A Four-Step Platform to Optimize Growth Conditions for High-Yield Production of Siderophores in Cyanobacteria.
Karishma KunduRoberta TetaGermana EspositoMariano StornaiuoloValeria CostantinoPublished in: Metabolites (2023)
In response to Iron deprivation and in specific environmental conditions, the cyanobacteria Anabaena flos aquae produce siderophores, iron-chelating molecules that in virtue of their interesting environmental and clinical applications, are recently gaining the interest of the pharmaceutical industry. Yields of siderophore recovery from in vitro producing cyanobacterial cultures are, unfortunately, very low and reach most of the times only analytical quantities. We here propose a four-step experimental pipeline for a rapid and inexpensive identification and optimization of growth parameters influencing, at the transcriptional level, siderophore production in Anabaena flos aquae . The four-steps pipeline consists of: (1) identification of the promoter region of the operon of interest in the genome of Anabaena flos aquae ; (2) cloning of the promoter in a recombinant DNA vector, upstream the cDNA coding for the Green Fluorescent Protein (GFP) followed by its stable transformation in Escherichia Coli ; (3) identification of the environmental parameters affecting expression of the gene in Escherichia coli and their application to the cultivation of the Anabaena strain; (4) identification of siderophores by the combined use of high-resolution tandem mass spectrometry and molecular networking. This multidisciplinary, sustainable, and green pipeline is amenable to automation and is virtually applicable to any cyanobacteria, or more in general, to any microorganisms.
Keyphrases
- escherichia coli
- tandem mass spectrometry
- high resolution
- liquid chromatography
- gene expression
- transcription factor
- bioinformatics analysis
- dna methylation
- ultra high performance liquid chromatography
- poor prognosis
- genome wide
- mass spectrometry
- gas chromatography
- klebsiella pneumoniae
- protein protein
- staphylococcus aureus
- high throughput
- long non coding rna
- sensitive detection
- high speed
- data analysis
- amino acid