How to Improve Surveillance Program for Shiga Toxin-Producing E. coli (STEC): Gap Analysis and Pilot Study.

Several pathotypes of enteric E. coli have been identified. The group represented by Shiga toxin-producing E. coli (STEC) is of particular interest. Raw milk and raw milk products are significant sources of STEC infection in humans; therefore, identifying pathogens at the herd level is crucial for public health. Most national surveillance programs focus solely on raw milk and raw milk cheeses that are ready for retail sale, neglecting the possibility of evaluating the source of contamination directly at the beginning of the dairy chain. To assess the viability of the application of new molecular methodologies to STEC identification in raw milk filters and in calf feces, we analyzed 290 samples from 18 different dairy herds, including 88 bulk tank milk (BTM), 104 raw milk filters (RMF), and 98 calf feces samples. In total 3.4% of BTM, 41.4% of RMF, and 73.4% of calves' feces were positive for stx, supporting our hypothesis that BTM is not a suitable matrix to assess the presence of STEC at herd level, underestimating it. Our conclusion is that the surveillance program needs critical and extensive improvements such as RMF and calves' feces analysis implementation to be more efficient in detecting and preventing STEC infections. The epidemiology of these infections and the characteristics of the pathogen clearly show how a One Health approach will be pivotal in improving our capabilities to control the spread of these infections.

Innovative Elastomers with Antimicrobial Activity May Decrease Infection Risks during Milking.

Contagious pathogens are very costly to dairy herds, and they may have zoonotic and reverse-zoonotic potentials and may contribute to the spread of antimicrobial resistance. One of the most important risk factors for spreading these infections is milking, when liner contamination may transfer the pathogens from infected to healthy cows. There is no effective protocol to prevent the transmission of infection without the segregation of infected cows. Recently, the availability of elastomers with patented antimicrobial components in their formulations has allowed the exploration of alternative methods to reduce the risk of infection. Two different types of elastomers (rubber and silicone) and nine different formulations were challenged with three major mastitis pathogens (S. aureus, S. agalactiae, and E. coli). The results that were obtained in this study were interesting and unexpected. Indeed, to our knowledge, this is the first study to show that basic rubber materials have intrinsic antimicrobial activity. Silicone elastomers did not exhibit the same levels of bactericidal activity, although they did exhibit some antibacterial capacity. A significant decrease in bacterial survival curves was observed for all the formulations tested when antimicrobial components were added. The different results observed for the various products are likely due to the different formulations and diverse manufacturing processes. The availability of these new materials that significantly reduce the bacterial load on the liner surface may reduce the risk of spreading intramammary infections during milking. This would be an important step forward in achieving global sustainability of dairy herds, consistent with the objectives of One Health, by reducing the risks of zoonotic diseases and antimicrobial treatments.

Epidemiology of Antimicrobial Resistance Genes in Staphylococcus aureus Isolates from a Public Database from a One Health Perspective-Sample Origin and Geographical Distribution of Isolates.

Staphylococcus aureus are commensal bacteria that are found in food, water, and a variety of settings in addition to being present on the skin and mucosae of both humans and animals. They are regarded as a significant pathogen as well, with a high morbidity that can cause a variety of illnesses. The Centers for Disease Control and Prevention (CDC) has listed them among the most virulent and resistant to antibiotics bacterial pathogens, along with Escherichia coli, Staphylococcus, Klebsiella pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa, Enterococcus faecalis, and Enterococcus faecium. Additionally, S. aureus is a part of the global threat posed by the existence of antimicrobial resistance (AMR). Using 26,430 S. aureus isolates from a global public database (NPDIB; NCBI Pathogen Detection Isolate Browser), epidemiological research was conducted. The results corroborate the evidence of notable variations in isolate distribution and ARG (Antimicrobial Resistance Gene) clusters between isolate sources and geographic origins. Furthermore, a link between the isolates from human and animal populations is suggested by the ARG cluster patterns. This result and the widespread dissemination of the pathogens among animal and human populations highlight how crucial it is to learn more about the epidemiology of these antibiotic-resistance-related infections using a One Health approach.

Epidemiology of Antimicrobial Resistance Genes in Staphyloccocus aureus Isolates from a Public Database in a One Health Perspective-Sample Characteristics and Isolates' Sources.

Staphylococcus aureus is considered one of the most widespread bacterial pathogens for both animals and humans, being the causative agent of various diseases like food poisoning, respiratory tract infections, nosocomial bacteremia, and surgical site and cardiovascular infections in humans, as well as clinical and subclinical mastitis, dermatitis, and suppurative infections in animals. Thanks to their genetic flexibility, several virulent and drug-resistant strains have evolved mainly due to horizontal gene transfer and insurgence of point mutations. Infections caused by the colonization of such strains are particularly problematic due to frequently occurring antibiotic resistance, particulary methicillin-resistant S. aureus (MRSA), and are characterized by increased mortality, morbidity, and hospitalization rates compared to those caused by methicillin-sensitive S. aureus (MSSA). S. aureus infections in humans and animals are a prime example of a disease that may be managed by a One Health strategy. In fact, S. aureus is a significant target for control efforts due to its zoonotic potential, the frequency of its illnesses in both humans and animals, and the threat posed by S. aureus antibiotic resistance globally. The results of an epidemiological analysis on a worldwide public database (NCBI Pathogen Detection Isolate Browser; NPDIB) of 35,026 S. aureus isolates were described. We considered the diffusion of antibiotic resistance genes (ARGs), in both human and animal setting, and the results may be considered alarming. The result of this study allowed us to identify the presence of clusters with specific ARG patterns, and that these clusters are associated with different sources of isolation (e.g., human, non-human).

Current Research on Infectious Diseases of Domestic Animals from a One Health Perspective.

One Health is a well-known strategy for promoting and developing interdisciplinary collaboration across all aspects of health in human, animal, and environmental domains [...].

Early Milk Total and Differential Cell Counts as a Diagnostic Tool to Improve Antimicrobial Therapy Protocols.

Mastitis is a major cause of antimicrobial treatments either during lactation or at drying off. From a One Health perspective, there should be a balance between the risk of IMI that may impair cow health and welfare and the reduction of antimicrobial usage to decrease antimicrobial resistance, as may happen when applying selective dry-cow therapy. This reduction may be achieved by an early and accurate diagnosis followed by prudent and rationale therapeutical protocols. This study aims to assess the accuracy of PLCC (neutrophils + lymphocyte count/mL) in identifying cows at risk of having IMI due to major pathogens (S.aureus, Str.agalactiae, Str.uberis, and Str.dysgalactiae), and to simulate the impact of this early diagnosis on the potential number of treatments using a decision-tree model. The results of this study showed that PLCC had an overall accuracy of 77.6%. The results of the decision-tree model based on data from the 12 participating herds, with an overall prevalence of major pathogens of 1.5%, showed a potential decrease in the number of treatments of about 30% (from 3.4% to 2.5%) when PLCC in early lactation (days 5-16) was used to identify cows at risk for major pathogens compared with using SCC at the first milk test (days 17-43). The study confirmed that it is possible to improve animal health and reduce the risk of antimicrobial use through early IMI detection based on PLCC and applying a rationale and prudent antimicrobial protocol.

Regulatory Role of microRNA of Milk Exosomes in Mastitis of Dairy Cows.

The aim of this study was to compare the cargos of miRNA in exosomes isolated from the milk of healthy (H) cows, cows at risk of mastitis (ARM), and cows with subclinical mastitis (SCM). Based on the number of somatic cells and the percentage of polymorphonuclear cells, 10 cows were assigned to group H, 11 to group ARM, and 11 to group SCM. After isolating exosomes in milk by isoelectric precipitation and ultracentrifugation, the extracted RNA was sequenced to 50 bp long single reads, and these were mapped against Btau_5.0.1. The resulting 225 miRNAs were uploaded to the miRNet suite, and target genes for Bos taurus were identified based on the miRTarBase and miRanda databases. The list of differentially expressed target genes resulting from the comparisons of the three groups was enriched using the Function Explorer of the Kyoto Encyclopedia of Genes and Genomes. A total of 38, 18, and 12 miRNAs were differentially expressed (DE, p < 0.05) in the comparisons of H vs. ARM, ARM vs. SCM, and H vs. SCM, respectively. Only 1 DE miRNA was shared among the three groups (bta-mir-221), 1 DE miRNA in the H vs. SCM comparison, 9 DE miRNAs in the ARM vs. SCM comparison, and 21 DE miRNAs in the H vs. ARM comparison. A comparison of the enriched pathways of target genes from the H, SCM, and ARM samples showed that 19 pathways were differentially expressed in the three groups, while 56 were expressed in the H vs. SCM comparison and 57 in the H vs. ARM comparison. Analyzing milk exosome miRNA cargos can be considered as a promising approach to study the complex molecular machinery set in motion in response to mastitis in dairy cows.

Herd and animal factors affect the variability of total and differential somatic cell count in bovine milk.

The aim of this study was to quantify some environmental (individual herds, herd productivity, milking system, and season) and animal factors [individual animals, breed, days in milk (DIM) and parity] on the variability of the log-10 transformation of somatic cell count (LSCC) and differential somatic cell count (DSCC) on individual bovine milk. A total of 159,360 test-day records related to milk production and composition were extracted from 12,849 Holstein-Friesian and 9,275 Simmental cows distributed across 223 herds. Herds were classified into high and low productivity, defined according to the average daily milk net energy output (DMEO) yielded by the cows. Data included daily milk yield (DYM; kg/d), milk fat, protein, lactose, SCC, and DSCC, and information on herds (i.e., productivity, milking system). The daily production of total and differential somatic cells in milk was calculated and then log-10 transformed, obtaining DLSCC and DLDSCC, respectively. Data were analyzed using a mixed model including the effects of individual herd, animal, repeated measurements intra animal as random, and herd productivity, milking system, season, breed, DIM, parity, DIM × parity, breed × season, DIM × milking system and parity × milking system as fixed factors. Herds with a high DMEO were characterized by a lower content of LSCC and DSCC, and higher DLSCC and DLDSCC, compared to the low DMEO herds. The association between milking system and somatic cell traits suggested that the use of the automatic milking systems would not allow for a rapid intervention on the cow, as evidenced by the higher content of all somatic cell traits compared to the other milking systems. Season was an important source of variation, as evidenced by high LSCC and DSCC content in milk during summer. Breed of cow had a large influence, with Holstein-Friesian having greater LSCC, DSCC, DLSCC, and DLDSCC compared to Simmental. With regard to DIM, the variability of LSCC was mostly related to that of DSCC, showing an increase from calving to the end of lactation, and suggesting the higher occurrence of chronic mastitis in cows toward the end of lactation. All the somatic cell traits increased across number of parities, possibly because older cows may have increased susceptibility to intramammary infections.

This study investigated factors affecting the variability of somatic cell traits in bovine milk. Animal had greater influence on somatic cell score (SCS) and differential somatic cell count (DSCC) compared to herd factors. Herds producing high average of daily milk energy were characterized by lower SCS and DSCC compared to the low average daily milk energy herds. The SCS and DSCC were higher in Holstein-Friesian than in Simmental, and during summer with respect to the other seasons. Older cows at the end of lactation showed the highest content of somatic cell traits. These results are helpful for the management of somatic cell traits at herd and animal levels.

Epidemiology of Antimicrobial Resistance Genes in Streptococcus agalactiae Sequences from a Public Database in a One Health Perspective.

Streptococcus agalactiae is a well-known pathogen in humans and food-producing animals. Therefore, this bacterium is a paradigmatic example of a pathogen to be controlled by a One Health approach. Indeed, the zoonotic and reverse-zoonotic potential of the bacteria, the prevalence of Group B Streptococci (GBS) diseases in both human and animal domains, and the threatening global situation on GBS antibiotic resistance make these bacteria an important target for control programs. An epidemiological analysis using a public database containing sequences of S. agalactiae from all over the world was conducted to evaluate the frequency and evolution of antibiotic resistance genes in those isolates. The database we considered (NCBI pathogen detection isolate browser-NPDIB) is maintained on a voluntary basis. Therefore, it does not follow strict epidemiological criteria. However, it may be considered representative of the bacterial population related to human diseases. The results showed that the number of reported sequences increased largely in the last four years, and about 50% are of European origin. The frequency data and the cluster analysis showed that the AMR genes increased in frequency in recent years and suggest the importance of verifying the application of prudent protocols for antimicrobials in areas with an increasing frequency of GBS infections both in human and veterinary medicine.

Subclinical Ketosis in Dairy Herds: Impact of Early Diagnosis and Treatment.

Clinical and subclinical ketosis (SCK) in dairy cows occurs during the lactation period frequently in many herds, causing a reduction in milk yield and alterations in milk quality with significant economic losses for farmers. SCK is defined as a preclinical stage of ketosis characterized by an elevated ketone body level without clinical signs. Often many cows develop an elevated ketone body level during the first weeks of lactation even though it never goes up to a critical point causing clinical signs. This study aimed to evaluate the prevalence of SCK in Sicily and assess the effect of a treatment with propylene glycol (PG) to control the SCK, thus, reducing the negative effect on milk quality yield. This cross-sectional study was carried out on 22 farms located south-east of Sicily and 1,588 cows in lactation. A total of 3,989 individual milk samples were collected from calving to 80 subsequently days to check the ß-hydroxybutyrate (BHB) values in order to establish the SCK status by the Fourier Transform Infrared Spectroscopy. Moreover, the contents of fat, protein, lactose, casein, urea, somatic cell count and acetone were evaluated to identify a correlation between SCK and milk quality. A total of 1,100 cows showed BHB values higher than 0.10 mmol/L. These cows were considered SCK positive, were separated from the rest of the herd, and treated with PG (400 g/head per day), all SCK cows were treated with PG and cows without SCK were not treated. The results showed a prevalence of 41.5% of SCK-positive cows during the first 9 days of lactation. The comparison among the cure rate of treated cows shows that the treatment was most effective in the first 7 days of lactation (76.5% of treated cows) than in the following days. PG positively influenced the milk quality parameters, except for the fat proportion. Moreover, the animals treated with PG showed also an increase in milk yield, supporting the economical sustainability of treatment.

Milk Quality and Safety in a One Health Perspective: Results of a Prevalence Study on Dairy Herds in Lombardy (Italy).

Mastitis is one of the major diseases of dairy cows that affects milk quality and quantity and increases the potential risk for the presence of antimicrobial residues (AR) in milk, which could lead to the development of antimicrobial resistance (AMR) among human pathogens. Even if the presence of AR in milk and milk products is low in many countries, the threat is not negligible and cannot be ignored. These problems may be investigated by applying a One Health approach, and this prevalence study aimed to estimate the risks for human health related to milk production applied to dairy herds in Lombardy. Three hundred thirty-one bulk tank milk samples were randomly collected and analyzed by CombiFoss 7 and MilkoScan 7 (milk quality, bacteria, and somatic cell count), an HPLC system coupled to a Q-Exactive Orbitrap (AR), and qPCR (contagious pathogens). The data were analyzed by a generalized linear model. The results showed a relatively high prevalence of contagious pathogens (S. aureus 28.1%; Str. agalactiae 7.3%; M. bovis 3%), which primarily affect milk nutritional components decreasing mainly milk fat content (range 1%-2.5%), but did not show them to be associated to an increase of the risk of antimicrobial residues. These latter ones were recovered only in 7/331 samples at concentrations far below official MLRs. The results support currently active surveillance programs' efficacy in reducing AR risks, which may be further improved by prioritizing them based on geographical area characteristics.

Linear Mixed-Effects Model to Quantify the Association between Somatic Cell Count and Milk Production in Italian Dairy Herds.

Milk production loss due to mastitis in dairy herds is economically important. Before estimating the economic impacts of mastitis, it is crucial to quantify the association between mastitis and milk production. The objective of this study was to estimate the association between somatic cell count (SCC, as an indicator of intramammary infection due to mastitis) and milk production for dairy cows in Lombardy, Italy. The test-day (TD) records data of 3816 dairy herds located in three different geographical areas of Lombardy from January 2016 to December 2018 were used. After data editing, the final dataset comprised 10,445,464 TD records from 2970 farms and 826,831 cows. The analysis was carried out by using a mixed-effects model with six fixed effects (geographical Area, Breed, Days in Milk, Parity, Season and Year) and nested random effects for each cow and herd. The results confirmed that the SCC had a negative association with milk production. On average, this study found that any two-fold increase of SCC resulted in a milk production loss of 0.830 (95% CI: -0.832, -0.828) kg/cow/day in the whole of Lombardy. These results can be used for economic calculations on the costs of mastitis.

Assessment of Sensitivity and Profitability of an Intravaginal Sensor for Remote Calving Prediction in Dairy Cattle.

One critical point of dairy farm management is calving and neonatal first care. Timely calving assistance is associated with the reduction of calf mortality and postpartum uterine disease, and with improved fertility in dairy cattle. This study aimed to evaluate the performance and profitability of an intravaginal sensor for the prediction of stage II of labor in dairy farms, thus allowing proper calving assistance. Seventy-three late-gestating Italian Holstein cows were submitted to the insertion of an intravaginal device, equipped with light and temperature sensors, connected with a Central Unit for the commutation of a radio-signal into a cell phone alert. The remote calving alarm correctly identified the beginning of the expulsive phase of labor in 86.3% of the monitored cows. The mean interval from alarm to complete expulsion of the fetus was 71.56 ± 52.98 min, with a greater range in cows with dystocia (p = 0.012). The sensor worked correctly in both cold and warm weather conditions, and during day- or night-time. The intravaginal probe was well tolerated, as any cow showed lesions to the vaginal mucosa after calving. Using sex-sorted semen in heifers and beef bull semen in cows at their last lactation, the economic estimation performed through PrecisionTree™ software led to an income improvement of 119 € and 123 €/monitored delivery in primiparous and pluriparous cows, respectively. Remote calving alarm devices are key components of "precision farming" management and proven to improve animal welfare, to reduce calf losses and to increase farm incomes.

Extraintestinal Pathogenic Escherichia coli: Virulence Factors and Antibiotic Resistance.

The One Health approach emphasizes the importance of antimicrobial resistance (AMR) as a major concern both in public health and in food animal production systems. As a general classification, E. coli can be distinguished based on the ability to cause infection of the gastrointestinal system (IPEC) or outside of it (ExPEC). Among the different pathogens, E. coli are becoming of great importance, and it has been suggested that ExPEC may harbor resistance genes that may be transferred to pathogenic or opportunistic bacteria. ExPEC strains are versatile bacteria that can cause urinary tract, bloodstream, prostate, and other infections at non-intestinal sites. In this context of rapidly increasing multidrug-resistance worldwide and a diminishingly effective antimicrobial arsenal to tackle resistant strains. ExPEC infections are now a serious public health threat worldwide. However, the clinical and economic impact of these infections and their optimal management are challenging, and consequently, there is an increasing awareness of the importance of ExPECs amongst healthcare professionals and the general public alike. This review aims to describe pathotype characteristics of ExPEC to increase our knowledge of these bacteria and, consequently, to increase our chances to control them and reduce the risk for AMR, following a One Health approach.

Novel ways to use sensor data to improve mastitis management.

Current sensor systems are used to detect cows with clinical mastitis. Although, the systems perform well enough to not negatively affect the adoption of automatic milking systems, the performance is far from perfect. An important advantage of sensor systems is the availability of multiple measurements per day. By clearly defining the need for detection of subclinical mastitis (SCM) and clinical mastitis (CM) from the farmers' management perspective, detection and management of SCM and CM may be improved. Sensor systems may also be used for other aspects of mastitis management. In this paper we have defined 4 mastitis situations that could be managed with the support of sensor systems. Because of differences in the associated management and the epidemiology of these specific mastitis situations, the required demands for performance of the sensor systems do differ. The 4 defined mastitis situations with the requirements of performance are the following: (1) Cows with severe CM needing immediate attention. Sensor systems should have a very high sensitivity (>95% and preferably close to 100%) and specificity (>99%) within a narrow time window (maximum 12 h) to ensure that close to all cows with true cases of severe CM are detected quickly. Although never studied, it is expected that because of the effects of severe CM, such a high detection performance is feasible. (2) Cows with mastitis that do not need immediate attention. Although these cows have a risk of progressing into severe CM or chronic mastitis, they should get the chance to cure spontaneously under close monitoring. Sensor alerts should have a reasonable sensitivity (>80%) and a high specificity (>99.5%). The time window may be around 7 d. (3) Cows needing attention at drying off. For selective dry cow treatment, the absence or presence of an intramammary infection at dry-off needs to be known. To avoid both false-positive and false-negative alerts, sensitivity and specificity can be equally high (>95%). (4) Herd-level udder health. By combining sensor readings from all cows in the herd, novel herd-level key performance indicators can be developed to monitor udder health status and development over time and raise alerts at significant deviances from predefined thresholds; sensitivity should be reasonably high, >80%, and because of the costs for further analysis of false-positive alerts, the specificity should be >99%. The development and validation of sensor-based algorithms specifically for these 4 mastitis situations will encourage situation-specific farmer interventions and operational udder health management.

Airborne Coronaviruses: Observations from Veterinary Experience.

The virus responsible for the pandemic that has affected 152 countries worldwide is a new strain of coronavirus (CoV), which belongs to a family of viruses widespread in many animal species, including birds, and mammals including humans. Indeed, CoVs are known in veterinary medicine affecting several species, and causing respiratory and/or enteric, systemic diseases and reproductive disease in poultry. Animal diseases caused by CoV may be considered from the following different perspectives: livestock and poultry CoVs cause mainly "population disease"; while in companion animals they are a source of mainly "individual/single subject disease". Therefore, respiratory CoV diseases in high-density, large populations of livestock or poultry may be a suitable example for the current SARS-CoV-2/COVID-19 pandemic. In this review we describe some strategies applied in veterinary medicine to control CoV and discuss if they may help to develop practical and useful strategies to control the SARS-CoV-2/COVID-19 pandemic.

Characterization of Microbiome on Feces, Blood and Milk in Dairy Cows with Different Milk Leucocyte Pattern.

Mastitis is an inflammatory disease of the mammary gland, caused by the invasion of microorganism on this site, associated with an altered immune response. Recent studies in this field hypothesize that the origin of these pathogens can also be from the gastrointestinal tract, through the entero-mammary pathway in relation to an increase in gut permeability. In this study, we wanted to investigate if inflammatory status of the mammary gland is related to an alteration of gut permeability. The microbiome of feces, blood and milk of lactating cows, recruited on the basis of the total somatic cell count and of the percentage of polymorphonuclear neutrophils and lymphocytes, was studied. Cows were divided into healthy (G), at risk of mastitis (Y) and with mastitis (R) classifications. The bacterial DNA was extracted and the V3 and V4 regions of 16S rRNA sequenced. Moreover, the quantification of total bacteria was performed with quantitative real-time PCR. A non-parametric Kruskal-Wallis test was applied at the phylum, family and genera levels and beta biodiversity was evaluated with the unweighted UniFrac distance metric. Significant differences between groups were found for the microbial composition of feces (Clostridiaceae, Turicibacteriaceae for family level and Clostridium, Dorea, SMB53 and Turicibacter for genus level), blood (Tenericutes for phylum level and Mycoplasma for genus level) and milk (OD1 and Proteobacteria for phylum level, Enterobacteriaceae and Moraxallaceae for family level and Olsenella and Rhodococcus for genus level). The beta biodiversity of feces and blood did not change between groups. Significant differences (p < 0.05) were observed between the beta diversity in milk of G group and Y group and between Y group and R group. The number of taxa in common between feces, blood and milk were 8 at a phylum, 19 at a family and 15 at a genus level. From these results, the bacterial crossing from gut to milk in cows was not confirmed but remained hypothetical and deserves further investigation.

Total and Differential Cell Counts as a Tool to Identify Intramammary Infections in Cows after Calving.

Milk differential somatic cells count (DSCC), made possible under field conditions by the recent availability of a high-throughput milk analyzer may represent an improvement in mastitis diagnosis. While an increasing number of studies reports data on DSCC on individual cow samples, very few concerns DSCC from quarter milk samples. This paper reports for the first time the results of a retrospective study aiming to assess the performance of total (SCC), DSCC, and a novel calculated marker (PLCC) measured on quarter milk samples as a method to identify cows at risk for intramammary infection (IMI) in the first 30 days after calving. Overall, 14,586 valid quarter milk samples (3658 cows) taken in the first 30 days of lactation were considered. Quarters with major pathogens (MP) IMI, as expected, showed significantly higher means for SCC, DSCC, and PLCC. The accuracy, sensitivity, and specificity of the diagnosis based on different cut-offs calculated by ROC analysis are relatively close among DSCC, PLCC, and SCC (up to cut-off of 200,000 cells/mL). However, decision-tree analysis which includes the costs of analysis, but also the costs of the actions taken after test results showed as PLCC has the lowest cost among the three markers, and PLCC and SCC are cost effective when MP prevalence is higher than 6-10%. This diagnostic approach is of high interest particularly when selective dry cow therapy is applied to improve animal health at the herd level.

Raw Cow Milk Bacterial Consortium as Bioindicator of Circulating Anti-Microbial Resistance (AMR).

The environment, including animals and animal products, is colonized by bacterial species that are typical and specific of every different ecological niche. Natural and human-related ecological pressure promotes the selection and expression of genes related to antimicrobial resistance (AMR). These genes might be present in a bacterial consortium but might not necessarily be expressed. Their expression could be induced by the presence of antimicrobial compounds that could originate from a given ecological niche or from human activity. In this work, we applied (meta)proteomics analysis of bacterial compartment of raw milk in order to obtain a method that provides a measurement of circulating AMR involved proteins and gathers information about the whole bacterial composition. Results from milk analysis revealed the presence of 29 proteins/proteoforms linked to AMR. The detection of mainly ß-lactamases suggests the possibility of using the milk microbiome as a bioindicator for the investigation of AMR. Moreover, it was possible to achieve a culture-free qualitative and functional analysis of raw milk bacterial consortia.

Raw milk and fecal microbiota of commercial Alpine dairy cows varies with herd, fat content and diet.

The factors that influence the diversity and composition of raw milk and fecal microbiota in healthy commercial dairy herds are not fully understood, partially because the majority of metataxonomic studies involve experimental farms and/or single factors. We analyzed the raw milk and fecal microbiota of 100 healthy cows from 10 commercial alpine farms from the Province of Trento, Italy, using metataxonomics and applied statistical modelling to investigate which extrinsic and intrinsic parameters (e.g. herd, diet and milk characteristics) correlated with microbiota richness and composition in these relatively small traditional farms. We confirmed that Firmicutes, Ruminococcaceae and Lachnospiraceae families dominated the fecal and milk samples of these dairy cows, but in addition, we found an association between the number of observed OTUs and Shannon entropy on each farm that indicates higher microbiota richness is associated with increased microbiota stability. Modelling showed that herd was the most significant factor affecting the variation in both milk and fecal microbiota composition. Furthermore, the most important predictors explaining the variation of microbiota richness were milk characteristics (i.e. percentage fat) and diet for milk and fecal samples, respectively. We discuss how high intra-herd variation could affect the development of treatments based on microbiota manipulation.