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Transcriptomic analysis of a classical model of carbon catabolite regulation in Streptomyces coelicolor

Overview of attention for article published in BMC Microbiology, April 2016
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Title
Transcriptomic analysis of a classical model of carbon catabolite regulation in Streptomyces coelicolor
Published in
BMC Microbiology, April 2016
DOI 10.1186/s12866-016-0690-y
Pubmed ID
Authors

Alba Romero-Rodríguez, Diana Rocha, Beatriz Ruiz-Villafan, Víctor Tierrafría, Romina Rodríguez-Sanoja, Daniel Segura-González, Sergio Sánchez

Abstract

In the genus Streptomyces, one of the most remarkable control mechanisms of physiological processes is carbon catabolite repression (CCR). This mechanism regulates the expression of genes involved in the uptake and utilization of alternative carbon sources. CCR also affects the synthesis of secondary metabolites and morphological differentiation. Even when the outcome effect of CCR in different bacteria is the same, their essential mechanisms can be quite different. In several streptomycetes glucose kinase (Glk) represents the main glucose phosphorylating enzyme and has been regarded as a regulatory protein in CCR. To evaluate the paradigmatic model proposed for CCR in Streptomyces, a high-density microarray approach was applied to Streptomyces coelicolor M145, under repressed and non-repressed conditions. The transcriptomic study was extended to assess the ScGlk role in this model by comparing the transcriptomic profile of S. coelicolor M145 with that of a ∆glk mutant derived from the wild-type strain, complemented with a heterologous glk gene from Zymomonas mobilis (Zmglk), insensitive to CCR but able to grow in glucose (ScoZm strain). Microarray experiments revealed that glucose influenced the expression of 651 genes. Interestingly, even when the ScGlk protein does not have DNA binding domains and the glycolytic flux was restored by a heterologous glucokinase, the ScGlk replacement modified the expression of 134 genes. From these, 91 were also affected by glucose while 43 appeared to be under the control of ScGlk. This work identified the expression of S. coelicolor genes involved in primary metabolism that were influenced by glucose and/or ScGlk. Aside from describing the metabolic pathways influenced by glucose and/or ScGlk, several unexplored transcriptional regulators involved in the CCR mechanism were disclosed. The transcriptome of a classical model of CCR was studied in S. coelicolor to differentiate between the effects due to glucose or ScGlk in this regulatory mechanism. Glucose elicited important metabolic and transcriptional changes in this microorganism. While its entry and flow through glycolysis and pentose phosphate pathway were stimulated, the gluconeogenesis was inhibited. Glucose also triggered the CCR by repressing transporter systems and the transcription of enzymes required for secondary carbon sources utilization. Our results confirm and update the agar model of the CCR in Streptomyces and its dependence on the ScGlk per se. Surprisingly, the expected regulatory function of ScGlk was not found to be as global as thought before (only 43 out of 779 genes were affected), although may be accompanied or coordinated by other transcriptional regulators. Aside from describing the metabolic pathways influenced by glucose and/or ScGlk, several unexplored transcriptional regulators involved in the CCR mechanism were disclosed. These findings offer new opportunities to study and understand the CCR in S. coelicolor by increasing the number of known glucose and ScGlk -regulated pathways and a new set of putative regulatory proteins possibly involved or controlling the CCR.

Twitter Demographics

The data shown below were collected from the profiles of 3 tweeters 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 47 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 47 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 10 21%
Researcher 10 21%
Student > Master 6 13%
Student > Bachelor 4 9%
Student > Doctoral Student 4 9%
Other 6 13%
Unknown 7 15%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 18 38%
Agricultural and Biological Sciences 10 21%
Immunology and Microbiology 2 4%
Chemical Engineering 2 4%
Nursing and Health Professions 1 2%
Other 4 9%
Unknown 10 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 29 April 2016.
All research outputs
#5,497,508
of 7,625,034 outputs
Outputs from BMC Microbiology
#817
of 1,286 outputs
Outputs of similar age
#171,556
of 266,764 outputs
Outputs of similar age from BMC Microbiology
#31
of 63 outputs
Altmetric has tracked 7,625,034 research outputs across all sources so far. This one is in the 24th percentile – i.e., 24% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,286 research outputs from this source. They receive a mean Attention Score of 3.0. This one is in the 31st percentile – i.e., 31% 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 266,764 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 29th percentile – i.e., 29% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 63 others from the same source and published within six weeks on either side of this one. This one is in the 36th percentile – i.e., 36% of its contemporaries scored the same or lower than it.