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Different bacterial communities in heat and gamma irradiation treated replant disease soils revealed by 16S rRNA gene analysis - contribution to improved aboveground apple plant growth?

ABSTRACT: Replant disease (RD) severely affects apple production in propagation tree nurseries and in fruit orchards worldwide. This study aimed to investigate the effects of soil disinfection treatments on plant growth and health in a biotest in two different RD soil types under greenhouse conditions and to link the plant growth status with the bacterial community composition at the time of plant sampling. In the biotest performed we observed that the aboveground growth of apple rootstock M26 plants after 8 weeks was improved in the two RD soils either treated at 50°C or with gamma irradiation compared to the untreated RD soils. Total community DNA was extracted from soil loosely adhering to the roots and quantitative real-time PCR revealed no pronounced differences in 16S rRNA gene copy numbers. 16S rRNA gene-based bacterial community analysis by denaturing gradient gel electrophoresis (DGGE) and 454-pyrosequencing revealed significant differences in the bacterial community composition even after 8 weeks of plant growth. In both soils, the treatments affected different phyla but only the relative abundance of Acidobacteria was reduced by both treatments. The genera Streptomyces, Bacillus, Paenibacillus, and Sphingomonas had a higher relative abundance in both heat treated soils, whereas the relative abundance of Mucilaginibacter, Devosia, and Rhodanobacter was increased in the gamma-irradiated soils and only the genus Phenylobacterium was increased in both treatments. The increased abundance of genera with potentially beneficial bacteria, i.e., potential degraders of phenolic compounds might have contributed to the improved plant growth in both treatments.

SUBMITTER: Yim B

PROVIDER: S-EPMC4654428 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature

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Different bacterial communities in heat and gamma irradiation treated replant disease soils revealed by 16S rRNA gene analysis - contribution to improved aboveground apple plant growth?

Yim Bunlong B Winkelmann Traud T Ding Guo-Chun GC Smalla Kornelia K

Frontiers in microbiology 20151106

Replant disease (RD) severely affects apple production in propagation tree nurseries and in fruit orchards worldwide. This study aimed to investigate the effects of soil disinfection treatments on plant growth and health in a biotest in two different RD soil types under greenhouse conditions and to link the plant growth status with the bacterial community composition at the time of plant sampling. In the biotest performed we observed that the aboveground growth of apple rootstock M26 plants afte ...[more]

PMID: 26635733

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Project description:Two consortia (Consortium A and Consortium B) that can use 1,4-dioxane (a groundwater contaminant of emerging concern) as the sole carbon source were enriched from Rice University (Houston, TX, USA) campus soil. Phylogenetic analysis by 16S rRNA sequencing revealed the dominant genus in both of the consortia is Mycobacterium (56% in Consortium A and 49% in Consortium B). The predominance of Mycobacterium spp, in these consortia support the notion that this is an important and commonly encountered genus of dioxane degraders. Among other genera present that make at least 2% of these consortia, only Afipia encompasses a strain (i.e., Afipia sp. D1) that was reported to degrade dioxane as sole carbon and energy source. A nested PCR analysis using two degenerate primers to target the hydroxylase alpha subunit of groups 3 to 6 SDIMOs was performed to gain insights into which enzymes were responsible for dioxane degradation by these consortia. The purified products obtained from the second PCR run were sequenced and compared to genes databases (NCBI) encompassing all of the currently reported SDIMOs. The dominant SDIMO genes in Consortium A corresponded to a group-6 putative propane monooxygenase-like SDIMO (98.8%); while in Consortium B, SDIMO genes from both groups 5 (47.3%) and 6 (51.9%) were observed. In both consortia, the relative abundance of thmA/dxmA gene was negligible (0.03%), which is consistent with the negative amplification of these genes as verified in qPCR. Overall, the high relative abundance of group-6 putative propane monooxygenases in our two consortia suggests the novel finding that group 6-SDIMOs could also play an important role in dioxane degradation. This underscores the need for further research on genes and enzymes involved in dioxane biodegradation to develop novel biomarkers that can be useful for forensic analysis and performance assessment of bioremediation and natural attenuation at dioxane-impacted sites. DNA was extracted from bacteria biomass harvested in exponential growth phase, when half or more of the added dioxane (100 mg/L) was consumed. Total DNA extractions were performed using the UltraClean® Microbial DNA Isolation Kit (MO BIO, Carlsbad, CA, USA) according to the manufacturer’s protocol. The V4 region of the 16S rRNA gene was amplified by PCR using the forward 515F and reverse 806R primers. Sequencing was performed at MR DNA (www.mrdnalab.com, Shallowater, TX, USA) by Illumina MiSeq paired-end sequencing (approximately 2×300 bp as the read length). Sequence data were processed using MR DNA analysis pipeline. Operational taxonomic units (OTUs) were defined by clustering at 3% divergence (97% similarity). Final OTUs were taxonomically classified using BLASTn against the RDPII (http://rdp.cme.msu.edu) and NCBI (www.ncbi.nlm.nih.gov) databases.Previously designed degenerate primers NVC57, NVC58, NVC65 and NVC66 to target conserved regions in the soluble di-iron monooxygenases (SDIMO) alpha subunit gene (groups 3 to 6) were used to examine the presence and diversity of SDIMO genes in these two consortia. A nested PCR strategy was used to increase the PCR product yield. In the first run, the PCR mixture contained 1 µL of NVC65 and NVC58 primer mixture (10 µM), 20 ng of the extracted genomic DNA, 12.5 µL of KAPA HiFi HotStart ReadyMix (2X) (KAPA Biosystems, Wilmington, MA, USA), and nuclease-free water to yield a total volume of 25 µL. PCR was performed in a Bio-Rad Thermal Cycler (Bio-Rad, Hercules, CA, USA) with the following temperature profile: initial denaturation (94°C, 5 min), then 29 amplification cycles (94°C for 30 s, 55°C for 30 s, 72°C for 1 min per kb) and a final extension (72°C for 5 min). The length of the PCR products in the first run was checked by 1% agarose gel and DNA bands of the correct size (1100 bp) were excised and purified. 20 ng of the purified PCR product was used as the DNA template in the second run, with the second set of primers (NVC57 and NVC66). The purified product (420 bp) from the second PCR was sent to MR DNA (www.mrdnalab.com, Shallowater, TX, USA) for Illumina MiSeq paired-end sequencing (approximately 2×300 bp as the read length). Sequence data were processed using MR DNA analysis pipeline. Operational taxonomic units (OTUs) were defined by clustering at 3% divergence (97% similarity). A database including all of the currently reported SDIMO genes on NCBI was created and used to taxonomically classify the final OTUs.

Project description:IntroductionBiological communities present in soil are essential to sustainable and productive agricultural practices; however, an accurate determination of the ecological status of agricultural soils remains to date an elusive task. An ideal indicator should be pervasive, play a relevant role in the ecosystem, show a rapid and proportional answer to external perturbations and be easily and economically measurable. Rhizobacteria play a major role in determining soil properties, becoming an attractive candidate for the detection of ecological indicators. The application of massive sequencing technologies to metagenomic analysis is providing an increasingly more precise view of the structure and composition of soil communities. In this work, we analyse soil rhizobacterial composition under various stress levels to search for potential ecological indicators.General biodiversity indicatorsOur results suggest that the Shannon index requires observation of a relatively large number of individuals to be representative of the true population diversity, and that the Simpson index may underestimate rare taxa in rhizobacterial environments.Taxonomical classification methodsDetection of indicator taxa requires comparison of taxonomical classification of sequences. We have compared RDP classifier, RTAX and similarity-based taxonomical classification and selected the latter for taxonomical assignment because it provides larger detail.Taxonomy-based ecological indicatorsThe study of significant variations in common, clearly identified, taxa, using paired datasets allows minimization of non-treatment effects and avoidance of false positives. We have identified taxa associated to specific perturbations as well as taxa generally affected in treated soils. Changes in these taxa, or combinations of them, may be used as ecological indicators of soil health. The overall number and magnitude of changes detected in taxonomic groups does also increase with stress. These changes constitute an alternative indicator to measuring specific taxa, although their determination requires large sample sizes, better obtained by massive sequencing.SummaryThe main ecological indicators available are the Shannon index, OTU counts and estimators, overall detection of the number and proportion of changes, and changes of specific indicator taxa. Massive sequencing remains the most accurate tool to measure rhizobacterial ecological indicators. When massive sequencing is not an option, various cultivable taxonomic groups, such as specific groups in the Actinobacteria tree, are attractive as potential indicators of large disruptions to the rhizobiome.

Project description:BackgroundApple replant disease (ARD) is a syndrome that occurs in areas where apple plants or closely related species have been previously cultivated. Even though ARD is a well-known phenomenon, which has been observed in different regions worldwide and occurs independent of the soil type, its causes still remain unclear.ResultsAs expected, the biomass of plants grown in replant soil was significantly lower compared to those grown in control (virgin) soil. A shotgun metagenome analysis showed a clear differentiation between the rhizosphere and bulk soil compartments independent from the soil used. However, significant differences associated with apple replant disease were only observed in the rhizosphere compartment, for which we detected changes in the abundance of major bacterial genera. Interestingly, reads assigned to Actinobacteria were significantly reduced in relative abundance in rhizosphere samples of the soil affected by replant disease. Even though reads assigned to pathogenic fungi were detected, their relative abundance was low and did not differ significantly between the two different soils. Differences in microbiome structure also resulted in shifts in functional pattern. We observed an increase in genes related to stress sensing in the rhizosphere of soils affected by replant disease, whereas genes linked to nutrient sensing and uptake dominated in control soils. Moreover, we observed a lower abundance of genes coding for enzymes which trigger the degradation of aromatic compounds in rhizosphere of soils affected by replant disease, which is probably connected with higher concentration of phenolic compounds, generally associated with disease progression.ConclusionsOur study shows, for the first time, how apple replanting affects soil functioning by altering the soil microbiome. Particularly, the decrease in the abundance of genes which code for enzymes catalyzing the degradation of aromatic compounds, observed in the rhizosphere of plants grown in soil affected by apple replant disease, is of interest. Apple rootstocks are known to synthetize many phenolic compounds, including defense related phytoalexins, which have been considered for long to be connected with the emergence of replant disease. The knowledge gained in this study might help to develop targeted strategies to overcome or at least reduce the effects of ARD symptoms.

Dataset Information

Different bacterial communities in heat and gamma irradiation treated replant disease soils revealed by 16S rRNA gene analysis - contribution to improved aboveground apple plant growth?

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Different bacterial communities in heat and gamma irradiation treated replant disease soils revealed by 16S rRNA gene analysis - contribution to improved aboveground apple plant growth?

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