Biosignatures of diverse eukaryotic life from a Snowball Earth analogue environment in Antarctica

Domain: earth_science
Published: 2025-06-19
Editorial outcome: major_revision

Abstract
The ephemeral, supraglacial meltwater ponds of the McMurdo Ice Shelf’s undulating ice serve as analogues for refugia where eukaryotic organisms could have thrived during the Cryogenian period. These seafloor sediment and debris lined ponds support the growth of a diverse array of cyanobacterial mat communities and provide habitats for a variety of protists and meiofauna. Here, we show that these eukaryotic assemblages, assessed by steroid biomarker and 18S rRNA gene analyses, inform long-standing questions regarding the diversity of, and controls on, community composition in these environments. Sixteen photosynthetically active microbial mats from meltwater ponds, a 700-year-old relict microbial mat, and a microbial mat from the Bratina Lagoon were analysed for their sterol compositions. These sterols were subjected to simulated diagenesis via catalytic hydrogenation/hydrogenolysis affording their sterane hydrocarbon counterparts, facilitating comparisons with ancient settings. Pond salinity appeared to be a factor influencing the sterol distributions observed. Analyses of 18S rRNA gene sequences conducted on the modern mats independently confirm that the ponds host diverse eukaryotes, including many types of microalgae, protists, and an array of unclassifiable organisms. Our findings support the hypothesis that supraglacial meltwater ponds like those of the McMurdo ice are strong candidates for refugia that sheltered complex life during Snowball Earth episodes.

Introduction
The global prevalence of late Neoproterozoic glacial deposits at equatorial latitudes, together with a range of accompanying features such as the distinctive cap dolostones and unusual iron formations, led to the articulation of the Snowball Earth hypothesis1–3. Following extensive research in high precision geochronology, stratigraphy, palaeontology, geochemistry, and modelling, the Cryogenian period was established; the 720 to 635 million year ago interval is marked by two long-lived Sturtian and Marinoan glacial epochs with a warmer interglacial4–6. The extreme environmental transformation that took place during the Cryogenian has been cited as an evolutionary driver for the Ediacaran expansion of multicellular life7,8. The idea of a hard Snowball, a scenario in which the entire planet was encapsulated in ice so thick that sub-ice photosynthesis in the marine realm was prevented, has faced numerous critiques, with alternative proposals such as a soft Snowball, slushball9, or thin ice scenarios10 that would have been less disruptive to the marine carbon cycle. Whatever the case, it is instructive to consider the viability of eukaryotic refugia under these scenarios, specifically supraglacial settings, where aquatic photosynthesis could have been productive in support of ecosystems where complex life persisted and evolved11,12.

Supraglacial meltwater ponds, analogous to those presently scattered atop the McMurdo Ice Shelf, would have been prevalent along continental margins and supported microbial communities during the Cryogenian11–13. In turn, these communities would have sheltered antecedents for the succeeding Ediacaran Period’s diversification and proliferation of complex eukaryotic life, including the first animals5,14. Still, outstanding questions remain regarding the persistence and distribution of such eukaryotic refugia, as well as of the types of organisms that may have existed within them. The scarcity of fossil records of Cryogenian ecosystems, coupled with the low likelihood that evidence of life from supraglacial habitats could be preserved in the geologic record, highlights the value of detailed characterisations of contemporary analogues. While acknowledging that Cryogenian microbiota would have been different from those of today, it has long been recognised that the ecological and metabolic structuring of modern microbial mats serve as useful models for those of Earth’s past15.

Detailed characterisations of the eukaryotic communities of Antarctic supraglacial ecosystems are limited and, until recently, were primarily constructed through microscopy13,16–19. Such visual approaches necessitate the identification of distinct morphological characters—a prospect complicated by morphotype similarities for many eukaryotic microbial groups, including metazoa and SAR19. Early, microscopy-based identifications of diatoms, chlorophytes, chrysophytes, and metazoa have been confirmed and expanded upon via contemporary applications of environmental 18S rRNA gene sequencing techniques19–21. However, methodological challenges, such as the optimisation of primers and amplification techniques for psychrophiles, still limit the understanding of microbial eukaryotic diversity in Antarctica22. Some of these limitations may be addressed by the identification of sterols, the membrane-stabilising and cell-signalling lipid biomarkers of eukaryotes, which can be closely associated with distinct eukaryotic groups23,24. The detection of sterols and their chemically reduced counterparts, the stanols and steranes, in ancient and modern sedimentary settings enables an independent reconstruction of the eukaryotic community. Though sterol biosynthetic pathways may be shared across many eukaryotic taxa, broad classifications may be assigned, and steroid biomarker compositions may be compared across different environmental settings and time.

The McMurdo Ice Shelf’s undulating ice affords a readily accessible Cryogenian analogue environment with the opportunity to examine microbial eukaryotic distributions across a variety of supraglacial settings, including physicochemically-diverse meltwater ponds (Fig. 1 and Table 1) supporting photosynthetically active microbial communities (Fig. 2A), former pond basins that are now elevated and have desiccated (Fig. 2B), and an active meltwater lagoon system. This environment also hosts an array of marine debris on the ice surface (Fig. 2C, D). To characterise signatures of eukaryotic life across the undulating ice, steroid biomarker distributions were examined in 16 microbial mats collected from the landscape and compared with 18S rRNA gene characterisations of the mat communities. Sterols derived from the microbial mats were further subjected to simulated diagenesis via catalytic hydrogenation/hydrogenolysis to generate sterane assemblages that can be compared to those preserved in the fossil record. The results of these analyses support the notion that diverse communities of protists and meiofauna persist within supraglacial meltwater ponds, and that the meltwater refugia on the McMurdo Ice Shelf are plausible candidates for settings which harboured complex ecosystems during the Cryogenian Period.

Results
Sterol TMS ethers
Diverse assemblages of C26 to C30 sterols were identified across the ponds, Bratina Lagoon, and within the relict microbial mat. Representative chromatograms for ponds Skua, Duet, and Brack are shown in Fig. 3; systematic names corresponding to peak numbers are denoted in Table 2. A list of common names corresponding to systematic names is available in Supplementary Table 1. Twenty-nine individual steroids were identified across the samples not including the internal standard, cholest-5-en-3β-ol (2H)7. In some cases, sterols clearly co-eluted with another compound, as in peaks 16, 17, 21, 25, and 26. For peaks 21 and 26, the sterols co-eluted with non-steroidal molecules, such as α-tocopherol in the latter. 24-Ethylcholesta-5,24(28)Z-dien-3β-ol, peak 25, co-elutes with (24R)-ethyl-5α-cholestan-3β-ol on a standard DB-5MS column as shown in the supplementary material (Supplementary Fig. 1). Nine unknown steroids were identified for which standards and reference spectra were not available; their mass spectra and observed characteristics are reported in the supplementary material (Supplementary Figs. 2–10).

A sole C26 sterol, 22-trans-24-norcholesta-5,22E-dien-3β-ol, was detected in the Brack Pond microbial mat. Most samples contained a range of C27 sterols and stanols, including 5α-cholest-22E-en-3β-ol, 5β-cholestan-3β-ol, 27-nor-(24S)-cholesta-5,22E-dien-3β-ol, cholesta-5,22E-dien-3β-ol, cholest-5-en-3β-ol, 5α-cholestan-3β-ol, and 5α-cholest-7-en-3β-ol. In nearly all microbial mat samples, cholest-5-en-3β-ol had the greatest percent abundance of all sterols except in the case of ponds Skua, Fogghorne, Conophyton, Orange, Legin, Brack, and in the relict microbial mat. In those ponds except Brack and Salt, a C29 sterol, (24R)-ethylcholest-5-en-3β-ol, was the dominant sterol. Brack and Salt Pond’s sterol assemblages were dominated by 24-methylcholesta-5,22E-dien-3β-ol, a C28 sterol. The C28 sterols 24-methylcholesta-5,22E-dien-3β-ol and (24R)-methylcholest-5-en-3β-ol were present in all microbial mats examined, while 24-methylcholesta-5,24(28)-dien-3β-ol was detected in all ponds except Skua, Roger, AMS, and the Bratina Lagoon. 24-Methyl-5α-cholest-7-en-3β-ol was detected in most of the mat samples except in those from ponds Roger, AMS, Salt, the Bratina Lagoon, and the relict microbial mat.

(24R)-Methyl-5α-cholestan-3β-ol minorly contributed to the total sterol abundances and was only detectable in ponds Skua, Duet, Fresh, Conophyton, Castenholz, Legin, Seventy, and Brack. The C29 sterols (24S)-ethylcholesta-5,22E-dien-3β-ol and (24R)-ethylcholest-5-en-3β-ol were present in all samples and together represented the largest proportion of sterols except in pond New, where they were present in equal proportion to cholest-5-en-3β-ol, and in ponds Salt and AMS. 24-Ethylcholesta-5,24(28)Z-dien-3β-ol was not quantified due to its co-elution with (24R)-ethyl-5α-cholestan-3β-ol but its fragment ions, including 484, 386, 296, 281, 257, and 129 Da, were present within the wide C30 peaks across samples. The C29 phytosterol (24S)-ethyl-5α-cholesta-7,22E-dien-3β-ol was present in all environments except those of ponds Roger, AMS, Salt, the Bratina Lagoon, and within the relict microbial mat. 23,24-Dimethyl-5α-cholest-22E-en-3β-ol was detected, though in minor proportions across ponds Skua, Duet, Conophyton, Legin, and Pond Seventy. 4α,23,24-Trimethylcholest-22E-en-3β-ol was the sole C30 sterol detected within the sample set, in Skua Pond, and it co-eluted with a compound containing a strong 502 Da fragment, as well as 237, 221, and 73 Da fragments, which was tentatively identified to be α-tocopherol.

Sterane hydrocarbons
The simulated diagenesis of microbial mat sterols yielded an assortment of steranes with varying proportions across the sample set; the abundances of 4-desmethylsteranes are described in Table 3. C27 through C29 steranes dominated the total sterane distributions; minor proportions of C26 steranes, C30 4-desmethylsteranes, and C30 4-methylsteranes were also present. Mat sterols from all ponds generated the C26 norsteranes 24-norcholestane and 27-norcholestane in varying proportions, while the C30 4-desmethylsteranes 24-n-propylcholestane and 24-isopropylcholestane were recovered from ponds Skua, Fresh, Conophyton, Castenholz, Legin, Pond Seventy, Brack, Salt and from the Bratina Lagoon and were present in varying proportions. C30 4-methylsteranes were detected at either trace or quantifiable abundances in all the ponds and were not employed in abundance calculations. A putative C31 sterane (Supplementary Fig. 11) was detected after hydrogenation of the Pond Seventy sterols and comprised 0.02% of the total 4-desmethylsteranes; this compound was not detected elsewhere.

C27 to C29 sterane distributions varied across the mat samples. When plotted on a C27-C28-C29 ternary diagram, the mat-derived steranes cluster centrally, though steranes derived from mats from ponds with conductivities >4000 µS/cm have higher proportions of C28 steranes (Fig. 4). Steranes derived from the relict microbial plotted closely with those derived from Pond Seventy, Legin Pond, Duet Pond, and Castenholz Pond. Steranes analysed from the hydrocarbon fraction of the relict mats, which was not subjected to hydrogenation, plotted closely with its hydrogenated sterol counterpart.

Catalytic hydrogenation/hydrogenolysis of the microbial mat sterol fractions yielded ααα20R and βαα20R sterane epimers; representative MRM chromatograms and peak identities from Fresh Pond are shown in Fig. 5. A total of ten 4-desmethylsteranes were detected, with the 5α epimer present in greater abundance than the 5β epimer in all cases. The isomer ratios are compiled for the steranes across the mats for C27 through C29 steranes in Supplementary Fig. 12. Across the sample set, the 5α:5β ratio ranged from close to 1:1 in the case of the relict mat and the mat from the Skua Pond margin, while steranes generated from the Bratina Lagoon mat exceeded a 7:1 ratio. Steranes generated from photosynthetically active microbial mats in meltwater ponds contained ratios intermediate to these end members. No clear trend was observed between carbon number and 5α:5β ratios.

In addition to the detection of C26 norsteranes across the sample set, a series of C27 to C29 norsteranes were present as shown in Fig. 5; they eluted slightly after the primary ααα20R and βαα20R cholestane, 24-methylcholestane, and 24-ethylcholestane peaks and appear to be the 27-nor series. In some cases, the C27 to C29 norsteranes were present in abundances too low for integration, such as in the case of Orange Pond, while in the relict microbial mat hydrogenated sterols, norsteranes comprised nearly 9% of the total steranes (Table 3). The presence of these norsteranes in the hydrocarbon fraction of the relict microbial mat, which was not subjected to any chemical treatment, confirm the natural occurrence of the C27 to C29 norsterane series detected (Supplementary Fig. 13).

18S rRNA gene analysis
The 18S rRNA gene sequencing of microbial eukaryotes in the microbial mat fragments revealed the presence of a variety of eukaryotic groups, including SAR, Opisthokonta, and Archaeplastida. These groups had the largest relative abundances (Fig. 6) across all ponds studied, followed by Amoebozoa and Excavata. Centrohelida comprised a small relative abundance in all ponds except Salt, where it was absent, while Cryptophyceae were minor constituents of ponds New, Fogghorne, Roger, Conophyton, Orange, Castenholz, Legin, Salt, and in the Bratina Lagoon. Haptophyta had low relative abundances in ponds Duet, Fresh, Conophyton, Orange, Castenholz, Seventy, and Brack. In some ponds, including Duet, Fresh, and AMS, the relative abundance of uncategorisable eukaryotes exceeded 50%; in other cases, some of the 18S rRNA gene sequences were grouped into incertae sedis.

Further evaluation revealed that certain subgroups dominated within the mats (Fig. 6 and Supplementary Fig. 14). Among the 18S rRNA genes assigned to Stramenopiles, Ochrophyta had the highest relative abundance, followed by minor contributions from Labyrinthulomycetes, Peronosporomycetes, and Bicosoecida. A small proportion of Stramenopiles were classified as incertae sedis and comprised less than 0.2% relative abundance in ponds Brack and New. Among the categorizable Alveolata, Ciliophora had the highest relative abundance, followed by Protalveolata and Dinoflagellata. Apicomplexa were detected in Fogghorne and Conophyton Ponds, corresponding to less than 0.1% relative abundance. All Rhizaria detected belonged to Cercozoa. Nearly all Archaeplastida sequences detected across all ponds grouped within Chloroplastida and mostly consisted of 18S rRNA gene sequences from the green alga Chlorophyta, followed by Charophyta. Among the ponds, Salt exclusively contained 18S rRNA gene sequences grouping into Chlorophyta, while it comprised the majority of the Archaeplastida in all ponds except AMS, where Charophyta was in the majority. The SAR group, comprising Stramenopiles, Alveolata, and Rhizaria, had the highest relative abundances in Salt Pond and in the Bratina Lagoon.

Within the Opisthokonta (Supplementary Fig. 15), Holozoa, including Metazoa and Choanoflagellida, comprised the largest relative abundance of 18S rRNA gene sequences in all ponds. Among the Nucletmycea, the Fungi and the Nucleariidae and Fonticula groups were detected and comprised at least 20% of the Opisthokonta relative abundance in ponds Brack, Orange, Duet, and Fresh.

Among the categorizable Amoebozoa (Supplementary Fig. 16), Tubulinea and Discosea had the largest relative abundances, followed by smaller contributions from Schizoplasmodiida. Protosteliida were only detected Roger Pond and comprised less than 0.2% of the relative abundance. Brack Pond, which had the highest relative abundance of Amoebozoa among all the ponds, also had the highest relative abundance of unclassified Amoebozoa among the microbial mats studied. Salt Pond had the largest relative abundance of Leptomyxida, while Fogghorne Pond had the highest relative abundance of Euamoebida; these groups were a minor constituent or absent in all other ponds. Centrohelida (Supplementary Fig. 17) were detected in all ponds except Salt; in these ponds, the group comprised less than 1% of the eukaryotic community.

Cryptophyceae (Supplementary Fig. 18) were present in low relative abundances in most ponds and were absent in ponds Seventy, Brack, Duet, Fresh, and AMS. The majority of the 18S rRNA gene sequences were assigned to Cryptomonadales, specifically Cryptophyta. The vast majority of Excavata detected (Supplementary Fig. 19) were assigned to Discoba and were present in all the microbial mats studied. Few 18S rRNA gene sequences from Haptophyta were detected (Supplementary Fig. 20); of the ponds that contained their sequences, Pond Seventy contained the largest relative abundance of 18S rRNA gene sequences assigned to Haptophyta, all of which were members of the Prymnesiophyceae class. Other ponds, such as Brack, Castenholz, Orange, Duet, and Fresh, contained 18S rRNA gene sequences from Pavlovophyceae. Haptophyte 18S rRNA gene sequences across the ponds belonged to either Prymnesiophyceae or Pavlovophyceae—no ponds in this work contained 18S rRNA gene sequences from both subgroups simultaneously. Small proportions of 18S rRNA gene sequences from some ponds were broadly categorised as incertae sedis (Supplementary Fig. 21), including Apusomonadidae and Amastigomonas in ponds Roger, Legin, and Seventy, as well as the Bratina Lagoon, as Breviata in ponds New, Duet, Roger, Conophyton, Orange, AMS, and Seventy, and as Telonema in Salt Pond and Legin Pond.

Principal component analysis
Principal component analysis (PCA) revealed relationships between the meltwater ponds and accompanying sterane and 18S rRNA gene data (Fig. 7). PCA biplots were comprised of loadings, which describe how strongly variables such as sterane or 18S rRNA gene categories influenced each principal component, and the principal component scores for each pond examined. For sterane distributions, the analysis recovered five principal components (PCs), while ten components were recovered for 18S rRNA gene distributions. PCs with the largest eigenvalues that explained at least 80% of the total variance were selected; this resulted in the retention of 2 PCs for each analysis. Environmental parameters such as pH, temperature, and conductivity were overlaid on individual pond PC scores to examine their potential impacts on the distribution of the data; no trends were observed for pH and temperature, which only varied slightly across ponds. Ponds Salt and Brack, which had the highest conductivities, had similar PC scores and clustered in both analyses, unlike ponds Duet and Fresh, which had the lowest conductivities but dissimilar scores across PCs.

Within the sterane PCA analysis, minor sterane constituents exerted weak influence on the principal components, while the C27, C28, and C29 steranes strongly influenced PC1. The C27 and C29 steranes influenced PC2 while the C28 steranes did not. Ponds Brack and Salt were most influenced by C28 steranes, while ponds with lower conductivities were more influenced by C27 and C29 steranes. Duet Pond, which had the lowest conductivity, was most influenced by C29 steranes. In the 18S rRNA gene distribution PCA analysis, only Ophisthokonta, SAR, Archaeplastida, and Uncategorisable Eukaryota had strong influences on the PCs; Cryptophyceae, Centrohelida, Haptophyta, Excavata, and incertae sedis were largely uninfluential. Amoebozoa were slightly correlated with SAR. Ponds AMS and Fresh were influenced by Uncategorisable Eukaryota, while Conophyton was most influenced by Archaeplastida. Ponds Legin and Roger were most influenced by Opisthokonta. Ponds which plotted near the origin, such Castenholz, Seventy, Brack, and Salt, which had higher salinities than ponds with greater PC scores, were largely uninfluenced by any 18S rRNA gene distribution variables.

Methods
Study site
During the austral summer, cyanobacterial mats perennially grow in the meltwater ponds of the debris-covered ‘Dirty Ice’ located between Antarctica’s Bratina Island (78°00'27“S, 165°33'10“E) and the north tip of Brown Peninsula (78°02'01“S, 165°31'46“E) (Fig. 1). Known as the undulating ice, the landscape is shaped by the slow compression of ice against Bratina Island and is part of the McMurdo Ice Shelf’s ablation zone16,70,71. Dark-coloured moraine and seafloor debris cover most of the ice surface; previous measurements have estimated sediment heights from the surface of the ice to range from upwards of 10 cm to 30 cm in some places16,71,72. For a few weeks each year, meltwater ponds with various physicochemistries unfreeze atop the ice shelf, their floors lined with multi-annual cyanobacteria-dominated benthic microbial mat communities with stable community compositions (Fig. 2a)16,18,72–76.

Atop the ‘Dirty Ice,’ together with the photosynthetically active microbial mats, relict microbial mats from dried ponds are scattered throughout the region (Fig. 2b)27,77, as are marine debris, which are transported to the ice shelf surface from the seafloor via a combination of basal freezing and surface ablation, i.e., the conveyor belt mechanism detailed and supported by Hawes et al. in 2018 (Fig. 2c, d)12 and first formally suggested by Frank Debenham nearly a century earlier56. In addition to the marine debris pictured in Fig. 2, corals, shells, sponge spicules, frozen fish, and fragments of various marine invertebrates have been observed on the ice since the site’s first characterisations in the early twentieth century, beginning with those made during the Discovery expedition56,70,78,79. Located southwest of Bratina Island is the Bratina Lagoon (78°00‘56“S, 165°29’51“E). The tidal lagoon sits at the margins of the McMurdo Ice Shelf and Bratina Island and Brown Peninsula landmass, and it is flushed once-daily through a tide crack12,16,80. Hawes et al.80 measured a low conductivity of the tidal waters, indicating a meltwater, rather than seawater origin. Microbial mats line the lagoon shoreline as well80.

Sample collection
Sixteen microbial mat samples were collected from the study area in January 2018 using clean stainless steel spatulas21,27. Portions of the samples were frozen and stored in sterile tubes for rRNA analysis and in pre-combusted glass jars for lipid biomarker analysis21,27. Thirteen of the mats considered for this work were collected from active meltwater ponds, and two decaying microbial mat samples were collected from the margins of Skua Pond and the Bratina Lagoon. One desiccated relict mat was collected from a mound of dried mats located between Fresh and Brack ponds; its age was determined to be ca. 700 years old via radiocarbon dating at the National Ocean Sciences Accelerator Mass Spectrometry Facility as reported by Drozd et al. in 202327. At the time of collection, pH, temperature, and conductivity measurements were taken for some pond environments21. A summary of the samples and data collected are detailed in Table 1.

Sterol analysis
Sterol analysis was conducted on the same lipid extracts analysed by Evans et al.21; four additional samples were added to the sample set in this work, including the relict microbial mat, the lagoon microbial mat, as well as those from ponds Roger and AMS. Total lipids were manually extracted from the four samples as well as from microbial mat fragments from the original set of ponds via ultrasonication ahead of catalytic hydrogenation to convert mat sterols to their sterane hydrocarbon counterparts. Due to a lack of remaining biomass, total lipid extracts were not collected from ponds New or Fogghorne and so they are not included in the sterane analysis. Homogenised mat powders were mixed with dichloromethane and methanol (9:1 vol/vol) in ashed glass vials and sonicated for 20 min; extracted lipids were pipetted into a clean glass vial and the procedure was repeated a total of three times. A fourth extraction was conducted with acetone and methanol (7:2 vol/vol) to collect any remaining polar lipids from the microbial mat samples. The collected lipid extracts were concentrated under a gentle stream of N2.

The total lipid extracts from the 14 samples were reacted with 0.5 M HCl in methanol at 60°C for 16 h; following dilution in 18.2 MΩ·cm H2O, organic compounds were extracted with hexane and dichloromethane (4:1 vol/vol) until the organic layer appeared colourless. The extracted organic compounds were concentrated under a gentle stream of N2 before column separation into three fractions. An aliquot of the acid hydrolysed TLE was loaded onto a short column containing deactivated silica gel (2% H2O total weight) and its fractions were eluted with 2 dead volumes (DV) of hexane, 3 DV hexane and dichloromethane (1:1 vol/vol), 3 DV dichloromethane and methanol (4:1 vol/vol), and 2 DV washes with pure methanol to elute any remaining polar columns from the gel. The sterols eluted in the dichloromethane and methanol fraction; the resulting polar fraction was concentrated under a gentle stream of N2.

An aliquot of the sterol-containing fractions from both sample sets was reacted with pyridine and N,O-Bis(trimethylsilyl)trifluoroacetamide (1:1 vol/vol) for 30 min at 70°C to produce sterol trimethylsilyl ethers after the addition of a cholest-5-en-3β-ol (2H)7 standard. The sterol fractions of Evans et al.21 were spiked with 1000 ng of a 10 ng/µL cholest-5-en-3β-ol (2H)7 standard solution, corresponding to 10 ng/µL injected, while the sterol fractions of the additional four samples were spiked with cholest-5-en-3β-ol (2H)7 to correspond to 2.5 ng/µL injected.

The resulting sterol trimethylsilyl ethers were analysed on an Agilent 7890A GC System equipped with an Agilent J&W DB-5MS fused silica capillary column (60 m × 250 μm × 0.25 μm) coupled to an Agilent 5975C Inert XL MSD with Triple-Axis Detector. Samples were run in full-scan mode (scanning masses 50 to 700 Da) using the following parameters: inject splitless on a split/splitless inlet at 300°C and hold for 2 min, after another 2 min ramp oven from 60°C to 315°C at 3.5°C/min and hold for 30.8 min. The flow rate of helium through the column was 1 mL/min and constant flow was achieved throughout the run. The 5975C Inert EI 350 source was held at 250°C and its electron energy was set to 70 eV; the quadrupole was held at 150°C. Masses were scanned from 50 to 700 Da and results were analysed using Agilent MassHunter Qualitative Analysis Navigator B.08.00. Relative response factors for detected compounds were calculated against the known quantity of cholest-5-en-3β-ol (2H)7 standard within each sample, and blanks were run in between samples to monitor instrumental background and baseline conditions. Whenever possible, samples were run against authentic sterol standards for retention time and mass spectral matches. For the sterols with no commercially available standards for comparison, mass spectra were analysed and primarily matched against those described by Gillan in 198181, against spectra compiled by NIST, and against the reference spectra database on William H. Christie’s The Lipid Web.

Sterane analysis
Aliquots of the sterol-containing fractions from the 14 microbial mats extracted in this work were subjected to simulated diagenesis to yield their sterane hydrocarbon counterparts. The conversion of sterols and stanols to steranes by catalytic hydrogenation/hydrogenolysis bypasses natural sterol diagenesis pathways which can result in the formation of sterenes, diasterenes, diasteranes. Hydrogenation/hydrogenolysis was conducted on the sterol-containing fraction using Adams’ catalyst (PtO2). Following addition of the catalyst, the lipid fraction was suspended in hexane; hydrogen gas was gently bubbled into the solvent-sample mixture while it was stirred with a magnetic stir bar for a total of 3 hours. Post-hydrogenation, the solvent-sample mixture was filtered over activated silica gel and separated into fractions. The nonpolar, sterane hydrocarbon-containing fraction was eluted using 2 DV hexane, while the polar fraction was eluted using 2 DV of hexane and dichloromethane (1:1 vol/vol) and 2 DV dichloromethane and methanol (4:1 vol/vol). Both fractions were concentrated under a gentle stream of N2. The nonpolar, sterane-containing fraction was resuspended in hexane for analysis.

The resulting steranes were analysed on an Agilent 7890B GC System equipped with an Agilent J&W DB5-MS fused silica capillary column (59.9 m × 250 μm × 0.25 μm) coupled to an Agilent 7010 GC/MS Triple Quad. Samples were run in dynamic multiple reaction monitoring (dMRM) mode using the following parameters: inject splitless in a multimode inlet at 60°C and hold for 0.01 min before ramping to 340°C at 700°C/min. The oven was ramped from 60°C to 220°C at 8°C/min before being ramped to 325°C at 2°C/min and held for 30.5 min. The flow rate of helium through the column was 1.2 mL/min and constant flow was achieved throughout the run. The 7010 High Efficiency source was held at 270°C and its electron energy was set to 70 eV; quadrupoles 1 and 2 were held at 150°C. Transitions were viewed and analysed using Agilent MassHunter Qualitative Analysis Navigator B.08.00. The following transitions were targeted for sterane analysis: 358.3→217.2 for C26-steranes, 372.3→217.2 for C27-steranes, 386.3→217.2 for C28-steranes, 400.4→217.2 for C29-steranes, 414.4→217.2 for C30-steranes, 414.4→231.2 for methylated C30-steranes, and 428.4→217.2 for C31-steranes. Samples were run alongside aliquots of the Baghewala-A oil from the late Neoproterozoic-early Cambrian Marwar Supergroup82 and of KG-8 from the Miocene-age Monterey formation83 to aid in peak identification for C26 steranes and C30-steranes, as well as blanks to monitor instrument background and baseline conditions.

Select samples were also run on the same instrument in product ion mode to capture the principal fragment ions of specific sterane peaks to differentiate 4-methylsteranes from 24-n-propylcholestane and 24-isopropylcholestane. Scan segment times were determined based on elution times of corresponding dMRM runs. Chromatographic conditions were identical to those in the dMRM run; the 7010 High Efficiency source was held at 270°C and its electron energy was set to 70 eV; the quadrupoles 1 and 2 were held at 150°C. Masses were scanned from 55 to 600 Da; the collision energy for the scan segments was set to 10 eV. Results were analysed using Agilent MassHunter Qualitative Analysis Navigator B.08.00.

18S rRNA gene analysis
18S rRNA gene sequencing data and sequence analysis was conducted on subsample fragments of the microbial mats as previously detailed in Evans et al.21. In brief, DNA was extracted from the mats using a MO BIO Laboratories PowerBiofilm DNA Isolation Kit and amplified using polymerase chain reaction. The V9 hypervariable regions of the 18S rRNA genes were amplified using the universal forward primer 1391F (5′-GTACACACCGCCCGTC-3′) and the eukaryotic reverse primer EukBR (5′-TGATCCTTCTGCAGGTTCACCTAC-3′) containing Illumina MiSeq sequencing adaptors84–86. Following purification with Axygen AxyPrep MAG PCR Clean-up Kits, samples were sequenced on an Illumina MiSeq system at the Natural History Museum’s sequencing facility in the United Kingdom. The resulting 18S rRNA gene amplicon libraries from the mat were deposited with accession PRJNA758785 in the Sequence Read Archive. The raw 18S rRNA gene sequences from the mats were processed with the QIIME2 microbiome bioinformatics platform (version 2019.4)87. Reads were quality filtered and merged, and the DADA2 pipeline was used to denoise and produce amplicon sequence variants (ASVs) using the default settings88. Taxonomy was assigned to ASVs with the sklearn-based taxonomy classifier using the SILVA 132 SSU Ref_NR99 database89,90. To enable comparisons across different ponds, datasets for all samples were rarefied to 25,000 reads using default QIMME2 settings which randomly subsample sequences from each sample. The rarefied data for the ponds are included in the Source Data file.

Principal component analysis
To identify potential patterns or correlations within the data, principal component analysis was conducted. C26-C30 sterane and 18S rRNA gene data were applied as variables, and pond measurements were overlaid on individual pond principal component scores to determine whether the measured environmental parameters exerted any controls on the distributions of principal component scores. Samples with missing pond measurements, sterane, or 18S rRNA gene data were excluded from the analysis. Analyses were conducted in GraphPad Prism 10.4.1.

Peer review rounds
[{"round": 1, "reviewer_comments": {"reviewer_1": "Overview\nThis manuscript characterizes an environment analogous to the refugia for eukaryotes in the Cryogenian. Microeukaryotes\ninhabiting supraglacial meltwater ponds of the McMurdo Ice Shelf have been identified by sequencing their 18S rRNA, and\nassessed by steroid biomarker. These biomarkers were also converted to their fossil analogues via simulated diagenesis.\nThese are important data that should be published, but current limitations in the description of the statistical methods and in\nthe interpretation of the data prevent us from supporting publication in its present form, as detailed below.\nStrengths\nThe manuscript constitutes a rather imaginative study. The limitations that exist for studying an Antarctic microbial\ncommunity, such as the optimization of primers and amplification techniques for psychrophiles, coupled with the lack of\navailability of fully sequenced genomes, is being addressed by applying steroid biomarker analysis.\nLimitations\n- It is true that the environment studied has been proposed as a contemporary analog of a Snowball Earth, but this study\ndoes not demonstrate that this environment is a good analog. The studies cited (references 10-12) are based on geological\narguments. There is no biological evidence that eukaryotic life persisted in that milieu. It is true that there is no fossil record,\nand that this is all a hypothesis to be tested. Does this paper test the hypothesis?\n- An approximation is made by comparing biomarkers from some regions of the planet and from other geological periods\nwith those from Antarctica. Two biomarkers (references 29 and 30) are used in GC-MS analyses to aid in peak identification\nfor norsteranes and C30-steranes. Are these biomarkers comparable, or would the molecules subjected to Antarctic\nconditions have evolved differently than they have evolved in other regions?\n- Correspondences between steroids and taxonomic groups have been made on the basis of the literature (lines 413-430).\nFor example, some steroid distributions have been related with diatoms, dinoflagellates, rhizaria or microalgae. The study\nwould be greatly improved if the presence or concentration of specific sterols were statistically related to each taxonomic\ngroup of eukaryotes. For instance, it would be required to make a Canonical Correspondence Analysis (CCA), or any other\nanalysis demonstrating this relationship.\n- Would it be feasible to perform a statistical evaluation of the correlation between relative abundance and sterol/stanol\nratios?\nTo summarize, this is an exciting data set that should eventually be published, but the present interpretation of the results,\nwhich do not demonstrate a statistically significant relationship is not sufficiently robust to warrant publication.\nSpecific comments\n- Line 71: The Introduction should be separated from the Study site. The Study site should be included in the Methods\nsection.\n- Line 246: The term “metagenome” is usually associated with whole-genome sequencing (WGS) results. In this case, terms\nsuch as “sequencing results”, “resulting sequences” or similar might be more accurate.\n- Line 249: To ensure reproducibility, it is recommended to publish the parameters used in the DADA2 pipeline processing.\n- Line 249: The SILVA database provides multiple options in each of its versions. In this study, it can be assumed that the\nSILVA 132 SSURef_NR99 version was used, but it would be important to specify this clearly.\n- Line 250: Publication of the parameters applied during the rarefaction process is crucial for reproducibility. In addition,\nincluding rarefaction curves could help to confirm that the diversity metrics obtained are sufficiently reliable.\n- Line 363: The phrase “were members of the Prymnesiophyceae” seems incomplete. Adding a term such as “subdivision”,\n“group” or “class” at the end could provide clarity.\n- Figure 1 should be in color to better understand the difference between land and sea. The location of the specific sampling\npoints should also be indicated.", "reviewer_2": "Dear Authors,\nThank you for the time and effort you devoted to this study. You present interesting findings for an important, poorly\nunderstood, aspect of paleobiology/origins-of-life research. I offer this review with the hope that my outside perspective will\nyield improvements that will enhance the overall significance of the study to the field.\nStrengths:\nThe manuscript provides a compelling introduction for investigating meltwater ponds of the McMurdo Ice Shelf as present-\nday analogs that may offer insight into how life persisted during the Cryogenian period. This period featured planet-wide\nglaciation events where ice covered most, if not all, of Earth. It additionally makes the case that eukaryotes are less well\nstudied than bacteria and that the radiation of multicellular, eukaryotic life after the end of the Cryogenian makes this a\ncritical gap in knowledge. The main question to be answered might be summarized as, “Are present-day eukaryotes found in\nsupraglacial meltwater ponds of the McMurdo Ice Shelf representative of life that may have persisted in hypothesized\nrefugia from Snowball Earth events?”\nTwo approaches were used to characterize eukaryotic life- lipid biomarkers (steroids/steranes) and DNA gene marker (18S\nrRNA)- to cover gaps in characterization inherent in each respective approach. The methodologies used for these analyses\nare supported by published peer-reviewed literature and follow established protocols. The figures and tables of the results\nare clear and interpretable, and the results sections are sufficiently detailed. The discussion sections for the lipid biomarker\nanalyses offer a thorough contextualization of findings in relation to existing literature of taxonomic assignments. References\nmake good use of existing literature to provide a suitable rationale for the study as well as contextualize specific results.\nOverall, the writing is sound and accessible.\nWeaknesses:\nThe individual discussion sections for lipid analyses place the specific findings in appropriate context. However, the\ndiscussion of the 18S data is limited and there is a lack of broader synthesis across the analyses which limits the scope and\ninfluence of the study. The current ‘in summary’ paragraph reads more as an argument for using lipid biomarkers to fill gaps\nin knowledge of DNA sequencing than an argument for why this study addresses ours gaps in knowledge about Snowball\nEarth refugia.\nCertainly, methodological arguments are important, but the main summary/conclusions of the study should address the main\naim for the study provided in the introduction (i.e., characterizing eukaryotic life in meltwater ponds and why this system\noffers novel insight as a potential analog for Snowball Earth refugia). In this manuscript, I think the justifications for the\nmethods are better restricted to the introduction/methods sections, and the main study aims could be better addressed by\nincluding a synthesis with these two components:\nFirst, synthesize the results found across the analyses (i.e., 18S, sterols, sterane). Explain how the 18S and lipid biomarkers\ncomplement, or contrast, the characterizations of the eukaryotes. In its present form, the manuscript reuses 18S data already\ncharacterized in Evans et al. (2022), plus two new samples of the 14 presented- AMS pond and Lagoon. Furthermore, the\nmain figure associated with the 18S data (Figure 7) is less informative than the one presented in Evans et al. (2022).\nImportantly, you dedicated ample effort to more in-depth analyses of the 18S data by identifying relative abundances within\nspecific phylogenies, but those analyses are buried in the supplementary material (Supplementary Figure 13-22). I think to\njustify the use of this 18S data, integrating those more in-depth taxonomic analyses into the discussion and figures of the\nmain manuscript is warranted. And then using that more taxonomically refined DNA data, and synthesizing it with the\ntaxonomic assignments from the lipid data, will present a stronger body of evidence for the composition of these ponds.\nAfter performing the composition synthesis suggested above, the study could then offer answers to the following questions:\nWhat is the general composition of eukaryotes found in the various ponds, relic mat, and lagoon? How are they\nsimilar/different among the different study sites? Some of the existing discussion mentions differences in conductivity (Figure\n4), expand on this notion. The study has conductivity, temperature, and pH for each site (and perhaps more?). Tools are\navailable to help characterize the study system in ways helpful to the reader (e.g., Evans et al. 2022 for PCoA plots). Tools\nare also available for multivariate data analysis that would provide a more quantitative approach- e.g., Permanova statistical\nmodels would allow you to test the if community compositions correlate with the physiochemical data. If not familiar with\nPermanova, here is a nice resource that explains the underlying math with example R code\n(https://uw.pressbooks.pub/appliedmultivariatestatistics/chapter/permanova/). In summary, strive to provide the reader with a\ngreater contextualization of the present-day ecology of this proposed analog.\nSecond, explain how the findings above fit within the broader research theme of Snowball Earth refugia, or perhaps even\nclimate refugia in general. Going forward, why should these meltwater ponds on the McMurdo Ice Shelf be considered useful\nas representatives of Snowball Earth-era refugia? How do they compare to other potential analogs? What may we learn from\nthis system that offers novel insight into life in the Cryogenian period and the eukaryotic radiation that occurred after? This\ncontextualization would provide much stronger support for the main conclusion of the study that these ponds are ‘strong\ncandidates’ for analogs of Cryogenian refugia.\nConclusion:\nI think the manuscript would be greatly strengthened by expanding on the data available and really focusing the discussion\non the main study aims regarding characterization of eukaryotes in the meltwater ponds and how the ponds are a useful\nmodel system as present-day analogs of Snowball Earth refugia. My overall assessment is that this study has the elements\nto make a novel contribution to the field but not as presented in the manuscript’s present form, thus I recommend the major\nrevisions mentioned above.", "reviewer_3": "I co-reviewed this manuscript with one of the reviewers who provided the listed reports. This is part of the Nature Communications initiative to facilitate training in peer review and to provide appropriate recognition for Early Career Researchers who co-review manuscripts.", "reviewer_4": "The report attached provides detailed comments on the manuscript, many of which address the suggested questions, but responses to the six considerations are summarized here:\n1. The manuscript establishes the viability of meltwater ponds as refugia for eukaryotes during the Cryogenian.\n2. The work is of interest to a broad audience given the importance of understanding how the snowball Earth shaped the evolution of life on Earth.\n3. The conclusions are justified by the data, although some additional considerations should be discussed.\n4. All of the comments provided should be readily addressed by authors and do not preclude publication.\n5. The analytical protocols are all standard within the discipline.\n6. The challenge with evaluation of natural samples (especially from Antarctica) is that reproducing the work may be logistical challenging and the environments may have changed in the meantime.\n\nSummary\nThis manuscript reports the sterol compositions of microbial mats from Antarctica as an\nanalogue for refugia supporting eukaryotes during the Cryogenian. It also seeks to establish\nconnections between these compositions and the signatures they would generate that could be\npreserved in ancient rocks. Evidence from the sterol compositions is augmented by 18S rRNA\nanalyses to determine which eukaryotes are present within the different environments. There\nare specific aspects of the study that would benefit from further elaboration and minor issues\nin the manuscript that need addressing, as documented in the comments below. However, this\nstudy is clearly worthy of publication and of interest to a broad audience given the importance\nof understanding how the snowball Earth shaped the evolution of life on Earth. In particular, it\nestablishes the viability of meltwater ponds as refugia for eukaryotes during the Cryogenian.\n\nGeneral Comments\nThis manuscript explores the composition of steroidal components in microbial mats from\nmeltwater ponds in Antarctica as an analogue for refugia during the Cryogenian. Overall, the\nmanuscript represents a valuable contribution in addressing how eukaryotic organisms\nsurvived the snowball Earth. Apart from a few considerations, it is well written and conveys its\nresults in an appropriate range of tables and figures, although Fig. 6 could be moved to the\nsupplementary figures. However, the manuscript would benefit from an additional table relating\nthe different sterols to their sources as a substitute for the second paragraph in the steroids\nsection of the discussion. Transferring this specialized information to a table would allow the\ntext to focus on the organisms represented by the sterols without the need to provide all their\nnames, which detracts from the readability of the text to a broader audience unfamiliar with\nsterol nomenclature.\n\nThere are also themes in the manuscript that would benefit from additional data and discussion,\nand each of these points is further documented in the specific comments below. First, the focus\non sterols is understandable as they represent the major diagnostic lipids for characterizing\neukaryotic signatures. Yet there are other steroidal compounds, especially steroidal ketones,\nthat are widely produced by eukaryotes or formed in natural environments by microbial or\noxidative processes, inter alia. Second, the hydrogenation process replicates the pathway from\nprecursor sterols to steranes, but it bypasses the alternate fate for sterols, namely the possibility\nfor their rearrangement to form diasterenes that serve as precursors for diasteranes. The\nexistence of instances where sterane and diasterane distributions are different justifies the\nneed to mention this simplified view of products in the discussion. Third, in discussing the\nanalogy to the Cryogenian there is a need to consider the evolutionary ancestry of the\neukaryotes in the contemporaneous microbial mats. Given the detailed discussion of the\nbiological sources of sterols, can the compounds more likely to be representative of\nNeoproterozoic eukaryotes be distinguished and evaluated? Finally, other potential refugia\nduring the Cryogenian are areas surrounding hydrothermal systems and a figure depicting the\npossibilities for these different settings would be helpful, especially in addressing whether the\nsterol data from meltwater ponds indicate any key differences in their distributions from those\nexpected from hydrothermal settings based on literature data.\n\nSteroidal Compounds\nThe manuscript focuses only on the identities and distributions of sterols within the varied\nsamples. However, most natural environments (and biota) contain other steroidal components\nthat contribute to the pool of these compounds in microbial systems and sediments, notably\nsteryl esters and steroidal ketones. The former tends to be more resistant to alteration than\nsterols, but the formation of esters during desiccation of microbial mats has been established\n(doi:10.1130/G30398). The latter occur in sediments and are produced in higher abundance by\nsome algae during senescence (doi:10.1038/308439a0) and also formed by oxidation, as\ndemonstrated decades ago by microbial mat incubations (doi:10.1016/0079-1946(79)90124-1).\nIt would seem plausible that the relict microbial mat would have experienced oxidation and\ntherefore might contain higher concentrations of steroidal ketones than the fresh or submerged\nmicrobial mats. In addition, a recent publication (doi:10.1016/j.gca.2023.11.024) suggests that\noxidative processes have the potential to alter the carbon number distributions of sterols. Some\nassessment of these other pools of steroidal compounds therefore seems appropriate because\ntheir distributions may differ from those of the sterols and may be enhanced during microbial\nalteration with implications for preserved signatures. It would also be relevant to evaluate the\ncomposition of steroidal hydrocarbons in the relict mat to determine whether sterenes (i.e.,\ninitial products of sterol dehydration) are present.\n\nHydrogenation\nUse of a hydrogenation procedure to generate steranes provides a simplified means of\ndetermining the likely distributions that would appear in mature sediments as products from\nprecursor sterols. However, the resultant sterane distributions may not be an truly accurate\nrepresentation if there are significant proportions of other potential sterane precursors in\nseparate pools of steroidal compounds (see above). An additional difference from natural\nprocesses is that hydrogenation does not replicate the diagenetic pathway that proceeds via\ndiasterenes to diasteranes. The possibility that the diagenetic rearrangement process acts on a\ndiscrete pool of steroidal hydrocarbons can lead to discrepancies in the distributions of\nsteranes and diasteranes (doi:10.1036/12111514199; doi:10.1016/j.marpetgeo.2017.04.018).\nIt's therefore important that the manuscript acknowledge the limitations of hydrogenation of\nsterols to steranes as a simulation of natural processes providing evidence of likely products\nfrom thermal transformations.\n\nRelevance to the Cryogenian\nIn extrapolating the features of microbial mats in meltwater ponds to the Cryogenian, it seems\nrelevant to consider how their steroid distributions differ from those in other settings that could\nserve as refugia, including cryoconite holes, ice-covered lakes (doi:10.1126/sciadv.1600983;\ndoi:10.1098/rspb.2021.1956) and hydrothermal settings (doi:10.1038/scientificamerican0100-\n68). Perhaps a figure illustrating these different settings would be useful in combination with\nconsideration of possible differences in their respective sterol distributions. In addition, it\nseems appropriate to address the question of the extent of ice cover during the Cryogenian and\nhow this study has relevance for snowball versus slushball, and other (doi:10.1038/ngeo355)\nscenarios.\n\nDiscussion of the relationship of the eukaryotic organisms found in the microbial mats to their\nancestry also seems appropriate. Specifically, it is important to note that not all of the\norganisms (e.g., diatoms) populating the modern meltwater microbial mats were extant in the\nCryogenian. Hence, consideration of the sterol distributions for organisms in the samples that\nare known to have been extant in the Neoproterozoic versus those that evolved later should be\naddressed. Complementing discussion of C26 sterane distributions obtained from\nhydrogenation of sterols with comparisons of the changes over geological time for C28 versus\nC29 constituents also seems relevant (doi:10.1016/0146-6380(88)90115-5; doi:10.1111/j.1472-\n4669.2008.00167.x).\n\nAlternatively, does the conservatism of biosynthetic pathways leading to sterols suggest that\nsuch considerations are moot? The presence of sponges and their diagnostic sterols in the mat\nsystems could be further discussed. It has significance for the development of multicellular\norganisms (doi:10.1098/rspb.2023.2767) and implications for oxygenation levels during the\nCryogenian as demosponges can survive in environments with only 0.5-4 % of modern-day\natmospheric O2 (doi:10.1073/pnas.1400547111).\n\nOther Comments\nParts of the text containing detailed information of the biological origins of the various sterols\nmight be summarized in a table rather than detailed in the text. This change would improve the\nreadability of the steroids section of the discussion by focusing on the eukaryotes represented\nwithout the need to specify the individual sterols using their designated nomenclature.\n\nThe text contains a few errors and oversights, some of which are documented below, and\ninstances where simplification of phrasing is possible and desirable.\n\nMinor Concerns\nAbstract: Meltwater pond salinity primarily controlled the assemblages of organisms, which\ndetermines the sterol compositions. (l. 64/65)\n\nPhrasing: Several choices of words and phrasing could be modified to improve clarity and\nmake the text more succinct.\n\nTerms: The text often uses the term \"steroids\" (l. 257 et sequitur) when sterols would be more\naccurate since other class of steroids are not examined. It refers to \"unique\" steroids when\nindividual or discrete would be more appropriate.\n\nCitations: Use of number designations is not uniform. There are citations of author et al., year\n(l. 141 et sequitur) where the numbers would suffice, and also ref 35 (l. 249), rather than\njust the number. Some additional citations would seem appropriate, e.g., natural reduction\nof sterols (l. 441). In addition, the discussion of the sterane ternary diagram (this is the term more\ncommonly used in the literature rather than triplot analysis) makes limited reference to other\nstudies employing this approach to deciphering sterol sources.\n\nAbbreviations: The manuscript has instances where SI conventions are not followed (l. 183 et\nsequitur).\n\nQuantification: Were the 5/5 steranes ratios (Fig. 6) calculated from the MRM responses?\n\nInaccuracies: Unsure how Hawes et al. observed (l. 104) conductivity rather than measured it!\n\nRedundancies: The internal line from the C apex representing 50/50 C /C in Fig. 4 seems\n27 28 29\nredundant. Fig. 5 should specify the norsteranes as 27-nor or 24-nor\n\nColors: Fig. 7 has repeated use of the same colors (e.g., Cryptophyceae and Haptophyta),\nwhich is confusing. All colors should be unambiguous.\n\nItalics: Table 1: Nostoc\n\nNomenclature: The stereochemistry of C-24 alkylation in the sterols is sometimes designated\nusing the IUPAC convention of S and R but also uses - and -. The former convention\nshould be employed uniformly. …methyl… not …methy… in the text (l. 319) and sterol peak #5\nis 27-nor-24S-methylcholest-5,22E-dien-3b-ol (l. 423 & Table 2). Refer to \"norsteranes\" as C\n26\nsteranes to avoid ambiguity with 27-nor-24-methylsteranes.\n\nSupplementary Figures: SF2, #4. The ion at m/z 299 is minimal and m/z 354 is primarily the 13C\nisotopic peak corresponding to m/z 353. Elution time makes it more likely to be 8 than 7,\nunless it's 5 7. #9 seems unlikely to be 8 based on its Rt. #13 seems to have a co-eluting\ncompound with an M+. ion at m/z 456. #29 has m/z 345, which corresponds to loss of 127 or a\nC H side chain.\n9 19", "reviewer_5": "I co-reviewed this manuscript with one of the reviewers who provided the listed reports. This is part of the Nature Communications initiative to facilitate training in peer review and to provide appropriate recognition for Early Career Researchers who co-review manuscripts."}, "author_response": "We thank this reviewer for their thorough review of our work. We have worked to address the limitations\nraised in the review and have added statistical analyses as requested.\n\nWe thank the reviewer for this assessment and have worked to further strengthen the work presented with\ntheir feedback incorporated.\n\nThe primary aim of our work is to evaluate, from an organic geochemical and geobiological perspective,\nwhether this contemporary Cryogenian analog is capable of supporting diverse eukaryotic assemblages –\na prerequisite for hypothesized refugia. While there are no fossils from this type of environment\nspecifically, there is geological, paleontological, and phylogenetic evidence that life not only persisted\nglobally through the Cryogenian, but also became more complex – these details have been made more\nexplicit in the revised manuscript. Later ‘icehouse’ states on Earth, such as those of the late Paleozoic\n(360 to 255 Ma) in Gondwana, do have fossil records which serve as evidence for thriving eukaryotic life\nin glaciomarine settings. A prime example would be the oil shale lenses in the Woody Island Formation of\nthe Lower Parmeener Supergroup in Tasmania, which are comprised of highly fossiliferous organic-rich\nglaciomarine mudstones and siltstones, Tasmanites algal fossils, and dropstones (Reid, C.M. and Burrett,\nC.F., 2004. The geology and hydrocarbon potential of the glaciomarine Lower Parmeener Supergroup,\nTasmania Basin.). We have made edits to the introduction and discussion to better explain why\nsupraglacial meltwater ponds do serve as valid analogues for settings where eukaryotic life could have\npersisted.\n\nWe employed a combination of standards, reference spectra, and previously characterized lipid samples to\nconfirm our identifications of the sterols and steranes detected in this study. We believe the biomarkers\nreferenced are appropriately comparable to the ones recovered in the microbial mats studied, given that\nmany sterols are biosynthesized by a wide variety of eukaryotic taxa. We do not expect the diagenesis of\nsteroids to be different under Antarctic conditions compared to temperate environments. This process of\ndiagenesis is influenced by water chemistry, sediment lithology, and some other factors, but the sterane\nand diasterane end-products are the same (Mackenzie, A.S., Brassell, S.C., Eglinton, G. and Maxwell,\nJ.R., 1982. Chemical fossils: the geological fate of steroids. Science, 217(4559), pp.491-504.)\n\nThank you for this suggestion; we have added statistical analyses (principal component analysis) to the\nmain text of the paper that recovers associations between steranes, the taxonomic groups recovered in this\nwork, and environmental data to the extent that it is possible. The association of particular sterol\nbiomarkers with specific taxonomic groups is most informative when derived from culture studies of\nindividual species, as environmental samples such as the ones examined in this work generally contain\nindividual sterol biomarkers potentially produced by multiple distinct groups organisms over time, some\nof whom whose genetic material may not have been sufficiently intact for 18S rRNA gene analysis.\nFurther, the high proportions of uncategorizable Eukaryota complicate efforts to associate the sterols\nrecovered with particular producers statistically. The specific sterol distributions you have highlighted –\nthose related to diatoms, dinoflagellates, Rhizaria, or microalgae are particularly hard to disentangle since\nthese organisms produce many of the same sterols (we have added a list of potential sterol sources to our\nTable 2 to show this more clearly) and because microbial diversity within the SAR clades, particularly in\nfreshwater settings like those of the meltwater ponds in this work, is distinctly uncharacterized.\n\nThe description of the study site has now been moved to the materials and methods section.\n\nWe have replaced “metagenome” with “resulting sequences” as suggested.\n\nThank you for this suggestion; we have added more details to the methods describing the parameters\nused.\n\nThank you for this suggestion; we did use this database and have now added this detail to the methods.\n\nThank you for these suggestions; we have now provided additional information describing the rarefaction\nprocess in the methods.\n\nWe have added “class” after Prymnesiophyceae and appreciate this catch.\n\nThank you for this suggestion. We have colored in this figure using blue for water in the ponds studied\nand grey for land in panel B. In panel A, we have added additional labels for the sea ice in the McMurdo\nSound as well as McMurdo Ice Shelf. Specific sampling points were not recorded in this study as the\nponds are very small, and this study was not intended to test homogeneity or heterogeneity within\nindividual ponds. Further, the environment is dynamic such that any specific sampling point noted may\nnot exist a year or two following the sampling.\n\nThank you for your positive remarks. We have worked to improve the manuscript and its take-home\npoints, and we have additionally added statistical analyses (principal component analysis) that reveal a\nclearer salinity control on eukaryotic community composition.\n\nWe aim to convey that the 18s rRNA gene data and lipid biomarker datasets are highly complementary,\nand that each dataset reports some findings that the other cannot. We have added and reworded text in the\ndiscussion to more clearly convey this point and to make clearer how this study evaluates how well this\nparticular proposed Cryogenian analogue meets the requirement of Cryogenian refugia to support diverse\neukaryotic assemblages.\n\nThank you for these suggestions. We have added text to the discussion that more clearly describes how\nthese two datasets complement each other and their limitations. While a version of this 18S rRNA gene\ndata was reported in Evans et al., 2022, our presentation and interpretation of the dataset contrasts with\nthat work. Evans and colleagues reported only the most abundant categorizable Eukaryotic taxa, while we\nhave reported all ASVs, demonstrating the significant presence of uncategorizable eukaryotes. We\nappreciate the suggestion to bring more detailed 18S rRNA analysis to the main figure; to do so, we have\nshown more detailed characterizations for the Archaeplastida and SAR eukaryotic assemblages, which\nappear to be strongly associated with sterol production in these environments. We additionally updated\nthe text discussing the 18S rRNA data in the results to describe our 18S rRNA gene findings in more\ndetail.\n\nThank you for these suggestions; we have incorporated statistical analyses (principal component analysis)\ninto the main text which reveal the differences in community composition and community activity\n(steranes) in the ponds, and we have also worked to address these specific questions directly in the results\nand discussion.\n\nThank you for these questions; we have added some additional points and have made references to\nSnowball Earth-era refugia.\n\nThank you for your insights and for training in peer-review. We have supplied specific responses to the\npoints mentioned for reviews #1, #2, and #4.\n\nThank you for this detailed and constructive review. We have worked to add additional text and modify\nfigures in accordance with the points raised.\n\nWe appreciate this suggestion, and we have moved Figure 6 to the supplementary materials. We have also\nincorporated into Table 2, the sterol relative abundance table, information about possible sterol sources.\nAccordingly, we have moved the column of common names to a new table in the supplementary materials\nand have noted this in the text as well.\n\nThank you for these suggestions. We screened our GC-MS data for steroidal ketones and sterenes and\nwere not able to detect them; it is possible they are present at intensities below the instrumental baseline\nor that they are not major steroid components in these particular kinds of mats, which are frozen most of\nthe year and do not undergo burial or experience anoxia in the same manner that would be expected of the\ndiagenetic fates of eukaryotic biomass in non-supraglacial settings. We have expanded our discussion to\ndiscuss the evolutionary ancestry of the eukaryotes in these microbial mats. The significance of this study,\nas shown by both 18S rRNA gene analysis and sterol analysis is that environments like the McMurdo Ice\nShelf meltwater ponds, which must have been relevant during the extended duration of the Cryogenian\n(independent of whether or not Hard Snowball or Slushball models prevailed), currently support diverse\nand productive eukaryotic communities as they would have 730 to 580 million years ago. We have\naddressed the diasteranes in response further below.\n\nOur total lipid extracts from the microbial mats were transmethylated prior to chromatography and\ncatalytic hydrogenation/hydrogenolysis, thus converting any steryl esters present to their free sterol\ncounterparts. Steryl esters, if present in the mats, were converted to free sterols and then converted to\nsteranes during catalytic hydrogenation/hydrogenolysis; thus, they would be represented in the dataset.\nAdditionally, we have added a citation for Gaskell and Eglinton’s incubation experiments to the text in\nour manuscript which discusses the stanols recovered from the mats.\n\nWe have added text to our methods noting this limitation. We examined our GC-MS data for evidence of\nin situ sterol diagenesis in the microbial mats and did not detect these diagenetic products in mats\ncollected from ponds; however, we do detect small abundances of diasteranes in the ca. 700-year-old\nrelict microbial mat hydrocarbon fraction (sans hydrogenation); they are represented by the minor early\neluting peaks in Supplementary Figure 12. Though it is possible that there are other pools of steroidal\ncompounds in these microbial mats, the close placement of samples 1 and F, representing the\nhydrogenation-produced relict microbial mat steranes and the naturally occurring steranes in the ternary\ndiagram (Figure 4), gives us confidence that our analyses accurately account for the major steroid pools in\nthese types of samples.\n\nWe have added a paragraph to the introduction which articulates some of the variations of the Hard\nSnowball hypothesis. In the case of a Hard Snowball, Slushball, or thin ice scenario, meltwater ponds\nwould have still been prevalent on continental margin ice shelves and on the surfaces of continental\nglaciers. They likewise would have been colonized by cyanobacterial microbial mat communities like\nthose described here.\n\nSteranes with carbon numbers 26 to 31 have been identified in Ediacaran rocks and oils as well as\nPhanerozoic. We know, in the latter case, that there are trends in the abundances of these compounds that\ncorrelate, to some extent, with the rise and fall of the major eukaryotic plankton clades as discussed by\nKnoll and colleagues in 2006 in “Eukaryotic organisms in Proterozoic oceans,” for example. Something\nakin to this is seen in the transition from C dominant red to C green algal clades in the Neoproterozoic\n27 29\nas discussed by Brocks and colleagues in 2017 in “The rise of algae in Cryogenian oceans and the\nemergence of animals.” However, detailed discussion of the secular patterns of less abundant compounds\nare precluded, apart from the case of sponge-derived C (and now C ) steranes due to the lack of\n30 31\nrelevant published data.\n\nThank you for alerting us to the paper by Crockett and colleagues. We have now cited this. Work by some\nco-authors, currently in review at PNAS, addresses the sponge biomarker hypothesis through recognition\nof C steranes in Neoproterozoic samples. Accordingly, we think it inappropriate to add any additional\n31\ndiscussion of sponges over and above what is already here.\n\nWe have corrected this text.\n\nWe have modified words and phrases whenever possible throughout the manuscript to improve clarity.\n\nWe have updated the terminology and vocabulary used throughout the text.\n\nWe have worked to make these citations more uniform whenever possible and have added the additional\ncitation requested. We have modified the text to use the term ternary diagram, we have added additional\nreferences to this type of analysis in other works in the discussion.\n\nSI is now used in the main text and supplement.\n\nYes – we have added this detail to the figure caption in addition to moving this figure to the\nsupplementary materials.\n\nThank you for this catch! We have corrected this language.\n\nWe have included this line to draw a reader’s eye to the influence of salinity on sterane C /C ratios.\n28 29\n\nThank you for this suggestion; we have changed the fill color for Cryptophyceae so that these groups are\nnow more distinct.\n\nWe have corrected this; thank you for this catch.\n\nWe have made these corrections in the text, but we also note that the word norsteranes has been used\nwhen generalising about C -C compounds; that is, not all the norsteranes were C .\n26 28 26\n\nThank you for these interpretations; we have updated the descriptions of these peaks accordingly with\ncredit, and we are grateful for your insights towards characterizing these molecules."}, {"round": 2, "reviewer_comments": {"reviewer_1": "The first version of the manuscript has been significantly improved after revision, especially with regard to the statistical methods and data interpretation. We support its publication in its present form.", "reviewer_2": "The authors have taken care to prepare a improved manuscript. Regarding my previous review, they have sufficiently addressed my concerns/questions. This manuscript will make a contribution to the literature in paleobiology, particularly of the Snowball Earth era, as well as present day extremophiles. I recommend publication.", "reviewer_3": "I co-reviewed this manuscript with one of the reviewers who provided the listed reports. This is part of the Nature Communications initiative to facilitate training in peer review and to provide appropriate recognition for Early Career Researchers who co-review manuscripts."}, "author_response": ""}]

Decision letter