The role of physiological heterogeneity in microbial population behavior

Quantitative metabolomics: a phantom?

'Mass specs are precise but biology is not!' is a frequently heard argument when quantitative experimental data do not fit into the overall picture. The problem with this opinion is that the significance of measured biological data becomes a matter of gut feeling. Doubtlessly, the measurement precision of modern mass spectrometers is far better than the reproducibility of biological experiments. However, precisely for this reason, technical reproduction of mass spectrometric measurements neither characterizes the whole experiment from cell cultivation to producing biological data nor says anything about systematic errors in the overall measurement procedure. Taking quantitative metabolomics as a fruitful example, we deal with the question of why it is so difficult to say something precise about imprecision in biology.

Single cell analysis with probe ESI-mass spectrometry: detection of metabolites at cellular and subcellular levels

Molecular analysis at cellular and subcellular levels, whether on selected molecules or at the metabolomics scale, is still a challenge now. Here we propose a method based on probe ESI mass spectrometry (PESI-MS) for single cell analysis. Detection of metabolites at cellular and subcellular levels was successfully achieved. In our work, tungsten probes with a tip diameter of about 1 μm were directly inserted into live cells to enrich metabolites. Then the enriched metabolites were directly desorbed/ionized from the tip of the probe for mass spectrometry (MS) detection. The direct desorption/ionization of the enriched metabolites from the tip of the probe greatly improved the sensitivity by a factor of about 30 fold compared to those methods that eluted the enriched analytes into a liquid phase for subsequent MS detection. We applied the PESI-MS to the detection of metabolites in single Allium cepa cells. Different kinds of metabolites, including 6 fructans, 4 lipids, and 8 flavone derivatives in single cells, have been successfully detected. Significant metabolite diversity was observed among different cells types of A. cepa bulb and different subcellular compartments of the same cell. We found that the inner epidermal cells had about 20 fold more fructans than the outer epidermal cells, while the outer epidermal cells had more lipids. We expected that PESI-MS might be a candidate in the future studies of single cell "omics".

Particle invasion, survival, and non-ergodicity in 2D diffusion processes with space-dependent diffusivity

We study the thermal Markovian diffusion of tracer particles in a 2D medium with spatially varying diffusivity D(r), mimicking recently measured, heterogeneous maps of the apparent diffusion coefficient in biological cells. For this heterogeneous diffusion process (HDP) we analyse the mean squared displacement (MSD) of the tracer particles, the time averaged MSD, the spatial probability density function, and the first passage time dynamics from the cell boundary to the nucleus. Moreover we examine the non-ergodic properties of this process which are important for the correct physical interpretation of time averages of observables obtained from single particle tracking experiments. From extensive computer simulations of the 2D stochastic Langevin equation we present an in-depth study of this HDP. In particular, we find that the MSDs along the radial and azimuthal directions in a circular domain obey anomalous and Brownian scaling, respectively. We demonstrate that the time averaged MSD stays linear as a function of the lag time and the system thus reveals a weak ergodicity breaking. Our results will enable one to rationalise the diffusive motion of larger tracer particles such as viruses or submicron beads in biological cells.

Heteroresistance at the single-cell level: adapting to antibiotic stress through a population-based strategy and growth-controlled interphenotypic coordination

Heteroresistance refers to phenotypic heterogeneity of microbial clonal populations under antibiotic stress, and it has been thought to be an allocation of a subset of “resistant” cells for surviving in higher concentrations of antibiotic. The assumption fits the so-called bet-hedging strategy, where a bacterial population “hedges” its “bet” on different phenotypes to be selected by unpredicted environment stresses. To test this hypothesis, we constructed a heteroresistance model by introducing a bla_CTX-M-14 gene (coding for a cephalosporin hydrolase) into a sensitive Escherichia coli strain. We confirmed heteroresistance in this clone and that a subset of the cells expressed more hydrolase and formed more colonies in the presence of ceftriaxone (exhibited stronger “resistance”). However, subsequent single-cell-level investigation by using a microfluidic device showed that a subset of cells with a distinguishable phenotype of slowed growth and intensified hydrolase expression emerged, and they were not positively selected but increased their proportion in the population with ascending antibiotic concentrations. Therefore, heteroresistance—the gradually decreased colony-forming capability in the presence of antibiotic—was a result of a decreased growth rate rather than of selection for resistant cells. Using a mock strain without the resistance gene, we further demonstrated the existence of two nested growth-centric feedback loops that control the expression of the hydrolase and maximize population growth in various antibiotic concentrations. In conclusion, phenotypic heterogeneity is a population-based strategy beneficial for bacterial survival and propagation through task allocation and interphenotypic collaboration, and the growth rate provides a critical control for the expression of stress-related genes and an essential mechanism in responding to environmental stresses.

Heteroresistance is essentially phenotypic heterogeneity, where a population-based strategy is thought to be at work, being assumed to be variable cell-to-cell resistance to be selected under antibiotic stress. Exact mechanisms of heteroresistance and its roles in adaptation to antibiotic stress have yet to be fully understood at the molecular and single-cell levels. In our study, we have not been able to detect any apparent subset of “resistant” cells selected by antibiotics; on the contrary, cell populations differentiate into phenotypic subsets with variable growth statuses and hydrolase expression. The growth rate appears to be sensitive to stress intensity and plays a key role in controlling hydrolase expression at both the bulk population and single-cell levels. We have shown here, for the first time, that phenotypic heterogeneity can be beneficial to a growing bacterial population through task allocation and interphenotypic collaboration other than partitioning cells into different categories of selective advantage.

Application of a genetically encoded biosensor for live cell imaging of L-valine production in pyruvate dehydrogenase complex-deficient Corynebacterium glutamicum strains

The majority of biotechnologically relevant metabolites do not impart a conspicuous phenotype to the producing cell. Consequently, the analysis of microbial metabolite production is still dominated by bulk techniques, which may obscure significant variation at the single-cell level. In this study, we have applied the recently developed Lrp-biosensor for monitoring of amino acid production in single cells of gradually engineered L-valine producing Corynebacterium glutamicum strains based on the pyruvate dehydrogenase complex-deficient (PDHC) strain C. glutamicum ΔaceE. Online monitoring of the sensor output (eYFP fluorescence) during batch cultivation proved the sensor's suitability for visualizing different production levels. In the following, we conducted live cell imaging studies on C. glutamicum sensor strains using microfluidic chip devices. As expected, the sensor output was higher in microcolonies of high-yield producers in comparison to the basic strain C. glutamicum ΔaceE. Microfluidic cultivation in minimal medium revealed a typical Gaussian distribution of single cell fluorescence during the production phase. Remarkably, low amounts of complex nutrients completely changed the observed phenotypic pattern of all strains, resulting in a phenotypic split of the population. Whereas some cells stopped growing and initiated L-valine production, others continued to grow or showed a delayed transition to production. Depending on the cultivation conditions, a considerable fraction of non-fluorescent cells was observed, suggesting a loss of metabolic activity. These studies demonstrate that genetically encoded biosensors are a valuable tool for monitoring single cell productivity and to study the phenotypic pattern of microbial production strains.

Quantitative dynamics of triacylglycerol accumulation in microalgae populations at single-cell resolution revealed by Raman microspectroscopy

BACKGROUND

Rapid, real-time and label-free measurement of the cellular contents of biofuel molecules such as triacylglycerol (TAG) in populations at single-cell resolution are important for bioprocess control and understanding of the population heterogeneity. Raman microspectroscopy can directly detect the changes of metabolite profile in a cell and thus can potentially serve these purposes.

RESULTS

Single-cell Raman spectra (SCRS) of the unicellular oleaginous microalgae Nannochloropsis oceanica from the cultures under nitrogen depletion (TAG-producing condition) and nitrogen repletion (non-TAG-producing condition) were sampled at eight time points during the first 96 hours upon the onset of nitrogen depletion. Single N. oceanica cells were captured by a 532-nm laser and the SCRS were acquired by the same laser within one second per cell. Using chemometric methods, the SCRS were able to discriminate cells between nitrogen-replete and nitrogen-depleted conditions at as early as 6 hours with >93.3% accuracy, and among the eight time points under nitrogen depletion with >90.4% accuracy. Quantitative prediction of TAG content in single cells was achieved and validated via SCRS and liquid chromatography-mass spectrometry (LC-MS) analysis at population level. SCRS revealed the dynamics of heterogeneity in TAG production among cells in each isogenic population. A significant negative correlation between TAG content and lipid unsaturation degree in individual microalgae cells was observed.

CONCLUSIONS

Our results show that SCRS can serve as a label-free and non-invasive proxy for quantitatively tracking and screening cellular TAG content in real-time at single-cell level. Phenotypic comparison of single cells via SCRS should also help investigating the mechanisms of functional heterogeneity within a cellular population.

c-di-GMP heterogeneity is generated by the chemotaxis machinery to regulate flagellar motility

Individual cell heterogeneity is commonly observed within populations, although its molecular basis is largely unknown. Previously, using FRET-based microscopy, we observed heterogeneity in cellular c-di-GMP levels. In this study, we show that c-di-GMP heterogeneity in Pseudomonas aeruginosa is promoted by a specific phosphodiesterase partitioned after cell division. We found that subcellular localization and reduction of c-di-GMP levels by this phosphodiesterase is dependent on the histidine kinase component of the chemotaxis machinery, CheA, and its phosphorylation state. Therefore, individual cell heterogeneity in c-di-GMP concentrations is regulated by the activity and the asymmetrical inheritance of the chemotaxis organelle after cell division. c-di-GMP heterogeneity results in a diversity of motility behaviors. The generation of diverse intracellular concentrations of c-di-GMP by asymmetric partitioning is likely important to the success and survival of bacterial populations within the environment by allowing a variety of motility behaviors.

DOI:http://dx.doi.org/10.7554/eLife.01402.001

Bacterial populations have traditionally been assumed to be made up of identical cells. However, while the bacteria within a population may be genetically identical, individual cells have different growth rates, metabolisms and motilities, among other things. This ‘phenotypic heterogeneity’ has been observed in many different species of bacteria, and in some cases it can be attributed to changes in the concentration of molecules called second messengers that help to relay signals from the external environment to targets within the cell.

It can be challenging to monitor changes in the concentration of specific molecules inside cells, but researchers recently developed a form of microscopy based on FRET (short for Forster resonance energy transfer) that can measure the levels of a second messenger molecule called cyclic di-guanylate (c-di-GMP) inside individual cells. This technique was used to study P. aeruginosa, a bacterium that has a single corkscrew-shaped propeller that enables it to swim through liquid. P. aeruginosa divides to form two daughter cells—one with a propeller and one without.

Although the daughter cell that does not have a propeller quickly grows one, FRET-based microscopy revealed that the daughter cell with a propeller had less c-di-GMP than the daughter without a propeller, but the reasons underlying this difference and its effects on bacterial behavior were not clear.

Now Kulasekara et al. show that the cell that inherits the propeller contains an enzyme that degrades c-di-GMP, and that the low levels of this second messenger molecule—caused by the enzyme being concentrated near the base of the propeller, and the presence of a protein (CheA) that enables the bacteria to swim towards sources of nutrients—result in faster swimming speeds and increased responsiveness to nutrients. In other words, although the two daughter cells are genetically identical, they behave quite differently because of the different levels of this second messenger molecule.

The existence of heterogeneity within a bacterial population likely leads to increased success and survival within changing diverse environments, and this work sets the stage for similar investigations into what establishes heterogeneity in other bacterial populations.

DOI:http://dx.doi.org/10.7554/eLife.01402.002

Incorporation of flexible objectives and time-linked simulation with flux balance analysis

We present two modifications of the flux balance analysis (FBA) metabolic modeling framework which relax implicit assumptions of the biomass reaction. Our flexible flux balance analysis (flexFBA) objective removes the fixed proportion between reactants, and can therefore produce a subset of biomass reactants. Our time-linked flux balance analysis (tFBA) simulation removes the fixed proportion between reactants and byproducts, and can therefore describe transitions between metabolic steady states. Used together, flexFBA and tFBA model a time scale shorter than the regulatory and growth steady state encoded by the biomass reaction. This combined short-time FBA method is intended for integrated modeling applications to enable detailed and dynamic depictions of microbial physiology such as whole-cell modeling. For example, when modeling Escherichia coli, it avoids artifacts caused by low-copy-number enzymes in single-cell models with kinetic bounds. Even outside integrated modeling contexts, the detailed predictions of flexFBA and tFBA complement existing FBA techniques. We show detailed metabolite production of in silico knockouts used to identify when correct essentiality predictions are made for the wrong reason.

Single-cell force spectroscopy of the medically important Staphylococcus epidermidis-Candida albicans interaction

Despite the clinical importance of bacterial-fungal interactions, their molecular details are poorly understood. A hallmark of such medically important interspecies associations is the interaction between the two nosocomial pathogens Staphylococcus aureus and Candida albicans, which can lead to mixed biofilm-associated infections with enhanced antibiotic resistance. Here, we use single-cell force spectroscopy (SCFS) to quantify the forces engaged in bacterial-fungal co-adhesion, focusing on the poorly investigated S. epidermidis-C. albicans interaction. Force curves recorded between single bacterial and fungal germ tubes showed large adhesion forces (~5 nN) with extended rupture lengths (up to 500 nm). By contrast, bacteria poorly adhered to yeast cells, emphasizing the important role of the yeast-to-hyphae transition in mediating adhesion to bacterial cells. Analysis of mutant strains altered in cell wall composition allowed us to distinguish the main fungal components involved in adhesion, i.e. Als proteins and O-mannosylations. We suggest that the measured co-adhesion forces are involved in the formation of mixed biofilms, thus possibly as well in promoting polymicrobial infections. In the future, we anticipate that this SCFS platform will be used in nanomedicine to decipher the molecular mechanisms of a wide variety of pathogen-pathogen interactions and may help in designing novel anti-adhesion agents.

(p)ppGpp controls bacterial persistence by stochastic induction of toxin-antitoxin activity

Persistence refers to the phenomenon in which isogenic populations of antibiotic-sensitive bacteria produce rare cells that transiently become multidrug tolerant. Whether slow growth in a rare subset of cells underlies the persistence phenotype has not be examined in wild-type bacteria. Here, we show that an exponentially growing population of wild-type Escherichia coli cells produces rare cells that stochastically switch into slow growth, that the slow-growing cells are multidrug tolerant, and that they are able to resuscitate. The persistence phenotype depends hierarchically on the signaling nucleotide (p)ppGpp, Lon protease, inorganic polyphosphate, and toxin-antitoxins. We show that the level of (p)ppGpp varies stochastically in a population of exponentially growing cells and that the high (p)ppGpp level in rare cells induces slow growth and persistence. (p)ppGpp triggers slow growth by activating toxin-antitoxin loci through a regulatory cascade depending on inorganic polyphosphate and Lon protease.

Quantifying the forces driving cell-cell adhesion in a fungal pathogen

Owing to its ability to form biofilms on implanted medical devices, the fungal pathogen Candida albicans causes frequent infections in humans. A hallmark of C. albicans biofilms is the presence of two types of cells, budding yeast cells and growing hyphae, which are bound together and embedded in extracellular matrix material. Although cell-cell adhesion is critical to biofilm formation, architecture, and cohesion, we know little about the fundamental forces behind this interaction. Here, we use single-cell force spectroscopy to quantify the forces engaged in yeast-hyphae adhesion, focusing on the role of Als (agglutinin-like sequence) proteins as prototypes of cell adhesion molecules. We show that adhesion between individual yeast and hyphal cells involves strong, short-range cohesive interactions (1.1 ± 0.2 nN; 86 ± 33 nm) and weak, long-range tether interactions (0.4 ± 0.2 nN; 234 ± 81 nm). Control experiments demonstrate that these interactions originate from cell surface proteins that are specific to C. albicans. Using mutant strains deficient for Als expression, we find that Als3 proteins, primarily expressed on the germ tube, play a key role in establishing strong cohesive adhesion. We suggest a model in which cohesive adhesion during biofilm formation originates from tight hydrophobic interactions between Als tandem repeat domains on adjacent cells. When subjected to force, the two interacting cell surfaces detach, but the cell bodies remain tethered through macromolecular extensions. Our results represent the first direct, noninvasive measurement of adhesion forces between interacting fungal cells and provide novel insights into the molecular origin of the cohesive strength of fungal biofilms.

Improved statistical analysis of low abundance phenomena in bimodal bacterial populations

Accurate detection of subpopulation size determinations in bimodal populations remains problematic yet it represents a powerful way by which cellular heterogeneity under different environmental conditions can be compared. So far, most studies have relied on qualitative descriptions of population distribution patterns, on population-independent descriptors, or on arbitrary placement of thresholds distinguishing biological ON from OFF states. We found that all these methods fall short of accurately describing small population sizes in bimodal populations. Here we propose a simple, statistics-based method for the analysis of small subpopulation sizes for use in the free software environment R and test this method on real as well as simulated data. Four so-called population splitting methods were designed with different algorithms that can estimate subpopulation sizes from bimodal populations. All four methods proved more precise than previously used methods when analyzing subpopulation sizes of transfer competent cells arising in populations of the bacterium Pseudomonas knackmussii B13. The methods’ resolving powers were further explored by bootstrapping and simulations. Two of the methods were not severely limited by the proportions of subpopulations they could estimate correctly, but the two others only allowed accurate subpopulation quantification when this amounted to less than 25% of the total population. In contrast, only one method was still sufficiently accurate with subpopulations smaller than 1% of the total population. This study proposes a number of rational approximations to quantifying small subpopulations and offers an easy-to-use protocol for their implementation in the open source statistical software environment R.

Forces driving the attachment of Staphylococcus epidermidis to fibrinogen-coated surfaces

Cell surface proteins of bacteria play essential roles in mediating the attachment of pathogens to host tissues and, therefore, represent key targets for anti-adhesion therapy. In the opportunistic pathogen Staphylococcus epidermidis , the adhesion protein SdrG mediates attachment of bacteria to the blood plasma protein fibrinogen (Fg) through a binding mechanism that is not yet fully understood. We report the direct measurement of the forces driving the adhesion of S. epidermidis to Fg-coated substrates using single-cell force spectroscopy. We found that the S. epidermidis -Fg adhesion force is of ~150 pN magnitude and that the adhesion strength and adhesion probability strongly increase with the interaction time, suggesting that the adhesion process involves time-dependent conformational changes. Control experiments with mutant bacteria lacking SdrG and substrates coated with the Fg β(6-20) peptide, instead of the full Fg protein, demonstrate that these force signatures originate from the rupture of specific bonds between SdrG and its peptide ligand. Collectively, our results are consistent with a dynamic, multi-step ligand-binding mechanism called "dock, lock, and latch".

Recent advances in the development of single cell analysis--a review

Development of techniques for the analysis of the content of individual cells represents an important direction in modern bioanalytical chemistry. While the analysis of chromosomes, organelles, or location of selected proteins has been traditionally the domain of microscopic techniques, the advances in miniaturized analytical systems bring new possibilities for separations and detections of molecules inside the individual cells including smaller molecules such as hormones or metabolites. It should be stressed that the field of single cell analysis is very broad, covering advanced optical, electrochemical and mass spectrometry instrumentation, sensor technology and separation techniques. The number of papers published on single cell analysis has reached several hundred in recent years. Thus a complete literature coverage is beyond the limits of a journal article. The following text provides a critical overview of some of the latest developments with the main focus on mass spectrometry, microseparation methods, electrophoresis in capillaries and microfluidic devices and respective detection techniques for performing single cell analyses.

Going local: technologies for exploring bacterial microenvironments

Microorganisms lead social lives and use coordinated chemical and physical interactions to establish complex communities. Mechanistic insights into these interactions have revealed that there are remarkably intricate systems for coordinating microbial behaviour, but little is known about how these interactions proceed in the spatially organized communities that are found in nature. This Review describes the technologies available for spatially organizing small microbial communities and the analytical methods for characterizing the chemical environment surrounding these communities. Together, these complementary technologies have provided novel insights into the impact of spatial organization on both microbial behaviour and the development of phenotypic heterogeneity within microbial communities.

Deciphering the single-cell omic: innovative application for translational medicine

Traditional technologies to investigate system biology are limited by the detection of parameters resulting from the averages of large populations of cells, missing cells produced in small numbers, and attempting to uniform the heterogeneity. The advent of proteomics and genomics at a single-cell level has set the basis for an outstanding improvement in analytical technology and data acquisition. It has been well demonstrated that cellular heterogeneity is closely related to numerous stochastic transcriptional events leading to variations in patterns of expression among single genetically identical cells. The new-generation technology of single-cell analysis is able to better characterize a cell's population, identifying and differentiating outlier cells, in order to provide both a single-cell experiment and a corresponding bulk measurement, through the identification, quantification and characterization of all system biology aspects (genomics, transcriptomics, proteomics, metabolomics, degradomics and fluxomics). The movement of omics into single-cell analysis represents a significant and outstanding shift.

Dormancy is not necessary or sufficient for bacterial persistence

The antibiotic tolerances of bacterial persisters have been attributed to transient dormancy. While persisters have been observed to be growth inhibited prior to antibiotic exposure, we sought to determine whether such a trait was essential to the phenotype. Furthermore, we sought to provide direct experimental evidence of the persister metabolic state so as to determine whether the common assumption of metabolic inactivity was valid. Using fluorescence-activated cell sorting (FACS), a fluorescent indicator of cell division, a fluorescent measure of metabolic activity, and persistence assays, we found that bacteria that are rapidly growing prior to antibiotic exposure can give rise to persisters and that a lack of replication or low metabolic activity prior to antibiotic treatment simply increases the likelihood that a cell is a persister. Interestingly, a lack of significant growth or metabolic activity does not guarantee persistence, as the majority of even "dormant" subpopulations (>99%) were not persisters. These data suggest that persistence is far more complex than dormancy and point to additional characteristics needed to define the persister phenotype.

Somewhat in control--the role of transcription in regulating microbial metabolic fluxes

The most common way for microbes to control their metabolism is by controlling enzyme levels through transcriptional regulation. Yet recent studies have shown that in many cases, perturbations to the transcriptional regulatory network do not result in altered metabolic phenotypes on the level of the flux distribution. We suggest that this may be a consequence of cells protecting their metabolism against stochastic fluctuations in expression as well as enabling a fast response for those fluxes that may need to be changed quickly. Furthermore, it is impossible for a regulatory program to guarantee optimal expression levels in all conditions. Several studies have found examples of demonstrably suboptimal regulation of gene expression, and improvements to the regulatory network have been investigated in laboratory evolution experiments.

Single-molecule methods for studying gene regulation in vivo

The recent emergence of new experimental tools employing sensitive fluorescence detection in vivo has made it possible to visualize various aspects of gene regulation at the single-molecule level in the native, intracellular context. In this review, we will first describe general considerations for in vivo, single-molecule fluorescence detection of DNA, mRNA, and protein molecules involved in gene regulation. We will then give an overview of the rapidly evolving suite of molecular tools available for observing gene regulation in vivo and discuss new insights they have brought into gene regulation.

A novel staining protocol for multiparameter assessment of cell heterogeneity in Phormidium populations (cyanobacteria) employing fluorescent dyes

Bacterial populations display high heterogeneity in viability and physiological activity at the single-cell level, especially under stressful conditions. We demonstrate a novel staining protocol for multiparameter assessment of individual cells in physiologically heterogeneous populations of cyanobacteria. The protocol employs fluorescent probes, i.e., redox dye 5-cyano-2,3-ditolyl tetrazolium chloride, ‘dead cell’ nucleic acid stain SYTOX Green, and DNA-specific fluorochrome 4′,6-diamidino-2-phenylindole, combined with microscopy image analysis. Our method allows simultaneous estimates of cellular respiration activity, membrane and nucleoid integrity, and allows the detection of photosynthetic pigments fluorescence along with morphological observations. The staining protocol has been adjusted for, both, laboratory and natural populations of the genus Phormidium (Oscillatoriales), and tested on 4 field-collected samples and 12 laboratory strains of cyanobacteria. Based on the mentioned cellular functions we suggest classification of cells in cyanobacterial populations into four categories: (i) active and intact; (ii) injured but active; (iii) metabolically inactive but intact; (iv) inactive and injured, or dead.

Mapping of bacterial biofilm local mechanics by magnetic microparticle actuation

Most bacteria live in the form of adherent communities forming three-dimensional material anchored to artificial or biological surfaces, with profound impact on many human activities. Biofilms are recognized as complex systems but their physical properties have been mainly studied from a macroscopic perspective. To determine biofilm local mechanical properties, reveal their potential heterogeneity, and investigate their relation to molecular traits, we have developed a seemingly new microrheology approach based on magnetic particle infiltration in growing biofilms. Using magnetic tweezers, we achieved what was, to our knowledge, the first three-dimensional mapping of the viscoelastic parameters on biofilms formed by the bacterium Escherichia coli. We demonstrate that its mechanical profile may exhibit elastic compliance values spread over three orders of magnitude in a given biofilm. We also prove that heterogeneity strongly depends on external conditions such as growth shear stress. Using strains genetically engineered to produce well-characterized cell surface adhesins, we show that the mechanical profile of biofilm is exquisitely sensitive to the expression of different surface appendages such as F pilus or curli. These results provide a quantitative view of local mechanical properties within intact biofilms and open up an additional avenue for elucidating the emergence and fate of the different microenvironments within these living materials.

Comprehensive analysis of OmpR phosphorylation, dimerization, and DNA binding supports a canonical model for activation

The OmpR/PhoB family of response regulators (RRs) is the largest class of two-component system signal transduction proteins. Extensive biochemical and structural characterization of these transcription factors has provided insights into their activation and DNA-binding mechanisms. For the most part, OmpR/PhoB family proteins are thought to become activated through phosphorylation from their cognate histidine kinase partners, which in turn facilitates an allosteric change in the RR, enabling homodimerization and subsequently enhanced DNA binding. Incongruently, it has been suggested that OmpR, the eponymous member of this RR family, becomes activated via different mechanisms, whereby DNA binding plays a central role in facilitating dimerization and phosphorylation. Characterization of the rate and extent of the phosphorylation of OmpR and OmpR DNA-binding mutants following activation of the EnvZ/OmpR two-component system shows that DNA binding is not essential for phosphorylation of OmpR in vivo. In addition, detailed analyses of the energetics of DNA binding and dimerization of OmpR in both its unphosphorylated and phosphorylated state indicate that phosphorylation enhances OmpR dimerization and that this dimerization enhancement is the energetic driving force for phosphorylation-mediated regulation of OmpR-DNA binding. These findings suggest that OmpR phosphorylation-mediated activation follows the same paradigm as the other members of the OmpR/PhoB family of RRs in contrast to previously proposed models of OmpR activation.

A single-cell perspective on non-growing but metabolically active (NGMA) bacteria

A long-standing and fundamental problem in microbiology is the non-trivial discrimination between live and dead cells. The existence of physically intact and possibly viable bacterial cells that fail to replicate during a more or less protracted period of observation, despite environmental conditions that are ostensibly propitious for growth, has been extensively documented in many different organisms. In clinical settings, non-culturable cells may contribute to non-apparent infections capable of reactivating after months or years of clinical latency, a phenomenon that has been well documented in the specific case of Mycobacterium tuberculosis. The prevalence of these silent but potentially problematic bacterial reservoirs has been highlighted by classical approaches such as limiting culture dilution till extinction of growing cells, followed by resuscitation of apparently "viable but non-culturable" (VBNC) subpopulations. Although these assays are useful to demonstrate the presence of VBNC cells in a population, they are effectively retrospective and are not well suited to the analysis of non-replicating cells per se. Here, we argue that research on a closely related problem, which we shall refer to as the "non-growing but metabolically active" state, is poised to advance rapidly thanks to the recent development of novel technologies and methods for real-time single-cell analysis. In particular, the combination of fluorescent reporter dyes and strains, microfluidic and microelectromechanical systems, and time-lapse fluorescence microscopy offers tremendous and largely untapped potential for future exploration of the physiology of non-replicating cells.

Monitoring of population dynamics of Corynebacterium glutamicum by multiparameter flow cytometry

Phenotypic variation of microbial populations is a well-known phenomenon and may have significant impact on the success of industrial bioprocesses. Flow cytometry (FC) and the large repertoire of fluorescent dyes bring the high-throughput analysis of multiple parameters in single bacterial cells into reach. In this study, we evaluated a set of different fluorescent dyes for suitability in FC single cell analysis of the biotechnological platform organism Corynebacterium glutamicum. Already simple scattering properties of C. glutamicum cells in the flow cytometer were shown to provide valuable information on the growth activity of analysed cells. Furthermore, we used DAPI staining for a FC-based determination of the DNA content of C. glutamicum cells grown on standard minimal or complex media. Characteristic DNA patterns were observed mirroring the typical uncoupled DNA synthesis in the logarithmic (log) growth phase and are in agreement with a symmetric type of cell division of C. glutamicum. Application of the fluorescent dyes Syto 9, propidium iodide, and DiOC₂(3) allowed the identification of subpopulations with reduced viability and membrane potential within early log and stationary phase populations. The presented data highlight the potential of FC-based analyses for online monitoring of C. glutamicum bioprocesses and provide a first reference for future applications and protocols.

Pre-disposition and epigenetics govern variation in bacterial survival upon stress

Bacteria suffer various stresses in their unpredictable environment. In response, clonal populations may exhibit cell-to-cell variation, hypothetically to maximize their survival. The origins, propagation, and consequences of this variability remain poorly understood. Variability persists through cell division events, yet detailed lineage information for individual stress-response phenotypes is scarce. This work combines time-lapse microscopy and microfluidics to uniformly manipulate the environmental changes experienced by clonal bacteria. We quantify the growth rates and RpoH-driven heat-shock responses of individual Escherichia coli within their lineage context, stressed by low streptomycin concentrations. We observe an increased variation in phenotypes, as different as survival from death, that can be traced to asymmetric division events occurring prior to stress induction. Epigenetic inheritance contributes to the propagation of the observed phenotypic variation, resulting in three-fold increase of the RpoH-driven expression autocorrelation time following stress induction. We propose that the increased permeability of streptomycin-stressed cells serves as a positive feedback loop underlying this epigenetic effect. Our results suggest that stochasticity, pre-disposition, and epigenetic effects are at the source of stress-induced variability. Unlike in a bet-hedging strategy, we observe that cells with a higher investment in maintenance, measured as the basal RpoH transcriptional activity prior to antibiotic treatment, are more likely to give rise to stressed, frail progeny.

A microfluidic platform for rapid, stress-induced antibiotic susceptibility testing of Staphylococcus aureus

The emergence and spread of bacterial resistance to ever increasing classes of antibiotics intensifies the need for fast phenotype-based clinical tests for determining antibiotic susceptibility. Standard susceptibility testing relies on the passive observation of bacterial growth inhibition in the presence of antibiotics. In this paper, we present a novel microfluidic platform for antibiotic susceptibility testing based on stress-activation of biosynthetic pathways that are the primary targets of antibiotics. We chose Staphylococcus aureus (S. aureus) as a model system due to its clinical importance, and we selected bacterial cell wall biosynthesis as the primary target of both stress and antibiotic. Enzymatic and mechanical stresses were used to damage the bacterial cell wall, and a β-lactam antibiotic interfered with the repair process, resulting in rapid cell death of strains that harbor no resistance mechanism. In contrast, resistant bacteria remained viable under the assay conditions. Bacteria, covalently-bound to the bottom of the microfluidic channel, were subjected to mechanical shear stress created by flowing culture media through the microfluidic channel and to enzymatic stress with sub-inhibitory concentrations of the bactericidal agent lysostaphin. Bacterial cell death was monitored via fluorescence using the Sytox Green dead cell stain, and rates of killing were measured for the bacterial samples in the presence and absence of oxacillin. Using model susceptible (Sanger 476) and resistant (MW2) S. aureus strains, a metric was established to separate susceptible and resistant staphylococci based on normalized fluorescence values after 60 min of exposure to stress and antibiotic. Because this ground-breaking approach is not based on standard methodology, it circumvents the need for minimum inhibitory concentration (MIC) measurements and long wait times. We demonstrate the successful development of a rapid microfluidic-based and stress-activated antibiotic susceptibility test by correctly designating the phenotypes of 16 additional clinically relevant S. aureus strains in a blinded study. In addition to future clinical utility, this method has great potential for studying the effects of various stresses on bacteria and their antibiotic susceptibility.

Investigating transcriptional states at single-cell-resolution

Gene expression analysis at single-cell-resolution is a powerful tool for uncovering individual cell differences within heterogeneous cell populations and complex tissues, which can provide invaluable insights into the extent of gene expression variability. Multi-dimensional information of gene expression at the level of the individual cell can help to identify distinct and rare molecular cell 'states' within populations and aid in unravelling genetic regulatory circuits. Gene expression analysis at the single-cell-level will also enhance our understanding of the molecular basis of aberrant cell states and disease development and holds great promise for the advancement of personalized medicine. We present approaches that provide large-scale views of gene expression at the level of the individual cell.

Isolated microbial single cells and resulting micropopulations grow faster in controlled environments

Singularized cells of Pichia pastoris, Hansenula polymorpha, and Corynebacterium glutamicum displayed specific growth rates under chemically and physically constant conditions that were consistently higher than those obtained in populations. This highlights the importance of single-cell analyses by uncoupling physiology and the extracellular environment, which is now possible using the Envirostat 2.0 concept.

Physiological heterogeneities in microbial populations and implications for physical stress tolerance

BACKGROUND

Traditionally average values of the whole population are considered when analysing microbial cell cultivations. However, a typical microbial population in a bioreactor is heterogeneous in most phenotypes measurable at a single-cell level. There are indications that such heterogeneity may be unfavourable on the one hand (reduces yields and productivities), but also beneficial on the other hand (facilitates quick adaptation to new conditions--i.e. increases the robustness of the fermentation process). Understanding and control of microbial population heterogeneity is thus of major importance for improving microbial cell factory processes.

RESULTS

In this work, a dual reporter system was developed and applied to map growth and cell fitness heterogeneities within budding yeast populations during aerobic cultivation in well-mixed bioreactors. The reporter strain, which was based on the expression of green fluorescent protein (GFP) under the control of the ribosomal protein RPL22a promoter, made it possible to distinguish cell growth phases by the level of fluorescence intensity. Furthermore, by exploiting the strong correlation of intracellular GFP level and cell membrane integrity it was possible to distinguish subpopulations with high and low cell membrane robustness and hence ability to withstand freeze-thaw stress. A strong inverse correlation between growth and cell membrane robustness was observed, which further supports the hypothesis that cellular resources are limited and need to be distributed as a trade-off between two functions: growth and robustness. In addition, the trade-off was shown to vary within the population, and the occurrence of two distinct subpopulations shifting between these two antagonistic modes of cell operation could be distinguished.

CONCLUSIONS

The reporter strain enabled mapping of population heterogeneities in growth and cell membrane robustness towards freeze-thaw stress at different phases of cell cultivation. The described reporter system is a valuable tool for understanding the effect of environmental conditions on population heterogeneity of microbial cells and thereby to understand cell responses during industrial process-like conditions. It may be applied to identify more robust subpopulations, and for developing novel strategies for strain improvement and process design for more effective bioprocessing.

Detecting sequence dependent transcriptional pauses from RNA and protein number time series

BACKGROUND

Evidence suggests that in prokaryotes sequence-dependent transcriptional pauses affect the dynamics of transcription and translation, as well as of small genetic circuits. So far, a few pause-prone sequences have been identified from in vitro measurements of transcription elongation kinetics.

RESULTS

Using a stochastic model of gene expression at the nucleotide and codon levels with realistic parameter values, we investigate three different but related questions and present statistical methods for their analysis. First, we show that information from in vivo RNA and protein temporal numbers is sufficient to discriminate between models with and without a pause site in their coding sequence. Second, we demonstrate that it is possible to separate a large variety of models from each other with pauses of various durations and locations in the template by means of a hierarchical clustering and a random forest classifier. Third, we introduce an approximate likelihood function that allows to estimate the location of a pause site.

CONCLUSIONS

This method can aid in detecting unknown pause-prone sequences from temporal measurements of RNA and protein numbers at a genome-wide scale and thus elucidate possible roles that these sequences play in the dynamics of genetic networks and phenotype.

Antibiotic transport in resistant bacteria: synchrotron UV fluorescence microscopy to determine antibiotic accumulation with single cell resolution

A molecular definition of the mechanism conferring bacterial multidrug resistance is clinically crucial and today methods for quantitative determination of the uptake of antimicrobial agents with single cell resolution are missing. Using the naturally occurring fluorescence of antibacterial agents after deep ultraviolet (DUV) excitation, we developed a method to non-invasively monitor the quinolones uptake in single bacteria. Our approach is based on a DUV fluorescence microscope coupled to a synchrotron beamline providing tuneable excitation from 200 to 600 nm. A full spectrum was acquired at each pixel of the image, to study the DUV excited fluorescence emitted from quinolones within single bacteria. Measuring spectra allowed us to separate the antibiotic fluorescence from the autofluorescence contribution. By performing spectroscopic analysis, the quantification of the antibiotic signal was possible. To our knowledge, this is the first time that the intracellular accumulation of a clinical antibiotic could be determined and discussed in relation with the level of drug susceptibility for a multiresistant strain. This method is especially important to follow the behavior of quinolone molecules at individual cell level, to quantify the intracellular concentration of the antibiotic and develop new strategies to combat the dissemination of MDR-bacteria. In addition, this original approach also indicates the heterogeneity of bacterial population when the same strain is under environmental stress like antibiotic attack.

A disposable picolitre bioreactor for cultivation and investigation of industrially relevant bacteria on the single cell level

In the continuously growing field of industrial biotechnology the scale-up from lab to industrial scale is still a major hurdle to develop competitive bioprocesses. During scale-up the productivity of single cells might be affected by bioreactor inhomogeneity and population heterogeneity. Currently, these complex interactions are difficult to investigate. In this report, design, fabrication and operation of a disposable picolitre cultivation system is described, in which environmental conditions can be well controlled on a short time scale and bacterial microcolony growth experiments can be observed by time-lapse microscopy. Three exemplary investigations will be discussed emphasizing the applicability and versatility of the device. Growth and analysis of industrially relevant bacteria with single cell resolution (in particular Escherichia coli and Corynebacterium glutamicum) starting from one single mother cell to densely packed cultures is demonstrated. Applying the picolitre bioreactor, 1.5-fold increased growth rates of C. glutamicum wild type cells were observed compared to typical 1 litre lab-scale batch cultivation. Moreover, the device was used to analyse and quantify the morphological changes of an industrially relevant l-lysine producer C. glutamicum after artificially inducing starvation conditions. Instead of a one week lab-scale experiment, only 1 h was sufficient to reveal the same information. Furthermore, time lapse microscopy during 24 h picolitre cultivation of an arginine producing strain containing a genetically encoded fluorescence sensor disclosed time dependent single cell productivity and growth, which was not possible with conventional methods.

Beyond homeostasis: a predictive-dynamic framework for understanding cellular behavior

Microbial regulatory strategies have long been understood in terms of the homeostatic framework, in which a response is interpreted as a restoring force counteracting the immediate intracellular consequences of a change in the environment. In this review, we summarize the breadth of recent discoveries of cellular behavior extending beyond the homeostatic framework. We argue that the nonrandom structure of native habitats makes environmental fluctuations inherently multidimensional. Beyond its utility for accurate perception of immediate events, the temporal regularity of this multidimensional correlation structure allows microbes to make predictions about the trajectory of their sensory environment. We describe recently discovered examples of such predictive behavior, their physiological benefits, and the underlying evolutionary forces shaping them. These observations compel us to go beyond homeostasis and consider a predictive-dynamic framework in which cellular behavior is orchestrated in response to the meaning of an environmental perturbation, not only its direct and immediate fitness consequences.

Using gene expression noise to understand gene regulation

Phenotypic variation is ubiquitous in biology and is often traceable to underlying genetic and environmental variation. However, even genetically identical cells in identical environments display variable phenotypes. Stochastic gene expression, or gene expression "noise," has been suggested as a major source of this variability, and its physiological consequences have been topics of intense research for the last decade. Several recent studies have measured variability in protein and messenger RNA levels, and they have discovered strong connections between noise and gene regulation mechanisms. When integrated with discrete stochastic models, measurements of cell-to-cell variability provide a sensitive "fingerprint" with which to explore fundamental questions of gene regulation. In this review, we highlight several studies that used gene expression variability to develop a quantitative understanding of the mechanisms and dynamics of gene regulation.

Nanoscale imaging of Bacillus thuringiensis flagella using atomic force microscopy

Because bacterial flagella play essential roles in various processes (motility, adhesion, host interactions, secretion), studying their expression in relation to function is an important challenge. Here, we use atomic force microscopy (AFM) to gain insight into the nanoscale surface properties of two wild-type and four mutant strains of Bacillus thuringiensis exhibiting various levels of flagellation. We show that, unlike AFM in liquid, AFM in air is a simple and reliable approach to observe the morphological details of the bacteria, and to quantify the density and dimensions of their flagella. We found that the amount of flagella expressed by the six strains, as observed at the nanoscale, correlates with their microscopic swarming motility. These observations provide novel information on flagella expression in gram-positive bacteria and demonstrate the power of AFM in genetic studies for the fast assessment of the phenotypic characteristics of bacterial strains altered in cell surface appendages.

High-throughput examination of fluorescence resonance energy transfer-detected metal-ion response in mammalian cells

Fluorescence resonance energy transfer (FRET)-based genetically encoded metal-ion sensors are important tools for studying metal-ion dynamics in live cells. We present a time-resolved microfluidic flow cytometer capable of characterizing the FRET-based dynamic response of metal-ion sensors in mammalian cells at a throughput of 15 cells/s with a time window encompassing a few milliseconds to a few seconds after mixing of cells with exogenous ligands. We have used the instrument to examine the cellular heterogeneity of Zn(2+) and Ca(2+) sensor FRET response amplitudes and demonstrated that the cluster maps of the Zn(2+) sensor FRET changes resolve multiple subpopulations. We have also measured the in vivo sensor response kinetics induced by changes in Zn(2+) and Ca(2+) concentrations. We observed an ∼30 fold difference between the extracellular and intracellular sensors.

Responding to chemical gradients: bacterial chemotaxis

Chemotaxis allows bacteria to follow gradients of nutrients and other environmental stimuli. The bacterium Escherichia coli performs chemotaxis via a run-and-tumble strategy in which sensitive temporal comparisons lead to a biased random walk, with longer runs in the preferred gradient direction. The chemotaxis network of E. coli has developed over the years into one of the most thoroughly studied model systems for signal transduction and behavior, yielding general insights into such properties of cellular networks as signal amplification, signal integration, and robustness. Despite its relative simplicity, the operation of the E. coli chemotaxis network is highly refined and evolutionarily optimized at many levels. For example, recent studies revealed that the network adjusts its signaling properties dependent on the extracellular environment, apparently to optimize chemotaxis under particular conditions. The network can even utilize potentially detrimental stochastic fluctuations in protein levels and reaction rates to maximize the chemotactic performance of the population.

Locked nucleic acid and flow cytometry-fluorescence in situ hybridization for the detection of bacterial small noncoding RNAs

We describe the development and testing of a high-throughput method that enables the detection of small noncoding RNAs (ncRNAs) from single bacterial cells using locked nucleic acid probes (LNA) and flow cytometry-fluorescence in situ hybridization (flow-FISH). The LNA flow-FISH method and quantitative reverse transcription-PCR (qRT-PCR) were used to monitor the expression of three ncRNAs (6S, CsrB, and TPP-2) in Vibrio campbellii ATCC BAA-1116 cultures during lag phase, mid-log phase, and stationary phase. Both LNA flow-FISH and qRT-PCR revealed that CsrB and TPP-2 were highly expressed during lag phase but markedly reduced in mid-log phase and stationary phase, whereas 6S demonstrated no to little expression during lag phase but increased thereafter. Importantly, while LNA flow-FISH and qRT-PCR demonstrated similar overall expression trends, only LNA flow-FISH, which enabled the detection of ncRNAs in individual cells as opposed to the lysate-based ensemble measurements generated by qRT-PCR, was able to capture the cell-to-cell heterogeneity in ncRNA expression. As such, this study demonstrates a new method that simultaneously enables the in situ detection of ncRNAs and the determination of gene expression heterogeneity within an isogenic bacterial population.

Can a systems perspective help us appreciate the biological meaning of small effects?

The study of dramatic phenotypes has been pivotal to elucidating biological mechanisms. Effectively approaching low-magnitude quantitative phenotypes, a common outcome of systematic loss-of-function studies, will be critical for understanding how individual components of cells interact to generate functioning systems.