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How do I know if I can trust my antibody?


Have you heard of The Domino Effect? I’m sure you have but let me remind you what it is. The Domino Effect is the cumulative, often disastrous effect produced when one single event sets off a chain of other events, the last one depending on the very first one.

In the context of your daily lab activity, The Domino Effect is at play when you discover the disastrous results you might get when you don’t put enough time and effort into planning your experiments from the very first step. Read on to find out how you can prevent this catastrophic chain of reactions when it comes to antibody-based experiments.

Whether you are a beginner or a veteran researcher, you have surely experienced, heard stories, or know someone who has cautionary tales to tell about experimental failures. Planning an experiment is a delicate matter and genuine mistakes can occur at every level. However, although you must worry about every single step during your planning process, as each of them represents a crucial juncture, it is true that the first step can set the direction of the whole experiment.

One target, different results?

The most common and easy mistake that happens in the lab is due to poor attention when choosing and preparing reagents. Buffers and chemicals are all good candidates. But think about the majority of biological assays run daily in the lab: immunohistochemistry, immunocytochemistry, western blot, enzyme-linked immunoassay, flow cytometry, and immunoprecipitation. What do they have in common? Antibodies! They all rely on a specific antibody-epitope binding. These antibodies may be monoclonal, polyclonal, or recombinant from different organisms, and they may be used to interrogate biological systems and signaling pathways on normal, cancerous, or other tissues.

Choosing a highly validated and well-characterized antibody is a fundamental step and is certainly an essential starting point to drive your results in the desired direction. It is not about good and bad antibodies, but antibodies that can be trusted, that are reproducible, and that work in specific tissue-application combinations. Even a good antibody can fail if used in the wrong context.

So, if you do have a choice, look for an antibody you can trust and increase your chances of success. But how can you trust an antibody?

The dictionary definition of trust is “the belief that someone or something is being truthful”. Trust is a mixture of character and competence, in other words, your strengths, what you do, and the results you produce.

The character and competence of an antibody are defined, at least, by three characteristics such as specificity, selectivity, and reproducibility – in relation to the context in which it will be used. Although these are all equally important features, they depend on different concepts.


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To be trustful an antibody must be specific, selective, and reproducible

Specificity defines the antibody function, what it does: the precise detection of a target antigen and no others. This is achieved through the unique antigen-binding site located at the tip of the variable region of every antibody. Each individual antibody must be capable of binding specifically with one unique epitope on the target protein. Polyclonal but not monoclonal antibodies can recognize multiple epitopes on the same protein; this is a characteristic that could be used to your advantage.

1. Specificity

Sometimes an antibody could potentially recognize two or more proteins if these proteins are highly homologous and contain the same epitope. But this is something you want to avoid. So, specificity starts with a proper antibody design.

An antigen sequence of 50-150 amino acids typically results in antibody-containing 3-5 epitopes, which is optimal for sensitivity and versatility (tolerability to different sample treatments and thus different applications). Can you find the sequence of your antigen on the vendor’s website?

Selectivity is the ability to bind to a specific site on the target protein. A selective antibody shows little cross-reactivity: it recognizes a given epitope with much higher affinity than other epitopes. A non-selective antibody is highly cross-reactive: it recognizes a range of molecules with similar levels of affinities.

2. Selectivity

Reproducibility is the ability of every new lot of an antibody to perform equally compared to a previous lot in all assays. Thus, reproducibility should not be confused with antibody selectivity or specificity: a highly selective but non-specific antibody can be equally bad in each new lot, and still, have high reproducibility.

3. Reproducibility

In IHC for example, a great way to test for reproducibility of a new antibody lot is to test it against its reference lot on consecutive sections. Some companies provide a selection of 1-5 images obtained with tissue microarray from multiple samples of normal and cancer tissues stained with different lots of the same antibody. Take advantage of this information.

There are so many other factors that can affect antigen-antibody binding more difficult to control. The temperature (depending on the chemical nature of the epitope and the bond it creates), the pH (optimal in a range of 6.5 and 8.4), the ionic strength, the concentration of the antigen in your samples, the tissue preparation such as embedding media and fixation protocol, and morphology are the more common parameters.






Be skeptic!

How many times have you found yourself asking: "Does the application in which the antibody has been validated really matter all that much? If the antigen name is stated on the vial, why should I question the antibody’s performance? Should I care about the host species?" Although many of us like to think that we can trust a commercial antibody 100%, the truth is that some of them have limitations that impact our results.

So, be a skeptic! Look for images of stained tissues. Look for antibodies thoroughly validated in different applications. Weigh the amount of data behind it. Don't let yourself become distracted by what's going on around you.

Failure in one assay does not necessarily predict failure in another. This is the reason why it is so important that antibodies are tested in all the applications they are intended to be used in. It is the primary responsibility of the manufacturer to provide this information. Make sure to take a few moments to compare your experimental needs with the antibody’s characteristics on the company website and the antibody datasheet.

Remember to always include positive or negative controls in your experiments. Be sure the tissue contains your protein at detectable levels. Work on protocol optimization since every step in the protocol impacts antibody performance. Don’t play with antibody concentration: run a titration curve to determine the optimal one. Use signal amplification if needed. When in doubt: ask the vendors.

Be wise!

As scientists, we know that for every success there’s usually a string of failures along the way. Don’t cry over those failures – you won’t get very far. Learn instead how to deal with them and use the experience to your advantage.

As someone who has worked at the lab bench for a dozen years, I could sit here and tell you about every single experiment that has gone wrong because of the lack of sufficient information or the willingness to know. But remember The Domino Effect.

A bit more effort upfront can save you the trauma of wasted lab time and can make all the difference in finishing your Ph.D. on time and on quality.