The Project


Background


Lanthanides are a series of fifteen chemical elements with atomic numbers 57 through 71, from lanthanum through lutetium. All but one of the lanthanides are f-block elements, corresponding to the filling of the 4f electron shell (lutetium is a d-block element). The presence of f orbitals is responsible for their unique properties such as strong paramagnetism.
They are usen in a variety of modern technologies, such as electronics, aviation (eg. jet engines) and superconductors, thanks to their magnetic properties.
According to their name 'rare earths metals' their deposits on Earth are scarce at best and dispersed. Most of their ores lay in China and with China being very cautious with their recources situation on lanthanides market is not getting any better.
Other problems with lanthanides avaibility are problems with extraction of pure metals from minerals. Most of lanthanides appear together in ores and similar properties of their ions in aquous solutions makes extraction and purification difficult. Lanthanides are often purified by ion-exchange chromatography, despite it's cost.

Proof of concept


In 2013 group of prof. He from the University of Chicago published paper in Journal of American Chemical Society in which they described devised by themselves lanthanide detecting system.
To accomplish this, they engineered two-component system from Salmonella enterica.
Something went straight to Hell

Detailed explanation


In initial plans, our project would consist of two parts, first being lanthanide detecting system in BioBrick standard, much like the one constructed by group of prof. He and the second being lanthanide binding system, which would bind lanthanides much more effectively than the detecting system.
Both of these systems would be based on PmrA-PmrB two-component system, native to Salmonella enterica. This system consists of two proteins, PmrA and PmrB. PmrB is a transmembrane kinase with iron (III) binding tag on it's extracellular loop. When iron (III) is bound to this tag, PmrB gains kinase activity and phosphorylates PmrA. PmrA is a transctriptoral factor and, upon activation, binds to pmrC promoter and induces expression of CheZ, a chemotaxis protein.
So much for native systems.

Design

Detecting system
Our detecting system was planned as follows:
Iron binding tag would be replaced with lanthanide binding tag (of which a various collection can be find in literature) and a reporter protein would be inserted downstream of pmrC. Thus, in the presence of lanthanides, fluorescence of GFP should be observed.
Binding system
Binding system would be more tricky. PmrA-PmrB would stay the same, with LBT (lanthanide binding tag) instead of iron binding tag. The difference would be downstream the pmrC promoter. First of all, we must have some sort of binding agent. We were planning to use some sort of small protein (like ubiquitin) or structurised peptide as a structural basis and fuse it with LBT.
Another problem would be with pmrC. pmrC, even induced by PmrA, is a very weak promoter. So, even in the presence of lanthanides, expression of binding agent would be poor. To overcome that, we planned to use some genetic device to boost the expression from upon the pmrC. Our first idea was to put two subsequent inverters (based on different proteins, eg. tetR and lacI), which should fix the problem. Expression of binding agent would be high in the presence of lanthanides and low in absence.
Binding agent expression
Lanthanide presence pmrC pmrC-inverter1 pmrC-inverter1-inverter2
none zero (very low) high low
present low low high

This may seem like an excessive mean, but we could not have invented anything subtler.

Project goals

  1. Construction of lanthanide sensor in BioBrick standard
  2. Cloning of PmrA/PmrB parts into pSB1C3 in BioBrick standard
  3. Construction of lanthanide sensoring system with other LBT described in literature with their deposition in the Registry
  4. Construction of lanthanide binding system

Modelling


Two-component systems are the most prevalent mechanism of transmembrane signal transduction. They control gene expression thus make bacteria respond to environmental changes and drive pathongen-host interactions. A typical TCS consists of a membrane-bound histidine kinase and a partner response regulator protein. The pmrA/pmrB system implemented this year by our team also belongs to this class. pmrB is histidine kinase and pmrA is response regulator which when bound to pmrC promoter strongly enhances expression. In order to get better understanding of the system and to prevent any problems before starting the wet lab stage we decided to create precise model of this signaling pathway. Other two component systems were successfully modeled before, but not the pmrA/pmrB.

The model

When designing our model we assumed the following pathway:

  1. lanthanide ion binds to the pmrB protein which leads to its autophosphorylation,
  2. phosphorylated pmrB transphers its phosphate group onto pmrA
  3. phosphorylated pmrA binds to pmrC and allows expression of reporter GFP protein
  4. dephosphorylated pmrB induces pmrA dephoshporylation
    5. Additionally for model to work properly feedback loop in which phoshporylated pmrA induces pmrA expression is needed.

    The model diagram looks as follows: Signaling pathway

We concluded that quantities of observed species change according to these equations: Equation 1 Equation 2 Equation 3 Equation 4 Equation 5 Equation 6 Equation 7 Equation 8 Equation 9 where:

  • mRNApmrB is concentration of pmrB mRNA, the same goes for mRNApmrA and mRNARP,
  • L is lanthanide concentration,
  • RP is reporter protein concentration,
  • pmrB.bound is pmrB with lanthanide ion bound,
  • prmB.bound.ph is phosphorylated pmrB with lanthanide ion bound,
  • pmrA.ph is phosphorylated pmrA,
  • ABComplex is complex of pmrA and pmrB.bound.ph during pmrA phosphorylation,
  • AComplex, RPComplex are pmrA.ph inductors bound to respective promoters,
  • ABRevComplex is complex of pmrA.ph and pmrB during pmrA dephosphorylation

The parameters

Initial parameters were found in literature as we didn’t make component measures on our own.

Simulation and results

Deterministic simulations were performed using TinkerCell software. There are few bugs in it, but it allows for fast model building and makes changes to the model quite easy. Simulation showed that signal greatly enhances GFP expression and that its growth is exponential with growing condensation of lanthanide ions.

GFP level when there is no lanthanide ions: Chart

GFP levels with 100 um of ions: Chart

References

Kierzek AM, Zhou L, Wanner BL. Stochastic kinetic model of two compo- nent system signalling reveals all-or-none, graded and mixed mode stochastic switching responses. Mol Biosyst. 2010;6(3):531-42

Wastewater study


System analysis


Safety


Possibilities of development


We can see two clear paths in which our project could be enhanced. One is to use more LBTs described in literature in detection and the other is to plan and construct more effective binding systems.
Overmore, we had ideas about utilising some sulphur bacterias instead of E. coli. Their sulphur metabolism and ability to survive in low pH (in which metal leaching is more efficient) makes them excellent candidates for industrial utilisation of our project.
Another thing that could produce glitches; our system should not be present in bacterias as plasmids. It would be much better idea to integrate it with bacterias' genome, so it would not 'mutate away' so quickly.
/*tu JEST KONIEC STRONY*/

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