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Intracellular Nanovesicles: their formation, transport and cargo

Lead Research Organisation: University of Warwick
Department Name: Warwick Medical School

Abstract

Humans are built from lots of cells. Rather than being boring building blocks, the interior of each cell is a busy world where proteins are made and go to work, constantly moving around. This allows each cell to eat, drink, reproduce, and much more. We are interested in the cell's membrane trafficking system: a transport network of different types of membrane vesicles that important proteins can travel in. Membrane trafficking ensures that cargo proteins go to the right place at the right time. This keeps cells functioning healthily and normally. We recently found a new type of vesicle and we now want to understand it in more detail. These vesicles are called intracellular nanovesicles, or INVs for short. In cells, when a vesicle is formed, it gathers the proteins that it will take and buds from its origin. It must then be transported to its destination where it fuses with the target membrane. You can think of this as the vesicle's life cycle: they are born, they travel and then they die when they deliver their important cargo. In this project we want to document the life story of INVs. We will focus on their "early years". How are they born? How do they travel? Which friends do they carry along the way? Very little is known about INVs because they were only recently discovered. The details of the life story of INVs is likely to change how cell biologists think about the membrane traffic system.

Technical Summary

Membrane trafficking is crucial to eukaryotic life. The membrane traffic system is a network of vesicles that ensures proteins are moved to the right place at the right time. This process controls many important cellular functions, for example, cell signalling or motility. We have recently found a new class of transport vesicle, termed intracellular nanovesicles (INVs). These small vesicles are widespread in the membrane trafficking system and play a role in anterograde traffic, Golgi integrity and recycling of endocytosed material. Due to their recent discovery, there is a lot to learn about these vesicles. For example, how do they form? How are they transported? What cargos do they carry? We will answer these questions in this project using a combination of state-of-the-art imaging methods (super-resolution microscopy and electron microscopy), genetically encoded probes and proteomics. Understanding INVs in more detail is therefore likely to have wide impact in the membrane trafficking field and on cell biology in general.

Planned Impact

The Pathways to Impact document sets out our five directions to maximise the impact of our discoveries. These are: 1) public presentations - publications, talks, and seminars; 2) interactions with the general public - lab tours and outreach events; 3) online promotion - web-based promotion of results; 4) press releases - engaging the press office to publicise our discoveries; and 5) sharing resources - plasmids and code.
We have three specific objectives. 1) To generate 3D models relevant to our work for a hands-on outreach experience. 2) Make a video abstract for each of the papers from this project, to publicise our work online. 3) To discuss dissemination of our work with the press team. A timeline is included to describe our impact plan throughout the project.
 
Description We analysed how small vesicles are transported in cells. In contrast to large vesicles and organelles, which move using motors inside cells, our analysis revealed that passive diffusion is the main mode of small vesicle transport.

Inside cells, molecules are moved in tiny transport packets called vesicles. Large vesicles are moved by motors that tug them along cellular railway tracks. We find that small vesicles instead move by diffusion - the same process that turns a whole glass of water blue after a drop of ink is added.
Exploitation Route We developed new imaging methods and analysis tools (software) that can be applied to other biophysical analysis of particle motions inside cells.
Sectors Digital/Communication/Information Technologies (including Software)

Pharmaceuticals and Medical Biotechnology

 
Title Simulated data for particle tracking and use in TrackMateR package 
Description The purpose of this dataset is to provide some example data for users of TrackMateR to use to become familiar with the package. The dataset contains three elements: Code to simulate some images (movies) of particle motions in 2D in Fiji. `particleSimulator.ijm` will generate images and ground truth positions of particles moving in six different modes (see below). An example output is given in `particleSimulatorOutput/` Code to automate the tracking of these images using TrackMate in Fiji. An example output is give in `TrackMateOutput/` These XML files can be used as the input in TrackMateR package. Outputs from TrackMate v 0.3.5 in `TrackMateROutput/` The simulated data is: Simulation A - particles moving in linear direction, variable but constant direction, high speed Simulation B - particles moving in linear direction, variable but constant direction, slow speed Simulation C - random motion high D (diffusion coefficient) Simulation D - random motion low D Simulation E - random motion, 50:50 mix of high and low D particles Simulation F - random motion, subdiffusive These TrackMate XML files can be processed using TrackMateR as described here. 
Type Of Material Database/Collection of data 
Year Produced 2023 
Provided To Others? Yes  
Impact Benchmarking dataset for reuse by other researchers. 
URL https://zenodo.org/record/7985499
 
Title Simulated data for particle tracking and use in TrackMateR package 
Description The purpose of this dataset is to provide some example data for users of TrackMateR to use to become familiar with the package. The dataset contains three elements: Code to simulate some images (movies) of particle motions in 2D in Fiji. `particleSimulator.ijm` will generate images and ground truth positions of particles moving in six different modes (see below). An example output is given in `particleSimulatorOutput/` Code to automate the tracking of these images using TrackMate in Fiji. An example output is give in `TrackMateOutput/` These XML files can be used as the input in TrackMateR package. Outputs from TrackMate v 0.3.5 in `TrackMateROutput/` The simulated data is: Simulation A - particles moving in linear direction, variable but constant direction, high speed Simulation B - particles moving in linear direction, variable but constant direction, slow speed Simulation C - random motion high D (diffusion coefficient) Simulation D - random motion low D Simulation E - random motion, 50:50 mix of high and low D particles Simulation F - random motion, subdiffusive These TrackMate XML files can be processed using TrackMateR as described here. 
Type Of Material Database/Collection of data 
Year Produced 2023 
Provided To Others? Yes  
URL https://zenodo.org/record/7985498
 
Title Single particle tracking data for Sittewelle & Royle (2023) 
Description A project to analyse intracellular vesicle mobility. A preprint of the manuscript is available at https://doi.org/10.1101/2023.05.10.540182 Code associated with the manuscript can be found at https://github.com/quantixed/p063p036 TrackMate XML files for: ATG9A, Clathrin, EB3, LAMP1, ML1N, Rab5, Rab11, Rab30, Rab35, SCAMP1, SCAMP3, TPD54 TPD54 (pre and post bleach) are available here together with some of the larger outputs from the code. These TrackMate XML files can be processed using TrackMateR as described here or using the code associated with the manuscript. The folders contain calibration csv files which will correct the scaling where required during processing with TrackMateR. 
Type Of Material Database/Collection of data 
Year Produced 2023 
Provided To Others? Yes  
Impact Our paper in Life Science Alliance (Sittewelle & Royle 2024) 
URL https://zenodo.org/record/7905013
 
Title Single particle tracking data for Sittewelle & Royle (2023) 
Description A project to analyse intracellular vesicle mobility. A preprint of the manuscript is available at https://doi.org/10.1101/2023.05.10.540182 Code associated with the manuscript can be found at https://github.com/quantixed/p063p036 TrackMate XML files for: ATG9A, Clathrin, EB3, LAMP1, ML1N, Rab5, Rab11, Rab30, Rab35, SCAMP1, SCAMP3, TPD54 TPD54 (pre and post bleach) are available here together with some of the larger outputs from the code. These TrackMate XML files can be processed using TrackMateR as described here or using the code associated with the manuscript. The folders contain calibration csv files which will correct the scaling where required during processing with TrackMateR. 
Type Of Material Database/Collection of data 
Year Produced 2023 
Provided To Others? Yes  
URL https://zenodo.org/record/7905012
 
Title TrackMateR 
Description R package to analyse cell migration and particle tracking data captured with TrackMate in Fiji 
Type Of Technology Software 
Year Produced 2022 
Open Source License? Yes  
Impact Used in the community. 
URL https://doi.org/10.5281/zenodo.7042948
 
Title quantixed/TrackMateR: Version 0.3.9 
Description This release of TrackMateR v0.3.9 is the version used in the first publication using the package Sittewelle & Royle, 2023 You can view the changelog here 
Type Of Technology Software 
Year Produced 2023 
Open Source License? Yes  
URL https://zenodo.org/doi/10.5281/zenodo.10036190