Nematode grazing promotes bacterial community dynamics in soil at the aggregate level

Abstract

Nematode predation has important roles in determining bacterial community composition and dynamics, but the extent of the effects remains largely rudimentary, particularly in natural environment settings. Here, we investigated the complex microbial–microfaunal interactions in the rhizosphere of maize grown in red soils, which were derived from four long-term fertilization regimes. Root-free rhizosphere soil samples were separated into three aggregate fractions whereby the abundance and community composition were examined for nematode and total bacterial communities. A functional group of alkaline phosphomonoesterase (ALP) producing bacteria was included to test the hypothesis that nematode grazing may significantly affect specific bacteria-mediated ecological functions, that is, organic phosphate cycling in soil. Results of correlation analysis, structural equation modeling and interaction networks combined with laboratory microcosm experiments consistently indicated that bacterivorous nematodes enhanced bacterial diversity, and the abundance of bacterivores was positively correlated with bacterial biomass, including ALP-producing bacterial abundance. Significantly, such effects were more pronounced in large macroaggregates than in microaggregates. There was a positive correlation between the most dominant bacterivores Protorhabditis and the ALP-producing keystone 'species' Mesorhizobium. Taken together, these findings implicate important roles of nematodes in stimulating bacterial dynamics in a spatially dependent manner.

Mud, microbes, and macrofauna: seasonal dynamics of the iron biogeochemical cycle in an intertidal mudflat

“…This finding corroborates observations 540 primarily based from direct species counts and identification (Montagna et al, 1989). Nematode 541 abundance and grazing activity have also been observed to increase bacterial activity and 542 diversity in terrestrial sediments (Jiang et al, 2017). Nematodes play an important role in grazing 543 of bacteria and other microbial eukaryotes in sediments (Pascal et al, 2008), and potentially play 544 an important role in controlling iron biogeochemical dynamics.…”

Root ethylene mediates rhizosphere microbial community reconstruction when chemically detecting cyanide produced by neighbouring plants

“…Microbial communities can harbour keystone taxa, whose removal can cause a dramatic shift in microbiome structure and functioning [57,60]. Keystone taxa in network analysis can be computationally identified as hubs with a high within-module degree Zi (Zi ≥ 6.2 indicates that the nodes are "well-connected" to other nodes in the module) [59,[61][62][63]. In this study, bacterial module hubs affiliated with Dokdonella (OTU1, H1 belonging to Gammaproteobacteria), Catenulispora (OTU235, H2 belonging to Actinobacteria) and Pseudolabrys (OTU73, H3, belonging to Alphaproteobacteria) were respectively identified in the cassava, intercropped peanut and monocropped peanut rhizosphere samples (CRi, PRi and PRm) ( Table 3, Fig.…”

“…1a). Soil that tightly adhered to the plant roots was defined as rhizosphere soil [63]. Due to the small amount of rhizosphere soil per plant, we randomly selected six plant roots that were pooled into a single rhizosphere soil sample.…”

“…The topological role of each node was determined based on two properties: the within-module connectivity (Zi) and the among-module connectivity (Pi) [61]. All species were sorted into four subcategories on the basis of these simple criteria: peripherals (nodes in the modules with few outside connections, Zi < 2.5 and Pi < 0.62), connectors (nodes that connect modules, Pi > 0.62), module hubs (highly connected nodes within modules, Zi > 2.5) and network hubs (highly connected nodes within the entire network, Zi > 2.5 and Pi > 0.62) [59,63,82,84]. Correlation networks were visualized using Gephi software [85].…”

“…In this study, we used Shannon and Chao 1 indices to characterize bacterial ɑ-diversity [90], and the data were subjected to ANOVA using Tukey's HSD test at P < 0.05. To assess the influence of the different experimental factors on β-diversity, we calculated Bray-Curtis distances and then performed a canonical analysis of principal coordinates (CAP) constrained by the factor of interest and conditioned by the remaining variables [63,91]. We employed the "capscale" and "permutest" permutationbased testing functions for the CAP analysis and the calculation of the significance values, respectively [63].…”