A total of 80 seawater samples were collected seasonally at five different depths: 5, 25, 75, 100, and 200 meters, which corresponds to 5 depth strata, from four stations. A total of 8 sediment samples were collected seasonally from two coastal stations (K1 and K3).
3.1. Environmental Parameters
Environmental parameters are presented in Table S1 and Figure S1. Clear vertical stratification was detected in some environmental parameters with different gradients between zones. The surface mixed layer (SML, 5 m) and upper thermocline (TL, 25 m) was characterized by seasonal changes in temperature, whereas the deeper zone was relatively stable. Water temperature and salinity did not differ between sites or with increasing distance from shore. The temperature at SML and TL were warmer during the summer and spring, reflecting seasonal patterns. The temperatures at the mineralization/nitrification zone (MNZ, 75 m) and below were within the same range in all seasons. Salinity and density increased with increasing depth in all seasons. Light dramatically declined between SML and TL. Depths below MNZ appeared to be aphotic. Drastic changes in Chlorophyll-a and dissolved oxygen were observed between TL and MNZ.
The highest silicate concentration was measured in MNZ, significantly different than SMZ. Seasonally, the lowest silicate concentration was measured in summer, and the highest concentration was measured in autumn. The availability of silica limits diatom production . Decreased silicate in summer may be related to the increased abundance of diatoms. The highest nitrate concentration was detected in winter, whereas the lowest in summer. Vertically, in terms of nitrate, SML was the poorest, and TL was the richest zone. Spatially and vertically, nitrate concentration significantly (P < 0.01) differed in coastal stations and OMZ. Seasonally, nitrate concentration in autumn and winter was significantly different from spring and summer. Comparatively higher nitrate and lower nitrite in this study indicated the rapid conversion of ammonia to nitrate. The highest phosphate concentration was measured in autumn, which significantly differed from other seasons. Phosphate concentration increased with depth, with the highest concentration in AZ. The lowest ammonia concentration was calculated in autumn, which showed a significant seasonal difference. Vertically highest ammonia concentration was calculated for OMZ, whereas the lowest for TL. Dissolved oxygen concentrations decreased dramatically after TL in all seasons, and hydrogen sulfide concentrations increased exponentially after Oxygen minimum zone (OMZ) and remained relatively constant in all seasons. The highest total organic carbon (TOC) concentrations were measured in surface waters during the summer months, attributed to increased water temperature and phytoplankton growth. Although water quality parameters measured at stations close to the shore (K1 and K3) were considerably higher in most of the cases compared to the offshore stations, differences were insignificant (p<0.05).
3.2. Metabarcoding and Microbial Diversity
The MiSeq paired-end sequencing of the libraries yielded a total of 2,358,752 reads. After assembly of paired-reads, quality filtering, and chimera removal, a total of 2,019,141 valid reads were retrieved from 88 samples. The total number of sequence reads ranged between 157,998 (Summer-K3–25 m) and 285,952 (Spring-K1-SED), with an average of 207,960. The number of raw reads for each library was relatively uniform. Average Phred quality score for Q30 was 98.66.
Metabarcoding successfully detected 23 phyla (Table S2), 45 classes, 102 orders, 208 families (Table S3), 527 genera, and 750 species (Table S4) from a total of 88 samples collected seasonally from 4 different stations at five different depths in each station in the Black Sea. Rarefaction curves of sampling sites were similar, and most reached a plateau, excluding sediment samples, indicating that sampling effort was sufficient to detect microorganisms in the water community (Figure S2). The rarefaction curves of the sediment samples did not form plateau which might indicate that sediment samples is not a good representation of the microbial community. Thus, the accumulation curves failed to reach a plateau (Figure S3). Sampling different layers of sediment would give a better representation of the sediment microbial community. Alpha diversity indices are presented in Table S5 and Figure S4. There are a few metabarcoding studies performed in the Black Sea. Bobrova (Bobrova et al., 2016) detected the presence of 8 bacterial phyla from the surface waters of three estuaries. Zhang et al. (2020) conducted the most comprehensive metabarcoding study in which water samples were collected at four vertical layers from 12 stations for once and detected 141 prokaryotic species. Our finding differed from previous studies in which comparatively more diverse microbial communities were found, with higher-level at deeper stations. This could also be due to methodological differences especially in the bioinformatics. Also, the previous study did not have sediment samples which would increase diversity. In this study, prokaryotic reads were assigned to 750 bacteria species. The percentage of taxonomically classified reads was high, which is the expected outcome of seasonal sampling from different water layers. The present study’s annotation results reflected the Black Sea’s microbial communities’ composition based on the current knowledge and information contained in reference databases. Our findings indicated that the number of observed OTUs and species richness increased from the surface to deeper zones reflecting diversified species adapted to a broader range of ecological niches. An increase in species richness from the surface to deeper layers was also reported previously (Pommier et al., 2010; Haro-Moreno et al., 2018; Xue et al., 2020). However, our findings reflect the global relevance of species richness pattern. The deeper sites (100 and 200 m) had the highest diversity. An increase in bacterial diversity with depth could be explained by the increased availability of different inorganic substances (Arnosti, 2014; Haro-Moreno et al., 2018). Instable environmental parameters, high light intensity, and temperature fluctuations at the surface layer can be extreme for some bacterial taxa, resulting in fewer taxa’s survival with higher abundance.
At the phylum level, almost half of the phyla (9 out of 25) represented in each sample (Figure 2a). Overall, the majority of the reads and OTUs belonged to Proteobacteria (40% reads and 58.4% OTUs), Cyanobacteria (19.5% reads and 2.8% OTUs), Planctomycetes (12.2% reads and 2.5 OTUs), Bacteroidetes (10.9% reads and 13.8% OTUs), Verrucomicrobia (9.6 reads and 2.9 OTUs), and Actinobacteria (2.3% reads and 5.6% OTUs) (Table 1, Figure 2b and 2c). The major phyla composition, which represented the highest number of reads and OTUs, was uniform among seasons (Figure 2d) and stations (Figure 2e). Meanwhile, the composition of most phyla differed among depths. Almost 20% of lineages (5 out of 25) were dominant in SML and TL, 48% lineages (12 of 25) in MNZ and OMZ, and 32% lineages (8 of 25) were more abundant in AZ (Figure 2f).
After excluding OTUs with low reads at the family level, 29 out of 76 OTUs were presented in each station (Figure 3a). Overall, the bacterial community was dominated by Prochloraceae, a family of Cyanobacteria (16.9% reads) represented with a single species, Prochlorococcus marinus. The remaining majority of the reads and OTUs belonged to Rhodobacteraceae (11.6% reads and 11% OTUs), Planctomycetaceae (10% reads and 0.9% OTUs), and Flavobacteriaceae (7.5% reads and 13.2% OTUs), which is the most diverse family represented with 60 OTUs (Figure 3b and 3c). The composition of the major families represented with the highest number of reads and OTUs was uniform among seasons (Figure 3d) and stations (Figure 3e). Most of the community composition differed with depth at the family level (Figure 3f). Some of the lineages’ distribution was non-uniform among different depths with asymmetrical allocations of reads (Figure S5-S10).
A total of 12 families were identified as indicator taxa for the seasonal changes in microbial communities. A detailed list of indicator family taxa for stations, seasons, depths, and zones is tabulated in Table S6. In particular, Cyanobacteria families of Chamaesiphonaceae and Spirulinaceae were among the strongest indicator taxa in the Autumn and Spring season. Anaerolineaceae and Spirulinaceae families were recovered as indicator taxa for station groups of K1 and K1-K3, respectively. However, not all sampling sites belonging to these groups are included in these taxa. We observed zonation in the microbial communities belonging to Desulfobacteraceae, Vicinamibacteraceae, Ectothiorhodospiraceae, Dehalogenimonas (Genus), Desulfuromonadaceae, and Methyloligella (Genus) being commonly recovered from water samples below MNZ (Sewell et al., 2017; Kato et al., 2019; He et al., 2020), while Lentimicrobiaceae and Desulfobulbaceae were identified as indicator taxa for AZ. The absence or low recovery of Caldilineaceae appeared as an indicator for surface SML. Families of Rhodothermaceae and Mycobacteriaceae were identified as indicator taxa for SML, TL, MNZ, and OMZ, respectively, with low restriction to these zones. On the other hand, four taxa were assigned as an indicator for an anoxic zone. The strongest indicator taxon for AZ was OTUs assigned to Anaerolineaceae. The presence of OTUs belonging to the families, Desulfobacteraceae, Caldilineaceae, and Vicinamibacteraceae were strongly associated with aphotic and anoxic zones (Table S6).
3.3. Variation in microbial community composition
Microbial community composition difference between sampling sites was insignificant (p>0.05). K3 station was chosen to assess whether the copper mining discharge system in that specific region at a depth of 180 meters affected the microbial community structure and composition. However, there was no significant difference between sampling stations (PERMANOVA, F=0.927, R2=0.031, p=0.538). Similar communities could be found between long distances as long as no oceanographic front was crossed. A similar absence of horizontal stratification for microbial communities in the Black Sea was recently reported (Zhang et al., 2020). Meanwhile, significant differences were found in community compositions between depths (PERMANOVA, F=0.889, R2=0.376, p=0.001) and seasons (PERMANOVA, F=3.054, R2=0.098, p=0.002) . Vertically, microbial community compositions were significantly different except for SML-TL, MNZ-OMZ, MNZ-AZ, and OMZ-AZ. Additionally, community compositions of the seawaters and sediments were significantly different (p<0.0001). Limited studies have shown vertical stratification of microbial communities in the seawater column using the metabarcoding technique (Qian et al., 2011; Haro-Moreno et al., 2018; Xue et al., 2020). Seasonally, only winter samples were significantly different from spring samples when all the depth groups were considered whole for each station (p = 0.0201). Specifically, community composition in SML in summer was significantly different than in other seasons. Temperature appeared to be a leading cause of the difference between shallow depths. Community composition at remaining zones was insignificant seasonally (p>0.05). Sampling fast-changing unstable surface layer can be problematic. Besides fluctuations in environmental parameters, sampling at different sites and seasons may result in microbial community differences. The grouping of samples (based on Bray-Curtis dissimilarity) displayed on nMDS plots showed similarity in microbial community composition between the four sampling sites (stress: 0.1161) (Figure 4A). In contrast, dissimilarities were observed between seasons and depths (Figure 4B and C). There was a strong influence of sampling depth on microbial community composition, where samples from SML-TL, MNZ-OMZ, and AZ were separately clustered (Figure 4D). Clustering samples from SML and TL were expected since both depths were within the mixed layer. Samples from 75 and 100 m did not join the surface cluster. Moreover, these samples were more similar to the deeper than the surface samples. The grouping of microbial communities at the various season, depths, and zone in each sampling station are presented in Figure S11. Seasonally, microbial community composition in autumn was less tightly clustered within seasonal clustering.
SIMPER analysis revealed that the AZ was differentiated from the other zones by an increase in abundance of taxa belonging to the family Helicobacteraceae. In contrast, decreased abundance of Rhodobacteraceae, Prochloraceae, Verrucomicrobiaceae, and increased abundance of Planctomycetaceae and Nitrospinaceae in the MNZ and OMZ were the major contributor to the dissimilarity between the communities of SML-TL and MNZ-OMZ. The major contributor phyla and families to the dissimilarities between seasons, stations, depth, and zones are tabulated (Figure 4, Table S7-S10).
Among the most abundant phyla, Proteobacteria, Cyanobacteria, Bacteroidetes, and Verrucomicrobia were present in the whole water column. Conversely, Nitrospinae, Chloroflexi, and Kiritimatiellaeota were more restricted, appearing abundantly at 75 meters and deeper layers. While the abundance of Planctomycetes, Acidobacteria, and Firmicutes increased with depth, the abundance of Cyanobacteria, Bacteroidetes, and Balneolaeota decreased with depth. Ecologically distinct microbial taxa occupy different niches. Nevertheless, information about most of the bacterial taxa in the marine environment is limited. The Proteobacteria members’ adaptation (Planctomycetes, Bacteroidetes, Verrucomicrobia, and Acidobacteria group) to most water depths spanning the entire chemical gradient could indicate an adaptation to a wide range of chemical stressors and an efficient survival strategy. SML and TL were dominated by Cyanobacteria that perform photosynthesis and nitrogen fixation with light and oxygen. Cyanobacteria were found in all water column and sediment, but their abundance decreased in the deeper layers. A comparatively lower but still high abundance of Cyanobacteria in AZ might be due to the precipitation of dying bacteria from the water column into the sediment. The abundance of Nitrospinae, Chloroflexi, Kiritimatiellaeota, and Planctomycetes were high in MNZ and below, inconsistent with the previous report on the abundance of the Chloroflexi taxa below the chlorophyll maximum zone (Morris et al., 2002; Qian et al., 2011). Iron-reducer (Geoalkalibacter ferrihydriticus) and Iron-Manganese reducer (G. subterraneus) of the genus Geoalkalibacter (Greene et al., 2009) were found at 75 m and below, including sediment. Geobacter sulfurreducens was mostly found in the water column where H2S is present. Since G. sulfurreducens produce electricity(Poddar and Khurana, 2011), environmentally friendly microbial fuel cells can be produced (Bond and Lovley, 2003) to create electricity by the degradation of waste products using G. sulfurreducens (Poddar and Khurana, 2011).
Phylum Nitrospinae is represented with five species in the Black Sea. Nitrococcus mobilis was detected in high abundance in the aphotic and anoxic zones, whereas N. gracilis was only detected in the sediment. N. mobilis and N. gracilis are obligate chemoautotrophic nitrite-oxidizing bacterial species. Enrichment of N. mobilis indicates prevalent nitrite cycling in the aphotic and anoxic zones(Watson and Waterbury, 1971). Although the other three obligately anaerobic, thermophilic, sulfate-reducing bacterial species (Thermodesulfovibrio hydrogeniphilus, T. aggregans, and T. thiophilusare) were previously isolated from thermophilic environments (Haouari et al., 2008; Sekiguchi et al., 2008), their presence was detected in AZ with water temperature around 8°C.
Sulfate-, sulfur- and sulfite- reducing bacteria produce hydrogen sulfide by reducing different inorganic and organic materials. Sulfur-oxidizing and anoxic bacteria groups were enriched in AZ due to the high H2S and low O2 content in these deep waters in the Black Sea. Sulfate-reducing bacteria use sulfate as an electron acceptor during the breakdown of organic material to produce hydrogen sulfide (Rückert, 2016). Sulfate-reducing bacteria families (Helicobacteraceae, Granulosicoccaceae, Desulfobacteraceae, and Desulfobulbaceae) of the phylum Proteobacteria dominated the AZ. Enrichment of these groups is a clear indication of prevalent sulfur cycling. Shewanella hafniensis and Shewanella vesiculosa that produce H2S from thiosulfate were found in all water column and sediment. Metabolic activities of identified sulfide reducing bacteria taxa distributed abundantly in sediment and 100–200 meters might be the source of H2S in the Black Sea. The presence of strict anaerobic bacterial groups in high abundances, such as the Anaerolineaceae family of the phylum Chloroflexi in AZ, reflects the anoxic properties of these layers. Members of Fusobacteria, Gemmatimonadetes, and Lentisphaerae phyla were absent in the sediment. Distribution and presence of bacterial phyla in AZ were similar, except for Lentisphaerae, found only in waters, and Fibrobacteres found only in sediment.
Based on abundance, the most common five species found in each depth and sediment of the Black Sea were Prochlorococcus marinus, Gimesia maris, Kineobactrum sediminis, Azotobacter beijerinckii, and Planctopirus limnophila. Genus of Prochlorococcus has a single species called Prochlorococcus marinus, common in oligotrophic oceans (Partensky et al., 1999). P. marinus contains both chlorophyll-a and chlorophyll-b, which supports its growth in deeper waters with low light (Ralf and Repeta, 1992). Chlorophyll-b absorbs blue light and carries out photosynthesis even at 200 m depth as long as blue light penetrates (Zinser et al., 2007). This might be the main reason behind the distribution of photosynthetic cyanobacteria, P. marinus, abundantly in all of the Black Sea’s sampled depths or environmental DNA of the dead individuals might be another reason behind the presence of photosynthetic cyanobacteria in anoxic zone and aphotic zone. Although P. marinus adapt in low phosphate waters by replacing phospholipids membranes to sulfolipids membrane (Van Mooy et al., 2006), phosphate concentrations were not scarce, ranging between 0.02 µM in summer at surface water and 2.5 µM in fall in AZ.
Members of the Planctomycetes are known to colonize both oxic and anoxic layers (Dedysh and Ivanova, 2019). Planctomycetes are an important phylum for carbon and nitrogen cycles in the environment found in fresh, brackish, and marine water (Van Niftrik et al., 2004). Gimesia maris, previously known as Planctomyces maris, a species of the phylum Planctomycetes, was first isolated from the shallow waters at USA (Ferreira et al., 2016). Planctopirus limnophila is a member of the Planctomycetaceae family that do not contain peptidoglycan in their cell wall (Jeske et al., 2015). G. maris and P. limnophila were recorded in each sampling depth abundantly, yet the research on these species’ function is limited. Kineobactrum sediminis was first described and isolated from marine sediment (Chang et al., 2019). K. sediminis was found in each sampling depth and sediment in the Black Sea. The Genus of Azotobacter is mostly a soil bacterium that play a role in the nitrogen cycle by binding atmospheric nitrogen and converting it to ammonium. Azotobacter beijerinckii is found in soils and water associated plants (Tejera et al., 2005). It was the fourth most abundant bacterial species in the Black Sea. Although Azotobacter fixes atmospheric nitrogen in the soil, its function in the water column is unknown. All the five most abundant species were also found in the sediment of AZ. Since we used molecular techniques to identify microorganisms, both the live and debris of dead organisms could be identified. Thus, their actual presence in the sediment cannot be ascertained.
3.4. Influence of Environmental Parameters on Microbial Community Structure
When the entire water column was considered, the permutation test indicated that temperature, salinity, sigma-t, conductivity, light, chlorophyll-a, O2 NO3, NH3, PO4, Si, and H2S appeared to have a significant effect on the vertical bacterial community richness (p<0.05). In contrast, TOC and NO2 did not have any significant impact (p>0.05) on vertical bacterial community compositions following Bonferroni type correction (Table S11). Among the significant environmental factors, temperature (r2 = 0.605), PO4 (r2 = 0.634), and O2 (r2 = 0.33) were found to have the most influence on the overall bacterial community composition. Correlation between each environmental parameter with the microbial community composition at each zone is presented in Figure S12. Correlation between environmental parameters and vertical distribution of bacterial families are presented in Figure 5. Varied correlations were detected between environmental variables and the community structures of samples. Partial redundancy analysis (Figure S13) was performed to assess further the relationship between environmental variables, which revealed a similar set of environmental variables that statistically influenced the microbial community. Environmental parameters are represented by arrows that point toward the direction of variation.
Correlation between environmental parameters (Figure S13) and microbial communities appeared to be different in each zone. In SML and TL, the temperature was positively correlated with conductivity (Pearson’s test R2>0.95, p<0.001), and salinity negatively correlated with TOC. Mantel test indicated that temperature and conductivity were strongly related to microbial composition (Mantel’s R>0.5, p<0.01) (Figure 6A). In MNZ and OMZ, conductivity was positively correlated with salinity and dissolved oxygen (Pearson’s test R2>0.95, p<0.001). Conversely, oxygen was negatively correlated with conductivity and H2S. Salinity and H2S were positively correlated with conductivity. Mantel test indicated that NO2, NO3, PO4, and Si had an influence on community composition (Mantel’s R>0.25, p<0.01) (Figure 6B). In AZ, NO3 was negatively correlated with temperature, salinity, conductivity, and NH3, whereas conductivity was positively correlated with temperature and salinity (Pearson’s test R2>0.95, p<0.001). Mantel test indicated that PO4 was strongly related to microbial composition (Mantel’s R>0.5, p<0.01) (Figure 6C).
The Black Sea is an inland water body with permanent vertical stratification. In terms of water density, there are five well-defined strata in the Black Sea. In this study, seasonal fluctuations and heterogeneity of environmental parameters between the zones led to differences in the microbial community. Microbial diversity and density showed trends consistent with vertical stratification and environmental parameters for some of the taxa. High temperature, light, and dissolved oxygen in the upper zones facilitated the growth of photosynthetic bacteria in high density. However, lack of dissolved oxygen and light and high concentrations of hydrogen sulfide in the anoxic zone facilitated heterotrophic and anaerobic microorganisms in great abundance. OMZ and MNZ appeared to be the most diverse zones. Numerous studies addressed the environmental factors (Langenheder and Ragnarsson, 2007; Zheng et al., 2014) and deterministic partitioning of available resources (Zhang et al., 2009; Yan et al., 2017; Wu et al., 2019), shaping the microbial community compositions. Previous studies showed a strong impact of temperature, light, and dissolved oxygen on vertical stratification of microbial communities rather than geographic position and/or other environmental factors (Sunagawa et al., 2015). Nevertheless, environmental parameters did not appear as an apparent regularity for the entire community assemblages as previously reported (Niño-García et al., 2016).