Individuality in bacteria

TOR regulates variability of protein synthesis rates

Cellular processes are subject to inherent variability, but the extent to which cells can regulate this variability has received little investigation. Here, we explore the characteristics of the rate of cellular protein synthesis in single cells of the eukaryote fission yeast. Strikingly, this rate is highly variable despite protein synthesis being dependent on hundreds of reactions which might be expected to average out at the overall cellular level. The rate is variable over short time scales, and exhibits homoeostatic behaviour at the population level. Cells can regulate the level of variability through processes involving the TOR pathway, suggesting there is an optimal level of variability conferring a selective advantage. While this could be an example of bet-hedging, but we propose an alternative explanation: regulated 'loose' control of complex processes of overall cellular metabolism such as protein synthesis, may lead to this variability. This could ensure cells are fluid in control and agile in response to changing conditions, and may constitute a novel organisational principle of complex metabolic cellular systems.

Spectral analysis and sorting of microbial organisms using a spectral sorter

This chapter discusses the problems related to the application of conventional flow cytometers to microbiology. To address some of those limitations, the concept of spectral flow cytometry is introduced and the advantages over conventional flow cytometry for bacterial sorting are presented. We demonstrate by using ThermoFisher's Bigfoot spectral sorter where the spectral signatures of different stains for staining bacteria are demonstrated with an example of performing unmixing on spectral datasets. In addition to the Bigfoot's spectral analysis, the special biosafety features of this instrument are discussed. Utilizing these biosafety features, the sorting and patterning at the single cell level is optimized using non-pathogenic bacteria. Finally, the chapter is concluded by presenting a novel, label free, non-destructive, and rapid phenotypic method called Elastic Light Scattering (ELS) technology for identification of the patterned bacterial cells based on their unique colony scatter patterns.

Emerging tools for uncovering genetic and transcriptomic heterogeneities in bacteria

Bacterial communities display an astonishing degree of heterogeneities among their constituent cells across both the genomic and transcriptomic levels, giving rise to diverse social interactions and stress-adaptation strategies indispensable for proliferating in the natural environment (Ackermann in Nat Rev Microbiol 13:497-508, 2015). Our knowledge about bacterial heterogeneities and their physiological ramifications critically depends on our ability to unambiguously resolve the genetic and phenotypic states of the individual cells that make up the population. In this short review, I highlight several recently developed methods for studying bacterial heterogeneities, primarily focusing on single-cell techniques based on advanced sequencing and microscopy technologies. I will discuss the working principle of each technique as well as the types of problems each technique is best positioned to address. With significant improvements in resolution and throughput, these emerging tools together offer unprecedented and complementary views of various types of heterogeneities found within bacterial populations, paving the way for mechanistic dissections and systematic interventions in laboratory and clinical settings.

Hierarchical network structure as the source of hierarchical dynamics (power-law frequency spectra) in living and non-living systems: How state-trait continua (body plans, personalities) emerge from first principles in biophysics

Living systems are hierarchical control systems that display a small world network structure. In such structures, many smaller clusters are nested within fewer larger ones, producing a fractal-like structure with a 'power-law' cluster size distribution (a mereology). Just like their structure, the dynamics of living systems shows fractal-like qualities: the timeseries of inner message passing and overt behavior contain high frequencies or 'states' (treble) that are nested within lower frequencies or 'traits' (bass), producing a power-law frequency spectrum that is known as a 'state-trait continuum' in the behavioral sciences. Here, we argue that the power-law dynamics of living systems results from their power-law network structure: organisms 'vertically encode' the deep spatiotemporal structure of their (anticipated) environments, to the effect that many small clusters near the base of the hierarchy produce high frequency signal changes and fewer larger clusters at its top produce ultra-low frequencies. Such ultra-low frequencies exert a tonic regulatory pressure that produces morphological as well as behavioral traits (i.e., body plans and personalities). Nested-modular structure causes higher frequencies to be embedded within lower frequencies, producing a power-law state-trait continuum. At the heart of such dynamics lies the need for efficient energy dissipation through networks of coupled oscillators, which also governs the dynamics of non-living systems (e.q., earthquakes, stock market fluctuations). Since hierarchical structure produces hierarchical dynamics, the development and collapse of hierarchical structure (e.g., during maturation and disease) should leave specific traces in system dynamics (shifts in lower frequencies, i.e. morphological and behavioral traits) that may serve as early warning signs to system failure. The applications of this idea range from (bio)physics and phylogenesis to ontogenesis and clinical medicine.

A trailing ribosome speeds up RNA polymerase at the expense of transcript fidelity via force and allostery

In prokaryotes, translation can occur on mRNA that is being transcribed in a process called coupling. How the ribosome affects the RNA polymerase (RNAP) during coupling is not well understood. Here, we reconstituted the E. coli coupling system and demonstrated that the ribosome can prevent pausing and termination of RNAP and double the overall transcription rate at the expense of fidelity. Moreover, we monitored single RNAPs coupled to ribosomes and show that coupling increases the pause-free velocity of the polymerase and that a mechanical assisting force is sufficient to explain the majority of the effects of coupling. Also, by cryo-EM, we observed that RNAPs with a terminal mismatch adopt a backtracked conformation, while a coupled ribosome allosterically induces these polymerases toward a catalytically active anti-swiveled state. Finally, we demonstrate that prolonged RNAP pausing is detrimental to cell viability, which could be prevented by polymerase reactivation through a coupled ribosome.

Mass spectrometry imaging to explore molecular heterogeneity in cell culture

Molecular analysis on the single-cell level represents a rapidly growing field in the life sciences. While bulk analysis from a pool of cells provides a general molecular profile, it is blind to heterogeneities between individual cells. This heterogeneity, however, is an inherent property of every cell population. Its analysis is fundamental to understanding the development, function, and role of specific cells of the same genotype that display different phenotypical properties. Single-cell mass spectrometry (MS) aims to provide broad molecular information for a significantly large number of cells to help decipher cellular heterogeneity using statistical analysis. Here, we present a sensitive approach to single-cell MS based on high-resolution MALDI-2-MS imaging in combination with MALDI-compatible staining and use of optical microscopy. Our approach allowed analyzing large amounts of unperturbed cells directly from the growth chamber. Confident coregistration of both modalities enabled a reliable compilation of single-cell mass spectra and a straightforward inclusion of optical as well as mass spectrometric features in the interpretation of data. The resulting multimodal datasets permit the use of various statistical methods like machine learning-driven classification and multivariate analysis based on molecular profile and establish a direct connection of MS data with microscopy information of individual cells. Displaying data in the form of histograms for individual signal intensities helps to investigate heterogeneous expression of specific lipids within the cell culture and to identify subpopulations intuitively. Ultimately, t-MALDI-2-MSI measurements at 2-µm pixel sizes deliver a glimpse of intracellular lipid distributions and reveal molecular profiles for subcellular domains.

Antiactivators prevent self-sensing in Pseudomonas aeruginosa quorum sensing

Quorum sensing is described as a widespread cell density-dependent signaling mechanism in bacteria. Groups of cells coordinate gene expression by secreting and responding to diffusible signal molecules. Theory, however, predicts that individual cells may short-circuit this mechanism by directly responding to the signals they produce irrespective of cell density. In this study, we characterize this self-sensing effect in the acyl-homoserine lactone quorum sensing system of Pseudomonas aeruginosa. We show that antiactivators, a set of proteins known to affect signal sensitivity, function to prevent self-sensing. Measuring quorum-sensing gene expression in individual cells at very low densities, we find that successive deletion of antiactivator genes qteE and qslA produces a bimodal response pattern, in which increasing proportions of constitutively induced cells coexist with uninduced cells. Comparing responses of signal-proficient and -deficient cells in cocultures, we find that signal-proficient cells show a much higher response in the antiactivator mutant background but not in the wild-type background. Our results experimentally demonstrate the antiactivator-dependent transition from group- to self-sensing in the quorum-sensing circuitry of P. aeruginosa. Taken together, these findings extend our understanding of the functional capacity of quorum sensing. They highlight the functional significance of antiactivators in the maintenance of group-level signaling and experimentally prove long-standing theoretical predictions.

High-throughput sequencing analysis reveals genomic similarity in phenotypic heterogeneous Photorhabdus luminescens cell populations

Purpose

Phenotypic heterogeneity occurs in many bacterial populations: single cells of the same species display different phenotypes, despite being genetically identical. The Gram-negative entomopathogenic bacterium Photorhabdus luminescens is an excellent example to investigate bacterial phenotypic heterogeneity. Its dualistic life cycle includes a symbiotic stage interacting with entomopathogenic nematodes (EPNs) and a pathogenic stage killing insect larvae. P. luminescens appears in two phenotypically different cell forms: the primary (1°) and the secondary (2°) cell variants. While 1° cells are bioluminescent, pigmented, and produce a huge set of secondary metabolites, 2° cells lack all these phenotypes. The main difference between both phenotypic variants is that only 1° cells can undergo symbiosis with EPNs, a phenotype that is absent from 2° cells. Recent comparative transcriptome analysis revealed that genes mediating 1° cell-specific traits are modulated differently in 2° cells. Although it was previously suggested that heterogeneity in P. luminescens cells cultures is not genetically mediated by, e.g., larger rearrangements in the genome, the genetic similarity of both cell variants has not clearly been demonstrated yet.

Methods

Here, we analyzed the genomes of both 1° and 2° cells by genome sequencing of each six single 1° and 2° clones that emerged from a single 1° clone after prolonged growth. Using different bioinformatics tools, the sequence data were analyzed for clustered point mutations or genetic rearrangements with respect to the respective phenotypic variant.

Result

We demonstrate that isolated clones of 2° cells that switched from the 1° cell state do not display any noticeable mutation and do not genetically differ from 1° cells.

Conclusion

In summary, we show that the phenotypic differences in P. luminescens cell cultures are obviously not caused by mutations or genetic rearrangements in the genome but truly emerge from phenotypic heterogeneity.

The evolution of mechanisms to produce phenotypic heterogeneity in microorganisms

In bacteria and other microorganisms, the cells within a population often show extreme phenotypic variation. Different species use different mechanisms to determine how distinct phenotypes are allocated between individuals, including coordinated, random, and genetic determination. However, it is not clear if this diversity in mechanisms is adaptive-arising because different mechanisms are favoured in different environments-or is merely the result of non-adaptive artifacts of evolution. We use theoretical models to analyse the relative advantages of the two dominant mechanisms to divide labour between reproductives and helpers in microorganisms. We show that coordinated specialisation is more likely to evolve over random specialisation in well-mixed groups when: (i) social groups are small; (ii) helping is more "essential"; and (iii) there is a low metabolic cost to coordination. We find analogous results when we allow for spatial structure with a more detailed model of cellular filaments. More generally, this work shows how diversity in the mechanisms to produce phenotypic heterogeneity could have arisen as adaptations to different environments.

Behavior Individuality: A Focus on Drosophila melanogaster

Among individuals, behavioral differences result from the well-known interplay of nature and nurture. Minute differences in the genetic code can lead to differential gene expression and function, dramatically affecting developmental processes and adult behavior. Environmental factors, epigenetic modifications, and gene expression and function are responsible for generating stochastic behaviors. In the last decade, the advent of high-throughput sequencing has facilitated studying the genetic basis of behavior and individuality. We can now study the genomes of multiple individuals and infer which genetic variations might be responsible for the observed behavior. In addition, the development of high-throughput behavioral paradigms, where multiple isogenic animals can be analyzed in various environmental conditions, has again facilitated the study of the influence of genetic and environmental variations in animal personality. Mainly, Drosophila melanogaster has been the focus of a great effort to understand how inter-individual behavioral differences emerge. The possibility of using large numbers of animals, isogenic populations, and the possibility of modifying neuronal function has made it an ideal model to search for the origins of individuality. In the present review, we will focus on the recent findings that try to shed light on the emergence of individuality with a particular interest in D. melanogaster.

Phenotypic Variants of Bacterial Colonies in Microbiological Diagnostics: How Often Are They Indicative of Differing Antimicrobial Susceptibility Patterns?

Phenotypic variants (PV) are colonies of the same species in the same specimen with different morphological features. It is controversial whether antimicrobial susceptibility testing (AST) should be done for all PV. The objectives of this study were to quantify the proportion of differing antimicrobial susceptibility patterns (dASP) among PV and to identify species and antimicrobial compounds that are mostly affected. All PV from routine diagnostics (University Hospital Münster, Germany; 1 September 2019 to 31 August 2020) were subjected to species identification (matrix-assisted laser desorption ionization-time of flight mass spectrometry [MALDI-TOF MS]) and AST (Vitek 2). To assess the dASP, only antimicrobial agents were considered for which Vitek-derived MIC were available (interpreted according to the EUCAST clinical breakpoints). The categorical agreement (CA; agreement with the AST categories S [susceptible, standard dosing regimen], I [susceptible, increased exposure], R [resistant]) of the PV was calculated. The PV of Escherichia coli (n = 260), Pseudomonas aeruginosa (n = 86), Klebsiella pneumoniae (n = 47), Enterobacter cloacae complex (n = 45), and Staphylococcus aureus (n = 38) were included. The median CA was 95% (range, 80 to 100%, depending on the species). The colony characteristics (e.g., form/size, color, margin, hemolysis) were not indicative for dASP. PV showed a high categorical agreement in the AST categories. This observation supports a test strategy to perform AST for only one colony of PV. IMPORTANCE Phenotypic variants of bacteria are frequent in routine diagnostics and can display differing antimicrobial susceptibility patterns. We found that the likelihood of different antimicrobial susceptibility is low among PV. To save laboratory resources, only one isolate per PV could be tested to guide the antimicrobial treatment of patients.

Inducible Population Quality Control of Engineered Bacillus subtilis for Improved N-Acetylneuraminic Acid Biosynthesis

Biosynthesis by microorganisms using renewable feedstocks is an important approach for realizing sustainable chemical manufacturing. However, cell-to-cell variation in biosynthesis capability during fermentation restricts the robustness and efficiency of bioproduction, hampering the industrialization of biosynthesis. Herein, we developed an inducible population quality control system (iPopQC) for dynamically modulating the producing and nonproducing subpopulations of engineered Bacillus subtilis, which was constructed via inducible promoter- and metabolite-responsive biosensor-based genetic circuit for regulating essential genes. Moreover, iPopQC achieved a 1.97-fold increase in N-acetylneuraminic acid (NeuAc) titer by enriching producing cell subpopulation during cultivation, representing 52% higher than that of previous PopQC. Strains with double-output iPopQC cocoupling the expression of double essential genes with NeuAc production improved production robustness further, retaining NeuAc production throughout 96 h of fermentation, upon which the strains cocoupling one essential gene expression with NeuAc production abolished the production ability.

Minimal Organizational Requirements for the Ascription of Animal Personality to Social Groups

Recently, psychological phenomena have been expanded to new domains, crisscrossing boundaries of organizational levels, with the emergence of areas such as social personality and ecosystem learning. In this contribution, we analyze the ascription of an individual-based concept (personality) to the social level. Although justified boundary crossings can boost new approaches and applications, the indiscriminate misuse of concepts refrains the growth of scientific areas. The concept of social personality is based mainly on the detection of repeated group differences across a population, in a direct transposition of personality concepts from the individual to the social level. We show that this direct transposition is problematic for avowing the nonsensical ascription of personality even to simple electronic devices. To go beyond a metaphoric use of social personality, we apply the organizational approach to a review of social insect communication networks. Our conceptual analysis shows that socially self-organized systems, such as isolated ant trails and bee's recruitment groups, are too simple to have social personality. The situation is more nuanced when measuring the collective choice between nest sites or foraging patches: some species show positive and negative feedbacks between two or more self-organized social structures so that these co-dependent structures are inter-related by second-order, social information systems, complying with a formal requirement for having social personality: the social closure of constraints. Other requirements include the decoupling between individual and social dynamics, and the self-regulation of collective decision processes. Social personality results to be sometimes a metaphorical transposition of a psychological concept to a social phenomenon. The application of this organizational approach to cases of learning ecosystems, or evolutionary learning, could help to ground theoretically the ascription of psychological properties to levels of analysis beyond the individual, up to meta-populations or ecological communities.

Genome-Wide Identification and Expression Analysis of SOS Response Genes in Salmonella enterica Serovar Typhimurium

A bioinformatic search for LexA boxes, combined with transcriptomic detection of loci responsive to DNA damage, identified 48 members of the SOS regulon in the genome of Salmonella enterica serovar Typhimurium. Single cell analysis using fluorescent fusions revealed that heterogeneous expression is a common trait of SOS response genes, with formation of SOS^OFF and SOS^ON subpopulations. Phenotypic cell variants formed in the absence of external DNA damage show gene expression patterns that are mainly determined by the position and the heterology index of the LexA box. SOS induction upon DNA damage produces SOS^OFF and SOS^ON subpopulations that contain live and dead cells. The nature and concentration of the DNA damaging agent and the time of exposure are major factors that influence the population structure upon SOS induction. An analogy can thus be drawn between the SOS response and other bacterial stress responses that produce phenotypic cell variants.

Different analysis strategies of 16S rRNA gene data from rodent studies generate contrasting views of gut bacterial communities associated with diet, health and obesity

Background

One of the main functions of diet is to nurture the gut microbiota and this relationship affects the health of the host. However, different analysis strategies can generate different views on the relative abundance of each microbial taxon, which can affect our conclusions about the significance of diet to gut health in lean and obese subjects. Here we explored the impact of using different analysis strategies to study the gut microbiota in a context of diet, health and obesity.

Methods

Over 15 million 16S rRNA gene sequences from published studies involving dietary interventions in obese laboratory rodents were analyzed. Three strategies were used to assign the 16S sequences to Operational Taxonomic Units (OTUs) based on the GreenGenes reference OTU sequence files clustered at 97% and 99% similarity.

Results

Different strategies to select OTUs influenced the relative abundance of all bacterial taxa, but the magnitude of this phenomenon showed a strong study effect. Different taxa showed up to 20% difference in relative abundance within the same study, depending on the analysis strategy. Very few OTUs were shared among the samples. ANOSIM test on unweighted UniFrac distances showed that study, sequencing technique, animal model, and dietary treatment (in that order) were the most important factors explaining the differences in bacterial communities. Except for obesity status, the contribution of diet and other factors to explain the variability in bacterial communities was lower when using weighted UniFrac distances. Predicted functional profile and high-level phenotypes of the microbiota showed that each study was associated with unique features and patterns.

Conclusions

The results confirm previous findings showing a strong study effect on gut microbial composition and raise concerns about the impact of analysis strategies on the membership and composition of the gut microbiota. This study may be helpful to guide future research aiming to investigate the relationship between diet, health, and the gut microbiota.

Bacterial Vivisection: How Fluorescence-Based Imaging Techniques Shed a Light on the Inner Workings of Bacteria

The rise in fluorescence-based imaging techniques over the past 3 decades has improved the ability of researchers to scrutinize live cell biology at increased spatial and temporal resolution. In microbiology, these real-time vivisections structurally changed the view on the bacterial cell away from the "watery bag of enzymes" paradigm toward the perspective that these organisms are as complex as their eukaryotic counterparts. Capitalizing on the enormous potential of (time-lapse) fluorescence microscopy and the ever-extending pallet of corresponding probes, initial breakthroughs were made in unraveling the localization of proteins and monitoring real-time gene expression. However, later it became clear that the potential of this technique extends much further, paving the way for a focus-shift from observing single events within bacterial cells or populations to obtaining a more global picture at the intra- and intercellular level. In this review, we outline the current state of the art in fluorescence-based vivisection of bacteria and provide an overview of important case studies to exemplify how to use or combine different strategies to gain detailed information on the cell's physiology. The manuscript therefore consists of two separate (but interconnected) parts that can be read and consulted individually. The first part focuses on the fluorescent probe pallet and provides a perspective on modern methodologies for microscopy using these tools. The second section of the review takes the reader on a tour through the bacterial cell from cytoplasm to outer shell, describing strategies and methods to highlight architectural features and overall dynamics within cells.

Tailoring plant-associated microbial inoculants in agriculture: a roadmap for successful application

Plants are now recognized as metaorganisms which are composed of a host plant associated with a multitude of microbes that provide the host plant with a variety of essential functions to adapt to the local environment. Recent research showed the remarkable importance and range of microbial partners for enhancing the growth and health of plants. However, plant-microbe holobionts are influenced by many different factors, generating complex interactive systems. In this review, we summarize insights from this emerging field, highlighting the factors that contribute to the recruitment, selection, enrichment, and dynamic interactions of plant-associated microbiota. We then propose a roadmap for synthetic community application with the aim of establishing sustainable agricultural systems that use microbial communities to enhance the productivity and health of plants independently of chemical fertilizers and pesticides. Considering global warming and climate change, we suggest that desert plants can serve as a suitable pool of potentially beneficial microbes to maintain plant growth under abiotic stress conditions. Finally, we propose a framework for advancing the application of microbial inoculants in agriculture.

Enhancement of gene expression noise from transcription factor binding to genomic decoy sites

The genome contains several high-affinity non-functional binding sites for transcription factors (TFs) creating a hidden and unexplored layer of gene regulation. We investigate the role of such “decoy sites” in controlling noise (random fluctuations) in the level of a TF that is synthesized in stochastic bursts. Prior studies have assumed that decoy-bound TFs are protected from degradation, and in this case decoys function to buffer noise. Relaxing this assumption to consider arbitrary degradation rates for both bound/unbound TF states, we find rich noise behaviors. For low-affinity decoys, noise in the level of unbound TF always monotonically decreases to the Poisson limit with increasing decoy numbers. In contrast, for high-affinity decoys, noise levels first increase with increasing decoy numbers, before decreasing back to the Poisson limit. Interestingly, while protection of bound TFs from degradation slows the time-scale of fluctuations in the unbound TF levels, the decay of bound TFs leads to faster fluctuations and smaller noise propagation to downstream target proteins. In summary, our analysis reveals stochastic dynamics emerging from nonspecific binding of TFs and highlights the dual role of decoys as attenuators or amplifiers of gene expression noise depending on their binding affinity and stability of the bound TF.

Akkermansia and Microbial Degradation of Mucus in Cats and Dogs: Implications to the Growing Worldwide Epidemic of Pet Obesity

Akkermansia muciniphila is a mucin-degrading bacterium that has shown the potential to provide anti-inflammatory and anti-obesity effects in mouse and man. We here focus on companion animals, specifically cats and dogs, and evaluate the microbial degradation of mucus and its health impact in the context of the worldwide epidemic of pet obesity. A literature survey revealed that the two presently known Akkermansia spp., A. muciniphila and A. glycaniphila, as well as other members of the phylum of Verrucomicrobia seem to be neither very prevalent nor abundant in the digestive tract of cats and dog. While this may be due to methodological aspects, it suggests that bacteria related to Akkermansia are not the major mucus degraders in these pets and hence other mucus-utilizing taxa may deserve attention. Hence, we will discuss the potential of these endogenous mucus utilizers and dietary interventions to boost these as well as the use of Akkermansia spp. related bacteria or their components as strategies to target feline and canine obesity.

Antibiotic Resistance and Epigenetics: More to It than Meets the Eye

The discovery of antibiotics in the last century is considered one of the most important achievements in the history of medicine. Antibiotic usage has significantly reduced morbidity and mortality associated with bacterial infections. However, inappropriate use of antibiotics has led to emergence of antibiotic resistance at an alarming rate. Antibiotic resistance is regarded as a major health care challenge of this century. Despite extensive research, well-documented biochemical mechanisms and genetic changes fail to fully explain mechanisms underlying antibiotic resistance. Several recent reports suggest a key role for epigenetics in the development of antibiotic resistance in bacteria. The intrinsic heterogeneity as well as transient nature of epigenetic inheritance provides a plausible backdrop for high-paced emergence of drug resistance in bacteria. The methylation of adenines and cytosines can influence mutation rates in bacterial genomes, thus modulating antibiotic susceptibility. In this review, we discuss a plethora of recently discovered epigenetic mechanisms and their emerging roles in antibiotic resistance. We also highlight specific epigenetic mechanisms that merit further investigation for their role in antibiotic resistance.

Laboratory Study on the Gastroenteritis Outbreak Caused by a Multidrug-Resistant Campylobacter coli in China

Three severe acute gastroenteritis patients were identified within a 5-h period in a sentinel hospital enrolled in the foodborne pathogen surveillance project in Beijing. All patients had high fever (over 38.5°C), diarrhea, abdominal pain, vomiting, and headache. Ten grams of fresh patient stool sample and 25 g of six suspected foods were collected for real-time PCR screening for 10 major pathogens. Bacterial isolation was performed. Pulsed-field gel electrophoresis (PFGE), multilocus sequence typing (MLST), and antibiotic susceptibility tests were conducted for all the isolates. Whole-genome sequences of the three Campylobacter coli isolates were compared using whole-genome MLST. All stool samples were positive for C. coli, as revealed by PCR. Eleven of the C. coli isolates had the same PFGE and ST type. All isolates were resistant to nalidixic acid, ciprofloxacin, streptomycin, and tetracycline, consistent with the findings of the in silico antibiotic resistance gene profiling. Most coding sequences (99%, 1736/1739) were identical among the three sequenced isolates, except for three frameshift-mutated genes caused by the simple sequence repeats (poly-Gs). This was likely a single-source outbreak caused by a group of highly clonal C. coli. This was the first outbreak of severe gastroenteritis caused by C. coli in China.

Phenotypic Heterogeneity of the Insect Pathogen Photorhabdus luminescens: Insights into the Fate of Secondary Cells

Photorhabdus luminescens is a Gram-negative bacterium that lives in symbiosis with soil nematodes and is simultaneously highly pathogenic toward insects. The bacteria exist in two phenotypically different forms, designated primary (1°) and secondary (2°) cells. Yet unknown environmental stimuli as well as global stress conditions induce phenotypic switching of up to 50% of 1° cells to 2° cells. An important difference between the two phenotypic forms is that 2° cells are unable to live in symbiosis with nematodes and are therefore believed to remain in the soil after a successful infection cycle. In this work, we performed a transcriptomic analysis to highlight and better understand the role of 2° cells and their putative ability to adapt to living in soil. We could confirm that the major phenotypic differences between the two cell forms are mediated at the transcriptional level as the corresponding genes were downregulated in 2° cells. Furthermore, 2° cells seem to be adapted to another environment as we found several differentially expressed genes involved in the cells' metabolism, motility, and chemotaxis as well as stress resistance, which are either up- or downregulated in 2° cells. As 2° cells, in contrast to 1° cells, chemotactically responded to different attractants, including plant root exudates, there is evidence for the rhizosphere being an alternative environment for the 2° cells. Since P. luminescens is biotechnologically used as a bio-insecticide, investigation of a putative interaction of 2° cells with plants is also of great interest for agriculture.IMPORTANCE The biological function and the fate of P. luminescens 2° cells were unclear. Here, we performed comparative transcriptomics of P. luminescens 1° and 2° cultures and found several genes, not only those coding for known phenotypic differences of the two cell forms, that are up- or downregulated in 2° cells compared to levels in 1° cells. Our results suggest that when 1° cells convert to 2° cells, they drastically change their way of life. Thus, 2° cells could easily adapt to an alternative environment such as the rhizosphere and live freely, independent of a host, putatively utilizing plant-derived compounds as nutrient sources. Since 2° cells are not able to reassociate with the nematodes, an alternative lifestyle in the rhizosphere would be conceivable.

A Minor Subpopulation of Mycobacteria Inherently Produces High Levels of Reactive Oxygen Species That Generate Antibiotic Resisters at High Frequency From Itself and Enhance Resister Generation From Its Major Kin Subpopulation

Antibiotic-exposed bacteria produce elevated levels of reactive oxygen species (ROS), to which either they succumb or get mutated genome-wide to generate antibiotic resisters. We recently showed that mycobacterial cultures contained two subpopulations, short-sized cells (SCs; ∼10%) and normal/long-sized cells (NCs; ∼90%). The SCs were significantly more antibiotic-susceptible than the NCs. It implied that the SCs might naturally be predisposed to generate significantly higher levels of ROS than the NCs. This in turn could make the SCs more susceptible to antibiotics or generate more resisters as compared to the NCs. Investigation into this possibility showed that the SCs in the actively growing mid-log phase culture naturally generated significantly high levels of superoxide, as compared to the equivalent NCs, due to the naturally high expression of a specific NADH oxidase in the SCs. This caused labile Fe²⁺ leaching from 4Fe-4S proteins and elevated H₂O₂ formation through superoxide dismutation. Thus, the SCs of both Mycobacterium smegmatis and Mycobacterium tuberculosis inherently contained significantly higher levels of H₂O₂ and labile Fe²⁺ than the NCs. This in turn produced significantly higher levels of hydroxyl radical through Fenton reaction, promoting enhanced antibiotic resister generation from the SCs than from the NCs. The SCs, when mixed back with the NCs, at their natural proportion in the actively growing mid-log phase culture, enhanced antibiotic resister generation from the NCs, to a level equivalent to that from the unfractionated whole culture. The enhanced antibiotic resister generation from the NCs in the reconstituted SCs-NCs natural mixture was found to be due to the high levels of H₂O₂ secreted by the SCs. Thus, the present work unveils and documents the metabolic designs of two mycobacterial subpopulations where one subpopulation produces high ROS levels, despite higher susceptibility, to generate significantly higher number of antibiotic resisters from itself and to enhance resister generation from its kin subpopulation. These findings show the existence of an inherent natural mechanism in both the non-pathogenic and pathogenic mycobacteria to generate antibiotic resisters. The presence of the SCs and the NCs in the pulmonary tuberculosis patients’ sputum, reported by us earlier, alludes to the clinical significance of the study.

The Mechanisms of Substrate Selection, Catalysis, and Translocation by the Elongating RNA Polymerase

Multi-subunit DNA-dependent RNA polymerases synthesize all classes of cellular RNAs, ranging from short regulatory transcripts to gigantic messenger RNAs. RNA polymerase has to make each RNA product in just one try, even if it takes millions of successive nucleotide addition steps. During each step, RNA polymerase selects a correct substrate, adds it to a growing chain, and moves one nucleotide forward before repeating the cycle. However, RNA synthesis is anything but monotonous: RNA polymerase frequently pauses upon encountering mechanical, chemical and torsional barriers, sometimes stepping back and cleaving off nucleotides from the growing RNA chain. A picture in which these intermittent dynamics enable processive, accurate, and controllable RNA synthesis is emerging from complementary structural, biochemical, computational, and single-molecule studies. Here, we summarize our current understanding of the mechanism and regulation of the on-pathway transcription elongation. We review the details of substrate selection, catalysis, proofreading, and translocation, focusing on rate-limiting steps, structural elements that modulate them, and accessory proteins that appear to control RNA polymerase translocation.

Heterogeneity of ROS levels in antibiotic-exposed mycobacterial subpopulations confers differential susceptibility

Phenotypically heterogeneous but genetically identical mycobacterial subpopulations exist in in vitro cultures, in vitro-infected macrophages, infected animal models and tuberculosis patients. In this regard, we recently reported the presence of two subpopulations of cells, which are phenotypically different in length and buoyant density, in mycobacterial cultures. These are the low-buoyant-density short-sized cells (SCs), which constitute ~10-20 % of the population, and the high-buoyant-density normal/long-sized cells (NCs), which form ~80-90 % of the population. The SCs were found to be significantly more susceptible to rifampicin (RIF), isoniazid (INH), H2O2 and acidified nitrite than the NCs. Here we report that the RIF-/INH-/H2O2-exposed SCs showed significantly higher levels of oxidative stress and therefore higher susceptibility than the equivalent number of exposed NCs. Significantly higher levels of hydroxyl radical and superoxide were found in the antibiotic-exposed SCs than in the equivalently exposed NCs. Different proportions of the subpopulation of SCs were found to have different levels of reactive oxygen species (ROS). The hydroxyl radical quencher, thiourea, and the superoxide dismutase mimic, TEMPOL, significantly reduced hydroxyl radical and superoxide levels, respectively, in the antibiotic-exposed SCs and NCs and thereby decreased their differential susceptibility to antibiotics. Thus, the present study shows that the heterogeneity of the reactive oxygen species (ROS) levels in these mycobacterial subpopulations confers differential susceptibility to antibiotics. We have discussed the possible mechanisms that can generate differential ROS levels in the antibiotic-exposed SCs and NCs. The present study advances our current understanding of the molecular mechanisms underlying antibiotic tolerance in mycobacteria.

Two stochastic processes shape diverse senescence patterns in a single-cell organism

Despite advances in aging research, a multitude of aging models, and empirical evidence for diverse senescence patterns, understanding of the biological processes that shape senescence is lacking. We show that senescence of an isogenic Escherichia coli bacterial population results from two stochastic processes. The first process is a random deterioration process within the cell, such as generated by random accumulation of damage. This primary process leads to an exponential increase in mortality early in life followed by a late age mortality plateau. The second process relates to the stochastic asymmetric transmission at cell fission of an unknown factor that influences mortality. This secondary process explains the difference between the classical mortality plateaus detected for young mothers' offspring and the near nonsenescence of old mothers' offspring as well as the lack of a mother-offspring correlation in age at death. We observed that lifespan is predominantly determined by underlying stochastic stage dynamics. Surprisingly, our findings support models developed for metazoans that base their arguments on stage-specific actions of alleles to understand the evolution of senescence. We call for exploration of similar stochastic influences that shape aging patterns beyond simple organisms.

Multiple factors contribute to bimodal toxin gene expression in Clostridioides (Clostridium) difficile

Clostridioides (formerly Clostridium) difficile produces two major toxins, TcdA and TcdB, upon entry into stationary phase. Transcription of tcdA and tcdB requires the specialized sigma factor, σTcdR , which also directs RNA Polymerase to transcribe tcdR itself. We fused a gene for a red fluorescent protein to the tcdA promoter to study toxin gene expression at the level of individual C. difficile cells. Surprisingly, only a subset of cells became red fluorescent upon entry into stationary phase. Breaking the positive feedback loop that controls σTcdR production by engineering cells to express tcdR from a tetracycline-inducible promoter resulted in uniform fluorescence across the population. Experiments with two regulators of tcdR expression, σD and CodY, revealed neither is required for bimodal toxin gene expression. However, σD biased cells toward the Toxin-ON state, while CodY biased cells toward the Toxin-OFF state. Finally, toxin gene expression was observed in sporulating cells. We conclude that (i) toxin production is regulated by a bistable switch governed by σTcdR , which only accumulates to high enough levels to trigger toxin gene expression in a subset of cells, and (ii) toxin production and sporulation are not mutually exclusive developmental programs.

Controlling and exploiting cell-to-cell variation in metabolic engineering

Individual cells within a population can display diverse phenotypes due to differences in their local environment, genetic variation, and stochastic expression of genes. Understanding this cell-to-cell variation is important for metabolic engineering applications because variability can impact production. For instance, recent studies have shown that production can be highly heterogeneous among engineered cells, and strategies that manage this diversity improve yields of biosynthetic products. These results suggest the potential of controlling variation as a novel approach towards improving performance of engineered cells. In this review, we focus on identifying the origins of cell-to-cell variation in metabolic engineering applications and discuss recent developments on strategies that can be employed to diminish, accept, or even exploit cell-to-cell variation.

Phyllosphere microbiology: at the interface between microbial individuals and the plant host

Contents Summary 1327 I. Introduction 1327 II. Individuality and the relevance of scales for the investigation of bacteria 1328 III. Bacterial aggregation and community patterning at the single-cell resolution 1329 IV. What are the effects on the plant host? 1330 V. Future directions and current questions 1331 Acknowledgements 1332 ORCID 1332 References 1332 SUMMARY: Leaf surfaces are home to diverse bacterial communities. Within these communities, every individual cell perceives its unique environment and responds accordingly. In this insight article, the perspective of the bacterial individual is assumed in an attempt to describe how the spatially heterogeneous leaf surface determines the fate of bacteria. To investigate behaviour at scales relevant to bacteria, single-cell approaches are essential. Single-cell studies provide important lessons about how current 'omics' approaches fail to give an accurate picture of the behaviour of bacterial populations in heterogeneous environments. Upcoming techniques will soon allow us to combine the power of single-cell and omics approaches.

Metabolic interactions between dynamic bacterial subpopulations

Individual microbial species are known to occupy distinct metabolic niches within multi-species communities. However, it has remained largely unclear whether metabolic specialization can similarly occur within a clonal bacterial population. More specifically, it is not clear what functions such specialization could provide and how specialization could be coordinated dynamically. Here, we show that exponentially growing Bacillus subtilis cultures divide into distinct interacting metabolic subpopulations, including one population that produces acetate, and another population that differentially expresses metabolic genes for the production of acetoin, a pH-neutral storage molecule. These subpopulations exhibit distinct growth rates and dynamic interconversion between states. Furthermore, acetate concentration influences the relative sizes of the different subpopulations. These results show that clonal populations can use metabolic specialization to control the environment through a process of dynamic, environmentally-sensitive state-switching.

The chemical reactions that occur within a living organism are collectively referred to as its metabolism. Many metabolic reactions produce byproducts that will poison the cells if they are not dealt with: fermenting bacteria, for example, release harmful organic acids and alcohols. How the bacteria respond to these toxins has been most studied at the level of entire microbial populations, meaning the activities of individual cells are effectively “averaged” together. Yet, even two bacteria with the same genes and living in the same environment can behave in different ways. This raises the question: do bacterial populations specialize into distinct subpopulations that play distinct roles when dealing with metabolic products, or do all cells in the community act in unison?

Rosenthal et al. set out to answer this question for a community of Bacillus subtilis, a bacterium that is commonly studied in the laboratory and used for the industrial production of enzymes. The analysis focused on genes involved in fundamental metabolic processes, known as the TCA cycle, which the bacteria use to generate energy and build biomass. The experiments revealed that, even when all the cells are genetically identical, different Bacillus subtilis cells do indeed specialize into metabolic subpopulations with distinct growth rates.

Time-lapse movies of bacteria that made fluorescent markers of different colors whenever certain metabolic genes became active showed cells switching different colors on and off, indicating that they switch between metabolic subpopulations. Further biochemical studies and measures of gene activity revealed that the different subpopulations produce and release distinct metabolic products, including toxic byproducts. Notably, the release of these metabolites by one subpopulation appeared to activate other subpopulations within the community.

This example of cells specializing into unique interacting metabolic subpopulations provides insight into several fundamental issues in microbiology and beyond. It is relevant to evolutionary biologists, since the fact that fractions of the population can switch in and out of a metabolic state, instead of evolving into several inflexible specialists, may provide an evolutionary advantage in fluctuating natural environments by reducing the risk of extinction. It also has implications for industrial fermentation processes and metabolic engineering, and may help biotechnologists design more efficient ways to harness bacterial metabolism to produce useful products.

Cell-to-cell variation and specialization in sugar metabolism in clonal bacterial populations

While we have good understanding of bacterial metabolism at the population level, we know little about the metabolic behavior of individual cells: do single cells in clonal populations sometimes specialize on different metabolic pathways? Such metabolic specialization could be driven by stochastic gene expression and could provide individual cells with growth benefits of specialization. We measured the degree of phenotypic specialization in two parallel metabolic pathways, the assimilation of glucose and arabinose. We grew Escherichia coli in chemostats, and used isotope-labeled sugars in combination with nanometer-scale secondary ion mass spectrometry and mathematical modeling to quantify sugar assimilation at the single-cell level. We found large variation in metabolic activities between single cells, both in absolute assimilation and in the degree to which individual cells specialize in the assimilation of different sugars. Analysis of transcriptional reporters indicated that this variation was at least partially based on cell-to-cell variation in gene expression. Metabolic differences between cells in clonal populations could potentially reduce metabolic incompatibilities between different pathways, and increase the rate at which parallel reactions can be performed.

This study addresses a fundamental question in bacterial metabolism: do all individuals in a clonal population express the same metabolic functions, or do individuals specialize on different metabolic functions and assimilate different substrates? Reports about stochastic gene expression in bacterial populations raise the possibility that transcriptional differences between individuals translate into different metabolic behaviors, but the prevalence and magnitude of such effects is currently not known. Here, we quantified the assimilation of two isotope-labeled sugars by single Escherichia coli cells using nanometer-scale secondary ion mass spectrometry, an analytical approach seldom used in systems biology. By comparing sugar assimilation and gene expression dynamics, we were able to differentiate the metabolic profiles of individual cells. We observed a previously hidden level of cell-to-cell variation in metabolism: cells differed both in the total amount of sugar they assimilated, as well as with respect to which of the two sugars they preferentially assimilated. Intriguingly, a cell’s preference in sugar assimilation was only partially based on specialization in gene expression. Taken together, this study is a step towards understanding the magnitude and the relevance of metabolic differences between genetically identical cells.

Shaping bacterial population behavior through computer-interfaced control of individual cells

Bacteria in groups vary individually, and interact with other bacteria and the environment to produce population-level patterns of gene expression. Investigating such behavior in detail requires measuring and controlling populations at the single-cell level alongside precisely specified interactions and environmental characteristics. Here we present an automated, programmable platform that combines image-based gene expression and growth measurements with on-line optogenetic expression control for hundreds of individual Escherichia coli cells over days, in a dynamically adjustable environment. This integrated platform broadly enables experiments that bridge individual and population behaviors. We demonstrate: (i) population structuring by independent closed-loop control of gene expression in many individual cells, (ii) cell–cell variation control during antibiotic perturbation, (iii) hybrid bio-digital circuits in single cells, and freely specifiable digital communication between individual bacteria. These examples showcase the potential for real-time integration of theoretical models with measurement and control of many individual cells to investigate and engineer microbial population behavior.

Individual bacteria interact with each other and their environment to produce population-level patterns of gene expression. Here the authors use an automated platform combined with optogenetic feedback to manipulate population behaviors through dynamic control of individual cells.

Autonomous control of metabolic state by a quorum sensing (QS)-mediated regulator for bisabolene production in engineered E. coli

Inducible gene expression systems are widely used in microbial host strains for protein and commodity chemical production because of their extensive characterization and ease of use. However, some of these systems have disadvantages such as leaky expression, lack of dynamic control, and the prohibitively high costs of inducers associated with large-scale production. Quorum sensing (QS) systems in bacteria control gene expression in response to population density, and the LuxI/R system from Vibrio fischeri is a well-studied example. A QS system could be ideal for biofuel production strains as it is self-regulated and does not require the addition of inducer compounds, which reduce operational costs for inducer. In this study, a QS system was developed for inducer-free production of the biofuel compound bisabolene from engineered E. coli. Seven variants of the Sensor plasmid, which carry the luxI-luxR genes, and four variants of the Response plasmid, which carry bisabolene producing pathway genes under the control of the P_luxI promoter, were designed for optimization of bisabolene production. Furthermore, a chromosome-integrated QS strain was engineered with the best combination of Sensor and Response plasmid and produced bisabolene at a titer of 1.1g/L without addition of external inducers. This is a 44% improvement from our previous inducible system. The QS strain also displayed higher homogeneity in gene expression and isoprenoid production compared to an inducible-system strain.

The impact of bottlenecks on microbial survival, adaptation, and phenotypic switching in host-pathogen interactions

Microbial pathogens and viruses can often maintain sufficient population diversity to evade a wide range of host immune responses. However, when populations experience bottlenecks, as occurs frequently during initiation of new infections, pathogens require specialized mechanisms to regenerate diversity. We address the evolution of such mechanisms, known as stochastic phenotype switches, which are prevalent in pathogenic bacteria. We analyze a model of pathogen diversification in a changing host environment that accounts for selective bottlenecks, wherein different phenotypes have distinct transmission probabilities between hosts. We show that under stringent bottlenecks, such that only one phenotype can initiate new infections, there exists a threshold stochastic switching rate below which all pathogen lineages go extinct, and above which survival is a near certainty. We determine how quickly stochastic switching rates can evolve by computing a fitness landscape for the evolutionary dynamics of switching rates, and analyzing its dependence on both the stringency of bottlenecks and the duration of within-host growth periods. We show that increasing the stringency of bottlenecks or decreasing the period of growth results in faster adaptation of switching rates. Our model provides strong theoretical evidence that bottlenecks play a critical role in accelerating the evolutionary dynamics of pathogens.

Reconstructing the genotype-to-fitness map for the bacterial chemotaxis network and its emergent behavioural phenotypes

The signal-transduction network responsible for chemotaxis in Escherichia coli has been characterised in extraordinary detail. Yet, relatively little is known about eco-evolutionary aspects of chemotaxis, such as how the network has been shaped by selection and to what extent natural populations may fine-tune their chemotactic behaviour to the ecological conditions. To address these questions, we here develop an evolutionary-systems-biology model of the chemotaxis network of E. coli, which we apply to estimate the resource accumulation rate (here used as a proxy for fitness) of wildtype and a large number of potential mutant genotypes. Mutant genotypes differ from the wildtype in the concentrations of one or more constituent proteins of the chemotaxis signalling network or in one or more of its kinetic parameters. To guarantee model consistency across the genotype space, we explicitly incorporated biochemical constraints that underly observed phenotypic trade-offs. The model was validated by reconstructing the phenotypic properties of several known mutant genotypes. We also characterised differences in the fitness distribution between genotypes, and reconstructed adaptive walks in genotype space for populations exposed to different environmental conditions. We found that the local fitness landscape is rugged, due to non-additive interactions between mutations. When selection has a consistent direction, just a few adaptive mutations are required to reach a local peak, and different local peaks can be reached by adaptive walks starting from the same initial genotype. However, when the direction of selection is fluctuating, evolutionary paths are much longer and genotype space is explored further. Longer adaptive walks were also observed when evolution was started from a low-fitness genotype such as a CheZ knockout mutant. In line with empirical observations, the initial ΔcheZ mutant did not respond to a step-down stimulus, but a dynamic response similar to the wildtype was recovered following the fixation of compensatory mutations.

Mycobacterial Cultures Contain Cell Size and Density Specific Sub-populations of Cells with Significant Differential Susceptibility to Antibiotics, Oxidative and Nitrite Stress

The present study shows the existence of two specific sub-populations of Mycobacterium smegmatis and Mycobacterium tuberculosis cells differing in size and density, in the mid-log phase (MLP) cultures, with significant differential susceptibility to antibiotic, oxidative, and nitrite stress. One of these sub-populations (~10% of the total population), contained short-sized cells (SCs) generated through highly-deviated asymmetric cell division (ACD) of normal/long-sized mother cells and symmetric cell divisions (SCD) of short-sized mother cells. The other sub-population (~90% of the total population) contained normal/long-sized cells (NCs). The SCs were acid-fast stainable and heat-susceptible, and contained high density of membrane vesicles (MVs, known to be lipid-rich) on their surface, while the NCs possessed negligible density of MVs on the surface, as revealed by scanning and transmission electron microscopy. Percoll density gradient fractionation of MLP cultures showed the SCs-enriched fraction (SCF) at lower density (probably indicating lipid-richness) and the NCs-enriched fraction (NCF) at higher density of percoll fractions. While live cell imaging showed that the SCs and the NCs could grow and divide to form colony on agarose pads, the SCF, and NCF cells could independently regenerate MLP populations in liquid and solid media, indicating their full genomic content and population regeneration potential. CFU based assays showed the SCF cells to be significantly more susceptible than NCF cells to a range of concentrations of rifampicin and isoniazid (antibiotic stress), H2O2 (oxidative stress),and acidified NaNO2 (nitrite stress). Live cell imaging showed significantly higher susceptibility of the SCs of SC-NC sister daughter cell pairs, formed from highly-deviated ACD of normal/long-sized mother cells, to rifampicin and H2O2, as compared to the sister daughter NCs, irrespective of their comparable growth rates. The SC-SC sister daughter cell pairs, formed from the SCDs of short-sized mother cells and having comparable growth rates, always showed comparable stress-susceptibility. These observations and the presence of M. tuberculosis SCs and NCs in pulmonary tuberculosis patients' sputum earlier reported by us imply a physiological role for the SCs and the NCs under the stress conditions. The plausible reasons for the higher stress susceptibility of SCs and lower stress susceptibility of NCs are discussed.

A Precise Temperature-Responsive Bistable Switch Controlling Yersinia Virulence

Different biomolecules have been identified in bacterial pathogens that sense changes in temperature and trigger expression of virulence programs upon host entry. However, the dynamics and quantitative outcome of this response in individual cells of a population, and how this influences pathogenicity are unknown. Here, we address these questions using a thermosensing virulence regulator of an intestinal pathogen (RovA of Yersinia pseudotuberculosis) as a model. We reveal that this regulator is part of a novel thermoresponsive bistable switch, which leads to high- and low-invasive subpopulations within a narrow temperature range. The temperature range in which bistability is observed is defined by the degradation and synthesis rate of the regulator, and is further adjustable via a nutrient-responsive regulator. The thermoresponsive switch is also characterized by a hysteretic behavior in which activation and deactivation occurred on vastly different time scales. Mathematical modeling accurately mirrored the experimental behavior and predicted that the thermoresponsiveness of this sophisticated bistable switch is mainly determined by the thermo-triggered increase of RovA proteolysis. We further observed RovA ON and OFF subpopulations of Y. pseudotuberculosis in the Peyer’s patches and caecum of infected mice, and that changes in the RovA ON/OFF cell ratio reduce tissue colonization and overall virulence. This points to a bet-hedging strategy in which the thermoresponsive bistable switch plays a key role in adapting the bacteria to the fluctuating conditions encountered as they pass through the host’s intestinal epithelium and suggests novel strategies for the development of antimicrobial therapies.

The ability of pathogens to sense temperature changes when they enter their mammalian hosts from the environment is crucial to optimize their fitness and adjust expression of their virulence programs. Until now it has been assumed that all cells within a population participate in the thermo-triggered adaptive response. Here, we show that a small subpopulation of an enteric pathogen does not follow thermo-induced reprogramming when the bacteria pass the intestinal epithelial layer. Observed heterogeneity is promoted by a new type of bistable switch, implicating a highly precise, thermoresponsive control element. Moreover, we demonstrate that this regulatory implement is important for virulence as it prepares the pathogen for sudden, unpredictable fluctuations encountered during host entry and exit.

Effects of cell cycle noise on excitable gene circuits

We assess the impact of cell cycle noise on gene circuit dynamics. For bistable genetic switches and excitable circuits, we find that transitions between metastable states most likely occur just after cell division and that this concentration effect intensifies in the presence of transcriptional delay. We explain this concentration effect with a three-states stochastic model. For genetic oscillators, we quantify the temporal correlations between daughter cells induced by cell division. Temporal correlations must be captured properly in order to accurately quantify noise sources within gene networks.

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

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

Specificity and complexity in bacterial quorum-sensing systems

Quorum sensing (QS) is a microbial cell-to-cell communication process that relies on the production and detection of chemical signals called autoinducers (AIs) to monitor cell density and species complexity in the population. QS allows bacteria to behave as a cohesive group and coordinate collective behaviors. While most QS receptors display high specificity to their AI ligands, others are quite promiscuous in signal detection. How do specific QS receptors respond to their cognate signals with high fidelity? Why do some receptors maintain low signal recognition specificity? In addition, many QS systems are composed of multiple intersecting signaling pathways: what are the benefits of preserving such a complex signaling network when a simple linear ‘one-to-one’ regulatory pathway seems sufficient to monitor cell density? Here, we will discuss different molecular mechanisms employed by various QS systems that ensure productive and specific QS responses. Moreover, the network architectures of some well-characterized QS circuits will be reviewed to understand how the wiring of different regulatory components achieves different biological goals.

This review focuses on the specificity and complexity of quorum-sensing circuits in both Gram-negative and Gram-positive bacterial species.

Recent advances in marine N-cycle studies using 15N labeling methods

¹⁵N enriched compounds such as ammonium and nitrate, as well as ^15-15N₂ gas are invaluable tools in marine N-cycle research. ¹⁵N stable isotope approaches allow researchers to delve into the often complex world of N-transformations and trace microbially mediated processes such as nitrification, denitrification, anammox and N-fixation. While ¹⁵N stable isotope approaches are well established, experimental approaches which take advantage of them are constantly evolving. Here we summarize recent advances in methodology, including in the direct application of ¹⁵N stable isotopes themselves, improved experimental design and the use of ¹⁵N stable isotopes in single cell studies. Furthermore, we discuss how these advances have led to new insights into marine N-cycling, particularly in the fields of nitrification and N-fixation.

Phase-dependent dynamics of the lac promoter under nutrient stress

To survive, a bacterial population must sense nutrient availability and adjust its growth phase accordingly. Few studies have quantitatively analyzed the single-cell behavior of stress and growth phase-related transcriptional changes in Escherichia coli. To investigate the dynamic changes in transcription during different growth phases and starvation, we analyzed the single-cell transcriptional dynamics of the E. coli lac promoter. Cells were grown under different starvation conditions, including glucose, magnesium, phosphate and thiamine limitations, and transcription dynamics was quantified using a single RNA detection method at different phases. Differences in gene expression over conditions and phases indicate that stochasticity in transcription dynamics is directly connected to cell phase and availability of nutrients. Except for glucose, the pattern of transcription dynamics under all starvation conditions appears to be similar. Transcriptional bursts were more prominent in lag and stationary phase cells starved for energy sources. Identical behavior was observed in exponential phase cells starved for phosphate and thiamine. Noise measurements under all nutrient exhaustion conditions indicate that intrinsic noise is higher than extrinsic noise. Our results, obtained in a relA1 mutational background, which led to suboptimal production of ppGpp, suggest that the single-cell transcriptional changes we observed were largely ppGpp-independent. Taken together, we propose that, under different starvation conditions, cells are able to decrease the trend in cell-to-cell variability in transcription as a common means of adaptation.