4D epigenomics: deciphering the coupling between genome folding and epigenomic regulation with biophysical modeling.

Recent experimental observations suggest a strong coupling between the 3D nuclear chromosome organization and epigenomics. However, the mechanistic and functional bases of such interplay remain elusive. In this review, we describe how biophysical modeling has been instrumental in characterizing how genome folding may impact the formation of epigenomic domains and, conversely, how epigenomic marks may affect chromosome conformation. Finally, we discuss how this mutual feedback loop between chromatin organization and epigenome regulation, via the formation of physicochemical nanoreactors, may represent a key functional role of 3D compartmentalization in the assembly and maintenance of stable - but yet plastic - epigenomic landscapes.

Painters in chromatin: a unified quantitative framework to systematically characterize epigenome regulation and memory.

In eukaryotes, many stable and heritable phenotypes arise from the same DNA sequence, owing to epigenetic regulatory mechanisms relying on the molecular cooperativity of 'reader-writer' enzymes. In this work, we focus on the fundamental, generic mechanisms behind the epigenome memory encoded by post-translational modifications of histone tails. Based on experimental knowledge, we introduce a unified modeling framework, the painter model, describing the mechanistic interplay between sequence-specific recruitment of chromatin regulators, chromatin-state-specific reader-writer processes and long-range spreading mechanisms. A systematic analysis of the model building blocks highlights the crucial impact of tridimensional chromatin organization and state-specific recruitment of enzymes on the stability of epigenomic domains and on gene expression. In particular, we show that enhanced 3D compaction of the genome and enzyme limitation facilitate the formation of ultra-stable, confined chromatin domains. The model also captures how chromatin state dynamics impact the intrinsic transcriptional properties of the region, slower kinetics leading to noisier expression. We finally apply our framework to analyze experimental data, from the propagation of γH2AX around DNA breaks in human cells to the maintenance of heterochromatin in fission yeast, illustrating how the painter model can be used to extract quantitative information on epigenomic molecular processes.

Active modulation of surfactant-driven flow instabilities by swarming bacteria.

Models based on surfactant-driven instabilities have been employed to describe pattern formation by swarming bacteria. However, by definition, such models cannot account for the effect of bacterial sensing and decision making. Here we present a more complete model for bacterial pattern formation which accounts for these effects by coupling active bacterial motility to the passive fluid dynamics. We experimentally identify behaviors which cannot be captured by previous models based on passive population dispersal and show that a more accurate description is provided by our model. It is seen that the coupling of bacterial motility to the fluid dynamics significantly alters the phase space of surfactant-driven pattern formation. We also show that our formalism is applicable across bacterial species.

Tuning the torque-speed characteristics of the bacterial flagellar motor to enhance swimming speed.

In a classic paper, Purcell [Proc. Natl. Acad. Sci. U. S. A. 94, 11307 (1997)10.1073/pnas.94.21.11307] analyzed the dynamics of flagellated bacterial swimmers and derived a geometrical relationship which maximizes the propulsion efficiency. Experimental measurements for wild-type bacterial species E. coli have revealed that they closely satisfy this geometric optimality. However, dependence of the flagellar motor speed on the load and more generally the role of the torque-speed characteristics of the flagellar motor are not considered in Purcell's original analysis. Here we derive a tuned condition representing a match between the flagella geometry and the torque-speed characteristics of the flagellar motor to maximize the bacterial swimming speed for a given load. This condition is independent of the geometric optimality condition derived by Purcell. Interestingly, this condition is not satisfied by wild-type E. coli which swims 2-3 times slower than the maximum possible speed given the amount of available motor torque. Finally, we present experimental data on swimming dynamics of a cargo laden bacterial system which follows our analytical model. Our analysis also reveals the existence of an anomalous propulsion regime where the swim speed increases with increasing load (drag).