# Evolutionary Algorithms in a Bacterial Consortium of Synthetic Bacteria
## 2 Materials and Methods  
### Microbial Community or Consortium Meta-Model  
Nowadays, most of the synthetic bacteria are programmed according to a _top-down_ strategy. That is, the genetic circuitry is computer-designed to suit the task that the bacterium is expected to perform. The programmed expression of the genes through a certain model of regulation of the genetic network will result in a certain cellular behavior that will be displayed by the synthetic bacteria. Once the genetic circuit is designed, it is inserted into a plasmid (Figure 1), i.e., into a circular extrachromosomal DNA molecule that is independent of the chromosomal DNA. To draw an analogy between genetics and a computer, the plasmid plays the role of the code, either a script or a program in a computer. Thus, while the synthetic bacterium is the shell or 'computer' whose dynamic behavior, e.g., the control of cell division, is governed by the chromosomal DNA, the expression of the genes carried by the plasmid plays the role that corresponds to the execution of a program in a computer. The top-down strategy applied to the design of synthetic bacteria is actually the classic protocol used by engineers to design the devices or mechanisms of a car, a microwave oven, or any other machine or device.  
In this paper, we propose the design of synthetic bacteria by applying a _bottom-up_ strategy. That is to say, bacteria are evolutionarily programmed either as a colony or as a bacterial consortium. A bacterial colony is a bacterial population resulting from the multiplication of a strain or species of bacteria. Likewise, a microbial consortium is a community of microbes formed by two or more groups of bacterial strains or species. Therefore, whether it is a colony or a consortium, we start with some features present in the bacteria that will progressively acquire a particular behavior or cellular response, i.e., output (Figure 1). In our meta-model, the evolution of bacteria is the result of the temporal changes that take place in the colony or microbial community.  
In the present work, we studied two possible bottom-up scenarios. On the one hand, we studied the programming of synthetic bacteria through a Darwinian evolutionary model using an evolutionary algorithm that we termed BAGA. In this case, the mutation experienced in bacteria leads to random changes in the genetic circuit present in their plasmid. Depending on the configuration of the resulting genetic circuit, so too will be the adaptability or fitness of the bacterium. If the fitness value increases, the bacterial growth rate of a given species will also increase, and consequently the number of bacteria belonging to that species will grow.  
On the other hand, we studied the design of communities of synthetic bacteria considering in this case that the change in the number of bacteria of each strain or species resulted from social interactions between bacteria. That is, assuming bacteria of different species, bacteria of one species interact with bacteria of another species by emitting chemical signals to the environment. Once the signals are emitted, they will have a positive or negative effect on other neighboring bacteria depending on their species. If the molecule released into the environment by an emitting bacterium of a given species has a positive effect on the receiving bacterium of another species, then the bacterial growth rate of the latter will increase, thereby increasing the number of bacteria of that species.  
Indeed, whether it is Darwinian evolution or the effect of social interactions among bacterial species, the bottom-up protocol assumes as a guiding principle that evolution, i.e., the change in the number of synthetic bacteria, will be the result of the bacterial growth rate or Malthusian parameter adjustment. In other words, evolution is the result of the change in the value of the parameter of the equation governing the growth or colony size of a bacterial strain.