Soil Microbial Community Structure and Diversity in Cut Flower Cultures Under Conventional and Ecological Management

Santamaría, Johanna; Parrado, Carmen Alicia; López, Liliana

doi:10.1590/18069657rbcs20170016

Cited by 6 publications

(4 citation statements)

References 22 publications

(20 reference statements)

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…The types of operations in farmland, such as effective management, the tillage regime, and fertilization practice, have been found to have an impact on soil microorganisms. The microbial community structure and diversity of three different management practices (conventional, ecological, and intermediate) of cut flower cultures were investigated, and it was found that the bacterial community structure differed considerably among the three management practices, indicating that it can effectively monitor the soil quality change by different management practices of cut flower cultures [ 68 ]. In addition to management practices, the tillage regime has also been found to influence the soil microbial community.…”

Section: Microbial Indicators In Artificial Ecosystemsmentioning

confidence: 99%

Development of Microbial Indicators in Ecological Systems

Wang

Zhang

et al. 2022

IJERPH

View full text Add to dashboard Cite

Indicators can monitor ecological environment changes and help maintain ecological balance. Bioindicators are divided into animal, plant, and microbial indicators, of which animal and plant indicators have previously been the most researched, but microbial indicators have drawn attention recently owing to their high sensitivity to the environment and their potential for use in monitoring environmental changes. To date, reviews of studies of animals and plants as indicator species have frequently been conducted, but reviews of research on microorganisms as indicator species have been rare. In this review, we summarize and analyze studies using microorganisms as indicator species in a variety of ecosystems, such as forests, deserts, aquatic and plateau ecosystems, and artificial ecosystems, which are contained in wetlands, farmlands, and mining ecosystems. This review provides useful information for the further use of microorganisms as indicators to reflect the changes in different environmental ecosystems.

show abstract

Section: Microbial Indicators In Artificial Ecosystemsmentioning

confidence: 99%

Development of Microbial Indicators in Ecological Systems

Wang

Zhang

et al. 2022

IJERPH

View full text Add to dashboard Cite

show abstract

“…PCR cycling temperatures for the 433 bp fragment amplification with the 968F and 1401R primers were as follows: 94 °C for 3 min (1 cycle); 94 °C for 50 s, 48 °C for 20 s, and 72 °C for 45 s (30 cycles); followed by a final step at 72 °C for 5 min. The DGGE analysis of the 433 pb PCR products was performed according to Santamaría et al [38], using a different denaturing gradient (37 % to 65 %) and an electrophoresis run time of 17 h at 35 V and 60 °C.…”

Section: Dna Extraction and Molecular Analysismentioning

confidence: 99%

Gut bacteria comparison between wild and captive neotropical otters

Santamaría-Vanegas

Rodríguez-Rey

2020

Universitas Scientiarum

View full text Add to dashboard Cite

The neotropical otter (Lontra longicaudis) is considered a flagship species for the conservation of the ecosystems in which it resides and is currently in a vulnerable state. As a conservation strategy for this species, rehabilitation, breeding, and reintroduction programs of captive individuals have been proposed. However, it is likely that the environment and feeding conditions in captivity result in gut microbial communities that differ from those in wild animals. Gut microbial communities have an important role in the physiological performance of an animal. To determine differences between gut microbial communities of otters in wild and captive living conditions, the structure and diversity of their gut bacterial communities were determined using 16S rDNA molecular markers. Total DNA was isolated from fecal samples of wild animals from the La Vieja River basin and from captive animals in the Cali Zoo. As expected, the gut bacterial communities of captive animals converged to a more similar structure, and their bacterial diversity was significantly lower than that found in wild animals.

show abstract

“…The 16S rRNA gene is the standard utilised in the assessment of prokaryotic community composition by amplicon sequencing (Fukuda et al 2016). 16S rRNA has been used for community analysis in diverse environments such as the gut microbiota of cattle and pigs (Avila-Jaime, Kawas, and Garcia-Mazcorro 2018), soil (Santamaria, Parrado, and López 2018), marine environments (Dang and Lovell 2000), and the human gut (Jovel et al 2016). The success of this method hinges on the presence of the 16S rRNA gene in all domains and its relatively slow rate of base substitution; thus the rDNA regions can be targeted with primers but the amplicon sequences exhibit enough diversity that organisms can be differentiated at the genus or species level (Woese and Fox 1977;Woo et al 2008).…”

Section: Introductionmentioning

confidence: 99%

Mining underutilized whole-genome sequencing projects to improve 16S rRNA databases

Nolan

Abram

Brennan

et al. 2021

Preprint

View full text Add to dashboard Cite

Current approaches to interpreting 16S rDNA amplicon data are hampered by several factors. Among these are database inaccuracy or incompleteness, sequencing error, and biased DNA/RNA extraction. Existing 16S rRNA databases source the majority of sequences from deposited amplicon sequences, draft genomes, and complete genomes. Most of the draft genomes available are assembled from short reads. However, repeated ribosomal regions are notoriously difficult to assemble well from short reads, and as a consequence the short-read-assembled 16S rDNA region may be an amalgamation of different loci within the genome. This complicates high-resolution community analysis, as a draft genome’s 16S rDNA sequence may be a chimera of multiple loci; in such cases, the draft-derived sequences in a database may not represent a 16S rRNA sequence as it occurs in biology. We present Focus16, a pipeline for improving 16S rRNA databases by mining NCBI’s Sequence Read Archive for whole-genome sequencing runs that could be reassembled to yield additional 16S rRNA sequences. Using riboSeed (a genome assembly tool for correcting rDNA misassembly), Focus16 provides a way to augment 16S rRNA databases with high-quality re-assembled sequences. In this study, we augmented the widely-used SILVA 16S rRNA database with the novel sequences disclosed by Focus16 and re-processed amplicon sequences from several benchmarking datasets with DADA2. Using this augmented SILVA database increased the number of amplicon sequence variants that could be assigned taxonomic annotations. Further, fine-scale classification was improved by revealing ambiguities. We observed, for example, that amplicon sequence variants (ASVs) may be assigned to a specific genus where Focus16-correction would indicate that the ASV is represented in two or more genera. Thus, we demonstrate that improvements can be made to taxonomic classification by incorporating these carefully re-assembled 16S rRNA sequences, and we invite the community to expand our work to augment existing 16S rRNA reference databases such as SILVA, GreenGenes, and RDP.

show abstract

Soil Microbial Community Structure and Diversity in Cut Flower Cultures Under Conventional and Ecological Management

Cited by 6 publications

References 22 publications

Development of Microbial Indicators in Ecological Systems

Development of Microbial Indicators in Ecological Systems

Gut bacteria comparison between wild and captive neotropical otters

Mining underutilized whole-genome sequencing projects to improve 16S rRNA databases

Contact Info

Product

Resources

About