Metagenomic and metatranscriptomic analysis of the microbial community in Swiss-type Maasdam cheese during ripening

Development and evaluation of statistical and artificial intelligence approaches with microbial shotgun metagenomics data as an untargeted screening tool for use in food production

The increasing knowledge of microbial ecology in food products relating to quality and safety and the established usefulness of machine learning algorithms for anomaly detection in multiple scenarios suggests that the application of microbiome data in food production systems for anomaly detection could be a valuable approach to be used in food systems. These methods could be used to identify ingredients that deviate from their typical microbial composition, which could indicate food fraud or safety issues. The objective of this study was to assess the feasibility of using shotgun sequencing data as input into anomaly detection algorithms using fluid milk as a model system. Contrastive principal component analysis (PCA), cluster-based methods, and explainable artificial intelligence (AI) were evaluated for the detection of two anomalous sample classes using longitudinal metagenomic profiling of fluid milk compared to baseline (BL) samples collected under comparable circumstances. Traditional methods (alpha and beta diversity, clustering-based contrastive PCA, multidimensional scaling, and dendrograms) failed to differentiate anomalous sample classes; however, explainable AI was able to classify anomalous vs baseline samples and indicate microbial drivers in association with antibiotic use. We validated the potential for explainable AI to classify different milk sources using larger publicly available fluid milk 16S rDNA sequencing data sets and demonstrated that explainable AI is able to differentiate between milk storage methods, processing stages, and seasons. Our results indicate that the application of artificial intelligence continues to hold promise in the realm of microbiome data analysis and could present further opportunities for downstream analytic automation to aid in food safety and quality.

IMPORTANCE

We evaluated the feasibility of using untargeted metagenomic sequencing of raw milk for detecting anomalous food ingredient content with artificial intelligence methods in a study specifically designed to test this hypothesis. We also show through analysis of publicly available fluid milk microbial data that our artificial intelligence approach is able to successfully predict milk in different stages of processing. The approach could potentially be applied in the food industry for safety and quality control.

Unexplored microbial diversity from 2,500 food metagenomes and links with the human microbiome

Complex microbiomes are part of the food we eat and influence our own microbiome, but their diversity remains largely unexplored. Here, we generated the open access curatedFoodMetagenomicData (cFMD) resource by integrating 1,950 newly sequenced and 583 public food metagenomes. We produced 10,899 metagenome-assembled genomes spanning 1,036 prokaryotic and 108 eukaryotic species-level genome bins (SGBs), including 320 previously undescribed taxa. Food SGBs displayed significant microbial diversity within and between food categories. Extension to >20,000 human metagenomes revealed that food SGBs accounted on average for 3% of the adult gut microbiome. Strain-level analysis highlighted potential instances of food-to-gut transmission and intestinal colonization (e.g., Lacticaseibacillus paracasei) as well as SGBs with divergent genomic structures in food and humans (e.g., Streptococcus gallolyticus and Limosilactobabillus mucosae). The cFMD expands our knowledge on food microbiomes, their role in shaping the human microbiome, and supports future uses of metagenomics for food quality, safety, and authentication.

The effects of soaking in salted blackcurrant wine on the properties of cheese

The study assessed the effects of soaking hard cheeses and cheese slices in blackcurrant wine on their antioxidant, microbiological, and sensory properties. Soaking increased weekly, the phenolic content by 40.86 ± 0.3 mg GAE/100 g (gallic acid equivalent) of cheese, and their reached the maximum ethanol content of 1.29 ± 0.08 g/100 g. Soaking reduced the amount of foodborne pathogenic bacteria, enhancing microbiological safety. The lactic acid bacteria count significantly decreased during soaking time. The sensory evaluation shows that 45 % of tasters preferred the soaked cheese. Positive correlations were observed between taste and color (in whole-soaked cheese), while negative correlations were revealed among color, smell, and texture (in soaked quarter cheese). The results suggest that blackcurrant wine, containing a wealth of bioactive constituents, has the capacity to augment the favorable attributes of cheese and presents prospects for developing a novel gastronomic offering.

gNOMO2: a comprehensive and modular pipeline for integrated multi-omics analyses of microbiomes

BACKGROUND

In recent years, omics technologies have offered an exceptional chance to gain a deeper insight into the structural and functional characteristics of microbial communities. As a result, there is a growing demand for user-friendly, reproducible, and versatile bioinformatic tools that can effectively harness multi-omics data to provide a holistic understanding of microbiomes. Previously, we introduced gNOMO, a bioinformatic pipeline tailored to analyze microbiome multi-omics data in an integrative manner. In response to the evolving demands within the microbiome field and the growing necessity for integrated multi-omics data analysis, we have implemented substantial enhancements to the gNOMO pipeline.

RESULTS

Here, we present gNOMO2, a comprehensive and modular pipeline that can seamlessly manage various omics combinations, ranging from 2 to 4 distinct omics data types, including 16S ribosomal RNA (rRNA) gene amplicon sequencing, metagenomics, metatranscriptomics, and metaproteomics. Furthermore, gNOMO2 features a specialized module for processing 16S rRNA gene amplicon sequencing data to create a protein database suitable for metaproteomics investigations. Moreover, it incorporates new differential abundance, integration, and visualization approaches, enhancing the toolkit for a more insightful analysis of microbiomes. The functionality of these new features is showcased through the use of 4 microbiome multi-omics datasets encompassing various ecosystems and omics combinations. gNOMO2 not only replicated most of the primary findings from these studies but also offered further valuable perspectives.

CONCLUSIONS

gNOMO2 enables the thorough integration of taxonomic and functional analyses in microbiome multi-omics data, offering novel insights in both host-associated and free-living microbiome research. gNOMO2 is available freely at https://github.com/muzafferarikan/gNOMO2.

Microbial interactions shape cheese flavour formation

Cheese fermentation and flavour formation are the result of complex biochemical reactions driven by the activity of multiple microorganisms. Here, we studied the roles of microbial interactions in flavour formation in a year-long Cheddar cheese making process, using a commercial starter culture containing Streptococcus thermophilus and Lactococcus strains. By using an experimental strategy whereby certain strains were left out from the starter culture, we show that S. thermophilus has a crucial role in boosting Lactococcus growth and shaping flavour compound profile. Controlled milk fermentations with systematic exclusion of single Lactococcus strains, combined with genomics, genome-scale metabolic modelling, and metatranscriptomics, indicated that S. thermophilus proteolytic activity relieves nitrogen limitation for Lactococcus and boosts de novo nucleotide biosynthesis. While S. thermophilus had large contribution to the flavour profile, Lactococcus cremoris also played a role by limiting diacetyl and acetoin formation, which otherwise results in an off-flavour when in excess. This off-flavour control could be attributed to the metabolic re-routing of citrate by L. cremoris from diacetyl and acetoin towards α-ketoglutarate. Further, closely related Lactococcus lactis strains exhibited different interaction patterns with S. thermophilus, highlighting the significance of strain specificity in cheese making. Our results highlight the crucial roles of competitive and cooperative microbial interactions in shaping cheese flavour profile.

Metagenomic Insights into the Taxonomic and Functional Features of Traditional Fermented Milk Products from Russia

Fermented milk products (FMPs) contain probiotics that are live bacteria considered to be beneficial to human health due to the production of various bioactive molecules. In this study, nine artisanal FMPs (kefir, ayran, khurunga, shubat, two cottage cheeses, bryndza, khuruud and suluguni-like cheese) from different regions of Russia were characterized using metagenomics. A metagenomic sequencing of ayran, khurunga, shubat, khuruud and suluguni-like cheese was performed for the first time. The taxonomic profiling of metagenomic reads revealed that Lactococcus species, such as Lc. lactis and Lc. cremoris prevailed in khuruud, bryndza, one sample of cottage cheese and khurunga. The latter one together with suluguni-like cheese microbiome was dominated by bacteria, affiliated to Lactobacillus helveticus (32-35%). In addition, a high proportion of sequences belonging to the genera Lactobacillus, Lactococcus and Streptococcus but not classified at the species level were found in the suluguni-like cheese. Lactobacillus delbrueckii, as well as Streptococcus thermophilus constituted the majority in another cottage cheese, kefir and ayran metagenomes. The microbiome of shubat, produced from camel's milk, was significantly distinctive, and Lentilactobacillus kefiri, Lactobacillus kefiranofaciens and Bifidobacterium mongoliense represented the dominant components (42, 7.4 and 5.6%, respectively). In total, 78 metagenome-assembled genomes with a completeness ≥ 50.2% and a contamination ≤ 8.5% were recovered: 61 genomes were assigned to the Enterococcaceae, Lactobacillaceae and Streptococcaceae families (the Lactobacillales order within Firmicutes), 4 to Bifidobacteriaceae (the Actinobacteriota phylum) and 2 to Acetobacteraceae (the Proteobacteria phylum). A metagenomic analysis revealed numerous genes, from 161 to 1301 in different products, encoding glycoside hydrolases and glycosyltransferases predicted to participate in lactose, alpha-glucans and peptidoglycan hydrolysis as well as exopolysaccharides synthesis. A large number of secondary metabolite biosynthetic gene clusters, such as lanthipeptides, unclassified bacteriocins, nonribosomal peptides and polyketide synthases were also detected. Finally, the genes involved in the synthesis of bioactive compounds like β-lactones, terpenes and furans, nontypical for fermented milk products, were also found. The metagenomes of kefir, ayran and shubat was shown to contain either no or a very low count of antibiotic resistance genes. Altogether, our results show that traditional indigenous fermented products are a promising source of novel probiotic bacteria with beneficial properties for medical and food industries.

Applications of multi-omics techniques to unravel the fermentation process and the flavor formation mechanism in fermented foods

Fermented foods are important components of the human diet. There is increasing awareness of abundant nutritional and functional properties present in fermented foods that arise from the transformation of substrates by microbial communities. Thus, it is significant to unravel the microbial communities and mechanisms of characteristic flavor formation occurring during fermentation. There has been rapid development of high-throughput and other omics technologies, such as metaproteomics and metabolomics, and as a result, there is growing recognition of the importance of integrating these approaches. The successful applications of multi-omics approaches and bioinformatics analyses have provided a solid foundation for exploring the fermentation process. Compared with single-omics, multi-omics analyses more accurately delineate microbial and molecular features, thus they are more apt to reveal the mechanisms of fermentation. This review introduces fermented foods and an overview of single-omics technologies - including metagenomics, metatranscriptomics, metaproteomics, and metabolomics. We also discuss integrated multi-omics and bioinformatic analyses and their role in recent research progress related to fermented foods, as well as summarize the main potential pathways involved in certain fermented foods. In the future, multilayered analyses of multi-omics data should be conducted to enable better understanding of flavor formation mechanisms in fermented foods.

Fungal communities on alpine cheese rinds in Southern Switzerland

BACKGROUND

The biodiversity of the mycobiota of soft cheese rinds such as Brie or Camembert has been extensively studied, but scant information is available on the fungi colonizing the rinds of cheese produced in the Southern Switzerland Alps. This study aimed at exploring the fungal communities present on rinds of cheese matured in five cellars in Southern Switzerland and to evaluate their composition with regards to temperature, relative humidity, type of cheese, as well as microenvironmental and geographic factors. We used macro- and microscopical morphology, matrix-assisted laser desorption/ionization-time of flight (MALDI-TOF) mass spectrometry, and sequencing to characterize the fungal communities of the cheeses, and compared them with metabarcoding targeting the ITS region.

RESULTS

Isolation by serial dilution yielded 201 isolates (39 yeasts and 162 filamentous fungi) belonging to 9 fungal species. Mucor and Penicillium were dominant, with Mucor racemosus, M. lanceolatus, P. biforme, and P. chrysogenum/rubens being the most frequent species. All but two yeast isolates were identified as Debaryomyces hansenii. Metabarcoding detected 80 fungal species. Culture work and metabarcoding produced comparable results in terms of similarity of the fungal cheese rind communities in the five cellars.

CONCLUSIONS

Our study has shown that the mycobiota on the rinds of the cheeses studied is a comparatively species-poor community influenced by temperature, relative humidity, type of cheese, and manufacturing steps, as well as microenvironmental and possibly geographic factors.

Development of processed low-sodium Maasdam cheese

ABSTRACT The article assesses the effect of different potassium emulsifying salts concentrations on physicochemical, colorimetric, and texture characteristics of processed cheese manufactured using Maasdam. Except for pH, physicochemical parameters remained unchanged, but the gradual substitution of sodium emulsifying salts with potassium-based salts influenced color and texture. Treatments with at least 50% potassium salts showed a reduction of at least 30% of sodium. The sodium decrease allows the product's classification as processed cheese with low-sodium content (<140mg per 56.7g serving). The data obtained present substantial information that can help the dairy industries develop newly reduced-sodium products.

Authenticity and Typicity of Traditional Cheeses: A Review on Geographical Origin Authentication Methods

Food fraud, corresponding to any intentional action to deceive purchasers and gain an undue economical advantage, is estimated to result in a 10 to 65 billion US dollars/year economical cost worldwide. Dairy products, such as cheese, in particular cheeses with protected land- and tradition-related labels, have been listed as among the most impacted as consumers are ready to pay a premium price for traditional and typical products. In this context, efficient food authentication methods are needed to counteract current and emerging frauds. This review reports the available authentication methods, either chemical, physical, or DNA-based methods, currently used for origin authentication, highlighting their principle, reported application to cheese geographical origin authentication, performance, and respective advantages and limits. Isotope and elemental fingerprinting showed consistent accuracy in origin authentication. Other chemical and physical methods, such as near-infrared spectroscopy and nuclear magnetic resonance, require more studies and larger sampling to assess their discriminative power. Emerging DNA-based methods, such as metabarcoding, showed good potential for origin authentication. However, metagenomics, providing a more in-depth view of the cheese microbiota (up to the strain level), but also the combination of methods relying on different targets, can be of interest for this field.

Elucidation of the initial bacterial community of Ezine PDO cheese using next-generation sequencing

This study aims to reveal initial bacterial consortia of Ezine PDO cheeses comprehensively by following a metagenomic approach. A total of 8 artisanal Ezine cheese samples were collected from the Bayramiç and Ezine districts of Çanakkale province of Turkey. Ezine cheese was found to contain Firmicutes, Bacteroidetes, and Proteobacteria phyla dominantly. Streptococcus, Lactococcus, and Lactobacillus genera dominated the microbiota with relative abundances of 4.47-56.07%, 7.33-20.34%, and 1.21-25.12%, respectively, followed by Bacteroides and Prevotella genera. Excluding two cheese samples obtained from the Ezine district, the most dominant species was Streptococcus thermophilus (8.24-54.34%). It was also found in greater proportions in the cheeses of the Bayramiç district. Unexpectedly, Lactobacillus graminis (11.50-23.63%) was the most abundant species in two samples collected from the Ezine district. However, lower bacterial diversity was determined in the samples collected from the Bayramiç district. The lowest species richness was 129 OTU-species in the cheeses from the Bayramiç district while the highest species richness was 267 OTU-species in cheeses from the Ezine district. In addition, the Simpson index was the highest in cheeses from the Ezine district, where different species were evenly distributed. Permutational multivariate analysis of variance tests also confirmed that the differences in the structure of bacterial consortia in cheeses from two different districts were statistically significant. This study will provide pioneer data for further investigations on the role of complex bacterial composition in maintaining and improving the quality and safety of Ezine cheese.

In silico metatranscriptomic approach for tracking biofilm-related effectors in dairies and its importance for improving food safety

Sessile microorganisms are usually recalcitrant to antimicrobial treatments, and it is possible that finding biofilm-related effectors in metatranscriptomics datasets helps to understand mechanisms for bacterial persistence in diverse environments, by revealing protein-encoding genes that are expressed in situ. For this research, selected dairy-associated metatranscriptomics bioprojects were downloaded from the public databases JGI GOLD and NCBI (eight milk and 45 cheese samples), to screen for sequences encoding biofilm-related effectors. Based on the literature, the selected genetic determinants were related to adhesins, BAP, flagellum-related, intraspecific QS (AHL, HK, and RR), interspecific QS (LuxS), and QQ (AHL-acylases, AHL-lactonases). To search for the mRNA sequences encoding for those effector proteins, a custom database was built from UniprotKB, yielding 1,154,446 de-replicated sequences that were indexed in DIAMOND for alignment. The results revealed that in all the dairy-associated metatranscriptomic datasets obtained, there were reads assigned to genes involved with flagella, adhesion, and QS/QQ, but BAP-reads were found only for milk. Significant Pearson correlations (p < 0.05) were observed for transcripts encoding for flagella, RR, histidine kinases, adhesins, and LuxS, although no other significant correlations were found. In conclusion, the rationale used in this study was useful to demonstrate the presence of biofilm-associated effectors in metatranscriptomics datasets, pointing out to possible regulatory mechanisms in action in dairy-related biofilms, which could be targeted in the future to improve food safety.

Extensive diversity and rapid turnover of phage defense repertoires in cheese-associated bacterial communities

BACKGROUND

Phages are key drivers of genomic diversity in bacterial populations as they impose strong selective pressure on the evolution of bacterial defense mechanisms across closely related strains. The pan-immunity model suggests that such diversity is maintained because the effective immune system of a bacterial species is the one distributed across all strains present in the community. However, only few studies have analyzed the distribution of bacterial defense systems at the community-level, mostly focusing on CRISPR and comparing samples from complex environments. Here, we studied 2778 bacterial genomes and 188 metagenomes from cheese-associated communities, which are dominated by a few bacterial taxa and occur in relatively stable environments.

RESULTS

We corroborate previous laboratory findings that in cheese-associated communities nearly identical strains contain diverse and highly variable arsenals of innate and adaptive (i.e., CRISPR-Cas) immunity systems suggesting rapid turnover. CRISPR spacer abundance correlated with the abundance of matching target sequences across the metagenomes providing evidence that the identified defense repertoires are functional and under selection. While these characteristics align with the pan-immunity model, the detected CRISPR spacers only covered a subset of the phages previously identified in cheese, providing evidence that CRISPR does not enable complete immunity against all phages, and that the innate immune mechanisms may have complementary roles.

CONCLUSIONS

Our findings show that the evolution of bacterial defense mechanisms is a highly dynamic process and highlight that experimentally tractable, low complexity communities such as those found in cheese, can help to understand ecological and molecular processes underlying phage-defense system relationships. These findings can have implications for the design of robust synthetic communities used in biotechnology and the food industry. Video Abstract.

Potential of Meta-Omics to Provide Modern Microbial Indicators for Monitoring Soil Quality and Securing Food Production

Soils are fundamental resources for agricultural production and play an essential role in food security. They represent the keystone of the food value chain because they harbor a large fraction of biodiversity-the backbone of the regulation of ecosystem services and "soil health" maintenance. In the face of the numerous causes of soil degradation such as unsustainable soil management practices, pollution, waste disposal, or the increasing number of extreme weather events, it has become clear that (i) preserving the soil biodiversity is key to food security, and (ii) biodiversity-based solutions for environmental monitoring have to be developed. Within the soil biodiversity reservoir, microbial diversity including Archaea, Bacteria, Fungi and protists is essential for ecosystem functioning and resilience. Microbial communities are also sensitive to various environmental drivers and to management practices; as a result, they are ideal candidates for monitoring soil quality assessment. The emergence of meta-omics approaches based on recent advances in high-throughput sequencing and bioinformatics has remarkably improved our ability to characterize microbial diversity and its potential functions. This revolution has substantially filled the knowledge gap about soil microbial diversity regulation and ecology, but also provided new and robust indicators of agricultural soil quality. We reviewed how meta-omics approaches replaced traditional methods and allowed developing modern microbial indicators of the soil biological quality. Each meta-omics approach is described in its general principles, methodologies, specificities, strengths and drawbacks, and illustrated with concrete applications for soil monitoring. The development of metabarcoding approaches in the last 20 years has led to a collection of microbial indicators that are now operational and available for the farming sector. Our review shows that despite the recent huge advances, some meta-omics approaches (e.g., metatranscriptomics or meta-proteomics) still need developments to be operational for environmental bio-monitoring. As regards prospects, we outline the importance of building up repositories of soil quality indicators. These are essential for objective and robust diagnosis, to help actors and stakeholders improve soil management, with a view to or to contribute to combining the food and environmental quality of next-generation farming systems in the context of the agroecological transition.

Omics Approaches to Assess Flavor Development in Cheese

Cheese is characterized by a rich and complex microbiota that plays a vital role during both production and ripening, contributing significantly to the safety, quality, and sensory characteristics of the final product. In this context, it is vital to explore the microbiota composition and understand its dynamics and evolution during cheese manufacturing and ripening. Application of high-throughput DNA sequencing technologies have facilitated the more accurate identification of the cheese microbiome, detailed study of its potential functionality, and its contribution to the development of specific organoleptic properties. These technologies include amplicon sequencing, whole-metagenome shotgun sequencing, metatranscriptomics, and, most recently, metabolomics. In recent years, however, the application of multiple meta-omics approaches along with data integration analysis, which was enabled by advanced computational and bioinformatics tools, paved the way to better comprehension of the cheese ripening process, revealing significant associations between the cheese microbiota and metabolites, as well as their impact on cheese flavor and quality.

Resource recovery of lignocellulosic biomass waste into lactic acid - Trends to sustain cleaner production

Biomass waste generation concerns regulatory authorities to develop novel methods to sustain biotransformation processes. Particularly, lactic acid (LA) is a bulk commodity chemical used in diverse industries and holds a growing global market demand. Recently, lignocellulosic waste biomass is preferred for LA bio-production because of its non-edible and inexpensive nature. However, the information about new pretreatment methods for lignocellulosic feedstock, and novel strains capable to produce LA through fermentation is limited. Therefore, this review highlights the advancement of pretreatments methods of lignocellulosic biomass and biotransformation. Herein, we first briefly explored the main sources of lignocellulosic waste biomass, then we explored their latest advances in pretreatment processes particularly supercritical fluid extraction, and microwave-assisted extraction. Approaches for bioconversion were also analyzed, such as consolidated bioprocessing (CBP), simultaneous saccharification and fermentation (SSF), separate hydrolysis fermentation (SHF), among other alternatives. Also, new trends and approaches were documented, such as metagenomics to find novel strains of microorganisms and the use of recombinant strategies for the creation of new strains. Finally, we developed a holistic and sustainable perspective based on novel microbial ecology tools such as next-gen sequencing, bioinformatics, and metagenomics. All these shed light on the needs to culture powerful microbial isolates, co-cultures, and mixed consortia to improve fermentation processes with the aim of optimizing cultures and feedstock pretreatments.

Foodomic-Based Approach for the Control and Quality Improvement of Dairy Products

The food quality assurance before selling is a needed requirement intended for protecting consumer interests. In the same way, it is also indispensable to promote continuous improvement of sensory and nutritional properties. In this regard, food research has recently contributed with studies focused on the use of 'foodomics'. This review focuses on the use of this technology, represented by transcriptomics, proteomics, and metabolomics, for the control and quality improvement of dairy products. The complex matrix of these foods requires sophisticated technology able to extract large amounts of information with which to influence their aptitude for consumption. Thus, throughout the article, different applications of the aforementioned technologies are described and discussed in essential matters related to food quality, such as the detection of fraud and/or adulterations, microbiological safety, and the assessment and improvement of transformation industrial processes (e.g., fermentation and ripening). The magnitude of the reported results may open the door to an in-depth transformation of the most conventional analytical processes, with the introduction of new techniques that allow a greater understanding of the biochemical phenomena occurred in this type of food.

Next-Generation Food Research: Use of Meta-Omic Approaches for Characterizing Microbial Communities Along the Food Chain

Microorganisms exist along the food chain and impact the quality and safety of foods in both positive and negative ways. Identifying and understanding the behavior of these microbial communities enable the implementation of preventative or corrective measures in public health and food industry settings. Current culture-dependent microbial analyses are time-consuming and target only specific subsets of microbes. However, the greater use of culture-independent meta-omic approaches has the potential to facilitate a thorough characterization of the microbial communities along the food chain. Indeed, these methods have shown potential in contributing to outbreak investigation, ensuring food authenticity, assessing the spread of antimicrobial resistance, tracking microbial dynamics during fermentation and processing, and uncovering the factors along the food chain that impact food quality and safety. This review examines the community-based approaches, and particularly the application of sequencing-based meta-omics strategies, for characterizing microbial communities along the food chain. Expected final online publication date for the Annual Review of Food Science and Technology, Volume 13 is March 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

A Review on the General Cheese Processing Technology, Flavor Biochemical Pathways and the Influence of Yeasts in Cheese

Cheese has a long history and this naturally fermented dairy product contains a range of distinctive flavors. Microorganisms in variety cheeses are an essential component and play important roles during both cheese production and ripening. However, cheeses from different countries are still handmade, the processing technology is diverse, the microbial community structure is complex and the cheese flavor fluctuates greatly. Therefore, studying the general processing technology and relationship between microbial structure and flavor formation in cheese is the key to solving the unstable quality and standardized production of cheese flavor on basis of maintaining the flavor of cheese. This paper reviews the research progress on the general processing technology and key control points of natural cheese, the biochemical pathways for production of flavor compounds in cheeses, the diversity and the role of yeasts in cheese. Combined with the development of modern detection technology, the evolution of microbial structure, population evolution and flavor correlation in cheese from different countries was analyzed, which is of great significance for the search for core functional yeast microorganisms and the industrialization prospect of traditional fermented cheese.

Identification and characterization of extracellular enzymes secreted by Aspergillus spp. involved in lipolysis and lipid-antioxidation during katsuobushi fermentation and ripening

A mild-flavored soup stock made from katsuobushi is an important element of traditional Japanese cuisine and is the basic seasoning responsible for the taste. Fermented and ripened katsuobushi, known as karebushi, is manufactured by simmering skipjack tuna that is then smoke-dried, fermented, and ripened in a repeated molding process by five dominant Aspergillus species. Here, our aim was to characterize and identify the lipolytic enzymes secreted by the dominant Aspergillus species, especially A. chevalieri and A. pseudoglaucus, which are involved in hydrolyzing lipids during the molding process. The crude enzyme preparations from the five Aspergillus spp. cultivated on katsuobushi solid medium hydrolyzed triglycerides in fish oil, and more saturated and unsaturated fatty acids (C16:0, C16:1, C18:0, C18:1) were produced than major polyunsaturated fatty acids (C20:5, C22:6). On the basis of ion exchange chromatograms, the composition of the lipolytic enzymes was different in the five species. There was at least one active fraction with high hydrolytic activity toward fish oil in four of the Aspergillus spp., but not A. sydowii; the lipolytic enzyme secreted by A. sydowii had quite high activity toward the artificial substrate p-nitrophenyl butyrate, but low activity toward the natural oil. The lipolytic fractions from A. chevalieri and A. pseudoglaucus were further purified by hydrophobic interaction chromatography then gel-filtration chromatography; LC-MS-MS Mascot analysis identified a variety of lipolytic enzymes, including cutinase, esterase, phospholipase, and carboxyl esterase in the lipolytic fractions from these species. The identified enzymes had 30%-70% identity to previously reported or manually annotated lipases or esterases from taxa other than Aspergillus. The different lipolytic enzymes likely acted on triglycerides in the katsuobushi fish oil. Furthermore, catalase B and Cu/Zn superoxide dismutase, which limit oxidative damage of lipids, were also identified. These antioxidant enzymes may prevent lipid oxidation and rancidity as the lipolytic enzymes hydrolyze lipids during the long fermentation and ripening process. Umami and richness tastes tended to increase in extracts from culture of protease- and peptidase-producing A. sydowii. Our results will aid in the selection and application of desirable strains of Aspergillus species as starter cultures to improve the storage and quality of fermented and ripened karebushi.

Bio-augmented effect of Bacillus amyloliquefaciens and Candida versatilis on microbial community and flavor metabolites during Chinese horse bean-chili-paste fermentation

Chinese horse bean-chili-paste (CHCP), a fermented condiment in China, is traditionally manufactured through naturally spontaneous semi-solid fermentation procedures without intentionally inoculated microorganisms. The aim of this study was to investigate the effect on microbiota and quality variations during CHCP fermentation by inoculation of selected autochthonous microorganisms Bacillus amyloliquefaciens and Candida versatilis. The results showed that relative abundance of Bacillus in the samples inoculated with B. amyloliquefaciens were increased from about 0.6% to almost 25%, and the batches bio-augmented with C. versatilis exhibited clearly 0.7 Lg copies/g higher biomass than that of the other samples. By bio-augmentation, six enzyme activities, namely acid protease, leucine aminopeptidase, α-amylase, cellulose, β-glucosidase and esterase, were considerably enhanced. As a result, inoculation of these two strains exhibited significant effect on the volatile profiles of CHCP. B. amyloliquefaciens herein was found to contribute mainly to the accumulation of acids, sulfur-containing compounds and pyrazines, whereas C. versatilis was considerably associated with the formation of alcohols, esters and phenols. This study proved that combination of B. amyloliquefaciens and C. versatilis could obtain more extensive aroma profiles, especially for the enrichment of miso-like and fruity flavors, which could provide a guideline for the tailored control of CHCP fermentation process.

Lifestyle, metabolism and environmental adaptation in Lactococcus lactis

Lactococcus lactis serves as a paradigm organism for the lactic acid bacteria (LAB). Extensive research into the molecular biology, metabolism and physiology of several model strains of this species has been fundamental for our understanding of the LAB. Genomic studies have provided new insights into the species L. lactis, including the resolution of the genetic basis of its subspecies division, as well as the control mechanisms involved in the fine-tuning of growth rate and energy metabolism. In addition, it has enabled novel approaches to study lactococcal lifestyle adaptations to the dairy application environment, including its adjustment to near-zero growth rates that are particularly relevant in the context of cheese ripening. This review highlights various insights in these areas and exemplifies the strength of combining experimental evolution with functional genomics and bacterial physiology research to expand our fundamental understanding of the L. lactis lifestyle under different environmental conditions.

Monitoring the microbiome for food safety and quality using deep shotgun sequencing

In this work, we hypothesized that shifts in the food microbiome can be used as an indicator of unexpected contaminants or environmental changes. To test this hypothesis, we sequenced the total RNA of 31 high protein powder (HPP) samples of poultry meal pet food ingredients. We developed a microbiome analysis pipeline employing a key eukaryotic matrix filtering step that improved microbe detection specificity to >99.96% during in silico validation. The pipeline identified 119 microbial genera per HPP sample on average with 65 genera present in all samples. The most abundant of these were Bacteroides, Clostridium, Lactococcus, Aeromonas, and Citrobacter. We also observed shifts in the microbial community corresponding to ingredient composition differences. When comparing culture-based results for Salmonella with total RNA sequencing, we found that Salmonella growth did not correlate with multiple sequence analyses. We conclude that microbiome sequencing is useful to characterize complex food microbial communities, while additional work is required for predicting specific species' viability from total RNA sequencing.

The diversity of microbial communities in Chinese milk fan and their effects on volatile organic compound profiles

Milk fan is a cheese-like fermented milk product produced in Yunnan Province, China. In this study, we characterized the microbial communities of milk fan from 6 distinct geographical origins and investigated their generation of volatile organic compounds (VOC). The microbial communities found in all milk fan samples were dominated by Lactococcus, Lactobacillus, and Raoultella bacteria and Rhodotorula, Torulaspora, and Candida fungi. Samples from the Kunming and Weishan regions had greater bacterial richness, and samples from Xizhou had greater fungal community richness. Sixty prominent VOC (i.e., those having odor activity values ≥1), including esters, acids, alcohols, aldehydes, ketones, and aromatic compounds, were identified by gas chromatography-mass spectrometry analysis of milk fan samples. Pearson correlation analysis revealed that Lactobacillus, Rhodotorula, Lodderomyces, and Debaryomyces had significant correlations with various VOC, revealing a total of 13 compounds that are characteristic of the odor of milk fan. These bacteria and fungi are therefore identified as functional microorganisms that collectively create the complex VOC profile of milk fan. This study provides a comprehensive overview of the microbial community of milk fan and demonstrates its contribution to the unique aroma profile of this fermented milk product.

Metatranscriptomic approach reveals the functional and enzyme dynamics of core microbes during noni fruit fermentation

Noni (Morinda citrifolia L.) has been recognized as an important herb for treating various physiological disorders worldwide. Fermented noni fruit juice, established as a novel food in European Union, is the most important noni product. However, the structure, functions and enzyme profiles of microbiome during fermentation remain unclear. The metatranscriptomic was used to comprehensively explore the active microbial community and key metabolic function. Acetobacter sp., Acetobacter aceti and Gluconobacter sp. were the major microorganisms and appeared in succession during fermentation. According to principal components analysis (PCA) of metabolism-related unigenes by KEGG database, the fermentation process was divided into three stages and almost completed at the end of the second stage. Furthermore, carbohydrate-active enzymes (CAZymes) and the expression of key enzymes in major metabolic pathways were analyzed systematically. Analysis by HS-SPME-GC-MS and odor active value (OAV) revealed that butanoic acid and hexanoic acid were the main volatile compounds for the unpleasant odor of fermented noni fruit juice. The microbiome in the fermentation process lacked key enzymes that degrade butanoic acid and hexanoic acid, which imparted rancid and sweat odor. This study provides theoretical basis for product improvement and new product development, thus promoting the development of noni food industry.

Metagenomics for taxonomy profiling: tools and approaches

The study of metagenomics is an emerging field that identifies the total genetic materials in an organism along with the set of all genetic materials like deoxyribonucleic acid and ribose nucleic acid, which play a key role with the maintenance of cellular functions. The best part of this technology is that it gives more flexibility to environmental microbiologists to instantly pioneer the immense genetic variability of microbial communities. However, it is intensively complex to identify the suitable sequencing measures of any specific gene that can exclusively indicate the involvement of microbial metagenomes and be able to advance valuable results about these communities. This review provides an overview of the metagenomic advancement that has been advantageous for aggregation of more knowledge about specific genes, microbial communities and its metabolic pathways. More specific drawbacks of metagenomes technology mainly depend on sequence-based analysis. Therefore, this 'targeted based metagenomics' approach will give comprehensive knowledge about the ecological, evolutionary and functional sequence of significantly important genes that naturally exist in living beings either human, animal and microorganisms from distinctive ecosystems.

Transcriptomic Analysis of Staphylococcus xylosus in Solid Dairy Matrix Reveals an Aerobic Lifestyle Adapted to Rind

Staphylococcus xylosus is found in the microbiota of traditional cheeses, particularly in the rind of soft smeared cheeses. Despite its frequency, the molecular mechanisms allowing the growth and adaptation of S. xylosus in dairy products are still poorly understood. A transcriptomic approach was used to determine how the gene expression profile is modified during the fermentation step in a solid dairy matrix. S. xylosus developed an aerobic metabolism perfectly suited to the cheese rind. It overexpressed genes involved in the aerobic catabolism of two carbon sources in the dairy matrix, lactose and citrate. Interestingly, S. xylosus must cope with nutritional shortage such as amino acids, peptides, and nucleotides, consequently, an extensive up-regulation of genes involved in their biosynthesis was observed. As expected, the gene sigB was overexpressed in relation with general stress and entry into the stationary phase and several genes under its regulation, such as those involved in transport of anions, cations and in pigmentation were up-regulated. Up-regulation of genes encoding antioxidant enzymes and glycine betaine transport and synthesis systems showed that S. xylosus has to cope with oxidative and osmotic stresses. S. xylosus expressed an original system potentially involved in iron acquisition from lactoferrin.

Comparative metagenomics and characterization of antimicrobial resistance genes in pasteurized and homemade fermented Arabian laban

The aim of this study was to investigate bacterial diversity and function in a fermented milk drink called laban, which is traditionally served in the Middle East, Africa, and Indian subcontinent. Pasteurized laban (LBP) and unpasteurized, homemade, raw laban (LBR) underwent 16S rRNA gene amplicon and shotgun sequencing to analyze their bacterial community, presence of antimicrobial resistance genes (ARGs), and metabolic pathways. This study highlighted relatively greater diversity in LBR bacterial populations compared to LBP, despite containing similar major taxa that consisted primarily of Firmicutes followed by Proteobacteria, Bacteroidetes, and Actinobacteria. The dominant species, Streptococcus thermophilus, was relatively more abundant in LBP (80.7%) compared to LBR (47.9%). LBR had increased diversity and higher relative abundance of several known probiotic bacteria, such as Streptococcus salivarius and Lactococcus lactis, whereas Lactobacillus acidophilus was detected at a higher abundance in LBP. Pathogens like Acinetobacter baumannii, Streptococcus pneumoniae, Streptococcus pyogenes, and Escherichia coli had lower abundance in LBP compared to LBR. Thirty-three ARGs were detected in LBR compared to nine in LBP and are responsible for resistance to 11 classes of antibiotics. A significant proportion of the metagenomes from both types of laban were assigned to housekeeping functions, such as amino acid metabolism, translation, membrane transport, and carbohydrate metabolism. LBR demonstrated increased diversity in probiotics and metabolic functions compared to LBP. However, the relatively high diversity of pathogenic and opportunistic bacteria and ARGs in LBR raises safety concerns and highlights the need for a more hygienic environment for the processing of homemade fermented dairy foods.

Extracellular and intracellular DNA for bacterial profiling of long-ripened cheeses

A novel approach was developed to extract the extracellular DNA (eDNA), i.e. the free DNA outside the microbial cell, compared to the intracellular DNA (iDNA). The two DNA fractions were investigated in seven long-ripened cheeses. Among different buffer solutions tested, EDTA 0.5 M at pH 8 enabled a mild homogenization of cheese samples and the highest eDNA recovery. The extraction protocol was tested on single strains of lactic acid bacteria characterizing many Italian long-ripened cheeses, such as Streptococcus thermophilus, Lactobacillus helveticus, and Lactobacillus rhamnosus. The method resulted suitable for eDNA extraction because it minimized cell-lysis, avoiding the leakage of iDNA from the cells. The yields of eDNA, ranging from 0.01 to 0.36 µg g-1 cheese, were generally higher than the iDNA, indicating that autolytic phenomena prevailed over intact cells after 8-12 months of ripening. In four of the seven cheeses, the same LAB species were detected in the eDNA and iDNA fractions by length-heterogeneity PCR, while in the remaining three samples, a higher number of species was highlighted in the eDNA compared to the corresponding iDNA. The sequential extraction of eDNA and iDNA can be applied to obtain additional information on the composition of the bacterial community in long-aged cheeses.

The Microbiota of Edam Cheeses Determined by Cultivation and High-Throughput Sequencing of the 16S rRNA Amplicon

The aim of this study was to evaluate the microbiome of industrially produced ripened Edam cheeses by next-generation sequencing. The samples for analyses were collected in spring and autumn. Spring samples were characterized by significantly higher Lactococcus and Bacillus counts and lower counts of Enterobacteriaceae, Enterococcus, and yeasts than autumn samples. The predominant microorganisms identified by the Illumina high-throughput sequencing technology belonged to four phyla: Firmicutes, Actinobacteria, Proteobacteria and Bacteroidetes. The dominant species were starter culture bacteria. Lactobacillus rhamnosus, Lactobacillus kefiri, Lactobacillus kefiranofaciens, Lactobacillus casei, Streptococcus thermophilus, and Bifidobacterium had the highest share of microbial cheese communities. The number of γ-Proteobacteria reads was higher in autumn cheese samples. A high number of reads was also noted in the genus Clostridium. The counts of spore-forming bacteria of the genus Bacillus were higher in cheeses produced in spring. The study revealed highly similar relationships between the analyzed production periods. The present results contribute to the existing knowledge of cheese microbiota, and they can be used to improve and modify production processes based on the composition of microbial communities, as well as to improve the quality of the final product.

Microbial communities of a variety of cheeses and comparison between core and rind region of cheeses

Understanding the microbial community of cheese is important in the dairy industry, as the microbiota contributes to the safety, quality, and physicochemical and sensory properties of cheese. In this study, the microbial compositions of different cheeses (Cheddar, provolone, and Swiss cheese) and cheese locations (core, rind, and mixed) collected from the Arbuthnot Dairy Center at Oregon State University were analyzed using 16S rRNA gene amplicon sequencing with the Illumina MiSeq platform (Illumina, San Diego, CA). A total of 225 operational taxonomic units were identified from the 4,675,187 sequencing reads generated. Streptococcus was observed to be the most abundant organism in provolone (72 to 85%) and Swiss (60 to 67%), whereas Lactococcus spp. were found to dominate Cheddar cheese (27 to 76%). Species richness varied significantly by cheese. According to alpha diversity analysis, porter-soaked Cheddar cheese exhibited the highest microbial richness, whereas smoked provolone cheese showed the lowest. Rind regions of each cheese changed color through smoking and soaking for the beverage process. In addition, the microbial diversity of the rind region was higher than the core region because smoking and soaking processes directly contacted the rind region of each cheese. The microbial communities of the samples clustered by cheese, indicated that, within a given type of cheese, microbial compositions were very similar. Moreover, 34 operational taxonomic units were identified as biomarkers for different types of cheese through the linear discriminant analysis effect size method. Last, both carbohydrate and AA metabolites comprised more than 40% of the total functional annotated genes from 9 varieties of cheese samples. This study provides insight into the microbial composition of different types of cheese, as well as various locations within a cheese, which is applicable to its safety and sensory quality.

Pathway Tools version 23.0 update: software for pathway/genome informatics and systems biology

MOTIVATION

Biological systems function through dynamic interactions among genes and their products, regulatory circuits and metabolic networks. Our development of the Pathway Tools software was motivated by the need to construct biological knowledge resources that combine these many types of data, and that enable users to find and comprehend data of interest as quickly as possible through query and visualization tools. Further, we sought to support the development of metabolic flux models from pathway databases, and to use pathway information to leverage the interpretation of high-throughput data sets.

RESULTS

In the past 4 years we have enhanced the already extensive Pathway Tools software in several respects. It can now support metabolic-model execution through the Web, it provides a more accurate gap filler for metabolic models; it supports development of models for organism communities distributed across a spatial grid; and model results may be visualized graphically. Pathway Tools supports several new omics-data analysis tools including the Omics Dashboard, multi-pathway diagrams called pathway collages, a pathway-covering algorithm for metabolomics data analysis and an algorithm for generating mechanistic explanations of multi-omics data. We have also improved the core pathway/genome databases management capabilities of the software, providing new multi-organism search tools for organism communities, improved graphics rendering, faster performance and re-designed gene and metabolite pages.

AVAILABILITY

The software is free for academic use; a fee is required for commercial use. See http://pathwaytools.com.

CONTACT

pkarp@ai.sri.com.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Briefings in Bioinformatics online.

Investigation of genomic characteristics and carbohydrates' metabolic activity of Lactococcus lactis subsp. lactis during ripening of a Swiss-type cheese

Genetic diversity and metabolic properties of Lactococcus lactis subsp. lactis were explored using phylogenetic, pan-genomic and metatranscriptomic analysis. The genomes, used in the current study, were available and downloaded from the GenBank which were primarily related with microorganisms isolated from dairy products and secondarily from other foodstuffs. To study the genetic diversity of the microorganism, various bioinformatics tools were employed such as average nucleotide identity, digital DNA-DNA hybridization, phylogenetic analysis, clusters of orthologous groups analysis, KEGG orthology analysis and pan-genomic analysis. The results showed that Lc. lactis subsp. lactis strains cannot be sufficiently separated into phylogenetic lineages based on the 16S rRNA gene sequences and core genome-based phylogenetic analysis was more appropriate. Pan-genomic analysis of the strains indicated that the core, accessory and unique genome comprised of 1036, 3146 and 1296 genes, respectively. Considering the results of pan-genomic and KEGG orthology analyses, the metabolic network of Lc. lactis subsp. lactis was rebuild regarding its carbohydrates' metabolic capabilities. Based on the metatranscriptomic data during the ripening of the Swiss-type Maasdam cheese at 20 °C and 5 °C, it was shown that the microorganism performed mixed acid fermentation producing lactate, formate, acetate, ethanol and 2,3-butanediol. Mixed acid fermentation was more pronounced at higher ripening temperatures. At lower ripening temperatures, the genes involved in mixed acid fermentation were repressed while lactate production remained unaffected resembling to a homolactic fermentation. Comparative genomics and metatranscriptomic analysis are powerful tools to gain knowledge on the genomic diversity of the lactic acid bacteria used as starter cultures as well as on the metabolic activities occurring in fermented dairy products.

High Throughput Sequencing Technologies as a New Toolbox for Deep Analysis, Characterization and Potentially Authentication of Protection Designation of Origin Cheeses?

Protected Designation of Origin (PDO) labeling of cheeses has been established by the European Union (EU) as a quality policy that assures the authenticity of a cheese produced in a specific region by applying traditional production methods. However, currently used scientific methods for differentiating and establishing PDO are limited in terms of time, cost, accuracy and their ability to identify through quantifiable methods PDO fraud. Cheese microbiome is a dynamic community that progressively changes throughout ripening, contributing via its metabolism to unique qualitative and sensorial characteristics that differentiate each cheese. High Throughput Sequencing (HTS) methodologies have enabled the more precise identification of the microbial communities developed in fermented cheeses, characterization of their population dynamics during the cheese ripening process, as well as their contribution to the development of specific organoleptic and physio-chemical characteristics. Therefore, their application may provide an additional tool to identify the key microbial species that contribute to PDO cheeses unique sensorial characteristics and to assist to define their typicityin order to distinguish them from various fraudulent products. Additionally, they may assist the cheese-makers to better evaluate the quality, as well as the safety of their products. In this structured literature review indications are provided on the potential for defining PDO enabling differentiating factors based on distinguishable microbial communities shaped throughout the ripening procedures associated to cheese sensorial characteristics, as revealed through metagenomic and metatranscriptomic studies. Conclusively, HTS applications, even though still underexploited, have the potential to demonstrate how the cheese microbiome can affect the ripening process and sensorial characteristics formation via the catabolism of the available nutrients and interplay with other compounds of the matrix and/or production of microbial origin metabolites and thus their further quality enhancement.

Food authentication from shotgun sequencing reads with an application on high protein powders

Here we propose that using shotgun sequencing to examine food leads to accurate authentication of ingredients and detection of contaminants. To demonstrate this, we developed a bioinformatic pipeline, FASER (Food Authentication from SEquencing Reads), designed to resolve the relative composition of mixtures of eukaryotic species using RNA or DNA sequencing. Our comprehensive database includes >6000 plants and animals that may be present in food. FASER accurately identified eukaryotic species with 0.4% median absolute difference between observed and expected proportions on sequence data from various sources including sausage meat, plants, and fish. FASER was applied to 31 high protein powder raw factory ingredient total RNA samples. The samples mostly contained the expected source ingredient, chicken, while three samples unexpectedly contained pork and beef. Our results demonstrate that DNA/RNA sequencing of food ingredients, combined with a robust analysis, can be used to find contaminants and authenticate food ingredients in a single assay.

Milk microbiota: Characterization methods and role in cheese production

Milk is a complex body fluid aimed at addressing the nutritional and defensive needs of the mammal's newborns. Harbored microbiota plays a pivotal role throughout the cheesemaking process and contributes to the development of flavor and texture typical of different type of cheeses. Understanding the dairy microbiota dynamics is of paramount importance for controlling the qualitative, sensorial and biosafety features of the dairy products. Although many studies investigated the contribution of single or few microorganisms, still there is some information lacking about microbial communities. The widespread of the omics platforms and bioinformatic tools enable the investigation of the cheese-associated microbial community in both phylogenetical and functional terms, highlighting the effects of the diverse cheesemaking variables. In this review, the most relevant literature is revised to provide an introduction of the milk- and cheese-associated microbiota, along with their structural and functional dynamics in relation to the diverse cheesemaking technologies and influencing variables. Also, we focus our attention on the latest omics technologies adopted in dairy microbiota investigation. Discussion on the key-steps and major drawbacks of each omics discipline is provided along with a collection of results from the latest research studies performed to unravel the fascinating world of the dairy-associated microbiota. SIGNIFICANCE: Understanding the milk- and cheese- associated microbial community is nowadays considered a key factor in the dairy industry, since it allows a comprehensive knowledge on how all phases of the cheesemaking process impact the harbored microflora; thus, predict the consequences in the finished products in terms of texture, organoleptic characteristics, palatability and biosafety. This review, collect the pioneering and milestones works so far performed in the field of dairy microbiota, and provide the basic guidance to whom approaching the cheese microbiota investigation by means of the latest omics technologies. Also, the review emphasizes the benefits and drawbacks of the omics disciplines, and underline how the integration of diverse omics sciences enhance a comprehensive depiction of the cheese microbiota. In turn, a better consciousness of the dairy microbiota might results in the application of improved starter cultures, cheesemaking practices and technologies; supporting a bio-safe and standardized production of cheese, with a strong economic benefit for both large-scale industries and local traditional dairy farms.

Antibiotic Resistant Pseudomonas Spp. Spoilers in Fresh Dairy Products: An Underestimated Risk and the Control Strategies

Microbial multidrug resistance (MDR) is a growing threat to public health mostly because it makes the fight against microorganisms that cause lethal infections ever less effective. Thus, the surveillance on MDR microorganisms has recently been strengthened, taking into account the control of antibiotic abuse as well as the mechanisms underlying the transfer of antibiotic genes (ARGs) among microbiota naturally occurring in the environment. Indeed, ARGs are not only confined to pathogenic bacteria, whose diffusion in the clinical field has aroused serious concerns, but are widespread in saprophytic bacterial communities such as those dominating the food industry. In particular, fresh dairy products can be considered a reservoir of Pseudomonas spp. resistome, potentially transmittable to consumers. Milk and fresh dairy cheeses products represent one of a few "hubs" where commensal or opportunistic pseudomonads frequently cohabit together with food microbiota and hazard pathogens even across their manufacturing processes. Pseudomonas spp., widely studied for food spoilage effects, are instead underestimated for their possible impact on human health. Recent evidences have highlighted that non-pathogenic pseudomonads strains (P. fluorescens, P. putida) are associated with some human diseases, but are still poorly considered in comparison to the pathogen P. aeruginosa. In addition, the presence of ARGs, that can be acquired and transmitted by horizontal genetic transfer, further increases their risk and the need to be deeper investigated. Therefore, this review, starting from the general aspects related to the physiological traits of these spoilage microorganisms from fresh dairy products, aims to shed light on the resistome of cheese-related pseudomonads and their genomic background, current methods and advances in the prediction tools for MDR detection based on genomic sequences, possible implications for human health, and the affordable strategies to counteract MDR spread.

Transcription Profiling Reveals Cooperative Metabolic Interactions in a Microbial Cheese-Ripening Community Composed of Debaryomyces hansenii, Brevibacterium aurantiacum, and Hafnia alvei

Ripening cultures containing fungi and bacteria are widely used in smear-ripened cheese production processes, but little is known about the biotic interactions of typical ripening microorganisms at the surface of cheese. We developed a lab-scale mini-cheese model to investigate the biotic interactions of a synthetic community that was composed of Debaryomyces hansenii, Brevibacterium aurantiacum, and Hafnia alvei, three species that are commonly used for smear-ripened cheese production. Transcriptomic analyses of cheese samples produced with different combinations of these three species revealed potential mechanisms of biotic interactions concerning iron acquisition, proteolysis, lipolysis, sulfur metabolism, and D-galactonate catabolism. A strong mutualistic interaction was observed between H. alvei and B. aurantiacum. We propose an explanation of this positive interaction in which B. aurantiacum would benefit from siderophore production by H. alvei, and the latter would be stimulated by the energy compounds liberated from caseins and triglycerides through the action of the proteases and lipases secreted by B. aurantiacum. In the future, it would be interesting to take the iron acquisition systems of cheese-associated strains into account for the purpose of improving the selection of the ripening culture components and their association in mixed cultures.

Long-read based de novo assembly of low-complexity metagenome samples results in finished genomes and reveals insights into strain diversity and an active phage system

BACKGROUND

Complete and contiguous genome assemblies greatly improve the quality of subsequent systems-wide functional profiling studies and the ability to gain novel biological insights. While a de novo genome assembly of an isolated bacterial strain is in most cases straightforward, more informative data about co-existing bacteria as well as synergistic and antagonistic effects can be obtained from a direct analysis of microbial communities. However, the complexity of metagenomic samples represents a major challenge. While third generation sequencing technologies have been suggested to enable finished metagenome-assembled genomes, to our knowledge, the complete genome assembly of all dominant strains in a microbiome sample has not been demonstrated. Natural whey starter cultures (NWCs) are used in cheese production and represent low-complexity microbiomes. Previous studies of Swiss Gruyère and selected Italian hard cheeses, mostly based on amplicon metagenomics, concurred that three species generally pre-dominate: Streptococcus thermophilus, Lactobacillus helveticus and Lactobacillus delbrueckii.

RESULTS

Two NWCs from Swiss Gruyère producers were subjected to whole metagenome shotgun sequencing using the Pacific Biosciences Sequel and Illumina MiSeq platforms. In addition, longer Oxford Nanopore Technologies MinION reads had to be generated for one to resolve repeat regions. Thereby, we achieved the complete assembly of all dominant bacterial genomes from these low-complexity NWCs, which was corroborated by a 16S rRNA amplicon survey. Moreover, two distinct L. helveticus strains were successfully co-assembled from the same sample. Besides bacterial chromosomes, we could also assemble several bacterial plasmids and phages and a corresponding prophage. Biologically relevant insights were uncovered by linking the plasmids and phages to their respective host genomes using DNA methylation motifs on the plasmids and by matching prokaryotic CRISPR spacers with the corresponding protospacers on the phages. These results could only be achieved by employing long-read sequencing data able to span intragenomic as well as intergenomic repeats.

CONCLUSIONS

Here, we demonstrate the feasibility of complete de novo genome assembly of all dominant strains from low-complexity NWCs based on whole metagenomics shotgun sequencing data. This allowed to gain novel biological insights and is a fundamental basis for subsequent systems-wide omics analyses, functional profiling and phenotype to genotype analysis of specific microbial communities.

Shotgun Metagenomics of a Water Kefir Fermentation Ecosystem Reveals a Novel Oenococcus Species

Water kefir is a fruity, sour, slightly alcoholic and carbonated beverage, which is made by fermentation of an aqueous sucrose solution in the presence of dried figs and water kefir grains. These polysaccharide grains contain lactic acid bacteria (LAB), yeasts, and sometimes bifidobacteria and/or acetic acid bacteria, which consume sucrose to produce exopolysaccharides, lactic acid, acetic acid, ethanol, and carbon dioxide. Shotgun metagenomic sequencing was used to examine the microbial species diversity present at two time points during water kefir fermentation in detail, both in the water kefir liquor and on the water kefir grains, hence representing four samples. Lactobacillus harbinensis, Lactobacillus hilgardii, Lactobacillus nagelii, Lactobacillus paracasei, and a Lactobacillus species similar to Lactobacillus hordei/mali were present in the water kefir examined, along with Bifidobacterium aquikefiri and two yeast species, namely Saccharomyces cerevisiae and Dekkera bruxellensis. In addition, evidence for a novel Oenococcus species related to Oenococcus oeni and Oenococcus kitaharae was found. Its genome was derived from the metagenome and made available under the name of Candidatus Oenococcus aquikefiri. Through functional analysis of the four metagenomic data sets, it was possible to link the production of lactic acid, acetic acid, ethanol, and carbon dioxide to subgroups of the microbial species found. In particular, the production of mannitol from fructose was linked to L. hilgardii, Candidatus O. aquikefiri, and B. aquikefiri, whereas glycerol production was associated with S. cerevisiae. Also, there were indications of cross-feeding, for instance in the case of amino acid supply. Few bacterial species could synthesize a limited number of cofactors, making them reliant on the figs or S. cerevisiae. The LAB species in turn were found to be capable of contributing to water kefir grain growth, as dextransucrase-encoding genes were attributed to L. hilgardii, L. hordei/mali, and Candidatus O. aquikefiri.