title: Genetically-encoded nanosensor for quantitative monitoring of methionine in bacterial and yeast cells.
abstract: Metabolic engineering of microorganisms for production of biological molecules represent a key goal for industrial biotechnology. The metabolic engineering requires detailed knowledge of the concentrations and flux rates of metabolites and metabolic intermediates in vivo. Genetically-encoded fluorescence resonance energy transfer (FRET) sensors represent a promising technology for measuring metabolite levels and corresponding rate changes in live cells. In the present paper, we report the development of genetically-encoded FRET-based nanosensor for methionine as metabolic engineering of microbial strains for the production of l-methionine is of major interest in industrial biotechnology. In this nanosensor, methionine binding protein (MetN) from Escherichia coli (E. coli) K12 was taken and used as the reporter element of the sensor. The MetN was sandwiched between cyan fluorescent protein (CFP) and yellow fluorescent protein (YFP). Specificity, affinity, pH stability and metal effects was analyzed for the in vitro characterization of this nanosensor, named as FLIPM. The FLIPM is very specific to methionine and found to be stable with the pH within the physiological range. The calculated affinity (Kd) of FLIPM was 203 µM. This nanosensor successfully monitored the intracellular level of methionine in bacterial as well as yeast cell. The data suggest that these nanosensors may be a versatile tool for studying the in vivo dynamics of methionine level non-invasively in living cells.
authors.affiliation: Molecular Ecology Laboratory, Department of Botany, Jamia Hamdard (Hamdard University), New Delhi 110062, India.
authors.forename: Mohd
authors.initials: M
authors.lastname: Mohsin
authors.affiliation: Molecular Ecology Laboratory, Department of Botany, Jamia Hamdard (Hamdard University), New Delhi 110062, India. Electronic address: aahmed@jamiahamdard.ac.in.
authors.forename: Altaf
authors.initials: A
authors.lastname: Ahmad
mesh_terms: D000251:Adenosine Triphosphatases / Q000235:genetics / Q000378:metabolism; D001426:Bacterial Proteins / Q000235:genetics / Q000378:metabolism; D015374:Biosensing Techniques / Q000379:methods; D003001:Cloning, Molecular; D004926:Escherichia coli / Q000235:genetics / Q000378:metabolism*; D029968:Escherichia coli Proteins / Q000235:genetics / Q000378:metabolism; D031541:Fluorescence Resonance Energy Transfer / Q000379:methods*; D049452:Green Fluorescent Proteins / Q000235:genetics / Q000378:metabolism; D008164:Luminescent Proteins / Q000235:genetics / Q000378:metabolism; D008715:Methionine / Q000032:analysis* / Q000378:metabolism; D008958:Models, Molecular; D015202:Protein Engineering / Q000379:methods; D011994:Recombinant Proteins / Q000235:genetics / Q000378:metabolism; D012441:Saccharomyces cerevisiae / Q000378:metabolism*
chemical_list: D001426:Bacterial Proteins; C485182:Cyan Fluorescent Protein; D029968:Escherichia coli Proteins; D008164:Luminescent Proteins; D011994:Recombinant Proteins; C054562:yellow fluorescent protein, Bacteria; D049452:Green Fluorescent Proteins; D008715:Methionine; D000251:Adenosine Triphosphatases; C466428:MetN protein, E coli
keywords: Fluorescence resonance energy transfer; Fluorescent proteins; Genetically-encoded nanosensor; Imaging; Methionine