AnalyzER—Quantifying the Hidden Architecture of the Plant ER

The endoplasmic reticulum (ER) is one of the most important — and most complex — structures inside living plant cells. Often described as a dynamic highway system, the ER is responsible for essential functions like protein production, lipid synthesis, calcium storage, and stress responses. It consists of a shifting network of tubules and sheet-like structures that constantly reorganize in response to the cell’s needs.

Despite its vital role in cell biology, the structure and behaviour of the ER have remained surprisingly difficult to quantify. Much of what we know has come from descriptive imaging or manual analysis — powerful, but limited in speed and objectivity.

Our recent work addresses this challenge head-on with the development of AnalyzER: a new, automated software tool that extracts and analyzes ER structure and dynamics from high-resolution fluorescence microscopy images. AnalyzER distinguishes between the tubules and sheet-like cisternae, measuring key features like shape, connectivity, protein localization, and how the network behaves over time — all with minimal user input.

Why It Matters

By automating ER analysis, we’ve taken a step toward making this kind of research more reproducible, scalable, and statistically robust. This is especially important for experiments that generate large datasets or require subtle comparisons between treatments.

We validated AnalyzER using both manually-traced networks and high-resolution electron microscopy. We then put it to the test under a wide range of experimental conditions — including heat stress, drug treatments, and the overexpression of proteins known to alter ER shape. The software could not only detect changes in network architecture but also quantify how those changes affect overall ER behaviour, like its ability to move or respond to stress.

AnalyzER also supports multiple imaging channels, meaning it can track different fluorescent markers at the same time — whether you're looking at protein co-localization or physiological changes using sensors like roGFP. The tool can be run in batch mode, making it suitable for medium-throughput screens such as mutant analysis or drug response profiling.

A Broader Impact

Although developed for plant cells, AnalyzER is flexible and could be applied to study ER networks in other systems, including animal cells. As cell biology becomes increasingly data-rich and quantitative, tools like this help transform descriptive imaging into measurable, comparable science — aligning with key research priorities in bioscience data integration and bioimaging technology innovation.