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Systems and Photosystems: Cellular Limits of Autotrophic Productivity in Cyanobacteria

Overview of attention for article published in Frontiers in Bioengineering and Biotechnology, January 2015
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Title
Systems and Photosystems: Cellular Limits of Autotrophic Productivity in Cyanobacteria
Published in
Frontiers in Bioengineering and Biotechnology, January 2015
DOI 10.3389/fbioe.2015.00001
Pubmed ID
Authors

Robert L. Burnap

Abstract

Recent advances in the modeling of microbial growth and metabolism have shown that growth rate critically depends upon the optimal allocation of finite proteomic resources among different cellular functions and that modeling growth rates becomes more realistic with the explicit accounting for the costs of macromolecular synthesis, most importantly, protein expression. The "proteomic constraint" is considered together with its application to understanding photosynthetic microbial growth. The central hypothesis is that physical limits of cellular space (and corresponding solvation capacity) in conjunction with cell surface-to-volume ratios represent the underlying constraints on the maximal rate of autotrophic microbial growth. The limitation of cellular space thus constrains the size the total complement of macromolecules, dissolved ions, and metabolites. To a first approximation, the upper limit in the cellular amount of the total proteome is bounded this space limit. This predicts that adaptation to osmotic stress will result in lower maximal growth rates due to decreased cellular concentrations of core metabolic proteins necessary for cell growth owing the accumulation of compatible osmolytes, as surmised previously. The finite capacity of membrane and cytoplasmic space also leads to the hypothesis that the species-specific differences in maximal growth rates likely reflect differences in the allocation of space to niche-specific proteins with the corresponding diminution of space devoted to other functions including proteins of core autotrophic metabolism, which drive cell reproduction. An optimization model for autotrophic microbial growth, the autotrophic replicator model, was developed based upon previous work investigating heterotrophic growth. The present model describes autotrophic growth in terms of the allocation protein resources among core functional groups including the photosynthetic electron transport chain, light-harvesting antennae, and the ribosome groups.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 126 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 2 2%
Netherlands 2 2%
Sweden 1 <1%
Unknown 121 96%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 31 25%
Researcher 19 15%
Student > Master 17 13%
Student > Doctoral Student 9 7%
Student > Bachelor 9 7%
Other 24 19%
Unknown 17 13%
Readers by discipline Count As %
Agricultural and Biological Sciences 37 29%
Biochemistry, Genetics and Molecular Biology 26 21%
Environmental Science 10 8%
Engineering 9 7%
Earth and Planetary Sciences 6 5%
Other 11 9%
Unknown 27 21%
Attention Score in Context

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 06 February 2015.
All research outputs
#17,737,508
of 22,778,347 outputs
Outputs from Frontiers in Bioengineering and Biotechnology
#2,883
of 6,524 outputs
Outputs of similar age
#241,803
of 352,028 outputs
Outputs of similar age from Frontiers in Bioengineering and Biotechnology
#33
of 47 outputs
Altmetric has tracked 22,778,347 research outputs across all sources so far. This one is in the 19th percentile – i.e., 19% of other outputs scored the same or lower than it.
So far Altmetric has tracked 6,524 research outputs from this source. They receive a mean Attention Score of 3.4. This one is in the 48th percentile – i.e., 48% 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 352,028 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 27th percentile – i.e., 27% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 47 others from the same source and published within six weeks on either side of this one. This one is in the 25th percentile – i.e., 25% of its contemporaries scored the same or lower than it.