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Article

Metagenomic Analysis of Bacterial Community Structure and Pollutant Removal Process in High-Altitude Municipal Wastewater Treatment Plants of Tibet, China

by
Rui Zhang
1,
Yiwen Liu
1,
Haibo Li
1,*,
Jian Xiong
2,
Qiangying Zhang
2,
Pengtao Li
1,
Lingjie Liu
1 and
Xuebin Lu
2
1
School of Environmental and Municipal Engineering, Tianjin Chengjian University, Tianjin 300384, China
2
School of Ecology and Environment, Tibet University, Lhasa 850000, China
*
Author to whom correspondence should be addressed.
Water 2025, 17(9), 1284; https://doi.org/10.3390/w17091284
Submission received: 14 March 2025 / Revised: 19 April 2025 / Accepted: 23 April 2025 / Published: 25 April 2025
(This article belongs to the Section Wastewater Treatment and Reuse)
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Versions Notes

Abstract

:
The bacterial communities of activated sludge are correlative with influent characteristics, geographical discrepancies, and environmental variables, which are essential for wastewater treatment plants (WWTPs). However, the comprehensive deciphering of bacterial community diversity in high-altitude WWTPs is scarce in Tibet, China. This study collected activated sludge samples from four A2O WWTPs (2980–3650 m above sea level) in Tibet. Illumina NovaSeq high-throughput sequencing revealed that Proteobacteria was the most abundant phylum (46.2–62.9%), followed by Bacteroidetes (14.8–21.8%) and Actinobacteria (3.5–10.9%). Candidatus Accumulibacter (7.2–15.1%) was the dominant denitrifying polyphosphate-accumulating organisms (DPAOs). Moreover, a principal coordinate analysis (PCA) revealed strong correlations between environmental factors and dominant phyla, while Candidatus Accumulibacter as a dominant genus was unaffected by environmental factors. Additionally, the reaction mechanisms were analyzed based on the functional gene abundance of carbon, nitrogen, and phosphorus metabolic pathways in high-altitude WWTPs. The carbon metabolism pathway, especially carbohydrate metabolism (14.52%), has more abundant functional genes in Nyingchi (LZ). Nitrogen metabolism mainly consists of assimilatory nitrate reduction, dissimilatory nitrate reduction, and denitrification; the high abundance of functional genes in phosphorus metabolism ensures efficient phosphorus removal. The obtained microbial information in the WWTPs could provide essential guidance for the sustainable management of wastewater treatment systems in high-altitude environments. Future research should focus on monitoring the seasonal dynamics of bacterial communities in high-altitude WWTPs and responses to environmental disturbances, to optimize treatment efficiency and ensure long-term sustainability.

1. Introduction

Wastewater treatment plants (WWTPs) in high-altitude regions worldwide commonly face adverse environmental conditions including low temperatures, low dissolved oxygen levels, and intense ultraviolet radiation [1]. These factors significantly constrain the efficiency of biological treatment processes and the operational stability of the systems. The Tibet Plateau, as a representative high-altitude region, presents even more severe natural environmental challenges, which further exacerbate the operational difficulties of wastewater treatment systems [2]. As the “Asian Water Tower”, the Tibet Plateau is significant in protecting the upstream region’s ecological environment because Tibet is a natural barrier to ecological security in China [3]. In recent decades, a large amount of domestic sewage has been generated in Tibet due to rapid economic development, and the municipal wastewater treatment rate in Tibet is inefficient because of the uneven population distribution and the harsh plateau environment. Wastewater treatment methods primarily encompass physical [4], chemical [5,6], and biological treatment processes [7]. Among these, biological treatment has gained widespread application due to its cost-effectiveness and environmental sustainability [8]. Therefore, the establishment and effective operation of WWTPs are crucial for water environmental problems and protecting the environment of the Tibet Plateau [9].
Municipal wastewater treatment mainly removes pollutants via activated sludge systems, which depend on the metabolism and interactions of the bacterial community to effectively remove pollutants [10]. Furthermore, municipal wastewater treatment plants mainly use the activated sludge biological system in Tibet, and the anaerobic–anoxic–oxic (A2O) process is widely applied to control water pollution and improve water quality due to its cost-effectiveness in nutrient removal process [11,12]. Therefore, a systematic study of the bacterial community in the A2O process may enhance the understanding of the microorganisms in Tibetan WWTPs, which are characterized by high altitude. Furthermore, the A2O process contains anaerobic, anoxic, and aerobic zones to remove organic matter, nitrogen, and phosphorus [13]. The bacterial community in the A2O process is significant for pollutant removal, and it is affected by various environmental variables [14]. For example, the influent quality, including pH, TN, TP and COD, can be the most significant factor affecting the bacterial community of WWTPs [15,16]. Meanwhile, geographical discrepancies, including altitude, temperature, and air pressure, are also important for the abundance of a functional community [17,18].
However, high-altitude WWTPs face operational challenges and poor treatment performance, and the main reasons are the extreme environment and geographical conditions (low temperatures, low dissolved oxygen, low air pressure, and large diurnal temperature differences) [19]. Meanwhile, the particular environmental conditions may be more conducive to the growth of specific bacteria at high-altitude WWTPs [20], but the relationships between impact factors (influent quality and geographical conditions) and bacterial community are scarce in Tibet. Moreover, high-altitude WWTPs also show different characteristics in municipal wastewater and bacterial community [19]. Nevertheless, the bacterial community of WWTPs in high-altitude regions of Tibet was mainly dependent on denaturing gradient gel electrophoresis (DGGE) [21] and 16S rRNA [22]. DGGE and 16S rRNA gene profiling only reveal the taxonomic composition of the bacterial community and lack information of functional annotation [17,23]. Comparatively, Whole Genome Shotgun (WGS) not only provides a stronger and more reliable assessment of bacterial diversity but also provides valuable information on functional annotation, including the metabolic potential of bacterial community [24,25,26]. In addition, metabolic potential analysis reveals complete knowledge in the field of microbial ecology [26]. Nevertheless, studies on the metabolic potential of activated sludge microorganisms at high-altitude WWTPs are very limited. Therefore, WGS was used to enhance the understanding of bacterial community and metabolism at high-altitude WWTPs.
The main goals of this research were to (1) explore the bacterial community diversity of the A2O process in four high-altitude WWTPs using Illumina NovaSeq and WGS; (2) reveal the effects of environmental variables on the bacterial community by principal coordinate analysis (PCA); and (3) analyze the functional bacterial metabolic pathways of pollutant degradation in WWTPs located at an average altitude of 3000 m in Tibet. Therefore, the molecular biological evidence was beneficial to dissect the relationship between the microbial abundance and the performance of WWTPs at the high-altitude conditions of Tibet.

2. Materials and Methods

2.1. Sample Collection of WWTPs

In this study, activated sludge samples were collected from four full-scale high-altitude WWTPs (2980–3650 m above sea level) in Tibet, located on the southwestern part of the Tibetan Plateau in China (see Supplemental Figure S1). All the four WWTPs used the conventional A2O process, a biological pollutant removal system that includes sequential anaerobic, anoxic, and aerobic zones, enabling the efficient removal of nitrogen and phosphorus. Relevant parameters and descriptions of these WWTPs are summarized in Table 1. Activated sludge samples were obtained from the anaerobic, anoxic, and aerobic functional zones, which were collected in triplicate from the anterior, middle, and posterior sections of each functional zone and combined into one sample. A total of 12 composite samples were preserved in 50 mL centrifuge tubes.

2.2. DNA Library Construction and Sequencing

Metagenomic sequencing was performed using the Illumina NovaSeq, and the WGS strategy was adopted. For library construction, the extracted DNA sample was processed according to the Paired-end Genomic DNA Sample Prep Kit protocol (Illumina, San Diego, CA, USA) for generating 2 × 150 bp paired-end reads. The quality of the raw data generated from the sequencing was assessed using FastQC, and the average quality and distribution of the raw data met expectations. To ensure reliable quality for subsequent analysis, the original sequencing data were screened and filtered after quality filtering. The SortMeRNA (http://bioinfo.univ-lille.fr/sortmerna/sortmerna.php (version 2.1, accessed on 29 August 2022)) software and rRNA reference libraries were used to remove residual rRNA from sequencing results. The resulting valid set of sequences (clean data set) was used for subsequent analyses. After BBCMS (https://sourceforge.net/projects/bbmap/ (version 39.96, accessed on 29 August 2022)) correction, the long read sequences were assembled using MEGAHIT (http://github.com/voutcn/megahit (version 39.96, accessed on 29 August 2022)). Default overlapping groups with a length of no less than 300 bp (contigs) were retained. The Linclust mode of the MMseqs2 software (https://github.com/soedinglab/MMseqs2 (version 13, accessed on 29 August 2022)) was used to remove the redundancy from the merged contig sequence set based on 95% similarity and 90% coverage of the alignment region (the proportion of short sequences), and the non-redundant set of contigs was obtained.

2.3. Bacterial Community Taxonomic

For overlapping clusters (contigs), MetaGeneMark software (http://exon.gatech.edu/GeneMark (version 3.38, accessed on 29 August 2022)), designed for predicting genes in metagenomic sequences, was used to identify the ORFs (open reading frames) and predict the coding regions. Followed by the cluster module of the MMseqs2 software (https://github.com/soedinglab/MMseqs2 (version 13, accessed on 29 August 2022)), the merged set of protein sequences was used to remove redundancy by achieving 95% similarity and 90% coverage of aligned regions (as a percentage of short sequences), resulting in a non-redundant set of protein sequences. Meanwhile, the non-target sequences were filtered to ensure the accuracy of subsequent species and functional analyses. The filtered protein sequence sets were subsequently compared with common protein databases to annotate and analyze the functional gene across all samples. The LCA (lowest common ancestor) algorithm in Blast2lca software (https://github.com/emepyc/Blast2lca (version 0.8, accessed on 29 August 2022)) was used to obtain the annotation information for contig sequences at each taxonomic level, resulting in the Species Information Table for contig sequences.

2.4. Metabolic Pathway Analysis

Based on the obtained KO (Kyoto Encyclopedia of Genes and Genomes orthologous groups, KEGG orthologous groups) results and the integration of the gene abundance matrix, the KO abundance corresponding to the protein was identified, and the number of KEGG metabolic pathways was calculated by MinPath (https://omics.informatics.indiana.edu/MinPath/ (version 0.8, accessed on 29 August 2022)). Based on annotation results of proteins and their abundance spectra, KEGG metabolic pathways at different taxonomic levels can be obtained. Subsequently, KEGG metabolic pathways were divided into four levels, which were the biological metabolic pathways (first level), the sub-functions of metabolic pathways (second level), the relationship to metabolic pathway maps (third level), and the specific annotation information for each KO (fourth level). Finally, KEGG metabolic pathways of the bacterial community were obtained in the four WWTPs. The corresponding bacterial metabolic activities related to nitrogen and phosphorus removal were studied by identifying the functional pathways and genes.

2.5. Data Processing and Statistical Analysis

The bacterial community in four high-altitude WWTPs was evaluated using principal coordinate analysis (PCA) with Canoco software (version 5.0). The correlations between functional bacterial community (at the phylum and genus levels) and environmental parameters (type of functional zone, COD, TN, TP, NH4+-N, and pH) were assessed among the four high-altitude WWTPs. Correlations between environmental parameters and bacterial community can be intuitively observed through the visualization of analysis results, facilitating a more detailed examination of the roles that these variables play in shaping the structure of the bacterial community. In order to further investigate potential key interactions of bacterial communities in high-altitude WWTPs, bacterial co-occurrence networks were constructed for the top 10 most abundant genera by R software (version 4.4.2). Spearman correlation analysis (Spearman p-value ≤ 0.05) was conducted with the Benjamini–Hochberg p-value adjustment procedure using the Psych R package (version 2.4.6.26) in the top 10 genera. Network analysis was performed by the Igraph R package (version 2.1.1), and the co-occurrence network analysis was visualized using the interactive interface of Gephi (version 0.10).

3. Results and Discussion

3.1. Differences in Physicochemical Factors

Influent and effluent characteristics of four high-altitude WWTPs are summarized in Table 1, and the WWTPs at higher altitudes generally had higher COD concentrations. LZ in the lowest altitude possessed the lowest influent pollutant concentrations, which resulted in its inefficient pollutant removal. Meanwhile, the influent concentrations of NH4+-N and TN were highest in CD, which achieved the highest removal efficiency for NH4+-N (99.97%) and TN (91.91%) in the four WWTPs. The TP influent concentration was highest in LW with the highest altitude, which achieved the highest TP removal (96.14%) among the four WWTPs. Moreover, TP removal performance was better than that of TN in all four high-altitude WWTPs. Additionally, the effluent quality from all four WWTPs met the Class I standard according to the Chinese Discharge Standard of Pollutants for Municipal Wastewater Treatment Plants (GB 18918-2002) [27].

3.2. Bacterial Community Diversity

The bacterial diversity of activated sludge was relevant for the removal performance and stability of WWTPs, therefore the bacterial community diversity was analyzed by alpha-diversity and beta-diversity. The Coverage index ranged from 99.42% to 99.60%, indicating that the sequencing depth was sufficient to represent the community structure in the real environment of high-altitude WWTPs. Alpha-diversity was assessed by Chao 1, abundance-based coverage estimation (ACE), and Shannon and Simpson indices as shown in Figure 1. Among these, Chao 1 and ACE indices were used to estimate the number of OTUs in a community, and higher bacterial richness was indicated by higher values. The Chao 1 and ACE results showed that the number of OTUs generally decreases with increasing altitude, suggesting that bacterial communities were shaped by a high-altitude environment, resulting in functional bacteria that played dominant roles in high-altitude WWTPs. Meanwhile, Shannon and Simpson indices were used to assess bacterial diversity, where higher community diversity was indicated by higher Shannon values and lower Simpson values. Shannon and Simpson results showed that LW (3650 m) with the highest influent COD (340.19 mg/L) among the four WWTPs possessed the highest bacterial diversity, and LZ (2980 m), with the lowest influent COD (45.8 mg/L) concentration, had the lowest bacterial diversity. Consequently, the microorganisms that could degrade complex organics might survive better in plateau WWTPs [17]. The reduction in richness and the increase in diversity suggested that the number of species in the bacterial community decreased in high-altitude WWTPs, but the relative abundance distribution of species became more even. Therefore, the unique environmental conditions and influent characteristics at high-altitude WWTPs led to an even distribution of dominant species, which contributes to the enhanced stability of wastewater treatment systems in high-altitude WWTPs.
Based on the Unifrac metric, Principal Component Analysis (PCA) can be used to evaluate the beta-diversity of the bacterial community in WWTPs. As shown in Figure 2a, the bacterial community was discrete across different WWTPs, whereas samples from the same WWTP were clustered together. This suggests that the beta-diversity was more influenced by sludge systems rather than by functional zones in high-altitude WWTPs. Additionally, the Venn diagram visually presented the species composition of each sample, and a higher proportion of shared species indicated greater similarity between the samples. As shown in Figure 2b, the number of unique species in the three functional zones was 3.27–3.63% in LZ (2980 m), 3.35–3.81% in CD (3240 m), 2.72–2.86% in LS (3564 m), and 2.24–2.32% in LW (3650 m), respectively. The results suggested that the number of unique species decreased as the altitude increased, because the extreme environments in high-altitude WWTPs prevent some species from surviving.

3.3. Bacterial Community at the Phylum and Genus Levels

3.3.1. The Phylum Level

Based on the classification information from the SILVA database, the high-throughput sequencing results from anaerobic, anoxic, and aerobic zones of the A2O process in four high-altitude WWTPs were classified at the phylum and genus levels. As illustrated in Figure 3, the major bacterial phyla (with abundance > 1% at least in one functional zone) were numbered 13, 7, 11, and 9 in the four WWTPs, representing 96.8–97.0%, 95.0–95.4%, 96.3–96.6%, and 96.6–97.0% of the total effective sequences. Among them, the abundance of Proteobacteria and Bacteroidetes accounted for 63.3–84.3%, and they were the most dominant bacterial community in the A2O system, which was consistent with those previous studies [17]. Proteobacteria, the most diverse bacterial phylum with significant genetic variation, was prevalent in WWTPs [28]. Proteobacteria played a critical role in the metabolism of acetic acid, butyric acid, glucose, and propionate [29]. Moreover, Proteobacteria facilitated nitrogen removal, and the highest abundance in CD resulted in the highest nitrogen removal efficiency. Meanwhile, Bacteroidetes possessed the capacity to degrade complex organics such as proteins, lipids, and other macromolecules [30]. Bacteroidetes had the highest abundance (17.7–21.8%) in LW, which contributed to the degradation of complex organic matter.
Furthermore, Actinobacteria, Chloroflexi, Firmicutes, Verrucomicrobia, and Acidobacteria with a proportion over 1% accounted for 12.4–14.6%, 11.5–14.3%, 19.2–22.0%, and 19.0–22.4% in LZ, CD, LS and LW. These phyla were the subdominant functional bacteria in the typical plateau environment. Among them, Firmicutes with an abundance of 1.2–2.3% can degrade complex polysaccharides, contributing to COD removal in the four WWTPs [31]. Verrucomicrobia was commonly found in the aquatic environment and human feces, which was regarded as indigenous bacteria in the wastewater environment that rarely participate in wastewater treatment processes [32]. Moreover, Acidobacteria can be involved in the degradation of plant residues and single-carbon compounds [33]. Additionally, Nitrospirae was a typical phylum with the ability to convert ammonia into nitrate or nitrite, which was beneficial to the nitrification process in WWTPs [34]. Furthermore, the abundance of Nitrospirae exceeded 1% only in LZ (2.0–2.6%) and LS (4.0–5.0%), implying that nitrification capacity was higher in the WWTPs of LZ and LS. In summary, the abundance of dominant bacterial phyla enhanced pollutant removal in the four high-altitude WWTPs. The composition of these dominant phyla in high-altitude regions showed a high degree of concordance with that observed in low-altitude A2O WWTPs. Notably, Proteobacteria, Bacteroidetes, Firmicutes, Actinobacteria, Chloroflexi, and Acidobacteria have also been reported to possess strong pollutant degradation capabilities in low-altitude systems [35]. This suggests that, despite environmental differences associated with altitude, there exists a consistent core of functional bacterial groups that play key roles in the wastewater treatment process across diverse geographical settings.

3.3.2. The Genus Level

To further understand the functional bacterial community in the four high-altitude WWTPs, bacterial samples were analyzed at the genus level. As illustrated in Figure 4, the identified bacterial genera in LZ, CD, LS, and LW were 287, 313, 336, and 333, respectively. The major bacterial genera (abundance > 1% at least in one functional zone) were 11, 19, 17, and 15 in LZ, CD, LS, and LW, which accounted for 37.2–40.5%, 33.6–34.8%, 30.7–37.6%, and 29.0–29.3% of the total effective sequences. Among them, the abundance of Candidatus Accumulibacter was 7.2–15.1% at the four WWTPs, and the genus as predominant can utilize volatile fatty acids (VFAs) as a preferred carbon source and converts polyhydroxyalkanoic acids (PHAs) during the phosphorus removal process [36]. Moreover, Candidatus Accumulibacter as phosphate-accumulating organisms (PAOs) had respiratory nitrate reductase, which supported denitrifying phosphorus removal in the activated sludge system [37]. Therefore, the high abundance of Candidatus Accumulibacter was conducive to efficient phosphorus removal in the four WWTPs. Meanwhile, Dechloromonas, Propionivibrio, Nitrospira, Rhodoferax, Flavobacterium, and Pseudomonas as subdominant functional genera accounted for 6.90–20.70% in LZ, CD, LS, and LW. Among them, the abundance of Propionivibrio was 4.5–6.2%, 1.3–1.5%, 0.9–0.9%, and 1.9–2.3% in the four WWTPs, and Propionivibrio as the dominant glycogen-accumulating organisms (GAOs) was significantly lower than the abundance of Candidatus Accumulibacter (dominant PAOs). The results suggested that PAOs possessed a competitive advantage over GAOs in the long-term operation environment of low-temperature and high-altitude. Meanwhile, Rhodoferax as denitrifying phosphorus-removing bacteria accounted for 1.0–2.6% of the total effective sequences. Rhodoferax was more enriched in CD, which facilitated total nitrogen and phosphorus removal. Moreover, the abundance of Pseudomonas ranged from 0.90% to 2.50% in LZ, CD, LS and LW. Pseudomonas played an essential role in the degradation of organic matter and nitrogen in WWTPs, which was associated with the biological denitrification process [38]. Additionally, Nitrospira with a higher abundance (8.3%) in LS was the main nitrite-oxidizing bacteria and also had the capacity for complete ammonia oxidation (comammox) [34]; thus, its high abundance contributed to ammonium removal via nitrification in LS. Furthermore, Dechloromonas was more competitive for utilizing small organic molecules including sodium acetate and glucose, and its abundance was 4.8–6.8% in LZ compared to less than 0.1% in LW. Presumably, the influent in LZ included more small-molecule carbon sources, which promoted the enrichment of Dechloromonas. Moreover, Flavobacterium was denitrifying bacteria and can reduce nitrate at temperatures below 15 °C [39], which accounted for 1.10–2.60% in the four high-altitude WWTPs. Consequently, the low-temperature environment (14.90–16.55 °C) promoted the enrichment of Flavobacterium at high-altitude WWTPs, which enhanced denitrification for nitrogen removal in the four WWTPs.
In addition, the abundance of Candidatus Microthrix increased in LW with higher altitude and lower temperature, and the genus can cause sludge bulking because of its competitiveness for carbon sources and dissolved oxygen at low temperatures (10–15 °C). The highest abundance of Candidatus Microthrix was observed in LW, which may be at risk for sludge bulking. On the other hand, Geobacter and Candidatus contendobacter were only the dominant genus in LZ (abundance above 1%), which played key roles in organic matter degradation and denitrification processes, respectively [40]. The genus Nannocystis, enriched in CD (abundance above 1%), has the ability to degrade organic matter [41]. The abundance of Tetrasphaera, Mesorhizobium and Sulfuritalea, which were found in abundance (>1%) exclusively in LS, contributing to phosphorus removal, nitrogen fixation, and organic matter degradation, respectively [29,42,43]. Meanwhile, Ottowia, Novosphingobium, and Limnohabitans were unique bacterial genera in LW, involved in organic matter degradation, denitrification, and phosphorus removal [44,45,46].
In summary, phosphorus-removing bacteria were more abundant than nitrogen-removing bacteria within the dominant genera in the four high-altitude WWTPs. Traditionally, nitrogen removal was more efficient than phosphorus removal in low-altitude WWTPs because denitrifying bacteria had a competitive advantage in utilizing carbon sources compared to PAOs [46]. In the low-altitude WWTPs (see Supplemental Table S1), the dominant genera were primarily associated with nitrification, denitrification, and organic matter degradation, including Thauera (denitrification), Ferruginibacter (organic matter degradation and denitrification), Nitrospira (nitrification), Caldilinea (organic matter degradation), Planococcus (organic matter degradation), and Terrimicrobium (organic matter degradation) [44,47,48]. In comparison, the four high-altitude WWTPs showed that Candidatus Accumulibacter (denitrifying polyphosphate accumulating organism, DPAO) and Dechloromonas (organic matter degradation and denitrifying phosphorus removal) were dominant, indicating that high-altitude environments may promote the enrichment of denitrifying polyphosphate-accumulating organisms (DPAOs) and thus facilitate simultaneous nitrogen and phosphorus removal. This alteration in bacterial community may be attributed to ecological factors characteristic of high-altitude environments, such as reduced temperatures, which can significantly influence bacterial competition dynamics and functional specialization. Moreover, the nitrification reaction became difficult to achieve when the temperature of the wastewater biochemical treatment system was lower than 15 °C, resulting in the nitrogen removal capacity becoming significantly reduced in the four high-altitude WWTPs. In contrast, phosphorus removal efficiency was higher than that of nitrogen removal in high-altitude WWTPs because of the high-altitude tolerance exhibited of PAOs [46]. Therefore, phosphorus removal was better than nitrogen at high-altitude WWTPs, and environmental factors led to a shift in the priority of nitrogen versus phosphorus removal between low and high-altitude WWTPs.

3.4. Correlations Between the Bacterial Community and Environmental Variables

The correlations between the bacterial community and environmental variables were assessed by PCA at altitudes of 2980–3650 m as shown in Figure 5. The results of the PCA showed that 9 dominant phyla and 21 dominant genera were positively correlated with influent pollutant concentrations and altitude, indicating that higher pollutant concentrations and altitudes increased the complexity of bacterial community in WWTPs. Among them, LW possessed the highest altitude and influent pollutant concentrations among the four WWTPs.

3.4.1. Correlation Analysis at Phylum Level

At the phylum level (Figure 5a), the separation of the sludge samples in four WWTPs suggested that the bacterial distribution depended on wastewater treatment systems rather than the anaerobic, anoxic, and aerobic environments. Acute angles emerged among COD, NH4+-N, temperature, TP, and TN, indicating that these variables significantly impacted the bacterial community. Meanwhile, the vector length order of environmental factors was COD > NH4+-N > TP > TN > pH, suggesting that COD and NH4+-N were primary influencing factors for the bacterial community. Meanwhile, Bacteroidetes, Verrucomicrobia, Actinobacteria, Chloroflexi, Planctomycetes, Firmicutes and Proteobacteria exhibited high abundance in the four WWTPs and were strongly correlated with influent pollutant concentrations.
Among them, Bacteroidetes with the highest abundance of 17.7–21.8% in LW was significantly correlated with the concentrations of NH4+-N and TP. Furthermore, filamentous bacteria played an important role in composing the skeleton structure of activated sludge [49]. However, high altitudes with low temperatures and low dissolved oxygen could increase the competitive advantage of filamentous bacteria in the uptake of organic matter. Therefore, Actinobacteria, a typical filamentous bacterium, was enriched in LW, which raised the risk of sludge bulking at this WWTP. Meanwhile, Chloroflexi with the highest abundance of 5.2–5.7% in LS was significantly correlated with COD, serving as a structural component of sludge flocs that were beneficial for the formation of granular sludge and the decomposition of refractory organics [49]; thus, a high COD concentration can promote the growth of Chloroflexi in LS. Moreover, Firmicutes, involved in anaerobic hydrolysis and the acidification process, was also positively correlated with TN concentration and was essential for nitrogen removal in CD. Furthermore, Proteobacteria was more relevant to CD and LZ, because it can participate in the removal of organic matter, nitrogen, and phosphorus in the wastewater treatment process [28]. Proteobacteria, as the most widespread and ubiquitous bacteria in WWTPs, can adapt to high altitudes. Additionally, Euryarchaeota, the dominant phylum in LZ, was negatively correlated with influent pollutant concentrations. Euryarchaeota included species with diverse physiological characteristics that can adapt to various ecological environments; thus, they were hardly affected by pollutant concentrations. In summary, the top three dominant bacterial phyla (Proteobacteria, Bacteroidetes, Actinobacteria) showed the strongest correlation with the influent pollutant concentrations of the WWTPs. At the phylum level, influent quality was the greatest influence factor to the bacterial community in the four WWTPs [14].

3.4.2. Correlation Analysis at Genus Level

At the genus level (Figure 5b), the bacterial community of the four WWTPs was also dispersed separately, indicating that wastewater systems, rather than functional zones in WWTPs, can importantly affect the bacterial community. Among them, CD and LS possessed high TN removal efficiency, indicating that the genera of CD and LS were most similar. Moreover, LW was most positively correlated with TP resulting in the highest TP removal performance, while LZ was negatively correlated with the influent pollutant concentrations because of the lowest pollutant concentration in LZ influent. Meanwhile, Geobacter, Pseudomonas, Mesorhizobium, and Novosphingobium were the most dominant genera in LZ, CD, LS, and LW, respectively. Among them, Geobacter had the ability to dissimilatory nitrate reduction to ammonium (DNRA), and DNRA can coordinate with denitrification to enhance nitrogen removal efficiency in LZ [30]. Meanwhile, Pseudomonas was also related to denitrification and denitrifying phosphorus removal [38]; thus, Pseudomonas was significantly correlated with TN concentration and achieved effective nitrogen removal (91.91%) in CD. Furthermore, Mesorhizobium was regarded as both a nitrogen-fixing bacterium and a denitrifier [42] and was positively correlated with excellent nitrogen removal (88.21%) in LS. Novosphingobium contributed to removing organics, nitrogen, and phosphorus (Wang et al., 2022) [44]; thus, Novosphingobium was positively correlated with TP and COD removal in LW.
On the other hand, Candidatus Accumulibacter, Dechloromonas, Propionivibrio, Nitrospira, Rhodoferax, and Flavobacterium as dominant genera in the four WWTPs were hardly correlated with the influent pollutant concentrations. Among them, Candidatus Accumulibacter (PAO) was the dominant genus in the four high-altitude WWTPs, which was resistant to low temperatures [36]. Meanwhile, Dechloromonas (PAO) can assimilate VFAs using nitrite as the electron acceptor under anoxic conditions, which played an important role in the denitrifying the phosphorus removal process of LZ [46]. Furthermore, Rhodoferax as a PAO was significantly correlated with TP concentration and enriched in LW, thereby resulting in the efficient TP removal in LW. Propionivibrio (GAO) can accumulate glycogen and polyhydroxyalkanoates inside cells but cannot effectively accumulate phosphorus [15]. Propionivibrio had the highest abundance (6.2%) in the anaerobic zone of LZ, which led to the lowest TP removal efficiency in LZ due to competition for organics between GAOs and PAOs. However, the TP effluent concentration in the WWTP ranged from 0.17 to 0.27 mg/L with efficient TP removal performance, because PAOs were the most abundant functional bacteria in the four WWTPs. Additionally, Nitrospira (NOB) was positively correlated with LZ and LS, because the low ammonium concentration in influent helped to prevent inhibition of the nitrification process and enrichment of Nitrospira in LZ and LS. Furthermore, Nitrospira can consume nitrite better than other anaerobic microorganisms at a low nitrogen concentration and compete with denitrifying bacteria [50]. Thus, Nitrospira, considered unfavorable for nitrogen removal processes in biological systems [50], may be responsible for the low nitrogen removal efficiency in LZ. In addition, Flavobacterium can degrade complex organics in the denitrification process, resulting in the highest nitrogen removal efficiency in CD [51]. Consequently, Flavobacterium was significantly correlated with TN concentration and enriched in CD. Furthermore, influent quality with a combination of TP, NH4+-N, COD, altitude, TN, and pH had a significant impact on the growth and distribution of bacteria community relating to nitrogen and phosphorus removal at high altitudes, and this finding was consistent with the observations made by Niu et al. [52]. In summary, the bacterial communities are shaped by the characteristics of the influent, particularly the COD concentration. Functional bacteria, such as Pseudomonas and Flavobacterium, play a key role in TN removal, while Candidatus Accumulibacter and Dechloromonas (PAOs) contribute to the optimization of phosphorus removal. Adjusting the C/N and supplementing external carbon sources, such as starch and food processing wastewater, can enhance nutrient removal efficiency, optimize bacterial community composition, and improve the stability of the sludge system.

3.4.3. Analysis of Bacterial Network Diagrams at Genus Level

Furthermore, the top 10 bacterial genera were analyzed using co-occurrence network analysis. As shown in Figure 5c, positive correlations were more prevalent than negative correlations, indicating that core bacteria tend to co-occur rather than co-exclude each other. Among them, Nitrospira, Acidovorax, Polaromonas and Propionivibrio were the key genera, followed by Acinetobacter, Rhodoferax, and Dechloromonas. The results showed that the key genera were involved in the organic matter removal process, except for the nitrifying bacterium Nitrospira, which primarily exhibited co-exclusion with other genera. This was because the nitrification activity of Nitrospira was inhibited by high concentrations of organic matter, which affected its interactions with other genera [53]. Moreover, Acinetobacter, Polaromonas, and Acidovorax, as environmentally adaptable microorganisms, can maintain activity in extreme environments [54,55,56]. Thereinto, Polaromonas had a unique low-temperature adaptation mechanism [54], while Acinetobacter and Acidovorax were capable of maintaining degradation activity under low temperature and high pollution load [55,56]. The three genera exhibited more positive correlations with other genera, suggesting that most of the bacterial relationships were symbiotic and synergistic. In addition, the prevalence of positive correlations also suggested that bacterial communities possessed adaptive capacity for environmental changes, thereby maintaining system stability.

3.5. Functional Metabolism Pathway Analysis

Metabolic functional genes were obtained using Metagenomic sequencing technology, and metabolic pathways such as carbon, nitrogen, and phosphorus can be revealed by the KEGG database in high-altitude WWTPs. The KEGG metabolism pathways (Figure 6a) showed that carbohydrate metabolism (14.52%, 13.61%, 14.30%, and 14.19%) was the most abundant sub-pathway system among the four WWTPs, followed by amino acid metabolism (11.11%, 11.34%, 11.57%, and 11.58%) and energy metabolism (7.05%, 6.71%, 6.94%, and 6.95%). These three main pathways (carbohydrate metabolism, amino acid metabolism, and energy metabolism) were related to microorganism growth and metabolism, and they can provide energy and carbon sources for microbial activities [57].

3.5.1. Carbon Metabolism

Carbon metabolism was the most fundamental and played a major role in the degradation of organic pollutants [58]. Carbohydrate metabolism mainly focused on glycolysis/gluconeogenesis, tricarboxylic acid cycle (TCA cycle), pentose phosphate, and other related pathways. Firstly, glycolysis catalyzed the degradation of glucose into pyruvate through various genes (Figure 6b), producing electron donors (NADH) and energy (ATP) under anaerobic conditions [59]. One of the key genes in glycolysis was 6-phosphofructokinase (PFK), which acted in the first step of the glycolytic pathway, converting fructose-6-phosphate into fructose-1, 6-diphosphate. Therefore, this reaction prevented the synthesis of sucrose and starch from fructose-6-phosphate and acted as a regulatory step in the entire glycolysis process. Meanwhile, 6-phosphofructokinase (PFK), the key gene in the glycolysis process, was detected at high abundance in LZ, LS, and LW. The following two key genes were phosphoglucomutase (PGM) and pyruvate kinase (PK), which were detected at high abundance in LZ and LW. The results suggested that the microorganisms may have a greater potential for degrading glucose and sodium acetate in LZ and LW. However, the relative abundance of the three key genes PFK, PGM, and PK was low in CD, implying that carbon metabolism in CD was independent of glycolysis due to the variant influent characteristics of WWTPs. Through the glycolytic pathway, functional microorganisms gradually converted glucose into pyruvate via a series of biochemical reactions, which then entered the TCA as acetyl-CoA [60].
Secondly, the TCA cycle further converted acetyl-CoA into NADH and CO2, and NADH can enhance the synthesis of polyhydroxyalkanoates (PHAs) and support glycolysis [61]. As shown in Figure 6b, citrate synthase (CS) catalyzed the reaction between acetyl-CoA and oxaloacetate to produce citric acid, which regulated entry into the TCA cycle and was the main rate-limiting step of the TCA cycle [62]. Meanwhile, citrate synthase (CS) was detected at low levels in CD samples due to the low concentration of carbohydrate substrates in CD influent, which may negatively affect the enzyme activities involved in carbon metabolism. Additionally, isocitrate dehydrogenase (IDH) and malate dehydrogenase (MDH) were two critical genes for NADH production in the TCA cycle [63]. Moreover, isocitrate dehydrogenase (IDH) was detected at high abundance in the four WWTPs, while a high abundance of malate dehydrogenase (MDH) was detected in LZ, LS, and LW. However, isocitrate dehydrogenase (IDH) with high abundance in CD can also catalyze isocitrate to complete the TCA cycle, serving as a substitute for malate dehydrogenase (MDH). This further confirmed that carbon metabolism in CD was dominated by the TCA cycle, and the presence of key genes CS, IDH, and MDH were beneficial for COD removal.
Finally, the pentose phosphate pathway was the basic energy metabolism in central carbon metabolism, which generated NADPH during glucose metabolism [64]. As shown in Figure 6b, one of the key genes in the pentose phosphate pathway was PGD, which catalyzed glucose-6-phosphate to 6-phosphogluconolactone accompanying NADPH generation [65]. PGD had the least relative abundance in LZ, while the pentose phosphate pathway was the lowest abundance of carbohydrate metabolism in the four WWTPs. In summary, glycolysis/gluconeogenesis, the TCA cycle, and pentose phosphate pathways were relatively more abundant in LZ, which facilitated the degradation of organic pollutants. As shown in Figure 6b, the TCA cycle was the pathway with the highest relative abundance of carbon metabolism among the four WWTPs, indicating that sufficient electron donors were available for denitrification.

3.5.2. Nitrogen Metabolism

The core nitrogen metabolism (ko 00910) involved four reduction pathways and two oxidation pathways. Nitrogen fixation transformed atmospheric molecular nitrogen into ammonium, which was essential for the formation of amino acids and other vital compounds. The reduction pathways also included assimilatory nitrate reduction and dissimilatory nitrate reduction, both of which converted nitrate to ammonium. Meanwhile, denitrification was another reduction pathway in which nitrate or nitrite served as the terminal electron acceptor, producing gaseous nitrogen compounds (N2, NO, and N2O) under low-oxygen or anoxic conditions.
In the nitrogen fixation pathway, N2 was converted into NH3 by the NifDKH genes (Figure 6b), and there was high abundance in LZ. Meanwhile, in the first step of the denitrification pathway, nitrate was converted into nitrite under anoxic conditions by the NarGHI genes, or under aerobic conditions by the NapAB genes [66]. Moreover, the conversion of nitrate to nitrite, catalyzed by nitrate reductase, was an essential step in the denitrification pathway and promoted nitrogen removal [51]. The second step of denitrification was the conversion of nitrite to nitric oxide via the NirK and NirS genes. Subsequently, the reduction of NO to N2O and N2 was catalyzed by NorBC and NosZ, respectively. The results showed that the low abundance of NorBC and the high abundance of NosZ reduced the accumulation of the intermediate product N2O, promoting complete denitrification in LS [67]. Additionally, the enrichment functional genes of denitrification enhanced denitrification performance and improved the utilization capacity of refractory organics in the four WWTPs [67]. On the other hand, NasA was the key gene for the assimilatory nitrate reduction to the ammonium (ANRA) pathway [68], and the anabolic nitrate reductase encoded by the NasA gene catalyzed the reduction of NO3− to NH4+ [69]. The highest abundance of genes associated with the ANRA pathway contributed to the most efficient nitrogen removal in CD. In the DNRA pathway, nitrate was converted to nitrite by the NarGHI and NapAB genes, respectively. And, then, nitrite can be reduced to ammonium by the NirBD and NrfAH genes [66]. The DNRA typically occurred in anaerobic environments and possessed an intact metabolic pathway in four high-altitude WWTPs. Furthermore, the abundance of NirBD was the highest in CD, indicating that the DNRA metabolism pathway had excellent nitrogen removal. In summary, the DNRA metabolic pathway achieved more economical removal of nitrogen than the denitrification pathway [70].
In addition, the two oxidation pathways were nitrification and anaerobic ammonium oxidation (anammox). In the conventional nitrification pathway, ammonia monooxygenase (Amo) was the key gene for oxidizing ammonia to hydroxylamine. Meanwhile, hydroxylamine oxidoreductase (Hao) and nitrite oxidoreductase (Nxr) were key genes that oxidize hydroxylamine and nitrite, respectively [66]. Nevertheless, the abundance of nitrification-related genes, such as AmoABC and Hao, was low in CD, LS, and LW, but LZ had a high abundance of the nitrification pathway functional genes. This suggested that the nitrification process was limited due to the high ammonium concentration in influent, which was unfavorable for nitrogen removal [50]. Moreover, nitrification was inhibited by the higher COD concentrations in CD, LS, and LW [71]. Additionally, nitrification can also be hampered by low temperatures (14.9–16.55 °C), low dissolved oxygen, and low air pressure at high altitudes, because the harsh environment reduced bacterial activity and affected the internal pressure of the cells. Meanwhile, the absence of the functional genes (Hzs and Hdh) of anaerobic ammonium oxidation (anammox) was observed in all samples due to the low substrate concentration of ammonium and nitrite in WWTPs. Furthermore, wastewater treatment systems on the Tibetan Plateau exhibited an imbalance between ammonification and deamidation capacities in degrading nitrogenous pollutants, indicating that the anammox process ineffectively contributed to TN removal. In conclusion, the four high-altitude WWTPs mainly relied on assimilatory nitrate reduction, dissimilatory nitrate reduction, and denitrification to achieve TN effective removal. Additionally, LZ had the highest abundance of nitrogen fixation and nitrification metabolic pathways. Moreover, the dominant nitrogen metabolism pathway was more affluent in LZ than in CD, LS, and LW, indicating that the nitrogen metabolism pathways were more comprehensive in LZ.

3.5.3. Phosphorus Metabolism

The phosphorus metabolism pathway was primarily interrelated to polyphosphorus (poly-P) accumulation and phosphorus release by microorganisms such as PAOs [72]. The functional genes of phosphorus metabolism (PPK, PPX, PPA, PHO, PstS, and ADK) were detected in the four WWTPs (Figure 6b), and these functional genes served as the basis for efficient TP removal. Under anaerobic conditions, PAOs converted polyphosphorus into phosphate by the polyphosphatase (PPX) gene [72]. Subsequently, phosphate was excreted from the cells with the synthesis of PHA. In aerobic conditions, PAOs converted phosphate to polyphosphorus by consuming ATP and NAD(P)H, in which the polyphosphate kinase (PPK) gene was important for the process of taking in phosphate. Thereafter, the polyphosphate was stored in PAOs for glycogen synthesis that was associated with the PPA (inorganic pyrophosphatase) gene. The high abundance of PPK and PPA genes contributed to stable and efficient TP removal in LZ, CD, LS, and LW. However, the relative abundance of nitrogen-removing bacteria and functional genes was significantly lower than that of phosphorus-removing bacteria and functional genes in high-altitude WWTPs, which led to the TP removal performance that was higher than TN. This was because phosphorus-removing bacteria demonstrate a greater tolerance to low temperatures and low pressure than nitrogen-removing bacteria in high-altitude WWTPs. In conclusion, the four WWTPs achieved effective TP removal by alternating aerobic–anaerobic conditions within the A2O system, and the altitude and influent quality hardly affected TP removal efficiency.

3.6. Mechanism Analysis of Wastewater Treatment Efficiency by Bacteria

As shown in Figure 7, the nitrogen and phosphorus removal efficiency in the four high-altitude WWTPs was affected by three main factors, including influent quality, low temperatures and low air pressures characteristic of high-altitude environments, and wastewater treatment systems. Among them, influent quality, including COD and ammonium concentration, caused the greatest effect on the bacteria. This was because the high COD concentrations were beneficial for increasing bacterial community diversity and promoting nitrogen and phosphorus removal, while low ammonium concentrations in influent promoted the growth of NOB that competed with denitrifies for nitrite. Furthermore, high altitudes were typically characterized by low temperatures and low air pressures compared to low altitudes, which can increase the competitive advantage of PAOs over that of GAOs, resulting in efficient phosphorus removal in high-altitude WWTPs. However, low temperatures were unsuitable for the growth of nitrogen-removing bacteria at high altitudes, which resulted in phosphorus removal being prioritized over nitrogen removal in high-altitude WWTPs. Additionally, the wastewater treatment system generally exerted a greater influence on the bacterial community than the functional zones, because bacteria within the same system tended to exhibit similarities in WWTPs. In summary, the growth of phosphorus-removal bacteria is favorable in high-altitude WWTPs, with the main phosphorus-removing bacteria being PAOs, which possessed denitrifying phosphorus removal capabilities. This resulted in effective nitrogen and phosphorus removal in the four high-altitude WWTPs.

4. Conclusions

This study aimed to investigate the bacterial community structure and metabolic functions using WGS sequencing in high-altitude WWTPs located in Tibet (2980–3650 m). The results showed that low temperatures in high-altitude environments enhanced bacterial diversity and promoted the functional gene expression of polyphosphate-accumulating organisms (PAOs). Moreover, the influent quality in the four WWTPs importantly affected the bacterial community. Meanwhile, the dominant phyla at the phylum level were Proteobacteria, Bacteroidetes, Actinobacteria, Chloroflexi, Firmicutes, Verrucomicrobia, and Acidobacteria, which were typical phyla of high-altitude WWTPs. The dominant genera were Candidatus Accumulibacter, Dechloromonas, Propionivibrio, Nitrospira, Rhodoferax, Flavobacterium, and Pseudomonas. Meanwhile, the abundance of phosphorus-removing genera was higher than that of nitrogen-removing genera in high-altitude WWTPs, which resulted in better phosphorus removal performance than nitrogen in high-altitude WWTPs. Furthermore, pollutant concentrations strongly correlated with the top three dominant phyla of Proteobacteria, Bacteroidetes, and Actinobacteria, and bacterial genera were also affected by environmental factors including TP, NH4+-N, COD, altitude, TN, and pH. Additionally, functional genes related to carbon and nitrogen metabolism pathways were most abundant in LZ; Nitrogen metabolism relied on assimilatory nitrate reduction, dissimilatory nitrate reduction, and denitrification, which were beneficial to efficient nitrogen removal. Moreover, the low temperatures in high-altitude WWTPs favored the expression of functional genes in phosphorus-removing bacteria compared to nitrogen-removing bacteria, which promoted more efficient phosphorus removal than nitrogen. In conclusion, this study systematically elucidates microbial adaptation mechanisms and pollutant removal processes in high-altitude WWTPs from a metagenomic perspective. These findings provide a scientific foundation for optimizing wastewater treatment processes under extreme environmental conditions and contribute to sustainable water resource management. These findings provide critical insights into the bacterial adaptation mechanisms and pollutant removal dynamics in extreme environments, offering a scientific basis for optimizing wastewater treatment processes in high-altitude regions and supporting the development of sustainable wastewater management strategies.

Supplementary Materials

The following supporting information can be downloaded at https://www.mdpi.com/article/10.3390/w17091284/s1, Figure S1: The map of sampled wastewater treatment plants in Tibet of China. LZ: Nyingtri (29.6548° N, 94.3614° E; 2980 m); CD: Chamdo (31.1400° N, 97.1780° E; 3240 m); LS: Lhasa (29.6500° N, 91.1000° E; 3564 m); LW: Liuwu (24.3167° N, 109.4000° E; 3650 m); Table S1: Bacterial abundance and function at genus level in low-altitude WWTPs.

Author Contributions

R.Z.: Conceptualization, funding acquisition, supervision, writing—review and editing. Y.L.: Data curation, writing—original draft. H.L.: Formal analysis, methodology, supervision, writing—review and editing. J.X.: Investigation. Q.Z.: Investigation. P.L.: Software, validation. L.L.: Methodology, validation. X.L.: Conceptualization, investigation, supervision. All authors have read and agreed to the published version of the manuscript.

Funding

This work was supported by the Science and Technology Plan Projects of Tibet Autonomous Region (XZ202202YD0016C) and Tianjin Science and Technology Planning Project (Grant No. 24PTLYHZ00310).

Data Availability Statement

The original contributions presented in this study are included in the article/Supplementary Material. Further inquiries can be directed to the corresponding author.

Conflicts of Interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

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Water 17 01284 g001
Figure 1. Boxplots of the alpha-diversity index ((a) Ace, (b) Chao 1, (c) Shannon and (d) Simpson index) under anaerobic, anoxic, and aerobic zones in the four high-altitude WWTPs. Statistical significance between groups is indicated by asterisks: p ≤ 0.05 (*), p ≤ 0.01 (**), p ≤ 0.001 (***).
Figure 1. Boxplots of the alpha-diversity index ((a) Ace, (b) Chao 1, (c) Shannon and (d) Simpson index) under anaerobic, anoxic, and aerobic zones in the four high-altitude WWTPs. Statistical significance between groups is indicated by asterisks: p ≤ 0.05 (*), p ≤ 0.01 (**), p ≤ 0.001 (***).
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Figure 2. Beta-diversity analysis obtained by PCA (a) from anaerobic, anoxic, and aerobic zones of the four WWTPs. Species shared and unique to each sample obtained by the Venn diagram (b) from anaerobic, anoxic, and aerobic zones of the four WWTPs.
Figure 2. Beta-diversity analysis obtained by PCA (a) from anaerobic, anoxic, and aerobic zones of the four WWTPs. Species shared and unique to each sample obtained by the Venn diagram (b) from anaerobic, anoxic, and aerobic zones of the four WWTPs.
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Figure 3. The abundance of bacterial communities at the phylum level in the four high-altitude WWTPs.
Figure 3. The abundance of bacterial communities at the phylum level in the four high-altitude WWTPs.
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Figure 4. Relative abundance of bacterial communities at genus level in the four high-altitude WWTPs.
Figure 4. Relative abundance of bacterial communities at genus level in the four high-altitude WWTPs.
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Figure 5. PCA of bacterial communities and environmental variables at the phylum (a) and genus level (b), and co-occurrence network analysis of the top 10 bacterial genera in the four high-altitude WWTPs (c).
Figure 5. PCA of bacterial communities and environmental variables at the phylum (a) and genus level (b), and co-occurrence network analysis of the top 10 bacterial genera in the four high-altitude WWTPs (c).
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Figure 6. The potential functional categories of metabolism (KEGG level 3) predicted from PICRUSt (a), and metabolism levels of carbohydrate, nitrogen, and phosphorus compound functional genes groups through depth (b).
Figure 6. The potential functional categories of metabolism (KEGG level 3) predicted from PICRUSt (a), and metabolism levels of carbohydrate, nitrogen, and phosphorus compound functional genes groups through depth (b).
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Figure 7. Mechanistic analysis of influent quality (a), low temperatures and air pressures (b), and wastewater treatment plant operating parameters (c) for nitrogen and phosphorus removal in high-altitude WWTPs.
Figure 7. Mechanistic analysis of influent quality (a), low temperatures and air pressures (b), and wastewater treatment plant operating parameters (c) for nitrogen and phosphorus removal in high-altitude WWTPs.
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Table 1. Influent and effluent characteristics of four A2O WWTPs.
Table 1. Influent and effluent characteristics of four A2O WWTPs.
SampleLZCDLSLW
InfluentEffluentInfluentEffluentInfluentEffluentInfluentEffluent
COD (mg/L)45.807.20147.9017.15223.6424.44340.1924.37
NH4+-N (mg/L)5.702.0220.3430.00716.310.4223.092.46
TN (mg/L)6.706.4749.193.9818.232.1525.055.73
TP (mg/L)1.100.264.2910.17161.700.196.990.27
pH7.157.077.707.367.327.487.27.06
Temperature (°C)16.2815.5614.916.5515.616.415.516.2
Altitude (m)2980324035643650
Note: LZ: Nyingtri; CD: Chamdo; LS: Lhasa; LW: Liuwu; COD: chemical oxygen demand; NH4+-N: ammonium nitrogen; TN: total nitrogen; and TP: total phosphorus.
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Zhang, R.; Liu, Y.; Li, H.; Xiong, J.; Zhang, Q.; Li, P.; Liu, L.; Lu, X. Metagenomic Analysis of Bacterial Community Structure and Pollutant Removal Process in High-Altitude Municipal Wastewater Treatment Plants of Tibet, China. Water 2025, 17, 1284. https://doi.org/10.3390/w17091284

AMA Style

Zhang R, Liu Y, Li H, Xiong J, Zhang Q, Li P, Liu L, Lu X. Metagenomic Analysis of Bacterial Community Structure and Pollutant Removal Process in High-Altitude Municipal Wastewater Treatment Plants of Tibet, China. Water. 2025; 17(9):1284. https://doi.org/10.3390/w17091284

Chicago/Turabian Style

Zhang, Rui, Yiwen Liu, Haibo Li, Jian Xiong, Qiangying Zhang, Pengtao Li, Lingjie Liu, and Xuebin Lu. 2025. "Metagenomic Analysis of Bacterial Community Structure and Pollutant Removal Process in High-Altitude Municipal Wastewater Treatment Plants of Tibet, China" Water 17, no. 9: 1284. https://doi.org/10.3390/w17091284

APA Style

Zhang, R., Liu, Y., Li, H., Xiong, J., Zhang, Q., Li, P., Liu, L., & Lu, X. (2025). Metagenomic Analysis of Bacterial Community Structure and Pollutant Removal Process in High-Altitude Municipal Wastewater Treatment Plants of Tibet, China. Water, 17(9), 1284. https://doi.org/10.3390/w17091284

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