Statistics of sequencing results and partition of bacterial metacommunities
The 69 samples including water, sediment, and biofilms were sequenced by PacBio and identified by Barcode. A total of 882, 211 circular consensus sequencing (CCS) sequences were obtained. Each sample was produced at least 10, 129 CCS sequences, with an average of 12, 786 CCS sequences. After rarefaction, the sequences were clustered into 1434 OTUs, among which 1350, 1285, and 1078 OTUs were identified from water, sediment, and biofilm, respectively. The bacterial metacommunities were partitioned at the OTU level with different rarity thresholds by Dirichlet multinomial mixture (DMM) methods (Fig. 1a). Four optimal clusters were finally obtained, indicating that the samples from three habitats (water, sediment, and biofilm) could be automatically classified into four different ecotypes of bacterial communities acclimated to the environment of the Ili River. Cluster I (Sediment) included 26 sediment samples and two water samples. Cluster II (Biofilm) included all biofilm samples and one sediment sample. Cluster III (Water I) was composed of most water samples from Kunes River and mainstream of Ili River, and one sediment sample. All water samples from Tekes River and Kashi river, and one sample from Kunes River constituted Cluster IV (Water II). Considering the consistency of sample habitat, the two water samples, one and one sediment sample from Cluster I, Cluster II and Cluster III were removed in the following study. The PCOA (Fig. 1b) and the differences in Bray-Curtis within groups (Fig. 1d) also confirmed the confidential clusters. These results also indicated that the water samples could be mainly divided into two clusters. The average population and gross domestic product (GDP) in the main region (Tekes river and Kashi river basin) of Water II were 21.34 people per km2 and 472, 500 RMB per km2, which were lower than those in the main region of Water I (48.00 people per km2 and 1, 025, 000 RMB per km2). Grassland and woodland were the dominant landscape in the main region of Water II. The main towns (Xinyuan County, Gongliu County, Yining City) in the Ili River Valley are located along the Kunes River and mainstream of Ili River (Water I). Therefore, bacterial communities in water are more sensitive to human activities, compared to sediment and biofilm under the same background of climate and geography.
Species diversity and abundance distribution at four optimal clusters
From the results of the Kruskal-Wallis test, there were no statistical differences in the Chao1 richness and Shannon index between the metacommunities from biofilm and Water I (Fig. 2a). Sediment had the highest Chao1 richness (601±116) and Shannon index (4.87±0.45), which were higher than those in Water II (471±115 and 4.11±0.31), biofilm (305±126 and 3.05±0.96), and Water I (341±135 and 2.92±0.82) (Fig. 2a and 2b). These results indicated that bacterial diversity and richness in water decreased as the intensity of human activities increased. However, there was no difference in Chao1 and Shannon index in bacterial communities between water and sediment according to the common conditional analysis based on habitat types (Fig. 2c and 2d). The significant difference within water samples was also ignored by habitat type.
At the phylum level, the most abundant and common taxa across all the four clusters were Proteobacteria (Fig. 1c). Fig. 3 showed the differences in relative abundance of the top 12 phyla in Water I, Water II, biofilm, and sediment samples. The average proportion of Proteobacteria in Water II (68.41%) and biofilm (65.83%), were significantly higher than those in sediment (50.97%) and Water I (38.80%). Firmicutes had the highest percentage in Water I (44.17%), followed by Water II (8.94%), sediment (5.93%), and biofilm (0.42%). Significant higher proportions of Bacteroidota, Acidobacteriota, Panctomycetota, Desulfobacterota, Germmatimonadota, and unclassified bacteria were found in sediment. Biofilm had the highest percentage of Cyanobacteria (18.38%), which were higher than those in Water I (5.52%), Water II (2.95%), and sediment (0.20%). Actinobacteriota was observed in Water II with a relative abundance of 9.3%, which was higher than those in Water I (2.97%), sediment (2.06%), and biofilm (0.26%). That is also to say, Proteobacteria and Actinobacteriota had significantly higher relative abundance in Tekes River and Kashi River with less human activities than those in Kunes River and mainstream of Ili River, while the relative abundance of Firmicutes was reversed. By habitat types, the neglect of significant differences within water samples led to different results in the relative abundance of bacterial communities. For example, no difference in the relative abundance of Proteobacteria between water and biofilm was found; and the significant difference in the relative abundance of Firmicutes within water samples was also ignored (Fig. S2). Therefore, these results further confirmed that ecotypes may be a better way to understand the characteristics of bacterial metacommunities than habitat types.
The function profile of bacterial communities across the four optimal ecotypes
Distinct function profile of bacterial communities predicated by FAPROTAX was found across different habitats or ecotypes in the Ili River (Fig. S3 and Fig.4). Chemoheterotrophy and aerobic chemoheterotrophy were the main functions. To further analyze the difference, the Turkey test was applied for function composition across the four different ecotypes (Fig. 4). The bacterial communities with functions of manganese oxidation, human pathogens nosocomia, human pathogens pneumonia, plastic degradation in the Water I had significantly higher relative abundance than those in Water II, sediment, and biofilm. Sediment had a significantly higher relative abundance in function of chemoheterotrophy and aerobic chemoheterotrophy than those in the Water I, Water II, and biofilm. Biofilm had a higher relative abundance of bacterial communities with phototrophy function than those of the other three ecotypes. Biofilm also had a higher relative abundance of photoautotrophy, cyanobacteria, and oxygenic photoautotrophy than those in Water II and sediment, but showed no significant difference compared with Water I. Compared with the habitat types (Fig. S3), the significant differences in function within the water samples were also neglected, such as the manganese oxidation, human pathogens nosocomia, human pathogens pneumonia, and plastic degradation.
Bacterial communities across different ecotypes fitted to NCM
The internal assembly mechanism of bacterial community across the four ecotypes was analyzed via NCM and shown in Fig. 5. Water (including Water I and Water II) and sediment showed higher goodness-of-fit to NCM (R2 > 0.5) than that of biofilm (R2 =0.154). The migration rates of the four ecotypes were shown in the following order: biofilm (0.0634) < sediment (0.1525) < water I (0.2514) < water II (0.3415). These results indicated that an immigrant from metacommunities was less likely to randomly colonize in the saturated local communities in sediment and biofilm compared to water in the Ili River. Meanwhile, the water I influenced by higher anthropogenic impacts also had a lower migration rate compared with water II with less human activities.
Environmental factors influencing the composition and function of bacterial communities
The relationship between environmental factors and community structure was important to understand the bacterial assembly process from the perspective of deterministic selection. Mantel’s test (Fig. 6) showed that three, two, two and three environmental factors could influence the bacterial community structure at the OTU level for sediment, water, Water I, and Water II, respectively. While no tested environmental factors showed influence on the taxonomic structure of the biofilm. For bacterial communities in sediment, TOC, TN, and AP (available phosphorus) were the main drivers shaping the biogeography of taxonomic structure. In Water I with higher intensity of human activities, salinity and mean annual precipitation (MAP) were the main drivers, while mean annual temperature (MAT), TOC, and ammonium nitrogen (ANM) were the environmental factors influencing the taxonomic structure in the Water II with less human activities. If water was considered as a habitat, it was found that MAT and salinity were the main drivers influencing the water bacterial communities in the Ili River.