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The presence of an atmosphere over sufficiently long timescales is widely perceived as one of the most prominent criteria associated with planetary surface habitability. We address the crucial question of whether the seven Earth-sized planets transiting the recently discovered ultracool dwarf star TRAPPIST-1 are capable of retaining their atmospheres. To this effect, we carry out numerical simulations to characterize the stellar wind of TRAPPIST-1 and the atmospheric ion escape rates for all of the seven planets. We also estimate the escape rates analytically and demonstrate that they are in good agreement with the numerical results. We conclude that the outer planets of the TRAPPIST-1 system are capable of retaining their atmospheres over billion-year timescales. The consequences arising from our results are also explored in the context of abiogenesis, biodiversity, and searches for future exoplanets. In light of the many unknowns and assumptions involved, we recommend that these conclusions must be interpreted with due caution.

Life emerged on Earth within the first quintile of its habitable window, but a technological civilization did not blossom until its last. Efforts to infer the rate of abiogenesis, based on its early emergence, are frustrated by the selection effect that if the evolution of intelligence is a slow process, then life’s early start may simply be a prerequisite to our existence, rather than useful evidence for optimism. In this work, we interpret the chronology of these two events in a Bayesian framework, extending upon previous work by considering that the evolutionary timescale is itself an unknown that needs to be jointly inferred, rather than fiducially set. We further adopt an objective Bayesian approach, such that our results would be agreed upon even by those using wildly different priors for the rates of abiogenesis and evolution—common points of contention for this problem. It is then shown that the earliest microfossil evidence for life indicates that the rate of abiogenesis is at least 2.8 times more likely to be a typically rapid process, rather than a slow one. This modest limiting Bayes factor rises to 8.7 if we accept the more disputed evidence of 13C-depleted zircon deposits [E. A. Bell, P. Boehnke, T. M. Harrison, W. L. Mao, Proc. Natl. Acad. Sci. U.S.A. 112, 14518–14521 (2015)]. For intelligence evolution, it is found that a rare-intelligence scenario is slightly favored at 3:2 betting odds. Thus, if we reran Earth’s clock, one should statistically favor life to frequently reemerge, but intelligence may not be as inevitable.

We present a comprehensive multiwavelength investigation into flares and activity in nearby M dwarf stars. We leverage the most extensive contemporaneous data set obtained through the Transiting Exoplanet Sky Survey, Kepler/K2, the Neil Gehrels Swift Observatory, and the Hubble Space Telescope, spanning the optical and near-ultraviolet (NUV) regimes. In total, we observed 213 NUV flares on 24 nearby M dwarfs, with ∼27% of them having detected optical counterparts, and found that all optical flares had NUV counterparts. We explore NUV/optical energy fractionation in M dwarf flares. Our findings reveal a slight decrease in the ratio of optical to NUV energies with increasing NUV energies, a trend in agreement with prior investigations on G–K stars’ flares at higher energies. Our analysis yields an average NUV fraction of flaring time for M0–M3 dwarfs of 2.1%, while for M4–M6 dwarfs it is 5%. We present an empirical relationship between NUV and optical flare energies and compare to predictions from radiative hydrodynamic and blackbody models. We conducted a comparison of the flare frequency distribution (FFDs) of NUV and optical flares, revealing that the FFDs of both NUV and optical flares exhibit comparable slopes across all spectral subtypes. NUV flares on stars affect the atmospheric chemistry, the radiation environment, and the overall potential to sustain life on any exoplanets they host. We find that early and mid-M dwarfs (M0–M5) have the potential to generate NUV flares capable of initiating abiogenesis.

We present a simple model for estimating the probability of interplanetary panspermia in the recently discovered system of seven planets orbiting the ultracool dwarf star TRAPPIST-1 and find that panspermia is potentially orders of magnitude more likely to occur in the TRAPPIST-1 system compared with the Earth-to-Mars case. As a consequence, we argue that the probability of abiogenesis is enhanced on the TRAPPIST-1 planets compared with the solar system. By adopting models from theoretical ecology, we show that the number of species transferred and the number of lifebearing planets are also likely to be higher because of the increased rates of immigration. We propose observational metrics for evaluating whether life was initiated by panspermia on multiple planets in the TRAPPIST-1 system. These results are also applicable to habitable exoplanets and exomoons in other planetary systems.

The aim of this article is to provide the reader with an overview of the different possible scenarios for the emergence of life, to critically assess them and, according to the conclusions we reach, to analyze whether similar processes could have been conducive to independent origins of life on the several icy moons of the Solar System. Instead of directly proposing a concrete and unequivocal cradle of life on Earth, we focus on describing the different requirements that are arguably needed for the transition between non-life to life. We approach this topic from geological, biological, and chemical perspectives with the aim of providing answers in an integrative manner. We reflect upon the most prominent origins hypotheses and assess whether they match the aforementioned abiogenic requirements. Based on the conclusions extracted, we address whether the conditions for abiogenesis are/were met in any of the oceanic icy moons.

Research on the origin of life is highly heterogeneous. After a peculiar historical development, it still includes strongly opposed views which potentially hinder progress. In the 1st Interdisciplinary Origin of Life Meeting, early-career researchers gathered to explore the commonalities between theories and approaches, critical divergence points, and expectations for the future. We find that even though classical approaches and theories—e.g., bottom-up and top-down, RNA world vs. metabolism-first—have been prevalent in origin of life research, they are ceasing to be mutually exclusive and they can and should feed integrating approaches. Here we focus on pressing questions and recent developments that bridge the classical disciplines and approaches, and highlight expectations for future endeavours in origin of life research.

Few traces of Earth’s geologic record are preserved from the time of life’s emergence, over 3,800 million years ago. Consequently, what little we understand about abiogenesis — the origin of life on Earth — is based primarily on laboratory experiments and theory. The best geological lens for understanding early Earth might actually come from Mars, a planet with a crust that’s overall far more ancient than our own. On Earth, surface sedimentary environments are thought to best preserve evidence of ancient life, but this is mostly because our planet has been dominated by high photosynthetic biomass production at the surface for the last ~2,500 million years or more. By the time oxygenic photosynthesis evolved on Earth, Mars had been a hyperarid, frozen desert with a surface bombarded by high-energy solar and cosmic radiation for more than a billion years, and as a result, photosynthetic surface life may never have occurred on Mars. Therefore, one must question whether searching for evidence of life in Martian surface sediments is the best strategy. This Perspective explores the possibility that the abundant hydrothermal environments on Mars might provide more valuable insights into life’s origins.

M-dwarfs are common stellar hosts of habitable-zone exoplanets. Near-UV (NUV) radiation can severely impact the atmospheric and surface conditions of such planets, making the characterization of NUV flaring activity a key aspect in determining habitability. We use archival data from the Galaxy Evolution Explorer (GALEX) and XMM-Newton telescopes to study the flaring activity of M-dwarfs in the NUV. The GALEX observations form the most extensive data set of M-dwarfs in the NUV to date, with the exploitation of this data possible due to the new gphoton2 pipeline. We run a dedicated algorithm to detect flares in the pipeline-produced lightcurves and find some of the most energetic flares observed to date within the NUV bandpass, with energies of ∼1034 erg. Using GALEX data, we constrain flare frequency distributions for stars from M0-M6 in the NUV up to 105 s in equivalent duration and 1034 erg in energy, orders of magnitude above any previous study in the UV. We estimate the combined effect of NUV luminosities and flare rates of stars later than M2 to be sufficient for abiogenesis on habitable-zone exoplanets orbiting them. As a counterpoint, we speculate the high frequencies of energetic UV flares and associated coronal mass ejections would inhibit the formation of an ozone layer, possibly preventing the genesis of complex Earth-like life-forms due to sterilizing levels of surface UV radiation. We also provide a framework for future observations of M-dwarfs with ULTRASAT, a wide field-of-view NUV telescope to be launched in 2026.

Abiogenesis has long been suspected to require that chemical reaction networks contain multiple autocatalytic cores, but little is known about what features of these networks allow for the gradual accretion of complexity. To identify realistic scenarios for the emergence of life-like properties, we develop the concept of a seed-dependent autocatalytic system (SDAS), which is a subnetwork that can autocatalytically self-maintain given a flux of food, but cannot be initiated by food alone. Rather, initiation of SDASs requires the transient introduction of chemical “seeds”. We show that, depending on the topological relationship of SDASs in a chemical reaction network, a food-driven system can accrete complexity in a historically contingent manner, governed by rare seeding events. We develop new algorithms for detecting and analyzing SDASs in chemical reaction databases and describe parallels between multi-SDAS networks and biological ecosystems. Applying our algorithms to both an abiotic reaction network and a biochemical one, each driven by a set of simple food chemicals, we detect SDASs that are organized as trophic tiers, of which the higher tier can be seeded by relatively simple chemicals if the lower tier is already activated. This indicates that sequential activation of trophically organized SDASs by seed chemicals that are not much more complex than what already exist could be a mechanism of gradual complexification from relatively simple abiotic reactions to more complex life-like systems. Interestingly, in both reaction networks, higher-tier SDASs include chemicals that might alter emergent features of chemical systems and could serve as early targets of selection. Our analysis provides computational tools for analyzing very large chemical/biochemical reaction networks and suggests new approaches to studying abiogenesis in the lab.

Estimating the plausibility of RNA self-reproduction is central to origin-of-life scenarios. However, this property has been shown in only a handful of catalytic RNAs. Here, we compare models for their generative power in diversifying a reference ribozyme, based on statistical covariation and secondary structure prediction, and experimentally test model predictions using high-throughput sequencing. Leveraging statistical physics methods, we compute the number of ribozymes capable of autocatalytic self-reproduction from oligonucleotide fragments to be over 10 39 , with sequences found up to 65 mutations from the original sequence and 99 mutations away from each other, far beyond the 10 mutations achieved by deep mutational scanning. The findings demonstrate an efficient method for exploring RNA sequence space, and provide quantitative data on self-reproducing RNA that further illuminates the potential pathways to abiogenesis. The spontaneous emergence of autocatalytic RNAs is central to origin of life. Here, the authors use machine learning, high-throughput screening and statistical physics to explore large neutral space of catalytic RNAs.