VIII' Nanobio

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Nanoscale Science and Technology
VIII. Nano-bio M. Meyyappan NASA Ames Research
Center Moffett Field, CA 94035 email
mmeyyappan_at_mail.arc.nasa.gov web
http//www.ipt.arc.nasa.gov
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Outline
DNA - The Basics DNA Conductance DNA
Computing DNA Sequencing using Nanopores
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DNA The Basics
DNA is the carrier of genetic information in
all living species The double-helix structure
consists of two strands of DNA wound around each
other - Each strand has a long polymer
backbone built from repeating sugar molecules
and phosphate groups - Each sugar group is
attached to one of four bases Guanine
(G) Cytosine (C) Adenine (A) Thymine
(T) Order or sequence of this genetic alphabet
along the molecule constitutes the genetic
code In double-stranded DNA, hydrogen bonds
between the bases couple the two strands
together - Chemical coupling is such
that - The base pairs look like the
rungs of a helical ladder
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DNA - Some More Basics
DNA Polymerase - Given a strand of DNA, under
appropriate conditions, DNA polymerase
produces a complementary strand in which every
C is replaced by G, every G by a C, every A
by a T and every T by an A - The polymerase
enables DNA to reproduce Ligases bind molecules
together. DNA ligase will take two strands of
DNA in proximity and covalently bond them into a
single strand - The cell uses DNA ligase to
repair any breaks in DNA Nucleases cut nucleic
acid Gel eletrophoresis separating DNA
strands by length - A solution of DNA molecules
is placed on one end of a slab of gel and an
electric field is applied - Negatively
charged DNA molecules move toward the
anode - Their mobility is dependent on length
shorter ones move faster DNA synthesis - Routi
ne, commercial, fairly inexpensive
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Gel Electrophoresis
Fabrication of the system - Construction of a
high sensitivity diode detector on a silicon
substrate - Channel is filled with 1 agarose
gel Operation - DNA sample is loaded into
the inlet reservoir - Electric field
applied along the channel for driving and
separating the DNA molecule - With this
setup, separation by 500 µm basepairs ? 5
minutes, 4.6 mm channel
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(Artificial) Gel Electrophoresis
Dense array of 100 nm wide Si3N4 posts (spaced
100 nm) on polysilicon E-beam lithography
followed by selective etching This sieve
instead of the randomly arranged long-chain
polymers in a gel DNA piece lengths of 43 and
7.2 kbase had a factor of 2 difference in
velocity for a 18 V potential difference over
15 mm.
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DNA Chips
DNA chips have patterns with many short pieces
of single-strand DNA, each with a different
sequence of bases - The target DNA, extracted
from a cell, is first labeled with a
fluorescent marker - The target DNA will
bind only to those fragments of the probe DNA
that have exactly the right genetic
code Optical read-outs are used widely
now Electronic read-outs are not as common.
They will exploit different electrochemical
responses of SS- and ds- DNAs attaching to a
surface The gene chips are produced using
microfabrication techniques
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Integrated Devices for DNA Analysis
Genetic diagnostics - Thermal cycling for DNA
amplification (PCR) - Mixing with
reagents - Labeling (using dyes) - Fragmentati
on Integrated systems, doing all functions, are
becoming popular - On flexible plastics or
silicon MEM technology - Complete computer
control, internal values, external pumps
Single chip system, 3 cm long - Injectors,
mixers, heating chamber, separation channels with
electrodes - Detection using diode detectors
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DNA Conductance
Courtesy M. Anantram
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DNA Conductance

• Double helix a backbone base pairs
• Building blocks are the base pairs
• A, T, C G
• Example 10 base pairs per turn, distance of 3.4
  Angstroms between base pairs.
• Arbitrary sequences possible
• A challenge for nanotechnology is controlled /
  reproducible growth. DNA is an example with some
  success. However, there are many copies in a
  solution!
• 2D and 3D structures with DNA base pairs as a
  building block have been demonstrated
• Lithography? Not yet.

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DNA Conductance
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DNA Conductivity Experiments
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DNA Conductivity Experiments
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Counter-ions

• Is conduction through the base pair or backbone?
  - Basepair
• When DNA is dried, where are the counter ions?
• Crystalline / non crystalline?
• Counter ions significantly modify the energy
  levels of the base pairs
• Counter-ion species is also important
• Resistance increases with the length of the DNA
  sample (exponential within the context of simple
  models)

Counter-ions
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DNA Computing
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DNA Computing
Pioneering work by Leonard M. Adleman of U. of
Southern California To build a computer, it is
necessary to have (1) a method to store
information (2) a few simple operations to act
on that information Early Turing machines
(1930s) stored information as sequences of
letters on tape and manipulated that
information with simple instructions in the
finite control Modern electronic computers
store information as sequences of zeroes and ones
in memory and manipulate this information using
the operations available on the processor
chip DNA is a great way to store information.
Enzymes such as polymerases and ligases operate
on this information. This is the basis for DNA
computing. Adleman solved the Hamitonian Path
problem using this idea. The following
material is based on his work.
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Hamitonian Path Problem
Consider the map of cities (called graph) The
arrows (directed edges) represent nonstop flights
between the cities (vertices) Determine if a
sequence of connecting flights (path) exists that
starts in Atlanta (the start vertex) and ends
in Detroit (the end vertex), while passing
through each of the remaining cities - Boston
Chicago - only once. Hamiltonian
Path Problem The case shown here is trivial a
Hamiltonian path does exist Atlanta, Boston,
Chicago, Detroit If the start city was Detroit
and the end city was Atlanta, then, no
Hamiltonian Path exists
DETROIT
CHICAGO
BOSTON
ATLANTA
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Hamiltonian Path Problem
Given a graph with directed edges, and a
specified start vertex and an end
vertex, - There is a Hamiltonian Path if and
only if - There is a path that starts on the
start vertex and ends on a end vertex and
passes through each remaining vertex only
once Hamiltonian path problem is to decide for
any given graph with any number of vertices and
with start and end vertices specified, if a
Hamiltonian path exists or not No efficient
algorithm exists - Even with best algorithms
and computers, some graphs with about 100
vertices for which solving Hamiltonian path
problem would take hundreds of years!
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An Algorithm for Hamiltonian Path Problem
Given a graph with N vertices (1) Generate a
set of random paths through the graph (2) For
each path in the set (a) Check if that path
starts on the start vertex and ends with
the end vertex if not, remove that path from the
set (b) Check if that path passes through
exactly N vertices if not, remove that path
from the set (c) For each vertex, check if
that path passes through that vertex if
not, remove that path from the set (3) If the
set is not empty, there is a Hamiltonian path if
the set is empty, then there is no Hamiltonian
path Generation of paths should be random and
the resulting set should be large enough
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Solution for 4-City Problem
Each city assigned an arbitrary DNA
sequence - Think of the first 4 letters as
first name - The last 4 letters as last
name DNA flight number is the combination of
the last name of originating city and first
name of ending city Complementary city names
consists of replacements C ? G G ? C A ? T T
? A The actual Hamiltonian Path (Atlanta ?
Boston ? Chicago ? Detroit) is given by
GCAGTCGGACTGGGCTATGTCCGA ? a DNA sequence of
length 24 How do you actually do
this?
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Solution Implementation
Synthesize the complementary DNA city names and
DNA flight numbers Take a sample (1014
molecules) in a test tube add water, salt,
ligase The solution to the problem is in
the tube How do you distinguish it from
all other molecules? (1) PCR with primers of
the last name of the start city (GCAG) and
complement of the first name of end city
(GGCT) (2) Gel electrophoresis to identify the
right length (24) (3) Affinity separation process
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Potential of DNA Computing
Extremely dense information storage - 1 gm of
DNA (when dried, occupies 1 cm3) equivalent to 1
trillion CDs Enormous parallelism Extraordinar
y energy efficiency - 1 J is good for 2 x 1019
ligation operations - 2nd Law of Thermodynamics
dictates a theoretical maximum of 34 x 1019
(irreversible) operations per J at room
temperature - Current computers are for less
efficient (109 operations/J) Error correcting
codes are needed - Biological operations are
imperfect - Information coded in DNA decays at
a finite rate Application - Cryptography - C
omputer-aided design - Factoring large
numbers
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DNA Sequencing Using Nanopores
Goal Very rapid gene sequencing
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DNA Sequencing with Nanopores The Concept
(2nm diameter)
a-hemolysin pore
(very first, natural pore)
Axial View
Side View
G. Church, D.
Branton
, J.
Golovchenko
, Harvard
D.
Deamer
, UC Santa Cruz
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Nanopore Ion Conductance
When there is no DNA translocation, there is a
background ionic current When DNA goes
through the pore, there is a drop in the
background signal The goal is to correlate the
extent and duration of the drop in the signal to
the individual nucleotides
Open nanopore
DNA translocation event
Source Viktor Stolc
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Potential Advantages of Solid-State vs. Protein
Nanopores
After a decade of using protein pores, efforts
are underway in many groups to develop synthetic
pores (such as in Si3N4) Interaction with
single nuclotides - 20 nucleotides in aHL
simultaneously Slower translocation - 1-5 ms
/nucleotide in aHL Resistance to extreme
conditions - Temperature -
pH - Voltage ? - hemolysin is toxic and hard
to work with
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Nanopore Dimensions Determined by DNA Structure
Source Viktor Stolc
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DNA Sequencing Experiments

• Voltage-clamp amplifier designed to measure pA
  level currents
• Fast (up to 1GHz) data acquisition
• Software for automatic blocking event detection
  and recording

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Status of Nanopore based DNA Sequencing
C
C
G
G
G
G
A
A