Metagenomics insights into food fermentations

Robust Approaches for the Production of Active Ingredient and Drug Product for Human Phage Therapy

To be successful, academic and commercial efforts to reintroduce phage therapy must ensure that only safe and efficacious products are used to treat patients. This raises a number of manufacturing, formulation, and delivery challenges. Since phages are biologics, robust manufacturing processes will be crucial to avoid unwanted variability in each step of the process. The quality standards themselves need to be developed, as patients are currently being treated with phages produced under quality standards ranging from cGMP for clinical trials in EMA and FDA regulated environments to no standards at all in some last resort treatments. In this short review, we will systematically review the literature covering technical issues and approaches to increase robustness at every step of the production process: the identity of the phage and bacterial production strains, the fermentation process and purification, the formulation of the drug product, the quality controls and the documentation standards themselves. We conclude that it is possible to control cost at the same time, which is critical to re-introduce phage therapy to western medicine.

Novel sequencing technologies to support industrial biotechnology

Industrial biotechnology develops and applies microorganisms for the production of bioproducts and enzymes with applications ranging from food and feed ingredients and processing to bio-based chemicals, biofuels and pharmaceutical products. Next generation DNA sequencing technologies play an increasingly important role in improving and accelerating microbial strain development for existing and novel bio-products via screening, gene and pathway discovery, metabolic engineering and additional optimization and understanding of large-scale manufacturing. In this mini-review, we describe novel DNA sequencing and analysis technologies with a focus on applications to industrial strain development, enzyme discovery and microbial community analysis.

On the Role of Bioinformatics and Data Science in Industrial Microbiome Applications

Advances in sequencing and computational biology have drastically increased our capability to explore the taxonomic and functional compositions of microbial communities that play crucial roles in industrial processes. Correspondingly, commercial interest has risen for applications where microbial communities make important contributions. These include food production, probiotics, cosmetics, and enzyme discovery. Other commercial applications include software that takes the user's gut microbiome data as one of its inputs and outputs evidence-based, automated, and personalized diet recommendations for balanced blood sugar levels. These applications pose several bioinformatic and data science challenges that range from requiring strain-level resolution in community profiles to the integration of large datasets for predictive machine learning purposes. In this perspective, we provide our insights on such challenges by touching upon several industrial areas, and briefly discuss advances and future directions of bioinformatics and data science in microbiome research.

Systems Biology - A Guide for Understanding and Developing Improved Strains of Lactic Acid Bacteria

Lactic Acid Bacteria (LAB) are extensively employed in the production of various fermented foods, due to their safe status, ability to affect texture and flavor and finally due to the beneficial effect they have on shelf-life. More recently, LAB have also gained interest as production hosts for various useful compounds, particularly compounds with sensitive applications, such as food ingredients and therapeutics. As for all industrial microorganisms, it is important to have a good understanding of the physiology and metabolism of LAB in order to fully exploit their potential, and for this purpose, many systems biology approaches are available. Systems metabolic engineering, an approach that combines optimization of metabolic enzymes/pathways at the systems level, synthetic biology as well as in silico model simulation, has been used to build microbial cell factories for production of biofuels, food ingredients and biochemicals. When developing LAB for use in foods, genetic engineering is in general not an accepted approach. An alternative is to screen mutant libraries for candidates with desirable traits using high-throughput screening technologies or to use adaptive laboratory evolution to select for mutants with special properties. In both cases, by using omics data and data-driven technologies to scrutinize these, it is possible to find the underlying cause for the desired attributes of such mutants. This review aims to describe how systems biology tools can be used for obtaining both engineered as well as non-engineered LAB with novel and desired properties.

AFLP protocol comparison for microbial diversity fingerprinting

Over the last decade, several methods based on genomic DNA have been developed for the identification and genotyping of prokaryotic and eukaryotic organisms. These genomic methods differ regarding taxonomic range, discriminatory power, reproducibility, and ease of interpretation and standardization. The amplified fragment length polymorphism (AFLP) technique is a very powerful DNA fingerprinting technique for DNA of any source or complexity, varying in both size and base composition. In addition, this method shows high discriminatory power and good reproducibility allowing it to be efficient in discriminating at both the species and strain levels. The development and application of AFLP have allowed significant progress in the study of biodiversity and taxonomy of microorganisms. In the last years, the Applied Biosystems AFLP Microbial Fingerprinting Kit, now out of production, was widely used in various studies to perform AFLP characterization of selected bacteria strains (described by Vos et al. (Nucleic Acids Res 23(21):4407-4414, 1995)). Its replacement gives the possibility for laboratories to continue the use of the previous AFLP data as a reference for bacteria genetic fingerprinting analysis in biodiversity studies. To overcome this issue a result comparison, by using an improved AFLP protocol and the AFLP commercial kit, was performed. In particular, previous results on different species (Listeria monocytogenes, Lactobacillus plantarum, and Streptococcus thermophilus) obtained with the commercial kit were compared with the improved AFLP procedure to validate the protocol. When compared with the AFLP Microbial Fingerprinting Kit, the improved protocol shows high reproducibility, resolution, and overall, is a faster method with lower costs.

Fungal Species Diversity in French Bread Sourdoughs Made of Organic Wheat Flour

Microbial communities are essential for the maintenance and functioning of ecosystems, including fermented food ecosystems. The analysis of food microbial communities is mainly focused on lactic acid bacteria (LAB), while yeast diversity is less understood. Here, we describe the fungal diversity of a typical food fermented product, sourdough bread. The species diversity of 14 sourdoughs collected from bakeries located all over France was analyzed. Bakeries were chosen to represent diverse bakery practices and included bakers and farmer-bakers. Both non-culture-based (pyrosequencing of Internal Transcribed Spacer 1 amplicons) and culture-based methods were used. While both identification methods were in agreement regarding the dominant yeast species of each sourdough, the ITS1 metabarcoding analysis identified an increased number of fungal species in sourdough communities. Two third of the identified sequences obtained from sourdoughs were Saccharomycetales, mostly in the Kazachstania genus. No Saccharomycetales species was shared by all the sourdoughs, whereas five other fungal species, mainly known plant pathogens, were found in all sourdoughs. Interestingly, Saccharomyces cerevisiae, known as “baker’s yeast,” was identified as the dominant species in only one sourdough. By contrast, five Kazachstania species were identified as the dominant sourdough species, including one recently described Kazachstania species, Kazachstania saulgeensis and an undescribed Kazachstania sp. Sourdoughs from farmer-bakers harbored Kazachstania bulderi, Kazachstania unispora and two newly described Kazachstania species, while sourdough from bakers mostly carried Kazachstania humilis as the dominant species. Such yeast diversity has not been found in sourdoughs before, highlighting the need to maintain different traditional food practices to conserve microbial diversity.

The Microbiome of an Active Meat Curing Brine

Traditional food products are important to our culture and heritage, and to the continued success of the food industry. Many of the production processes associated with these products have not been subjected to an in-depth microbial compositional analysis. The traditional process of curing meat, both preserves a natural protein source, as well as increasing its organoleptic qualities. One of the most important salting processes is known as Wiltshire curing. The Wiltshire process involves injecting pork with a curing solution and immersing the meat into microbial-rich brine which promotes the development of the distinct organoleptic characteristics. The important microbial component of Wiltshire brine has not been extensively characterized. We analyzed the key microbial component of Wiltshire brine by performing microbiome analysis using Next Generation Sequencing (NGS) technologies. This analysis identified the genera, Marinilactibacillus, Carnobacterium, Leuconostoc, and Vibrio as the core microflora present in Wiltshire curing brine. The important food industrial applications of these bacteria were also assessed. The bacterial diversity of the brine was investigated, and the community composition of the brine was demonstrated to change over time. New knowledge on the characterization of key microbiota associated with a productive Wiltshire brine is an important development linked to promoting enhanced quality and safety of meat processing in the food industry.

Exploring Foodborne Pathogen Ecology and Antimicrobial Resistance in the Light of Shotgun Metagenomics

In this chapter, applications of shotgun metagenomics for taxonomic profiling and functional investigation of food microbial communities with a focus on antimicrobial resistance (AMR) were overviewed in the light of last data in the field. Potentialities of metagenomic approach, along with the challenges encountered for a wider and routinely use in food safety was discussed.

Characterization and Antimicrobial Susceptibility of Lactococcus lactis Isolated from Endodontic Infections in Ouagadougou, Burkina Faso

Background: This study aimed to characterize and test the antimicrobial susceptibility of Lactococcus lactis isolated in endodontic infections in Burkina Faso. Material and methods: This was a prospective study conducted at the Municipal Oral Health Center of Ouagadougou, Burkina Faso, from June to October 2014. Clinical data were collected using a questionnaire form. The method of streaking on selective medium was used to isolate bacteria. Identification was made using the API 20 Strep gallery. Antibiotic susceptibility was performed by the diffusion method on solid medium. Results: One hundred and twenty-five (125) patients were received with a significant proportion from the age group of 19 to 40 years (55.2%). Apical periodontitis accounted for 50.4% and cellulitis for 49.6% of cases. Lactococcus lactis ssp. lactis was identified in five exudate samples. Isolates were 100% resistant to cefixime and metronidazole, 80% to ceftriaxone, cefuroxime, cefotaxime, chloramphenicol and 60% to penicillin G, amoxicillin, amoxicillin clavulanic acid. A multidrug resistance of more than three families of antibiotics was noticed. No strains produced extended spectrum ß-lactamases. Conclusion: Lactococcus lactis is part of endodontic biofilm. The reported strong antibiotic resistance involving endodontic therapy will focus on the effect of the disinfectant solution and the mechanical action of the canal instruments.

Correlation between microbiota and flavours in fermentation of Chinese Sichuan Paocai

Sichuan Paocai (SCP), a traditional fermentationed food, possesses unique flavours driven by various microbiota in fermentation ecosystems. However, the association between these microbiota and flavours is poorly understood. Here, we measured the structural dynamics of the microbial diversity and flavour compounds during SCP fermentation (0-7 days) using high-throughput sequencing and flavour analyses. Firstly, a total of 90 bacteria and 135 fungi were identified. The results showed that fermentation process was initiated by environmental microorganisms, such as Micrococcaceae, followed by a heterolactic fermentation phase dominated by Leuconostocaceae, and finally succeeded by homolactic fermentation led by Lactobacillaceae. Secondly, 6 organic acids, 12 amino acids and 86 volatile flavours were detected. The fermentation process was divided into 4 stages based on flavours: Day 0; Days 1-3; Days 4-6; and Day 7. Analysis of the correlation between microbiota and flavours indicated that bacteria contributed more to flavours formation than did fungi, and Lactobacillus, Leuconostoc, Achromobacter and Pediococcus were closely correlated with flavours. This study provides a systematic method for understanding the characteristics of fermented foods and useful guidelines for screening of strains that produce desirable flavours and functional substances.

How the Fewest Become the Greatest. L. casei's Impact on Long Ripened Cheeses

Members of the Lactobacillus casei group, including species classified currently as L. casei, L. paracasei, and L. rhamnosus, are among the most frequently found species in raw milk, hard cooked, long-ripened cheeses. Starting from very low numbers in raw milk, they become dominant in the cheese during ripening, selected by physical and chemical changes produced by cheese making and ripening. Their presence at different stages of cheese making and ripening is crucial in defining product features. For these reasons, the scientific community has been more and more interested in studying these “tiny but mighty microbes” and their implications during cheese making and ripening. The present paper reviews the current literature on the effect of L. casei in cheeses, with particular reference to the case of Parmigiano Reggiano and Grana Padano, two of the most famous PDO (Protected Designation of Origin) Italian cheeses. Recent advances regarding the selection of new wild strains able to persist until the end of ripening and carrying out slow but crucial activities resulting in specific aromatic features, are also presented.

Spoilage yeasts: What are the sources of contamination of foods and beverages?

Foods and beverages are nutrient-rich ecosystems in which most microorganisms are able to grow. Moreover, several factors, such as physicochemical characteristics, storage temperature, culinary practices, and application of technologies for storage, also define the microbial population of foods and beverages. The yeast population has been well-characterised in fresh and processed fruit and vegetables, dairy products, dry-cured meat products, and beverages, among others. Some species are agents of alteration in different foods and beverages. Since the most comprehensive studies of spoilage yeasts have been performed in the winemaking process, hence, these studies form the thread of the discussion in this review. The natural yeast populations in raw ingredients and environmental contamination in the manufacturing facilities are the main modes by which food contamination occurs. After contamination, yeasts play a significant role in food and beverage spoilage, particularly in the alteration of fermented foods. Several mechanisms contribute to spoilage by yeasts, such as the production of lytic enzymes (lipases, proteases, and cellulases) and gas, utilisation of organic acids, discolouration, and off-flavours. This review addresses the role of yeasts in foods and beverages degradation by considering the modes of contamination and colonisation by yeasts, the yeast population diversity, mechanisms involved, and the analytical techniques for their identification, primarily molecular methods.

Profiling white wine seed vinegar bacterial diversity through viable counting, metagenomic sequencing and PCR-DGGE

The production of traditional vinegar is usually carried out using the so-called "seed vinegar" or "mother of vinegar" that is composed of an undefined and complex pool of microorganisms deriving from a previous vinegar production. To date, there have been relatively few studies on the microbiota of seed vinegars. The present study was carried out to discover the bacterial biota of seed vinegar samples used in the homemade production of local vinegars obtained from the acetic fermentation of white wine. The seed vinegar samples were subjected to viable counting and advanced molecular analyses, namely, Illumina sequencing and PCR-DGGE. The adopted polyphasic approach allowed the bacterial diversity of the analyzed samples to be profiled, thus revealing the presence of acetic acid bacteria ascribed to the genera Acetobacter, Gluconacetobacter, Gluconobacter and Komagataeibacter. Moreover, other microbial genera as Pseudomonas, Bacillus and Clostridium were abundantly found in almost all the samples, together with other minority genera. The results of viable counting confirmed the well-acknowledged limitations inherent with acetic acid bacteria recovery on plate growth media. The overall results confirmed that seed vinegars have a complex and heterogeneous biodiversity, thus encouraging their exploitation for the isolation and future technological characterization of cultures to be selected for the manufacture of mixed starter cultures.

Sequencing of the Cheese Microbiome and Its Relevance to Industry

The microbiota of cheese plays a key role in determining its organoleptic and other physico-chemical properties. It is essential to understand the various contributions, positive or negative, of these microbial components in order to promote the growth of desirable taxa and, thus, characteristics. The recent application of high throughput DNA sequencing (HTS) facilitates an even more accurate identification of these microbes, and their functional properties, and has the potential to reveal those microbes, and associated pathways, responsible for favorable or unfavorable characteristics. This technology also facilitates a detailed analysis of the composition and functional potential of the microbiota of milk, curd, whey, mixed starters, processing environments, and how these contribute to the final cheese microbiota, and associated characteristics. Ultimately, this information can be harnessed by producers to optimize the quality, safety, and commercial value of their products. In this review we highlight a number of key studies in which HTS was employed to study the cheese microbiota, and pay particular attention to those of greatest relevance to industry.

Apical periodontitis: preliminary assessment of microbiota by 16S rRNA high throughput amplicon target sequencing

Background

Apical periodontitis includes periapical granulomas and radicular cysts, which are histologically distinguished by the absence and the presence of an epithelial lining, respectively. The main cause of apical periodontitis is the bacterial colonization of the root canal space. This research aimed at assessing whether and how periapical granulomas and radicular cysts differ in terms of microbiota using high throughput amplicon target sequencing (HTS) techniques.

Methods

This study included 5 cases of Periapical Granulomas (PGs) and 5 cases of Radicular Cysts (RCs) selected on the base of histology out of 37 patients from January 2015 to February 2016. Complete medical history, panoramic radiograms (OPTs) and histologic records of each patient were assessed. Only lesions greater than 1 cm in diameter and developed in proximity to teeth with bad prognosis were included. The microbiota present in periapical granulomas and radicular cysts thus retrieved was finely characterized by pyrosequencing of the 16S rRNA genes.

Results

The core of OTUs shared between periapical granulomas and radicular cysts was dominated by the presence of facultative anaerobes taxa such as: Lactococcus lactis, Propionibacterium acnes, Staphylococcus warneri, Acinetobacter johnsonii and Gemellales. L. lactis, the main OTUs of the entire datasets, was associated with periapical granuloma samples. Consistently with literature, the anaerobic taxa detected were most abundant in radicular cyst samples. Indeed, a higher abundance of presumptive predicted metabolic pathways related to Lipopolysaccharide biosynthesis was found in radicular cyst samples.

Conclusions

The present pilot study confirmed the different microbial characterization of the two main apical periodontitis types and shade light on the possible role of L. lactis in periapical granulomas.

Species classifier choice is a key consideration when analysing low-complexity food microbiome data

BACKGROUND

The use of shotgun metagenomics to analyse low-complexity microbial communities in foods has the potential to be of considerable fundamental and applied value. However, there is currently no consensus with respect to choice of species classification tool, platform, or sequencing depth. Here, we benchmarked the performances of three high-throughput short-read sequencing platforms, the Illumina MiSeq, NextSeq 500, and Ion Proton, for shotgun metagenomics of food microbiota. Briefly, we sequenced six kefir DNA samples and a mock community DNA sample, the latter constructed by evenly mixing genomic DNA from 13 food-related bacterial species. A variety of bioinformatic tools were used to analyse the data generated, and the effects of sequencing depth on these analyses were tested by randomly subsampling reads.

RESULTS

Compositional analysis results were consistent between the platforms at divergent sequencing depths. However, we observed pronounced differences in the predictions from species classification tools. Indeed, PERMANOVA indicated that there was no significant differences between the compositional results generated by the different sequencers (p = 0.693, R² = 0.011), but there was a significant difference between the results predicted by the species classifiers (p = 0.01, R² = 0.127). The relative abundances predicted by the classifiers, apart from MetaPhlAn2, were apparently biased by reference genome sizes. Additionally, we observed varying false-positive rates among the classifiers. MetaPhlAn2 had the lowest false-positive rate, whereas SLIMM had the greatest false-positive rate. Strain-level analysis results were also similar across platforms. Each platform correctly identified the strains present in the mock community, but accuracy was improved slightly with greater sequencing depth. Notably, PanPhlAn detected the dominant strains in each kefir sample above 500,000 reads per sample. Again, the outputs from functional profiling analysis using SUPER-FOCUS were generally accordant between the platforms at different sequencing depths. Finally, and expectedly, metagenome assembly completeness was significantly lower on the MiSeq than either on the NextSeq (p = 0.03) or the Proton (p = 0.011), and it improved with increased sequencing depth.

CONCLUSIONS

Our results demonstrate a remarkable similarity in the results generated by the three sequencing platforms at different sequencing depths, and, in fact, the choice of bioinformatics methodology had a more evident impact on results than the choice of sequencer did.

Advancement in LH-PCR methodology for multiple microbial species detections in fermented foods

The length-heterogeneity PCR is a low throughput molecular biology methods explored to monitor bacteria populations in different environments. It could be more used in food microbiology analysis, not only for fingerprinting analysis, but it has been hampered until now by a limiting factor which relates to the high percentage of secondary peaks. With the aim to overcome this problem, different experiments were performed focusing on changing PCR parameters in order to obtain more specific amplicon patterns and also to reduce the complexity of community patterns. With this purpose, different annealing temperatures were tested on complex fermented food matrices taken from both animal and vegetable origin and also on the bacteria isolated from the same food source. In particular, the optimal annealing temperature identified for the fermented food samples is 59 °C and the optimal for bacterial strains varied between 63 °C and 65 °C. The approach allowed the modification of the LH-PCR protocol increasing the amplification efficiency and therefore the bacteria species discrimination. These temperatures also allowed the implementation of the previous LH-PCR published database. The modification in the level of accuracy of the LH-PCR technique could also allow an improvement in the relative species quantification by the peak area evaluation.

Symposium review: Interaction of starter cultures and nonstarter lactic acid bacteria in the cheese environment

The microbiota of ripening cheese is dominated by lactic acid bacteria, which are either added as starters and adjunct cultures or originate from the production and processing environments (nonstarter or NSLAB). After curd formation and pressing, starters reach high numbers, but their viability then decreases due to lactose depletion, salt addition, and low pH and temperature. Starter autolysis releases cellular contents, including nutrients and enzymes, into the cheese matrix. During ripening, NSLAB may attain cell densities up to 8 log cfu per g after 3 to 9 mo. Depending on the species and strain, their metabolic activity may contribute to defects or inconsistency in cheese quality and to the development of typical cheese flavor. The availability of gene and genome sequences has enabled targeted detection of specific cheese microbes and their gene expression over the ripening period. Integrated systems biology is needed to combine the multiple perspectives of post-genomics technologies to elucidate the metabolic interactions among microorganisms. Future research should delve into the variation in cell physiology within the microbial populations, because spatial distribution within the cheese matrix will lead to microenvironments that could affect localized interactions of starters and NSLAB. Microbial community modeling can contribute to improving the efficiency and reduce the cost of food processes such as cheese ripening.

Dietary Fibers and Protective Lactobacilli Drive Burrata Cheese Microbiome

This study was aimed at improving the functional attributes and shelf life of burrata cheese by using protective lactobacilli (Lactobacillus plantarum LPAL and Lactobacillus rhamnosus LRB), fructooligosaccharides, and inulin. Six burrata cheeses were made using (i) the traditional protocol (control), (ii) the addition of 0.5% fructooligosaccharides and inulin (DF cheese), (iii) protective lactobacilli in milk alone (PL cheese), (iv) protective lactobacilli in milk and governing liquid (2PL cheese), (v) protective lactobacilli in milk and dietary fibers (DF_PL cheese), and (vi) protective lactobacilli in milk and governing liquid and dietary fibers (DF_2PL cheese). As expected, DF, DF_PL, and DF_2PL cheeses showed 1.5% of total fibers. Burrata cheeses produced by adding protective lactobacilli only in milk (PL and DF_PL cheeses) showed the lowest acidification during cheese making and storage. Lactic and acetic acids and ethanol were found at the lowest concentrations in these samples. Analyses of cultivable microbiota and the microbiome showed that protective lactobacilli reduced the house microbiota components (e.g., Streptococcus thermophilus, Lactococcus lactis, and Leuconostoc lactis) during cheese making and storage. Protective lactobacilli slowed the growth of staphylococci, coliforms, and Pseudomonas spp., especially in early storage. According to the different microbiome assemblies, burrata samples differed in peptide profiles and the levels of free amino acids. As shown by a sensory analysis, the addition of protective lactobacilli in milk improved the flavor and increased the shelf life of burrata cheese. In comparison to cheeses made using protective cultures only in milk, the shelf lives of those containing cultures also in the governing liquid were not further prolonged and they received lower acceptability scores by the panelists.IMPORTANCE This study provides more in-depth knowledge of the microbiome of burrata cheese and the set-up for a novel biotechnology using prebiotic dietary fibers and protective probiotic Lactobacillus plantarum LPAL and Lactobacillus rhamnosus LRB in milk. The biotechnology proposed in this study should be considered a useful tool to improve the functional value of burrata cheese. The use of protective lactobacilli in milk enhanced the flavor formation and shelf life of burrata cheese.

A Review on the Applications of Next Generation Sequencing Technologies as Applied to Food-Related Microbiome Studies

The development of next generation sequencing (NGS) techniques has enabled researchers to study and understand the world of microorganisms from broader and deeper perspectives. The contemporary advances in DNA sequencing technologies have not only enabled finer characterization of bacterial genomes but also provided deeper taxonomic identification of complex microbiomes which in its genomic essence is the combined genetic material of the microorganisms inhabiting an environment, whether the environment be a particular body econiche (e.g., human intestinal contents) or a food manufacturing facility econiche (e.g., floor drain). To date, 16S rDNA sequencing, metagenomics and metatranscriptomics are the three basic sequencing strategies used in the taxonomic identification and characterization of food-related microbiomes. These sequencing strategies have used different NGS platforms for DNA and RNA sequence identification. Traditionally, 16S rDNA sequencing has played a key role in understanding the taxonomic composition of a food-related microbiome. Recently, metagenomic approaches have resulted in improved understanding of a microbiome by providing a species-level/strain-level characterization. Further, metatranscriptomic approaches have contributed to the functional characterization of the complex interactions between different microbial communities within a single microbiome. Many studies have highlighted the use of NGS techniques in investigating the microbiome of fermented foods. However, the utilization of NGS techniques in studying the microbiome of non-fermented foods are limited. This review provides a brief overview of the advances in DNA sequencing chemistries as the technology progressed from first, next and third generations and highlights how NGS provided a deeper understanding of food-related microbiomes with special focus on non-fermented foods.

BeerDeCoded: the open beer metagenome project

Next generation sequencing has radically changed research in the life sciences, in both academic and corporate laboratories. The potential impact is tremendous, yet a majority of citizens have little or no understanding of the technological and ethical aspects of this widespread adoption. We designed BeerDeCoded as a pretext to discuss the societal issues related to genomic and metagenomic data with fellow citizens, while advancing scientific knowledge of the most popular beverage of all. In the spirit of citizen science, sample collection and DNA extraction were carried out with the participation of non-scientists in the community laboratory of Hackuarium, a not-for-profit organisation that supports unconventional research and promotes the public understanding of science. The dataset presented herein contains the targeted metagenomic profile of 39 bottled beers from 5 countries, based on internal transcribed spacer (ITS) sequencing of fungal species. A preliminary analysis reveals the presence of a large diversity of wild yeast species in commercial brews. With this project, we demonstrate that coupling simple laboratory procedures that can be carried out in a non-professional environment with state-of-the-art sequencing technologies and targeted metagenomic analyses, can lead to the detection and identification of the microbial content in bottled beer.

BeerDeCoded: the open beer metagenome project

Next generation sequencing has radically changed research in the life sciences, in both academic and corporate laboratories. The potential impact is tremendous, yet a majority of citizens have little or no understanding of the technological and ethical aspects of this widespread adoption. We designed BeerDeCoded as a pretext to discuss the societal issues related to genomic and metagenomic data with fellow citizens, while advancing scientific knowledge of the most popular beverage of all. In the spirit of citizen science, sample collection and DNA extraction were carried out with the participation of non-scientists in the community laboratory of Hackuarium, a not-for-profit organisation that supports unconventional research and promotes the public understanding of science. The dataset presented herein contains the targeted metagenomic profile of 39 bottled beers from 5 countries, based on internal transcribed spacer (ITS) sequencing of fungal species. A preliminary analysis reveals the presence of a large diversity of wild yeast species in commercial brews. With this project, we demonstrate that coupling simple laboratory procedures that can be carried out in a non-professional environment, with state-of-the-art sequencing technologies and targeted metagenomic analyses, can lead to the detection and identification of the microbial content in bottled beer.

Different Amplicon Targets for Sequencing-Based Studies of Fungal Diversity

Target-gene amplicon sequencing is the most exploited high-throughput sequencing application in microbial ecology. The targets are taxonomically relevant genes, with 16S rRNA being the gold standard for bacteria. As for fungi, the most commonly used target is the internal transcribed spacer (ITS). However, the uneven ITS length among species may promote preferential amplification and sequencing and incorrect estimation of their abundance. Therefore, the use of different targets is desirable. We evaluated the use of three different target amplicons for the characterization of fungal diversity. After an in silico primer evaluation, we compared three amplicons (the ITS1-ITS2 region [ITS1-2], 18S ribosomal small subunit RNA, and the D1/D2 domain of the 26S ribosomal large subunit RNA), using biological samples and a mock community of common fungal species. All three targets allowed for accurate identification of the species present. Nevertheless, high heterogeneity in ITS1-2 length was found, and this caused an overestimation of the abundance of species with a shorter ITS, while both 18S and 26S amplicons allowed for more reliable quantification. We demonstrated that ITS1-2 amplicon sequencing, although widely used, may lead to an incorrect evaluation of fungal communities, and efforts should be made to promote the use of different targets in sequencing-based microbial ecology studies.IMPORTANCE Amplicon-sequencing approaches for fungi may rely on different targets affecting the diversity and abundance of the fungal species. An increasing number of studies will address fungal diversity by high-throughput amplicon sequencing. The description of the communities must be accurate and reliable in order to draw useful insights and to address both ecological and biological questions. By analyzing a mock community and several biological samples, we demonstrate that using different amplicon targets may change the results of fungal microbiota analysis, and we highlight how a careful choice of the target is fundamental for a thorough description of the fungal communities.

Metabolic gene-targeted monitoring of non-starter lactic acid bacteria during cheese ripening

Long ripened cheeses, such as Grana Padano (GP), a Protected Designation of Origin (PDO) Italian cheese, harbor a viable microbiota mainly composed of non-starter lactic acid bacteria (NSLAB), which contribute to the final characteristics of cheese. The NSLAB species Lactobacillus rhamnosus, Lb. casei and Lb. paracasei are frequently found in GP, and form a closely related taxonomic group (Lb. casei group), making it difficult to distinguish the three species through 16S rRNA sequencing. SpxB, a metabolic gene coding for pyruvate oxidase in Lb. casei group, was recently used to distinguish the species within this bacterial group, both in pure cultures and in cheese, where it could provide an alternative energy source through the conversion of pyruvate to acetate. The aim of this work was to study the evolution of the metabolically active microbiota during different stages of GP ripening, targeting 16S rRNA to describe the whole microbiota composition, and spxB gene to monitor the biodiversity within the Lb. casei group. Furthermore, activation of pyruvate oxidase pathway was measured directly in cheese by reverse transcription real time PCR (RT-qPCR). The results showed that Lb. casei group dominates throughout the ripening and high-throughput sequencing of spxB allowed to identify four clusters inside the Lb. casei group. The dynamics of the sequence types forming the clusters were followed during ripening. Pyruvate oxidase pathway was expressed in cheese, showing a decreasing trend over ripening time. This work highlights how the composition of the microbiota in the early manufacturing stages influences the microbial dynamics throughout ripening, and how targeting of a metabolic gene can provide an insight into the activity of strains relevant for dairy products.

Metagenomic Approaches to Assess Bacteriophages in Various Environmental Niches

Bacteriophages are ubiquitous and numerous parasites of bacteria and play a critical evolutionary role in virtually every ecosystem, yet our understanding of the extent of the diversity and role of phages remains inadequate for many ecological niches, particularly in cases in which the host is unculturable. During the past 15 years, the emergence of the field of viral metagenomics has drastically enhanced our ability to analyse the so-called viral ‘dark matter’ of the biosphere. Here, we review the evolution of viral metagenomic methodologies, as well as providing an overview of some of the most significant applications and findings in this field of research.

Metagenomics insights into food fermentations

This review describes the recent advances in the study of food microbial ecology, with a focus on food fermentations. High‐throughput sequencing (HTS) technologies have been widely applied to the study of food microbial consortia and the different applications of HTS technologies were exploited in order to monitor microbial dynamics in food fermentative processes. Phylobiomics was the most explored application in the past decade. Metagenomics and metatranscriptomics, although still underexploited, promise to uncover the functionality of complex microbial consortia. The new knowledge acquired will help to understand how to make a profitable use of microbial genetic resources and modulate key activities of beneficial microbes in order to ensure process efficiency, product quality and safety.