Microbial aerotrophy enables continuous primary production in diverse cave ecosystems

Domain: earth_science
Published: 2025-11-21
Editorial outcome: minor_revision

Abstract
Aerated caves receive minimal light energy, yet host diverse microbial communities and the strategies allowing them to meet energy and carbon needs remain unclear. We determined the processes and mediators of primary production in aerated limestone and basalt caves through paired metagenomic and biogeochemical profiling. Four caves were sampled, including sediments and biofilms, yielding 94 metagenomes. Based on 1458 metagenome-assembled genomes, over half of microbial cells encode enzymes to use atmospheric trace gases as energy and carbon sources. The most abundant microbes are chemosynthetic primary producers, notably the gammaproteobacterial methanotrophic order Ca. Methylocavales and two uncultivated actinobacterial genera predicted to grow on atmospheric hydrogen, carbon dioxide, and carbon monoxide. Biogeochemical and isotopic measurements confirmed that these gases are rapidly consumed at rates likely sustaining a substantial fraction of the community and potentially driving primary production. Conventional chemolithoautotrophs, using ammonium and sulfide, are also enriched and active. Altogether, these results indicate that caves are unique in microbial biodiversity and the biogeochemical processes sustaining them. Consumption of atmospheric trace gases likely has a dual role in caves, providing energy for microbial survival and potentially supporting chemosynthetic growth, thereby introducing organic carbon. This process, defined as ‘aerotrophy’, operates alongside organic and inorganic inputs.

Introduction
Terrestrial caves provide unique habitats for life, given that they are dark, humid, thermally insulated, and relatively isolated systems1,2. The sediments and mineral surfaces of caves harbour abundant and diverse microbiota. The nine dominant bacterial phyla from surface soils are also the most abundant microbes in caves, with most assumed to be aerobes dependent on organic carbon (i.e. organoheterotrophs)3–6. However, a long-standing question is how these microbes obtain sufficient carbon and energy to live in these environments with minimal photosynthesis7. Some caves receive extensive external inputs of organic matter (allochthonous sources), for example, due to seasonal flooding, groundwater percolation, or animal sources (e.g. bat guano8). However, these inputs are spatially and temporally variable9, and there is extensive evidence that most caves are highly nutrient-limited ecosystems10. It’s also well-recognised that chemosynthetic microbes produce organic matter (autochthonous sources) by harnessing the inorganic energy sources from reduced sulphur, nitrogen, and iron compounds present in drip water and mineral surfaces6,11–13. Given that these inorganic compounds generally occur in trace amounts, chemosynthetic processes are thought to play a minor role in cave microbial ecosystems, except in globally rare, deep geothermally-heated caves usually isolated from the surface13–18.

A potential alternative source of energy and carbon in typical cave ecosystems is the atmosphere itself. We have recently discovered that atmospheric molecular hydrogen (H2) and carbon monoxide (CO) are critical energy sources supporting the biodiversity of soils and waters worldwide, and enable complex ecosystems to form in oligotrophic environments such as Antarctic soils19–23. Bacteria use high-affinity hydrogenases and CO dehydrogenases to liberate electrons from these gases for aerobic respiration and carbon fixation via the Calvin–Benson–Bassham (CBB) cycle24. Aerobic methanotrophs, which use atmospheric methane (CH4) as a dual energy and carbon source25–27, have also been identified in various cave systems and mediate CH4 oxidation rates comparable to those of surface soils28–37. Considering these findings, we sought to disentangle the relative roles of atmospheric, rock-derived, and solar energy sources in supporting primary production and energy conservation in cave ecosystems. To do so, we integrated genome-resolved metagenomic profiling, in situ and ex situ biogeochemical and isotopic measurements, and thermodynamic modelling of sediment and biofilm microbial communities collected along transects from four aerated limestone and basalt caves sampled within Australia. Our results reveal that aerated caves host abundant communities of methane and hydrogen oxidisers, which continuously oxidise atmospheric trace gases to assimilate carbon and fix CO2. We predict that this process enables continuous growth, suggesting that aerated caves are potentially major systems sustained by aerotrophic primary production.

Results
Most cave microbes encode enzymes to harvest atmospheric energy sources
We studied four aerated caves in southeastern Australia, two limestone caves and two basalt lava tubes (Fig. 1a). In each cave, we sampled along a transect extending from the entrance to twilight, transition and deep zones. We collected a total of 94 environmental samples, including sediments, biofilm, and mineral samples, which were analysed using metagenomics as well as gas and isotopic studies to determine microbial composition, capabilities, and metabolic activity. The samples from the four caves (Fig. 1a, Supplementary Data 1) spanned a broad range of organic carbon (0.2–31.3%), pH (3.6–8.7), and moisture levels (10.8–55.8%). This suggests much spatial variability in their allochthonous supply of organic carbon and other resources, in support of previous studies7. Based on shotgun metagenomic profiling, microbial communities varied between cave sediments and biofilms, between rock types, and with cave depth (Fig. 1b–e; Supplementary Data 3a–c). Microbial abundance (av. 6.7×109 16S rRNA gene copies per gram of dry sediment) and richness (av. 450 taxa per sample; Chao1 based on metagenomic reads of 16S rRNA genes of sediment) decreased by 3.3-fold and 2-fold, respectively, between the cave entrance and interior sediments (Supplementary Data 2 and 3b). In line with most other sampled caves5, Actinobacteriota, Proteobacteria, Acidobacteriota, Chloroflexota and Gemmatimonadota were the most common phyla, along with Thermoproteota (predominantly Nitrosophaerales) (Fig. 1b; Supplementary Data 3c). Metagenomic assembly and binning yielded 1458 dereplicated high- and medium-quality metagenome-assembled genomes (MAGs) spanning 35 different phyla, including one unclassified (Supplementary Data 4c).

The energy and carbon acquisition strategies of the cave microbes are inferred by searching for 52 conserved marker genes encoding the potential of key energy and carbon acquisition processes in the MAGs and short reads (Fig. 2a; Supplementary Data 4a–c). These analyses suggested that most cave bacteria mediate aerobic respiration using both organic compounds and trace gases as substrates (Fig. 2a, b). 44% of MAGs, accounting for 54% of mapped metagenomic reads (Supplementary Data 4c), encode enzymes to consume one or more atmospheric trace gases, namely form I CO dehydrogenases for CO oxidation (25.4% genomes/74.3% community based on short reads; Supplementary Fig. 1), group 1 and 2 [NiFe]-hydrogenases for H2 oxidation (25.8%/43%; Supplementary Fig. 2), and particulate methane monooxygenases for CH4 oxidation (2.9%/5.5%; Supplementary Fig. 3). These findings suggest that most microbial cells in caves encode enzymes that could enable trace gas oxidation. A smaller proportion of cave microbes can also use rock-derived energy sources such as sulphide (13.9%/18%), thiosulfate (6.7%/7%), ammonia (4.1%/3.5%; Supplementary Fig. 4), nitrite (1.2%/3.7%; Supplementary Fig. 5), and ferrous iron (2.7%/2.2%).

As expected, photosynthesis genes were abundant in sediments and biofilms at the entrance of each cave (29%) but declined by an average of 73-fold in the cave interior. Conversely, there were marked increases in cave interior compared to entrance communities for the genes enabling the oxidation of CH4 (7.3-fold), ammonium (1.5-fold), nitrite (2.3-fold), sulphide (1.4-fold), H2 (2-fold, average group 1h & 1l [NiFe]-hydrogenases) and CO (1.1-fold). Concordant patterns were observed for carbon fixation genes, with the photosynthetic cyanobacterial Type IB RuBisCO decreasing 39-fold, and the chemosynthetic, predominantly actinobacterial Type IE RuBisCO increasing 2-fold in cave interiors compared to entrances (Supplementary Data 4b, c; Fig. 2a, b; Supplementary Fig. 6). Some carbon fixation also likely occurs through primarily 4-hydroxybutyrate cycle (3.6%/2.2%), reductive tricarboxylic acid cycle (1.6%/2%), and 3-hydroxypropionate cycle (0.9%/0.7%). Altogether, these findings indicate a shift from photosynthetic to chemosynthetic primary production in cave ecosystems, driven both by atmospheric and rock-derived substrates. A driver analysis, using both random forest and linear models, revealed that key soil physicochemical components significantly influence the abundance of different community members. Trace gas oxidisers encoding genes for CH4, H2 and CO responded variably between basalt and limestone caves to a wide range of factors, primarily to electrical conductivity (EC), pH and total organic carbon (TOC). The response of ammonia, nitrite, sulphide, and iron oxidisers was more conserved to limestone caves, suggesting pH, TOC and soil water content (SWC) as dominant drivers of their abundance (Supplementary Fig 11a, d; Supplementary Data 7d).

To ensure these insights were representative of caves worldwide, we further analysed twelve previously published metagenomes representative of diverse global cave ecosystems (Fig. 2a, Supplementary Data 4a). Oxidation of ambient trace gases and, to a lesser extent, rock-derived inorganic compounds are widespread strategies in sediments and rocks of cave interiors. For example, in rock metagenomes from Monte Cristo Cave (Brazil) and in white microbial mats in Kipuka Kanohina Cave (Hawaii), almost all microbes encode high-affinity hydrogenases38. The three exceptions are photosynthetic biofilms collected from an illuminated entrance and sinkhole, as well as a cave lake likely to receive considerable organic inputs (Supplementary Data 4b).

Previously uncharacterised microbes drive cave energy acquisition and primary production
We used genome-resolved metagenomics and phylogenetic analyses to resolve which microbes mediate these processes (Supplementary Data 4c; Supplementary Figs. 1–6). Most hydrogenases, CO dehydrogenases, and RuBisCOs were co-encoded by the most abundant Actinobacteriota lineages residing in the caves (primarily classes Actinomycetia, Thermoleophilia, Acidimicrobiia, and Ca. Aridivitia)21 (Fig. 3a), suggesting that they may be important primary producers in these ecosystems, although we cannot exclude the possibility of transient and dynamic heterotrophic and mixotrophic strategies. Multiple phyla nevertheless encoded each of these enzymes (14 hydrogenase-, 11 CO dehydrogenase-, and 10 RuBisCO-encoding phyla), highlighting that trace gas oxidation and chemosynthesis are ubiquitous traits (Supplementary Data 4c). These enzymes were also encoded by various uncultivated lineages, for example with CO dehydrogenases being encoded by high-quality genomes from the candidate bacterial phyla CSP1-3 and KSB1, as well as two enigmatic orders (RBG-16-68-12, UBA184) of Thermoplasmata archaea inhabiting diverse cave samples (Supplementary Fig. 1). Corroborated by the short-read analysis (Fig. 2a, Supplementary Data 4b), almost all of these belong to high-affinity clades of hydrogenases (groups 1h, 1l and 2a [NiFe]-hydrogenases21,39,40) (Fig. 2a), suggesting they adapted to atmospheric rather than elevated levels of these gases. Of the 30 most abundant microbes based on genome read mapping (Supplementary Data 4), 21 were capable of trace gas oxidation, including four putative methanotrophs (all affiliated with the USCγ/JACCXJ01 clade), whereas none mediated photosynthesis, nitrification, sulphide oxidation, or iron oxidation. The top ten most abundant microbes (comprising 20% of all mapped reads) were all from uncultivated genera from Pseudonocardiaceae and Egibacteraceae (both within class Actinomycetia), each of which co-encode RuBisCO with either CO dehydrogenase and/or uptake hydrogenases. Thus, caves appear to select for highly productive actinobacterial primary producers that grow on atmospheric energy and carbon sources. These Actinobacteriota are the most abundant lineages in the cave biofilms, whereas the methanotrophs are the single most abundant species in the cave sediments.

We comprehensively analysed the energy and carbon acquisition pathways of the three most abundant predicted hydrogenotrophs in the caves (Fig. 3b), namely the candidate genera herein named Hydrogenomurus, Hydrogenocavus and Hydrogenolapis (all etymological information in Supplementary Note 2; formerly Pseudonocardiaceae GCA-003244245, Egibacteraceae JACCXR01, and Actinomycetia JACCUZ01). These lineages were selectively enriched in distinct habitats, with Hydrogenomurus prevalent across basalt caves and constituting over half of multiple biofilm communities (up to 73%), Hydrogenocavus dominant in limestone biofilms and moonmilks (up to 54%), and Hydrogenolapis abundant in both biofilms and sediments within limestone caves (Fig. 3a; Supplementary Data 4c). All three taxa encode high-affinity group 1h [NiFe]-hydrogenases and CO dehydrogenases, consistent with the use of trace gases as an energy source. In addition, these MAGs encode a complete TCA cycle and a full suite of aerobic respiratory complexes (I-V), indicating they can conserve energy through both lithotrophic and organotrophic aerobic respiration. Both Hydrogenomurus and Hydrogenocavus also encode Type IE RuBisCO and a complete CBB cycle, indicating they are facultative chemolithoautotrophs; the lack of enzymes for oxidation of rock-derived inorganic compounds strongly suggests reductants necessary for carbon fixation are provided by H2 and CO. Their autotrophic capacity likely underline their dominance along nutrient-limited cave mineral surfaces. Conversely, Hydrogenolapis appears to be solely reliant on organic carbon sources, potentially including peptides and mono- and disaccharides, based on the presence of various ABC transporters. Energy provided by atmospheric trace gases likely enables these microbes to allocate more organic carbon for anabolism than catabolism41. All taxa encode the pentose phosphate and Embden–Meyerhof–Parnas pathways for organic carbon catabolism, although only Hydrogenomurus MAGs encode all genes necessary for complete glycolysis.

Methanotrophs are the most enriched metabolic specialists in the cave interior, based on both genomic read mapping (Fig. 3a; Supplementary Data 4b, c) and marker gene profiles (Fig. 2a, b). Given this, we performed an in-depth analysis to resolve the evolutionary history and functional capabilities of putative cave methanotrophs encoding particulate methane monooxygenases (PmoABC), as elaborated in Supplementary Note 1. A genome tree revealed that these bacteria span the alphaproteobacterial genus Methylocella (encompassing Methylocapsa within the GTDB framework), the gammaproteobacterial order Methylococcales, and two candidate gammaproteobacterial orders herein named Methyloligotrophales and Methylocavales (formerly JACCXJ01 and CAJXQU01; etymology in Supplementary Note 2). These methanotrophs were progressively enriched from entrance and cave sediments to biofilms, with a single Methyloligotrophales MAG encompassing 10.8% of microbes in a complex limestone sediment (Fig. 3a; Supplementary Data 4c), suggesting CH4 is a primary growth substrate of cave communities. While Methylocella and Methyloligotrophales encompass the USCα and USCγ lineages of atmospheric methanotrophs25,26,42,43, Methylocavales is not known to be methanotrophic and is represented by just one previously reported genome that lacks pmo genes. Consistent with being novel methanotrophs, the cave-exclusive Methylocavales bacteria each encode complete pmoCAB operons and their PmoA protein formed a novel sister clade with Methyloligotrophales (Supplementary Fig. 3a-b). They also encode a complete set of genes to oxidise methanol (lanthanide-dependent methanol dehydrogenases), formaldehyde (tetrahydromethanopterin pathway), and formate (formate dehydrogenase) to carbon dioxide for energy conservation (Fig. 3c, Supplementary Fig. 3c). However, in common with other atmospheric gammaproteobacterial methanotrophs, including the Methyloligotrophales MAGs analysed, the carbon assimilation pathways used remain incompletely resolved (Supplementary Note 1).

Though the capacity for oxidation of rock-derived inorganic substrates was less widespread, numerous chemolithoautotrophs were nevertheless highly enriched in cave sediments and biofilms. Most notable are nitrifiers, including ammonia-oxidising archaea and bacteria, as well as nitrite-oxidising and comammox Nitrospirales (Fig. 2a, b; Supplementary Data 4b, c). Members of three archaeal families, Nitrososphaeraceae, Nitrosopumilaceae (e.g. acidophilic Nitrosotalea dominant in basalt caves), and novel clade Nitrosomiraceae (e.g. Ca. Nitrosomirus44 abundant in limestone caves) vastly outnumber ammonia-oxidising bacteria (Nitrosospira) (Fig. 3a); most encode high-affinity Amt1 ammonia transporters, carbon sequestering ABC-type bicarbonate transporters, and carbonic anhydrase consistent with their oligotrophic lifestyle45. Remarkably, urease, cyanase, and glycine cleavage system genes were also present in most MAGs, suggesting these archaea also sequester ammonia from organic substrates such as urea, cyanate, and glycine. Comammox Nitrospirales (genus Palsa-1315), known for their high-affinity for ammonia46, were also widely distributed (Supplementary Data 4b, c). These cave nitrifiers use distinct pathways to fix CO2, spanning the 4-hydroxybutyrate cycle (Nitrososphaerales), the reductive tricarboxylic acid cycle (Nitrospirales), and the CBB cycle (Nitrosospira). Altogether, these findings indicate that caves select for oligotrophic chemolithoautotrophs and that nitrifiers are likely important primary producers given their autotrophic lifestyle and enrichment. Apart from nitrification, some nine phyla were capable of sulphide oxidation, including numerous Proteobacteria and Actinobacteriota MAGs. We also reconstructed genomes of iron-oxidising Acidobacteriota and Proteobacteria (Fig. 2a, b).

Trace gas oxidation occurs together with nitrification and sulphide oxidation
To substantiate these findings, we performed in situ and ex situ profiling of the processes of trace gas oxidation, nitrification, and sulphide oxidation in each cave. In situ measurements of sediment-to-atmosphere fluxes revealed ambient average concentrations in limestone/basalt cave entrances of CH4 (1.5/0.65 ppmv) H2 (0.71/0.34 ppmv), and CO (0.06/0.03 ppmv), respectively (Fig. 4a; Supplementary Fig. 7). It is likely that these gases are predominantly atmospherically derived, given their concentrations are at or below global average concentrations of these gases in the lower troposphere47–49, though it can’t be ruled out that they are also produced through geogenic and biological processes and maintained at such concentrations through microbial consumption. On average, ambient air concentrations of all three gases decreased 4-fold from the cave entrances to the interiors of the limestone caves, suggesting microbial consumption (Fig. 4a; Supplementary Fig. 7). Equivalent trends were not observed in the basalt caves, though this is potentially due to their relatively consistent tunnel-like architecture (Fig. 1a) facilitating rapid equilibration with outside air, as opposed to decreased gas consumption. Though air exchange rates were not measured, based on in situ gas fluxes, consumption was observed across all four caves. On average, in situ CH4 fluxes increased from 1.1 nmol m−2 s−1 at the entrance to 3 nmol m−2 s−1 inside (mean of transient and equilibrium flux estimates), consistent with localised methanotrophic activity within caves (Fig. 4b; Supplementary Fig. 7, Supplementary Data 5a). In contrast, H2 fluxes were highest at the entrance and modestly declined inside the caves, averaging around 7.5 nmol m−2 s−1 (Fig. 4b; Supplementary Fig. 7, Supplementary Data 5a).

Given the limitations in conducting flux measurements only in areas with sufficient sediment depth for flux chambers, we employed microcosm incubations with bulk sediments and biofilms extracted from cave walls to validate these observations. In these incubations, H2, CO and CH4 were supplied at slightly elevated levels (10 ppmv each) in otherwise ambient headspaces, in order to calculate robust first-order rate constants and atmospheric consumption rates (see “Materials and Methods”). These trace gases were consumed by the microbial communities in all samples, including biofilms and sediments, though at variable rates; most samples consumed these gases to below atmospheric concentrations, reaching observed ambient in situ ranges and/or falling below average global mixing ratios (100%, 93%, and 43% of samples for H2, CO, and CH4, respectively) (Supplementary Figs. 8 and 9, Supplementary Data 5b). H2 was consumed most quickly on average, followed by CO and CH4. CH4 oxidation rates closely matched in situ patterns, especially in limestone caves, with a 16.5-fold increase in cell-specific CH4 oxidation rates (6.89×10−13–1.13×10−11 nmol cell−1 s−1) occurring from entrance to deep zones (Fig. 4c; Supplementary Figs. 8 and 9, Supplementary Data 5b), in line with metagenomic observations of increased methanotrophic abundance (Fig. 2a). A driver analysis for cell-specific reaction rates revealed a significant influence of soil physicochemistry, with pH, TOC, and SWC and EC as drivers of activity for H2, CO and CH4 oxidisers in limestone caves, whereas CO oxidisers responded more strongly to the concentration of these compounds in basalt caves (Supplementary Fig. 11b, e; Supplementary Data 7d).

We also tested whether rock-derived inorganic substrates, namely ammonium and sulphide, were also used as energy sources given the metagenomic observations (Fig. 2a). The cave sediments contained varying concentrations of ammonium (1.35–40.2 mg/kg), sulphur (7.3–2468 mg/kg), and iron (6.96–2003 mg/kg) (Supplementary Data 1). Microcosm incubations showed ammonium was oxidised at variable rates across the samples and increased from the entrance to the interior of the cave (Fig. 4e; Supplementary Fig. 10; Supplementary Data 6). Nitrite and nitrate also accumulated in these incubations, consistent with stepwise nitrification processes occurring within the cave environments. Sulphide oxidation was also evident from the accumulation of the end-product sulphate (Fig. 4e; Supplementary Fig. 10; Supplementary Data 6). It should be noted that our in situ and ex situ biogeochemistry results are based on a single sampling expedition per cave, yet there can be much seasonal variability in cave hydrology and substrate availability, including trace gases; more extensive seasonal sampling would be required to understand temporal variability in biogeochemical activities.

Trace gas oxidation drives community-wide carbon and energy provision
Thermodynamic calculations based on bulk oxidation rates of H2, CO and CH4 revealed that trace gas oxidation rates inside the cave yielded an average power output of 1.6×10−15, 6.2×10−16 and 4.7×10−13 W per H2, CO and CH4-oxidising cell, respectively. Power per cell outputs were similar between rock types and cave depths for H2 and CO, but were higher in basalt compared to limestone, and between surface and subsurface for CH4 (Fig. 4d; Supplementary Data 5b). As we did not simultaneously measure oxygen consumption, we are unable to determine what proportion of total aerobic respiration is attributable to trace gas oxidation. These values represent theoretical estimates averaged across all cells, and it is likely that only a fraction of the community is metabolically active, meaning the per-cell power for active trace gas oxidisers maybe higher. Nevertheless, the observed rates may theoretically provide sufficient power to support the growth and survival of localised populations of trace gas oxidisers in these caves, particularly at the entrance and twilight sites in basalt caves. Indeed, based on our culture-based studies of four oligotrophic bacteria that grow on trace gases alone (e.g. M. gorgona), the CH4 power output in cave greatly exceeds growth requirements and H2 power output is at the same magnitude to support growth42,50. Importantly, these rates are averaged for all cells and samples, while in reality, some microbes may co-consume these gases, notably the highly abundant Hydrogenocavus and Hydrogenomurus. Altogether, our data indicate that atmospheric trace gas consumption can theoretically support localised activity, including growth of the methanotrophs and the survival of the hydrogenotrophs, with some bacteria potentially capable of chemolithoautotrophic growth using H2 and/or CO. We note that cultivation of these microorganisms will be a necessary next step to validate their capacity to grow on atmospheric gases.

To probe the major pathways forming organic matter in caves, we quantified the fractionation signature of biomass 13C/12C in cave sediments and biofilms (Fig. 5a). Two autotrophically-grown hydrogenotrophs and three methanotrophs (including atmospheric CH4 oxidiser M. gorgona) were also analysed for their carbon fractionation as a comparison. The organic fractions in the cave samples exhibited a depletion of 13C (δ13Corganic) from −21.7 to 40.7‰, consistent with biomass derived from CBB cycle, but distinct from other carbon fixation pathways51,52 (Fig. 5a). It is likely that organic carbon from external plant-derived inputs (allochthonous inputs) is transported into cave interiors. However, despite δ¹³Corganic values overlapping those of C₃-plant detritus (a shared CBB signature), multiple lines of evidence suggest cave-dwelling primary producers are also major sources of organic matter (autochthonous inputs). First, δ13Corganic was progressively more negative from sediments in limestone caves to biofilms in basalt caves, in line with the increasing trends of bacterial rbcL and pmoA gene abundance (Figs. 2a and 5b). Second, random forest analysis reveals rbcL abundance is the best carbon assimilation gene predictor for δ13Corganic (Fig. 5b), and also the most negatively correlated with δ13Corganic among all metabolic marker genes (Spearman’s rho = −0.56, p = 2.0×10−6), also suggesting autochthonous inputs from the CBB cycle. Moreover, the δ13Corganic signatures are similar to those of the tested hydrogenotrophs (Fig. 5a) and, as elaborated below, we directly detected considerable hydrogenotrophic CO2 fixation through ex situ assays. CH4 assimilation, which yields biomass strongly depleted in 13C, may also contribute to the negative δ13Corganic in some cave samples (Fig. 5a). This was supported by calculating methane carbon assimilation as a function of cell-specific methane oxidation rates (Fig. 5c). 13C/12C signatures were significantly associated with both SWC and TOC (Supplementary Fig. 11c; Supplementary Data 7d).

Finally, we traced radioisotope incorporation of 14C-CO2 into biomass to ascertain the relative contributions of dark, hydrogenotrophic, and photosynthetic CO2 fixation pathways, including as a source of the δ13Corganic signatures. Whereas photosynthesis was strongly stimulated at the entrance of basalt caves, it was negligible elsewhere. Hydrogenotrophic CO2 fixation was observed in cave interiors, with two-fold and five-fold more carbon fixed in limestone and basalt caves respectively compared to dark conditions (Fig. 5d; Supplementary Data 7a). Notably, basalt biofilm and sediment microbes mediated higher hydrogenotrophic CO2 fixation activities (5.7×10−13 nmol 14C cell−1 min−1) compared to average rates by limestone sediment microbes (5.3×10−14 nmol 14C cell−1 min−1). This supports our metagenomic inferences that H2 is the predominant driver of CO2 fixation and may contribute to the observed δ13Corganic signatures in caves. Gross carbon fixation rates are probably orders of magnitude higher than measured 14CO2-fixation rates, as unlabelled native inorganic carbon, CO2 from the ambient air headspace, and internally recycled CO2 within samples invariably competed with the trace levels of added 14CO2 (400 ppm), especially in carbonate-rich limestone samples (1.7–29% carbon; Supplementary Data 1). Therefore, these rates are a conservative estimate to only reflect the potential for hydrogenotrophic CO2 fixation under elevated H2 conditions, and should not be interpreted as ambient net CO2 fixation rates. Methanotrophs also contribute to carbon acquisition from methane, as they are estimated to assimilate −3.5×10−7 to −1.1×10−12 nmol C cell−1 min−1 based on their ex situ cell-specific oxidation rates, and a theoretical 40% methane-carbon conversion efficiency53–55, which is further supported by their activities based on the in situ flux analysis (Fig. 5c; Supplementary Data 7b). We acknowledge that methanotrophic CO2 fixation via the CBB cycle, as well as other dark and anaplerotic processes not accounted for in this study, may contribute to CO2 fixation in caves. These experiments demonstrate that microbial energy and carbon acquisition from atmospheric substrates occur continuously, with chemosynthetic primary productivity being sustained across a range of cave surfaces.

Aerotrophy as a key process in cave ecosystems
Here, we provide extensive metagenomic and biogeochemical evidence for the consumption of atmosphere-derived trace gases in cave sediments and biofilms. This consumption may support a potentially large fraction of the microbial community. Primary production appears to be driven by highly abundant and active methanotrophs oxidising atmospheric methane. Previously undescribed lineages of actinobacterial lithoautotrophs are predicted to oxidise hydrogen to fix CO2. Together, these organisms continuously use the gases methane, hydrogen, carbon dioxide and carbon monoxide present in cave atmospheres. Cave ecosystems differ from polar desert soils, the other major type of ecosystem shown to be atmospherically powered19–21, in that trace gases appear to drive continual growth rather than long-term survival in these nutrient-deprived environments. This is reflected by the abundant primary producers in cave sediments and biofilms, the rapid fluxes and activities of trace gas oxidisers, and the theoretical considerations based on thermodynamic and biogeochemical modelling. Given the relatively stable environment, humid conditions, and aeration of most caves, it is predicted that aerotrophs will continually cycle gases such as hydrogen, methane, and carbon dioxide, whether of atmospheric origin or geogenic origin (including at atmospheric concentrations), allowing continuous primary production. On this basis, we propose defining the term “aerotrophy” as “the process of growth through the use of atmospheric trace gases, as energy and carbon sources” (derived from Greek, by combining the prefix “aero” meaning “air” and the suffix “trophic”, derived from “trophē”, meaning “nourishment”), with caves as major systems often driven by ‘aerotrophic microorganisms’.

Aerotrophy nevertheless co-occurs with other energy and carbon acquisition processes in cave systems. There is likely much spatio-temporal variation in the relative contributions of atmospheric, inorganic, organic, and even solar energy sources within and between caves. We provide metagenomic and biogeochemical evidence that other chemosynthetic processes, including nitrification and sulphide oxidation, are also important in diverse caves and are likely to be dominant where rock-derived substrates are locally elevated. Moreover, while the atmosphere is most likely the primary source of trace gases in the caves sampled, some caves or microenvironments therein will have elevated inputs through geological processes (e.g. serpentinisation, radiolysis) and biological production (e.g. fermentation, nitrogen fixation, methanogenesis) that could supplement primary production30,37,56. Our analyses also do not differentiate the relative contribution of aerotrophy and other chemosynthetic carbon fixation (autochthonous inputs) and external organic matter (allochthonous inputs) to the organic carbon levels observed in the sampled caves. External inputs are likely to be substantial in certain sections of the caves, in line with the high moisture and carbon content of certain samples (1.7–29% carbon; Supplementary Data 1), and will also vary in response to seasonal hydrological dynamics. These inputs are predicted to primarily enter the cave via sinking streams and surface water that gradually seep through soil and rock layers9. While sinking streams can provide substantial concentrations of organic carbon comparable with surface streams, water percolation tends to spread smaller amounts of organic carbon over a wider area. Depending on the geomorphology of each cave, these modes of carbon and nutrient inputs likely interact to create the varied local conditions we observed. Given the genome collection suggests most of the bacteria in these caves can use both trace gases and organic carbon to meet their resource needs, it is likely most will take advantage of external carbon whenever available across space and time, but continually sustain themselves on trace gases otherwise. Indeed, given that atmospheric trace gases are such rich and dependable energy sources, they are continuously used by the most abundant microbes in these ecosystems. Exceptions likely include those caves that have more extensive solar or guano inputs, are disconnected from the atmosphere, or are otherwise largely anoxic15. Altogether, our analyses suggest that atmospheric trace gases support a basal level of primary production and energy conservation, which in turn sustains the substantial biodiversity found in various cave ecosystems.

Methods
Site description and sampling
Samples were collected from four caves in Victoria Australia, belonging to two major lithologies, sedimentary limestone and igneous volcanic rock: 3M-3—Shades of death (S37.40591; E148.21114); 3M-49—Scrubby creek (S37.44000; E148.17000); 3H-11—Harman 1 (S37.9075; E141.9769); and 3H-9—Tunnel cave (S 38.05706; E141.92000). Two limestone caves (M3/M49) were sampled in April 2021, and two volcanic caves (H-11/H-9) were sampled in November 2021. Samples were collected using sterile techniques along a distance transect traversing four sites consisting of the cave entrance at the surface (Entrance) and cave interior (Twilight, Transition and Deep), with the Deep sites representing the furthest point from the entrance (Fig. 1a). At each site (~25 m2), three sampling plots (~1 m2) were selected at random (Fig. 1a). At each plot, sediment-atmosphere fluxes were measured, and samples of sediments and biofilms were collected in triplicate for ex situ oxidation measurements, physicochemical analysis, and DNA extractions to perform qPCR and metagenomic sequencing. Additionally, opportunistic sampling of conspicuously hued biofilms, fungal spores, moonmilk57 and sediments were collected for metagenomic sequencing. An alternative design was used for Harman 1 cave, given the lack of bulk sediments on the cave floor and high prevalence of brown biofilms meant flux measurements could not be taken. Instead, sampling focused on ambient air measurements and the collection of sediments from three plots at the Entrance and biofilm from three plots at the Deep zone and two plots at the Transition site. All sampling occurred during daylight hours and dry weather conditions, gas samples and incubations were processed within 48h of collection, and sediment samples for DNA extraction were initially stored at 5°C for transport and frozen at −20°C until DNA extraction. Sampling at Harman 1 and Tunnel cave were conducted under Parks Victoria Access Agreement AA-0000038. Sampling at Scrubby Creek cave and Shades of Death cave were privately arranged with owners at the Rimstone Cooperative Ltd.

Sediment physicochemical analysis
For sediment chemistry analysis, sediment samples from each plot were pooled to form one representative composite sample per site and sent to the Environmental Analysis Laboratory (EAL), Southern Cross University. In total, 37 separate soil physicochemical parameters were selected for analysis, based on commonly reported drivers of soil microbial composition globally. These included: Phosphorus (mg/kg P), Nitrate Nitrogen (mg/kg N), Ammonium Nitrogen (mg/kg N), Sulphur (mg/kg S), pH, EC (dS/m), Estimated Organic Matter (% OM), Exchangeable Calcium (mg/kg), Exchangeable Magnesium (mg/kg), Exchangeable Potassium (mg/kg), Exchangeable Sodium (mg/kg), Exchangeable Aluminium (mg/kg), Exchangeable Hydrogen (mg/kg), Effective Cation Exchange Capacity (ECEC) (cmol+/kg), Calcium (%), Magnesium (%), Potassium (%), Sodium - ESP (%), Aluminium (%), Hydrogen (%), Calcium/Magnesium Ratio, Zinc (mg/kg), Manganese (mg/kg), Iron (mg/kg), Copper (mg/kg), Boron (mg/kg), Silicon (mg/kg Si), Total Carbon (%), Total Nitrogen (%), Carbon/Nitrogen Ratio, Chloride Estimate (equiv. mg/kg), TOC (%), Moisture content (%), Gravel (%), Sand (%), Silt (%), Clay (%).

Community DNA extraction
Total community DNA was extracted from a total of 105 samples (94 environmental samples +11 controls) using 0.25g of sediments and biofilms. Extractions were performed using the FastDNA Spin Kit for Soil according to the manufacturer’s instructions with an additional round of bead beating to improve DNA yield. Samples were eluted in DNase- and RNase-free UltraPure Water (ThermoFisher). Eleven sample-free negative controls were also extracted. Nucleic acid purity and yield were measured using a NanoDrop ND-1000 spectrophotometer and a Qubit Fluorometer 2.0.

Quantitative PCR
Quantitative polymerase chain reactions (qPCR) were used to estimate total bacterial and archaeal abundance. The 16S rRNA gene was amplified using the degenerate primer pair (515F 5ʹ-GTGYCAGCMGCCGCGGTAA-3ʹ and 806R 5ʹ-GGACTACNVGGGTWTC TAAT-3ʹ). A synthetic Escherichia coli 16S rRNA gene sequence in a pUC-like cloning vector (pMA plasmid; GeneArt, ThermoFisher Scientific) was used as a standard. PCR reactions were setup in each well of a 96-well plate using LightCycler 480 SYBR Green I Master Mix. Each sample was run in triplicate and standards in duplicate on a QuantStudio 7 Flex Instrument (Applied Biosystems). The qPCR conditions were as follows: pre-incubation at 95°C for 3min and 45 cycles of denaturation 95°C for 30s, annealing at 54°C for 30s, and extension at 72°C for 24s. 16S rRNA gene copy numbers were calculated based on a standard curve constructed by plotting average Ct values of a serial dilution of the plasmid-borne standard against their copy numbers.

Metagenome sequencing, assembly, and binning
Metagenomic shotgun libraries were prepared using the Nextera XT DNA Sample Preparation Kit (Illumina Inc., San Diego, CA, USA) and subject to paired-end sequencing (2×150bp) on an Illumina NovaSeq 6000 platform at the Australian Centre for Ecogenomics (ACE), University of Queensland. Raw metagenomic sequences were subjected to quality filtering using the BBDuk function of the BBTools v38.80 (https://sourceforge.net/projects/bbmap/); contaminating adaptors (k-mer size of 23 and hamming distance of 1), PhiX sequences (k-mer size of 31 and hamming distance of 1), and bases from 3’ ends with a Phred score below 20 were trimmed. After removing resultant reads with lengths shorter than 50bp, 93% high-quality read pairs were retained for downstream analysis. Coassemblies were conducted according to cave type (limestone vs basalt) and sample nature (dividing by biofilm, sediment, and moonmilk) were conducted using quality-controlled reads in megahit (v1.2.9) using kmers of 27, 37, 47, 57, 67, 77, 87, 97, 107, 117 and 127. In addition, assemblies for each individual sample were performed using metaSPAdes (v3.15.5) with the same set of kmers58. Contigs from both coassemblies and individual assemblies with a minimum length of 500bp were used for binning with MetaBAT2 (v2.12.1)59, MaxBin2 (v2.2.7)60 and CONCOCT (v1.1.0)61 to reconstruct MAGs, which is implemented in the “binning” module of MetaWRAP (v1.3.2)62. Subsequently, the ‘bin refinement’ modules of MetaWRAP and DAS tool63 were used in parallel to consolidate the MAGs from the three binners into one bin set for each assembly. A final MAG set was obtained by dereplicating MAGs from all assemblies at 99% average nucleotide identity using dRep “dereplicate” (v3.4.2)13,64. The completeness and contamination of the MAGs were estimated using CheckM2 (v0.1.3)65 “predict”. Taxonomy of each MAG was assigned using GTDB-Tk “classify_wf” (v2.3.0)66 against GTDB release 214. CoverM (v0.6.1) “genome” was used to calculate the relative abundance of each MAGs within each sample

Bacterial and archaeal community profiling
To profile bacterial, archaeal, and eukaryotic community composition based on the metagenomes, quality-filtered short reads encoding 16S rRNA genes were retrieved and assigned using PhyloFlash v.3.067. The function PhyloFlash.pl was given a -taxlevel 6 flag for bacteria/archaea specifying a taxonomic assignment down to genus level. Retrieved sequences were then clustered using PhyloFlash.pl into NTUs (nearest taxonomic units), mapped to the SILVA database (release 138)68, and filtered to exclude rare hits (min. read count≥10). Alpha and beta diversity were calculated using R (version 4.1.0 (2021-05-18) — “Camp Pontanezen”) and the Phyloseq package69. First, reads were normalised using the coverage-based rarefaction and extrapolation method implemented in the R package iNEXT70. Coverage was calculated for each sample using the function phyloseq_coverage, followed by rarefaction of all reads, using the function phyloseq_coverage_raref with default parameters. Observed and estimated richness was calculated using the estimate_richness function specifying with “observed” and “chao1” flags. To calculate beta diversity, sample counts were first transformed to relative abundance and clustered using a Non-metric Multidimensional Scaling ordination via the ordinate function with flags “NMDS” and “Bray” function. A stress plot was used to determine linear (R2=0.83) and non-metric (R2=0.96) fit between ordination distance and dissimilarity (Bray-Curtis). The final stress of <0.2 (0.18) indicated a good representation in reduced dimension.

Metagenomic functional analysis and metabolic reconstruction
To estimate the metabolic capability of the sediment and biofilm communities, quality-filtered and unassembled short reads were searched against custom protein databases of representative metabolic markers using DIAMOND v.0.9.31 (query cover >80%)71. Searches were carried out using all quality-filtered unassembled reads with lengths over 120bp. The metabolic markers searched are involved in oxidative phosphorylation (AtpA), NADH oxidation (NuoF), aerobic respiration (CoxA, CcoN, CyoA, CydA), formate oxidation (FdhA), arsenic cycling (ARO, ArsC), selenium cycling (YgfK), sulphur cycling (AsrA, FCC, Sqr, DsrA, Sor, SoxB), nitrogen cycling (AmoA, HzsA, NifH, NarG, NapA, NirS, NirK, NrfA, NosZ, NxrA, NorB), iron cycling (Cyc2, MtrB, OmcB), reductive dehalogenation (RdhA), phototrophy (PsaA, PsbA, energy-converting microbial rhodopsin (RHO)), methane cycling (McrA, MmoX, PmoA), hydrogen cycling (large subunit of NiFe-, FeFe-, and Fe-hydrogenases), isoprene oxidation (IsoA), CO oxidation (CoxL, CooS), succinate oxidation (SdhA), fumarate reduction (FrdA), and carbon fixation (RbcL, AcsB, AclB, Mcr, HbsT, HbsC)72–74. Results were filtered based on an identity threshold of 50%, except for RHO (40%), NuoF, group 4 NiFe-hydrogenases, MmoX, FeFe-hydrogenases, CoxL, AmoA, NxrA, RbcL (all 60%), PsaA (80%), PsbA, IsoA, AtpA, ARO, YgfK (70%), and HbsT (75%). Read counts for each gene were normalised to reads per kilobase per million (RPKM) and average gene copy per organism as previously described21,27,75. Proteins from each MAGs were predicted intrinsically in CheckM65. Best gene hits were filtered to retain only those either at least 40 amino acids in length or with at least 80% query or 80% subject coverage3. For predicted proteins, the same thresholds were used as above except for AtpA (60%), PsbA (60%), RdhA (45%), Cyc2 (35%) and RHO (30%)23. Metabolic reconstruction for the three most dominant hydrogenotrophs and methanotrophs was performed via annotation of relevant MAGs with DRAM76, based on the KEGG database. Pathways were identified through the KEGG pathway database and literature77. No MAGs encoded a GSH-linked pathway for formaldehyde oxidation, which is consequently omitted from the metabolism figure.

Methanotroph phylogenetic and metabolic analysis
GraftM v 0.1478 was used to ascertain gene phylogeny. PmoA and MmoX packages79 were used and updated with sequences published in ref. 21,27,80–86. HMM and DIAMOND (hmmsearch+diamond) search methods were applied, along with a conditional E-value (c-Evalue) threshold of 1e-1026,78. Multiple sequence alignment of protein sequences was performed with MAFFT v 7.49087, trimming at minimum 20% representation was performed with TrimAl v. 1.4.188. Phylogenetic trees of protein sequences were generated with IQ-TREE v. 2.2.0.389 with the ultrafast bootstrap approximation option using 1000 iterations and enabling the ModelFinder option (Best-fit model: LG+F+R6). The trees were rerooted and grouped in ARB v. 6.0.390. Visualisation of protein trees was done in iTOL v691. The genome phylogenetic tree was generated by extracting the multiple sequence alignment of high-quality MAGs (completion >90% and contamination <5%) and known methanotrophs generated by GTDB-Tk (v2.1.1)66 against GTDB release 214. The tree was constructed with IQ-TREE v. 2.2.0.389 using model WAG+G and ultrafast bootstrap approximation option using 1000 iterations. The trees were rerooted and grouped in ARB v. 6.0.335 and visualised in iTOL v691. Annotation was performed using DRAM and the KEGG database, and pathways were identified through the KEGG pathway database and literature77. No MAGs encoded a GSH-linked pathway for formaldehyde oxidation, which is consequently omitted from the metabolism figure.

In situ sediment–atmosphere gas fluxes
In situ sediment-atmosphere fluxes of H2, CO and CH4 were measured using static flux chambers. The chamber consisted of a polyvinyl chloride (PVC) pipe of 20 cm height and 15 cm diameter, with a threaded access cap. The cap was fitted with a gastight O-ring, two butyl rubber septa (one for air sampling and one for a thermometer), and an axial fan on the inside to promote internal mixing. At each plot, a PVC base collar of 10 cm height and 14.8 cm diameter was inserted ~5 cm into the sediment and left to equilibrate for ~15min prior to sampling to reduce lateral gas fluxes. Once the chamber was fitted over the collar, an ambient air measurement was taken at the base of the collar, the cap was immediately closed, and the axial fan was started, and the next measurement was taken within 30s. Additionally, ambient measurements were taken over a 30-min period. For each measurement, 25 mL of gas was collected using a gas-tight Terumo syringe fitted with a Luer Lock and Discofix three-way stopcock. Data quality checks and measurements by gas chromatography were conducted as described below. The temperature of the chamber, ambient air, and sediment were monitored throughout. Concentrations were then converted to nmol m−3 at ambient pressure and temperature using the ideal gas law. Atmospheric flux (J nmol m2 s−1) was calculated from the initial ambient conditions (t0) and rate of change at chamber deployment, using linear regression and an exponential model for each chamber measurement as previously described27. We calculated two separate flux phases “transient flux”, which includes the t0 ambient state, and the equilibrium flux, which excludes t0 to capture steady-state conditions. This was done to obtain an upper and lower bound flux range, to better reflect the unique conditions inside each cave, including shallow sediments, unique microclimate and absence of soil matrix.

Ex situ bulk oxidation rates
Microcosms were used to determine the capacity of sediment and biofim microbial communities to oxidise H2, CO and CH4 by gas chromatography. Overall, 44 biological replicates from four caves consisting of the Entrance (n=12), Twilight (n=9 plots), Transition (n=11) and Deep (n=12) zones were used. 5g of sediment/brown biofilm (Harman 1) samples were placed in a 120 ml serum vial and incubated at 20°C. The ambient air headspace was amended with H2, CO and CH4 (via a mixed gas cylinder containing 0.1% v/v H2, CO and CH4 each in N2, BOC Australia) to give starting mixing ratios of approximately 10 parts per million (ppmv) for each gas. At each time interval, 2 ml of headspace gas was sampled using a gas-tight syringe and stored in a sealed 3 ml glass exetainer flushed prior with ultra-high purity N2 (99.999% pure, BOC Australia). A VICI gas chromatograph instrument with a pulsed discharge helium ionisation detector (model TGA-6791-W-4U-2, Valco Instruments Company Inc.) and an autosampler was used to measure gas concentrations as previously described92. The instrument was calibrated against ultra-pure H2, CO and CH4 standards. Calibration mixed gas (10.20 ppmv of H2, 10.10 ppmv of CH4, 9.95 ppmv of CO in N2, Air Liquide Australia) and pressurised air (Air Liquide Australia) with known trace gas concentrations were used as internal reference standards. Pooled heat-killed sediments for each triplicate (treated at 121°C, 15 p.s.i. for 60min) and empty vials (duplicate) were prepared as negative controls. All measurements were quality checked for peak anomalies, injection failures or leaks and excluded from downstream analysis. Reflecting the natural variation oxidation rates, measurements were halted once oxidation approached sub-atmospheric concentrations for individual samples. First order reaction rate constants were calculated by fitting an exponential model as determined by the lowest overall Root Mean Squared Error when compared to a linear model and normalised to average global concentrations for each gas.

Cell specific power calculations
The calculation was performed as previously described21,27, involving the determination of cell-specific power generated by the oxidation of H2, CO and CH4, measured as Gibbs energy per unit time per microbial cell. This was accomplished by factoring in the reaction rate for each gas, the Gibbs energy of the reaction, and the number of microbial cells involved. The Gibbs energy calculations considered the standard Gibbs energy, the reaction quotient, gas-phase compound activities, and sediment conditions. Measurement of reactant concentrations and reaction rates was conducted via gas chromatography. Estimates of microbial cells performing these reactions were calculated from 16S rRNA gene copy number datasets and abundances inferred from metagenomics datasets, focusing on trace gas-oxidising communities. This approach was compared to previous literature by recalculating the theoretical maximum population of trace-gas oxidising bacteria using modelled Gibbs energy and measured reaction rates.

Ammonium and sulphide oxidation
Oxic slurry experiments were undertaken to determine the oxidation rates of ammonium and sulphide of the cave sediments. Biotic and abiotic oxidation rates were distinguished using sterilised (autoclaved at 120°C for 1h) and non-sterilised cave sediments. Slurries containing 10g sediment (wet weight) and 200 mL substrate amended ultrapure water (50 µM of either ammonium chloride or sodium sulphide) were prepared in 250 mL Schott bottles. The slurries were aerated for 5 min to ensure oxic conditions. The bottles containing the slurries were left uncapped but loosely covered with pre-combusted aluminium foil. The slurries were incubated in the dark and were mixed from time to time for the duration of the incubation period (up to 22 days). At each time point, 15 mL of samples were collected and filtered through 0.22 µm pore-sized filters (Sartorius Minisart syringe filter). Filtered samples were analysed for ammonium, nitrate, nitrite and sulphate concentrations using a Lachat Quickchem 8000 Flow Injection Analyzer (APHA standard method). Oxidation rates of ammonium were calculated using linear and non-linear regression of uptake over time as well as liner regression of nitrite and nitrate accumulation over time. Similarly, rates of sulphide oxidation were calculated from linear regression of sulphate increase over time.

Measurement of carbon isotope at natural abundance level (δ13C)
Stable isotope measurements were performed to probe possible pathways contributing to the formation of organic matter in caves. Approximately 1g of sediment was dried at 60°C for 24h, pulverised and homogenised with a clean mortar and pestle. The pulverised sample was further dried at 60°C overnight. Biofilm samples were first resuspended in sterile ultrapure water, pelleted by centrifugation at 13500g for 2min, and dried at 60°C. Samples were weighed into 8mm × 5mm silver capsules, repeatedly treated with 10% hydrochloric acid (HCl) to remove inorganic carbon, and dried at 60°C until no further effervescence was observed. All samples were analysed on an ANCA GSL 2 elemental analyser interfaced to a Hydra 20-22 continuous flow isotope ratio mass spectrometer (CF-IRMS; Sercon Ltd., UK). The precision of the analysis was ±0.2‰. To ensure the accuracy of the isotopic values, internal standards (i.e. sucrose, gelatine and bream) were run concurrently with the samples. These internal standards have been calibrated against internationally recognised reference materials (i.e. USGS40, USGS41 and IAEA C-6). In addition to δ13C, the instrumental analysis also yielded information on the percentage of organic carbon in each sample, with a quantification limit of 0.1mg and a precision of 0.5 µg for carbon content.

Culture-based natural isotope preparation
To contextualise the δ13C of biomass originating from different carbon fixation pathways, we referred to the carbon isotopic fractionation effects observed in pure cultures. Our dataset includes previously reported literature values for autotrophic pure cultures52,93–96 and new analyses of two hydrogenotrophs (Cupriavidus necator H16, Hydrogenophaga pseudoflava 1034) and three methanotrophs (Methylocapsa gorgona MG08, Methylococcus capsulatus NCIB 11132, Methylosinus trichosporium OB3b). H. pseudoflava and C. necator grew autotrophically (CBB cycle) on H2 as follows. Pre-culture of both species was prepared by cultivating autotrophically on 20% H2 + 5% CO2 in minimal medium DSMZ 81 with an initial OD600 of 0.03 in gas-tight 120 ml serum vials sealed with rubber stoppers and aluminium caps at 30°C with an agitation speed of 180rpm. The main cultures were prepared by inoculating with an initial OD600 of 0.05 under identical conditions in a 1L Schott bottle, sealed with rubber stoppers (GL45 open-top cap) and screw caps (GL45 cap open-top). M. gorgona, M. capsulatus, M. trichosporium were grown on CH4 as follows. NCIMB nitrate mineral salts (NMS) medium131 was used for M. capsulatus and M. trichosporium while DSMZ medium 921 supplemented with 10 ml/L of 10x NMS salts and lanthanum (a final concentration of 1 µM) was used for M. gorgona. Exponential M. capsulatus and M. trichosporium cultures were grown in 1L Schott bottles under 20% v/v CH4 in air at 37°C and 30°C, respectively, with shaking (200 rpm) for 7 days. M. gorgona cultures were prepared by inoculating 250 mL medium with 70 mL of an early stationary phase culture in 1L glass bottles under 30% v/v CH4 in air at 20°C without shaking. δ13C values of CO2 and CH4 were determined to be −10.6±0.1‰ and −51.9±1.5‰, respectively. Triplicate cultures were prepared for all strains. Following incubation, cells at late exponential or stationary phase were subject to centrifugation at 4°C. Supernatants were discarded, and cell pellets were resuspended in 1x PBS buffer, followed by another round of centrifugation. Supernatants were discarded again, and the cell pellets were stored at −80°C until freeze-drying. Cell pellets were lyophilised for 48h and analysed for δ13C, using the same method as for the sediment and biofilm samples. One outlier was removed with an anomalously light signature of −67.40‰. The expected δ13C values of autotrophs reported in the literatures and current measurements when grown on atmospheric CO2 (δ13C average −8.5‰)97 and CH4 (δ13C average −47.2‰)98 were reported. A random forest model was then generated assessing the importance of key functional genes (pmoA, mcr, hbsT, aclB and rbcL) against depletion of biomass 13C stable isotope (δ13Corganic), using the randomForest function in R. Parameters were as follows: Number of variables randomly sampled as candidates at each split=10, number of trees grown=10,000 and sampling of cases was conducted with replacement.

14CO₂ fixation assay
A radiolabelled carbon dioxide (14CO2) incubation assay was used to measure the capacity of cave sediments/biofilms to mediate three processes: (i) dark CO2 assimilation/fixation, (ii) hydrogenotrophic CO2 fixation, and (iii) photosynthetic CO2 fixation as previously reported19,20,22,99. The sample was added with 50% v/w of sterile water containing 0.0833 μmol of NaH14CO3 (equivalent amount as 400 ppmv headspace 14CO2; Perkin Elmer, 56.6 mCi mmol−1) and the vial was immediately sealed with PTFE/silicone septum lid (Supelco, Sigma-Aldrich). The samples were then incubated for 96h at either 20°C under three conditions: (1) dark (covered in aluminium foil), (2) light (40 μmol photons m−2 s−1 under constant illumination), and (3) dark hydrogenotrophic condition (100 ppmv of headspace H2). For each condition and location, a technical triplicate and a heat-killed sediment control was prepared. Following incubation, each sample was treated with 2 ml of 1M HCl to remove unfixed CO2 and the content was transferred to a 20 ml scintillation vial. After overnight acidification treatment, the sample was added with an additional 1 ml of 1M HCl and allowed to dry at 60°C under a heat lamp. 20 ml of liquid scintillation cocktail (EcoLume™, MP Biomedical) was added to the dried sample and the signal of fixed 14C was measured on an automated liquid scintillation counter (Tri-Carb 2810TR, Perkin Elmer) for 5 min. The instrument was regularly calibrated with 14C standards of known activity.

Phylogenetic analysis
The evolutionary relationships of maker genes, including methane oxidation (PmoA), hydrogen oxidation (NiFe), CO oxidation (CoxL), ammonia oxidation (AmoA), nitrite oxidation (NxrA) and carbon fixation (RbcL) were visualised by constructing phylogenetic trees of protein sequences. Briefly, protein sequences retrieved from the MAGs and metagenomic assembled reads by homology-based searches against a subset of reference sequences from a custom database100, and were aligned using MAFFT87 with default parameters, and subsequently trimmed using Trimal v1.2rev59 (“-gappyout”)88. The trimmed multiple sequence alignments were used to infer phylogenetic trees with the maximum likelihood method incorporating substitution model selection and 1000 bootstrap iterations implement in IQ-TREE2 v1.6.12 (“-alrt 1000 -B 1000 -m TEST”)89. Tree rendering was performed using the Python package ETE3101 combined with visualisation in iTOL91.

Methane carbon conversion efficiency
Theoretical estimation of carbon assimilation into microbial biomass was based on measured methane oxidation rates. Three seminal papers on methane carbon assimilation were used to calculate a constant conversion factor54,55,102. The percentage of methane carbon assimilation varied between 20 and 62%. By utilising the median for each range and computing the mean (40%), we determined the amount of methane carbon assimilated in units of nmol C cell−1 min−1 by multiplying the cell-specific methane oxidation rate by a constant fraction of 0.4. This measurement provides a quantifiable indicator of the role of aerobic methanotrophs in the carbon cycle. One drawback of this approach is that it does not consider variations in assimilation across different cells and variations in assimilation across different physicochemical conditions.

Peer review rounds
[{"round": 1, "reviewer_comments": {"reviewer_1": "Bay and coworkers strongly increased the quality of the manuscript, and I fully agree with the molecular analysis and observations made in Fig. 1 to 3. Indeed, caves harbor many microorganisms with the genomic potential to use H2, CO2, and CH4 airborne gases. But do they use this potential to produce a substantial amount of chemolithogenic biomass? I question the claims made about the importance of these substances as energy sources for microorganisms. There might indeed be higher H2 concentrations at the cave's entrance than in the twilight zone, but I do not see any further trend toward the interior of the caves. If so, only the entrance /twilight zones show hydrogen consumption, but the middle and deep zones of the caves do not further contribute to hydrogen oxidation, and the same holds for other gases.\n\nThe authors make statements such as high/ substantial rates without bringing their data into context. How much is 1 nM per m² and sec or 86.4 µM per sqm and day? Let’s get the number into context. The lowest oxygen fluxes on Earth were measured for the South Pacific Gyre- about 0.1 to 1mmol per sqm and day. In the South Pacific Gyre, the oxygen penetration depth is 100 meters. I don’t think that anything similar can be observed in the cave. The oxygen consumption in this cave is likely many times higher than the contribution of CO (clearly), hydrogen (for sure in the deeper cave), and methane. Hence, airborne autotrophy will also result in only traces of biomass production, which will hardly affect the carbon flow in the cave. These are just estimates, but the key experiment to call the hydrogen consumption substantial / and, if at all, is connected to maybe 1% of the oxygen consumption (this would be my estimate) has not been done.\n\nBecause of the low rates, cell-specific reaction rates become unrealistically low (Fig 4c-d). Data points such as 10^14 nmol mean the respiration of single molecules per second. This would be difficult to replicate – it would take 7 billion seconds to fix the carbon of the average cell. It is more likely that some few cells are active, but this makes average cell-specific rates odd. It is like having 100000 homeless and Elon Musk at your party and stating, based on average, that all your guests are millionaires.\n\nBecause it is impossible to compare the low hydrogen, methane, CO oxidation rates with the missing total oxygen consumption rates, statements such as the last sentence of the abstract are not justified:\n“Trace gases sustain a basic level of biodiversity and productivity through a process we define as aerotrophy that is supplemented by organic and inorganic input”. In fact, looking at the data, it is rather unlikely that the contribution of these trace gases to the overall microbial activity is very high.\n\nA solution for this abstract could be:\n“The energy from airborne trace gasses may support the growth of a yet unquantified share of the cave communities. These organisms may add organic carbon compounds to the energy-limited cave ecosystems. “\n\nThe entire paper has an awkward tendentiousness. Whenever a rate shows a bit towards “aerotrophy” it is excessively reported: Just look at Fig. 4ab, discussed in line 250ff. Gas concentrations decreased significantly. I don’t see significant value. If you start from twilight, there is simply no decline anymore. Wording like high rates do not match if you cannot compare it with other rates.\n\nFig. 4. B: Fluxes are never negative according to the graph. But look at the MS. This would also be impossible because it is a logarithmic scale. Numbers of replicates are not given. But data points are up to 5 orders of magnitude different.\n\nFig. 5: There is much higher methane than CO2 fixation (Fig. 5 c,d) – but the d13C argues against methanotrophy and more for CBB-derived fixed carbon. Of course, most of the organic carbon is not produced by microorganisms but is from sunlight-fixed organic matter.\n\nL244ff: I cannot agree that trace gas consumption is described as high rates.\n\nFig. 4a: Extended data Figure 7: I do not see a substantial or statistically significant decrease for most curves, except “entrance” and methane in twilight. If so, there is a difference between T0 and T1 – not after. The entrance of the cave might be a difference.\n\nLine 343ff: particularly high hydrogenotrophic carbon fixation rates of 6.7*10^-12 nmol per cell and minute – that does not sound to be a lot\n\nIt is unclear what a strong consumption means; see comment above. A change of a fractions of a ppm difference in flux chambers is never a lot. Here and in other cases, I miss comparison with other habitats / or other rates.\n\nLine 364: About half of the carbon should come from CO2 when methane is assimilated. Methane assimilation cannot be three orders of magnitude higher than CO2 assimilation. You may have triggered methane oxidation by the addition of large amounts of 14C-tracer. Unfortunately, methods do not describe 14C-methane oxidation rates. I fear that these high rates derive from incubations with large amounts of 14C: 1 MBq carbon/CH4 is already 0.4 µmol. Please report also on the duration of this incubation.\n\n14CO2-based rate measurement: (line 637) 14C isotope labeling is not the correct terminology here). Note that you measure hydrogen-dependent CO2 fixation rates at H2 concentrations that are 100 times elevated compared to nature. Still, these rates are small.\n\nExtended Fig. 8: Here, a logarithmic curve is not good - or tells a lot – the organisms only start picking on the higher concentrations after a lack phase. This may suggest that environmental trace gas concentrations are hardly used.\n\nPlease find a meaningful order of the methods i.e., best use the order of how data appears in the MS", "reviewer_2": "The authors have addressed nearly all of my concerns and the manuscript is much improved. I still don't like \"aerotrophy\" as used here, but I seem to be alone in this opinion.", "reviewer_3": "Bay and colleagues have investigated metagenomic capacities and actual biogeochemical cues for active microbial consumption of atmospheric trace gasses, mostly H2, CH4 and CO, in 4 Southern Australia cave systems.\n\nCave microbiota are compared across longitudinal transects and different compartments of two basalt and two limestone caves in Victoria. With ~1500 high-quality MAGs assembled for many dozens of samples, ~half of the MAGs hosted capacities to consume either one of the different trace gasses. Amongst them, abundant hydrogenotrophic candidate genera within the Actinobacteriota, methanotrophic gammaproteobacterial Ca. Methylocavales, and also some MAGs of enigmatic candidate phyla. Aerotrophic primary production is shown to be substantial throughout most samples, with methane and hydrogen-derived energy delivering enough power-per-cell to allow for continued growth, or at least sustained activities and survival in lack of other substrates. The concept of, at least temporary or partial, aerotrophy as a dominating physiology in caves is a highly interesting addition to our understanding of these underexplored ecosystems. This piece clearly warrants publication in a journal like NatComms. Still, before acceptance, the authors should address the following comments:\n\n1. It Would be good if the results (& discussion) section could start with some basic primers on the nature of the sampled cave systems (basalt and limestone), locations (entrance, longitudinal transects) sample types (biofilms, sediment, …) and overall sample numbers. This is important to grasp the scope of the study, as not every reader will (first or at all?) grind through the M&M or supplement. Just a bit more info on the basic settings of the study, before delving into all the community composition and the metagenomic details.\n\n2. In contrast to the authors notion, caves do typically not contain soil (Fig. 1b). Unless it is washed in or collapses in from above. Please change to “Sediments” in Fig. 1b, as correctly implemented already in other Figs. Also, “soil” must still be replaced on some occasions throughout the text, e.g. L129 or L343.\n\n3. L318: this must be a mistake. Explain that this was just one sample of many dozens with this extremely light signature at MINUS (!) 67.4 permil. And that this is much too depleted to be consistent with the CBB cycle OR any typical methanotrophs growing on light methane. This must point towards a local influx of geogenic, isotopically highly depleted (potentially fossil ?) methane in this one limestone sample. But I agree that especially the biofilm samples in basalt (lighter than -30 permil) are in clear agreement with the CBB\n\n4. There is a clear increase of methanotrophs towards the cave interior. Same as for methane (Esp. for basalt), consumption rates, fluxes, and per-cell power availability. All of this is not fully consistent with a consumption (and influx) of atmospheric methane via the entrance alone. In addition, there must be a contribution of geogenic methane influx. This should be better discussed, same as its implications for the “aerotrophy” concept as defined by the authors. Geogenic methane is still a trace gas, but does not come from the atmosphere.\n\n5. Along the same line, I am perfectly fine with the authors’ findings on aerotrophic chemosynthesis being ubiquitous and unexpectedly important in cave microbiota. Their overarching conclusions on aerotrophy being able to sustain microbial life clearly beyond mere survival or maintenance energy needs and over longer time spans are convincing and novel.\nBut still, I suggest to add another grain of caution to some remaining statements on e.g. “dominant primary producers” e.g. line 153. More sampling and data (seasonal or hydraulic event-triggered) would be required to really waterproof such posits, especially for members of the well-known and typically heterotrophic lineage of the Actinobacteriota. At least the option of transient and dynamic heterotrophic, mixotrophic, or aerotrophic growth should not be excluded.\n\nAlso the abstract does not offer any conditional or cautioning statements in the latest version. Please add accordingly.\n\nMinor comments:\nL97: Consistent taxonomic rigour must be used throughout MS, Text and Figs. E.g. Proteobacteria are correctly named “Pseudomonatdota” etc. Please check https://doi.org/10.1099/ijsem.0.005056 and elsewhere for the latest authoritative nomenclature.\nL103: marker genes of basic physiologies?\nL116: give abundance range of photosynthesis genes at entrance.\nL139: I would refrain from calling them “strategies”, as long as overall activity and rate data are not always available. “Capacities”?\nL167: Pseudomonadaceae are NOT within the Actinomycetia, no way! Egibacteracerae, of course, are?\nL169: caves appear to…\nL 171 here and elsewhere report findings in past tense."}, "author_response": "Reviewer #1 (Remarks to the Author):\nBay and coworkers strongly increased the quality of the manuscript, and I fully agree with\nthe molecular analysis and observations made in Fig. 1 to 3. Indeed, caves harbor many\nmicroorganisms with the genomic potential to use H2, CO2, and CH4 airborne gases. But do\nthey use this potential to produce a substantial amount of chemolithogenic biomass? I\nquestion the claims made about the importance of these substances as energy sources for\nmicroorganisms.\nWe thank the reviewer for this important question and agree to tone down prediction\nin this regard by removing subjective terms such as high and significant without\nqualification.\nL449-453 - Methanotrophs also contribute to carbon acquisition, as they are estimated\nto assimilate -3.5 x 10-7 to - 2.0 x 1.02-12 nmol C cell-1 min-1 based on their ex situ cell-\nspecific oxidation rates, and a theoretical 40% carbon conversion efficiency, which is\nfurther supported by their activities based on the in situ flux analysis (Fig. 5b;\nExtended Data Table 7b).\nL279 - Trace gas oxidation occurs together with nitrification and sulfide oxidation\nWe have removed the term ‘significant’ where no statistical test was performed,\nincluding the following sentences:\nL359-362 - Power per cell outputs were similar between rock types and cave depths\nfor H and CO, but were higher in basalt compared to limestone, and between surface\n2\nand subsurface for CH (Fig. 4d; Extended Data Table 5b).\nacquisition from atmospheric substrates occur continuously, with chemosynthetic\nprimary productivity being sustained across a range of cave surfaces.\nThere might indeed be higher H2 concentrations at the cave's entrance than in the twilight\nzone, but I do not see any further trend toward the interior of the caves. If so, only the\nentrance /twilight zones show hydrogen consumption, but the middle and deep zones of the\ncaves do not further contribute to hydrogen oxidation, and the same holds for other gases.\nWe respectfully disagree that the absence of a further declining trend of gas\nconcentrations with the distance from the interior of the caves necessarily implies no\nmicrobial oxidation in the interior. As we explained thoroughly during the last\nrevision, gas concentrations within caves are influenced by multiple factors\nespecially cave geomorphological features that affect gas equilibrium. In a system\nwhere gas transport and equilibrium exceed local consumption, it is reasonable to\nexpect little variations in measured concentrations. For example, soils are known to\nbe the largest sink for trace gases but the high equilibrium rates of the atmosphere\nwill mask local consumption if ambient gas concentrations at soil surface are\nconsidered as a sole indication of consumption. The distance from the twilight to\ndeep zones within the sampled caves is relatively short. Gas diffusion and mixing is\nexpected to occur rapidly, though a moderate declining trend of gas at the deep\ninterior is still sometimes observed (e.g. in limestone cave).\nIn the manuscript, we provide multifaceted evidence that trace gas oxidation is\nwidespread (by genome-resolved metagenomics) and active (by flux, activity, and\nisotope studies) across all caves samples. Active trace gas oxidation by cave\nsamples across all depths was validated through both in situ flux chamber\nmeasurement and ex situ microcosm incubations. These rates are theoretically\nsufficient to maintain the energy needs of all microbes capable of using these gases,\nas well as generate biomass. As in the last revision, we agree with the reviewer that\nwe cannot determine exactly what proportion of energy and carbon is generated from\natmospheric energy sources compared to others, and have ensured that this is\nappropriately reflected in our text.\nNevertheless, we agree that the activity at entrance and twilight zones was\ninadequately described and have clarified this further in text. Reflecting the\nlimitations of the static flux chamber approach, including insufficient sediments in\none of the lava tubes, we used ex situ microcosm assays to confirm trace gas activity.\nEx situ microcosm assays across all zones confirmed active oxidation within every\nsection of the transect (entrance, twilight, transition, deep) in each of the four caves.\nDespite lower rates under potential substrate (CH , H , CO) limitation, these\n4 2\ncommunities appear to fully retain their chemosynthetic activity, even when in situ\nconcentrations are diminished below atmospheric.\nWe have changed the following:\nSection: In situ rates\nRemoved the term significantly and replaced with the average fold change instead.\nL289-291 - Ambient air concentrations of all three gases decreased 4-fold from the\ncave entrances to the interiors of the limestone caves, suggesting microbial\nconsumption (Fig. 4a; Extended Data Fig. 7).\nSection: Energy yield calculation\nWe added a cautionary statement, highlighting that the high energy yield samples\nwere constrained to entrance and twilight sites in basalt caves.\nL367- 369 - Nevertheless, the observed rates may theoretically provide sufficient\npower to support the growth and survival of localized populations of trace gas\noxidisers in these caves, particularly at the entrance and twilight sites in basalt caves.\nThe authors make statements such as high/ substantial rates without bringing their data into\ncontext. How much is 1 nM per m² and sec or 86.4 µM per sqm and day? Let’s get the\nnumber into context. The lowest oxygen fluxes on Earth were measured for the South Pacific\nGyre- about 0.1 to 1mmol per sqm and day. In the South Pacific Gyre, the oxygen\npenetration depth is 100 meters. I don’t think that anything similar can be observed in the\ncave.\nWe thank the reviewer for raising concern regarding the contextual framing of gas\nfluxes and subjective terminology.\nWe have removed the subjective term ‘greatly’ and amended the section as follows:\nL295-298 - On average, in situ CH fluxes increased from 1.4 nmol m−2 s−1 at the\n4\nentrance to 3.1 nmol m−2 s−1 inside (mean of transient and equilibrium flux estimates),\nconsistent with localized methanotrophic activity within caves (Fig. 4b; Extended Data\nFig. 7, Extended Data Table 5a)\nWe agree that the term ‘substantial’ is too subjective and have removed it from the\nfollowing sentences:\nL132-135 - A smaller proportion of cave microbes can also use rock-derived energy\nsources such as sulfide (13.9% / 18%), thiosulfate (6.7% / 7%), ammonia (4.1% / 3.5%;\nExtended Data Fig. 4), nitrite (1.2% / 3.7%; Extended Data Fig. 5), and ferrous iron\n(2.7% / 2.2%).\nL463-466 - Cave ecosystems differ from polar desert soils, the other major type of\necosystem shown to be atmospherically powered 19–21, in that trace gases appear to\ndrive continual growth rather than long-term survival in these nutrient-deprived\nenvironments.\nThe oxygen consumption in this cave is likely many times higher than the contribution of CO\n(clearly), hydrogen (for sure in the deeper cave), and methane. Hence, airborne autotrophy\nwill also result in only traces of biomass production, which will hardly affect the carbon flow\nin the cave. These are just estimates, but the key experiment to call the hydrogen\nconsumption substantial / and, if at all, is connected to maybe 1% of the oxygen\nconsumption (this would be my estimate) has not been done.\nWe thank the reviewer for this important point. We agree that without direct O\n2\nconsumption measurements, the relative contributions of CH , H and CO oxidation to\n4 2\ntotal respiration and biomass production remain unclear. As a caution we have\nremoved subjective terms and emphasised localized microbial activity rather than\necosystem scale inferences on carbon flow.\nWe have made the following changes to acknowledge the limitation of no O\n2\nmeasurements and highlighting the relative high power rates at entrance and twilight\nsites in basalt caves.\nL362-366 - As we did not simultaneously measure oxygen consumption, we are\nunable to determine what proportion of total aerobic respiration is attributable to trace\ngas oxidation. These values represent theoretical estimates averaged across all cells,\nand it is likely that only a fraction of the community is metabolically active, meaning\nthe per-cell power for active trace gas oxidisers may be higher.\nL386-389 - Altogether, our data indicate that atmospheric trace gas consumption can\ntheoretically support localized activity, including growth of the methanotrophs and\nthe survival of the hydrogenotrophs, with some bacteria potentially capable of\nchemolithoautotrophic growth using H and/or CO.\nData points such as 10^14 nmol mean the respiration of single molecules per second. This\nwould be difficult to replicate – it would take 7 billion seconds to fix the carbon of the average\ncell. It is more likely that some few cells are active, but this makes average cell-specific rates\nodd. It is like having 100000 homeless and Elon Musk at your party and stating, based on\naverage, that all your guests are millionaires.\nWe appreciate the reviewers’ important point regarding low cell specific rates and\ntheir relation to power yield required for growth. A major challenge in this field is\ndiscriminating exactly what the reviewer indicates: is atmospheric trace gas oxidation\ndominated by a several highly active cells (the highest values) or billions of low\nactivity cells (the lowest values)? This is very difficult to discriminate given H and\n2\ntypically CO are not directly assimilated into biomass, unlike CH , making techniques\n4\nsuch as SIP unreliable. It is likely somewhere in the middle. Most cells likely benefit\nfrom a low level of H and CO oxidation to sustain their basal (maintenance) needs\n2\nand use these gases purely as energy sources; indeed, for most cells, the generation\nof 10-13 to 10-15 W per cell will be sufficient for this purpose. However, it is likely that\nsome cells are also adapted to use these gases to fix carbon dioxide as primary\nproducers, including potentially much more quickly. We have made the following\nchanges to the entire power per cell section to caution our interpretation of the\ntheoretical power calculations derived from bulk cell-specific rates.\nL357 - 389 - Thermodynamic calculations based on bulk oxidation rates of H , CO, and\n4\noutput of 1.3 × 10-15, 8.3 × 10-16, and 5.8 × 10-13 W per H , CO, and CH -oxidising cell,\n2 4\nrespectively. Power per cell outputs were similar between rock types and cave depths\nfor H and CO, but were higher in basalt compared to limestone, and between surface\n2\nand subsurface for CH (Fig. 4d; Extended Data Table 5b). As we did not simultaneously\n4\nmeasure oxygen consumption, we are unable to determine what proportion of total\naerobic respiration is attributable to trace gas oxidation. These values represent\ntheoretical estimates averaged across all cells, and it is likely that only a fraction of the\ncommunity is metabolically active, meaning the per-cell power for active trace gas\noxidisers may be higher. Nevertheless, the observed rates may theoretically provide\nsufficient power to support the growth and survival of localized populations of trace\ngas oxidisers in these caves, particularly at the entrance and twilight sites in basalt\ncaves. Indeed, based on our culture-based studies of four oligotrophic bacteria that\ngrow on trace gases alone (e.g. M. gorgona), the CH power output in cave greatly\n4\nexceeds growth requirements and H power output is at the same magnitude to support\n2\ngrowth42,50. Importantly, these rates are averaged for all cells and samples, while in\nreality some microbes may co-consume these gases, notably the highly abundant\nHydrogenocavus and Hydrogenomurus. Altogether, our data indicate that atmospheric\ntrace gas consumption can theoretically support localized activity, including growth of\nthe methanotrophs and the survival of the hydrogenotrophs, with some bacteria\npotentially capable of chemolithoautotrophic growth using H and/or CO.\nmissing total oxygen consumption rates, statements such as the last sentence of the abstract\nare not justified: “Trace gases sustain a basic level of biodiversity and productivity through a\nprocess we define as aerotrophy that is supplemented by organic and inorganic input”. In fact,\nlooking at the data, it is rather unlikely that the contribution of these trace gases to the overall\nmicrobial activity is very high. A solution for this abstract could be: “The energy from airborne\ntrace gasses may support the growth of a yet unquantified share of the cave communities.\nThese organisms may add organic carbon compounds to the energy-limited cave ecosystems.\n“\nWe have amended the abstract according to the reviewer’s suggestion. We have made\nan amendment to reflect the key point that trace gases do not just support primary\nproduction in these ecosystems: they also sustain the basal energy needs of\ncommunities.\nL40-43 - In situ and ex situ biogeochemical and isotopic measurements consistently\nconfirmed that these gases are rapidly consumed at rates sufficient to meet\ncommunity-wide energy needs and potentially drive primary production.\nL46-49 - Consumption of atmospheric trace gases likely has a dual role in cave\necosystems, providing energy to sustain survival of diverse microbes and potentially\nsupporting chemosynthetic growth of an undefined fraction, thereby introducing\norganic carbon into the system. This process, which we herein define as ‘aerotrophy’,\noperates alongside organic and inorganic inputs.\nThe entire paper has an awkward tendentiousness. Whenever a rate shows a bit towards\n“aerotrophy” it is excessively reported: Just look at Fig. 4ab, discussed in line 250ff. Gas\nconcentrations decreased significantly. I don’t see significant value. If you start from twilight,\nthere is simply no decline anymore. Wording like high rates do not match if you cannot\ncompare it with other rates.\nWe thank the reviewer for this critical observation. We agree that terminology such as\nsignificant, high and substantial can be misleading if not qualified by statistical\nreference or clear reference point. We have systematically revised the manuscript to\nremove these subjective terms throughout, as described above.\nFig. 4. B: Fluxes are never negative according to the graph. But look at the MS. This would\nalso be impossible because it is a logarithmic scale. Numbers of replicates are not given. But\ndata points are up to 5 orders of magnitude different.\nWe thank the reviewer for this important point. All fluxes represent net uptake\n(negative values) and are plotted as positive values on a log scale for visualization.\nWe have amended this in the figure caption and main text make this clear.\nFig. 5: There is much higher methane than CO2 fixation (Fig. 5 c,d) – but the d13C argues\nagainst methanotrophy and more for CBB-derived fixed carbon. Of course, most of the\norganic carbon is not produced by microorganisms but is from sunlight-fixed organic matter.\nWe thank the reviewer for their interpretation of the d13C data. We agree the data is\nsuggestive of organic carbon from cave samples is predominantly contributed by\nCBB carbon fixation and it is reflected in this discussion of the results, in addition of\nthe caution that possibility of these organic carbon being derived from external plant\nderived matter:\nThe organic fractions in the cave samples exhibited a depletion of 13C (δ13C ) from\norganic\n-21.7 to -67.4 ‰, consistent with biomass derived from CBB cycle, but distinct from\nother carbon fixation pathways51,52 (Fig. 5a). It is likely that some of organic carbon\nare external plant-derived inputs (allochthonous inputs) transported into cave\ninteriors.\nHowever, it’s highly likely that that some organic carbon is derived from\nmethanotrophy and microbial carbon fixation. First, both correlations and random\nforest analysis showed that marker genes for CBB (RuBisCO) and methanotrophy\n(PmoA) are the best predictors of measured d13C values, noting the former is\nwidespread in microbes and plants. Second, biofilm samples which showed more\nnegative d13C values of organic carbon than sediment samples are more enriched in\nmethanotrophs. Both observations cannot be reasonably explained if organic matter\nof the sample is solely derived from same sunlight-fixed organic matter. We provide\nbalanced consideration of both processes in the revised manuscript.\nL244ff: I cannot agree that trace gas consumption is described as high rates.\nFig. 4a: Extended data Figure 7: I do not see a substantial or statistically significant\ndecrease for most curves, except “entrance” and methane in twilight. If so, there is a\ndifference between T0 and T1 – not after. The entrance of the cave might be a difference.\nWe thank the reviewer for highlighting this observation in our flux data. Indeed, ED\nFigure 7 shows that the majority of the observed flux for H , in particular at entrance\n2\nand twilight samples stem from the t0-t1 step.\nFor context, we have repeated the calculations and now present a dual flux analysis,\nwhere we show a ‘transient flux phase’, which includes the t0 timepoint, and an\n‘equilibrium flux phase’, which shows the fluxes under equilibrated conditions,\nexcluding t0. Transient flux measurements are therefore a high range estimate, since\nthey include the full time series with ambient conditions. They capture the maximum\npotential uptake rate, incorporating the steepest concentration drop (ambient (t0) - t1).\nThey are highly sensitive to changes in initial concentration and therefore have the\npotential to overestimate steady state consumption. Equilibrium fluxes are predicted\nto be a lower range estimate since they only capture consumption once the chamber\nconditions are fully equilibrated. Removing the ambient condition and exaggerated\ninitial draw down, equilibrium fluxes are a more conservative lower bound estimate on\nmicrobial soil to air fluxes.\nBy presenting both transient and equilibrium fluxes side by side (Fig. 4b), we show\nthe likely maximum (transient) and minimum (equilibrium) bounds of microbial gas\nuptake. This is also in light of the large flux range, which covers multiple orders of\nmagnitude. Both analyses show net in situ consumption of all gases, albeit at varying\nrates, supporting our conclusions.\nOverall, this analysis shows that H fluxes at entrance and twilight zones are mostly\n2\naffected by the rapid change between t0-t1 timepoint. Carbon monoxide and methane\nfluxes, largely retain their flux trend across all samples under both transient and\nequilibrium flux phases, and retain an increasing trend with cave depth, in line with\nour conclusions.\nLine 343ff: particularly high hydrogenotrophic carbon fixation rates of 6.7*10^-12 nmol per\ncell and minute – that does not sound to be a lot.\nWe thank the reviewer and have toned down this statement.\nL418 – 422 - Notably, basalt biofilm and soil microbes mediated higher\nhydrogenotrophic CO fixation activities (4 × 10-13 nmol 14C cell-1 min-1) compared to\n2\naverage rates by limestone sediment microbes (5.8 × 10-14 nmol 14C cell-1 min-1). This\nsupports our metagenomic inferences that H is the predominant driver of CO\n2 2\nfixation and may contribute to the observed δ13C signatures in caves.\norganic\nIt is unclear what a strong consumption means; see comment above. A change of a fractions\nof a ppm difference in flux chambers is never a lot. Here and in other cases, I miss\ncomparison with other habitats / or other rates.\nWe agree that the term ‘strong’ is too subjective without direct comparison and have\nremoved it through the manuscript.\nLine 364: About half of the carbon should come from CO2 when methane is assimilated.\nMethane assimilation cannot be three orders of magnitude higher than CO2 assimilation.\nYou may have triggered methane oxidation by the addition of large amounts of 14C-tracer.\nUnfortunately, methods do not describe 14C-methane oxidation rates. I fear that these high\nrates derive from incubations with large amounts of 14C: 1 MBq carbon/CH4 is already 0.4\nµmol. Please report also on the duration of this incubation.\nWe thank the reviewer and would like to clarify our approach. No 14C-labelled methane\nwas used in this study. All radiotracer experiments were conducted using 14C-\nbicarbonate to measure CO fixation under H enriched conditions. We estimated\n2 2\nmethane carbon assimilation based on our ex situ microcosm experiments and the\nderived cell specific reaction rates. We applied a 40% carbon conversion efficiency\nbased on literature values to determine a theoretical approximation. These values\nwere not intended to serve as a direct comparison to our 14C CO fixation rates.\nL449-453 - Methanotrophs also contribute to carbon acquisition, as they are estimated\nto assimilate -3.5 x 10-7 to - 2.0 x 1.02-12 nmol C cell-1 min-1 based on their ex situ cell-\nspecific oxidation rates, and a theoretical 40% carbon conversion efficiency, which is\nfurther supported by their activities based on the in situ flux analysis (Fig. 5b;\nExtended Data Table 7b).\n14CO2-based rate measurement: (line 637) 14C isotope labeling is not the correct\nterminology here). Note that you measure hydrogen-dependent CO2 fixation rates at H2\nconcentrations that are 100 times elevated compared to nature. Still, these rates are small.\nWe thank the reviewer and agree with both points. We have revised the terminology to\n14CO fixation assay throughout. We also agree that hydrogenotrophic CO fixation\n2 2\nassays don’t represent hydrogenotrophic CO fixation at ambient H concentrations.\n2 2\nInstead, enriching the H concentration was necessary to elicit a measurable\n2\nresponse above background 14CO fixation. This also reflects competition from\n2\nunlabelled bicarbonate and internal CO cycling. We have added this caution to the\n2\ntext, emphasising these findings as a conservative estimation of CO fixation\n2\npotential rather than absolute values.\nL422-427 - Gross carbon fixation rates are probably orders of magnitude higher than\nmeasured 14CO -fixation rates, as unlabelled native inorganic carbon and internally\n2\nrecycled CO within samples invariably competed with the trace levels of added 14CO ,\n2 2\nespecially in carbonate-rich limestone samples. Therefore, these rates are a\nconservative estimate to only reflect the potential for hydrogenotrophic CO fixation\n2\nunder elevated H conditions, not ambient rates.\nstart picking on the higher concentrations after a lack phase. This may suggest that\nenvironmental trace gas concentrations are hardly used.\nWe agree with the reviewer that as a standalone figure it is not meaningful. We added\nExtended Data Figure 9 to show the oxidation traces as well as linear and nonlinear\nmodel fits.\nPlease find a meaningful order of the methods i.e., best use the order of how data appears\nin the MS\nThank you, we have amended the order of methods to follow the manuscript flow.\nReviewer #2 (Remarks to the Author):\nThe authors have addressed nearly all of my concerns, and the manuscript is much\nimproved. I still don't like \"aerotrophy\" as used here, but I seem to be alone in this opinion.\nWe thank the author for their review.\nReviewer #3 (Remarks to the Author):\nComments and Suggestions for Authors\nBay and colleagues have investigated metagenomic capacities and actual biogeochemical\ncues for active microbial consumption of atmospheric trace gasses, mostly H2, CH4 and CO,\nin 4 Southern Australia cave systems. Cave microbiota are compared across longitudinal\ntransects and different compartments of two basalt and two limestone caves in Victoria. With\n~1500 high-quality MAGs assembled for many dozens of samples, ~half of the MAGs hosted\ncapacities to consume either one of the different trace gasses. Amongst them, abundant\nhydrogenotrophic candidate genera within the Actinobacteriota, methanotrophic\ngammaproteobacterial Ca. Methylocavales, and also some MAGs of enigmatic candidate\nphyla. Aerotrophic primary production is shown to be substantial throughout most samples,\nwith methane and hydrogen-derived energy delivering enough power-per-cell to allow for\ncontinued growth, or at least sustained activities and survival in lack of other substrates. The\nconcept of, at least temporary or partial, aerotrophy as a dominating physiology in caves is a\nhighly interesting addition to our understanding of these underexplored ecosystems. This\npiece clearly warrants publication in a journal like NatComms.\nStill, before acceptance, the authors should address the following comments:\n1. It Would be good if the results (& discussion) section could start with some basic primers\non the nature of the sampled cave systems (basalt and limestone), locations (entrance,\nlongitudinal transects) sample types (biofilms, sediment, …) and overall sample numbers.\nThis is important to grasp the scope of the study, as not every reader will (first or at all?)\ngrind through the M&M or supplement. Just a bit more info on the basic settings of the study,\nbefore delving into all the community composition and the metagenomic details.\nWe thank the reviewer and agree to add an additional set up to this section. We have\nadded the following text:\nL98-102 - We studied four aerated caves in southeastern Australia, two limestone and\ntwo basalt lava tubes (Fig.1a). In each cave, we sampled along a transect extending\nfrom the entrance to twilight, transition and deep zones. We collected a total of 94\nenvironmental samples including sediments, biofilm, and mineral samples, which\nwere analysed using metagenomics as well as gas and isotopic studies to determine\nmicrobial composition, function and metabolic activity.\n2. In contrast to the authors notion, caves do typically not contain soil (Fig. 1b). Unless it is\nwashed in or collapses in from above. Please change to “Sediments” in Fig. 1b, as correctly\nimplemented already in other Figs. Also, “soil” must still be replaced on some occasions\nthroughout the text, e.g. L129 or L343.\nWe thank the reviewer and agree that in the absence of a true soil matrix ‘sediment’ is\na more appropriate term. An exception are samples collected at the cave entrance or\ndoline where the material on the cave floor reflected soils rather than sediment. To\nensure consistency we have changed the name from soil to sediment in all instances,\nwhich exception for entrance samples, referring explicitly to material resembling\ncharacteristics of surface soil.\n3. L318: this must be a mistake. Explain that this was just one sample of many dozens with\nthis extremely light signature at MINUS (!) 67.4 permil. And that this is much too depleted to\nbe consistent with the CBB cycle OR any typical methanotrophs growing on light methane. This\nmust point towards a local influx of geogenic, isotopically highly depleted (potentially\nfossil ?) methane in this one limestone sample. But I agree that especially the biofilm\nsamples in basalt (lighter than -30 permil) are in clear agreement with the CBB\nWe thank the reviewer for the insightful comment. The one sample with highly\nnegative d13C values was not sequenced and thus we could not confirm the main\norganic\npathway of organic carbon formation that best explain the measured value. As a\ncaution, we have now elected to remove this outliner and clarified this in the methods.\n4. There is a clear increase of methanotrophs towards the cave interior. Same as for\nmethane (Esp. for basalt), consumption rates, fluxes, and per-cell power availability. All of\nthis is not fully consistent with a consumption (and influx) of atmospheric methane via the\nentrance alone. In addition, there must be a contribution of geogenic methane influx. This\nshould be better discussed, same as its implications for the “aerotrophy” concept as defined\nby the authors. Geogenic methane is still a trace gas, but does not come from the\natmosphere.\nWe thank the reviewer for this important point. A limitation of our study is that we did\nnot use isotope studies to differentiate the sources of atmospheric trace gases. We\namended the manuscript as follows:\nL258-261 - It is likely that these gases are predominantly atmospherically derived,\ngiven their concentrations are at or below global average concentrations of these\ngases in the lower troposphere47–49, though it can’t be ruled out that they are also\nproduced through geogenic and biological processes and maintained at such\nconcentrations through microbial consumption.\nL470-473 - Given the relatively stable environment, humid conditions, and aeration of\nmost caves, it is predicted that aerotrophs will continually cycle gases such as\nhydrogen, methane, and carbon dioxide, whether of atmospheric origin or geogenic\norigin (including at atmospheric concentrations), allowing continuous primary\nproduction.\n5. Along the same line, I am perfectly fine with the authors’ findings on aerotrophic\nchemosynthesis being ubiquitous and unexpectedly important in cave microbiota. Their\noverarching conclusions on aerotrophy being able to sustain microbial life clearly beyond\nmere survival or maintenance energy needs and over longer time spans are convincing and\nnovel. But still, I suggest to add another grain of caution to some remaining statements on\ne.g. “dominant primary producers” e.g. line 153. More sampling and data (seasonal or\nhydraulic event-triggered) would be required to really waterproof such posits, especially for\nmembers of the well-known and typically heterotrophic lineage of the Actinobacteriota. At\nleast the option of transient and dynamic heterotrophic, mixotrophic, or aerotrophic growth\nshould not be excluded.\nWe thank the reviewer and have revised as follows:\nL174-179 - Most hydrogenases, CO dehydrogenases, and RuBisCOs were co-\nencoded by the most abundant Actinobacteriota lineages residing in the caves\n(primarily classes Actinomycetia, Thermoleophilia, Acidimicrobiia, and Ca. Aridivitia)21\n(Fig. 3a), suggesting that they may be important primary producers in these\necosystems, although we cannot exclude the possibility of transient and dynamic\nheterotrophic and mixotrophic strategies.\nAlso the abstract does not offer any conditional or cautioning statements in the latest\nversion. Please add accordingly.\nWe agree and note that a similar point was raised by Reviewer 1. We have amended\nthe final sentence of the abstract as follows:\nConsumption of atmospheric trace gases likely has a dual role in cave ecosystems,\nproviding energy to sustain survival of diverse microbes and potentially supporting\nchemosynthetic growth of an undefined fraction, thereby introducing organic carbon\ninto the system. This process, which we herein define as ‘aerotrophy’, operates\nalongside organic and inorganic inputs.\nMinor comments:\nL97: Consistent taxonomic rigour must be used throughout MS, Text and Figs. E.g.\nProteobacteria are correctly named “Pseudomonatdota” etc. Please\ncheck https://doi.org/10.1099/ijsem.0.005056 and elsewhere for the latest authoritative\nnomenclature.\nOur manuscript is taxonomically rigorous and adopts the taxonomy of the GTDB\nrelease (GTDB release 214, April 28 2023) in which we annotated these MAGs.\nL103: marker genes of basic physiologies?\nWe thank the reviewer and have clarified as follows (using key rather than basic):\nL122-124 - The energy and carbon acquisition strategies of the cave microbes were\ninferred by searching for 52 conserved marker genes encoding the potential of key\nenergy and carbon acquisition processes in the MAGs and short reads (Fig 2a;\nExtended Data Table 4a-c).\nL116: give abundance range of photosynthesis genes at entrance.\nWe thank the reviewer and have added this as follows:\nL161-L162 - As expected, photosynthesis genes were abundant in sediments and\nbiofilms at the entrance of each cave (29%) but declined by an average of 72-fold in\nthe cave interior.\nL139: I would refrain from calling them “strategies”, as long as overall activity and rate data\nare not always available. “Capacities”?\nWe thank the reviewer and have added the term ‘potential’ as follows:\nL122-124 - The energy and carbon acquisition strategies of the cave microbes were\ninferred by searching for 52 conserved marker genes encoding the potential of key\nenergy and carbon acquisition processes in the MAGs and short reads (Fig 2a;\nExtended Data Table 4a-c).\nL167: Pseudomonadaceae are NOT within the Actinomycetia, no way! Egibacteracerae, of\ncourse, are?\nWe thank the reviewer for spotting this unfortunate error. We have corrected this to\nPseudonocardiaceae which are Actinomycetia.\nL169: caves appear to…\nWe thank the reviewer and have checked this sentence. It reads: Thus, caves appear\nto select for highly productive actinobacterial primary producers that grow on\natmospheric energy and carbon sources.\nL 171 here and elsewhere report findings in past tense.\nWe thank the reviewer and have checked the manuscript for these instances\nthroughout.\nWe thank reviewers 1-3 for their insightful and thorough and thoughtful comments.\nWe hope these edits address their concerns and present a more precise and balanced\nnarrative."}, {"round": 2, "reviewer_comments": {"reviewer_1": "Bay and coworkers significantly improved the paper; however, I still have some questions/ remarks:\n\nL41ff: at rates sufficient to meet community-wide energy needs this need to be tested differently, as it would mean that all biomass would cycle internally, i.e. also biomass of heterotrophs. Below I used your data from CO2 fixation that this is not the case. i.e. in a single example I calculated biomass turnover time of 35,000 years. I simply doubt that this meets the energy demands of all organisms. Maybe: with rates which likely sustain the energy demands of a substantial fraction of the community.\"\n\nL114: keep consistently present tense when talking about metagenomic data, “encode”, and past when you talk about rates...\n\nL120: be moderate: You can not infer from MAGs that organisms do something: … of cave microorganism that encode enzymes that would allow the use of.. or something\n\nL153: avoid novel here\n\nL169: belong to high-affinity clades of hydrogenases\n\nL183: I discourage the authors from naming uncultured organisms after potential energy sources. i.e., to my knowledge, there are no other hydrogenotrophs within the Pseudonocardinaceae, Egibacteraceae, and Actinomycetia – all of them are rather heterotrophs. Spreading this attribute and manifesting it in their names, based on metagenomic information, seems to be wrong. To my knowledge there are no knallgas bacteria in the Actions. Culture them in the lab, investigate their capabilities, and then this naming is adequate. Instead you may use locations in the name.\n\nL293: Sulfur and iron are only energy substrates when they are reduced. Total S and Fe are not important. What species do you speak of?\n\nL323: Again, I do not see convincing evidence for the growth of these organisms as hydrogen oxidizers. If you want to state this, cultivate the organisms.\n\nL 329ff: The isotopic signatures of most organic matter from cave samples are also consistent with photosynthetic matter, which is no surprise because they use the same C-fixation pathway. Only the basalt biofilm shows robust signs for another carbon source/pathway, which could indeed be methane-derived organic matter.\n\nL357ff: Please contextualize your data – here the reported carbon fixation rates: “Notably, basalt biofilm and sediment microbes mediated higher hydrogenotrophic CO2 fixation activities (5.7 × 10-13 nmol 14C cell-1 min-1) compared to average rates by limestone sediment microbes (5.3 × 10-14 nmol 14C cell-1 min-1). “\nIs this a lot? Let’s see how long it would take to build 1.2 % carbon - (12 mg=1 mmolC) this way, 5.3x10^-14 nmol/min per cell * 10^9 cells per g (I guess it is less in this particulate sample – we have 5.3x10^-5 nmol per minute and ccm. How much time does it take to fix 1 mM? To fix 1 mmol of carbon, this takes 1/(5.3*10-5*10-^-6) minutes = 1/(5+10^-11) minutes = 35,870 years!\nTherefore, it would take 35,000 years to rebuild the 1% carbon. Although sedimentation rates of organic matter in the caves will also be quite low, it appears that the contribution of CO2 fixation is relatively low.\nI ask for similar comments like this in earlier versions.\n\nSince methanotrophs will always fix ~20% of the carbon from CO2, methane carbon fixation can only be four times higher than that. Additionally, we also miss discussing heterotrophic CO2 fixation, which can also be part of the discussion. In total it seems that methane oxidation rates are orders of magnitude higher than H2 oxidation (although so many more organisms encode hydrogen oxidation).\n\nThe conclusions are not justified.\n\nL376: “Here we provide extensive metagenomic and biogeochemical evidence that diverse caves are atmospherically powered ecosystems.” See above. Given your data (i.e., H2 consumption, CO2 fixation), I don’t think you can make this claim. As suggested earlier, and implemented before:\nHere we provide extensive metagenomic and biogeochemical evidence that diverse caves are atmospherically powered ecosystems.\nHere, we provide metagenomic and biogeochemical evidence for the consumption of atmosphere-derived trace gases in cave sediments and biofilms (note that this does not include lakes, walls, etc.). This consumption may feed a yet-to-be-quantified fraction of the microbial community. (or something similar)\n\n“Primary production appears to be driven by highly abundant and active methanotrophs, as well as novel lineages of actinobacterial lithoautotrophs, that continuously use the gases methane, hydrogen, carbon dioxide, and carbon monoxide present in cave atmospheres.”\nI still have my doubts about the hydrogenotrophic nature of actinobacteria. Please also split these arguments. Primary production is performed by different microorganisms. This includes abundant and active methanotrophs. Novel lineages of Actinobacteria encode the capacity to grow as chemoautotrophs. Together, they may use trace gases such as methane, hydrogen, and carbon monoxide as energy sources.\"\n\nL413: Again, you did not at all quantify the contribution of aerotrophy to the cave ecosystem. All these statements require a comparison of methane/H2, etc, consumption\n\nL420: Better: \"Altogether, our analyses suggest that atmospheric trace gases support a basal level of primary production and energy conservation, which in turn sustains the substantial biodiversity found in various cave ecosystems.\"", "reviewer_3": "Thanks to the authors for their careful and well-balanced rework of the submitted manuscript.\nNo further requests."}, "author_response": "Reviewer #1 (Remarks to the Author):\nBay and coworkers significantly improved the paper; however, I still have some questions/\nremarks:\nWe thank the reviewer for their further appraisals and suggestions, and have further\ntoned down and cautioned our findings.\nL41ff: at rates sufficient to meet community-wide energy needs this need to be tested\ndifferently, as it would mean that all biomass would cycle internally, i.e. also biomass of\nheterotrophs. Below I used your data from CO2 fixation that this is not the case. i.e. in a\nsingle example I calculated biomass turnover time of 35,000 years. I simply doubt that this\nmeets the energy demands of all organisms. Maybe: with rates which likely sustain the\nenergy demands of a substantial fraction of the community.\"\nThe abstract has been revised accordingly.\nL114: keep consistently present tense when talking about metagenomic data, “encode”, and\npast when you talk about rates...\nWe agree and have revised throughout.\nL120: be moderate: You can not infer from MAGs that organisms do something: … of cave\nmicroorganism that encode enzymes that would allow the use of.. or something\nWe agree and have tempered claims of function as follows:\nL121: These findings suggest that most microbial cells in caves encode enzymes that\ncould enable trace gas oxidation.\nL153: avoid novel here\nWe have replaced with ‘previously uncharacterised’ to reflect these microbes have\nnot been previously characterized genomically and metabolically.\nL169: belong to high-affinity clades of hydrogenases\nWe have revised this sentence accordingly:\nL177-180: Corroborated by the short-read analysis (Fig. 2a, Extended Data Table 4b),\nalmost all of these belong to high-affinity clades of hydrogenases (groups 1h, 1l, and\n2a [NiFe]-hydrogenases21,39,40) (Fig. 2a), suggesting they are adapted to atmospheric\nrather than elevated levels of these gases.\nL183: I discourage the authors from naming uncultured organisms after potential energy\nsources. i.e., to my knowledge, there are no other hydrogenotrophs within the\nPseudonocardinaceae, Egibacteraceae, and Actinomycetia – all of them are rather\nheterotrophs. Spreading this attribute and manifesting it in their names, based on\nmetagenomic information, seems to be wrong. To my knowledge there are no knallgas\nbacteria in the Actions. Culture them in the lab, investigate their capabilities, and then this\nnaming is adequate. Instead you may use locations in the name.\nWe consulted with the Editor on this point and they have confirmed they are happy for\nus to use the originally proposed names. We respectfully maintain that function-\nbased candidate names are appropriate under current Candidatus nomenclature\nconventions and in harmony with the SeqCode and GTDB placeholder naming logic.\nAutotrophic growth on H has been reported on multiple actinobacterial isolates,\n2\nincluding reports from over 60 years ago, such as Pseudonocardia autotrophica\n(previously known as Streptomyces autotrophicus; doi.org/10.1007/BF00424890) and\nMycobacterium gordonae (doi.org/10.1099/00207713-24-3-338). These actinobacteria\nsimilarly encode the same set of genes required for Knallgas-like metabolism as we\nidentified in the three named cave actinobacterial taxa (group 1h hydrogenases and\nCBB cycle, in addition to CODH).\nOur proposed names are based on high quality MAGs (completeness ≥ 84 %,\ncontamination ≤ 3.3 %) underscoring robustness of their metabolic predictions.\n ‘Candidatus Hydrogenomurus basanatii’ (MAG SE1519_metabat2.bin.2; 100% /\n2.8%)\n ‘Candidatus Hydrogenocavus calcicola’ (MAG M3-B2_metabat2.bin.58; 96.6% /\n3.3%)\n ‘Candidatus Hydrogenolapis speleophilus’ (MAG SD8021_metabat2.bin.4;\n84.1% / 1.1%)\nThe 2019 International Code of Nomenclature of Prokaryotes (Parker et al. 2019)\nexplicitly allows genome assemblies combined with predicted metabolic features and\nhabitat preference to underpin a Candidatus designation (Appendix 11). Guidance on\nthe vernacular epithet (Appendix 11.3) states that it may be any genus / species\nnames provided the description include genomic, physiological / metabolic and\nenvironmental information.\nThis approach has been widely adopted, prominent examples include ‘Candidatus\nMethanoperedens nitroreducens’ (Haroon et al., 2013, Nature), named for its nitrate-\ndependent methane oxidation, and ‘Candidatus Nitrososphaera gargensis’ (Spang et\nal. 2014, Environmental Microbiology), named for its ammonia-oxidizing capacity.\nThese function-based names are both permissible under the ICNP guidance and\nremain highly informative for the wider research community.\nOur etymologies in Supplementary note 2 include MAG source, quality metrics and\nlinguistic derivations. For example, Hydrogenomurus basanatii combines N.L.\nhydrogenum (“hydrogen”) + L. murus (“wall”), with basanatii denoting “of the basalt\ncave.” Overall names accurately reflect the predicted trace gas lifestyles and are\nderived from high quality genomic data and robust functional gene predictions.\nL293: Sulfur and iron are only energy substrates when they are reduced. Total S and Fe are\nnot important. What species do you speak of?\nWe thank the reviewer for highlighting the need to specify redox species. We report\ntotal sediment ammonium, sulfur etc., only for geochemical context. The consumption\nof these substrates was determined by our nitrification and sulfide oxidation assays,\nwhich measured changes in the aqueous species NH₄⁺, NO₂⁻, NO₃⁻, and SO₄²\nrespectively as reported in Extended Data Table 6. We have modified the text to better\nclarify this.\nL321-325: “The cave sediments contained varying concentrations of ammonium (1.35-\n40.2 mg/kg), sulfur (7.3-2468 mg/kg), and iron (6.96-2003 mg/kg) (Extended Data Table\n1). Microcosm incubations showed ammonium was oxidised at variable rates across\nthe samples and increased from the entrance to interior of the cave (Fig. 4e; Extended\nData Fig. 11; Extended Data Table 6).”\nL323: Again, I do not see convincing evidence for the growth of these organisms as\nhydrogen oxidizers. If you want to state this, cultivate the organisms.\nAs we elaborated in the text, the inference is based on multiple independent evidence,\nincluding the genomic characterization of these organisms, carbon stable isotope\nsignatures of pure culture benchmarks of hydrogenotrophs (C. necator H16; H.\npseudoflava) compared to cave samples, H oxidation rate power calculation (1.5 x 10-\n2\ncharacterized aerotrophs (e.g. Methylocapsa gorgana), and the detection of\nstimulated 14CO incorporation when supplied with H .\n2 2\nHowever, we agree cultivation will be necessary to definitely prove this and have now\nincluded a new sentence to better caution this:\nL366-367: “We note that cultivation of these microorganisms will be a necessary next\nstep to validate their capacity to grow on atmospheric gases.”\nL 329ff: The isotopic signatures of most organic matter from cave samples are also\nconsistent with photosynthetic matter, which is no surprise because they use the same C-\nfixation pathway. Only the basalt biofilm shows robust signs for another carbon\nsource/pathway, which could indeed be methane-derived organic matter.\nWe have now explicitly presented this other possibility in the setup sentence of this\nsection as follows:\nL374-375: “It is likely that organic carbon from external plant-derived inputs\n(allochthonous inputs) is transported into cave interiors. However, despite δ¹³C\norganic\nvalues overlapping those of C₃‐plant detritus (a shared CBB signature), multiple lines\nof evidence suggest cave-dwelling primary producers are also major sources of\norganic matter (autochthonous inputs)”.\nL357ff: Please contextualize your data – here the reported carbon fixation rates: “Notably,\nbasalt biofilm and sediment microbes mediated higher hydrogenotrophic CO2 fixation\nactivities (5.7 × 10-13 nmol 14C cell-1 min-1) compared to average rates by limestone\nsediment microbes (5.3 × 10-14 nmol 14C cell-1 min-1). “\nIs this a lot? Let’s see how long it would take to build 1.2 % carbon - (12 mg=1 mmolC) this way, 5.3x10^-14 nmol/min per cell * 10^9 cells per g (I guess it is less in this particulate sample – we have 5.3x10^-5 nmol per minute and ccm. How much time does it take to fix 1 mM? To fix 1 mmol of carbon, this takes 1/(5.3*10-5*10-^-6) minutes = 1/(5+10^-11) minutes = 35,870 years!\nTherefore, it would take 35,000 years to rebuild the 1% carbon. Although sedimentation rates of organic matter in the caves will also be quite low, it appears that the contribution of CO2 fixation is relatively low. I ask for similar comments like this in earlier versions.\nWe appreciate the reviewer for their further comments and calculations on the 14C\nfixation assay. However, as we have elaborated and discussed in the last revision, the\n14CO measurements do not reflect gross carbon fixation rates as abundant carbon\n2\n(predominantly non-radioactive 12C) already present within cave samples and CO in\n2\nthe ambient air headspace will compete with added 14CO (400 ppm), leading to a\n2\nsubstantial underestimate of true carbon fixation rates. As a context, the cave\nsamples have carbon content between 1.7 - 29%, which are many orders of magnitude\nhigher than the provided 14CO tracer. Therefore, the multi-thousand years carbon\n2\nturnover calculation by the reviewer is impropriate in this context.\nThe 14C measurements clearly demonstrated H supplementation significantly\n2\nenhanced carbon fixation compared to the dark control, strongly suggesting H\n2\noxidation is coupled to carbon fixation in line with metagenomic and genomic\ninference, whereas photosynthetic carbon fixation is minimal at inner caves.\nWe have now further elaborated this:\nL402-406: “Gross carbon fixation rates are probably orders of magnitude higher than\nmeasured 14CO -fixation rates, as unlabelled native inorganic carbon, CO from the\n2 2\nambient air headspace, and internally recycled CO within samples invariably\n2\ncompeted with the trace levels of added 14CO (400 ppm), especially in carbonate-rich\n2\nlimestone samples (1.7 - 29% carbon; Extended Data Table 1). Therefore, these rates\nare a conservative estimate to only reflect the potential for hydrogenotrophic CO\n2\nfixation under elevated H conditions, and should not be interpreted as ambient net\ncan only be four times higher than that. Additionally, we also miss discussing heterotrophic\nCO2 fixation, which can also be part of the discussion.\nWe thank the reviewer for raising this point. We would like to clarify that our methane\ncarbon assimilation studies are based on the assumption of methane carbon\nassimilation primarily via the serine and RuMP pathways, not autotrophic CO\n2\nfixation. Soil tracer studies (Roslev et al. 1997 & 1999; Holmes et al. 1999) show that\nmethane carbon assimilation fully encompass our 40% conversion factor. (methane\noxidation rate * 0.4). We have amended this section including relevant references as\nfollows:\nL408-411: Methanotrophs also contribute to carbon acquisition from methane, as they\nare estimated to assimilate 3.5 x 10-7 to - 1.1 x 10-12 nmol C cell-1 min-1 based on their ex\nsitu cell-specific oxidation rates, and a theoretical 40% methane-carbon conversion\nefficiency53–55, which is further supported by their activities based on the in situ flux\nanalysis (Fig. 5b; Extended Data Table 7b). We acknowledge that methanotrophic CO\n2\nfixation via the CBB cycle as well as other dark and anaplerotic processes not\naccounted for in this study may contribute to inorganic CO fixation in caves.\noxidation (although so many more organisms encode hydrogen oxidation).\nThat’s incorrect, the average rates of H , CH , and CO oxidation in cave samples are 6\n2 4\n× 10-2 , 8.1 × 10-3 , 2.5 × 10-3, at their respective atmospheric concentrations (Extended\nData Table 6). However, normalising these rates to a per cell basis, methanotroph\ncells appear to consume gases at a comparable or higher rates to the other gases\n(Fig. 4C).\nWe have amended the information provided in Extended Data Table 6 to include the\nintermediate steps for these calculations.\nThe conclusions are not justified.\nL376: “Here we provide extensive metagenomic and biogeochemical evidence that diverse\ncaves are atmospherically powered ecosystems.” See above. Given your data (i.e., H2\nconsumption, CO2 fixation), I don’t think you can make this claim. As suggested earlier, and\nimplemented before:\nHere we provide extensive metagenomic and biogeochemical evidence that diverse caves are atmospherically powered ecosystems.\nHere, we provide metagenomic and biogeochemical evidence for the consumption of atmosphere-derived trace gases in cave sediments and biofilms (note that this does not include lakes, walls, etc.). This consumption may feed a yet-to-be-quantified fraction of the microbial community. (or something similar).\nWe have toned down the statement and amended the sentences as follows:\nL421-423: Here we provide extensive metagenomic and biogeochemical evidence for\nthe consumption of atmosphere-derived trace gases in cave sediments and biofilms.\nThis consumption may support a potentially large fraction of the microbial\ncommunity.\n“Primary production appears to be driven by highly abundant and active methanotrophs, as\nwell as novel lineages of actinobacterial lithoautotrophs, that continuously use the gases\nmethane, hydrogen, carbon dioxide, and carbon monoxide present in cave atmospheres.” I\nstill have my doubts about the hydrogenotrophic nature of actinobacteria. Please also split\nthese arguments. Primary production is performed by different microorganisms. This\nincludes abundant and active methanotrophs. Novel lineages of Actinobacteria encode the\ncapacity to grow as chemoautotrophs. Together, they may use trace gases such as\nmethane, hydrogen, and carbon monoxide as energy sources.\"\nWe thank the reviewer for the suggestions and have split these arguments as follows:\nL423-424: Primary production appears to be driven by highly abundant and active\nmethanotrophs oxidising atmospheric methane. Novel lineages of actinobacterial\nlithoautotrophs are predicted to oxidise hydrogen to fix CO . Together, these\n2\norganisms continuously use the gases methane, hydrogen carbon dioxide and carbon\nmonoxide present in cave atmospheres.\nL413: Again, you did not at all quantify the contribution of aerotrophy to the cave ecosystem.\nAll these statements require a comparison of methane/H2, etc, consumption\nWe have further cautioned as follows:\nL464-465: Our analyses also do not differentiate the relative contribution of\naerotrophy and other chemosynthetic carbon fixation (autochthonous inputs) and\nexternal organic matter (allochthonous inputs) to the organic carbon levels observed\nin the sampled caves.\nL420: Better: \"Altogether, our analyses suggest that atmospheric trace gases support a\nbasal level of primary production and energy conservation, which in turn sustains the\nsubstantial biodiversity found in various cave ecosystems.\nWe thank the reviewer and have amended as suggested:\nL482-485: Altogether, our analyses suggest that atmospheric trace gases support a\nbasal level of primary production and energy conservation, which in turn sustains the\nsubstantial biodiversity found in various cave ecosystems.\nReviewer #3 (Remarks to the Author):\nThanks to the authors for their careful and well-balanced rework of the submitted\nmanuscript.\nNo further requests.\nWe thank the reviewer for their time and insightful comments to improve the quality of\nthis manuscript."}]

Decision letter