Turnover Dependent Phenotypic Simulation: A Quantitative Constraint-Based Simulation Method That Accommodates All Main Strain Design Strategies
Artikel i vetenskaplig tidskrift, 2019

The uncertain relationship between genotype and phenotype can make strain engineering an arduous trial and error process. To identify promising gene targets faster, constraint-based modeling methodologies are often used, although they remain limited in their predictive power. Even though the search for gene knockouts is fairly established in constraint-based modeling, most strain design methods still model gene up/down-regulations by forcing the corresponding flux values to fixed levels without taking in consideration the availability of resources. Here, we present a constraint-based algorithm, the turnover dependent phenotypic simulation (TDPS) that quantitatively simulates phenotypes in a resource conscious manner. Unlike other available algorithms, TDPS does not force flux values and considers resource availability, using metabolite production turnovers as an indicator of metabolite abundance. TDPS can simulate up-regulation of metabolic reactions as well as the introduction of heterologous genes, alongside gene deletion and down-regulation scenarios. TDPS simulations were validated using engineered Saccharomyces cerevisiae strains available in the literature by comparing the simulated and experimental production yields of the target metabolite. For many of the strains evaluated, the experimental production yields were within the simulated intervals and the relative strain performance could be predicted with TDPS. However, the algorithm failed to predict some of the production changes observed experimentally, suggesting that further improvements are necessary. The results also showed that TDPS may be helpful in finding metabolic bottlenecks, but further experiments would be required to confirm these findings.

network rigidity

metabolic engineering

metabolite turnovers

genome-scale models

Saccharomyces cerevisiae

phenotype simulation


Rui Pereira

Chalmers, Biologi och bioteknik, Systembiologi

Universidade do Minho

P. Vilaca

SilicoLife Lda

Universidade do Minho

P. Maia

Universidade do Minho

SilicoLife Lda

Jens B Nielsen

Chalmers, Biologi och bioteknik, Systembiologi

Danmarks Tekniske Universitet (DTU)

I. Rocha

Universidade NOVA de Lisboa

Universidade do Minho

ACS Synthetic Biology

2161-5063 (eISSN)

Vol. 8 5 976-988


Teknisk mekanik

Bioinformatik (beräkningsbiologi)

Bioinformatik och systembiologi





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