Team:ETH Zurich/Sensor Module

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AND Gate overall presentation:

Our idea was to recognize bowel infection and its possible cause based on the intestine level of Nitric Oxyde (NO) which is infection specific, and of Acyl Homoserine-Lactone (AHL) which is microbiota specific. Thus, the simultaneous presence of those two chemicals in an abnormal amount can de detected, and later associated.

Lactate is also a molecule of interest in IBD research : non only is it playing an important role in metabolism, but recent studies tend to show that it is present in high amount in certain cases of severe IBD.

Thus it turns out that two type of sensors are interesting to devellop in order to investigate the causes of IBD. The first AND Gate will be able to detect the presence of both AHL and NO, while the second one will detect Lactate and NO.

Description and Design

-- insert here a picture with design of the circuit--

Goals

• Have an overall overview of the behavior and characteristic of our system
• Discuss the specification of our model and see how the design may influence the equations and this the output behavior
• Define the parameters that can be tuned and that can impact the output of our system so we can control our system range of working
• Compare the different design
• Infer the input state from the output signal analysis

Nitric Oxyde sensor

In the absence of NO, NorR is produced constitutively and binds repressively to the PnorV promoter, preventing gene transcription. When NO is present in the medium, it binds cooperatively to the hexameric form of NorR,and activate the promoter.

Assumption

We considered here that the binding of NO to NorR and PnorV_{i} does not affect the other species binding. Thus the reactions \begin{align*} NorR+NO&\rightleftharpoons NorR_{NO}\\ \end{align*} and \begin{align*} PnorV_{NorR}+NO&\rightleftharpoons NorR_{NO}\\ \end{align*} have the same reaction rate. Under those assumption, the system of equation can thus be simplified as follows:

Chemical species, reaction and equations

Reaction

NorR system:

\begin{align*} &\rightarrow NorR\\ NO+NorR&\rightleftharpoons NorR_{NO}\\ 2NorR_{NO}&\rightleftharpoons DNorR_{NO2}\\ 2NorR &\rightleftharpoons DNorR\\ DNorR+NO&\rightleftharpoons DNorR_{NO1}\\ DNorR_{NO1}+NO&\rightleftharpoons DNorR_{NO2}\\ DNorR_{NO2}+PnorV0&\rightleftharpoons PnorV1\\ DNorR_{NO2}+PnorV1&\rightleftharpoons PnorV2\\ DNorR_{NO2}+PnorV2&\rightleftharpoons PnorV3\\ PnorV3&\rightarrow mRNA_{Bxb1}\\ NorR&\rightarrow\\ DNorR&\rightarrow \\ DNorR_{NO1}&\rightarrow\\ DNorR_{NO2}&\rightarrow\\ NorR_{NO}&\rightarrow\\ mRNA_{Bxb1}&\rightarrow\\ \end{align*}

Name	Description
NO	Nitric Oxyde produced from DETA/NO reaction
NorR	NorR constitutively produced insideE. coli cells
NorRNO	NorR with No boundE. coli cells
DNorR	Dimer of NorR , regulatory protein PnorV operon
DNorRNO1	Dimer with one NO bound to one of its site
DNorRNO2	Dimer two NO bound to it
PnorVi	PnorV promoter with i sites occupied by DNoRNO2
PnorV3	PnorV3 is the active promoter

Deterministic simulation

As a first approach, considering that the amount of nitric oxyde to detect in case of infection should be quite fast, we decided to deterministicaly simulate the system in order to have a quantitative idea of the behavior of the system

Stochastic simulation

However, the output of the NO module is the number of PnorV promoter activated by the NO. This number, at a cell level is between 1 and 15, so noise may play an important role in the system behavior, that is why a stochastic simulation may, in case of low NO level, be interested in order to get deeper insight on the system response to NO.

AHL sensor

In the absence of AHL, EsaR is constitutively produced, dimerizes and bind as a dimer to the esaBox situated downstream the promoter, preventing transcription as a roadblock. When a higher than normal amount of AHL is present in the gut, it binds to the EsaR dimer, and free the promoter, allowing transcription. Later on, several EsaBox can be added, in order to tune the sensor sensitivity.

Assumption

Chemical species, reaction and equations

EsaR Hybrid Promoter System:

\begin{align*} &\rightarrow EsaR\\ 2 EsaR & \rightleftharpoons DEsaR\\ AHL+DEsaR &\rightleftharpoons DEsaR_{AHL1}\\ AHL+DEsaR_{AHL1}&\rightleftharpoons DEsaR_{AHL2}\\ Pesar1+AHL&\rightleftharpoons Pesar1_{AHL1}\\ Pesar1_{AHL1}+AHL&\rightleftharpoons Pfree +DEsaR_{AHL2}\\ Pfree &\rightarrow mRNA_{GFP}\\ EsaR&\rightarrow\\ DEsaR&\rightarrow \\ DEsaR_{AHL1}&\rightarrow\\ DEsaR_{AHL2}&\rightarrow\\ mRNA_{GFP} &\rightarrow\\ \end{align*}

Esar Reporter System:

\begin{align*} &\rightarrow EsaR\\ 2 EsaR & \rightleftharpoons DEsaR\\ AHL+DEsaR&\rightleftharpoons DEsaR_{AHL1}\\ AHL+DEsaR_{AHL1} & \rightleftharpoons DEsaR_{AHL2}\\ Pesar2+AHL&\rightleftharpoons Pesar2_{AHL1}\\ Pesar2_{AHL1}+AHL&\rightleftharpoons Pout+DEsaR_{AHL2}\\ Pout &\rightarrow mRNA_{GFP}\\ EsaR&\rightarrow \\ DEsaR&\rightarrow \\ DEsaR_{AHL1}&\rightarrow\\ DEsaR_{AHL2}&\rightarrow\\ mRNA_{GFP} &\rightarrow\\ \end{align*}

Name	Description
AHL	Acyl Homocerine Lactone introduced in the medium
EsaR	EsaR constitutively produced insideE. coli cells
DEsaR	Dimer of EsaR , regulatory protein binding to Esaboxes situated downstream the promoter
DEsaRAHL1	Dimer with one AHL bound to one of its site
DEsaRAHL2	Dimer with two AHL bound to one of its site
DNorRNO2	Dimer two NO bound to it
Pesari	Pesar1 correspond to the hybrid promoter. Pesar1 is the reporter promoter. They are independant
Pfree Pout respectively	prmoter freed from the road block constituted by the EsaR bound to the downstream esaboxes

Deterministic simulation

first approach, high input -> enought for a good inderstanding of the system behavior

Stochastic simulation

However the output is a amount of freed promoter at a cell level. As our cells only contain around 15 plasmid so stochastic modeling may be interesting

Lactate sensor

The promoter if flanked of two LldR specific binding sites : O1 and O2. In the absence of of lactate, LldR and LldD are constitutively produced. LldR then binds to O1 and O2 as a dimer, forms a DNA loop and preventing transcription. When Lactate (Lac) is present, it binds to the LldR complex and free the promoter. LldD lowers the concentration of Lactate inside the cell by catalyzing its transformation into pyruvate. The idea is to set a tunable treshold to the Lactate sensor, as this species, just like AHL, is anyway always present in the gut, and we only want to sense abnormal concentration.

Reaction

Lactate system:

\begin{align*} &\rightarrow LldD\\ &\rightarrow LldR\\ LldD+Lac&\rightleftharpoons Pyr+LldD\\ 2LldR&\rightleftharpoons DLldR\\ DLldR+ G_on&\rightleftharpoons G_off\\ DLldR + Lac&\rightleftharpoons DLldR_{Lac1}\\ DLldR_{Lac1}+Lac&\rightleftharpoons DLldR_{Lac2}\\ G_off + Lac&\rightleftharpoons G_off_1\\ G_off_1 + Lac&\rightleftharpoons G_on + DLldR_{Lac2}\\ G_on&\rightleftharpoons mRNA_{GFP}\\ LldD&\rightarrow\\ LldR&\rightarrow\\ DLldR&\rightarrow\\ DLldR_{Lac1}&\rightarrow\\ DLldR_{Lac2}&\rightarrow\\ \end{align*}

Name	Description
LldR	regulatory protein of the Lac system, acts as a repressor
DLldR	Dimer of LldR
Lac	Lactate introduced in the medium. Forms a complex with LldR, preventing it from repressing the Promoter. Acts thus as an activatorE. coli cells
PyrNO	Pyruvate, inactive form of lactateE. coli cells
LldD	Regulatory protein, catalyse the oxydation of Lactate into Pyruvate
G_onNO1	Active promoter
G_offNO2	Promoter repressed by LldR binding
G_off_1NO2	Repressed promoter with 1 lactate molecule bound
DLldR_Lac1i	DLldR with one Lactate molecule boundNO2
DLldR_Lac23	DLldR with two Lactate molecule bound

Deterministic simulation

high input, nice behavior.

Stochastic simulation

always the output issue.

Full AND Gate

Now it is time to link the two previous modules together in order to create the full AND Gate. Ideally, we would like to keep the model as modular as possible. In a first part, our way to proceed in order to recreate the hybrid promoter behavior from the two simple PnorV+Esabox promoter will be described. Then we propose a second model which takes into account all the different states of the promoter under NO and AHL/lactate binding, that can be stochastically simulated.

Full state model

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modular model

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