Shotgun Metagenomics and Volatilome Profile of the Microbiota of Fermented Sausages

Abstract

Changes in the microbial gene content and abundance can be analyzed to detect shifts in the microbiota composition due to the use of a starter culture in the food fermentation process, with the consequent shift of key metabolic pathways directly connected with product acceptance. Meat fermentation is a complex process involving microbes that metabolize the main components in meat. The breakdown of carbohydrates, proteins, and lipids can lead to the formation of volatile organic compounds (VOCs) that can drastically affect the organoleptic characteristics of the final products. The present meta-analysis, performed with the shotgun DNA metagenomic approach, focuses on studying the microbiota and its gene content in an Italian fermented sausage produced by using a commercial starter culture (a mix of Lactobacillus sakei and Staphylococcus xylosus), with the aim to discover the connections between the microbiota, microbiome, and the release of volatile metabolites during ripening. The inoculated fermentation with the starter culture limited the development of Enterobacteriaceae and reduced the microbial diversity compared to that from spontaneous fermentation. KEGG database genes associated with the reduction of acetaldehyde to ethanol (EC 1.1.1.1), acetyl phosphate to acetate (EC 2.7.2.1), and 2,3-butanediol to acetoin (EC 1.1.1.4) were most abundant in inoculated samples (I) compared to those in spontaneous fermentation samples (S). The volatilome profiles were highly consistent with the abundance of the genes; elevated acetic acid (1,173.85 μg/kg), ethyl acetate (251.58 μg/kg), and acetoin (1,100.19 μg/kg) were observed in the presence of the starters at the end of fermentation. Significant differences were found in the liking of samples based on flavor and odor, suggesting a higher preference by consumers for the spontaneous fermentation samples. Inoculated samples exhibited the lowest scores for the liking data, which were clearly associated with the highest concentration of acetic acid.IMPORTANCE We present an advance in the understanding of meat fermentation by coupling DNA sequencing metagenomics and metabolomics approaches to describe the microbial function during this process. Very few studies using this global approach have been dedicated to food, and none have examined sausage fermentation, underlying the originality of the study. The starter culture drastically affected the organoleptic properties of the products. This finding underlines the importance of starter culture selection that takes into consideration the functional characteristics of the microorganism to optimize production efficiency and product quality.

Keywords: fermented sausages; metabolic pathways; shotgun metagenomics; volatile organic compounds.

FIG 1

Taxonomy analysis of fermented sausages. The plot shows the distribution of taxa during ripening. Only taxa with an incidence above 0.5% in at least 2 samples are shown. Samples are labeled according to time (0, 3, 7, and 40 days) and type (S, spontaneous; I, inoculated).

FIG 2

Functional classification of fermented sausages during ripening. Functional classes were determined according to the first level of the KEGG annotations. Samples are color coded according to time (0, 3, 7, and 40 days) and type (S, spontaneous; I, inoculated). Data in the two batches for each sampling time were averaged.

FIG 3

Relationships between metabolic pathways and samples. KEGG network summarizing the relationships between metabolic pathways related to carbohydrates (red), amino acids (yellow), and lipids (blue) and samples (cyan, spontaneous; green, inoculated). Metabolic pathways and samples are connected with lines (i.e., edges) for which the thickness is proportional to the abundance of that pathway in the connected sample.

FIG 4

Abundance of VOCs during ripening. Acetic acid, acetoin, and ethyl acetate concentrations over time (0, 3, 7, and 40 days) and under two fermentation conditions (red, inoculated; blue, spontaneous fermentation). Boxes represent the interquartile ranges (IQRs) between the first and third quartiles, and the lines inside represent the medians (2nd quartiles). Whiskers denote the lowest and the highest values within IQRs from the first and third quartiles, respectively. Circles represent outliers beyond the whiskers.

FIG 5

Correlation patterns between VOCs and samples. Correlations between the abundance of VOCs and spontaneous fermented (S) and inoculated (I) samples. Rows and columns are clustered by Ward linkage hierarchical clustering. The intensity of the colors represents the degree of correlation between the samples and VOCs as measured by Spearman's correlations.

FIG 6

Correlations between taxa, ripening-related metabolic pathways, and volatilome data. Correlation network showing significant (false-discovery rate [FDR], <0.05) Spearman's correlations between KEGG genes belonging to amino acid and lipid metabolism, VOCs, and taxa. Node sizes are proportional to the numbers of significant correlations. Colors of the edges indicate negative (blue) or positive (pink) correlations.

FIG 7

Liking test. (A) Radar graphs displaying the liking of appearance, odor, taste, flavor, and texture and overall liking expressed by consumers for the sausages made by spontaneous and inoculated fermentation. (B) Distributions of the liking scores of flavor and odor (P < 0.05) for fermentation conditions (red, inoculated; blue, spontaneous fermentation). Boxes represent the interquartile ranges (IQRs) between the first and third quartiles, and the lines inside represent the medians (2nd quartiles). Whiskers denote the lowest and the highest values within IQRs from the first and third quartiles, respectively. Circles represent outliers beyond the whiskers.