# A Microbial Screening in Silico Method for the Fitness Step Evaluation in Evolutionary Algorithms
## 2 Materials and Methods
### Microbial Screening Methods in Silico: Procedures and Implementation
For this reason, three reactions have been defined that will regulate the system: (a) obtaining glucose from biomass by the catalytic action of an enzyme, (b) lactose degradation by lacZ obtaining glucose and galactose and (c) degradation of galactose by an enzyme. * Chemotaxis: Although this biological phenomenon is not usually part of a laboratory experimental protocol, we have designed a screening procedure based on this bacterial behavior. Chemotaxis consists of directional locomotion of bacteria towards a source of a chemical stimulus. This movement is made possible by a structure called a flagellum. A motor drives the flagellum, consisting of a rotor and stator. Motor assembly was simulated in Reference [22], regulating its assembly via the temporal expression of specific operons [23; 24]. Gro routine (Appendix A, Figure A3) is inspired by the logic [25] of the molecular mechanism involved in bacterial chemotaxis (Figure 6) and in which Che proteins are the regulators of chemotaxis. The mechanism is not simulated in detail, but the function that simulates it is based on the messenger role of CheY protein. In short, the phosphorylation levels of this protein depend on signals from extracellular receptors for nutrients such as sugars or amino acids. A higher phosphorylation of CheY implies a more effective binding to the motor complex, allowing it to rotate effectively, and thus causing the bacteria to move in a specific direction. If CheY is not sufficiently phosphorylated then the binding to the motor complex is not effective, which translates into erratic movement by the bacterial cell. At a logical level, CheY checks the levels of certain nutrients, making the motor work at higher levels of phosphorylation. This behavior is modeled as follows: When the levels of an 'attractive' substance increase, then the levels of phosphorylation will allow an effective movement or 'run'. Conversely, when attractor levels decrease, then CheY phosphorylation declines, and then an erratic movement of the bacterium or 'tumble' is induced. Since the presence of a motor system represents a bacterial advantage by allowing its access to an area with an abundance of nutrients, the bacterial growth rate is related to the concentration of attractant substance that bacteria receives. Therefore, only those synthetic bacteria that incorporate the genes necessary to synthesize the motor machinery will succeed in the selection (Appendix A, Figure A3). The above routines were used to obtain the evaluation function, which in turn was used in the evolutionary SGA and SMGA algorithms. Next, and in order to study the usefulness of the method proposed to obtain the fitness function, the evolutionary algorithms were applied to solve two instances, one of the 0/1 knapsack problem and the other of the 2-SAT (2-satisfiability) problem. In the following, we describe the general methodology applied to obtain the evaluation function in each of the previously cited optimization problems.