Bacterial community composition
In order to study the microbial structure of the biofilm and activated sludge that were developing in the IFAS-MBSBBR reactor, a total of 15 samples were taken at intervals during an experiment lasting 573 days. The microbiome of both environments was described at the phylum and genus levels. A total of 26 bacterial phyla and 783 bacterial genera were identified. The most numerous phyla and genera in the biofim and activated sludge samples are presented in in Figs. 1 and 2. Both in the biofilm and the activated sludge, the most numerous phyla were Proteobacteria, with respective mean abundances of 39.3% ± 9.0 and 40.8% ± 8.2, and Bacteroidota, with respective mean abundances of 14.2% ± 4.9 and 26.1% ± 13.7. Additionally, the phylum Chloroflexi was rather abundant in the biofilm (with a mean abundance of 13.9 ± 8.1), while Actinobacteriota and Patescibacteria were relatively abundant in the activated sludge (with mean abundances of 9.0% ± 9.6 and 7.5% ± 8.1, respectively). STAMP analysis identified significant overrepresentations of Chloroflexi, Acidobacteriota, and Nitrospirota in biofilm and of Firmicutes in activated sludge.
Relative abundance (%) of the most prevalent phyla in the biofilm and activated sludge samples in general, as the mean values of relative abundance from all biofilm and activated sludge samples (A), and in each individual sample (B). The graph shows only phyla which contributed more than 0.5% to the total bacterial community in at least one sample. The abundance of the remaining phyla was summed and labelled as “other”.
Relative abundance (%) of the most prevalent genera in the biofilm and activated sludge samples in general, as the mean values of relative abundance from all biofilm and activated sludge samples (A), and in each individual sample (B). The graph shows only genera which contributed more than 1.5% to the total bacterial community in at least one sample. The abundance of the remaining genera was summed and labelled as “other”.
In both environments, the abundances of various groups of bacteria changed over time. In the biofilm, the abundance of Proteobacteria and Actinobacteria gradually decreased, while that of Chloroflexi increased. In the activated sludge, the changes in abundance were larger and more rapid, and the abundance of Bacteroidota changed to the largest extent, ranging from 12.7% after 42 days of reactor operation to 52.3% after 110 days, when it was the predominant phylum. The abundance of Patescibacteria also changed substantially: its abundance was highest on the 78th, 205th and 447th days of the process, reaching values of 20.1%, 11.0%, and 7.2%, respectively. Similar changes took place in the abundance of Armatimonadota, which reached 11.4% and 7.6% on the 547th and 573th day, but did not exceed 0.1% in the samples taken at other times.
At the genus level, the less abundant genera (each < 1.5% of the total bacterial community) combined to constitute the largest shares in all samples of biofilm and activated sludge samples (mean abundance of 45.6% ± 5.8 and 30.5% ± 6.0, respectively). Initially, Ornithinibacter was relatively abundant in the biofilm, which is the reason for its fairly large mean abundance of 4.3% ± 5.3%. Over time, however, the abundance of this group decreased substantially, and at the end of the process, it was only 0.3%. Similarly, the abundance of Rhizorhapis was 13.92% in the first sample, but then it decreased and this genus was not detected after the 205th day. The changes in the abundance of Nitrospira and Candidatus Competibacter are also noteworthy, first increasing and then decreasing. Nitrospira was most abundant in the sample from 447th day (5.7%), and Candidatus Competibacter, in the sample from 110th day (6.4%). The abundance of the remaining genera did not exceed 5% at any time during this study.
In the samples of activated sludge, the abundance of Ornithinibacter also decreased significantly at the beginning of the experiment (from 23.0% in the first sample and 12.5% on the 78th day to values below 3% in subsequent periods). Generally, the abundances of individual genera changed more rapidly in the activated sludge than in the biofilm. There were also rapid decreases and increases in the abundance of many groups of bacteria in the following periods, particularly in the case of uncultured Saccharimonadales and Zoogloea. Figure 3 shows groups of bacteria that differed significantly between biofilm and sludge samples. Denitratisoma, Nitrospira, Candidatus Competibacter, Dechlorosoma, Candidatus Accumulibactrer, and Kouleothrix were significantly more abundant in the biofilm than in the biomass, while Zooglea, uncultured Saccharimonadales, Rhodobacter, and Ottowia were significantly less abundant in the biofilm.
Mean proportions of microbial phyla (A) and genera (B) that differed significantly between biofilm (red) and sludge (blue) samples. Plots were made using Statistical Analysis of Metagenomic Profiles (STAMP) software. P-values and confidence intervals were calculated with White’s nonparametric t-test.
Bacterial diversity
Bacterial community indices were estimated using the EZBioCloud platform (Table 1). The average Good’s coverage of all samples was 99.75% ± 0.047%, indicating that the sequencing coverage was very high. The total number of OTUs differed between samples and types of biomass. The mean number of OTUs was 1614 ± 141 for biofilm and 993 ± 109 for activated sludge. The Chao1 index was used to evaluate community richness, i.e., the number of species in the biofilm and activated sludge communities, and the Shannon index was used to measure community diversity, taking into account both the abundance and the evenness of the species. The mean values of these indices indicated that the biofilm community was richer and more diverse than the activated sludge community (Chao1: 1734.64 ± 138.59 vs. 1105.72 ± 138.59; Shannon: 5.34 ± 0.23 vs. 4.27 ± 0.41). The differences between communities were all statistically significant (P < 0.05).
Figure 4 shows the results of beta diversity analysis based on the Bray–Curtis dissimilarity. Principal Coordinates Analysis showed that the biofilm and activated sludge samples grouped into two separate clusters, although the distances between individual samples were quite large. Hierarchical analysis indicated the development of biofilm and activated sludge was independent and confirmed the distance of the differences between these two types of biomass.
Hierarchical clustering and Principal Coordinates Analysis plot of biofilm (B) and sludge (S) samples.
To model interactions and relationships between bacteria in the biofilm and activated sludge, co-occurrence network analysis was used. In the present study, two networks were created that represent the co-occurrence of genera in the biofilm and activated sludge. In Figs. 5 and 6, the color of each node is based on its modularity class parameter, and its size is based on its betweenness centrality. The basic parameters characterizing both networks are presented in Table S1. In general, the biofilm network had more connections between nodes than the activated sludge network, and the distance between nodes was smaller in the biofilm network, indicating that the microorganisms creating the biofilm are more closely related and have more relationships between them. Both networks had the same number of nodes (83), but the biofilm network had more edges (connectors between nodes symbolizing co-occurrence). In both networks, the number of positive associations was slightly higher than that of negative associations, accounting for 55% of the total number of connections. The mean clustering coefficient (i.e., the ratio between the observed and the maximum possible number of links between a node and its neighbors) was higher for the biofilm than for the activated sludge (0.556 vs. 0.432). Similarly, the network density, which is the ratio between the observed number edges and the maximum possible number of them, was higher for the biofilm (0.073 vs. 0.05). The network diameter (the distance between the two most distant nodes) was shorter for the biofilm than for the biomass (6 vs. 7). Likewise, the average path length, which is the number of edges in the shortest path between pair of nodes, was shorter in the biofilm network than in the activated sludge network (1.984 vs. 2.241). The mean node degree (the number of edges between one node and other nodes in the network) was greater in the biofilm network than in the activated sludge network (6.012 vs. 4.12). Node degree ranged from 1 to 31 in the biofilm network and from 1 to 23 in the activated sludge network. In the biofilm network there were four nodes with the highest degrees (≥ 30) that can be considered hub nodes: Diaphorobacter, Rhizorapis, Mesorhizobium, and Pseudoxanthomonas. These microorganisms had 61.5% positive and 38.5% negative connections with other microorganisms. Interestingly, although the abundance of Mesorhizobium and Pseudoxanthomonas was low (not exceeding 1.5% of the total bacterial community in any sample) they had positive associations with highly abundant bacteria, e.g., Ornithinibacter. The activated sludge network also had 4 hub nodes (with node degree ≥ 20): Nocardioides, Gemmatimonas, Leptothrix and Rhizorhapis. These hub nodes were connected to other nodes by similar amounts of positive and negative edges (51.8% and 48.2%, respectively). The size of the nodes in the created networks is proportional to their betweenness centrality (a parameter that indicates the frequency of occurrence of a particular node on the paths between two other nodes). High values of betweenness centrality indicate that a node has a central location in a network, while low values indicate that it has a peripheral location13. Microorganisms with high betweenness centrality play key roles and act like bridges between other bacteria in the network. In the biofilm network, Paracoccus, Phaeodactylibacter, and Pseudoxanthomonas had the highest values of betweenness centrality, whereas in the activated sludge network, Dongia, Diaphorobacter, and Rhizorhapis had the highest values.
Network of the biofilm microbiome with nodes representing taxa at the genus level or efficiencies of pollutant removal and edges representing correlations (green edges—positive correlation; red edges—negative correlation).
Network of the activated sludge microbiome with nodes representing taxa at the genus level or efficiencies of pollutant removal and edges representing correlations (green edges—positive correlation, red edges—negative correlation).
The networks were constructed with additional nodes representing the efficiency of pollutant removal processes, i.e., removal of organic and phosphorus compounds, as well as denitrification, ammonification, and nitrification. In the biofilm network, the efficiencies of phosphorus compound removal and of nitrification had the most associations with microbial nodes (9 positive and 2 negative, and 6 positive and 4 negative, respectively). The efficiency of phosphorus removal was positively associated with the abundance of Candidatus Accumulibacter, Dechlorosoma, Thauera, and uncultured Saccharimonadales, while nitrification was positively associated with the abundance of taxa such as Nitrosomonas, Sphingomonas, and Thermomonas. The remaining efficiencies of pollutant removal had no or only 1–2 connections with microbial nodes. In the activated sludge network, in contrast, all efficiency nodes were connected with those of microbes, with degree ranging from 2 to 9. The nitrification and ammonification efficiency nodes had the highest degree and were positively associated with, for example, Nocardioides, Rhodobacter, and Sphingomonas. Organic compound removal efficiency was positively associated with Blastocatella, Ornithinibacter, and Terrimonas, whereas in the biofilm network, it had no edges.
Source: Ecology - nature.com
