Computational models of the transcriptional machinery and spatial patterning of the early mammalian embryo

Computational models of the transcriptional machinery and spatial patterning of the early mammalian embryo

Systems Biology of Stem Cells, Irvine, CA May 24-25, 2010

Carsten Peterson

Computational Biology & Biological Physics Lund University, Sweden

http://cbbp.thep.lu.se/

Lund Stem Cell Center, Lund University, Sweden

Cdx2 Oct4 Sox2

Nanog Gata-6

Overview

Transcriptional machinery



Switch properties

An embryonic ground state Reprogramming

 Trophectoderm/endoderm extensions

Overview

Spatial patterning

 Geometrical constraints in the embryo

 Mechanics and biochemistry Trophectoderm formation

Endoderm formation

Transcriptional machinery



Switch properties

An embryonic ground state Reprogramming

 Trophectoderm/endoderm extensions

Early “single gene” experiments identified OCT4, SOX2 and NANOG as key players Niwa (2000); Chambers (2003)

Followed by ChIP-chip experiments for their binding sites and microarray profiling for further insights

Boyer (2005); Loh (2006); Ivanova (2006)

A core structure emerges:

Core transcriptional network of embryonic stem cells

Early “single gene” experiments identified OCT4, SOX2 and NANOG as key players

Followed by ChIP-chip experiments for their binding sites and microarray profiling for further insights

A core structure emerges:

Core transcriptional network of embryonic stem cells

Nature of interactions

explored by the dynamics

ON OFF OFF

ON Switch ON =>

OFF =>

Early “single gene” experiments identified OCT4, SOX2 and NANOG as key players

Followed by ChIP-chip experiments for their binding sites and microarray profiling for further insights

A core structure emerges:

Core transcriptional network of embryonic stem cells

ON OFF OFF

ON Switch ON =>

OFF =>

Simple model considerations:

Everyone is an activator

Deterministic rate equations

Solve iteratively the Shea-Ackers rate equations:

Concentrations:

[A] = External signal [O] = OCT4

[S] = SOX2 [N] = NANOG

[OS] = OCT4/SOX2 complex

OS Binds first

Then recruits NANOG

……..

…….. Similar structure

……..

Turning the switch “ON”

ON OFF

NANOG

Signal A₊

OCT4-SOX2

ON OFF

Wnt + ..

How does the Oct4-Sox2-Nanog system respond to external activating signals, e.g. Wnt?

The switch is very robust against parameter variations

Turning the switch “OFF”

OCT4-SOX2

NANOG

Signal B_-

ON

ON

OFF

OFF

p53 How does the Oct4-Sox2-Nanog system respond to

external repressive signals, e.g. p53?

The switch is very robust against parameter variations

An ESC “ground state”

Signal A₊

By over-expressing NANOG one obtains an irreversible switch.

Once ON, the stem cell can continue to self-renew in the absence of external

factors – a “ground state” Ying (2008)

Reprogramming

Expressing Oct4/Sox2 when OFF turns the switch ON

- Mechanism: Oct4 recruits Nanog to turn on the switch - Only expressing Nanog is not sufficient

The other known reprogramming factors Klf4 and c-Myc

are not part of our simplified network, but …

Takahashi, 2006

Lineage specification

Rossant (2006)

Lineage specification – the extensions

OCT4

OCT4

TARGETTARGET

Global expression profiling of Oct4 manipulated ES cells combined with (ChIP) assays

=>

Genes show both activation and repression depending on Oct4 expression levels

Matoba (2006)

OCT4 Trophectoderm Endoderm

OCT4

ES

T E

Lineage specification - trophectoderm

GCNF

Trophectoderm extension

OCT4–SOX2

NANOG CDX2

OCT4 SOX2

Lineage specification -endoderm

GCNF

Endoderm extension

OCT4–SOX2

NANOG

OCT4 SOX2

GATA6

Lineage specification – closing a loop

GCNF

Endoderm extension

OCT4–SOX2

NANOG

OCT4 SOX2

GATA6

Trophectoderm

CDX2

extension

GCNF

Endoderm extension

OCT4–SOX2

NANOG

OCT4 SOX2

GATA6

Trophectoderm

CDX2

extension

Suppress OCT4 -Trophectoderm lineage

GATA6, CDX2, GCNF

OCT4, SOX2, NANOG

SN

Suppress OCT4 -Trophectoderm lineage

GCNF

Endoderm extension

OCT4–SOX2

NANOG

OCT4 SOX2

GATA6

Trophectoderm

CDX2

extension

Overexpress OCT4 - endoderm lineage

Connecting two worlds

Gene expression meets cell division and mobility

1. Trophectoderm formation Oct4/Cdx2

2. Endoderm formation

Nanog/Gata-6

t<E0.5 n=1 t=E1.0 n=2 t=E1.5 n=4 t=E2.0 n=8

t=E2.5 n=8 t=E3.5 n=32

Laboratoire de Biologie de la Reproduction; Lausanne

The early embryonic development

Live imaging data emerging with geometric and some genetic info

Rossant (2009); Zernicka-Goetz (2005)

The early embryonic development

Develop a computational modeling framework for simulating the patterning of the embryo

Mechanics meets biochemistry

Mechanistic model of embryogenesis

Blastomers are incompressible ellipsoids

Elastic response is lumped into principal axes Measure deformation in cell overlap

Elastic, adhesion and drag forces Total force = F

+ F

+ F

Overdamped mechanics (no acceleration)

• F

• F

Attracts nearby cells in proportion to overlap area

Tangential drag force proportional to relative velocities and overlap area

• F

Mechanistic model of embryogenesis

Blastomers are incompressible ellipsoids

Elastic response is lumped into principal axes Measure deformation in cell overlap

Elastic, adhesion and drag forces Total force = F

+ F

+ F

Overdamped mechanics (no acceleration)

• F

• F

Attracts nearby cells in proportion to overlap area

Tangential drag force proportional to relative velocities and overlap area

• F

Cell division

• Cell cycle times sampled from experimental distribution Daughters share parental cell volume

• Selection of division plane is either

- random or directional (with respect to pellucid zone)

• Partition rules for cell content - Equal partition

- Asymmetric partition

Ready to go

Each cell has a set of internal data

- concentration of proteins, cell cycle length, etc.

Different “cell species” can have different division/growth rules, interaction parameters

Neighborhood determined by Voronoi diagram relatio

n

Track cell lineages, protein concentration, elastic energy, etc.

Analyze statistics of different cell lineages - explore hypothesis

Trophectoderm formation

Current conceptional models

Position-based model (inside-outside):

Inner or outer position of a cell dictates its Cdx2 level Polarity-based model:

Outer cells, which are known to be polarized, polarize Cdx2 as well Asymmetric divisions for cells with high/low Cdx2 content

Model the alternatives with mechanics and a simplified biochemical network with Cdx2 and Oct4 only

Trophectoderm formation

Cdx2 levels Inner/outer Tracking

Polarity-based model

Trophectoderm formation

Position-based model Polarity-based model

Trophectoderm formation

Computational model outcome:

Position-based model (inside-outside) or polarity-based model?

Both models give rise to the desired pattern

However, the inside-outside model is more robust

Blastocoel expansion

The fluid-filled blastocoel is formed after the 32-cell stage A slowly expanding spherically shaped region

Endoderm formation

After the blastocoel is formed:

Nanog and Gata-6 cells randomly distributed

Problem: How do these separate (cluster) in a directional manner?

Proposed mechanisms:

Differential adhesion and directional signaling

Model the system and evaluate the impact from such mechanisms

Differential adhesion

For moving cells; randomly, through homing signals or cell divisions, adhesion properties could be important

We explore such effects in endoderm formation by assigning different adhesion and cross-adhesion strengths

With Nanog/Nanog > Gata-6/Gata-6 > Nanog/Gata-6, the two cell populations segregate

However, a homing signal from the blastocoil surface is needed for robust endoderm formation

Towards the endoderm

Differential adhesion only

Directional signal only Nanog

Gata-6

Towards the endoderm

Nanog Gata-6

Differential adhesion + directional signal

Efficiency versus adhesion strength

Summary

The ESC switch including lineage sub-switches

Core Oct4/Sox2/Nanog model (2006) still captures essentials Bistability

Reprogramming with Oct4/Sox2

“ground state” with no external signals

The Cdx2 and Gata-6 “plug-ins” handles trophectoderm and endoderm formation

Ongoing and future work

Epigenetics and more components

Noise – transcriptional versus epigenetic

Benefit from novel data; e.g on Nanog knockdowns (Lu, 2010)

Summary

Patterning mammalian embryonic development

Mechanics is important

Trophectoderm formation Endoderm formation

A simulation modeling framework essential for testing hypothesis

Future work

Implementing signalling and extend mechanics to describe further development

Key collaborators & publications

Vijay Chickarmane Biology Division, Caltech

V. Chickarmane et al, Transcriptional dynamics of the embryonic stem cell switch, PloS Comp Bio e123 (2006)

V. Chickarmane et al, A computational model for understanding stem cell, trophectoderm and endoderm lineage determination, PloS One e3470 (2008) P. Krupinski et al, Simulating the mammalian blastocyst – how biochemical and mechanical interactions pattern the embryo, submitted (2010)

Pawel Krupinski

Computational Biology, Lund