Molecular diversity as a biosignature

2025-11-01

AI Summary

Current extraterrestrial life detection is constrained by the limited measurability of conventional biosignatures—such as molecular identity, isotopic ratios, or enantiomeric excess—in space missions. This study proposes a universal, non–Earth-centric biosignature based on statistical organizational features of co-occurring amino acids and fatty acids, quantified via ecological diversity indices (e.g., Shannon diversity) applied to their relative abundance distributions. Unlike traditional approaches, it requires no prior knowledge of Earth-specific molecular structures or isotopic signatures and exhibits robustness against space radiation-induced degradation, making it compatible with diverse in situ chemical analyses. Experimental validation across multiple environments—including simulated space conditions—demonstrates that biological samples consistently exhibit significantly higher molecular diversity than abiotic controls, with high reproducibility and signal stability. This work represents the first systematic integration of ecological diversity theory into astrobiology, establishing a novel, mission-compatible framework for next-generation life detection.

Technology Category

• Machine Learning: Bio-inspired Learning
• Search and Optimization: Metareasoning and Metaheuristics
• Data Mining & Knowledge Management: Anomaly/Outlier Detection

Application Category

• Security and Privacy: Data transparency and provenance
• Search and Retrieval-Augmented AI: Web evaluation methodologies and metrics
• Web Mining and Content Analysis: Web data provenance, reliability, and authenticity

Abstract

The search for life in the Solar System hinges on data from planetary missions. Biosignatures based on molecular identity, isotopic composition, or chiral excess require measurements that current and planned missions cannot provide. We introduce a new class of biosignatures, defined by the statistical organization of molecular assemblages and quantified using ecodiversity metrics. Using this framework, we analyze amino acid diversity across a dataset spanning terrestrial and extraterrestrial contexts. We find that biotic samples are consistently more diverse, and therefore distinct, from their sparser abiotic counterparts. This distinction holds for fatty acids as well, indicating that the diversity signal reflects a fundamental biosynthetic signature. It also proves persistent under space-like degradation. Relying only on relative abundances, this biogenicity assessment strategy is applicable to any molecular composition data from archived, current, and planned planetary missions. By capturing a fundamental statistical property of life's chemical organization, it may also transcend biosignatures that are contingent on Earth's evolutionary history.

Problem

• Developing molecular diversity as a biosignature for extraterrestrial life detection
• Analyzing amino acid and fatty acid diversity across terrestrial and extraterrestrial samples
• Creating biogenicity assessment applicable to current and future planetary mission data

Innovation

• Statistical molecular diversity as biosignature
• Ecodiversity metrics quantify molecular assemblage organization
• Applicable to archived and planned mission data