Localizatome: a novel tool to study stress-dependent subcellular protein localization changes

Using a high-throughput fluorescence microscopy system and machine learning algorithms, oxidative stress-related changes in protein localization have been mapped by researchers from Japan. Furthermore, a comprehensive database called Localizatome has been developed by compiling the subcellular protein localization data of 10,287 human proteins. This database provides information on both the steady-state subcellular localization of proteins and dynamic localization changes that occur in response to oxidative stress.

Proteins are an important class of biological macromolecules that are made up of long chains of amino acid residues. These macromolecules play an important role in regulating the diverse functions of cells, tissues, and organ systems. To ensure the smooth functioning of vital cellular processes, proteins need to be present at the appropriate site in adequate amounts. This specific accumulation of a protein within a cell is known as subcellular protein localization.

In recent years, several databases have been developed to provide information on subcellular localization of proteins in mammalian cells. However, the data in these repositories are limited to protein localization within cells that are maintained under stable or steady-state conditions. Information about dynamic changes in protein localization when cells are subjected to stress is paramount to advancing the current understanding of health disorders and may aid in the development of therapeutic strategies.

To reveal oxidative stress-related dynamic localization changes of proteins, a team of researchers led by Professor Hiroshi Asahara from the Department of Systems BioMedicine, Institute of Science Tokyo (Science Tokyo), Japan, has developed the Localizatome database. The researchers from Science Tokyo collaborated with scientists from Osaka University, RIKEN, Musashino University, and the National Institute of Advanced Industrial Science and Technology to create the database. Their findings were published online in the journal Database on April 21,2025.

Sharing the genesis behind the development of the Localizatome database, Asahara says, “Oxidative stress caused by the excessive production of reactive oxygen species is a critical factor in the onset and progression of certain diseases, including ageing and cancer. Understanding how proteins behave under oxidative stress is important for elucidating the underlying mechanisms. Localizatome encompasses the various oxidative stress-dependent changes in subcellular localization of proteins.”

To capture the dynamic localization changes, the researchers initially utilized HeLa cells—a human cell line expressing 10,287 human proteins containing fluorescent protein labels. Subsequently, they employed a customized high-throughput microscopy system that included a plate transport robot. Live-cell fluorescence imaging was used to map the localization patterns of each protein before and after exposure to oxidative stress. Furthermore, a machine learning-based image analysis was conducted to accurately detect stress-dependent subcellular protein localization changes.

Through both machine learning analysis and manual verification, the localization data of 8,055 human proteins are currently made available in the Localizatome database. Notably, the scientists observed that 1,910 proteins exhibited distinct foci formation patterns in response to oxidative stress. Further analysis of these 1,910 proteins by Gene Ontology and the Kyoto Encyclopedia of Genes and Genomes pathway analysis revealed that these proteins were related to the Hippo signaling pathway, cell division, and protein degradation.

Upon developing the Localizatome database, Asahara states, “Localizatome database can be easily accessed through a user-friendly web interface and provides open access to fluorescence image data, cell coordinate information, and protein accumulation scores and changes.”

The development of the Localizatome database can drive future research in subcellular protein localization and may contribute to the elucidation of molecular mechanisms underlying oxidative stress-related diseases and aid the development of new therapeutic approaches.

Authors:

Takahide Matsushima¹, Yuki Naito¹, Tomoki Chiba¹, Ryota Kurimoto¹, Keiko Itano²,
Koji Ochiai³, Koichi Takahashi³, Naoki Goshima^4,5, and Hiroshi Asahara^1,6*

Title:

Localizatome: a database for stress-dependent subcellular localization changes in proteins

Journal:

Database

DOI:

10.1093/database/baaf028

Affiliations:

¹Department of Systems BioMedicine, Institute of Science Tokyo, Japan
²Department of Biomolecular Science and Engineering, Osaka University, Japan
³Laboratory for Biologically Inspired Computing, RIKEN Center for Biosystems Dynamics Research, Japan
⁴Molecular Profiling Research Center for Drug Discovery, National Institute of Advanced Industrial Science and Technology, Japan
⁵Department of Human Science, Musashino University, Japan
⁶Department of Molecular Medicine, Scripps Research, United States

• MATSUSHIMA Takahide | Science Tokyo Research Information DB
• ASAHARA Hiroshi | Science Tokyo Research Information DB
• Systems BioMedicine (Asahara Laboratory)
• Graduate School of Medical and Dental Sciences

• The University of Osaka
• RIKEN
• Musashino University
• National Institute of Advanced Industrial Science and Technology (AIST)