There are several reasons why the world is still plagued by diseases we cannot treat or vaccinate against, one of them being the vast complexity of the human immune system. Danish researchers have now developed a method, which can help expose a complicated but crucial part of the immune system's defence mechanisms. This method can lead to entirely new vaccines and treatments.
Researchers from BioCentrum DTU and the Faculty of Health Sciences at the University of Copenhagen have combined the fields of Bioinformatics and ImmunoChemistry and created models of neural networks, which can do what has thus far been impossible: Simulate how the immune system defends itself from disease. The neural network models also indicate that the immune system protects itself from being deceived by microorganisms, by using ingenious PIN code-like mechanisms.
Every human being has its own unique immune system PIN code, so that even if e.g. a virus unlocks the code in one person, the knowledge gained by the virus is useless in infecting the next individual. But the same defence mechanism makes it difficult to decode the entire human immune system and develop precise immunological treatments such as vaccines.
With the new neural networks, however, Danish researchers will be able to predict all the different known, but also the as of yet unknown immune system PIN codes. This makes it the most comprehensive tool of its kind, putting the technology at the forefront of international research.
On a global scale, the neural networks can help researchers deal with all the variables of an epidemic threat. "We'll be able to find candidates for vaccines which can help both the individual and all of humanity," says Professor Søren Buus from the Department of International Health, Immunology and Microbiology, University of Copenhagen.
Our immune system protects us against threats from e.g. bacteria, viruses and cancer. So-called T-cells constantly inspect the body's cells and check if they are healthy, infected or broken. T-cells can distinguish between antigens belonging to the body and those that do not. If an antigen is alien - it could originate from a virus, which has infected the cell. The T-cells can attack the sick cell and thereby remove the location of the virus and terminate the infection.
The T-cells, however, cannot see directly into other cells. To do this job, they use "samplers", called tissue type molecules, which drag fragments of everything inside the cell being investigated to its surface, and show these samples to the T-cells. Researchers have known for a long time that this selection of samples plays a key part in the workings of the immune system; if a microorganism can evade the samplers, it evades the entire immune system.
The complexity of the immune system protects against disease
To prevent microorganisms from learning how the samplers work, the immune system has furnished itself with an amazing variety of samplers or tissue type molecules. Each of us only has a few variants (our own "pin code"), but the whole of humanity has thousands.
So a microorganism can never know which samplers it encounters; and even if it does figure this out in one human, the knowledge is useless in the next person infected. This defence strategy provides one of the most sturdy ways of protecting the immune system from being infiltrated - a little like PIN codes protecting our credit cards.
If we are to understand how the T-cells work, and use this knowledge of the immune system to discover, diagnose and treat diseases, the researchers must first identify precisely those cell fragments that the samplers choose to display, since it is only if the tissue type molecules show the right part of an infected cell to the T-cell, that the immune system reacts.
Why human tissue type is vital to immunology
Today, researchers know approx. 5000 different tissue type molecules in humans and the number is increasing day-by-day. Each of us expresses a unique combination of the molecules, and this explains why two individuals never react in the same way to the diseases they encounter during their lives.
The vast number of different tissue types ("pin codes") also affect transplants, so doctors must search for optimal tissue type compatibility during e.g. bone marrow transplants, a procedure vital in treating leukaemia. If the researchers know the tissue type molecules (the "pin code") of a patient, the neural networks can map all the cell fragments his/her immune system will be presented with, and therefore which pathogens the T-cells will get to see. If e.g. a patients own immune system does not react to a disease, the new knowledge can find, isolate and produce the necessary T-cells which can see the pathogen (virus, cancer cell etc.)
This can have far reaching consequences for the treatment of cancer, infectious diseases and transplants.
The full article on this development has just been published in PloS One.
Cite This Page: