Punctuated equilibrium at 50: Anything there for evolutionary anthropology? Yes; definitely.

The theory of punctuated equilibrium (PE) was developed a little over 50 years ago to explain long-term, large-scale appearance and disappearance of species in the fossil record. A theory designed specifically for that purpose cannot be expected, out of the box, to be directly applicable to biocultural evolution, but in revised form, PE offers a promising approach to incorporating not only a wealth of recent empirical research on genetic, linguistic, and technological evolution but also large databases that document human biological and cultural diversity across time and space. Here we isolate the fundamental components of PE and propose which pieces, when reassembled or renamed, can be highly useful in evolutionary anthropology, especially as humanity faces abrupt ecological challenges on an increasingly larger scale.

A cultural evolutionary theory that explains both gradual and punctuated change.

Cumulative cultural evolution (CCE) occurs among humans who may be presented with many similar options from which to choose, as well as many social influences and diverse environments. It is unknown what general principles underlie the wide range of CCE dynamics and whether they can all be explained by the same unified paradigm. Here, we present a scalable evolutionary model of discrete choice with social learning, based on a few behavioural science assumptions. This paradigm connects the degree of transparency in social learning to the human tendency to imitate others. Computer simulations and quantitative analysis show the interaction of three primary factors-information transparency, popularity bias and population size-drives the pace of CCE. The model predicts a stable rate of evolutionary change for modest degrees of popularity bias. As popularity bias grows, the transition from gradual to punctuated change occurs, with maladaptive subpopulations arising on their own. When the popularity bias gets too severe, CCE stops. This provides a consistent framework for explaining the rich and complex adaptive dynamics taking place in the real world, such as modern digital media.

Ecological firewalls for synthetic biology.

It has been recently suggested that engineered microbial strains could be used to protect ecosystems from undesirable tipping points and biodiversity loss. A major concern in this context is the potential unintended consequences, which are usually addressed in terms of designed genetic constructs aimed at controlling overproliferation. Here we present and discuss an alternative view grounded in the nonlinear attractor dynamics of some ecological network motifs. These ecological firewalls are designed to perform novel functionalities (such as plastic removal) while containment is achieved within the resident community. That could help provide a self-regulating biocontainment. In this way, engineered organisms have a limited spread while-when required-preventing their extinction. The basic synthetic designs and their dynamical behavior are presented, each one inspired in a given ecological class of interaction. Their possible applications are discussed and the broader connection with invasion ecology outlined.

Engineering self-organized criticality in living cells.

Complex dynamical fluctuations, from intracellular noise, brain dynamics or computer traffic display bursting dynamics consistent with a critical state between order and disorder. Living close to the critical point has adaptive advantages and it has been conjectured that evolution could select these critical states. Is this the case of living cells? A system can poise itself close to the critical point by means of the so-called self-organized criticality (SOC). In this paper we present an engineered gene network displaying SOC behaviour. This is achieved by exploiting the saturation of the proteolytic degradation machinery in E. coli cells by means of a negative feedback loop that reduces congestion. Our critical motif is built from a two-gene circuit, where SOC can be successfully implemented. The potential implications for both cellular dynamics and behaviour are discussed.

Synthetic Lateral Inhibition in Periodic Pattern Forming Microbial Colonies.

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 also display characteristic scales with repeating distributions of signals or chemical species across space. Many candidate patterning modules have been used to explain processes during development and typically include a set of interacting and diffusing chemicals or agents known as morphogens. Great effort has been put forward to better understand the conditions in which pattern-forming processes can occur in the biological domain. However, evidence and practical knowledge allowing us to engineer symmetry-breaking is still lacking. Here we follow a different approach by designing a synthetic gene circuit in E. coli that implements a local activation long-range inhibition mechanism. The synthetic gene network implements an artificial differentiation process that changes the physicochemical properties of the agents. Using both experimental results and modeling, we show that the proposed system is capable of symmetry-breaking leading to regular spatial patterns during colony growth. Studying how these patterns emerge is fundamental to further our understanding of the evolution of biocomplexity and the role played by self-organization. The artificial system studied here and the engineering perspective on embryogenic processes can help validate developmental theories and identify universal properties underpinning biological pattern formation, with special interest for the area of synthetic developmental biology.

Synthetic soil crusts against green-desert transitions: a spatial model.

Semiarid ecosystems are threatened by global warming due to longer dehydration times and increasing soil degradation. Mounting evidence indicates that, given the current trends, drylands are likely to expand and possibly experience catastrophic shifts from vegetated to desert states. Here, we explore a recent suggestion based on the concept of ecosystem terraformation, where a synthetic organism is used to counterbalance some of the nonlinear effects causing the presence of such tipping points. Using an explicit spatial model incorporating facilitation and considering a simplification of states found in semiarid ecosystems including vegetation, fertile and desert soil, we investigate how engineered microorganisms can shape the fate of these ecosystems. Specifically, two different, but complementary, terraformation strategies are proposed: Cooperation-based: C-terraformation; and Dispersion-based: D-terraformation. The first strategy involves the use of soil synthetic microorganisms to introduce cooperative loops (facilitation) with the vegetation. The second one involves the introduction of engineered microorganisms improving their dispersal capacity, thus facilitating the transition from desert to fertile soil. We show that small modifications enhancing cooperative loops can effectively modify the aridity level of the critical transition found at increasing soil degradation rates, also identifying a stronger protection against soil degradation by using the D-terraformation strategy. The same results are found in a mean-field model providing insights into the transitions and dynamics tied to these terraformation strategies. The potential consequences and extensions of these models are discussed.

Coexistence of nestedness and modularity in host-pathogen infection networks.

The long-term coevolution of hosts and pathogens in their environment forms a complex web of multi-scale interactions. Understanding how environmental heterogeneity affects the structure of host-pathogen networks is a prerequisite for predicting disease dynamics and emergence. Although nestedness is common in ecological networks, and theory suggests that nested ecosystems are less prone to dynamic instability, why nestedness varies in time and space is not fully understood. Many studies have been limited by a focus on single habitats and the absence of a link between spatial variation and structural heterogeneity such as nestedness and modularity. Here we propose a neutral model for the evolution of host-pathogen networks in multiple habitats. In contrast to previous studies, our study proposes that local modularity can coexist with global nestedness, and shows that real ecosystems are found in a continuum between nested-modular and nested networks driven by intraspecific competition. Nestedness depends on neutral mechanisms of community assembly, whereas modularity is contingent on local adaptation and competition. The structural pattern may change spatially and temporally but remains stable over evolutionary timescales. We validate our theoretical predictions with a longitudinal study of plant-virus interactions in a heterogeneous agricultural landscape.

Synthetic Biology for Terraformation Lessons from Mars, Earth, and the Microbiome.

What is the potential for synthetic biology as a way of engineering, on a large scale, complex ecosystems? Can it be used to change endangered ecological communities and rescue them to prevent their collapse? What are the best strategies for such ecological engineering paths to succeed? Is it possible to create stable, diverse synthetic ecosystems capable of persisting in closed environments? Can synthetic communities be created to thrive on planets different from ours? These and other questions pervade major future developments within synthetic biology. The goal of engineering ecosystems is plagued with all kinds of technological, scientific and ethic problems. In this paper, we consider the requirements for terraformation, i.e., for changing a given environment to make it hospitable to some given class of life forms. Although the standard use of this term involved strategies for planetary terraformation, it has been recently suggested that this approach could be applied to a very different context: ecological communities within our own planet. As discussed here, this includes multiple scales, from the gut microbiome to the entire biosphere.

Population dynamics of synthetic terraformation motifs.

Ecosystems are complex systems, currently experiencing several threats associated with global warming, intensive exploitation and human-driven habitat degradation. Because of a general presence of multiple stable states, including states involving population extinction, and due to the intrinsic nonlinearities associated with feedback loops, collapse in ecosystems could occur in a catastrophic manner. It has been recently suggested that a potential path to prevent or modify the outcome of these transitions would involve designing synthetic organisms and synthetic ecological interactions that could push these endangered systems out of the critical boundaries. In this paper, we investigate the dynamics of the simplest mathematical models associated with four classes of ecological engineering designs, named Terraformation motifs (TMs). These TMs put in a nutshell different ecological strategies. In this context, some fundamental types of bifurcations pervade the systems' dynamics. Mutualistic interactions can enhance persistence of the systems by means of saddle-node bifurcations. The models without cooperative interactions show that ecosystems achieve restoration through transcritical bifurcations. Thus, our analysis of the models allows us to define the stability conditions and parameter domains where these TMs must work.

Exploiting delayed transitions to sustain semiarid ecosystems after catastrophic shifts.

Semiarid ecosystems (including arid, semiarid and dry-subhumid ecosystems) span more than 40% of extant habitats and contain a similar percentage of the human population. Theoretical models and palaeoclimatic data predict a grim future, with rapid shifts towards a desert state, with accelerated diversity losses and ecological collapses. These shifts are a consequence of the special nonlinearities resulting from ecological facilitation. Here, we investigate a simple model of semiarid ecosystems identifying the so-called ghost, which appears after a catastrophic transition from a vegetated to a desert state once a critical rate of soil degradation is overcome. The ghost involves a slowdown of transients towards the desert state, making the ecosystem seem stable even though vegetation extinction is inevitable. We use this model to show how to exploit the ecological ghosts to avoid collapse. Doing so involves the restoration of small fractions of desert areas with vegetation capable of maintaining a stable community once the catastrophic shift condition has been achieved. This intervention method is successfully tested under the presence of demographic stochastic fluctuations.

Synthetic associative learning in engineered multicellular consortia.

Associative learning (AL) is one of the key mechanisms displayed by living organisms in order to adapt to their changing environments. It was recognized early as a general trait of complex multicellular organisms but is also found in 'simpler' ones. It has also been explored within synthetic biology using molecular circuits that are directly inspired in neural network models of conditioning. These designs involve complex wiring diagrams to be implemented within one single cell, and the presence of diverse molecular wires become a challenge that might be very difficult to overcome. Here we present three alternative circuit designs based on two-cell microbial consortia able to properly display AL responses to two classes of stimuli and displaying long- and short-term memory (i.e. the association can be lost with time). These designs might be a helpful approach for engineering the human gut microbiome or even synthetic organoids, defining a new class of decision-making biological circuits capable of memory and adaptation to changing conditions. The potential implications and extensions are outlined.