Research
The Biological Complexity Unit studies how stochastic fluctuations influence the dynamics of biological systems, and the strategies implemented by biological systems to cope with these fluctuations. We study these phenomena by means of theoretical methods and computational approaches from non-equilibrium statistical physics.
Information processing in cells
Biological functions at the sub-cellular level are often performed with remarkable accuracy and speed, despite the presence of thermal fluctuations. We study how macromolecules replicating biological information, such as replisomes and ribosomes, can achieve such high performance. We recently developed a method to infer the detailed dynamics of bacterial replisomes by combining theory and deep sequencing experiments.
Selected recent publications
- F. Pflug, D. Bhat, S. Pigolotti, "Genome replication in asynchronously growing microbial populations", PLOS Computational Biology 20(1), e1011753 (2024).
- D. Bhat, S. Hauf, C. Plessy, S. Pigolotti, "Speed variations of bacterial replisomes", Elife 11:e75884 (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).
- D. Chiuchiù, Y. Tu, S. Pigolotti, "Error-speed correlations in biopolymer synthesis", Phys. Rev. Lett. 123, 038101, arXiv:1905.12869 (2019).
- M. Cencini, S. Pigolotti, "Energetic funnel facilitates facilitated diffusion", Nucleic Acid Research 46(2), 558-567 (2018).
- P. Sartori and S. Pigolotti. “Thermodynamics of error correction”. Phys. Rev. X, 5:041039, (2015).
- P. Sartori and S. Pigolotti. "Kinetic vs. energetic discrimination in biological copying". Phys. Rev. Lett., 110:188101, (2013).
Population dynamics
Ecosystems display a remarkable degree of spatial organization. We are interested in predicting biodiversity patterns in spatially structured ecosystems. Examples range from bacteria competing in microchannels to planktonic communities in marine ecosystems. We are also exploring how ecological and evolutionary mechanisms, such as the possibility of adopting a "bet-hedging" strategy in a fluctuating environment, are affected by spatially-structured environments.
Selected recent publications
- A. Koldaeva, H. Tsai, A.Q. Shen, S. Pigolotti, "Population genetics in microchannels", Proc. Natl. Acad. Sci. 119 (12) e2120821119 (2022).
- P.V Martín, A. Bucek, T. Bourguignon, S. Pigolotti, "Ocean currents promote rare species diversity in protists", Science Advances 6(29), eaaz9037 (2020).
- P.V. Martín, M.A. Muñoz, S. Pigolotti, "Bet-hedging strategies in expanding populations", Plos. Comp. Biol. 15(4), e100652, (2019).
- S. Pigolotti and R. Benzi. "Selective advantage of diffusing faster". Phys. Rev. Lett., 112:188102, (2014).
- S. Pigolotti, R. Benzi, M. H. Jensen, and D. R. Nelson. "Population genetics in compressible flows". Phys. Rev. Lett., 108:128102, (2012).
Non-equilibrium thermodynamics
Stochastic thermodynamics studies non-equilibrium properties of mesoscopic physical systems. Fluctuation relations are fundamental results in stochastic thermodynamics. They govern non-equilibrium behavior of a vast class of systems and find application in experimentally measuring free energy differences by means of non-equilibrium manipulation protocols. In recent years, we have been discovering several additional universal properties of mesoscopic systems. We are interested in characterizing these novel properties and organize them into a unified theory.
Selected recent publications
- L. Peliti and S. Pigolotti, "Stochastic Thermodynamics: An Introduction", Princeton University Press (2021).
- D. Chiuchiù, S. Pigolotti, "Mapping of uncertainty relations between continuous and discrete time", Phys. Rev. E 97, 032110, arXiv:1711.00615 (2018).
- A.C. Barato, É. Roldán, I.A. Martínez, S. Pigolotti, "Arcsine laws in stochastic thermodynamics", Phys. Rev. Lett. 121, 090601, arXiv/1712.00795 (2018).
- S. Pigolotti, I. Neri, É. Roldán, F. Jülicher, "Generic Properties of Stochastic Entropy Production". Phys. Rev. Lett. 119, 140604 (2017).