Johan Winnubst

A cell is a vibrating, densely packed bag of molecules. The ratios of these molecules are not balanced, however. A typical HeLa cell, for example, has about 20 times more protein than DNA by mass. Why, then, are the methods available to study proteins so much more expensive, and less scalable, than those used to study DNA? Human cells make thousands of different proteins using 20 amino acids. Those amino acids can be arranged in a staggering number of combinations to make everything from small, spindly structures like insulin (51 amino acids) to globular giants such as titin (34,350 amino acids). This chemical diversity is what makes proteins so adaptable and infinitely useful. Ideally, scientists would be able to study the proteomes of thousands of cells in one experiment! And cheaply, too! But in reality, existing proteomics technologies can only be used to analyze about a dozen cells at once — a paltry amount. Modern proteomics is majorly bottlenecked, in other words. And it's a shame, because many of the diseases we care about are influenced by proteins. Protein alterations — like phosphorylation and ubiquitination — can change a protein’s function in ways that are invisible at the level of DNA or RNA. Diseases like Alzheimer’s are partly driven by these changes. And it is exceptionally difficult to study the brain, with its billions of cells, by looking at the proteins of just a few cells each day. For my latest essay in @AsimovPress, I explain how a non-profit organization, called Parallel Squared Technology Institute, is trying to solve this problem. Their goal is to make proteomics as scalable and accessible as DNA sequencing. And remarkably, they are working toward this goal NOT by making better hardware (aka bigger, more expensive machines), but rather by inventing better molecular barcodes, devising protocols to squeeze more data out of mass spectrometers, and writing software to handle all the data. So far, they’ve made a 9-plex barcode system (up from the state-of-the-art 3), and combined it with a time-staggered injection method called timePlex, thus enabling 27-plex experiments on existing machines. Their strategy has already boosted the number of proteomes scientists can study in a single day by a great deal. Now they want to 100x this again. The Parallel Squared team is now applying their tools to study Alzheimer’s. They’re mapping the proteomes of individual neurons taken from patients who died at various disease stages, from Braak 0 to Braak 6. By lining up healthy and diseased cells and watching how protein quantities change, they aim to flag molecular markers that appear before symptoms begin — in the disease’s quiet, prodromal phase, when treatments might still work. Thanks for reading. You can check out the full article here: press.asimov.com/articles/pr…