Microbial individuality: how single-cell heterogeneity enables population level strategies

Quantitative macromolecular patterns in phytoplankton communities resolved at the taxonomical level by single-cell Synchrotron FTIR-spectroscopy

BACKGROUND

Technical limitations regarding bulk analysis of phytoplankton biomass limit our comprehension of carbon fluxes in natural populations and, therefore, of carbon, nutrients and energy cycling in aquatic ecosystems. In this study, we took advantage of Synchrotron FTIR micro-spectroscopy and the partial least square regression (PLSr) algorithm to simultaneously quantify the protein, lipid and carbohydrate content at the single-cell level in a mock phytoplankton community (composed by a cyanobacterium, a green-alga and a diatom) grown at two temperatures (15 °C and 25 °C).

RESULTS

The PLSr models generated to quantify cell macromolecules presented high quality fit (R² ≥ 0.90) and low error of prediction (RMSEP 2-6% of dry weight). The regression coefficients revealed that the prediction of each macromolecule was not exclusively dependent on spectral features corresponding to that compound, but rather on all major macromolecular pools, reflecting adjustments in the overall cell carbon balance. The single-cell analysis, studied by means of Kernel density estimators, showed that the modes of density distribution of macromolecules were different at 15 °C and 25 °C. However, a substantial proportion of cells was biochemically identical at the two temperatures because of population heterogeneity.

CONCLUSIONS

The spectroscopic approach presented in this study allows the quantification of macromolecules in single phytoplankton cells. This method showed that population heterogeneity most likely ensures a backup of non-acclimated cells that may rapidly exploit new favourable niches. This finding may have important consequences for the ecology of phytoplankton populations and shows that the "average cell" concept might substantially limit our comprehension of population dynamics and biogeochemical cycles in aquatic ecosystems.

A modular atomic force microscopy approach reveals a large range of hydrophobic adhesion forces among bacterial members of the leaf microbiota

Bacterial adhesion is the initial step in surface colonization and community formation. At the single-cell level, atomic force microscopy (AFM) techniques have enabled the quantification of adhesive forces between bacteria and substrata. However, conventional techniques depend on the irreversible immobilization of cells onto cantilevers, thus hampering throughput. Here, we developed a modular AFM method to reversibly immobilize functionalized beads as surface mimic and to probe adhesion of individual bacteria. We performed single-cell force spectroscopies with phylogenetically diverse leaf isolates of various size and morphology. Adhesion measurement of 28 bacterial strains revealed large differences in hydrophobic interactions of about three orders of magnitude. The highest adhesion forces of up to 50 nN were recorded for members of the Gammaproteobacteria. The hydrophobicity of the different isolates correlated positively with the retention of bacteria observed in planta and might provide a basis for successful leaf colonization and potentially disease outbreaks of pathogens.

Complex Relationships between the Blue Pigment Marennine and Marine Bacteria of the Genus Vibrio

Marennine, the water-soluble blue pigment produced by the marine diatom Haslea ostrearia, is known to display antibacterial activities. Previous studies have demonstrated a prophylactic effect of marennine on bivalve larvae challenged with a pathogenic Vibrio splendidus, suggesting that the blue Haslea is a good candidate for applications in aquaculture as a source of a natural antimicrobial agent. Indeed, the genus Vibrio is ubiquitous in aquaculture ecosystems, and regular events of pathogenic invasion cause some of the biggest losses worldwide. To better characterize the effects of marennine on Vibrios, a panel of 30 Vibrio strains belonging to 10 different species was tested, including bivalve pathogenic species (e.g., Vibrio crassostreae and Vibrio harveyi). Vibrio strains were first exposed to 10 and 25 µg mL^-1 of Blue Water (BW), a concentrated culture supernatant of H. ostrearia containing marennine. This screening evidenced a great diversity in responses, from growth stimulation to a total inhibition, at both the interspecific or intraspecific level. In a second series of experiments, 10 Vibrio strains were exposed to BW at concentrations ranging from 5 to 80 µg mL^-1. The highest concentrations of BW did not systematically result in the highest growth inhibition as hormetic responses-opposite effects regarding the concentration-were occasionally evidenced. The relationships between marennine and Vibrio strains appear more complex than expected and justify further study-in particular, on the mechanisms of action-before considering applications as a natural prophylactic or antibiotic agent in aquaculture.

The effect of acetate on population heterogeneity in different cellular characteristics of Escherichia coli in aerobic batch cultures

Acetate as the major by-product in industrial-scale bioprocesses with Escherichia coli is found to decrease process efficiency as well as to be toxic to cells, which has several effects like a significant induction of cellular stress responses. However, the underlying phenomena are poorly explored. Therefore, we studied time-resolved population heterogeneity of the E. coli growth reporter strain MG1655/pGS20PrrnBGFPAAV expressing destabilized green fluorescent protein during batch growth on acetate and glucose as sole carbon sources. Additionally, we applied five fluorescent stains targeting different cellular properties (viability as well as metabolic and respiratory activity). Quantitative analysis of flow cytometry data verified that bacterial populations in the bioreactor are more heterogeneous in growth as well as stronger metabolically challenged during growth on acetate as sole carbon source, compared to growth on glucose or acetate after diauxic shift. Interestingly, with acetate as sole carbon source, significant subpopulations were found with some cells that seem to be more robust than the rest of the population. In conclusion, following batch cultures population heterogeneity was evident in all measured parameters. Our approach enabled a deeper study of heterogeneity during growth on the favored substrate glucose as well as on the toxic by-product acetate. Using a combination of activity fluorescent dyes proved to be an accurate and fast alternative as well as a supplement to the use of a reporter strain. However, the choice of combination of stains should be well considered depending on which population traits to aim for.

Hemizygosity Enables a Mutational Transition Governing Fungal Virulence and Commensalism

Candida albicans is a commensal fungus of human gastrointestinal and reproductive tracts, but also causes life-threatening systemic infections. The balance between colonization and pathogenesis is associated with phenotypic plasticity, with alternative cell states producing different outcomes in a mammalian host. Here, we reveal that gene dosage of a master transcription factor regulates cell differentiation in diploid C. albicans cells, as EFG1 hemizygous cells undergo a phenotypic transition inaccessible to "wild-type" cells with two functional EFG1 alleles. Notably, clinical isolates are often EFG1 hemizygous and thus licensed to undergo this transition. Phenotypic change corresponds to high-frequency loss of the functional EFG1 allele via de novo mutation or gene conversion events. This phenomenon also occurs during passaging in the gastrointestinal tract with the resulting cell type being hypercompetitive for commensal and systemic infections. A "two-hit" genetic model therefore underlies a key phenotypic transition in C. albicans that enables adaptation to host niches.

Shortsighted Evolution Constrains the Efficacy of Long-Term Bet Hedging

To survive unpredictable environmental change, many organisms adopt bet-hedging strategies that are initially costly but provide a long-term fitness benefit. The temporal extent of these deferred fitness benefits determines whether bet-hedging organisms can survive long enough to realize them. In this article, we examine a model of microbial bet hedging in which there are two paths to extinction: unpredictable environmental change and demographic stochasticity. In temporally correlated environments, these drivers of extinction select for different switching strategies. Rapid phenotype switching ensures survival in the face of unpredictable environmental change, while slower-switching organisms become extinct. However, when both switching strategies are present in the same population, then demographic stochasticity-enforced by a limited population size-leads to extinction of the faster-switching organism. As a result, we find a novel form of evolutionary suicide whereby selection in a fluctuating environment can favor bet-hedging strategies that ultimately increase the risk of extinction. Population structures with multiple subpopulations and dispersal can reduce the risk of extinction from unpredictable environmental change and shift the balance so as to facilitate the evolution of slower-switching organisms.

Monitoring Phenotypic Switching in Candida albicans and the Use of Next-Gen Fluorescence Reporters

Candida albicans is an opportunistic human fungal pathogen that is able to cause both mucosal and systemic infections. It is also a frequent human commensal, where it is typically found inhabiting multiple niches including the gastrointestinal tract. One of the most remarkable features of C. albicans biology is its ability to undergo heritable and reversible switching between different phenotypic states, a phenomenon known as phenotypic switching. This is best exemplified by the white-opaque switch, in which cells undergo epigenetic transitions between two alternative cellular states. Here, we describe assays to quantify the frequency of switching between states, as well as methods to help identify cells in different phenotypic states. We also describe the use of environmental cues that can induce switching into either the white or opaque state. Finally, we introduce the use of mNeonGreen and mScarlet fluorescent proteins that have been optimized for use in C. albicans and which outperform commonly used fluorescent proteins for both fluorescence microscopy and flow cytometry. © 2019 by John Wiley & Sons, Inc.

The Role of the Host in Driving Phenotypic Heterogeneity in Salmonella

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

Intrinsic and extrinsic noise of gene expression in lineage trees

Cell-to-cell heterogeneity is driven by stochasticity in intracellular reactions and the population dynamics. While these sources are usually studied separately, we develop an agent-based framework that accounts for both factors while tracking every single cell of a growing population. Apart from the common intrinsic variability, the framework also predicts extrinsic noise without the need to introduce fluctuating rate constants. Instead, extrinsic fluctuations are explained by cell cycle fluctuations and differences in cell age. We provide explicit formulas to quantify mean molecule numbers, intrinsic and extrinsic noise statistics in two-colour experiments. We find that these statistics differ significantly depending on the experimental setup used to observe the cells. We illustrate this fact using (i) averages over an isolated cell lineage tracked over many generations as observed in the mother machine, (ii) population snapshots with known cell ages as recorded in time-lapse microscopy, and (iii) snapshots with unknown cell ages as measured from static images or flow cytometry. Applying the method to models of stochastic gene expression and feedback regulation elucidates that isolated lineages, as compared to snapshot data, can significantly overestimate the mean number of molecules, overestimate extrinsic noise but underestimate intrinsic noise and have qualitatively different sensitivities to cell cycle fluctuations.

Widespread inter-individual gene expression variability in Arabidopsis thaliana

A fundamental question in biology is how gene expression is regulated to give rise to a phenotype. However, transcriptional variability is rarely considered although it could influence the relationship between genotype and phenotype. It is known in unicellular organisms that gene expression is often noisy rather than uniform, and this has been proposed to be beneficial when environmental conditions are unpredictable. However, little is known about inter-individual transcriptional variability in multicellular organisms. Using transcriptomic approaches, we analysed gene expression variability between individual Arabidopsis thaliana plants growing in identical conditions over a 24-h time course. We identified hundreds of genes that exhibit high inter-individual variability and found that many are involved in environmental responses, with different classes of genes variable between the day and night. We also identified factors that might facilitate gene expression variability, such as gene length, the number of transcription factors regulating the genes and the chromatin environment. These results shed new light on the impact of transcriptional variability in gene expression regulation in plants.

Sources, propagation and consequences of stochasticity in cellular growth

Growth impacts a range of phenotypic responses. Identifying the sources of growth variation and their propagation across the cellular machinery can thus unravel mechanisms that underpin cell decisions. We present a stochastic cell model linking gene expression, metabolism and replication to predict growth dynamics in single bacterial cells. Alongside we provide a theory to analyse stochastic chemical reactions coupled with cell divisions, enabling efficient parameter estimation, sensitivity analysis and hypothesis testing. The cell model recovers population-averaged data on growth-dependence of bacterial physiology and how growth variations in single cells change across conditions. We identify processes responsible for this variation and reconstruct the propagation of initial fluctuations to growth and other processes. Finally, we study drug-nutrient interactions and find that antibiotics can both enhance and suppress growth heterogeneity. Our results provide a predictive framework to integrate heterogeneous data and draw testable predictions with implications for antibiotic tolerance, evolutionary and synthetic biology.

The drivers of growth rate variability in bacteria are yet unknown. Here, the authors present a theory to predict the growth dynamics of individual cells and use a stochastic cell model integrating metabolism, gene expression and replication to identify the processes that underlie growth variation.

Single-cell Raman spectroscopy reveals microsporidia spore heterogeneity in various insect hosts

Single-cell Raman spectroscopy was used to analyze the spore heterogeneity of 16 microsporidia strains from various insect hosts in order to better understand the basic biology of microsporidia. The Raman spectrum of a single spore revealed basic spore composition, and microsporidia spores in various hosts were found to be rich in trehalose. Principal component analysis and Raman intensity showed obvious heterogeneity in the trehalose, nucleic acid, and protein content of various spores; however, there was no correlation between various spore groups and host type. Trehalose content correlated with spore infectivity on Bombyx mori. Raman spectroscopy is an excellent tool for label-free investigation of intercellular molecular constituents, providing insight into the heterogeneity of microsporidia spores.

Bimodal Expression of the Salmonella Typhimurium spv Operon

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

Ultra-high throughput functional enrichment of large monoamine oxidase (MAO-N) libraries by fluorescence activated cell sorting

Directed evolution enables the improvement and optimisation of enzymes for particular applications and is a valuable tool for biotechnology and synthetic biology. However, studies are often limited in their scope by the inability to screen very large numbers of variants to identify improved enzymes. One class of enzyme for which a universal, operationally simple ultra-high throughput (>106 variants per day) assay is not available is flavin adenine dinucleotide (FAD) dependent oxidases. The current high throughput assay involves a visual, colourimetric, colony-based screen, however this is not suitable for very large libraries and does not enable quantification of the relative fitness of variants. To address this, we describe an optimised method for the sensitive detection of oxidase activity within single Escherichia coli (E. coli) cells, using the monoamine oxidase from Aspergillus niger, MAO-N, as a model system. In contrast to other methods for the screening of oxidase activity in vivo, this method does not require cell surface expression, emulsion formation or the addition of an extracellular peroxidase. Furthermore, we show that fluorescence activated cell sorting (FACS) of large libraries derived from MAO-N under the assay conditions can enrich the library in functional variants at much higher rates than via the colony-based method. We demonstrate its use for directed evolution by identifying a new mutant of MAO-N with improved activity towards a novel secondary amine substrate. This work demonstrates, for the first time, an ultra-high throughput screening methodology widely applicable for the directed evolution of FAD dependent oxidases in E. coli.

Rocking Aspergillus: morphology-controlled cultivation of Aspergillus niger in a wave-mixed bioreactor for the production of secondary metabolites

Background

Filamentous fungi including Aspergillus niger are cell factories for the production of organic acids, proteins and bioactive compounds. Traditionally, stirred-tank reactors (STRs) are used to cultivate them under highly reproducible conditions ensuring optimum oxygen uptake and high growth rates. However, agitation via mechanical stirring causes high shear forces, thus affecting fungal physiology and macromorphologies. Two-dimensional rocking-motion wave-mixed bioreactor cultivations could offer a viable alternative to fungal cultivations in STRs, as comparable gas mass transfer is generally achievable while deploying lower friction and shear forces. The aim of this study was thus to investigate for the first time the consequences of wave-mixed cultivations on the growth, macromorphology and product formation of A. niger.

Results

We investigated the impact of hydrodynamic conditions on A. niger cultivated at a 5 L scale in a disposable two-dimensional rocking motion bioreactor (CELL-tainer^®) and a BioFlo STR (New Brunswick^®), respectively. Two different A. niger strains were analysed, which produce heterologously the commercial drug enniatin B. Both strains expressed the esyn1 gene that encodes a non-ribosomal peptide synthetase ESYN under control of the inducible Tet-on system, but differed in their dependence on feeding with the precursors d-2-hydroxyvaleric acid and l-valine. Cultivations of A. niger in the CELL-tainer resulted in the formation of large pellets, which were heterogeneous in size (diameter 300–800 μm) and not observed during STR cultivations. When talcum microparticles were added, it was possible to obtain a reduced pellet size and to control pellet heterogeneity (diameter 50–150 μm). No foam formation was observed under wave-mixed cultivation conditions, which made the addition of antifoam agents needless. Overall, enniatin B titres of about 1.5–2.3 g L⁻¹ were achieved in the CELL-tainer^® system, which is about 30–50% of the titres achieved under STR conditions.

Conclusions

This is the first report studying the potential use of single-use wave-mixed reactor systems for the cultivation of A. niger. Although final enniatin yields are not competitive yet with titres achieved under STR conditions, wave-mixed cultivations open up new avenues for the cultivation of shear-sensitive mutant strains as well as high cell-density cultivations.

Making sense of snapshot data: ergodic principle for clonal cell populations

Population growth is often ignored when quantifying gene expression levels across clonal cell populations. We develop a framework for obtaining the molecule number distributions in an exponentially growing cell population taking into account its age structure. In the presence of generation time variability, the average acquired across a population snapshot does not obey the average of a dividing cell over time, apparently contradicting ergodicity between single cells and the population. Instead, we show that the variation observed across snapshots with known cell age is captured by cell histories, a single-cell measure obtained from tracking an arbitrary cell of the population back to the ancestor from which it originated. The correspondence between cells of known age in a population with their histories represents an ergodic principle that provides a new interpretation of population snapshot data. We illustrate the principle using analytical solutions of stochastic gene expression models in cell populations with arbitrary generation time distributions. We further elucidate that the principle breaks down for biochemical reactions that are under selection, such as the expression of genes conveying antibiotic resistance, which gives rise to an experimental criterion with which to probe selection on gene expression fluctuations.

A bacterial signaling system regulates noise to enable bet hedging

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

Complex microbial systems across different levels of description

Complex biological systems offer a variety of interesting phenomena at the different physical scales. With increasing abstraction, details of the microscopic scales can often be extrapolated to average or typical macroscopic properties. However, emergent properties and cross-scale interactions can impede naïve abstractions and necessitate comprehensive investigations of these complex systems. In this review paper, we focus on microbial communities, and first, summarize a general hierarchy of relevant scales and description levels to understand these complex systems: (1) genetic networks, (2) single cells, (3) populations, and (4) emergent multi-cellular properties. Second, we employ two illustrating examples, microbial competition and biofilm formation, to elucidate how cross-scale interactions and emergent properties enrich the observed multi-cellular behavior in these systems. Finally, we conclude with pointing out the necessity of multi-scale investigations to understand complex biological systems and discuss recent investigations.

Single cell assessment of yeast metabolic engineering for enhanced lipid production using Raman and AFM-IR imaging

BACKGROUND

Biodiesel is a valuable renewable fuel made from derivatized fatty acids produced in plants, animals, and oleaginous microbes. Of the latter, yeasts are of special interest due to their wide use in biotechnology, ability to synthesize fatty acids and store large amounts of triacylglycerols while utilizing non-food carbon sources. While yeast efficiently produce lipids, genetic modification and indeed, lipid pathway metabolic engineering, is usually required for cost-effective production. Traditionally, gas chromatography (GC) is used to measure fatty acid production and to track the success of a metabolic engineering strategy in a microbial culture; here we have employed vibrational spectroscopy approaches at population and single cell level of engineered yeast while simultaneously investigating metabolite levels in subcellular structures.

RESULTS

Firstly, a strong correlation (r² > 0.99) was established between Fourier transform infrared (FTIR) lipid in intact cells and GC analysis of fatty acid methyl esters in the differently engineered strains. Confocal Raman spectroscopy of individual cells carrying genetic modifications to enhance fatty acid synthesis and lipid accumulation revealed changes to the lipid body (LB), the storage organelle for lipids in yeast, with their number increasing markedly (up to tenfold higher); LB size was almost double in the strain that also expressed a LB stabilizing gene but considerable variation was also noted between cells. Raman spectroscopy revealed a clear trend toward reduced unsaturated fatty acid content in lipids of cells carrying more complex metabolic engineering. Atomic force microscopy-infrared spectroscopy (AFM-IR) analysis of individual cells indicated large differences in subcellular constituents between strains: cells of the most highly engineered strain had elevated lipid and much reduced carbohydrate in their cytoplasm compared with unmodified cells.

CONCLUSIONS

Vibrational spectroscopy analysis allowed the simultaneous measurement of strain variability in metabolite production and impact on cellular structures as a result of different gene introductions or knockouts, within a lipid metabolic engineering strategy and these inform the next steps in comprehensive lipid engineering. Additionally, single cell spectroscopic analysis measures heterogeneity in metabolite production across microbial cultures under genetic modification, an emerging issue for efficient biotechnological production.

Population heterogeneity in microbial bioprocesses: origin, analysis, mechanisms, and future perspectives

Population heterogeneity is omnipresent in all bioprocesses even in homogenous environments. Its origin, however, is only so well understood that potential strategies like bet-hedging, noise in gene expression and division of labour that lead to population heterogeneity can be derived from experimental studies simulating the dynamics in industrial scale bioprocesses. This review aims at summarizing the current state of the different parts of single cell studies in bioprocesses. This includes setups to visualize different phenotypes of single cells, computational approaches connecting single cell physiology with environmental influence and special cultivation setups like scale-down reactors that have been proven to be useful to simulate large-scale conditions. A step in between investigation of populations and single cells is studying subpopulations with distinct properties that differ from the rest of the population with sub-omics methods which are also presented here. Moreover, the current knowledge about population heterogeneity in bioprocesses is summarized for relevant industrial production hosts and mixed cultures, as they provide the unique opportunity to distribute metabolic burden and optimize production processes in a way that is impossible in traditional monocultures. In the end, approaches to explain the underlying mechanism of population heterogeneity and the evidences found to support each hypothesis are presented. For instance, population heterogeneity serving as a bet-hedging strategy that is used as coordinated action against bioprocess-related stresses while at the same time spreading the risk between individual cells as it ensures the survival of least a part of the population in any environment the cells encounter.

Programmed cell death can increase the efficacy of microbial bet -hedging

Programmed cell death (PCD) occurs in both unicellular and multicellular organisms. While PCD plays a key role in the development and maintenance of multicellular organisms, explaining why single-celled organisms would evolve to actively commit suicide has been far more challenging. Here, we explore the potential for PCD to act as an accessory to microbial bet-hedging strategies that utilize stochastic phenotype switching. We consider organisms that face unpredictable and recurring disasters, in which fitness depends on effective phenotypic diversification. We show that when reproductive opportunities are limited by carrying capacity, PCD drives population turnover, providing increased opportunities for phenotypic diversification through stochastic phenotype switching. The main cost of PCD, providing resources for growth to a PCD(−) competitor, is ameliorated by genetic assortment in spatially structured populations. Using agent -based simulations, we explore how basic demographic factors, namely bottlenecks and local dispersal, can generate sufficient spatial structure to favor the evolution of high PCD rates.

Beyond the bulk: disclosing the life of single microbial cells

Microbial single cell analysis has led to discoveries that are beyond what can be resolved with population-based studies. It provides a pristine view of the mechanisms that organize cellular physiology, unbiased by population heterogeneity or uncontrollable environmental impacts. A holistic description of cellular functions at the single cell level requires analytical concepts beyond the miniaturization of existing technologies, defined but uncontrolled by the biological system itself. This review provides an overview of the latest advances in single cell technologies and demonstrates their potential. Opportunities and limitations of single cell microbiology are discussed using selected application-related examples.

Engineering Microbial Metabolite Dynamics and Heterogeneity

As yields for biological chemical production in microorganisms approach their theoretical maximum, metabolic engineering requires new tools, and approaches for improvements beyond what traditional strategies can achieve. Engineering metabolite dynamics and metabolite heterogeneity is necessary to achieve further improvements in product titers, productivities, and yields. Metabolite dynamics, the ensemble change in metabolite concentration over time, arise from the need for microbes to adapt their metabolism in response to the extracellular environment and are important for controlling growth and productivity in industrial fermentations. Metabolite heterogeneity, the cell-to-cell variation in a metabolite concentration in an isoclonal population, has a significant impact on ensemble productivity. Recent advances in single cell analysis enable a more complete understanding of the processes driving metabolite heterogeneity and reveal metabolic engineering targets. The authors present an overview of the mechanistic origins of metabolite dynamics and heterogeneity, why they are important, their potential effects in chemical production processes, and tools and strategies for engineering metabolite dynamics and heterogeneity. The authors emphasize that the ability to control metabolite dynamics and heterogeneity will bring new avenues of engineering to increase productivity of microbial strains.

Bioprocess scale-up/down as integrative enabling technology: from fluid mechanics to systems biology and beyond

Efficient optimization of microbial processes is a critical issue for achieving a number of sustainable development goals, considering the impact of microbial biotechnology in agrofood, environment, biopharmaceutical and chemical industries. Many of these applications require scale-up after proof of concept. However, the behaviour of microbial systems remains unpredictable (at least partially) when shifting from laboratory-scale to industrial conditions. The need for robust microbial systems is thus highly needed in this context, as well as a better understanding of the interactions between fluid mechanics and cell physiology. For that purpose, a full scale-up/down computational framework is already available. This framework links computational fluid dynamics (CFD), metabolic flux analysis and agent-based modelling (ABM) for a better understanding of the cell lifelines in a heterogeneous environment. Ultimately, this framework can be used for the design of scale-down simulators and/or metabolically engineered cells able to cope with environmental fluctuations typically found in large-scale bioreactors. However, this framework still needs some refinements, such as a better integration of gas-liquid flows in CFD, and taking into account intrinsic biological noise in ABM.

Phenotypic Heterogeneity in Attachment of Marine Bacteria toward Antifouling Copolymers Unraveled by AFM

Up to recent years, bacterial adhesion has mostly been evaluated at the population level. Single cell level has improved in the past few years allowing a better comprehension of the implication of individual behaviors as compared to the one of a whole community. A new approach using atomic force microscopy (AFM) to measure adhesion forces between a live bacterium attached via a silica microbead to the AFM tipless cantilever and the surface has been recently developed. The objectives of this study is to examine the bacterial adhesion to a surface dedicated to ship hulls at the population and the cellular level to understand to what extent these two levels could be correlated. Adhesion of marine bacteria on inert surfaces are poorly studied in particular when substrata are dedicated to ship hulls. Studying these interactions in this context are worthwhile as they may involve different adhesion behaviors, taking place in salty conditions, using different surfaces than the ones usually utilized in the literacy. FRC (fouling release coatings)-SPC (self-polishing coatings) hybrids antifouling coatings have been used as substrata and are of particular interest for designing environmentally friendly surfaces, combining progressive surface erosion and low adhesion properties. In this study, a hybrid coating has been synthetized and used to study the adhesion of three marine bacteria, displaying different surface characteristics, using microplate assays associated with confocal scanning laser microscopy (CSLM) and AFM. This study shows that the bacterial strain that appeared to have the weakest adhesion and biofilm formation abilities when evaluated at the population level using microplates assays and CSLM, displayed stronger adhesion forces on the same surfaces at the single cell level using AFM. In addition, one of the strains tested which presented a strong ability to adhere and to form biofilm at the population level, displayed a heterogeneous phenotypic behavior at the single cell level. Therefore, these results suggest that the evaluation of adhesion at the population level cannot always be correlated with adhesion forces measured individually by AFM and that some bacteria are prone to phenotypic heterogeneity among their population.

Taking control over microbial populations: Current approaches for exploiting biological noise in bioprocesses

Phenotypic plasticity of microbial cells has attracted much attention and several research efforts have been dedicated to the description of methods aiming at characterizing phenotypic heterogeneity and its impact on microbial populations. However, different approaches have also been suggested in order to take benefit from noise in a bioprocess perspective, e.g. by increasing the robustness or productivity of a microbial population. This review is dedicated to outline these controlling methods. A common issue, that has still to be addressed, is the experimental identification and the mathematical expression of noise. Indeed, the effective interfacing of microbial physiology with external parameters that can be used for controlling physiology depends on the acquisition of reliable signals. Latest technologies, like single cell microfluidics and advanced flow cytometric approaches, enable linking physiology, noise, heterogeneity in productive microbes with environmental cues and hence allow correctly mapping and predicting biological behavior via mathematical representations. However, like in the field of electronics, signals are perpetually subjected to noise. If appropriately interpreted, this noise can give an additional insight into the behavior of the individual cells within a microbial population of interest. This review focuses on recent progress made at describing, treating and exploiting biological noise in the context of microbial populations used in various bioprocess applications.

Morphology heterogeneity within a Campylobacter jejuni helical population: the use of calcofluor white to generate rod-shaped C. jejuni 81-176 clones and the genetic determinants responsible for differences in morphology within 11168 strains

Campylobacter jejuni helical shape is important for colonization and host interactions with straight mutants having altered biological properties. Passage on calcofluor white (CFW) resulted in C. jejuni 81‐176 isolates with morphology changes: either a straight morphology from frameshift mutations and single nucleotide polymorphisms in peptidoglycan hydrolase genes pgp1 or pgp2 or a reduction in curvature due a frameshift mutation in cjj81176_1105, a putative peptidoglycan endopeptidase. Shape defects were restored by complementation. Whole genome sequencing of CFW‐passaged strains showed no specific changes correlating to CFW exposure. The cjj81176_1279 (recR; recombinational DNA repair) and cjj81176_1449 (unknown function) genes were highly variable in all 81‐176 strains sequenced. A frameshift mutation in pgp1 of our laboratory isolate of the straight genome sequenced variant of 11168 (11168‐GS) was also identified. The PG muropeptide profile of 11168‐GS was identical to that of Δpgp1 in the original minimally passaged 11168 strain (11168‐O). Introduction of wild type pgp1 into 11168‐GS did not restore helical morphology. The recR gene was also highly variable in 11168 strains. Microbial cell‐to‐cell heterogeneity is proposed as a mechanism of ensuring bacterial survival in sub‐optimal conditions. In certain environments, changes in C. jejuni morphology due to genetic heterogeneity may promote C. jejuni survival.

Frequency doubling in the cyanobacterial circadian clock

Organisms use circadian clocks to generate 24‐h rhythms in gene expression. However, the clock can interact with other pathways to generate shorter period oscillations. It remains unclear how these different frequencies are generated. Here, we examine this problem by studying the coupling of the clock to the alternative sigma factor sigC in the cyanobacterium Synechococcus elongatus. Using single‐cell microscopy, we find that psbAI, a key photosynthesis gene regulated by both sigC and the clock, is activated with two peaks of gene expression every circadian cycle under constant low light. This two‐peak oscillation is dependent on sigC, without which psbAI rhythms revert to one oscillatory peak per day. We also observe two circadian peaks of elongation rate, which are dependent on sigC, suggesting a role for the frequency doubling in modulating growth. We propose that the two‐peak rhythm in psbAI expression is generated by an incoherent feedforward loop between the clock, sigC and psbAI. Modelling and experiments suggest that this could be a general network motif to allow frequency doubling of outputs.

Phenotypic Profiling Reveals that Candida albicans Opaque Cells Represent a Metabolically Specialized Cell State Compared to Default White Cells

The white-opaque switch is a bistable, epigenetic transition affecting multiple traits in Candida albicans including mating, immunogenicity, and niche specificity. To compare how the two cell states respond to external cues, we examined the fitness, phenotypic switching, and filamentation properties of white cells and opaque cells under 1,440 different conditions at 25°C and 37°C. We demonstrate that white and opaque cells display striking differences in their integration of metabolic and thermal cues, so that the two states exhibit optimal fitness under distinct conditions. White cells were fitter than opaque cells under a wide range of environmental conditions, including growth at various pHs and in the presence of chemical stresses or antifungal drugs. This difference was exacerbated at 37°C, consistent with white cells being the default state of C. albicans in the mammalian host. In contrast, opaque cells showed greater fitness than white cells under select nutritional conditions, including growth on diverse peptides at 25°C. We further demonstrate that filamentation is significantly rewired between the two states, with white and opaque cells undergoing filamentous growth in response to distinct external cues. Genetic analysis was used to identify signaling pathways impacting the white-opaque transition both in vitro and in a murine model of commensal colonization, and three sugar sensing pathways are revealed as regulators of the switch. Together, these findings establish that white and opaque cells are programmed for differential integration of metabolic and thermal cues and that opaque cells represent a more metabolically specialized cell state than the default white state.

IMPORTANCE

Epigenetic transitions are an important mechanism by which microbes adapt to external stimuli. For Candida albicans, such transitions are crucial for adaptation to complex, fluctuating environments, and therefore contribute to its success as a human pathogen. The white-opaque switch modulates multiple C. albicans attributes, from sexual competency to niche specificity. Here, we demonstrate that metabolic circuits are extensively rewired between white and opaque states, so that the two cell types exhibit optimal fitness under different nutritional conditions and at different temperatures. We thereby establish that epigenetic events can profoundly alter the metabolism of fungal cells. We also demonstrate that epigenetic switching regulates filamentation and biofilm formation, two phenotypes closely associated with pathogenesis. These experiments reveal that white cells, considered the most clinically relevant form of C. albicans, are a "general-purpose" state suited to many environments, whereas opaque cells appear to represent a more metabolically specialized form of the species.

Proteomics progresses in microbial physiology and clinical antimicrobial therapy

Clinical microbial identification plays an important role in optimizing the management of infectious diseases and provides diagnostic and therapeutic support for clinical management. Microbial proteomic research is aimed at identifying proteins associated with microbial activity, which has facilitated the discovery of microbial physiology changes and host–pathogen interactions during bacterial infection and antimicrobial therapy. Here, we summarize proteomic-driven progresses of host–microbial pathogen interactions at multiple levels, mass spectrometry-based microbial proteome identification for clinical diagnosis, and antimicrobial therapy. Proteomic technique progresses pave new ways towards effective prevention and drug discovery for microbial-induced infectious diseases.

Superposition of Individual Activities: Urea-Mediated Suppression of Nitrate Uptake in the Dinoflagellate Prorocentrum minimum Revealed at the Population and Single-Cell Levels

Dinoflagellates readily use diverse inorganic and organic compounds as nitrogen sources, which is advantageous in eutrophied coastal areas exposed to high loads of anthropogenic nutrients, e.g., urea, one of the most abundant organic nitrogen substrates in seawater. Cell-to-cell variability in nutritional physiology can further enhance the diversity of metabolic strategies among dinoflagellates of the same species, but it has not been studied in free-living microalgae. We applied stable isotope tracers, isotope ratio mass spectrometry and nanoscale secondary ion mass spectrometry (NanoSIMS) to investigate the response of cultured nitrate-acclimated dinoflagellates Prorocentrum minimum to a sudden input of urea and the effect of urea on the concurrent nitrate uptake at the population and single-cell levels. We demonstrate that inputs of urea lead to suppression of nitrate uptake by P. minimum, and urea uptake exceeds the concurrent uptake of nitrate. Individual dinoflagellate cells within a population display significant heterogeneity in the rates of nutrient uptake and extent of the urea-mediated inhibition of the nitrate uptake, thus forming several groups characterized by different modes of nutrition. We conclude that urea originating from sporadic sources is rapidly utilized by dinoflagellates and can be used in biosynthesis or stored intracellularly depending on the nutrient status; therefore, sudden urea inputs can represent one of the factors triggering or supporting harmful algal blooms. Significant physiological heterogeneity revealed at the single-cell level is likely to play a role in alleviation of intra-population competition for resources and can affect the dynamics of phytoplankton populations and their maintenance in natural environments.

Cellular Deconstruction: Finding Meaning in Individual Cell Variation

The advent of single cell transcriptome analysis has permitted the discovery of cell-to-cell variation in transcriptome expression of even presumptively identical cells. We hypothesize that this variability reflects a many-to-one relation between transcriptome states and the phenotype of a cell. In this relation, the molecular ratios of the subsets of RNA are determined by the stoichiometric constraints of the cell systems, which underdetermine the transcriptome state. Furthermore, the variability is, in part, induced by the tissue context and is important for system-level function. This theory is analogous to theories of literary deconstruction, where multiple 'signifiers' work in opposition to one another to create meaning. By analogy, transcriptome phenotypes should be defined as subsets of RNAs comprising selected RNA systems where the system-associated RNAs are balanced with each other to produce the associated cellular function. This idea provides a framework for understanding cellular heterogeneity in phenotypic responses to variant conditions, such as disease challenge.

Comparison of the Effects of Environmental Parameters on the Growth Variability of Vibrio parahaemolyticus Coupled with Strain Sources and Genotypes Analyses

Microbial growth variability plays an important role on food safety risk assessment. In this study, the growth kinetic characteristics corresponding to maximum specific growth rate (μmax) of 50 V. parahaemolyticus isolates from different sources and genotypes were evaluated at different temperatures (10, 20, 30, and 37°C) and salinity (0.5, 3, 5, 7, and 9%) using the automated turbidimetric system Bioscreen C. The results demonstrated that strain growth variability increased as the growth conditions became more stressful both in terms of temperature and salinity. The coefficient of variation (CV) of μmax for temperature was larger than that for salinity, indicating that the impact of temperature on strain growth variability was greater than that of salinity. The strains isolated from freshwater aquatic products had more conspicuous growth variations than those from seawater. Moreover, the strains with tlh (+) /tdh (+) /trh (-) exhibited higher growth variability than tlh (+) /tdh (-) /trh (-) or tlh (+) /tdh (-) /trh (+), revealing that gene heterogeneity might have possible relations with the growth variability. This research illustrates that the growth environments, strain sources as well as genotypes have impacts on strain growth variability of V. parahaemolyticus, which can be helpful for incorporating strain variability in predictive microbiology and microbial risk assessment.

Biochemical Engineering Approaches for Increasing Viability and Functionality of Probiotic Bacteria

The literature presents a growing body of evidence demonstrating the positive effect of probiotics on health. Probiotic consumption levels are rising quickly in the world despite the fluctuation of their viability and functionality. Technological methods aiming at improving probiotic characteristics are thus highly wanted. However, microbial metabolic engineering toolbox is not available for this kind of application. On the other hand, basic microbiology teaches us that bacteria are able to exhibit adaptation to external stresses. It is known that adequately applied sub-lethal stress, i.e., controlled in amplitude and frequency at a given stage of the culture, is able to enhance microbial robustness. This property could be potentially used to improve the viability of probiotic bacteria, but some technical challenges still need to be overcome before any industrial implementation. This review paper investigates the different technical tools that can be used in order to define the proper condition for improving viability of probiotic bacteria and their implementation at the industrial scale. Based on the example of Bifidobacterium bifidum, potentialities for simultaneously improving viability, but also functionality of probiotics will be described.

Single-Cell Analysis of the Dps Response to Oxidative Stress

Microorganisms have developed an elaborate spectrum of mechanisms to respond and adapt to environmental stress conditions. Among these is the expression of dps, coding for the DNA-binding protein from starved cells. Dps becomes the dominant nucleoid-organizing protein in stationary-phase Escherichia coli cells and is required for robust survival under stress conditions, including carbon or nitrogen starvation, oxidative stress, metal exposure, and irradiation. To study the complex regulation of Dps in E. coli, we utilized time-lapse fluorescence microscopy imaging to examine the kinetics, input encoding, and variability of the Dps response in single cells. In the presence of an oxidative stressor, we observed a single pulse of activation of Dps production. Increased concentrations of H2O2 led to increased intensity and duration of the pulse. While lower concentrations of H2O2 robustly activated the Dps response with little effect on the growth rate, higher concentrations of H2O2 resulted in dramatically lower and highly varied growth rates. A comparison of cells exposed to the same concentration of H2O2 revealed that increased levels of Dps expression did not confer a growth advantage, indicating that recovery from stress may rely primarily upon variation in the amount of damage caused to individual cells.

IMPORTANCE

We show for the first time the response of the DNA-binding protein from starved cells (Dps) to oxidative stress in single cells of E. coli Through time-lapse fluorescence microscopy, a single pulse of Dps production is observed in cells exposed to H2O2, with a duration and intensity of induction proportional to the concentration of the applied stress. More intense Dps expression did not provide a growth benefit to the bacteria, suggesting that healing from oxidative stress may largely depend upon the amount of damage in each individual cell.

Developmental mechanisms underlying variable, invariant and plastic phenotypes

BACKGROUND

Discussions of phenotypic robustness often consider scenarios where invariant phenotypes are optimal and assume that developmental mechanisms have evolved to buffer the phenotypes of specific traits against stochastic and environmental perturbations. However, plastic plant phenotypes that vary between environments or variable phenotypes that vary stochastically within an environment may also be advantageous in some scenarios.

SCOPE

Here the conditions under which invariant, plastic and variable phenotypes of specific traits may confer a selective advantage in plants are examined. Drawing on work from microbes and multicellular organisms, the mechanisms that may give rise to each type of phenotype are discussed.

CONCLUSION

In contrast to the view of robustness as being the ability of a genotype to produce a single, invariant phenotype, changes in a phenotype in response to the environment, or phenotypic variability within an environment, may also be delivered consistently (i.e. robustly). Thus, for some plant traits, mechanisms have probably evolved to produce plasticity or variability in a reliable manner.

Variation is function: Are single cell differences functionally important?: Testing the hypothesis that single cell variation is required for aggregate function

There is a growing appreciation of the extent of transcriptome variation across individual cells of the same cell type. While expression variation may be a byproduct of, for example, dynamic or homeostatic processes, here we consider whether single-cell molecular variation per se might be crucial for population-level function. Under this hypothesis, molecular variation indicates a diversity of hidden functional capacities within an ensemble of identical cells, and this functional diversity facilitates collective behavior that would be inaccessible to a homogenous population. In reviewing this topic, we explore possible functions that might be carried by a heterogeneous ensemble of cells; however, this question has proven difficult to test, both because methods to manipulate molecular variation are limited and because it is complicated to define, and measure, population-level function. We consider several possible methods to further pursue the hypothesis that variation is function through the use of comparative analysis and novel experimental techniques.

Fluorescent Reporter Libraries as Useful Tools for Optimizing Microbial Cell Factories: A Review of the Current Methods and Applications

The use of genetically encoded fluorescent reporters allows speeding up the initial optimization steps of microbial bioprocesses. These reporters can be used for determining the expression level of a particular promoter, not only the synthesis of a specific protein but also the content of intracellular metabolites. The level of protein/metabolite is thus proportional to a fluorescence signal. By this way, mean expression profiles of protein/metabolites can be determined non-invasively at a high-throughput rate, allowing the rapid identification of the best producers. Actually, different kinds of reporter systems are available, as well as specific cultivation devices allowing the on-line recording of the fluorescent signal. Cell-to-cell variability is another important phenomenon that can be integrated into the screening procedures for the selection of more efficient microbial cell factories.

Enhanced and homogeneous oxygen availability during incubation of microfluidic droplets

Up to now, droplets have been statically incubated, resulting in limited and inhomogeneous oxygenation affecting encapsulated cells. Dynamic droplet incubation is presented as a solution.