Origin of the Clock in Neurospora crassa?

Jonathan Arnold^1*Ahmad Al-Omari²Cara Altimus³Sam Arsenault⁴Suchendra Bhandarkar¹Shishir Bhusal¹Christian Caranica⁵Jia Hwei Cheong¹Zhaojie Deng⁶Arthur S Edison¹Garrett Floyd¹James Griffith¹Brooke Hull⁷Michael T. Judge⁸Yang Liu⁹Leidong Mao¹Bijoy Mohanty¹Xiao Qiu¹⁰Heinz-Bernd Schuttler¹Ashley Scruse¹¹Thiab Taha¹Lingyun Wu¹²Yue Wu¹³

• ¹Genetics Department, University of Georgia, Athens, GA, United States
• ²Yarmouk University, Irbid, Jordan
• ³The Milken Institute, Washington, United States
• ⁴Harvard University, Cambridge, United States
• ⁵Northeastern University, Boston, United States
• ⁶RareCyte, Inc., Seattle, United States
• ⁷Princeton University, Princeton, United States
• ⁸National Institute of Standards and Technology Physical Measurement Laboratory, Gaithersburg, United States
• ⁹University of Georgia, Athens, United States
• ¹⁰Johnson & Johnson Innovation LLC, New Brunswick, United States
• ¹¹Morehouse College, Atlanta, United States
• ¹²Google LLC, Mountain View, United States
• ¹³Stanford University, Stanford, United States

We examine the collective behavior of single cells in microbial systems to provide insights onto the origin of the biological clock. Microfluidics has opened a window onto how single cells can synchronize their behavior. Four hypotheses are proposed to explain the origin of the clock from synchronized behavior of single cells. The four hypotheses depend on the presence or absence of a communication mechanism between the clocks in single cells and the presence or absence of a stochastic component in the clock mechanism. To test these models we integrate physical models for the behavior of the clocks in single cells or filaments with new approaches to measuring clocks in single cells. As an example, we provide evidence for a quorum sensing signal both with microfluidics experiments on single cells and with Continuous in vivo metabolism NMR (CIVM-NMR). We also provide evidence for the stochastic component in clocks of single cells. Throughout this work ensemble methods from statistical physics are used to characterize the clock both at the single cell level and the macroscopic scale of 106 cells.