title: Looking for Rhizobacterial Ecological Indicators in Agricultural Soils Using 16S rRNA metagenomic Amplicon Data.
abstract: BACKGROUND
  Biological 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.
  Our 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.
  Detection 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.
  The 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.
  
  
  CONCLUSIONS
  The 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.
authors: Centro Nacional de Biotecnología, CSIC. c/Darwin, Madrid, Spain.
authors: José R
authors: http://orcid.org/0000-0002-6655-7114
authors: JR
authors: Valverde
authors: Centro Nacional de Biotecnología, CSIC. c/Darwin, Madrid, Spain.
authors: Sonia
authors: S
authors: Gullón
authors: Centro Nacional de Biotecnología, CSIC. c/Darwin, Madrid, Spain.
authors: Rafael
authors: R
authors: Pérez Mellado
mesh_terms: D018556:Crops, Agricultural / Q000254:growth & development; D004275:DNA, Ribosomal / Q000235:genetics; D017753:Ecosystem; D059014:High-Throughput Nucleotide Sequencing / Q000379:methods; D056186:Metagenomics / Q000379:methods*; D010802:Phylogeny; D012336:RNA, Ribosomal, 16S / Q000235:genetics*; D012230:Rhizobiaceae / Q000145:classification* / Q000235:genetics / Q000302:isolation & purification; D017422:Sequence Analysis, DNA / Q000379:methods; D012987:Soil / Q000737:chemistry*; D012988:Soil Microbiology
chemical_list: D004275:DNA, Ribosomal; D012336:RNA, Ribosomal, 16S; D012987:Soil