4
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      The Effects of Soil Depth on the Structure of Microbial Communities in Agricultural Soils in Iowa (United States)

      research-article

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Determining how microbial properties change across different soils and within the soil depth profile will be potentially beneficial to understanding the long-term processes that are involved in the health of agricultural ecosystems. Most literature on soil microbes has been restricted to the easily accessible surface soils.

          ABSTRACT

          This study investigated the differences in microbial community abundance, composition, and diversity throughout the depth profiles in soils collected from corn and soybean fields in Iowa (United States) using 16S rRNA amplicon sequencing. The results revealed decreased richness and diversity in microbial communities at increasing soil depth. Soil microbial community composition differed due to crop type only in the top 60 cm and due to location only in the top 90 cm. While the relative abundance of most phyla decreased in deep soils, the relative abundance of the phylum Proteobacteria increased and dominated agricultural soils below the depth of 90 cm. Although soil depth was the most important factor shaping microbial communities, edaphic factors, including soil organic matter, soil bulk density, and the length of time that deep soils were saturated with water, were all significant factors explaining the variation in soil microbial community composition. Soil organic matter showed the highest correlation with the exponential decrease in bacterial abundance with depth. A greater understanding of how soil depth influences the diversity and composition of soil microbial communities is vital for guiding sampling approaches in agricultural soils where plant roots extend beyond the upper soil profile. In the long term, a greater knowledge of the influence of depth on microbial communities should contribute to new strategies that enhance the sustainability of soil, which is a precious resource for food security.

          IMPORTANCE Determining how microbial properties change across different soils and within the soil depth profile will be potentially beneficial to understanding the long-term processes that are involved in the health of agricultural ecosystems. Most literature on soil microbes has been restricted to the easily accessible surface soils. However, deep soils are important in soil formation, carbon sequestration, and providing nutrients and water for plants. In the most productive agricultural systems in the United States where soybean and corn are grown, crop plant roots extend into the deeper regions of soils (>100 cm), but little is known about the taxonomic diversity or the factors that shape deep-soil microbial communities. The findings reported here highlight the importance of soil depth in shaping microbial communities, provide new information about edaphic factors that influence the deep-soil communities, and reveal more detailed information on taxa that exist in deep agricultural soils.

          Related collections

          Most cited references108

          • Record: found
          • Abstract: not found
          • Article: not found

          QIIME allows analysis of high-throughput community sequencing data.

            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            Naive Bayesian classifier for rapid assignment of rRNA sequences into the new bacterial taxonomy.

            The Ribosomal Database Project (RDP) Classifier, a naïve Bayesian classifier, can rapidly and accurately classify bacterial 16S rRNA sequences into the new higher-order taxonomy proposed in Bergey's Taxonomic Outline of the Prokaryotes (2nd ed., release 5.0, Springer-Verlag, New York, NY, 2004). It provides taxonomic assignments from domain to genus, with confidence estimates for each assignment. The majority of classifications (98%) were of high estimated confidence (> or = 95%) and high accuracy (98%). In addition to being tested with the corpus of 5,014 type strain sequences from Bergey's outline, the RDP Classifier was tested with a corpus of 23,095 rRNA sequences as assigned by the NCBI into their alternative higher-order taxonomy. The results from leave-one-out testing on both corpora show that the overall accuracies at all levels of confidence for near-full-length and 400-base segments were 89% or above down to the genus level, and the majority of the classification errors appear to be due to anomalies in the current taxonomies. For shorter rRNA segments, such as those that might be generated by pyrosequencing, the error rate varied greatly over the length of the 16S rRNA gene, with segments around the V2 and V4 variable regions giving the lowest error rates. The RDP Classifier is suitable both for the analysis of single rRNA sequences and for the analysis of libraries of thousands of sequences. Another related tool, RDP Library Compare, was developed to facilitate microbial-community comparison based on 16S rRNA gene sequence libraries. It combines the RDP Classifier with a statistical test to flag taxa differentially represented between samples. The RDP Classifier and RDP Library Compare are available online at http://rdp.cme.msu.edu/.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              Development of a dual-index sequencing strategy and curation pipeline for analyzing amplicon sequence data on the MiSeq Illumina sequencing platform.

              Rapid advances in sequencing technology have changed the experimental landscape of microbial ecology. In the last 10 years, the field has moved from sequencing hundreds of 16S rRNA gene fragments per study using clone libraries to the sequencing of millions of fragments per study using next-generation sequencing technologies from 454 and Illumina. As these technologies advance, it is critical to assess the strengths, weaknesses, and overall suitability of these platforms for the interrogation of microbial communities. Here, we present an improved method for sequencing variable regions within the 16S rRNA gene using Illumina's MiSeq platform, which is currently capable of producing paired 250-nucleotide reads. We evaluated three overlapping regions of the 16S rRNA gene that vary in length (i.e., V34, V4, and V45) by resequencing a mock community and natural samples from human feces, mouse feces, and soil. By titrating the concentration of 16S rRNA gene amplicons applied to the flow cell and using a quality score-based approach to correct discrepancies between reads used to construct contigs, we were able to reduce error rates by as much as two orders of magnitude. Finally, we reprocessed samples from a previous study to demonstrate that large numbers of samples could be multiplexed and sequenced in parallel with shotgun metagenomes. These analyses demonstrate that our approach can provide data that are at least as good as that generated by the 454 platform while providing considerably higher sequencing coverage for a fraction of the cost.
                Bookmark

                Author and article information

                Contributors
                Role: Editor
                Journal
                Appl Environ Microbiol
                Appl Environ Microbiol
                aem
                aem
                AEM
                Applied and Environmental Microbiology
                American Society for Microbiology (1752 N St., N.W., Washington, DC )
                0099-2240
                1098-5336
                11 December 2020
                29 January 2021
                February 2021
                : 87
                : 4
                : e02673-20
                Affiliations
                [a ]Department of Agronomy and Horticulture, University of Nebraska—Lincoln, Lincoln, Nebraska, USA
                [b ]Center for Plant Science Innovation, University of Nebraska—Lincoln, Lincoln, Nebraska, USA
                [c ]Department of Agronomy, Iowa State University, Ames, Iowa, USA
                [d ]Department of Plant Science and Industries Building, Pennsylvania State University, University Park, Pennsylvania, USA
                University of Michigan—Ann Arbor
                Author notes
                Address correspondence to Daniel P. Schachtman, daniel.schachtman@ 123456unl.edu .

                Citation Hao J, Chai YN, Lopes LD, Ordóñez RA, Wright EE, Archontoulis S, Schachtman DP. 2021. The effects of soil depth on the structure of microbial communities in agricultural soils in Iowa (United States). Appl Environ Microbiol 87:e02673-20. https://doi.org/10.1128/AEM.02673-20.

                Author information
                https://orcid.org/0000-0003-0308-7378
                https://orcid.org/0000-0003-1807-4369
                Article
                02673-20
                10.1128/AEM.02673-20
                7851703
                33310710
                e5eeed1a-07f2-4b0f-a789-202cf41e5acb
                Copyright © 2021 Hao et al.

                This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International license.

                History
                : 3 November 2020
                : 1 December 2020
                Page count
                Figures: 6, Tables: 1, Equations: 0, References: 105, Pages: 17, Words: 11209
                Funding
                Funded by: National Science Foundation EPSCOR to fund The Center for Root and Rhizobiome Innovation Award;
                Award ID: OIA-1557417
                Award Recipient :
                Funded by: USDA Hatch Project;
                Award ID: IOW10480
                Award Recipient :
                Funded by: Foundation for Food and Agriculture Research (FFAR), https://doi.org/10.13039/100011929;
                Award ID: #534264
                Award Recipient :
                Categories
                Microbial Ecology
                Custom metadata
                February 2021

                Microbiology & Virology
                iowa,usa,agricultural soils,microbial communities,soil depth
                Microbiology & Virology
                iowa, usa, agricultural soils, microbial communities, soil depth

                Comments

                Comment on this article