Molecular identification of Coxiella burnetii in raw milk samples collected from farm animals in districts Kasur and Lahore of Punjab, Pakistan.

Coxiella burnetii is the worldwide zoonotic infectious agent for Q fever in humans and animals. Farm animals are the main reservoirs of C. burnetii infection, which is mainly transmitted via tick bites. In humans, oral, percutaneous, and respiratory routes are the primary sources of infection transmission. The clinical signs vary from flu-like symptoms to endocarditis for humans' acute and chronic Q fever. While it is usually asymptomatic in livestock, abortion, stillbirth, infertility, mastitis, and endometritis are its clinical consequences. Infected farm animals shed C. burnetii in birth products, milk, feces, vaginal mucus, and urine. Milk is an important source of infection among foods of animal origin. This study aimed to determine the prevalence and molecular characterization of C. burnetii in milk samples of dairy animals from two districts in Punjab, Pakistan, as it has not been reported there so far. Using a convenience sampling approach, the current study included 304 individual milk samples from different herds of cattle, buffalo, goats, and sheep present on 39 farms in 11 villages in the districts of Kasur and Lahore. PCR targeting the IS1111 gene sequence was used for its detection. Coxiella burnetii DNA was present in 19 of the 304 (6.3%) samples. The distribution was 7.2% and 5.2% in districts Kasur and Lahore, respectively. The results showed the distribution in ruminants as 3.4% in buffalo, 5.6% in cattle, 6.7% in goats, and 10.6% in sheep. From the univariable analysis, the clinical signs of infection i.e. mastitis and abortion were analyzed for the prevalence of Coxiella burnetii. The obtained sequences were identical to the previously reported sequence of a local strain in district Lahore, Sahiwal and Attock. These findings demonstrated that the prevalence of C. burnetii in raw milk samples deserves more attention from the health care system and veterinary organizations in Kasur and Lahore of Punjab, Pakistan. Future studies should include different districts and human populations, especially professionals working with animals, to estimate the prevalence of C. burnetii.

Molecular detection of Coxiella burnetii in raw meat samples collected from different abattoirs in districts Kasur and Lahore of Punjab, Pakistan.

Coxiella burnetii is the zoonotic pathogen that causes Q fever; it is widespread globally. Livestock animals are its main reservoir, and infected animals shed C. burnetii in their birth products, feces, vaginal mucus, urine, tissues, and food obtained from them, i.e., milk and meat. There were previously very few reports on the prevalence of C. burnetii in raw meat. This study aimed to determine the prevalence of C.burnetii and its molecular characterization in raw ruminant meat from the Kasur and Lahore districts in Punjab, Pakistan, as this has not been reported so far. In this study, 200 meat samples, 50 from each species of cattle, buffalo, goat, and sheep, were collected from the slaughterhouses in each district, Kasur and Lahore in 2021 and 2022. PCR was used for the detection of the IS1111 element of C. burnetii. The data were recorded and univariate analysis was performed to determine the frequency of C. burnetii DNA in raw meat samples obtained from different ruminant species using the SAS 9.4 statistical package. Of the total of 200 raw meat samples, C. burnetii DNA was present in 40 (20%) of them, tested by PCR using the IS1111 sequence. The prevalence of C.burnetii differed among the studied species of ruminants. When species were compared pairwise, the prevalence in cattle was statistically significantly lower than in sheep (P = 0.005). The sequence alignment based on origin implied that the strains are genetically diverse in different districts of Punjab, Pakistan. The findings demonstrated that the prevalence of C. burnetii, especially in raw meat samples, deserves more attention from the health care system and professionals from Punjab, Pakistan, i.e., abattoir workers and veterinarians.

Effects of pathogen-specific clinical mastitis occurrence in the first 100 days of lactation 1 on future mastitis occurrence in Holstein dairy cows: An observational study.

The objective of this observational study was to estimate effects of clinical mastitis (CM) cases caused by different pathogens (Streptococcus spp., Staphylococcus aureus, Staphylococcus spp., Escherichia coli, Klebsiella spp., and CM cases with no growth) occurring in the first 100 d in lactation 1, of a dairy cow on the future rate of occurrence of different types of CM during a cow's full lifetime. The outcomes were occurrence of Streptococcus spp., Staphylococcus aureus, Staphylococcus spp., Escherichia coli, Klebsiella spp., and CM cases with no growth, after the first 100 d of lactation 1, until a cow's removal through death or sale in that or a subsequent lactation. Data, including information on CM cases, milk production, and event dates (including death or sale dates), were collected from 14,440 cows in 5 New York State Holstein herds from January 2004 until February 2014. Generalized linear mixed models with a Poisson distribution and log link function were fit for each pathogen. The individual cow was the unit of analysis. Escherichia coli was a predictor of future occurrence of E. coli, Klebsiella spp., and CM cases with no growth. Early-occurring Klebsiella spp. was a predictor of future cases of Klebsiella spp. Cases with no growth were predictors of future occurrence of Staphylococcus spp., E. coli, Klebsiella spp., and cases with no growth. Thus, E. coli and cases with no growth occurring early in lactation 1 appear to be consistent risk factors for future cases of CM, whether cases with the same pathogen or a different pathogen. In this study, farm effects on later pathogen occurrence differed somewhat, so treatment protocol and culling strategy may play a role in the findings. Nevertheless, the findings may help farmers in managing young cows with CM in early productive life, especially those with E. coli or cases with no growth, in that they may be more susceptible to future CM cases in their later productive life, thus meriting closer attention.

Association of pathogen-specific clinical mastitis in the first 100 days of first lactation with productive lifetime: An observational study comparing competing risks models for death and sale with the Cox model.

The objective of this observational study was to study the association between clinical mastitis (CM) (Streptococcus spp., Staphylococcus aureus, Staphylococcus spp., Escherichia coli, Klebsiella spp., cases with other treated or other not treated organisms, CM without growth) occurring in a dairy cow's first 100 days (d) of her first lactation and her total productive lifetime, ending in death or sale (for slaughter). Data were collected from 24,831 cows in 5 New York Holstein herds from 2004 to 2014. Two analytical approaches were compared. First, removals (death, sale) were treated as competing events in separate survival analyses, in proportional subdistribution hazards models. In one, death was coded as the event of interest and sale as the competing event; in another, sale was the event of interest and death the competing event. Second, traditional survival analysis (Cox proportional hazards) was conducted. In all models, the time variable was number of days from date of first calving until event (death or sale) date; if the cow was alive at study end, she was censored. Models were stratified by herd. Ten percent of cows died; 48.4 % were sold. In the competing risks analysis, E. coli and CM without growth were associated with death; the former with an increased hazard rate of death, the latter with a lower one. Streptococcus spp., Staph. aureus, Klebsiella spp., cases with other treated or untreated organisms, and CM without growth were associated with higher hazard rates of sale. The Cox proportional hazards model's hazard rates were higher than those in the competing risks model in which death was the event of interest, and resembled those in the model in which sale was the event of interest. Four additional Cox models, omitting dead or sold cows, or censoring each, were also fitted; hazard ratios were similar to the above models. Proportional subdistribution hazards models were appropriate due to competing risks (death, sale); they produce less-biased estimates. A study limitation is that while proportional subdistribution hazards models were appropriate, they have the illogical feature of keeping subjects at risk for the event of interest even after experiencing the competing event. This is, however, necessary in estimating cumulative incidence functions. Another limitation concerns pathogen variability among study farms, implying that CM decisions are farm-specific. Misclassification of 'dead' vs. 'sold' cows was also possible. Nevertheless, the findings may help in optimizing management of cows contracting specific types of CM early in productive lifetime.

Antimicrobial resistance trends among canine Escherichia coli isolated at a New York veterinary diagnostic laboratory between 2007 and 2020.

Dogs are a potential source of drug-resistant Escherichia coli, but very few large-scale antimicrobial resistance surveillance studies have been conducted in the canine population. Here, we assess the antimicrobial susceptibility patterns, identify temporal resistance and minimum inhibitory concentration (MIC) trends, and describe associations between resistance phenotypes among canine clinical E. coli isolates in the northeastern United States. Through a retrospective study design, we collected MICs from 7709 E. coli isolates from canine infections at the Cornell University Animal Health Diagnostic Center between 2007 and 2020. The available clinical data were limited to body site. Isolates were classified as resistant or susceptible to six (urinary) and 22 (non-urinary) antimicrobials based on Clinical and Laboratory Standards Institute breakpoints. We used the Mann-Kendall test (MKT) and Sen's slope to identify the presence of a significant trend in the percent of resistant isolates over the study period. Multivariable logistic regression (MLR) models were built with ceftiofur, enrofloxacin, or trimethoprim-sulfamethoxazole resistance as the outcome and either body site and isolation date, or resistance to other antimicrobials as predictors. MIC trends were characterized with survival analysis models, controlling for body site and year of isolation. Overall, 16.4% of isolates were resistant to enrofloxacin, 14.3% to ceftiofur, and 14% to trimethoprim-sulfamethoxazole. The MKT and Sen's slope revealed a significant decreasing temporal trend for gentamicin and trimethoprim-sulfamethoxazole resistance among non-urinary isolates. No significant temporal resistance trends were detected by MKT for other antimicrobials. However, controlling for body-site in MLR models identified a decrease in resistance rates to enrofloxacin and trimethoprim-sulfamethoxazole after 2010. Similarly, survival analysis data confirmed these findings and showed a decrease in MIC values after 2010 for gentamicin and trimethoprim-sulfamethoxazole, but an increase in cephalosporin MICs. MLR showed that non-urinary isolates were significantly more likely than urinary isolates to demonstrate in vitro resistance to ceftiofur, enrofloxacin, and trimethoprim-sulfamethoxazole after controlling for year of isolation. We identified a higher level of ceftiofur resistance among enrofloxacin resistant isolates from urinary and non-urinary origins. Our findings confirmed that dogs are still a non-negligeable reservoir of drug-resistant E. coli in the northeastern United States. The increase in extended-spectrum cephalosporin MIC values in 2018-2020 compared to 2007-2010 constitutes a particularly worrying issue; the relationship between ceftiofur and enrofloxacin resistance suggests that the use of fluoroquinolones could contribute to this trend. Trimethoprim-sulfamethoxazole may be a good first-line choice for empiric treatment of E. coli infections; it is already recommended for canine urinary tract infections.

Genetic and seasonal variations of Trypanosoma theileri and the association of Trypanosoma theileri infection with dairy cattle productivity in Northern Japan.

Trypanosoma theileri is considered a non- or low-pathogenic trypanosome that generally causes latent infection in apparently healthy cattle; however, T. theileri propagates in the bloodstream and may cause clinical disease in pregnant animals or co-infection with bovine leukemia virus or Theileria orientalis. In the current study, a monthly survey of T. theileri infection over one year was carried out in a research dairy farm in Hokkaido, Japan to determine the 1) seasonal variations in the prevalence, 2) genetic characterization of T. theileri, and 3) associations of milk and blood parameters in dairy cattle with T. theileri infection, including data of metabolic profile tests and dairy herd performance tests, using linear mixed models. We found that 1) the prevalence of T. theileri infection was significantly higher in summer and winter than in other seasons; 2) T. theileri possibly showed genetic diversity in Eastern Hokkaido; and 3) T. theileri infection was associated with significantly lower levels of blood urea nitrogen, milk protein, and solids-not-fat, which are caused by a low rumen fermentation level. This is the first study to report the negative impact of T. theileri infection in dairy cattle, and our study indicates that control of T. theileri infection can improve the productivity of dairy cattle.

Is Salmonella enterica shared between wildlife and cattle in cattle farming areas? An 11-year retrospective study in Tokachi district, Hokkaido, Japan.

BACKGROUND: Salmonella enterica in cattle has long been problematic and suspected to be transmitted by wildlife in Tokachi, Hokkaido, a major cattle farming area in Japan. Understanding the role of wildlife in S. enterica transmission would be helpful for developing control strategies of bovine salmonellosis. OBJECTIVES: We aimed to elucidate the possibility of S. enterica transmission between sympatric wildlife, including raccoons and crows and cattle, in Tokachi from 2008 to 2018 by analysing S. enterica detection records, and the genetic relatedness of serotypes shared between wildlife and cattle. METHODS: S. enterica detection records were based on the results of a field survey and existing cattle records at relevant organisations, including clinical reports, a monitoring survey and quarantine for introduced calves at growing farms and public calving farms. S. enterica was identified by polymerase chain reaction assay and serotyped by agglutination assay. The detection records were organised chronologically to investigate whether common serotypes in wildlife and cattle were detected in the same year. The isolates corresponding to detection records were assessed for their genetic patterns by pulsed-field gel electrophoresis. RESULTS: The prevalence of S. enterica in raccoons and crows was 10.7% (17/159) and 5.7% (55/967), respectively. The following serotypes were detected from both wildlife and cattle: Braenderup, Dublin, Infantis, Mbandaka, Montevideo, 4,[5],12:i:- and Typhimurium. Genetically similar isolates for S. Braenderup, S. Dublin, S. Montevideo and S. 4,[5],12:i:- were detected from both species in the same year. CONCLUSIONS: Our long-term retrospective observations supported that S. enterica was shared between wildlife and cattle. Wildlife invasions should be controlled at farms to prevent inter-species transmission of S. enterica from livestock farms.

System Economic Costs of Antibiotic Use Elimination in the US Beef Supply Chain.

There is consumer pressure on the US beef cattle industry to minimize antibiotic use (ABU) in order to aid in the global antimicrobial resistance mitigation efforts. Our objective was to estimate the economic costs of ABU constraints in a conceptual US integrated beef supply chain (IBSC) to aid the beef industry in mitigating the ever-increasing risk of antimicrobial resistance, by reducing their ABU. An IBSC network model was developed and differentiated into 37 different nodes of production. Each node could only raise a specific type of animals, differentiated based on the production technique and animal health status. The cost, as well as the weight gain coefficient, was estimated for each node, using an IBSC cost of production model. Linear programming solutions to this network model provided the least cost path of beef supply through the system, under various ABU constraints. The cost as well as weight gain coefficient of the 37 nodes, initial supply of 28.5 million calves weighing 0.65 million metric tons, and final demand of 16.14 million metric tons of slaughter-ready fed cattle were used as inputs/constraints to the three different linear programming scenarios, with different ABU constraints. Our first scenario, which placed no constraint on ABU, estimated that the minimum total economic cost to meet the final beef demand was $38.6 billion. The optimal solution was to use only the high health status calves for beef production. Because low health calves occur in the beef system, our second scenario required all the calves irrespective of their health status to be used, which increased the system cost to $41.5 billion. Thus, the value of only producing high health status calves is $2.9 billion. Our third scenario, which restricted feedlots from using antibiotics even for low health calves, incurred a total cost of $41.9 billion for antibiotic-free beef production. We concluded that the additional cost of $367 million for implementing antibiotic-free beef production is relatively low, ~0.90% of the minimum cost incurred for the conventional beef supply chain (model 2 cost of $41.5 billion). However, a much higher cost savings is obtained by producing only high health status calves.

Who infects whom?-Reconstructing infection chains of Mycobacterium avium ssp. paratuberculosis in an endemically infected dairy herd by use of genomic data.

Recent evidence of circulation of multiple strains within herds and mixed infections of cows marks the beginning of a rethink of our knowledge on Mycobacterium avium ssp. paratuberculosis (MAP) epidemiology. Strain typing opens new ways to investigate MAP transmission. This work presents a method for reconstructing infection chains in a setting of endemic Johne's disease on a well-managed dairy farm. By linking genomic data with demographic field data, strain-specific differences in spreading patterns could be quantified for a densely sampled dairy herd. Mixed infections of dairy cows with MAP are common, and some strains spread more successfully. Infected cows remain susceptible for co-infections with other MAP genotypes. The model suggested that cows acquired infection from 1-4 other cows and spread infection to 0-17 individuals. Reconstructed infection chains supported the hypothesis that high shedding animals that started to shed at an early age and showed a progressive infection pattern represented a greater risk for spreading MAP. Transmission of more than one genotype between animals was recorded. In this farm with a good MAP control management program, adult-to-adult contact was proposed as the most important transmission route to explain the reconstructed networks. For each isolate, at least one more likely ancestor could be inferred. Our study results help to capture underlying transmission processes and to understand the challenges of tracing MAP spread within a herd. Only the combination of precise longitudinal field data and bacterial strain type information made it possible to trace infection in such detail.

Comparison of China's and the European Union's Approaches to Antimicrobial Stewardship in the Pork Industry.

Antimicrobial resistance (AMR) is a recognized global public health concern. Although the link between antimicrobial usage in food animals and AMR in humans is established, the detailed interactions are unclear. Antimicrobial stewardship (AMS) in livestock was first implemented in Europe with Sweden as the pioneer in 1986. Despite this head start, AMR is still an ongoing challenge for Europe. The European Union (EU) is an established agriculture producer, the second largest pork producer globally, and one of the largest markets for organic food. China is the global leader in both production and consumption of pork. China's rise in prosperity has led to an increase in its pork demand. Chinese producers commonly use antimicrobials during production for disease treatment and prevention to meet this increased demand. China's rising prosperity together with recent publicized food safety scandals, disease outbreaks in domestic livestock products, and increased AMR awareness have resulted in an increased willingness to pay and demand for organic food by Chinese consumers. Responding to the growing concerns of AMR by consumers and the World Health Organization (WHO), the Chinese government introduced a national pilot program in 2016 to reduce unnecessary antimicrobial use. Compared with China, the EU is a different entity as it is a political union comprising diverse countries and although it may have more experience in AMS, both entities face similar issues with AMR and increasing demand for organic food. Increased interest in organic food has arisen due to concerns about AMR, food safety, outbreaks of bacterial food contamination, and animal welfare. This article aims to compare the different AMS strategies employed by each entity, China and the EU, and how the increased demand for organic produce globally also influences the effort to reduce antimicrobial use in these entities' pork industries.

Evolutionary genomic and bacteria GWAS analysis of Mycobacterium avium subsp. paratuberculosis and dairy cattle Johne's disease phenotypes.

Mycobacterium avium subsp. paratuberculosis (MAP) is the causative agent of Johne's disease in ruminants, which has important health consequences for dairy cattle. The Regional Dairy Quality Management Alliance (RDQMA) project is a multistate research program involving MAP isolates taken from three intensively studied commercial dairy farms in the northeastern United States, which emphasized longitudinal data collection of both MAP isolates and animal health in three regional dairy herds for a period of about 7 years. This paper reports the results of a pan-GWAS analysis involving 318 MAP isolates and dairy cow Johne's disease phenotypes, taken from these three farms. Based on our highly curated accessory gene count the pan-GWAS analysis identified several MAP genes associated with bovine Johne's disease phenotypes scored from these three farms, with some of the genes having functions suggestive of possible cause/effect relationships to these phenotypes. This paper reports a pan-genomic comparative analysis between MAP and Mycobacterium tuberculosis, assessing functional Gene Ontology category enrichments between these taxa. Finally, we also provide a population genomic perspective on the effectiveness of herd isolation, involving closed dairy farms, in preventing MAP inter-farm cross infection on a micro-geographic scale.IMPORTANCE Mycobacterium avium subsp. paratuberculosis (MAP) is the causative agent of Johne's disease in ruminants, which has important health consequences for dairy cattle, and enormous economic consequences for the dairy industry. Understanding which genes in this bacterium are correlated with key disease phenotypes can lead to functional experiments targeting these genes and ultimately lead to improved control strategies. This study represents a rare example of a prolonged longitudinal study of dairy cattle where the disease was measured and the bacteria were isolated from the same cows. The genome sequences of over 300 MAP isolates were analyzed for genes that were correlated with a wide range of Johne's disease phenotypes. A number of genes were identified that were significantly associated with several aspects of the disease and suggestive of further experimental follow-up.

Analysis of Multidrug Resistance in Staphylococcus aureus with a Machine Learning-Generated Antibiogram.

Multidrug resistance (MDR) surveillance consists of reporting MDR prevalence and MDR phenotypes. Detailed knowledge of the specific associations underlying MDR patterns can allow antimicrobial stewardship programs to accurately identify clinically relevant resistance patterns. We applied machine learning and graphical networks to quantify and visualize associations between resistance traits in a set of 1,091 Staphylococcus aureus isolates collected from one New York hospital between 2008 and 2018. Antimicrobial susceptibility testing was performed using reference broth microdilution. The isolates were analyzed by year, methicillin susceptibility, and infection site. Association mining was used to identify resistance patterns that consisted of two or more individual antimicrobial resistance (AMR) traits and quantify the association among the individual resistance traits in each pattern. The resistance patterns captured the majority of the most common MDR phenotypes and reflected previously identified pairwise relationships between AMR traits in S. aureus Associations between ß-lactams and other antimicrobial classes (macrolides, lincosamides, and fluoroquinolones) were common, although the strength of the association among these antimicrobial classes varied by infection site and by methicillin susceptibility. Association mining identified associations between clinically important AMR traits, which could be further investigated for evidence of resistance coselection. For example, in skin and skin structure infections, clindamycin and tetracycline resistance occurred together 1.5 times more often than would be expected if they were independent from one another. Association mining efficiently discovered and quantified associations among resistance traits, allowing these associations to be compared between relevant subsets of isolates to identify and track clinically relevant MDR.

Modeling the Effect of Tylosin Phosphate on Macrolide-Resistant Enterococci in Feedlots and Reducing Resistance Transmission.

Tylosin phosphate (TYL) is administered to more than 50% of U.S. beef cattle to reduce the incidence of liver abscesses but may increase the risk of macrolide-lincosamide-streptogramin-resistant bacteria disseminating from the feedlot. Limited evidence has been collected to understand how TYL affects the proportion of resistant bacteria in cattle or the feedlot environment. We created a mathematical model to investigate the effects of TYL administration on Enterococcus dynamics and examined preharvest strategies to mitigate the impact of TYL administration on resistance. The model simulated the physiological pharmacokinetics of orally administered TYL and estimated the pharmacodynamic effects of TYL on populations of resistant and susceptible Enterococcus within the cattle large intestine, feedlot pen, water trough, and feed bunk. The model parameters' population distributions were based on the available literature; 1000 Monte Carlo simulations were performed to estimate the likely distribution of outcomes. At the end of the simulated treatment period, the median estimated proportion of macrolide-resistant enterococci was only 1 percentage point higher within treated cattle compared with cattle not fed TYL, in part because the TYL concentrations in the large intestine were substantially lower than the enterococci minimum inhibitory concentrations. However, 25% of the simulated cattle had a >10 percentage point increase in the proportion of resistant enterococci associated with TYL administration, termed the TYL effect. The model predicts withdrawing TYL treatment and moving cattle to an antimicrobial-free terminal pen with a low prevalence of resistant environmental enterococci for as few as 6 days could reduce the TYL effect by up to 14 percentage points. Additional investigation of the importance of this subset of cattle to the overall risk of resistance transmission from feedlots will aid in the interpretation and implementation of resistance mitigation strategies.

Characterizing infectious disease progression through discrete states using hidden Markov models.

Infectious disease management relies on accurate characterization of disease progression so that transmission can be prevented. Slowly progressing infectious diseases can be difficult to characterize because of a latency period between the time an individual is infected and when they show clinical signs of disease. The introduction of Mycobacterium avium ssp. paratuberculosis (MAP), the cause of Johne's disease, onto a dairy farm could be undetected by farmers for years before any animal shows clinical signs of disease. In this time period infected animals may shed thousands of colony forming units. Parameterizing trajectories through disease states from infection to clinical disease can help farmers to develop control programs based on targeting individual disease state, potentially reducing both transmission and production losses due to disease. We suspect that there are two distinct progression pathways; one where animals progress to a high-shedding disease state, and another where animals maintain a low-level of shedding without clinical disease. We fit continuous-time hidden Markov models to multi-year longitudinal fecal sampling data from three US dairy farms, and estimated model parameters using a modified Baum-Welch expectation maximization algorithm. Using posterior decoding, we observed two distinct shedding patterns: cows that had observations associated with a high-shedding disease state, and cows that did not. This model framework can be employed prospectively to determine which cows are likely to progress to clinical disease and may be applied to characterize disease progression of other slowly progressing infectious diseases.

Corrigendum: Shared Multidrug Resistance Patterns in Chicken-Associated Escherichia coli Identified by Association Rule Mining.

[This corrects the article DOI: 10.3389/fmicb.2019.00687.].

The effect of tylosin on antimicrobial resistance in beef cattle enteric bacteria: A systematic review and meta-analysis.

BACKGROUND: Tylosin is a commonly used in-feed antimicrobial and is approved in several countries to reduce the incidence of liver abscesses in beef cattle. Macrolides are critically important antimicrobials in human health and used to treat some foodborne bacterial diseases, such as Campylobacter jejuni and Salmonella. Feeding tylosin could select for resistant enteric bacteria in cattle, which could contaminate beef products at slaughter and potentially cause foodborne illness. We conducted a systematic review and meta-analysis to evaluate the impact of feeding tylosin to cattle on phenotypic and genotypic resistance in several potential zoonotic enteric bacteria: Enterococcus species, Escherichia coli, Salmonella enterica subspecies enterica, and Campylobacter species. This review was registered with PROSPERO (#CRD42018085949). RESULTS: Eleven databases were searched for primary research studies that fed tylosin at approved doses to feedlot cattle and tested bacteria of interest for phenotypic or genotypic resistance. We screened 1,626 citations and identified 13 studies that met the inclusion criteria. Enterococcus species were tested in seven studies, Escherichia coli was isolated in five studies, three studies reported on Salmonella, and two studies reported on Campylobacter species. Most studies relied on phenotypic antimicrobial susceptibility testing and seven also reported resistance gene testing. A random-effects meta-analyses of erythromycin-resistant enterococci from four studies had significant residual heterogeneity. Only two studies were available for a meta-analysis of tylosin-resistant enterococci. A semi-quantitative analysis demonstrated an increase in macrolide-resistant enterococci after long durations of tylosin administration (>100 days). Semi-quantitative analyses of other bacteria-antimicrobial combinations revealed mixed results, but many comparisons found no effect of tylosin administration. However, about half of these no-effect comparisons did not record the cumulative days of tylosin administration or the time since the last dose. CONCLUSIONS: When fed at approved dosages for typical durations, tylosin increases the proportion of macrolide-resistant enterococci in the cattle gastrointestinal tract, which could pose a zoonotic risk to human beef consumers. Feeding tylosin for short durations may mitigate the impact on macrolide-resistant enterococci and further studies are encouraged to determine the effect of minimizing or eliminating tylosin use in beef cattle. There may also be an impact on other bacteria and other antimicrobial resistances but additional details or data are needed to strengthen these comparisons. We encourage authors of antimicrobial-resistance studies to follow reporting guidelines and publish details of all comparisons to strengthen future meta-analyses.

Identification of Sero-Diagnostic Antigens for the Early Diagnosis of Johne's Disease using MAP Protein Microarrays.

Considerable effort has been directed toward controlling Johne's disease (JD), a chronic granulomatous intestinal inflammatory disease caused by Mycobacterium avium subsp. paratuberculosis (MAP) in cattle and other ruminants. However, progress in controlling the spread of MAP infection has been impeded by the lack of reliable diagnostic tests that can identify animals early in the infection process and help break the transmission chain. To identify reliable antigens for early diagnosis of MAP infection, we constructed a MAP protein array with 868 purified recombinant MAP proteins, and screened a total of 180 well-characterized serum samples from cows assigned to 4 groups based on previous serological and fecal test results: negative low exposure (NL, n = 30); negative high exposure (NH, n = 30); fecal-positive, ELISA-negative (F + E-, n = 60); and both fecal- and ELISA-positive (F + E+, n = 60). The analyses identified a total of 49 candidate antigens in the NH, F + E-, and F + E+ with reactivity compared with the NL group (p < 0.01), a majority of which have not been previously identified. While some of the antigens were identified as reactive in only one of the groups, others showed reactivity in multiple groups, including NH (n = 28), F + E- (n = 26), and F + E+ (n = 17) groups. Using combinations of top reactive antigens in each group, the results reveal sensitivities of 60.0%, 73.3%, and 81.7% in the NH, F + E-, and F + E+, respectively at 90% specificity, suggesting that early detection of infection in animals may be possible and enable better opportunities to reduce within herd transmission that may be otherwise missed by traditional serological assays that are biased towards more heavily infected animals. Together, the results suggest that several of the novel candidate antigens identified in this study, particularly those that were reactive in the NH and F + E- groups, have potential utility for the early sero-diagnosis of MAP infection.

Mastitis risk effect on the economic consequences of paratuberculosis control in dairy cattle: A stochastic modeling study.

The benefits and efficacy of control programs for herds infected with Mycobacterium avium subsp. paratuberculosis (MAP) have been investigated under various contexts. However, most previous research investigated paratuberculosis control programs in isolation, without modeling the potential association with other dairy diseases. This paper evaluated the benefits of MAP control programs when the herd is also affected by mastitis, a common disease causing the largest losses in dairy production. The effect of typically suggested MAP controls were estimated under the assumption that MAP infection increased the rate of clinical mastitis. We evaluated one hundred twenty three control strategies comprising various combinations of testing, culling, and hygiene, and found that the association of paratuberculosis with mastitis alters the ranking of specific MAP control programs, but only slightly alters the cost-benefit difference of particular MAP control components, as measured by the distribution of net present value of a representative U.S. dairy operation. In particular, although testing and culling for MAP resulted in a reduction in MAP incidence, that control led to lower net present value (NPV) per cow. When testing was used, ELISA was more economically beneficial than alternative testing regimes, especially if mastitis was explicitly modeled as more likely in MAP-infected animals, but ELISA testing was only significantly associated with higher NPV if mastitis was not included in the model at all. Additional hygiene was associated with a lower NPV per cow, although it lowered MAP prevalence. Overall, the addition of an increased risk of mastitis in MAP-infected animals did not change model recommendations as much as failing to consider.

Estimation of multidrug resistance variability in the National Antimicrobial Monitoring System.

Multidrug resistance is a serious problem raising the specter of infections for which there is no treatment. One of the most important tools in combating multidrug resistance is large scale monitoring programs, because they track resistance over large geographic areas and time scales. This large scope, however, can also introduce variability into the data. The primary monitoring program in the United States is the National Antimicrobial Resistance Monitoring System (NARMS). This study examines the variability of a previously identified resistance pattern in Escherichia coli among ampicillin, gentamicin, sulfisoxazole, and tetracycline using samples isolated from chicken during the years 2004 to 2006 and 2008 to 2012. 2007 is excluded because sulfisozaxole resistance was not measured at slaughter that year. To assess variability in this resistance pattern susceptibility/resistance contingency tables were constructed for each of the 15 combinations of the 4 drugs for each of the years. For each table, variability across the years was assessed at the full table multinomial level as a measure of general variability of the resistance pattern and at the level of the highest order interaction term in a log-linear model of the table as a measure of variability in that particular component of the resistance pattern. A power analysis using the traditional asymptotic normal approximation and one using a Dirichlet-multinomial simulation were carried out to determine the effect of variation on ability to detect nonzero highest order loglinear model terms and the validity of the normal approximation in carrying out such tests. All tables exhibit overdispersion at the multinomial level and in their highest order model parameters. The normal approximation performs well for large sample sizes, low levels of dispersion, and small log-linear model parameters. The approximation breaks down as dispersion or the log linear model parameter grows or sample size shrinks. Taken together these analyses indicate that the level of variability in the NARMS dataset makes it difficult to detect multidrug resistance patterns at the current level of sample collection. In order to better control this dispersion NARMS could collect more variables on each of the samples.