Extra benefit of microalgae in raw piggery wastewater treatment: pathogen reduction

Abstract

Background: Monitoring microbial communities especially focused on pathogens in newly developed wastewater treatment systems is recommended for public health. Thus, we investigated the microbial community shift in a pilot-scale microalgal treatment system for piggery wastewater.

Results: Microalgae showed reasonable removal efficiencies for COD and ammonia, resulting in higher transparency of the final effluent. Metagenome and microbial diversity analyses showed that heterotrophic microalgal cultivation barely changed the bacterial community; however, the mixotrophic microalgal cultivation induced a sudden change. In addition, an evaluation of risk groups (RGs) of bacteria showed that raw piggery wastewater included abundant pathogens, and the microalgal treatment of the raw piggery wastewater decreased the RG2 pathogens by 63%. However, co-cultivation of microalgae and the most dominant RG2 pathogen, Oligella, showed no direct effects between them.

Conclusions: Thus, a microbial interaction network was constructed to elucidate algae-bacteria interrelationships, and the decrease in Oligella was indirectly connected with microalgal growth via Brevundimonas, Sphingopyxis, and Stenotrophomonas. In a validation test, 3 among 4 connecting bacterial strains exhibited inhibition zones against Oligella. Therefore, we showed that microalgal wastewater treatment causes a decrease in RG2 bacteria, which is an indirect impact of microalgae associated with bacteria. Video abstract.

Keywords: Metagenome analysis; Microalgae; Network analysis; Pathogens; Piggery wastewater.

Fig. 1

Methodology and results of piggery wastewater treatment using microalgae. A Experimental scheme of wastewater treatment, B changes of ammonia concentration, C chemical oxygen demand (COD) with 95% confidence intervals, D absorbance, E oxygen-reduction potential (ORP), F pH, and G temperature.

Fig. 2

Results of next-generation sequencing in amplicon sequence variant (ASV) reads of control and microalgae-treated group. A Relative abundances of the 30 most abundant genera in control and treatment; and box charts of various diversity indices for B Shannon index, C Simpson index, D Inverse Simpson index, E Menhinick’s index, F species richness, and G species evenness at significance level of *p < 0.05 and **p < 0.01

Fig. 3

Ordination diagrams of environmental factors using A principal coordinate analysis (PCoA) and B distance-based redundancy analysis (db-RDA) based on canonical analysis of principal coordinate (CAP) plots using Bray–Curtis distance. Each graph shows the difference between the microalgae-wastewater treatment group and the control group

Fig. 4

A Subtotal relative abundances of Risk Group 2 (RG2) (429 ASVs, 28 genera) in the control and microalgal treatment. B Relative abundances of the four most abundant genera in RGs of the control group and C microalgal treatment group

Fig. 5

A Experimental schemes to examine the relationship between Coelastrella sp. and Oligella sp. B Coelastrella-Oligella co-cultivation results in copy numbers of total bacteria, that of Oligella, and biomass of Coelastrella, identified by global 16S rRNA qPCR, Oligella-specific 16S qPCR, and dry cell weight, respectively. C Relative abundance changes of Oligella by time in the co-cultivation test

Fig. 6

A Results of disk diffusion test for direct interaction between Coelastrella sp. and Oligella sp. B A network of amplicon sequencing variants (ASVs) and environmental factors in pilot-scale wastewater treatment and C a core network of abundant species (over 0.2%) filtered with statistical significance at p_BH < 0.001 and |ρ| > 0.88. D Results of disk diffusion tests for interaction between Oligella sp. and four bridge bacteria identified by network analysis. E Inhibition zones without disc