September 6, 2019 • 43 mins
How can a DNA sequence represent digital information? How dense is the data storage with DNA? What could be the future of computers with DNA? Join Jonathan and Chris as they delve into the depths and future of DNA and computing.
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Speaker 1 (00:04):
Welcome to tech Stuff, a production of I Heart Radios
How Stuff Works. Hey there, everybody, and welcome to tech Stuff.
I'm your host, Jonathan Strickland. I'm an executive producer with
How Stuff Works and iHeart radio and I love all
things tech, and it is time for another classic episode
of tech Stuff. The episode you are about to hear
(00:25):
originally published way back on October two thousand and twelve.
It is called how d n A Computers Work and
Chris and I dive into the weird, wild world of
computers based on DNA. Hope you guys enjoy. We were
going to share some twisted logic with you today. Yes,
(00:45):
we wanted to talk about dioxy ribonucleic acid computers, DONA,
DONA no nonda, do NAA d n A computers And
what is a DNA computer? What would it be? Because
we're really in the very early stages of using DNA
(01:07):
for the reasons of uh purposes of a computer. But
what would a DNA computer be? Why would we even
use DNA? And what the heck is this DNA stuff? Anyway? Well,
you know, I've got a USB port in the back
of my head, so yeah, he also woke up one
day and he was in a giant battery and he
(01:28):
had to get out. Turns out Chris is the one.
And I'm definitely not we got this. You know, We've
got agents Smith showing up every other day at the
office and we're like, he's not here, today's teleworking and
us is irritating. But anyways, a glitch in the matrix DNA.
So DNA is is is important stuff. I mean, this
(01:51):
is a molecule that contains information that you know, collectively,
this information makes makes organisms what they are, yes and
uh and so biologically DNA is used to store information
and that is really the key there, you know, saying,
(02:13):
wait a minute, if DNA stores information for organisms, could
we use DNA to store information for other purposes. But
to to really explain this, DNA, it's this, it's it's
that double helix molecule you're pricing, uh, you know, illustrations
of it. You may have built a model of it.
If you are in school, you may be studying this
(02:36):
so much that the terms I'm going to use you're thinking, Wow,
he's really glossing over this. But it's because this is
tech stuff, not stuff to blow your mind. So we're
not going to go too deep into the cellular biology
aspect of DNA. Yes, And if you're looking for your
mind being blown, I'm sorry you've come to the wrong place.
Right now. DNA has a has a lot of instructions
in it. Yes, As it turns out, it's a very
(02:58):
tiny molecule with with a very large capacity for for
carrying information. Yeah, if you were to actually stretch out
a DNA molecule and lay it lengthwise, it would end
up taking much more space than it typically does because
it has this twisted three dimensional uh uh structure. Hence
(03:18):
my earlier dumb joke. Right, So this twisted structure actually
allows this this very dense uh storage medium to exist
in a relatively small volume of space. Yeah, because you've
twisted it. And you know, it's the whole thing about
uh conserving surface area and all that great stuff that
(03:40):
all my biologist friends go on and on and on
about and then I end up wandering away. Um. But
DNA has, among many other attributes, there are pairs of
bases that that pair up in DNA, and this is
(04:00):
you know, the the structure of those the sequence of
those determines what information is stored in that strand of DNA. Okay,
so those four bases you have ad anine, citazine, guanine,
and thym ing and usually we just call those A, C,
G and T. And the way that those are sequenced,
(04:24):
like I said, within a strand of DNA, determines the
type of information that that DNA holds. Uh and uh,
it's it's it's that that forms the basis of the
idea of using a DNA computer because in our of course,
in our our classic computer model, we've got computers thinking
(04:48):
quote unquote thinking in binary right, zeros and ones and
so uh. With using DNA. Uh, the approach now is
to associate certain of those bases with zeros and the
others with ones, and the idea being that way you
(05:09):
could sequence a DNA down the length of a strand
of DNA with these zeros and ones. You encode a
strand of DNA that way, and then you would decode it.
You would read back those those base pairings and that
would determine whether each pair was a zero or a one,
and then you would decode that into binary language, and
(05:33):
thus you would get back to whatever information you originally
stored onto the DNA. UM. This is it makes it
sound pretty simple. But this is high tech science stuff
right now. Now, granted it's high tech science stuff that
we have made huge advances in over the last two decades. Really,
(05:55):
So things that were seen as practically a possible two
decades ago are things that we do almost not quite routinely,
but with a greater ease than we could have expected. Yeah,
but over the course of of the last few decades. Um,
it's the kind of thing that when people see the
(06:16):
double helix, it's familiar. Um, you know, it's it's it's
it's high tech science, but it's in our public consciousness too,
it's in our DNA. There you go the fact that
that that's a a uh slang term, you know for something.
When you say it's, it's basically you're saying it's deeply
ingrained in your personality or whatever you're saying that about. Um,
(06:38):
you know, it's it's certainly something that that we're all
familiar with now, but only a few decades ago, you know,
it was completely foreign to us. Yeah. So yeah, let's
we'll do a quick, quick rundown of the history of
our knowledge about DNA, because clearly DNA has existed for
millions of years, but we've only really been aware of
(06:59):
it sense about well, we knew something about it back
in eighteen yes when Freedrich Meischer, who was thank you
was he was a biologist from Switzerland and he was
looking at something pretty darn gross. He was looking at
(07:21):
bandages that had puss on them, and he isolated DNA
from the pus on the bandages, and he thought that
perhaps the this stuff, these nucleic acids, which is DNA
is a nucleic acid. He thought that perhaps this stuff
might contain information in it that would determine why stuff
(07:47):
is the way it is so, genetic information. He thought
that that probably did contain that information, but there was
no way for him to be able to confirm it.
He could not point to anything and say see, I'm right.
So that had to wait for future scientists to uh,
to really dive into it. Not not the past that
(08:08):
bi gross, but to really dive into the information and
study it and and figure out more details. So in
ninete some scientists at Rockefeller University, including Oswald Avery, showed
that DNA taken from a bacterium could make a non
infectious type of bacteria become infectious bacteria. So The thought
(08:34):
was that there must be some information from this nucleic
acid taken from one type of bacteria that could transfer
properties to a different bacteria that otherwise would not have
that infectious property. But what does it r Yes, that's
kind of what everyone was saying. Well, there's some sort
(08:56):
of information holding material here. We don't really in ud
stand the mechanism by which it stores information, nor how
does it impart that information uh or or replicated. We
didn't know that at the time. Uh. And then in
nineteen fifty two, Alfred Hershey and Martha Chase showed that
(09:17):
to make new viruses bacteria fage virus injected DNA into
the host cell, which was important because previously it was
thought that perhaps it was through protein exchange, but instead
of protein exchange, it was DNA exchange. So that showed, yes,
there's something in this. This d N A is what
(09:38):
is important. And then came along Watson and Crick. Yes,
James D. Watson and Francis Crick. Yeah. They it was
clear that, uh, that people were already onto something. Hershey
and Chase had something there, and it was only a
year later when Watson and Crick, uh you know, made
(09:59):
their announcement they had discovered the structure of DNA, right,
and so this is when we started to really learn
what how DNA you know, forms, and what shape it
takes and why that's important. And um So once all
of that was taken, once we learned all that, we
(10:22):
began to see that these base pairings I was talking about,
we learned that they pair in very specific ways. You know,
I mentioned there are the four different bases. There's A,
the A, C, G T. Well, half of those A
and G are called purines. Uh, C and T are
(10:42):
uh perimidines. I'm glad you took that part. Yeah, me too,
Uh you know, way back when I was actually really
good at biology. But man, that was a few decades ago.
So anyway, uh puriings and peri perim pyrimidines. Look, I
can't even do it now, periods of paramidines. Still, glad
(11:02):
you took that bond together. Right, So, uh, you don't
get two puringes bonding together, and you don't get two
pyramidines bonding together. And to be even more specific, A
and T will bond together and C and G will
bond together. All right, so that that means that you know,
(11:22):
you can't. You're not going to get a strand of
DNA where A and C or A and G are
paired together. It does not happen, right they Structurally that
doesn't happen. So uh. That also dictates the rationale behind
using uh these pairings as zeros and ones, because you
(11:45):
can either have uh. You can either have the A
T pairing or the C G pairing, right, so that
that lets you say, okay, well that's binary. It's either
you you just designate that one means one, pairing means zero,
the other pairing means one. Um. If it weren't that case,
if we could have multiple pairing multiple uh uh, like
(12:09):
like if A could pair with G instead of just
A and T, then you would say, all right, well,
now we've got a system that goes beyond binary, which,
in theory, if you completely change the way computers work,
would mean that you could dramatically increase parallel processing because
(12:29):
you could designate things. It would almost be like the
cubits of a quantum computer, where you know the basic
explanation as a cubit represents both a zero and a
one and all values in between in superposition of one another,
and that if you have enough cubits, you can perform
(12:50):
a massive parallel processing problem all at the same time
because those that that one group of cubits is behaving
as if it's uh, you know, a huge number of
traditional bits. I think it's important to remember too that
no matter how many bases DNA has, they all belong
(13:14):
to us. Oh I knew it. I knew it. I
was like, oh, I's gonna do an all your base
I belonged to us if someone set us up the bomb,
so well, it could be Actually, if you if you
were trying to if those pairs become corrupted, they will
not work and uh and a cell can die. Actually,
we're getting a lot of this information to from our
(13:35):
our excellent article on how stuff Works dot com about
how DNA works. It gets into a whole lot more detailed, right, Yeah,
if you want to learn more about and and it's
very accessible. It's a very accessible article. So if you're
curious about you know, you've always heard about d N A,
and you've heard about DNA testing, and you know about
chromosomes and genes, but you're not really you know, beyond that,
(13:55):
you're kind of confused. I highly recommend you read how
DNA works at how stuff works dot com. We also
have an article on how DNA computers work, which is
pretty interesting because it's talking about an earlier era of
DNA computers, but recent developments have really brought it brought
to lights some interesting, uh, new technologies and new use
(14:17):
cases for d n A and we'll get into those
in a second. Yeah, It's it's funny that you say that,
because I'm sure that people this is futuristic enough where
people are saying, what are you talking about new developments?
We haven't heard of a d n A computer before?
But yeah, that's that's not really surprising. This is the
kind of thing like like quantum computing, where they've been
working on it for some time, but it's not at
(14:38):
a point where they can really, you know, put something
on a shelf and go look at this. Yeah, yeah,
where people really take notice of it. In general, this
is all stuff that's taking place in universities and research facilities,
and it's you know, most of these machines that are
being made now or or these implementations of using DNA
for information digital information are are really in the prototype stage.
(15:01):
But we're getting the technology that allows us to create
these machines is becoming more and more sophisticated and less expensive,
which of course is key huge any news. And Gordon
Moore explained that back and when he did his his
paper about cramming more components onto an integrated circuit. His
point was not just that technology was advancing to a
(15:24):
point where we could shrink stuff down and fit twice
as many components onto a square inch of silicon as
we could a year ago. It was also that the
manufacturing process was becoming efficient enough and cheap enough where
that made sense. So same sort of thing here. Well,
all right, so we've we've determined that DNA contains information.
(15:45):
It because of its very structure, it can contain a
lot of information in a small volume. Uh. And then
it wasn't until about nine and I remember it was
the it was the fifties, the early fifties when we
started to really understand what DNA was and how how
it formed and how and its structured and everything like that.
Into a man named Leonard Edelman came up with this idea.
(16:09):
He sort of uh introduced the idea of using DNA
to solve math problems. And it was essentially this idea
of coding DNA as if it were a strip of
binary code. And so he took this idea and he
(16:30):
sort of ran with it. He began to formulate an
idea about how to how to create an experiment that
could show that this would work. And it's funny because
it's talking about a DNA computer, but if you read
about the experiment, it sounds more like someone in a
chemistry lab mixing various chemical compositions together and then coming
(16:52):
up with a solution at the end of it. And
that's it turns out that this is a computational solution,
not just a chemical solution. I see what you did there,
Ye little word play there. Yeah, it's a little a
little incredible. So he yeah, he um, he dissolved my objections.
Chris and I have more to say about DNA in
(17:13):
just a moment, but first let's take a quick break
to thank our sponsor. Let me read I'll read the
steps from our article on DNA computers, because I want
to explain how this early, early, early implementation of a
DNA computer, how it how it played out, and it's
(17:37):
kind of amazing. All right. Here are the steps. Number
one strands of DNA represent the seven cities now when
it says seven cities in here, what he was doing
was he was trying to solve something called the traveling
salesman problem, also the directed Hamilton's path problem. The idea
being that you're supposed to find the shortest route between
(17:58):
a group of cities and and it could be any
number really of cities, but you have to only go
through each city one time, um, and it becomes more complex.
This is this is why this is such a fascinating
problem uh as Jonathan pointed out to me right before,
he reminded me that this is something that quantum computing
is fascinated with because this is such a I don't
(18:20):
know what you call it, thorny, a thorny problem. So
it was that problem that they were were that he
wanted to work on, and he chose, I believe seven cities,
he said, that is his benchmark he wanted to do.
And see, this is this is an interesting problem for
uh in computers because think about it, you've got seven cities,
you can only travel through each city once. You have
to find the most efficient pathway to go. Well, the
(18:42):
way a computer would do this, generally speaking, is to
start going through every single possible um permutation of that
trip going from city to city and determining which of
those is the most efficient by the end of it,
by comparing them all, which can take ages and as
as of course, as you add more cities, as you
(19:04):
add complexity to the problem, it creates an exponentially more
difficult problem for the computer to solve. You know, I
don't think it's that unlike trying to crack a password. Yeah,
in the in the you know, other references we've made
to these again, parallel processing. That's another reason why quantum
computers are very scary for anyone who's in cryptography who
(19:25):
wants to create good encryption, because they're talking about using
parallel processing to attack, you know, do a brute force
attack on a password. You can really reduce the amount
of time it would take you to crack a password,
like a password that would probably take you thousands of
years in classic computer time might only take an hour
(19:46):
in using a quantum computer because it's using that parallel approach.
So just remember, quantum computing is the cure for the
common code. Man, what is it with you today? I
don't know. Chris is in a move anyway? All right,
Getting back to getting back to this thing, this set
of steps. All right, So Edelman creates strands of DNA
(20:09):
that represent the seven cities. Uh and so it's these A, T,
and CG pairings and then um, these various sequences represent
each city and possible flight path. He then took the
molecules that these strands of DNA and mixed them in
a test tube, and some of the strands of DNA
(20:32):
stuck together in a chain. Of those strands represented a
potential answer to that question, which of these you know,
which route is the most efficient. Within a few seconds,
all of the possible combinations of DNA strands were created
in the test tube, and then Adelman eliminated the wrong
molecules through chemical reactions, which left behind only the flight
(20:53):
paths that connect all seven cities. So here he was
doing chemistry and looking at molecules by uh and it
was and it was biological chemistry because he was using
organic DNA um and and trying to come up with
the answer that way, which is pretty interesting to me.
(21:15):
I mean, it looks that sounds so different from the
way we think of computing today, where you're using microprocessors
and you know, the user interface looking at screen this
guy is using test tubes and molecules um and he
was actually thinking at the time that this would be
DNA computing is going to be the future because it
packs so much information in such a small form factor
(21:37):
and it's plentiful. Yes, because there's a lot of life
out there, and organic life relies on DNA heavily. There's
some that rely on RNA, but we're not going to
go into that. But anyway, a great amount of organic
life out there has lots and lots of DNA, so
the we've got plenty of materials to work from. Uh.
(22:01):
What's interesting is that since that time where his first
experiments were showing the viability of a DNA computer, our
ability to sequence synthetic DNA has improved to the point
where organic DNA is not really what we care about anymore.
We can synthesize DNA in the lab and just make
(22:22):
it ourselves so we don't have to um harvest it.
As Chris was saying in the pre show, you know,
it would be a totally different world if you realize
that your computer was running out a memory, so you
checked another hamster into your machine so that you could
finish whatever it was you were doing. That was a
particularly gory idea. Well we didn't know, but yeah, I
(22:44):
left out the part about the grinding noises, you know,
and for flying out the back you yeah, and I
thought that was my contribution. Um, yeah, they University of Rochester,
there were some researchers at found ways to use DNA
to create logic gates. Again in the it looks like
(23:08):
um so uh and that's we've touched on on several occasions,
but that those logic gates are basically key to classic computing. Yeah,
this is what uh, this is. This is what allows
the computer to dictate how information moves through it so
that it has any meaning. You know. The logic gates
(23:28):
essentially dictate whether the zero or one that goes into
the gate comes out at zero or one on the
other side or something. Usually it's a pair. If it's
a zero and a one on the other side of
the gate, is that going to be a one or zero?
And it all depends on the type of gate it is. Um.
And of course you you can link a bunch of
gates together to create all sorts of different outcomes depending
(23:51):
upon what the input is. This is all very important
from classical computing. So getting to that step of being
able to build logic gates out of d in a
it was pivotal if you want to be able to
eventually build a true DNA computer. And again this is
you know, you compare the components of a DNA computer
(24:12):
to those of a an inorganic computer. UM. And we have,
as a Jonathan pointed out and Gordon Moore's uh famous
prediction that the transistors would double in number per square
inch of silicon back in the original prediction, UM, you
know every you know over a certain period of time,
(24:34):
which again has changed, you know, year, year and a half,
two years. The thing is, um, we're talking about a
flat piece of silicon. And we've also talked about how
hard drives, the classical hard drive, UM, you know has
so much information on it. It's in a it's in
a flat plane. We've talked about electronic memory and how
(24:56):
you know this information is is getting stored. But we
basically been talking two dimensional and and a long time
ago we talked about processors and how at some point,
due to the limitations of physics like it's at some
point electrons will begin to tunnel through layers of the
material used to create transistors, basically making them ineffective. So
(25:18):
at some point, theoretically the traditional transistor chip is going
to be so full that you cannot fill it anymore
without having serious electrical problems. So they were talking about
going into three D processors. Well, d N a kind
of goes around that problem or is a natural if
you will solution. Hey, for once, that wasn't a pun
(25:40):
intended um, because DNA is volumetric. It isn't it can
fit because of its its natural characteristics. It doesn't have
to be in a two dimensional flat shape. You don't
have to stretch out the helix and stick it on
a piece of silicon or whatever to make it work. Um,
(26:01):
and that gives uh, that gives computing so much more
advantage to move to a DNA based existence, right. Yeah.
The the challenge is building The challenge is building the
equipment that allows you to sequence and decode that information
because you know that's where where that's where the bottleneck is.
(26:23):
Right now, is that the it's not simple, Yeah, we
have to get there. Yeah, But once we get to
a point where we're able to construct the DNA and
lay it out in such a way where we're able
to pack in all that information, and then we have
the companion devices that can decode that and make it
meaningful to a computer. Again, then you're talking about some
(26:48):
huge leaps in storage capacity. One gram of d n
A can store up to four hundred and fifty five
billion gigabytes of data, which is about a hundred billion
DVDs worth of information. Yea, yea. As a matter of fact,
this is the article that sort of uh turned me
(27:10):
onto this idea was something that my friends Kim and
Tim pointed out to me in the in the Guardian,
which really wasn't that long ago August two thousand twelve.
They started talking about how books had been encoded in
dna UM and that that got me to thinking and
to suggesting this to Jonathan as a potential topic because
(27:33):
it's it's fascinating that d n A, something so small,
can hold that much information. Yeah, and it's funny because
the story goes it talks about how Professor George Church
lead this project and he belongs to he well, he teaches,
he teaches at HAVD, but not just Harvard, it's Harvard
(27:55):
Medical School. This is this is one of those weird things,
uh that this this overlaps science, computer science, and uh medicine. Yeah,
so you've got I'm sorry, physical science and medical science.
Let's say that right. No, No, that's that's fine. That's
a computer science and and medical science. It's it's multidisciplinary obviously,
(28:18):
just like nanobiology or nanotechnology is a multidisciplinary approach. So
is this DNA computer or DNA storage idea. We've got
a little bit more about DNA ahead of us, and
before we get to that, let's take another quick break.
(28:42):
So what what Professor Church did was they decided to
take a book that was about five point to seven
megabits of digital space once you converted into digital information,
and to uh encode that as d N A and UM.
(29:05):
They didn't do it just once. They decided to duplicate
it a few times, seven seventy billion times, seventy billion
copies of this book, which, according to an article in
Extreme Tech, prompted them to joke that it made it
the best selling book of all time, yes, and that
(29:27):
it was. The seventy billion copies totaled about forty four
peta bytes of data. UM. So that is slightly larger
than the N A S I have attached at my
network at home. Yeah, yeah, forty four pea bites. That's
an incredible amount of information. It's also quite a bit
smaller than my n A s Yeah. So so when
(29:50):
you think about it, the the promise of d n
A is that with a relatively small amount of DNA
you could store the sum total of all human knowledge
in a very tiny compartment, relatively speaking, a tiny compartment.
(30:11):
And uh, if you're able to use that same sort
of uh of capacity in a processing way as opposed
to just storage storage is great. I mean, that's fantastic.
The the the this project was really showing how using
DNA is great for archival purposes if you want to
(30:33):
store information for longevity's sake. And another point about that
is that this yeah, is that here's here's an issue
that we have with storing information. The way we access
information changes over time, and some of the there there
are multiple problems here. Sometimes the way we store information, uh,
(30:55):
we store it on a medium that can decompose, which
means it as time passes, the likelihood that that data
is intact decreases. So let's say like a book. Okay,
books are susceptible to lots of different environmental factors that
can make them impossible to read. So as time goes by,
(31:19):
a book's ability to preserve the information decreases, particularly depending
upon its environment. Yeah. And and one of the things
that's funny to me about this is, and I'll keep
this short, but it's it's funny to me that in
a way, Uh, the increase in technology, um has only
(31:39):
increased the rate of data rot as some people call it.
Because you think about something like the Rosetta stone and
how long ago that was chiseled, but it's still there
because hey, you know it's stone. If now, if you
left it out in the elements, eventually the the writing
on it will wear away due to the effects of erosion.
But um, that's longer lived than say, paper, which could
(32:01):
be eaten by weevils or could be affected by mold
or mildew or or even water or fire. Um. You
know there there are many things acid in the paper. Um.
But but that would be longer lived than say, um,
a magnetic storage medium, which might may only live a
few decades. Yeah, because you've got with magnetic storage, eventually
(32:23):
that magnetic properties starts to kind of and I have
Dad gets corrupted. Yeah, and I've had CDs and DVDs
that I've burned and a few years ago that are
starting to show signs of deterioration. And I'm thinking all
this futuristic stuff, it's kind of funny. The stuff that's
chiseled in stone is still there well. And on top
of all that, besides the fact that you've got these media,
(32:46):
these media that will that can degrade over time. Um,
magnetic definitely is more susceptible that I would say than
optical storage. But but both can can degree and both
are susceptible to damage. I mean, just about everything is.
But but the other problem is that we move away
(33:07):
from those older forms of media and eventually we get
to a point where nothing we have can read what
we used to use, or if you do have something
that can read it, it's a legacy system. So like
the keeping old computers around simply to read those documents, right,
like like anything that's on an old five and a
quarter inch diskette from the early days of the personal computer,
(33:31):
you know, and I still have something, I would wager
that most people do not have easy access to such
a disk drive. Um, you know, especially if you're just
kind of an average user and you've gone out and
you're like, oh, I want a new laptop. You go again.
If you buy a new laptop today, you might not
even have an optical drive, which means that there you
could come across records of information that you have no
(33:54):
way of accessing because you do not have the tech
capable of accessing it. Well, d n A is a
basic building block of organic life, and so the idea
is that because it's something so basic, we will always
have the ability and assuming that you know, we don't
have some sort of post apocalyptic event, while an apocalyptic
(34:16):
event that then leads to post apocalyptic events, um, then
we should be able to have equipment that can read
this same information. Hey, do you have the instructions on
how to read DNA? Yeah? I saved it on that
magnetic wa now here in Atlanta. Were used to post
apocalyptic events because we've got zombies. Yes, you may have
seen if you've watched the documentary The Walking Dead as
(34:38):
seen on TV. So, um, yeah, the the idea was
that this will d n A does not degrade over time. Well,
it takes a much longer time than something like a
paper book. Right, So since you're not worried about degrading.
I mean when I say it doesn't degrade over time,
we're talking generations here, the undreds of thousands of years
(34:59):
so people. So yes, I wouldn't know eventually it will degrade,
but for the foreseeable future it won't. Uh. It takes
up far less space. We don't have to worry so
much about not being able to access the information anymore
because against the basic building block, we will presumably be
still be interested in DNA in the future. Uh. In fact,
(35:22):
it become increasingly interested as we learn more about how
to uh to tweet DNA to do things like fight
off illnesses and other scientific applications of that knowledge. So
that was kind of the whole point was that it's
great for archival and that reason it's gonna be. It's
it's it's a it's a more permanent solution in multiple ways.
(35:46):
And uh, that's really where the focus is on the
recent articles that we've been reading, although there's still obviously
quite a bit of development on the research and about
building a true DNA computer that would have of an
incredibly small form factor. I mean, you're talking about, uh,
DNA being the size of a couple of atoms, and
(36:08):
this is some small stuff. I mean, we could theoretically
have a DNA computer capable of performing huge calculations and
storing an enormous amount of data in a tiny, tiny
form factor. It would be amazing if we could look
into the future, maybe I don't know, twenty fifty years
(36:29):
something like that, where perhaps we have reached the point
where this technology is viable and reproducible and economic, where
we could see it in applications that actually the average
consumer could access. It wouldn't just be the realm of
the scientific community or the research community. It would also
be within our grasp. Because then can you imagine you
(36:51):
can have a smartphone that could literally contain all the
data that we have ever generated ever since the dawn
of man on your phone. I was waiting for you
to go all the data. No, that was it, just
all of all the data, um well, all the data
we have access to. Um there there. It's astounding to
(37:15):
think of something uh so common that has been with
us for so long being an answer and fairly easy
answer to a lot of these problems. I mean, like
I said, it's not easy to get there, but the
idea is like really just DNA. As it turns out.
You know, they've they've been using synthetic DNA to run
(37:36):
these experiments, and there are some drawbacks, one of which
is it can't be rewritten. That is true. So once
you write that data, it's that's another reason why people
are talking about for archival purposes. Once you write the data,
that's it. Now. Granted, you're talking about a construct that's
so small that you could keep doing that indefinitely and
(37:58):
not have to worry about taking up too much space.
But that's just the way they're thinking of it right now. Right.
But but you know you can't. You can't always think
that way because someday that will catch up to you.
Apparently that might be when we're actually saying, hey, hey,
we finally got a plan on how to get off
this rock because the Sun's gonna swallow us up in
(38:20):
another million years. That that would never happen. By the way,
don't don't write into me and explain to me why
that would be ridiculous. I understand. I was just using
that as a an example. Well, and and the other
thing is, um, you know, and yes, I realized that
this is you know that you could destroy DNA, but um,
(38:41):
thinking about that the sensitive information can't be erased. Then
you would need to keep up with your Let's say
you had a DNA drive like you have a flash
drive to carry back and forth with you, uh, and
it gets lost and it had I don't know importance
and sitive documents related to national security or um you know,
(39:04):
the secret um uh copy of your unpublished book, and
somebody else runs across it and makes billions of dollars
off of it because they found it. You can't you
can't remotely wipe that information. I don't know how you
would do that without destroying without physically destroying the material.
So it's that's sort of a a minor drawback, really,
(39:28):
but it's something it's it's something very different from the
media that we typically talk about. So clearly in that case,
you would be talking about, all right, well, now we've
got this incredible archival ability. Now we have to figure
out a way of securing it. Oh well, don't see that. Well,
and this brings me to my brilliant science fiction idea
which I I said in the pre show. I said,
(39:49):
if if someone steals this, I will find you. See.
That was my That was my like shout out to
your no, no, I'm sharing it because if someone out
there makes the us, I want to cut. So here's
the sci fi idea. Guys. You have a character who
is just an ordinary guy or girl, you know, someone
who is going through life and they've got the same
(40:12):
sort of challenges and problems and joys and despairs as
all the rest of us. But then suddenly they noticed
that they're being watched and people are closing in on them,
and they don't know why because they're just a normal person,
and so they're trying to get away, and it turns
out they find out that they themselves are a synthetic
life form. They were built in a lab from the
(40:34):
ground up, and in fact, their DNA contains this incredibly
important information encoded into this person's very being is a
secret message of such import that various forces are closing
in on them, determined to get hold of this person,
lop off a finger and figure out what the heck
is going on, And so the character has to go
(40:55):
through this incredible series of adventures in order to figure out.
It's kind of a journey of self discovery as well
as protection, and there's a whole like hero arc and
the credits are great and Bruce Willis Stars and I
want to cut I've got data under my skin, are
in it and through it. So, guys, yeah that was
(41:17):
I'm sure someone's gonna write in and say, yeah, that
was a great story when so and so wrote it
years ago. I want to read it. Yeah, yeah, I
I have no illusions that someone has not already come
up with that idea. But if they haven't, and then
you guys think that's a great idea and you want
to go out and make it. Remember, I want to
credit and some money or at least a sandwich. Come on,
(41:39):
writer's gotta eat all right, assassinating stuff though, it's it's
the kind of thing that I would never have thought
to do, so, I mean, I'm blown away by that. Yeah,
it's a it's a pretty fascinating subject. And like we said,
there's that we have some great articles on how stuff.
We actually can go and check those out and read
up on DNA and DNA computers and you know, like
I said, they are the articles on the Guardian as
(42:01):
well as other places that are talking about this storage
medium and it blows my mind. Hey, guys, hope you
enjoyed that classic episode of tech Stuff Always a joy
to revisit the old episodes we did in the past.
It's also interesting that I decided to throw this one
in there, because obviously a lot has happened since two
(42:23):
thousand twelve, so I may have to do a full
update episode about d n A computers in the near future.
If you're interested in hearing such a thing, let me know.
The email address for the show is tech Stuff at
how stuff works dot com, or jump on over to
the website that's text stuff podcast dot com. That's where
you're gonna find an archive to all of our previous episodes,
(42:45):
as well as our presence on social media, and you
also find a link to our online store, where every
purchase you make goes to help the show and we
greatly appreciate it, and I'll talk to you again really soon.
Text Stuff is a production of I Heart Radio's How
Stuff Works. For more podcasts from I heart Radio, visit
(43:07):
the I heart Radio app, Apple Podcasts, or wherever you
listen to your favorite shows.
Welcome to tech Stuff, a production of I Heart Radios
How Stuff Works. Hey there, everybody, and welcome to tech Stuff.
I'm your host, Jonathan Strickland. I'm an executive producer with
How Stuff Works and iHeart radio and I love all
things tech, and it is time for another classic episode
of tech Stuff. The episode you are about to hear
(00:25):
originally published way back on October two thousand and twelve.
It is called how d n A Computers Work and
Chris and I dive into the weird, wild world of
computers based on DNA. Hope you guys enjoy. We were
going to share some twisted logic with you today. Yes,
(00:45):
we wanted to talk about dioxy ribonucleic acid computers, DONA,
DONA no nonda, do NAA d n A computers And
what is a DNA computer? What would it be? Because
we're really in the very early stages of using DNA
(01:07):
for the reasons of uh purposes of a computer. But
what would a DNA computer be? Why would we even
use DNA? And what the heck is this DNA stuff? Anyway? Well,
you know, I've got a USB port in the back
of my head, so yeah, he also woke up one
day and he was in a giant battery and he
(01:28):
had to get out. Turns out Chris is the one.
And I'm definitely not we got this. You know, We've
got agents Smith showing up every other day at the
office and we're like, he's not here, today's teleworking and
us is irritating. But anyways, a glitch in the matrix DNA.
So DNA is is is important stuff. I mean, this
(01:51):
is a molecule that contains information that you know, collectively,
this information makes makes organisms what they are, yes and
uh and so biologically DNA is used to store information
and that is really the key there, you know, saying,
(02:13):
wait a minute, if DNA stores information for organisms, could
we use DNA to store information for other purposes. But
to to really explain this, DNA, it's this, it's it's
that double helix molecule you're pricing, uh, you know, illustrations
of it. You may have built a model of it.
If you are in school, you may be studying this
(02:36):
so much that the terms I'm going to use you're thinking, Wow,
he's really glossing over this. But it's because this is
tech stuff, not stuff to blow your mind. So we're
not going to go too deep into the cellular biology
aspect of DNA. Yes, And if you're looking for your
mind being blown, I'm sorry you've come to the wrong place.
Right now. DNA has a has a lot of instructions
in it. Yes, As it turns out, it's a very
(02:58):
tiny molecule with with a very large capacity for for
carrying information. Yeah, if you were to actually stretch out
a DNA molecule and lay it lengthwise, it would end
up taking much more space than it typically does because
it has this twisted three dimensional uh uh structure. Hence
(03:18):
my earlier dumb joke. Right, So this twisted structure actually
allows this this very dense uh storage medium to exist
in a relatively small volume of space. Yeah, because you've
twisted it. And you know, it's the whole thing about
uh conserving surface area and all that great stuff that
(03:40):
all my biologist friends go on and on and on
about and then I end up wandering away. Um. But
DNA has, among many other attributes, there are pairs of
bases that that pair up in DNA, and this is
(04:00):
you know, the the structure of those the sequence of
those determines what information is stored in that strand of DNA. Okay,
so those four bases you have ad anine, citazine, guanine,
and thym ing and usually we just call those A, C,
G and T. And the way that those are sequenced,
(04:24):
like I said, within a strand of DNA, determines the
type of information that that DNA holds. Uh and uh,
it's it's it's that that forms the basis of the
idea of using a DNA computer because in our of course,
in our our classic computer model, we've got computers thinking
(04:48):
quote unquote thinking in binary right, zeros and ones and
so uh. With using DNA. Uh, the approach now is
to associate certain of those bases with zeros and the
others with ones, and the idea being that way you
(05:09):
could sequence a DNA down the length of a strand
of DNA with these zeros and ones. You encode a
strand of DNA that way, and then you would decode it.
You would read back those those base pairings and that
would determine whether each pair was a zero or a one,
and then you would decode that into binary language, and
(05:33):
thus you would get back to whatever information you originally
stored onto the DNA. UM. This is it makes it
sound pretty simple. But this is high tech science stuff
right now. Now, granted it's high tech science stuff that
we have made huge advances in over the last two decades. Really,
(05:55):
So things that were seen as practically a possible two
decades ago are things that we do almost not quite routinely,
but with a greater ease than we could have expected. Yeah,
but over the course of of the last few decades. Um,
it's the kind of thing that when people see the
(06:16):
double helix, it's familiar. Um, you know, it's it's it's
it's high tech science, but it's in our public consciousness too,
it's in our DNA. There you go the fact that
that that's a a uh slang term, you know for something.
When you say it's, it's basically you're saying it's deeply
ingrained in your personality or whatever you're saying that about. Um,
(06:38):
you know, it's it's certainly something that that we're all
familiar with now, but only a few decades ago, you know,
it was completely foreign to us. Yeah. So yeah, let's
we'll do a quick, quick rundown of the history of
our knowledge about DNA, because clearly DNA has existed for
millions of years, but we've only really been aware of
(06:59):
it sense about well, we knew something about it back
in eighteen yes when Freedrich Meischer, who was thank you
was he was a biologist from Switzerland and he was
looking at something pretty darn gross. He was looking at
(07:21):
bandages that had puss on them, and he isolated DNA
from the pus on the bandages, and he thought that
perhaps the this stuff, these nucleic acids, which is DNA
is a nucleic acid. He thought that perhaps this stuff
might contain information in it that would determine why stuff
(07:47):
is the way it is so, genetic information. He thought
that that probably did contain that information, but there was
no way for him to be able to confirm it.
He could not point to anything and say see, I'm right.
So that had to wait for future scientists to uh,
to really dive into it. Not not the past that
(08:08):
bi gross, but to really dive into the information and
study it and and figure out more details. So in
ninete some scientists at Rockefeller University, including Oswald Avery, showed
that DNA taken from a bacterium could make a non
infectious type of bacteria become infectious bacteria. So The thought
(08:34):
was that there must be some information from this nucleic
acid taken from one type of bacteria that could transfer
properties to a different bacteria that otherwise would not have
that infectious property. But what does it r Yes, that's
kind of what everyone was saying. Well, there's some sort
(08:56):
of information holding material here. We don't really in ud
stand the mechanism by which it stores information, nor how
does it impart that information uh or or replicated. We
didn't know that at the time. Uh. And then in
nineteen fifty two, Alfred Hershey and Martha Chase showed that
(09:17):
to make new viruses bacteria fage virus injected DNA into
the host cell, which was important because previously it was
thought that perhaps it was through protein exchange, but instead
of protein exchange, it was DNA exchange. So that showed, yes,
there's something in this. This d N A is what
(09:38):
is important. And then came along Watson and Crick. Yes,
James D. Watson and Francis Crick. Yeah. They it was
clear that, uh, that people were already onto something. Hershey
and Chase had something there, and it was only a
year later when Watson and Crick, uh you know, made
(09:59):
their announcement they had discovered the structure of DNA, right,
and so this is when we started to really learn
what how DNA you know, forms, and what shape it
takes and why that's important. And um So once all
of that was taken, once we learned all that, we
(10:22):
began to see that these base pairings I was talking about,
we learned that they pair in very specific ways. You know,
I mentioned there are the four different bases. There's A,
the A, C, G T. Well, half of those A
and G are called purines. Uh, C and T are
(10:42):
uh perimidines. I'm glad you took that part. Yeah, me too,
Uh you know, way back when I was actually really
good at biology. But man, that was a few decades ago.
So anyway, uh puriings and peri perim pyrimidines. Look, I
can't even do it now, periods of paramidines. Still, glad
(11:02):
you took that bond together. Right, So, uh, you don't
get two puringes bonding together, and you don't get two
pyramidines bonding together. And to be even more specific, A
and T will bond together and C and G will
bond together. All right, so that that means that you know,
(11:22):
you can't. You're not going to get a strand of
DNA where A and C or A and G are
paired together. It does not happen, right they Structurally that
doesn't happen. So uh. That also dictates the rationale behind
using uh these pairings as zeros and ones, because you
(11:45):
can either have uh. You can either have the A
T pairing or the C G pairing, right, so that
that lets you say, okay, well that's binary. It's either
you you just designate that one means one, pairing means zero,
the other pairing means one. Um. If it weren't that case,
if we could have multiple pairing multiple uh uh, like
(12:09):
like if A could pair with G instead of just
A and T, then you would say, all right, well,
now we've got a system that goes beyond binary, which,
in theory, if you completely change the way computers work,
would mean that you could dramatically increase parallel processing because
(12:29):
you could designate things. It would almost be like the
cubits of a quantum computer, where you know the basic
explanation as a cubit represents both a zero and a
one and all values in between in superposition of one another,
and that if you have enough cubits, you can perform
(12:50):
a massive parallel processing problem all at the same time
because those that that one group of cubits is behaving
as if it's uh, you know, a huge number of
traditional bits. I think it's important to remember too that
no matter how many bases DNA has, they all belong
(13:14):
to us. Oh I knew it. I knew it. I
was like, oh, I's gonna do an all your base
I belonged to us if someone set us up the bomb,
so well, it could be Actually, if you if you
were trying to if those pairs become corrupted, they will
not work and uh and a cell can die. Actually,
we're getting a lot of this information to from our
(13:35):
our excellent article on how stuff Works dot com about
how DNA works. It gets into a whole lot more detailed, right, Yeah,
if you want to learn more about and and it's
very accessible. It's a very accessible article. So if you're
curious about you know, you've always heard about d N A,
and you've heard about DNA testing, and you know about
chromosomes and genes, but you're not really you know, beyond that,
(13:55):
you're kind of confused. I highly recommend you read how
DNA works at how stuff works dot com. We also
have an article on how DNA computers work, which is
pretty interesting because it's talking about an earlier era of
DNA computers, but recent developments have really brought it brought
to lights some interesting, uh, new technologies and new use
(14:17):
cases for d n A and we'll get into those
in a second. Yeah, It's it's funny that you say that,
because I'm sure that people this is futuristic enough where
people are saying, what are you talking about new developments?
We haven't heard of a d n A computer before?
But yeah, that's that's not really surprising. This is the
kind of thing like like quantum computing, where they've been
working on it for some time, but it's not at
(14:38):
a point where they can really, you know, put something
on a shelf and go look at this. Yeah, yeah,
where people really take notice of it. In general, this
is all stuff that's taking place in universities and research facilities,
and it's you know, most of these machines that are
being made now or or these implementations of using DNA
for information digital information are are really in the prototype stage.
(15:01):
But we're getting the technology that allows us to create
these machines is becoming more and more sophisticated and less expensive,
which of course is key huge any news. And Gordon
Moore explained that back and when he did his his
paper about cramming more components onto an integrated circuit. His
point was not just that technology was advancing to a
(15:24):
point where we could shrink stuff down and fit twice
as many components onto a square inch of silicon as
we could a year ago. It was also that the
manufacturing process was becoming efficient enough and cheap enough where
that made sense. So same sort of thing here. Well,
all right, so we've we've determined that DNA contains information.
(15:45):
It because of its very structure, it can contain a
lot of information in a small volume. Uh. And then
it wasn't until about nine and I remember it was
the it was the fifties, the early fifties when we
started to really understand what DNA was and how how
it formed and how and its structured and everything like that.
Into a man named Leonard Edelman came up with this idea.
(16:09):
He sort of uh introduced the idea of using DNA
to solve math problems. And it was essentially this idea
of coding DNA as if it were a strip of
binary code. And so he took this idea and he
(16:30):
sort of ran with it. He began to formulate an
idea about how to how to create an experiment that
could show that this would work. And it's funny because
it's talking about a DNA computer, but if you read
about the experiment, it sounds more like someone in a
chemistry lab mixing various chemical compositions together and then coming
(16:52):
up with a solution at the end of it. And
that's it turns out that this is a computational solution,
not just a chemical solution. I see what you did there,
Ye little word play there. Yeah, it's a little a
little incredible. So he yeah, he um, he dissolved my objections.
Chris and I have more to say about DNA in
(17:13):
just a moment, but first let's take a quick break
to thank our sponsor. Let me read I'll read the
steps from our article on DNA computers, because I want
to explain how this early, early, early implementation of a
DNA computer, how it how it played out, and it's
(17:37):
kind of amazing. All right. Here are the steps. Number
one strands of DNA represent the seven cities now when
it says seven cities in here, what he was doing
was he was trying to solve something called the traveling
salesman problem, also the directed Hamilton's path problem. The idea
being that you're supposed to find the shortest route between
(17:58):
a group of cities and and it could be any
number really of cities, but you have to only go
through each city one time, um, and it becomes more complex.
This is this is why this is such a fascinating
problem uh as Jonathan pointed out to me right before,
he reminded me that this is something that quantum computing
is fascinated with because this is such a I don't
(18:20):
know what you call it, thorny, a thorny problem. So
it was that problem that they were were that he
wanted to work on, and he chose, I believe seven cities,
he said, that is his benchmark he wanted to do.
And see, this is this is an interesting problem for
uh in computers because think about it, you've got seven cities,
you can only travel through each city once. You have
to find the most efficient pathway to go. Well, the
(18:42):
way a computer would do this, generally speaking, is to
start going through every single possible um permutation of that
trip going from city to city and determining which of
those is the most efficient by the end of it,
by comparing them all, which can take ages and as
as of course, as you add more cities, as you
(19:04):
add complexity to the problem, it creates an exponentially more
difficult problem for the computer to solve. You know, I
don't think it's that unlike trying to crack a password. Yeah,
in the in the you know, other references we've made
to these again, parallel processing. That's another reason why quantum
computers are very scary for anyone who's in cryptography who
(19:25):
wants to create good encryption, because they're talking about using
parallel processing to attack, you know, do a brute force
attack on a password. You can really reduce the amount
of time it would take you to crack a password,
like a password that would probably take you thousands of
years in classic computer time might only take an hour
(19:46):
in using a quantum computer because it's using that parallel approach.
So just remember, quantum computing is the cure for the
common code. Man, what is it with you today? I
don't know. Chris is in a move anyway? All right,
Getting back to getting back to this thing, this set
of steps. All right, So Edelman creates strands of DNA
(20:09):
that represent the seven cities. Uh and so it's these A, T,
and CG pairings and then um, these various sequences represent
each city and possible flight path. He then took the
molecules that these strands of DNA and mixed them in
a test tube, and some of the strands of DNA
(20:32):
stuck together in a chain. Of those strands represented a
potential answer to that question, which of these you know,
which route is the most efficient. Within a few seconds,
all of the possible combinations of DNA strands were created
in the test tube, and then Adelman eliminated the wrong
molecules through chemical reactions, which left behind only the flight
(20:53):
paths that connect all seven cities. So here he was
doing chemistry and looking at molecules by uh and it
was and it was biological chemistry because he was using
organic DNA um and and trying to come up with
the answer that way, which is pretty interesting to me.
(21:15):
I mean, it looks that sounds so different from the
way we think of computing today, where you're using microprocessors
and you know, the user interface looking at screen this
guy is using test tubes and molecules um and he
was actually thinking at the time that this would be
DNA computing is going to be the future because it
packs so much information in such a small form factor
(21:37):
and it's plentiful. Yes, because there's a lot of life
out there, and organic life relies on DNA heavily. There's
some that rely on RNA, but we're not going to
go into that. But anyway, a great amount of organic
life out there has lots and lots of DNA, so
the we've got plenty of materials to work from. Uh.
(22:01):
What's interesting is that since that time where his first
experiments were showing the viability of a DNA computer, our
ability to sequence synthetic DNA has improved to the point
where organic DNA is not really what we care about anymore.
We can synthesize DNA in the lab and just make
(22:22):
it ourselves so we don't have to um harvest it.
As Chris was saying in the pre show, you know,
it would be a totally different world if you realize
that your computer was running out a memory, so you
checked another hamster into your machine so that you could
finish whatever it was you were doing. That was a
particularly gory idea. Well we didn't know, but yeah, I
(22:44):
left out the part about the grinding noises, you know,
and for flying out the back you yeah, and I
thought that was my contribution. Um, yeah, they University of Rochester,
there were some researchers at found ways to use DNA
to create logic gates. Again in the it looks like
(23:08):
um so uh and that's we've touched on on several occasions,
but that those logic gates are basically key to classic computing. Yeah,
this is what uh, this is. This is what allows
the computer to dictate how information moves through it so
that it has any meaning. You know. The logic gates
(23:28):
essentially dictate whether the zero or one that goes into
the gate comes out at zero or one on the
other side or something. Usually it's a pair. If it's
a zero and a one on the other side of
the gate, is that going to be a one or zero?
And it all depends on the type of gate it is. Um.
And of course you you can link a bunch of
gates together to create all sorts of different outcomes depending
(23:51):
upon what the input is. This is all very important
from classical computing. So getting to that step of being
able to build logic gates out of d in a
it was pivotal if you want to be able to
eventually build a true DNA computer. And again this is
you know, you compare the components of a DNA computer
(24:12):
to those of a an inorganic computer. UM. And we have,
as a Jonathan pointed out and Gordon Moore's uh famous
prediction that the transistors would double in number per square
inch of silicon back in the original prediction, UM, you
know every you know over a certain period of time,
(24:34):
which again has changed, you know, year, year and a half,
two years. The thing is, um, we're talking about a
flat piece of silicon. And we've also talked about how
hard drives, the classical hard drive, UM, you know has
so much information on it. It's in a it's in
a flat plane. We've talked about electronic memory and how
(24:56):
you know this information is is getting stored. But we
basically been talking two dimensional and and a long time
ago we talked about processors and how at some point,
due to the limitations of physics like it's at some
point electrons will begin to tunnel through layers of the
material used to create transistors, basically making them ineffective. So
(25:18):
at some point, theoretically the traditional transistor chip is going
to be so full that you cannot fill it anymore
without having serious electrical problems. So they were talking about
going into three D processors. Well, d N a kind
of goes around that problem or is a natural if
you will solution. Hey, for once, that wasn't a pun
(25:40):
intended um, because DNA is volumetric. It isn't it can
fit because of its its natural characteristics. It doesn't have
to be in a two dimensional flat shape. You don't
have to stretch out the helix and stick it on
a piece of silicon or whatever to make it work. Um,
(26:01):
and that gives uh, that gives computing so much more
advantage to move to a DNA based existence, right. Yeah.
The the challenge is building The challenge is building the
equipment that allows you to sequence and decode that information
because you know that's where where that's where the bottleneck is.
(26:23):
Right now, is that the it's not simple, Yeah, we
have to get there. Yeah, But once we get to
a point where we're able to construct the DNA and
lay it out in such a way where we're able
to pack in all that information, and then we have
the companion devices that can decode that and make it
meaningful to a computer. Again, then you're talking about some
(26:48):
huge leaps in storage capacity. One gram of d n
A can store up to four hundred and fifty five
billion gigabytes of data, which is about a hundred billion
DVDs worth of information. Yea, yea. As a matter of fact,
this is the article that sort of uh turned me
(27:10):
onto this idea was something that my friends Kim and
Tim pointed out to me in the in the Guardian,
which really wasn't that long ago August two thousand twelve.
They started talking about how books had been encoded in
dna UM and that that got me to thinking and
to suggesting this to Jonathan as a potential topic because
(27:33):
it's it's fascinating that d n A, something so small,
can hold that much information. Yeah, and it's funny because
the story goes it talks about how Professor George Church
lead this project and he belongs to he well, he teaches,
he teaches at HAVD, but not just Harvard, it's Harvard
(27:55):
Medical School. This is this is one of those weird things,
uh that this this overlaps science, computer science, and uh medicine. Yeah,
so you've got I'm sorry, physical science and medical science.
Let's say that right. No, No, that's that's fine. That's
a computer science and and medical science. It's it's multidisciplinary obviously,
(28:18):
just like nanobiology or nanotechnology is a multidisciplinary approach. So
is this DNA computer or DNA storage idea. We've got
a little bit more about DNA ahead of us, and
before we get to that, let's take another quick break.
(28:42):
So what what Professor Church did was they decided to
take a book that was about five point to seven
megabits of digital space once you converted into digital information,
and to uh encode that as d N A and UM.
(29:05):
They didn't do it just once. They decided to duplicate
it a few times, seven seventy billion times, seventy billion
copies of this book, which, according to an article in
Extreme Tech, prompted them to joke that it made it
the best selling book of all time, yes, and that
(29:27):
it was. The seventy billion copies totaled about forty four
peta bytes of data. UM. So that is slightly larger
than the N A S I have attached at my
network at home. Yeah, yeah, forty four pea bites. That's
an incredible amount of information. It's also quite a bit
smaller than my n A s Yeah. So so when
(29:50):
you think about it, the the promise of d n
A is that with a relatively small amount of DNA
you could store the sum total of all human knowledge
in a very tiny compartment, relatively speaking, a tiny compartment.
(30:11):
And uh, if you're able to use that same sort
of uh of capacity in a processing way as opposed
to just storage storage is great. I mean, that's fantastic.
The the the this project was really showing how using
DNA is great for archival purposes if you want to
(30:33):
store information for longevity's sake. And another point about that
is that this yeah, is that here's here's an issue
that we have with storing information. The way we access
information changes over time, and some of the there there
are multiple problems here. Sometimes the way we store information, uh,
(30:55):
we store it on a medium that can decompose, which
means it as time passes, the likelihood that that data
is intact decreases. So let's say like a book. Okay,
books are susceptible to lots of different environmental factors that
can make them impossible to read. So as time goes by,
(31:19):
a book's ability to preserve the information decreases, particularly depending
upon its environment. Yeah. And and one of the things
that's funny to me about this is, and I'll keep
this short, but it's it's funny to me that in
a way, Uh, the increase in technology, um has only
(31:39):
increased the rate of data rot as some people call it.
Because you think about something like the Rosetta stone and
how long ago that was chiseled, but it's still there
because hey, you know it's stone. If now, if you
left it out in the elements, eventually the the writing
on it will wear away due to the effects of erosion.
But um, that's longer lived than say, paper, which could
(32:01):
be eaten by weevils or could be affected by mold
or mildew or or even water or fire. Um. You
know there there are many things acid in the paper. Um.
But but that would be longer lived than say, um,
a magnetic storage medium, which might may only live a
few decades. Yeah, because you've got with magnetic storage, eventually
(32:23):
that magnetic properties starts to kind of and I have
Dad gets corrupted. Yeah, and I've had CDs and DVDs
that I've burned and a few years ago that are
starting to show signs of deterioration. And I'm thinking all
this futuristic stuff, it's kind of funny. The stuff that's
chiseled in stone is still there well. And on top
of all that, besides the fact that you've got these media,
(32:46):
these media that will that can degrade over time. Um,
magnetic definitely is more susceptible that I would say than
optical storage. But but both can can degree and both
are susceptible to damage. I mean, just about everything is.
But but the other problem is that we move away
(33:07):
from those older forms of media and eventually we get
to a point where nothing we have can read what
we used to use, or if you do have something
that can read it, it's a legacy system. So like
the keeping old computers around simply to read those documents, right,
like like anything that's on an old five and a
quarter inch diskette from the early days of the personal computer,
(33:31):
you know, and I still have something, I would wager
that most people do not have easy access to such
a disk drive. Um, you know, especially if you're just
kind of an average user and you've gone out and
you're like, oh, I want a new laptop. You go again.
If you buy a new laptop today, you might not
even have an optical drive, which means that there you
could come across records of information that you have no
(33:54):
way of accessing because you do not have the tech
capable of accessing it. Well, d n A is a
basic building block of organic life, and so the idea
is that because it's something so basic, we will always
have the ability and assuming that you know, we don't
have some sort of post apocalyptic event, while an apocalyptic
(34:16):
event that then leads to post apocalyptic events, um, then
we should be able to have equipment that can read
this same information. Hey, do you have the instructions on
how to read DNA? Yeah? I saved it on that
magnetic wa now here in Atlanta. Were used to post
apocalyptic events because we've got zombies. Yes, you may have
seen if you've watched the documentary The Walking Dead as
(34:38):
seen on TV. So, um, yeah, the the idea was
that this will d n A does not degrade over time. Well,
it takes a much longer time than something like a
paper book. Right, So since you're not worried about degrading.
I mean when I say it doesn't degrade over time,
we're talking generations here, the undreds of thousands of years
(34:59):
so people. So yes, I wouldn't know eventually it will degrade,
but for the foreseeable future it won't. Uh. It takes
up far less space. We don't have to worry so
much about not being able to access the information anymore
because against the basic building block, we will presumably be
still be interested in DNA in the future. Uh. In fact,
(35:22):
it become increasingly interested as we learn more about how
to uh to tweet DNA to do things like fight
off illnesses and other scientific applications of that knowledge. So
that was kind of the whole point was that it's
great for archival and that reason it's gonna be. It's
it's it's a it's a more permanent solution in multiple ways.
(35:46):
And uh, that's really where the focus is on the
recent articles that we've been reading, although there's still obviously
quite a bit of development on the research and about
building a true DNA computer that would have of an
incredibly small form factor. I mean, you're talking about, uh,
DNA being the size of a couple of atoms, and
(36:08):
this is some small stuff. I mean, we could theoretically
have a DNA computer capable of performing huge calculations and
storing an enormous amount of data in a tiny, tiny
form factor. It would be amazing if we could look
into the future, maybe I don't know, twenty fifty years
(36:29):
something like that, where perhaps we have reached the point
where this technology is viable and reproducible and economic, where
we could see it in applications that actually the average
consumer could access. It wouldn't just be the realm of
the scientific community or the research community. It would also
be within our grasp. Because then can you imagine you
(36:51):
can have a smartphone that could literally contain all the
data that we have ever generated ever since the dawn
of man on your phone. I was waiting for you
to go all the data. No, that was it, just
all of all the data, um well, all the data
we have access to. Um there there. It's astounding to
(37:15):
think of something uh so common that has been with
us for so long being an answer and fairly easy
answer to a lot of these problems. I mean, like
I said, it's not easy to get there, but the
idea is like really just DNA. As it turns out.
You know, they've they've been using synthetic DNA to run
(37:36):
these experiments, and there are some drawbacks, one of which
is it can't be rewritten. That is true. So once
you write that data, it's that's another reason why people
are talking about for archival purposes. Once you write the data,
that's it. Now. Granted, you're talking about a construct that's
so small that you could keep doing that indefinitely and
(37:58):
not have to worry about taking up too much space.
But that's just the way they're thinking of it right now. Right.
But but you know you can't. You can't always think
that way because someday that will catch up to you.
Apparently that might be when we're actually saying, hey, hey,
we finally got a plan on how to get off
this rock because the Sun's gonna swallow us up in
(38:20):
another million years. That that would never happen. By the way,
don't don't write into me and explain to me why
that would be ridiculous. I understand. I was just using
that as a an example. Well, and and the other
thing is, um, you know, and yes, I realized that
this is you know that you could destroy DNA, but um,
(38:41):
thinking about that the sensitive information can't be erased. Then
you would need to keep up with your Let's say
you had a DNA drive like you have a flash
drive to carry back and forth with you, uh, and
it gets lost and it had I don't know importance
and sitive documents related to national security or um you know,
(39:04):
the secret um uh copy of your unpublished book, and
somebody else runs across it and makes billions of dollars
off of it because they found it. You can't you
can't remotely wipe that information. I don't know how you
would do that without destroying without physically destroying the material.
So it's that's sort of a a minor drawback, really,
(39:28):
but it's something it's it's something very different from the
media that we typically talk about. So clearly in that case,
you would be talking about, all right, well, now we've
got this incredible archival ability. Now we have to figure
out a way of securing it. Oh well, don't see that. Well,
and this brings me to my brilliant science fiction idea
which I I said in the pre show. I said,
(39:49):
if if someone steals this, I will find you. See.
That was my That was my like shout out to
your no, no, I'm sharing it because if someone out
there makes the us, I want to cut. So here's
the sci fi idea. Guys. You have a character who
is just an ordinary guy or girl, you know, someone
who is going through life and they've got the same
(40:12):
sort of challenges and problems and joys and despairs as
all the rest of us. But then suddenly they noticed
that they're being watched and people are closing in on them,
and they don't know why because they're just a normal person,
and so they're trying to get away, and it turns
out they find out that they themselves are a synthetic
life form. They were built in a lab from the
(40:34):
ground up, and in fact, their DNA contains this incredibly
important information encoded into this person's very being is a
secret message of such import that various forces are closing
in on them, determined to get hold of this person,
lop off a finger and figure out what the heck
is going on, And so the character has to go
(40:55):
through this incredible series of adventures in order to figure out.
It's kind of a journey of self discovery as well
as protection, and there's a whole like hero arc and
the credits are great and Bruce Willis Stars and I
want to cut I've got data under my skin, are
in it and through it. So, guys, yeah that was
(41:17):
I'm sure someone's gonna write in and say, yeah, that
was a great story when so and so wrote it
years ago. I want to read it. Yeah, yeah, I
I have no illusions that someone has not already come
up with that idea. But if they haven't, and then
you guys think that's a great idea and you want
to go out and make it. Remember, I want to
credit and some money or at least a sandwich. Come on,
(41:39):
writer's gotta eat all right, assassinating stuff though, it's it's
the kind of thing that I would never have thought
to do, so, I mean, I'm blown away by that. Yeah,
it's a it's a pretty fascinating subject. And like we said,
there's that we have some great articles on how stuff.
We actually can go and check those out and read
up on DNA and DNA computers and you know, like
I said, they are the articles on the Guardian as
(42:01):
well as other places that are talking about this storage
medium and it blows my mind. Hey, guys, hope you
enjoyed that classic episode of tech Stuff Always a joy
to revisit the old episodes we did in the past.
It's also interesting that I decided to throw this one
in there, because obviously a lot has happened since two
(42:23):
thousand twelve, so I may have to do a full
update episode about d n A computers in the near future.
If you're interested in hearing such a thing, let me know.
The email address for the show is tech Stuff at
how stuff works dot com, or jump on over to
the website that's text stuff podcast dot com. That's where
you're gonna find an archive to all of our previous episodes,
(42:45):
as well as our presence on social media, and you
also find a link to our online store, where every
purchase you make goes to help the show and we
greatly appreciate it, and I'll talk to you again really soon.
Text Stuff is a production of I Heart Radio's How
Stuff Works. For more podcasts from I heart Radio, visit
(43:07):
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listen to your favorite shows.
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