Israeli immune-response algorithm could aid TB diagnosis
An Israeli algorithm that predicts the immune response to a pathogen could lead to early diagnosis for such diseases as tuberculosis.
The phenomenon is explained by lead author Roi Avraham from the Institute’s Biological Regulation Department: “When immune cell and bacterium meet, there can be several outcomes –the immune system can kill the bacteria; the bacteria can overcome the immune defenses; or, in the case of diseases like tuberculosis, the bacterium can lie dormant for years, sometimes causing disease at a later stage and sometimes remaining in hibernation for good. We think that the junction in which one of those paths is chosen takes place some 24 to 48 hours after infection.”
Noa Bossel Ben Moshe and Shelly Hen-Avivi in Avraham’s group began by introducing immune cells from blood samples to Salmonella bacteria. Using a method developed in recent years, partially at the Weizmann Institute, they sequenced the gene activity in thousands of immune cells to see what each cell looked like as it responded to the Salmonella and mapped the activation profiles of each.
This process revealed patterns not seen in standard lab tests, and it seemed to confirm their hypothesis – there were indeed differences that enabled them to trace responses from the initial meetings to the later outcomes.
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