Chapter title |
Noise in Biological Systems: Pros, Cons, and Mechanisms of Control
|
---|---|
Chapter number | 23 |
Book title |
Yeast Systems Biology
|
Published in |
Methods in molecular biology, January 2011
|
DOI | 10.1007/978-1-61779-173-4_23 |
Pubmed ID | |
Book ISBNs |
978-1-61779-172-7, 978-1-61779-173-4
|
Authors |
Yitzhak Pilpel |
Abstract |
Genetic regulatory circuits are often regarded as precise machines that accurately determine the level of expression of each protein. Most experimental technologies used to measure gene expression levels are incapable of testing and challenging this notion, as they often measure levels averaged over entire populations of cells. Yet, when expression levels are measured at the single cell level of even genetically identical cells, substantial cell-to-cell variation (or "noise") may be observed. Sometimes different genes in a given genome may display different levels of noise; even the same gene, expressed under different environmental conditions, may display greater cell-to-cell variability in specific conditions and more tight control in other situations. While at first glance noise may seem to be an undesired property of biological networks, it might be beneficial in some cases. For instance, noise will increase functional heterogeneity in a population of microorganisms facing variable, often unpredictable, environmental changes, increasing the probability that some cells may survive the stress. In that respect, we can speculate that the population is implementing a risk distribution strategy, long before genetic heterogeneity could be acquired. Organisms may have evolved to regulate not only the averaged gene expression levels but also the extent of allowed deviations from such an average, setting it at the desired level for every gene under each specific condition. Here we review the evolving understanding of noise, its molecular underpinnings, and its effect on phenotype and fitness--when it can be detrimental, beneficial, or neutral and which regulatory tools eukaryotic cells may use to optimally control it. |
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Geographical breakdown
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United Kingdom | 2 | 4% |
United States | 1 | 2% |
Italy | 1 | 2% |
Switzerland | 1 | 2% |
Unknown | 45 | 90% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 22 | 44% |
Researcher | 7 | 14% |
Student > Master | 6 | 12% |
Professor > Associate Professor | 5 | 10% |
Student > Bachelor | 2 | 4% |
Other | 3 | 6% |
Unknown | 5 | 10% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 17 | 34% |
Biochemistry, Genetics and Molecular Biology | 13 | 26% |
Engineering | 6 | 12% |
Computer Science | 2 | 4% |
Physics and Astronomy | 2 | 4% |
Other | 6 | 12% |
Unknown | 4 | 8% |