Case story: Analysis of the Cell Cycle · 2006. 1. 2. · Prediction of cell cycle regulated...

DNA micorarray analysis 27612, January 2nd 2006Ulrik de Lichtenberg

Technical University of Denmark

Ulrik de LichtenbergCenter for Biological Sequence Analysis


DNA microarray analysis, January 2nd 2006

Case story:

Analysis of the Cell Cycle


Technical University of DenmarkOutline

Experimental studies of cell cycle regulation

• DNA microarrays & cell culture synchronization

• Finding periodically expressed genes

My Research Projects

• Project 1: Comparing computational methods

• Project 2: Finding weakly expressed genes

• Project 3: Regulation of protein complexes

Introduction

• Cell division and cell cycle regulation


Technical University of DenmarkCell division

How does one cell become many?


Technical University of DenmarkThe importance of research in cell division

164

720

6404

Leland Hartwell Tim Hunt Sir Paul Nurse

The 2001 Nobel Prize in

Physiology or Medicine

“for their discoveries of key

regulators of the cell cycle“

Cell division research is important for:

Cancer, cell factories, biomass increase,

cell differentiation, stem cells, signalling,

apoptosis, developmental disorders,

fertility, etc.

Cell division is one of the most

fundametal processes of all

living things and therefore of

enormous importance for our

understanding of life itself.


Technical University of DenmarkThe cell cycle


Technical University of DenmarkA complex biological system


Technical University of DenmarkDifferent levels of control in the cell

The activity of a protein depends on– regulation of its transcription (by activator/inhibitors)

– its mRNA stability

– the efficiency of translation (from mRNA to protein)

– stability of the mature protein

– the subcellular localization of the protein

– regulation of the protein function by binding ofactivator and inhibitors

– regulation of the protein function by post-translational modification (e.g. phosphorylation)

– targeted degradation of the protein (e.g. byubiquitination)


Technical University of DenmarkThe Just-in-time principle

• Some products you use all the

time, while others are only

needed once in a while

• People tend to buy or order

things right before they need

them…


Technical University of DenmarkJust-in-time synthesis in the cell

Simon et al., Cell, 2001

S phase S phase

Periodically expressed genes

Cell cycle regulated genes










Introduction



Technical University of DenmarkDNA microarray technology


Technical University of DenmarkBut cells grow out of synchrony?!


Technical University of DenmarkArrest-and-release synchronization

• Temperature sensitive mutants – unable to pass a

certain point in the cell cycle at high temperatures

• Alpha factor – all cells arrest in the same stage

until a factor is supplied to the culture



Synchronized

cell cultureMicroarrays Expression Profile

Microarray analysis of cell cycle regulation

1. Take samples from a synchronized cell culture

2. Hybridize each sample to a microarray chip

3. Normalize to make the chips comparable

4. String the data-points together to a profile

5. Look for genes whose expression is periodic










Introduction



Technical University of DenmarkTime-series versus comparative studies

• Most microarray experiments compare measurementsfrom condition A with condition B to find those genesthat are differentially expressed– the typical analysis is a statistical test, e.g. t-test

• Time-series experiments are usually aimed at studyinghow gene expression changes over time (i.e. identifyinggenes that show a specific pattern of expression)– you can’t make a t-test, instead you have to look for some

pattern!



Synchronized


Quiz

“You have 6000 profiles with about 20 time-points in each”

“How do you find out which of them are

regulated during the cell cycle and in

which phase they are expressed?”

?


Technical University of DenmarkMeasuring Periodicity

Fourier-scoring: extracting the ”signal” at the

interdivision frequency.


Technical University of DenmarkFourier score distribution


Technical University of DenmarkThe thresholding problem

Yeast Human



WARNING!

The next slide may be the mostimportant slide of your career…

…so pay attention!



Specificity

Sensitivity

Sensitivity versus Specificity

find little, of which

most is rightfind a lot, of which

most is right

find little, of which

most is wrongfind a lot, of which

most is wrong

Sensitivity = how many of the edible mushrooms do you accept

Specificity = how many of the mushrooms you accept are edible

edible

poisonous


Technical University of DenmarkThe thresholding problem

• Every threshold corresponds to a sensitivity and a specificity

• There is (almost always) a trade-off between the two










Introduction




Synchronized


Microarray analysis of cell cycle regulation

Budding yeast

Cho et al., 1998

Spellman et al., 1998

de Lichtenberg et al., 2005

Fission yeast

Rustici et al., 2004

Peng et al., 2004

Oliva et al., 2005

Human cells

Cho et al., 2001

Whitfield et al., 2002

Plant cells

Menges et al., 2003

Periodicity Analysis

Computational methods

Spellman et al., 1998

Zhao et al., 2001

Johansson et al, 2003

Wichert et al., 2004

Luan & Li, 2004

Lu et al., 2004

Liu et al., 2004

de Lichtenberg et al., 2005

Ahdesmaki et al., 2005


Technical University of DenmarkBenchmark of computational methods

Expression Profile Periodicity Analysis

Motivation?

• The overlap between different

computational methods is

remarkably poor when they are

applied to the same data.

• Although, most analyses have

concluded the periodically

expressed subset of the yeast

genome to comprise about 300 to

800 genes, nearly 1800 different

genes have been proposed in total


Technical University of DenmarkBenchmarking of computational methods

Computational Methods

• Cho et al., 1998– visual inspection

• Spellman et al., 1998– fourier scoring and correlation

• Zhao et al., 2001– single pulse model

• Johansson et al., 2003– partial least squares regression

• Luan & Li, 2004– cubic spline fitting

• Lu et al., 2004– Bayesian, mixture model

• de Lichtenberg et al., 2004/2005– permutation based statistics

Benchmark sets

B1 113 known periodic genes from smallscale experiments

B2 352 genes bound by at least one ofnine known cell cycle transcriptionfactors, excluding those in set B1

B3 518 genes annotated as “cell cycle andDNA processing” in MIPS, excluding“meiosis” and those in set B1

How do we benchmark?

We assume that the benchmark sets B1-B3

are enriched in cell cycle regulated genes.

We then benchmarks the ability of each

computational method to retrieve these

genes from the data (rank them high)


Technical University of DenmarkComparison of different methods

--- random

Cho et al.

Spellman et al.

Zhao et al.

Johansson et al.

Luan & Li

Lu et al.

de Lichtenberg et al.


Technical University of DenmarkWords of wisdom…

“Before you criticize someone, you

should walk a mile in their shoes.

That way when you criticize them,

you’ll be a mile away and you’ll

have their shoes.”

-- Anonymous


Technical University of DenmarkWhy are some methods better?

“is the gene significantly regulated?”– p(regulation): compare actual standard deviation to randomly

sampled background distribution

“is the expression pattern periodic?”– p(periodicity): compare the actual fourier signal to distribution

made by randomly shuffling the data point within each profile

Combined score with penalty function– Combi score: Combination of p-values for regulation and

periodicity, with penalty terms that require both componentsto be significant.


Technical University of DenmarkRegulation versus periodicity

--- random

regulation alone

periodicity alone

combined

combined + re-norm

combined + consistency


Technical University of DenmarkBetter methods give better overlap

• Different experimental conditions,such as cell culture synchronizationmethods

• Handling of samples, amplification,hybridization, etc.

• DNA microarray data are noisy andreplicates rarely overlap completely.

• Signal-to-noise ratio low for weaklyexpressed –and regulated genes

Why not perfect overlap?










Introduction




Periodic

genes

Non-periodic

genes

??Grey zone

area {Train

Model

Predicting new cell cycle regulated genes

periodic

proteins

non-periodic

proteins


Technical University of DenmarkPrediction of cell cycle regulated proteins

Protein required for mating1.50.96MID2YLR332W

cell-cycle regulation protein, may be involved in the correct timing of cell separation after cytokinesisSK8.70.96EGT2YNL327W

cold- and heat-shock induced protein of the Srp1p/Tip1p family of serine-alanine-rich proteinsCSZK5.90.96TIP1YBR067C

Protein of unknown function2.40.96YGR161C

TIP1-relatedS2.60.96TIR3YIL011W

Protein of unknown functionS5.40.96YLR194C

Factor-Induced Gene 2: expression is induced by the mating pheromones, a and alpha factor3.40.97FIG2YCR089W

Protein of unknown function2.10.97YMR317W

Mid-Two Like 11.80.97MTL1YGR023W

anchorage subunit of a-agglutininSK6.50.97AGA1YNR044W

Protein of unknown function2.50.97YOR220W

Protein of unknown functionSZ4.10.97GAS5YOL030W

EndochitinaseCSK9.30.97CTS1YLR286C

Protein of unknown functionC3.00.97YOL155C

Delayed Anaerobic Gene1.30.97DAN4YJR151C

Protein of unknown function1.00.98TIR4YOR009W

Protein of unknown function5.30.98YDL038C

Pathogen Related in Sc, contains homology to the plant PR-1 class of pathogen related proteins.CS5.50.98PRY3YJL078C

cell wall beta-glucan assembly1.70.98KRE1YNL322C

Protein of unknown functionC2.80.98YIL169C

ANNscore



Protein required for mating1.50.96MID2YLR332W

cell-cycle regulation protein, may be involved in the correct timing of cell separation after cytokinesisSK8.70.96EGT2YNL327W

cold- and heat-shock induced protein of the Srp1p/Tip1p family of serine-alanine-rich proteinsCSZK5.90.96TIP1YBR067C

Protein of unknown function2.40.96YGR161C

TIP1-relatedS2.60.96TIR3YIL011W

Protein of unknown functionS5.40.96YLR194C

Factor-Induced Gene 2: expression is induced by the mating pheromones, a and alpha factor3.40.97FIG2YCR089W

Protein of unknown function2.10.97YMR317W

Mid-Two Like 11.80.97MTL1YGR023W

anchorage subunit of a-agglutininSK6.50.97AGA1YNR044W

Protein of unknown function2.50.97YOR220W

Protein of unknown functionSZ4.10.97GAS5YOL030W

EndochitinaseCSK9.30.97CTS1YLR286C

Protein of unknown functionC3.00.97YOL155C

Delayed Anaerobic Gene1.30.97DAN4YJR151C

Protein of unknown function1.00.98TIR4YOR009W

Protein of unknown function5.30.98YDL038C

Pathogen Related in Sc, contains homology to the plant PR-1 class of pathogen related proteins.CS5.50.98PRY3YJL078C

cell wall beta-glucan assembly1.70.98KRE1YNL322C

Protein of unknown functionC2.80.98YIL169C

ANNscore

Prediction of cell cycle regulated proteins


Technical University of DenmarkNo bias towards strongly expressed genes

Estimated gene expression level


Technical University of DenmarkExperimental validation of predictions


Technical University of DenmarkExperimental setup

• Synchronization with temperature

sensitive mutant strain (Cdc15-2)

• Fermentation in chemostat

• Sampling every 20 min

• Custom made probes (OligoWiz)

• Custom made microarrays (febit ag)

• New computational method


Technical University of DenmarkThe results


Technical University of DenmarkExamples of new discoveries


Technical University of DenmarkNew genes are weakly expressed

Predicted genes Confirmed genesde Lichtenberg et al., Yeast, 2005de Lichtenberg et al., JMB, 2003










Introduction



Technical University of DenmarkModeling through data integration


Technical University of DenmarkNetworks – from topology to dynamics

Jeong, Nature, 2001

Dynamics Interactions

Dynamic

Models

Ideker & Lauffenburger, TRENDS in Biotechnology, 2003


Technical University of DenmarkExtracting a cell cycle interaction network

include non-periodic

proteins that are

strongly connected

to periodic proteins.

Data sourcesNode selection

list of periodically

expressed proteins

with peak timing

Interactions

score and filter by

network topology and

subcellular localization

cell cycle gene

expression data

protein-protein

interaction data

extract cell cycle

network


Technical University of DenmarkVisualizing the network

G1

S

M

G2

“Interacting proteins

are usually expressed

close in time”

Colorrepresents

transcriptional

timing


Technical University of DenmarkCoverage of interaction space

Most stable complexes were

captured, at least partially, in

the network. Still, no interactions

could be found for 2/3 of the

dynamic proteins.

Why?

• Some may be missed subunits

of complexes already in the

network

• Some may not participate in

protein-protein interactions

• But, the majority probably

participate in transient

interactions that are not so

well captured by current

interaction assays


Technical University of DenmarkNetworks as discovery tools

Obervation: The network

places 30+ uncharacterized

proteins in a temporal

interaction context.

The network thus generates

detailed hypothesis about

their function.

Obervation: The network

contains entire novel

modules and complexes.


Technical University of DenmarkStatic “scaffold proteins” play a major role

Observation: Static (scaffold)

proteins comprise about a third

of the network and participate

in interactions throughout the

entire cycle



• Expression based time mapping corresponds closely

to the timing of complex assembly and activity.

• Hypothesis: We propose a just-in-time assembly

mechanism where the expression of the dynamic

subunits of each complex control the timing of final

assembly, and thereby the complex function.

Just-in-time complex assembly


Technical University of DenmarkPhosphorylation of dynamic proteins

By detailed analysis of the network we discover that

this regulation specifically affects the dynamic

proteins, but not the static proteins.

An experimentally determined* set of 332 Cdc28

targets constitute:

6% of all yeast proteins

8% of the static proteins

27% of the dynamic proteins

This over-representation is significant at P < 10-4

The yeast cyclin-dependent kinase, Cdc28/Cdk1,

regulates of a large number of cell cycle proteins by

phosphorylation.

* Ubersax et al., Nature,2003


Technical University of DenmarkDegradation signals in dynamic proteins

PEST degradation signals are

found in the sequence of many

proteins known to be selectively

targeted for degradation.

We discover that PEST signals

are significantly more frequent

among the dynamic proteins

and among the Cdc28-targets.

Transcriptional

regulationTargeted

degradation

Post-translational

regulation

Dynamic

proteins



Are the special properties of dynamic proteins conserved?

“What’s the chance of finding the overrepresentation of PEST

regions observed among the dynamic proteins by random?”

Budding yeast (S. cerevisiae): P < 10-2

Fission yeast (S. pombe): P < 10-2

Human (HeLa cells): P < 10-7

Transcriptional

regulationTargeted

degradation

Post-translational

regulation

Dynamic

proteins


Technical University of DenmarkAcknowledgments

Center for Biological Sequence Analysis, Denmark

Søren Brunak

Thomas Skøt Jensen

Anders Fausbøll

Rasmus Wernersson

Henrik Bjørn Nielsen

The rest of CBS!

EMBL Biocomputing, Heidelberg, Germany

Lars Juhl Jensen

Peer Bork

Sean Hooper


Technical University of DenmarkFurther reading…

http://www.cbs.dtu.dk/cellcycle

All data and supplementary information available at:

Comparison of Computational Methods for the

Identification of Cell Cycle Regulated GenesUlrik de Lichtenberg, Lars Juhl Jensen, Anders Fausbøll, Thomas Skøt

Jensen, Peer Bork and Søren Brunak

Bioinformatics, 21(7), 1164-1171, 2005

New weakly expressed cell cycle regulated genes in yeastUlrik de Lichtenberg, Rasmus Wernersson, Thomas Skøt Jensen, Henrik

Bjørn Nielsen, Peer Schmidt, Flemming Bryde Hansen, Steen Knudsen

and Søren Brunak

Yeast, 22(15), 1191-2017, 2005

Dynamic Complex Formation During the Yeast Cell CycleUlrik de Lichtenberg, Lars Juhl Jensen, Søren Brunak and Peer Bork

Science, 307 (5710), 724-727, 2005

Case story: Analysis of the Cell Cycle · 2006. 1. 2. · Prediction of cell cycle regulated...

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