Transcriptional heterogeneity of catabolic genes on the plasmid pCAR1 causes host-specific carbazole degradation

To elucidate why plasmid-borne catabolic ability differs among host bacteria, we assessed the expression dynamics of the Pant promoter on the carbazole-degradative conjugative plasmid pCAR1 in Pseudomonas putida KT2440(pCAR1) (hereafter, KTPC) and Pseudomonas resinovorans CA10. The Pant promoter regulates the transcription of both the car and ant operons, which are responsible for converting carbazole into anthranilate and anthranilate into catechol, respectively. In the presence of anthranilate, transcription of the Pant promoter is induced by the AraC/XylS family regulator AntR, encoded on pCAR1. A reporter cassette containing the Pant promoter followed by gfp was inserted into the chromosomes of KTPC and CA10. After adding anthranilate, GFP expression in the population of CA10 showed an unimodal distribution, whereas a small population with low GFP fluorescence intensity appeared for KTPC. CA10 has a gene, antRCA, that encodes an iso-functional homolog of AntR on its chromosome. When antRCA was disrupted, a small population with low GFP fluorescence intensity appeared. In contrast, overexpression of pCAR1-encoded AntR in KTPC resulted in unimodal expression under the Pant promoter. These results suggest that the expression of pCAR1-encoded AntR is insufficient to ameliorate the stochastic expression of the Pant promoter. Raman spectra of single cells collected using deuterium-labeled carbazole showed that the C-D Raman signal exhibited greater variability for KTPC than CA10. These results indicate that heterogeneity at the transcriptional level of the Pant promoter due to insufficient AntR availability causes fluctuations in the pCAR1-borne carbazole-degrading capacity of host bacterial cells.IMPORTANCEHorizontally acquired genes increase the competitiveness of host bacteria under selective conditions, although unregulated expression of foreign genes may impose fitness costs. The "appropriate" host for a plasmid is empirically known to maximize the expression of plasmid-borne traits. In the case of pCAR1-harboring Pseudomonas strains, P. resinovorans CA10 exhibits strong carbazole-degrading capacity, whereas P. putida KT2440 harboring pCAR1 exhibits low degradation capacity. Our results suggest that a chromosomally encoded transcription factor affects transcriptional and metabolic fluctuations in host cells, resulting in different carbazole-degrading capacities as a population. This study may provide a clue for determining appropriate hosts for a plasmid and for regulating the expression of plasmid-borne traits, such as the degradation of xenobiotics and antibiotic resistance.

Engineering Green-light-responsive Heterologous Gene Expression in Pseudomonas

Engineering bacterial properties requires precision and fine-tuning for optimal control of the desired application. In consequence, it is essential to accurately turn the function of interest from OFF to ON state and vice versa, avoiding any type of residual activation. For this type of purpose, light switches have revealed a clean and powerful tool in which control does not depend on the addition of chemical compounds that may remain in the media. To reach this degree of directed regulation through light, the switch based on the cyanobacterial two-component system CcaSR system was previously adapted to manipulate Pseudomonas putida for transcription of a gene of interest. In this chapter, we describe how to induce biofilm formation by placing the expression of the c-di-GMP-producing diguanylate cyclase PleD from Caulobacter sp. under the control of the CcaSR system. The regulation through optogenetics accomplished with this protocol promotes higher exploitation of biofilm beneficial features in a cheaper and cleaner way compared to chemical induction.

Potential Utilization of Bacterial Consortium of Symbionts Marine Sponges in Removing Polyaromatic Hydrocarbons and Heavy Metals, Review

Toxic materials in waste generally contain several components of the global trending pollutant category, especially PAHs and heavy metals. Bioremediation technology for waste management that utilizes microorganisms (bacteria) has not been fully capable of breaking down these toxic materials into simple and environmentally friendly chemical products. This review paper examines the potential application of a consortium of marine sponge symbionts with high performance and efficiency in removing PAHs and heavy metal contaminants. The method was carried out through a review of several related research articles by the author and published by other researchers. The results of the study conclude that the development of global trending pollutant (GTP) bioremediation technology could be carried out to increase the efficiency of remediation. Several types of marine sponge symbiont bacteria, hydrocarbonoclastic (R-1), metalloclastic (R-2), and metallo-hydro-carbonoclastic (R-3), have the potential to be applied to improve waste removal performance. A consortium of crystalline bacterial preparations is required to mobilize into GTP-exposed sites rapidly. Bacterial symbionts of marine sponges can be traced mainly to sea sponges, whose body surface is covered with mucus.

Culture-Independent Raman Spectroscopic Identification of Bacterial Pathogens from Clinical Samples Using Deep Transfer Learning

The rapid identification of bacterial pathogens in clinical samples like blood, urine, pus, and sputum is the need of the hour. Conventional bacterial identification methods like culturing and nucleic acid-based amplification have limitations like poor sensitivity, high cost, slow turnaround time, etc. Raman spectroscopy, a label-free and noninvasive technique, has overcome these drawbacks by providing rapid biochemical signatures from a single bacterium. Raman spectroscopy combined with chemometric methods has been used effectively to identify pathogens. However, a robust approach is needed to utilize Raman features for accurate classification while dealing with complex data sets such as spectra obtained from clinical isolates, showing high sample-to-sample heterogeneity. In this study, we have used Raman spectroscopy-based identification of pathogens from clinical isolates using a deep transfer learning approach at the single-cell level resolution. We have used the data-augmentation method to increase the volume of spectra needed for deep-learning analysis. Our ResNet model could specifically extract the spectral features of eight different pathogenic bacterial species with a 99.99% classification accuracy. The robustness of our model was validated on a set of blinded data sets, a mix of cultured and noncultured bacterial isolates of various origins and types. Our proposed ResNet model efficiently identified the pathogens from the blinded data set with high accuracy, providing a robust and rapid bacterial identification platform for clinical microbiology.

Relatedness and the evolution of mechanisms to divide labor in microorganisms

Division of labor occurs when cooperating individuals specialize to perform different tasks. In bacteria and other microorganisms, some species divide labor by random specialization, where an individual's role is determined by random fluctuations in biochemical reactions within the cell. Other species divide labor by coordinating across individuals to determine which cells will perform which task, using mechanisms such as between-cell signaling. However, previous theory, examining the evolution of mechanisms to divide labor between reproductives and sterile helpers, has only considered clonal populations, where there is no potential for conflict between individuals. We used a mixture of analytical and simulation models to examine nonclonal populations and found that: (a) intermediate levels of coordination can be favored, between the extreme of no coordination (random) and full coordination; (b) as relatedness decreases, coordinated division of labor is less likely to be favored. Our results can help explain why coordinated division of labor is relatively rare in bacteria, where groups may frequently be nonclonal.

Ten recent insights for our understanding of cooperation

Since Hamilton published his seminal papers in 1964, our understanding of the importance of cooperation for life on Earth has evolved beyond recognition. Early research was focused on altruism in the social insects, where the problem of cooperation was easy to see. In more recent years, research into cooperation has expanded across the entire tree of life, and has been revolutionized by advances in genetic, microbiological and analytical techniques. We highlight ten insights that have arisen from these advances, which have illuminated generalizations across different taxa, making the world simpler to explain. Furthermore, progress in these areas has opened up numerous new problems to solve, suggesting exciting directions for future research.

Single-Cell Mass Spectroscopic Analysis for Quantifying Active Metabolic Pathway Heterogeneity in a Bacterial Population on an Electrode

Microbial electrochemical catalysis based on respiratory reactions coupled with extracellular electron transport (EET), which is critical for bioenergy applications, strongly depends on the biocompatibility of the electrode material. However, the comparison of materials for such physiological responses has been difficult because of the lack of a quantitative assay for characterizing cellular metabolism at the electrode surface. Here, we developed a single-cell analysis method specific for the cells attached to the electrode to quantify active metabolic pathway heterogeneity as an index of physiological cell/electrode interaction, which generally increases with metabolic robustness in the microbial population. Nanoscale secondary ion mass spectrometry followed by microbial current production with model EET-capable bacteria, Shewanella oneidensis MR-1 and its mutant strains lacking carbon assimilation pathways, showed that different active metabolic pathways resulted in nearly identical ¹³C/¹⁵N assimilation ratios for individual cells in the presence of isotopically labeled nutrients, demonstrating a correlation between the ¹³C/¹⁵N ratio and the active metabolic pathway. Compared to the nonelectrode conditions, the heterogeneity of the assimilated ¹³C/¹⁵N ratio was highly enhanced on the electrode surface, suggesting that the metabolic robustness of the microbial population increased through the electrochemical interaction with the electrode. The present methodology enables us to quantitatively compare and screen electrode materials that increase the robustness of microbial electrocatalysis.

Biotransformation of 2,4-dinitrotoluene in a phototrophic co-culture of engineered Synechococcus elongatus and Pseudomonas putida

In contrast to the current paradigm of using microbial mono-cultures in most biotechnological applications, increasing efforts are being directed towards engineering mixed-species consortia to perform functions that are difficult to programme into individual strains. In this work, we developed a synthetic microbial consortium composed of two genetically engineered microbes, a cyanobacterium (Synechococcus elongatus PCC 7942) and a heterotrophic bacterium (Pseudomonas putida EM173). These microbial species specialize in the co-culture: cyanobacteria fix CO2 through photosynthetic metabolism and secrete sufficient carbohydrates to support the growth and active metabolism of P. putida, which has been engineered to consume sucrose and to degrade the environmental pollutant 2,4-dinitrotoluene (2,4-DNT). By encapsulating S. elongatus within a barium-alginate hydrogel, cyanobacterial cells were protected from the toxic effects of 2,4-DNT, enhancing the performance of the co-culture. The synthetic consortium was able to convert 2,4-DNT with light and CO2 as key inputs, and its catalytic performance was stable over time. Furthermore, cycling this synthetic consortium through low nitrogen medium promoted the sucrose-dependent accumulation of polyhydroxyalkanoate, an added-value biopolymer, in the engineered P. putida strain. Altogether, the synthetic consortium displayed the capacity to remediate the industrial pollutant 2,4-DNT while simultaneously synthesizing biopolymers using light and CO2 as the primary inputs.

Combination of an Artificial Intelligence Approach and Laser Tweezers Raman Spectroscopy for Microbial Identification

Raman spectroscopy is a nondestructive, label-free, highly specific approach that provides the chemical information on materials. Thus, it is suitable to be used as an effective analytical tool to characterize biological samples. Here we introduce a novel method that uses artificial intelligence to analyze biological Raman spectra and identify the microbes at a single-cell level. The combination of a framework of convolutional neural network (ConvNet) and Raman spectroscopy allows the extraction of the Raman spectral features of a single microbial cell and then categorizes cells according to their spectral features. As the proof of concept, we measured Raman spectra of 14 microbial species at a single-cell level and constructed an optimal ConvNet model using the Raman data. The average accuracy of classification by ConvNet is 95.64 ± 5.46%. Meanwhile, we introduced an occlusion-based Raman spectra feature extraction to visualize the weights of Raman features for distinguishing different species.

Microfluidic Single-Cell Analytics

What is the impact of cellular heterogeneity on process performance? How do individual cells contribute to averaged process productivity? Single-cell analysis is a key technology for answering such key questions of biotechnology, beyond bulky measurements with populations. The analysis of cellular individuality, its origins, and the dependency of process performance on cellular heterogeneity has tremendous potential for optimizing biotechnological processes in terms of metabolic, reaction, and process engineering. Microfluidics offer unmatched environmental control of the cellular environment and allow massively parallelized cultivation of single cells. However, the analytical accessibility to a cell's physiology is of crucial importance for obtaining the desired information on the single-cell production phenotype. Highly sensitive analytics are required to detect and quantify the minute amounts of target analytes and small physiological changes in a single cell. For their application to biotechnological questions, single-cell analytics must evolve toward the measurement of kinetics and specific rates of the smallest catalytic unit, the single cell. In this chapter, we focus on an introduction to the latest single-cell analytics and their application for obtaining physiological parameters in a biotechnological context from single cells. We present and discuss recent advancements in single-cell analytics that enable the analysis of cell-specific growth, uptake, and production kinetics, as well as the gene expression and regulatory mechanisms at a single-cell level.

A portable epigenetic switch for bistable gene expression in bacteria

We describe a portable epigenetic switch based on opvAB, a Salmonella enterica operon that undergoes bistable expression under DNA methylation control. A DNA fragment containing the opvAB promoter and the opvAB upstream regulatory region confers bistability to heterologous genes, yielding OFF and ON subpopulations. Bistable expression under opvAB control is reproducible in Escherichia coli, showing that the opvAB switch can be functional in a heterologous host. Subpopulations of different sizes can be produced at will using engineered opvAB variants. Controlled formation of antibiotic-resistant and antibiotic-susceptible subpopulations may allow use of the opvAB switch in the study of bacterial heteroresistance to antibiotics.

Biochemistry, genetics and biotechnology of glycerol utilization in Pseudomonas species

The use of renewable waste feedstocks is an environment‐friendly choice contributing to the reduction of waste treatment costs and increasing the economic value of industrial by‐products. Glycerol (1,2,3‐propanetriol), a simple polyol compound widely distributed in biological systems, constitutes a prime example of a relatively cheap and readily available substrate to be used in bioprocesses. Extensively exploited as an ingredient in the food and pharmaceutical industries, glycerol is also the main by‐product of biodiesel production, which has resulted in a progressive drop in substrate price over the years. Consequently, glycerol has become an attractive substrate in biotechnology, and several chemical commodities currently produced from petroleum have been shown to be obtained from this polyol using whole‐cell biocatalysts with both wild‐type and engineered bacterial strains. Pseudomonas species, endowed with a versatile and rich metabolism, have been adopted for the conversion of glycerol into value‐added products (ranging from simple molecules to structurally complex biopolymers, e.g. polyhydroxyalkanoates), and a number of metabolic engineering strategies have been deployed to increase the number of applications of glycerol as a cost‐effective substrate. The unique genetic and metabolic features of glycerol‐grown Pseudomonas are presented in this review, along with relevant examples of bioprocesses based on this substrate – and the synthetic biology and metabolic engineering strategies implemented in bacteria of this genus aimed at glycerol valorization.

The Metabolic Redox Regime of Pseudomonas putida Tunes Its Evolvability toward Novel Xenobiotic Substrates

During evolution of biodegradation pathways for xenobiotic compounds involving Rieske nonheme iron oxygenases, the transition toward novel substrates is frequently associated with faulty reactions. Such events release reactive oxygen species (ROS), which are endowed with high mutagenic potential. In this study, we evaluated how the operation of the background metabolic network by an environmental bacterium may either foster or curtail the still-evolving pathway for 2,4-dinitrotoluene (2,4-DNT) catabolism. To this end, the genetically tractable strain Pseudomonas putida EM173 was implanted with the whole genetic complement necessary for the complete biodegradation of 2,4-DNT (recruited from the environmental isolate Burkholderia sp. R34). By using reporter technology and direct measurements of ROS formation, we observed that the engineered P. putida strain experienced oxidative stress when catabolizing the nitroaromatic substrate. However, the formation of ROS was neither translated into significant activation of the SOS response to DNA damage nor did it result in a mutagenic regime (unlike what has been observed in Burkholderia sp. R34, the original host of the pathway). To inspect whether the tolerance of P. putida to oxidative challenges could be traced to its characteristic reductive redox regime, we artificially altered the NAD(P)H pool by means of a water-forming, NADH-specific oxidase. Under the resulting low-NAD(P)H status, catabolism of 2,4-DNT triggered a conspicuous mutagenic and genomic diversification scenario. These results indicate that the background biochemical network of environmental bacteria ultimately determines the evolvability of metabolic pathways. Moreover, the data explain the efficacy of some bacteria (e.g., pseudomonads) to host and evolve with new catabolic routes.IMPORTANCE Some environmental bacteria evolve with new capacities for the aerobic biodegradation of chemical pollutants by adapting preexisting redox reactions to novel compounds. The process typically starts by cooption of enzymes from an available route to act on the chemical structure of the substrate-to-be. The critical bottleneck is generally the first biochemical step, and most of the selective pressure operates on reshaping the initial reaction. The interim uncoupling of the novel substrate to preexisting Rieske nonheme iron oxygenases usually results in formation of highly mutagenic ROS. In this work, we demonstrate that the background metabolic regime of the bacterium that hosts an evolving catabolic pathway (e.g., biodegradation of the xenobiotic 2,4-DNT) determines whether the cells either adopt a genetic diversification regime or a robust ROS-tolerant status. Furthermore, our results offer new perspectives to the rational design of efficient whole-cell biocatalysts, which are pursued in contemporary metabolic engineering.

Ecology of Contaminant Biotransformation in the Mycosphere: Role of Transport Processes

Fungi and bacteria often share common microhabitats. Their co-occurrence and coevolution give rise to manifold ecological interactions in the mycosphere, here defined as the microhabitats surrounding and affected by hyphae and mycelia. The extensive structure of mycelia provides ideal "logistic networks" for transport of bacteria and matter in structurally and chemically heterogeneous soil ecosystems. We describe the characteristics of the mycosphere as a unique and highly dynamic bacterial habitat and a hot spot for contaminant biotransformation. In particular, we emphasize the role of the mycosphere for (i) bacterial dispersal and colonization of subsurface interfaces and new habitats, (ii) matter transport processes and contaminant bioaccessibility, and (iii) the functional stability of microbial ecosystems when exposed to environmental fluctuations such as stress or disturbances. Adopting concepts from ecological theory, the chapter disentangles bacterial-fungal impacts on contaminant biotransformation in a systemic approach that interlinks empirical data from microbial ecosystems with simulation data from computational models. This approach provides generic information on key factors, processes, and ecological principles that drive microbial contaminant biotransformation in soil. We highlight that the transport processes create favorable habitat conditions for efficient bacterial contaminant degradation in the mycosphere. In-depth observation, understanding, and prediction of the role of mycosphere transport processes will support the use of bacterial-fungal interactions in nature-based solutions for contaminant biotransformation in natural and man-made ecosystems, respectively.

Metabolic interactions between dynamic bacterial subpopulations

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

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

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

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

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

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.

Assessing Carbon Source-Dependent Phenotypic Variability in Pseudomonas putida

The soil bacterium Pseudomonas putida is rapidly becoming a platform of choice for applications that require a microbial host highly resistant to different types of stresses and elevated rates of reducing power regeneration. P. putida is capable of growing in a wide variety of carbon sources that range from simple sugars to complex substrates such as aromatic compounds. Interestingly, the growth of the reference strain KT2440 on glycerol as the sole carbon source is characterized by a prolonged lag phase, not observed with other carbon substrates. This macroscopic phenomenon has been shown to be connected with the stochastic expression of the glp genes, which encode the enzymes needed for glycerol processing. In this protocol, we propose a general procedure to examine bacterial growth in small-scale cultures while monitoring the metabolic activity of individual cells. Assessing the metabolic capacity of single bacteria by means of fluorescence microscopy and flow cytometry, in combination with the analysis of the temporal takeoff of growth in single-cell cultures, is a simple and easy-to-implement approach. It can help to understand the link between macroscopic phenotypes (e.g., microbial growth in batch cultures) and stochastic phenomena at the genetic level. The implementation of these methodologies revealed that the adoption of a glycerol-metabolizing regime by P. putida KT2440 is not the result of a gradual change in the whole population, but it rather reflects a time-dependent bimodal switch between metabolically inactive (i.e., not growing) to fully active (i.e., growing) bacteria.

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

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

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

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.

Cooperation in microbial communities and their biotechnological applications

Microbial communities are increasingly utilized in biotechnology. Efficiency and productivity in many of these applications depends on the presence of cooperative interactions between members of the community. Two key processes underlying these interactions are the production of public goods and metabolic cross-feeding, which can be understood in the general framework of ecological and evolutionary (eco-evo) dynamics. In this review, we illustrate the relevance of cooperative interactions in microbial biotechnological processes, discuss their mechanistic origins and analyse their evolutionary resilience. Cooperative behaviours can be damaged by the emergence of 'cheating' cells that benefit from the cooperative interactions but do not contribute to them. Despite this, cooperative interactions can be stabilized by spatial segregation, by the presence of feedbacks between the evolutionary dynamics and the ecology of the community, by the role of regulatory systems coupled to the environmental conditions and by the action of horizontal gene transfer. Cooperative interactions enrich microbial communities with a higher degree of robustness against environmental stress and can facilitate the evolution of more complex traits. Therefore, the evolutionary resilience of microbial communities and their ability to constraint detrimental mutants should be considered to design robust biotechnological applications.

Deconvolution of Gene Expression Noise into Spatial Dynamics of Transcription Factor-Promoter Interplay

Gene expression noise is not only the mere consequence of stochasticity, but also a signal that reflects the upstream physical dynamics of the cognate molecular machinery. Soil bacteria facing recalcitrant pollutants exploit noise of catabolic promoters to deploy beneficial phenotypes such as metabolic bet-hedging and/or division of biochemical labor. Although the role of upstream promoter-regulator interplay in the origin of this noise is little understood, its specifications are probably ciphered in flow cytometry data patterns. We studied Pm promoter activity of the environmental bacterium Pseudomonas putida and its cognate regulator XylS by following expression of Pm-gfp fusions in single cells. Using mathematical modeling and computational simulations, we determined the kinetic properties of the system and used them as a baseline code to interpret promoter activity in terms of upstream regulator dynamics. Transcriptional noise was predicted to depend on the intracellular physical distance between regulator source (where XylS is produced) and the target promoter. Experiments with engineered bacteria in which this distance is minimized or enlarged confirmed the predicted effects of source/target proximity on noise patterns. This approach allowed deconvolution of cytometry data into mechanistic information on gene expression flow. It also provided a basis for selecting programmable noise levels in synthetic regulatory circuits.

Engineering Gram-Negative Microbial Cell Factories Using Transposon Vectors

The construction of microbial cell factories à la carte largely depends on specialized molecular biology and synthetic biology tools needed to reprogram bacteria for modifying their existing functions or for bestowing them with new-to-Nature tasks. In this chapter, we document the use of a series of broad-host-range mini-Tn5 vectors for the delivery of gene(s) into the chromosome of Gram-negative bacteria and for the generation of saturated, random mutagenesis libraries for studies of gene function. The application of these tailored mini-transposon vectors, which could also be used for chromosomal engineering of a wide variety of Gram-negative microorganisms, is demonstrated in the platform environmental bacterium Pseudomonas putida KT2440.

Pyridine nucleotide transhydrogenases enable redox balance of Pseudomonas putida during biodegradation of aromatic compounds

The metabolic versatility of the soil bacterium Pseudomonas putida is reflected by its ability to execute strong redox reactions (e.g., mono- and di-oxygenations) on aromatic substrates. Biodegradation of aromatics occurs via the pathway encoded in the archetypal TOL plasmid pWW0, yet the effect of running such oxidative route on redox balance against the background metabolism of P. putida remains unexplored. To answer this question, the activity of pyridine nucleotide transhydrogenases (that catalyze the reversible interconversion of NADH and NADPH) was inspected under various physiological and oxidative stress regimes. The genome of P. putida KT2440 encodes a soluble transhydrogenase (SthA) and a membrane-bound, proton-pumping counterpart (PntAB). Mutant strains, lacking sthA and/or pntAB, were subjected to a panoply of genetic, biochemical, phenomic and functional assays in cells grown on customary carbon sources (e.g., citrate) versus difficult-to-degrade aromatic substrates. The results consistently indicated that redox homeostasis is compromised in the transhydrogenases-defective variant, rendering the mutant sensitive to oxidants. This metabolic deficiency was, however, counteracted by an increase in the activity of NADP⁺ -dependent dehydrogenases in central carbon metabolism. Taken together, these observations demonstrate that transhydrogenases enable a redox-adjusting mechanism that comes into play when biodegradation reactions are executed to metabolize unusual carbon compounds.

From dirt to industrial applications: Pseudomonas putida as a Synthetic Biology chassis for hosting harsh biochemical reactions

The soil bacterium Pseudomonas putida is endowed with a central carbon metabolic network capable of fulfilling high demands of reducing power. This situation arises from a unique metabolic architecture that encompasses the partial recycling of triose phosphates to hexose phosphates-the so-called EDEMP cycle. In this article, the value of P. putida as a bacterial chassis of choice for contemporary, industrially-oriented metabolic engineering is addressed. The biochemical properties that make this bacterium adequate for hosting biotransformations involving redox reactions as well as toxic compounds and intermediates are discussed. Finally, novel developments and open questions in the continuous quest for an optimal microbial cell factory are presented at the light of current and future needs in the area of biocatalysis.

New perspectives for the design of sustainable bioprocesses for phosphorus recovery from waste

Phosphate rock has long been used for the production of phosphorus based chemicals. However, considering the depletion of the reservoirs and the decrease of the quality of phosphate rocks, a potential market is now emerging for the recovery of phosphate from waste and its reuse for different applications. Notably, phosphate recovery from wastewater could be included in a circular economy approach. This review focuses on the use of microbial systems for phosphorus accumulation and recovery, by considering the actual range of analytical techniques available for the monitoring of phosphorus accumulating organisms, as well as the actual biochemical and metabolic engineering toolbox available for the optimization of bioprocesses. In this context, knowledge gathered from process, system and synthetic biology could potentially lead to innovative process design.

Stochastic developmental variation, an epigenetic source of phenotypic diversity with far-reaching biological consequences

This article reviews the production of different phenotypes from the same genotype in the same environment by stochastic cellular events, nonlinear mechanisms during patterning and morphogenesis, and probabilistic self-reinforcing circuitries in the adult life. These aspects of phenotypic variation are summarized under the term 'stochastic developmental variation' (SDV) in the following. In the past, SDV has been viewed primarily as a nuisance, impairing laboratory experiments, pharmaceutical testing, and true-to-type breeding. This article also emphasizes the positive biological effects of SDV and discusses implications for genotype-to-phenotype mapping, biological individuation, ecology, evolution, and applied biology. There is strong evidence from experiments with genetically identical organisms performed in narrowly standardized laboratory set-ups that SDV is a source of phenotypic variation in its own right aside from genetic variation and environmental variation. It is obviously mediated by molecular and higher-order epigenetic mechanisms. Comparison of SDV in animals, plants, fungi, protists, bacteria, archaeans, and viruses suggests that it is a ubiquitous and phylogenetically old phenomenon. In animals, it is usually smallest for morphometric traits and highest for life history traits and behaviour. SDV is thought to contribute to phenotypic diversity in all populations but is particularly relevant for asexually reproducing and genetically impoverished populations, where it generates individuality despite genetic uniformity. In each generation, SDV produces a range of phenotypes around a well-adapted target phenotype, which is interpreted as a bet-hedging strategy to cope with the unpredictability of dynamic environments. At least some manifestations of SDV are heritable, adaptable, selectable, and evolvable, and therefore, SDV may be seen as a hitherto overlooked evolution factor. SDV is also relevant for husbandry, agriculture, and medicine because most pathogens are asexuals that exploit this third source of phenotypic variation to modify infectivity and resistance to antibiotics. Since SDV affects all types of organisms and almost all aspects of life, it urgently requires more intense research and a better integration into biological thinking.

Tn7-Based Device for Calibrated Heterologous Gene Expression in Pseudomonas putida

The soil bacterium Pseudomonas putida is increasingly attracting considerable interest as a platform for advanced metabolic engineering through synthetic biology approaches. However, genomic context, gene copy number, and transcription/translation interplay often introduce considerable uncertainty to the design of reliable genetic constructs. In this work, we have established a standardized heterologous expression device in which the promoter strength is the only variable; the remaining parameters of the flow have stable default values. To this end, we tailored a mini-Tn7 delivery transposon vector that inserts the constructs in a single genomic locus of P. putida's chromosome. This was then merged with a promoter insertion site, an unvarying translational coupler, and a downstream location for placing the gene(s) of interest under fixed assembly rules. This arrangement was exploited to benchmark a collection of synthetic promoters with low transcriptional noise in this bacterial host. Growth experiments and flow cytometry with single-copy promoter-GFP constructs revealed a robust, constitutive behavior of these promoters, whose strengths and properties could be faithfully compared. This standardized expression device significantly extends the repertoire of tools available for reliable metabolic engineering and other genetic enhancements of P. putida.

Pseudomonas putida mt-2 tolerates reactive oxygen species generated during matric stress by inducing a major oxidative defense response

Background

Soil bacteria typically thrive in water-limited habitats that cause an inherent matric stress to the cognate cells. Matric stress gives rise to accumulation of intracellular reactive oxygen species (ROS), which in turn may induce oxidative stress, and even promote mutagenesis. However, little is known about the impact of ROS induced by water limitation on bacteria performing important processes as pollutant biodegradation in the environment. We have rigorously examined the physiological consequences of the rise of intracellular ROS caused by matric stress for the toluene- and xylene-degrading soil bacterium Pseudomonas putida mt-2.

Methods

For the current experiments, controlled matric potential stress was delivered to P. putida cells by addition of polyethylene glycol to liquid cultures, and ROS formation in individual cells monitored by a specific dye. The physiological response to ROS was then quantified by both RT-qPCR of RNA transcripts from genes accredited as proxies of oxidative stress and the SOS response along with cognate transcriptional GFP fusions to the promoters of the same genes.

Results

Extensive matric stress at −1.5 MPa clearly increased intracellular accumulation of ROS. The expression of the two major oxidative defense genes katA and ahpC, as well as the hydroperoxide resistance gene osmC, was induced under matric stress. Different induction profiles of the reporters were related to the severity of the stress. To determine if matric stress lead to induction of the SOS-response, we constructed a DNA damage-inducible bioreporter based on the LexA-controlled phage promoter P_PP3901. According to bioreporter analysis, this gene was expressed during extensive matric stress. Despite this DNA-damage mediated gene induction, we observed no increase in the mutation frequency as monitored by emergence of rifampicin-resistant colonies.

Conclusions

Under conditions of extensive matric stress, we observed a direct link between matric stress, ROS formation, induction of ROS-detoxifying functions and (partial) activation of the SOS system. However, such a stress-response regime did not translate into a general DNA mutagenesis status. Taken together, the data suggest that P. putida mt-2 can cope with this archetypal environmental stress while preserving genome stability, a quality that strengthens the status of this bacterium for biotechnological purposes.

Interactions between closely related bacterial strains are revealed by deep transcriptome sequencing

Comparative genomics, metagenomics, and single-cell technologies have shown that populations of microbial species encompass assemblages of closely related strains. This raises the question of whether individual bacterial lineages respond to the presence of their close relatives by modifying their gene expression or, instead, whether assemblages simply act as the arithmetic addition of their individual components. Here, we took advantage of transcriptome sequencing to address this question. For this, we analyzed the transcriptomes of two closely related strains of the extremely halophilic bacterium Salinibacter ruber grown axenically and in coculture. These organisms dominate bacterial assemblages in hypersaline environments worldwide. The strains used here cooccurred in the natural environment and are 100% identical in their 16S rRNA genes, and each strain harbors an accessory genome representing 10% of its complete genome. Overall, transcriptomic patterns from pure cultures were very similar for both strains. Expression was detected along practically the whole genome albeit with some genes at low levels. A subset of genes was very highly expressed in both strains, including genes coding for the light-driven proton pump xanthorhodopsin, genes involved in the stress response, and genes coding for transcriptional regulators. Expression differences between pure cultures affected mainly genes involved in environmental sensing. When the strains were grown in coculture, there was a modest but significant change in their individual transcription patterns compared to those in pure culture. Each strain sensed the presence of the other and responded in a specific manner, which points to fine intraspecific transcriptomic modulation.

Variability in subpopulation formation propagates into biocatalytic variability of engineered Pseudomonas putida strains

Pivotal challenges in industrial biotechnology are the identification and overcoming of cell-to-cell heterogeneity in microbial processes. While the development of subpopulations of isogenic cells in bioprocesses is well described (intra-population variability), a possible variability between genetically identical cultures growing under macroscopically identical conditions (clonal variability) is not. A high such clonal variability has been found for the recombinant expression of the styrene monooxygenase genes styAB from Pseudomonas taiwanensis VLB120 in solvent-tolerant Pseudomonas putida DOT-T1E using the alk-regulatory system from P. putida GPo1. In this study, the oxygenase subunit StyA fused to eGFP was used as readout tool to characterize the population structure in P. putida DOT-T1E regarding recombinant protein content. Flow cytometric analyses revealed that in individual cultures, at least two subpopulations with highly differing recombinant StyA-eGFP protein contents appeared (intra-population variability). Interestingly, subpopulation sizes varied from culture-to-culture correlating with the specific styrene epoxidation activity of cells derived from respective cultures (clonal variability). In addition, flow cytometric cell sorting coupled to plasmid copy number (PCN) determination revealed that detected clonal variations cannot be correlated to the PCN, but depend on the combination of the regulatory system and the host strain employed. This is, to the best of our knowledge, the first work reporting that intra-population variability (with differing protein contents in the presented case study) causes clonal variability of genetically identical cultures. Respective impacts on bioprocess reliability and performance and strategies to overcome respective reliability issues are discussed.

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.

Pseudomonas putida KT2440 Strain Metabolizes Glucose through a Cycle Formed by Enzymes of the Entner-Doudoroff, Embden-Meyerhof-Parnas, and Pentose Phosphate Pathways

The soil bacterium Pseudomonas putida KT2440 lacks a functional Embden-Meyerhof-Parnas (EMP) pathway, and glycolysis is known to proceed almost exclusively through the Entner-Doudoroff (ED) route. To investigate the raison d'être of this metabolic arrangement, the distribution of periplasmic and cytoplasmic carbon fluxes was studied in glucose cultures of this bacterium by using (13)C-labeled substrates, combined with quantitative physiology experiments, metabolite quantification, and in vitro enzymatic assays under both saturating and non-saturating, quasi in vivo conditions. Metabolic flux analysis demonstrated that 90% of the consumed sugar was converted into gluconate, entering central carbon metabolism as 6-phosphogluconate and further channeled into the ED pathway. Remarkably, about 10% of the triose phosphates were found to be recycled back to form hexose phosphates. This set of reactions merges activities belonging to the ED, the EMP (operating in a gluconeogenic fashion), and the pentose phosphate pathways to form an unforeseen metabolic architecture (EDEMP cycle). Determination of the NADPH balance revealed that the default metabolic state of P. putida KT2440 is characterized by a slight catabolic overproduction of reducing power. Cells growing on glucose thus run a biochemical cycle that favors NADPH formation. Because NADPH is required not only for anabolic functions but also for counteracting different types of environmental stress, such a cyclic operation may contribute to the physiological heftiness of this bacterium in its natural habitats.

The glycerol-dependent metabolic persistence of Pseudomonas putida KT2440 reflects the regulatory logic of the GlpR repressor

The growth of the soil bacterium Pseudomonas putida KT2440 on glycerol as the sole carbon source is characterized by a prolonged lag phase, not observed with other carbon substrates. We examined the bacterial growth in glycerol cultures while monitoring the metabolic activity of individual cells. Fluorescence microscopy and flow cytometry, as well as the analysis of the temporal start of growth in single-cell cultures, revealed that adoption of a glycerol-metabolizing regime was not the result of a gradual change in the whole population but rather reflected a time-dependent bimodal switch between metabolically inactive (i.e., nongrowing) and fully active (i.e., growing) bacteria. A transcriptional Φ(glpD-gfp) fusion (a proxy of the glycerol-3-phosphate [G3P] dehydrogenase activity) linked the macroscopic phenotype to the expression of the glp genes. Either deleting glpR (encoding the G3P-responsive transcriptional repressor that controls the expression of the glpFKRD gene cluster) or altering G3P formation (by overexpressing glpK, encoding glycerol kinase) abolished the bimodal glpD expression. These manipulations eliminated the stochastic growth start by shortening the otherwise long lag phase. Provision of glpR in trans restored the phenotypes lost in the ΔglpR mutant. The prolonged nongrowth regime of P. putida on glycerol could thus be traced to the regulatory device controlling the transcription of the glp genes. Since the physiological agonist of GlpR is G3P, the arrangement of metabolic and regulatory components at this checkpoint merges a positive feedback loop with a nonlinear transcriptional response, a layout fostering the observed time-dependent shift between two alternative physiological states.

Phenotypic variation is a widespread attribute of prokaryotes that leads, inter alia, to the emergence of persistent bacteria, i.e., live but nongrowing members within a genetically clonal population. Persistence allows a fraction of cells to avoid the killing caused by conditions or agents that destroy most growing bacteria (e.g., some antibiotics). Known molecular mechanisms underlying the phenomenon include genetic changes, epigenetic variations, and feedback-based multistability. We show that a prolonged nongrowing state of the bacterial population can be brought about by a distinct regulatory architecture of metabolic genes when cells face specific nutrients (e.g., glycerol). Pseudomonas putida may have adopted the resulting carbon source-dependent metabolic bet hedging as an advantageous trait for exploring new chemical and nutritional landscapes. Defeating such naturally occurring adaptive features of environmental bacteria is instrumental in improving the performance of these microorganisms as whole-cell catalysts in a bioreactor setup.

Proteomic characterization of the outer membrane vesicle of Pseudomonas putida KT2440

Outer membrane vesicles (OMVs) are produced by various pathogenic Gram-negative bacteria such as Escherichia coli, Pseudomonas aeruginosa, and Acinetobacter baumannii. In this study, we isolated OMVs from a representative soil bacterium, Pseudomonas putida KT2440, which has a biodegradative activity toward various aromatic compounds. Proteomic analysis identified the outer membrane proteins (OMPs) OprC, OprD, OprE, OprF, OprH, OprG, and OprW as major components of the OMV of P. putida KT2440. The production of OMVs was dependent on the nutrient availability in the culture media, and the up- or down-regulation of specific OMPs was observed according to the culture conditions. In particular, porins (e.g., benzoate-specific porin, BenF-like porin) and enzymes (e.g., catechol 1,2-dioxygenase, benzoate dioxygenase) for benzoate degradation were uniquely found in OMVs prepared from P. putida KT2440 that were cultured in media containing benzoate as the energy source. OMVs of P. putida KT2440 showed low pathological activity toward cultured cells that originated from human lung cells, which suggests their potential as adjuvants or OMV vaccine carriers. Our results suggest that the protein composition of the OMVs of P. putida KT2440 reflects the characteristics of the total proteome of P. putida KT2440.