Processing Oscillatory Signals by Incoherent Feedforward Loops.
From the timing of amoeba development to the maintenance of stem cell pluripotency, many biological signaling pathways exhibit the ability to differentiate between pulsatile and sustained signals in the regulation of downstream gene expression. While the networks underlying this signal decoding are...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Public Library of Science (PLoS)
2016-09-01
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| Series: | PLoS Computational Biology |
| Online Access: | http://europepmc.org/articles/PMC5021367?pdf=render |
| _version_ | 1818982775036837888 |
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| author | Carolyn Zhang Ryan Tsoi Feilun Wu Lingchong You |
| author_facet | Carolyn Zhang Ryan Tsoi Feilun Wu Lingchong You |
| author_sort | Carolyn Zhang |
| collection | DOAJ |
| description | From the timing of amoeba development to the maintenance of stem cell pluripotency, many biological signaling pathways exhibit the ability to differentiate between pulsatile and sustained signals in the regulation of downstream gene expression. While the networks underlying this signal decoding are diverse, many are built around a common motif, the incoherent feedforward loop (IFFL), where an input simultaneously activates an output and an inhibitor of the output. With appropriate parameters, this motif can exhibit temporal adaptation, where the system is desensitized to a sustained input. This property serves as the foundation for distinguishing input signals with varying temporal profiles. Here, we use quantitative modeling to examine another property of IFFLs-the ability to process oscillatory signals. Our results indicate that the system's ability to translate pulsatile dynamics is limited by two constraints. The kinetics of the IFFL components dictate the input range for which the network is able to decode pulsatile dynamics. In addition, a match between the network parameters and input signal characteristics is required for optimal "counting". We elucidate one potential mechanism by which information processing occurs in natural networks, and our work has implications in the design of synthetic gene circuits for this purpose. |
| first_indexed | 2024-12-20T17:52:34Z |
| format | Article |
| id | doaj.art-9e28a93b204f47bfa84ee8f3cec31ec6 |
| institution | Directory Open Access Journal |
| issn | 1553-734X 1553-7358 |
| language | English |
| last_indexed | 2024-12-20T17:52:34Z |
| publishDate | 2016-09-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS Computational Biology |
| spelling | doaj.art-9e28a93b204f47bfa84ee8f3cec31ec62022-12-21T19:30:50ZengPublic Library of Science (PLoS)PLoS Computational Biology1553-734X1553-73582016-09-01129e100510110.1371/journal.pcbi.1005101Processing Oscillatory Signals by Incoherent Feedforward Loops.Carolyn ZhangRyan TsoiFeilun WuLingchong YouFrom the timing of amoeba development to the maintenance of stem cell pluripotency, many biological signaling pathways exhibit the ability to differentiate between pulsatile and sustained signals in the regulation of downstream gene expression. While the networks underlying this signal decoding are diverse, many are built around a common motif, the incoherent feedforward loop (IFFL), where an input simultaneously activates an output and an inhibitor of the output. With appropriate parameters, this motif can exhibit temporal adaptation, where the system is desensitized to a sustained input. This property serves as the foundation for distinguishing input signals with varying temporal profiles. Here, we use quantitative modeling to examine another property of IFFLs-the ability to process oscillatory signals. Our results indicate that the system's ability to translate pulsatile dynamics is limited by two constraints. The kinetics of the IFFL components dictate the input range for which the network is able to decode pulsatile dynamics. In addition, a match between the network parameters and input signal characteristics is required for optimal "counting". We elucidate one potential mechanism by which information processing occurs in natural networks, and our work has implications in the design of synthetic gene circuits for this purpose.http://europepmc.org/articles/PMC5021367?pdf=render |
| spellingShingle | Carolyn Zhang Ryan Tsoi Feilun Wu Lingchong You Processing Oscillatory Signals by Incoherent Feedforward Loops. PLoS Computational Biology |
| title | Processing Oscillatory Signals by Incoherent Feedforward Loops. |
| title_full | Processing Oscillatory Signals by Incoherent Feedforward Loops. |
| title_fullStr | Processing Oscillatory Signals by Incoherent Feedforward Loops. |
| title_full_unstemmed | Processing Oscillatory Signals by Incoherent Feedforward Loops. |
| title_short | Processing Oscillatory Signals by Incoherent Feedforward Loops. |
| title_sort | processing oscillatory signals by incoherent feedforward loops |
| url | http://europepmc.org/articles/PMC5021367?pdf=render |
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