An international team, co-led by SciLifeLab researcher Ola Söderberg and Carolina Kampf (Atlas Antibodies), have developed a tool named MolBoolean. It can determine protein levels in individual cells, identify to what extent they bind together, and report on relative amounts of protein and protein complexes.
MolBoolean is a tool for color-labeling both individual proteins and complexes, which allows for a greater extraction of information than ever before. Studying individual proteins and tissue samples is of great interest to Life Science professionals, and with enhanced accuracy and speed comes important scientific discoveries and advances.
The novel technology, presented in Nature Communications, was developed by a team of SciLifeLab researchers at Uppsala University, together with the university of Porto and Atlas Antibodies.
“MolBoolean is a method to be able to determine levels of proteins in individual cells, while also enabling the identification of what percentage of these bind each other. We have built on a tool we created in 2006 and which today is used all over the world. The functions we are now adding will be able to generate information about relative amounts of proteins as well as relative amounts of protein complexes and make the cells’ activity status and communication better visible. We can compare it to assessing a restaurant, ten positive reviews provide some information, but it is valuable to know whether it is ten or 1000 who answered the question”, says shared last author Ola Söderberg, SciLifeLab researcher at Uppsala University in a Press Release.
Both industry and academia has show interest in the results of their study. The Stockholm-based company Atlas Antibodies recently took over the patent for MolBoolean and is now preparing the method for the market.
“The goal of our research is to develop tools to make processes inside cells visible, and in our own team to increase the understanding of what happens in cancer cells. Knowledge of the balance between free and interacting proteins is important in the study of cell signaling, and we believe that MolBoolean will be appreciated in many laboratories”, notes shared first author and SciLifeLab researcher Doroteya Raykova.
This tool has a lot of potential for modern research as well as healthcare in the long term – streamlining routine diagnostics and improving cancer treatment choices.