A high-throughput screen for hyaluronic acid accumulation in recombinant Escherichia coli transformed by libraries of engineered sigma factors.
Hyaluronic acid (HA) is an important biomaterial with functional medical and cosmetic applications. As its synthesis has been recently reported in recombinant bacteria, it is of interest to develop a high throughput screening method for the rapid isolation of HA accumulating strains transformed by combinatorial libraries. Here we report a novel two-step screening strategy to select for better HA-producing recombinant Escherichia coli strains transformed by mutation libraries of rpoD and rpoS, coding for the sigma(D) and sigma(S) factors of the RNA polymerase, respectively. The first screen, based on translucent colony morphology identification, was used to qualitatively distinguish HA-producing strains on agar plates from non-HA producing strains that exhibit dense colony morphology. The second screen was based on the photometric measurement of an alcian blue staining solution that precipitates with HA, creating an inverse relationship between HA concentration and alcian blue absorbance. The color attenuation fitted a second-order polynomial between HA concentration and OD(540) absorbance. Using the alcian blue absorbance quantification, 74 translucent colonies from the HA-rpoD library and 78 translucent colonies from the HA-rpoS library were isolated and cultured for optimal strain selection. Three representative superior recombinants with high, medium and low increase of HA accumulation, respectively, were identified by the screen from the HA-rpoD and HA-rpoS mutant library. Further flask culture confirmed that results of the library screen were reliable and the superior recombinant D72 highly accumulated HA of 561.4 mg/L with a productivity of approximately 265 mg HA/g dry cell. Sequencing results showed that the mutant rpoD gene in D72 is in a truncated protein that lacks the conserved regions 3 and 4 of the sigma(D). Generally, this two-step high throughput screen presents a promising strategy for selecting superior HA-producing strains from large scale mutation libraries.
Yu
Huimin
H
Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA.
Tyo
Keith
K
Alper
Hal
H
Klein-Marcuschamer
Daniel
D
Stephanopoulos
Gregory
G
D004926:Escherichia coli / Q000235:genetics* / Q000378:metabolism*; D015723:Gene Library; D006820:Hyaluronic Acid / Q000096:biosynthesis*; D050505:Mutant Proteins / Q000235:genetics / Q000378:metabolism; D009154:Mutation; D017434:Protein Structure, Tertiary; D011994:Recombinant Proteins / Q000235:genetics; D017384:Sequence Deletion; D012808:Sigma Factor / Q000235:genetics*; D013194:Staining and Labeling / Q000379:methods; D014170:Transformation, Genetic
D050505:Mutant Proteins; D011994:Recombinant Proteins; D012808:Sigma Factor; D006820:Hyaluronic Acid