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Spots in negative control of TB patients


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Hi Mabtech

 

I bought your product Human IFN-γ ELISpot PRO (ALP), strips (3420-2AST-10) several months ago.

I have a question about this kit. Please check out the attached image below.

 

16 pulmonary tuberculosis patient’s PBMCs were detected (2.5x105 viable PBMCs per well).

N: negative control, 100ul AIM-V+100ul PBMCs.

T: Testing Well, 100ul TB antigen+100ul PBMCs.

P: positive control, 100ul phytohemagglutinin+100ul PBMCs.

 

My problem is that there are many spots in the negative control of sample 1, 2, 5 and 11. Generally speaking, there should be few or no spots in negative control. I don’t know why I get this result. Could you explain it?

 

I am looking forward to hearing from you. Thanks.

 

Best regards,

Y

post-64-0-14347000-1456743628_thumb.png

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Dear Y,

 

I trust that you treated all cell sample equally, and since just a few and not all samples have the high background, we can exclude possible systematic mistakes. 

 

Thus, my interpretation of the image is that we’re looking at a natural variation of the patient group. Do you have any further patient data that could explain such variations? For example, how long after diagnosis was the test done? Could it be so that for example patient sample 1 (having the highest background of them all) comes from a patient with active TB?

 

Unfortunately we do not have solid data on this potential natural variation. But one may speculate that at some time points during the course of the disease a patient would have constitutively IFNg producing T cells in circulation. 

 

From conversations with other customers, we know that background is seen in a few percent of all TB samples. One way to address background is to adjust the criteria for positive spots on the reader to not count smaller and weaker spots. However, in the case of sample 1, 2 and 5 in your plate, these spots are too intense to be regarded as “background” e.g. possible NK cell secretions. Rather, these spots are most likely true T cell responses and, as said, probably part of the natural variation of your sample group. 

 

If you have the possibility to access material from the same patients again, I would recommend you to test them again at a later time point. It is very possible that you would see different results due to the different time point after initial disease diagnosis. 

 

Finally, in general if you cannot explain an anomaly, it is not uncommon that some samples just have to be disqualified from analysis.

 

Kind regards,

Jens

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