Flux Balance Analysis for Media Optimization and Genetic Targets to Improve Heterologous Siderophore Production

Swayambhu, Girish; Moscatello, Nicholas; Atilla‐Gokcumen, G. Ekin; Pfeifer, Blaine A.

doi:10.1016/j.isci.2020.101016

Cited by 17 publications

(13 citation statements)

References 28 publications

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“…Braud et al [33] showed that the siderophores produced by the genus Pseudomonas have a greater affinity not only for Fe 3+ sequestration, but for other minerals as well, such as Hg. In the presence of Hg in the soil, the sequestration of Fe 3+ by siderophores is not negatively affected and remains available to plants and can also be incorporated thanks to the action of reducing enzymes that transform it into Fe 2+ , another form that is soluble and bioavailable for the plant [34].…”

Section: Discussionmentioning

confidence: 99%

Evaluation of the PGPR Capacity of Four Bacterial Strains and Their Mixtures, Tested on Lupinus albus var. Dorado Seedlings, for the Bioremediation of Mercury-Polluted Soils

et al. 2021

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Soil contamination by mercury, which is one of the most toxic heavy metals due to its bioaccumulative capacity, poses a risk to the environment as well as health. The Almadén mining district in Ciudad Real, Spain is one of the most heavily-polluted sites in the world, making the soils unusable. Bioremediation, and more specifically phyto-rhizoremediation, based on the synergistic interaction established between plant and Plant Growth Promoting Rhizobacteria (PGPR), improves the plant's ability to grow, mobilize, accumulate, and extract contaminants from the soil. The objective of this study is to evaluate the plant growth-promoting ability of four PGPR strains (and mixtures), isolated from the bulk soil and rhizosphere of naturally grown plants in the Almadén mining district, when they are inoculated in emerged seeds of Lupinus albus, var. Dorado in the presence of high concentrations of mercury. After 20 days of incubation and subsequent harvesting of the seedlings, biometric measurements were carried out at the root and aerial levels. The results obtained show that the seeds treatment with PGPR strains improves plants biometry in the presence of mercury. Specifically, strain B2 (Pseudomonas baetica) and B1 (Pseudomonas moraviensis) were those that contributed the most to plant growth, both individually and as part of mixtures (CS5 and CS3). Thus, these are postulated to be good candidates for further in situ phyto-rhizoremediation tests of mercury-contaminated soils.

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Section: Discussionmentioning

confidence: 99%

Evaluation of the PGPR Capacity of Four Bacterial Strains and Their Mixtures, Tested on Lupinus albus var. Dorado Seedlings, for the Bioremediation of Mercury-Polluted Soils

et al. 2021

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“…FBA can be applied to predict media composition to enhance production yield that can be further verified experimentally. Recently FBA has been applied to improve the heterologous expression of siderophores by E. coli K-12 MG1655 [202]. In conclusion, computational and bioinformatics approaches are helpful to identify novel siderophores, their biosynthetic pathways, and biological activities.…”

Section: Computational Approaches For the Application Of Siderophoresmentioning

confidence: 99%

Biosynthesis Pathways, Transport Mechanisms and Biotechnological Applications of Fungal Siderophores

Pecoraro

Wang

Shah

et al. 2021

JoF

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Iron (Fe) is the fourth most abundant element on earth and represents an essential nutrient for life. As a fundamental mineral element for cell growth and development, iron is available for uptake as ferric ions, which are usually oxidized into complex oxyhydroxide polymers, insoluble under aerobic conditions. In these conditions, the bioavailability of iron is dramatically reduced. As a result, microorganisms face problems of iron acquisition, especially under low concentrations of this element. However, some microbes have evolved mechanisms for obtaining ferric irons from the extracellular medium or environment by forming small molecules often regarded as siderophores. Siderophores are high affinity iron-binding molecules produced by a repertoire of proteins found in the cytoplasm of cyanobacteria, bacteria, fungi, and plants. Common groups of siderophores include hydroxamates, catecholates, carboxylates, and hydroximates. The hydroxamate siderophores are commonly synthesized by fungi. L-ornithine is a biosynthetic precursor of siderophores, which is synthesized from multimodular large enzyme complexes through non-ribosomal peptide synthetases (NRPSs), while siderophore-Fe chelators cell wall mannoproteins (FIT1, FIT2, and FIT3) help the retention of siderophores. S. cerevisiae, for example, can express these proteins in two genetically separate systems (reductive and nonreductive) in the plasma membrane. These proteins can convert Fe (III) into Fe (II) by a ferrous-specific metalloreductase enzyme complex and flavin reductases (FREs). However, regulation of the siderophore through Fur Box protein on the DNA promoter region and its activation or repression depend primarily on the Fe availability in the external medium. Siderophores are essential due to their wide range of applications in biotechnology, medicine, bioremediation of heavy metal polluted environments, biocontrol of plant pathogens, and plant growth enhancement.

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“…They combined the FBA with Plackett Burman (PB) in silico to identify the amino acids and carbon sources that significantly impacted productivity. [ 52 ] Fouladiha et al. used a GEM of the Chinese hamster ovary (CHO) to design feeding strategies to increase the production of a monoclonal antibody.…”

Section: Cbm: a Mechanistic‐driven Approachmentioning

confidence: 99%

Synergisms of machine learning and constraint‐based modeling of metabolism for analysis and optimization of fermentation parameters

Khaleghi

Savizi

Lewis

et al. 2021

Biotechnology Journal

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Recent noteworthy advances in developing high‐performing microbial and mammalian strains have enabled the sustainable production of bio‐economically valuable substances such as bio‐compounds, biofuels, and biopharmaceuticals. However, to obtain an industrially viable mass‐production scheme, much time and effort are required. The robust and rational design of fermentation processes requires analysis and optimization of different extracellular conditions and medium components, which have a massive effect on growth and productivity. In this regard, knowledge‐ and data‐driven modeling methods have received much attention. Constraint‐based modeling (CBM) is a knowledge‐driven mathematical approach that has been widely used in fermentation analysis and optimization due to its ability to predict the cellular phenotype from genotype through high‐throughput means. On the other hand, machine learning (ML) is a data‐driven statistical method that identifies the data patterns within sophisticated biological systems and processes, where there is inadequate knowledge to represent underlying mechanisms. Furthermore, ML models are becoming a viable complement to constraint‐based models in a reciprocal manner when one is used as a pre‐step of another. As a result, a more predictable model is produced. This review highlights the applications of CBM and ML independently and the combination of these two approaches for analyzing and optimizing fermentation parameters.

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Flux Balance Analysis for Media Optimization and Genetic Targets to Improve Heterologous Siderophore Production

Cited by 17 publications

References 28 publications

Evaluation of the PGPR Capacity of Four Bacterial Strains and Their Mixtures, Tested on Lupinus albus var. Dorado Seedlings, for the Bioremediation of Mercury-Polluted Soils

Evaluation of the PGPR Capacity of Four Bacterial Strains and Their Mixtures, Tested on Lupinus albus var. Dorado Seedlings, for the Bioremediation of Mercury-Polluted Soils

Biosynthesis Pathways, Transport Mechanisms and Biotechnological Applications of Fungal Siderophores

Synergisms of machine learning and constraint‐based modeling of metabolism for analysis and optimization of fermentation parameters

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