Bio Eats World

You don't have to build a million planes to test a million aeronautical designs; we have mathematical simulations and models that do that for us. But in biology—once the class you'd take in high school if you loved science, but hated math—that's been impossible... until very recently. In this episode, Markus Covert, Professor of Bioengineering at Stanford, a16z deal partner Judy Savitskaya, and Bio Eats World host Hanne Winarsky, talk all about where we are in our ability to simulate and build models for how biology works. Because biology has been so qualitative in the past, and so complex, it's been extremely difficult to translate samples that are, say, gel smudges on a plate into the kind of qualitative data we need for these simulations and models. But we're finally reaching the “Google Maps” moment in biology, Covert says, beginning to be able to build models at the single molecule level, of genetic circuits, whole cells, the dynamic interactions between different cells, map them onto larger networks like tissue... even, of course, model on a global level the effects of a pandemic. The conversation covers Marcus’ story of the Eureka moment behind the first whole cell model; what this new ability to simulate and model will allow us to understand and predict that we haven’t been able to before; and why it all matters—how these tools are bringing us into a new era of designing new functionalities, even new kinds of biological life.

Descriptions of the mental illness we today call schizophrenia are as old as humankind itself. And more than likely, we are are all familiar with this disease in some way, as it touches 1% of us—millions of lives—and of course, their families. In this episode, we dive into the remarkable story of one such American family, the Galvins: Mimi, Don, and their 12 children, 6 of whom were afflicted with schizophrenia. In his book, Hidden Valley Road: Inside the Mind of an American Family, Robert Kolker follows the Galvins from the 1950s to today—through, he writes, “the eras of institutionalization and shock therapy, the debates between psycho-therapy versus medication, the needle-in-a-haystack search for genetic markers for the disease, and the profound disagreements about the cause and origin of the illness itself.” Because of that, this is really more than just a portrait of one family; it’s a portrait of how we have struggled over the last decades to understand this mysterious and devastating mental illness: the biology of it, the drivers, the behaviors and pathology, the genomics, and of course the search for treatments that might help, from lobotomies to ECT to thorazine. Also joining Robert Kolker and a16z’s Hanne Winarsky in this conversation is Stefan McDonough, Executive Director of Genetics at Pfizer World R&D, one of the genetic researchers who worked closely with the Galvins. The conversation follows the key moments where our understanding of this disease began to shift, especially with new technologies and the advent of the Human Genome Project—and finally where we are today, and where our next big break might come from.

One of the enduring mysteries of COVID-19 is why some people get a severe disease that can be fatal, whereas the majority experience a very mild or even asymptomatic disease. On this episode of the Bio Eats World Journal Club, host Lauren Richardson (@lr_bio) discussed this discrepancy with Dr. Helen Su of the NIH and co-leader of the COVID Human Genetic Effort. This international collaboration set out to investigate whether there is a genetic component to severe COVID and published the first of their findings in two articles in Science. Both papers demonstrate that dysfunction in a very specific part of the immune system leads to severe COVID, but through distinct mechanisms. We break down these results, how they can inform treatment, and how this collaboration was able to uncover these important findings in record time.

Dr. Helen Su, Chief of the Human Immunological Diseases Section at the National Institute of Allergy and Infectious Diseases (part of the NIH) and co-leader of the COVID Human Genetic Effort, joins host Lauren Richardson to discuss the results and implications of the articles "Inborn errors of type I IFN immunity in patients with life-threatening COVID-19" and "Autoantibodies against type I IFNs in patients with life-threatening COVID-19", both published in Science.

Move over microdosing, there is a new approach to psychedelic medicine. Psychedelics — like LSD and psilocybin — are some of the most powerful drugs that affect our brains, but their therapeutic potential has been limited due to their adverse side effects. This is where the work of today's guest, Dr. David Olson (@DEOlsonLab) of UC Davis, comes in. He talks to host Lauren Richardson (@lr_bio) about his lab's effort to develop new drugs based off the structure of psychedelics that retain their therapeutic properties, but that have better safety profiles, and that importantly, are non-hallucinogenic. The conversation covers his team’s recent Nature paper creating a non-hallucinogenic derivative of ibogaine, the evidence from animal models of its ability to treat depression and alcohol- and heroin-seeking behaviors, and the unexpected challenges facing the psychedelic medicine field.

David Olson, Ph.D, Assistant Professor at the University of California, Davis, joins host Lauren Richardson to discuss the results and implications of the article "A non-hallucinogenic psychedelic analogue with therapeutic potential" by Lindsay P. Cameron, Robert J. Tombari, Ju Lu, Alexander J. Pell, Zefan Q. Hurley, Yann Ehinger, Maxemiliano V. Vargas, Matthew N. McCarroll, Jack C. Taylor, Douglas Myers-Turnbull, Taohui Liu, Bianca Yaghoobi, Lauren J. Laskowski, Emilie I. Anderson, Guoliang Zhang, Jayashri Viswanathan, Brandon M. Brown, Michelle Tjia, Lee E. Dunlap2, Zachary T. Rabow, Oliver Fiehn, Heike Wulff, John D. McCorvy, Pamela J. Lein, David Kokel, Dorit Ron, Jamie Peters, Yi Zuo & David E. Olson, published in Nature.

with @lifelikephysics, @vijaypande, and @omnivorousread Where does life truly begin? How do we understand the fundamental nature of what is “alive” and what is “not alive”? In this episode of Bio Eats World, Professor Jeremy England discusses his new book, Every Life is on Fire, all about how what we might use physics to understand to be the origins of life—and how we define what being alive is. As biologists, we are taught that life evolved as the result of Darwinian natural selection. But what happens if instead, you use a physicist’s lens to examine what life looks to be—and define it as a specialized order and relationship between matter and the patterns of it’s an environment? England—a senior director in artificial intelligence at GlaxoSmithKline, principal research scientist at Georgia Tech, former associate professor of physics at MIT, and one of Forbes’ “30 Under 30 Rising Stars of Science”—describes this new idea as “dissapative adaptation”. The conversation covers how looking at “life” in these terms changes what we understand to be alive and what the nature of "life" is; sheds new light on the “queasy middle ground” between those definitions, especially in areas like machine learning and AI; and allows us to ask new questions about things like what makes DNA so special, and what life can do.