Insights on the Advancements of In Silico Metabolic Studies of Succinic Acid Producing Microorganisms: A Review with Emphasis on Actinobacillus succinogenes

Fermentation ◽  
2021 ◽  
Vol 7 (4) ◽  
pp. 220
Author(s):  
Wubliker Dessie ◽  
Zongcheng Wang ◽  
Xiaofang Luo ◽  
Meifeng Wang ◽  
Zuodong Qin
Keyword(s):  
Succinic Acid ◽  
In Silico ◽  
Value Added ◽  
Research Progress ◽  
Efficient Production ◽  
Actinobacillus Succinogenes ◽  
Cell Factories ◽  
In Silico Studies ◽  
Current Scenario ◽  
Critical Problems

Succinic acid (SA) is one of the top candidate value-added chemicals that can be produced from biomass via microbial fermentation. A considerable number of cell factories have been proposed in the past two decades as native as well as non-native SA producers. Actinobacillus succinogenes is among the best and earliest known natural SA producers. However, its industrial application has not yet been realized due to various underlying challenges. Previous studies revealed that the optimization of environmental conditions alone could not entirely resolve these critical problems. On the other hand, microbial in silico metabolic modeling approaches have lately been the center of attention and have been applied for the efficient production of valuable commodities including SA. Then again, literature survey results indicated the absence of up-to-date reviews assessing this issue, specifically concerning SA production. Hence, this review was designed to discuss accomplishments and future perspectives of in silico studies on the metabolic capabilities of SA producers. Herein, research progress on SA and A. succinogenes, pathways involved in SA production, metabolic models of SA-producing microorganisms, and status, limitations and prospects on in silico studies of A. succinogenes were elaborated. All in all, this review is believed to provide insights to understand the current scenario and to develop efficient mathematical models for designing robust SA-producing microbial strains.

Efficient production of succinic acid from duckweed (Landoltia punctata) hydrolysate by Actinobacillus succinogenes GXAS137

2018 ◽  
Vol 250 ◽  
pp. 35-42 ◽  
Author(s):  
Naikun Shen ◽  
Hongyan Zhang ◽  
Yan Qin ◽  
Qingyan Wang ◽  
Jing Zhu ◽  
...  
Keyword(s):  
Succinic Acid ◽  
Efficient Production ◽  
Actinobacillus Succinogenes

scholarly journals In Silico Design for Systems-Based Metabolic Engineering In Escherichia Coli for The Bioconversion of Aerobic Glycerol to Succinic Acid

2020 ◽  
Author(s):  
Albert Enrique Tafur Rangel ◽  
Wendy Lorena Rios Guzman ◽  
Carmen Elvira Ojeda Cuella ◽  
Daissy Esther Mejia Perez ◽  
Ross Carlson ◽  
...  
Keyword(s):  
Machine Learning ◽  
Escherichia Coli ◽  
Metabolic Engineering ◽  
Succinic Acid ◽  
In Silico ◽  
Rational Design ◽  
Industrial Biotechnology ◽  
E Coli ◽  
Cell Factories ◽  
Transcriptomics Data

Abstract BackgroundGlycerol has become an interesting carbon source for industrial processes as consequence of the biodiesel business growth since it has shown promising results in terms of biomass/substrate yields. Selecting the appropriate metabolic targets to build efficient cell factories and maximize the desired chemical production in as little time as possible is a major challenge in industrial biotechnology. The engineering of microbial metabolism following rational design has been widely studied. However, it is a cost-, time-, and laborious-intensive process because of the cell network complexity; thus, to be proficient is needed known in advance the effects of gene deletions.ResultsAn in silico experiment was performed to model and understand the effects of metabolic engineering over the metabolism by transcriptomics data integration. In this study, systems-based metabolic engineering to predict the metabolic engineering targets was used in order to increase the bioconversion of glycerol to succinic acid by Escherichia coli. Transcriptomics analysis suggest insights of how increase the glycerol utilization of the cell for further design efficient cell factories. Three models were used; an E. coli core model, a model obtained after the integration of transcriptomics data obtained from E. coli growing in an optimized culture media, and a third one obtained after integration of transcriptomics data obtained from E. coli after adaptive laboratory evolution experiments. A total of 2402 strains were obtained from these three models. Fumarase and pyruvate dehydrogenase were frequently predicted in all the models, suggesting that these reactions are essential to increasing succinic acid production from glycerol. Finally, using flux balance analysis results for all the mutants predicted, a machine learning method was developed to predict new mutants as well as to propose optimal metabolic engineering targets and mutants based on the measurement of importance of each knockout’s (feature’s) contribution.ConclusionsThe combination of transcriptome, systems metabolic modeling, and machine learning analyses revealed versatile molecular mechanisms involved in the utilization of glycerol. These data provide a platform to improve the prediction of metabolic engineering targets to design efficient cell factories. Our results may also work a guide platform for the selection/engineering of microorganisms for production of interesting chemical compounds.

scholarly journals De novo biosynthesis of bioactive isoflavonoids by engineered yeast cell factories

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Quanli Liu ◽  
Yi Liu ◽  
Gang Li ◽  
Otto Savolainen ◽  
Yun Chen ◽  
...  
Keyword(s):  
Natural Products ◽  
Yeast Cell ◽  
De Novo ◽  
Structural Complexity ◽  
Value Added ◽  
Fine Tuning ◽  
Attractive Alternative ◽  
Efficient Production ◽  
De Novo Biosynthesis ◽  
Cell Factories

AbstractIsoflavonoids comprise a class of plant natural products with great nutraceutical, pharmaceutical and agricultural significance. Their low abundance in nature and structural complexity however hampers access to these phytochemicals through traditional crop-based manufacturing or chemical synthesis. Microbial bioproduction therefore represents an attractive alternative. Here, we engineer the metabolism of Saccharomyces cerevisiae to become a platform for efficient production of daidzein, a core chemical scaffold for isoflavonoid biosynthesis, and demonstrate its application towards producing bioactive glucosides from glucose, following the screening-reconstruction-application engineering framework. First, we rebuild daidzein biosynthesis in yeast and its production is then improved by 94-fold through screening biosynthetic enzymes, identifying rate-limiting steps, implementing dynamic control, engineering substrate trafficking and fine-tuning competing metabolic processes. The optimized strain produces up to 85.4 mg L−1 of daidzein and introducing plant glycosyltransferases in this strain results in production of bioactive puerarin (72.8 mg L−1) and daidzin (73.2 mg L−1). Our work provides a promising step towards developing synthetic yeast cell factories for de novo biosynthesis of value-added isoflavonoids and the multi-phased framework may be extended to engineer pathways of complex natural products in other microbial hosts.

scholarly journals Chestnut Shells as Waste Material for Succinic Acid Production from Actinobacillus succinogenes 130Z

Fermentation ◽  
2020 ◽  
Vol 6 (4) ◽  
pp. 105
Author(s):  
Michela Ventrone ◽  
Chiara Schiraldi ◽  
Giuseppe Squillaci ◽  
Alessandra Morana ◽  
Donatella Cimini
Keyword(s):  
Succinic Acid ◽  
Acid Production ◽  
Value Added ◽  
Raw Material ◽  
Actinobacillus Succinogenes ◽  
Citrate Buffer ◽  
Bulk Chemicals ◽  
Renewable Raw Material ◽  
Succinic Acid Production ◽  
Byproduct Formation

Currently, the full exploitation of waste materials for the production of value-added compounds is one of the potential solutions to lower costs and increase the sustainability of industrial processes. In this respect, the aim of this work was to evaluate the potential of chestnut shells (CSH) as substrate for the growth of Actinobacillus succinogenes 130Z, a natural producer of succinic acid that is a precursor of several bulk chemicals with diverse applications, such as bioplastics production. Hydrolysis of ammonia pretreated CSH in citrate buffer with the Cellic CTec2 enzyme mix was optimized and strain performance was studied in bottle experiments. Data showed co-consumption of citrate, glucose and xylose, which resulted in a change of the relative ratio of produced acids, providing an insight into the metabolism of A. succinogenes that was never described to date. Furthermore, high C:N ratios seems to have a favorable impact on succinic acid production by decreasing byproduct formation. Finally, yield and volumetric production rate of succinic acid were studied in controlled 2 L bioreactors demonstrating the potential use of CSH as renewable raw material.

scholarly journals In silico Design for Systems-Based Metabolic Engineering for the Bioconversion of Valuable Compounds From Industrial By-Products

2021 ◽  
Vol 12 ◽  
Author(s):  
Albert Enrique Tafur Rangel ◽  
Wendy Ríos ◽  
Daisy Mejía ◽  
Carmen Ojeda ◽  
Ross Carlson ◽  
...  
Keyword(s):  
Machine Learning ◽  
Metabolic Engineering ◽  
Succinic Acid ◽  
In Silico ◽  
Industrial Biotechnology ◽  
Cell Factory ◽  
Cell Factories ◽  
Transcriptomics Data ◽  
Valuable Compounds ◽  
By Products

Selecting appropriate metabolic engineering targets to build efficient cell factories maximizing the bioconversion of industrial by-products to valuable compounds taking into account time restrictions is a significant challenge in industrial biotechnology. Microbial metabolism engineering following a rational design has been widely studied. However, it is a cost-, time-, and laborious-intensive process because of the cell network complexity; thus, it is important to use tools that allow predicting gene deletions. An in silico experiment was performed to model and understand the metabolic engineering effects on the cell factory considering a second complexity level by transcriptomics data integration. In this study, a systems-based metabolic engineering target prediction was used to increase glycerol bioconversion to succinic acid based on Escherichia coli. Transcriptomics analysis suggests insights on how to increase cell glycerol utilization to further design efficient cell factories. Three E. coli models were used: a core model, a second model based on the integration of transcriptomics data obtained from growth in an optimized culture media, and a third one obtained after integration of transcriptomics data from adaptive laboratory evolution (ALE) experiments. A total of 2,402 strains were obtained with fumarase and pyruvate dehydrogenase being frequently predicted for all the models, suggesting these reactions as essential to increase succinic acid production. Finally, based on using flux balance analysis (FBA) results for all the mutants predicted, a machine learning method was developed to predict new mutants as well as to propose optimal metabolic engineering targets and mutants based on the measurement of the importance of each knockout’s (feature’s) contribution. Glycerol has become an interesting carbon source for industrial processes due to biodiesel business growth since it has shown promising results in terms of biomass/substrate yields. The combination of transcriptome, systems metabolic modeling, and machine learning analyses revealed the versatility of computational models to predict key metabolic engineering targets in a less cost-, time-, and laborious-intensive process. These data provide a platform to improve the prediction of metabolic engineering targets to design efficient cell factories. Our results may also work as a guide and platform for the selection/engineering of microorganisms for the production of interesting chemical compounds.

Critical Review on the Chemical Aspects of Cannabidiol (CBD) and Harmonization of Computational Bioactivity Data

2020 ◽  
Vol 28 (2) ◽  
pp. 213-237 ◽  
Author(s):  
Andrea Mastinu ◽  
Giovanni Ribaudo ◽  
Alberto Ongaro ◽  
Sara Anna Bonini ◽  
Maurizio Memo ◽  
...  
Keyword(s):  
In Silico ◽  
Cannabis Sativa ◽  
Therapeutic Potential ◽  
The Novel ◽  
In Silico Studies ◽  
Computational Data ◽  
Synthetic Approaches ◽  
Analytical Approaches ◽  
Yield Sensitivity ◽  
Therapeutic Profile

: Cannabidiol (CBD) is a non-psychotropic phytocannabinoid which represents one of the constituents of the “phytocomplex” of Cannabis sativa. This natural compound is attracting growing interest since when CBD-based remedies and commercial products were marketed. This review aims to exhaustively address the extractive and analytical approaches that have been developed for the isolation and quantification of CBD. Recent updates on cutting-edge technologies were critically examined in terms of yield, sensitivity, flexibility and performances in general, and are reviewed alongside original representative results. As an add-on to currently available contributions in the literature, the evolution of the novel, efficient synthetic approaches for the preparation of CBD, a procedure which is appealing for the pharmaceutical industry, is also discussed. Moreover, with the increasing interest on the therapeutic potential of CBD and the limited understanding of the undergoing biochemical pathways, the reader will be updated about recent in silico studies on the molecular interactions of CBD towards several different targets attempting to fill this gap. Computational data retrieved from the literature have been integrated with novel in silico experiments, critically discussed to provide a comprehensive and updated overview on the undebatable potential of CBD and its therapeutic profile.

Recent In Vitro and In Silico Advances in the Understanding of Intranasal Drug Delivery

2020 ◽  
Vol 26 ◽  
Author(s):  
John Chen ◽  
Andrew Martin ◽  
Warren H. Finlay
Keyword(s):  
Drug Delivery ◽  
In Silico ◽  
Local Drug Delivery ◽  
In Vivo Studies ◽  
Intranasal Drug Delivery ◽  
Nasal Sprays ◽  
In Silico Studies ◽  
Drug Delivery Devices

Background: Many drugs are delivered intranasally for local or systemic effect, typically in the form of droplets or aerosols. Because of the high cost of in vivo studies, drug developers and researchers often turn to in vitro or in silico testing when first evaluating the behavior and properties of intranasal drug delivery devices and formulations. Recent advances in manufacturing and computer technologies have allowed for increasingly realistic and sophisticated in vitro and in silico reconstructions of the human nasal airways. Objective: To perform a summary of advances in understanding of intranasal drug delivery based on recent in vitro and in silico studies. Conclusion: The turbinates are a common target for local drug delivery applications, and while nasal sprays are able to reach this region, there is currently no broad consensus across the in vitro and in silico literature concerning optimal parameters for device design, formulation properties and patient technique which would maximize turbinate deposition. Nebulizers are able to more easily target the turbinates, but come with the disadvantage of significant lung deposition. Targeting of the olfactory region of the nasal cavity has been explored for potential treatment of central nervous system conditions. Conventional intranasal devices, such as nasal sprays and nebulizers, deliver very little dose to the olfactory region. Recent progress in our understanding of intranasal delivery will be useful in the development of the next generation of intranasal drug delivery devices.

In-silico Studies of Isolated Phytoalkaloid Against Lipoxygenase: Study Based on Possible Correlation

2018 ◽  
Vol 21 (3) ◽  
pp. 215-221
Author(s):  
Haroon Khan ◽  
Muhammad Zafar ◽  
Helena Den-Haan ◽  
Horacio Perez-Sanchez ◽  
Mohammad Amjad Kamal
Keyword(s):  
In Silico ◽  
Docking Studies ◽  
In Vivo Studies ◽  
In Vitro Assays ◽  
Chronic Obstructive ◽  
Lipoxygenase Inhibitors ◽  
Lipoxygenase Inhibition ◽  
In Silico Studies

Aim and Objective: Lipoxygenase (LOX) enzymes play an important role in the pathophysiology of several inflammatory and allergic diseases including bronchial asthma, allergic rhinitis, atopic dermatitis, allergic conjunctivitis, rheumatoid arthritis and chronic obstructive pulmonary disease. Inhibitors of the LOX are believed to be an ideal approach in the treatment of diseases caused by its over-expression. In this regard, several synthetic and natural agents are under investigation worldwide. Alkaloids are the most thoroughly investigated class of natural compounds with outstanding past in clinically useful drugs. In this article, we have discussed various alkaloids of plant origin that have already shown lipoxygenase inhibition in-vitro with possible correlation in in silico studies. Materials and Methods: Molecular docking studies were performed using MOE (Molecular Operating Environment) software. Among the ten reported LOX alkaloids inhibitors, derived from plant, compounds 4, 2, 3 and 1 showed excellent docking scores and receptor sensitivity. Result and Conclusion: These compounds already exhibited in vitro lipoxygenase inhibition and the MOE results strongly correlated with the experimental results. On the basis of these in vitro assays and computer aided results, we suggest that these compounds need further detail in vivo studies and clinical trial for the discovery of new more effective and safe lipoxygenase inhibitors. In conclusion, these results might be useful in the design of new and potential lipoxygenase (LOX) inhibitors.

Promising Anticancer Therapeutics From Mushrooms: Current Findings and Future Perceptions

2020 ◽  
Vol 21 ◽  
Author(s):  
Mrunmaya Kumar Panda ◽  
Manish Paul ◽  
Sameer Kumar Singdevsachan ◽  
Kumananda Tayung ◽  
Swagat Kumar Das ◽  
...  
Keyword(s):  
Cell Proliferation ◽  
Cancer Cell ◽  
In Silico ◽  
Present Review ◽  
Cancer Cell Proliferation ◽  
Research Papers ◽  
Medicinal Mushrooms ◽  
In Silico Studies ◽  
Anticancer Therapeutics ◽  
Ethnomedicinal Uses

Background: Nowadays medicines derived from natural sources have drawn much attention as potential therapeutic agents in the suppression and treatment of cancer because of their low toxicity and fewer side effects. Objective: The present review aims to assess the currently available knowledge on the ethnomedicinal uses and pharmacological activities of bioactive compounds obtained from medicinal mushrooms towards cancer treatment. Methods: Literature search has been conducted for the collection of research papers from universally accepted scientific databases. These research papers and published book chapters were scrutinized to retrieve information on ethnomedicinal uses of mushrooms, different factors involved in cancer cell proliferation, clinical and in silico pharmaceutical studies made for possible treatments of cancer using mushroom derived compounds. Overall 241 articles were retrieved and reviewed from the year of 1970 to 2020, out of which 98 relevant articles were finally considered for preparation of this review. Results: This review presents an update on the natural bioactive substances derived from medicinal mushrooms and their role in inhibiting the factors responsible for cancer cell proliferation. Along with it, the present review also provides information on the ethnomedicinal uses, solvents used for extraction of anticancer metabolites, clinical trials, and in silico studies that were undertaken towards anticancer drug development from medicinal mushrooms. Conclusion: The present review provides an extensive knowledge on various anticancer substances obtained from medicinal mushrooms, their biological actions and in silico drug designing approaches which could form a basis for the development of natural anticancer therapeutics.

In Vitro, In Silico and Ex Vivo Studies of Dihydroartemisinin Derivatives as Antitubercular Agents

2019 ◽  
Vol 19 (8) ◽  
pp. 633-644 ◽  
Author(s):  
Komal Kalani ◽  
Sarfaraz Alam ◽  
Vinita Chaturvedi ◽  
Shyam Singh ◽  
Feroz Khan ◽  
...  
Keyword(s):  
Bone Marrow ◽  
In Silico ◽  
Ex Vivo ◽  
Virulent Strain ◽  
Infection Model ◽  
Mouse Bone Marrow ◽  
Significant Activity ◽  
Macrophage Infection ◽  
In Silico Studies

Introduction: As a part of our drug discovery program for anti-tubercular agents, dihydroartemisinin (DHA-1) was screened against Mtb H37Rv, which showed moderate anti-tubercular activity (>25.0 µg/mL). These results prompted us to carry out the chemical transformation of DHA-1 into various derivatives and study their antitubercular potential. Materials and Methods: DHA-1 was semi-synthetically converted into four new acyl derivatives (DHA-1A – DHA-1D) and in-vitro evaluated for their anti-tubercular potential against Mycobacterium tuberculosis H37Rv virulent strain. The derivatives, DHA-1C (12-O-(4-nitro) benzoyl; MIC 12.5 µg/mL) and DHA-1D (12-O-chloro acetyl; MIC 3.12µg/mL) showed significant activity against the pathogen. Results: In silico studies of the most active derivative (DHA-1D) showed interaction with ARG448 inhibiting the mycobacterium enzymes. Additionally, it showed no cytotoxicity towards the Vero C1008 cells and Mouse bone marrow derived macrophages. Conclusion: DHA-1D killed 62% intracellular M. tuberculosis in Mouse bone marrow macrophage infection model. To the best of our knowledge, this is the first-ever report on the antitubercular potential of dihydroartemisinin and its derivatives. Since dihydroartemisinin is widely used as an antimalarial drug; these results may be of great help in anti-tubercular drug development from a very common, inexpensive, and non-toxic natural product.

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