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The rhizosphere microbiome plays a key role in plant protection against soil-borne pathogens. Plant breeding for resistance against soil-borne pathogens can alter the rhizosphere microbiome. However, most studies have focused on bacterial and fungal communities, leaving the role of the virus and viroids unassessed. Here, we tested the influence of resistance breeding on the composition of rhizosphere viruses and viroids. By analyzing metatranscriptomes from the rhizosphere of common bean (Phaseolus vulgaris) cultivars with varying resistance to the soil-borne pathogen Fusarium oxysporum, we recovered sequences representing 78 and 23 novel populations of viruses and viroids, respectively. We compared the abundances of these infectious agents across the different cultivars and found that the Fusarium-resistant cultivar harbored >1.2 times more viroids and a more different composition of viroids and viruses than less resistant plants. Given their role in interfering with host metabolism and their potential influence on plant-fungi associations, our study suggests that changes in the rhizosphere infectome are an important consideration in breeding for resistance against soil-borne pathogens.

Code provided with the publication of Mendes et al "Impact of the fungal pathogen Fusarium oxysporum on the taxonomic and functional diversity of the common bean root microbiome"

Additional file 1. Text file. Supplementary table and figure legends.

Additional file 4. Figure S3. Relative pmoA gene abundance along the density gradient of the 13C- and unlabelledC-CH4 incubations in the pristine peat at days 8, 13, and 19 (mean ± s.d.; n=4 each). The pmoA gene relative abundance was calculated as the proportion of each fraction over the total sum of all fractions per sample. The arrows denote the “light” and “heavy” fractions where the 16S rRNA gene was amplified for Illumina MiSeq sequencing in the 13C-CH4 incubations.

Additional file 5. Figure S4. Mean relative abundance of the methanotroph-affiliated OTUs in the paddy soil, landfill cover soil, pristine/restored peatlands, and riparian soil based on the 16S rRNA gene sequences in the starting material and after the incubation with 13C-methane (“light” and “heavy” fractions). The numbers at the bottom of the bars denote the mean proportion (%) of the methanotroph-affiliated OTUs among the total 16S rRNA gene sequences. Abbreviations; S.M, starting material; L, “light” fraction; H, “heavy” fraction.

Additional file 7. Figure S6. Principal component analysis showing the clustering of the 16S rRNA gene sequences in the “light” and “heavy” fractions of the (a) paddy soil (orange, triangle), (b) landfill cover soil (purple, circle), (c) pristine peatland (light green, square), (d) restored peatland (dark green, square), and (e) riparian soil (blue, inverted triangle). All replicates (n=4) are given; in the incubation with the riparian soil, fractionation was unsuccessful for one replicate. Full colored and striped symbols represent the “light” and “heavy” fraction, respectively.

Additional file 6. Figure S5. Mean relative abundance of the methanotroph-affiliated OTUs in the pristine peatland after 8, 13, and 19 days incubation with 13C-methane (“light” and “heavy” fractions), based on the 16S rRNA gene sequences. The numbers at the bottom of the bars denote the mean proportion (%) of the methanotroph-affiliated OTUs among the total 16S rRNA gene sequences.

Additional file 2. Figure S1. The pmoA and 16S rRNA gene abundances in the starting material and after incubation in diverse environments (mean ± s.d.; n ≥ 4). The qPCR assay was performed in duplicate for each DNA extraction. The 16S rRNA and pmoA gene abundances for all samples were at least an order of magnitude higher than the lower detection limit of the qPCR assays. The upper and lower case letters indicate the level of significance (p

Additional file 3. Figure S2. Relative pmoA gene abundance along the density gradient of the 13C- and unlabelledC-CH4 incubations with the (a) paddy soil, (b) landfill cover soil, (c) restored peatland, (d) pristine peatland, and (e) riparian soil (mean ± s.d.; n=4 each). The results of the paddy soil (a; [2]) and the peatlands (c,d; [1]) were re-analysed for the present study. The pmoA gene relative abundance was calculated as the proportion of each fraction over the total sum of all fractions per sample. The density gradients of the 13C- and unlabelledC-CH4 incubations were compared to distinguish the “light” from the “heavy” fraction in the 13C-CH4 incubation. The arrows denote the “light” and “heavy” fractions where the 16S rRNA gene was amplified for Illumina MiSeq sequencing in the 13C-CH4 incubations.

Additional file 9. Figure S8. Co-occurrence network analysis of methane hotspots derived from the 13C- and unlabelledC-DNA. The corresponding topological parameters of the networks are provided in Table 2. Each node represents a bacterial taxon at the OTU level, while the size and shade of the node corresponds to the number of connections per node and the number of connections passing through the node (i.e., darker shade for nodes acting as a bridge between other nodes at higher frequencies), respectively. A connection denotes significant SparCC correlation (p 0.8 (positive correlation, blue edges) or < -0.8 (negative correlations, red edges).

Additional file 8. Figure S7. Principal component analysis showing the clustering of the 16S rRNA gene sequences in the ‘light’ and ‘heavy’ fractions of the pristine peatland over time (days 8, 13, and 19). All replicates (n=4) are given. Full colored and striped symbols represent the ‘heavy’ and ‘light’ fraction, respectively.

The importance of beef production for Brazil’s economy and the growing demand for animal protein across the globe warrant an improvement in the beef production system. While most attention has been on modulation of the rumen microbiome to improve ruminant production, the role of the lower-gut microbiome in host health and nutrition remains relatively unexplored. This work aimed to investigate the taxonomy and functional variations in the fecal microbiome of Brazilian beef cattle reared in two different production systems using a metagenomic approach. Sixty male beef cattle from six farms representing semi-intensive (I, n = 2) and traditional (T, n = 4) Brazilian beef production systems were enrolled in the study. Shotgun sequencing was used to characterize taxonomic and functional composition and diversity of the microbiome in fecal samples collected from each animal. Fecal samples were analyzed for copper (Cu), lead (Pb), nitrogen (N), phosphorous (P), selenium (Se) and zinc (Zn) and stable isotopes of carbon (13C) and nitrogen (15N). The fecal microbiome was influenced by the beef production systems with greater functional and lower taxonomic diversity in beef cattle feces from I systems compared to T systems. The concentration of N, P, and Zn was higher in beef cattle feces from I systems compared to T systems and was associated with taxonomic and functional profile of fecal microbiome in I system, suggesting the role of fecal nutrients in shaping system-specific microbiome. Semi-intensive management practices led to a more complex but less connected fecal microbiome in beef cattle. The microbial community in beef cattle feces from I systems was characterized by greater abundance of beneficial bacteria (phylum Firmicutes and butyrate-producing bacteria family Lachnospiraceae and genera Anaerostipes, Blautia, Butyrivibrio, Eubacterium, Roseburia, and Ruminococcus). In addition, the fecal abundance of microbial genes related to immune system, nutrient metabolism and energy production was greater in beef cattle raised under I systems compared to T systems. Findings of the current study suggest that semi-intensive management practices could facilitate the development of a healthier and more efficient fecal microbiome in beef cattle by driving an increase in the abundance of beneficial bacteria and functional genes.

Made available in DSpace on 2021-06-25T10:19:30Z (GMT). No. of bitstreams: 0 Previous issue date: 2021-01-01 Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) Nederlandse Organisatie voor Wetenschappelijk Onderzoek Wastewater is considered a renewable resource water and energy. An advantage of decentralized sanitation systems is the separation of the blackwater (BW) stream, contaminated with human pathogens, from the remaining household water. However, the composition and functions of the microbial community in BW are not known. In this study, we used shotgun metagenomics to assess the dynamics of microbial community structure and function throughout a new BW anaerobic digestion system installed at The Netherlands Institute of Ecology. Samples from the influent (BW), primary effluent (anaerobic digested BW), sludge and final effluent of the pilot upflow anaerobic sludge blanket (UASB) reactor and microalgae pilot tubular photobioreactor (PBR) were analyzed. Our results showed a decrease in microbial richness and diversity followed by a decrease in functional complexity and co-occurrence along the different modules of the bioreactor. The microbial diversity and function decrease were reflected both changes in substrate composition and wash conditions. Our wastewater treatment system also decreased microbial functions related to pathogenesis. In summary, the new sanitation system studied here fosters microbial groups and functions that allow the system to efficiently and robustly recover carbon and nutrients while reducing pathogenic groups, ultimately generating a final effluent safe for discharge and reuse. Department of Microbial Ecology Netherlands Institute of Ecology (NIOO-KNAW), Droevendaalsesteeg 10 Ecology and Biodiversity Institute of Environmental Biology Utrecht University, Padualaan 8 Department of Environmental and Civil Engineering São Paulo State University (UNESP) Department of Terrestrial Ecology Netherlands Institute of Ecology (NIOO-KNAW), Droevendaalsesteeg 10 Department of Aquatic Ecology Netherlands Institute of Ecology (NIOO-KNAW), Droevendaalsesteeg 10 Department of Environmental and Civil Engineering São Paulo State University (UNESP) FAPESP: 2013/50351-4 CNPq: 206884/2014-1 Nederlandse Organisatie voor Wetenschappelijk Onderzoek: 729.004.003