Seeing gene expression in cells: the future of structural biology.
Wei DaiSeth A DarstChristine M DunhamRobert LandickGregory A PetskoAlbert WeixlbaumerPublished in: Faculty reviews (2021)
Although much is known about the machinery that executes fundamental processes of gene expression in cells, much also remains to be learned about how that machinery works. A recent paper by O'Reilly et al. reports a major step forward in the direct visualization of central dogma processes at submolecular resolution inside bacterial cells frozen in a native state. The essential methodologies involved are cross-linking mass spectrometry (CLMS) and cryo-electron tomography (cryo-ET). In-cell CLMS provides in vivo protein interaction maps. Cryo-ET allows visualization of macromolecular complexes in their native environment. These methods have been integrated by O'Reilly et al. to describe a dynamic assembly in situ between a transcribing RNA polymerase (RNAP) and a translating ribosome - a complex known as the expressome - in the model bacterium Mycoplasma pneumoniae 1 . With the application of improved data processing and classification capabilities, this approach has allowed unprecedented insights into the architecture of this molecular assembly line, confirming the existence of a physical link between RNAP and the ribosome and identifying the transcription factor NusA as the linking molecule, as well as making it possible to see the structural effects of drugs that inhibit either transcription or translation. The work provides a glimpse into the future of integrative structural cell biology and can serve as a roadmap for the study of other molecular machineries in their native context.
Keyphrases
- gene expression
- induced apoptosis
- electron microscopy
- transcription factor
- cell cycle arrest
- high resolution
- dna methylation
- single cell
- machine learning
- signaling pathway
- deep learning
- cell death
- oxidative stress
- physical activity
- mental health
- current status
- amino acid
- dna binding
- gas chromatography
- artificial intelligence
- ms ms
- tandem mass spectrometry