Microsoft Research, Cambridge scientists develop blood development model
Researchers at the University of Cambridge and Microsoft Research have joined hands to develop a computer model that provides for the first time a comprehensive simulation of development of blood cells paving way for better understanding of the control mechanisms that keep blood production normal.
Researchers say that the model will not only help understand development of blood cells, but it could also lead to new treatments for leukemia and lymphoma.
“With this new computer model, we can carry out simulated experiments in seconds that would take many weeks to perform in the laboratory, dramatically speeding up research into blood development and the genetic mutations that cause leukaemia,” said Professor Bertie Gottgens at Cambridge Institute for Medical Research.
The human body produces over 2.5 million new blood cells during every second of our adult lives, but how this process is controlled remains poorly understood.
Blood cancers, which include leukaemia, lymphoma and myeloma, occur when the production of new blood cells gets out of balance, for example if the body produces an overabundance of white blood cells.
To construct the computer model, PhD student Vicki Moignard from the Wellcome Trust-MRC Cambridge Stem Cell Institute measured the activity of 48 genes in over 3,900 blood progenitor cells that give rise to all other types of blood cell: red and white blood cells, and platelets.
These genes include TAL1 and RUNX1, both of which are essential for the development of blood stem cells, and hence to human life.
Computational biology PhD student Steven Woodhouse then used the resulting dataset to construct the computer model of blood cell development, using computational approaches originally developed at Microsoft Research for synthesis of computer code. Importantly, subsequent laboratory experiments validated the accuracy of this new computer model.
One way the computer model can be used is to simulate the activity of key genes implicated in blood cancers. For example, around one in five of all children who develop leukaemia has a faulty version of the gene RUNX1, as does a similar proportion of adults with acute myeloid leukaemia, one of the most deadly forms of leukaemia in adults.
The computer model shows how RUNX1 interacts with other genes to control blood cell development: the gene produces a protein also known as Runx1, which in healthy patients activates a particular network of key genes; in patients with leukaemia, an altered form of the protein is thought to suppress this same network.
If the researchers change the ‘rules’ in the network model, they can simulate the formation of abnormal leukaemia cells. By tweaking the leukaemia model until the behaviour of the network reverts back to normal, the researchers believe they can identify promising pathways to target with drugs.
“The huge advantage of this executable biology approach is that it also allows us to simulate and analyze these behaviors very quickly – in a matter of seconds we get an answer as to whether a certain combination of drugs would lead to a desired effect or not”, said Dr. Jasmin Fisher, a senior researcher with Microsoft Research Cambridge who collaborated on this project.
The research is published in the journal Nature Biotechnology.