Session 4: How is Evolution Measured

00:00:07.24 Hi. My name is Melina Hale.
00:00:09.08 I'm a professor at the University of Chicago.
00:00:11.14 In my lab, we study neurobiology,
00:00:13.10 biomechanics,
00:00:14.22 and evolution.
00:00:16.09 I'm going to present two different topics.
00:00:18.12 The first is an introduction to evolution.
00:00:22.12 Then we'll go on to talk about
00:00:24.10 a specific example from my lab
00:00:26.26 of how we map the nervous system
00:00:29.20 and aspects of the nervous system
00:00:31.12 onto the evolution of animals.
00:00:33.18 We work in my lab, specifically,
00:00:35.06 on vertebrate animals,
00:00:36.18 things like fish and tetrapods,
00:00:38.17 mammals, and reptiles,
00:00:40.27 and so I'm going to focus on that
00:00:43.07 part of biodiversity
00:00:45.07 in my talks.
00:00:46.22 There's a lot of other organisms out there, of course,
00:00:49.08 invertebrates, and insects, and plants,
00:00:51.18 and microbes,
00:00:52.26 that we won't touch on in these lectures.
00:00:55.26 So, we'll start with this introduction into evolution.
00:00:58.10 What is evolution?
00:01:00.05 Now, Charles Darwin
00:01:02.13 originally proposed the theory of evolution,
00:01:05.00 which can be summarized
00:01:06.27 in a very succinct phrase:
00:01:08.14 descent with modification.
00:01:10.05 Now, let's break that down a little bit, though,
00:01:12.17 to a broader definition,
00:01:14.22 which is change in the heritable characteristics
00:01:17.10 of organisms
00:01:18.29 from generation to generation.
00:01:20.29 We can break that down
00:01:22.13 even further to look at
00:01:24.11 the component parts of that sentence.
00:01:25.18 First, if we think about
00:01:27.03 this idea of generation to generation,
00:01:29.12 that means that when we look at evolution,
00:01:31.05 we're really not talking about changes
00:01:33.00 in individuals
00:01:34.17 or over short time frames.
00:01:36.01 Instead, we're talking about
00:01:38.04 changes that we see
00:01:39.28 over a long history
00:01:41.23 of the descent of an organism over time.
00:01:45.11 What about heritable characteristics?
00:01:47.04 Well, we all have lots of characteristics
00:01:49.01 to our bodies.
00:01:51.02 We may have big muscles
00:01:52.24 if we exercise a lot,
00:01:54.09 we may have had injuries in our lifetime
00:01:56.11 that have given us scars.
00:01:57.21 Those are not heritable characteristics.
00:02:00.10 Heritable characteristics
00:02:02.02 are the types of traits
00:02:03.19 that we pass on to subsequent generations,
00:02:06.11 or that we inherited from our parents
00:02:08.29 and grandparents.
00:02:10.18 Heritable characteristics
00:02:12.15 are an important part of evolution,
00:02:14.11 because it allows transmission
00:02:17.12 from one generation to the next,
00:02:18.24 and on and on through evolutionary history.
00:02:21.23 Now, the last part of this is change,
00:02:23.29 and change is also really important.
00:02:26.08 There has to be the ability in evolution
00:02:29.05 for these heritable characteristics
00:02:30.29 to vary,
00:02:32.21 to change in response to environmental factors
00:02:35.13 that might favor one type of characteristic
00:02:38.09 or another,
00:02:39.16 and we'll come back to that.
00:02:40.25 And that's what Darwin was getting at
00:02:42.21 with this idea of modification,
00:02:44.13 that there's going to be change
00:02:46.01 in how organisms are organized
00:02:47.24 and how they look over time.
00:02:52.03 So, here's an example,
00:02:53.18 a cute picture of a pair of dogs
00:02:56.07 and their puppies,
00:02:57.19 where you can really see
00:02:59.07 the variation in characteristics,
00:03:00.25 even in one generation.
00:03:02.23 If you look at the parents
00:03:04.11 and you look at the pups,
00:03:05.21 you can see some of the puppies
00:03:07.03 look like one parent,
00:03:08.21 with, you know, pure light fur,
00:03:11.03 others look like the other parent,
00:03:12.27 with very dark fur around the face,
00:03:15.03 but yet there are other puppies in the litter
00:03:17.13 that look different yet again,
00:03:19.04 that have a mix of the characteristics
00:03:21.29 of those two adults.
00:03:24.05 So, you can get a sense
00:03:25.29 of the variation in this image
00:03:27.26 that can be explored in evolution
00:03:30.29 and capitalized upon
00:03:33.06 through evolutionary time.
00:03:35.29 One example of variation
00:03:38.05 that's been really important for us
00:03:40.11 to understand how we can
00:03:43.17 change the characteristics,
00:03:45.07 the features of a species,
00:03:47.14 over time,
00:03:48.28 is the peppered moth.
00:03:50.12 So, these two moths,
00:03:51.23 that look very, very different
00:03:53.06 -- the light one on the left
00:03:54.24 and the dark one on the right --
00:03:56.01 are the same species.
00:03:57.12 They can interbreed.
00:03:58.23 Now, the dark one and the light one,
00:04:00.04 as you might expect,
00:04:02.07 do better in different types of environments.
00:04:06.03 This color characteristic
00:04:08.03 varies, of course,
00:04:10.00 and in some environments
00:04:11.29 it benefits the organisms
00:04:13.21 to be light or to be dark.
00:04:15.02 In other environments,
00:04:16.21 that same characteristic
00:04:18.16 may be detrimental to the animal.
00:04:20.14 So, these peppered moths
00:04:22.10 provided a classic example
00:04:24.01 of how characteristics can vary
00:04:27.07 with environment,
00:04:28.12 and how populations of a particular species
00:04:30.28 can vary.
00:04:32.22 So, this was noted
00:04:34.07 particularly in the industrial revolution.
00:04:36.19 At that time,
00:04:38.00 we went from manufacturing
00:04:39.22 using people
00:04:41.21 sewing or create objects
00:04:43.08 to using a lot of machines
00:04:44.26 to make products.
00:04:47.01 With the use of machines
00:04:48.21 came the use of coal,
00:04:50.25 and with coal came soot,
00:04:52.19 or pollution in the air.
00:04:54.06 Now, with that soot and pollution,
00:04:55.24 you could imagine that structures in the environment,
00:04:59.03 like trees,
00:05:00.19 would become darker,
00:05:01.28 and the peppered moth populations
00:05:04.05 changed in order to accommodate that.
00:05:06.27 And the darker morph
00:05:09.05 of the peppered moth
00:05:11.14 survived better. Right?
00:05:12.26 It was better camouflaged
00:05:14.23 against potential predators in the environment.
00:05:17.08 When the environment cleared up
00:05:19.21 and pollution decreased,
00:05:21.08 the tree barks became lighter
00:05:23.26 and the lighter version of the moth
00:05:25.25 actually survived better.
00:05:27.17 So, we can see variation
00:05:29.00 in the characteristics in a population,
00:05:31.19 even over this short amount of time,
00:05:34.20 and due to a human-induced
00:05:37.07 artifact in the environment,
00:05:38.09 this pollution from coal.
00:05:41.01 Now, just to show you how striking
00:05:43.05 this difference can be in the camouflage
00:05:45.05 of these moths on trees,
00:05:46.29 we can see some here.
00:05:48.19 So, here's our dark morph and our light morph,
00:05:50.17 and if we look at this tree,
00:05:51.28 we can see both the dark morph
00:05:53.15 and the light morph.
00:05:54.19 Here's the light one right down here,
00:05:56.20 and you can see it better camouflages
00:05:58.00 against the light bark
00:05:59.17 in this healthy tree.
00:06:01.05 The dark morph stands out against that light tree,
00:06:03.27 expect in this area over here,
00:06:05.22 where it's against this injury to the tree,
00:06:08.09 which shows up darker.
00:06:10.03 Another example in variation in populations
00:06:14.08 that we've probably all had experience with
00:06:16.14 is in bacteria
00:06:18.19 and the treatment of bacteria with antibiotics.
00:06:21.06 So, when we go to our doctor's office
00:06:22.26 with a bacterial infection,
00:06:24.08 we're prescribed antibiotics,
00:06:26.06 medicine to kill those bacteria,
00:06:28.19 and doctors are often very specific
00:06:31.09 about the need to take that medicine
00:06:34.11 over a precise time course,
00:06:36.11 and in particularly they say,
00:06:37.27 "Don't stop the medicine early.
00:06:40.12 You have to take the full course of medicine.
00:06:42.19 Even if you're feeling better,
00:06:44.21 take the full course of medicine."
00:06:46.07 It's important to do that.
00:06:47.25 Why is that?
00:06:49.02 It's because of the selection
00:06:51.00 that's acting on the variation in the population.
00:06:54.13 So, when we have a bacterial infection,
00:06:57.00 the species of bacteria
00:06:58.27 that's in our bodies
00:07:00.07 may have lots of variants to it,
00:07:02.04 and this is shown in number 1 on the left.
00:07:04.06 They might vary in aspects of their biology,
00:07:07.16 including how strong they are,
00:07:09.01 how resistant they are
00:07:11.01 to antibiotic medicines.
00:07:12.27 If we treat them,
00:07:15.06 shown in point 2 over here,
00:07:17.05 but we don't treat them long enough,
00:07:19.14 which are the bacteria
00:07:21.03 that are going to survive?
00:07:22.12 It's going to be the ones that are the strongest,
00:07:23.28 that are the most resistant
00:07:25.25 to the medication.
00:07:27.06 So, if we don't kill them
00:07:29.03 and we stop taking the medicine,
00:07:30.26 they'll be able to multiply
00:07:32.24 and will take on a larger part
00:07:34.28 of the population
00:07:36.20 of the bacteria.
00:07:37.25 It's not unless we kill them all
00:07:39.17 that we can prevent those resistant bacteria
00:07:42.06 from then multiplying
00:07:43.28 and becoming a problem
00:07:45.15 for our antibiotic medications
00:07:47.16 down the road.
00:07:49.07 So, I've shown you several examples
00:07:51.08 of how populations of a species can vary,
00:07:55.07 whether it's peppered moths or bacteria,
00:07:58.05 but how do we go from that
00:07:59.23 population-level variation
00:08:01.26 to the evolution of new species?
00:08:05.11 This is called speciation,
00:08:07.13 and in general
00:08:09.15 what happens is that populations
00:08:11.08 of a species
00:08:12.28 will be separated
00:08:14.13 and unable to interbreed,
00:08:16.03 and if they're separated
00:08:18.01 for a long enough period of time,
00:08:19.17 when they come back together
00:08:21.02 they may not be able to interbreed,
00:08:23.27 and then we would call them
00:08:25.25 different species.
00:08:27.02 One of the ways
00:08:28.25 that interbreeding is prevented
00:08:30.16 is through geographic isolation.
00:08:35.06 One of the students in my lab,
00:08:36.18 Andrew Trandai,
00:08:38.07 actually helped me out
00:08:40.13 by developing this hypothetical example
00:08:42.14 that I'm going to show you
00:08:44.23 on what a speciation event
00:08:46.13 might look like,
00:08:47.23 so I have to thank Andrew
00:08:49.19 for all of the images
00:08:50.28 that are coming up in the next series.
00:08:54.06 Okay, so in our hypothetical example,
00:08:56.29 what we're looking at is
00:08:58.29 some rodent squirrel-like animal
00:09:01.00 in an environment
00:09:02.19 -- one species --
00:09:04.06 all together as one population.
00:09:07.20 So, how do we separate them
00:09:09.16 and get new populations to evolve?
00:09:11.17 Well, in Andrew's example, here,
00:09:13.23 we have flooding
00:09:15.29 and an aquatic barrier
00:09:17.27 that these animals cannot cross,
00:09:20.01 so effectively
00:09:21.29 the population in the trees
00:09:23.12 and the population in the sand
00:09:25.19 are separated now
00:09:27.16 and will be evolving independently.
00:09:30.21 Over time, if we look at each of them,
00:09:32.23 we may see differences
00:09:34.12 being incorporated
00:09:37.17 into their biology.
00:09:38.25 Just superficially,
00:09:40.06 we might see the animals
00:09:41.29 that are in the forest
00:09:43.23 turning a different color,
00:09:45.19 other aspects of their anatomy
00:09:47.15 might change
00:09:49.17 to live in the trees.
00:09:51.04 On the opposite side of our river,
00:09:54.18 we may see the populations
00:09:56.07 that are in more of a sandy desert environment
00:09:59.18 change coat color
00:10:01.09 to match that environment,
00:10:02.20 or change size
00:10:04.15 to better adjust physiologically
00:10:06.10 to this drier environment.
00:10:08.13 Then ultimately,
00:10:10.00 once these differences have occurred
00:10:12.06 over, again, a very, very long period of time,
00:10:15.01 through evolution,
00:10:16.08 what would happen if the river dried up
00:10:18.16 and these animals
00:10:20.24 were able to come back together?
00:10:22.27 Well, they might come back together
00:10:25.07 and be able to interbreed,
00:10:27.10 but they may come back together
00:10:28.29 and not recognize each other
00:10:30.18 as the same species,
00:10:32.00 and therefore,
00:10:33.16 even though they're together
00:10:34.25 in this environment,
00:10:35.29 they would not interbreed
00:10:37.18 and their independent characteristics
00:10:39.04 would be carried on
00:10:40.25 from generation to generation
00:10:42.12 in those species.
00:10:47.14 So, that was an example
00:10:49.04 of geographic isolation,
00:10:51.04 and the biggest example of geographic isolation
00:10:53.22 happened about 200 million years ago,
00:10:56.18 when Pangaea,
00:10:58.06 which was this big super continental landmass,
00:11:00.25 broke apart to give us
00:11:03.16 the different continents that we know today.
00:11:05.28 So, South America and Africa
00:11:09.16 broke apart from North America and Europe,
00:11:13.08 and those continents
00:11:15.03 moved and separated around the globe.
00:11:17.22 With that separation,
00:11:20.00 the species that were together
00:11:22.08 prior to this breakup
00:11:23.25 then became separated,
00:11:25.16 and so if we look at species
00:11:27.10 that are in Africa versus South America,
00:11:29.20 for example,
00:11:30.28 we can see animals that
00:11:32.27 perhaps came from the same lineage,
00:11:34.14 but now are very, very different,
00:11:37.06 and are in fact different species.
00:11:43.20 Okay, so we've talked about this
00:11:46.04 process of evolution
00:11:47.16 and how it can occur.
00:11:49.28 What if we want to understand
00:11:51.16 the evolutionary history
00:11:53.11 of the animals that are
00:11:55.22 alive on earth today?
00:11:58.09 Well, we have to use a different set of techniques
00:12:00.28 to do that.
00:12:02.14 Here's just some of vertebrate diversity
00:12:04.16 and, as I said at the beginning of the lecture,
00:12:07.11 we also have lots of plants
00:12:09.16 and invertebrates and insects.
00:12:11.10 So I'm just showing you a very small part
00:12:12.14 of biodiversity here.
00:12:14.14 How do we figure out,
00:12:16.06 with animals so diverse as these,
00:12:18.17 how they're related to one another?
00:12:20.16 And how they evolved through time?
00:12:23.10 Well, we can take
00:12:25.04 a very simple example
00:12:27.03 of how we construct our own family trees
00:12:29.24 over very short time periods,
00:12:31.23 over several generations, say.
00:12:33.21 We research our genealogy,
00:12:35.11 we use birth notices and death notices,
00:12:38.27 and we recalled history
00:12:40.27 from our parents or grandparents,
00:12:42.29 and we can use that
00:12:45.01 to construct relationships
00:12:46.21 among our relatives and ourselves.
00:12:49.13 This is a really interesting family tree
00:12:51.25 that's on the wall of a Czech castle, actually,
00:12:55.01 and shows the relatedness
00:12:56.19 of this family,
00:12:58.04 going from a founder
00:12:59.17 down at the base of the tree, in the trunk,
00:13:01.20 up to the descendants at the top of the tree.
00:13:05.24 So, if we take a hypothetical example,
00:13:07.25 again,
00:13:09.01 of building a family tree,
00:13:11.05 and we start with
00:13:13.06 this family of green-ish and blue-ish,
00:13:15.13 big-eared and small-eared organisms,
00:13:18.04 and try to construct how they're related,
00:13:20.21 we can just look and see how family trees
00:13:23.05 are organized.
00:13:26.01 So, here I've taken that population
00:13:27.29 and put them onto their tree
00:13:29.25 -- that I made up --
00:13:32.01 and we can see that they're related to one another.
00:13:36.10 So, the individuals
00:13:39.12 that are connected at the first branch
00:13:41.21 are siblings.
00:13:43.11 They have the same parents.
00:13:45.21 If we move back in the tree,
00:13:48.01 we're looking at the different common ancestors
00:13:51.23 of these individuals.
00:13:54.17 So, if we go back,
00:13:56.21 these groups that are bracketed
00:13:58.23 in the orange boxes
00:14:00.14 are shared pairs of grandparents,
00:14:03.20 so they'd be cousins.
00:14:06.19 And if we look down near the base,
00:14:08.28 we can see that all of these organisms
00:14:11.07 share a pair of grandparents.
00:14:13.28 Now, because we're in recent history
00:14:16.25 and we have all sorts of ways
00:14:18.13 to record our history,
00:14:19.25 we may even know what these grandparents look like,
00:14:22.19 what our common ancestors of us,
00:14:24.15 and our sibling, and cousins, look like,
00:14:28.04 and I've reconstructed them this way.
00:14:30.01 If we look at at a group of animals
00:14:31.27 that's as broad as fish and mammals
00:14:33.27 and amphibians and reptiles, though,
00:14:36.04 we don't have that record,
00:14:38.18 to know what those common ancestors are
00:14:41.17 or what they looked like.
00:14:43.03 We have to use other types of approaches,
00:14:44.29 called phylogenetic approaches,
00:14:46.16 to basically try
00:14:48.26 to reconstruct the common ancestor
00:14:51.06 and how those species are related.
00:14:53.22 So, if we take this set of vertebrates,
00:14:56.22 this small number of animals,
00:14:58.20 and try to put them on a tree,
00:15:00.21 this is what it would look like,
00:15:02.04 and this is based on lots of peoples' research
00:15:04.08 over many, many years,
00:15:06.06 and I'll run you through it quickly.
00:15:08.20 On the far left,
00:15:10.18 we have the base of the vertebrate tree,
00:15:13.12 and these are lampreys,
00:15:14.28 these are animals that don't even have, really,
00:15:17.16 jaws.
00:15:18.20 They have these suction discs
00:15:20.02 that rasp and grip onto other species.
00:15:22.26 As we move up the tree,
00:15:24.13 we get into things like sharks,
00:15:26.00 and skates, and rays,
00:15:27.16 that have jaws,
00:15:30.02 but they have a cartilaginous skeleton.
00:15:31.29 When we move up yet again,
00:15:33.14 we get to the bony organisms
00:15:35.03 that include the fishes,
00:15:36.18 shown with these anemone fish,
00:15:38.14 the third image from the left,
00:15:40.08 and then we get up into the tetrapods,
00:15:42.26 that include amphibians,
00:15:45.17 reptiles, birds, and mammals.
00:15:48.14 Now, how do we construct
00:15:50.10 this kind of tree when
00:15:52.14 we don't have these detailed records
00:15:53.29 that we have of families?
00:15:55.12 Well, we do it by looking at
00:15:57.23 what characteristics these organisms share
00:16:00.14 and what characteristics vary between them.
00:16:02.26 There are lots of different types of characteristics
00:16:04.15 that we can use.
00:16:08.04 So, one of the features that we look for
00:16:10.20 when we're looking at shared characteristics,
00:16:12.22 or similarities and differences among organisms,
00:16:15.20 are anatomical features,
00:16:17.22 things like the shape of bones
00:16:20.06 or where sutures
00:16:21.14 -- where bones connect to one another --
00:16:23.04 or where we see holes through our skull
00:16:25.03 or other parts of our anatomy.
00:16:27.12 Bone and other structures
00:16:29.09 from the body
00:16:30.26 provide really nice characters
00:16:32.11 that we can use to try to figure
00:16:34.03 the relatedness of organisms.
00:16:36.11 In addition to using anatomical features
00:16:39.10 to try to understand the evolutionary history
00:16:41.20 of organisms and their relatedness,
00:16:43.24 DNA is now also
00:16:46.14 providing a really powerful way
00:16:48.24 of generating characters
00:16:50.17 to try to understand
00:16:52.20 how organisms have evolved.
00:16:54.08 In particular, we can compare a single gene
00:16:56.24 among different organisms,
00:16:58.14 different animals and species,
00:17:00.17 and see how it varies and how it's similar,
00:17:03.05 and look for changes in that
00:17:07.17 organization of the gene itself
00:17:09.05 that might give us signals
00:17:11.07 about how close a species is
00:17:12.27 to another species
00:17:14.20 and the relationship among them
00:17:16.28 and to different species.
00:17:18.18 Now, another set of data
00:17:20.12 that's been useful in understanding evolutionary history,
00:17:22.28 of course, is fossils.
00:17:24.22 They're really important.
00:17:26.01 Now, fossils provide information
00:17:28.16 about when and how features arose.
00:17:30.26 They won't, though,
00:17:32.20 provide the common ancestor.
00:17:34.07 It would be very unlikely
00:17:35.21 to actually dig up a fossil
00:17:37.12 that gives you the exact common ancestor of a species
00:17:39.24 but, nevertheless,
00:17:41.20 what they can provide us,
00:17:42.28 how they can ground our understanding
00:17:45.29 of when an organism
00:17:47.24 or particular elements and characteristics
00:17:49.11 of an organism arose,
00:17:50.28 is incredibly important.
00:17:53.25 So, to summarize
00:17:56.23 our introduction to evolution
00:17:58.09 and some of the major points we've talked about...
00:18:00.11 first, evolution is change
00:18:02.13 in the heritable characteristics of organisms
00:18:05.00 from generation to generation,
00:18:06.17 descent with modification
00:18:08.21 as proposed by Darwin.
00:18:11.08 Variation in characteristics
00:18:13.09 allows some subsets of populations
00:18:15.18 to be selected for or against.
00:18:18.20 And selection can cause change
00:18:20.14 in the characteristics
00:18:22.11 that persist in a population,
00:18:23.26 and this can allow for populations to diverge.
00:18:28.27 Reconstructing how the diversity of organisms
00:18:31.19 evolved
00:18:33.09 involves making trees,
00:18:34.23 or these phylogenies that I talked about,
00:18:37.09 that show different organisms
00:18:39.12 are related to one another.
00:18:41.19 And phylogenies, though,
00:18:43.08 depend on identifying characteristics
00:18:45.29 that are shared between organisms
00:18:48.06 and that can suggest their common ancestry.
00:18:50.07 And, again, we can get those characteristics
00:18:52.22 from morphology, from genes,
00:18:54.24 from all sorts of different sources.
00:18:57.19 Thank you.

00:00:02.17 Hello, and welcome to iBioSeminars. My name is Dianne Newman, and I'm a professor in the Divisions of Biology
00:00:07.16 and Geology and Planetary Sciences at the California Institute of Technology,
00:00:11.26 and I am also an investigator at the Howard Hughes Medical Institute.
00:00:15.13 So I am going to be giving you a lecture in three parts today,
00:00:19.16 and this is part one, which will be a very general overview on microbial diversity and evolution.
00:00:25.09 In part two, I'll tell a specific story about a modern example of a microbial metabolism
00:00:30.29 that's quite interesting and very important in affecting the geochemistry of the environment with
00:00:36.04 regard to arsenic geochemistry.
00:00:38.06 And in part three, I'll talk about work we've been doing that is more directed
00:00:43.17 at understanding a metabolism that evolved in the past, namely oxygenic photosynthesis.
00:00:49.02 But let's start with an overview now
00:00:52.14 and consider four important points about
00:00:57.00 microorganisms and their history. And I am going to walk you through each of these four points.
00:01:02.14 So the microbial world is really quite remarkable
00:01:06.23 and my goal in this first overview is to leave you with an impression
00:01:10.22 of its diversity, its antiquity, and how abundant and ubiquitous
00:01:16.18 this world is. So let's begin with antiquity.
00:01:20.27 When we think about the evolution of life, oftentimes we think in terms of macroscopic
00:01:25.23 fossils such as the ones that you see here. And it is pretty clear when you look
00:01:30.01 at these rocks, that something living was present on Earth when they formed.
00:01:33.24 In this panel over here you see a fossil of some type of algae. It is not clear
00:01:39.26 exactly what type, but it is inferred to be an alga.
00:01:42.09 And this shape here is known as a trilobite.
00:01:45.06 And this section of rock that you are looking at is one of the most famous fossils on the plane.
00:01:50.12 It is called the Burgess Shale. It's found in Canada, and it dates to what we call the Cambrian explosion,
00:01:57.14 which occurred roughly half a billion years ago around
00:02:00.29 five hundred and sixty million years ago.
00:02:04.16 So we can certainly claim when we look at rocks of this age that life was present.
00:02:09.17 But if we want to think about the evolutionary history of life,
00:02:12.22 over a much larger time span of billions of years,
00:02:15.26 given that the Earth is 4.6 billion years old,
00:02:20.02 we need to step back in time and look at more ancient rocks.
00:02:22.12 And when we do this, the shapes suddenly change, and it becomes
00:02:26.03 not quite as evident that we are looking actually at fossilized versions of life,
00:02:30.09 and yet we are. So for instance, take this rock as an example.
00:02:34.07 Here you see these dome-like structures, and these are vestiges of a type of microbial community
00:02:41.29 forming in a shallow marine environment
00:02:44.16 that became lithified and left these domal structures,
00:02:48.07 and we call these structures stromatolites.
00:02:50.08 Now this particular rock that you are looking at
00:02:52.21 is about 3 billion years old and is from South Africa.
00:02:56.19 But these rocks can be found all over the world, and they occur
00:02:59.21 throughout Earth's history, going back as far as 3.4 billion years.
00:03:04.20 However, when we go even further back in time,
00:03:08.04 for example, back to 3.8 billion years,
00:03:10.17 you can see ore deposits that one might not intuit immediately had anything to do with
00:03:16.26 microorganisms, and yet they do. They indeed record a history of microbial activities that was quite profound,
00:03:24.24 so profound that it quite literally transformed the planet.
00:03:27.19 And this is one beautiful example. So what you are looking at here is actually a 2.4 billion year old quarry.
00:03:35.27 This is in Western Australia in the Hamersley formation, and this is known as a banded iron formation.
00:03:41.13 And they're extremely important today because they constitute the world's largest source of iron ore.
00:03:47.03 But they also record a remarkable history of the evolution of metabolism.
00:03:51.13 Now how can this be? How do these massive rock quarries tell us anything about microbial life?
00:03:57.14 Well, when you think about what they actually constitute
00:04:01.00 they are made up of iron minerals, as well as other minerals
00:04:04.21 cherts, which is a type of silicon oxide,
00:04:07.07 intermixed with these iron species, but for now let's just focus on the iron.
00:04:12.02 So how did this iron get into this big deposit that you see here?
00:04:15.12 Well, it began a long time ago in ancient seas, in the form of ferrous iron
00:04:20.23 that's called Fe2+.
00:04:22.17 And then some process, which I'll get to in just a minute, oxidized this ferrous iron to ferric iron,
00:04:29.00 and at that point it could react with constituents in the waters such as hydroxyl species,
00:04:34.26 to form iron minerals, such as this one: ferric oxyhydroxide, rust.
00:04:41.01 And over time this mineral transformed and changed
00:04:44.19 into different types of minerals, became compacted,
00:04:47.17 and mingled with others and wound up in these rocks that we today know as banded iron formations.
00:04:54.14 But this initial step here is the critical one in terms of giving us some insight into microbial
00:05:00.23 activities on the ancient Earth. And let's think about two scenarios where microorganisms
00:05:06.05 might have been involved. The first scenario
00:05:09.03 is one where a very primitive type of photosynthetic organism,
00:05:12.27 well, I should say primitive in quotes, because actually this metabolism is remarkably sophisticated.
00:05:17.16 Nonetheless, this is primitive in the sense that it is a type of photosynthesis
00:05:21.18 that does not generate oxygen. Rather it is called anoxygenic, meaning that there is
00:05:29.09 an electron donor, in this case ferrous iron, that is oxidized to ferric iron
00:05:35.29 and that powers the reduction of inorganic carbon, CO2, to biomass.
00:05:42.18 And you can see this is a very dramatic metabolism
00:05:46.25 when it occurs because all you need is light, microorganisms, and ferrous iron,
00:05:52.21 and a few other things to help them get going, but those are really the three most important ones
00:05:57.22 in a bottle here, with, as I said, a few nutrients added so they can do their thing,
00:06:04.19 and when light is shined on this bottle,
00:06:08.24 these organisms very rapidly are able to oxidize the iron.
00:06:12.19 And they produce rust, and you can see the rusty color here in this bottle.
00:06:16.14 And this rust is exactly the type of iron that is the predecessor of the minerals that constitute
00:06:22.04 these banded iron formations. Now in the middle you see these organism growing on a different
00:06:27.03 electron donor, and I'll get to what I mean by an electron donor and an electron acceptor later in this lecture.
00:06:33.17 And in this case they are utilizing hydrogen as an electron donor, and the pink color you see
00:06:39.13 is due to photosynthetic pigments in their membranes
00:06:42.16 that enable them to harvest light and grow in this way.
00:06:45.07 So this scenario, as I said, is one that is catalyzed by
00:06:51.01 organisms that do not generate oxygen. They are anoxygenic phototrophs
00:06:55.14 capable of oxidizing iron in a photosynthetically mediated
00:06:58.29 process under environments where no oxygen is present whatsoever, and yet these ferric minerals can form.
00:07:07.22 Now scenario two, that is entirely different
00:07:11.02 is one where the organisms that ultimately catalyze the precipitation
00:07:15.11 of these minerals were producers of molecular oxygen, and these are the cyanobacteria
00:07:21.24 that you can see here that were critically important in the history of the evolution of metabolism
00:07:27.08 and quite frankly also in changing the overall chemistry of the Earth including its atmosphere
00:07:33.04 because they evolved the ability, the remarkable ability, to use water as an electron donor in photosynthesis,
00:07:40.05 oxidize it to molecular oxygen, and through this process, power the reduction of CO2 to biomass.
00:07:48.19 Now once they produce this oxygen, the oxygen chemically would have been able to react
00:07:55.09 with ferrous iron, oxidizing it to ferric iron,
00:07:58.25 and then this in turn would go down the pathway to precipitate these rusty minerals I showed you.
00:08:03.06 So here we have two options: one scenario where no oxygen is involved,
00:08:10.11 and a second scenario where oxygen is mandatory.
00:08:12.21 And both of these are biological processes.
00:08:15.22 So how do we distinguish between them if we are interested in understanding
00:08:20.19 the types of organisms that were present on Earth in the remote past?
00:08:23.29 Well this is quite a challenge, indeed, and there will be many years of investigations in the future
00:08:31.07 in order to really pin this down.
00:08:32.29 And it is a great field to get into if you are a beginning student
00:08:36.07 and interested in both biochemistry and evolution,
00:08:39.16 but what I'll say just for now is that we know from a variety of indicators
00:08:43.23 that somewhere between 2 billion and 3 billion years old
00:08:47.26 it is very probable, indeed it is almost certain,
00:08:52.05 that the process of oxygenic photosynthesis arose.
00:08:54.19 But when exactly this happened and how the evolutionary events came together
00:09:00.19 such that these anoxygenic phototrophs that can utilized reduced substrates
00:09:06.05 such as hydrogen, or sulfur species, or iron as electron donors in photosynthesis
00:09:12.13 morphed into a more sophisticated type of phototroph,
00:09:18.00 that was capable of using water as an electron donor,
00:09:20.25 the cyanobacteria, which in turn, are what became the plastids,
00:09:26.22 the chloroplasts that we find in modern marine algae
00:09:30.10 and also of course, in plants that are very well known for their ability to do oxygenic photosynthesis.
00:09:36.09 We do not know. We do not know when this happened.
00:09:39.14 And in my third lecture in this series, I will discuss ways that we can begin to approach this problem.
00:09:44.22 But it's a profound question, and what I would like to leave you with now
00:09:47.27 is just the simple message that these very ancient rocks, such as these banded iron formations,
00:09:52.16 here are holding clues to a mystery that we have to unravel.
00:09:56.22 And it is through tools of modern biology that ultimately we hope to get there.
00:10:01.13 All right, now as I said the history of microbial life
00:10:06.19 extends very far back in time, as far as 3.8 billion years as we currently estimate,
00:10:12.22 but this might have been even earlier for all we know.
00:10:15.22 How do we decipher when particular microbial metabolisms evolved and what types they were?
00:10:22.04 Well, this indeed is extremely challenging.
00:10:24.09 And there are three primary ways that we can gain insight
00:10:28.04 into the microbiology of the past through using either
00:10:31.25 morphological, molecular, or genomic, which is of course a form of molecular biosignatures.
00:10:38.21 And these are very different in what they can tell us.
00:10:41.20 So the first two, morphological and molecular,
00:10:45.01 are important because they can be concretely linked to rocks, old rocks, that we can date.
00:10:51.02 And because of this when we see a particular form,
00:10:55.09 this is being held in the hand a sample of stromatolite.
00:10:58.29 This is at a very different scale here. You are looking at a thin section of a rock,
00:11:03.14 and that is true for these images below
00:11:05.28 where the scale is about 1 millimeter, in this image, and it is even smaller down here.
00:11:12.10 The structures that you observe have been interpreted as being vestiges of ancient life for various reasons.
00:11:19.13 But this interpretation is often ambiguous, and it is a challenge to be able to come up with unambiguous
00:11:25.06 biosignatures simply on the basis of their shape.
00:11:28.12 And so geobiologists, those interested in seeking to understand life in ancient times,
00:11:35.02 have turned recently to what we call molecular biosignatures that come in two forms:
00:11:39.27 either organic biosignatures, or some type of inorganic biosignature,
00:11:46.26 often expressed as a ratio of different isotopes in a sample.
00:11:51.04 Now this in turn is challenging as well,
00:11:54.25 but it may be the best way that we can gain more specific insight into
00:11:59.18 different types of metabolisms, by looking at actually the chemistry what is left in the rock
00:12:04.10 and being able to deduce through finer scale analyses whether or not
00:12:09.14 this chemistry was one that was uniquely imparted by a biological process.
00:12:13.13 Lastly we can think of genes as fossils, and the genomic record has been crucial
00:12:20.03 in establishing the diversity of life on the planet, as I'll get to in a little while in this lecture,
00:12:25.21 but it also helps us understand the relatedness of different enzymatic functions
00:12:30.22 and how they evolved from one another.
00:12:33.19 While this does not give us a concrete date when these metabolisms
00:12:37.14 evolved, it does provide us with an ability to look at
00:12:41.10 the relationship between different metabolisms, and come up with an order in which they likely were invented.
00:12:49.06 So that is all I am going to say right now on the antiquity of microbial life,
00:12:53.22 and if you are interested, tune in for lecture three in this series,
00:12:56.22 where I will spend some more detail talking about how we use a particular compound found in lipids
00:13:02.13 in modern cells as a potential indicator for oxygenic photosynthesis
00:13:06.19 and whether or not this is a valid thing to do.
00:13:10.01 The next point now I want to turn to is just how numerous microbes are.
00:13:14.22 So let's ask a very simple question. How many microbes are there on Earth?
00:13:18.11 And to bring this into a human reference point, let's begin with the number of the human population.
00:13:23.19 So I am from Los Angeles, which at the latest census,
00:13:27.27 was around 10 million people. And in the state of California, we are up to approximately 35 million,
00:13:34.11 and in the United States in general, nearly 300 million.
00:13:39.16 These are large numbers, but overall in the world we are up three orders of magnitude.
00:13:44.18 at 6 billion people. And that's a lot of folks.
00:13:47.27 However, this is nothing in comparison to the microbial population
00:13:51.18 as estimated by a wonderful paper that I am citing here at the bottom of the slide
00:13:55.22 called, "Prokaryotes, the Unseen Majority" that was published in PNAS in 1998.
00:14:01.29 These are very rough numbers, but give or take an order of magnitude
00:14:05.01 here or there, I think you are going to be impressed when you see the number that I am about to show you.
00:14:09.06 So the estimates for the microbial population are just enormous, 5 times 10 to the 30th cells.
00:14:15.08 And this indeed is such a large number that it is very difficult to wrap our minds around it.
00:14:20.21 So to try to make this a bit easier to do,
00:14:22.16 I did a very simple calculation, where I assumed that the length of a given micro-organism
00:14:27.01 was one micron and asked, "how many times would we need to go back and forth between the Earth
00:14:33.11 and the Sun if we lined up all of these organisms end to end in order to account for this number?"
00:14:38.29 And the answer, shockingly, is we would need to go back and forth 200 trillion times.
00:14:45.12 So hopefully that impresses you with just how many of these creatures there are on the planet.
00:14:49.28 Now where are they, if there are so many?
00:14:52.08 How come we don't think about this all the time?
00:14:54.27 Why aren't we overwhelmed?
00:14:56.04 Well, one reason is that oftentimes we are shockingly ignorant
00:14:59.19 about the fact that they are all around us, that we ourselves are walking micro-organisms.
00:15:04.04 So one of the first scientists to appreciate this profound fact
00:15:08.10 was the father of microscopy, Antony van Leeuwenhoek.
00:15:11.11 And this is a lovely image that he drew from his observations down his first microscope
00:15:18.01 in 1684, and you can see he drew some nice rods and cocci, and even pictures of probably motility
00:15:26.22 what is meant by these dotted lines from C to D.
00:15:30.29 And he reflected, as he was looking through the microscope about his own teeth, and this is I think a very funny quote.
00:15:37.28 He said, "Though my teeth are kept usually very clean,
00:15:40.24 nevertheless when I view them in a magnifying glass,
00:15:43.25 I find growing between them white matter as thick as a wetted flower.
00:15:47.09 The number of these animals in the scurf of a man's teeth,
00:15:50.05 are so many that I believe they exceed the number of men in a kingdom."
00:15:54.17 Well, this indeed is actually an underestimate.
00:15:58.28 Not only do they exceed the number of men and women in a kingdom,
00:16:02.13 they go far beyond that. So if we actually look at our own bodies...
00:16:06.13 just take a look at your wrist, at one square inch on the surface of your wrist.
00:16:10.23 Right there, we are estimated to have five to fifty thousand bacterial cells.
00:16:16.22 And it just increases in density as we move to other parts of the body, such as the groin and the underarms,
00:16:22.28 in our teeth, and really where it's mainly at in our bodies is in our colon.
00:16:29.06 And the overall total per person is seventy trillion.
00:16:33.25 That is quite a lot.
00:16:35.24 And one thing that I think is really important for you
00:16:38.18 to know about the microbial community within your own body,
00:16:42.16 is that there are ten times the number of microbial cells
00:16:47.04 in our system than there are human cells.
00:16:51.21 And not only that, when we look at the genetic potential of the DNA
00:16:56.09 within these organisms, the genetic potential of only those within our guts
00:17:02.15 is over one hundred times that of the human genome.
00:17:06.21 So you might begin to ask whether or not humans are not merely walking vats of microorganisms,
00:17:11.29 carriers serving their existence.
00:17:14.08 It is something to think about, and there's a great deal of research now emerging
00:17:18.20 that is beginning to illuminate just how crucial these organisms are
00:17:21.25 for human health, not only with regard to being able to help us digest our food,
00:17:27.07 but also interfacing and controlling our immune system,
00:17:30.09 in ways that are fascinating and profound.
00:17:32.29 Now despite the fact that this number, ten to the twelfth, seems really large, and indeed it is,
00:17:38.25 it's peanuts when we compare it to other domains where we find microorganisms.
00:17:44.09 So let's start with the least abundant, up in the air,
00:17:46.24 It is quite amazing to me that they've been detected as high as thirty four to forty six miles up
00:17:53.06 into the sky. But these concentrations are really small relative to other compartments.
00:18:00.00 As I told you, within the human body we have quite a few.
00:18:04.12 And when you add up all of the humans and domestic animals, and then termites,
00:18:08.08 which I'll get back to in just a bit,
00:18:09.20 the order of magnitude jumps up to about ten to the 23rd, to 24th
00:18:14.06 This is superceded by the quantities that you can find in soils,
00:18:20.06 in forests and grasslands, deserts, tundras, swamp environments.
00:18:24.10 These places are very fertile homes for microorganisms and there their activities can transform
00:18:29.23 the chemistry of their environment quite profoundly.
00:18:31.29 And this is of course also true in aquatic domains, where at similar orders of magnitude
00:18:38.08 we find microorganisms in both marine and freshwater environments.
00:18:42.01 But all of these numbers pale in comparison to the numbers that we find in the subsurface,
00:18:46.14 both in terrestrial and oceanic environments, where microorganisms
00:18:51.09 have been detected as deep as two miles.
00:18:54.22 Now, this really is a very interesting frontier area in microbiology
00:18:58.05 It is hard to go down into these depths, and yet nowadays, researchers are equipped with the tools
00:19:05.02 they need in order to access these remote communities.
00:19:07.26 And what remains to be learned is what exactly these organisms are doing in situ.
00:19:12.11 Are they active? And if so, what are their activities?
00:19:15.26 Are these activities affecting in a significant way
00:19:19.05 the physical and chemical properties of these environments?
00:19:22.07 We don't know, and we look forward in the coming decades to finding
00:19:25.04 the answers to these and other interesting questions.
00:19:27.19 So now let me just give you an example, a tour through various parts of the world
00:19:34.05 and other inhabitants of that world where we find these organisms.
00:19:39.17 Just to bring home to you how ubiquitous microbes are on the planet.
00:19:44.07 So to start with what might be a more familiar image, here what you are looking at is pond scum.
00:19:51.09 You are looking at a wonderful assemblage of phototrophs
00:19:54.27 and other microorganisms in this pond. And my favorites of course are these purple phototrophs.
00:20:00.03 These are the ones that I told you about earlier that are what we call the anoxygenic phototrophs
00:20:04.27 that are not utilizing water as a substrate in photosynthesis,
00:20:08.29 but are utilizing other more reduced compounds such as different types of sulfur species, hydrogen, or iron.
00:20:17.15 Now these organisms that we see in modern day ponds, as I told you at the beginning when I was illustrating
00:20:23.20 the antiquity of microbial life with the example of the banded iron formations,
00:20:27.25 are absolutely historically important for their metabolism,
00:20:33.19 and the diversity of their metabolism, and how it's changed the geochemistry of the Earth.
00:20:38.00 Not only has the evolution of photosynthesis contributed to evolving our atmosphere
00:20:43.20 to one that contains oxygen over the course of time,
00:20:46.14 but as I also showed you with the banded iron formations,
00:20:48.29 these types of organisms have likely shaped ore formation as well.
00:20:54.21 And many other important processes have been able to come about
00:21:00.21 thanks to these organisms doing what they do, and it should be noted
00:21:05.15 that this type of metabolic activity, photosynthesis, is one that today we are highly interested in
00:21:12.06 because of our need for coming up with alternative energy sources, and
00:21:16.25 certainly if chemists were able to mimic what these wonderful microbes in this pond do, we would
00:21:22.25 be able to not worry so much about our dependence on foreign oil
00:21:27.02 and our fossil fuel supplies being burnt, but that's a story for another day.
00:21:32.08 The point is, their metabolic diversity is old. We see it all around us, and the biochemistry is really quite fascinating.
00:21:39.18 Continuing on with the chemistry and the metabolism of these organisms
00:21:44.28 not only do they do important things when they are growing,
00:21:48.00 but they also do important things when they start hitting what we call stationary phase.
00:21:51.24 And this is a point in their development where they're not necessarily actively growing,
00:21:56.12 but they are at a higher density and they are just hanging out metabolically.
00:22:00.26 And when this occurs in their lifecycle,
00:22:04.09 sometimes metabolites and pigments begin to be excreted.
00:22:08.08 And these pigments, which are called secondary metabolites,
00:22:12.14 although that name itself may be a bit misleading, because they are only secondary in a temporal sense,
00:22:18.14 in that they are made after a phase of active growth,
00:22:21.21 but by no means are they secondary in terms of the physiology of the organisms that produce them.
00:22:27.00 None the less, these metabolites oftentimes are used today by pharmaceutical companies
00:22:32.14 as natural products that confer antibiotic activity.
00:22:35.13 And a terrific example of this are organisms in the Streptomycetes family that you see here
00:22:40.18 in this Petri dish that are producing a whole host of wonderful antibiotic compounds.
00:22:45.02 Now containing in the environment of the soil of course are roots of plants.
00:22:51.00 And in this part of soil known as the rhizosphere,
00:22:55.04 we can find microorganisms as well that are colonizing in a very beneficial way the plant roots.
00:23:00.28 And here is a tomato root seedling. This is an image taken by Guido Bloemberg.
00:23:06.25 And he showed in experiments in the laboratory that when he took tomato root seedlings
00:23:12.27 and mixed them with an organism called Pseudomonas,
00:23:16.01 that this bacterium was able to colonize the plant and form what we call biofilms on the surface of the root.
00:23:22.18 And this is just one example of organisms that interact with plants.
00:23:26.20 There are many that fall into this category with different names.
00:23:30.12 And the bottom line is that they have a very beneficial relationship with these plants,
00:23:34.11 where sometimes they produce natural products that fend the plant off from fungal predators
00:23:40.05 and so they serve as biocontrol agents.
00:23:42.24 Other times these organisms are capable of fixing molecular nitrogen
00:23:48.14 into a usable form and essentially acting as a natural fertilizer.
00:23:53.14 Now crawling around in not only soil environments,
00:23:58.00 but of course we are very familiar with these from our homes, are termites.
00:24:01.00 And the termites are a terrific source of microbial diversity
00:24:05.17 and one that is becoming an increasingly important micro-environment
00:24:10.07 in which to look because of our desire to understand microbial processes
00:24:16.00 that might be harnessed for lignocellulose degradation.
00:24:19.04 Again, out of a need to develop alternative sources of energy.
00:24:22.22 Now a colleague of mine, Professor Jared Leadbetter at Caltech
00:24:26.14 studies these termites, and he likes to call them "an ecosystem in a microliter".
00:24:31.05 And I think this is really a fantastic description of them because it is within their hindgut that you find a zoo
00:24:38.21 of microorganisms and protozoa that are swimming around
00:24:43.12 doing all sorts of important activities that make it possible for the termites
00:24:47.12 to digest their wood. And in the process they emit methane,
00:24:52.02 and not an insignificant fraction of this methane ultimately makes its way
00:24:55.16 up into the atmosphere and contributes to the overall chemistry on the planet.
00:25:02.17 So speaking of methanogens, here you see
00:25:05.08 a dramatic illustration of them at work.
00:25:07.18 This image that I am standing in front of is taken from Cedar Swamp in Woods Hole, Massachusetts.
00:25:12.15 And it is an image from a group of students from the microbial diversity class,
00:25:18.02 which is a fantastic course for about twenty students, half from the United States and half from overseas,
00:25:24.07 who come together every summer to understand how
00:25:27.00 microorganisms are able to perform these various metabolic activities
00:25:32.08 that I have been describing in these lectures.
00:25:34.26 And what you can see here is that the students have gone waist deep into this swamp
00:25:39.19 and they have stomped around, and as they have done this they have collected the bubbles that come up
00:25:46.03 as they stomp the sediment, and collected them in these inverted funnels.
00:25:51.11 And then some brave individual holds that funnel
00:25:54.14 and removes their hand just at the moment when a friend comes by with a flame,
00:25:59.09 and ignites it, and here you see a lovely illustration of methane at work.
00:26:04.25 So methanogenesis led to the creation of the methane gas that was ignited here.
00:26:10.06 Now in the past the activity of these organisms that generate this methane
00:26:15.23 that are called methanogens, might have been important in shaping the chemistry of the Earth's environment.
00:26:19.27 And the reason we suspect this may be the case is because early in Earth's history the environment
00:26:25.00 contained appreciably more methane than it does today.
00:26:28.18 Now a different example of a habitat where microorganisms are very important
00:26:33.21 is in Chile and in other places on Earth,
00:26:37.19 but this example here is taken from the Andina Copper mine in the Andes in Chile
00:26:44.23 where microorganisms are exploited for their abilities to help
00:26:48.27 with bioleaching. And so what happens is that in these mines there are piles
00:26:54.06 that are built up, and they are fertilized essentially with indigenous microbial populations
00:27:01.08 that are able to live in shockingly low pH levels,
00:27:05.17 down to pH as low as one, and sometimes even lower.
00:27:08.23 And these organisms are essentially eating the minerals in this mine pile
00:27:14.14 and the process of metabolizing it, changing the mineralogy, in such a way
00:27:19.06 that copper is solubilized and leached. So here is another example of an environment
00:27:25.27 that is quite extraordinary and yet microorganisms have been able to adapt and even to thrive in this extreme condition.
00:27:33.04 So on our tour of extreme pHs, we just saw an example of low pH, so let's go to a high pH environment.
00:27:39.24 This one I am showing you is Mono Lake that is in Northern California.
00:27:44.09 And Mono Lake is quite an extraordinary place. It looks almost like it is from another planet.
00:27:49.25 You see these beautiful tufa towers that are calcium carbonate minerals forming,
00:27:55.05 and it is because the pH is so high and the alkalinity is so high that they naturally precipitate from these waters.
00:28:01.19 In addition to having these carbonate minerals, contained within this lake environment
00:28:07.09 is a ton of arsenic, and I will get to this in part two of my lecture today.
00:28:11.07 And what I want to point out right now is that in this very high pH environment, and also one
00:28:17.14 that's replete with arsenic, nevertheless we find organisms called alkaliphiles
00:28:21.23 that thrive here, that are able to make a living utilizing arsenic as a terminal electron receptor in respiration.
00:28:30.05 This is the subject of my second lecture. And in so doing account for 14% of the carbon turnover in this system.
00:28:38.23 Now let's go on to another example of an extreme environment.
00:28:42.14 Here now we are looking at an extreme of salt.
00:28:45.26 And there is no better example of this than the Dead Sea in Israel, but
00:28:50.06 you can find organisms such as those that inhabit the Dead Sea also in the Great Salt Lake,
00:28:56.04 and other places on Earth such as salt flats, where you have very high salt content.
00:29:04.19 And the organisms living here are capable of growing despite this high salt
00:29:08.21 and have adapted particular molecular strategies to cope with it.
00:29:12.15 One very elegant example of this is their ability to use special photopigments called rhodopsin
00:29:18.23 and these are colored purple.
00:29:21.24 And these rhodopsins, they have in their membranes, and enable them to generate energy
00:29:27.11 under conditions where they need to use slightly different
00:29:30.02 strategies than organisms that are growing under
00:29:33.28 conditions that we would consider more normal.
00:29:36.27 Now, so approaching the end of our tour through microbial diversity and ubiquity, I want to end with a few other extremes
00:29:44.00 now that are based on temperature and pressure.
00:29:46.04 If we think about the extremes of cold there is no better place to go than Antarctica.
00:29:50.27 And you might be surprised to realize that even in this environment you have microorganisms thriving in the crust.
00:29:57.02 And these organisms are psychrophiles, and they're ability to grow is dependent upon dust
00:30:02.26 from winds carrying nutrients picked up from the continents surrounding Antarctica, South America, Australia, Africa,
00:30:14.24 that reach Antarctica, deposit their dust and fertilize these upper crusts of the ice
00:30:20.14 where we have intrepid pioneer organisms that are able to utilize these nutrients
00:30:26.03 and grow, even in these very cold regimes.
00:30:28.02 So another extreme is that of temperature and pressure, and there is no better environment in which to observe this
00:30:34.24 than at the bottom of the ocean, in environments where we have hydrothermal vents
00:30:39.21 that are releasing nutrients into the deep. And here is an example of one of these vents. It is called a black smoker
00:30:46.17 because the nutrients that it releases, including manganese and iron,
00:30:51.14 often precipitate in the conditions of the oceans at these sites
00:30:57.16 such that they look black.
00:30:59.22 Now around these vents there is abundant life,
00:31:04.07 really extraordinary life, not just microbial life.
00:31:06.08 but giant tube worms, and fish, and other macroscopic organisms.
00:31:10.10 So the ability of all of this abundant life to be in this environment
00:31:15.10 crucially depends upon the activities of microorganisms that are chemosynthetic.
00:31:20.01 that are able to grow by the oxidation of sulfur and other compounds that you have
00:31:25.03 present in this environment, and couple that oxidation of these reduced substrates to
00:31:31.05 the fixation of CO2 into biomass.
00:31:34.15 And this is at the base of the food chain that then sustains the growth of other marine organisms.
00:31:40.12 such as these tube worms. And here you see an example of that
00:31:43.10 in these beautiful tubeworms. If you cut them open and you look at one of their organs,
00:31:50.29 called the trophosome within these organs are bacterial symbionts
00:31:55.27 that are doing the process that I just mentioned.
00:31:58.08 So my final example that I will end with
00:32:01.12 is one that might be the most familiar to you
00:32:04.02 if you have ever done any PCR in molecular biology.
00:32:06.25 So most of you have heard of the enzyme Taq polymerase,
00:32:10.06 and this polymerase is what allows us to do an amplification reaction when we are doing PCR.
00:32:18.21 Now this enzyme, Taq, derives from a bacterium called Thermus aquaticus,
00:32:24.28 that is where the Taq comes from. The "T" is from the Thermus and the "aq" from aquaticus.
00:32:31.05 And this is a thermophile that was isolated in Yellowstone
00:32:35.14 at a hot spring, many decades ago.
00:32:38.03 And it was presciently realized by Kary Mullis
00:32:41.18 and others that the enzymes contained within it could be useful for various biotechnological applications
00:32:47.26 because they wouldn't denature at the temperatures that would kill most other types of cells.
00:32:54.02 So these thermophiles are a very fascinating group of organisms
00:32:57.28 whose molecular adaptations include not only DNA polymerases,
00:33:03.26 but also a wide variety of other enzymes that might be of industrial use.
00:33:10.01 So let's now end with diversity, which is really my favorite part
00:33:14.14 of the microbial world. And I want to cover a few different areas of this.
00:33:18.18 The first is phylogenetic diversity.
00:33:20.03 Now one of the most important lessons to be learned in evolutionary theory
00:33:25.03 was learned several decades ago from work by Carl Woese and his colleagues,
00:33:30.03 including Norman Pace, who applied Carl Woese's fundamental
00:33:34.07 insights into the diversity of life to the natural world.
00:33:38.02 And these individuals together with others were able to demonstrate very clearly
00:33:44.05 that when we think about the diversity of life out there on the planet,
00:33:48.16 we are really talking about a microbial world, whether we call these
00:33:52.22 microorganisms Bacteria or Archaea or even Eucaryotes.
00:33:58.23 What I want you to appreciate is that when you look at the tree of life,
00:34:03.11 that's what this is. It is a tree that is drawn based upon comparing the sequences of a very particular molecule
00:34:11.06 that every living organism has, that is ribosomal RNA, that is necessary for the process of translating
00:34:19.07 messenger RNA into protein.
00:34:21.07 Because this is a very universal and highly conserved molecule
00:34:24.28 Carl Woese and colleagues were able to deduce that it was a beautiful molecular chronometer
00:34:31.01 that we can employ to look at the evolutionary relatedness between different organisms.
00:34:36.16 And when he and his colleagues did this , he recognized that
00:34:39.19 there were three primary domains of life, the Bacteria, the Archaea, and the Eucarya.
00:34:43.16 And moreover, what I want to stress now is that our entire universe of Homo sapiens
00:34:52.12 and humans and plants and animals, the macroscopic eucaryotic world,
00:34:57.12 is only occupying in terms of this space on the tree,
00:35:01.27 which is known as a phylogenetic tree, meaning a tree of evolutionary distances
00:35:06.21 between different types of life forms, a very tiny miniscule branch.
00:35:12.00 And everything else that I am showing here is microbial.
00:35:14.13 So hopefully that impresses you, but before we leave this tree let me point out two more
00:35:19.20 facts that are very important.
00:35:20.29 All of the metabolism on the planet was invented by microorganisms
00:35:26.05 including the metabolism that we perform in our bodies today in our mitochondria.
00:35:31.11 So the mitochondrion is nothing more than an ancient bacterial cell
00:35:36.28 that invented the ability to do oxidative phosphorylation, which I'll tell you about in a little bit,
00:35:42.24 that was engulfed or brought into symbiosis with some other type of cell,
00:35:47.23 and over the course of time involved into the organelle that we call the mitochondrion.
00:35:52.28 But it was a microorganism first, and that is where the beautiful metabolism that it goes through was generated.
00:36:02.14 The same story is true for the chloroplast. This is nothing more
00:36:06.03 than cyanobacteria that over time turned into plastids and became incorporated into other cells.
00:36:11.25 Now the next important point I want to make is that microbial diversity also manifests itself morphologically.
00:36:18.19 And this is something that only recently we are coming to appreciate in its full glory.
00:36:24.02 Back in the days of Leeuwenhoek, when he had a simple microscope, all he could really see were different shapes of microbes,
00:36:30.24 and to be quite honest, that is not terribly spectacular and includes rods and spirals and some cocci.
00:36:37.11 Once in a while you see higher structures forming of communities however,
00:36:41.25 and Leeuwenhouk didn't necessarily know about these,
00:36:44.05 but here is an example of one here. This is a beautiful example
00:36:48.13 of fruiting bodies beginning to form by the soil organism Myxobacteria
00:36:53.10 that does all sorts of interesting things when it comes together in a group
00:36:57.01 that it wouldn't do as any individual cell.
00:37:00.25 This is social behavior. So this is an example of bacteria acting in a multicellular fashion, if you will.
00:37:06.11 Microorganisms, however, can get remarkably large. They are not just on the scale of microns.
00:37:11.21 And here is a good example of this.
00:37:13.20 This is, to my knowledge, one of the largest microbial
00:37:16.28 cells known to date. It is called Thiomargarita namibiensis,
00:37:19.29 which means the sulfur pearl of Namibia.
00:37:22.17 And it is on the same scale as the eye of a fruit fly.
00:37:25.13 And when you look at it in more detail, the reason it is so big is that it contains this huge vacuole
00:37:31.21 filled inside with nitrate, which is one of the substrates it uses to power its metabolism.
00:37:38.02 And it couples the reduction of nitrate to a more reduced form of nitrogen
00:37:43.07 to the oxidation of sulfide, and in this way it powers energy for growth.
00:37:48.00 But let's leave the metabolism aside and stay focused now just on the form.
00:37:52.03 Here is an example of one of my favorite organisms, Rhodopseudonomas palustris,
00:37:57.02 and the reason I am showing you this is simply to illustrate
00:37:59.24 that it has quite an amazing membrane structure within it.
00:38:05.27 One that is reminiscent even of the Golgi in higher organisms.
00:38:09.09 And indeed it might have been the progenitor of that at the cell biological level.
00:38:14.17 And how these various structures form, these are what we call
00:38:18.06 the inner cytoplasmic membranes where the photosynthetic machinery is housed in this case,
00:38:22.19 in terms of the detail of what creates their shape is an open and exciting question
00:38:27.08 that future microbial cell biologists will no doubt solve.
00:38:30.17 But the final example, which is probably my all time favorite, is of an organism called a magnetotactic bacterium.
00:38:38.16 And here you see if you just look at it in a light microscope,
00:38:41.15 although this is actually an image of fluorescence where we have put some GFP into the bug,
00:38:46.04 it looks like just a common spiral.
00:38:48.09 If you take a fancier microscope, a transmission electron micrograph, and cut it
00:38:53.01 open and do a thin section, you can see that it has this beautiful chain of magnetic particles inside it.
00:39:00.00 And now what I am going to show you is, I think, the best advertisement for the beauty of bacterial cell biology
00:39:05.28 that I know, and it is a cryo-electron tomogram of one cell.
00:39:13.10 And this was work done by Arash Komeili who is now a professor at UC Berkeley
00:39:18.26 and his collaborator Zhuo Li in Grant Jensen's lab at Caltech. And together
00:39:23.17 we made this movie showing the internal structure of these organisms.
00:39:27.26 So what you are going to see now is coming up through the bacteria different sections,
00:39:32.11 and here you see the magnetosomes coming into view. Those are the membranes that contain the magnetite.
00:39:39.10 If you missed them, now look, OK.
00:39:41.02 Here they are in red, those magnetosome membranes, and then there is this yellow filament surrounding them.
00:39:46.27 And what we have come to appreciate is that this filament is a protein that is very similar to actin.
00:39:52.11 And it is necessary for these magnetosomes, for these organelle-like,
00:39:58.01 although they never separate from the membrane, so they are not true organelles.
00:40:01.14 Here you see they're attached by a neck that's only 5 nanometers in diameter, which is quite amazing, to this inner membrane.
00:40:10.24 They invaginate and form these vesicles within which a beautiful single domain crystal of magnetite can form.
00:40:19.19 And this order, the fact that they are linear in a chain,
00:40:22.21 is enabled by a cytoskeletal filament, an actin-like protein.
00:40:28.17 OK. So the next to the last point that I want to make on diversity
00:40:33.09 is behavioral diversity, and there is another lecture in this iBioSeminar series
00:40:37.06 by Professor Bonnie Bassler from Princeton that can give you more information about this if you are interested.
00:40:41.28 But what I wanted to point out here while we are going through a tour through diversity
00:40:46.13 is simply that microorganisms can act in ways that are quite extraordinary
00:40:51.15 when they are acting as a group.
00:40:53.11 And you can see that illustrated by the activities of the bacterium Vibrio fischeri within the light organ of a squid.
00:41:01.10 And here is an image that is from the beautiful pioneering work of Margaret Mefal-Ngai
00:41:06.18 and Ned Ruby at the University of Wisconsin, Madison where they have been studying for decades the interactions
00:41:12.01 between the microorganisms in the light organ of the squid and the squid,
00:41:16.28 and the ability of these organisms to colonize this environment,
00:41:20.06 and when the lights go out at night, emit a beautiful luminescence. Here you can see pictures of these organisms
00:41:28.12 that have just been streaked out on a plate in the dark.
00:41:30.11 They are glowing. Well, they glow as well here at night in the belly of the squid.
00:41:35.27 And it shields these squids from predators below
00:41:39.00 because the light of the moonlight coming down from the top
00:41:41.28 is roughly of the same luminescence as the light that they are emitting.
00:41:45.26 So it allows them to have a stealth function and glide around in the oceans
00:41:50.19 and be unseen to predators deeper below them.
00:41:56.07 Now, this isn't just a phenomenon that affects the squid. This is a phenomenon that can get quite enormous in its scope.
00:42:03.19 And the best example to illustrate this is this satellite image here taken off of the Somalian coast,
00:42:09.11 where you see an image that quite literally is of milky seas as described by the ancient mariners,
00:42:17.21 but what today we understand as glowing bacteria.
00:42:21.26 In this case an organism, likely called Vibrio harveyi, associating with micro-algae in this environment
00:42:28.22 that for whatever reasons that are not fully understood at this particular point in time
00:42:33.22 when this satellite image was taken, had a bloom and began luminescing like crazy, and filled up a volume the size of Connecticut.
00:42:41.27 All right, so, to end I want to just mention a few rules of microbial diversity
00:42:47.23 because almost everything that I have talked about so far
00:42:51.11 in this lecture ultimately comes back to the ability of organisms to generate energy in ways that are quite amazing.
00:42:59.06 And I would stipulate that microbes are by far the best chemists on the planet.
00:43:02.25 And so if you are a chemist, pay attention, because a lot of lessons can be learned from these guys.
00:43:07.06 All right. Now when we are talking about the phase of active growth,
00:43:11.13 the bottom-line that microbes are facing is they simply want to divide.
00:43:15.12 And to do this they need two things. They need energy, and they need carbon.
00:43:20.08 And beyond that, they are virtually unconstrained, although there are a few constraints,
00:43:26.25 and we will come back to that in a moment.
00:43:29.03 They need substrates, and these substrates can be organic or inorganic compounds.
00:43:36.11 This is now for the part where they are going to be generating energy.
00:43:40.22 Those substrates are converted to products through catabolic reactions, or energy generation, if you will.
00:43:49.09 And often times we think of energy generation in the form of ATP,
00:43:52.20 the most important energy carrying molecule within the cell.
00:43:57.06 Now this part of metabolism, catabolism, is coupled to anabolism,
00:44:03.12 which is the part of metabolism that is concerned with energy consumption, or biosynthesis.
00:44:08.12 And now down here what we are talking about is the conversion of
00:44:12.01 carbon, often in the monomeric form, to biomolecules that are far more complex, so protein, DNA, lipid, for example.
00:44:22.27 Now if we are thinking just about the substrates, as I said they can come from a variety of sources.
00:44:30.06 Always they're chemical, although light can help enable cells
00:44:34.21 to actually utilize those chemicals in ways that they otherwise wouldn't be able to do.
00:44:39.10 But when we are talking about the growth of organisms just purely on chemicals, without needing
00:44:46.15 a boost from light, the name we give to this metabolism is chemotrophy.
00:44:50.18 And that in turn is classified into two different types, inorganic and organic.
00:44:57.06 And when we are talking about inorganic sources of energy like hydrogen, and sulfide, and iron minerals,
00:45:03.18 this is called chemolithotrophy. And when we are talking about growing on organic substrates like glucose, or glycerol, or acetate,
00:45:11.23 this is called chemoorganotrophy.
00:45:14.04 And of course, as I said, while chemistry is always at the basis for any type of metabolism,
00:45:20.20 there is a photochemical boost that is often necessary,
00:45:25.09 when activating a compound that otherwise might not be biologically utilizable
00:45:30.16 for energy, and that is when we call that process a phototrophic one.
00:45:36.10 So the final part of this that I want to just mention is that the carbon source,
00:45:42.02 which is distinct or can be distinct from the energy source...
00:45:44.28 sometimes they are the same thing, but they don't have to be the same thing...
00:45:47.26 is either coming from inorganic carbon, CO2, or organic carbon.
00:45:52.19 And when it is coming from inorganic carbon that is called autotrophy,
00:45:55.21 and when it is coming from organic carbon, that is called heterotrophy.
00:45:58.22 So we are heterotrophs, we need to eat some type of organic carbon whether we are vegetarians
00:46:04.28 or meat eaters, but microorganisms are far more sophisticated.
00:46:09.12 They can eat minerals. They can just take CO2 from the air, and they'll be on their way.
00:46:17.14 So finally the last part I want to mention about metabolic diversity writ quite large
00:46:22.29 is that you can generate ATP through one of two different ways.
00:46:26.13 The first way is through what is called substrate level phosphorylation.
00:46:29.15 And this is also termed fermentation, and essentially is the process
00:46:33.22 where different types of reactions between chemicals within a cell
00:46:39.26 enable transfer of an inorganic phosphate ultimately to ADP to produce ATP.
00:46:49.21 And this process is enabled by chemical rearrangements within the cell
00:46:55.05 and reactions one on one between compounds.
00:46:57.18 The next major way that ATP can be formed in a cell is through the remarkable process of oxidative phosphorylation.
00:47:03.10 Basically this is about electron transport chains in membranes
00:47:07.23 that are coupled to generating a battery around a membrane
00:47:11.08 by extruding protons to one side and polarizing it so that there is an electrochemical potential gradient
00:47:18.00 across this membrane that can be harnessed to do the work of making ATP.
00:47:22.06 Now something that I am not showing you on this diagram,
00:47:25.03 but I want to introduce as terms are an electron donor and an electron acceptor.
00:47:31.00 So in metabolism there is always a substrate that is used as the primary electron donor
00:47:36.14 that can be metabolized through various pathways
00:47:39.08 and reduced to a compound that can donate electrons
00:47:43.17 to the electron transport chain in the membrane.
00:47:45.20 And then there is always something that serves as the acceptor of those electrons at the end of the chain,
00:47:52.10 and that is called the terminal electron acceptor.
00:47:54.28 And it is the path of electron transfer and proton translocation
00:47:58.22 between this electron donor and this terminal electron acceptor that is really harnessed by the membrane to do work.
00:48:05.05 And so that is what you see here pictured very generically without a whole lot of detail
00:48:10.08 in the sense that through this electron transport process,
00:48:13.20 which imagine if you will, is coupled as I said to proton translocation,
00:48:18.00 and that is achieved by different things within this membrane.
00:48:22.15 They can be proteins, or small molecules that are able to simultaneously
00:48:26.25 pass electrons through the membrane to something else
00:48:29.24 in the electron transport chain and push protons, or translocate protons
00:48:34.15 across the membrane so that there is this gradient that arises where there is more positive charge on the outside
00:48:42.07 than on the inside. Now once this happens this gradient can be used to drive ATP synthesis.
00:48:49.21 And this happens through a really amazing molecular machine called the ATP synthase,
00:48:54.09 which allows the traversal through the membrane of a proton,
00:48:58.27 that concomitantly gives the energy to phosphorylate ADP, adding that inorganic phosphate on, and making ATP.
00:49:09.08 And as this happens, the electrochemical potential gradient lessens.
00:49:15.00 And so that is what I am showing here: the energized membrane
00:49:16.25 due to proton transport coupled to electron transfer through the membrane,
00:49:22.10 and then this being expended and used in order to drive ATP synthesis.
00:49:26.12 Now while you can imagine a whole variety of things that can be electron donors
00:49:32.02 and electron acceptors from microbial metabolism,
00:49:34.27 metabolic diversity does have to conform to some rules.
00:49:37.06 And there are three that I want to point out that I think are particularly important.
00:49:41.02 The first is that the amount of energy has to be at a very minimal level,
00:49:47.14 at least in order to sustain the cell, both with regard to active growth, where you need a high level of energy,
00:49:53.27 at some threshold amount in order to double, but also at the level where you are generating enough energy simply to maintain
00:50:01.18 basic cellular processes even if they are not coupled directly to growth.
00:50:05.11 Now what is this number and how do we constrain it?
00:50:09.13 Thermodynamically, this can be expressed in this very straight forward equation here,
00:50:14.20 which is saying that the standard free energy that can be gained
00:50:18.04 from a process where there is electron transfer between the electron donor and the electron acceptor
00:50:23.13 is a function of the number of electrons transferred,
00:50:26.22 multiplied by the Faraday constant, and this in turn multiplied by
00:50:32.21 the difference in redox potential between the electron donor and the electron acceptor.
00:50:37.21 So for example, a common intracellular reductant, is NADH,
00:50:43.09 and in its oxidized state this is NAD+.
00:50:45.10 The redox potential of this redox pair is very low.
00:50:51.07 It is very negative on the electron potential scale that is typically expressed in millivolts.
00:50:57.07 On the other side of this scale are the electron acceptors with very high redox potentials, like oxygen.
00:51:04.20 And so when you couple through the membrane
00:51:09.27 a process of electron transfer from NADH to oxygen, thermodynamically you have the potential to generate
00:51:16.16 a lot of energy, and this is captured through a beautiful sequence of proton carriers and electron
00:51:24.14 transfer biomolecules contained within these membranes.
00:51:28.28 But these electron transport chains need not be between NADH and oxygen,
00:51:33.26 you can have a whole assemblage of things that can interrelate and so the minimum amount of energy
00:51:39.13 that needs to be supplied has been calculated. And this is a very crude estimation,
00:51:45.03 but it is an interesting study, and I refer you to below where you can see the reference.
00:51:49.05 Where for organisms operating in very low energy regime,
00:51:55.03 it was inferred that the minimum free energy required to sustain them and their growth
00:52:00.29 was about -4 kilojoules per mole, and that is about as low as you can go at least as experimentally measured.
00:52:06.21 Finally, regardless of the thermodynamic potential there are two other very important factors to keep in mind.
00:52:14.02 The second point is that the substrates themselves must be bioavailable. And so this is more of a kinetic problem
00:52:21.07 where we need to consider accessibility and transport of substrates
00:52:25.17 across the membrane to the site in the cell where they are used.
00:52:28.21 Or the ability of the cell to figure out a way to access them even if they can't transport them inside.
00:52:34.05 And the final point is that these substrates or the products after the metabolism has done its thing
00:52:42.00 must not themselves be toxic. So in the next couple of sections of this lecture,
00:52:47.26 I am going to give you examples of different microbial metabolisms to illustrate
00:52:52.12 these general points I have been making,
00:52:55.02 but I hope what you will remember from this seminar is the four big points about microbial diversity.
00:53:01.03 One, that it is incredibly ancient and over this long period of Earth history
00:53:06.08 numerous microorganisms in ubiquitous environments
00:53:09.18 have evolved diverse metabolisms that allow them
00:53:13.00 to catalyze fascinating chemical reactions and that these reactions
00:53:16.23 have affected not only the ability of the cells to grow and divide,
00:53:20.07 but in many instances have profoundly affected their environment,
00:53:24.09 be that environment one in an ancient ocean,
00:53:27.05 or today inside the human body.
00:53:30.18 Thank you.

00:00:07.17 For the last part of my lecture series,
00:00:10.11 I wanna talk about examples of natural selections in humans,
00:00:14.29 and the two particular examples
00:00:17.01 that I'm going to be talking about
00:00:19.00 are the evolution or lactose tolerance in east Africa,
00:00:22.10 and of pygmy short stature.
00:00:25.04 So if we're going to be talking about natural selection,
00:00:27.11 we have to first of course
00:00:28.29 acknowledge Charles Darwin,
00:00:31.12 who came up with the theory of natural selection.
00:00:36.10 In fact, to quote from Darwin, he said,
00:00:39.13 "This preservation of favourable variations
00:00:42.03 and the rejection of injurious variations,
00:00:44.21 I call Natural Selection.
00:00:47.06 Variations neither useful nor injurious
00:00:49.27 would not be affected by natural selection,
00:00:52.18 and would be left a fluctuating element,
00:00:55.01 as perhaps we see in the species called polymorphic."
00:00:58.10 And that was from his classic book
00:01:00.06 On The Origin of Species,
00:01:01.24 published in 1859,
00:01:03.25 and you might recognize from our first lecture,
00:01:07.03 that this is really talking about genetic drift,
00:01:09.27 random fluctuations.
00:01:13.13 However, part of the evolutionary change that we see
00:01:18.12 is not just going to be due to random genetic drift,
00:01:21.03 it's also going to be due to natural selection.
00:01:24.18 And so, according to that theory,
00:01:27.10 natural variation exists and is heritable,
00:01:30.02 more organisms are born than can survive,
00:01:32.11 and therefore organisms best suited to the environment
00:01:35.07 survive more often,
00:01:36.25 and slight differences can accumulate in a species over time.
00:01:40.24 So this is the idea of gradual evolution of a species
00:01:43.27 by natural selection.
00:01:45.18 And this is Huxley,
00:01:47.03 who was also known as Darwin's bulldog
00:01:50.11 because he was the big proponent of his theory,
00:01:52.17 and he said,
00:01:54.05 "How extremely stupid not to have thought of that!"
00:01:57.12 So when Darwin first came up with his theory of natural selection,
00:02:01.08 there was really no concept of genetics
00:02:04.12 as we know it today.
00:02:06.02 In fact, it wasn't until the late 1800s
00:02:08.12 that Mendel proposed his theory of genetics.
00:02:13.02 So in the 1930s and 1940s
00:02:15.22 there was sort of a synthesis of natural selection
00:02:19.09 and genetics and mathematics,
00:02:22.16 population genetics,
00:02:23.25 and at that time it was proposed that genetic variation in populations
00:02:27.05 arises by chance through mutation and recombination,
00:02:31.15 that evolution consists primarily of changes in the
00:02:34.12 frequencies of alleles between one generation and another,
00:02:37.25 largely as a result of genetic drift,
00:02:40.24 gene flow,
00:02:42.05 and natural selection.
00:02:43.27 And that speciation occurs gradually when populations
00:02:46.00 are reproductively isolated, for example,
00:02:48.20 by geographic barriers.
00:02:52.14 And so if we look at this timeline,
00:02:54.12 starting with the Origin of Species,
00:02:56.21 and then Mendelian inheritance
00:02:59.04 is actually rediscovered in 1900,
00:03:01.19 it was first proposed in the late 1880s,
00:03:04.01 but very few people knew about it at that time.
00:03:06.27 And then in the early 1900s
00:03:09.09 we have the theoretical foundations of population genetics
00:03:12.21 and then, as I mentioned,
00:03:14.09 the modern synthesis in the 30s.
00:03:16.19 And then in the 70s we have Kimura's theory of neutral evolution,
00:03:21.19 which was proposing that most changes and speciation events
00:03:25.07 are simply due to random genetic drift
00:03:27.22 and to new mutation events.
00:03:29.20 And I think that today we would say
00:03:31.14 it's a combination of all of the above.
00:03:33.19 There's certainly a lot of genetic drift that occurs,
00:03:36.02 but we know that natural selection
00:03:37.29 is having a very important influence
00:03:40.26 on the variation that we see
00:03:43.05 in terms of phenotypic variation and even disease susceptibility.
00:03:48.04 So let's look what happens
00:03:49.08 when a neutral mutation occurs in a population,
00:03:52.07 as indicated by this individual in green.
00:03:55.25 Let's look what happens as we proceed forward in generations,
00:03:59.08 and you can see there's not too many changes
00:04:01.21 in allele frequency.
00:04:03.29 But what happens when we have a beneficial mutation,
00:04:09.05 which means that it increases the fitness of the individual,
00:04:12.20 meaning that they're more likely to produce children,
00:04:16.12 and their children are more likely to produce more children,
00:04:19.00 and so on and so forth.
00:04:21.15 And so we can see that each generation,
00:04:24.04 this beneficial mutation is going to spread,
00:04:27.22 until eventually it may be nearly fixed
00:04:32.06 in the population.
00:04:34.17 So I want to tell you about some of our studies
00:04:37.20 focused in African populations
00:04:39.14 in which we're trying to identify
00:04:41.02 genetic signatures of natural selection,
00:04:43.19 and regions of the genome that are targets of natural selection.
00:04:47.29 And this is important
00:04:49.22 because it's thought that mutations associated with diseases
00:04:52.16 in modern populations,
00:04:54.13 like hypertension
00:04:56.03 , diabetes,
00:04:57.08 obesity,
00:04:58.10 and asthma,
00:04:59.08 may have been selectively advantageous or adaptive
00:05:01.23 in past hunter-gatherer environments.
00:05:04.04 So if we can identify these regions
00:05:06.25 that are targets of selection, or actual variable sites
00:05:09.18 that are targets of selection,
00:05:11.16 those may be functionally important
00:05:13.14 and may give us a clue about disease risk.
00:05:16.11 So here I'm showing you a few of the populations
00:05:18.12 that we've studied in Africa,
00:05:20.23 and we have people who are living at very different climates,
00:05:23.15 high altitude, low altitude,
00:05:26.03 savannah, and tropical environments, for example.
00:05:30.10 We have people who have very different diets,
00:05:32.22 so agriculturalists,
00:05:34.08 hunter-gatherers,
00:05:35.23 or pastoralists.
00:05:37.14 And they have very different infectious disease exposures,
00:05:40.05 so they've likely undergone local adaptation
00:05:42.13 to different environments.
00:05:45.25 And I'm going to, as I mentioned,
00:05:47.16 tell you about two examples today.
00:05:49.15 The first one is the evolution of lactose tolerance
00:05:51.29 in east African pastoralist populations.
00:05:57.07 So, the ability to digest the sugar lactose,
00:06:00.21 which is quite common in milk,
00:06:03.07 is due to an enzyme called lactase-phlorizine hydrolase,
00:06:07.15 or known as lactase for short.
00:06:09.28 And lactase is expressed specifically
00:06:13.01 in the brush border cells of the small intestine,
00:06:16.25 and in individuals who maintain high levels of this enzyme
00:06:20.29 as adults,
00:06:22.23 they're able to break down the complex sugar lactose
00:06:26.16 into glucose and galactose,
00:06:29.14 which is rapidly taken up into the bloodstream.
00:06:32.23 However,
00:06:35.19 most mammals, and most humans,
00:06:38.19 shut down lactase activity
00:06:40.23 shortly after weaning.
00:06:42.28 So, as adults, they do not have an active form of this enzyme.
00:06:46.24 And what's going to happen is
00:06:48.19 they're not going to be able to break down that complex sugar.
00:06:51.26 It's going to go down into the lower gut,
00:06:54.13 it's going to be attacked by bacteria,
00:06:56.25 and you're going to have severe intestinal distress.
00:07:01.00 Now, it has been noted for many years by anthropologists
00:07:04.27 that there is a very strong correlation
00:07:06.27 between the lactose tolerance trait,
00:07:09.19 or you could think of it also as the lactase persistence trait,
00:07:13.26 because there's persistence of the enzyme activity as adults.
00:07:18.15 And they've seen a strong correlation
00:07:20.20 between the prevalence of that trait
00:07:23.14 with populations who traditionally practice cattle domestication
00:07:28.04 and dairying.
00:07:30.05 So for example, this trait is most common in northern Europe,
00:07:33.19 it decreases in frequency as one moves
00:07:36.23 into southern Europe
00:07:38.29 and into the Middle East.
00:07:40.24 It's very uncommon in eastern Asia
00:07:43.26 and in the Americas,
00:07:46.13 and it's uncommon in western Africa,
00:07:48.26 which is one of the reasons that we see high levels
00:07:51.17 of lactose intolerance in African Americans, for example.
00:07:55.24 But in regions of Africa where there's a high prevalence
00:07:59.04 of cattle domestication, pastoralism, and dairying,
00:08:03.14 we see a high prevalence of this trait.
00:08:07.15 So, in 2002,
00:08:10.18 there was an elegant study done
00:08:12.20 by Leena Peltonen's group in Finland,
00:08:14.28 in which they identified a genetic mutation
00:08:17.08 that regulates lactose tolerance in Europeans.
00:08:20.20 And it was located near the...
00:08:23.25 upstream of the lactase gene.
00:08:26.01 When we sequenced that region in east African pastoralists,
00:08:29.04 they didn't have it,
00:08:31.10 so we knew they must have something else.
00:08:33.13 So in order to identify those mutations,
00:08:35.21 we did something that's called a lactose tolerance test.
00:08:38.29 So, basically what we do is
00:08:42.11 we give people the sugar lactose in a powdered form,
00:08:46.20 we add water, and it basically tastes like orange Kool-Aid,
00:08:51.09 and then we have to line people up
00:08:54.17 and have them drink the lactose at the same time.
00:08:57.27 This is a group of Maasai women from Tanzania.
00:09:03.28 This is a group of pastoralists from southern Ethiopia.
00:09:11.23 And then we can use a standard diabetes monitoring kit,
00:09:16.03 and what we can do is to measure the blood glucose,
00:09:19.29 starting at baseline before they drink the lactose,
00:09:23.29 and then every 20 minutes we're gonna measure this,
00:09:27.06 over a period of about an hour.
00:09:30.02 And then we're gonna look at the maximum rise
00:09:32.25 in blood glucose.
00:09:35.15 If individuals have a rise
00:09:37.09 that is greater than 1.7 millimolar (mM)
00:09:39.20 we consider them to be lactose tolerant,
00:09:42.20 or to have the lactase persistent trait,
00:09:45.03 shown in light blue.
00:09:47.07 And if they have a rise that is less than 1.1 mM,
00:09:51.12 they're considered to be intolerant,
00:09:53.25 shown in dark blue.
00:09:55.18 So, we measured this trait
00:09:57.12 in nearly 500 individuals
00:09:59.17 from Tanzania, Kenya, and the Sudan,
00:10:02.00 and then we looked for association
00:10:04.10 with genetic variation that we identified
00:10:06.21 by resequencing the region
00:10:08.28 where the European variant had been identified.
00:10:13.13 And in doing so we identified
00:10:15.12 three novel genetic polymorphisms
00:10:18.21 that are associated with the lactose tolerance trait in east Africa,
00:10:22.17 and those are shown here by the boxes.
00:10:26.29 The most common was this one at position 14010,
00:10:31.06 but we also saw those others
00:10:32.24 at positions 13915 and 13907,
00:10:36.03 located roughly 14,000 basepairs
00:10:38.25 upstream of the lactase gene
00:10:41.18 which is located on chromosome 2.
00:10:44.07 Now, one of the really interesting things about this is that,
00:10:48.11 one, these regulatory mutations were pretty far away,
00:10:51.28 about 14,000 basepairs from the gene,
00:10:54.26 and they were located in an intron
00:10:57.25 in a non-coding region of a neighboring gene called MCM6.
00:11:03.00 So this is demonstrating that
00:11:04.25 functionally important variation
00:11:07.13 can actually be located in non-coding regions,
00:11:10.21 and we were able to show,
00:11:13.13 using in vitro cell line studies,
00:11:16.20 that these variants that are derived,
00:11:20.19 shown in the different colors here,
00:11:23.22 that they regulate expression
00:11:26.15 of the lactase gene using the lactase promoter.
00:11:31.10 Now, they're located very close to the mutation
00:11:35.01 associated with lactose tolerance in Europeans,
00:11:38.20 located at position 13910,
00:11:41.14 but they arose independently
00:11:43.17 due to a process called convergent evolution,
00:11:46.13 and probably due to a very strong
00:11:48.27 selective force to be able to drink milk that contains lactose,
00:11:56.15 in these different regions of the world.
00:12:00.27 What's also interesting
00:12:02.19 is that the variants that we identified
00:12:04.16 have a very distinct geographic distribution.
00:12:07.09 So the one that we found that was most common in our study
00:12:10.06 was at position 14010,
00:12:12.08 and we can see that it is pretty localized
00:12:15.01 to east Africa, to Tanzania and Kenya,
00:12:17.26 and that's the most likely site of origin of that mutation.
00:12:21.11 Interestingly, we also see it a bit in south Africa,
00:12:26.01 probably reflecting migration of pastoralists
00:12:28.29 from east Africa into that region.
00:12:32.16 The variant position at 13915
00:12:35.08 appears to have originated in the Middle East,
00:12:37.21 and we could see that it was introduced into northeast Africa,
00:12:40.17 probably by migration.
00:12:43.10 And then the variant at position 13907
00:12:46.26 likely arose in northeast Africa.
00:12:49.21 But again, one of the important take-home points is that
00:12:53.02 we have a functionally important variant
00:12:55.07 that's occurring at high frequency, sometimes as high as 40%,
00:12:59.12 and it's very geographically restricted,
00:13:02.22 and there are likely to be other mutations like that,
00:13:05.06 some of which may have implications for disease susceptibility,
00:13:09.11 again emphasizing the importance
00:13:11.23 to look amongst ethnically diverse Africans.
00:13:16.29 So the next thing we wanted to do
00:13:19.21 was to look for a signature of positive selection,
00:13:23.17 and this is the method in which we can do that.
00:13:27.21 So imagine, here in red,
00:13:30.25 imagine that this is a new mutation that has occurred, say,
00:13:34.15 one of the mutations associated with lactose tolerance.
00:13:38.00 And it's adaptive,
00:13:39.10 meaning that it increases the fitness of individuals who have it,
00:13:43.25 meaning that they're more likely to have children,
00:13:45.27 and their children are more likely to have children,
00:13:47.22 and so on.
00:13:49.28 And so it's going to increase in frequency
00:13:52.24 in the population,
00:13:54.29 and it's going to drag with it
00:13:57.15 the neighboring variants nearby.
00:14:00.03 So, you can see that when it originated, it had...
00:14:02.29 it was on a chromosome with a green variant
00:14:05.18 and a black variant.
00:14:08.03 And now these got dragged along to high frequency,
00:14:11.04 through a process known as hitchhiking.
00:14:14.07 Now, if this had gone to fixation,
00:14:17.12 meaning that everybody has it,
00:14:19.00 we would have called it a full selective sweep.
00:14:21.20 In this case, it hasn't quite reached a full selective sweep,
00:14:26.15 so we call it a partial sweep.
00:14:29.24 Now, that could just mean that
00:14:31.17 there hasn't been time for it to go to a full sweep,
00:14:33.06 or it could be that for some reason
00:14:35.17 there may be some negative aspects of having it,
00:14:38.02 and there's a reason that both variants are maintained in the population.
00:14:43.17 Now, after the sweep occurs,
00:14:45.19 you're going to have new mutation events
00:14:47.26 and new recombination events
00:14:49.21 shuffling up the variants
00:14:52.04 that are linked to the mutation that's adaptive.
00:14:56.12 And so that will decrease the association
00:15:01.00 observed between the mutation and the flanking variation.
00:15:05.00 And in fact,
00:15:06.15 if we have an estimate of the recombination rate,
00:15:08.27 we can use computational methods
00:15:10.24 to estimate how old this mutation is.
00:15:14.18 And that's exactly what we did here.
00:15:17.12 So shown on top
00:15:19.28 is an example from the most common mutation
00:15:22.27 that we found associated with lactose tolerance,
00:15:25.03 at position 14010.
00:15:27.18 Individuals who have the C variant
00:15:29.26 are able to digest milk,
00:15:31.22 and individuals who are homozygous are shown as red.
00:15:35.28 And what we did is we genotyped markers
00:15:38.28 going a distance of about 3 million nucleotides,
00:15:42.26 and what we would do is that if someone is homozygous,
00:15:46.20 starting at the lactose tolerance mutation,
00:15:49.02 and then we go to the next mutation.
00:15:51.02 If they're homozygous,
00:15:53.00 then we continue going.
00:15:55.13 If they underwent a recombination,
00:15:57.05 we stop the line.
00:15:59.13 And what we can basically see is that homozygosity
00:16:02.28 extends about 2 million basepairs
00:16:06.01 on chromosomes that have the lactose tolerance mutation.
00:16:09.15 But if we look at chromosomes that have the ancestral mutation,
00:16:14.00 they have almost no extended haplotype homozygosity.
00:16:19.07 And so this is a classic signature of a selective sweep.
00:16:22.25 It means that this variant
00:16:24.16 was under very strong positive selection
00:16:28.14 and it rapidly increased in frequency in the population,
00:16:32.04 dragging with it the neighboring variation.
00:16:38.16 Now, here I'm showing the European variant,
00:16:41.17 in this case the T variant
00:16:43.20 is associated with lactose tolerance,
00:16:45.27 and it shows a very similar pattern.
00:16:50.22 So using computational approaches,
00:16:52.27 we were able to estimate the age of the African mutation
00:16:57.22 to be somewhere between about 3,000-7,000 years of age.
00:17:01.28 These are the populations
00:17:03.25 that had the oldest age estimates,
00:17:06.08 and they include individuals
00:17:08.07 who speak Cushitic languages.
00:17:10.04 They came from Ethiopia,
00:17:12.10 and they practiced agro-pastoralism.
00:17:15.01 They came into Kenya and Tanzania
00:17:17.16 within the past 5,000 years.
00:17:20.23 And then we saw it at very high prevalence
00:17:23.26 and an old age estimate in Nilo-Saharan-speaking groups,
00:17:27.11 and these would include, for example, the Maasai.
00:17:30.09 Now, they came into the region more recently,
00:17:32.17 from southern Sudan,
00:17:34.08 within the past 3,000 years, so if I were to guess,
00:17:37.05 I would think perhaps this mutation
00:17:39.04 arose in the Cushitic speaking populations.
00:17:42.03 But irregardless, it quickly, rapidly spread
00:17:45.07 to all of the populations in the area
00:17:47.21 because it was so selectively advantageous
00:17:51.22 and adaptive to have this mutation.
00:17:55.03 Now, because we see the correlation
00:17:59.18 between the practice of cattle domestication and pastoralism
00:18:04.11 and the rise in this mutations,
00:18:06.16 this is a really excellent example
00:18:08.22 of gene-culture co-evolution.
00:18:12.03 And in fact, what's really interesting is
00:18:15.01 that the date estimates that we came up with correlate really well
00:18:18.25 with the archaeological data,
00:18:20.17 which shows that cattle domestication
00:18:22.14 arose in the Middle East or north Africa
00:18:27.04 somewhere between 8,000-10,000 years ago,
00:18:29.26 and that corresponds with the age estimate for the European mutation,
00:18:33.18 which we inferred to be about 9,000 years old.
00:18:37.25 But cattle domestication was not introduced
00:18:40.25 south of the Saharan desert
00:18:44.20 until roughly 5,000 or 5,500 years ago,
00:18:48.21 correlating very well with the age estimate
00:18:52.03 for the mutation we found in eastern Africa.
00:18:54.24 And then it was introduced
00:18:56.13 much more recently into southern Africa.
00:19:00.12 But one could argue that perhaps Mendelian traits like lactose tolerance,
00:19:05.04 which are regulated by a single locus or gene of major effect,
00:19:10.23 are in a sense the low hanging fruit;
00:19:12.20 they're the easiest to identify.
00:19:15.04 So one thing that my lab is interesting in doing
00:19:17.10 is looking at more complex traits,
00:19:19.23 and perhaps one of the most classic complex traits is height.
00:19:23.28 So, height is highly heritable,
00:19:26.19 genome wide association studies in tens of thousands of Europeans
00:19:30.12 have identified hundreds of loci,
00:19:33.06 each of very small effect,
00:19:35.06 and explaining only a very small proportion of the variation in height.
00:19:39.20 Now, interestingly, most of these are not part of
00:19:42.22 the growth hormone/IGF1 pathway,
00:19:45.07 which we know plays a very important role in idiopathic short stature,
00:19:49.16 for example.
00:19:53.05 Now, in Africa, we see some of the broadest distributions,
00:19:56.21 or ranges in height,
00:19:59.02 ranging from the very short statured Pygmies in central Africa,
00:20:03.28 and then we see some of the tallest individuals
00:20:07.13 in the Sudan and in eastern Africa.
00:20:10.23 And it's thought that these differences
00:20:12.14 may be partly due to adaptation
00:20:14.29 to different environments.
00:20:16.27 So what I want to tell you today is about
00:20:18.19 our genetic studies of short stature
00:20:22.01 in Pygmy populations from central Africa.
00:20:25.14 And, for you to fully understand and appreciate the work we've done,
00:20:29.17 I think I should first tell you a little bit about
00:20:32.07 how we went about collecting these samples
00:20:34.07 and how challenging it could be.
00:20:35.25 So, this is...
00:20:37.18 to get to one of the groups that we studied in Cameroon,
00:20:39.27 you have to cross this river,
00:20:41.28 and you have a person who has a ferry,
00:20:44.05 he's actually using a hand crank here
00:20:47.13 to get us across.
00:20:50.12 And I guess I'm very fortunate
00:20:52.19 because as a woman, I was able to get shade,
00:20:54.15 but not everybody was that lucky.
00:20:56.28 And here are some other hazards that we run into,
00:20:59.15 but I'm smiling because the head is cut off of this snake.
00:21:03.01 But I actually have to give credit to Dr. Alain Froment,
00:21:06.24 who has been studying the Pygmy populations in Cameroon
00:21:09.16 for greater than 30 years,
00:21:11.20 and he did the majority of the sample collection
00:21:14.01 in this case.
00:21:16.21 So, the genetic basis of short stature in Pygmies
00:21:19.26 is a question that's been of tremendous interest
00:21:22.08 to endocrinologists and human geneticists alike
00:21:25.07 for most than 50 years.
00:21:27.08 The particular populations that we studied
00:21:29.25 are located in Cameroon, three different groups from Cameroon,
00:21:34.27 who mean male height is 152 cm.
00:21:40.11 And they live in very close connection and interaction
00:21:44.29 with neighboring populations who speak Bantu languages
00:21:47.29 and practice agriculture,
00:21:50.06 and their mean male height is 170 cm,
00:21:54.04 so that's quite a difference between the two.
00:21:58.16 So, the Pygmy short statured phenotype in humans
00:22:01.26 has arisen independently in different global populations.
00:22:05.12 Typically, these are populations
00:22:07.03 that live in tropical environments,
00:22:09.14 so there have been a number of hypotheses
00:22:11.11 about why this trait might be adaptive.
00:22:14.28 And these include thermoregulation,
00:22:19.04 limited food resources,
00:22:21.19 locomotion - that it may be easier to move
00:22:23.28 in a dense tropical environment if you're short,
00:22:26.18 and more recently there's a theory
00:22:30.10 that this is due to a life-history tradeoff,
00:22:32.10 and I'm going to focus on that theory.
00:22:35.08 And that has to do with the fact that
00:22:37.14 Pygmies have a remarkably short lifespan.
00:22:40.11 Their chance of living to age 15
00:22:42.06 is only about 40%,
00:22:44.18 and if they make it to age 15,
00:22:46.23 the expected lifespan is only around 25 years of age.
00:22:50.01 Now, that is due largely to very high infectious disease burden
00:22:54.05 and a very challenging life in dense tropical forests.
00:22:59.24 Now, what the study showed is that
00:23:02.18 Pygmies appear to be reaching reproduction...
00:23:05.25 they appear to be reproducing and reaching puberty
00:23:08.09 at a significantly earlier age
00:23:11.01 than other Africans.
00:23:13.13 And the growth trajectory in Pygmies
00:23:14.28 appears to be similar to other populations until the point of puberty,
00:23:19.21 and then they lack the adolescent growth spurt.
00:23:22.15 So this may be some sort of a tradeoff:
00:23:24.18 there's selection to reproduce earlier
00:23:26.22 because they're dying very young,
00:23:28.22 but that may be a tradeoff,
00:23:30.24 in that they're not undergoing the adolescent growth spurt.
00:23:35.20 Now, there have been only a handful
00:23:37.28 of physiologic and metabolic studies in Pygmies,
00:23:42.00 but nearly all of these are pointing towards
00:23:44.18 disruptions of the growth hormone/IGF1 pathway,
00:23:47.19 so this is in contrast to what we're seeing in European populations.
00:23:52.05 However, there's been quite a bit of dispute of
00:23:54.28 where along this pathway these disruptions are occurring.
00:24:00.04 So, in order to try to address these questions,
00:24:03.06 we genotyped one million single nucleotide polymorphisms
00:24:08.06 in 67 pygmy individuals
00:24:10.23 and 58 of the neighboring Bantu individuals.
00:24:14.14 And here we can see a plot,
00:24:17.10 similar to what I've shown you before,
00:24:19.09 based on structure analysis.
00:24:21.09 And to remind you,
00:24:23.02 this is composed of a series of lines,
00:24:24.23 and each line represents a person,
00:24:26.16 and they can have ancestry
00:24:28.08 from different ancestral populations,
00:24:31.01 represented by the different colors.
00:24:33.04 So here in orange
00:24:34.29 are individuals who speak the Bantu language
00:24:38.00 and practice agriculture,
00:24:40.08 and in dark green are individuals who self-identify as Pygmies.
00:24:44.19 And what you can see is that there's been
00:24:46.22 a lot of admixture between the Pygmies
00:24:49.29 and the neighboring Bantu people.
00:24:52.03 Now, interestingly, this tends to be unidirectional,
00:24:54.28 and it tends to be gene flow between males
00:24:57.27 from the Bantu population
00:25:00.03 with females of the Pygmy population.
00:25:02.22 This is largely due to socioeconomic factors.
00:25:06.23 Now, when we look at a correlation
00:25:08.26 between ancestry and height,
00:25:11.03 we observed a very strong and significant positive correlation.
00:25:15.04 So, we can see that Pygmies who have more of the Bantu ancestry
00:25:19.23 tend to be taller.
00:25:21.19 And, so this is showing
00:25:22.25 that there's a strong genetic component to this trait.
00:25:26.17 We've also worked with collaborators
00:25:28.11 to develop methods
00:25:30.19 to infer tracts of Pygmy and Bantu ancestry
00:25:35.11 across the chromosome.
00:25:36.29 So here, these are the different chromosomes,
00:25:38.18 starting with chromosome 1
00:25:40.05 and going up to chromosome 22,
00:25:42.25 and here I'm showing you an example from chromosome 3.
00:25:46.04 And in blue is showing tracts of the genome
00:25:49.03 that are Pygmy ancestry,
00:25:50.24 and in red are tracts of the genome that are Bantu ancestry,
00:25:54.23 and what we tend to see are very, very short tracts of Bantu ancestry.
00:25:58.28 And that's reflected in the fact that admixture
00:26:01.08 has been occurring over thousands of years.
00:26:06.11 Now, the next question that we wanted to address
00:26:08.17 is how do the genomes of the Pygmy hunter-gatherers
00:26:12.04 differ from the genomes of the Bantu agriculturalists
00:26:17.00 and from other groups, such as the Maasai pastoralists
00:26:20.28 from east Africa.
00:26:22.28 And to do that,
00:26:25.03 we use a number of scans of natural selection
00:26:27.28 across the genome.
00:26:29.29 Without getting into detail about the methods,
00:26:32.26 I'll just point out that you can see by the different colors here
00:26:37.00 across the different chromosomes,
00:26:39.00 here's chromosome 22 and going down to chromosome 1,
00:26:42.04 that we found a number of regions of the genome
00:26:44.22 that are targets of selection.
00:26:47.05 But there was one region in particular,
00:26:49.26 on chromosome 3,
00:26:52.04 where we saw a cluster of targets of natural selection.
00:26:57.01 And this was over about a 15 million basepair region.
00:27:01.14 Now, given our small sample size,
00:27:03.20 we have very little power
00:27:05.15 to detect a genome-wide association.
00:27:09.04 And so what we did is,
00:27:10.26 under the hypothesis that this is an adaptive trait,
00:27:13.17 we just focused on the regions of the genome
00:27:16.07 that are targets of selection, shown here,
00:27:19.11 and then we looked for an association with height.
00:27:22.10 And one of the strongest, most significant associations
00:27:25.09 was exactly in that same 15 million basepair region
00:27:29.19 of chromosome 3.
00:27:31.23 And indeed, it encompassed several genes,
00:27:34.15 one of which is DOCK3,
00:27:36.18 which has been shown to be associated with height
00:27:39.09 in non-African populations,
00:27:41.08 so we replicated that finding.
00:27:43.20 But nearby was another gene called CISH,
00:27:47.09 which is a member of the cytokine signaling family,
00:27:50.10 plays a very important role in regulating
00:27:52.28 IL-2 cytokine signaling pathway,
00:27:56.18 and studies have shown that it's associated
00:27:58.26 with resistance to a number of infectious diseases
00:28:01.18 in Africa.
00:28:04.01 Now, interestingly,
00:28:05.29 CISH also directly inhibits
00:28:07.14 human growth hormone receptor action
00:28:10.06 by blocking the STAT5 phosphorylation pathway.
00:28:13.15 And so we know that studies in mice
00:28:15.17 show that when this gene is overexpressed,
00:28:18.06 the mice are short statured.
00:28:20.23 Now, this led me to the hypothesis that,
00:28:24.14 could it be that there could actually be selection
00:28:26.19 for immune function
00:28:28.11 that is indirectly resulting
00:28:30.05 in short stature in Pygmies,
00:28:32.05 because that gene plays an important role in both.
00:28:35.29 And we need to do further functional studies,
00:28:38.20 and look at differences in gene expression
00:28:40.13 to test this hypothesis.
00:28:44.04 The last study I wanna tell you about is a study
00:28:46.20 in which we sequenced the entire genomes,
00:28:49.15 at high coverage,
00:28:51.07 of 15 African hunter-gatherers,
00:28:53.22 including 5 Pygmies,
00:28:55.28 5 Hadza,
00:28:57.10 and 5 Sandawe.
00:28:59.26 We identified over 13 million variants,
00:29:02.29 3 million of which are completely novel;
00:29:05.29 they have never previously been identified.
00:29:08.13 And that's just from 15 individuals,
00:29:10.14 so you can imagine how much variation is out there.
00:29:13.16 Many of these are novel variants...
00:29:15.27 many of these novel variants are in known regulatory sites.
00:29:21.04 So now, combining the two studies,
00:29:24.08 we wanted to ask the question,
00:29:26.03 which pathways are enriched for genes near targets of selection?
00:29:29.16 And these enriched pathways
00:29:31.25 include genes involved in neuro-endocrine signaling,
00:29:35.01 reproduction,
00:29:36.06 metabolism,
00:29:37.11 and immune function,
00:29:38.22 and interestingly, based on the whole genome sequencing study,
00:29:42.08 we saw an enrichment for genes
00:29:44.06 that play a role in pituitary function in Pygmies,
00:29:47.13 including follicle-stimulating hormone receptor,
00:29:50.13 growth hormone receptor,
00:29:52.11 HESX1, which I'll tell you more about in a moment,
00:29:55.11 and thyrotropin-releasing hormone receptor.
00:29:58.15 In fact, TRHR was one of the biggest hits
00:30:02.13 that we saw in terms of these studies of selection.
00:30:05.17 And what's interesting is that this gene
00:30:08.22 plays an important role in the hypothalamic-pituitary-thyroid axis,
00:30:12.28 influencing a number of traits that could potentially
00:30:15.14 be of adaptive significance in Pygmies.
00:30:18.26 And also of interest was that anthropologists
00:30:21.18 have noted that there is a significant difference
00:30:24.23 in the prevalence of Goiter
00:30:27.00 among Pygmies and neighboring Bantu groups.
00:30:29.24 So the Pygmies have a much lower frequency of Goiter
00:30:33.16 compared to the neighboring Bantu populations,
00:30:36.16 and this could reflect a biological adaptation in Pygmies
00:30:41.20 to a low iodine environment.
00:30:43.24 It's very deleterious to get Goiter
00:30:46.22 because it can also lead to a diseased called Cretinism,
00:30:49.27 which of course is going to be very deleterious.
00:30:52.18 So again, here's an example
00:30:54.10 where something like adaptation to diet
00:30:56.13 could indirectly influence growth
00:30:58.28 or other phenotypes in the Pygmy population.
00:31:04.01 The last thing we wanted to do
00:31:06.01 was to look for regions of the genome,
00:31:08.08 using the whole genome sequencing data,
00:31:10.13 that are specific to Pygmies,
00:31:12.20 and those are shown in green here.
00:31:16.02 Now, we identified 25 clusters in the genome,
00:31:19.23 and the largest cluster
00:31:22.27 was right in that same region of chromosome 3
00:31:25.14 that we had previously identified.
00:31:28.00 But we had missed it in the prior study,
00:31:30.11 and the reason why is because
00:31:32.17 it contains these Pygmy-specific variants,
00:31:35.08 that were not captured by the SNP array that we used,
00:31:39.17 and thus demonstrating the great importance
00:31:42.00 of doing resequencing for identifying novel
00:31:44.24 and potentially functionally important variation
00:31:47.15 in ethnically diverse populations.
00:31:50.28 Now, this cluster consisted of
00:31:55.10 44 SNPs in 100% association with each other
00:31:59.16 over 170,000 nucleotide,
00:32:03.06 shown here,
00:32:05.24 and it contained a very interesting candidate gene called HESX1.
00:32:10.10 HESX1 codes for a transcription factor
00:32:13.05 that plays a very important role
00:32:15.04 in regulating the development
00:32:17.15 at the anterior pituitary in the brain,
00:32:20.14 and that's the site of production of growth hormone,
00:32:22.23 as well as other reproductive hormones.
00:32:25.11 Now, interestingly,
00:32:27.06 we identified a non-synonymous,
00:32:29.28 so an amino acid change, basically,
00:32:33.23 in this gene
00:32:36.03 that had been previously associated
00:32:38.13 with idiopathic short stature in humans.
00:32:41.26 But it turns out that this varian
00:32:44.01 t is present at about a 20% frequency in other Africans.
00:32:47.12 So what we hypothesize is that
00:32:49.13 there's something about this region
00:32:51.22 that may be altering gene expression of HESX1
00:32:55.07 or other genes in that region.
00:32:58.01 Upstream, we found another cluster
00:33:01.18 near this gene POU1F1, also known at Pit-1 in mouse,
00:33:07.13 and again this codes for a transcription factor
00:33:09.18 that plays a critical role in regulating growth hormone expression.
00:33:14.23 So another excellent candidate gene.
00:33:17.28 Now, what is interesting is that
00:33:19.27 both of these clusters, or genes,
00:33:23.18 are amongst the most differentiated regions
00:33:26.27 of the Pygmy genomes,
00:33:28.27 compared to genomes from elsewhere in Africa.
00:33:31.29 So we then picked out some of the SNPs in these regions
00:33:37.13 and genotyped them in a larger set
00:33:39.19 of western and eastern Pygmies,
00:33:41.26 and we showed that they are statistically
00:33:44.02 associated with short stature in Pygmies.
00:33:47.29 So the next step is going to be
00:33:49.24 to try to make transgenic models
00:33:52.01 that express these variants using transgenic mouse models,
00:33:56.06 and see what the phenotype looks like.
00:34:00.19 So that leads us to a number of hypotheses.
00:34:03.19 One, is that alterations in the growth hormone/IGF1 pathway
00:34:07.15 play a role in the short stature trait in Pygmies.
00:34:13.01 Two, is that anterior pituitary hormones
00:34:15.10 may play a central role in the Pygmy phenotype,
00:34:18.09 influencing growth, reproduction,
00:34:20.15 metabolism, and immunity.
00:34:24.00 And thirdly, that short stature
00:34:26.16 could be a byproduct of selection
00:34:28.11 acting on pleiotropic loci.
00:34:31.04 So if we look here,
00:34:32.21 one of the candidate loci that we identified is HESX1.
00:34:36.13 That's going to influence expression and development
00:34:39.20 of the anterior pituitary,
00:34:42.02 site of production of growth hormone.
00:34:44.20 Growth hormone expression is also regulated
00:34:46.23 by this other gene we found, POU1F1.
00:34:50.04 And this CISH regulates growth hormone receptor.
00:34:54.17 Now, if we look at the downstream effects
00:34:56.24 of growth hormone,
00:34:59.07 growth hormone, when it binds to growth hormone receptor,
00:35:02.18 will trigger off expression of IGF1,
00:35:06.12 predominantly from the liver, but from other tissues as well.
00:35:10.06 IGF1 will have an effect on muscle growth
00:35:13.14 and also on bone growth and height,
00:35:16.02 but the other impact, or the other role of growth hormone
00:35:20.12 is that it also influences insulin metabolism,
00:35:24.06 it influences fat metabolism.
00:35:28.01 And then we know that infectious disease
00:35:30.01 alters immune response and cytokine levels,
00:35:33.08 and that these can influence gene expression from CISH,
00:35:36.11 or other genes that are in this pathway.
00:35:40.09 So, when we go back to Africa to study the Pygmies,
00:35:42.28 what we would ultimately like to do next
00:35:45.16 is to measure all of the phenotypes,
00:35:48.01 because if you want to understand something
00:35:50.04 like the evolution of short stature in Pygmies,
00:35:52.19 I think you can't just be looking at stature
00:35:55.09 because the growth hormone pathway
00:35:58.25 plays a role in all of these different traits,
00:36:01.01 so we need to be looking at this as an integrative picture.
00:36:06.01 And in fact, our approach in the future
00:36:08.26 is to use an integrative genomics approach
00:36:11.24 combining whole genome data,
00:36:14.15 data on protein variation from blood,
00:36:17.25 epigenetic variation,
00:36:19.21 which can be influenced by diet and environment,
00:36:22.12 gene expression,
00:36:24.10 we're starting to look at the microbiome,
00:36:27.16 which is the spectrum of bacteria in the gut,
00:36:32.05 because that can not only be influenced by diet,
00:36:35.16 it can also have an influence on the metabolome,
00:36:38.12 or the set of all the metabolites, for example,
00:36:40.27 in blood.
00:36:42.20 And we want to combine that information
00:36:44.25 together with information on diet
00:36:46.22 and other environmental factors,
00:36:48.29 to try to identify genetic and environmental factors
00:36:52.15 that play a role in short stature
00:36:55.05 and in other anthropometric,
00:36:56.25 cardiovascular,
00:36:58.01 and metabolic traits.
00:37:00.20 One of the other approaches we can take
00:37:02.20 to distinguish the role of genetics and environment is, for example,
00:37:06.00 to look at individuals of the same or similar ethnic background,
00:37:10.29 but living in an urban versus a rural environment.
00:37:16.21 We can also take a different...
00:37:18.14 the opposite approach.
00:37:20.00 We can look at individuals who have
00:37:22.06 very different genetic ancestries,
00:37:25.03 but live in similar environments.
00:37:27.13 So for example,
00:37:29.20 this is a girl who is from the Fulani population,
00:37:33.17 and here's a neighboring...
00:37:35.19 an individual from the Tupuri population.
00:37:38.26 So they are genetically very differentiated,
00:37:41.20 but live in a similar environment,
00:37:43.16 yet the Fulani seem to have some innate resistance
00:37:47.06 to malaria infection.
00:37:50.03 By contrast, in the San,
00:37:53.09 from southern Africa,
00:37:54.29 are very differentiated from the Bantu,
00:37:57.15 but the San seem to have an innate susceptibility
00:38:01.09 to TB infection.
00:38:03.20 So again, by contrasting populations with different ancestry,
00:38:07.26 and living in different environments,
00:38:09.11 we may identify clues about the genetic basis
00:38:12.10 of differences in phenotypic variation
00:38:14.26 and disease susceptibility.
00:38:17.23 So in conclusion,
00:38:20.20 Africans have the highest levels of genetic diversity
00:38:23.04 within and among populations.
00:38:26.28 The demographic history of Africans
00:38:29.00 and local adaptation to different environments
00:38:31.04 has resulted in population
00:38:33.01 or region specific genetic variation.
00:38:36.25 And we need to be including
00:38:38.21 ethnically diverse Africans in genomic studies
00:38:41.17 to better identify both unique rare, and common variants
00:38:45.28 which may be of functional importance,
00:38:47.28 including those that play a role in disease risk
00:38:50.13 in these populations.
00:38:52.14 And I will just end by thanking
00:38:54.04 the many individuals
00:38:55.25 who contributed to these studies,
00:38:57.29 and my funding agencies,
00:39:00.16 and particular thanks to the Africans
00:39:02.20 who have contributed to these studies.

00:00:12.26 I'm David Haussler, scientific director
00:00:16.03 of the UC Santa Cruz Genomics Institute,
00:00:18.19 and Howard Hughes Medical Institute investigator.
00:00:21.13 It's my pleasure to be able to speak to you
00:00:24.26 on the great questions in biology.
00:00:27.13 I want to have you imagine
00:00:32.17 that you just got your genome sequenced.
00:00:35.06 Now, when we sequenced the first genome
00:00:37.21 in the year 2000, it cost about $300 million,
00:00:41.27 just for the sequencing reagents and activities.
00:00:44.25 But nowadays, it's a couple thousand bucks.
00:00:47.14 So let's assume, you went out and got your sequence done.
00:00:52.18 Now looking at that, it may be hard to interpret
00:00:58.23 but it's got to be a moving experience,
00:01:03.03 to look at that DNA sequence and think about
00:01:06.09 how it got there.
00:01:08.27 In particular the DNA in your genome
00:01:13.00 was passed on from generation to generation
00:01:16.11 for eons.
00:01:18.04 We all come out of the primordial ooze somewhere
00:01:21.24 billions of years ago
00:01:23.29 And it's stunning to think that a record
00:01:27.11 of many of those evolutionary events
00:01:29.24 is still present in the genomes today.
00:01:33.02 So what would you do? What would you look a
00:01:38.17 to start to understand where you came from?
00:01:41.19 And what is specifically interesting about your genome
00:01:46.14 versus all the other genomes on the planet?
00:01:49.09 Probably the first thing you would think about
00:01:54.16 in terms of the way that DNA is inherited
00:01:57.23 from parent to offspring is:
00:02:00.14 are there any new elements of your genome
00:02:04.03 that weren't even in your parents?
00:02:05.21 And statistics say there will be a few
00:02:09.00 So there will be a few changes in the way the DNA
00:02:12.16 was copied. You could think of them as errors,
00:02:16.01 but you could also think of them as fortuitous events
00:02:19.14 that caused something different in your genome
00:02:23.01 that wasn't in either of your parent's genome.
00:02:24.27 Those would be interesting, certainly.
00:02:27.18 And there are probably only a very small handful of those.
00:02:31.27 The next thing you would think about is
00:02:34.21 is there something I inherited from my parents
00:02:40.05 that's just specific to my family in some sense?
00:02:43.21 Maybe it's something special that happened in
00:02:47.12 a great grandparent and has been passed down
00:02:51.11 to me through all of these generations.
00:02:53.20 Now this is the very stuff of genetics.
00:02:57.20 To think about this, in particular, medical genetics
00:03:00.25 you would be very concerned if this actually
00:03:04.14 made you prone to a disease
00:03:05.18 You might also be protected from a disease
00:03:10.09 by a special version of a gene that's in your genome
00:03:13.13 that's specific, or private, to your specific family.
00:03:17.21 That would be exciting.
00:03:20.28 And as we start to get the era from just one genome
00:03:25.27 in the year 2000, to the coming era of millions of genomes,
00:03:29.25 we will be able to, by comparing genomes,
00:03:33.14 understand what's specific to certain families,
00:03:37.19 what's specific to certain ethnic groups,
00:03:39.24 what's specific to humans in general, but not
00:03:45.24 with other species.
00:03:47.09 It's an enormous computational problem
00:03:50.18 to compare all of these genomes, and this is probably
00:03:53.21 the most significant challenge facing the computational part
00:03:58.25 of genetics and genomics today.
00:04:01.20 If you understood what was specific to humans
00:04:05.21 that would be fascinating, you could start to think about
00:04:08.20 what happened since we diverged from our common ancestor
00:04:12.14 with our closest species, the neanderthal.
00:04:16.22 While the neanderthals are extinct,
00:04:19.17 we were able to sequence DNA from their bones
00:04:23.18 and hence, get an idea of their genomes looked like.
00:04:27.06 And we find that there are more than a million changes
00:04:31.27 that occurred in the human lineage
00:04:34.26 since we diverged from our common ancestor
00:04:37.18 to neanderthal.
00:04:38.28 What an exciting project at this point, to try to understand
00:04:42.05 those changes that almost everybody
00:04:47.24 almost all of humankind share,
00:04:49.22 as opposed to and distinguish them from the neanderthal.
00:04:54.23 Going back further, about 5-6 million years ago,
00:05:01.05 we shared a common ancestor with the chimpanzee
00:05:03.25 Since that time, there have been roughly 15 million changes
00:05:07.23 in our genome.
00:05:09.15 Which ones actually account for the difference
00:05:12.22 between a human and a chimp?
00:05:14.10 This is a substantial difference
00:05:16.22 and remarkably, we still know very little
00:05:19.29 about which of those changes actually make that huge difference
00:05:25.04 between a human and a chimp.
00:05:27.04 One thing that you'll run into, in this quest,
00:05:31.06 is the fact that most of these changes
00:05:35.16 are probably not important
00:05:39.03 in some sense.
00:05:40.18 If you look at the structure of your DNA
00:05:45.08 and in particular, if you look at it from this perspective
00:05:48.14 of going back and looking at where the DNA came from
00:05:52.16 what it's history is,
00:05:54.08 you see that there are some parts of your genome
00:05:56.28 that are shared with virtually all other life
00:06:00.11 on the planet.
00:06:01.21 The genes and the DNA in the genes
00:06:03.24 and the ribosome sequences,
00:06:05.20 DNA polymerase. Other fundamental molecules
00:06:11.07 that make life itself possible
00:06:13.02 are remarkably little changed
00:06:15.07 over the eons of evolutionary time.
00:06:17.26 And so when you look at one of those bases in your genome
00:06:21.22 you can sit back and say, "wow, that's a really ancient base!"
00:06:26.19 "That base of DNA was passed on to me
00:06:30.21 all the way back from the beginning
00:06:33.25 billions of years, copied faithfully
00:06:36.29 again and again and again.
00:06:38.15 And now it is a gift to me
00:06:41.18 so that my cells work."
00:06:45.01 In between that are all stages of evolutionary innovation.
00:06:51.00 So when you look at your genome
00:06:53.01 you'll find genes that were created essentially
00:06:58.12 as an evolutionary process in the bilaterian animals,
00:07:02.24 for example.
00:07:04.07 The set of animals that have bilateral symmetry
00:07:07.23 is a huge collection of animals on the planet
00:07:10.27 that they didn't exist 2 billion years ago.
00:07:13.17 So all of their genetic innovations happened
00:07:17.11 after that period.
00:07:19.06 If you look at vertebrates,
00:07:20.24 animals with a backbone,
00:07:22.12 they didn't exist 800 million years ago, but now
00:07:27.24 we can find all of the different innovations
00:07:31.03 that are specific to the vertebrates,
00:07:33.06 the backboned animals, that don't exist in other animals.
00:07:36.02 And each one of these beautiful genetic variations
00:07:39.20 happened at a particular time
00:07:42.05 in the marvelous history of life.
00:07:44.03 So when you're looking at every gene in your genome,
00:07:47.04 you can say "Aha! That's a bilaterian innovation."
00:07:51.02 "Oh, and this one was invented by vertebrates."
00:07:54.17 "And maybe this one was invented by primates."
00:07:57.27 "And maybe this one is specific to apes."
00:08:00.22 Understanding this, is probably the greatest challenge
00:08:07.16 to genomics, going forward at this point.
00:08:11.19 And we have an extraordinary opportunity
00:08:13.28 to look at every base in the genome
00:08:17.05 for the first time.
00:08:18.28 And more importantly, to compare it
00:08:22.23 to the bases in other genomes.
00:08:25.06 The lesson we've learned from first sequencing the human genome
00:08:30.04 in the year 2000, and subsequently looking
00:08:33.17 at the first chimpanzee genome,
00:08:35.09 the first mouse genome,
00:08:36.25 the first rat genome,
00:08:38.17 the first dog genome,
00:08:40.07 is that no genome is ever understandable
00:08:44.08 in isolation.
00:08:45.12 Every time we sequence the genome of a new species
00:08:48.25 we learn more about the genomes that we had previously
00:08:52.28 sequenced from other species.
00:08:55.08 And that is precisely because
00:08:57.20 we share a common heritage
00:08:59.26 and because we are sculpted by evolution.
00:09:03.07 By looking at these patterns of conservation,
00:09:06.27 and change within our genome,
00:09:08.18 we can often decode something about the function
00:09:13.07 of a region of DNA.
00:09:15.00 For example, if it codes for protein sequence,
00:09:19.03 then it has to have this triplet pattern of codons
00:09:22.25 and you'll find that while there are changes in the region
00:09:26.25 they preserve this fundamental property of being able to code
00:09:31.00 for a protein, and we can see that clearly
00:09:33.25 in the pattern of changes which are allowed
00:09:35.27 or not allowed.
00:09:38.00 So that gives us a window,
00:09:40.19 just by studying comparisons between many pieces of DNA,
00:09:44.19 into the function of those pieces of DNA.
00:09:47.17 But we're only seeing the tip of the iceberg here.
00:09:51.13 We're very much at the beginning
00:09:53.12 of a long journey, now that we're in the genomics era
00:09:57.13 and being able to look at all of these genomes
00:10:00.09 together, of decoding them through
00:10:03.11 their history, through comparison.
00:10:05.29 I hope you will consider taking this journey
00:10:09.03 with us. It's a journey that needs not only biologists,
00:10:14.16 but computer scientists.
00:10:15.24 Right now the world is struggling
00:10:18.16 to be able to write the software code
00:10:21.01 to create the computer architecture
00:10:22.29 to be able to compare the full genomes
00:10:26.01 from hundreds, or thousands, of different species
00:10:30.10 This is the very edge of our capabilities at this point.
00:10:35.13 And we can look forward to great innovations,
00:10:38.24 both in terms of computers and algorithms,
00:10:43.15 big data, cloud computing, all of these
00:10:46.18 things will have a say, along with traditional
00:10:50.17 fields like biology, molecular biology, biochemistry,
00:10:54.12 and evolution population genetics.
00:10:57.26 So it's a great time to be involved in this,
00:11:01.09 and I invite you to this wonderful adventure.