Gold In-and-Out: New software automates and standardizes electron microscopy data analysis

April 5, 2022

Scientists from the electron microscopy core at Max Planck Florida Institute for Neuroscience recently developed software that helps analyze the precise location of proteins in the brain in an automated and efficient manner. The user-friendly software named Gold In-and-Out, or GIO, was published in the scientific journal Frontiers in Neuroanatomy.

“The software provides a time savings of up to 24 times for each data set. It is also open-source, requires no programming skills, and is packaged in an intuitive interface,” says Seth Goldin, an FAU high school student and co-lead author of the paper.

The software analyzes images taken using a highly-sensitive immunoelectron microscopy technique that can precisely determine the locations of specific proteins in brain tissue. This is done by attaching tiny particles of gold to each copy of the protein, which can then be visualized as dark dots under the electron microscope. After taking images of the thousands of gold particles in the brain tissue, scientists mark each gold particle and its location before using mathematical and statistical analyses to test whether there are meaningful patterns in the data. For example, scientists may calculate the distance between proteins or determine whether a specific protein is clustered at synapses. Small changes in protein localization patterns, which might occur during aging or disease, could lead to significant changes in neuronal and brain function, so understanding these patterns is essential.

While this type of data is crucial to our understanding of the brain, its analysis can be tedious and time-consuming. “Previously, we analyzed much of the data manually or using disparate macros and algorithms. We didn’t have a cohesive and standardized workflow that was easy to apply. We dreamed of developing a simple software that would allow scientists to upload their data, select several options, and get results,” explained Dr. Naomi Kamasawa, lead of the project and Head of the Imaging Center at the Max Planck Florida Institute.

However, tackling this project required a team with diverse expertise, including deep knowledge of electron microscopy, imaging data analysis, statistics, and programming. “Fortunately, we were able to put together an amazing team whose combined expertise made this project successful,” said one of the co-lead authors Connon Thomas. “Each individual’s contribution was key.”

Research scientist and co-lead author Dr. Debbie Guerrero-Givens added, “Besides being a multi-disciplinary team, we also had team members from all career stages. It was wonderful to have high school students, undergraduate trainees, and senior scientists working together and learning new things.”

It was important to the more senior scientists that the trainees were involved and contributing to all aspects of the project from conception through the scientific publication process, a tremendous opportunity for the trainees.

As Goldin described, “the most satisfying aspect of the project for me was the level of responsibility I was given and seeing the impact I could make as a high school student. It was thrilling to know that my programming work mattered for science. And as a bonus, I learned a lot about neuroscience and the scientific process along the way!”

Another trainee involved in the project, Skylar Anthony, an FAU undergraduate working on her thesis with the MPFI electron microcopy core, agreed. “This was the first time I was exposed to all sides of a research project, biological, technical, and the publication process. The openness and collaborative nature of the team allowed me to learn a tremendous amount.”

Dr. Kamasawa is rightfully proud of her team’s accomplishment, “The development of this program has standardized our analysis procedures and removed any potential human error. Moreover, we can use the time saved by this task to answer more scientific questions. I am so proud of my EM team for their hard work and collaboration to make this software a reality.”

The publication on GIO can be accessed here. GIO can be downloaded from Github here.

Guerrero-Given, D., Goldin, S. L., Thomas, C. I., Anthony, S. A., Jerez, D., & Kamasawa, N. (2022). Gold In-and-Out: A Toolkit for Analyzing Subcellular Distribution of Immunogold-Labeled Membrane Proteins in Freeze-Fracture Replica Images. Frontiers in Neuroanatomy, 16.