Quantitative ‘omics
EuroSyStem
Edinburgh
November, 2009
Ed Southern
Outline
• What is ‘omics: where did it come from?
• OGT’s role in EuroSyStem
– Single cell expression analysis
– Our system and what it will do
• What will it do for you?
Ed Southern
Ed Southern
H. A. Krebs:
The citric acid cycle.
Biochemical Journal, London, 1940, 34: 460-463.
Ed Southern
Ed Southern
The conceptual basis of metabolic flux –
the beginnings of Systems Biology
• From Kacser and Burns (1973)
“One bit of theory is usually represented as metabolic maps. These maps
give information on the structure of the system : they tell us about transformations,
syntheses and degradations and they represent the molecular
anatomy. They tell us „what goes‟ but not „how much‟.”
I think that is „Omics‟
Ed Southern
The conceptual basis of metabolic flux –
the beginnings of Systems Biology
• From Kacser and Burns (1973)
“One bit of theory is usually represented as metabolic maps. These maps
give information on the structure of the system : they tell us about transformations,
syntheses and degradations and they represent the molecular
anatomy. They tell us „what goes‟ but not „how much‟.”
I think that is „Omics‟
• From Kacser (1957b)
“The problem is therefore the investigation of systems, i.e. components related
or organised in a specific way. The properties of a system are in fact more than
(or different from) the sum of the properties of its components, a fact often overlooked
in zealous attempts to demonstrate additivity of certain phenomonena.
It is with these systemic properties that we shall be mainly concerned…”
I think that is „Systems Biology‟
Ed Southern
KACSER, H. & BURNS, J. A. (1973).
The control of flux. Symp. Soc. Exp. Biol. 27, 65-104.
Ed Southern
Control of Flux
“An important conclusion was that the
„pacemaker‟ (or similar term) has
little meaning (except in extreme
circumstances) and should be replaced
by the assignment of a quantity, the Flux
Control Coefficient, to each of
the enzymes. There will, in general, be a
distribution of such values of
coefficients in a pathway rather than two
extreme classes.”
Ed Southern
Control of Flux
• Note the use of
genetics
• Neurospora chosen
because it allows for
manipulation of gene
copy number
Ed Southern
Lessons from Krebs and Kacser
• Biological processes may involve a lot of
sequential steps
• Flux depends on properties of the whole
system
• Small changes in individual steps can have
large effects on the system
• Therefore – need sensitive accurate
measurement
Ed Southern
What is new about ‘omics?
• Much more data
–
–
–
–
Proteomics – O’Farrell gels, MS
Genomics – DNA sequences
Transcriptomics – microarrays
Metabonomics – GC-MS
• Data sometimes the starting point
– i.e. no prior knowledge of functions and
connections
• More sophisticated models
Ed Southern
What we need for Systems Biology
• Integration of different ‘omics
– Models – biological systems and computer
– Data collection
Ed Southern
Why focus on Nucleic Acids
• Easy to sequence
• Powerful genetic tools
– E.g. Knockouts etc gave direct link between
gene and phenotype
• Powerful analytical tools
– Hybridisation provides gene specific reagents
Ed Southern
OGT’s focus on Nucleic Acids
• HTS on microarrays (John Anson)
• Single cell expression analysis (ES)
• mRNA single molecule counts (Dietrich
Lueerssen)
Ed Southern
Why single cells?
• Essence of differentiation
is formation of new cell types
from individual cells
• We need to see
molecules in individual cells,
not the ensemble
Ed Southern
Conventional methods analyse
mixtures
• Sample is mixture of
cells
• E.g. tissue,
• Non-synchronised
population
Ed Southern
OGT’s “CellScribe” – a new platform for
gene expression analysis
• Array of 1-100 large patches of gene specific oligonucleotides
• Cells spread over array surface
• Signal detected from cells expressing the gene
Ed Southern
A Simple Protocol – Step 1
Slide coupled with
oligo probe
Hot-Block
Ed Southern
A Simple Protocol – Step 2
•Cells can be stained with antibody
•Slide scanned to locate (identify) cells
Cells fixed onto slide
Slide coupled with
oligo probe
Hot-Block
Ed Southern
A Simple Protocol – Step 3
Gel pad soaked
in lysis buffer
Cells fixed onto slide
Slide coupled with
oligo probe
Hot-Block
Ed Southern
A Simple Protocol – Step 3
Glass slide “lid”
Gel pad soaked
in lysis buffer
Cells fixed onto slide
Slide coupled with
oligo probe
Hot-Block
Ed Southern
Cell lysis, RNA capture
• Lysis complete
in <20 sec
• Gel left in place
1 hr for hybridisation
Ed Southern
A Simple Protocol – Step 3
This, and a couple of washes, completes the “Sample preparation”
Glass slide “lid”
Gel pad
in lysis buffer
Cells fixed onto slide
Slide coupled with
oligo probe
Hot-Block
Ed Southern
A Simple Protocol – Step 4 labelling
RNA
• Carried out
under coverslip
• We are now at about 2 hr
from start
dNTP
Only one gene per cell
Ed Southern
Multiplexing
1. Hybridise
mRNA to lawn of
oligodT
2. Perform probe
extension by RT
3. Remove RNA by
RNAse H or
denaturation
5. Strip
6. Repeat steps 4 and 5
Ed Southern
Lucille
Mathers
4. Hybridise genespecific detection
probes
Reading at single molecule resolution
• Conventional scanners
– ~2 m resolution
– Intensity value
– Detection limit 100-1000
molecules per cell
• High resolution scanner
– ~130nm
– Count of mRNA molecules
– Detection limit 0 molecules
(in theory!)
Ed Southern
Dietrich
Lueerssen
A range of expression levels
18S rRNA probe
dT30 probe
Arbp probe
Up to a max. 1000 copies/cell
for a single mRNA species
Av. 3 X 105 mRNAs/cell
Av. 2 X 106 18S rRNAs/cell
Ed Southern
Natalie
Milner
Eight heat shock genes at basal expression level.
transcription factor
oligodT
hsf1
hspa4
hspa1a
HSP70
HSP70
hspa8
HSP27
hspb3
HSP72
HSP27
hspb1
HSP10
HSP90
hspca
hspe1
Ed Southern
Natalie
Milner
Analysis of total mRNA – Cells lysed on oligo dT
oligo patch
outer region of a single cell
Region of the array
approx. 250um X 250um
showing several cells
Single cell with 10um
grid overlaid
Intensity plot through single
molecules
Ed Southern
Natalie
Milner
The Result – a population description
Cell population 1
Cell population 2
22 24 23 23 22 24 22 23 24 25
3
4
5
3
1
2
4
1
2
3
21 23 22 24 23 24 15 18 19 17
3
1
5
3
5
3
2
5
4
5
130 140151159 2
1
2
3
5
3
25 26 23 21 22 20 21 20 21 22
Mean expression level = 22
Mean expression level = 22
Both populations give the same value
using conventional arrays or qPCR
Ed Southern
The Result – a population description
Cell population 1
Cell population 2
22 24 23 23 22 24 22 23 24 25
3
4
5
3
1
2
4
1
2
3
21 23 22 24 23 24 15 18 19 17
3
1
5
3
5
3
2
5
4
5
130 140151159 2
1
2
3
5
3
25 26 23 21 22 20 21 20 21 22
Mean expression level = 22
The CellScribe gives a distribution
9
Number of cells
Mean expression level = 22
8
7
6
5
4
3
2
1
0
140
1
6
11
16
21
26
Gene expression level
Ed Southern
145
145
150
Connections
• When Gene1 is
high
3
4
5
3
1
2
4
1
2
3
3
1
5
3
5
3
2
5
4
5
1
2
3
5
3
130 140 151 159
Ed Southern
2
Connections
• When Gene1 is
high
• Is Gene2 also
high
3
4
5
3
1
2
4
1
2
3
3
1
5
3
5
3
2
5
4
5
1
2
3
5
3
130 140 151 159
Ed Southern
2
Connections
• When Gene1 is
high
• Is Gene2 also
high
• And are these
cells expressing
an Antigen
3
4
5
3
1
2
4
1
2
3
3
1
5
3
5
3
2
5
4
5
1
2
3
5
3
130 140 151 159
Ed Southern
2
Limitations of CellScribe
•
•
•
•
Suspension cells – e.g. blood, cell cultures
One or few gene per cell
No time resolution – a snapshot at one time point
Little spatial resolution
• Some technical issues to resolve
Ed Southern
What questions can we address?
• Can we find rare cells in a large population?
– E.g. Minimal residual disease
• Can we classify cancer cells?
– E.g. Diffuse Large B-cell Lymphoma subtypes1
• Can we discover connections in systems that other
methods cannot reach?
– E.g. qPCR:
• single cells?
• difficult to multiplex,
Ed Southern
Control of Flux
Ed Southern
Control of Flux
• Changes in high levels have small effects
Ed Southern
Control of Flux
• Changes in high levels have small effects
• System is sensitive to changes in
components at low concentrations
Ed Southern
Control of Flux
• Changes in high levels have small effects
• System is sensitive to changes in components at
low concentrations
• The most important concentration is often zero
Ed Southern
Summary
• CellScribe potential
– Single cell gene expression analysis
• Linked to antigen expression
– Many cells
• Up to tens of thousands
– Simple protocol
– Absolute counting of molecules
• High sensitivity and accuracy
Ed Southern
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Molecular biology
George Easow
Amanda Hopes
Simon Hughes
Sandra Lam
Lucille Mathers
Natalie Milner
Hanny Musa
Kaajal Reeves
Andrew Rogers
Nicole Sparkes
Graham Speight
• Engineering, optics,
computing
• Steve Latham
• Dietrich Lueerssen
• Daniele Malleo
Ed Southern
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Molecular biology
George Easow
Amanda Hopes
Simon Hughes
Sandra Lam
Lucille Mathers
Natalie Milner
Hanny Musa
Kaajal Reeves
Andrew Rogers
Nicole Sparkes
Graham Speight
• Engineering, optics,
computing
• Steve Latham
• Dietrich Lueerssen
• Daniele Malleo
Ed Southern
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Molecular biology
George Easow
Amanda Hopes
Simon Hughes
Sandra Lam
Lucille Mathers
Natalie Milner
Hanny Musa
Kaajal Reeves
Andrew Rogers
Nicole Sparkes
Graham Speight
• Engineering, optics,
computing
• Steve Latham
• Dietrich Lueerssen
• Daniele Malleo
• Commercial and
managing collaborations
• Paul Fallen
Ed Southern
Results: Comparing MCA to qPCR of basal
gene expression levels
qPCR
MCA
hsf1
hsf1
Expression level
hspe1
hspe1
hspa1a
hspa1a
Cycle number
Basal gene expression levels of three heat shock proteins
Strictly Confidential
Ed Southern
O'Farrell PH. High resolution two-dimensional electrophoresis of proteins.
J Biol Chem. 1975 May 25;250(10):4007-21.
Ed Southern