Insect-Derived Enzymes: A Treasure for Industrial Biotechnology and Food Biotechnology

The Value Proposition of Indian Biotechnology

Asia-Pacific Biotech News ◽

10.1142/s0219030305000261 ◽

2005 ◽

Vol 09 (18) ◽

pp. 924-929

Author(s):

Kiran Mazumdar-Shaw

Keyword(s):

Regenerative Medicine ◽

Industrial Biotechnology ◽

Value Proposition ◽

Food Biotechnology ◽

Agriculture And Food ◽

Biotechnology Sector

The article written by a very experienced veteran in the biotechnology sector, Dr Mazumdar Shaw describes India's biopharma sector and also shows a sectoral roadmap. It touches on agriculture and food biotechnology, industrial biotechnology, diagnostic biotechnology, regenerative medicine, therapeutic biotechnology, pharmaocogenomics, nanotechnology and bioinformatics.

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Patenting Trends and Innovation in Industrial Biotechnology

SSRN Electronic Journal ◽

10.2139/ssrn.1302904 ◽

2009 ◽

Cited By ~ 1

Author(s):

Katherine Connor Linton ◽

Jeremy Wise ◽

Philip Stone

Keyword(s):

Industrial Biotechnology

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In Silico Study of 1, 4 Alpha Glucan Branching Enzyme and Substrate Docking Studies

Current Proteomics ◽

10.2174/1570164616666190401204009 ◽

2020 ◽

Vol 17 (1) ◽

pp. 40-50

Author(s):

Farzane Kargar ◽

Amir Savardashtaki ◽

Mojtaba Mortazavi ◽

Masoud Torkzadeh Mahani ◽

Ali Mohammad Amani ◽

...

Keyword(s):

Phylogenetic Tree ◽

In Silico ◽

Alpha Helix ◽

In Silico Analysis ◽

Glycogen Storage ◽

Docking Studies ◽

Random Coil ◽

Special Topic ◽

Industrial Biotechnology ◽

In Silico Study

Background: The 1,4-alpha-glucan branching protein (GlgB) plays an important role in the glycogen biosynthesis and the deficiency in this enzyme has resulted in Glycogen storage disease and accumulation of an amylopectin-like polysaccharide. Consequently, this enzyme was considered a special topic in clinical and biotechnological research. One of the newly introduced GlgB belongs to the Neisseria sp. HMSC071A01 (Ref.Seq. WP_049335546). For in silico analysis, the 3D molecular modeling of this enzyme was conducted in the I-TASSER web server. Methods: For a better evaluation, the important characteristics of this enzyme such as functional properties, metabolic pathway and activity were investigated in the TargetP software. Additionally, the phylogenetic tree and secondary structure of this enzyme were studied by Mafft and Prabi software, respectively. Finally, the binding site properties (the maltoheptaose as substrate) were studied using the AutoDock Vina. Results: By drawing the phylogenetic tree, the closest species were the taxonomic group of Betaproteobacteria. The results showed that the structure of this enzyme had 34.45% of the alpha helix and 45.45% of the random coil. Our analysis predicted that this enzyme has a potential signal peptide in the protein sequence. Conclusion: By these analyses, a new understanding was developed related to the sequence and structure of this enzyme. Our findings can further be used in some fields of clinical and industrial biotechnology.

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Exploiting RNA thermometer-driven molecular bioprocess control as a concept for heterologous rhamnolipid production

Scientific Reports ◽

10.1038/s41598-021-94400-4 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Philipp Noll ◽

Chantal Treinen ◽

Sven Müller ◽

Lars Lilge ◽

Rudolf Hausmann ◽

...

Keyword(s):

High Titer ◽

Production Capacity ◽

Batch Process ◽

Product Formation ◽

Effect Of Temperature ◽

Industrial Biotechnology ◽

Temperature Sensitive ◽

Translation Control ◽

Rhamnolipid Production ◽

Rna Thermometer

AbstractA key challenge to advance the efficiency of bioprocesses is the uncoupling of biomass from product formation, as biomass represents a by-product that is in most cases difficult to recycle efficiently. Using the example of rhamnolipid biosurfactants, a temperature-sensitive heterologous production system under translation control of a fourU RNA thermometer from Salmonella was established to allow separating phases of preferred growth from product formation. Rhamnolipids as bulk chemicals represent a model system for future processes of industrial biotechnology and are therefore tied to the efficiency requirements in competition with the chemical industry. Experimental data confirms function of the RNA thermometer and suggests a major effect of temperature on specific rhamnolipid production rates with an increase of the average production rate by a factor of 11 between 25 and 38 °C, while the major part of this increase is attributable to the regulatory effect of the RNA thermometer rather than an unspecific overall increase in bacterial metabolism. The production capacity of the developed temperature sensitive-system was evaluated in a simple batch process driven by a temperature switch. Product formation was evaluated by efficiency parameters and yields, confirming increased product formation rates and product-per-biomass yields compared to a high titer heterologous rhamnolipid production process from literature.

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A genome-scale metabolic model of Saccharomyces cerevisiae that integrates expression constraints and reaction thermodynamics

Nature Communications ◽

10.1038/s41467-021-25158-6 ◽

2021 ◽

Vol 12 (1) ◽

Author(s):

Omid Oftadeh ◽

Pierre Salvy ◽

Maria Masid ◽

Maxime Curvat ◽

Ljubisa Miskovic ◽

...

Keyword(s):

Saccharomyces Cerevisiae ◽

Expression System ◽

Biomass Composition ◽

Industrial Biotechnology ◽

Overflow Metabolism ◽

Cellular Expression ◽

A Genome ◽

Wide Range ◽

Eukaryotic Organisms ◽

Genome Scale

AbstractEukaryotic organisms play an important role in industrial biotechnology, from the production of fuels and commodity chemicals to therapeutic proteins. To optimize these industrial systems, a mathematical approach can be used to integrate the description of multiple biological networks into a single model for cell analysis and engineering. One of the most accurate models of biological systems include Expression and Thermodynamics FLux (ETFL), which efficiently integrates RNA and protein synthesis with traditional genome-scale metabolic models. However, ETFL is so far only applicable for E. coli. To adapt this model for Saccharomyces cerevisiae, we developed yETFL, in which we augmented the original formulation with additional considerations for biomass composition, the compartmentalized cellular expression system, and the energetic costs of biological processes. We demonstrated the ability of yETFL to predict maximum growth rate, essential genes, and the phenotype of overflow metabolism. We envision that the presented formulation can be extended to a wide range of eukaryotic organisms to the benefit of academic and industrial research.

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