A bioenergetic model to predict habitability, biomass and biosignatures in astrobiology and extreme conditions

Rebuilding the Habitable Zone from the Bottom up with Computational Zones

Computation, if treated as a set of physical processes that act on information represented by states of matter, encompasses biological systems, digital systems, and other constructs and may be a fundamental measure of living systems. The opportunity for biological computation, represented in the propagation and selection-driven evolution of information-carrying organic molecular structures, has been partially characterized in terms of planetary habitable zones (HZs) based on primary conditions such as temperature and the presence of liquid water. A generalization of this concept to computational zones (CZs) is proposed, with constraints set by three principal characteristics: capacity (including computation rates), energy, and instantiation (or substrate, including spatial extent). CZs naturally combine traditional habitability factors, including those associated with biological function that incorporate the chemical milieu, constraints on nutrients and free energy, as well as element availability. Two example applications are presented by examining the fundamental thermodynamic work efficiency and Landauer limit of photon-driven biological computation on planetary surfaces and of generalized computation in stellar energy capture structures (a.k.a. Dyson structures). It is suggested that CZs that involve nested structures or substellar objects could manifest unique observational signatures as cool far-infrared emitters. While these latter scenarios are entirely hypothetical, they offer a useful, complementary introduction to the potential universality of CZs.

The minimum energy required to build a cell

Understanding the energy requirements for cell synthesis accurately and comprehensively has been a longstanding challenge. We introduce a computational model that estimates the minimum energy necessary to build any cell from its constituent parts. This method combines omics and internal cell compositions from various sources to calculate the Gibbs Free Energy of biosynthesis independently of specific metabolic pathways. Our public tool, Synercell, can be used with other models for minumum species-specific energy estimations in any well-sequenced species. The energy for synthesising the genome, transcriptome, proteome, and lipid bilayer of four cell types: Escherichia coli, Saccharomyces cerevisiae, an average mammalian cell and JCVI-syn3A were estimated. Their modelled minimum synthesis energies at 298 K were 9.54 × 10 - 11 J/cell, 4.99 × 10 - 9 J/cell, 3.71 × 10 - 7 J/cell and 3.69 × 10 - 12 respectively. Gram-for-gram synthesis of lipid bilayers requires the most energy, followed by the proteome, genome, and transcriptome. The average per gram cost of biomass synthesis is in the 300s of J/g for all four cells. Implications for the generalisability of cell construction and applications to biogeosciences, cellular biology, biotechnology, and astrobiology are discussed.

Linking Methanogenesis in Low-Temperature Hydrothermal Vent Systems to Planetary Spectra: Methane Biosignatures on an Archean-Earth-like Exoplanet

In this work, the viability of the detection of methane produced by microbial activity in low-temperature hydrothermal vents on an Archean-Earth-like exoplanet in the habitable zone is explored via a simplified bottom-up approach using a toy model. By simulating methanogens at hydrothermal vent sites in the deep ocean, biological methane production for a range of substrate inflow rates was determined and compared to literature values. These production rates were then used, along with a range of ocean floor vent coverage fractions, to determine likely methane concentrations in the simplified atmosphere. At maximum production rates, a vent coverage of 4-15 × 10^-4 % (roughly 2000-6500 times that of modern Earth) is required to achieve 0.25% atmospheric methane. At minimum production rates, 100% vent coverage is not enough to produce 0.25% atmospheric methane. NASA's Planetary Spectrum Generator was then used to assess the detectability of methane features at various atmospheric concentrations. Even with future space-based observatory concepts (such as LUVOIR and HabEx), our results show the importance of both mirror size and distance to the observed planet. Planets with a substantial biomass of methanogens in hydrothermal vents can still lack a detectable, convincingly biological methane signature if they are beyond the scope of the chosen instrument. This work shows the value of coupling microbial ecological modeling with exoplanet science to better understand the constraints on biosignature gas production and its detectability.

Biologically Available Chemical Energy in the Temperate but Uninhabitable Venusian Cloud Layer: What Do We Want to Know?

The cloud layer has been hypothesized to be the most habitable region of Venus. In the lower clouds, both temperature and pressure fall within bounds that support reproduction of microbial life on Earth, although the water activity of the sulfuric acid cloud droplets makes the clouds uninhabitable to known life. In this study, we carried out an analysis of CHNOPS (carbon, hydrogen, nitrogen, oxygen, phosphorus, sulfur) elements and potential redox couples in the cloud layer, and we used a microbial energetic growth model to investigate quantitatively the chemical energy available for microbial growth from methanogenesis, sulfate reduction, and hydrogen oxidation at temperatures between 278 and 350 K. The purpose was to improve knowledge of how far the venusian cloud layer comes from being habitable. Hydrogen oxidation was favorable at all temperatures; however, negative Gibbs free energies for sulfate reduction and methanogenesis depended critically on the assumed concentrations of electron donors, acceptors, and products. Improved measurements and the investigation of new molecules will allow us to better assess quantitatively how far Venus comes from possessing a habitable cloud layer and what would need to be different to make it habitable. We identify specific required measurements. These data will advance our understanding of the habitability of planetary atmospheres on extrasolar greenhouse worlds and the habitability of Earth when the planet eventually enters a greenhouse state.