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Antimicrobial resistance has been described in all ecosystems, including wildlife. Here we investigated the presence of methicillin-resistant and susceptible staphylococci in both colony-born and wild vervet monkeys (Chlorocebus sabaeus). Through selective isolation, PCR, MALDI-TOF, and whole-genome sequencing, methicillin-resistant and susceptible Staphylococcus spp. isolated from vervet monkeys were characterized. We obtained putatively methicillin-resistant staphylococci from 29 of the 34 nasal samples collected. Strains were identified by MALDI-TOF analysis. Staphylococcus cohnii (n = 15) was the most commonly isolated species, while nine other species were isolated one or two times. PCR analysis indicated that eight [28%] strains were mecA positive. The whole-genome sequencing [WGS] included eight methicillin-resistant strains (S. epidermidis (n = 2), S. cohnii (n = 3), S. arlettae (n = 2) and S. hominis (n = 1)), nine additional S. cohnii strains and two strains that could not be identified by MALDI-TOF, but genetically characterized as one S. cohnii and one S. warneri. Different resistance genes carried by different mobile genetic elements, mainly blaZ (n = 10) and tet(K) (n = 5) were found, while msr(A), cat, fosB, dfrG, erm(C), mph(C) and str were identified in one to three strains. Phylogenetic analysis of the S. cohnii strains based on SNPs indicated four clusters associated with colony born or wild. In addition, one singleton S. cohnii isolated did not form a separate group and clustered within other S. cohnii strains submitted to the NCBI. In this study, we demonstrated the presence of AMR and mobile genetic elements to both colony-born and wild vervet monkeys. We also identified a previously undescribed prevalence of S. cohnii in the nasal flora of these monkeys, which merits further investigation.

OBJECTIVES: WGS-based antimicrobial susceptibility testing (AST) is as reliable as phenotypic AST for several antimicrobial/bacterial species combinations. However, routine use of WGS-based AST is hindered by the need for bioinformatics skills and knowledge of antimicrobial resistance (AMR) determinants to operate the vast majority of tools developed to date. By leveraging on ResFinder and PointFinder, two freely accessible tools that can also assist users without bioinformatics skills, we aimed at increasing their speed and providing an easily interpretable antibiogram as output. METHODS: The ResFinder code was re-written to process raw reads and use Kmer-based alignment. The existing ResFinder and PointFinder databases were revised and expanded. Additional databases were developed including a genotype-to-phenotype key associating each AMR determinant with a phenotype at the antimicrobial compound level, and species-specific panels for in silico antibiograms. ResFinder 4.0 was validated using Escherichia coli (n = 584), Salmonella spp. (n = 1081), Campylobacter jejuni (n = 239), Enterococcus faecium (n = 106), Enterococcus faecalis (n = 50) and Staphylococcus aureus (n = 163) exhibiting different AST profiles, and from different human and animal sources and geographical origins. RESULTS: Genotype-phenotype concordance was ≥95% for 46/51 and 25/32 of the antimicrobial/species combinations evaluated for Gram-negative and Gram-positive bacteria, respectively. When genotype-phenotype concordance was <95%, discrepancies were mainly linked to criteria for interpretation of phenotypic tests and suboptimal sequence quality, and not to ResFinder 4.0 performance. CONCLUSIONS: WGS-based AST using ResFinder 4.0 provides in silico antibiograms as reliable as those obtained by phenotypic AST at least for the bacterial species/antimicrobial agents of major public health relevance considered.

Actinobacillus pleuropneumoniae is the etiological agent of porcine pleuropneumonia. Tetracycline is used for therapy of this disease, and A. pleuropneumoniae carrying the tet(B) gene, coding for an efflux protein that reduces the intercellular tetracycline level, has been described previously. Of the 46 tetracycline-resistant (Tcr) Spanish A. pleuropneumoniae isolates used in this study, 32 (70%) carried the tet(B) gene, and 30 of these genes were associated with plasmids. Eight (17%) isolates carried the tet(O) gene, two (4%) isolates carried either the tet(H) or the tet(L) gene, and all these genes were associated with plasmids. This is the first description of these tet genes in A. pleuropneumoniae. The last two Tcr isolates carried none of the tet genes examined. Except for tet(O)-containing plasmids, the other 34 Tcr plasmids were transformable into an Escherichia coli recipient. Two plasmids were completely sequenced. Plasmid p11745, carrying the tet(B) gene, was 5,486 bp and included a rep gene, encoding a replication-related protein, and two open reading frames (ORFs) with homology to mobilization genes of Neisseria gonorrhoeae plasmid pSJ7.4. Plasmid p9555, carrying the tet(L) gene, was 5,672 bp and, based on its G C content, consisted of two regions, one of putative gram-positive origin containing the tet(L) gene and the other comprising four ORFs organized in an operon-like structure with homology to mobilization genes in other plasmids of gram-negative bacteria

Actinobacillus pleuropneumoniae is the etiological agent of porcine pleuropneumonia. Tetracycline is used for therapy of this disease, and A. pleuropneumoniae carrying the tet(B) gene, coding for an efflux protein that reduces the intercellular tetracycline level, has been described previously. Of the 46 tetracycline-resistant (Tcr) Spanish A. pleuropneumoniae isolates used in this study, 32 (70%) carried the tet(B) gene, and 30 of these genes were associated with plasmids. Eight (17%) isolates carried the tet(O) gene, two (4%) isolates carried either the tet(H) or the tet(L) gene, and all these genes were associated with plasmids. This is the first description of these tet genes in A. pleuropneumoniae. The last two Tcr isolates carried none of the tet genes examined. Except for tet(O)-containing plasmids, the other 34 Tcr plasmids were transformable into an Escherichia coli recipient. Two plasmids were completely sequenced. Plasmid p11745, carrying the tet(B) gene, was 5,486 bp and included a rep gene, encoding a replication-related protein, and two open reading frames (ORFs) with homology to mobilization genes of Neisseria gonorrhoeae plasmid pSJ7.4. Plasmid p9555, carrying the tet(L) gene, was 5,672 bp and, based on its G C content, consisted of two regions, one of putative gram-positive origin containing the tet(L) gene and the other comprising four ORFs organized in an operon-like structure with homology to mobilization genes in other plasmids of gram-negative bacteria

The presence of antibiotic drug residues, antibiotic resistant bacteria, and antibiotic resistance genes in agroecosystems has become a significant area of research in recent years and is a growing public health concern. While antibiotics are used in both human medicine and agricultural practices, the majority of their use occurs in animal production where historically they have been used for growth promotion, in addition to the prevention and treatment of disease. The widespread use of antibiotics and the application of animal wastes to agricultural lands play major roles in the introduction of antibiotic-related contamination into the environment. Overt toxicity in organisms directly exposed to antibiotics in agroecosystems is typically not a major concern because environmental concentrations are generally lower than therapeutic doses. However, the impacts of introducing antibiotic contaminants into the environment are unknown, and concerns have been raised about the health of humans, animals, and ecosystems. Despite increased research focused on the occurrence and fate of antibiotics and antibiotic resistance over the past decade, standard methods and practices for analyzing environmental samples are limited and future research needs are becoming evident. To highlight and address these issues in detail, this special collection of papers was developed with a framework of five core review papers that address the (i) overall state of science of antibiotics and antibiotic resistance in agroecosystems using a causal model, (ii) chemical analysis of antibiotics found in the environment, (iii) need for background and baseline data for studies of antibiotic resistance in agroecosystems with a decision-making tool to assist in designing research studies, as well as (iv) culture- and (v) molecular-based methods for analyzing antibiotic resistance in the environment. With a focus on the core review papers, this introduction summarizes the current state of science for analyz

The presence of antibiotic drug residues, antibiotic resistant bacteria, and antibiotic resistance genes in agroecosystems has become a significant area of research in recent years and is a growing public health concern. While antibiotics are used in both human medicine and agricultural practices, the majority of their use occurs in animal production where historically they have been used for growth promotion, in addition to the prevention and treatment of disease. The widespread use of antibiotics and the application of animal wastes to agricultural lands play major roles in the introduction of antibiotic-related contamination into the environment. Overt toxicity in organisms directly exposed to antibiotics in agroecosystems is typically not a major concern because environmental concentrations are generally lower than therapeutic doses. However, the impacts of introducing antibiotic contaminants into the environment are unknown, and concerns have been raised about the health of humans, animals, and ecosystems. Despite increased research focused on the occurrence and fate of antibiotics and antibiotic resistance over the past decade, standard methods and practices for analyzing environmental samples are limited and future research needs are becoming evident. To highlight and address these issues in detail, this special collection of papers was developed with a framework of five core review papers that address the (i) overall state of science of antibiotics and antibiotic resistance in agroecosystems using a causal model, (ii) chemical analysis of antibiotics found in the environment, (iii) need for background and baseline data for studies of antibiotic resistance in agroecosystems with a decision-making tool to assist in designing research studies, as well as (iv) culture- and (v) molecular-based methods for analyzing antibiotic resistance in the environment. With a focus on the core review papers, this introduction summarizes the current state of science for analyz