This course will introduce the student to contemporary Systems Biology focused on mammalian cells, their constituents and their functions. Biology is moving from molecular to modular. As our knowledge of our genome and gene expression deepens and we develop lists of molecules (proteins, lipids, ions) involved in cellular processes, we need to understand how these molecules interact with each other to form modules that act as discrete functional systems. These systems underlie core subcellular processes such as signal transduction, transcription, motility and electrical excitability. In turn these processes come together to exhibit cellular behaviors such as secretion, proliferation and action potentials. What are the properties of such subcellular and cellular systems? What are the mechanisms by which emergent behaviors of systems arise? What types of experiments inform systems-level thinking? Why do we need computation and simulations to understand these systems? The course will develop multiple lines of reasoning to answer the questions listed above. Two major reasoning threads are: the design, execution and interpretation of multivariable experiments that produce large data sets; quantitative reasoning, models and simulations. Examples will be discussed to demonstrate “how” cell- level functions arise and “why” mechanistic knowledge allows us to predict cellular behaviors leading to disease states and drug responses.
Pathways to Networks - MAP-kinase Pathways/Network II
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From the course by Icahn School of Medicine at Mount Sinai
Introduction to Systems Biology
233 оценки
Icahn School of Medicine at Mount Sinai
233 оценки
Course 1 of 6 in the Specialization Systems Biology and Biotechnology
From the lesson
Pathways to Networks | Physical Forces and Electrical Activity in Cell Biology
Module description goes here.
Meet the Instructors
Ravi Iyengar, PhDDorothy H. and Lewis Rosenstiel Professor
Department of Pharmacology and Systems Therapeutics, Systems Biology Center New York (SBCNY)
[SOUND] Continuing
on let us now consider how signaling
proteins interact with one another, to form pathways and networks.
Signalling proteins with mutual chemical specificity due to secondary and
tertiary structure, enable connectivity between components to form pathways.
So in the example shown here, the protein kinases make 1 and 2 interact
with, and phosphorlate the protein kinases irak 1 and irak 1, or map kinase 1 and 2.
Same molecules, multiple names.
These protein kinases, the irak 1 and 2 in turn can regulate enzymes.
Such as phosopho lipase A 2.
How to inscription factors such as stat, and NF cap of B.
[BLANK_AUDIO]
In another pathway, the protein kinases is mech 4
and mech 7 regulate the MAP-Kinases, a
different class of MAP-Kinases called GNK1, 2 and
3 and the GNK in turn phosphorylate transcription
factor such as CGEN or ATF to regulate their
RTCF, to regulate their functions.
So, the, so mech 1 and mech 2 interact with irk
1 and irk 2, and does not with j and k.
Similarly mech 4 and mech 7 interact with j and k's, but
not irk one and irk two, and this is what I mean by
mutuals chemical specificity, so you can see how pathways are formed by sort
of the, interactions of comp upstream
and downstream components in a specific manner.
You can also see that not all target effectors such as
enzymes, such as phospholite BZ 2, or transcription
factors, or other, ce, cellular components
[UNKNOWN] by some, but not all protein kinases.
So, for instance, in this example, mh, CPLA2, and Maka
are phosphated by irk 1, 2, but they are not phosphorlated by junk.
Similarly, ATF, and, P53 are phosphorylated by junk.
By j and ks, but not by irk 1 and 2.
So you can see how there is
propagation of these bi-directional specificities to form pathways.
Also clear from this example is a number of cellular components, transcription
factors such as stat, TCF and AP1 that are [INAUDIBLE] related boot
by URK1, URK2, and by JNK1, JNK2, and JNK3.
These components that are phosphorylated by both kinases can
serve as integrator of signals, integrator of signals from
both two pathways and subsequently re, produce responses, in
this case, gene expression due to signal from multiple pathways.
And these components that can have the ability to receive
signals or interact with, with multiple upstream pathway components
enable for cross pathway specificity and the formation of network.
In the particular example shown here, the network
is formed by this two upstream components interacting
with downstream components that a set of downstream components
that receive signals with both the crossovers and the Pattern that is
formed here [UNKNOWN] called the motif is a code network motif is called
a by fan motif.
I will discuss about by fans further in a,
in a later lecture, but you can regular regularly
see here the contours of how signalling pathways interacting with
the same components can lead to networking between pathways.
[BLANK_AUDIO]
Again let us now look at some details of these various
cartoons that I've been showing you to make understand other points.
One key sort of, place with connectivity or, networking, emerges.
Is, is at the level of receptor itself.
And, in this particular, cartoon, let's focus on the EGF receptor, and just what
EGF receptor directly connects to, and, you can see that EGF receptor directly
connects to the exchange factor Vav2 to activate CDC 42.
It directly connects to Grb2, to activate them in a small G-protein Ras through the
exchange factor SOS it directly connects to phosphol IPC gamma, and so on.
So the ability of the sa, of the same receptor to engage multiple
pathways orderly allows for the start of networking to occur.
So it is very much like a, a, a, like
a single node from which from it's multiple signals can emerge.
In some ways you can think of it as like a, a terminus at a train station.
You might have a, a terminus that is
kind of central terminal,something where trains start off
at one point, and then can go to various parts of the northern subway of New York.
So you can think of receptor in, in, in that line of our organization.
Now there is a complexity at the level of receptors at well.
And this is most often, sort of exemplified
in G-protein-coupled receptors, much more so than growth factor receptors.
Almost all G-protein-coupled receptors, almost all
G-protein-coupled receptors have multi, almost all ligands for G-protein,
excuse me, have multiple receptors that coupled to different signaling pathways.
Take of the case of adrenaline here, adrenaline
can interact with 3 kinds of adrenalgic receptors.
The alpha 1 adrenergic receptor that couples
to G2, the Alpha 2 adrenergic receptors
that couple to' Gi'/' Go' and the Beta adrenergic receptors that couples to' Gs'.
There are multiple forms of each of the alpha 1, alpha 2
and beta, but we won't con we won't concern ourselves about that.
And by connecting to these different pathways,
the same lyengar can induce different effects.
So there's alpha 1, adrenergic receptors in the smooth muscle and so adrenaline
can cause smooth muscle contraction, to the alpha1 [UNKNOWN] BC pathways.
[BLANK_AUDIO]
There is also alpha-2s can cause inhibition
of neurotransmitters in the brain through the
coupling through the GI Go pathway, and
thus blocks synaptic transmission or inhibits synaptic transmission.
So this is through the GI GO pathway in beta gamma to regulating iron channels.
To the beta-adrenergic receptor in psychic
AMP, it can cause, Glycogenolosis, production
of glucose, heart-muscle contraction to the L type calcium channels, and so on.
So the ligand may be the same, but because of the
different receptor isoforms, one can get different effects in different sub-types.
And in, in the, in different cell types.
I'm sorry.
And indeed the specificity of a, of a response in a cell type is often
dependent on the type or the isoform of the receptor that's present in that cell.
[BLANK_AUDIO]
So now what can happen when a single
ligand, that works through multiple receptors produces multiple signals.
Consider the case, which is actually quite
common in neurons, adrenaline, noradrenaline or norepinephrine
can signal to the alpha 1 receptor pathway and to the alpha 2 receptor pathways.
To sort of activate phospholipase C and to activate the last pathways.
Activating these two pathways allows downstream for the formation of this
positive feedback loop here, that allows for signal from Ras and Raf to go
to MAP kinase to activate the enzyme phospholipase A2 that can activate
the enzyme protein kinase C that in turn feeds back into Ras and Raf.
And I will deal about this positive feedback loop in, sub, in in a subsequent
lectures and how this gives rise to bistablility or multiple stable state.
But here the key point to remember is the presence of this
multiple isoforms of the, that bind the same ligand can involve
multiple pathways that come together due to cross connectivity
to form eh, to form eh, organization that allows
for this positive feedback loop and switching to [UNKNOWN].
[BLANK_AUDIO]
Another type of organizational feature that is often found in biological systems
is the so-called bowtie configuration, where a single component or a
one or two components can get signals from many cell, from many
pathways, and in turn regulate multiple effector systems to regulate various
kinds of cellular responses.
Here we show how the presence of the multiple isoforms of the enzime
adenylyl cyclase allows the cyclic AMP pathway
to receive signals from a variety of receptors, including the the
receptor channels the growth factor, growth factor receptors,
and GPCRs, and these, in turn, are all either
stimulate or inhibit cyclic AMP plungers representing inhibition arrows
represent stimulation, and these changes in psychic AMP through PTA
can regulate a variety of functions including cytoskeleton movements,
gene expression, enzyme activity, and channel activity for synaptic plasticity.
So you can Just visually see the bowtie, and
it's sometimes also called the hourglass, hourglass configuration here.
[BLANK_AUDIO]
In addition to receptors, small GTPases enable networking
by acting through multiple pathways to reach different effectors.
I took the big eh, eh, network picture from from the previous
part of this lecture, and I whited out the middle for you to highlight how
the EGF receptor through either RAB or through the exchange factor
GRAB, can interact with the small G protein CDC42 Rac,
or Racs, to engage different map kinase batteries
to, to get to different kinds of to
get to different kinds of transcription factors including crab,
B53, eh June, and AP 1 and so on.
So by using these different pathways one can then turn
on different gene expression patterns and then produce multiple effects.
So GTPases are very important nodes for that enable networking within cells.
[BLANK_AUDIO]
In addition to GTPases, and I've already alluded
to this, the ability of a protein kinase
to phosphorylate many substrates such as conscription factors,
leads to cross- connectivity that enables extensive networking.
And this again is a blow up of one of the previous slides that I
showed you, but you can see that Irk 1/ g and Irk 2 can phosphorylate
a number of transcription factors that are also phosphorylated by
J and K, the, these transcription factors such as STAT3 and TCF,
can, can get multiple signals in contrast to transcription
factors in contrast to transcription factors that only get signals from,
say, mm from C Irk 1 which is, such as NF kappa B.
eh, please note there's a little bit of confusion here, because there are some
enzymes that are also down here, so not all of these are transcription factors.
So this mix and match profile allows, of course, for
networking, and we'll talk about this type of networking later on.
So protein kin, kinases are also very important for networking.
So the take home points for lecture 3 are as follows.
Receptors as well as other intracellular
signaling components, enable networking between signaling pathways.
Pathways arise due to the bidirectional biochemical specificity of the signaling
component, I've sort of demo given you examples of these, both the cyclic AMP
and the MAP kinase pathways and networking arises, the
ability of these components to selectively interact with and
regulate components of another pathway such as how PKA regulates
components of the MAP kinase pathway and actually MAP kinase also in turn can
regulate components of the PKA pathway though I have not shown examples of that.
So this kind of ability to cross regulate between pathways
or between the different MAP-Kinase pathways, give rise to networking.
So this ends lecture 3.
Thank you very much.
[SOUND]
[BLANK_AUDIO]
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