- Open Access
Antimicrobial usage and resistance in beef production
Journal of Animal Science and Biotechnology volume 7, Article number: 68 (2016)
Antimicrobials are critical to contemporary high-intensity beef production. Many different antimicrobials are approved for beef cattle, and are used judiciously for animal welfare, and controversially, to promote growth and feed efficiency. Antimicrobial administration provides a powerful selective pressure that acts on the microbial community, selecting for resistance gene determinants and antimicrobial-resistant bacteria resident in the bovine flora. The bovine microbiota includes many harmless bacteria, but also opportunistic pathogens that may acquire and propagate resistance genes within the microbial community via horizontal gene transfer. Antimicrobial-resistant bovine pathogens can also complicate the prevention and treatment of infectious diseases in beef feedlots, threatening the efficiency of the beef production system. Likewise, the transmission of antimicrobial resistance genes to bovine-associated human pathogens is a potential public health concern. This review outlines current antimicrobial use practices pertaining to beef production, and explores the frequency of antimicrobial resistance in major bovine pathogens. The effect of antimicrobials on the composition of the bovine microbiota is examined, as are the effects on the beef production resistome. Antimicrobial resistance is further explored within the context of the wider beef production continuum, with emphasis on antimicrobial resistance genes in the food chain, and risk to the human population.
The emergence of antimicrobial resistance in bacterial pathogens is a serious global issue. Antimicrobial use in livestock, aquaculture, pets, crops, and humans selects for antimicrobial-resistant (AMR) bacteria that reside in agricultural and clinical biomes. Besides pathogens, AMR bacteria include many harmless and beneficial microbes acting as a genetic reservoir of AMR gene determinants (‘the resistome’ [1, 2]), which can be transferred via mechanisms of horizontal gene transfer (HGT) (reviewed in ) throughout the microbial community. With alarming frequency, untreatable human and animal pathogens with multiple AMR determinants arise. AMR in pathogens is commonly accepted as a result of widespread use and abuse of antimicrobials in agriculture and medicine. Although the use of antimicrobials in livestock and aquaculture has attracted particular attention, antimicrobials are also widely used in companion animals and in plant agriculture (e.g. oxytetracycline and streptomycin), for feed crops, and for tomatoes, citrus, and many other fruits . Here, the focus is on large-scale beef production, where antimicrobials are routinely used to support animal welfare, and controversially, to promote growth and production efficiency. In this review, the usage of antimicrobials in cattle will be summarized along with recent studies on AMR explored within the context of the beef production system.
Worldwide, beef production is the third largest meat industry (~65 million t globally), behind swine and poultry . In 2015, the major beef producing countries included the United States (US) (11.4 million t), Brazil (9.6 million t), the 28 member countries of the European Union (EU) (7.5 million t), China (6.7 million t), and India (4.5 million t) (Fig. 1a)  with the global beef cattle population exceeding 1 billion . Beef production is complex and involves multiple stages, wherein calves are birthed, raised and fed for slaughter, and processed for meat. The raising of cattle in high-throughput production typically involves the movement of animals from (I) cow-calf systems (a permanent herd used to produce young beef cattle), to (II) backgrounding (post-weaning intermediate feeding, typically forage-based diets), and (III) feedlot/finishing operations (concentrated animal feeding, typically with high-energy grain-based diets). After finishing, animals are transported to a slaughterhouse and processed. Antimicrobials may be given to live cattle at any production stage for therapeutic and non-therapeutic purposes.
Antimicrobial usage in beef production
Rationale for antimicrobial use
Antimicrobials are used in beef cattle for the therapeutic treatment of infections caused by bacteria or other microbes. Cattle can be afflicted by a variety of endemic infectious diseases, which may exist ubiquitously in the ranching environment . Endemic pathogens often go unnoticed, but compromise animal health—affecting herd growth performance and farm profitability. Infections spread rapidly in high-density feedlots, and despite herd management procedures, both endemic and exotic diseases can be introduced by importation of diseased animals into the beef production system. Globally, 4.7 million cattle are exported to beef producing countries, with the top exporters being Mexico, Australia, and Canada, exporting >1.3, >1.2, and >1.0 million cattle, respectively. These cattle are sent primarily to the US, which received >2.2 million cattle in 2015 . The risk of disease transmission creates significant economic pressure for antimicrobial usage to prevent infectious bovine diseases.
Therapeutic and non-therapeutic use of antimicrobials
Antimicrobial use in cattle is unavoidable for the treatment of infections for which vaccines, bacterins, or alternate therapies are not available. A prevalent, controversial practice involves antimicrobials used in non-therapeutic applications. Judicious antimicrobial use typically requires that diseased cattle are treated individually to maximize therapeutic efficacy and reduce the spread of AMR, but entire herds are often dosed with in-feed antimicrobials. This is the typical administration route for practices such as (I) prophylaxis, (II) metaphylaxis, and (III) growth promotion. These practices are described by inconsistent and often agenda-driven terminology. For example, prophylaxis and metaphylaxis are considered therapeutic uses by the American Veterinary Medical Association and the US Food and Drug Administration (FDA) [8, 9], but others consider such practices ‘sub-therapeutic’, ‘non-therapeutic’, or ‘production usage’. More recently, the FDA uses ‘production purposes’ to refer to antimicrobial usage with the intent of growth and feed efficiency enhancement . Prophylaxis is action taken to prevent disease and involves the administration of antimicrobials to an individual that is perceived to be at risk of developing disease. Metaphylaxis refers to the treatment of a larger cohort or entire herd to provide: (I) therapy to infected animals, and (II) prophylaxis to uninfected or potentially susceptible animals. Metaphylaxis is often applied to herds receiving new animals. Growth promotion refers to the use of antimicrobial growth promoters (AGPs) for extended duration to improve feed efficiency (the ratio of feed consumed vs. animal weight gain). ‘Sub-therapeutic’ typically refers to low-dose concentrations of antimicrobials in feeds over an extended duration. The FDA Centre for Veterinary Medicine defines sub-therapeutic as amounts <200 g per ton (US) of feed for 12 wk .
Complexity of production usage of antimicrobials
Although prophylaxis/metaphylaxis may be a more judicious use of antimicrobials than growth promotion, growth promotion is often a benefit of either treatment. For example, antimicrobial treatment and prevention of cattle liver abscesses simultaneously provides prophylactic/metaphylactic therapy and growth promotion. Liver abscesses occur frequently in cattle, and are common in feedlots, where high-energy grain-based diets can cause acidosis, leading to ruminal lesions that predispose cattle to hepatic disease caused by invasive bacteria . Cattle with liver abscesses have reduced production efficiency (reduced feed intake and weight gain) . Thus, feedlot cattle receiving antimicrobials for liver abscess control can also indirectly exhibit growth promotion as a result of disease prevention. Some antimicrobials are approved for both growth promotion and therapeutic applications [13, 14]. Some countries, particularly in the EU, have banned the use of AGPs in beef and other meat production industries (the EU ban was implemented in 2006 ). In 2012, the US introduced a voluntary ‘ban’ on AGPs, and a similar program is expected in Canada . While such policies are laudable, their effectiveness is questionable. For example, the volume of agricultural antimicrobials used within the EU has not decreased, and the EU ban may also have resulted in compensatory increases in the usage of antimicrobials with even greater relevance to human health . Regardless, bacterial resistance acquired in response to any antimicrobial usage could compromise future efficacy, especially in the case of AMR genes that are genetically linked in clusters, as is often the case in multi-drug resistant (MDR) organisms.
Global veterinary antimicrobial usage
Antimicrobial usage data is scarce: most countries do not survey or collect usage data, and cattle producers and pharmaceutical companies have little incentive to report such information. Where usage data exists, typically in high-income countries, it takes the form of volume sales data rather than actual usage. The caveat of antimicrobial sales and distribution data is that it does not accurately indicate how or if antimicrobials were used. In a global analysis of antimicrobial usage, Van Boeckel et al.  estimated the worldwide consumption of antimicrobials in food animal production at ≥57,000 t (1 t = 1,000 kg) and projected a 67% increase in total usage by 2030 to ≥95,000 t. Total food-animal antimicrobial sales in the US was reported to be approximately 9,475 t (2014) , 8,122 t in the EU (2013) , 1,127 t in Canada (2012) , 644 t in Australia (2010) , and 429 t in the United Kingdom (UK) (2014)  (Fig. 1b; excludes ionophores sales). Based on these sales data, and estimations of food animal populations, Van Boeckel et al. projected that the top countries consuming antimicrobials in livestock production are China, the US, India, Brazil and Germany, with China accounting for 23% of global consumption .
Data for antimicrobial usage by animal type is not routinely available, such that the proportion and type of antimicrobials sold exclusively for use in cattle is largely unknown or estimated. Some information can be gleaned from country data where specific antimicrobial formulations with indicated routes of administration (e.g. in-feed, injection etc.) are provided for specific livestock (Fig. 1c). However, this data is largely unreliable because (I) most antimicrobials are approved for use in multiple food-animal species, (II) off-label non-intended usage of antimicrobials is a common practice worldwide, and (III) the antimicrobial may not have actually been administered to the animal. Data on therapeutic vs. non-therapeutic use is not collected, and difficult to estimate. Without reliable antimicrobial usage data to link to AMR, it is challenging to create scientific policies to optimize veterinary antimicrobials. Thus, judicious use policies in some countries are the subject of debate, with critics decrying heavy-handed bans and regulations, and proponents criticizing ineffective and optional compliance schemes.
One method to improve antimicrobial usage estimate by species is to take into account (I) the size of the animal population (demographics), and (II) the average theoretical weight of the animal species at time of treatment (physiology). This is the population correction unit (PCU), and is used in the UK Veterinary Medicines Directorate UK-VARSS report , the EU European Medicines Agency ESVAC report , and the Public Health Agency of Canada’s CIPARS report . Briefly, 1 PCU = 1 kg of livestock, such that the amount of antimicrobials sold can be normalized by species weight, allowing for a comparative indication of overall usage between species (Fig. 1d). Van Boeckel et al. used PCU values to estimate global consumption of antimicrobials per kg of animal produced at 45 mg/PCU (= mg/kg) for cattle, 148 mg/PCU for chickens, and 172 mg/PCU for pigs . This trend is consistent with UK-VARSS data, in which cattle consumed 8 mg / PCU of antimicrobials compared to 172 mg / PCU for swine and poultry . This approach gives an appreciation for the overall use of antimicrobials within a livestock species, but does not indicate usage within the various segments of the production system. These are limitations of using antimicrobial sales and distribution data as a proxy for actual usage data .
In some countries, the majority of antimicrobials manufactured or sold are used in food animals rather than in human medicine (e.g. US: ~10,670 t active ingredient for food animals (2014) vs. ~3,290 t for humans (2012) [19, 25]; EU: ~7,982 t active ingredient for food animals vs. ~3,399 t (2012)  (food animal values exclude ionophores and other non-medically important antimicrobials)). However, direct human-animal antimicrobial use comparisons are limited by differences in estimation and measurement methodology (e.g. antimicrobials sold vs. prescribed), differences in animal physiology and antimicrobial use practices, and are further complicated by the inclusion/exclusion of antimicrobials irrelevant to human medicine (e.g. ionophores). Thus, food animal vs. human antimicrobial consumption comparisons must be interpreted with caution. Since food animals outnumber/outweigh the human population, volume usage is less surprising than the concurrent use of antimicrobials essential for human medicine. The FDA reports that medically important antimicrobials accounted for 62% of sales of all antimicrobials approved for use in food-producing animals , with 74% of clinically relevant antimicrobials administered in-feed . Of the 38% of antimicrobials sold that were not medically important, 80% were ionophores (e.g. monensin). Ionophores are not used in human medicine, have no human counterpart, and do not appear to promote AMR. However, ionophores are important for animal welfare, and are administered for production and therapeutic indications for the treatment/prevention of coccidiosis, a disease associated with Eimeria spp. infestations . In the EU, ionophores are defined as anticoccidials/coccidiostats, and are not reported as antimicrobials [20, 23]. Besides the ionophores and another class of AGPs called flavophospholipols, most veterinary antimicrobials are identical or structurally similar to antimicrobials used in human medicine. Stringent EU policies regulate the use of in-feed antimicrobials, and penicillins sales are proportionally high-from a low of 11.9% in France to as high as 61.3% in Sweden of all veterinary antimicrobials sold . Sweden was the first country to ban AGPs in 1986 , a policy that likely contributed to high therapeutic use of penicillins. Resistance to an agricultural antimicrobial may confer resistance to the human drug, many of which are considered to be essential medicines by the World Health Organization (WHO) . Significant veterinary antimicrobials generally include tetracyclines, penicillin (penam) and other β-lactams, macrolides, sulfonamides, and aminoglycosides (Fig. 1e). Other antimicrobials represent a miniscule fraction of veterinary antimicrobials sold and distributed (each <2%), but they are not unimportant. Thus, cephalosporins, lincosamides, phenicols, and fluoroquinolones (among others) include some of the most effective antimicrobials in veterinary and clinical medicine.
Antimicrobial resistance in bovine pathogens
Much focus on AMR in food animals concerns the hazards for human health, but AMR is also a veterinary problem. Knowledge about resistance in exclusively bovine pathogens is also exceptionally poor compared to that of bovine zoonotic enteric pathogens, such as Campylobacter, Salmonella, E. coli and Enterococcus spp. These species are typically used as ‘indicators’ of AMR in production animals as they (I) are of importance in human disease, (II) are relatively easy to culture, (III) can be isolated from healthy animals, and (IV) have established AMR minimum inhibitory concentration (MIC) breakpoints (for human infections). To reiterate, for several of the bacterial species discussed below, the designation of “resistant” or “sensitive” is often author-determined because clear criteria have not been established by relevant standardization bodies, such as the Clinical Laboratory Standards Institute (CLSI), and the European Committee on Antimicrobial Susceptibility Testing (EUCAST). Surveillance programs monitoring AMR in beef production are typically constrained to human enteropathogens and sentinel AMR indicator species, but independent research from many countries gives rough estimates of AMR in cattle pathogens. Several recent studies have found strong correlations between the level of use of specific antimicrobials and the level of resistance observed [28, 29].
Scientific literature pertaining to AMR in pathogens of significance to beef production was reviewed, and the median percent resistance of 16 different pathogens to antimicrobials was collected from 58 scientific reports ([30–88]; 2000-present), shown in Fig. 2 (see Methods for details). Reports were selected if they contained an antibiogram of isolates without prior antimicrobial selection, and in most cases, if the isolates were obtained from diseased animals. In general, differing levels of tetracycline resistance were present in most cattle-associated bacteria. Macrolide resistance was often reported in BRD pathogens, and in liver abscess pathogens. For almost every species there was a report of resistance to at least one antimicrobial from each major antimicrobial class. A caveat of many of the studies selected is that MIC resistance/sensitivity breakpoint criteria have not been defined for many cattle pathogens, as well as some antimicrobials (e.g. streptomycin). Complicating a general view of resistance across multiple species are the following caveats: (I) some studies do not test the same antimicrobials as others, (II) for some species, reports are very scarce, (III) some studies test relatively few isolates for resistance, (IV) in some cases, designation of resistance is defined by the author and not via standardized interpretive criteria, and (V) the median value of percent of resistance is biased towards values for which there are fewer comparative data points. Thus, the data presented in Fig. 2 should be viewed with caution.
Antimicrobial resistance in bovine respiratory pathogens
Bovine Respiratory Disease (BRD) is the most frequent and economically important of the primary cattle diseases . Approximately 15% of cattle in North America are treated for BRD, which accounts for ~70% of cattle morbidity, and ~40% of all mortality in feedlots . BRD control is thus a major target of antimicrobial usage [90, 91], and possibly an important source of AMR pathogens. BRD involves a complex of etiological agents including Mannheimia haemolytica, the predominant agent , Pasteurella multocida, and Histophilus somni [92, 93]. H. somni occurs sporadically, and can cause fatal septicemia in cattle. Mycoplasma bovis is also frequently associated with BRD . These ubiquitous pathogens are often described as commensals because colonization is asymptomatic in most healthy animals. As opportunistic pathogens, respiratory disease may develop with detrimental changes to the immune status of the host animal as a result of stress (e.g. transportation, weaning) or viral infections (e.g. Bovine Herpes Virus-1, Bovine Respiratory Syncytial Virus) . Typing of M. haemolytica isolates obtained from fatal pneumonia cases in calves show substantial diversity , suggesting that outbreaks of BRD are not due to the herd-wide transmission of a single virulent strain, but originate from formerly commensal strains [95, 96]. In North America and many countries, macrolides are often given as BRD metaphylaxis to asymptomatic animals in the presence of diseased animals. Individual cattle symptomatic for BRD may also be treated with a wide range of antimicrobials, with the fluoroquinolone marbofloxacin used in this manner . Clinical symptoms may only become apparent after pulmonary damage has occurred. Consequently, metaphylactic control of BRD often improves the welfare of cattle as well as financial returns through cost savings achieved by reduction in morbidity and mortality .
In calves experimentally infected with M. haemolytica (4 × 107 CFU), Lhermie et al.  demonstrated that low-dose (2 mg/kg) marbofloxacin 12 h after inoculation eliminated this pathogen from all calves, but at 45 h post-inoculation a high-dose (10 mg/kg) failed to do so. Since M. haemolytica persisted after this high-dose, a higher risk for AMR development may have been created by a practice thought to be more judicious than mass medication . Thus, although metaphylactic approaches may expose more bacteria to antimicrobial selection, they may also reduce pathology, and eliminate pathogens more effectively than single-dose therapeutic approaches. In another study, continuous sub-therapeutic administration of the macrolide tylosin (Tylan, Elanco; 11 mg/kg in-feed) had no effect in reducing carriage of M. haemolytica in beef cattle, compared to substantial reductions after therapy with a single subcutaneous injection of tilmicosin (Micotil, Elanco; 10 mg/kg) or tulathromycin (Draxxin, Pfizer; 2.5 mg/kg) . Antimicrobial usage in single animals has been shown to increase the risk of isolating both susceptible and MDR M. haemolytica from pen mates, highlighting the importance of bacterial transmission in the dissemination of AMR . Furthermore, Klima et al.  found that MDR occurred more frequently in diseased than healthy cattle (37% vs. 2%) in M. haemolytica collected from healthy cattle vs. cattle with clinical BRD. In that study, tetracycline resistance (18%) was the most prevalent resistance phenotype . Resistant M. haemolytica and P. multocida can also be recovered from diseased antimicrobial non-treated cattle. Via the pan-European VetPath susceptibility monitoring program, de Jong et al.  analyzed isolates collected between 2002 and 2006 from diseased cattle with no antimicrobial exposure for at least 15 d prior to sampling, and found that 14.6% of M. haemolytica (231 total isolates) were resistant to tetracycline, and 5.7, 3.5 and 0.4% of P. multocida (138 total isolates) were resistant to tetracycline, spectinomycin, and florfenicol, respectively .
MDR has also been reported in BRD agents. Lubbers et al.  evaluated records from 2009 to 2011 from the Kansas State Diagnostic Laboratory for co-resistance in M. haemolytica to 6 antimicrobial classes including ceftiofur, danofloxacin and enrofloxacin, florfenicol, oxytetracycline, spectinomycin, tilmicosin and tulathromycin. They found that in 2009, ~5% of isolates were resistant to 5 or more antimicrobials as compared to ~35% in 2011 . M. haemolytica isolates resistant to oxytetracycline were 3.5-fold more likely to be resistant to 1 or more antimicrobials, compared to non-oxytetracycline-resistant isolates . MDR has been detected in P. multocida and H. somni. Klima et al.  isolated M. haemolytica, P. multocida and H. somni from BRD mortalities, and determined that 72% of M. haemolytica and 50% of P. multocida isolates exhibited AMR. Surprisingly, 30% of M. haemolytica and 12.5% of P. multocida were resistant to >7 antimicrobial classes, including aminoglycosides, penicillins, fluoroquinolones, lincosamides, macrolides, pleuromutilins, and tetracyclines . The MDR isolates originated from feedlots in Texas or Nebraska. MDR was found in multiple M. haemolytica populations, suggesting that a clonal population was not responsible for this observation . MDR was due to a tandem array of AMR genes concentrated within an Integrative and Conjugable Element (ICE), a mobile genetic element (MGE) . These elements constitute a diverse group of MGEs found in both Gram-positive and -negative bacteria, and are notable for encoding the conjugation machinery required for mobilisation of ICE to other bacteria, where they often integrate into multi-copy genes such as tRNAs and rRNAs. ICEs also frequently encode virulence factors, heavy metal transporters, and toxin-antitoxin systems, thought to ensure the stability of chromosomally-inserted ICE within cells.
A putative ICE, designated ICEMh1, was recently detected in M. haemolytica strain 42548 by Eidam et al. that carried resistance to aminoglycosides (aphA-1, strA, strB genes), tetracyclines (tet(H) gene), and sulfonamides (sul2 gene) [103, 104]. ICEMh1 has a size of 92 ,345 bp, harbors ~107 genes, and shares a high degree of similarity with ICEPmu1, an ~82 kb element identified in P. multocida that encodes ~88 genes . The structure of ICEPmu1 is depicted in Fig. 3a. ICEPmu1 integrates into a chromosomal copy of tRNALeu . Eleven resistance genes are encoded within two gene clusters, conferring resistance to tetracyclines (tetR-tet(H) genes), streptomycin (strA and strB), streptomycin/spectinomycin (aadA25), gentamicin (aadB), kanamycin/neomycin (aphA1), phenicols (floR), sulfonamides (sul2), macrolides/lincosamides (erm(42) gene) or tilmicosin/tulathromycin (msr(E)-mph(E) genes) [92, 105]. ICEPmu1 was shown to conjugatively transfer in vivo into recipient P. multocida, M. haemolytica and E. coli at frequencies of 1.4 × 10−4, 1.0 × 10−5 and 2.9 × 10−6 respectively . E. coli transconjugants demonstrated up to 64-fold higher MIC values for florfenicol, suggesting better functional activity of FloR in E. coli . A β-lactam oxacillinase (bla OXA-2) was also present, and conferred greater ampicillin resistance in E. coli harboring ICEPmu1 . As many of the ICEPmu1 resistance genes may not be indigenous to Pasteurellaceae, acquisition of AMR determinants from Enterobacteriaceae is likely . ICEPmu1 and ICEMh1 were isolated from feedlot BRD cases in Nebraska in 2005 and Pennsylvania in 2007, respectively [104, 105]. There is currently little information on the prevalence of these or similar ICE elements in herds, but the presence of AMR-ICEs in BRD agents represents a critical risk for the efficacy of future antimicrobial therapy. Simultaneous and rapid acquisition of multiple resistance genes via a single HGT event could severely limit therapeutic options.
Besides HGT via MGEs, AMR determinants arise spontaneously via mutation. In some isolates of M. haemolytica and P. multocida, high-level (MIC ≥ 64 mg/L) macrolide resistance has been attributed to mutations in the multicopy 23S rRNA genes (e.g. M. haemolytica A2058G; P. multocida A2059G) . Resistance to macrolides, lincosamides and other ribosome-targeting antibiotics has been shown to be conferred by monomethylation of the M. haemolytica and P. multocida 23S rRNAs at position A2058 . Methylation is catalyzed by a novel monomethyltransferase, designated erm(42), which appears to have been disseminated among the Pasterellaceae . Plasmid borne transfer of AMR genes may also be significant among BRD bacteria. In the first report of a floR florfenicol resistance gene in M. haemolytica, Katsuda et al.  identified pMH1405, a 7.7 kb florfenicol resistance plasmid, which appears to be remarkably similar to plasmids from P. multocida (pCCK381; 10.8 kb) and Dichelobacter nodosus (pDN1; 5.1 kb). Collectively, these findings reveal the importance and diversity of AMR and HGT mechanisms in BRD pathogens.
Antimicrobial resistance in liver abscess pathogens
Liver abscesses in beef cattle result from aggressive grain-feeding, and represent an economic liability. Liver abscess incidence in North American feedlot cattle ranges from 12 to 32% . Fusobacterium necrophorum, an anaerobic rumen bacterium, is the major etiological agent isolated from condemned livers, followed closely by Trueperella pyogenes . Hepatic disease is detected after slaughter since cattle with abscesses are usually asymptomatic. Liver perforation that leads to systemic infection is rare. In-feed antimicrobials, such as the FDA-approved tylosin, chlortetracycline, oxytetracycline, bacitracin, and the streptogramin, virginiamycin, are approved for liver abscess prevention in many countries. In a study of ~7,000 feedlot cattle, tylosin reduced the incidence of liver abscesses by up to 70%, and increased weight gain by 2.3% [12, 109]. Although a common rumen inhabitant, F. necrophorum is an opportunistic pathogen also associated with calf diphtheria and foot rot . In a 2-year comparison of flora isolated from liver abscesses in cattle fed with or without tylosin, Nagaraja et al.  found that the incidence of T. pyogenes in mixed culture with F. necrophorum was higher in abscesses from tylosin-fed cattle (53% vs. 10% in the non-tylosin fed cattle). In contrast, the incidence of F. necrophorum was higher in cattle that were not fed tylosin (61%), as compared to those that were (33%). No differences in tylosin susceptibility between isolates from antimicrobial-free or tylosin-exposed cattle were identified . AMR in Fusobacterium spp. isolated from humans is also relatively rare [112, 113], suggesting that AMR in this genera is yet to present a major risk to beef production or human medicine. AMR in bovine T. pyogenes is of greater concern, due to the versatility of the bacterium as a cause of liver, skin, joint, and visceral abscesses, and roles in mastitis and abortion . Tylosin resistance has been documented and linked to the presence of erm(X) or an erm(B) gene similar to that found on the Enterococcus faecalis MDR plasmid pRE25 [115, 116]. This suggests AMR transfer occurs between these human and cattle pathogens. Jost et al.  examined 48 T. pyogenes isolates, of which 27 were derived from cattle, and identified erm(X) as the most prevalent tylosin resistance determinant. An erm(X) tylosin and tetracycline tet(33) resistance plasmid, pAP2, was also identified . Other studies have found high prevalence of tetracycline and sulfonamide resistance, and suggest that AMR in T. pyogenes may of greater significance in bovine mastitis as compared to liver abscesses [117, 118].
Antimicrobial resistance in keratoconjunctivitis pathogens
Infectious bovine keratoconjunctivitis is a painful ocular disease caused primarily by non-self-limiting infections with Moraxella bovis and bovoculi. The disease is common worldwide in cattle, transmitted by flies, and if untreated, may result in ulceration and cornea rupture. In the US, only oxytetracycline and tulathromyin are approved for the treatment of bovine keratoconjunctivitis, although penicillin may be used in other countries. In a study of 32 Moraxella spp. isolated from cattle and sheep, Maboni et al.  found that 40% of isolates were penicillin-resistant and 20% were tetracycline-resistant, but most were susceptible to other antimicrobials. Dickey et al.  published the genome sequence for an AMR isolate of Moraxella bovoculi, Mb58069. It was found to be resistant to florfenicol, oxytetracycline, sulfonamides, and displayed intermediate resistance to macrolides. Ten AMR determinants were co-located on a >27 kb genomic island . The biofilm-forming capabilities of Moraxella bovis may also enhance antimicrobial resistance. Prieto et al.  found that Moraxella bovis readily forms biofilms, increasing resistance to ampicillin, chloramphenicol, gentamicin, and oxtetracycline by 256-, 1,024-, 512-, and 1,024-fold as compared to when this bacterium grows planktonically  Thus, antimicrobial susceptibility via standard disk diffusion and microtiter MIC determinations failed to reflect the true level of resistance of this isolate.
Antimicrobial resistance in notifiable/reportable bovine bacterial pathogens
Many countries maintain registries of notifiable diseases associated with zoonotic, unvaccinable, highly infectious, economy-damaging, or largely untreatable pathogens. For cattle, notifiable diseases include (I) abortive agents: Brucella abortus (Brucellosis), Coxiella burnetti (Q fever), and Leptospira spp. (Leptospirosus); (II) bovine pneumonia agents: Mycoplasma mycoides subsp. mycoides small colony type (Contagious bovine pleuropneumonia), and Mycobacterium bovis (Bovine tuberculosis); and (III) enteritis agents: Mycobacterium avium subsp. paratuberculosis (Johne’s disease), and Bacillus anthracis (Anthrax) . Although it might be assumed that AMR would be a major issue in these pathogens, for the most part AMR has not been studied in these pathogens or is rare. Besides the rarity of cases, other reasons for this include: (I) the notifiable pathogen is already intrinsically resistant to many antimicrobials (e.g. Mycobacterium spp.); (II) the pathogen resides in an antimicrobial-exclusive intracellular niche that renders antimicrobial therapy impractical (e.g. Brucella abortus and Coxiella burnetti); or (III) a secreted toxin causes pathology (e.g. Bacillus anthracis). Control of outbreaks of these diseases rarely involves antimicrobial therapy and relies on animal segregation, herd control, or depopulation .
AMR susceptibility tests of human clinical isolates of Mycobacterium bovis have been performed because of the role of M. bovis in human tuberculosis (TB). Although it can infect many species, the main reservoir of M. bovis is cattle, and transmission to humans is primarily via contact with infected animals and drinking unpasteurized milk . In clinical isolates of M. tuberculosis and M. bovis collected over 15 yr, Bobadilla-del Valle et al.  found that 16.6% of isolates from human TB cases were M. bovis. Susceptibility testing to first-line anti-TB drugs revealed that 10.9% of M. bovis were streptomycin-resistant, and 7.6% were MDR (isoniazid- and rifampin-resistant). The aminoglycoside streptomycin is approved for use in cattle against aerobic Gram-negatives such as enteritis-causing E. coli and Salmonella spp. . Bovine-human transmission of AMR M. bovis appears to be rare in developed countries, but may occur more frequently in developing countries [124, 126].
Antmicrobial resistance in zoonotic human enteropathogens
Antimicrobial resistance in bovine-origin Escherichia coli
Cattle are E. coli reservoirs, with most strains harmless commensals. Some E. coli, particularly invasive and enterohemorrhagic E. coli (EHEC) cause septicemia in neonatal calves, but are primarily pathogenic to humans. E. coli strains from bovines and other food production animals serve as indicators of AMR prevalence in Gram-negative bacterial populations, thus sentinel ‘generic’ E. coli help establish and track the persistence of AMR genes in environments affected by beef production and other human activities. For example, in a recent survey of AMR in E. coli from Nebraska cattle feedlot runoff catchment ponds and the effluent of municipal wastewater treatment plants, Agga et al.  found that the diversity of AMR genes in human-associated samples was greater than from environments impacted by cattle. Interestingly, E. coli resistant to 3rd generation cephalosporins and trimethoprim/sulfamethoxazole were found at equivalent high-frequency (>70% of E. coli isolates) in both livestock and municipal wastewater environments .
Extended-spectrum β-lactamases (ESBLs) that inactivate newer cephalosporins are a major focus of sentinel E. coli susceptibility testing. Cottell et al.  evaluated E. coli originating from 88 steers that were treated with ceftiofur and/or chlortetracycline in an experimental US feedlot. The ESBL bla CTX-M-32, was detected in cefoxatime-resistant E. coli in 29 animals, and was found to be present on a self-transmissible IncN-family plasmid (reviewed in ). In Germany, bla CTX-M-1 was the predominant ESBL in E. coli, found on 87% of assessed farms . In a Swiss study of the wider food processing chain, Geser et al.  screened for ESBL in fecal samples collected at slaughter as well as in raw milk, and minced beef. They found that of 124 bovine fecal samples 13.7% hosted ESBL-producing bacteria, 98% of which were E. coli. Despite enrichment for ESBL-producing organisms, ESBL were not detected in raw milk or minced beef samples. The ESBLs detected in the study included bla CTX-M-1, bla TEM-1 bla CTX-M-14, bla CTX-M-117, and bla CTX-M-15. Many of the ESBL-positive isolates were frequently co-resistant to tetracycline (76%), trimethoprim/sulfamethoxazole (76%), nalidixic acid (47%), at least one aminoglycoside (76%), chloramphenicol (65%) and ciprofloxacin (41%). The authors suggested that slaughter hygiene prevented the transmission of ESBLs into the food chain . Similarly, the prevalence of AMR E. coli O157:H7 was investigated in 510 fecal, hide, carcass, and raw meat samples from 4 beef slaughterhouses in China. STEC was detected in 1.4% of fecal and hide sample, but not in pre- and post-evisceration carcasses, nor in raw meat samples, with all isolates sensitive to 16 relevant antimicrobials . During slaughter, cattle hides are major contributors to carcass contamination [133, 134]. In another study tracking E. coli resistant to 3rd-generation cephalosporins or trimethoprim/sulfamethoxazole, Schmidt et al.  determined the prevalence of generic and AMR E. coli at various sites along the beef processing continuum. The prevalence of cephalosporin-resistant and trimethoprim/sulfamethoxazole-resistant E. coli in fecal samples at processing was 75 and 95%, respectively. Prevalence in pre-evisceration carcasses was 3 and 33%, and resistant isolates were only found in 0.5% of final carcasses, and no isolates were associated with the final striploin product. All cephalosporin-resistant E. coli isolated were resistant to ampicillin, ceftiofur, and ceftriaxone, and 64% of isolates harbored bla CMY, conferring additional resistance to clavulanate/amoxicillin and cefoxitin . These reports suggest that hygienic practices in beef processing are effective against AMR bacteria.
Antimicrobial resistance in bovine-origin Salmonella
Non-typhoidal Salmonella spp. (often Salmonella enterica serotype Typhimurium or Enteritidis) are frequent laboratory-confirmed infectious agents of gastroenteritis. Although the enteritis is usually self-limiting, invasive S. enterica spp. infections often require antimicrobial therapy. Cattle are infected/colonized by many Salmonella species, and ground beef is a vehicle of Salmonella transmission, implicated in 45% of outbreaks linked to beef . In cattle, susceptible adults develop enteritis, and calves may also develop septicemia. S. enterica serotypes Dublin and Newport are associated with bovine salmonellosis, and adult cattle may carry and shed Salmonella asymptomatically for many years. In humans, serotype Dublin has the highest proportion of invasive infections resulting in hospitalization and mortality . Due to the frequency of infections, the development of AMR in Salmonella is a risk to human health. In North America, MDR Salmonella are on average resistant to 7 antimicrobials . In the US, Salmonella (and other enteropathogens) are collected from humans, animals, and retail meat for the National Antimicrobial Resistance Monitoring System (NARMS) . In 2013, Salmonella was isolated from 7.9% of beef cattle, and in 0.9% of ground beef samples . MDR (>3 antimicrobials) was found in 20% of all ground beef serotype Dublin isolates, many of which were resistant to ampicillin, chloramphenicol, streptomycin, sulfonamides, and tetracycline . Worse still, the prevalence of ceftriaxone resistance (3rd generation cephalosporin) in bovine-origin serotype Dublin increased from 0 to 86% between 1996 and 2013 . As this is a major risk to human health, adoption and adherence to good practices during beef processing and proper cooking are critical to prevent transmission [136, 139, 140].
Antimicrobial resistance in bovine-origin Campylobacter
Campylobacter is the most frequent cause of human bacterial gastroenteritis in the developed world, with Campylobacter jejuni responsible for >90% of Campylobacter infections . Mostly a self-limiting infection in humans, severe cases of campylobacteriosis are treated with drugs such as erythromycin or ciprofloxacin. Campylobacter are frequent colonizers of chickens, but cattle are an important reservoir, and can carry high numbers of Campylobacter asymptomatically . Susceptible cattle can suffer from enteritis, and Campylobacter fetus subsp. fetus and subsp. venerealis can cause venereal bovine genital campylobacteriosis, leading to infertility and abortion [13, 142]. In the NARMS report, Campylobacter was isolated from 42% of beef cattle, with 14% of isolates resistant to ciprofloxacin . In a Japanese study of beef cattle, C. jejuni was isolated from 36% of cattle on 88% of the farms surveyed: ~40% of C. jejuni isolates were enrofloxacin- and nalidixic acid-resistant, but none were erythromycin-resistant . In a Swiss study of 97 Campylobacter isolates obtained from a beef processing plant, Jonas et al.  found that 31% were fluoroquinolone-resistant and ~1% were erythromycin-resistant. Wieczorek et al.  examined Campylobacter abattoir prevalence on 812 bovine hides and corresponding carcasses, and found Campylobacter on 25.6% of hides, and 2.7% of carcasses. The isolates obtained were equally resistant to nalidixic acid and ciprofloxacin (38.3%), streptomycin (24.3%), tetracycline (20.9%), erythromycin (4.3%), and gentamicin (2.6%) .
Antimicrobial resistance in bovine-origin Enterococcus
Enterococcus spp. are ubiquitous Firmicutes in the healthy intestinal microbiota of both humans and cattle, and indicate fecal contamination. Most Enterococcus spp. are not foodborne pathogens, nor are they bovine pathogens . Despite this, isolates of Enterococcus faecalis and faecium may cause life-threatening human infections, such as UTIs and meningitis. Control of enterococci infections is complicated by high-level MDR . Enterococci are referred to as ‘drug-resistance gene traffickers’ due to their omnipresence, robustness, and capability of transferring AMR to other species and pathogens [147, 148]. E. faecalis transferred gentamicin resistance plasmids to transplanted human flora in a BALB/c mouse model . The US NARMS report indicates that Enterococcus were recovered from ~90% of cattle, and ~80% of retail ground beef tested. The incidence of MDR (>3 antimicrobials) in both E. faecium and faecalis was lower in cecal isolates from beef cattle (19 and 14%, respectively) than in cecal samples from chickens (67 and 46%, respectively) or turkeys (25 and 58%, respectively) . Other studies of AMR Enterococcus typically focus on the emergence of resistance to vancomycin— an antimicrobial used in the treatment of MRSA and other Gram-positive infections [122, 150]. Vancomycin or linelozid resistance was not detected in bovine-origin Enterococcus spp. in the United States or Canada [137, 151], but ~30% of E. faecium NARMS isolates were found to be quinupristin/dalfopristin-resistant . Overall, despite the possibility for transmission of pathogenic strains to humans, Enterococcus spp. in the beef production environment have been studied mainly for their presumptive importance as AMR determinant sentinels/reservoirs.
Antimicrobials and the bovine microbiota
Cattle house a dense (>1010 microbes/ml; rumen fluid ) consortia of microbial species in the distinct physiological niches of the rumen and lower digestive tract . Different host compartments functionally select for, and are shaped by, distinct microbial communities that are essential for the proper physiology and development of the host [154, 155]. Cattle are dependent on rumen microbes for feed digestion, and the microbiome collectively degrades complex polysaccharides, converting plant mass into volatile fatty acids for absorption by the host animal. Core microbial species in the rumen include Prevotella, Butyrivibrio, Ruminococcus, as well as many unclassified organisms [156, 157]. Other bovine niches harbor unique microbial communities, such as the nasopharyngeal and vaginal tracts [153, 158, 159]. The microbial community in the jejunum also has a role in feed digestion, and influences feed efficiency . The fecal microbiota is dominated by Firmicutes and Bacteroidetes, but also contains Proteobacteria and human enteropathogens, which are shed in feces [154, 161, 162]. Collectively, the intestinal microbiota hosts a portion of the cattle resistome.
Unlike in humans and experimental animal models, there is currently limited information concerning the effect of antimicrobials on the bovine microbiota/resistome. However, much work describes the effect of therapeutic and sub-therapeutic administration of antimicrobials on the prevalence of specific bacteria in bovines. These studies typically involve antimicrobial administration to a controlled animal cohort, followed by culture-dependent collection of an organism-of-interest for susceptibility testing. These approaches provide a biased snapshot of microbiome changes. Newer methods include culture-independent collection of metagenomic DNA for detection and quantitation of specific AMR genes by PCR-based methodology, or for high-throughput sequencing and functional AMR gene annotation (Table 1). There are currently few studies describing the effects of antimicrobials on microbial population diversity in bovines using high-resolution sequencing methodology.
Effect of antimicrobials on the bovine microbiota
Pereira et al.  characterized the gut microbiota (fecal samples) of pre-weaned dairy calves fed raw milk spiked with ‘residual’ concentrations of ceftiofur (ceftiofur sodium; 0.1 μg/mL), ampicillin (ampicillin sodium; 0.01 μg/mL), penicillin (penicillin G sodium; 0.005 μg/mL), and oxytetracycline (oxytetracycline hydrochloride; 0.3 μg/mL) using 16S rRNA Illumina MiSeq-based sequencing. Exposure resulted in Genus-level differences, but taxa above the Family level were not altered . The microbiota of exposed calves was also less diverse than treatment-free calves . Similarly, Reti et al.  examined the effects of a sub-therapeutic AGP on the abundance and composition of microflora in the small and large intestine of adult beef cattle. The US- and Canada-approved chlortetracycline/sulfmethazine AGP (Aureo S-700 G, Alpharma) was administered at 350 mg of each antimicrobial per head per day for 28 d . Compared to non-treated control cattle, beef cattle administered the AGP showed no differences in bacterial abundance or richness/diversity composition (determined via quantitative PCR and terminal restriction fragment length polymorphism analyses) . Studies using advanced 16S rRNA metagenomic sequence-based and whole metagenome methodologies may be of greater significance in future work exploring the effect of antimicrobials on the microbiota.
Effect of therapeutic and sub-therapeutic antimicrobial usage on AMR gene prevalence
Kanwar et al.  recently explored the effects of differential treatment strategies on the prevalence of AMR determinants in the fecal metagenome. In a 26-day field trial, 176 beef steers were divided into 4 cohorts and given therapeutic doses of ceftiofur (ceftiofur crystalline-free acid (CCFA), Excede, Zoetis; 6.6 mg/kg body weight) and/or chlortetracycline (Aureomycin, Alpharma; 22 mg/kg body weight). One of the four cohorts included steers in which only 1 of the animals was administered ceftiofur and chlortetracycline, while the remaining animals received chlortetracycline alone. Via quantitative PCR, the authors determined gene copies/g of wet feces of bla CMY-2 and bla CTX-M (ceftiofur resistance), tet(A) and tet(B) (tetracycline resistance), and 16S rRNA genes in fecal community DNA from the pens of each treated cohort. Pens where all cattle were treated with ceftiofur had greater numbers of bla CMY-2 and bla CTX-M ceftiofur resistance determinants than single-animal treatment pens . Chlortetracycline treatment increased the levels of bla CMY-2 and bla CTX-M gene copies compared to cattle in pens that did not receive chlortetracycline. In contrast, tetracycline AMR gene prevalence decreased in pens where all cattle received ceftiofur compared to pens where only one animal received ceftiofur . The authors discussed these findings in the context of expansion or suppression of singly- or co-resistant AMR populations under antimicrobial selection, which served to highlight the complexity of the effects of antimicrobials on the resistome, and the potential for discrepancies between culture- and non-culture-based AMR quantitation methodologies .
Utilizing advanced total community metagenomic sequencing, Chambers et al.  examined the effect of ceftiofur treatment on the prevalence of AMR genes in the bovine fecal microbiome. Holstein cows were injected subcutaneously with ceftiofur (CCFA, Excede, Zoetis; 1 mg per 45.4 kg body weight) and fecal samples were collected prior to and post-treatment. Total DNA was sequenced on the Illumina HiSeq platform, and AMR genes were detected using the antibiotic resistance genes database (ARDB) . The proportion of β-lactam and MDR sequences were found to be higher in ceftiofur-treated cows relative to control cows. The β-lactamase genes cfxA2 and cfxA3 were most abundant, and have previously been associated with Prevotella—a common rumen microbe . Ceftiofur also changed the fecal bacterial community composition, increasing Bacteroidia and decreasing Actinobacteria. This study was also notable because metagenomic data was functionally assessed with MG-RAST , allowing examination of antimicrobial-induced changes to the metagenome. Functional ceftiofur-associated shifts included increased prevalence of genes associated with stress, chemotaxis, and resistance to toxic compounds . This work and others like it likely represent the future direction of AMR surveillance research.
Sub-therapeutic antimicrobial administration is one of the most controversial beef production practices with many studies exploring this topic in the context of AMR development. Alexander et al.  investigated effects of chlortetracycline/sulfamethezine AGPs (Aureu S-700 G, Alpharma; 44 mg/kg each in-feed) on the prevalence of AMR E. coli in the beef production continuum. With respect to treated and non-treated cattle, E. coli was collected from live-animal feces, hides, intestinal digesta, carcasses, and ground beef. Animals fed chlortetracycline/sulfamethezine harbored more tetracycline-resistant E. coli than non-treated animals (50.9% vs. 12.6%), but there were no differences in the prevalence or profile of AMR E. coli between treatments in the hide, carcass or ground beef samples . To the authors this suggested that AMR E. coli can enter the food chain at slaughter regardless of AGP administration . Sub-therapeutic administration of tetracycline/sulfamethazine also increased the prevalence of tetracycline-resistant organisms, and increased the frequency of ampicillin-resistant E. coli, in agreement with similar studies using the same antimicrobials . Another study found that sub-therapeutic tylosin treatment (Tylan, Elanco; 11 mg/kg in-feed) increased the frequency of Enterococcus spp. harboring erm(B) and/or msrC (a macrolide/streptogramin efflux pump gene) . The authors of that study concluded that the diversity of Enterococcus decreased in the period between when cattle entered and exited the feedlot, and that the AMR Enteroccocus were derived from strains present in the intestinal microbiota before tylosin administration . Selection for co-resistance and MDR is one of the main arguments against AGPs.
Effect of BRD-related antimicrobial usage
Given the importance of antimicrobials in the treatment of BRD agents, much research examines the effect of antimicrobial treatment on AMR development in BRD bacteria. Investigated the effects of therapeutic and sub-therapeutic macrolide administration on the nasopharyngeal and enteric microbiota, with specific focus on M. haemolytica and Enterococcus, respectively. Forty beef steers were injected once with tilmicosin (Micotil, Elanco; 10 mg/kg) or tulathromycin (Draxxin, Pfizer; 2.5 mg/kg) or fed sub-therapeutic tylosin (Tylan, Elanco; 11 mg/kg in-feed) continuously over 28 d. Therapeutic tilmicosin and tulathromycin decreased nasopharyngeal carriage of M. haemolytica: at the beginning of the trial, 60% of the steers tested positive for M. haemolytica, at 7 d post- injection, none of the steers treated with tilmicosin harbored M. haemolytica, and only one steer treated with tulathromycin was positive for M. haemolytica. Sub-therapeutic tylosin had no effect on nasopharyngeal carriage, and tylosin-exposed M. haemolytica isolates did not acquire macrolide resistance. In contrast, a significant proportion of the bystander Enterococcus acquired erm(B) erythromycin resistance following treatment with either injectable tilmicosin or tulathromycin, or in-feed tylosin, and were 76-fold more likely to be erythromycin-resistant than those recovered from non-antimicrobial-treated steers. Catry et al.  correlated 2-year of Belgian farm-standard antimicrobial usage to the occurrence of AMR in rectum and nasal flora, represented by E. coli and Pasteurellaceae, respectively. Narrow spectrum penicillins were the most frequently administered parenteral antimicrobials, often in combination with an aminoglycoside, such as neomycin or dihydrostreptomycin . Among rectal E. coli, 20.6% were resistant to least one antimicrobial. The most frequent resistance patterns were ampicillin-tetracycline-streptomycin (15.9%), tetracycline-streptomycin (11.4%), and ampicillin-streptomycin (9.8%) . Among 206 P. multocida isolates and 42 M. haemolytica isolates originating from the nasal cavity, the predominant resistance found was to the aminoglycoside spectinomycin . The authors confirmed that antimicrobials altered the prevalence of AMR in the digestive and respiratory tracts and highlighted that the route of administration affected resistance outcomes. Individual therapy was linked to increased but transient resistance, whereas in-feed antimicrobials were linked to higher levels of MDR . Others have also suggested that the route of administration affects overall AMR prevalence [173, 174], but there are also contradictory reports where no such association exists [99, 175].
Heavy metal supplementation and AMR
Cattle also receive trace mineral supplements that include elements with AGP activity. Some heavy metals, such as zinc, manganese, and copper may be given as salt-mixes, injected, or administered in slow-release ruminal capsules . Copper and zinc promote growth, potentially via suppression of pathogens and alteration of microbiota [176, 177]. In other production animals, zinc and copper can select for AMR . This may be due in part to MGEs such as ICE, in which AMR determinants are co-localized with heavy-metal resistance genes. For example, in addition to multiple AMR determinants, ICEPmu1 (Fig. 3a) encodes for a multi-copper oxidase, which is potentially involved in resistance to copper and other heavy metals . Thus, heavy metal exposure can co-select for AMR. Jacob et al.  studied the effect of elevated copper and zinc fed to heifers receiving high-energy rations by isolating and characterizing AMR E. coli and Enterococcus from fecal samples. Resistance to copper and zinc in E. coli isolates was increased, and abundance of the tetracycline resistance determinant tet(M) was elevated following heavy metal supplementation . In a study combining tylosin (Tylan, Elanco; 0 or 10 mg/kg in-feed) with copper (CuSO4; 10 or 100 mg/kg in-feed), Amachawadi et al.  investigated fecal Enterococcus spp. to determine if elevated copper supplementation co-selects for macrolide resistance. The transferable copper resistance gene tcrB was identified in 8.5% of Enterococcus from elevated copper- and tylosin-fed cattle, compared to copper alone (4.5%), tylosin alone (3.5%), or the low copper/no tylosin control (2.0%) [181, 182]. All the tcrB-positive isolates proved to be E. faecium, and interestingly, all tcrB-positive isolates harbored tetracycline tet(M) and erythromycin resistance erm(B) determinants . The authors concluded that elevated dietary copper could co-select for AMR in feedlot cattle . Thus, heavy metal supplementation should also be considered as a selective pressure with the potential to promote the dissemination AMR determinants, and is a practice that likely needs to be revisited as these minerals may be added to the diet in excess of the animal’s requirement.
The bovine resistome & the wider environment
The primary concern relating to antimicrobials in agriculture is the potential for AMR determinants to expand and spread via the food chain. Although urban lifestyles rarely bring people into direct contact with livestock, the animal production continuum extensively connects with numerous industries, infrastructure, and ecologies. For example, manure from antimicrobial-treated animals may be applied to crops, or waste from farms may drain into rivers, reservoirs, and wastewater treatment plants. In the US, cattle produce between 0.86 and 6.4 million t of manure daily . AMR can thus be transferred to the wider environment, increasing the risk of contact with a human pathogen. At present, knowledge about the identity, diversity, distribution, and patterns of co-resistance in beef-related AMR genes, and how they compare to determinants in other ecosystems is scarce, due in part to the difficulty in defining the bovine resistome in the context of the larger environmental resistome. AMR genes are widely present in both pristine and human-impacted environments , so the occurrence of AMR in any specific biome does not necessarily validate the impact of antimicrobial usage. However, with the advent of next-generation sequencing and total metagenomics, and resources like ARDB, and CARD (the Comprehensive Antibiotic Resistance Database; ), high-throughput AMR gene profiling resistomics is shedding light on these relationships.
Resistome characterization via shotgun metagenomics
Noyes et al.  examined AMR genes of 1,741 beef cattle as they moved longitudinally through the production chain, characterizing feedlot, slaughter, and beef product resistomes via shotgun metagenomics performed on the Illumina HiSeq platform, and assessed against the Resfinder , ARG-ANNOT , and CARD  AMR gene databases. This identified 300 unique AMR genes, and showed that, the diversity of the AMR genes decreased while cattle were in the feedlot, indicative of selective pressure imposed by antimicrobials, consistent with other studies showing diversity reduction following antimicrobial exposure . Examination of post-slaughter samples obtained from belts and tables in the slaughterhouse, meat trimmings, and market-ready samples revealed no AMR genes . The authors concluded that effective practices at slaughter minimized the likelihood of AMR gene being passed through the food chain. However, the high prevalence of bovine DNA complicates shotgun metagenomics and may result in low sensitivity of AMR gene detection. Despite this, this study exemplifies the powerful utility of metagenomic approaches in the study of AMR gene ecology.
Metagenomics have also proved useful in the examination of AMR genes found in wastewater treatment plants associated with tanneries and slaughterhouses. Wastewater treatment plants are thought to be HGT hotspots because of high bacterial diversity and density [189, 190]. Wang et al.  profiled AMR genes and MGEs in wastewater sludge from a Chinese leather tannery via Illumina HiSeq and assessment with MG-RAST  and ARDB . Proteobacteria were most-prevalent in anaerobic and aerobic sludge accounting for 35.95 and 58.36% of annotated reads, respectively, followed by Firmicutes (16.31 and 6.08%, respectively) . Concerning AMR genes 747 reads (0.0081%) and 877 reads (0.0101%) in anaerobic and aerobic sludge, respectively, were assigned to 54 and 42 types of known AMR genes . MDR efflux transporters were most common, followed by tetracycline and sulfonamide resistance genes (>20% of AMR-associated reads) . The authors also detected MGEs in tannery DNA samples, but limitations in methodology restricted investigating linkages with AMR genes. Taking a similar approach, Li et al.  examined the resistome of plasmids harvested from influent, activated sludge, and digested sludge of two Hong Kong wastewater treatment plants receiving domestic and slaughterhouse (cattle and other production animals) sewage. AMR genes were detected in all of the plasmid metagenomes: the most abundant were tetracycline resistance genes (29% of all AMR gene sequences), quinolone resistance genes (17%), and β-lactam resistance genes (12%) . The AMR gene distribution and abundance in each wastewater treatment plant sample is shown Fig. 3b, in circular relationship format [192, 193]. This plasmid-centric study highlights the mobile resistome and plasmid fates more so than a total metagenome study, and future experiments could involve comparisons between plasmid and total resistomes to explore HGT of AMR determinants. This paper also highlights a methodology to examine MGE-associated AMR genes that is not confounded by environmental AMR genes or host DNA contamination.
Resistome characterization via functional metagenomic library screening
Sequence-based metagenomic AMR gene profiling is also limited to those genes with similarity to already known AMR genes, and metagenomic shotgun read lengths present difficulties for the characterization of the AMR genomic context. Functional metagenomic library-based approaches have proved to be complementary in the identification, quantification, and characterization of novel resistance determinants. Wichmann et al.  examined the resistome of dairy cow manure with large-insert (>35 kb) fosmid libraries constructed from 5 manure samples. The resulting E. coli-based libraries (containing 25.9 Gb of DNA) were screened for resistance to kanamycin, chloramphenicol, tetracycline, and the β-lactams carbenicillin (penicillin) and ceftazidime (cephalosporin). Of 87 AMR E. coli clones with genes conferring resistance to at least one of the antimicrobials tested, 80 carried unique AMR genes, suggesting that the cow microbiome harbors AMR genes that are unique or unidentified elsewhere. A novel clade of chloramphenicol acetyltransferases was also described . Flanking sequence analysis indicated that the AMR determinants originated from typical cattle microbes: Firmicutes were predominant (50% of sequenced clones), followed by Bacteroidetes (23%) and Proteobacteria (14%) . Another powerful advantage of the fosmid library approach is the ability to examine AMR gene context: i.e. co-occurrence with other AMR genes, or association with MGEs. Wichmann et al. found 2 kanamycin-resistant E. coli clones with >5 putative genes with predicted AMR or MGE functions . Thus, library-based functional metagenomic approaches combined with next-generation sequencing are a powerful way to screen for AMR determinants associated with MGEs, plasmids, or phages .
Linking antimicrobial use in beef production to human health risk
Assessing the differential risk, importance, and source of AMR genes
Given the ubiquity of AMR determinants in bovine and other microbial communities, it is difficult to appraise the relative risk any particular determinant presents for the likelihood of transfer into a human pathogen and clinical therapy failure. Confounding the issue are AMR determinants that are expressed or silent in different hosts, as well as AMR determinants akin to housekeeping genes . For the latter, ‘decontextualized’ housekeeping genes, such as those harbored on MGEs, pose a greater risk [1, 197]. Prioritizing the differential human health risk posed by an AMR gene is complicated by such issues, but risk ranking schemes have been discussed [1, 198, 199]. Greatest risk may be presented by AMR genes already hosted on MGEs in human pathogens, and known to cause therapy failure. An example of this is the recently detected plasmid-mediated colistin (polymyxin E) resistance gene (mcr-1) in E. coli isolates from poultry, swine, and infected humans [200, 201]. A beef-related example is the ~38 kb R plasmid found in S. enterica serotype Newport, which confers resistance to tetracycline, ampicillin, and carbenicillin . This caused severe penicillin-unresponsive salmonellosis linked to contaminated hamburger meat . The next level of risk may be from functional AMR genes conferring resistance to human antimicrobials, but which are hosted in MGEs in non-pathogenic bacteria. These might include the AMR determinants encoded by ICEPmu1 and ICEMh1 found in P. multocida and M. haemolytica, respectively [103, 104]. Elevated risk is credited to MGEs because the acquisition and selection of an AMR determinant in a MGE might be the initial step for transmission to a human pathogen. In the future, more focus should be devoted to AMR in the context of MGEs, particularly for total resistome studies utilizing libraries and shotgun metagenomics, or emerging long-read sequencing technologies.
An example of risk and source determination may be given by the long-term global epidemics of ground beef-associated MDR S. enterica serotype Typhimurium phage type DT104, which may express resistance to ampicillin, chloramphenicol, streptomycin, sulfamethoxazole, and tetracycline (resistance-type ACSSuT) [203–205]. In some isolates, these AMR genes are hosted in a 13 kb MDR region, residing in a larger chromosome-encoded ~43 kb region called Salmonella genomic island 1 (SGI1). The MDR region harbors Class I integrons—genetic elements capable of consolidating multiple AMR gene cassettes . Integrons are often found in conjunction with MGEs; in the case of DT104, HGT can occur via phage-mediated transfer . Although veterinary antimicrobial usage and food animals have long been the chief culprit for the origin and dissemination of DT104, Mather et al. [208, 209] challenged the perception that DT104 originated from a single zoonotic population by whole-genome sequencing Scottish DT104 collections. In total, 135 isolates from humans and 83 from cattle were sequenced and compared against 111 other DT104 isolates from diverse host animals and countries. Using phylogenetic diffusion models, the authors found that AMR DT104 populations were distinguishable between cattle and humans, and that animal-to-human and human-to-animal transitions were rare, and occurred at the same frequency . This suggested that most human infections were unlikely to originate from the local cattle. AMR diversity was greater in human isolates, resulting from multiple, independent recombination events in SGI1’s MDR region . In part, this suggested that most human infections were acquired from humans, and that DT104 circulated separately in the animal and human populations, and/or unique sources infected humans vs. animals . Mather et al. emphasized the importance of integrating veterinary and clinical data to make evidence-based judgments concerning the sources of AMR infections.
Direct evidence of human health impact of beef antimicrobial usage
Linking on-farm antimicrobial use to human infection is difficult. While antimicrobial usage evidently selects for drug-resistant organisms, there is a gap in knowledge connecting usage to the flow of AMR determinants from the bovine microbiota to outbreaks of human AMR diseases. To bridge this gap, a number of studies compared outbreak clinical isolates to animal isolates taken at similar times from nearby locations [210–212]. Typically, isolates were examined for similar AMR/genetic profiles, and if identical, this provided some evidence of the AMR outbreak source. Direct links to specific antimicrobial usage is rarely identified for outbreaks. A caveat of many studies is that transfer is assumed to be from cattle to humans, or remains unknown. Several AMR E. coli and Salmonella outbreaks have been associated with beef [213–215], but there are few examples where those AMR determinants have been traced back to AMR bacteria in cattle . This reinforces the need for greater integration of human and veterinary data. For beef production, tracing the source of an AMR outbreak is complicated by system complexity, herd movement, and lack of industry motivation. And although beef production is a major industry, more focus has been on the human health impact of AMR transfer in dairy cattle, and in the swine and poultry industries (reviewed in ). Dairy-related outbreaks may be easier to document because the source animal population is maintained, whereas the beef, swine, and poultry populations are consumed. Selected examples of outbreaks and human health threats posed by bovine AMR bacteria are listed in Table 2. These demonstrate that the most convincing molecular and epidemiological AMR links are found when the infected human is directly connected to the animal population on farms or via farm workers [211, 216, 217]. Direct exposure to livestock is a known risk factor for zoonotic transmission (reviewed in ).
Conclusions & future focus
As in most environments, AMR determinants exist ubiquitously in the beef production biome, regardless of antimicrobial exposure. Nevertheless, the use of antimicrobials for bovine welfare and growth promotion contributes selective pressure that increases the abundance of AMR genes and their host bacteria, and promotes the genesis and dissemination of MDR organisms. The presence or absence of connections between AMR in bovine microbial populations to human health threats are likely to become clearer with the increasing application of whole-genome sequencing and metagenomic resistomics. The role of MGEs in AMR propagation is likely to be an important focus for understanding the impact of veterinary antimicrobials. Future investigations may validate mitigation strategies, such as the separation of antimicrobials for use in beef cattle from those used in humans. Proper and judicious use of antimicrobials will help prolong the usefulness of both clinical and veterinary antimicrobials, but ever-increasing usage of antimicrobials in food-animal production suggests that microbes will only continue to acquire resistance. Of particular concern for cattle are the MDR BRD agents: in the future, respiratory infections may become untreatable with current antimicrobials. On a positive note, several studies reveal that adequate hygiene and appropriate treatment at slaughterhouse and wastewater treatment facilities are efficacious at reducing or eliminating transmission of AMR organisms and genes. Thus, such procedures and facilities should be explored further, and promoted in deficient areas of food-animal production.
The literature search was conducted from January to March 2016 via Google Scholar and PubMed. Recent (2012-present) studies that described AMR or usage in context with beef production, bovine pathogens, commensal bacteria, metagenomics, the resistome, and cattle were included. Older reports, or studies referring to dairy operations were excluded, except for where beef production information was sparse.
Comparison of most frequently reported AMR in bovine pathogens
A literature search was conducted for AMR in bovine pathogens. Journal articles ([30–88], 2000-present) were collected if the AMR data was presented in a format conducive to comparison. Reports that determined the percentage of resistant isolates in a larger collection of isolates were considered. Reports were not considered if the collection of isolates had been pre-screened or enriched for resistance to any antimicrobial. The percent resistance value (i.e. number of resistant isolates compared to the total number of isolates) for each antimicrobial tested and for each strain was recorded. Journal articles that did not provide resistant, intermediate, or susceptible determinations were excluded. Intermediate resistance was not included in the percent resistance. For several antimicrobials/species, the percent resistance was given by author-determined values; in many cases, resistance was determined according to standardized interpretive criteria. The median of the percent of resistant isolates was calculated, and the resulting median value is proportional to the diameter of each circle in Fig. 2.
Antimicrobial growth promoter
Antimicrobial resistance gene database
Bovine respiratory disease
The comprehensive antibiotic resistance database
Canadian integrated program for antimicrobial resistance surveillance
Enterohaemorrhagic E. coli
Extended spectrum β-lactamase
European surveillance of veterinary antimicrobial consumption
Food and Drug Administration
Horizontal gene transfer
Integrative and conjugative element
Mobile genetic element
Metagenomics rapid annotation using subsystem technology
National antimicrobial resistance monitoring system
Population correction unit
Shiga toxin-producing E. coli
UK veterinary antibiotic resistance and sales surveillance
Martínez JL, Coque TM, Baquero F. What is a resistance gene? Ranking risk in resistomes. Nat Rev Microbiol. 2015;13:116–23.
D’Costa VM, McGrann KM, Hughes DW, Wright GD. Sampling the antibiotic resistome. Science. 2006;311:374–7.
Soucy SM, Huang J, Gogarten JP. Horizontal gene transfer: building the web of life. Nat Rev Genet. 2015;16:472–82.
Vidaver AK. Uses of antimicrobials in plant agriculture. Clin Infect Dis. 2002;34 Suppl 3:S107–10.
Food and Agriculture Organization of the United Nations. Food outlook: Biannual report on global food markets. 2015.
USDA. Foreign Agricultural Service. Livestock and Poultry: World Markets and Trade. 2015.
Radostits OM, Gay CC, Hinchcliff KW, Constable PD: Veterinary Medicine: A textbook of the diseases of cattle, horses, sheep, pigs and goats. UK: Elsevier Health Sciences; 2006.
Draft AVMA principles on judicious therapeutic use of antimicrobials. American Veterinary Medical Association. J Am Vet Med Assoc. 1998;213:763.
McEwen SA, Fedorka-Cray PJ. Antimicrobial use and resistance in animals. Clin Infect Dis. 2002;34 Suppl 3:S93–106.
Center for Veterinary Medicine, US Food and Drug Administration. The judicious use of medically important antimicrobial drugs in food-producing animals. Guidance for Industry #209. p. 1–26:1–26.
Swartz M. Human health risks with the subtherapeutic use of penicillin or tetracyclines in animal feed. USA: IOM Publication; 1989.
Nagaraja T, Chengappa M. Liver abscesses in feedlot cattle: a review. J Anim Sci. 1998;76:287–98.
Kahn CM, Line S, Merck Co. The Merck veterinary manual. Whitehouse Station, N.J.: Merck & Co.; 2010.
US Food and Drug Administration: Approved Animal Drug Products (Green Book). 2016.
35 years of resistance. Nat Rev Microbiol 2012, 10:373–373.
Ad-Hoc Committee for Antimicrobial Stewardship in Canadian Agriculture and Veterinary Medicine. Antibiotic stewardship’s golden moment: Resistance or change? Can Vet J. 2015;56:115–9.
Woolhouse M, Ward M, van Bunnik B, Farrar J. Antimicrobial resistance in humans, livestock and the wider environment. Philos Trans R Soc London. 2015;370:20140083.
Van Boeckel TP, Brower C, Gilbert M, Grenfell BT, Levin SA, Robinson TP, et al. Global trends in antimicrobial use in food animals. Proc Natl Acad Sci U S A. 2015;112:5649–54.
US Food and Drug Administration. 2014 Summary report on antimicrobials sold or distributed for use in food-producing animals. 2015.
European Medicines Agency, European Surveillance of Veterinary Antimicrobial Consumption. Sales of veterinary antimicrobial agents in 26 EU/EEA countries in 2013. Fifth ESVAC report. 2015.
Government of Canada. Canadian Integrated Program for Antimicrobial Resistance Surveillance (CIPARS) 2012 Annual Report. Public Health Agency of Canada, Guelph, Ontario, 2014.
Australian Government. Quantity of antimicrobial products sold for veterinary use in Australia: July 2005 to June 2010. Canberra: Australian Pesticides and Veterinary Medicines Authority; 2014.
UK-VARSS 2014. UK Veterinary Antibiotic Resistance and Sales Surveillance. Veterinary Medicines Directorate. 2014.
Chapman HD, Barta JR, Blake D, Gruber A, Jenkins M, Smith NC, et al. A selective review of advances in coccidiosis research. Adv Parasitol. 2013;83:93–171.
US Food and Drug Administration. Estimates of antibacterial drug sales in human medicine. 2012.
ECDC (European Centre for Disease Prevention and Control), EFSA (European Food Safety Authority) and EMA (European Medicines Agency). ECDC/EFSA/EMA first joint report on the integrated analysis of the consumption of antimicrobial agents and occurrence of antimicrobial resistance in bacteria from humans and foodproducing animals. Stockholm/Parma/London: ECDC/EFSA/EMA, 2015. EFSA J. 2015;13(1):4006,114 pp.
WHO model list of essential medicines: 19th list (updated) August 2015. World Health Organization. 2015.
Chantziaras I, Boyen F, Callens B, Dewulf J. Correlation between veterinary antimicrobial use and antimicrobial resistance in food-producing animals: a report on seven countries. J Antimicrob Chemother. 2014;69:827–34.
Garcia-Migura L, Hendriksen RS, Fraile L, Aarestrup FM. Antimicrobial resistance of zoonotic and commensal bacteria in Europe: the missing link between consumption and resistance in veterinary medicine. Vet Microbiol. 2014;170:1–9.
Van Duijkeren E, Wannet W, Houwers D, Van Pelt W. Antimicrobial susceptibilities of Salmonella strains isolated from humans, cattle, pigs, and chickens in the Netherlands from 1984 to 2001. J Clin Microbiol. 2003;41:3574–8.
Zhao S, McDermott PF, White DG, Qaiyumi S, Friedman SL, Abbott JW, et al. Characterization of multidrug resistant Salmonella recovered from diseased animals. Vet Microbiol. 2007;123:122–32.
Davis MA, Hancock DD, Besser TE, Daniels JB, Baker KN, Call DR. Antimicrobial resistance in Salmonella enterica serovar Dublin isolates from beef and dairy sources. Vet Microbiol. 2007;119:221–30.
Fitzgerald A, Edrington T, Looper M, Callaway T, Genovese K, Bischoff K, et al. Antimicrobial susceptibility and factors affecting the shedding of E. coli O157: H7 and Salmonella in dairy cattle. Lett Appl Microbiol. 2003;37:392–8.
Katsuda K, Kohmoto M, Mikami O, Uchida I. Antimicrobial resistance and genetic characterization of fluoroquinolone-resistant Mannheimia haemolytica isolates from cattle with bovine pneumonia. Vet Microbiol. 2009;139:74–9.
Hendriksen RS, Mevius DJ, Schroeter A, Teale C, Meunier D, Butaye P, et al. Prevalence of antimicrobial resistance among bacterial pathogens isolated from cattle in different European countries: 2002–2004. Acta Vet Scand. 2008;50:28.
Önat K, Kahya S, Çarli KT. Frequency and antibiotic susceptibility of Pasteurella multocida and Mannheimia haemolytica isolates from nasal cavities of cattle. Turk J Vet Anim Sci. 2010;34:91–4.
Welsh RD, Dye LB, Payton ME, Confer AW. Isolation and antimicrobial susceptibilities of bacterial pathogens from bovine pneumonia: 1994–2002. J Vet Diagn Invest. 2004;16:426–31.
Portis E, Lindeman C, Johansen L, Stoltman G. A ten-year (2000–2009) study of antimicrobial susceptibility of bacteria that cause bovine respiratory disease complex--Mannheimia haemolytica, Pasteurella multocida, and Histophilus somni--in the United States and Canada. J Vet Diagn Invest. 2012;24:932–44.
Schwarz S, Kehrenberg C, Salmon SA, Watts JL. In vitro activities of spectinomycin and comparator agents against Pasteurella multocida and Mannheimia haemolytica from respiratory tract infections of cattle. J Antimicrob Chemother. 2004;53:379–82.
Esaki H, Asai T, Kojima A, Ishihara K, Morioka A, Tamura Y, et al. Antimicrobial susceptibility of Mannheimia haemolytica isolates from cattle in Japan from 2001 to 2002. J Vet Med Sci. 2005;67:75–7.
Katsuda K, Kohmoto M, Mikami O. Relationship between serotype and the antimicrobial susceptibility of Mannheimia haemolytica isolates collected between 1991 and 2010. Res Vet Sci. 2003;94:205–8.
Katsuda K, Hoshinoo K, Ueno Y, Kohmoto M, Mikami O. Virulence genes and antimicrobial susceptibility in Pasteurella multocida isolates from calves. Vet Microbiol. 2013;167:737–41.
Cusack P, McMeniman N, Lean I. The medicine and epidemiology of bovine respiratory disease in feedlots. Aust Vet J. 2003;81:480–7.
Lamm CG, Love BC, Krehbiel CR, Johnson NJ, Step DL. Comparison of antemortem antimicrobial treatment regimens to antimicrobial susceptibility patterns of postmortem lung isolates from feedlot cattle with bronchopneumonia. J Vet Diagn Invest. 2012;24:277–82.
de Jong A, Thomas V, Simjee S, Moyaert H, El Garch F, Maher K, et al. Antimicrobial susceptibility monitoring of respiratory tract pathogens isolated from diseased cattle and pigs across Europe: the VetPath study. Vet Microbiol. 2014;172:202–15.
Francoz D, Fortin M, Fecteau G, Messier S. Determination of Mycoplasma bovis susceptibilities against six antimicrobial agents using the E test method. Vet Microbiol. 2005;105:57–64.
Siugzdaite J, Gabinaitiene A, Kerziene S. Susceptibility of Mycoplasma bovis field isolates to antimicrobial agents. Vet Med. 2012;57:575–82.
Soehnlen MK, Kunze ME, Karunathilake KE, Henwood BM, Kariyawasam S, Wolfgang DR, et al. In vitro antimicrobial inhibition of Mycoplasma bovis isolates submitted to the Pennsylvania Animal Diagnostic Laboratory using flow cytometry and a broth microdilution method. J Vet Diagn Invest. 2011;23:547–51.
Jimenez R, Piriz S, Mateos E, Vadillo S. Minimum inhibitory concentrations for 25 selected antimicrobial agents against Dichelobacter nodosus and Fusobacterium strains isolated from footrot in sheep of Portugal and Spain. J Vet Med B Infect Dis Vet Public Health. 2004;51:245–8.
Palanisamy K, Rajeswar J, Malmarugan S. Antibiogram pattern of bacteria causing endometritis in cows. 2013.
Sheldon I, Bushnell M, Montogomery J, Rycroft A. Minimum inhibitory concentrations of some antimicrobial drugs against bacteria causing uterine infections in cattle. Vet Rec. 2004;155:383–7.
Kim E. Antimicrobial resistance in foot rot bacteria. Diss. Calgary: University of Calgary; 2014.
Malinowski E, Lassa H, Markiewicz H, Kaptur M, Nadolny M, Niewitecki W, et al. Sensitivity to antibiotics of Arcanobacterium pyogenes and Escherichia coli from the uteri of cows with metritis/endometritis. Vet J. 2011;187:234–8.
Malinowski E, Lassa H, Smulski S, Kłossowska A, Kaczmarowski M. Antimicrobial susceptibility of bacteria isolated from cows with mastitis in 2006–2007. Bull Vet Inst Pulawy. 2008;52:565–72.
Yoshimura H, Kojima A, Ishimaru M. Antimicrobial susceptibility of Arcanobacterium pyogenes isolated from cattle and pigs. J Vet Med B Infect Dis Vet Public Health. 2000;47:139–43.
Santos TM, Caixeta LS, Machado VS, Rauf AK, Gilbert RO, Bicalho RC. Antimicrobial resistance and presence of virulence factor genes in Arcanobacterium pyogenes isolated from the uterus of postpartum dairy cows. Vet Microbiol. 2010;145:84–9.
Liu MC, Wu CM, Liu YC, Zhao JC, Yang YL, Shen JZ. Identification, susceptibility, and detection of integron-gene cassettes of Arcanobacterium pyogenes in bovine endometritis. J Dairy Sci. 2009;92:3659–66.
Englen M, Hill A, Dargatz D, Ladely S, Fedorka‐Cray P. Prevalence and antimicrobial resistance of Campylobacter in US dairy cattle. J Appl Microbiol. 2007;102:1570–7.
Inglis GD, McAllister TA, Busz HW, Yanke LJ, Morck DW, Olson ME, et al. Effects of subtherapeutic administration of antimicrobial agents to beef cattle on the prevalence of antimicrobial resistance in Campylobacter jejuni and Campylobacter hyointestinalis. Appl Environ Microbiol. 2005;71:3872–81.
Pezzotti G, Serafin A, Luzzi I, Mioni R, Milan M, Perin R. Occurrence and resistance to antibiotics of Campylobacter jejuni and Campylobacter coli in animals and meat in northeastern Italy. Int J Food Microbiol. 2003;82:281–7.
Bae W, Kaya KN, Hancock DD, Call DR, Park YH, Besser TE. Prevalence and antimicrobial resistance of thermophilic Campylobacter spp. from cattle farms in Washington State. Appl Environ Microbiol. 2005;71:169–74.
Parisi A, Lanzilotta SG, Addante N, Normanno G, Di Modugno G, Dambrosio A, et al. Prevalence, molecular characterization and antimicrobial resistance of thermophilic campylobacter isolates from cattle, hens, broilers and broiler meat in south-eastern Italy. Vet Res Commun. 2007;31:113–23.
Englen MD, Fedorka-Cray PJ, Ladely SR, Dargatz DA. Antimicrobial resistance patterns of Campylobacter from feedlot cattle. J Appl Microbiol. 2005;99:285–91.
Sato K, Bartlett P, Kaneene J, Downes F. Comparison of prevalence and antimicrobial susceptibilities of Campylobacter spp. isolates from organic and conventional dairy herds in Wisconsin. Appl Environ Microbiol. 2004;70:1442–7.
Inglis GD, Morck DW, McAllister TA, Entz T, Olson ME, Yanke LJ, et al. Temporal prevalence of antimicrobial resistance in Campylobacter spp. from beef cattle in Alberta feedlots. Appl Environ Microbiol. 2006;72:4088–95.
Hakkinen M, Heiska H, Hanninen ML. Prevalence of Campylobacter spp. in cattle in Finland and antimicrobial susceptibilities of bovine Campylobacter jejuni strains. Appl Environ Microbiol. 2007;73:3232–8.
Padungtod P, Kaneene JB, Hanson R, Morita Y, Boonmar S. Antimicrobial resistance in Campylobacter isolated from food animals and humans in northern Thailand. FEMS Immunol Med Microbiol. 2006;47:217–25.
Halbert LW, Kaneene JB, Ruegg PL, Warnick LD, Wells SJ, Mansfield LS, et al. Evaluation of antimicrobial susceptibility patterns in Campylobacter spp isolated from dairy cattle and farms managed organically and conventionally in the midwestern and northeastern United States. J Am Vet Med Assoc. 2006;228:1074–81.
Lyautey E, Hartmann A, Pagotto F, Tyler K, Lapen DR, Wilkes G, et al. Characteristics and frequency of detection of fecal Listeria monocytogenes shed by livestock, wildlife, and humans. Can J Microbiol. 2007;53:1158–67.
Wieczorek K, Dmowska K, Osek J. Prevalence, characterization, and antimicrobial resistance of Listeria monocytogenes isolates from bovine hides and carcasses. Appl Environ Microbiol. 2012;78:2043–5.
Angelos JA, Ball LM, Byrne BA. Minimum inhibitory concentrations of selected antimicrobial agents for Moraxella bovoculi associated with infectious bovine keratoconjunctivitis. J Vet Diagn Invest. 2011;23:552–5.
Sosa V, Zunino P. Diversity of Moraxella spp. strains recovered from infectious bovine keratoconjunctivitis cases in Uruguay. J Infect Dev Ctries. 2013;7:819–24.
Mohammed MJ, Marston CK, Popovic T, Weyant RS, Tenover FC. Antimicrobial susceptibility testing of Bacillus anthracis: comparison of results obtained by using the National Committee for Clinical Laboratory Standards broth microdilution reference and Etest agar gradient diffusion methods. J Clin Microbiol. 2002;40:1902–7.
Edrington TS, Schultz CL, Bischoff KM, Callaway TR, Looper ML, Genovese KJ, et al. Antimicrobial resistance and serotype prevalence of Salmonella isolated from dairy cattle in the southwestern United States. Microb Drug Resist. 2004;10:51–6.
Dargatz D, Fedorka‐Cray P, Ladely S, Kopral C, Ferris K, Headrick M. Prevalence and antimicrobial susceptibility of Salmonella spp. isolates from US cattle in feedlots in 1999 and 2000. J Appl Microbiol. 2003;95:753–61.
Akiba M, Nakaoka Y, Kida M, Ishioka Y, Sameshima T, Yoshii N, et al. Changes in antimicrobial susceptibility in a population of Salmonella enterica serovar Dublin isolated from cattle in Japan from 1976 to 2005. J Antimicrob Chemother. 2007;60:1235–42.
Dargatz DA, Fedorka-Cray PJ, Ladely SR, Ferris KE, Green AL, Headrick ML. Antimicrobial susceptibility patterns of Salmonella isolates from cattle in feedlots. J Anim Physiol Anim Nutr. 2002;221:268–72.
Erskine R, Walker R, Bolin C, Bartlett P, White D. Trends in antibacterial susceptibility of mastitis pathogens during a seven-year period. J Dairy Sci. 2002;85:1111–8.
Sawant AA, Hegde NV, Straley BA, Donaldson SC, Love BC, Knabel SJ, et al. Antimicrobial-resistant enteric bacteria from dairy cattle. Appl Environ Microbiol. 2007;73:156–63.
Srinivasan V, Gillespie BE, Lewis MJ, Nguyen LT, Headrick SI, Schukken YH, et al. Phenotypic and genotypic antimicrobial resistance patterns of Escherichia coli isolated from dairy cows with mastitis. Vet Microbiol. 2007;124:319–28.
Rajala-Schultz PJ, Smith KL, Hogan JS, Love BC. Antimicrobial susceptibility of mastitis pathogens from first lactation and older cows. Vet Microbiol. 2004;102:33–42.
Luthje P, Schwarz S. Antimicrobial resistance of coagulase-negative staphylococci from bovine subclinical mastitis with particular reference to macrolide-lincosamide resistance phenotypes and genotypes. J Antimicrob Chemother. 2006;57:966–9.
Pitkälä A, Haveri M, Pyörälä S, Myllys V, Honkanen-Buzalski T. Bovine mastitis in Finland 2001—prevalence, distribution of bacteria, and antimicrobial resistance. J Dairy Sci. 2004;87:2433–41.
Guerra B, Junker E, Schroeter A, Malorny B, Lehmann S, Helmuth R. Phenotypic and genotypic characterization of antimicrobial resistance in German Escherichia coli isolates from cattle, swine and poultry. J Antimicrob Chemother. 2003;52:489–92.
Huber H, Ziegler D, Pfluger V, Vogel G, Zweifel C, Stephan R. Prevalence and characteristics of methicillin-resistant coagulase-negative staphylococci from livestock, chicken carcasses, bulk tank milk, minced meat, and contact persons. BMC Vet Res. 2011;7:6.
Vintov J, Aarestrup FM, Zinn CE, Olsen JE. Association between phage types and antimicrobial resistance among bovine Staphylococcus aureus from 10 countries. Vet Microbiol. 2003;95:133–47.
Rajala-Schultz PJ, Torres AH, Degraves FJ, Gebreyes WA, Patchanee P. Antimicrobial resistance and genotypic characterization of coagulase-negative staphylococci over the dry period. Vet Microbiol. 2009;134:55–64.
Bengtsson B, Unnerstad HE, Ekman T, Artursson K, Nilsson-Ost M, Waller KP. Antimicrobial susceptibility of udder pathogens from cases of acute clinical mastitis in dairy cows. Vet Microbiol. 2009;136:142–9.
Snowder GD, Van Vleck LD, Cundiff LV, Bennett GL. Bovine respiratory disease in feedlot cattle: environmental, genetic, and economic factors. J Anim Sci. 2006;84:1999–2008.
Hilton WM. BRD in 2014: where have we been, where are we now, and where do we want to go? Anim Health Res Rev. 2014;15:120–2.
DeDonder KD, Apley MD. A literature review of antimicrobial resistance in Pathogens associated with bovine respiratory disease. Anim Health Res Rev. 2015;16:125–34.
Klima CL, Zaheer R, Cook SR, Booker CW, Hendrick S, Alexander TW, et al. Pathogens of bovine respiratory disease in North American feedlots conferring multidrug resistance via integrative conjugative elements. J Clin Microbiol. 2014;52:438–48.
Goldspink LK, Mollinger JL, Barnes TS, Groves M, Mahony TJ, Gibson JS. Antimicrobial susceptibility of Histophilus somni isolated from clinically affected cattle in Australia. Vet J. 2015;203:239–43.
Maunsell F, Woolums A, Francoz D, Rosenbusch R, Step D, Wilson DJ, et al. Mycoplasma bovis infections in cattle. J Vet Intern Med. 2011;25:772–83.
Rainbolt S, Pillai DK, Lubbers BV, Moore M, Davis R, Amrine D, et al. Comparison of Mannheimia haemolytica isolates from an outbreak of bovine respiratory disease. Vet Microbiol. 2016;182:82–6.
Timsit E, Christensen H, Bareille N, Seegers H, Bisgaard M, Assié S. Transmission dynamics of Mannheimia haemolytica in newly-received beef bulls at fattening operations. Vet Microbiol. 2013;161:295–304.
Lhermie G, Ferran AA, Assie S, Cassard H, El Garch F, Schneider M, et al. Impact of Timing and Dosage of a Fluoroquinolone Treatment on the Microbiological, Pathological, and Clinical Outcomes of Calves Challenged with Mannheimia haemolytica. Front Microbiol. 2016;7:237.
Tennant TC, Ives SE, Harper LB, Renter DG, Lawrence TE. Comparison of tulathromycin and tilmicosin on the prevalence and severity of bovine respiratory disease in feedlot cattle in association with feedlot performance, carcass characteristics, and economic factors. J Anim Sci. 2014;92:5203–13.
Zaheer R, Cook SR, Klima CL, Stanford K, Alexander T, Topp E, et al. Effect of subtherapeutic vs. therapeutic administration of macrolides on antimicrobial resistance in Mannheimia haemolytica and enterococci isolated from beef cattle. Front Microbiol. 2013;4:133.
Noyes NR, Benedict KM, Gow SP, Booker CW, Hannon SJ, McAllister TA, et al. Mannheimia haemolytica in feedlot cattle: prevalence of recovery and associations with antimicrobial use, resistance, and health outcomes. J Vet Intern Med. 2015;29:705–13.
Klima CL, Alexander TW, Hendrick S, McAllister TA. Characterization of Mannheimia haemolytica isolated from feedlot cattle that were healthy or treated for bovine respiratory disease. Can J Vet Res. 2014;78:38–45.
Lubbers BV, Hanzlicek GA. Antimicrobial multidrug resistance and coresistance patterns of Mannheimia haemolytica isolated from bovine respiratory disease cases--a three-year (2009–2011) retrospective analysis. J Vet Diagn Invest. 2013;25:413–7.
Eidam C, Poehlein A, Brenner Michael G, Kadlec K, Liesegang H, Brzuszkiewicz E, et al. Complete Genome Sequence of Mannheimia haemolytica Strain 42548 from a Case of Bovine Respiratory Disease. Genome Announc.201;1(3). pii:e00318-13.
Eidam C, Poehlein A, Leimbach A, Michael GB, Kadlec K, Liesegang H, et al. Analysis and comparative genomics of ICEMh1, a novel integrative and conjugative element (ICE) of Mannheimia haemolytica. J Antimicrob Chemother. 2015;70:93–7.
Michael GB, Kadlec K, Sweeney MT, Brzuszkiewicz E, Liesegang H, Daniel R, et al. ICEPmu1, an integrative conjugative element (ICE) of Pasteurella multocida: analysis of the regions that comprise 12 antimicrobial resistance genes. J Antimicrob Chemother. 2012;67:84–90.
Olsen AS, Warrass R, Douthwaite S. Macrolide resistance conferred by rRNA mutations in field isolates of Mannheimia haemolytica and Pasteurella multocida. J Antimicrob Chemother. 2015;70:420–3.
Desmolaize B, Rose S, Warrass R, Douthwaite S. A novel Erm monomethyltransferase in antibiotic-resistant isolates of Mannheimia haemolytica and Pasteurella multocida. Mol Microbiol. 2011;80:184–94.
Katsuda K, Kohmoto M, Mikami O, Tamamura Y, Uchida I. Plasmid-mediated florfenicol resistance in Mannheimia haemolytica isolated from cattle. Vet Microbiol. 2012;155:444–7.
Laudert S, Vogel G, Parrott J, White D. The effect of two levels of Rumensin on feedlot performance of young Holstein steers fed to slaughter. J Anim Sci. 1994;72:291.
Calcutt MJ, Foecking MF, Nagaraja TG, Stewart GC. Draft Genome Sequence of Fusobacterium necrophorum subsp. funduliforme Bovine Liver Abscess Isolate B35. Genome Announc. 2014;2(2). pii: e00412-14.
Nagaraja T, Beharka A, Chengappa M, Carroll L, Raun A, Laudert S, et al. Bacterial flora of liver abscesses in feedlot cattle fed tylosin or no tylosin. J Anim Sci. 1999;77:973–8.
Brazier J, Hall V, Yusuf E, Duerden B. Fusobacterium necrophorum infections in England and Wales 1990–2000. J Med Microbiol. 2002;51:269–72.
Riordan T. Human infection with Fusobacterium necrophorum (Necrobacillosis), with a focus on Lemierre’s syndrome. Clin Microbiol Rev. 2007;20:622–59.
Jost BH, Billington SJ. Arcanobacterium pyogenes: molecular pathogenesis of an animal opportunist. A Van Leeuw J Microb. 2005;88:87–102.
Jost BH, Trinh HT, Songer JG, Billington SJ. A second tylosin resistance determinant, ErmB, in Arcanobacterium pyogenes. Antimicrob Agents Chemother. 2004;48:721–7.
Jost BH, Field AC, Trinh HT, Songer JG, Billington SJ. Tylosin resistance in Arcanobacterium pyogenes is encoded by an ErmX determinant. Antimicrob Agents Chemother. 2003;47:3519–24.
Zastempowska E, Lassa H. Genotypic characterization and evaluation of an antibiotic resistance of Trueperella pyogenes (Arcanobacterium pyogenes) isolated from milk of dairy cows with clinical mastitis. Vet Microbiol. 2012;161:153–8.
Alkasir R, Wang J, Gao J, Ali T, Zhang L, Szenci O, et al. Properties and antimicrobial susceptibility of Trueperella pyogenes isolated from bovine mastitis in China. Acta Vet Hung. 2016;64:1–12.
Maboni G, Gressler LT, Espindola JP, Schwab M, Tasca C, Potter L, et al. Differences in the antimicrobial susceptibility profiles of Moraxella bovis, M. bovoculi and M. ovis. Braz J Microbiol. 2015;46:545–9.
Dickey AM, Loy JD, Bono JL, Smith TP, Apley MD, Lubbers BV, et al. Large genomic differences between Moraxella bovoculi isolates acquired from the eyes of cattle with infectious bovine keratoconjunctivitis versus the deep nasopharynx of asymptomatic cattle. Vet Res. 2016;47:1.
Prieto C, Serra DO, Martina P, Jacobs M, Bosch A, Yantorno OM. Evaluation of biofilm-forming capacity of Moraxella bovis, the primary causative agent of infectious bovine keratoconjunctivitis. Vet Microbiol. 2013;166:504–15.
Pesavento G, Calonico C, Ducci B, Magnanini A, Nostro AL. Prevalence and antibiotic resistance of Enterococcus spp. isolated from retail cheese, ready-to-eat salads, ham, and raw meat. Food Microbiol. 2014;41:1–7.
World Organisation for Animal Health. OIE-Listed diseases, infections and infestations in force in 2016. 2016.
Cosivi O, Grange J, Daborn C, Raviglione M, Fujikura T, Cousins D, et al. Zoonotic tuberculosis due to Mycobacterium bovis in developing countries. Emerg Infect Dis. 1998;4:59.
Bobadilla-del Valle M, Torres-González P, Cervera-Hernández ME, Martínez-Gamboa A, Crabtree-Ramirez B, Chávez-Mazari B, et al. Trends of Mycobacterium bovis Isolation and First-Line Anti-tuberculosis Drug Susceptibility Profile: A Fifteen-Year Laboratory-Based Surveillance. PLoS Negl Trop Dis. 2015;9:e0004124.
Michel AL, Müller B, Van Helden PD. Mycobacterium bovis at the animal–human interface: A problem, or not? Vet Microbiol. 2010;140:371–81.
Agga GE, Arthur TM, Durso LM, Harhay DM, Schmidt JW. Antimicrobial-resistant bacterial populations and antimicrobial resistance genes obtained from environments impacted by livestock and municipal waste. PLoS One. 2015;10:e0132586.
Cottell JL, Kanwar N, Castillo-Courtade L, Chalmers G, Scott HM, Norby B, et al. blaCTX-M-32 on an IncN plasmid in Escherichia coli from beef cattle in the United States. Antimicrob Agents Chemother. 2013;57:1096–7.
Carattoli A. Resistance plasmid families in Enterobacteriaceae. Antimicrob Agents Chemother. 2009;53:2227–38.
Schmid A, Hörmansdorfer S, Messelhäusser U, Käsbohrer A, Sauter-Louis C, Mansfeld R. Prevalence of extended-spectrum β-lactamase-producing Escherichia coli on Bavarian dairy and beef cattle farms. Appl Environ Microbiol. 2013;79:3027–32.
Geser N, Stephan R, Hächler H. Occurrence and characteristics of extended-spectrum β-lactamase (ESBL) producing Enterobacteriaceae in food producing animals, minced meat and raw milk. BMC Vet Res. 2012;8:1.
Dong P, Zhu L, Mao Y, Liang R, Niu L, Zhang Y, et al. Prevalence and characterization of Escherichia coli O157: H7 from samples along the production line in Chinese beef-processing plants. Food Control. 2015;54:39–46.
Chopyk J, Moore RM, DiSpirito Z, Stromberg ZR, Lewis GL, Renter DG, et al. Presence of pathogenic Escherichia coli is correlated with bacterial community diversity and composition on pre-harvest cattle hides. Microbiome. 2016;4:1.
Elder RO, Keen JE, Siragusa GR, Barkocy-Gallagher GA, Koohmaraie M, Laegreid WW. Correlation of enterohemorrhagic Escherichia coli O157 prevalence in feces, hides, and carcasses of beef cattle during processing. Proc Natl Acad Sci U S A. 2000;97:2999–3003.
Schmidt JW, Agga GE, Bosilevac JM, Brichta-Harhay DM, Shackelford SD, Wang R, et al. Occurrence of antimicrobial-resistant Escherichia coli and Salmonella enterica in the beef cattle production and processing continuum. Appl Environ Microbiol. 2015;81:713–25.
Laufer A, Grass J, Holt K, Whichard J, Griffin P, Gould L. Outbreaks of Salmonella infections attributed to beef–United States, 1973–2011. Epidemiol Infect. 2015;143:2003–13.
US Food and Drug Administration. The 2012–2013 Integrated NARMS Report. National Antimicrobial Resistance Monitoring System. 2015.
Glenn LM, Lindsey RL, Folster JP, Whichard JM, Pecic G, Boerlin P, et al. Antimicrobial resistance genes in multi-drug resistant Salmonella enterica serovars isolated most frequently from animals, retail meat, and humans in the US and Canada. Microb Drug Resist. 2013;19:175.
Barlow RS, McMillan KE, Duffy LL, Fegan N, Jordan D, Mellor GE. Prevalence and Antimicrobial Resistance of Salmonella and Escherichia coli from Australian Cattle Populations at Slaughter. J Food Prot. 2015;78:912–20.
Narvaez-Bravo C, Miller MF, Jackson T, Jackson S, Rodas-Gonzalez A, Pond K, et al. Salmonella and Escherichia coli O157: H7 prevalence in cattle and on carcasses in a vertically integrated feedlot and harvest plant in Mexico. J Food Prot. 2013;76:786–95.
Silva J, Leite D, Fernandes M, Mena C, Gibbs PA, Teixeira P. Campylobacter spp. as a Foodborne Pathogen: A Review. Front Microbiol. 2011;2:200.
Stanley K, Jones K. Cattle and sheep farms as reservoirs of Campylobacter. J Appl Microbiol. 2003;94:104–13.
Haruna M, Sasaki Y, Murakami M, Mori T, Asai T, Ito K, et al. Prevalence and antimicrobial resistance of Campylobacter isolates from beef cattle and pigs in Japan. J Vet Med Sci. 2013;75:625–8.
Jonas R, Kittl S, Overesch G, Kuhnert P. Genotypes and antibiotic resistance of bovine Campylobacter and their contribution to human campylobacteriosis. Epidemiol Infect. 2015;143:2373–80.
Wieczorek K, Denis E, Lynch O, Osek J. Molecular characterization and antibiotic resistance profiling of Campylobacter isolated from cattle in Polish slaughterhouses. Food Microbiol. 2013;34:130–6.
Cattoir V, Leclercq R. Twenty-five years of shared life with vancomycin-resistant enterococci: is it time to divorce? J Antimicrob Chemother. 2013;68:731–42.
Werner G, Coque TM, Franz CM, Grohmann E, Hegstad K, Jensen L, et al. Antibiotic resistant enterococci—tales of a drug resistance gene trafficker. Int J Med Microbiol. 2013;303:360–79.
Jahan M, Holley RA. Transfer of antibiotic resistance from Enterococcus faecium of fermented meat origin to Listeria monocytogenes and Listeria innocua. Lett Appl Microbiol. 2016;62:304–10.
Sparo M, Urbizu L, Solana M, Pourcel G, Delpech G, Confalonieri A, et al. High‐level resistance to gentamicin: genetic transfer between Enterococcus faecalis isolated from food of animal origin and human microbiota. Lett Appl Microbiol. 2012;54:119–25.
Różańska H, Lewtak-Piłat A, Osek J. Antimicrobial resistance of Enterococcus faecalis isolated from meat. Bull Vet Inst Pulawy. 2015;59:229–33.
Aslam M, Diarra MS, Checkley S, Bohaychuk V, Masson L. Characterization of antimicrobial resistance and virulence genes in Enterococcus spp. isolated from retail meats in Alberta, Canada. Int J Food Microbiol. 2012;156:222–30.
Hungate RE. The rumen and its microbes. Elsevier. 2013.
Durso L, Wells JE, Kim MS. Diversity of Microbiomes in Beef Cattle. In: S. K. Highlander, F. Rodriguez-Valera and B. A. White (eds.) Encyclopedia of Metagenomics: Environmental Metagenomics. Boston: Springer; 2015. p. 129-138.
Kim M, Wells JE. A Meta-analysis of Bacterial Diversity in the Feces of Cattle. Curr Microbiol. 2016;72:145–51.
Li RW, Connor EE, Li C, Baldwin V, Ransom L, Sparks ME. Characterization of the rumen microbiota of pre‐ruminant calves using metagenomic tools. Environ Microbiol. 2012;14:129–39.
Henderson G, Cox F, Ganesh S, Jonker A, Young W, Collaborators GRC, et al. Rumen microbial community composition varies with diet and host, but a core microbiome is found across a wide geographical range. Sci Rep. 2015;5:14567.
Jami E, Mizrahi I. Composition and similarity of bovine rumen microbiota across individual animals. PLoS One. 2012;7:e33306.
Holman DB, Timsit E, Alexander TW. The nasopharyngeal microbiota of feedlot cattle. Sci Rep. 2015;5:15557.
Swartz JD, Lachman M, Westveer K, O’Neill T, Geary T, Kott RW, et al. Characterization of the vaginal microbiota of ewes and cows reveals a unique microbiota with low levels of lactobacilli and near-neutral pH. Front Vet Sci. 2014;1:19.
Myer P, Wells J, Smith T, Kuehn L, Freetly H. Microbial community profiles of the jejunum from steers differing in feed efficiency. J Anim Sci. 2016;94:327–38.
Jami E, White BA, Mizrahi I. Potential role of the bovine rumen microbiome in modulating milk composition and feed efficiency. PLoS One. 2014;9:e85423.
Reti KL, Thomas MC, Yanke LJ, Selinger LB, Inglis GD. Effect of antimicrobial growth promoter administration on the intestinal microbiota of beef cattle. Gut Pathog. 2013;5:1.
Pereira RVV, Lima S, Siler JD, Foditsch C, Warnick LD, Bicalho RC. Ingestion of Milk Containing Very Low Concentration of Antimicrobials: Longitudinal Effect on Fecal Microbiota Composition in Preweaned Calves. PLoS One. 2016;11:e0147525.
Kanwar N, Scott HM, Norby B, Loneragan GH, Vinasco J, Cottell JL, et al. Impact of treatment strategies on cephalosporin and tetracycline resistance gene quantities in the bovine fecal metagenome. Sci Rep. 2014;4:5100.
Chambers L, Yang Y, Littier H, Ray P, Zhang T, Pruden A, et al. Metagenomic Analysis of Antibiotic Resistance Genes in Dairy Cow Feces following Therapeutic Administration of Third Generation Cephalosporin. PLoS One. 2015;10:e0133764.
Liu B, Pop M. ARDB--Antibiotic Resistance Genes Database. Nucleic Acids Res. 2009;37:D443–7.
Iwahara K, Kuriyama T, Shimura S, Williams DW, Yanagisawa M, Nakagawa K, et al. Detection of cfxA and cfxA2, the beta-lactamase genes of Prevotella spp., in clinical samples from dentoalveolar infection by real-time PCR. J Clin Microbiol. 2006;44:172–6.
Meyer F, Paarmann D, D’Souza M, Olson R, Glass EM, Kubal M, et al. The metagenomics RAST server - a public resource for the automatic phylogenetic and functional analysis of metagenomes. BMC Bioinformatics. 2008;9:386.
Alexander T, Inglis G, Yanke L, Topp E, Read R, Reuter T, et al. Farm-to-fork characterization of Escherichia coli associated with feedlot cattle with a known history of antimicrobial use. Int J Food Microbiol. 2010;137:40–8.
Alexander T, Yanke L, Topp E, Olson M, Read R, Morck D, et al. Effect of subtherapeutic administration of antibiotics on the prevalence of antibiotic-resistant Escherichia coli bacteria in feedlot cattle. Appl Environ Microbiol. 2008;74:4405–16.
Beukers AG, Zaheer R, Cook SR, Stanford K, Chaves AV, Ward MP, et al. Effect of in-feed administration and withdrawal of tylosin phosphate on antibiotic resistance in enterococci isolated from feedlot steers. Front Microbiol. 2015;6:483.
Catry B, Dewulf J, Maes D, Pardon B, Callens B, Vanrobaeys M, et al. Effect of Antimicrobial Consumption and Production Type on Antibacterial Resistance in the Bovine Respiratory and Digestive Tract. PLoS One. 2016;11:e0146488.
Varga C, Rajic A, McFall ME, Reid-Smith RJ, Deckert AE, Checkley SL, et al. Associations between reported on-farm antimicrobial use practices and observed antimicrobial resistance in generic fecal Escherichia coli isolated from Alberta finishing swine farms. Prev Vet Med. 2009;88:185–92.
Zhang L, Huang Y, Zhou Y, Buckley T, Wang HH. Antibiotic administration routes significantly influence the levels of antibiotic resistance in gut microbiota. Antimicrob Agents Chemother. 2013;57:3659–66.
Benedict KM, Gow SP, McAllister TA, Booker CW, Hannon SJ, Checkley SL, et al. Antimicrobial Resistance in Escherichia coli Recovered from Feedlot Cattle and Associations with Antimicrobial Use. PLoS One. 2015;10:e0143995.
Ahola J, Baker D, Burns P, Mortimer R, Enns R, Whittier J, et al. Effect of copper, zinc, and manganese supplementation and source on reproduction, mineral status, and performance in grazing beef cattle over a two-year period. J Anim Sci. 2004;82:2375–83.
Enjalbert F, Lebreton P, Salat O. Effects of copper, zinc and selenium status on performance and health in commercial dairy and beef herds: retrospective study. J Anim Physiol Anim Nutr. 2006;90:459–66.
Holman DB, Chenier MR. Antimicrobial use in swine production and its effect on the swine gut microbiota and antimicrobial resistance. Can J Microbiol. 2015;61:785–98.
Michael GB, Kadlec K, Sweeney MT, Brzuszkiewicz E, Liesegang H, Daniel R, et al. ICEPmu1, an integrative conjugative element (ICE) of Pasteurella multocida: structure and transfer. J Antimicrob Chemother. 2012;67:91–100.
Jacob ME, Fox JT, Nagaraja T, Drouillard JS, Amachawadi RG, Narayanan SK. Effects of feeding elevated concentrations of copper and zinc on the antimicrobial susceptibilities of fecal bacteria in feedlot cattle. Foodborne Pathog Dis. 2010;7:643–8.
Amachawadi R, Scott H, Aperce C, Vinasco J, Drouillard J, Nagaraja T. Effects of in‐feed copper and tylosin supplementations on copper and antimicrobial resistance in faecal enterococci of feedlot cattle. J Appl Microbiol. 2015;118:1287–97.
Hasman H. Aarestrup FM: tcrB, a gene conferring transferable copper resistance in Enterococcus faecium: occurrence, transferability, and linkage to macrolide and glycopeptide resistance. Antimicrob Agents Chemother. 2002;46:1410–6.
Capper JL. The environmental impact of beef production in the United States: 1977 compared with 2007. J Anim Sci. 2011;89:4249–61.
Nesme J, Cécillon S, Delmont TO, Monier J-M, Vogel TM, Simonet P. Large-scale metagenomic-based study of antibiotic resistance in the environment. Curr Biol. 2014;24:1096–100.
McArthur AG, Waglechner N, Nizam F, Yan A, Azad MA, Baylay AJ, et al. The comprehensive antibiotic resistance database. Antimicrob Agents Chemother. 2013;57:3348–57.
Noyes NR, Yang X, Linke LM, Magnuson RJ, Dettenwanger A, Cook S, et al. Resistome diversity in cattle and the environment decreases during beef production. ELife. 2016;5:e13195.
Zankari E, Hasman H, Cosentino S, Vestergaard M, Rasmussen S, Lund O, et al. Identification of acquired antimicrobial resistance genes. J Antimicrob Chemother. 2012;67:2640–4.
Gupta SK, Padmanabhan BR, Diene SM, Lopez-Rojas R, Kempf M, Landraud L, et al. ARG-ANNOT, a new bioinformatic tool to discover antibiotic resistance genes in bacterial genomes. Antimicrob Agents Chemother. 2014;58:212–20.
Zhang T, Shao M-F, Ye L. 454 Pyrosequencing reveals bacterial diversity of activated sludge from 14 sewage treatment plants. ISME J. 2012;6:1137–47.
Grady Jr CL, Daigger GT, Love NG, Filipe CD: Biological wastewater treatment. CRC press; 2011.
Wang Z, Zhang X-X, Huang K, Miao Y, Shi P, Liu B, et al. Metagenomic profiling of antibiotic resistance genes and mobile genetic elements in a tannery wastewater treatment plant. PLoS One. 2013;8:e76079.
Li A-D, Li L-G, Zhang T. Exploring antibiotic resistance genes and metal resistance genes in plasmid metagenomes from wastewater treatment plants. Front Microbiol. 2015;6:1025.
Krzywinski M, Schein J, Birol I, Connors J, Gascoyne R, Horsman D, et al. Circos: an information aesthetic for comparative genomics. Genome Res. 2009;19:1639–45.
Wichmann F, Udikovic-Kolic N, Andrew S, Handelsman J. Diverse antibiotic resistance genes in dairy cow manure. MBio. 2014;5:e01017–01013.
Colomer-Lluch M, Imamovic L, Jofre J, Muniesa M. Bacteriophages carrying antibiotic resistance genes in fecal waste from cattle, pigs, and poultry. Antimicrob Agents Chemother. 2011;55:4908–11.
Dantas G, Sommer MO. Context matters—the complex interplay between resistome genotypes and resistance phenotypes. Curr Opin Microbiol. 2012;15:577–82.
Baquero F, Alvarez‐Ortega C, Martinez J. Ecology and evolution of antibiotic resistance. Environ Microbiol. 2009;1:469–76.
Martinez JL, Coque TM, Baquero F. Prioritizing risks of antibiotic resistance genes in all metagenomes. Nat Rev Microbiol. 2015;13:396.
Bengtsson-Palme J, Larsson DG. Antibiotic resistance genes in the environment: prioritizing risks. Nat Rev Microbiol. 2015;13:396.
Liu Y-Y, Wang Y, Walsh TR, Yi L-X, Zhang R, Spencer J, et al. Emergence of plasmid-mediated colistin resistance mechanism MCR-1 in animals and human beings in China: a microbiological and molecular biological study. Lancet Infect Dis. 2016;16:161-168.
Hasman H, Hammerum A, Hansen F, Hendriksen RS, Olesen B, Agersø Y, et al. Detection of mcr-1 encoding plasmid-mediated colistin-resistant Escherichia coli isolates from human bloodstream infection and imported chicken meat, Denmark 2015. Euro Surveill. 2015;20:1–5.
Holmberg SD, Osterholm MT, Senger KA, Cohen ML. Drug-resistant Salmonella from animals fed antimicrobials. N Engl J Med. 1984;311:617–22.
Cloeckaert A, Schwarz S. Molecular characterization, spread and evolution of multidrug resistance in Salmonella enterica Typhimurium DT104. Vet Res. 2001;32:301–10.
Davies A, O’neill P, Towers L, Cooke M. An outbreak of Salmonella typhimurium DT104 food poisoning associated with eating beef. Commun Dis Rep CDR Rev. 1996;6:R159–62.
dos Reis EM, Ddos Rodrigues P, de Freitas-Almeida AC, Hofer E. Prevalence of R-type ACSSuT in strains of Salmonella serovar Typhimurium DT193 isolated from human infections in Brazil. Rev Panam Salud Publica. 2011;29:387–92.
Mazel D. Integrons: agents of bacterial evolution. Nat Rev Microbiol. 2006;4:608–20.
Schmieger H, Schicklmaier P. Transduction of multiple drug resistance of Salmonella enterica serovar Typhimurium DT104. FEMS Microbiol Lett. 1999;170:251–6.
Mather AE, Denwood MJ, Haydon DT, Matthews L, Mellor DJ, Coia JE, et al. The prevalences of Salmonella genomic island 1 variants in human and animal Salmonella Typhimurium DT104 are distinguishable using a Bayesian Approach. PLoS One. 2011;6:e27220.
Mather A, Reid S, Maskell D, Parkhill J, Fookes M, Harris S, et al. Distinguishable epidemics of multidrug-resistant Salmonella Typhimurium DT104 in different hosts. Science. 2013;341:1514–7.
Winokur P, Vonstein D, Hoffman L, Uhlenhopp E, Doern G. Evidence for Transfer of CMY-2 AmpC β-Lactamase Plasmids between Escherichia coli and Salmonella Isolates from Food Animals and Humans. Antimicrob Agents Chemother. 2001;45:2716–22.
Harrison EM, Paterson GK, Holden MT, Larsen J, Stegger M, Larsen AR, et al. Whole genome sequencing identifies zoonotic transmission of MRSA isolates with the novel mecA homologue mecC. EMBO Mol Med. 2013;5:509–15.
Afema J, Mather A, Sischo W. Antimicrobial resistance profiles and diversity in Salmonella from humans and cattle, 2004–2011. Zoonoses Public Health. 2015;62:506–17.
Dechet AM, Scallan E, Gensheimer K, Hoekstra R, Gunderman-King J, Lockett J, et al. Outbreak of multidrug-resistant Salmonella enterica serotype Typhimurium definitive type 104 infection linked to commercial ground beef, northeastern United States, 2003–2004. Clin Infect Dis. 2006;42:747–52.
Marshall BM, Levy SB. Food animals and antimicrobials: impacts on human health. Clin Microbiol Rev. 2011;24:718–33.
Werber D, Fruth A, Liesegang A, Littmann M, Buchholz U, Prager R, et al. A multistate outbreak of Shiga toxin–producing Escherichia coli O26: H11 infections in Germany, detected by molecular subtyping surveillance. J Infect Dis. 2002;186:419–22.
Fey PD, Safranek TJ, Rupp ME, Dunne EF, Ribot E, Iwen PC, et al. Ceftriaxone-resistant Salmonella infection acquired by a child from cattle. N Engl J Med. 2000;342:1242–9.
Graveland H, Wagenaar JA, Heesterbeek H, Mevius D, Van Duijkeren E, Heederik D. Methicillin resistant Staphylococcus aureus ST398 in veal calf farming: human MRSA carriage related with animal antimicrobial usage and farm hygiene. PLoS One. 2010;5:e10990.
Klous G, Huss A, Heederik DJ, Coutinho RA. Human–livestock contacts and their relationship to transmission of zoonotic pathogens, a systematic review of literature. One Health. 2016;2:65–76.
Thames CH, Pruden A, James RE, Ray PP, Knowlton KF. Excretion of antibiotic resistance genes by dairy calves fed milk replacers with varying doses of antibiotics. Front Microbiol. 2012;3:139.
Hanssen A-M, Sollid JUE. SCCmec in staphylococci: genes on the move. FEMS Immunol Med Microbiol. 2006;46:8–20.
AC is supported by an NSERC Postdoctoral Fellowship and the program as a whole is supported by the Beef Cattle Research Council BCRC – Agriculture and Agri-Food Canada beef cluster.
Availability of data and materials
AC and TAM researched and co-wrote the review. Both authors read and approved the final manuscript.
The authors declare that they have no competing interests.
Consent for publication
About this article
Cite this article
Cameron, A., McAllister, T.A. Antimicrobial usage and resistance in beef production. J Animal Sci Biotechnol 7, 68 (2016). https://doi.org/10.1186/s40104-016-0127-3
- Antimicrobial resistance
- Antimicrobial usage
- Beef production
- Bovine pathogens
- Bovine microbiota
- Fecal bacteria