dynamic processes in cells (a systems approach to...
Transcript of dynamic processes in cells (a systems approach to...
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.” (*)