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While bacterial chromosomes were long thought to be amorphous, recentexperiments reveal pronounced organizational features. However, the extent ofbacterial chromosome organization remains unclear. Here, we develop a fullydata-driven maximum entropy approach to extract the distribution of single-cellchromosome conformations from experimental normalized Hi-C data. We apply thisinference to the model organism Caulobacter crescentus. On small genomic scalesof 104-105 basepairs, our model reveals a pattern of local chromosomeextensions that correlates with transcriptional and DNA loop extrusionactivity. On larger genomic scales, we find that chromosome structure ispredominantly present along the long cell axis: chromosomal loci not only havewell-defined axial positions, they also exhibit long-ranged correlations dueinteracting large emergent genomic clusters, termed Super Domains. Finally, ourmodel reveals information contained in chromosome structure that can guidecellular processes. Our approach can be generalized to other species, providinga principled way of analyzing spatial chromosome organization.

Resolving the degree of order in the bacterial chromosome using a statistical physics approach