Plenary Lecture 12: The causes and consequences of metabolic specialization
32 mins 52 secs,
60.13 MB,
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Description: |
Johnson, D (ETH Zürich)
Friday 31 October 2014, 11:55-12:30 |
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Created: | 2014-11-05 11:17 |
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Collection: | Understanding Microbial Communities; Function, Structure and Dynamics |
Publisher: | Isaac Newton Institute |
Copyright: | Johnson, D |
Language: | eng (English) |
Distribution: | World (downloadable) |
Explicit content: | No |
Aspect Ratio: | 16:9 |
Screencast: | No |
Bumper: | UCS Default |
Trailer: | UCS Default |
Abstract: | Co-authors: Elin E Lilja (ETH Zürich and Eawag), Felix Goldschmidt (ETH Zürich and Eawag), Martin Ackermann (ETH Zürich and Eawag)
Consider a microbial cell residing within a lake, soil, or the human gut. This cell encounters a myriad of different substrates that could theoretically satisfy its growth requirements. Yet, even if this cell were near starvation, it would only consume a subset of the available substrates. Why is this? What is the advantage of consuming only a subset of the available substrates rather than all of them? We hypothesize that particular metabolic processes are in biochemical conflict with each other, thus causing those processes to be more effectively performed by different strains than by the same strain. A biochemical conflict could occur, for example, if different metabolic processes compete for the same pool of limiting intracellular resources or if different metabolic processes produce products that inhibit other metabolic processes. In this talk, I first present a general theoretical model that uses information about biochemical conflicts to predict whether any two metaboli c processes will be retained by a single metabolic generalist strain or will segregate into different metabolic specialist strains over evolutionary time. I next present empirical evidence of specific environmental conditions when consortia of metabolically specialized strains consume substrates more rapidly than a single metabolic generalist strain. Our findings are potentially relevant for any pair of metabolic processes and could therefore be useful for predicting how best to distribute different metabolic processes among different cells in order to maximize the conversion of a substrate into a desired product. |
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