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Projeto de investigação
Bio Innovation of a Circular Economy for Plastics
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Boosting bacterial nanocellulose production from chemically recycled post-consumer polyethylene terephthalate
Publication . Pereira, Everton Henrique Da Silva; Attallah, Olivia A.; Tas, Cuneyt Erdinc; Chee, Bor Shin; Freitas, Filomena; Garcia, Eduardo Lanzagorta; Auliffe, Michael A.P.Mc; Mojicevic, Marija; Batista, Maria N.; Reis, Maria A.M.; Fournet, Margaret Brennan; UCIBIO - Applied Molecular Biosciences Unit; Elsevier
The circular economy is emerging with new sustainable solutions to the ever-growing plastic waste challenge, garnering increasing attention. In this study, the possibility to modify expensive Hestrin–Schramm medium (HS) for bacterial nanocellulose (BNC) production and replace significant amounts of glucose with terephthalic acid (TPA) derived after reactive extrusion processing of mixed plastic waste yielding post consumer TPA (pcTPA), was evaluated from laboratory scale to fermentation at pilot scale. Fourier-transform infrared spectroscopy (FTIR), Scanning electron microscopy (SEM), Thermogravimetric Analysis (TGA) were used to assess the structural, thermal, and morphological properties of BNC and its generated derivatives. The study's findings highlight the positive impact of pcTPA on BNC yield, surpassing the performance of conventional TPA. The presence of pcTPA in the medium resulted in a BNC yield of 4.01 g/L in a scale-up step of 100 mL cultivation, while the positive control using glucose resulted in a yield of 3.57 g/L. The efficiency of glucose substitution with pcTPA increased with each scale-up step, ultimately reaching a 320% yield increase in comparison to the positive control. Additionaly, the procedure that enhanced the materials' thermoplasticity in the form of derivatives has been established resulting in the production of BNC laurate and BNC octanoate derivatives with melting temperatures of 270 °C and 280 °C, respectively. Overall, this study investigates the potential of this approach as an important circular economic solution, enabling an increased sustainable perspective for polyethylene terephthalate (PET) circularity and significantly a much needed cost reduction for BNC production with enhanced thermoplasticity.
Characterization of the Thermostable Biosurfactant Produced by Burkholderia thailandensis DSM 13276
Publication . Gil, Cátia V.; Rebocho, Ana Teresa; Esmail, Asiyah; Sevrin, Chantal; Grandfils, Christian; Torres, Cristiana A.V.; Reis, Maria A.M.; Freitas, Filomena; DQ - Departamento de Química; UCIBIO - Applied Molecular Biosciences Unit; MDPI - Multidisciplinary Digital Publishing Institute
Biosurfactants synthesized by microorganisms represent safe and sustainable alternatives to the use of synthetic surfactants, due to their lower toxicity, better biodegradability and biocompatibility, and their production from low-cost feedstocks. In line with this, the present study describes the physical, chemical, and functional characterization of the biopolymer secreted by the bacterium Burkholderia thailandensis DSM 13276, envisaging its validation as a biosurfactant. The biopolymer was found to be a glycolipopeptide with carbohydrate and protein contents of 33.1 ± 6.4% and 23.0 ± 3.2%, respectively. Galactose, glucose, rhamnose, mannose, and glucuronic acid were detected in the carbohydrate moiety at a relative molar ratio of 4:3:2:2:1. It is a high-molecular-weight biopolymer (1.0×107Da) with low polydispersity (1.66), and forms aqueous solutions with shear-thinning behavior, which remained after autoclaving. The biopolymer has demonstrated a good emulsionstabilizing capacity towards different hydrophobic compounds, namely, benzene, almond oil, and sunflower oil. The emulsions prepared with the biosurfactant, as well as with its autoclaved solution, displayed high emulsification activity (>90% and ~50%, respectively). Moreover, the almond and sunflower oil emulsions stabilized with the biosurfactant were stable for up to 4 weeks, which further supports the potential of this novel biopolymer for utilization as a natural bioemulsifier.
A General Hybrid Modeling Framework for Systems Biology Applications
Publication . Pinto, José; Ramos, João R. C.; Costa, Rafael S.; Oliveira, Rui; LAQV@REQUIMTE; DQ - Departamento de Química; MDPI - Multidisciplinary Digital Publishing Institute
In this paper, a computational framework is proposed that merges mechanistic modeling with deep neural networks obeying the Systems Biology Markup Language (SBML) standard. Over the last 20 years, the systems biology community has developed a large number of mechanistic models that are currently stored in public databases in SBML. With the proposed framework, existing SBML models may be redesigned into hybrid systems through the incorporation of deep neural networks into the model core, using a freely available python tool. The so-formed hybrid mechanistic/neural network models are trained with a deep learning algorithm based on the adaptive moment estimation method (ADAM), stochastic regularization and semidirect sensitivity equations. The trained hybrid models are encoded in SBML and uploaded in model databases, where they may be further analyzed as regular SBML models. This approach is illustrated with three well-known case studies: the Escherichia coli threonine synthesis model, the P58IPK signal transduction model, and the Yeast glycolytic oscillations model. The proposed framework is expected to greatly facilitate the widespread use of hybrid modeling techniques for systems biology applications.
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Entidade financiadora
European Commission
Programa de financiamento
H2020
Número da atribuição
870292