Chemiluminescent images with standard cameras

I work with proteins, so I’ve done Western blots throughout my career. Originally that meant using film and developers, and later with imagers. Imagers are way better than having to deal with film, so as soon as I knew I was going to start up a lab, I started looking at various imagers and quoting them out. Even the most basic imagers with chemiluminescent capabilities quoted in the $24-27k range. But then it dawned on me….. are these imagers nothing but kind of old cameras with a light-proof chassis and dedicated acquisition and analysis software? During my stint in Seattle, I dabbled with taking some long-exposure photography of stars in my parents back yard. Perhaps I could do something similar for taking images of blots?

I had bought an Olympus E-PM2 16.1MP mirrorless camera for $320 back in 2014. While I used it a decent amount at first, I eventually stopped using it as often as I started using my smartphone for quicker snaps, while using Anna’s Nikon DSLR with an old telephoto lens for more long-distance pictures. So, with the E-PM2 now not doing much at home, I figured I’d bring it in and try it with this. I cut out a hole in the top of a cardboard box I could stick the camera into. I dug up the intervalometer I had used for those long-exposure photos of the sky. Nidhi had been doing some western blots recently, and had kept her initial attempts in the fridge, which was good since I could just grab one of those membranes instead of running and transferring a gel just for this. I kept it in some anti beta-actin HRP antibody I recently blot, washed it, and exposed.

OLYMPUS DIGITAL CAMERA

Above is something like a 5 minute exposure. So my cardboard box wasn’t perfectly around the sides, so there’s a decent amount of light bleeding in. I had the blot lifted up within the blot on a metal pedestal (some heat-blocks that weren’t being used), so the blot itself is actually pretty free from being affected by the bleed-over light. Notably, the beta-actin bands are blue! Which makes sense, as if you’ve ever mixed bleach with luminol, you see a flash of blue light. Furthermore, if you google “hrp luminol nm”, you see that the reaction should emit 425nm light (which is in the Indiga / violet range). Notably; this would be a difference between my regular use Olympus camera, which is a color camera, with cameras you’d normally encounter on equipment like fluorescent cameras, which are normally black-and-white.

I had actually been playing around a bit with image analysis in python over the last week or so (to potentially boot up a automated image analysis pipeline). That work reminded by that color images are a mixture of red-green-blue. Thus, I figured I could isolate the actual signal I cared about (the chemiluminescent bands) from the rest of the image by keeping signal in the blue channel but not the others. So I wrote a short python script using the scikit-image, matplotlit, and numpy libraries and ran code to isolate only the blue image and convert it to greyscale, and to invert it so the bands would appear dark against a white background.

To be honest, the above picture isn’t the first ~ 5-minute exposure I mentioned and showed earlier. Knowing this seemed to be working, I started playing around with another aspect that I thought should be possible, which was combining the values from multiple exposures to make an ensemble composition. The reason for this being that a single large exposure might saturate the detector, making you lose quantitation at the darkest parts of the band. I figured why couldn’t one just take a bunch of shorter exposures and add them up in-silico? So I took five one-minute exposures. The above image is the inverted first image (with an exposure of one minute).

And the above image here is what it looks like if I make an ensemble plot from 5 separate 1-minute exposures. With it now effectively being a “longer exposure” (due to the combining of data in silico), the signal over the background has been improved, with no risk of over-saturating any of the detectors.

So while I’m sure there are many suboptimal parts of what I did (for example, the color camera may have less sensitivity for looking at chemiluminescent signals), it still seemed to have worked pretty well. And it was essentially free since I had already had all of the equipment sitting around unused (and would have cost < $400 if I had to buy them just for this). And also gave me a chance to look under the hood of this a bit, practice some python-based image analysis, and prove to myself that I was right.