The Toxicity Exerted by the Antibiotic Sulfadiazine on the Growth of Soil Bacterial Communities May Increase over Time

Santás-Miguel, Vanesa; Rodríguez-González, Laura; Núñez‐Delgado, Avelino; Díaz-Raviña, Montserrat; Arias‐Estévez, Manuel; Fernández‐Calviño, David

doi:10.3390/ijerph17238773

Cited by 5 publications

(5 citation statements)

References 48 publications

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“…The review clearly evidences that the response of microorganisms to the presence of these compounds measured by means of different parameters related to their mass, activity, and diversity (microbial C, total PLFA biomass and specific microbial groups PLFA biomass, soil respiration, bacterial growth, soil enzymes, microbial community structure), were variable; thus, although a negative temporal effect was often observed on microorganisms living in the soil, non effect, or even a positive effect, could also be detected. This is in agreement with recent investigations conducted by our research group performed with acid agricultural soils located in Galicia (NW Iberian Peninsula) added with antibiotics of different groups (tetracyclines, sulfonamides, fluorquinones, penicillins, cephalosphorine, diaminopyridine, β-lactams) (Santás-Miguel et al, 2020a;Santás-Miguel et al, 2020b;Santás-Miguel et al, 2020c;Rodríguez-González et al, 2021;Santás-Miguel et al, 2021;Rodríguez-González et al, 2022;Santás-Miguel et al, 2022;Rodríguez-González et al, 2023).…”

Section: Introductionsupporting

confidence: 92%

Microbial Communities as Affected by Clarithromycin Addition in Four Acid Soils (NW Iberian Peninsula)

et al. 2023

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A laboratory experiment was carried out to investigate the response of the microbial communities in acid agricultural soils located in the NW Iberian Peninsula to the presence of clarithromycin. Four soils, with different organic C content and similar pH, and seven different concentrations of clarithromycin (0.49, 1.95, 7.81, 31.25, 125, 500 and 2,000 mg kg−1 of soil) were used, and microbial estimates were made after 8 and 42 incubation days. The phospholipid fatty acids (PLFA) technique was used to estimate the total microbial biomass and biomass of specific microbial groups as well as the microbial community structure (PLFA pattern). The microbial biomass (total and specific groups) was different in the four studied soils, the lowest values being exhibited by soils with the lowest organic C. The antibiotic addition showed a positive effect on microbial biomass (total and specific groups), especially at the highest dose; the effect being similar or even more accentuated with time passed after the addition (42 days ≥8 days). Principal component analysis (PCA) of the PLFA data carried out with the whole data set showed that the main determining factors of the microbial structure followed the order: soil > time incubation ≥ antibiotic dose. When the PCA was performed individually for each incubation time, the results indicated that microbial communities of the four soils were different. Likewise, for each soil, different microbial communities were observed depending on antibiotic concentration. The microbial biomass and PLFA pattern data were coincidentally showing that the clarithromycin addition favored fungi and G− bacteria more that bacteria and G+ bacteria; the effect being dose-dependent. Our data (microbial biomass, PLFA pattern) also demonstrated that the effect of clarithromycin addition on microbial communities in these four acid agricultural soils persisted even after 42 incubation days.

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Section: Introductionsupporting

confidence: 92%

Microbial Communities as Affected by Clarithromycin Addition in Four Acid Soils (NW Iberian Peninsula)

et al. 2023

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“…[48]. Therefore, the clarithromycin toxicity effect on the growth of soil bacterial communities has a low persistence in the soil, contrary to the behavior found for other antibiotics such as tetracyclines [31,32] or sulfadiazine [52], and other organic substances such as propiconazole [57]) or terbutryn [58].…”

Section: Discussionmentioning

confidence: 95%

“…Finally, the bacteria in the microcentrifugation tubes were washed as described by Bååth et al [50] and radioactivity determined using scintillation liquid counting (Tri-Carb 2810 TR, Perkin Elmer). This methodology was previously used for other antibiotics such as streptomycin [51], sulfadiazine [52] and tetracycline antibiotics [31,32,51].…”

Section: Estimation Of Bacterial Community Growthmentioning

confidence: 99%

The Effect of Clarithromycin Toxicity on the Growth of Bacterial Communities in Agricultural Soils

et al. 2021

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The presence of antibiotics in different environmental matrices is a growing concern. The introduction of antibiotics into the soil is mainly due to sewage treatment plants. Once in the soil, antibiotics may become toxic to microbial communities and, as a consequence, can pose a risk to the environment and human health. This study evaluates the potential toxicity of the antibiotic clarithromycin (CLA) in relation to the bacterial community of 12 soils with different characteristics. Bacterial community growth was evaluated in soils spiked in the laboratory with different concentrations of CLA after 1, 8, and 42 incubation days. The results indicated that the addition of clarithromycin to the soil may cause toxicity in the bacterial communities of the soil. In addition, it was observed that toxicity decreases between 1 and 8 incubation days, while the bacterial community recovers completely in most soils after 42 incubation days. The results also show that soil pH and effective cation exchange capacity may influence CLA toxicity.

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“…subtilis), whereas, SA–TC and SAP–TC mixtures displayed antagonism . Moreover, the consideration of time-dependent toxicity is crucial, as antibiotic toxicity exhibits a characteristic time-related behavior. − The antibiotic sulfadiazine (SDZ) has been reported to show a significant increase in toxicity to soil bacteria over time when added to agricultural soils during a continuous exposure of 100 days, and five-antibiotic mixture systems exhibit obvious time-dependent synergism toxicity . However, the reason for the time-dependent toxicity of antibiotics has not yet been clearly explained and may be due to the metabolites of antibiotics, postantibiotic effect of antibiotics, and irreversible inhibition of enzymes of the organisms by antibiotics. , Therefore, it is essential to study the time-dependent toxicities of mixtures composed of antibiotics.…”

Section: Introductionmentioning

confidence: 99%

“…14) where r c is the Pearson correlation coefficient of the overall data set x−y, r t is the Pearson correlation coefficient of the training set x−y , r e is the Pearson correlation coefficient of the prediction set x−y , β c is the regression coefficient of the overall data set variable, and β t is the regression coefficient of the training set variable. If F 1 , F 2 , F 3 , and F 4 are all positive, this indicates that the variable sign has remained consistent.The model's quality is evaluated using statistical measures such as the R 2 , adjusted coefficient of determination (R adj 2…”

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confidence: 99%

Predicting the Time-Dependent Toxicities of Binary Mixtures of Five Antibiotics to Vibrio qinghaiensis sp.-Q67 Based on the QSAR Model

Xu,

Liu,

et al. 2024

Environ. Health

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Antibiotics may be exposed in a mixed state in natural environments. The toxicity of antibiotic mixtures exhibits time-dependent characteristics, and data on the time-dependent toxicity of antibiotic mixtures is also relatively lacking. In this study, the toxicities of 45 binary mixtures composed of five antibiotics were investigated against Vibrio qinghaiensis sp.-Q67 (Q67) at multiple exposure times (4, 6, 8, 10, and 12 h). Quantitative structure−activity relationship (QSAR) models were developed for predicting the time-dependent toxicities of 45 binary mixtures. The results showed that the best QSAR models presented coefficient of determination (R 2 ) of (0.818−0.913) and explained variance in prediction leave-one-out (Q 2 LOO ) of (0.781−0.894) and predictive ability (Q 2 F1 , Q 2 F2 , Q 2 F3 > 0.682, concordance correlation coefficient > 0.859). The R 2 values of QSAR models outperformed the R 2 (0.628−0.810) of the conventional concentration addition models and the R 2 (0.654−0.792) of the independent action models. Furthermore, the QSAR models showed higher R 2 and Q 2 LOO values at 4 h compared to other exposure times. Specifically, the model at the 30% effective concentration (EC 30 ) had R 2 of 0.902 and Q 2 LOO of 0.883, while the model at the 50% effective concentration (EC 50 ) had R 2 of 0.913 and Q 2 LOO of 0.894. The CATS2D_04_DP descriptor was found to be the most dominant and negatively correlated factor influencing the toxicity of mixed antibiotics against Q67 in the nine QSAR models developed over five exposure times. The reduction in the number of DP pharmacophore point pairs with a topological distance of 4 in the represented molecules is the primary cause for the rise in the time-dependent toxicity of the antibiotics against Q67.

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The Toxicity Exerted by the Antibiotic Sulfadiazine on the Growth of Soil Bacterial Communities May Increase over Time

Cited by 5 publications

References 48 publications

Microbial Communities as Affected by Clarithromycin Addition in Four Acid Soils (NW Iberian Peninsula)

Microbial Communities as Affected by Clarithromycin Addition in Four Acid Soils (NW Iberian Peninsula)

The Effect of Clarithromycin Toxicity on the Growth of Bacterial Communities in Agricultural Soils

Predicting the Time-Dependent Toxicities of Binary Mixtures of Five Antibiotics to Vibrio qinghaiensis sp.-Q67 Based on the QSAR Model

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