Analysis of the granule size distribution of sludge from different reactors showed that the type of wastewater was the major factor affecting the difference in granule size (Fig. 1A). Granules from the reactor treating SPW (AnS_b and AnS_u) were smaller than those from the reactors treating EPW (AnE_b and ICE_b). In the reactor treating SPW, midsize granules with diameters between 330 and 1,040 µm comprised more than 70% of the sludge; the proportions of the sludge comprising small (0-330 µm) and large (1,040-3,280 µm) granules were less than 10% and 20%, respectively. In the reactors treating EPW, the sludge was mainly large granules (approximately 50%), and the small granules comprised more than 20%. Furthermore, granules from the AnaEG reactor (AnE_b) were smaller than those from the IC reactor (ICE_b), although both reactors were used to treat EPW. The average granule diameters in different reactors and wastewaters were consistent with the above results; the average granule diameter in the AnaEG reactor treating SPW was approximately 900 µm, but the average was approximately 1,200 µm in the IC reactor treating EPW (Fig. 1B). In other words, the AnaEG reactor treating SPW formed smaller granules than the IC reactor treating EPW.
As observed by SEM, there were distinct differences in the surface appearance and the inner microstructure of AGS in different wastewaters and reactors (Fig. 2). In the AnaEG reactor treating SPW, the AGS consisted of small and smooth particles. Filamentous- and bacillus-shaped microorganisms predominated near the surface in SPW (surface, AnS), whereas the bacillus-shaped microorganisms intertwined randomly throughout the cross-section (cut plane, AnS). Moreover, a small bulge was observed on the surface of the AGS, and numerous bacillus- and filamentous-shaped bacteria constituted the surface matrix (surface, AnE). In the AnaEG reactor employed for EPW treatment, cocci-shaped microorganisms of many different sizes were widely distributed throughout the cross-section (cut plane, AnE). Furthermore, although both AnaEG and IC reactors were used to treat EPW, the granule morphology and microbial composition in the two reactors were quite different. AGS in the IC reactor consisted of large elliptical particles with uneven surfaces, but no obvious bulge was observed. Bacillus- and filamentous-shaped microorganisms were located on the surface of the AGS (surface, ICE). In the inner layer, there was an observable niche formed by bacillus-shaped microorganisms surrounded by many filamentous-shaped microorganisms (cut plane, ICE). The results suggested that the type of wastewater affected the appearance and morphology of the AGS, but the type of reactor was also an important factor, even for the same wastewater.
The alpha diversity indices are displayed in Table 1 and Fig. 3. The Good’s coverage of all samples was above 0.996, indicating that the current sequencing depth accurately reflected the microbial community in the samples. The diversity of the microbial community differed between the two types of reactors, but no significant difference was detected between the two types of wastewater. The Shannon index of the AnaEG reactor was 6.19, which was significantly higher than that of the IC reactor (5.67), even when processing the same wastewater (EPW) (data not shown). However, no difference was observed between the SPW and EPW (Fig. 3A). The number of species observed in the AnaEG reactor was 538, but only 459 were observed in the IC reactor, which agreed with the results of the Shannon index (Fig. 3D). However, no significant differences were observed in the Chao1 (Fig. 3B) and Simpson (Fig. 3C) indices. These results indicated that the AnaEG reactor possessed a higher number of species and greater species diversity compared to the IC reactor.
Table 1 . Alpha diversity index of the different AGS samples.
WastewaterSample IDShannon indexChao1SimpsonObserved speciesGood's coverageSPWAnS_b6.28605.610.975580.996AnS_u6.18579.430.975250.997EPWAnE6.12607.960.975320.997ICE_b5.83585.710.964750.996ICE_u5.5544.150.934430.996PCoA, based on an unweighted UniFrac distance matrix, detected similar microbial community structures in the lower and upper sections of the same reactor, and different reactors and wastewaters shaped the specific microbial community structure (Fig. 4A). In general, PC1 contributed 80.9% of the interpretation of the overall microbial distribution, and samples from different wastewaters were grouped far apart along the PC1 axis. Hence, substrate differences were the major reason for the formation of a specific microbial community structure. In addition, samples from different reactors were separated from each other along the PC2 axis (contributing 12.2% to the total variation); hence, the type of reactor also affected the microbial composition. The UPGMA tree further confirmed that the largest genetic distances existed between samples from different wastewaters, but more similar phylogenetic relationships were present in the same reactor type, even when it was used to treat different wastewaters (Fig. 4B). Therefore, both wastewater and reactor type could affect the microbial community structure, but the former was the major determinant.
Venn diagram analysis was carried out to further dissect the microbial composition differences between samples from different reactors and wastewaters (Fig. 5A). Of 1,035 OTUs, 110 were shared members that accounted for 50.66% relative abundance of the total OTUs, although the percentage of shared OTUs only accounted for 10.63% of the total OTUs. These results illustrated that there were many common microorganisms in the two kinds of wastewaters and that the OTUs were concentrated in a few microbial populations. AnE_b possessed 77 unique OTUs, followed by AnS_b (26) and ICE_b (20), whereas AnS_u (16) and ICE_u (7) contained the fewest unique OTUs. Moreover, the percentage and relative abundance of unique OTUs were highest in AnE_b, and this bottom region contained more unique OTUs than the upper region of the same reactor (Fig. 5B). This implies that the AnaEG reactor supported more specific microbes, of which Proteobacteria (19.6%), Chloroflexi (9.4%) and Euryarchaeota (8.7%) constituted the most predominant phyla among the shared OTUs. Moreover, many unclassified microorganisms (9.4%) existed in these samples (Fig. 5C). At the genus level (Fig. 5D), Geobacter (13.0%), which can couple ethanol, acetate, formate or lactate oxidation with the reduction of iron or manganese oxides [23], was the most predominant genus among the shared OTUs. Syntrophobacter (2.4%) and Syntrophorhabdus (1.3%) also showed high relative abundances. The former has the ability to degrade propionate and fumarate [24] and has been thought to be a species that can degrade toxic organic matter, such as quinoline [17]. Syntrophorhabdus is a potential syntrophic phenol-degrading bacterium [25]. Some methanogens, such as Methanosaeta (5.4%) and Methanobacterium (3.1%), which are acetoclastic [26] and hydrogenotrophic methanogens [27], respectively, also constituted high proportions of the shared OTUs.
The taxonomic composition of predominant microbial populations revealed that different reactors and wastewaters supported correspondingly different functional microbial communities. In the SPW and EPW samples, 62.9% and 83.9% of the sequences, respectively, were identified at the phylum level (Fig. 6A). The most predominant member in samples from EPW was Proteobacteria, with an average relative abundance of 35%. Its relative abundance was higher in the upper region of the IC reactor (ICE_u = 42.6%) than in the bottom region (ICE_b = 30.7%). However, this phylum constituted only 13.5% in samples of SPW, and no obvious difference was detected between the bottom and upper regions. Chloroflexi also constituted a high proportion (average = 15.5%) in all samples, but Bacteroidetes was relatively more abundant in ICE_b (18.8%) than in other samples (average = 5.9%). The abundance of Firmicutes was higher in the SPW samples (average = 9.7%) than in the EPW samples (average = 2.4%). Other phyla, including Cloacimonetes, Ignavibacteriae, and Thermotogae, were dominant microbial community members in SPW samples, but they were rare members in EPW samples. In contrast, bacteria belonging to the phyla Acidobacteria, Aminicenantes, Synergistetes and Spirochaetes were the dominant populations in the EPW samples but were only detected at low abun- dances in the SPW samples. Additionally, more Euryarchaeota were detected in EPW samples (average = 12.4%) than in samples from SPW (average = 3.5%).
At the genus level (Fig. 6B), Geobacter was the most predominant member in EPW samples, with an average relative abundance of 19.7%, but only comprised 3% of the population in SPW samples. Syntrophobacter (average = 5.5%) and Syntrophorhabdus (average = 3.7%) were also more abundant in the EPW samples than in SPW. Therefore, although the Venn diagram indicates that these three genera were of high relative abundance among the shared species, they were mainly present in the EPW samples. Notably, Longilinea (average = 2.0%), a filamentous bacterium of the phylum Chloroflexi [28] capable of carbohydrate and amino acid degradation [29], was the predominant genus in EPW samples, but it was not detected in SPW samples. In addition, the hemicellulose-degrading phylum Prevotella constituted a high proportion of the bacteria in ICE_b (7.6%); however, it was rarely found in other samples (average < 0.5%). Conversely, higher relative abundances of Candidatus, Cloacamonas and Desulfovibrio were observed in samples of SPW compared to EPW, and Mangrovibacterium was only detected in SPW samples (average = 1.7%). The percentage of unclassified genera in SPW (average = 75.6%) was higher than that in EPW (average = 44.2%). Even in the same wastewater (EPW), the proportion of unclassified genera in the AnaEG reactor was higher than that in the IC reactor, especially in the bottom section. There are many potential functional species that may exist amid these unclassified microorganisms. These results show that samples of EPW were predominated by more classified microorganisms than what was found in other samples, but the bottom area of the bioreactor supported more species with potential functional roles in industrial wastewater treatment, especially in the AnaEG reactor.
Methanogens constitute the majority of archaea in anaerobic bioreactors, and they play an important role in the anaerobic degradation of organic pollutants. Their abundance and composition in AGS should significantly affect the wastewater treatment efficiency. Hence, it is necessary to assess their population composition and abundance in different reactors and wastewaters. The average proportion of archaea was 12.5% in EPW samples but was only 3.5% in SPW samples. Their quantity in the upper area of the IC reactor was significantly higher than that in the bottom area (Fig. 7A). The composition of the methanogens also differed between the two reactors and wastewaters (Fig. 7B). In SPW samples, Methanosaeta (average = 2.7%) was the predominant methanogen, and the relative abundances of Methanobacterium, Methanolinea and Methanomassiliicoccus were less than 0.5%. In the EPW samples, Methanosaeta (7.1%) and Methanobacterium (5.0%) were relatively more abundant, while Methanolinea and Methanomassiliicoccus were not the major methane-producing archaea.
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