The search for life in the universe has traditionally focused on "habitability"—a binary state largely defined by the presence of liquid water and equilibrium temperatures (
We propose that an exoplanetary atmosphere should not be viewed merely as a gas envelope, but as a potential planetary biome. By integrating terrestrial extremophile biology, atmospheric chemistry simulations, and topological analysis of Chemical Reaction Networks (CRNs), we aim to model how life acts as a global pressure that reshapes its environment.
Core Philosophy: "Life is not just something that happens on a planet; it is a thermodynamic process that happens to a planet."
This repository will serve as the central data lake and documentation hub for the Exobioma roadmap. Our research is driven by three fundamental questions:
- Beyond The Goldilocks Zone: Can we quantify the "biological capacity" of an atmosphere using strictly measured extremophilic tolerances rather than Earth-centric assumptions?
- The Ecological Imprint: How does a microbial biosphere modify the chemical complexity of an atmosphere over geological timescales?
- Observational Reality: Can we link high-complexity indices in atmospheric networks to specific volatile organic compounds (VOCs) detectable by JWST and ARIEL?
The Exobioma Project is structured into five distinct developmental phases.
- Goal: Introduction of the MLS (Multiparametric Life Score) paradigm.
- Method: Mapping terrestrial extremophile limits (Temperature, Pressure, UV/X-Ray flux) onto simulated exoplanetary atmospheric layers.
- Output: Creation of "Atmospheric Tomography" maps identifying viable ecological niches in vertical atmospheric columns.
- Codebase: See our companion repository for the MLS calculation engine and visualization tools.
- Goal: Building
MLS 2.0. - Focus: Expanding the database beyond terrestrial analogs. Integrating theoretical biochemistries and metabolic pathways suitable for non-standard environments (e.g., high-pressure ice, hydrocarbon lakes).
- Goal: Simulating atmospheric impacts.
- Focus: Moving from static "suitability" to dynamic interaction. Using kinetic modeling to simulate how a thriving biomass impacts atmospheric composition (consumption of substrates, release of byproducts).
- Goal: Linking MLS to Biosignatures.
- Focus: Application of Network Theory to chemical reaction pathways. Identifying "topological anomalies" in atmospheric CRNs that betray the presence of non-equilibrium biological drivers.
- Goal: Observational Validation.
- Focus: Direct comparison of Exobioma model predictions with high-resolution spectroscopic data from the ARIEL mission and future HWO concepts.
We stand at a unique intersection in history. We have the biological data (from decades of microbiology and extremophile research) and, for the first time, the observational power (JWST, ARIEL) to test our hypotheses.
However, data without a framework is noise. The Exobioma Project seeks to build the theoretical scaffold that allows us to interpret the spectral signals of the coming decade.
This repository is currently being populated.
/Data: Future home for the Unified Extremophile Database and CRN topology datasets./Docs: White papers, theoretical frameworks, and supplementary material for publications./Models: Long-term storage for atmospheric impact simulation outputs.
For the active code regarding the MLS algorithm and Python visualization tools, please refer to the author's primary code repository.
Principal Investigator: marco.marcellino@inaf.it
INAF - Osservatorio Astronomico di Palermo Focus: Molecular Biology & Computational Astrobiology
We welcome collaboration from:
- Microbiologists (specializing in poly-extremophiles).
- Atmospheric Physicists (specializing in 1D/3D climate modeling).
- Data Scientists (specializing in Network Theory and Topology).
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