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One of the most delicate stages of an evolutionary algorithm is the evaluation of the goodness of the solutions by some procedure providing a fitness value. However, although there are general rules, it is not always easy to find an appropriate evaluation function for a given problem. In the biological realm, today, there is a variety of experimental methods under the name of microbial screening to identify and select bacteria from their traits, as well as to obtain their fitness. In this paper, we show how given an optimization problem, a colony of synthetic bacteria or bacterial agents is able to evaluate the fitness of candidate solutions by building an evaluation function. The evaluation function is obtained simulating, in silico, a bacterial colony conducting the laboratory methods used in microbiology, biotechnology and synthetic biology to measure microbial fitness. Once the evaluation function is built, it is included in the code of the genetic algorithm as part of the fitness routine. The practical use of this approach is illustrated in two classic optimization problems. In silico routines have been programmed in Gro, a cell programming language oriented to synthetic biology, and can easily be customized to many other optimization problems.

Metaheuristics (MH) are Artificial Intelligence procedures that frequently rely on evolution. MH approximate difficult problem solutions, but are computationally costly as they explore large solution spaces. This work pursues to lay the foundations of general mappings for implementing MH using Synthetic Biology constructs in cell colonies. Two advantages of this approach are: harnessing large scale parallelism capability of cell colonies and, using existing cell processes to implement basic dynamics defined in computational versions. We propose a framework that maps MH elements to synthetic circuits in growing cell colonies to replicate MH behavior in cell colonies. Cell-cell communication mechanisms such as quorum sensing (QS), bacterial conjugation, and environmental signals map to evolution operators in MH techniques to adapt to growing colonies. As a proof-of-concept, we implemented the workflow associated to the framework: automated MH simulation generators for the gro simulator and two classes of algorithms (Simple Genetic Algorithms and Simulated Annealing) encoded as synthetic circuits. Implementation tests show that synthetic counterparts mimicking MH are automatically produced, but also that cell colony parallelism speeds up the execution in terms of generations. Furthermore, we show an example of how our framework is extended by implementing a different computational model: The Cellular Automaton., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 Ortiz, Carrión, Lahoz-Beltrá and Gutiérrez.)

When a new type of individual appears in a stable population, the newcomer is typically not advantageous. Due to stochasticity, the new type can grow in numbers, but the newcomers can only become advantageous if they manage to change the environment in such a way that they increase their fitness. This dynamics is observed in several situations in which a relatively stable population is invaded by an alternative strategy, for instance the evolution of cooperation among bacteria, the invasion of cancer in a multicellular organism and the evolution of ideas that contradict social norms. These examples also show that, by generating different versions of itself, the new type increases the probability of winning the struggle for fitness. Our model captures the imposed cooperation whereby the first generation of newcomers dies while changing the environment such that the next generations become more advantageous., (Copyright © 2018 Elsevier Inc. All rights reserved.)

Morphological stomatal traits, such as size, form and frequency, have been subject of much literature, including their relationships with environmental factors. However, little effort have focused on ferns, and very few in the genus Blechnum. Stomatal length, width and frequency (as stomatal index) of a number of specimens of fourteen Neotropical species of Blechnum were measured in adult pinnae. The aim of the work was to find biometrical relationships between stomatal traits and between stomatal traits and habit, habitat and ecosystem of the plants. Statistical analyses of data were conducted using Exploratory Data Analysis and Multivariate Statistical Methods. Stomatal length and width showed a very high correlation, suggesting an endogenous, genetic control, thus giving these traits a considerable diagnostic utility. With respect to the relationships between stomatal traits and environment, we found significant statistical relationships between altitude and stomatal index. We also addressed the interpretation of the ecological-selective significance of various assemblages of stomatal traits in a diverse conjunction of habits, habitats and ecosystems.

A proliferating population of cells may be considered complex when its proliferative or growth fraction P is lower than 1 and/or when it is formed by subpopulations with different mean cycle times. The present paper shows that in such complex populations exponential growth is consistent with a steady-state distribution of cells. Obviously, when P=1 then cell distribution is only a function of cell age. An analytical model has been developed to study complex populations including both quiescent fractions formed by cells with unreplicated genome (G(0) cells) and cells with fully duplicated chromosomes (Q(2) cells). The model also considers those quasi-quiescent cells in their last transit through G(1) and S (Q(1) and Q(s) cells) before becoming quiescent. In order to solve the difficulties of a direct analysis of the whole population, its kinetic parameters have been obtained by studying the negative exponential distribution of two subpopulations: one formed by the proliferating cells and another formed by the quasi-quiescent cells. Additionally, the model could be applied when quiescence is initiated at any other cycle phase different from G(1) and G(2), for instance, cells in the process of replicating their DNA or being at any other mitotic phases. The utility of the method was illustrated in populations which constitute the root meristems of both Allium cepa L. and Pisum sativum L. Three facts should be stressed: (1) the method seems to be rather powerful because it can be carried out from different sets of experimentally measured parameters; (2) the rate of division and, therefore, the population doubling time can be easily estimated by this method; and (3) it also allows the determination of the amount of cells that had become quiescent either before they had replicated their DNA (G(0)) or after having completed their replication (Q(2)), as well as those quasi-quiescent cells which are progressing throughout their last pre-replicative and replicative periods (thus Q(1) and Q(s), respectively)., (Copyright 2002 Elsevier Science Ltd. All rights reserved.)

The kinetics of the autolytic phase of growth in cultures of Aspergillus niger has been studied. Two different autolytic periods could be distinguished. One, consisting of a rapid (exponential) loss (62%) of mycelial weight, occurred between 36 and 117 hours of incubation. A second, consisting of a slow autolysis, occurred between the 117th and the 190th hour of incubation; the mycelial loss here being 5%. Based on the degree of autolysis (alpha = 67.0%), 92.5% and 7.5% are lost during the first and the second autolytic periods, respectively.