Genetic variability and structuring of deep Corallium rubrum (Linnaeus, 1758) populations

ABSTRACT Given the decline of shallow-water red coral populations resulting from over-exploitation and mass mortality events, deeper populations below 50 metres depth (mesophotic populations) are currently the most harvested; unfortunately, very little is known about their biology and ecology. The persistence of these populations is tightly linked to their adult density, reproductive success, larval dispersal and recruitment. Moreover, for their conservation, it is paramount understand processes such as connectivity within and among populations. Here, for the first time, genetic variability and structuring of Corallium rubrum populations collected in the Tyrrhenian Sea ranging from 58 to 118 metres were analyzed using ten microsatellite loci and two mitochondrial markers (mtMSH and MtC). The aims of the work were 1) to examine patterns of genetic diversity within each geographic area (Elba, Ischia and Praiano) and 2) to define population structuring at different spatial scales (from tens of metres to hundreds of kilometres). Based on microsatellite data set, significant deviations from Hardy-Weinberg equilibrium due to elevated heterozygote deficiencies were detected in all samples, probably related to the presence of null alleles and/or inbreeding, as was previously observed in shallow-water populations. Moreover, significant levels of genetic differentiation were observed at all spatial scale, suggesting a recent isolation of populations. Biological factors which act at small spatial scale and/or abiotic factors at larger scale (e.g. summer gyres or absence of suitable substrata for settlement) could determine this genetic isolation. Using mitochondrial markers, significant differences were found only at wider scale (between Tuscany and Campania regions). These results could be related to the different mutation rate of the molecular makers or to the occurrence of some historical links within regions. A significant isolation by distance pattern was then observed using both data sets, confirming the restricted larval dispersal capability of the species. Therefore, the hypothesis that deeper populations may act as a source of larvae helping recovery of threatened shallow-water populations is not proved. Conservation strategies have to take into account these results, and management plans of deep and currently harvested populations have to be defined at a regional or sub regional level, similarly to shallow-water populations. Nevertheless, further investigations should be needed to understand better the genetic structuring of this species in the mesophotic zone, e.g. extending studies to other Mediterranean deep-water populations.

Genetic structure and connectivity between populations of two common Mediterranean sessile invertebrates

Population genetic and phylogeography of two common mediterranean species were studied in 10 localities located on the coasts of Toscana, Puglia and Calabria. The aim of the study was to verify the extent of genetic breaks, in areas recognized as boundaries between Mediterranean biogeographic sectors. From about 100 sequences obtained from the mitochondrial Cytochrome Oxidase subunit I (COI) gene of Halocynthia papillosa and Hexaplex trunculus genetic diversity, genetic structure at small and large distances and demographic history of both specieswere analyzed. No evidences of genetic breaks were found for the two species in Toscana and Puglia. The genetic structure of H. trunculus evidences the extent of a barrier to gene flow localized in Calabria, which could be represented by the Siculo-Tunisian Strait and the Strait of Messina. The observed patterns showed similar level of gene flow at small distances in both species, although the two species have different larval ecology. These results suggest that other factors, such as currents, local dynamics and seasonal temperatures, influence the connectivity along the Italian peninsula. The geographic distribution of the haplotypes shows that H. papillosacould represent a single genetic pool in expansion, whereas H. trunculus has two distinct genetic pools in expansion. The demographic pattern of the two species suggests that Pleistocene sea level oscillations, in particular of the LGM, may have played a key role in shaping genetic structure of the two species. This knowledge provides basic information, useful for the definition of management plans, or for the design of a network of marine protected areas along the Italian peninsula.

Modeling and simulation of a synthetic genetic circuit that implements a multicelled behavior in a growing microcolony of E. coli

Synthetic Biology is a relatively new discipline, born at the beginning of the New Millennium, that brings the typical engineering approach (abstraction, modularity and standardization) to biotechnology. These principles aim to tame the extreme complexity of the various components and aid the construction of artificial biological systems with specific functions, usually by means of synthetic genetic circuits implemented in bacteria or simple eukaryotes like yeast. The cell becomes a programmable machine and its low-level programming language is made of strings of DNA. This work was performed in collaboration with researchers of the Department of Electrical Engineering of the University of Washington in Seattle and also with a student of the Corso di Laurea Magistrale in Ingegneria Biomedica at the University of Bologna: Marilisa Cortesi. During the collaboration I contributed to a Synthetic Biology project already started in the Klavins Laboratory. In particular, I modeled and subsequently simulated a synthetic genetic circuit that was ideated for the implementation of a multicelled behavior in a growing bacterial microcolony. In the first chapter the foundations of molecular biology are introduced: structure of the nucleic acids, transcription, translation and methods to regulate gene expression. An introduction to Synthetic Biology completes the section. In the second chapter is described the synthetic genetic circuit that was conceived to make spontaneously emerge, from an isogenic microcolony of bacteria, two different groups of cells, termed leaders and followers. The circuit exploits the intrinsic stochasticity of gene expression and intercellular communication via small molecules to break the symmetry in the phenotype of the microcolony. The four modules of the circuit (coin flipper, sender, receiver and follower) and their interactions are then illustrated. In the third chapter is derived the mathematical representation of the various components of the circuit and the several simplifying assumptions are made explicit. Transcription and translation are modeled as a single step and gene expression is function of the intracellular concentration of the various transcription factors that act on the different promoters of the circuit. A list of the various parameters and a justification for their value closes the chapter. In the fourth chapter are described the main characteristics of the gro simulation environment, developed by the Self Organizing Systems Laboratory of the University of Washington. Then, a sensitivity analysis performed to pinpoint the desirable characteristics of the various genetic components is detailed. The sensitivity analysis makes use of a cost function that is based on the fraction of cells in each one of the different possible states at the end of the simulation and the wanted outcome. Thanks to a particular kind of scatter plot, the parameters are ranked. Starting from an initial condition in which all the parameters assume their nominal value, the ranking suggest which parameter to tune in order to reach the goal. Obtaining a microcolony in which almost all the cells are in the follower state and only a few in the leader state seems to be the most difficult task. A small number of leader cells struggle to produce enough signal to turn the rest of the microcolony in the follower state. It is possible to obtain a microcolony in which the majority of cells are followers by increasing as much as possible the production of signal. Reaching the goal of a microcolony that is split in half between leaders and followers is comparatively easy. The best strategy seems to be increasing slightly the production of the enzyme. To end up with a majority of leaders, instead, it is advisable to increase the basal expression of the coin flipper module. At the end of the chapter, a possible future application of the leader election circuit, the spontaneous formation of spatial patterns in a microcolony, is modeled with the finite state machine formalism. The gro simulations provide insights into the genetic components that are needed to implement the behavior. In particular, since both the examples of pattern formation rely on a local version of Leader Election, a short-range communication system is essential. Moreover, new synthetic components that allow to reliably downregulate the growth rate in specific cells without side effects need to be developed. In the appendix are listed the gro code utilized to simulate the model of the circuit, a script in the Python programming language that was used to split the simulations on a Linux cluster and the Matlab code developed to analyze the data.