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      Inorganic Chemical Fertilizer Application to Wheat Reduces the Abundance of Putative Plant Growth-Promoting Rhizobacteria

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          Abstract

          The profound negative effect of inorganic chemical fertilizer application on rhizobacterial diversity has been well documented using 16S rRNA gene amplicon sequencing and predictive metagenomics. We aimed to measure the function and relative abundance of readily culturable putative plant growth-promoting rhizobacterial (PGPR) isolates from wheat root soil samples under contrasting inorganic fertilization regimes. We hypothesized that putative PGPR abundance will be reduced in fertilized relative to unfertilized samples. Triticum aestivum cv. Cadenza seeds were sown in a nutrient depleted agricultural soil in pots treated with and without Osmocote ® fertilizer containing nitrogen-phosphorous-potassium (NPK). Rhizosphere and rhizoplane samples were collected at flowering stage (10 weeks) and analyzed by culture-independent (CI) amplicon sequence variant (ASV) analysis of rhizobacterial DNA as well as culture-dependent (CD) techniques. Rhizosphere and rhizoplane derived microbiota culture collections were tested for plant growth-promoting traits using functional bioassays. In general, fertilizer addition decreased the proportion of nutrient-solubilizing bacteria (nitrate, phosphate, potassium, iron, and zinc) isolated from rhizocompartments in wheat whereas salt tolerant bacteria were not affected. A “PGPR” database was created from isolate 16S rRNA gene sequences against which total amplified 16S rRNA soil DNA was searched, identifying 1.52% of total community ASVs as culturable PGPR isolates. Bioassays identified a higher proportion of PGPR in non-fertilized samples [rhizosphere (49%) and rhizoplane (91%)] compared to fertilized samples [rhizosphere (21%) and rhizoplane (19%)] which constituted approximately 1.95 and 1.25% in non-fertilized and fertilized total community DNA, respectively. The analyses of 16S rRNA genes and deduced functional profiles provide an in-depth understanding of the responses of bacterial communities to fertilizer; our study suggests that rhizobacteria that potentially benefit plants by mobilizing insoluble nutrients in soil are reduced by chemical fertilizer addition. This knowledge will benefit the development of more targeted biofertilization strategies.

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          Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2

          In comparative high-throughput sequencing assays, a fundamental task is the analysis of count data, such as read counts per gene in RNA-seq, for evidence of systematic changes across experimental conditions. Small replicate numbers, discreteness, large dynamic range and the presence of outliers require a suitable statistical approach. We present DESeq2, a method for differential analysis of count data, using shrinkage estimation for dispersions and fold changes to improve stability and interpretability of estimates. This enables a more quantitative analysis focused on the strength rather than the mere presence of differential expression. The DESeq2 package is available at http://www.bioconductor.org/packages/release/bioc/html/DESeq2.html. Electronic supplementary material The online version of this article (doi:10.1186/s13059-014-0550-8) contains supplementary material, which is available to authorized users.
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            DADA2: High resolution sample inference from Illumina amplicon data

            We present DADA2, a software package that models and corrects Illumina-sequenced amplicon errors. DADA2 infers sample sequences exactly, without coarse-graining into OTUs, and resolves differences of as little as one nucleotide. In several mock communities DADA2 identified more real variants and output fewer spurious sequences than other methods. We applied DADA2 to vaginal samples from a cohort of pregnant women, revealing a diversity of previously undetected Lactobacillus crispatus variants.
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              The SILVA ribosomal RNA gene database project: improved data processing and web-based tools

              SILVA (from Latin silva, forest, http://www.arb-silva.de) is a comprehensive web resource for up to date, quality-controlled databases of aligned ribosomal RNA (rRNA) gene sequences from the Bacteria, Archaea and Eukaryota domains and supplementary online services. The referred database release 111 (July 2012) contains 3 194 778 small subunit and 288 717 large subunit rRNA gene sequences. Since the initial description of the project, substantial new features have been introduced, including advanced quality control procedures, an improved rRNA gene aligner, online tools for probe and primer evaluation and optimized browsing, searching and downloading on the website. Furthermore, the extensively curated SILVA taxonomy and the new non-redundant SILVA datasets provide an ideal reference for high-throughput classification of data from next-generation sequencing approaches.
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                Author and article information

                Contributors
                Journal
                Front Microbiol
                Front Microbiol
                Front. Microbiol.
                Frontiers in Microbiology
                Frontiers Media S.A.
                1664-302X
                11 March 2021
                2021
                : 12
                : 642587
                Affiliations
                [1] 1Sustainable Agriculture Sciences, Rothamsted Research , Harpenden, United Kingdom
                [2] 2Cranfield Soil and Agrifood Institute, Cranfield University , Cranfield, United Kingdom
                Author notes

                Edited by: Aleksa Obradović, University of Belgrade, Serbia

                Reviewed by: Abhishek Walia, Chaudhary Sarwan Kumar Himachal Pradesh Krishi Vishvavidyalaya, India; Aymé Spor, INRA UMR 1347 Agroécologie, France

                *Correspondence: Tim H. Mauchline, tim.mauchline@ 123456rothamsted.ac.uk

                This article was submitted to Microbe and Virus Interactions with Plants, a section of the journal Frontiers in Microbiology

                Article
                10.3389/fmicb.2021.642587
                7991844
                33776974
                46ea11c2-1215-465d-8909-b29967bd217c
                Copyright © 2021 Reid, Kavamura, Abadie, Torres-Ballesteros, Pawlett, Clark, Harris and Mauchline.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 16 December 2020
                : 15 February 2021
                Page count
                Figures: 8, Tables: 0, Equations: 0, References: 78, Pages: 16, Words: 0
                Funding
                Funded by: Biotechnology and Biological Sciences Research Council 10.13039/501100000268
                Award ID: BB/N016246/1
                Award ID: BBS/E/C/00005196
                Award ID: BBS/E/C/000I0310
                Categories
                Microbiology
                Original Research

                Microbiology & Virology
                rhizosphere,rhizoplane,fertilizer,microbiome,bacteria,plant growth-promoting rhizobacteria

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