Biohub is building imaging tools across biological scales

Transcript

Transcribed by machine (Whisper) from the episode’s audio, so a word may be off here and there.

1. 30:32

   How do you think about that challenge and what are the techniques you think are kind of most promising to get over those humps? Yeah, it's a really great question. I think it really gets to, you know, what is so hard and so difficult about this problem. It's that there's, it's really a multi-scale problem and complexity down to the molecular level can influence events of the macro scale, right? A single point mutation in a gene can cause disease.

2. 31:04

   And so you really ultimately are going to need to have an understanding that bridges those vast divides. scale. And it is a technology problem. I think it is very much a technology problem. I think in the near future, kind of the ability to identify the entire system down to the molecular level is not possible. You know, maybe someday in the future, you know, something like that would be possible. But, you know, today we can, we can look at, we can look at tissue, we can look at cells within tissue. And I think, so we can see that kind of mesoscale of the cellular biology.

3. 31:52

   But what I, what I do think is, you know, we can use, we can use these informational principles to bridge the gap because if we, I think you have to be clear, you know, when I talk about the cell and I talk about a model of the cell, I don't mean the cell in isolation. And, you know, biologists, they do often think about, you know, the cell in isolation and culture systems. They think about, you know, these kind of laboratory proxies for in situ biology. But, you know, I think that a real complete model of the cell, you know, it would have to include the the understanding of the cell in its context in, in these living systems, because, you know, living systems are, are created by the interaction between cells and, you know, really in a certain sense, you know, the interfaces that they have with each other, the input output relations and

4. 32:52

   the, and the transitions and state that they can undergo. So I think you can learn a lot kind of at this mesoscale that's going to be really, really informative to kind of the complete picture of the system. But you really have to think about the complexity levels. And so you can think about the complexity of the cell in isolation. And that's going to be really valuable because, you know, so you can learn a great deal about cellular biology from, you know, a cell in culture, from cells that are transformed. They may be very different from the states of cells in in situ and tissue but they still you know they still have those that core machinery and those core programs right and so you can learn a lot about them you know even even if you're looking at the cell kind of in a very and a poor proxy like like a culture system but but we can

5. 33:44

   learn even more if we start to really look at the cell yet at that next level of context where we can see it in tissue or systems. And, you know, we're really working to address those kind of gaps, right? So at Biohub, we have an imaging institute that's really kind of building technologies at each of these complexity levels. So, you know, the laser phase plate is kind of opening up the atomic resolution view, but you can really only see that for a part of the cell.

6. 34:16

   You know, it's not going to give you the picture for an entire tissue. We're building technologies that allow us to... kind of fields of cells to be able to perturb those cells, understand their responses, and measure that statistically across many cells in culture. And then we're also, you know, really developing whole organism level imaging, which is really incredible. And so we do a lot of work with zebrafish, which are, you know, transparent fish, which means you can really image, you can image them and you can actually see every single cell. And so we have microscopes that allow us, for example, to track a developing zebrafish embryo over time and actually see and track every single cell, how that system goes from one cell all the way to a fully developed organism. We have systems where you can label different cell types. So for example, all the

7. 35:15

   immune cells. So you can look in a living fish and track and follow all the immune systems and see how they move and traffic and interact with each other and the surrounding tissue. So I think it's possible to get information at each of these different scales. And then what you really need to do is kind of build that model that can integrate across the hierarchies of biological complexity. Hey, we'll continue our interview in a moment after a word from our sponsors. The Cognitive Revolution is brought to you and powered by Tasklet. I've been running