28 episodes

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!

The molpigs Podcast molpigs

    • Education
    • 5.0 • 1 Rating

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!

    Viktorija Glembockyte: Light-based diagnostics

    Viktorija Glembockyte: Light-based diagnostics

    On this episode the molpigs team talks with Viktorija Glembockyte, a postdoc in the Tinnefeld lab at Ludwig-Maximilians University. Her research focuses on how we can make highly sensitive diagnostic tools for a variety of biomolecules using DNA origami to merge sensing with signal amplification. She describes how her scientific and management skills have grown from her time in a hardcore chemistry lab, to now starting her own independent group.

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    Viktorija Glembockyte did her bachelors in chemistry at Jacobs University Bremen and her PhD with Gonzalo Cosa at McGil University before joining the lab of Phillip Tinnefeld at Ludwigs-Maximillians University to work on modular nanosensors based on DNA origami where she developed multiple modular platforms for single-molecule biosensing. She is now a junior group leader at LMU and is currently planning her next career move later this year.

    ---Find more information at the episode page here:https://podcast.molpi.gs/media/glembockyte-v-dac88fee5420473b/

    • 52 min
    Jacob Majikes: The boring, basic details of molecular programming

    Jacob Majikes: The boring, basic details of molecular programming

    On this episode the molpigs team talks with Jacob Majikes, the ‘boring materials physics’ expert of the DNA origami field. We discuss the incentive structures of the field, Hatch Act violations*, and how guinea pig bedding relates to biologics production. He explains to us how the National Institute of Standards and Technology became interested in DNA origami and how defining ‘yield’ of a structure is a more challenging problem than you would expect. He also shares the excitement and challenges of organizing FNANO, one of DNA origami’s annual conferences, and how he thinks the conferences will develop into the future.

    * Jacob is not entirely sure on his description of the Hatch Act!

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    Jacob Majikes is a Research Scientist in the Microsystems and Nanotechnology Division of NIST. He received his B.S. and Ph.D. in materials science and engineering from North Carolina State University. His doctoral research focused on probing the folding/assembly of DNA origami nanostructures. Jacob is working with Alex Liddle to develop metrics to quantify the yield of discrete DNA nanostructures and to understand the effect of structure design on yield.

    ---Find more information at the episode page here:https://podcast.molpi.gs/media/majikes-j-24e8817ee9f1e8e6/

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

    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

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    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/

    • 45 min
    Ashwin Gopinath: Merging top-down and bottom-up synthesis

    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

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    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/

    • 47 min
    Katherine Dunn

    Katherine Dunn

    Join the molpigs team for a discussion with Prof. Katherine Dunn from the University of Edinburgh about her work on using DNA nanotechnology for medical applications and her exciting new ideas regarding "electrosynbionics," using biological engineering to tackle hard problems in energy production and storage. She also discusses her experiences transitioning from terahertz spectroscopy to biophysics and the challenges in teaching and mentoring students to prepare them for a variety of career paths in today's interdisciplinary world.

    Katherine completed her undergraduate degree in physics at the University of Oxford. She started a PhD there in Terahertz Spectroscopy before seeing the light and changing to DNA Origami. She has continued to study molecular programming within an engineering context, working on DNA nanomachines for bioelectronic computing at the University of York. She is now a Senior Lecturer at the University of Edinburgh, and has been named as one of the Top 50 Women in Engineering 2021 by the Women’s Engineering Society.

    ---Find more information at the episode page here:https://podcast.molpi.gs/media/dunn-k-68bc3b6fe46f8f0d/

    • 47 min
    Erika DeBenedictis

    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/

    • 58 min

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