Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/38681
Title: Patterns of antimicrobial resistance in Salmonella isolates from fattening pigs in Spain
Authors: Teng, Kendy Tzu-Yun
AERTS, Marc 
JASPERS, Stijn 
Ugarte-Ruiz, Maria
Moreno, Miguel A.
Luis Saez, Jose
Collado, Soledad
de Frutos, Cristina
Dominguez, Lucas
Alvarez, Julio
Issue Date: 2022
Publisher: BMC
Source: BMC veterinary research, 18 (1) , p. 333 (Art N° 333)
Abstract: Background: Swine are considered a major source of foodborne salmonellosis, a public health issue further complicated by the circulation of multidrug-resistant Salmonella strains that threaten the safety of the food chain. The current study aimed to identify patterns that can help to understand the epidemiology of antimicrobial resistance (AMR) in Salmonella in pigs in Spain through the application of several multivariate statistical methods to data from the AMR national surveillance programs from 2001 to 2017. Results: A total of 1,318 pig Salmonella isolates belonging to 63 different serotypes were isolated and their AMR profiles were determined. Tetracycline resistance across provinces in Spain was the highest among all antimicrobials and ranged from 66.7% to 95.8%, followed by sulfamethoxazole resistance (range: 42.5% - 77.8%), streptomycin resistance (range: 45.7% - 76.7%), ampicillin resistance (range: 24.3% - 66.7%, with a lower percentage of resistance in the South-East of Spain), and chloramphenicol resistance (range: 8.5% - 41.1%). A significant increase in the percentage of resistant isolates to chloramphenicol, sulfamethoxazole, ampicillin and trimethoprim from 2013 to 2017 was observed. Bayesian network analysis showed the existence of dependencies between resistance to antimicrobials of the same but also different families, with chloramphenicol and sulfamethoxazole in the centre of the networks. In the networks, the conditional probability for an isolate susceptible to ciprofloxacin that was also susceptible to nalidixic acid was 0.999 but for an isolate resistant to ciprofloxacin that was also resistant to nalidixic acid was only 0.779. An isolate susceptible to florfenicol would be expected to be susceptible to chloramphenicol, whereas an isolate resistant to chloramphenicol had a conditional probability of being resistant to florfenicol at only 0.221. Hierarchical clustering further demonstrated the linkage between certain resistances (and serotypes). For example, a higher likelihood of multidrug-resistance in isolates belonging to 1,4,[5],12:i:- serotype was found, and in the cluster where all isolates were resistant to tetracycline, chloramphenicol and florfenicol, 86.9% (n =53) of the isolates were Typhimurium. Conclusion: Our study demonstrated the power of multivariate statistical methods in discovering trends and patterns of AMR and found the existence of serotype-specific AMR patterns for serotypes of public health concern in Salmonella isolates in pigs in Spain.
Notes: Teng, KTY (corresponding author), Univ Complutense, VISAVET Hlth Surveillance Ctr, Madrid, Spain.; Teng, KTY (corresponding author), Natl Chung Hsing Univ, Coll Vet Med, Dept Vet Med, Taichung, Taiwan.
kendy.t.teng@gmail.com
Keywords: Multidrug resistance;Multivariate analysis;Typhimurium;1;4;[5];12:i:-;Bayesian network analysis;Hierarchical clustering
Document URI: http://hdl.handle.net/1942/38681
e-ISSN: 1746-6148
DOI: 10.1186/s12917-022-03377-3
ISI #: 000849473600001
Rights: The Author(s) 2022. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativeco mmons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
Category: A1
Type: Journal Contribution
Validations: ecoom 2023
Appears in Collections:Research publications

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