Protist feeding patterns and growth rate are related to their predatory impacts on soil bacterial communities

Abstract

Predatory protists are major consumers of soil micro-organisms. By selectively feeding on their prey, they can shape soil microbiome composition and functions. While different protists are known to show diverging impacts, it remains impossible to predict a priori the effect of a given species. Various protist traits including phylogenetic distance, growth rate and volume have been previously linked to the predatory impact of protists. Closely related protists, however, also showed distinct prey choices which could mirror specificity in their dietary niche. We, therefore, aimed to estimate the dietary niche breadth and overlap of eight protist isolates on 20 bacterial species in plate assays. To assess the informative value of previously suggested and newly proposed (feeding-related) protist traits, we related them to the impacts of predation of each protist on a protist-free soil bacterial community in a soil microcosm via 16S rRNA gene amplicon sequencing. We could demonstrate that each protist showed a distinct feeding pattern in vitro. Further, the assayed protist feeding patterns and growth rates correlated well with the observed predatory impacts on the structure of soil bacterial communities. We thus conclude that in vitro screening has the potential to inform on the specific predatory impact of selected protists.

Keywords: in vitro assay; dietary niche; microbes; microcosm; predation; soil.

Figure 1.

Heatmap of the protist population density on each bacterial isolate representing the feeding patterns at days 3 (panel A) and 5 (panel B) after inoculation. The protist density has been scaled per row to facilitate comparison; each co-culture was set in triplicates (N = 3). The y-axis is ordered according to similarities between protist feeding patterns (Euclidean distance of the achieved protist density on each bacterium). The x-axis is fixed with the bacteria grouped per phylum. Orange colors correspond to negative values, i.e. lower density compared to average population density, per protist, and blue colors correspond to positive values, i.e. higher density compared to average population density, per protist. Asterisks highlight significantly higher/lower protist densities compared to the control with no added bacterial cells: ‘*’, ‘**’, ‘***’ indicate P <0.05,  P < 001 and P < 0.001 respectively.

Figure 2.

Visualization of the effect of each protist treatment on the bacterial community composition in a soil microcosm. The visualization is based on a Principal Coordinate Analysis (PCoA) on the Bray–Curtis dissimilarity between samples.

Figure 3.

Relation between the dietary niche breadth (coefficient of variation at days 3 and 5, A and B panel respectively) and the magnitude of the predatory impact on the bacterial prey community (Bray–Curtis dissimilarity of each treatment relative to control and NTI). The y-axis on the left gives the values for the Bray–Curtis to control dissimilarity (dark-brown dot and line) and the y-axis on the right gives the values for the NTI (blue dots and line). Coefficient estimates are given next to the line. Statistical results of the linear model analysis are given in Table S10.

Figure 4.

Principal Component Analysis using the pair-wise Euclidean distances of protist traits (Volume, Phylogenetic distance, and Growth rate; blue color), pair-wise Euclidean distances between protist feeding pattern (plate assay, at day 3, yellow color) and the Bray-Curtis dissimilarity between bacterial community composition (soil microcosm, red-brown color). Each dot represents a protist pair such as P33-S24D2, P33-P147, or S24D2-C5D3; there is a total of 28 pairs.