The Bioinformatics and Beyond Podcast

Leo Elworth

Hear from the leading experts in bioinformatics and other closely related fields. Topics discussed include computational biology, biotechnology, computer science, genetics, synthetic biology, math, statistics, and more. You can also find discussions on topics related to the scientific career field. For example, exploring career path options in science, or highlighting important skill sets such as writing and public speaking.

  1. 10/23/2021

    Dr. Justin Siegel: Enzyme Design, Large-scale Mutant Generation, and Cloud Labs

    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

    22 min
  2. 10/09/2021

    Dr. Justin Siegel: Lab Automation, Cloud Labs, and the Future of the Wet Lab

    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.

    33 min
  3. 08/28/2021

    Dr. Afshin Beheshti: The Hazards and Molecular Features of Spaceflight

    This episode concludes the podcast’s series of episodes focused on space biology and space omics. NASA scientist Dr. Afshin Beheshti discusses the many high level hazards and corresponding molecular features of spaceflight throughout this episode. For instance, we begin with a discussion of the hazards of radiation and microgravity. Dr. Beheshti spends time explaining a high level view of what each hazard is, why it is a concern for spaceflight, and educates us on many useful and interesting pieces of information for each hazard. Further hazards discussed include confinement and isolation, hostile and closed environment, and distance from Earth. After learning about all the high level hazards of extended living in space, we learn about how these hazards cause issues to human health through a series of lower level biological features. Dr. Beheshti again explains what these fundamental molecular features are, what techniques we have to study them, and ways we could overcome these problematic processes. These problematic molecular features include oxidative stress, DNA damage, mitochondrial damage, epigenetic and gene regulation changes, telomere-length dynamics, and microbiome shifts.  We end by discussing how we can simulate and study the negative effects of space here on Earth and the future of spaceflight biology research. Dr. Beheshti explain how studies like "bed studies" and mountain climber studies can help simulate impacts on human health in space. Finally, I ask Dr. Beheshti for his view of the future. He explains NASA's surveys that can guide research and how omics research was identified as a future focus. We conclude with a discussion on the plan for Mars exploration and habitation. For additional reading on this topic, check out Dr. Beheshti's recent Cell review: https://www.sciencedirect.com/science/article/pii/S0092867420314574

    49 min
  4. 07/17/2021

    Wet Lab / Dry Lab Transitioning with Dr. Willian da Silveira

    For people who work in the life sciences, a very common occurrence is for folks who work on the "wet" side of research, largely doing bench work, to become interested in or start wanting to transition to doing more "dry" research, like computational research in bioinformatics. In this special episode, dedicated to those thinking about transitioning from "wet" lab work to doing more "dry" lab type work, my guest Dr. Willian da Silveira explains his own transition from a full bench scientist to a full time bioinformatician. Dr. da Silveira also answers many questions from the bioinformatics subreddit on this topic. Following Dr. da Silveira's explanation of his career trajectory and his own shift from "wet" lab work to "dry" lab work, I ask a series of questions from the bioinformatics subreddit seen below, with time stamps included: [19:00] Bioinformatics subreddit questions begin. [20:00] What general stats and technical requisites are necessary to transition from wet lab to dry lab work? [23:30] Is it boring to only do data analysis versus conducting lab experiments? [27:50] Should you transition early, for example during a masters or PhD program, or can it be done later? [33:30] Does the transition need to be forced or does it happen more often by chance? [35:10] Is there a downside to being self-taught as a bioinformatician? [36:20] What are the upsides of picking up bioinformatics later on, starting as a wet lab scientist first? [40:25] How to get accepted into a bioinformatics PhD program with no formal CS education? [42:07] What about dry lab to wet lab transitioning? [48:07] How do you get your foot in the door when switching from the wet lab to a dry lab with little or no dry lab experience on your CV? [50:45] If you do feel stuck, would the best route be to go ahead and pick up some formal education like a paid masters degree? [52:48] Would it make sense to transition to dry lab work given employment and financial considerations? Finally, to end the discussion, I ask Willian what he thinks the ideal mix of wet lab and dry lab experience might look like.

    1h 2m
  5. 07/03/2021

    Dr. Willian da Silveira: The Mitochondria as a Central Hub for Spaceflight Impact

    In this episode we begin discussing the biology of spaceflight with Dr. Willian da Silveira. We start by hearing the story of how Dr. da Silveira's recent high profile space omics paper (https://www.cell.com/cell/pdf/S0092-8674(20)31461-6.pdf) came to be. He first describes the NASA GeneLab and how he got involved, and how his story of this paper began with an analysis of some liver transcriptomics data. We hear about all the different types of data used in this study, including epigenetics and metabolomics data. Dr. da Silveira discusses how to try to incorporate and work with this many types of data all at the same time. He then further elaborates and explains data like epigenetics and metabolomics.  After discussing all the different types of data, and how to try to analyze all the data together, Dr. da Silveira talks more about the biological side of some of the data, for instance discussing rodent data and human cell lines. Finally, we discuss the results of his paper and how all the data analysis point to a central hub of the impact of spaceflight, with mitochondrial stress acting as this central hub. We conclude with a discussion of the principal risks to humans when they go to space and what Dr. da Silveira sees coming for the future of space omics research. Link to Dr. da Silveira's recent publication: https://www.cell.com/cell/pdf/S0092-8674(20)31461-6.pdf Link to spaceflight impact review paper mentioned: https://pubmed.ncbi.nlm.nih.gov/33242416/

    47 min

Ratings & Reviews

5
out of 5
10 Ratings

About

Hear from the leading experts in bioinformatics and other closely related fields. Topics discussed include computational biology, biotechnology, computer science, genetics, synthetic biology, math, statistics, and more. You can also find discussions on topics related to the scientific career field. For example, exploring career path options in science, or highlighting important skill sets such as writing and public speaking.