Fig. 3

Pipelines of the different multiomics spatial phenotyping technologies used in the OA field. a Spatial transcriptomics is a cutting-edge technology that merges oligonucleotides with slides and combines them with tissue samples for detection. This method enables the detection of RNA signals with high accuracy, sensitivity, and a resolution of 200 nanometers. However, this technology is relatively costly and has potentially compatibility challenges when applied to bone and cartilage specimens. b Spatial proteomics uses certain protein enzymes to dissect the protein sequence into peptide segments. The sample is then ionized using different techniques, including matrix-assisted laser desorption/ionization (MALDI) and desorption electrospray ionization (DESI); finally, the laser is used to extract the mass for mapping with a resolution up to 20 μm. It spatially detects peptide signals, with mid to high sensitivity. However, the data is difficult to interpret. Specific peptide signals point to various proteins, and they need further validation. c Mass spectrometry imaging (MSI)-guided multiomics combines MSI and laser microdissection microscopy for separation, cross-validation and analysis. It can reach high accuracy and sensitivity but requires an optimized section-transferring system. d Digital spatial profiler (DSP) employs barcoded fluorescent markers for RNA and protein detection. It is easy to use with multiple genes and protein detection capability available, although it shows only partial information in the gene clusters without mapping. e Functional mass spectrometry imaging (fMSI) uses specific substrates for digesting the enzyme. Then, MSI instruments can extract ionized product signals for mapping with a resolution of up to 20 μm, confirming high sensitivity and accuracy when spatially detecting substrates and products. However, researchers need to first validate the existence of the enzyme. This figure was created with BioRender.com