Prevalence of antibiotic resistance genes in faecal samples from cattle, pigs and poultry

0
0
7
1 week ago
PDF Preview
Full text
(1)Original Paper. Veterinarni Medicina, 58, 2013: (6): 298–304. Prevalence of antibiotic resistance genes in faecal samples from cattle, pigs and poultry M. Faldynova1, P. Videnska1, H. Havlickova1, F. Sisak1, H. Juricova1, V. Babak1, L. Steinhauser2, I. Rychlik1 1. Veterinary Research Institute, Brno, Czech Republic Faculty of Veterinary Medicine, University of Veterinary and Pharmaceutical Sciences, Brno, Czech Republic. 2. ABSTRACT: Antibiotic resistant bacteria can be easily isolated from the faeces of cattle, pigs or poultry. However, whether the production of different farm animals is associated with a higher or lower prevalence of antibiotic resistance is not clear. In this study we therefore used real time PCR for the quantification of antibiotic gene prevalence in the DNA purified from the faeces of farm animals. First we showed that experimental streptomycin therapy of 12-week-old chickens and 46-week-old hens significantly increased the relative prevalence of strA and sul2 genes though this did not necessarily indicate an absolute increase of strA-encoding bacteria. Next we quantified antibiotic gene prevalence in the DNA purified from the faeces of cattle, pigs and laying hens. The lowest prevalence of strA, aadA, sul1, sul2, tet(A), tet(B), tet(G) and cat genes was recorded in the intestinal contents of laying hens. In cattle and pig faecal samples, an intermediate prevalence of antibiotic resistance genes was observed with strA and sul2 dominating by two logs over the remaining six tested genes. The differences in strA and sul2 prevalence between cattle and pig microbiota were not significant whilst the prevalence of strA and sul2 in laying hen microbiota was significantly lower than in the other two species. Cattle and pig production systems may therefore represent a more important reservoir of antibiotic resistant bacteria than laying hens. Keywords: real time PCR; antibiotic resistance; farm animals; chicken; pig; cattle. Acquired antibiotic resistance in bacteria is reaching alarming levels. Nowadays, acquired resistance can be found in pathogenic bacteria as well as in commensal bacteria, despite the fact that the latter population is never intentionally targeted by antimicrobial treatment. The antibiotic resistance genes in commensal bacteria represent a reservoir from which these genes can be disseminated into different recipients even in the absence of antibiotic therapy (Nikolich et al. 1994). Even though antibiotic resistant clones are underrepresented in the microbiomes of healthy individuals, such clones are immediately positively selected for when an individual is subjected to antibiotic therapy.. Antibiotic resistance genes can be found associated with genetic elements of varying mobility. Conjugative plasmids can spread easily across bacterial populations (Sunde and Norstrom 2006; Hradecka et al. 2008), whilst genetic elements such as Salmonella genomic island 1 are mobilised for transfer at a significantly lower frequency (Doublet et al. 2005). Despite this, the mobility of elements transferring antibiotic resistance is not limited by species or genus and genetic elements with the same antibiotic resistance genes can be found across a broad range of different bacterial species. A simple way to assess the range of antibiotic resistance in complex bacterial populations is by. Supported by the SafeOrganic Project, PROMISE Project of the 7th Framework Programme of EU, the Ministry of Education, Youth and Sports of the Czech Republic (AdmireVet; Grant No. CZ 1.05/2.1.00/01.0006-ED 0006/01/01), and the Ministry of Agriculture of the Czech Republic (Grant No. MZE 0002716202).. 298.

(2) Veterinarni Medicina, 58, 2013 (6): 298–304 bacterial culture on nutrient agars with and without antibiotics followed by a comparison of the numbers of total and resistant colonies. For many purposes, this strategy is the most appropriate. However, it only provides information for the antibiotic resistance of bacterial species which are capable of growth under given culture conditions and not for those which may require different culture conditions. This is why culture-independent techniques such as quantitative real-time PCR are used for the characterisation of the prevalence of a particular gene in a given bacterial community (Yu et al. 2005; Chen et al. 2007). This experimental approach is especially useful for the quantification of antibiotic resistance genes in faecal microbiota, where the population is quite dense allowing for frequent horizontal gene transfer (Nikolich et al. 1994). Antibiotic resistance poses a serious problem that is difficult to overcome. Prudent use of antibiotics and/or ecological farming may lead to a decrease in the prevalence of antibiotic resistance genes in bacterial populations (Young et al. 2009). However, although the recommendation of the prudent use of antibiotics may appear simple, the actual logistical and associated costs might be quite high (Salyers and Amabile-Cuevas 1997; Andersson and Hughes 2010). Animal production is commonly associated with large-scale use of antibiotics and is therefore considered as one of the major sources of new combinations of antibiotic resistance. Although it is quite simple to isolate multidrug resistant bacteria from the faeces of farm animals, this neither provides information on their quantitative representation, nor allows for the comparison between different farm animals. In this study we therefore tested whether some animal production systems represent reservoirs of antibiotic resistant bacteria more so than others. Furthermore, to avoid any bias potentially introduced by bacterial culture, we selected eight different target genes known to be responsible for antibiotic resistance and quantified their prevalence by real time PCR. In doing this we quantified and compared the prevalence of antibiotic resistance genes in the faecal microbiomes of cattle, pigs and egg-laying hens. We found that the prevalence of strA and sul2 in cattle and pig faecal microbiota were significantly higher than in laying hen microbiota and cattle and pig production systems therefore represent a more important reservoir and source of antibiotic resistant bacteria than egg production.. Original Paper MATERIAL AND METHODS Sample characterisation. Altogether 34 cattle (24 meat type bulls and 10 cows of dairy cattle) and 39 pig samples were collected from the rectum immediately after slaughter in 2011. Seventy-seven laying hen samples were collected as fresh faecal droppings from four egg laying hen farms over a period of three years between 2009 and 2011 in the Czech Republic. DNA purification and real time PCR. DNA was extracted using the QIAamp DNA Stool Mini Kit according to the manufacturer’s instructions (Qiagen) and stored at –20 °C until use. Two sets of primers were used in real time PCR; those targeted at selected bacterial taxa and those targeted at selected antibiotic resistance genes. Taxon-specific primers were designed from the variable regions of 16S rRNA genes with PRIMROSE software (http:// www.cardiff.ac.uk/biosi/research/biosoft/), and the specificity of the primers was verified using the RDP ProbeMatch program. The primers for quantification of the antibiotic resistance genes were designed using Primer3 software (Rozen and Skaletsky 2000). Finally, two primer pairs specific for the conserved regions of 16S rRNA genes (domain Bacteria-universal primer pairs) served to determine the total bacterial DNA present in these samples (Table 1). Real-time PCR was carried out using the QuantiTect SYBR Green PCR Kit (Qiagen) in a LightCycler LC480 thermocycler (Roche). After PCR, the Ct values of the genes of interest were subtracted from an average Ct value of amplifications performed with the domain Bacteria-universal primers (∆Ct). The relative frequency of each taxon or antibiotic resistance gene in the total bacterial population was finally calculated as 2–∆Ct. Streptomycin therapy of chickens. Chickens were obtained from a farm with no history of antibiotic use. Daily water consumption was determined during the first days of their adaptation to the new environment and the determined daily water consumption was used to provide chickens with streptomycin in the drinking water at such a concentration that the daily uptake was equivalent to 15 mg of streptomycin per kg of body weight. In the first experiment, five 12-week-old chickens were administered streptomycin in the drinking water for seven days. In the second experiment, five 46-week-old hens were subjected to streptomycin therapy for two days only. Faecal samples 299.

(3) Original Paper. Veterinarni Medicina, 58, 2013: (6): 298–304. Table 1. List of primers used in this study Primer. Target. Sequence 5'-3'. Reference. StrA-F. strA. CCAGTTCTCTTCGGCGTTAG. this study. StrA-R. strA. ACTCTTCAATGCACGGGTCT. this study. AadA-F. aadA2. CAG CCC GTC TTA CTT GAA GC. this study. AadA-R. aadA2. GAT CTC GCC TTT CAC AAA GC. this study. TetB-F. tetB. TACAGGGATTATTGGTGAGC. this study. TetB-R. tetB. ACATGAAGGTCATCGATAGC. this study. TetA-F. tetA. CGA TCT TCC AAG CGT TTG TT. this study. TetA-R. tetA. CCA GAA GAA CGA AGC CAG TC. this study. TetG-F. tetG. GTG TTC CCG ATT CTG TTG CT. this study. TetG-R. tetG. GAT TGG TGA GGC TCG TTA GC. this study. Cat-F. cat1. TCC ATG AGC AAA CTG AAA CG. this study. Cat-R. cat1. GGG AAA TAG GCC AGG TTT TC. this study. Sul1-F. sul1. GGATCAGACGTCGTGGATGT. this study. Sul1-R. sul1. GTCTAAGAGCGGCGCAATAC. this study. Sul2-F. sul2. CGCAATGTGATCCATGATGT. this study. Sul2-R. sul2. GCGAAATCATCTGCCAAACT. this study. 16S_Bifido-F. Bifidobacteriales. GGTGTGAAAGTCCATCG. Juricova et al. 2013. 16S_Bifido-R. Bifidobacteriales. ACCGGGAATTCCAGTCT. Juricova et al. 2013. 16S_Clost-F. Clostridiales. GCGTTATCCGGATTTAC. Juricova et al. 2013. 16S_Clost-R. Clostridiales. ACACCTAGTATTCATCG. Juricova et al. 2013. 16S_Entero-F. Enterobacteriales. STGAGACAGGTGCTGCA. Juricova et al. 2013. 16S_Entero-R. Enterobacteriales. AAAGGATAAGGGTTGCG. Juricova et al. 2013. 16S_Lacto-F. Lactobacillales. CTTGAGTGCAGAAGAGG. Juricova et al. 2013. 16S_Lacto-R. Lactobacillales. CACTGGTGTTCTTCCAT. Juricova et al. 2013. 16S_univ-1F. all bacteria. GTGSTGCAYGGYTGTCGTCA. Maeda et al. 2003. 16S_univ-1R. all bacteria. ACGTCRTCCMCACCTTCCTC. Maeda et al. 2003. 16S_univ-2F. all bacteria. GAGGAAGGIGIGGAIGACGT. Tseng et al. 2003. 16S_univ-2R. all bacteria. AGICCCGIGAACGTATTCAC. Tseng et al. 2003. were collected individually from each chicken. The first sampling was performed just prior to streptomycin administration (day 0) followed by sampling on days 1, 2, 3, 4, 7, 8, 9, 10, 11 and 14. The handling of animals in the study was performed in accordance with current Czech legislation (Animal protection and welfare Act No. 246/1992 Coll. of the Government of the Czech Republic). Statistics. ANOVA followed by Tukey’s post hoc test was used for the comparison of antibiotic resistance gene prevalence in the microbiome of different animal species. ANOVA followed by Dunnet’s test post hoc test was used for evaluating the statistical significance in the experiments where streptomycin was administered to chickens. 300. RESULTS Quantification of antibiotic resistance gene prevalence by real time PCR The lowest antibiotic gene prevalence was recorded in the intestinal contents of laying hens. Real time PCR quantification indicated that strA or sul2 was present in 20 or 8 out of 100 000 bacteria in the laying hen faecal microbiomes, respectively. In cattle and pig faecal samples, an intermediate level of prevalence for these two antibiotic resistance genes was observed (Figure 1). In the faecal microbiomes of these animals, strA and sul2 dominated over the remaining six tested antibiotic re-.

(4) reached 0.40% in the samples originating from the cattle, 1.04% in pigs and 0.80% laying hens (Figure 2). The Enterobacteriales prevalence among the samples therefore cannot explain the lower prevalence of strA and sul2 in laying hen samples when compared with those from cattle and pigs.. Poultry. Figure 1. Real time PCR quantification of the prevalence of antibiotic resistance genes in faecal material from cattle, pigs and poultry. Asterisks indicate antibiotic resistance genes significantly differing in their prevalence of the same gene in poultry samples. sistance genes such as sul1, tet(A), tet(B), tet(G), aadA and cat. The genes strA and sul2 were estimated to be present in 5 to 30 out of 10 000 bacteria indicating an approximately 10 times higher relative prevalence than in laying hen samples. When cattle, pig and laying hen samples were compared for the relative prevalence of strA and sul2, the differences in strA and sul2 antibiotic gene prevalence between cattle and pig microbiota were not significant whilst the laying hen microbiota was a significantly less important reservoir of strA and sul2 (P < 0.05) than microbiota of the former two farm animal species (Figure 1).. Quantification of key bacterial taxa present in analysed samples Since we initially expected that the antibiotic resistance genes targeted in real time PCR were commonly found in Enterobacteriales (Sunde and Norstrom 2006; Karczmarczyk et al. 2011; Soufi et al. 2011), enrichment of some of the samples for Enterobacteriales could affect the final results. In the next experiment we therefore tested the composition of bacterial taxa (Clostridiales, Lactobacillales, Enterobacteriales, Bifidobacteriales) present in the faecal DNA by taxon-specific real time PCR. In cattle samples, Clostridiales dominated over the remaining orders. In pig samples, Clostridiales and Lactobacillales were present at a similar prevalence, significantly higher than Enterobacteriales or Bifidobacteriales. In laying hen samples, Lactobacillales dominated over the remaining three orders. The relative prevalence of Enterobacteriales. The different prevalence of antibiotic resistance genes observed in the cattle, pig and laying hen samples prompted us to test to what extent this could be influenced by a recently administered antibiotic therapy. To test this we treated chickens with streptomycin in two independent experiments. In the first experiment, chickens were treated for seven days whilst in the second experiment the antibiotic administration lasted for two days only. In both experiments, a rapid increase in the prevalence of strA and sul2 genes was recorded. In addition, the prevalence of the sul1 gene increased in the second experiment. The increase in strA and sul2 prevalence reached statistical significance on day 2 and 4 when compared with day 0 in the first experiment. In the second experiment, the sul2 and sul1 prevalence increased significantly on day 3 and 4 when compared with day 0, respectively. Streptomycin therapy therefore not only increased the prevalence of strA-encoding streptomycin phosphotransferase responsible for the resistance to streptomycin, but 0.12. a. a. 0.10 a. 0.08 0.06. a. 0.04 0.02 0. b. b b b. b. Cattle. c. c. Pig. Bifidob. Pigs. b. Clostrid Enterob Lactob. Cattle. Influence of streptomycin therapy on the presence of antibiotic resistance genes in the faeces of chickens. Bifidob. 0. * strA sul1 sul2 tetB tetA cat aadA tetG. 0.002. *. strA sul1 sul2 tetB tetA cat aadA tetG. 0.004. Clostrid Enterob Lactob. 0.006. Bifidob. *. 0.008. Clostrid Enterob Lactob. *. 0.010. Original Paper. Relative taxon prevalence. 0.012. strA sul1 sul2 tetB tetA cat aadA tetG. Relative gene prevalence. Veterinarni Medicina, 58, 2013 (6): 298–304. Poultry. Figure 2. Taxon composition in faecal material from cattle, pigs and poultry determined by real time PCR. Indices indicate microbiota members not differing in prevalence from each other but differing from the remaining microbiota members within the same animal samples. 301.

(5) Original Paper. Veterinarni Medicina, 58, 2013: (6): 298–304 0.04. strA sul1. Relative gene prevalence. 0.3. tetB sul2. 0.03 0.2. 0.02. * 0.1. *. 0.01. * 0. * 0. 0. 5. Day of live. 10. 15. 0. 5. 10. 15. Day of live. Figure 3. Influence of streptomycin therapy on the prevalence of antibiotic resistance genes in faecal DNA determined by real time PCR. Left panel, the first experiment with 7-day-long therapy. Right panel, the second experiment with 2-daylong therapy. Asterisks indicate a significant difference in gene prevalence when compared with day 0. resulted also in the co-selection of “non-target” genes such as sul2 in the first experiment, and sul1 and sul2 in the second experiment, both encoding resistance to sulphonamides (Figure 3).. DISCUSSION In this study we were interested in the prevalence of antibiotic resistance genes in faecal material from cattle, pigs and laying hens originating from the Czech Republic. When the farm animals were compared among each other, the highest prevalence of the antibiotic resistance genes targeted in this study was found in the faecal microbiota of pigs, followed by cattle and laying hens. There was a notable numeric difference between the pig and cattle samples, but this did not reach statistical significance. However, this difference corresponded with the observations of Yu et al. who reported a slightly higher prevalence of tetracycline resistance genes in pig faecal samples than in those from cattle (Yu et al. 2005). On the other hand, the prevalence of strA and sul2 in the faecal microbiota of egglaying hens was significantly lower than in pigs or cattle and therefore egg production can be considered as a lower risk for the selection and shedding of antibiotic-resistant bacteria. The antibiotic resistance genes that were targeted consisted of those commonly present in Enterobacteriales (Faldynova et al. 2003; Hradecka et al. 2008; Havlickova et al. 2009). The expected association of the target genes with a particular 302. order was the reason why we also monitored the presence of selected bacterial taxa in the collected samples. Since the prevalence of Enterobacteriales was similar in all the samples ranging from 0.4 to 1.08 %, this difference could not explain the difference in the antibiotic resistance gene prevalence. In the second part of this study, we tested to what extent recent antibiotic therapy may influence the relative gene prevalence in faecal samples. Experimental streptomycin therapy in chickens increased the prevalence of the strA gene so that one or 15 out of 100 bacteria in the chicken faecal microbiomes harboured strA in their genome in the experiment 1 or 2, respectively. Interestingly, streptomycin therapy also increased the prevalence of genes coding for sulfonamide resistance in both experiments, which is likely due to the common presence of strA and sul2 genes on the same genetic elements (Sunde and Norstrom 2006; Hradecka et al. 2008). However, it has to be noted that the increases reported in this study may not necessarily correlate with an absolute increase of strA-encoding bacteria. If streptomycin killed streptomycinsusceptible bacteria but left the strA-positive ones unaffected, the latter will increase in proportion but not in actual numbers. Interestingly, the remission of antibiotic resistance gene prevalence after therapy withdrawal was nearly as rapid as the increase immediately after the therapies, similar to the total microbiota restoration soon after antibiotic withdrawal as reported elsewhere (Antonopoulos et al. 2009; Jernberg et al. 2010; Videnska et al. 2013). This could be caused by a positive selection.

(6) Veterinarni Medicina, 58, 2013 (6): 298–304 of streptomycin-resistant bacteria not harbouring the strA gene dependent mode of resistance during the course of therapy and/or rapid multiplication of antibiotic-susceptible bacteria soon after streptomycin withdrawal. Unfortunately, this phenomenon makes the use of real time PCR quantification of these antibiotic resistance genes less suitable for assessment of recent antibiotic use in these animal species.. Acknowledgement The authors would like to thank Peter Eggenhuizen (Monash Medical Centre, Australia) for his English language corrections.. REFERENCES Andersson DI, Hughes D (2010): Antibiotic resistance and its cost: is it possible to reverse resistance? Nature Reviews Microbiology 8, 260–271. Antonopoulos DA, Huse SM, Morrison HG, Schmidt TM, Sogin ML, Young VB (2009): Reproducible community dynamics of the gastrointestinal microbiota following antibiotic perturbation. Infection and Immunity 77, 2367–2375. Chen J, Yu Z, Michel FC, Jr., Wittum T, Morrison M (2007): Development and application of real-time PCR assays for quantification of erm genes conferring resistance to macrolides-lincosamides-streptogramin B in livestock manure and manure management systems. Applied and Environmental Microbiology 73, 4407–4416. Doublet B, Boyd D, Mulvey MR, Cloeckaert A (2005): The Salmonella genomic island 1 is an integrative mobilizable element. Molecular Microbiology 55, 1911–1924. Faldynova M, Pravcova M, Sisak F, Havlickova H, Kolackova I, Cizek A, Karpiskova R, Rychlik I (2003): Evolution of antibiotic resistance in Salmonella enterica serovar Typhimurium strains isolated in the Czech Republic between 1984 and 2002. Antimicrobial Agents and Chemotherapy 47, 2002–2005. Havlickova H, Hradecka H, Bernardyova I, Rychlik I (2009): Distribution of integrons and SGI1 among antibiotic-resistant Salmonella enterica isolates of animal origin. Veterinary Microbiology 133, 193–198. Hradecka H, Karasova D, Rychlik I (2008): Characterization of Salmonella enterica serovar Typhimurium conjugative plasmids transferring resistance to antibiotics and their interaction with the virulence plasmid. Journal of Antimicrobial Chemotherapy 62, 938–941.. Original Paper Jernberg C, Lofmark S, Edlund C, Jansson JK (2010): Long-term impacts of antibiotic exposure on the human intestinal microbiota. Microbiology 156, 3216– 3223. Juricova H, Videnska P, Lukac M, Faldynova M, Babak V, Havlickova H, Sisak F, Rychlik I. (2013): Influence of Salmonella enterica serovar Enteritidis infection on the development of the cecum microbiota in newly hatched chicks. Applied and Environmental Microbiology 79, 745–747. Karczmarczyk M, Walsh C, Slowey R, Leonard N, Fanning S (2011): Molecular characterization of multidrug-resistant Escherichia coli isolates from Irish cattle farms. Applied and Environmental Microbiology 77, 7121–7127. Maeda H, Fujimoto C, Haruki Y, Maeda T, Kokeguchi S, Petelin M, Arai H, Tanimoto I, Nishimura F, Takashiba S (2003): Quantitative real-time PCR using TaqMan and SYBR Green for Actinobacillus actinomycetemcomitans, Porphyromonas gingivalis, Prevotella intermedia, tetQ gene and total bacteria. FEMS Immunology and Medical Microbiology 39, 81–86. Nikolich MP, Hong G, Shoemaker NB, Salyers AA (1994): Evidence for natural horizontal transfer of tetQ between bacteria that normally colonize humans and bacteria that normally colonize livestock. Applied and Environmental Microbiology 60, 3255–3260. Rozen S, Skaletsky H (2000): Primer3 on the WWW for general users and for biologist programmers. Methods in Molecular Biology 132, 365–386. Salyers AA, Amabile-Cuevas CF (1997): Why are antibiotic resistance genes so resistant to elimination? Antimicrobial Agents and Chemotherapy 41, 2321– 2325. Soufi L, Saenz Y, Vinue L, Abbassi MS, Ruiz E, Zarazaga M, Ben Hassen A, Hammami S, Torres C (2011): Escherichia coli of poultry food origin as reservoir of sulphonamide resistance genes and integrons. International Journal of Food Microbiology 144, 497–502. Sunde M, Norstrom M (2006): The prevalence of, associations between and conjugal transfer of antibiotic resistance genes in Escherichia coli isolated from Norwegian meat and meat products. Journal Antimicrobial Chemotherapy 58, 741–747. Tseng CP, Cheng JC, Tseng CC, Wang C, Chen YL, Chiu DT, Liao HC, Chang SS (2003): Broad-range ribosomal RNA real-time PCR after removal of DNA from reagents: melting profiles for clinically important bacteria. Clinical Chemistry 49, 306–309. Videnska P, Faldynova M, Juricova H, Babak V, Sisak F, Havlickova H, Rychlik I (2013): Chicken faecal microbiota and disturbances induced by single or repeated. 303.

(7) Original Paper therapy with tetracycline and streptomycin. BMC Veterinary Research 9, 30. Young I, Rajic A, Wilhelm BJ, Waddell L, Parker S, McEwen SA (2009): Comparison of the prevalence of bacterial enteropathogens, potentially zoonotic bacteria and bacterial resistance to antimicrobials in organic and conventional poultry, swine and beef production: a systematic review and meta-analysis. Epidemiology and Infection 137, 1217–1232.. Veterinarni Medicina, 58, 2013: (6): 298–304 Yu Z, Michel FC Jr., Hansen G, Wittum T, Morrison M (2005): Development and application of real-time PCR assays for quantification of genes encoding tetracycline resistance. Applied and Environmental Microbiology 71, 6926–6933. Received: 2013–04–29 Accepted after corrections: 2013–06–12. Corresponding Author: Ivan Rychlik, Veterinary Research Institute, Hudcova 70, 621 00 Brno, Czech Republic Tel. +420 533 331 201, E-mail: rychlik@vri.cz. 304.

(8)

New documents

Policing vulnerability through building community connections
The underlying aim is to explore how far there is capacity within this community to generate assets that can be drawn on to improve the health and well-being of local people; in this
1 Amino N,N di­benzyl 1,6 di­de­oxy β L fructo­furan­ose
Department of Chemical Crystallography, Chemical Research Laboratory, Oxford University, Mansfield Road, Oxford OX1 3TA, England, and bDepartment of Organic Chemistry, Chemical Research
A proteomic approach for the rapid, multi informative and reliable identification of blood
Since blood provenance is also a forensic question of interest and as the m/z of haem would not permit the determination of the blood source, the m/z of intact Haemoglobin chains were
L Phenyl­alanine L phenyl­alaninium malonate
Data collection: CAD-4 EXPRESS Enraf–Nonius, 1994; cell refinement: CAD-4 EXPRESS; data reduction: XCAD4 Harms & Wocadlo, 1996; programs used to solve structure: SHELXS97 Sheldrick,
3 [(2R*,3S*) 3 (2 Meth­oxy­anilino) 2 methyl 3 phenyl­propionyl]­spiro­[2H 1,3 benzoxazine 2,1′ cyclo­hexan] 4(3H) one
Data collection: PROCESS-AUTO Rigaku, 1998; cell refinement: PROCESS-AUTO ; data reduction: CrystalStructure Rigaku/ MSC, 2004; programs used to solve structure: SHELXS97 Sheldrick,
Competitiveness and the Process of Co adaptation in Team Sport Performance
This definition supports the need to create, within the same team, an ‘interteam’ environment e.g., small-sided and conditioned games, designing task constraints representative of
1,3,3 Trimeth­yl 6′ (4 phenyl­piperazin 1 yl) 2,3 di­hydro­spiro­[1H indole 2,3′ 3H naphth[2,1 b][1,4]oxazine]
Data collection: SMART Bruker, 1998; cell refinement: SAINT Bruker, 1999; data reduction: SAINT; programs used to solve structure: SHELXS97 Sheldrick, 1997; programs used to refine
Band gap narrowing in ferroelectric KNbO3 Bi(Yb,Me)O3 (Me=Fe or Mn) ceramics
Hence, based on both permittivity measurements and Raman spectroscopy analysis all ceramics studied exhibit dielectric anomalies associated with structural phase transitions and their
An orthorhombic polymorph of di­chloro­bis­­[4 (di­methyl­amino)­phenyl]­tellurium
Data collection: SMART Bruker, 2000; cell refinement: SAINT Bruker, 2000; data reduction: SAINT; programs used to solve structure: SHELXS97 Sheldrick, 1997; programs used to refine
Understanding travel behaviour change during mega events: Lessons from the London 2012 Games
An initial outcome was the understanding that those with a specific intention to change behaviour during the Games or equally, at the minimum, contemplating in reference to the stages

Related documents

Relationship between antibiotic resistance genes and metals in residential soil samples from Western Australia
This study examined 90 garden soils from Western Australia to evaluate predictions of antibiotic resistance genes from total metal conditions by comparing the concentrations of 12
0
0
11
Antibiotic resistant bacteria found in municipal drinking water
2 Key words: antimicrobial resistance, water distribution system, intI, qac, sul Highlights • Plumbing systems contain antibiotic resistance bacteria • sul1 and sul2 genes are found in
0
0
24
Summer and December surveys on cattle, pig, sheep and goat livestock population 1997 1998 4
SUMMER AND D ECEMBER SURVEYS ON CATTLE, PIG, SHEEP AND GOAT LIVESTOCK POPULATION 1997 CATTLE.. In D ecember 1997 there were ca 83.1 million bo­ vine animals in the European Union
0
0
12
Cryptosporidium infections in terrestrial ungulates with focus on livestock: a systematic review and meta analysis
Considering livestock species cattle, sheep, goats, pigs, horses and buffaloes, analysis revealed higher Cryptosporidium infection prevalence in ungulates of the Cetartiodactyla than in
0
0
23
Molecular epidemiological studies on animal trypanosomiases in Ghana
A total of 613 samples including 219 tsetse flies, 146 cattle and 248 pigs blood samples were subjected to ITS1 PCR screening for different trypanosome species and the prevalence of the
0
0
7
Spatio temporal analysis to identify determinants of Oncomelania hupensis infection with Schistosoma japonicum in Jiangsu province, China
japonicum-infected snails, human sero-prevalence and human stool prevalence in the study villages of Jiangsu province, China, from 2003 to 2008... history, livestock such as cattle were
0
0
8
Prevalence of Escherichia coli O157:H7 in beef cattle at slaughter and beef carcasses at retail shops in Ethiopia
coli O157 observed in the cattle population fecal, intestinal mucosal swabs and skin swab samples as well as on the skins.. Even though the prevalence of
0
0
6
Epidemiological investigations of Shiga toxin producing Escherichia coli (STEC) O157 And STEC O26 in New Zealand slaughter cattle, and the source attribution of human illness : a thesis presented in partial fulfilment of the requirements for the degree of
A repeated cross-sectional study investigating the prevalence of faecal shedding of Shiga toxin-producing Escherichia coli O157 and O26 in very young calves and adult cattle at
0
0
31
Epidemiological investigations of Shiga toxin producing Escherichia coli (STEC) O157 And STEC O26 in New Zealand slaughter cattle, and the source attribution of human illness : a thesis presented in partial fulfilment of the requirements for the degree of
A repeated cross-sectional study investigating the prevalence of faecal shedding of Shiga toxin-producing Escherichia coli O157 and O26 in very young calves and adult cattle at
0
0
333
Geographical variation in antibiotic resistance profiles of Escherichia coli isolated from swine, poultry, beef and dairy cattle farm water retention ponds in Florida
Geographical variation in antibiotic resistance profiles of Escherichia coli isolated from swine, poultry, beef and dairy cattle farm water retention ponds in Florida1 S.. Braun5 and
0
0
8
Draft genomes of Vancomycin resistant isolates of animal Enterococcus faecium
Multiple antibiotic resistance genes were identified in the chicken E429, calf E172 and pig E142 strain genomes such as genes encode resistance to antibiotics as follows: ermA and ermB
0
0
7
Abundance and seasonal distribution of filth flies and their hymenopteran puparia parasitoids in Puducherry, India
Activity and relative abundance of hymenopterous parasitoids that attack puparia of Musca domestica and Stomoxys calcitrans Diptera: Muscidae on confined pig and cattle farms in
0
0
7
Associations between membership of farm assurance and organic certification schemes and compliance with animal welfare legislation
Logistic binomial mixed effects models of the association between certification status and the proportion of AH inspection code C/D on pig, sheep, cattle and poultry enterprises
0
0
21
Prevalence of sulfonamide resistance genes in bacterial isolates from manured agricultural soils and pig slurry in the United Kingdom
Wellington Article Title: Prevalence of Sulfonamide Resistance Genes in Bacterial Isolates from Manured Agricultural Soils and Pig Slurry in the United Kingdom Year of publication: 2009
0
0
24
PREVALENCE OF CRYPTOSPORIDIUM PARVUM IN DUNG COLLECTED FROM CATTLE IN BAMENDA, NORTHWEST REGION OF CAMEROON
Table 1: Overall prevalence of parasites in 60 cattle in Bamenda Central cattle market Identified helminthes/protozoan Number of cattle infected Prevalence % Fasciola spp 10 16.67
0
0
6
Show more