Vesicle Trafficking

In this series "From Image to Results", explore various case studies explaining how to reach results from your demanding samples and acquired images in an efficient way. For each case study, we highlight different samples, imaging systems, and research questions.

We start the series with an analysis of vesicle trafficking in Cos7 cells.

Key Learnings:

• How to generate a high-resolution longitudinal study of vesicle trafficking within a single cell
• Explore basic observations concerning vesicle transport
• Showcase image analysis tools to segment vesicles and generate vesicle tracks to derive meaningful data to confirm our observations
  

The overall distribution of vesicles helps in deducing the overall cellular architecture of the sample (Figure D). The area of high-density Golgi-associated vesicles presumably represents the main Golgi apparatus region of the cell. Next to it is a large “vesicle-free” region that represents the nuclear area. The three-dimensional contours of the nucleus can also be deduced by the spherical volume void of vesicle tracks in a 3D representation (Figure F).​

​A further validation is the option to visualize the cell as a “scatter plot” based on the objects’ x-y coordinates (Figure E). This shows again an accumulation of vesicles (and tracks) at the Golgi and an exclusion of vesicles from the nuclear area. This plot type is also a valuable tool for visualization of certain observations.​

​All other cellular regions may be assigned to “Periphery”. Assigning these areas aids a more precise description for the subsequent vesicle and track observations.​

Size and Distribution of Vesicles

Having defined “endosomal” and “Golgi-associated” compartments during image analysis it is now possible to make observations and prove them with measurements and suitable visualizations.​

​Vesicular compartments mainly differ in size and cellular localization. The ~ 26000 identified endosomal vesicles have an average volume of 0.63 µm³, while the ~ 22000 identified Golgi-associated vesicles have an average volume of 1.062 µm³. The volume distributions are also shown in Figure G. Endosomal vesicles are devoid in the Golgi area and evenly distributed over the cell periphery (Figure H). Golgi-associated vesicles accumulate more in the central “Golgi area” of the cell (Figure I). By color-coding the plot with vesicle volumes, it becomes apparent that large vesicles are primarily located in the Golgi area. This is further illustrated by Figure J, that compares vesicle sizes within the central Golgi region and in the cell periphery.

Density of Vesicles

The next goal was to determine the density of vesicles throughout the cell. Vesicle density takes into account both vesicle volumes and the accumulation of vesicles in a certain region of a cell, and is hence related to these two features.​

There is no direct way of plotting object densities in ZEISS arivis Pro. Vesicle positions and volumes were therefore exported via spread sheet and calculated density maps weighted for vesicle volumes were generated using Python (Figure K-M).​

The results confirm the observations made for vesicle sizes and distribution: The Golgi area is the vesicle center of the cell. The vesicle density here is more than 10 times higher than in the cell periphery (Figure K). This enhanced density is attributed almost exclusively to Golgi-associated (Golgi7-positive) vesicles (compared Figure L and M).​

Fast Vesicle Motion Enriched in Periphery (Ring Zone around Nucleus)​

Vesicle trafficking is a process of directed vesicle transport along cytoskeletal filaments (e.g. microtubules). This process generates cellular zones of strong vesicle motion. To analyze vesicle motion in this data set, the tracks from endosome vesicles (1408 tracks) and Golgi-associated vesicles (551 tracks) were used to determine the track speed, which is the average movement of vesicles from one frame to another. ​

​Endosomal vesicles displayed an average speed of 0.206 nm/s and therefore were significantly faster than Golgi-associated vesicles with 0.125 nm/s (Figure N). When analyzing the distribution in the cell, vesicle motion was found to be fast in the periphery, more specifically in a zone around the nucleus and the cell’s protrusions (Figures O-Q). In contrast, vesicle motion in the central Golgi area was 2-3 times slower. The fast vesicle movement in the periphery was mainly attributable to endosomal vesicles. ​

Directed Motion Enriched in Periphery (Ring Zone around Nucleus)​

Vesicle track speed, as determined in the previous section, does not take into account the overall direction of vesicle movement. Hence, a vesicle that ends up at its original starting point, might still have a high track speed. In order to consider directed motion, the Mean Square Displacement (MSD) of the vesicle tracks was determined, which measured the total distance from a track’s starting point.​

​Endosomal vesicles and Golgi-associated vesicles displayed an average MSD of 1.994 µm² and 0.721 µm², respectively (Figure R). As for track speed, vesicles with high MSDs were located in the periphery, more specifically, in a zone around the nucleus and towards the cell’s protrusions (Figures S-U). Again, endosomal vesicle tracks were mainly responsible for high MSDs.​

Main Motion Directions throughout the Cell​

Both parameters track speed and MSD allows evaluation of vesicle velocity and directed motion. However, these evaluations do not display active transport, as they cannot take into account the track directions. Visual inspection of the dataset suggests, that such active transport takes place in the zones of fast vesicle motions around the nucleus and towards the cell protrusions. To illustrate that vesicles indeed have a preferred motion direction it is possible to use track displacement vectors of vesicles and tracks. ​

ZEISS arivis Pro  offers limited options for visualizing vectors. As a result, the relevant vesicle positions were exported together with their parent tracks and data science tools in Python were used to obtain different visualizations of track directions (Figure W-Y).​

All visualizations show that there are main motion directions in different parts of the cell. Vesicles move across a ring zone around the nucleus as well as towards the cellular protrusions at the upper end of the cell.​

This case study has showcased how to approach the analysis of a complex imaging data set employing the arivis Pro software. ZEISS arivis Pro provided tailor-made image processing and segmentation to derive and track the biological objects that represent the full complexity of the sample. After definition of the objects, visualization or plotting important object features for both vesicles and tracks was possible from within ZEISS arivis Pro. For features not accounted for by ZEISS arivis Pro, the necessary data were extracted and analysis was continued using customized analysis with Python.​

The biological results obtained for the two vesicle compartments fit nicely with what is expected from their biological background. Golgi-associated vesicles are packed densely in a zone next to the nucleus that appears to form the Golgi apparatus of the cell. These are large and move relatively slowly. On the other hand, endosomal vesicles, responsible for directed transport throughout the cell, appear to be more distributed throughout the cell periphery and are devoid from the Golgi zone. They are smaller and move faster and in a more directed way than Golgi-associated vesicles, especially in a specific peripheral zone around the nucleus. ​
Of note, the intention of this use case was not to perform a thorough analysis, but to provide an overview of the analysis strategy. Other important observations may be buried within the data set, e.g., the measurement of “active vesicle transport” by means of analyzing the MSD over time, or vesicle fusion and budding by means of a more complex tracking strategy. ZEISS arivis Pro has the tools to find answers to these questions also. This dataset is available for you to try these analysis approaches for yourself in ZEISS arivis Pro so you can find out more about these observations.