The science behind dry-aged meat has advanced majorly during the last few years. Unlike wet-aging, where meat is vacuum packed, the dry-aging process is conducted without packaging or protection, which may change its bacterial diversity and consequently alter its sensory characteristics. Traditional techniques and Next Generation Sequencing (NGS) stand out among the different methods used to identify bacterial diversity. This study evaluated the bacterial diversity of dry- and wet-aged beef using traditional microbiological tests and NGS to compare their specificity in bacterial diversity identification. Samples from beef strip loins (n = 6) were collected directly from the slaughterhouse and transported to the laboratory, where they were dry- or wet-aged for 20 and 34 days. Before and after aging, the samples were analyzed by traditional microbiological testing and NGS. Traditional microbiology testing found an increase in total bacterial count, particularly of psychrotrophic bacteria, in the wet-aged samples from 0 to 20 and 34 days. Dry-aged samples showed a decrease in the total bacterial count, with only molds and yeast presenting significant growth during aging. Metagenomics analysis detected eleven main bacterial genera in the meat microbiota, with a relative abundance higher than 2 %, including Carnobacterium, Pseudomonas, Lactobacillus, Romboutsia, Leuconostoc, Candidatus Nitrosotalea, and Akkermansia. Alpha diversity showed a higher richness in non-aged samples, whereas wet-aged samples (20 and 34 days) showed the lowest richness. Moreover, beta diversity analysis found that the microorganisms are highly related when considering time but form different clustering when comparing the aging process. Dry-aged beef had a higher presence (80.9 % on the 34th day) of Pseudomonas sp., a group of microorganisms with a large range of ideal bacterial growth conditions. Conversely, due to their controlled anaerobic environment, wet-aged samples showed a higher presence (79.4 % on the 34th day) of Carnobacterium. Traditional microbiology testing remains an important tool to ensure food safety since it can clearly identify the main groups of bacteria present in food. NGS, in turn, allows to identify more microbial groups but is an expensive tool, especially when considering the number of samples. Despite showing different data specificity, both techniques efficiently differentiated the beef microbiota.

Comparison of bacterial diversity in wet- and dry-aged beef using traditional microbiology and next generation sequencing / L.G. de Matos, A.C. da Silva Abreu, V.P.P. Alonso, J.L. Gonçalves, M.D. Silva do Nascimento, S.B. Pflanzer Jr, J.H. Rezende-de-Souza, C. Gini, N.F. Murad, M.M. Brandão, N.C.C. Silva. - In: THE MICROBE. - ISSN 2950-1946. - 2:(2024 Mar), pp. 100035.1-100035.7. [10.1016/j.microb.2024.100035]

Comparison of bacterial diversity in wet- and dry-aged beef using traditional microbiology and next generation sequencing

L.G. de Matos
Primo
;
C. Gini;
2024

Abstract

The science behind dry-aged meat has advanced majorly during the last few years. Unlike wet-aging, where meat is vacuum packed, the dry-aging process is conducted without packaging or protection, which may change its bacterial diversity and consequently alter its sensory characteristics. Traditional techniques and Next Generation Sequencing (NGS) stand out among the different methods used to identify bacterial diversity. This study evaluated the bacterial diversity of dry- and wet-aged beef using traditional microbiological tests and NGS to compare their specificity in bacterial diversity identification. Samples from beef strip loins (n = 6) were collected directly from the slaughterhouse and transported to the laboratory, where they were dry- or wet-aged for 20 and 34 days. Before and after aging, the samples were analyzed by traditional microbiological testing and NGS. Traditional microbiology testing found an increase in total bacterial count, particularly of psychrotrophic bacteria, in the wet-aged samples from 0 to 20 and 34 days. Dry-aged samples showed a decrease in the total bacterial count, with only molds and yeast presenting significant growth during aging. Metagenomics analysis detected eleven main bacterial genera in the meat microbiota, with a relative abundance higher than 2 %, including Carnobacterium, Pseudomonas, Lactobacillus, Romboutsia, Leuconostoc, Candidatus Nitrosotalea, and Akkermansia. Alpha diversity showed a higher richness in non-aged samples, whereas wet-aged samples (20 and 34 days) showed the lowest richness. Moreover, beta diversity analysis found that the microorganisms are highly related when considering time but form different clustering when comparing the aging process. Dry-aged beef had a higher presence (80.9 % on the 34th day) of Pseudomonas sp., a group of microorganisms with a large range of ideal bacterial growth conditions. Conversely, due to their controlled anaerobic environment, wet-aged samples showed a higher presence (79.4 % on the 34th day) of Carnobacterium. Traditional microbiology testing remains an important tool to ensure food safety since it can clearly identify the main groups of bacteria present in food. NGS, in turn, allows to identify more microbial groups but is an expensive tool, especially when considering the number of samples. Despite showing different data specificity, both techniques efficiently differentiated the beef microbiota.
Dry-aged; Wet-aged; Meat microbiota; Next-generation sequencing;
Settore VET/04 - Ispezione degli Alimenti di Origine Animale
mar-2024
20-gen-2024
https://www.sciencedirect.com/science/article/pii/S2950194624000025?ref=cra_js_challenge&fr=RR-1
Article (author)
File in questo prodotto:
File Dimensione Formato  
1-s2.0-S2950194624000025-main.pdf

accesso aperto

Tipologia: Publisher's version/PDF
Dimensione 1.55 MB
Formato Adobe PDF
1.55 MB Adobe PDF Visualizza/Apri
Pubblicazioni consigliate

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2434/1043489
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus ND
  • ???jsp.display-item.citation.isi??? ND
social impact