Moving bed biofilm reactors can purify urban domestic sewage through microbial biodegradation. High-throughput sequencing was used to study the response mechanism of the biofilm microbial community to temperature. The effluent quality of the reactor declined with the decrease in temperature. Proteobacteria, Bacteroidota, and Nitrospirota were the dominant bacteria, accounting for 59.2, 11.9, and 9.4%, respectively. Gammaproteobacteria (38.3%), Alphaproteobacteria (23.2%), and Bacteroidia (12.4%) were the dominant bacteria at the class level. Low temperature had an obvious directional domestication effect on microbial flora, and the composition of the bacterial community was more similar. Pseudomonas was one of the dominant bacterial groups at 5 °C. Nitrospira (p < 0.001) and Trichococcus (p < 0.05) were significantly negatively correlated with effluent ammonia nitrogen and significantly positively correlated with NO3 (p < 0.05) at low temperature. Functional bacteria related to chemoheterotrophy (25.88%) and aerobic_chemoheterotrophy (21.56%) accounted for a relatively high proportion. The bacteria related to nitrate reduction only accounted for 2.62%. Studies have shown that low temperatures can inhibit the growth of nitrogen-cycling bacteria, and few domesticated and selected nitrogen-cycling bacteria play a major role in the removal and transformation of ammonia nitrogen. The degradation of chemical oxygen demand can still be achieved through the adsorption and degradation of dominant functional bacteria.

  • Study the variations of MBBR effluent quality under different temperature gradients.

  • Investigate the growth characteristics of the biofilm attached to new filler under low temperature and high pollution load impact resistance.

  • Specify the functional characteristics of microbial communities influenced by temperature.

  • Identify the dominant flora under the combined action of low temperature and high pollution load.

As an important part of the earth's ecosystem, rivers are the main supply source of water resources and have important economic and social value (Ibekwe et al. 2016; Zhang et al. 2020a; Chen et al. 2023). Owing to the limitation and stability of urban infrastructure construction, urban domestic sewage can not be completely collected and treated (Yang et al. 2013; Wang et al. 2021). High-pollution domestic sewage spills into the river, which has a serious impact on the water environment and poses a threat to the survival of aquatic organisms and human health (Yang et al. 2013; Qin et al. 2019; Chen et al. 2023). The biological treatment process is the core process of domestic sewage treatment. In the micro-ecological environment formed by microbial attachment, organic matter, nitrogen, phosphorus, and other pollutants in domestic sewage are removed by microbial degradation and adsorption. The main biological treatment processes are anaerobic-oxide process (A/O), anaerobic-anoxic-oxic process (A2/O), sequencing batch reactor activated sludge process (SBR), membrane bio-reactor (MBR), moving bed biological reactor (MBBR), and so on (Zheng et al. 2020). Among them, MBBR has been widely concerned because of its advantages of great treatment efficiency, convenience, and low cost (Wang et al. 2018).

The biofilm attached to the surface of MBBR carrier material is the main contributor to the degradation and transformation of pollutants. Microorganisms and extracellular polymers affected by quorum sensing are the main components of the biofilm (Sun et al. 2018; Huang et al. 2020). Different microorganisms can use organic or inorganic substances for growth and metabolism in different anaerobic, anoxic, aerobic, and other environments, and the inter-species competition of flora caused by carbon sources and the inhibition of biomass activity caused by low temperature will affect the metabolic level (Zhang et al. 2020b; Mishra et al. 2022). Previous studies have shown that MBBR technology plays an important role in the treatment of wastewater with high pollution loads. However, the high sensitivity of biomass to low temperatures leads to the fluctuation of MBBR effluent quality in low-temperature environments (Jin et al. 2012; Tomaszewski et al. 2017; Huang et al. 2020). The biofilm formation and stability of MBBR are affected and limited at low temperatures (Hu et al. 2017). Hoang et al. revealed that the average ammonia removal rate of MBBR in the laboratory after long-term exposure to 1 °C was measured to be 18 ± 5.1% as compared to the average removal rate at 20 °C (Hoang et al. 2014). Previous studies focused on the changes of microbial nitrogen cycling functional bacteria under low-temperature conditions (Hoang et al. 2014; Young et al. 2017; Zekker et al. 2017). However, the response mechanism of microbial flora and functional bacteria to changes in COD and ammonia nitrogen under the simultaneous influence of high pollution load and low temperature needs to be further studied. Therefore, the study of cryotolerant bacteria of MBBR is of great significance to improve the effluent quality of engineering sites under low-temperature conditions and high pollution loads.

Environmental functional bacteria are the main microbial groups that realize the degradation and transformation of pollutants (Karakurt-Fischer et al. 2023). The ability of microorganisms to absorb and degrade pollutants stems from their physiological and metabolic functions (Chen et al. 2018). In the biological nitrogen removal process of sewage, the main functional microorganisms include ammonia-oxidizing bacteria, nitrifying bacteria, denitrifying bacteria, and anaerobic ammonia-oxidizing bacteria (Hoang et al. 2014). Nitrogen-cycling bacteria can decompose and transform nitrogen through the expression of functional genes. At low temperatures, the gene expression of some functional microorganisms is inhibited, and the biological activity and sewage treatment effect are reduced (Chen et al. 2018; Huang et al. 2020). Therefore, it is extremely important to study the dominant functional microorganisms at low temperatures to improve the sewage treatment effect of the MBBR system.

Therefore, in this study, the self-developed modified MBBR filler was used as the biofilm attachment carrier. High-throughput sequencing was used to study and analyze the response mechanism of the growth characteristics of the biofilm attached to new filler under low temperature and high pollution load impact resistance. The main objectives of this investigation are (1) to study the response mechanism of microbial composition and functional microorganisms to ammonia nitrogen and organic pollution load changes, (2) to predict the functional characteristics of microbial communities influenced by temperature, and (3) to identify the dominant flora under the combined action of low temperature and high pollution load.

Experiment design

The experimental setup is composed of an MBBR reactor, a primary water tank, a peristaltic pump, an aerator, and an outlet water tank (Figure 1). The MBBR reactor is made of plexiglass, with a diameter of 50 cm and a height of 20 cm. The reactor was placed in a constant temperature and humidity chamber of 80 cm × 65 cm × 110 cm to simulate different temperature conditions. The influent concentrations of COD and -N were 100 and 15 mg/L, respectively. The filling rate of padding in MBBR was set at 20%. The influent flow rate was 100–150 mL/min, and the hydraulic retention time (HRT) was set at 4 h. Biofilm culture experiments were carried out at 15, 10, and 5 °C, respectively, and each temperature gradient was run for 1 month.
Figure 1

The experimental setup of the MBBR reactor. (1) Raw water storage pool. (2) Raw water buffer pool. (3) MBBR reaction tank. (4) Temperature and humidity chamber. (5) Peristaltic pump. (6) Flowmeter. (7) Aeration machine. (8) Air inlet valve. (9) Aeration head. (10) Clean water storage pool.

Figure 1

The experimental setup of the MBBR reactor. (1) Raw water storage pool. (2) Raw water buffer pool. (3) MBBR reaction tank. (4) Temperature and humidity chamber. (5) Peristaltic pump. (6) Flowmeter. (7) Aeration machine. (8) Air inlet valve. (9) Aeration head. (10) Clean water storage pool.

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Water quality testing

The effluent water quality was detected at 1, 4, 7, and 28 days under different temperatures. Chemical oxygen demand (COD) concentration was determined by the dichromate method. -N concentration was determined by Nessler's reagent spectrophotometry. Ultraviolet spectrophotometry was used to measure concentration and the molecular absorption spectrophotometry was applied to measure concentration.

Sample collection, DNA extraction, and high-throughput sequencing

Bioreactor filler biofilm was collected at 1, 4, 7, and 28 days, respectively. The collected biofilm samples were placed in dry ice and sent to Lingen Biotechnology Co., Ltd in Shanghai for high-throughput sequencing. Deoxyribonucleic acid (DNA) was extracted using the FastDNATM Spin Kit for Soil Kit (MP, USA), and the integrity of genomic DNA was detected by 1% agalose gel electrophoresis. The V3–V4 variable region of the bacterial 16SrDNA gene was amplified by using the 341F-806R primer (Wilhelm et al. 2015; Li et al. 2020), with three replicates per sample. Polymerase chain reaction (PCR) products from the same sample were mixed and detected by 2% agarose gel electrophoresis. High-throughput sequencing was carried out based on PCR amplification products using the Illumina PE250 platform.

Sequencing data processing

The Miseq sequencing data based on bacterial 16S rRNA was analyzed using the Mothur software package and SILVA database (Li et al. 2020). The process of using Mothur software for biological information analysis is as follows: (1) If the length of the original sequence is less than 50 bp, or there is a deviation, the original sequence will be eliminated. (2) PCR chimeras were examined and removed using the chimera.uchime instruction provided by Mothur software. (3) Comparing the remaining sequences with the Ribosomal Database Project (RDP) classification database and using an 80% confidence interval to determine the systematic comparison of the sequences. (4) Based on Mothur software, creating an operational taxonomic unit (OTU) table of sequencing columns with a 97% similarity threshold (Liu et al. 2015).

Data analysis methods

The α diversity index of each sample was analyzed using Mothur software. The bacterial community structure was analyzed based on the phylum level and genus level. The R software package was used for heatmap and Principal Coordinates Analysis (PCoA), and Pearson correlation analysis was carried out based on SPSS 20.0 (Niu et al. 2015). For the identification of biomarkers for highly dimensional colonic bacteria, LEfSe analysis was applied. The Kruskal–Wallis sum-rank test was performed to examine the changes and dissimilarities among classes, followed by linear discriminant analysis (LDA) analysis to determine the size effect of each distinctively abundant taxa. FAPROTAX software was used for bacterial functional prediction (Sansupa et al. 2021; Huang et al. 2023).

Effluent quality analysis

Figure 2 revealed the concentration and removal rate of COD and -N of MBBR reactor effluent. The overall COD concentration in effluent shows an increasing tendency with the decrease in temperature, and the COD removal rate decreases by about 13.5%. The removal rate of ammonia nitrogen is relatively stable at 15 and 10 °C, while it decreases from 90 to 70% at 5 °C. In line with existing investigation, the effluent quality was affected at low temperatures under different treatment conditions to some extent (Mahmoud et al. 2004; Song et al. 2006; Li et al. 2012). According to the variation tendency of -N, and , the -N concentration was lower while the concentration was higher at 15 and 10 °C. The -N concentration was relatively high at 5 °C, and the removal efficiency showed a decreasing trend with the increase of culture time. The influence of temperature on conversion between -N, , and is stronger. Under low temperatures, the metabolic capacity of nitrogen-cycling bacteria will be decreased. The growth and degradation functions of microorganisms cannot respond to the fluctuations caused by sudden temperature drops in time. However, the cold-tolerant microorganisms will gradually show growth advantages under long-term low-temperature conditions (Zhou et al. 2021). Previous studies have shown that inhibition of activity or death of nitrifying bacteria during low-temperature exposure resulted in decreased ammonia removal rate (Hoang et al. 2014).
Figure 2

Pollutant concentration and removal efficiency in the effluent of MBBR reactor influenced by different temperatures.

Figure 2

Pollutant concentration and removal efficiency in the effluent of MBBR reactor influenced by different temperatures.

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Bacterial diversity and flora structure characteristics under different temperature gradients

Bacterial diversity analysis

The analysis of microbial diversity can be revealed by α diversity (Table 1). The Shannon index and Simpson index represent bacterial diversity. The Chao1 index and Ace index reflect the richness of microbial community, and the Evenness index represents species uniformity (Hua et al. 2020). Under different temperature gradients, the growth of microorganisms showed different characteristics. The bacterial diversity of S15-1 fluctuated greatly, and the microbial community growth was not stable, which may be due to the initial impact of the biofilm flora by sewage and culture conditions. With the decrease in temperature, the abundance and uniformity of bacteria increased slightly and tended to be relatively stable. The diversity of bacteria did not change significantly under the influence of different temperatures. With the increase of culture time at 5 °C, the abundance, uniformity, and diversity of bacteria all showed a tendency of first increasing and then decreasing. The results showed that low-temperature conditions could promote the growth of some cold-adapted bacteria, while long-term low-temperature environments may have a certain effect on bacterial activity. Wang et al. showed that as the temperature dropped from 15 to 5 °C, the nitrogen removal capacity of biofilm increased (Wang et al. 2024). In order to resist the impact of low temperatures, cold-adapted microorganisms will carry out functional enhancement modifications in their membranes, component proteins, and enzymes, and thus show the advantage of low-temperature growth (Bajaj & Singh 2015).

Table 1

Bacterial diversity under different temperature gradients

Observed_speciesChao1ACEShannonSimpsonEvenness
S15-1 679 870 898 2.81 0.789 0.431 
S15-7 1,206 1,391 1,454 5.10 0.983 0.719 
S15-14 1,072 1,287 1,329 5.03 0.983 0.721 
S15-28 1,135 1,381 1,419 5.03 0.983 0.714 
S10-1 1,144 1,363 1,407 5.11 0.984 0.725 
S10-7 1,385 1,529 1,621 5.07 0.979 0.700 
S10-14 1,224 1,458 1,499 5.04 0.981 0.709 
S10-28 1,244 1,443 1,484 5.05 0.982 0.709 
S5-1 1,401 1,577 1,582 5.52 0.986 0.761 
S5-7 1,400 1,650 1,671 5.56 0.989 0.767 
S5-14 1,473 1,649 1,694 5.56 0.986 0.762 
S5-28 1,359 1,635 1,618 5.33 0.983 0.739 
Observed_speciesChao1ACEShannonSimpsonEvenness
S15-1 679 870 898 2.81 0.789 0.431 
S15-7 1,206 1,391 1,454 5.10 0.983 0.719 
S15-14 1,072 1,287 1,329 5.03 0.983 0.721 
S15-28 1,135 1,381 1,419 5.03 0.983 0.714 
S10-1 1,144 1,363 1,407 5.11 0.984 0.725 
S10-7 1,385 1,529 1,621 5.07 0.979 0.700 
S10-14 1,224 1,458 1,499 5.04 0.981 0.709 
S10-28 1,244 1,443 1,484 5.05 0.982 0.709 
S5-1 1,401 1,577 1,582 5.52 0.986 0.761 
S5-7 1,400 1,650 1,671 5.56 0.989 0.767 
S5-14 1,473 1,649 1,694 5.56 0.986 0.762 
S5-28 1,359 1,635 1,618 5.33 0.983 0.739 

Analysis of bacterial community structure and composition

From the perspective of phylum level (Figure 3), Proteobacteriab (59.2%), Bacteroidota (11.9%), and Nitrospirota (9.4%) are the top three predominant phyla with the highest abundance. The abundance of Proteobacteria, Bacteroidota, and Myxococcota increased with the decrease in temperature. And the abundance of Proteobacteria rose with the increase of culture time at 5 °C. The result showed that the low-temperature-resistant strains of Proteobacteria played a vital role in low-temperature conditions.
Figure 3

Variations of the abundance of bacteria on the phylum level in the biofilm influenced by different temperatures.

Figure 3

Variations of the abundance of bacteria on the phylum level in the biofilm influenced by different temperatures.

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Proteobacteria and Bacteroidota are common bacterial groups in freshwater, and Proteobacteria have high adaptability to habitats. Previous studies have pointed out that Proteobacteria can adapt to various ecological habitats, such as the bottom material and activated sludge samples of freshwater systems (Liu et al. 2015; Li et al. 2020). Studies have shown that Bacteroidota can survive in polluted rivers, and this is because Bacteroidota can effectively degrade polymer-quality organic matter with a strong ability to degrade organic matter (Xu et al. 2023). Nitrospirota is a group of Gram-negative bacteria, of which Nitrospira is a nitrifying bacterium that oxidizes nitrite to nitrate. As revealed, the growth of Nitrospira was better at 15 and 10 °C. While the growth of Nitrospira was inhibited at 5 °C. This result indicates that low-temperature conditions may have a certain effect on the growth of Nitrospira (Chen et al. 2018).

PCoA analysis is a non-binding data dimensionality reduction method that can be used to study similarities or differences in the composition of sample communities. The potential principal components contributing to the otherness of sample community composition were identified by dimensionality reduction. The heterogeneity of microbial composition was analyzed by PCoA (Figure 4). PCoA1 and PCoA2 explain 58 and 33% of the intersample variation, respectively. The results showed that the bacterial communities under the same temperature gradients clustered into one type. It was found that low temperature (5 °C) had an obvious directional domestication effect on microbial flora. The community clustering degree was higher, and the composition of microbial flora was more similar.
Figure 4

PCoA analysis of microbial flora composition under different temperature gradients.

Figure 4

PCoA analysis of microbial flora composition under different temperature gradients.

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The heatmap was analyzed based on the bacterial communities at the genus level (Figure 5). At 5 °C, Haliangium, Acidovorax, Sphaerotilus, Pseudomonas, Hydrogenophaga, and Elstera were the dominant flora. Nitrospira has a relatively high abundance at both 15 and 10 °C, while low-temperature environments can significantly inhibit the growth of Nitrospira, as well as the variation of Trichococcus. Previous studies have also confirmed that Pseudomonas had better low-temperature resistance (Zhou et al. 2021; Zhang et al. 2023).
Figure 5

Heatmap of microbial flora composition under different temperature gradients.

Figure 5

Heatmap of microbial flora composition under different temperature gradients.

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Recently, two types of processes, deterministic process and stochastic process, have been considered to explain the response of microbial community variations to environmental disturbance (Li et al. 2015; Zhang et al. 2020c). Ya et al. analyzed the relative importance of various ecological processes in regulating microbial community diversity and succession through community assembly mechanisms, which also found that temperature-declining processes significantly enhanced the important role of deterministic ecological processes in community assembly (Ya et al. 2022). This investigation suggests that the deterministic assembly mechanism of microorganisms driven by low temperature may play an important role in contributing to the high similarity of microorganisms. Previous studies also revealed that microbial communities could be largely structured by deterministic effects, such as niche differentiation (Wilhelm et al. 2015; Zhang et al. 2020c).

LEfSe analysis was used to further study and identify the major differential communities (Figure 6). According to the results, 45 bacterial species belong to the distinct biomarkers species and exhibit LDA scores of more than four across sample groups. The length of the column represents the size of the LDA score, which is the degree of influence of distinct species between different groups. The lower the temperature, the more species were found with significant differences, of which, Alphaproteobacteria has the most significant difference at 5 °C. Yang et al. (2019) studied the wastewater treatment performance of biofilm reactors at low temperatures and found that Proteobacteria were dominant in nitrogen removal and organic degradation, among which Gammaproteobacteria and Alphaproteobacteria were the dominant bacteria.
Figure 6

LEfSe analysis was performed on the samples at multiple taxonomic levels.

Figure 6

LEfSe analysis was performed on the samples at multiple taxonomic levels.

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Correlation analysis between effluent quality and bacterial community structure

The Pearson correlation analysis was used to analyze the correlation between the composition of the top 30 bacterial genera and effluent water quality under different temperature (Figure 7). The result suggested that Nitrospira (p < 0.001), Trichococcus (p < 0.05), NS9 marine group_norank (p < 0.05), A0839_norank (p < 0.05) and NS9 marine group_norank (p < 0.001) were negatively correlated with effluent ammonia nitrogen, while positively correlated with and . This result indicated that the five bacteria may play an important role in nitrification. Furthermore, the study analyzed the correlation between the top 30 dominant bacteria genera and effluent water quality at 5 °C (Table 2). Results showed that among the above six dominant bacteria genera, only Nitrospira and Trichococcus were significantly positively correlated with in effluent (p < 0.05), while A0839_norank is significantly correlated with (p < 0.05).
Table 2

Correlations between the top 30 bacteria and effluent water quality at 5 °C

GenusCOD-N
Nitrospira −0.133 −0.883 0.971* −0.747 
Hydrogenophaga −0.329 −0.732 0.976* −0.607 
Trichococcus −0.389 −0.658 0.962* −0.534 
Acidovorax 0.144 0.943 −0.701 0.984* 
A0839_norank 0.14 0.824 −0.994** 0.654 
Chitinophagaceae_uncultured −0.121 −.962* 0.789 −0.954* 
Ferruginibacter 0.192 0.936 −0.742 0.969* 
Flavobacterium 0.363 −.959* 0.791 −0.765 
Zoogloea −0.303 −0.794 0.970* −0.686 
Hyphomicrobium −0.002 0.894 −0.973* 0.71 
GenusCOD-N
Nitrospira −0.133 −0.883 0.971* −0.747 
Hydrogenophaga −0.329 −0.732 0.976* −0.607 
Trichococcus −0.389 −0.658 0.962* −0.534 
Acidovorax 0.144 0.943 −0.701 0.984* 
A0839_norank 0.14 0.824 −0.994** 0.654 
Chitinophagaceae_uncultured −0.121 −.962* 0.789 −0.954* 
Ferruginibacter 0.192 0.936 −0.742 0.969* 
Flavobacterium 0.363 −.959* 0.791 −0.765 
Zoogloea −0.303 −0.794 0.970* −0.686 
Hyphomicrobium −0.002 0.894 −0.973* 0.71 

Note. Only bacteria genera that have a significant correlation with effluent water quality indexes are shown. Two asterisks indicate that the variable is significantly correlated to the α-diversity index (p < 0.01) and an asterisk also represents the relevance between the variable and the diversity index (p < 0.05).

Figure 7

Relationship between bacterial community structure and effluent quality based at the genus level under different temperatures. Two asterisks indicate that the variable is significantly correlated to the α-diversity index (p < 0.01) and an asterisk also represents the relevance between the variable and the diversity index (p < 0.05).

Figure 7

Relationship between bacterial community structure and effluent quality based at the genus level under different temperatures. Two asterisks indicate that the variable is significantly correlated to the α-diversity index (p < 0.01) and an asterisk also represents the relevance between the variable and the diversity index (p < 0.05).

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As a kind of nitrite-oxidizing bacteria, previous studies have found that Nitrospira plays a dominant role among nitrifying bacteria at low temperatures (Zhou et al. 2021). Huang et al. (2023) discovered that Nitrospira could acclimate to low-temperature environments and actively engage in nitrification processes. A cold environment would significantly inhibit the growth of ammonium-oxidizing bacteria (AOB), which may be related to the ecological barriers of AOB. As previous studies revealed, Nitrosomonas has a relatively low affinity for ammonia nitrogen, but the environment with high ammonia nitrogen concentration is conducive to the growth of the flora or the enhancement of the ammonia-oxidizing activity of bacterial communities. To a certain extent, it can promote the dominant growth of bacterial communities associated with nitrogen removal (Kits et al. 2017; Liu et al. 2023). Trichococcus belongs to Nostocoida Limicola I. Nostocoida Limicola I can adapt to anaerobic conditions and often appears in nitrogen and phosphorus removal systems (Snaidr et al. 2002). Trichococcus is also an important filamentous bacterium in denitrification and phosphorus removal-activated sludge systems.

Prediction and analysis of functional characteristics of microbial communities under different temperature gradients

The functional annotation of bacterial OTU was carried out by using FAPROTAX, and the biogeochemical cycle process was predicted by functional annotation. It was found that, among the top 10 functional microflora (Figure 8), bacteria with the function of chemoheterotrophy and aerobic_chemoheterotrophy accounted for a relatively high proportion under different temperature gradients, with an average abundance of 25.88 and 21.56%, respectively, which is consistent with previous research (Huang et al. 2023). With the increase of culture time, the abundance of the two functional bacteria was more significant at 5 °C, while the variation tendency of other functional bacteria was gradually weakened with the increase of culture time. According to nitrogen cycling bacteria, the proportion of bacteria related to nitrate reduction function was 2.62%, while the proportion of other nitrogen cycle functional bacteria was less than 1%. At 15 and 10 °C, the abundance of nitrate-reducing bacteria increased with culture time, while decreased at 5 °C. The results showed that low temperatures inhibited the growth of nitrogen-cycling functional bacteria but had little effect on chemoheterotrophic microorganisms. At low temperatures, COD degradation could still be achieved through the adsorption and degradation of microorganisms. This is the key to the stable removal of COD in effluent at low temperatures.
Figure 8

Analysis of the composition of the top 10 predictive functional flora under different temperature gradients.

Figure 8

Analysis of the composition of the top 10 predictive functional flora under different temperature gradients.

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Redundancy Analysis (RDA) was used to perform correlation redundancy analysis between the predicted functional flora composition and effluent quality. According to the results (Figure 9), -N (R2 = 0.87, p < 0.01), (R2 = 0.56, p < 0.05) and (R2 = 0.85, p < 0.01) were significantly correlated with the changes of functional bacteria. Functional bacteria also showed significant temperature clustering characteristics. The lower the temperature was, the more concentrated the functional bacteria clustered. -N concentration in the effluent was positively correlated with functional bacteria composition of samples at 5 °C. The results showed that the lower the temperature, the fewer strains of the dominant functional strains participating in the nitrogen cycle process. The bacterial functions related to nitrification decreased and ultimately resulted in the inability to effective degradation and transformation of effluent ammonia nitrogen. Bacterial communities related to chemoheterotrophy and aerobic_chemoheterotrophy also showed a positive correlation with -N concentration and a negative correlation with effluent COD concentration, which indicated that bacteria related to these two functions mainly consumed organic pollutants.
Figure 9

RDA redundancy analysis of predicted functional flora composition and effluent quality.

Figure 9

RDA redundancy analysis of predicted functional flora composition and effluent quality.

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MBBR plays a major role in the treatment of wastewater with high pollution loads. It is extremely important to clarify the fluctuation of MBBR effluent quality and expound possible ecological reasons under low temperatures. With the decrease in temperature, the effluent quality of MBBR decreased, and the removal rate of ammonia nitrogen decreased more significantly than that of COD. According to the bacterial diversity, with the increase of culture time at 5 °C, bacterial abundance, evenness, and diversity showed an increasing tendency and then decreased. Low-temperature conditions would promote the advantageous growth of some low-temperature-resistant bacteria, but long-term low temperature might have a certain impact on bacterial activity. In terms of the composition of bacteria, Proteobacteria, Bacteroidota, and Nitrospirota were the dominant bacteria, accounting for 59.2, 11.9, and 9.4%, respectively. At the class level, Gammaproteobacteria, Alphaproteobacteria, and Bacteroidia were the dominant bacteria and accounted for t 38.3, 23.2, and 12.4%, respectively. The low temperature had a certain effect on the growth of Nitrospiria and had an obvious directional domestication effect on microbial flora. The community clustering degree was higher and the composition of microbial flora was more similar. Pseudomonas was dominant at 5 °C. According to Pearson correlation analysis, Nitrospira (p < 0.001) and Trichococcus (p < 0.05) were significantly negatively correlated with effluent ammonia nitrogen and significantly positively correlated with (p < 0.05) at low temperature. Functional bacteria related to chemoheterotrophy (25.88%) and aerobic_chemoheterotrophy (21.56%) accounted for a relatively high proportion. Among the nitrogen-cycling bacteria, bacteria related to nitrate reduction accounted for 2.62%. Studies have shown that low temperatures can inhibit the growth of nitrogen-cycling bacteria. Few domesticated and selected nitrogen-cycling bacteria (such as Nitrospirota and Trichococcus) play a major role in the removal and transformation of ammonia nitrogen. The degradation of COD can still be achieved through the adsorption and degradation of dominant functional bacteria.

This study was supported by the Science and Technology Planning Project of Jiangsu Provincial Environmental Protection Group (No. JSEP-TZ-2021-1005-RE). And also supported by the Research and Development Project of Jiangsu Environmental Engineering Technology Co., Ltd (No. JSEP-GJ20220011-RE-ZL, No. JSEP-GJ2023-1005-RE-ZL).

All relevant data are included in the paper or its Supplementary Information.

The authors declare there is no conflict.

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