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Architecture and genomic arrangement of the MurE-MurF bacterial cell wall biosynthesis complex.

Karina T ShirakawaFernanda Angélica SalaMayara M MiyachiroViviana JobDaniel Maragno TrindadeAndréa Dessen
Published in: Proceedings of the National Academy of Sciences of the United States of America (2023)
Peptidoglycan (PG) is a central component of the bacterial cell wall, and the disruption of its biosynthetic pathway has been a successful antibacterial strategy for decades. PG biosynthesis is initiated in the cytoplasm through sequential reactions catalyzed by Mur enzymes that have been suggested to associate into a multimembered complex. This idea is supported by the observation that in many eubacteria, mur genes are present in a single operon within the well conserved dcw cluster, and in some cases, pairs of mur genes are fused to encode a single, chimeric polypeptide. We performed a vast genomic analysis using >140 bacterial genomes and mapped Mur chimeras in numerous phyla, with Proteobacteria carrying the highest number. MurE-MurF, the most prevalent chimera, exists in forms that are either directly associated or separated by a linker. The crystal structure of the MurE-MurF chimera from Bordetella pertussis reveals a head-to-tail, elongated architecture supported by an interconnecting hydrophobic patch that stabilizes the positions of the two proteins. Fluorescence polarization assays reveal that MurE-MurF interacts with other Mur ligases via its central domains with K D s in the high nanomolar range, backing the existence of a Mur complex in the cytoplasm. These data support the idea of stronger evolutionary constraints on gene order when encoded proteins are intended for association, establish a link between Mur ligase interaction, complex assembly and genome evolution, and shed light on regulatory mechanisms of protein expression and stability in pathways of critical importance for bacterial survival.
Keyphrases
  • cell wall
  • genome wide
  • copy number
  • genome wide identification
  • transcription factor
  • big data
  • electronic health record
  • stem cells
  • high throughput
  • gene expression
  • bone marrow
  • single molecule
  • machine learning