# Snow- and ice-ecosystem cleaning capability of the pucciniomycotinous yeast Phenoliferia psychrophenolica

Jade Ezzedine, Pierre Guenzi-Tiberi, Gaëlle Villain, Riccardo Aiese Cigliano, Yacine Diagne, Enzo Franceschi, Elodie Drula, Jérôme Forêt, Jean-Gabriel Valay, Lenka Procházková, et al.

<figure><img src="image_1.png" /></figure>

## To cite this version:

Jade Ezzedine, Pierre Guenzi-Tiberi, Gaëlle Villain, Riccardo Aiese Cigliano, Yacine Diagne, et al. Snow- and ice-ecosystem cleaning capability of the pucciniomycotinous yeast Phenoliferia psychrophenolica. Communications Biology, 2025, 8 (1), pp.1084. 10.1038/s42003-025-08506-w. hal-05285714

HAL Id: hal-05285714

https://amu.hal.science/hal-05285714v1

Submitted on 30 Sep 2025

HAL is a multi-disciplinary open access
archive for the deposit and dissemination of sci-
entific research documents, whether they are pub-
lished or not. The documents may come from
teaching and research institutions in France or
abroad, or from public or private research centers.

L'archive ouverte pluridisciplinaire HAL, est
destinée au dépôt et à la diffusion de documents
scientifiques de niveau recherche, publiés ou non,
émanant des établissements d'enseignement et de
recherche français ou étrangers, des laboratoires
publics ou privés.

<figure><img src="image_2.png" /></figure>

Distributed under a Creative Commons Attribution 4.0 International License
<figure><img src="image_3.png" /></figure>

# Snow- and ice-ecosystem cleaning capability of the pucciniomycotinous yeast *Phenoliferia psychrophenolica*

<figure><img src="image_4.png" /></figure>

Check for updates

Jade A. Ezzedine Ⓓ<fnref n="1" />,⁸, Pierre Guenzi-Tiberi<fnref n="1" />,⁸, Gaëlle Villain Ⓓ<fnref n="1" />, Riccardo Aiese Cigliano Ⓓ²,

Yacine Diagne<fnref n="1" />, Enzo Franceschi³, Elodie Drula Ⓓ⁴,⁵, Jérôme Forêt³, Jean-Gabriel Valay³,

Lenka Procházková⁶, Daniel Remias Ⓓ⁷, Nicolas Terrapon Ⓓ⁴, Alberto Amato Ⓓ<fnref n="1" />✉ & Eric Maréchal Ⓓ<fnref n="1" />✉

Psychrophilic pucciniomycotinous yeasts inhabit snowfields and glacial ecosystems worldwide, yet their ecological role remains unclear. We isolated a clonal strain of *Phenoliferia psychrophenolica* (LCC-F-001-001) from an alpine red snowfield. Its 42-Mbp genome contains 11,523 genes, including 37 ice-binding protein genes, the highest number recorded in fungi, mainly acquired through horizontal transfers. This yeast tolerates freezing, grows optimally at 10 °C and forms pseudohyphae above 15 °C. Known to assimilate phenol and small metabolites, we found LCC-F-001-001 also hydrolyzes carotenoid and phenolic pigments from snow and glacier ice algae. LCC-F-001-001 genome encodes ~ 500 carbohydrate-active enzymes, ranking among the most catalytically versatile sequenced Microbotryomycetes, alongside a related permafrost species. *P. psychrophenolica* and related fungi are therefore key players in snow and ice ecosystems, capable of degrading organic molecules in snowfields and glaciers, likely during algal bloom declines, and connecting the carbon cycle between cryospheric environments and soils through their exceptional metabolic adaptability.

The snowpack formed by seasonal snowfall in high-altitude and high-
latitude regions is a key component of the cryosphere. It is a dynamic system,
characterized by snow accumulation in winter and melting in summer. It is
profoundly affected by global warming. During the spring and summer
seasons, when specific conditions are met<fnref n="1" /> melting snowfields are colonized
by a still poorly characterized microbial biodiversity. Phototrophic micro-
organisms (cyanobacteria and eukaryotic microalgae) are pioneers in the
colonization of these habitats². Some microalgae proliferate to such an
extent that they form blooms known as ‘colored snows’, most frequent being
red snows caused by *Sanguina nivaloides*³,⁴. Heterotrophic microorganisms,
like bacteria and unicellular fungi, are supposed to feed from organic
molecules produced, at least partly, by snow algae. Our understanding of the
structure and dynamics of snowfield ecosystems is limited by our lack of
knowledge about the species that inhabit them and their detailed biology.
Moreover, current studies rely mostly on colored/red snows, whereas, the

initial colonization step in pristine white snow and the later stages of bloom
decline or collapse remain largely unexplored. The analysis of biodiversity in
red snows is ideal to detect and characterize bloom-forming microalgal
species. It holds also significant value in identifying heterotrophic popula-
tions that depend on algal-based trophic networks.

In cultivation trials conducted with microbial consortia dominated by *S. nivaloides* spread on solid growth media, we regularly observe non-pigmented yeast-like cells near red cysts, persisting even in the presence of fungicides (Fig. 1a–c). Molecular analyses identified the presence of pucciniomycotinous species, including strains belonging to the *Phenoliferia* genus, i.e., *P. psychrophenolica* and *P. glacialis*. These fungi were first described by Margesin et al.⁵ under the names *Rhodotorula psychrophenolica*, *R. psychrophila* and *R. glacialis*, found in cryoconites, the thawing zone of a glacier, and the soil of a railway, in the Austrian and French Alps. Another species, *R. himalayensis* was identified in the soil of a lake in the

<footnote n="1">¹Laboratoire de Physiologie Cellulaire et Végétale, Centre National de la Recherche Scientifique, Institut National de Recherche pour l'Agriculture, l'Alimentation et l'Environnement, Commissariat à l'Energie Atomique et aux Energies Alternatives, Université Grenoble Alpes; IRIG, CEA-Grenoble, Grenoble, France. ²Sequentia Biotech SL, Barcelona, Spain. ³Jardin du Lautaret, Université Grenoble-Alpes, Centre National de la Recherche Scientifique; 2233 rue de la piscine, Domaine Universitaire, Gières, France. ⁴Architecture et Fonction des Macromolécules Biologiques, UMR 7257 Centre National de la Recherche Scientifique, Aix-Marseille Univ, USC 1408 Institut National de Recherche pour l'Agriculture, l'Alimentation et l'Environnement, Marseille, France. ⁵Biodiversité et Biotechnologie Fongique, UMR1163 Institut National de Recherche pour l'Agriculture, l'Alimentation et l'Environnement, Aix-Marseille Univ, Marseille, France. ⁶Department of Ecology, Faculty of Science, Charles University, Prague, Czech Republic. ⁷Department of Environment and Biodiversity, University of Salzburg, Salzburg, Austria. ⁸These authors contributed equally: Jade A. Ezzedine, Pierre Guenzi-Tiberi. ✉ e-mail: alberto.amato@cea.fr; eric.marechal@cea.fr</footnote>
<figure><img src="image_5.png" /><figcaption>**Fig. 1** | Pucciniomycotina yeasts from red snows. a–c Detection of micromycete cells in various red snow samples spread and cultivated on minimum solid media. Observations were made after two weeks of cultivation of red snow microbial assemblages sampled in Vallon de Roche Noire, French Alps, at 4 °C in a TP medium without any additional carbon source. a Isolated unidentified micromycete cell (bottom left) in red snow containing *Sanguina nivaloides* (upper right). b, c Large mats of micromycetes observed around a red cyst of *S. nivaloides* under inverted microscope. Scale bar: A, 20 µm; B, 10 µm; C, 100 µm. d, e Detection of micromycete cells in red snows in 19th century studies. d First microscopic description of non-pigmented and pigmented cells in red snow collected in 1818 in the Arctic. Both non-pigmented and red cells were taxonomically considered as a unique fungal species under the name *Uredo nivalis* (Public domain; Modified from Bauer, 1819).</figcaption></figure>

e Microscopic observation of a red snow sample collected in the Alps in 1839 (Public domain; Modified from Shuttleworth, 1848). f ITS rDNA molecular phylogeny of *Phenolifera psychrophenolica* LCC-F-001-001 and *Phenolifera glacialis* LCC-F-001-002. The phylogenetic tree was inferred using Bayesian method based on 824 aligned positions of 49 sequences. Posterior probabilities (PP) followed by bootstraps (BS) values are reported by the nodes.
Himalaya⁶. They were all reclassified a decade ago as distinct from *Rhodo-
torula*, and named *Phenoliferia psychrophenolica*, *P. psychrophila*, *P. gla-
cialis* and *P. himalayensis*, respectively, based on the comparison of multiple
phylogenetic markers¹.

The *Phenoliferia* genus belongs to the Kriegeriales order in the Puc-
ciniomycotina class. This class was formerly known as the Urediniomyce-
tidae. It comprises many ecologically important species, ranging from plant
pathogenic fungal rusts, like the *Uredo* genus, to cryophilic yeasts like
*Phenoliferia* spp.

In 1819, Franz Bauer conducted the earliest taxonomic assessment of microbial cells from a red snow sample obtained during one of the first Arctic expeditions⁸. Non-pigmented cells and red cysts were erroneously thought to be two life stages of a pucciniomycotinous species, proposed to belong to the *Uredo* genus, under the name *Uredo nivalis* (Fig. 1d)⁸. Later mid-nineteenth century descriptions of red snow samples collected in the Alps also showed the formation of microbial mats of non-pigmented cells, mixed with red cysts (Fig. 1e)⁷. We have no evidence regarding the taxonomic assessment of fungi observed in these early studies, in association with snow algae, but they may possibly correspond to pucciniomycotinous yeasts.

Known species in the *Phenoliferia* genus have a preference for low temperatures and can grow on a broad spectrum of artificial carbon sources. In particular, *P. glacialis* and *P. psychrophenolica* can feed on high concentrations of phenol up to 5 mM and 12.5 mM, respectively⁹. Psychrophilic species are defined by their capacity to grow at temperatures below 15–20 °C¹⁰,¹¹. The molecular determinants of adaptation to cold range from general properties of enzymes allowing metabolic pathways and biological processes to operate at low temperature¹²,¹³, to the development of dedicated mechanisms, not encountered in mesophilic species. Psychrophilic enzymes are considered as valuable in bioremediation processes in cold environments¹⁴,¹⁵. *P. psychrophenolica* has been considered therefore as a psychrophilic yeast with a wide geographical distribution in cold environments¹⁶⁻²⁰ and a powerful potential for the bioremediation of phenolic compounds⁵,²¹.

We addressed the ecological role of this species in trophic networks in
snow and ice microbial ecosystems. To this purpose, we isolated a strain
from a red snow and evaluated its capability to hydrolyze carotenoid pig-
ments produced by multiple snow algal cysts²², as well as phenolic pigments
produced by glacier algae²³⁻²⁵. We sequenced and annotated the genome of
*P. psychrophenolica* and sought molecular determinants of cold adaptation
and metabolic pathways involved in the assimilation of biomolecules of algal
origin.

**Results and discussion**

Isolation of *P. psychrophenolica* in microbial consortia from red snow samples dominated by *Sanguina nivaloides*

In microbial red snow samples collected in Vallon de Roche Noire, French
Alps, dominated by cysts of *S. nivaloides*, grown in minimum TP medium at
5 °C, in presence of broad spectrum antibiotics (carbenicilin and nalidixic
acid) and fungicides (amphotericin B and azoxystrobin), and under per-
manent light exposure, yeast-like cells were frequently observed (Fig. 1a). In
multiple instances, after 5 weeks at 5 °C, micromycetes proliferated to such
an extent that they formed dense mats (Fig. 1b) and clusters surrounding *S.
nivaloides* cysts (Fig. 1c), reminiscent of observations reported since the
earliest observations of red snow microbial samples in the 19th century
(Fig. 1d, e). Cells forming such dense microbial mats were picked randomly
and transferred to YPD plates and incubated at 5 °C in the dark. Colonies
were isolated through multiple rounds of subcultures, and molecularly
identified based on ITS rDNA marker. The dominant species was *P. psychrophenolica*.
One clonal strain of *P. psychrophenolica* was added to the
Lautaret Culture Collection (LCC), under the LCC-F-001-001 accession
number, and used as a reference for this study. A clonal strain of *P. glacialis*
was also isolated, under the LCC-F-001-002 accession.

The ITS rDNA phylogenies generated using Bayesian inference and
maximum likelihood methods yielded congruent topologies and indicate

that LCC-F-001-001 clusters with the previously characterized *P. psychro-
phenolica* strains A12 and AG15 from the Austrian and French Alps, and
CPCC (MZ683236.1) from King George Island, Antarctica (Fig. 1f). The
holotype *P. psychrophenolica* AG21⁵ groups in an internal sub-clade. The
ITS2 secondary structure is composed of three helices (Supplementary
Fig. 2). Comparing AG21 with LCC-F-001-001, two transversions were
recorded, i.e. an A-to-U in a non-paired region between helix II and III and
an A-to-C on a side stem of helix III resulting in bond breaking. No com-
pensatory base changes (CBCs) or non-homoplasious synapomorphies
(NHSS) were observed, confirming that the two strains are conspecific
(Supplementary Fig. 2).

P. psychrophenolica LCC-F-001-001 genome assembly and
functional annotation

The final assembly size of the genome of *P. psychrophenolica* LCC-F-001-001 was 41.6 Mbp (Supplementary Figs. 2, 3) with a BUSCO completeness of 93.5% (Supplementary Table 1). The repeat content of the genome annotated by RepeatMasker represents 4.2% (1,747,476 bp) of the whole genome with very low proportion of predicted retroelements (0.03% of the whole genome), DNA transposons (0.04%), repeats of low complexity (0.37%) and simple repeats (1.21%).

P. psychrophenolica LCC-F-001-001 possesses one of the largest genomes reported to date in the Microbotryomycetes class (Supplementary Fig. 4a). This comparative analysis could not include previously released draft genomes of snow yeasts being too fragmented and incomplete²⁶. *P. psychrophenolica* LCC-F-001-001 genome size is not exceptionally large compared to sequenced Basidiomycota (Supplementary Fig. 4b). The genome annotation identified 11,523 predicted genes, which is among highest values among Microbotryomycetes (Supplementary Fig. 4c, d). Gene number is close to that of *Meredithblackwellia eburnea* (11,135) occurring in tropical regions and smaller than that of a *Kriegeriales* sp. P6C61 (15,297) isolated from thawed permafrost, and taxonomically defined as a *P. himalayensis* strain²⁷. The gene count observed may be a characteristic feature of the Kriegeriales order rather than an adaptive feature. Genomic analyses of psychrophilic algae²⁸,²⁹, suggested that a large genome size, containing extensive duplicated regions, may confer increased resistance to icy conditions. A high content in highly similar duplicated (HSD) genes was also suggested to be an adaptive trait of some ice algae in Antarctica³⁰. The number of HSD genes in *P. psychrophenolica* LCC-F-001-001 (108) is smaller to that in *M. eburnean* (179) and *Kriegeriales* sp. P6C61 (1,031) (Supplementary Data 1). Only 77 out of the 108 HSD genes are associated to a known Pfam domain. More than half of these HSD genes contain histone-related domains (H2A/2B, H3, H4; Supplementary Fig. 5). HSD genes also include 6 alcohol dehydrogenases, a family of enzymes known to act in catabolic pathways, including carotenoid breakdown.

We refined the functional annotation of *P. psychrophenolica* LCC-F-001-001 genome by focusing on some pathways known to interact with environmental organic molecules. We semi-manually annotated enzyme families known to degrade, modify, or create glycosidic bonds (carbohydrate-active enzymes; CAZymes)³¹. To that purpose, we compared CAZyme annotation across 32 closely related fungal genomes available in the CAZy and JGI Mycoscosm websites³²,³³ (Supplementary Data 2). We also used specific InterPro domains to refine functional annotation, including domains corresponding to ortho-cleavage pathways (Supplementary Data 2) in fungi³⁴.

The mitochondrial genome (35,551 bp) of *P. psychrophenolica* was also
fully sequenced and annotated (Supplementary Fig. 6a). It is circular and
contains 19 protein-coding or rDNA genes, and 26 tRNA genes. It is smaller
than the four Microbotryomycetes mitochondrial genomes sequenced to
date (*Microbotryum lychnidis-dioicae* KC285586.1, 107.81 kb; *Micro-
botryum cf. violaceum* KC285587.1/BFL-2013, 92.11 kb; *Rhodotorula
mucilaginosa* MF694646.1, 47.02 kb; and *Rhodotorula toruloides*
MT362617.1, 125.94 kb), and falls within the lower range of mitochondrial
genome sizes observed across Basidiomycota (Supplementary Fig. 6b).
**Fig. 2** | *P. psychrophenolica* LCC-F-001-001 phe-
notype at various temperatures. a–d Morphology
of *P. psychrophenolica* LCC-F-001-001 cultivated in
YPD medium at different temperatures. a At 5 °C,
yeast-like shape, characterized by single-celled
growth. b At 10 °C, yeast-like shape, becoming
ovoid. c At 15 °C, yeast-like shape with spherical and
stretched cells. d At 20°C, filamentous form, char-
acterized by pseudohyphae or false hyphae. Scale
bar: 20 µm. e Growth curves of *P. psychrophenolica*
LCC-F-001-001 cultivated at 5, 10, 15, and 20 °C.
Growth was monitored over 240 h, in liquid YPD
medium, after 15 days of acclimation at the respec-
tive temperatures. All OD values were normalized to
the initial OD at day 1.

<figure><img src="image_6.png" /></figure>

**Functional and genomic analysis of *P. psychrophenolica* LCC-F-001-001 adaptation to cold and freezing**

Physiological characterization of *P. psychrophenolica* LCC-F-001-001 was performed on YPD medium. Growth was determined on cells acclimated for 15 days at 5 °C, 10 °C, 15 °C, and 20 °C. Cell morphology varied with temperature (Fig. 2a–d). From 5 to 15 °C, yeast-like spherical cells were observed, becoming more ovoid when temperature increased (Fig. 2a–c). At 20 °C (Fig. 2d), the cells were no longer isolated or with a yeast-like shape, but formed false hyphae or pseudohyphae of varying sizes and lengths. The colony appearance also differed, with smoothed-surface colonies observed at 5 °C and a rough appearance at 20 °C, due to the development of pseudohyphae (Supplementary Fig. 7). The growth of *P. psychrophenolica* LCC-F-001-001 was optimal at 10 °C and minimal at 20 °C (Fig. 2 e). Temperatures higher than 20°C were reported to be lethal for *P. psychrophenolica*¹⁷. In the vicinity of LCC-F-001-001 sampling site, a meteorological station at Col du Lautaret (https://www.romma.fr/) showed an average temperature ranging from -4.1 to 13.9 °C in 2023, with a minimum of -7 °C and a maximum of 18.6 °C. Taking into account heat wave episodes, higher temperatures can be encountered, suggesting that resisting forms may exist to overcome summer seasons.

Cells acclimated at either 5 °C or 20 °C showed a striking recovery after freezing at -20°C (Supplementary Fig. 7) showing a strong resistance to congelation for more than two days.

Cytosolic lipid droplets (LD) were observed in *P. psychrophenolica* acclimated at 5°C (Supplementary Fig. 8a, c) or 20°C (Supplementary Fig. 8b, d), using Nile Red and AUTODOT indicating the accumulation of triacylglycerol, a performant metabolic storage form of carbon for long-term survival in icy conditions⁴.

We sought molecular determinants of cold adaptation characterized previously in other organisms, in particular ice-binding proteins (IBP)³⁵, fatty acid desaturases (FAD)³⁶, and heat shock proteins (HSP) or domains (Hsp20 for cold stress, Hsp60, Hsp90, Hsp104, Hsp30, and Hsp10 proteins for heat stress)³⁷. Based on Pfam domain detections, the predicted proteome of *P. psychrophenolica* LCC-F-001-001 contains more IBPs, FAD1 and HSP12, HSP20, HSP70, than any sequenced non-psychrophilic Basiodiomycota (Supplementary Data 2). The number of IBPs (46 IB domains found in 37 proteins, Supplementary Data 2), is the highest described in a fungus to date. These IBPs include homologous proteins in *Kriegeriales* sp. P6C61 but not in *M. eburnea*. The lack of IBP in other known psychrotolerant or psychrophilic fungi such as *Mortierella alpina*, *Leucosporidium creatinivorum*, and *Sclerotinia borealis* supports that *P. psychrophenolica* and more generally the *Phenolifera* genus may have a higher ecological success in most psychrophilic conditions. HSP12 domains, involved in cold stress responses³⁸ are detected only in two proteins of *P. psychrophenolica* and *Kriegeriales* sp. and in one copy in *M. eburnea*. Fatty acid desaturase FAD1 domains are also detected more abundantly in psychrophilic fungi (Supplementary Data 2). Cold shock (PF17876), HSP33 (PF01430), and FAD2 (PF03405) domains were not detected in any of the compared fungi (Supplementary Data 2). Altogether, these results provide evidence for a strong physiological and molecular adaptation of *P. psychrophenolica* LCC-F-001-001 to cold and freezing.

**P. psychrophenolica** LCC-F-001-001 capacity to resist to a wide range of fungicidal molecular structures

In the initial description of *P. psychrophenolica*⁷ no fungicide resistance was reported. We analyzed the resistance of *P. psychrophenolica* LCC-F-001-001
<figure><img src="image_7.png" /><figcaption>**Fig. 3** | Resistance of *P. psychrophenolica* LCC-F-001-001 to fungicides. **a** Ziram solubilized in acetone. **b** Amphotericine B solubilized in DMSO. **c** Carboxin solubilized in acetone. **d** Azoxystrobin solubilized in acetone YPD supplemented with acetone and DMSO were used as growth control. DMSO dimethylsulfoxide. Scale bar: 6 mm.</figcaption></figure>

to ziram, amphotericin B, carboxin, and azoxystrobin (chemical structures shown in Supplementary Fig. 9) at 15 °C (Fig. 3a–d). Ziram and azoxystrobin were dissolved in acetone, whereas amphotericin B and carboxin in DMSO. Addition of these solvents had no impact on the growth of *P. psychrophenolica* LCC-F-001-001 (Fig. 3). *P. psychrophenolica* LCC-F-001-001 was remarkably resistant to all the tested concentrations of ziram (Fig. 3a) and azoxystrobin (Fig. 3d). Carboxin showed a dose effect on growth, but did not block completely the development of *P. psychrophenolica* LCC-F-001-001 in the studied concentration range (Fig. 3c). The only fungicide impacting growth was amphotericin B, above 2.5 mg.L⁻¹, with almost no visible colonies at 20 and 40 mg.L⁻¹ (Fig. 3b).

Sensitivity to ziram relies on an increased cell vulnerability to oxidative stress³⁹. Amphotericin B exerts its antifungal effects by targeting ergosterol, resulting in the formation of membrane pores compromising cell viability⁴⁰. Carboxin inhibits the activity of succinate dehydrogenase, an essential enzyme in the mitochondrial electron transport chain⁴¹. Azoxystrobin also exerts its antifungal effects by targeting the mitochondrial electron transport chain¹². Resistance to multiple fungicides may reflect the evolution of biological processes countering each compound. Other defensive mechanisms could involve efflux pumps. Alternatively, the capability to hydrolyze a broad spectrum of molecular scaffolds for nutritional purposes, may provide an additional advantage, helping *P. psychrophenolica* detoxifying the surrounding environment from deleterious molecules.

## Hydrolysis of snow and ice algal pigments

*P. psychrophenolica* was shown to grow on a series of different artificial carbons sources⁵ but none of them was directly correlated to specific molecules present in environments, where the species had been identified. Snow algae like *S. nivaloides* produce great quantities of a red carotenoid pigment, astaxanthin⁴, in acyl ester forms²². Glacier ice algae such as *Ancylonema* spp. synthesize a phenolic secondary pigment, purpurogallin, also present in chemically conjugated forms²⁵. Following bloom formation

in snowfields and glaciers' surface, algal populations constitute a biomass with high nutritional potential. Their pigments can spread in the environment when cells break down or die. We tested therefore the ability of *P. psychrophenolica* to hydrolyze three pigment sources available from commercial sources, i.e., pure astaxanthin, astaxanthin acyl esters and pure purpurogallin. Astaxanthin acyl esters derive from extracts of *Haemato-coccus pluvialis*, a green alga producing this conjugated form in high yield⁴³. Increasing concentrations of each pigment were tested at four temperatures (5, 10, 15, and 20 °C) in presence and absence of *P. psychrophenolica* LCC-F-001-001 (Fig. 4 and Supplementary Fig. 11). Absorbance spectra were used to define optimal OD to monitor the presence of each pigment (Supplementary Fig. 10). Visual inspection of multi-well plates indicated that astaxanthin acyl ester was degraded in presence of *P. psychrophenolica* at all temperatures (Fig. 4a–f). Optimal hydrolysis occurred at 5 °C (Fig. 4a). This was confirmed by monitoring OD at 490 nm: after 25 days, the remaining pigment level was lower in samples incubated at 5 °C (Fig. 4e) mimicking environmental conditions where an algal bloom may possibly start declining. After 35 days, the trend remained the same, showing a more intense pigment depletion (Supplementary Fig. 12a). Microscopic observations at day 25 revealed an accumulation of astaxanthin acyl ester as red spherical particles on the surface or within fungal cells for all concentrations higher than 0.025 mg.mL⁻¹ (Fig. 4a–d). In these conditions, *P. psychrophenolica* cells internalized the pigment (Fig. 5a–j). At 20 °C, pseudohyphae became pigmented in red.

Altogether, these data show that astaxanthin acyl esters form aggregated structures or particles in the presence of the fungus, binds to the cell surface, and undergo internalization. The decrease in pigments based on OD suggests that the carotenoid moiety, giving the red color, is at least partly broken down. This suggests that astaxanthin acyl ester can represent a source of carbon for *P. psychrophenolica*. Nevertheless, the number of cells did not increase, suggesting that under these conditions, astaxanthin acyl ester was not provided in sufficient concentration to support visible growth
<figure><img src="image_8.png" /><figcaption>**Fig. 4** | *P. psychrophenolica* LCC-F-001-001 capacity to hydrolyze snow and ice algal pigments. *P. psychrophenolica* LCC-F-001-001 cell cultures were incubated at 5, 10, 15, and 20 °C in presence of pigments for 25 days. Pigment concentrations are reported. DMSO was used as control. A + and a – symbol indicate presence and absence of cells, respectively. Analyses were performed in duplicates. Microscopic images shown on the right of plates are representative of each temperature condition. a–d Astaxanthin acyl ester detection after a 25-day incubation. Arrow-heads</figcaption></figure>

indicate extracellular structures, containing red astaxanthin acyl esters, in contact with fungal cells (a, b, d: scale bar 20 µm and c: scale bar 5 µm). e OD₄₉₀ decrease in presence of cells. Asterisk correspond to *p* values < 0.1 with t test. f–i Purpurogallin detection after a 25-day incubation Arrow-heads indicate point *P. psychrophenolica*, in cells turning yellow due to incorporation of purpurogallin (scale bar 20 µm). j OD₄₃₆ decrease in presence of cells.
<figure><img src="image_9.png" /><figcaption>**Fig. 5** | *P. psychrophenolica* LCC-F-001-001 internalization of snow and ice algal pigments. Incorporation of astaxanthin acyl esters by *P. psychrophenolica* LCC-F-001-001 cells at 5 °C. Incubation was performed for 25 days with 0.025 (a), 0.05 (b), 0.25 (c), 0.5 (d), and 1.25 mg·mL⁻¹ (e) of astaxanthin acyl esters (Scale bar = 20 µm). **f–j** Incorporation of astaxanthin acyl esters by *P. psychrophenolica* LCC-F-001-001 cells at 20 °C. Incubation was performed for 25 days with 0.025 (f), 0.05 (g), 0.25 (h), 0.5 (i), and 1.25 mg·mL⁻¹ (j) of astaxanthin acyl esters (Scale bar = 20 µm). **k–o** Incorporation of purpurogallin by *P. psychrophenolica* LCC-F-001-001 cells at 5 °C,</figcaption></figure>

10 °C, and 20 °C. Images show the incorporation of purpurogallin by *P. psychrophenolica* LCC-F-001-001 cells at 5 °C, 10 °C, and 20 °C. Incubation was performed as described in “Methods” for 25 days at 5 °C, with 0.5 mg·mL⁻¹ purpurogallin (k), at 10 °C with 0.5 mg·mL⁻¹ purpurogallin (l, m), and at 20 °C, with 1.25 mg·mL⁻¹ purpurogallin (n, o) (Scale bar = 20 µm). Cells began to show coloration starting at 0.05 mg·mL⁻¹, and a subset of cells displayed swelling at higher concentrations (0.5 and 1.25 mg·mL⁻¹). Swelling and coloration were not dependent on temperature.

(Fig. 6). Similar experiments performed with pure astaxanthin, without any esterification to an acyl moiety, showed no significant pigment decrease (Supplementary Figs. 11, 12b), highlighting the importance of acyl groups, for the processing of this metabolite by *P. psychrophenolica* LCC-F-001-001.

Pure purpurogallin was not apparently degraded by *P. psychrophenolica* LCC-F-001-001 at any of the tested concentrations or temperatures (Fig. 4f–i). Based on OD detection, a moderate decrease was only noticed at the highest pigment supplies, i.e. 0.5 and 1.25 mg·mL⁻¹ (Fig. 4j). A microscopic inspection revealed that *P. psychrophenolica* cells internalized purpurogallin that stained the cytoplasm in ochre (Fig. 5k–o). At high concentrations (0.5 and 1.25 mg·mL⁻¹), cell protrusions or swelling induced by purpurogallin were observed (Fig. 5k–o). Cell swelling was not observed in negative control, without any added pigment (Fig. 2a–d). Consistently with the absence of any apparent breakdown of pure purpurogallin, *P. psychrophenolica* LCC-F-001-001 cells did not proliferate, when fed with this pigment for 17 days. We then evaluated purpurogallin carboxylic acid-6-O-β-D-glucopyranoside extracted and purified from *Ancylonema alaskanum*. When fed with a natural extract of purpurogallin carboxylic acid-6-O-β-D-glucopyranoside for 17 days at 5 °C, the pigment was reduced

in the medium (Fig. 6b) and *P. psychrophenolica* LCC-F-001-001 cells showed a spectacular growth (Fig. 6d).

These results show that *P. psychrophenolica* has the capability to incorporate and hydrolyze algal pigments, as long as they are provided in chemically conjugated forms naturally produced by algae. Interaction of the *P. psychrophenolica* with astaxanthin acyl esters seems to rely on the formation of particles at the surface of fungal cells, suggesting the induction of a specific extracellular platform for the incorporation of this snow algal pigment. Concerning glacier ice algae, purpurogallin can be internalized into cells. A natural extract of purpurogallin carboxylic acid-6-O-β-D-glucopyranoside was shown to be an efficient source of carbon for fungal growth, possibly by the release of its glucosyl moiety.

## Genomic determinants of algal carbohydrate and pigment hydrolysis and assimilation

It is anticipated that a variety of sugar polymers, commonly produced by photosynthetic organisms, occur in snow and ice environments. We identified 498 CAZy domains from 90 distinct families associated with the degradation, modification, or creation of glycosidic bonds³¹ (Supplementary
<figure><img src="image_10.png" /><figcaption>**Fig. 6** | Analysis of snow and ice algal pigments as a potential source of carbon for *P. psychrophenolica* LCC-F-001-001 growth. *P. psychrophenolica* was incubated for 17 days in a minimum TP medium, complemented with either astaxanthin acyl esters (a) or purpurogallin carboxylic acid-6-O-β-D-glucopyranoside extracted from *Ancylonema alaskanum*, referred to as *Ancylonema* pigment (b). or DMSO used as control (c). + and - symbols indicate presence and absence of the cells, respectively. d Growth curve of *P. psychrophenolica* over 408 h (17 days) in the presence of the three substrates. Experiment was performed in triplicate. Scale bar: 6 mm.</figcaption></figure>

Data 2), representing the second highest number among all sequenced Microbotryomycetes. It is similar to *Kriegeriales* sp. P6C61 (504 domains from 90 families) and far above the third richest, *Meredithblackwellia eburnean* (405 domains from 85 families), all three being the sole representatives of the Kriegeriales order in the CAZy database (Supplementary Data 2). All categories in CAZy were more represented in *P. psychrophenolica* compared to other Microbotryomycetes, with the exception of the carbohydrate binding module domain (Supplementary Data 2). The most striking enrichments appears in the degradation repertoire with more than twice the average of GH (glycoside hydrolases), PL (polysaccharide lyases), AA (auxiliary activities) and CE (carbohydrate esterases). We identified 19 CAZy classes or sub-classes that were apparently not present in other Kriegeriales (7 GH5_23, 2 GH20_n1, 2 GH27_1, 1 GH31_3, 1 GH43_13, 1 GH53, 1 GH89, 1 GH127, 1 GH130 and 2 CE12 modules). Interestingly, the enriched families show functional specificities pointing towards algal and land plants polysaccharides: cellulose (GH1, GH3, GH5_23, GH7 and GH12 known to target β-1,4-glucan)⁴⁴, xylan (AA14 and GH51), pectins (GH43 and GH51 for arabinans; GH35 and GH53 for galactan; GH28, GH88 and GH105 both required to handle unsaturated residues resulting from the β-elimination by PLs, such as PL38, all four likely targeting rhamnogalacturonan type-I, assisted by CE5, CE8 and CE16 for ester decorations from pectins or maybe other substrates such as aforementioned astaxanthin), and the lignin protecting it (AA1 and AA3). By comparison, most other fungal species appear to have more limited capacities to degrade storage polysaccharides such as starch (GH13) and alginate (PL14, PL35), for which *P. psychrophenolica* is also equipped. The hydrolytic equipment of *P. psychrophenolica* appears therefore as strikingly well adapted to deconstruct a broad variety of natural carbohydrate polymers and conjugates.

We identified *P. psychrophenolica* homologs of all the enzymes involved in the phenol degradation pathway characterized in *Candida tropicalis*³⁴ (Fig. 7). The β-Keto adipate synthesis step, typically performed by carboxymethylenebutenolidase (CMBL), can alternatively be carried out by two other enzymes: muconolactone-D-isomerase (catC) and 3-oxoadipate enol-lactonase (pcaD)³⁴. However, these two enzymes were not detected in *P. psychrophenolica*. This pathway is likely involved in the hydrolysis of

phenol, reported for *P. psychrophenolica* up to 12 mM⁵, and could also function in the degradation of naturally occurring phenolic compounds such as catechol or the ice algal pigment scaffold purpurogallin.

Concerning astaxanthin acyl ester, and other esterified carotenoids, several lipase domains and 5 carotenoid monooxygenase domains were detected in the genome (Supplementary Data 2). Lipases may hydrolyze fatty acyls esterified to astaxanthin and the carotenoid oxygenases may be involved in the hydrolysis of astaxanthin component.

Altogether, the genome of *P. psychrophenolica* LCC-F-001-001 reveals an exceptional repertoire of hydrolytic enzymes, positioning *P. psychrophenolica* as one of the most proficient known Microbotryomycetes for degrading a wide range of complex biomolecules.

## Acquisition of carbohydrate-metabolizing and ice-binding protein genes by horizontal transfer

An Alien Index was used to search for putative horizontal gene transfers (HGT) with a bacterial origin. Based on this index, *P. psychrophenolica* likely acquired half of its GH1 glycosyl-hydrolases and possibly 92% of its IBPs (Supplementary Data 3) *via* this process. Only three of the genes related to monosaccharide metabolism were identified in other known Kriegeriaceae species - one shared with *M. eburnea* and two with *Kriegeriales* sp. Although horizontally transferred genes appear broadly scattered across the genome, five clusters were identified (g7252-g7254; g7328-g7329; g8236-g8237; g8842-g8851; g9479, g9482-g9483), which may reflect the integration of large genomic fragments. Most HGT-derived genes contain introns (Supplementary Data 3). Due to the lack of high-quality genomic data from cryophilic prokaryotes, it is not currently possible to pinpoint the bacterial species or phyla that served as donors. Nevertheless, the widespread presence of introns suggests that these horizontal gene transfers are relatively ancient. Altogether, HGT may have played a key role in the acquisition of genes involved in adaptation to cold and icy environments during the early diversification of the Kriegeriaceae.

## Phylogenomic comparison with pucciniomycotinous yeasts, and mucoromycotinous and ascomycotinous fungi occurring in cold environments

*P. psychrophenolica* LCC-F-001-001 has 6856 gene families, with 2572 orthogroups shared across all species. A phylogenomic tree was constructed using 247 single-copy orthogroups from 10 pucciniomycotinous yeasts, including plant pathogen species. Two distant fungi occurring also in cold environments, *Mortieralla alpina* (Mucoromycota) and a psychrotrophic plant pathogen, *Sclerotinia borealis* (Ascomycota), were also included (Supplementary Data 4). Results of this phylogenomic inference (Supplementary Fig. 13) corroborate those of ITS rDNA (Fig. 1f). 95.8% of the genes were classified in an orthogroup, and half of the genes were unique in their orthogroup (Supplementary Data 4). 740 genes were detected as specific to *P. psychrophenolica*. Among these, only 268 genes match with previously identified proteins in the non-redundant (NR) NCBI database⁴⁵, 139 genes have Pfam domains and of these, 74 genes have GO terms associated with an InterPro domain. The GO term analysis of these species-specific genes (Fig. 8) reinforces the conclusion that *P. psychrophenolica* is specialized in the degradation of a broad variety of components. Among the most representative terms, several domains of CAZymes (Glycoside hydrolase family 1, Glycoside hydrolase family 5) and other catabolic domains (Aldehyde deshydrogenase domain) are found. Membrane transporters (ABC transporter type 1, transmembrane domain, major facilitator, sugar transporter-like) are coherent with a capability to incorporate extracellular metabolites and nutrients. Other species-specific genes are involved in the control of genome expression (Histone H2A/H2B/G3, Transcription factor domain, fungi, Transcription initiation factor TFIID subunit 12 domain) and signaling pathways (Protein kinase domains). One *P. psychrophenolica* specific gene contains a cold-shock domain. For proteins with no associated InterPro domain, the DIAMOND results obtained during HGT search were analyzed. We found several genes possibly associated with carotenoid acyl ester breakdown (carotenoid ester lipase precursor, Supplementary Data 2)
<figure><img src="image_11.png" /><figcaption>Fig. 7 | Predicted phenol degradation pathway in *P. psychrophenolica* LCC-F-001-001.</figcaption></figure>

and other CAZy enzymes. The major facilitator superfamily (MFS) includes classical transporters of small molecules, including monosaccharides, but has been described as possibly involved in cold adaptation in *Mrakia psychrophila*⁴⁶, was not over represented in *P. psychrophenolica* LCC-F-001-001 genome. The metabolic evolution of pucciniomycotinous yeasts therefore appears to support their ecological success in organic matter-rich environments, ranging from a saprophytic lifestyle in soils to parasitism of plants. The presence of pucciniomycotinous psychrophilic species in snowfields and ice glaciers therefore suggests that they can find these habitats rich in organic matter, a condition observed when dense blooms enter their declining phase.

## Detection of *P. psychrophenolica* in glacier ice and snow algal blooms

*P. psychrophenolica* was previously identified in the French and Austrian Alps⁵, on a glacier in Alaska⁴⁷, in Svalbard subglacial ice¹⁶ and in the Antarctic Peninsula⁴⁸. Using metagenomic data obtained in various snow and glacier ice algal blooms, we detected *P. psychrophenolica* in all of the 10 samples of red snow tested, dominated by *S. nivaloides* in different locations in the Northern hemisphere (Vallon de Roche Noire, Brévent, Saint-Sorlin and Col du Galibier (French Alps); Mount Olympus (Greece); Trondheim (Norway), and Phippsøya (Svalbard)) (Supplementary Data 5). For example, in the red snow sample blo13 from Vallon de Roche Noire, 13,295 reads could be mapped to *P. psychrophenolica* ITS2. In the Morteratsch glacier ice dark bloom, 311 reads from Bowles et al.⁴⁹ data were mapped with 100% of identity to the ITS2 of *P. psychrophenolica*. *P. psychrophenolica* was not detected in another dataset of *Ancylonema* from the same glacier in

Switzerland (Supplementary Data 5). The mapping of metagenomics reads to *P. psychrophenolica* ITS2 are available in Supplementary Data 5.

## Conclusion

In this study, we demonstrate that *P. psychrophenolica* is among the most snow- and ice-adapted pucciniomycetous yeasts identified so far, characterized by a significant repertoire of IBPs and other cold-adapted proteins. Snow and ice being oligotrophic environments, saprotrophic organisms rely on quantitatively limited carbon sources, requesting the development of efficient hydrolytic machineries acting on the broadest variety of substrates. *P. psychrophenolica* was initially shown to hydrolyze phenol and to assimilate small organic compounds⁵. Here we further showed that the *P. psychrophenolica* genome contains ~500 CAZy genes, suggesting a capacity to hydrolyze a myriad of sugar polymers and complex organic molecules.

*P. psychrophenolica* was shown to hydrolyze pigments commonly found in snow and ice algae. The presence of astaxanthin acyl ester in the medium activated the formation of specific aggregates of the pigment at the cell surface, likely via the specific release of fungal components triggering the formation of these extracellular structures, possibly anchoring hydrolytic enzymes. Microscopic observations at the 4 temperatures revealed that the astaxanthin acyl ester bodies concentrated at the surface of the cells, but it was not possible to determine whether these structures could be directly internalized. A few fungal cells turned red, showing pigment's incorporation. By contrast, pure astaxanthin did not trigger the formation of extracellular particles, and was not bioavailable to the fungal enzymes. In addition to *S. nivaloides*, a multitude of other characterized and uncharacterized algal species thrive in red snows, also producing high levels of red carotenoids
<figure><img src="image_12.png" /><figcaption>**Fig. 8** | InterPro domains of species-specific proteins in the predicted proteome of *P. psychrophenolica* LCC-F-001-001. The histogram counts the number of genes with indicated domains.</figcaption></figure>

accumulating in cytosolic lipid bodies (Supplementary Fig. 14). Our results suggest therefore that pucciniomycotinous yeasts can feed from cell debris of a broad diversity of red snow algae, provided that astaxanthin and other carotenoid moieties are conjugated to acyl or other appropriate chemical groups.

Purpurogallin is an oxidative dimer of pyrogallol, and has antioxidant properties similar to astaxanthin. In presence of purpurogallin and at all temperatures, *P. psychrophenolica* cells turned yellow, indicating internalization of the pigment. When fed with purpurogallin carboxylic acid-6-α-D-glycopyranoside from *A. alaskanum*, *P. psychrophenolica* showed a significant growth reaching saturation after approximately 16 days. Two other fungi from a distant Ascomyceta phylum can hydrolyze purpurogallin glucopyranoside from *Ancylonema*, converting it into a sugar moiety, believed to be used as a nutrient, and purpurogallin carboxylic acid aglycone released in the medium and the mycelium⁵⁰. Various factors, such as algal cell burst, death, and release through exudation, could contribute to the presence of purpurogallin glucopyranoside in the extracellular environment. We did not quantify the decrease or increase of the aforementioned degradation compounds, and it would be important to evaluate in future studies whether this mechanism unraveled in Ascomycota is conserved in Basidiomycota clades. The presence of all the enzymes of the phenol degradation pathway could explain why *P. psychrophenolica* was able to degrade phenol in the initial characterization of the species, and purpurogallin from *Ancylonema*.

The ability to degrade acyl esters of astaxanthin and glucosylated forms of purpurogallin may reflect an adaptation of *P. psychrophenolica* to *Ancylonema* and *Sanguina* blooms. During winter, fungi face stringent ecological constraints characterized by cold temperatures, freezing conditions, water scarcity, and limited nutrient availability. Long-term storage of carbon within cytosolic LDs and the production of enzymes remaining active in the cold are likely involved in this life stage. Upon snowmelt, the

snow environment is enriched in dusts and mineral depositions, mixed with algal bloom biofilms, making a nutrient-rich matrix. This environmental heterogeneity may have promoted adaptive strategies such as the acquisition and increase of enzymes with CAZy domains, facilitating efficient degradation of available organic substrates and production of protective intra/extra-cellular polysaccharides for such environmental conditions. It can also explain the function of the species-specific genes of *P. psychrophenolica*. The Major facilitator superfamily domains suggests the presence of proteins involved in the transport of sugars or other organic compounds, deriving from the algal cell wall and membranes and cell debris degraded by CAZy enzymes.

The geographical distribution of *P. psychrophenolica* covers a large range of locations worldwide, in red snow blooms and in glacier ice, in the European Alps (in previous works⁵ and Supplementary Data 5), in the Arctic (in previous works¹⁶,⁴⁷ and Supplementary Data 5) and in the Antarctic⁴⁸. *Close Phenolifera* species has been found in lake soils and thawed permafrost⁶,²⁷. *P. psychrophenolica* also occurred in areas exposed to anthropogenic pollution⁵. This study reveals therefore that *P. psychrophenolica* and close fungi are potential key players during the decline or collapsing stages of snow and ice algal blooms, and that they can also connect components of the cryosphere with other habitats, most importantly soils. Pucciniomycotinous snow yeasts therefore provide an overlooked ecosystem service as versatile ‘cleaners’ of organic molecules present in snowfields and glacier ice, connecting the carbon cycle between cryospheric environments and soils. Future research is needed to fully understand and appreciate this role.

## Methods

### Micromycete sampling, cultivation, isolation, and molecular identification

A red snow sample dominated by *Sanguina nivaloides* cysts was collected from Vallon de Roche Noire (French Alps; 45.0487314 N, 6.3946644 E) at
2296 m a.s.l on June 18, 2021. An aliquot fraction of the microbial assemblage contained in this red snow sample was spread onto an agar (1%; agar suitable for plant A7921, Sigma, USA) plate containing TP medium (H₂NC(CH₂OH)₃ Tris(hydroxymethyl)-aminomethane 2.42 g·L⁻¹; NH₄Cl 3.75 × 10⁻¹ g·L⁻¹; MgSO₄·7H₂O 1 × 10⁻¹ g·L⁻¹; CaCl₂·2H₂O 5 × 10⁻² g·L⁻¹; K₂HPO₄ 2.88 × 10⁻³ g·L⁻¹; KH₂PO₄ 1.44 × 10⁻¹ g·L⁻¹; Na₂EDTA·2H₂O 4 g·L⁻¹; ZnSO₄·7H₂O 2.2 g·L⁻¹; H₃BO₃ 2.28 g·L⁻¹; MnCl₂·4H₂O 2.53 × 10⁻¹ g·L⁻¹; CoCl₂·6H₂O 8.05 × 10⁻² g·L⁻¹; CuSO₄·5H₂O 7.85 × 10⁻² g·L⁻¹; (NH₄) 6MoO₃·4H₂O 5.5 × 10⁻² g·L⁻¹; FeSO₄·7H₂O 2.495 × 10⁻¹ g·L⁻¹; pH 7) and kept at 5 °C and low light irradiance (5 µmol photons m⁻² s⁻¹) in a cold chamber. After two weeks, micromycetes colonies were observed. Colonies were picked, isolated and cultured through transferring onto an YPD solid agar 1% plate (Sigma, USA). Isolated colonies were identified after PCR amplification of the ITS rDNA using ITS1 (5'-TCCGTAGGTGAACCTGCGG-3') and ITS4 (5'-TCCTCCGCTTATTGATATGC-3')⁵¹. For this purpose, single colonies were lysed in 40 µL of Phire Plant buffer (Thermo Scientific, USA). After mixing using a vortex and heating at 60 °C for 10 min, debris were removed by centrifugation at 1000 × g for 5 min. DNA was quantified using a NanoDrop 2000 spectrophotometer and adjusted to 25 ng·µL⁻¹. Then 2 µL of DNA was used for PCR amplification using the 2× Phire Plant Direct PCR Master mix (Thermo Scientific) in 20 µL reaction volume with 0.5 µM (final concentration) of ITS1 and ITS4 primers. PCR cycling protocol was as follows: an initial denaturation at 98 °C for 5 min; 40 amplification cycles (98 °C–5 s, 61°C–5 s, 72 °C–60 s), and a final extension step at 72 °C for 1 min. Amplicon size is approximately 600 bp. Amplicons were sent to Macrogen, South Korea, for a bidirectional Sanger sequencing. The forward and reverse sequences were checked and assembled using SnapGene v5.0.8⁵². The length of the complete ITS rDNA for *P. psychrophenolica* is 612 bp. Colonies identified as *P. psychrophenolica* were further isolated and grown on YPD solid medium (Sigma, USA) and maintained at 5 °C. One strain was added to the Lautaret Culture Collection (LCC) (our laboratory) under the code LCC-F-001-001. Same processes have been applied for *P. glacialis* LCC-F-001-002 identified based on its complete 602 bp-ITS rDNA length.

## Phylogenetic analyses and ITS2 secondary structure

To infer the phylogenetic position of *P. psychrophenolica* LCC-F-001-001 and *P. glacialis* LCC-F-001-002, 47 sequences corresponding to partial 18S, complete 5.8S, internal transcribed spacer and partial 28S of Microbotryomycetes were downloaded from the NCBI database⁴⁵. All 49 sequences were aligned using MUSCLE v3.8.1551⁵³ implemented in SnapGene v5.0.8⁵² and trimmed manually at 5' and 3' extremities, resulting in 824 aligned positions. Best-fit model of nucleotide substitution was computed using ModelTest-NG v0.1.7⁵⁴ with option -h uigf -f ef. The GTR + I (0.2442) + G (0.7185) substitution model was chosen on the basis of the AICc (corrected Akaike information criterion). Base frequencies were A, 0.2813; C, 0.2008; G, 0.2095 and T, 0.3084. The phylogenetic tree was inferred through Bayesian method using MrBayes v3.2.6⁵⁵ default parameter with a burn-in value of 25% and 1,000,000 generations (standard deviation of split frequencies <0.01). A maximum likelihood phylogeny was also computed using PhyML v3.3.2019⁵⁶ with 1000 bootstrap replicates⁵⁷. Trees were visualized and exported in SVG format on FigTree v1.4.4⁵⁸ and edited using Inkscape 0.92.4³⁹. ITS2 secondary structure prediction and folding is detailed in the supplementary methods

## Growth curves

Four colonies of *P. psychrophenolica* maintained at 5 °C were transferred to flasks with vented caps (T25 tissue culture flask, Thermofisher, USA) containing 10 mL of YPD liquid medium. Flasks were incubated in parallel at 5 °C, 10 °C, 15 °C, and 20 °C in Binder incubators (Binder, Germany) and acclimated for 15 days in the dark. Optical density (OD) was measured in 96-well plates with a Tecan Infinite M1000 Pro (Tecan Group Ltd., Männedorf, Switzerland), performing 24 measurements per well at a distance of 1000 µm from the borders. Plates were orbitally shaken for 30 s prior to measurements. Acclimated cultures were transferred in triplicate to new

flasks containing 20 mL of YPD liquid medium and diluted to OD of 0.07. Growth curves were established over 240 h with 18 measuring points. To determine OD values, 200 µL of each culture were transferred to a 96-well plate and measured as described above. Triplicate YPD blanks were measured in parallel. Normalization was performed using the initially measured OD value (day 1, 0 h) for each temperature. Growth curve graphs were generated using the R⁶⁰ package ggplot2⁶¹.

## Cytosolic lipid droplet staining

Lipid droplets (LDs) were stained with Nile Red (9-diethylamino-5-benz[a]-phenoxazinone, Thermofisher) for 20 min at a final concentration of 0.5 mg·mL⁻¹, 20% Dimethylsulfoxide (DMSO). Nile Red excitation and emission wavelengths were 530 nm and 580 nm, respectively. AUTODOT Visualization Dye (Abcepta) was used as well because it more specifically stains LD.

## Resistance to fungicides and hydrolysis of snow and ice algal pigments

Resistance to ziram (Sigma, USA), amphotericine B (Sigma, USA), carboxin (Sigma, USA) and azoxystrobin (Sigma, USA) was tested. Ziram and azoxystrobin were solubilized in acetone, whereas amphotericine B and carboxin were dissolved in dimethyl sulfoxide (DMSO). 20 µL of *P. psychrophenolica* cells acclimated at 15 °C for 15 days were diluted to an OD of 0.08 and deposited in 24-well plates filled with solid YPD supplemented agar, and increasing concentrations of fungicides. For ziram, the tested concentration were 0.25, 0.5, 1, 2, 4 and 8 mg·L⁻¹; for amphotericine B, 1.25, 2.5, 5, 10, 20, and 40 mg·L⁻¹; for carboxin, 2, 4, 8, 16, 32, and 64 mg·L⁻¹, and for azoxystrobin 10, 20, 40, and 80 mg·L⁻¹. Either acetone or DMSO alone were used as growth controls. Volumes of acetone for ziram and azoxystrobin were 1.1, 2.2, 4.3, 8.7, 17.4, 34.8 µL and 1.2, 2.3, 4.7 and 9.3 µL, respectively. Volumes of DMSO for amphotericine B and Carboxin were 1, 2, 4, 8, 16, 32 µL and 1.1, 2.2, 4.4, 8.9, 17.8, 35.6 µL, respectively. Analyses were performed in triplicates. Algal pigment hydrolysis by *P. psychrophenolica* at 5, 10, 15 and 20 °C were tested using 1.25, 0.5, 0.25, 0.05, 0.025, and 0 mg·mL⁻¹ of purpurogallin (Sigma, USA), astaxanthine (Sigma, USA) and astaxanthine acyl-esters (Sigma, USA) solubilized in DMSO. A natural extract enriched in purpurogallin carboxylic acid-6-O-β-D-glucopyranoside, purified by HPLC, from the glacier alga *Ancylonema alaskanum*²⁵ was tested as well. Cultures were acclimated at the desired temperature for 15 days in liquid YPD. Cells were washed 3 times in minimum media in order to replace YPD by a TP minimum medium (deprived of Tris and Hütner's trace elements), containing no carbon source. In a 96-well plate, 190 µL of cells diluted at an OD of 0.05 were incubated with pigments or DMSO as controls. TP minimum medium with and without cells and pigments without cells were used as blanks. OD of Purpurogallin was measured at 436 nm, and that of astaxanthine and astaxanthine acyl-esters at 490 nm after absorbance spectrum determination. These measurements were performed using a Tecan Spark 10 M. Pigment hydrolysis experiments were performed over 25 days. Decrease of pigment OD with respect to the control was calculated as follows:

$$1 - \frac{(\text{Pigm. control OD} - \text{MM blank OD}) - (\text{Pigm. with cells OD} - \text{MM with cells OD})}{(\text{Pigm. control OD})}$$

where *Pigmcontrol OD* and *Pigmwith cells OD* represent the final OD values of wells containing pigments without and with fungal cells, respectively. *MM blank OD* and *MM with cells OD* represent final OD values in wells containing minimum media without and with cells, respectively. Analyses were performed using R⁶⁰ package ggplot2⁶¹. A basic t-test was conducted, using data obtained at 0.025 mg·mL⁻¹ as a reference and p-values lower than 0.1 were indicated. Microscopic observations were performed at the end of each experiment using an Olympus BX43 upright light microscope equipped with a U-LHLEDC White LED Lamphouse (Olympus Corporation, Tokyo, Japan) through a 10× PLCN20XPH1/0.40-1-7 Plan Achromat C objective. The microscope is equipped with a
DP23-CU digital camera and a CoolLED's pE-300lite for fluorescence microscopy. The camera/computer connection is driven by cellSens Standard Imaging Software version 4.2.1.at the end of the experiment, *P. psychrophenolica* cells were enumerated using a Malassez chamber, following the manufacturer's instructions.

## Growth on solid and liquid media supplemented with snow and ice algal pigments

*P. psychrophenolica* acclimated at 5 °C was tested for growth on various algal pigments known to occur in snow and ice algae, i.e., pure astaxanthin, astaxanthin acyl esters (approximate distribution of 75% monoester, 20% diester, and 5% free astaxanthin), pure purpurogallin, and purpurogallin carboxylic acid-6-O-β-D-glucopyranoside, as described in supplementary methods.

## Resistance to freezing

*P. psychrophenolica* cultures were acclimated at 5 °C and 20 °C for 15 days and then froze at -20 °C for 3, 12, 24, and 53 h. Resistance to freezing was analyzed as described in supplementary methods.

## Genomic DNA library preparation and sequencing

Genomic DNA was extracted from 250 ml of *P. psychrophenolica* LCC-F-001-001 cultivated for 30 days in YPD liquid medium, following Dellaporta et al.⁶² (see supplementary methods). DNA concentration, purity, and integrity were assessed with the PicoGreen method with Victor 3 fluorometry (Invitrogen) according to manufacturer's instruction, using a NanoDrop spectrophotometer (Thermofischer, USA) and by gel electrophoresis, respectively. A sequencing library was produced using the Illumina TruSeq Nano DNA Kit according to manufacturer's instructions. Sequencing was performed on an Illumina Novaseq-6000 producing 150 bp paired-end reads and on an Illumina Miseq producing 300 bp paired-end reads. 11-Gbp forward and reverse reads were obtained for Miseq data and 14-Gbp forward and reverse reads for Novaseq data. Quality of Illumina raw sequence data was assessed using FastQC v0.11.5 software⁶³. Reads were trimmed using Trimmomatic v0.39⁶⁴ in accordance with software setting adjusted for a quality threshold of 20 and a minimum length of 35 bp. Trimmed reads were re-analyzed with FastQC to verify the improved data quality.

## De novo assembly, gene prediction, and functional annotation

Genome size was estimated based on k-mer frequency distribution generated by Jellyfish v2.3.0⁶⁵ (kmer = 21) and GenomeScope v2.0⁶⁶. Illumina reads were used to produce a de novo genome assembly with SPADES v3.15.0⁶⁷. The draft assembly was corrected through the Pilon v1.24⁶⁸ algorithm using the Illumina raw reads (one round). The quality and accuracy of the final assembly were evaluated using Quast v 5.1⁶⁹ and BUSCO v 5.0⁷⁰, respectively. Quast was used to generate general genome statistics. Contigs longer than 50 kbp, were retained for further analyses. BUSCO analysis was performed by comparing with data from both Eukaryotes and Fungi lineages to ensure completeness and accuracy of the genome assembly. The repeats elements library was created by RepeatModeler⁷¹ and were masked by RepeatMasker⁷². Gene annotation was performed by Maker2 v3.0.2⁷³, using closely related reviewed proteins from UniProtKB of Fungi (https://www.uniprot.org; June 2022) to improve the accuracy of the annotation and the polished de novo assembly. After the first annotation, an AUGUSTUS v3.5.3⁷⁴ model was trained to produce a more complete annotation. The final gene annotation was further analyzed using BUSCO on both Eukaryotes and Fungi lineages to evaluate the accuracy of gene-prediction. Functional annotation of the protein-coding genes was performed by identifying best BLAST hits using DIAMOND v2.1.8⁷⁵ (in ultra-sensitive mode, E-value < 1 × 10⁻⁵) against the UniProtKB database (Fungi part, March 2024). InterProScan v5.66-98.0⁷⁶ was utilized to annotate Pfam domains using the curated Pfam database v36⁷⁷. InterProScan was also used to assign Gene Ontology (GO) terms corresponding to the Pfam annotations.

## Annotation of genes related to the degradation, modification, or creation of glycosidic bonds

For over 30 years, the CAZy classifies into sequence-based families the catalytic and binding modules that degrade, modify, or create glycosidic bonds³¹. CAZyme-encoding genes were identified by manual curation following the procedure used in the CAZy database³¹. Curation consisted of the expert validation of the predicted modularity for each protein, using a combination of BLASTp⁷⁸ pairwise alignments against both characterized members and previously curated sequences integrated in the CAZy database, as well as HMMER v3.4⁷⁹ comparisons to in-house profiles of the families, and subfamilies when available. The CAZy proteins of *P. psychrophenolica* were compared with the annotation of 32 fungal genomes from the NCBI⁴⁵ and JGI MycoCosm databases³²,³³. These annotations were produced following the same procedure by CAZy curators. The final annotation file with general feature format (GFF3) was built by AGAT⁸⁰ with stringent parameters (sp_managed_functionalAnnotation.pl, blast_t_evalue 0.00001 -pcds options) parameters.

## Horizontal gene transfer (HGT) detection, highly similar duplicated (HSD) gene predictions, mitochondrion genome identification and phylogenomics

HGT detection was performed on the *P. psychrophenolica* protein dataset as described in Supplementary Methods. For highly similar duplicated genes predictions, the predicted proteins were blasted against themselves with DIAMOND v2.1.8 (ultra-sensitive mode, E-value < 1 × 10⁻⁵), as detailed in supplementary methods. The mitochondrial genome was identified from the initial assembly by mapping the cox1 gene of *Rhodotorula mucilaginosa* (NC_036340.1, position: 11605-15597) as detailed in supplementary methods. The Phylogenomics analysis of *P. psychrophenolica* was conducted using Orthofinder v2.5.4⁸¹ as detailed in supplementary methods.

## Prediction of proteins adapted to cold life

The proteins potentially involved in adaptation to cold life were manually checked. Ice-binding proteins (IBP)³⁵, fatty acid desaturases (FAD)³⁶, and several heat shock proteins (HSP) or domains (Hsp20 for cold stress, Hsp60, Hsp90, Hsp104, Hsp30, and Hsp10 proteins for heat stress)³⁷ were included. The Pfam domains corresponding to ice-binding (PF11999), heat shock (PF04119, PF00011, PF01430, PF00012, and PF00183), cold shock (PF17876), and fatty acid desaturase (PF00487, PF03405) were selected, and their abundance was calculated.

## Prediction of hydrolysis pathways acting on snow and ice algal pigments

Proteins predicted to act in phenol breakdown were searched in *P. psychrophenolica* translated genome. To refine this analysis, Interpro⁸² (https://www.ebi.ac.uk/InterPro) domains corresponding to ortho-cleavage pathways in fungi³⁴ were used to search for homologs in *P. psychrophenolica*. Interpro domains corresponding to lipases⁸³, esterases, and Cytochrome P450 were also selected as enzymes that might be involved in carotenoid (astaxanthine) acyl ester hydrolysis.

## Detection of *P. psychrophenolica* in metagenomes of snow and ice algal blooms

For the analysis of the distribution of *P. psychrophenolica* across different geographical locations, we evaluated its presence in selected metagenomic datasets, obtained by Illumina Novaseq or Illumina MiSeq sequencing. The internal transcribed spacer 2 of the ribosomal cistron (ITS2 rDNA) was used as a reference. Metagenomic reads, which were trimmed using Trimmomatic to remove low-quality bases and adapters, were mapped onto the ITS2 reference sequence using BWA v0.7.17-r1188²⁹ with default options. The alignment of metagenomic reads to the ITS2 sequence was visualized using IGV v2.11.2²⁸ to assess completeness of coverage and to verify that the main haplotype corresponded to the reference sequence. *P. psychrophenolica* was considered detected in a sample if the main haplotype of the mapped reads was identical to the reference ITS2 sequence.
**Statistics and reproducibility**

Quality statistics for raw reads, assembly metrics (e.g., N50, genome size, completeness), and annotation summaries are provided. All the scripts used to generated the analyses and the graphs are available in a Github repository (https://github.com/pguenzi-tiberi/Phenolifera_psy_repository). The script used to calculate the Alien index is in another repository (https://github.com/pguenzi-tiberi/Alien_index_report_generator).

**Reporting summary**

Further information on research design is available in the Nature Portfolio Reporting Summary linked to this article.

**Data availability**

All sequence data have been submitted to NCBI under BioProject ID [PRJNA1021013] and are publicly available. Data used to generate curves and histograms are provided in Supplementary Supplementary Data 6.

Received: 30 January 2025; Accepted: 9 July 2025;
Published online: 21 July 2025

**References**

1. Roussel, L. et al. Snowmelt duration controls red algal blooms in the snow of the European Alps. *Proc. Natl. Acad. Sci.* **121**, e2400362121 (2024).

2. Hoham, R. W. & Remias, D. Snow and glacial algae: A review.1. *J. Phycol.* **56**, 264–282 (2020).

3. Procházková, L., Leya, T., Krížková, H. & Nedbalová, L. Sanguina nivaloides and Sanguina aurantia gen. et spp. Nov. (Chlorophyta): The taxonomy, phylogeny, biogeography and ecology of two newly recognised algae causing red and orange snow. *FEMS Microbiol. Ecol.* **95**, 1–21 (2019).

4. Ezzedine, J. A. et al. Adaptive traits of cysts of the snow alga Sanguina nivaloides unveiled by 3D subcellular imaging. *Nat. Commun.* **14**, 1–18 (2023).

5. Margesin, R., Fonteyne, P. A., Schinner, F. & Sampaio, J. P. Rhodotorula psychrophila sp. nov., Rhodotorula psychrophenolica sp. nov. and Rhodotorula glaucis sp. nov., novel psychrophilic basidiomycetous yeast species isolated from alpine environments. *Int. J. Syst. Evol. Microbiol.* **57**, 2179–2184 (2007).

6. Shivaji, S., Bhadra, B., Rao, R. S. & Pradhan, S. Rhodotorula himalayensis sp. nov., a novel psychrophilic yeast isolated from Roopkund Lake of the Himalayan mountain ranges, India. *Extremophiles* **12**, 375–381 (2008).

7. Wang, Q. M. et al. Phylogenetic classification of yeasts and related taxa within Pucciniomycotina. *Stud. Mycol.* **81**, 149–189 (2015).

8. Bauer, F. Microscopical observation on the red snow. *Q. J. Lit. Sci. Arts VII*, 222–229 (1819).

9. Shuttleworth, R. J. Nouvelles observations sur la matière colorante de la neige rouge. *Bibl. Univers. Gen.ève* **25**, 383–406 (1840).

10. Männistö, M. K. & Puhakka, J. A. Psychrotolerant and microaerophilic bacteria in boreal groundwater. *FEMS Microbiol. Ecol.* **41**, 9–16 (2002).

11. Moyer, C. L., Eric Collins, R. & Morita, R. Y. Psychrophiles and psychrotrophs. in *Reference Module in Life Sciences* (Elsevier, 2017). https://doi.org/10.1016/B978-0-12-809633-8.02282-2.

12. Kumar, A., Mukhia, S. & Kumar, R. Industrial applications of cold-adapted enzymes: challenges, innovations and future perspective. *3 Biotech* **11**, 426 (2021).

13. Cavicchioli, R. et al. Biotechnological uses of enzymes from psychrophiles. *Microb. Biotechnol.* **4**, 449–460 (2011).

14. Chaudhary, D. K. & Kim, J. New insights into bioremediation strategies for oil-contaminated soil in cold environments. *Int. Biodeterior. Biodegrad.* **142**, 58–72 (2019).

15. Liu, Y. et al. Advances in cold-adapted enzymes derived from microorganisms. *Front. Microbiol.* **14**, 1–15 (2023).

16. Perini, L., Gostinčar, C. & Gunde-Cimerman, N. Fungal and bacterial diversity of Svalbard subglacial ice. *Sci. Rep.* **9**, 1–15 (2019).

17. Turchetti, B. et al. Psychrophilic yeasts in glacial environments of Alpine glaciers. *FEMS Microbiol. Ecol.* **63**, 73–83 (2008).

18. Tsuji, M., Uetake, J. & Tanabe, Y. Changes in the fungal community of Austre Brøggerbreen deglaciation area, Ny-Ålesund, Svalbard, High Arctic. *Mycoscience* **57**, 448–451 (2016).

19. Kachalkin, A. V. New data on the distribution of certain psychrophilic yeasts in Moscow oblast. *Microbiology* **79**, 840–844 (2010).

20. de Menezes, G. C. A. et al. Diversity, distribution, and ecology of fungi in the seasonal snow of antarctica. *Microorganisms* **7**, 1–16 (2019).

21. Margesin, R., Gander, S., Zacke, G., Gounot, A. M. & Schinner, F. Hydrocarbon degradation and enzyme activities of cold-adapted bacteria and yeasts. *Extremophiles* **7**, 451–458 (2003).

22. Osterrothová, K. et al. Analyzing carotenoids of snow algae by Raman microspectroscopy and high-performance liquid chromatography. *Spectrochim. Acta - Part A Mol. Biomol. Spectrosc.* **212**, 262–271 (2019).

23. Procházková, L., Rezanka, T., Nedbalová, L. & Remias, D. Unicellular versus filamentous: The glacial alga ancylonema alaskana comb. et stat. nov. and its ecophysiological relatedness to ancylonema nordenskiöldii (zygnematophyceae, streptophyta). *Microorganisms* **9**, 1103 (2021).

24. Remias, D. & Procházková, L. The first cultivation of the glacier ice alga Ancylonema alaskanum (Zygnematophyceae, Streptophyta): Differences in morphology and photophysiology of field vs laboratory strain cells. *J. Glaciol.* **69**, 1080–1084 (2023).

25. Remias, D. et al. Characterization of an UV- and VIS-absorbing, purpurogallin-derived secondary pigment new to algae and highly abundant in Mesotaenium berggrenii (Zygnematophyceae, Chlorophyta), an extremophyte living on glaciers. *FEMS Microbiol. Ecol.* **79**, 638–648 (2012).

26. Turchetti, B., Buzzini, P. & Baeza, M. A genomic approach to analyze the cold adaptation of yeasts isolated from Italian Alps. *Front. Microbiol.* **13**, 1–17 (2022).

27. JGI MycoCosm. Kriegeriales sp. P6C61 genome portal. Joint Genome Institute. https://mycocosm.jgi.doe.gov/Krisp1/Krisp1.home.html (accessed 28 December 2024).

28. Robinson, J. T. et al. Integrative genomics viewer. *Nat. Biotechnol.* **29**, 24–26 (2011).

29. Li, H. & Durbin, R. Fast and accurate short read alignment with Burrows-Wheeler transform. *Bioinformatics* **25**, 1754–1760 (2009).

30. Zhang, X., Cvetkovska, M., Morgan-Kiss, R., Hüner, N. P. A. & Smith, D. R. Draft genome sequence of the Antarctic green alga Chlamydomonas sp. UWO241. *iScience* **24**, 102084 (2021).

31. Drula, E. et al. The carbohydrate-active enzyme database: Functions and literature. *Nucleic Acids Res* **50**, D571–D577 (2022).

32. Grigoriev, I. V. et al. Fueling the future with fungal genomics. *Mycology* **2**, 192–209 (2011).

33. Grigoriev, I. V. et al. MycoCosm portal: Gearing up for 1000 fungal genomes. *Nucleic Acids Res.* **42**, 699–704 (2014).

34. He, Y. et al. Biodegradation of phenol by Candida tropicalis sp.: Kinetics, identification of putative genes and reconstruction of catabolic pathways by genomic and transcriptomic characteristics. *Chemosphere* **308**, 136443 (2022).

35. Davies, P. L. Ice-binding proteins: a remarkable diversity of structures for stopping and starting ice growth. *Trends Biochem. Sci.* **39**, 548–555 (2014).

36. Cui, J. et al. Identification and characterization of a novel bifunctional Δ12/Δ15-fatty acid desaturase gene from Rhodosporidium kratochvilovae. *Biotechnol. Lett.* **38**, 1155–1164 (2016).

37. Tiwari, S., Thakur, R. & Shankar, J. Role of heat-shock proteins in cellular function and in the biology of fungi. *Biotechnol. Res. Int.* **2015**, 132635 (2015).
38. Murata, Y. et al. Genome-wide expression analysis of yeast response during exposure to 4°C. *Extremophiles* **10**, 117–128 (2006).

39. Kanemoto-Kataoka, Y., Oyama, K., Oyama, T. M., Ishibashi, H. & Oyama, Y. Ziram, a dithiocarbamate fungicide, exhibits pseudo-cytoprotective actions against oxidative stress in rat thymocytes: Possible environmental risks. *Environ. Res.* **160**, 232–238 (2018).

40. Gray, K. C. et al. Amphotericin primarily kills yeast by simply binding ergosterol. *Proc. Natl. Acad. Sci. USA* **109**, 2234–2239 (2012).

41. Mathre, D. E. Mode of action of oxathiin systemic fungicides structure-activity relationships. *J. Agric. Food Chem.* **19**, 872–874 (1971).

42. Bartlett, D. W. et al. The strobilurin fungicides. *Pest Manag. Sci.* **58**, 649–662 (2002).

43. Jin, C., Zhou, Z., Zhu, Y., Liu, Q. & Zhou, X. Photosynthetic activity and astaxanthin production of Haematococcus pluvialis regulated by manipulated light quality. *Aquac. Int.* **32**, 3617–3635 (2024).

44. Fiolka, M. J., Takeuchi, N., Sofińska-Chmiel, W., Mieszawska, S. & Treska, I. Morphological and physicochemical diversity of snow algae from Alaska. *Sci. Rep.* **10**, 1–18 (2020).

45. Sayers, E. W. et al. Database resources of the national center for biotechnology information. *Nucleic Acids Res* **50**, D20–D26 (2022).

46. Su, Y. et al. Genomic, Transcriptomic, and proteomic analysis provide insights into the cold adaptation mechanism of the obligate psychrophilic fungus mrakia psychrophila. *G3 Genes*|*Genomes*| *Genet.* **6**, 3603–3613 (2016).

47. Uetake, J., Yoshimura, Y., Nagatsuka, N. & Kanda, H. Isolation of oligotrophic yeasts from supraglacial environments of different altitude on the Gulkana Glacier (Alaska). *FEMS Microbiol. Ecol.* **82**, 279–286 (2012).

48. Ferreira, E. M. S., de Sousa, F. M. P., Rosa, L. H. & Pimenta, R. S. Taxonomy and richness of yeasts associated with angiosperms, bryophytes, and meltwater biofilms collected in the Antarctic Peninsula. *Extremophiles* **23**, 151–159 (2019).

49. Bowles, A. M. C., Williams, T. A., Donoghue, P. C. J., Campbell, D. A. & Williamson, C. J. Metagenome-assembled genome of the glacier alga Ancylonema yields insights into the evolution of streptophyte life on ice and land. *New Phytol.* **244**, 1629–1643 (2024).

50. Perini, L. et al. Interactions of fungi and algae from the greenland ice sheet. *Microb. Ecol.* **86**, 282–296 (2023).

51. White, T. J. et al. 315–322 (Academic Press, 1990). https://doi.org/10.1016/B978-0-12-372180-8.50042-1.

52. SnapGene software. SnapGene. (2020).

53. Edgar, R. C. MUSCLE: multiple sequence alignment with high accuracy and high throughput. *Nucleic Acids Res.* **32**, 1792–1797 (2004).

54. Darriba, D. et al. ModelTest-NG: A new and scalable tool for the selection of DNA and protein evolutionary models. *Mol. Biol. Evol.* **37**, 291–294 (2020).

55. Ronquist, F. et al. MrBayes 3.2: Efficient bayesian phylogenetic inference and model choice across a large model space. *Syst. Biol.* **61**, 539–542 (2012).

56. Guindon, S. et al. New algorithms and methods to estimate maximum-likelihood phylogenies: assessing the performance of PhyML 3.0. *Syst. Biol.* **59**, 307–321 (2010).

57. Pattengale, N. D., Alipour, M., Bininda-Emonds, O. R. P., Moret, B. M. E. & Stamatakis, A. How many bootstrap replicates are necessary?. *J. Comput. Biol.* a *J. Comput. Mol. cell Biol.* **17**, 337–354 (2010).

58. Rambaut, A. FigTree v1.3.1. Institute of Evolutionary Biology, University of Edinburgh, Edinburgh. http://tree.bio.ed.ac.uk/software/figtree/ (2010).

59. Inkscape Project. Inkscape. (2020).

60. R. Core Team. R: A Language and Environment for Statistical Computing. (2021).

61. Wickham, H. *ggplot2: Elegant Graphics for Data Analysis*. (Springer-Verlag New York, 2016).

62. Dellaporta, S. L., Wood, J. & Hicks, J. B. A plant DNA minipreparation: Version II. *Plant Mol. Biol. Report.* **1**, 19–21 (1983).

63. Andrews, S. *FastQC: A Quality Control Tool for High Throughput Sequence Data*, (2010).

64. Bolger, A. M., Lohse, M. & Usadel, B. Trimmomatic: A flexible trimmer for Illumina sequence data. *Bioinformatics* **30**, 2114–2120 (2014).

65. Marçais, G. & Kingsford, C. A fast, lock-free approach for efficient parallel counting of occurrences of k-mers. *Bioinformatics* **27**, 764–770 (2011).

66. Ranallo-Benavidez, T. R., Jaron, K. S. & Schatz, M. C. GenomeScope 2.0 and Smudgeplot for reference-free profiling of polyploid genomes. *Nat. Commun.* **11**, 1432 (2020).

67. Bankevich, A. et al. SPAdes: a new genome assembly algorithm and its applications to single-cell sequencing. *J. Comput. Biol. a J. Comput. Mol. cell Biol.* **19**, 455–477 (2012).

68. Walker, B. J. et al. Pilon: An integrated tool for comprehensive microbial variant detection and genome assembly improvement. *PLoS One* **9**, 1–14 (2014).

69. Gurevich, A., Saveliev, V., Vyahhi, N. & Tesler, G. QUAST: Quality assessment tool for genome assemblies. *Bioinformatics* **29**, 1072–1075 (2013).

70. Simão, F. A., Waterhouse, R. M., Ioannidis, P., Kriventseva, E. V. & Zdobnov, E. M. BUSCO: assessing genome assembly and annotation completeness with single-copy orthologs. *Bioinformatics* **31**, 3210–3212 (2015).

71. Flynn, J. M. et al. RepeatModeler2 for automated genomic discovery of transposable element families. *Proc. Natl. Acad. Sci. USA.* **117**, 9451–9457 (2020).

72. Smit, A. F. A., Hubley, R. & Green, P. RepeatMasker Open-4.0.

73. Holt, C. & Yandell, M. MAKER2: An annotation pipeline and genome-database management tool for second-generation genome projects. *BMC Bioinformatics* **12**, 491 (2011).

74. Stanke, M. et al. AUGUSTUS: Ab initio prediction of alternative transcripts. *Nucleic Acids Res* **34**, W435–W439 (2006).

75. Buchfink, B., Reuter, K. & Drost, H. G. Sensitive protein alignments at tree-of-life scale using DIAMOND. *Nat. Methods* **18**, 366–368 (2021).

76. Jones, P. et al. InterProScan 5: genome-scale protein function classification. *Bioinformatics* **30**, 1236–1240 (2014).

77. Finn, R. D. et al. Pfam: the protein families database. *Nucleic Acids Res.* **42**, D222–D230 (2013).

78. Camacho, C. et al. BLAST+: Architecture and applications. *BMC Bioinforma.* **10**, 1–9 (2009).

79. Eddy, S. R. Accelerated profile HMM searches. *PLOS Comput. Biol.* **7**, 1–16 (2011).

80. Dainat, J., Hereñú, D. & Pucholt, P. NBISweden/AGAT: AGAT-v0.5.1. https://doi.org/10.5281/zenodo.4205393 (2020).

81. Emms, D. M. & Kelly, S. OrthoFinder: Phylogenetic orthology inference for comparative genomics. *Genome Biol.* **20**, 238 (2019).

82. Paysan-Lafosse, T. et al. InterPro in 2022. *Nucleic Acids Res.* **51**, D418–D427 (2023).

83. Zhao, Y. et al. Astaxanthin preparation by lipase-catalyzed hydrolysis of its esters from Haematococcus pluvialis algal extracts. *J. Food Sci.* **76**, C643–C650 (2011).

## Acknowledgements

This work was supported by the French National Research Agency (GRAL Labex ANR-10-LABEX-04, EUR CBS ANR-17-EURE-0003, CDP Glyco@Alps ANR-15-IDEX-0002, Alpalga ANR-20-CE02-0020, DIM ANR-21-CE02-0021), Institut Carnot 3BCAR and the Kilian Jornet Foundation. Part of this research was supported by the Jardin du Lautaret (Univ. Grenoble Alpes, CNRS) on the Lautaret - Roche Noire eLTER site (Horizon 2020 research and innovation program under grant agreement No 871128). L.P. has been supported by Charles University Research Center program (UNCE/24/SCI/006) and acknowledges GAČR 24-10019S. D.R. was supported by the Austrian Science Fund (FWF): P 34073. Authors thank Parc
National des Ecrins, France and Olympus National Park, Greece, where sampling have been performed, and Greenlandia for sampling in Scoresby Fjord, Greenland.

## Author contributions

J.A.E., G.V., E.F., J.F., J.G.V., and E.M. have collected red snow algal blooms used to isolate and purify snow yeasts and to provide metagenomic data. L.P. and D.R. have collected samples of glacier algal blooms to purify purpurogallin natural extracts and provide metagenomic data. J.A.E., G.V., and Y.D. have performed physiological, cell biology and metabolic analyses. J.A.E. and G.V. have developed the method to purify fungi DNA used for genome sequencing. P.G.T. and R.A.C. have assembled and annotated the fungal genome. P.G.T. and N.T. have annotated and analyzed CAZy genes. J.A.E., P.G.T., and A.A. have performed phylogenetic and phylogenomic analyses. A.A. and E.M. have contributed to genomic and physiological analyses. J.A.E. and P.G.T. have contributed equally to the study. E.M. has designed the study. J.A.E., P.G.T., A.A., and E.M. have organized the writing of the manuscript. All authors have contributed to the writing of the manuscript.

## Competing interests

The authors declare no competing interest.

## Additional information

**Supplementary information** The online version contains supplementary material available at https://doi.org/10.1038/s42003-025-08506-w.

**Correspondence** and requests for materials should be addressed to Alberto Amato or Eric Maréchal.

**Peer review information** *Communications Biology* thanks Jason Stajich and Masaharu Tsuji for their contribution to the peer review of this work. Primary Handling Editor: Ophelia Bu.

**Reprints and permissions information** is available at http://www.nature.com/reprints

**Publisher's note** Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

**Open Access** This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/.

© The Author(s) 2025