The molpigs Podcast

molpigs
The molpigs Podcast

Welcome to molpigs, the Molecular Programming Interest Group! molpigs is a group aimed at PhD students and early career researchers within the fields of Molecular Programming, DNA Computing, and other related specialties. We run most of our events in the form of podcasts, which you can find right here!

  1. ١٠ ربيع الأول

    molpigs Team: 4 years in the sty

    On this episode of the molpigs Podcast we introduce the new members of the molpigs team and re-introduce the long-term hosts, Boya Wang and Erik Poppleton. Hannah and Georgeos have stepped down from the podcast team, though Hannah continues to support us from behind the scenes. Joining us today are our two new members, Spencer Winter and Anuhya Edupuganti. On this episode we interview each other about why we're here, our strengths, our dreams, and why you should host boardgame nights at DNA conferences. A couple of factual errata:When Erik is talking about annealing ramps for DNA origami crystal assemblies, he says that they use a zigzag temperature around the nucleation temperature. In fact, they just ran extremely slow annealing ramps around the nucleation temperature (see the SI of the paper linked below)The word for the plant cellular structure that Erik can't remember is plasmodesmata, not desmosome. Links to the papers discussed in this episode:Anuhya's favorite paper: Isothermal self-assembly of multicomponent and evolutive DNA nanostructures by Rossi-Gendron et. al. (2023) https://www.nature.com/articles/s41565-023-01468-2Spencer's favorite paper: A deoxyribozyme-based molecular automaton by Stojanovic & Stefanovic (2003) https://www.nature.com/articles/nbt862Boya's favorite paper: Scaling Up Digital Circuit Computation with DNA Strand Displacement Cascades by Qian & Winfree (2011) https://www.science.org/doi/10.1126/science.1200520Erik's favorite paper: Binding to nanopatterned antigens is dominated by the spatial tolerance of antibodies by Shaw et. al. (2019) https://www.nature.com/articles/s41565-018-0336-3 Erik also mentioned a series of other papers which use similar ideas in nanopatterning to study biological systems:https://academic.oup.com/nar/article/48/10/5777/5827196https://pubs.acs.org/doi/full/10.1021/acsnano.0c10104https://www.nature.com/articles/s41565-020-0719-0https://www.biorxiv.org/content/10.1101/2023.12.29.573647v1https://www.biorxiv.org/content/10.1101/2022.06.08.495340v3 The papers on crystal assembly:https://www.science.org/doi/full/10.1126/science.adl5549https://www.science.org/doi/10.1126/science.adl2733 (edited) ---Find more information at the episode page here:https://podcast.molpi.gs/media/team2-aa6644d339dcddb0/

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    Zibo Chen: What's really cool is when it's functional and predictable

    In this episode of the molpigs podcast, Hannah, Boya and Erik talk with Zibo Chen, a new professor at Westlake University about his scientific journey through the world of biological information system design. We discuss how he went from designing DNA, to proteins, to entire cellular systems. Designing with different materials requires different design and modeling methods. We also take a look to the future and how he plans to take protein-based neural networks from living cells to synthetic cells. Further Reading:"A cargo sorting DNA robot" - https://www.science.org/doi/full/10.1126/science.aan6558?rss=1="Programmable design of orthogonal protein heterodimers" - https://www.nature.com/articles/s41586-018-0802-y"Confirmation of intersubunit connectivity and topology of designed protein complexes by native MS" - https://www.pnas.org/doi/full/10.1073/pnas.1713646115"A synthetic protein-level neural network in mammalian cells" - https://www.biorxiv.org/content/10.1101/2022.07.10.499405v1.abstract"De novo design of modular and tunable protein biosensors" - https://www.nature.com/articles/s41586-021-03258-z --- Zibo Chen is an assistant professor in the School of Life Sciences at Westlake University. He received his Ph.D. degree in biochemistry in the labs of David Baker and Frank DiMaio at the University of Washington and worked on mammalian synthetic biology with Michael Elowitz at Caltech as a Damon Runyon Fellow. His work focuses on programming biology using proteins as the coding language. He has received a number of awards, including the Robert Dirks Molecular Programming Prize, and was included in Forbes 30 Under 30. Outside of the lab, Zibo is an instrument rated pilot and enjoys flying around in a small Cessna. ---Find more information at the episode page here:https://podcast.molpi.gs/media/chen-z-b52941b1a263e1a2/

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    Ashwin Gopinath: Merging top-down and bottom-up synthesis

    On this episode, the molpigs team talks with Ashwin Gopinath about bridging size scales in nanomaterial size scales. We explore his journey from optical physics to learning DNA nanotechnology in the Rothemund lab and his current projects and vision for highly multiplexed molecular measurements. Ashwin's career path has been quite the adventure, starting in academia, working for Google and then starting and later selling his own company. Finally, we turn to ways that AI is going to change research and the impending death of the current grant-funding structure. His excitement for scientific progress, perspective on different work environments and creativity in research is always inspiring for scientists young and old. The paper Ashwin mentions on developing new AI capabilities can be found here: https://arxiv.org/abs/2303.11366 --- Ashwin received his PhD in Electrical Engineering from Boston University, working on devices for detecting and characterizing single biomolecules. Challenges he encountered during this motivated him to switch focus from optical physics to DNA nanotechnology, leading to a postdoc under Paul Rothemund at Caltech. After working briefly for Google X, he is now an Assistant Professor at MIT. He has received the Robert Dirks Molecular Programming Prize for his work combining DNA nanotechnology with conventional micro-fabrication. ---Find more information at the episode page here:https://podcast.molpi.gs/media/gopinath-a-e8cafaf0680033a7/

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    Erika DeBenedictis

    This week’s podcast is with Erika DeBenedictis, a new principal investigator who is founding her lab at the Crick Institute in London. Her lab will focus around the broad field of bioautomation, but before talking about any of that, we delve into her past. Erika is just another one in a long string of podcast guests who has had an unconventional entry into the field of molecular programming! She started her scientific career interested in space science, telling us that her interest was kindled as a child because of the accessibility of this field to anyone. This led her to work at NASA’s Jet Propulsion Laboratory. Afterwards she talks about her time as a PhD student in Kevin Esvelt’s lab working on massively parallelised directed evolution, harnessing the power of robotics in order to develop her technique known as PRANCE. She talks about the use of these techniques in expanding the genetic code, and the main hurdles in doing so. We then move on to her post-doc at David Baker’s lab in Washington, where she worked on using machine learning for de novo protein engineering. At the same time we talk about the place of robots in modern laboratories, whether they will replace all hand pipettes (and wet lab scientists!), and the feasibility of cloud laboratories in making science more accessible. Finally we move on to the start of Erika’s new lab at the Crick Institute, her vision for what she wants to do, and ultimately the bioautomation challenge, which is a programme spearheaded by her to get bioautomation equipment into more laboratories to accelerate research. --- Erika began her science career as a computational physicist and astronomer and worked on space mission design at NASA’s Jet Propulsion Laboratory. She received a BS in Computer science from Caltech in 2014. She then worked at Dropbox as a software engineer and at D. E. Shaw Research on computational biophysics. She received a PhD in Biological Engineering from MIT in 2020, working with Kevin Esvelt. Erika’s research focused on developing techniques for robotics-accelerated evolution (PRANCE) and applying these techniques to quadruplet codon genetic code expansion and origin of life research in E. coli. Her postdoc in David Baker’s lab at the Institute for Protein Design at the University of Washington focused on using machine learning techniques to systematically engineer de novo proteins. In 2022, she launched the Bioautomation Challenge, a program designed to make experimental life science more reproducible, scalable and sharable by giving researchers access to programmable experiments. She now leads the Biodesign Laboratory at the Francis Crick Institute in London, UK. ---Find more information at the episode page here:https://podcast.molpi.gs/media/debenedictis-e-59f6feebc1495d48/

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Welcome to molpigs, the Molecular Programming Interest Group! molpigs is a group aimed at PhD students and early career researchers within the fields of Molecular Programming, DNA Computing, and other related specialties. We run most of our events in the form of podcasts, which you can find right here!

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