A convolutional autoencoder approach for mining features in cellular electron cryo-tomograms and weakly supervised coarse segmentation

Cellular electron cryo-tomography enables the 3D visualization of cellular organization in the near-native state and at submolecular resolution. However, the contents of cellular tomograms are often complex, making it difficult to automatically isolate different in situ cellular components. In this paper, we propose a convolutional autoencoder-based unsupervised approach to provide a coarse grouping of 3D small subvolumes extracted from tomograms. We demonstrate that the autoencoder can be used for efficient and coarse characterization of features of macromolecular complexes and surfaces, such as membranes. In addition, the autoencoder can be used to detect non-cellular features related to sample preparation and data collection, such as carbon edges from the grid and tomogram boundaries. The autoencoder is also able to detect patterns that may indicate spatial interactions between cellular components. Furthermore, we demonstrate that our autoencoder can be used for weakly supervised semantic segmentation of cellular components, requiring a very small amount of manual annotation.Comment: Accepted by Journal of Structural Biolog

Active Learning to Classify Macromolecular Structures in situ for Less Supervision in Cryo-Electron Tomography

Motivation: Cryo-Electron Tomography (cryo-ET) is a 3D bioimaging tool that visualizes the structural and spatial organization of macromolecules at a near-native state in single cells, which has broad applications in life science. However, the systematic structural recognition and recovery of macromolecules captured by cryo-ET are difficult due to high structural complexity and imaging limits. Deep learning based subtomogram classification have played critical roles for such tasks. As supervised approaches, however, their performance relies on sufficient and laborious annotation on a large training dataset. Results: To alleviate this major labeling burden, we proposed a Hybrid Active Learning (HAL) framework for querying subtomograms for labelling from a large unlabeled subtomogram pool. Firstly, HAL adopts uncertainty sampling to select the subtomograms that have the most uncertain predictions. Moreover, to mitigate the sampling bias caused by such strategy, a discriminator is introduced to judge if a certain subtomogram is labeled or unlabeled and subsequently the model queries the subtomogram that have higher probabilities to be unlabeled. Additionally, HAL introduces a subset sampling strategy to improve the diversity of the query set, so that the information overlap is decreased between the queried batches and the algorithmic efficiency is improved. Our experiments on subtomogram classification tasks using both simulated and real data demonstrate that we can achieve comparable testing performance (on average only 3% accuracy drop) by using less than 30% of the labeled subtomograms, which shows a very promising result for subtomogram classification task with limited labeling resources.Comment: Statement on authorship changes: Dr. Eric Xing was an academic advisor of Mr. Haohan Wang. Dr. Xing was not directly involved in this work and has no direct interaction or collaboration with any other authors on this work. Therefore, Dr. Xing is removed from the author list according to his request. Mr. Zhenxi Zhu's affiliation is updated to his current affiliatio

Structural insights into muscle organisation by electron cryo-tomography

Movement is the essence of life in the animal realm. Skeletal muscle is an essential tissue specialised for movement. Muscle cells are multi-nucleated cells containing bundles of myofibrils, which are segmented into the smallest contractile units, named sarcomeres. While sarcomeres are known to contain thin (actin) and thick (myosin) filaments, the detailed architecture, especially the high-resolution and 3-dimensional (3D) information, remains obscure. In this thesis, I obtained the first high-resolution 3D pictures of the sarcomere using cryo-focused ion beam milling (cryo-FIB-milling) and electron cryo-tomography (cryo-ET). The sarcomere organisation highlights a molecular plasticity which ensures efficient muscle contraction in different environments. Furthermore, from these native 3D images, I determined the first structures of the ruler protein, nebulin, to a resolution of 4.5 Å, which establishes the molecular basis for its functions in thin filament stabilisation, length control and myosin-binding regulation. The in situ structures also revealed a double-head conformation of myosin that reveals inherent variability to increases myosin’s capability for binding to the thin filaments. Collectively, my thesis research provides unique insights into muscle structures that allow improved dynamic modelling of muscle contraction and muscle diseases. This research also establishes a new cryo-FIB-ET approach for structurally characterising muscle components in different types of muscles and diseased states

Structural characterization of Ebola virus uncoating

Viruses initiate infection of host cells by entering through a variety of different pathways. Their entry is concluded by the release of the viral genome into the cytoplasm, where the cellular machinery gets repurposed for virus replication. Prerequisite for genome release is the uncoating of the viral particles, a process which requires the destabilization of interactions established during virus assembly. Ebola viruses (EBOVs) are highly pathogenic, enveloped RNA viruses of remarkable filamentous morphology. Their shape is dictated by the viral matrix protein VP40, which forms a tubular scaffold underneath the viral envelope and confers stability to the particles during EBOV transmission. EBOVs enter host cells via the endocytic pathway and release their genome into the cytoplasm after fusion of their envelope with the endosomal membrane. The first line of defence against a viral infection is blocking viral entry, and EBOV entry has accordingly been well investigated with respect to receptor engagement and potential membrane fusion triggers. However, key mechanisms governing the final step of virus entry are still unknown, including the central question of how these unusually shaped virions undergo uncoating. Whether and how the VP40 matrix disassembles to enable membrane fusion; whether uncoating involves additional triggers; and finally, how and where the viral genome gets released from the viral particles and nucleocapsids remains to be elucidated. In this thesis, I investigate EBOV uncoating during entry into host cells and shed light on the fate of the most abundant and versatile viral protein, VP40. As a main tool, I use in situ cryo-electron tomography and provide structural insights into EBOV uncoating both in vitro and in infected host cells at molecular resolution. I discover that at low endosomal pH, the VP40 matrix detaches from the viral envelope and disassembles. This is caused by the disruption of electrostatic interactions between membrane lipids and anionic amino acids exposed on the surface of VP40 dimers, which I show are the structural units of the VP40 matrix. The strong effect of low pH on the integrity of the VP40 matrix is a consequence of acidification of the viral lumen, which I further investigate to uncover its mechanism. I show that protons diffuse passively across the viral envelope independently of a dedicated ion channel, which might be relevant for other late-penetrating viruses lacking viroporins. Finally, I provide the first high-resolution images of Ebola virions in endolysosomal compartments of infected cells. These images confirm the disassembly of the VP40 matrix in virions located in acidified compartments while clearly showing that their nucleocapsids remain intact. Together, these findings reveal that VP40 matrix disassembly is an essential step during EBOV uncoating, which precedes membrane fusion and genome release from the nucleocapsids. Overall, this thesis extends the current understanding of virus uncoating and indicates that pH-driven structural remodeling of viral matrix proteins may act as a switch coupling matrix uncoating to membrane fusion during host cell entry of enveloped viruses

Removal of antagonistic spindle forces can rescue metaphase spindle length and reduce chromosome segregation defects

Regular Abstracts - Tuesday Poster Presentations: no. 1925Metaphase describes a phase of mitosis where chromosomes are attached and oriented on the bipolar spindle for subsequent segregation at anaphase. In diverse cell types, the metaphase spindle is maintained at a relatively constant length. Metaphase spindle length is proposed to be regulated by a balance of pushing and pulling forces generated by distinct sets of spindle microtubules and their interactions with motors and microtubule-associated proteins (MAPs). Spindle length appears important for chromosome segregation fidelity, as cells with shorter or longer than normal metaphase spindles, generated through deletion or inhibition of individual mitotic motors or MAPs, showed chromosome segregation defects. To test the force balance model of spindle length control and its effect on chromosome segregation, we applied fast microfluidic temperature-control with live-cell imaging to monitor the effect of switching off different combinations of antagonistic forces in the fission yeast metaphase spindle. We show that spindle midzone proteins kinesin-5 cut7p and microtubule bundler ase1p contribute to outward pushing forces, and spindle kinetochore proteins kinesin-8 klp5/6p and dam1p contribute to inward pulling forces. Removing these proteins individually led to aberrant metaphase spindle length and chromosome segregation defects. Removing these proteins in antagonistic combination rescued the defective spindle length and, in some combinations, also partially rescued chromosome segregation defects. Our results stress the importance of proper chromosome-to-microtubule attachment over spindle length regulation for proper chromosome segregation.postprin