varying numbers of transcripts and proteins per cell. Here, we showcase studies that reveal links between stochastic cellular events and biological functions in isogenic microbial populations. Then, we highlight emerging tools from engineering, computation, and synthetic and molecular biology that enable precise measurement, control, and analysis of gene expression noise in microorganisms. The capabilities offered by this sophisticated toolbox will shape future directions in the field and generate insight into the behavior of living systems at the single-cell level.

Understanding How Microorganisms Respond to Acid pH Is Central to Their Control and Successful Exploitation

Microbes from the three domains of life, Bacteria, Archaea, and Eukarya, share the need to sense and respond to changes in the external and internal concentrations of protons. When the proton concentration is high, acidic conditions prevail and cells must respond appropriately to ensure that macromolecules and metabolic processes are sufficiently protected to sustain life. While, we have learned much in recent decades about the mechanisms that microbes use to cope with acid, including the unique challenges presented by organic acids, there is still much to be gained from developing a deeper understanding of the effects and responses to acid in microbes. In this perspective article, we survey the key molecular mechanisms known to be important for microbial survival during acid stress and discuss how this knowledge might be relevant to microbe-based applications and processes that are consequential for humans. We discuss the research approaches that have been taken to investigate the problem and highlight promising new avenues. We discuss the influence of acid on pathogens during the course of infections and highlight the potential of using organic acids in treatments for some types of infection. We explore the influence of acid stress on photosynthetic microbes, and on biotechnological and industrial processes, including those needed to produce organic acids. We highlight the importance of understanding acid stress in controlling spoilage and pathogenic microbes in the food chain. Finally, we invite colleagues with an interest in microbial responses to low pH to participate in the EU-funded COST Action network called EuroMicropH and contribute to a comprehensive database of literature on this topic that we are making publicly available.

A Two-Enzyme Adaptive Unit within Bacterial Folate Metabolism

Enzyme function and evolution are influenced by the larger context of a metabolic pathway. Deleterious mutations or perturbations in one enzyme can often be compensated by mutations to others. We used comparative genomics and experiments to examine evolutionary interactions with the essential metabolic enzyme dihydrofolate reductase (DHFR). Analyses of synteny and co-occurrence across bacterial species indicate that DHFR is coupled to thymidylate synthase (TYMS) but relatively independent from the rest of folate metabolism. Using quantitative growth rate measurements and forward evolution in Escherichia coli, we demonstrate that the two enzymes adapt as a relatively independent unit in response to antibiotic stress. Metabolomic profiling revealed that TYMS activity must not exceed DHFR activity to prevent the depletion of reduced folates and the accumulation of the intermediate dihydrofolate. Comparative genomics analyses identified >200 gene pairs with similar statistical signatures of modular co-evolution, suggesting that cellular pathways may be decomposable into small adaptive units.

Sulfamethoxazole drug stress upregulates antioxidant immunomodulatory metabolites in Escherichia coli

Escherichia coli is an important model organism in microbiology and a prominent member of the human microbiota¹. Environmental isolates readily colonize the gastrointestinal tract of humans and other animals, and they can serve diverse probiotic, commensal and pathogenic roles in the host^2-4. Although certain strains have been associated with the severity of inflammatory bowel disease (IBD)^2,5, the diverse immunomodulatory phenotypes remain largely unknown at the molecular level. Here, we decode a previously unknown E. coli metabolic pathway that produces a family of hybrid pterin-phenylpyruvate conjugates, which we named the colipterins. The metabolites are upregulated by subinhibitory levels of the antifolate sulfamethoxazole, which is used to treat infections including in patients with IBD^6,7. The genes folX/M and aspC/tyrB involved in monapterin biosynthesis^8-10 and aromatic amino acid transamination,¹¹ respectively, were required to initiate the colipterin pathway. We show that the colipterins are antioxidants, harbour diverse immunological activities in primary human tissues, activate anti-inflammatory interleukin-10 and improve colitis symptoms in a colitis mouse model. Our study defines an antifolate stress response in E. coli and links its associated metabolites to a major immunological marker of IBD.

Molecular design of a signaling system influences noise in protein abundance under acid stress in different γ-Proteobacteria

Bacteria have evolved different signaling systems to sense and adapt to acid stress. One of these systems, the CadABC-system, responds to a combination of low pH and lysine availability. In Escherichia coli, the two signals are sensed by the pH sensor and transcription activator CadC and the co-sensor LysP, a lysine-specific transporter. Activated CadC promotes the transcription of the cadBA operon, which codes for the lysine decarboxylase CadA and the lysine/cadaverine antiporter CadB. The copy number of CadC is controlled translationally. Using a bioinformatics approach, we identified the presence of CadC with ribosomal stalling motifs together with LysP in species of the Enterobacteriaceae family. In contrast, we identified CadC without stalling motifs in species of the Vibrionaceae family, but the LysP co-sensor was not identified. Therefore, we compared the output of the Cad system in single cells of the distantly related organisms E. coli and V. campbellii using fluorescently-tagged CadB as the reporter. We observed a heterogeneous output in E. coli, and all the V. campbellii cells produced CadB. The copy number of the pH sensor CadC in E. coli was extremely low (≤4 molecules per cell), but it was 10-fold higher in V. campbellii An increase in the CadC copy number in E. coli correlated with a decrease in heterogeneous behavior. This study demonstrated how small changes in the design of a signaling system allow a homogeneous output and, thus, adaptation of Vibrio species that rely on the CadABC-system as the only acid resistance system.Importance Acid resistance is an important property of bacteria, such as Escherichia coli, to survive acidic environments like the human gastrointestinal tract. E. coli possess both passive and inducible acid resistance systems to counteract acidic environments. Thus, E. coli evolved sophisticated signaling systems to sense and appropriately respond to environmental acidic stress by regulating the activity of its three inducible acid resistance systems. One of these systems is the Cad system that is only induced under moderate acidic stress in a lysine-rich environment by the pH-responsive transcriptional regulator CadC. The significance of our research is in identifying the molecular design of the Cad systems in different Proteobacteria and their target expression noise at single cell level during acid stress conditions.

A Strategic Target Rescues Trimethoprim Sensitivity in Escherichia coli

Trimethoprim, a preferred treatment for urinary tract infections, is becoming obsolete owing to the rapid dissemination of resistant E. coli. Although direct resistance mechanisms such as overexpression of a mutant FolA and dfr enzymes are well characterized, associated alterations that drive or sustain resistance are unknown. We identify the repertoire of resistance-associated perturbations by constructing and interrogating a transcriptome-integrated functional interactome. From the cross talk between perturbations in stress-response and metabolic pathways, we identify the critical dependence on serine hydroxymethyltransferase (GlyA) as an emergent vulnerability. Through its deletion, we demonstrate that GlyA is necessary to sustain high levels of resistance in both laboratory-evolved resistant E. coli and a multidrug-resistant clinical isolate. Through comparative evolution, we show that the absence of GlyA activity decelerates the acquisition of resistance in E. coli. Put together, our results identify GlyA as a promising target, providing a basis for the rational design of drug combinations.

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TMP-resistant E. coli show cross talk between stress response and metabolic pathways

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Dependence on glyA is an emergent vulnerability associated with TMP resistance

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Knockout of glyA partially rescues sensitivity to TMP in E. coli

Bacterial interspecies interactions modulate pH-mediated antibiotic tolerance

Predicting antibiotic efficacy within microbial communities remains highly challenging. Interspecies interactions can impact antibiotic activity through many mechanisms, including alterations to bacterial physiology. Here, we studied synthetic communities constructed from the core members of the fruit fly gut microbiota. Co-culturing of Lactobacillus plantarum with Acetobacter species altered its tolerance to the transcriptional inhibitor rifampin. By measuring key metabolites and environmental pH, we determined that Acetobacter species counter the acidification driven by L. plantarum production of lactate. Shifts in pH were sufficient to modulate L. plantarum tolerance to rifampin and the translational inhibitor erythromycin. A reduction in lag time exiting stationary phase was linked to L. plantarum tolerance to rifampicin, opposite to a previously identified mode of tolerance to ampicillin in E. coli. This mechanistic understanding of the coupling among interspecies interactions, environmental pH, and antibiotic tolerance enables future predictions of growth and the effects of antibiotics in more complex communities.

Notch pathway: a bistable inducer of biological noise?

Notch signalling pathway is central to development of metazoans. The pathway codes a binary fate switch. Upon activation, downstream signals contribute to resolution of fate dichotomies such as proliferation/differentiation or sub-lineage differentiation outcome. There is, however, an interesting paradox in the Notch signalling pathway. Despite remarkable predictability of fate outcomes instructed by the Notch pathway, the associated transcriptome is versatile and plastic. This inconsistency suggests the presence of an interface that compiles input from the plastic transcriptome of the Notch pathway but communicates only a binary output in biological decisions. Herein, we address the interface that determines fate outcomes. We provide an alternative hypothesis for the Notch pathway as a biological master switch that operates by induction of genetic noise and bistability in order to facilitate resolution of dichotomous fate outcomes in development.

β-Catenin: A Metazoan Filter for Biological Noise?

Molecular noise refers to fluctuations of biological signals that facilitate phenotypic heterogeneity in a population. While endogenous mechanisms exist to limit genetic noise in biological systems, such restrictions are sometimes removed to propel phenotypic variability as an adaptive strategy. Herein, we review evidence for the potential role of β-catenin in restricting gene expression noise by transcriptional and post-transcriptional mechanisms. We discuss mechanisms that restrict intrinsic noise subsequent to nuclear mobilization of β-catenin. Nuclear β-catenin promotes initiation of transcription but buffers against the resultant noise by restraining transcription elongation. Acceleration of cell cycle, mediated via Wnt/β-catenin downstream signals, further diminishes intrinsic noise by curtailing the efficiency of protein synthesis. Extrinsic noise, on the other hand, is restricted by β-catenin–mediated regulation of major cellular stress pathways.

A phenotypic screening bioassay for Escherichia coli stress and antibiotic responses based on Fourier-transform infrared (FTIR) spectroscopy and multivariate analysis

AIMS

To develop and optimize a Fourier-transform infrared spectroscopy (FTIRS) phenotypic screening bioassay for stress responses, regarding the effect of nutrient content, bacterial growth phase and stress agent exposure time.

METHODS AND RESULTS

A high-throughput FTIRS bioassay was developed to distinguish the stress responses of Escherichia coli to sodium hydroxide, hydrochloric acid, sodium chloride, sodium hypochlorite and ethanol. Principal component analysis and hierarchical clustering were used to quantify the effect of each parameter on bioassay performance, namely its reproducibility and metabolic resolution. Bioassay performance varied greatly, ranging from poor to very good. Spectra were partitioned into biologically relevant regions to evaluate their contributions to bioassay performance, but further improvements were not observed. Bioassay optimization was validated against empirical parameters, which confirmed a closer representation of known mechanisms on the antibiotic-induced stress responses.

CONCLUSIONS

The optimized bioassay used standard nutrient content, cells in the late-stationary growth phase and a one-shift exposure duration. Only the optimized bioassay adequately and reproducibly distinguished the E. coli stress and antibiotic responses. The absence of performance improvements using partitioned spectra indicated that stress responses are imprinted on the whole-spectra metabolic signature.

SIGNIFICANCE AND IMPACT OF THE STUDY

Highly optimized FTIRS bioassay parameters are vital in capturing whole-spectra metabolic signatures that can be used for satisfactory and reproducible phenotypic screening of stress and antibiotic responses.

Forecasting cell fate during antibiotic exposure using stochastic gene expression

Antibiotic killing does not occur at a single, precise time for all cells within a population. Variability in time to death can be caused by stochastic expression of genes, resulting in differences in endogenous stress-resistance levels between individual cells in a population. Here we investigate whether single-cell differences in gene expression prior to antibiotic exposure are related to cell survival times after antibiotic exposure for a range of genes of diverse function. We quantified the time to death of single cells under antibiotic exposure in combination with expression of reporters. For some reporters, including genes involved in stress response and cellular processes like metabolism, the time to cell death had a strong relationship with the initial expression level of the genes. Our results highlight the single-cell level non-uniformity of antibiotic killing and also provide examples of key genes where cell-to-cell variation in expression is strongly linked to extended durations of antibiotic survival.

Temporal order and precision of complex stress responses in individual bacteria

Sudden stress often triggers diverse, temporally structured gene expression responses in microbes, but it is largely unknown how variable in time such responses are and if genes respond in the same temporal order in every single cell. Here, we quantified timing variability of individual promoters responding to sublethal antibiotic stress using fluorescent reporters, microfluidics, and time-lapse microscopy. We identified lower and upper bounds that put definite constraints on timing variability, which varies strongly among promoters and conditions. Timing variability can be interpreted using results from statistical kinetics, which enable us to estimate the number of rate-limiting molecular steps underlying different responses. We found that just a few critical steps control some responses while others rely on dozens of steps. To probe connections between different stress responses, we then tracked the temporal order and response time correlations of promoter pairs in individual cells. Our results support that, when bacteria are exposed to the antibiotic nitrofurantoin, the ensuing oxidative stress and SOS responses are part of the same causal chain of molecular events. In contrast, under trimethoprim, the acid stress response and the SOS response are part of different chains of events running in parallel. Our approach reveals fundamental constraints on gene expression timing and provides new insights into the molecular events that underlie the timing of stress responses.

Escherichia coli can survive stress by noisy growth modulation

Gene expression can be noisy, as can the growth of single cells. Such cell-to-cell variation has been implicated in survival strategies for bacterial populations. However, it remains unclear how single cells couple gene expression with growth to implement these strategies. Here, we show how noisy expression of a key stress-response regulator, RpoS, allows E. coli to modulate its growth dynamics to survive future adverse environments. We reveal a dynamic positive feedback loop between RpoS and growth rate that produces multi-generation RpoS pulses. We do so experimentally using single-cell, time-lapse microscopy and microfluidics and theoretically with a stochastic model. Next, we demonstrate that E. coli prepares for sudden stress by entering prolonged periods of slow growth mediated by RpoS. This dynamic phenotype is captured by the RpoS-growth feedback model. Our synthesis of noisy gene expression, growth, and survival paves the way for further exploration of functional phenotypic variability.

Noisy gene expression leading to phenotypic variability can help organisms to survive in changing environments. Here, Patange et al. show that noisy expression of a stress response regulator, RpoS, allows E. coli cells to modulate their growth rates to survive future adverse environments.

Lessons and perspectives for applications of stochastic models in biological and cancer research

The effects of randomness, an unavoidable feature of intracellular environments, are observed at higher hierarchical levels of living matter organization, such as cells, tissues, and organisms. Additionally, the many compounds interacting as a well-orchestrated network of reactions increase the difficulties of assessing these systems using only experiments. This limitation indicates that elucidation of the dynamics of biological systems is a complex task that will benefit from the establishment of principles to help describe, categorize, and predict the behavior of these systems. The theoretical machinery already available, or ones to be discovered to help solve biological problems, might play an important role in these processes. Here, we demonstrate the application of theoretical tools by discussing some biological problems that we have approached mathematically: fluctuations in gene expression and cell proliferation in the context of loss of contact inhibition. We discuss the methods that have been employed to provide the reader with a biologically motivated phenomenological perspective of the use of theoretical methods. Finally, we end this review with a discussion of new research perspectives motivated by our results.

A bacterial signaling system regulates noise to enable bet hedging

Phenotypic diversity helps populations persist in changing and often unpredictable environments. One diversity-generating strategy is for individuals to switch randomly between phenotypic states such that one subpopulation has high fitness in the present environment, and another subpopulation has high fitness in an environment that might be encountered in the future. This sort of biological bet hedging can be found in all domains of life. Here, we discuss a recently described example from the bacterium Escherichia coli. When exposed to both oxygen and trimethylamine oxide (TMAO), E. coli hedges its bets on the possibility of oxygen loss by generating high cell-to-cell variability in the expression of the TMAO respiratory system. If oxygen is rapidly depleted from the environment, only those cells that had been expressing the TMAO respiratory system at high levels can continue to grow. This particular bet-hedging scheme possesses some unusual characteristics, most notably the decoupling of gene expression noise from the mean expression level. This decoupling allows bacteria to sense oxygen and regulate the amount of variability in TMAO reductase expression (that is, to turn bet hedging on or off) without having to adjust the mean TMAO reductase expression level. In this review, we discuss the features of the TMAO signaling pathway that permit the decoupling of gene expression noise from the mean and the regulation of bet hedging. We also highlight some open questions regarding the TMAO respiratory system and its regulatory architecture that may be relevant to many signaling systems.

Limits of noise for autoregulated gene expression

Gene expression is influenced by extrinsic noise (involving a fluctuating environment of cellular processes) and intrinsic noise (referring to fluctuations within a cell under constant environment). We study the standard model of gene expression including an (in-)active gene, mRNA and protein. Gene expression is regulated in the sense that the protein feeds back and either represses (negative feedback) or enhances (positive feedback) its production at the stage of transcription. While it is well-known that negative (positive) feedback reduces (increases) intrinsic noise, we give a precise result on the resulting fluctuations in protein numbers. The technique we use is an extension of the Langevin approximation and is an application of a central limit theorem under stochastic averaging for Markov jump processes (Kang et al. in Ann Appl Probab 24:721-759, 2014). We find that (under our scaling and in equilibrium), negative feedback leads to a reduction in the Fano factor of at most 2, while the noise under positive feedback is potentially unbounded. The fit with simulations is very good and improves on known approximations.