Have you ever wondered about the minds behind our antibodies? We talk a lot about validation, specificity, sensitivity, and reproducibility. All of that is very important, but that doesn't tell you much about who developed it.
When you’re shopping for antibodies, there are so many factors to consider. For example, will it work in my cell or tissue model? Has it been tested in the application I want to use? Sometimes it’s a struggle to find what you need because your options are limited, but in other instances there may be several reagents that seem like they could work in your experiment.
Researchers who run a lot of chromatin immunoprecipitation "ChIP" assays – maybe even your advisor – might subscribe to the idea that polyclonal antibodies perform better than monoclonal antibodies. But is that always actually true?
It’s worth your time to understand the differences between the two in terms of antigen recognition and specificity, and dispel some myths.
As a development scientist at CST, people sometimes ask me what exactly it is that I do. “I make antibodies,” is my typical reply, but that is not exactly true.
Topics: Antibody Validation
We as scientists learn from each success and failure. Sometimes it takes many failures to achieve success. And some discoveries are made with no fanfare, far from the spotlight. Other times, a good day’s work is even sweeter when you realize someone noticed!
The importance of antibodies as tools in scientific research studies cannot be understated, yet these reagents have increasingly come under fire for their lack of reproducibility. Part of the issue is that the antibody market is composed of hundreds of vendors and resellers with varying definitions for validation and consistency. Cell Signaling Technology (CST) believes that antibody suppliers should be held accountable for the products they provide, but that vendors alone cannot solve the reproducibility “crisis." How antibodies are validated and used in the laboratory is a critical component to this process. Researchers need to be more attentive to following established protocols and leverage the expertise of the scientists who have developed and tested the product they are using. Journals need to be more active in enforcing existing policies regarding materials and methods or develop more clear-cut means to identify and describe the use of biological reagents in published research. During this webinar we will address the role vendors, researchers, and journals should play in minimizing irreproducibility. We will also outline CST’s antibody validation process, while highlighting steps all users should consider when selecting and using antibodies in their research.
A picture is worth a thousand words, or in the case of immunofluorescent imaging, a thousand proteins. The images used to illustrate a scientific experiment should convey as much information as the text itself. Here at CST, we pride ourselves in the quality of our antibodies and our rigorous validation process. When we approve our primary antibodies for IF, we like to showcase them using high quality images generated in-house. Beyond our recommended IF protocols (check it out here), here are some additional considerations to make when planning your IF staining.
If you’ve ever transitioned your IHC experiments from a manual protocol to an automated platform, you may have found the conversion process to be a drag. It isn’t an easy thing to do. For that reason, we’re happy to announce our IHC Leadership in Automation initiative. This rigorous validation initiative expands on our already thorough measures, allowing researchers to not only use CST products with our recommended manual IHC protocol, but also to bridge the assay to new platforms and techniques. Our foray into the world of automated IHC aims to reduce the amount of time researchers spend on assay transfer and protocol optimization.
After months of hard work, your research has honed in on a hypothesis you can test with immunofluorescence (IF). You've chosen antibodies and performed pilot IF experiments (see The Importance of Validation), and the localization of the protein appears reasonable. But how can you be sure the IF data you've acquired represents real biological phenomena? We present two examples of experimental controls in this post.
After months of hard work, your research has zeroed in on a hypothesis you can test with immunofluorescence (IF). But now you have to make a choice. How do you decide which antibody to use to get reliable IF results? How do you know if the images are accurately reporting the target's localization? We explore some considerations in this post.