What is the animal in this video?

What is the animal in this video?

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I made some research however there seems to be a conflict with this animal's translation to my language and the original. So I couldn't find it. Do you mind helping me out ?

Some resources say pufferfish or Porcupinefish. Are these the same thing ?

This is a Northern pufferfish. It is called Sphoeroides maculatus.


You can confirm this on FishBase.

I'm no expert in the field, so I can't identify the fish in your video; but it seems that pufferfish belong to the family Tetraodontidae, while porcupinefish are of the family Diodontidae. So, no, they are not the same thing.

Biological Carrying Capacity

Biological carrying capacity is defined as the maximum number of individuals of a species that can exist in a habitat indefinitely without threatening other species in that habitat. Factors such as available food, water, cover, prey and predator species will affect biological carrying capacity. Unlike cultural carrying capacity, biological carrying capacity cannot be influenced by public education.

When a species exceeds its biological carrying capacity, the species is overpopulated. A topic of much debate in recent years due to the rapidly expanding human populations, some scientists believe that humans have exceeded their biological carrying capacity.

Top 10 Amazing Biology Videos

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Cyborgs, stem cells, glowing mice, and hilarious music videos are great reasons to be excited about biology. Here are some of our favorite clips from the life sciences.

10. Immune Cell Chasing a Bacterium It may look like the predecessor to Pac Man, but this vintage clip shows a neutrophil wending its way through a crowd of red blood cells to destroy its bacterial nemesis.

  1. How High Speed Gene Sequencing Works Within the next few years, Helicos BioSciences may be able to read an entire human genome for under one thousand dollars. This video explains the science behind their amazing technology.

8. Shrimp Jogging on a Treadmill While comparing the stamina of sick shrimp to their healthy brethren, David Scholnick filmed this video of a cute little crustacean running on a treadmill. He had no idea that it would be come an internet sensation.

7. El Corazón An unusual music video about the heart, in Spanish, with English subtitles.

6. The PCR Song Biochemists often use the polymerase chain reaction to copy DNA molecules. This hilarious music video, tells the history of that technology and makes some jokes about its many uses, including paternity testing.

5. Glowing Mice Shed Some Light on Stem Cells This year, the Nobel Prize in Chemistry went to three scientists who studied a fluorescent protein from jellyfish. It has become a tremendously important tool for scientific research, because biologists can use it to understand what is going on inside of cells. An experiment with glowing mice led to a major discovery about stem cells.

4. DNA Origami Using a mix of chemistry, biology, and computer tricks, Paul Rothemund can design DNA molecules that fold up into complicated two-dimensional shapes. In this TED talk, he explains some of the logic behind his work, and how living things operate.

3. Cyborg Monkey Controls Robot Arm By implanting an array of electrodes directly into the motor area of a monkey’s brain, researchers can read some of its thoughts. Their interface is so good that the animal can take control of a robot arm and use it to feed itself. Someday, these brain-computer interfaces could be used to help paralyzed people live normal lives.

2. Evolution and Human Ancestry Genetic tests are becoming an important part of medicine, but can also tell us about our ancestry. This charming cartoon, made by 23andMe, offers a fantastic overview of how humans evolved.

1. Building Body Parts from Scratch Last week, regenerative medicine researchers announced that they have grown a new windpipe for a woman who was crippled by tuberculosis. Years ago, other scientists were able to make bladders, from scratch, and implant them in children with malformed urinary tracts. This video shows some amazing footage from two tissue engineering labs.

Lecture 6: Genetics 1

Download the video from iTunes U or the Internet Archive.

Topics covered: Genetics 1

Instructors: Prof. Eric Lander

Lecture 10: Molecular Biolo.

Lecture 11: Molecular Biolo.

Lecture 12: Molecular Biolo.

Lecture 13: Gene Regulation

Lecture 14: Protein Localiz.

Lecture 15: Recombinant DNA 1

Lecture 16: Recombinant DNA 2

Lecture 17: Recombinant DNA 3

Lecture 18: Recombinant DNA 4

Lecture 19: Cell Cycle/Sign.

Lecture 26: Nervous System 1

Lecture 27: Nervous System 2

Lecture 28: Nervous System 3

Lecture 29: Stem Cells/Clon.

Lecture 30: Stem Cells/Clon.

Lecture 31: Molecular Medic.

Lecture 32: Molecular Evolu.

Lecture 33: Molecular Medic.

Lecture 34: Human Polymorph.

Lecture 35: Human Polymorph.

I am the other half of the teaching team for 7.01.

You've already gotten to meet my good colleague Bob Weinberg.

My name is Eric Lander. And Bob and I are both faculty here in the Biology Department. In fact, we're both members over at the Whitehead Institute for Biomedical Research.

In fact, we just spent the whole weekend together at the Whitehead Retreat. And so, Bob and I have been doing this course together for a number of years. And we very much love it. I am -- I'll take a brief moment and introduce myself, since I haven't had the opportunity to do so yet. I am by training, well, actually, I'm really a geneticist. By training I'm actually a pure mathematician.

That was actually what my undergraduate degree was in, and even my PhD was in, but then wandered into biology.

And for the last almost 20 years, I have been doing genetics in some form or another. So I love genetics and look forward to talking a lot about genetics. And it's really lovely that my first lecture today is actually going to be our first introduction to genetics. I am -- Just for other backgrounds, I direct this new Broad Institute that is here. And it's actually a joint institute between MIT and Harvard. And you will know it now as a hole in the ground next to Legal Seafood.

If you see a bunch of cranes and things opposite the biology building and opposite Legal Seafood next to the Whitehead, that's the Broad Institute. And we have ambition some day to be more than the hole in the ground but to actually rise above the ground.

And the Broad is about genomic medicine and using genomes and things like that. And the Broad Institute includes this center at MIT that was one of the leading participants in the Human Genome project. So that's a lot of what I do with my day job, in addition to teaching, is work on things like the Human Genome project. And, now that we actually have a sequence to the human genome, figuring out what in the world it all means. And I hope I'll get a chance to tell you, during the course of this class, about the human genome and about what's in it and things like that. Like I say, that's one of the things I tremendously love about teaching biology as opposed, if I can get in trouble, to any of the other required introductory courses, is that our curriculum changes every year because the field is moving so rapidly. I look back at what we taught ten years ago in this course, because I've been teaching it that long, and all sorts of open questions now we know the answers to and are part of the curriculum. Some of the things we thought we knew we now know are false and we know new things.

And every year we get to introduce new stuff.

And I know, I mean with all due respect to calculus, it's just not the case for calculus that there's anything really new to introduce. Most of it sort of settled down about three or four centuries ago. And, you know, that's just not the case with what we do. Anyway, so that's why I love it. All right. So Bob has been talking to you about biochemistry largely. And I'm going to now turn to genetics. But I want you to understand that that is an overarching framework that explains how all the materials you're going to see, at least in the first half or more of this course fit together.

And Bob may have mentioned it, but I'm going to mention it again, I would use this following diagram as kind of our roadmap or subway map of where we're going in this course. What we really want to do is understand biological function. That's what we most want. How is it that an organism is able to breathe in air and distribute it to its cells? How is it that an organism is able to move its muscles?

How is it that an organism is able to fight off invaders to its body, microbes, things like that? How is it that an embryo develops into a full adult? Zillions of questions. That's what I mean by biological function. The two complimentary approaches to studying biological function, over the course of the past century or so in biology, have been the following. There have been the biochemists.

Biochemistry seeks to break down the organism into individual components and study them on their own in a test tube.

They will take an organisms, and to a biochemist wishing to study the beauty of a butterfly flapping in the wind and understanding all of the mechanics of how it could possibly flap those wings and all, he or she would start by taking the butterfly, putting it in the blender, pressing puree and making an extract, and trying to purify individual components that would explain muscles moving back and forth and all that. This is, of course, a geneticist's point of view, but it's all right. You have Bob who will represent biochemistry just fine. And they want to purify out individual components. Individual components away from the organism. And the most important individual type of component that they study are proteins because there are zillions of proteins and they do all sorts of things in the body.

And so you could say, in some sense, that this whole theme of biochemistry, which got started at the turn of the 20th century, really just a few years before the turn of the 20th century, of grinding up an organism, studying its components and being able to find, for example, I want to understand how I can digest lunch. Well. Or how yeast can digest the sugar.

Grind up yeast, fractionate it and find some protein that's able to digest the sugar all by itself without the rest of the organism, an enzyme to do that. That's the logic of biochemistry.

Genetics is the complimentary point of view. Genetics is the study of organisms minus one component. Of course, what I mean by that are mutants. The geneticist who wants to understand the butterflies and how the butterfly can fly would isolate butterfly strains that have lost the ability to fly.

And ideally one is extremely closely related to the normal butterfly, but for some reason, ideally due to the mutation of a single component they're now unable to fly. And the geneticist would then say, ah-ha, that component must matter an awful lot for the ability to fly because the butterfly that lacks that component cannot fly. It's a totally complimentary point of view. And the objects the geneticists study in order to do that are genes. Now, what is of course hard for you guys to understand but will form a structure for some of the lectures that I'm going to give over the continuing part of this course, is that through most of the 20th century the folks who studied biochemistry and tried to understand proteins and the folks who studied genetics and tried to understand mutants had nothing to say to each other. They didn't speak the same language.

They had nothing to relate to each other by because there was no idea of how this gene stuff, which started as a totally abstract business, could possibly relate to this protein stuff which started as a very practical in the test-tube thing. And they went for a very long time as if they were just ships sailing in the dark unaware of each other. And I exaggerate, but it's more true than not.

The great intellectual event was the unification of these two points of view through the discipline of molecular biology.

Molecular biology was the discipline that realized, oh, my goodness, these are two different sides of the same coin. That, in fact, genes encode proteins, proteins are encoded by genes. Ah-ha. This was a wonderful and important thunder clap in the 20th century. Now, it was a theoretical piece of information at first.

The idea that genes and proteins were related in this way was abstract, very important, but you couldn't do anything really with it, because it turned out you couldn't actually work with individual genes. The next great revolution of the 20th century was a technological revolution that let you actually work with genes. And that was the recombinant DNA revolution in which the tools to be able to study genes on their own away from the organism, study proteins, use genes to figure out what protein they encode, given a protein and figure out what the gene is, given a gene and actually go in and make a mutant in it, not wait for a random one to rise in the lab but deliberately knock it out, all of that operationalized this intellectual procedure, this intellectual framework. So that is, in some sense, a roadmap to coming lectures that I'm going to give.

I'm going to talk about genetics, I'm going to talk about molecular biology, and I'm going to talk about recombinant DNA.

That's the structure of the next several weeks of this course.

And what I want you to do is to recognize that although we're going to dive down into the individual components of it, everything we're going to do over the coming weeks fits into this very amazing intellectual framework. And this is the intellectual framework that you inherit as the new students coming into this field and going into the 21st century is all this was worked out in the last century. You now have an understanding of how all these pieces fit together, or at least you will, how these can be used to study biological function and, as I will also talk about, the recombinant DNA has grown into a world of genomics that has given us the complete picture of all of the components. It's actually not bad.

You were very wise to have shown up when you did because an awful lot of that groundwork has now been laid. You know, if you would have come along 50 years earlier, you know, all that would have been slogged through. Right now you have this laid out for you very nicely. And that's sort of what the theme will be. OK? I would ask are there any questions, but there should be a zillion questions about that.

This is just intended as a framework there.

So let's now dive in. Section 1. And I'll give a bit more background today than I will in some of the other lectures, but we've got to get going. What I really want to do first is talk about, in fact, most of today will be about Mendel.

I confess, Mendel is my hero. He is one of my absolute heroes in science. I just love Mendel. And so I'll dwell on him a little bit today. Now, here's the problem with trying to tell you about Mendel. You already know about Mendel, right? Who here hasn't met Mendel and the peas and the stuff and all that in their high school textbooks? So what am I doing talking about Mendel today? Well, I think what you learn about Mendel in the textbooks in high school does not really bring out what really went on with Mendel's thinking, what's really important about those experiments, what's really interesting.

And so I want to ask you to put aside what you think you know about Mendel and let's go back over the setting of who Mendel was, what he was doing, how it all adds up. Because I think in Mendel you can find just the seeds of how to do great science.

Now, for starters let me clear up, I'll take five minutes to clear up, four minutes to clear up some misconceptions about Mendel.

It has generally been written that Mendel was this monk working in this monastery often in the Chez Republic, at that point in the Austro-Hungarian Empire, and he was isolated, working by himself, and it was amazing he discovered all this stuff.

It's nonsense. Mendel working on genetics was no accident.

It was the result of extraordinary historical and economic forces over the course of about three centuries that culminated Mendel.

Let me briefly explain why. It starts with the Age of Exploration. Europe starts sending out boats around the world, explorers to meet other parts of the world in the 1500s.

The boats come back. They bring back stories of amazing lands. They also bring back odd plants, odd animals.

People begin to look at these plants and animals.

They begin to cross them, grow them and cross them, and look at the weird odd combinations of things that are going on.

And they say, wow, there's so much more variation out in the world than we thought about. Some of it's kind of useful. We can make new kinds of varieties of plants different than we had before, new kinds of varieties of apples. Now, it turns out that's not just an intellectual curiosity that that was the case because economics was changing in the face of Europe in the 1600s and in the 1700s with better transportation networks. So if you happen to be able to make a better apple, it was good, not just for your family, but you would be able to project that through lines of distribution to larger markets. It became economically sensible to invest your efforts in producing a better crop because you could sell it to more people because unified markets and transportation systems were developing across Europe. And, therefore, economic forces began to work toward getting a hold on the understanding of how you could do better breeding. Now, this turned out to be particularly important to the folks in Central Europe in the Austro-Hungarian Empire, which was the center of the textile industry. They were particularly concerned, in the late 1700s, about the fact that as the center of the textile industry they had to be concerned about the raw materials like wool that they used. Wool you could get from Central Europe, the Spanish had begun producing by breeding better sheep with better wool. This freaked out the guys in the Austro-Hungarian Empire because they were risking now losing this stuff to the Spanish because of their better sheep.

And they began, around 1800, to say we better start understanding how to do breeding. They put together societies to understand better the science of inheritance and breeding.

By 1820, a society which was not about sheep but about plants, in fact, apples and grapes, the Pomological and Enological Society of Braunau was organized. Braunau being the capital of the Austro-Hungarian Empire. And this society got all the town fathers of Braunau together. In those days it was just fathers, you know. Together in Braunau and started this society to encourage the scientific study of agricultural inheritance. They had this big dinner and they were drinking and things, and the speech is actually written down where the president gets up and says, "Some day the world may be as indebted as it is to Isaac Newton for physics. They may be as indebted to the City of Braunau for its contributions to inheritance." Which is just eerie to read that in 1820 in setting up this society. That was their high hopes for what they would do. In particular, the president of this society, one CF Nap was president of the society as a side job, his main job was he was head of the Augustinian monastery in Braunau. So he began keeping an eye out for bright young math and physic students. Basically, you know, MIT kids coming out of high schools. And he identified a bunch of smart ones and attracted them to the monastery and gave them problems to work on. He particularly was impressed with this relatively poor kid, Gregor Mendel, who had been floundering around with a couple of things, didn't have bright family prospects, and attracted him to the monastery to work on problems of inheritance. So this was no accident. This was a biotech incubator that had been set up in the Austro-Hungarian Empire.

Not of the sort we'd recognize today, but it's just fascinating to realize Mendel was not in a vacuum at all. He knew what he was doing here. He really wanted, for the good of mankind, to understand how to improve inheritance. But why do we celebrate Mendel today?

We celebrate Mendel today because he went about it, lots of people were interested in this problem, right?

You could probably find hundreds of people who tried to do something on this problem. Mendel was different because he went about it as a scientist. He went about it with a rigor and a persistence unlike all of his peers at the time. So let's think about what it was that Mendel did. So, anyway, forgive me for the historical digression, but I think it's interesting.

What did Mendel do? Mendel started by taking peas.

Now, he went off to the market and he got different varieties of peas.

And he brought back all of these varieties of peas and he tried growing them. Now, actually, although I don't have the records, I'm sure he did lots more than peas.

He brought probably lots of stuff and he tried growing it.

And the first order of question he wanted to ask is if I study inheritance, I've got to start with something that has constant properties. This seems obvious to you guys, but it was not at all obvious at the time that the most important thing you could do, if you wanted to understand the transmission of traits and crosses and inheritance and all that, is not to set up any crosses. It was first to set up your experimental system and make sure it was rock solid. He probably devoted years to getting varieties of different plants, and in particular settling on peas, with a property that when he had peas with different traits, like whether or not the pea seed was round or wrinkled, which will be some of our favorite traits here, that when you simply selfed this plant, crossed it to itself and looked at the next generation, it bred true. Hard to emphasize how important that was, but this was careful experimental design.

So many biological projects fail because people don't take the trouble to set up a system that's rock solid. They set up a system that's noisy and you're not really sure you're going to be able to interpret the data, etc. So Mendel did that. Very good.

Always, no matter how long you continued to breed these things, you continued to get round or you continued to get wrinkled.

Now Mendel was ready. He was ready to set up his first controlled cross.

So what he did was he took a round pea and a wrinkled pea and he crossed them together. Now, that's again some serious work.

You first have to go along to one of the peas, cut off its little pollen producing organs so it doesn't self-fertilize because peas will self-fertilize. You've got to cut them off early, make sure it doesn't get its own pollen on it. Then you go over to the other one with a paint brush, you get some pollen and you paint the pollen on the first plant. That's how you set up the cross.

If you screw it up you could have self-fertilization or the wind could carry some pollen from something from somewhere else.

So it had to be done very carefully. He set it up.

And his first big-time observation was? Now, again, I know you know all this, so feel free to chime in. In the next generation all the peas were round. We denote generations with an F. F stands for filial meaning children. We sometimes denote them with a G for generation. Anyway, I tend to use F, and most geneticists tend to use F. The parental generation here is called F0, the first generation is called F1, the second generation F2, etc. So why was this a big deal? This was a huge big deal.

If you took a poll, a CNN Gallup poll of Braunau at that time and you ask voters what do you think would happen if I cross a round pea to a wrinkled pea, what do you think the majority of voters would say?

Well, maybe half and half or maybe all a little wrinkled, you know, a little puckered or something like that.

The notion that one trait would be totally dominant over the other trait was by no means the general thinking. And you know what?

It wasn't even the general case. If you took plants, you guys must know. If you take plants and you cross them, the F1 usually looks like some kind of a mix. It's some kind of a blend between the two. And, of course, that's because you're really looking at situations where you're crossing things in which zillions of different traits are being inherited and it's a hodgepodge. But Mendel had a situation here where he got an absolutely crisp dominance of one trait over the other. And so wrinkled completely disappears, round dominates, wrinkled disappears completely.

Now, next he does another generation.

He goes to the second generation. And here he does this by selfing this plant. That is he simply kind of puts a bag over it and lets its own pollen fertilize itself or he takes a little brush and he brushes its own pollen onto it. And in the next generation his remarkable thing was he saw some rounds and some wrinkles.

What was remarkable about that?

Wrinkled came back. I thought wrinkled was gone.

And it didn't come back in some half-hearted way like a little puckered. It came back fully, totally, every bit as wrinkled as the parental wrinkled. And the rounds were every bit as round. These were discrete traits.

Wrinkled reappeared, and it reappeared with no loss.

No change in the phenotype, no change in the appearance. And that was very important because at the time some of the predominant models were blending of traits. And you would never imagine, if I were to take grape juice and water and blend them together to get some kind of pinkish thing that I would be able to separate that back out into clear water and deep dark grape juice.

But somehow this trait had appeared. Thus, the trait was discrete. Big difference. Big news. This trait could be found still lurking there. It was merely hidden in the first generation. Mendel did one other thing, dear to my heart as someone trained as a mathematician, he counted. When he counted up the rounds and the wrinkles he found what?

Sorry? Three to one round to wrinkled? No, it's not. He found 5, 74 to 1,850. That's what he found.

Now, what do you recognize about that?

Three to one? No, it's not. It's 2.96 to one.

It's not three to one. What's this three to one business?

[LAUGHTER] Why isn't there a famous 2.96 to one rule?

No, no, I'm serious. Mendel did one more thing. He counted.

And then he did something a little bit outrageous.

He intuited. He said although the data do not say three to one, notwithstanding your textbook, I think the data are trying to tell me it's three to one. [LAUGHTER] This is part of science.

I'm sorry? Two sig figs, right. You know, this is actually a big deal because so many people are unwilling to kind of look at their data to say what's the data trying to tell me?

And, of course, there are so many people who are too willing to look at their data and say what's the data trying to tell me? Because you can go off the tracks in both directions.

So Mendel tried some experiments, 3.04 to one, 2.91 to one, etc. And occasionally, yes? No. How could he?

Nobody had done this. He had no textbooks he could consult. So do you think it's possible he experimented with other things that didn't show these properties and said maybe these are lousy traits to work on. I'm getting such good results on wrinkled, let's stay with wrinkled for a while. That is an incredible act of experimental judgment to know that some problems are too complicated, we'll come back to them later. It's not cheating.

You get to say this is an interesting problem, I'm going to work on it. Not only that. I'll tell you, occasionally Mendel did these experiments and he got completely abhorrent results. They didn't match three to one at all. You know what he did? He threw out the data. Do you know why? No, not small sample.

Large numbers. He's sitting there in this garden.

You know, I've actually been to Mendel's monastery.

He's in the garden in Braunau. Remember, he's got to go cut off the little pollen producing organs, he's got to paint the stuff. What if he screws up? What if the wind blows and stuff like that? If an experiment was way off, he had to consider the possibility that he just screwed up because he hadn't gotten to it soon enough and pollen had blown in and had fertilized his plants.

Now, boy, that's a dangerous thing to do, discarding data.

But let's be honest. Sometimes experiments screw up.

And if an experimentalist hasn't got enough judgment to know that sometimes you cannot believe the data you also can go wrong.

So Mendel, who sometimes is accused for cheating for that, it's not at all cheating. What you have to do is say, OK, I've got a problem here. I'm going to redo this experiment a bunch more times. I'm always getting about this three to one thing, but occasionally I get something that's way off there and I feel comfortable saying that's an error. You can go wrong with that, but Mendel exercised very good judgment in excluding that rather than trying to muck this all up by saying occasionally I get something weird. So I know the textbook summarizes this beautiful 3:1 ratio, but so much creativity. First discipline of counting and creativity of interpretation went into all of this. So in the modern world what would Mendel do? In the modern world, upon seeing this three to one result which he, I will note, he saw for a couple of other traits.

Actually, what he did next was he wanted to explain -- This was also part of his brilliance. He made a model, the model of what was going on. Mendel said how can I possibly explain this beautiful observation that for round and wrinkled, and for other traits, I observe an approximately 3:1 ratio in the F0, F1 and F2 generations? Mendel, my heart beats for Mendel. Oh.

A mathematician he is. He says let's make a very simple model. Let's assume that there are two factors of the control inheritance of this trait. I'll call them big R and little R.

The round plants have big R and big R. They have two copies of this factor that controls shape. The wrinkled plant has two copies of the factor that control shape, and the copy of the factor they get is different. So the flavor here is big R, the flavor here is little R.

This has two copies, this has two copies.

And let's assume that this plant transmits one at random of its two factors onto the next generation. It will transmit a big R. Let's assume that this transmits one of the two at random.

It will transmit a little R. And that plant there in the middle will be big R over little R. And what will big R over little R be as an appearance? How does he know that that's going to be round? Sorry? From the result.

He knows because that's what happened. It's not an overwhelming reason. But to make the data work he's got to say, well, then this must be round. OK? So no points for that. He's just fitting the data. Then here, when you self this, the two parental gametes transmit either a big R, so we'll put it over here, big R, big R, little R, little R, they transmit. And the offspring are of that type.

You can either get that. Question there?

Could be. So he had some knowledge.

But, of course, this is his model.

He's entitled to make his model. And you're saying he had good reasons to think in these. So everybody knows Mendel's model, right? So, now, in the modern world, the minute you've got data like this and you've got a model to explain it, what do you do?

Publish. So Mendel, let's put Mendel as a young assistant professor who is all fired up about these results, writes this up for publication in Nature. It's a short thousand word letter to Nature, let's say. And he races it off, he emails it to the offices of Nature in London.

Because he's in Europe, he'll use the London office of Nature saying I have this amazing result, I did these crosses.

Here are the results here. And I have a model that explains the data perfectly. What does Nature do? Sorry? Why does it reject it?

Well, the first thing he does is sends it out to referees, right? The way that scientific publication works is it chooses two or three anonymous referees. It sends the paper out anonymously to those two or three referees for comment saying we've received this interesting paper from this young monk in Austria.

What do you think about it? Give us your opinions? Please write back in two weeks, etc. So you're the referees.

You get Mendel's paper. What do you advise Nature?

Publish or not? No. Why not? It's outrageous.

Why? It's never been heard of. Yeah, that's great.

But, I mean, you sound like a very conservative, you know, you cannot write that. You cannot say it's wrong because it's never been heard of. Yeah? Regenerate.

It would be wonderful if referees could regenerate the result themselves, but it's not practical. For one thing, it takes a long time to grow peas. They might not have those strains of peas. The best test really would be independent replication of this, but unfortunately you cannot get the referee to reproduce each result before accepting the paper. So you have to go on the own internal results of the paper. Has Mendel proved his case for this model? How many people vote Mendel has proved his case for the model?

He's my hero. How many people vote that he hasn't proved the case?

How many people are conscience abstainers? [LAUGHTER] OK. Who says he hasn't proved the case? Why? Exactly.

I mean, great, the model fits the data. He had the data first and he made a model to fit it. Big deal. So you would say?

Yes, he should be able to make a variety of predictions.

That would be a confirmation of a model, at least the beginning of a confirmation of a model is he could make some predictions based on a model. But an ex post facto model to explain the data you already have, of course you're going to have one.

It might be a little whacky, but you always make a model to explain your data. That's not the hard thing. Now give me some predictions.

So, guys, give me some predictions. We write back to Mendel saying we find the author's work to be of interest, it's a provocative and unheard of finding, and it's a fascinating model, but it is just a model. We'd like to see some predictions verified.

So what would they be? Sorry? Color.

Oh, show me more traits. OK. Fine. We want to see more traits. In addition to seeing some more traits, and Mendel actually did have more traits in the paper. I'm just simplifying here. Prove this model. What predictions would you make if this model is correct?

Yes? Keep crossing them. So tell me what you would do.

Please send him instructions here.

OK, so you would like me to cross one of the rounds, an F2 round by a wrinkled. What will happen in the next generation?

How do I do that? I don't have DNA sequencing available or anything, so. [LAUGHTER] See what happens.

So what might happen? What is this round plant here?

What might it be? And what are the probabilities of that?

One-third of the time it will big R, big R. Two-thirds of the time it will be big R, little R. If it is big R, big R then the offspring will all be what? Round. If, on the other hand, it is the case that that's big R, little R then the offspring will all be?

They won't be all anything. They'll be half round, a 1:1 ratio of round to wrinkled. OK? That's an odd prediction that a third of the time the offspring from such crosses will all be round and two-thirds of the time the offspring will be 50/50 round and wrinkled. You wouldn't normally think of that, right? That's the kind of thing that has to be done.

And Mendel, of course, did crosses like that. I simplified here. This is really what Mendel did was demonstrated that all sorts of predictions would be satisfied.

Another prediction that Mendel could make, oops.

Stop, stop, stop, stop. Which should be wrinkled?

Oh, my goodness. Oh, wrinkle that pea. OK. Onward.

Thank you very much, Claudette. That's good.

So he made more and more predictions like this. His predictions, for example, let's just take that F1 pea, round over wrinkled here.

If you cross this back with wrinkled then it's pretty simply because then always, if this is an F1 as opposed to an F2, you're going to get a 50:50 ratio of round to wrinkled.

Moreover, these rounds, if you cross them back, will still give you a 50:50, etc. That's science.

That's the heart of science, is being able to look at data, intuit what the data is trying to tell you, build a model and test a model. All of that is in Mendel. OK? So I know you all know Mendel, but this Mendel really. OK? Now, some definitions.

I need to give you, so Section 2, some definitions.

Because I've been skirting around using some words here.

OK? Number one, the word gene. Gene is one of these factors of inheritance controlling a trait.

Mendel didn't use the word gene. The word gene came along much later.

The variant flavors of a gene, big R and little R, are known as alleles from the Greek word meaning other. These are the alternative forms of a gene.

It can come in the form big R, little R. I might write big A, little A. I might write plus for normal and M for mutant.

There are a lot of different notations geneticists use for that.

The word phenotype means appearance. The plant was round. The peas were round. That's a phenotype. The individual was 7" 7' tall.

That's a phenotype. OK? Those are phenotypes. Genotype means the pair of alleles carried by the individual.

Big R, little R is a genotype.

Big R, big R is a genotype. Little R, little R. Those are genotypes.

An important difference between genotype and phenotype.

Other important words so that we can actually talk to each other.

Homozygous or homozygote. A homozygote is an individual who has a genotype that has two of the same alleles. Two copies of the same allele, the individual is said to be homozygous.

And, alternatively, an individual is said to be heterozygous, heterozygote if they have two alternatives.

A couple of other important definitions.

A phenotype round is said to be dominant over a phenotype wrinkled if what? If the heterozygote shows that phenotype, the heterozygote between pure breeding strains. So phenotype one, pheno one is dominant over phenotype two if the F1 of pure breeding strains shows phenotype one. Similarly, we have the word recessive. Now, I'll mention, and you will then proceed to promptly forget, because all of my colleagues forget, dominant and recessive do not refer to alleles. Big R is not dominant.

Round is dominant. Big R is an allele. Now, you say who cares?

The textbooks get this wrong all the time, it's true.

You won't even find the textbooks use this correctly.

They will tell you big R is dominant.

What if it turned out that big R controlled three different traits?

Maybe roundness. An ability to grow with low salt in the soil.

An ability to bloom in May. Some of those traits might be recessive.

Some of them might be dominant. We know examples of that, where the same allele can control multiple traits, some of which show dominance, some of which show recessiveness.

So real card-carrying geneticists try hard to use the word dominant and recessive to refer to phenotypes, not to alleles or genotypes.

Now, since 80% of the facility in the Biology Department don't use the word with that degree of precision, I don't have high hope that you will either. But I'm going to try to say the words dominant and recessive refer to phenotypes. OK? This is a geneticists' kind of hang-up. We all have our shtick, but this one of mine, is that these really do refer to phenotypes. And it's quite important because otherwise you could get quite bollixed up. And I'll come to a case with sickle cell anemia where you won't be able to describe the sickle cell anemia allele as recessive, dominant or co-dominant.

OK? Good. Those are some definitions. They're worth knowing.

If we get those definitions right the rest of it is pretty easy. All right.

So Mendel publishes this paper in 1865. It's accepted.

It appears not in Nature but in the proceeding the Royal Academy of Braunau and it's published. And what happens?

Nothing. It sinks like a stone. Mendel's paper is totally ignored.

Nobody really pays any attention to it. This paper was sent to many people. Charles Darwin has a copy of Mendel's papers in his files.

But, in those days, the way printing worked, in order to read a book you had to slit the pages open.

Darwin never slit the pages of Mendel's paper, so it's pretty clear he never read the paper, even though it had the answer to much of what he wanted to know about evolution.

No one really read Mendel's paper because it was so far ahead of its time, it just was pretty strange. It had all these concepts. And, anyway, you could always dismiss it with that kiss of death of biology "it's just the model". Right? You can kill things with "it's just the model". People were just not prepared to deal with Mendel. So Mendel, in fact, poor Mendel, maybe he had a good time, I don't think, instead didn't really do much more on this topic of genetics per se.

He became an administrator. Became abbot of the monastery and did other things. Worked on meteorology, etc. And we don't really hear from Mendel again. So what really begins to reignite interest in this is the understanding in the late 1800s of chromosomes. Very briefly, cytologists, people studying cells in the microscope. Cytologists are folks who study cells. They noticed these very funny little structures in cells. They noticed these structures that when you stain then with a dye would stain very funny.

They picked up dye in a certain way. And they noticed that they had this very interesting choreography that when a cell underwent mitosis these funny things would divide down the midline and these little x-shaped structures would go to the two daughter cells like this.

That is these Xs would become single individual pieces. Again, you know about these things.

They had no clue what these were. What is the appropriate scientific procedure when you have no clue what something is? You need to give it a name that somewhat covers up the fact that you have no clue what you're talking about because it sounds much better than just saying they are "these funny things". And so they were referred to as chromosomes, meaning literally colored things. [LAUGHTER] You need to understand these sorts of things. OK? So these chromosomes here, these colored things, for lack of any other knowledge of them, that was the property they could be given. Chromosomes.

Look it up. They executed this very interesting choreography during mitosis. That is cell division. Oh, boy, is that going to be noisy.

Someone should shoot it and put it out of its misery. [LAUGHTER] All right.

But what they then noticed was the following. And we're going to run just a couple of minutes over. I'm going to keep it short. But they noticed that when organisms made sperm and eggs rather than normal cell division, they noticed that these chromosomes, instead of all of them lining up on the midline, lined up in pairs.

And the pairs underwent a series of two divisions.

There was a first division which we call meiosis one in which -- -- one copy of each of these Xs went to each daughter cell. Very different than mitosis where the Xs would be split down the middle. Then a second division occurred, meiosis two. And in that each of the daughter cells now the X is divided.

And they got that. This one looked, for all the world, like mitosis. But instead, at the end of the day instead of ending up with four chromosomes, here we end up with only two chromosomes in each gamete, sperm or eggs. And what happened was from this pair, one member of the pair was selected. Now, this is either producing sperm or eggs. When a sperm like that came together with an egg like that and fertilization occurred, you get back to four chromosomes. You all know this. You learned this in high school. But the important point about this was that people said, ha, things lining up in pairs, one copy of each going to the offspring, then a copy from mom and a copy from dad restoring the pair. Sounds just like what that dead monk was talking about. [LAUGHTER] It was just the reason people really didn't think much of Mendel's paper was because it was so abstract. What were these genes? He didn't point to anything. There was nothing concrete. And folks hate that. By contrast they now began to see things and vaguely remembered that this was just like what Mendel's story was about. And three different groups around the world began to redo this work on crosses and all that.

And wonderfully in 1900 three groups simultaneously published papers about this. Now, Mendel's Law is rediscovered.

Now, the explanation here. How does the cytological observations about meiosis explain Mendel's laws of inheritance of traits?

Very simply. All you have to imagine is that big R is being carried on one of these chromosomes. Little R on the other one.

And then half the offspring had big R, half the offspring had little R.

All of Mendel's laws can be implemented by simply assuming that genes and the alleles of those genes live on these chromosomes.

So it's beautiful, except for one problem. You may remember from your high schools that Mendel also had another law about more than one trait, pairs of traits. Not just that we have this segregations of alleles away for one trait. What was his law about two traits? We'll go over this next time. What was his law about two traits, like round and wrinkled and green and yellow?

That they would be inherited independently of each other.

How would that fit into this model? Different chromosomes. They'd be on different chromosomes. But what if I had three traits?

Eventually, if I had, now, peas actually have seven pairs of chromosomes. So if I study eight traits in peas, two would have to lie on the same chromosomes. So then the chromosome model would contradict independent inheritance. So either Mendel cannot be right with this other law of independent inheritance that you learned about or the Chromosome Theory cannot be right of these living on these physical molecules and getting distributed that way.

Right? So we have a deep problem because either Mendel, my hero, is wrong or this chromosome model is wrong.

And the problem is we don't have enough time to resolve this today, so we're going to have to come back on Wednesday and figure out what happens.

What's human? What's animal? And what of the biology in between?

F riday's report by the Academy of Medical Sciences on the increasingly fuzzy boundaries between the human and the animal is the latest in a long series of policy reflections on how to keep pace with developments in the biosciences.

It can justly be said that politics and regulation have not dealt well with our newfound capacities for muddying the boundaries between us and other species. And yet the last two decades have witnessed an unprecedented growth in bioscientific techniques that increasingly call into question what it means to be human. Take the human genome project: many of us may have intuitively suspected that we might have more genetically in common with the chimpanzee than even Darwin had envisaged, only then to be told of our cousinly closeness to the fruit fly, maize and the zebra fish.

Casting a glance back to the 1990s, trans-species transplantation seemed to promise a new era of limitless animal organs and tissues. Who knows, it may still. But that dream slowly sank from view amid concerns about potentially catastrophic trans-species disease, and increasing evidence of its poor performance in preclinical trials with primates. Move forward a decade and we have the trans-species embryo debate, resulting in legislative changes permitting a whole new class of research embryos incorporating animal DNA. So to the classical question of "what is an embryo", has been added the equally vexing puzzle "what is an animal".

Bioscientific hybrids are difficult to categorise, disorderly, existing on the fringes of the humanised animal and the animalised human. And yet policymaking has arguably had a poor track in getting to grips with and understanding trans-species innovation. Trans-species biologies present acute difficulties especially in terms of regulation because they confuse and traverse regulatory institutional boundaries.

In the UK, as elsewhere, regulatory agencies have tended to regulate humans on the one hand, and animals on the other, with little consideration for what might lie between. The tendency has been to deal with all things animal through the Home Office and its Animal Procedures Inspectorate, and to deal with all things human through the Department of Health. There are good and disturbing grounds for suspecting this division has become increasingly naive and meaningless, as the biosciences enter their trans-species future.

In the late 1990s the UK deemed it necessary to establish a regulatory body to manage the many murky trans-species hybrid implications of xenotransplantation, the UK Xenotransplantation Interim Regulatory Authority. But far from being a porous conduit between the DoH and the Home Office, UKXIRA found itself hamstrung. The Home Office would seek its advice on animal experiments involving primates but would not allow the authority to see confidential trial applications or the results of previous studies. This proved to be a poor basis on which to advise the DoH about the wisdom or otherwise of proceeding to clinical trials with humans. UKXIRA wasn't perfect, but it represented an important attempt to overcome the regulatory divide between the human and the animal. The government's decision to disband UKXIRA in 2006 could justifiably be viewed as myopic and short-sighted, given the trans-species direction of travel in the biosciences. In losing UKXIRA, the UK also lost important institutional experience and a model for dealing with interspecies biotechnological developments.

Even more recently, the UK trans-species embryo debate points to equally serious flaws in the regulation of the wild indeterminate zones between us and other animals. One strategy evident in the run-up to changes in legislation allowing the creation of trans-species embryos was to downplay that they might be trans-species at all. Just reflect for a moment on shifts in the language used to describe these embryos: the DoH, for instance, started out talking about "trans-species embryos" before finally settling on its preferred term, "human admixed embryos". In other words, these embryos might be a bit mixed up, but they're essentially human. No worries.

Such embryos would allow stem-cell scientists to use animal eggs rather than scarce human eggs to create stem-cell lines. The animal nuclei could be removed and replaced with human nuclei leaving only a residue of animal egg DNA behind. It was striking to see this process now described by some stem-cell scientists as "especiation" in place of the more scientifically conventional term "enucleation". In this way, the vexing animal is tidied away behind a thin veneer of language and rhetoric.

More worrying is the continuing confusion over whether trans-species embryos should be regulated by human or animal agencies – again, the Home Office or the DoH. That boundary comes down to potentially confused assessments of whether it is the animal or the human which "predominates" in the resulting embryo. I had the privilege of discussing this recently with an eminent UK reproductive scientist who had been involved in crafting the legislation. "Ultimately," he said, "it has to be either human or animal to be regulated . otherwise we would have to do away with our whole regulatory edifice." Well, that is exactly what we may have to do.

It could be argued that the report by the Academy of Medical Sciences searchingly arrives at a point of dissatisfaction with the bipedal and binary regulation of transbiology. Perhaps it's time for an overhaul of our institutions, their language and assumptions about what it is to be human, animal and the many murky zones in between.

Constructing an Animal Phylogenetic Tree

The current understanding of evolutionary relationships between animal, or Metazoa, phyla begins with the distinction between “true” animals with true differentiated tissues, called Eumetazoa, and animal phyla that do not have true differentiated tissues (such as the sponges), called Parazoa. Both Parazoa and Eumetazoa evolved from a common ancestral organism that resembles the modern-day protists called choanoflagellates. These protist cells strongly resemble the sponge choanocyte cells today (Figure 2).

Figure 2. Cells of the protist choanoflagellate resemble sponge choanocyte cells. Beating of choanocyte flagella draws water through the sponge so that nutrients can be extracted and waste removed.

Eumetazoa are subdivided into radially symmetrical animals and bilaterally symmetrical animals, and are thus classified into clade Bilateria or Radiata, respectively. As mentioned earlier, the cnidarians and ctenophores are animal phyla with true radial symmetry. All other Eumetazoa are members of the Bilateria clade. The bilaterally symmetrical animals are further divided into deuterostomes (including chordates and echinoderms) and two distinct clades of protostomes (including ecdysozoans and lophotrochozoans) (Figure 3). Ecdysozoa includes nematodes and arthropods they are so named for a commonly found characteristic among the group: exoskeletal molting (termed ecdysis). Lophotrochozoa is named for two structural features, each common to certain phyla within the clade. Some lophotrochozoan phyla are characterized by a larval stage called trochophore larvae, and other phyla are characterized by the presence of a feeding structure called a lophophore.

Figure 3. Animals that molt their exoskeletons, such as these (a) Madagascar hissing cockroaches, are in the clade Ecdysozoa. (b) Phoronids are in the clade Lophotrochozoa. The tentacles are part of a feeding structure called a lophophore. (credit a: modification of work by Whitney Cranshaw, Colorado State University, credit b: modification of work by NOAA)

Animal Behavior

Did you ever see a dog sit on command? Have you ever watched a cat trying to catch a mouse? These are just two examples of the many behaviors of animals. Animal behavior includes all the ways that animals interact with each other and the environment. Examples of common animal behaviors are pictured in Figure below.

Examples of Animal Behavior. Can you think of other examples of animal behavior besides the three shown here?

The branch of biology that studies animal behavior is called ethology. Ethologists usually study how animals behave in their natural environment, rather than in a lab. They generally try to answer four basic questions about the behaviors they observe:

  1. What causes the behavior? What is the stimulus, or trigger, for the behavior? What structures and functions of the animal are involved in the behavior?
  2. How does the behavior develop? Is it present early in life? Or does it appear only as the animal matures? Are certain experiences needed for the behavior to develop?
  3. Why did the behavior evolve? How does the behavior affect the fitness of the animal performing it? How does it affect the survival of the species?
  4. How did the behavior evolve? How does it compare with similar behaviors in related species? In what ancestor did the behavior first appear?

Bacteria Kingdom

Patrick has been teaching AP Biology for 14 years and is the winner of multiple teaching awards.

The Bacteria Kingdom, formerly called monera, are single celled prokaryotic organisms. Bacteria encompass two domains: eubacteria and archaea. Eubacteria and archaea have very different cell walls. They are also distinguished by their DNA - the DNA of archaea has histone proteins while that of eubacteria does not.

Under traditional classification schemes Monera is the name of the Kingdom of Bacteria but in most modern textbooks, scientists due to the big diversity in the group that we normally call bacteria because there are such diversity, scientists are starting to split that into two other groups called Domains. One of these Domains is called Eubacteria, the other Domain is called Archea. So what are some of the characteristics of the Eubacteria or "true bacteria" well they're all prokaryotic which you should know what that means? They have cell walls made of a mesh between polysaccharides and amino acids called peptidioglycan.
They have what is called naked DNA what does that mean, just means it doesn't have the histone proteins that Eurkaryotic DNA like ours is wrapped around to help organize it. They have what I sometimes call "prokaryotic-style" ribosomes which if you really want to look at the details of, go ahead and Google it but most of the time you don't need to know that. And what are some examples of it, this is a huge group with huge diversity within it, it includes the photosynthetic cyanobacteria that are a major source of oxygen and food in many ecosystems. There is the nitrogen-fixing bacteria that are in our soil that help provide materials for our plants. There's lots of different kinds of Eubacteria.
The Domain Archea is a little bit unusual, now they're all prokaryotic however they have unusual cell walls made out of not peptidioglycogen but these weird other polysaccharides, even their cell membranes have unusual phospholipids within them. They don't have naked DNA like majority of the prokaryots do instead they have histone proteins wrapped around their DNA. They have "Eukaryotic-style" ribosomes, these two factors are one of the major reasons why scientists now think that ultimately the eukaryotes like ourselves and plants ultimately evolve from the Archea. Now they also have a number of different roles in the environment, many of them are Methanogens which means they're the things that in your large intestine and especially in the large intestine of things like cows. They're the things breaking down some of the undigested polysaccharides to produce methane. Halogens they inhabit really weird unusual environment and the Halogens they love salty water because by living in that kind of environment they're able to avoid competition from a lot of the other creatures. So usually they get lumped together into this group called extremophiles which simply means they love the extreme environments, and those are the bacteria.

WATCH: This Two-Minute Synthetic Biology Video Is A Far-Out Vision Of The Future

In this conception of bio meets space tech, a SpaceX capsule journeys through the cosmos. The outer . [+] shield self-repairs while other parts of the ship convert waste carbon into useful materials.

Most of my professional life is centered on synthetic biology, an industry and movement to make biology easier to engineer. So far, this emerging discipline has yielded everything from living medicines and spider silk jackets to impossible hamburgers. But what will humankind be growing in the next century?

I came across a magical video that I think helps to show this. Vasil Hnatiuk, an Emmy award-winning animator, who has since become a friend, created this beautiful answer. In just two minutes, he invites us to see a universe where manufacturing, transportation, entertainment and more have all been radically transformed through the power of synthetic biology.

The video features flying vehicles inspired by insects, an excavator crossed with a crab, a supercomputer made from actual neurons, and much more. How are all these bits of science fiction connected? By unlocking the DNA code, Hnatiuk explains, our species could usher in the greatest technological advancement ever witnessed.

You could call me a bio-futurist, but what do the founders of the field think?

I asked famed Harvard geneticist George Church for his take on the video: “much of engineering is about reordering matter into other structures in a reliable and affordable way. But life already makes atomically precise objects at large scale, and it does so inexpensively.” To expand the kinds of things that can be built with biology, figures like Church are leading the push to make DNA easier to read, write and edit.

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In imagining how to grow buildings of the future, synthetic biologists consider how to impart the . [+] instructions to follow an architectural plan in the same way that nature imparts the instructions on how to become a human, a tree, or a bee.

In construction, this could mean growing rather than building our homes and cities, as Hnatiuk illustrates. Several synthetic biology companies are in the earliest stages of doing this, having produced insulation and other biodegradable building materials using fungus. The biomaterials company Ecovative has already partnered with IKEA, Dell, and other household brands who are looking to move away from styrofoam packaging towards bio-based packaging that’s grown from mushroom roots.

In transportation, this could mean new biological vehicles, both on Earth and in space. Obviously, no one has such a product on the market or is even close, but as I wrote last week, investors like Jeff Bezos who are interested in long-term space missions should take note of the power of engineered biology. NASA is already testing how well algae suck up carbon dioxide when grown on the International Space Station.

A number of non-fictional firms appear in the video essay. A SpaceX logo is clearly visible on a squid-like space-faring vessel, and a giant wasp-inspired racer is stamped with a black horse on a yellow shield — the unmistakable mark of a Ferrari. These corporate nods are reminiscent of the very real fact that many of the biggest brands are taking an interest in synthetic biology, from Microsoft’s project around storing data in DNA to the North Face’s spider silk jacket with partner Spiber. United Airlines has even begun using bio-based jet fuel made by companies like Lanzatech, which is using engineered microbes to convert waste CO2 into fuel.

“We don't yet fully understand the power of the genetic code, and we have only scratched the surface of its potential,” said Axel Trefzer, director of synthetic biology research and development for the biotech supply company ThermoFisher. “I strongly believe that engineering biology will bring us many advancements that we can't even envision today.”

Artist’s conception of what a bioengineered flying sports craft could look like in the future. . [+] Fasten your seat belt — the future will be built by biology.

Are far-out animated visions of the future useful? Stanford bioengineer Drew Endy, one of the founders of the field of synthetic biology, believes such work is “absolutely essential.” Depicting technology as it might be, rather than simply how it is today, offers a chance to reassess what is considered possible. “Too many people are simply recreating the status quo.”

Elon Musk clearly gets this message. As part of a 2016 effort to inspire the public into believing in his plans to get humans to Mars, Musk’s rocket company SpaceX released a four-minute animation of its theoretical Interplanetary Transport System. The video has since racked up over six million views on YouTube, and SpaceX’s valuation now exceeds $30B. Visions of the future can inspire long before they ever have a chance of becoming true.

Science fact versus science fiction

Stanford’s Endy is skeptical about ever riding in a tentacle-clad spaceship. The vacuum of space is rather unforgiving to life. But synthetic biology “fully realized”, he said, would result in “practical mastery of joules, bits, and atoms, together.”

Many people expect more flying drones in the future, but could we really be riding on giant engineered animals? I asked Church what he thought of the video’s more fantastical visions.

“The largest flying animal was Quetzalcoatlus northropi at 200 kilograms,” he said. “It could fly at 130 kilometers per hour. This is probably not the upper limit, but it is likely very hard to beat a 285,000 kilogram Antonov-225 or the X-15 at 7,200 kilometers per hour.”

In this depiction of Quetzalcoatlus northropi, a juvenile titanosaur has been caught by one . [+] pterosaur, while the others stalk through the scrub in search of small vertebrates and other food. Biology can grow very big things.

Mark Witton and Darren Naish

How about cities grown from seeds?

“The tallest building is the 828-meter tall Burj Khalifa in Dubai. The tallest tree is a Sequoia sempervirens named Hyperion that stands at 115 meters tall.”

Church noted human brains perform at 20 watts, which is far more power-efficient than the best silicon computers. His research group at Harvard has worked to fully map activity in the human brain and is even growing miniature ones to better understand how they function.

It is not hard to see that rewriting the code of life will lead to new insights and cures. But visions like Hnatiuk’s are important reminders that, when it comes to this new century of biology, we ain’t seen nothing yet.

Disclaimer: I am the founder of SynBioBeta, the innovation network for the synthetic biology industry. Some of the companies that I write about are sponsors of the SynBioBeta conference (click here for a full list of sponsors).

The Animal Model

Although humans and animals (technically “non-human animals”) may look different, at a physiological and anatomical level they are remarkably similar. Animals, from mice to monkeys, have the same organs (heart, lungs, brain etc.) and organ systems (respiratory, cardiovascular, nervous systems etc.) which perform the same functions in pretty much the same way. The similarity means that nearly 90% of the veterinary medicines that are used to treat animals are the same as, or very similar to, those developed to treat human patients. There are minor differences, but these are far outweighed by the similarities. The differences can give important clues about diseases and how they might be treated – for instance, if we knew why the mouse with muscular dystrophy suffers less muscle wasting than human patients, this might lead to a treatment for this debilitating and fatal disorder.

At a physiological and anatomical level, humans and other animals are remarkably similar

We share approximately 99% of our DNA with mice (1), and moreover, we can use “knockout” mice to work out what effect individual human genes have in our body. We do this by “turning off” one of the genes in a mouse, common to a human, and seeing what effect this has on the mouse. By recreating human genetic diseases in this way we can begin to look for treatments.

Nobel Prizes and animal research

For just over a century the Nobel prize has been awarded each year in recognition of the world’s greatest medical advances. Of the 108 Nobel Prizes awarded for Physiology or Medicine, 96 were directly dependent on animal research. Animal research underpinned the very first Nobel Prize to be awarded for Physiology or Medicine to Emil von Behring in 1901 for developing serum therapy against diphtheria, as it did the most recent awarded in 2016.

Animal model explained

The role of the animal model is neatly explained in “The Animal Research War”, by Michael Conn and James Parker (2):

If you are going to study a human disease you can’t, for ethical reasons, perform the initial work in humans you have to develop a model. Some models may be in vitro – literally, in glass tubes – but as you learn more and more, you must eventually test ideas in vivo– in living animals. That means you have to have a way of producing the disease that allows you to study it.
Let’s consider AIDS, one of Podell’s interests. You could take its causative agent, the Human Immunodeficiency Virus (HIV), grow it in a test tube, and kill it by pouring bleach on it. Do you now have a way to kill HIV? Yes, you do. Do you have a treatment that can be used in humans? Absolutely not: bleach is toxic. Killing HIV in a test tube and killing it in a living animal are two very different accomplishments.
To complicate things further, viruses grow differently in test tubes than in humans. Humans have an immune system: test tubes do not. A virus growing in a test tube is not a good model for the human disease, but drugs that don’t kill the test tube virus probably won’t work in humans either – and these might be eliminated from further consideration.
Animal models allow closer approximation to a human response. They are not perfect, of course animals host different diseases and different responses. While the fundamentals of life are the same – there is a 67 percent similarity between the DNA of humans and earthworms – there are differences in species and even in individual animals. Some animals are good human-like models for one thing and some for another some have a cardiovascular system that is similar to humans while others have similar skin.

Current examples of animal research in medicine

Find hundreds of examples of how animal studies have contributed to medical breakthroughs, please see our Research Index, which lists all our posts categorised by either the species involved, or the disease addressed.