Comparing the Efficacy of MALDI-TOF MS and Sequencing-Based Identification Techniques (Sanger and NGS) to Monitor the Microbial Community of Irrigation Water

Abstract

In order to intensify and guarantee the agricultural productivity and thereby to be able to feed the world's rapidly growing population, irrigation has become very important. In parallel, the limited water resources lead to an increase in usage of poorly characterized sources of water, which is directly linked to a higher prevalence of foodborne diseases. Therefore, analyzing the microorganisms or even the complete microbiome of irrigation water used for food production can prevent the growing numbers of such cases. In this study, we compared the efficacy of MALDI-TOF Mass spectrometry (MALDI TOF MS) identification to 16S rRNA gene Sanger sequencing of waterborne microorganisms. Furthermore, we analyzed the whole microbial community of irrigation water using high-throughput 16S rRNA gene amplicon sequencing. The identification results of MALDI-TOF MS and 16S rRNA gene Sanger sequencing were almost identical at species level (66.7%; 64.3%). Based on the applied cultivation techniques, Acinetobacter spp., Enterobacter spp., Pseudomonas spp., and Brevundimonas spp. were the most abundant cultivable genera. In addition, the uncultivable part of the microbiome was dominated by Proteobacteria followed by Actinobacteria, Bacteroidota, Patescibacteria, and Verrucomicrobiota. Our findings indicate that MALDI-TOF MS offers a fast, reliable identification method and can act as an alternative to 16S rRNA gene Sanger sequencing of isolates. Moreover, the results suggest that MALDI-TOF MS paired with 16S rRNA gene amplicon sequencing have the potential to support the routine monitoring of the microbiological quality of irrigation water.

Keywords: 16S rRNA gene amplicon sequencing; MALDI-TOF MS; Sanger sequencing; irrigation water; microbial monitoring.

Figure 1

Relative abundance of ASVs regarding each irrigation water sample. ASVs are shown on phylum level.

Figure 2

Taxonomic distribution of the phylogenetic groups at phylum level of irrigation water samples shown by combining Hierarchical Clustering and Heatmap visualization.

Figure 3

Relative abundance of the 30 most abundantly occurring bacterial genera in the irrigation water samples. The rest of the taxa merged into the group of others.