Description

The Project

Bacteriophage infection represents an interesting process in science and industry. The idea of being able to contend at a population level with such infections is the main motivation for the development of our project.

We propose a population level approach relaying on a defense system delivered by an engineered version of the enterobacteria phage P4. The purpose of the defense construction is to make a bacteria to hold back the process of infection by triggering a cellular death response when a cell encounters a specific component of the infective phage. Such response will be fast enough to stop the formation process of viral particles, thus preventing the phage proliferation and population decline.

Delivery of the defense system take advantage of the satellite properties of P4 phage. This means that a P4 phage engineered with the defense construction will be able to infect an E.coli strain which harbors some genes from the helper phage P2 that are used for complementing and completing P4 life cycle, hence creating a production line of our version of P4.
On the other hand the defense system will consist of DNA and RNA degradation by toxins which will be transcribed by T3 or T7 RNA-Polymerases fast enough to stop phage assembly and scattering in the environment. Simultaneously, a quorum sensing signal will be difunding to the non-infected bacterias acting as a transcriptional activator of an antisense RNA against bacteriophage's transcriptional machinery , hence "warning" the population to prepare against further T3 or T7 infection.

Furthermore, we will implement a stochastic population model based on the basic properties of the bacterial cells and the phages such as movement, reproduction, etc. The model will make simulations of the infection processes and quantification of the efficiency of our system possible.

Design

Delivery

Defence

A virus infection is a process that takes place inside and individual but the real consequences of the infection become important at the population scale. In order to efficiently and accurately simulate the behaviour of our system we need to implement two different kinds of approaches: an individual-based simulation and a population simulation.
We designed a kamikaze system that will prevent the spreading of phage infection. We fused T7’s promoter with toxin E3 and GFP genes. Naive T7 will infect protected E. Coli which will start producing toxins that deactivate ribosomes. The result: No translation Machinery, no phages production and a heroic bacterium’s death. We expect the burst size to be significantly reduced when our system is working.

We designed and implemented a stochastic simulation for the essential reactions involved in the infection process: T7’s DNA insertion, transcription, translation, capsid assembly, toxins production, DNA degradation etc. With a fairly big number of simulations we are going to generate probability distributions for the number of molecules for each metabolite as a function of time. We are particularly interested in the Burst-Size Distribution (BSD); the burst-size is the number of phages an infected cell will produce.

Once we have the BSD we are ready for the Spatial Population Model. The kamikaze system we designed is meant to increase the probability that the population as a whole survive an infection process. We make infected-E. Coli commit suicide for the benefit of the population. In case suicide wasn’t altruistic enough we thought an ‘’alarm system’’ might be useful. Once a bacterium is infected it will use Quorum Sensing to communicate the message that phages are near, advised bacteria will produce antisense RNA against phage DNA Polymerase.

To simulate this system we used two different approaches:

We solved the system of Ordinary Differential Equations (ODE’s) described in REFERENCE and We designed and implemented a Cellular Automaton (CA).

Using the CA we simulate:

• Bacteria’s duplication, movement, infection and lysis.
• AHL and T7 Diffusion.
• The alarm system.

So let’s put all together:

Parameters of the events occurring in the CA are random variables that take values according to a corresponding Probability Distribution. We have distributions from literature and distributions generated by our simulations. So, for instance, when a bacterium gets infected we sample the Burst-Size Distribution, when a bacterium duplicate we sample the Duplication Time Distribution to assign lifetime to the newborn bacteria and so on. Sampling the distributions is the link between kinetic and population simulations: Random Variables in the population simulations take values from the kinetic simulations and voila we have our multi-scale stochastic model.

System Specifications

Construction:
E Coli Strain:
Toxins:
Bacteriophages:

Model Validation

We expect the Burst-Size to be significantly reduced. An optimal result would be a Burst-Size of 0; we see in our results that this is not the case. The BSD has mean ___ and variance___. We can calculate the likelihood of the model (BSD) given the observed burst size for both the wild type and modified E.Coli. The CA and the ODE’s generate growth curves that can be compared with those obtained experimentally.

Relevance of the project

Application areas

Bacteria play a fundamental role in human life. They are still the preferred models in science for the study of the molecular dynamics of organisms; probiotics are of vital importance in industry and food manufacturing. Infection by phages represents a relevant and expensive problem. That is the reason why we decided to construct a system to contend bacteriophage infection.

Portability

The project is designed in such a way that contributes on molecular biology as well as on industry. Our aim is to achieve this by making the defense system portable enough to be used as a tool for protection of profitable bacteria. With portability we mean that we will be able to work with the device in a wide range of bacterial species. Because of the system activation relies on the presence of the replication machinery of the infectious phage not depending on the identity of the protected bacteria, thus leaving the possibility to modify the multi promoter that controls the device to be triggered against specific phages. In the other hand, phage P4 seems to be able to infect a wide range of bacteria, which would contribute to the portability of the system.

Defence approach

An important artefact concerning with the defense system is the use of toxins as the main element in the disruption of phage’s assembly and scattering. Even though the contention of the infection implies that some bacteria will die, the use of a RNAse and a DNAse induces a delay of the phages production by beating host machinery. This in turn, avoids the possibility of the phage to getting resistance against toxins.

Using a population approach makes feasible to achieve a faster and wider protection response by amplifying the infection signal of the delivery phage in order to increase the number of "immune" bacteria at every lytic cycle.

Standarization and delivery

Standardization of biobricks has become an alternative in the development of easier and more profitable tools for genetic engineering. In this context, our project takes advantage of the phages property for infecting and transducing genetic material into bacteria. We will modify P4 bacteriophage in such a way that facilitates gene cloning into phage’s genome for its subsequent transduction into bacteria harboring the P2 genes for completing lytic cycle of the carrier phage and its exponential release.