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Quantifying the biases in metagenome mining for realistic assessment of microbial ecology of naturally fermented foods

View Article: PubMed Central - PubMed

ABSTRACT

Cultivation-independent investigation of microbial ecology is biased by the DNA extraction methods used. We aimed to quantify those biases by comparative analysis of the metagenome mined from four diverse naturally fermented foods (bamboo shoot, milk, fish, soybean) using eight different DNA extraction methods with different cell lysis principles. Our findings revealed that the enzymatic lysis yielded higher eubacterial and yeast metagenomic DNA from the food matrices compared to the widely used chemical and mechanical lysis principles. Further analysis of the bacterial community structure by Illumina MiSeq amplicon sequencing revealed a high recovery of lactic acid bacteria by the enzymatic lysis in all food types. However, Bacillaceae, Acetobacteraceae, Clostridiaceae and Proteobacteria were more abundantly recovered when mechanical and chemical lysis principles were applied. The biases generated due to the differential recovery of operational taxonomic units (OTUs) by different DNA extraction methods including DNA and PCR amplicons mix from different methods have been quantitatively demonstrated here. The different methods shared only 29.9–52.0% of the total OTUs recovered. Although similar comparative research has been performed on other ecological niches, this is the first in-depth investigation of quantifying the biases in metagenome mining from naturally fermented foods.

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Related in: MedlinePlus

PCR-DGGE fingerprinting of eubacterial and yeast communities showed that DNA extraction methods with similar lysis principles clustered together.(a) Pearson correlation based UPGMA clustering of normalized eubacterial community PCR-DGGE fingerprints obtained from fermented milk (n = 10) showing clustering of different extraction methods. The analysis was performed in GelCompar II v6.5 with band matching performed at 1% position tolerance. Value at the nodes represents distance similarity. (b) PCA plotting of the methods using normalized PCR-DGGE fingerprints of eubacterial communities generated from all food types (n = 10 each) revealed the clustering of methods based on cell lysis principles. Clustering of the methods based on enzymatic lysis principle (II, III, IV, V) and non-enzymatic lysis principles (I, VI) is highlighted. (c) Dendrogram based on yeast community PCR-DGGE fingerprints obtained using the selected three different extraction methods in fermented milk, fish, soybean and bamboo shoot (n = 10 each). Text related to PCR-DGGE optimization is included in Supplementary Note.
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f2: PCR-DGGE fingerprinting of eubacterial and yeast communities showed that DNA extraction methods with similar lysis principles clustered together.(a) Pearson correlation based UPGMA clustering of normalized eubacterial community PCR-DGGE fingerprints obtained from fermented milk (n = 10) showing clustering of different extraction methods. The analysis was performed in GelCompar II v6.5 with band matching performed at 1% position tolerance. Value at the nodes represents distance similarity. (b) PCA plotting of the methods using normalized PCR-DGGE fingerprints of eubacterial communities generated from all food types (n = 10 each) revealed the clustering of methods based on cell lysis principles. Clustering of the methods based on enzymatic lysis principle (II, III, IV, V) and non-enzymatic lysis principles (I, VI) is highlighted. (c) Dendrogram based on yeast community PCR-DGGE fingerprints obtained using the selected three different extraction methods in fermented milk, fish, soybean and bamboo shoot (n = 10 each). Text related to PCR-DGGE optimization is included in Supplementary Note.

Mentions: PCR-DGGE analysis of both the eubacterial and yeast communities were performed to understand the impact of extraction methods on the assessment of microbial community structure and diversity, as well as to verify whether the variation in DNA yield among the methods influenced the microbial community recovery. Pearson correlation based UPGMA clustering of the eubacterial PCR-DGGE profiles showed that the extraction methods with similar lysis principles mostly clustered together. This impact was clearly visible in fermented milk products in which the two major groups were clustered at 44% similarity (Fig. 2a). For a better comparison of the impact of different methods on the recovery of microbial community structure, an unsupervised principal component analysis (PCA) plotting of the extraction methods using normalized PCR-DGGE band densitometric data was performed. The PCA plot (Fig. 2b) with 52.8% variance showed that the methods based on enzymatic lysis (II, III, IV, V) and non-enzymatic lysis (I, VI) formed separate clusters (Analysis of similarity (ANOSIM), R = 0.814, p = 0.0293) while the mechanical bead beating method (VII) formed an out-group. Different diversity parameters were compared to understand the variation in eubacterial species richness and diversity (see Supplementary Table S2). Bacterial species richness (Chao1) and diversity (Shannon’s diversity) were higher in both enzyme-based methods and mechanical bead beating method for most of the food types. For subsequent analyzes, three DNA extraction methods for each food type were selected based on high DNA recovery, discrete eubacterial community profile and high eubacterial diversity. The highly diverse yeast community profiles (Fig. 2c) recovered by the selected methods underlined the importance of selecting an efficient and standard DNA extraction method for metagenomic studies. In general, the mechanical lysis by bead beating (VII) recovered higher yeast richness and diversity (see Supplementary Table S3) across all the food types.


Quantifying the biases in metagenome mining for realistic assessment of microbial ecology of naturally fermented foods
PCR-DGGE fingerprinting of eubacterial and yeast communities showed that DNA extraction methods with similar lysis principles clustered together.(a) Pearson correlation based UPGMA clustering of normalized eubacterial community PCR-DGGE fingerprints obtained from fermented milk (n = 10) showing clustering of different extraction methods. The analysis was performed in GelCompar II v6.5 with band matching performed at 1% position tolerance. Value at the nodes represents distance similarity. (b) PCA plotting of the methods using normalized PCR-DGGE fingerprints of eubacterial communities generated from all food types (n = 10 each) revealed the clustering of methods based on cell lysis principles. Clustering of the methods based on enzymatic lysis principle (II, III, IV, V) and non-enzymatic lysis principles (I, VI) is highlighted. (c) Dendrogram based on yeast community PCR-DGGE fingerprints obtained using the selected three different extraction methods in fermented milk, fish, soybean and bamboo shoot (n = 10 each). Text related to PCR-DGGE optimization is included in Supplementary Note.
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f2: PCR-DGGE fingerprinting of eubacterial and yeast communities showed that DNA extraction methods with similar lysis principles clustered together.(a) Pearson correlation based UPGMA clustering of normalized eubacterial community PCR-DGGE fingerprints obtained from fermented milk (n = 10) showing clustering of different extraction methods. The analysis was performed in GelCompar II v6.5 with band matching performed at 1% position tolerance. Value at the nodes represents distance similarity. (b) PCA plotting of the methods using normalized PCR-DGGE fingerprints of eubacterial communities generated from all food types (n = 10 each) revealed the clustering of methods based on cell lysis principles. Clustering of the methods based on enzymatic lysis principle (II, III, IV, V) and non-enzymatic lysis principles (I, VI) is highlighted. (c) Dendrogram based on yeast community PCR-DGGE fingerprints obtained using the selected three different extraction methods in fermented milk, fish, soybean and bamboo shoot (n = 10 each). Text related to PCR-DGGE optimization is included in Supplementary Note.
Mentions: PCR-DGGE analysis of both the eubacterial and yeast communities were performed to understand the impact of extraction methods on the assessment of microbial community structure and diversity, as well as to verify whether the variation in DNA yield among the methods influenced the microbial community recovery. Pearson correlation based UPGMA clustering of the eubacterial PCR-DGGE profiles showed that the extraction methods with similar lysis principles mostly clustered together. This impact was clearly visible in fermented milk products in which the two major groups were clustered at 44% similarity (Fig. 2a). For a better comparison of the impact of different methods on the recovery of microbial community structure, an unsupervised principal component analysis (PCA) plotting of the extraction methods using normalized PCR-DGGE band densitometric data was performed. The PCA plot (Fig. 2b) with 52.8% variance showed that the methods based on enzymatic lysis (II, III, IV, V) and non-enzymatic lysis (I, VI) formed separate clusters (Analysis of similarity (ANOSIM), R = 0.814, p = 0.0293) while the mechanical bead beating method (VII) formed an out-group. Different diversity parameters were compared to understand the variation in eubacterial species richness and diversity (see Supplementary Table S2). Bacterial species richness (Chao1) and diversity (Shannon’s diversity) were higher in both enzyme-based methods and mechanical bead beating method for most of the food types. For subsequent analyzes, three DNA extraction methods for each food type were selected based on high DNA recovery, discrete eubacterial community profile and high eubacterial diversity. The highly diverse yeast community profiles (Fig. 2c) recovered by the selected methods underlined the importance of selecting an efficient and standard DNA extraction method for metagenomic studies. In general, the mechanical lysis by bead beating (VII) recovered higher yeast richness and diversity (see Supplementary Table S3) across all the food types.

View Article: PubMed Central - PubMed

ABSTRACT

Cultivation-independent investigation of microbial ecology is biased by the DNA extraction methods used. We aimed to quantify those biases by comparative analysis of the metagenome mined from four diverse naturally fermented foods (bamboo shoot, milk, fish, soybean) using eight different DNA extraction methods with different cell lysis principles. Our findings revealed that the enzymatic lysis yielded higher eubacterial and yeast metagenomic DNA from the food matrices compared to the widely used chemical and mechanical lysis principles. Further analysis of the bacterial community structure by Illumina MiSeq amplicon sequencing revealed a high recovery of lactic acid bacteria by the enzymatic lysis in all food types. However, Bacillaceae, Acetobacteraceae, Clostridiaceae and Proteobacteria were more abundantly recovered when mechanical and chemical lysis principles were applied. The biases generated due to the differential recovery of operational taxonomic units (OTUs) by different DNA extraction methods including DNA and PCR amplicons mix from different methods have been quantitatively demonstrated here. The different methods shared only 29.9–52.0% of the total OTUs recovered. Although similar comparative research has been performed on other ecological niches, this is the first in-depth investigation of quantifying the biases in metagenome mining from naturally fermented foods.

No MeSH data available.


Related in: MedlinePlus