Researchers have recently developed an open, low-cost imaging-based spatial transcriptomics (ST) platform that can also integrate spatial metabolomics (SM) on the same slide.

Called OpenFISH, the new technique addresses two major challenges in spatial transcriptomics: high cost and incompatibility with spatial metabolomics.

The study, led by Prof. DUAN Lihui at the Institute of Genetics and Developmental Biology (IGDB) of the Chinese Academy of Sciences (CAS), was published in Neuron on September 29.

A molecular system works like a multi-story building. Information flows from the genome, to transcripts, to proteins, to metabolites, and finally to the phenotype—and every layer interacts with the others. Measuring just one layer can miss the full picture and the connections between them.

Scientists can now detect molecular features in place at single-cell resolution, but existing spatial transcriptomics technologies remain expensive and difficult for many laboratories to adopt. Integrating imaging-based ST with MALDI-MSI-based spatial metabolomics on the same tissue section presents an additional challenge.

To address this barrier, the researchers used a modular probe design to cut probe synthesis costs and a simple coding system for genes that eliminates the need for a microfluidic system. They also optimized the experimental procedure, bringing the wet-lab time down to no more than 13 hours. A standard 20X widefield fluorescent microscope is sufficient to capture clear signals in situ. Together, these efforts reduce the total cost of OpenFISH by about 95% compared with leading commercial platforms.

The researchers then used OpenFISH in two neuroscience applications: examining cell-type-associated transposable element (TE) elevation during inflammation and neuronal cell lamination distortion after Reln gene knockout. They observed reproducible TE elevation, pointing to a role for TEs in regulating cells. Beyond the known anatomical changes caused by Reln knockout, they also observed a decrease in D1-type inhibitory striatal neurons.

ST and SM are commonly performed on serial sections. However, inherent differences between two adjacent slides can compromise how the data is interpreted. To address this problem, the researchers modified conductive slides for the state-of-the-art untargeted SM method MALDI-MSI. Through polyacrylamide gel embedding, protein digestion, and lipid removal, OpenFISH signals could still be readily detected even after the harsh laser processing used in MALDI-MSI.

Ion feature signals and transcript quality were barely affected by the integration. With this combined pipeline, the researchers revealed cell-type-associated metabolites in mouse brain cells and found that merging the two modalities improves anatomical depiction.

They also applied the pipeline to 5xFAD mice, a model for Alzheimer's disease (AD). Microglia showed the strongest changes after AD, and multiple metabolites associated with specific cell types were elevated in AD mice compared with healthy controls.

According to the researchers, this work provides an ST tool at a substantially lower cost—one that can be paired with an SM platform to better untangle the complex interactions between the molecular layers of biology.