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1.
Front Microbiol ; 12: 759432, 2021.
Artigo em Inglês | MEDLINE | ID: mdl-34759912

RESUMO

Using two successive types of diets (100% concentrate and 67% forage), this study explores the relationship between the ruminal microbiota of 78 Romane lambs and their feed efficiency (residual feed intake trait) or feeding behavior (feeding rate trait). Analysis was carried out phenotypically by correlating feed efficiency or feeding behavior traits with the relative abundance of bacteria at the phylum, family, and genus levels, and then genetically by comparing the microbiota of lambs selected for extreme breeding values for residual feed intake or feeding rate. Our results confirmed the major effect of diet on the ruminal microbiota composition. The microbiota of lambs consuming a forage-based diet was distinguished by higher microbial diversity and also by higher relative abundance of Firmicutes, whereas Bacteriodetes and Actinobacteria were relatively more abundant in the microbiota of lambs consuming a concentrate-based diet. Moreover, the comparison of lambs divergent for residual feed intake breeding values revealed that regardless of diet, more efficient lambs possessed a ruminal microbiota enriched in Coprococcus, Moryella, [Eubacterium] Brachy group, and [Eubacterium] hallii group, but depleted in Lachnospiraceae FD2005 and Shuttleworthia. The connection between microbiota composition and feeding rate was more tenuous, with no link between the abundance of particular genera and lambs genetically divergent for feeding rate.

2.
Microbiologyopen ; 9(3): e977, 2020 03.
Artigo em Inglês | MEDLINE | ID: mdl-31927795

RESUMO

Metabarcoding of the 16S rRNA gene is commonly used to characterize microbial communities, by estimating the relative abundance of microbes. Here, we present a method to retrieve the concentrations of the 16S rRNA gene per gram of any environmental sample using a synthetic standard in minuscule amounts (100 ppm to 1% of the 16S rRNA sequences) that is added to the sample before DNA extraction and quantified by two quantitative polymerase chain reaction (qPCR) reactions. This allows normalizing by the initial microbial density, taking into account the DNA recovery yield. We quantified the internal standard and the total load of 16S rRNA genes by qPCR. The qPCR for the latter uses the exact same primers as those used for Illumina sequencing of the V3-V4 hypervariable regions of the 16S rRNA gene to increase accuracy. We are able to calculate the absolute concentration of the species per gram of sample, taking into account the DNA recovery yield. This is crucial for an accurate estimate as the yield varied between 40% and 84%. This method avoids sacrificing a high proportion of the sequencing effort to quantify the internal standard. If sacrificing a part of the sequencing effort to the internal standard is acceptable, we however recommend that the internal standard accounts for 30% of the environmental 16S rRNA genes to avoid the PCR bias associated with rare phylotypes. The method proposed here was tested on a feces sample but can be applied more broadly on any environmental sample. This method offers a real improvement of metabarcoding of microbial communities since it makes the method quantitative with limited efforts.


Assuntos
Código de Barras de DNA Taxonômico , Metagenoma , Metagenômica , Microbiota/genética , RNA Ribossômico 16S/genética , Sequência de Bases , Biodiversidade , Código de Barras de DNA Taxonômico/métodos , Microbiologia Ambiental , Sequenciamento de Nucleotídeos em Larga Escala , Metagenômica/métodos , RNA Ribossômico 16S/química , Reação em Cadeia da Polimerase em Tempo Real , Análise de Sequência de DNA
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