RESUMO
Antimicrobial Resistance (AMR) poses a global threat to both human health and environmental well-being. Our study delved into Costa Rican wildlife reserves, uncovering a substantial human impact on these ecosystems and underscoring the imperative to pinpoint AMR hotspots. Embracing a One Health perspective, we advocated for a comprehensive landscape analysis that intricately intertwined geographic, climatic, forest, and human factors. This study illuminated the link between laboratory results and observed patterns of antimicrobial use, thereby paving the way for sustainable solutions. Our innovative methodology involved deploying open-ended questions to explore antimicrobial usage across livestock activities, contributing to establishing a comprehensive methodology. Non-invasive sampling in wildlife emerged as a critical aspect, shedding light on areas contaminated by AMR. Feline species, positioned at the apex of the food chain, acted as sentinels for environmental health due to heightened exposure to improperly disposed waste. Regarding laboratory findings, each sample revealed the presence of at least one antimicrobial resistance gene (ARG). Notably, genes encoding resistance to tetracyclines dominated (94.9%), followed by beta-lactams (75.6%), sulfonamides (53.8%), aminoglycosides (51.3%), quinolones (44.9%), phenicols (25.6%), and macrolides (20.5%). Genes encoding polymyxins were not detected. Moreover, 66% of samples carried a multi-resistant microbiome, with 15% exhibiting resistance to three antimicrobial families and 51% to four. The absence of a correlation between forest coverage and ARG presence underscored the profound human impact on wildlife reserves, surpassing previous estimations. This environmental pressure could potentially modify microbiomes and resistomes in unknown ways. As not all antimicrobial families encoding ARGs were utilized by farmers, our next step involved evaluating other human activities to identify the primary sources of contamination. This comprehensive study contributed crucial insights into the intricate dynamics of AMR in natural ecosystems, paving the way for targeted interventions and sustainable coexistence.
Assuntos
Ecossistema , Animais , Costa Rica , Antibacterianos/farmacologia , Gatos , Monitoramento Ambiental/métodos , Farmacorresistência Bacteriana , HumanosRESUMO
In this investigation, the presence of antibiotics and pharmaceuticals in Costa Rican surface waters, specifically in regions near feline habitats, was examined. The study revealed that 47% of the water samples contained detectable traces of at least one antibiotic. Ciprofloxacin and norfloxacin were the most frequently detected compounds, each with a detection rate of 27%. Other antibiotics, such as erythromycin, roxithromycin, and trimethoprim, were also found but at lower frequencies, around 14%. Notably, all antibiotic concentrations remained below 10 ng/L, with ciprofloxacin, norfloxacin, and erythromycin showing the highest concentrations. Furthermore, the investigation revealed the presence of non-antibiotic pharmaceutical residues in the water samples, typically at concentrations below 64 ng/L. Tramadol was the most frequently detected compound, present in 18% of the samples. The highest concentrations were observed for acetaminophen and tramadol, measuring 64 and 10 ng/L, respectively. Comparing these findings with studies conducted in treated wastewater and urban rivers, it became evident that the concentrations of antibiotics and pharmaceuticals were notably lower in this study. While previous research reported higher values, the limited number of studies conducted in protected areas raises concerns about the potential environmental impact on biodiversity. In summary, these results emphasize the importance of monitoring pharmaceutical residues and antimicrobial resistance genes ARGs in vulnerable ecosystems, especially those in close proximity to feline habitats in Costa Rica. Additionally, the study delved into the detection of (ARGs). All tested water samples were positive for at least one ARG, with the blaTEM gene being the most prevalent at 82%, followed by tetS at 64% and qnrB at 23%. Moreover, this research shed light on the complexity of evaluating ARGs in environmental samples, as their presence does not necessarily indicate their expression. It also highlighted the potential for co-selection and co-regulation of ARGs, showcasing the intricate behaviors of these genes in aquatic environments.
Assuntos
Roxitromicina , Tramadol , Poluentes Químicos da Água , Gatos , Animais , Antibacterianos/farmacologia , Antibacterianos/análise , Costa Rica , Farmacorresistência Bacteriana , Norfloxacino , Ecossistema , Ciprofloxacina , Preparações Farmacêuticas , Água , Rios/química , Monitoramento Ambiental , Poluentes Químicos da Água/análiseRESUMO
El objetivo del presente estudio fue evaluar el modelo NRC (1996) nivel I para la predicción de la ganancia diaria de peso en novillas suplementadas bajo condiciones tropicales. Para tal fin, se realizaron dos experimentos. En el experimento 1 se evaluaron 30 novillas divididas en dos grupos de 15 animales cada uno, el grupo suplementado (GS) presentó un peso inicial de 365,27 ± 24,40 kg, recibió concentrado a razón de 1% del peso vivo (5,5% PC, 2,85 Mcal ED) y el no suplementado (GNS) con un peso inicial de 367,47 ± 31,65 kg. En el experimento 2 se utilizaron 45 novillas divididas en dos grupos, el GSb con 22 animales, teniendo un peso inicial de 342,23 ± 36,04 kg se les proporcionó alimento a razón del 1% del peso vivo (13% PC; 3,15 Mcal ED) y el GNSb se constituyó por 23 animales teniendo un peso inicial promedio de 326,30 ± 31,53 kg. En ambos experimentos los animales fueron suplementados a lo largo de 45 días, y estuvieron pastoreando praderas de Estrella Africana (Cynodon nlemfuensis), Candelario (Pennisteum purpureum) y Ratana (Ischaemum indicum). En ambos experimentos no se observaron diferencias (P > 0,05) para los cambios de peso. El GS obtuvo ganancias diarias de peso (GDP) de 0,27 kg/d, mientras que el GNS mostró pérdidas de -0,05 kg/d; en el experimento 2 el GSb presentó GDP de 0,90 kg/d y el GNSb de 0,60 kg/d. La GDP predicha en el experimento 1 fue similar a la ganancia observada para el grupo suplementado (P > 0,05) en contraste con la presentada en el grupo no suplementado en el que la ganancia de peso fue sobrestimada (P < 0,05). En el segundo experimento, la predicción de la GDP tanto para el grupo suplementado como el no suplementado fue subestimada (P < 0,05). El nivel 1 del modelo de simulación NRC no fue apropiado para la predicción de los cambios de peso en novillas bajo condiciones tropicales.
The aim of this study was to evaluate the model NRC level 1 to predict the daily weight gain in heifers supplemented under tropical conditions. For this purpose, two experiments were done, in the first experiment 30 heifers were divided into two groups of fifteen animals each, the supplemented group (GS) showed an initial weight of 365.27 ± 24.40 kg, received commercial concentrate to the ratio of 1% of live weight (5.5% PC 2.85 Mcal ED) and the control group which was not supplemented (GNS) with an initial weight of 367.47 ± 31.65 kg. In the second study 45 heifers were divided in two groups, the GSb with 22 animals having an initial weight of 342.23 ± 36.4 kg and given concentrate to the rate of 1% of live weight (13% PC 3.5 Mcal ED) and the GNSb were made up of 23 animals having an initial average weight of 326.0 ± 31.3 kg. In both trials the animals were supplemented throughout for forty-five days and let them grazed on African Star grass (Cynodon nlemfuensis), Candelario grass (Pennisteum purpureum) and Ratana grass (Ischaemum indicum). In both experiments no differences were observed (P > 0.05) in weight change .The GS had daily weight gains (GDP) of 0.27 kg/d while the GNS showed losses of -0.05 kg/d. In the second trial the GSb showed a GDP of 0.90 kg/d and the GNSb of 0.60 kg/d. The predicted GDP of the first experiment was similar in comparison with the observed value for the supplemented group (P > 0.05), in contrast with that presented in the GNS group in which the daily weight gain was over estimated (P < 0.05). In the second trial the GDP predicted for both groups was under estimated (P < 0.05). The level 1 of the NRC simulation model does not seem to be appropriate for predicting changes in weight in heifers under tropical conditions.