Proteome allocation and the evolution of metabolic cross-feeding

Metabolic cross-feeding (MCF) is a widespread type of ecological interaction where organisms share nutrients. In a common instance of MCF, an organism incompletely metabolizes sugars and releases metabolites that are used by another as a carbon source to produce energy. Why would the former waste edible food, and why does this preferentially occur at specific locations in the sugar metabolic pathway (acetate and glycerol are preferentially exchanged) have challenged evolutionary theory for decades. After showing that cells should in principle prioritise upstream reactions, we investigate how a special feature of these metabolites - their high diffusivity across the cell membrane - may trigger the emergence of cross feeding in a population. We explicitly model metabolic reactions, their enzyme-driven catalysis, and the cellular constraints on the proteome that may incur a cost to expressing all enzymes along the metabolic pathway. We find that up to high permeability coefficients of an intermediate metabolite, the expected evolutionary outcome is not a diversification that resembles cross-feeding but a single genotype that instead overexpresses the enzymes downstream the metabolite to limit its diffusion. Only at very high permeabilities and under restricted sets of parameters should the population diversify and MCF evolve.

Comparison Between Lotka-Volterra and Multivariate Autoregressive Models of Ecological Interaction Systems

Lotka-Volterra (LV) and Multivariate Autoregressive (MAR) models are computational frameworks with different mathematical structures that have both been proposed for the same purpose of extracting governing features of dynamic interactions among coexisting populations of different species from observed time series data.We systematically compare the feasibility of the two modeling approaches, using four synthetically generated datasets and seven ecological datasets from the literature.The overarching result is that LV models outperform MAR models in most cases and are generally superior for representing cases where the dependent variables deviate greatly from their steady states. A large dynamic range is particularly prevalent when the populations are highly abundant, change considerably over time, and exhibit a large signal-to-noise ratio. By contrast, MAR models are better suited for analyses of populations with low abundances and for investigations where the quantification of noise is important.We conclude that the choice of either one or the other modeling framework should be guided by the specific goals of the analysis and the dynamic features of the data.Availability of algorithms usedhttps://github.com/LBSA-VoitLab/Comparison-Between-LV-and-MAR-Models-of-Ecological-Interaction-Systems

The Biodiversity of Ecological Interactions: Challenges for recording and documenting the Web of Life

Biodiversity is more than a collection of individual species. It is the combination of biological entities and processes supporting life on Earth: no single species persists without interacting with other species. A full account of biodiversity on Earth needs to document the essential ecological interactions that support Earth’s system through their functional outcomes. Quantifying biodiversity’s interactome (the whole suite of interactions among biotic organisms) is challenging not just because of the daunting task of describing ecosystem complexity, it’s also limited by the need to define and establish a proper grammar to record and catalog species interactions. Actually, a record of a pairwise interaction between two species can be identified as a "tetranomial species", with just a concatenation of the two Latin binomials. Thus sampling interactions requires solving exactly the same constraints and problems we face when sampling biodiversity. In real interaction webs, the number of actual pairwise interactions among species in local assemblages scales exponentially with species richness. I discuss the main components of these interactions and those that are key to properly sample and document them. Interactions take the form of predation, competition, commensalism, amensalism, mutualism, symbiosis, and parasitism and, in all cases, involve reciprocal effects for the interacting species and build into highly complex networks (Fig. 1). The type of metadata required to document ecological interactions between partner species depends on interaction type; yet a fraction of these metadata is shared with those of the partner species. The interaction type sets limits to between-species encounters (actually, encounters between individuals of the partner species) and, more importantly, sets the type of outcome emerging from the interactions. There is a broad range of information that can eventually be acquired when recording an ecological interaction: from its simple presence (the interaction exists, it's been just recorded) to an estimate of its frequency, to obtaining data about its outcome or per-interaction effect (e.g., number of flowers pollinated in a visit by a pollinator to a plant). In addition, the types of interaction data can be quite diverse, reflecting the variety of sampling methods: interaction records from direct observation in the field; camera-traps; DNA-barcoding; bibliographic sources; surveys of image databases, etc. Interaction biodiversity inventories may require merging information coming from these distinct data sources. All these components need to be properly defined in order to build informative metadata and to document ecological interaction records. We are just starting to delineate the main components needed to catalog and inventory ecological interactions as a part of biodiversity inventories.

Human-Nature Ecological Interaction of African Traditional Community in Chinua Achebe’s Things Fall Apart (Literary Ecology Approach in Literature)

This research paper discusses the ecological interaction between humans and nature in African traditional Ibo tribe community as described in a literary work of Chinua Achebe’s Things Fall Apart by using literary ecology approach in literature. The result of the research indicates that African traditional tribe community has a good, intense interaction and has a harmonious life with nature, for instances, they learn to mingle familiarly with dry season, rainy season, and harmattan season for a successful farming method and harvest of yam, they also learn to interact very well with various kinds of vegetations such as bamboo, kola nut, banana leaves, grasses, roots, barks of trees to fulfil their life necessities, and they learn to have knowledge for an effective interaction and good usage of animals for ritual and meal, especially goat and locust. African traditional community also has a strong commitment to keep the harmonious relationship with nature by maintaining a life balance with nature including vegetation and animal, to enjoy living in happiness with nature by warmly welcoming various seasons, such as rainy season, dry season, and the cold dusty harmattan season, and to maintain natural resources friendly and wisely in clearing the new land for planting staple-food plants and other supporting plants sufficiently.

Does size really matter?

Analysis of the smallest known arthropod genome reveals a mechanism for genome reduction that appears to be driven by a specialized ecological interaction with plants.