Lecture: DNA nanostructures
Goals: show strategies and examples of bottom-up assembly of
DNA-based nanostructures
Construction with “Smart Bricks”
The bricks that make a nano-object can already have the information necessary to selfassemble bottom-up if placed in the right conditions, without any other external
intervention by some ‘large scale’ agent.
Static structures based on the DNA linear helix
These are structures made by design. They exploit the Watson-Crick pairing to
make a doube-helix from separate parts.
For example, there are techniques that can attach new objects to DNA, allowing
to assemble objects with funcions that are not normally assembled.
DNA serves as the coupling signal.
“Asymmetrical Protein-DNA dumbbells” organic synthesis of
modfied oligonucleotides that can be derivatized with
proteins
Tomkins et al. ChemBioChem 2001
Christof Niemeyer: the
preparation of DNA-protein
hybrids and the creation of
objects.
Exploiting the tetravalent
Streptavidin, it is possible to
attach more oligonucleotide
molecules to the same
bridging streptavidin.
Different geometries can be
obtained (a small ring or
branched structures). As
another example, streptavidin
can be immobilized on a long
RNA via a complementary
probing oligonucleotide
bound to the streptavidin.
Building on a surface
Surface localization is a facile method to imobilize a nanoobject in a precise
location in space. You can then study the object, or use it.
The presence of the surface leads to a
serious change in the behavior of
molecules, as these are not free to move
around any more and they have a wall
next to them (excluded volume effecs).
The reduced dimensionality also
increases the effective molecular
concentrations.
Two examples of the
use of DNA to make
protein layers or to
localize proteins
specificallyin order to
make a proten
microarray.
DNA detection thanks to the formation of
large adducts beginning from colloidal
nanoparticles (Chad Mirkin and Paul
Alivisatos)
The color of colloidal particles depends on their size
(other parameters left untouched) due to plasmon
resonance. Solutions of 10-20 nm gold nanoparticles
are red, while larger aggregates are bluish.
This provides with a strategy towards a colorimetric
assay of the presence of a sequence of DNA.
Scanometric detection of DNA hybridization (Chad Mirkin)
According to the same strategy, colloidal gold nanoparticles can be tethered to a probe sequence
on the surface only if a DNA sequence complementary both to the surface bound probe and to the
nanoparticle-bound probe is present. A ‘sandwich’ is obtained. If nanoparticles of different size are
used, a colorimetric response can be obtained also for signals such as sequence polymorphism
and they can be localized on only one spot on the surface.
Afer binding, the gold
nanoparticles can be developed
through Ag+ reduction: Silver
nanopaticles then fuse and lead
to a visible stain on the surface.
A common and cheap flatbed
scanner can be used to read the
signal of only a few analyte
molecules recognized by the
DNA microarray.
DNA Computing: DNA vs. Silicon
(http://arstechnica.com/reviews/2q00/dna/dna-2.html)
Transistor-based computers typically handle operations in a sequential
manner. Of course there are multi-processor computers, and modern CPUs
incorporate some parallel processing, but in general, in the basic von Neumann
architecture computer, instructions are handled sequentially. Typically, increasing
performance of silicon computing means faster clock cycles (and larger data
paths), where the emphasis is on the speed of the CPU and not on the size of the
memory.
For DNA computing, though, the power comes from the memory capacity and
parallel processing. For example, let's look at the read and write rate of DNA. In
bacteria, DNA can be replicated at a rate of about 500 base pairs a second. But
this is only 1000 bits/sec, which is a snail's pace when compared to the data
throughput of an average hard drive. But you can allow many copies of the
replication enzymes to work on DNA in parallel. First of all, the replication enzymes
can start on the second replicated strand of DNA even before they're finished
copying the first one. So already the data rate jumps to 2000 bits/sec. But look
what happens after each replication is finished - the number of DNA strands
increases exponentially (2^n after n iterations). With each additional strand, the
data rate increases by 1000 bits/sec. So after 10 iterations, the DNA is being
replicated at a rate of about 1Mbit/sec; after 30 iterations it increases to 1000
Gbits/sec. This is beyond the sustained data rates of the fastest hard drives.
The Adleman experiment
Suppose that I live in LA, and need to visit four cities: Houston, Chicago, Miami, and
NY, with NY being my final destination. The airline I’m taking has a specific set of
connecting flights that restrict which routes I can take (i.e. there is a flight from L.A.
to Chicago, but no flight from Miami to Chicago). What should my itinerary be if I
want to visit each city only once?
Starting from L.A. you need to fly to Chicago, Dallas, Miami and then to N.Y.
Any other choice of cities will force you to miss a destination, visit a city twice, or not
make it to N.Y.
For six, seven, or even eight cities, the problem is still manageable. However, as
the number of cities increases, the problem quickly gets out of hand. Assuming a
random distribution of connecting routes, the number of itineraries you need to
check increases exponentially. So you will need a computer ...or perhaps DNA.
Adleman first generated all the possible itineraries and then selected the correct
itinerary. This is the advantage of DNA. It’s small and there are combinatorial
techniques that can quickly generate many different data strings. Since the
enzymes work on many DNA molecules at once, the selection process is massively
parallel.
Specifically, the method based on Adleman’s experiment would be as follows:
1
Generate all possible routes.
2
Select itineraries that start with the proper city and end with the
final city.
3
Select itineraries with the correct number of cities.
4
Select itineraries that contain each city only once.
All of the above steps can be accomplished with standard molecular biology
techniques.
Part I: Generate all possible routes
Strategy: Encode city names in short DNA sequences. Encode itineraries by
connecting the city sequences for which routes exist.
DNA can simply be treated as a string of data. For example, each city can be
represented by a "word" of six bases:
Los Angeles: GCTACG
Chicago: CTAGTA
Dallas: TCGTAC
Miami: CTACGG
New York: ATGCCG
The entire itinerary can be encoded by simply stringing together these DNA
sequences that represent specific cities. For example, the route from L.A -> Chicago > Dallas -> Miami -> New York would simply be
GCTACGCTAGTATCGTACCTACGGATGCCG, or equivalently it could be
represented in double stranded form with its complement sequence.
Itineraries can then be produced from the city encodings by linking them together in
proper order. For example, you can encode the routes between cities by
encoding the compliment of the second half (last three letters) of the departure city
and the first half (first three letters) of the arrival city. For example the route
between Miami (CTACGG) and NY (ATGCCG) can be made by taking the second
half of the coding for Miami (CGG) and the first half of the coding for NY (ATG).
This gives CGGATG. By taking the complement of this you get, GCCTAC, which
not only uniquely represents the route from Miami to NY, but will connect the
DNA representing Miami and NY by hybridizing itself to the second half of the
code representing Miami (...CGG) and the first half of the code representing
NY (ATG...). For example:
Random itineraries can be made by mixing city encodings with the route encodings.
Finally, the DNA strands can be connected together by an enzyme called
ligase. What we are left with are strands of DNA representing itineraries with a
random number of cities and random set of routes. For example:
We can be confident that we have all possible combinations including the correct
one by using an excess of DNA encodings, say 1013 copies of each city and each
route between cities.
Part II: Select itineraries that start and end with the correct cities
Strategy: Selectively copy and amplify only the section of the DNA that starts with LA
and ends with NY by using the Polymerase Chain Reaction.
After Part I, we now have a test tube full of various lengths of DNA that encode
possible routes between cities. What we want are routes that start with LA and end
with NY. To accomplish this we can use a technique called Polymerase Chain
Reaction (PCR), which allows you to produce many copies of a specific sequence of
DNA. So to selectively amplify the itineraries that start and stop with our cities of
interest, we use primers that are complimentary to LA and NY. What we end up with
after PCR is a test tube full of double stranded DNA of various lengths, encoding
itineraries that start with LA and end with NY.
Part III: Select itineraries that contain the correct number of cities.
Strategy: Sort the DNA by length and select the DNA whose length corresponds to
5 cities.
Our test tube is now filled with DNA encoded itineraries that start with LA and end
with NY, where the number of cities in between LA and NY varies. We now want to
select those itineraries that are five cities long. To accomplish this we use Gel
Electrophoresis
We can then simply cut out the band of interest to isolate DNA of a specific length.
Since we known that each city is encoded with 6 base pairs of DNA, knowing the
length of the itinerary gives us the number of cities. In this case we would isolate the
DNA that was 30 base pairs long (5 cities times 6 base pairs).
Part IV: Select itineraries that have a complete set of cities
Strategy: Successively filter the DNA molecules by city, one city at a time by affinity
purification: the compliment of the sequence in question to a substrate like a
magnetic bead.
The beads are then mixed with
the DNA. DNA, which contains
the sequence you're after then
hybridizes with the complement
sequence on the beads. These
beads can then be retrieved
and the DNA isolated.
So we now affinity purify fives times, using a different city complement for each run. If
an itinerary is missing a city, then it will not be "fished out" during one of the runs and
will be removed from the candidate pool. What we are left with are the are itineraries
that start in LA, visit each city once, and end in NY. This is exactly what we are
looking for. If the answer exists we would retrieve it at this step.
Reading out the answer: simply sequence the DNA strands.
However, since we already have the sequence of the city encodings we can use an alternate method called graduated PCR.
Here we do a series of PCR amplifications using the primer corresponding to L.A., with a different primer for each city in
succession. By measuring the various lengths of DNA for each PCR product we can piece together the final sequence of cities
in our itinerary. For example, we know that the DNA itinerary starts with LA and is 30 base pairs long, so if the PCR product
for the LA and Dallas primers was 24 base pairs long, you know Dallas is the fourth city in the itinerary (24 divided by 6).
Finally, if we were careful in our DNA manipulations the only DNA left in our test tube should be DNA itinerary encoding LA,
Chicago, Miami, Dallas, and NY. So if the succession of primers used is LA & Chicago, LA & Miami, LA & Dallas, and LA &
NY, then we would get PCR products with lengths 12, 18, 24, and 30 base pairs.
Caveats
Adleman's experiment solved a seven city problem, but there are two major
shortcomings preventing a large scaling up of his computation. The complexity of
the traveling salesman problem simply doesn’t disappear when applying a different
method of solution - it still increases exponentially. For Adleman’s method, what
scales exponentially is not the computing time, but rather the amount of DNA: more
than a few people have pointed out that using his method to solve a 200 city HP
problem would take an amount of DNA that weighed more than the earth. Another
factor that places limits on his method is the error rate for each operation. Since
these operations are not deterministic but stochastically driven (we are doing
chemistry here), each step contains statistical errors, limiting the number of
iterations you can do successively before the probability of producing an error
becomes greater than producing the correct result. For example an error rate of 1%
is fine for 10 iterations, giving less than 10% error, but after 100 iterations this error
grows to 63%.
CONCLUSION:
So will DNA ever be used to solve a traveling salesman problem with a higher
number of cities than can be done with traditional computers? Well, considering that
the record is a whopping 13,509 cities, it certainly will not be done with the procedure
described above. It took this group only three months, using three Digital AlphaServer
4100s (a total of 12 processors) and a cluster of 32 Pentium-II PCs. The solution was
possible not because of brute force computing power, but because they used some
very efficient branching rules. This first demonstration of DNA computing used a
rather unsophisticated algorithm, but as the formalism of DNA computing becomes
refined, new algorithms perhaps will one day allow DNA to overtake conventional
computation and set a new record.
On the side of the "hardware" (or should I say "wetware"), improvements in
biotechnology are happening at a rate similar to the advances made in the
semiconductor industry. For instance, look at sequencing; what once took a
graduate student 5 years to do for a Ph.D thesis takes Celera just one day. With the
amount of government funded research dollars flowing into genetic-related R&D and
with the large potential payoffs from the lucrative pharmaceutical and medical-related
markets, this isn't surprising. Just look at the number of advances in DNA-related
technology that happened in the last five years: "DNA chips," the Human Genome
Project is producing rapid innovations in sequencing technology. The future of DNA
manipulation is speed, automation, and miniaturization.
Static structures based on branched forms of DNA
“DNA is every designer’s dream, being at the same time the
blueprint of the structure and the structure itself” [N.C. Seeman]
Structural DNA nanotechnology (as Ned Seeman puts it)
“A key motivation for constructing objects from DNA is to generate rational means for constructing
periodic matter. At least three properties are necessary for the components of systems where this
is possible: (a) The predictable specificity of intermolecular interactions between components; (b)
the local structural predictability of intermolecular products; and (c) the structural rigidity of the
components”
Making things with the blocked
Holliday junction
Making nonnatural objects
with nantural
materials
Church of S. Francis - Evora, Portugal
The Holliday junction
Why building with DNA?
“The nucleic-acid ‘system’ that operates in terrestrial
life is optimized (through evolution) chemistry
incarnate. Why not use it ... to allow human beings to
sculpt something new, perhaps beautiful, perhaps
useful, certainly unnatural.” Roald Hoffmann, su
American Scientist, 1994
DNA is perfect as a nanotech brick: 2 nm diameter, 3.4 nm pitch, 50 nm persistence
length, a fully nanoscale object .
Sticky ends cohesion is probably the best example of
programmable molecular recognition: you can have a
lot of different possible sticky ends (4N for N-long
ends) and the cohesion product is the normal double
helix (structural predictability). Solid phase
oligonucleotide synthesis makes molecular
programming attainable. Molecular interaction can be
programmed to be specific.
A general route towards
crystallization of
molecules?
WHY NUCLEIC ACIDS? Can you achieve the same using antigens and antibodies,
for instance? You could probably get a similar affinity, but the relative orientation of
partners would have to be defined for each partner. This is why nucleic acids are
quite unique, they provide a readily available programmable system for organizing
molecular assembly.
From linear to branched DNA: the Holliday juncion
as a nanoconstruction brick
An intermediate in recombination
DNA Duplex, most of the nucleic
acids is in linear form
Nadrian C. Seeman
J1 JUNCTION
J1 = Holliday junction with a
modified sequence that prevents
the branch-point migration that is
fundamental in biological
recombination
A STABLE STRUCTURE
Important for:
1- studying the structure of the
Holliday junction
2- a brick for structural DNA
nanotechnology
(Seeman, N. C. (1982) J. Theor. Biol. 99, 237-247)
Designing a parallelogram
Physical
ligation
Informatics
ligation
Nadrian C. Seeman also developed sequence selection software
PAGE characterization of a parallelogram
6
•10% non-denaturing gel
• 4°C
4
3
2
1
M
434
1.1+2+3+4+5+6
2.1+2+3+4+5
3.1+2+3+4
4.1+2+3
5.1+5
6.4
M. pBR322 marker
6
5
267
234
213
192
184
123
104
89
80
3
5
64
57
51
4
1
2
Do the 6 oligos assemble in one object?
M 1 2
32P
3
4 5
6
labelling
•10% native PAGE, RT
•Lanes 1-6: only one oligo is
labelled in each
HOT ATP + strand
T4 DNA kinasi
HOT (5’) strand + ADP
•Lane M: HOT marker – 25 bp
ladder
375-350
A bidimenional array
1D – 2D by changing sticky-ends
(Mao e Seeman, JACS 1999)
AFM of the 2D array of
parallelograms
Design and preparation of
supramolecular constructs
Double-crossover structures (introduced in
1993): the design and realization of rigid tiles for
making DNA mosaics.
These structures, inspired from meiosis
intermediates, are made by two parallel double
helices rigidly joined thanks to the exchange of
strands. Some strands belong to one helix at the
beginning and then switch helix.
There are different types of DX as a function of the
geometry and topology of the strand exchange.
Some of the DX possible on paper are not stable,
though.
By equipin DX with sticky ends, they can be
assembled into 1D or 2D polymeric structures.
Similarly, 3 double helices can be paired,
making 2 reciprocal exchanges between
each couple of helices. These are named
triple crossover (TX), and are bigger than
DX.
Other possible variations: DX+J, where an
hairpin sticks out from the center of a DX
and it can be made perpendicular to the DX
plane.
A scheme for the TX
Periodic structures with controlled spacing can be made by assembling DX tiles
through sticky ends. They can also extend out of the plane.
Tiles are assembled in a non-computational manner to make simple and repetitive
structures with a small number of different tiles. Alternatively, a larger variety of tiles
can be assembled in an ‘algorithmic’ manner thus making computation while they
assemble. The computational rules are defined in the base sequence of the sticky
ends..
This is an intrinsically more efficient method to do
computation than the one proposed by Adleman:
by proper coding of the sticky ends, only the
assembly that follows the coded rules can take
place (and not a myriad of products). Once tiles
are formed and assembled, they are ligated.
Ligation generates long oligonucleotides that
contain the solution to the problem (that you read
by sequencing the oligo).
Very thin arrays of constant thickness
These TX linear arrangements can be
functionalized at desired locations and serve
as spacing templates for proteins or
nanoparticles. Such molecular wire is
mechanically very rigid.
You can achieve strings of gold
beads by using streptavidincoated gold nanoparticles.
(Li et al. JACS 2003)
Making tubes with DNA tiles
The group of Reif
made the assembly of
TX tiles with a diedral
angle different from
180°: a curvature in
the tile plane is
produced ad
eventally a DNA tube
will emerge. (Reif,
PNAS 2004)
An alternative way to make tubes (N. Seeman)
Seeman could design and
make a large hollow tile of
DNA made by a helix
bundle. This can be
assembled along its axis
through stiky ends to
make a tube. (Seeman,
2005 NanoLetters).
Ribbonds or 2D lattices of DNA with the 4-by-4 junction
The base tile is made of 4 J1 junctions joined with a
central strand that participates in each junction. 5
oligos make the trick.
Sticky ends are located at the ends of the chains, so
self-assembly is possible.
Giunzioni J1
Depending on the way to join the tiles,
the assembly results in a ribbon/tubeor
in a flat 2D lattice: one joining strategy
sums the small deformation of the tile
and the assembly plane curves in a tube
(A), while the alternative assembly
cancels the deformations out and makes
a large flat 2D array of tiles (B)
nastri
Array 2D
A
B
(Yan et al. Science 2003)
Proteins can be specificaly located on the arrays (you could make nanocircuits)
Biotins are bound at the center of the
oligonucleotide that participates in all 4 J1.
Streptavidin is added in solution so i can locate
of the biotins.
The DNA ribbons can be metallized to make
conductive nanowires with a diameter of about
40 nm and the length of a few micrometers.
One 4-by-4 silver-coated ribbon laid on
top of microelectrodes in an attempt to
measure its electrical properties.
A self-assembling octahedron made with a 1.7 kb DNA molecule
A 1669 nt single-stranded DNA molecule self-assembles together with 5
40 n long oligonucleotides to make an octahedron. The threedimensional object can be assembled with a piece of Dna that can be
replicated with a DNA polymerase! It could host a 14 nm sphere; from the
opening of its faces, a 8 nm sphere could enter.
DX
1
(Shih et al. Nature 2004)
2PX
PX
A recent examle shows the degree of complexity
that can be achieved:
A molecular fabric made through the self-assembly of crossovers on a
natural DNA
Paul Rothemund, Nature 16 March 2006 (vol 440, pages 297-302 )
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According to this approach, a DNA molecule can be sewn together to make
any desired form through a certain number of synthetic oligonucleotides.
Results are astonishing: DNA
origami can reproduce any
desired shape in the nanoscale!
100 nm
scale 1:2x1014
Rothemund, Nature, vol 440, pages 297-302
1 µm
1 µm
100 nm
The first DNA motor: Bernard Yurke e Andrew Turberfield (2000)
A motor made of oligonucleotides that reorganize as a
response to the introduction of an oligonucleotide in
solution. It is the opening and closing of a molecular
tweezer. The movement is visualized thanks to FRET.
The strategy to extract a component from the
structure is worth noticing and has been re-used many
times since. A protruding single-stranded tail is
exploited in order to nucleate a new, more stable
double helix that then strips off one oligo from the
nanostructure (recycling the motor). This takes place
at room temperature, without the neeed of
disassembling anything else.
Main disadvantages of the most common DNA
nanodevices
1. Production of waste DNA
• Degradation of the performance over time
2. Need of bi-macromolecular events
• Concentration-dependent performance
• Performance depends on bulky molecules
• Opening and closing signals through
expensive molecules
Design of a triplex-based DNA motor
Marco Brucale et al.
Design / 2
• the generated waste(salt) does not interfere with the
functioning of the motor up to 1M or more.
Static characterizations
CD spectrum at different pH.
Absorbance at 260nm at different
pH.
Electrophoretic mobility for
a construct with or without
the TFO
Dynamic characterizations / 1
E
Q
E
Q
Fluorescnece emission of A+B* alternating the pH between 5
and 9
• The emission intensity depends exclusively on the separation between
donor and acceptor
• No degradation of the performance with the successive additions
Dynamic characterizations
At high dilution
• Same performance!
/2
Putting the device on a surface
95% EtOH
5% H2O pH 4.5
16h
b)
glass
O
Oligo B*
O
Si
SS(L)
Si
SS(L)
O
O
glass
pH 5.0 buffer
16h
O
MPTS gas phase
R1SS(L)-Oligo A
pH 9.0 buffer
16h
2h 150°C
0.05 torr
glass
glass
a)
MPTS
O
O
O
O
Si
SH
Dynamic Single-Molecular DNA structures
Single molecule characterization by scanning confocal fluorescence microscopy on
the surface
Single molecule fluorescence studies confirm that the structure can assume both
conformations when immobilized on a surface.
Take-home message:
with DNA you can design and make nanostructures with the desired
shape and mechanical properties.
They can be static or dynamic, can be made of DNA only or decorated
with a large variety of other functional nano-objects.
Seeman e coll.: a molecular machine
based on the B → Z transition.
A DNA segment of particular sequence can
have a B to Z transition. If this is located
between two DX (which carry fluorophors)
then their motion can be studied.
Disadvantages: it is difficult to cycle the motor
back and forth.
A molecular machine based on a DNA quadruplex
[ W. Tan et al, 2002]
A DNA biped that walks along a sidewalk
Using the same strategy that Yurke and turberfield employed to
strip off oligos from a structure, Ned Seeman implemented a
walker that can move controllably along a track, by sticking and
releasing its feet from posts. Each motion requires the addition of
an oligonucleotide. The waste can be removed by proper
oligonucleotide functionalization.
[animazione]
(Sherman e Seeman, NanoLetters 2004)
An autonomous DNA motor: it runs as long as there is fuel
An autonomous molecular machine: a DNAzyme cuts the RNA oligonucleotide
that keeps a structure extended after it binds to it. After the cut, the fragments
separated and the structure is ready to host another copy of the same RNA oligo,
effectively ‘breathing’ as long as there are oligos that can bind and get cut.
[ C. Mao et al, 2004]
Interesting videos:
DNA structural nanotech
Hao Yan
Paul Rothemund