Enhancing iDynoMiCS framework with a plasmid conjugation module

Actualmente existen aplicaciones que permiten simular el comportamiento de bacterias en distintos hábitats y los procesos que ocurren en estos para facilitar su estudio y experimentación sin la necesidad de un laboratorio. Una de las aplicaciones de software libre para la simulación de poblaciones bacteriológicas mas usada es iDynoMiCS (individual-based Dynamics of Microbial Communities Simulator), un simulador basado en agentes que permite trabajar con varios modelos computacionales de bacterias en 2D y 3D. Este simulador permite una gran libertad al configurar una numerosa cantidad de variables con respecto al entorno, reacciones químicas y otros detalles importantes. Una característica importante es el poder simular de manera sencilla la conjugación de plásmidos entre bacterias. Los plásmidos son moléculas de ADN diferentes del cromosoma celular, generalmente circularles, que se replican, transcriben y conjugan independientemente del ADN cromosómico. Estas están presentes normalmente en bacterias procariotas, y en algunas ocasiones en eucariotas, sin embargo, en este tipo de células son llamados episomas. Dado el complejo comportamiento de los plásmidos y la gama de posibilidades que estos presentan como mecanismos externos al funcionamiento básico de la célula, en la mayoría de los casos confiriéndole distintas ventajas evolutivas, como por ejemplo: resistencia antibiótica, entre otros, resulta importante su estudio y subsecuente manipulación. Sin embargo, el marco operativo del iDynoMiCS, en cuanto a simulación de plásmidos se refiere, es demasiado sencillo y no permite realizar operaciones más complejas que el análisis de la propagación de un plásmido en la comunidad. El presente trabajo surge para resolver esta deficiencia de iDynomics. Aquí se analizarán, desarrollarán e implementarán las modificaciones necesarias para que iDynomics pueda simular satisfactoriamente y mas apegado a la realidad la conjugación de plásmidos y permita así mismo resolver distintas operaciones lógicas, como lo son los circuitos genéticos, basadas en plásmidos. También se analizarán los resultados obtenidos de acuerdo a distintos estudios relevantes y a la comparación de los resultados obtenidos con el código original de iDynomics. Adicionalmente se analizará un estudio comparando la eficiencia de detección de una sustancia mediante dos circuitos genéticos distintos. Asimismo el presente trabajo puede tener interés para el grupo LIA de la Facultad de Informática de la Universidad Politécnica de Madrid, el cual está participando en el proyecto europeo BACTOCOM que se centra en el estudio de la conjugación de plásmidos y circuitos genéticos. --ABSTRACT--Currently there are applications that simulate the behavior of bacteria in different habitats and the ongoing processes inside them to facilitate their study and experimentation without the need for an actual laboratory. One of the most used open source applications to simulate bacterial populations is iDynoMiCS (individual-based Dynamics of Microbial Communities Simulator), an agent-based simulator that allows working with several computer models of 2D and 3D bacteria in biofilms. This simulator allows great freedom by means of a large number of configurable variables regarding environment, chemical reactions and other important details of the simulation. Within these characteristics there exists a very basic framework to simulate plasmid conjugation. Plasmids are DNA molecules physically different from the cell’s chromosome, commonly found as small circular, double-stranded DNA molecules that are replicated, conjugated and transcribed independently of chromosomal DNA. These bacteria are normally present in prokaryotes and sometimes in eukaryotes, which in this case these cells are called episomes. Plasmids are external mechanisms to the cells basic operations, and as such, in the majority of the cases, confer to the host cell various evolutionary advantages, like antibiotic resistance for example. It is mperative to further study plasmids and the possibilities they present. However, the operational framework of the iDynoMiCS plasmid simulation is too simple, and does not allow more complex operations that the analysis of the spread of a plasmid in the community. This project was conceived to resolve this particular deficiency in iDynomics, moreover, in this paper is discussed, developed and implemented the necessary changes to iDynomics simulation software so it can satisfactorily and realistically simulate plasmid conjugation, and allow the possibility to solve various ogic operations, such as plasmid-based genetic circuits. Moreover the results obtained will be analyzed and compared with other relevant studies and with those obtained with the original iDynomics code. Conjointly, an additional study detailing the sensing of a substance with two different genetic circuits will be presented. This work may also be relevant to the LIA group of the Faculty of Informatics of the Polytechnic University of Madrid, which is participating in the European project BACTOCOM that focuses on the study of the of plasmid conjugation and genetic circuits.

Probabilistic reasoning with a bayesian DNA device based on strand displacement

We present a computing model based on the DNA strand displacement technique which performs Bayesian inference. The model will take single stranded DNA as input data, representing the presence or absence of a specific molecular signal (evidence). The program logic encodes the prior probability of a disease and the conditional probability of a signal given the disease playing with a set of different DNA complexes and their ratios. When the input and program molecules interact, they release a different pair of single stranded DNA species whose relative proportion represents the application of Bayes? Law: the conditional probability of the disease given the signal. The models presented in this paper can empower the application of probabilistic reasoning in genetic diagnosis in vitro.

Probabilistic reasoning with an enzyme-driven DNA device

We present a biomolecular probabilistic model driven by the action of a DNA toolbox made of a set of DNA templates and enzymes that is able to perform Bayesian inference. The model will take single-stranded DNA as input data, representing the presence or absence of a specific molecular signal (the evidence). The program logic uses different DNA templates and their relative concentration ratios to encode the prior probability of a disease and the conditional probability of a signal given the disease. When the input and program molecules interact, an enzyme-driven cascade of reactions (DNA polymerase extension, nicking and degradation) is triggered, producing a different pair of single-stranded DNA species. Once the system reaches equilibrium, the ratio between the output species will represent the application of Bayes? law: the conditional probability of the disease given the signal. In other words, a qualitative diagnosis plus a quantitative degree of belief in that diagno- sis. Thanks to the inherent amplification capability of this DNA toolbox, the resulting system will be able to to scale up (with longer cascades and thus more input signals) a Bayesian biosensor that we designed previously.