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Martinez-Corral, R.* ; Raimundez-Alvarez, E. ; Lin, Y.* ; Elowitz, M.B.* ; Garcia-Ojalvo, J.*

Self-amplifying pulsatile protein dynamics without positive feedback.

Cell Syst. 7, 453-462 (2018)
Verlagsversion DOI PMC
Free by publisher
Open Access Green möglich sobald Postprint bei der ZB eingereicht worden ist.
Many proteins exhibit dynamic activation patterns in the form of irregular pulses. Such behavior is typically attributed to a combination of positive and negative feedback loops in the underlying regulatory network. However, the presence of positive feedbacks is difficult to demonstrate unequivocally, raising the question of whether stochastic pulses can arise from negative feedback only. Here, we use the protein kinase A (PKA) system, a key regulator of the yeast pulsatile transcription factor Msn2, as a case example to show that irregular pulses of protein activity can arise from a negative feedback loop alone. Simplification to two variables reveals that a combination of zero-order ultrasensitivity, timescale separation between the activator and the repressor, and an effective delay in the feedback are sufficient to amplify a perturbation into a pulse. The same circuit topology can account for both activation and inactivation pulses, pointing toward a general mechanism of stochastic pulse generation.
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Publikationstyp Artikel: Journalartikel
Dokumenttyp Wissenschaftlicher Artikel
Korrespondenzautor
Schlagwörter Biological Noise ; Cell Signaling Dynamics ; Cellular Oscillations ; Feedback ; Protein Activation ; Protein Activity Pulses ; Ultrasensitivity; Yeast Transcription Factor; Saccharomyces-cerevisiae; Kinase-a; Nuclear-localization; Regulatory Subunit; Gene-regulation; Factor Msn2; Nucleocytoplasmic Oscillations; Bacillus-subtilis; Stress-response
ISSN (print) / ISBN 2405-4712
e-ISSN 2405-4720
Zeitschrift Cell Systems
Quellenangaben Band: 7, Heft: 4, Seiten: 453-462 Artikelnummer: , Supplement: ,
Verlag Elsevier
Verlagsort Maryland Heights, MO
Nichtpatentliteratur Publikationen
Institut(e) Institute of Computational Biology (ICB)