Metagenomics applied to the food industry

Controlling microbiological contamination is of vital importance for the food industry to prevent food alterations or risks for consumers’ safety. Microbiological controls in food and work environments usually revolve around assessing microbiological indicators, for example, counting total aerobic microorganisms or enterobacteria, or identifying the presence of pathogenic microorganisms such as Listeria monocytogenes, Salmonella or Campylobacter. Thus, this type of controls focusses on detecting the presence of a series of previously selected microorganisms, without considering other unwanted microorganisms that may be present, either due to lack of awareness or because their presence is considered unlikely.

This limitation on the level of detail of the microbiological contamination study is mainly due to the fact that the type of cultivation techniques used are based on specific media for each type or group of microorganisms. It is therefore not feasible to study microbial diversity in a sample using conventional techniques. Characterising the microbial flora composition in food and production environments enables knowing in greater depth the interactions between microorganisms and food properties and providing solutions to different needs of the food industries, such as:

  • Identifying altering microorganisms and their prevalence in the production environment.
  • Applying sanitation processes adapted to particular microbiota of a production environment.
  • Identifying agents causing food alerts or food deterioration.
  • Detecting alterations in regular microbiota and identifying the causes.

The acquisition of this knowledge is now possible thanks to metagenomics, an innovative technology developed in recent years as a branch of genomic sciences. Metagenomics focuses on studying the metagenome of a specific niche, that is, the total DNA of a given environmental sample [1].

Metagenomics is a new generation sequencing technique (NGS) presented as a solid alternative to traditional microbiology, as it enables identifying all microorganisms present in a sample, at a genus and species level, by amplifying and sequencing their DNA without the need for them to be cultivable in the laboratory [2][3]. Applying metagenomics to food safety means opening a new world of possibilities, which were not accessible until recently.

This article describes one of the experiences carried out by CHRISYTEINS for improving microbiological control in a fish industry. In this study, metagenomics was applied to characterise the composition of the finished product microbiota and working areas with the aim of identifying microorganisms altering food and the transmission routes of these microorganisms. Samples were taken at different points in the process, as well as in food, throughout the storage time.

The results obtained have enabled characterising the predominant microbiota at each production process point. Figure 1 shows the percentage of relative abundance of the 4 main identified microbial genera, in each of the sampling points. As shown, the genus Pseudomonas is the most abundant, especially at the filleting, peeling and slicing points. The relative abundance of the Stenotrophomonas genus should also be noted, mainly in the cutting process.

Figure 1: Relative abundance of the 4 main microbial genera during the production process in a fishing industry.

Moreover, the metagenomic analysis of samples taken at the same production process points was performed, but this time after the cleaning and disinfection process (Figure 2).

Figure 2: Relative abundance of the 4 main microbial genera after cleaning and disinfecting throughout the production process in a fishing industry.

As shown in Figure 2, the Pseudomonas genus levels are significantly reduced after the cleaning and disinfection process. However, the figure also shows that the decrease in Pseudomonas relative abundance is accompanied by a slight increase in the relative abundance of other microbial genera such as Stenotrophomonas, Vagococcus or Acinetobacter.

Finally, the finished product and the evolution of its microbiota over time have been analysed using metagenomics, up to a maximum of 7 days. The results are shown in Figure 3.

Figure 3: Main microbial genera present in the finished product over time.

Even though Figure 3 represents the relative abundance of the 16 microbial genera found in a greater percentage in the finished product, it shows that only 2 genera prevail over time: Photobacterium and Pseudomonas.

Photobacterium has a relative abundance of approximately 40%, which remains more or less stable over time. On the other hand, Pseudomonas has a light relative abundance at the beginning, but it increases over time, reaching an abundance of approximately 40% within 3 days.

All these results lead to draw the following conclusions:

Pseudomonas is the main microbial genus present in a fish processing industry throughout its production process.

By applying cleaning and disinfection processes, Pseudomonas levels are reduced throughout the production process, slightly increasing the relative abundance of other microbial genera.

Photobacterium is a bacterial genus frequently found in raw materials from fishing origin, especially fish from aquaculture. As shown, there is not an important relative abundance during the production process, probably due to the existence of other bacterial genera in higher proportions. However, it plays yet again an important role in the finished product, where most microbial genera are reduced to very low levels.

Pseudomonas has a significant role in the finished product as it increases its relative abundance over time [4].

The results described here, together with other aspects of the production, cleaning and disinfection processes studied, have allowed identifying critical points of cross contamination that affect the useful life of food. Thus, using metagenomics, it is possible to know in greater depth the microbial ecology of food and production environments and take appropriate measures to improve their quality and safety.

At CHRISTEYNS we offer the Metasafe service that provides food and beverage industries with the necessary tools to achieve the maximum degree of control over microorganisms’ populations in food and facilities. This way, it is possible to develop safer and higher quality products and achieve better control of microbiological alerts. Metasafe is a revolutionary service in the food and agriculture sector, based on the metagenomic analysis of food, water and surface samples.



The authors wish to extend their appreciation to the Instituto Valenciano de Competitividad Empresarial (Valencian Institute of Business Competitiveness) (IVACE) for the award of the research project “Evaluación del impacto de las operaciones de limpieza y desinfección en la microbiota de las industrias alimentarias” (Assessment of the impact of cleaning and disinfection operations on microbiota of food industries » (IMIDCA/2016/19).


[1] R Hernández-León, I Velázquez-Sepúlveda, MC Orozco-Mosqueda, G Santoyo, J Exp Bot. 2010, 79, 133-1396.

[2] LM Coughlan, PD Cotter, C Hill, A Álvarez-Ordoñez, Front. Microbiol20156, 672. doi: 10.3389/fmicb.2015.00672

[3] CJ Doyle, PW O’Toole, PD Cotter. Environ. Microbiol201719, 11, 4382-4391.

[4] T Moretro, B Moen, E Heir, AA Hansen, S Lansrud. Int J. Food Microbiol2016237, 98-108.

Sanz-Puig M.1, Lorenzo F.1, Bertó R.1, Orihuel E1.


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