Development of a Data-driven Integrative Model of Bacterial Chromosome

Abstract

The chromosome of archetypal bacteria E. coli is known for a complex topology with 4.6 x 106 base pairs (bp) long sequence of nucleotide packed within a micrometer-sized celllular confinement. The inherent organization underlying this chromosome eludes general consensus due to the lack of a high-resolution picture of its conformation. Here we present our development of an integrative model of E. coli at a 500 bp resolution (https://github.com/JMLab-tifrh/ecoli_finer), which optimally combines a set of multi-resolution genome-wide experimentally measured data within a framework of polymer based architecture. In particular the model is informed with intra-genome contact probability map at 5000 bp resolution derived via Hi-C experiment and RNA-sequencing data at 500 bp resolution. Via dynamical simulations, this data-driven polymer based model generates appropriate conformational ensemble commensurate with chromosome architectures that E. coli adopts. As a key hallmark, the model chromosome spontaneously self-organizes into a set of non-overlapping macrodomains and suitably locates plectonemic loops near the cell membrane. As novel extensions, it predicts a contact probability map simulated at a higher resolution than precedent experiments and can demonstrate segregation of chromosomes in a partially replicating cell. Finally, the modular nature of the model helps us to devise control simulations to quantify the individual role of key features in hierarchical organization of the bacterial chromosome.