Association of Pseudomonas putida formaldehyde dehydrogenase with superparamagnetic nanoparticles: an effective way of improving the enzyme stability, performance and recycling

Netto, Caterina Gruenwaldt Cunha Marques; Andrade, Leandro H.; Toma, Henrique E.

doi:10.1039/c4nj01716a

Cited by 8 publications

(6 citation statements)

References 31 publications

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“…17,18 Through the enzyme immobilization procedure, the activity and stability of the enzymes are influenced by various factors such as immobilization method, binding sites concentration on the support surface, and physical and chemical parameters of reaction media. 19 Among the various enzyme immobilization techniques, covalent linkage is a suitable approach to strongly bind enzyme molecules onto the support preventing enzyme leakage from the support surface in the reaction systems. 20 The concentration of binding sites present on the solid support surface is important to achieve an appropriate enzyme loading capacity, as well as desired activity and conformational stability for the immobilized enzyme under various reaction conditions.…”

Section: ■ Introductionmentioning

confidence: 99%

Study of Molecular Conformation and Activity-Related Properties of Lipase Immobilized onto Core–Shell Structured Polyacrylic Acid-Coated Magnetic Silica Nanocomposite Particles

Esmaeilnejad-Ahranjani

Kazemeini

Singh

et al. 2016

Langmuir

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A facile approach for the preparation of core-shell structured poly(acrylic acid) (PAA)-coated Fe3O4 cluster@SiO2 nanocomposite particles as the support materials for the lipase immobilization is reported. Low- or high-molecular-weight (1800 and 100,000, respectively) PAA molecules were covalently attached onto the surface of amine-functionalized magnetic silica nanoacomposite particles. The successful preparation of particles were verified by scanning transmission electron microscopy (STEM), X-ray diffraction (XRD), vibrating sample magnetometer (VSM), thermogravimetric analysis (TGA), zeta potential measurement, and Fourier-transform infrared (FTIR) techniques. Once lipase is covalently immobilized onto the particles with an average diameter of 210 ± 50 nm, resulting from high binding sites concentrations on the low- and high-molecular-weight PAA-coated particles, high lipase immobilization efficiencies (86.2% and 89.9%, respectively), and loading capacities (786 and 816 mg g(-1), respectively) are obtained. Results from circular dichroism (CD) analysis and catalytic activity tests reveal an increase in the β-sheet content of lipase molecules upon immobilization, along with an enhancement in their activities and stabilities. The lipases immobilized onto the low- and high-molecular-weight PAA-coated particles show maximum activities at 55 and 50 °C, respectively, which are ∼28% and ∼15% higher than that of the free lipase at its own optimum temperature (40 °C), respectively. The immobilized lipases exhibit excellent performance at broader temperature and pH ranges and high thermal and storage stabilities, as well as superior reusability. These prepared magnetic nanocomposite particles can be offered as suitable support materials for efficient immobilization of enzymes and improvement of the immobilized enzymes properties.

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Section: ■ Introductionmentioning

confidence: 99%

Study of Molecular Conformation and Activity-Related Properties of Lipase Immobilized onto Core–Shell Structured Polyacrylic Acid-Coated Magnetic Silica Nanocomposite Particles

Esmaeilnejad-Ahranjani

Kazemeini

Singh

et al. 2016

Langmuir

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“…E. coli expressing pFA-GESS and FalDH from Pseudomonas putida or pFrm-GESS and Bsmdh from B. stearothermophilus, were used to investigate whether the biosensors could test the activities of the C1-converting enzymes [30,31,32]. FalDH is an NAD + -dependent oxidoreductase that reversibly catalyzes formaldehyde to formate.…”

Section: Resultsmentioning

confidence: 99%

“…For the application study of FA-GESS and Frm-GESS, formaldehyde dehydrogenase (FalDH from Pseudomonas putida ) and methanol dehydrogenase (Mdh from Bacillus methanolicus ) were used as the model enzymes as in References [30,31,32]. The falDH and mdh genes were synthesized with codon optimization (Macrogen) and then cloned into the pET28a (+) plasmid (Novagen, Merck, Germany) with a trc promoter.…”

Section: Methodsmentioning

confidence: 99%

C1 Compound Biosensors: Design, Functional Study, and Applications

Lee

Sung

et al. 2019

IJMS

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The microbial assimilation of one-carbon (C1) gases is a topic of interest, given that products developed using this pathway have the potential to act as promising substrates for the synthesis of valuable chemicals via enzymatic oxidation or C–C bonding. Despite extensive studies on C1 gas assimilation pathways, their key enzymes have yet to be subjected to high-throughput evolution studies on account of the lack of an efficient analytical tool for C1 metabolites. To address this challenging issue, we attempted to establish a fine-tuned single-cell–level biosensor system constituting a combination of transcription factors (TFs) and several C1-converting enzymes that convert target compounds to the ligand of a TF. This enzymatic conversion broadens the detection range of ligands by the genetic biosensor systems. In this study, we presented new genetic enzyme screening systems (GESSs) to detect formate, formaldehyde, and methanol from specific enzyme activities and pathways, named FA-GESS, Frm-GESS, and MeOH-GESS, respectively. All the biosensors displayed linear responses to their respective C1 molecules, namely, formate (1.0–250 mM), formaldehyde (1.0–50 μM), and methanol (5–400 mM), and they did so with high specificity. Consequently, the helper enzymes, including formaldehyde dehydrogenase and methanol dehydrogenase, were successfully combined to constitute new versatile combinations of the C1-biosensors.

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“…Memory is one of the most amazing faculties of the human being and construed as the brain's ability to code, store, and retrieve information [1][2][3][4]. For decades, understanding and simulating the basis of human learning, cognition processing, and its perception and vision system has been the motivation of the machine intelligence field.…”

Section: Introductionmentioning

confidence: 99%

Introducing the structural bases of typicality effects in deep learning

Pino,

Nascimento,

Campos

2021

Preprint

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In this paper, we hypothesize that the effects of the degree of typicality in natural semantic categories can be generated based on the structure of artificial categories learned with deep learning models. Motivated by the human approach to representing natural semantic categories and based on the foundations of Prototype Theory, we propose a novel Computational Prototype Model (CPM) to represent the internal structure of semantic categories. Unlike other prototype learning approaches, our mathematical framework proposes a first approach to provide deep neural networks with the ability to model abstract semantic concepts such as category central semantic meaning (semantic prototype), typicality degree of object's image, and family resemblance relationship. We proposed several methodologies based on the typicality's concept to evaluate our CPM model in image semantic processing tasks such as image classification, a global semantic description of images, and transfer learning. Our experiments on different image datasets, such as ImageNet and Coco, showed that our approach might be an admissible proposition in the effort to endow machines with greater power of abstraction for the semantic representation of objects' categories.

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Association of Pseudomonas putida formaldehyde dehydrogenase with superparamagnetic nanoparticles: an effective way of improving the enzyme stability, performance and recycling

Cited by 8 publications

References 31 publications

Study of Molecular Conformation and Activity-Related Properties of Lipase Immobilized onto Core–Shell Structured Polyacrylic Acid-Coated Magnetic Silica Nanocomposite Particles

Study of Molecular Conformation and Activity-Related Properties of Lipase Immobilized onto Core–Shell Structured Polyacrylic Acid-Coated Magnetic Silica Nanocomposite Particles

C1 Compound Biosensors: Design, Functional Study, and Applications

Introducing the structural bases of typicality effects in deep learning

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