Physical models of bacterial chromosomes

被引:3
|
作者
Harju, Janni [1 ]
Broedersz, Chase P. [1 ,2 ,3 ]
机构
[1] Vrije Univ Amsterdam, Dept Phys & Astron, NL-1081 HV Amsterdam, Netherlands
[2] Ludwig Maximilian Univ Munich, Arnold Sommerfeld Ctr Theoret Phys, Dept Phys, Munich, Germany
[3] Ludwig Maximilian Univ Munich, Ctr Nanosci, Munich, Germany
关键词
Bacterial chromosomes; Data-driven modeling; Loop extrusion; Maximum Entropy; HI-C; SPATIAL-ORGANIZATION; COLI CHROMOSOME; DNA; PARB; PROTEINS; SEGREGATION; SINGLE; GENOME; CONDENSIN;
D O I
10.1111/mmi.15257
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
The interplay between bacterial chromosome organization and functions such as transcription and replication can be studied in increasing detail using novel experimental techniques. Interpreting the resulting quantitative data, however, can be theoretically challenging. In this minireview, we discuss how connecting experimental observations to biophysical theory and modeling can give rise to new insights on bacterial chromosome organization. We consider three flavors of models of increasing complexity: simple polymer models that explore how physical constraints, such as confinement or plectoneme branching, can affect bacterial chromosome organization; bottom-up mechanistic models that connect these constraints to their underlying causes, for instance, chromosome compaction to macromolecular crowding, or supercoiling to transcription; and finally, data-driven methods for inferring interpretable and quantitative models directly from complex experimental data. Using recent examples, we discuss how biophysical models can both deepen our understanding of how bacterial chromosomes are structured and give rise to novel predictions about bacterial chromosome organization. Connecting experimental observations to biophysical models can give rise to new insights on bacterial chromosome organization. Simple polymer models explore how physical constraints affect bacterial chromosome organization; bottom-up mechanistic models connect these constraints to their underlying causes; and data-driven models are inferred directly from complex experimental data.image
引用
收藏
页码:143 / 153
页数:11
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