Dr. Justin Siegel begins this episode by explaining what enzymes are, how they have evolved, and why Dr. Siegel is motivated to try to engineer enzymes to perform functions tailored to help humanity instead of to perform functions based on how they evolved in nature. He explains the primary goal of the work discussed and relating enzyme sequence to function. Dr. Siegel also explains how his work was the first of its kind by scaling up enzyme design to hundreds of mutants instead of dozens. 

We then dig into the details of Dr. Siegel’s work. We learn details of his study such as why his team chose to study the particular enzyme that was used to create a massive set of enzyme mutants. We hear the previous difficulty of doing a study like this on only one enzyme and what enabled this increase in the scale of enzyme design. We also hear about how the use of cloud labs was introduced into the project and why. 

Next, we hear all about the cloud lab aspect of this project. Dr. Siegel explains which parts of the enzyme mutant creation process were most challenging and benefited most to be moved to cloud labs. 

Finally, we learn about how machine learning was then applied to the large set of generated enzyme mutants. Dr. Siegel explains how the generated data allowed his team to test previous hypotheses about mutant enzymes and to start trying to predict the functions of enzymes from sequence. Dr. Siegel also comments on a finding of the paper that for highly conserved residues, if you change them, you lose the function. 

Learn more about Dr. Siegel’s work by reading the corresponding publication which you can find here: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0147596

Dr. Justin Siegel explains the past, present, and future of wet lab work and wet lab automation. We start by hearing a description of what it is like to work in a wet lab, covering the contrast between the excitement of seeing life changing results and the countless hours of monotony that is often involved to produce these results. 

We then begin discussing where automation will fit in to help alleviate the burden of long term monotonous work in the wet lab. We learn about the challenges of implementing automation in a lab, and hear about the dream that exists from the promise of automation versus the reality of implementing automation in an actual academic lab or in industry. We also hear Dr. Siegel’s take on the current state of implementing automation in an actual lab right now. We hear about the intricacies of implementing automation, such as discussing the pros and cons of different types of brands of robots, hearing about how lab robots can end up sitting unutilized or underutilized in academic labs, and considering practical questions that are involved when implementing automation. We end our discussion of robots that could be purchased with a discussion on Opentrons.  

Finally, we discuss cloud labs. Dr. Siegel starts by explaining what cloud labs are. Then, we hear about how a scientist would actually go about utilizing a cloud lab service. Dr. Siegel shares his thoughts on the potential promise of cloud labs and gives justification for the excitement surrounding this new approach. Dr. Siegel also shares his personal experience using cloud labs and how things like the accuracy and reliability of cloud labs can already make it a viable option for automating academic lab tasks. He also explains an unintended benefit of using cloud labs in that it allows researchers to spend more time thinking critically about the tasks that need to be done and how they will be done.

Dr. Afshin Beheshti begins this episode by explaining what microRNAs are and why they are emerging as an important area of biological research. He then explains how microRNAs relate to viruses, which is a recently developing area of research in this already young field of study. Dr. Beheshti then tells the story of how he started to discover that microRNAs could be a driver of COVID-19 infections. 

His story begins by using microRNA analysis tools to analyze COVID-19 infected patients from China which predicted a handful of microRNAs that could be involved in COVID-19 infection. He discusses how his team decided to focus on microRNA 2392 and how he continued to dig further into how it could be connected to COVID-19. His story then weaves through tales of successful collaborations with a large team of scientists that led to studying RNA samples from deceased COVID-19 patients, testing expressing the microRNA in healthy cells, analyzing multiple organs in COVID-19 infections, and testing a delivery system for a microRNA antagonist as a potential novel therapeutic.

We conclude with a quick discussion of the connection between microRNAs and space biology and space omics research.

Learn more about this work by checking out Dr. Beheshti's preprint on these topics: https://www.biorxiv.org/content/10.1101/2021.04.23.441024v4.abstract