The Relationship between Ribosomal RNA Operon Copy Number and Ecological Characteristics of Activated Sludge Microbial Communities across China

Abstract

It is well accepted that the high performance of wastewater treatment plants (WWTPs) relies on the microbial community in activated sludge (AS). Hence, it is crucial to illuminate the geographic distributions and influencing factors of the ecological strategies employed by the AS microbial community. Here, we investigated how the ecological strategies of AS microbial communities influenced their ecological characteristics in 60 WWTPs across 15 cities in China. Our study showed that the average rrn copy number of the whole AS microbial community across China was 2.25 ± 0.12. The highest average rrn copy number of the core community indicated that core members tend to be r-strategists with an advantage in rapid pollutant removal and recovery of the community after environmental disturbances. High nutrient availability promoted microorganisms with higher average rrn copy numbers, while long sludge retention time (SRT) was preferred to the microorganisms with lower average rrn copy numbers. Homogenous selection and dispersal limitation were the predominant assembling processes at the city level, with a shift from deterministic to stochastic processes with increasing average rrn copy numbers. Furthermore, more r-strategists participated in chemoheterotrophic functions, while more K-strategists were related to the nitrification processes. Overall, our findings enrich the knowledge of AS microbial ecology and lay the theoretical foundation for the precise regulation of WWTPs.

1. Introduction

Wastewater treatment plants (WWTPs) play a crucial role in degrading and removing organic pollutants, nutrients such as nitrogen and phosphorus, and toxic and hazardous substances from sewage, thereby serving as an indispensable infrastructure for environmental protection. With the development of high-throughput sequencing technology, we have a deeper understanding of microbial communities within activated sludge (AS). For example, the richness of the AS microbial community at the global scale is as high as 10⁹, which is only about one order of magnitude lower than that of the global ocean microbiome [1]. The stable and efficient operation of WWTPs mainly relies on a few key microbial communities in AS, and temperature is the most important factor influencing microbial community diversity and structures [1,2,3]. Moreover, the AS microbial community manifests a skewed abundance distribution characterized by a small fraction of highly abundant species and the majority of species occurring with much lower abundances. Our previous study has demonstrated that the abundant and rare sub-communities have distinctly ecological and functional differences across China [4]. Under low temperature conditions, the abnormal growth and proliferation of certain microorganisms can lead to operational failures of WWTPs, such as nitrification failure and sludge bulking [5,6,7]. Recent studies have shown that stochastic and deterministic processes drive AS microbial compositions simultaneously, but their relative contributions are debatable and can be influenced by many factors, such as research scale and geographic locations. For example, Wu et al. [1] found stochastic processes dominated at the global scale, while Zhang et al. [2] found that deterministic processes dominated the AS microbial community in China (at the national scale). Moreover, South China had higher proportions of stochastic processes compared to North China [8].

In macroecology, the concept of r- and K-strategy has been widely applied. With advances in molecular biology and bioinformatics, the r/K selection theory has been extended to microorganisms in both natural and engineered ecosystems [9]. It serves as a metric to delineate the ecological characteristics of the population studied, thereby affording a comparably effective and convenient framework for the categorization and discrimination of diverse microorganisms. The r-strategists are considered as “opportunists” due to their higher average abundance-weighted of average rrn operon copies and their adaptability to eutrophic environments. Meanwhile, they exhibit rapid growth rates but relatively low resource utilization efficiency, coupled with high community-resilient potential in response to environmental disturbances. Conversely, K-strategists, acting as “conservatism”, have a lower abundance-weighted average rrn copy number of community. They are capable of adapting to resource-limited environments, demonstrating a high efficiency in resource utilization, and exhibiting strong resistance against environmental disturbance. As the average rrn copy number is phylogenetically conserved, it can be used as an indicator to elucidate microbial functional characteristics and life-history strategies, and to characterize community responses to environmental changes. For example, the flow rate and types of wastewater (such as domestic wastewater and industrial wastewater) have a significant effect on structures and the average rrn copy number of microbial communities [10]. Increasing resource availability heightened the average rrn copy number of microbial communities in anaerobic digesters [11]. Moreover, Pérez et al. conducted a time-series survey and found clear differences between disturbed and stable operational periods regarding bacterial rrn copy numbers [12], where operational disturbances increased the relative proportion of bacteria with higher rrn copy numbers [12].

Considering the average rrn copy number has been studied as a potential indicator of microbial growth rate and metabolic activity, and understanding the ecological strategy of the AS microbial community is vital to revealing and predicting microbial behavior [13]. Recent studies have shown that the AS microbial community with a lower average rrn copy number was more stable. The resistance stability (based on the average rrn copy number) of the microbial community in AS was higher than that of the influent community, and the fluctuation over time was smaller [6]. Discerning the relationship between rrn copy number and microbial ecological characteristics (such as diversity, assembly mechanism, and potential functions) is crucial for wastewater treatment process optimization and control. For example, WWTPs with high fluctuations would benefit from K-strategists to enhance stability, while newly established WWTPs or those experiencing operational failures would require r-strategists to facilitate recovery of the AS microbial community. To better understand the response of the ecological characteristics of AS microbial communities to microbial ecological strategy, and to provide a new perspective for precise regulation of WWTPs in the future, the objectives are: (1) to clarify geographic distributions of average rrn copy number and the corresponding ecological strategy of four groups (the whole community, the core community, the abundant community, and the rare sub-communities in AS); (2) to reveal the response of the ecological characteristics of the AS community, especially the assembly mechanisms to average rrn copy numbers; and (3) to identify the potential functions of four groups and the relationship between average rrn copy numbers and microbial functions in AS.

2. Materials and Methods

2.1. Sample Collection

In this study, a unified sampling method was employed to collect AS samples from aeration tanks of WWTPs in 15 cities across China, spanning from south to north. These cities include Sanya (SY), Shenzhen (SZ), Xiamen (XM), Changsha (CS), Chongqing (CQ), Wuhan (WH), Chengdu (CD), Shanghai (SH), Wuxi (WX), Xi’an (XA), Qingdao (QD), Jinan (JN), Dalian (DL), Beijing (BJ), and Harbin (HB), as illustrated in Figure 1. To ensure more reliable statistical analysis, the sampling strategy followed specific guidelines: at least 4 WWTPs using biological treatment and having aeration tanks were sampled in each city (In the case of DL, where only 2 WWTPs were available, 2 different aeration tanks of the same WWTP were sampled according to the same standard). To enhance the representativeness of the samples and provide a more accurate reflection of the microbial composition present in AS throughout the aeration tank, 1 L of activated sludge was gathered close to the inlet, at the midpoint within the tank, and adjacent to the outlet in each aeration tank. For the acquired samples, a minor aliquot of 2 milliliters was designated for DNA extraction and high-throughput 16 S rRNA sequencing. Meanwhile, the remainder of the samples were utilized for the determination of water quality parameters. These parameters encompassed a comprehensive set of critical indicators: chemical oxygen demand (COD), ammonia–nitrogen (NH₃-N), nitrite–nitrogen (NO₂-N), nitrate-nitrogen (NO₃-N), total nitrogen (TN), and total phosphorus (TP). It should be noted that this study presents a cross-sectional analysis, capturing a single-time snapshot of microbial communities. The temporal dynamics of rrn copy numbers and community attributes throughout the operation of WWTPs remain unexplored. Furthermore, the conclusions and findings are based on samples collected from Chinese WWTPs. The generalizability of these findings to other global regions warrants further investigation.

2.2. Sample 16S rRNA Gene High-Throughput Sequencing

The PowerSoil^® DNA extraction kit from MoBio Laboratories (Carlsbad, CA, USA) was used to extract the DNA from sludge sediments of 211 AS samples after centrifugation. The extracted DNA samples were confirmed to meet the requirements for sequencing in terms of quantity (DNA concentration maintained between 50 and 200 ng/μL) and purity (A260/A280 around 1.8, A260/A230 greater than 1.7) before proceeding to two-step PCR amplification [11]. The first step of PCR utilized universal primers 515F (5′-GTGCCAGCMGCCGCGGTAA-3′) and 806R (5′-GGACTACHVGGGTWTCTAAT-3′), targeting the amplification of the V4 region of 16S rDNA without adding components to avoid additional biases from spacers and other additives [14]. Subsequently, 200 ng of PCR products from each sample were pooled and loaded onto 1% agarose gel. The segment of the gel harboring the target genes was sliced and agarose was removed by using the QIAGEN Gel Extraction Kit. Then, the purified products were sequenced for the 16S average rRNA gene on the Miseq platform (Illumina, San Diego, CA, USA). The raw sequence data were processed through an internal pipeline established on the Galaxy platform (https://dmap.denglab.org.cn/, accessed on 4 April 2023) at the University of Oklahoma, with parameter settings detailed in references [11,14,15].

2.3. Data Processing and Analysis Methods

The taxonomy for each Operational Taxonomic Unit (OTU) was identified by Ribosomal Database Project (RDP) Classifier platform (http://rdp.cme.msu.edu/classifier/classifier.jsp, accessed on 9 December 2023) with a bootstrap confidence threshold of 50%. The rrn copy number for each OTU was estimated by identifying its closest relatives with known rrn copy numbers in the rrnDB database. When the child taxa record of the OTU was available, the estimation was refined by using the mean rrn copy number of the child. Conversely, for OTUs without available child taxa records, the mean rrn copy number of the higher-rank parent taxa was utilized. The abundance-weighted average rrn copy number of the microbial community was calculated using the equation mentioned in the reference [16].

Notably, there are currently no unified criteria for the screening of core, abundant, and rare microbial sub-communities. Screening results obtained from different criteria may exhibit slight differences. In this study, OTUs were classified as core microorganisms if they met the following two criteria. The relative abundance of the OTU was required to rank within the top 100. Meanwhile, its distribution frequency across the samples reached a minimum threshold of 80% [2]. Abundant microorganisms were defined as OTUs with a relative abundance greater than 0.1% on average across all samples [17]. The rare sub-community can serve as a “seed bank” for microbial communities and may become the dominant species under favorable conditions [18]. Here, OTUs that exhibited a relative abundance of less than 0.001% across all samples were categorized as rare microorganisms [17]. Microbial α diversity characterized the abundance and evenness of microorganisms in a community, and this paper adopted microbial richness (q₀), Shannon–Wiener Index (q₁), and inverse Simpson index (q₂) to evaluate the alpha diversity of AS microbial communities. The Bray–Curtis distance was selected to characterize the β diversity of AS microbial communities. Different groups of AS microbial assembly were investigated by the null model. In this model, environmental selections containing homogeneous selection and variable selection are classified as deterministic processes, while dispersal limitation, homogenizing dispersal, and drift are identified as stochastic processes. More detailed descriptions and calculations of the null model can be found in the reference [19]. The Biozeron Cloud Platform (http://www.cloud.biomicroclass.com/CloudPlatform, accessed on 15 April 2024) was used for intergroup and intragroup differential analysis of average rrn copy numbers by t test. Spearman correlation analysis of average rrn copy number with α and β diversity index, assembling mechanism, and environmental factor parameters was performed by using vegan and parallel packages in R. Functional Annotation of Prokaryotic Taxa (Faprotax) is a common database to predict bacterial potential functions [20] and it was adopted to predict the function of the whole, the core, the abundant, and the rare community through Deng Lab platform (https://dmap.denglab.org.cn/, accessed on 19 April 2024). However, it should be acknowledged that predictions made by FAPROTAX (v1.2.4) could potentially underestimate the functional diversity of AS microbial communities because FAPROTAX provides accurate predictions based on verified cultured bacteria.

3. Results and Discussion

3.1. Geographical Distributions and Influencing Factors of Average rrn Copy Number of Microbial Communities

3.1.1. Geographical Distributions of Average rrn Copy Number

The growth rate, growth efficiency, resource utilization rate, and speed of adaptation to different environmental conditions of microorganisms can be marked by abundance-weighted average ribosomal RNA operon copy number (average rrn copy number) [10,21]. Meanwhile, the average rrn copy number reflects the ecological strategies of bacteria. Briefly, the average rrn copy number of r-strategists is usually higher, while the average rrn copy number of K-strategist holders is lower [16]. In order to comprehensively analyze the ecological strategy characteristics of different microbial groups in WWTPs, the average rrn copy numbers of the whole microbial community, the core community, the rare community, and the abundant community were calculated, respectively. The abundance-weighted average rrn copy numbers of the four groups were 2.25 ± 0.12, 2.34 ± 0.13, 2.27 ± 0.11 and 2.27 ± 0.13, respectively. The average rrn copy number of the whole microorganisms is lower than that of the core microorganisms, the rare microorganisms, and the high-abundance microorganisms. Among the four communities, the average rrn copy number of the core microorganisms is the highest, followed by that of the rare microorganisms. The average rrn copy number of the core microorganisms is significantly higher than that of the other three types of microorganisms, indicating that the core microbial community tends to be r-strategist, has a high reproductive rate, has strong resilience to environmental disturbances [22], and can achieve high pollutant removal loading rates [9]. It also suggests that increasing nutrient levels or COD load may be an effective way to promote the abundance of the core community in WWTPs.

Upon comparing the average rrn copy number of microbial communities in other environmental systems, it is found that the average rrn copy number of communities in different ecosystems was significantly different. For instance, the average rrn copy number at the global coastal sediment community level is about 2.74 ± 0.06; The average rrn copy number of community level in deep seawater is higher than that in surface seawater, at about 1.54 ± 0.01 [16]. In the anaerobic digester rich in organic matter, the average rrn copy number of the microbial community was about 2.96, and the increase in organic loading rate could further increase the average rrn copy number of the microbial community (3.09 and 3.38, respectively). Guo et al. [10,23] compared the average rrn copy number of sewage, activated sludge, human gut, and soil microbial community, and found that the average rrn copy number of soil microbial community was the lowest (average value was 2.1), followed by human gut and AS, which were 2.6 and 2.75 ± 0.15, respectively. The average rrn copy number of microbial communities in influent wastewater was much higher (3.64 ± 0.27) than that in AS, possibly due to the higher food to microbe (F/M) in influent wastewater.

To discern geographic distributions of the ecological strategy of different AS groups, the average rrn copy numbers of four groups were calculated at the city level (Figure 2). Overall, the average rrn copy numbers of core microorganisms in all cities were higher than that of whole microorganisms. Therefore, it indicated that the core microorganisms may have a higher maximum growth rate and more adaption in high levels of nutrients than that of the other three groups of AS microbial communities, and core microorganisms may have more advantages in competition for nutrients and resources and a high level of resilience to recovery microbial community after environmental disturbances, thereby ensuring the function of WWTPs. The average rrn copy numbers of the AS microbial community in CS, DL, and SH cities were significantly higher than the national level, while the average rrn copy numbers of SY and WX cities were significantly lower than the national average value (Figure 3). This discrepancy may be due to differences in the concentration of organic matter in wastewater and the frequency of environmental disturbances affecting microorganisms. Moreover, there is no significant difference in the average rrn copy number of four groups (whole, core, rare, and high abundance) in nearly half of WWTPs (7/15).

Notably, the intragroup difference of the average rrn copy number in XA was the most significant (p < 0.01), with the core microbial community having the highest average rrn copy number and the rare microbial group having the lowest copy number. This suggests that different subcommunities may adopt different ecological strategies and functions, with the core microbial community potentially playing an important role in rapid pollutant removal and recovery of the community after environmental disturbances. In contrast, the rare microbial groups may have an advantage in resisting external disturbances and maintaining community stability. The average rrn copy number of different subcommunities in SY’s sewage treatment plant was significantly lower than the national average, possibly due to the excessively low concentration of influent organic matter in SY, resulting in the microbial community in the activated sludge being in an oligotrophic state.

3.1.2. Influencing Factors of Average rrn Copy Number

Previous studies have indicated that the compositions and structures of the AS microbial community can be affected by geographic location (e.g., latitude), inf. COD and temperature [1,6]. Moreover, factors influencing abundant and rare microbial communities were distinct. The geographic location of WWTPs had a substantial impact on the composition of their rare microbial communities, whereas the wastewater characteristics exhibited a stronger correlation with the structure of the abundant microbial communities [4]. Given the metabolic significance of microorganisms in wastewater treatment and the fact that environmental factors are the main drivers of microbial community composition [24], it is crucial to elucidate how environmental variables affect the ecological strategy of different AS groups [25]. Here, heatmap Spearman correlation was utilized to visualize the influence of environmental factors on the average rrn copy number of four groups. Generally, environmental factors influencing the average rrn copy number characteristics of the whole microbial community and the abundant microbial community were similar, while those affecting the average rrn copy number of the rare microbial group were significantly different (Figure 4).

Water quality parameters such as NH₃, F/M, TN, and COD loading describe the nutrient level of AS, while Inf.COD, inf.BOD, and inf.TN characterize the nutrient level of the influent wastewater. Our results showed that the average rrn copy number of four AS groups increased with significantly positive correlations with NH₃, F/M, TN, COD loading, and Inf.COD, which is consistent with the results of existing reports. For example, Wu et al. [22] found that when the organic loading rate increased, the copy number of average rrn also increased accordingly. Dai et al. [16] observed that the average rrn copy number of coastal communities was significantly positively correlated with NH₄⁺-N concentration under high nutrient loads. The gradual increase in average rrn copy number with the increase in available resources indicated that the microorganisms in AS adopted the r-strategy when the available resources were abundant. It provided a possible strategy for selectively enriching the microbial community in AS. Moreover, our results suggested that the nutrient availability of AS had a stronger influence on the AS microbial community than that of influent wastewater. Also, it indicates the potential of using the average rrn copy number of the AS microbial community to evaluate the nutrient level of the system. It should be noted that the rare community had a significant positive correlation with both latitude and longitude, while such correlations were not observed in the core community and the high-abundance community, indicating that the ecological strategy of the rare community is significantly affected by geographical locations. The rare microbial communities in high-latitude regions tend to be r-strategists, while those in low-latitude regions tend to be K-strategists. This may be attributed to the features of WWTPs in the north and south of China, where the water quality in low-latitude regions fluctuates more, and the increase in K-strategists is beneficial for the community to enhance resistant stability. In contrast, in northern WWTPs, the higher pollutant concentration promotes the average rrn copy number of different subcommunities. Moreover, the persistent influence of geographic locations on the composition and ecological strategies of rare communities highlights the distinctiveness of the adaptive tactics employed by their constituent members. In comparison, wastewater characteristics had a more substantial effect on the composition of abundant communities, rather than on their ecological strategies. This indicates that members of abundant communities, despite potential variations in their taxonomic affiliations, are more likely to adopt analogous ecological strategies, enabling them to flourish in their shared environmental conditions.

Different from the effects of available resources on ecological strategy, the average rrn copy number of the four groups of microorganisms was negatively correlated with Taveg, conductivity, NO₃⁻, DO, and SRT. Among these, only SRT had a significant negative correlation with all four microbial groups, meaning that the microbial community may gradually evolve into K-strategists under the condition of long SRT. It is reasonable that longer SRT allows K-strategists to have more time for growth and reproduction, thus increasing their competitive advantage. The study by Vuono et al. [26] also supported this conclusion: r-strategists are more abundant in the system during a 3-day SRT, while K-strategists only exist when SRT is greater than 12 days. In addition, the results showed that only the average rrn copy number of the whole and rare communities had significant negative correlations with Taveg, which agreed with the effect of latitude on the average rrn copy number of the community, indicating that the effect of latitude on the average rrn copy number of the microbial community mainly results from the effect of temperature. Although Haller et al. [24] pointed out that pH and TP significantly affected the structures and distributions of microbial communities, the results of our study showed that the average rrn copy number of the four groups of microorganisms have no significant correlation with TP and pH, indicating that the ecological strategy of the microbial community was less affected by the acidity and phosphorus concentration of AS.

3.2. The Relationship of Community Average rrn Copy Number to Biodiversity and Assembly Mechanism

3.2.1. The Response of Community Diversity to Average rrn Copy Number

Response of α diversity (taxonomic diversity and phylogenetic diversity) and β diversity (based on Bray–Curtis distance) to the average rrn copy number of the AS microbial community was revealed by Spearman correlation. The analysis revealed that average rrn copy number was significantly negatively correlated with taxonomic diversity (r₀ = −0.640, r₁ = −0.675, r₂ = −0.554, P < 0.05, Figure 5a–c) and phylogenetic diversity (r₀ = −0.600, r₁ = −0.693, r₂ = −0.564, P < 0.05, Figure 5d–f). This indicated that as the community evolved towards microbial populations with higher average rrn copy numbers, the taxonomic and phylogenetic diversity within the AS system decreased. A possible explanation for this phenomenon is that microbial populations with high average rrn copy numbers (r-strategist) exhibit faster growth rates and preferential exploitation of resources. This leads to a reduction in available resources for other microbial groups. Additionally, these fast-growing microbes may release metabolites during their growth, altering the living environment that further inhibits the growth of other microbial groups, thereby resulting in a decline in biodiversity.

In contrast to the response of α diversity, there was no significant correlation between the average rrn copy number and β diversity (r = −0.011, p > 0.05, Figure S1). This finding agreed with the study of Dai et al. [27], which revealed that the differences in AS microbial communities from different municipal WWTPs were not driven by microbial community survival strategies. Furthermore, some studies have indicated that both β diversity and average rrn copy number can be used to assess the resistant stability of communities. Specifically, higher β diversity and average rrn copy number are associated with lower resistance stability [6]. Our results suggest that results evaluating resistant stability of the microbial community based on β diversity and average rrn copy number are not always consistent, and appropriate methods should be chosen according to the certain purpose.

3.2.2. The Relationship between the Assembly Mechanism and Average rrn Copy Number

Revealing microbial assembly advances our knowledge of how current microbial composition and structure are established and maintained, which is vital to predict ecological responses to environmental disturbance or changes [28]. In the majority of cities, homogeneous selection and dispersal limitation were the main assembling processes (Figure 6a). In some cities, such as CD, CQ, and HB, homogeneous selection made up more than 80%. The relative contributions of dispersal limitation varied greatly across cities. It accounted for more than 55% in WH, but only made a proportion of 14.3% in HB. Variable selection was only observed in the AS microbial communities from JN, WH, and XM, and homogenizing dispersal was only detected in microbial communities from SH and WX. In general, deterministic and stochastic processes drove the AS microbial community simultaneously at the city level. However, their contributions were not consistent across different cities, which was consistent with current perception. Stochastic processes dominated the AS microbial community in SH, while deterministic processes had greater effects on BJ.

Subsequently, a linear model was used to elucidate the relationship between the microbial assembly and their ecological strategies. Due to the high overlaps of OTUs between the core microbial community and the abundant microbial community, only the whole, the abundant, and the rare community was considered in this part. The results showed that the deterministic processes of the whole microorganisms and abundant microbial communities were significantly negatively correlated with the average rrn copy number (Figure 7a: r_Whole = −0.62, P_Whole < 0.05, r_Abundant = −0.57, P_Abundant < 0.05). The opposite results were observed between stochastic processes and average rrn copy number (Figure 7b: r_Whole = 0.62, P_Whole < 0.05, r_Abundant = −0.57, P_Abundant < 0.05). There was no significant correlation between the two processes and the average rrn copy number of the rare community (|r| < 0.15, P > 0.05).

Nemergut et al. [29] tracked the bacterial communities at different time points in the natural environment to study how the average rrn copy number affected the assembly and evolution of the microbial community. They found that as the average rrn copy number decreased, microorganisms potentially optimized their resource utilization efficiency, thus better adapting to environmental changes during the succession process. This resulted in community assembly processes displaying more deterministic processes under resource-limited conditions. These findings were consistent with our study, which showed that the average rrn copy number of the whole microorganisms was negatively correlated with deterministic processes and positively correlated with stochastic processes. It also indicated that more existence of bacteria with higher average rrn copy numbers tend to develop the relative importance of stochastic processes in community structure. In contrast, van Der Gast et al. [30] found that with the increase in the concentration of industrial wastewater in the whole bioreactor, the microbial community gradually shifted from a stochastic process to a deterministic process. The inconsistencies in the above results may be due to the characteristics of industrial wastewater, which is a strong selection for the AS microbial community.

3.3. Study on the Relationship between Average rrn Copy Number and Community Microbial Function

The relationship between resource availability and environmental disturbance of different groups of AS microbial communities and their predicted functions was explored by FAPROTAX (Figure 8). To reduce analysis complexity, only the top 10 abundant functions remained, including denitrification, anaerobic ammoxidation, nitrogen fixation, nitrite oxidation, ammonia oxidation, nitrogen respiration, sulfate respiration, sulfur respiration, fermentation, and chemoheterotrophic functions. In general, bacteria involved in chemoheterotrophy had the predominant abundance among the four microbial groups, followed by those related to fermentation function. Based on the whole AS community, the relative abundance of chemoheterotrophic functional microorganisms in SY was much lower than that in other cities, which may be due to the low concentration of organic matter of the influent wastewater in SY (Figure 8a). Although the definitions for core microorganisms and abundant microorganisms are similar, it is worth noting that more core bacteria were related to WWTP nitrogen removal processes (ammonia oxidation and nitrite oxidation), especially those in BJ, CD, CQ, JN, and WX (Figure 8b). In contrast, bacteria with chemoheterotrophic function were obtained with higher abundance in the abundant community (Figure 8d). Additionally, compared to the other three groups, the relative abundance of rare microorganisms involved in sulfur respiration and sulfate respiration functions was higher in most of the sampled cities. This finding supports the point that rare sub-communities were primarily involved in sulfur cycling [4] (Figure 8c).

The average rrn copy number of the whole community was detected to positively correlate (Spearman, p < 0.05) with chemoheteritrophy, fermentation, and nitrogen respiration (Figure 8a). Such positive correlations were also observed between the average rrn copy number of the core community and fermentation and between the average rrn copy number of the rare community and chemohetrophy (Figure 8b,c). Nevertheless, there were significantly negative correlations between the average rrn copy number of the whole, the core, and the rare community and nitrite oxidation, suggesting that more K-strategists participated in the nitrification processes. This finding is reasonable based on our previous study, which showed that nitrite oxidation bacteria (NOB) in WWTPs prefer longer SRT and oligotrophic environments [31]. Moreover, Vuono et al. [26] found that when an r-strategist was predominant, the denitrification function of the ecosystem weakened. Notably, no significant correlations were recognized between the average rrn copy number of the abundant community and its potential functions. It suggests that the alteration of ecological strategies has no significant effects on the potential functions performed by the abundant community, thereby contributing to the functional stability of WWTPs. It also suggests that increasing nutrient levels or COD load may be an effective way to promote the abundance of the core community in WWTPs.

4. Conclusions

Our results showed the average rrn copy number of the AS microbial community across China was 2.25 ± 0.12. The core microorganisms had the highest average rrn copy numbers compared to the other three groups, indicating a preference for r-strategy with rapid reproduction, growth rates, and high resource availability. Variations in average rrn copy numbers at the city level suggested diverse strategies and adaptions of the microbial community to local conditions. The nutrient level of AS was positively correlated with average rrn copy numbers, suggesting that microorganisms in the community will evolve to the r-strategist when the available resources are abundant. In contrast, long SRT favored K-strategists. Many more r-strategies reduced both phylogenetic and taxonomic diversity because of the bacterial competition. Homogeneous selection and dispersal limitation predominated assembling mechanisms for AS microbial communities, and more stochastic processes were observed in the communities with higher average rrn copy numbers. Furthermore, microbes with chemoheterotrophic and fermentative functions predominated, and the rrn copy numbers of core and high-abundance communities remained unaffected by chemoheterotrophic microorganisms. These findings provide insights into the life strategies of different AS microbial communities and their responses to resource availability and environmental stress, offering guidance for optimizing wastewater treatment processes. Further research should corroborate how rrn copy numbers of different AS microbial communities vary over time, and their relationship between resilience and resistance of AS microbial communities should be explored so that the stability of the system can be predicted based on the rrn copy number.