While interesting, I think that the relevance of MassSpec based approaches will decline over the next years.
Single cell genomics already had to learn the hard lesson that pure gene quantification and big data approaches without spatial resolution or deep understanding of the biology can only get you so far. Billions have been spent on cell atlases that just deal with biology as individual cells without much to show for in terms of changes in clinical practice. Spatial omics is now finally spreading and spatial organization and interactions are being taken into account again, but the common analysis pipeline still just focus on gene level expression at the cellular level. Subcellular and extracellular information is often completely lost and gene levels are highly variant and only somewhat correlate with the phosphoproteome, the actual effect layer of biology.
Mass spec approaches share many of the same limitations, even though they deal with protein. Spatial information is blurry at best or lost at worst and equipment is expensive and requires specialized training.
Imo, the most interesting advances in the next years will come from low cost high resolution spatial proteomics with high target counts that integrate with biological modeling of processes.
Single cell genomics already had to learn the hard lesson that pure gene quantification and big data approaches without spatial resolution or deep understanding of the biology can only get you so far. Billions have been spent on cell atlases that just deal with biology as individual cells without much to show for in terms of changes in clinical practice. Spatial omics is now finally spreading and spatial organization and interactions are being taken into account again, but the common analysis pipeline still just focus on gene level expression at the cellular level. Subcellular and extracellular information is often completely lost and gene levels are highly variant and only somewhat correlate with the phosphoproteome, the actual effect layer of biology.
Mass spec approaches share many of the same limitations, even though they deal with protein. Spatial information is blurry at best or lost at worst and equipment is expensive and requires specialized training.
Imo, the most interesting advances in the next years will come from low cost high resolution spatial proteomics with high target counts that integrate with biological modeling of processes.