Terminal restriction fragment length polymorphism is an "old school" reliable technique for swift microbial community screening in anaerobic digestion

Abstract

The microbial community in anaerobic digestion has been analysed through microbial fingerprinting techniques, such as terminal restriction fragment length polymorphism (TRFLP), for decades. In the last decade, high-throughput 16S rRNA gene amplicon sequencing has replaced these techniques, but the time-consuming and complex nature of high-throughput techniques is a potential bottleneck for full-scale anaerobic digestion application, when monitoring community dynamics. Here, the bacterial and archaeal TRFLP profiles were compared with 16S rRNA gene amplicon profiles (Illumina platform) of 25 full-scale anaerobic digestion plants. The α-diversity analysis revealed a higher richness based on Illumina data, compared with the TRFLP data. This coincided with a clear difference in community organisation, Pareto distribution, and co-occurrence network statistics, i.e., betweenness centrality and normalised degree. The β-diversity analysis showed a similar clustering profile for the Illumina, bacterial TRFLP and archaeal TRFLP data, based on different distance measures and independent of phylogenetic identification, with pH and temperature as the two key operational parameters determining microbial community composition. The combined knowledge of temporal dynamics and projected clustering in the β-diversity profile, based on the TRFLP data, distinctly showed that TRFLP is a reliable technique for swift microbial community dynamics screening in full-scale anaerobic digestion plants.

Figure 1

Spearman’s Rank correlation for the H₀, H₁ and H₂ Hill numbers. The richness (H₀), exponential of the Shannon diversity index (H₁) and the Inverse Simpson index (H₂) are included. Correlation between the Illumina and TRFLP data for H₀ (P = 0.87) was not significant, yet, for H₁ (ρ = 0.37 & P = 0.033) and H₂ (ρ = 0.42 & P = 0.015) a significant positive correlation was observed. The grey zone represents the 95% confidence interval.

Figure 2

Spearman’s Rank correlation for the community organisation (Co) and Pareto values. The Co was calculated based on the Lorenz distribution curves^,, and the Pareto value was calculated as the total relative abundance of the 20% most abundant OTUs or TRFs^,. A significant positive correlation between the Illumina and TRFLP data was observed for Co (ρ = 0.45 & P = 0.009) and Pareto (ρ = 0.56 & P = 0.0009). The grey zone represents the 95% confidence interval.

Figure 3

Non-metric distance scaling (NMDS) analysis of the Bray-Curtis dissimilarity distance indices of the (a) Illumina (stress = 0.09), bacterial TRFLP (stress = 0.24), and (c) archaeal TRFLP (stress = 0.17) at OTU/TRF level. The four different clusters Cluster 1 (red), Cluster 2 (blue), Cluster 3 (green), and Cluster 4 (orange) are distinguished, and the ellipses represent the 95% value of the standard error of the average value for each cluster.

Figure 4

Canonical correspondence analysis of the (a) Illumina, (b) bacterial TRFLP and (c) archaeal TRFLP profile of each sample at OTU/TRF level. The PERMANOVA analysis (9999 permutations) identified the relationship between the diversity and operational parameters on community composition, and significant (P < 0.05) correlations are presented by the arrows. The four different clusters Cluster 1 (red), Cluster 2 (blue), Cluster 3 (green), and Cluster 4 (orange) are distinguished. TAN = total ammonia nitrogen.

Figure 5

Network of co-occurring (a) OTUs of the Illumina and (b) TRFs of the bacterial data, based on the Spearman correlation analysis. A connection stands for a strong positive (blue) or negative (red) significant (Spearman’s ρ > 0.5, P < 0.001) correlation. The size of each node is proportional to the number of connections (Normalised degree).

Figure 6

Betweenness centrality and normalised degree, calculated from the co-occurrence network correlations for the Illumina and bacterial TRFLP data. ***P < 0.001.