FY2021 Annual Report

Biological Complexity Unit
Associate Professor Simone Pigolotti

BCU in April 2022. From left to right: Shrabani Mondal, Kaori Yamashiro, Anzhelika Koldaeva, Qiao Lu, Samuel Cure, Simone Pigolotti, Deepak Bhat, Florian Pflug, Ryo Nakatani, Robert Ross.

Abstract

The Biological Complexity Unit at OIST studies biological and biophysical systems that evolve stochastically. FY2020 has been the fourth year of activity of our Unit, that has been growing in size and productivity. Our main research lines in biophysics are the understanding of non-equilibrium mechanism of error correction in biology and modeling extended microbial populations at individual-based level. A third research line is in statistical physics and in particular in stochastic thermodynamics.

1. Staff

Prof. Simone Pigolotti, Associate Professor
Dr. Robert Ross, OIST Interdisciplinary Postdoctoral Fellow
Dr. Deepak Bhat, Postdoctoral Scholar
Dr. Shrabani Mondal, Postdoctoral Scholar
Dr. Florian Pflug, Postdoctoral Scholar
Ms. Anzhelika Koldaeva, PhD Student
Mr. Qiao Lu, PhD Student
Mr. Samuel Cyrus Cure, PhD Student
Ms. Kaori Yamashiro, Research Unit Administrator

2. Collaborations

2.1 Bacterial growth in microchannels

Description: We are collaborating with the Micro/Bio/Nanofluidics Unit at OIST to understand bacterial growth in microchannel from a theoretical and experimental perspective.
Type of collaboration: Joint research
Researchers:
- Prof. Amy Shen (OIST)
- Dr. Hsie-Fu Tsai (OIST)

2.2 Speed variations of bacterial replisomes

Description: We have collaborated with the Nucleic Acid Chemistry and Engineering Unit at OIST to understand the dynamics of bacterial replisomes theoretical and experimental perspective.
Type of collaboration: Joint research
Researchers:
- Prof. Yohei Yokobayashi (OIST)
- Dr. Samuel Hauf (OIST)
- Dr. Charles Plessy (OIST)

2.3 Cellular energetics

Description: We are continuing an internationa collaboration to understand the energy consumption and dissipation of cells using non-equilibrium thermodynamics.
Type of collaboration: Joint research
Researchers:
- Prof. Matthias Heinemann (University of Groningen, Netherlands)
- Dr. Pablo Sartori (Gulbekian Institute, Lisbon, Portugal)
- Dr. Jonathan Rodenfels (MPI-CBG, Dresden, Germany).

3. Activities and Findings

3.1 Population genetics in microchannels

Population genetics of well-mixed microorganisms is well understood. Much less is known about population genetics of microorganisms in confined space. In this project, we proposed a model for bacterial competition in microchannels where reproducing cells push entire lanes of cells, leading to expulsions of other bacteria from the channel. Our theory predict that the outcome of this dynamics is a fast diversity loss in the direction of the channel and a much slower loss in the ortogonal direction. Experiments from our collaborators in the Micro/Bio/Nanofluidics Unit at OIST confirm this prediction (see Fig. 1). Our results illustrate a fundamental mechanism underlying biological competition in confined structures (A. Koldaeva, H. Tsai, A.Q. Shen, S. Pigolotti, "Population genetics in microchannels", Proc. Natl. Acad. Sci. 119 (12) e2120821119 , 2022)

Figure 1: Snapshot of two different strains of bacteria (different colors) competing in microchannels of different widths and forming stripes.

3.2 Search and localization dynamics of the CRISPR/Cas9 system

Important proteins need to find specific locations on the DNA to perform their biological function. In this project, we considered a model of DNA sliding and detaching of Cas9, a central protein of the CRISPR/Cas9 system. The model, fitted to experimental data (See Figure 3), supports that Cas9 slides, but with a short sliding length. We then studied the search problem on a long DNA containing a large number of targets. We found that this problem can be analyzed by applying the theory of Anderson localization. Our results rationalize recent experimental results and provide a fresh viewpoint on the problem of DNA target search (Q. Lu, D. Bhat, D. Stepanenko, S. Pigolotti, "Search and localization dynamics of the CRISPR/Cas9 system", Phys. Rev. Lett. 127, 208102, arXiv/2103.10667 , Featured in Physics, 2021).

Figure 2: (a) Model of Cas9 sliding and detaching, (b) fit of detachment rate (lines) to single molecule data (points).

3.3 Generalized Euler-Lotka equation

The cell division time of growing unicellular organisms displays significant fluctuation, even for genetically identical individuals. The distribution of cell division time is related with the fitness by the so-called Euler-Lotka equation. A crucial assumption of the Euler-Lotka equation is that the reproduction times of different cells are statistically independent. Recent experiments have proven that, in most bacterial colonies, this is not the case. We rigorously proved a generalization of the Euler-Lotka equation which remains valid for correlated cell divisions. By applying the result to experimental data (see figure 3), we found that these correlations have a large enough effect to be appreciable in experiments (S. Pigolotti, "Generalized Euler-Lotka equation for correlated cell divisions" , Phys. Rev. E (Letter) 103, L060402 (Editors' Suggestion), arXiv/2101.02403 , 2021).

Figure 3: Generalized Euler-Lotka equation. (a) Genealogic trees at fixed time and fixed number of divisions (b) Predicted growth rate from experimental deta from the Euler-Lotka (EL) and generalized Euler-Lotka (GEL) equations.

3.4 Stochastic Thermodynamics: An Introduction

Our introductory book on Stochastic Thermodynamics was published during this fiscal year. It provides a pedagogical introduction to this field (L. Peliti, S. Pigolotti, "Stochastic Thermodynamics: An Introduction". Princeton University Press, 2021)

Figure 4: Cover of book "Stochastic thermodynamics. An introduction".

4. Publications

4.1 Journals

A. Koldaeva, H. Tsai, A.Q. Shen, S. Pigolotti, "Population genetics in microchannels", Proc. Natl. Acad. Sci. 119 (12) e2120821119 (2022).
Q. Lu, D. Bhat, D. Stepanenko, S. Pigolotti, "Search and localization dynamics of the CRISPR/Cas9 system", Phys. Rev. Lett. 127, 208102, arXiv/2103.10667 , Featured in Physics, (2021).
J.M. Miotto, S. Pigolotti, A.V. Chechkin, S. Roldán-Vargas, "Length scales in Brownian yet non-Gaussian dynamics", Phys. Rev. X 11, 031002 , arXiv/1991.07761, (2021).
S. Pigolotti, "Generalized Euler-Lotka equation for correlated cell divisions" , Phys. Rev. E (Letter) 103, L060402 (Editors' Suggestion), arXiv/2101.02403 (2021).
Y. Kinjo, N. Lo, P. V. Martín, G. Tokuda, S. Pigolotti, T. Bourguignon, "Enhanced Mutation Rate, Relaxed Selection, and the “Domino Effect” are associated with Gene Loss in Blattabacterium, A Cockroach Endosymbiont", Molecular Biology and Evolution, msab159, (2021).
X. Yang, M. Heinemann, J. Howard, G. Huber, S. Iyer-Biswas, G. Le Treut, M. Lynch, K. L. Montooth, D. J. Needleman, S. Pigolotti, J. Rodenfels, P. Ronceray, S. Shankar, I. Tavassoly, S. Thutupalli, D. V. Titov, J. Wang, and P. J. Foster, "Physical bioenergetics: Energy fluxes, budgets, and constraints in cells". Proc. Natl. Acad. Sci. (Perspective), 118 (26) (2021).

4.2 Books and other one-time publications

L. Peliti, S. Pigolotti, "Stochastic Thermodynamics: An Introduction". Princeton University Press, (2021)

4.3 Oral and Poster Presentations

Pigolotti S., “Information processing in cells: from CRISPR to replisomes”, invited seminar, hybrid workshop “Frontiers in Theoretical Biophysics”, APCTP (South Korea), 17 November 2021.
Pigolotti S.. “Dynamics of Bacterial replisomes”, American Physical Society (APS) March Meeting, 15 March 2022.
Koldaeva, A., “Population genetics in microchannels”, American Physical Society (APS) March Meeting, 16 March 2022.
Lu Q., “Search and Localization Dynamics of the CRISPR-Cas9 System”, American Physical Society (APS) March Meeting, 16 March 2022.
Mondal, S., “Optimality in biological proofreading”, American Physical Society (APS) March Meeting, Invited Focus Session Speaker, 18 March 2022.