Microbiomic Analysis of Bacteria Associated with Rock Tripe Lichens in Continental and Maritime Antarctic Regions

Increased research attention is being given to bacterial diversity associated with lichens. Rock tripe lichens (Umbilicariaceae) were collected from two distinct Antarctic biological regions, the continental region near the Japanese Antarctic station (Syowa Station) and the maritime Antarctic South Orkney Islands (Signy Island), in order to compare their bacterial floras and potential metabolism. Bulk DNA extracted from the lichen samples was used to amplify the 18S rRNA gene and the V3-V4 region of the 16S rRNA gene, whose amplicons were Sanger- and MiSeq-sequenced, respectively. The fungal and algal partners represented members of the ascomycete genus Umbilicaria and the green algal genus Trebouxia, based on 18S rRNA gene sequences. The V3-V4 sequences were grouped into operational taxonomic units (OTUs), which were assigned to eight bacterial phyla, Acidobacteriota, Actinomyceota, Armatimonadota, Bacteroidota, Cyanobacteria, Deinococcota, Pseudomonadota and the candidate phylum Saccharibacteria (also known as TM7), commonly present in all samples. The OTU floras of the two biological regions were clearly distinct, with regional biomarker genera, such as Mucilaginibacter and Gluconacetobacter, respectively. The OTU-based metabolism analysis predicted higher membrane transport activities in the maritime Antarctic OTUs, probably influenced by the sampling area’s warmer maritime climatic setting.


Introduction
Lichens are common and widely distributed symbiotic organisms. Although they are not charismatic in appearance, they occur in a wide variety of habitats and environmental conditions. While lichens photosynthesize and may superficially resemble mosses and grow with them, they are not phylogenetically related to mosses or other plant groups [1,2]. When lichens are present epiphytically, such as on tree trunks and branches or on moss surfaces, they occur commensally using the plants as colonization substrates. The physical structure of lichens is provided by lichen-forming fungi [3], which provide the formal scientific name of the lichen, while the photosynthetic function is provided by symbiotic microalgae and/or cyanobacteria [4][5][6], termed the mycobiont and photobiont, respectively. The entire lichen is a symbiotic holobiont consisting of a fungal and one or more algal/cyanobacterial partners.
Lichens require air, water, micronutrients and substrates to survive [7]. Like mosses, they cannot regulate their hydrological balance. However, as a group, they show impressive cryptobiotic adaptations and can tolerate and grow under conditions of irregular water supply, as well as showing high tolerance to severe abiotic conditions, such as extreme temperatures and high levels of light and ultraviolet radiation [8,9]. Based on these adaptations, lichens are often the pioneer microorganisms colonizing extreme environments such as montane areas, hot and cold deserts and the polar regions.
In addition to the symbiotic partnership between fungal and algal/cyanobacterial bionts, bacteria have also attracted increasing research attention in recent years as a third biotic component present within lichens [10]. Recognizing the roles of bacteria in fungal niches, research attention initially focused on the mycorrhizosphere. Since the pioneering work of Maria Cengia-Sambo in the 1920s [11], a number of bacteria have been isolated from cultured lichen thalli or, more recently, been detected by shotgun DNA sequencing [12,13]. Lichen-associated bacteria have also been proved to be an important contributor to lichen symbiosis [14][15][16]. A growing number of studies of the bacterial associations of lichens have changed the emphasis of research from basic taxonomic description to more in-depth functional analyses using next-generation sequencing and multi-omics approaches [14,17,18]. Among the lichen-associated bacteria, Alphaproteobacteria is probably the most prominent bacterial class detected, with abundant bacterial taxa representing the phyla Acidobacteriota, Actinomyceota and the Bacteroidota-Chlorobiota group (also known as Sphingobacteria) [18][19][20][21][22][23] (phylum names following the latest validation [24]).
The contributions bacteria make to the lichen symbiosis range across stress resistance, nitrogen fixation, provision of vitamins and acting as cofactors in the degradation of phenolic compounds [24,25]. The current study set out to analyze the lichen-associated bacterial diversity of selected Antarctic lichens by a culture-independent analysis of operational taxonomic units (OTUs) combined with OTU-derived prediction of bacterial metabolic potential in the lichen symbiosis. Rock tripe lichens (Umbilicariaceae) were targeted in this study because of their widespread occurrence on fellfield rocks in Antarctica, facilitating a first biogeographic comparison of OTU diversities and similarities/differences in metabolic potential in Antarctica. Lichens from the biogeographically distinct continental Antarctic and maritime Antarctic regions, sampled from Antarctic Conservation Biogeographic Regions (ACBRs) 5 and 2, respectively [26,27], were chosen for this purpose.

Collection of Rock Tripe Lichen Samples
Rock tripe lichens growing on fellfield rocks were sampled from two distinct Antarctic biogeographic regions: continental Antarctica (near Syowa Station in ACBR 5 Enderby Land) and maritime Antarctica (Signy Island in ACBR 2 South Orkney Islands) [27]. The former location was on the east shore of Lützow-Holm Bay, coastal Queen Maud Land, East Antarctica, where lichens were sampled in January and February 2011 during the 52nd Japanese Antarctic Research Expedition. On Signy Island, lichens were collected in January and February 2017 during a field season supported by the British Antarctic Survey. In total, 22 lichen samples were collected, 18 from three areas within a 50 km range in the Lützow-Holm Bay region near Syowa Station, and four from Signy Island ( Figure 1, Table 1). Signy Island is about 3780 km distant from Syowa Station as calculated by Great Circle Calculator [28].  Table 1. Thalli of rock tripe lichens were collected using a flame-sterilized surgical blade and tweezers and placed in pre-sterilized Whirl-Pak bags (Nasco, Fort Atkinson, WI, USA) or pre-sterilized 50 mL centrifuge tubes (As One, Osaka, Japan). The amounts of collected thalli varied between the individual sampling sites. The collected thalli were air-dried on site, stored in the dark during transportation and kept frozen at −25 • C in the laboratory until bulk DNA extraction.

Bulk DNA Extraction from Lichen Thalli
Approximately 1 g of lichen thalli from each sampling site was washed using autoclaved Milli-Q ultrapure water from Direct-Q UV 5 (Merck Millipore, Burlington, MA, USA). After washing, the lichen thalli were cut into small pieces using flame-sterilized scissors and ground using an autoclaved mortar and pestle. Bulk DNA was extracted from the ground thalli by bead-beating using the ISOIL Large for Beads ver.2 (Nippon Gene, Tokyo, Japan) and precipitated in 70% ethanol with the precipitation-facilitator Ethachinmate (Nippon Gene, Tokyo, Japan) [29]. The DNA precipitate was resuspended in sterilized ultrapure water, assessed for purity and quantity using a NanoDrop 2000c (Thermo Fisher Scientific, Waltham, MA, USA) and stored at −20 • C until PCR amplification.

Amplification and Sequencing of Fungal/Algal 18S rRNA Gene
The bulk DNA samples were used for PCR amplification of near-full-length 18S rRNA gene sequences of fungi and algae. The primers listed in Table 2 were used to amplify the target sequences by PCR using a TaKaRa PCR Thermal Cycler Dice Touch TP350 and a TaKaRa PCR Thermal Cycler PERSONAL (TaKaRa Bio, Kusatsu, Japan).
Thermal cycling for amplification of fungal 18S rRNA genes consisted of one cycle of initial denaturation at 95 • C for 5 min followed by 30 cycles of 95 • C for 45 s, 61 • C for 45 s and 72 • C for 80 s and one cycle of final elongation at 72 • C for 12 min. The same thermal cycling protocol, but with annealing at 53 • C, was used for the amplification of algal 18S rRNA genes. The eukaryotic positive controls were Saccharomyces-derived and Zooxanthella-derived DNAs. The negative control used autoclaved Milli-Q ultrapure water.

Amplification and Sequencing of V3-V4 Region of Bacterial 16S rRNA Gene
The extracted DNA from the lichen samples was used for PCR amplification with the V3-V4 specific primers 341 F and 806 R (Table 2) using the Kapa HiFi HotStart ReadyMix PCR kit (Kapa Biosystems, Inc., Wilmington, DE, USA) on a TaKaRa PCR Thermal Cycler Dice Touch TP350 (TaKaRa Bio). The thermal cycling protocol followed was: 95 • C for 3 min, 25 cycles of 95 • C for 30 s, 55 • C for 30 s, and 72 • C for 30 s and a final elongation at 72 • C for 5 min. The sequence library was constructed following [29]. Paired-end 300 bp sequencing by MiSeq (Illumina, San Diego, CA, USA) was performed using a Nextera XT Index Kit (Illumina) at the Department of Biomedical Science, N-BARD, Hiroshima University and at the molecular diagnostic company SolGent (Daejeon, Korea).

Sequence Data Analysis and OTU Determination
The Sanger-generated sequences of the 18S rRNA genes were aligned by ClustalW [35] using the BioEdit sequence alignment editor [36] to remove low-quality sequences. The remaining sequences were assembled manually and Chimera-checked by tree topology analysis [37]. The resulting sequences were BLAST-searched to identify the fungal and algal partners of the studied lichens.
The MiSeq-generated V3-V4 reads were processed with the Microbiome Taxonomic Profiling (MTP) pipeline of the EzBioCloud (https://www.ezbiocloud.net/contents/16 smtp; accessed on 9 February 2022) [38]. Briefly, the paired-end read merging as well as adapter and primer trimming were conducted using the EzBioCloud in-house scripts; in this step, unmerged reads, as well as ambiguous reads with <100 nucleotides or low average quality scores (<25), were omitted. For the quality-checked reads, the identical sequences were dereplicated, and then the non-redundant reads obtained were compared to the EzBioCloud 16S rRNA gene sequence database PKSSU4.0, with the option of the target taxon "bacteria". In this PKSSU4.0 database, the uncultured taxonomic group is tentatively given the hierarchical name assigned to the DDBJ/ENA/GenBank sequence accession number with the following suffixes: "_s" (for species), "_g" (genus), "_f" (family), "_o" (order), "_c" (class) and "_p" (phylum). The taxonomic assignment was performed based on the following sequence similarity cut-offs: ≥97% for species, 97 > x ≥ 94.5% for genus; 94.5 > x ≥ 86.5% for family; 86.5 > x ≥ 82% for order; 82 > x ≥ 78.5% for class; and 78.5 > x ≥ 75% for phylum, where x corresponds to a sequence s similarity to reference sequences [39]; reads below these cut-off values at the species or higher level were appended with the suffix "_uc" (for unclassified). All reads that could not be identified at the species level (<97% similarity) were subjected to chimera sequence detection through comparison with the EzBioCloud chimera-free reference database (https://help.ezbiocloud. net/mtp-pipeline/; accessed on 9 February 2022), and any chimera reads identified were discarded. Next, singleton reads as well as eukaryotic plastid reads were excluded. Finally, retrieved V3-V4 sequences were clustered into operational taxonomic units (OTUs) at a 97% identity cutoff value [38], which shows better universality over proposals for >98% [40]. The representative OTUs in the final data set were BLAST-searched.
The MiSeq-generated V3-V4 sequence datasets are available at DDBJ/ENA/GenBank under the DDBJ Sequence Read Archive (DRA) accession numbers DRA008580 and DRA014252, the BioProject numbers PRJDB8443 and PRJDB13657, and the BioSample numbers SAMD00175323, SAMD00175324, SAMD00175326-SAMD00175328 and SAMD00494392-SAMD00494408. The Sanger-generated 18S rRNA gene sequences were deposited in the DDBJ/ENA/GenBank database under the accession numbers LC487917, LC487919-LC487922 and LC712411-LC712427 for fungal 18S rRNA gene sequences and LC487925 and LC713009-LC713029 for algal 18S rRNA gene sequences. The sample-tonumber correspondences are listed in Tables S1-S3. Note that the data from DRA008580 were obtained in our previous study [29] and were used for comparison purposes (the relevant BioProject, BioSample, and 18S rRNA gene sequence numbers are as listed above).

Diversity Indices and Bioinformatic Analyses of OTUs
Using the EzBioCloud MTP pipeline, rarefaction curve analysis was computed. The alpha-diversity indices (Chao1, Shannon and Simpson indices) were also calculated by the EzBioCloud MTP to estimate the richness/evenness of bacterial OTUs associated with the lichen samples (note that the Chao1 index takes singletons into account).
The beta-diversity was illustrated by principal component analysis (PCA) and hierarchical clustering based on the UniFrac distance matrix for the Antarctic OTUs [41]. Biomarker OTUs that discriminate the lichen OTU populations were specified by the linear discriminant analysis (LDA) [42] and LDA-Effect Size algorithm (LEfSe; http:// huttenhower.sph.harvard.edu/galaxy/; accessed on 10 May 2022) [43]. While previous studies of lichen-associated microorganisms set the threshold LDA score to 2 [44,45], this study set the threshold to 4 and 5 in order to focus on biomarkers having large statistical differences between the two sampling regions. Differential abundance analysis was performed using the Analysis of Compositions of Microbiomes with Bias Correction (ANCOM-BC) [46].

Identification of Rock Tripe Lichen-Forming Fungi and Algae
BLAST search of the near-full-length 18S rRNA gene sequences obtained showed that the fungal members of the lichens sampled in the Syowa Station region were most closely related to the ascomycetes Umbilicaria decussata (17 of the 18 samples) and U. rhizinata (one sample from the Skallen Hills). In the four samples obtained from Signy Island, three were most closely related to U. rhizinata and one to U. aprina. Similarity values were 94.2% or higher (Table S2). Intra-specific variations in the gene sequences were observed.
The algal sequences obtained were most closely related to the green algal genus Trebouxia, which is the most common photobiont in lichens [50], with similarity values of 98.5% or higher (Table S3). Trebouxia aggregata and Trebouxia sp. SAG 2463, which are most closely related to each other, were the most closely related cultured species to the algal partners of the studied Umbilicaria lichens.

Evaluation of MiSeq-Generated V3-V4 Sequences and OTUs
MiSeq sequencing generated a total of 1,357,573 raw reads from the 22 lichen samples, yielding 1,028,426 valid reads to be grouped into OTUs. The mean length of the valid reads was 412 bp, which is within the quantile range of Q1 403 bp and Q3 427 bp, based on the EzBioCloud database [35]. The numbers of OTUs and OTU-derived species, genera, families, orders, classes and phyla in each sample are shown in Table 3. Table 3. Numbers of MiSeq-generated V3-V4 region reads, 97% similarity-based OTUs, OTU-derived species, genera, families, orders, classes and phyla in each sample. The sub-total and total numbers of taxa are smaller than the simple sums due to overlaps among samples. Mean lengths of valid reads are also listed. Samples S1 to S18 were collected in the region of Syowa Station, and samples SI01 to SI04 from Signy Island.

Sample
Raw Read  Table 4 shows the regional distributions of the numbers of taxa (OTU, species, genus, family, order, class and phylum) that were detected only in the samples from the Syowa Station region, only in those from Signy Island and in both regions. Higher percentages of region-specific OTUs were seen at the OTU and species ranks, while more than half of the classes and phyla were commonly seen in both regions, indicating bi-regional similarity at higher ranks and regional uniqueness at lower ranks.
Rarefaction curves were drawn based on the numbers of reads and OTUs ( Figure S1). The rarefaction analysis indicated that the coverage (the ratio of an observed OTU number against an estimated OTU number; equivalent to the alpha diversity index, Chao1) ranged from 80.93% in S8 to 98.38% in S16, with an overall average of 90.43% (respective coverages can be calculated from Table 5). Therefore, the numbers of MiSeq-generated reads are considered sufficient to perform further statistical and bioinformatic analyses. Table 4. Numbers of assigned OTUs and OTU-derived species, genera, families, orders, classes and phyla that were detected only from the Syowa Station region, only from Signy Island and from both regions. The total numbers are equal to those in Table 3.

Distribution
Observed

Taxonomic Composition of Lichen-Associated Bacterial Community
The compositions of the OTU-derived bacterial phyla from the 22 lichen samples are shown in Figure 2. Eight bacterial phyla were commonly present in all samples, with read abundances of >1% of total reads. Each lichen sample harbored a total 12 to 18 bacterial phyla (Table 3), with the additional 4 to 10 phyla representing <1% of reads. The common phyla were Acidobacteriota, Actinomycota (formerly Actinobacteria), Armatimonadota, Bacteroidota, Cyanobacteria, Deinococcota, Pseudomonadota (formerly Proteobacteria) and the candidate phylum Saccharibacteria_TM7.

Alpha and Beta Diversity
Alpha-diversity indices were calculated to evaluate the OTU richness of each lichen sample ( Table 5). The Chao1 index values were used as the estimated OTU numbers for the rarefaction analysis. The values of the Shannon and Simpson indices were used to calculate the effective number of species (ENS) [51]. Higher Chao1, Shannon and ENS values, as well as observed OTU numbers, indicating higher species richness were found in samples from Signy Island. Lower Simpson index values calculated for Signy Island samples also indicate higher species richness and evenness. Figure 2. Bacterial phylum compositions of OTUs obtained from lichen samples from the Syowa Station region in continental Antarctica (S1 to S18) and Signy Island in maritime Antarctica (SI01 to SI04). Eight phyla were observed with read abundances of >1% of the total read number. Compositions of bacterial classes, orders, families, genera and species are shown in Figures S2-S5.
The ENS values based on Shannon and Simpson indices were much smaller than the Chao1 values (estimated OTU numbers) as well as the observed OTU numbers and the OTU-derived species numbers (Table 3). Bacterial species richness of a large sample size may be better represented by Chao1, as also reported in other studies [52,53].
Beta diversity was assessed using PCA and hierarchical cluster analysis to depict similarity/dissimilarity between samples (Figure 3). Both the PCA plot and hierarchical clustering dendrogram showed the clear separation between OTU diversity obtained from Signy Island and the Syowa Station region at the species level. Clear regional separation was also apparent at the genus, family, order, class and phylum ranks ( Figure S6). In contrast, the different sampling areas within the Syowa Station region were not distinct at any taxonomic rank (PCA plots at species, genus, family, order, class and phylum rank are shown in Figure S7).
The regional distinction in OTU diversity was driven by biomarker OTUs or biomarker taxa, which were identified by LEfSe and are represented in the phylogenetic cladogram ( Figure 4). Among these, significant biomarkers having LDA scores >5 are listed in Table 6. Significant biomarkers in the Syowa Station region included OTU EU861966_s and the derived taxa (genus to phylum) of the genus Mucilaginibacter, the family Sphingobacteriaceae, the order Sphingobacteriales, the class Sphingobacteria and the phylum Bacteroidota. Significant biomarkers for Signy Island were the OTU Actinomycetota_c that was affiliated with the class-level taxon within the phylum Actinomycetota, as well as the family Acetobacteraceae and its superior taxa, i.e., the order Rhodospirillales, the class Alphaproteobacteria and the phylum Pseudomonadota.
At the species rank, only one biomarker OTU, EU861966_s from the Syowa Station region, was identified when the LDA score threshold was set to 5 (Table 6). By lowering the threshold to 4, a total of 16 biomarker OTUs (nine from Signy Island and seven from the Syowa Station region) were identified at the species rank and used for differential analysis by ANCOM-BC; the top biomarkers from the two regions are shown in Figure 5, and other biomarkers are shown in Figure S8.    Figure S8. Table 6. Biomarker OTUs and taxa having LDA scores >5 identified from the assigned OTU diversity obtained in the Syowa Station region and from Signy Island.

Region
Code in Figure 4 Rank Biomarkers with LDA scores >4, including the 16 species-rank biomarkers, were further characterized by PICRUSt to predict metabolic features of lichen-associated bacteria in both sampling regions. The biomarker OTUs were projected on the LEGG metabolic map, and key metabolic features were visualized. At the KEGG Level 1, consisting of the largest metabolic categories, each OTU population showed seven large pathways, including metabolism, genetic information processing, unclassified, environmental information processing, and cellular processes, in order of relative abundance ( Figure 6). Relative abundances of OTUs relevant to the "metabolism" pathway were as high as >50% in OTUs from both regions. At Level 2, consisting of sub-categories, OTUs from both sampling regions had the 26 pathways ( Figure S9), of which the top five were carbohydrate metabolism (11.2% in Signy and 11.0% in Syowa), amino acid metabolism (11.0% in Signy and 10.9% in Syowa), replication and repair (7.4% in Signy and 9.2% in Syowa), energy metabolism (5.7% in Signy and 6.4% in Syowa) and membrane transport (11.3% in Signy and 6.5% in Syowa). The greatest difference in the metabolic pathways was apparent in "membrane transport", which was more dominant in the Signy Island OTUs. At Level 3 ( Figure S10), large differences were apparent in "transporters" (5.5% in Signy and 3.6% in Syowa), "ABC transporters" (3.3% in Signy and 1.3% in Syowa) and "bacterial motility proteins" (1.5% in Signy and 0.5% in Syowa), suggesting higher activities in membrane transport-mediated metabolism and cellular mobility in the Signy Island OTUs. In addition, low but higher percentages of "cell motility" and "xenobiotic biodegradation and metabolism" in Signy Island may be associated with liquid water availability due to the island's warmer climate and potential human impact, respectively.

Discussion
Rock tripe lichens with mycobionts of the genus Umbilicaria and photobionts of the genus Trebouxia are commonly seen [29,54]. Variations in 18S rRNA gene sequences were found for U. decussata and U. rhizinata in this study, as reported in other Umbilicaria species [55]. The associated bacterial diversity showed no lichen species-specific grouping. For example, the bacterial OTUs associated with U. rhizinata sampled in the Syowa Station region and on Signy Island (samples S5 and SI01, respectively) were distinct in both PCA and hierarchical clustering analysis (Figure 3). Even comparing samples from the same general area (Skallen Hills and Langhovde Hills), bacterial OTUs associated with the same lichen species, U. decussata, were scattered rather than clustered on the dendrogram ( Figure 3). Rather, bacterial OTUs were clearly clustered by geographical region, irrespective of the different Umbilicaria species. We conclude that it is not the difference in lichen species but rather the geographical/environmental setting that is the major influence on the bacterial floras associated with the Umbilicaria species studied here.
The influence of the algal species, Trebouxia aggregata and Trebouxia sp. SAG 2463, on the OTU floras, should not necessarily be considered. The 18S rRNA gene sequence (MT901379) of the most closely related T. aggregata is from the strain T. aggregata SAG 219-1d, isolated from the foliose lichen of the ascomycete Xanthoria in Europe [56] and maintained at the Culture Collection of Algae at Göttingen University (Sammlung von Algenkulturen der Universität Göttingen, SAG), Germany. The strain Trebouxia sp. SAG 2463 may have also been cultured at SAG but is not listed in the current SAG catalog (https://uni-goettingen. de/en/45175.html; accessed on 17 May 2022). The 18S rRNA gene sequences of the two strains are so closely related (99.8% similarity) that they would have been grouped into a single species. Therefore, we conclude that the algal photobionts of the studied Umbilicaria lichens should be regarded as monospecific despite intraspecific variations in 18S rRNA gene sequences being present and, thus, not influencing the composition of associated OTUs.
The number of valid reads from Signy Island was only about 10% of the total obtained, contrasting with 57% from the Syowa Station region, resulting in lower numbers being recorded at all taxonomic ranks on Signy Island. However, the assigned OTUs from Signy Island showed higher alpha-diversity, despite the smaller sample size, than those from the Syowa Station region (Table 5). In terms of beta-diversity, the Signy Island and Syowa Station regions were clearly separated by the PCA and hierarchical cluster analysis (Figure 3), while the 18 samples from three areas within a 50 km range in the Syowa Station region did not show any evidence supporting clustering of associated bacterial diversity by local area. This suggests that the~4000 km distance between the two sampling regions is sufficient to provide a strong biogeographic barrier, while the 50 km local separation within the near-Syowa Station region is not. The possibility that the 6-year difference in sampling seasons at the two locations (2011 and 2017) may have influenced the data obtained cannot be excluded, but we consider this to be unlikely.
The difference in the maritime and continental Antarctic settings of the two sampling regions may also affect beta diversity. On Signy Island, the recorded annual mean/maximum/minimum ground temperatures are −1.7/18.4/−8.7 • C [57]. It should be noted that a (then) record high air temperature (19.8 • C) for weather stations south of 60 • was reported from Signy Island in 1982 [58]. In the Langhovde area near Syowa Station, recorded annual mean/maximum/minimum ground temperatures are −8.9/21.7/−32.8 • C [59], showing lower mean and minimum ground temperatures and a wider temperature range in the continental area than the maritime region. Thus, temperature may be a key driver amongst the environmental variables likely to influence both lichen and associated bacterial occurrence and community interactions.
Higher metabolic activities predicted for the Signy Island OTUs could be related to the generally warmer and less stressful climate of this Maritime Antarctic island. Metabolism generally scales with temperature regardless of acclimation and evolutionary adaptation [60]. A warmer (and also damper) climate may favor bacterial species having higher metabolic potential, as suggested by the PICRUSt prediction ( Figure 6 and Figures S9 and S10), thus influencing microbiome structures as represented by OTU diversity and biomarker OTUs. Note that the accuracy of metabolic predictions by the PICRUSt depends on the presence of reference genomes that are phylogenetically related to the OTUs detected. In order to more deeply elucidate their metabolic characteristics, future studies will need to isolate and characterize bacteria related to key OTUs or reconstruct their genomes by culture-independent metagenomic approaches (also known as metagenome-assembled genomes). The metabolism of the other lichen components, fungi and algae/cyanobacteria, also scales with temperature and may itself have direct or indirect influences on associated bacteria. Patterns of bacterial and fungal/algal metabolic interactions may vary among lichens and be subject to selection. The OTU analyses presented here provide clues to understanding the functional roles of bacteria as a third component of the lichen symbiosis, though more data are clearly required in this very young research area.
Supplementary Materials: The following supporting information can be downloaded at: https: //www.mdpi.com/article/10.3390/jof8080817/s1. Table S1: List of BioProject numbers, DDBJ Sequence Read Archive (DRA) accession numbers, and BioSample accession numbers of the V3-V4 sequence datasets registered to the public database of DDBJ; Table S2: List of the accession numbers of near-full-length fungal 18S rRNA gene sequences of the studied rock tripe lichen samples, the accession numbers and the most closely related species with respective accession numbers, as well as similarity values (%); Table S3: List of the accession numbers of near-full-length algal 18S rRNA gene sequences of the studied rock tripe lichen samples, the accession numbers and the most closely related species with respective accession numbers, as well as similarity values (%). Figure S1: Rarefaction curves based on the numbers of reads and OTUs from 18 sites in the Syowa Station region and 4 sites on Signy Island; Figure S2: Bacterial class compositions of OTUs in lichen samples from the Syowa Station region in East Antarctica (S1 to S18) and Signy Island in the Maritime Antarctic (SI01 to SI04); Figure S3: Bacterial order compositions of OTUs in lichen samples from the Syowa Station region (S1 to S18) and Signy Island in the Maritime Antarctic (SI01 to SI04); Figure S4: Bacterial family compositions of OTUs in lichen samples from the Syowa Station region (S1 to S18) and Signy Island in the Maritime Antarctic (SI01 to SI04); Figure S5: Bacterial genus compositions of OTUs in lichen samples from the Syowa Station region (S1 to S18) and Signy Island in the Maritime Antarctic (SI01 to SI04); Figure S6: PCA plots of OTU-derived species (upper left), genera (upper middle), families (upper right), orders (lower left), classes (lower middle) and phyla (lower right) of the lichens sampled from Signy Island (green) and the Syowa Station region (red); Figure S7: PCA plot of OTU-derived species of the lichens sampled from three areas (purple, thin blue and yellow in Figure 1) within the Syowa Station region; Figure S8: Significant differences (p < 0.05) in relative abundances of biomarker OTUs from the Syowa Station region (red) and Signy Island (green) analyzed by ANCOM-BC. Names of possibly affiliated genera or phyla are shown below the OTU names if applicable; Figure S9: KEGG Level 2 metabolic pathways found in the biomarker OTUs from Signy Island (green) and the Syowa Station region (red); Figure S10: KEGG Level 3 metabolic pathways found in the biomarker OTUs from Signy Island (green) and the Syowa Station region (red). Figure S11. Excerpt of KO functions found in the biomarker OTUs from Signy Island (green) and the Syowa Station region (red). Horizontal axis indicates relative abundance (%) of each function to be compared between the two regions. The functions are selected by cut-off value of mean relative abundance distance of two region > |0.0015|.
Author Contributions: Z.H. performed the bioinformatic analyses and prepared the first draft of the manuscript. T.N. planned the study, performed the sample collection in the Syowa Station (Lützow-Holm Bay) region and reviewed/edited the manuscript. R.N. supported the bioinformatic analyses and edited the manuscript. S.I. supported the sample collection and reviewed the manuscript. M.T. performed and P.C. supervised the sample collection on Signy Island, and both reviewed/edited the manuscript. All authors have read and agreed to the published version of the manuscript.
Funding: This work was supported by JSPS KAKENHI Grant Number 16H05765 to T.N. P.C. is supported by NERC core funding to the BAS 'Biodiversity, Evolution and Adaptation' team.
Institutional Review Board Statement: Not applicable.