Bio 123, UZH

In yeast two-hybrid interaction screening schaut man ob zwei Proteine miteinander interagieren können. Probleme davon sind unter anderem, dass nur binäre Interaktionen ablaufen können. Auch findet es immer im Nucleus statt (wo jedoch einige Proteine z.B. Ein zu basisches Milieu vorfinden).

Systematic affinity purification: in vitro, ziehe gezielt an einem Protein und schaue was dabei mitkommt.

Dabei testet man systematisch mit Robotern verschiedene Mutationen gegeneinander, denn manchmal resultieren 2 Mutationen gleichzeitig In eine Lethalität. 

Dabei gibt man eine Chemikalie mit reaktiven Enden hinzu , welche zufälligerweise 2 Proteine miteinander verbindet.

Arbeitet mit der These: proteine die sich binden bleiben zusammen

Nach pH oder grösse etc auftrennen

Beobachten welche proteine möglichst lange zusammen geblieben sind

Protein docking: "puzzlen" im Computer. Jedoch sehr hohe Fehlerrate (Den proteine sind ja nicht einfach starr, sondern sehr dynamisch und falten sich wieder etc schwierig so zwei zusammenzusetzen)

Was etwas besser funktioniert sind

Correlated mutations

Meisten stirbt er bei einer Mutation ABER es kann auch sein das zufällig gibt es zweite mutation

(compensatory mutation), das passiert gar nicht so selten

Und das kann man im computer analysieren.

Oder vorhersage durch genome information.

Synthetic biology is the engineering of biology:

the synthesis of complex, biologically based (or inspired) systems which display funcions that do not exist in nature.

Synthetic biology is a) the design and construction of new biological parts, devices and systems and b) the re-design of existing natural biological systems for useful purposes.

You start with a target function, which you want to have in the end. So you know already exactly your goal. After you designed and modelled it, you built it. Then you caracterise it. Here, at first attemp you often get a mismacht and so you have to iterate (repeat). In the end get a conclusion or application. 

In opposite to the traditionally biology (create mutants, and then draw some conclusion if something stopped working, etc.) you go from the opposite direction.

Because once you know these components, then you can try to rebuild things (and learn a lot about how this works).

But we always only rebuild parts of it, never the whole thing at once! And we also don‘t recreate it with exactly the same, but different genes.

The main credo of synthetic biology is "What I cannot create, I do not understand."

Occur in the transcription network much more often than it would be expected in random networks. They are the building blocks so to say for more complicated things.

Synthetic biology is the engineering of biology

It uses a typical engineering workflow

SynBio is a complementary approach to understand biological systems and their design rules

Engineered biological systems have potentially many applications (biotechnology, medicine, biofuels, biosensors etc.)

• green fluorescent protein: GFP
• shines green when exposed to blue light
• isolated from the jellyfish Aequorea Victoria
• used as a reporter of expression

• Repressor from lac operon (lac Inhibitor)
• Lac operon encodes proteins necessery for the transport and breakdown of the sugar lactose
• 1st natural gene regulatory network studied in detail

see picture

• Repressor from lambda phage
• Involved in switching between lytic and lysogenic pathway

Tet repressor protein: Controls the expression of the tet genes, whose product confer resistance to the antibiotic tetracyline

• Toogle Switch
• Repressilator

• The synthetic network (repressilator) works as oscillator
• However, the oscillations are not regular
• In contrast, natural oscillators are very precise
• Nature is using different network designs

The toggle switch was built with 2 repressors and can be switched between 2 states

The repressilator consists of 3 repressors and oscilates

Its the elementary building block of a digital circuit.

Each gate has a separate symbol and a name, f.e. "A or B", "not A", etc.

The relationship between the in- and outputs is given in the truthtable. Its always either 1 or 0. (zero means for example that we have no input of A)

Here you will need both together (A and B) to have an output. One alone is not enough. 

There are also layered AND gates, when you combine different gates together.

An example of an AND gate is the treatment of Psoriasis. Its a chronic inflammatory skin disease.

Gates can also be built by using integrases.

With our input we control these integrases. They can for example inverte the terminator, or even cut the whole thing out!

This one works when either A or B are present

see picture

In the classic cloning, you have a cDNA library, which you amplify by PCR, etc.

But nowadays, you just go online and order your genes of interest. And they synthesize the DNA for you. There are many advantages (you can delete restriction sites etc.) and its not even that expensive.

But how do they synthesize these genes for you?

Take the DNA, divide it into parts and synthesize Oligonucleotides which have overlappings to each other. Then insert primers with uniques sites.

1.       Many parts are undefined

2.       The circuits are unpredictable

3.       Many parts are incompatible

4.       Variability crashes the system

5.       Safety and ethical challenges

Genetically identical cells which are grown under same circumstances and still show differences

Its logical that individual cells from an organism are different (f.e. From the liver, heart, etc.).

But how about the variability between cells from the same type, that are siblings from the same parent cell and are grown under identical conditions?

And where lies the boundary between differentiation and non-genetic cell-to-cell variability?

(Its to mention that to notice this is only possible with the newest technologies, where we can quantify the cells)

Such variability cannot described with qualitative terms, so we need quantification.

• Fluorescence activated cell sorter/analyzer (flow cytometry)
• Single-cell micro-dissection for further analysis

• Ultrasensitivity
• positive feedback

Intrinsic noise is when you have two gens which are regulated identically, but you get different outputs (even under identical conditions!).

Otherwise, when you get the same output (and maybe sometimes a little darker yellow or lighter, etc.) you only would have extrinsic noise.

Intrinsic noise is when you have two gens which are regulated identically, but you get different outputs (even under identical conditions!).

Otherwise, when you get the same output (and maybe sometimes a little darker yellow or lighter, etc.) you only would have extrinsic noise.

when you cannot explain where it cames from, its stochastic, not regulated or controlled

Active: can measure noise and somehow create an anti-noise signal which cancel the noise out

Passive: prevents noise from entering 

Active: can measure noise and somehow create an anti-noise signal which cancel the noise out

Passive: prevents noise from entering