Bistable expression of virulence genes in salmonella leads to the formation of an antibiotic-tolerant subpopulation

Bacterial quorum sensing and phenotypic heterogeneity: how the collective shapes the individual

Bacteria communicate with each other through a plethora of small, diffusible organic molecules called autoinducers. This cell-density-dependent regulatory principle is termed quorum sensing, and in many cases the process indeed coordinates group behavior of bacterial populations. Yet, even clonal bacterial populations are not uniform entities; rather, they adopt phenotypic heterogeneity to cope with consecutive, rapid, and frequent environmental fluctuations (bet-hedging) or to concurrently interact with each other by exerting different, often complementary, functions (division of labor). Quorum sensing is mainly regarded as a coordinator of bacterial collective behavior. However, it can also be a driver or a target of individual phenotypic heterogeneity. Hence, quorum sensing increases the overall fitness of a bacterial community by orchestrating group behavior as well as individual traits.

Microbiota-derived metabolites inhibit Salmonella virulent subpopulation development by acting on single-cell behaviors

Salmonella spp. express Salmonella pathogenicity island 1 Type III Secretion System 1 (T3SS-1) genes to mediate the initial phase of interaction with their host. Prior studies indicate short-chain fatty acids, microbial metabolites at high concentrations in the gastrointestinal tract, limit population-level T3SS-1 gene expression. However, only a subset of Salmonella cells in a population express these genes, suggesting short-chain fatty acids could decrease T3SS-1 population-level expression by acting on per-cell expression or the proportion of expressing cells. Here, we combine single-cell, theoretical, and molecular approaches to address the effect of short-chain fatty acids on T3SS-1 expression. Our in vitro results show short-chain fatty acids do not repress T3SS-1 expression by individual cells. Rather, these compounds act to selectively slow the growth of T3SS-1-expressing cells, ultimately decreasing their frequency in the population. Further experiments indicate slowed growth arises from short-chain fatty acid-mediated depletion of the proton motive force. By influencing the T3SS-1 cell-type proportions, our findings imply gut microbial metabolites act on cooperation between the two cell types and ultimately influence Salmonella's capacity to establish within a host.

Noise suppression in stochastic genetic circuits using PID controllers

Inside individual cells, protein population counts are subject to molecular noise due to low copy numbers and the inherent probabilistic nature of biochemical processes. We investigate the effectiveness of proportional, integral and derivative (PID) based feedback controllers to suppress protein count fluctuations originating from two noise sources: bursty expression of the protein, and external disturbance in protein synthesis. Designs of biochemical reactions that function as PID controllers are discussed, with particular focus on individual controllers separately, and the corresponding closed-loop system is analyzed for stochastic controller realizations. Our results show that proportional controllers are effective in buffering protein copy number fluctuations from both noise sources, but this noise suppression comes at the cost of reduced static sensitivity of the output to the input signal. In contrast, integral feedback has no effect on the protein noise level from stochastic expression, but significantly minimizes the impact of external disturbances, particularly when the disturbance comes at low frequencies. Counter-intuitively, integral feedback is found to amplify external disturbances at intermediate frequencies. Next, we discuss the design of a coupled feedforward-feedback biochemical circuit that approximately functions as a derivate controller. Analysis using both analytical methods and Monte Carlo simulations reveals that this derivative controller effectively buffers output fluctuations from bursty stochastic expression, while maintaining the static input-output sensitivity of the open-loop system. In summary, this study provides a systematic stochastic analysis of biochemical controllers, and paves the way for their synthetic design and implementation to minimize deleterious fluctuations in gene product levels.

In the noisy cellular environment, biochemical species such as genes, RNAs and proteins that often occur at low molecular counts, are subject to considerable stochastic fluctuations in copy numbers over time. How cellular biochemical processes function reliably in the face of such randomness is an intriguing fundamental problem. Increasing evidence suggests that random fluctuations (noise) in protein copy numbers play important functional roles, such as driving genetically identical cells to different cell fates. Moreover, many disease states have been attributed to elevated noise levels in specific proteins. Here we systematically investigate design of biochemical systems that function as proportional, integral and derivative-based feedback controllers to suppress protein count fluctuations arising from bursty expression of the protein and external disturbance in protein synthesis. Our results show that different controllers are effective in buffering different noise components, and identify ranges of feedback gain for minimizing deleterious fluctuations in protein levels.

Quorum sensing governs a transmissive Legionella subpopulation at the pathogen vacuole periphery

The Gram‐negative bacterium Legionella pneumophila is the causative agent of Legionnaires' disease and replicates in amoebae and macrophages within a distinct compartment, the Legionella‐containing vacuole (LCV). The facultative intracellular pathogen switches between a replicative, non‐virulent and a non‐replicating, virulent/transmissive phase. Here, we show on a single‐cell level that at late stages of infection, individual motile (P_flaA‐GFP‐positive) and virulent (P_ralF‐ and P_sidC‐GFP‐positive) L. pneumophila emerge in the cluster of non‐growing bacteria within an LCV. Comparative proteomics of P_flaA‐GFP‐positive and P_flaA‐GFP‐negative L. pneumophila subpopulations reveals distinct proteomes with flagellar proteins or cell division proteins being preferentially produced by the former or the latter, respectively. Toward the end of an infection cycle (˜ 48 h), the P_flaA‐GFP‐positive L. pneumophila subpopulation emerges at the cluster periphery, predominantly escapes the LCV, and spreads from the bursting host cell. These processes are mediated by the Legionella quorum sensing (Lqs) system. Thus, quorum sensing regulates the emergence of a subpopulation of transmissive L. pneumophila at the LCV periphery, and phenotypic heterogeneity underlies the intravacuolar bi‐phasic life cycle of L. pneumophila.

A Primed Subpopulation of Bacteria Enables Rapid Expression of the Type 3 Secretion System in Pseudomonas aeruginosa

Type 3 secretion systems (T3SS) are complex nanomachines that span the cell envelope and play a central role in the biology of Gram-negative pathogens and symbionts. In Pseudomonas aeruginosa, T3SS expression is strongly associated with human disease severity and with mortality in murine acute pneumonia models. Uniform exposure of isogenic cells to T3SS-activating signal results in heterogeneous expression of this critical virulence trait. To understand the function of such diversity, we measured the production of the T3SS master regulator ExsA and the expression of T3SS genes using fluorescent reporters. We found that heterogeneous expression of ExsA in the absence of activating signal generates a "primed" subpopulation of cells that can rapidly induce T3SS gene expression in response to signal. T3SS expression is accompanied by a reproductive trade-off as measured by increased division time of T3SS-expressing cells. Although T3SS-primed cells are a minority of the population, they compose the majority of T3SS-expressing cells for several hours following activation. The primed state therefore allows P. aeruginosa to maximize reproductive fitness while maintaining the capacity to quickly express the T3SS. As T3SS effectors can serve as shared public goods for nonproducing cells, this division of labor benefits the population as a whole. IMPORTANCE The expression of specific virulence traits is strongly associated with Pseudomonas aeruginosa's success in establishing acute infections but is thought to carry a cost for bacteria. Producing multiprotein secretion systems or motility organelles is metabolically expensive and can target a cell for recognition by innate immune system receptors that recognize structural components of the type 3 secretion system (T3SS) or flagellum. These acute virulence factors are also negatively selected when P. aeruginosa establishes chronic infections in the lung. We demonstrate a regulatory mechanism by which only a minority subpopulation of genetically identical P. aeruginosa cells is "primed" to respond to signals that turn on T3SS expression. This phenotypic heterogeneity allows the population to maximize the benefit of rapid T3SS effector production while maintaining a rapidly growing and nonexpressing reservoir of cells that perpetuates this genotype within the population.

Waddington's Landscapes in the Bacterial World

Conrad Waddington’s epigenetic landscape, a visual metaphor for the development of multicellular organisms, is appropriate to depict the formation of phenotypic variants of bacterial cells. Examples of bacterial differentiation that result in morphological change have been known for decades. In addition, bacterial populations contain phenotypic cell variants that lack morphological change, and the advent of fluorescent protein technology and single-cell analysis has unveiled scores of examples. Cell-specific gene expression patterns can have a random origin or arise as a programmed event. When phenotypic cell-to-cell differences are heritable, bacterial lineages are formed. The mechanisms that transmit epigenetic states to daughter cells can have strikingly different levels of complexity, from the propagation of simple feedback loops to the formation of complex DNA methylation patterns. Game theory predicts that phenotypic heterogeneity can facilitate bacterial adaptation to hostile or unpredictable environments, serving either as a division of labor or as a bet hedging that anticipates future challenges. Experimental observation confirms the existence of both types of strategies in the bacterial world.

Transient Mitochondria Dysfunction Confers Fungal Cross-Resistance against Phagocytic Killing and Fluconazole

Loss or inactivation of antivirulence genes is an adaptive strategy in pathogen evolution. Candida glabrata is an important opportunistic pathogen related to baker’s yeast, with the ability to both quickly increase its intrinsic high level of azole resistance and persist within phagocytes. During C. glabrata’s evolution as a pathogen, the mitochondrial DNA polymerase CgMip1 has been under positive selection. We show that CgMIP1 deletion not only triggers loss of mitochondrial function and a petite phenotype, but increases C. glabrata’s azole and endoplasmic reticulum (ER) stress resistance and, importantly, its survival in phagocytes. The same phenotype is induced by fluconazole and by exposure to macrophages, conferring a cross-resistance between antifungals and immune cells, and can be found in clinical isolates despite a slow growth of petite strains. This suggests that petite constitutes a bet-hedging strategy of C. glabrata and, potentially, a relevant cause of azole resistance. Mitochondrial function may therefore be considered a potential antivirulence factor.

A rationally designed oral vaccine induces immunoglobulin A in the murine gut that directs the evolution of attenuated Salmonella variants

The ability of gut bacterial pathogens to escape immunity by antigenic variation-particularly via changes to surface-exposed antigens-is a major barrier to immune clearance¹. However, not all variants are equally fit in all environments^2,3. It should therefore be possible to exploit such immune escape mechanisms to direct an evolutionary trade-off. Here, we demonstrate this phenomenon using Salmonella enterica subspecies enterica serovar Typhimurium (S.Tm). A dominant surface antigen of S.Tm is its O-antigen: a long, repetitive glycan that can be rapidly varied by mutations in biosynthetic pathways or by phase variation^4,5. We quantified the selective advantage of O-antigen variants in the presence and absence of O-antigen-specific immunoglobulin A and identified a set of evolutionary trajectories allowing immune escape without an associated fitness cost in naive mice. Through the use of rationally designed oral vaccines, we induced immunoglobulin A responses blocking all of these trajectories. This selected for Salmonella mutants carrying deletions of the O-antigen polymerase gene wzyB. Due to their short O-antigen, these evolved mutants were more susceptible to environmental stressors (detergents or complement) and predation (bacteriophages) and were impaired in gut colonization and virulence in mice. Therefore, a rationally induced cocktail of intestinal antibodies can direct an evolutionary trade-off in S.Tm. This lays the foundations for the exploration of mucosal vaccines capable of setting evolutionary traps as a prophylactic strategy.

Bistability in cell signalling and its significance in identifying potential drug targets

MOTIVATION

Bistability is one of the salient dynamical features in various all-or-none kinds of decision-making processes. The presence of bistability in a cell signalling network plays a key role in input-output (I/O) relation. Our study is aiming to capture and emphasise the role of motif structure influencing the I/O relation between two nodes in the context of bistability. Here, a model-based analysis is made to investigate the critical conditions responsible for the emergence of different bistable protein-protein interaction (PPI) motifs and their possible applications to find the potential drug targets.

RESULTS

The global sensitivity analysis is used to identify sensitive parameters and their role in maintaining the bistability. Additionally, the bistable switching through hysteresis is explored to develop an understanding of the underlying mechanisms involved in the cell signalling processes, when significant motifs exhibiting bistability have emerged. Further, we elaborate the application of the results by the implication of the emerged PPI motifs to identify potential drug-targets in three cancer networks, which is validated with existing databases. The influence of stochastic perturbations that could hinder desired functionality of any signalling networks is also described here.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Ecology and evolution of antimicrobial resistance in bacterial communities

Accumulating evidence suggests that the response of bacteria to antibiotics is significantly affected by the presence of other interacting microbes. These interactions are not typically accounted for when determining pathogen sensitivity to antibiotics. In this perspective, we argue that resistance and evolutionary responses to antibiotic treatments should not be considered only a trait of an individual bacteria species but also an emergent property of the microbial community in which pathogens are embedded. We outline how interspecies interactions can affect the responses of individual species and communities to antibiotic treatment, and how these responses could affect the strength of selection, potentially changing the trajectory of resistance evolution. Finally, we identify key areas of future research which will allow for a more complete understanding of antibiotic resistance in bacterial communities. We emphasise that acknowledging the ecological context, i.e. the interactions that occur between pathogens and within communities, could help the development of more efficient and effective antibiotic treatments.

Single Cell Analysis of Bistable Expression of Pathogenicity Island 1 and the Flagellar Regulon in Salmonella enterica

Bistable expression of the Salmonella enterica pathogenicity island 1 (SPI-1) and the flagellar network (Flag) has been described previously. In this study, simultaneous monitoring of OFF and ON states in SPI-1 and in the flagellar regulon reveals independent switching, with concomitant formation of four subpopulations: SPI-1^OFF Flag^OFF, SPI-1^OFF Flag^ON, SPI-1^ON Flag^OFF, and SPI-1^ON Flag^ON. Invasion assays upon cell sorting show that none of the four subpopulations is highly invasive, thus raising the possibility that Flag^OFF cells might contribute to optimal invasion as previously proposed for SPI-1^OFF cells. Time lapse microscopy observation indicates that expression of the flagellar regulon contributes to the growth impairment previously described in SPI-1^ON cells. As a consequence, growth resumption in SPI-1^ON Flag^ON cells requires switching to both SPI-1^OFF and Flag^OFF states.

Adaptivity and dynamics in type III secretion systems

The type III secretion system is the common core of two bacterial molecular machines: the flagellum and the injectisome. The flagellum is the most widely distributed prokaryotic locomotion device, whereas the injectisome is a syringe-like apparatus for inter-kingdom protein translocation, which is essential for virulence in important human pathogens. The successful concept of the type III secretion system has been modified for different bacterial needs. It can be adapted to changing conditions, and was found to be a dynamic complex constantly exchanging components. In this review, we highlight the flexibility, adaptivity, and dynamic nature of the type III secretion system.

Synthetic gene-regulatory networks in the opportunistic human pathogen Streptococcus pneumoniae

Streptococcus pneumoniae is a major human pathogen responsible for enormous global morbidity and mortality. Despite this, the pneumococcus makes up part of the commensal nasopharyngeal flora. How the pneumococcus switches from this commensal to pathogenic state and causes disease is unclear and very likely involves variability in expression of its virulence factors. Here, we used synthetic biology approaches to generate complex gene-regulatory networks such as logic gates and toggle switches. We show that these networks are functional in vivo to control capsule production in an influenza-superinfection model. This opens the field of systematically testing the role of phenotypic variation in pneumococcal virulence. The approaches used here may serve as an example for synthetic biology projects in unrelated organisms.

Streptococcus pneumoniae can cause disease in various human tissues and organs, including the ear, the brain, the blood, and the lung, and thus in highly diverse and dynamic environments. It is challenging to study how pneumococci control virulence factor expression, because cues of natural environments and the presence of an immune system are difficult to simulate in vitro. Here, we apply synthetic biology methods to reverse-engineer gene expression control in S. pneumoniae. A selection platform is described that allows for straightforward identification of transcriptional regulatory elements out of combinatorial libraries. We present TetR- and LacI-regulated promoters that show expression ranges of four orders of magnitude. Based on these promoters, regulatory networks of higher complexity are assembled, such as logic AND gates and IMPLY gates. We demonstrate single-copy genome-integrated toggle switches that give rise to bimodal population distributions. The tools described here can be used to mimic complex expression patterns, such as the ones found for pneumococcal virulence factors. Indeed, we were able to rewire gene expression of the capsule operon, the main pneumococcal virulence factor, to be externally inducible (YES gate) or to act as an IMPLY gate (only expressed in absence of inducer). Importantly, we demonstrate that these synthetic gene-regulatory networks are functional in an influenza A virus superinfection murine model of pneumonia, paving the way for in vivo investigations of the importance of gene expression control on the pathogenicity of S. pneumoniae.

Subpopulations of Stressed Yersinia pseudotuberculosis Preferentially Survive Doxycycline Treatment within Host Tissues

Severe systemic bacterial infections result in colonization of deep tissues, which can be very difficult to eliminate with antibiotics. It remains unclear if this is because antibiotics are not reaching inhibitory concentrations within tissues, if subsets of bacteria are less susceptible to antibiotics, or if both contribute to limited treatment efficacy. To detect exposure to doxycycline (Dox) present in deep tissues following treatment, we generated a fluorescent transcriptional reporter derived from the tet operon to specifically detect intracellular tetracycline exposure at the single bacterial cell level. Dox exposure was detected in the spleen 2 h after intraperitoneal injection, and by 4 h postinjection, this treatment resulted in a significant decrease in viable Yersinia pseudotuberculosis bacteria in the spleen. Nitric oxide-stressed bacteria preferentially survived treatment, suggesting that stress was sufficient to alter Dox susceptibility. Many bacteria (∼10%) survived a single dose of Dox, and the antibiotic accumulated at the periphery of microcolonies to growth inhibitory concentrations until 48 h posttreatment. After this time point, antibiotic concentrations decreased and bacterial growth resumed. Dox-treated mice eventually succumbed to the infection, albeit with significantly prolonged survival relative to that of untreated mice. These results indicate that Dox delivery by intraperitoneal injection results in rapid diffusion of inhibitory concentrations of antibiotic into the spleen, but stressed cells preferentially survive drug treatment, and bacterial growth resumes once drug concentrations decrease. This fluorescent reporter strategy for antibiotic detection could easily be modified to detect the concentration of additional antimicrobial compounds within host tissues following drug administration.IMPORTANCE Bacterial infections are very difficult to treat when bacteria spread into the bloodstream and begin to replicate within deep tissues, such as the spleen. Subsets of bacteria can survive antibiotic treatment, but it remains unclear if this survival is because of limited drug diffusion into tissues, or if there are changes within the bacteria, promoting survival of some bacterial cells. Here, we have developed a fluorescent reporter to detect doxycycline (Dox) diffusion into host tissues, and we show that Dox impacts the bacterial population within hours of administration and inhibits bacterial growth for 48 h. However, bacterial growth resumes when antibiotic concentrations decrease. Subsets of bacteria, stressed by the host response to infection, survive Dox treatment at a higher rate. These results provide critical information about the dynamics that occur within deep tissues following antibiotic administration and suggest that subsets of bacteria are predisposed to survive inhibitory concentrations of antibiotic before exposure.

For the Greater (Bacterial) Good: Heterogeneous Expression of Energetically Costly Virulence Factors

Bacterial populations are phenotypically heterogeneous, which allows subsets of cells to survive and thrive following changes in environmental conditions. For bacterial pathogens, changes within the host environment occur over the course of the immune response to infection and can result in exposure to host-derived, secreted antimicrobials or force direct interactions with immune cells. Many recent studies have shown host cell interactions promote virulence factor expression, forcing subsets of bacterial cells to battle the host response, while other bacteria reap the benefits of this pacification. It still remains unclear whether virulence factor expression is truly energetically costly within host tissues and whether expression is sufficient to impact the growth kinetics of virulence factor-expressing cells. However, it is clear that slow-growing subsets of bacteria emerge during infection and that these subsets are particularly difficult to eliminate with antibiotics. This minireview will focus on our current understanding of heterogenous virulence factor expression and discuss the evidence that supports or refutes the hypothesis that virulence factor expression is linked to slowed growth and antibiotic tolerance.

Quantifying plasmid dynamics using single-cell microfluidics and image bioinformatics

Multicopy plasmids play an important role in bacterial ecology and evolution by accelerating the rate of adaptation and providing a platform for rapid gene amplification and evolutionary rescue. Despite the relevance of plasmids in bacterial evolutionary dynamics, evaluating the population-level consequences of randomly segregating and replicating plasmids in individual cells remains a challenging problem, both in theory and experimentally. In recent years, technological advances in fluorescence microscopy and microfluidics have allowed studying temporal changes in gene expression by quantifying the fluorescent intensity of individual cells under controlled environmental conditions. In this paper, we will describe the manufacture, experimental setup, and data analysis pipeline of different microfluidic systems that can be used to study plasmid dynamics, both in single-cells and in populations. To illustrate the benefits and limitations of microfluidics to study multicopy plasmid dynamics, we will use an experimental model system consisting on Escherichia coli K12 carrying non-conjugative, multicopy plasmids (19 copies per cell, in average) encoding different fluorescent markers and β-lactam resistance genes. First, we will use an image-based flow cytometer to estimate changes in the allele distribution of a heterogeneous population under different selection regimes. Then we will use a mothermachine microfluidic device to obtain time-series of fluorescent intensity of individual cells to argue that plasmid segregation and replication dynamics are inherently stochastic processes. Finally, using a microchemostat, we track thousands of cells in time to reconstruct bacterial lineages and evaluate the allele frequency distributions that emerge in response to a range of selective pressures.

Evolutionary causes and consequences of bacterial antibiotic persistence

Antibiotic treatment failure is of growing concern. Genetically encoded resistance is key in driving this process. However, there is increasing evidence that bacterial antibiotic persistence, a non-genetically encoded and reversible loss of antibiotic susceptibility, contributes to treatment failure and emergence of resistant strains as well. In this Review, we discuss the evolutionary forces that may drive the selection for antibiotic persistence. We review how some aspects of antibiotic persistence have been directly selected for whereas others result from indirect selection in disparate ecological contexts. We then discuss the consequences of antibiotic persistence on pathogen evolution. Persisters can facilitate the evolution of antibiotic resistance and virulence. Finally, we propose practical means to prevent persister formation and how this may help to slow down the evolution of virulence and resistance in pathogens.

Quantitation and Comparison of Phenotypic Heterogeneity Among Single Cells of Monoclonal Microbial Populations

Phenotypic heterogeneity within microbial populations arises even when the cells are exposed to putatively constant and homogeneous conditions. The outcome of this phenomenon can affect the whole function of the population, resulting in, for example, new "adapted" metabolic strategies and impacting its fitness at given environmental conditions. Accounting for phenotypic heterogeneity becomes thus necessary, due to its relevance in medical and applied microbiology as well as in environmental processes. Still, a comprehensive evaluation of this phenomenon requires a common and unique method of quantitation, which allows for the comparison between different studies carried out with different approaches. Consequently, in this study, two widely applicable indices for quantitation of heterogeneity were developed. The heterogeneity coefficient (HC) is valid when the population follows unimodal activity, while the differentiation tendency index (DTI) accounts for heterogeneity implying outbreak of subpopulations and multimodal activity. We demonstrated the applicability of HC and DTI for heterogeneity quantitation on stable isotope probing with nanoscale secondary ion mass spectrometry (SIP-nanoSIMS), flow cytometry, and optical microscopy datasets. The HC was found to provide a more accurate and precise measure of heterogeneity, being at the same time consistent with the coefficient of variation (CV) applied so far. The DTI is able to describe the differentiation in single-cell activity within monoclonal populations resolving subpopulations with low cell abundance, individual cells with similar phenotypic features (e.g., isotopic content close to natural abundance, as detected with nanoSIMS). The developed quantitation approach allows for a better understanding on the impact and the implications of phenotypic heterogeneity in environmental, medical and applied microbiology, microbial ecology, cell biology, and biotechnology.

Emergent microscale gradients give rise to metabolic cross-feeding and antibiotic tolerance in clonal bacterial populations

Bacteria often live in spatially structured groups such as biofilms. In these groups, cells can collectively generate gradients through the uptake and release of compounds. In turn, individual cells adapt their activities to the environment shaped by the whole group. Here, we studied how these processes can generate phenotypic variation in clonal populations and how this variation contributes to the resilience of the population to antibiotics. We grew two-dimensional populations of Escherichia coli in microfluidic chambers where limiting amounts of glucose were supplied from one side. We found that the collective metabolic activity of cells created microscale gradients where nutrient concentration varied over a few cell lengths. As a result, growth rates and gene expression levels varied strongly between neighbouring cells. Furthermore, we found evidence for a metabolic cross-feeding interaction between glucose-fermenting and acetate-respiring subpopulations. Finally, we found that subpopulations of cells were able to survive an antibiotic pulse that was lethal in well-mixed conditions, likely due to the presence of a slow-growing subpopulation. Our work shows that emergent metabolic gradients can have important consequences for the functionality of bacterial populations as they create opportunities for metabolic interactions and increase the populations' tolerance to environmental stressors. This article is part of a discussion meeting issue 'Single cell ecology'.

Multisite phosphorylation drives phenotypic variation in (p)ppGpp synthetase-dependent antibiotic tolerance

Isogenic populations of cells exhibit phenotypic variability that has specific physiological consequences. Individual bacteria within a population can differ in antibiotic tolerance, but whether this variability can be regulated or is generally an unavoidable consequence of stochastic fluctuations is unclear. Here we report that a gene encoding a bacterial (p)ppGpp synthetase in Bacillus subtilis, sasA, exhibits high levels of extrinsic noise in expression. We find that sasA is regulated by multisite phosphorylation of the transcription factor WalR, mediated by a Ser/Thr kinase-phosphatase pair PrkC/PrpC, and a Histidine kinase WalK of a two-component system. This regulatory intersection is crucial for controlling the appearance of outliers; rare cells with unusually high levels of sasA expression, having increased antibiotic tolerance. We create a predictive model demonstrating that the probability of a given cell surviving antibiotic treatment increases with sasA expression. Therefore, multisite phosphorylation can be used to strongly regulate variability in antibiotic tolerance.

Diffusion-driven enhancement of the antibiotic resistance selection window

The current crisis of antimicrobial resistance in clinically relevant pathogens has highlighted our limited understanding of the ecological and evolutionary forces that drive drug resistance adaptation. For instance, although human tissues are highly heterogeneous, most of our mechanistic understanding about antibiotic resistance evolution is based on constant and well-mixed environmental conditions. A consequence of considering spatial heterogeneity is that, even if antibiotics are prescribed at high dosages, the penetration of drug molecules through tissues inevitably produces antibiotic gradients, exposing bacterial populations to a range of selective pressures and generating a dynamic fitness landscape that changes in space and time. In this paper, we will use a combination of mathematical modelling and computer simulations to study the population dynamics of susceptible and resistant strains competing for resources in a network of micro-environments with varying degrees of connectivity. Our main result is that highly connected environments increase diffusion of drug molecules, enabling resistant phenotypes to colonize a larger number of spatial locations. We validated this theoretical result by culturing fluorescently labelled Escherichia coli in 3D-printed devices that allow us to control the rate of diffusion of antibiotics between neighbouring compartments and quantify the spatio-temporal distribution of resistant and susceptible bacterial cells.

Synergistic action of SPI-1 gene expression in Salmonella enterica serovar typhimurium through transcriptional crosstalk with the flagellar system

BACKGROUND

Salmonella enterica serovar Typhimurium is a common food-borne pathogen. S. enterica uses a type III secretion system encoded within Salmonella pathogenicity island 1 (SPI-1) to invade intestinal epithelial cells. A complex network of interacting transcription factors regulates SPI-1 gene expression. In addition, SPI-1 gene expression is coupled to flagellar gene expression. Both SPI-1 and flagellar gene expression are bistable, with co-existing populations of cells expressing and not expressing these genes. Previous work demonstrated that nutrients could be used to tune the fraction of cells expressing the flagellar genes. In the present study, we tested whether nutrients could also tune the fraction of cells expressing the SPI-1 genes through transcriptional crosstalk with the flagellar genes.

RESULTS

Nutrients alone were not found to induce SPI-1 gene expression. However, when the cells were also grown in the presence of acetate, the concentration of nutrients in the growth medium was able to tune the fraction of cells expressing the SPI-1 genes. During growth in nutrient-poor medium, acetate alone was unable to induce SPI-1 gene expression. These results demonstrate that acetate and nutrients synergistically activate SPI-1 gene expression. The response to acetate was governed by the BarA/SirA two-component system and the response to nutrients was governed by transcriptional crosstalk with the flagella system, specifically through the action of the flagellar regulator FliZ.

CONCLUSIONS

Acetate and nutrients are capable of synergistically activating SPI-1 gene expression. In addition, these signals were found to tune the fraction of cells expressing the SPI-1 genes. The governing mechanism involves transcriptional crosstalk with the flagellar gene network. Collectively, these results further our understanding of SPI-1 gene regulation and provide the basis for future studies investigating this complex regulatory mechanism.

MMHelper: An automated framework for the analysis of microscopy images acquired with the mother machine

Live-cell imaging in microfluidic devices now allows the investigation of cellular heterogeneity within microbial populations. In particular, the mother machine technology developed by Wang et al. has been widely employed to investigate single-cell physiological parameters including gene expression, growth rate, mutagenesis, and response to antibiotics. One of the advantages of the mother machine technology is the ability to generate vast amounts of images; however, the time consuming analysis of these images constitutes a severe bottleneck. Here we overcome this limitation by introducing MMHelper ( https://doi.org/10.5281/zenodo.3254394 ), a publicly available custom software implemented in Python which allows the automated analysis of brightfield or phase contrast, and any associated fluorescence, images of bacteria confined in the mother machine. We show that cell data extracted via MMHelper from tens of thousands of individual cells imaged in brightfield are consistent with results obtained via semi-automated image analysis based on ImageJ. Furthermore, we benchmark our software capability in processing phase contrast images from other laboratories against other publicly available software. We demonstrate that MMHelper has over 90% detection efficiency for brightfield and phase contrast images and provides a new open-source platform for the extraction of single-bacterium data, including cell length, area, and fluorescence intensity.

Spontaneous mutations in a regulatory gene induce phenotypic heterogeneity and adaptation of Ralstonia solanacearum to changing environments

An evolution experiment with the bacterial plant pathogen Ralstonia solanacearum revealed that several adaptive mutations conferring enhanced fitness in plants arose in the efpR gene encoding a regulator of virulence and metabolic functions. In this study, we found that an efpR mutant systematically displays colonies with two morphotypes: the type S ('smooth', similar to the wild type) and the type EV ('efpR variant'). We demonstrated that the efpH gene, a homologue of efpR, plays a key role in the control of phenotypic heterogeneity, the ΔefpR-ΔefpH double mutant being stably locked into the EV type. Using mixed infection assays, we demonstrated that the type EV is metabolically more proficient than the type S and displays fitness gain in specific environments, whereas the type S has a better fitness into the plant environment. We provide evidence that this efpR-dependent phenotypic heterogeneity is a general feature of strains of the R. solanacearum species complex and could occur in natural conditions. This study highlights the potential role of phenotypic heterogeneity in this plant pathogen as an adaptive trait to changing environments.

Evolutionary Stability of Salmonella Competition with the Gut Microbiota: How the Environment Fosters Heterogeneity in Exploitative and Interference Competition

Following ingestion, gastrointestinal pathogens compete against the gastrointestinal microbiota and overcome host immune defenses in order to cause infections. Besides employing direct killing mechanisms, the commensal microbiota occupies metabolic niches to outcompete invading pathogens. Salmonella enterica serovar Typhimurium (S. Typhimurium) uses several strategies to successfully colonize the gut and establish infection, of which an increasing number is based on phenotypic heterogeneity within the S. Typhimurium population. The utilization of myo-inositol (MI) and the production of colicin confer a selective advantage over the microbiota in terms of exploitative and interference competition, respectively. In this review, we summarize the genetic basis underlying bistability of MI catabolism and colicin production. As demonstrated by single-cell analyses, a stochastic switch in the expression of the genes responsible for colicin production and MI degradation constitutes the heterogeneity of the two phenotypes. Both genetic systems are tightly regulated to avoid their expression under non-appropriate conditions and possible detrimental effects on bacterial fitness. Moreover, evolutionary mechanisms underlying formation and stability of these phenotypes in S. Typhimurium are discussed. We propose that both MI catabolism and colicin production create a bet-hedging strategy, which provides an adaptive benefit for S. Typhimurium in the fluctuating environment of the mammalian gut.

Cell Heterogeneity in Staphylococcal Communities

The human pathogen Staphylococcus aureus is a gram-positive bacterium that causes difficult-to-treat infections. One of the reasons why S. aureus is such as successful pathogen is due to the cell-to-cell physiological variability that exists within microbial communities. Many laboratories around the world study the genetic mechanisms involved in S. aureus cell heterogeneity to better understand infection mechanism of this bacterium. It was recently shown that the Agr quorum-sensing system, which antagonistically regulates biofilm-associated or acute bacteremia infections, is expressed in a subpopulation of specialized cells. In this review, we discuss the different genetic mechanism for bacterial cell differentiation and the physiological properties of the distinct cell types that are already described in S. aureus communities, as well as the role that these cell types play during an infection process.

Single cell, super-resolution imaging reveals an acid pH-dependent conformational switch in SsrB regulates SPI-2

After Salmonella is phagocytosed, it resides in an acidic vacuole. Its cytoplasm acidifies to pH 5.6; acidification activates pathogenicity island 2 (SPI-2). SPI-2 encodes a type three secretion system whose effectors modify the vacuole, driving endosomal tubulation. Using super-resolution imaging in single bacterial cells, we show that low pH induces expression of the SPI-2 SsrA/B signaling system. Single particle tracking, atomic force microscopy, and single molecule unzipping assays identified pH-dependent stimulation of DNA binding by SsrB. A so-called phosphomimetic form (D56E) was unable to bind to DNA in live cells. Acid-dependent DNA binding was not intrinsic to regulators, as PhoP and OmpR binding was not pH-sensitive. The low level of SPI-2 injectisomes observed in single cells is not due to fluctuating SsrB levels. This work highlights the surprising role that acid pH plays in virulence and intracellular lifestyles of Salmonella; modifying acid survival pathways represents a target for inhibiting Salmonella.

Mutational and non mutational adaptation of Salmonella enterica to the gall bladder

During systemic infection of susceptible hosts, Salmonella enterica colonizes the gall bladder, which contains lethal concentrations of bile salts. Recovery of Salmonella cells from the gall bladder of infected mice yields two types of isolates: (i) bile-resistant mutants; (ii) isolates that survive lethal selection without mutation. Bile-resistant mutants are recovered at frequencies high enough to suggest that increased mutation rates may occur in the gall bladder, thus providing a tentative example of stress-induced mutation in a natural environment. However, most bile-resistant mutants characterized in this study show defects in traits that are relevant for Salmonella colonization of the animal host. Mutation may thus permit short-term adaptation to the gall bladder at the expense of losing fitness for transmission to new hosts. In contrast, non mutational adaptation may have evolved as a fitness-preserving strategy. Failure of RpoS⁻ mutants to colonize the gall bladder supports the involvement of the general stress response in non mutational adaptation.

Stress-induced protein aggregates shape population heterogeneity in bacteria

The concept of phenotypic heterogeneity preparing a subpopulation of isogenic cells to better cope with anticipated stresses has been well established. However, less is known about how stress itself can drive subsequent cellular individualization in clonal populations. In this perspective, we focus on the impact of stress-induced cellular protein aggregates, and how their segregation and disaggregation can act as a deterministic incentive for heterogeneity in the population emerging from a stressed ancestor.

Evolutionary ecology meets the antibiotic crisis: Can we control pathogen adaptation through sequential therapy?

The spread of antibiotic resistance is a global challenge that is fueled by evolution and ecological processes. Therefore, the design of new sustainable therapy should take account of these underlying processes—as proposed within the field of evolutionary medicine, yet usually not receiving the necessary attention from national and international health agencies. We here put the spotlight on a currently neglected treatment strategy: sequential therapy. Changes among antibiotics generate fluctuating selection conditions that are in general difficult to counter by any organism. We argue that sequential treatment designs can be specifically optimized by exploiting evolutionary trade-offs, for example collateral sensitivity and/or inducible physiological constraints, such as negative hysteresis, where pre-exposure to one antibiotic induces temporary hyper-sensitivity to another antibiotic. Our commentary provides an overview of sequential treatment strategies and outlines steps towards their further optimization.

The Role of the Host in Driving Phenotypic Heterogeneity in Salmonella

The complex infection environment within hosts exerts unique stresses across tissues and cell types, selecting for phenotypic heterogeneity in bacterial populations. Pathogens maintain variability during infection as a strategy to cope with fluctuating host immune conditions, leading to diversification of virulence phenotypes. Recent improvements in single-cell analyses have revealed that distinct bacterial subpopulations contribute unique colonization and growth strategies across infection sites. We discuss several examples of host-driven phenotypic heterogeneity in Salmonella populations throughout the course of infection, highlighting how variation in gene expression, growth rate, immune evasion, and metabolic activity contribute to overall bacterial success at the population level. We additionally focus our discussion on the implications of diversity within bacterial communities for antimicrobial efficacy.

Relapse of typhoid fever following delayed response to meropenem: A case report and review of previously published cases indicating limited clinical efficacy of meropenem for the treatment of typhoid fever

In times of emerging multi-drug resistance among Gram-negative bacteria (including Salmonella enterica, Serovar Typhi), we observed relapse of typhoid fever following delayed response to treatment with meropenem, suggestive for limited clinical efficacy of the drug. Three previously published cases supported our suspicion. Within this context, we discuss the case details with a focus on potential explanations for insufficient clinical response to meropenem (e.g. limited intracellular penetration, phenomena of tolerance and persistence). Meropenem is a last-resort antimicrobial agent for the treatment of multi-drug resistant Gram-negative infections. Reliable clinical data evaluating the efficacy of meropenem for the treatment of typhoid fever are urgently needed. Future clinical studies evaluating typhoid fever outcome should also investigate the impact of (i) intracellular penetration of antibiotics, and (ii) tolerance and persistence on outcome.

Bacterial growth: a statistical physicist's guide

Bacterial growth presents many beautiful phenomena that pose new theoretical challenges to statistical physicists, and are also amenable to laboratory experimentation. This review provides some of the essential biological background, discusses recent applications of statistical physics in this field, and highlights the potential for future research.

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.

Contribution of SPI-1 bistability to Salmonella enterica cooperative virulence: insights from single cell analysis

Salmonella enterica pathogenicity island 1 (SPI-1) is a gene cluster that encodes a type III secretion system and effectors involved in epithelial cell invasion. SPI-1 undergoes bistable expression, with concomitant formation of SPI-1^ON and SPI-1^OFF lineages. This study describes single cell analysis of SP1-1 bistability and epithelial cell invasion, and reports the unsuspected observation that optimal invasion of epithelial cells requires the presence of both SPI-1^ON and SPI-1^OFF subpopulations. The contribution of SPI-1^OFF cells to optimal invasion may rely on their ability to invade epithelial cells if a SPI-1^ON subpopulation is present. In fact, Salmonella SPI-1 mutants are also able to invade epithelial cells in the presence of SPI-1^ONSalmonellae, a phenomenon described in the 1990’s by Galán and co-workers. Invasion by SPI-1^OFF cells does not seem to involve a diffusible factor. A small number of SPI-1^ON cells is sufficient to endow the bacterial population with invasion capacity, a feature that may permit host colonization regardless of the bottlenecks encountered by Salmonella populations inside animals.

Bimodal Expression of the Salmonella Typhimurium spv Operon

The well-studied spv operon of Salmonellatyphimurium is important for causing full virulence in mice and both the regulation and function of the Spv proteins have been characterized extensively over the past several decades. Using quantitative single-cell fluorescence microscopy, we demonstrate the spv regulon to display a bimodal expression pattern that originates in the bimodal expression of the SpvR activator. The spv expression pattern is influenced by growth conditions and the specific Styphimurium strain used, but does not require Salmonella-specific virulence regulators. By monitoring real-time promoter kinetics, we reveal that SpvA has the ability to impart negative feedback on spvABCD expression without affecting spvR expression. Together, our data suggest that the SpvA protein counteracts the positive feedback loop imposed by SpvR, and could thus be responsible for dampening spvABCD expression and coordinating virulence protein production in time. The results presented here yield new insights in the intriguing regulation of the spv operon and adds this operon to the growing list of virulence factors exhibiting marked expression heterogeneity in Styphimurium.

One for All, but Not All for One: Social Behavior during Bacterial Diseases

It has been known for decades that individual cells within pathogenic bacterial populations have reduced antibiotic susceptibility, which is linked to decreased metabolic rates. A similar phenomenon occurs with virulence-associated proteins, as reduced expression is associated with increased fitness of individual cells. Non-producers within the population can benefit from the virulence proteins produced by others in the population without suffering a fitness cost, thus maintaining a genetically uniform population. Cooperative behavior has been reported for Salmonella and Yersinia, consistent with selection of social behavior to retain genes associated with pathogenesis; however, cooperation was unclear within Mycobacterium populations. This review focuses on these recent descriptions of cooperation, discusses the mechanisms driving heterogeneity, and evaluates the evidence that expression of virulence-associated proteins comes at a fitness cost.

The Culture Environment Influences Both Gene Regulation and Phenotypic Heterogeneity in Escherichia coli

Microorganisms shape the composition of the medium they are growing in, which in turn has profound consequences on the reprogramming of the population gene-expression profile. In this paper, we investigate the progressive changes in pH and sugar availability in the medium of a growing Escherichia coli (E. coli) culture. We show how these changes have an effect on both the cellular heterogeneity within the microbial community and the gene-expression profile of the microbial population. We measure the changes in gene-expression as E. coli moves from lag, to exponential, and finally into stationary phase. We found that pathways linked to the changes in the medium composition such as ribosomal, tricarboxylic acid cycle (TCA), transport, and metabolism pathways are strongly regulated during the different growth phases. In order to quantify the corresponding temporal changes in the population heterogeneity, we measure the fraction of E. coli persisters surviving different antibiotic treatments during the various phases of growth. We show that the composition of the medium in which β-lactams or quinolones, but not aminoglycosides, are dissolved strongly affects the measured phenotypic heterogeneity within the culture. Our findings contribute to a better understanding on how the composition of the culture medium influences both the reprogramming in the population gene-expression and the emergence of phenotypic variants.

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.

Fundamental principles in bacterial physiology-history, recent progress, and the future with focus on cell size control: a review

Bacterial physiology is a branch of biology that aims to understand overarching principles of cellular reproduction. Many important issues in bacterial physiology are inherently quantitative, and major contributors to the field have often brought together tools and ways of thinking from multiple disciplines. This article presents a comprehensive overview of major ideas and approaches developed since the early 20th century for anyone who is interested in the fundamental problems in bacterial physiology. This article is divided into two parts. In the first part (sections 1-3), we review the first 'golden era' of bacterial physiology from the 1940s to early 1970s and provide a complete list of major references from that period. In the second part (sections 4-7), we explain how the pioneering work from the first golden era has influenced various rediscoveries of general quantitative principles and significant further development in modern bacterial physiology. Specifically, section 4 presents the history and current progress of the 'adder' principle of cell size homeostasis. Section 5 discusses the implications of coarse-graining the cellular protein composition, and how the coarse-grained proteome 'sectors' re-balance under different growth conditions. Section 6 focuses on physiological invariants, and explains how they are the key to understanding the coordination between growth and the cell cycle underlying cell size control in steady-state growth. Section 7 overviews how the temporal organization of all the internal processes enables balanced growth. In the final section 8, we conclude by discussing the remaining challenges for the future in the field.

Substrate and electron donor limitation induce phenotypic heterogeneity in different metabolic activities in a green sulphur bacterium

Populations of genetically identical cells can display marked variation in phenotypic traits; such variation is termed phenotypic heterogeneity. Here, we investigate the effect of substrate and electron donor limitation on phenotypic heterogeneity in N₂ and CO₂ fixation in the green sulphur bacterium Chlorobium phaeobacteroides. We grew populations in chemostats and batch cultures and used stable isotope labelling combined with nanometer-scale secondary ion mass spectrometry (NanoSIMS) to quantify phenotypic heterogeneity. Experiments in H₂ S (i.e. electron donor) limited chemostats show that varying levels of NH4+ limitation induce heterogeneity in N₂ fixation. Comparison of phenotypic heterogeneity between chemostats and batch (unlimited for H₂ S) populations indicates that electron donor limitation drives heterogeneity in N₂ and CO₂ fixation. Our results demonstrate that phenotypic heterogeneity in a certain metabolic activity can be driven by different modes of limitation and that heterogeneity can emerge in different metabolic processes upon the same mode of limitation. In conclusion, our data suggest that limitation is a general driver of phenotypic heterogeneity in microbial populations.

Bistability and phase variation in Salmonella enterica

Cell-to-cell differences in bacterial gene expression can merely reflect the occurrence of noise. In certain cases, however, heterogeneous gene expression is a programmed event that results in bistable expression. If bistability is heritable, bacterial lineages are formed. When programmed bistability is reversible, the phenomenon is known as phase variation. In certain cases, bistability is controlled by genetic mechanisms (e. g., DNA rearrangement). In other cases, bistability has epigenetic origin. A robust epigenetic mechanism for the formation of bacterial lineages is the formation of heritable DNA methylation patterns. However, bistability can also arise upon propagation of gene expression patterns by feedback loops that are stable upon cell division. This review describes examples of bistability and phase variation in Salmonella enterica and discusses their adaptive value, sometimes in a speculative manner.