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Time-Resolved Transcriptomics and Constraint-Based Modeling Identify System-Level Metabolic Features and Overexpression Targets to Increase Spiramycin Production in Streptomyces ambofaciens

Overview of attention for article published in Frontiers in Microbiology, May 2017
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  • Above-average Attention Score compared to outputs of the same age and source (57th percentile)

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Title
Time-Resolved Transcriptomics and Constraint-Based Modeling Identify System-Level Metabolic Features and Overexpression Targets to Increase Spiramycin Production in Streptomyces ambofaciens
Published in
Frontiers in Microbiology, May 2017
DOI 10.3389/fmicb.2017.00835
Pubmed ID
Authors

Marco Fondi, Eva Pinatel, Adelfia Talà, Fabrizio Damiano, Clarissa Consolandi, Benedetta Mattorre, Daniela Fico, Mariangela Testini, Giuseppe E. De Benedetto, Luisa Siculella, Gianluca De Bellis, Pietro Alifano, Clelia Peano

Abstract

In this study we have applied an integrated system biology approach to characterize the metabolic landscape of Streptomyces ambofaciens and to identify a list of potential metabolic engineering targets for the overproduction of the secondary metabolites in this microorganism. We focused on an often overlooked growth period (i.e., post-first rapid growth phase) and, by integrating constraint-based metabolic modeling with time resolved RNA-seq data, we depicted the main effects of changes in gene expression on the overall metabolic reprogramming occurring in S. ambofaciens. Moreover, through metabolic modeling, we unraveled a set of candidate overexpression gene targets hypothetically leading to spiramycin overproduction. Model predictions were experimentally validated by genetic manipulation of the recently described ethylmalonyl-CoA metabolic node, providing evidence that spiramycin productivity may be increased by enhancing the carbon flow through this pathway. The goal was achieved by over-expressing the ccr paralog srm4 in an ad hoc engineered plasmid. This work embeds the first metabolic reconstruction of S. ambofaciens and the successful experimental validation of model predictions and demonstrates the validity and the importance of in silico modeling tools for the overproduction of molecules with a biotechnological interest. Finally, the proposed metabolic reconstruction, which includes manually refined pathways for several secondary metabolites with antimicrobial activity, represents a solid platform for the future exploitation of S. ambofaciens biotechnological potential.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 40 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 40 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 9 23%
Student > Bachelor 7 18%
Researcher 4 10%
Other 3 8%
Student > Master 3 8%
Other 4 10%
Unknown 10 25%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 8 20%
Agricultural and Biological Sciences 5 13%
Computer Science 2 5%
Chemical Engineering 2 5%
Chemistry 2 5%
Other 7 18%
Unknown 14 35%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 4. 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 30 May 2017.
All research outputs
#6,769,637
of 22,968,808 outputs
Outputs from Frontiers in Microbiology
#6,788
of 25,018 outputs
Outputs of similar age
#105,910
of 310,140 outputs
Outputs of similar age from Frontiers in Microbiology
#223
of 523 outputs
Altmetric has tracked 22,968,808 research outputs across all sources so far. This one has received more attention than most of these and is in the 70th percentile.
So far Altmetric has tracked 25,018 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.3. This one has gotten more attention than average, scoring higher than 72% 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 310,140 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 65% of its contemporaries.
We're also able to compare this research output to 523 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 57% of its contemporaries.