High-throughput dilution-based growth method enables time-resolved exo-metabolomics of Pseudomonas putida and Pseudomonas aeruginosa

Understanding metabolism is fundamental to access and harness bacterial physiology. In most bacteria, nutrient utilization is hierarchically optimized according to their energetic potential and their availability in the environment to maximise growth rates. Low-throughput methods have been largely used to characterize bacterial metabolic profiles. However, in-depth analysis of large collections of strains across several conditions is challenging since high-throughput approaches are still limited – especially for non-traditional hosts. Here, we developed a high-throughput dilution-resolved cultivation method for metabolic footprinting of Pseudomonas putida and Pseudomonas aeruginosa. This method was benchmarked against a conventional low-throughput time-resolved cultivation approach using either a synthetic culture medium (where a single carbon source is present) for P. putida or a complex nutrient mixture for P. aeruginosa. Dynamic metabolic footprinting, either by sugar quantification or by targeted exo-metabolomic analyses, revealed overlaps between the bacterial metabolic profiles irrespective of the cultivation strategy, suggesting a certain level of robustness and flexibility of the high-throughput dilution-resolved method. Cultivation of P. putida in microtiter plates imposed a metabolic constraint, dependent on oxygen availability, which altered the pattern of secreted metabolites at the level of sugar oxidation. Deep-well plates, however, constituted an optimal cultivation set-up yielding consistent and comparable metabolic profiles across conditions and strains. Altogether, the results illustrate the usefulness of this technological advance for high-throughput analyses of bacterial metabolism for both biotechnological applications and automation purposes.     

Unravelling the thioesterases responsible for propionate formation in engineered Pseudomonas putida KT2440

Pseudomonas putida KT2440 is becoming a new robust metabolic chassis for biotechnological applications, due to its metabolic versatility, low nutritional requirements and biosafety status. We have previously engineered P. putida KT2440 to be an efficient propionate producer from L-threonine, although the internal enzymes converting propionyl-CoA to propionate are not clear. In this study, we thoroughly investigated 13 genes annotated as potential thioesterases in the KT2440 mutant. One thioesterase encoded by locus tag PP_4975 was verified to be the major contributor to propionate production in vivo. Deletion of PP_4975 significantly decreased propionate production, whereas the performance was fully restored by gene complement. Compared with thioesterase HiYciA from Haemophilus influenza, thioesterase PP_4975 showed a faster substrate conversion rate in vitro. Thus, this study expands our knowledge on acyl-CoA thioesterases in P. putida KT2440 and may also reveal a new target for further engineering the strain to improve propionate production performance.     

Metabolic reconstruction and flux analysis of industrial Pichia yeasts

Pichia yeasts have been recognized as important microbial cell factories in the biotechnological industry. Notably, the Pichia pastoris and Pichia stipitis species have attracted much research interest due to their unique cellular physiology and metabolic capability: P. pastoris has the ability to utilize methanol for cell growth and recombinant protein production, while P. stipitis is capable of assimilating xylose to produce ethanol under oxygen-limited conditions. To harness these characteristics for biotechnological applications, it is highly required to characterize their metabolic behavior. Recently, following the genome sequencing of these two Pichia species, genome-scale metabolic networks have been reconstructed to model the yeasts’ metabolism from a systems perspective. To date, there are three genome-scale models available for each of P. pastoris and P. stipitis. In this mini-review, we provide an overview of the models, discuss certain limitations of previous studies, and propose potential future works that can be conducted to better understand and engineer Pichia yeasts for industrial applications.     

Reconciliation of genome-scale metabolic reconstructions for comparative systems analysis

In the past decade, over 50 genome-scale metabolic reconstructions have been built for a variety of single- and multi- cellular organisms. These reconstructions have enabled a host of computational methods to be leveraged for systems-analysis of metabolism, leading to greater understanding of observed phenotypes. These methods have been sparsely applied to comparisons between multiple organisms, however, due mainly to the existence of differences between reconstructions that are inherited from the respective reconstruction processes of the organisms to be compared. To circumvent this obstacle, we developed a novel process, termed metabolic network reconciliation, whereby non-biological differences are removed from genome-scale reconstructions while keeping the reconstructions as true as possible to the underlying biological data on which they are based. This process was applied to two organisms of great importance to disease and biotechnological applications, Pseudomonas aeruginosa and Pseudomonas putida, respectively. The result is a pair of revised genome-scale reconstructions for these organisms that can be analyzed at a systems level with confidence that differences are indicative of true biological differences (to the degree that is currently known), rather than artifacts of the reconstruction process. The reconstructions were re-validated with various experimental data after reconciliation. With the reconciled and validated reconstructions, we performed a genome-wide comparison of metabolic flexibility between P. aeruginosa and P. putida that generated significant new insight into the underlying biology of these important organisms. Through this work, we provide a novel methodology for reconciling models, present new genome-scale reconstructions of P. aeruginosa and P. putida that can be directly compared at a network level, and perform a network-wide comparison of the two species. These reconstructions provide fresh insights into the metabolic similarities and differences between these important Pseudomonads, and pave the way towards full comparative analysis of genome-scale metabolic reconstructions of multiple species.     

Becoming settlers: Elements and mechanisms for surface colonization by Pseudomonas putida

Pseudomonads are considered to be among the most widespread culturable bacteria in mesophilic environments. The evolutive success of Pseudomonas species can be attributed to their metabolic versatility, in combination with a set of additional functions that enhance their ability to colonize different niches. These include the production of secondary metabolites involved in iron acquisition or having a detrimental effect on potential competitors, different types of motility, and the capacity to establish and persist within biofilms. Although biofilm formation has been extensively studied using the opportunistic pathogen Pseudomonas aeruginosa as a model organism, a significant body of knowledge is also becoming available for non-pathogenic Pseudomonas. In this review, we focus on the mechanisms that allow Pseudomonas putida to colonize biotic and abiotic surfaces and adapt to sessile life, as a relevant persistence strategy in the environment. This species is of particular interest because it includes plant-beneficial strains, in which colonization of plant surfaces may be relevant, and strains used for environmental and biotechnological applications, where the design and functionality of biofilm-based bioreactors, for example, also have to take into account the efficiency of bacterial colonization of solid surfaces. This work reviews the current knowledge of mechanistic and regulatory aspects of biofilm formation by P. putida and pinpoints the prospects in this field.     

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.     

Pseudomonas putida KT2440 metabolism undergoes sequential modifications during exponential growth in a complete medium as compounds are gradually consumed

Pseudomonas putida is a soil bacterium with a versatile and robust metabolism. When confronted with mixtures of carbon sources, it prioritizes the utilization of the preferred compounds, optimizing metabolism and growth. This response is particularly strong when growing in a complex medium such as LB. This work examines the changes occurring in P. putida KT2440 metabolic fluxes, while it grows exponentially in LB medium and sequentially consumes the compounds available. Integrating the uptake rates for each compound at three different moments during the exponential growth with the changes observed in the proteome, and with the metabolic fluxes predicted by the iJN1411 metabolic model for this strain, allowed the metabolic rearrangements that occurred to be determined. The results indicate that the bacterium changes significantly the configuration of its metabolism during the early, mid and late exponential phases of growth. Sugars served as an energy source during the early phase and later as energy and carbon source. The configuration of the tricarboxylic acids cycle varied during growth, providing no energy in the early phase, and turning to a reductive mode in the mid phase and to an oxidative mode later on. This work highlights the dynamism and flexibility of P. putida metabolism.     

Engineering sucrose metabolism in Pseudomonas putida highlights the importance of porins

Using agricultural wastes as a substrate for biotechnological processes is of great interest in industrial biotechnology. A prerequisite for using these wastes is the ability of the industrially relevant microorganisms to metabolize the sugars present therein. Therefore, many metabolic engineering approaches are directed towards widening the substrate spectrum of the workhorses of industrial biotechnology like Escherichia coli, yeast or Pseudomonas putida. For instance, neither xylose or arabinose from cellulosic residues, nor sucrose, the main sugar in waste molasses, can be metabolized by most E. coli and P. putida wild types. We evaluated a new, so far uncharacterized gene cluster for sucrose metabolism from Pseudomonas protegens Pf-5 and showed that it enables P. putida to grow on sucrose as the sole carbon and energy source. Even when integrated into the genome of P. putida, the resulting strain grew on sucrose at rates similar to the rate of the wild type on glucose – making it the fastest growing, plasmid-free P. putida strain known so far using sucrose as substrate. Next, we elucidated the role of the porin, an orthologue of the sucrose porin ScrY, in the gene cluster and found that in P. putida, a porin is needed for sucrose transport across the outer membrane. Consequently, native porins were not sufficient to allow unlimited growth on sucrose. Therefore, we concluded that the outer membrane can be a considerable barrier for substrate transport, depending on strain, genotype and culture conditions, all of which should be taken into account in metabolic engineering approaches. We additionally showed the potential of the engineered P. putida strains by growing them on molasses with efficiencies twice as high as obtained with the wild-type P. putida. This can be seen as a further step towards the production of low-value chemicals and biofuels with P. putida from alternative and more affordable substrates in the future.     

Luciferase and fluorescent protein as dual reporters analyzing the effect of <Emphasis Type="Italic">n</Emphasis>-dodecyltrimethylammonium bromide on the physiology of <Emphasis Type="Italic">Pseudomonas putida</Emphasis>

With the growing interest in using surfactants to improve microbial cell performance for whole-cell biocatalysis and bioremediation, understanding the interactions between surfactants and bacteria is of great importance. By using cyanine fluorescent protein (CFP) and bacterial luciferase (LUX) as dual bioreporters, the effects of n-dodecyltrimethylammonium bromide (DTAB) on the whole cells and intracellular proteins in Pseudomonas putida cultures were quantitatively and systematically studied. The dual reporter system was shown to be a useful indicator to assess the effect of DTAB treatment on whole-cell metabolic activity, membrane permeability, and cellular enzyme activity. CFP was useful to assess the leakage of intracellular enzymes and the lysis of cells and was able to reflect the activities of most cellular enzymes, while LUX reflected the permeability of cell membranes and cellular metabolic activity. The validity of CFP–LUX dual bioreporters was further confirmed by detecting changes in extracellular proteins, membrane potential, oxygen consumption rate (OUR), and intracellular catechol 2,3-dioxygenase (C23O) activity with the addition of DTAB. The dual LUX–CFP bioreporter is a useful tool for analyzing the surfactant–bacterium interactions for biotechnological applications.     

CRISPR/Cas9-enhanced ssDNA recombineering for Pseudomonas putida

Implementation of single-stranded DNA (ssDNA) recombineering in Pseudomonas putida has widened the range of genetic manipulations applicable to this biotechnologically relevant bacterium. Yet, the relatively low efficiency of the technology hampers identification of mutated clones lacking conspicuous phenotypes. Fortunately, the use of CRISPR/Cas9 as a device for counterselection of wild-type sequences helps to overcome this limitation. Merging ssDNA recombineering with CRISPR/Cas9 thus enables a suite of genomic edits with a straightforward approach: a CRISPR plasmid provides the spacer DNA sequence that directs the Cas9 nuclease ribonucleoprotein complex to cleave the genome at the wild-type sequences that have not undergone the change entered by the mutagenic ssDNA oligonucleotide(s). This protocol describes a complete workflow of the method optimized for P. putida, although it could in principle be applicable to many other pseudomonads. As an example, we show the deletion of the edd gene that encodes one key enzyme that operates the EDEMP cycle for glucose metabolism in P. putida EM42. By combining two incompatible CRISPR plasmids with different antibiotic selection markers, we show that the procedure can be cycled to implement consecutive deletions in the same strain, e.g. deletion of the pyrF gene following that of the edd mutant. This approach adds to the wealth of genetic technologies available for P. putida and strengthens its status as a chassis of choice for a suite of biotechnological applications.     

Production of selenium nanoparticles occurs through an interconnected pathway of sulphur metabolism and oxidative stress response in Pseudomonas putida KT2440

The soil bacterium Pseudomonas putida KT2440 has been shown to produce selenium nanoparticles aerobically from selenite; however, the molecular actors involved in this process are unknown. Here, through a combination of genetic and analytical techniques, we report the first insights into selenite metabolism in this bacterium. Our results suggest that the reduction of selenite occurs through an interconnected metabolic network involving central metabolic reactions, sulphur metabolism, and the response to oxidative stress. Genes such as sucA, D2HGDH and PP_3148 revealed that the 2-ketoglutarate and glutamate metabolism is important to convert selenite into selenium. On the other hand, mutations affecting the activity of the sulphite reductase decreased the bacteria's ability to transform selenite. Other genes related to sulphur metabolism (ssuEF, sfnCE, sqrR, sqr and pdo2) and stress response (gqr, lsfA, ahpCF and sadI) were also identified as involved in selenite transformation. Interestingly, suppression of genes sqrR, sqr and pdo2 resulted in the production of selenium nanoparticles at a higher rate than the wild-type strain, which is of biotechnological interest. The data provided in this study brings us closer to understanding the metabolism of selenium in bacteria and offers new targets for the development of biotechnological tools for the production of selenium nanoparticles.     

Rhamnolipids produced by Pseudomonas: from molecular genetics to the market

Rhamnolipids are biosurfactants with a wide range of industrial applications that entered into the market a decade ago. They are naturally produced by Pseudomonas aeruginosa and some Burkholderia species. Occasionally, some strains of different bacterial species, like Pseudomonas chlororaphis NRRL B-30761, which have acquired RL-producing ability by horizontal gene transfer, have been described. P. aeruginosa, the ubiquitous opportunistic pathogenic bacterium, is the best rhamnolipids producer, but Pseudomonas putida has been used as heterologous host for the production of this biosurfactant with relatively good yields. The molecular genetics of rhamnolipids production by P. aeruginosa has been widely studied not only due to the interest in developing overproducing strains, but because it is coordinately regulated with the expression of different virulence-related traits by the quorum-sensing response. Here, we highlight how the research of the molecular mechanisms involved in rhamnolipid production have impacted the development of strains that are suitable for industrial production of this biosurfactant, as well as some perspectives to improve these industrial useful strains.     

Systems-level analysis of genome-scalein silico metabolic models using MetaFluxNet

The systems-level analysis of microbes with myriad of heterologous data generated by omics technologies has been applied to improve our understanding of cellular function and physiology and consequently to enhance production of various bioproducts. At the heart of this revolution residesin silico genome-scale metabolic model. In order to fully exploit the power of genome-scale model, a systematic approach employing user-friendly software is required. Metabolic flux analysis of genome-scale metabolic network is becoming widely employed to quantify the flux distribution and validate model-driven hypotheses. Here we describe the development of an upgraded MetaFluxNet which allows (1) construction of metabolic models connected to metabolic databases, (2) calculation of fluxes by metabolic flux analysis, (3) comparative flux analysis with flux-profile visualization, (4) the use of metabolic flux analysis markup language to enable models to be exchanged efficiently, and (5) the exporting of data from constraints-based flux analysis into various formats. MetaFluxNet also allows cellular physiology to be predicted and strategies for strain improvement to be developed from genome-based information on flux distributions. This integrated software environment promises to enhance our understanding on metabolic network at a whole organism level and to establish novel strategies for improving the properties of organisms for various biotechnological applications.     

Biodesulfurization in Biphasic Systems Containing Organic Solvents

Biphasic systems can overcome the problem of low productivity in conventional media and have been exploited for biocatalysis. Solvent-tolerant microorganisms are useful in biotransformation with whole cells in biphasic reactions. A solvent-tolerant desulfurizing bacterium, Pseudomonas putida A4, was constructed by introducing the biodesulfurizing gene cluster dszABCD, which was from Rhodococcus erythropolis XP, into the solvent-tolerant strain P. putida Idaho. Biphasic reactions were performed to investigate the desulfurization of various sulfur-containing heterocyclic compounds in the presence of various organic solvents. P. putida A4 had the same substrate range as R. erythropolis XP and could degrade dibenzothiophene at a specific rate of 1.29 mM g (dry weight) of cells⁻¹ h⁻¹ for the first 2 h in the presence of 10% (vol/vol) p-xylene. P. putida A4 was also able to degrade dibenzothiophene in the presence of many other organic solvents at a concentration of 10% (vol/vol). This study is a significant step in the exploration of the biotechnological potential of novel biocatalysts for developing an efficient biodesulfurization process in biphasic reaction mixtures containing toxic organic solvents.     

The Ssr protein (T1E_1405) from Pseudomonas putida DOT‐T1E enables oligonucleotide‐based recombineering in platform strain P. putida EM42

Some strains of the soil bacterium Pseudomonas putida have become in recent years platforms of choice for hosting biotransformations of industrial interest. Despite availability of many genetic tools for this microorganism, genomic editing of the cell factory P. putida EM42 (a derivative of reference strain KT2440) is still a time‐consuming endeavor. In this work we have investigated the in vivo activity of the Ssr protein encoded by the open reading frame T1E_1405 from Pseudomonas putida DOT‐T1E, a plausible functional homologue of the β protein of the Red recombination system of λ phage of Escherichia coli. A test based on the phenotypes of pyrF mutants of P. putida (the yeast's URA3 ortholog) was developed for quantifying the ability of Ssr to promote invasion of the genomic DNA replication fork by synthetic oligonucleotides. The efficiency of the process was measured by monitoring the inheritance of the changes entered into pyrF by oligonucleotides bearing mutated sequences. Ssr fostered short and long genomic deletions/insertions at considerable frequencies as well as single‐base swaps not affected by mismatch repair. These results not only demonstrate the feasibility of recombineering in P. putida, but they also enable a suite of multiplexed genomic manipulations in this biotechnologically important bacterium.     

An automated DIY framework for experimental evolution of Pseudomonas putida

Adaptive laboratory evolution (ALE) is a general and effective strategy for optimizing the design of engineered genetic circuits and upgrading metabolic phenotypes. However, the specific characteristics of each microorganism typically ask for exclusive conditions that need to be adjusted to the biological chassis at stake. In this work, we have adopted a do-it-yourself (DIY) approach to implement a flexible and automated framework for performing ALE experiments with the environmental bacterium and metabolic engineering platform Pseudomonas putida. The setup includes a dual-chamber semi-continuous log-phase bioreactor design combined with an anti-biofilm layout to manage specific traits of this bacterium in long-term cultivation experiments. As a way of validation, the prototype was instrumental for selecting fast-growing variants of a P. putida strain engineered to metabolize D-xylose as sole carbon and energy source after running an automated 42 days protocol of iterative regrowth. Several genomic changes were identified in the evolved population that pinpointed the role of RNA polymerase in controlling overall physiological conditions during metabolism of the new carbon source.     

Anaerobic C–H Oxyfunctionalization: Coupling of Nitrate Reduction and Quinoline Hydroxylation in Recombinant Pseudomonas putida

Whole‐cell biocatalysis for C–H oxyfunctionalization depends on and is often limited by O₂ mass transfer. In contrast to oxygenases, molybdenum hydroxylases use water instead of O₂ as an oxygen donor and thus have the potential to relieve O₂ mass transfer limitations. Molybdenum hydroxylases may even allow anaerobic oxyfunctionalization when coupled to anaerobic respiration. To evaluate this option, the coupling of quinoline hydroxylation to denitrification is tested under anaerobic conditions employing Pseudomonas putida (P. putida) 86, capable of aerobic growth on quinoline. P. putida 86 reduces both nitrate and nitrite, but at low rates, which does not enable significant growth and quinoline hydroxylation. Introduction of the nitrate reductase from Pseudomonas aeruginosa enables considerable specific quinoline hydroxylation activity (6.9 U g_CDW^?1) under anaerobic conditions with nitrate as an electron acceptor and 2‐hydroxyquinoline as the sole product (further metabolization depends on O₂). Hydroxylation‐derived electrons are efficiently directed to nitrate, accounting for 38% of the respiratory activity. This study shows that molybdenum hydroxylase‐based whole‐cell biocatalysts enable completely anaerobic carbon oxyfunctionalization when coupled to alternative respiration schemes such as nitrate respiration.     

Integrative network analysis reveals active microRNAs and their functions in gastric cancer

Background

Ralstonia eutropha H16, found in both soil and water, is a Gram-negative lithoautotrophic bacterium that can utillize CO₂ and H₂ as its sources of carbon and energy in the absence of organic substrates. R. eutropha H16 can reach high cell densities either under lithoautotrophic or heterotrophic conditions, which makes it suitable for a number of biotechnological applications. It is the best known and most promising producer of polyhydroxyalkanoates (PHAs) from various carbon substrates and is an environmentally important bacterium that can degrade aromatic compounds. In order to make R. eutropha H16 a more efficient and robust biofactory, system-wide metabolic engineering to improve its metabolic performance is essential. Thus, it is necessary to analyze its metabolic characteristics systematically and optimize the entire metabolic network at systems level.

Results

We present the lithoautotrophic genome-scale metabolic model of R. eutropha H16 based on the annotated genome with biochemical and physiological information. The stoichiometic model, RehMBEL1391, is composed of 1391 reactions including 229 transport reactions and 1171 metabolites. Constraints-based flux analyses were performed to refine and validate the genome-scale metabolic model under environmental and genetic perturbations. First, the lithoautotrophic growth characteristics of R. eutropha H16 were investigated under varying feeding ratios of gas mixture. Second, the genome-scale metabolic model was used to design the strategies for the production of poly[R-(-)-3hydroxybutyrate] (PHB) under different pH values and carbon/nitrogen source uptake ratios. It was also used to analyze the metabolic characteristics of R. eutropha when the phosphofructokinase gene was expressed. Finally, in silico gene knockout simulations were performed to identify targets for metabolic engineering essential for the production of 2-methylcitric acid in R. eutropha H16.

Conclusion

The genome-scale metabolic model, RehMBEL1391, successfully represented metabolic characteristics of R. eutropha H16 at systems level. The reconstructed genome-scale metabolic model can be employed as an useful tool for understanding its metabolic capabilities, predicting its physiological consequences in response to various environmental and genetic changes, and developing strategies for systems metabolic engineering to improve its metabolic performance.