The Life Cycle of a Scientific Technique: A Relatable Guide

Today, scientific techniques come and go faster than ever. What is cool today will not fly tomorrow, not even in a thesis!

Examples include “suicide PCR“, a clever technique that is now very niche, and ethidium bromide, which some labs still use but are increasingly replacing.

This article provides a humorous overview of the method lifecycle, which I hope you will find relatable.

Stage 1: You Hear About It from a “Very Cool Guy” from MIT at a Conference

The technique looks complicated (and expensive), but the results are great. You want to try it, but your boss tells you to concentrate on your western blots instead…*yawn*

Stage 2: Somebody used it in Cambridge, England

Your boss reviews the manuscript and asks for your opinion. You give a glowing review, but your boss is not so sure and points out in his (final) review that it is susceptible to artifacts. Why DO you bother suggesting anything…

Stage 3: The Lab Next Door Starts Using It

You discover that the postdoc positions you are interested in list the technique in the job ad under “optional” skills.

Better start asking around for a demo so you can at least pretend you know what you’re talking about…

Stage 4: You FINALLY get The Boss’s Permission to Use the Technique

Job ads start listing the technique as essential, so you put it on your CV. After all, how are you meant to get experience in something if you need experience to get the job?

You consider inventing time travel so that you can get your hands on this technique before you’re revealed to be a fraud.

Alternatively: A respected, prominent researcher gives a presentation at your institute, calls the technique outdated nonsense, and presents a newer, more expensive technique to replace it. You go back to Stage 1 and start the cycle all over again.

Stage 5: Undergrads Start Using It

Undergrads start using it in the lab for their projects. In fact, you attracted these very undergrads by listing the method in the project description.

However, the method requires so much optimization and general technical skill that a student has no chance of getting worthwhile results.

You show the undergrad how to do it once “as advertised.” She tries to repeat it and fails, briefly reconsidering whether a scientific career is for her. You start to wonder too…

Stage 6: The Beginning of the End

Somebody publishes a paper showing that the technique can produce artifacts under certain conditions, including the one you are using. You tell your boss that you’d like to stop using it, but he pushes for results.

You spent a lot of time and grant money optimizing this pointless method you no longer believe in. You mention the results in your paper as “data not shown…”

Stage 7: Exile

The technique has such a bad reputation that nobody, including you, wants to use it. You claim you knew it was nonsense all along, and you get rid of any evidence that suggests you said otherwise.

Stage 8: Nobody Even Remembers Using It

Five years on, people look at you bemused when you try to tell the story of your struggles with the method, and you try to encourage new starters to use it when everything else fails.

When they don’t take the bait, you mumble, “kids these days…” and go read our article, “Spare a Thought for the Old Scientist.“

You immediately feel better, realizing no one is immune to the passage of time, and life goes on regardless.

In Memoriam: An Author Retrospect

When I first wrote this, I reckoned I’d watched the cycle play out for cloning into phage lambda (I caught the tail end of stage 6 myself), 2D gels, microarrays, and LC-MS.

So, where are they now? Their lifecycles turned out completely differently:

• Lambda cloning is now far less common in routine molecular biology workflows, though I still have the war stories
• 2D gels were pushed out of much mainstream proteomics but hang on in specialized uses
• Microarrays lost much expression-profiling work to RNA-seq, yet still earn their keep in certain research and diagnostic applications
• LC-MS became a core workhorse across proteomics, metabolomics, lipidomics, pharmaceutical analysis, and beyond

The last example shows that a technique doesn’t always go straight from “hot” to “obsolete.” Sometimes they stubbornly hang around for decades (like a bad lab smell…check out our article on that next)