Structure, Composition and Metagenomic Profile of Soil Microbiomes Associated to Agricultural Land Use and Tillage Systems in Argentine Pampas

Carbonetto, Belén; Rascovan, Nicolás; Álvarez, Roberto; Mentaberry, Alejandro; Vázquez, Martı́n

doi:10.1371/journal.pone.0099949

Cited by 185 publications

(113 citation statements)

References 86 publications

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“…Additionally, through 454-pyrosequencing of the 16S rRNA gene we identified the most represented phyla as Acidobacteria, Proteobacteria and Verrucomicrobia, the same main phyla that Carbonetto et al (2014) reported in Argentinean pampas. Similarly, Acidobacteria and Proteobacteria were the most abundant phyla reported by Fierer et al (2007) in bulk soil across a wide range of ecosystems in North America.…”

Section: Microbial Diversity In Maize Rhizosphere Samples Agricultursupporting

confidence: 72%

“…These authors suggested that the overall abundances of studied taxa or numerically abundant subgroups within these taxa can be broadly classified into copiotrophic or oligotrhophic categories. Copiotrophic attributes refer to microorganisms growing in fertilized soils with a high nutrient amendment, while an oligotrophic life style is more frequently found in microbiomes of non-cultivated homogenous soils (Carbonetto et al, 2014;Fierer et al, 2007). Fierer et al (2007) found Acidobacteria was more abundant in soils with low availability of nutritional resources (oligotrophic strategists).…”

Section: Microbial Diversity In Maize Rhizosphere Samples Agriculturmentioning

confidence: 99%

“…Many studies of stability and diversity of microbial communities showed that the abundance of individual taxa changed according to different agricultural management practices (Acosta-Martinez et al, 2008;Yin et al, 2010, Figuerola et al 2012Carbonetto et al, 2014). Also using DGGE, Marileo et al (2016) evaluated the total bacterial and ammonia-oxidizing bacteria communities shifts using various herbicides in urea-fertilized soils, revealing significant changes in community structures depending on the urea and herbicide dosage, herbicide type and sampling time.…”

Section: Microbial Diversity In Maize Rhizosphere Samples Agriculturmentioning

confidence: 99%

“…Microbial community analysis assessing biodiversity variability with classical fingerprinting techniques, such as DGGE (denaturing gradient gel electrophoresis), lacks information about microbial taxonomic identity and only captures the most dominant species in the environment. Nowadays, 16S rRNA gene amplicon pyrosequencing has been largely implemented to determine microbial diversity and community structure in many different ecosystems, allowing a more exhaustive characterization of community patterns and composition (Carbonetto et al 2014). Using both 16S rRNA gene DGGE and 454-pyrosequencing technology, we aim to analyze possible changes in composition and diversity of bacterial populations in: i) rhizosphere during maize growth cycle at elongation, flowering and maturity of two transgenic maize cultivars: 699 MGRR and DK feed2 RR (MONSANTO-DEKALB); and in ii) agricultural soil before sowing and non-cultivated soil near the experimental site.…”

Section: Introductionmentioning

confidence: 99%

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Soil and Rhizosphere Bacterial Diversity in Maize Agro- Ecosystem

Federici

Valverde

Lagurara³

et al. 2017

SAR

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Management practices used in maize production have an impact on soil agro-ecosystems where different microbial communities coexist. Soil inhabiting bacteria are numerous and diverse, but we know very little about their ecological distribution. Here we analyzed the bacterial community diversity in the rhizosphere of two transgenic maize cultivars, in agricultural soil before sowing and in non-cultivated soil in an experimental site in the south region of Uruguay. We followed two culture-independent methods: DGGE (denaturing gradient gel electrophoresis) and 454-pyrosequencing of 16S rRNA gene amplicon. Through pyrosequencing, the three environments analyzed presented differences in terms of bacterial composition. However, no differences were found in the relative abundance of the ten most represented phyla in the rhizosphere of the two cultivars at different phenological stages. We found significant differences of Bacteroidetes, Gemmatimonadetes, Planctomycetes, Proteobacteria and Verrucomicrobia phyla when comparing agricultural and non-cultivated soils, as well as a significant enrichment of members of the phylum Gemmatimonadetes in all rhizosphere samples compared to soil. Through DGGE analysis we evidenced that maize rhizosphere bacterial communities changed at different phenological stages in both cultivars. We also provided baseline information about bacterial specific taxa within maize agro-ecosystem for further evaluation of possible rhizosphere bacterial community shifts of genetically modified maize cultivars under different management practices.

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Section: Microbial Diversity In Maize Rhizosphere Samples Agricultursupporting

confidence: 72%

Section: Microbial Diversity In Maize Rhizosphere Samples Agriculturmentioning

confidence: 99%

Section: Microbial Diversity In Maize Rhizosphere Samples Agriculturmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Soil and Rhizosphere Bacterial Diversity in Maize Agro- Ecosystem

Federici

Valverde

Lagurara³

et al. 2017

SAR

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“…Therefore most of the methods used for profiling microbial communities and describe their main functional features are now adopting whole DNA extraction and the use of NGS on the entire sample, with the objective of sequencing and characterizing DNA fragments of all the species included, i.e., the metagenome. The application of metagenomics in agriculture also proved to be appropriate for depicting the complex patterns of interactions occurring among microorganisms in soil [44] and in plant rhizosphere [45], as well as in specific tissues or organs [6,46,47].…”

Section: -Impact Of Ngs In Agriculturementioning

confidence: 99%

Bioinformatics for agriculture in the Next-Generation sequencing era

Esposito

Colantuono

Ruggieri

et al. 2016

Chem. Biol. Technol. Agric.

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Abstract:The key role of bioinformatics is acquiring striking importance in the era of outstanding advances in omics technologies for its fundamental support in describing the multifaceted aspects of biological functionalities. The manifold omics efforts flourishing worldwide are also contributing fundamental novelties in many aspects of agricultural sciences and, as a consequence, bioinformatics is acquiring a crucial role also in these research fields. Indeed, the transformation of natural environment for improvement of goods from animal, plants, and microbial worlds for human nutrition and health requires the comprehension of the molecular mechanisms influencing the structure and the function of the individuals, the populations, and the communities. The expanding knowledge about the molecules and the mechanisms associated with specific phenotypic traits and specific responses to biotic or abiotic stresses, complemented with the predictive power of bioinformatics, has an impact on agriculture practices and favors innovative methods in diagnostics, monitoring, and traceability, improving human benefits at lower costs, thus supporting sustainability. We here describe main bioinformatics approaches in the era of Next-Generation Sequencing for its impact in genomics, transcriptomics, and metagenomics efforts, describing their role in agriculture sciences. We aim to introduce common aspects, open questions and perspectives in this cutting-edge field of research.

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