At BenchSci, while we work hard to design and develop the platform, it is equally important for us to understand what researchers think about our work.
For the BenchSci Case Study series, we reach out to researchers on the platform on a regular basis to learn about their thoughts on BenchSci.
Read on to find out what they have to say!
Researcher: Marmendia Meester, Graduate Student, University of Toronto
Marmendia Meester is a graduate student at the University of Toronto. Her project focuses on unravelling oxygen-independent protein folding pathways in the context of tumor hypoxia. Besides her lab you can regularly find her dancing Forró at the Cumberland House, dancing Zouk on Bloor st. West and working out at Hart House. Also, she frequently attend socials and workshops at the Grad Room.
Research: Protein Folding Factors that Interact with ER Cargo
Meester is studying protein folding factors that interact with ER cargo during anaerobic protein folding, with specific interest on factors that facilitate oxygen-independent disulfide bond formation. “My project requires me to constantly look for antibodies against protein folding pathways,” she says. “I pay special interest to the epitope a specific antibody was raised, as I am working on recombinant proteins myself.”
Challenge: Underreporting
Meester’s biggest challenge with antibodies: underreporting. “The materials and methods sections in scientific articles become more brief as word limits are applied,” she says. “Not only are we shown the best images of results obtained with the stated antibodies, but optimization details are more commonly omitted.” These include things like dilution ratios, diluents used, incubation times, and temperatures.
Considering it is already quite laborious to find papers that use antibodies targeting proteins of interest, Meester finds it especially disappointing when authors omitted details that would have made optimization easier. “It would be incredibly helpful if there is already information available in which applications antibodies were used (especially since manufacturers only report positive outcomes within their own protocols), so I can focus on reviewing the papers.”
Several Thousand Dollars in Antibodies—and Lots of Time
The impact of this challenge: Time and money.
A single testing vial of an antibody easily costs $500, says Meester. On average, she tests 2-3 antibodies per protein, per application. This easily exceeds several thousands of dollars without taking into account the cost of disposables used for repeat experiments.
Being a graduate student, her time is precious. “I primarily perform co-immunoprecipitations, western blots, and immunofluorescent experiments,” she says. “These experiments easily take 2-3 days each; rogue antibodies can therefore easily cost months of research without leading to a tangible result.”
For example, one co-immunoprecipitation protocol cost her half a year of trial-and-error with an antibody that was reported by the manufacturer to be suitable for her application. “I have now switched to another antibody and will be repeating the optimization process yet again,” she says.
Solution: Diverse Reporting Frequency—and BenchSci
To address this challenge, Meester tries to use antibodies that have been used in different labs for the same application, which usually leads to finding a robust antibody that is applicable in various conditions within an application. “In short, I use the amount of times reported as a marker for the rigidity of an antibody,” she says. “This overcomes challenges in optimization due to minor variations in laboratory protocols for specific applications.”
Next, she prefers to choose antibodies reported in publications over manufacturer-recommended antibodies. “I would assess the quality of the results as seen in the Results section of the papers, and then note the details as reported in the Materials & Methods section,” she says.
Shortening Days of Work to Minutes
BenchSci allows her to get a quick overview of the antibodies available for her application and protein of interest, as well as the amount of times a specific antibody has been reported both by manufacturers and researchers. “In addition, I can easily find the images that display results obtained from the specific antibody without having to skim through numbers of pages,” she says. “It makes the initial shortlisting of candidate antibodies a lot easier.”
Such a process normally took her hours to days, but it’s shortened to half an hour—tops—with BenchSci. “Up until now the antibodies I purchased from my first search on BenchSci have lead to an optimized protocol and tangible results,” she says.
The Power of Filters
When asked about her favorite BenchSci feature, Meester doesn’t hesitate. “Filters,” she says. “I can’t stress enough how easy my antibody search becomes by applying filters.”
But hastening antibody search isn’t the only benefit of filters. Sometimes, Meester’s interested to see how Western blots of a particular protein look, without really being interested in the antibody that has been used. “I search my protein of interest, filter for the cell line I use and for Western blots, and the output contains loads of images that give me information on what to expect when I perform a Western blot for this particular protein in lysates of my cell line,” she says.
If a user gets creative enough with filters, she says, BenchSci can be a great tool for a variety of questions regarding antibody-based applications.
Have you tried out BenchSci for your antibody search? In what ways has BenchSci helped with your research? Let us know in the comments and we would love to chat with you for our next article!
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