Prevalence, Resistance Patterns and Risk Factors for Antimicrobial Resistance in Poultry Farms and Retail Chicken Meat in Colombia and Molecular Characterization of Salmonella Paratyphi B and Salmonella Heidelberg by Maria del Pilar Donado Godoy DVM (Universidad Nacional de Colombia) 1988 M.Sc. (University of Guelph, Ontario Veterinary College) 1992 DISSERTATION Submitted in partial satisfaction of the requirements for the degree of DOCTOR OF PHILOSOPHY in Epidemiology in the OFFICE OF GRADUATE STUDIES of the UNIVERSITY OF CALIFORNIA DAVIS Approved: _____________________________________ Ian Gardner, Chair _____________________________________ Barbara Byrne _____________________________________ Woutrina Miller Committee in Charge 2010
111
Embed
Salmonella Paratyphi B and Salmonella Heidelberg ... · Barbosa, Alvaro Pedraza, Anita Puentes, Aida Rojas, Ivonne Hernandez, Claudia Calderon, ... thanks to Aura Lucia Leal from
This document is posted to help you gain knowledge. Please leave a comment to let me know what you think about it! Share it to your friends and learn new things together.
Transcript
Prevalence, Resistance Patterns and Risk Factors for Antimicrobial Resistance in Poultry Farms
and Retail Chicken Meat in Colombia and Molecular Characterization of Salmonella Paratyphi B and Salmonella Heidelberg
by
Maria del Pilar Donado Godoy DVM (Universidad Nacional de Colombia) 1988
M.Sc. (University of Guelph, Ontario Veterinary College) 1992 DISSERTATION
Submitted in partial satisfaction of the requirements for the degree of
DOCTOR OF PHILOSOPHY
in
Epidemiology
in the
OFFICE OF GRADUATE STUDIES
of the
UNIVERSITY OF CALIFORNIA
DAVIS
Approved:
_____________________________________ Ian Gardner, Chair
_____________________________________ Barbara Byrne
_____________________________________ Woutrina Miller
Committee in Charge
2010
ii
Prevalence, Resistance Patterns and Risk Factors for Antimicrobial Resistance in Poultry Farms and Retail Chicken Meat in Colombia and Molecular Characterization of Salmonella Paratyphi
B and Salmonella Heidelberg
Maria del Pilar Donado Godoy
2010
iii
Dedicated to
My parents, Guillermo and Bertha and,
Mi amor, Xavier
iv
ABSTRACT
The development of antimicrobial resistance among bacteria (AMR) is currently one of the world’s
most pressing public health problems. Misuse of antimicrobial agents both in humans and
animals has narrowed the potential use of antibiotics for the treatment of infections in humans. To
monitor the evolution of AMR and to develop control measures, some countries, such as the
USA, Canada and Denmark have set up national integrated monitoring systems. Surveillance
components in these programs help monitor changes in susceptibility/resistance of selected
zoonotic bacterial pathogens and commensal organisms recovered from animals, some retail
meats, and humans to antimicrobial agents. The growth of Colombia as an emerging economy
has resulted in the rapid development of its poultry industry and consequently new challenges in
food safety with the increased use of antibiotics. Since Colombia presents scenarios that can
potentially foster the emergence of antibiotic resistance and also does not have a monitoring
system, we conducted this pilot research to establish baseline data and to adapt processes for
the establishment of a Colombian Integrated Program for Antimicrobial Resistance Surveillance
(COIPARS).
We assessed the prevalence, risk factors and antimicrobial resistance profiles of a single food-
borne pathogen of importance for human health, Salmonella sp., and two commensal bacteria
Escherichia coli and Enterococcus, in commercial broiler farms of the two largest poultry
producing departments of Colombia and in retail meat chicken collected in Bogota, Capital District.
We further characterized isolates of the most prevalent Salmonella serovars, Salmonella
Paratyphi B dT+ and Heidelberg, using pulsed-field gel electrophoresis (PFGE) to evaluate their
genetic relatedness and to determine potential geographically predominant clones.
Our study found a high prevalence of Salmonella sp. in commercial broiler farms (41%) and
poultry houses (65%) and almost 26% in retail meat samples. Salmonella Paratyphi B dT+
represented 76% of Salmonella sp. isolated on farms and 51% of those isolated from retail meat
samples. Salmonella Heidelberg represented 23% and 16% of Salmonella isolates from farms
v
and retail meat samples, respectively. This is the first time that Salmonella Paratyphi B dT+ has
been reported in the poultry chain in Colombia.
Salmonella isolated from farms and retail meat as well as Escherichia coli and enterococci
isolated from chicken meat showed extensive resistance to antimicrobial agents. Ninety-eight
percent of Salmonella sp. isolates were reported as multi-drug resistant. Ceftiofur, enrofloxacin,
nalidixic acid and tetracycline were the antimicrobials that showed the highest frequency of
resistance among Salmonella and E. coli isolates. For enterococci, we found that 62% of E.
faecium isolates were resistant to quinupristin/dalfopristin, which is used to treat nosocomial
human infections when vancomycin resistance is present.
The DNA fingerprinting of S. Paratyphi B dT+ and S. Heidelberg isolates revealed marked
heterogeneity. However, similar genotypes of both serovars were demonstrated to be present in
farms and in retail outlets as well as among isolates coming from different farms within each
region and from farms located in the two geographically distant departments. A possible
dissemination of similar genotypes of both serovars along the poultry chain was hypothesized.
Lack of rigorous biosecurity and some high risk management practices of the poultry industry in
Colombia were possible explanations.
In conclusion, we consider that the findings of our pilot project, the first of its kind conducted in
Colombia, indicate potential risks for human health related to food-borne pathogens present in
the poultry chain. Despite the fact that longitudinal studies are required to further characterize
these risks, we believe that these results confirm the utility of establishing the COIPARS. Our
findings also suggest that it is possible to follow the processes required for establishing a
surveillance system similar to the ones in the USA or Canada while adapting the protocols for
local conditions. Finally, a program like COIPARS can also provide scientific evidence for
implementation of the new Colombian biosecurity legislation (Resolution 001183 issued by the
Colombian Agricultural Institute on March 25, 2010) to decrease the prevalence of Salmonella in
LIST OF TABLES......................................................................................................... XIV LIST OF FIGURES........................................................................................................ XV
CHAPTER 1 : INTRODUCTION AND LITERATURE REVIEW.........................................1
THE ISSUE: STEADY INCREASE IN ANTIMICROBIAL RESISTANCE AND THE LACK OF DEVELOPMENT OF NEW ANTIMICROBIAL DRUGS...................................................1 AN APPROPRIATE RESPONSE: INTEGRATED AMR SURVEILLANCE SYSTEMS ..3 THE COLOMBIAN SITUATION ......................................................................................4 DESIGN OF THE PILOT PROGRAM OF COIPARS.......................................................6 REFERENCES ...............................................................................................................9
CHAPTER 2 PREVALENCE, RISK FACTORS, AND ANTIMICROBIAL RESISTANCE (AMR) PROFILES OF SALMONELLA SP. IN COMMERCIAL BROILER FARMS IN TWO IMPORTANT POULTRY-PRODUCING REGIONS OF COLOMBIA ......................................................13
CHAPTER 3 PREVALENCE, RESISTANCE PATTERNS AND RISK FACTORS FOR ANTIMICROBIAL RESISTANCE (AMR) BACTERIA IN RETAIL CHICKEN MEAT IN COLOMBIA..........................................................................................................................................42
CHAPTER 4 MOLECULAR CHARACTERIZATION OF SALMONELLA PARATYPHI B DT+ (S. JAVA) AND SALMONELLA HEIDELBERG FROM POULTRY AND RETAIL CHICKEN MEAT IN COLOMBIA. ......................................................................................................................82
Chapter 2 TABLE 2-1. MINIMUM INHIBITORY CONCENTRATION (MIC) RANGE AND INTERPRETATIONS FOR
ANTIMICROBIALS USED IN THE PANEL............................................................................27 TABLE 2-2.MINIMUM INHIBITORY CONCENTRATIONS (MIC) AND ZONE DIAMETER FOR THE
INTERPRETATION OF ANTIMICROBIALS NOT INCLUDED IN THE PANEL. ..............................28 TABLE 2-3. REPORTED USE OF ANTIMICROBIALS IN THE FARMS FROM TWO POULTRY PRODUCTION
DEPARTMENTS OF COLOMBIA ......................................................................................29 TABLE 2-4. DISTRIBUTION OF SALMONELLA SEROVARS BY DEPARTMENT ................................30 TABLE 2-5. PERCENTAGE OF ANTIMICROBIAL SENSITIVE AND RESISTANT SALMONELLA SP. ISOLATES
..................................................................................................................................31 TABLE 2-6. COMPARISON OF RESISTANCE (%) AMONG SALMONELLA ISOLATES FROM THE TWO
DEPARTMENTS............................................................................................................32 TABLE 2-7. NUMBER OF ANTIMICROBIALS PER RESISTANCE PATTERN CLASSIFIED PER SEROVAR33 TABLE 2-8. NUMBER OF RESISTANT ISOLATES IN PATTERNS BY SEROVARS AND BY DEPARTMENT34 TABLE 2-9. AMR PATTERN DISTRIBUTION BY SEROVAR..........................................................35 TABLE 2-10: MULTIPLE LOGISTIC REGRESSION MODEL OF FACTORS ASSOCIATED WITH THE PREVALENCE
OF SALMONELLA AT THE HOUSE LEVEL (N=296) AND INCLUDING FARM AS A RANDOM EFFECT...................................................................................................................................36
Chapter 3 TABLE 3-1 DISTRIBUTION OF SALMONELLA SEROVARS BY TYPE OF STORE ..............................55 TABLE 3-2 PREVALENCE OF ANTIMICROBIAL RESISTANT BACTERIAL ISOLATES.........................56 TABLE 3-3 ANTIMICROBIAL RESISTANCE PATTERN DISTRIBUTION FOR THE MOST PREVALENT SALMONELLA
SEROVARS..................................................................................................................57 TABLE 3-4 PREVALENCE OF ANTIMICROBIAL RESISTANT SALMONELLA SP., ESCHERICHIA COLI AND
ENTEROCOCCUS ISOLATES OF VERY HIGH IMPORTANCE IN HUMAN MEDICINE..................58 TABLE 3-5 PREVALENCE OF RESISTANT SALMONELLA, E.COLI , AND ENTEROCOCCUS OF HIGH AND
MEDIUM IMPORTANCE IN HUMAN MEDICINE....................................................................59 TABLE 3-6 DISTRIBUTION SALMONELLA SP., E.COLI AND ENTEROCOCCUS BY THE NUMBER OF
ANTIMICROBIAL DRUGS TO WHICH THEY WERE RESISTANT. ............................................60 TABLE 3-7 RESISTANCE MARKERS PRESENT IN ENTEROCOCCUS SP. ......................................61
xv
LIST OF FIGURES Chapter 3 FIGURE 1 PREVALENCE OF RESISTANCE TO ANTIMICROBIALS IN SALMONELLA SP. ISOLATED FROM
CHICKENS: FARM VS RETAIL STORES IN BOGOTA, COLOMBIA, 2009. ..............................62 Chapter 4 FIGURE 1 SIMILARITY DENDOGRAM OF S. PARATYPHI B DT+ MACRORESTRICTION PATTERNS GENERATED
USING XBAL. CLONE COLUMN INDICATES THE NUMBER OF INDISTINGUISHABLE ISOLATES PRESENTING THE SAME PFGE PATTERN. THE CLUSTERS ARE MENTIONED AS CX (PERCENTAGE SIMILARITY COEFFICIENT). THE ORIGINS OF THE ISOLATES ARE REPORTED AS SANTANDER FARMS, CUNDINAMARCA FARMS, INDEPENDENT RETAIL SHOPS OR RETAIL CHAIN IN BOGOTA DC. THE DIFFERENT INTEGRATED COMPANIES ARE IDENTIFIED AS SAOX OR RCOX. THE SCALE BAR INDICATES PERCENT SIMILARITY COEFFICIENT...............................................................92
FIGURE 2 SIMILARITY DENDOGRAM OF S. HEIDLEBERG MACRO RESTRICTION PATTERNS GENERATED USING XBAL. CLONE COLUMN INDICATES THE NUMBER OF INDISTINGUISHABLE ISOLATES PRESENTING THE SAME PFGE PATTERN. THE CLUSTER IS MENTIONED AS CX (PERCENTAGE OF SIMILARITY COEFFICIENT). THE ORIGIN OF THE ISOLATES ARE REPORTED AS SANTANDER FARMS, CUNDINAMARCA FARMS, INDEPENDENT RETAIL SHOPS OR RETAIL CHAIN IN BOGOTA, DC. THE DIFFERENT INTEGRATED COMPANIES ARE IDENTIFIED AS SAOX OR RCOX. THE SCALE BAR INDICATES PERCENT SIMILARITY...................................................................................93
1
Chapter 1 : Introduction and Literature Review THE ISSUE: STEADY INCREASE IN ANTIMICROBIAL RESISTANCE AND THE LACK OF DEVELOPMENT OF NEW ANTIMICROBIAL DRUGS
The use of antimicrobials combined with improvements in sanitation, nutrition and immunization
has lead to a dramatic decrease in deaths and a major gain in human life expectancy 1. However,
with the increased use of antimicrobials, antimicrobial resistance (AMR) has emerged as one of
the greatest threats to human health security 2 and a most pressing public health problem of
serious concern to public health, animal health and also food safety authorities 3-7.
The increase in AMR has narrowed the potential uses of antibiotics for the treatment of infections
in humans and animals 8. As a striking example, the Centers for Disease Control and Prevention
(CDC), estimated that the total of Methicillin Resistant Staphylococcus Infections (MRSI) in US
hospitals and communities has increased from 2 % in 1974 to almost 63% in 2004 9.
Similarly, with Salmonella being an important cause of food-borne diarrheal disease in human
beings 10-12, the reduction in the number of antibiotics available for effective treatment of
Salmonella related infectious diseases in humans and animals has become a serious concern 8.
The frequency and extent of the resistance to antimicrobials by Salmonella vary based on the
antimicrobial usage in humans and animals and the ecological differences in the epidemiology of
Salmonella infections 13. Globally, Salmonella exhibits extensive resistance profiles which have
been associated with higher rates of morbidity and mortality 13-15 and the use of antimicrobials in
food producing animals 16.
Similarly the important commensal bacteria, Escherichia coli (Gram-negative) and Enteroccus
(Gram-positive) also result in infectious diseases in man. With their ability to transfer resistance
genes to human pathogens 17, 18, these bacteria pose a more serious global threat for human
health than selection pressure 19. Furthermore, the level and degree of resistance that occur in
commensal bacteria is linked to the amount and class of antimicrobial agents used to produce a
2
kilogram of meat 20 which varies from country to country 21. Finally, since E. coli and enterococci
can be easily obtained from healthy animals, they are good indicator bacteria to monitor AMR.
The causes of AMR are hypothesized to include the abuse and misuse of antibiotics in both
human and animals (Aarestrup, 2005). These practices include: over-prescription of broad-
spectrum antimicrobials when a narrow-spectrum oral agent would be more appropriate 22; self-
medication with antimicrobials 23; low patient compliance 24; and the combination of highly
susceptible patients in hospital settings, with the intensive and prolonged antimicrobial use
resulting in nosocomial infections with highly resistant bacterial pathogens 25.
In humans, WHO has identified several underlying causes for the increased need of
antimicrobials and consequently their misuse stemming from an increase in infections due to a)
urbanization with overcrowding and poor sanitation, b) pollution, environmental degradation and
changing weather patterns, c) increased exposure of the elderly to nosocomial infections, d) the
spread of infectious diseases and resistant microorganism between continents due to booming
global trade and travel, and e) massive use of antibiotics in food-producing animals and poultry
flocks 1.
The presence of AMR bacteria in primary animal production represents a high risk for humans
since AMR bacteria of animal origin can be transmitted from animals to humans through the food
supply (food-borne pathogens), water or direct contact with animals 26-28.
In farms, factors that can influence bacterial resistance vary depending on herd or flock health
status, farm management and environment 29. These practices include over-prescription of broad-
spectrum drugs by veterinarians instead of narrow-spectrum drugs 30, feeding of low doses of
antibiotics for growth promotion 31-34 and use of non-approved drugs or drugs used in extra-label
manner are believed to contribute to the development of antimicrobial resistance 35, 36. Although
widespread use of antimicrobials in the primary sector has benefits for producers, it also
contributes to the increasing emergence of AMR bacteria 37.
One of the solutions to minimize the effects of AMR could be the production of new antimicrobials
but unfortunately, the development of new antimicrobials has not been able to keep up with the
3
increased demand for new antibiotics due to AMR 38. After the discovery of penicillin by Fleming
in 1929, the sulphonamides, the first class of antibiotics was launched in 1937 followed in 1944
by streptomycin, the first aminoglycoside 39. Since then, several other classes of antibiotics have
Following the recommendation of the advisory team, the standard procedures developed by
CIPARS were established as reference approaches and were adapted to the Colombian situation
as needed 54, 55
Selection of the poultry chain for the pilot program
To establish a baseline in the animal production sector, the poultry industry was selected
because it is by far the most integrated and standardized animal production system in Colombia,
and offers an excellent tracking system of production from the farm level through to the retail
sales outlets. Poultry production is a strategic sector in the emerging economy of Colombia and is
the fastest growing animal production sector (11% of growth in 2007). In 2007, a nationwide
initiative was launched about the health and safety status in the poultry chain by 5 ministries,
namely COMPES Avicola, resulting in favourable conditions to obtain collaboration of the various
stakeholders of the poultry sector towards the COIPARS initiative.
Selection of bacteria to be included in the pilot program
One food-borne pathogen of importance for human health, Salmonella sp, was included in the
pilot program, in addition to two commensal bacteria, Escherichia coli and Enterococcus sp.
Sampling geographical regions
At the farm level, the study was done in the two departments where poultry farming is the main
economic activity: Santander and Cundinamarca. The department of Santander is situated in
eastern Colombia and contributes about 32% of the total chicken production with 134 million birds
per year. Cundinamarca is situated in the oriental branch of Andes Cordillera and produces 137
million chickens/year and contributes about 33% of the country’s total chicken production. At the
retail level, the sampling was focused in the Capital District of Bogota (Bogota, DC). This is the
largest urban concentration in Colombia with 8 million inhabitants and represents the main
commercialization area for poultry products from the Santander and Cundinamarca regions.
Overall design
In order to establish baseline data in the poultry chain of Colombia, 3 studies were conducted:
8
1. Prevalence, risk factors, and antimicrobial resistance (AMR) profiles of Salmonella sp. in
commercial broiler farms in the two important poultry-producing regions of Colombia.
2. Prevalence, resistance patterns and risk factors for antimicrobial resistance (AMR) of
Salmonella, Escherichia coli and Enterococcus in retail chicken meat in Colombia.
3. Molecular characterization of Salmonella Paratyphi B dT+ and S. Heidelberg isolates
from poultry and retail chicken meat in Colombia.
The objectives of this pilot project were to establish baseline data and to validate processes for
the implementation of an integrated surveillance program for antimicrobial resistance (AMR) in
Colombia.
9
REFERENCES
[1] WHO. Antimicrobial resistance. Fact Sheet No 194, 2002.
[2] WHO. The World Health Report 2007 - A safer future: global public health security in the 21st century. Chapter 2: Threats to public health security. World Health Organizationed, 2007.
[3] Tenover FC. Mechanisms of antimicrobial resistance in bacteria. Am J Med. 2006 119: S3-10; discussion S62-70.
[4] Talbot GH, Bradley J, Edwards JE, Jr., Gilbert D, Scheld M, Bartlett JG. Bad bugs need drugs: an update on the development pipeline from the Antimicrobial Availability Task Force of the Infectious Diseases Society of America. Clin Infect Dis. 2006 42: 657-68.
[5] Courvalin P. Antimicrobial Drug Resistance: "Prediction Is Very Difficult, Especially about the Future". Emerg Infect Dis. 2005 11: 1503-6.
[6] O'Brien TF. Emergence, spread, and environmental effect of antimicrobial resistance: how use of an antimicrobial anywhere can increase resistance to any antimicrobial anywhere else. Clin Infect Dis. 2002 34 Suppl 3: S78-84.
[7] Marchese A, Schito GC. [Recent results of multinational studies on antibiotic resistance: should we have "PROTECTion" against these resistances?]. Med Mal Infect. 2007 37 Spec No 1: 2-5.
[8] Angulo FJ, Nargund VN, Chiller TC. Evidence of an association between use of anti-microbial agents in food animals and anti-microbial resistance among bacteria isolated from humans and the human health consequences of such resistance. J Vet Med B Infect Dis Vet Public Health. 2004 51: 374-9.
[9] CDC. Overview of Healthcare-associated MRSA. Atlanta, 2010.
[10] Kang ZW, Jung JH, Kim SH, Lee BK, Lee DY, Kim YJ, et al. Genotypic and phenotypic diversity of Salmonella enteritidis isolated from chickens and humans in Korea. J Vet Med Sci. 2009 71: 1433-8.
[11] Hanning IB, Nutt JD, Ricke SC. Salmonellosis outbreaks in the United States due to fresh produce: sources and potential intervention measures. Foodborne Pathog Dis. 2009 6: 635-48.
[12] [CDC] Centers for Disease Control and Prevention. Annual listing of foodborne disease outbreaks. Outbreak Surveillance Data Reported Foodborne Disease Outbreaks and Illnesses by Etiology and Food Commodities, United States. Atlanta, GA: CDCed, 2008.
[13] McDermott PF. Antimicrobial resistance in non-typhoidal Salmonellae. In: Aarestrup FM, ed. Antimicrobial resistance in bacteria of animal origen. Washington, D.C.: ASM Pressed, 2006.
[14] Kariuki S, Revathi G, Kariuki N, Muyodi J, Mwituria J, Munyalo A, et al. Increasing prevalence of multidrug-resistant non-typhoidal Salmonellae, Kenya, 1994-2003. Int J Antimicrob Agents. 2005 25: 38-43.
[15] Martin LJ, Fyfe M, Dore K, Buxton JA, Pollari F, Henry B, et al. Increased burden of illness associated with antimicrobial-resistant Salmonella enterica serotype typhimurium infections. J Infect Dis. 2004 189: 377-84.
[16] Angulo FJ, Baker NL, Olsen SJ, Anderson A, Barrett TJ. Antimicrobial use in agriculture: controlling the transfer of antimicrobial resistance to humans. Semin Pediatr Infect Dis. 2004 15: 78-85.
[17] Poppe C, Martin LC, Gyles CL, Reid-Smith R, Boerlin P, McEwen SA, et al. Acquisition of resistance to extended-spectrum cephalosporins by Salmonella enterica subsp. enterica serovar Newport and Escherichia coli in the turkey poult intestinal tract. Appl Environ Microbiol. 2005 71: 1184-92.
10
[18] van den Bogaard AE, Stobberingh EE. Epidemiology of resistance to antibiotics. Links between animals and humans. Int J Antimicrob Agents. 2000 14: 327-35.
[19] Boerlin P, Reid-Smith RJ. Antimicrobial resistance: its emergence and transmission. Anim Health Res Rev. 2008 9: 115-26.
[20] Parveen S, Taabodi M, Schwarz JG, Oscar TP, Harter-Dennis J, White DG. Prevalence and antimicrobial resistance of Salmonella recovered from processed poultry. J Food Prot. 2007 70: 2466-72.
[21] Aarestrup FM. Veterinary drug usage and antimicrobial resistance in bacteria of animal origin. Basic Clin Pharmacol Toxicol. 2005 96: 271-81.
[22] Louie JP, Bell LM. Appropriate use of antibiotics for common infections in an era of increasing resistance. Emerg Med Clin North Am. 2002 20: 69-91.
[23] Dryden MS, Cooke J, Davey P. Antibiotic stewardship--more education and regulation not more availability? J Antimicrob Chemother. 2009 64: 885-8.
[24] Kardas P. Patient compliance with antibiotic treatment for respiratory tract infections. J Antimicrob Chemother. 2002 49: 897-903.
[25] Levin PD, Fowler RA, Guest C, Sibbald WJ, Kiss A, Simor AE. Risk factors associated with resistance to ciprofloxacin in clinical bacterial isolates from intensive care unit patients. Infect Control Hosp Epidemiol. 2007 28: 331-6.
[26] Ramchandani M, Manges AR, DebRoy C, Smith SP, Johnson JR, Riley LW. Possible animal origin of human-associated, multidrug-resistant, uropathogenic Escherichia coli. Clin Infect Dis. 2005 40: 251-7.
[27] Swartz MN. Human diseases caused by foodborne pathogens of animal origin. Clin Infect Dis. 2002 34 Suppl 3: S111-22.
[28] Funk JA, Lejeune JT, Wittum TE, Rajala-Schultz PJ. The effect of subtherapeutic chlortetracycline on antimicrobial resistance in the fecal flora of swine. Microb Drug Resist. 2006 12: 210-8.
[29] Acar JF, Moulin G. Antimicrobial resistance at farm level. Rev Sci Tech. 2006 25: 775-92.
[30] Sarkar P, Gould IM. Antimicrobial agents are societal drugs: how should this influence prescribing? Drugs. 2006 66: 893-901.
[31] Prescott JF. Antimicrobial use in food and companion animals. Anim Health Res Rev. 2008 9: 127-33.
[32] Mathew AG, Cissell R, Liamthong S. Antibiotic resistance in bacteria associated with food animals: a United States perspective of livestock production. Foodborne Pathog Dis. 2007 4: 115-33.
[33] Hammerum AM, Heuer OE, Emborg HD, Bagger-Skjot L, Jensen VF, Rogues AM, et al. Danish integrated antimicrobial resistance monitoring and research program. Emerg Infect Dis. 2007 13: 1632-9.
[34] Hammerum AM, Heuer OE, Lester CH, Agerso Y, Seyfarth AM, Emborg HD, et al. Comment on: withdrawal of growth-promoting antibiotics in Europe and its effects in relation to human health. Int J Antimicrob Agents. 2007 30: 466-8.
[35] Sharma R, Sharma CL, Kapoor B. Antibacterial resistance: current problems and possible solutions. Indian J Med Sci. 2005 59: 120-9.
[36] Weese JS. Prudent use of antimicrobials. In: Giguère S, ed. Antimicrobial therapy in veterinary medicine. Ames, Iowa: Blackwell Pub., 4th ed, 2006:xvii, 626 p.
11
[37] Aarestrup FM, Pires SM. Comment on: Causal regulations vs. political will: why human zoonotic infections increase despite precautionary bans on animal antibiotics. Environ Int. 2009 35: 760-1.
[38] Coates A, Hu Y, Bax R, Page C. The future challenges facing the development of new antimicrobial drugs. Nat Rev Drug Discov. 2002 1: 895-910.
[39] Giguère S. Antimicrobial therapy in veterinary medicine. 4th ed. Ames, Iowa: Blackwell Pub., 2006.
[40] Diekema DI, Jones RN. Oxazolidinones: a review. Drugs. 2000 59: 7-16.
[41] Spellberg B. Antibiotic resistance:promoting critically needed antibiotic research and developement and the apropiate use ("stewardship") of these precious drug. Before the House Committee on Energy and Commerce Subcommittee on Health: Infectious Disease Society of America (IDSA). 2010.
[42] ECDC/EMEA. The bacterial challenge: time to react. A call to narrow the gap between multidrug-resistant bacteria in the EU and the development of new antibacterial agents. Stockholm: European Centre for Disease Prevention and Control/European Medicines Agency, 2009.
[43] CIPARS. Canadian Integrated Program for Antimicrobial Resistance Surveillance (CIPARS), 2007. Guelph, ON: Government of Canada. Public Health Agency of Canada.ed, 2010.
[44] CDC. National Antimicrobial Resistance Monitoring System (NARMS). ed, 2009.
[45] Wiesner M, Hidalgo M, Castaneda E, Agudelo CI. Molecular analysis of Salmonella enteritidis and Typhimurium clinical and food isolates by pulsed-field gel electrophoresis in Bogota, Colombia. Microb Drug Resist. 2006 12: 68-73.
[46] Agudelo CI, Moreno J, Sanabria OM, Ovalle MV, Di Fabio JL, Castaneda E. [Streptococcus pneumoniae: serotype evolution and patterns of antimicrobial susceptibility in invasive isolates from 11 years surveillance (1994 -2004) in Colombia]. Biomedica. 2006 26: 234-49.
[47] Moreno J, Phandanouvong V, Castaneda E. [Molecular surveillance of invasive penicillin-resistant Streptococcus pneumoniae Colombian isolates recovered from children less than 5 years of age]. Biomedica. 2004 24: 296-301.
[48] Ovalle MV, Agudelo CI, Munoz N, Castaneda E, Gallego CR, Nunez S, et al. [Surveillance of Haemophilus influenzae serotypes and antimicrobial resistance in Colombia, 1994-2002]. Biomedica. 2003 23: 194-201.
[49] INS. Serotipos y Patrones de Susceptibilidad Antimicrobiana de Patógenos de Importancia en Salud Pública. Estadisticas de la Vigilancia en Salud Publicaed, 2010.
[50] Leal AL, Eslava-Schmalbach J, Alvarez C, Buitrago G, Mendez M. [Endemic tendencies and bacterial resistance markers in third-level hospitals in Bogota, Colombia]. Rev Salud Publica (Bogota). 2006 8 Suppl 1: 59-70.
[51] Miranda MC, Perez F, Zuluaga T, Olivera Mdel R, Correa A, Reyes SL, et al. [Antimicrobial resistance in gram negative bacteria isolated from intensive care units of Colombian hospitals, WHONET 2003, 2004 and 2005]. Biomedica. 2006 26: 424-33.
[52] Arias CA, Reyes J, Zuniga M, Cortes L, Cruz C, Rico CL, et al. Multicentre surveillance of antimicrobial resistance in enterococci and staphylococci from Colombian hospitals, 2001-2002. J Antimicrob Chemother. 2003 51: 59-68.
[53] Pfaller MA, Jones RN, Doern GV, Salazar JC. Multicenter evaluation of antimicrobial resistance to six broad-spectrum beta-lactams in Colombia: comparison of data from 1997 and 1998 using the Etest method. The Colombian Antimicrobial Resistance Study Group. Diagn Microbiol Infect Dis. 1999 35: 235-41.
12
[54] CIPARS. CIPARS: Retail Field Staff Manual - Ontario. In: Public Health Agency of Canada. 2007.
[55] Public Health Agency of Canada. Canadian Integrated Program for Antimicrobial Resistance Survaival (CIPARS). Methodology fo the isolation of Salmonella sp. from meat and poultry samples. LLZA-Unite de Saint-Hyacintheed, 2007:5.
13
Chapter 2 Prevalence, Risk Factors, and Antimicrobial Resistance (AMR) Profiles of Salmonella sp. in Commercial Broiler Farms in Two Important Poultry-Producing Regions of Colombia
ABSTRACT
Salmonella sp. is the most common food-borne pathogen associated with diarrheal disease in
humans. Food animals, especially poultry, are important direct and indirect sources of human
Salmonella sp. infections. The use of antimicrobials in the primary sector benefits producers but
also contributes to the increasing emergence of AMR bacteria. As a first step towards
implementing the Colombian Integrated Program for Antimicrobial Resistance Surveillance
(COIPARS), this study aimed to establish the prevalence, distribution of serovars, antimicrobial
resistance profiles and risk factors for Salmonella sp. isolated from poultry farms in the two
largest areas of poultry production in Colombia. Salmonella was isolated from 29 farms (41.4%)
with a Salmonella sp. positive prevalence of 65% in the 315 houses sampled. S. Paratyphi B was
the most prevalent serovar (76.4%), followed by S. Heidelberg (22.7%). None of the Salmonella
isolates were susceptible to all the antimicrobials tested in this study and the number of
antimicrobials to which an isolate was resistant ranged from 2 to 15. The resistance pattern
TCY-XNL-NAL was found in over 40% of the isolates of S. Heidelberg. For S. Paratyphi B, many
patterns (34) were present even though the predominant resistance pattern was CIP-NIT-TCY-
SXT-XNL-STR-ENR-NAL (15%). Of all the biosecurity practices, the two factors that were
significantly (P < 0.05) associated with the presence of Salmonella on a farm were related to
hygiene: the cleaning of fixed equipment and the composting of dead birds within the farm.
Findings from the present study provide scientific evidence for implementation of official policies
that support new biosecurity legislation to decrease the prevalence of Salmonella in poultry farms.
INTRODUCTION
14
Worldwide, Salmonella is an important cause of food-borne diarrheal disease in human beings
and often is associated with the consumption of poultry products 1-3. In recent years, an added
public health concern has been the development of antimicrobial resistance (AMR) that markedly
reduces the number of antibiotics available for effective treatment of infectious diseases in
humans and animals 4.
Modern food animal production systems often use antimicrobial agents to prevent, control and
treat bacterial infections and these agents are commonly used as growth promoters in poultry and
swine production systems 5,6. Widespread use of antimicrobials in the primary sector has benefits
for producers but also contributes to the increasing emergence of AMR bacteria 5. Factors that
can influence bacterial resistance in farms are numerous and vary depending on flock health
status, farm management and environment 7. Practices such as the prescription of broad-
spectrum drugs by veterinarians instead of narrow-spectrum drugs 8, feeding of low doses of
antibiotics for growth promotion 9-12, and use of non-approved drugs or drugs used in extra-label
manner are believed to contribute to the development of antimicrobial resistance 13,14.
The presence of AMR bacteria in primary production represents a high risk for humans since
AMR bacteria of animal origin can be transmitted from animals to humans through the food
supply, water or by direct contact with animals. Sometimes resistance genes can even be
transferred from animals through human pathogens that are normally human-specific 15.
Awareness of the prevalence of AMR in food animals provides baseline data in order to
implement an integrated AMR surveillance system and also facilitates the evaluation of
interventions used to control the AMR.
Over the past decade, the Colombian poultry sector production has expanded and is attempting
to meet international food safety and animal health standards. The Colombian poultry industry is
free of avian influenza, which allows it access to international markets. However, there are
limiting factors such as endemic Newcastle Disease as well as insufficient knowledge of the
baseline prevalence of chemical residues and pathogens such as Salmonella sp.
15
In Colombia, there has not been a comprehensive prevalence survey of Salmonella in poultry in
the last 10 years. Only fragmented reports in localized areas with limited sample sizes are
available. Furthermore, there is a lack of knowledge regarding AMR in farms, abattoirs and retail
stores for any of the predominant animal production systems. The Colombian poultry industry has
been showing interest in improving the quality of the poultry-derived products, and in
implementing Hazard Analysis Critical Control Point HACCP systems on farms and at abattoirs.
In both cases, knowledge of the frequency, risk factors and resistance patterns of AMR in the
country is fundamental to the development of HACCP programs.
The objective of the present study was to determine the prevalence, distribution of serovars,
antimicrobial resistance profiles and risk factors for Salmonella sp. isolated from poultry farms in
the two largest areas of poultry production in Colombia. This was the first step to provide
baseline data for an integrated and unified antimicrobial resistance surveillance system in the
country.
METHODS
Study Site: The study was done in the two departments (states) where poultry farming is the
main economic activity: Santander and Cundinamarca. The department of Santander is situated
in eastern Colombia and contributes 32.4% of the total chicken production with 134 million birds
per year. Cundinamarca is situated in the oriental branch of Andes Cordillera and produces 137
million chickens/year, contributing approximately 33.1% of the total chicken production.
Farms
The sampling unit was the farm. A convenience sample of 70 farms from 12 of the largest 20
poultry companies in these two regions was selected based on the willingness of the enterprise
managers to participate. The numbers of farms per enterprise was selected proportional to the
chicken population of the operation. In each farm, two to five houses that were in production were
selected randomly.
Questionnaire
16
A questionnaire was completed for each farm and included general characteristics of the farm,
biosecurity practices and house-specific information. The questionnaire was conducted by the
senior author and was answered by the veterinarian of each farm. Questions related to farm type,
altitude of the farm, size, biosecurity management, type of ventilation, antimicrobial treatments of
chickens, type of housing, cleaning of housing, feeding management, use of prophylactic and
therapeutic treatments, and use of growth promoters were considered. A pre-test of the
questionnaire was done in five operations.
Sampling Procedure
Two drag swabs and a pooled fecal sample were collected from each selected house. The pooled
sample was taken from fecal samples collected in five different places of the house at random.
Then, the samples were placed in sterile Nasco bags and transported on ice in insulated
containers to the Instituto Colombiano Agropecuario Animal (ICA)- Diagnostic Laboratories
(LNDV) laboratories in Bogota within 12 hours of collection. All the samples were processed at
the ICA-LNDV Salmonella Laboratory.
Salmonella culture and serotyping of isolates
Culture for Salmonella followed World Organization of Animal Health recommendations 16. Briefly,
following pre-enrichment on brain heart infusion (BHI) broth at 37 and 42°C for 24 hours, drag
swabs and fecal samples were subcultured to tetrathionate broth for 18-24 hours at 37°C and
Rappaport-Vassiliadis broth at 43°C for 18-24 hours. Salmonella growth was assessed by the
use of MacConkey agar and selective plating media, xylose lysine desoxycholate (XLD), xylose
lactose tergitol 4 (XLT-4) and CHROMagar Salmonella. Three presumptive Salmonella
colonies per plate were screened by biochemical tests such as lysine iron agar, triple sugar iron
agar, citrate agar, Sulfur Indol Motility (SIM) media and urease. Identification was confirmed by
the use of direct slide agglutination with Salmonella O antiserum Poly A & Vi (Difco, Franklin
Lakes, NJ). Three to five suspect colonies from each Salmonella-positive plate were streaked on
nutrient agar and incubated for 18-24 hours at 37°C, with re-confirmation of Salmonella sp. done
on one of these colonies by the automated PhoenixTM system (Carrol et al., 2006). Serovar
17
identification was performed based on the Kauffman-White scheme. Salmonella Paratyphi B was
differentiated by the fermentation of d-tartrate based on lead acetate test following the protocol
described in a prior study 17. Serotyping was done in the ICA-LNDV Salmonella laboratory.
Three colonies of all Salmonella strains were frozen at -70° C in a strain collection for further
characterization. Detailed records of their origin, dates, farm, flock, houses and type of sample
were registered for each isolate.
Antimicrobial susceptibility testing methods
The PhoenixTM automated microbiological system was used to determine the antimicrobial
minimum inhibitory concentration (MIC) for isolates. The PhoenixTM is an automated microbroth
dilution system for Gram-positive and Gram-negative bacteria (Carrol et al., 2006). The selection
of antimicrobials was based on their use in animal and human health and included amoxicillin-
Table 2-10: Multiple logistic regression model of factors associated with the prevalence of Salmonella at the house level (n=296) and including farm as a random effect.
Variable
Positive Salmonella
n (%)
Negative Salmonella
n (%)
Odds ratio
95% confidence
interval
Use of compost for the disposal of dead birds Yes No
48 (19.8) 12 (22.6)
195 (80.2) 41 (77.4)
0.44 1
0.1, 1.5
Cleaning of fixed equipment (blower/wiping down) Yes No
33 (13.2) 27 (58.7)
217 (86.8) 19 (41.3)
0.05 1
0.02, 0.2
Bird density per square meter
1.2 1.0, 1.43
Hosmer and Lemeshow Goodness-of-Fit test probability= 0.93
37
Appendix 2-1 Multiple logistic regression model of factors associated with the prevalence of Salmonella at the farm level (n=70)
Variable
Positive Salmonella
n (%)
Negative Salmonella
n (%) Odds ratio
95% confidence
interval
Disposal of dead birds by composting Yes No
22 (37.9) 7 (58.3)
36 (62.1) 5 (41.7)
0.3 1
0.01, 1.3
Cleaning of fixed equipment (blower/wiping down) Yes No
22 (37.3) 4 (36.4)
37 (62.7) 7 (63.6)
0.2 1
0.06, 0.8
38
Appendix 2-2 Multiple logistic regression model of factors associated with the prevalence of Salmonella at sample level (n=886) and adjusting for farm as a random effect.
Variable
Positive Salmonella
n (%)
Negative Salmonella
n (%)
Prevalence odds ratio
95% confidence
interval
Disposal of dead birds by composting Yes No
88 (12.1) 22 (14.0)
641 (87.9) 135 (86)
0.12 1
0.04, 0.37
Blown off or wiped clean of all equipment Yes No
65 (8.7) 45 (33.1)
685 (91.3) 91 (66.9)
0.45 1
0.14, 1.38
Bird density per square meter
1.14
0.97, 1.34
Sample type Drag swab Feces
93 (16.0) 17 (5.6)
487 (84.0) 289 (94.4)
5.95
1
2.98, 11.9
39
REFERENCES
1. Kang ZW, Jung JH, Kim SH, Lee BK, Lee DY, Kim YJ, Lee JY, Won HK, Kim EH, Hahn TW. Genotypic and phenotypic diversity of Salmonella enteritidis isolated from chickens and humans in Korea. J Vet Med Sci 2009;71(11):1433-8.
2. Hanning IB, Nutt JD, Ricke SC. Salmonellosis outbreaks in the United States due to fresh produce: sources and potential intervention measures. Foodborne Pathog Dis 2009;6(6):635-48.
3. [CDC] Centers for Disease Control and Prevention. Annual listing of foodborne disease outbreaks. Outbreak Surveillance Data. Reported Foodborne Disease Outbreaks and Illnesses by Etiology and Food Commodities, United States. Vol. 2010. Atlanta, GA: CDC, 2008.
4. Angulo FJ, Nargund VN, Chiller TC. Evidence of an association between use of anti-microbial agents in food animals and anti-microbial resistance among bacteria isolated from humans and the human health consequences of such resistance. J Vet Med B Infect Dis Vet Public Health 2004;51(8-9):374-9.
5. Aarestrup FM, Pires SM. Comment on: Causal regulations vs. political will: why human zoonotic infections increase despite precautionary bans on animal antibiotics. Environ Int 2009;35(4):760-1.
6. Dibner JJ, Richards JD. Antibiotic growth promoters in agriculture: history and mode of action. Poult Sci 2005;84(4):634-43.
7. Acar JF, Moulin G. Antimicrobial resistance at farm level. Rev Sci Tech 2006;25(2):775-92.
8. Sarkar P, Gould IM. Antimicrobial agents are societal drugs: how should this influence prescribing? Drugs 2006;66(7):893-901.
9. Prescott JF. Antimicrobial use in food and companion animals. Anim Health Res Rev 2008;9(2):127-33.
10. Mathew AG, Cissell R, Liamthong S. Antibiotic resistance in bacteria associated with food animals: a United States perspective of livestock production. Foodborne Pathog Dis 2007;4(2):115-33.
11. Hammerum AM, Heuer OE, Emborg HD, Bagger-Skjot L, Jensen VF, Rogues AM, Skov RL, Agerso Y, Brandt CT, Seyfarth AM, Muller A, Hovgaard K, Ajufo J, Bager F, Aarestrup FM, Frimodt-Moller N, Wegener HC, Monnet DL. Danish integrated antimicrobial resistance monitoring and research program. Emerg Infect Dis 2007;13(11):1632-9.
12. Hammerum AM, Heuer OE, Lester CH, Agerso Y, Seyfarth AM, Emborg HD, Frimodt-Moller N, Monnet DL. Comment on: withdrawal of growth-promoting antibiotics in Europe and its effects in relation to human health. Int J Antimicrob Agents 2007;30(5):466-8.
13. Sharma R, Sharma CL, Kapoor B. Antibacterial resistance: current problems and possible solutions. Indian J Med Sci 2005;59(3):120-9.
14. Weese JS. Prudent use of antimicrobials. In: Giguère S, ed. Antimicrobial therapy in veterinary medicine. 4th ed. Ames, Iowa: Blackwell Pub., 2006;xvii, 626 p.
15. Odensvik K, Grave K, Greko C. Antibacterial drugs prescribed for dogs and cats in Sweden and Norway 1990-1998. Acta Vet Scand 2001;42(1):189-98.
16. OIE. . Terrestrial Animal Health Code. World Organization for Animal Health, 2009.
17. Malorny B, Bunge C, Helmuth R. Discrimination of d-tartrate-fermenting and -nonfermenting Salmonella enterica subsp. enterica isolates by genotypic and phenotypic methods. J Clin Microbiol 2003;41(9):4292-7.
40
18. Clinical and Laboratory Standards Institute. Performance Standards for Antimicrobial Susceptibility Testing. 19th. Informational Supplement M100-S19. Wayne, PA 19087-1898: CLSI/NCCLS, 2007.
19. Clinical and Laboratory Standars Institute. Performance Standards for Antimicrobial Disk and Dilution Susceptibility Tests for Bacteria Isolated from animals. Approved Standards. M31-A3. 3th ed. PA: Wayne, 2008.
20. Pierson FW. Biosecurity: Principles and Practices in the Commercial Poultry Industry.Available at: nsgd.gso.uri.edu/vsgcp/vsgcpc98001/vsgcpc98001_part1.pdf Accessed on April 2010.
21. Salles RPR, Teixeira RSdC, Moura J, Siqueira AAd, Silva EEd, Moraes TGVd, Nogueira GC, Andrade JDMd, Castro SBd, Cardoso WM. Salmonella sp. bacteriology monitoring in laying hens at different growing and laying periods from poultry farms in Metropolitan Region of Fortaleza, CE, Brazil. Ciencia Animal Brasileira 2008;9(2):427-432.
22. Gama NMSQ, Berchieri Junior A, Fernandes SA. Occurrence of Salmonella sp. in laying hens. Revista Brasileira de Ciencia Avicola 2003;5(1):15-21.
23. Dione MM, Ieven M, Garin B, Marcotty T, Geerts S. Prevalence and antimicrobial resistance of Salmonella isolated from broiler farms, chicken carcasses, and street-vended restaurants in Casamance, Senegal. J Food Prot 2009;72(11):2423-7.
24. Elgroud R, Zerdoumi F, Benazzouz M, Bouzitouna-Bentchouala C, Granier SA, Fremy S, Brisabois A, Dufour B, Millemann Y. Characteristics of Salmonella contamination of broilers and slaughterhouses in the region of Constantine (Algeria). Zoonoses and Public Health 2009;56(2):84-93.
25. Arsenault J, Letellier A, Quessy S, Normand V, Boulianne M. Prevalence and risk factors for Salmonella sp. and Campylobacter sp. caecal colonization in broiler chicken and turkey flocks slaughtered in Quebec, Canada. Prev Vet Med 2007;81(4):250-64.
26. Boscan-Duque LA, Arzalluz-Fisher AM, Ugarte C, Sanchez D, Wittum TE, Hoet AE. Reduced susceptibility to quinolones among Salmonella serotypes isolated from poultry at slaughter in Venezuela. J Food Prot 2007;70(9):2030-5.
27. Oloya J, Doetkott D, Khaitsa ML. Antimicrobial drug resistance and molecular characterization of Salmonella isolated from domestic animals, humans, and meat products. Foodborne Pathog Dis 2009;6(3):273-84.
28. Zewdu E, Cornelius P. Antimicrobial resistance pattern of Salmonella serotypes isolated from food items and personnel in Addis Ababa, Ethiopia. Trop Anim Health Prod 2009;41(2):241-9.
29. Lestari SI, Han F, Wang F, Ge B. Prevalence and antimicrobial resistance of Salmonella serovars in conventional and organic chickens from Louisiana retail stores. J Food Prot 2009;72(6):1165-72.
30. van Pelt W, van der Zee H, Wannet WJ, van de Giessen AW, Mevius DJ, Bolder NM, Komijn RE, van Duynhoven YT. Explosive increase of Salmonella Java in poultry in the Netherlands: consequences for public health. Euro Surveill 2003;8(2):31-5.
31. Denny J, Threlfall J, Takkinen J, Lofdahl S, Westrell T, Varela C, Adak B, Boxall N, Ethelberg S, Torpdahl M, Straetemans M, van Pelt W. Multinational Salmonella Paratyphi B variant Java (Salmonella Java) outbreak, August - December 2007. Euro Surveill 2007;12(12):E071220 2.
32. DANMAP 2005. Use of antimicrobial agens and occurrence of antimicrobial resistance in bacteria from food animals, foods and humans in Denmark. Denmark: Danish Institute for Food and Veterinary Research, 2005.
41
33. Government of Canada. Canadian Integrated Progam for Antimicrobial Resistance Surveillance (CIPARS) 2004. Guelph, ON: Public Health Agency of Canada, 2006.
34. Dutil L, Irwin R, Finley R, Ng LK, Avery B, Boerlin P, Bourgault AM, Cole L, Daignault D, Desruisseau A, Demczuk W, Hoang L, Horsman GB, Ismail J, Jamieson F, Maki A, Pacagnella A, Pillai DR. Ceftiofur resistance in Salmonella enterica serovar Heidelberg from chicken meat and humans, Canada. Emerg Infect Dis;16(1):48-54.
35. I Censo Nacional de Avicultura Industrial. Bogota: Ministero de Agricultura Y Desarrollo Rural, Departamento Adminstrativo Nacional De Estacdistica-Dane, Federacion Nacional de Avicultores de Colombia-Fenavi, 2002.
36. Morgan-Jones SC. The occurrence of Salmonellae during the rearing of broiler birds. Br Poult Sci 1980;21(6):463-70.
37. Murray CJ. Environmental Aspects of Salmonella. In: Wray C, Wray A, eds. Salmonella in domestic animals. Wallingford, Oxon, UK ; New York, NY, USA: CABI Pub., 2000;x, 463 p.
42
Chapter 3 Prevalence, Resistance Patterns and Risk Factors for Antimicrobial Resistance (AMR) bacteria in Retail Chicken Meat in Colombia
ABSTRACT
Antimicrobial resistance can be transferred from zoonotic bacteria in food animals and from food
of animal origin to human populations, narrowing the potential uses of antimicrobials for the
treatment of severe infections. As a step towards implementing the Colombian Integrated
Program for Antimicrobial Resistance Surveillance (COIPARS), this study aimed to establish the
baseline antimicrobial resistance patterns of Salmonella sp., generic Escherichia coli and
Enterococcus sp. isolates in retail poultry meat from independent stores and from a main chain
distributor center. Several antimicrobials used in humans and animals were tested using an
automated system. Salmonella sp. was isolated from 26% of the samples while E. coli and
Enterococcus were detected in 82.5% and 93.5% of the samples, respectively. The principal
finding of concern in this study was that almost 98% of isolates tested were multidrug resistant
(MDR) and only one isolate of Salmonella was susceptible to all of the antimicrobials tested (2%).
Ceftiofur, enrofloxacin, nalidixic acid and tetracycline were the antimicrobials that showed the
highest frequency of resistance among Salmonella and E. coli isolates. For enterococci, we found
that 62% E. faecium isolates were resistant to quinupristin/dalfopristin, which is significant
because it is used to treat nosocomial infections when vancomycin resistance is present.
Vancomycin resistance was detected in 3% of the E. faecalis isolates. The results of our study
highlight the need for the rapid implementation of an integrated program for surveillance of
antimicrobial resistance by the Colombian authorities in order to monitor trends, raise
awarenesss, and help promote practices to safeguard higher generation antimicrobial agents.
43
INTRODUCTION
In recent years, antimicrobial resistance (AMR) has emerged as a global public health problem by
threatening to narrow the potential uses of antibiotics for the treatment of infectious diseases(17).
The implications of AMR raise concerns not only among public health authorities but also among
animal and food safety authorities(17, 32, 48, 49) because AMR bacteria can be transmitted from
food animals to humans through the food chain(45).
Modern food animal production systems commonly use antimicrobial agents to prevent, control
and treat bacterial infections(45) and some of these agents are also used as growth promoters in
poultry and swine production systems (4, 43). Although widespread use of antimicrobials in the
primary sector has benefits for producers, it also contributes to the increasing emergence of AMR
bacteria (4).
Meat products are sources of human infection for known food-borne AMR pathogens such as
Salmonella sp. and Campylobacter (25, 29, 34, 36). Salmonella sp. can carry resistance genes
that can be transmitted to humans(9). Similarly, because commensal bacteria, such as
Escherichia coli and enterococci, can transfer resistance genes to pathogens (38, 50), it makes
them a more serious global threat to human health than antibiotic selection pressure (10) .
Furthermore, the frequency and extent of resistance that occur in commensal bacteria is linked to
the amount and class of antimicrobial agents used to produce a kilogram of meat (34), which
varies from country to country (2).
Animal protein consumption is rapidly increasing in Colombia, similar to the trend in other
developing countries. It is estimated that a person on minimum wage in Colombia purchases
almost three times more chicken meat and twice as much swine meat annually than bovine meat.
In such dynamic conditions, the food safety considerations, particularly in the poultry chain, are
an increasing challenge.
Because Colombia is free of avian influenza, the poultry industry has attempted to reach
international food safety and animal health standards in order to take advantage of access to
international markets. However, there are still limiting factors including inadequate knowledge of
44
the baseline prevalence of food-borne pathogens like Salmonella and their antimicrobial
resistance profiles in retail meat of different origins that prevent Colombia from fully benefiting
from international commerce. There is also limited data about the antimicrobial resistance of
commensal bacteria such as Escherichia coli and enterococci in retail chicken meat in Colombia.
To properly assess the risk linked to food-borne pathogens and to the development of AMR,
several countries including Canada (11), USA (26), and Denmark (8) have initiated integrated and
unified programs for the surveillance of antimicrobial resistance. These programs integrate data
along the meat chain from farm production, abattoirs, and retail sectors with data from human
populations. Based on the surveillance data, a risk assessment is performed and policies are
developed. These programs have been shown to be effective at slowing the development of
AMR(18, 28).
As part of a pilot initiative to set-up such integrated systems in Colombia, namely COIPARS
(Colombian integrated Program for Antimicrobial Resistance Surveillance), we conducted a
survey with the objective of determining the prevalence, resistance patterns and risk factors for
AMR Salmonella sp., generic Escherichia coli and Enterococcus sp. in retail poultry meat.
METHODS
Study site and sample size. Samples were collected in Bogota between March and October
2009 from two different retail facilities. The sample size (n = 200) was determined by financial
constraints. One hundred samples were collected from independent retail stores and 100 were
taken from the distribution center of the main retail chain market group of the country. The
selection of independent retail stores was done based on the political division of Bogota
(localities).
Sample collection and transporting. For the independent stores, samples were placed in
insulated containers with cold gel packs following the methodology of the Canadian Integrated
Program for Antimicrobial Resistance Surveillance (CIPARS) (13) and then transported in less
than four hours to the laboratory for processing. In the main distribution center, samples were
selected at arrival and transported immediately to the laboratory for processing.
45
Data collection. Date and time of sample collection, ambient temperature, company, store type,
store name, location, type of sample, origin, if coming from organic or antibiotic free farm, sell-by
date and the price per kilogram were recorded, as well as the date and sample temperature on
arrival at the laboratory for processing. The socio-economic status of each locality where the
sample was collected was also noted in order to allow us to represent the AMR situation through
the political and economic divisions of the city. Bogota is stratified based on the location of the
owner's residence and income into 6 socio-economic strata(44): 1 (lowest), 2 (low), 3 (mid-low),
4 (mid-high), 5 (high) and 6 (highest).
Sampling procedure. Sampling of chicken meat was done following the CIPARS protocols
(2007) (13) which consists of one pack of thighs with skin on styrofoam trays per sample. This
sample type was chosen because it is the most popular chicken product in supermarkets.
Microbiological isolation and identification. Isolation and identification were done at the
Laboratory of Microbiological and Food Ecology, (LEMA), Universidad de los Andes, Bogota and
at the Laboratory for Quality Control of the main chain market. Serotyping of Salmonella was
done at the Microbiological Laboratory of National Institute for Drug and Food Surveillance
(INVIMA) which is the national reference laboratory for bacteria isolated from food.
Briefly, the microbiological isolation was done following the protocols of the CIPARS, 2007:
Isolation methods for Salmonella sp., generic E.coli, and Enterococcus sp. from meat and poultry
samples (39-41) (See Appendices 1-4). The confirmation of the bacterial genus of the isolates
was done using the automated antimicrobial susceptibility system (PhoenixTM) for AMR testing.
The serovar identification was done based on the Kauffman-White scheme for classification of
somatic O and flagellar H antigen type. All the isolates were frozen at -70°C for further study.
Antimicrobial susceptibility testing methods. The PhoenixTM automated microbiological
system was used to determine the antimicrobial minimum inhibitory concentration (MIC) for
isolates. The PhoenixTM is an automated microbroth dilution system for Gram-positive and
Gram-negative bacteria (12). The selection of antimicrobials was based on their use in animal
and human health. For Gram-negative bacteria, the panel included amoxicillin-clavulanic acid
Table 3-7 Resistance markers present in Enterococcus sp.
Number (Percentage resistant) Markers E. faecalis (n=110) E. faecium (n=26) HLGRI 17 (10.6%) 1(3.8%) HLSRII
70 (63.6%) 12 (46.2%) HLSR-HLGRIII
17 (15.4%) 3(11.5%) HLSR-VREIV
2 (1.8%) 1(3.8%) VREV
3(2.7%) 1(3.8%) I High Level Gentamicin Resistance IIHigh Level Streptomycin Resistance III High Level Gentamicin Resistance - High Level Streptomycin Resistance IV High Level Streptomycin Resistance - Vancomycin Resistance VVancomycin Resistance
62
Figure 1.Prevalence of resistance to antimicrobials in Salmonella sp. isolated from chickens: farm vs retail stores in Bogota, Colombia, 2009.
0 10 20 30 40 50 60 70 80 90 100
ETPIPM
MEMFEPCTXFOXCAZXNL
CROCIP
ENRLVXAZT
AMKAMCAMPTZP
GENTOBSTRCZONALSTXNIT
TCYCHL
Cat
egor
izat
ion
of a
ntim
icro
bial
s ba
sed
on im
port
ance
in h
uman
med
icin
e
Resistant isolates (%)
Farm Retail
I
II
III
63
REFERENCES
1. [BD] Becton Dickinson. 2009. BDXpert™ System User’s Manual for BD Phoenix™ and BD EpiCenter™ . In, Detection of Resistance Markers/Resistance and Expert Interpretation of Associated Antimicrobial Agents Using the BDXpert System.
2. Aarestrup, F. M. 2005. Veterinary drug usage and antimicrobial resistance in bacteria of animal origin. Basic Clin Pharmacol Toxicol. 96:271-81.
3. Aarestrup, F. M. 2006. Antimicrobial resistance in bacteria of animal origin. ASM Press, Washington, D.C.
4. Aarestrup, F. M., and S. M. Pires. 2009. Comment on: Causal regulations vs. political will: why human zoonotic infections increase despite precautionary bans on animal antibiotics. Environ Int. 35:760-1.
5. Alali, W. Q., H. M. Scott, K. L. Christian, V. R. Fajt, R. B. Harvey, and D. B. Lawhorn. 2009. Relationship between level of antibiotic use and resistance among Escherichia coli isolates from integrated multi-site cohorts of humans and swine. Prev Vet Med. 90:160-7.
6. Alvarez, C., J. Cortes, A. Arango, C. Correa, and A. Leal. 2006. [Anti-microbial resistance in intensive care units in Bogota, Colombia, 2001-2003]. Rev Salud Publica (Bogota). 8 Suppl 1:86-101.
7. Anonymous. 2008. SPSS for Windows. In SPSS Inc., Chicago.
8. Bager, F. 2000. DANMAP: monitoring antimicrobial resistance in Denmark. Int J Antimicrob Agents. 14:271-4.
9. Barza, M. 2002. Potential mechanisms of increased disease in humans from antimicrobial resistance in food animals. Clin Infect Dis. 34 Suppl 3:S123-5.
10. Boerlin, P., and R. J. Reid-Smith. 2008. Antimicrobial resistance: its emergence and transmission. Anim Health Res Rev. 9:115-26.
11. Canadian Integrated Program for Antimicrobial Resistance Surveillance., and Public Health Agency of Canada. 2004. Canadian Integrated Program for Antimicrobial Resistance Surveillance. p. v. In Public Health Agency of Canada], [Guelph, ON.
12. Carroll, K. C., A. P. Borek, C. Burger, B. Glanz, H. Bhally, S. Henciak, and D. C. Flayhart. 2006. Evaluation of the BD Phoenix automated microbiology system for identification and antimicrobial susceptibility testing of staphylococci and enterococci. J Clin Microbiol. 44:2072-7.
13. CIPARS. 2007. CIPARS: Retail Field Staff Manual - Ontario. In Public Health Agency of Canada (ed.).
14. CIPARS. 2010. Canadian Integrated Program for Antimicrobial Resistance Surveillance (CIPARS), 2007. In Government of Canada. Public Health Agency of Canada., Guelph, ON.
15. Clinical and Laboratory Standards Institute. 2007. Performance Standards for Antimicrobial Susceptibility Testing. 19th. Informational Supplement. CLSI/NCCLS, Wayne, PA 19087-1898.
16. Clinical and Laboratory Standars Institute. 2008. Performance Standards for Antimicrobial Disk and Dilution Susceptibility Tests for Bacteria Isolated from animals. Approved Standards. Wayne, PA.
17. Courvalin, P. 2005. Antimicrobial Drug Resistance: "Prediction Is Very Difficult, Especially about the Future". Emerg Infect Dis. 11:1503-1506.
64
18. DANMAP. 2009. DANMAP 2008 - Use of antimicrobial agents and occurrence of antimicrobial resistance in bacteria from food animals, foods and humans in Denmark. In National Food Institute, Technical University of Denmark.
19. Dutil, L., R. Irwin, R. Finley, L. K. Ng, B. Avery, P. Boerlin, A. M. Bourgault, L. Cole, D. Daignault, A. Desruisseau, W. Demczuk, L. Hoang, G. B. Horsman, J. Ismail, F. Jamieson, A. Maki, A. Pacagnella, and D. R. Pillai. 2010. Ceftiofur resistance in Salmonella enterica serovar Heidelberg from chicken meat and humans, Canada. Emerg Infect Dis. 16:48-54.
20. Forward, K. R., K. M. Matheson, M. Hiltz, H. Musgrave, and C. Poppe. 2004. Recovery of cephalosporin-resistant Escherichia coli and Salmonella from pork, beef and chicken marketed in Nova Scotia. Can J Infect Dis Med Microbiol. 15:226-30.
21. Giguère, S. 2006. Antimicrobial therapy in veterinary medicine. Blackwell Pub., Ames, Iowa.
22. Hammerum, A. M., O. E. Heuer, H. D. Emborg, L. Bagger-Skjot, V. F. Jensen, A. M. Rogues, R. L. Skov, Y. Agerso, C. T. Brandt, A. M. Seyfarth, A. Muller, K. Hovgaard, J. Ajufo, F. Bager, F. M. Aarestrup, N. Frimodt-Moller, H. C. Wegener, and D. L. Monnet. 2007. Danish integrated antimicrobial resistance monitoring and research program. Emerg Infect Dis. 13:1632-9.
23. Kieke, A. L., M. A. Borchardt, B. A. Kieke, S. K. Spencer, M. F. Vandermause, K. E. Smith, S. L. Jawahir, and E. A. Belongia. 2006. Use of streptogramin growth promoters in poultry and isolation of streptogramin-resistant Enterococcus faecium from humans. J Infect Dis. 194:1200-8.
24. Leal, A. L., J. Eslava-Schmalbach, C. Alvarez, G. Buitrago, and M. Mendez. 2006. [Endemic tendencies and bacterial resistance markers in third-level hospitals in Bogota, Colombia]. Rev Salud Publica (Bogota). 8 Suppl 1:59-70.
25. Lestari, S. I., F. Han, F. Wang, and B. Ge. 2009. Prevalence and antimicrobial resistance of Salmonella serovars in conventional and organic chickens from Louisiana retail stores. J Food Prot. 72:1165-72.
26. Marano, N. N., S. Rossiter, K. Stamey, K. Joyce, T. J. Barrett, L. K. Tollefson, and F. J. Angulo. 2000. The National Antimicrobial Resistance Monitoring System (NARMS) for enteric bacteria, 1996-1999: surveillance for action. J Am Vet Med Assoc. 217:1829-30.
27. McDermott, P. F. 2006. Antimicrobial resistance in non-typhoidal Salmonellae. In F.M. Aarestrup (ed.), Antimicrobial resistance in bacteria of animal origen ASM Press, Washington, D.C.
28. McEwen, S. A., and P. J. Fedorka-Cray. 2002. Antimicrobial use and resistance in animals. Clin Infect Dis. 34 Suppl 3:S93-S106.
29. Meldrum, R. J., and I. G. Wilson. 2007. Salmonella and Campylobacter in United Kingdom retail raw chicken in 2005. J Food Prot. 70:1937-9.
30. Microsoft Corporation. 2006. Microsoft Office Access 2007. In.
31. Miranda, M. C., F. Perez, T. Zuluaga, R. Olivera Mdel, A. Correa, S. L. Reyes, and M. V. Villegas. 2006. [Antimicrobial resistance in gram negative bacteria isolated from intensive care units of Colombian hospitals, WHONET 2003, 2004 and 2005]. Biomedica. 26:424-33.
32. O'Brien, T. F. 2002. Emergence, spread, and environmental effect of antimicrobial resistance: how use of an antimicrobial anywhere can increase resistance to any antimicrobial anywhere else. Clin Infect Dis. 34 Suppl 3:S78-84.
33. Oprea, S. F., N. Zaidi, S. M. Donabedian, M. Balasubramaniam, E. Hershberger, and M. J. Zervos. 2004. Molecular and clinical epidemiology of vancomycin-resistant Enterococcus faecalis. J Antimicrob Chemother. 53:626-30.
65
34. Parveen, S., M. Taabodi, J. G. Schwarz, T. P. Oscar, J. Harter-Dennis, and D. G. White. 2007. Prevalence and antimicrobial resistance of Salmonella recovered from processed poultry. J Food Prot. 70:2466-72.
35. Perreten, V. 2005. Resistance in food chain in bacteria from animals: Relevance to human infections. In M.N.A.a.P.M. D. G. White (ed.), Frontiers in a antimicrobial resistance: a tribute to Stuart B. Levy ASM, Press, Washington, DC.
36. Phan, T. T., L. T. Khai, N. Ogasawara, N. T. Tam, A. T. Okatani, M. Akiba, and H. Hayashidani. 2005. Contamination of Salmonella in retail meats and shrimps in the Mekong Delta, Vietnam. J Food Prot. 68:1077-80.
37. Pointon, A., M. Sexton, P. Dowsett, T. Saputra, A. Kiermeier, M. Lorimer, G. Holds, G. Arnold, D. Davos, B. Combs, S. Fabiansson, G. Raven, H. McKenzie, A. Chapman, and J. Sumner. 2008. A baseline survey of the microbiological quality of chicken portions and carcasses at retail in two Australian states (2005 to 2006). J Food Prot. 71:1123-34.
38. Poppe, C., L. C. Martin, C. L. Gyles, R. Reid-Smith, P. Boerlin, S. A. McEwen, J. F. Prescott, and K. R. Forward. 2005. Acquisition of resistance to extended-spectrum cephalosporins by Salmonella enterica subsp. enterica serovar Newport and Escherichia coli in the turkey poult intestinal tract. Appl Environ Microbiol. 71:1184-92.
39. Public Health Agency of Canada. Canadian Integrated Program for Antimicrobial Resistance Survival (CIPARS). 2007. Methodology fo the isolation of Salmonella spp. from meat and poultry samples. p. 5. In, LLZA-Unite de Saint-Hyacinthe.
40. Public Health Agency of Canada. Canadian Integrated program for Antimicrobial Resistance Survival (CIPARS). 2007. Methodology for the isolation of E.coli from meat and poultry samples. In, LLZA-Unite de Saint-Hyacinthe.
41. Public Health Agency of Canada. Canadian Integrated Program for Antimicrobial Resistance Survival (CIPARS). 2007. Methodology for the isolation of Enterococcus faecium and Enterococcus faecalis from meat and poultry samples. In LLZA-Unite de Saint-Hyacinthe.
42. Ribeiro, A. R., Kellerman, A., Ruschel dos Santos, L. , Bessa, M.C., Pinheiro do Nascimiento, V. 2007. Salmonella spp. in raw broiler parts: occurrence, antimicrobial resistance profile and phage typing of the Salmonella Enteritidis isolates. Brazilian Journal of Microbiology. 38.
43. Sapkota, A. R., L. Y. Lefferts, S. McKenzie, and P. Walker. 2007. What do we feed to food-production animals? A review of animal feed ingredients and their potential impacts on human health. Environ Health Perspect. 115:663-70.
44. Secretaria de Gobierno de Bogota. 2008. Proyecto de Acuerdo 651 de 2008 (in Spanish). . In.
45. Silbergeld, E. K., J. Graham, and L. B. Price. 2008. Industrial food animal production, antimicrobial resistance, and human health. Annu Rev Public Health. 29:151-69.
46. Simjee, S., D. G. White, J. Meng, D. D. Wagner, S. Qaiyumi, S. Zhao, J. R. Hayes, and P. F. McDermott. 2002. Prevalence of streptogramin resistance genes among Enterococcus isolates recovered from retail meats in the Greater Washington DC area. J Antimicrob Chemother. 50:877-82.
47. Snyder, J. W., G. K. Munier, and C. L. Johnson. 2008. Direct comparison of the BD phoenix system with the MicroScan WalkAway system for identification and antimicrobial susceptibility testing of Enterobacteriaceae and nonfermentative gram-negative organisms. J Clin Microbiol. 46:2327-33.
48. Talbot, G. H., J. Bradley, J. E. Edwards, Jr., D. Gilbert, M. Scheld, and J. G. Bartlett. 2006. Bad bugs need drugs: an update on the development pipeline from the Antimicrobial Availability Task Force of the Infectious Diseases Society of America. Clin Infect Dis. 42:657-68.
66
49. Tenover, F. C. 2006. Mechanisms of antimicrobial resistance in bacteria. Am J Med. 119:S3-10; discussion S62-70.
50. van den Bogaard, A. E., and E. E. Stobberingh. 2000. Epidemiology of resistance to antibiotics. Links between animals and humans. Int J Antimicrob Agents. 14:327-35.
51. Wong, T. L., C. Nicol, R. Cook, and S. MacDiarmid. 2007. Salmonella in uncooked retail meats in New Zealand. J Food Prot. 70:1360-5.
67
Appendices
Appendix 1 Salmonella sp., E. coli and Enterococccus sp. isolation scheme
HANDLING PROCEDURE
Clean the bag with gauze sterile and 70 % alcohol. Cut the bag with sterile scissors and take out the sample with the sterile forceps.
Put 25 g of chicken in the bag for stomacher with 225 ml of buffered peptone water and mix for 15 minutes at 230 RPM in the stomacher.
Pour out the content in a sterile SCHOTT bottle of 500 ml for transport of the processed sample.
Salmonella sp. Use a sterile test-tube to transfer 50 ml to a 200 ml sterile bottle with lid. Incubate at 35°C for 24 h.
E. coli Use a sterile test-tube to transfer 50 ml to a sterile bottle with lid of 200 ml, that contains 50 ml of E. coli (EC) broth at double concentration. Incubate at 45°C for 24 h.
Enterococcus sp. Use a sterile test-tube to transfer 50 ml to a sterile bottle with lid of 200 ml, that contains 50 ml of Enterococcosel broth at double concentration. Incubate at 35°C for 24 h.
SAMPLE ALLOCATION
68
Appendix 2 Salmonella sp. isolation scheme from 50 ml of Buffered Peptone Water (BPW) incubated at 35°C for 24 hours
Check the purity of MCK plate. If the colonies are not pure repeat the procedure transferring the isolated colonies from the same MCK plates.
Transfer 0.1 ml from the 50 ml of BPW incubated to the Modified Semi-Solid Rappaport Vassiliadis (MSRV) plate using a pipette sterile. Incubate at 42°C for 24 to 72 h
Inspect the MSRV plate at 24 h. Take the distance measure from the inoculation point to the limit of migration.
If migration is not evident or <20 mm, the plate should be re-incubated up to 72 h, and then can be classified as migration negative.
If the limit of migration is >20 mm, transfer a loopful of growth from the migration edge on MRSV onto Chromoagar -Salmonella. Incubate at 35°C for 24 h.
Inspect the CHROMagar Salmonella plate to confirm light mauve to mauve-colored colonies.
Transfer a typical colony onto a MacConkey (MCK) plate for isolation. Repeat this procedure for three typical colonies. Incubate at 35°C for 24 h.
If the MCK plate shows typical growth lactose fermenting colonies, the sample will be classified as negative.
69
Appendix 2 (ctd) Salmonella sp. isolation scheme from 50 ml of BPW incubated at 35°C for 24 hours
Kliger
Azucares K/A UREA (-)
H2S variable INDOL (-)
Gas (+)
Check the purity of MCK plate. If the colonies are not pure repeat the procedure transferring the isolated colonies from the same MCK plates.
For each one of the isolates on the MCK plates, inoculate the isolated colonies in an Urea tube, SIM (Sulfur-Indol-Motility) tube and a tube of inclined Kliger Iron Agar. Incubate all of them at 35°C for 24 h.
Interpret the results of the biochemical tests.
If the results are typical for Salmonella sp., inoculate a BHI tube for each of the isolates beginning from a Trypticase soy agar (TSA) colony. Incubate at 35°C for 24 h.
Put 0.5 ml of turbid broth BHI in 4 cryovials with 0.5 ml of sterile glycerol. Mix in vortex and mark the cryo vials. Store frozen at -70°C
If the results are not typical the isolate will be classified as negative.
Typical results for Salmonella sp.; to read the test indol add 2 or 3 drops of Kovac’s reagent to the SIM tube.
70
Appendix 3 E. coli isolation scheme from 50 ml of BPW incubated at 35°C for 24 hours and from 50 ml of double concentration EC broth incubated et 45°C for 24 hours
For each isolate, transfer a loopful of the incubated mix onto a Eosin Methylene Blue (EMB) plate. Incubate at 35°C for 24 hours
If the EMB plate has typical growth for E. coli, select 3 typical colonies and inoculate each one onto a new EMB plate. Incubate at 35°C for 24 hours
If the plate of EMB does not have a metallic shine, typical of E. coli, the sample will be classified as negative.
Inspect the TSA plates for purity; if they are not pure, repeat the procedure transferring the isolated colonies from the same MCK plates.
For each isolate on TSA plates, inoculate beginning from the isolated colonies; one SIM tube and one inclined citrate tube. Incubate all of them at 35°C for 24 h.
The citrate should be incubated with the lid loose because its utilization requires oxygen.
If the EMB isolates are pure and confirm the growth of E.coli with metallic sheen, choose one well isolated colony and inoculate a TSA plate.
71
Appendix 3 (ctd): E. coli isolation scheme from 50 ml of BPW incubated at 35°C for 24 hours and from 50 ml of double concentration EC broth incubated et 45°C for 24 hours
INDOL CITRATE
(+) (-)
(-) (-)
Interpret the results of the biochemical tests.
If the results are not typical, the isolate will be classified as negative.
Typical results for E .coli; read the indole test by adding 2 or 3 drops of Kovac’s reagent to the SIM tube.
If the results are typical for E. coli, inoculate a BHI tube for each one of the isolates beginning from one colony from TSA. Incubate at 35°C for 24 h.
Put 0.5 ml of the turbid BHI broth in 4 cryovials with 0.5 ml of sterile glycerol. Mix in the vortex and mark the cryovials. Store frozen at -70°C
72
Appendix 4 Enterococcus faecalis and E. faecium isolation scheme from 50 ml of BPW incubated at 35°C for 24 hours and 50 ml of double concentration Enterococcosel incubated at 35°C for 24 hours
For each isolate, transfer a loopful of the incubated mix, onto an Enterococcosel plate. Incubate at 35°C for 24 to 48 h
If the Enterococcosel plate has typical growth for Enterococcus, select 3 typical colonies and inoculate them onto a new Enterococcus plates. Incubate at 35°C for 48 h
If at 24 h. there are not typical colonies for Enterococcus sp. (reduction of esculin), the sample will be re-incubated for 48h and then, could be classified as negative.
Check the Enterococcosel plates for purity; if they are not pure, repeat the procedure transferring the isolated colonies from the same Enterococcosel plates.
Take one typical colony from each plate and transfer a onto a Slanetz and Bartley (SB) agar plates. Incubate at 35°C for 48 h.
If 24 h later, there is growth or the broth turns brown.
If at 24 hours there is not growth or broth does not turn brown, the sample is classified as negative.
If at 24 hours there are not typical colonies of Enterococcus sp, the sample will be re-incubated up to 48 h and then can be classified as negative
73
Appendix 4. (ctd): Enterococcus faecalis and faecium isolation scheme from 50 ml of BPW incubated at 35°C for 24 hours and 50 ml of double concentration Enterococcosel incubated at 35°C for 24 hours From each plate of SB agar,
transfer a typical colony onto a TSA-Blood agar plate. Incubate at 35°C for 48 h.
Pick one colony from each pure plate of TSA-Blood and put it in a microscope slide and add a drop of hydrogen peroxide at 3%. If there is presence of bubbles,
the catalase test is positive (+) and the isolate is negative for Enterococcus sp.
Also, inoculate colonies from TSA-Blood agar onto tubes phenol red with 0.25% L-arabinosa and with 1% d-mannitol. Incubate at 35°C for 24 to 48 h.
Interpret the results of the biochemical tests for sugar fermentation (if the fermentation is positive the tube turns the color to yellow, if this is negative stays red), and check the TSA-Blood and SB agar plates. Compare with the next table.
For the test of fermentation you need to take a high quantity of inoculum because if the sample is insufficient, it is possible to obtain a false-negative. If at 24 h, the tube shows an orange coloring, the tube should be re-incubated up to 48 h.
74
Appendix 4 (ctd). Enterococcus faecalis and faecium isolation scheme from 50 ml of BPW incubated at 35°C for 24 hours and 50 ml of double concentration Enterococcus incubated at 35°C for 24 hours
Blood Agar SB agar l-Arabinose D-Mannitol
E. faecalis Medium Colonies Red colonies (-) (+)
No gamma-hemolisis
With or without metallic shine
E. faecium Small Colonies Red colonies (+) (+)
Partial α-hemolysis With or without metallic shine
If the results are typical for Enterococcus sp., from one colony on TSA, inoculate a BHI tube for each one of the isolates. Incubate at 35°C for 24 h.
Put 0.5 ml of the BHI turbid broth in 4 cryovials with 0.5 ml of sterile glycerol. Mix in vortex and mark the cryo vials. Store frozen at -70°C
75
Appendix 5 Minimum Inhibitory concentration (MIC) range and interpretations for antimicrobials used in the gram-negative panel for Salmonella sp, E.coli and Enterococcus sp.
Chapter 4 Molecular Characterization of Salmonella Paratyphi B Dt+ (S. Java) and Salmonella Heidelberg from Poultry and Retail Chicken Meat in Colombia. ABSTRACT
Salmonella Paratyphi B dT+ variant (also termed Salmonella Java) and Salmonella Heidelberg
are human pathogens that are frequently isolated from poultry. As part of the steps towards
implementing the Colombian Integrated Program for Antimicrobial Resistantence Surveillance
(COIPARS), this study characterized molecular patterns of S. Paratyphi B dT+ and Salmonella
Heidelberg isolated from poultry and retail chicken meat using pulsed-field gel electrophoresis
(PFGE). The objective of this study was to analyze the genetic relationship among isolates and to
determine potential geographically-predominant genotypes. Both serovars exhibited marked
heterogeneity. The DNA fingerprinting of 82 isolates of S. Paratyphi B dT+ revealed 42 patterns,
while the PFGE of the 21isolates of S. Heidelberg revealed 10 patterns. Similar genotypes of both
serovars were demonstrated to be present in farms and in retail outlets. For S. Paratyphi B dT+,
closely genetically related isolates were found among isolates coming from different farms and
different integrated poultry companies within both departments (Santander and Cundinamarca)
and from farms located in the two geographically distant departments. For S. Heidelberg, the
number of farms with genetically related isolates was less than for S.Paratyphi B dT+. A possible
dissemination of similar genotypes of both serovars along the poultry chain is hypothesized and
some facilitating factors existing in Colombia are reviewed. To further characterize the potential
risks for human outbreaks related to the presence of these two Salmonella serovars in the
Colombian poultry chain, and to monitor the dynamic evolution of their clonage lineages in
Colombia, longitudinal studies using pulsed-field gel electrophoresis combined with other
molecular sub-typing methods are needed.
INTRODUCTION
Salmonella Paratyphi B d-tartrate-fermenting (dT+) variant (also termed Salmonella Java) and
Salmonella Heidelberg are food-borne pathogens associated worldwide with human
83
salmonellosis (16, 20). Risks associated with these two human pathogens are two-fold: their
specific pathogenicity in humans and their multidrug resistance (MDR) profiles to antimicrobials.
Salmonella Paratyphi B dT+ is an emerging public health pathogen that causes enteric fever and
self-limiting gastroenteritis (7, 36). Salmonella Paratyphi B dT+ has animal reservoirs and has
caused significant outbreaks in several countries as a result of the contamination of food products
(36). The organism has been reported in poultry worldwide (4, 17, 33) and is thought to become
the most important pathogen at the end of the broiler growing period (33). Strains of S. Paratyphi
B dT+ are generally multidrug resistant (MDR) to antimicrobials such as ampicillin,
chloramphenicol, streptomycin, spectomycin, sulphonamides and tetracyclines (11). Salmonella
Heidelberg was among the top four serotypes isolated in 2006 in the US from human
salmonellosis cases (6) and was associated with approximately 7% of Salmonella-related deaths.
Salmonella Heidelberg is mainly derived from poultry, is notable for MDR and is of great concern,
because it can cause septicemia and myocarditis (22). Antimicrobial resistant (AMR) S. Paratyphi
B as well as AMR S. Heidelberg can spread through the food chain from the primary production
to the retail chicken meat resulting in significant risks to human health.
To monitor food-borne pathogens and to conduct AMR surveillance, the World Health
Organization has recommended a three-fold approach to include human clinical cases, food
animals and retail meats(37). Countries like Canada (8), USA (21) and Denmark (1) have
established integrated and unified programs for the surveillance of antimicrobial resistance.
These programs integrate the data along the food chain in order to monitor food-borne pathogens
and to prevent the spread of AMR bacteria from animals to humans.
The current study is part of a pilot initiative to implement an integrated system in Colombia,
namely COIPARS (Colombian Integrated Program for Antimicrobial Resistance Surveillance). In
the first phase, the prevalence of Salmonella isolates and Salmonella serovars and their
antimicrobial resistance patterns were defined in chickens on 70 farms including 350 houses from
the two main poultry production departments of Colombia: Santander and Cundinamarca. That
study was followed by a second in retail poultry meat of 100 independent stores and the main
84
chain distributor center in Bogota District Capital (DC). Results from this preliminary study
showed a prevalence of 41.4% of Salmonella isolates on farms (65% at house level), and 25.5%
in retail meat samples. Salmonella Paratyphi B dT+ was the most prevalent serovar (76.4%) on
farms and in retail meat samples (51%), followed by S. Heidelberg, 22.7% and 15.7% on farms
and retail meat samples, respectively. Both serovars exhibited MDR profiles to antibiotics.
In this study we characterized the molecular patterns of isolates of S. Paratyphi B dT+ and S.
Heidelberg obtained from poultry farms from Santander and Cundinamarca, and from
independent stores and the main retailer distribution center of Bogota DC. We used Pulsed-field
gel electrophoresis (PFGE) since it is among the most reliable, discriminatory, and reproducible
typing methods to detect high degrees of DNA polymorphism for epidemiological purposes (12,
25, 38). The objectives of this study were to assess the genetic relatedness of these isolates and
to determine whether there were geographically predominant clones.
MATERIALS AND METHODS
Salmonella strain sources
A total of 114 serotyped (Kauffman-White scheme) Salmonella isolates were included in this
study. Salmonella were collected during 2008 and 2009 on poultry farms from the departments of
Santander and Cundinamarca, and from independent retail stores and a main chain meat
distributor center in Bogota DC and were kept frozen at -70C. Salmonella Paratyphi B dT+
isolates (n = 85) were obtained from three different sources: 38 drag swabs samples and 16 fecal
samples from 29 poultry farms; 6 cecal content samples obtained in processing plants and from
25 retail chicken meat samples from 10 independent stores and one main chain center of Bogota
DC. Twenty-nine isolates of S. Heidelberg came from 16 drag swabs and 5 feces from poultry
farms and, from 8 samples from retail stores.
Pulsed-field gel electrophoresis analysis (PFGE)
PFGE was used to assess the genetic relatedness following the protocol of the Centers for
Disease Control and Prevention (27) with the following modifications. Cell suspensions were
made using the procedure of the National Health Institute of Colombia (INS), which consisted of
85
suspending the cells in 2 ml of cell suspension buffer (100 mM Tris:100 mM EDTA, pH 8.0; CSB)
and then a dilution of 1:10 of the initial suspension (1900 µl CSB plus 100 µl of the initial
suspension) was made. Next, the concentration of the cell suspension was adjusted to an optical
density (OD) of 1.35 at 610 nm in the spectrophotometer. Finally, the concentration was adjusted
to a final volume of 200 µl with cell suspension using the following formula 200 /(OD x 10) where
200 is the final volume, OD is the optical density and 10 is the dilution factor. Ten microliters of
proteinase K (Sigma-Aldrich, Baltimore MD, USA) solution (20 mg/ml) was added to the
suspension. Casting plugs were made with 1% Seakem Gold agarose (Cambrex, Cambridge MD,
USA). The isolates were processed by adding 200 µl of 1% Seakem Gold agarose to 200 µl of
the cell suspension. Digestion of DNA was performed by incubating a quarter of each casting
plug with Xbal (Fermentas, Burlington ON, Canada). Gel electrophoresis was carried out using a
CHEF DR–III unit (Bio-Rad, Hercules, CA) with an initial and final switch times of 2.2 and 63.8
seconds, respectively. The included angle was 120º at 14ºC and the run time was 18 hours.
Salmonella Braenderup H9812 was used as reference strain on each gel. Gels were stained with
ethidium bromide (10mg/ml) and photographed in Gel Doc. Genotypes were compared
(Molecular Analysis Fingerprinting Software, version 1.6, Bio-Rad Laboratories, Hercules, CA) by
the use of the Dice coefficient of similarity with the unweighted pair group technique using
arithmetic averages (UPGMA) to prepare the dendograms. To evaluate different patterns, a
demarcation system based on the concepts of Tenover (32) were used: ≥ 93%, probably the
same isolate; 85 to 92%, very similar; 80 to 84%, similar: 75 to 79%, somewhat similar; and ≤
74%, not similar. This criteria states that if an isolate varies from a main type by just three or
fewer bands, it will be considered as a subtype.
RESULTS
The genotypes obtained by PFGE were analyzed separately by Salmonella serovar category and
similarity dendograms were constructed for S. Paratyphi B dT+ (Figure 1) and S. Heidelberg
(Figure 2). Both serovars exhibited extensive heterogeneity. Of the 114 isolates, 103 were
differentiated with the use of PFGE. Eleven isolates were not include in the analysis because they
either were untypable due to DNA degradation (29) or had insufficient DNA loading.
86
Salmonella Paratyphi B dT+.
The DNA fingerprinting by PFGE of the 82 isolates revealed 42 patterns: 19 patterns among the
37 isolates from farms of the department of Santander (SA), 9 patterns among the 20 isolates
from farms of Cundinamarca (RC) and 20 patterns among the 25 isolates from retail stores from
Bogota DC.
The similarity dendogram of S. Paratyphi B dT+ genotypes showed three clusters of 30 (C1), 27
(C2) and 5 (C3) isolates with a percentage similarity coefficient (% SC) of > 85 % within each
cluster. For C1, 50 % of isolates were from farms of 3 different integrated companies operating in
Santander department; 27% were isolates from farms of a single integrated company operating in
Cundinamarca and 23% of the isolates were isolates from retail stores and the chain center in
Bogota DC. For C2 (n=27), 56, 26 and 18 % of isolates were isolates from farms in Santander
department (belonging to four different integrated companies), farms in Cundinamarca (belonging
to three integrated companies) and retail stores and main chain center of Bogota DC, respectively.
For C3, all the isolates were from retail market chicken collected in Bogota DC.
Two groups of 9 and 22 indistinguishable isolates were identified within C1 and C2 clusters
respectively. In both groups, isolates were isolates from farms of Santander and of Cundinamarca
as well as from retail chicken meat from Bogota.
Salmonella Heidelberg
The DNA fingerprinting by PFGE of the 21 isolates revealed 10 patterns: 8 patterns among the 13
isolates from farms of the department of Santander, 3 patterns from farms of Cundinamarca and
4 patterns among the isolates of retail from Bogota DC (See Figure 2)
The similarity dendogram of Salmonella Heidelberg genotypes showed one cluster of 8 isolates
with a %SC of > 85 %. All the isolates were isolates from farms of Santander belonging to 2
integrated companies. Within the cluster, 5 isolates coming from farms of one integrated
company were indistinguishable.
DISCUSSION
87
The present study showed that S.Paratyphi B dT+ and S. Heidelberg isolates obtained from the
two most important poultry producing departments, and the retail meat of the area with the
greatest chicken consumption in Colombia, exhibited high genetic heterogeneity. The
demonstrated presence of S. Paratyphi B dT+, which had not been reported in Colombia to date,
and S. Heidelberg, with hypothesized dissemination along the Colombian poultry chain may
create a risky situation for possible human outbreaks as has been shown in Europe and USA (6,
36).
For S. Paratyphi B dT+, the finding of high genetic heterogeneity appears to be different from the
one reported in Germany where one clonage lineage of S. Paratyphi B dT+ successfully
displaced the others after a period of time (23). As far as S. Heidelberg is concerned, the genetic
diversity found in this study is consistent with results reported by Linne et al. (20), in a study of S.
Heidelberg isolates from food animals in the USA that showed 30 patterns among 58 S.
Heidelberg isolates tested using XbaI.
The presence of closely genetically related S. Paratyphi B dT+ isolates in this study, some of
them with indistinguishable PFGE patterns, between poultry farms of the two departments and
the retail stores, between farms within the same department, and between farms located in the
two distant departments led us to hypothesize about possible dissemination of clones along the
poultry chain in Colombia. The possible causes of the dissemination of S. Paratyphi B dT+ could
be related to the contamination from the environment (10), to the findings that hygiene measures
seem to be not as effective for S. Paratyphi B dT+ as they are for other Salmonella (S. Enteritidis,
S. Infantis and S. Virchow)(35) and to the ability of this serovar to colonize and to rapidly spread
within a group of chickens and persist until slaughter (34).
Some specific poultry industry practices in Colombia could facilitate dissemination of S. Paratyphi
B dT+. The transportation of birds to the abattoirs is done in open trucks using the same plastic
boxes for different farms that could facilitate farm-to-farm contamination(24). Use of the same
feed trucks for many farms in the same company should be considered as a possible cause of
cross-contamination between farms (28). Also, most of the farms have soil floors which readily
88
allow for the development and persistence of rodent and beetle populations that can transmit
Salmonella between adjoining farms (30). Similarly, farms belonging to different integrated
companies are geographically mixed and the reduced distances between farms, between the
sources of water and the poor isolation measures makes an effective Salmonella control program
difficult (3). Finally, poultry manure is transported and commercialized across the country in order
to use it as fertilizer or feed components for other animal productions(26).
For S. Heidelberg, the presence of closely genetically related isolates, some of them with
indistinguishable PFGE patterns, has been shown to exist on poultry farms of the two
departments and the retail stores and mainly between farms within Santander department. The
possible dissemination within a department appears to be less than for S. Paratyphi B dT+.
Almost 90% of the isolates of the identified S. Heidelberg cluster came from the same integrated
company. This result could be correlated to the demonstrated S. Heidelberg vertical transmission
from layers to the eggs (13-15) making the hatchery of an integrated company a potential source
of contamination(18). Contamination of the integrated feedmill (9, 19) and the Salmonella status
of the previous flock also could play a role (5).
The demonstrated dynamic evolution of a clonal population of these serovars such as the
reported case for S. Paratyphi B dT+ in Europe (23) suggests the need for implementing
longitudinal studies in the poultry chain in Colombia including hatchery, farms, slaughter houses
and retail stores. Even though PFGE is considered the “gold standard” of the molecular typing
techniques and is used worldwide for outbreak investigations, is a technically challenging
technique with some limitations as reported by Barret et al. (2). Therefore, we recommend that
for these longitudinal studies the PFGE analysis should be complemented by other molecular
tools such DNA microarrays that are more discriminative than PFGE. (31).
89
REFERENCES
1. Bager, F. 2000. DANMAP: monitoring antimicrobial resistance in Denmark. Int J Antimicrob Agents. 14:271-4.
2. Barrett, T. J., P. Gerner-Smidt, and B. Swaminathan. 2006. Interpretation of pulsed-field gel electrophoresis patterns in foodborne disease investigations and surveillance. Foodborne Pathog Dis. 3:20-31.
3. Benschop, J., M. L. Hazelton, M. A. Stevenson, J. Dahl, R. S. Morris, and N. P. French. 2008. Descriptive spatial epidemiology of subclinical Salmonella infection in finisher pig herds: application of a novel method of spatially adaptive smoothing. Vet Res. 39:02.
4. Boscan-Duque, L. A., A. M. Arzalluz-Fisher, C. Ugarte, D. Sanchez, T. E. Wittum, and A. E. Hoet. 2007. Reduced susceptibility to quinolones among Salmonella serotypes isolated from poultry at slaughter in Venezuela. J Food Prot. 70:2030-5.
5. Cardinale, E., F. Tall, E. F. Gueye, M. Cisse, and G. Salvat. 2004. Risk factors for Salmonella enterica subsp. enterica infection in Senegalese broiler-chicken flocks. Prev Vet Med. 63:151-61.
6. CDC. 2008. Salmonella Surveillance: Annual Summary, 2006. In US Department of Health and Human Services, Atlanta, Georgia.
7. Chart, H. 2003. The pathogenicity of strains of Salmonella Paratyphi B and Salmonella java. J Appl Microbiol. 94:340-8.
8. CIPARS. 2010. Canadian Integrated Program for Antimicrobial Resistance Surveillance (CIPARS), 2007. In Government of Canada. Public Health Agency of Canada., Guelph, ON.
9. Corry, J. E., V. M. Allen, W. R. Hudson, M. F. Breslin, and R. H. Davies. 2002. Sources of Salmonella on broiler carcasses during transportation and processing: modes of contamination and methods of control. J Appl Microbiol. 92:424-32.
10. Crippen, T. L., C. L. Sheffield, K. Andrews, S. E. Dowd, R. J. Bongaerts, and D. J. Nisbet. 2008. Planktonic and biofilm community characterization and Salmonella resistance of 14-day-old chicken cecal Microflora-derived continuous-flow cultures. J Food Prot. 71:1981-7.
11. Denny, J., J. Threlfall, J. Takkinen, S. Lofdahl, T. Westrell, C. Varela, B. Adak, N. Boxall, S. Ethelberg, M. Torpdahl, M. Straetemans, and W. van Pelt. 2007. Multinational Salmonella Paratyphi B variant Java (Salmonella Java) outbreak, August - December 2007. Euro Surveill. 12:E071220 2.
12. Edrington, T. S., C. L. Schultz, K. M. Bischoff, T. R. Callaway, M. L. Looper, K. J. Genovese, Y. S. Jung, J. L. McReynolds, R. C. Anderson, and D. J. Nisbet. 2004. Antimicrobial resistance and serotype prevalence of Salmonella isolated from dairy cattle in the southwestern United States. Microb Drug Resist. 10:51-6.
13. Gast, R. K., J. Guard-Bouldin, and P. S. Holt. 2005. The relationship between the duration of fecal shedding and the production of contaminated eggs by laying hens infected with strains of Salmonella enteritidis and Salmonella Heidelberg. Avian Dis. 49:382-6.
14. Gast, R. K., R. Guraya, J. Guard-Bouldin, P. S. Holt, and R. W. Moore. 2007. Colonization of specific regions of the reproductive tract and deposition at different locations inside eggs laid by hens infected with Salmonella enteritidis or Salmonella heidelberg. Avian Dis. 51:40-4.
15. Gast, R. K., P. S. Holt, and T. Murase. 2005. Penetration of Salmonella enteritidis and Salmonella heidelberg into egg yolks in an in vitro contamination model. Poult Sci. 84:621-5.
90
16. Gupta, S. K., F. Medalla, M. W. Omondi, J. M. Whichard, P. I. Fields, P. Gerner-Smidt, N. J. Patel, K. L. Cooper, T. M. Chiller, and E. D. Mintz. 2008. Laboratory-based surveillance of paratyphoid fever in the United States: travel and antimicrobial resistance. Clin Infect Dis. 46:1656-63.
17. Huehn, S., R. Helmuth, C. Bunge, B. Guerra, E. Junker, R. H. Davies, P. Wattiau, W. van Pelt, and B. Malorny. 2009. Characterization of pathogenic and resistant genome repertoire reveals two clonal lines in Salmonella enterica subsp. enterica serovar Paratyphi B (+)-tartrate positive. Foodborne Pathog Dis. 6:431-43.
18. Kim, A., Y. J. Lee, M. S. Kang, S. I. Kwag, and J. K. Cho. 2007. Dissemination and tracking of Salmonella spp. in integrated broiler operation. J Vet Sci. 8:155-61.
19. Liebana, E., C. J. Crowley, L. Garcia-Migura, M. F. Breslin, J. E. Corry, V. M. Allen, and R. H. Davies. 2002. Use of molecular fingerprinting to assist the understanding of the epidemiology of Salmonella contamination within broiler production. Br Poult Sci. 43:38-46.
20. Lynne, A. M., P. Kaldhone, D. David, D. G. White, and S. L. Foley. 2009. Characterization of antimicrobial resistance in Salmonella enterica serotype Heidelberg isolated from food animals. Foodborne Pathog Dis. 6:207-15.
21. Marano, N. N., S. Rossiter, K. Stamey, K. Joyce, T. J. Barrett, L. K. Tollefson, and F. J. Angulo. 2000. The National Antimicrobial Resistance Monitoring System (NARMS) for enteric bacteria, 1996-1999: surveillance for action. J Am Vet Med Assoc. 217:1829-30.
22. McDermott, P. F. 2006. Antimicrobial resistance in non-typhoidal Salmonellae. In F.M. Aarestrup (ed.), Antimicrobial resistance in bacteria of animal origen ASM Press, Washington, D.C.
23. Miko, A., B. Guerra, A. Schroeter, C. Dorn, and R. Helmuth. 2002. Molecular characterization of multiresistant d-tartrate-positive Salmonella enterica serovar Paratyphi B isolates. J Clin Microbiol. 40:3184-91.
24. Murray, C. J. 2000. Environmental Aspects of Salmonella. p. x, 463 p. In C. Wray, and A. Wray (ed.), Salmonella in domestic animals CABI Pub., Wallingford, Oxon, UK ; New York, NY, USA.
25. Oloya, J., D. Doetkott, and M. L. Khaitsa. 2009. Antimicrobial drug resistance and molecular characterization of Salmonella isolated from domestic animals, humans, and meat products. Foodborne Pathog Dis. 6:273-84.
26. Poppe, C. 2000. Salmonella Infections in the Domestic Fowl. p., 463 p. In C. Wray, and A. Wray (ed.), Environmental Aspects of Salmonella. CABI Pub., Wallingford, Oxon, UK ; New York, NY, USA.
27. Ribot, E. M., M. A. Fair, R. Gautom, D. N. Cameron, S. B. Hunter, B. Swaminathan, and T. J. Barrett. 2006. Standardization of pulsed-field gel electrophoresis protocols for the subtyping of Escherichia coli O157:H7, Salmonella, and Shigella for PulseNet. Foodborne Pathog Dis. 3:59-67.
28. Rose, N., F. Beaudeau, P. Drouin, J. Y. Toux, V. Rose, and P. Colin. 1999. Risk factors for Salmonella enterica subsp. enterica contamination in French broiler-chicken flocks at the end of the rearing period. Prev Vet Med. 39:265-77.
29. Silbert, S., L. Boyken, R. J. Hollis, and M. A. Pfaller. 2003. Improving typeability of multiple bacterial species using pulsed-field gel electrophoresis and thiourea. Diagn Microbiol Infect Dis. 47:619-21.
30. Skov, M. N., A. G. Spencer, B. Hald, L. Petersen, B. Nauerby, B. Carstensen, and M. Madsen. 2004. The role of litter beetles as potential reservoir for Salmonella enterica and thermophilic Campylobacter spp. between broiler flocks. Avian Dis. 48:9-18.
91
31. Szabo, I., S. Hühn, B. Malorny, B. Guerra, C. Dorn, A. Schroeter and R. Helmuth. 2008. Epidemiology and Biology of d-Tartrate Positive Salmonella enterica Serovar Paratyphi B (S. Java). In K.A. Mooijman. (ed.), The thirteenth CRL-Salmonella workshop. National Institute for Public Health and Environment .Bilthoven, the Netherlands.
32. Tenover, F. C., R. D. Arbeit, R. V. Goering, P. A. Mickelsen, B. E. Murray, D. H. Persing, and B. Swaminathan. 1995. Interpreting chromosomal DNA restriction patterns produced by pulsed-field gel electrophoresis: criteria for bacterial strain typing. J Clin Microbiol. 33:2233-9.
33. van Asselt, E. D., J. T. Thissen, and H. J. van der Fels-Klerx. 2009. Salmonella serotype distribution in the Dutch broiler supply chain. Poult Sci. 88:2695-701.
34. Van Immerseel, F., L. Meulemans, J. De Buck, F. Pasmans, P. Velge, E. Bottreau, F. Haesebrouck, and R. Ducatelle. 2004. Bacteria-host interactions of Salmonella Paratyphi B dT+ in poultry. Epidemiol Infect. 132:239-43.
35. van Pelt, W., H. van der Zee, W. J. Wannet, A. W. van de Giessen, D. J. Mevius, N. M. Bolder, R. E. Komijn, and Y. T. van Duynhoven. 2003. Explosive increase of Salmonella Java in poultry in the Netherlands: consequences for public health. Euro Surveill. 8:31-5.
36. Weill, F. X., L. Fabre, B. Grandry, P. A. Grimont, and I. Casin. 2005. Multiple-antibiotic resistance in Salmonella enterica serotype Paratyphi B isolates collected in France between 2000 and 2003 is due mainly to strains harboring Salmonella genomic islands 1, 1-B, and 1-C. Antimicrob Agents Chemother. 49:2793-801.
37. World Health Organization. 2001. WHO Global Strategy for Containment of Antimicrobial Resistance. Genevae.
38. Xia, X., S. Zhao, A. Smith, J. McEvoy, J. Meng, and A. A. Bhagwat. 2009. Characterization of Salmonella isolates from retail foods based on serotyping, pulse field gel electrophoresis, antibiotic resistance and other phenotypic properties. Int J Food Microbiol. 129:93-8.
92
Figure 1 Similarity dendogram of S. Paratyphi B dT+ macrorestriction patterns generated using Xbal. Clone column indicates the number of indistinguishable isolates presenting the same PFGE pattern. The clusters are mentioned as Cx (percentage similarity coefficient). The origins of the isolates are reported as Santander farms, Cundinamarca farms, Independent retail shops or retail chain in Bogota DC. The different integrated companies are identified as SaOx or RcOx. The scale bar indicates percent similarity coefficient.
92
11
A
I
158
133
137
169
30
69
159
39
25
22
87
121
136
146
81
G
140
74
128
61
18
55
120
8
149
23
160
161
125
162
127
1
29
46
J
4
27
164
100908070605040 Ref. Clones Santander
Farm
Cundinamarca
Farm
Independent
Retail
Chain
Retail
92 Sa03
11 Sa01
A A
I Sa03
158 2 Sa01 1
133 Rc04
137 Sa01
169 Rc04
30 2 2 Rc04
69 Rc04
159 1
39 Sa01
25 Rc04
22 Rc04
87 Sa01
121 2 A Rc04
136 Sa01
146 9 Sa01,Sa02 ,3 Sa03 3Rc04 Rc04
81 Sa03
G 3 2 Sa01, Sa02
140 Sa01
74 Rc04
128 Sa02
61 Rc04
18 Sa02
55 Rc04
120 3 Sa01 E, Rc04
8 22 6 Sa01, 2 Sa02, 3Sa03, Sa05 3 Rc04, Rc01, 2 Rc03, Rc07 A O, Rc04
149 2 2 Sa03
23 3 Rc01, Rc03, Rc05
160 1
161 1
125 Rc04
162 1
127 O
1 Sa03
29 Rc05
46 Sa02
J 2 Sa01 1
4 Sa03
27 Rc04
164 1
c1
(88.1)
c2
(87.2)
c3
(86.5)
93
Ref Clones Santander
Farm
Cundina-marca
Farm Independent
Retail Chain Retail
Sa03
1
Sa01 A
2 Sa01, Sa03
5 5 Sa01
Sa01
2 Rc08 Rc08
Sa03
Sa01 2 Rc04
3 Sa01 Rc05 Rc09
Figure 2 Similarity dendogram of S. Heidelberg macro restriction patterns generated using Xbal. Clone column indicates the number of indistinguishable isolates presenting the same PFGE pattern. The cluster is mentioned as Cx (percentage of similarity coefficient). The origin of the isolates are reported as Santander farms, Cundinamarca farms, independent retail shops or retail chain in Bogota, DC. The different integrated companies are identified as SaOx or RcOx. The scale bar indicates percent similarity.
41
C
E
F
14
6
68
178
H
B
1009080706050
c (87/6%)
94
Chapter 5 Conclusion Our research provided four main indications about the current situation in the Colombian poultry
chain concerning one food-borne pathogen, Salmonella sp., and two commensal bacteria:
Escherichia coli and enterococci. First, we found a high prevalence of Salmonella sp. in
commercial broiler farms (41%) and in retail meat samples (26%). Second, Salmonella Paratyphi
B dT+ and Salmonella Heidelberg were the most frequent serovars among Salmonella isolates
on farms and in retail meat samples. This is the first time that Salmonella Paratyphi B dT+ has
been reported in the poultry chain in Colombia. Third, Salmonella isolated from farms and retail
meat, as well as Escherichia coli and enterococci isolated from chicken meat, showed extensive
resistance to antimicrobial agents. Ninety-eight percent of isolates were reported as multi-drug
resistant. Ceftiofur, enrofloxacin, nalidixic acid and tetracycline were the antimicrobials that
showed the highest frequency of resistance among Salmonella and E. coli isolates. For
enterococci, we found that 62% of E. faecium isolates were resistant to quinupristin/dalfopristin,
which is used to treat nosocomial human infections when vancomycin resistance is present.
Fourth, the DNA fingerprinting of S. Paratyphi B dT+ and S. Heidelberg isolates revealed that
similar genotypes of both serovars were present in farms and in retail outlets, as well as among
isolates coming from different farms within each region and from farms located in the two
geographically distant departments.
These findings indicate potential risks for human health in Colombia related to food-borne
infections with bacteria of poultry origin. These risks are related to the high prevalence of
Salmonella, the extensive antimicrobial resistance (AMR) of the food-borne pathogen and two
commensal bacteria surveyed, and to the possible dissemination of these pathogens along the
poultry chain. Because the potential impact on human health can be significant, further
characterization of these risks and development of appropriate measures to mitigate them are
needed. We recommend that further studies be done to determine if the profiles of Salmonella,
Escherichia coli and enterococci isolates from humans show any similarity with the profiles of the
isolates from the poultry chain. Furthermore, studies should also take place to confirm the
hypothesized dissemination of Salmonella along the poultry chain, which could be followed by a
95
review of the efficiency of biosecurity measures currently implemented in Colombia’s poultry
sector. Finally, the extensive AMR profiles we found trigger the need for an in-depth assessment
of the antimicrobial drug usage in the production sector.
The future research agenda should therefore include a comparison of phenotypic AMR and
genotypic profiles of Salmonella, Escherichia coli and enterococci of human isolates with those of
the poultry chain. The dynamic evolution of a clonal population of Salmonella sp. and their
potential circulation in the poultry chain should be investigated through longitudinal studies in the
poultry chain including hatchery, farms, slaughter houses and retail stores with phenotypic AMR
and genetic profiles characterization. In order to complement the results, new research on
consumption of antimicrobials through various stages of production in the poultry chain in
Colombia is also necessary. These data could be gathered by cross-sectional studies and also
by using the records gathered by the National Institute of Agriculture (ICA) on the kilograms of
active ingredient imported by pharmaceutical companies and by poultry companies. Once the use
of antimicrobials in the poultry primary chain is established, it would be necessary to adapt
existing software to monitor the antimicrobial use in the primary production. Finally, studies are
also needed to compare different practices of consumption of antimicrobial agents in animals (the
use of antimicrobials in low doses as growth promoters and the use of antimicrobials in-feed and
in-water for metaphylaxis and prophylaxis) along with the development of resistance.
In Colombia, the poultry production sector is facing a double challenge, i.e. increasing the volume
of production to address a rapidly growing national demand, and at the same time improving the
quality and food safety aspects of retail products. As in other emerging economies, the
Colombian poultry sector grows at a much higher rate than those of established economies such
as the USA. Due to the demographic and economic growth of the country and to the fact that the
buying capacity of a person on minimum wage is 124 kg of chicken meat, per capita consumption
of broiler meat increased substantially from 14.2 kg/year in 2000 to 22.7 kg/year in 2009. This
was nearly a 58% increase as compared to 16% during the same period for the USA. Between
2005 and 2009, the Colombian poultry production grew by 34%, whereas the US production
remained almost flat with less than 1% growth. In these dynamic conditions in Colombia, the
96
food safety aspects along the poultry chain face many challenges. Over the past decade, both
the Colombian poultry sector production and the authorities have attempted to reach international
food safety and animal health standards. Significant progress has been made through
implementation of Good Manufacturing Practices (GMPs) and Hazard Analysis Critical Control
Point (HACCP), which was recently made mandatory in slaughterhouses. However, our research
indicates that these efforts in the biosecurity area including the usage of antimicrobials need to be
strengthened, especially at the primary production level. Specifically for antimicrobial usage, it
would be interesting to monitor the efficiency of pilot measures that some countries have already
implemented. These include measures such as mandatory veterinary prescription for the use of
antimicrobials for any purpose in the animal industry, limitations on the veterinarian’s prescription,
registration of use and delivery of drugs by a veterinarian, or the prohibition of pharmacies and
pharmaceutical industries from offering economic incentives to the veterinarians for antimicrobial
sales.
All the stakeholders, poultry producers, retailers, agriculture and health authorities are conscious
about the challenges faced in Colombia. Fortunately, the conditions and the timing have been
conducive to strengthening the network of stakeholders that was initiated by our research project.
Indeed, it is the first time that most of the stakeholders who have a potential role in minimizing
AMR development have jointly participated. The technical procedures that our project used to
create this network and conduct surveillance should be published and adapted for the use in
other animal production systems such as bovine milk and meat, swine and aquaculture.
Finally, with the support of PAHO-WHO and the cooperation of stakeholders, we are looking
forward to the progressive implementation of COIPARS. Our recommendation is to continue the
expansion of the surveillance program by inviting other animal production sectors, such as the
swine and cattle, to participate in the process and develop similar plans that will help to improve
the food safety and biosecurity of the animal production chains in Colombia.