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A Systems Approach to
Measuring the Binding
Energy Landscapes of
Transcription Factors
By
Sebastian J. Maerkl
Stephen R. Quake
Background
Measuring affinities was a difficult task:


The traditional method cannot be used to
measure interactions with small affinities.
Results were often “1 or 0”.
The new method provides solution by
combining the microarray and microfluidic
technology
Background
How is a specific protein
produced inside a cell?
DNA
RNA Polymerase
RNA
Transcription Factor
Where
should I
bind to?
Transcription
Factor
RNA
Polymerase
DNA
Transcription Factor
A protein that mediates the binding of RNA
polymerase and the initiation of transcription.
(Wiki)
Without transcription factor, RNA
synthesis cannot occur, thus
protein production.
A transcription factor can
actually bind to a number of
different initialization zone of
gene—how does it know
where to go for a specific
RNA/protein synthesis?
Revisit
With the traditional methods, we were unable to
produce… This
With the ability to quantify the absolute affinities of interactions,
we are given the ability to produce a detailed graph such as the
one above.
This provides a lot more useful information.
What can we achieve?
Predict in vivo function for 2 yeast TFs.
Make a comprehensive test of the base
additivity assumption.
Test the hypothesis that the base region
alone determines binding specificity of
bHLH TFs.
MITOMI
The new method, mechanically induced
trapping of molecular interactions,
provides solution by fusing the microarray
and microfluidic technology together.
MITOMI
1. The DNA Chamber, connecting
with the channels which will be
filled with other components.
2. The valves controlling flow of the
channels.
3. The “button” which creates a
circular area when pressure is
applied; able to stretch to the
bottom of the slide.
The enclosed cell
will be used for TF
binding energy
topography to
measure/quantify
the affinities.
Process
3. The button is
released, leaving
the protected area
ready to be
connected to
antibodies.
1. Button was
pressed to
protect the
area.
2. The surface other
than the protected
area is filled by
biotinylated bovine
serum albumin.
Process Continued
5. The button is
again pressed to
trap the DNA bound
on the bottom of the
slides.
ouch
4. The channel is filled
with DNA, transcription
factors, as well as
antibodies.
No pocket; zero
dead volume.
The Results
The results showed
that optimal binding
sequence is
CACGTG. Similar
forms also proven to
be relatively effective,
such as CATGTG,
CTCGTG, CAGGTG.
The structures
were found in lowaffinity range,
which couldn’t be
detected with
traditional methods
before.
Additivity Assumption
States that each base inside a codon
behaves independently, without having to
work with its neighbor bases to perform a
task.
That is to say, if you substitute bases
around, you will get results which shall be
different from the original, but will not be
completely off.
Additivity Assumption Ctd…
2.5
Substituting 1 base seems to be perfectly fine as the data in blue
boxes lies perfectly on the prediction line. Substitution of 2 bases
seems to be ok, but then about half of the data points lie
distinctively far away from the line.
Additivity Assumption Ctd…
So…is the data for or against the argument
that additivity assumption is true? We don’t
know!
PWM fails to predict properly for everything
above 2.5 kcal/mol, because of non-specific
interactions.
Basic Region is Enough?
First looking at Pho4p and Cbf1p, which
seem to have the same motifs with
CACGTG.
By adding flanking bases at the beginning
or end of the sequence.
Pho4p  CCCACGTGGG
Cbf1p  [A/G]GTCACGTGAC[T/C]
Basic Region is Enough.
The reason they
couldn’t do it before:
could not detect lowaffinities.
By cloning the basic
regions of Pho4p and
Cbflp into the MAX
isoform B backbone,
it was shown that the
basic region alone is
enough for
recognition.
Comparing with other Methods
Trying to list the
number of genes
regulated by Pho4p
and Cbf1p.
Pho4p was
assumed to work
on Phosphate
metabolism.
Cbf1p on
Chromosome
Segregation and
Methionine
Metabolism.
Comparing with other Methods
No
Funding
-The data seems to be fairly consistent for Pho4p, as for all three
different methods, there’s a considerable large region of overlap.
-Data seems to be way off for Cbf1p.
-Where did Microarray go??
Comparing with other Methods
Does this mean the MITOMI approach is
not practical  answer is no.
The data collected through different
approach can be used as reference to
each other for possible final confidential
result.
Critique
Clear and distinctive graphical
representations.
Number of experiments provided here
The MITOMI method is clearly presented
with details (no hiding techi details)
Shadow area for Additivity Assumption
Some more reference needed, e.g. for ITT
ChIP-Chip
ChIP-Chip
ChIP-on-chip, also known as genomewide location analysis, is a technique for
isolation and identification of the DNA
sequences occupied by specific DNA
binding proteins in cells. These binding
sites may indicate functions of various
transcriptional regulators and help identify
their target genes during animal
development and disease progression.