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For you to achieve accurate and precise results, you need antibodies that bind to the intended target in a manner that is consistent between batches. Here we provide an overview of the validation processes we follow to give you high-quality reagents, so that you get accurate results first time.
Antibody validation can be very application-specific, which is why there typically is a need to use multiple validation methods. To address this, we carry out quality checks via ICC/IF, IHC, WB, flow cytometry, ELISA, IP, ChIP, and peptide array. This means that we can ensure that each antibody is validated using an appropriate method, and all of our products achieve the required levels of activity, stability, and performance.
We use application-specific criteria to pass or fail our antibodies and typically test all of our antibodies in multiple applications. These criteria include basic standards, like a specific signal and relevant controls. If we take our RabMAb® range of rabbit monoclonal antibodies as an example, every antibody needs to pass several criteria before we add it to our catalog:
If an antibody does not meet these criteria, we fail it and it doesn’t get added to the catalog. Specificity and consistency are a major focus for us because we know how important these are to researchers, which is why we subject our antibodies to additional testing.
It’s essential to know that your antibody binds specifically to the intended target. We are addressing antibody specificity with an ongoing knockout (KO)-validation program using human KO cell lines, generated from haploid cellular models, via CRISPR/Cas9. KO models provide an excellent standard for antibody validation as they represent a true negative control.
Genetic KO models are so powerful because they allow us to understand the function of a particular gene by observing the loss-of-function phenotype. Over the past year, we have worked with Horizon Discovery to KO validate over 500 antibodies and have also removed a further 200 unspecific antibodies from our catalog. KO validation is just one of many steps we are taking to raise antibody standards.
Figure 1. Specificity testing of PD-L1 RabMAb (ab205921) by immunohistochemistry – knockout (KO) testing: loss of detection on KO cells. Strong IHC detection with anti-PD-L1 is seen in human lung adenocarcinoma tumor cell line L2987. PDL1 gene was edited in L2987 cells using TALEN constructs targeting exon4 of human PD-L1, transcript variant 1 (NM_014143.3) and complete KO confirmed by deep sequencing in clone L2-14. IHC detection is completely eliminated in the L2987 L2-14 KO cell line.
Figure 2. Specificity testing of PD-L1 RabMAb (ab205921) by flow cytometry – knockout (KO)testing: loss of detection on KO cells. Strong detection with anti-PD-L1 TALEN constructs targeting exon4 of human PD-L1, transcript variant 1 (NM_014143.3) and complete KO confirmed by deep sequencing in clone L2-14. Cell surface staining is almost completely eliminated in the L2987 L2-14 KO cell line.
In addition to specificity, you want to know that you can achieve the same results with a new batch of the same antibody. To ensure this, we perform consistency tests to assess any batch-to-batch variation. In the case of recombinant antibodies, consistency between batches is very high, meaning you are unlikely to need to perform additional optimization procedures (eg titration experiments) between batches. This may not be the case with other non-recombinant monoclonal and polyclonal antibodies where the degree of variation is inherently higher.
Figure 3. Batch testing of PD-L1 RabMAb (ab205921) by IHC – analysis of CHO PD-L1 expressed cells. A: rabbit IgG, 5 µg/mL no staining. B: anti PD-L1, 2 µg/mL (batch 1). C: anti PD-L1, 2 µg/mL (batch 3). D: anti PD-L1, 2 µg/mL (batch 4). E: anti PD-L1, 2 µg/mL (batch 5). F: anti PD-L1, 2 µg/mL (batch 6). G: anti PD-L1, 2 µg/mL (batch 7.) All batches (1,3,4,5,6,7) showed consistent results.
Delivering the highest standards
By using different validation techniques, we can provide you with antibodies that are as specific and consistent as they can be. This is an approach we have employed for a number of years, and it sits at the core of our ongoing strategy to promote robust and reproducible science.