Recommended measurement instruments for menopausal vasomotor symptoms: the COMMA (Core Outcomes in Menopause) consortium.

OBJECTIVE: The aim of the study is to identify suitable definitions and patient-reported outcome measures (PROMs) to assess each of the six core outcomes previously identified through the COMMA (Core Outcomes in Menopause) global consensus process relating to vasomotor symptoms: frequency, severity, distress/bother/interference, impact on sleep, satisfaction with treatment, and side effects. METHODS: A systematic review was conducted to identify relevant definitions for the outcome of side-effects and PROMs with acceptable measurement properties for the remaining five core outcomes. The consensus process, involving 36 participants from 16 countries, was conducted to review definitions and PROMs and make final recommendations for the measurement of each core outcome. RESULTS: A total of 21,207 publications were screened from which 119 reporting on 40 PROMs were identified. Of these 40 PROMs, 36 either did not adequately map onto the core outcomes or lacked sufficient measurement properties. Therefore, only four PROMs corresponding to two of the six core outcomes were considered for recommendation. We recommend the Hot Flash Related Daily Interference Scale to measure the domain of distress, bother, or interference of vasomotor symptoms and to capture impact on sleep (one item in the Hot Flash Related Daily Interference Scale captures interference with sleep). Six definitions of "side effects" were identified and considered. We recommend that all trials report adverse events, which is a requirement of Good Clinical Practice. CONCLUSIONS: We identified suitable definitions and PROMs for only three of the six core outcomes. No suitable PROMs were found for the remaining three outcomes (frequency and severity of vasomotor symptoms and satisfaction with treatment). Future studies should develop and validate PROMs for these outcomes.

Removal of selected sulfonamides and sulfonamide resistance genes from wastewater in full-scale constructed wetlands.

Sulfonamides are high-consumption antibiotics that reach the aquatic environment. The threat related to their presence in wastewater and the environment is not only associated with their antibacterial properties, but also with risk of the spread of drug resistance in bacteria. Therefore, the aim of this work was to evaluate the occurrence of eight commonly used sulfonamides, sulfonamide resistance genes (sul1-3) and integrase genes intI1-3 in five full-scale constructed wetlands (CWs) differing in design (including hybrid systems) and in the source of wastewater (agricultural drainage, domestic sewage/surface runoff, and animal runs runoff in a zoo). The CWs were located in low-urbanized areas in Poland and in Czechia. No sulfonamides were detected in the CW treating agricultural tile drainage water. In the other four systems, four sulfonamide compounds were detected. Sulfamethoxazole exhibited the highest concentration in those four CWs and its highest was 12,603.23 ± 1000.66 ng/L in a CW treating a mixture of domestic sewage and surface runoff. Despite the high removal efficiencies of sulfamethoxazole in the tested CWs (86 %-99 %), it was still detected in the treated wastewater. The sul1 genes occurred in all samples of raw and treated wastewater and their abundance did not change significantly after the treatment process and it was, predominantly, at the level 105 gene copies numbers/mL. Noteworthy, sul2 genes were only found in the influents, and sul3 were not detected. The sulfonamides can be removed in CWs, but their elimination is not complete. However, hybrid CWs treating sewage were superior in decreasing the relative abundance of genes and the concentration of SMX. CWs may play a role in the dissemination of sulfonamide resistance genes of the sul1 type and other determinants of drug resistance, such as the intI1 gene, in the environment, however, the magnitude of this phenomenon is a matter of further research.

Linkages between the concept of nature-based solutions and the notion of landscape.

As the effects of Nature-based solutions (NBS) application are usually much broader than only the area under the project implementation, it is necessary to capture the impact on these actions of landscape as well as the influence of landscape type on the NBS effectiveness. The main aim of this study was to detect linkages between the operational of NBS and the landscape dimention, based on a systematic literature review. The results showed the existence of seven linkages: (1, 2) 'input' and 'output' resulting from the consideration of landscape as a scale of NBS implementation; (3, 4) 'stimulator' and 'inspiration' based on the contribution of landscape-based management to the implementation of NBS; (5) 'co-beneficiary' since the implementation of NBS affects aesthetic dimensions of landscape; (6) 'tool' as landscape-based indicators are used to assess the impacts of NBS; and (7) 'foundation' as health-supporting landscapes may be considered as a type of NBS action.

On-line targeted metabolomics for real-time monitoring of relevant compounds in fermentation processes.

Fermentation monitoring is a powerful tool for bioprocess development and optimization. On-line metabolomics is a technology that is starting to gain attention as a bioprocess monitoring tool, allowing the direct measurement of many compounds in the fermentation broth at a very high time resolution. In this work, targeted on-line metabolomics was used to monitor 40 metabolites of interest during three Escherichia coli succinate production fermentation experiments every 5 min with a triple quadrupole mass spectrometer. This allowed capturing high-time resolution biological data that can provide critical information for process optimization. For nine of these metabolites, simple univariate regression models were used to model compound concentration from their on-line mass spectrometry peak area. These on-line metabolomics univariate models performed comparably to vibrational spectroscopy multivariate partial least squares regressions models reported in the literature, which typically are much more complex and time consuming to build. In conclusion, this work shows how on-line metabolomics can be used to directly monitor many bioprocess compounds of interest and obtain rich biological and bioprocess data.

Microalgae harvesting for wastewater treatment and resources recovery: A review.

Microalgae-based wastewater treatment has been conceived to obtain reclaimed water and produce microalgal biomass for bio-based products and biofuels generation. However, microalgal biomass harvesting is challenging and expensive, hence one of the main bottlenecks for full-scale implementation. Finding an integrated approach that covers concepts of engineering, green chemistry and the application of microbial anabolism driven towards the harvesting processes, is mandatory for the widespread establishment of full-scale microalgae wastewater treatment plants. By using nature-based substances and applying concepts of chemical functionalization in already established harvesting methods, the costs of harvesting processes could be reduced while preventing microalgae biomass contamination. Moreover, microalgae produced during wastewater treatment have unique culture characteristics, such as the consortia, which are primarily composed of microalgae and bacteria, that should be accounted for prior to downstream processing. The aim of this review is to examine recent advances in microalgal biomass harvesting and recovery in wastewater treatment systems, considering the impact of consortia variability. The costs of available harvesting technologies, such as coagulation/flocculation, coupled to sedimentation and differential air flotation, are provided. Additionally, promising technologies are discussed, including autoflocculation, bioflocculation, new filtration materials, nanotechnology, microfluidic and magnetic methods.

New strategy for bioplastic and exopolysaccharides production: Enrichment of field microbiomes with cyanobacteria.

Seven photosynthethic microbiomes were collected from field environmental samples to test their potential in polyhydroxybutyrate (PHB) and exopolysaccharides (EPS) production, both alternatives to chemical-based polymers. Microscope observations together with microbial sequence analysis revealed the microbiome enrichment in cyanobacteria after culture growth under phosphorus limitation. PHB and EPS production were studied under three culture factors (phototrophy, mixotrophy and heterotrophy) by evaluating and optimizing the effect of three parameters (organic and inorganic carbon and days under light:dark cycles) by Box-Behnken design. Results showed that optimal conditions for both biopolymers synthesis were microbiome-dependent; however, the addition of organic carbon boosted PHB production in all the tested microbiomes, producing up to 14 %dcw PHB with the addition of 1.2 g acetate·L-1 and seven days under light:dark photoperiods. The highest EPS production was 59 mg·L-1 with the addition of 1.2 g acetate·L-1 and four days under light:dark photoperiods. The methodology used is suitable for enriching microbiomes in cyanobacteria, and for testing the best conditions for bioproduct synthesis for further scale up.

Streamlined identification of strain engineering targets for bioprocess improvement using metabolic pathway enrichment analysis.

Metabolomics is a powerful tool for the identification of genetic targets for bioprocess optimisation. However, in most cases, only the biosynthetic pathway directed to product formation is analysed, limiting the identification of these targets. Some studies have used untargeted metabolomics, allowing a more unbiased approach, but data interpretation using multivariate analysis is usually not straightforward and requires time and effort. Here we show, for the first time, the application of metabolic pathway enrichment analysis using untargeted and targeted metabolomics data to identify genetic targets for bioprocess improvement in a more streamlined way. The analysis of an Escherichia coli succinate production bioprocess with this methodology revealed three significantly modulated pathways during the product formation phase: the pentose phosphate pathway, pantothenate and CoA biosynthesis and ascorbate and aldarate metabolism. From these, the two former pathways are consistent with previous efforts to improve succinate production in Escherichia coli. Furthermore, to the best of our knowledge, ascorbate and aldarate metabolism is a newly identified target that has so far never been explored for improving succinate production in this microorganism. This methodology therefore represents a powerful tool for the streamlined identification of strain engineering targets that can accelerate bioprocess optimisation.

On the holobiont 'predictome' of immunocompetence in pigs.

BACKGROUND: Gut microbial composition plays an important role in numerous traits, including immune response. Integration of host genomic information with microbiome data is a natural step in the prediction of complex traits, although methods to optimize this are still largely unexplored. In this paper, we assess the impact of different modelling strategies on the predictive capacity for six porcine immunocompetence traits when both genotype and microbiota data are available. METHODS: We used phenotypic data on six immunity traits and the relative abundance of gut bacterial communities on 400 Duroc pigs that were genotyped for 70 k SNPs. We compared the predictive accuracy, defined as the correlation between predicted and observed phenotypes, of a wide catalogue of models: reproducing kernel Hilbert space (RKHS), Bayes C, and an ensemble method, using a range of priors and microbial clustering strategies. Combined (holobiont) models that include both genotype and microbiome data were compared with partial models that use one source of variation only. RESULTS: Overall, holobiont models performed better than partial models. Host genotype was especially relevant for predicting adaptive immunity traits (i.e., concentration of immunoglobulins M and G), whereas microbial composition was important for predicting innate immunity traits (i.e., concentration of haptoglobin and C-reactive protein and lymphocyte phagocytic capacity). None of the models was uniformly best across all traits. We observed a greater variability in predictive accuracies across models when microbiability (the variance explained by the microbiome) was high. Clustering microbial abundances did not necessarily increase predictive accuracy. CONCLUSIONS: Gut microbiota information is useful for predicting immunocompetence traits, especially those related to innate immunity. Modelling microbiome abundances deserves special attention when microbiability is high. Clustering microbial data for prediction is not recommended by default.

Constructed wetlands for winery wastewater treatment: A review on the technical, environmental and socio-economic benefits.

In wineries, wastewater production and solid waste generation can pose serious environmental threats. Winery wastewater production has a seasonal behavior and needs a treatment system that can adapt to these fluctuations while reducing costs, and environmental impacts and promoting other winery activities. The implementation of constructed wetlands (CWs) has been demonstrated to be a competitive solution for winery wastewater and sludge treatment. In this article, worldwide experiences over the last 25 years of CWs for winery wastewater treatment are reviewed. The review shows that the application of hybrid CWs coupled with anaerobic digestion can reduce >90 % of the organic pollutants and solids from winery wastewater while avoiding clogging. These efficiencies and advantages can be also attained with French vertical systems. Not only CWs have a good technical performance, but they also reduce up to >90 % the environmental impacts associated with winery wastewater treatment. It is due to low energy requirements, no chemicals consumption and avoidance of off-site management and transportation practices. In terms of costs, CWs can reduce up to 60 times the costs associated with winery wastewater treatment and management. More efforts should be made in order to define the social benefits of this technology and the quality of the recovered resources (e.g. treated water, fertilizer) in order to promote the circular economy without compromising human and ecosystem health.

Discovery and Development of a Selective Inhibitor of the ER Resident Chaperone Grp78.

A recent study illustrated that a fluorescence polarization assay can be used to identify substrate-competitive Hsp70 inhibitors that can be isoform-selective. Herein, we use that assay in a moderate-throughput screen and report the discovery of a druglike amino-acid-based inhibitor with reasonable specificity for the endoplasmic reticular Hsp70, Grp78. Using traditional medicinal chemistry approaches, the potency and selectivity were further optimized through structure-activity relationship (SAR) studies in parallel assays for six of the human Hsp70 isoforms. The top compounds were all tested against a panel of cancer cell lines and disappointingly showed little effect. The top-performing compound, 8, was retested using a series of endoplasmic reticulum (ER) stress-inducing agents and found to synergize with these agents. Finally, 8 was tested in a spheroid tumor model and found to be more potent than in two-dimensional models. The optimized Grp78 inhibitors are the first reported isoform-selective small-molecule-competitive inhibitors of an Hsp70-substrate interaction.

Production of phycobiliproteins, bioplastics and lipids by the cyanobacteria Synechocystis sp. treating secondary effluent in a biorefinery approach.

Cyanobacteria have been identified as promising organisms to reuse nutrients from waste effluents and produce valuable compounds such as lipids, polyhydroxyalkanoates (PHAs), and pigments. However, almost all studies on cyanobacterial biorefineries have been performed under lab scale and short cultivation periods. The present study evaluates the cultivation of the cyanobacterium Synechocystis sp. in a pilot scale 30 L semi-continuous photobioreactor fed with secondary effluent for a period of 120 days to produce phycobiliproteins, polyhydroxybutyrate (PHB) and lipids. To this end, the harvested biomass from the semi-continuous photobioreactor was transferred into 5 L vertical column batch photobioreactors to perform PHB and lipid accumulation under nutrient starvation. Three hydraulic retention times (HRT) (6, 8 and 10 days) were tested in the semi-continuous photobioreactor to evaluate its influence on biomass growth and microbial community. A maximum biomass concentration of 1.413 g L-1 and maximum productivity of 173 mg L-1 d-1 was reached under HRT of 8 days. Microscopy analysis revealed a shift from Synechocystis sp. to Leptolyngbya sp. and green algae when HRT of 6 days was used. Continuous, stable production of phycobiliproteins in the semi-continuous photobioreactor was obtained, reaching a maximum content of 7.4%dcw in the biomass. In the batch photobioreactors a PHB content of 4.8%dcw was reached under 7 days of nitrogen and phosphorus starvation, while a lipids content of 44.7%dcw was achieved under 30 days of nitrogen starvation. PHB and lipids production was strongly dependent on the amount of nutrients withdrawn from the grow phase. In the case of lipids, their production was stimulated when there was only phosphorus depletion. While Nitrogen and phosphorus limitation was needed to enhance the PHB production. In conclusion, this study demonstrates the feasibility of cultivating cyanobacteria in treated wastewater to produce bio-based valuable compounds within a circular bioeconomy approach.

On-line untargeted metabolomics monitoring of an Escherichia coli succinate fermentation process.

The real-time monitoring of metabolites (RTMet) is instrumental for the industrial production of biobased fermentation products. This study shows the first application of untargeted on-line metabolomics for the monitoring of undiluted fermentation broth samples taken automatically from a 5 L bioreactor every 5 min via flow injection mass spectrometry. The travel time from the bioreactor to the mass spectrometer was 30 s. Using mass spectrometry allows, on the one hand, the direct monitoring of targeted key process compounds of interest and, on the other hand, provides information on hundreds of additional untargeted compounds without requiring previous calibration data. In this study, this technology was applied in an Escherichia coli succinate fermentation process and 886 different m/z signals were monitored, including key process compounds (glucose, succinate, and pyruvate), potential biomarkers of biomass formation such as (R)-2,3-dihydroxy-isovalerate and (R)-2,3-dihydroxy-3-methylpentanoate and compounds from the pentose phosphate pathway and nucleotide metabolism, among others. The main advantage of the RTMet technology is that it allows the monitoring of hundreds of signals without the requirement of developing partial least squares regression models, making it a perfect tool for bioprocess monitoring and for testing many different strains and process conditions for bioprocess development.

Monitoring PHB production in Synechocystis sp. with hyperspectral images.

Microalgae wastewater treatment systems have the potential for producing added-value products. More specifically, cyanobacteria are able to accumulate polyhydroxybutyrates (PHBs), which can be extracted and used for bioplastics production. Nonetheless, PHB production requires proper culture conditions and continue monitoring, challenging the state-of-the-art technologies. The aim of this study was to investigate the application of hyperspectral technologies to monitor cyanobacteria population growth and PHB production. We have established a ground-breaking measurement method able to discern spectral reflectance changes from light emitted to cyanobacteria in different phases. All in all, enabling to distinguish between cyanobacteria growth phase and PHB accumulation phase. Furthermore, first tests of classification algorithms used for machine learning and image recognition technologies had been applied to automatically recognize the different cyanobacteria species from a complex microbial community containing cyanobacteria and microalgae cultivated in pilot-scale photobioreactors (PBRs). We have defined three main indicators for monitoring PHB production: (i) cyanobacteria specific-strain density, (ii) differentiate between growth and PHB-accumulation and (iii) chlorosis progression. The results presented in this study represent an interesting alternative for traditional measurements in cyanobacteria PHB production and its application in pilot-scale PBRs. Although not directly determining the amount of PHB production, they would give insights on the undergoing processes.

Process optimization of the polyhydroxybutyrate production in the cyanobacteria Synechocystis sp. and Synechococcus sp.

The effect of four parameters (acetate, NaCl, inorganic carbon and days in darkness) affecting the polyhydroxybutyrate (PHB) production were tested and optimized for Synechococcus sp. and Synechocystis sp. using a Box-Behnken design. The optimal conditions for Synechocystis sp. were found to be 1.2 g L-1 of acetate, 4 gC L-1 of NaHCO3, 18 g L-1 of NaCl and 0 days in darkness. For Synechococcus sp., equal acetate concentration and days in darkness, and lower inorganic carbon and NaCl concentrations than those for Synechocystis sp. were needed (0.05 g L-1 inorganic carbon and 9 g L-1 NaCl). Optimal conditions were scaled up to 3 L photobioreactors. Using Synechocystis sp., 5.6 %dcw of PHB was obtained whether adding or not acetate. In opposition, a maximum of 26.1 %dcw by using acetate was reached with Synechococcus sp. These results provide an easy method to optimize the cultivation conditions to enhance PHB production with cyanobacteria.

Fate and removal of emerging contaminants in anaerobic fluidized membrane bioreactor filled with thermoplastic gel as biofilm support.

The Anaerobic Fluidized Membrane Bioreactor (AnFMBR) is a membrane-based hybrid technology that can overcome the limitations of conventional anaerobic sewage treatment. Although previous studies have demonstrated excellent performance in the removal of conventional organic pollutants, further research into the removal paths of emerging contaminants (ECs) under various operating conditions is required for proper design and development of the AnFMBR technology. Regarding this, the fate of four ECs in a lab-scale AnFMBR filled with thermoplastic gel for biofilm growth was investigated under various Hydraulic Retention Time (HRT) conditions. When the HRT was 13 h, diclofenac and 17ß-estradiol were efficiently removed at 93% and 72% respectively. Even after an HRT reduction to 6.5 h, the system was still able to maintain high ECs removals (74% for diclofenac and 69% for 17ß-estradiol). However, irrespective of HRT operational condition, smaller removals of 17a-ethinylestradiol (37-52%) were observed, while only marginal removals of amoxicillin were achieved (5-29%). Biotransformation was attributed as the main route for ECs removal. The results obtained in this study indicate that the membrane-based hybrid AnFMBR can be used to treat the target ECs without influence on anaerobic process. The technology had better removal efficiency for diclofenac and 17ß-estradiol. However, the AnFMBR system exhibits high variability in EC removal and low capacity for amoxicillin removal, implying that a combination of other processes is still required to properly avoid the release of these contaminants into the environment.

Rapid HILIC-Z ion mobility mass spectrometry (RHIMMS) method for untargeted metabolomics of complex biological samples.

INTRODUCTION: Recent advances in high-throughput methodologies in the 'omics' and synthetic biology fields call for rapid and sensitive workflows in the metabolic phenotyping of complex biological samples. OBJECTIVE: The objective of this research was to evaluate a straightforward to implement LC-MS metabolomics method using a commercially available chromatography column that provides increased throughput. Reducing run time can potentially impact chromatography and therefore the effects of ion mobility spectrometry to expand peak capacity were also evaluated. Additional confidence provided via collision cross section measurements for detected features was also explored. METHODS: A rapid untargeted metabolomics workflow was developed with broad metabolome coverage, combining zwitterionic-phase hydrophilic interaction chromatography (HILIC-Z) with drift tube ion mobility-quadrupole time-of-flight (DTIM-qTOF) mass spectrometry. The analytical performance of our method was explored using extracts from complex biological samples, including a reproducibility study on chicken serum and a simple comparative study on a bacterial metabolome. RESULTS: The method is acronymised RHIMMS for rapid HILIC-Z ion mobility mass spectrometry. We present the RHIMMS workflow starting with data acquisition, followed by data processing and analysis. RHIMMS demonstrates improved chromatographic separation for a selection of metabolites with wide physicochemical properties while maintaining reproducibility at better than 20% over 200 injections at 3.5 min per sample for the selected metabolites, and a mean of 13.9% for the top 50 metabolites by intensity. Additionally, the combination of rapid chromatographic separation with ion mobility allows improved annotation and the ability to distinguish isobaric compounds. CONCLUSION: Our results demonstrate RHIMMS to be a rapid, reproducible, sensitive and high-resolution analytical platform that is highly applicable to the untargeted metabolomics analysis of complex samples.

Inorganic carbon stimulates the metabolic routes related to the polyhdroxybutyrate production in a Synechocystis sp. strain (cyanobacteria) isolated from wastewater.

Cyanobacteria are capable of transforming CO2 into polyhydroxybutyrate (PHB). In this study, different inorganic carbon concentrations (0-2 gC L-1) were evaluated for a Synechocystis sp. strain isolated from wastewater. Quantitative RT-qPCR was also performed to decipher the links between inorganic carbon and PHB and glycogen metabolism. 2 gC L-1 of bicarbonate stimulated cell growth, nutrients consumption and production of PHB. Using this concentration, a 14%dcw of PHB and an average productivity of 2.45 mgPHB L-1 d-1 were obtained. Gene expression analysis revelated that these conditions caused the overexpression of genes related to glycogen and PHB synthesis. Moreover, a positive correlation between the genes codifying for the glycogen phosphorylase, the acetyl-CoA reductase and the poly(3-hydroxyalkanoate) polymerase was found, meaning that PHB synthesis and glycogen catabolism are strongly related. These results provide an exhaustive evaluation of the effect of carbon on the PHB production and cyanobacterial metabolism.

Advanced biokinetic and hydrodynamic modelling to support and optimize the design of full-scale high rate algal ponds.

High rate algal ponds (HRAP) are known for their suitability to treat wastewater and to produce microalgal biomass, which can be converted into bioproducts. However, full-scale application of HRAP is still limited to few cases, and design procedures are not consolidated or standardized. In this study, a demonstrative-scale HRAP system for secondary wastewater treatment to be implemented in India (treatment capacity of 50 m3·d-1) has been designed combining conventional dimensioning techniques and advanced modelling tools. The objective of the study was to assist, verify and optimize the conventional dimensioning of the secondary HRAP by means of simulations predicting the behaviour of the system in the specific local conditions under different configurations and operational strategies. Biokinetic modelling and hydrodynamic analysis using Computational Fluid Dynamics (CFD) were carried out. The simulations performed with the biokinetic model showed that the optimal hydraulic retention time to enhance nutrient removal and biomass production is 4 days. For the hydrodynamic modelling, a 3D model of the HRAP was built to simulate the hydrodynamic behaviour of 36 different designs. Simulations allowed quantifying the presence of low velocity zones as well as the land use efficiency of the different designs in terms of the useful area vs. the total occupied area. Two baffles and tear-shapes with a diameter equal to » of the channel width was the most efficient configuration. Moreover, a technical-economic assessment of the system was carried out, resulting in an investment cost of 483 € per population equivalent and an operational cost of 0.19 € per m3 of treated wastewater.

PRGdb 4.0: an updated database dedicated to genes involved in plant disease resistance process.

The Plant Resistance Genes database (PRGdb; http://prgdb.org/prgdb4/) has been greatly expanded, keeping pace with the increasing amount of available knowledge and data (sequenced proteomes, cloned genes, public analysis data, etc.). The easy-to-use style of the database website has been maintained, while an updated prediction tool, more data and a new section have been added. This new section will contain plant resistance transcriptomic experiments, providing additional easy-to-access experimental information. DRAGO3, the tool for automatic annotation and prediction of plant resistance genes behind PRGdb, has been improved in both accuracy and sensitivity, leading to more reliable predictions. PRGdb offers 199 reference resistance genes and 586.652 putative resistance genes from 182 sequenced proteomes. Compared to the previous release, PRGdb 4.0 has increased the number of reference resistance genes from 153 to 199, the number of putative resistance genes from 177K from 76 proteomes to 586K from 182 sequenced proteomes. A new section has been created that collects plant-pathogen transcriptomic data for five species of agricultural interest. Thereby, with these improvements and data expansions, PRGdb 4.0 aims to serve as a reference to the plant scientific community and breeders worldwide, helping to further study plant resistance mechanisms that contribute to fighting pathogens.

Optimization of the phototrophic Cyanobacteria polyhydroxybutyrate (PHB) production by kinetic model simulation.

Cyanobacteria can grow using inorganic substrates, such as CO2 from industrial sources and nutrients from wastewaters, and therefore are promising microorganisms to produce polyhydroxybutyrate in a cleaner circular context. However, this biotechnological production is highly challenging because it involves different interlinked reactions that are affected by environmental conditions, which hinders process optimization. In this study a new biokinetic mechanistic model using novel experimental approaches was developed to optimize polyhydroxybutyrate (PHB) and glycogen production. The model includes, for the first time, the production of glycogen and its conversion into PHB, which has been found as the main pathway to produce PHB. Model was successfully (r2: 0.6-0.99) calibrated and validated with experimental data from photobioreactors inoculated with Synechocystis sp. The developed model was used to determine suitable initial conditions for a lab scale batch reactor (6.4 mgN·L-1 and 2 mgP·L-1) and a new configuration for the continuous industrial production of PHB was proposed and optimized using this tool. The maximum productivity (5.1 mgPHB·L-1·d-1) and the optimal configuration and operation of the serial reactors to produce PHB in an industrial scale was achieved using a hydraulic retention time of 4 days in the growth reactor. Then, this reactor daily fed 20 batch accumulation reactors, which were discharged after 20 days. The optimal influent nutrients concentrations for this configuration was found to be 50 mgN·L-1 and 10 mgP·L-1. Results found in this study show the necessity to optimize biopolymers production with Cyanobacteria considering environmental conditions, and demonstrated the potential of this model as a tool to increase PHB productivity.