Tracking the Dairy Microbiota from Farm Bulk Tank to Skimmed Milk Powder

Dynamics of microbiota and antimicrobial resistance in on-farm dairy processing plants using metagenomic and culture-dependent approaches

On-farm dairy processing plants, which are situated close to farms and larger dairy processing facilities, face unique challenges in maintaining environmental hygiene. This can impact various stages of dairy processing. These plants operate on smaller scales and use Low-Temperature-Long-Time (LTLT) pasteurization, making them more susceptible to microbial contamination through direct and indirect contact. Antimicrobial-resistant bacteria found on dairy farms pose risks to human health by potentially transferring resistance via dairy products. Our study aimed to investigate microbial distribution and antimicrobial resistance at four key stages: the farm, pre-pasteurization, post-pasteurization, and processing environments. We assessed microbial distribution by quantifying indicator bacteria and conducting metagenomic analysis. Antimicrobial resistance was examined by identifying resistance phenotypes and detecting resistance genes in bacterial isolates and metagenomes. Our results showed that the indicator bacteria were detected at all stages of on-farm dairy processing. We observed a significant reduction in aerobic microbes and coliforms post-pasteurization. However, contamination of the final dairy products increased, suggesting potential cross-contamination during post-pasteurization. Metagenomic analysis revealed that Pseudomonas, a representative psychrotrophic bacterium, was predominant in both the farm (24.1 %) and pre-pasteurization (65.9 %) stages, indicating microbial transfer from the farms to the processing plants. Post-pasteurization, Pseudomonas and other psychrotrophs like Acinetobacter and Enterobacteriaceae remained dominant. Core microbiota analysis identified 74 genera in total, including 13 psychrotrophic bacteria, across all stages. Of the 59 strains isolated from these plants, 49 were psychrotrophic. Antimicrobial resistance analysis showed that 74.6 % (44/59) of isolates were resistant to at least one antibiotic, with cefoxitin-, ampicillin-, amoxicillin-, and ticarcillin-resistant bacteria present at all stages. Identical antimicrobial resistance patterns were observed in isolates from serial stages of the same farm and season, suggesting bacterial transmission across stages. Additionally, 27.1 % (16/59) of isolates carried plasmid-mediated resistance genes, which were also detected in the metagenomes of non-isolated samples, indicating potential antimicrobial resistance gene transmission and their presence in uncultured bacteria. These findings reveal the persistence of antimicrobial-resistant psychrotrophic bacteria in on-farm dairy processing plants, which pose potential health risks via dairy consumption. Our study underscores the importance of both culture-dependent and culture-independent methods to fully understand their distribution and impact.

Seasonal and geographical impact on the Irish raw milk microbiota correlates with chemical composition and climatic variables

Season and location have previously been shown to be associated with differences in the microbiota of raw milk, especially in milk from pasture-based systems. Here, we further advance research in this area by examining differences in the raw milk microbiota from several locations across Ireland over 12 months, and by investigating microbiota associations with climatic variables and chemical composition. Shotgun metagenomic sequencing was used to investigate the microbiota of raw milk collected from nine locations (n = 241). Concurrent chemical analysis of the protein, fat, lactose, total solids, nonprotein nitrogen contents, and titratable acidity (TA) of the same raw milk were performed. Although the raw milk microbiota was highly diverse, a core microbiota was found, with Pseudomonas_E, Lactococcus, Acinetobacter, and Leuconostoc present in all samples. Microbiota diversity significantly differed by season and location, with differences in seasonality and geography corresponding to 11.8% and 10.5% of the variation in the microbiota. Functional and antibiotic resistance profiles also varied across season and location. The analysis of other metadata revealed additional interactions, such as an association between mean daily air and grass temperatures with the abundance of spoilage taxa like Pseudomonas species. Correlations were identified between pathogenic, mastitis-related species, fat content, and the number of sun hours, suggesting a seasonal effect. Ultimately, this study expands our understanding of the interconnected nature of the microbiota, environment/climate variables, and chemical composition of raw milk and provides evidence of a season- and location-specific microbiota.

IMPORTANCE

The microbiota of raw milk is influenced by many factors that encourage or prevent the introduction and growth of both beneficial and undesirable microorganisms. The seasonal and geographical impacts on the microbial communities of raw milk have been previously seen, but the relationships with environmental factors and the chemical composition has yet to be investigated. In this year-long study, we found that while raw milk is highly diverse, a core microbiota was detected for Irish raw milk, with strong evidence of seasonal and geographical influence. We also found associations between groups of microorganisms, environmental factors, and milk composition, which expand current knowledge on the relationships between microbial and chemical composition and the climate. These results provide evidence for the development of a tool to allow for the prediction of raw milk quality and safety.

Calcium-mediated modulation of Pseudomonas fluorescens biofilm formation

Biofilm formation is usually affected by many environmental factors, including divalent cations. The purpose of the current work was to analyze how calcium (Ca2+) affects the biofilm formation of dairy Pseudomonas fluorescens isolates by investigating their growth, swarming motility, biofilm-forming capacity, extracellular polymeric substance production, and biofilm structures. Moreover, the regulation mechanism of Ca2+ involved in its biofilm formation was explored through RNA-sequencing analysis. This work revealed that supplementation of 5, 10, 15, and 20 mM Ca2+ significantly reduced the swarming motility of P. fluorescens strains (P.F2, P.F4, and P.F17), but the biofilm-forming ability and polysaccharide production were increased after the supplementation of 5 and 10 mM Ca2+. By the supplementation of Ca2+, complex structures with more cell clusters glued together in P. fluorescens P.F4 biofilms were confirmed by scanning electron microscopy, and increased biomass and coverage of P. fluorescens P.F4 biofilms were observed by confocal laser scanning microscopy. In addition, RNA-sequencing results showed that P. fluorescens P.F4 showed a transcriptional response to the supplementation of 10 mM Ca2+, and a total of 137 genes were significantly expressed. The differential genes were represented in 4 upregulated Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways (nonribosomal peptide structures, quorum sensing, biosynthesis of siderophore group nonribosomal peptides, and phenylalanine metabolism), and 4 downregulated KEGG pathways (flagellar assembly, amino sugar and nucleotide sugar metabolism, nitrotoluene degradation, and cationic antimicrobial peptide resistance). The results indicate that Ca2+ might serve as an enhancer to substantially trigger the biofilm formation of dairy P. fluorescens isolates in the dairy industry.

The Investigation of Changes in Bacterial Community of Pasteurized Milk during Cold Storage

The quality of pasteurized milk is commonly assessed through microbiological analysis, with variations in storage conditions significantly impacting the suppression of bacterial growth throughout the milk's shelf life. This study investigated the dynamics of total bacterial counts (TBCs) and bacterial community shifts in milk that underwent pasteurization at 80 °C for 15 s. The milk was subsequently stored at 4 °C for varying intervals of 1, 4, 7, 10, 13, and 16 days. Culture-based testing revealed a significant TBC increase during the storage period spanning 1 to 16 days (up to -log10 4.2 CFU/mL at day 16). The TBC in pasteurized milk exhibited accelerated microbial growth from day 13 onwards, ultimately peaking on day 16. Bacillus was detected through 16S rRNA identification. Principal component analysis demonstrated a significant impact of storage time on bacterial communities in pasteurized milk. Analysis of bacterial diversity revealed a negative correlation between the Shannon index and the duration of pasteurized milk storage. Using high-throughput sequencing, Streptococcus and Acinetobacter were detected as prevalent bacterial genera, with Streptococcus dysgalactiae and Streptococcus uberis showing as dominant taxa. The presence of Streptococcus dysgalactiae and Streptococcus uberis in pasteurized milk might be attributed to the initial contamination from raw milk with mastitis. This study offers new evidence of the prevalence of bacterial community in pasteurized milk, thereby adding value to the enhancement of quality control and the development of strategies for reducing microbial risks.

Host DNA depletion methods and genome-centric metagenomics of bovine hindmilk microbiome

Bovine mastitis is a multi-etiological and complex disease, resulting in serious economic consequences for dairy farmers and industry. In recent years, the microbiological evaluation of raw milk has been investigated in-depth using next-generation sequencing approaches such as metataxonomic analysis. Despite this, host DNA is a major concern in the shotgun metagenomic sequencing of microbial communities in milk samples, and it represents a big challenge. In this study, we aimed to evaluate different methods for host DNA depletion and/or microbial DNA enrichment and assess the use of PCR-based whole genome amplification in milk samples with high somatic cell count (SCC) by using short- and long-read sequencing technologies. Our results evidenced that DNA extraction performed differently in terms of host DNA removal, impacting metagenome composition and functional profiles.. Moreover, the ratio of SCC/bacteria ultimately impacts microbial DNA yield, and samples with low SCC (SCC below 100,000 cells/mL) are the most problematic. When milk samples with high SCC (SCC above 200,000 cells/mL) underwent multiple-displacement amplification (MDA), we successfully recovered high-quality metagenome-assembled genomes (MAGs), and long-read sequencing was feasible even for samples with low DNA concentration. By associating MDA and short-read sequencing, we recovered two times more MAGs than in untreated samples, and an ongoing co-infection not reported by traditional methods was detected for mastitis pathogen. Overall, this new approach will improve the detection of mastitis-associated microorganisms and make it possible to examine host-microbiome interactions in bovine mastitis.IMPORTANCENext-generation sequencing technologies have been widely used to gain new insights into the diversity of the microbial community of milk samples and dairy products for different purposes such as microbial safety, profiling of starter cultures, and host-microbiome interactions. Milk is a complex food matrix, and additionally, the presence of host nucleic acid sequences is considered a contaminant in untargeted high-throughput sequencing studies. Therefore, genomic-centric metagenomic studies of milk samples focusing on the health-disease status in dairy cattle are still scarce, which makes it difficult to evaluate the microbial ecophysiology of bovine hindmilk. This study provides an alternative method for genome-centric metagenome studies applied to hindmilk samples with high somatic cell content, which is indispensable to examining host-microbiome interactions in bovine mastitis.

Phylogenetic variation in raw cow milk microbiota and the impact of forage combinations and use of silage inoculants

Introduction

The microbiota of bulk tank raw milk is known to be closely related to that of microbial niches of the on-farm environment. Preserved forage types are partof this ecosystem and previous studies have shown variations in their microbial ecology. However, little is known of the microbiota of forage ration combinations and the transfer rates of associated species to milk.

Methods

We identified raw milk bacteria that may originate from forage rations encompassing either hay (H) or grass/legume silage uninoculated (GL) as the only forage type, or a combination of GL and corn silage uninoculated (GLC), or grass/legume and corn silage both inoculated (GLICI). Forage and milk samples collected in the fall and spring from 24 dairy farms were analyzed using 16S rRNA gene high-throughput sequencing following a treatment with propidium monoazide to account for viable cells.

Results and discussion

Three community types separating H, GL, and GLICI forage were identified. While the H community was co-dominated by Enterobacteriaceae, Microbacteriaceae, Beijerinckiaceae, and Sphingomonadaceae, the GL and GLICI communities showed high proportions of Leuconostocaceae and Acetobacteraceae, respectively. Most of the GLC and GLICI rations were similar, suggesting that in the mixed forage rations involving grass/legume and corn silage, the addition of inoculant in one or both types of feed does not considerably change the microbiota. Raw milk samples were not grouped in the same way, as the GLC milk was phylogenetically different from that of GLICI across sampling periods. Raw milk communities, including the GLICI group for which cows were fed inoculated forage, were differentiated by Enterobacteriaceae and other Proteobacteria, instead of by lactic acid bacteria. Of the 113 amplicon sequence variants (ASVs) shared between forage rations and corresponding raw milk, bacterial transfer rates were estimated at 18 to 31%. Silage-based forage rations, particularly those including corn, share more ASVs with raw milk produced on corresponding farms compared to that observed in the milk from cows fed hay. These results show the relevance of cow forage rations as sources of bacteria that contaminate milk and serve to advance our knowledge of on-farm raw milk contamination.

Associations between the Bacterial Composition of Farm Bulk Milk and the Microbiota in the Resulting Swedish Long-Ripened Cheese

The maturation of a traditional Swedish long-ripened cheese has shown increasing variation in recent years and the ripening time is now generally longer than in the past. While the cheese is reliant on non-starter lactic acid bacteria for the development of its characteristic flavour, we hypothesised that the observed changes could be due to variations in the microbiota composition and number of bacteria in the raw milk used for production of the cheese. To evaluate associations between microbiota in the raw milk and the resulting cheese, three clusters of commercial farms were created to increase variation in the microbiota of dairy silo milk used for cheese production. Cheese production was performed in three periods over one year. Within each period, milk from the three farm clusters was collected separately and transported to the cheese production facility. Following pasteurisation, the milk was processed into the granular-eyed cheese and matured at a dedicated cheese-ripening facility. For each cheese batch, farm bulk and dairy silo milk samples, a starter culture, early process samples and cheese samples from different stages of maturation (7-20 months) were collected and their microbiota characterised using 16S rRNA amplicon sequencing. The microbiota in the farm bulk milk differed significantly between periods and clusters. Differences in microbiota in dairy silo milk were observed between periods, but not between farm clusters, while the cheese microbiota differed between periods and clusters. The top 13 amplicon sequence variants were dominant in early process samples and the resulting cheese, making up at least 93.3% of the relative abundance (RA). Lactococcus was the dominant genus in the early process samples and, together with Leuconostoc, also dominated in the cheese samples. Contradicting expectations, the RA of the aroma-producing genus Lactobacillus was low in cheese during ripening and there was an unexpected dominance of starter lactic acid bacteria even at the later stages of cheese ripening. To identify factors behind the recent variations in ripening time of this cheese, future studies should address the effects of process variables and the dairy environment.

Microbiome Interconnectedness throughout Environments with Major Consequences for Healthy People and a Healthy Planet

Microbiomes have highly important roles for ecosystem functioning and carry out key functions that support planetary health, including nutrient cycling, climate regulation, and water filtration. Microbiomes are also intimately associated with complex multicellular organisms such as humans, other animals, plants, and insects and perform crucial roles for the health of their hosts. Although we are starting to understand that microbiomes in different systems are interconnected, there is still a poor understanding of microbiome transfer and connectivity. In this review we show how microbiomes are connected within and transferred between different habitats and discuss the functional consequences of these connections. Microbiome transfer occurs between and within abiotic (e.g., air, soil, and water) and biotic environments, and can either be mediated through different vectors (e.g., insects or food) or direct interactions. Such transfer processes may also include the transmission of pathogens or antibiotic resistance genes. However, here, we highlight the fact that microbiome transmission can have positive effects on planetary and human health, where transmitted microorganisms potentially providing novel functions may be important for the adaptation of ecosystems.

Microbiota and Resistome Analysis of Colostrum and Milk from Dairy Cows Treated with and without Dry Cow Therapies

This study investigated the longitudinal impact of methods for the drying off of cows with and without dry cow therapy (DCT) on the microbiota and resistome profile in colostrum and milk samples from cows. Three groups of healthy dairy cows (n = 24) with different antibiotic treatments during DCT were studied. Colostrum and milk samples from Month 0 (M0), 2 (M2), 4 (M4) and 6 (M6) were analysed using whole-genome shotgun-sequencing. The microbial diversity from antibiotic-treated groups was different and higher than that of the non-antibiotic group. This difference was more evident in milk compared to colostrum, with increasing diversity seen only in antibiotic-treated groups. The microbiome of antibiotic-treated groups clustered separately from the non-antibiotic group at M2-, M4- and M6 milk samples, showing the effect of antibiotic treatment on between-group (beta) diversity. The non-antibiotic group did not show a high relative abundance of mastitis-causing pathogens during early lactation and was more associated with genera such as Psychrobacter, Serratia, Gordonibacter and Brevibacterium. A high relative abundance of antibiotic resistance genes (ARGs) was observed in the milk of antibiotic-treated groups with the Cephaguard group showing a significantly high abundance of genes conferring resistance to cephalosporin, aminoglycoside and penam classes. The data support the use of non-antibiotic alternatives for drying off in cows.

Effects of UV-B radiation on epiphytic bacterial communities on male and female Sargassum thunbergii

The effects of increased UV-B radiation on macroalgae have been widely studied, but knowledge concerning the response of communities of algal epiphytic bacteria to increased UV-B radiation and differences between male and female algae is still lacking. Via 16S rDNA high-throughput sequencing technology, changes in the epiphytic bacterial communities on male and female S. thunbergii under increased UV-B radiation were studied in the lab. Under different UV-B radiation intensities, although the α diversity and community composition of epiphytic bacteria changed little, the β diversity indicated that the community structure of bacteria on S. thunbergii was obviously clustered, and the relative abundance of dominant bacteria and indicator species changed considerably. There were unique bacteria in each experimental group, and the bacteria whose abundance obviously changed were members of groups related to environmental resistance or adaptability. The variation in the abundance of epiphytic bacteria was different in male and female S. thunbergii, and the bacteria whose abundance greatly changed were mainly related to algal growth and metabolism. The abundance of genes with predicted functions related to metabolism, genetic information processing, environmental adaptation and infectious diseases changed with increased UV-B radiation, and those variations differed between epiphytic bacteria on male and female S. thunbergii. This study found that the algal epiphytic bacteria were influenced by the increase in UV-B radiation and underwent certain adaptations through adjustments to community structure and function, and this response was also affected by the sex of the macroalgae. These results are expected to serve as experimental basis and provide reference for further understanding of the response of algae epiphytic bacteria to enhanced UV-B radiation caused by the thinning of the ozone layer and the resulting changes in the relationship between algae and bacteria, which may change the community of the marine ecosystem and affect important marine ecological process.

Invited review: Redefining raw milk quality-Evaluation of raw milk microbiological parameters to ensure high-quality processed dairy products

Raw milk typically has little bacterial contamination as it leaves the udder of the animal; however, through a variety of pathways, it can become contaminated with bacteria originating from environmental sources, the cow herself, and contact with contaminated equipment. Although the types of bacteria found in raw milk are very diverse, select groups are particularly important from the perspective of finished product quality. In particular, psychrophilic and psychrotolerant bacteria that grow quickly at low temperatures (e.g., species in the genus Pseudomonas and the family Enterobacteriaceae) and produce heat-stable enzymes, and sporeforming bacteria that survive processing hurdles in spore form, are the 2 primary groups of bacteria related to effects on processed dairy products. Understanding factors leading to the presence of these important bacterial groups in raw milk is key to reducing their influence on processed dairy product quality. Here we examine the raw milk microbiological parameters used in the contemporary dairy industry for their utility in identifying raw milk supplies that will perform well in processed dairy products. We further recommend the use of a single microbiological indicator of raw milk quality, namely the total bacteria count, and call for the development of a whole-farm approach to raw milk quality that will use data-driven, risk-based tools integrated across the continuum from production to processing and shelf-life to ensure continuous improvement in dairy product quality.

A culture-, amplification-independent, and rapid method for identification of pathogens and antibiotic resistance profile in bovine mastitis milk

Introduction

Rapid and accurate diagnosis of causative pathogens in mastitis would minimize the imprudent use of antibiotics and, therefore, reduce the spread of antimicrobial resistance. Whole genome sequencing offers a unique opportunity to study the microbial community and antimicrobial resistance (AMR) in mastitis. However, the complexity of milk samples and the presence of a high amount of host DNA in milk from infected udders often make this very challenging.

Methods

Here, we tested 24 bovine milk samples (18 mastitis and six non-mastitis) using four different commercial kits (Qiagens' DNeasy^® PowerFood^® Microbial, Norgens' Milk Bacterial DNA Isolation, and Molzyms' MolYsis™ Plus and Complete5) in combination with filtration, low-speed centrifugation, nuclease, and 10% bile extract of male bovine (Ox bile). Isolated DNA was quantified, checked for the presence/absence of host and pathogen using PCR and sequenced using MinION nanopore sequencing. Bioinformatics analysis was performed for taxonomic classification and antimicrobial resistance gene detection.

Results

The results showed that kits designed explicitly for bacterial DNA isolation from food and dairy matrices could not deplete/minimize host DNA. Following using MolYsis™ Complete 5 + 10% Ox bile + micrococcal nuclease combination, on average, 17% and 66.5% of reads were classified as bovine and Staphylococcus aureus reads, respectively. This combination also effectively enriched other mastitis pathogens, including Escherichia coli and Streptococcus dysgalactiae. Furthermore, using this approach, we identified important AMR genes such as Tet (A), Tet (38), fosB-Saur, and blaZ. We showed that even 40 min of the MinION run was enough for bacterial identification and detecting the first AMR gene.

Conclusion

We implemented an effective method (sensitivity of 100% and specificity of 92.3%) for host DNA removal and bacterial DNA enrichment (both gram-negative and positive) directly from bovine mastitis milk. To the best of our knowledge, this is the first culture- and amplification-independent study using nanopore-based metagenomic sequencing for real-time detection of the pathogen (within 5 hours) and the AMR profile (within 5-9 hours), in mastitis milk samples. These results provide a promising and potential future on-farm adaptable approach for better clinical management of mastitis.

Milk Contamination by Mycobacterium tuberculosis Complex, Implications for Public Health in Amazonas, Brazil

ABSTRACT

In Brazil, contamination of raw milk with Mycobacterium tuberculosis complex (MTC) has been reported in several states. The highest rate of consumption of raw milk and its derivatives in Brazil occurs in Amazonas. This state also has the highest prevalence of tuberculosis in both humans and livestock. We assessed the contamination of cow's milk and buffalo's milk with MTC in Amazonas, focusing on Mycobacterium bovis, the species most commonly found in cattle and buffalo. In 2019, 250 samples of raw milk (91 from cattle, 159 from buffalo) were collected before processing from three milk plants in the state of Amazonas. The samples were placed into 21 pools and analyzed using shotgun metagenomic sequencing and taxonomic classification with Kraken 2 and MegaBLAST. To confirm the identity of mycobacterial species found, BLASTN was used to identify specific genomic positions in the TbD1 and RD1 regions and flanking RD4 region. MTC genetic material was identified in all pools of raw milk. Genetic material consistent with M. bovis was identified in seven pools of raw milk (1 from cattle, 6 from buffalo). Buffalo's milk had significantly higher MTC reads than did cow's milk. The common practice of consumption of raw milk and its derivatives in Amazonas presents a risk to public health. Urgent measures to prevent transmission of foodborne tuberculosis are needed in the Amazon region. Greater efforts and resources also should be directed toward elimination of bovine tuberculosis in cattle and buffalo herds in Amazonas and the rest of Brazil.

HIGHLIGHTS

The Application of Metagenomics to Study Microbial Communities and Develop Desirable Traits in Fermented Foods

The microbial communities present within fermented foods are diverse and dynamic, producing a variety of metabolites responsible for the fermentation processes, imparting characteristic organoleptic qualities and health-promoting traits, and maintaining microbiological safety of fermented foods. In this context, it is crucial to study these microbial communities to characterise fermented foods and the production processes involved. High Throughput Sequencing (HTS)-based methods such as metagenomics enable microbial community studies through amplicon and shotgun sequencing approaches. As the field constantly develops, sequencing technologies are becoming more accessible, affordable and accurate with a further shift from short read to long read sequencing being observed. Metagenomics is enjoying wide-spread application in fermented food studies and in recent years is also being employed in concert with synthetic biology techniques to help tackle problems with the large amounts of waste generated in the food sector. This review presents an introduction to current sequencing technologies and the benefits of their application in fermented foods.

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.

Graduate Student Literature Review: Farm management practices: Potential microbial sources that determine the microbiota of raw bovine milk

Environmental and herd-associated factors such as geographical location, climatic conditions, forage types, bedding, soil, animal genetics, herd size, housing, lactation stage, and udder health are exploited by farmers to dictate specific management strategies that ensure dairy operation profitability and enhance the sustainability of milk production. Along with milking routines, milking systems, and storage conditions, these farming practices greatly influence the microbiota of raw milk, as evidenced by several recent studies. During the past few years, the increased interest in high-throughput sequencing technologies combined with culture-dependent methods to investigate dairy microbial ecology has improved our understanding of raw milk community dynamics throughout storage and processing. However, knowledge is still lacking on the niche-specific communities in the farm environment, and on the factors that determine bacteria transfer to the raw milk. This review summarizes findings from the past 2 decades regarding the effects of farm management practices on the diversity of bacterial species that determine the microbiological quality of raw cow milk.

Microbiome Research as an Effective Driver of Success Stories in Agrifood Systems – A Selection of Case Studies

Increasing knowledge of the microbiome has led to significant advancements in the agrifood system. Case studies based on microbiome applications have been reported worldwide and, in this review, we have selected 14 success stories that showcase the importance of microbiome research in advancing the agrifood system. The selected case studies describe products, methodologies, applications, tools, and processes that created an economic and societal impact. Additionally, they cover a broad range of fields within the agrifood chain: the management of diseases and putative pathogens; the use of microorganism as soil fertilizers and plant strengtheners; the investigation of the microbial dynamics occurring during food fermentation; the presence of microorganisms and/or genes associated with hazards for animal and human health (e.g., mycotoxins, spoilage agents, or pathogens) in feeds, foods, and their processing environments; applications to improve HACCP systems; and the identification of novel probiotics and prebiotics to improve the animal gut microbiome or to prevent chronic non-communicable diseases in humans (e.g., obesity complications). The microbiomes of soil, plants, and animals are pivotal for ensuring human and environmental health and this review highlights the impact that microbiome applications have with this regard.

Comparison Between Full-Length 16S rRNA Metabarcoding and Whole Metagenome Sequencing Suggests the Use of Either Is Suitable for Large-Scale Microbiome Studies

Since the number of studies of the microbial communities related to food and food-associated matrices almost completely reliant on next-generation sequencing techniques is rising, evaluations of these high-throughput methods are critical. Currently, the two most used sequencing methods to profile the microbiota of complex samples, including food and food-related matrices, are the 16S ribosomal RNA (rRNA) metabarcoding and the whole metagenome sequencing (WMS), both of which are powerful tools for the monitoring of foodborne pathogens and the investigation of the microbiome. Herein, the microbial profiles of 20 bulk tank milk filters from different dairy farms were investigated using both the full-length 16S (FL-16S) rRNA metabarcoding, a third-generation sequencing method whose application in food and food-related matrices is yet in its infancy, and the WMS, to evaluate the correlation and the reliability of these two methods to explore the microbiome of food-related matrices. Metabarcoding and metagenomic data were generated on a MinION platform (Oxford Nanopore Technologies) and on a Illumina NovaSeq 6000 platform, respectively. Our findings support the greater resolution of WMS in terms of both increased detection of bacterial taxa and enhanced detection of diversity; in contrast, FL-16S rRNA metabarcoding has proven to be a promising, less expensive, and more practical tool to profile most abundant taxa. The significant correlation of the two technologies both in terms of taxa diversity and richness, together with the similar profiles defined for both highly abundant taxa and core microbiomes, including Acinetobacter, Bacillus, and Escherichia genera, highlights the possible application of both methods for different purposes. This study allowed the first comparison of FL-16S rRNA sequencing and WMS to investigate the microbial composition of a food-related matrix, pointing out the advantageous use of FL-16S rRNA to identify dominant microorganisms and the superior power of WMS for the taxonomic detection of low abundant microorganisms and to perform functional analysis of the microbial communities.

Advances in multi-omics based quantitative microbial risk assessment in the dairy sector: A semi-systematic review

With the increasing consumption of packaged and ready-to-eat food products, the risk of foodborne illness has drastically increased and so has the dire need for proper management. The conventional Microbial Risk Assessment (MRA) investigations require prior knowledge of process flow, exposure, and hazard assessment throughout the supply chain. These data are often generated using conventional microbiological approaches based either on shelf-life studies or specific spoilage organisms (SSOs), frequently overlooking crucial information such as antimicrobial resistance (AMR), biofilm formation, virulence factors and other physiological variations coupled with bio-chemical characteristics of food matrix. Additionally, the microbial risks in food are diverse and heterogenous, that might be an outcome of growth and activity of multiple microbial populations rather than a single species contamination. The uncertainty on the microbial source, time as well as point of entry into the food supply chain poses a constraint to the efficiency of preventive approaches and conventional MRA. In the last few decades, significant breakthroughs in molecular methods and continuously progressing bioinformatics tools have opened up a new horizon for risk analysis-based approaches in food safety. Real time polymerase chain reaction (qPCR) and kit-based assays provide better accuracy and precision with shorter processing time. Despite these improvements, the effect of complex food matrix on growth environment and recovery of pathogen is a persistent problem for risk assessors. The dairy industry is highly impacted by spoilage and pathogenic microorganisms. Therefore, this review discusses the evolution and recent advances in MRAmethodologies equipped with predictive interventions and "multi-omics" approach for robust MRA specifically targeting dairy products. It also highlights the limiting gap area and the opportunity for improvement in this field to ensure precision food safety.

Source Tracker Modeling Based on 16S rDNA Sequencing and Analysis of Microbial Contamination Sources for Pasteurized Milk

Milk is rich in fat, protein, minerals, vitamins, peptides, immunologically active substances, and other nutrients, and it plays an important role in satisfying human nutrition and health. However, dairy product safety incidents caused by microbial contamination have occurred. We found that the total bacterial numbers in the pasteurized product were low and far below the limit requirements of the food safety standards of the European Union, the United States, and China. At the genus level, the primary microbial groups found in milk samples were Acinetobacter, Macrococcus, Pseudomonas, and Lactococcus, while in the equipment rinse water and air samples there was contamination by Stenotrophomonas and Acinetobacter. The Source Tracker model analysis indicated that the microorganisms in the final milk products were significantly related to the contamination in product tanks and raw milk. Therefore, it is the hope that this work can provide guidance to pinpoint contamination problems using the proper quality control sampling at specific stages in the pasteurization process.

Rapid Identification of Pseudomonas fluorescens Harboring Thermostable Alkaline Protease by Real-Time Loop-Mediated Isothermal Amplification

ABSTRACT

Thermostable alkaline protease (TAP) harbored by Pseudomonas fluorescens decomposes protein in milk and dairy products, leading to milk and dairy product spoilage during storage. Thus, a specific, sensitive, rapid, and simple method is required to detect TAP-harboring P. fluorescens. Two sets of primers targeting the aprX and gyrB genes of P. fluorescens were designed. The detection system and conditions were optimized, and a real-time loop-mediated isothermal amplification (real-time LAMP) method was developed for the simultaneous detection of TAP-harboring P. fluorescens in two separate reaction tubes. The phylogenetic tree targeting aprX showed that P. fluorescens and Pseudomonas lurida clustered on the same branch. The phylogenetic tree targeting gyrB showed that P. fluorescens clustered on the same branch with 95% confidence value, whereas P. lurida clustered on different branches. DNA of 16 strains of P. fluorescens and 34 strains of non-P. fluorescens was detected by real-time LAMP. TAP-harboring P. fluorescens can only be identified when the real-time LAMP detection results of both aprX and gyrB are positive. The dissociation temperatures of aprX and gyrB in the real-time LAMP-amplified products were approximately 90.0 and 88.0°C, respectively. The detection limits of the real-time LAMP targeting aprX and gyrB were 4.9 CFU per reaction in pure culture and 2.2 CFU per reaction in skimmed milk. The coefficient of variation of the repeatability test was less than 2%, indicating that the established real-time LAMP of P. fluorescens targeting gyrB and aprX has good stability and repeatability. Real-time LAMP was used to test 200 raw milk samples for the presence of TAP-harboring P. fluorescens in 3 h, and the coincidence rate of the results with those obtained using the traditional method, which takes at least 5 to 7 days, was 100%. Real-time LAMP will be a practical and effective method for accurate and rapid identification of TAP-harboring P. fluorescens in raw milk.

HIGHLIGHTS

Single Molecule Real-Time Sequencing and Traditional Cultivation Techniques Reveal Complex Community Structures and Regional Variations of Psychrotrophic Bacteria in Raw Milk

In this study, we investigated the species composition and diversity of psychrotrophic bacteria in raw milk from Heilongjiang, Inner Mongolia, Gansu, Henan, Anhui, Jiangsu, Chongqing, and Hunan provinces in China using traditional cultivation and PacBio Single Molecule Real-Time sequencing methods. The isolated psychrotrophic bacteria were highly diverse, which composed of 21 genera and 59 species. Pseudomonas accounted for 58.9% of the total genera while Stenotrophomonas and Enterococcus were also highly represented (above 5.0%). In particular, P. azotoformans occurred at a level of 16.9% and P. paralactis, P. lactis, E. faecalis, and P. marginalis were present in relatively high proportions (above 4.0%). Regional differences were found significantly among the test regions except samples from Heilongjiang and Inner Mongolia were similar. Additionally, differences were observed between days in Henan, Anhui, and Jiangsu samples. Therefore, control strategies must be implemented on regional and season basis.

Effect of two thermoresistant non-starter lactic acid bacteria strains on volatilome profile during Cheddar ripening simulation

Dairy farm management practices can modify milk microbiota and therefore modulate non-starter lactic acid bacteria (NSLAB) found in cheese. These NSLAB can cause organoleptic defects. This study aimed to investigate the impact of two potential NSLAB in Cheddar cheesemaking: Lactiplantibacillus plantarum RKG 2-212 a strain isolated both in corn silage and raw milk, and Lactobacillus delbrueckii RKG R10, a strain isolated after pasteurisation of milk from a farm using grass and legume silage, and corn silage. The whole genome of these two lactobacilli was first sequenced. Then, the thermoresistance was evaluated after treatment at 60 °C for 5 min and compared to reference strains. Both lactobacilli were highly thermoresistant compared to other three lactic acid bacteria which are Lactococcus lactis subsp. cremoris ATCC 19257 and SK11, and L. plantarum ATCC 14917 (P < 0.0001). They lost less than 1 log cfu/mL (Δlog) and their genome contained a great number of copy number of genes coding for heat shock protein. During a Pearce test activity simulating Cheddar cheesemaking, the two lactobacilli did not show interaction with the starter Lcc. lactis subsp. cremoris SK11, and their population remained stable. During a ripening simulation, L. delbrueckii RKG R10 had a slight loss in viability in cheese slurry samples incubated at 30 °C for 12 d. However, L. plantarum RKG 2-212 had considerable growth, from 6.51 to 8.3 log cfu/g. This growth was associated with the acidification of the slurries (P < 0.0001). The presence of the lactobacilli modified the profile of volatile compounds evaluated by gas chromatography-mass spectrometry, accounting for 10.7% of the variation. The strain L. plantarum RKG 2-212 produced volatile compounds in greater quantity that could be associated with organoleptic defects such as acetic acid and 2-methylbutyraldehyde. Therefore, silage can be a vector of thermoresistant lactic acid bacteria for milk which can lead to flavor defects in cheese.

Seasonality and Geography Have a Greater Influence than the Use of Chlorine-Based Cleaning Agents on the Microbiota of Bulk Tank Raw Milk

Cleaning of the production environment is vital to ensure the safety and quality of dairy products. Although cleaning with chlorine-based agents is widely adopted, it has been associated with detrimental effects on milk quality and safety, which has garnered increasing interest in chlorine-free cleaning. However, the influence of these methods on the milk microbiota is not well documented. This study investigated the factors that influence the raw milk microbiota, with a focus on the differences when chlorine-based and chlorine-free cleaning of milking equipment are used. Bulk tank raw milk was sampled during three sampling months (April, August, and November), from farms across Ireland selected to capture the use of different cleaning methods, i.e., exclusively chlorine-based (n = 51) and chlorine-free cleaning (n = 92) and farms that used chlorine-free agents for the bulk tank and chlorine-based cleaning agents for the rest of the equipment (n = 28). Shotgun metagenomic analysis revealed the significant influence of seasonal and geographic factors on the bulk tank milk microbiota, indicated by differences in diversity, taxonomic composition, and functional characteristics. Taxonomic and functional profiles of samples collected in November clustered separately from those of samples collected in other months. In contrast, cleaning methods only accounted for 1% of the variation in the bulk tank milk bacterial community, and samples collected from farms using chlorine-based versus chlorine-free cleaning did not differ significantly, suggesting that the chlorine-free approaches used did not negatively impact microbiological quality. This study shows the value of shotgun metagenomics in advancing our knowledge of the raw milk microbiota. IMPORTANCE The microbiota of raw milk is affected by many factors that can control or promote the introduction of undesirable microorganisms. Chlorine-based cleaning agents have been commonly used due to their effectiveness in controlling undesirable microorganisms, but they have been associated with the formation of chlorine residues that are detrimental to product quality and may impact consumer health. Chlorine-free alternatives have been recommended in some countries, but the influence of cleaning agents on the milk microbiota is unknown. Here, we investigated the influence of cleaning methods and other factors on bulk tank raw milk. Results showed that season and location had a greater influence on the milk microbiota than the cleaning agents used. Indeed, the similar microbiota compositions of raw milk from farms that used chlorine-based and those that used chlorine-free cleaning methods supports the further use of chlorine-free cleaning agents in dairy production.

Novel methods of microbiome analysis in the food industry

The study of the food microbiome has gained considerable interest in recent years, mainly due to the wide range of applications that can be derived from the analysis of metagenomes. Among these applications, it is worth mentioning the possibility of using metagenomic analyses to determine food authenticity, to assess the microbiological safety of foods thanks to the detection and tracking of pathogens, antibiotic resistance genes and other undesirable traits, as well to identify the microorganisms responsible for food processing defects. Metataxonomics and metagenomics are currently the gold standard methodologies to explore the full potential of metagenomes in the food industry. However, there are still a number of challenges that must be solved in order to implement these methods routinely in food chain monitoring, and for the regulatory agencies to take them into account in their opinions. These challenges include the difficulties of analysing foods and food-related environments with a low microbial load, the lack of validated bioinformatics pipelines adapted to food microbiomes and the difficulty of assessing the viability of the detected microorganisms. This review summarizes the methods of microbiome analysis that have been used, so far, in foods and food-related environments, with a specific focus on those involving Next-Generation Sequencing technologies.

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.

WGS based analysis of acquired antimicrobial resistance in human and non-human Acinetobacter baumannii isolates from a German perspective

Background

Acinetobacter baumannii ability to develop and acquire resistance makes it one of the most critical nosocomial pathogens globally. Whole-genome sequencing (WGS) was applied to identify the acquired or mutational variants of antimicrobial resistance (AMR) genes in 85 German A. baumannii strains utilizing Illumina technology. Additionally, the whole genome of 104 German isolates deposited in the NCBI database was investigated.

Results

In-silico analysis of WGS data revealed wide varieties of acquired AMR genes mediating resistance mostly to aminoglycosides, cephalosporins, carbapenems, sulfonamides, tetracyclines and macrolides. In the 189 analyzed genomes, the ant (3″)-IIa conferring resistance to aminoglycosides was the most frequent (55%), followed by bla_ADC.25 (38.6%) conferring resistance to cephalosporin, bla_OXA-23 (29%) and the bla_OXA-66 variant of the intrinsic bla_OXA-51-likes (26.5%) conferring resistance to carbapenems, the sul2 (26%) conferring resistance to sulfonamides, the tet. B (19.5%) conferring resistance to tetracycline, and mph. E and msr. E (19%) conferring resistance to macrolides. bla_TEM variants conferring resistance to cephalosporins were found in 12% of genomes. Thirteen variants of the intrinsic bla_OXA-51 carbapenemase gene, bla_OXA-510 and bla_ADC-25 genes were found in isolates obtained from dried milk samples.

Conclusion

The presence of strains harboring acquired AMR genes in dried milk raises safety concerns and highlights the need for changes in producing dried milk. Acquired resistance genes and chromosomal gene mutation are successful routes for disseminating AMR determinants among A. baumannii. Identification of chromosomal and plasmid-encoded AMR in the genome of A. baumannii may help understand the mechanism behind the genetic mobilization and spread of AMR genes.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12866-021-02270-7.

Combining Culture-Dependent and Culture-Independent Methods: New Methodology Insight on the Vibrio Community of Ruditapes philippinarum

Vibrios represent a natural contaminant of seafood products. V. alginolyticus, V. cholerae, V. parahaemolyticus and V. vulnificus are the most hazardous species to human health. Given the worldwide consumption of mollusc products, reliable detection of Vibrio species is recommended to prevent human vibriosis. In this study, culture-dependent and -independent methods were compared and integrated to implement knowledge of the Manila clam Vibrio community composition. Here, 16S and recA-pyrH metabarcoding were applied to compare the microbial communities of homogenate clam samples (culture-independent method) and their culture-derived samples plated on three different media (culture-dependent method). In addition, a subset of plated clam samples was investigated using shotgun metagenomics. Homogenate metabarcoding characterized the most abundant taxa (16S) and Vibrio species (recA-pyrH). Culture-dependent metabarcoding detected the cultivable taxa, including rare species. Moreover, marine agar medium was found to be a useful substrate for the recovery of several Vibrio species, including the main human pathogenic ones. The culture-dependent shotgun metagenomics detected all the main human pathogenic Vibrio species and a higher number of vibrios with respect to the recA-pyrH metabarcoding. The study revealed that integration of culture-dependent and culture-independent methods might be a valid approach for the characterization of Vibrio biodiversity.

Microbiome Sample Comparison and Search: From Pair-Wise Calculations to Model-Based Matching

A huge quantity of microbiome samples have been accumulated, and more are yet to come from all niches around the globe. With the accumulation of data, there is an urgent need for comparisons and searches of microbiome samples among thousands of millions of samples in a fast and accurate manner. However, it is a very difficult computational challenge to identify similar samples, as well as identify their likely origins, among such a grand pool of samples from all around the world. Currently, several approaches have already been proposed for such a challenge, based on either distance calculation, unsupervised algorithms, or supervised algorithms. These methods have advantages and disadvantages for the different settings of comparisons and searches, and their results are also drastically different. In this review, we systematically compared distance-based, unsupervised, and supervised methods for microbiome sample comparison and search. Firstly, we assessed their accuracy and efficiency, both in theory and in practice. Then we described the scenarios in which one or multiple methods were applicable for sample searches. Thirdly, we provided several applications for microbiome sample comparisons and searches, and provided suggestions on the choice of methods. Finally, we provided several perspectives for the future development of microbiome sample comparison and search, including deep learning technologies for tracking the sources of microbiome samples.

Building a Resilient, Sustainable, and Healthier Food Supply Through Innovation and Technology

The modern food supply faces many challenges. The global population continues to grow and people are becoming wealthier, so the food production system must respond by creating enough high-quality food to feed everyone with minimal damage to our environment. The number of people suffering or dying from diet-related chronic diseases, such as obesity, diabetes, heart disease, stroke, and cancer, continues to rise, which is partly linked to overconsumption of highly processed foods, especially high-calorie or rapidly digestible foods. After falling for many years, the number of people suffering from starvation or malnutrition is rising, and thishas been exacerbated by the global COVID-19 pandemic. The highly integrated food supply chains that spread around the world are susceptible to disruptions due to policy changes, economic stresses, and natural disasters, as highlighted by the recent pandemic. In this perspective article, written by members of the Editorial Committee of the Annual Review of Food Science and Technology, we highlight some of the major challenges confronting the modern food supply chain as well as how innovations in policy and technology can be used to address them. Pertinent technological innovations include robotics, machine learning, artificial intelligence, advanced diagnostics, nanotechnology, biotechnology, gene editing, vertical farming, and soft matter physics. Many of these technologies are already being employed across the food chain by farmers, distributors, manufacturers, and consumers to improve the quality, nutrition, safety, and sustainability of the food supply. These innovations are required to stimulate the development and implementation of new technologies to ensure a more equitable, resilient, and efficient food production system. Where appropriate, these technologies should be carefully tested before widespread implementation so that proper risk-benefit analyses can be carried out. They can then be employed without causing unforeseen adverse consequences. Finally, it is important to actively engage all stakeholders involved in the food supply chain throughout the development and testing of these new technologies to support their adoption if proven safe and effective.

Invited review: Controlling dairy product spoilage to reduce food loss and waste

Food loss and waste is a major concern in the United States and globally, with dairy foods representing one of the top categories of food lost and wasted. Estimates indicate that in the United States, approximately a quarter of dairy products are lost at the production level or wasted at the retail or consumer level annually. Premature microbial spoilage of dairy products, including fluid milk, cheese, and cultured products, is a primary contributor to dairy food waste. Microbial contamination may occur at various points throughout the production and processing continuum and includes organisms such as gram-negative bacteria (e.g., Pseudomonas), gram-positive bacteria (e.g., Paenibacillus), and a wide range of fungal organisms. These organisms grow at refrigerated storage temperatures, often rapidly, and create various degradative enzymes that result in off-odors, flavors, and body defects (e.g., coagulation), rendering them inedible. Reducing premature dairy food spoilage will in turn reduce waste throughout the dairy continuum. Strategies to reduce premature spoilage include reducing raw material contamination on-farm, physically removing microbial contaminants, employing biocontrol agents to reduce outgrowth of microbial contaminants, tracking and eliminating microbial contaminants using advanced molecular microbiological techniques, and others. This review will address the primary microbial causes of premature dairy product spoilage and methods of controlling this spoilage to reduce loss and waste in dairy products.

Evaluation of methods for the reduction of contaminating host reads when performing shotgun metagenomic sequencing of the milk microbiome

Shotgun metagenomic sequencing is a valuable tool for the taxonomic and functional profiling of microbial communities. However, this approach is challenging in samples, such as milk, where a low microbial abundance, combined with high levels of host DNA, result in inefficient and uneconomical sequencing. Here we evaluate approaches to deplete host DNA or enrich microbial DNA prior to sequencing using three commercially available kits. We compared the percentage of microbial reads obtained from each kit after shotgun metagenomic sequencing. Using bovine and human milk samples, we determined that host depletion with the MolYsis complete5 kit significantly improved microbial sequencing depth compared to other approaches tested. Importantly, no biases were introduced. Additionally, the increased microbial sequencing depth allowed for further characterization of the microbiome through the generation of metagenome-assembled genomes (MAGs). Furthermore, with the use of a mock community, we compared three common classifiers and determined that Kraken2 was the optimal classifier for these samples. This evaluation shows that microbiome analysis can be performed on both bovine and human milk samples at a much greater resolution without the need for more expensive deep-sequencing approaches.

Impacts of Milking and Housing Environment on Milk Microbiota

The aim of the present study was to determine the effects of farming environments on microbiota in raw milk and to assess the relationship among microbes by 16S rRNA sequencing methods. Samples of raw milk, cow trough water, teat dip cup, teat, teat liner, dairy hall air, cowshed air, feces, feed, and bedding from two farms were collected. The two highest abundant bacterial groups of Moraxellaceae and Staphylococcaceae were found in milk and teat liner samples, respectively, at Zhengzhou farm, Henan Province. Moreover, the two highest abundant bacterial groups of Enterobacteriaceae and Moraxellaceae were found in milk and teat dip cup samples, respectively, at Qiqihar farm, Heilongjiang Province. Source Tracker analysis revealed that the teat liner and teat dip cup were the most important contributors of microbes in milk samples at Zhengzhou farm and Qiqihar farm, respectively, which could be attributed to the management level of the farm. Therefore, disinfection and cleaning procedures should be developed to improve the quality of raw milk.

Detection of Antimicrobial Resistance Genes in the Milk Production Environment: Impact of Host DNA and Sequencing Depth

Over the past decades, antimicrobial resistance (AMR) has been recognized as one of the most serious threats to public health. Although originally considered a problem to human health, the emerging crisis of AMR requires a "One Health" approach, considering human, animal, and environmental reservoirs. In this regard, the extensive use of antibiotics in the livestock production systems to treat mastitis and other bacterial diseases can lead to the presence of AMR genes in bacteria that contaminate or naturally occur in milk and dairy products, thereby introducing them into the food chain. The recent development of high-throughput next-generation sequencing (NGS) technologies is improving the fast characterization of microbial communities and their functional capabilities. In this context, whole metagenome sequencing (WMS), also called shotgun metagenomic sequencing, allows the generation of a vast amount of data which can be interrogated to generate the desired evidence, including the resistome. However, the amount of host DNA poses a major challenge to metagenome analysis. Given the current absence of literature concerning the application of WMS on milk to detect the presence of AMR genes, in the present study, we evaluated the effect of different sequencing depths, host DNA depletion methods and matrices to characterize the resistome of a milk production environment. WMS was conducted on three aliquots of bulk tank milk and three aliquots of the in-line milk filter collected from a single dairy farm; a fourth aliquot of milk and milk filter was bioinformatically subsampled. Two commercially available host DNA depletion methods were applied, and metagenomic DNA was sequenced to two different sequencing depth. Milk filters proved to be the most suitable matrices to evaluate the presence of AMR genes; besides, the pre-extraction host DNA depletion method was the most efficient approach to remove host reads. To our knowledge, this is the first study to evaluate the limitations posed by the host DNA in investigating the milk resistome with a WMS approach, confirming the circulation of AMR genes in the milk production environment.

Gaps in the assortment of rapid assays for microorganisms of interest to the dairy industry

This review presents the results of a study into the offering of rapid microbial detection assays to the Irish dairy industry. At the outset, a consultation process was undertaken whereby key stakeholders were asked to compile a list of the key microorganisms of interest to the sector. The resultant list comprises 19 organisms/groups of organisms divided into five categories: single pathogenic species (Cronobacter sakazakii, Escherichia coli and Listeria monocytogenes); genera containing pathogenic species (Bacillus, Clostridium, Listeria, Salmonella; Staphylococcus); broad taxonomic groupings (Coliforms, Enterobacteriaceae, fecal Streptococci, sulfite reducing bacteria/sulfite reducing Clostridia [SRBs/SRCs], yeasts and molds); organisms displaying certain growth preferences or resistance as regards temperature (endospores, psychrotrophs, thermodurics, thermophiles); indicators of quality (total plate count, Pseudomonas spp.). A survey of the rapid assays commercially available for the 19 organisms/groups of organisms was conducted. A wide disparity between the number of rapid tests available was found. Four categories were used to summarize the availability of rapid assays per organism/group of organisms: high coverage (>15 assays available); medium coverage (5-15 assays available); low coverage (<5 assays available); no coverage (0 assays available). Generally, species or genera containing pathogens, whose presence is regulated-for, tend to have a good selection of commercially available rapid assays for their detection, whereas groups composed of heterogenous or even undefined genera of mainly spoilage organisms tend to be "low coverage" or "no coverage." Organisms/groups of organisms with "low coverage" by rapid assays include: Clostridium spp.; fecal Streptococci; and Pseudomonas spp. Those with "no coverage" by rapid assays include: endospores; psychrotrophs; SRB/SRCs; thermodurics; and thermophiles. An important question is: why have manufacturers of rapid microbiological assays failed to respond to the necessity for rapid methods for these organisms/groups of organisms? The review offers explanations, ranging from the technical difficulty involved in detecting as broad a group as the thermodurics, which covers the spores of multiple sporeforming genera as well at least six genera of mesophilic nonsporeformers, to the taxonomically controversial issue as to what constitutes a fecal Streptococcus or SRBs/SRCs. We review two problematic areas for assay developers: validation/certification and the nature of dairy food matrices. Development and implementation of rapid alternative test methods for the dairy industry is influenced by regulations relating to both the microbiological quality standards and the criteria alternative methods must meet to qualify as acceptable test methods. However, the gap between the certification of developer's test systems as valid alternative methods in only a handful of representative matrices, and the requirement of dairy industries to verify the performance of alternative test systems in an extensive and diverse range of dairy matrices needs to be bridged before alternative methods can be widely accepted and adopted in the dairy industry. This study concludes that many important dairy matrices have effectively been ignored by assay developers.