Who Replaces Whom? Local versus Non-local Replacement in Social and Evolutionary Dynamics

In this paper, we inspect well-known population genetics and social dynamics models. In these models, interacting individuals, while participating in a self-organizing process, give rise to the emergence of complex behaviors and patterns. While one main focus in population genetics is on the adaptive behavior of a population, social dynamics is more often concerned with the splitting of a connected array of individuals into a state of global polarization, that is, the emergence of speciation. Applying computational and mathematical tools we show that the way the mechanisms of selection, interaction and replacement are constrained and combined in the modeling have an important bearing on both adaptation and the emergence of speciation. Differently (un)constraining the mechanism of individual replacement provides the conditions required for either speciation or adaptation, since these features appear as two opposing phenomena, not achieved by one and the same model. Even though natural selection, operating as an external, environmental mechanism, is neither necessary nor sufficient for the creation of speciation, our modeling exercises highlight the important role played by natural selection in the interplay of the evolutionary and the self-organization modeling methodologies.Comment: 14 pages, 11 figure

Integrated transcriptomic and proteomic analyses ofP. falciparumgametocytes: molecular insight into sex-specific processes and translational repression

Sexual differentiation of malaria parasites into gametocytes in the vertebrate host and subsequent gamete fertilization in mosquitoes is essential for the spreading of the disease. The molecular processes orchestrating these transitions are far from fully understood. Here, we report the first transcriptome analysis of male and female Plasmodium falciparum gametocytes coupled with a comprehensive proteome analysis. In male gametocytes there is an enrichment of proteins involved in the formation of flagellated gametes; proteins involved in DNA replication, chromatin organization and axoneme formation. On the other hand, female gametocytes are enriched in proteins required for zygote formation and functions after fertilization; protein-, lipid- and energy-metabolism. Integration of transcriptome and proteome data revealed 512 highly expressed maternal transcripts without corresponding protein expression indicating large scale translational repression in P. falciparum female gametocytes for the first time. Despite a high degree of conservation between Plasmodium species, 260 of these 'repressed transcripts' have not been previously described. Moreover, for some of these genes, protein expression is only reported in oocysts and sporozoites indicating that repressed transcripts can be partitioned into short- and long-term storage. Finally, these data sets provide an essential resource for identification of vaccine/drug targets and for further mechanistic studies

Primal Eukaryogenesis:On the Communal Nature of Precellular States, Ancestral to Modern Life

This problem-oriented, exploratory and hypothesis-driven discourse toward the unknown combines several basic tenets: (i) a photo-active metal sulfide scenario of primal biogenesis in the porespace of shallow sedimentary flats, in contrast to hot deep-sea hydrothermal vent conditions; (ii) an inherently complex communal system at the common root of present life forms; (iii) a high degree of internal compartmentalization at this communal root, progressively resembling coenocytic (syncytial) super-cells; (iv) a direct connection from such communal super-cells to proto-eukaryotic macro-cell organization; and (v) multiple rounds of micro-cellular escape with streamlined reductive evolution—leading to the major prokaryotic cell lines, as well as to megaviruses and other viral lineages. Hopefully, such nontraditional concepts and approaches will contribute to coherent and plausible views about the origins and early life on Earth. In particular, the coevolutionary emergence from a communal system at the common root can most naturally explain the vast discrepancy in subcellular organization between modern eukaryotes on the one hand and both archaea and bacteria on the other

Scalable phylogenetic profiling using MinHash uncovers likely eukaryotic sexual reproduction genes

Phylogenetic profiling is a computational method to predict genes involved in the same biological process by identifying protein families which tend to be jointly lost or retained across the tree of life. Phylogenetic profiling has customarily been more widely used with prokaryotes than eukaryotes, because the method is thought to require many diverse genomes. There are now many eukaryotic genomes available, but these are considerably larger, and typical phylogenetic profiling methods require at least quadratic time as a function of the number of genes. We introduce a fast, scalable phylogenetic profiling approach entitled HogProf, which leverages hierarchical orthologous groups for the construction of large profiles and locality-sensitive hashing for efficient retrieval of similar profiles. We show that the approach outperforms Enhanced Phylogenetic Tree, a phylogeny-based method, and use the tool to reconstruct networks and query for interactors of the kinetochore complex as well as conserved proteins involved in sexual reproduction: Hap2, Spo11 and Gex1. HogProf enables large-scale phylogenetic profiling across the three domains of life, and will be useful to predict biological pathways among the hundreds of thousands of eukaryotic species that will become available in the coming few years. HogProf is available at https://github.com/DessimozLab/HogProf

Biomimetic Engineering

Humankind is a privileged animal species for many reasons. A remarkable one is its ability to conceive and manufacture objects. Human industry is indeed leading the various winning strategies (along with language and culture) that has permitted this primate to extraordinarily increase its life expectancy and proliferation rate. (It is indeed so successful, that it now threatens the whole planet.) The design of this industry kicks off in the brain, a computing machine particularly good at storing, recognizing and associating patterns. Even in a time when human beings tend to populate non-natural, man-made environments, the many forms, colorings, textures and behaviors of nature continuously excite our senses and blend in our thoughts, even more deeply during childhood. Then, it would be exaggerated to say that Biomimetics is a brand new strategy. As long as human creation is based on previously acquired knowledge and experiences, it is not surprising that engineering, the arts, and any form of expression, is influenced by nature’s way to some extent. The design of human industry has evolved from very simple tools, to complex engineering devices. Nature has always provided us with a rich catalog of excellent materials and inspiring designs. Now, equipped with new machinery and techniques, we look again at Nature. We aim at mimicking not only its best products, but also its design principles. Organic life, as we know it, is indeed a vast pool of diversity. Living matter inhabits almost every corner of the terrestrial ecosphere. From warm open-air ecosystems to the extreme conditions of hot salt ponds, living cells have found ways to metabolize the sources of energy, and get organized in complex organisms of specialized tissues and organs that adapt themselves to the environment, and can modify the environment to their own needs as well. Life on Earth has evolved such a diverse portfolio of species that the number of designs, mechanisms and strategies that can actually be abstracted is astonishing. As August Krogh put it: "For a large number of problems there will be some animal of choice, on which it can be most conveniently studied". The scientific method starts with a meticulous observation of natural phenomena, and humans are particularly good at that game. In principle, the aim of science is to understand the physical world, but an observer’s mind can behave either as an engineer or as a scientist. The minute examination of the many living forms that surround us has led to the understanding of new organizational principles, some of which can be imported in our production processes. In practice, bio-inspiration can arise at very different levels of observation: be it social organization, the shape of an organism, the structure and functioning of organs, tissular composition, cellular form and behavior, or the detailed structure of molecules. Our direct experience of the wide portfolio of species found in nature, and their particular organs, have clearly favored that the initial models would come from the organism and organ levels. But the development of new techniques (on one hand to observe the micro- and nanostructure of living beings, and on the other to simulate the complex behavior of social communities) have significantly extended the domain of interest

Implications of Behavioral Architecture for the Evolution of Self-Organized Division of Labor

Division of labor has been studied separately from a proximate self-organization and an ultimate evolutionary perspective. We aim to bring together these two perspectives. So far this has been done by choosing a behavioral mechanism a priori and considering the evolution of the properties of this mechanism. Here we use artificial neural networks to allow for a more open architecture. We study whether emergent division of labor can evolve in two different network architectures; a simple feedforward network, and a more complex network that includes the possibility of self-feedback from previous experiences. We focus on two aspects of division of labor; worker specialization and the ratio of work performed for each task. Colony fitness is maximized by both reducing idleness and achieving a predefined optimal work ratio. Our results indicate that architectural constraints play an important role for the outcome of evolution. With the simplest network, only genetically determined specialization is possible. This imposes several limitations on worker specialization. Moreover, in order to minimize idleness, networks evolve a biased work ratio, even when an unbiased work ratio would be optimal. By adding self-feedback to the network we increase the network's flexibility and worker specialization evolves under a wider parameter range. Optimal work ratios are more easily achieved with the self-feedback network, but still provide a challenge when combined with worker specialization

Program and Abstracts, Neurospora 2012

Program and Abstracts from the Neurospora 2012 meeting at Asilomar, March 8 - 11