Biology subjects

Pla-Mauri, J.

Publications and source records attributed to Pla-Mauri, J..

4 recordsLinked to original sources

bioRxiv2026

Animals or plants? Evolutionary branching of sessile versus mobile cognitive agents in noisy environments

The evolution of complex cognition has been tied to movement and the need to locate resources in uncertain environments. Plants present a striking contrast: despite sophisticated environmental responses, their sessile lifestyle involves predictable energy capture and growth-mediated foraging. What ecological conditions could separate these alternative strategies? We address this question using spatially explicit individual-based simulations and Adaptive Dynamics models in which evolving agents allocate resources between harvesting a stable energy source (light) and exploiting patchy, fluctuating resources through costly sensing and movement. Starting from intermediate generalists, evolution repeatedly produces two contrasting specialist lineages: sessile, light-dependent agents that abandon sensing and locomotion, and mobile foragers that sacrifice light harvesting while investing in active resource search. Spatial gradients promote divergence through niche partitioning, but specialization also emerges in homogeneous environments through frequency-dependent ecological feedbacks, showing that environmental heterogeneity is not required. Under linear or convex returns, intermediate strategies can be disadvantaged because they bear the costs of both resource-acquisition systems without fully exploiting either; under sufficiently concave returns, intermediate strategies may instead be favored. These results suggest that plant- and animal-based organizations can emerge as alternative evolutionary solutions to a common foraging problem. More broadly, they support the idea that the evolution of costly cognitive machinery depends critically on the statistical structure of the resources that organisms must find and exploit.

evolutionary biology↗

bioRxiv2026

Ecological constraints to mirror life

Our biosphere exhibits remarkable diversity yet is constrained by universal organizational principles, including molecular homochirality. Advances in synthetic biology have raised the possibility of engineering alternative life forms based on mirror-image biomolecules, prompting both technological interest and biosecurity concerns. While current discussions of mirror life largely emphasize molecular feasibility and cellular function, its potential establishment in natural environments remains poorly understood. Here, we develop a theoretical framework to assess the invasion potential of mirror organisms within existing ecosystems. Using population-level models that incorporate resource competition, metabolic constraints, and ecological network interactions, we show that mirror life might face severe limitations arising from both nutrient incompatibility and competitive exclusion by established biota. In particular, the reliance on rare or achiral substrates and the asymmetry of interactions with natural organisms constrain growth and persistence across a broad range of ecological conditions. These results highlight the importance of ecological constraints in evaluating the risks and feasibility of synthetic life.

ecology↗

bioRxiv2025

Engineering Basal Cognition: Minimal Genetic Circuits for Habituation, Sensitization, and Massed-Spaced Learning

Cognition is often associated with complex brains, yet many forms of learning--such as habituation, sensitization, and even spacing effects--have been observed in single cells and aneural organisms. These simple cognitive abilities, despite their cost, offer evolutionary advantages by allowing organisms to reduce environmental uncertainty and improve survival. Recent studies have confirmed early claims of learning-like behavior in protists and slime molds, pointing to the presence of basal cognitive functions long before the emergence of nervous systems. In this work, we adopt a synthetic biology approach to explore how minimal genetic circuits can implement non-associative learning in unicellular and multicellular systems. Building on theoretical models and using well-characterized regulatory elements, we design and simulate synthetic circuits capable of reproducing habituation, sensitization, and the massed-spaced learning effect. Our designs incorporate activators, repressors, fluorescent reporters, and quorum-sensing molecules, offering a platform for experimental validation. By examining the structural and dynamical constraints of these circuits, we highlight the distinct temporal dynamics of gene-based learning systems compared to neural counterparts and provide insights into the evolutionary and engineering challenges of building synthetic cognitive behavior at the cellular level.

synthetic biology↗

bioRxiv2025

A Minimal Genetic Circuit for Cellular Anticipation

Living systems have evolved cognitive complexity to reduce environmental uncertainty, enabling them to predict and prepare for future conditions. Anticipation, distinct from simple prediction, involves active adaptation before an event occurs and is a key feature of both neural and aneural biological agents. Building on the moving average convergence-divergence principle from financial trend analysis, we propose an implementation of anticipation through synthetic biology by designing and evaluating experimentally testable minimal genetic circuits capable of anticipating environmental trends. Through deterministic and stochastic analyses, we demonstrate that these motifs achieve robust anticipatory responses under a wide range of conditions. Our findings suggest that simple genetic circuits could be naturally exploited by cells to prepare for future events, providing a foundation for engineering predictive biological systems.

synthetic biology↗