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Coupling gene regulatory patterns to bioprocess conditions to optimize synthetic metabolic modules for improved sesquiterpene production in yeast

Overview of attention for article published in Biotechnology for Biofuels, February 2017
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Title
Coupling gene regulatory patterns to bioprocess conditions to optimize synthetic metabolic modules for improved sesquiterpene production in yeast
Published in
Biotechnology for Biofuels, February 2017
DOI 10.1186/s13068-017-0728-x
Pubmed ID
Authors

Bingyin Peng, Manuel R. Plan, Alexander Carpenter, Lars K. Nielsen, Claudia E. Vickers

Abstract

Assembly of heterologous metabolic pathways is commonly required to generate microbial cell factories for industrial production of both commodity chemicals (including biofuels) and high-value chemicals. Promoter-mediated transcriptional regulation coordinates the expression of the individual components of these heterologous pathways. Expression patterns vary during culture as conditions change, and this can influence yeast physiology and productivity in both positive and negative ways. Well-characterized strategies are required for matching transcriptional regulation with desired output across changing culture conditions. Here, constitutive and inducible regulatory mechanisms were examined to optimize synthetic isoprenoid metabolic pathway modules for production of trans-nerolidol, an acyclic sesquiterpene alcohol, in yeast. The choice of regulatory system significantly affected physiological features (growth and productivity) over batch cultivation. Use of constitutive promoters resulted in poor growth during the exponential phase. Delaying expression of the assembled metabolic modules using the copper-inducible CUP1 promoter resulted in a 1.6-fold increase in the exponential-phase growth rate and a twofold increase in productivity in the post-exponential phase. However, repeated use of the CUP1 promoter in multiple expression cassettes resulted in genetic instability. A diauxie-inducible expression system, based on an engineered GAL regulatory circuit and a set of four different GAL promoters, was characterized and employed to assemble nerolidol synthetic metabolic modules. Nerolidol production was further improved by 60% to 392 mg L(-1) using this approach. Various carbon source systems were investigated in batch/fed-batch cultivation to regulate induction through the GAL system; final nerolidol titres of 4-5.5 g L(-1) were achieved, depending on the conditions. Direct comparison of different transcriptional regulatory mechanisms clearly demonstrated that coupling the output strength to the fermentation stage is important to optimize the growth fitness and overall productivities of engineered cells in industrially relevant processes. Applying different well-characterized promoters with the same induction behaviour mitigates against the risks of homologous sequence-mediated genetic instability. Using these approaches, we significantly improved sesquiterpene production in yeast.

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 82 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 82 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 19 23%
Student > Ph. D. Student 18 22%
Student > Master 9 11%
Other 8 10%
Student > Bachelor 7 9%
Other 6 7%
Unknown 15 18%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 30 37%
Agricultural and Biological Sciences 21 26%
Chemistry 5 6%
Chemical Engineering 2 2%
Engineering 2 2%
Other 5 6%
Unknown 17 21%

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 22 February 2017.
All research outputs
#4,945,134
of 9,098,986 outputs
Outputs from Biotechnology for Biofuels
#385
of 757 outputs
Outputs of similar age
#149,262
of 255,176 outputs
Outputs of similar age from Biotechnology for Biofuels
#32
of 48 outputs
Altmetric has tracked 9,098,986 research outputs across all sources so far. This one is in the 27th percentile – i.e., 27% of other outputs scored the same or lower than it.
So far Altmetric has tracked 757 research outputs from this source. They receive a mean Attention Score of 4.1. This one is in the 32nd percentile – i.e., 32% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 255,176 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 32nd percentile – i.e., 32% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 48 others from the same source and published within six weeks on either side of this one. This one is in the 6th percentile – i.e., 6% of its contemporaries scored the same or lower than it.