Lenia and Expanded Universe

We report experimental extensions of Lenia, a continuous cellular automata family capable of producing lifelike self-organizing autonomous patterns. The rule of Lenia was generalized into higher dimensions, multiple kernels, and multiple channels. The final architecture approaches what can be seen as a recurrent convolutional neural network. Using semi-automatic search e.g. genetic algorithm, we discovered new phenomena like polyhedral symmetries, individuality, self-replication, emission, growth by ingestion, and saw the emergence of "virtual eukaryotes" that possess internal division of labor and type differentiation. We discuss the results in the contexts of biology, artificial life, and artificial intelligence.Comment: 8 pages, 5 figures, 1 table; submitted to ALIFE 2020 conferenc

Self-Replicating Machines in Continuous Space with Virtual Physics

JohnnyVon is an implementation of self-replicating machines in continuous two-dimensional space. Two types of particles drift about in a virtual liquid. The particles are automata with discrete internal states but continuous external relationships. Their internal states are governed by finite state machines but their external relationships are governed by a simulated physics that includes Brownian motion, viscosity, and spring-like attractive and repulsive forces. The particles can be assembled into patterns that can encode arbitrary strings of bits. We demonstrate that, if an arbitrary "seed" pattern is put in a "soup" of separate individual particles, the pattern will replicate by assembling the individual particles into copies of itself. We also show that, given sufficient time, a soup of separate individual particles will eventually spontaneously form self-replicating patterns. We discuss the implications of JohnnyVon for research in nanotechnology, theoretical biology, and artificial life

Integrating transposable elements in the 3D genome

Chromosome organisation is increasingly recognised as an essential component of genome regulation, cell fate and cell health. Within the realm of transposable elements (TEs) however, the spatial information of how genomes are folded is still only rarely integrated in experimental studies or accounted for in modelling. Whilst polymer physics is recognised as an important tool to understand the mechanisms of genome folding, in this commentary we discuss its potential applicability to aspects of TE biology. Based on recent works on the relationship between genome organisation and TE integration, we argue that existing polymer models may be extended to create a predictive framework for the study of TE integration patterns. We suggest that these models may offer orthogonal and generic insights into the integration profiles (or "topography") of TEs across organisms. In addition, we provide simple polymer physics arguments and preliminary molecular dynamics simulations of TEs inserting into heterogeneously flexible polymers. By considering this simple model, we show how polymer folding and local flexibility may generically affect TE integration patterns. The preliminary discussion reported in this commentary is aimed to lay the foundations for a large-scale analysis of TE integration dynamics and topography as a function of the three-dimensional host genome

Procedural function-based modelling of volumetric microstructures

We propose a new approach to modelling heterogeneous objects containing internal volumetric structures with size of details orders of magnitude smaller than the overall size of the object. The proposed function-based procedural representation provides compact, precise, and arbitrarily parameterised models of coherent microstructures, which can undergo blending, deformations, and other geometric operations, and can be directly rendered and fabricated without generating any auxiliary representations (such as polygonal meshes and voxel arrays). In particular, modelling of regular lattices and cellular microstructures as well as irregular porous media is discussed and illustrated. We also present a method to estimate parameters of the given model by fitting it to microstructure data obtained with magnetic resonance imaging and other measurements of natural and artificial objects. Examples of rendering and digital fabrication of microstructure models are presented

Polyphosphate granule biogenesis is temporally and functionally tied to cell cycle exit during starvation in Pseudomonas aeruginosa

Polyphosphate (polyP) granule biogenesis is an ancient and ubiquitous starvation response in bacteria. Although the ability to make polyP is important for survival during quiescence and resistance to diverse environmental stresses, granule genesis is poorly understood. Using quantitative microscopy at high spatial and temporal resolution, we show that granule genesis in Pseudomonas aeruginosa is tightly organized under nitrogen starvation. Following nucleation as many microgranules throughout the nucleoid, polyP granules consolidate and become transiently spatially organized during cell cycle exit. Between 1 and 3 h after nitrogen starvation, a minority of cells have divided, yet the total granule number per cell decreases, total granule volume per cell dramatically increases, and individual granules grow to occupy diameters as large as ∼200 nm. At their peak, mature granules constitute ∼2% of the total cell volume and are evenly spaced along the long cell axis. Following cell cycle exit, granules initially retain a tight spatial organization, yet their size distribution and spacing relax deeper into starvation. Mutant cells lacking polyP elongate during starvation and contain more than one origin. PolyP promotes cell cycle exit by functioning at a step after DNA replication initiation. Together with the universal starvation alarmone (p)ppGpp, polyP has an additive effect on nucleoid dynamics and organization during starvation. Notably, cell cycle exit is temporally coupled to a net increase in polyP granule biomass, suggesting that net synthesis, rather than consumption of the polymer, is important for the mechanism by which polyP promotes completion of cell cycle exit during starvation

The protozoan nucleus

The nucleus is arguably the defining characteristic of eukaryotes, distinguishing their cell organisation from both bacteria and archaea. Though the evolutionary history of the nucleus remains the subject of debate, its emergence differs from several other eukaryotic organelles in that it appears not to have evolved through symbiosis, but by cell membrane elaboration from an archaeal ancestor. Evolution of the nucleus has been accompanied by elaboration of nuclear structures that are intimately linked with most aspects of nuclear genome function, including chromosome organisation, DNA maintenance, replication and segregation, and gene expression controls. Here we discuss the complexity of the nucleus and its substructures in protozoan eukaryotes, with a particular emphasis on divergent aspects in eukaryotic parasites, which shed light on nuclear function throughout eukaryotes and reveal specialisations that underpin pathogen biology