Genome-scale metabolic network guided engineering of Streptomyces tsukubaensis for FK506 production improvement

Abstract

Background: FK506 is an important immunosuppressant, which can be produced by Streptomyces tsukubaensis. However, the production capacity of the strain is very low. Hereby, a computational guided engineering approach was proposed in order to improve the intracellular precursor and cofactor availability of FK506 in S. tsukubaensis.

Results: First, a genome-scale metabolic model of S. tsukubaensis was constructed based on its annotated genome and biochemical information. Subsequently, several potential genetic targets (knockout or overexpression) that guaranteed an improved yield of FK506 were identified by the recently developed methodology. To validate the model predictions, each target gene was manipulated in the parent strain D852, respectively. All the engineered strains showed a higher FK506 production, compared with D852. Furthermore, the combined effect of the genetic modifications was evaluated. Results showed that the strain HT-ΔGDH-DAZ with gdhA-deletion and dahp-, accA2-, zwf2-overexpression enhanced FK506 concentration up to 398.9 mg/L, compared with 143.5 mg/L of the parent strain D852. Finally, fed-batch fermentations of HT-ΔGDH-DAZ were carried out, which led to the FK506 production of 435.9 mg/L, 1.47-fold higher than the parent strain D852 (158.7 mg/L).

Conclusions: Results confirmed that the promising targets led to an increase in FK506 titer. The present work is the first attempt to engineer the primary precursor pathways to improve FK506 production in S. tsukubaensis with genome-scale metabolic network guided metabolic engineering. The relationship between model prediction and experimental results demonstrates the rationality and validity of this approach for target identification. This strategy can also be applied to the improvement of other important secondary metabolites.

Figure 1

Structures and biosynthetic gene cluster of FK506 and byproducts (FK520, FK506D) in S. tsukubaensis. (A) Structures of FK506 and byproducts FK520, FK506D. The allyl side chain at C-21 of FK506 is replaced by an ethyl group in FK520 and a propyl group in FK506D. (B) Schematic representation of FK506 and analogues (FK520, FK506D) biosynthetic gene cluster in S. tsukubaensis.

Figure 2

Schematic representation of metabolic pathways for S. tsukubaensis. The predicted targets for improved production are shown in green (amplification) and red (knockout). The shaded boxes represent precursors of FK506 biosynthesis.

Figure 3

Single gene knockout, overexpression and knockout-overexpression combinations target identification in S. tsukubaensis. (A) The effect of single gene knockout on the specific FK506 production rate and the specific growth rate. (B) The effect of single gene overexpression on the specific FK506 production and f_PH. (C) The effect of knockout-overexpression combinations on the specific FK506 production and f_PH. The enzymes encoded by these genes are as follows: aceA, isocitrate lyase; aceB2/B1, malate synthase; sucC/D, succinyl-CoA synthase; gdhA, glutamate dehydrogenase; pgi, glucose-6-phosphate isomerase; ppc, phosphoenolpyruvate carboxylase; dahp, 3-deoxy-D-arabino-heptulosonate-7-phosphate synthase; pntAB, pyridine nucleotide transhydrogenase; accA2, acetyl-CoA carboxylase; fkbA, fkbB, fkbC, polyketide synthase; fkbO, chorismatase, 4,5-dihydroxycyclohex-1-enecarboxylic acid (DHCHC) synthesis; fkbL, lysine cyclodeaminase; fkbP, non-ribosomal peptide synthetase; fkbM, 31-O-methyltrasferase; fkbD, C9 hydroxylase; fkbG, fkbH, fkbI, fkbJ, fkbK, genes for methoxymalonyl-ACP synthesis; tcsA, tcsB, tcsC, tcsD, genes for allymalonyl-CoA synthesis; zwf2, glucose-6-phosphate dehydrogenase; pccB, propionyl-CoA carboxylase; metK, S-adenosylmethionine synthetase.

Figure 4

The effect of single gene knockout and complementation on FK506 production and cell growth. The data are the average values of at least three series of three parallel tests, and error bars represent standard deviations.

Figure 5

Intracellular metabolite profiles at 72 h for engineered strains. Heat map visualizes most intracellular metabolites from glycolysis, TCA, PPP and amino acid pathways of engineered strains under the same fermentation condition. The color code indicates an increased (red) or a decreased (green) availability as compared to the reference wild-type strain D852, as indicated by the color legend as aside the graph. Availability for each metabolite was calculated as ratio of the concentration of each engineered strain to that of the wild-type strain D852. The data are the average values of at least five series of five parallel tests.

Figure 6

The effect of single gene overexpression on FK506 production and cell growth. The data are the average values of at least three series of three parallel tests, and error bars represent standard deviations.

Figure 7

The effect of combined gene knockout and overexpression on FK506 production. Plus or minus symbols denote presence or absence of the indicated gene(s) manipulation. The data are the average values of at least three series of three parallel tests, and error bars represent standard deviations.

Figure 8

The production performance profiles of wild-type strain D852 and engineered strain HT-ΔGDH-DAZ in fed-batch fermentation. (A) Total sugar and biomass profiles; (B) FK506 and by-products profiles. The data are the average values of at least three series of three parallel tests, and error bars represent standard deviations.