Development of a Data-Driven Integrative Model of a Bacterial Chromosome

The chromosome of archetypal bacteria E. coli is known for a complex topology with a 4.6 x 106 base pairs (bp) long sequence of nucleotides packed within a micrometer-sized cellular 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 multiresolution genome-wide experimentally measured data within a framework of polymer based architecture. In particular the model is informed with an intragenome contact probability map at 5000 bp resolution derived via the Hi-C experiment and RNA-sequencing data at 500 bp resolution. Via dynamical simulations, this data-driven polymer based model generates an appropriate conformational ensemble commensurate with chromosome architectures that E. coli adopts. As a key hallmark of the E. coli chromosome the model spontaneously self-organizes into a set of nonoverlapping 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 devise control simulations to quantify the individual role of key features in hierarchical organization of the bacterial chromosome.

Automated summary

We developed an integrative model of E. coli chromosome, which combines multiresolution genome-wide experimental data to describe its conformation. The model generates an appropriate ensemble of conformations and exhibits key features of the E. coli chromosome, such as nonoverlapping macrodomains and plectonemic loops. It can predict a higher resolution contact probability map than previous experiments and demonstrate chromosome segregation in a partially replicating cell. The modular nature of the model allows us to quantify the individual role of key features in hierarchical organization of the bacterial chromosome.