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February 06, 2006

More on nitrogen metabolism and lac operon

Follow-up to Paper: PII signal transduction proteins, Ninfa 2000 from Schreibfaul in Warwick

About time to get started on lac operon and nitrogen mebaolism background. Here the link:


More on nitrogen metabolism and lac operon

Follow-up to Paper: PII signal transduction proteins, Ninfa 2000 from Schreibfaul in Warwick

About time to get started on lac operon and nitrogen mebaolism background. Here the link:


January 09, 2006

Paper: PII signal transduction proteins, Ninfa 2000

Writing about web page http://dx.doi.org/10.1016/S0966-842X(00)01709-1

The Atkinson 2003 synthetic gene circuit relies among others on components of the bacterial nitrogen regulation system, more precisely on

  • the glnG gene and its product, the NRI protein
  • the glnAp2 promoter (product of glnA gene is GS) (requires NRI-P for activation)
  • the glnKp promoter (also requires NRI-P for activation, activation less potent) (prodcut of glnK gene is glnK protein, PII like, see below)

To have a better understanding where these components are coming from I had a look at the above named paper Ninfa 2000 .


Remark:
It seem noteworthy that NRI-P has a inhibiting influence on the glnA transcritption at higher concentrations, and that glnK is only expressed at these higher concentrations. Or so I understand the description of the various levels of the response to nitrogen stress, see below .



Introduction:

  • PII proteins, found in bacteria, Archaea and plants, are involved in coordinating carbon and nitrogen assimilation by regulation of correponding signal transduction enzymes. They integrate antagonistic signals of carbon and nitrogen status.
  • developmental regulation systems probably eveolved from metabolic regulation systems.
  • switching between regulatory cell types depending on carbon-nitrogen condition is reversible, but cell should not flip back and forth to often -> certain constraints.
  • PII is direct and indirect sensor of various stimuli that cause the formation of different PII conformations

Nitrogen regulation in E. coli

  • if ammonia is present, assimilation of ammonia into glutamine is regulated in response to the intracellular concentration of glutamine (nitrogen signal) and 2-ketoglutarate (2KG) (carbon signal).
  • glutamine synthetase (GS) is responsible for most of the ammonia assimilation, closely regulated and limits the rate of nitrogen assimilation to keep it in balance with the rate of caron assimilation.

GS regulation

  • GS regulated by a) regulation of its structural gene glnA and b) by regulation of GS activity by reversible covalent adenylylation.
  • Adenylylation state of GS is controlled by the bifunctional enzyme adenylyltransferase (ATase)
  • transcription of glnA requires transcription factor NRI-P (phosporylated NRI)
  • phosphorylation of NRI is controlled by NRII
  • So NRII and ATase control level and activity (respectively) and are at least in part controlled by PII

Role of PII

  • PII inhibits autophosphorylation of NRII and activates its phophatase activity -> results in decrease in the extent of NRI phosphorylation.
  • PII, by binding to ATase, activates GS adenylylation.

Regulation of PII

  • PII activity in turn is regulated by small-molecule signals of carbon and nitrogen status:

PII regulation by nitrogen signal

  • Glutamine is sensed by ATase and a bifunctional uridylyltransferase-uridylylremoving enzyme UTase-UR, which controls PII activity: it uridylylates PII if glutamine concentration is low and deuridylylates PII when the glutamine concentration is high.
  • PII-UMP does not bind to NRII, thus at low glutamine, NRII can phosphorylate NRI, thus turning on nitrogen-regulated gene expresion Ntr including glnA, gene of GS.
  • Further PII-UMP binds to ATase, stimulating deadenylylation of GS-AMP, activating GS.

PII regulation by carbon signal

  • Carbon signals, mainly 2KG, directly bind to PII, which as a trimer has three binding sites for 2KG and ATP. Synergistic dynamics lead to binding of one 2KG and three ATP at normal concentrations and saturation of PII only at very high 2KG levels.
  • 2KG saturated PII cannot interact with NRII or ATase. So carbon signal can counteract the effect of the nitrogen signal.
  • Signals are sensed independently since saturation of PII by 2KG does not affect its interaction with UTase-UR.

  • Concentration of the components of the signal transduction system must be balanced

Response of the cell to nitrogen stress (starvation)

  • Level One: Increase of NRI and NRII expression.
  • Level Two: Switching on of Ntr genes.
  • Level Three: Switching on of nif genes (in some organisms).

Closer look at switch from first two second level response:

  • The transcription factor NRI-P binds upstream enhancers and interacts with sigma RNA polymerase at the target promoters by means of a DNA loop, whose stability is further regulated by other factors.
  • Boils down to: Each Ntr promoter becomes activated only when the NRI-P concentration is above a certain threshhold.
  • Negative regulation of NRI-P has also been observed. In particular, the expression of glnA first increases and then decreases at high NRI-P concentrations.
  • The Ntr genes of the second level require a higher level of NRI-P concentration than the glnA promoter.
  • One second level gene is GlnK, which encodes the PII like protein GlnK, which seems to be designed to function under nitrogen starvation conditions. It might serve a role similar to PII or replacing it under these conditions. Not fully understood.

November 20, 2005

Network Meeting 15. November

Discussion of Leloup and Goldbeter 1998. The article-pdf is also availabe via Goldbeters Homepage.

Introduction

  • Current model is an extension to Goldbeter 1995 or his book from 1996.
  • 1995 model based on PER and PER mRNA alone and featured phosphorylation and negative autoregulation of PER.
  • Model now extended to include the formation of the TIM-PER complex, which migrates into nucleus and represses tim and per, also phosphorlyation of TIM und the rapid degradation of TIM induced by light.

Model Hypothesis

  • PER mRNA is syntesised in the nuclues, transported into the cytosol. There it undergoes subsequent phosphorylations (here two). The assumptions for TIM are the same.
  • The fully phosphorylated proteins reversibly form the PER-TIM complex, which migrates into the nucleus and there represses the gene transcription.
  • The variables considered are per and tim mRNA, the protein (oP,1P,2P), PER-TIM in the cytosolol, PER-TIM in the nucleus.
  • all reaction kinetics either of MA or MM type, except the repression, whch is a Hill function.

Oscillations

  • oscillation for large parameter range
  • numeric results for symmetric and assymetric reaction rates (w.r.t. PER and TIM)
  • dependence of varous model parameters on the period, comparison to experimental results
  • birhythmicity and chaos in small parameter region
  • parameter range for which oscillations occur increases by introduction of complex, phosphorylation and cooperativity.
  • LD regime modelled by doubling TIM degradation during the light interval
  • comparing theoretical and experimental phase resonse curves, also investigating effect of magnitude and lenght of the light impulse on the phase response curve. (hmm.. a blog on circadian clocks)

Phd relevance:

  • might be a model which can be decomposed into two subnetworks each capable of generating oscillations

November 18, 2005

Recap of Network meetings of 8. November

The orignial entry wasn't very long..

The papers discussed were Smolen 2000 and Hasty 2001. These references were taken from the paper of the week before.

The Hasty paper read actually very similar to the Collins pape of the week before and several expamples were discussed in both, which might be due to the fact that Collins is a co-author of both papers. Therefor I will only go through the Smolen paper:

Techniques for Gene Network modeling
Two major approaches:

Qualitative Models of Simple Gene Networks:
Some expamples of networks

  • with multistability and time delays allowing for state- and history-dependet responses to stimuli – needs positive feedback – (Figure)
  • with conditions allowing oscillations – needs negative feedback, time-delay also good for oscillations, ruling out oscillations for a large class of systems Smith1987 and Smolen1999
  • Oligomerizations of transciption factors helps to generate complex dynamics: typically modeled by Hill function
  • competition between transcriptional activators and repressors could yield optimal stimulus frequencies for transcription: hmm…
  • Modeling macromolecular transport with a time delay or diffusefiley can affect dynamics: comparative studies show that if transport is modeled by diffusion oscillations are typically damped as the peak is flatted out. time deley conserves activation peaks and makes osciallations more likely.
  • random fluctuations in macromolecule numbers can yield significant variability in system dynamics: MCMC method by Gillespie 1977.

Models of specific Gene Networks
Some expamples:


October 31, 2005

Engineered gene circuits

Writing about web page http://dx.doi.org/10.1038/nature01257

Had a look at this paper by Collins. (See Boston conference earlier).
I put down some concepts and references that caught my attention:

Introduction

  • "Gene circuit approach" tackles analysis of gentic networks by analogies with eletric circuits and circuit diagrams.
  • discussion of related modelling techniques in Smolen 2000 and Hasty 2001 (these should give me answers of the specific structure of typical model equations…)
  • think Gen. Net. as modular structures: Hartwell 1999 – for modules think, e.g. minimal switches or oscillators

– on the side: Brabasi 2004 on Network Biology

Autoregulatory systems

Toggle Switch

  • bistability necessary for memory, created by positive feedback or mutual inhibition (RS-latch or here )
  • mutual inhibition synthetic switch in E. Coli: Gardner 2000

Logic Gates

  • formulation of Gen. Net. as logical AND, OR, etc. switches depending on proteins or external chemicals as input signals (Weiss 2002)
  • creation of gates by combinatorical synthesis, Guet 2002

Repressilator

Sources of Noise

Intercell signalling

  • modeling study of synchronisation of osciallations, McMillen 2002

Applications

  • engineered adenovirus specifically killing p53 defective tumor cells, Ramachandra 2001
  • coupling oscialltory synthetic network with intrinsic one, Hasty 2002, for entraining and amplifying oscillations

Ulrich Janus

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