Today we cover Cytosis, a worker-placement game about cell biology from Genius Games. This is one of our all-time high scorers, with both excellent science and excellent gameplay. Join us for a tour de cell as we go through the nucleus, endoplasmic reticulum, Golgi, mitochondria, and cell membrane, plus gush over how cute kinesins are and argue about whether bacteria have organelles. Find our socials at GamingWithScience.net #BoardGames #Science #CellBiology #GeniusGames #Cytosis #Protein #RNA #DNA #Hormones Timestamps: 00:51 - Protein sequencing03:54 - Intro to Genius Games06:50 - Intro to Cytosis12:48 - Cells & their parts16:06 - RNA & ribosomes20:22 - Endoplasmic reticulum, Golgi, & hormones24:48 - Mitochondria & glucose transport27:11 - Learning from the game28:40 - Bacteria30:58 - Inconsequential nitpicks36:11 - Final grades Links: Official Website (Genius Games)Reverse Translation (preprint)Video of John ConveyouOrganelles of a Euakaryotic cell (Wikipedia)Kinsesin motor proteins Full Transcript: Jason 0:00 Music. Hello and welcome to the gaming with science podcast where we talk about the science behind some of your favorite games. Brian 0:12 Today, we're going to discuss Cytosis by Genius Games. Hey, I'm Brian. Jason 0:21 This is Jason. Brian 0:23 Welcome back to Gaming with Science. Today, we're going to talk about Cytosis, a cell biology game. It was a game designed by John Coveyou by Genius Games. I don't know why it's taken us this long to do a Genius Games game, considering they are specialists in hard science games, and they seem to share the exact same core values as gaming with Science. I know this is our first. I'm sure it won't be our last. But anyway, before we get into that game, Jason, do you have anything for us to banter about? Jason 0:51 Well, I like the science topics, and you actually pointed me out to one that's related to this, which is a preprint. So you've got publications in final journals, but you also these things called Preprints, which is where you post your paper up before it's been peer-reviewed, so you can get the results out. You can kind of stake a claim to it. But according to their preprint, they've developed a way to do not quite reverse translation, but something similar. So we're going to talk about this more later today, where translation is where you take the genetic information from a cell and turn it into protein, and it's generally a one way street. You can't go back, but this group has developed a method to, not so much go backwards, but at least to take the proteins apart in such a way that it's encoded in DNA that they can then sequence and get back out. And this is really cool, because we're really good, like we as a field, science is very good at sequencing DNA right now. DNA sequencing in some form, has been around for 40, 50, years, but high throughput sequencing has been around for at least 20 years now. Ee're very, very good at it now. In fact, we're astonishingly good at how much DNA we can sequence. We suck at sequencing proteins. It can be done. It's like, don't get me wrong, there are methods to do it, but compared to what we can do with DNA, it's slow, it's expensive, it's hard, and I don't know that this method really solves all of those problems, but it potentially gets rid of some of them. And if we can find a way of turning proteins, protein information, into DNA information, and just hooking into the existing DNA sequencing infrastructure, that could open up whole new ways of looking at biology, looking at things, because most of the time, it's the protein that matters. We look at the DNA because the DNA is easy, but most of that, one way or another, ends up in a protein, either directly or by changing which proteins are around. And so being able to look at the proteins more directly gives us a lot more information about diseases, about things that in plant science we care about, like crop production or disease resistance. It's like there's a really cool thing that could open up there. And so even if this group doesn't work out, I hope someone manages to, like, build off of this and make it work. Brian 3:00 This is the first time I've seen a preprint, and be like, someone's going to get a Nobel Prize for this idea. Maybe not this group, but somebody's going to get this to work, and somebody's going to have a Nobel Prize for this. I mean, the whole idea about DNA. Why are we so good at doing DNA? Because DNA is set up to make copies of itself, right? You can take a very small amount of nucleic acid and using a process called the polymerase chain reaction, generate massive amounts of DNA. You can go from one molecule to a billion in a couple of hours. So you could start from a low amount of material and work up to a huge amount of material. But proteins don't do that right? It's one direction. So the only way to read the proteins out is you just make more and more and more sensitive instruments. It's ...
