RESUMO
Cellular cryo-electron tomography (cryo-ET) has emerged as a key method to unravel the spatial and structural complexity of cells in their near-native state at unprecedented molecular resolution. To enable quantitative analysis of the complex shapes and morphologies of lipid membranes, the noisy three-dimensional (3D) volumes must be segmented. Despite recent advances, this task often requires considerable user intervention to curate the resulting segmentations. Here, we present ColabSeg, a Python-based tool for processing, visualizing, editing, and fitting membrane segmentations from cryo-ET data for downstream analysis. ColabSeg makes many well-established algorithms for point-cloud processing easily available to the broad community of structural biologists for applications in cryo-ET through its graphical user interface (GUI). We demonstrate the usefulness of the tool with a range of use cases and biological examples. Finally, for a large Mycoplasma pneumoniae dataset of 50 tomograms, we show how ColabSeg enables high-throughput membrane segmentation, which can be used as valuable training data for fully automated convolutional neural network (CNN)-based segmentation.
Assuntos
Algoritmos , Microscopia Crioeletrônica , Tomografia com Microscopia Eletrônica , Software , Microscopia Crioeletrônica/métodos , Tomografia com Microscopia Eletrônica/métodos , Processamento de Imagem Assistida por Computador/métodos , Redes Neurais de Computação , Membrana Celular/ultraestrutura , Mycoplasma pneumoniae/ultraestrutura , Interface Usuário-Computador , Imageamento Tridimensional/métodosRESUMO
Lassa virus is a negative-strand RNA virus with only four structural proteins that causes periodic outbreaks in West Africa. The nucleoprotein (NP) encapsidates the viral genome, forming ribonucleoprotein complexes (RNPs) together with the viral RNA and the L protein. RNPs must be continuously restructured during viral genome replication and transcription. The Z protein is important for membrane recruitment of RNPs, viral particle assembly, and budding and has also been shown to interact with the L protein. However, the interaction of NP, viral RNA, and Z is poorly understood. Here, we characterize the interactions between Lassa virus NP, Z, and RNA using structural mass spectrometry. We identify the presence of RNA as the driver for the disassembly of ring-like NP trimers, a storage form, into monomers to subsequently form higher order RNA-bound NP assemblies. We locate the interaction site of Z and NP and demonstrate that while NP binds Z independently of the presence of RNA, this interaction is pH-dependent. These data improve our understanding of RNP assembly, recruitment, and release in Lassa virus.
Assuntos
Vírus Lassa , Ribonucleoproteínas , Vírus Lassa/genética , Vírus Lassa/metabolismo , Ribonucleoproteínas/química , Nucleoproteínas , Montagem de Vírus , RNA Viral/genética , RNA Viral/metabolismoRESUMO
The detection of specific biological macromolecules in cryogenic electron tomography data is frequently approached by applying cross-correlation-based 3D template matching. To reduce computational cost and noise, high binning is used to aggregate voxels before template matching. This remains a prevalent practice in both practical applications and methods development. Here, the relation between template size, shape and angular sampling is systematically evaluated to identify ribosomes in a ground-truth annotated data set. It is shown that at the commonly used binning, a detailed subtomogram average, a sphere and a heart emoji result in near-identical performance. These findings indicate that with current template-matching practices macromolecules can only be detected with high precision if their shape and size are sufficiently different from the background. Using theoretical considerations, the experimental results are rationalized and it is discussed why primarily low-frequency information remains at high binning and that template matching fails to be accurate because similarly shaped and sized macromolecules have similar low-frequency spectra. These challenges are discussed and potential enhancements for future template-matching methodologies are proposed.