Podcasts about transposons

A marcha solitária do Estado sem controle https://www.estadao.com.br/opiniao/fernando-gabeira/a-marcha-solitaria-do-estado-sem-controle/ (via ChatGPT) Introns, Transposons, Introners https://chatgpt.com/share/683075ed-4298-8006-9607-e865cc448d2e Hōryūji, the world's oldest wooden architecture https://youtu.be/n9ZKdmKpSNQ?si=yd1G46QHqtRcPSJx This Is Not The Buddha (yet) https://youtu.be/3KRqbZ1hiLk?si=hCrrzGU4-8pri_HJ Mozilla dará fim ao Pocket, serviço de “ler depois”, em julho deste ano http://macmagazine.com.br/post/2025/05/22/mozilla-dara-fim-ao-pocket-servico-de-ler-depois-em-julho-deste-ano Honeybees are getting confused by electric pollution from power lines http://newscientist.com/article/2480997-honeybees-are-getting-confused-by-electric-pollution-from-power-lines Did Climate ... Read more The post o Buda que é ou não é o Buda! o Nemo encolheu! ChatGPT é um puxa-saco? appeared first on radinho de pilha.

When I think of digital biology, I think of Patrick Hsu—he's the prototype, a rarified talent in both life and computer science, who recently led the team that discovered bridge RNAs, what may be considered CRISPR 3.0 for genome editing, and is building new generative A.I. models for life science. You might call them LLLMs-large language of life models. He is Co-Founder and a Core Investigator of the Arc Institute and Assistant Professor of Bioengineering and Deb Faculty Fellow at the University of California, Berkeley.Above is a brief snippet of our conversation. Full videos of all Ground Truths podcasts can be seen on YouTube here. The audios are also available on Apple and Spotify.Here's the transcript with links to the audio and external links to relevant papers and things we discussed.Eric Topol (00:06):Well hello, it's Eric Topol with Ground Truths and I'm really delighted to have with me today Patrick Hsu. Patrick is a co-founder and core investigator at the Arc Institute and he is also on the faculty at the University of California Berkeley. And he has been lighting things up in the world of genome editing and AI and we have a lot to talk about. So welcome, Patrick.Patrick Hsu (00:29):Thanks so much. I'm looking forward to it. Appreciate you having me on, Eric.The Arc InstituteEric Topol (00:33):Well, the first thing I'd like to get into, because you're into so many important things, but one that stands out of course is this Arc Institute with Patrick Collison who I guess if you can tell us a bit about how you two young guys got to meet and developed something that's really quite unique that I think brings together investigators at Stanford, UCSF, and Berkeley. Is that right? So maybe you can give us the skinny about you and Patrick and how all this got going.Patrick Hsu (01:05):Yeah, sure. That sounds great. So we started Arc with Patrick C and with Silvana Konermann, a longtime colleague and chemistry faculty at Stanford about three years ago now, though we've been physically operational just over two years and we're an independent research institute working at the interface of biomedical science and machine learning. And we have a few different aspects of our model, but our overall mission is to understand and treat complex human diseases. And we have three pillars to our model. We have this PI driven side of the house where we centrally fund our investigators so that they don't have to write grants and work on their very best ideas. We have a technical staff side of the house more like you'd see in a frontier AI lab or in biotech industry where we have professional teams of R&D scientists working cross-functionally on higher level organizational wide goals that we call our institute initiatives.(02:05):One focused on Alzheimer's disease experimentally and one that we call a virtual cell initiative to simulate human biology with AI foundation models. And our third pillar over time is to have things not just end up as academic papers, but really get things out into the real world as products or as medicines that can actually help patients on the translational side. And so, we thought that some really important scientific programs could be unlocked by enabling new organizational models and we are experimenting at the institutional scale with how we can better organize and incentivize and support scientists to reach these long-term capability breakthroughs.Patrick, Patrick and SilvanaEric Topol (02:52):So the two Patrick's. How did you, one Patrick I guess is a multi-billionaire from Stripe and then there's you who I suspect maybe not quite as wealthy as the other Patrick, how did you guys come together to do this extraordinary thing?Patrick Hsu (03:08):Yeah, no, science is certainly expensive. I met Patrick originally through Silvana actually. They actually met, so funny trivia, all three Arc founders did high school science together. Patrick and Silvana originally met in the European version of the European Young Scientist competition in high school. And Silvana and I met during our PhDs in her case at MIT and I was at Harvard, but we met at the Broad Institute sort of also a collaborative Harvard, MIT and Harvard hospitals Institute based in Kendall Square. And so, we sort of in various pairwise combinations known each other for decades and worked together for decades and have all collectively been really excited about science and technology and its potential to accelerate societal progress. Yet we also felt in our own ways that despite a lot of the tremendous progress, the structures in which we do this work, fund it, incentivize it and roll it out into the real world, seems like it's really possible that we'll undershoot that potential. And if you take 15 years ago, we didn't have the modern transformer that launched the current AI revolution, CRISPR technology, single-cell, mRNA technology or broadly addressable LNPs. That's a tremendous amount of technologies have developed in the next 15 years. We think there's a real unique opportunity for new institutes in the 2020s to take advantage of all of these breakthroughs and the new ones that are coming to continue to accelerate biological progress but do so in a way that's fast and flexible and really focused.Eric Topol (04:58):Yeah, I did want to talk with you a bit. First of all before I get to the next related topic, I get a kick out of you saying you've worked or known each other for decades because I think you're only in your early thirties. Is that right?Patrick Hsu (05:14):I was lucky to get an early start. I first started doing research at the local university when I was 14 actually, and I was homeschooled actually until college. And so, one of the funny things that you got to do when you're homeschooled is well, you could do whatever you want. And in my case that was work in the lab. And so, I actually worked basically full time as an intern volunteer, cut my teeth in single cell patch clamp, molecular biology, protein biochemistry, two photon and focal imaging and kind of spiraled from there. I loved the lab, I loved doing bench work. It was much more exciting to me than programming computers, which was what I was doing at the time. And I think these sort of two loves have kind of brought me and us to where we are today.Eric Topol (06:07):Before you got to Berkeley and Arc, I know you were at Broad Institute, but did you also pick up formal training in computer science and AI or is that something that was just part of the flow?Patrick Hsu (06:24):So I grew up coding. I used to work through problems sets before dinner growing up. And so, it's just something that you kind of learn natively just like learning French or Mandarin.New Models of Funding Life ScienceEric Topol (06:42):That's what I figured. Okay. Now this model of Arc Institute came along in a kind of similar timeframe as the Arena BioWorks in Boston, where some of the faculty left to go to Arena like my friend Stuart Schreiber and many others. And then of course Priscilla and Mark formed the Chan Zuckerberg Institute and its biohub and its support. So can you contrast for one, these three different models because they're both very different than of course the traditional NIH pathway, how Arc is similar or different to the others, and obviously the goal here is accelerating things that are going to really make a difference.Patrick Hsu (07:26):Yeah, the first thing I would say is zooming out. There have been lots of efforts to experiment with how we do science, the practice of science itself. And in fact, I've recently been reading this book, the Demon Under the Microscope about the history of infectious disease, and it talks about how in the 1910s through the 1930s, these German industrial dye manufacturing companies like Bayer and BASF actually launched what became essentially an early model for industrial scale science, where they were trying to develop Prontosil, Salvarsan and some of these early anti-infectives that targeted streptococcus. And these were some of the major breakthroughs that led to huge medical advances on tackling infectious disease compared to the more academic university bound model. So these trends of industrial versus academic labs and different structures to optimize breakthroughs and applications has been a through current throughout international science for the last century.(08:38):And so, the way that we do research today, and that's some of our core tenets at Arc is basically it hasn't always been this way. It doesn't need to necessarily be this way. And so, I think organizational experiments should really matter. And so, there's CZI, Altos, Arena, Calico, a variety of other organizational experiments and similarly we had MRC and Bell Labs and Xerox PARCS, NIBRT, GNF, Google Research, and so on. And so, I think there are lots of different ways that you can organize folks. I think at a high level you can think about ways that you can play with for-profit versus nonprofit structures. Whether you want to be a completely independent organization or if you want to be partnered with universities. If you want to be doing application driven science or really blue sky curiosity driven work. And I think also thinking through internally the types of expertise that you bring together.(09:42):You can think of it like a cancer institute maybe as a very vertically integrated model. You have folks working on all kinds of different areas surrounding oncology or immunotherapy and you might call that the Tower of Babel model. The other way that folks have built institutes, you might call the lily pad model where you have coverage of as many areas of biomedical research as possible. Places like the Whitehead or Salk, it will be very broad. You'll have planned epigenetics, folks looking at RNA structural biology, people studying yeast cell cycle, folks doing in vivo melanoma models. It's very broad and I think what we try to do at Arc is think about a model that you might liken more to overlapping Viking shields where there's sort of five core areas that we're deeply investing in, in genetics and genomics, computation, neuroscience, immunology and chemical biology. Now we really think of these as five areas that are maybe the minimal critical mass that you would need to make a dent on something as complicated as complex human diseases. It's certainly not the only thing that you need, but we needed a critical mass of investigators working at least in these areas.Eric Topol (11:05):Well, yeah, and they really converge on where the hottest advances are being made these days. Now can you work at Arc Institute without being one of these three universities or is it really that you maintain your faculty and your part of this other entity?Patrick Hsu (11:24):So we have a few elements to even just the academic side of the house. We have our core investigators. I'm one of them, where we have dually appointed faculty who retain their latter rank or tenured appointment in their home department, but their labs are physically cited at the Arc headquarters where we built out a lab in Stanford Research Park in Palo Alto. And so, folks move their labs there. They continue to train graduate students based on whatever graduate programs they're formally affiliated with through their university affiliation. And so, we have nearly 40 PhD students across our labs that are training on site every day.(12:03):So in addition to our core investigators, we also have what we call our innovation investigators, which is more of a grant program to faculty at our partner universities. They receive unrestricted funding from us to seed a new project or accelerate an existing area in their group and their labs stay at their home campus and they just get that funding to augment their work. The third way is our technical staff model where folks basically just come work at Arc and many of them also are establishing their own research groups focusing on technology R&D areas. And so, we have five of those technology centers working in molecular engineering, multi-omics, complex cellular models, in vivo models, and in machine learning.Discovery of Bridge RNAsEric Topol (12:54):Yeah, that's a great structure. In fact, just a few months ago, Patrick Collison, the other Patrick came to Stanford HAI where I'm on the board and you've summarized it really well and it's very different than the other models and other entities, companies included that you mentioned. It's really very impressive. Now speaking of impressive on June 26, this past few months ago, which incidentally is coincident with the draft genome in the year 2000, the human sequence. You and your colleagues, perhaps the most impressive jump in terms of an Arc Institute contribution published two papers back-to-back in Nature about bridge RNA: [Bridge RNAs direct programmable recombination of target and donor DNA] and [Structural mechanism of bridge RNA-guided recombination.] And before I get you to describe this breakthrough in genome editing, some would call it genome editing 3.0 or CRISPR 3.0, whatever. But what we have today in the clinic with the approval of CRISPR 1.0 for sickle cell and thalassemia is actually quite crude. I think most people will know it's just a double stranded DNA cleavage with all sorts of issues about repair and it's not very precise. And so, CRISPR 2.0 is supposed to be represented by David Liu's contributions and his efforts at Broad like prime and base editing and then comes yours. So maybe you can tell us about it and how it is has to be viewed as quite an important advance.Patrick Hsu (14:39):The first thing I would say before CRISPR, is that we had RNA interference. And so, even before this modern genome editing revolution with programmable CRISPRs, we had this technology that had a lot of the core selling points as well. Any target will now become druggable to us. We simply need to reprogram a guide RNA and we can get genetic access to things that are intracellular. And I think both the discovery of RNA interference by Craig Mello and Andy Fire or the invention or discovery of programmable CRISPR technologies, both depend on the same fundamental biological mechanism. These non-coding guide RNAs that are essentially a short RNA search string that you can easily reprogram to retarget a desired enzyme function, and natively both RNAi and CRISPR are molecular scissors. Their RNA or DNA nucleases that can be reprogrammed to different regions of the genome or the transcriptome to make a cut.(15:48):And as bioengineers, we have come up with all kinds of creative ways to leverage the ability to make site specific cuts to do all kinds of incredible things including genome editing or beyond transcriptional up or down regulation, molecular imaging and so on and so forth. And so, the first thing that we started thinking about in our lab was, why would mother nature have stopped only RNAi and CRISPR? There probably are lots of other non-coding RNAs out there that might be able to be programmable and if they did exist, they probably also do more complicated and interesting things than just guide a molecular scissors. So that was sort of the first core kind of intuition that we had. The second intuition that we had on the technology side, I was just wearing my biology hat, I'll put on my technology hat, is the thing that we call genome editing today hardly involves the genome.(16:50):It's really you're making a cut to change an individual base or an individual gene or locus. So really you're doing small scale single locus editing, so you might call it gene level or locus level cuts. And what you really want to be able to do is do things at the genome scale at 100 kb, a megabase at the chromosome scale. And I think that's where I think the field will inevitably go if you follow the technology curves of longer and longer range gene sequencing, longer and longer range gene synthesis, and then longer and longer range gene editing. And so, what would that look like? And we started thinking, could there be essentially recombination technologies that allow you to do cut and paste in a single step. Now, the reason for that is the way that we do gene editing today involves a cut and then a multi-step process of cellular DNA repair that resolves the cut to make the exertion or the error prone deletion or the modification that ends up happening.(17:59):And so, it's very complicated and whether that's nucleases or base or prime editing, you're all generally limited to the small-scale single locus changes. However, there are natural mechanisms that have solved this cut and paste problem, right? There are these viruses or bacterial versions of viruses known as phage that have generally been trying to exert their multi kilobase genomes into bacterial hosts and specialize throughout billions of years. So our core thought was, well, if there are these new non-coding RNAs, what kind of functions would we be excited about? Can we look in these mobile genetic elements, these so-called jumping genes for new mechanisms? They're incredibly widespread. Transposons are thought to be some of the most diverse enzyme mechanisms found in nature. And so, we started computationally by asking ourselves a very simple question. If a mobile element inserts itself into foreign DNA and it's able to somehow be programmable, presumably the inside or something encoded in the inside of the element is predictive of some sequence on the outside of the element.(19:15):And so, that was the core insight we took, and we thought let's look across the boundaries of many different mobile genetic elements and we zoomed in on a particular sub family of these MGE known as insertion sequence (IS) elements which are the most autonomous minimal transposons. Normally transposons have all kinds of genes that they use to hitchhike around the genomic galaxy and endow the bacterial host with some fitness advantage like some ability to metabolize some copper and some host or some metal. And these IS elements have only the enzymes that they need to jump around. And if you identify the boundaries of these using modern computational methods, this is actually a really non-trivial problem. But if you solve that problem to figure out with nucleotide resolution where the element boundaries end and then you look for the open reading frame of the transposases enzyme inside of this element, you'll find that it's not just that coding sequence.(20:19):There are also these non-coding flanks inside of the element boundaries. And when we looked across the non-coding, the entire IS family tree, there are hundreds of these different types of elements. We found that this particular family IS110, had the longest non-coding ends of all IS elements. And we started doing experiments in the lab to try to figure out how these work. And what we found was that these elements are cut and paste elements, so they excise themselves into a circular form and paste themselves back in into a target site linearly. But the circularization of this element brings together two distal ends together, which brings together a -35 and a -10 box that create and reconstitute a canonical bacterial transcriptional promoter. This essentially is like plugging a plug into an electrical socket in the wall and it jacks up transcription. Now you would think this transcription would turn on the transposase enzyme so it can jump around more but it transcribes a non-coding RNA out of this non-coding end.(21:30):We're like, holy crap, are these RNAs actually involved in regulating the transposon? Now the boring answer would be, oh, it regulates the expression. It's like an antisense regulate or something. The exciting answer would be, oh, it's a new type of guide RNA and you found an RNA guided integrase. So we started zooming in bound dramatically on this and we undertook a covariation analysis where we were able to show that this cryptic non-coding RNA has a totally novel guide RNA structure, totally distinct from RNAi or CRISPR guide RNAs. And it had a target site that covaried with the target site of the element. And so we're like, oh wow, this could be a programmable transposase. The second thing that we found was even more surprising, there was a second region of complementarity in that same RNA that recognized the donor sequence, which is the circularized element itself. And so, this was the first example of a bispecific guide RNA, and also the first example of RNA guided self-recognition by a mobile genetic element.Eric Topol (22:39):It's pretty extraordinary because basically you did a systematic assessment of jumping genes or transposons and you found that they contain things that previously were not at all recognized. And then you have a way to program these to edit, change the genome without having to do any cuts or nicks, right?Patrick Hsu (23:05):Yeah. So what we showed in a test tube is when we took this, so-called bridge RNA, which we named because it bridges the target and donor together along with the recombinase enzyme. So the two component system, those are the only two things that you need. They're able to cut and paste DNA and recombine them in a test tube without any DNA repair, meaning that it's independent of cellular DNA repair and it does strand nicking, exchange, junction resolution and religation all in a single mechanism. So that's when we got super excited about its potential applications as bioengineering tool.Eric Topol (23:46):Yeah, it's pretty extraordinary. And have you already gone into in vivo assessment?Patrick Hsu (23:54):Yes, in our initial set of papers, what we showed is that these are programmable and functional or recombinases in a test tube and in bacterial cells. And by reprogramming the target and donor the right way, you can use these enzymes not just for insertion, but also for flipping and cutting out DNA. And so, we actually have in a single mechanism the ability to do bridge editing, if you will, for universal DNA recombination, insertion, excision or inversion, similar to what folks have been doing for decades with Cre recombinase, but with fully programmable recognition sequences. The work that we're doing now in the lab as you can imagine is to adapt these into robust tools for mammalian genome editing, including of course, human genomes. We're excited about this, we're making good progress. The CRISPR has had thousands of labs over the last 10, 15 years working on it to make these therapeutic level potency and selectivity. We're going to work and follow that same blueprint for getting bridge systems to get to that level of performance, but we're on the path and we're very optimistic for the future.Exemplar of Digital BiologyEric Topol (25:13):Yeah, I think it's quite extraordinary and it's a whole different look to what we've been seeing in the CRISPR era for over the past decade and how that's been advancing and getting more specific and less need for repair and being able to be more versatile. But this takes it to yet another dimension. Now, this brings me to the field that when I think of this term digital biology, I think of you and now our mutual acquaintance, Jensen Huang, who everybody knows now. Back some months ago, he wrote and said at a conference, “Where do I think the next amazing revolution is going to come? And this is going to be flat out one of the biggest ones ever. There's no question that digital biology is going to be it. For the first time in human history, biology has the opportunity to be engineering, not science.” So can you critique Jensen? Is he right? And tell us how you conceive the field of digital biology.Patrick Hsu (26:20):If you look at gene therapy today, the core concepts are actually remarkably simple. They're elegant. Of course, you're missing a broken gene, you need to put it back. And that can be curative. Very simple, powerful concept. However, for complex diseases where you don't have just a single gene that goes wrong, in many cases we actually have no idea what to do. And in fact, when you're trying to put in DNA, that's over more than a gene scale. We kind of very quickly run out of ideas. Is it a CAR and a cytokine, a CAR and a cytokine and another thing? And then we're kind of out of ideas. And so, we started thinking in the lab, how can we actually design genomes where it's not just let's reduce the genome into individual Lego blocks, iGem style with promoters and different genes that we just sort of shuffle the Lego blocks around, but actually use AI to design genome sequences.(27:29):So to do that, we thought we would have to first of all, train a model that can learn and decode the foreign language of biology and use that in order to design sequences. And so, we sort of have been training DNA foundation models and virtual cell models at Arc, sort of a major effort of ours where the first thing that we tried was to take a variance of transformer architecture that's used to train ChatGPT from OpenAI, but instead apply this to study the next DNA token, right? Now, the interesting thing about next token prediction in English is that you can actually learn a surprising amount of information by just predicting the next word. You can learn world knowledge is the capital of Azerbaijan, is it Baku or is it London, right? Or if you're walking around in the kitchen, then the next text is, I then left the kitchen or the bathroom, right?(28:33):Now you're learning about spatial reasoning, and so you can also learn translation obviously. And so similarly, I think predicting the next token or the next base and DNA can lead you to learn about molecular biochemistry, is the next amino acid residue, hydrophobic or hydrophilic. And it can teach you about the mechanics of some catalytic binding pocket or something. You can learn about a disease mutation. Is the next base, the sick linked base or the wild type base and so on and so forth. And what we found was that at massive scale, DNA foundation models learn about molecular function, not just at the DNA level, but also at the RNA and the protein. And indeed, we could use these to design molecular systems like CRISPR-Cas systems, where you have a protein and the guide RNA. It could also design new DNA transposons, and we could design sequences that look plausibly like real genomes, where we generate a megabase a million bases of continuous genome sequence. And it really looks and feels like it could be a blurry picture of something that you would actually sequence. This has been a wonderful collaboration with Brian Hie, a PI at Stanford and an Arc investigator, and we're really excited about what we've seen in this work because it promises the better performance with even more scale. And so, simply by scaling up these models, by adding in more compute, more training data or more powerful models, they're going to get sharper and sharper.New A.I. Models in Life ScienceEric Topol (30:25):Yeah. Well, this whole use of large language models for the language of life, whether it's the genome proteins and on and on, actually RNA and even cells has really taken root. And of course, this is really one of the foundations of that field of digital biology, which brings together generative AI, AI tools and trying to push forward our understanding in biology. And also, obviously what's been emphasized in drug discovery, perhaps it's been emphasized even too much because we still have a lot to learn about biology, but that gets me to these models. Like today, AlphaProteo was announced by DeepMind, as we all know, AlphaFold 1, 2, now 3. They were kind of precursors of being able to predict proteins from amino acid 3D structure. And that kind of took the field by a little bit like ChatGPT for life science, but now it's a new model all the time. So you've been working on various models and Arc Institute, how do you see this unfolding? Are we just going to have every aspect of the language of life being approached in all the different interactions? And this is going to help us get to a much more deep level of understanding.Patrick Hsu (31:56):I'll say two things. The first is a lot of models that you just described are what I would call task specific models. A model for de novo design of a binder, a model for protein structure prediction. And there are other models for protein fitness or for RNA structure prediction, et cetera, et cetera. And I think what we're going to move towards are more unifying models where there's different classes of models at different levels of scale. So we will have these atomic level models for looking at generative chemistry or ligand docking. We have models that can unify genomes and their molecules, and then we have models that can unify cells and tissues. And so, for example, if you took an H&E stain of some liver, there are folks building models where you can then predict what the single cell spatial transcriptome will look like of that model. And that's obviously operating at a very different level of abstraction than a de novo protein binder. But in the long run, all of these are going to get, I think unified. I think the reason why this is possible is that biology, unlike physics, actually has this unifying theory of evolution that runs across all of its length scales from atomic, molecular, cellular, organismal to entire ecosystem. And the promise of these models is no short then to make biology a predictive discipline.Patrick Hsu (33:37):In physics, the experimentalists win the big prizes for the theorists when they measure gravitational waves or whatever. But in biology, we're very practical people. You do something three times and do a T-test. And I think my prediction is we can actually gauge the success of these LLMs or whatever in biology by how much we respect theory in this field.The A.I. ScientistEric Topol (34:05):Yeah. Well, that's a really interesting perspective, an important perspective because the proliferation of models, which we're going to get into not just doing the things that you described, but also being able to be “pseudo” scientists, the so-called AI scientist. Maybe you could comment about that concept because that's been the idea that everything from the question that could be asked to the hypothesis and the experiment design and the analysis of data and then the feedback. So what is the role of the scientists, that seems to have been overplayed? And maybe you can put that in context.Patrick Hsu (34:48):So yeah, right now there's a lot of excitement that we can use AI agents not just to do software enterprise workflows, but to be a research assistant. And then over time, itself an autonomous research scientist that can read the literature, come up with an idea, maybe run a bunch of robots in the lab or do a bunch of computational analyses and then potentially even analyze data, conclude what is going on and actually write an entire paper. Now, I think the vision of this is compelling in the long term. I think the question is really about timescale. If you break down the scientific method into its constituent parts, like hypothesis generation, doing an experiment, analyzing experiment and iterating, we're clearly going to use AI of some kind at every single step of this cycle. I think different steps will require different levels of maturity. The way that I would liken this is just wet lab automation, folks have dreamed about having pipetting robots that just do their western blots and do their cell culture for them for generations.(36:01):But of course, today they don't actually really feel fundamentally different from the same ones that we had in the 90s, let's say. Right? And so, obviously they're getting better, but it seems to me one of the trends I'm very bullish about is the explosion of humanoid robots and robot foundation models that have a world model and a sense of physics and proportionate space loaded onto them. Within five years, we're going to have home robots that can fold your clothes, that can organize your kitchen and do all of this while you're sleeping, so you wake up to a clean home every day.Eric Topol (36:40):It's not going to be just Roomba anymore. There's going to be a lot more, but it isn't just the hardware, it's also the agents playing in software, right?Patrick Hsu (36:50):It's the integrated loop of the hardware and the software where the ability to make the same machine generally intelligent will make it adaptable to a broad array of tasks. Now, what I'm excited about is those generally intelligent humanoid robots coming into the lab, where instead of creating a centrifuge or a new type of pipetter that's optimized for your Beckman or Hamilton device, instead you just have robot arms that you snap onto the edge of the bench and then they just work alongside you. And I do think that's coming, although it'll take a lot of hardware and software and computer vision engineering to make that possible.A Sense of HumorEric Topol (37:32):Yeah, and I think also going back to originating the question, there still is quite a debate about the creativity and the lack of any simulation of AGI, whatever that means anymore. And so, the human in the loop part of this is obviously I think it's still of critical nature. Now, the other thing I learned about you is you have a great sense of humor, which is really important by the way. And recently, which is great that you're active on X or Twitter because that's one way we get to see what you're thinking on a day-to-day basis. But I think you put out a poll which was really quite provocative , and it was about, here's what it said, “do more people in the world *truly* understand transformers or health insurance?” And interestingly, you got 49% for transformers at 51% for health insurance. Can you tell us what you're thinking when you put that poll together? Because obviously a lot of people don't understand either of these.Patrick Hsu (38:44):I think the core question is, there are different ways of looking at the world, some of which are very bottom up and some of which are very top down. And one of the very surprising things about transformers is they're taking something that is in principle, an incredibly simple task, which is if you have a string of text, what is the next letter? And somehow at massive, massive scale, you can unlock something that looks an awful lot like reasoning, and you've got these emergent behaviors. Now the bottoms up theory of just the linear algebra that's going on in these models couldn't possibly really help us predict that we have these emerging capabilities. And I think similarly in healthcare, there's a literal set of parts that are operating in some complex way that at massive scale becomes this incredibly confusing and dynamic system for how we can actually incentivize how we make medicines, how we actually take care of people, and how we actually pay for any of this from an economic point of view. And so, I think it was, in some sense if transformers can actually be an explainable by just linear algebra equations, maybe there will be a way to decompose the seemingly incredibly confusing world of healthcare in order to actually build a better way forward.Computing Power and the GPU Arms RaceEric Topol (40:12):Yeah. Well that's great. Now the other thing I wanted to ask you about, we open source and the arms race of GPUs and this whole kind of idea is you touched on the need for coalescing a lot of these tools to exploit the synergy. But we have an issue because many academic labs like here at Scripps Research and so many others, including as I learned even at Stanford, have limited access to GPUs. So computing power of large language models is a problem. And then the models that exist today that can be adopted like Llama or others, and they're somewhat limited. And then we also have a movement towards trying to make things more open source, like for example, recently OpenCRISPR with Profluent Bio that is basically trying to use AI for CRISPR guides. And so, how do you deal with this arms race, computing power, open source, proprietary models that are not easily accessible without a lot of resources?Patrick Hsu (41:30):So the first thing I would say is, we are in the academic science sphere really unprepared for the level of resources that are required for doing this type of cutting edge computational work. There are top Stanford computer science professors or computational researchers who have a single GPU in their office, and that's actually what their whole lab runs off of.(41:58):The UC Berkeley campus, the grid runs on something like 12 megawatts of power and how are they going to build an on-premises GPU clusters, like a central question that can scale across the entire needs? And these are two of the top computer science universities in the world. And so, I think one of our kind of core beliefs at Arc is, as science both experimentally and computationally has gotten incredibly complex, not just in terms of conceptually, but also just the actual infrastructure and machines and know-how that you need to do things. We actually need to essentially support this. So we have a private GPU cloud that we use to train our models, and we have access to significantly large clusters for large burst kind of train outs as necessary. And I think infrastructurally for running genomics experiments or doing scalable brain organoid screens, right, we're also building out the infrastructure to support that experimentally.Eric Topol (43:01):Yeah, no, I think this is one of the advantages of the new model like the Arc Institute because not many centers have that type of plasticity with access to computing power when needed. So that's where a brilliant mind you and the Arc Institute together makes for a formidable recipe for future advances and of course building on the ones you've already accomplished.The Primacy of Human TalentPatrick Hsu (43:35):I would just say, my main skill, if I have one, is to recruit really, really smart people. And so, everything that you're seeing and hearing about is the work of unbelievable colleagues who are curious, passionate, and incredible scientists.Eric Topol (43:53):But it also takes the person who can judge those who are in that category set as a role model. And you're certainly doing that. I guess just in closing, I mean, it's just such a delight to get to meet you here and kind of get your thoughts on what is the hottest thing in life science without question, which brings together the fields of AI and what's going on, not just obviously in genome editing, but this digital biology era that we're still in the early phases of, I mean, I think you could say that it's just going to continue to accelerate the exponential curve. We're still kind of on the bottom of that, I would imagine where we're headed. Any other things that you want to bring up that I haven't touched on that will round out this conversation?Patrick Hsu (44:50):I mean, I think it's very early days here at Arc.Patrick Hsu (44:53):When we founded Arc, we asked ourselves, how do we measure success? We don't have customers or revenue in the way that a typical startup does. And we felt sort of three things. The first was research institutes live and die by their talent. Can we actually hire incredible people when we make offers to people we want to come, do they come? The second was, when those folks do come to Arc, do they feel like they're able to work on important research programs that they couldn't do sort of at their prior university or company? And then longer term, the third thing was, and there's just no shortcut around this, you need to do important work. And I think we've been really excited that there are early signs that we're able to do all three of these things, and we're still, again, just following the same scaling laws that we're seeing in natural language and vision, but for the domain of biology. And so, we're excited about what's ahead and think if there are folks who are interested in learning more about Arc, just shoot me an email or DM.Eric Topol (46:07):Yeah, well I would just say, congratulations on what you've already achieved. I know you're going to keep rocking it because you already have in a short time. And for anybody who doesn't know about Arc Institute and your work and your team, I hope this is going to be putting them on notice actually what can be accomplished outside of the usual NIH funded model, which is kind of a risk-free zone where you basically have to have your results nailed down before you send in your proposal frequently, and it doesn't do great things for young people. Really, I think you actually qualify in that demographic where it's hard for them to break in for getting NIH grants and also for this type of work that you're doing. So we'll look for the next bridge beyond bridge RNAs of your just fantastic efforts. So Patrick, thanks so much for joining us today, and we'll be checking back with you and following all the great work that you'll be doing in the times ahead.Patrick Hsu (47:14):Thanks so much, Eric. It was such a pleasure to be here today. Appreciate the opportunity.*******************Thanks for listening, reading or watching!The Ground Truths newsletters and podcasts are all free, open-access, without ads.Please share this post/podcast with your friends and network if you found it informative!Voluntary paid subscriptions all go to support Scripps Research. Many thanks for that—they greatly help fund our summer internship programs.Thanks to my producer Jessica Nguyen and Sinjun Balabanoff for audio and video support at Scripps Research.Note: you can select preferences to receive emails about newsletters, podcasts, or all I don't want to bother you with an email for content that you're not interested in. Get full access to Ground Truths at erictopol.substack.com/subscribe

Non, l'évolution n'agit pas seulement à petit pas, sur le temps long. Des espèces peuvent aussi se transformer brutalement, quasiment du jour au lendemain, sous l'effet de grands morceaux d'ADN mobiles qui viennent se coller dans leur génome : ce sont les transposons. On sait aujourd'hui suivre leurs mouvements au cœur de l'ADN.Chaque avancée scientifique raconte une nouvelle histoire et ce sont ces histoires piquantes ou vertigineuses que nous aimons raconter dans les pages d'Epsiloon, le nouveau magazine d'actualité scientifique édité par Unique Heritage Media. Chaque semaine, notre journaliste Valérie Greffoz vous embarque dans l'une des enquêtes de la rédaction.Un podcast écrit et interprété par Valérie GreffozInspiré des articles de la rédaction d'EpsiloonAvec la scientifique Marie Mirouze et le journaliste d'Epsiloon Jean-Baptiste VeyrierasEnregistrement : Léopold Roy et Fanny DupuisCréation musicale : Léopold RoyEnregistré au Studio DuparkUnique Heritage Media 2022 Hébergé par Acast. Visitez acast.com/privacy pour plus d'informations.

Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Value Claims (In Particular) Are Usually Bullshit, published by johnswentworth on May 30, 2024 on LessWrong. Epistemic status: mental model which I have found picks out bullshit surprisingly well. Idea 1: Parasitic memes tend to be value-claims, as opposed to belief-claims By "parasitic memes" I mean memes whose main function is to copy themselves - as opposed to, say, actually provide value to a human in some way (so that the human then passes it on). Scott's old Toxoplasma of Rage post is a central example; "share to support X" is another. Insofar as a meme is centered on a factual claim, the claim gets entangled with lots of other facts about the world; it's the phenomenon of Entangled Truths, Contagious Lies. So unless the meme tries to knock out a person's entire epistemic foundation, there's a strong feedback signal pushing against it if it makes a false factual claim. (Of course some meme complexes do try to knock out a person's entire epistemic foundation, but those tend to be "big" memes like religions or ideologies, not the bulk of day-to-day memes.) But the Entangled Truths phenomenon is epistemic; it does not apply nearly so strongly to values. If a meme claims that, say, it is especially virtuous to eat yellow cherries from Switzerland... well, that claim is not so easily falsified by a web of connected truths. Furthermore, value claims always come with a natural memetic driver: if X is highly virtuous/valuable/healthy/good/etc, and this fact is not already widely known, then it's highly virtuous and prosocial of me to tell other people how virtuous/valuable/healthy/good X is, and vice-versa if X is highly dangerous/bad/unhealthy/evil/etc. Idea 2: Transposons are ~half of human DNA There are sequences of DNA whose sole function is to copy and reinsert themselves back into the genome. They're called transposons. If you're like me, when you first hear about transposons, you're like "huh that's pretty cool", but you don't expect it to be, like, a particularly common or central phenomenon of biology. Well, it turns out that something like half of the human genome consists of dead transposons. Kinda makes sense, if you think about it. Now we suppose we carry that fact over, by analogy, to memes. What does that imply? Put Those Two Together... … and the natural guess is that value claims in particular are mostly parasitic memes. They survive not by promoting our terminal values, but by people thinking it's good and prosocial to tell others about the goodness/badness of X. I personally came to this model from the other direction. I've read a lot of papers on aging. Whenever I mention this fact in a room with more than ~5 people, somebody inevitably asks "so what diet/exercise/supplements/lifestyle changes should I make to stay healthier?". In other words, they're asking for value-claims. And I noticed that the papers, blog posts, commenters, etc, who were most full of shit were ~always exactly the ones which answered that question. To a first approximation, if you want true information about the science of aging, far and away the best thing you can do is specifically look for sources which do not make claims about diet or exercise or supplements or other lifestyle changes being good/bad for you. Look for papers which just investigate particular gears, like "does FoxO mediate the chronic inflammation of arthritis?" or "what's the distribution of mutations in mitochondria of senescent cells?". … and when I tried to put a name on the cluster of crap claims which weren't investigating gears, I eventually landed on the model above: value claims in general are dominated by memetic parasites. Thanks for listening. To help us out with The Nonlinear Library or to learn more, please visit nonlinear.org

Link to original articleWelcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Value Claims (In Particular) Are Usually Bullshit, published by johnswentworth on May 30, 2024 on LessWrong. Epistemic status: mental model which I have found picks out bullshit surprisingly well. Idea 1: Parasitic memes tend to be value-claims, as opposed to belief-claims By "parasitic memes" I mean memes whose main function is to copy themselves - as opposed to, say, actually provide value to a human in some way (so that the human then passes it on). Scott's old Toxoplasma of Rage post is a central example; "share to support X" is another. Insofar as a meme is centered on a factual claim, the claim gets entangled with lots of other facts about the world; it's the phenomenon of Entangled Truths, Contagious Lies. So unless the meme tries to knock out a person's entire epistemic foundation, there's a strong feedback signal pushing against it if it makes a false factual claim. (Of course some meme complexes do try to knock out a person's entire epistemic foundation, but those tend to be "big" memes like religions or ideologies, not the bulk of day-to-day memes.) But the Entangled Truths phenomenon is epistemic; it does not apply nearly so strongly to values. If a meme claims that, say, it is especially virtuous to eat yellow cherries from Switzerland... well, that claim is not so easily falsified by a web of connected truths. Furthermore, value claims always come with a natural memetic driver: if X is highly virtuous/valuable/healthy/good/etc, and this fact is not already widely known, then it's highly virtuous and prosocial of me to tell other people how virtuous/valuable/healthy/good X is, and vice-versa if X is highly dangerous/bad/unhealthy/evil/etc. Idea 2: Transposons are ~half of human DNA There are sequences of DNA whose sole function is to copy and reinsert themselves back into the genome. They're called transposons. If you're like me, when you first hear about transposons, you're like "huh that's pretty cool", but you don't expect it to be, like, a particularly common or central phenomenon of biology. Well, it turns out that something like half of the human genome consists of dead transposons. Kinda makes sense, if you think about it. Now we suppose we carry that fact over, by analogy, to memes. What does that imply? Put Those Two Together... … and the natural guess is that value claims in particular are mostly parasitic memes. They survive not by promoting our terminal values, but by people thinking it's good and prosocial to tell others about the goodness/badness of X. I personally came to this model from the other direction. I've read a lot of papers on aging. Whenever I mention this fact in a room with more than ~5 people, somebody inevitably asks "so what diet/exercise/supplements/lifestyle changes should I make to stay healthier?". In other words, they're asking for value-claims. And I noticed that the papers, blog posts, commenters, etc, who were most full of shit were ~always exactly the ones which answered that question. To a first approximation, if you want true information about the science of aging, far and away the best thing you can do is specifically look for sources which do not make claims about diet or exercise or supplements or other lifestyle changes being good/bad for you. Look for papers which just investigate particular gears, like "does FoxO mediate the chronic inflammation of arthritis?" or "what's the distribution of mutations in mitochondria of senescent cells?". … and when I tried to put a name on the cluster of crap claims which weren't investigating gears, I eventually landed on the model above: value claims in general are dominated by memetic parasites. Thanks for listening. To help us out with The Nonlinear Library or to learn more, please visit nonlinear.org

Episode 199 – Eternal Information – Part 7 – Living Information 2 Welcome to Anchored by Truth brought to you by Crystal Sea Books. In John 14:6, Jesus said, “I am the way, the truth, and the life.” The goal of Anchored by Truth is to encourage everyone to grow in the Christian faith by anchoring themselves to the secure truth found in the inspired, inerrant, and infallible word of God. Script: By faith we understand that the entire universe was formed at God’s command, that what we now see did not come from anything that can be seen. Hebrews, chapter 11, verse 3, New Living Translation ******** VK: Hello! I’m Victoria K. Welcome to Anchored by Truth brought to you by Crystal Sea Books. Thank you for joining us here today on Anchored by Truth. For several episodes we have been doing a series we call “Eternal Information.” We’ve covered a lot of ground so far in this series. For those listening today who may have missed some of the earlier episodes we encourage you to go to our website crystalseabooks.com where you can hear them. And, of course, anyone who just wants to review an episode even if they heard it before can always go to crystalseabooks.com for a review. This series in particular has been one of those series where each episode builds on the material from previous episodes. In the studio we have RD Fierro. RD is an author and the founder of Crystal Sea Books. RD, would you like to amplify a little more on what I was just talking about – that this series of Anchored by Truth is a series where we are steadily building on what came before? RD: Sure. But before I do that I would also like to extend my greetings to everyone who is joining us here today. I suspect most listeners are probably like me. When I first came across the concept of information as one more way in which God’s presence in the universe is manifest I was completely unfamiliar with it. Like all listeners, I used information everyday throughout the day. But I never gave any thought about information itself. Information was kind of like air. It was just there. But I never stopped to think about how it got there. Then I came across Dr. Werner Gitt’s book entitled In the Beginning was Information and I had one of those “light bulb” moments. The presence of information requires the presence of intelligence and there is no way we can avoid living in this universe and avoid the fact that it contains information. But to try to communicate all that this concept involves isn’t easy. Unlike some subjects where we connect with them easily digging deeper into how information functions within the universe requires a lot of … well, information. VK: Studying information requires a lot of information. I’m not sure if that is profound or just redundant … RD: Probably a little of both. At any rate there are a lot of ideas that are tied up in thinking about how information again assures us that there must be a Designing Mind behind the universe as we know it. So, we began unpacking those ideas one at a time. VK: Such as the fact that information is an essential component of the universe that we know. Unlike other components with which we are more familiar like matter and energy information stands apart in the way in which it presents itself. Information is non-material. It is not dependent for its existence on matter or energy but matter and energy can be used to transmit, receive, or store it. The same keyboard, wires, and screens can exchange recipes for pies, maps to buried treasure, or diagrams for making bombs. The information doesn’t change the plastic, copper, or silicon in the keyboard or screen. But neither is the plastic, copper, or silicon responsible for the content of the information. These aren’t the kind of ideas we think about everyday. RD: Right. And those ideas are just the beginning of what we had to undertake. And the specific idea that we have been pursuing for the last couple of episodes of Anchored by Truth is that the presence of information in living creatures is undeniable. A couple of episodes ago we spent some time on the basics of biochemistry and last time we began our dive into the most information storage system on the planet: DNA. VK: So, today we want to finish that discussion. But just as a brief recap last time we began covering the fact that DNA is actually a four-dimensional information storage system. Just about every information system invented or used by man is one-dimensional. When we transmit information through written text we get the information by reading the text from left to right. And even though there are some writing systems like ancient Hebrew that are read right to left the same observation applies. We get the information by going in one direction. Try to read the same text backward and all you get is gobbledygook. But as we began showing last time DNA doesn’t just store and transmit information in one dimension or in one direction. DNA does so on multiple levels. RD, why don’t you briefly remind us of what we covered when we went over the first three dimensions in which DNA stores information? RD: And DNA is built from compounds called nucleotides. Nucleotides consist of a sugar, a nitrogen containing base, and a phosphate group. There are 4 bases that comprise the structure of DNA: adenine [a-duh-neen], guanine [gwaa-neen}, cytosine [sai-tuh-seen], and thymine [thigh-mean]. They are usually abbreviated A, G, C, and T. So, these are the “letters” of the genetic alphabet. And DNA is made up of two long strands – the famous double helix – joined by means of the associations: A with T and C with G. This means that the two strands are complimentary. One of the key takeaways about DNA is that DNA’s information function is not dependent on its chemistry. Just as the chemistry of ink and paper do not determine the information that is present on a printed page, the chemical components that comprise DNA do not determine the messages that it stores and sends. So, the first level of information that DNA contains is simply the order of the “letters” – the nucleotide base pairs. The entire human genome has been mapped. So, we know the order of the letters for it. The first 15 letters of DNA in the human “Y” chromosome are “CTAACCCTAACCCTA.” VK: So, this first level of information is just a sequence of letters. That seems pretty simple. But you start to get a hint of the other levels of information when you realize that we have between 20,000 and 25,000 genes but our bodies produce over 100,000 different proteins. Some estimates are that the human body produces over 300,000 distinct proteins. If the sequence of the letters in DNA is the first level of information, what is the second level? RD: The second dimension of the genome deals with the way one section of DNA interacts with another section. It’s easy enough to create a visual depiction of the first dimension of DNA. It is essentially just a long sequence of the letters A, C, T, and G. But trying to draw a pictorial representation of the second dimension would be a dizzying array of lines and arrows connecting different parts of the linear string of DNA. At first when scientists discovered DNA and genes they thought they had discovered the key to a lot of biological mysteries. One of the key ideas that emerged into science was the idea that one gene coded for one protein. Proteins are, of course, the molecular machines of life. VK: But that idea was too simple wasn’t it, especially for higher organisms? As we mentioned earlier the human body produces far more different proteins than we have genes. RD: Yes. The linear left to right read of DNA coupled with the idea that each gene, essentially a subsection of DNA, coded for one protein turned out to be far too simplistic. For instance, our protein genes are broken up into a series of “exons” (the parts that code for protein) and “introns” (non-coding intervening sequences). To make a protein, the gene is first transcribed into RNA, then the introns are spliced out, the exons are stitched together, and the remainder is translated into protein. That might seem straightforward. But we now know that some proteins are manufactured through a process called “alternate splicing”, where exons from different locations in the genome are combined to create many different proteins. In fact, we have learned that alternate splicing is so pervasive that the definition of the word “gene” as it was originally conceived had just about lost its meaning. The one gene-one enzyme hypothesis turned out to be a gross oversimplification. VK: Biologist Dr. Robert Carter has said this about the second informational dimension of DNA. “The second dimension deals with things like specificity factors, enhancers, repressors, activators, and transcription factors. These are proteins that are coded in the DNA, but they move to another part of the genome after they are made and turn something on or off. But there are additional things happening in this dimension.” In other words there’s a lot of information that DNA supplies to the body that isn’t tied to a simple left to right reading of the letters. There are connections being made between different sections of the DNA that are also necessary for life. RD: Yes. As I said last time, trying to pictorially represent the information connections within DNA would be so complicated it would be as if you were standing in the midst of a galaxy with beams of light zinging among the stars. There would be so many beams connecting various stars you wouldn’t be able to count them all. And we still are only talking about the second dimension of DNA that supplies information. The third dimension has to do with how DNA is actually stored within the body. The body doesn’t store DNA as a long string. It couldn’t. The DNA is coiled into a very precise 3-D shape. VK: Dr. Carter has also written that, “The third dimension [of information] deals with how the shape of the DNA molecule affects the expression and control of different genes. We have learned that sections of DNA that are buried deep within the coiled-up DNA cannot be activated easily. So genes that are used often are generally easily accessible. Thus, when God wrote out the information in the genome along that one-dimensional strand, He intentionally put things in a certain order so that they would be in the correct place when the DNA was folded into a 3-D shape.” RD: Yes. It would be extremely impractical for the body to store DNA in a linear state. We talked about the amazing fact that the DNA in a single cell would be about 6 feet long if it were laid out in a straight line. It would be extremely thin but it would stretch for 6 feet. The National Institutes for Health have estimated that the DNA present in a human body would be over 67 Billion miles long if all the strands were laid end to end – that’s the equivalent of 150,000 trips to the moon – and back. To store all that DNA the body coils it in tight coils that fit within the nuclei of the various cells. And we now know that genes that are used together are generally found next to each other in the 3 dimensional storage arrangement even when those genes are found on different chromosomes. VK: Last time we used the example of a homeowner organizing his garage. A wise homeowner is likely to organize the garage so the garden shears are close to the rakes rather than with the Christmas light strings and nativity set. The homeowner does this it is because the homeowner knows and understands the use of the things they are storing. In putting things away in the garage they are applying information and intelligence. So, the first dimension of information storage in DNA is the order of the letters. The second is how various sections of DNA actually act in concert with other sections. And the third is how the DNA functions in its 3-dimensional configuration not just as a linear string. RD: Exactly. Well our time ran out last time before we could get to the 4th dimension of the information that DNA contains. VK: Which is …? RD: Time. VK: Time? RD: Time. As incredible as it might seem we now know that the way DNA performs its function changes as time goes by and we know that these changes occur in all the other dimensions. Dr. Carter has written “The shape (3rd dimension), interaction network (2nd dimension), and the sequence of letters (1st dimension) all change. This so far outstrips even our most modern computers that the analogy isn’t even fair anymore.” Dr. Carter gives this example. “We know that different liver cells have different chromosome counts. This is due to the fact that the liver needs lots of copies of certain genes that are involved in metabolism and detoxification. Instead of filling the genome with many copies of these genes, the liver just makes copies of them for its own use. We also know that different brain cells have different number and locations of various transposons.” VK: Transposons are segments of DNA which are capable of moving within or among chromosomes. Transposons were once thought by evolutionists to be “jumping genes” that were leftovers from ancient viral infections. But they’re not. Transposons are vital for the development of the human brain. In other words, our genome is able to dynamically reprogram itself. As Dr. Carter wrote, “This is something that computer scientists have long struggled with. How can you make a self-modifying code that does not run out of control?” RD: So, as amazing as the first three dimensions of DNA’s information are in some ways the 4th dimension truly seems like something out of science fiction. As we go through life our DNA reprograms itself to adapt for where we are in life. It’s hard sometimes to remember that we are talking about a group of atoms and molecules that are present in the nucleus of every one of our 30 to 40 trillion cells. Now again, let’s not lose sight of the basic point. The alternate hypothesis that is offered to Biblical creationism is blind and random chance. VK: Those people who reject the existence of God, and in particular the God of the Bible, must conceive of the world and universe as being composed of matter, energy, time, and space. But no one sees time and space as possessing creative capacity so they are really down to matter and energy. So, their concept for the origin of DNA is that at one point some hydrogen, oxygen, nitrogen, and carbon atoms fortuitously collided and started making some simple organic compounds. Some of these organic compounds ran into each other and poof some simple amino acids or nucleotides were produced. Then these extremely elementary organic collections ran randomly and accidentally collected in one place and all that jostling about produced a string of DNA which contains, at a minimum, millions of atoms. The more you talk about it the more far-fetched it seems. RD: It seems far-fetched because it is far-fetched. And it’s not like evolutionists don’t realize the problems their scenario involves they do. So, they try to craft solutions such as saying that there are unseen “organizing forces” present within physics and chemistry that overcome most of the seeming impossibilities. And there have been extensive computer simulations offered with supposedly random substitutions occurring in strings of letters that show that with enough time and chemical components just the right set needed will emerge. But one basic problem with all these attempts is that they start with a huge amount of information about how life functions today. They ignore the fact that undirected matter and energy would have none of that. Moreover, undirected matter and energy would have no goal of producing life. The evolutionary apologists always start with their own goal of showing how it might be possible. But that’s quite a different thing from showing how it actually occurred. VK: As we often point out on Anchored by Truth explaining the origin of a thing is quite different from explaining its operation. We know today much about how life operates. We know the chemical elements involved. We know the structure of organic compounds and how those compounds can link up and form the ever increasingly complicated structures used by all living things. But an ocean of chemicals just drifting about knows none of that. RD: And I should emphasize at this point that this discussion that we have had about the four dimensional nature of the information DNA contains has only skimmed the surface. I would highly recommend listeners going to the website for Creation Ministries International and spending some time there reading the various articles on DNA. There’s a lot more to DNA than we have time to discuss in this series. VK: Such as? RD: Such as the fact that DNA has its own repair system. VK: Wikipedia says this about the DNA repair system. “DNA repair is a collection of processes by which a cell identifies and corrects damage to the DNA molecules that encode its genome. In human cells, both normal metabolic activities and environmental factors such as radiation can cause DNA damage, resulting in tens of thousands of individual molecular lesions per cell per day. Many of these lesions cause structural damage to the DNA molecule and can alter or eliminate the cell's ability to transcribe the gene that the affected DNA encodes. … As a consequence, the DNA repair process is constantly active as it responds to damage in the DNA structure.” RD: The DNA repair system is just another facet of DNA that defies explanation by evolutionary development. Without the repair system DNA would quickly be damaged so badly that normal cellular replication would cease. That means death for the organism. So, DNA needs the repair system to keep functioning but it is the DNA itself that tells the body how to produce the repair system. And we have only discovered this very recently. The 2015 Nobel Prize in Chemistry was awarded to Tomas Lindahl, Paul Modrich, and Aziz Sancar for their work on the DNA repair processes. VK: So, what else do you want to cover for today? RD: I want to give our listeners a very inexact model for DNA’s amazing information system. Imagine that you found a long sheet of paper that contained a lengthy list of ingredients for a meal. As you examined the list you realized that it was a list of ingredients for an amazing 7 course meal. At the bottom of the sheet the final line said “roll this into a 2 inch tube.” After you did so you found out that the letters that are now on the outside of the rolled sheet gave you all the steps in preparing the ingredients – the chopping, slicing, dicing, grating, etc. Then the final instruction said “hold near the stove.” And when you did so you found out that certain portions of the letters were now lit up and they gave you precise instructions for cooking the various ingredients like temperature, time, basting, stirring, etc. The last line of illuminated letters now said, “place near the completed dishes.” And when you did that you found out that different letters were now lit up which told you how to garnish, arrange, put on final toppings, and serve. You get the idea. No human technology would permit us to create an information storage system that sophisticated yet we’re asked to believe that random chance built a biological information system that contains hundreds of millions of ingredients. Our most elegant examples of technology and advanced design pale in comparison to the complexity present to every strand of DNA on the planet. Yet, the most amazing thing is that some people continue to insist that all of that sophisticated complexity could have arisen by chance. VK: Well, all that has made me a little hungry but it does make the point. We’re familiar with single dimension information systems because that’s what we experience in our daily lives. Probably, with a lot of effort and planning, we might create a single system that has multiple dimensions of information. But those systems certainly wouldn’t run into the billions of letter or symbols that served multiple tasks simultaneously. The sophistication of DNA eludes us even now. The only reasonable explanation for DNA’s relentless display of information sophistication is because it was prepared and created by the Ultimate, Infinite Designer. It’s just a little bit silly to believe that unintelligent and undirected matter and energy could produce DNA when even the most intelligent scientists could not do so. But God could and that’s what our opening scripture from Hebrews tells us. This sounds like a time to go to God in prayer. Since our children are back in school and busily working their way through the academic year, today let’s listen to a prayer for all of them who could benefit from a little divine help with upcoming tests. ---- PRAYER FOR TAKING A TEST VK: We’d like to remind our audience that a lot of our radio episodes are linked together in series of topics so if they missed any episodes or if they just want to hear one again, all of these episodes are available on your favorite podcast app. To find them just search on “Anchored by Truth by Crystal Sea Books.” If you’d like to hear more, try out crystalseabooks.com where “We’re not perfect but our Boss is!” (Bible Quote from the New Living Translation) Hebrews, chapter 11, verse 3, New Living Translation The human genome is amazingly complex (creation.com) Four Dimensional Genome (creation.com) Splicing and dicing the human genome (creation.com) We are less than dust (creation.com) Epigenetics challenges neo-Darwinism (creation.com)

KSQD 5-04-2022: (Archive show) Review of genetics research focusing on genetic diseases: sickle cell, Huntingtons, fragile X syndrome, cystic fibrosis, breast cancer, Tay-Sachs, tuberculosis, Creutzfeldt–Jakob disease and prions; More genetics topics such as repetitive DNA, transposons, jumping genes, oncogenes and retroviruses

In today's episode I spoke again to Dr Christopher Todd from the Babraham institute. Chris is a postdoctoral researcher in Wolf Reiks lab who talked to me about transposable elements and epigenetic priming of enhancers with human embryonic development. Chris gave a great talk at GREECS 2022 where he discussed his research and I absolutely loved his talk, so immediately messaged him to join me on the podcast! If like me, you feel unclear on what exactly are transposable elements, the details of their function & classification and want to learn more about enhancer priming, stay tuned to learn lots! Even if you do know these things, I guarantee you will still learn so much from Chris! Hope you all enjoy! Chris' twitter: https://twitter.com/C_D_Todd Reik lab twitter: https://twitter.com/ReikLab Chris profile on Babraham website: https://www.babraham.ac.uk/people/member/746 Google scholar: https://scholar.google.com/citations?user=WPqJa6QAAAAJ&hl=en

* Nature Paper Confirms RSR Rejection of 'Junk' DNA: A landmark study by 440 researchers working in 32 laboratories aro und the world has so far been able to identify function for 80 percent of the human genome! Real Science Radio co-hosts Bob Enyart and Fred Williams also present six minutes of audio from 1998 when leading evolutionist Eugenie Scott tells Bob that genetic scientists were "over the hump" and affirmatively knew that the pseudogenes had no function and that such junk DNA was therefore evidence against the existence of a Designer. Hear the fundamentalist Bible teacher disagree with the degreed scientist, and guess who science has vindicated? * Notice the Nucleotides in the Trash Bags: :) -->* Hear Eugenie Scott & Bob Spar on Junk DNA: At the beginning of this radio program, hear audio from 1998 from Bob and leading anti-creationist Eugenie Scott debating the merits of the Junk DNA argument! (And see more below). Hear also physicist Lawrence Krauss acknowledge to Bob Enyart that his friend Eugenie was wrong. * ENCODE Project Takes Out the Trash: The project leader for ENCODE (the Encyclopedia of DNA Elements) is predicting that eventually, we will learn that "100%" of the genome is functional. (ENCODE Consortium, Dunham, et al., Nature, 2012, pp. 57-74). When the scientist finally reaches the summit, he finds the theologian already there. * Famed Molecular Evolutionist in a Tough Spot: Please pray for Dan Graur. To a young-earth creationist who has been vindicated by ENCODE (and now through 2019 with mountains of consistent data continuously rising up), Dan Graur's angst is our celebration. In 2017 he published, desperately, that based on evolutionary assumptions the human genome cannot be more than at the very most 25% functional. Oh boy. Then in 2019 he acknowledged even more bluntly: If the human genome is indeed devoid of junk DNA as implied by the ENCODE project, then a long, undirected evolutionary process cannot explain the human genome. If, on the other hand, organisms are designed, then all DNA, or as much as possible, is expected to exhibit function. If ENCODE is right, then Evolution is wrong.  * 2019 Worm Update: Worm "junk DNA" turns out to control their ability to regenerate, says Harvard's Evolutionary Biology department. So, even with the worms Dr. Graur, it wasn't junk after all.   For this show, RSR recommends Dr. Don Johnson's Programming of Life DVD! * Junky Real Science Radio Shows - "Nature" Confirms Creationist Rejection of Junk DNA (this webpage) - Bob Debates an Evolutionist 1998 DVD (from our archives) - RSR: Enyart Exhumes Eugenie Scott (2005 radio program: show summary copied here...) * RSR: Bob Debates Ph.D. Evolutionist Eugenie Scott: One of the world's leading anti-creationists vs. Bob Enyart. The debate is decided in the first round, by TKO. That's after Bob asked the well-known scientist for any evidence that any high-level function had ever evolved, like eyesight, or hearing, or flight, or mobility in general? Through the hour-long debate, this evolutionist refused to offer any such evidence but finally settled on a claim of evidence against design, which was: junk DNA! * JUNK DNA: Eugenie Flubs Genetics Prediction, Creationist Hits the Bull's-eye. The negative evidence that Eugenie did offer was Junk DNA. This scientist, from her Darwinist worldview, therefore didn't offer scientific evidence but made this philosophical argument about what a Creator would or would not do; namely, that He wouldn't fill our genome with so much non-protein-coding DNA. While some simple worms have 20,000 genes, it is typically a small portion of DNA that actually codes for proteins. A human has only 20,500 genes, which fills only 2% of our genome. Yet the widespread evolutionary claim for decades (including through the last two decades, and for many, still held today) was that the rest of the genome was left-over evolutionary garbage. Debating this physical anthropologist, Bob Enyart was just a Christian fundamentalist talk show host who spoke from his biblical worldview. Bob argued that our knowledge of genetics was in its infancy, and that it was too early to make the determination that all those non-coding segments of DNA had no function. After this 1998 debate, the next decade of explosive genetic discoveries overwhelmingly validated this creationist perspective, so much so that aside from coding for 20,500 proteins, it is estimated that the remainder of the genome has approximately four million other functional regulatory segments of DNA. So much for junk. Fulfilled predictions, as the world saw with Einstein's 1919 eclipse prediction, go toward scientific credibility. However, Dr. Scott strongly rejected this creationist prediction making an extraordinary claim, which Bob immediately offered her to retract, that scientists currently knew everything they would ever need to know about genetics to conclusively state that all those regions were useless junk. Bob would love a rematch. But Eugenie Scott, (Ph.D. in Physical Anthropology, leading anti-creationist, and director of the National Center for Science Education), who had just debated evolution on a nationwide PBS television program, ended this one-hour program with Bob stating, "Well, I don't debate." * The Diet Pop Junk DNA Syndrome: Junk DNA = Junk Science. Junk DNA was a science stopper. The many Darwinists who strongly pushed (and many still do) the Junk DNA claim predicted that nearly 100% of the entire human genome, the portion that was non-coding, was mostly just left-over junk DNA. It's like a diet cola having NO sugar, NO calories, NO cholesterol, NO fiber, NO protein, NO carbs, NO sodium, NO fat. One wonders what in the world gives it its taste. So from the 1970s it's not surprising, assuming as they did that nearly 95% or so of the DNA was junk anyway, that evolutionists could make such sloppy claims about DNA reinforcing the Darwinian tree. However, now, with the List of Genomes that Just Don't Fit, evolutionary geneticists have falsified the claim that DNA confirms Darwinian predictions. And all that progress aside, the canard that there's nearly a 99% similarity between humans and chimps should have been falsified merely by a careful look at differences in brain and overall anatomy. * Tossing the Wright Brothers Materials and Tools: Consider the significance of the four million regulatory regions of the human genome as compared to the relatively tiny portion that codes for proteins. The creationist Wright Brothers' design, that is, their regulatory input, so-to-speak, dwarfed the importance of the particular kinds of materials and tools that built their airplane. Other tools and materials could suffice. But all the tools and materials in the world assembled for workers who had no design to begin with would not produce an airplane. Thus the regulatory portion of the genome, including that in epigenetics, very possibly may be the more significant part. And similarly, the design concept of a nucleus itself is far more important than what specific chemistry will implement it. * Another Bit of (Famous) Junk DNA Reclassified: (2013 Update.) First consider this analogy from astronomy. Cosmologists cannot show that a big bang could create the contents of the universe because it's impossible to formulate an explanation for the origin of something if you don't know what that something is! And 96% of what's supposedly in a "big bang universe", all that dark matter and dark energy, is of unknown composition. Thus it's no wonder that even the latest textbooks on big bang nucleosynthesis don't even mention, for example, the production of dark matter! Likewise, because geneticists have difficulty even to defining what a "gene" is (see Moran on Dawkins, for example), evolutionists have oversold their case in calling portions of a genome a "pseudogene". As it turns out, a piece of DNA spectacularly referred to as a functionless piece of junk by famed evolutionist Kenneth Miller apparently has important function, according to a 2013 paper in the journal Genome Biology and Evolution. There's a layman's explanation of this issue written by Casey Luskin. Leading evolutionists misunderstood and thus misused the beta-globin "pseudogene" to make what amounts to a religious argument about what a Designer may or may not be inclined to do. As Luskin explains, Darwinists claimed that "matching mistakes" in various species in this "pseudogene" disproved the claim of a designer. But as it turns out, those "matching mistakes" are actually conserved genetic functionality, so that like Darwinist arguments generally, this evolution claim was based on ignorance and it evaporated as science learned more. Additionally, however, (and this gets to the related question of how much marijuana is smoked by leading evolutionists) the theory of neo-Darwinism itself refutes this popular beta-globin pseudogene claim. For if this segment of DNA had no function (i.e., if it were junk) it would NOT have been conserved by natural selection! Mutations over millions of years would have altered any "mistaken" nucleotides. Thus, by the theory itself, we do not expect to see non-functioning segments of DNA with conserved sequences of junk that arose from mutations over millions of years. Thus, the fact that these segments were conserved pointed directly to their being conserved, and functional (and, by the way, to their being designed). * Can Evolution Proceed One Small Step at a Time? If it is true that there are no "small steps," logically or physically, between monochromatic and dichromatic vision, then at least for this wildly complex vision-system upgrade, Richard Dawkins' Mt. Improbable must be scaled in one huge step. And scaling such a complexity cliff in one step, he himself admits, would be very difficult to advocate. There are no Darwin-friendly small steps between eukaryote (nucleus) and prokaryote (no nucleus), nor between invertebrate and vertebrate, nor between monochromatic and dichromatic vision. Whether you are an extinct fossil or a living species, you either have a backbone or you don't; you either have a nucleus or you don't, you might have monochromatic or dichromatic vision, or not, but you don't have something in between. Post-show Note: Illustrating this nicely the Wikipedia article on transposons states, ironically that transposition elements, "are often considered 'junk DNA'. In Oxytricha... they play a critical role..." And from Scientific American, "The term 'junk DNA' repelled mainstream researchers from studying noncoding genetic material for many years." Today's Resource: Get the greatest cell biology video ever made! Getting this on DVD: - helps you to share it with others - helps keep Real Science Radio on the air, and - gets you Dr. Don Johnson's book as a bonus! Information is encoded in every cell in our DNA and in all living things. Learn how the common worldview of life's origin, chemical evolution, conflicts with our knowledge of Information Science. Finally, information Science is changing the way millions of people think about all living systems! Also, have you browsed through our Science Department in the KGOV Store? You just might LOVE IT! We offer a 30-day money back guarantee on all purchases.

We'd love to hear from you (feedback@breakingbadscience.com)Look us up on social media Facebook: https://www.facebook.com/groups/385282925919540Instagram: https://www.instagram.com/breakingbadsciencepodcast/Website: http://www.breakingbadscience.com/Patreon: https://www.patreon.com/breakingbadscienceIt's widely understood that flushing your pet turtle results in them being found by a rat in a robe, learning to walk on two legs, and getting borderline addicted to the consumption of pizza. But aside from the adolescent genetically altered martial artist tortoises, are there more natural ways for mutation to come about? Is Xavier's prediction that mutant humans are already among us true? Join hosts Shanti and Danny as we explore what mutation is and how it's linked to things like radioactivity and the sun. ReferencesRehman, H.; Heterochromia. Canadian Medical Association Journal. 26-Aug-2008. 179:5 (447 - 448). Doi: https://doi.org/10.1503/cmaj.070497CIA. Explore All Countries World. CIA.gov. 27-Jul-2021. https://www.cia.gov/the-world-factbook/countries/world/Cox, M., Battista, J.; Deinococcus radiodurans - The Consummate Survivor. Nature Reviews Microbiology. 01-Nov-2005. 3 (882 - 892). Doi: https://doi.org/10.1038/nrmicro1264The Pierre Auger Collaboration. Observation of a Large-Scale Anisotropy in the Arrival Directions of Cosmic Rays Above 8 x 1018 eV. Science. 22-Sep-2017. 357:6357 (1266 - 1270). Doi: https://doi.org/10.1126/science.aan4338Venken, K., Bellen, H.; Chemical Mutagens, Transposons, and Transgenes to Interrogate Gene Function in Drosophila melanogaster. Methods. 15-Jun-2014. 68:1 (15 - 28). Doi: https://doi.org/10.1016/j.ymeth.2014.02.025Support the show (https://www.patreon.com/breakingbadscience?fan_landing=true)

Transposons cette fable intemporelle de Jean de la Fontaine à l'époque de la 5G, du big data et des startup. Dans cette version revisitée, le lièvre de la nouvelle économie remporterait la course face à la tortue de l'ancien monde. Une analogie qui s'appuie sur les nouveaux leaders mondiaux (Tesla, Amazon, Airbnb…) qui ont détrôné en quelques années les anciens fleurons (Exon, General Motors…) grâce à leur agilité et leur audace. La raison de ce succès ? Ces success stories sont dirigées par des entrepreneurs audacieux et visionnaires comme Elon Musk, Mark Zuckerberg ou Jeff Bezos. Là où les anciens capitaines d'industrie étaient de simples gestionnaires. ************* Vous avez aimé cet épisode ? Vous souhaitez le commenter ? N'hésitez pas à laisser un commentaire en bas de cette page ! ⬇️ ************* La version texte de ce podcast est accessible sur https://fabricelamirault.com/la-fable-du-lievre-et-de-la-tortue-a-lere-des-start-up/ Vous appréciez ce Podcast ? N'hésitez pas à vous inscrire à la Newsletter : https://lempreintedigitale.com/newsletter Vous pouvez également vous abonner à cette chaine et partager cet épisode sur les réseaux sociaux !

Link to bioRxiv paper: http://biorxiv.org/cgi/content/short/2020.10.30.360610v1?rss=1 Authors: Ecovoiu, A. A., Ghita, I. C., Chifiriuc, D. I. M., Ghionoiu, I. C., Ciuca, A. M., Bologa, A. M., Ratiu, A. C. Abstract: Transposon annotation is a very dynamic field of genomics and various tools assigned to support this bioinformatics endeavor were reported. Genome ARTIST (GA) software was initially developed for mapping artificial transposons mobilized during insertional mutagenesis projects. Now, the new functions of GA_v2 qualify it as an effective companion for mapping and annotation of class II natural transposons in assembled genomes, contigs or sequencing reads. Tabular export of mapping and annotation data for subsequent high-throughput data analysis, the export of a list of flanking sequences around either the coordinates of insertion or around the target site duplications (TSDs) and generation of a consensus sequence for the respective flanking sequences are all key assets of GA_v2. Additionally, we developed two accompanying short scripts that enable the user to annotate transposons existent in assembled genomes and to use various annotation offered by FlyBase for Drosophila melanogaster genome. Herein, we present the applicability of GA_v2 for a preliminary annotation of the class II transposon P-element in the genome of D. melanogaster strain Horezu, Romania, which was sequenced with Nanopore technology in our laboratory. Our results point that GA_v2 is a reliable tool to be integrated in pipelines designed to perform transposon annotation in new sequenced genomes. GA_v2 is open source software compatible with Ubuntu, Mac OS and Windows and is available at https://github.com/genomeartist/genomeartist and at www.genomeartist.ro. Copy rights belong to original authors. Visit the link for more info

Christos Velanis works at the University of Edinburgh and discusses work published in PloS Genetics entitled ‘The domesticated transposase ALP2 mediates formation of a novel Polycomb protein complex by direct interaction with MSI1, a core subunit of Polycomb Repressive Complex 2 (PRC2)‘. http://blog.garnetcommunity.org.uk/wp-content/uploads/2020/07/Velanis_edit-13072020-09.32.mp3 Pumi Perera is co-first author on this work from the Goodrich lab[...] The post Christos Velanis discusses the polycomb group complex, domesticated transposons and the future of scientific funding. appeared first on Weeding the Gems.

Review of genetics research focusing on genetic diseases: sickle cell, Huntington's, fragile X syndrome, cystic fibrosis, breast cancer, Tay-Sachs, tuberculosis, Creutzfeldt–Jakob disease and prions; More genetics topics such as homosexuality, repetitive DNA, transposons, jumping genes, oncogenes and retroviruses

Review of genetics research focusing on genetic diseases: sickle cell, Huntington's, fragile X syndrome, cystic fibrosis, breast cancer, Tay-Sachs, tuberculosis, Creutzfeldt–Jakob disease and prions; More genetics topics such as homosexuality, repetitive DNA, transposons, jumping genes, oncogenes and retroviruses

Menschliche DNA ist über 3 Milliarden Nucleotidpaare lang und beinhaltet die Information für ungefähr 25.000 Gene. Fast die Hälfte des menschlichen Erbguts, etwa 45%, besteht aus beweglichen genetischen Elementen, den Transposons, umgangssprachlich als „springende Gene“ bezeichnet. Sie sind in der Lage, ihre Position innerhalb des Genoms zu verändern.

Sparked by an contemporaneous news article "Man who had transplant finds out months later his DNA has changed to that of donor 5,000 miles away" and a request by Dr. Tammy of Milwaukee,  Dr. Clary explains why genetic material (DNA, RNA)  is so powerful and is currently being looked at by the scientific community to address a whole host of diseases and conditions.  But like Dr. Victor Frankenstein should we pause to understand what we are dealing with or 'make it up as we go" like so many other failed scientific endeavors.  Should we play the long game?  Dr. Fred Clary, founder of Functional Analysis Chiropractic Technique and lifting and life coach and gym chalk covered philosopher opens a conversation on genetic manipulation. 

Kaushik Panda and Keith Slotkin come on the podcast to educate us about repetitive DNA and transposable elements. We talk LINEs, SINEs, LTRs, and even Sleeping Beauty transposons! Kaushik and Keith explain why repeats matter for your whole-genome analysis and answer listeners’ questions. Links: Keith’s paper: The case for not masking away repetitive DNA Questions for this episode on Reddit

This episode: Certain transposons, genetic elements that move around the genome on their own, have co-opted the bacterial immune system, CRISPR, to use for jumping to new hosts! Thanks to Dr. Joseph Peters for his contribution! Download Episode (10.7 MB, 11.75 minutes) Show notes: Microbe of the episode: Streptomyces yokosukanensis Journal Paper: Peters JE, Makarova KS, Shmakov S, Koonin EV. 2017. Recruitment of CRISPR-Cas systems by Tn7-like transposons. Proc Natl Acad Sci 114:E7358–E7366. Other interesting stories: Microbe found producing antibiotic previously only known to be man-made (paper) Modifying genetics to change bacterial colony colors Making microbe communities that help plants in specific ways Gut microbes can protect mice against death from sepsis Fungus affects cicada behavior to infect more hosts   Email questions or comments to bacteriofiles at gmail dot com. Thanks for listening! Subscribe: iTunes, RSS, Google Play. Support the show at Patreon, or check out the show at Twitter or Facebook

In MicrobeWorld Video episode 66 Dr. Stan Maloy talks with Curtis Suttle, Professor of Earth & Ocean Sciences, Microbiology & Immunology, and Botany, and Associate Dean of Science University of British Columbia.  Dr. Suttle is one of the World's leading marine virologists, and is among a small group of researchers that is credited with launching the field of marine virology. Dr. Maloy talks with Dr. Suttle about the incredible diversity of the ocean's microscopic inhabitants that have long been overlooked.  The oceans are mostly microbial, 98% by weight, which means most of what is going on in the oceans is unseen and until recently largely unknown. Dr. Suttle explains the large role that ocean viruses play in keeping our planet alive. In fact, Dr. Suttle points out that viruses do more to create life than take it away. If you were to take the viruses out of the ocean much of the planet's life-cycle would stop, there would be no more photosynthesis. Viral replication drives the major bio-geochemical cycles on Earth.  Dr. Suttle also discusses transposons, "the world's first immune system," phage and using genomic sequencing to do ecology outside of the lab environment. This episode was recorded at the American Association for the Advancement of Science Meeting in Vancouver, British Columbia on February 17, 2012.

In MicrobeWorld Video episode 66 Dr. Stan Maloy talks with Curtis Suttle, Professor of Earth & Ocean Sciences, Microbiology & Immunology, and Botany, and Associate Dean of Science University of British Columbia.  Dr. Suttle is one of the World's leading marine virologists, and is among a small group of researchers that is credited with launching the field of marine virology. Dr. Maloy talks with Dr. Suttle about the incredible diversity of the ocean's microscopic inhabitants that have long been overlooked.  The oceans are mostly microbial, 98% by weight, which means most of what is going on in the oceans is unseen and until recently largely unknown. Dr. Suttle explains the large role that ocean viruses play in keeping our planet alive. In fact, Dr. Suttle points out that viruses do more to create life than take it away. If you were to take the viruses out of the ocean much of the planet's life-cycle would stop, there would be no more photosynthesis. Viral replication drives the major bio-geochemical cycles on Earth.  Dr. Suttle also discusses transposons, "the world's first immune system," phage and using genomic sequencing to do ecology outside of the lab environment.  This episode was recorded at the American Association for the Advancement of Science Meeting in Vancouver, British Columbia on February 17, 2012.

In MicrobeWorld Video episode 66 Dr. Stan Maloy talks with Curtis Suttle, Professor of Earth & Ocean Sciences, Microbiology & Immunology, and Botany, and Associate Dean of Science University of British Columbia.  Dr. Suttle is one of the World's leading marine virologists, and is among a small group of researchers that is credited with launching the field of marine virology. Dr. Maloy talks with Dr. Suttle about the incredible diversity of the ocean's microscopic inhabitants that have long been overlooked.  The oceans are mostly microbial, 98% by weight, which means most of what is going on in the oceans is unseen and until recently largely unknown. Dr. Suttle explains the large role that ocean viruses play in keeping our planet alive. In fact, Dr. Suttle points out that viruses do more to create life than take it away. If you were to take the viruses out of the ocean much of the planet's life-cycle would stop, there would be no more photosynthesis. Viral replication drives the major bio-geochemical cycles on Earth.  Dr. Suttle also discusses transposons, "the world's first immune system," phage and using genomic sequencing to do ecology outside of the lab environment. This episode was recorded at the American Association for the Advancement of Science Meeting in Vancouver, British Columbia on February 17, 2012.

Part 3 of the Molecular Evidence for Evolution.

Das Ac-Element aus Zea mays, das zur Familie der hAT-Elemente gehört, codiert für ein einzelnes Protein, die Transposase (TPase). Dieses Protein ist in vivo als einziges essentiell für die Transposition von Ac notwendig. Die Expression der TPase in E. coli war bisher nur in unlöslicher Form möglich. Der Nachweis, daß die TPase in vitro an die subterminalen Enden des Transposons bindet, wurde mit de- und wieder renaturiertem Protein erbracht (Kunze und Starlinger, 1989). In dieser Arbeit wurde zum ersten Mal TPase in löslicher Form in E. coli exprimiert bzw. aus transgenen Tabakpflanzen isoliert. Die Reinigung des Proteins bis zur Homogenität war nicht möglich. Das lösliche Protein besitzt eine hohe Aggregationsneigung. In vitro wurde gezeigt, daß die TPase als Oligomer DNA bindet. Ein in vitro-Nachweis der endonukleolytischen Aktivität der TPase konnte jedoch nicht erbracht werden. Die Transposition von Ac läuft wahrscheinlich in einem synaptischen Komplex ab, in dem über zahlreiche Proteininteraktionen die Enden des Transposons in räumliche Nähe zueinander ge-bracht werden. Dabei ist die TPase als Oligomer aktiv (Kunze et al, 1993). Gleichzeitig unterliegt die TPase einer negativen Autoregulation. Bei hoher TPase-Konzentration in der Zelle oligomerisiert das Protein zu inaktiven Aggregaten. Die Transposition von Ac hängt vom Vorhandensein mehrerer Proteininteraktionsdomänen ab. In dieser Arbeit wurde eine C-terminale Dimerisierungsdomäne der TPase charakterisiert, die unter den Transposasen der hAT-Elemente hochkonserviert ist und sowohl an der Transposition als auch an der negativen Autoregulation von Ac beteiligt zu sein scheint. Damit ist es zum ersten Mal gelungen, einer der drei hAT-Domänen eine Funktion zuzuschreiben. Am N-Terminus der TPase wurde eine Oligomerisierungsdomäne identifiziert, die mehrere hydrophobe „Zippermotive“ enthält. In vitro ist diese zum Teil ebenfalls konservierte Domäne am Aufbau eines synaptischen Komplexes beteiligt. Als weitere Proteininteraktionsdomäne der TPase wurde die PQ-Domäne identifiziert, deren essentielle Funktion bisher unbekannt war. Diese Domäne ist in vitro am Aufbau des Transpososoms beteiligt, aber auch in die Ausbildung vermutlich inaktiver TPase-Aggregate verwickelt. Als mutmaßliches katalytisches Zentrum der Ac-TPase wurde durch Sequenzvergleiche mit bakteriellen Transposasen und in vivo-Transposition entsprechender Mutanten ein (N)DE-Motiv postuliert. Durch einfache Aminosäureaustausche wurden dabei zum ersten Mal hyperaktive TPase-Mutanten isoliert, die teilweise defekt in der Aggregatbildung sind. Der Aktivitätstest der TPase-Mutanten erfolgte unter anderem in einem neu entwickelten Transpositionssystem in Hefe (Weil und Kunze, 2000).