A self-organized geometry sensing oscillator spatially regulates cell division in archaea
Du, S.; Zheng, W.; Zhao, S.; Liu, Y.; Chen, Z.; Wu, J.; Zou, X.; Cui, J.; Chen, X.; Lutkenhaus, J.; Wu, F.
Show abstract
Cell division must be tightly regulate in time and space. Many bacteria and eukaryotes employ geometry sensing systems to regulate cell division spatiotemporally. However, how archaea ensure they divide in the right place at the right time is little understood. Here, we report the discovery of a geometry sensing oscillator that determines the division plane in the model haloarcheon Haloferax volcanii, which relies on two tubulin-like proteins, FtsZ1 and FtsZ2, for division. This archaeal oscillator (named as Arco system) is composed of three components, ArcoA, ArcoB and ArcoC, which are a membrane associated Ras superfamily GTPase, a SepF-like protein and an antagonist of FtsZ1, respectively. ArcoA interacts with both ArcoB and ArcoC. ArcoAB sense the geometry of the cell to oscillate between the two cell poles, generating a time-averaged ArcoC gradient which is high at the cell poles but low at the midcell, where FtsZs can assemble into the Z ring to initiate cytokinesis. As a result, deletion of the Arco system caused aberrant FtsZ assembly throughout the cell, leading to irregular division and formation of minicells. Interestingly, the Arco system is globally distributed among archaea and co-occurs with FtsZ1, suggesting that it emerged in the last archaeal common ancestor (LACA). The oscillatory behavior and phenotypes of the archaeal Arco system is remarkably analogous to the bacterial Min system and yet share no protein homology, representing a remarkable example of convergent evolution. Overall, these results suggest that archaea, similar to bacteria and eukaryotes, independently evolved self-organized Turing reaction diffusion systems to sense geometry and spatially regulate cell division.
Matching journals
The top 2 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Beyond bacterial paradigms: uncovering the functional significance and first biogenesis machinery of archaeal lipoproteins 98%
- Essential dynamic interdependence of FtsZ and SepF for Z-ring and septum formation in Corynebacterium glutamicum 97%
- Transient inhibition of cell division in competent pneumococcal cells results from deceleration of the septal peptidoglycan complex 97%
Similar papers in this journal
- PomX, a ParA/MinD ATPase activating protein, is a triple regulator of cell division in Myxococcus xanthus 97%
- Amoxicillin-resistant Streptococcus pneumoniae can be resensitized by targeting the mevalonate pathway as indicated by sCRilecs-seq 96%
- Staphylococcus aureus FtsZ and PBP4 bind to the conformationally dynamic N-terminal domain of GpsB 96%
Similar papers in this journal
- Spatio-temporal control of DNA replication by the pneumococcal cell cycle regulator CcrZ 98%
- Gamma-Mobile-Trio systems define a new class of mobile elements rich in bacterial defensive and offensive tools 96%
- E. coli FtsN coordinates synthesis and degradation of septal peptidoglycan by partitioning between a synthesis track and a denuded glycan track 96%
Similar papers in this journal
- Nucleoid Compaction Influences Carboxysome Localization and Dynamics in Synechococcus elongatus PCC 7942 97%
- Evidence for a widespread third system for bacterial polysaccharide export across the outer membrane comprising a composite OPX/β-barrel translocon 96%
- Identification of polyphosphate-binding proteins in E. coli uncovers targets involved in translation control and ribosome biogenesis 96%
Similar papers in this journal
- Versatile NTP recognition and domain fusions expand the functional repertoire of the ParB-CTPase fold beyond chromosome segregation 96%
- Structural modeling reveals the allosteric switch controlling the chitin utilization program of Vibrio cholerae 96%
- Halofilins as Emerging Bactofilin Families of Archaeal Cell Shape Plasticity Orchestrators 96%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.