Multicellular entities are characterized by intricate spatial patterns, intimately related to the functions they perform. These patterns are often created from isotropic embryonic structures, without external information cues guiding the symmetry breaking process. Mature biological structures frequently display characteristic scales with periodic distributions of signals or chemical species across space. A general mechanism to explain these structures was found by Alan Turing, involving substances diffusing in space and interacting with one another in an Activator-Inhibitor motif. However, evidence and practical knowledge allowing us to engineer symmetry breaking and patterning processes is still lacking. In particular, recent research has shown that although Turing Patterns are ubiquitous in random interaction networks, they are rarely robust to parameter changes. In this talk, I will discuss a different approach by using modeling and synthetic biology to explore the pattern forming capabilities of Turing-adjacent mechanisms. These make use of the physical embodiment of the patterning agents, a feature sometimes overlooked in the field, in order to robustly create periodic structures. Understanding how patterns emerge in this larger class of mechanisms is important to further our understanding of the evolution of biocomplexity and the role played by self-organization in it.

Drylands (areas where it rains less than 35% of what is evaporated) are the vastest biome on Earth and host more than 2 billion people whose livelihood strongly depends on the services provided by ecosystem that they inhabit. Within these areas climate change will worsen water shortages, increasing aridity experienced by these ecosystems. Of particular concern is the fact that changes imposed by increasing aridity may occur abruptly rather than gradually. Here I summarize the research done globally to unveil whether abrupt changes in key ecosystem attributes and functions are common in drylands and which ecosystem attributes are most affected by them. I report: i) three aridity thresholds unchaining abrupt changes in different attributes and functions of drylands as  aridity increases in environmental gradients, ii) that dynamics of ecosystem productivity are also predominantly abrupt in drylands and match some of the thresholds announced and iii) that soil moisture dynamics shows a marked threshold behaviour depending on soil organic carbon, pointing into some mechanisms that may explain abrupt changes in drylands.

The engineering of biology strives on the creation of biological devices concerning society-impact applications. We have developed mathematical and experimental tools for the standard and rational design of living devices for biomedical purposes, offering robust and reliable responses. By breaking-up cellular device complexity into functional modules, we have analysed how extracellular information is detected, processed and transformed thanks to re-engineering intrinsic cellular components. We show how the desired range of action of a biosensor could be tuned by modifying the relative levels from two-component receptors’ biosensors. Regarding information processing, combining multicellularity and space permits to develop a 2D multi-branch approach inspired from printed electronics, allowing to perform logic computation by transferring device complexity into the geometrical arrangement. Sensing and processing capabilities have been applied as a proof-of-concept for the design of cellular devices for Diabetes Mellitus. Treating the cellular device closed-loop response as the fourth-functional module allowed to in silico decipher device characteristics on glycaemia regulation and design novel strategies based on dietary modulation, putting the manifest the need to combine both experimental and computational tools for living device application-based designs.

The risk exposure to mosquito-borne disease  depends critically on the dynamics of human-mosquito interactions. The latter are highly heterogeneous in time and space and despite there are methods for measuring mosquito activity and risk exposure at the local scale (e.g. human landing catch), these measurements are difficult to upscale in space or to obtain at adequate temporal resolution. More recently, the use of novel technologies (mobile phones and the Internet) combined with active citizen participation to collect key mosquito-related information opens the opportunity to obtain data on human-mosquito interactions at an unprecedented level of detail.

In this work, we model mosquito encounters from data collected with the Mosquito Alert citizen science platform. We focus on the Asian tiger mosquito (i.e. Aedes albopictus) as one of the most concerning disease vectors in Spain and across Europe, capable of transmitting dengue, chikungunya, Zika, and yellow fever among other arboviruses.  First, we model participation dynamics across age-classes using the complete Mosquito Alert dataset. Second, we derive the number of mosquito encounters per human and unit time in the city of Barcelona along the year 2020, and show how this measure correlates with mosquito abundances obtained from mosquito traps deployed in the city.