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Translation efficiency of heterologous proteins is significantly affected by the genetic context of RBS sequences in engineered cyanobacterium Synechocystis sp. PCC 6803

Overview of attention for article published in Microbial Cell Factories, March 2018
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  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (74th percentile)
  • Good Attention Score compared to outputs of the same age and source (74th percentile)

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Title
Translation efficiency of heterologous proteins is significantly affected by the genetic context of RBS sequences in engineered cyanobacterium Synechocystis sp. PCC 6803
Published in
Microbial Cell Factories, March 2018
DOI 10.1186/s12934-018-0882-2
Pubmed ID
Authors

Kati Thiel, Edita Mulaku, Hariharan Dandapani, Csaba Nagy, Eva-Mari Aro, Pauli Kallio

Abstract

Photosynthetic cyanobacteria have been studied as potential host organisms for direct solar-driven production of different carbon-based chemicals from CO2and water, as part of the development of sustainable future biotechnological applications. The engineering approaches, however, are still limited by the lack of comprehensive information on most optimal expression strategies and validated species-specific genetic elements which are essential for increasing the intricacy, predictability and efficiency of the systems. This study focused on the systematic evaluation of the key translational control elements, ribosome binding sites (RBS), in the cyanobacterial host Synechocystis sp. PCC 6803, with the objective of expanding the palette of tools for more rigorous engineering approaches. An expression system was established for the comparison of 13 selected RBS sequences in Synechocystis, using several alternative reporter proteins (sYFP2, codon-optimized GFPmut3 and ethylene forming enzyme) as quantitative indicators of the relative translation efficiencies. The set-up was shown to yield highly reproducible expression patterns in independent analytical series with low variation between biological replicates, thus allowing statistical comparison of the activities of the different RBSs in vivo. While the RBSs covered a relatively broad overall expression level range, the downstream gene sequence was demonstrated in a rigorous manner to have a clear impact on the resulting translational profiles. This was expected to reflect interfering sequence-specific mRNA-level interaction between the RBS and the coding region, yet correlation between potential secondary structure formation and observed translation levels could not be resolved with existing in silico prediction tools. The study expands our current understanding on the potential and limitations associated with the regulation of protein expression at translational level in engineered cyanobacteria. The acquired information can be used for selecting appropriate RBSs for optimizing over-expression constructs or multicistronic pathways in Synechocystis, while underlining the complications in predicting the activity due to gene-specific interactions which may reduce the translational efficiency for a given RBS-gene combination. Ultimately, the findings emphasize the need for additional characterized insulator sequence elements to decouple the interaction between the RBS and the coding region for future engineering approaches.

X Demographics

X Demographics

The data shown below were collected from the profiles of 13 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 115 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 115 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 20 17%
Researcher 19 17%
Student > Master 19 17%
Student > Bachelor 8 7%
Student > Doctoral Student 6 5%
Other 6 5%
Unknown 37 32%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 44 38%
Agricultural and Biological Sciences 19 17%
Chemical Engineering 4 3%
Engineering 3 3%
Social Sciences 1 <1%
Other 3 3%
Unknown 41 36%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 8. 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 09 November 2019.
All research outputs
#4,209,997
of 23,025,074 outputs
Outputs from Microbial Cell Factories
#223
of 1,613 outputs
Outputs of similar age
#83,670
of 331,404 outputs
Outputs of similar age from Microbial Cell Factories
#10
of 39 outputs
Altmetric has tracked 23,025,074 research outputs across all sources so far. Compared to these this one has done well and is in the 81st percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,613 research outputs from this source. They receive a mean Attention Score of 4.4. This one has done well, scoring higher than 86% of its peers.
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 331,404 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 74% of its contemporaries.
We're also able to compare this research output to 39 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 74% of its contemporaries.