ay in
PM-249
HUMAN IMMUNOLOGY
Human IL-8 ELISA
Georgia Halliday
906091
Introduction-
ELISA stands for enzyme-linked immunosorbent assay which is a Immunological technique (Murphy, 2012, Owen et al., 2009) that can quantify substances like peptides, proteins, antibodies and hormones but in this practical, we used the specificity of antibodies to detect and quantify proteins in an aqueous sample through adsorption to a solid surface. It uses an enzyme reaction to generate a colour change that can be detected and varies due to the amount of the target molecule present.
The ELISA technique has many uses due to its high sensitivity and specific nature without needing radioactive substances which would also need counter apparatus.
There are a few types of ELISA practical, these are; direct, indirect, sandwich, competition, ELISPOT, multiple and portable (Shah K, 2016).
A direct ELISA is when only a primary labelled antibody is used, whereas an indirect ELISA is where the antigen is bound by the primary antibody and then detected by a labelled secondary antibody. A less common form of ELISA is a sandwich ELISA; however, it is highly efficient as it quantifies antigens between two layers of antibodies. In this experiment, we did an indirect sandwich which is where the biotinylated anti-IL-8-Pab binds to the anti-IL-8-Mab which is then attached to the primary antibody when Streptavidin HRP is added. Next, when the TMB peroxide substrate is added a colour change from colourless to blue and finally blue to yellow when HCl is added, which indicates the presence of the antibody or IL-8 is present.
The ELISA technique has many uses due to its high sensitivity and specific nature without needing radioactive substances which would also need counter apparatus.
We looked at an ELISA to detect IL-8 which is a major neutrophil chemokine able to amplify the immune response and which is also a vital biomarker of certain inflammatory and infectious diseases (Shahzad et al., 2010, Yoshimura, 2015). It can detect certain infections due to its ability to detect and measure antibodies in the blood that correspond to the disease. Infections that can be detected include HIV (AIDS), Lyme disease (Borrelia burgdoferi), Toxoplasmosis (toxoplasma gondii) Zika virus and many more.
Method-
Firstly, we took our ELISA plate that had been pre-coated and blocked which we initially flood washed by overflowing each of the wells in a linear fashion and then blotted out, by shaking out the excess vigorously then blotting on paper we repeated the flood wash 3 times. Then to complete step one we added aliquot standards (50microliters or 50l) of the varying known concentration and 50l of the unknowns as shown in the table on the proforma. Next, we left to incubate for 30-45 mins. After incubation, we flood washed the ELISA plate another 3 times, then added aliquot 50l of Biotinylated Secondary Ab to each well then allowed to incubate for another 30-45 mins. After another round of flood washing, we carefully added aliquot 50l of streptavidin HRP to all the wells and allowed to incubate for 20 mins. Followed by another round of flood washing and for each induvial scientist we added 50l of the colour reagent and incubated for 20 mins. Then added 50l of the 0.1M HCl to all the wells. Finally, we looked at the plate at 450nm on the plate reader.
Results-
Graph 1-
Table 1-
Optical Density (raw figures) (nm)
Optical Density
(raw figures)(nm)
Optical density average (nm)
Optical Density minus Blank (nm)
0.055
0.075
0.065
0
0.098
0.128
0.113
0.048
0.13
0.159
0.1445
0.0795
0.155
0.163
0.159
0.094
0.253
0.256
0.2545
0.1895
0.42
0.427
0.4235
0.3585
0.671
0.65
0.6605
0.5955
1.138
1.087
1.1125
1.0475
Working out the Unknown concentrations-
To work out the unknowns we need to use the equation for a straight line. Which is as follows-
Using our trend line on our graph we can get the values for m which is the gradient. As well as c which is the y-intercept.
Then to get the y I used the average absorbance of the two unknowns of the same concentration minus the blank column, we then substituted all these values into a rearranged equation where I made x the subject as it is the only unknown.
So here is the rearranged equation-
Table 2-
Unknown OD
Unknown OD
Unknown OD averages
Unknown OD averages minus blank
0.193
0.17
0.1815
0.1165
0.685
0.714
0.6995
0.6345
0.188
0.152
0.17
0.105
1.109
0.973
1.041
0.976
0.088
0.092
0.09
0.025
0.411
0.43
0.4205
0.3555
1.353
1.368
1.3605
1.2955
0.199
0.148
0.1735
0.1085
So here is Unknown 1 (fully laid out)
X=? y= 0.1165 c=0.0452 m=0.001
Unknown 2-
Unknown 3-
Unknown 4-
Unknown 5-
Unknown 6-
Unknown 7-
Unknown 8-
Table 3-
Unknown sample
Concentration pg/ml
1
71.3
2
589.3
3
59.8
4
930.8
5
20.2
6
310.3
7
1250.3
8
63.3
Table 3- each unknown sample with their respective concentration.
The proforma states that are a sample have ‘350pg/ml or over’ this indicates a possible infection therefore from my workings unknown 2,4 and 7 are infected samples.
Discussion-
I used the example data because when we looked at the plate under the plate reader at 450nm we found that our absorbance readings didn’t correspond with what should have happened in theory. There was no discernible colour gradient present as the concentration of the IL-8 increased which isn’t possible as the higher the concentration the antigen increases there will be more to detect in the mass spectrometer, so no gradient clearly indicates a problem occurred and that our results were unreliable. The sample data which looks to be quite reliable as the repeats are generally quite close to each other, therefore, there is little variation so the average of the two is likely to be a more accurate representation of the true value.
The reasons our results could have has such discrepancies are human error and problems with the microtiter before commencing the ELISA practical. Problems beforehand could be improper stacking of the microtiter, or it could have been incorrectly blocked and pre-coated or even contaminated. However, it is more likely to have been human error, some of the most probable human errors to have occurred are, inadequate flood washing of the wells, poor pipetting technique meaning that either didn’t pipette the correct amount or carelessness when filling wells (some over filled some missed completely).
If I did this experiment again, I would make sure that each of the 96 wells on the microtiter plate was filled every time we added a new substance, I would use pipette with a smaller error margin thereby increasing my accuracy.
My standard curve isn’t very good I believe this because a standard curve should be linear with all points on the line however my standard curve has a slight margin of error. As my points, do vary either side of the standard curve which could mean that the gradient could be slightly off meaning that my unknown sample concentrations would be slightly off subsequently.
Another technique for measuring IL-8 protein in biological samples would be to reduced IL-8, so undergo RNA isolation and reverse transcription, then a quantitative real-time polymerase chain reaction will measure the IL-8 messenger RNA expression.
IL-8 is used as a universal biomarker because it has a high sensitivity and specificity as a part of the CXC chemokine subfamily. IL-8 is a biomarker mainly because it is under/over synthesised in certain physiological and metabolic conditions, therefore is acts as a signal.
To conclude, I would say that my results were not successful however using the sample data I found that 3 of my samples have a possible infected. Sample 2,4 and 7 have over 350pg/ml meaning they have a higher concentration and contain the IL-8 biomarker.
Bibliography-
Shah K, British J of Hospital Medicine 2016. 77 (7) pC98-C101
Murphy, K., (2012) Janeway's Immunobiology. Garland Science, London and New York.
Owen, J.A., J. Punt & S.A. Stranford, (2009) Kuby Immunology. Macmillan Higher Education, Houndmills, Basingstoke.
Shahzad, A., M. Knapp, I. Lang & G. Kohler, (2010) Interleukin 8 (IL-8) – a universal biomarker? Int Arch Med 3: 11.
Yoshimura, T., (2015) Discovery of IL-8/CXCL8 (The Story from Frederick). Front Immunol 6: 278.
here…