dynamic processes in cells(a systems approach to biology)

jeremy gunawardenadepartment of systems biology

harvard medical school

lecture 723 september 2014

4. cellular identity & gene regulatory networks

human embryonic development

stage 1, day 1totipotent zygote or

fertilised oocyte

stage 3, day 4-5pre-implantation

blastocyst stage 9, day 19-21neural folds, somites 1-3

stage 7, day 15-17gastrulation, notochord

stage 11, day 23-2613 somites

stage 13, day 28-32leg buds, pharyngeal arches, lens placode

stage 19, day 48-51fingers emerged, bone

has started to form

stage 17, day 42-44fingers emerging

UNSW Carnegie Stages http://php.med.unsw.edu.au/embryology/index.php?title=Embryonic_DevelopmentKyoto Human Embryo Visualization Project http://bird.cac.med.kyoto-u.ac.jp/index_e.html

cell cycle & mitosis

microtubule organising centre or centrosome in

animal cells

microtubules forming a mitotic spindle

Andrew Murray, Tim Hunt, The Cell Cycle: An Introduction, OUP 1993.

stages of mitosis in onion (Allium cepa) root tip cells

germ cell formation by meiosis is more complicated

hierarchical construction of cellular identity

hematopoietic stem cell

platelet red blood cell

mast cell

basophil eosinophil

granulocytes

dendritic cells

monocytes

B-cell T-cell

“myeloid” = from the bone marrow

“lymphoid” = from the lymphatic system

neutrophil

macrophage

in the blood (“hematopoietic”) system, which undergoes continuous renewal

specialised (“terminally differentiated”) cells

progenitor and stem cells

cellular identity

cellular identity is both stable and plastic

Antsiferova, Werner, “The bright and dark sides of activin in wound healing and cancer”, J Cell Sci, 125:3929-37, 2012; Kalluri, Weinberg, “The basics of epithelial-mesenchymal transition”, J Clin Invest, 119:1420-8, 2009.

wound healing & tissue regeneration

cancer

EMT = epithelial-mesenchymal transitionMET = mesenchymal-epithelial transition

cellular identity can be re-programmed – I

Jaenisch, Young, “Stem cells, the molecular circuitry of pluripotency and nuclear reprogramming”, Cell, 132:567-82, 2008; Lensch, Mummery, “From stealing fire to cellular reprogramming: a scientific history leading to the 2012 Nobel Prize”, Stem Cell Reports 1:5-17, 2013

John Gurdon (1933-)Shinya Yamanaka (1962-)

(l to r) Keith Campbell (1954-2012)Dolly the Sheep (1996-2002)

a n otherIan Wilmut (1944-)

in frogs

in mammals

cellular identity can be re-programmed – II

Mintz, Illmensee, “Normal genetically-mosaic mice produced from malignant teratocarcinoma cells”, PNAS, 72:3585-9, 1975; Bissell, Radisky, “Putting tumours in context”, Nat Rev Cancer, 1:46-54, 2001

Beatrice Mintz1921-

cellular identity can be re-programmed – III

Francis, Diorio, Liu, Meaney, “Nongenomic transmission across generations of maternal behaviour and stress responses in the rat”, Science 286:1155-8 1999; Szyf, Weaver, Champagne, Diorio, Meaney, “Maternal programming of steroid receptor expression and phenotype through DNA methylation in the rat”, Frontiers in Neuroendocrinology 26:139-62 2005

open field exploration

licking/grooming

adult female offspring

cross-fostering group

epigenetic mechanisms

molecular basis of cellular identity

how does a single genome give rise to many different cellular identities?

cells create different stable states of feedback between inherited genetic and epigenetic information and patterns of molecular expression from DNA

genetic (DNA sequence) informationepigenetic information

RNA speciespeptides & proteins

act uponto express

and these states are stably inherited by daughter cells

Jacques Monod, Francois Jacob, “Genetic regulatory mechanisms in the synthesis of proteins”, J Mol Biol 3:318-56 1961

gene expression in eukaryotes

expression of genetic information is regulated by weak linkage

sequence specific transcription factors bind DNA, in a 3D chromatin context, and recruit general purpose co-regulators, such as mediator and chromatin organisers, thereby regulating the presence of RNA polymerase and transcription initiation

Ptashne & Gann, Genes & Signals, Cold Spring Harbor Lab Press, 2002; Levine & Tjian, “Transcription regulation and animal diversity”, Nature 424:147-51 2003

Ahsendorff, Wong, Eils, Gunawardena, “A graph-based framework for modelling gene regulation reveals history-dependent complexity away from equilibrium”, submitted, 2014

epigenetic information in eukaryotes

Bergmann, “Programming of DNA methylation patterns”, Annu Rev Biochem, 81:97-117, 2012

DNA methylation

histone PTM

nucleosome

chromatin structure

mitotic inheritance of epigenetic information

DNA methylation is semi-conservatively replicated on daughter strands

a similar mechanism may also operate for histone PTM marks (*)

Krude, “Nucleosome assembly during DNA replication”, Curr Biol, 5:1232-4, 1995; Ushijima et al, “Fidelity of the methylation pattern and its variation in the genome”, Genome Res, 13:868-74, 2003; (*) Moazed, “Mechanisms for the inheritance of chromatin states”, Cell, 146:510-8, 2011

meiotic inheritance (during germ cell generation) remains controversial

thermodynamic formalism

oligomerisation

binding unbinding

.

.

.

state

s of

TF

bin

din

g t

o D

NA

RNAPol II

mRNA

transcription averages over the equilibrium states

thermodynamic equilibrium

assumes that TF oligomerisation and TF binding & unbinding to DNA is at thermodynamic equilibrium and transcription averages over the equilibrium states

the linear framework at equilibrium

Dij0mna[T]

b

Dij1mn

Dijkmnc

Eijkmn

labelled directed graph

binding/unbinding of transcription factor T changes only one bit

change of DNA state (looping, nucleosome repositioning, etc) without changing TF binding pattern

bitstring indicating TF bindingDNA state Xvertices (microstates):

edges:

uncoupling condition

✓

no-depletion assumption: binding of T to DNA does not appreciably change its concentration, so that [T] = Ttot

calculating gene expression

1. each microstate has a characteristic rate of gene expression and the overall rate is proportional to the average over all microstates

2. the transcriptional machinery (Pol II, RNAP) is treated as if it were a transcription factor binding to its own site and the rate of gene expression is taken to be proportional to the probability of finding that site bound (fractional saturation)

Ackers, Johnson, Shea, PNAS, 79:1129-33 1982; Shea, Ackers, J Mol Biol 181:211-30 1985

probability of microstate

calculating using detailed balance

principle of detailed balance (in the linear framework): at thermodynamic equilibrium, every edge has a complementary reverse edge and in any steady state, each pair of reversible edges is independently in steady state, irrespective of any other edges reaching those vertices

detailed balance is a consequence of microscopic reversibility: the fundamental laws of physics, whether classical newtonian mechanics or quantum mechanics, exhibit time-reversal symmetry (+)

(*) Gilbert Lewis, “A new principle of equilibrium”, PNAS 11:179-83 1925

(+) Bruce Mahan, “Microscopic reversibility and detailed balance”, J Chem Edu 52:299-302 1975

1. if the system reaches thermodynamic equilibrium, then detailed balance holds and can be calculated using a single path in the graph or by equilibrium statistical mechanics (next lecture)

“For if this were not the case we could add a minute amount of some catalyst which would increase the rate of the reaction and its inverse along one of the paths, without affecting the two rates in the other path. This would disturb the existing equilibrium, contrary to the results of observation and of thermodynamics.” (*)