Improved sampling and DNA extraction procedures for microbiome analysis in food processing environments

Improved sampling and DNA extraction procedures for microbiome analysis in food processing environments
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As part of the European innovation action MASTER (Microbiome Applications for Sustainable food systems through Technologies and EnteRprise), it was our aim to develop standard operating procedures and tools for mapping the microbiome of foods and food processing environments to improve food quality and safety and reduce withholding periods and food waste.

Industrial food production and processing environments can harbor many different types of microorganisms, which have a substantial impact on food quality and safety. Although exhaustive cleaning and disinfection procedures are carried out inside food processing plants, there are some microorganisms which persist and can become part of a resident microbiota in different industry surfaces, mainly encased in biofilms. High Throughput DNA Sequencing (HTS) technologies are revolutionizing the study of microbiomes in many different research fields. However, different technical challenges have so far limited the application of these DNA sequencing technologies to analyze environmental microbiomes in food processing facilities, the most relevant one being the recovery of a sufficient amount of DNA from samples taken from industrial equipment, tools and surfaces. which frequently harbor very low microbial loads. Thus, an urgent need existed to develop standard procedures for microbiome analyses tailored to the particular requirements of low-biomass samples from food-production and -processing environments, especially dealing with sampling approaches, sample manipulation and storage and DNA extraction, but also covering other more unspecific aspects like library preparation, sequencing and bioinformatic analysis. In the MASTER project, the recovery of DNA from this type of samples has been improved through the design of new sampling and DNA purification procedures, in the latter case in collaboration with Qiagen, a world leader in the manufacturing of DNA purification kits. With the application of the new procedure, mean DNA concentrations of >50 ng/µL are obtained, which are sufficient for high-quality sequencing with Illumina technology, allowing even the reconstruction of bacterial genomes (>10 genomes on average per sample). The following figure demonstrate the success of the new approach for the in-depth characterization of the microbiome of low-biomass environments.

Results after reads filtering for all the samples successfully sequenced with ≥1 million reads obtained. a, Total number of reads, contigs and MAGs obtained per sample as a function of the DNA yield of the sample. The type of surface is indicated by shape, and the type of industry is indicated by colors. The gray line indicates the smoothed conditional means (calculated by geom_smooth and the ‘lm’ method in the ggplot2 R-library), and the gray shaded area indicates the standard error of the trend line. b, Total DNA and number of reads, contigs and MAGs by surface type, including negative controls taken in both the food-processing site and the laboratory. Black diamonds indicate mean values, and the central lines of box plots indicate median values. The upper and lower horizontal lines indicate the first quartile (Q1) and the third quartile (Q3), respectively; where Q3 − Q1 = IQR (interquartile range), while the vertical lines indicate Q1 − 1.5 × IQR and Q3 + 1.5 × IQR, respectively, from bottom to top. Samples with DNA concentration above the limit of detection of the Qubit high-sensitivity double-stranded DNA quantification kit (120 ng/µl) are represented as having a DNA concentration equal to 120 ng/µl. Most negative controls could not be sequenced because of very low DNA yields, and the mean represented in this figure is calculated from the small proportion of negative controls that could be sequenced.
Figure1. Overview of whole-metagenome sequecing  results. Results after reads filtering for all the samples successfully sequenced with ≥1 million reads obtained. a, Total number of reads, contigs and MAGs obtained per sample as a function of the DNA yield of the sample. The type of surface is indicated by shape, and the type of industry is indicated by colo rs. The gray line indicates the smoothed conditional means (calculated by geom_smooth and the ‘lm’ method in the ggplot2 R-library), and the gray shaded area indicates the standard error of the trend line. b, Total DNA and number of reads, contigs and MAGs by surface type, including negative controls taken in both the food-processing site and the laboratory. Black diamonds indicate mean values, and the central lines of box plots indicate median values. The upper and lower horizontal lines indicate the first quartile (Q1) and the third quartile (Q3), respectively; where Q3Q1 = IQR (interquartile range), while the vertical lines indicate Q1 − 1.5 × IQR and Q3 + 1.5 × IQR, respectively, from bottom to top. Samples with DNA concentration above the limit of detection of the Qubit high-sensitivity double-stranded DNA quantification kit (120 ng/µl) are represented as having a DNA concentration equal to 120 ng/µl. Most negative controls could not be sequenced because of very low DNA yields, and the mean represented in this figure is calculated from the small proportion of negative controls that could be sequenced.

In the article published in Nature Protocols, we firstly provide a detailed step-by-step approach for sampling inside the facilities. We include a Supplementary Video and Supplementary Note describing in detail how samples should be taken in order to maximize the recovery of microorganisms while avoiding cross-contamination from external sources. We then provide recommendations for the pre-processing and manipulation of samples to concentrate microbial cells. Subsequently, we describe the DNA purification procedure. One of the first questions we faced towards designing the experimental procedure was if there would be enough DNA to follow with sequencing. Considering that samples are obtained after cleaning and disinfection the microbial biomass was expected to be very low in some of them. In order to improve the effectiveness of DNA recovery from such type of samples, various DNA extraction protocols were tested and the one yielding the highest DNA load was selected. Finally, standard procedures for library preparation, Illumina sequencing and bioinformatic analysis are presented.

The protocol has been validated and applied in 114 processing facilities from different production sectors (meat, dairy, minimally processed vegetables, fish and seafood) in different European countries (Austria, Ireland, Iceland, Italy and Spain). Additionally, a video has been produced to demonstrate the sampling method and several outreach events and webinars have been organized for food business operators in different countries and languages. A webinar in English is available on vimeo through the following link: https://vimeo.com/837907433/5eae94c2c9.

Although the protocol was developed for the application in foods and their related processing environments, it could be also adopted for characterizing the microbiomes in other built environments, such as hospitals or households. It could be also applicable to other similar environmental and surface samples with low microbial biomass such as those from some urban surroundings.

Despite metagenomics-based approaches still have some limitations to overcome, such as the possible sequencing of DNA from death cells or from non-microbial sources, or the limited sensitivity of the technology for the detection of low-abundance microorganisms, they offer a much broader information that allows the untargeted detection and in-depth characterization of a large number of microbial taxa and genetic elements, and even the discovery of new taxa and functions. We hope that our protocol will encourage to take a step forward with the application of whole-metagenome sequencing in the food industry as an alternative, or as a complement, to the classic culture-based analyses that are carried out as part of regulated food safety management systems.

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Food Microbiology
Life Sciences > Biological Sciences > Microbiology > Food Microbiology
Next-generation sequencing
Life Sciences > Biological Sciences > Biological Techniques > Genomic Analysis > Sequencing > Next-generation sequencing
Microbiome
Life Sciences > Biological Sciences > Microbiology > Microbial Communities > Microbiome