Environmental characterization
Ice bottom (SI) and water column (WC) samples from Lake Labynkyr (LL) and Lake Vorota (LV) were collected and analysed during three ice-cover periods in April through May 2016 and June 2017 (Table 1). Both lakes were 100% covered with snow, and its thickness in April was 30 cm, while in May-June it varied between 1 and 5 cm. The ice thickness in the sampling sites varied between 86 and 111 cm. The ice in April and May was solid and transparent, while in June it became acicular and dark. Ice bottom sampling was not performed in June, because the ice was impregnated with water. Water temperature near the ice bottom varied between 0.4 and 1.2°C. A water temperature of 1.2–3.6°C recorded in water column of the northern and central parts of LL was lower compared to that in the southern part of the lake, 3.7–5.6°C. Water temperature in LV did not exceed 3.2°C (Table 2). The pH values in April were weakly alkaline, 7.70–8.28, and in May they shifted to more alkaline range 7.81–9.34, and were neutral in June, 6.80–7.21. Dissolved oxygen values were stable between 6.7 mg/L and 10.6 mg/L.
Table 2
Physical, chemical and biological characteristics of samples
Time point | Sample | T ºC | рН | EC µS/cm | DO mg/L | PO43− mg/L | NH4+ mg/L | NO2− mg/L | NO3− mg/L | Nmin mg/L | TDS mg/L | TOC mgC/L | TMA×103 cells/L | TMB g/m3 |
April | L1SI04 | 0.4 | 8.28 | 49.00 | 10.6 | 0.001 | 0.021 | 0.002 | 0.35 | 0.10 | 33.19 | 3.26 | 19.57 | 0.07 |
L1WC04 | 1.2 | 7.84 | 43.22 | 0.003 | 0.059 | 0.002 | 0.30 | 0.12 | 29.29 | 2.58 | 13.70 | 0.03 |
L2SI04 | 1.2 | 7.71 | 45.98 | 7.5 | 0.001 | 0.062 | 0.002 | 0.34 | 0.13 | 31.82 | 2.88 | 24.10 | 0.06 |
L2WC04 | 2.6 | 7.93 | 39.49 | 0.002 | 0.058 | 0.001 | 0.29 | 0.11 | 26.67 | 2.21 | 35.95 | 0.01 |
L3SI04 | 0.4 | 7.55 | 44.92 | 8.9 | 0.001 | 0.014 | 0.002 | 0.33 | 0.08 | 30.72 | 3.45 | 20.95 | 0.02 |
L3WC04 | 1.9 | 7.93 | 39.49 | 0.002 | 0.058 | 0.001 | 0.29 | 0.11 | 26.67 | 2.21 | 28.85 | 0.03 |
L4SI04 | 0.4 | 7.48 | 50.1 | 8.2 | 0.004 | 0.019 | 0.001 | 0.42 | 0.11 | 33.96 | 3.04 | 40.40- | 0.04 |
L4WC04 | 3.7 | 7,70 | 39.85 | 0.001 | 0.069 | 0.002 | 0.28 | 0.12 | 26.54 | 3.04 | 39.55 | 0.13 |
May | L1SI05 | 0.5 | 8.78 | 38.41 | 8.5 | 0.009 | 0.013 | 0.002 | 0.33 | 0.08 | 25.33 | 1.45 | 15.75 | 0.01 |
L1WC05 | 2.6 | 9.34 | 45.72 | 0.003 | 0.012 | 0.002 | 0.34 | 0.09 | 30.30 | 2.14 | 222.23 | 0.08 |
L3SI05 | 1.2 | 7.81 | 23.34 | 9.8 | 0.006 | 0.007 | 0.003 | 0.19 | 0.05 | 17.16 | 1.99 | 34.40 | 0.03 |
L3WC05 | 3.4 | 9.26 | 40.76 | 0.002 | 0.016 | 0.001 | 0.20 | 0.09 | 27.71 | 2.66 | 313.67 | 0.03 |
L4SI05 | 1.3 | 6.97 | 8.517 | 9.6 | 0.000 | 0.009 | 0.002 | 0.17 | 0.05 | 6.56 | 1.50 | 52.56 | 0.06 |
L4WC05 | 3.7 | 9.20 | 41.53 | 0.007 | 0.012 | 0.002 | 0.33 | 0.08 | 28.47 | 1.28 | 227.78 | 0.07 |
V1SI05 | 0.4 | 8.94 | 41.48 | 8.5 | 0.008 | 0.001 | 0.003 | 0.10 | 0.02 | 31.74 | 1.24 | 192.7 | 0.03 |
V1WC05 | 3.1 | 8.82 | 51.21 | 0.012 | 0.004 | 0.000 | 0.08 | 0.02 | 42.47 | 0.86 | 79.55 | 0.08 |
June | L1WC06 | 3.6 | 6.80 | 30.89 | 8.3 | 0.003 | 0.017 | 0.003 | 0.33 | 0.09 | n.d. | 1.05 | 173.3 | 0.02 |
L3WC06 | 2.5 | 6.97 | 37.71 | 7.3 | 0.003 | 0.012 | 0.003 | 0.38 | 0.09 | n.d. | 0.86 | 127.1 | 0.03 |
L4WC06 | 5.6 | 6.98 | 41.07 | 8.4 | 0.016 | 0.012 | 0.005 | 0.45 | 0.11 | n.d. | 0.86 | 121.3 | 0.05 |
V1SI06 | 0.4 | 7.15 | 49.55 | 6.7 | 0.014 | 0.015 | 0.003 | 0.05 | 0.02 | n.d. | 0.83 | 55.67 | 0.02 |
V1WC06 | 3.2 | 7.21 | 54.75 | 0.023 | 0.016 | 0.006 | 0.06 | 0.02 | n.d. | 1.84 | 95.13 | 0.04 |
V2WC06 | 2.2 | 7.10 | 33.80 | 8.3 | 0.014 | 0.016 | 0.003 | 0.04 | 0.03 | n.d. | 0.75 | 84.91 | 0.02 |
Phosphate, nitrite, nitrate and total nitrogen concentrations in SI samples did not considerably differ from those in WC samples. Phosphate concentrations in April did not exceed 0.004 mg/L in LL, in May and June they increased to 0.009 mg/L and 0.016 mg/L respectively. In LV they remained within 0.008–0.024 mg/L. Nitrite concentrations in all samples did not exceed 0.006 mg/L. Nitrate concentrations in LL were between 0.17 mg/L and 0.45 mg/L, exceeding those in LV, which were in the range of 0.04–0.10 mg/L. Ammonium ion content in WC samples was equal to 0.058–0.069 mg/L in April and 0.004–0.017 mg/L in May-June, and was higher than in SI samples. The lakes have a low salt content; the sum of main ions did not exceed 33.96 mg/L in LL and 42.47 mg/L in LV. Organic matter indicators varied between 0.75 mgC/L and 3.26 mgC/L; they were higher in April than in May and June.
LL phytoplankton included Bacillariophyta, Chrysophyta, Dinophyta, Haptophyta, Cryptophyta, and Chlorophyta species, and the biomass of algae was in the range 0.01 to 0.13 g/m3. Small centric diatoms Pantocsekiella costei (J.C. Druart & F.Straub) K.T.Kiss & E.Ács were the most abundant in all samples (65–90%), while larger diatoms Lindavia minuta were within 5%. Bacillariophyta and Cryptophyta species dominated LV phytoplankton; the biomass of algae varied between 0.02 and 0.08 g /m3. Diatoms P. costei and Lindavia ocellata (Pantocsek) T.Nakov et al. prevailed in all samples; Lindavia minuta (Skvortsov) T.Nakov et al. was about 20% of the total number in May, while in June the contribution of cryptophytic Rhodomonas pusilla (H.Bachmann) Javornicky was in the range 10 to 50%.
Richness, diversity and bacterial community composition
2177 OTUs (97% similarity) from 997349 quality-filtered, chimera-free, paired sequences obtained from 21 samples (47517 reads in average in a sample, mean length 455 bps) were identified in total. Rarefaction curves built for all samples at a genetic distance of 0.03 reached the saturation, indicating that the bacterial diversity was sufficiently embraced (Fig. S1). The number of OTUs and the values of taxonomic richness (Chao1) and diversity (Shannon and Simpson) indices of the communities were higher in LL than in LV, with higher values being found in water column of the northern (L1WC05, L1WC06) and southern parts of LL (L4WC06) in May and June. In total, the number of OTUs in SI and WC communities was similar (406–465) in April; in May and June, it was higher in WC (535–1301) than in SI (439–600) (Table 3).
Table 3
Non-parametric alpha diversity metrics calculated for the bottom surface of the ice and water column samples collected from lakes Labynkyr and Vorota over three sampling dates
Time point | Samples | Reads | Richness (OTU) | Chao1 | Simpson | Shannon |
April | L1SI04 | 47504 | 431 | 431.0 | 0.0286 | 4.31 |
L1WC04 | 47535 | 424 | 424.0 | 0.041 | 4.11 |
L2SI04 | 47512 | 433 | 433.0 | 0.0268 | 4.32 |
L2WC04 | 47508 | 417 | 417.0 | 0.0217 | 4.52 |
L3SI04 | 47513 | 406 | 406.0 | 0.0238 | 4.41 |
L3WC04 | 47488 | 465 | 465.7 | 0.0286 | 4.35 |
L4SI04 | 47453 | 434 | 435.9 | 0.0269 | 4.37 |
L4WC04 | 47468 | 464 | 464.9 | 0.018 | 4.61 |
May | L1SI05 | 47485 | 439 | 440.4 | 0.054 | 3.85 |
L1WC05 | 47449 | 1301 | 1301.3 | 0.0371 | 4.86 |
L3SI05 | 47491 | 600 | 606.4 | 0.182 | 3.16 |
L3WC05 | 47519 | 568 | 569.2 | 0.0254 | 4.51 |
L4SI05 | 47558 | 379 | 381.2 | 0.393 | 1.82 |
V1SI05 | 47513 | 409 | 410.2 | 0.0902 | 3.44 |
V1WC05 | 47474 | 447 | 448.1 | 0.0338 | 4.13 |
June | L1WC06 | 47632 | 1022 | 1023.7 | 0.133 | 3.21 |
L3WC06 | 47534 | 535 | 536.2 | 0.0482 | 4.01 |
L4WC06 | 47729 | 1253 | 1253.0 | 0.0232 | 4.98 |
V1WC06 | 47459 | 509 | 513.9 | 0.102 | 3.35 |
V1SI06 | 47521 | 392 | 393.8 | 0.0928 | 3.15 |
V2WC06 | 47504 | 342 | 345.7 | 0.130 | 2.82 |
All OTUs were distributed by 15 phyla, about 3% of all sequences belonged to unclassified Bacteria. The bacterial phyla, to which the most sequences had been attributed, included Proteobacteria (OTUs, ~ 59%) and Actinobacteriota (OTUs, ~ 11%). It is noteworthy that the abundance of Proteobacteria was represented mainly by Gammaproteobacteria and Alphaproteobacteria was relatively even in all communities, while the abundance of Actinobacteriota dramatically decreased in all communities of both lakes in June, compared with April and May (Fig. 2). Other abundant phyla that had a different distribution among the communities included Planctomycetоta (OTUs, ~ 6%), Cyanobacteria (OTUs, ~ 5%), Bacteroidota (OTUs, ~ 4%), Verrucomicrobiota (OTUs, ~ 4%), and Patescibacteria (OTUs, ~ 3%). These taxa were relatively evenly abundant in April in all communities. In May and June, Planctomycetоta were decreased, while Bacteroidota and Verrucomicrobiota were more abundant. Cyanobacteria were the most abundant in all LV communities, while the Patescibacteria species was found in quantity in several LL water column communities (Fig. 2). Distribution of Acidobacteriota, Bdellovibrionota, Chloroflexi, Dependentiae, and Firmicutes phyla were within 1% of all sequences, and also differed depending on community.
Community structure relationships
Exploratory analysis revealed a high intra-group similarity of April and May LL communities as well as an isolated position of LV samples (Fig. 3). June LL communities formed a more diffuse cluster. According to the analysis, L4SI05 and L3SI05 communities were excluded from the sampling when quantifying the number of OTUs by sampling time. LV communities are divided in two groups: the first includes V1SI06 and V2WC06 (group June), the second unites three remaining samples V1WC06, V1SI05 and V1WC05 (group May). Heat map clustering results (Fig. 4) confirm that April LL communities are similar. The analysis of dissimilarity of OTU number among samples of this group revealed only Moraxellaceae (OTU27 Acinetobacter) and Sphingomonadaceae (OTU49 Sphingobium) were more abundant in WC samples than in samples from communities at the ice-water interface (SI samples).
The most significant dissimilarities are observed between bacterial communities are taken in April and June LL (Fig. 4). For example, OTUs taxonomically affiliated to chloroplast-specific sequences, Comamonadaceae (Curvibacter, Acidovorax), Cyanobiaceae (Cyanobium_PCC-6307), uncultured Methylacidiphilaceae, Mycobacteriaceae (Mycobacterium), uncultured Pirellulaceae, and uncultured Gaiellales were significantly more abundant in June. OTUs affiliated to Burkholderiaceae (Polynucleobacter), Chthoniobacteriaceae (Chthoniobacter), Comamonadaceae (Limnohabitans), Ilumatobacteraceae (CL500-29_marine_group), Moraxellaceae (Acinetobacter), Sporichthyaceae (Candidatus_Planktophila, hgcI_clade), Burkholderiales (TRA3-20) were less abundant in June then in April (Table S2). Oxalobacteraceae (Massilia) have a similar temporal dynamics when comparing LL communities in April/May and April/June, their abundance increases in end spring and early summer.
May/June and April/June LL communities demonstrated a similar pattern of changes, though the list of differentially abundant OTUs and the range of abundance differences was slightly less pronounced (Fig. 4, Table S2). OTUs affiliated to uncultured Pirellulaceae and uncultured Gaiellales were found mainly in June, while Polynucleobacter, Chthoniobacter, SAR11, Limnohabitans, unclassified Comamonadaceae, Ilumatobacteraceae (CL500-29_marine_group), and Acinetobacter were significantly more abundant in in May. Within LV communities Sporichthyaceae and Ilumatobacteraceae were abundant in May, while Beijerinckiaceae (Methylobacterium-Methylorubrum) had the opposite dynamics. Comparative analysis of the distribution of the most abundant OTUs also suggests differences in OTU abundance across the LL and LV communities. OTUs belonged to unclassified Beijerinckiaceae, Burkholderiaceae (Polynucleobacter), Chthoniobacteraceae, (Chthoniobacter), Moraxellaceae (Acinetobacter), uncultured Pirellulaceae, and Pseudomonadaceae (Pseudomonas) were more abundant in LL communities, while chloroplast-specific sequences, Cyanobiaceae (Cyanobium_PCC-6307), Ilumatobacteraceae (CL500-29_marine_group), uncultured Methylacidiphilaceae, uncultured Oligoflexales, and uncultured Gaiellales were found mainly in LV communities (Fig. 4, Table S2).
Effect of the environmental factors on community composition
We studied the correlation between the structure of bacterial communities and different environmental parameters, such as thickness of snow mantle, water temperature, pH, EC25, DO, PO43−, NH4+, NO3−, NO2−, Nmin, TOC, TMA and TMB. According to the results of transformation-based RDA, the important exploratory variables were the thickness of snow mantle (R2adj = 0.19, p = 1.3E-3), pH (R2adj = 0.11, p = 2E-3), conductivity (R2adj = 0.11, p = 1.3E-3), and total nitrogen concentration (R2adj = 0.10, p = 1.3E-3) (Fig. 5a). The proportion of the total variation explained by these four variables is ~ 70%, which is rather high. The grouping pattern revealed by the constrained ordination approach is very similar to that of the unconstrained approach (Fig. 3a). Variance partitioning (Fig. 5b) shows almost no overlap between the model variables except snow thickness and total nitrogen. The latter fact highlights that snow thickness and TN are autocorrelated considerably.
Cultivated organotrophic bacteria
The total number of microorganisms in the lakes was not high, 0.2–1.0×106 cells/mL, and the quantity of cultivable bacteria varied between 10 to 330 CFU/mL. Forty-nine strains were isolated from the under-ice communities of the lakes. Twenty-six strains with different morphological characteristics were chosen for taxonomical identification via the phylogenetic analysis of 16S rRNA gene. The resulting sequences of the cultivable strains were attributed to Proteobacteria, Actinobacteria, Bacteroidetes, and Firmicutes (Fig. 6). More than half of the sequences had a high similarity (99–100%) with bacterial sequences from cold habitats (Table S3). The genus Pseudomonas represented by seven species (Ps. gramilis, Ps. fragi, Ps. antarctica, Ps. collierea, Ps. yamanorum, Ps. tolaasy and Ps. fluorescens) dominated among Proteobacteria. In addition, Proteobacteria were represented by strains closely related to Janthinobacterium (J. lividum), Rahnella (R. aquatilis), Serratia (S. myotis). Actinobacteria belonged to the genera Micrococcus (M. yunnanensis) and Rhodococcus; their sequences were attributed to three species: R. cerastii, R. fascians, and R. qingshengi. Bacteriodetes species were from the genera Chryseobacterium and Pedobacter (P. terrae). Firmicutes was represented by a sole strain Paenibacillus amylolyticus.