A day in the life of a microbiome scientist:
My day at the David lab consists of a lot of sample processing. Human fecal samples don’t just automatically go through a machine and become pretty strings of As, Ts, Cs, and Gs or numbers explaining their exact molecular makeup. Instead, I spend a few hours before lunch cycling through a series of steps including: adding various buffers to the samples, spinning them down, filtering them, incubating them, and transferring between many small tubes that had to be labeled earlier, and then spinning and transferring some more. In previous weeks, I was preparing samples for a machine called the HPAE which measures carbohydrate content, but this week, with my mentor out with our familiar foe Covid, I have been helping another lab mate do DNA extraction for his research. It can be a bit tedious, but after having practiced the process a few times this week I’ve become exceedingly more efficient and independent during the process, and can now perform a whole extraction myself. It’s also been an opportunity to talk to my lab members as we load and run samples almost out of muscle memory.
We then break for lunch, my favorite part of the day. Yes, I love food (especially the free food provided for lab meetings and other lab events!), but I also love getting to know my lab members. Most of us eat lunch together every day around the same time- something I’ve really come to appreciate as I get to know each of them better. They’re all exceptionally welcoming and helpful, as well as just really nice people to have random conversations with over Panda Express. After lunch, I finish up the rest of the processing and store the samples in the fridge to use later.
In the off time between sample spinning or when it’s too late to start a new batch of DNA extractions toward the end of the day, I hunker down at my desk and begin learning R. Because: what happens after all of these meticulously prepared samples go through their respective machine runs? That’s where data analysis comes in. While I have little experience with the software, many PhD students in the David lab are adept at using R to visualize and analyze data.
I follow online tutorials, resources provided by my lab mates, and use practice data files to play around with the software and figure out how to plot biological data. I’ve attached my earliest and proudest creations from such a session, but I’ve learned a lot since and hope to continue learning both wet lab and computational techniques moving forward.
